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stringclasses 1
value | original_example
dict | step_ids
listlengths 1
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from MultisizerReader import MultiSizerReader
import os
import matplotlib.pyplot as plt
#Get all spread sheet files in fodler and create multisizer files for each
folder = "./Data_Organised/DilutionTestingLowOD"
allFiles = os.listdir(folder)
multiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i].endswith(".XLS")]
data = []
for files in multiSizerFiles:
data.append(MultiSizerReader(path=os.path.join(folder,files)))
#split files into YD133 and YD133 + PWR20
ODs = []
labels = []
dilutions =[]
for d in data:
OD = d.name.split("_")[4] + "." + d.name.split("_")[5]
if d.name.split("_")[2] == "5":
dilutions.append("$10^5$")
labels.append("$10^5$ OD: {}".format(OD))
if d.name.split("_")[2] == "7":
dilutions.append("$10^7$")
labels.append("$10^7$ OD: {}".format(OD))
ODs.append(float(OD))
fig, ax = plt.subplots(nrows=1,ncols=2,figsize=(14,9))
combinedData,combinedTypes,combinedLabels = MultiSizerReader.sumByGroup(data,ODs,labels)
MultiSizerReader.plotData(combinedData,combinedTypes,labels=combinedLabels,logAxis=False,legend=True,title="OD ~ 0.05",logNormalFits=False,xLims=(0.4,4),colorScale=False,smoothing=5,showStats=False,ax=ax[0],text=False,cbarLabel="$\mathbf{OD_{600}}$")
#Get all spread sheet files in fodler and create multisizer files for each
folder = "./Data_Organised/DilutionTestingHighOD"
allFiles = os.listdir(folder)
multiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i].endswith(".XLS")]
data = []
for files in multiSizerFiles:
data.append(MultiSizerReader(path=os.path.join(folder,files)))
#split files into YD133 and YD133 + PWR20
ODs = []
labels = []
dilutions =[]
for d in data:
OD = d.name.split("_")[4] + "." + d.name.split("_")[5]
if d.name.split("_")[2] == "5":
dilutions.append("$10^5$")
labels.append("$10^5$ OD: {}".format(OD))
if d.name.split("_")[2] == "7":
dilutions.append("$10^7$")
labels.append("$10^7$ OD: {}".format(OD))
ODs.append(float(OD))
combinedData,combinedTypes,combinedLabels = MultiSizerReader.sumByGroup(data,ODs,labels)
MultiSizerReader.plotData(combinedData,combinedTypes,labels=combinedLabels,logAxis=False,legend=True,title="OD ~ 0.2",logNormalFits=False,xLims=(0.4,4),colorScale=False,smoothing=5,showStats=False,ax=ax[1],text=False,cbarLabel="$\mathbf{OD_{600}}$")
ax[0].text(0.03, 0.93 , "A", transform=ax[0].transAxes, size=35, weight='bold',color="k")
ax[1].text(0.03, 0.93 , "B", transform=ax[1].transAxes, size=35, weight='bold',color="k")
ax[0].legend(fontsize="xx-large")
ax[1].legend(fontsize="xx-large")
fig.tight_layout()
plt.show()
|
normal
|
{
"blob_id": "2f0aa1f294f34a4f3ffb47c15ab74fc792765f10",
"index": 9195,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\n<mask token>\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\n<mask token>\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.05',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[0], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\n<mask token>\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\n<mask token>\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\n<mask token>\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.2',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[1], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\nax[0].text(0.03, 0.93, 'A', transform=ax[0].transAxes, size=35, weight=\n 'bold', color='k')\nax[1].text(0.03, 0.93, 'B', transform=ax[1].transAxes, size=35, weight=\n 'bold', color='k')\nax[0].legend(fontsize='xx-large')\nax[1].legend(fontsize='xx-large')\nfig.tight_layout()\nplt.show()\n",
"step-3": "<mask token>\nfolder = './Data_Organised/DilutionTestingLowOD'\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i]\n .endswith('.XLS')]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\nODs = []\nlabels = []\ndilutions = []\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\nfig, ax = plt.subplots(nrows=1, ncols=2, figsize=(14, 9))\ncombinedData, combinedTypes, combinedLabels = MultiSizerReader.sumByGroup(data,\n ODs, labels)\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.05',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[0], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\nfolder = './Data_Organised/DilutionTestingHighOD'\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i]\n .endswith('.XLS')]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\nODs = []\nlabels = []\ndilutions = []\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\ncombinedData, combinedTypes, combinedLabels = MultiSizerReader.sumByGroup(data,\n ODs, labels)\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.2',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[1], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\nax[0].text(0.03, 0.93, 'A', transform=ax[0].transAxes, size=35, weight=\n 'bold', color='k')\nax[1].text(0.03, 0.93, 'B', transform=ax[1].transAxes, size=35, weight=\n 'bold', color='k')\nax[0].legend(fontsize='xx-large')\nax[1].legend(fontsize='xx-large')\nfig.tight_layout()\nplt.show()\n",
"step-4": "from MultisizerReader import MultiSizerReader\nimport os\nimport matplotlib.pyplot as plt\nfolder = './Data_Organised/DilutionTestingLowOD'\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i]\n .endswith('.XLS')]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\nODs = []\nlabels = []\ndilutions = []\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\nfig, ax = plt.subplots(nrows=1, ncols=2, figsize=(14, 9))\ncombinedData, combinedTypes, combinedLabels = MultiSizerReader.sumByGroup(data,\n ODs, labels)\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.05',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[0], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\nfolder = './Data_Organised/DilutionTestingHighOD'\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i]\n .endswith('.XLS')]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder, files)))\nODs = []\nlabels = []\ndilutions = []\nfor d in data:\n OD = d.name.split('_')[4] + '.' + d.name.split('_')[5]\n if d.name.split('_')[2] == '5':\n dilutions.append('$10^5$')\n labels.append('$10^5$ OD: {}'.format(OD))\n if d.name.split('_')[2] == '7':\n dilutions.append('$10^7$')\n labels.append('$10^7$ OD: {}'.format(OD))\n ODs.append(float(OD))\ncombinedData, combinedTypes, combinedLabels = MultiSizerReader.sumByGroup(data,\n ODs, labels)\nMultiSizerReader.plotData(combinedData, combinedTypes, labels=\n combinedLabels, logAxis=False, legend=True, title='OD ~ 0.2',\n logNormalFits=False, xLims=(0.4, 4), colorScale=False, smoothing=5,\n showStats=False, ax=ax[1], text=False, cbarLabel='$\\\\mathbf{OD_{600}}$')\nax[0].text(0.03, 0.93, 'A', transform=ax[0].transAxes, size=35, weight=\n 'bold', color='k')\nax[1].text(0.03, 0.93, 'B', transform=ax[1].transAxes, size=35, weight=\n 'bold', color='k')\nax[0].legend(fontsize='xx-large')\nax[1].legend(fontsize='xx-large')\nfig.tight_layout()\nplt.show()\n",
"step-5": "from MultisizerReader import MultiSizerReader\nimport os\nimport matplotlib.pyplot as plt\n\n#Get all spread sheet files in fodler and create multisizer files for each\nfolder = \"./Data_Organised/DilutionTestingLowOD\"\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i].endswith(\".XLS\")]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder,files)))\n\n#split files into YD133 and YD133 + PWR20\nODs = []\nlabels = []\ndilutions =[]\nfor d in data:\n OD = d.name.split(\"_\")[4] + \".\" + d.name.split(\"_\")[5]\n if d.name.split(\"_\")[2] == \"5\":\n dilutions.append(\"$10^5$\")\n labels.append(\"$10^5$ OD: {}\".format(OD))\n if d.name.split(\"_\")[2] == \"7\":\n dilutions.append(\"$10^7$\")\n labels.append(\"$10^7$ OD: {}\".format(OD))\n ODs.append(float(OD))\n\nfig, ax = plt.subplots(nrows=1,ncols=2,figsize=(14,9))\n\ncombinedData,combinedTypes,combinedLabels = MultiSizerReader.sumByGroup(data,ODs,labels)\nMultiSizerReader.plotData(combinedData,combinedTypes,labels=combinedLabels,logAxis=False,legend=True,title=\"OD ~ 0.05\",logNormalFits=False,xLims=(0.4,4),colorScale=False,smoothing=5,showStats=False,ax=ax[0],text=False,cbarLabel=\"$\\mathbf{OD_{600}}$\")\n\n#Get all spread sheet files in fodler and create multisizer files for each\nfolder = \"./Data_Organised/DilutionTestingHighOD\"\nallFiles = os.listdir(folder)\nmultiSizerFiles = [allFiles[i] for i in range(len(allFiles)) if allFiles[i].endswith(\".XLS\")]\ndata = []\nfor files in multiSizerFiles:\n data.append(MultiSizerReader(path=os.path.join(folder,files)))\n\n#split files into YD133 and YD133 + PWR20\nODs = []\nlabels = []\ndilutions =[]\nfor d in data:\n OD = d.name.split(\"_\")[4] + \".\" + d.name.split(\"_\")[5]\n if d.name.split(\"_\")[2] == \"5\":\n dilutions.append(\"$10^5$\")\n labels.append(\"$10^5$ OD: {}\".format(OD))\n if d.name.split(\"_\")[2] == \"7\":\n dilutions.append(\"$10^7$\")\n labels.append(\"$10^7$ OD: {}\".format(OD))\n ODs.append(float(OD))\n\n\n\n\ncombinedData,combinedTypes,combinedLabels = MultiSizerReader.sumByGroup(data,ODs,labels)\nMultiSizerReader.plotData(combinedData,combinedTypes,labels=combinedLabels,logAxis=False,legend=True,title=\"OD ~ 0.2\",logNormalFits=False,xLims=(0.4,4),colorScale=False,smoothing=5,showStats=False,ax=ax[1],text=False,cbarLabel=\"$\\mathbf{OD_{600}}$\")\n\n\n\n\n\n\n\n\n\nax[0].text(0.03, 0.93 , \"A\", transform=ax[0].transAxes, size=35, weight='bold',color=\"k\")\nax[1].text(0.03, 0.93 , \"B\", transform=ax[1].transAxes, size=35, weight='bold',color=\"k\")\nax[0].legend(fontsize=\"xx-large\")\nax[1].legend(fontsize=\"xx-large\")\nfig.tight_layout()\nplt.show()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from secrets import randbelow
print(randbelow(100))
|
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|
{
"blob_id": "18ae982c7fac7a31e0d257f500da0be0851388c2",
"index": 8985,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(randbelow(100))\n",
"step-3": "from secrets import randbelow\nprint(randbelow(100))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
# ex: set sts=4 ts=4 sw=4 noet:
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the datalad package for the
# copyright and license terms.
#
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
"""Test create publication target github"""
from os.path import join as opj
# this must with with and without pygithub
from datalad.api import create_sibling_github
from datalad.api import Dataset
from datalad.support.exceptions import MissingExternalDependency
from datalad.tests.utils import with_tempfile
from nose.tools import assert_raises, assert_in, assert_true, assert_false, \
assert_not_in, assert_equal
from nose import SkipTest
try:
import github as gh
except ImportError:
# make sure that the command complains too
assert_raises(MissingExternalDependency, create_sibling_github, 'some')
raise SkipTest
@with_tempfile
def test_invalid_call(path):
# no dataset
assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)
ds = Dataset(path).create()
# no user
assert_raises(gh.BadCredentialsException, ds.create_sibling_github, 'bogus', github_user='')
@with_tempfile
def test_dont_trip_over_missing_subds(path):
ds1 = Dataset(opj(path, 'ds1')).create()
ds2 = Dataset(opj(path, 'ds2')).create()
subds2 = ds1.install(source=ds2.path, path='subds2')
assert_true(subds2.is_installed())
assert_in('subds2', ds1.get_subdatasets())
subds2.uninstall(remove_handles=True, remove_history=True)
assert_in('subds2', ds1.get_subdatasets())
assert_false(subds2.is_installed())
# this will deinit the submodule
ds1.save(files=['subds2'])
# see if it wants to talk to github (and fail), or if it trips over something
# before
assert_raises(gh.BadCredentialsException, ds1.create_sibling_github, 'bogus', recursive=True, github_user='')
# inject remote config prior run
assert_not_in('github', ds1.repo.get_remotes())
# fail on existing
ds1.repo.add_remote('github', 'http://nothere')
assert_raises(ValueError, ds1.create_sibling_github, 'bogus', recursive=True, github_user='')
# talk to github when existing is OK
assert_raises(gh.BadCredentialsException, ds1.create_sibling_github, 'bogus', recursive=True, github_user='', existing='reconfigure')
# return happy emptiness when all is skipped
assert_equal(ds1.create_sibling_github('bogus', recursive=True, github_user='', existing='skip'), [])
|
normal
|
{
"blob_id": "035043460805b7fe92e078e05708d368130e3527",
"index": 8965,
"step-1": "<mask token>\n\n\n@with_tempfile\ndef test_invalid_call(path):\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n assert_raises(gh.BadCredentialsException, ds.create_sibling_github,\n 'bogus', github_user='')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@with_tempfile\ndef test_invalid_call(path):\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n assert_raises(gh.BadCredentialsException, ds.create_sibling_github,\n 'bogus', github_user='')\n\n\n@with_tempfile\ndef test_dont_trip_over_missing_subds(path):\n ds1 = Dataset(opj(path, 'ds1')).create()\n ds2 = Dataset(opj(path, 'ds2')).create()\n subds2 = ds1.install(source=ds2.path, path='subds2')\n assert_true(subds2.is_installed())\n assert_in('subds2', ds1.get_subdatasets())\n subds2.uninstall(remove_handles=True, remove_history=True)\n assert_in('subds2', ds1.get_subdatasets())\n assert_false(subds2.is_installed())\n ds1.save(files=['subds2'])\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='')\n assert_not_in('github', ds1.repo.get_remotes())\n ds1.repo.add_remote('github', 'http://nothere')\n assert_raises(ValueError, ds1.create_sibling_github, 'bogus', recursive\n =True, github_user='')\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='', existing='reconfigure')\n assert_equal(ds1.create_sibling_github('bogus', recursive=True,\n github_user='', existing='skip'), [])\n",
"step-3": "<mask token>\ntry:\n import github as gh\nexcept ImportError:\n assert_raises(MissingExternalDependency, create_sibling_github, 'some')\n raise SkipTest\n\n\n@with_tempfile\ndef test_invalid_call(path):\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n assert_raises(gh.BadCredentialsException, ds.create_sibling_github,\n 'bogus', github_user='')\n\n\n@with_tempfile\ndef test_dont_trip_over_missing_subds(path):\n ds1 = Dataset(opj(path, 'ds1')).create()\n ds2 = Dataset(opj(path, 'ds2')).create()\n subds2 = ds1.install(source=ds2.path, path='subds2')\n assert_true(subds2.is_installed())\n assert_in('subds2', ds1.get_subdatasets())\n subds2.uninstall(remove_handles=True, remove_history=True)\n assert_in('subds2', ds1.get_subdatasets())\n assert_false(subds2.is_installed())\n ds1.save(files=['subds2'])\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='')\n assert_not_in('github', ds1.repo.get_remotes())\n ds1.repo.add_remote('github', 'http://nothere')\n assert_raises(ValueError, ds1.create_sibling_github, 'bogus', recursive\n =True, github_user='')\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='', existing='reconfigure')\n assert_equal(ds1.create_sibling_github('bogus', recursive=True,\n github_user='', existing='skip'), [])\n",
"step-4": "<mask token>\nfrom os.path import join as opj\nfrom datalad.api import create_sibling_github\nfrom datalad.api import Dataset\nfrom datalad.support.exceptions import MissingExternalDependency\nfrom datalad.tests.utils import with_tempfile\nfrom nose.tools import assert_raises, assert_in, assert_true, assert_false, assert_not_in, assert_equal\nfrom nose import SkipTest\ntry:\n import github as gh\nexcept ImportError:\n assert_raises(MissingExternalDependency, create_sibling_github, 'some')\n raise SkipTest\n\n\n@with_tempfile\ndef test_invalid_call(path):\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n assert_raises(gh.BadCredentialsException, ds.create_sibling_github,\n 'bogus', github_user='')\n\n\n@with_tempfile\ndef test_dont_trip_over_missing_subds(path):\n ds1 = Dataset(opj(path, 'ds1')).create()\n ds2 = Dataset(opj(path, 'ds2')).create()\n subds2 = ds1.install(source=ds2.path, path='subds2')\n assert_true(subds2.is_installed())\n assert_in('subds2', ds1.get_subdatasets())\n subds2.uninstall(remove_handles=True, remove_history=True)\n assert_in('subds2', ds1.get_subdatasets())\n assert_false(subds2.is_installed())\n ds1.save(files=['subds2'])\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='')\n assert_not_in('github', ds1.repo.get_remotes())\n ds1.repo.add_remote('github', 'http://nothere')\n assert_raises(ValueError, ds1.create_sibling_github, 'bogus', recursive\n =True, github_user='')\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github,\n 'bogus', recursive=True, github_user='', existing='reconfigure')\n assert_equal(ds1.create_sibling_github('bogus', recursive=True,\n github_user='', existing='skip'), [])\n",
"step-5": "# ex: set sts=4 ts=4 sw=4 noet:\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\n#\n# See COPYING file distributed along with the datalad package for the\n# copyright and license terms.\n#\n# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##\n\"\"\"Test create publication target github\"\"\"\n\nfrom os.path import join as opj\n# this must with with and without pygithub\nfrom datalad.api import create_sibling_github\nfrom datalad.api import Dataset\nfrom datalad.support.exceptions import MissingExternalDependency\nfrom datalad.tests.utils import with_tempfile\nfrom nose.tools import assert_raises, assert_in, assert_true, assert_false, \\\n assert_not_in, assert_equal\nfrom nose import SkipTest\n\n\ntry:\n import github as gh\nexcept ImportError:\n # make sure that the command complains too\n assert_raises(MissingExternalDependency, create_sibling_github, 'some')\n raise SkipTest\n\n\n@with_tempfile\ndef test_invalid_call(path):\n # no dataset\n assert_raises(ValueError, create_sibling_github, 'bogus', dataset=path)\n ds = Dataset(path).create()\n # no user\n assert_raises(gh.BadCredentialsException, ds.create_sibling_github, 'bogus', github_user='')\n\n\n@with_tempfile\ndef test_dont_trip_over_missing_subds(path):\n ds1 = Dataset(opj(path, 'ds1')).create()\n ds2 = Dataset(opj(path, 'ds2')).create()\n subds2 = ds1.install(source=ds2.path, path='subds2')\n assert_true(subds2.is_installed())\n assert_in('subds2', ds1.get_subdatasets())\n subds2.uninstall(remove_handles=True, remove_history=True)\n assert_in('subds2', ds1.get_subdatasets())\n assert_false(subds2.is_installed())\n # this will deinit the submodule\n ds1.save(files=['subds2'])\n # see if it wants to talk to github (and fail), or if it trips over something\n # before\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github, 'bogus', recursive=True, github_user='')\n # inject remote config prior run\n assert_not_in('github', ds1.repo.get_remotes())\n # fail on existing\n ds1.repo.add_remote('github', 'http://nothere')\n assert_raises(ValueError, ds1.create_sibling_github, 'bogus', recursive=True, github_user='')\n # talk to github when existing is OK\n assert_raises(gh.BadCredentialsException, ds1.create_sibling_github, 'bogus', recursive=True, github_user='', existing='reconfigure')\n # return happy emptiness when all is skipped\n assert_equal(ds1.create_sibling_github('bogus', recursive=True, github_user='', existing='skip'), [])\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
def parse_detail_for_one_course(page, course, no_info_course):
print(f'{course["name"]} is processing**: {course["url"]}')
map = {"Locatie": "location",
"Location": "location",
"Startdatum": "effective_start_date",
"Start date": "effective_start_date",
"Duur": "duration_desc",
"Wekelijkse studie": "duration_desc",
"Expensive": "duration_desc",
"Colleges": "consecutive_desc",
"Languages": "languages",
"Languages ": "languages",
"Talen": "languages",
"Fee": "price",
"Fee ": "price",
"Fairy ": "price",
"Weekly study": "second_duration_desc",
"Accreditations ": "third_duration_desc",
"Investering": "price"}
info = {"location": "",
"effective_start_date": "",
"duration_desc": "",
"consecutive_desc": "",
"languages": "",
"price": "",
"second_duration_desc": "",
"third_duration_desc": ""}
info_div = page.find('div', attrs={"class": "program-general-info"})
info_sessions = None
if info_div:
info_sessions = info_div.find_all('div', attrs={"class": "info-item"})
if not info_sessions:
print(f'-------{course["url"]} not div')
no_info_course.append(course)
elif info_sessions:
for info_session in info_sessions:
try:
label = info_session.find('label')
label_text = label.text.strip()
info_attr = map.get(label_text, '')
if "Wekeli" in label_text:
info_attr = "duration_desc"
elif "Permanente educatie" in label_text:
continue
elif "Accreditaties" in label_text:
continue
elif "Deadline voor aanmelding" in label_text:
continue
res = info_session.find('div')
res_text = res.text.strip()
info[info_attr] = res_text
except Exception as e:
print(f'{course["url"]} has problem of {e}')
continue
# print(title)
detail = {**course, **info}
# pprint(detail)
return detail
# page = requests.get("https://www.nyenrode.nl/opleidingen/p/collegereeks-excellent-leiderschap")
# page = requests.get("https://www.nyenrode.nl/opleidingen/p/behavioral-and-cultural-governance")
# page = requests.get("https://www.nyenrode.nl/opleidingen/p/advanced-management-program")
# page = requests.get("https://www.nyenrode.nl/opleidingen/p/mba-thesis")
# course = {"name": "",
# "url": ""}
# page = page.text
# page = bs4.BeautifulSoup(page, 'html.parser')
#
# detail = get_detail_for_one_course(page, course, [])
# pprint(detail)
|
normal
|
{
"blob_id": "0f4fa9f8835ae22032af9faa6c7cb10af3facd79",
"index": 5389,
"step-1": "<mask token>\n",
"step-2": "def parse_detail_for_one_course(page, course, no_info_course):\n print(f\"{course['name']} is processing**: {course['url']}\")\n map = {'Locatie': 'location', 'Location': 'location', 'Startdatum':\n 'effective_start_date', 'Start date': 'effective_start_date',\n 'Duur': 'duration_desc', 'Wekelijkse studie': 'duration_desc',\n 'Expensive': 'duration_desc', 'Colleges': 'consecutive_desc',\n 'Languages': 'languages', 'Languages ': 'languages', 'Talen':\n 'languages', 'Fee': 'price', 'Fee ': 'price', 'Fairy ': 'price',\n 'Weekly study': 'second_duration_desc', 'Accreditations ':\n 'third_duration_desc', 'Investering': 'price'}\n info = {'location': '', 'effective_start_date': '', 'duration_desc': '',\n 'consecutive_desc': '', 'languages': '', 'price': '',\n 'second_duration_desc': '', 'third_duration_desc': ''}\n info_div = page.find('div', attrs={'class': 'program-general-info'})\n info_sessions = None\n if info_div:\n info_sessions = info_div.find_all('div', attrs={'class': 'info-item'})\n if not info_sessions:\n print(f\"-------{course['url']} not div\")\n no_info_course.append(course)\n elif info_sessions:\n for info_session in info_sessions:\n try:\n label = info_session.find('label')\n label_text = label.text.strip()\n info_attr = map.get(label_text, '')\n if 'Wekeli' in label_text:\n info_attr = 'duration_desc'\n elif 'Permanente educatie' in label_text:\n continue\n elif 'Accreditaties' in label_text:\n continue\n elif 'Deadline voor aanmelding' in label_text:\n continue\n res = info_session.find('div')\n res_text = res.text.strip()\n info[info_attr] = res_text\n except Exception as e:\n print(f\"{course['url']} has problem of {e}\")\n continue\n detail = {**course, **info}\n return detail\n",
"step-3": "def parse_detail_for_one_course(page, course, no_info_course):\n print(f'{course[\"name\"]} is processing**: {course[\"url\"]}')\n map = {\"Locatie\": \"location\",\n \"Location\": \"location\",\n \"Startdatum\": \"effective_start_date\",\n \"Start date\": \"effective_start_date\",\n \"Duur\": \"duration_desc\",\n \"Wekelijkse studie\": \"duration_desc\",\n \"Expensive\": \"duration_desc\",\n \"Colleges\": \"consecutive_desc\",\n \"Languages\": \"languages\",\n \"Languages \": \"languages\",\n \"Talen\": \"languages\",\n \"Fee\": \"price\",\n \"Fee \": \"price\",\n \"Fairy \": \"price\",\n \"Weekly study\": \"second_duration_desc\",\n \"Accreditations \": \"third_duration_desc\",\n \"Investering\": \"price\"}\n\n info = {\"location\": \"\",\n \"effective_start_date\": \"\",\n \"duration_desc\": \"\",\n \"consecutive_desc\": \"\",\n \"languages\": \"\",\n \"price\": \"\",\n \"second_duration_desc\": \"\",\n \"third_duration_desc\": \"\"}\n\n info_div = page.find('div', attrs={\"class\": \"program-general-info\"})\n info_sessions = None\n if info_div:\n info_sessions = info_div.find_all('div', attrs={\"class\": \"info-item\"})\n\n if not info_sessions:\n print(f'-------{course[\"url\"]} not div')\n no_info_course.append(course)\n elif info_sessions:\n for info_session in info_sessions:\n try:\n label = info_session.find('label')\n label_text = label.text.strip()\n info_attr = map.get(label_text, '')\n if \"Wekeli\" in label_text:\n info_attr = \"duration_desc\"\n elif \"Permanente educatie\" in label_text:\n continue\n elif \"Accreditaties\" in label_text:\n continue\n elif \"Deadline voor aanmelding\" in label_text:\n continue\n res = info_session.find('div')\n res_text = res.text.strip()\n info[info_attr] = res_text\n except Exception as e:\n print(f'{course[\"url\"]} has problem of {e}')\n continue\n # print(title)\n detail = {**course, **info}\n # pprint(detail)\n return detail\n\n\n# page = requests.get(\"https://www.nyenrode.nl/opleidingen/p/collegereeks-excellent-leiderschap\")\n# page = requests.get(\"https://www.nyenrode.nl/opleidingen/p/behavioral-and-cultural-governance\")\n# page = requests.get(\"https://www.nyenrode.nl/opleidingen/p/advanced-management-program\")\n# page = requests.get(\"https://www.nyenrode.nl/opleidingen/p/mba-thesis\")\n# course = {\"name\": \"\",\n# \"url\": \"\"}\n# page = page.text\n# page = bs4.BeautifulSoup(page, 'html.parser')\n#\n# detail = get_detail_for_one_course(page, course, [])\n# pprint(detail)\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
from nltk.tokenize import RegexpTokenizer
from stop_words import get_stop_words
from nltk.stem.porter import PorterStemmer
from gensim import corpora, models
import gensim
tokenizer = RegexpTokenizer(r'\w+')
# create English stop words list
en_stop = get_stop_words('en')
# Create p_stemmer of class PorterStemmer
p_stemmer = PorterStemmer()
# create sample documents
doc_a = "Brocolli is good to eat. My brother likes to eat good brocolli, but not my mother."
doc_b = "My mother spends a lot of time driving my brother around to baseball practice."
doc_c = "Some health experts suggest that driving may cause increased tension and blood pressure."
doc_d = "I often feel pressure to perform well at school, but my mother never seems to drive my brother to do better."
doc_e = "Health professionals say that brocolli is good for your health."
rev1 = "I pre-ordered this for my wife mostly to use as a Kindle E-reader as I figured the tablet would be slow and the display would be less than impressive. I was wrong. What a bargain this little beauty is! This model cost $49.00 but it comes with ad's displayed on the lock screen when your tablet is dormant. Once your screen times out, they disappear. You can pay $15.00 up front to get an ad free version so I assumed to unlock the tablet I'd have to spend 15 to 30 seconds looking at an ad for Amazon Prime, or a product from the daily specials section of Amazon.com I abstained from paying for Ad removal and was pleasantly surprised to find that the ads are only on the lock screen and that as soon as I unlock the tablet they disappear immediately. Here are my pros and cons thus far. PRO: Perfect size for Ebooks, and web surfing to alleviate strain on the eyes from my 5 phone display nice sturdy casing that gives it a nice heft but still weighs in as one of the lighter tablets on the market Child Accounts- Amazon allows you to set up this tablet with age restricted access for kids making this a low cost piece of tech that is perfect for school kids and allows mom and dad to ration the amount of time lil Johnny can play Clash of Clans and how much he can hit the ol' Visa card for. Battery life thus far; wife was on it for about 5 hours last night and battery was at about 46% Kindle Integration -this goes without saying but having my ebooks and audible books synced to the tablet is awesome and my Kindle books look great"
rev2 = "UPDATED - After spending quite a bit more time with the device, I would give it a 4.5 due to a few specific gaps that are a bit annoying. However, you are still getting an amazing 7” tablet, with front and rear facing cameras, a gorgeous interface, fairly snappy performance and durability, all for under 50 bucks! I can’t imagine not buying these for myself and my whole family, but not a primary tablet for a techie adult by any means. For background, I have every Kindle, a couple Fires, and multiple tablets from Apple, Microsoft and Samsung. Note that my review with 5 stars considers the value equation, not just performance and how that may or may not compare to other tablets - if you are expecting this to compare to a tablet costing several times more, don't bother. But if you are looking for a great entry level tablet that does most of the things people want, this little tablet definitely delivers the value! PRICING/CONFIG: I prefer this tablet with ads and no accessories to keep the costs down. You have the option to spend more money, but I recommend against it. You can easily see the specs online, so I won’t do you the discourtesy of simply cutting and pasting those here. Here is the price breakdown: 9.99 base price – what an incredible price point! Or buy 5 and get a sixth one free! This puts it into reach of schools and non-profits."
rev3 ="The short/summed up version: it's the new budget king in the 6-8 size. It's screen is a little lower in resolution but still pleasant to look at, it has enough power for most of the typical tablet tasks, and it shares many of the same features as its higher priced brothers such as front and back cameras, b/g/n wifi, and good overall battery life (minus an hour) My favorite size tablet is 8, so if you're looking at the amazon fire lineup, i would take this over the 6 for sure, and would have a hard time picking the 8 fire at 3x the price. If you re not a prime member, it s still a good tablet, if you are a prime member: it s a great tablet. Possible quality control issue: Mine had two dead pixels (not very noticeable, but still will exchange) You can load APKs(enable unknown sources), i loaded antutu and panasonic image app, both work properly."
# compile sample documents into a list
#doc_set = [doc_a, doc_b, doc_c, doc_d, doc_e]
doc_set = [rev1,rev2,rev3]
# list for tokenized documents in loop
texts = []
# loop through document list
for i in doc_set:
# clean and tokenize document string
raw = i.lower()
tokens = tokenizer.tokenize(raw)
# remove stop words from tokens
stopped_tokens = [i for i in tokens if not i in en_stop]
# stem tokens
stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]
# add tokens to list
texts.append(stemmed_tokens)
# turn our tokenized documents into a id <-> term dictionary
dictionary = corpora.Dictionary(texts)
# convert tokenized documents into a document-term matrix
corpus = [dictionary.doc2bow(text) for text in texts]
# generate LDA model
ldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=4, id2word=dictionary, passes=20)
print("LDA............")
topics = ldamodel.print_topics(num_topics=3, num_words=5)
for topic in topics:
print(type(topic))
print(topic)
print("LSA.................")
#id2word = gensim.corpora.Dictionary.load_from_text("c:\lda_test.txt")
lsi = gensim.models.lsimodel.LsiModel(corpus, id2word=dictionary)
from nltk.corpus import sentiwordnet as swn
topics = lsi.print_topics(5)
for topic in topics:
print(topic[1])
print(swn.senti_synsets(topic[1]))
print("----------------------------------------")
#print(list(swn.senti_synsets('slow')))
happy = swn.senti_synsets('happy')
print(happy.neg_score())
all = swn.all_senti_synsets()
#print(all)
|
normal
|
{
"blob_id": "3035ac8044b5629d0b5de7934e46890ad36ed551",
"index": 7798,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in doc_set:\n raw = i.lower()\n tokens = tokenizer.tokenize(raw)\n stopped_tokens = [i for i in tokens if not i in en_stop]\n stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]\n texts.append(stemmed_tokens)\n<mask token>\nprint('LDA............')\n<mask token>\nfor topic in topics:\n print(type(topic))\n print(topic)\nprint('LSA.................')\n<mask token>\nfor topic in topics:\n print(topic[1])\n print(swn.senti_synsets(topic[1]))\n print('----------------------------------------')\n<mask token>\nprint(happy.neg_score())\n<mask token>\n",
"step-3": "<mask token>\ntokenizer = RegexpTokenizer('\\\\w+')\nen_stop = get_stop_words('en')\np_stemmer = PorterStemmer()\ndoc_a = (\n 'Brocolli is good to eat. My brother likes to eat good brocolli, but not my mother.'\n )\ndoc_b = (\n 'My mother spends a lot of time driving my brother around to baseball practice.'\n )\ndoc_c = (\n 'Some health experts suggest that driving may cause increased tension and blood pressure.'\n )\ndoc_d = (\n 'I often feel pressure to perform well at school, but my mother never seems to drive my brother to do better.'\n )\ndoc_e = 'Health professionals say that brocolli is good for your health.'\nrev1 = (\n \"I pre-ordered this for my wife mostly to use as a Kindle E-reader as I figured the tablet would be slow and the display would be less than impressive. I was wrong. What a bargain this little beauty is! This model cost $49.00 but it comes with ad's displayed on the lock screen when your tablet is dormant. Once your screen times out, they disappear. You can pay $15.00 up front to get an ad free version so I assumed to unlock the tablet I'd have to spend 15 to 30 seconds looking at an ad for Amazon Prime, or a product from the daily specials section of Amazon.com I abstained from paying for Ad removal and was pleasantly surprised to find that the ads are only on the lock screen and that as soon as I unlock the tablet they disappear immediately. Here are my pros and cons thus far. PRO: Perfect size for Ebooks, and web surfing to alleviate strain on the eyes from my 5 phone display nice sturdy casing that gives it a nice heft but still weighs in as one of the lighter tablets on the market Child Accounts- Amazon allows you to set up this tablet with age restricted access for kids making this a low cost piece of tech that is perfect for school kids and allows mom and dad to ration the amount of time lil Johnny can play Clash of Clans and how much he can hit the ol' Visa card for. Battery life thus far; wife was on it for about 5 hours last night and battery was at about 46% Kindle Integration -this goes without saying but having my ebooks and audible books synced to the tablet is awesome and my Kindle books look great\"\n )\nrev2 = (\n \"UPDATED - After spending quite a bit more time with the device, I would give it a 4.5 due to a few specific gaps that are a bit annoying. However, you are still getting an amazing 7” tablet, with front and rear facing cameras, a gorgeous interface, fairly snappy performance and durability, all for under 50 bucks! I can’t imagine not buying these for myself and my whole family, but not a primary tablet for a techie adult by any means. For background, I have every Kindle, a couple Fires, and multiple tablets from Apple, Microsoft and Samsung. Note that my review with 5 stars considers the value equation, not just performance and how that may or may not compare to other tablets - if you are expecting this to compare to a tablet costing several times more, don't bother. But if you are looking for a great entry level tablet that does most of the things people want, this little tablet definitely delivers the value! PRICING/CONFIG: I prefer this tablet with ads and no accessories to keep the costs down. You have the option to spend more money, but I recommend against it. You can easily see the specs online, so I won’t do you the discourtesy of simply cutting and pasting those here. Here is the price breakdown: 9.99 base price – what an incredible price point! Or buy 5 and get a sixth one free! This puts it into reach of schools and non-profits.\"\n )\nrev3 = (\n \"The short/summed up version: it's the new budget king in the 6-8 size. It's screen is a little lower in resolution but still pleasant to look at, it has enough power for most of the typical tablet tasks, and it shares many of the same features as its higher priced brothers such as front and back cameras, b/g/n wifi, and good overall battery life (minus an hour) My favorite size tablet is 8, so if you're looking at the amazon fire lineup, i would take this over the 6 for sure, and would have a hard time picking the 8 fire at 3x the price. If you re not a prime member, it s still a good tablet, if you are a prime member: it s a great tablet. Possible quality control issue: Mine had two dead pixels (not very noticeable, but still will exchange) You can load APKs(enable unknown sources), i loaded antutu and panasonic image app, both work properly.\"\n )\ndoc_set = [rev1, rev2, rev3]\ntexts = []\nfor i in doc_set:\n raw = i.lower()\n tokens = tokenizer.tokenize(raw)\n stopped_tokens = [i for i in tokens if not i in en_stop]\n stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]\n texts.append(stemmed_tokens)\ndictionary = corpora.Dictionary(texts)\ncorpus = [dictionary.doc2bow(text) for text in texts]\nldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=4, id2word=\n dictionary, passes=20)\nprint('LDA............')\ntopics = ldamodel.print_topics(num_topics=3, num_words=5)\nfor topic in topics:\n print(type(topic))\n print(topic)\nprint('LSA.................')\nlsi = gensim.models.lsimodel.LsiModel(corpus, id2word=dictionary)\n<mask token>\ntopics = lsi.print_topics(5)\nfor topic in topics:\n print(topic[1])\n print(swn.senti_synsets(topic[1]))\n print('----------------------------------------')\nhappy = swn.senti_synsets('happy')\nprint(happy.neg_score())\nall = swn.all_senti_synsets()\n",
"step-4": "from nltk.tokenize import RegexpTokenizer\nfrom stop_words import get_stop_words\nfrom nltk.stem.porter import PorterStemmer\nfrom gensim import corpora, models\nimport gensim\ntokenizer = RegexpTokenizer('\\\\w+')\nen_stop = get_stop_words('en')\np_stemmer = PorterStemmer()\ndoc_a = (\n 'Brocolli is good to eat. My brother likes to eat good brocolli, but not my mother.'\n )\ndoc_b = (\n 'My mother spends a lot of time driving my brother around to baseball practice.'\n )\ndoc_c = (\n 'Some health experts suggest that driving may cause increased tension and blood pressure.'\n )\ndoc_d = (\n 'I often feel pressure to perform well at school, but my mother never seems to drive my brother to do better.'\n )\ndoc_e = 'Health professionals say that brocolli is good for your health.'\nrev1 = (\n \"I pre-ordered this for my wife mostly to use as a Kindle E-reader as I figured the tablet would be slow and the display would be less than impressive. I was wrong. What a bargain this little beauty is! This model cost $49.00 but it comes with ad's displayed on the lock screen when your tablet is dormant. Once your screen times out, they disappear. You can pay $15.00 up front to get an ad free version so I assumed to unlock the tablet I'd have to spend 15 to 30 seconds looking at an ad for Amazon Prime, or a product from the daily specials section of Amazon.com I abstained from paying for Ad removal and was pleasantly surprised to find that the ads are only on the lock screen and that as soon as I unlock the tablet they disappear immediately. Here are my pros and cons thus far. PRO: Perfect size for Ebooks, and web surfing to alleviate strain on the eyes from my 5 phone display nice sturdy casing that gives it a nice heft but still weighs in as one of the lighter tablets on the market Child Accounts- Amazon allows you to set up this tablet with age restricted access for kids making this a low cost piece of tech that is perfect for school kids and allows mom and dad to ration the amount of time lil Johnny can play Clash of Clans and how much he can hit the ol' Visa card for. Battery life thus far; wife was on it for about 5 hours last night and battery was at about 46% Kindle Integration -this goes without saying but having my ebooks and audible books synced to the tablet is awesome and my Kindle books look great\"\n )\nrev2 = (\n \"UPDATED - After spending quite a bit more time with the device, I would give it a 4.5 due to a few specific gaps that are a bit annoying. However, you are still getting an amazing 7” tablet, with front and rear facing cameras, a gorgeous interface, fairly snappy performance and durability, all for under 50 bucks! I can’t imagine not buying these for myself and my whole family, but not a primary tablet for a techie adult by any means. For background, I have every Kindle, a couple Fires, and multiple tablets from Apple, Microsoft and Samsung. Note that my review with 5 stars considers the value equation, not just performance and how that may or may not compare to other tablets - if you are expecting this to compare to a tablet costing several times more, don't bother. But if you are looking for a great entry level tablet that does most of the things people want, this little tablet definitely delivers the value! PRICING/CONFIG: I prefer this tablet with ads and no accessories to keep the costs down. You have the option to spend more money, but I recommend against it. You can easily see the specs online, so I won’t do you the discourtesy of simply cutting and pasting those here. Here is the price breakdown: 9.99 base price – what an incredible price point! Or buy 5 and get a sixth one free! This puts it into reach of schools and non-profits.\"\n )\nrev3 = (\n \"The short/summed up version: it's the new budget king in the 6-8 size. It's screen is a little lower in resolution but still pleasant to look at, it has enough power for most of the typical tablet tasks, and it shares many of the same features as its higher priced brothers such as front and back cameras, b/g/n wifi, and good overall battery life (minus an hour) My favorite size tablet is 8, so if you're looking at the amazon fire lineup, i would take this over the 6 for sure, and would have a hard time picking the 8 fire at 3x the price. If you re not a prime member, it s still a good tablet, if you are a prime member: it s a great tablet. Possible quality control issue: Mine had two dead pixels (not very noticeable, but still will exchange) You can load APKs(enable unknown sources), i loaded antutu and panasonic image app, both work properly.\"\n )\ndoc_set = [rev1, rev2, rev3]\ntexts = []\nfor i in doc_set:\n raw = i.lower()\n tokens = tokenizer.tokenize(raw)\n stopped_tokens = [i for i in tokens if not i in en_stop]\n stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]\n texts.append(stemmed_tokens)\ndictionary = corpora.Dictionary(texts)\ncorpus = [dictionary.doc2bow(text) for text in texts]\nldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=4, id2word=\n dictionary, passes=20)\nprint('LDA............')\ntopics = ldamodel.print_topics(num_topics=3, num_words=5)\nfor topic in topics:\n print(type(topic))\n print(topic)\nprint('LSA.................')\nlsi = gensim.models.lsimodel.LsiModel(corpus, id2word=dictionary)\nfrom nltk.corpus import sentiwordnet as swn\ntopics = lsi.print_topics(5)\nfor topic in topics:\n print(topic[1])\n print(swn.senti_synsets(topic[1]))\n print('----------------------------------------')\nhappy = swn.senti_synsets('happy')\nprint(happy.neg_score())\nall = swn.all_senti_synsets()\n",
"step-5": "from nltk.tokenize import RegexpTokenizer\nfrom stop_words import get_stop_words\nfrom nltk.stem.porter import PorterStemmer\nfrom gensim import corpora, models\nimport gensim\n\ntokenizer = RegexpTokenizer(r'\\w+')\n\n# create English stop words list\nen_stop = get_stop_words('en')\n\n# Create p_stemmer of class PorterStemmer\np_stemmer = PorterStemmer()\n\n# create sample documents\ndoc_a = \"Brocolli is good to eat. My brother likes to eat good brocolli, but not my mother.\"\ndoc_b = \"My mother spends a lot of time driving my brother around to baseball practice.\"\ndoc_c = \"Some health experts suggest that driving may cause increased tension and blood pressure.\"\ndoc_d = \"I often feel pressure to perform well at school, but my mother never seems to drive my brother to do better.\"\ndoc_e = \"Health professionals say that brocolli is good for your health.\"\n\nrev1 = \"I pre-ordered this for my wife mostly to use as a Kindle E-reader as I figured the tablet would be slow and the display would be less than impressive. I was wrong. What a bargain this little beauty is! This model cost $49.00 but it comes with ad's displayed on the lock screen when your tablet is dormant. Once your screen times out, they disappear. You can pay $15.00 up front to get an ad free version so I assumed to unlock the tablet I'd have to spend 15 to 30 seconds looking at an ad for Amazon Prime, or a product from the daily specials section of Amazon.com I abstained from paying for Ad removal and was pleasantly surprised to find that the ads are only on the lock screen and that as soon as I unlock the tablet they disappear immediately. Here are my pros and cons thus far. PRO: Perfect size for Ebooks, and web surfing to alleviate strain on the eyes from my 5 phone display nice sturdy casing that gives it a nice heft but still weighs in as one of the lighter tablets on the market Child Accounts- Amazon allows you to set up this tablet with age restricted access for kids making this a low cost piece of tech that is perfect for school kids and allows mom and dad to ration the amount of time lil Johnny can play Clash of Clans and how much he can hit the ol' Visa card for. Battery life thus far; wife was on it for about 5 hours last night and battery was at about 46% Kindle Integration -this goes without saying but having my ebooks and audible books synced to the tablet is awesome and my Kindle books look great\"\nrev2 = \"UPDATED - After spending quite a bit more time with the device, I would give it a 4.5 due to a few specific gaps that are a bit annoying. However, you are still getting an amazing 7” tablet, with front and rear facing cameras, a gorgeous interface, fairly snappy performance and durability, all for under 50 bucks! I can’t imagine not buying these for myself and my whole family, but not a primary tablet for a techie adult by any means. For background, I have every Kindle, a couple Fires, and multiple tablets from Apple, Microsoft and Samsung. Note that my review with 5 stars considers the value equation, not just performance and how that may or may not compare to other tablets - if you are expecting this to compare to a tablet costing several times more, don't bother. But if you are looking for a great entry level tablet that does most of the things people want, this little tablet definitely delivers the value! PRICING/CONFIG: I prefer this tablet with ads and no accessories to keep the costs down. You have the option to spend more money, but I recommend against it. You can easily see the specs online, so I won’t do you the discourtesy of simply cutting and pasting those here. Here is the price breakdown: 9.99 base price – what an incredible price point! Or buy 5 and get a sixth one free! This puts it into reach of schools and non-profits.\"\nrev3 =\"The short/summed up version: it's the new budget king in the 6-8 size. It's screen is a little lower in resolution but still pleasant to look at, it has enough power for most of the typical tablet tasks, and it shares many of the same features as its higher priced brothers such as front and back cameras, b/g/n wifi, and good overall battery life (minus an hour) My favorite size tablet is 8, so if you're looking at the amazon fire lineup, i would take this over the 6 for sure, and would have a hard time picking the 8 fire at 3x the price. If you re not a prime member, it s still a good tablet, if you are a prime member: it s a great tablet. Possible quality control issue: Mine had two dead pixels (not very noticeable, but still will exchange) You can load APKs(enable unknown sources), i loaded antutu and panasonic image app, both work properly.\"\n\n# compile sample documents into a list\n#doc_set = [doc_a, doc_b, doc_c, doc_d, doc_e]\ndoc_set = [rev1,rev2,rev3]\n# list for tokenized documents in loop\ntexts = []\n\n# loop through document list\nfor i in doc_set:\n # clean and tokenize document string\n raw = i.lower()\n tokens = tokenizer.tokenize(raw)\n\n # remove stop words from tokens\n stopped_tokens = [i for i in tokens if not i in en_stop]\n\n # stem tokens\n stemmed_tokens = [p_stemmer.stem(i) for i in stopped_tokens]\n\n # add tokens to list\n texts.append(stemmed_tokens)\n\n# turn our tokenized documents into a id <-> term dictionary\ndictionary = corpora.Dictionary(texts)\n\n# convert tokenized documents into a document-term matrix\ncorpus = [dictionary.doc2bow(text) for text in texts]\n\n# generate LDA model\nldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=4, id2word=dictionary, passes=20)\nprint(\"LDA............\")\ntopics = ldamodel.print_topics(num_topics=3, num_words=5)\nfor topic in topics:\n print(type(topic))\n print(topic)\n\nprint(\"LSA.................\")\n#id2word = gensim.corpora.Dictionary.load_from_text(\"c:\\lda_test.txt\")\nlsi = gensim.models.lsimodel.LsiModel(corpus, id2word=dictionary)\n\nfrom nltk.corpus import sentiwordnet as swn\n\ntopics = lsi.print_topics(5)\nfor topic in topics:\n print(topic[1])\n print(swn.senti_synsets(topic[1]))\n print(\"----------------------------------------\")\n\n\n\n#print(list(swn.senti_synsets('slow')))\n\nhappy = swn.senti_synsets('happy')\n\nprint(happy.neg_score())\n\nall = swn.all_senti_synsets()\n#print(all)",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
#-*-coding:utf-8 -*-
import subprocess
def get_audio(text):
stat = subprocess.call(['./tts', text])
if stat == 0:
return "Success"
else:
print "Failed"
if __name__ == '__main__':
text = "我是聊天机器人"
get_audio(text)
|
normal
|
{
"blob_id": "93eafb5b23bac513fc5dcc177a4e8a080b2a49b4",
"index": 9054,
"step-1": "#-*-coding:utf-8 -*-\n\nimport subprocess\n\ndef get_audio(text):\n stat = subprocess.call(['./tts', text])\n \n if stat == 0:\n return \"Success\"\n else:\n print \"Failed\"\n\nif __name__ == '__main__':\n text = \"我是聊天机器人\"\n get_audio(text)",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
import glob
import json
import pickle
import gzip
import os
import hashlib
import re
import bs4, lxml
import concurrent.futures
URL = 'http://mangamura.org'
def _map(arg):
key, names = arg
size = len(names)
urls = set()
for index, name in enumerate(names):
html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()
soup = bs4.BeautifulSoup(html, 'lxml')
for a in soup.findAll('a', href=True):
url = a.get('href')
if len(url) >= 2 and url[0] == '/':
url = URL + url
if URL not in url:
continue
if re.search(r'kai_pc_viewer\?p=', url) is None:
continue
print(f'{key} {index}/{size} {url}')
urls.add(url)
return urls
args = {}
for index, name in enumerate([name.split('/').pop() for name in glob.glob('htmls/*')]):
key = index%12
if args.get(key) is None:
args[key] = []
args[key].append( name )
args = [(key,names) for key, names in args.items()]
urls = set()
with concurrent.futures.ProcessPoolExecutor(max_workers=12) as exe:
for _urls in exe.map(_map,args) :
[urls.add(url) for url in _urls]
open('pc_viewer_urls.pkl.gz', 'wb').write(gzip.compress(pickle.dumps(urls)))
|
normal
|
{
"blob_id": "3acd592594ae4f12b9b694aed1aa0d48ebf485f5",
"index": 5787,
"step-1": "<mask token>\n\n\ndef _map(arg):\n key, names = arg\n size = len(names)\n urls = set()\n for index, name in enumerate(names):\n html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()\n soup = bs4.BeautifulSoup(html, 'lxml')\n for a in soup.findAll('a', href=True):\n url = a.get('href')\n if len(url) >= 2 and url[0] == '/':\n url = URL + url\n if URL not in url:\n continue\n if re.search('kai_pc_viewer\\\\?p=', url) is None:\n continue\n print(f'{key} {index}/{size} {url}')\n urls.add(url)\n return urls\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef _map(arg):\n key, names = arg\n size = len(names)\n urls = set()\n for index, name in enumerate(names):\n html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()\n soup = bs4.BeautifulSoup(html, 'lxml')\n for a in soup.findAll('a', href=True):\n url = a.get('href')\n if len(url) >= 2 and url[0] == '/':\n url = URL + url\n if URL not in url:\n continue\n if re.search('kai_pc_viewer\\\\?p=', url) is None:\n continue\n print(f'{key} {index}/{size} {url}')\n urls.add(url)\n return urls\n\n\n<mask token>\nfor index, name in enumerate([name.split('/').pop() for name in glob.glob(\n 'htmls/*')]):\n key = index % 12\n if args.get(key) is None:\n args[key] = []\n args[key].append(name)\n<mask token>\nwith concurrent.futures.ProcessPoolExecutor(max_workers=12) as exe:\n for _urls in exe.map(_map, args):\n [urls.add(url) for url in _urls]\nopen('pc_viewer_urls.pkl.gz', 'wb').write(gzip.compress(pickle.dumps(urls)))\n",
"step-3": "<mask token>\nURL = 'http://mangamura.org'\n\n\ndef _map(arg):\n key, names = arg\n size = len(names)\n urls = set()\n for index, name in enumerate(names):\n html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()\n soup = bs4.BeautifulSoup(html, 'lxml')\n for a in soup.findAll('a', href=True):\n url = a.get('href')\n if len(url) >= 2 and url[0] == '/':\n url = URL + url\n if URL not in url:\n continue\n if re.search('kai_pc_viewer\\\\?p=', url) is None:\n continue\n print(f'{key} {index}/{size} {url}')\n urls.add(url)\n return urls\n\n\nargs = {}\nfor index, name in enumerate([name.split('/').pop() for name in glob.glob(\n 'htmls/*')]):\n key = index % 12\n if args.get(key) is None:\n args[key] = []\n args[key].append(name)\nargs = [(key, names) for key, names in args.items()]\nurls = set()\nwith concurrent.futures.ProcessPoolExecutor(max_workers=12) as exe:\n for _urls in exe.map(_map, args):\n [urls.add(url) for url in _urls]\nopen('pc_viewer_urls.pkl.gz', 'wb').write(gzip.compress(pickle.dumps(urls)))\n",
"step-4": "import glob\nimport json\nimport pickle\nimport gzip\nimport os\nimport hashlib\nimport re\nimport bs4, lxml\nimport concurrent.futures\nURL = 'http://mangamura.org'\n\n\ndef _map(arg):\n key, names = arg\n size = len(names)\n urls = set()\n for index, name in enumerate(names):\n html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()\n soup = bs4.BeautifulSoup(html, 'lxml')\n for a in soup.findAll('a', href=True):\n url = a.get('href')\n if len(url) >= 2 and url[0] == '/':\n url = URL + url\n if URL not in url:\n continue\n if re.search('kai_pc_viewer\\\\?p=', url) is None:\n continue\n print(f'{key} {index}/{size} {url}')\n urls.add(url)\n return urls\n\n\nargs = {}\nfor index, name in enumerate([name.split('/').pop() for name in glob.glob(\n 'htmls/*')]):\n key = index % 12\n if args.get(key) is None:\n args[key] = []\n args[key].append(name)\nargs = [(key, names) for key, names in args.items()]\nurls = set()\nwith concurrent.futures.ProcessPoolExecutor(max_workers=12) as exe:\n for _urls in exe.map(_map, args):\n [urls.add(url) for url in _urls]\nopen('pc_viewer_urls.pkl.gz', 'wb').write(gzip.compress(pickle.dumps(urls)))\n",
"step-5": "import glob\n\nimport json\n\nimport pickle\n\nimport gzip\n\nimport os\n\nimport hashlib\n\nimport re\n\nimport bs4, lxml\n\nimport concurrent.futures\nURL = 'http://mangamura.org'\ndef _map(arg):\n key, names = arg\n size = len(names)\n urls = set()\n for index, name in enumerate(names):\n html = gzip.decompress(open('htmls/' + name, 'rb').read()).decode()\n soup = bs4.BeautifulSoup(html, 'lxml')\n for a in soup.findAll('a', href=True):\n url = a.get('href')\n if len(url) >= 2 and url[0] == '/':\n url = URL + url\n if URL not in url:\n continue\n if re.search(r'kai_pc_viewer\\?p=', url) is None:\n continue\n print(f'{key} {index}/{size} {url}')\n urls.add(url)\n return urls\n\nargs = {}\nfor index, name in enumerate([name.split('/').pop() for name in glob.glob('htmls/*')]):\n key = index%12\n if args.get(key) is None:\n args[key] = []\n args[key].append( name )\nargs = [(key,names) for key, names in args.items()]\nurls = set()\nwith concurrent.futures.ProcessPoolExecutor(max_workers=12) as exe:\n for _urls in exe.map(_map,args) :\n [urls.add(url) for url in _urls]\nopen('pc_viewer_urls.pkl.gz', 'wb').write(gzip.compress(pickle.dumps(urls)))\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
default_app_config = 'reman.apps.RemanConfig'
|
normal
|
{
"blob_id": "0b0b928aef9a4e9953b02639bf5e7769cc4389d7",
"index": 2488,
"step-1": "<mask token>\n",
"step-2": "default_app_config = 'reman.apps.RemanConfig'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
from keras.models import load_model
from DataManager import *
def loadModel(name):
model = load_model('./Model/%s.h5' % name)
return model
def predict(tag):
test = getPIData(tag, '2019-11-05', '2019-11-06')
test_arg = addFeature(test)
test_norm = normalize(test_arg)
X_test, Y_test = buildTrain(test_norm, 12 * 12, 1)
model = loadModel(tag)
return model.predict(X_test)
print(predict('USG60_eth0_ifInOctets'))
|
normal
|
{
"blob_id": "a6154c5d855dc53d73db08bbb5b5d7437056e156",
"index": 1566,
"step-1": "<mask token>\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n return model\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n return model\n\n\ndef predict(tag):\n test = getPIData(tag, '2019-11-05', '2019-11-06')\n test_arg = addFeature(test)\n test_norm = normalize(test_arg)\n X_test, Y_test = buildTrain(test_norm, 12 * 12, 1)\n model = loadModel(tag)\n return model.predict(X_test)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n return model\n\n\ndef predict(tag):\n test = getPIData(tag, '2019-11-05', '2019-11-06')\n test_arg = addFeature(test)\n test_norm = normalize(test_arg)\n X_test, Y_test = buildTrain(test_norm, 12 * 12, 1)\n model = loadModel(tag)\n return model.predict(X_test)\n\n\nprint(predict('USG60_eth0_ifInOctets'))\n",
"step-4": "from keras.models import load_model\nfrom DataManager import *\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n return model\n\n\ndef predict(tag):\n test = getPIData(tag, '2019-11-05', '2019-11-06')\n test_arg = addFeature(test)\n test_norm = normalize(test_arg)\n X_test, Y_test = buildTrain(test_norm, 12 * 12, 1)\n model = loadModel(tag)\n return model.predict(X_test)\n\n\nprint(predict('USG60_eth0_ifInOctets'))\n",
"step-5": null,
"step-ids": [
1,
2,
3,
4
]
}
|
[
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ==============================================================================
# Created By : Karl Thompson
# Created Date: Mon March 25 17:34:00 CDT 2019
# ==============================================================================
"""nasdaq_itch_vwap - Generate a table of running volume-weighted average price
[VWAP] for NASDAQ stocks at trading hours based on Nasdaq TotalView-ITCH 5 data.
Data available at: ftp://emi.nasdaq.com/ITCH/01302019.NASDAQ_ITCH50.gz
If you use this code in your work, please cite the following:
Karl H. Thompson, NASDAQ-ITCH-VWAP, (2019), GitHub repository,
https://github.com/karlhthompson/nasdaq-itch-vwap"""
# ==============================================================================
# Imports
# ==============================================================================
import pandas as pd
import struct
import gzip
import csv
# function to parse select messages in ITCH data:
def parse_itch_data(itch_data):
# read the first byte of each message in the data file:
msg_header = itch_data.read(1)
# initialize the csv file that will store parsed Add Order and Add Order
# with MPID messages:
add_order_data = open('add_order_data.csv','w')
add_order_wrtr = csv.writer(add_order_data)
# initialize the csv file that will store parsed Order Executed messages:
ord_exec_data = open('ord_exec_data.csv','w')
ord_exec_wrtr = csv.writer(ord_exec_data)
# initialize the csv file that will store parsed Order Executed With Price
# messages:
ord_exec_pr_data = open('ord_exec_pr_data.csv','w')
ord_exec_pr_wrtr = csv.writer(ord_exec_pr_data)
# initialize the csv file that will store parsed Trade messages:
trade_data = open('trade_data.csv','w')
trade_wrtr = csv.writer(trade_data)
# iterate over all messages in the data file:
while msg_header:
# process Add Order and Add Order with MPID messages:
if msg_header == b'A' or msg_header == b'F':
message = itch_data.read(35)
if len(message) < 35: break
un_pkd = struct.unpack('>4s6sQcI8cI',message)
re_pkd = struct.pack('>s4s2s6sQsI8sI',msg_header,un_pkd[0],
b'\x00\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],
b''.join(list(un_pkd[5:13])),un_pkd[13])
parsed_ao = list(struct.unpack('>sHHQQsI8sI',re_pkd))
# filter for data with valid Buy/Sell Indicators:
if parsed_ao[5] == b'B' or parsed_ao[5] == b'S':
# further filter for data with plausible field values:
if (parsed_ao[4] < 1e14 and parsed_ao[6] < 1e8):
# write the parsed message to the csv file:
try:
sto = parsed_ao[7].decode() # stock
except:
sto = '0' # Write 0 if stock byte decode fails
tim = parsed_ao[3] # timestamp
ref = parsed_ao[4] # order reference number
sha = parsed_ao[6] # shares
pri = float(parsed_ao[8])/1e4 # price
add_order_wrtr.writerow([sto, tim, ref, sha, pri])
# process Order Executed messages:
if msg_header == b'E':
message = itch_data.read(30)
if len(message) < 30: break
un_pkd = struct.unpack('>4s6sQIQ',message)
re_pkd = struct.pack('>s4s2s6sQIQ',msg_header,un_pkd[0],b'\x00\x00',
un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4])
parsed_oe = list(struct.unpack('>sHHQQIQ',re_pkd))
# filter for data with plausible field values:
if (parsed_oe[4] < 1e14 and parsed_oe[5] < 1e8 and parsed_oe[6] < 1e11):
# write the parsed message to the csv file:
ref = parsed_oe[4] # order reference number
sha = parsed_oe[5] # shares
ord_exec_wrtr.writerow([ref, sha])
# process Order Executed With Price messages:
if msg_header == b'C':
message = itch_data.read(35)
if len(message) < 35: break
un_pkd = struct.unpack('>4s6sQIQcI',message)
re_pkd = struct.pack('>s4s2s6sQIQsI',msg_header,un_pkd[0],
b'\x00\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],un_pkd[5],
un_pkd[6])
parsed_oewp = list(struct.unpack('>sHHQQIQsI',re_pkd))
# filter for data with plausible field values:
if (parsed_oewp[4] < 1e14 and parsed_oewp[5] < 1e6 and
parsed_oewp[6] < 1e10 and parsed_oewp[7] == b'Y'):
# write the parsed message to the csv file:
ref = parsed_oewp[4] # order reference number
sha = parsed_oewp[5] # shares
pri = float(parsed_oewp[8])/1e4 # new price
ord_exec_pr_wrtr.writerow([ref, sha, pri])
# process Trade messages:
if msg_header == b'P':
message = itch_data.read(43)
if len(message) < 43: break
un_pkd = struct.unpack('>4s6sQcI8cIQ',message)
re_pkd = struct.pack('>s4s2s6sQsI8sIQ',msg_header,un_pkd[0],
b'\x00\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],
b''.join(list(un_pkd[5:13])),un_pkd[13],un_pkd[14])
parsed_t = list(struct.unpack('>sHHQQsI8sIQ',re_pkd))
# filter for data with valid Order Reference Numbers
# and Buy/Sell Indicators:
if parsed_t[4] == 0 and parsed_t[5] == b'B':
# write the parsed message to the csv file:
sto = parsed_t[7].decode() # stock
tim = parsed_t[3] # timestamp
sha = parsed_t[6] # shares
pri = float(parsed_t[8])/1e4 # price
pro = parsed_t[6]*float(parsed_t[8])/1e4 # product
trade_wrtr.writerow([sto, tim, sha, pri, pro])
# advance the file position to the next message:
msg_header = itch_data.read(1)
# close the csv files:
add_order_data.close()
ord_exec_data.close()
ord_exec_pr_data.close()
trade_data.close()
# function to calculate the hourly VWAP based on parsed ITCH data:
def calculate_vwap():
# import the parsed Add Order data into a Pandas dataframe:
add_order_df = pd.read_csv('add_order_data.csv', index_col = None,
names = ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])
# import the parsed Order Executed data into a Pandas dataframe:
ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col = None,
names = ['Reference', 'Shares'])
# import the parsed Order Executed With Price data into a Pandas dataframe:
ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col = None,
names = ['Reference', 'Shares', 'Price'])
# import the parsed Trade data into a Pandas dataframe:
trade_1_df = pd.read_csv('trade_data.csv', index_col = 0,
names=['Stock', 'Timestamp', 'Shares', 'Price', 'Product'])
# merge the Order Executed data with the Add Order data to extract
# the executed trades data within:
trade_2_df = ord_exec_df.merge(add_order_df,on=['Reference'],how='inner')
trade_2_df = trade_2_df[trade_2_df['Stock']!='0']
trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']].set_index('Stock')
trade_2_df = trade_2_df.rename(columns={"Shares_x": "Shares"})
trade_2_df['Product'] = trade_2_df['Price']*trade_2_df['Shares']
# merge the Order Executed With Price data with the Add Order data
# to extract the executed trades data within:
trade_3_df = ord_exec_pr_df.merge(add_order_df,on=['Reference'],how='inner')
trade_3_df = trade_3_df[trade_3_df['Stock']!='0']
trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']].set_index('Stock')
trade_3_df = trade_3_df.rename(columns={"Shares_x": "Shares", "Price_x": "Price"})
trade_3_df['Product'] = trade_3_df['Price']*trade_3_df['Shares']
# concatenate all three trade dataframes (trades from Trade messages,
# trades from Executed Order messages, and trades from Executed Order
# With Price messages) into a comprehensive dataframe:
trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])
# create a dataframe for hourly running VWAP values:
vwap_df = trade_df.groupby(['Stock']).all().drop(
columns=['Timestamp', 'Shares', 'Price', 'Product'])
# create a list of trading hours in nanoseconds:
hour_list = [3.6e12 * i for i in [9.5, 10, 11, 12, 13, 14, 15, 16]]
# iterate over the trading hours list:
for hour in hour_list:
# extract data for trades that occurred before the specified hour:
trade_df_copy = trade_df[trade_df.Timestamp <= hour]
# group the trade dataframe by stock:
trade_df_groups = trade_df_copy.groupby(['Stock'])
# calculate the mean for all trade data:
trade_df_mean = trade_df_groups.mean(numeric_only=False)
# calculate the VWAP for all stocks:
trade_df_mean['VWAP'] = trade_df_mean['Product']/trade_df_mean['Shares']
# merge the calculated VWAP fields into the VWAP dataframe:
vwap_df = pd.merge(vwap_df,trade_df_mean['VWAP'],on=['Stock'],how='left')
# adjust the column names in the VWAP dataframe:
vwap_df.columns = ['VWAP at 09:30AM','VWAP at 10:00AM','VWAP at 11:00AM',
'VWAP at 12:00PM','VWAP at 01:00PM','VWAP at 02:00PM',
'VWAP at 03:00PM', 'VWAP at 04:00PM']
# save the hourly VWAP table in Excel format:
vwap_df.to_excel("NASDAQ_VWAP_01_30_2019.xlsx")
if __name__ == '__main__':
# open the ITCH data file:
itch_data = gzip.open('01302019.NASDAQ_ITCH50.gz','rb')
# parse the data:
parse_itch_data(itch_data)
# close the ITCH data file:
itch_data.close()
# calculate the hourly VWAP for all stocks:
calculate_vwap()
|
normal
|
{
"blob_id": "806124926008078e592141d80d08ccfbb3046dbf",
"index": 7092,
"step-1": "<mask token>\n\n\ndef calculate_vwap():\n add_order_df = pd.read_csv('add_order_data.csv', index_col=None, names=\n ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])\n ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col=None, names=[\n 'Reference', 'Shares'])\n ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col=None,\n names=['Reference', 'Shares', 'Price'])\n trade_1_df = pd.read_csv('trade_data.csv', index_col=0, names=['Stock',\n 'Timestamp', 'Shares', 'Price', 'Product'])\n trade_2_df = ord_exec_df.merge(add_order_df, on=['Reference'], how='inner')\n trade_2_df = trade_2_df[trade_2_df['Stock'] != '0']\n trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']\n ].set_index('Stock')\n trade_2_df = trade_2_df.rename(columns={'Shares_x': 'Shares'})\n trade_2_df['Product'] = trade_2_df['Price'] * trade_2_df['Shares']\n trade_3_df = ord_exec_pr_df.merge(add_order_df, on=['Reference'], how=\n 'inner')\n trade_3_df = trade_3_df[trade_3_df['Stock'] != '0']\n trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']\n ].set_index('Stock')\n trade_3_df = trade_3_df.rename(columns={'Shares_x': 'Shares', 'Price_x':\n 'Price'})\n trade_3_df['Product'] = trade_3_df['Price'] * trade_3_df['Shares']\n trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])\n vwap_df = trade_df.groupby(['Stock']).all().drop(columns=['Timestamp',\n 'Shares', 'Price', 'Product'])\n hour_list = [(3600000000000.0 * i) for i in [9.5, 10, 11, 12, 13, 14, \n 15, 16]]\n for hour in hour_list:\n trade_df_copy = trade_df[trade_df.Timestamp <= hour]\n trade_df_groups = trade_df_copy.groupby(['Stock'])\n trade_df_mean = trade_df_groups.mean(numeric_only=False)\n trade_df_mean['VWAP'] = trade_df_mean['Product'] / trade_df_mean[\n 'Shares']\n vwap_df = pd.merge(vwap_df, trade_df_mean['VWAP'], on=['Stock'],\n how='left')\n vwap_df.columns = ['VWAP at 09:30AM', 'VWAP at 10:00AM',\n 'VWAP at 11:00AM', 'VWAP at 12:00PM', 'VWAP at 01:00PM',\n 'VWAP at 02:00PM', 'VWAP at 03:00PM', 'VWAP at 04:00PM']\n vwap_df.to_excel('NASDAQ_VWAP_01_30_2019.xlsx')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_itch_data(itch_data):\n msg_header = itch_data.read(1)\n add_order_data = open('add_order_data.csv', 'w')\n add_order_wrtr = csv.writer(add_order_data)\n ord_exec_data = open('ord_exec_data.csv', 'w')\n ord_exec_wrtr = csv.writer(ord_exec_data)\n ord_exec_pr_data = open('ord_exec_pr_data.csv', 'w')\n ord_exec_pr_wrtr = csv.writer(ord_exec_pr_data)\n trade_data = open('trade_data.csv', 'w')\n trade_wrtr = csv.writer(trade_data)\n while msg_header:\n if msg_header == b'A' or msg_header == b'F':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQcI8cI', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13])\n parsed_ao = list(struct.unpack('>sHHQQsI8sI', re_pkd))\n if parsed_ao[5] == b'B' or parsed_ao[5] == b'S':\n if parsed_ao[4] < 100000000000000.0 and parsed_ao[6\n ] < 100000000.0:\n try:\n sto = parsed_ao[7].decode()\n except:\n sto = '0'\n tim = parsed_ao[3]\n ref = parsed_ao[4]\n sha = parsed_ao[6]\n pri = float(parsed_ao[8]) / 10000.0\n add_order_wrtr.writerow([sto, tim, ref, sha, pri])\n if msg_header == b'E':\n message = itch_data.read(30)\n if len(message) < 30:\n break\n un_pkd = struct.unpack('>4s6sQIQ', message)\n re_pkd = struct.pack('>s4s2s6sQIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4])\n parsed_oe = list(struct.unpack('>sHHQQIQ', re_pkd))\n if parsed_oe[4] < 100000000000000.0 and parsed_oe[5\n ] < 100000000.0 and parsed_oe[6] < 100000000000.0:\n ref = parsed_oe[4]\n sha = parsed_oe[5]\n ord_exec_wrtr.writerow([ref, sha])\n if msg_header == b'C':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQIQcI', message)\n re_pkd = struct.pack('>s4s2s6sQIQsI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n un_pkd[5], un_pkd[6])\n parsed_oewp = list(struct.unpack('>sHHQQIQsI', re_pkd))\n if parsed_oewp[4] < 100000000000000.0 and parsed_oewp[5\n ] < 1000000.0 and parsed_oewp[6\n ] < 10000000000.0 and parsed_oewp[7] == b'Y':\n ref = parsed_oewp[4]\n sha = parsed_oewp[5]\n pri = float(parsed_oewp[8]) / 10000.0\n ord_exec_pr_wrtr.writerow([ref, sha, pri])\n if msg_header == b'P':\n message = itch_data.read(43)\n if len(message) < 43:\n break\n un_pkd = struct.unpack('>4s6sQcI8cIQ', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13], un_pkd[14])\n parsed_t = list(struct.unpack('>sHHQQsI8sIQ', re_pkd))\n if parsed_t[4] == 0 and parsed_t[5] == b'B':\n sto = parsed_t[7].decode()\n tim = parsed_t[3]\n sha = parsed_t[6]\n pri = float(parsed_t[8]) / 10000.0\n pro = parsed_t[6] * float(parsed_t[8]) / 10000.0\n trade_wrtr.writerow([sto, tim, sha, pri, pro])\n msg_header = itch_data.read(1)\n add_order_data.close()\n ord_exec_data.close()\n ord_exec_pr_data.close()\n trade_data.close()\n\n\ndef calculate_vwap():\n add_order_df = pd.read_csv('add_order_data.csv', index_col=None, names=\n ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])\n ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col=None, names=[\n 'Reference', 'Shares'])\n ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col=None,\n names=['Reference', 'Shares', 'Price'])\n trade_1_df = pd.read_csv('trade_data.csv', index_col=0, names=['Stock',\n 'Timestamp', 'Shares', 'Price', 'Product'])\n trade_2_df = ord_exec_df.merge(add_order_df, on=['Reference'], how='inner')\n trade_2_df = trade_2_df[trade_2_df['Stock'] != '0']\n trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']\n ].set_index('Stock')\n trade_2_df = trade_2_df.rename(columns={'Shares_x': 'Shares'})\n trade_2_df['Product'] = trade_2_df['Price'] * trade_2_df['Shares']\n trade_3_df = ord_exec_pr_df.merge(add_order_df, on=['Reference'], how=\n 'inner')\n trade_3_df = trade_3_df[trade_3_df['Stock'] != '0']\n trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']\n ].set_index('Stock')\n trade_3_df = trade_3_df.rename(columns={'Shares_x': 'Shares', 'Price_x':\n 'Price'})\n trade_3_df['Product'] = trade_3_df['Price'] * trade_3_df['Shares']\n trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])\n vwap_df = trade_df.groupby(['Stock']).all().drop(columns=['Timestamp',\n 'Shares', 'Price', 'Product'])\n hour_list = [(3600000000000.0 * i) for i in [9.5, 10, 11, 12, 13, 14, \n 15, 16]]\n for hour in hour_list:\n trade_df_copy = trade_df[trade_df.Timestamp <= hour]\n trade_df_groups = trade_df_copy.groupby(['Stock'])\n trade_df_mean = trade_df_groups.mean(numeric_only=False)\n trade_df_mean['VWAP'] = trade_df_mean['Product'] / trade_df_mean[\n 'Shares']\n vwap_df = pd.merge(vwap_df, trade_df_mean['VWAP'], on=['Stock'],\n how='left')\n vwap_df.columns = ['VWAP at 09:30AM', 'VWAP at 10:00AM',\n 'VWAP at 11:00AM', 'VWAP at 12:00PM', 'VWAP at 01:00PM',\n 'VWAP at 02:00PM', 'VWAP at 03:00PM', 'VWAP at 04:00PM']\n vwap_df.to_excel('NASDAQ_VWAP_01_30_2019.xlsx')\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef parse_itch_data(itch_data):\n msg_header = itch_data.read(1)\n add_order_data = open('add_order_data.csv', 'w')\n add_order_wrtr = csv.writer(add_order_data)\n ord_exec_data = open('ord_exec_data.csv', 'w')\n ord_exec_wrtr = csv.writer(ord_exec_data)\n ord_exec_pr_data = open('ord_exec_pr_data.csv', 'w')\n ord_exec_pr_wrtr = csv.writer(ord_exec_pr_data)\n trade_data = open('trade_data.csv', 'w')\n trade_wrtr = csv.writer(trade_data)\n while msg_header:\n if msg_header == b'A' or msg_header == b'F':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQcI8cI', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13])\n parsed_ao = list(struct.unpack('>sHHQQsI8sI', re_pkd))\n if parsed_ao[5] == b'B' or parsed_ao[5] == b'S':\n if parsed_ao[4] < 100000000000000.0 and parsed_ao[6\n ] < 100000000.0:\n try:\n sto = parsed_ao[7].decode()\n except:\n sto = '0'\n tim = parsed_ao[3]\n ref = parsed_ao[4]\n sha = parsed_ao[6]\n pri = float(parsed_ao[8]) / 10000.0\n add_order_wrtr.writerow([sto, tim, ref, sha, pri])\n if msg_header == b'E':\n message = itch_data.read(30)\n if len(message) < 30:\n break\n un_pkd = struct.unpack('>4s6sQIQ', message)\n re_pkd = struct.pack('>s4s2s6sQIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4])\n parsed_oe = list(struct.unpack('>sHHQQIQ', re_pkd))\n if parsed_oe[4] < 100000000000000.0 and parsed_oe[5\n ] < 100000000.0 and parsed_oe[6] < 100000000000.0:\n ref = parsed_oe[4]\n sha = parsed_oe[5]\n ord_exec_wrtr.writerow([ref, sha])\n if msg_header == b'C':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQIQcI', message)\n re_pkd = struct.pack('>s4s2s6sQIQsI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n un_pkd[5], un_pkd[6])\n parsed_oewp = list(struct.unpack('>sHHQQIQsI', re_pkd))\n if parsed_oewp[4] < 100000000000000.0 and parsed_oewp[5\n ] < 1000000.0 and parsed_oewp[6\n ] < 10000000000.0 and parsed_oewp[7] == b'Y':\n ref = parsed_oewp[4]\n sha = parsed_oewp[5]\n pri = float(parsed_oewp[8]) / 10000.0\n ord_exec_pr_wrtr.writerow([ref, sha, pri])\n if msg_header == b'P':\n message = itch_data.read(43)\n if len(message) < 43:\n break\n un_pkd = struct.unpack('>4s6sQcI8cIQ', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13], un_pkd[14])\n parsed_t = list(struct.unpack('>sHHQQsI8sIQ', re_pkd))\n if parsed_t[4] == 0 and parsed_t[5] == b'B':\n sto = parsed_t[7].decode()\n tim = parsed_t[3]\n sha = parsed_t[6]\n pri = float(parsed_t[8]) / 10000.0\n pro = parsed_t[6] * float(parsed_t[8]) / 10000.0\n trade_wrtr.writerow([sto, tim, sha, pri, pro])\n msg_header = itch_data.read(1)\n add_order_data.close()\n ord_exec_data.close()\n ord_exec_pr_data.close()\n trade_data.close()\n\n\ndef calculate_vwap():\n add_order_df = pd.read_csv('add_order_data.csv', index_col=None, names=\n ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])\n ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col=None, names=[\n 'Reference', 'Shares'])\n ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col=None,\n names=['Reference', 'Shares', 'Price'])\n trade_1_df = pd.read_csv('trade_data.csv', index_col=0, names=['Stock',\n 'Timestamp', 'Shares', 'Price', 'Product'])\n trade_2_df = ord_exec_df.merge(add_order_df, on=['Reference'], how='inner')\n trade_2_df = trade_2_df[trade_2_df['Stock'] != '0']\n trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']\n ].set_index('Stock')\n trade_2_df = trade_2_df.rename(columns={'Shares_x': 'Shares'})\n trade_2_df['Product'] = trade_2_df['Price'] * trade_2_df['Shares']\n trade_3_df = ord_exec_pr_df.merge(add_order_df, on=['Reference'], how=\n 'inner')\n trade_3_df = trade_3_df[trade_3_df['Stock'] != '0']\n trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']\n ].set_index('Stock')\n trade_3_df = trade_3_df.rename(columns={'Shares_x': 'Shares', 'Price_x':\n 'Price'})\n trade_3_df['Product'] = trade_3_df['Price'] * trade_3_df['Shares']\n trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])\n vwap_df = trade_df.groupby(['Stock']).all().drop(columns=['Timestamp',\n 'Shares', 'Price', 'Product'])\n hour_list = [(3600000000000.0 * i) for i in [9.5, 10, 11, 12, 13, 14, \n 15, 16]]\n for hour in hour_list:\n trade_df_copy = trade_df[trade_df.Timestamp <= hour]\n trade_df_groups = trade_df_copy.groupby(['Stock'])\n trade_df_mean = trade_df_groups.mean(numeric_only=False)\n trade_df_mean['VWAP'] = trade_df_mean['Product'] / trade_df_mean[\n 'Shares']\n vwap_df = pd.merge(vwap_df, trade_df_mean['VWAP'], on=['Stock'],\n how='left')\n vwap_df.columns = ['VWAP at 09:30AM', 'VWAP at 10:00AM',\n 'VWAP at 11:00AM', 'VWAP at 12:00PM', 'VWAP at 01:00PM',\n 'VWAP at 02:00PM', 'VWAP at 03:00PM', 'VWAP at 04:00PM']\n vwap_df.to_excel('NASDAQ_VWAP_01_30_2019.xlsx')\n\n\nif __name__ == '__main__':\n itch_data = gzip.open('01302019.NASDAQ_ITCH50.gz', 'rb')\n parse_itch_data(itch_data)\n itch_data.close()\n calculate_vwap()\n",
"step-4": "<mask token>\nimport pandas as pd\nimport struct\nimport gzip\nimport csv\n\n\ndef parse_itch_data(itch_data):\n msg_header = itch_data.read(1)\n add_order_data = open('add_order_data.csv', 'w')\n add_order_wrtr = csv.writer(add_order_data)\n ord_exec_data = open('ord_exec_data.csv', 'w')\n ord_exec_wrtr = csv.writer(ord_exec_data)\n ord_exec_pr_data = open('ord_exec_pr_data.csv', 'w')\n ord_exec_pr_wrtr = csv.writer(ord_exec_pr_data)\n trade_data = open('trade_data.csv', 'w')\n trade_wrtr = csv.writer(trade_data)\n while msg_header:\n if msg_header == b'A' or msg_header == b'F':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQcI8cI', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13])\n parsed_ao = list(struct.unpack('>sHHQQsI8sI', re_pkd))\n if parsed_ao[5] == b'B' or parsed_ao[5] == b'S':\n if parsed_ao[4] < 100000000000000.0 and parsed_ao[6\n ] < 100000000.0:\n try:\n sto = parsed_ao[7].decode()\n except:\n sto = '0'\n tim = parsed_ao[3]\n ref = parsed_ao[4]\n sha = parsed_ao[6]\n pri = float(parsed_ao[8]) / 10000.0\n add_order_wrtr.writerow([sto, tim, ref, sha, pri])\n if msg_header == b'E':\n message = itch_data.read(30)\n if len(message) < 30:\n break\n un_pkd = struct.unpack('>4s6sQIQ', message)\n re_pkd = struct.pack('>s4s2s6sQIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4])\n parsed_oe = list(struct.unpack('>sHHQQIQ', re_pkd))\n if parsed_oe[4] < 100000000000000.0 and parsed_oe[5\n ] < 100000000.0 and parsed_oe[6] < 100000000000.0:\n ref = parsed_oe[4]\n sha = parsed_oe[5]\n ord_exec_wrtr.writerow([ref, sha])\n if msg_header == b'C':\n message = itch_data.read(35)\n if len(message) < 35:\n break\n un_pkd = struct.unpack('>4s6sQIQcI', message)\n re_pkd = struct.pack('>s4s2s6sQIQsI', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n un_pkd[5], un_pkd[6])\n parsed_oewp = list(struct.unpack('>sHHQQIQsI', re_pkd))\n if parsed_oewp[4] < 100000000000000.0 and parsed_oewp[5\n ] < 1000000.0 and parsed_oewp[6\n ] < 10000000000.0 and parsed_oewp[7] == b'Y':\n ref = parsed_oewp[4]\n sha = parsed_oewp[5]\n pri = float(parsed_oewp[8]) / 10000.0\n ord_exec_pr_wrtr.writerow([ref, sha, pri])\n if msg_header == b'P':\n message = itch_data.read(43)\n if len(message) < 43:\n break\n un_pkd = struct.unpack('>4s6sQcI8cIQ', message)\n re_pkd = struct.pack('>s4s2s6sQsI8sIQ', msg_header, un_pkd[0],\n b'\\x00\\x00', un_pkd[1], un_pkd[2], un_pkd[3], un_pkd[4],\n b''.join(list(un_pkd[5:13])), un_pkd[13], un_pkd[14])\n parsed_t = list(struct.unpack('>sHHQQsI8sIQ', re_pkd))\n if parsed_t[4] == 0 and parsed_t[5] == b'B':\n sto = parsed_t[7].decode()\n tim = parsed_t[3]\n sha = parsed_t[6]\n pri = float(parsed_t[8]) / 10000.0\n pro = parsed_t[6] * float(parsed_t[8]) / 10000.0\n trade_wrtr.writerow([sto, tim, sha, pri, pro])\n msg_header = itch_data.read(1)\n add_order_data.close()\n ord_exec_data.close()\n ord_exec_pr_data.close()\n trade_data.close()\n\n\ndef calculate_vwap():\n add_order_df = pd.read_csv('add_order_data.csv', index_col=None, names=\n ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])\n ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col=None, names=[\n 'Reference', 'Shares'])\n ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col=None,\n names=['Reference', 'Shares', 'Price'])\n trade_1_df = pd.read_csv('trade_data.csv', index_col=0, names=['Stock',\n 'Timestamp', 'Shares', 'Price', 'Product'])\n trade_2_df = ord_exec_df.merge(add_order_df, on=['Reference'], how='inner')\n trade_2_df = trade_2_df[trade_2_df['Stock'] != '0']\n trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']\n ].set_index('Stock')\n trade_2_df = trade_2_df.rename(columns={'Shares_x': 'Shares'})\n trade_2_df['Product'] = trade_2_df['Price'] * trade_2_df['Shares']\n trade_3_df = ord_exec_pr_df.merge(add_order_df, on=['Reference'], how=\n 'inner')\n trade_3_df = trade_3_df[trade_3_df['Stock'] != '0']\n trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']\n ].set_index('Stock')\n trade_3_df = trade_3_df.rename(columns={'Shares_x': 'Shares', 'Price_x':\n 'Price'})\n trade_3_df['Product'] = trade_3_df['Price'] * trade_3_df['Shares']\n trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])\n vwap_df = trade_df.groupby(['Stock']).all().drop(columns=['Timestamp',\n 'Shares', 'Price', 'Product'])\n hour_list = [(3600000000000.0 * i) for i in [9.5, 10, 11, 12, 13, 14, \n 15, 16]]\n for hour in hour_list:\n trade_df_copy = trade_df[trade_df.Timestamp <= hour]\n trade_df_groups = trade_df_copy.groupby(['Stock'])\n trade_df_mean = trade_df_groups.mean(numeric_only=False)\n trade_df_mean['VWAP'] = trade_df_mean['Product'] / trade_df_mean[\n 'Shares']\n vwap_df = pd.merge(vwap_df, trade_df_mean['VWAP'], on=['Stock'],\n how='left')\n vwap_df.columns = ['VWAP at 09:30AM', 'VWAP at 10:00AM',\n 'VWAP at 11:00AM', 'VWAP at 12:00PM', 'VWAP at 01:00PM',\n 'VWAP at 02:00PM', 'VWAP at 03:00PM', 'VWAP at 04:00PM']\n vwap_df.to_excel('NASDAQ_VWAP_01_30_2019.xlsx')\n\n\nif __name__ == '__main__':\n itch_data = gzip.open('01302019.NASDAQ_ITCH50.gz', 'rb')\n parse_itch_data(itch_data)\n itch_data.close()\n calculate_vwap()\n",
"step-5": "#!/usr/bin/env python3\r\n# -*- coding: utf-8 -*-\r\n# ==============================================================================\r\n# Created By : Karl Thompson\r\n# Created Date: Mon March 25 17:34:00 CDT 2019\r\n# ==============================================================================\r\n\"\"\"nasdaq_itch_vwap - Generate a table of running volume-weighted average price\r\n[VWAP] for NASDAQ stocks at trading hours based on Nasdaq TotalView-ITCH 5 data.\r\nData available at: ftp://emi.nasdaq.com/ITCH/01302019.NASDAQ_ITCH50.gz\r\nIf you use this code in your work, please cite the following:\r\nKarl H. Thompson, NASDAQ-ITCH-VWAP, (2019), GitHub repository, \r\nhttps://github.com/karlhthompson/nasdaq-itch-vwap\"\"\"\r\n# ==============================================================================\r\n# Imports\r\n# ==============================================================================\r\nimport pandas as pd\r\nimport struct\r\nimport gzip\r\nimport csv\r\n\r\n# function to parse select messages in ITCH data:\r\ndef parse_itch_data(itch_data):\r\n\r\n # read the first byte of each message in the data file:\r\n msg_header = itch_data.read(1)\r\n\r\n # initialize the csv file that will store parsed Add Order and Add Order \r\n # with MPID messages:\r\n add_order_data = open('add_order_data.csv','w')\r\n add_order_wrtr = csv.writer(add_order_data)\r\n\r\n # initialize the csv file that will store parsed Order Executed messages:\r\n ord_exec_data = open('ord_exec_data.csv','w')\r\n ord_exec_wrtr = csv.writer(ord_exec_data)\r\n\r\n # initialize the csv file that will store parsed Order Executed With Price \r\n # messages:\r\n ord_exec_pr_data = open('ord_exec_pr_data.csv','w')\r\n ord_exec_pr_wrtr = csv.writer(ord_exec_pr_data)\r\n\r\n # initialize the csv file that will store parsed Trade messages:\r\n trade_data = open('trade_data.csv','w')\r\n trade_wrtr = csv.writer(trade_data)\r\n\r\n # iterate over all messages in the data file:\r\n while msg_header:\r\n\r\n # process Add Order and Add Order with MPID messages:\r\n if msg_header == b'A' or msg_header == b'F':\r\n message = itch_data.read(35)\r\n if len(message) < 35: break\r\n un_pkd = struct.unpack('>4s6sQcI8cI',message)\r\n re_pkd = struct.pack('>s4s2s6sQsI8sI',msg_header,un_pkd[0],\r\n b'\\x00\\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],\r\n b''.join(list(un_pkd[5:13])),un_pkd[13])\r\n parsed_ao = list(struct.unpack('>sHHQQsI8sI',re_pkd))\r\n # filter for data with valid Buy/Sell Indicators:\r\n if parsed_ao[5] == b'B' or parsed_ao[5] == b'S':\r\n # further filter for data with plausible field values:\r\n if (parsed_ao[4] < 1e14 and parsed_ao[6] < 1e8):\r\n # write the parsed message to the csv file:\r\n try:\r\n sto = parsed_ao[7].decode() # stock\r\n except:\r\n sto = '0' # Write 0 if stock byte decode fails\r\n tim = parsed_ao[3] # timestamp\r\n ref = parsed_ao[4] # order reference number\r\n sha = parsed_ao[6] # shares\r\n pri = float(parsed_ao[8])/1e4 # price\r\n add_order_wrtr.writerow([sto, tim, ref, sha, pri])\r\n\r\n # process Order Executed messages:\r\n if msg_header == b'E':\r\n message = itch_data.read(30)\r\n if len(message) < 30: break\r\n un_pkd = struct.unpack('>4s6sQIQ',message)\r\n re_pkd = struct.pack('>s4s2s6sQIQ',msg_header,un_pkd[0],b'\\x00\\x00',\r\n un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4])\r\n parsed_oe = list(struct.unpack('>sHHQQIQ',re_pkd))\r\n # filter for data with plausible field values:\r\n if (parsed_oe[4] < 1e14 and parsed_oe[5] < 1e8 and parsed_oe[6] < 1e11):\r\n # write the parsed message to the csv file:\r\n ref = parsed_oe[4] # order reference number\r\n sha = parsed_oe[5] # shares\r\n ord_exec_wrtr.writerow([ref, sha])\r\n\r\n # process Order Executed With Price messages:\r\n if msg_header == b'C':\r\n message = itch_data.read(35)\r\n if len(message) < 35: break\r\n un_pkd = struct.unpack('>4s6sQIQcI',message)\r\n re_pkd = struct.pack('>s4s2s6sQIQsI',msg_header,un_pkd[0],\r\n b'\\x00\\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],un_pkd[5],\r\n un_pkd[6])\r\n parsed_oewp = list(struct.unpack('>sHHQQIQsI',re_pkd))\r\n # filter for data with plausible field values:\r\n if (parsed_oewp[4] < 1e14 and parsed_oewp[5] < 1e6 and\r\n parsed_oewp[6] < 1e10 and parsed_oewp[7] == b'Y'):\r\n # write the parsed message to the csv file:\r\n ref = parsed_oewp[4] # order reference number\r\n sha = parsed_oewp[5] # shares\r\n pri = float(parsed_oewp[8])/1e4 # new price\r\n ord_exec_pr_wrtr.writerow([ref, sha, pri])\r\n\r\n # process Trade messages:\r\n if msg_header == b'P':\r\n message = itch_data.read(43)\r\n if len(message) < 43: break\r\n un_pkd = struct.unpack('>4s6sQcI8cIQ',message)\r\n re_pkd = struct.pack('>s4s2s6sQsI8sIQ',msg_header,un_pkd[0],\r\n b'\\x00\\x00',un_pkd[1],un_pkd[2],un_pkd[3],un_pkd[4],\r\n b''.join(list(un_pkd[5:13])),un_pkd[13],un_pkd[14])\r\n parsed_t = list(struct.unpack('>sHHQQsI8sIQ',re_pkd))\r\n # filter for data with valid Order Reference Numbers\r\n # and Buy/Sell Indicators:\r\n if parsed_t[4] == 0 and parsed_t[5] == b'B':\r\n # write the parsed message to the csv file:\r\n sto = parsed_t[7].decode() # stock\r\n tim = parsed_t[3] # timestamp\r\n sha = parsed_t[6] # shares\r\n pri = float(parsed_t[8])/1e4 # price\r\n pro = parsed_t[6]*float(parsed_t[8])/1e4 # product\r\n trade_wrtr.writerow([sto, tim, sha, pri, pro])\r\n\r\n # advance the file position to the next message:\r\n msg_header = itch_data.read(1)\r\n\r\n # close the csv files:\r\n add_order_data.close()\r\n ord_exec_data.close()\r\n ord_exec_pr_data.close()\r\n trade_data.close()\r\n\r\n\r\n# function to calculate the hourly VWAP based on parsed ITCH data:\r\ndef calculate_vwap():\r\n\r\n # import the parsed Add Order data into a Pandas dataframe:\r\n add_order_df = pd.read_csv('add_order_data.csv', index_col = None, \r\n names = ['Stock', 'Timestamp', 'Reference', 'Shares', 'Price'])\r\n\r\n # import the parsed Order Executed data into a Pandas dataframe:\r\n ord_exec_df = pd.read_csv('ord_exec_data.csv', index_col = None, \r\n names = ['Reference', 'Shares'])\r\n\r\n # import the parsed Order Executed With Price data into a Pandas dataframe:\r\n ord_exec_pr_df = pd.read_csv('ord_exec_pr_data.csv', index_col = None,\r\n names = ['Reference', 'Shares', 'Price'])\r\n\r\n # import the parsed Trade data into a Pandas dataframe:\r\n trade_1_df = pd.read_csv('trade_data.csv', index_col = 0,\r\n names=['Stock', 'Timestamp', 'Shares', 'Price', 'Product'])\r\n \r\n # merge the Order Executed data with the Add Order data to extract\r\n # the executed trades data within:\r\n trade_2_df = ord_exec_df.merge(add_order_df,on=['Reference'],how='inner')\r\n trade_2_df = trade_2_df[trade_2_df['Stock']!='0']\r\n trade_2_df = trade_2_df[['Stock', 'Timestamp', 'Shares_x', 'Price']].set_index('Stock')\r\n trade_2_df = trade_2_df.rename(columns={\"Shares_x\": \"Shares\"})\r\n trade_2_df['Product'] = trade_2_df['Price']*trade_2_df['Shares']\r\n\r\n # merge the Order Executed With Price data with the Add Order data\r\n # to extract the executed trades data within:\r\n trade_3_df = ord_exec_pr_df.merge(add_order_df,on=['Reference'],how='inner')\r\n trade_3_df = trade_3_df[trade_3_df['Stock']!='0']\r\n trade_3_df = trade_3_df[['Stock', 'Timestamp', 'Shares_x', 'Price_x']].set_index('Stock')\r\n trade_3_df = trade_3_df.rename(columns={\"Shares_x\": \"Shares\", \"Price_x\": \"Price\"})\r\n trade_3_df['Product'] = trade_3_df['Price']*trade_3_df['Shares']\r\n\r\n # concatenate all three trade dataframes (trades from Trade messages,\r\n # trades from Executed Order messages, and trades from Executed Order\r\n # With Price messages) into a comprehensive dataframe:\r\n trade_df = pd.concat([trade_1_df, trade_2_df, trade_3_df])\r\n\r\n # create a dataframe for hourly running VWAP values:\r\n vwap_df = trade_df.groupby(['Stock']).all().drop(\r\n columns=['Timestamp', 'Shares', 'Price', 'Product'])\r\n\r\n # create a list of trading hours in nanoseconds:\r\n hour_list = [3.6e12 * i for i in [9.5, 10, 11, 12, 13, 14, 15, 16]]\r\n\r\n # iterate over the trading hours list:\r\n for hour in hour_list:\r\n # extract data for trades that occurred before the specified hour:\r\n trade_df_copy = trade_df[trade_df.Timestamp <= hour]\r\n # group the trade dataframe by stock:\r\n trade_df_groups = trade_df_copy.groupby(['Stock'])\r\n # calculate the mean for all trade data:\r\n trade_df_mean = trade_df_groups.mean(numeric_only=False)\r\n # calculate the VWAP for all stocks:\r\n trade_df_mean['VWAP'] = trade_df_mean['Product']/trade_df_mean['Shares']\r\n # merge the calculated VWAP fields into the VWAP dataframe:\r\n vwap_df = pd.merge(vwap_df,trade_df_mean['VWAP'],on=['Stock'],how='left')\r\n\r\n # adjust the column names in the VWAP dataframe:\r\n vwap_df.columns = ['VWAP at 09:30AM','VWAP at 10:00AM','VWAP at 11:00AM',\r\n 'VWAP at 12:00PM','VWAP at 01:00PM','VWAP at 02:00PM',\r\n 'VWAP at 03:00PM', 'VWAP at 04:00PM']\r\n\r\n # save the hourly VWAP table in Excel format:\r\n vwap_df.to_excel(\"NASDAQ_VWAP_01_30_2019.xlsx\")\r\n\r\nif __name__ == '__main__':\r\n \r\n # open the ITCH data file:\r\n itch_data = gzip.open('01302019.NASDAQ_ITCH50.gz','rb')\r\n\r\n # parse the data:\r\n parse_itch_data(itch_data)\r\n\r\n # close the ITCH data file:\r\n itch_data.close()\r\n\r\n # calculate the hourly VWAP for all stocks:\r\n calculate_vwap()\r\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
##############################################################################
# Copyright by The HDF Group. #
# All rights reserved. #
# #
# This file is part of HSDS (HDF5 Scalable Data Service), Libraries and #
# Utilities. The full HSDS copyright notice, including #
# terms governing use, modification, and redistribution, is contained in #
# the file COPYING, which can be found at the root of the source code #
# distribution tree. If you do not have access to this file, you may #
# request a copy from [email protected]. #
##############################################################################
#
# Simple looger for hsds
#
import asyncio
from aiohttp.web_exceptions import HTTPServiceUnavailable
from .util.domainUtil import getDomainFromRequest
req_count = {"GET": 0, "POST": 0, "PUT": 0, "DELETE": 0, "num_tasks": 0}
log_count = {"DEBUG": 0, "INFO": 0, "WARN": 0, "ERROR": 0}
# the following defaults will be adjusted by the app
config = {"log_level": "DEBUG", "prefix": ""}
def debug(msg):
if config["log_level"] == "DEBUG":
print(config["prefix"] + "DEBUG> " + msg)
log_count["DEBUG"] += 1
def info(msg):
if config["log_level"] not in ("ERROR", "WARNING", "WARN"):
print(config["prefix"] + "INFO> " + msg)
log_count["INFO"] += 1
def warn(msg):
if config.get("log_level") != "ERROR":
print(config["prefix"] + "WARN> " + msg)
log_count["WARN"] += 1
def warning(msg):
if config.get("log_level") != "ERROR":
print(config["prefix"] + "WARN> " + msg)
log_count["WARN"] += 1
def error(msg):
print(config["prefix"] + "ERROR> " + msg)
log_count["ERROR"] += 1
def request(req):
app = req.app
domain = getDomainFromRequest(req, validate=False)
if domain is None:
print("REQ> {}: {}".format(req.method, req.path))
else:
print("REQ> {}: {} [{}]".format(req.method, req.path, domain))
if req.path in ("/about", "/register", "/info", "/nodeinfo", "/nodestate", "/register"):
# always service these state requests regardles of node state and task load
return
node_state = app["node_state"] if "node_state" in app else None
if node_state != "READY":
warning(f"returning 503 - node_state: {node_state}")
raise HTTPServiceUnavailable()
if req.method in ("GET", "POST", "PUT", "DELETE"):
req_count[req.method] += 1
num_tasks = len(asyncio.Task.all_tasks())
active_tasks = len([task for task in asyncio.Task.all_tasks() if not task.done()])
req_count["num_tasks"] = num_tasks
if config["log_level"] == "DEBUG":
debug(f"num tasks: {num_tasks} active tasks: {active_tasks}")
max_task_count = app["max_task_count"]
if app["node_type"] == "sn" and max_task_count and active_tasks > max_task_count:
warning(f"more than {max_task_count} tasks, returning 503")
raise HTTPServiceUnavailable()
def response(req, resp=None, code=None, message=None):
level = "INFO"
if code is None:
# rsp needs to be set otherwise
code = resp.status
if message is None:
message=resp.reason
if code > 399:
if code < 500:
level = "WARN"
else:
level = "ERROR"
log_level = config["log_level"]
prefix = config["prefix"]
if log_level in ("DEBUG", "INFO") or (log_level == "WARN" and level != "INFO") or (log_level == "ERROR" and level == "ERROR"):
print("{}{} RSP> <{}> ({}): {}".format(prefix, level, code, message, req.path))
|
normal
|
{
"blob_id": "e15ea7d167aad470d0a2d95a8a328b35181e4dc3",
"index": 7832,
"step-1": "<mask token>\n\n\ndef info(msg):\n if config['log_level'] not in ('ERROR', 'WARNING', 'WARN'):\n print(config['prefix'] + 'INFO> ' + msg)\n log_count['INFO'] += 1\n\n\n<mask token>\n\n\ndef warning(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef info(msg):\n if config['log_level'] not in ('ERROR', 'WARNING', 'WARN'):\n print(config['prefix'] + 'INFO> ' + msg)\n log_count['INFO'] += 1\n\n\ndef warn(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\ndef warning(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\n<mask token>\n\n\ndef request(req):\n app = req.app\n domain = getDomainFromRequest(req, validate=False)\n if domain is None:\n print('REQ> {}: {}'.format(req.method, req.path))\n else:\n print('REQ> {}: {} [{}]'.format(req.method, req.path, domain))\n if req.path in ('/about', '/register', '/info', '/nodeinfo',\n '/nodestate', '/register'):\n return\n node_state = app['node_state'] if 'node_state' in app else None\n if node_state != 'READY':\n warning(f'returning 503 - node_state: {node_state}')\n raise HTTPServiceUnavailable()\n if req.method in ('GET', 'POST', 'PUT', 'DELETE'):\n req_count[req.method] += 1\n num_tasks = len(asyncio.Task.all_tasks())\n active_tasks = len([task for task in asyncio.Task.all_tasks() if not\n task.done()])\n req_count['num_tasks'] = num_tasks\n if config['log_level'] == 'DEBUG':\n debug(f'num tasks: {num_tasks} active tasks: {active_tasks}')\n max_task_count = app['max_task_count']\n if app['node_type'\n ] == 'sn' and max_task_count and active_tasks > max_task_count:\n warning(f'more than {max_task_count} tasks, returning 503')\n raise HTTPServiceUnavailable()\n\n\n<mask token>\n",
"step-3": "<mask token>\nreq_count = {'GET': 0, 'POST': 0, 'PUT': 0, 'DELETE': 0, 'num_tasks': 0}\nlog_count = {'DEBUG': 0, 'INFO': 0, 'WARN': 0, 'ERROR': 0}\nconfig = {'log_level': 'DEBUG', 'prefix': ''}\n\n\ndef debug(msg):\n if config['log_level'] == 'DEBUG':\n print(config['prefix'] + 'DEBUG> ' + msg)\n log_count['DEBUG'] += 1\n\n\ndef info(msg):\n if config['log_level'] not in ('ERROR', 'WARNING', 'WARN'):\n print(config['prefix'] + 'INFO> ' + msg)\n log_count['INFO'] += 1\n\n\ndef warn(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\ndef warning(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\ndef error(msg):\n print(config['prefix'] + 'ERROR> ' + msg)\n log_count['ERROR'] += 1\n\n\ndef request(req):\n app = req.app\n domain = getDomainFromRequest(req, validate=False)\n if domain is None:\n print('REQ> {}: {}'.format(req.method, req.path))\n else:\n print('REQ> {}: {} [{}]'.format(req.method, req.path, domain))\n if req.path in ('/about', '/register', '/info', '/nodeinfo',\n '/nodestate', '/register'):\n return\n node_state = app['node_state'] if 'node_state' in app else None\n if node_state != 'READY':\n warning(f'returning 503 - node_state: {node_state}')\n raise HTTPServiceUnavailable()\n if req.method in ('GET', 'POST', 'PUT', 'DELETE'):\n req_count[req.method] += 1\n num_tasks = len(asyncio.Task.all_tasks())\n active_tasks = len([task for task in asyncio.Task.all_tasks() if not\n task.done()])\n req_count['num_tasks'] = num_tasks\n if config['log_level'] == 'DEBUG':\n debug(f'num tasks: {num_tasks} active tasks: {active_tasks}')\n max_task_count = app['max_task_count']\n if app['node_type'\n ] == 'sn' and max_task_count and active_tasks > max_task_count:\n warning(f'more than {max_task_count} tasks, returning 503')\n raise HTTPServiceUnavailable()\n\n\ndef response(req, resp=None, code=None, message=None):\n level = 'INFO'\n if code is None:\n code = resp.status\n if message is None:\n message = resp.reason\n if code > 399:\n if code < 500:\n level = 'WARN'\n else:\n level = 'ERROR'\n log_level = config['log_level']\n prefix = config['prefix']\n if (log_level in ('DEBUG', 'INFO') or log_level == 'WARN' and level !=\n 'INFO' or log_level == 'ERROR' and level == 'ERROR'):\n print('{}{} RSP> <{}> ({}): {}'.format(prefix, level, code, message,\n req.path))\n",
"step-4": "import asyncio\nfrom aiohttp.web_exceptions import HTTPServiceUnavailable\nfrom .util.domainUtil import getDomainFromRequest\nreq_count = {'GET': 0, 'POST': 0, 'PUT': 0, 'DELETE': 0, 'num_tasks': 0}\nlog_count = {'DEBUG': 0, 'INFO': 0, 'WARN': 0, 'ERROR': 0}\nconfig = {'log_level': 'DEBUG', 'prefix': ''}\n\n\ndef debug(msg):\n if config['log_level'] == 'DEBUG':\n print(config['prefix'] + 'DEBUG> ' + msg)\n log_count['DEBUG'] += 1\n\n\ndef info(msg):\n if config['log_level'] not in ('ERROR', 'WARNING', 'WARN'):\n print(config['prefix'] + 'INFO> ' + msg)\n log_count['INFO'] += 1\n\n\ndef warn(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\ndef warning(msg):\n if config.get('log_level') != 'ERROR':\n print(config['prefix'] + 'WARN> ' + msg)\n log_count['WARN'] += 1\n\n\ndef error(msg):\n print(config['prefix'] + 'ERROR> ' + msg)\n log_count['ERROR'] += 1\n\n\ndef request(req):\n app = req.app\n domain = getDomainFromRequest(req, validate=False)\n if domain is None:\n print('REQ> {}: {}'.format(req.method, req.path))\n else:\n print('REQ> {}: {} [{}]'.format(req.method, req.path, domain))\n if req.path in ('/about', '/register', '/info', '/nodeinfo',\n '/nodestate', '/register'):\n return\n node_state = app['node_state'] if 'node_state' in app else None\n if node_state != 'READY':\n warning(f'returning 503 - node_state: {node_state}')\n raise HTTPServiceUnavailable()\n if req.method in ('GET', 'POST', 'PUT', 'DELETE'):\n req_count[req.method] += 1\n num_tasks = len(asyncio.Task.all_tasks())\n active_tasks = len([task for task in asyncio.Task.all_tasks() if not\n task.done()])\n req_count['num_tasks'] = num_tasks\n if config['log_level'] == 'DEBUG':\n debug(f'num tasks: {num_tasks} active tasks: {active_tasks}')\n max_task_count = app['max_task_count']\n if app['node_type'\n ] == 'sn' and max_task_count and active_tasks > max_task_count:\n warning(f'more than {max_task_count} tasks, returning 503')\n raise HTTPServiceUnavailable()\n\n\ndef response(req, resp=None, code=None, message=None):\n level = 'INFO'\n if code is None:\n code = resp.status\n if message is None:\n message = resp.reason\n if code > 399:\n if code < 500:\n level = 'WARN'\n else:\n level = 'ERROR'\n log_level = config['log_level']\n prefix = config['prefix']\n if (log_level in ('DEBUG', 'INFO') or log_level == 'WARN' and level !=\n 'INFO' or log_level == 'ERROR' and level == 'ERROR'):\n print('{}{} RSP> <{}> ({}): {}'.format(prefix, level, code, message,\n req.path))\n",
"step-5": "##############################################################################\n# Copyright by The HDF Group. #\n# All rights reserved. #\n# #\n# This file is part of HSDS (HDF5 Scalable Data Service), Libraries and #\n# Utilities. The full HSDS copyright notice, including #\n# terms governing use, modification, and redistribution, is contained in #\n# the file COPYING, which can be found at the root of the source code #\n# distribution tree. If you do not have access to this file, you may #\n# request a copy from [email protected]. #\n##############################################################################\n#\n# Simple looger for hsds\n#\nimport asyncio\nfrom aiohttp.web_exceptions import HTTPServiceUnavailable\nfrom .util.domainUtil import getDomainFromRequest\n\nreq_count = {\"GET\": 0, \"POST\": 0, \"PUT\": 0, \"DELETE\": 0, \"num_tasks\": 0}\nlog_count = {\"DEBUG\": 0, \"INFO\": 0, \"WARN\": 0, \"ERROR\": 0}\n# the following defaults will be adjusted by the app\nconfig = {\"log_level\": \"DEBUG\", \"prefix\": \"\"}\n\n\ndef debug(msg):\n\tif config[\"log_level\"] == \"DEBUG\":\n\t\tprint(config[\"prefix\"] + \"DEBUG> \" + msg)\n\t\tlog_count[\"DEBUG\"] += 1\n\ndef info(msg):\n\tif config[\"log_level\"] not in (\"ERROR\", \"WARNING\", \"WARN\"):\n\t\tprint(config[\"prefix\"] + \"INFO> \" + msg)\n\t\tlog_count[\"INFO\"] += 1\n\ndef warn(msg):\n\tif config.get(\"log_level\") != \"ERROR\":\n\t\tprint(config[\"prefix\"] + \"WARN> \" + msg)\n\t\tlog_count[\"WARN\"] += 1\n\ndef warning(msg):\n\tif config.get(\"log_level\") != \"ERROR\":\n\t\tprint(config[\"prefix\"] + \"WARN> \" + msg)\n\t\tlog_count[\"WARN\"] += 1\n\ndef error(msg):\n\tprint(config[\"prefix\"] + \"ERROR> \" + msg)\n\tlog_count[\"ERROR\"] += 1\n\ndef request(req):\n\tapp = req.app\n\tdomain = getDomainFromRequest(req, validate=False)\n\tif domain is None:\n\t\tprint(\"REQ> {}: {}\".format(req.method, req.path))\n\telse:\n\t\tprint(\"REQ> {}: {} [{}]\".format(req.method, req.path, domain))\n\tif req.path in (\"/about\", \"/register\", \"/info\", \"/nodeinfo\", \"/nodestate\", \"/register\"):\n\t\t# always service these state requests regardles of node state and task load\n\t\treturn\n\tnode_state = app[\"node_state\"] if \"node_state\" in app else None\n\tif node_state != \"READY\":\n\t\twarning(f\"returning 503 - node_state: {node_state}\")\n\t\traise HTTPServiceUnavailable()\n\tif req.method in (\"GET\", \"POST\", \"PUT\", \"DELETE\"):\n\t\treq_count[req.method] += 1\n\tnum_tasks = len(asyncio.Task.all_tasks())\n\tactive_tasks = len([task for task in asyncio.Task.all_tasks() if not task.done()])\n\treq_count[\"num_tasks\"] = num_tasks\n\tif config[\"log_level\"] == \"DEBUG\":\n\t\tdebug(f\"num tasks: {num_tasks} active tasks: {active_tasks}\")\n\n\tmax_task_count = app[\"max_task_count\"]\n\tif app[\"node_type\"] == \"sn\" and max_task_count and active_tasks > max_task_count:\n\t\twarning(f\"more than {max_task_count} tasks, returning 503\")\n\t\traise HTTPServiceUnavailable()\n\n\ndef response(req, resp=None, code=None, message=None):\n\tlevel = \"INFO\"\n\tif code is None:\n\t\t# rsp needs to be set otherwise\n\t\tcode = resp.status\n\tif message is None:\n\t\tmessage=resp.reason\n\tif code > 399:\n\t\tif code < 500:\n\t\t\tlevel = \"WARN\"\n\t\telse:\n\t\t\tlevel = \"ERROR\"\n\n\tlog_level = config[\"log_level\"]\n\tprefix = config[\"prefix\"]\n\tif log_level in (\"DEBUG\", \"INFO\") or (log_level == \"WARN\" and level != \"INFO\") or (log_level == \"ERROR\" and level == \"ERROR\"):\n\t\tprint(\"{}{} RSP> <{}> ({}): {}\".format(prefix, level, code, message, req.path))\n",
"step-ids": [
2,
4,
8,
9,
10
]
}
|
[
2,
4,
8,
9,
10
] |
# 예시 입력값
board = [[0,0,0,0,0],[0,0,1,0,3],[0,2,5,0,1],[4,2,4,4,2],[3,5,1,3,1]]
moves = [1,5,3,5,1,2,1,4]
# 로직
resultList = []
count = 0
for nth in moves:
for i in range(len(board)):
selected = board[i][nth - 1]
if selected == 0:
continue
else:
# 인형을 resultList에 넣고
resultList.append(selected)
# resultList를 탐색하여 같은 인형이 있는지 보기
lenR = len(resultList)
if lenR > 1:
if resultList[lenR - 2] == resultList[lenR - 1]:
del resultList[lenR - 2:]
count += 2
# 뽑힌 인형은 board에서 사라짐
board[i][nth - 1] = 0
break
# print(resultList)
print(count)
|
normal
|
{
"blob_id": "18e032b7ff7ae9d3f5fecc86f63d12f4da7b8067",
"index": 6180,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor nth in moves:\n for i in range(len(board)):\n selected = board[i][nth - 1]\n if selected == 0:\n continue\n else:\n resultList.append(selected)\n lenR = len(resultList)\n if lenR > 1:\n if resultList[lenR - 2] == resultList[lenR - 1]:\n del resultList[lenR - 2:]\n count += 2\n board[i][nth - 1] = 0\n break\nprint(count)\n",
"step-3": "board = [[0, 0, 0, 0, 0], [0, 0, 1, 0, 3], [0, 2, 5, 0, 1], [4, 2, 4, 4, 2],\n [3, 5, 1, 3, 1]]\nmoves = [1, 5, 3, 5, 1, 2, 1, 4]\nresultList = []\ncount = 0\nfor nth in moves:\n for i in range(len(board)):\n selected = board[i][nth - 1]\n if selected == 0:\n continue\n else:\n resultList.append(selected)\n lenR = len(resultList)\n if lenR > 1:\n if resultList[lenR - 2] == resultList[lenR - 1]:\n del resultList[lenR - 2:]\n count += 2\n board[i][nth - 1] = 0\n break\nprint(count)\n",
"step-4": "# 예시 입력값\nboard = [[0,0,0,0,0],[0,0,1,0,3],[0,2,5,0,1],[4,2,4,4,2],[3,5,1,3,1]]\nmoves = [1,5,3,5,1,2,1,4]\n\n# 로직\nresultList = []\ncount = 0\n\nfor nth in moves:\n for i in range(len(board)):\n selected = board[i][nth - 1]\n if selected == 0:\n continue\n else:\n # 인형을 resultList에 넣고\n resultList.append(selected)\n # resultList를 탐색하여 같은 인형이 있는지 보기\n lenR = len(resultList)\n if lenR > 1:\n if resultList[lenR - 2] == resultList[lenR - 1]:\n del resultList[lenR - 2:]\n count += 2\n\n # 뽑힌 인형은 board에서 사라짐\n board[i][nth - 1] = 0\n break\n\n# print(resultList)\nprint(count)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
"""
# System of national accounts (SNA)
This is an end-to-end example of national accounts sequence,
from output to net lending. It is based on Russian Federation data
for 2014-2018.
Below is a python session transcript with comments.
You can fork [a github repo](https://github.com/epogrebnyak/sna-ru)
to replicate calculations.
"""
"""
## Chart
A short mnemonic chart to accompaign the calculations:
```
[controlling for factor income and transfers]
| |
V V
X -> GDP -> GNI -> GNDI = C + S (+ net capital transfers)
| |
Ch + I + Cg + NX S = I + Net lending
|
W + t' + P Always a mystery:
| S - I = NX = Net lending
X - AX (See Open Economy identitites below)
```
"""
"""
## Preparations
"""
import pandas as pd
import handout
doc = handout.Handout("handout") # handout: exclude
"""
`eq` function will check identities considering some rounding error.
"""
def eq(df1, df2, precision=0.5) -> bool:
"""Compare two dataframes by element with precision margin."""
return ((df1 - df2).abs() < precision).all()
"""
Read dataset from file.
"""
df = pd.read_csv("data/sna.csv", index_col=0)
"""
## 1. Output at market prices
Output at market prices is output at basic prices
plus tax on products less subsidy on products.
"""
df["X"] = df.Xb + df.Tp - df.Sp
"""
## 2. Production of goods and services account
Output and import are resources,
consumption, investment (I) and export are uses.
Consumption is intermediate (AX) and final (C).
"""
resources = df.X + df.IM
uses = df.AX + df.C + df.I + df.EX
doc.add_image("res_use.png", "png", width=1) # handout: exclude
doc.show() # handout: exclude
"""
Resources and uses are equal, controlling for
[statistical discrepancy](https://www.stat.fi/meta/kas/tilastollinen_e_en.html).
"""
assert eq(resources, uses + df.desc)
"""
## 3. Gross domestic product (GDP)
There are three ways to calculate a GDP.
With some luck they yield to similar values.
"""
gdp1 = df.X - df.AX
gdp2 = (df.C + df.I - df.IM) + df.EX + df.desc
gdp3 = df.W + df.Tf - df.Sf + df.GP
assert eq(gdp1, gdp2)
assert eq(gdp2, df.GDP)
assert eq(gdp3, df.GDP)
"""```
>> gdp1.divide(10**6).round(1)
2014 79.1
2015 83.1
2016 86.0
2017 92.1
2018 103.9
```"""
"""
## 4. Controlling for income and current transfers from abroad
Gross national income (GNI) is GDP and
net property and labor ("factor") income
form rest of the world (ROW).
"""
gni = (
df.GDP
+ df.ROW_property_income_recieved
- df.ROW_property_income_paid
+ df.ROW_wage_net
)
assert eq(gni.iloc[1:,], df.GNI.iloc[1:,])
"""
Gross national disposable income (GNDI)
is GNI and net current transfers from abroad
"""
gndi = gni + df.CT_recieved - df.CT_paid
assert eq(gndi, df.GNDI)
"""
## 5. Savings
Savings is gross domestic income
less household and government consumption.
"""
S = gndi - (df.HH + df.G)
assert eq(df.C, df.HH + df.G)
assert eq(S, df.S)
"""
Investment is gross fixed capital formation
and change in inventories.
"""
I = df.GFCF + df.inv
assert eq(I, df.I)
"""
## 6. Net lending
Net lending is S-I, and a balance of capital transfers
and a non-produced non-material asset aquisition (K.2).
"""
NL = S + df.d9_recieved - df.d9_paid - I - df.k2
assert eq(NL, df.NL0)
"""
Net lending is an entry value into financial account (flow of funds).
Is usually contains a statistical error, later netted in flow of funds.
"""
"""
## Links
- [SNA 2008 manual](https://unstats.un.org/unsd/nationalaccount/docs/SNA2008.pdf)
- [Russian national accounts data](https://www.gks.ru/folder/210/document/13221)
- [Open economy identitites](https://github.com/hisamsabouni/macroLectures/blob/master/lecture_6.pdf)
"""
doc.show() # handout: exclude
|
normal
|
{
"blob_id": "2d4187ab5d178efa4920110ccef61c608fdb14c0",
"index": 8780,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef eq(df1, df2, precision=0.5) ->bool:\n \"\"\"Compare two dataframes by element with precision margin.\"\"\"\n return ((df1 - df2).abs() < precision).all()\n\n\n<mask token>\ndoc.add_image('res_use.png', 'png', width=1)\ndoc.show()\n<mask token>\nassert eq(resources, uses + df.desc)\n<mask token>\nassert eq(gdp1, gdp2)\nassert eq(gdp2, df.GDP)\nassert eq(gdp3, df.GDP)\n<mask token>\nassert eq(gni.iloc[1:,], df.GNI.iloc[1:,])\n<mask token>\nassert eq(gndi, df.GNDI)\n<mask token>\nassert eq(df.C, df.HH + df.G)\nassert eq(S, df.S)\n<mask token>\nassert eq(I, df.I)\n<mask token>\nassert eq(NL, df.NL0)\n<mask token>\ndoc.show()\n",
"step-3": "<mask token>\ndoc = handout.Handout('handout')\n<mask token>\n\n\ndef eq(df1, df2, precision=0.5) ->bool:\n \"\"\"Compare two dataframes by element with precision margin.\"\"\"\n return ((df1 - df2).abs() < precision).all()\n\n\n<mask token>\ndf = pd.read_csv('data/sna.csv', index_col=0)\n<mask token>\ndf['X'] = df.Xb + df.Tp - df.Sp\n<mask token>\nresources = df.X + df.IM\nuses = df.AX + df.C + df.I + df.EX\ndoc.add_image('res_use.png', 'png', width=1)\ndoc.show()\n<mask token>\nassert eq(resources, uses + df.desc)\n<mask token>\ngdp1 = df.X - df.AX\ngdp2 = df.C + df.I - df.IM + df.EX + df.desc\ngdp3 = df.W + df.Tf - df.Sf + df.GP\nassert eq(gdp1, gdp2)\nassert eq(gdp2, df.GDP)\nassert eq(gdp3, df.GDP)\n<mask token>\ngni = (df.GDP + df.ROW_property_income_recieved - df.\n ROW_property_income_paid + df.ROW_wage_net)\nassert eq(gni.iloc[1:,], df.GNI.iloc[1:,])\n<mask token>\ngndi = gni + df.CT_recieved - df.CT_paid\nassert eq(gndi, df.GNDI)\n<mask token>\nS = gndi - (df.HH + df.G)\nassert eq(df.C, df.HH + df.G)\nassert eq(S, df.S)\n<mask token>\nI = df.GFCF + df.inv\nassert eq(I, df.I)\n<mask token>\nNL = S + df.d9_recieved - df.d9_paid - I - df.k2\nassert eq(NL, df.NL0)\n<mask token>\ndoc.show()\n",
"step-4": "<mask token>\nimport pandas as pd\nimport handout\ndoc = handout.Handout('handout')\n<mask token>\n\n\ndef eq(df1, df2, precision=0.5) ->bool:\n \"\"\"Compare two dataframes by element with precision margin.\"\"\"\n return ((df1 - df2).abs() < precision).all()\n\n\n<mask token>\ndf = pd.read_csv('data/sna.csv', index_col=0)\n<mask token>\ndf['X'] = df.Xb + df.Tp - df.Sp\n<mask token>\nresources = df.X + df.IM\nuses = df.AX + df.C + df.I + df.EX\ndoc.add_image('res_use.png', 'png', width=1)\ndoc.show()\n<mask token>\nassert eq(resources, uses + df.desc)\n<mask token>\ngdp1 = df.X - df.AX\ngdp2 = df.C + df.I - df.IM + df.EX + df.desc\ngdp3 = df.W + df.Tf - df.Sf + df.GP\nassert eq(gdp1, gdp2)\nassert eq(gdp2, df.GDP)\nassert eq(gdp3, df.GDP)\n<mask token>\ngni = (df.GDP + df.ROW_property_income_recieved - df.\n ROW_property_income_paid + df.ROW_wage_net)\nassert eq(gni.iloc[1:,], df.GNI.iloc[1:,])\n<mask token>\ngndi = gni + df.CT_recieved - df.CT_paid\nassert eq(gndi, df.GNDI)\n<mask token>\nS = gndi - (df.HH + df.G)\nassert eq(df.C, df.HH + df.G)\nassert eq(S, df.S)\n<mask token>\nI = df.GFCF + df.inv\nassert eq(I, df.I)\n<mask token>\nNL = S + df.d9_recieved - df.d9_paid - I - df.k2\nassert eq(NL, df.NL0)\n<mask token>\ndoc.show()\n",
"step-5": "\"\"\"\n# System of national accounts (SNA)\n\nThis is an end-to-end example of national accounts sequence, \nfrom output to net lending. It is based on Russian Federation data \nfor 2014-2018. \n\nBelow is a python session transcript with comments. \nYou can fork [a github repo](https://github.com/epogrebnyak/sna-ru) \nto replicate calculations.\n\"\"\"\n\n\"\"\"\n## Chart \n\nA short mnemonic chart to accompaign the calculations:\n \n```\n [controlling for factor income and transfers] \n | |\n V V\nX -> GDP -> GNI -> GNDI = C + S (+ net capital transfers)\n | | \n Ch + I + Cg + NX S = I + Net lending \n |\n W + t' + P Always a mystery:\n | S - I = NX = Net lending \n X - AX (See Open Economy identitites below) \n\n```\n\"\"\"\n\n\"\"\"\n## Preparations\n\"\"\"\n\nimport pandas as pd\nimport handout\n\ndoc = handout.Handout(\"handout\") # handout: exclude\n\n\"\"\"\n`eq` function will check identities considering some rounding error.\n\"\"\"\n\n\ndef eq(df1, df2, precision=0.5) -> bool:\n \"\"\"Compare two dataframes by element with precision margin.\"\"\"\n return ((df1 - df2).abs() < precision).all()\n\n\n\"\"\"\nRead dataset from file. \n\"\"\"\n\ndf = pd.read_csv(\"data/sna.csv\", index_col=0)\n\n\"\"\"\n## 1. Output at market prices\n\nOutput at market prices is output at basic prices \nplus tax on products less subsidy on products.\n\"\"\"\n\ndf[\"X\"] = df.Xb + df.Tp - df.Sp\n\n\n\"\"\"\n## 2. Production of goods and services account\n\nOutput and import are resources,\nconsumption, investment (I) and export are uses.\nConsumption is intermediate (AX) and final (C).\n\"\"\"\n\nresources = df.X + df.IM\nuses = df.AX + df.C + df.I + df.EX\n\ndoc.add_image(\"res_use.png\", \"png\", width=1) # handout: exclude\ndoc.show() # handout: exclude\n\n\"\"\"\nResources and uses are equal, controlling for \n[statistical discrepancy](https://www.stat.fi/meta/kas/tilastollinen_e_en.html).\n\"\"\"\nassert eq(resources, uses + df.desc)\n\n\n\"\"\"\n## 3. Gross domestic product (GDP)\n\nThere are three ways to calculate a GDP. \n\nWith some luck they yield to similar values.\n\n\"\"\"\n\ngdp1 = df.X - df.AX\ngdp2 = (df.C + df.I - df.IM) + df.EX + df.desc\ngdp3 = df.W + df.Tf - df.Sf + df.GP\n\nassert eq(gdp1, gdp2)\nassert eq(gdp2, df.GDP)\nassert eq(gdp3, df.GDP)\n\n\"\"\"```\n>> gdp1.divide(10**6).round(1)\n\n2014 79.1\n2015 83.1\n2016 86.0\n2017 92.1\n2018 103.9\n\n```\"\"\"\n\n\n\"\"\"\n## 4. Controlling for income and current transfers from abroad\n\nGross national income (GNI) is GDP and \nnet property and labor (\"factor\") income \nform rest of the world (ROW).\n\"\"\"\n\n\ngni = (\n df.GDP\n + df.ROW_property_income_recieved\n - df.ROW_property_income_paid\n + df.ROW_wage_net\n)\nassert eq(gni.iloc[1:,], df.GNI.iloc[1:,])\n\n\"\"\"\n\nGross national disposable income (GNDI) \nis GNI and net current transfers from abroad\n\"\"\"\n\ngndi = gni + df.CT_recieved - df.CT_paid\nassert eq(gndi, df.GNDI)\n\n\"\"\"\n## 5. Savings\n\nSavings is gross domestic income \nless household and government consumption. \n\"\"\"\n\nS = gndi - (df.HH + df.G)\nassert eq(df.C, df.HH + df.G)\nassert eq(S, df.S)\n\n\"\"\"\nInvestment is gross fixed capital formation \nand change in inventories.\n\"\"\"\n\nI = df.GFCF + df.inv\nassert eq(I, df.I)\n\n\"\"\"\n## 6. Net lending\n\nNet lending is S-I, and a balance of capital transfers\nand a non-produced non-material asset aquisition (K.2).\n\"\"\"\n\nNL = S + df.d9_recieved - df.d9_paid - I - df.k2\nassert eq(NL, df.NL0)\n\n\"\"\"\nNet lending is an entry value into financial account (flow of funds).\nIs usually contains a statistical error, later netted in flow of funds.\n\"\"\"\n\n\n\"\"\"\n## Links\n\n- [SNA 2008 manual](https://unstats.un.org/unsd/nationalaccount/docs/SNA2008.pdf)\n- [Russian national accounts data](https://www.gks.ru/folder/210/document/13221)\n- [Open economy identitites](https://github.com/hisamsabouni/macroLectures/blob/master/lecture_6.pdf)\n\"\"\"\n\ndoc.show() # handout: exclude\n",
"step-ids": [
0,
2,
3,
4,
5
]
}
|
[
0,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.4 on 2017-10-02 14:41
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
class Migration(migrations.Migration):
dependencies = [
('barriers', '0011_auto_20170904_1658'),
]
operations = [
migrations.CreateModel(
name='BarrierCountry',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('name', models.CharField(max_length=100, verbose_name='Country or Territory Name')),
('code', models.CharField(blank=True, max_length=100, null=True, verbose_name='Country or Territory Code')),
('official_name', models.CharField(blank=True, max_length=100, null=True, verbose_name='Offical Country or Territory name')),
('govuk_index_entry_code', models.CharField(blank=True, max_length=10, null=True, verbose_name='GOV.UK index code')),
('country_or_territory', models.CharField(choices=[('CO', 'Country'), ('TE', 'Territory')], default='CO', max_length=2, verbose_name='Country or Territory flag')),
],
options={
'verbose_name_plural': 'countries or territories',
},
),
migrations.CreateModel(
name='BarrierNotification',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('title', models.TextField(blank=True, verbose_name='Title')),
('description', models.TextField(blank=True, verbose_name='Description')),
('distribution_date', models.DateField(blank=True, null=True, verbose_name='Distribution Date')),
('barrier_symbol', models.CharField(blank=True, max_length=500, verbose_name='Barrier Symbol')),
('core_symbol', models.CharField(blank=True, max_length=500, verbose_name='Core Symbol')),
('mab_type', models.CharField(blank=True, max_length=500, verbose_name='Barrier type')),
('products_text', models.TextField(blank=True, verbose_name='Products')),
('product_codes', models.TextField(blank=True, verbose_name='Product codes')),
('objectives', models.TextField(blank=True, verbose_name='Objectives')),
('keywords', models.TextField(blank=True, verbose_name='Keywords')),
('regions_affected', models.TextField(blank=True, verbose_name='Regions affected')),
('comments_due_date', models.DateField(blank=True, null=True, verbose_name='Final date for comments')),
('notification_type', models.CharField(blank=True, max_length=50, verbose_name='Notification type')),
('document_link', models.CharField(blank=True, max_length=1500, verbose_name='Document link')),
('external_link', models.CharField(blank=True, max_length=1500, verbose_name='External site link')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='BarrierRecord',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('status', models.CharField(blank=True, choices=[('Active', 'Active')], default=None, max_length=10, null=True)),
('title', models.TextField(blank=True, verbose_name='Title')),
('description', models.TextField(blank=True, verbose_name='Description')),
('products_text', models.TextField(blank=True, verbose_name='Products affected')),
('sectors_text', models.TextField(blank=True, verbose_name='Sectors affected')),
('source_id', models.CharField(blank=True, max_length=20, null=True, verbose_name='ID in source system')),
('distribution_date', models.DateField(blank=True, null=True, verbose_name='Distribution Date')),
('external_link', models.CharField(blank=True, max_length=1500, verbose_name='External site link')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='BarrierReport',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('status', models.CharField(blank=True, choices=[('Draft', 'Draft'), ('Submitted', 'Submitted')], default=None, max_length=10, null=True)),
('name', models.CharField(blank=True, max_length=200, null=True)),
('problem_description', models.TextField(blank=True, null=True)),
('product_text', models.TextField(blank=True, null=True)),
('product_code', models.CharField(blank=True, max_length=500, null=True)),
('business_impact_description', models.TextField(blank=True, null=True)),
('problem_duration_description', models.TextField(blank=True, null=True)),
('other_companies_affected_choice', models.CharField(blank=True, choices=[('Yes', 'Yes'), ('No', 'No'), ('DontKnow', "Don't know")], default=None, max_length=10, null=True)),
('other_countries_affected_description', models.TextField(blank=True, null=True)),
('steps_taken_to_resolve', models.TextField(blank=True, null=True)),
('outcome_looking_for', models.TextField(blank=True, null=True)),
('support_desired_choice', models.CharField(blank=True, choices=[('SUPPORT_DESIRED_NONE', 'None - this is for your information only'), ('SUPPORT_DESIRED_LOCAL', 'Local engagement only with UK Government officials in the country I am trying to export to'), ('SUPPORT_DESIRED_BROAD', 'Broader UK Government involvement'), ('SUPPORT_DESIRED_NOT_SURE', 'Not sure')], default=None, max_length=10, null=True)),
('confidentiality_issues_description', models.TextField(blank=True, null=True)),
('happy_to_publish_choice', models.CharField(blank=True, choices=[('HAPPY_TO_PUBLISH_YES', 'Yes'), ('HAPPY_TO_PUBLISH_NO', 'No'), ('HAPPY_TO_PUBLISH_MAYBE', 'Maybe, following consultation with me')], default=None, max_length=10, null=True)),
('any_other_details_description', models.TextField(blank=True, null=True)),
('country', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierCountry')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='BarrierReporter',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('name', models.CharField(blank=True, max_length=1500, verbose_name='Reporter name')),
('company', models.CharField(blank=True, max_length=1500, verbose_name='Company name')),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='BarrierSource',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('name', models.CharField(max_length=100)),
('description', models.CharField(blank=True, max_length=500, null=True)),
('short_name', models.CharField(blank=True, max_length=20, null=True)),
('remote_url', models.URLField(blank=True, max_length=20, null=True)),
],
options={
'abstract': False,
},
),
migrations.CreateModel(
name='BarrierTypeMapping',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_date', models.DateTimeField(auto_now_add=True)),
('updated_date', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('destination_barrier_list', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='destination_barrier_list', to='barriers.BarrierSource')),
],
options={
'abstract': False,
},
),
migrations.RemoveField(
model_name='marketaccessbarrier',
name='barrier_types',
),
migrations.RenameField(
model_name='barriertype',
old_name='ec_barrier_code',
new_name='barrier_code',
),
migrations.AlterField(
model_name='barriertype',
name='name',
field=models.CharField(max_length=200),
),
migrations.DeleteModel(
name='MarketAccessBarrier',
),
migrations.AddField(
model_name='barriertypemapping',
name='destination_barrier_type',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='destination_barrier_type', to='barriers.BarrierType'),
),
migrations.AddField(
model_name='barriertypemapping',
name='source_barrier_list',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='source_barrier_list', to='barriers.BarrierSource'),
),
migrations.AddField(
model_name='barriertypemapping',
name='source_barrier_type',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='source_barrier_type', to='barriers.BarrierType'),
),
migrations.AddField(
model_name='barrierreport',
name='reporter',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierReporter'),
),
migrations.AddField(
model_name='barrierreport',
name='top_level_barrier_type',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='barrier_reports', to='barriers.BarrierType'),
),
migrations.AddField(
model_name='barrierrecord',
name='barrier_source',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),
),
migrations.AddField(
model_name='barrierrecord',
name='barrier_types',
field=mptt.fields.TreeManyToManyField(blank=True, db_index=True, related_name='types', to='barriers.BarrierType'),
),
migrations.AddField(
model_name='barrierrecord',
name='country',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierCountry'),
),
migrations.AddField(
model_name='barriernotification',
name='barrier_source',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),
),
migrations.AddField(
model_name='barriernotification',
name='barrier_types',
field=mptt.fields.TreeManyToManyField(blank=True, db_index=True, related_name='barrier_types', to='barriers.BarrierType'),
),
migrations.AddField(
model_name='barriernotification',
name='country',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='notification_countries', to='barriers.BarrierCountry'),
),
migrations.AddField(
model_name='barriertype',
name='barrier_source',
field=models.ForeignKey(default=1, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),
),
]
|
normal
|
{
"blob_id": "645f8f1ebd3bfa0ba32d5be8058b07e2a30ba9b5",
"index": 1314,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('barriers', '0011_auto_20170904_1658')]\n operations = [migrations.CreateModel(name='BarrierCountry', fields=[(\n 'id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('created_date', models.\n DateTimeField(auto_now_add=True)), ('updated_date', models.\n DateTimeField(auto_now=True)), ('is_deleted', models.BooleanField(\n default=False)), ('name', models.CharField(max_length=100,\n verbose_name='Country or Territory Name')), ('code', models.\n CharField(blank=True, max_length=100, null=True, verbose_name=\n 'Country or Territory Code')), ('official_name', models.CharField(\n blank=True, max_length=100, null=True, verbose_name=\n 'Offical Country or Territory name')), ('govuk_index_entry_code',\n models.CharField(blank=True, max_length=10, null=True, verbose_name\n ='GOV.UK index code')), ('country_or_territory', models.CharField(\n choices=[('CO', 'Country'), ('TE', 'Territory')], default='CO',\n max_length=2, verbose_name='Country or Territory flag'))], options=\n {'verbose_name_plural': 'countries or territories'}), migrations.\n CreateModel(name='BarrierNotification', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'title', models.TextField(blank=True, verbose_name='Title')), (\n 'description', models.TextField(blank=True, verbose_name=\n 'Description')), ('distribution_date', models.DateField(blank=True,\n null=True, verbose_name='Distribution Date')), ('barrier_symbol',\n models.CharField(blank=True, max_length=500, verbose_name=\n 'Barrier Symbol')), ('core_symbol', models.CharField(blank=True,\n max_length=500, verbose_name='Core Symbol')), ('mab_type', models.\n CharField(blank=True, max_length=500, verbose_name='Barrier type')),\n ('products_text', models.TextField(blank=True, verbose_name=\n 'Products')), ('product_codes', models.TextField(blank=True,\n verbose_name='Product codes')), ('objectives', models.TextField(\n blank=True, verbose_name='Objectives')), ('keywords', models.\n TextField(blank=True, verbose_name='Keywords')), (\n 'regions_affected', models.TextField(blank=True, verbose_name=\n 'Regions affected')), ('comments_due_date', models.DateField(blank=\n True, null=True, verbose_name='Final date for comments')), (\n 'notification_type', models.CharField(blank=True, max_length=50,\n verbose_name='Notification type')), ('document_link', models.\n CharField(blank=True, max_length=1500, verbose_name='Document link'\n )), ('external_link', models.CharField(blank=True, max_length=1500,\n verbose_name='External site link'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierRecord', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'status', models.CharField(blank=True, choices=[('Active', 'Active'\n )], default=None, max_length=10, null=True)), ('title', models.\n TextField(blank=True, verbose_name='Title')), ('description',\n models.TextField(blank=True, verbose_name='Description')), (\n 'products_text', models.TextField(blank=True, verbose_name=\n 'Products affected')), ('sectors_text', models.TextField(blank=True,\n verbose_name='Sectors affected')), ('source_id', models.CharField(\n blank=True, max_length=20, null=True, verbose_name=\n 'ID in source system')), ('distribution_date', models.DateField(\n blank=True, null=True, verbose_name='Distribution Date')), (\n 'external_link', models.CharField(blank=True, max_length=1500,\n verbose_name='External site link'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierReport', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'status', models.CharField(blank=True, choices=[('Draft', 'Draft'),\n ('Submitted', 'Submitted')], default=None, max_length=10, null=True\n )), ('name', models.CharField(blank=True, max_length=200, null=True\n )), ('problem_description', models.TextField(blank=True, null=True)\n ), ('product_text', models.TextField(blank=True, null=True)), (\n 'product_code', models.CharField(blank=True, max_length=500, null=\n True)), ('business_impact_description', models.TextField(blank=True,\n null=True)), ('problem_duration_description', models.TextField(\n blank=True, null=True)), ('other_companies_affected_choice', models\n .CharField(blank=True, choices=[('Yes', 'Yes'), ('No', 'No'), (\n 'DontKnow', \"Don't know\")], default=None, max_length=10, null=True)\n ), ('other_countries_affected_description', models.TextField(blank=\n True, null=True)), ('steps_taken_to_resolve', models.TextField(\n blank=True, null=True)), ('outcome_looking_for', models.TextField(\n blank=True, null=True)), ('support_desired_choice', models.\n CharField(blank=True, choices=[('SUPPORT_DESIRED_NONE',\n 'None - this is for your information only'), (\n 'SUPPORT_DESIRED_LOCAL',\n 'Local engagement only with UK Government officials in the country I am trying to export to'\n ), ('SUPPORT_DESIRED_BROAD', 'Broader UK Government involvement'),\n ('SUPPORT_DESIRED_NOT_SURE', 'Not sure')], default=None, max_length\n =10, null=True)), ('confidentiality_issues_description', models.\n TextField(blank=True, null=True)), ('happy_to_publish_choice',\n models.CharField(blank=True, choices=[('HAPPY_TO_PUBLISH_YES',\n 'Yes'), ('HAPPY_TO_PUBLISH_NO', 'No'), ('HAPPY_TO_PUBLISH_MAYBE',\n 'Maybe, following consultation with me')], default=None, max_length\n =10, null=True)), ('any_other_details_description', models.\n TextField(blank=True, null=True)), ('country', models.ForeignKey(\n blank=True, null=True, on_delete=django.db.models.deletion.CASCADE,\n to='barriers.BarrierCountry'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierReporter', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'name', models.CharField(blank=True, max_length=1500, verbose_name=\n 'Reporter name')), ('company', models.CharField(blank=True,\n max_length=1500, verbose_name='Company name'))], options={\n 'abstract': False}), migrations.CreateModel(name='BarrierSource',\n fields=[('id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('created_date', models.\n DateTimeField(auto_now_add=True)), ('updated_date', models.\n DateTimeField(auto_now=True)), ('is_deleted', models.BooleanField(\n default=False)), ('name', models.CharField(max_length=100)), (\n 'description', models.CharField(blank=True, max_length=500, null=\n True)), ('short_name', models.CharField(blank=True, max_length=20,\n null=True)), ('remote_url', models.URLField(blank=True, max_length=\n 20, null=True))], options={'abstract': False}), migrations.\n CreateModel(name='BarrierTypeMapping', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'destination_barrier_list', models.ForeignKey(on_delete=django.db.\n models.deletion.CASCADE, related_name='destination_barrier_list',\n to='barriers.BarrierSource'))], options={'abstract': False}),\n migrations.RemoveField(model_name='marketaccessbarrier', name=\n 'barrier_types'), migrations.RenameField(model_name='barriertype',\n old_name='ec_barrier_code', new_name='barrier_code'), migrations.\n AlterField(model_name='barriertype', name='name', field=models.\n CharField(max_length=200)), migrations.DeleteModel(name=\n 'MarketAccessBarrier'), migrations.AddField(model_name=\n 'barriertypemapping', name='destination_barrier_type', field=models\n .ForeignKey(on_delete=django.db.models.deletion.CASCADE,\n related_name='destination_barrier_type', to='barriers.BarrierType')\n ), migrations.AddField(model_name='barriertypemapping', name=\n 'source_barrier_list', field=models.ForeignKey(on_delete=django.db.\n models.deletion.CASCADE, related_name='source_barrier_list', to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barriertypemapping', name='source_barrier_type', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE,\n related_name='source_barrier_type', to='barriers.BarrierType')),\n migrations.AddField(model_name='barrierreport', name='reporter',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.\n models.deletion.CASCADE, to='barriers.BarrierReporter')),\n migrations.AddField(model_name='barrierreport', name=\n 'top_level_barrier_type', field=models.ForeignKey(blank=True, null=\n True, on_delete=django.db.models.deletion.CASCADE, related_name=\n 'barrier_reports', to='barriers.BarrierType')), migrations.AddField\n (model_name='barrierrecord', name='barrier_source', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barrierrecord', name='barrier_types', field=mptt.fields.\n TreeManyToManyField(blank=True, db_index=True, related_name='types',\n to='barriers.BarrierType')), migrations.AddField(model_name=\n 'barrierrecord', name='country', field=models.ForeignKey(blank=True,\n null=True, on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierCountry')), migrations.AddField(model_name=\n 'barriernotification', name='barrier_source', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barriernotification', name='barrier_types', field=mptt.fields.\n TreeManyToManyField(blank=True, db_index=True, related_name=\n 'barrier_types', to='barriers.BarrierType')), migrations.AddField(\n model_name='barriernotification', name='country', field=models.\n ForeignKey(blank=True, null=True, on_delete=django.db.models.\n deletion.CASCADE, related_name='notification_countries', to=\n 'barriers.BarrierCountry')), migrations.AddField(model_name=\n 'barriertype', name='barrier_source', field=models.ForeignKey(\n default=1, on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource'))]\n",
"step-4": "from __future__ import unicode_literals\nfrom django.db import migrations, models\nimport django.db.models.deletion\nimport mptt.fields\n\n\nclass Migration(migrations.Migration):\n dependencies = [('barriers', '0011_auto_20170904_1658')]\n operations = [migrations.CreateModel(name='BarrierCountry', fields=[(\n 'id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('created_date', models.\n DateTimeField(auto_now_add=True)), ('updated_date', models.\n DateTimeField(auto_now=True)), ('is_deleted', models.BooleanField(\n default=False)), ('name', models.CharField(max_length=100,\n verbose_name='Country or Territory Name')), ('code', models.\n CharField(blank=True, max_length=100, null=True, verbose_name=\n 'Country or Territory Code')), ('official_name', models.CharField(\n blank=True, max_length=100, null=True, verbose_name=\n 'Offical Country or Territory name')), ('govuk_index_entry_code',\n models.CharField(blank=True, max_length=10, null=True, verbose_name\n ='GOV.UK index code')), ('country_or_territory', models.CharField(\n choices=[('CO', 'Country'), ('TE', 'Territory')], default='CO',\n max_length=2, verbose_name='Country or Territory flag'))], options=\n {'verbose_name_plural': 'countries or territories'}), migrations.\n CreateModel(name='BarrierNotification', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'title', models.TextField(blank=True, verbose_name='Title')), (\n 'description', models.TextField(blank=True, verbose_name=\n 'Description')), ('distribution_date', models.DateField(blank=True,\n null=True, verbose_name='Distribution Date')), ('barrier_symbol',\n models.CharField(blank=True, max_length=500, verbose_name=\n 'Barrier Symbol')), ('core_symbol', models.CharField(blank=True,\n max_length=500, verbose_name='Core Symbol')), ('mab_type', models.\n CharField(blank=True, max_length=500, verbose_name='Barrier type')),\n ('products_text', models.TextField(blank=True, verbose_name=\n 'Products')), ('product_codes', models.TextField(blank=True,\n verbose_name='Product codes')), ('objectives', models.TextField(\n blank=True, verbose_name='Objectives')), ('keywords', models.\n TextField(blank=True, verbose_name='Keywords')), (\n 'regions_affected', models.TextField(blank=True, verbose_name=\n 'Regions affected')), ('comments_due_date', models.DateField(blank=\n True, null=True, verbose_name='Final date for comments')), (\n 'notification_type', models.CharField(blank=True, max_length=50,\n verbose_name='Notification type')), ('document_link', models.\n CharField(blank=True, max_length=1500, verbose_name='Document link'\n )), ('external_link', models.CharField(blank=True, max_length=1500,\n verbose_name='External site link'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierRecord', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'status', models.CharField(blank=True, choices=[('Active', 'Active'\n )], default=None, max_length=10, null=True)), ('title', models.\n TextField(blank=True, verbose_name='Title')), ('description',\n models.TextField(blank=True, verbose_name='Description')), (\n 'products_text', models.TextField(blank=True, verbose_name=\n 'Products affected')), ('sectors_text', models.TextField(blank=True,\n verbose_name='Sectors affected')), ('source_id', models.CharField(\n blank=True, max_length=20, null=True, verbose_name=\n 'ID in source system')), ('distribution_date', models.DateField(\n blank=True, null=True, verbose_name='Distribution Date')), (\n 'external_link', models.CharField(blank=True, max_length=1500,\n verbose_name='External site link'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierReport', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'status', models.CharField(blank=True, choices=[('Draft', 'Draft'),\n ('Submitted', 'Submitted')], default=None, max_length=10, null=True\n )), ('name', models.CharField(blank=True, max_length=200, null=True\n )), ('problem_description', models.TextField(blank=True, null=True)\n ), ('product_text', models.TextField(blank=True, null=True)), (\n 'product_code', models.CharField(blank=True, max_length=500, null=\n True)), ('business_impact_description', models.TextField(blank=True,\n null=True)), ('problem_duration_description', models.TextField(\n blank=True, null=True)), ('other_companies_affected_choice', models\n .CharField(blank=True, choices=[('Yes', 'Yes'), ('No', 'No'), (\n 'DontKnow', \"Don't know\")], default=None, max_length=10, null=True)\n ), ('other_countries_affected_description', models.TextField(blank=\n True, null=True)), ('steps_taken_to_resolve', models.TextField(\n blank=True, null=True)), ('outcome_looking_for', models.TextField(\n blank=True, null=True)), ('support_desired_choice', models.\n CharField(blank=True, choices=[('SUPPORT_DESIRED_NONE',\n 'None - this is for your information only'), (\n 'SUPPORT_DESIRED_LOCAL',\n 'Local engagement only with UK Government officials in the country I am trying to export to'\n ), ('SUPPORT_DESIRED_BROAD', 'Broader UK Government involvement'),\n ('SUPPORT_DESIRED_NOT_SURE', 'Not sure')], default=None, max_length\n =10, null=True)), ('confidentiality_issues_description', models.\n TextField(blank=True, null=True)), ('happy_to_publish_choice',\n models.CharField(blank=True, choices=[('HAPPY_TO_PUBLISH_YES',\n 'Yes'), ('HAPPY_TO_PUBLISH_NO', 'No'), ('HAPPY_TO_PUBLISH_MAYBE',\n 'Maybe, following consultation with me')], default=None, max_length\n =10, null=True)), ('any_other_details_description', models.\n TextField(blank=True, null=True)), ('country', models.ForeignKey(\n blank=True, null=True, on_delete=django.db.models.deletion.CASCADE,\n to='barriers.BarrierCountry'))], options={'abstract': False}),\n migrations.CreateModel(name='BarrierReporter', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'name', models.CharField(blank=True, max_length=1500, verbose_name=\n 'Reporter name')), ('company', models.CharField(blank=True,\n max_length=1500, verbose_name='Company name'))], options={\n 'abstract': False}), migrations.CreateModel(name='BarrierSource',\n fields=[('id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('created_date', models.\n DateTimeField(auto_now_add=True)), ('updated_date', models.\n DateTimeField(auto_now=True)), ('is_deleted', models.BooleanField(\n default=False)), ('name', models.CharField(max_length=100)), (\n 'description', models.CharField(blank=True, max_length=500, null=\n True)), ('short_name', models.CharField(blank=True, max_length=20,\n null=True)), ('remote_url', models.URLField(blank=True, max_length=\n 20, null=True))], options={'abstract': False}), migrations.\n CreateModel(name='BarrierTypeMapping', fields=[('id', models.\n AutoField(auto_created=True, primary_key=True, serialize=False,\n verbose_name='ID')), ('created_date', models.DateTimeField(\n auto_now_add=True)), ('updated_date', models.DateTimeField(auto_now\n =True)), ('is_deleted', models.BooleanField(default=False)), (\n 'destination_barrier_list', models.ForeignKey(on_delete=django.db.\n models.deletion.CASCADE, related_name='destination_barrier_list',\n to='barriers.BarrierSource'))], options={'abstract': False}),\n migrations.RemoveField(model_name='marketaccessbarrier', name=\n 'barrier_types'), migrations.RenameField(model_name='barriertype',\n old_name='ec_barrier_code', new_name='barrier_code'), migrations.\n AlterField(model_name='barriertype', name='name', field=models.\n CharField(max_length=200)), migrations.DeleteModel(name=\n 'MarketAccessBarrier'), migrations.AddField(model_name=\n 'barriertypemapping', name='destination_barrier_type', field=models\n .ForeignKey(on_delete=django.db.models.deletion.CASCADE,\n related_name='destination_barrier_type', to='barriers.BarrierType')\n ), migrations.AddField(model_name='barriertypemapping', name=\n 'source_barrier_list', field=models.ForeignKey(on_delete=django.db.\n models.deletion.CASCADE, related_name='source_barrier_list', to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barriertypemapping', name='source_barrier_type', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE,\n related_name='source_barrier_type', to='barriers.BarrierType')),\n migrations.AddField(model_name='barrierreport', name='reporter',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.\n models.deletion.CASCADE, to='barriers.BarrierReporter')),\n migrations.AddField(model_name='barrierreport', name=\n 'top_level_barrier_type', field=models.ForeignKey(blank=True, null=\n True, on_delete=django.db.models.deletion.CASCADE, related_name=\n 'barrier_reports', to='barriers.BarrierType')), migrations.AddField\n (model_name='barrierrecord', name='barrier_source', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barrierrecord', name='barrier_types', field=mptt.fields.\n TreeManyToManyField(blank=True, db_index=True, related_name='types',\n to='barriers.BarrierType')), migrations.AddField(model_name=\n 'barrierrecord', name='country', field=models.ForeignKey(blank=True,\n null=True, on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierCountry')), migrations.AddField(model_name=\n 'barriernotification', name='barrier_source', field=models.\n ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource')), migrations.AddField(model_name=\n 'barriernotification', name='barrier_types', field=mptt.fields.\n TreeManyToManyField(blank=True, db_index=True, related_name=\n 'barrier_types', to='barriers.BarrierType')), migrations.AddField(\n model_name='barriernotification', name='country', field=models.\n ForeignKey(blank=True, null=True, on_delete=django.db.models.\n deletion.CASCADE, related_name='notification_countries', to=\n 'barriers.BarrierCountry')), migrations.AddField(model_name=\n 'barriertype', name='barrier_source', field=models.ForeignKey(\n default=1, on_delete=django.db.models.deletion.CASCADE, to=\n 'barriers.BarrierSource'))]\n",
"step-5": "# -*- coding: utf-8 -*-\n# Generated by Django 1.11.4 on 2017-10-02 14:41\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\nimport mptt.fields\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('barriers', '0011_auto_20170904_1658'),\n ]\n\n operations = [\n migrations.CreateModel(\n name='BarrierCountry',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('name', models.CharField(max_length=100, verbose_name='Country or Territory Name')),\n ('code', models.CharField(blank=True, max_length=100, null=True, verbose_name='Country or Territory Code')),\n ('official_name', models.CharField(blank=True, max_length=100, null=True, verbose_name='Offical Country or Territory name')),\n ('govuk_index_entry_code', models.CharField(blank=True, max_length=10, null=True, verbose_name='GOV.UK index code')),\n ('country_or_territory', models.CharField(choices=[('CO', 'Country'), ('TE', 'Territory')], default='CO', max_length=2, verbose_name='Country or Territory flag')),\n ],\n options={\n 'verbose_name_plural': 'countries or territories',\n },\n ),\n migrations.CreateModel(\n name='BarrierNotification',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('title', models.TextField(blank=True, verbose_name='Title')),\n ('description', models.TextField(blank=True, verbose_name='Description')),\n ('distribution_date', models.DateField(blank=True, null=True, verbose_name='Distribution Date')),\n ('barrier_symbol', models.CharField(blank=True, max_length=500, verbose_name='Barrier Symbol')),\n ('core_symbol', models.CharField(blank=True, max_length=500, verbose_name='Core Symbol')),\n ('mab_type', models.CharField(blank=True, max_length=500, verbose_name='Barrier type')),\n ('products_text', models.TextField(blank=True, verbose_name='Products')),\n ('product_codes', models.TextField(blank=True, verbose_name='Product codes')),\n ('objectives', models.TextField(blank=True, verbose_name='Objectives')),\n ('keywords', models.TextField(blank=True, verbose_name='Keywords')),\n ('regions_affected', models.TextField(blank=True, verbose_name='Regions affected')),\n ('comments_due_date', models.DateField(blank=True, null=True, verbose_name='Final date for comments')),\n ('notification_type', models.CharField(blank=True, max_length=50, verbose_name='Notification type')),\n ('document_link', models.CharField(blank=True, max_length=1500, verbose_name='Document link')),\n ('external_link', models.CharField(blank=True, max_length=1500, verbose_name='External site link')),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.CreateModel(\n name='BarrierRecord',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('status', models.CharField(blank=True, choices=[('Active', 'Active')], default=None, max_length=10, null=True)),\n ('title', models.TextField(blank=True, verbose_name='Title')),\n ('description', models.TextField(blank=True, verbose_name='Description')),\n ('products_text', models.TextField(blank=True, verbose_name='Products affected')),\n ('sectors_text', models.TextField(blank=True, verbose_name='Sectors affected')),\n ('source_id', models.CharField(blank=True, max_length=20, null=True, verbose_name='ID in source system')),\n ('distribution_date', models.DateField(blank=True, null=True, verbose_name='Distribution Date')),\n ('external_link', models.CharField(blank=True, max_length=1500, verbose_name='External site link')),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.CreateModel(\n name='BarrierReport',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('status', models.CharField(blank=True, choices=[('Draft', 'Draft'), ('Submitted', 'Submitted')], default=None, max_length=10, null=True)),\n ('name', models.CharField(blank=True, max_length=200, null=True)),\n ('problem_description', models.TextField(blank=True, null=True)),\n ('product_text', models.TextField(blank=True, null=True)),\n ('product_code', models.CharField(blank=True, max_length=500, null=True)),\n ('business_impact_description', models.TextField(blank=True, null=True)),\n ('problem_duration_description', models.TextField(blank=True, null=True)),\n ('other_companies_affected_choice', models.CharField(blank=True, choices=[('Yes', 'Yes'), ('No', 'No'), ('DontKnow', \"Don't know\")], default=None, max_length=10, null=True)),\n ('other_countries_affected_description', models.TextField(blank=True, null=True)),\n ('steps_taken_to_resolve', models.TextField(blank=True, null=True)),\n ('outcome_looking_for', models.TextField(blank=True, null=True)),\n ('support_desired_choice', models.CharField(blank=True, choices=[('SUPPORT_DESIRED_NONE', 'None - this is for your information only'), ('SUPPORT_DESIRED_LOCAL', 'Local engagement only with UK Government officials in the country I am trying to export to'), ('SUPPORT_DESIRED_BROAD', 'Broader UK Government involvement'), ('SUPPORT_DESIRED_NOT_SURE', 'Not sure')], default=None, max_length=10, null=True)),\n ('confidentiality_issues_description', models.TextField(blank=True, null=True)),\n ('happy_to_publish_choice', models.CharField(blank=True, choices=[('HAPPY_TO_PUBLISH_YES', 'Yes'), ('HAPPY_TO_PUBLISH_NO', 'No'), ('HAPPY_TO_PUBLISH_MAYBE', 'Maybe, following consultation with me')], default=None, max_length=10, null=True)),\n ('any_other_details_description', models.TextField(blank=True, null=True)),\n ('country', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierCountry')),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.CreateModel(\n name='BarrierReporter',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('name', models.CharField(blank=True, max_length=1500, verbose_name='Reporter name')),\n ('company', models.CharField(blank=True, max_length=1500, verbose_name='Company name')),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.CreateModel(\n name='BarrierSource',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('name', models.CharField(max_length=100)),\n ('description', models.CharField(blank=True, max_length=500, null=True)),\n ('short_name', models.CharField(blank=True, max_length=20, null=True)),\n ('remote_url', models.URLField(blank=True, max_length=20, null=True)),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.CreateModel(\n name='BarrierTypeMapping',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('created_date', models.DateTimeField(auto_now_add=True)),\n ('updated_date', models.DateTimeField(auto_now=True)),\n ('is_deleted', models.BooleanField(default=False)),\n ('destination_barrier_list', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='destination_barrier_list', to='barriers.BarrierSource')),\n ],\n options={\n 'abstract': False,\n },\n ),\n migrations.RemoveField(\n model_name='marketaccessbarrier',\n name='barrier_types',\n ),\n migrations.RenameField(\n model_name='barriertype',\n old_name='ec_barrier_code',\n new_name='barrier_code',\n ),\n migrations.AlterField(\n model_name='barriertype',\n name='name',\n field=models.CharField(max_length=200),\n ),\n migrations.DeleteModel(\n name='MarketAccessBarrier',\n ),\n migrations.AddField(\n model_name='barriertypemapping',\n name='destination_barrier_type',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='destination_barrier_type', to='barriers.BarrierType'),\n ),\n migrations.AddField(\n model_name='barriertypemapping',\n name='source_barrier_list',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='source_barrier_list', to='barriers.BarrierSource'),\n ),\n migrations.AddField(\n model_name='barriertypemapping',\n name='source_barrier_type',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='source_barrier_type', to='barriers.BarrierType'),\n ),\n migrations.AddField(\n model_name='barrierreport',\n name='reporter',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierReporter'),\n ),\n migrations.AddField(\n model_name='barrierreport',\n name='top_level_barrier_type',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='barrier_reports', to='barriers.BarrierType'),\n ),\n migrations.AddField(\n model_name='barrierrecord',\n name='barrier_source',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),\n ),\n migrations.AddField(\n model_name='barrierrecord',\n name='barrier_types',\n field=mptt.fields.TreeManyToManyField(blank=True, db_index=True, related_name='types', to='barriers.BarrierType'),\n ),\n migrations.AddField(\n model_name='barrierrecord',\n name='country',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierCountry'),\n ),\n migrations.AddField(\n model_name='barriernotification',\n name='barrier_source',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),\n ),\n migrations.AddField(\n model_name='barriernotification',\n name='barrier_types',\n field=mptt.fields.TreeManyToManyField(blank=True, db_index=True, related_name='barrier_types', to='barriers.BarrierType'),\n ),\n migrations.AddField(\n model_name='barriernotification',\n name='country',\n field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='notification_countries', to='barriers.BarrierCountry'),\n ),\n migrations.AddField(\n model_name='barriertype',\n name='barrier_source',\n field=models.ForeignKey(default=1, on_delete=django.db.models.deletion.CASCADE, to='barriers.BarrierSource'),\n ),\n ]\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
"""Файл, который запускается при python qtester
"""
|
normal
|
{
"blob_id": "90fc6590dab51141124ca73082b8d937008ae782",
"index": 7400,
"step-1": "<mask token>\n",
"step-2": "\"\"\"Файл, который запускается при python qtester\n\"\"\"",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
"""Derivation of variable ``co2s``."""
import dask.array as da
import iris
import numpy as np
import stratify
from ._baseclass import DerivedVariableBase
def _get_first_unmasked_data(array, axis):
"""Get first unmasked value of an array along an axis."""
mask = da.ma.getmaskarray(array)
numerical_mask = da.where(mask, -1.0, 1.0)
indices_first_positive = da.argmax(numerical_mask, axis=axis)
indices = da.meshgrid(
*[da.arange(array.shape[i]) for i in range(array.ndim) if i != axis],
indexing='ij')
indices.insert(axis, indices_first_positive)
first_unmasked_data = np.array(array)[tuple(indices)]
return first_unmasked_data
class DerivedVariable(DerivedVariableBase):
"""Derivation of variable ``co2s``.
Use linear interpolation/extrapolation and surface air pressure to
calculate CO2 mole fraction at surface.
Note
----
In some cases, ``co2`` data is masked. In these cases, the masked values
correspond to values where the pressure level is higher than the surface
air pressure (e.g. the 1000 hPa level for grid cells with high elevation).
To obtain an unmasked ``co2s`` field, it is necessary to fill these masked
values accordingly, i.e. with the lowest unmasked value for each grid cell.
"""
@staticmethod
def required(project):
"""Declare the variables needed for derivation."""
required = [{'short_name': 'co2'}, {'short_name': 'ps'}]
return required
@staticmethod
def calculate(cubes):
"""Compute mole fraction of CO2 at surface."""
co2_cube = cubes.extract_cube(
iris.Constraint(name='mole_fraction_of_carbon_dioxide_in_air'))
ps_cube = cubes.extract_cube(
iris.Constraint(name='surface_air_pressure'))
# Fill masked data if necessary (interpolation fails with masked data)
(z_axis,) = co2_cube.coord_dims(co2_cube.coord(axis='Z',
dim_coords=True))
mask = da.ma.getmaskarray(co2_cube.core_data())
if mask.any():
first_unmasked_data = _get_first_unmasked_data(
co2_cube.core_data(), axis=z_axis)
dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]
first_unmasked_data = iris.util.broadcast_to_shape(
first_unmasked_data, co2_cube.shape, dim_map)
co2_cube.data = da.where(mask, first_unmasked_data,
co2_cube.core_data())
# Interpolation (not supported for dask arrays)
air_pressure_coord = co2_cube.coord('air_pressure')
original_levels = iris.util.broadcast_to_shape(
air_pressure_coord.points, co2_cube.shape,
co2_cube.coord_dims(air_pressure_coord))
target_levels = np.expand_dims(ps_cube.data, axis=z_axis)
co2s_data = stratify.interpolate(
target_levels,
original_levels,
co2_cube.data,
axis=z_axis,
interpolation='linear',
extrapolation='linear',
)
co2s_data = np.squeeze(co2s_data, axis=z_axis)
# Construct co2s cube
indices = [slice(None)] * co2_cube.ndim
indices[z_axis] = 0
co2s_cube = co2_cube[tuple(indices)]
co2s_cube.data = co2s_data
if co2s_cube.coords('air_pressure'):
co2s_cube.remove_coord('air_pressure')
ps_coord = iris.coords.AuxCoord(ps_cube.data,
var_name='plev',
standard_name='air_pressure',
long_name='pressure',
units=ps_cube.units)
co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))
co2s_cube.convert_units('1e-6')
return co2s_cube
|
normal
|
{
"blob_id": "7c9b68b2d32d8e435f332d4412ea1ba899607ec4",
"index": 9395,
"step-1": "<mask token>\n\n\nclass DerivedVariable(DerivedVariableBase):\n <mask token>\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': 'co2'}, {'short_name': 'ps'}]\n return required\n\n @staticmethod\n def calculate(cubes):\n \"\"\"Compute mole fraction of CO2 at surface.\"\"\"\n co2_cube = cubes.extract_cube(iris.Constraint(name=\n 'mole_fraction_of_carbon_dioxide_in_air'))\n ps_cube = cubes.extract_cube(iris.Constraint(name=\n 'surface_air_pressure'))\n z_axis, = co2_cube.coord_dims(co2_cube.coord(axis='Z', dim_coords=True)\n )\n mask = da.ma.getmaskarray(co2_cube.core_data())\n if mask.any():\n first_unmasked_data = _get_first_unmasked_data(co2_cube.\n core_data(), axis=z_axis)\n dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]\n first_unmasked_data = iris.util.broadcast_to_shape(\n first_unmasked_data, co2_cube.shape, dim_map)\n co2_cube.data = da.where(mask, first_unmasked_data, co2_cube.\n core_data())\n air_pressure_coord = co2_cube.coord('air_pressure')\n original_levels = iris.util.broadcast_to_shape(air_pressure_coord.\n points, co2_cube.shape, co2_cube.coord_dims(air_pressure_coord))\n target_levels = np.expand_dims(ps_cube.data, axis=z_axis)\n co2s_data = stratify.interpolate(target_levels, original_levels,\n co2_cube.data, axis=z_axis, interpolation='linear',\n extrapolation='linear')\n co2s_data = np.squeeze(co2s_data, axis=z_axis)\n indices = [slice(None)] * co2_cube.ndim\n indices[z_axis] = 0\n co2s_cube = co2_cube[tuple(indices)]\n co2s_cube.data = co2s_data\n if co2s_cube.coords('air_pressure'):\n co2s_cube.remove_coord('air_pressure')\n ps_coord = iris.coords.AuxCoord(ps_cube.data, var_name='plev',\n standard_name='air_pressure', long_name='pressure', units=\n ps_cube.units)\n co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))\n co2s_cube.convert_units('1e-6')\n return co2s_cube\n",
"step-2": "<mask token>\n\n\nclass DerivedVariable(DerivedVariableBase):\n \"\"\"Derivation of variable ``co2s``.\n\n Use linear interpolation/extrapolation and surface air pressure to\n calculate CO2 mole fraction at surface.\n\n Note\n ----\n In some cases, ``co2`` data is masked. In these cases, the masked values\n correspond to values where the pressure level is higher than the surface\n air pressure (e.g. the 1000 hPa level for grid cells with high elevation).\n To obtain an unmasked ``co2s`` field, it is necessary to fill these masked\n values accordingly, i.e. with the lowest unmasked value for each grid cell.\n\n \"\"\"\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': 'co2'}, {'short_name': 'ps'}]\n return required\n\n @staticmethod\n def calculate(cubes):\n \"\"\"Compute mole fraction of CO2 at surface.\"\"\"\n co2_cube = cubes.extract_cube(iris.Constraint(name=\n 'mole_fraction_of_carbon_dioxide_in_air'))\n ps_cube = cubes.extract_cube(iris.Constraint(name=\n 'surface_air_pressure'))\n z_axis, = co2_cube.coord_dims(co2_cube.coord(axis='Z', dim_coords=True)\n )\n mask = da.ma.getmaskarray(co2_cube.core_data())\n if mask.any():\n first_unmasked_data = _get_first_unmasked_data(co2_cube.\n core_data(), axis=z_axis)\n dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]\n first_unmasked_data = iris.util.broadcast_to_shape(\n first_unmasked_data, co2_cube.shape, dim_map)\n co2_cube.data = da.where(mask, first_unmasked_data, co2_cube.\n core_data())\n air_pressure_coord = co2_cube.coord('air_pressure')\n original_levels = iris.util.broadcast_to_shape(air_pressure_coord.\n points, co2_cube.shape, co2_cube.coord_dims(air_pressure_coord))\n target_levels = np.expand_dims(ps_cube.data, axis=z_axis)\n co2s_data = stratify.interpolate(target_levels, original_levels,\n co2_cube.data, axis=z_axis, interpolation='linear',\n extrapolation='linear')\n co2s_data = np.squeeze(co2s_data, axis=z_axis)\n indices = [slice(None)] * co2_cube.ndim\n indices[z_axis] = 0\n co2s_cube = co2_cube[tuple(indices)]\n co2s_cube.data = co2s_data\n if co2s_cube.coords('air_pressure'):\n co2s_cube.remove_coord('air_pressure')\n ps_coord = iris.coords.AuxCoord(ps_cube.data, var_name='plev',\n standard_name='air_pressure', long_name='pressure', units=\n ps_cube.units)\n co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))\n co2s_cube.convert_units('1e-6')\n return co2s_cube\n",
"step-3": "<mask token>\n\n\ndef _get_first_unmasked_data(array, axis):\n \"\"\"Get first unmasked value of an array along an axis.\"\"\"\n mask = da.ma.getmaskarray(array)\n numerical_mask = da.where(mask, -1.0, 1.0)\n indices_first_positive = da.argmax(numerical_mask, axis=axis)\n indices = da.meshgrid(*[da.arange(array.shape[i]) for i in range(array.\n ndim) if i != axis], indexing='ij')\n indices.insert(axis, indices_first_positive)\n first_unmasked_data = np.array(array)[tuple(indices)]\n return first_unmasked_data\n\n\nclass DerivedVariable(DerivedVariableBase):\n \"\"\"Derivation of variable ``co2s``.\n\n Use linear interpolation/extrapolation and surface air pressure to\n calculate CO2 mole fraction at surface.\n\n Note\n ----\n In some cases, ``co2`` data is masked. In these cases, the masked values\n correspond to values where the pressure level is higher than the surface\n air pressure (e.g. the 1000 hPa level for grid cells with high elevation).\n To obtain an unmasked ``co2s`` field, it is necessary to fill these masked\n values accordingly, i.e. with the lowest unmasked value for each grid cell.\n\n \"\"\"\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': 'co2'}, {'short_name': 'ps'}]\n return required\n\n @staticmethod\n def calculate(cubes):\n \"\"\"Compute mole fraction of CO2 at surface.\"\"\"\n co2_cube = cubes.extract_cube(iris.Constraint(name=\n 'mole_fraction_of_carbon_dioxide_in_air'))\n ps_cube = cubes.extract_cube(iris.Constraint(name=\n 'surface_air_pressure'))\n z_axis, = co2_cube.coord_dims(co2_cube.coord(axis='Z', dim_coords=True)\n )\n mask = da.ma.getmaskarray(co2_cube.core_data())\n if mask.any():\n first_unmasked_data = _get_first_unmasked_data(co2_cube.\n core_data(), axis=z_axis)\n dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]\n first_unmasked_data = iris.util.broadcast_to_shape(\n first_unmasked_data, co2_cube.shape, dim_map)\n co2_cube.data = da.where(mask, first_unmasked_data, co2_cube.\n core_data())\n air_pressure_coord = co2_cube.coord('air_pressure')\n original_levels = iris.util.broadcast_to_shape(air_pressure_coord.\n points, co2_cube.shape, co2_cube.coord_dims(air_pressure_coord))\n target_levels = np.expand_dims(ps_cube.data, axis=z_axis)\n co2s_data = stratify.interpolate(target_levels, original_levels,\n co2_cube.data, axis=z_axis, interpolation='linear',\n extrapolation='linear')\n co2s_data = np.squeeze(co2s_data, axis=z_axis)\n indices = [slice(None)] * co2_cube.ndim\n indices[z_axis] = 0\n co2s_cube = co2_cube[tuple(indices)]\n co2s_cube.data = co2s_data\n if co2s_cube.coords('air_pressure'):\n co2s_cube.remove_coord('air_pressure')\n ps_coord = iris.coords.AuxCoord(ps_cube.data, var_name='plev',\n standard_name='air_pressure', long_name='pressure', units=\n ps_cube.units)\n co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))\n co2s_cube.convert_units('1e-6')\n return co2s_cube\n",
"step-4": "<mask token>\nimport dask.array as da\nimport iris\nimport numpy as np\nimport stratify\nfrom ._baseclass import DerivedVariableBase\n\n\ndef _get_first_unmasked_data(array, axis):\n \"\"\"Get first unmasked value of an array along an axis.\"\"\"\n mask = da.ma.getmaskarray(array)\n numerical_mask = da.where(mask, -1.0, 1.0)\n indices_first_positive = da.argmax(numerical_mask, axis=axis)\n indices = da.meshgrid(*[da.arange(array.shape[i]) for i in range(array.\n ndim) if i != axis], indexing='ij')\n indices.insert(axis, indices_first_positive)\n first_unmasked_data = np.array(array)[tuple(indices)]\n return first_unmasked_data\n\n\nclass DerivedVariable(DerivedVariableBase):\n \"\"\"Derivation of variable ``co2s``.\n\n Use linear interpolation/extrapolation and surface air pressure to\n calculate CO2 mole fraction at surface.\n\n Note\n ----\n In some cases, ``co2`` data is masked. In these cases, the masked values\n correspond to values where the pressure level is higher than the surface\n air pressure (e.g. the 1000 hPa level for grid cells with high elevation).\n To obtain an unmasked ``co2s`` field, it is necessary to fill these masked\n values accordingly, i.e. with the lowest unmasked value for each grid cell.\n\n \"\"\"\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': 'co2'}, {'short_name': 'ps'}]\n return required\n\n @staticmethod\n def calculate(cubes):\n \"\"\"Compute mole fraction of CO2 at surface.\"\"\"\n co2_cube = cubes.extract_cube(iris.Constraint(name=\n 'mole_fraction_of_carbon_dioxide_in_air'))\n ps_cube = cubes.extract_cube(iris.Constraint(name=\n 'surface_air_pressure'))\n z_axis, = co2_cube.coord_dims(co2_cube.coord(axis='Z', dim_coords=True)\n )\n mask = da.ma.getmaskarray(co2_cube.core_data())\n if mask.any():\n first_unmasked_data = _get_first_unmasked_data(co2_cube.\n core_data(), axis=z_axis)\n dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]\n first_unmasked_data = iris.util.broadcast_to_shape(\n first_unmasked_data, co2_cube.shape, dim_map)\n co2_cube.data = da.where(mask, first_unmasked_data, co2_cube.\n core_data())\n air_pressure_coord = co2_cube.coord('air_pressure')\n original_levels = iris.util.broadcast_to_shape(air_pressure_coord.\n points, co2_cube.shape, co2_cube.coord_dims(air_pressure_coord))\n target_levels = np.expand_dims(ps_cube.data, axis=z_axis)\n co2s_data = stratify.interpolate(target_levels, original_levels,\n co2_cube.data, axis=z_axis, interpolation='linear',\n extrapolation='linear')\n co2s_data = np.squeeze(co2s_data, axis=z_axis)\n indices = [slice(None)] * co2_cube.ndim\n indices[z_axis] = 0\n co2s_cube = co2_cube[tuple(indices)]\n co2s_cube.data = co2s_data\n if co2s_cube.coords('air_pressure'):\n co2s_cube.remove_coord('air_pressure')\n ps_coord = iris.coords.AuxCoord(ps_cube.data, var_name='plev',\n standard_name='air_pressure', long_name='pressure', units=\n ps_cube.units)\n co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))\n co2s_cube.convert_units('1e-6')\n return co2s_cube\n",
"step-5": "\"\"\"Derivation of variable ``co2s``.\"\"\"\nimport dask.array as da\nimport iris\nimport numpy as np\nimport stratify\n\nfrom ._baseclass import DerivedVariableBase\n\n\ndef _get_first_unmasked_data(array, axis):\n \"\"\"Get first unmasked value of an array along an axis.\"\"\"\n mask = da.ma.getmaskarray(array)\n numerical_mask = da.where(mask, -1.0, 1.0)\n indices_first_positive = da.argmax(numerical_mask, axis=axis)\n indices = da.meshgrid(\n *[da.arange(array.shape[i]) for i in range(array.ndim) if i != axis],\n indexing='ij')\n indices.insert(axis, indices_first_positive)\n first_unmasked_data = np.array(array)[tuple(indices)]\n return first_unmasked_data\n\n\nclass DerivedVariable(DerivedVariableBase):\n \"\"\"Derivation of variable ``co2s``.\n\n Use linear interpolation/extrapolation and surface air pressure to\n calculate CO2 mole fraction at surface.\n\n Note\n ----\n In some cases, ``co2`` data is masked. In these cases, the masked values\n correspond to values where the pressure level is higher than the surface\n air pressure (e.g. the 1000 hPa level for grid cells with high elevation).\n To obtain an unmasked ``co2s`` field, it is necessary to fill these masked\n values accordingly, i.e. with the lowest unmasked value for each grid cell.\n\n \"\"\"\n\n @staticmethod\n def required(project):\n \"\"\"Declare the variables needed for derivation.\"\"\"\n required = [{'short_name': 'co2'}, {'short_name': 'ps'}]\n return required\n\n @staticmethod\n def calculate(cubes):\n \"\"\"Compute mole fraction of CO2 at surface.\"\"\"\n co2_cube = cubes.extract_cube(\n iris.Constraint(name='mole_fraction_of_carbon_dioxide_in_air'))\n ps_cube = cubes.extract_cube(\n iris.Constraint(name='surface_air_pressure'))\n\n # Fill masked data if necessary (interpolation fails with masked data)\n (z_axis,) = co2_cube.coord_dims(co2_cube.coord(axis='Z',\n dim_coords=True))\n mask = da.ma.getmaskarray(co2_cube.core_data())\n if mask.any():\n first_unmasked_data = _get_first_unmasked_data(\n co2_cube.core_data(), axis=z_axis)\n dim_map = [dim for dim in range(co2_cube.ndim) if dim != z_axis]\n first_unmasked_data = iris.util.broadcast_to_shape(\n first_unmasked_data, co2_cube.shape, dim_map)\n co2_cube.data = da.where(mask, first_unmasked_data,\n co2_cube.core_data())\n\n # Interpolation (not supported for dask arrays)\n air_pressure_coord = co2_cube.coord('air_pressure')\n original_levels = iris.util.broadcast_to_shape(\n air_pressure_coord.points, co2_cube.shape,\n co2_cube.coord_dims(air_pressure_coord))\n target_levels = np.expand_dims(ps_cube.data, axis=z_axis)\n co2s_data = stratify.interpolate(\n target_levels,\n original_levels,\n co2_cube.data,\n axis=z_axis,\n interpolation='linear',\n extrapolation='linear',\n )\n co2s_data = np.squeeze(co2s_data, axis=z_axis)\n\n # Construct co2s cube\n indices = [slice(None)] * co2_cube.ndim\n indices[z_axis] = 0\n co2s_cube = co2_cube[tuple(indices)]\n co2s_cube.data = co2s_data\n if co2s_cube.coords('air_pressure'):\n co2s_cube.remove_coord('air_pressure')\n ps_coord = iris.coords.AuxCoord(ps_cube.data,\n var_name='plev',\n standard_name='air_pressure',\n long_name='pressure',\n units=ps_cube.units)\n co2s_cube.add_aux_coord(ps_coord, np.arange(co2s_cube.ndim))\n co2s_cube.convert_units('1e-6')\n return co2s_cube\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
#from graph import *
#ex = open('ex_K.py', 'r')
#ex.read()
import ex_K
ex = ex_K
print "digraph K {"
print (str(ex.K))
print "}"
|
normal
|
{
"blob_id": "44dbb7587530fac9e538dfe31c7df15b1a016251",
"index": 7091,
"step-1": "#from graph import *\r\n#ex = open('ex_K.py', 'r')\r\n#ex.read()\r\nimport ex_K\r\nex = ex_K\r\n\r\nprint \"digraph K {\"\r\nprint (str(ex.K))\r\nprint \"}\"\r\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
class Solution:
def maxSideLength(self, mat: List[List[int]], threshold: int) -> int:
def squareSum(r1: int, c1: int, r2: int, c2: int) -> int:
return prefixSum[r2 + 1][c2 + 1] - prefixSum[r1][c2 + 1] - prefixSum[r2 + 1][c1] + prefixSum[r1][c1]
m = len(mat)
n = len(mat[0])
ans = 0
prefixSum = [[0] * (n + 1) for _ in range(m + 1)]
for i in range(1, m + 1):
for j in range(1, n + 1):
prefixSum[i][j] = mat[i - 1][j - 1] + prefixSum[i][j - 1] + \
prefixSum[i - 1][j] - prefixSum[i - 1][j - 1]
for i in range(m):
for j in range(n):
for length in range(ans, min(m - i, n - j)):
if squareSum(i, j, i + length, j + length) > threshold:
break
ans = max(ans, length + 1)
return ans
|
normal
|
{
"blob_id": "c8f2df1471a9581d245d52437470b6c67b341ece",
"index": 7297,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def maxSideLength(self, mat: List[List[int]], threshold: int) ->int:\n\n def squareSum(r1: int, c1: int, r2: int, c2: int) ->int:\n return prefixSum[r2 + 1][c2 + 1] - prefixSum[r1][c2 + 1\n ] - prefixSum[r2 + 1][c1] + prefixSum[r1][c1]\n m = len(mat)\n n = len(mat[0])\n ans = 0\n prefixSum = [([0] * (n + 1)) for _ in range(m + 1)]\n for i in range(1, m + 1):\n for j in range(1, n + 1):\n prefixSum[i][j] = mat[i - 1][j - 1] + prefixSum[i][j - 1\n ] + prefixSum[i - 1][j] - prefixSum[i - 1][j - 1]\n for i in range(m):\n for j in range(n):\n for length in range(ans, min(m - i, n - j)):\n if squareSum(i, j, i + length, j + length) > threshold:\n break\n ans = max(ans, length + 1)\n return ans\n",
"step-4": "class Solution:\n def maxSideLength(self, mat: List[List[int]], threshold: int) -> int:\n def squareSum(r1: int, c1: int, r2: int, c2: int) -> int:\n return prefixSum[r2 + 1][c2 + 1] - prefixSum[r1][c2 + 1] - prefixSum[r2 + 1][c1] + prefixSum[r1][c1]\n\n m = len(mat)\n n = len(mat[0])\n\n ans = 0\n prefixSum = [[0] * (n + 1) for _ in range(m + 1)]\n\n for i in range(1, m + 1):\n for j in range(1, n + 1):\n prefixSum[i][j] = mat[i - 1][j - 1] + prefixSum[i][j - 1] + \\\n prefixSum[i - 1][j] - prefixSum[i - 1][j - 1]\n\n for i in range(m):\n for j in range(n):\n for length in range(ans, min(m - i, n - j)):\n if squareSum(i, j, i + length, j + length) > threshold:\n break\n ans = max(ans, length + 1)\n\n return ans\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
/Users/sterlingbutters/anaconda3/lib/python3.6/encodings/cp037.py
|
normal
|
{
"blob_id": "85dfb30a380dc73f5a465c8f4be84decccfbcb59",
"index": 1290,
"step-1": "/Users/sterlingbutters/anaconda3/lib/python3.6/encodings/cp037.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
# Copyright 2017 Klarna AB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
import os
import base64
import json
from django.test import TestCase, override_settings
from django.conf import settings
from django.core import management
from django.urls import reverse
from django.contrib.auth import get_user_model
from django.contrib.auth.models import Group
from django.contrib.auth.hashers import make_password
from django_rethink.connection import r
from django_rethink.serializers import *
class TestSerializer(RethinkSerializer):
id = serializers.CharField(required=False, read_only=True)
permissions = PermissionsSerializer()
class Meta(RethinkSerializer.Meta):
table_name = 'django_rethink_test'
indices = [
('permissions_read', r.row['permissions']['read']),
('permissions_write', r.row['permissions']['write']),
('permissions_create', r.row['permissions']['create']),
]
class TestReviewSerializer(NeedsReviewMixin, HistorySerializerMixin):
id = serializers.CharField(required=False, read_only=True)
field1 = serializers.CharField(required=True)
permissions = PermissionsSerializer()
class Meta(RethinkSerializer.Meta):
table_name = 'django_rethink_test_reviewed'
indices = [
('permissions_read', r.row['permissions']['read']),
('permissions_write', r.row['permissions']['write']),
('permissions_create', r.row['permissions']['create']),
]
class TestHistoryPermissionsSerializer(HistorySerializerMixin):
id = serializers.CharField(required=False, read_only=True)
field1 = serializers.CharField(required=True)
permissions = PermissionsSerializer()
class Meta(RethinkSerializer.Meta):
table_name = 'django_rethink_test_history_permissions'
indices = [
('permissions_read', r.row['permissions']['read']),
('permissions_write', r.row['permissions']['write']),
('permissions_create', r.row['permissions']['create']),
]
class TestHistoryHasReadPermissionSerializer(HistorySerializerMixin):
id = serializers.CharField(required=False, read_only=True)
field1 = serializers.CharField(required=True)
user = serializers.CharField(required=True)
class Meta(RethinkSerializer.Meta):
table_name = 'django_rethink_test_history_has_read_permission'
def has_read_permission(self, user):
return self.instance['user'] == user.username
@override_settings(
RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB', 'django_rethinkci'),
)
class APITests(TestCase):
@classmethod
def setUpClass(cls):
super(APITests, cls).setUpClass()
cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.RETHINK_DB_PORT)
try:
r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)
except:
pass
r.db_create(settings.RETHINK_DB_DB).run(cls.conn)
cls.conn.db = settings.RETHINK_DB_DB
management.call_command('syncrethinkdb', verbosity=0)
@classmethod
def tearDownClass(cls):
r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)
super(APITests, cls).tearDownClass()
def tearDown(self):
for t in [
"django_rethink_test",
"history",
"django_rethink_test_reviewed",
"django_rethink_test_history_permissions",
"django_rethink_test_history_has_read_permission",
]:
r.table(t).delete().run(self.conn)
super(APITests, self).tearDown()
def create_user(self, username='tester', password='tester', is_superuser=True, groups=[], **kwargs):
user = get_user_model().objects.create(
username=username,
password=make_password(password),
is_superuser=is_superuser,
**kwargs
)
for name in groups:
group, created = Group.objects.get_or_create(name=name)
user.groups.add(group)
auth = "Basic %s" % (base64.b64encode(("%s:%s" % (username, password)).encode("ascii")).decode("ascii"))
return user, auth
def test_history_no_type(self):
super_user, super_auth = self.create_user()
response = self.client.get(reverse('django_rethink:history_list',
kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),
HTTP_AUTHORIZATION=super_auth
)
self.assertEqual(response.status_code, 404)
def test_history_with_permissions(self):
super_user, super_auth = self.create_user()
luser, lauth = self.create_user(username='luser', is_superuser=False, groups=['group1'])
serializer = TestHistoryPermissionsSerializer(None,
data={'field1': 'test1', 'user': luser.username,
'permissions': {'write': ['group1']}},
context={'username': luser.username}
)
serializer.is_valid(raise_exception=True)
test1 = serializer.save()
serializer = TestHistoryPermissionsSerializer(None,
data={'field1': 'test2', 'user': super_user.username,
'permissions': {'write': []}},
context={'username': super_user.username}
)
serializer.is_valid(raise_exception=True)
test2 = serializer.save()
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryPermissionsSerializer.Meta.table_name,
'pk': test1['id'],
}), HTTP_AUTHORIZATION=lauth)
self.assertEqual(response.status_code, 200)
data = json.loads(response.content)
self.assertEqual(len(data), 1)
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryPermissionsSerializer.Meta.table_name,
'pk': test2['id'],
}), HTTP_AUTHORIZATION=lauth)
self.assertEqual(response.status_code, 403)
def test_history_with_has_read_permission(self):
super_user, super_auth = self.create_user()
luser, lauth = self.create_user(username='luser', is_superuser=False, groups=['group1'])
serializer = TestHistoryHasReadPermissionSerializer(None,
data={'field1': 'test1', 'user': luser.username},
context={'username': luser.username}
)
serializer.is_valid(raise_exception=True)
test1 = serializer.save()
serializer = TestHistoryHasReadPermissionSerializer(test1,
data={'field1': 'test1.1'}, partial=True,
context={'username': luser.username},
)
serializer.is_valid(raise_exception=True)
test1 = serializer.save()
serializer = TestHistoryHasReadPermissionSerializer(None,
data={'field1': 'test2', 'user': super_user.username},
context={'username': super_user.username}
)
serializer.is_valid(raise_exception=True)
test2 = serializer.save()
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,
'pk': test1['id'],
}), HTTP_AUTHORIZATION=lauth)
self.assertEqual(response.status_code, 200)
data = json.loads(response.content)
self.assertEqual(len(data), 2)
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,
'pk': test2['id'],
}), HTTP_AUTHORIZATION=lauth)
self.assertEqual(response.status_code, 403)
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,
'pk': test2['id'],
}), HTTP_AUTHORIZATION=super_auth)
self.assertEqual(response.status_code, 200)
data = json.loads(response.content)
self.assertEqual(len(data), 1)
serializer = TestHistoryHasReadPermissionSerializer(test1,
context={'username': luser.username},
)
serializer.delete()
response = self.client.get(reverse('django_rethink:history_list',
kwargs={
'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,
'pk': test1['id'],
}), HTTP_AUTHORIZATION=lauth)
self.assertEqual(response.status_code, 200)
data = json.loads(response.content)
self.assertEqual(len(data), 3)
|
normal
|
{
"blob_id": "d5d12e2269b343dde78534eddf2cce06759eb264",
"index": 9128,
"step-1": "<mask token>\n\n\n@override_settings(RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB',\n 'django_rethinkci'))\nclass APITests(TestCase):\n\n @classmethod\n def setUpClass(cls):\n super(APITests, cls).setUpClass()\n cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.\n RETHINK_DB_PORT)\n try:\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n except:\n pass\n r.db_create(settings.RETHINK_DB_DB).run(cls.conn)\n cls.conn.db = settings.RETHINK_DB_DB\n management.call_command('syncrethinkdb', verbosity=0)\n\n @classmethod\n def tearDownClass(cls):\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n super(APITests, cls).tearDownClass()\n\n def tearDown(self):\n for t in ['django_rethink_test', 'history',\n 'django_rethink_test_reviewed',\n 'django_rethink_test_history_permissions',\n 'django_rethink_test_history_has_read_permission']:\n r.table(t).delete().run(self.conn)\n super(APITests, self).tearDown()\n\n def create_user(self, username='tester', password='tester',\n is_superuser=True, groups=[], **kwargs):\n user = get_user_model().objects.create(username=username, password=\n make_password(password), is_superuser=is_superuser, **kwargs)\n for name in groups:\n group, created = Group.objects.get_or_create(name=name)\n user.groups.add(group)\n auth = 'Basic %s' % base64.b64encode(('%s:%s' % (username, password\n )).encode('ascii')).decode('ascii')\n return user, auth\n\n def test_history_no_type(self):\n super_user, super_auth = self.create_user()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),\n HTTP_AUTHORIZATION=super_auth)\n self.assertEqual(response.status_code, 404)\n\n def test_history_with_permissions(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test1', 'user': luser.username, 'permissions': {'write': [\n 'group1']}}, context={'username': luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test2', 'user': super_user.username, 'permissions': {'write':\n []}}, context={'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n def test_history_with_has_read_permission(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test1', 'user': luser.username}, context={'username':\n luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(test1, data={\n 'field1': 'test1.1'}, partial=True, context={'username': luser.\n username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test2', 'user': super_user.username}, context={\n 'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 2)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=super_auth\n )\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n serializer = TestHistoryHasReadPermissionSerializer(test1, context=\n {'username': luser.username})\n serializer.delete()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 3)\n",
"step-2": "<mask token>\n\n\nclass TestHistoryPermissionsSerializer(HistorySerializerMixin):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_permissions'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestHistoryHasReadPermissionSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n user = serializers.CharField(required=True)\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_has_read_permission'\n\n def has_read_permission(self, user):\n return self.instance['user'] == user.username\n\n\n@override_settings(RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB',\n 'django_rethinkci'))\nclass APITests(TestCase):\n\n @classmethod\n def setUpClass(cls):\n super(APITests, cls).setUpClass()\n cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.\n RETHINK_DB_PORT)\n try:\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n except:\n pass\n r.db_create(settings.RETHINK_DB_DB).run(cls.conn)\n cls.conn.db = settings.RETHINK_DB_DB\n management.call_command('syncrethinkdb', verbosity=0)\n\n @classmethod\n def tearDownClass(cls):\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n super(APITests, cls).tearDownClass()\n\n def tearDown(self):\n for t in ['django_rethink_test', 'history',\n 'django_rethink_test_reviewed',\n 'django_rethink_test_history_permissions',\n 'django_rethink_test_history_has_read_permission']:\n r.table(t).delete().run(self.conn)\n super(APITests, self).tearDown()\n\n def create_user(self, username='tester', password='tester',\n is_superuser=True, groups=[], **kwargs):\n user = get_user_model().objects.create(username=username, password=\n make_password(password), is_superuser=is_superuser, **kwargs)\n for name in groups:\n group, created = Group.objects.get_or_create(name=name)\n user.groups.add(group)\n auth = 'Basic %s' % base64.b64encode(('%s:%s' % (username, password\n )).encode('ascii')).decode('ascii')\n return user, auth\n\n def test_history_no_type(self):\n super_user, super_auth = self.create_user()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),\n HTTP_AUTHORIZATION=super_auth)\n self.assertEqual(response.status_code, 404)\n\n def test_history_with_permissions(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test1', 'user': luser.username, 'permissions': {'write': [\n 'group1']}}, context={'username': luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test2', 'user': super_user.username, 'permissions': {'write':\n []}}, context={'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n def test_history_with_has_read_permission(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test1', 'user': luser.username}, context={'username':\n luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(test1, data={\n 'field1': 'test1.1'}, partial=True, context={'username': luser.\n username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test2', 'user': super_user.username}, context={\n 'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 2)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=super_auth\n )\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n serializer = TestHistoryHasReadPermissionSerializer(test1, context=\n {'username': luser.username})\n serializer.delete()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 3)\n",
"step-3": "<mask token>\n\n\nclass TestReviewSerializer(NeedsReviewMixin, HistorySerializerMixin):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_reviewed'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestHistoryPermissionsSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n permissions = PermissionsSerializer()\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_permissions'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestHistoryHasReadPermissionSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n user = serializers.CharField(required=True)\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_has_read_permission'\n\n def has_read_permission(self, user):\n return self.instance['user'] == user.username\n\n\n@override_settings(RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB',\n 'django_rethinkci'))\nclass APITests(TestCase):\n\n @classmethod\n def setUpClass(cls):\n super(APITests, cls).setUpClass()\n cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.\n RETHINK_DB_PORT)\n try:\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n except:\n pass\n r.db_create(settings.RETHINK_DB_DB).run(cls.conn)\n cls.conn.db = settings.RETHINK_DB_DB\n management.call_command('syncrethinkdb', verbosity=0)\n\n @classmethod\n def tearDownClass(cls):\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n super(APITests, cls).tearDownClass()\n\n def tearDown(self):\n for t in ['django_rethink_test', 'history',\n 'django_rethink_test_reviewed',\n 'django_rethink_test_history_permissions',\n 'django_rethink_test_history_has_read_permission']:\n r.table(t).delete().run(self.conn)\n super(APITests, self).tearDown()\n\n def create_user(self, username='tester', password='tester',\n is_superuser=True, groups=[], **kwargs):\n user = get_user_model().objects.create(username=username, password=\n make_password(password), is_superuser=is_superuser, **kwargs)\n for name in groups:\n group, created = Group.objects.get_or_create(name=name)\n user.groups.add(group)\n auth = 'Basic %s' % base64.b64encode(('%s:%s' % (username, password\n )).encode('ascii')).decode('ascii')\n return user, auth\n\n def test_history_no_type(self):\n super_user, super_auth = self.create_user()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),\n HTTP_AUTHORIZATION=super_auth)\n self.assertEqual(response.status_code, 404)\n\n def test_history_with_permissions(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test1', 'user': luser.username, 'permissions': {'write': [\n 'group1']}}, context={'username': luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test2', 'user': super_user.username, 'permissions': {'write':\n []}}, context={'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n def test_history_with_has_read_permission(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test1', 'user': luser.username}, context={'username':\n luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(test1, data={\n 'field1': 'test1.1'}, partial=True, context={'username': luser.\n username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test2', 'user': super_user.username}, context={\n 'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 2)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=super_auth\n )\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n serializer = TestHistoryHasReadPermissionSerializer(test1, context=\n {'username': luser.username})\n serializer.delete()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 3)\n",
"step-4": "from __future__ import absolute_import\nimport os\nimport base64\nimport json\nfrom django.test import TestCase, override_settings\nfrom django.conf import settings\nfrom django.core import management\nfrom django.urls import reverse\nfrom django.contrib.auth import get_user_model\nfrom django.contrib.auth.models import Group\nfrom django.contrib.auth.hashers import make_password\nfrom django_rethink.connection import r\nfrom django_rethink.serializers import *\n\n\nclass TestSerializer(RethinkSerializer):\n id = serializers.CharField(required=False, read_only=True)\n permissions = PermissionsSerializer()\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestReviewSerializer(NeedsReviewMixin, HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n permissions = PermissionsSerializer()\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_reviewed'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestHistoryPermissionsSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n permissions = PermissionsSerializer()\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_permissions'\n indices = [('permissions_read', r.row['permissions']['read']), (\n 'permissions_write', r.row['permissions']['write']), (\n 'permissions_create', r.row['permissions']['create'])]\n\n\nclass TestHistoryHasReadPermissionSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n user = serializers.CharField(required=True)\n\n\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_has_read_permission'\n\n def has_read_permission(self, user):\n return self.instance['user'] == user.username\n\n\n@override_settings(RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB',\n 'django_rethinkci'))\nclass APITests(TestCase):\n\n @classmethod\n def setUpClass(cls):\n super(APITests, cls).setUpClass()\n cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.\n RETHINK_DB_PORT)\n try:\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n except:\n pass\n r.db_create(settings.RETHINK_DB_DB).run(cls.conn)\n cls.conn.db = settings.RETHINK_DB_DB\n management.call_command('syncrethinkdb', verbosity=0)\n\n @classmethod\n def tearDownClass(cls):\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n super(APITests, cls).tearDownClass()\n\n def tearDown(self):\n for t in ['django_rethink_test', 'history',\n 'django_rethink_test_reviewed',\n 'django_rethink_test_history_permissions',\n 'django_rethink_test_history_has_read_permission']:\n r.table(t).delete().run(self.conn)\n super(APITests, self).tearDown()\n\n def create_user(self, username='tester', password='tester',\n is_superuser=True, groups=[], **kwargs):\n user = get_user_model().objects.create(username=username, password=\n make_password(password), is_superuser=is_superuser, **kwargs)\n for name in groups:\n group, created = Group.objects.get_or_create(name=name)\n user.groups.add(group)\n auth = 'Basic %s' % base64.b64encode(('%s:%s' % (username, password\n )).encode('ascii')).decode('ascii')\n return user, auth\n\n def test_history_no_type(self):\n super_user, super_auth = self.create_user()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),\n HTTP_AUTHORIZATION=super_auth)\n self.assertEqual(response.status_code, 404)\n\n def test_history_with_permissions(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test1', 'user': luser.username, 'permissions': {'write': [\n 'group1']}}, context={'username': luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryPermissionsSerializer(None, data={'field1':\n 'test2', 'user': super_user.username, 'permissions': {'write':\n []}}, context={'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryPermissionsSerializer.Meta.\n table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n def test_history_with_has_read_permission(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=\n False, groups=['group1'])\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test1', 'user': luser.username}, context={'username':\n luser.username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(test1, data={\n 'field1': 'test1.1'}, partial=True, context={'username': luser.\n username})\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(None, data={\n 'field1': 'test2', 'user': super_user.username}, context={\n 'username': super_user.username})\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 2)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test2['id']}), HTTP_AUTHORIZATION=super_auth\n )\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n serializer = TestHistoryHasReadPermissionSerializer(test1, context=\n {'username': luser.username})\n serializer.delete()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': TestHistoryHasReadPermissionSerializer.\n Meta.table_name, 'pk': test1['id']}), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 3)\n",
"step-5": "# Copyright 2017 Klarna AB\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nfrom __future__ import absolute_import\nimport os\nimport base64\nimport json\nfrom django.test import TestCase, override_settings\nfrom django.conf import settings\nfrom django.core import management\nfrom django.urls import reverse\nfrom django.contrib.auth import get_user_model\nfrom django.contrib.auth.models import Group\nfrom django.contrib.auth.hashers import make_password\n\nfrom django_rethink.connection import r\nfrom django_rethink.serializers import *\n\nclass TestSerializer(RethinkSerializer):\n id = serializers.CharField(required=False, read_only=True)\n permissions = PermissionsSerializer()\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test'\n indices = [\n ('permissions_read', r.row['permissions']['read']),\n ('permissions_write', r.row['permissions']['write']),\n ('permissions_create', r.row['permissions']['create']),\n ]\n\nclass TestReviewSerializer(NeedsReviewMixin, HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n permissions = PermissionsSerializer()\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_reviewed'\n indices = [\n ('permissions_read', r.row['permissions']['read']),\n ('permissions_write', r.row['permissions']['write']),\n ('permissions_create', r.row['permissions']['create']),\n ]\n\nclass TestHistoryPermissionsSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n permissions = PermissionsSerializer()\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_permissions'\n indices = [\n ('permissions_read', r.row['permissions']['read']),\n ('permissions_write', r.row['permissions']['write']),\n ('permissions_create', r.row['permissions']['create']),\n ]\n\nclass TestHistoryHasReadPermissionSerializer(HistorySerializerMixin):\n id = serializers.CharField(required=False, read_only=True)\n field1 = serializers.CharField(required=True)\n user = serializers.CharField(required=True)\n class Meta(RethinkSerializer.Meta):\n table_name = 'django_rethink_test_history_has_read_permission'\n def has_read_permission(self, user):\n return self.instance['user'] == user.username\n\n@override_settings(\n RETHINK_DB_DB=os.environ.get('RETHINK_DB_DB', 'django_rethinkci'),\n)\nclass APITests(TestCase):\n @classmethod\n def setUpClass(cls):\n super(APITests, cls).setUpClass()\n cls.conn = r.connect(host=settings.RETHINK_DB_HOST, port=settings.RETHINK_DB_PORT)\n try:\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n except:\n pass\n r.db_create(settings.RETHINK_DB_DB).run(cls.conn)\n cls.conn.db = settings.RETHINK_DB_DB\n management.call_command('syncrethinkdb', verbosity=0)\n\n @classmethod\n def tearDownClass(cls):\n r.db_drop(settings.RETHINK_DB_DB).run(cls.conn)\n super(APITests, cls).tearDownClass()\n\n def tearDown(self):\n for t in [\n \"django_rethink_test\",\n \"history\",\n \"django_rethink_test_reviewed\",\n \"django_rethink_test_history_permissions\",\n \"django_rethink_test_history_has_read_permission\",\n ]:\n r.table(t).delete().run(self.conn)\n super(APITests, self).tearDown()\n\n def create_user(self, username='tester', password='tester', is_superuser=True, groups=[], **kwargs):\n user = get_user_model().objects.create(\n username=username,\n password=make_password(password),\n is_superuser=is_superuser,\n **kwargs\n )\n for name in groups:\n group, created = Group.objects.get_or_create(name=name)\n user.groups.add(group)\n auth = \"Basic %s\" % (base64.b64encode((\"%s:%s\" % (username, password)).encode(\"ascii\")).decode(\"ascii\"))\n return user, auth\n\n def test_history_no_type(self):\n super_user, super_auth = self.create_user()\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={'object_type': 'i_dont_exist', 'pk': '1'}),\n HTTP_AUTHORIZATION=super_auth\n )\n self.assertEqual(response.status_code, 404)\n\n def test_history_with_permissions(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=False, groups=['group1'])\n\n serializer = TestHistoryPermissionsSerializer(None,\n data={'field1': 'test1', 'user': luser.username,\n 'permissions': {'write': ['group1']}},\n context={'username': luser.username}\n )\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n\n serializer = TestHistoryPermissionsSerializer(None,\n data={'field1': 'test2', 'user': super_user.username,\n 'permissions': {'write': []}},\n context={'username': super_user.username}\n )\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryPermissionsSerializer.Meta.table_name,\n 'pk': test1['id'],\n }), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryPermissionsSerializer.Meta.table_name,\n 'pk': test2['id'],\n }), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n def test_history_with_has_read_permission(self):\n super_user, super_auth = self.create_user()\n luser, lauth = self.create_user(username='luser', is_superuser=False, groups=['group1'])\n\n serializer = TestHistoryHasReadPermissionSerializer(None,\n data={'field1': 'test1', 'user': luser.username},\n context={'username': luser.username}\n )\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n serializer = TestHistoryHasReadPermissionSerializer(test1,\n data={'field1': 'test1.1'}, partial=True,\n context={'username': luser.username},\n )\n serializer.is_valid(raise_exception=True)\n test1 = serializer.save()\n\n serializer = TestHistoryHasReadPermissionSerializer(None,\n data={'field1': 'test2', 'user': super_user.username},\n context={'username': super_user.username}\n )\n serializer.is_valid(raise_exception=True)\n test2 = serializer.save()\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,\n 'pk': test1['id'],\n }), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 2)\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,\n 'pk': test2['id'],\n }), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 403)\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,\n 'pk': test2['id'],\n }), HTTP_AUTHORIZATION=super_auth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 1)\n\n serializer = TestHistoryHasReadPermissionSerializer(test1,\n context={'username': luser.username},\n )\n serializer.delete()\n\n response = self.client.get(reverse('django_rethink:history_list',\n kwargs={\n 'object_type': TestHistoryHasReadPermissionSerializer.Meta.table_name,\n 'pk': test1['id'],\n }), HTTP_AUTHORIZATION=lauth)\n self.assertEqual(response.status_code, 200)\n data = json.loads(response.content)\n self.assertEqual(len(data), 3)\n",
"step-ids": [
8,
12,
14,
18,
19
]
}
|
[
8,
12,
14,
18,
19
] |
# -*- coding: utf-8 -*-
import scrapy
import os
from topdb.items import BiqugeItem
class NovelsSpider(scrapy.Spider):
name = 'novels'
allowed_domains = ['xbiquge.la']
start_urls = ['http://www.xbiquge.la/xiaoshuodaquan/']
def parse(self, response):
# 小说分类
path = '/Users/qx/Documents/小说/new/'
all=response.xpath(".//div[@class='novellist']")
for oneitem in all:
classname=oneitem.xpath('./h2/text()').extract_first()
if classname=='奇幻小说、玄幻小说大全列表':
classname='xuanhuan'
if classname=='历史小说、军事小说、穿越小说大全列表':
classname='chuanyue'
if classname=='武侠小说、仙侠小说、修真小说大全列表':
classname='xiuzhen'
if classname=='言情小说、都市小说大全列表':
classname='dushi'
if classname=='异灵小说、科幻小说大全列表':
classname='kehuan'
if classname=='游戏小说、竞技小说、网游小说大全列表':
classname='wangyou'
urls=oneitem.xpath('./ul/li/a/@href').extract()
names=oneitem.xpath('./ul/li/a/text()').extract()
for i in range(len(urls)):
url=urls[i]
name=names[i]
yield scrapy.Request(url, meta={'name': name, 'classname': classname}, callback=self.url_parse)
def url_parse(self, response):
# 小说章节列表
print('小说章节')
path = '/Users/qx/Documents/小说/new/'
name = response.meta['name']
classname = response.meta['classname']
author = response.xpath("//div[@id ='info']/p/text()").extract_first()
if author:
author=author.split('：',1)[1]
print(name+'-'+author)
listurls = response.xpath("//div[@id ='list']/dl/dd/a/@href").extract()
chapternames = response.xpath("//div[@id ='list']/dl/dd/a/text()").extract()
for i in range(len(listurls)):
url = "http://www.xbiquge.la" + listurls[i]
chaptername=chapternames[i]
oldname=path+ classname+'/'+name+ '-作者:' + author
newname=path+ classname+'/'+name
if (os.path.exists(oldname)):
os.rename(oldname,newname)
if (not os.path.exists(newname)):
os.makedirs(newname)
if(not os.path.exists(newname+'/'+ str(i) + ".txt")):
yield scrapy.Request(url, meta={'chaptername':chaptername,'tag':classname,'name':name,'author':author,'index':i}, callback=self.detail_parse)
def detail_parse(self, response):
# 章节详细内容
tag = response.meta['tag']
name = response.meta['name']
author = response.meta['author']
chaptername = response.meta['chaptername']
index = response.meta['index']
item = BiqugeItem()
novel = response.xpath("//div[@id='content']/text()").extract()
item['novel'] = "\n".join(novel).replace(" ", " ")
item['name'] = name
item['tag'] = tag
item['author'] = author
item['chapter'] = chaptername
item['index'] = index
# print(item['classname'])
# print(item['name'])
# print(item['title'])
# print('\n')
yield item
# 这里是爬取整个网站且按照分类进行爬取 但是重点是 爬取太慢scrapy 是异步操作 还需要了解一下多线程的问题 这样速度能更快些
|
normal
|
{
"blob_id": "af668751074df6f182c7121821587270734ea5af",
"index": 1075,
"step-1": "<mask token>\n\n\nclass NovelsSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self, response):\n path = '/Users/qx/Documents/小说/new/'\n all = response.xpath(\".//div[@class='novellist']\")\n for oneitem in all:\n classname = oneitem.xpath('./h2/text()').extract_first()\n if classname == '奇幻小说、玄幻小说大全列表':\n classname = 'xuanhuan'\n if classname == '历史小说、军事小说、穿越小说大全列表':\n classname = 'chuanyue'\n if classname == '武侠小说、仙侠小说、修真小说大全列表':\n classname = 'xiuzhen'\n if classname == '言情小说、都市小说大全列表':\n classname = 'dushi'\n if classname == '异灵小说、科幻小说大全列表':\n classname = 'kehuan'\n if classname == '游戏小说、竞技小说、网游小说大全列表':\n classname = 'wangyou'\n urls = oneitem.xpath('./ul/li/a/@href').extract()\n names = oneitem.xpath('./ul/li/a/text()').extract()\n for i in range(len(urls)):\n url = urls[i]\n name = names[i]\n yield scrapy.Request(url, meta={'name': name, 'classname':\n classname}, callback=self.url_parse)\n\n def url_parse(self, response):\n print('小说章节')\n path = '/Users/qx/Documents/小说/new/'\n name = response.meta['name']\n classname = response.meta['classname']\n author = response.xpath(\"//div[@id ='info']/p/text()\").extract_first()\n if author:\n author = author.split('：', 1)[1]\n print(name + '-' + author)\n listurls = response.xpath(\"//div[@id ='list']/dl/dd/a/@href\").extract()\n chapternames = response.xpath(\"//div[@id ='list']/dl/dd/a/text()\"\n ).extract()\n for i in range(len(listurls)):\n url = 'http://www.xbiquge.la' + listurls[i]\n chaptername = chapternames[i]\n oldname = path + classname + '/' + name + '-作者:' + author\n newname = path + classname + '/' + name\n if os.path.exists(oldname):\n os.rename(oldname, newname)\n if not os.path.exists(newname):\n os.makedirs(newname)\n if not os.path.exists(newname + '/' + str(i) + '.txt'):\n yield scrapy.Request(url, meta={'chaptername': chaptername,\n 'tag': classname, 'name': name, 'author': author,\n 'index': i}, callback=self.detail_parse)\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass NovelsSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self, response):\n path = '/Users/qx/Documents/小说/new/'\n all = response.xpath(\".//div[@class='novellist']\")\n for oneitem in all:\n classname = oneitem.xpath('./h2/text()').extract_first()\n if classname == '奇幻小说、玄幻小说大全列表':\n classname = 'xuanhuan'\n if classname == '历史小说、军事小说、穿越小说大全列表':\n classname = 'chuanyue'\n if classname == '武侠小说、仙侠小说、修真小说大全列表':\n classname = 'xiuzhen'\n if classname == '言情小说、都市小说大全列表':\n classname = 'dushi'\n if classname == '异灵小说、科幻小说大全列表':\n classname = 'kehuan'\n if classname == '游戏小说、竞技小说、网游小说大全列表':\n classname = 'wangyou'\n urls = oneitem.xpath('./ul/li/a/@href').extract()\n names = oneitem.xpath('./ul/li/a/text()').extract()\n for i in range(len(urls)):\n url = urls[i]\n name = names[i]\n yield scrapy.Request(url, meta={'name': name, 'classname':\n classname}, callback=self.url_parse)\n\n def url_parse(self, response):\n print('小说章节')\n path = '/Users/qx/Documents/小说/new/'\n name = response.meta['name']\n classname = response.meta['classname']\n author = response.xpath(\"//div[@id ='info']/p/text()\").extract_first()\n if author:\n author = author.split('：', 1)[1]\n print(name + '-' + author)\n listurls = response.xpath(\"//div[@id ='list']/dl/dd/a/@href\").extract()\n chapternames = response.xpath(\"//div[@id ='list']/dl/dd/a/text()\"\n ).extract()\n for i in range(len(listurls)):\n url = 'http://www.xbiquge.la' + listurls[i]\n chaptername = chapternames[i]\n oldname = path + classname + '/' + name + '-作者:' + author\n newname = path + classname + '/' + name\n if os.path.exists(oldname):\n os.rename(oldname, newname)\n if not os.path.exists(newname):\n os.makedirs(newname)\n if not os.path.exists(newname + '/' + str(i) + '.txt'):\n yield scrapy.Request(url, meta={'chaptername': chaptername,\n 'tag': classname, 'name': name, 'author': author,\n 'index': i}, callback=self.detail_parse)\n\n def detail_parse(self, response):\n tag = response.meta['tag']\n name = response.meta['name']\n author = response.meta['author']\n chaptername = response.meta['chaptername']\n index = response.meta['index']\n item = BiqugeItem()\n novel = response.xpath(\"//div[@id='content']/text()\").extract()\n item['novel'] = '\\n'.join(novel).replace(' ', ' ')\n item['name'] = name\n item['tag'] = tag\n item['author'] = author\n item['chapter'] = chaptername\n item['index'] = index\n yield item\n",
"step-3": "<mask token>\n\n\nclass NovelsSpider(scrapy.Spider):\n name = 'novels'\n allowed_domains = ['xbiquge.la']\n start_urls = ['http://www.xbiquge.la/xiaoshuodaquan/']\n\n def parse(self, response):\n path = '/Users/qx/Documents/小说/new/'\n all = response.xpath(\".//div[@class='novellist']\")\n for oneitem in all:\n classname = oneitem.xpath('./h2/text()').extract_first()\n if classname == '奇幻小说、玄幻小说大全列表':\n classname = 'xuanhuan'\n if classname == '历史小说、军事小说、穿越小说大全列表':\n classname = 'chuanyue'\n if classname == '武侠小说、仙侠小说、修真小说大全列表':\n classname = 'xiuzhen'\n if classname == '言情小说、都市小说大全列表':\n classname = 'dushi'\n if classname == '异灵小说、科幻小说大全列表':\n classname = 'kehuan'\n if classname == '游戏小说、竞技小说、网游小说大全列表':\n classname = 'wangyou'\n urls = oneitem.xpath('./ul/li/a/@href').extract()\n names = oneitem.xpath('./ul/li/a/text()').extract()\n for i in range(len(urls)):\n url = urls[i]\n name = names[i]\n yield scrapy.Request(url, meta={'name': name, 'classname':\n classname}, callback=self.url_parse)\n\n def url_parse(self, response):\n print('小说章节')\n path = '/Users/qx/Documents/小说/new/'\n name = response.meta['name']\n classname = response.meta['classname']\n author = response.xpath(\"//div[@id ='info']/p/text()\").extract_first()\n if author:\n author = author.split('：', 1)[1]\n print(name + '-' + author)\n listurls = response.xpath(\"//div[@id ='list']/dl/dd/a/@href\").extract()\n chapternames = response.xpath(\"//div[@id ='list']/dl/dd/a/text()\"\n ).extract()\n for i in range(len(listurls)):\n url = 'http://www.xbiquge.la' + listurls[i]\n chaptername = chapternames[i]\n oldname = path + classname + '/' + name + '-作者:' + author\n newname = path + classname + '/' + name\n if os.path.exists(oldname):\n os.rename(oldname, newname)\n if not os.path.exists(newname):\n os.makedirs(newname)\n if not os.path.exists(newname + '/' + str(i) + '.txt'):\n yield scrapy.Request(url, meta={'chaptername': chaptername,\n 'tag': classname, 'name': name, 'author': author,\n 'index': i}, callback=self.detail_parse)\n\n def detail_parse(self, response):\n tag = response.meta['tag']\n name = response.meta['name']\n author = response.meta['author']\n chaptername = response.meta['chaptername']\n index = response.meta['index']\n item = BiqugeItem()\n novel = response.xpath(\"//div[@id='content']/text()\").extract()\n item['novel'] = '\\n'.join(novel).replace(' ', ' ')\n item['name'] = name\n item['tag'] = tag\n item['author'] = author\n item['chapter'] = chaptername\n item['index'] = index\n yield item\n",
"step-4": "import scrapy\nimport os\nfrom topdb.items import BiqugeItem\n\n\nclass NovelsSpider(scrapy.Spider):\n name = 'novels'\n allowed_domains = ['xbiquge.la']\n start_urls = ['http://www.xbiquge.la/xiaoshuodaquan/']\n\n def parse(self, response):\n path = '/Users/qx/Documents/小说/new/'\n all = response.xpath(\".//div[@class='novellist']\")\n for oneitem in all:\n classname = oneitem.xpath('./h2/text()').extract_first()\n if classname == '奇幻小说、玄幻小说大全列表':\n classname = 'xuanhuan'\n if classname == '历史小说、军事小说、穿越小说大全列表':\n classname = 'chuanyue'\n if classname == '武侠小说、仙侠小说、修真小说大全列表':\n classname = 'xiuzhen'\n if classname == '言情小说、都市小说大全列表':\n classname = 'dushi'\n if classname == '异灵小说、科幻小说大全列表':\n classname = 'kehuan'\n if classname == '游戏小说、竞技小说、网游小说大全列表':\n classname = 'wangyou'\n urls = oneitem.xpath('./ul/li/a/@href').extract()\n names = oneitem.xpath('./ul/li/a/text()').extract()\n for i in range(len(urls)):\n url = urls[i]\n name = names[i]\n yield scrapy.Request(url, meta={'name': name, 'classname':\n classname}, callback=self.url_parse)\n\n def url_parse(self, response):\n print('小说章节')\n path = '/Users/qx/Documents/小说/new/'\n name = response.meta['name']\n classname = response.meta['classname']\n author = response.xpath(\"//div[@id ='info']/p/text()\").extract_first()\n if author:\n author = author.split('：', 1)[1]\n print(name + '-' + author)\n listurls = response.xpath(\"//div[@id ='list']/dl/dd/a/@href\").extract()\n chapternames = response.xpath(\"//div[@id ='list']/dl/dd/a/text()\"\n ).extract()\n for i in range(len(listurls)):\n url = 'http://www.xbiquge.la' + listurls[i]\n chaptername = chapternames[i]\n oldname = path + classname + '/' + name + '-作者:' + author\n newname = path + classname + '/' + name\n if os.path.exists(oldname):\n os.rename(oldname, newname)\n if not os.path.exists(newname):\n os.makedirs(newname)\n if not os.path.exists(newname + '/' + str(i) + '.txt'):\n yield scrapy.Request(url, meta={'chaptername': chaptername,\n 'tag': classname, 'name': name, 'author': author,\n 'index': i}, callback=self.detail_parse)\n\n def detail_parse(self, response):\n tag = response.meta['tag']\n name = response.meta['name']\n author = response.meta['author']\n chaptername = response.meta['chaptername']\n index = response.meta['index']\n item = BiqugeItem()\n novel = response.xpath(\"//div[@id='content']/text()\").extract()\n item['novel'] = '\\n'.join(novel).replace(' ', ' ')\n item['name'] = name\n item['tag'] = tag\n item['author'] = author\n item['chapter'] = chaptername\n item['index'] = index\n yield item\n",
"step-5": "# -*- coding: utf-8 -*-\nimport scrapy\n\nimport os\nfrom topdb.items import BiqugeItem\n\nclass NovelsSpider(scrapy.Spider):\n name = 'novels'\n allowed_domains = ['xbiquge.la']\n start_urls = ['http://www.xbiquge.la/xiaoshuodaquan/']\n\n def parse(self, response):\n # 小说分类\n path = '/Users/qx/Documents/小说/new/'\n\n all=response.xpath(\".//div[@class='novellist']\")\n\n for oneitem in all:\n\n classname=oneitem.xpath('./h2/text()').extract_first()\n if classname=='奇幻小说、玄幻小说大全列表':\n classname='xuanhuan'\n if classname=='历史小说、军事小说、穿越小说大全列表':\n classname='chuanyue'\n if classname=='武侠小说、仙侠小说、修真小说大全列表':\n classname='xiuzhen'\n if classname=='言情小说、都市小说大全列表':\n classname='dushi'\n if classname=='异灵小说、科幻小说大全列表':\n classname='kehuan'\n if classname=='游戏小说、竞技小说、网游小说大全列表':\n classname='wangyou'\n\n urls=oneitem.xpath('./ul/li/a/@href').extract()\n\n names=oneitem.xpath('./ul/li/a/text()').extract()\n\n for i in range(len(urls)):\n url=urls[i]\n name=names[i]\n yield scrapy.Request(url, meta={'name': name, 'classname': classname}, callback=self.url_parse)\n\n\n def url_parse(self, response):\n # 小说章节列表\n print('小说章节')\n path = '/Users/qx/Documents/小说/new/'\n\n name = response.meta['name']\n classname = response.meta['classname']\n\n author = response.xpath(\"//div[@id ='info']/p/text()\").extract_first()\n\n if author:\n author=author.split('：',1)[1]\n\n print(name+'-'+author)\n\n listurls = response.xpath(\"//div[@id ='list']/dl/dd/a/@href\").extract()\n chapternames = response.xpath(\"//div[@id ='list']/dl/dd/a/text()\").extract()\n\n for i in range(len(listurls)):\n url = \"http://www.xbiquge.la\" + listurls[i]\n chaptername=chapternames[i]\n\n oldname=path+ classname+'/'+name+ '-作者:' + author\n newname=path+ classname+'/'+name\n\n if (os.path.exists(oldname)):\n os.rename(oldname,newname)\n\n if (not os.path.exists(newname)):\n os.makedirs(newname)\n\n if(not os.path.exists(newname+'/'+ str(i) + \".txt\")):\n yield scrapy.Request(url, meta={'chaptername':chaptername,'tag':classname,'name':name,'author':author,'index':i}, callback=self.detail_parse)\n\n def detail_parse(self, response):\n # 章节详细内容\n\n tag = response.meta['tag']\n name = response.meta['name']\n author = response.meta['author']\n chaptername = response.meta['chaptername']\n index = response.meta['index']\n\n item = BiqugeItem()\n\n novel = response.xpath(\"//div[@id='content']/text()\").extract()\n item['novel'] = \"\\n\".join(novel).replace(\" \", \" \")\n item['name'] = name\n item['tag'] = tag\n item['author'] = author\n item['chapter'] = chaptername\n item['index'] = index\n\n # print(item['classname'])\n # print(item['name'])\n # print(item['title'])\n # print('\\n')\n yield item\n\n # 这里是爬取整个网站且按照分类进行爬取 但是重点是 爬取太慢scrapy 是异步操作 还需要了解一下多线程的问题 这样速度能更快些\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
from .plutotv_html import PlutoTV_HTML
class Plugin_OBJ():
def __init__(self, fhdhr, plugin_utils):
self.fhdhr = fhdhr
self.plugin_utils = plugin_utils
self.plutotv_html = PlutoTV_HTML(fhdhr, plugin_utils)
|
normal
|
{
"blob_id": "ee0cf2325c94821fa9f5115e8848c71143eabdbf",
"index": 4775,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Plugin_OBJ:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Plugin_OBJ:\n\n def __init__(self, fhdhr, plugin_utils):\n self.fhdhr = fhdhr\n self.plugin_utils = plugin_utils\n self.plutotv_html = PlutoTV_HTML(fhdhr, plugin_utils)\n",
"step-4": "from .plutotv_html import PlutoTV_HTML\n\n\nclass Plugin_OBJ:\n\n def __init__(self, fhdhr, plugin_utils):\n self.fhdhr = fhdhr\n self.plugin_utils = plugin_utils\n self.plutotv_html = PlutoTV_HTML(fhdhr, plugin_utils)\n",
"step-5": "\nfrom .plutotv_html import PlutoTV_HTML\n\n\nclass Plugin_OBJ():\n\n def __init__(self, fhdhr, plugin_utils):\n self.fhdhr = fhdhr\n self.plugin_utils = plugin_utils\n\n self.plutotv_html = PlutoTV_HTML(fhdhr, plugin_utils)\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import sys
import getopt
import datetime
import gettext
import math
import datetime
import json
import gettext
from datetime import datetime
FIELD_INDEX_DATE = 0
FIELD_INDEX_DATA = 1
def getPercentile(arr, percentile):
percentile = min(100, max(0, percentile))
index = (percentile / 100) * (len(arr) - 1)
fractionPart = index - math.floor(index)
intPart = math.floor(index)
percentile = float(arr[intPart])
if fractionPart > 0:
percentile += fractionPart * \
(float(arr[intPart + 1]) - float(arr[intPart]))
else:
percentile += 0
return percentile
def write(output_filename, content):
with open(output_filename, 'w') as outfile:
outfile.write(content)
def main(argv):
"""
WebPerf Core Carbon Percentiles
Usage:
* run webperf-core test on all websites you want to use for your percentiles (with json as output file)
* run this file against your output file, for example like this: carbon-rating.py -i data\carbon-references-2022.json -o tests\energy_efficiency_carbon_percentiles.py
Options and arguments:
-h/--help\t\t\t: Help information on how to use script
-i/--input <file path>\t: input file path (.json)
-o/--output <file path>\t: output file path (.py)
"""
output_filename = ''
input_filename = ''
langCode = 'en'
language = False
# add support for default (en) language
language = gettext.translation(
'webperf-core', localedir='locales', languages=[langCode])
language.install()
_ = language.gettext
try:
opts, args = getopt.getopt(
argv, "hi:o:", ["help", "input=", "output="])
except getopt.GetoptError:
print(main.__doc__)
sys.exit(2)
if (opts.__len__() == 0):
print(main.__doc__)
sys.exit(2)
for opt, arg in opts:
if opt in ('-h', '--help'): # help
print(main.__doc__)
sys.exit(2)
elif opt in ("-i", "--input"): # input file path
input_filename = arg
file_ending = ""
file_long_ending = ""
if (len(input_filename) > 4):
file_ending = input_filename[-4:].lower()
if (len(input_filename) > 7):
file_long_ending = input_filename[-7:].lower()
if file_long_ending == ".sqlite":
from engines.sqlite import read_sites, add_site, delete_site
elif (file_ending == ".csv"):
from engines.csv import read_sites, add_site, delete_site
elif (file_ending == ".xml"): # https://example.com/sitemap.xml
from engines.sitemap import read_sites, add_site, delete_site
else:
from engines.json import read_tests, read_sites, add_site, delete_site
pass
elif opt in ("-o", "--output"): # output file path
output_filename = arg
pass
tests = read_tests(input_filename, 0, -1)
generated_date = False
co2s = list()
for test in tests:
if not generated_date:
generated_date = datetime.fromisoformat(
test[FIELD_INDEX_DATE]).strftime('%Y-%m-%d')
str_data = test[FIELD_INDEX_DATA].replace('\'', '"')
data = json.loads(str_data)
print(str_data)
co2s.append(data['co2'])
if not generated_date:
generated_date = datetime.today().strftime('%Y-%m-%d')
output_content = "# This array was last generated with carbon-rating.py on {0}\n".format(
generated_date)
output_content += "def get_generated_date():\n"
output_content += "\treturn '{0}'\n".format(
generated_date)
output_content += "\n"
output_content += "def get_percentiles():\n"
output_content += "\treturn [\n"
co2s_sorted = sorted(co2s)
intervals = list()
index = 1
while (index <= 100):
percentile = getPercentile(co2s_sorted, index)
intervals.append(percentile)
position = index - 1
if index < 100:
if position % 10 == 0 and position != 0:
output_content += "\t\t# {0} percentile\n".format(position)
output_content += "\t\t{0},\n".format(percentile)
else:
output_content += "\t\t{0}\n".format(percentile)
index += 1
output_content += "\t]"
print(output_content)
if (len(output_filename) > 0):
write(output_filename, output_content)
"""
If file is executed on itself then call a definition, mostly for testing purposes
"""
if __name__ == '__main__':
main(sys.argv[1:])
|
normal
|
{
"blob_id": "a801ca6ae90556d41fd278032af4e58a63709cec",
"index": 7977,
"step-1": "<mask token>\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * run webperf-core test on all websites you want to use for your percentiles (with json as output file)\n * run this file against your output file, for example like this: carbon-rating.py -i data\\\\carbon-references-2022.json -o tests\\\\energy_efficiency_carbon_percentiles.py\n\n Options and arguments:\n -h/--help\t\t\t: Help information on how to use script\n -i/--input <file path>\t: input file path (.json)\n -o/--output <file path>\t: output file path (.py)\n \"\"\"\n output_filename = ''\n input_filename = ''\n langCode = 'en'\n language = False\n language = gettext.translation('webperf-core', localedir='locales',\n languages=[langCode])\n language.install()\n _ = language.gettext\n try:\n opts, args = getopt.getopt(argv, 'hi:o:', ['help', 'input=', 'output=']\n )\n except getopt.GetoptError:\n print(main.__doc__)\n sys.exit(2)\n if opts.__len__() == 0:\n print(main.__doc__)\n sys.exit(2)\n for opt, arg in opts:\n if opt in ('-h', '--help'):\n print(main.__doc__)\n sys.exit(2)\n elif opt in ('-i', '--input'):\n input_filename = arg\n file_ending = ''\n file_long_ending = ''\n if len(input_filename) > 4:\n file_ending = input_filename[-4:].lower()\n if len(input_filename) > 7:\n file_long_ending = input_filename[-7:].lower()\n if file_long_ending == '.sqlite':\n from engines.sqlite import read_sites, add_site, delete_site\n elif file_ending == '.csv':\n from engines.csv import read_sites, add_site, delete_site\n elif file_ending == '.xml':\n from engines.sitemap import read_sites, add_site, delete_site\n else:\n from engines.json import read_tests, read_sites, add_site, delete_site\n pass\n elif opt in ('-o', '--output'):\n output_filename = arg\n pass\n tests = read_tests(input_filename, 0, -1)\n generated_date = False\n co2s = list()\n for test in tests:\n if not generated_date:\n generated_date = datetime.fromisoformat(test[FIELD_INDEX_DATE]\n ).strftime('%Y-%m-%d')\n str_data = test[FIELD_INDEX_DATA].replace(\"'\", '\"')\n data = json.loads(str_data)\n print(str_data)\n co2s.append(data['co2'])\n if not generated_date:\n generated_date = datetime.today().strftime('%Y-%m-%d')\n output_content = (\n '# This array was last generated with carbon-rating.py on {0}\\n'.\n format(generated_date))\n output_content += 'def get_generated_date():\\n'\n output_content += \"\\treturn '{0}'\\n\".format(generated_date)\n output_content += '\\n'\n output_content += 'def get_percentiles():\\n'\n output_content += '\\treturn [\\n'\n co2s_sorted = sorted(co2s)\n intervals = list()\n index = 1\n while index <= 100:\n percentile = getPercentile(co2s_sorted, index)\n intervals.append(percentile)\n position = index - 1\n if index < 100:\n if position % 10 == 0 and position != 0:\n output_content += '\\t\\t# {0} percentile\\n'.format(position)\n output_content += '\\t\\t{0},\\n'.format(percentile)\n else:\n output_content += '\\t\\t{0}\\n'.format(percentile)\n index += 1\n output_content += '\\t]'\n print(output_content)\n if len(output_filename) > 0:\n write(output_filename, output_content)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef getPercentile(arr, percentile):\n percentile = min(100, max(0, percentile))\n index = percentile / 100 * (len(arr) - 1)\n fractionPart = index - math.floor(index)\n intPart = math.floor(index)\n percentile = float(arr[intPart])\n if fractionPart > 0:\n percentile += fractionPart * (float(arr[intPart + 1]) - float(arr[\n intPart]))\n else:\n percentile += 0\n return percentile\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * run webperf-core test on all websites you want to use for your percentiles (with json as output file)\n * run this file against your output file, for example like this: carbon-rating.py -i data\\\\carbon-references-2022.json -o tests\\\\energy_efficiency_carbon_percentiles.py\n\n Options and arguments:\n -h/--help\t\t\t: Help information on how to use script\n -i/--input <file path>\t: input file path (.json)\n -o/--output <file path>\t: output file path (.py)\n \"\"\"\n output_filename = ''\n input_filename = ''\n langCode = 'en'\n language = False\n language = gettext.translation('webperf-core', localedir='locales',\n languages=[langCode])\n language.install()\n _ = language.gettext\n try:\n opts, args = getopt.getopt(argv, 'hi:o:', ['help', 'input=', 'output=']\n )\n except getopt.GetoptError:\n print(main.__doc__)\n sys.exit(2)\n if opts.__len__() == 0:\n print(main.__doc__)\n sys.exit(2)\n for opt, arg in opts:\n if opt in ('-h', '--help'):\n print(main.__doc__)\n sys.exit(2)\n elif opt in ('-i', '--input'):\n input_filename = arg\n file_ending = ''\n file_long_ending = ''\n if len(input_filename) > 4:\n file_ending = input_filename[-4:].lower()\n if len(input_filename) > 7:\n file_long_ending = input_filename[-7:].lower()\n if file_long_ending == '.sqlite':\n from engines.sqlite import read_sites, add_site, delete_site\n elif file_ending == '.csv':\n from engines.csv import read_sites, add_site, delete_site\n elif file_ending == '.xml':\n from engines.sitemap import read_sites, add_site, delete_site\n else:\n from engines.json import read_tests, read_sites, add_site, delete_site\n pass\n elif opt in ('-o', '--output'):\n output_filename = arg\n pass\n tests = read_tests(input_filename, 0, -1)\n generated_date = False\n co2s = list()\n for test in tests:\n if not generated_date:\n generated_date = datetime.fromisoformat(test[FIELD_INDEX_DATE]\n ).strftime('%Y-%m-%d')\n str_data = test[FIELD_INDEX_DATA].replace(\"'\", '\"')\n data = json.loads(str_data)\n print(str_data)\n co2s.append(data['co2'])\n if not generated_date:\n generated_date = datetime.today().strftime('%Y-%m-%d')\n output_content = (\n '# This array was last generated with carbon-rating.py on {0}\\n'.\n format(generated_date))\n output_content += 'def get_generated_date():\\n'\n output_content += \"\\treturn '{0}'\\n\".format(generated_date)\n output_content += '\\n'\n output_content += 'def get_percentiles():\\n'\n output_content += '\\treturn [\\n'\n co2s_sorted = sorted(co2s)\n intervals = list()\n index = 1\n while index <= 100:\n percentile = getPercentile(co2s_sorted, index)\n intervals.append(percentile)\n position = index - 1\n if index < 100:\n if position % 10 == 0 and position != 0:\n output_content += '\\t\\t# {0} percentile\\n'.format(position)\n output_content += '\\t\\t{0},\\n'.format(percentile)\n else:\n output_content += '\\t\\t{0}\\n'.format(percentile)\n index += 1\n output_content += '\\t]'\n print(output_content)\n if len(output_filename) > 0:\n write(output_filename, output_content)\n\n\n<mask token>\nif __name__ == '__main__':\n main(sys.argv[1:])\n",
"step-3": "<mask token>\nFIELD_INDEX_DATE = 0\nFIELD_INDEX_DATA = 1\n\n\ndef getPercentile(arr, percentile):\n percentile = min(100, max(0, percentile))\n index = percentile / 100 * (len(arr) - 1)\n fractionPart = index - math.floor(index)\n intPart = math.floor(index)\n percentile = float(arr[intPart])\n if fractionPart > 0:\n percentile += fractionPart * (float(arr[intPart + 1]) - float(arr[\n intPart]))\n else:\n percentile += 0\n return percentile\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * run webperf-core test on all websites you want to use for your percentiles (with json as output file)\n * run this file against your output file, for example like this: carbon-rating.py -i data\\\\carbon-references-2022.json -o tests\\\\energy_efficiency_carbon_percentiles.py\n\n Options and arguments:\n -h/--help\t\t\t: Help information on how to use script\n -i/--input <file path>\t: input file path (.json)\n -o/--output <file path>\t: output file path (.py)\n \"\"\"\n output_filename = ''\n input_filename = ''\n langCode = 'en'\n language = False\n language = gettext.translation('webperf-core', localedir='locales',\n languages=[langCode])\n language.install()\n _ = language.gettext\n try:\n opts, args = getopt.getopt(argv, 'hi:o:', ['help', 'input=', 'output=']\n )\n except getopt.GetoptError:\n print(main.__doc__)\n sys.exit(2)\n if opts.__len__() == 0:\n print(main.__doc__)\n sys.exit(2)\n for opt, arg in opts:\n if opt in ('-h', '--help'):\n print(main.__doc__)\n sys.exit(2)\n elif opt in ('-i', '--input'):\n input_filename = arg\n file_ending = ''\n file_long_ending = ''\n if len(input_filename) > 4:\n file_ending = input_filename[-4:].lower()\n if len(input_filename) > 7:\n file_long_ending = input_filename[-7:].lower()\n if file_long_ending == '.sqlite':\n from engines.sqlite import read_sites, add_site, delete_site\n elif file_ending == '.csv':\n from engines.csv import read_sites, add_site, delete_site\n elif file_ending == '.xml':\n from engines.sitemap import read_sites, add_site, delete_site\n else:\n from engines.json import read_tests, read_sites, add_site, delete_site\n pass\n elif opt in ('-o', '--output'):\n output_filename = arg\n pass\n tests = read_tests(input_filename, 0, -1)\n generated_date = False\n co2s = list()\n for test in tests:\n if not generated_date:\n generated_date = datetime.fromisoformat(test[FIELD_INDEX_DATE]\n ).strftime('%Y-%m-%d')\n str_data = test[FIELD_INDEX_DATA].replace(\"'\", '\"')\n data = json.loads(str_data)\n print(str_data)\n co2s.append(data['co2'])\n if not generated_date:\n generated_date = datetime.today().strftime('%Y-%m-%d')\n output_content = (\n '# This array was last generated with carbon-rating.py on {0}\\n'.\n format(generated_date))\n output_content += 'def get_generated_date():\\n'\n output_content += \"\\treturn '{0}'\\n\".format(generated_date)\n output_content += '\\n'\n output_content += 'def get_percentiles():\\n'\n output_content += '\\treturn [\\n'\n co2s_sorted = sorted(co2s)\n intervals = list()\n index = 1\n while index <= 100:\n percentile = getPercentile(co2s_sorted, index)\n intervals.append(percentile)\n position = index - 1\n if index < 100:\n if position % 10 == 0 and position != 0:\n output_content += '\\t\\t# {0} percentile\\n'.format(position)\n output_content += '\\t\\t{0},\\n'.format(percentile)\n else:\n output_content += '\\t\\t{0}\\n'.format(percentile)\n index += 1\n output_content += '\\t]'\n print(output_content)\n if len(output_filename) > 0:\n write(output_filename, output_content)\n\n\n<mask token>\nif __name__ == '__main__':\n main(sys.argv[1:])\n",
"step-4": "import sys\nimport getopt\nimport datetime\nimport gettext\nimport math\nimport datetime\nimport json\nimport gettext\nfrom datetime import datetime\nFIELD_INDEX_DATE = 0\nFIELD_INDEX_DATA = 1\n\n\ndef getPercentile(arr, percentile):\n percentile = min(100, max(0, percentile))\n index = percentile / 100 * (len(arr) - 1)\n fractionPart = index - math.floor(index)\n intPart = math.floor(index)\n percentile = float(arr[intPart])\n if fractionPart > 0:\n percentile += fractionPart * (float(arr[intPart + 1]) - float(arr[\n intPart]))\n else:\n percentile += 0\n return percentile\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * run webperf-core test on all websites you want to use for your percentiles (with json as output file)\n * run this file against your output file, for example like this: carbon-rating.py -i data\\\\carbon-references-2022.json -o tests\\\\energy_efficiency_carbon_percentiles.py\n\n Options and arguments:\n -h/--help\t\t\t: Help information on how to use script\n -i/--input <file path>\t: input file path (.json)\n -o/--output <file path>\t: output file path (.py)\n \"\"\"\n output_filename = ''\n input_filename = ''\n langCode = 'en'\n language = False\n language = gettext.translation('webperf-core', localedir='locales',\n languages=[langCode])\n language.install()\n _ = language.gettext\n try:\n opts, args = getopt.getopt(argv, 'hi:o:', ['help', 'input=', 'output=']\n )\n except getopt.GetoptError:\n print(main.__doc__)\n sys.exit(2)\n if opts.__len__() == 0:\n print(main.__doc__)\n sys.exit(2)\n for opt, arg in opts:\n if opt in ('-h', '--help'):\n print(main.__doc__)\n sys.exit(2)\n elif opt in ('-i', '--input'):\n input_filename = arg\n file_ending = ''\n file_long_ending = ''\n if len(input_filename) > 4:\n file_ending = input_filename[-4:].lower()\n if len(input_filename) > 7:\n file_long_ending = input_filename[-7:].lower()\n if file_long_ending == '.sqlite':\n from engines.sqlite import read_sites, add_site, delete_site\n elif file_ending == '.csv':\n from engines.csv import read_sites, add_site, delete_site\n elif file_ending == '.xml':\n from engines.sitemap import read_sites, add_site, delete_site\n else:\n from engines.json import read_tests, read_sites, add_site, delete_site\n pass\n elif opt in ('-o', '--output'):\n output_filename = arg\n pass\n tests = read_tests(input_filename, 0, -1)\n generated_date = False\n co2s = list()\n for test in tests:\n if not generated_date:\n generated_date = datetime.fromisoformat(test[FIELD_INDEX_DATE]\n ).strftime('%Y-%m-%d')\n str_data = test[FIELD_INDEX_DATA].replace(\"'\", '\"')\n data = json.loads(str_data)\n print(str_data)\n co2s.append(data['co2'])\n if not generated_date:\n generated_date = datetime.today().strftime('%Y-%m-%d')\n output_content = (\n '# This array was last generated with carbon-rating.py on {0}\\n'.\n format(generated_date))\n output_content += 'def get_generated_date():\\n'\n output_content += \"\\treturn '{0}'\\n\".format(generated_date)\n output_content += '\\n'\n output_content += 'def get_percentiles():\\n'\n output_content += '\\treturn [\\n'\n co2s_sorted = sorted(co2s)\n intervals = list()\n index = 1\n while index <= 100:\n percentile = getPercentile(co2s_sorted, index)\n intervals.append(percentile)\n position = index - 1\n if index < 100:\n if position % 10 == 0 and position != 0:\n output_content += '\\t\\t# {0} percentile\\n'.format(position)\n output_content += '\\t\\t{0},\\n'.format(percentile)\n else:\n output_content += '\\t\\t{0}\\n'.format(percentile)\n index += 1\n output_content += '\\t]'\n print(output_content)\n if len(output_filename) > 0:\n write(output_filename, output_content)\n\n\n<mask token>\nif __name__ == '__main__':\n main(sys.argv[1:])\n",
"step-5": "# -*- coding: utf-8 -*-\nimport sys\nimport getopt\nimport datetime\nimport gettext\nimport math\nimport datetime\nimport json\nimport gettext\nfrom datetime import datetime\n\nFIELD_INDEX_DATE = 0\nFIELD_INDEX_DATA = 1\n\n\ndef getPercentile(arr, percentile):\n percentile = min(100, max(0, percentile))\n index = (percentile / 100) * (len(arr) - 1)\n fractionPart = index - math.floor(index)\n intPart = math.floor(index)\n percentile = float(arr[intPart])\n\n if fractionPart > 0:\n percentile += fractionPart * \\\n (float(arr[intPart + 1]) - float(arr[intPart]))\n else:\n percentile += 0\n\n return percentile\n\n\ndef write(output_filename, content):\n with open(output_filename, 'w') as outfile:\n outfile.write(content)\n\n\ndef main(argv):\n \"\"\"\n WebPerf Core Carbon Percentiles\n\n\n Usage:\n * run webperf-core test on all websites you want to use for your percentiles (with json as output file)\n * run this file against your output file, for example like this: carbon-rating.py -i data\\carbon-references-2022.json -o tests\\energy_efficiency_carbon_percentiles.py\n\n Options and arguments:\n -h/--help\\t\\t\\t: Help information on how to use script\n -i/--input <file path>\\t: input file path (.json)\n -o/--output <file path>\\t: output file path (.py)\n \"\"\"\n\n output_filename = ''\n input_filename = ''\n langCode = 'en'\n language = False\n\n # add support for default (en) language\n language = gettext.translation(\n 'webperf-core', localedir='locales', languages=[langCode])\n language.install()\n _ = language.gettext\n\n try:\n opts, args = getopt.getopt(\n argv, \"hi:o:\", [\"help\", \"input=\", \"output=\"])\n except getopt.GetoptError:\n print(main.__doc__)\n sys.exit(2)\n\n if (opts.__len__() == 0):\n print(main.__doc__)\n sys.exit(2)\n\n for opt, arg in opts:\n if opt in ('-h', '--help'): # help\n print(main.__doc__)\n sys.exit(2)\n elif opt in (\"-i\", \"--input\"): # input file path\n input_filename = arg\n\n file_ending = \"\"\n file_long_ending = \"\"\n if (len(input_filename) > 4):\n file_ending = input_filename[-4:].lower()\n if (len(input_filename) > 7):\n file_long_ending = input_filename[-7:].lower()\n\n if file_long_ending == \".sqlite\":\n from engines.sqlite import read_sites, add_site, delete_site\n elif (file_ending == \".csv\"):\n from engines.csv import read_sites, add_site, delete_site\n elif (file_ending == \".xml\"): # https://example.com/sitemap.xml\n from engines.sitemap import read_sites, add_site, delete_site\n else:\n from engines.json import read_tests, read_sites, add_site, delete_site\n pass\n elif opt in (\"-o\", \"--output\"): # output file path\n output_filename = arg\n pass\n\n tests = read_tests(input_filename, 0, -1)\n generated_date = False\n co2s = list()\n\n for test in tests:\n if not generated_date:\n generated_date = datetime.fromisoformat(\n test[FIELD_INDEX_DATE]).strftime('%Y-%m-%d')\n\n str_data = test[FIELD_INDEX_DATA].replace('\\'', '\"')\n data = json.loads(str_data)\n print(str_data)\n co2s.append(data['co2'])\n\n if not generated_date:\n generated_date = datetime.today().strftime('%Y-%m-%d')\n\n output_content = \"# This array was last generated with carbon-rating.py on {0}\\n\".format(\n generated_date)\n output_content += \"def get_generated_date():\\n\"\n output_content += \"\\treturn '{0}'\\n\".format(\n generated_date)\n output_content += \"\\n\"\n output_content += \"def get_percentiles():\\n\"\n output_content += \"\\treturn [\\n\"\n\n co2s_sorted = sorted(co2s)\n\n intervals = list()\n\n index = 1\n while (index <= 100):\n percentile = getPercentile(co2s_sorted, index)\n intervals.append(percentile)\n position = index - 1\n if index < 100:\n if position % 10 == 0 and position != 0:\n output_content += \"\\t\\t# {0} percentile\\n\".format(position)\n\n output_content += \"\\t\\t{0},\\n\".format(percentile)\n else:\n output_content += \"\\t\\t{0}\\n\".format(percentile)\n index += 1\n\n output_content += \"\\t]\"\n\n print(output_content)\n if (len(output_filename) > 0):\n write(output_filename, output_content)\n\n\n\"\"\"\nIf file is executed on itself then call a definition, mostly for testing purposes\n\"\"\"\nif __name__ == '__main__':\n main(sys.argv[1:])\n",
"step-ids": [
2,
4,
5,
6,
7
]
}
|
[
2,
4,
5,
6,
7
] |
_method_adaptors = dict()
def register_dist_adaptor(method_name):
def decorator(func):
_method_adaptors[method_name] = func
def wrapper(*args, **kwargs):
func(*args, **kwargs)
return wrapper
return decorator
def get_nearest_method(method_name, parser):
"""
all candidates toked
all protocol untoked
input:
queries:
[
(protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)
(protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)
(protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)
]
output:
[
nearest_idx1,
nearest_idx2,
nearest_idx3,
...
]
"""
return _method_adaptors[method_name](parser)
def get_method_names():
return list(_method_adaptors.keys())
|
normal
|
{
"blob_id": "ed2f3bbc7eb0a4d8f5ccdb7a12e00cbddab04dd0",
"index": 577,
"step-1": "<mask token>\n\n\ndef get_nearest_method(method_name, parser):\n \"\"\"\n all candidates toked\n all protocol untoked\n input:\n queries:\n [\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n ]\n output:\n [\n nearest_idx1,\n nearest_idx2,\n nearest_idx3,\n ...\n ]\n \"\"\"\n return _method_adaptors[method_name](parser)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_nearest_method(method_name, parser):\n \"\"\"\n all candidates toked\n all protocol untoked\n input:\n queries:\n [\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n ]\n output:\n [\n nearest_idx1,\n nearest_idx2,\n nearest_idx3,\n ...\n ]\n \"\"\"\n return _method_adaptors[method_name](parser)\n\n\ndef get_method_names():\n return list(_method_adaptors.keys())\n",
"step-3": "<mask token>\n\n\ndef register_dist_adaptor(method_name):\n\n def decorator(func):\n _method_adaptors[method_name] = func\n\n def wrapper(*args, **kwargs):\n func(*args, **kwargs)\n return wrapper\n return decorator\n\n\ndef get_nearest_method(method_name, parser):\n \"\"\"\n all candidates toked\n all protocol untoked\n input:\n queries:\n [\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n ]\n output:\n [\n nearest_idx1,\n nearest_idx2,\n nearest_idx3,\n ...\n ]\n \"\"\"\n return _method_adaptors[method_name](parser)\n\n\ndef get_method_names():\n return list(_method_adaptors.keys())\n",
"step-4": "_method_adaptors = dict()\n\n\ndef register_dist_adaptor(method_name):\n\n def decorator(func):\n _method_adaptors[method_name] = func\n\n def wrapper(*args, **kwargs):\n func(*args, **kwargs)\n return wrapper\n return decorator\n\n\ndef get_nearest_method(method_name, parser):\n \"\"\"\n all candidates toked\n all protocol untoked\n input:\n queries:\n [\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)\n ]\n output:\n [\n nearest_idx1,\n nearest_idx2,\n nearest_idx3,\n ...\n ]\n \"\"\"\n return _method_adaptors[method_name](parser)\n\n\ndef get_method_names():\n return list(_method_adaptors.keys())\n",
"step-5": null,
"step-ids": [
1,
2,
3,
4
]
}
|
[
1,
2,
3,
4
] |
# Generated by Django 3.1.1 on 2021-03-25 14:42
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = []
operations = [
migrations.CreateModel(
name="Experiment",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("name", models.CharField(max_length=255)),
("description", models.TextField()),
("is_test", models.BooleanField(default=False)),
("type", models.CharField(max_length=255)),
("created_at", models.DateTimeField(auto_now_add=True)),
("updated_at", models.DateTimeField(auto_now=True)),
("deleted_at", models.DateTimeField(null=True)),
],
options={
"db_table": "experiment",
},
),
migrations.CreateModel(
name="ExperimentPlio",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("split_percentage", models.CharField(max_length=255)),
(
"experiment",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to="experiments.experiment",
),
),
],
options={
"db_table": "experiment_plio",
},
),
]
|
normal
|
{
"blob_id": "b308d81fb8eab9f52aa0ad4f88e25d6757ef703a",
"index": 1761,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = True\n dependencies = []\n operations = [migrations.CreateModel(name='Experiment', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('name', models.CharField(max_length=\n 255)), ('description', models.TextField()), ('is_test', models.\n BooleanField(default=False)), ('type', models.CharField(max_length=\n 255)), ('created_at', models.DateTimeField(auto_now_add=True)), (\n 'updated_at', models.DateTimeField(auto_now=True)), ('deleted_at',\n models.DateTimeField(null=True))], options={'db_table':\n 'experiment'}), migrations.CreateModel(name='ExperimentPlio',\n fields=[('id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('split_percentage', models.\n CharField(max_length=255)), ('experiment', models.ForeignKey(\n on_delete=django.db.models.deletion.CASCADE, to=\n 'experiments.experiment'))], options={'db_table': 'experiment_plio'})]\n",
"step-4": "from django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n initial = True\n dependencies = []\n operations = [migrations.CreateModel(name='Experiment', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('name', models.CharField(max_length=\n 255)), ('description', models.TextField()), ('is_test', models.\n BooleanField(default=False)), ('type', models.CharField(max_length=\n 255)), ('created_at', models.DateTimeField(auto_now_add=True)), (\n 'updated_at', models.DateTimeField(auto_now=True)), ('deleted_at',\n models.DateTimeField(null=True))], options={'db_table':\n 'experiment'}), migrations.CreateModel(name='ExperimentPlio',\n fields=[('id', models.AutoField(auto_created=True, primary_key=True,\n serialize=False, verbose_name='ID')), ('split_percentage', models.\n CharField(max_length=255)), ('experiment', models.ForeignKey(\n on_delete=django.db.models.deletion.CASCADE, to=\n 'experiments.experiment'))], options={'db_table': 'experiment_plio'})]\n",
"step-5": "# Generated by Django 3.1.1 on 2021-03-25 14:42\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n initial = True\n\n dependencies = []\n\n operations = [\n migrations.CreateModel(\n name=\"Experiment\",\n fields=[\n (\n \"id\",\n models.AutoField(\n auto_created=True,\n primary_key=True,\n serialize=False,\n verbose_name=\"ID\",\n ),\n ),\n (\"name\", models.CharField(max_length=255)),\n (\"description\", models.TextField()),\n (\"is_test\", models.BooleanField(default=False)),\n (\"type\", models.CharField(max_length=255)),\n (\"created_at\", models.DateTimeField(auto_now_add=True)),\n (\"updated_at\", models.DateTimeField(auto_now=True)),\n (\"deleted_at\", models.DateTimeField(null=True)),\n ],\n options={\n \"db_table\": \"experiment\",\n },\n ),\n migrations.CreateModel(\n name=\"ExperimentPlio\",\n fields=[\n (\n \"id\",\n models.AutoField(\n auto_created=True,\n primary_key=True,\n serialize=False,\n verbose_name=\"ID\",\n ),\n ),\n (\"split_percentage\", models.CharField(max_length=255)),\n (\n \"experiment\",\n models.ForeignKey(\n on_delete=django.db.models.deletion.CASCADE,\n to=\"experiments.experiment\",\n ),\n ),\n ],\n options={\n \"db_table\": \"experiment_plio\",\n },\n ),\n ]\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from lib.utility import start_time, end_time
from lib.prime import read_primes
from bisect import bisect_left
start_time()
primes = read_primes(100)
# limit = 10 ** 16
import random
# limit = random.randint(1000, 10 ** 5)
limit = 43268
# limit = 10 ** 16
print('limit=', limit)
v1 = set()
v2 = set()
def version_100_iq(limit):
nums = []
for x in range(2, limit):
facs = 0
n = x
for p in primes:
if n % p == 0:
facs += 1
while n % p == 0:
n //= p
if n == 1 or facs >= 4:
break
if facs >= 4:
nums.append(x)
return set(nums)
def version_1(limit):
def search(prod, i, num_distinct):
if prod >= limit or i >= len(primes):
return 0
if prod not in v1 and num_distinct >= 4:
v1.add(prod)
not_used = (prod % primes[i] != 0)
count = (num_distinct >= 4) and not not_used
count += search(prod * primes[i], i, num_distinct + not_used)
count += search(prod, i + 1, num_distinct)
return count
return search(1, 0, 0)
def version_2(limit):
def search(prod, i, num_distinct):
if prod >= limit:
return
if prod not in v1 and num_distinct >= 4:
v1.add(prod)
if i >= len(primes):
return
search(prod * primes[i], i + 1, num_distinct + 1)
search(prod, i + 1, num_distinct)
return search(1, 0, 0)
def find_prods_by_num_distinct_primes(limit, primes):
prods_by_num_distinct = [set() for _ in range(5)]
prods_by_num_distinct[0] |= {1}
def add_prods(prod, i, num_distinct):
if prod >= limit or i >= len(primes):
return
# not_used = (prod % primes[i] != 0)
# if not not_used:
prods_by_num_distinct[min(num_distinct, 4)].add(prod)
add_prods(prod * primes[i], i + 1, num_distinct + 1)
add_prods(prod, i + 1, num_distinct)
add_prods(1, 0, 0)
return [sorted(s) for s in prods_by_num_distinct]
version_2(limit)
pset = set(primes)
res = set()
count = 0
for n in sorted(v1):
for mult in range(1, 401):
if mult * n >= limit:
break
# if n % mult != 0 and mult in pset:
if mult in pset:
# assert(n * mult in v1), (n, mult)
continue
# print(n, mult)
if n * mult in res:
print(n, mult, n * mult)
res.add(n * mult)
count += 1
else:
print('not enough huh...', n)
count += (limit - 100*n) // n
print(len(res))
# n = 7 # a splitting point that seems to be the fastest
# lo = find_prods_by_num_distinct_primes(limit, primes[:n])
# hi = find_prods_by_num_distinct_primes(limit, primes[n:])
# max_sol = 0
# count = 0
# for lo_num_distinct_primes in range(0, 5):
# for prod in lo[lo_num_distinct_primes]:
# for hi_num_distinct_primes in range(4 - lo_num_distinct_primes, 5):
# # count += bisect_left(hi[hi_num_distinct_primes], limit / prod)
# for v in hi[hi_num_distinct_primes]:
# if v * prod < limit:
# count += 1
# # count += (limit - 1) // (v * prod)
print('Solution:', count)
iq_100 = version_100_iq(limit)
print('100 IQ version:', len(iq_100))
# if count != len(iq_100):
# print(iq_100 - v1)
# assert count == len(iq_100)
end_time()
|
normal
|
{
"blob_id": "ea8676a4c55bbe0ae2ff8abf924accfc0bd8f661",
"index": 1272,
"step-1": "<mask token>\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n while n % p == 0:\n n //= p\n if n == 1 or facs >= 4:\n break\n if facs >= 4:\n nums.append(x)\n return set(nums)\n\n\ndef version_1(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return 0\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n not_used = prod % primes[i] != 0\n count = num_distinct >= 4 and not not_used\n count += search(prod * primes[i], i, num_distinct + not_used)\n count += search(prod, i + 1, num_distinct)\n return count\n return search(1, 0, 0)\n\n\ndef version_2(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit:\n return\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n if i >= len(primes):\n return\n search(prod * primes[i], i + 1, num_distinct + 1)\n search(prod, i + 1, num_distinct)\n return search(1, 0, 0)\n\n\ndef find_prods_by_num_distinct_primes(limit, primes):\n prods_by_num_distinct = [set() for _ in range(5)]\n prods_by_num_distinct[0] |= {1}\n\n def add_prods(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return\n prods_by_num_distinct[min(num_distinct, 4)].add(prod)\n add_prods(prod * primes[i], i + 1, num_distinct + 1)\n add_prods(prod, i + 1, num_distinct)\n add_prods(1, 0, 0)\n return [sorted(s) for s in prods_by_num_distinct]\n\n\n<mask token>\n",
"step-2": "<mask token>\nstart_time()\n<mask token>\nprint('limit=', limit)\n<mask token>\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n while n % p == 0:\n n //= p\n if n == 1 or facs >= 4:\n break\n if facs >= 4:\n nums.append(x)\n return set(nums)\n\n\ndef version_1(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return 0\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n not_used = prod % primes[i] != 0\n count = num_distinct >= 4 and not not_used\n count += search(prod * primes[i], i, num_distinct + not_used)\n count += search(prod, i + 1, num_distinct)\n return count\n return search(1, 0, 0)\n\n\ndef version_2(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit:\n return\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n if i >= len(primes):\n return\n search(prod * primes[i], i + 1, num_distinct + 1)\n search(prod, i + 1, num_distinct)\n return search(1, 0, 0)\n\n\ndef find_prods_by_num_distinct_primes(limit, primes):\n prods_by_num_distinct = [set() for _ in range(5)]\n prods_by_num_distinct[0] |= {1}\n\n def add_prods(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return\n prods_by_num_distinct[min(num_distinct, 4)].add(prod)\n add_prods(prod * primes[i], i + 1, num_distinct + 1)\n add_prods(prod, i + 1, num_distinct)\n add_prods(1, 0, 0)\n return [sorted(s) for s in prods_by_num_distinct]\n\n\nversion_2(limit)\n<mask token>\nfor n in sorted(v1):\n for mult in range(1, 401):\n if mult * n >= limit:\n break\n if mult in pset:\n continue\n if n * mult in res:\n print(n, mult, n * mult)\n res.add(n * mult)\n count += 1\n else:\n print('not enough huh...', n)\n count += (limit - 100 * n) // n\nprint(len(res))\nprint('Solution:', count)\n<mask token>\nprint('100 IQ version:', len(iq_100))\nend_time()\n",
"step-3": "<mask token>\nstart_time()\nprimes = read_primes(100)\n<mask token>\nlimit = 43268\nprint('limit=', limit)\nv1 = set()\nv2 = set()\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n while n % p == 0:\n n //= p\n if n == 1 or facs >= 4:\n break\n if facs >= 4:\n nums.append(x)\n return set(nums)\n\n\ndef version_1(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return 0\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n not_used = prod % primes[i] != 0\n count = num_distinct >= 4 and not not_used\n count += search(prod * primes[i], i, num_distinct + not_used)\n count += search(prod, i + 1, num_distinct)\n return count\n return search(1, 0, 0)\n\n\ndef version_2(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit:\n return\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n if i >= len(primes):\n return\n search(prod * primes[i], i + 1, num_distinct + 1)\n search(prod, i + 1, num_distinct)\n return search(1, 0, 0)\n\n\ndef find_prods_by_num_distinct_primes(limit, primes):\n prods_by_num_distinct = [set() for _ in range(5)]\n prods_by_num_distinct[0] |= {1}\n\n def add_prods(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return\n prods_by_num_distinct[min(num_distinct, 4)].add(prod)\n add_prods(prod * primes[i], i + 1, num_distinct + 1)\n add_prods(prod, i + 1, num_distinct)\n add_prods(1, 0, 0)\n return [sorted(s) for s in prods_by_num_distinct]\n\n\nversion_2(limit)\npset = set(primes)\nres = set()\ncount = 0\nfor n in sorted(v1):\n for mult in range(1, 401):\n if mult * n >= limit:\n break\n if mult in pset:\n continue\n if n * mult in res:\n print(n, mult, n * mult)\n res.add(n * mult)\n count += 1\n else:\n print('not enough huh...', n)\n count += (limit - 100 * n) // n\nprint(len(res))\nprint('Solution:', count)\niq_100 = version_100_iq(limit)\nprint('100 IQ version:', len(iq_100))\nend_time()\n",
"step-4": "from lib.utility import start_time, end_time\nfrom lib.prime import read_primes\nfrom bisect import bisect_left\nstart_time()\nprimes = read_primes(100)\nimport random\nlimit = 43268\nprint('limit=', limit)\nv1 = set()\nv2 = set()\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n while n % p == 0:\n n //= p\n if n == 1 or facs >= 4:\n break\n if facs >= 4:\n nums.append(x)\n return set(nums)\n\n\ndef version_1(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return 0\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n not_used = prod % primes[i] != 0\n count = num_distinct >= 4 and not not_used\n count += search(prod * primes[i], i, num_distinct + not_used)\n count += search(prod, i + 1, num_distinct)\n return count\n return search(1, 0, 0)\n\n\ndef version_2(limit):\n\n def search(prod, i, num_distinct):\n if prod >= limit:\n return\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n if i >= len(primes):\n return\n search(prod * primes[i], i + 1, num_distinct + 1)\n search(prod, i + 1, num_distinct)\n return search(1, 0, 0)\n\n\ndef find_prods_by_num_distinct_primes(limit, primes):\n prods_by_num_distinct = [set() for _ in range(5)]\n prods_by_num_distinct[0] |= {1}\n\n def add_prods(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return\n prods_by_num_distinct[min(num_distinct, 4)].add(prod)\n add_prods(prod * primes[i], i + 1, num_distinct + 1)\n add_prods(prod, i + 1, num_distinct)\n add_prods(1, 0, 0)\n return [sorted(s) for s in prods_by_num_distinct]\n\n\nversion_2(limit)\npset = set(primes)\nres = set()\ncount = 0\nfor n in sorted(v1):\n for mult in range(1, 401):\n if mult * n >= limit:\n break\n if mult in pset:\n continue\n if n * mult in res:\n print(n, mult, n * mult)\n res.add(n * mult)\n count += 1\n else:\n print('not enough huh...', n)\n count += (limit - 100 * n) // n\nprint(len(res))\nprint('Solution:', count)\niq_100 = version_100_iq(limit)\nprint('100 IQ version:', len(iq_100))\nend_time()\n",
"step-5": "from lib.utility import start_time, end_time\nfrom lib.prime import read_primes\nfrom bisect import bisect_left\nstart_time()\n\nprimes = read_primes(100)\n# limit = 10 ** 16\nimport random\n# limit = random.randint(1000, 10 ** 5)\nlimit = 43268\n# limit = 10 ** 16\nprint('limit=', limit)\nv1 = set()\nv2 = set()\n\n\ndef version_100_iq(limit):\n nums = []\n for x in range(2, limit):\n facs = 0\n n = x\n for p in primes:\n if n % p == 0:\n facs += 1\n\n while n % p == 0:\n n //= p\n\n if n == 1 or facs >= 4:\n break\n\n if facs >= 4:\n nums.append(x)\n\n return set(nums)\n\n\ndef version_1(limit):\n def search(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return 0\n\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n\n not_used = (prod % primes[i] != 0)\n count = (num_distinct >= 4) and not not_used\n count += search(prod * primes[i], i, num_distinct + not_used)\n count += search(prod, i + 1, num_distinct)\n return count\n\n return search(1, 0, 0)\n\n\ndef version_2(limit):\n def search(prod, i, num_distinct):\n if prod >= limit:\n return\n\n if prod not in v1 and num_distinct >= 4:\n v1.add(prod)\n\n if i >= len(primes):\n return\n\n search(prod * primes[i], i + 1, num_distinct + 1)\n search(prod, i + 1, num_distinct)\n\n return search(1, 0, 0)\n\n\ndef find_prods_by_num_distinct_primes(limit, primes):\n prods_by_num_distinct = [set() for _ in range(5)]\n prods_by_num_distinct[0] |= {1}\n\n def add_prods(prod, i, num_distinct):\n if prod >= limit or i >= len(primes):\n return\n\n # not_used = (prod % primes[i] != 0)\n # if not not_used:\n prods_by_num_distinct[min(num_distinct, 4)].add(prod)\n\n add_prods(prod * primes[i], i + 1, num_distinct + 1)\n add_prods(prod, i + 1, num_distinct)\n\n add_prods(1, 0, 0)\n return [sorted(s) for s in prods_by_num_distinct]\n\n\nversion_2(limit)\n\npset = set(primes)\n\nres = set()\ncount = 0\nfor n in sorted(v1):\n for mult in range(1, 401):\n if mult * n >= limit:\n break\n # if n % mult != 0 and mult in pset:\n if mult in pset:\n # assert(n * mult in v1), (n, mult)\n continue\n\n\n # print(n, mult)\n if n * mult in res:\n print(n, mult, n * mult)\n res.add(n * mult)\n count += 1\n else:\n print('not enough huh...', n)\n count += (limit - 100*n) // n\n\n\nprint(len(res))\n# n = 7 # a splitting point that seems to be the fastest\n# lo = find_prods_by_num_distinct_primes(limit, primes[:n])\n# hi = find_prods_by_num_distinct_primes(limit, primes[n:])\n\n\n# max_sol = 0\n# count = 0\n# for lo_num_distinct_primes in range(0, 5):\n# for prod in lo[lo_num_distinct_primes]:\n# for hi_num_distinct_primes in range(4 - lo_num_distinct_primes, 5):\n# # count += bisect_left(hi[hi_num_distinct_primes], limit / prod)\n# for v in hi[hi_num_distinct_primes]:\n# if v * prod < limit:\n# count += 1\n# # count += (limit - 1) // (v * prod)\n\n\nprint('Solution:', count)\n\niq_100 = version_100_iq(limit)\nprint('100 IQ version:', len(iq_100))\n\n# if count != len(iq_100):\n # print(iq_100 - v1)\n# assert count == len(iq_100)\n\n\n\nend_time()\n",
"step-ids": [
4,
5,
6,
7,
8
]
}
|
[
4,
5,
6,
7,
8
] |
import random
responses = ['Seems so','Never','Untrue','Always no matter what','You decide your fate','Not sure','Yep','Nope','Maybe','Nein','Qui','Ask the person next to you','That question is not for me']
def answer():
question = input('Ask me anything: ')
print(random.choice(responses))
answer()
secondQuestion = (input('Another question? Yes/No: '))
while secondQuestion == str('Yes'):
answer()
secondQuestion = (input('Another question? Yes/No: '))
else:
print('Thank you for asking the wise magic 8 ball')
|
normal
|
{
"blob_id": "41eef711c79fb084c9780b6d2638d863266e569d",
"index": 837,
"step-1": "<mask token>\n\n\ndef answer():\n question = input('Ask me anything: ')\n print(random.choice(responses))\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef answer():\n question = input('Ask me anything: ')\n print(random.choice(responses))\n\n\nanswer()\n<mask token>\nwhile secondQuestion == str('Yes'):\n answer()\n secondQuestion = input('Another question? Yes/No: ')\nelse:\n print('Thank you for asking the wise magic 8 ball')\n",
"step-3": "<mask token>\nresponses = ['Seems so', 'Never', 'Untrue', 'Always no matter what',\n 'You decide your fate', 'Not sure', 'Yep', 'Nope', 'Maybe', 'Nein',\n 'Qui', 'Ask the person next to you', 'That question is not for me']\n\n\ndef answer():\n question = input('Ask me anything: ')\n print(random.choice(responses))\n\n\nanswer()\nsecondQuestion = input('Another question? Yes/No: ')\nwhile secondQuestion == str('Yes'):\n answer()\n secondQuestion = input('Another question? Yes/No: ')\nelse:\n print('Thank you for asking the wise magic 8 ball')\n",
"step-4": "import random\nresponses = ['Seems so', 'Never', 'Untrue', 'Always no matter what',\n 'You decide your fate', 'Not sure', 'Yep', 'Nope', 'Maybe', 'Nein',\n 'Qui', 'Ask the person next to you', 'That question is not for me']\n\n\ndef answer():\n question = input('Ask me anything: ')\n print(random.choice(responses))\n\n\nanswer()\nsecondQuestion = input('Another question? Yes/No: ')\nwhile secondQuestion == str('Yes'):\n answer()\n secondQuestion = input('Another question? Yes/No: ')\nelse:\n print('Thank you for asking the wise magic 8 ball')\n",
"step-5": "import random\nresponses = ['Seems so','Never','Untrue','Always no matter what','You decide your fate','Not sure','Yep','Nope','Maybe','Nein','Qui','Ask the person next to you','That question is not for me']\n\ndef answer():\n question = input('Ask me anything: ')\n print(random.choice(responses))\nanswer()\n\nsecondQuestion = (input('Another question? Yes/No: '))\nwhile secondQuestion == str('Yes'):\n answer()\n secondQuestion = (input('Another question? Yes/No: '))\n \nelse: \n print('Thank you for asking the wise magic 8 ball')\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
from math import gcd
from random import randint, choice
task = """6. Реализовать алгоритм построения ПСП методом Фиббоначи с
запаздываниями. Обосновать выбор коэффициентов алгоритма. Для
начального заполнения использовать стандартную линейную конгруэнтную
ПСП с выбранным периодом. Реализовать возможность для пользователя
вводить коэффициенты заранее."""
def factor(n):
result = []
d = 2
while d * d <= n:
if n % d == 0:
result.append(d)
n //= d
else:
d += 1
if n > 1:
result.append(n)
return result
def get_coeff(period):
c = randint(0, period)
while gcd(c, period) != 1:
c += 1
b = 2
a = None
factor_result = factor(period)
while b <= period:
if all([b % p == 0 for p in factor_result]):
if period % 4 == 0:
if b % 4 == 0:
a = b + 1
break
else:
a = b + 1
break
b += 1
return a, c, randint(2, period)
def gen_linear_congruential(period):
coeff_a, coeff_c, x0 = get_coeff(period)
result = [x0]
for i in range(1, period):
result.append((coeff_a * result[i - 1] + coeff_c) % period)
return result
def LFG(init, lst, m, count):
result = init.copy()
for i in range(len(init), count):
result.append(sum([result[len(result) - j] for j in lst]) % (2 ** m))
return result
delays = input("Параметры запаздывания: ")
if not delays:
# y = x^k + x^j + 1 must be primitive
delays = choice([[7, 10], [5, 17], [24, 55], [65, 71], [128, 159]])
k = delays[1] + 10
m = 8
print(f"delays = {delays}, k = {k}, m = {m}")
else:
delays = [int(item) for item in delays.split()]
k = int(input("Длина начального заполнения: "))
m = int(input("Модуль: "))
initial_filling = gen_linear_congruential(k)
print(LFG(initial_filling, delays, m, 1000))
|
normal
|
{
"blob_id": "11e9d25c30c8c9945cfa3c234ffa1aab98d1869e",
"index": 8023,
"step-1": "<mask token>\n\n\ndef factor(n):\n result = []\n d = 2\n while d * d <= n:\n if n % d == 0:\n result.append(d)\n n //= d\n else:\n d += 1\n if n > 1:\n result.append(n)\n return result\n\n\ndef get_coeff(period):\n c = randint(0, period)\n while gcd(c, period) != 1:\n c += 1\n b = 2\n a = None\n factor_result = factor(period)\n while b <= period:\n if all([(b % p == 0) for p in factor_result]):\n if period % 4 == 0:\n if b % 4 == 0:\n a = b + 1\n break\n else:\n a = b + 1\n break\n b += 1\n return a, c, randint(2, period)\n\n\ndef gen_linear_congruential(period):\n coeff_a, coeff_c, x0 = get_coeff(period)\n result = [x0]\n for i in range(1, period):\n result.append((coeff_a * result[i - 1] + coeff_c) % period)\n return result\n\n\ndef LFG(init, lst, m, count):\n result = init.copy()\n for i in range(len(init), count):\n result.append(sum([result[len(result) - j] for j in lst]) % 2 ** m)\n return result\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef factor(n):\n result = []\n d = 2\n while d * d <= n:\n if n % d == 0:\n result.append(d)\n n //= d\n else:\n d += 1\n if n > 1:\n result.append(n)\n return result\n\n\ndef get_coeff(period):\n c = randint(0, period)\n while gcd(c, period) != 1:\n c += 1\n b = 2\n a = None\n factor_result = factor(period)\n while b <= period:\n if all([(b % p == 0) for p in factor_result]):\n if period % 4 == 0:\n if b % 4 == 0:\n a = b + 1\n break\n else:\n a = b + 1\n break\n b += 1\n return a, c, randint(2, period)\n\n\ndef gen_linear_congruential(period):\n coeff_a, coeff_c, x0 = get_coeff(period)\n result = [x0]\n for i in range(1, period):\n result.append((coeff_a * result[i - 1] + coeff_c) % period)\n return result\n\n\ndef LFG(init, lst, m, count):\n result = init.copy()\n for i in range(len(init), count):\n result.append(sum([result[len(result) - j] for j in lst]) % 2 ** m)\n return result\n\n\n<mask token>\nif not delays:\n delays = choice([[7, 10], [5, 17], [24, 55], [65, 71], [128, 159]])\n k = delays[1] + 10\n m = 8\n print(f'delays = {delays}, k = {k}, m = {m}')\nelse:\n delays = [int(item) for item in delays.split()]\n k = int(input('Длина начального заполнения: '))\n m = int(input('Модуль: '))\n<mask token>\nprint(LFG(initial_filling, delays, m, 1000))\n",
"step-3": "<mask token>\ntask = \"\"\"6. Реализовать алгоритм построения ПСП методом Фиббоначи с\nзапаздываниями. Обосновать выбор коэффициентов алгоритма. Для\nначального заполнения использовать стандартную линейную конгруэнтную\nПСП с выбранным периодом. Реализовать возможность для пользователя\nвводить коэффициенты заранее.\"\"\"\n\n\ndef factor(n):\n result = []\n d = 2\n while d * d <= n:\n if n % d == 0:\n result.append(d)\n n //= d\n else:\n d += 1\n if n > 1:\n result.append(n)\n return result\n\n\ndef get_coeff(period):\n c = randint(0, period)\n while gcd(c, period) != 1:\n c += 1\n b = 2\n a = None\n factor_result = factor(period)\n while b <= period:\n if all([(b % p == 0) for p in factor_result]):\n if period % 4 == 0:\n if b % 4 == 0:\n a = b + 1\n break\n else:\n a = b + 1\n break\n b += 1\n return a, c, randint(2, period)\n\n\ndef gen_linear_congruential(period):\n coeff_a, coeff_c, x0 = get_coeff(period)\n result = [x0]\n for i in range(1, period):\n result.append((coeff_a * result[i - 1] + coeff_c) % period)\n return result\n\n\ndef LFG(init, lst, m, count):\n result = init.copy()\n for i in range(len(init), count):\n result.append(sum([result[len(result) - j] for j in lst]) % 2 ** m)\n return result\n\n\ndelays = input('Параметры запаздывания: ')\nif not delays:\n delays = choice([[7, 10], [5, 17], [24, 55], [65, 71], [128, 159]])\n k = delays[1] + 10\n m = 8\n print(f'delays = {delays}, k = {k}, m = {m}')\nelse:\n delays = [int(item) for item in delays.split()]\n k = int(input('Длина начального заполнения: '))\n m = int(input('Модуль: '))\ninitial_filling = gen_linear_congruential(k)\nprint(LFG(initial_filling, delays, m, 1000))\n",
"step-4": "from math import gcd\nfrom random import randint, choice\ntask = \"\"\"6. Реализовать алгоритм построения ПСП методом Фиббоначи с\nзапаздываниями. Обосновать выбор коэффициентов алгоритма. Для\nначального заполнения использовать стандартную линейную конгруэнтную\nПСП с выбранным периодом. Реализовать возможность для пользователя\nвводить коэффициенты заранее.\"\"\"\n\n\ndef factor(n):\n result = []\n d = 2\n while d * d <= n:\n if n % d == 0:\n result.append(d)\n n //= d\n else:\n d += 1\n if n > 1:\n result.append(n)\n return result\n\n\ndef get_coeff(period):\n c = randint(0, period)\n while gcd(c, period) != 1:\n c += 1\n b = 2\n a = None\n factor_result = factor(period)\n while b <= period:\n if all([(b % p == 0) for p in factor_result]):\n if period % 4 == 0:\n if b % 4 == 0:\n a = b + 1\n break\n else:\n a = b + 1\n break\n b += 1\n return a, c, randint(2, period)\n\n\ndef gen_linear_congruential(period):\n coeff_a, coeff_c, x0 = get_coeff(period)\n result = [x0]\n for i in range(1, period):\n result.append((coeff_a * result[i - 1] + coeff_c) % period)\n return result\n\n\ndef LFG(init, lst, m, count):\n result = init.copy()\n for i in range(len(init), count):\n result.append(sum([result[len(result) - j] for j in lst]) % 2 ** m)\n return result\n\n\ndelays = input('Параметры запаздывания: ')\nif not delays:\n delays = choice([[7, 10], [5, 17], [24, 55], [65, 71], [128, 159]])\n k = delays[1] + 10\n m = 8\n print(f'delays = {delays}, k = {k}, m = {m}')\nelse:\n delays = [int(item) for item in delays.split()]\n k = int(input('Длина начального заполнения: '))\n m = int(input('Модуль: '))\ninitial_filling = gen_linear_congruential(k)\nprint(LFG(initial_filling, delays, m, 1000))\n",
"step-5": "from math import gcd\nfrom random import randint, choice\n\ntask = \"\"\"6. Реализовать алгоритм построения ПСП методом Фиббоначи с\nзапаздываниями. Обосновать выбор коэффициентов алгоритма. Для\nначального заполнения использовать стандартную линейную конгруэнтную\nПСП с выбранным периодом. Реализовать возможность для пользователя\nвводить коэффициенты заранее.\"\"\"\n\n\ndef factor(n):\n result = []\n d = 2\n while d * d <= n:\n if n % d == 0:\n result.append(d)\n n //= d\n else:\n d += 1\n if n > 1:\n result.append(n)\n return result\n\n\ndef get_coeff(period):\n c = randint(0, period)\n while gcd(c, period) != 1:\n c += 1\n b = 2\n a = None\n factor_result = factor(period)\n while b <= period:\n if all([b % p == 0 for p in factor_result]):\n if period % 4 == 0:\n if b % 4 == 0:\n a = b + 1\n break\n else:\n a = b + 1\n break\n b += 1\n return a, c, randint(2, period)\n\n\ndef gen_linear_congruential(period):\n coeff_a, coeff_c, x0 = get_coeff(period)\n result = [x0]\n for i in range(1, period):\n result.append((coeff_a * result[i - 1] + coeff_c) % period)\n return result\n\n\ndef LFG(init, lst, m, count):\n result = init.copy()\n for i in range(len(init), count):\n result.append(sum([result[len(result) - j] for j in lst]) % (2 ** m))\n return result\n\n\ndelays = input(\"Параметры запаздывания: \")\nif not delays:\n # y = x^k + x^j + 1 must be primitive\n delays = choice([[7, 10], [5, 17], [24, 55], [65, 71], [128, 159]])\n k = delays[1] + 10\n m = 8\n print(f\"delays = {delays}, k = {k}, m = {m}\")\nelse:\n delays = [int(item) for item in delays.split()]\n k = int(input(\"Длина начального заполнения: \"))\n m = int(input(\"Модуль: \"))\ninitial_filling = gen_linear_congruential(k)\nprint(LFG(initial_filling, delays, m, 1000))\n",
"step-ids": [
4,
5,
6,
7,
8
]
}
|
[
4,
5,
6,
7,
8
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 14 09:53:10 2021
@author: kaouther
"""
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import pandas as pd
#path = '/home/kaouther/Documents/Internship/pre_process/input_files/heart_forKaouther.xlsx'
#path = '/home/kaouther/Documents/Internship/pre_process/input_files/tissues_9m_forKaouther3.xlsx'
path = '/home/kaouther/Documents/Internship/pre_process/input_files/clean/TabulaMuris_Senis_Brain.xlsx'
#path=input('enter the complete path to your input file')
#path = input('Paste the absolute path to the file') #enter the path to the heart_forKaouther.xlsx
#df = pd.read_csv(path, delimiter = "\t")
df = pd.read_excel(path)
#function de extract the last caracterfrom a string
def get_rep_name(string):
return (string[-1:])
#get columns names (samples & biological replicates)
column_names = df.columns
column_names = column_names.delete([0]) #remove gene
#get only biological replicates
biological_rep=[]
mean_replicates= dict()
for name in column_names:
if get_rep_name(name) not in biological_rep:
#print(get_rep_name(name))
biological_rep.append(name[-1:])
#dictionnary to store the sum of values of a type of biological rep and nb of iteration
for i in range (0,len(biological_rep),1):
mean_replicates['mean_replicate_'+biological_rep[i]] = [0]*len(df)
mean_replicates['nb_itteration_'+biological_rep[i]] = [0]*len(df)
for k in range (0,len(df),1):
for i in range (0, len(column_names),1):
for j in biological_rep:
if j in get_rep_name(column_names[i]):
mean_replicates['mean_replicate_'+j][k]+= df.loc[k,column_names[i]]
mean_replicates['nb_itteration_'+j][k]+=1
dico2 = dict() #store tuples sum and iteration on each line
dico3 = dict() #store the mean calculation
for i in range (0,len(biological_rep),1):
dico3['mean_replicate_'+biological_rep[i]] = [0]*len(df)
#get list of mean replicates
list_mean_replicates =[]
for i in range (0,len(biological_rep),1):
list_mean_replicates.append('mean_replicate_'+biological_rep[i])
#dico to store as a tuple the sum and iteration for each mean rep
for key in list_mean_replicates:
for key2 in mean_replicates:
if key != key2 and get_rep_name(key) == get_rep_name(key2):
print( key,key2)
dico2[key]= list(zip((mean_replicates[key]),mean_replicates[key2]))
#dico to calculate the average per gene per mean replicate
for key in dico2:
for i in range(0,len(df),1):
cal = round(dico2[key][i][0]/ dico2[key][i][1])
dico3[key][i]= cal
#store results in new df in new columns
final_df = df.copy()
for mean in list_mean_replicates:
final_df[mean] = 0
for i in range(0,len(final_df),1):
for key in list_mean_replicates:
final_df.loc[i,key] = dico3[key][i]
#export as excel the df
final_df.to_excel ('/home/kaouther/Documents/Internship/pre_process/output_files/brain_matrix.xlsx', index = False, header=True)
#final_df.to_csv('/home/kaouther/Documents/Internship/pre_process/output_files/'+'tissues_mean.csv', index = False, header=True)
#final_df.to_excel('/home/kaouther/Documents/Internship/pre_process/output_files/'+'tissues_matrix.xlsx', index = False, header=True)
#file_name= input('file name')
#final_df.to_excel(file_name+'.xlsx', index = False, header=True)
duplicateRowsDF = final_df[final_df.iloc[:,0].duplicated()]
|
normal
|
{
"blob_id": "a3588a521a87765d215fd2048407e5e54fb87e94",
"index": 4276,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_rep_name(string):\n return string[-1:]\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef get_rep_name(string):\n return string[-1:]\n\n\n<mask token>\nfor name in column_names:\n if get_rep_name(name) not in biological_rep:\n biological_rep.append(name[-1:])\nfor i in range(0, len(biological_rep), 1):\n mean_replicates['mean_replicate_' + biological_rep[i]] = [0] * len(df)\n mean_replicates['nb_itteration_' + biological_rep[i]] = [0] * len(df)\nfor k in range(0, len(df), 1):\n for i in range(0, len(column_names), 1):\n for j in biological_rep:\n if j in get_rep_name(column_names[i]):\n mean_replicates['mean_replicate_' + j][k] += df.loc[k,\n column_names[i]]\n mean_replicates['nb_itteration_' + j][k] += 1\n<mask token>\nfor i in range(0, len(biological_rep), 1):\n dico3['mean_replicate_' + biological_rep[i]] = [0] * len(df)\n<mask token>\nfor i in range(0, len(biological_rep), 1):\n list_mean_replicates.append('mean_replicate_' + biological_rep[i])\nfor key in list_mean_replicates:\n for key2 in mean_replicates:\n if key != key2 and get_rep_name(key) == get_rep_name(key2):\n print(key, key2)\n dico2[key] = list(zip(mean_replicates[key], mean_replicates[key2]))\nfor key in dico2:\n for i in range(0, len(df), 1):\n cal = round(dico2[key][i][0] / dico2[key][i][1])\n dico3[key][i] = cal\n<mask token>\nfor mean in list_mean_replicates:\n final_df[mean] = 0\nfor i in range(0, len(final_df), 1):\n for key in list_mean_replicates:\n final_df.loc[i, key] = dico3[key][i]\nfinal_df.to_excel(\n '/home/kaouther/Documents/Internship/pre_process/output_files/brain_matrix.xlsx'\n , index=False, header=True)\n<mask token>\n",
"step-4": "<mask token>\npath = (\n '/home/kaouther/Documents/Internship/pre_process/input_files/clean/TabulaMuris_Senis_Brain.xlsx'\n )\ndf = pd.read_excel(path)\n\n\ndef get_rep_name(string):\n return string[-1:]\n\n\ncolumn_names = df.columns\ncolumn_names = column_names.delete([0])\nbiological_rep = []\nmean_replicates = dict()\nfor name in column_names:\n if get_rep_name(name) not in biological_rep:\n biological_rep.append(name[-1:])\nfor i in range(0, len(biological_rep), 1):\n mean_replicates['mean_replicate_' + biological_rep[i]] = [0] * len(df)\n mean_replicates['nb_itteration_' + biological_rep[i]] = [0] * len(df)\nfor k in range(0, len(df), 1):\n for i in range(0, len(column_names), 1):\n for j in biological_rep:\n if j in get_rep_name(column_names[i]):\n mean_replicates['mean_replicate_' + j][k] += df.loc[k,\n column_names[i]]\n mean_replicates['nb_itteration_' + j][k] += 1\ndico2 = dict()\ndico3 = dict()\nfor i in range(0, len(biological_rep), 1):\n dico3['mean_replicate_' + biological_rep[i]] = [0] * len(df)\nlist_mean_replicates = []\nfor i in range(0, len(biological_rep), 1):\n list_mean_replicates.append('mean_replicate_' + biological_rep[i])\nfor key in list_mean_replicates:\n for key2 in mean_replicates:\n if key != key2 and get_rep_name(key) == get_rep_name(key2):\n print(key, key2)\n dico2[key] = list(zip(mean_replicates[key], mean_replicates[key2]))\nfor key in dico2:\n for i in range(0, len(df), 1):\n cal = round(dico2[key][i][0] / dico2[key][i][1])\n dico3[key][i] = cal\nfinal_df = df.copy()\nfor mean in list_mean_replicates:\n final_df[mean] = 0\nfor i in range(0, len(final_df), 1):\n for key in list_mean_replicates:\n final_df.loc[i, key] = dico3[key][i]\nfinal_df.to_excel(\n '/home/kaouther/Documents/Internship/pre_process/output_files/brain_matrix.xlsx'\n , index=False, header=True)\nduplicateRowsDF = final_df[final_df.iloc[:, 0].duplicated()]\n",
"step-5": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 14 09:53:10 2021\n\n@author: kaouther\n\"\"\"\n\n# -*- coding: utf-8 -*-\n\"\"\"\nSpyder Editor\n\nThis is a temporary script file.\n\"\"\"\nimport pandas as pd\n#path = '/home/kaouther/Documents/Internship/pre_process/input_files/heart_forKaouther.xlsx'\n#path = '/home/kaouther/Documents/Internship/pre_process/input_files/tissues_9m_forKaouther3.xlsx'\n\npath = '/home/kaouther/Documents/Internship/pre_process/input_files/clean/TabulaMuris_Senis_Brain.xlsx'\n#path=input('enter the complete path to your input file')\n\n#path = input('Paste the absolute path to the file') #enter the path to the heart_forKaouther.xlsx\n#df = pd.read_csv(path, delimiter = \"\\t\")\ndf = pd.read_excel(path)\n#function de extract the last caracterfrom a string\ndef get_rep_name(string):\n return (string[-1:])\n\n#get columns names (samples & biological replicates)\ncolumn_names = df.columns\ncolumn_names = column_names.delete([0]) #remove gene\n\n#get only biological replicates \nbiological_rep=[]\nmean_replicates= dict()\nfor name in column_names:\n if get_rep_name(name) not in biological_rep:\n #print(get_rep_name(name))\n biological_rep.append(name[-1:])\n \n#dictionnary to store the sum of values of a type of biological rep and nb of iteration\nfor i in range (0,len(biological_rep),1): \n mean_replicates['mean_replicate_'+biological_rep[i]] = [0]*len(df)\n mean_replicates['nb_itteration_'+biological_rep[i]] = [0]*len(df)\nfor k in range (0,len(df),1):\n \n for i in range (0, len(column_names),1):\n for j in biological_rep:\n if j in get_rep_name(column_names[i]):\n mean_replicates['mean_replicate_'+j][k]+= df.loc[k,column_names[i]]\n mean_replicates['nb_itteration_'+j][k]+=1\n\n\ndico2 = dict() #store tuples sum and iteration on each line\ndico3 = dict() #store the mean calculation \n\nfor i in range (0,len(biological_rep),1):\n dico3['mean_replicate_'+biological_rep[i]] = [0]*len(df)\n\n#get list of mean replicates\nlist_mean_replicates =[]\nfor i in range (0,len(biological_rep),1):\n list_mean_replicates.append('mean_replicate_'+biological_rep[i])\n#dico to store as a tuple the sum and iteration for each mean rep\nfor key in list_mean_replicates:\n for key2 in mean_replicates:\n if key != key2 and get_rep_name(key) == get_rep_name(key2):\n print( key,key2)\n \n dico2[key]= list(zip((mean_replicates[key]),mean_replicates[key2]))\n#dico to calculate the average per gene per mean replicate \nfor key in dico2:\n for i in range(0,len(df),1): \n cal = round(dico2[key][i][0]/ dico2[key][i][1])\n dico3[key][i]= cal\n#store results in new df in new columns\nfinal_df = df.copy()\nfor mean in list_mean_replicates:\n final_df[mean] = 0\n \nfor i in range(0,len(final_df),1):\n for key in list_mean_replicates:\n final_df.loc[i,key] = dico3[key][i]\n#export as excel the df \nfinal_df.to_excel ('/home/kaouther/Documents/Internship/pre_process/output_files/brain_matrix.xlsx', index = False, header=True)\n#final_df.to_csv('/home/kaouther/Documents/Internship/pre_process/output_files/'+'tissues_mean.csv', index = False, header=True)\n#final_df.to_excel('/home/kaouther/Documents/Internship/pre_process/output_files/'+'tissues_matrix.xlsx', index = False, header=True)\n#file_name= input('file name')\n#final_df.to_excel(file_name+'.xlsx', index = False, header=True)\n\nduplicateRowsDF = final_df[final_df.iloc[:,0].duplicated()]\n",
"step-ids": [
0,
1,
2,
3,
5
]
}
|
[
0,
1,
2,
3,
5
] |
from openfermion import QubitOperator, FermionOperator
from openfermion.transforms import jordan_wigner
from src.utils import QasmUtils, MatrixUtils
from src.ansatz_elements import AnsatzElement, DoubleExchange
import itertools
import numpy
class EfficientDoubleExchange(AnsatzElement):
def __init__(self, qubit_pair_1, qubit_pair_2, rescaled_parameter=False, parity_dependence=False, d_exc_correction=False):
self.qubit_pair_1 = qubit_pair_1
self.qubit_pair_2 = qubit_pair_2
self.rescaled_parameter = rescaled_parameter
self.parity_dependence = parity_dependence
self.d_exc_correction = d_exc_correction
super(EfficientDoubleExchange, self).__init__(element='d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),
element_type=str(self), n_var_parameters=1)
@staticmethod
def second_angle(x):
if x == 0:
return 0
else:
tan_x = numpy.tan(x)
tan_x_squared = tan_x**2
tan_y = ((-tan_x_squared - 1 + numpy.sqrt(tan_x_squared ** 2 + 6 * tan_x_squared + 1)) / (2*tan_x))
return numpy.arctan(tan_y)
# this method constructs an operation that acts approximately as a double partial exchange
@staticmethod
def double_exchange(angle, qubit_pair_1, qubit_pair_2, parity_dependence=False, d_exc_correction=False):
assert len(qubit_pair_1) == 2
assert len(qubit_pair_2) == 2
theta_1 = numpy.pi/2 - angle
qasm = ['']
# 1st exchange + 0-2
qasm.append(QasmUtils.controlled_xz(qubit_pair_2[0], qubit_pair_1[0]))
qasm.append('ry({}) q[{}];\n'.format(theta_1, qubit_pair_2[0]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[0]))
qasm.append('ry({}) q[{}];\n'.format(-theta_1, qubit_pair_2[0]))
# 2nd exchange + 1-3
qasm.append(QasmUtils.controlled_xz(qubit_pair_2[1], qubit_pair_1[1]))
qasm.append('ry({}) q[{}];\n'.format(theta_1, qubit_pair_2[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[1], qubit_pair_2[1]))
qasm.append('ry({}) q[{}];\n'.format(-theta_1, qubit_pair_2[1]))
# CZ gates
qasm.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# qasm.append('cz q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1]))
# correction 3rd order terms approximates the operation of a double exchange
if d_exc_correction:
angle_2 = DoubleExchange.second_angle(angle)
# not correcting 3rd order terms approximates the operation of a double excitation (with 3rd order error terms)
else:
angle_2 = angle
theta_2 = numpy.pi / 2 - angle_2
# 3rd exchange - 0-2
qasm.append('ry({}) q[{}];\n'.format(theta_2, qubit_pair_2[0]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[0]))
qasm.append('ry({}) q[{}];\n'.format(-theta_2, qubit_pair_2[0]))
qasm.append(QasmUtils.controlled_xz(qubit_pair_2[0], qubit_pair_1[0], reverse=True))
# 4th exchange -1-3
qasm.append('ry({}) q[{}];\n'.format(theta_2, qubit_pair_2[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[1], qubit_pair_2[1]))
qasm.append('ry({}) q[{}];\n'.format(-theta_2, qubit_pair_2[1]))
qasm.append(QasmUtils.controlled_xz(qubit_pair_2[1], qubit_pair_1[1], reverse=True))
# correcting for parameter sign
if parity_dependence:
# do not include the first qubit of the second pair
parity_qubits = list(range(min(qubit_pair_1), max(qubit_pair_1))) + list(range(min(qubit_pair_2)+1, max(qubit_pair_2)))
# ladder of CNOT used to determine the parity
cnot_ladder = ['']
for i in range(len(parity_qubits) - 1):
cnot_ladder.append('cx q[{}], q[{}];\n'.format(parity_qubits[i], parity_qubits[i+1]))
if angle > 0:
# applies a CZ correction in front, to get a negative sign for the excitation term, if the parity is 1
# (or the parity of "parity_qubits" is 0)
front = ['']
# this is the CZ that determines the sign of the excitation term
front.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# this bit determines the parity and applies a CZ to negate the correction if the parity is wrong
front += cnot_ladder
front.append('x q[{}];\n'.format(parity_qubits[-1]))
front.append('cz q[{}], q[{}];\n'.format(parity_qubits[-1], qubit_pair_2[0]))
front.append('x q[{}];\n'.format(parity_qubits[-1]))
front += cnot_ladder[::-1]
# .. positive sign for the excitation term, if the parity is 0 (or the parity of "parity_qubits" is 1)
rear = ['']
# .. sign correction
rear.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# .. parity correction
rear += cnot_ladder
rear.append('cz q[{}], q[{}];\n'.format(parity_qubits[-1], qubit_pair_2[0]))
rear += cnot_ladder[::-1]
# additional correction of states 010 and 110
rear.append('x q[{}];\n'.format(qubit_pair_2[1]))
rear.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
rear.append('x q[{}];\n'.format(qubit_pair_2[1]))
qasm = front + qasm + rear
else:
front = ['']
# sign correction
front.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# parity correction
front += cnot_ladder
front.append('cz q[{}], q[{}];\n'.format(parity_qubits[-1], qubit_pair_2[0]))
front += cnot_ladder[::-1]
rear = ['']
# sign correction
rear.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# parity correction
rear += cnot_ladder
rear.append('x q[{}];\n'.format(parity_qubits[-1]))
rear.append('cz q[{}], q[{}];\n'.format(parity_qubits[-1], qubit_pair_2[0]))
rear.append('x q[{}];\n'.format(parity_qubits[-1]))
rear += cnot_ladder[::-1]
# 010 and 011 correction
rear.append('x q[{}];\n'.format(qubit_pair_2[1]))
rear.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
rear.append('x q[{}];\n'.format(qubit_pair_2[1]))
qasm = front + qasm + rear
else:
if angle > 0:
# adding a correcting CZ gate at the end will result in a minus sign
qasm.append('cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]))
# qasm.append('cz q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1]))
else:
# adding a correcting CZ gate at the front will result in a plus sign
qasm = ['cz q[{}], q[{}];\n'.format(qubit_pair_2[0], qubit_pair_2[1]),
] \
+ qasm
# 'cz q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1])
return ''.join(qasm)
def get_qasm(self, var_parameters):
assert len(var_parameters) == 1
parameter = var_parameters[0]
# rescaled parameter (used for easier gradient optimization)
if self.rescaled_parameter:
if var_parameters[0] > 0:
parameter = var_parameters[0] + numpy.tanh(var_parameters[0]**0.5)
else:
parameter = var_parameters[0] + numpy.tanh(-(-var_parameters[0])**0.5)
return self.double_exchange(parameter, self.qubit_pair_1, self.qubit_pair_2,
parity_dependence=self.parity_dependence, d_exc_correction=self.d_exc_correction)
class EfficientDoubleExcitation2(AnsatzElement):
def __init__(self, qubit_pair_1, qubit_pair_2):
self.qubit_pair_1 = qubit_pair_1
self.qubit_pair_2 = qubit_pair_2
super(EfficientDoubleExcitation2, self).__init__(element='optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),
element_type=str(self), n_var_parameters=1)
@staticmethod
def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):
qasm = ['']
theta = angle / 8
# determine the parity of the two pairs
qasm.append('cx q[{}], q[{}];\n'.format(*qubit_pair_1))
qasm.append('x q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(*qubit_pair_2))
qasm.append('x q[{}];\n'.format(qubit_pair_2[1]))
# apply a partial swap of qubits 0 and 2, controlled by 1 and 3 ##
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[0]))
# # partial ccc_y operation
qasm.append('rz({}) q[{}];\n'.format(numpy.pi/2, qubit_pair_1[0]))
qasm.append('rx({}) q[{}];\n'.format(theta, qubit_pair_1[0])) # +
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('rx({}) q[{}];\n'.format(-theta, qubit_pair_1[0])) # -
qasm.append('h q[{}];\n'.format(qubit_pair_2[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[1])) # 0 3
qasm.append('h q[{}];\n'.format(qubit_pair_2[1]))
qasm.append('rx({}) q[{}];\n'.format(theta, qubit_pair_1[0])) # +
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('rx({}) q[{}];\n'.format(-theta, qubit_pair_1[0])) # -
qasm.append('h q[{}];\n'.format(qubit_pair_2[0]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[0])) # 0 2
qasm.append('h q[{}];\n'.format(qubit_pair_2[0]))
qasm.append('rx({}) q[{}];\n'.format(theta, qubit_pair_1[0])) # +
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('rx({}) q[{}];\n'.format(-theta, qubit_pair_1[0])) # -
qasm.append('h q[{}];\n'.format(qubit_pair_2[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[1])) # 0 3
qasm.append('h q[{}];\n'.format(qubit_pair_2[1]))
qasm.append('rx({}) q[{}];\n'.format(theta, qubit_pair_1[0])) # +
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1
qasm.append('h q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('rx({}) q[{}];\n'.format(-theta, qubit_pair_1[0])) # -
qasm.append('rz({}) q[{}];\n'.format(-numpy.pi / 2, qubit_pair_1[0]))
##### test #####
# qasm.append('h q[{}];\n'.format(qubit_pair_2[0]))
# qasm.append('cx q[{}], q[{}];\n'.format(qubit_pair_1[0], qubit_pair_2[0])) # 0 2
# qasm.append('h q[{}];\n'.format(qubit_pair_2[0]))
# ###############
# partial ccc_y operation ############ to here
qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0], reverse=True))
# correct for parity determination
qasm.append('x q[{}];\n'.format(qubit_pair_1[1]))
qasm.append('cx q[{}], q[{}];\n'.format(*qubit_pair_1))
qasm.append('x q[{}];\n'.format(qubit_pair_2[1]))
qasm.append('cx q[{}], q[{}];\n'.format(*qubit_pair_2))
return ''.join(qasm)
def get_qasm(self, var_parameters):
assert len(var_parameters) == 1
parameter = var_parameters[0]
return self.efficient_double_excitation_2(parameter, self.qubit_pair_1, self.qubit_pair_2)
|
normal
|
{
"blob_id": "24cdbbadc8ff1c7ad5d42eeb518cb6c2b34724a2",
"index": 263,
"step-1": "<mask token>\n\n\nclass EfficientDoubleExcitation2(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n super(EfficientDoubleExcitation2, self).__init__(element=\n 'optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):\n qasm = ['']\n theta = angle / 8\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('rz({}) q[{}];\\n'.format(numpy.pi / 2, qubit_pair_1[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('rz({}) q[{}];\\n'.format(-numpy.pi / 2, qubit_pair_1[0]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0\n ], reverse=True))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n return ''.join(qasm)\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass EfficientDoubleExchange(AnsatzElement):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass EfficientDoubleExcitation2(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n super(EfficientDoubleExcitation2, self).__init__(element=\n 'optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):\n qasm = ['']\n theta = angle / 8\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('rz({}) q[{}];\\n'.format(numpy.pi / 2, qubit_pair_1[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('rz({}) q[{}];\\n'.format(-numpy.pi / 2, qubit_pair_1[0]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0\n ], reverse=True))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n return ''.join(qasm)\n\n def get_qasm(self, var_parameters):\n assert len(var_parameters) == 1\n parameter = var_parameters[0]\n return self.efficient_double_excitation_2(parameter, self.\n qubit_pair_1, self.qubit_pair_2)\n",
"step-3": "<mask token>\n\n\nclass EfficientDoubleExchange(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2, rescaled_parameter=False,\n parity_dependence=False, d_exc_correction=False):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n self.rescaled_parameter = rescaled_parameter\n self.parity_dependence = parity_dependence\n self.d_exc_correction = d_exc_correction\n super(EfficientDoubleExchange, self).__init__(element=\n 'd_exc {}, {}'.format(qubit_pair_1, qubit_pair_2), element_type\n =str(self), n_var_parameters=1)\n <mask token>\n <mask token>\n <mask token>\n\n\nclass EfficientDoubleExcitation2(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n super(EfficientDoubleExcitation2, self).__init__(element=\n 'optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):\n qasm = ['']\n theta = angle / 8\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('rz({}) q[{}];\\n'.format(numpy.pi / 2, qubit_pair_1[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('rz({}) q[{}];\\n'.format(-numpy.pi / 2, qubit_pair_1[0]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0\n ], reverse=True))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n return ''.join(qasm)\n\n def get_qasm(self, var_parameters):\n assert len(var_parameters) == 1\n parameter = var_parameters[0]\n return self.efficient_double_excitation_2(parameter, self.\n qubit_pair_1, self.qubit_pair_2)\n",
"step-4": "<mask token>\n\n\nclass EfficientDoubleExchange(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2, rescaled_parameter=False,\n parity_dependence=False, d_exc_correction=False):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n self.rescaled_parameter = rescaled_parameter\n self.parity_dependence = parity_dependence\n self.d_exc_correction = d_exc_correction\n super(EfficientDoubleExchange, self).__init__(element=\n 'd_exc {}, {}'.format(qubit_pair_1, qubit_pair_2), element_type\n =str(self), n_var_parameters=1)\n\n @staticmethod\n def second_angle(x):\n if x == 0:\n return 0\n else:\n tan_x = numpy.tan(x)\n tan_x_squared = tan_x ** 2\n tan_y = (-tan_x_squared - 1 + numpy.sqrt(tan_x_squared ** 2 + 6 *\n tan_x_squared + 1)) / (2 * tan_x)\n return numpy.arctan(tan_y)\n <mask token>\n <mask token>\n\n\nclass EfficientDoubleExcitation2(AnsatzElement):\n\n def __init__(self, qubit_pair_1, qubit_pair_2):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n super(EfficientDoubleExcitation2, self).__init__(element=\n 'optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):\n qasm = ['']\n theta = angle / 8\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('rz({}) q[{}];\\n'.format(numpy.pi / 2, qubit_pair_1[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_2[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0],\n qubit_pair_1[1]))\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0]))\n qasm.append('rz({}) q[{}];\\n'.format(-numpy.pi / 2, qubit_pair_1[0]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0\n ], reverse=True))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n return ''.join(qasm)\n\n def get_qasm(self, var_parameters):\n assert len(var_parameters) == 1\n parameter = var_parameters[0]\n return self.efficient_double_excitation_2(parameter, self.\n qubit_pair_1, self.qubit_pair_2)\n",
"step-5": "from openfermion import QubitOperator, FermionOperator\nfrom openfermion.transforms import jordan_wigner\n\nfrom src.utils import QasmUtils, MatrixUtils\nfrom src.ansatz_elements import AnsatzElement, DoubleExchange\n\nimport itertools\nimport numpy\n\n\nclass EfficientDoubleExchange(AnsatzElement):\n def __init__(self, qubit_pair_1, qubit_pair_2, rescaled_parameter=False, parity_dependence=False, d_exc_correction=False):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n self.rescaled_parameter = rescaled_parameter\n self.parity_dependence = parity_dependence\n self.d_exc_correction = d_exc_correction\n super(EfficientDoubleExchange, self).__init__(element='d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def second_angle(x):\n if x == 0:\n return 0\n else:\n tan_x = numpy.tan(x)\n tan_x_squared = tan_x**2\n tan_y = ((-tan_x_squared - 1 + numpy.sqrt(tan_x_squared ** 2 + 6 * tan_x_squared + 1)) / (2*tan_x))\n return numpy.arctan(tan_y)\n\n # this method constructs an operation that acts approximately as a double partial exchange\n @staticmethod\n def double_exchange(angle, qubit_pair_1, qubit_pair_2, parity_dependence=False, d_exc_correction=False):\n assert len(qubit_pair_1) == 2\n assert len(qubit_pair_2) == 2\n theta_1 = numpy.pi/2 - angle\n\n qasm = ['']\n\n # 1st exchange + 0-2\n qasm.append(QasmUtils.controlled_xz(qubit_pair_2[0], qubit_pair_1[0]))\n qasm.append('ry({}) q[{}];\\n'.format(theta_1, qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[0]))\n qasm.append('ry({}) q[{}];\\n'.format(-theta_1, qubit_pair_2[0]))\n\n # 2nd exchange + 1-3\n qasm.append(QasmUtils.controlled_xz(qubit_pair_2[1], qubit_pair_1[1]))\n qasm.append('ry({}) q[{}];\\n'.format(theta_1, qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[1], qubit_pair_2[1]))\n qasm.append('ry({}) q[{}];\\n'.format(-theta_1, qubit_pair_2[1]))\n\n # CZ gates\n qasm.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # qasm.append('cz q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1]))\n\n # correction 3rd order terms approximates the operation of a double exchange\n if d_exc_correction:\n angle_2 = DoubleExchange.second_angle(angle)\n # not correcting 3rd order terms approximates the operation of a double excitation (with 3rd order error terms)\n else:\n angle_2 = angle\n theta_2 = numpy.pi / 2 - angle_2\n\n # 3rd exchange - 0-2\n qasm.append('ry({}) q[{}];\\n'.format(theta_2, qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[0]))\n qasm.append('ry({}) q[{}];\\n'.format(-theta_2, qubit_pair_2[0]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_2[0], qubit_pair_1[0], reverse=True))\n\n # 4th exchange -1-3\n qasm.append('ry({}) q[{}];\\n'.format(theta_2, qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[1], qubit_pair_2[1]))\n qasm.append('ry({}) q[{}];\\n'.format(-theta_2, qubit_pair_2[1]))\n qasm.append(QasmUtils.controlled_xz(qubit_pair_2[1], qubit_pair_1[1], reverse=True))\n\n # correcting for parameter sign\n if parity_dependence:\n # do not include the first qubit of the second pair\n parity_qubits = list(range(min(qubit_pair_1), max(qubit_pair_1))) + list(range(min(qubit_pair_2)+1, max(qubit_pair_2)))\n\n # ladder of CNOT used to determine the parity\n cnot_ladder = ['']\n for i in range(len(parity_qubits) - 1):\n cnot_ladder.append('cx q[{}], q[{}];\\n'.format(parity_qubits[i], parity_qubits[i+1]))\n\n if angle > 0:\n # applies a CZ correction in front, to get a negative sign for the excitation term, if the parity is 1\n # (or the parity of \"parity_qubits\" is 0)\n front = ['']\n # this is the CZ that determines the sign of the excitation term\n front.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # this bit determines the parity and applies a CZ to negate the correction if the parity is wrong\n front += cnot_ladder\n front.append('x q[{}];\\n'.format(parity_qubits[-1]))\n front.append('cz q[{}], q[{}];\\n'.format(parity_qubits[-1], qubit_pair_2[0]))\n front.append('x q[{}];\\n'.format(parity_qubits[-1]))\n front += cnot_ladder[::-1]\n\n # .. positive sign for the excitation term, if the parity is 0 (or the parity of \"parity_qubits\" is 1)\n rear = ['']\n # .. sign correction\n rear.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # .. parity correction\n rear += cnot_ladder\n rear.append('cz q[{}], q[{}];\\n'.format(parity_qubits[-1], qubit_pair_2[0]))\n rear += cnot_ladder[::-1]\n # additional correction of states 010 and 110\n rear.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n rear.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n rear.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n\n qasm = front + qasm + rear\n else:\n front = ['']\n # sign correction\n front.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # parity correction\n front += cnot_ladder\n front.append('cz q[{}], q[{}];\\n'.format(parity_qubits[-1], qubit_pair_2[0]))\n front += cnot_ladder[::-1]\n\n rear = ['']\n # sign correction\n rear.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # parity correction\n rear += cnot_ladder\n rear.append('x q[{}];\\n'.format(parity_qubits[-1]))\n rear.append('cz q[{}], q[{}];\\n'.format(parity_qubits[-1], qubit_pair_2[0]))\n rear.append('x q[{}];\\n'.format(parity_qubits[-1]))\n rear += cnot_ladder[::-1]\n # 010 and 011 correction\n rear.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n rear.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n rear.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n\n qasm = front + qasm + rear\n else:\n if angle > 0:\n # adding a correcting CZ gate at the end will result in a minus sign\n qasm.append('cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]))\n # qasm.append('cz q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1]))\n\n else:\n # adding a correcting CZ gate at the front will result in a plus sign\n qasm = ['cz q[{}], q[{}];\\n'.format(qubit_pair_2[0], qubit_pair_2[1]),\n ] \\\n + qasm\n # 'cz q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1])\n return ''.join(qasm)\n\n def get_qasm(self, var_parameters):\n assert len(var_parameters) == 1\n parameter = var_parameters[0]\n\n # rescaled parameter (used for easier gradient optimization)\n if self.rescaled_parameter:\n if var_parameters[0] > 0:\n parameter = var_parameters[0] + numpy.tanh(var_parameters[0]**0.5)\n else:\n parameter = var_parameters[0] + numpy.tanh(-(-var_parameters[0])**0.5)\n\n return self.double_exchange(parameter, self.qubit_pair_1, self.qubit_pair_2,\n parity_dependence=self.parity_dependence, d_exc_correction=self.d_exc_correction)\n\n\nclass EfficientDoubleExcitation2(AnsatzElement):\n def __init__(self, qubit_pair_1, qubit_pair_2):\n self.qubit_pair_1 = qubit_pair_1\n self.qubit_pair_2 = qubit_pair_2\n super(EfficientDoubleExcitation2, self).__init__(element='optimized_d_exc {}, {}'.format(qubit_pair_1, qubit_pair_2),\n element_type=str(self), n_var_parameters=1)\n\n @staticmethod\n def efficient_double_excitation_2(angle, qubit_pair_1, qubit_pair_2):\n qasm = ['']\n theta = angle / 8\n\n # determine the parity of the two pairs\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n\n # apply a partial swap of qubits 0 and 2, controlled by 1 and 3 ##\n\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[0]))\n # # partial ccc_y operation\n qasm.append('rz({}) q[{}];\\n'.format(numpy.pi/2, qubit_pair_1[0]))\n\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0])) # +\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0])) # -\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[1])) # 0 3\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0])) # +\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0])) # -\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[0])) # 0 2\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0])) # +\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0])) # -\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[1])) # 0 3\n qasm.append('h q[{}];\\n'.format(qubit_pair_2[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(theta, qubit_pair_1[0])) # +\n\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_1[1])) # 0 1\n qasm.append('h q[{}];\\n'.format(qubit_pair_1[1]))\n\n qasm.append('rx({}) q[{}];\\n'.format(-theta, qubit_pair_1[0])) # -\n\n qasm.append('rz({}) q[{}];\\n'.format(-numpy.pi / 2, qubit_pair_1[0]))\n\n ##### test #####\n # qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n # qasm.append('cx q[{}], q[{}];\\n'.format(qubit_pair_1[0], qubit_pair_2[0])) # 0 2\n # qasm.append('h q[{}];\\n'.format(qubit_pair_2[0]))\n # ###############\n\n # partial ccc_y operation ############ to here\n\n qasm.append(QasmUtils.controlled_xz(qubit_pair_1[0], qubit_pair_2[0], reverse=True))\n\n # correct for parity determination\n qasm.append('x q[{}];\\n'.format(qubit_pair_1[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_1))\n qasm.append('x q[{}];\\n'.format(qubit_pair_2[1]))\n qasm.append('cx q[{}], q[{}];\\n'.format(*qubit_pair_2))\n\n return ''.join(qasm)\n\n def get_qasm(self, var_parameters):\n assert len(var_parameters) == 1\n parameter = var_parameters[0]\n\n return self.efficient_double_excitation_2(parameter, self.qubit_pair_1, self.qubit_pair_2)\n\n",
"step-ids": [
3,
5,
6,
7,
11
]
}
|
[
3,
5,
6,
7,
11
] |
import random
import copy
random.seed(42)
import csv
import torch
import time
import statistics
import wandb
from model import Net, LinearRegression, LogisticRegression
def byGuide(data, val=None, test=None):
val_guides = val
if val == None:
val_guides = [
"GGGTGGGGGGAGTTTGCTCCTGG",
"GACCCCCTCCACCCCGCCTCCGG",
"GGCCTCCCCAAAGCCTGGCCAGG",
"GAACACAAAGCATAGACTGCGGG"
]
test_guides = test
if test==None:
test_guides = [
"GCAAAACTCAACCCTACCCCAGG",
"GGCCCAGACTGAGCACGTGATGG",
"GGGAAAGACCCAGCATCCGTGGG",
"GGAATCCCTTCTGCAGCACCTGG",
"GTGAGTGAGTGTGTGCGTGTGGG",
"GATGATGATGCCCCGGGCGTTGG",
"GCCGGAGGGGTTTGCACAGAAGG"
]
train_set = []
val_set = []
test_set = []
for pair in data:
pair['off'] = torch.tensor([1., 0.])
if pair['grna_target_sequence'] in val_guides:
val_set.append(pair)
elif pair['grna_target_sequence'] in test_guides:
test_set.append(pair)
else:
train_set.append(pair)
return [train_set, val_set, test_set]
def byTarget(data, train=.7, val=.1, test=.2):
random.shuffle(data)
train_set = []
val_set = []
test_set = []
for i in range(len(data)):
if i <= len(data) * train:
train_set.append(data[i])
elif i <= len(data) * (train + val):
val_set.append(data[i])
else:
test_set.append(data[i])
return [train_set, val_set, test_set]
def byStudy(data, val=None, test=None):
val_studies = val
if val == None:
val_studies = [
'Anderson',
'Ran',
]
test_studies = test
if test==None:
test_studies = [
'Kim',
'Tsai',
'Cho',
]
train_set = []
val_set = []
test_set = []
for pair in data:
pair['off'] = torch.tensor([1., 0.])
if pair['study_name'] in val_studies:
val_set.append(pair)
elif pair['study_name'] in test_studies:
test_set.append(pair)
else:
train_set.append(pair)
return [train_set, val_set, test_set]
def one_hot(data, sign='+'):
sins = None
sequence = None
data = data.lower()
for n in data:
one_hot = torch.zeros((1, 4))
if n =='a':
one_hot[0][0] = 1
elif n == 'c':
one_hot[0][1] = 1
elif n == 'g':
one_hot[0][2] = 1
elif n == 't':
one_hot[0][3] = 1
if sins == None:
sequence = copy.deepcopy(one_hot)
sins = 1
else:
sequence = torch.cat((sequence, one_hot), dim=0)
if list(sequence.size())[0] < 23:
for i in range(23 - list(sequence.size())[0]):
sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0)
if list(sequence.size())[0] > 23:
sequence = sequence[:23]
if sign == '-':
sequence = torch.flip(sequence, [1])
return sequence
# import numpy as np
def dataLoader(file="crisprsql.csv", batch=64, mode="target"):
ftime = time.monotonic()
with open(file) as f:
d = list(csv.DictReader(f))
if mode == "study":
loadData = byStudy(d)
elif mode == "guide":
loadData = byGuide(d)
else:
loadData = byTarget(d)
data = list()
dl = list()
train = True
for t in range(3):
average_value = list()
thisdata = list()
for line in loadData[t]:
if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:
thisdata.append([
[one_hot(line['grna_target_sequence'], line['grna_target_strand']),
one_hot(line['target_sequence'], line["target_strand"])],
torch.tensor([float(line['cleavage_freq'])])])
average_value.append(float(line['cleavage_freq']))
# if line
# mode = 0
# zero = 0
# for p in average_value:
# if p == statistics.mode(average_value):
# mode+=1
# if p <0:
# zero+=1
# print(f"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\nMedian: {statistics.median(average_value)}.\nMode: {statistics.mode(average_value)} with {mode} datapoint.\nstandard deviation: {statistics.pstdev(average_value)}.\nlowest value: {min(average_value)}.\nHighest value: {max(average_value)}\n{zero} datapoints below zero\n\n")
if train == True:
dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(4 if torch.cuda.is_available() else 4)))
print(thisdata[0][0][0].size())
train = False
else:
dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(4 if torch.cuda.is_available() else 4)))
thisdata1 = list()
for i in range(int(len(thisdata)/batch)):
ones = None
twos = None
threes = None
for j in range(batch):
if ones == None:
ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)
twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)
threes = thisdata[(i * batch) + j][1].unsqueeze_(0)
else:
ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0)
twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0)
threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0)
thisdata1.append([[ones, twos], threes])
data.append(thisdata1)
print('time to load data: ', time.monotonic() - ftime, 'seconds')
return [data, dl]
# from scipy.stats import rankdata
class CRISPRDataset(torch.utils.data.Dataset):
def __init__(self, thisdata):
self.thisdata = thisdata
def __len__(self):
return len(self.thisdata)
def __getitem__(self, idx):
item = self.thisdata[idx]
sample = {
# (23, 4)
'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),
'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0),
# (1)
'cfd': torch.squeeze(item[1]).unsqueeze_(dim=0)
}
return sample
def collate_fn(batch):
# (256, 23, 4)
# (256, 1)
# print(sum(list(batch[0]['cfd'].shape)), sum(list(batch[0]['target'].shape, sum(list(batch[0]['guide'].shape)))))
output = {}
b = {key: [] for key in batch[0].keys()}
for i in batch:
if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)) > 0 and sum(list(i['guide'].shape)) > 0 :
for key in i.keys():
b[key].append(i[key])
else:
print('1', sum(list(i['cfd'].shape)), i['cfd'])
print('2', sum(list(i['target'].shape)), len(i['target'].shape), i['target'].tolist())
print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))
for key in b.keys():
# print(b[key])s
if len(b[key]) > 0:
output[key] = torch.stack(b[key])
else:
output[key] = torch.tensor([])
# output = {
# key: torch.stack([batch[i][key] for i in range(len(batch)) \
# if all( len(batch[i][k].shape) > 0 for k in batch[0].keys() )
# ])
# for key in batch[0].keys()
# }
return output
import pandas as pd
def rankDataLoader(file="crisprsql.csv", batch=64, mode="target"):
ftime = time.monotonic()
with open(file) as f:
d = list(csv.DictReader(f))
if mode == "study":
loadData = byStudy(d)
elif mode == "guide":
loadData = byGuide(d)
else:
loadData = byTarget(d)
data = list()
dl = list()
train = True
ranks = list()
for line in d:
if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:
ranks.append(float(line['cleavage_freq']))
ranks.sort()
for t in range(3):
df = pd.DataFrame(loadData[t])
# df.drop(df.columns.difference(['cleavage_freq']), 1, inplace=True)
# pd.to_numeric(df['cleavage_freq']
pd.to_numeric(df.cleavage_freq, errors='coerce')
# cleave = df.cleavage_freq
# df_ = pd.DataFrame(loadData[t]).drop(['cleavage_freq'], 1, inplace=True)
# df_.join(cleave)
df.dropna(subset=['cleavage_freq'], inplace=True)
print(df.head())
average_value = list()
thisdata = list()
for line in df.to_dict("records"):
if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:
thisdata.append([
[one_hot(line['grna_target_sequence'], line['grna_target_strand']),
one_hot(line['target_sequence'], line["target_strand"])],
torch.tensor(ranks.index(float(line['cleavage_freq'])) / len(ranks))])
average_value.append(float(line['cleavage_freq']))
# if line
# mode = 0
# zero = 0
# for p in average_value:
# if p == statistics.mode(average_value):
# mode+=1
# if p <0:
# zero+=1
# print(f"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\nMedian: {statistics.median(average_value)}.\nMode: {statistics.mode(average_value)} with {mode} datapoint.\nstandard deviation: {statistics.pstdev(average_value)}.\nlowest value: {min(average_value)}.\nHighest value: {max(average_value)}\n{zero} datapoints below zero\n\n")
if train == True:
# dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(1 if torch.cuda.is_available() else 0)))
dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, True, collate_fn=collate_fn, num_workers=(1 if torch.cuda.is_available() else 0)))
# print(thisdata[0][0][0])
train = False
else:
# dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(1 if torch.cuda.is_available() else 0)))
dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, False, collate_fn=collate_fn, num_workers=(1 if torch.cuda.is_available() else 0)))
# import pdb; pdb.set_trace()
thisdata1 = list()
for i in range(int(len(thisdata)/batch)):
ones = None
twos = None
threes = None
for j in range(batch):
if ones == None:
ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)
twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)
threes = thisdata[(i * batch) + j][1].unsqueeze_(0)
else:
ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0)
twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0)
threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0)
thisdata1.append([[ones, twos], threes])
data.append(thisdata1)
print('time to load data: ', time.monotonic() - ftime, 'seconds')
return [data, dl]
def fullDataLoader(file="augmentcrisprsql.csv", batch=64, mode="target", target='rank'):
ftime = time.monotonic()
with open(file) as f:
d = list(csv.DictReader(f))
random.shuffle(d)
if mode == "study":
loadData = byStudy(d)
elif mode == "guide":
loadData = byGuide(d)
else:
loadData = byTarget(d)
data = list()
dl = list()
train = True
for t in range(3):
average_value = list()
thisdata = list()
q = 0
for line in loadData[t]:
if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:
if target == 'regular':
label = float(line['cleavage_freq'])
elif target == 'rank':
label = [float(line['ranked_cleavage_freq'])]
else:
label = [0, 1] if float(line['threshhold_cleavage_freq']) == 0 else [1, 0]
if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)) > 0 and sum(list(one_hot(line['target_sequence'], line["target_strand"]).shape)) > 0:
thisdata.append([
[one_hot(line['grna_target_sequence'], line['grna_target_strand']),
one_hot(line['target_sequence'], line["target_strand"])],
torch.tensor(label)])
average_value.append(label)
# print(sum(list(torch.tensor([label]).shape)), sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)), sum(list(one_hot(line['target_sequence'], line["target_strand"]).shape)))
else:
q+=1
print(sum(list(torch.tensor([label]).shape)), sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)), sum(list(one_hot(line['target_sequence'], line["target_strand"]).shape)))
# print(torch.tensor([label), len(torch.tensor([label]).shape))
print(q)
# if line
# mode = 0
# zero = 0
# for p in average_value:
# if p == statistics.mode(average_value):
# mode+=1
# if p <0:
# zero+=1
# print(f"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\nMedian: {statistics.median(average_value)}.\nMode: {statistics.mode(average_value)} with {mode} datapoint.\nstandard deviation: {statistics.pstdev(average_value)}.\nlowest value: {min(average_value)}.\nHighest value: {max(average_value)}\n{zero} datapoints below zero\n\n")
if train == True:
# dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(1 if torch.cuda.is_available() else 0)))
dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, True, collate_fn=collate_fn, num_workers=4))
# print(thisdata[0][0][0])
train = False
else:
# dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(1 if torch.cuda.is_available() else 0)))
dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, False, collate_fn=collate_fn, num_workers=4))
# import pdb; pdb.set_trace()
thisdata1 = list()
for i in range(int(len(thisdata)/batch)):
ones = None
twos = None
threes = None
for j in range(batch):
if ones == None:
ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)
twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)
threes = thisdata[(i * batch) + j][1].unsqueeze_(0)
else:
ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0)
twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0)
threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0)
thisdata1.append([[ones, twos], threes])
data.append(thisdata1)
print('time to load data: ', time.monotonic() - ftime, 'seconds')
return [data, dl]
from sklearn.metrics import roc_curve
from sklearn.metrics import roc_auc_score
from sklearn.metrics import precision_recall_curve
from sklearn.metrics import f1_score
from sklearn.metrics import auc
def roc(labels, outputs):
llabels = labels.flatten().tolist()
loutputs = outputs.flatten().tolist()
average_values = dict()
# print(len(llabels), len(loutputs))
for i in range(1, 2):
thislabel = list()
thisoutput = list()
pres = 0
totalpres = 0
for j in range(len(llabels)):
if llabels[j] <= .01 / i:
thislabel.append(0)
else:
thislabel.append(1)
if loutputs[j] <= .01 / i:
thisoutput.append(0)
else:
thisoutput.append(1)
if thislabel[-1] == thisoutput[-1]:
pres += 1
totalpres +=1
lr_precision, lr_recall, _ = precision_recall_curve(thislabel, thisoutput)
average_values[.1/i] = [roc_auc_score(thislabel, thisoutput), auc(lr_recall, lr_precision), pres/totalpres]
return average_values
def accuracy(labels, outputs, percent=.10):
llabels = labels.flatten().tolist()
loutputs = outputs.flatten().tolist()
correct = 0
total = 0
# print(llabels)
for i in range(len(llabels)):
if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 + percent) >= loutputs[i]:
correct +=1
total += 1
return correct / total
def percentError(outputs, labels):
return torch.mean(torch.abs(labels - outputs) / labels)
def Test(net, dataset, device, crit, logpath=None):
net.eval()
correct = 0
total = 0
totalloss = 0
loss = 0
with torch.no_grad():
for i, data in enumerate(dataset, 0):
inputs, labels = data[0], data[1].to(device)
outputs = net(inputs)
_, predicted = torch.max(outputs.data, 1)
total += labels.size(0)
totalloss+=1
correct += (predicted == labels).sum().item()
loss+=crit(outputs, labels)
if logpath!= None:
f = open(logpath, 'w')
f.write('Accuracy of the network on the 10000 test images: %d %%' % (
100 * correct / total))
f.write(f"total: {total} correct: {correct}")
f.write(f'loss: {loss/totalloss}')
f.close()
print('Accuracy of the network on the 10000 test images: %d %%' % (
100 * correct / total))
print(f"total: {total} correct: {correct}")
print(f'loss: {loss/totalloss}')
return 100 * correct / total
def getAllStudy():
with open("crisprsql.csv") as f:
data = csv.DictReader(f)
alls = dict()
for row in data:
if row['grna_target_sequence'] not in ["C", 'G', 'A', "T"]:
try:
alls[row['study_name']].add(row['grna_target_sequence'])
except KeyError:
alls[row["study_name"]] = set(row['grna_target_sequence'])
for r in alls:
print(r)
print(alls[r])
print(len(alls[r]))
def getallGuide():
with open("crisprsql.csv") as f:
data = csv.DictReader(f)
alls = dict()
for row in data:
if row['grna_target_sequence'] not in ["C", 'G', 'A', "T"]:
try:
alls[row['grna_target_sequence']].add(row['target_sequence'])
except KeyError:
alls[row["grna_target_sequence"]] = set(row['target_sequence'])
for r in alls:
print(r)
print(alls[r])
print(len(alls[r]))
def aboveandbelow(threshold):
with open("crisprsql.csv") as f:
data = csv.DictReader(f)
alls = dict()
above = 0
total = 0
for row in data:
if row['grna_target_sequence'] not in ["C", 'G', 'A', "T"] and row['cleavage_freq'] != '':
if float(row['cleavage_freq']) > threshold:
above+=1
total+=1
print(f'Above: {above / total}%. Below: {(total - above) / total}')
def NewTrain(epochs, optim, crit, batch_per, train_data, val_data, net, device, optim_time=None, logpath=None):
net.to(device)
#def optim, loss, and init graph data
criterion = crit
optimizer = optim
# get all labels for ROC
full_full_labels = None
for i, data in enumerate(train_data, 0):
if full_full_labels == None:
full_full_labels = data[1].to(device)
else:
full_full_labels = torch.cat((full_full_labels, data[1].to(device)), 0)
full_val_labels = None
for i, data in enumerate(val_data, 0):
if full_val_labels == None:
full_val_labels = data[1].to(device)
else:
full_val_labels = torch.cat((full_val_labels, data[1].to(device)), 0)
print("begin training")
if logpath!= None:
f = open(logpath, 'w')
#these go down, and random loss is ~2.303 so 15 will be replaced
best = 15
bestval = 15
bestepoch = 0
e = 0
# begin training loop, larget loop is for lr scedule
times = list()
# bestnet = LogisticRegression()
# bestnet.load_state_dict(copy.deepcopy(net.state_dict()))
for q in optim_time:
optimizer = q[1]
print(q[0])
# net.load_state_dict(copy.deepcopy(bestnet.state_dict())
# print(
# 'params', [p for p in net.parameters()],
# '\ngrads', [p.grad for p in net.parameters()]
# )
# epoch loop
for epoch in range(q[0]): # loop over the dataset multiple times
ftime = time.monotonic()
random.shuffle(train_data)
correct = 0
total = 0
running_loss = 0.0
# train mode
net.train()
full_output = None
full_labels = None
full_full_output = None
for i, data in enumerate(train_data, 0):
# train step
inputs, labels = data[0], data[1].to(device)
# zero the parameter gradients
optimizer.zero_grad()
# forward + backward + optimize
# t = time.monotonic()
outputs = net(inputs)
# print(time.monotonic - t, " seconds for 512 outputs")
loss = criterion(outputs, labels)
loss.backward()
# import pdb; pdb.set_trace()
# things to look at:
# - loss
# - parameters
# - inputs
# - grads
# if e % 300 == 299:
# print(
# 'loss', loss,
# # '\ninputs', inputs,
# '\nlabels', labels,
# '\noutputs', outputs
# )
optimizer.step()
_, predicted = torch.max(outputs.data, 1)
total+= labels.size(0)
correct += (predicted == labels).sum().item()
# print()
running_loss += loss.item()
if full_output == None:
full_output = outputs
else:
full_output = torch.cat((full_output, outputs), 0)
if full_labels == None:
full_labels = labels
else:
full_labels = torch.cat((full_labels, labels), 0)
# w = {f'output {i}': outputs.flatten()[i] for i in range(outputs.flatten().size(0))}
# w.update({
# f'label {i}': labels.flatten()[i] for i in range(labels.flatten().size(0))
# })
w = ({'loss': loss.item(),
'accuracy': accuracy(labels, outputs),
'percent error': percentError(outputs, labels)})
wandb.log(
# {
# 'loss': loss.item(),
# # 'params': [p for p in net.parameters()],
# # 'grads': [p.grad for p in net.parameters()],
# # 'inputs': inputs,
# f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),
# f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),
# 'accuracy': accuracy(labels, outputs)
# }
w
)
# print statistics
if i % batch_per == batch_per - 1: # print every 2000 mini-batches
print('[%d, %5d] loss: %.3f' %
(e + 1, i + 1, running_loss / batch_per))
# best = min(best, running_loss / batch_per)
# print('Accuracy of the network on the ' + str(batch_per) + 'th update: %d %%' % (
# 100 * correct / total))
wl = roc(full_labels, full_output)
wandlog = {}
for q in wl:
wandlog[f"midepoch ROC_AUC"] = wl[q][0]
wandlog[f"midepoch PR_AUC"] = wl[q][1]
wandlog[f"midepoch threshhold accuracy"] = wl[q][2]
# wandlog.update({
# "LOSS": running_loss / batch_per,
# "TYPE": "TRAIN",
# 'EPOCH': e+1,
# 'UPDATE': (e*len(train_data)) + i + 1})
w.update({'midepoch loss': loss.item(),
'midepoch accuracy': accuracy(labels, outputs),
'midepoch percent error': percentError(outputs, labels)})
wandb.log(
# {
# 'loss': loss.item(),
# # 'params': [p for p in net.parameters()],
# # 'grads': [p.grad for p in net.parameters()],
# # 'inputs': inputs,
# f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),
# f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),
# 'accuracy': accuracy(labels, outputs)
# }
w
)
wandb.log(wandlog)
if full_full_output == None:
full_full_output = full_output
else:
full_full_output = torch.cat((full_full_output, full_output), 0)
full_output = None
full_labels = None
running_loss = 0
correct = 0
total = 0
# print('[%d] loss: %.20f' %
# (epoch + 1, running_loss / total))
# if logpath != None:
# f.write('[%d] loss: %.20f' %
# (epoch + 1, running_loss / total))
if full_full_output == None:
full_full_output = full_output
else:
full_full_output = torch.cat((full_full_output, full_output), 0)
# ROC is commented out when training on 10 samples
wl = roc(full_full_labels, full_full_output)
w = {}
for q in wl:
w[f"epoch ROC_AUC"] = wl[q][0]
w[f"epoch PR_AUC"] = wl[q][1]
w[f"epoch threshhold accuracy"] = wl[q][2]
# wandlog.update({
# "LOSS": running_loss / batch_per,
# "TYPE": "TRAIN",
# 'EPOCH': e+1,
# 'UPDATE': (e + 1) *len(train_data)})
w.update({'epoch loss': loss.item(),
'epoch accuracy': accuracy(full_full_labels, full_full_output),
'epoch percent error': percentError(full_full_output, full_full_labels),
'label': labels.flatten()[0],
'output': outputs.flatten()[0]})
wandb.log(
# {
# 'loss': loss.item(),
# # 'params': [p for p in net.parameters()],
# # 'grads': [p.grad for p in net.parameters()],
# # 'inputs': inputs,
# f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),
# f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),
# 'accuracy': accuracy(labels, outputs)
# }
w
)
if w['epoch accuracy'] == 1:
PATH = f'.accuracynet.pth'
torch.save(net.state_dict(), PATH)
if w['epoch PR_AUC'] == 1:
PATH = f'.PRnet.pth'
torch.save(net.state_dict(), PATH)
if w['epoch ROC_AUC'] == 1:
PATH = f'.ROCnet.pth'
torch.save(net.state_dict(), PATH)
# wandb.log(wandlog)
full_output = None
full_full_output = None
running_loss = 0
correct = 0
total = 0
running_loss = 0
net.eval()
correct = 0
total = 0
if e % 10 == 9:
PATH = f'.net.pth'
torch.save(net.state_dict(), PATH)
#check val set
for i, data in enumerate(val_data, 0):
inputs, labels = data[0], data[1].to(device)
outputs = net(inputs)
loss = criterion(outputs, labels)
loss.backward()
running_loss += loss.item()
total+= labels.size(0)
if full_output == None:
full_output = outputs
else:
full_output = torch.cat((full_output, outputs), 0)
# if e % 300 == 299:
print(f'Validation loss for Epoch [{e +1}]: {running_loss/total}')
# if logpath != None:
# f.write(f'Validation loss for Epoch [{epoch}]: {running_loss/total}')
# wl = roc(full_val_labels, full_output)
wandlog = {}
# for q in wl:
# wandlog[f"{q} ROC_AUC"] = wl[q][0]
# wandlog[f"{q} PR_AUC"] = wl[q][1]
# wandlog[f"{q} ACCURACY"] = wl[q][2]
# wandlog.update({
# "LOSS": running_loss / len(val_data),
# "TYPE": "VAL",
# 'EPOCH': e+1,
# 'UPDATE': (e + 1)*len(train_data)})
# wandb.log(wandlog)
# best = min(best, running_loss / total)
# early stop just goes to the next lr change checkpoint
if bestval <= running_loss / total:
# if epoch >= 5:
# print('Early Stop')
# print(f"Best Validation loss: {bestval}")
# print(f"Current Validation loss: {running_loss / total}")
e = e
# break
# continue
# return
else:
# bestnet.load_state_dict(copy.deepcopy(net.state_dict()))
bestepoch = e
bestval = running_loss / total
running_loss = 0
correct = 0
total = 0
times.append(time.monotonic() - ftime)
PATH = f'.net.pth'
torch.save(net.state_dict(), PATH)
# if e % 300 == 299:
print('time for epoch: ', times[-1], 'seconds')
if logpath != None:
f.write(f'time for epoch: {times[-1]}, seconds')
e+=1
# finish training. in future dont plot and save here just return them
print('Finished Training')
print('average time per epoch: ', sum(times)/len(times), 'seconds')
if logpath != None:
f.write('Finished Training')
f.write(f'average time per epoch: {sum(times)/len(times)} seconds')
f.close()
return
# def compute_dataframe(df: pd.DataFrame, checkpoint_path: str):
# model = LogisticRegression().load_state_dict(torch.load(checkpoint_path, map_location=torch.device("cuda:0" if torch.cuda.is_available() else "cpu")))
# targets, targets_s, guides, guides_s = df.target_sequence.tolist(), df.target_strand.tolist(), df.grna_target_sequence.tolist(), df.grna_target_strand.tolist()
# preds = []
# for guide, target, guide_s, target_s in zip(guides, targets, guides_s, targets_s):
# pred = model([one_hot(guide, guide_s), one_hot(target, target_s)])
# preds.append(pred.item())
# df['pred'] = preds
# return df
def compute_dataframe(df: pd.DataFrame, checkpoint_path):
model = checkpoint_path
targets, targets_s, guides, guides_s = df.target_sequence.tolist(), df.target_strand.tolist(), df.grna_target_sequence.tolist(), df.grna_target_strand.tolist()
preds = []
for guide, target, guide_s, target_s in zip(guides, targets, guides_s, targets_s):
pred = model([one_hot(guide, guide_s), one_hot(target, target_s)])
preds.append(pred.item())
df['pred'] = preds
return df
|
normal
|
{
"blob_id": "a0059563b2eed4ca185a8e0971e8e0c80f5fb8f8",
"index": 6668,
"step-1": "<mask token>\n\n\ndef byGuide(data, val=None, test=None):\n val_guides = val\n if val == None:\n val_guides = ['GGGTGGGGGGAGTTTGCTCCTGG', 'GACCCCCTCCACCCCGCCTCCGG',\n 'GGCCTCCCCAAAGCCTGGCCAGG', 'GAACACAAAGCATAGACTGCGGG']\n test_guides = test\n if test == None:\n test_guides = ['GCAAAACTCAACCCTACCCCAGG', 'GGCCCAGACTGAGCACGTGATGG',\n 'GGGAAAGACCCAGCATCCGTGGG', 'GGAATCCCTTCTGCAGCACCTGG',\n 'GTGAGTGAGTGTGTGCGTGTGGG', 'GATGATGATGCCCCGGGCGTTGG',\n 'GCCGGAGGGGTTTGCACAGAAGG']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['grna_target_sequence'] in val_guides:\n val_set.append(pair)\n elif pair['grna_target_sequence'] in test_guides:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef byTarget(data, train=0.7, val=0.1, test=0.2):\n random.shuffle(data)\n train_set = []\n val_set = []\n test_set = []\n for i in range(len(data)):\n if i <= len(data) * train:\n train_set.append(data[i])\n elif i <= len(data) * (train + val):\n val_set.append(data[i])\n else:\n test_set.append(data[i])\n return [train_set, val_set, test_set]\n\n\ndef byStudy(data, val=None, test=None):\n val_studies = val\n if val == None:\n val_studies = ['Anderson', 'Ran']\n test_studies = test\n if test == None:\n test_studies = ['Kim', 'Tsai', 'Cho']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['study_name'] in val_studies:\n val_set.append(pair)\n elif pair['study_name'] in test_studies:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef one_hot(data, sign='+'):\n sins = None\n sequence = None\n data = data.lower()\n for n in data:\n one_hot = torch.zeros((1, 4))\n if n == 'a':\n one_hot[0][0] = 1\n elif n == 'c':\n one_hot[0][1] = 1\n elif n == 'g':\n one_hot[0][2] = 1\n elif n == 't':\n one_hot[0][3] = 1\n if sins == None:\n sequence = copy.deepcopy(one_hot)\n sins = 1\n else:\n sequence = torch.cat((sequence, one_hot), dim=0)\n if list(sequence.size())[0] < 23:\n for i in range(23 - list(sequence.size())[0]):\n sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0)\n if list(sequence.size())[0] > 23:\n sequence = sequence[:23]\n if sign == '-':\n sequence = torch.flip(sequence, [1])\n return sequence\n\n\n<mask token>\n\n\nclass CRISPRDataset(torch.utils.data.Dataset):\n\n def __init__(self, thisdata):\n self.thisdata = thisdata\n\n def __len__(self):\n return len(self.thisdata)\n\n def __getitem__(self, idx):\n item = self.thisdata[idx]\n sample = {'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),\n 'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0), 'cfd':\n torch.squeeze(item[1]).unsqueeze_(dim=0)}\n return sample\n\n\ndef collate_fn(batch):\n output = {}\n b = {key: [] for key in batch[0].keys()}\n for i in batch:\n if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)\n ) > 0 and sum(list(i['guide'].shape)) > 0:\n for key in i.keys():\n b[key].append(i[key])\n else:\n print('1', sum(list(i['cfd'].shape)), i['cfd'])\n print('2', sum(list(i['target'].shape)), len(i['target'].shape),\n i['target'].tolist())\n print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))\n for key in b.keys():\n if len(b[key]) > 0:\n output[key] = torch.stack(b[key])\n else:\n output[key] = torch.tensor([])\n return output\n\n\n<mask token>\n\n\ndef rankDataLoader(file='crisprsql.csv', batch=64, mode='target'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n ranks = list()\n for line in d:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n ranks.append(float(line['cleavage_freq']))\n ranks.sort()\n for t in range(3):\n df = pd.DataFrame(loadData[t])\n pd.to_numeric(df.cleavage_freq, errors='coerce')\n df.dropna(subset=['cleavage_freq'], inplace=True)\n print(df.head())\n average_value = list()\n thisdata = list()\n for line in df.to_dict('records'):\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(ranks.index(float(line['cleavage_freq'])) / len(\n ranks))])\n average_value.append(float(line['cleavage_freq']))\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=1 if torch.\n cuda.is_available() else 0))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=1 if torch\n .cuda.is_available() else 0))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\ndef fullDataLoader(file='augmentcrisprsql.csv', batch=64, mode='target',\n target='rank'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n random.shuffle(d)\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n q = 0\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n if target == 'regular':\n label = float(line['cleavage_freq'])\n elif target == 'rank':\n label = [float(line['ranked_cleavage_freq'])]\n else:\n label = [0, 1] if float(line['threshhold_cleavage_freq']\n ) == 0 else [1, 0]\n if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)) > 0 and sum(list(one_hot\n (line['target_sequence'], line['target_strand']).shape)\n ) > 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(label)])\n average_value.append(label)\n else:\n q += 1\n print(sum(list(torch.tensor([label]).shape)), sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)), sum(list(one_hot(\n line['target_sequence'], line['target_strand']).shape))\n )\n print(q)\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=4))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=4))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\n<mask token>\n\n\ndef roc(labels, outputs):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n average_values = dict()\n for i in range(1, 2):\n thislabel = list()\n thisoutput = list()\n pres = 0\n totalpres = 0\n for j in range(len(llabels)):\n if llabels[j] <= 0.01 / i:\n thislabel.append(0)\n else:\n thislabel.append(1)\n if loutputs[j] <= 0.01 / i:\n thisoutput.append(0)\n else:\n thisoutput.append(1)\n if thislabel[-1] == thisoutput[-1]:\n pres += 1\n totalpres += 1\n lr_precision, lr_recall, _ = precision_recall_curve(thislabel,\n thisoutput)\n average_values[0.1 / i] = [roc_auc_score(thislabel, thisoutput),\n auc(lr_recall, lr_precision), pres / totalpres]\n return average_values\n\n\ndef accuracy(labels, outputs, percent=0.1):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n correct = 0\n total = 0\n for i in range(len(llabels)):\n if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 +\n percent) >= loutputs[i]:\n correct += 1\n total += 1\n return correct / total\n\n\n<mask token>\n\n\ndef Test(net, dataset, device, crit, logpath=None):\n net.eval()\n correct = 0\n total = 0\n totalloss = 0\n loss = 0\n with torch.no_grad():\n for i, data in enumerate(dataset, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n totalloss += 1\n correct += (predicted == labels).sum().item()\n loss += crit(outputs, labels)\n if logpath != None:\n f = open(logpath, 'w')\n f.write('Accuracy of the network on the 10000 test images: %d %%' %\n (100 * correct / total))\n f.write(f'total: {total} correct: {correct}')\n f.write(f'loss: {loss / totalloss}')\n f.close()\n print('Accuracy of the network on the 10000 test images: %d %%' % (100 *\n correct / total))\n print(f'total: {total} correct: {correct}')\n print(f'loss: {loss / totalloss}')\n return 100 * correct / total\n\n\ndef getAllStudy():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['study_name']].add(row['grna_target_sequence'])\n except KeyError:\n alls[row['study_name']] = set(row['grna_target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef byGuide(data, val=None, test=None):\n val_guides = val\n if val == None:\n val_guides = ['GGGTGGGGGGAGTTTGCTCCTGG', 'GACCCCCTCCACCCCGCCTCCGG',\n 'GGCCTCCCCAAAGCCTGGCCAGG', 'GAACACAAAGCATAGACTGCGGG']\n test_guides = test\n if test == None:\n test_guides = ['GCAAAACTCAACCCTACCCCAGG', 'GGCCCAGACTGAGCACGTGATGG',\n 'GGGAAAGACCCAGCATCCGTGGG', 'GGAATCCCTTCTGCAGCACCTGG',\n 'GTGAGTGAGTGTGTGCGTGTGGG', 'GATGATGATGCCCCGGGCGTTGG',\n 'GCCGGAGGGGTTTGCACAGAAGG']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['grna_target_sequence'] in val_guides:\n val_set.append(pair)\n elif pair['grna_target_sequence'] in test_guides:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef byTarget(data, train=0.7, val=0.1, test=0.2):\n random.shuffle(data)\n train_set = []\n val_set = []\n test_set = []\n for i in range(len(data)):\n if i <= len(data) * train:\n train_set.append(data[i])\n elif i <= len(data) * (train + val):\n val_set.append(data[i])\n else:\n test_set.append(data[i])\n return [train_set, val_set, test_set]\n\n\ndef byStudy(data, val=None, test=None):\n val_studies = val\n if val == None:\n val_studies = ['Anderson', 'Ran']\n test_studies = test\n if test == None:\n test_studies = ['Kim', 'Tsai', 'Cho']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['study_name'] in val_studies:\n val_set.append(pair)\n elif pair['study_name'] in test_studies:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef one_hot(data, sign='+'):\n sins = None\n sequence = None\n data = data.lower()\n for n in data:\n one_hot = torch.zeros((1, 4))\n if n == 'a':\n one_hot[0][0] = 1\n elif n == 'c':\n one_hot[0][1] = 1\n elif n == 'g':\n one_hot[0][2] = 1\n elif n == 't':\n one_hot[0][3] = 1\n if sins == None:\n sequence = copy.deepcopy(one_hot)\n sins = 1\n else:\n sequence = torch.cat((sequence, one_hot), dim=0)\n if list(sequence.size())[0] < 23:\n for i in range(23 - list(sequence.size())[0]):\n sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0)\n if list(sequence.size())[0] > 23:\n sequence = sequence[:23]\n if sign == '-':\n sequence = torch.flip(sequence, [1])\n return sequence\n\n\n<mask token>\n\n\nclass CRISPRDataset(torch.utils.data.Dataset):\n\n def __init__(self, thisdata):\n self.thisdata = thisdata\n\n def __len__(self):\n return len(self.thisdata)\n\n def __getitem__(self, idx):\n item = self.thisdata[idx]\n sample = {'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),\n 'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0), 'cfd':\n torch.squeeze(item[1]).unsqueeze_(dim=0)}\n return sample\n\n\ndef collate_fn(batch):\n output = {}\n b = {key: [] for key in batch[0].keys()}\n for i in batch:\n if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)\n ) > 0 and sum(list(i['guide'].shape)) > 0:\n for key in i.keys():\n b[key].append(i[key])\n else:\n print('1', sum(list(i['cfd'].shape)), i['cfd'])\n print('2', sum(list(i['target'].shape)), len(i['target'].shape),\n i['target'].tolist())\n print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))\n for key in b.keys():\n if len(b[key]) > 0:\n output[key] = torch.stack(b[key])\n else:\n output[key] = torch.tensor([])\n return output\n\n\n<mask token>\n\n\ndef rankDataLoader(file='crisprsql.csv', batch=64, mode='target'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n ranks = list()\n for line in d:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n ranks.append(float(line['cleavage_freq']))\n ranks.sort()\n for t in range(3):\n df = pd.DataFrame(loadData[t])\n pd.to_numeric(df.cleavage_freq, errors='coerce')\n df.dropna(subset=['cleavage_freq'], inplace=True)\n print(df.head())\n average_value = list()\n thisdata = list()\n for line in df.to_dict('records'):\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(ranks.index(float(line['cleavage_freq'])) / len(\n ranks))])\n average_value.append(float(line['cleavage_freq']))\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=1 if torch.\n cuda.is_available() else 0))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=1 if torch\n .cuda.is_available() else 0))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\ndef fullDataLoader(file='augmentcrisprsql.csv', batch=64, mode='target',\n target='rank'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n random.shuffle(d)\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n q = 0\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n if target == 'regular':\n label = float(line['cleavage_freq'])\n elif target == 'rank':\n label = [float(line['ranked_cleavage_freq'])]\n else:\n label = [0, 1] if float(line['threshhold_cleavage_freq']\n ) == 0 else [1, 0]\n if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)) > 0 and sum(list(one_hot\n (line['target_sequence'], line['target_strand']).shape)\n ) > 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(label)])\n average_value.append(label)\n else:\n q += 1\n print(sum(list(torch.tensor([label]).shape)), sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)), sum(list(one_hot(\n line['target_sequence'], line['target_strand']).shape))\n )\n print(q)\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=4))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=4))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\n<mask token>\n\n\ndef roc(labels, outputs):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n average_values = dict()\n for i in range(1, 2):\n thislabel = list()\n thisoutput = list()\n pres = 0\n totalpres = 0\n for j in range(len(llabels)):\n if llabels[j] <= 0.01 / i:\n thislabel.append(0)\n else:\n thislabel.append(1)\n if loutputs[j] <= 0.01 / i:\n thisoutput.append(0)\n else:\n thisoutput.append(1)\n if thislabel[-1] == thisoutput[-1]:\n pres += 1\n totalpres += 1\n lr_precision, lr_recall, _ = precision_recall_curve(thislabel,\n thisoutput)\n average_values[0.1 / i] = [roc_auc_score(thislabel, thisoutput),\n auc(lr_recall, lr_precision), pres / totalpres]\n return average_values\n\n\ndef accuracy(labels, outputs, percent=0.1):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n correct = 0\n total = 0\n for i in range(len(llabels)):\n if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 +\n percent) >= loutputs[i]:\n correct += 1\n total += 1\n return correct / total\n\n\n<mask token>\n\n\ndef Test(net, dataset, device, crit, logpath=None):\n net.eval()\n correct = 0\n total = 0\n totalloss = 0\n loss = 0\n with torch.no_grad():\n for i, data in enumerate(dataset, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n totalloss += 1\n correct += (predicted == labels).sum().item()\n loss += crit(outputs, labels)\n if logpath != None:\n f = open(logpath, 'w')\n f.write('Accuracy of the network on the 10000 test images: %d %%' %\n (100 * correct / total))\n f.write(f'total: {total} correct: {correct}')\n f.write(f'loss: {loss / totalloss}')\n f.close()\n print('Accuracy of the network on the 10000 test images: %d %%' % (100 *\n correct / total))\n print(f'total: {total} correct: {correct}')\n print(f'loss: {loss / totalloss}')\n return 100 * correct / total\n\n\ndef getAllStudy():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['study_name']].add(row['grna_target_sequence'])\n except KeyError:\n alls[row['study_name']] = set(row['grna_target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\n<mask token>\n\n\ndef aboveandbelow(threshold):\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n above = 0\n total = 0\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T'] and row[\n 'cleavage_freq'] != '':\n if float(row['cleavage_freq']) > threshold:\n above += 1\n total += 1\n print(f'Above: {above / total}%. Below: {(total - above) / total}')\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef byGuide(data, val=None, test=None):\n val_guides = val\n if val == None:\n val_guides = ['GGGTGGGGGGAGTTTGCTCCTGG', 'GACCCCCTCCACCCCGCCTCCGG',\n 'GGCCTCCCCAAAGCCTGGCCAGG', 'GAACACAAAGCATAGACTGCGGG']\n test_guides = test\n if test == None:\n test_guides = ['GCAAAACTCAACCCTACCCCAGG', 'GGCCCAGACTGAGCACGTGATGG',\n 'GGGAAAGACCCAGCATCCGTGGG', 'GGAATCCCTTCTGCAGCACCTGG',\n 'GTGAGTGAGTGTGTGCGTGTGGG', 'GATGATGATGCCCCGGGCGTTGG',\n 'GCCGGAGGGGTTTGCACAGAAGG']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['grna_target_sequence'] in val_guides:\n val_set.append(pair)\n elif pair['grna_target_sequence'] in test_guides:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef byTarget(data, train=0.7, val=0.1, test=0.2):\n random.shuffle(data)\n train_set = []\n val_set = []\n test_set = []\n for i in range(len(data)):\n if i <= len(data) * train:\n train_set.append(data[i])\n elif i <= len(data) * (train + val):\n val_set.append(data[i])\n else:\n test_set.append(data[i])\n return [train_set, val_set, test_set]\n\n\ndef byStudy(data, val=None, test=None):\n val_studies = val\n if val == None:\n val_studies = ['Anderson', 'Ran']\n test_studies = test\n if test == None:\n test_studies = ['Kim', 'Tsai', 'Cho']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['study_name'] in val_studies:\n val_set.append(pair)\n elif pair['study_name'] in test_studies:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef one_hot(data, sign='+'):\n sins = None\n sequence = None\n data = data.lower()\n for n in data:\n one_hot = torch.zeros((1, 4))\n if n == 'a':\n one_hot[0][0] = 1\n elif n == 'c':\n one_hot[0][1] = 1\n elif n == 'g':\n one_hot[0][2] = 1\n elif n == 't':\n one_hot[0][3] = 1\n if sins == None:\n sequence = copy.deepcopy(one_hot)\n sins = 1\n else:\n sequence = torch.cat((sequence, one_hot), dim=0)\n if list(sequence.size())[0] < 23:\n for i in range(23 - list(sequence.size())[0]):\n sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0)\n if list(sequence.size())[0] > 23:\n sequence = sequence[:23]\n if sign == '-':\n sequence = torch.flip(sequence, [1])\n return sequence\n\n\n<mask token>\n\n\nclass CRISPRDataset(torch.utils.data.Dataset):\n\n def __init__(self, thisdata):\n self.thisdata = thisdata\n\n def __len__(self):\n return len(self.thisdata)\n\n def __getitem__(self, idx):\n item = self.thisdata[idx]\n sample = {'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),\n 'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0), 'cfd':\n torch.squeeze(item[1]).unsqueeze_(dim=0)}\n return sample\n\n\ndef collate_fn(batch):\n output = {}\n b = {key: [] for key in batch[0].keys()}\n for i in batch:\n if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)\n ) > 0 and sum(list(i['guide'].shape)) > 0:\n for key in i.keys():\n b[key].append(i[key])\n else:\n print('1', sum(list(i['cfd'].shape)), i['cfd'])\n print('2', sum(list(i['target'].shape)), len(i['target'].shape),\n i['target'].tolist())\n print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))\n for key in b.keys():\n if len(b[key]) > 0:\n output[key] = torch.stack(b[key])\n else:\n output[key] = torch.tensor([])\n return output\n\n\n<mask token>\n\n\ndef rankDataLoader(file='crisprsql.csv', batch=64, mode='target'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n ranks = list()\n for line in d:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n ranks.append(float(line['cleavage_freq']))\n ranks.sort()\n for t in range(3):\n df = pd.DataFrame(loadData[t])\n pd.to_numeric(df.cleavage_freq, errors='coerce')\n df.dropna(subset=['cleavage_freq'], inplace=True)\n print(df.head())\n average_value = list()\n thisdata = list()\n for line in df.to_dict('records'):\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(ranks.index(float(line['cleavage_freq'])) / len(\n ranks))])\n average_value.append(float(line['cleavage_freq']))\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=1 if torch.\n cuda.is_available() else 0))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=1 if torch\n .cuda.is_available() else 0))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\ndef fullDataLoader(file='augmentcrisprsql.csv', batch=64, mode='target',\n target='rank'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n random.shuffle(d)\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n q = 0\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n if target == 'regular':\n label = float(line['cleavage_freq'])\n elif target == 'rank':\n label = [float(line['ranked_cleavage_freq'])]\n else:\n label = [0, 1] if float(line['threshhold_cleavage_freq']\n ) == 0 else [1, 0]\n if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)) > 0 and sum(list(one_hot\n (line['target_sequence'], line['target_strand']).shape)\n ) > 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(label)])\n average_value.append(label)\n else:\n q += 1\n print(sum(list(torch.tensor([label]).shape)), sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)), sum(list(one_hot(\n line['target_sequence'], line['target_strand']).shape))\n )\n print(q)\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=4))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=4))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\n<mask token>\n\n\ndef roc(labels, outputs):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n average_values = dict()\n for i in range(1, 2):\n thislabel = list()\n thisoutput = list()\n pres = 0\n totalpres = 0\n for j in range(len(llabels)):\n if llabels[j] <= 0.01 / i:\n thislabel.append(0)\n else:\n thislabel.append(1)\n if loutputs[j] <= 0.01 / i:\n thisoutput.append(0)\n else:\n thisoutput.append(1)\n if thislabel[-1] == thisoutput[-1]:\n pres += 1\n totalpres += 1\n lr_precision, lr_recall, _ = precision_recall_curve(thislabel,\n thisoutput)\n average_values[0.1 / i] = [roc_auc_score(thislabel, thisoutput),\n auc(lr_recall, lr_precision), pres / totalpres]\n return average_values\n\n\ndef accuracy(labels, outputs, percent=0.1):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n correct = 0\n total = 0\n for i in range(len(llabels)):\n if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 +\n percent) >= loutputs[i]:\n correct += 1\n total += 1\n return correct / total\n\n\ndef percentError(outputs, labels):\n return torch.mean(torch.abs(labels - outputs) / labels)\n\n\ndef Test(net, dataset, device, crit, logpath=None):\n net.eval()\n correct = 0\n total = 0\n totalloss = 0\n loss = 0\n with torch.no_grad():\n for i, data in enumerate(dataset, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n totalloss += 1\n correct += (predicted == labels).sum().item()\n loss += crit(outputs, labels)\n if logpath != None:\n f = open(logpath, 'w')\n f.write('Accuracy of the network on the 10000 test images: %d %%' %\n (100 * correct / total))\n f.write(f'total: {total} correct: {correct}')\n f.write(f'loss: {loss / totalloss}')\n f.close()\n print('Accuracy of the network on the 10000 test images: %d %%' % (100 *\n correct / total))\n print(f'total: {total} correct: {correct}')\n print(f'loss: {loss / totalloss}')\n return 100 * correct / total\n\n\ndef getAllStudy():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['study_name']].add(row['grna_target_sequence'])\n except KeyError:\n alls[row['study_name']] = set(row['grna_target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\ndef getallGuide():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['grna_target_sequence']].add(row[\n 'target_sequence'])\n except KeyError:\n alls[row['grna_target_sequence']] = set(row[\n 'target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\ndef aboveandbelow(threshold):\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n above = 0\n total = 0\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T'] and row[\n 'cleavage_freq'] != '':\n if float(row['cleavage_freq']) > threshold:\n above += 1\n total += 1\n print(f'Above: {above / total}%. Below: {(total - above) / total}')\n\n\ndef NewTrain(epochs, optim, crit, batch_per, train_data, val_data, net,\n device, optim_time=None, logpath=None):\n net.to(device)\n criterion = crit\n optimizer = optim\n full_full_labels = None\n for i, data in enumerate(train_data, 0):\n if full_full_labels == None:\n full_full_labels = data[1].to(device)\n else:\n full_full_labels = torch.cat((full_full_labels, data[1].to(\n device)), 0)\n full_val_labels = None\n for i, data in enumerate(val_data, 0):\n if full_val_labels == None:\n full_val_labels = data[1].to(device)\n else:\n full_val_labels = torch.cat((full_val_labels, data[1].to(device\n )), 0)\n print('begin training')\n if logpath != None:\n f = open(logpath, 'w')\n best = 15\n bestval = 15\n bestepoch = 0\n e = 0\n times = list()\n for q in optim_time:\n optimizer = q[1]\n print(q[0])\n for epoch in range(q[0]):\n ftime = time.monotonic()\n random.shuffle(train_data)\n correct = 0\n total = 0\n running_loss = 0.0\n net.train()\n full_output = None\n full_labels = None\n full_full_output = None\n for i, data in enumerate(train_data, 0):\n inputs, labels = data[0], data[1].to(device)\n optimizer.zero_grad()\n outputs = net(inputs)\n loss = criterion(outputs, labels)\n loss.backward()\n optimizer.step()\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n correct += (predicted == labels).sum().item()\n running_loss += loss.item()\n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0)\n if full_labels == None:\n full_labels = labels\n else:\n full_labels = torch.cat((full_labels, labels), 0)\n w = {'loss': loss.item(), 'accuracy': accuracy(labels,\n outputs), 'percent error': percentError(outputs, labels)}\n wandb.log(w)\n if i % batch_per == batch_per - 1:\n print('[%d, %5d] loss: %.3f' % (e + 1, i + 1, \n running_loss / batch_per))\n wl = roc(full_labels, full_output)\n wandlog = {}\n for q in wl:\n wandlog[f'midepoch ROC_AUC'] = wl[q][0]\n wandlog[f'midepoch PR_AUC'] = wl[q][1]\n wandlog[f'midepoch threshhold accuracy'] = wl[q][2]\n w.update({'midepoch loss': loss.item(),\n 'midepoch accuracy': accuracy(labels, outputs),\n 'midepoch percent error': percentError(outputs,\n labels)})\n wandb.log(w)\n wandb.log(wandlog)\n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output,\n full_output), 0)\n full_output = None\n full_labels = None\n running_loss = 0\n correct = 0\n total = 0\n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output, full_output), 0\n )\n wl = roc(full_full_labels, full_full_output)\n w = {}\n for q in wl:\n w[f'epoch ROC_AUC'] = wl[q][0]\n w[f'epoch PR_AUC'] = wl[q][1]\n w[f'epoch threshhold accuracy'] = wl[q][2]\n w.update({'epoch loss': loss.item(), 'epoch accuracy': accuracy\n (full_full_labels, full_full_output), 'epoch percent error':\n percentError(full_full_output, full_full_labels), 'label':\n labels.flatten()[0], 'output': outputs.flatten()[0]})\n wandb.log(w)\n if w['epoch accuracy'] == 1:\n PATH = f'.accuracynet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch PR_AUC'] == 1:\n PATH = f'.PRnet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch ROC_AUC'] == 1:\n PATH = f'.ROCnet.pth'\n torch.save(net.state_dict(), PATH)\n full_output = None\n full_full_output = None\n running_loss = 0\n correct = 0\n total = 0\n running_loss = 0\n net.eval()\n correct = 0\n total = 0\n if e % 10 == 9:\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n for i, data in enumerate(val_data, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n loss = criterion(outputs, labels)\n loss.backward()\n running_loss += loss.item()\n total += labels.size(0)\n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0)\n print(\n f'Validation loss for Epoch [{e + 1}]: {running_loss / total}')\n wandlog = {}\n if bestval <= running_loss / total:\n e = e\n else:\n bestepoch = e\n bestval = running_loss / total\n running_loss = 0\n correct = 0\n total = 0\n times.append(time.monotonic() - ftime)\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n print('time for epoch: ', times[-1], 'seconds')\n if logpath != None:\n f.write(f'time for epoch: {times[-1]}, seconds')\n e += 1\n print('Finished Training')\n print('average time per epoch: ', sum(times) / len(times), 'seconds')\n if logpath != None:\n f.write('Finished Training')\n f.write(f'average time per epoch: {sum(times) / len(times)} seconds')\n f.close()\n return\n\n\n<mask token>\n",
"step-4": "<mask token>\n\n\ndef byGuide(data, val=None, test=None):\n val_guides = val\n if val == None:\n val_guides = ['GGGTGGGGGGAGTTTGCTCCTGG', 'GACCCCCTCCACCCCGCCTCCGG',\n 'GGCCTCCCCAAAGCCTGGCCAGG', 'GAACACAAAGCATAGACTGCGGG']\n test_guides = test\n if test == None:\n test_guides = ['GCAAAACTCAACCCTACCCCAGG', 'GGCCCAGACTGAGCACGTGATGG',\n 'GGGAAAGACCCAGCATCCGTGGG', 'GGAATCCCTTCTGCAGCACCTGG',\n 'GTGAGTGAGTGTGTGCGTGTGGG', 'GATGATGATGCCCCGGGCGTTGG',\n 'GCCGGAGGGGTTTGCACAGAAGG']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['grna_target_sequence'] in val_guides:\n val_set.append(pair)\n elif pair['grna_target_sequence'] in test_guides:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef byTarget(data, train=0.7, val=0.1, test=0.2):\n random.shuffle(data)\n train_set = []\n val_set = []\n test_set = []\n for i in range(len(data)):\n if i <= len(data) * train:\n train_set.append(data[i])\n elif i <= len(data) * (train + val):\n val_set.append(data[i])\n else:\n test_set.append(data[i])\n return [train_set, val_set, test_set]\n\n\ndef byStudy(data, val=None, test=None):\n val_studies = val\n if val == None:\n val_studies = ['Anderson', 'Ran']\n test_studies = test\n if test == None:\n test_studies = ['Kim', 'Tsai', 'Cho']\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1.0, 0.0])\n if pair['study_name'] in val_studies:\n val_set.append(pair)\n elif pair['study_name'] in test_studies:\n test_set.append(pair)\n else:\n train_set.append(pair)\n return [train_set, val_set, test_set]\n\n\ndef one_hot(data, sign='+'):\n sins = None\n sequence = None\n data = data.lower()\n for n in data:\n one_hot = torch.zeros((1, 4))\n if n == 'a':\n one_hot[0][0] = 1\n elif n == 'c':\n one_hot[0][1] = 1\n elif n == 'g':\n one_hot[0][2] = 1\n elif n == 't':\n one_hot[0][3] = 1\n if sins == None:\n sequence = copy.deepcopy(one_hot)\n sins = 1\n else:\n sequence = torch.cat((sequence, one_hot), dim=0)\n if list(sequence.size())[0] < 23:\n for i in range(23 - list(sequence.size())[0]):\n sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0)\n if list(sequence.size())[0] > 23:\n sequence = sequence[:23]\n if sign == '-':\n sequence = torch.flip(sequence, [1])\n return sequence\n\n\ndef dataLoader(file='crisprsql.csv', batch=64, mode='target'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor([float(line['cleavage_freq'])])])\n average_value.append(float(line['cleavage_freq']))\n if train == True:\n dl.append(torch.utils.data.DataLoader(thisdata, batch, True,\n num_workers=4 if torch.cuda.is_available() else 4))\n print(thisdata[0][0][0].size())\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(thisdata, batch, False,\n num_workers=4 if torch.cuda.is_available() else 4))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\nclass CRISPRDataset(torch.utils.data.Dataset):\n\n def __init__(self, thisdata):\n self.thisdata = thisdata\n\n def __len__(self):\n return len(self.thisdata)\n\n def __getitem__(self, idx):\n item = self.thisdata[idx]\n sample = {'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),\n 'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0), 'cfd':\n torch.squeeze(item[1]).unsqueeze_(dim=0)}\n return sample\n\n\ndef collate_fn(batch):\n output = {}\n b = {key: [] for key in batch[0].keys()}\n for i in batch:\n if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)\n ) > 0 and sum(list(i['guide'].shape)) > 0:\n for key in i.keys():\n b[key].append(i[key])\n else:\n print('1', sum(list(i['cfd'].shape)), i['cfd'])\n print('2', sum(list(i['target'].shape)), len(i['target'].shape),\n i['target'].tolist())\n print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))\n for key in b.keys():\n if len(b[key]) > 0:\n output[key] = torch.stack(b[key])\n else:\n output[key] = torch.tensor([])\n return output\n\n\n<mask token>\n\n\ndef rankDataLoader(file='crisprsql.csv', batch=64, mode='target'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n ranks = list()\n for line in d:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n ranks.append(float(line['cleavage_freq']))\n ranks.sort()\n for t in range(3):\n df = pd.DataFrame(loadData[t])\n pd.to_numeric(df.cleavage_freq, errors='coerce')\n df.dropna(subset=['cleavage_freq'], inplace=True)\n print(df.head())\n average_value = list()\n thisdata = list()\n for line in df.to_dict('records'):\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(ranks.index(float(line['cleavage_freq'])) / len(\n ranks))])\n average_value.append(float(line['cleavage_freq']))\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=1 if torch.\n cuda.is_available() else 0))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=1 if torch\n .cuda.is_available() else 0))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\ndef fullDataLoader(file='augmentcrisprsql.csv', batch=64, mode='target',\n target='rank'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n random.shuffle(d)\n if mode == 'study':\n loadData = byStudy(d)\n elif mode == 'guide':\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n q = 0\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']\n ) >= 0:\n if target == 'regular':\n label = float(line['cleavage_freq'])\n elif target == 'rank':\n label = [float(line['ranked_cleavage_freq'])]\n else:\n label = [0, 1] if float(line['threshhold_cleavage_freq']\n ) == 0 else [1, 0]\n if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)) > 0 and sum(list(one_hot\n (line['target_sequence'], line['target_strand']).shape)\n ) > 0:\n thisdata.append([[one_hot(line['grna_target_sequence'],\n line['grna_target_strand']), one_hot(line[\n 'target_sequence'], line['target_strand'])], torch.\n tensor(label)])\n average_value.append(label)\n else:\n q += 1\n print(sum(list(torch.tensor([label]).shape)), sum(list(\n one_hot(line['grna_target_sequence'], line[\n 'grna_target_strand']).shape)), sum(list(one_hot(\n line['target_sequence'], line['target_strand']).shape))\n )\n print(q)\n if train == True:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, True, collate_fn=collate_fn, num_workers=4))\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata),\n batch, False, collate_fn=collate_fn, num_workers=4))\n thisdata1 = list()\n for i in range(int(len(thisdata) / batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n if ones == None:\n ones = thisdata[i * batch + j][0][0].unsqueeze_(0\n ).unsqueeze_(0)\n twos = thisdata[i * batch + j][0][1].unsqueeze_(0\n ).unsqueeze_(0)\n threes = thisdata[i * batch + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[i * batch + j][0][0].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n twos = torch.cat((twos, thisdata[i * batch + j][0][1].\n unsqueeze_(0).unsqueeze_(0)), dim=0)\n threes = torch.cat((threes, thisdata[i * batch + j][1].\n unsqueeze_(0)), dim=0)\n thisdata1.append([[ones, twos], threes])\n data.append(thisdata1)\n print('time to load data: ', time.monotonic() - ftime, 'seconds')\n return [data, dl]\n\n\n<mask token>\n\n\ndef roc(labels, outputs):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n average_values = dict()\n for i in range(1, 2):\n thislabel = list()\n thisoutput = list()\n pres = 0\n totalpres = 0\n for j in range(len(llabels)):\n if llabels[j] <= 0.01 / i:\n thislabel.append(0)\n else:\n thislabel.append(1)\n if loutputs[j] <= 0.01 / i:\n thisoutput.append(0)\n else:\n thisoutput.append(1)\n if thislabel[-1] == thisoutput[-1]:\n pres += 1\n totalpres += 1\n lr_precision, lr_recall, _ = precision_recall_curve(thislabel,\n thisoutput)\n average_values[0.1 / i] = [roc_auc_score(thislabel, thisoutput),\n auc(lr_recall, lr_precision), pres / totalpres]\n return average_values\n\n\ndef accuracy(labels, outputs, percent=0.1):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n correct = 0\n total = 0\n for i in range(len(llabels)):\n if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 +\n percent) >= loutputs[i]:\n correct += 1\n total += 1\n return correct / total\n\n\ndef percentError(outputs, labels):\n return torch.mean(torch.abs(labels - outputs) / labels)\n\n\ndef Test(net, dataset, device, crit, logpath=None):\n net.eval()\n correct = 0\n total = 0\n totalloss = 0\n loss = 0\n with torch.no_grad():\n for i, data in enumerate(dataset, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n totalloss += 1\n correct += (predicted == labels).sum().item()\n loss += crit(outputs, labels)\n if logpath != None:\n f = open(logpath, 'w')\n f.write('Accuracy of the network on the 10000 test images: %d %%' %\n (100 * correct / total))\n f.write(f'total: {total} correct: {correct}')\n f.write(f'loss: {loss / totalloss}')\n f.close()\n print('Accuracy of the network on the 10000 test images: %d %%' % (100 *\n correct / total))\n print(f'total: {total} correct: {correct}')\n print(f'loss: {loss / totalloss}')\n return 100 * correct / total\n\n\ndef getAllStudy():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['study_name']].add(row['grna_target_sequence'])\n except KeyError:\n alls[row['study_name']] = set(row['grna_target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\ndef getallGuide():\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T']:\n try:\n alls[row['grna_target_sequence']].add(row[\n 'target_sequence'])\n except KeyError:\n alls[row['grna_target_sequence']] = set(row[\n 'target_sequence'])\n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n\n\ndef aboveandbelow(threshold):\n with open('crisprsql.csv') as f:\n data = csv.DictReader(f)\n alls = dict()\n above = 0\n total = 0\n for row in data:\n if row['grna_target_sequence'] not in ['C', 'G', 'A', 'T'] and row[\n 'cleavage_freq'] != '':\n if float(row['cleavage_freq']) > threshold:\n above += 1\n total += 1\n print(f'Above: {above / total}%. Below: {(total - above) / total}')\n\n\ndef NewTrain(epochs, optim, crit, batch_per, train_data, val_data, net,\n device, optim_time=None, logpath=None):\n net.to(device)\n criterion = crit\n optimizer = optim\n full_full_labels = None\n for i, data in enumerate(train_data, 0):\n if full_full_labels == None:\n full_full_labels = data[1].to(device)\n else:\n full_full_labels = torch.cat((full_full_labels, data[1].to(\n device)), 0)\n full_val_labels = None\n for i, data in enumerate(val_data, 0):\n if full_val_labels == None:\n full_val_labels = data[1].to(device)\n else:\n full_val_labels = torch.cat((full_val_labels, data[1].to(device\n )), 0)\n print('begin training')\n if logpath != None:\n f = open(logpath, 'w')\n best = 15\n bestval = 15\n bestepoch = 0\n e = 0\n times = list()\n for q in optim_time:\n optimizer = q[1]\n print(q[0])\n for epoch in range(q[0]):\n ftime = time.monotonic()\n random.shuffle(train_data)\n correct = 0\n total = 0\n running_loss = 0.0\n net.train()\n full_output = None\n full_labels = None\n full_full_output = None\n for i, data in enumerate(train_data, 0):\n inputs, labels = data[0], data[1].to(device)\n optimizer.zero_grad()\n outputs = net(inputs)\n loss = criterion(outputs, labels)\n loss.backward()\n optimizer.step()\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n correct += (predicted == labels).sum().item()\n running_loss += loss.item()\n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0)\n if full_labels == None:\n full_labels = labels\n else:\n full_labels = torch.cat((full_labels, labels), 0)\n w = {'loss': loss.item(), 'accuracy': accuracy(labels,\n outputs), 'percent error': percentError(outputs, labels)}\n wandb.log(w)\n if i % batch_per == batch_per - 1:\n print('[%d, %5d] loss: %.3f' % (e + 1, i + 1, \n running_loss / batch_per))\n wl = roc(full_labels, full_output)\n wandlog = {}\n for q in wl:\n wandlog[f'midepoch ROC_AUC'] = wl[q][0]\n wandlog[f'midepoch PR_AUC'] = wl[q][1]\n wandlog[f'midepoch threshhold accuracy'] = wl[q][2]\n w.update({'midepoch loss': loss.item(),\n 'midepoch accuracy': accuracy(labels, outputs),\n 'midepoch percent error': percentError(outputs,\n labels)})\n wandb.log(w)\n wandb.log(wandlog)\n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output,\n full_output), 0)\n full_output = None\n full_labels = None\n running_loss = 0\n correct = 0\n total = 0\n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output, full_output), 0\n )\n wl = roc(full_full_labels, full_full_output)\n w = {}\n for q in wl:\n w[f'epoch ROC_AUC'] = wl[q][0]\n w[f'epoch PR_AUC'] = wl[q][1]\n w[f'epoch threshhold accuracy'] = wl[q][2]\n w.update({'epoch loss': loss.item(), 'epoch accuracy': accuracy\n (full_full_labels, full_full_output), 'epoch percent error':\n percentError(full_full_output, full_full_labels), 'label':\n labels.flatten()[0], 'output': outputs.flatten()[0]})\n wandb.log(w)\n if w['epoch accuracy'] == 1:\n PATH = f'.accuracynet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch PR_AUC'] == 1:\n PATH = f'.PRnet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch ROC_AUC'] == 1:\n PATH = f'.ROCnet.pth'\n torch.save(net.state_dict(), PATH)\n full_output = None\n full_full_output = None\n running_loss = 0\n correct = 0\n total = 0\n running_loss = 0\n net.eval()\n correct = 0\n total = 0\n if e % 10 == 9:\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n for i, data in enumerate(val_data, 0):\n inputs, labels = data[0], data[1].to(device)\n outputs = net(inputs)\n loss = criterion(outputs, labels)\n loss.backward()\n running_loss += loss.item()\n total += labels.size(0)\n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0)\n print(\n f'Validation loss for Epoch [{e + 1}]: {running_loss / total}')\n wandlog = {}\n if bestval <= running_loss / total:\n e = e\n else:\n bestepoch = e\n bestval = running_loss / total\n running_loss = 0\n correct = 0\n total = 0\n times.append(time.monotonic() - ftime)\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n print('time for epoch: ', times[-1], 'seconds')\n if logpath != None:\n f.write(f'time for epoch: {times[-1]}, seconds')\n e += 1\n print('Finished Training')\n print('average time per epoch: ', sum(times) / len(times), 'seconds')\n if logpath != None:\n f.write('Finished Training')\n f.write(f'average time per epoch: {sum(times) / len(times)} seconds')\n f.close()\n return\n\n\ndef compute_dataframe(df: pd.DataFrame, checkpoint_path):\n model = checkpoint_path\n targets, targets_s, guides, guides_s = df.target_sequence.tolist(\n ), df.target_strand.tolist(), df.grna_target_sequence.tolist(\n ), df.grna_target_strand.tolist()\n preds = []\n for guide, target, guide_s, target_s in zip(guides, targets, guides_s,\n targets_s):\n pred = model([one_hot(guide, guide_s), one_hot(target, target_s)])\n preds.append(pred.item())\n df['pred'] = preds\n return df\n",
"step-5": "import random\nimport copy\nrandom.seed(42)\nimport csv\nimport torch\nimport time\nimport statistics\nimport wandb\nfrom model import Net, LinearRegression, LogisticRegression\n\ndef byGuide(data, val=None, test=None):\n val_guides = val\n if val == None:\n val_guides = [\n \"GGGTGGGGGGAGTTTGCTCCTGG\",\n \"GACCCCCTCCACCCCGCCTCCGG\",\n \"GGCCTCCCCAAAGCCTGGCCAGG\",\n \"GAACACAAAGCATAGACTGCGGG\"\n \n ]\n test_guides = test\n if test==None:\n test_guides = [\n \"GCAAAACTCAACCCTACCCCAGG\",\n \"GGCCCAGACTGAGCACGTGATGG\",\n \"GGGAAAGACCCAGCATCCGTGGG\",\n \"GGAATCCCTTCTGCAGCACCTGG\",\n \"GTGAGTGAGTGTGTGCGTGTGGG\",\n \"GATGATGATGCCCCGGGCGTTGG\",\n \"GCCGGAGGGGTTTGCACAGAAGG\"\n ]\n \n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1., 0.])\n if pair['grna_target_sequence'] in val_guides:\n val_set.append(pair)\n elif pair['grna_target_sequence'] in test_guides:\n test_set.append(pair)\n else: \n train_set.append(pair)\n return [train_set, val_set, test_set] \n\ndef byTarget(data, train=.7, val=.1, test=.2):\n random.shuffle(data)\n train_set = []\n val_set = []\n test_set = []\n for i in range(len(data)):\n if i <= len(data) * train:\n train_set.append(data[i])\n elif i <= len(data) * (train + val):\n val_set.append(data[i])\n else:\n test_set.append(data[i])\n return [train_set, val_set, test_set] \n\n\n\n\ndef byStudy(data, val=None, test=None):\n val_studies = val\n if val == None:\n val_studies = [\n 'Anderson',\n 'Ran',\n \n ]\n test_studies = test\n if test==None:\n test_studies = [\n 'Kim',\n 'Tsai',\n 'Cho',\n ]\n train_set = []\n val_set = []\n test_set = []\n for pair in data:\n pair['off'] = torch.tensor([1., 0.])\n if pair['study_name'] in val_studies:\n val_set.append(pair)\n elif pair['study_name'] in test_studies:\n test_set.append(pair)\n else: \n train_set.append(pair)\n return [train_set, val_set, test_set] \n\n\n\ndef one_hot(data, sign='+'):\n sins = None\n sequence = None\n data = data.lower()\n for n in data:\n \n one_hot = torch.zeros((1, 4))\n if n =='a':\n one_hot[0][0] = 1\n elif n == 'c':\n one_hot[0][1] = 1\n elif n == 'g':\n one_hot[0][2] = 1\n elif n == 't':\n one_hot[0][3] = 1\n if sins == None:\n sequence = copy.deepcopy(one_hot)\n sins = 1\n else:\n sequence = torch.cat((sequence, one_hot), dim=0)\n if list(sequence.size())[0] < 23:\n for i in range(23 - list(sequence.size())[0]):\n sequence = torch.cat((sequence, torch.zeros((1, 4))), dim=0) \n if list(sequence.size())[0] > 23: \n sequence = sequence[:23]\n if sign == '-':\n sequence = torch.flip(sequence, [1]) \n return sequence \n\n \n# import numpy as np\n\ndef dataLoader(file=\"crisprsql.csv\", batch=64, mode=\"target\"):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == \"study\":\n loadData = byStudy(d)\n elif mode == \"guide\":\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n average_value = list()\n thisdata = list()\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n thisdata.append([\n [one_hot(line['grna_target_sequence'], line['grna_target_strand']), \n one_hot(line['target_sequence'], line[\"target_strand\"])],\n torch.tensor([float(line['cleavage_freq'])])])\n average_value.append(float(line['cleavage_freq'])) \n # if line \n\n\n # mode = 0\n # zero = 0\n # for p in average_value:\n # if p == statistics.mode(average_value):\n # mode+=1\n # if p <0:\n # zero+=1 \n # print(f\"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\\nMedian: {statistics.median(average_value)}.\\nMode: {statistics.mode(average_value)} with {mode} datapoint.\\nstandard deviation: {statistics.pstdev(average_value)}.\\nlowest value: {min(average_value)}.\\nHighest value: {max(average_value)}\\n{zero} datapoints below zero\\n\\n\")\n if train == True:\n dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(4 if torch.cuda.is_available() else 4)))\n print(thisdata[0][0][0].size())\n train = False\n else:\n dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(4 if torch.cuda.is_available() else 4)))\n \n thisdata1 = list() \n for i in range(int(len(thisdata)/batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n \n if ones == None:\n ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)\n twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)\n threes = thisdata[(i * batch) + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0) \n twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0) \n threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0) \n \n thisdata1.append([[ones, twos], threes]) \n\n\n data.append(thisdata1) \n \n print('time to load data: ', time.monotonic() - ftime, 'seconds') \n \n\n return [data, dl]\n\n# from scipy.stats import rankdata\n\nclass CRISPRDataset(torch.utils.data.Dataset):\n def __init__(self, thisdata):\n self.thisdata = thisdata\n \n def __len__(self):\n return len(self.thisdata)\n\n def __getitem__(self, idx):\n item = self.thisdata[idx]\n sample = {\n # (23, 4)\n 'target': torch.squeeze(item[0][1]).unsqueeze_(dim=0),\n 'guide': torch.squeeze(item[0][0]).unsqueeze_(dim=0),\n # (1)\n 'cfd': torch.squeeze(item[1]).unsqueeze_(dim=0)\n }\n return sample\n\n \ndef collate_fn(batch):\n # (256, 23, 4)\n # (256, 1)\n # print(sum(list(batch[0]['cfd'].shape)), sum(list(batch[0]['target'].shape, sum(list(batch[0]['guide'].shape)))))\n\n output = {}\n\n b = {key: [] for key in batch[0].keys()}\n for i in batch:\n if sum(list(i['cfd'].shape)) > 0 and sum(list(i['target'].shape)) > 0 and sum(list(i['guide'].shape)) > 0 :\n for key in i.keys():\n b[key].append(i[key])\n else:\n print('1', sum(list(i['cfd'].shape)), i['cfd'])\n print('2', sum(list(i['target'].shape)), len(i['target'].shape), i['target'].tolist())\n print('3', sum(list(i['guide'].shape)), len(i['guide'].shape))\n\n for key in b.keys():\n # print(b[key])s\n if len(b[key]) > 0:\n output[key] = torch.stack(b[key])\n else:\n output[key] = torch.tensor([])\n\n\n\n\n\n\n # output = {\n # key: torch.stack([batch[i][key] for i in range(len(batch)) \\\n # if all( len(batch[i][k].shape) > 0 for k in batch[0].keys() )\n # ])\n # for key in batch[0].keys()\n # }\n\n return output\nimport pandas as pd\n\ndef rankDataLoader(file=\"crisprsql.csv\", batch=64, mode=\"target\"):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n if mode == \"study\":\n loadData = byStudy(d)\n elif mode == \"guide\":\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n ranks = list()\n for line in d:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n ranks.append(float(line['cleavage_freq']))\n ranks.sort()\n for t in range(3):\n \n df = pd.DataFrame(loadData[t])\n\n # df.drop(df.columns.difference(['cleavage_freq']), 1, inplace=True)\n # pd.to_numeric(df['cleavage_freq']\n pd.to_numeric(df.cleavage_freq, errors='coerce')\n # cleave = df.cleavage_freq\n \n # df_ = pd.DataFrame(loadData[t]).drop(['cleavage_freq'], 1, inplace=True)\n # df_.join(cleave)\n df.dropna(subset=['cleavage_freq'], inplace=True)\n print(df.head())\n average_value = list()\n thisdata = list()\n for line in df.to_dict(\"records\"):\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n thisdata.append([\n [one_hot(line['grna_target_sequence'], line['grna_target_strand']), \n one_hot(line['target_sequence'], line[\"target_strand\"])],\n torch.tensor(ranks.index(float(line['cleavage_freq'])) / len(ranks))])\n average_value.append(float(line['cleavage_freq'])) \n # if line \n\n\n # mode = 0\n # zero = 0\n # for p in average_value:\n # if p == statistics.mode(average_value):\n # mode+=1\n # if p <0:\n # zero+=1 \n # print(f\"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\\nMedian: {statistics.median(average_value)}.\\nMode: {statistics.mode(average_value)} with {mode} datapoint.\\nstandard deviation: {statistics.pstdev(average_value)}.\\nlowest value: {min(average_value)}.\\nHighest value: {max(average_value)}\\n{zero} datapoints below zero\\n\\n\")\n if train == True:\n # dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(1 if torch.cuda.is_available() else 0)))\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, True, collate_fn=collate_fn, num_workers=(1 if torch.cuda.is_available() else 0)))\n \n # print(thisdata[0][0][0])\n train = False\n else:\n # dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(1 if torch.cuda.is_available() else 0)))\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, False, collate_fn=collate_fn, num_workers=(1 if torch.cuda.is_available() else 0)))\n # import pdb; pdb.set_trace()\n thisdata1 = list() \n for i in range(int(len(thisdata)/batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n \n if ones == None:\n ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)\n twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)\n threes = thisdata[(i * batch) + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0) \n twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0) \n threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0) \n \n thisdata1.append([[ones, twos], threes]) \n\n\n data.append(thisdata1) \n \n print('time to load data: ', time.monotonic() - ftime, 'seconds') \n \n return [data, dl]\n\n\n\n\n\n\n\ndef fullDataLoader(file=\"augmentcrisprsql.csv\", batch=64, mode=\"target\", target='rank'):\n ftime = time.monotonic()\n with open(file) as f:\n d = list(csv.DictReader(f))\n random.shuffle(d)\n if mode == \"study\":\n loadData = byStudy(d)\n elif mode == \"guide\":\n loadData = byGuide(d)\n else:\n loadData = byTarget(d)\n data = list()\n dl = list()\n train = True\n for t in range(3):\n \n average_value = list()\n thisdata = list()\n q = 0\n for line in loadData[t]:\n if line['cleavage_freq'] != '' and float(line['cleavage_freq']) >= 0:\n\n if target == 'regular':\n label = float(line['cleavage_freq'])\n elif target == 'rank':\n label = [float(line['ranked_cleavage_freq'])]\n else:\n label = [0, 1] if float(line['threshhold_cleavage_freq']) == 0 else [1, 0]\n\n if sum(list(torch.tensor([label]).shape)) > 0 and sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)) > 0 and sum(list(one_hot(line['target_sequence'], line[\"target_strand\"]).shape)) > 0:\n thisdata.append([\n [one_hot(line['grna_target_sequence'], line['grna_target_strand']), \n one_hot(line['target_sequence'], line[\"target_strand\"])],\n torch.tensor(label)])\n average_value.append(label)\n # print(sum(list(torch.tensor([label]).shape)), sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)), sum(list(one_hot(line['target_sequence'], line[\"target_strand\"]).shape)))\n \n else:\n q+=1\n print(sum(list(torch.tensor([label]).shape)), sum(list(one_hot(line['grna_target_sequence'], line['grna_target_strand']).shape)), sum(list(one_hot(line['target_sequence'], line[\"target_strand\"]).shape)))\n # print(torch.tensor([label), len(torch.tensor([label]).shape))\n print(q)\n # if line \n\n\n # mode = 0\n # zero = 0\n # for p in average_value:\n # if p == statistics.mode(average_value):\n # mode+=1\n # if p <0:\n # zero+=1 \n # print(f\"average CFD of {len(average_value)} datapoints in set {t + 1}: {sum(average_value)/len(average_value)}.\\nMedian: {statistics.median(average_value)}.\\nMode: {statistics.mode(average_value)} with {mode} datapoint.\\nstandard deviation: {statistics.pstdev(average_value)}.\\nlowest value: {min(average_value)}.\\nHighest value: {max(average_value)}\\n{zero} datapoints below zero\\n\\n\")\n if train == True:\n # dl.append(torch.utils.data.DataLoader(thisdata, batch, True, num_workers=(1 if torch.cuda.is_available() else 0)))\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, True, collate_fn=collate_fn, num_workers=4))\n \n # print(thisdata[0][0][0])\n train = False\n else:\n # dl.append(torch.utils.data.DataLoader(thisdata, batch, False, num_workers=(1 if torch.cuda.is_available() else 0)))\n dl.append(torch.utils.data.DataLoader(CRISPRDataset(thisdata), batch, False, collate_fn=collate_fn, num_workers=4))\n # import pdb; pdb.set_trace()\n thisdata1 = list() \n for i in range(int(len(thisdata)/batch)):\n ones = None\n twos = None\n threes = None\n for j in range(batch):\n \n if ones == None:\n ones = thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)\n twos = thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)\n threes = thisdata[(i * batch) + j][1].unsqueeze_(0)\n else:\n ones = torch.cat((ones, thisdata[(i * batch) + j][0][0].unsqueeze_(0).unsqueeze_(0)), dim=0) \n twos = torch.cat((twos, thisdata[(i * batch) + j][0][1].unsqueeze_(0).unsqueeze_(0)), dim=0) \n threes = torch.cat((threes, thisdata[(i * batch) + j][1].unsqueeze_(0)), dim=0) \n \n thisdata1.append([[ones, twos], threes]) \n\n\n data.append(thisdata1) \n\n print('time to load data: ', time.monotonic() - ftime, 'seconds') \n\n return [data, dl]\n\n\n\n\n\n\n\n\nfrom sklearn.metrics import roc_curve\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.metrics import precision_recall_curve\nfrom sklearn.metrics import f1_score\nfrom sklearn.metrics import auc\ndef roc(labels, outputs):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n average_values = dict()\n # print(len(llabels), len(loutputs))\n for i in range(1, 2):\n thislabel = list()\n thisoutput = list()\n pres = 0\n totalpres = 0\n for j in range(len(llabels)):\n\n if llabels[j] <= .01 / i:\n thislabel.append(0)\n else:\n thislabel.append(1) \n if loutputs[j] <= .01 / i:\n thisoutput.append(0)\n else:\n thisoutput.append(1)\n if thislabel[-1] == thisoutput[-1]:\n pres += 1\n totalpres +=1 \n lr_precision, lr_recall, _ = precision_recall_curve(thislabel, thisoutput)\n average_values[.1/i] = [roc_auc_score(thislabel, thisoutput), auc(lr_recall, lr_precision), pres/totalpres]\n return average_values \n\n\ndef accuracy(labels, outputs, percent=.10):\n llabels = labels.flatten().tolist()\n loutputs = outputs.flatten().tolist()\n correct = 0\n total = 0\n # print(llabels)\n for i in range(len(llabels)):\n if llabels[i] * (1 - percent) <= loutputs[i] and llabels[i] * (1 + percent) >= loutputs[i]:\n correct +=1\n total += 1\n\n return correct / total \n\n\ndef percentError(outputs, labels):\n return torch.mean(torch.abs(labels - outputs) / labels)\n\n\n \n\n\n \n\n\ndef Test(net, dataset, device, crit, logpath=None):\n \n net.eval()\n correct = 0\n total = 0\n totalloss = 0\n loss = 0\n with torch.no_grad():\n for i, data in enumerate(dataset, 0):\n inputs, labels = data[0], data[1].to(device) \n outputs = net(inputs)\n _, predicted = torch.max(outputs.data, 1)\n total += labels.size(0)\n totalloss+=1\n correct += (predicted == labels).sum().item()\n loss+=crit(outputs, labels)\n if logpath!= None:\n f = open(logpath, 'w')\n f.write('Accuracy of the network on the 10000 test images: %d %%' % (\n 100 * correct / total))\n f.write(f\"total: {total} correct: {correct}\")\n f.write(f'loss: {loss/totalloss}')\n f.close()\n print('Accuracy of the network on the 10000 test images: %d %%' % (\n 100 * correct / total))\n print(f\"total: {total} correct: {correct}\") \n print(f'loss: {loss/totalloss}')\n return 100 * correct / total \n\ndef getAllStudy():\n with open(\"crisprsql.csv\") as f:\n data = csv.DictReader(f)\n alls = dict()\n for row in data:\n if row['grna_target_sequence'] not in [\"C\", 'G', 'A', \"T\"]:\n try:\n alls[row['study_name']].add(row['grna_target_sequence']) \n except KeyError:\n alls[row[\"study_name\"]] = set(row['grna_target_sequence']) \n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n \n\ndef getallGuide():\n with open(\"crisprsql.csv\") as f:\n data = csv.DictReader(f)\n alls = dict()\n\n for row in data:\n if row['grna_target_sequence'] not in [\"C\", 'G', 'A', \"T\"]:\n try:\n alls[row['grna_target_sequence']].add(row['target_sequence']) \n except KeyError:\n alls[row[\"grna_target_sequence\"]] = set(row['target_sequence']) \n for r in alls:\n print(r)\n print(alls[r])\n print(len(alls[r]))\n \n\ndef aboveandbelow(threshold):\n with open(\"crisprsql.csv\") as f:\n data = csv.DictReader(f)\n alls = dict()\n above = 0\n total = 0\n for row in data:\n if row['grna_target_sequence'] not in [\"C\", 'G', 'A', \"T\"] and row['cleavage_freq'] != '':\n if float(row['cleavage_freq']) > threshold:\n above+=1\n total+=1\n \n\n print(f'Above: {above / total}%. Below: {(total - above) / total}')\n\n\n\n\n\n\n\ndef NewTrain(epochs, optim, crit, batch_per, train_data, val_data, net, device, optim_time=None, logpath=None):\n net.to(device)\n #def optim, loss, and init graph data\n criterion = crit\n optimizer = optim\n # get all labels for ROC\n full_full_labels = None\n for i, data in enumerate(train_data, 0):\n if full_full_labels == None:\n full_full_labels = data[1].to(device) \n else:\n full_full_labels = torch.cat((full_full_labels, data[1].to(device)), 0) \n full_val_labels = None \n for i, data in enumerate(val_data, 0):\n if full_val_labels == None:\n full_val_labels = data[1].to(device) \n else:\n full_val_labels = torch.cat((full_val_labels, data[1].to(device)), 0) \n print(\"begin training\")\n if logpath!= None:\n f = open(logpath, 'w')\n #these go down, and random loss is ~2.303 so 15 will be replaced\n best = 15\n bestval = 15\n bestepoch = 0\n e = 0\n # begin training loop, larget loop is for lr scedule\n times = list()\n # bestnet = LogisticRegression()\n # bestnet.load_state_dict(copy.deepcopy(net.state_dict()))\n for q in optim_time:\n optimizer = q[1]\n print(q[0])\n # net.load_state_dict(copy.deepcopy(bestnet.state_dict())\n # print(\n # 'params', [p for p in net.parameters()], \n # '\\ngrads', [p.grad for p in net.parameters()] \n # )\n # epoch loop\n for epoch in range(q[0]): # loop over the dataset multiple times\n ftime = time.monotonic()\n random.shuffle(train_data)\n correct = 0\n total = 0\n running_loss = 0.0\n # train mode\n net.train()\n full_output = None\n full_labels = None\n full_full_output = None\n \n for i, data in enumerate(train_data, 0):\n \n # train step\n inputs, labels = data[0], data[1].to(device) \n\n # zero the parameter gradients\n optimizer.zero_grad()\n\n # forward + backward + optimize\n # t = time.monotonic()\n outputs = net(inputs)\n # print(time.monotonic - t, \" seconds for 512 outputs\")\n loss = criterion(outputs, labels)\n loss.backward()\n # import pdb; pdb.set_trace()\n # things to look at:\n # - loss\n # - parameters\n # - inputs\n # - grads\n # if e % 300 == 299:\n\n # print(\n # 'loss', loss, \n # # '\\ninputs', inputs,\n # '\\nlabels', labels,\n # '\\noutputs', outputs\n # )\n \n optimizer.step()\n _, predicted = torch.max(outputs.data, 1)\n total+= labels.size(0) \n correct += (predicted == labels).sum().item()\n # print()\n \n running_loss += loss.item()\n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0)\n\n if full_labels == None:\n full_labels = labels\n else:\n full_labels = torch.cat((full_labels, labels), 0) \n # w = {f'output {i}': outputs.flatten()[i] for i in range(outputs.flatten().size(0))}\n # w.update({\n # f'label {i}': labels.flatten()[i] for i in range(labels.flatten().size(0))\n # })\n w = ({'loss': loss.item(), \n 'accuracy': accuracy(labels, outputs),\n 'percent error': percentError(outputs, labels)})\n wandb.log(\n # {\n # 'loss': loss.item(), \n # # 'params': [p for p in net.parameters()], \n # # 'grads': [p.grad for p in net.parameters()], \n # # 'inputs': inputs,\n # f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),\n # f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),\n # 'accuracy': accuracy(labels, outputs)\n # }\n w\n )\n # print statistics\n if i % batch_per == batch_per - 1: # print every 2000 mini-batches\n print('[%d, %5d] loss: %.3f' %\n (e + 1, i + 1, running_loss / batch_per))\n # best = min(best, running_loss / batch_per)\n \n # print('Accuracy of the network on the ' + str(batch_per) + 'th update: %d %%' % (\n # 100 * correct / total))\n \n wl = roc(full_labels, full_output)\n wandlog = {}\n for q in wl:\n wandlog[f\"midepoch ROC_AUC\"] = wl[q][0]\n wandlog[f\"midepoch PR_AUC\"] = wl[q][1]\n wandlog[f\"midepoch threshhold accuracy\"] = wl[q][2]\n\n\n\n # wandlog.update({\n # \"LOSS\": running_loss / batch_per, \n # \"TYPE\": \"TRAIN\", \n # 'EPOCH': e+1, \n # 'UPDATE': (e*len(train_data)) + i + 1})\n w.update({'midepoch loss': loss.item(), \n 'midepoch accuracy': accuracy(labels, outputs),\n 'midepoch percent error': percentError(outputs, labels)})\n wandb.log(\n # {\n # 'loss': loss.item(), \n # # 'params': [p for p in net.parameters()], \n # # 'grads': [p.grad for p in net.parameters()], \n # # 'inputs': inputs,\n # f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),\n # f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),\n # 'accuracy': accuracy(labels, outputs)\n # }\n w\n )\n wandb.log(wandlog)\n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output, full_output), 0) \n \n full_output = None\n full_labels = None\n\n\n running_loss = 0\n correct = 0\n total = 0\n # print('[%d] loss: %.20f' %\n # (epoch + 1, running_loss / total))\n # if logpath != None:\n # f.write('[%d] loss: %.20f' %\n # (epoch + 1, running_loss / total)) \n if full_full_output == None:\n full_full_output = full_output\n else:\n full_full_output = torch.cat((full_full_output, full_output), 0) \n # ROC is commented out when training on 10 samples\n wl = roc(full_full_labels, full_full_output)\n w = {}\n\n for q in wl:\n w[f\"epoch ROC_AUC\"] = wl[q][0]\n w[f\"epoch PR_AUC\"] = wl[q][1]\n w[f\"epoch threshhold accuracy\"] = wl[q][2]\n # wandlog.update({\n # \"LOSS\": running_loss / batch_per, \n # \"TYPE\": \"TRAIN\", \n # 'EPOCH': e+1, \n # 'UPDATE': (e + 1) *len(train_data)}) \n w.update({'epoch loss': loss.item(), \n 'epoch accuracy': accuracy(full_full_labels, full_full_output),\n 'epoch percent error': percentError(full_full_output, full_full_labels),\n 'label': labels.flatten()[0],\n 'output': outputs.flatten()[0]})\n wandb.log(\n # {\n # 'loss': loss.item(), \n # # 'params': [p for p in net.parameters()], \n # # 'grads': [p.grad for p in net.parameters()], \n # # 'inputs': inputs,\n # f'label {i}': labels.flatten()[i] for i in len(labels.flatten().size(0)),\n # f'output {i}': outputs.flatten()[i] for i in len(outputs.flatten().size(0)),\n # 'accuracy': accuracy(labels, outputs)\n # }\n w\n ) \n if w['epoch accuracy'] == 1:\n\n PATH = f'.accuracynet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch PR_AUC'] == 1:\n\n PATH = f'.PRnet.pth'\n torch.save(net.state_dict(), PATH)\n if w['epoch ROC_AUC'] == 1:\n\n PATH = f'.ROCnet.pth'\n torch.save(net.state_dict(), PATH)\n\n\n # wandb.log(wandlog) \n\n full_output = None\n full_full_output = None\n running_loss = 0\n correct = 0\n total = 0 \n running_loss = 0\n net.eval()\n correct = 0\n total = 0\n if e % 10 == 9:\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n #check val set\n for i, data in enumerate(val_data, 0):\n inputs, labels = data[0], data[1].to(device) \n outputs = net(inputs)\n loss = criterion(outputs, labels) \n loss.backward()\n running_loss += loss.item()\n total+= labels.size(0) \n if full_output == None:\n full_output = outputs\n else:\n full_output = torch.cat((full_output, outputs), 0) \n # if e % 300 == 299:\n print(f'Validation loss for Epoch [{e +1}]: {running_loss/total}') \n # if logpath != None:\n # f.write(f'Validation loss for Epoch [{epoch}]: {running_loss/total}') \n \n # wl = roc(full_val_labels, full_output)\n wandlog = {}\n # for q in wl:\n # wandlog[f\"{q} ROC_AUC\"] = wl[q][0]\n # wandlog[f\"{q} PR_AUC\"] = wl[q][1]\n # wandlog[f\"{q} ACCURACY\"] = wl[q][2]\n # wandlog.update({\n # \"LOSS\": running_loss / len(val_data), \n # \"TYPE\": \"VAL\", \n # 'EPOCH': e+1, \n # 'UPDATE': (e + 1)*len(train_data)}) \n # wandb.log(wandlog) \n # best = min(best, running_loss / total)\n # early stop just goes to the next lr change checkpoint\n \n if bestval <= running_loss / total:\n # if epoch >= 5:\n # print('Early Stop')\n # print(f\"Best Validation loss: {bestval}\")\n # print(f\"Current Validation loss: {running_loss / total}\")\n \n e = e\n # break\n # continue\n # return\n else:\n # bestnet.load_state_dict(copy.deepcopy(net.state_dict()))\n bestepoch = e\n bestval = running_loss / total\n\n running_loss = 0\n correct = 0\n total = 0\n times.append(time.monotonic() - ftime)\n PATH = f'.net.pth'\n torch.save(net.state_dict(), PATH)\n # if e % 300 == 299:\n print('time for epoch: ', times[-1], 'seconds')\n if logpath != None:\n f.write(f'time for epoch: {times[-1]}, seconds') \n e+=1\n \n\n\n\n\n # finish training. in future dont plot and save here just return them\n print('Finished Training')\n print('average time per epoch: ', sum(times)/len(times), 'seconds')\n if logpath != None:\n f.write('Finished Training')\n f.write(f'average time per epoch: {sum(times)/len(times)} seconds')\n f.close()\n \n return \n\n\n# def compute_dataframe(df: pd.DataFrame, checkpoint_path: str):\n# model = LogisticRegression().load_state_dict(torch.load(checkpoint_path, map_location=torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")))\n# targets, targets_s, guides, guides_s = df.target_sequence.tolist(), df.target_strand.tolist(), df.grna_target_sequence.tolist(), df.grna_target_strand.tolist()\n# preds = []\n# for guide, target, guide_s, target_s in zip(guides, targets, guides_s, targets_s):\n# pred = model([one_hot(guide, guide_s), one_hot(target, target_s)])\n# preds.append(pred.item())\n# df['pred'] = preds\n# return df\n\ndef compute_dataframe(df: pd.DataFrame, checkpoint_path):\n model = checkpoint_path\n targets, targets_s, guides, guides_s = df.target_sequence.tolist(), df.target_strand.tolist(), df.grna_target_sequence.tolist(), df.grna_target_strand.tolist()\n preds = []\n for guide, target, guide_s, target_s in zip(guides, targets, guides_s, targets_s):\n pred = model([one_hot(guide, guide_s), one_hot(target, target_s)])\n preds.append(pred.item())\n df['pred'] = preds\n return df",
"step-ids": [
15,
16,
19,
21,
24
]
}
|
[
15,
16,
19,
21,
24
] |
#!/usr/bin/env python3.4
from flask import Flask, render_template, request, jsonify
from time import time
application = Flask(__name__)
@application.route("/chutesnladders")
@application.route("/cnl")
@application.route("/snakesnladders")
@application.route("/snl")
def chutesnladders():
response = application.make_response(
render_template(
'chutesnladders.min.html'
)
)
return response
@application.route("/report", methods=['GET', 'POST'])
def reportBug():
d = {}
if request.method == 'POST':
try:
email = request.form.get("email", type=str).lower()
kind = request.form.get("kind", type=str).lower()
title = kind.upper() + ": " + request.form.get("title", type=str)
details = request.form.get("details", type=str)
ts = int(time()*(10**6))
report = request.form.get("reportingEnabled", type=bool)
if report:
sendmail.sendMeResponse({
'ts': ts,
'feed_email': email,
'feed_name': email.split('@')[0],
'feed_message': details,
'feed_subject': title,
})
d = {"result": "Received"}
except Exception:
d = {"result": "Error in receiving"}
else:
d = {"result": "Bad request"}
response = application.make_response(jsonify(**d))
return response
# EVERY FUNCTION FOR CHUTES n LADDERS END HERE
if __name__ == "__main__":
application.run(
host='0.0.0.0',
debug=False
)
|
normal
|
{
"blob_id": "a2c62091b14929942b49853c4a30b851ede0004b",
"index": 4563,
"step-1": "<mask token>\n\n\[email protected]('/chutesnladders')\[email protected]('/cnl')\[email protected]('/snakesnladders')\[email protected]('/snl')\ndef chutesnladders():\n response = application.make_response(render_template(\n 'chutesnladders.min.html'))\n return response\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\[email protected]('/chutesnladders')\[email protected]('/cnl')\[email protected]('/snakesnladders')\[email protected]('/snl')\ndef chutesnladders():\n response = application.make_response(render_template(\n 'chutesnladders.min.html'))\n return response\n\n\[email protected]('/report', methods=['GET', 'POST'])\ndef reportBug():\n d = {}\n if request.method == 'POST':\n try:\n email = request.form.get('email', type=str).lower()\n kind = request.form.get('kind', type=str).lower()\n title = kind.upper() + ': ' + request.form.get('title', type=str)\n details = request.form.get('details', type=str)\n ts = int(time() * 10 ** 6)\n report = request.form.get('reportingEnabled', type=bool)\n if report:\n sendmail.sendMeResponse({'ts': ts, 'feed_email': email,\n 'feed_name': email.split('@')[0], 'feed_message':\n details, 'feed_subject': title})\n d = {'result': 'Received'}\n except Exception:\n d = {'result': 'Error in receiving'}\n else:\n d = {'result': 'Bad request'}\n response = application.make_response(jsonify(**d))\n return response\n\n\nif __name__ == '__main__':\n application.run(host='0.0.0.0', debug=False)\n",
"step-3": "<mask token>\napplication = Flask(__name__)\n\n\[email protected]('/chutesnladders')\[email protected]('/cnl')\[email protected]('/snakesnladders')\[email protected]('/snl')\ndef chutesnladders():\n response = application.make_response(render_template(\n 'chutesnladders.min.html'))\n return response\n\n\[email protected]('/report', methods=['GET', 'POST'])\ndef reportBug():\n d = {}\n if request.method == 'POST':\n try:\n email = request.form.get('email', type=str).lower()\n kind = request.form.get('kind', type=str).lower()\n title = kind.upper() + ': ' + request.form.get('title', type=str)\n details = request.form.get('details', type=str)\n ts = int(time() * 10 ** 6)\n report = request.form.get('reportingEnabled', type=bool)\n if report:\n sendmail.sendMeResponse({'ts': ts, 'feed_email': email,\n 'feed_name': email.split('@')[0], 'feed_message':\n details, 'feed_subject': title})\n d = {'result': 'Received'}\n except Exception:\n d = {'result': 'Error in receiving'}\n else:\n d = {'result': 'Bad request'}\n response = application.make_response(jsonify(**d))\n return response\n\n\nif __name__ == '__main__':\n application.run(host='0.0.0.0', debug=False)\n",
"step-4": "from flask import Flask, render_template, request, jsonify\nfrom time import time\napplication = Flask(__name__)\n\n\[email protected]('/chutesnladders')\[email protected]('/cnl')\[email protected]('/snakesnladders')\[email protected]('/snl')\ndef chutesnladders():\n response = application.make_response(render_template(\n 'chutesnladders.min.html'))\n return response\n\n\[email protected]('/report', methods=['GET', 'POST'])\ndef reportBug():\n d = {}\n if request.method == 'POST':\n try:\n email = request.form.get('email', type=str).lower()\n kind = request.form.get('kind', type=str).lower()\n title = kind.upper() + ': ' + request.form.get('title', type=str)\n details = request.form.get('details', type=str)\n ts = int(time() * 10 ** 6)\n report = request.form.get('reportingEnabled', type=bool)\n if report:\n sendmail.sendMeResponse({'ts': ts, 'feed_email': email,\n 'feed_name': email.split('@')[0], 'feed_message':\n details, 'feed_subject': title})\n d = {'result': 'Received'}\n except Exception:\n d = {'result': 'Error in receiving'}\n else:\n d = {'result': 'Bad request'}\n response = application.make_response(jsonify(**d))\n return response\n\n\nif __name__ == '__main__':\n application.run(host='0.0.0.0', debug=False)\n",
"step-5": "#!/usr/bin/env python3.4\n\nfrom flask import Flask, render_template, request, jsonify\nfrom time import time\n\napplication = Flask(__name__)\n\n\[email protected](\"/chutesnladders\")\[email protected](\"/cnl\")\[email protected](\"/snakesnladders\")\[email protected](\"/snl\")\ndef chutesnladders():\n response = application.make_response(\n render_template(\n 'chutesnladders.min.html'\n )\n )\n return response\n\n\[email protected](\"/report\", methods=['GET', 'POST'])\ndef reportBug():\n d = {}\n if request.method == 'POST':\n try:\n email = request.form.get(\"email\", type=str).lower()\n kind = request.form.get(\"kind\", type=str).lower()\n title = kind.upper() + \": \" + request.form.get(\"title\", type=str)\n details = request.form.get(\"details\", type=str)\n ts = int(time()*(10**6))\n report = request.form.get(\"reportingEnabled\", type=bool)\n if report:\n sendmail.sendMeResponse({\n 'ts': ts,\n 'feed_email': email,\n 'feed_name': email.split('@')[0],\n 'feed_message': details,\n 'feed_subject': title,\n })\n d = {\"result\": \"Received\"}\n except Exception:\n d = {\"result\": \"Error in receiving\"}\n else:\n d = {\"result\": \"Bad request\"}\n response = application.make_response(jsonify(**d))\n return response\n# EVERY FUNCTION FOR CHUTES n LADDERS END HERE\n\nif __name__ == \"__main__\":\n application.run(\n host='0.0.0.0',\n debug=False\n )\n",
"step-ids": [
1,
3,
4,
5,
6
]
}
|
[
1,
3,
4,
5,
6
] |
from email.mime.text import MIMEText
import smtplib
def init_mail(server, user, pwd, port=25):
server = smtplib.SMTP(server, port)
server.starttls()
server.login(user, pwd)
return server
def send_email(mconn, mailto, mailfrom, mailsub, msgbody):
msg = MIMEText(msgbody)
msg['Subject'] = mailsub
msg['To'] = mailto
msg['From'] = mailfrom
mconn.sendmail(mailfrom, mailto, msg.as_string())
mconn.quit()
|
normal
|
{
"blob_id": "ec604aea28dfb2909ac9e4b0f15e6b5bbe1c3446",
"index": 2934,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef send_email(mconn, mailto, mailfrom, mailsub, msgbody):\n msg = MIMEText(msgbody)\n msg['Subject'] = mailsub\n msg['To'] = mailto\n msg['From'] = mailfrom\n mconn.sendmail(mailfrom, mailto, msg.as_string())\n mconn.quit()\n",
"step-3": "<mask token>\n\n\ndef init_mail(server, user, pwd, port=25):\n server = smtplib.SMTP(server, port)\n server.starttls()\n server.login(user, pwd)\n return server\n\n\ndef send_email(mconn, mailto, mailfrom, mailsub, msgbody):\n msg = MIMEText(msgbody)\n msg['Subject'] = mailsub\n msg['To'] = mailto\n msg['From'] = mailfrom\n mconn.sendmail(mailfrom, mailto, msg.as_string())\n mconn.quit()\n",
"step-4": "from email.mime.text import MIMEText\nimport smtplib\n\n\ndef init_mail(server, user, pwd, port=25):\n server = smtplib.SMTP(server, port)\n server.starttls()\n server.login(user, pwd)\n return server\n\n\ndef send_email(mconn, mailto, mailfrom, mailsub, msgbody):\n msg = MIMEText(msgbody)\n msg['Subject'] = mailsub\n msg['To'] = mailto\n msg['From'] = mailfrom\n mconn.sendmail(mailfrom, mailto, msg.as_string())\n mconn.quit()\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
from django.shortcuts import render
from django.http import HttpResponse
from chats.models import Chat
from usuario.models import Usuario
# Create your views here.
def chat(request):
chat_list = Chat.objects.order_by("id_chat")
chat_dict = {'chat': chat_list}
return render(request,'chats/Chat.html', context=chat_dict)
|
normal
|
{
"blob_id": "4a14265a9a2338be66e31110bba696e224b6a70f",
"index": 8395,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef chat(request):\n chat_list = Chat.objects.order_by('id_chat')\n chat_dict = {'chat': chat_list}\n return render(request, 'chats/Chat.html', context=chat_dict)\n",
"step-3": "from django.shortcuts import render\nfrom django.http import HttpResponse\nfrom chats.models import Chat\nfrom usuario.models import Usuario\n\n\ndef chat(request):\n chat_list = Chat.objects.order_by('id_chat')\n chat_dict = {'chat': chat_list}\n return render(request, 'chats/Chat.html', context=chat_dict)\n",
"step-4": "from django.shortcuts import render\nfrom django.http import HttpResponse\nfrom chats.models import Chat\nfrom usuario.models import Usuario\n\n# Create your views here.\ndef chat(request):\n \n chat_list = Chat.objects.order_by(\"id_chat\")\n chat_dict = {'chat': chat_list}\n\n return render(request,'chats/Chat.html', context=chat_dict)",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
from selenium import webdriver
import time
with webdriver.Chrome() as browser:
browser.get("http://suninjuly.github.io/selects1.html")
time.sleep(1)
x = int(browser.find_element_by_id("num1").text)
y = int(browser.find_element_by_id("num2").text)
sum_xy = str(int(x)+int(y))
browser.find_element_by_tag_name("select").click()
sum_opt = browser.find_element_by_css_selector("[value='{}']".format(sum_xy))
sum_opt.click()
browser.find_element_by_tag_name("button").click()
time.sleep(5)
|
normal
|
{
"blob_id": "42be9077ec51a9be1d4923011a38cd64d829f876",
"index": 1529,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith webdriver.Chrome() as browser:\n browser.get('http://suninjuly.github.io/selects1.html')\n time.sleep(1)\n x = int(browser.find_element_by_id('num1').text)\n y = int(browser.find_element_by_id('num2').text)\n sum_xy = str(int(x) + int(y))\n browser.find_element_by_tag_name('select').click()\n sum_opt = browser.find_element_by_css_selector(\"[value='{}']\".format(\n sum_xy))\n sum_opt.click()\n browser.find_element_by_tag_name('button').click()\n time.sleep(5)\n",
"step-3": "from selenium import webdriver\nimport time\nwith webdriver.Chrome() as browser:\n browser.get('http://suninjuly.github.io/selects1.html')\n time.sleep(1)\n x = int(browser.find_element_by_id('num1').text)\n y = int(browser.find_element_by_id('num2').text)\n sum_xy = str(int(x) + int(y))\n browser.find_element_by_tag_name('select').click()\n sum_opt = browser.find_element_by_css_selector(\"[value='{}']\".format(\n sum_xy))\n sum_opt.click()\n browser.find_element_by_tag_name('button').click()\n time.sleep(5)\n",
"step-4": "from selenium import webdriver\nimport time\n\nwith webdriver.Chrome() as browser:\n browser.get(\"http://suninjuly.github.io/selects1.html\")\n time.sleep(1)\n x = int(browser.find_element_by_id(\"num1\").text)\n y = int(browser.find_element_by_id(\"num2\").text)\n sum_xy = str(int(x)+int(y))\n browser.find_element_by_tag_name(\"select\").click()\n sum_opt = browser.find_element_by_css_selector(\"[value='{}']\".format(sum_xy))\n sum_opt.click()\n browser.find_element_by_tag_name(\"button\").click()\n time.sleep(5)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
def encrypt(key,plaintext):
ciphertext=""
for i in plaintext:
if i.isalpha():
alphabet = ord(i)+key
if alphabet > ord("Z"):
alphabet -= 26
letter = chr(alphabet)
ciphertext+=letter
return ciphertext
def decrypt(key,ciphertext):
plaintext=""
for i in ciphertext:
if i.isalpha():
alphabet = ord(i)-key
if alphabet < ord("A"):
alphabet += 26
letter = chr(alphabet)
plaintext+=letter
return plaintext
|
normal
|
{
"blob_id": "ac31cba94ee8ff7a2903a675954c937c567b5a56",
"index": 6739,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef decrypt(key, ciphertext):\n plaintext = ''\n for i in ciphertext:\n if i.isalpha():\n alphabet = ord(i) - key\n if alphabet < ord('A'):\n alphabet += 26\n letter = chr(alphabet)\n plaintext += letter\n return plaintext\n",
"step-3": "def encrypt(key, plaintext):\n ciphertext = ''\n for i in plaintext:\n if i.isalpha():\n alphabet = ord(i) + key\n if alphabet > ord('Z'):\n alphabet -= 26\n letter = chr(alphabet)\n ciphertext += letter\n return ciphertext\n\n\ndef decrypt(key, ciphertext):\n plaintext = ''\n for i in ciphertext:\n if i.isalpha():\n alphabet = ord(i) - key\n if alphabet < ord('A'):\n alphabet += 26\n letter = chr(alphabet)\n plaintext += letter\n return plaintext\n",
"step-4": "\ndef encrypt(key,plaintext):\n ciphertext=\"\"\n\n for i in plaintext:\n if i.isalpha():\n alphabet = ord(i)+key\n if alphabet > ord(\"Z\"):\n alphabet -= 26\n letter = chr(alphabet)\n ciphertext+=letter\n\n return ciphertext\n\ndef decrypt(key,ciphertext):\n plaintext=\"\"\n for i in ciphertext:\n if i.isalpha():\n alphabet = ord(i)-key\n if alphabet < ord(\"A\"):\n alphabet += 26\n letter = chr(alphabet)\n plaintext+=letter\n\n return plaintext\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
from flask_marshmallow import Marshmallow
from models import Uservet
ma = Marshmallow()
class UserVetSchema(ma.Schema):
class Meta:
model = Uservet
user_vet_1 = ['dni', 'email', 'nombre', 'apellidos', 'telefono', 'tipo_uservet'
]
|
normal
|
{
"blob_id": "677154aa99a5a4876532f3e1edfec45b1790384c",
"index": 9511,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass UserVetSchema(ma.Schema):\n\n\n class Meta:\n model = Uservet\n\n\n<mask token>\n",
"step-3": "<mask token>\nma = Marshmallow()\n\n\nclass UserVetSchema(ma.Schema):\n\n\n class Meta:\n model = Uservet\n\n\nuser_vet_1 = ['dni', 'email', 'nombre', 'apellidos', 'telefono', 'tipo_uservet'\n ]\n",
"step-4": "from flask_marshmallow import Marshmallow\nfrom models import Uservet\nma = Marshmallow()\n\n\nclass UserVetSchema(ma.Schema):\n\n\n class Meta:\n model = Uservet\n\n\nuser_vet_1 = ['dni', 'email', 'nombre', 'apellidos', 'telefono', 'tipo_uservet'\n ]\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
###############################################################################
##
## Copyright (C) 2011-2014, NYU-Poly.
## Copyright (C) 2006-2011, University of Utah.
## All rights reserved.
## Contact: [email protected]
##
## This file is part of VisTrails.
##
## "Redistribution and use in source and binary forms, with or without
## modification, are permitted provided that the following conditions are met:
##
## - Redistributions of source code must retain the above copyright notice,
## this list of conditions and the following disclaimer.
## - Redistributions in binary form must reproduce the above copyright
## notice, this list of conditions and the following disclaimer in the
## documentation and/or other materials provided with the distribution.
## - Neither the name of the University of Utah nor the names of its
## contributors may be used to endorse or promote products derived from
## this software without specific prior written permission.
##
## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
## AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
## THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
## PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
## CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
## EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
## PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
## OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
## WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
## OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
## ADVISED OF THE POSSIBILITY OF SUCH DAMAGE."
##
###############################################################################
# -*- coding: utf-8 -*-
# Resource object code
#
# Created: Mon Jul 19 16:02:11 2010
# by: The Resource Compiler for PyQt (Qt v4.6.3)
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore
qt_resource_data = b"\
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\x31\x42\x2d\x01\x49\x4b\x01\xb1\x1c\x28\x46\xe8\xd0\x1a\x07\x95\
\x87\xc0\x2a\x94\xe1\x11\x40\x00\x31\x0e\x74\xdf\x10\x20\x80\x06\
\xbc\x63\x02\x10\x40\x03\xee\x00\x80\x00\x1a\x70\x07\x00\x04\x18\
\x00\x4e\x12\xc6\x99\x32\x89\xe5\xec\x00\x00\x00\x00\x49\x45\x4e\
\x44\xae\x42\x60\x82\
"
qt_resource_name = b"\
\x00\x06\
\x07\x03\x7d\xc3\
\x00\x69\
\x00\x6d\x00\x61\x00\x67\x00\x65\x00\x73\
\x00\x0a\
\x0c\x91\x67\x27\
\x00\x63\
\x00\x61\x00\x6d\x00\x65\x00\x72\x00\x61\x00\x2e\x00\x70\x00\x6e\x00\x67\
"
qt_resource_struct = b"\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x02\
\x00\x00\x00\x12\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\
"
def qInitResources():
QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
|
normal
|
{
"blob_id": "2a6b373c443a1bbafe644cb770bc163536dd5573",
"index": 3348,
"step-1": "<mask token>\n\n\ndef qInitResources():\n QtCore.qRegisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef qInitResources():\n QtCore.qRegisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\nqInitResources()\n",
"step-3": "<mask token>\nqt_resource_data = (\n b'\\x00\\x00\\x07\\xb6\\x89PNG\\r\\n\\x1a\\n\\x00\\x00\\x00\\rIHDR\\x00\\x00\\x00 \\x00\\x00\\x00 \\x08\\x06\\x00\\x00\\x00szz\\xf4\\x00\\x00\\x00\\x04gAMA\\x00\\x00\\xaf\\xc87\\x05\\x8a\\xe9\\x00\\x00\\x00\\x19tEXtSoftware\\x00Adobe ImageReadyq\\xc9e<\\x00\\x00\\x07HIDATx\\xdab\\xfc\\xff\\xff?\\xc3@\\x02\\x80\\x00bb\\x18`\\x00\\x10@\\x03\\xee\\x00\\x80\\x00\\x1ap\\x07\\x00\\x04\\xd0\\x80;\\x00 \\x80X@\\x84\\xb1q*\\xc3\\x8f\\x1f?\\x99~\\xfe\\xfc\\xce\\xfd\\xff\\xff\\xbf\\xbfJJ\\xaa\\x86RR\\x02Y<<\\x8cf\\x7f\\xfe\\xfca~\\xf2\\xe4\\xed\\x8d\\xd3\\xa7\\xf7-\\xfb\\xf6\\xed\\xddv%%\\xc7\\x9f\\x0c\\x0c\\xff\\xa0\\xda\\x19!\\xbe`\\x82\\xf8\\x83\\x91\\x91\\x11\\x8e\\x99\\x98\\x18\\x19@\\xe9\\x1b\\xc4\\x86\\xc9\\x81\\xc4\\x98\\x98\\x98\\x19\\x7f\\xff\\xfe\\xf4\\xe5\\xcc\\x99\\xa5\\xe0\\xd4\\x0f\\x10@`\\x07\\xfc\\xfb\\xf7\\xdfNEE\\xa6AP\\x90\\x97\\x07\\x98+\\xferppjpq1\\n\\xb0\\xb11\\x81-\\xe1\\xe5\\xe5U\\x94\\x92\\x8au\\xff\\xf7\\xef\\xefe\\x06\\x86\\xff?A\\x86\\xb0\\xb3\\xb3\\x83\\x03\\x10d\\xfe\\xef\\xdf\\xbfA\\x06\\x83-\\x01z\\x00\\xcc\\x06;\\xe0\\xdf\\x7f\\x86\\xffp\\x87\\x81L\\x02:\\x80\\x99\\x99\\xf1\\xc5\\x8b\\x97\\xaf\\x1e<P\\xa9\\x7f\\xf3\\xe6\\xce\\x19\\x80\\x00\\x02;@MMvboo\\x9a\\x81\\xa0 \\x1f\\xd8\\xd5\\x9f?\\x7fg\\xf8\\xf8\\xf1+\\xc3\\xb7o\\xbf\\xc1|\\x16\\x16f\\x06VVV\\xa0G\\x99\\xf4A\\x86\\xb1\\xb1s0\\\\\\xbf|\\x9c\\xe1\\xf1\\x83;\\x0cj\\xdaF\\x0c\\xc2\"b@u\\x7f\\x80\\x1e\\xf9\\xc7\\xc0\\xcc\\xcc\\xcc\\xf0\\xf7/\\x13\\x03\\x07\\x07\\x1f\\x03;;P-\\x0b#\\x033(\\x10\\x18\\x99\\x18\\xbe|\\xfd\\xc1\\xf0\\xfd\\'+\\xd0\\xfc\\xbf\\x0c\\xf7\\xef_f\\x02: \\t \\x80\\xc0\\x0e\\x10\\x15\\xe5\\x96ea\\xf9\\xc7\\xf0\\xe5\\xcbg\\xb0\\xeb?}\\xfa\\xca\\xf0\\xf2\\xe5{\\x86\\x0f\\x1f\\xbe\\x83\\x83\\x8f\\x99\\x99\\x05\\x8cAr\\\\\\x9c\\\\\\x0cwo\\x9f`hYu\\x9cA\\xc9:\\x80\\xe1E\\xd3t\\x86%\\xfd\\xb9\\x0cK\\x96\\xaff\\xf8\\xf8\\xe1\\x03CEE%\\xd8\\xe7\\x97\\xaf^d\\x10\\x91\\x92e\\x10\\x92\\x94ax\\xf1\\x8d\\x91\\xe1\\xf9\\xd7\\xff\\x0c\\xaf\\xdf\\xfdd\\xe0zx\\x83ATP\\x11\\xe8@\\x0e\\x05\\xa0\\xd1\\n\\x00\\x01\\x04\\x8e\\xbc_\\xbf~\\xfd\\xfd\\xfd\\xfb/<\\xbeP\\xe3\\x0c\\x82A|ff&p\\xb4\\xbf|v\\x93\\xe1\\xfe\\'\\x1e\\x86\\xdd\\x8f\\xa5\\x18\\x189D\\x19\\x04\\xf8x\\x18V,_\\xc1\\xb0`\\xc1\"\\x86\\xef\\xdf\\x7f0(\\xab(3\\xd8X\\x9b1<\\xff\\xc6\\xc4p\\xe6\\xfeg\\x86\\xcb\\xf7\\xde0|\\xff\\xf2\\x9b\\x81\\xf9\\xe77\\x06\\x0e`\\xd4\\xfd\\xfe\\xf5\\x07\\x18m\\x7fA\\x96\\xb1\\x01\\x04\\x10\\x0b,1!\\xd9\\x8d\\x15@\\x1c\\xc7\\xc8\\xf0\\xf8\\xf1\\r\\x06w_o\\x06\\x0e\\xc1\\x13\\x0c\\x07\\x8fu1d\\x97\\x860\\xc8)k1,]\\xba\\x14h\\xf9w\\x06\\r\\ru`\\x82\\xfe\\r\\x8c2v\\x06\\x0b%\\x01\\x86_?~2\\\\\\xb9r\\x95A\\x98K\\x8d\\x81U\\x90\\x9f\\xe1\\x1d#;0z\\x7f\\xc2<\\xfb\\x1f \\x80X\\x88\\xcd. \\xdf\\xbfz\\xf5\\x88AL\\x8c\\x9fARR\\x9e!9^\\x99!;%\\x92\\x81\\x85\\x83\\x07,ogg\\x07W\\xfb\\xfb7$\\x97\\xf0\\xf0\\xf02\\xfcf\\xe7b004f\\xb8x\\xf1\\x1a\\x83\\xa4\\x9480=\\x81\\x92\\xe5\\x0f\\xb8\\x87\\x01\\x02\\x88\\x05\\xe1\\xbb\\xffx|\\xcf\\x04\\xf4\\xd5\\x0f\\xa0\\xaf\\xfe0\\xc8\\xc9)\\x83\\x83\\x99\\x81\\x81\\x95\\x81\\x81\\x9b\\x93\\x81\\r\\x18\\x9c_\\xbe|\\x02:\\xee\\x05X\\r\\x1f\\x1f?0MI\\x80\\x13\\xee\\xb7o?\\xc19\\x84\\x99\\x85\\x1dh\\xb9\\x08\\xc3\\xa3GW\\x18\\x04\\x04T\\x19\\x90\\xab\\x1f\\x80\\x00\"*\\x04@\\x89\\xef\\xc3\\x87\\x97\\x0c\\xb2\\xb2R\\xc0\\x14\\xfe\\x1f\\xecX\\x90\\xa3\\x81\\xd9\\x92\\xe1\\xde\\xbd\\x07\\x0c/^\\xbc\\x06\\n\\xb1\\x03-b\\x03&\\xde\\'\\xc0hz\\xc2\\xa0\\xa2\\xa2\\xca\\xc0\\xc5\\xc5\\x0fL_\\xa0\\xf8\\xfe\\xc3 ,,\\x0eN\\xd8?~|\\x87F9$\\x08\\x00\\x02\\x88\\x89P\\x81\\x08R\\xf8\\xf7\\xefo\\xa0A_\\x19\\xd8\\xd8\\xb8\\xc0\\x96B\\xa2\\x84\\x99\\xe1\\xcd\\x9b\\x97\\x0c\\xaf_\\xbfc\\xe0\\xe1\\x95dx\\xfd\\xe6#\\xc3\\xb9sg\\x1988\\x85\\x809\\x8e\\x87\\xe1\\xc6\\x8dk\\x0c\\xc0\\x82\\rZ6\\x00\\xcb\\x83\\xffL\\x0c\\xdc\\xdc\\xec\\xc0\\xd0z\\x0b\\x0c\\x1d\\x84\\xbf\\x01\\x02\\x88\\tb\\t\\xde\\xe4\\x07\\xf4\\xc1/\\x06NN\\xa0\\x0f\\x99Y\\xc1\\x86\\xc1|\\xff\\xfe\\xfd{\\x061q9\\x86S\\xa7\\x8e0$\\xa7\\x840\\x14\\x15\\xa5\\x02\\xb3a\\x16\\xb0\\xe0\\xe2\\x07F\\x17\\x17\\xc3\\xdb\\xb7\\xaf\\x80\\x96A<\\xf7\\xf7\\xef_\\xb0\\x19?~|\\x00G)\\x0c\\x00\\x04\\x10\\x11\\x0e`\\x00[\\n*\\xf9`m\\x07P\\xd1\\xfb\\xf3\\xe7\\x0fp\\xaa\\x11\\x13\\x17eX\\xb8`&\\xc3\\xe7O\\x9f@%*\\xc3\\x89\\xe3G\\x18\\xce\\x9c9\\xc6 .!\\x05,p>\\xc2-\\x83\\x98\\xc1\\x01\\xe4\\xff\\x03\\xab\\x83\\x15\\xe3\\x00\\x01\\xc4\\x84\\\\\\xa6\\xe3\\x03\\x10M\\x08\\x07\\x81\\x1c\\xf1\\x0f\\xe8\\xab\\xff\\xc0zAPH\\x18E-\\xbf\\x00?\\xc3\\x1f`\\xb4\\xfd\\xfd\\xfb\\x0f)*\\x19\\xc0%\\xe5\\xbf\\x7f\\xa8\\xe6\\x02\\x04\\x10R.\\xc0W\\x060\\x83\\xf38\\xc21\\xff\\x80\\xe9\\x81\\x13\\x98\\xe8X\\x18^>\\x7f\\xcaP^Q\\xcd\\xf0\\x13\\x98\\xb8^<\\x7f\\xce\\xe0\\xe1\\xed\\xc3`nn\\xc9p\\xe3\\xfaE\\x06I\\tIh\\x94A\\xec\\x00%@&&V\\xb0\\xe3av\\x02\\x04\\x10\\x0b\\xa1(\\x00\\x19\\xc0\\xc6\\xc6\\x06\\xcc\\x05\\xff\\x80>\\xfa\\x05T\\xcb\\x0e\\x97\\x13\\x03\\xd6\\x01\\xf7\\xee\\xdfe\\x10\\x11\\x91`\\x989{>8{\\xf2\\xf0p3\\xdc\\xbds\\x1dX\\xda\\xfdd\\x90\\x90\\x90\\x02\\xc7=\\xac>\\xf9\\xf1\\xe3\\x17P^\\x84\\x01X\\xc3\\xc2\\xed\\x04\\x08 \"\\xb2!$\\xb899\\xf9\\x19\\xbe~\\xfd\\xc4\\xc0\\xcf/\\x08OT\\xc2\"\\xa2@\\xd7\\xffgx\\xf2\\xe41\\xc3\\xdb\\x9f\\x7f\\x80\\xc1\\xfe\\x87\\xe1\\xc5\\xb3?\\xc0\\xc4\\xca\\xc8`jj\\x01.\\r\\x7f\\xff\\xfe\\x01\\xcdI\\xbf\\x80i\\xe2\\'0\\'\\x08\\x00\\x13\\xefWx\\xb4\\x03\\x04\\x10QQ\\x00\\xb2\\x8c\\x8fO\\x88\\xe1\\xd9\\xb3{\\xc0RP\\x12\\xe8 H(\\x80|\"!!\\r,\\x1dE\\x81\\x86\\x7f\\x01\\xe7\\x16\\x16\\x16V\\xa0/\\xf9\\xc1\\xf1\\xff\\xfd\\xfbO\\xb0:66V\\x86\\xdb\\xb7o\\x03\\x1d&\\x08\\xae\\xd4\\x90\\x01@\\x00\\x11\\x99\\x08\\xff\\x835rr\\x8a\\x82\\xf37(8a\\x8e\\xfe\\x0b\\xf45\\x0b\\xb0\\xa4\\x13\\x11\\x11\\x01:N\\nH\\x8b\\x82\\x83\\x17\\xe4h\\x10`ee\\x01F\\xdfk`\\xf9\\xff\\x97AFF\\r\\xac\\x1e\\xb9\\xee\\x01\\x08 \\xa2\\xb2!,\\x14\\x84\\x84D\\x81\\x05\\x12+\\xc3\\xe5\\xcb\\xe7\\xc0z@i\\x03Q\\xd0 \\xd4\\x81\\xf8\\xa0\\x82\\x8a\\x9d\\x9d\\x8d\\xe1\\xdd\\xbb\\xd7\\x0cw\\xee<\\x06VR\\xe6\\xf04\\x85\\x0c\\x00\\x02\\x88\\tZ\\xaa1\\x83*\\x1blU0r\\x13\\x0bT\\xf8HJ*\\x00\\x83\\x96\\x95\\xe1\\xc8\\x91\\xa3\\x0c\\xcf\\x9f?\\x01\\xfa\\x90\\x19\\\\\\xd8\\xc0\\x13\\x150t@\\x05\\x0e\\xa8\\x14\\xbcz\\xf520\\xe8\\x9f1\\xe8\\xe8X\\x03\\x8be\\x0epk\\tb\\x16\\x13\\xb8i\\x06R\\x0f\\x10@\\xe0\\x08y\\xf2\\xe4\\xcd\\xed\\x87\\x0f\\xdf\\t+*J\\x01\\xe3\\x15T\\x9b\\x81\\xe2\\x17\\x98\\xcf\\xff1\\xc1+#\\x18\\x06\\xb5\\x1b\\x84\\x85\\xe5\\x80)\\xfa\\x1b\\xb0\\x04\\xbc\\x07\\xacj\\xef\\x01C\\x86\\x17\\xe80q\\xb0\\x8f?\\x00\\x1b%\\xcf\\x9e\\x01\\xeb\\xff\\xef\\xff\\x80\\xe9F\\x8aA[[\\x05\\xec\\xf8_\\xbf\\x80%\\xc6?\\x90gX\\x80\\r\\x9e\\xcf\\xa0h\\x01\\xd5h\\xff\\x01\\x02\\x88\\x11\\x14$RRzv\\xe2\\xe2r\\xd5\\xbc\\xbc\\xdc\\xb2\\xa0\\xf8\\x06f\\xf3\\xff\\xa0\\x82\\x07V\\xec\"\\xb7\\x07@\\x86\\xc1*(P\\xf9\\x00\\xf2\\xe9\\xb7o\\x9f\\x80!\\xc1\\x08\\xf6=\\xa8\\xf2\\x01%R~~!P3\\x0eh\\xd6\\x1f\\xa8\\xc5\\x90\\xb4\\x04d3~\\xfc\\xf8\\xe6\\xe7\\xb5k\\x07\\xf7|\\xff\\xfei\\x0e@\\x001B-\\x01IK\\x01\\xb1\\x1c(F\\xe8\\xd0\\x1a\\x07\\x95\\x87\\xc0*\\x94\\xe1\\x11@\\x001\\x0et\\xdf\\x10 \\x80\\x06\\xbcc\\x02\\x10@\\x03\\xee\\x00\\x80\\x00\\x1ap\\x07\\x00\\x04\\x18\\x00N\\x12\\xc6\\x992\\x89\\xe5\\xec\\x00\\x00\\x00\\x00IEND\\xaeB`\\x82'\n )\nqt_resource_name = (\n b\"\\x00\\x06\\x07\\x03}\\xc3\\x00i\\x00m\\x00a\\x00g\\x00e\\x00s\\x00\\n\\x0c\\x91g'\\x00c\\x00a\\x00m\\x00e\\x00r\\x00a\\x00.\\x00p\\x00n\\x00g\"\n )\nqt_resource_struct = (\n b'\\x00\\x00\\x00\\x00\\x00\\x02\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\x00\\x02\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x02\\x00\\x00\\x00\\x12\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00'\n )\n\n\ndef qInitResources():\n QtCore.qRegisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(1, qt_resource_struct, qt_resource_name,\n qt_resource_data)\n\n\nqInitResources()\n",
"step-4": "from PyQt4 import QtCore\nqt_resource_data = (\n b'\\x00\\x00\\x07\\xb6\\x89PNG\\r\\n\\x1a\\n\\x00\\x00\\x00\\rIHDR\\x00\\x00\\x00 \\x00\\x00\\x00 \\x08\\x06\\x00\\x00\\x00szz\\xf4\\x00\\x00\\x00\\x04gAMA\\x00\\x00\\xaf\\xc87\\x05\\x8a\\xe9\\x00\\x00\\x00\\x19tEXtSoftware\\x00Adobe ImageReadyq\\xc9e<\\x00\\x00\\x07HIDATx\\xdab\\xfc\\xff\\xff?\\xc3@\\x02\\x80\\x00bb\\x18`\\x00\\x10@\\x03\\xee\\x00\\x80\\x00\\x1ap\\x07\\x00\\x04\\xd0\\x80;\\x00 \\x80X@\\x84\\xb1q*\\xc3\\x8f\\x1f?\\x99~\\xfe\\xfc\\xce\\xfd\\xff\\xff\\xbf\\xbfJJ\\xaa\\x86RR\\x02Y<<\\x8cf\\x7f\\xfe\\xfca~\\xf2\\xe4\\xed\\x8d\\xd3\\xa7\\xf7-\\xfb\\xf6\\xed\\xddv%%\\xc7\\x9f\\x0c\\x0c\\xff\\xa0\\xda\\x19!\\xbe`\\x82\\xf8\\x83\\x91\\x91\\x11\\x8e\\x99\\x98\\x18\\x19@\\xe9\\x1b\\xc4\\x86\\xc9\\x81\\xc4\\x98\\x98\\x98\\x19\\x7f\\xff\\xfe\\xf4\\xe5\\xcc\\x99\\xa5\\xe0\\xd4\\x0f\\x10@`\\x07\\xfc\\xfb\\xf7\\xdfNEE\\xa6AP\\x90\\x97\\x07\\x98+\\xferppjpq1\\n\\xb0\\xb11\\x81-\\xe1\\xe5\\xe5U\\x94\\x92\\x8au\\xff\\xf7\\xef\\xefe\\x06\\x86\\xff?A\\x86\\xb0\\xb3\\xb3\\x83\\x03\\x10d\\xfe\\xef\\xdf\\xbfA\\x06\\x83-\\x01z\\x00\\xcc\\x06;\\xe0\\xdf\\x7f\\x86\\xffp\\x87\\x81L\\x02:\\x80\\x99\\x99\\xf1\\xc5\\x8b\\x97\\xaf\\x1e<P\\xa9\\x7f\\xf3\\xe6\\xce\\x19\\x80\\x00\\x02;@MMvboo\\x9a\\x81\\xa0 \\x1f\\xd8\\xd5\\x9f?\\x7fg\\xf8\\xf8\\xf1+\\xc3\\xb7o\\xbf\\xc1|\\x16\\x16f\\x06VVV\\xa0G\\x99\\xf4A\\x86\\xb1\\xb1s0\\\\\\xbf|\\x9c\\xe1\\xf1\\x83;\\x0cj\\xdaF\\x0c\\xc2\"b@u\\x7f\\x80\\x1e\\xf9\\xc7\\xc0\\xcc\\xcc\\xcc\\xf0\\xf7/\\x13\\x03\\x07\\x07\\x1f\\x03;;P-\\x0b#\\x033(\\x10\\x18\\x99\\x18\\xbe|\\xfd\\xc1\\xf0\\xfd\\'+\\xd0\\xfc\\xbf\\x0c\\xf7\\xef_f\\x02: \\t 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"step-5": "###############################################################################\n##\n## Copyright (C) 2011-2014, NYU-Poly.\n## Copyright (C) 2006-2011, University of Utah. \n## All rights reserved.\n## Contact: [email protected]\n##\n## This file is part of VisTrails.\n##\n## \"Redistribution and use in source and binary forms, with or without \n## modification, are permitted provided that the following conditions are met:\n##\n## - Redistributions of source code must retain the above copyright notice, \n## this list of conditions and the following disclaimer.\n## - Redistributions in binary form must reproduce the above copyright \n## notice, this list of conditions and the following disclaimer in the \n## documentation and/or other materials provided with the distribution.\n## - Neither the name of the University of Utah nor the names of its \n## contributors may be used to endorse or promote products derived from \n## this software without specific prior written permission.\n##\n## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\" \n## AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, \n## THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR \n## PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR \n## CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, \n## EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, \n## PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; \n## OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, \n## WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR \n## OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF \n## ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\"\n##\n###############################################################################\n# -*- coding: utf-8 -*-\n\n# Resource object code\n#\n# Created: Mon Jul 19 16:02:11 2010\n# by: The Resource Compiler for PyQt (Qt v4.6.3)\n#\n# WARNING! All changes made in this file will be lost!\n\nfrom PyQt4 import QtCore\n\nqt_resource_data = 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7c\\xff\\xfe\\x69\\x0e\\x40\\x00\\\n\\x31\\x42\\x2d\\x01\\x49\\x4b\\x01\\xb1\\x1c\\x28\\x46\\xe8\\xd0\\x1a\\x07\\x95\\\n\\x87\\xc0\\x2a\\x94\\xe1\\x11\\x40\\x00\\x31\\x0e\\x74\\xdf\\x10\\x20\\x80\\x06\\\n\\xbc\\x63\\x02\\x10\\x40\\x03\\xee\\x00\\x80\\x00\\x1a\\x70\\x07\\x00\\x04\\x18\\\n\\x00\\x4e\\x12\\xc6\\x99\\x32\\x89\\xe5\\xec\\x00\\x00\\x00\\x00\\x49\\x45\\x4e\\\n\\x44\\xae\\x42\\x60\\x82\\\n\"\n\nqt_resource_name = b\"\\\n\\x00\\x06\\\n\\x07\\x03\\x7d\\xc3\\\n\\x00\\x69\\\n\\x00\\x6d\\x00\\x61\\x00\\x67\\x00\\x65\\x00\\x73\\\n\\x00\\x0a\\\n\\x0c\\x91\\x67\\x27\\\n\\x00\\x63\\\n\\x00\\x61\\x00\\x6d\\x00\\x65\\x00\\x72\\x00\\x61\\x00\\x2e\\x00\\x70\\x00\\x6e\\x00\\x67\\\n\"\n\nqt_resource_struct = b\"\\\n\\x00\\x00\\x00\\x00\\x00\\x02\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x01\\\n\\x00\\x00\\x00\\x00\\x00\\x02\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x02\\\n\\x00\\x00\\x00\\x12\\x00\\x00\\x00\\x00\\x00\\x01\\x00\\x00\\x00\\x00\\\n\"\n\ndef qInitResources():\n QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)\n\ndef qCleanupResources():\n QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data)\n\nqInitResources()\n",
"step-ids": [
2,
3,
4,
5,
6
]
}
|
[
2,
3,
4,
5,
6
] |
#
# Copyright (c) 2018 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
__all__ = ['lenet_mnist']
class Lenet(nn.Module):
def __init__(self):
super(Lenet, self).__init__()
self.conv1 = nn.Conv2d(1, 20, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(20, 50, 5)
self.fc1 = nn.Linear(800, 500)
self.fc2 = nn.Linear(500, 10)
def forward(self, x):
#print("weights sizes")
#print(self.conv1.weight.size())
layer_w = self.fc2.weight
sigma = layer_w.std().data.cpu().numpy()
layer_w_numpy = layer_w.data.cpu().numpy()
scale = 0.17
noise = np.random.normal(0, scale*sigma, layer_w.size())
w_noise = np.add(layer_w_numpy, noise)
w_noise_tensor = torch.tensor(w_noise)
#print(w_noise_tensor.size())
w_noise_tensor = w_noise_tensor.to('cuda')
w_noise = torch.nn.Parameter(w_noise_tensor.float())
self.fc2.weight = w_noise
#print("---------------------")
#print(self.conv2.weight.size())
#print("---------------------")
#print(self.fc1.weight.size())
#print("---------------------")
#print(self.fc2.weight.size())
#print("---------------------")
x = self.pool(F.relu(self.conv1(x)))
x = self.pool(F.relu(self.conv2(x)))
x = x.view(-1, 800)
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
#x = nn.Threshold(0.2, 0.0)#ActivationZeroThreshold(x)
return x
def lenet_mnist():
model = Lenet()
return model
|
normal
|
{
"blob_id": "a38a5010c9edbed0929da225b4288396bb0d814e",
"index": 6989,
"step-1": "<mask token>\n\n\nclass Lenet(nn.Module):\n <mask token>\n\n def forward(self, x):\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n scale = 0.17\n noise = np.random.normal(0, scale * sigma, layer_w.size())\n w_noise = np.add(layer_w_numpy, noise)\n w_noise_tensor = torch.tensor(w_noise)\n w_noise_tensor = w_noise_tensor.to('cuda')\n w_noise = torch.nn.Parameter(w_noise_tensor.float())\n self.fc2.weight = w_noise\n x = self.pool(F.relu(self.conv1(x)))\n x = self.pool(F.relu(self.conv2(x)))\n x = x.view(-1, 800)\n x = F.relu(self.fc1(x))\n x = F.relu(self.fc2(x))\n return x\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Lenet(nn.Module):\n\n def __init__(self):\n super(Lenet, self).__init__()\n self.conv1 = nn.Conv2d(1, 20, 5)\n self.pool = nn.MaxPool2d(2, 2)\n self.conv2 = nn.Conv2d(20, 50, 5)\n self.fc1 = nn.Linear(800, 500)\n self.fc2 = nn.Linear(500, 10)\n\n def forward(self, x):\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n scale = 0.17\n noise = np.random.normal(0, scale * sigma, layer_w.size())\n w_noise = np.add(layer_w_numpy, noise)\n w_noise_tensor = torch.tensor(w_noise)\n w_noise_tensor = w_noise_tensor.to('cuda')\n w_noise = torch.nn.Parameter(w_noise_tensor.float())\n self.fc2.weight = w_noise\n x = self.pool(F.relu(self.conv1(x)))\n x = self.pool(F.relu(self.conv2(x)))\n x = x.view(-1, 800)\n x = F.relu(self.fc1(x))\n x = F.relu(self.fc2(x))\n return x\n\n\ndef lenet_mnist():\n model = Lenet()\n return model\n",
"step-3": "<mask token>\n__all__ = ['lenet_mnist']\n\n\nclass Lenet(nn.Module):\n\n def __init__(self):\n super(Lenet, self).__init__()\n self.conv1 = nn.Conv2d(1, 20, 5)\n self.pool = nn.MaxPool2d(2, 2)\n self.conv2 = nn.Conv2d(20, 50, 5)\n self.fc1 = nn.Linear(800, 500)\n self.fc2 = nn.Linear(500, 10)\n\n def forward(self, x):\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n scale = 0.17\n noise = np.random.normal(0, scale * sigma, layer_w.size())\n w_noise = np.add(layer_w_numpy, noise)\n w_noise_tensor = torch.tensor(w_noise)\n w_noise_tensor = w_noise_tensor.to('cuda')\n w_noise = torch.nn.Parameter(w_noise_tensor.float())\n self.fc2.weight = w_noise\n x = self.pool(F.relu(self.conv1(x)))\n x = self.pool(F.relu(self.conv2(x)))\n x = x.view(-1, 800)\n x = F.relu(self.fc1(x))\n x = F.relu(self.fc2(x))\n return x\n\n\ndef lenet_mnist():\n model = Lenet()\n return model\n",
"step-4": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\n__all__ = ['lenet_mnist']\n\n\nclass Lenet(nn.Module):\n\n def __init__(self):\n super(Lenet, self).__init__()\n self.conv1 = nn.Conv2d(1, 20, 5)\n self.pool = nn.MaxPool2d(2, 2)\n self.conv2 = nn.Conv2d(20, 50, 5)\n self.fc1 = nn.Linear(800, 500)\n self.fc2 = nn.Linear(500, 10)\n\n def forward(self, x):\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n scale = 0.17\n noise = np.random.normal(0, scale * sigma, layer_w.size())\n w_noise = np.add(layer_w_numpy, noise)\n w_noise_tensor = torch.tensor(w_noise)\n w_noise_tensor = w_noise_tensor.to('cuda')\n w_noise = torch.nn.Parameter(w_noise_tensor.float())\n self.fc2.weight = w_noise\n x = self.pool(F.relu(self.conv1(x)))\n x = self.pool(F.relu(self.conv2(x)))\n x = x.view(-1, 800)\n x = F.relu(self.fc1(x))\n x = F.relu(self.fc2(x))\n return x\n\n\ndef lenet_mnist():\n model = Lenet()\n return model\n",
"step-5": "#\n# Copyright (c) 2018 Intel Corporation\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n#\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np \n\n__all__ = ['lenet_mnist']\n\nclass Lenet(nn.Module):\n def __init__(self):\n super(Lenet, self).__init__()\n self.conv1 = nn.Conv2d(1, 20, 5)\n self.pool = nn.MaxPool2d(2, 2)\n self.conv2 = nn.Conv2d(20, 50, 5)\n self.fc1 = nn.Linear(800, 500)\n self.fc2 = nn.Linear(500, 10)\n\n def forward(self, x):\n #print(\"weights sizes\")\n #print(self.conv1.weight.size())\n layer_w = self.fc2.weight\n sigma = layer_w.std().data.cpu().numpy()\n layer_w_numpy = layer_w.data.cpu().numpy()\n scale = 0.17\n noise = np.random.normal(0, scale*sigma, layer_w.size())\n w_noise = np.add(layer_w_numpy, noise)\n w_noise_tensor = torch.tensor(w_noise)\n #print(w_noise_tensor.size())\n w_noise_tensor = w_noise_tensor.to('cuda')\n w_noise = torch.nn.Parameter(w_noise_tensor.float())\n self.fc2.weight = w_noise \n #print(\"---------------------\")\n #print(self.conv2.weight.size())\n #print(\"---------------------\")\n #print(self.fc1.weight.size())\n #print(\"---------------------\")\n #print(self.fc2.weight.size())\n #print(\"---------------------\")\n x = self.pool(F.relu(self.conv1(x)))\n x = self.pool(F.relu(self.conv2(x)))\n x = x.view(-1, 800)\n x = F.relu(self.fc1(x))\n x = F.relu(self.fc2(x))\n #x = nn.Threshold(0.2, 0.0)#ActivationZeroThreshold(x)\n return x\n\ndef lenet_mnist():\n model = Lenet()\n return model\n",
"step-ids": [
2,
4,
5,
6,
7
]
}
|
[
2,
4,
5,
6,
7
] |
from typing import Tuple
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def lcaDeepestLeaves(self, root: TreeNode) ->TreeNode:
_, lca = self.get_lca(root, 0)
return lca
def get_lca(self, node: TreeNode, depth: int) ->Tuple[int, TreeNode]:
if not node:
return depth, node
left_depth, left_lca = self.get_lca(node.left, depth + 1)
right_depth, right_lca = self.get_lca(node.right, depth + 1)
if left_depth == right_depth:
return left_depth, node
if left_depth > right_depth:
return left_depth, left_lca
return right_depth, right_lca
|
normal
|
{
"blob_id": "0a528fb7fe4a318af8bd3111e8d67f6af6bd7416",
"index": 304,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def lcaDeepestLeaves(self, root: TreeNode) ->TreeNode:\n _, lca = self.get_lca(root, 0)\n return lca\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TreeNode:\n <mask token>\n\n\nclass Solution:\n\n def lcaDeepestLeaves(self, root: TreeNode) ->TreeNode:\n _, lca = self.get_lca(root, 0)\n return lca\n\n def get_lca(self, node: TreeNode, depth: int) ->Tuple[int, TreeNode]:\n if not node:\n return depth, node\n left_depth, left_lca = self.get_lca(node.left, depth + 1)\n right_depth, right_lca = self.get_lca(node.right, depth + 1)\n if left_depth == right_depth:\n return left_depth, node\n if left_depth > right_depth:\n return left_depth, left_lca\n return right_depth, right_lca\n",
"step-3": "<mask token>\n\n\nclass TreeNode:\n\n def __init__(self, x):\n self.val = x\n self.left = None\n self.right = None\n\n\nclass Solution:\n\n def lcaDeepestLeaves(self, root: TreeNode) ->TreeNode:\n _, lca = self.get_lca(root, 0)\n return lca\n\n def get_lca(self, node: TreeNode, depth: int) ->Tuple[int, TreeNode]:\n if not node:\n return depth, node\n left_depth, left_lca = self.get_lca(node.left, depth + 1)\n right_depth, right_lca = self.get_lca(node.right, depth + 1)\n if left_depth == right_depth:\n return left_depth, node\n if left_depth > right_depth:\n return left_depth, left_lca\n return right_depth, right_lca\n",
"step-4": "from typing import Tuple\n\n\nclass TreeNode:\n\n def __init__(self, x):\n self.val = x\n self.left = None\n self.right = None\n\n\nclass Solution:\n\n def lcaDeepestLeaves(self, root: TreeNode) ->TreeNode:\n _, lca = self.get_lca(root, 0)\n return lca\n\n def get_lca(self, node: TreeNode, depth: int) ->Tuple[int, TreeNode]:\n if not node:\n return depth, node\n left_depth, left_lca = self.get_lca(node.left, depth + 1)\n right_depth, right_lca = self.get_lca(node.right, depth + 1)\n if left_depth == right_depth:\n return left_depth, node\n if left_depth > right_depth:\n return left_depth, left_lca\n return right_depth, right_lca\n",
"step-5": null,
"step-ids": [
2,
4,
5,
6
]
}
|
[
2,
4,
5,
6
] |
from numpy import *
import KNN_1
import KNN_3
import KNN_suanfa as clf
def datingClassTest():
horatio = 0.1
data, datalabels = KNN_1.filel2matrix("datingTestSet2.txt")
normMat = KNN_3.autoNorm(data)
ml = normMat.shape[0]
numTestset = int(ml*horatio)
errorcount = 0
a=clf.classify0(normMat[0:numTestset,:],normMat[numTestset:ml,:],3,datalabels[numTestset:ml])
for i in range(len(a)):
if a[i] != datalabels[i]:
errorcount += 1
c = errorcount/100
return c
def predictperson():
level = ['not at all','in small does','in large does']
percenttats = float(input("percentage of time spent playing video games?"))
ffmiles = float(input("frequent flier miles earned per year?"))
icecream = float(input("liters of ice cream consumed per year?"))
data, datalabels = KNN_1.filel2matrix("datingTestSet2.txt")
normMat = KNN_3.autoNorm(data)
test_dataset = array([[percenttats,ffmiles,icecream]])
a = clf.classify0(test_dataset,data,3,datalabels)
print(level[a[0]-1])
predictperson()
|
normal
|
{
"blob_id": "3086f62d4057812fc7fb4e21a18bc7d0ba786865",
"index": 2526,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef datingClassTest():\n horatio = 0.1\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n ml = normMat.shape[0]\n numTestset = int(ml * horatio)\n errorcount = 0\n a = clf.classify0(normMat[0:numTestset, :], normMat[numTestset:ml, :], \n 3, datalabels[numTestset:ml])\n for i in range(len(a)):\n if a[i] != datalabels[i]:\n errorcount += 1\n c = errorcount / 100\n return c\n\n\ndef predictperson():\n level = ['not at all', 'in small does', 'in large does']\n percenttats = float(input('percentage of time spent playing video games?'))\n ffmiles = float(input('frequent flier miles earned per year?'))\n icecream = float(input('liters of ice cream consumed per year?'))\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n test_dataset = array([[percenttats, ffmiles, icecream]])\n a = clf.classify0(test_dataset, data, 3, datalabels)\n print(level[a[0] - 1])\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef datingClassTest():\n horatio = 0.1\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n ml = normMat.shape[0]\n numTestset = int(ml * horatio)\n errorcount = 0\n a = clf.classify0(normMat[0:numTestset, :], normMat[numTestset:ml, :], \n 3, datalabels[numTestset:ml])\n for i in range(len(a)):\n if a[i] != datalabels[i]:\n errorcount += 1\n c = errorcount / 100\n return c\n\n\ndef predictperson():\n level = ['not at all', 'in small does', 'in large does']\n percenttats = float(input('percentage of time spent playing video games?'))\n ffmiles = float(input('frequent flier miles earned per year?'))\n icecream = float(input('liters of ice cream consumed per year?'))\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n test_dataset = array([[percenttats, ffmiles, icecream]])\n a = clf.classify0(test_dataset, data, 3, datalabels)\n print(level[a[0] - 1])\n\n\npredictperson()\n",
"step-4": "from numpy import *\nimport KNN_1\nimport KNN_3\nimport KNN_suanfa as clf\n\n\ndef datingClassTest():\n horatio = 0.1\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n ml = normMat.shape[0]\n numTestset = int(ml * horatio)\n errorcount = 0\n a = clf.classify0(normMat[0:numTestset, :], normMat[numTestset:ml, :], \n 3, datalabels[numTestset:ml])\n for i in range(len(a)):\n if a[i] != datalabels[i]:\n errorcount += 1\n c = errorcount / 100\n return c\n\n\ndef predictperson():\n level = ['not at all', 'in small does', 'in large does']\n percenttats = float(input('percentage of time spent playing video games?'))\n ffmiles = float(input('frequent flier miles earned per year?'))\n icecream = float(input('liters of ice cream consumed per year?'))\n data, datalabels = KNN_1.filel2matrix('datingTestSet2.txt')\n normMat = KNN_3.autoNorm(data)\n test_dataset = array([[percenttats, ffmiles, icecream]])\n a = clf.classify0(test_dataset, data, 3, datalabels)\n print(level[a[0] - 1])\n\n\npredictperson()\n",
"step-5": "from numpy import *\nimport KNN_1\nimport KNN_3\nimport KNN_suanfa as clf\ndef datingClassTest():\n horatio = 0.1\n data, datalabels = KNN_1.filel2matrix(\"datingTestSet2.txt\")\n normMat = KNN_3.autoNorm(data)\n ml = normMat.shape[0]\n numTestset = int(ml*horatio)\n errorcount = 0\n a=clf.classify0(normMat[0:numTestset,:],normMat[numTestset:ml,:],3,datalabels[numTestset:ml])\n for i in range(len(a)):\n if a[i] != datalabels[i]:\n errorcount += 1\n c = errorcount/100\n return c\n\ndef predictperson():\n level = ['not at all','in small does','in large does']\n percenttats = float(input(\"percentage of time spent playing video games?\"))\n ffmiles = float(input(\"frequent flier miles earned per year?\"))\n icecream = float(input(\"liters of ice cream consumed per year?\"))\n data, datalabels = KNN_1.filel2matrix(\"datingTestSet2.txt\")\n normMat = KNN_3.autoNorm(data)\n test_dataset = array([[percenttats,ffmiles,icecream]])\n a = clf.classify0(test_dataset,data,3,datalabels)\n print(level[a[0]-1])\npredictperson()\n",
"step-ids": [
0,
2,
3,
4,
5
]
}
|
[
0,
2,
3,
4,
5
] |
from django.contrib import admin
from apap.models import *
# Register your models here.
admin.site.register(Doggo)
admin.site.register(Profile)
|
normal
|
{
"blob_id": "22504b466cdeb380b976e23e2708e94131722e11",
"index": 8147,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Doggo)\nadmin.site.register(Profile)\n",
"step-3": "from django.contrib import admin\nfrom apap.models import *\nadmin.site.register(Doggo)\nadmin.site.register(Profile)\n",
"step-4": "from django.contrib import admin\nfrom apap.models import *\n# Register your models here.\n\nadmin.site.register(Doggo)\nadmin.site.register(Profile)",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
# Downloads images from http://www.verseoftheday.com/ and saves it into a DailyBibleVerse folder
import requests, os, bs4
os.chdir('c:\\users\\patty\\desktop') #modify location where you want to create the folder
if not os.path.isdir('DailyBibleVerse'):
os.makedirs('DailyBibleVerse')
res = requests.get('http://www.verseoftheday.com/') #Downloading the page into the 'res' variable
res.raise_for_status()
soup= bs4.BeautifulSoup(res.text, "html.parser")
#BibleCaption= soup.select('#featured .bilingual-left') #If you want verse use this
#text= BibleCaption[0].getText()
BibleElem = soup.select('#tv-image-wrapper img') #searching the image
BibleUrl= BibleElem[0].get('src')
num=1
while os.path.exists('c:\\users\\patty\\desktop\\DailyBibleVerse\\verse%s.jpg' %num):
num += 1
File = open('c:\\users\\patty\\desktop\\DailyBibleVerse\\' +'verse'+ str(num)+ '.jpg', 'wb') #this is the name
res = requests.get(BibleUrl)
for chunk in res.iter_content(100000):
File.write(chunk)
File.close()
|
normal
|
{
"blob_id": "a8fb8ac3c102e460d44e533b1e6b3f8780b1145d",
"index": 4609,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.chdir('c:\\\\users\\\\patty\\\\desktop')\nif not os.path.isdir('DailyBibleVerse'):\n os.makedirs('DailyBibleVerse')\n<mask token>\nres.raise_for_status()\n<mask token>\nwhile os.path.exists(\n 'c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\verse%s.jpg' % num):\n num += 1\n<mask token>\nfor chunk in res.iter_content(100000):\n File.write(chunk)\nFile.close()\n",
"step-3": "<mask token>\nos.chdir('c:\\\\users\\\\patty\\\\desktop')\nif not os.path.isdir('DailyBibleVerse'):\n os.makedirs('DailyBibleVerse')\nres = requests.get('http://www.verseoftheday.com/')\nres.raise_for_status()\nsoup = bs4.BeautifulSoup(res.text, 'html.parser')\nBibleElem = soup.select('#tv-image-wrapper img')\nBibleUrl = BibleElem[0].get('src')\nnum = 1\nwhile os.path.exists(\n 'c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\verse%s.jpg' % num):\n num += 1\nFile = open('c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\' + 'verse' + str(\n num) + '.jpg', 'wb')\nres = requests.get(BibleUrl)\nfor chunk in res.iter_content(100000):\n File.write(chunk)\nFile.close()\n",
"step-4": "import requests, os, bs4\nos.chdir('c:\\\\users\\\\patty\\\\desktop')\nif not os.path.isdir('DailyBibleVerse'):\n os.makedirs('DailyBibleVerse')\nres = requests.get('http://www.verseoftheday.com/')\nres.raise_for_status()\nsoup = bs4.BeautifulSoup(res.text, 'html.parser')\nBibleElem = soup.select('#tv-image-wrapper img')\nBibleUrl = BibleElem[0].get('src')\nnum = 1\nwhile os.path.exists(\n 'c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\verse%s.jpg' % num):\n num += 1\nFile = open('c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\' + 'verse' + str(\n num) + '.jpg', 'wb')\nres = requests.get(BibleUrl)\nfor chunk in res.iter_content(100000):\n File.write(chunk)\nFile.close()\n",
"step-5": "# Downloads images from http://www.verseoftheday.com/ and saves it into a DailyBibleVerse folder \r\n\r\nimport requests, os, bs4\r\n\r\nos.chdir('c:\\\\users\\\\patty\\\\desktop') #modify location where you want to create the folder\r\nif not os.path.isdir('DailyBibleVerse'):\r\n os.makedirs('DailyBibleVerse')\r\n\r\nres = requests.get('http://www.verseoftheday.com/') #Downloading the page into the 'res' variable\r\nres.raise_for_status()\r\n\r\nsoup= bs4.BeautifulSoup(res.text, \"html.parser\")\r\n\r\n#BibleCaption= soup.select('#featured .bilingual-left') #If you want verse use this\r\n#text= BibleCaption[0].getText()\r\n\r\nBibleElem = soup.select('#tv-image-wrapper img') #searching the image\r\nBibleUrl= BibleElem[0].get('src')\r\n\r\nnum=1\r\nwhile os.path.exists('c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\verse%s.jpg' %num):\r\n num += 1\r\n \r\nFile = open('c:\\\\users\\\\patty\\\\desktop\\\\DailyBibleVerse\\\\' +'verse'+ str(num)+ '.jpg', 'wb') #this is the name\r\n\r\nres = requests.get(BibleUrl)\r\n\r\nfor chunk in res.iter_content(100000):\r\n File.write(chunk)\r\nFile.close()\r\n\r\n\r\n\r\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# Задание 1
# Выучите основные стандартные исключения, которые перечислены в данном уроке.
# Задание 2
# Напишите программу-калькулятор, которая поддерживает следующие операции: сложение, вычитание,
# умножение, деление и возведение в степень. Программа должна выдавать сообщения об ошибке и
# продолжать работу при вводе некорректных данных, делении на ноль и возведении нуля в
# отрицательную степень.
# Функция преобразования текстового списка в float
def list_convertion(user_list):
for index, item in enumerate(user_list):
user_list[index]=float(item)
return user_list
# Умножение
def multiplication(user_list):
multnum=1
for item in user_list:
multnum *= item
return multnum
# Деление. Здесь долго мучился, т.к. нужно первое число оставть и делить его на второе, т.е цикл со второго индекса
# пока не нашел в Интернете запись через slice напр.: for i in collection[1:]
def division(user_list):
divnum=user_list[0]
for item in user_list[1:]:
divnum /= item
return divnum
# Сложение
def adding(user_list):
sumnum=0
for item in user_list:
sumnum += item
return sumnum
# Вычитание. Логика та же, что и в делении
def subtraction(user_list):
subtractnum=user_list[0]
for item in user_list[1:]:
subtractnum -= item
return subtractnum
# Возведение в степень. Логика та же, что в делении
def powering(user_list):
pownum=user_list[0]
for item in user_list[1:]:
pownum **= item
return pownum
while True:
operation = input("Enter operation sign, please (*), (/), (+), (-), (^). \nTo quit, please enter 'done' > ")
if operation.lower() == "done": # Ключевым словом выхода из цикла будет done
print("Thank you for using the program!")
break
else:
try:
numbers_list = input("Enter the numbers separated by space > ").split(" ")
if len(numbers_list) < 2:
raise IndexError("You have entered less than 2 numbers")
else:
numbers_list = list_convertion(numbers_list) # Конвертация списка из str в float
try:
if "*" in operation: # Защита от ввода типа "*" или (*), т.е. проверяем есть ли во всей строке операция
print(f"Your multiplication result is {multiplication(numbers_list)}")
elif "^" in operation:
print(f"Your putting into power result is {powering(numbers_list)}")
elif "-" in operation:
print(f"Your subtraction result is {subtraction(numbers_list)}")
elif "+" in operation:
print(f"Your sum result is {adding(numbers_list)}")
elif "/" in operation:
print(f"Your division result is {division(numbers_list)}")
else:
raise ValueError("Unsupported operation, please try again")
except (ValueError, ZeroDivisionError) as e:
print(f"We have an issue. {e}")
except Exception as e:
print(f"We have an issue. {e}")
|
normal
|
{
"blob_id": "a8341bf422a4d31a83ff412c6aac75e5cb8c5e0f",
"index": 5876,
"step-1": "<mask token>\n\n\ndef adding(user_list):\n sumnum = 0\n for item in user_list:\n sumnum += item\n return sumnum\n\n\ndef subtraction(user_list):\n subtractnum = user_list[0]\n for item in user_list[1:]:\n subtractnum -= item\n return subtractnum\n\n\ndef powering(user_list):\n pownum = user_list[0]\n for item in user_list[1:]:\n pownum **= item\n return pownum\n\n\n<mask token>\n",
"step-2": "def list_convertion(user_list):\n for index, item in enumerate(user_list):\n user_list[index] = float(item)\n return user_list\n\n\ndef multiplication(user_list):\n multnum = 1\n for item in user_list:\n multnum *= item\n return multnum\n\n\n<mask token>\n\n\ndef adding(user_list):\n sumnum = 0\n for item in user_list:\n sumnum += item\n return sumnum\n\n\ndef subtraction(user_list):\n subtractnum = user_list[0]\n for item in user_list[1:]:\n subtractnum -= item\n return subtractnum\n\n\ndef powering(user_list):\n pownum = user_list[0]\n for item in user_list[1:]:\n pownum **= item\n return pownum\n\n\n<mask token>\n",
"step-3": "def list_convertion(user_list):\n for index, item in enumerate(user_list):\n user_list[index] = float(item)\n return user_list\n\n\ndef multiplication(user_list):\n multnum = 1\n for item in user_list:\n multnum *= item\n return multnum\n\n\ndef division(user_list):\n divnum = user_list[0]\n for item in user_list[1:]:\n divnum /= item\n return divnum\n\n\ndef adding(user_list):\n sumnum = 0\n for item in user_list:\n sumnum += item\n return sumnum\n\n\ndef subtraction(user_list):\n subtractnum = user_list[0]\n for item in user_list[1:]:\n subtractnum -= item\n return subtractnum\n\n\ndef powering(user_list):\n pownum = user_list[0]\n for item in user_list[1:]:\n pownum **= item\n return pownum\n\n\n<mask token>\n",
"step-4": "def list_convertion(user_list):\n for index, item in enumerate(user_list):\n user_list[index] = float(item)\n return user_list\n\n\ndef multiplication(user_list):\n multnum = 1\n for item in user_list:\n multnum *= item\n return multnum\n\n\ndef division(user_list):\n divnum = user_list[0]\n for item in user_list[1:]:\n divnum /= item\n return divnum\n\n\ndef adding(user_list):\n sumnum = 0\n for item in user_list:\n sumnum += item\n return sumnum\n\n\ndef subtraction(user_list):\n subtractnum = user_list[0]\n for item in user_list[1:]:\n subtractnum -= item\n return subtractnum\n\n\ndef powering(user_list):\n pownum = user_list[0]\n for item in user_list[1:]:\n pownum **= item\n return pownum\n\n\nwhile True:\n operation = input(\n \"\"\"Enter operation sign, please (*), (/), (+), (-), (^). \nTo quit, please enter 'done' > \"\"\"\n )\n if operation.lower() == 'done':\n print('Thank you for using the program!')\n break\n else:\n try:\n numbers_list = input('Enter the numbers separated by space > '\n ).split(' ')\n if len(numbers_list) < 2:\n raise IndexError('You have entered less than 2 numbers')\n else:\n numbers_list = list_convertion(numbers_list)\n try:\n if '*' in operation:\n print(\n f'Your multiplication result is {multiplication(numbers_list)}'\n )\n elif '^' in operation:\n print(\n f'Your putting into power result is {powering(numbers_list)}'\n )\n elif '-' in operation:\n print(\n f'Your subtraction result is {subtraction(numbers_list)}'\n )\n elif '+' in operation:\n print(f'Your sum result is {adding(numbers_list)}')\n elif '/' in operation:\n print(\n f'Your division result is {division(numbers_list)}'\n )\n else:\n raise ValueError(\n 'Unsupported operation, please try again')\n except (ValueError, ZeroDivisionError) as e:\n print(f'We have an issue. {e}')\n except Exception as e:\n print(f'We have an issue. {e}')\n",
"step-5": "# Задание 1\n# Выучите основные стандартные исключения, которые перечислены в данном уроке.\n# Задание 2\n# Напишите программу-калькулятор, которая поддерживает следующие операции: сложение, вычитание,\n# умножение, деление и возведение в степень. Программа должна выдавать сообщения об ошибке и\n# продолжать работу при вводе некорректных данных, делении на ноль и возведении нуля в\n# отрицательную степень.\n\n\n# Функция преобразования текстового списка в float\ndef list_convertion(user_list):\n for index, item in enumerate(user_list):\n user_list[index]=float(item)\n\n return user_list\n\n# Умножение\ndef multiplication(user_list):\n multnum=1\n for item in user_list:\n multnum *= item\n\n return multnum\n\n# Деление. Здесь долго мучился, т.к. нужно первое число оставть и делить его на второе, т.е цикл со второго индекса\n# пока не нашел в Интернете запись через slice напр.: for i in collection[1:]\ndef division(user_list):\n divnum=user_list[0]\n for item in user_list[1:]:\n divnum /= item\n\n return divnum\n\n# Сложение\ndef adding(user_list):\n sumnum=0\n for item in user_list:\n sumnum += item\n\n return sumnum\n\n# Вычитание. Логика та же, что и в делении\ndef subtraction(user_list):\n subtractnum=user_list[0]\n for item in user_list[1:]:\n subtractnum -= item\n\n return subtractnum\n\n# Возведение в степень. Логика та же, что в делении\ndef powering(user_list):\n pownum=user_list[0]\n for item in user_list[1:]:\n pownum **= item\n\n return pownum\n\nwhile True:\n operation = input(\"Enter operation sign, please (*), (/), (+), (-), (^). \\nTo quit, please enter 'done' > \")\n if operation.lower() == \"done\": # Ключевым словом выхода из цикла будет done\n print(\"Thank you for using the program!\")\n break\n else:\n try:\n numbers_list = input(\"Enter the numbers separated by space > \").split(\" \")\n if len(numbers_list) < 2:\n raise IndexError(\"You have entered less than 2 numbers\")\n else:\n numbers_list = list_convertion(numbers_list) # Конвертация списка из str в float\n try:\n if \"*\" in operation: # Защита от ввода типа \"*\" или (*), т.е. проверяем есть ли во всей строке операция\n print(f\"Your multiplication result is {multiplication(numbers_list)}\")\n elif \"^\" in operation:\n print(f\"Your putting into power result is {powering(numbers_list)}\")\n elif \"-\" in operation:\n print(f\"Your subtraction result is {subtraction(numbers_list)}\")\n elif \"+\" in operation:\n print(f\"Your sum result is {adding(numbers_list)}\")\n elif \"/\" in operation:\n print(f\"Your division result is {division(numbers_list)}\")\n else:\n raise ValueError(\"Unsupported operation, please try again\")\n except (ValueError, ZeroDivisionError) as e:\n print(f\"We have an issue. {e}\")\n except Exception as e:\n print(f\"We have an issue. {e}\")\n",
"step-ids": [
3,
5,
6,
7,
8
]
}
|
[
3,
5,
6,
7,
8
] |
import subprocess
from whoosh.index import create_in
from whoosh.fields import *
import os
import codecs
from whoosh.qparser import QueryParser
import whoosh.index as index
import json
from autosub.autosub import autosub
from azure.storage.blob import AppendBlobService
vedio_formats = ['mp4','avi','wmv','mov'] # 1
audio_formats = ['wav','flac','mp3','aiff'] # 2
def file_upload(file_pwd, append_blob_service):
regex = r"(.+)\/(.+)"
if re.search(regex, file_pwd):
match = re.search(regex, file_pwd)
file_dir = match.group(1) + '/'
file_name_and_type = match.group(2).lower()
else:
raise fileNameError('fileNameError')
regex = r"(.+)\.(.+)"
if re.search(regex, file_name_and_type):
match = re.search(regex, file_name_and_type)
file_name = match.group(1)
file_type = match.group(2).lower()
else:
raise fileNameError('fileNameError')
transcript = autosub(file_pwd, format="json")
print "Generated data structure: \n"
print(file_name_and_type)
whoosh_indexing(file_name_and_type,file_pwd,transcript, append_blob_service)
return transcript
# def autosubing(file_pwd,transcripts_timed_pwd,file_type):
# if not os.path.isfile(transcripts_timed_pwd):
# if file_format(file_type) == 1:
# # command = "python ./autosub/autosub.py -F json -V %s" %(file_pwd)
# # command = "python ./autosub/autosub.py %s -F json" %(file_pwd)
# autosub(file_pwd, format="json")
# elif file_format(file_type) == 2:
# # command = "python ./autosub/autosub.py %s -F json" %(file_pwd)
# autosub(file_pwd, format="json")
# else:
# autosub(file_pwd, format="json")
# print "Autosubed"
# else:
# print 'file has already been autosubed'
def whoosh_indexing(file_name,file_pwd,transcript, append_blob_service):
transcripts_timed = json.loads(transcript)
transcripts_content = ''
for i in transcripts_timed:
transcripts_content = transcripts_content + ' ' + i['content']
# Whoosh the search engine
schema = Schema(title=TEXT(stored=True), path=ID(stored=True), content=TEXT)
if not os.path.exists("temp_index"):
os.mkdir("temp_index")
#ix = index.create_in("temp_index", schema)
ix = index.open_dir("temp_index")
writer = ix.writer()
writer.update_document(title=file_name.decode('utf-8'), path=file_pwd.decode('utf-8'), content=transcripts_content.decode('utf-8'))
writer.commit()
# for filename in os.listdir('temp_index'):
# root, ext = os.path.splitext(filename)
# if root.startswith('MAIN_') and ext == '.seg':
# file = filename
# print(os.path.join('temp_index', file))
# append_blob_service.create_blob('search-file', file)
# append_blob_service.append_blob_from_path(
# 'search-file',
# file,
# os.path.join('temp_index', file)
# )
print("Written")
# throw formatError
def file_format(file_type):
if file_type in vedio_formats:
return 1;
elif file_type in audio_formats:
return 2
else:
return 3
|
normal
|
{
"blob_id": "7b5a16fdc536eb4ae3fdc08f827663613560187a",
"index": 8642,
"step-1": "import subprocess\nfrom whoosh.index import create_in\nfrom whoosh.fields import *\nimport os\nimport codecs\nfrom whoosh.qparser import QueryParser\nimport whoosh.index as index\nimport json\nfrom autosub.autosub import autosub\nfrom azure.storage.blob import AppendBlobService\n\nvedio_formats = ['mp4','avi','wmv','mov'] # 1\naudio_formats = ['wav','flac','mp3','aiff'] # 2\n\ndef file_upload(file_pwd, append_blob_service):\n\tregex = r\"(.+)\\/(.+)\"\n\tif re.search(regex, file_pwd):\n\t\tmatch = re.search(regex, file_pwd)\n\t\tfile_dir = match.group(1) + '/'\n\t\tfile_name_and_type = match.group(2).lower() \n\telse:\n\t\traise fileNameError('fileNameError')\n\tregex = r\"(.+)\\.(.+)\"\n\tif re.search(regex, file_name_and_type):\n\t match = re.search(regex, file_name_and_type)\n\t file_name = match.group(1)\n\t file_type = match.group(2).lower()\n\telse: \n\t\traise fileNameError('fileNameError')\n\ttranscript = autosub(file_pwd, format=\"json\")\n\tprint \"Generated data structure: \\n\"\n\tprint(file_name_and_type)\n\twhoosh_indexing(file_name_and_type,file_pwd,transcript, append_blob_service)\n\treturn transcript\n\n# def autosubing(file_pwd,transcripts_timed_pwd,file_type):\n# \tif not os.path.isfile(transcripts_timed_pwd):\n# \t\tif file_format(file_type) == 1:\t\n# \t\t\t# command = \"python ./autosub/autosub.py -F json -V %s\" %(file_pwd)\n# \t\t\t# command = \"python ./autosub/autosub.py %s -F json\" %(file_pwd)\n# \t\t\tautosub(file_pwd, format=\"json\")\n# \t\telif file_format(file_type) == 2:\n# \t\t\t# command = \"python ./autosub/autosub.py %s -F json\" %(file_pwd)\n# \t\t\tautosub(file_pwd, format=\"json\")\n# \t\telse:\n# \t\t\tautosub(file_pwd, format=\"json\")\n# \t\tprint \"Autosubed\"\n# \telse: \n# \t\tprint 'file has already been autosubed'\n\ndef whoosh_indexing(file_name,file_pwd,transcript, append_blob_service):\n\ttranscripts_timed = json.loads(transcript)\n\ttranscripts_content = ''\n\tfor i in transcripts_timed:\n\t\ttranscripts_content = transcripts_content + ' ' + i['content']\n\t# Whoosh the search engine\n\tschema = Schema(title=TEXT(stored=True), path=ID(stored=True), content=TEXT)\n\tif not os.path.exists(\"temp_index\"):\n\t os.mkdir(\"temp_index\")\n\t#ix = index.create_in(\"temp_index\", schema)\n\tix = index.open_dir(\"temp_index\")\n\twriter = ix.writer()\n\twriter.update_document(title=file_name.decode('utf-8'), path=file_pwd.decode('utf-8'), content=transcripts_content.decode('utf-8'))\n\twriter.commit()\n\n\t# for filename in os.listdir('temp_index'):\n\t# root, ext = os.path.splitext(filename)\n\t# if root.startswith('MAIN_') and ext == '.seg':\n\t# file = filename\n\n\t# print(os.path.join('temp_index', file))\n\t# append_blob_service.create_blob('search-file', file)\n\t# append_blob_service.append_blob_from_path(\n\t# \t'search-file',\n\t# \tfile,\n\t# \tos.path.join('temp_index', file)\n\t# )\n\tprint(\"Written\")\n\n# throw formatError\ndef file_format(file_type):\n\tif file_type in vedio_formats:\n\t\treturn 1;\n\telif file_type in audio_formats:\n\t\treturn 2\n\telse: \n\t\treturn 3\n\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
from __future__ import absolute_import, print_function
from django.db import models
from django.utils import timezone
from sentry.db.models import (
Model,
BaseManager,
UUIDField,
sane_repr,
)
class MonitorLocation(Model):
__core__ = True
guid = UUIDField(unique=True, auto_add=True)
name = models.CharField(max_length=128)
date_added = models.DateTimeField(default=timezone.now)
objects = BaseManager(cache_fields=('guid', ))
class Meta:
app_label = 'sentry'
db_table = 'sentry_monitorlocation'
__repr__ = sane_repr('guid', 'name')
|
normal
|
{
"blob_id": "1a4132358fa9bd4cd74970286ec8bb212b1857cd",
"index": 5247,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass MonitorLocation(Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n app_label = 'sentry'\n db_table = 'sentry_monitorlocation'\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass MonitorLocation(Model):\n __core__ = True\n guid = UUIDField(unique=True, auto_add=True)\n name = models.CharField(max_length=128)\n date_added = models.DateTimeField(default=timezone.now)\n objects = BaseManager(cache_fields=('guid',))\n\n\n class Meta:\n app_label = 'sentry'\n db_table = 'sentry_monitorlocation'\n __repr__ = sane_repr('guid', 'name')\n",
"step-4": "from __future__ import absolute_import, print_function\nfrom django.db import models\nfrom django.utils import timezone\nfrom sentry.db.models import Model, BaseManager, UUIDField, sane_repr\n\n\nclass MonitorLocation(Model):\n __core__ = True\n guid = UUIDField(unique=True, auto_add=True)\n name = models.CharField(max_length=128)\n date_added = models.DateTimeField(default=timezone.now)\n objects = BaseManager(cache_fields=('guid',))\n\n\n class Meta:\n app_label = 'sentry'\n db_table = 'sentry_monitorlocation'\n __repr__ = sane_repr('guid', 'name')\n",
"step-5": "from __future__ import absolute_import, print_function\n\nfrom django.db import models\nfrom django.utils import timezone\n\nfrom sentry.db.models import (\n Model,\n BaseManager,\n UUIDField,\n sane_repr,\n)\n\n\nclass MonitorLocation(Model):\n __core__ = True\n\n guid = UUIDField(unique=True, auto_add=True)\n name = models.CharField(max_length=128)\n date_added = models.DateTimeField(default=timezone.now)\n objects = BaseManager(cache_fields=('guid', ))\n\n class Meta:\n app_label = 'sentry'\n db_table = 'sentry_monitorlocation'\n\n __repr__ = sane_repr('guid', 'name')\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# Generated by Django 3.1.7 on 2021-02-20 02:52
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('usuarios', '0001_initial'),
('plataforma', '0005_auto_20210219_2343'),
]
operations = [
migrations.AlterField(
model_name='plataforma',
name='usuario',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='usuarios.usuario'),
),
]
|
normal
|
{
"blob_id": "3f9be81c86852a758440c6a144b8caba736b3868",
"index": 972,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('usuarios', '0001_initial'), ('plataforma',\n '0005_auto_20210219_2343')]\n operations = [migrations.AlterField(model_name='plataforma', name=\n 'usuario', field=models.ForeignKey(on_delete=django.db.models.\n deletion.CASCADE, to='usuarios.usuario'))]\n",
"step-4": "from django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n dependencies = [('usuarios', '0001_initial'), ('plataforma',\n '0005_auto_20210219_2343')]\n operations = [migrations.AlterField(model_name='plataforma', name=\n 'usuario', field=models.ForeignKey(on_delete=django.db.models.\n deletion.CASCADE, to='usuarios.usuario'))]\n",
"step-5": "# Generated by Django 3.1.7 on 2021-02-20 02:52\n\nfrom django.db import migrations, models\nimport django.db.models.deletion\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('usuarios', '0001_initial'),\n ('plataforma', '0005_auto_20210219_2343'),\n ]\n\n operations = [\n migrations.AlterField(\n model_name='plataforma',\n name='usuario',\n field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='usuarios.usuario'),\n ),\n ]\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
# Classe com os dados de um cliente que entra no sistema simulado.
class Client:
def __init__(self, id, color):
# Identificador do cliente, usada para o teste de correção.
self.id = id
# Tempo de chegada ao servidor (fila 1 e fila 2)
self.arrival = {}
# Tempo de saída do servidor (fila 1 e fila 2)
self.leave = {}
# Tempo no servidor (fila 1 e fila 2)
self.server = {}
# Indicador que diz qual fila o cliente está no momento
self.queue = 0
# Indicador que diz se o cliente já foi servido e saiu do sistema
self.served = 0
# Cor do cliente (TRANSIENT e EQUILIBRIUM)
self.color = color
def set_arrival(self, arrival):
self.arrival[self.queue] = arrival
def set_leave(self, leave):
self.leave[self.queue] = leave
def set_server(self, server):
self.server[self.queue] = server
def set_queue(self, queue):
self.queue = queue
def set_served(self, served):
self.served = served
# Tempo de espera na fila = Tempo de saída da fila para o servidor - Tempo de chegada na fila.
def wait(self, queue):
return (self.leave[queue] - self.arrival[queue])
|
normal
|
{
"blob_id": "5dc201f743705d6a57dfb61ec2cc2a827db0ba25",
"index": 7234,
"step-1": "class Client:\n\n def __init__(self, id, color):\n self.id = id\n self.arrival = {}\n self.leave = {}\n self.server = {}\n self.queue = 0\n self.served = 0\n self.color = color\n\n def set_arrival(self, arrival):\n self.arrival[self.queue] = arrival\n\n def set_leave(self, leave):\n self.leave[self.queue] = leave\n <mask token>\n <mask token>\n\n def set_served(self, served):\n self.served = served\n <mask token>\n",
"step-2": "class Client:\n\n def __init__(self, id, color):\n self.id = id\n self.arrival = {}\n self.leave = {}\n self.server = {}\n self.queue = 0\n self.served = 0\n self.color = color\n\n def set_arrival(self, arrival):\n self.arrival[self.queue] = arrival\n\n def set_leave(self, leave):\n self.leave[self.queue] = leave\n\n def set_server(self, server):\n self.server[self.queue] = server\n <mask token>\n\n def set_served(self, served):\n self.served = served\n <mask token>\n",
"step-3": "class Client:\n\n def __init__(self, id, color):\n self.id = id\n self.arrival = {}\n self.leave = {}\n self.server = {}\n self.queue = 0\n self.served = 0\n self.color = color\n\n def set_arrival(self, arrival):\n self.arrival[self.queue] = arrival\n\n def set_leave(self, leave):\n self.leave[self.queue] = leave\n\n def set_server(self, server):\n self.server[self.queue] = server\n\n def set_queue(self, queue):\n self.queue = queue\n\n def set_served(self, served):\n self.served = served\n <mask token>\n",
"step-4": "class Client:\n\n def __init__(self, id, color):\n self.id = id\n self.arrival = {}\n self.leave = {}\n self.server = {}\n self.queue = 0\n self.served = 0\n self.color = color\n\n def set_arrival(self, arrival):\n self.arrival[self.queue] = arrival\n\n def set_leave(self, leave):\n self.leave[self.queue] = leave\n\n def set_server(self, server):\n self.server[self.queue] = server\n\n def set_queue(self, queue):\n self.queue = queue\n\n def set_served(self, served):\n self.served = served\n\n def wait(self, queue):\n return self.leave[queue] - self.arrival[queue]\n",
"step-5": "# -*- coding:utf-8 -*-\n# Classe com os dados de um cliente que entra no sistema simulado.\n\nclass Client:\n def __init__(self, id, color):\n # Identificador do cliente, usada para o teste de correção.\n self.id = id\n # Tempo de chegada ao servidor (fila 1 e fila 2)\n self.arrival = {}\n # Tempo de saída do servidor (fila 1 e fila 2)\n self.leave = {}\n # Tempo no servidor (fila 1 e fila 2)\n self.server = {}\n # Indicador que diz qual fila o cliente está no momento\n self.queue = 0\n # Indicador que diz se o cliente já foi servido e saiu do sistema\n self.served = 0\n # Cor do cliente (TRANSIENT e EQUILIBRIUM)\n self.color = color\n\n def set_arrival(self, arrival):\n self.arrival[self.queue] = arrival\n\n def set_leave(self, leave):\n self.leave[self.queue] = leave\n\n def set_server(self, server):\n self.server[self.queue] = server\n\n def set_queue(self, queue):\n self.queue = queue\n \n def set_served(self, served):\n self.served = served\n\n # Tempo de espera na fila = Tempo de saída da fila para o servidor - Tempo de chegada na fila.\n def wait(self, queue):\n return (self.leave[queue] - self.arrival[queue])\n",
"step-ids": [
5,
6,
7,
8,
9
]
}
|
[
5,
6,
7,
8,
9
] |
def koodrinate(kraj, kraji):
for ime, x, y in kraji:
if ime == kraj:
return x, y
kraji = {
'Brežice': (68.66, 7.04),
'Lenart': (85.20, 78.75),
'Rateče': (-65.04, 70.04),
'Ljutomer': (111.26, 71.82),
'Rogaška Slatina': (71.00, 42.00),
'Ribnica': (7.10, -10.50),
'Dutovlje': (-56.80, -6.93),
'Lokve': (-57.94, 19.32),
'Vinica': (43.81, -38.43),
'Brtonigla': (-71.00, -47.25),
'Kanal': (-71.00, 26.25),
'Črnomelj': (39.05, -27.93),
'Trbovlje': (29.61, 35.07),
'Beltinci': (114.81, 80.54),
'Domžale': (-2.34, 31.50)
}
def koodrinate(kraj, kraji):
return kraji.get(kraj)
napis = "KRNEKI"
vrednost = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}
vsota = 0
for c in napis:
vsota += vrednost.get(c, 0)
print(sum(vrednost.get(c, 0) for c in napis))
for c in napis:
if c == "I":
vsota += 1
elif c == "V":
vsota += 5
elif c == "X":
vsota += 10
elif c == "L":
vsota += 50
elif c == "C":
vsota += 100
elif c == "D":
vsota += 500
elif c == "M":
vsota += 1000
|
normal
|
{
"blob_id": "2cfc1bea6dd1571eff67c3f49b2a1899560c7ba7",
"index": 3469,
"step-1": "def koodrinate(kraj, kraji):\n for ime, x, y in kraji:\n if ime == kraj:\n return x, y\n\n\n<mask token>\n",
"step-2": "def koodrinate(kraj, kraji):\n for ime, x, y in kraji:\n if ime == kraj:\n return x, y\n\n\n<mask token>\n\n\ndef koodrinate(kraj, kraji):\n return kraji.get(kraj)\n\n\n<mask token>\n",
"step-3": "def koodrinate(kraj, kraji):\n for ime, x, y in kraji:\n if ime == kraj:\n return x, y\n\n\n<mask token>\n\n\ndef koodrinate(kraj, kraji):\n return kraji.get(kraj)\n\n\n<mask token>\nfor c in napis:\n vsota += vrednost.get(c, 0)\nprint(sum(vrednost.get(c, 0) for c in napis))\nfor c in napis:\n if c == 'I':\n vsota += 1\n elif c == 'V':\n vsota += 5\n elif c == 'X':\n vsota += 10\n elif c == 'L':\n vsota += 50\n elif c == 'C':\n vsota += 100\n elif c == 'D':\n vsota += 500\n elif c == 'M':\n vsota += 1000\n",
"step-4": "def koodrinate(kraj, kraji):\n for ime, x, y in kraji:\n if ime == kraj:\n return x, y\n\n\nkraji = {'Brežice': (68.66, 7.04), 'Lenart': (85.2, 78.75), 'Rateče': (-\n 65.04, 70.04), 'Ljutomer': (111.26, 71.82), 'Rogaška Slatina': (71.0, \n 42.0), 'Ribnica': (7.1, -10.5), 'Dutovlje': (-56.8, -6.93), 'Lokve': (-\n 57.94, 19.32), 'Vinica': (43.81, -38.43), 'Brtonigla': (-71.0, -47.25),\n 'Kanal': (-71.0, 26.25), 'Črnomelj': (39.05, -27.93), 'Trbovlje': (\n 29.61, 35.07), 'Beltinci': (114.81, 80.54), 'Domžale': (-2.34, 31.5)}\n\n\ndef koodrinate(kraj, kraji):\n return kraji.get(kraj)\n\n\nnapis = 'KRNEKI'\nvrednost = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}\nvsota = 0\nfor c in napis:\n vsota += vrednost.get(c, 0)\nprint(sum(vrednost.get(c, 0) for c in napis))\nfor c in napis:\n if c == 'I':\n vsota += 1\n elif c == 'V':\n vsota += 5\n elif c == 'X':\n vsota += 10\n elif c == 'L':\n vsota += 50\n elif c == 'C':\n vsota += 100\n elif c == 'D':\n vsota += 500\n elif c == 'M':\n vsota += 1000\n",
"step-5": "def koodrinate(kraj, kraji):\n for ime, x, y in kraji:\n if ime == kraj:\n return x, y\n\n\nkraji = {\n 'Brežice': (68.66, 7.04),\n 'Lenart': (85.20, 78.75),\n 'Rateče': (-65.04, 70.04),\n 'Ljutomer': (111.26, 71.82),\n 'Rogaška Slatina': (71.00, 42.00),\n 'Ribnica': (7.10, -10.50),\n 'Dutovlje': (-56.80, -6.93),\n 'Lokve': (-57.94, 19.32),\n 'Vinica': (43.81, -38.43),\n 'Brtonigla': (-71.00, -47.25),\n 'Kanal': (-71.00, 26.25),\n 'Črnomelj': (39.05, -27.93),\n 'Trbovlje': (29.61, 35.07),\n 'Beltinci': (114.81, 80.54),\n 'Domžale': (-2.34, 31.50)\n}\n\n\ndef koodrinate(kraj, kraji):\n return kraji.get(kraj)\n\n\nnapis = \"KRNEKI\"\n\nvrednost = {\"I\": 1, \"V\": 5, \"X\": 10, \"L\": 50, \"C\": 100, \"D\": 500, \"M\": 1000}\n\nvsota = 0\n\nfor c in napis:\n vsota += vrednost.get(c, 0)\n\nprint(sum(vrednost.get(c, 0) for c in napis))\n\nfor c in napis:\n if c == \"I\":\n vsota += 1\n elif c == \"V\":\n vsota += 5\n elif c == \"X\":\n vsota += 10\n elif c == \"L\":\n vsota += 50\n elif c == \"C\":\n vsota += 100\n elif c == \"D\":\n vsota += 500\n elif c == \"M\":\n vsota += 1000\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
# ----------------------------------------------------------------------------
# Written by Khanh Nguyen Le
# May 4th 2019
# Discord: https://discord.io/skyrst
# ----------------------------------------------------------------------------
import operator
def validInput(x):
if x=="a": return True
elif x=="b": return True
elif x=="c": return True
elif x=="d": return True
else: return False
def takeInput():
x=input()
while not validInput(x):
print("Invalid input. Try another one:")
x=input()
return x
def main():
stats = {'Council':0, 'United':0, 'Faceless': 0, 'Warband':0}
print("Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.")
print("Answer the the following questions by typing a, b, c or d.")
print("1/8")
print("I'd die without my...\na. Freedom\nb. Knowledge\nc. Talent\nd. Hope")
x = takeInput()
if x=="a":
stats['Faceless'] += 1
elif x=="b":
stats['Council']+= 1
elif x=="c":
stats['Warband']+= 1
else:
stats['United']+= 1
print("2/8")
print("Pick an animal:\na. Owl\nb. Leopard\nc. Elepant\nd. Octopus")
x = takeInput()
if x=="a":
stats['Warband'] += 1
elif x=="b":
stats['Faceless']+= 1
elif x=="c":
stats['United']+= 1
else:
stats['Council']+= 1
print("3/8")
print("Wars are won...\na. In the heat of battle\nb. In the planning room\nc. With unbreaking resolve\nd. By the unpredictable")
x = takeInput()
if x=="a":
stats['Warband'] += 1
elif x=="b":
stats['Council']+= 1
elif x=="c":
stats['United']+= 1
else:
stats['Faceless']+= 1
print("4/8")
print("The perfect team would never...\na. Give up\nb. Lose focus\nc. Tell me what to do\nd. Feed my opponent")
x = takeInput()
if x=="a":
stats['United'] += 1
elif x=="b":
stats['Council']+= 1
elif x=="c":
stats['Warband']+= 1
else:
stats['Faceless']+= 1
print("5/8")
print("The enemy team is winning on all fronts. What do you do?\na. Outmaneuver them to steal some objectives\nb. Rally my team for a final stand\nc. Go pentakill them, like I always do\nd. This is right where I want them--I'll explain later")
x = takeInput()
if x=="a":
stats['Faceless'] += 1
elif x=="b":
stats['United']+= 1
elif x=="c":
stats['Warband']+= 1
else:
stats['Council']+= 1
print("6/8")
print("What's your favorite time of the day\na. Dawn\nb. Day\nc. Dusk\nd. Night")
x = takeInput()
if x=="a":
stats['United'] += 1
elif x=="b":
stats['Council']+= 1
elif x=="c":
stats['Faceless']+= 1
else:
stats['Warband']+= 1
print("7/8")
print("Which of these sounds like you\na. \"Can we please group\"\nb. \"Trust me. I'm not trolling\"\nc. \"ez\"\nd. \"WINNABLE\"")
x = takeInput()
if x=="a":
stats['Council'] += 1
elif x=="b":
stats['Faceless']+= 1
elif x=="c":
stats['Warband']+= 1
else:
stats['United']+= 1
print("8/8")
print("I want to be seen as a(n)...\na. Selfless leader\nb. Brilliant tactician\nc. Crafty wildcard\nd. Elite fighter")
x = takeInput()
if x=="a":
stats['United'] += 1
elif x=="b":
stats['Council']+= 1
elif x=="c":
stats['Faceless']+= 1
else:
stats['Warband']+= 1
print("\n")
result = max(stats.items(), key=operator.itemgetter(1))[0]
print("Congratulations! You are a " +result)
main()
|
normal
|
{
"blob_id": "5209638ec97a666783c102bec7a2b00991c41a08",
"index": 5438,
"step-1": "<mask token>\n\n\ndef takeInput():\n x = input()\n while not validInput(x):\n print('Invalid input. Try another one:')\n x = input()\n return x\n\n\ndef main():\n stats = {'Council': 0, 'United': 0, 'Faceless': 0, 'Warband': 0}\n print(\n \"Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.\"\n )\n print('Answer the the following questions by typing a, b, c or d.')\n print('1/8')\n print(\"I'd die without my...\\na. Freedom\\nb. Knowledge\\nc. Talent\\nd. Hope\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('2/8')\n print('Pick an animal:\\na. Owl\\nb. Leopard\\nc. Elepant\\nd. Octopus')\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Council'] += 1\n print('3/8')\n print(\n \"\"\"Wars are won...\na. In the heat of battle\nb. In the planning room\nc. With unbreaking resolve\nd. By the unpredictable\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Faceless'] += 1\n print('4/8')\n print(\n \"\"\"The perfect team would never...\na. Give up\nb. Lose focus\nc. Tell me what to do\nd. Feed my opponent\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Faceless'] += 1\n print('5/8')\n print(\n \"\"\"The enemy team is winning on all fronts. What do you do?\na. Outmaneuver them to steal some objectives\nb. Rally my team for a final stand\nc. Go pentakill them, like I always do\nd. This is right where I want them--I'll explain later\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['United'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Council'] += 1\n print('6/8')\n print(\n \"What's your favorite time of the day\\na. Dawn\\nb. Day\\nc. Dusk\\nd. Night\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('7/8')\n print(\n \"\"\"Which of these sounds like you\na. \"Can we please group\"\nb. \"Trust me. I'm not trolling\"\nc. \"ez\"\nd. \"WINNABLE\\\"\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Council'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('8/8')\n print(\n \"\"\"I want to be seen as a(n)...\na. Selfless leader\nb. Brilliant tactician\nc. Crafty wildcard\nd. Elite fighter\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('\\n')\n result = max(stats.items(), key=operator.itemgetter(1))[0]\n print('Congratulations! You are a ' + result)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef validInput(x):\n if x == 'a':\n return True\n elif x == 'b':\n return True\n elif x == 'c':\n return True\n elif x == 'd':\n return True\n else:\n return False\n\n\ndef takeInput():\n x = input()\n while not validInput(x):\n print('Invalid input. Try another one:')\n x = input()\n return x\n\n\ndef main():\n stats = {'Council': 0, 'United': 0, 'Faceless': 0, 'Warband': 0}\n print(\n \"Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.\"\n )\n print('Answer the the following questions by typing a, b, c or d.')\n print('1/8')\n print(\"I'd die without my...\\na. Freedom\\nb. Knowledge\\nc. Talent\\nd. Hope\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('2/8')\n print('Pick an animal:\\na. Owl\\nb. Leopard\\nc. Elepant\\nd. Octopus')\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Council'] += 1\n print('3/8')\n print(\n \"\"\"Wars are won...\na. In the heat of battle\nb. In the planning room\nc. With unbreaking resolve\nd. By the unpredictable\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Faceless'] += 1\n print('4/8')\n print(\n \"\"\"The perfect team would never...\na. Give up\nb. Lose focus\nc. Tell me what to do\nd. Feed my opponent\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Faceless'] += 1\n print('5/8')\n print(\n \"\"\"The enemy team is winning on all fronts. What do you do?\na. Outmaneuver them to steal some objectives\nb. Rally my team for a final stand\nc. Go pentakill them, like I always do\nd. This is right where I want them--I'll explain later\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['United'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Council'] += 1\n print('6/8')\n print(\n \"What's your favorite time of the day\\na. Dawn\\nb. Day\\nc. Dusk\\nd. Night\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('7/8')\n print(\n \"\"\"Which of these sounds like you\na. \"Can we please group\"\nb. \"Trust me. I'm not trolling\"\nc. \"ez\"\nd. \"WINNABLE\\\"\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Council'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('8/8')\n print(\n \"\"\"I want to be seen as a(n)...\na. Selfless leader\nb. Brilliant tactician\nc. Crafty wildcard\nd. Elite fighter\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('\\n')\n result = max(stats.items(), key=operator.itemgetter(1))[0]\n print('Congratulations! You are a ' + result)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef validInput(x):\n if x == 'a':\n return True\n elif x == 'b':\n return True\n elif x == 'c':\n return True\n elif x == 'd':\n return True\n else:\n return False\n\n\ndef takeInput():\n x = input()\n while not validInput(x):\n print('Invalid input. Try another one:')\n x = input()\n return x\n\n\ndef main():\n stats = {'Council': 0, 'United': 0, 'Faceless': 0, 'Warband': 0}\n print(\n \"Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.\"\n )\n print('Answer the the following questions by typing a, b, c or d.')\n print('1/8')\n print(\"I'd die without my...\\na. Freedom\\nb. Knowledge\\nc. Talent\\nd. Hope\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('2/8')\n print('Pick an animal:\\na. Owl\\nb. Leopard\\nc. Elepant\\nd. Octopus')\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Council'] += 1\n print('3/8')\n print(\n \"\"\"Wars are won...\na. In the heat of battle\nb. In the planning room\nc. With unbreaking resolve\nd. By the unpredictable\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Faceless'] += 1\n print('4/8')\n print(\n \"\"\"The perfect team would never...\na. Give up\nb. Lose focus\nc. Tell me what to do\nd. Feed my opponent\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Faceless'] += 1\n print('5/8')\n print(\n \"\"\"The enemy team is winning on all fronts. What do you do?\na. Outmaneuver them to steal some objectives\nb. Rally my team for a final stand\nc. Go pentakill them, like I always do\nd. This is right where I want them--I'll explain later\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['United'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Council'] += 1\n print('6/8')\n print(\n \"What's your favorite time of the day\\na. Dawn\\nb. Day\\nc. Dusk\\nd. Night\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('7/8')\n print(\n \"\"\"Which of these sounds like you\na. \"Can we please group\"\nb. \"Trust me. I'm not trolling\"\nc. \"ez\"\nd. \"WINNABLE\\\"\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Council'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('8/8')\n print(\n \"\"\"I want to be seen as a(n)...\na. Selfless leader\nb. Brilliant tactician\nc. Crafty wildcard\nd. Elite fighter\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('\\n')\n result = max(stats.items(), key=operator.itemgetter(1))[0]\n print('Congratulations! You are a ' + result)\n\n\nmain()\n",
"step-4": "import operator\n\n\ndef validInput(x):\n if x == 'a':\n return True\n elif x == 'b':\n return True\n elif x == 'c':\n return True\n elif x == 'd':\n return True\n else:\n return False\n\n\ndef takeInput():\n x = input()\n while not validInput(x):\n print('Invalid input. Try another one:')\n x = input()\n return x\n\n\ndef main():\n stats = {'Council': 0, 'United': 0, 'Faceless': 0, 'Warband': 0}\n print(\n \"Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.\"\n )\n print('Answer the the following questions by typing a, b, c or d.')\n print('1/8')\n print(\"I'd die without my...\\na. Freedom\\nb. Knowledge\\nc. Talent\\nd. Hope\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('2/8')\n print('Pick an animal:\\na. Owl\\nb. Leopard\\nc. Elepant\\nd. Octopus')\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Council'] += 1\n print('3/8')\n print(\n \"\"\"Wars are won...\na. In the heat of battle\nb. In the planning room\nc. With unbreaking resolve\nd. By the unpredictable\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Warband'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['United'] += 1\n else:\n stats['Faceless'] += 1\n print('4/8')\n print(\n \"\"\"The perfect team would never...\na. Give up\nb. Lose focus\nc. Tell me what to do\nd. Feed my opponent\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Faceless'] += 1\n print('5/8')\n print(\n \"\"\"The enemy team is winning on all fronts. What do you do?\na. Outmaneuver them to steal some objectives\nb. Rally my team for a final stand\nc. Go pentakill them, like I always do\nd. This is right where I want them--I'll explain later\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Faceless'] += 1\n elif x == 'b':\n stats['United'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['Council'] += 1\n print('6/8')\n print(\n \"What's your favorite time of the day\\na. Dawn\\nb. Day\\nc. Dusk\\nd. Night\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('7/8')\n print(\n \"\"\"Which of these sounds like you\na. \"Can we please group\"\nb. \"Trust me. I'm not trolling\"\nc. \"ez\"\nd. \"WINNABLE\\\"\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['Council'] += 1\n elif x == 'b':\n stats['Faceless'] += 1\n elif x == 'c':\n stats['Warband'] += 1\n else:\n stats['United'] += 1\n print('8/8')\n print(\n \"\"\"I want to be seen as a(n)...\na. Selfless leader\nb. Brilliant tactician\nc. Crafty wildcard\nd. Elite fighter\"\"\"\n )\n x = takeInput()\n if x == 'a':\n stats['United'] += 1\n elif x == 'b':\n stats['Council'] += 1\n elif x == 'c':\n stats['Faceless'] += 1\n else:\n stats['Warband'] += 1\n print('\\n')\n result = max(stats.items(), key=operator.itemgetter(1))[0]\n print('Congratulations! You are a ' + result)\n\n\nmain()\n",
"step-5": "# ----------------------------------------------------------------------------\r\n# Written by Khanh Nguyen Le\r\n# May 4th 2019\r\n# Discord: https://discord.io/skyrst\r\n# ----------------------------------------------------------------------------\r\nimport operator\r\ndef validInput(x):\r\n if x==\"a\": return True\r\n elif x==\"b\": return True\r\n elif x==\"c\": return True\r\n elif x==\"d\": return True\r\n else: return False\r\n \r\ndef takeInput():\r\n x=input()\r\n while not validInput(x):\r\n print(\"Invalid input. Try another one:\")\r\n x=input()\r\n return x\r\n \r\ndef main():\r\n stats = {'Council':0, 'United':0, 'Faceless': 0, 'Warband':0}\r\n print(\"Welcome to Skyrst's open-source recreation of League of Legends house entrance quiz.\")\r\n print(\"Answer the the following questions by typing a, b, c or d.\")\r\n print(\"1/8\")\r\n print(\"I'd die without my...\\na. Freedom\\nb. Knowledge\\nc. Talent\\nd. Hope\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['Faceless'] += 1\r\n elif x==\"b\":\r\n stats['Council']+= 1\r\n elif x==\"c\":\r\n stats['Warband']+= 1\r\n else:\r\n stats['United']+= 1\r\n print(\"2/8\")\r\n print(\"Pick an animal:\\na. Owl\\nb. Leopard\\nc. Elepant\\nd. Octopus\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['Warband'] += 1\r\n elif x==\"b\":\r\n stats['Faceless']+= 1\r\n elif x==\"c\":\r\n stats['United']+= 1\r\n else:\r\n stats['Council']+= 1\r\n print(\"3/8\")\r\n print(\"Wars are won...\\na. In the heat of battle\\nb. In the planning room\\nc. With unbreaking resolve\\nd. By the unpredictable\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['Warband'] += 1\r\n elif x==\"b\":\r\n stats['Council']+= 1\r\n elif x==\"c\":\r\n stats['United']+= 1\r\n else:\r\n stats['Faceless']+= 1\r\n print(\"4/8\")\r\n print(\"The perfect team would never...\\na. Give up\\nb. Lose focus\\nc. Tell me what to do\\nd. Feed my opponent\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['United'] += 1\r\n elif x==\"b\":\r\n stats['Council']+= 1\r\n elif x==\"c\":\r\n stats['Warband']+= 1\r\n else:\r\n stats['Faceless']+= 1\r\n print(\"5/8\")\r\n print(\"The enemy team is winning on all fronts. What do you do?\\na. Outmaneuver them to steal some objectives\\nb. Rally my team for a final stand\\nc. Go pentakill them, like I always do\\nd. This is right where I want them--I'll explain later\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['Faceless'] += 1\r\n elif x==\"b\":\r\n stats['United']+= 1\r\n elif x==\"c\":\r\n stats['Warband']+= 1\r\n else:\r\n stats['Council']+= 1\r\n print(\"6/8\")\r\n print(\"What's your favorite time of the day\\na. Dawn\\nb. Day\\nc. Dusk\\nd. Night\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['United'] += 1\r\n elif x==\"b\":\r\n stats['Council']+= 1\r\n elif x==\"c\":\r\n stats['Faceless']+= 1\r\n else:\r\n stats['Warband']+= 1\r\n print(\"7/8\")\r\n print(\"Which of these sounds like you\\na. \\\"Can we please group\\\"\\nb. \\\"Trust me. I'm not trolling\\\"\\nc. \\\"ez\\\"\\nd. \\\"WINNABLE\\\"\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['Council'] += 1\r\n elif x==\"b\":\r\n stats['Faceless']+= 1\r\n elif x==\"c\":\r\n stats['Warband']+= 1\r\n else:\r\n stats['United']+= 1\r\n print(\"8/8\")\r\n print(\"I want to be seen as a(n)...\\na. Selfless leader\\nb. Brilliant tactician\\nc. Crafty wildcard\\nd. Elite fighter\")\r\n x = takeInput()\r\n if x==\"a\":\r\n stats['United'] += 1\r\n elif x==\"b\":\r\n stats['Council']+= 1\r\n elif x==\"c\":\r\n stats['Faceless']+= 1\r\n else:\r\n stats['Warband']+= 1\r\n print(\"\\n\")\r\n \r\n result = max(stats.items(), key=operator.itemgetter(1))[0]\r\n print(\"Congratulations! You are a \" +result)\r\n\r\n\r\nmain()",
"step-ids": [
2,
3,
4,
5,
6
]
}
|
[
2,
3,
4,
5,
6
] |
from estmd import ESTMD
input_directory = "test.avi"
e = ESTMD()
e.open_movie(input_directory)
e.run(by_frame=True)
r = e.create_list_of_arrays()
print "Done testing!"
|
normal
|
{
"blob_id": "1fd4d1a44270ef29512e601af737accb916dc441",
"index": 974,
"step-1": "from estmd import ESTMD\n\ninput_directory = \"test.avi\"\ne = ESTMD()\ne.open_movie(input_directory)\ne.run(by_frame=True)\nr = e.create_list_of_arrays()\n\nprint \"Done testing!\"\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
# Required python libraries for attack.py
import socket
import os
import sys
from termcolor import colored
import StringIO
import time
# need to find Python equivalent libraries for these
import stdio
import stdlib
import unistd
# need to find Python equivalent libraries for these
import includes
import killer
import main
import protocol
import rand
import resolv
import scanner
import table
import util
def checksum_tcp_udp(ip_header, buffer_name, data_length, lenth):
return sum_checksum_tcp_udp
def checksum_generic(address, count):
return sum_checksum_generic
|
normal
|
{
"blob_id": "6d25b0fedf0d5081a3a0a93ddacc49748464d9d0",
"index": 405,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef checksum_tcp_udp(ip_header, buffer_name, data_length, lenth):\n return sum_checksum_tcp_udp\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef checksum_tcp_udp(ip_header, buffer_name, data_length, lenth):\n return sum_checksum_tcp_udp\n\n\ndef checksum_generic(address, count):\n return sum_checksum_generic\n",
"step-4": "import socket\nimport os\nimport sys\nfrom termcolor import colored\nimport StringIO\nimport time\nimport stdio\nimport stdlib\nimport unistd\nimport includes\nimport killer\nimport main\nimport protocol\nimport rand\nimport resolv\nimport scanner\nimport table\nimport util\n\n\ndef checksum_tcp_udp(ip_header, buffer_name, data_length, lenth):\n return sum_checksum_tcp_udp\n\n\ndef checksum_generic(address, count):\n return sum_checksum_generic\n",
"step-5": "# Required python libraries for attack.py\nimport socket\nimport os\nimport sys\nfrom termcolor import colored\nimport StringIO\nimport time\n\n# need to find Python equivalent libraries for these\n\nimport stdio\nimport stdlib\nimport unistd\n# need to find Python equivalent libraries for these\n\nimport includes\nimport killer\nimport main\nimport protocol\nimport rand\nimport resolv\nimport scanner\nimport table\nimport util\n\ndef checksum_tcp_udp(ip_header, buffer_name, data_length, lenth):\n return sum_checksum_tcp_udp\n\ndef checksum_generic(address, count):\n return sum_checksum_generic\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
#!/usr/bin/python
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
occl_frac = 0.445188
result = [1-occl_frac, occl_frac, 0]
#Reading res_data.txt
mnfa = [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9] #min NN factor array
nna = [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,24,26,28,30] #NN Aray
fraction_data=[[[0.0 for i in range(len(mnfa))] for j in range(len(nna))] for k in range(3)]
df = open("res_data.txt", "r")
while(True):
try:
x = df.readline()
y = map(float,x.split())
if y==[]:
break
mnfa_index = mnfa.index(y[0])
nna_index = nna.index(y[1])
df.readline() #Get no. of points in each
df.readline() #Get blown up fractions
frdata = map(float,df.readline().split()) #get actual fractions
assert(len(frdata) == 3)
for i in range(3):
fraction_data[i][nna_index][mnfa_index] = frdata[i]
except(IOError):
print "What?"
break
print "Read all data from file, plotting stuff..."
fig = plt.figure()
for i in range(3):
ax = fig.add_subplot(1,3,i, projection='3d')
X = mnfa
xlen = len(X)
Y = nna
ylen = len(Y)
X, Y = np.meshgrid(X, Y)
Z = fraction_data[i]
colortuple = ('r', 'b')
colors = np.empty(X.shape, dtype=str)
for y in range(ylen):
for x in range(xlen):
colors[y, x] = colortuple[(x+y) % len(colortuple)]
ax.plot_surface(X,Y,Z,rstride=1, cstride=1, cmap=cm.coolwarm, linewidth=0)
plt.show()
|
normal
|
{
"blob_id": "1c8b843174521f1056e2bac472c87d0b5ec9603e",
"index": 3370,
"step-1": "#!/usr/bin/python\nimport matplotlib.pyplot as plt\nfrom matplotlib import cm\nfrom mpl_toolkits.mplot3d import Axes3D\nimport numpy as np\n\noccl_frac = 0.445188\nresult = [1-occl_frac, occl_frac, 0]\n\n#Reading res_data.txt\nmnfa = [0.0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9] #min NN factor array\nnna = [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,24,26,28,30] #NN Aray\n\nfraction_data=[[[0.0 for i in range(len(mnfa))] for j in range(len(nna))] for k in range(3)]\n\ndf = open(\"res_data.txt\", \"r\")\nwhile(True):\n try:\n x = df.readline()\n y = map(float,x.split())\n if y==[]:\n break\n mnfa_index = mnfa.index(y[0])\n nna_index = nna.index(y[1])\n df.readline() #Get no. of points in each\n df.readline() #Get blown up fractions\n frdata = map(float,df.readline().split()) #get actual fractions\n assert(len(frdata) == 3)\n for i in range(3):\n fraction_data[i][nna_index][mnfa_index] = frdata[i]\n except(IOError):\n print \"What?\"\n break\nprint \"Read all data from file, plotting stuff...\"\n\nfig = plt.figure()\n\nfor i in range(3):\n ax = fig.add_subplot(1,3,i, projection='3d')\n X = mnfa\n xlen = len(X)\n Y = nna\n ylen = len(Y)\n X, Y = np.meshgrid(X, Y)\n Z = fraction_data[i]\n colortuple = ('r', 'b')\n colors = np.empty(X.shape, dtype=str)\n for y in range(ylen):\n for x in range(xlen):\n colors[y, x] = colortuple[(x+y) % len(colortuple)]\n ax.plot_surface(X,Y,Z,rstride=1, cstride=1, cmap=cm.coolwarm, linewidth=0)\nplt.show()\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
import uuid
from datetime import date
import os
import humanize
class Context:
def __init__(self, function_name, function_version):
self.function_name = function_name
self.function_version = function_version
self.invoked_function_arn = "arn:aws:lambda:eu-north-1:000000000000:function:{}".format(self.function_name)
self.aws_request_id = uuid.uuid1()
self.log_group_name = "/aws/lambda/{}".format(self.function_name)
today = date.today()
self.log_stream_name = "{}/[{}]4459c970fa6d4c77aca62c95850fce54".format(today.strftime("%Y/%m/%d"), self.function_version)
self.memory_limit_in_mb = Context.memory(self)
pass
def memory(self):
mem = int(os.popen("cat /sys/fs/cgroup/memory/memory.limit_in_bytes").read())
self.memory_limit_in_mb = humanize.naturalsize(mem, gnu=True)
return (self.memory_limit_in_mb)
pass
|
normal
|
{
"blob_id": "1c685514f53a320226402a4e4d8f3b3187fad615",
"index": 7814,
"step-1": "<mask token>\n\n\nclass Context:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Context:\n\n def __init__(self, function_name, function_version):\n self.function_name = function_name\n self.function_version = function_version\n self.invoked_function_arn = (\n 'arn:aws:lambda:eu-north-1:000000000000:function:{}'.format(\n self.function_name))\n self.aws_request_id = uuid.uuid1()\n self.log_group_name = '/aws/lambda/{}'.format(self.function_name)\n today = date.today()\n self.log_stream_name = ('{}/[{}]4459c970fa6d4c77aca62c95850fce54'.\n format(today.strftime('%Y/%m/%d'), self.function_version))\n self.memory_limit_in_mb = Context.memory(self)\n pass\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Context:\n\n def __init__(self, function_name, function_version):\n self.function_name = function_name\n self.function_version = function_version\n self.invoked_function_arn = (\n 'arn:aws:lambda:eu-north-1:000000000000:function:{}'.format(\n self.function_name))\n self.aws_request_id = uuid.uuid1()\n self.log_group_name = '/aws/lambda/{}'.format(self.function_name)\n today = date.today()\n self.log_stream_name = ('{}/[{}]4459c970fa6d4c77aca62c95850fce54'.\n format(today.strftime('%Y/%m/%d'), self.function_version))\n self.memory_limit_in_mb = Context.memory(self)\n pass\n\n def memory(self):\n mem = int(os.popen(\n 'cat /sys/fs/cgroup/memory/memory.limit_in_bytes').read())\n self.memory_limit_in_mb = humanize.naturalsize(mem, gnu=True)\n return self.memory_limit_in_mb\n pass\n",
"step-4": "import uuid\nfrom datetime import date\nimport os\nimport humanize\n\n\nclass Context:\n\n def __init__(self, function_name, function_version):\n self.function_name = function_name\n self.function_version = function_version\n self.invoked_function_arn = (\n 'arn:aws:lambda:eu-north-1:000000000000:function:{}'.format(\n self.function_name))\n self.aws_request_id = uuid.uuid1()\n self.log_group_name = '/aws/lambda/{}'.format(self.function_name)\n today = date.today()\n self.log_stream_name = ('{}/[{}]4459c970fa6d4c77aca62c95850fce54'.\n format(today.strftime('%Y/%m/%d'), self.function_version))\n self.memory_limit_in_mb = Context.memory(self)\n pass\n\n def memory(self):\n mem = int(os.popen(\n 'cat /sys/fs/cgroup/memory/memory.limit_in_bytes').read())\n self.memory_limit_in_mb = humanize.naturalsize(mem, gnu=True)\n return self.memory_limit_in_mb\n pass\n",
"step-5": "import uuid\nfrom datetime import date\nimport os\nimport humanize\n\n\nclass Context:\n def __init__(self, function_name, function_version):\n self.function_name = function_name\n self.function_version = function_version\n self.invoked_function_arn = \"arn:aws:lambda:eu-north-1:000000000000:function:{}\".format(self.function_name)\n self.aws_request_id = uuid.uuid1()\n self.log_group_name = \"/aws/lambda/{}\".format(self.function_name)\n today = date.today()\n self.log_stream_name = \"{}/[{}]4459c970fa6d4c77aca62c95850fce54\".format(today.strftime(\"%Y/%m/%d\"), self.function_version)\n self.memory_limit_in_mb = Context.memory(self)\n pass\n\n def memory(self):\n mem = int(os.popen(\"cat /sys/fs/cgroup/memory/memory.limit_in_bytes\").read())\n self.memory_limit_in_mb = humanize.naturalsize(mem, gnu=True)\n return (self.memory_limit_in_mb)\n pass\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
from e19_pizza import *
print("\n----------导入模块中的所有函数----------")
# 由于导入了每个函数，可通过名称来调用每个函数，无需使用句点表示法
make_pizza(16, 'pepperoni')
make_pizza(12, 'mushrooms', 'green peppers', 'extra cheese')
# 注意:
# 使用并非自己编写的大型模块时，最好不要采用这种导入方法，如果模块中
# 有函数的名称与你的项目中使用的名称相同，可能导致意想不到的结果。
# Python可能遇到多个名称相同的函数或变量，进而覆盖函数，而不是分别导
# 入所有的函数。
# 最佳做法:
# 导入需要使用的函数，或者导入整个模块并使用句点表示法。
|
normal
|
{
"blob_id": "c54a046ebde1be94ec87061b4fba9e22bf0f4d0a",
"index": 3508,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\"\"\"\n----------导入模块中的所有函数----------\"\"\")\nmake_pizza(16, 'pepperoni')\nmake_pizza(12, 'mushrooms', 'green peppers', 'extra cheese')\n",
"step-3": "from e19_pizza import *\nprint(\"\"\"\n----------导入模块中的所有函数----------\"\"\")\nmake_pizza(16, 'pepperoni')\nmake_pizza(12, 'mushrooms', 'green peppers', 'extra cheese')\n",
"step-4": "from e19_pizza import *\n\nprint(\"\\n----------导入模块中的所有函数----------\")\n# 由于导入了每个函数，可通过名称来调用每个函数，无需使用句点表示法\n\nmake_pizza(16, 'pepperoni')\nmake_pizza(12, 'mushrooms', 'green peppers', 'extra cheese')\n\n# 注意:\n# 使用并非自己编写的大型模块时，最好不要采用这种导入方法，如果模块中\n# 有函数的名称与你的项目中使用的名称相同，可能导致意想不到的结果。\n# Python可能遇到多个名称相同的函数或变量，进而覆盖函数，而不是分别导\n# 入所有的函数。\n\n# 最佳做法:\n# 导入需要使用的函数，或者导入整个模块并使用句点表示法。\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
import serial
import time
def main():
# '/dev/tty****' is your port ID
con=serial.Serial('/dev/tty****', 9600)
print('connected.')
while 1:
str=con.readline() # byte code
print (str.strip().decode('utf-8')) # decoded string
if __name__ == '__main__':
main()
|
normal
|
{
"blob_id": "108c8bbb4d3dbc6b7f32e084b13009296b3c5a80",
"index": 8016,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n con = serial.Serial('/dev/tty****', 9600)\n print('connected.')\n while 1:\n str = con.readline()\n print(str.strip().decode('utf-8'))\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef main():\n con = serial.Serial('/dev/tty****', 9600)\n print('connected.')\n while 1:\n str = con.readline()\n print(str.strip().decode('utf-8'))\n\n\nif __name__ == '__main__':\n main()\n",
"step-4": "import serial\nimport time\n\n\ndef main():\n con = serial.Serial('/dev/tty****', 9600)\n print('connected.')\n while 1:\n str = con.readline()\n print(str.strip().decode('utf-8'))\n\n\nif __name__ == '__main__':\n main()\n",
"step-5": "import serial\nimport time\n\ndef main():\n # '/dev/tty****' is your port ID\n con=serial.Serial('/dev/tty****', 9600)\n print('connected.')\n while 1:\n str=con.readline() # byte code\n print (str.strip().decode('utf-8')) # decoded string\n\nif __name__ == '__main__':\n main()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
def bfs(graph, start):
queue = [start]
queued = list()
path = list()
while queue:
print('Queue is: %s' % queue)
vertex = queue.pop(0)
print('Processing %s' % vertex)
for candidate in graph[vertex]:
if candidate not in queued:
queued.append(candidate)
queue.append(candidate)
path.append(vertex + '>' + candidate)
print('Adding %s to the queue' % candidate)
return path
|
normal
|
{
"blob_id": "7bb49712c4ef482c64f3c2a457a766de691ba7c3",
"index": 9427,
"step-1": "<mask token>\n",
"step-2": "def bfs(graph, start):\n queue = [start]\n queued = list()\n path = list()\n while queue:\n print('Queue is: %s' % queue)\n vertex = queue.pop(0)\n print('Processing %s' % vertex)\n for candidate in graph[vertex]:\n if candidate not in queued:\n queued.append(candidate)\n queue.append(candidate)\n path.append(vertex + '>' + candidate)\n print('Adding %s to the queue' % candidate)\n return path\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
from QnA_processor.question_analysis.google_question_classifier import GoogleQuestionClassifier
def classify_question(query):
try:
"""
Get answer-type from google autoML classifier
(by making POST requests with authorization key)
"""
question_classifier = GoogleQuestionClassifier()
answer_type = question_classifier.classify_by_api_call(query)
except KeyError :
"""
Get answer-type from google autoML classifier
(without authorization key by using google package)
"""
answer_type = question_classifier.classify_by_package(query)
except:
"""
Get answer-type from custom question classifier
"""
from QnA_processor.question_analysis.custom_question_classifier import CustomQuestionClassifier
question_classifier = CustomQuestionClassifier()
answer_type = question_classifier.classify_question(query)[0]
return answer_type
# print (classify_question("How many seasons are there in a year"))
|
normal
|
{
"blob_id": "db231ea92319414dd10ca8dfbc14e5a70ed2fe44",
"index": 7343,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef classify_question(query):\n try:\n \"\"\"\n Get answer-type from google autoML classifier \n (by making POST requests with authorization key)\n \"\"\"\n question_classifier = GoogleQuestionClassifier()\n answer_type = question_classifier.classify_by_api_call(query)\n except KeyError:\n \"\"\"\n Get answer-type from google autoML classifier \n (without authorization key by using google package)\n \"\"\"\n answer_type = question_classifier.classify_by_package(query)\n except:\n \"\"\"\n Get answer-type from custom question classifier\n \"\"\"\n from QnA_processor.question_analysis.custom_question_classifier import CustomQuestionClassifier\n question_classifier = CustomQuestionClassifier()\n answer_type = question_classifier.classify_question(query)[0]\n return answer_type\n",
"step-3": "from QnA_processor.question_analysis.google_question_classifier import GoogleQuestionClassifier\n\n\ndef classify_question(query):\n try:\n \"\"\"\n Get answer-type from google autoML classifier \n (by making POST requests with authorization key)\n \"\"\"\n question_classifier = GoogleQuestionClassifier()\n answer_type = question_classifier.classify_by_api_call(query)\n except KeyError:\n \"\"\"\n Get answer-type from google autoML classifier \n (without authorization key by using google package)\n \"\"\"\n answer_type = question_classifier.classify_by_package(query)\n except:\n \"\"\"\n Get answer-type from custom question classifier\n \"\"\"\n from QnA_processor.question_analysis.custom_question_classifier import CustomQuestionClassifier\n question_classifier = CustomQuestionClassifier()\n answer_type = question_classifier.classify_question(query)[0]\n return answer_type\n",
"step-4": " \r\n \r\nfrom QnA_processor.question_analysis.google_question_classifier import GoogleQuestionClassifier\r\n \r\ndef classify_question(query):\r\n \r\n try:\r\n \"\"\"\r\n Get answer-type from google autoML classifier \r\n (by making POST requests with authorization key)\r\n \"\"\"\r\n question_classifier = GoogleQuestionClassifier()\r\n answer_type = question_classifier.classify_by_api_call(query)\r\n except KeyError :\r\n \"\"\"\r\n Get answer-type from google autoML classifier \r\n (without authorization key by using google package)\r\n \"\"\"\r\n answer_type = question_classifier.classify_by_package(query)\r\n \r\n except:\r\n \"\"\"\r\n Get answer-type from custom question classifier\r\n \"\"\"\r\n from QnA_processor.question_analysis.custom_question_classifier import CustomQuestionClassifier\r\n question_classifier = CustomQuestionClassifier()\r\n answer_type = question_classifier.classify_question(query)[0]\r\n \r\n return answer_type\r\n\r\n# print (classify_question(\"How many seasons are there in a year\"))",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
## This file is the celeryconfig for the Task Worker (scanworker).
from scanworker.commonconfig import *
import sys
sys.path.append('.')
BROKER_CONF = {
'uid' : '{{ mq_user }}',
'pass' : '{{ mq_password }}',
'host' : '{{ mq_host }}',
'port' : '5672',
'vhost' : '{{ mq_vhost }}',
}
BROKER_URL = 'amqp://'+BROKER_CONF['uid']+':'+BROKER_CONF['pass']+'@'+BROKER_CONF['host']+':'+BROKER_CONF['port']+'/'+BROKER_CONF['vhost']
BROKER_HEARTBEAT=True
CELERY_IMPORTS = ('scanworker.tasks',)
from scanworker.tasks import VALID_SCANNERS as vs
VALID_SCANNERS=vs()
CELERY_QUEUES = VALID_SCANNERS.celery_virus_scan_queues()
CELERY_ROUTES = VALID_SCANNERS.celery_virus_scan_routes()
|
normal
|
{
"blob_id": "1a569b88c350124968212cb910bef7b09b166152",
"index": 8990,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('.')\n<mask token>\n",
"step-3": "<mask token>\nsys.path.append('.')\nBROKER_CONF = {'uid': '{{ mq_user }}', 'pass': '{{ mq_password }}', 'host':\n '{{ mq_host }}', 'port': '5672', 'vhost': '{{ mq_vhost }}'}\nBROKER_URL = 'amqp://' + BROKER_CONF['uid'] + ':' + BROKER_CONF['pass'\n ] + '@' + BROKER_CONF['host'] + ':' + BROKER_CONF['port'\n ] + '/' + BROKER_CONF['vhost']\nBROKER_HEARTBEAT = True\nCELERY_IMPORTS = 'scanworker.tasks',\n<mask token>\nVALID_SCANNERS = vs()\nCELERY_QUEUES = VALID_SCANNERS.celery_virus_scan_queues()\nCELERY_ROUTES = VALID_SCANNERS.celery_virus_scan_routes()\n",
"step-4": "from scanworker.commonconfig import *\nimport sys\nsys.path.append('.')\nBROKER_CONF = {'uid': '{{ mq_user }}', 'pass': '{{ mq_password }}', 'host':\n '{{ mq_host }}', 'port': '5672', 'vhost': '{{ mq_vhost }}'}\nBROKER_URL = 'amqp://' + BROKER_CONF['uid'] + ':' + BROKER_CONF['pass'\n ] + '@' + BROKER_CONF['host'] + ':' + BROKER_CONF['port'\n ] + '/' + BROKER_CONF['vhost']\nBROKER_HEARTBEAT = True\nCELERY_IMPORTS = 'scanworker.tasks',\nfrom scanworker.tasks import VALID_SCANNERS as vs\nVALID_SCANNERS = vs()\nCELERY_QUEUES = VALID_SCANNERS.celery_virus_scan_queues()\nCELERY_ROUTES = VALID_SCANNERS.celery_virus_scan_routes()\n",
"step-5": "\n## This file is the celeryconfig for the Task Worker (scanworker).\nfrom scanworker.commonconfig import *\nimport sys\nsys.path.append('.')\n\n\nBROKER_CONF = {\n 'uid' \t: '{{ mq_user }}',\n 'pass' \t: '{{ mq_password }}',\n 'host' \t: '{{ mq_host }}',\n 'port' \t: '5672',\n 'vhost' \t: '{{ mq_vhost }}',\n}\nBROKER_URL = 'amqp://'+BROKER_CONF['uid']+':'+BROKER_CONF['pass']+'@'+BROKER_CONF['host']+':'+BROKER_CONF['port']+'/'+BROKER_CONF['vhost']\n\nBROKER_HEARTBEAT=True\nCELERY_IMPORTS = ('scanworker.tasks',)\nfrom scanworker.tasks import VALID_SCANNERS as vs\nVALID_SCANNERS=vs()\nCELERY_QUEUES = VALID_SCANNERS.celery_virus_scan_queues()\nCELERY_ROUTES = VALID_SCANNERS.celery_virus_scan_routes()\n\n\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from django.contrib.auth.models import User
from django.core.management import call_command
from django.test import TestCase
from django.utils import timezone
from core import models
class ChildTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
def test_child_create(self):
child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
self.assertEqual(child, models.Child.objects.get(first_name='First'))
self.assertEqual(child.slug, 'first-last')
self.assertEqual(str(child), 'First Last')
self.assertEqual(child.name(), 'First Last')
self.assertEqual(child.name(reverse=True), 'Last, First')
def test_child_count(self):
self.assertEqual(models.Child.count(), 0)
models.Child.objects.create(
first_name='First 1',
last_name='Last 1',
birth_date=timezone.localdate()
)
self.assertEqual(models.Child.count(), 1)
child = models.Child.objects.create(
first_name='First 2',
last_name='Last 2',
birth_date=timezone.localdate()
)
self.assertEqual(models.Child.count(), 2)
child.delete()
self.assertEqual(models.Child.count(), 1)
class DiaperChangeTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
self.change = models.DiaperChange.objects.create(
child=self.child,
time=timezone.localtime() - timezone.timedelta(days=1),
wet=1,
solid=1,
color='black',
amount=1.25
)
def test_diaperchange_create(self):
self.assertEqual(self.change, models.DiaperChange.objects.first())
self.assertEqual(str(self.change), 'Diaper Change')
self.assertEqual(self.change.child, self.child)
self.assertTrue(self.change.wet)
self.assertTrue(self.change.solid)
self.assertEqual(self.change.color, 'black')
self.assertEqual(self.change.amount, 1.25)
def test_diaperchange_attributes(self):
self.assertListEqual(
self.change.attributes(), ['Wet', 'Solid', 'Black'])
class FeedingTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
def test_feeding_create(self):
feeding = models.Feeding.objects.create(
child=self.child,
start=timezone.localtime() - timezone.timedelta(minutes=30),
end=timezone.localtime(),
type='formula',
method='bottle',
amount=2
)
self.assertEqual(feeding, models.Feeding.objects.first())
self.assertEqual(str(feeding), 'Feeding')
self.assertEqual(feeding.duration, feeding.end - feeding.start)
def test_method_both_breasts(self):
feeding = models.Feeding.objects.create(
child=self.child,
start=timezone.localtime() - timezone.timedelta(minutes=30),
end=timezone.localtime(),
type='breast milk',
method='both breasts'
)
self.assertEqual(feeding, models.Feeding.objects.first())
self.assertEqual(str(feeding), 'Feeding')
self.assertEqual(feeding.method, 'both breasts')
class NoteTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
def test_note_create(self):
note = models.Note.objects.create(
child=self.child, note='Note', time=timezone.localtime())
self.assertEqual(note, models.Note.objects.first())
self.assertEqual(str(note), 'Note')
class SleepTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
def test_sleep_create(self):
sleep = models.Sleep.objects.create(
child=self.child,
start=timezone.localtime() - timezone.timedelta(minutes=30),
end=timezone.localtime(),
)
self.assertEqual(sleep, models.Sleep.objects.first())
self.assertEqual(str(sleep), 'Sleep')
self.assertEqual(sleep.duration, sleep.end - sleep.start)
class TemperatureTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
self.temp = models.Temperature.objects.create(
child=self.child,
time=timezone.localtime() - timezone.timedelta(days=1),
temperature=98.6
)
def test_temperature_create(self):
self.assertEqual(self.temp, models.Temperature.objects.first())
self.assertEqual(str(self.temp), 'Temperature')
self.assertEqual(self.temp.temperature, 98.6)
class TimerTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
self.user = User.objects.first()
self.named = models.Timer.objects.create(
name='Named',
end=timezone.localtime(),
user=self.user,
child=child
)
self.unnamed = models.Timer.objects.create(
end=timezone.localtime(),
user=self.user
)
def test_timer_create(self):
self.assertEqual(self.named, models.Timer.objects.get(name='Named'))
self.assertEqual(str(self.named), 'Named')
self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))
self.assertEqual(
str(self.unnamed), 'Timer #{}'.format(self.unnamed.id))
def test_timer_title_with_child(self):
self.assertEqual(self.named.title_with_child, str(self.named))
models.Child.objects.create(
first_name='Child',
last_name='Two',
birth_date=timezone.localdate()
)
self.assertEqual(
self.named.title_with_child,
'{} ({})'.format(str(self.named), str(self.named.child))
)
def test_timer_user_username(self):
self.assertEqual(self.named.user_username, self.user.get_username())
self.user.first_name = 'User'
self.user.last_name = 'Name'
self.user.save()
self.assertEqual(self.named.user_username, self.user.get_full_name())
def test_timer_restart(self):
self.named.restart()
self.assertIsNone(self.named.end)
self.assertIsNone(self.named.duration)
self.assertTrue(self.named.active)
def test_timer_stop(self):
stop_time = timezone.localtime()
self.unnamed.stop(end=stop_time)
self.assertEqual(self.unnamed.end, stop_time)
self.assertEqual(
self.unnamed.duration.seconds,
(self.unnamed.end - self.unnamed.start).seconds)
self.assertFalse(self.unnamed.active)
def test_timer_duration(self):
timer = models.Timer.objects.create(user=User.objects.first())
# Timer.start uses auto_now_add, so it cannot be set in create().
timer.start = timezone.localtime() - timezone.timedelta(minutes=30)
timer.save()
timer.refresh_from_db()
self.assertEqual(
timer.duration.seconds,
timezone.timedelta(minutes=30).seconds)
timer.stop()
self.assertEqual(
timer.duration.seconds,
timezone.timedelta(minutes=30).seconds)
class TummyTimeTestCase(TestCase):
def setUp(self):
call_command('migrate', verbosity=0)
self.child = models.Child.objects.create(
first_name='First',
last_name='Last',
birth_date=timezone.localdate()
)
def test_tummytime_create(self):
tummy_time = models.TummyTime.objects.create(
child=self.child,
start=timezone.localtime() - timezone.timedelta(minutes=30),
end=timezone.localtime(),
)
self.assertEqual(tummy_time, models.TummyTime.objects.first())
self.assertEqual(str(tummy_time), 'Tummy Time')
self.assertEqual(
tummy_time.duration, tummy_time.end - tummy_time.start)
|
normal
|
{
"blob_id": "135401ea495b80fc1d09d6919ccec8640cb328ce",
"index": 3901,
"step-1": "<mask token>\n\n\nclass TimerTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n child = models.Child.objects.create(first_name='First', last_name=\n 'Last', birth_date=timezone.localdate())\n self.user = User.objects.first()\n self.named = models.Timer.objects.create(name='Named', end=timezone\n .localtime(), user=self.user, child=child)\n self.unnamed = models.Timer.objects.create(end=timezone.localtime(),\n user=self.user)\n\n def test_timer_create(self):\n self.assertEqual(self.named, models.Timer.objects.get(name='Named'))\n self.assertEqual(str(self.named), 'Named')\n self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))\n self.assertEqual(str(self.unnamed), 'Timer #{}'.format(self.unnamed.id)\n )\n\n def test_timer_title_with_child(self):\n self.assertEqual(self.named.title_with_child, str(self.named))\n models.Child.objects.create(first_name='Child', last_name='Two',\n birth_date=timezone.localdate())\n self.assertEqual(self.named.title_with_child, '{} ({})'.format(str(\n self.named), str(self.named.child)))\n\n def test_timer_user_username(self):\n self.assertEqual(self.named.user_username, self.user.get_username())\n self.user.first_name = 'User'\n self.user.last_name = 'Name'\n self.user.save()\n self.assertEqual(self.named.user_username, self.user.get_full_name())\n\n def test_timer_restart(self):\n self.named.restart()\n self.assertIsNone(self.named.end)\n self.assertIsNone(self.named.duration)\n self.assertTrue(self.named.active)\n <mask token>\n\n def test_timer_duration(self):\n timer = models.Timer.objects.create(user=User.objects.first())\n timer.start = timezone.localtime() - timezone.timedelta(minutes=30)\n timer.save()\n timer.refresh_from_db()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n timer.stop()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n\n\nclass TummyTimeTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_tummytime_create(self):\n tummy_time = models.TummyTime.objects.create(child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime())\n self.assertEqual(tummy_time, models.TummyTime.objects.first())\n self.assertEqual(str(tummy_time), 'Tummy Time')\n self.assertEqual(tummy_time.duration, tummy_time.end - tummy_time.start\n )\n",
"step-2": "<mask token>\n\n\nclass SleepTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_sleep_create(self):\n sleep = models.Sleep.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime())\n self.assertEqual(sleep, models.Sleep.objects.first())\n self.assertEqual(str(sleep), 'Sleep')\n self.assertEqual(sleep.duration, sleep.end - sleep.start)\n\n\nclass TemperatureTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n self.temp = models.Temperature.objects.create(child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1),\n temperature=98.6)\n\n def test_temperature_create(self):\n self.assertEqual(self.temp, models.Temperature.objects.first())\n self.assertEqual(str(self.temp), 'Temperature')\n self.assertEqual(self.temp.temperature, 98.6)\n\n\nclass TimerTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n child = models.Child.objects.create(first_name='First', last_name=\n 'Last', birth_date=timezone.localdate())\n self.user = User.objects.first()\n self.named = models.Timer.objects.create(name='Named', end=timezone\n .localtime(), user=self.user, child=child)\n self.unnamed = models.Timer.objects.create(end=timezone.localtime(),\n user=self.user)\n\n def test_timer_create(self):\n self.assertEqual(self.named, models.Timer.objects.get(name='Named'))\n self.assertEqual(str(self.named), 'Named')\n self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))\n self.assertEqual(str(self.unnamed), 'Timer #{}'.format(self.unnamed.id)\n )\n\n def test_timer_title_with_child(self):\n self.assertEqual(self.named.title_with_child, str(self.named))\n models.Child.objects.create(first_name='Child', last_name='Two',\n birth_date=timezone.localdate())\n self.assertEqual(self.named.title_with_child, '{} ({})'.format(str(\n self.named), str(self.named.child)))\n\n def test_timer_user_username(self):\n self.assertEqual(self.named.user_username, self.user.get_username())\n self.user.first_name = 'User'\n self.user.last_name = 'Name'\n self.user.save()\n self.assertEqual(self.named.user_username, self.user.get_full_name())\n\n def test_timer_restart(self):\n self.named.restart()\n self.assertIsNone(self.named.end)\n self.assertIsNone(self.named.duration)\n self.assertTrue(self.named.active)\n\n def test_timer_stop(self):\n stop_time = timezone.localtime()\n self.unnamed.stop(end=stop_time)\n self.assertEqual(self.unnamed.end, stop_time)\n self.assertEqual(self.unnamed.duration.seconds, (self.unnamed.end -\n self.unnamed.start).seconds)\n self.assertFalse(self.unnamed.active)\n\n def test_timer_duration(self):\n timer = models.Timer.objects.create(user=User.objects.first())\n timer.start = timezone.localtime() - timezone.timedelta(minutes=30)\n timer.save()\n timer.refresh_from_db()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n timer.stop()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n\n\nclass TummyTimeTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_tummytime_create(self):\n tummy_time = models.TummyTime.objects.create(child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime())\n self.assertEqual(tummy_time, models.TummyTime.objects.first())\n self.assertEqual(str(tummy_time), 'Tummy Time')\n self.assertEqual(tummy_time.duration, tummy_time.end - tummy_time.start\n )\n",
"step-3": "<mask token>\n\n\nclass DiaperChangeTestCase(TestCase):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass FeedingTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_feeding_create(self):\n feeding = models.Feeding.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime(), type='formula', method='bottle', amount=2)\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.duration, feeding.end - feeding.start)\n\n def test_method_both_breasts(self):\n feeding = models.Feeding.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime(), type='breast milk', method='both breasts')\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.method, 'both breasts')\n\n\nclass NoteTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_note_create(self):\n note = models.Note.objects.create(child=self.child, note='Note',\n time=timezone.localtime())\n self.assertEqual(note, models.Note.objects.first())\n self.assertEqual(str(note), 'Note')\n\n\nclass SleepTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_sleep_create(self):\n sleep = models.Sleep.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime())\n self.assertEqual(sleep, models.Sleep.objects.first())\n self.assertEqual(str(sleep), 'Sleep')\n self.assertEqual(sleep.duration, sleep.end - sleep.start)\n\n\nclass TemperatureTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n self.temp = models.Temperature.objects.create(child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1),\n temperature=98.6)\n\n def test_temperature_create(self):\n self.assertEqual(self.temp, models.Temperature.objects.first())\n self.assertEqual(str(self.temp), 'Temperature')\n self.assertEqual(self.temp.temperature, 98.6)\n\n\nclass TimerTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n child = models.Child.objects.create(first_name='First', last_name=\n 'Last', birth_date=timezone.localdate())\n self.user = User.objects.first()\n self.named = models.Timer.objects.create(name='Named', end=timezone\n .localtime(), user=self.user, child=child)\n self.unnamed = models.Timer.objects.create(end=timezone.localtime(),\n user=self.user)\n\n def test_timer_create(self):\n self.assertEqual(self.named, models.Timer.objects.get(name='Named'))\n self.assertEqual(str(self.named), 'Named')\n self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))\n self.assertEqual(str(self.unnamed), 'Timer #{}'.format(self.unnamed.id)\n )\n\n def test_timer_title_with_child(self):\n self.assertEqual(self.named.title_with_child, str(self.named))\n models.Child.objects.create(first_name='Child', last_name='Two',\n birth_date=timezone.localdate())\n self.assertEqual(self.named.title_with_child, '{} ({})'.format(str(\n self.named), str(self.named.child)))\n\n def test_timer_user_username(self):\n self.assertEqual(self.named.user_username, self.user.get_username())\n self.user.first_name = 'User'\n self.user.last_name = 'Name'\n self.user.save()\n self.assertEqual(self.named.user_username, self.user.get_full_name())\n\n def test_timer_restart(self):\n self.named.restart()\n self.assertIsNone(self.named.end)\n self.assertIsNone(self.named.duration)\n self.assertTrue(self.named.active)\n\n def test_timer_stop(self):\n stop_time = timezone.localtime()\n self.unnamed.stop(end=stop_time)\n self.assertEqual(self.unnamed.end, stop_time)\n self.assertEqual(self.unnamed.duration.seconds, (self.unnamed.end -\n self.unnamed.start).seconds)\n self.assertFalse(self.unnamed.active)\n\n def test_timer_duration(self):\n timer = models.Timer.objects.create(user=User.objects.first())\n timer.start = timezone.localtime() - timezone.timedelta(minutes=30)\n timer.save()\n timer.refresh_from_db()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n timer.stop()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n\n\nclass TummyTimeTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_tummytime_create(self):\n tummy_time = models.TummyTime.objects.create(child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime())\n self.assertEqual(tummy_time, models.TummyTime.objects.first())\n self.assertEqual(str(tummy_time), 'Tummy Time')\n self.assertEqual(tummy_time.duration, tummy_time.end - tummy_time.start\n )\n",
"step-4": "<mask token>\n\n\nclass DiaperChangeTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n self.change = models.DiaperChange.objects.create(child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1), wet=1,\n solid=1, color='black', amount=1.25)\n <mask token>\n <mask token>\n\n\nclass FeedingTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_feeding_create(self):\n feeding = models.Feeding.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime(), type='formula', method='bottle', amount=2)\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.duration, feeding.end - feeding.start)\n\n def test_method_both_breasts(self):\n feeding = models.Feeding.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime(), type='breast milk', method='both breasts')\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.method, 'both breasts')\n\n\nclass NoteTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_note_create(self):\n note = models.Note.objects.create(child=self.child, note='Note',\n time=timezone.localtime())\n self.assertEqual(note, models.Note.objects.first())\n self.assertEqual(str(note), 'Note')\n\n\nclass SleepTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_sleep_create(self):\n sleep = models.Sleep.objects.create(child=self.child, start=\n timezone.localtime() - timezone.timedelta(minutes=30), end=\n timezone.localtime())\n self.assertEqual(sleep, models.Sleep.objects.first())\n self.assertEqual(str(sleep), 'Sleep')\n self.assertEqual(sleep.duration, sleep.end - sleep.start)\n\n\nclass TemperatureTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n self.temp = models.Temperature.objects.create(child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1),\n temperature=98.6)\n\n def test_temperature_create(self):\n self.assertEqual(self.temp, models.Temperature.objects.first())\n self.assertEqual(str(self.temp), 'Temperature')\n self.assertEqual(self.temp.temperature, 98.6)\n\n\nclass TimerTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n child = models.Child.objects.create(first_name='First', last_name=\n 'Last', birth_date=timezone.localdate())\n self.user = User.objects.first()\n self.named = models.Timer.objects.create(name='Named', end=timezone\n .localtime(), user=self.user, child=child)\n self.unnamed = models.Timer.objects.create(end=timezone.localtime(),\n user=self.user)\n\n def test_timer_create(self):\n self.assertEqual(self.named, models.Timer.objects.get(name='Named'))\n self.assertEqual(str(self.named), 'Named')\n self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))\n self.assertEqual(str(self.unnamed), 'Timer #{}'.format(self.unnamed.id)\n )\n\n def test_timer_title_with_child(self):\n self.assertEqual(self.named.title_with_child, str(self.named))\n models.Child.objects.create(first_name='Child', last_name='Two',\n birth_date=timezone.localdate())\n self.assertEqual(self.named.title_with_child, '{} ({})'.format(str(\n self.named), str(self.named.child)))\n\n def test_timer_user_username(self):\n self.assertEqual(self.named.user_username, self.user.get_username())\n self.user.first_name = 'User'\n self.user.last_name = 'Name'\n self.user.save()\n self.assertEqual(self.named.user_username, self.user.get_full_name())\n\n def test_timer_restart(self):\n self.named.restart()\n self.assertIsNone(self.named.end)\n self.assertIsNone(self.named.duration)\n self.assertTrue(self.named.active)\n\n def test_timer_stop(self):\n stop_time = timezone.localtime()\n self.unnamed.stop(end=stop_time)\n self.assertEqual(self.unnamed.end, stop_time)\n self.assertEqual(self.unnamed.duration.seconds, (self.unnamed.end -\n self.unnamed.start).seconds)\n self.assertFalse(self.unnamed.active)\n\n def test_timer_duration(self):\n timer = models.Timer.objects.create(user=User.objects.first())\n timer.start = timezone.localtime() - timezone.timedelta(minutes=30)\n timer.save()\n timer.refresh_from_db()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n timer.stop()\n self.assertEqual(timer.duration.seconds, timezone.timedelta(minutes\n =30).seconds)\n\n\nclass TummyTimeTestCase(TestCase):\n\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(first_name='First',\n last_name='Last', birth_date=timezone.localdate())\n\n def test_tummytime_create(self):\n tummy_time = models.TummyTime.objects.create(child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime())\n self.assertEqual(tummy_time, models.TummyTime.objects.first())\n self.assertEqual(str(tummy_time), 'Tummy Time')\n self.assertEqual(tummy_time.duration, tummy_time.end - tummy_time.start\n )\n",
"step-5": "# -*- coding: utf-8 -*-\nfrom django.contrib.auth.models import User\nfrom django.core.management import call_command\nfrom django.test import TestCase\nfrom django.utils import timezone\n\nfrom core import models\n\n\nclass ChildTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n\n def test_child_create(self):\n child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n self.assertEqual(child, models.Child.objects.get(first_name='First'))\n self.assertEqual(child.slug, 'first-last')\n self.assertEqual(str(child), 'First Last')\n self.assertEqual(child.name(), 'First Last')\n self.assertEqual(child.name(reverse=True), 'Last, First')\n\n def test_child_count(self):\n self.assertEqual(models.Child.count(), 0)\n models.Child.objects.create(\n first_name='First 1',\n last_name='Last 1',\n birth_date=timezone.localdate()\n )\n self.assertEqual(models.Child.count(), 1)\n child = models.Child.objects.create(\n first_name='First 2',\n last_name='Last 2',\n birth_date=timezone.localdate()\n )\n self.assertEqual(models.Child.count(), 2)\n child.delete()\n self.assertEqual(models.Child.count(), 1)\n\n\nclass DiaperChangeTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n self.change = models.DiaperChange.objects.create(\n child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1),\n wet=1,\n solid=1,\n color='black',\n amount=1.25\n )\n\n def test_diaperchange_create(self):\n self.assertEqual(self.change, models.DiaperChange.objects.first())\n self.assertEqual(str(self.change), 'Diaper Change')\n self.assertEqual(self.change.child, self.child)\n self.assertTrue(self.change.wet)\n self.assertTrue(self.change.solid)\n self.assertEqual(self.change.color, 'black')\n self.assertEqual(self.change.amount, 1.25)\n\n def test_diaperchange_attributes(self):\n self.assertListEqual(\n self.change.attributes(), ['Wet', 'Solid', 'Black'])\n\n\nclass FeedingTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n\n def test_feeding_create(self):\n feeding = models.Feeding.objects.create(\n child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime(),\n type='formula',\n method='bottle',\n amount=2\n )\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.duration, feeding.end - feeding.start)\n\n def test_method_both_breasts(self):\n feeding = models.Feeding.objects.create(\n child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime(),\n type='breast milk',\n method='both breasts'\n )\n self.assertEqual(feeding, models.Feeding.objects.first())\n self.assertEqual(str(feeding), 'Feeding')\n self.assertEqual(feeding.method, 'both breasts')\n\n\nclass NoteTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n\n def test_note_create(self):\n note = models.Note.objects.create(\n child=self.child, note='Note', time=timezone.localtime())\n self.assertEqual(note, models.Note.objects.first())\n self.assertEqual(str(note), 'Note')\n\n\nclass SleepTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n\n def test_sleep_create(self):\n sleep = models.Sleep.objects.create(\n child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime(),\n )\n self.assertEqual(sleep, models.Sleep.objects.first())\n self.assertEqual(str(sleep), 'Sleep')\n self.assertEqual(sleep.duration, sleep.end - sleep.start)\n\n\nclass TemperatureTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n self.temp = models.Temperature.objects.create(\n child=self.child,\n time=timezone.localtime() - timezone.timedelta(days=1),\n temperature=98.6\n )\n\n def test_temperature_create(self):\n self.assertEqual(self.temp, models.Temperature.objects.first())\n self.assertEqual(str(self.temp), 'Temperature')\n self.assertEqual(self.temp.temperature, 98.6)\n\n\nclass TimerTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n self.user = User.objects.first()\n self.named = models.Timer.objects.create(\n name='Named',\n end=timezone.localtime(),\n user=self.user,\n child=child\n )\n self.unnamed = models.Timer.objects.create(\n end=timezone.localtime(),\n user=self.user\n )\n\n def test_timer_create(self):\n self.assertEqual(self.named, models.Timer.objects.get(name='Named'))\n self.assertEqual(str(self.named), 'Named')\n self.assertEqual(self.unnamed, models.Timer.objects.get(name=None))\n self.assertEqual(\n str(self.unnamed), 'Timer #{}'.format(self.unnamed.id))\n\n def test_timer_title_with_child(self):\n self.assertEqual(self.named.title_with_child, str(self.named))\n\n models.Child.objects.create(\n first_name='Child',\n last_name='Two',\n birth_date=timezone.localdate()\n )\n self.assertEqual(\n self.named.title_with_child,\n '{} ({})'.format(str(self.named), str(self.named.child))\n )\n\n def test_timer_user_username(self):\n self.assertEqual(self.named.user_username, self.user.get_username())\n self.user.first_name = 'User'\n self.user.last_name = 'Name'\n self.user.save()\n self.assertEqual(self.named.user_username, self.user.get_full_name())\n\n def test_timer_restart(self):\n self.named.restart()\n self.assertIsNone(self.named.end)\n self.assertIsNone(self.named.duration)\n self.assertTrue(self.named.active)\n\n def test_timer_stop(self):\n stop_time = timezone.localtime()\n self.unnamed.stop(end=stop_time)\n self.assertEqual(self.unnamed.end, stop_time)\n self.assertEqual(\n self.unnamed.duration.seconds,\n (self.unnamed.end - self.unnamed.start).seconds)\n self.assertFalse(self.unnamed.active)\n\n def test_timer_duration(self):\n timer = models.Timer.objects.create(user=User.objects.first())\n # Timer.start uses auto_now_add, so it cannot be set in create().\n timer.start = timezone.localtime() - timezone.timedelta(minutes=30)\n timer.save()\n timer.refresh_from_db()\n\n self.assertEqual(\n timer.duration.seconds,\n timezone.timedelta(minutes=30).seconds)\n timer.stop()\n self.assertEqual(\n timer.duration.seconds,\n timezone.timedelta(minutes=30).seconds)\n\n\nclass TummyTimeTestCase(TestCase):\n def setUp(self):\n call_command('migrate', verbosity=0)\n self.child = models.Child.objects.create(\n first_name='First',\n last_name='Last',\n birth_date=timezone.localdate()\n )\n\n def test_tummytime_create(self):\n tummy_time = models.TummyTime.objects.create(\n child=self.child,\n start=timezone.localtime() - timezone.timedelta(minutes=30),\n end=timezone.localtime(),\n )\n self.assertEqual(tummy_time, models.TummyTime.objects.first())\n self.assertEqual(str(tummy_time), 'Tummy Time')\n self.assertEqual(\n tummy_time.duration, tummy_time.end - tummy_time.start)\n",
"step-ids": [
10,
17,
25,
26,
34
]
}
|
[
10,
17,
25,
26,
34
] |
import webbrowser
import time
x=10
while x > 0:
print (x), time.sleep(1)
x=x-1
while x==0:
print ("MEOW")
webbrowser.open("https://www.youtube.com/watch?v=IuysY1BekOE")
|
normal
|
{
"blob_id": "4d31357936ce53b2be5f9a952b99df58baffe7ea",
"index": 4937,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile x > 0:\n print(x), time.sleep(1)\n x = x - 1\nwhile x == 0:\n print('MEOW')\n webbrowser.open('https://www.youtube.com/watch?v=IuysY1BekOE')\n",
"step-3": "<mask token>\nx = 10\nwhile x > 0:\n print(x), time.sleep(1)\n x = x - 1\nwhile x == 0:\n print('MEOW')\n webbrowser.open('https://www.youtube.com/watch?v=IuysY1BekOE')\n",
"step-4": "import webbrowser\nimport time\nx = 10\nwhile x > 0:\n print(x), time.sleep(1)\n x = x - 1\nwhile x == 0:\n print('MEOW')\n webbrowser.open('https://www.youtube.com/watch?v=IuysY1BekOE')\n",
"step-5": "import webbrowser\nimport time\nx=10\nwhile x > 0:\n print (x), time.sleep(1)\n x=x-1\nwhile x==0:\n print (\"MEOW\")\n webbrowser.open(\"https://www.youtube.com/watch?v=IuysY1BekOE\")\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import re
def match_regex(filename, regex):
with open(filename) as file:
lines = file.readlines()
for line in reversed(lines):
match = re.match(regex, line)
if match:
regex = yield match.groups()[0]
def get_serials(filename):
ERROR_RE = 'XFS ERROR (\[sd[a-z]\])'
# Create generator of XFS ERROR
matcher = match_regex(filename, ERROR_RE)
device = next(matcher)
while True:
# Create regex pattern for BUS INFO base on DEVICE got ERROR
bus_regex = '(sd \S+) {}.*'.format(re.escape(device))
print('bus_regex:', bus_regex)
# Send BUS regex to generator to get BUS info of ERROR
bus = matcher.send(bus_regex)
# Send SERIAL regex to generator to get SERIAL NO of DEVICE in ERROR
serial_regex = '{} \(SERIAL=([^)]*)\)'.format(bus)
print('serial_regex:', serial_regex)
serial = matcher.send(serial_regex)
yield serial
# Send ERROR regex to generator to get next DEVICE in ERROR
device = matcher.send(ERROR_RE)
def main():
filename = 'iter2/log2.txt'
print('List of serial no found: ')
for serial in get_serials(filename=filename):
print(serial)
if __name__ == '__main__':
main()
|
normal
|
{
"blob_id": "a36a553342cfe605a97ddc0f636bbb73b683f6a6",
"index": 1239,
"step-1": "<mask token>\n\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex = yield match.groups()[0]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex = yield match.groups()[0]\n\n\ndef get_serials(filename):\n ERROR_RE = 'XFS ERROR (\\\\[sd[a-z]\\\\])'\n matcher = match_regex(filename, ERROR_RE)\n device = next(matcher)\n while True:\n bus_regex = '(sd \\\\S+) {}.*'.format(re.escape(device))\n print('bus_regex:', bus_regex)\n bus = matcher.send(bus_regex)\n serial_regex = '{} \\\\(SERIAL=([^)]*)\\\\)'.format(bus)\n print('serial_regex:', serial_regex)\n serial = matcher.send(serial_regex)\n yield serial\n device = matcher.send(ERROR_RE)\n\n\ndef main():\n filename = 'iter2/log2.txt'\n print('List of serial no found: ')\n for serial in get_serials(filename=filename):\n print(serial)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex = yield match.groups()[0]\n\n\ndef get_serials(filename):\n ERROR_RE = 'XFS ERROR (\\\\[sd[a-z]\\\\])'\n matcher = match_regex(filename, ERROR_RE)\n device = next(matcher)\n while True:\n bus_regex = '(sd \\\\S+) {}.*'.format(re.escape(device))\n print('bus_regex:', bus_regex)\n bus = matcher.send(bus_regex)\n serial_regex = '{} \\\\(SERIAL=([^)]*)\\\\)'.format(bus)\n print('serial_regex:', serial_regex)\n serial = matcher.send(serial_regex)\n yield serial\n device = matcher.send(ERROR_RE)\n\n\ndef main():\n filename = 'iter2/log2.txt'\n print('List of serial no found: ')\n for serial in get_serials(filename=filename):\n print(serial)\n\n\nif __name__ == '__main__':\n main()\n",
"step-4": "import re\n\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex = yield match.groups()[0]\n\n\ndef get_serials(filename):\n ERROR_RE = 'XFS ERROR (\\\\[sd[a-z]\\\\])'\n matcher = match_regex(filename, ERROR_RE)\n device = next(matcher)\n while True:\n bus_regex = '(sd \\\\S+) {}.*'.format(re.escape(device))\n print('bus_regex:', bus_regex)\n bus = matcher.send(bus_regex)\n serial_regex = '{} \\\\(SERIAL=([^)]*)\\\\)'.format(bus)\n print('serial_regex:', serial_regex)\n serial = matcher.send(serial_regex)\n yield serial\n device = matcher.send(ERROR_RE)\n\n\ndef main():\n filename = 'iter2/log2.txt'\n print('List of serial no found: ')\n for serial in get_serials(filename=filename):\n print(serial)\n\n\nif __name__ == '__main__':\n main()\n",
"step-5": "import re\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex = yield match.groups()[0]\n\ndef get_serials(filename):\n ERROR_RE = 'XFS ERROR (\\[sd[a-z]\\])'\n\n # Create generator of XFS ERROR\n matcher = match_regex(filename, ERROR_RE)\n device = next(matcher)\n\n while True:\n # Create regex pattern for BUS INFO base on DEVICE got ERROR\n bus_regex = '(sd \\S+) {}.*'.format(re.escape(device))\n print('bus_regex:', bus_regex)\n\n\n # Send BUS regex to generator to get BUS info of ERROR\n bus = matcher.send(bus_regex)\n\n # Send SERIAL regex to generator to get SERIAL NO of DEVICE in ERROR\n serial_regex = '{} \\(SERIAL=([^)]*)\\)'.format(bus)\n print('serial_regex:', serial_regex)\n serial = matcher.send(serial_regex)\n yield serial\n\n # Send ERROR regex to generator to get next DEVICE in ERROR\n device = matcher.send(ERROR_RE)\n\ndef main():\n filename = 'iter2/log2.txt'\n print('List of serial no found: ')\n for serial in get_serials(filename=filename):\n print(serial)\n\nif __name__ == '__main__':\n main()",
"step-ids": [
1,
3,
4,
5,
6
]
}
|
[
1,
3,
4,
5,
6
] |
# ""
# "deb_char_cont_x9875"
# # def watch_edit_text(self): # execute when test edited
# # logging.info("TQ : " + str(len(self.te_sql_cmd.toPlainText())))
# # logging.info("TE : " + str(len(self.cmd_last_text)))
# # logging.info("LEN : " + str(self.cmd_len))
# # if len(self.te_sql_cmd.toPlainText()) < self.cmd_len or \
# # self.te_sql_cmd.toPlainText().find(self.cmd_last_text) != 0:
# # # self.te_sql_cmd.setText(self.cmd_last_text) # not writch text
# #
# # # self.te_sql_cmd.setText(self.cmd_last_text) # Work but no text highLight
# # # after press backspace
# # # self.te_sql_cmd.setDocument(self.cmd_last_text_document)
# #
# # self.te_sql_cmd.setHtml(self.cmd_last_html_text)
# #
# # logging.info("TQ : " + str(len(self.te_sql_cmd.toPlainText())))
# # logging.info("TE : " + str(len(self.cmd_last_text)))
# #
# # tempCurs = self.te_sql_cmd.textCursor()
# # # tempCurs=QTextCursor()
# # # tempCurs.movePosition(QTextCursor.Right,QTextCursor.MoveAnchor,len(self.te_sql_cmd.toPlainText()))
# #
# # tempCurs.movePosition(QTextCursor.End, QTextCursor.MoveAnchor, 0)
# # self.te_sql_cmd.setTextCursor(tempCurs)
#
#
# #
# # import subprocess
# # proc = subprocess.Popen('cmd.exe', stdin = subprocess.PIPE, stdout = subprocess.PIPE)
# #
#
# app=QApplication(sys.argv)
# window=AbtTerminal()
#
# def my_commands_ana(command):
# if command == "cd":
# # return str(os.path.dirname(os.path.realpath(__file__))) # current file Directory
# return os.getcwd()
# if "cd" in command[:2] and len(command) > 2:
# dir_name = command[3:]
# try:
# os.chdir(dir_name)
# return '<h4>dir changed to</h4> <h4 style="color:rgb(0,230,120);">%s</h4>' % os.getcwd()
# except:
# return '<h4 style="color:red">Cant change current Directory To \n\t%s</h4>' % dir_name
# if "$$" in command[:2]:
# stdout, stderr = proc.communicate(bytes(str(command[2:]), 'UTF-8'))
# deleted_length_before=len("b'Microsoft Windows [Version 10.0.10586]\r\n(c) 2015 Microsoft Corporation. All rights reserved.\r\n\r\n")
# deleted_length_after=len(">More? '")
# # real_result=str(stdout)[deleted_length_before+4:len(str(stdout))-deleted_length_after]
# real_result=str(stdout.decode("utf-8")).replace("Microsoft Windows [Version 10.0.10586]\r\n(c) 2015 Microsoft Corporation. All rights reserved.\r\n\r\n","")
# real_result=real_result.replace(">More?","")
# print(real_result)
# return real_result
#
#
#
#
#
# ###############
# import subprocess
# cmdline = ["cmd", "/q", "/k", "echo off"]
# cmd = subprocess.Popen(cmdline, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
#
#
# if "$$" in command[:2]:
# batch = b"""\
# cd
# """
#
# # cmd.stdin.write(bytes(str(command[2:]), 'UTF-8'))
#
# cmd.stdin.write(batch)
# cmd.stdin.flush() # Must include this to ensure data is passed to child process
# result = cmd.stdout.read()
# return " "
|
normal
|
{
"blob_id": "f70f4f093aa64b8cd60acbb846855ca3fed13c63",
"index": 4837,
"step-1": "# \"\"\n# \"deb_char_cont_x9875\"\n# # def watch_edit_text(self): # execute when test edited\n# # logging.info(\"TQ : \" + str(len(self.te_sql_cmd.toPlainText())))\n# # logging.info(\"TE : \" + str(len(self.cmd_last_text)))\n# # logging.info(\"LEN : \" + str(self.cmd_len))\n# # if len(self.te_sql_cmd.toPlainText()) < self.cmd_len or \\\n# # self.te_sql_cmd.toPlainText().find(self.cmd_last_text) != 0:\n# # # self.te_sql_cmd.setText(self.cmd_last_text) # not writch text\n# #\n# # # self.te_sql_cmd.setText(self.cmd_last_text) # Work but no text highLight\n# # # after press backspace\n# # # self.te_sql_cmd.setDocument(self.cmd_last_text_document)\n# #\n# # self.te_sql_cmd.setHtml(self.cmd_last_html_text)\n# #\n# # logging.info(\"TQ : \" + str(len(self.te_sql_cmd.toPlainText())))\n# # logging.info(\"TE : \" + str(len(self.cmd_last_text)))\n# #\n# # tempCurs = self.te_sql_cmd.textCursor()\n# # # tempCurs=QTextCursor()\n# # # tempCurs.movePosition(QTextCursor.Right,QTextCursor.MoveAnchor,len(self.te_sql_cmd.toPlainText()))\n# #\n# # tempCurs.movePosition(QTextCursor.End, QTextCursor.MoveAnchor, 0)\n# # self.te_sql_cmd.setTextCursor(tempCurs)\n#\n#\n# #\n# # import subprocess\n# # proc = subprocess.Popen('cmd.exe', stdin = subprocess.PIPE, stdout = subprocess.PIPE)\n# #\n#\n# app=QApplication(sys.argv)\n# window=AbtTerminal()\n#\n# def my_commands_ana(command):\n# if command == \"cd\":\n# # return str(os.path.dirname(os.path.realpath(__file__))) # current file Directory\n# return os.getcwd()\n# if \"cd\" in command[:2] and len(command) > 2:\n# dir_name = command[3:]\n# try:\n# os.chdir(dir_name)\n# return '<h4>dir changed to</h4> <h4 style=\"color:rgb(0,230,120);\">%s</h4>' % os.getcwd()\n# except:\n# return '<h4 style=\"color:red\">Cant change current Directory To \\n\\t%s</h4>' % dir_name\n# if \"$$\" in command[:2]:\n# stdout, stderr = proc.communicate(bytes(str(command[2:]), 'UTF-8'))\n# deleted_length_before=len(\"b'Microsoft Windows [Version 10.0.10586]\\r\\n(c) 2015 Microsoft Corporation. All rights reserved.\\r\\n\\r\\n\")\n# deleted_length_after=len(\">More? '\")\n# # real_result=str(stdout)[deleted_length_before+4:len(str(stdout))-deleted_length_after]\n# real_result=str(stdout.decode(\"utf-8\")).replace(\"Microsoft Windows [Version 10.0.10586]\\r\\n(c) 2015 Microsoft Corporation. All rights reserved.\\r\\n\\r\\n\",\"\")\n# real_result=real_result.replace(\">More?\",\"\")\n# print(real_result)\n# return real_result\n#\n#\n#\n#\n#\n# ###############\n# import subprocess\n# cmdline = [\"cmd\", \"/q\", \"/k\", \"echo off\"]\n# cmd = subprocess.Popen(cmdline, stdin=subprocess.PIPE, stdout=subprocess.PIPE)\n#\n#\n# if \"$$\" in command[:2]:\n# batch = b\"\"\"\\\n# cd\n# \"\"\"\n#\n# # cmd.stdin.write(bytes(str(command[2:]), 'UTF-8'))\n#\n# cmd.stdin.write(batch)\n# cmd.stdin.flush() # Must include this to ensure data is passed to child process\n# result = cmd.stdout.read()\n# return \" \"\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
1
]
}
|
[
1
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from urllib import request,parse
# req = request.Request('https://api.douban.com/v2/book/2129650')
# req.add_header('User-Agent', 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36')
# with request.urlopen(req) as f:
# data = f.read()
# print('Status:', f.status, f.reason)
# for k, v in f.getheaders():
# print('%s:%s' % (k, v))
# print('Data:', data.decode('utf-8'))
print('Login to weibo.com')
email = input('Email:')
passwd = input('Password:')
login_data = parse.urlencode([
('username', email),
('password', passwd),
('entry', 'mwei'),
('client_id', ''),
('savestate', 1),
('ec', ''),
('pagerefer', 'https://passport.weibo.cn/signin/welcome?entry=mweibo&r=http%3A%2F%2Fm.weibo.cn%2F')
])
req = request.Request('https://chenshuaijun.com')
req.add_header('Host', 'chenshuaijun.com')
req.add_header('User-Agent', 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36')
with request.urlopen(req, data=login_data.encode('utf-8')) as f:
print('Status:', f.status, f.reason)
for k, v in f.getheaders():
print('%s: %s' % (k, v))
print('Data:', f.read().decode('utf-8'))
|
normal
|
{
"blob_id": "9bd63181de024c2f4517defa9ed51bdbc8d610d2",
"index": 6025,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Login to weibo.com')\n<mask token>\nreq.add_header('Host', 'chenshuaijun.com')\nreq.add_header('User-Agent',\n 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36'\n )\nwith request.urlopen(req, data=login_data.encode('utf-8')) as f:\n print('Status:', f.status, f.reason)\n for k, v in f.getheaders():\n print('%s: %s' % (k, v))\n print('Data:', f.read().decode('utf-8'))\n",
"step-3": "<mask token>\nprint('Login to weibo.com')\nemail = input('Email:')\npasswd = input('Password:')\nlogin_data = parse.urlencode([('username', email), ('password', passwd), (\n 'entry', 'mwei'), ('client_id', ''), ('savestate', 1), ('ec', ''), (\n 'pagerefer',\n 'https://passport.weibo.cn/signin/welcome?entry=mweibo&r=http%3A%2F%2Fm.weibo.cn%2F'\n )])\nreq = request.Request('https://chenshuaijun.com')\nreq.add_header('Host', 'chenshuaijun.com')\nreq.add_header('User-Agent',\n 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36'\n )\nwith request.urlopen(req, data=login_data.encode('utf-8')) as f:\n print('Status:', f.status, f.reason)\n for k, v in f.getheaders():\n print('%s: %s' % (k, v))\n print('Data:', f.read().decode('utf-8'))\n",
"step-4": "from urllib import request, parse\nprint('Login to weibo.com')\nemail = input('Email:')\npasswd = input('Password:')\nlogin_data = parse.urlencode([('username', email), ('password', passwd), (\n 'entry', 'mwei'), ('client_id', ''), ('savestate', 1), ('ec', ''), (\n 'pagerefer',\n 'https://passport.weibo.cn/signin/welcome?entry=mweibo&r=http%3A%2F%2Fm.weibo.cn%2F'\n )])\nreq = request.Request('https://chenshuaijun.com')\nreq.add_header('Host', 'chenshuaijun.com')\nreq.add_header('User-Agent',\n 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36'\n )\nwith request.urlopen(req, data=login_data.encode('utf-8')) as f:\n print('Status:', f.status, f.reason)\n for k, v in f.getheaders():\n print('%s: %s' % (k, v))\n print('Data:', f.read().decode('utf-8'))\n",
"step-5": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\nfrom urllib import request,parse\n\n# req = request.Request('https://api.douban.com/v2/book/2129650')\n# req.add_header('User-Agent', 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36')\n# with request.urlopen(req) as f:\n# data = f.read()\n# print('Status:', f.status, f.reason)\n# for k, v in f.getheaders():\n# print('%s:%s' % (k, v))\n# print('Data:', data.decode('utf-8'))\n\nprint('Login to weibo.com')\nemail = input('Email:')\npasswd = input('Password:')\nlogin_data = parse.urlencode([\n ('username', email),\n ('password', passwd),\n ('entry', 'mwei'),\n ('client_id', ''),\n ('savestate', 1),\n ('ec', ''),\n ('pagerefer', 'https://passport.weibo.cn/signin/welcome?entry=mweibo&r=http%3A%2F%2Fm.weibo.cn%2F')\n])\n\nreq = request.Request('https://chenshuaijun.com')\nreq.add_header('Host', 'chenshuaijun.com')\nreq.add_header('User-Agent', 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.62 Safari/537.36')\n\nwith request.urlopen(req, data=login_data.encode('utf-8')) as f:\n print('Status:', f.status, f.reason)\n for k, v in f.getheaders():\n print('%s: %s' % (k, v))\n print('Data:', f.read().decode('utf-8'))\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import requests
from multiprocessing import Process
from atomic_counter import AtomicCounter
class Downloader:
def __init__(self, src_url, num_threads):
try:
header = requests.head(src_url).headers
self.url = src_url
self.file_size = int(header.get('content-length'))
self.file_name = src_url.split('/')[-1]
self.num_threads = num_threads
self.chunk_size = self.file_size // self.num_threads
with open(self.file_name, 'wb') as f:
f.write(b'\x00' * self.file_size)
except requests.exceptions.ConnectionError:
print('Connection error, please check your internet connection.')
def _worker(self, download_range: tuple, counter: AtomicCounter):
start, end = download_range
header = {'Range': 'bytes=' + str(start) + '-' + str(end)}
r = requests.get(self.url, headers=header, stream=True, timeout=30)
binary_content = r.content
counter.increment_by_value(end - start + 1)
print(counter.get_value() / self.file_size)
with open(self.file_name, 'wb') as f:
f.seek(start)
f.write(binary_content)
def download(self) -> None:
download_ranges = []
for i in range(self.num_threads):
start = i * self.chunk_size
if i == self.num_threads - 1:
end = self.file_size
else:
end = start + self.chunk_size - 1
download_ranges.append((start, end))
atomic_counter = AtomicCounter()
process_pool = [Process(target=self._worker,
args=(download_ranges[i], atomic_counter))
for i in range(self.num_threads)]
for p in process_pool:
p.start()
for p in process_pool:
p.join()
if __name__ == "__main__":
downloader = Downloader(
'https://download-cf.jetbrains.com/idea/ideaIC-2019.3.3.tar.gz', 4)
downloader.download()
|
normal
|
{
"blob_id": "3dc3bbd00f9c2d00093bf8669963d96f5019b2da",
"index": 4648,
"step-1": "<mask token>\n\n\nclass Downloader:\n <mask token>\n\n def _worker(self, download_range: tuple, counter: AtomicCounter):\n start, end = download_range\n header = {'Range': 'bytes=' + str(start) + '-' + str(end)}\n r = requests.get(self.url, headers=header, stream=True, timeout=30)\n binary_content = r.content\n counter.increment_by_value(end - start + 1)\n print(counter.get_value() / self.file_size)\n with open(self.file_name, 'wb') as f:\n f.seek(start)\n f.write(binary_content)\n\n def download(self) ->None:\n download_ranges = []\n for i in range(self.num_threads):\n start = i * self.chunk_size\n if i == self.num_threads - 1:\n end = self.file_size\n else:\n end = start + self.chunk_size - 1\n download_ranges.append((start, end))\n atomic_counter = AtomicCounter()\n process_pool = [Process(target=self._worker, args=(download_ranges[\n i], atomic_counter)) for i in range(self.num_threads)]\n for p in process_pool:\n p.start()\n for p in process_pool:\n p.join()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Downloader:\n\n def __init__(self, src_url, num_threads):\n try:\n header = requests.head(src_url).headers\n self.url = src_url\n self.file_size = int(header.get('content-length'))\n self.file_name = src_url.split('/')[-1]\n self.num_threads = num_threads\n self.chunk_size = self.file_size // self.num_threads\n with open(self.file_name, 'wb') as f:\n f.write(b'\\x00' * self.file_size)\n except requests.exceptions.ConnectionError:\n print('Connection error, please check your internet connection.')\n\n def _worker(self, download_range: tuple, counter: AtomicCounter):\n start, end = download_range\n header = {'Range': 'bytes=' + str(start) + '-' + str(end)}\n r = requests.get(self.url, headers=header, stream=True, timeout=30)\n binary_content = r.content\n counter.increment_by_value(end - start + 1)\n print(counter.get_value() / self.file_size)\n with open(self.file_name, 'wb') as f:\n f.seek(start)\n f.write(binary_content)\n\n def download(self) ->None:\n download_ranges = []\n for i in range(self.num_threads):\n start = i * self.chunk_size\n if i == self.num_threads - 1:\n end = self.file_size\n else:\n end = start + self.chunk_size - 1\n download_ranges.append((start, end))\n atomic_counter = AtomicCounter()\n process_pool = [Process(target=self._worker, args=(download_ranges[\n i], atomic_counter)) for i in range(self.num_threads)]\n for p in process_pool:\n p.start()\n for p in process_pool:\n p.join()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Downloader:\n\n def __init__(self, src_url, num_threads):\n try:\n header = requests.head(src_url).headers\n self.url = src_url\n self.file_size = int(header.get('content-length'))\n self.file_name = src_url.split('/')[-1]\n self.num_threads = num_threads\n self.chunk_size = self.file_size // self.num_threads\n with open(self.file_name, 'wb') as f:\n f.write(b'\\x00' * self.file_size)\n except requests.exceptions.ConnectionError:\n print('Connection error, please check your internet connection.')\n\n def _worker(self, download_range: tuple, counter: AtomicCounter):\n start, end = download_range\n header = {'Range': 'bytes=' + str(start) + '-' + str(end)}\n r = requests.get(self.url, headers=header, stream=True, timeout=30)\n binary_content = r.content\n counter.increment_by_value(end - start + 1)\n print(counter.get_value() / self.file_size)\n with open(self.file_name, 'wb') as f:\n f.seek(start)\n f.write(binary_content)\n\n def download(self) ->None:\n download_ranges = []\n for i in range(self.num_threads):\n start = i * self.chunk_size\n if i == self.num_threads - 1:\n end = self.file_size\n else:\n end = start + self.chunk_size - 1\n download_ranges.append((start, end))\n atomic_counter = AtomicCounter()\n process_pool = [Process(target=self._worker, args=(download_ranges[\n i], atomic_counter)) for i in range(self.num_threads)]\n for p in process_pool:\n p.start()\n for p in process_pool:\n p.join()\n\n\nif __name__ == '__main__':\n downloader = Downloader(\n 'https://download-cf.jetbrains.com/idea/ideaIC-2019.3.3.tar.gz', 4)\n downloader.download()\n",
"step-4": "import requests\nfrom multiprocessing import Process\nfrom atomic_counter import AtomicCounter\n\n\nclass Downloader:\n\n def __init__(self, src_url, num_threads):\n try:\n header = requests.head(src_url).headers\n self.url = src_url\n self.file_size = int(header.get('content-length'))\n self.file_name = src_url.split('/')[-1]\n self.num_threads = num_threads\n self.chunk_size = self.file_size // self.num_threads\n with open(self.file_name, 'wb') as f:\n f.write(b'\\x00' * self.file_size)\n except requests.exceptions.ConnectionError:\n print('Connection error, please check your internet connection.')\n\n def _worker(self, download_range: tuple, counter: AtomicCounter):\n start, end = download_range\n header = {'Range': 'bytes=' + str(start) + '-' + str(end)}\n r = requests.get(self.url, headers=header, stream=True, timeout=30)\n binary_content = r.content\n counter.increment_by_value(end - start + 1)\n print(counter.get_value() / self.file_size)\n with open(self.file_name, 'wb') as f:\n f.seek(start)\n f.write(binary_content)\n\n def download(self) ->None:\n download_ranges = []\n for i in range(self.num_threads):\n start = i * self.chunk_size\n if i == self.num_threads - 1:\n end = self.file_size\n else:\n end = start + self.chunk_size - 1\n download_ranges.append((start, end))\n atomic_counter = AtomicCounter()\n process_pool = [Process(target=self._worker, args=(download_ranges[\n i], atomic_counter)) for i in range(self.num_threads)]\n for p in process_pool:\n p.start()\n for p in process_pool:\n p.join()\n\n\nif __name__ == '__main__':\n downloader = Downloader(\n 'https://download-cf.jetbrains.com/idea/ideaIC-2019.3.3.tar.gz', 4)\n downloader.download()\n",
"step-5": "import requests\nfrom multiprocessing import Process\nfrom atomic_counter import AtomicCounter\n\n\nclass Downloader:\n def __init__(self, src_url, num_threads):\n try:\n header = requests.head(src_url).headers\n self.url = src_url\n self.file_size = int(header.get('content-length'))\n self.file_name = src_url.split('/')[-1]\n self.num_threads = num_threads\n self.chunk_size = self.file_size // self.num_threads\n\n with open(self.file_name, 'wb') as f:\n f.write(b'\\x00' * self.file_size)\n\n except requests.exceptions.ConnectionError:\n print('Connection error, please check your internet connection.')\n\n def _worker(self, download_range: tuple, counter: AtomicCounter):\n start, end = download_range\n header = {'Range': 'bytes=' + str(start) + '-' + str(end)}\n\n r = requests.get(self.url, headers=header, stream=True, timeout=30)\n binary_content = r.content\n counter.increment_by_value(end - start + 1)\n print(counter.get_value() / self.file_size)\n\n with open(self.file_name, 'wb') as f:\n f.seek(start)\n f.write(binary_content)\n\n def download(self) -> None:\n download_ranges = []\n\n for i in range(self.num_threads):\n start = i * self.chunk_size\n if i == self.num_threads - 1:\n end = self.file_size\n else:\n end = start + self.chunk_size - 1\n\n download_ranges.append((start, end))\n\n atomic_counter = AtomicCounter()\n process_pool = [Process(target=self._worker,\n args=(download_ranges[i], atomic_counter))\n for i in range(self.num_threads)]\n\n for p in process_pool:\n p.start()\n\n for p in process_pool:\n p.join()\n\n\nif __name__ == \"__main__\":\n downloader = Downloader(\n 'https://download-cf.jetbrains.com/idea/ideaIC-2019.3.3.tar.gz', 4)\n downloader.download()\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
# file = open('suifeng.txt')
# # text = file.read()
# # print(text)
# # file.close()
# with open('suifeng.txt') as f:
# print(f.read())
newList=[]
for i in range(11):
newList.append(i*2)
print(newList)
newList2=[i*2 for i in range(11)]
print(newList2)
list = ["小米","王银龙","王思"]
emptyList=[]
for name in list:
if name.startswith('王'):
emptyList.append(name)
print(emptyList)
print([name for name in list if name.startswith('王')])
|
normal
|
{
"blob_id": "3752b68e151379c57e1494715a45172607f4aead",
"index": 8090,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(11):\n newList.append(i * 2)\nprint(newList)\n<mask token>\nprint(newList2)\n<mask token>\nfor name in list:\n if name.startswith('王'):\n emptyList.append(name)\nprint(emptyList)\nprint([name for name in list if name.startswith('王')])\n",
"step-3": "newList = []\nfor i in range(11):\n newList.append(i * 2)\nprint(newList)\nnewList2 = [(i * 2) for i in range(11)]\nprint(newList2)\nlist = ['小米', '王银龙', '王思']\nemptyList = []\nfor name in list:\n if name.startswith('王'):\n emptyList.append(name)\nprint(emptyList)\nprint([name for name in list if name.startswith('王')])\n",
"step-4": "# file = open('suifeng.txt')\n# # text = file.read()\n# # print(text)\n# # file.close()\n\n# with open('suifeng.txt') as f:\n# print(f.read())\n\n\nnewList=[]\nfor i in range(11):\n newList.append(i*2)\nprint(newList)\n\nnewList2=[i*2 for i in range(11)]\nprint(newList2)\n\n\nlist = [\"小米\",\"王银龙\",\"王思\"]\nemptyList=[]\nfor name in list:\n if name.startswith('王'):\n emptyList.append(name)\nprint(emptyList)\n\nprint([name for name in list if name.startswith('王')])",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.3 on 2016-11-17 14:47
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('votes', '0003_choice_votes'),
]
operations = [
migrations.CreateModel(
name='Token',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('token', models.CharField(editable=False, max_length=6)),
('used', models.BooleanField(default=False, editable=False)),
],
),
migrations.AlterField(
model_name='choice',
name='votes',
field=models.IntegerField(default=0, editable=False),
),
]
|
normal
|
{
"blob_id": "781cb59fb9b6d22547fd4acf895457868342e125",
"index": 8290,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('votes', '0003_choice_votes')]\n operations = [migrations.CreateModel(name='Token', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('token', models.CharField(editable=\n False, max_length=6)), ('used', models.BooleanField(default=False,\n editable=False))]), migrations.AlterField(model_name='choice', name\n ='votes', field=models.IntegerField(default=0, editable=False))]\n",
"step-4": "from __future__ import unicode_literals\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n dependencies = [('votes', '0003_choice_votes')]\n operations = [migrations.CreateModel(name='Token', fields=[('id',\n models.AutoField(auto_created=True, primary_key=True, serialize=\n False, verbose_name='ID')), ('token', models.CharField(editable=\n False, max_length=6)), ('used', models.BooleanField(default=False,\n editable=False))]), migrations.AlterField(model_name='choice', name\n ='votes', field=models.IntegerField(default=0, editable=False))]\n",
"step-5": "# -*- coding: utf-8 -*-\n# Generated by Django 1.10.3 on 2016-11-17 14:47\nfrom __future__ import unicode_literals\n\nfrom django.db import migrations, models\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('votes', '0003_choice_votes'),\n ]\n\n operations = [\n migrations.CreateModel(\n name='Token',\n fields=[\n ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),\n ('token', models.CharField(editable=False, max_length=6)),\n ('used', models.BooleanField(default=False, editable=False)),\n ],\n ),\n migrations.AlterField(\n model_name='choice',\n name='votes',\n field=models.IntegerField(default=0, editable=False),\n ),\n ]\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
config_info = {'n_input': 1, 'num_layers': 1, 'features': 20,
'sequence_length': 1344, 'num_steps': None, 'lstm_size': None,
'batch_size': None, 'init_learning_rate': None, 'learning_rate_decay':
None, 'init_epoch': None, 'max_epoch': None, 'dropout_rate': None}
|
normal
|
{
"blob_id": "8ede786526f4b730173777d9d3b9c7e4554fc887",
"index": 2443,
"step-1": "<mask token>\n",
"step-2": "config_info = {'n_input': 1, 'num_layers': 1, 'features': 20,\n 'sequence_length': 1344, 'num_steps': None, 'lstm_size': None,\n 'batch_size': None, 'init_learning_rate': None, 'learning_rate_decay':\n None, 'init_epoch': None, 'max_epoch': None, 'dropout_rate': None}\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
from django.db import models
# Create your models here.
class GeneralInformation(models.Model):
name = models.CharField(max_length=100)
address = models.TextField()
city = models.CharField(max_length=20)
class Meta:
ordering = ['name']
def __str__(self):
return "{} {} {}".format(self.name, self.address, self.city)
|
normal
|
{
"blob_id": "d0f83e3b7eb5e1bc81a56e46043f394757437af8",
"index": 5504,
"step-1": "<mask token>\n\n\nclass GeneralInformation(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n ordering = ['name']\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass GeneralInformation(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n ordering = ['name']\n\n def __str__(self):\n return '{} {} {}'.format(self.name, self.address, self.city)\n",
"step-3": "<mask token>\n\n\nclass GeneralInformation(models.Model):\n name = models.CharField(max_length=100)\n address = models.TextField()\n city = models.CharField(max_length=20)\n\n\n class Meta:\n ordering = ['name']\n\n def __str__(self):\n return '{} {} {}'.format(self.name, self.address, self.city)\n",
"step-4": "from django.db import models\n\n\nclass GeneralInformation(models.Model):\n name = models.CharField(max_length=100)\n address = models.TextField()\n city = models.CharField(max_length=20)\n\n\n class Meta:\n ordering = ['name']\n\n def __str__(self):\n return '{} {} {}'.format(self.name, self.address, self.city)\n",
"step-5": "from django.db import models\n\n\n# Create your models here.\n\nclass GeneralInformation(models.Model):\n name = models.CharField(max_length=100)\n address = models.TextField()\n city = models.CharField(max_length=20)\n\n class Meta:\n ordering = ['name']\n\n def __str__(self):\n return \"{} {} {}\".format(self.name, self.address, self.city)\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
import pytest
import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
import extract_tables_columns
def test_get_tables():
sql_str = "SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;"
assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]
def test_get_tables_mutiline():
sql_str = """
SELECT *
FROM table1, table2
WHERE table1.column1 = table2.column1;
"""
assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]
def test_get_tables_tables_on_muti_lines():
sql_str = """
SELECT *
FROM table1, table2,
table3
WHERE table1.column1 = table2.column1;
"""
assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2'), ('TABLE3', 'TABLE3')]
def test_get_tables_single_table():
sql_str = """
SELECT *
FROM table1
WHERE table1.column1 = table2.column1;
"""
assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1')]
def test_get_tables_left_join():
sql_str = """
SELECT *
FROM table1
LEFT JOIN table2 ON table1.column1 = table2.column2
WHERE table1.column1 < 10;
"""
assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]
|
normal
|
{
"blob_id": "72286078841c7fe5b297767576741dbbd0a80411",
"index": 3457,
"step-1": "<mask token>\n\n\ndef test_get_tables():\n sql_str = (\n 'SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;')\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_mutiline():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2 \n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\n<mask token>\n\n\ndef test_get_tables_left_join():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n LEFT JOIN table2 ON table1.column1 = table2.column2\n WHERE table1.column1 < 10;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n",
"step-2": "<mask token>\n\n\ndef test_get_tables():\n sql_str = (\n 'SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;')\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_mutiline():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2 \n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\n<mask token>\n\n\ndef test_get_tables_single_table():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1', 'TABLE1')]\n\n\ndef test_get_tables_left_join():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n LEFT JOIN table2 ON table1.column1 = table2.column2\n WHERE table1.column1 < 10;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n",
"step-3": "<mask token>\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),\n '..')))\n<mask token>\n\n\ndef test_get_tables():\n sql_str = (\n 'SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;')\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_mutiline():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2 \n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_tables_on_muti_lines():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2,\n table3\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2'), ('TABLE3', 'TABLE3')]\n\n\ndef test_get_tables_single_table():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1', 'TABLE1')]\n\n\ndef test_get_tables_left_join():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n LEFT JOIN table2 ON table1.column1 = table2.column2\n WHERE table1.column1 < 10;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n",
"step-4": "import pytest\nimport os\nimport sys\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),\n '..')))\nimport extract_tables_columns\n\n\ndef test_get_tables():\n sql_str = (\n 'SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;')\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_mutiline():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2 \n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n\n\ndef test_get_tables_tables_on_muti_lines():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2,\n table3\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2'), ('TABLE3', 'TABLE3')]\n\n\ndef test_get_tables_single_table():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1', 'TABLE1')]\n\n\ndef test_get_tables_left_join():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n LEFT JOIN table2 ON table1.column1 = table2.column2\n WHERE table1.column1 < 10;\n \"\"\"\n assert extract_tables_columns.get_tables(sql_str) == [('TABLE1',\n 'TABLE1'), ('TABLE2', 'TABLE2')]\n",
"step-5": "import pytest\nimport os\nimport sys\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))\n\nimport extract_tables_columns\n\ndef test_get_tables():\n sql_str = \"SELECT * FROM table1, table2 WHERE table1.column1 = table2.column1;\"\n assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]\n\ndef test_get_tables_mutiline():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2 \n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]\n\ndef test_get_tables_tables_on_muti_lines():\n sql_str = \"\"\"\n SELECT * \n FROM table1, table2,\n table3\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2'), ('TABLE3', 'TABLE3')]\n\ndef test_get_tables_single_table():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n WHERE table1.column1 = table2.column1;\n \"\"\"\n assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1')]\n\ndef test_get_tables_left_join():\n sql_str = \"\"\"\n SELECT * \n FROM table1\n LEFT JOIN table2 ON table1.column1 = table2.column2\n WHERE table1.column1 < 10;\n \"\"\"\n assert(extract_tables_columns.get_tables(sql_str)) == [('TABLE1', 'TABLE1'), ('TABLE2', 'TABLE2')]",
"step-ids": [
3,
4,
6,
7,
8
]
}
|
[
3,
4,
6,
7,
8
] |
#!/usr/bin/python
# coding: utf-8
# # import re
# # import urllib
# #
# #
# # def getHtml(url):
# # page = urllib.urlopen(url)
# # html = page.read()
# # return html
# #
# #
# # def getMp4(html):
# # r = r"href='(http.*\.mp4)'"
# # re_mp4 = re.compile(r)
# # mp4List = re.findall(re_mp4, html)
# # filename = 1
# # for mp4url in mp4List:
# # urllib.urlretrieve(mp4url, "%s.mp4" % filename)
# # print 'file "%s.mp4" done' % filename
# # filename += 1
# # url = "http://v.youku.com/v_show/id_XMjYxMjEyNDU0MA==.html"
# # html = getHtml(url)
# # getMp4(html)
#
#
#
#
# # import re
# #
# #
# # pattern = re.compile(r'hello world')
# # match = pattern.match('hello world!')
# #
# # if match:
# # print match.group()
#
#
# #
# # # 冒泡排序
# # array = [4, 5, 0, 2, 3, 7, 1, 6]
# #
# # for i in range(len(array) - 1, 1, -1):
# # for j in range(0, i):
# # if array[j] > array[j + 1]:
# # array[j], array[j + 1] = array[j + 1], array[j]
# # print array
#
# # theString = 'saaaay yes no yaaaass'
# # print theString.strip('say') #say后面有空格
#
#
#
# # -*- coding:utf-8 -*-
# import urllib
# import urllib2
# import re
# import thread
# import time
#
#
# # 糗事百科爬虫类
# class QSBK:
# # 初始化方法，定义一些变量
# def __init__(self):
# self.pageIndex = 1
# self.user_agent = 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'
# # 初始化headers
# self.headers = {'User-Agent': self.user_agent}
# # 存放段子的变量，每一个元素是每一页的段子们
# self.stories = []
# # 存放程序是否继续运行的变量
# self.enable = False
#
# # 传入某一页的索引获得页面代码
# def getPage(self, pageIndex):
# try:
# url = 'http://www.qiushibaike.com/hot/page/' + str(pageIndex)
# # 构建请求的request
# request = urllib2.Request(url, headers=self.headers)
# # 利用urlopen获取页面代码
# response = urllib2.urlopen(request)
# # 将页面转化为UTF-8编码
# pageCode = response.read().decode('utf-8')
# return pageCode
#
# except urllib2.URLError, e:
# if hasattr(e, "reason"):
# print u"连接糗事百科失败,错误原因", e.reason
# return None
#
# # 传入某一页代码，返回本页不带图片的段子列表
# def getPageItems(self, pageIndex):
# pageCode = self.getPage(pageIndex)
# if not pageCode:
# print "页面加载失败...."
# return None
# # pattern = re.compile('<div class=author clearfix>.*?<img src=.*? alt=(.*?)>.*?<div.*?' +
# # '<span>(.*?)</span>.*?stats-vote><i class=number>(.*?)</i>.*?' +
# # '<i class=number>(.*?)</i>', re.S)
# pattern = re.compile('h2>(.*?)</h2.*?content">(.*?)</.*?number">(.*?)</', re.S)
# items = re.findall(pattern, pageCode)
# # 用来存储每页的段子们
# pageStories = []
# # 遍历正则表达式匹配的信息
# # for item in items:
# # # 是否含有图片
# # haveImg = re.search("img", item[3])
# # # 如果不含有图片，把它加入list中
# # if not haveImg:
# # replaceBR = re.compile('<br/>')
# # text = re.sub(replaceBR, "\n", item[1])
# # # item[0]是一个段子的发布者，item[1]是内容，item[2]是发布时间,item[4]是点赞数
# # pageStories.append([item[0].strip(), text.strip(), item[2].strip(), item[4].strip()])
# # return pageStories
# for item in items:
# pageStories.append([item[0].strip(), item[1].strip(), item[2].strip()])
# return pageStories
#
# # 加载并提取页面的内容，加入到列表中
# def loadPage(self):
# # 如果当前未看的页数少于2页，则加载新一页
# if self.enable == True:
# if len(self.stories) < 2:
# # 获取新一页
# pageStories = self.getPageItems(self.pageIndex)
# # 将该页的段子存放到全局list中
# if pageStories:
# self.stories.append(pageStories)
# # 获取完之后页码索引加一，表示下次读取下一页
# self.pageIndex += 1
#
# # 调用该方法，每次敲回车打印输出一个段子
# def getOneStory(self, pageStories, page):
# # 遍历一页的段子
# for story in pageStories:
# # 等待用户输入
# input = raw_input()
# # 每当输入回车一次，判断一下是否要加载新页面
# self.loadPage()
# # 如果输入Q则程序结束
# if input == "Q":
# self.enable = False
# return
# print u"第%d页\t发布人:%s\t 赞:%s\n%s" % (page, story[0], story[2], story[1])
#
# # 开始方法
# def start(self):
# print u"正在读取糗事百科,按回车查看新段子，Q退出"
# # 使变量为True，程序可以正常运行
# self.enable = True
# # 先加载一页内容
# self.loadPage()
# # 局部变量，控制当前读到了第几页
# nowPage = 0
# while self.enable:
# if len(self.stories) > 0:
# # 从全局list中获取一页的段子
# pageStories = self.stories[0]
# # 当前读到的页数加一
# nowPage += 1
# # 将全局list中第一个元素删除，因为已经取出
# del self.stories[0]
# # 输出该页的段子
# self.getOneStory(pageStories, nowPage)
#
#
# spider = QSBK()
# spider.start()
#
# print [x * x for x in range(1, 11) if x % 2 == 0]
def _odd_iter():
n = 1
while True:
n += 2
yield n
def _not_divisible(n):
return lambda x: x % n > 0
def primes():
yield 2
it = _odd_iter() # 初始序列
while True:
n = next(it) # 返回序列的第一个数
yield n
it = filter(_not_divisible(n), it) # 构造新序列
def main():
# 打印1000以内的素数:
for n in primes():
if n < 1000:
print(n)
else:
break
def is_palindrome(n):
return int(str(n)[::-1]) == n
def count():
def f(j):
# def g():
return j*j
# return g
fs = []
for i in range(1, 4):
fs.append(f(i)) # f(i)立刻被执行，因此i的当前值被传入f()
return fs
from PIL import Image
def changeImage():
im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')
print(im.format, im.size, im.mode)
im.thumbnail((1000, 500))
im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')
from multiprocessing import Process, Pool
import os, time, random
def run_proc(name):
print("Run child process %s %s" % (name, os.getpid()))
def long_time_task(name):
print('Run task %s %s...' % (name, os.getpid()))
start = time.time()
time.sleep(random.random() * 3)
end = time.time()
print('Task %s run %0.2f' % (name, (start - end)))
def chinese_to_pinyin(x):
"""参数为字符串，返回为该字符串对应的汉语拼音"""
y = ''
# dic = {}
# with open("unicode_pinyin.txt") as f:
# for i in f.readlines():
# dic[i.split()[0]] = i.split()[1]
for i in x:
i = str(i.encode('unicode_escape'))[-5:-1].upper()
# try:
# y += dic[i] + ' '
# except:
# y += 'XXXX ' # 非法字符我们用XXXX代替
return y
if __name__ == '__main__':
# main()
# print(_not_divisible(3))
# output = filter(is_palindrome, range(1, 1000))
# print(list(output))
# print(range(100))[::-1]
# f1, f2, f3 = count()
# print(f1)
# print(f2)
# print(f3)
# changeImage()
# print("Parent process %s ", os.getpid())
# p = Process(target=run_proc, args=("test",))
# print('Child process will start.')
# p.start()
# p.join()
# print('Child process end.')
# print("Parent process %s ", os.getpid())
# p = Pool(5)
# for i in range(5):
# p.apply_async(long_time_task, args=(i,))
# print('Waiting for all subprocesses done...')
# p.close()
# p.join()
# print('All subprocesses done.')
print(chinese_to_pinyin(u"陈"))
|
normal
|
{
"blob_id": "ad94118b43e130aec5df3976fd0460164de17511",
"index": 8361,
"step-1": "<mask token>\n\n\ndef _not_divisible(n):\n return lambda x: x % n > 0\n\n\ndef primes():\n yield 2\n it = _odd_iter()\n while True:\n n = next(it)\n yield n\n it = filter(_not_divisible(n), it)\n\n\ndef main():\n for n in primes():\n if n < 1000:\n print(n)\n else:\n break\n\n\n<mask token>\n\n\ndef changeImage():\n im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')\n print(im.format, im.size, im.mode)\n im.thumbnail((1000, 500))\n im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')\n\n\n<mask token>\n\n\ndef run_proc(name):\n print('Run child process %s %s' % (name, os.getpid()))\n\n\ndef long_time_task(name):\n print('Run task %s %s...' % (name, os.getpid()))\n start = time.time()\n time.sleep(random.random() * 3)\n end = time.time()\n print('Task %s run %0.2f' % (name, start - end))\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef _not_divisible(n):\n return lambda x: x % n > 0\n\n\ndef primes():\n yield 2\n it = _odd_iter()\n while True:\n n = next(it)\n yield n\n it = filter(_not_divisible(n), it)\n\n\ndef main():\n for n in primes():\n if n < 1000:\n print(n)\n else:\n break\n\n\ndef is_palindrome(n):\n return int(str(n)[::-1]) == n\n\n\ndef count():\n\n def f(j):\n return j * j\n fs = []\n for i in range(1, 4):\n fs.append(f(i))\n return fs\n\n\n<mask token>\n\n\ndef changeImage():\n im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')\n print(im.format, im.size, im.mode)\n im.thumbnail((1000, 500))\n im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')\n\n\n<mask token>\n\n\ndef run_proc(name):\n print('Run child process %s %s' % (name, os.getpid()))\n\n\ndef long_time_task(name):\n print('Run task %s %s...' % (name, os.getpid()))\n start = time.time()\n time.sleep(random.random() * 3)\n end = time.time()\n print('Task %s run %0.2f' % (name, start - end))\n\n\ndef chinese_to_pinyin(x):\n \"\"\"参数为字符串，返回为该字符串对应的汉语拼音\"\"\"\n y = ''\n for i in x:\n i = str(i.encode('unicode_escape'))[-5:-1].upper()\n return y\n\n\n<mask token>\n",
"step-3": "def _odd_iter():\n n = 1\n while True:\n n += 2\n yield n\n\n\ndef _not_divisible(n):\n return lambda x: x % n > 0\n\n\ndef primes():\n yield 2\n it = _odd_iter()\n while True:\n n = next(it)\n yield n\n it = filter(_not_divisible(n), it)\n\n\ndef main():\n for n in primes():\n if n < 1000:\n print(n)\n else:\n break\n\n\ndef is_palindrome(n):\n return int(str(n)[::-1]) == n\n\n\ndef count():\n\n def f(j):\n return j * j\n fs = []\n for i in range(1, 4):\n fs.append(f(i))\n return fs\n\n\n<mask token>\n\n\ndef changeImage():\n im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')\n print(im.format, im.size, im.mode)\n im.thumbnail((1000, 500))\n im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')\n\n\n<mask token>\n\n\ndef run_proc(name):\n print('Run child process %s %s' % (name, os.getpid()))\n\n\ndef long_time_task(name):\n print('Run task %s %s...' % (name, os.getpid()))\n start = time.time()\n time.sleep(random.random() * 3)\n end = time.time()\n print('Task %s run %0.2f' % (name, start - end))\n\n\ndef chinese_to_pinyin(x):\n \"\"\"参数为字符串，返回为该字符串对应的汉语拼音\"\"\"\n y = ''\n for i in x:\n i = str(i.encode('unicode_escape'))[-5:-1].upper()\n return y\n\n\n<mask token>\n",
"step-4": "def _odd_iter():\n n = 1\n while True:\n n += 2\n yield n\n\n\ndef _not_divisible(n):\n return lambda x: x % n > 0\n\n\ndef primes():\n yield 2\n it = _odd_iter()\n while True:\n n = next(it)\n yield n\n it = filter(_not_divisible(n), it)\n\n\ndef main():\n for n in primes():\n if n < 1000:\n print(n)\n else:\n break\n\n\ndef is_palindrome(n):\n return int(str(n)[::-1]) == n\n\n\ndef count():\n\n def f(j):\n return j * j\n fs = []\n for i in range(1, 4):\n fs.append(f(i))\n return fs\n\n\n<mask token>\n\n\ndef changeImage():\n im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')\n print(im.format, im.size, im.mode)\n im.thumbnail((1000, 500))\n im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')\n\n\n<mask token>\n\n\ndef run_proc(name):\n print('Run child process %s %s' % (name, os.getpid()))\n\n\ndef long_time_task(name):\n print('Run task %s %s...' % (name, os.getpid()))\n start = time.time()\n time.sleep(random.random() * 3)\n end = time.time()\n print('Task %s run %0.2f' % (name, start - end))\n\n\ndef chinese_to_pinyin(x):\n \"\"\"参数为字符串，返回为该字符串对应的汉语拼音\"\"\"\n y = ''\n for i in x:\n i = str(i.encode('unicode_escape'))[-5:-1].upper()\n return y\n\n\nif __name__ == '__main__':\n print(chinese_to_pinyin(u'陈'))\n",
"step-5": "#!/usr/bin/python\n# coding: utf-8\n\n\n# # import re\n# # import urllib\n# #\n# #\n# # def getHtml(url):\n# # page = urllib.urlopen(url)\n# # html = page.read()\n# # return html\n# #\n# #\n# # def getMp4(html):\n# # r = r\"href='(http.*\\.mp4)'\"\n# # re_mp4 = re.compile(r)\n# # mp4List = re.findall(re_mp4, html)\n# # filename = 1\n# # for mp4url in mp4List:\n# # urllib.urlretrieve(mp4url, \"%s.mp4\" % filename)\n# # print 'file \"%s.mp4\" done' % filename\n# # filename += 1\n# # url = \"http://v.youku.com/v_show/id_XMjYxMjEyNDU0MA==.html\"\n# # html = getHtml(url)\n# # getMp4(html)\n#\n#\n#\n#\n# # import re\n# #\n# #\n# # pattern = re.compile(r'hello world')\n# # match = pattern.match('hello world!')\n# #\n# # if match:\n# # print match.group()\n#\n#\n# #\n# # # 冒泡排序\n# # array = [4, 5, 0, 2, 3, 7, 1, 6]\n# #\n# # for i in range(len(array) - 1, 1, -1):\n# # for j in range(0, i):\n# # if array[j] > array[j + 1]:\n# # array[j], array[j + 1] = array[j + 1], array[j]\n# # print array\n#\n# # theString = 'saaaay yes no yaaaass'\n# # print theString.strip('say') #say后面有空格\n#\n#\n#\n# # -*- coding:utf-8 -*-\n# import urllib\n# import urllib2\n# import re\n# import thread\n# import time\n#\n#\n# # 糗事百科爬虫类\n# class QSBK:\n# # 初始化方法，定义一些变量\n# def __init__(self):\n# self.pageIndex = 1\n# self.user_agent = 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'\n# # 初始化headers\n# self.headers = {'User-Agent': self.user_agent}\n# # 存放段子的变量，每一个元素是每一页的段子们\n# self.stories = []\n# # 存放程序是否继续运行的变量\n# self.enable = False\n#\n# # 传入某一页的索引获得页面代码\n# def getPage(self, pageIndex):\n# try:\n# url = 'http://www.qiushibaike.com/hot/page/' + str(pageIndex)\n# # 构建请求的request\n# request = urllib2.Request(url, headers=self.headers)\n# # 利用urlopen获取页面代码\n# response = urllib2.urlopen(request)\n# # 将页面转化为UTF-8编码\n# pageCode = response.read().decode('utf-8')\n# return pageCode\n#\n# except urllib2.URLError, e:\n# if hasattr(e, \"reason\"):\n# print u\"连接糗事百科失败,错误原因\", e.reason\n# return None\n#\n# # 传入某一页代码，返回本页不带图片的段子列表\n# def getPageItems(self, pageIndex):\n# pageCode = self.getPage(pageIndex)\n# if not pageCode:\n# print \"页面加载失败....\"\n# return None\n# # pattern = re.compile('<div class=author clearfix>.*?<img src=.*? alt=(.*?)>.*?<div.*?' +\n# # '<span>(.*?)</span>.*?stats-vote><i class=number>(.*?)</i>.*?' +\n# # '<i class=number>(.*?)</i>', re.S)\n# pattern = re.compile('h2>(.*?)</h2.*?content\">(.*?)</.*?number\">(.*?)</', re.S)\n# items = re.findall(pattern, pageCode)\n# # 用来存储每页的段子们\n# pageStories = []\n# # 遍历正则表达式匹配的信息\n# # for item in items:\n# # # 是否含有图片\n# # haveImg = re.search(\"img\", item[3])\n# # # 如果不含有图片，把它加入list中\n# # if not haveImg:\n# # replaceBR = re.compile('<br/>')\n# # text = re.sub(replaceBR, \"\\n\", item[1])\n# # # item[0]是一个段子的发布者，item[1]是内容，item[2]是发布时间,item[4]是点赞数\n# # pageStories.append([item[0].strip(), text.strip(), item[2].strip(), item[4].strip()])\n# # return pageStories\n# for item in items:\n# pageStories.append([item[0].strip(), item[1].strip(), item[2].strip()])\n# return pageStories\n#\n# # 加载并提取页面的内容，加入到列表中\n# def loadPage(self):\n# # 如果当前未看的页数少于2页，则加载新一页\n# if self.enable == True:\n# if len(self.stories) < 2:\n# # 获取新一页\n# pageStories = self.getPageItems(self.pageIndex)\n# # 将该页的段子存放到全局list中\n# if pageStories:\n# self.stories.append(pageStories)\n# # 获取完之后页码索引加一，表示下次读取下一页\n# self.pageIndex += 1\n#\n# # 调用该方法，每次敲回车打印输出一个段子\n# def getOneStory(self, pageStories, page):\n# # 遍历一页的段子\n# for story in pageStories:\n# # 等待用户输入\n# input = raw_input()\n# # 每当输入回车一次，判断一下是否要加载新页面\n# self.loadPage()\n# # 如果输入Q则程序结束\n# if input == \"Q\":\n# self.enable = False\n# return\n# print u\"第%d页\\t发布人:%s\\t 赞:%s\\n%s\" % (page, story[0], story[2], story[1])\n#\n# # 开始方法\n# def start(self):\n# print u\"正在读取糗事百科,按回车查看新段子，Q退出\"\n# # 使变量为True，程序可以正常运行\n# self.enable = True\n# # 先加载一页内容\n# self.loadPage()\n# # 局部变量，控制当前读到了第几页\n# nowPage = 0\n# while self.enable:\n# if len(self.stories) > 0:\n# # 从全局list中获取一页的段子\n# pageStories = self.stories[0]\n# # 当前读到的页数加一\n# nowPage += 1\n# # 将全局list中第一个元素删除，因为已经取出\n# del self.stories[0]\n# # 输出该页的段子\n# self.getOneStory(pageStories, nowPage)\n#\n#\n# spider = QSBK()\n# spider.start()\n#\n# print [x * x for x in range(1, 11) if x % 2 == 0]\n\n\ndef _odd_iter():\n n = 1\n while True:\n n += 2\n yield n\n\n\ndef _not_divisible(n):\n return lambda x: x % n > 0\n\n\ndef primes():\n yield 2\n it = _odd_iter() # 初始序列\n while True:\n n = next(it) # 返回序列的第一个数\n yield n\n it = filter(_not_divisible(n), it) # 构造新序列\n\n\ndef main():\n # 打印1000以内的素数:\n for n in primes():\n if n < 1000:\n print(n)\n else:\n break\n\n\ndef is_palindrome(n):\n return int(str(n)[::-1]) == n\n\n\ndef count():\n def f(j):\n # def g():\n return j*j\n # return g\n fs = []\n for i in range(1, 4):\n fs.append(f(i)) # f(i)立刻被执行，因此i的当前值被传入f()\n return fs\n\n\nfrom PIL import Image\n\n\ndef changeImage():\n im = Image.open('C:/Users/Administrator/Desktop/1111.jpg')\n print(im.format, im.size, im.mode)\n im.thumbnail((1000, 500))\n im.save('C:/Users/Administrator/Desktop/11111.jpg', 'JPEG')\n\n\nfrom multiprocessing import Process, Pool\nimport os, time, random\n\n\ndef run_proc(name):\n print(\"Run child process %s %s\" % (name, os.getpid()))\n\n\ndef long_time_task(name):\n print('Run task %s %s...' % (name, os.getpid()))\n start = time.time()\n time.sleep(random.random() * 3)\n end = time.time()\n print('Task %s run %0.2f' % (name, (start - end)))\n\n\ndef chinese_to_pinyin(x):\n \"\"\"参数为字符串，返回为该字符串对应的汉语拼音\"\"\"\n y = ''\n # dic = {}\n # with open(\"unicode_pinyin.txt\") as f:\n # for i in f.readlines():\n # dic[i.split()[0]] = i.split()[1]\n for i in x:\n i = str(i.encode('unicode_escape'))[-5:-1].upper()\n # try:\n # y += dic[i] + ' '\n # except:\n # y += 'XXXX ' # 非法字符我们用XXXX代替\n return y\n\n\nif __name__ == '__main__':\n # main()\n # print(_not_divisible(3))\n # output = filter(is_palindrome, range(1, 1000))\n # print(list(output))\n # print(range(100))[::-1]\n # f1, f2, f3 = count()\n # print(f1)\n # print(f2)\n # print(f3)\n # changeImage()\n # print(\"Parent process %s \", os.getpid())\n # p = Process(target=run_proc, args=(\"test\",))\n # print('Child process will start.')\n # p.start()\n # p.join()\n # print('Child process end.')\n # print(\"Parent process %s \", os.getpid())\n # p = Pool(5)\n # for i in range(5):\n # p.apply_async(long_time_task, args=(i,))\n # print('Waiting for all subprocesses done...')\n # p.close()\n # p.join()\n # print('All subprocesses done.')\n print(chinese_to_pinyin(u\"陈\"))",
"step-ids": [
6,
9,
10,
11,
13
]
}
|
[
6,
9,
10,
11,
13
] |
import unittest
import achemkit.properties_wnx
class TestDummy(unittest.TestCase):
pass
|
normal
|
{
"blob_id": "5f0e6f6dc645996b486f1292fe05229a7fae9b17",
"index": 2342,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestDummy(unittest.TestCase):\n pass\n",
"step-3": "import unittest\nimport achemkit.properties_wnx\n\n\nclass TestDummy(unittest.TestCase):\n pass\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
offset = input()
cal = 1030 + int(offset) * 100
if 0 < cal < 2400:
print('Tuesday')
elif cal < 0:
print('Monday')
else:
print('Wednesday')
|
normal
|
{
"blob_id": "aefb49410e077180a660d17c4c646265a75969a7",
"index": 7509,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif 0 < cal < 2400:\n print('Tuesday')\nelif cal < 0:\n print('Monday')\nelse:\n print('Wednesday')\n",
"step-3": "offset = input()\ncal = 1030 + int(offset) * 100\nif 0 < cal < 2400:\n print('Tuesday')\nelif cal < 0:\n print('Monday')\nelse:\n print('Wednesday')\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
from PyQt5.QtWidgets import QApplication, QWidget
import sys
class Calculator(QWidget):
def __init__(self):
self.number_str = ""
self.version = "小树计算器 V1.0"
super().__init__()
self.resize(400,400)
from PyQt5.uic import loadUi # 需要导入的模块
#loadUi("record.ui", self) #加载UI文件
loadUi("calculator_gui.ui", self) #加载UI文件
#信号槽---- 按键触发
self.Button_0.clicked.connect(lambda: self.accept_button_value(0))
self.Button_1.clicked.connect(lambda: self.accept_button_value(1))
self.Button_2.clicked.connect(lambda: self.accept_button_value(2))
self.Button_3.clicked.connect(lambda: self.accept_button_value(3))
self.Button_4.clicked.connect(lambda: self.accept_button_value(4))
self.Button_5.clicked.connect(lambda: self.accept_button_value(5))
self.Button_6.clicked.connect(lambda: self.accept_button_value(6))
self.Button_7.clicked.connect(lambda: self.accept_button_value(7))
self.Button_8.clicked.connect(lambda: self.accept_button_value(8))
self.Button_9.clicked.connect(lambda: self.accept_button_value(9))
#功能按键触发
self.Button_addition.clicked.connect(lambda: self.accept_button_value("+"))
self.Button_subtraction.clicked.connect(lambda: self.accept_button_value("-"))
self.Button_multiplication.clicked.connect(lambda: self.accept_button_value("*"))
self.Button_division.clicked.connect(lambda: self.accept_button_value("/"))
self.Button_Backspace.clicked.connect(lambda: self.accept_button_value("Backspace"))
self.Button_Clean.clicked.connect(lambda: self.accept_button_value("Clean"))
self.Button_Infor.clicked.connect(lambda: self.accept_button_value("Infor"))
self.Button_L_par.clicked.connect(lambda: self.accept_button_value("("))
self.Button_R_par.clicked.connect(lambda: self.accept_button_value(")"))
self.Button_result.clicked.connect(lambda: self.calculation_results("计算结果"))
def accept_button_value(self, number):
if number == "Clean":
self.number_str = ""
elif number == "Backspace":
self.number_str = list(self.number_str)
if len(self.number_str) > 0:
self.number_str.pop()
self.number_str = "".join(self.number_str)
else:
self.number_str = ""
elif number == "Infor":
self.number_str = self.version
else:
line_edit_content = self.lineEdit.text()
if line_edit_content.find(self.version) >= 0:
self.number_str = ""
self.number_str = str(self.number_str) + str(number)
print(self.number_str)
self.lineEdit.setText(str(self.number_str))
def calculation_results(self, infor):
line_edit_content = self.lineEdit.text()
print(line_edit_content)
result = 0.0
if line_edit_content.find(self.version) >= 0:
self.lineEdit.setText("输入错误")
else:
try:
result = eval(line_edit_content)
except:
result = "计算错误，请检查输入"
self.lineEdit.setText(str(result))
if __name__=='__main__':
app=QApplication(sys.argv)
w=Calculator()
w.show()
sys.exit(app.exec_())
|
normal
|
{
"blob_id": "4df9af863a857c3bbc3c266d745a49b6ef78ba9b",
"index": 1994,
"step-1": "<mask token>\n\n\nclass Calculator(QWidget):\n <mask token>\n\n def accept_button_value(self, number):\n if number == 'Clean':\n self.number_str = ''\n elif number == 'Backspace':\n self.number_str = list(self.number_str)\n if len(self.number_str) > 0:\n self.number_str.pop()\n self.number_str = ''.join(self.number_str)\n else:\n self.number_str = ''\n elif number == 'Infor':\n self.number_str = self.version\n else:\n line_edit_content = self.lineEdit.text()\n if line_edit_content.find(self.version) >= 0:\n self.number_str = ''\n self.number_str = str(self.number_str) + str(number)\n print(self.number_str)\n self.lineEdit.setText(str(self.number_str))\n\n def calculation_results(self, infor):\n line_edit_content = self.lineEdit.text()\n print(line_edit_content)\n result = 0.0\n if line_edit_content.find(self.version) >= 0:\n self.lineEdit.setText('输入错误')\n else:\n try:\n result = eval(line_edit_content)\n except:\n result = '计算错误，请检查输入'\n self.lineEdit.setText(str(result))\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Calculator(QWidget):\n\n def __init__(self):\n self.number_str = ''\n self.version = '小树计算器 V1.0'\n super().__init__()\n self.resize(400, 400)\n from PyQt5.uic import loadUi\n loadUi('calculator_gui.ui', self)\n self.Button_0.clicked.connect(lambda : self.accept_button_value(0))\n self.Button_1.clicked.connect(lambda : self.accept_button_value(1))\n self.Button_2.clicked.connect(lambda : self.accept_button_value(2))\n self.Button_3.clicked.connect(lambda : self.accept_button_value(3))\n self.Button_4.clicked.connect(lambda : self.accept_button_value(4))\n self.Button_5.clicked.connect(lambda : self.accept_button_value(5))\n self.Button_6.clicked.connect(lambda : self.accept_button_value(6))\n self.Button_7.clicked.connect(lambda : self.accept_button_value(7))\n self.Button_8.clicked.connect(lambda : self.accept_button_value(8))\n self.Button_9.clicked.connect(lambda : self.accept_button_value(9))\n self.Button_addition.clicked.connect(lambda : self.\n accept_button_value('+'))\n self.Button_subtraction.clicked.connect(lambda : self.\n accept_button_value('-'))\n self.Button_multiplication.clicked.connect(lambda : self.\n accept_button_value('*'))\n self.Button_division.clicked.connect(lambda : self.\n accept_button_value('/'))\n self.Button_Backspace.clicked.connect(lambda : self.\n accept_button_value('Backspace'))\n self.Button_Clean.clicked.connect(lambda : self.accept_button_value\n ('Clean'))\n self.Button_Infor.clicked.connect(lambda : self.accept_button_value\n ('Infor'))\n self.Button_L_par.clicked.connect(lambda : self.accept_button_value\n ('('))\n self.Button_R_par.clicked.connect(lambda : self.accept_button_value\n (')'))\n self.Button_result.clicked.connect(lambda : self.\n calculation_results('计算结果'))\n\n def accept_button_value(self, number):\n if number == 'Clean':\n self.number_str = ''\n elif number == 'Backspace':\n self.number_str = list(self.number_str)\n if len(self.number_str) > 0:\n self.number_str.pop()\n self.number_str = ''.join(self.number_str)\n else:\n self.number_str = ''\n elif number == 'Infor':\n self.number_str = self.version\n else:\n line_edit_content = self.lineEdit.text()\n if line_edit_content.find(self.version) >= 0:\n self.number_str = ''\n self.number_str = str(self.number_str) + str(number)\n print(self.number_str)\n self.lineEdit.setText(str(self.number_str))\n\n def calculation_results(self, infor):\n line_edit_content = self.lineEdit.text()\n print(line_edit_content)\n result = 0.0\n if line_edit_content.find(self.version) >= 0:\n self.lineEdit.setText('输入错误')\n else:\n try:\n result = eval(line_edit_content)\n except:\n result = '计算错误，请检查输入'\n self.lineEdit.setText(str(result))\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Calculator(QWidget):\n\n def __init__(self):\n self.number_str = ''\n self.version = '小树计算器 V1.0'\n super().__init__()\n self.resize(400, 400)\n from PyQt5.uic import loadUi\n loadUi('calculator_gui.ui', self)\n self.Button_0.clicked.connect(lambda : self.accept_button_value(0))\n self.Button_1.clicked.connect(lambda : self.accept_button_value(1))\n self.Button_2.clicked.connect(lambda : self.accept_button_value(2))\n self.Button_3.clicked.connect(lambda : self.accept_button_value(3))\n self.Button_4.clicked.connect(lambda : self.accept_button_value(4))\n self.Button_5.clicked.connect(lambda : self.accept_button_value(5))\n self.Button_6.clicked.connect(lambda : self.accept_button_value(6))\n self.Button_7.clicked.connect(lambda : self.accept_button_value(7))\n self.Button_8.clicked.connect(lambda : self.accept_button_value(8))\n self.Button_9.clicked.connect(lambda : self.accept_button_value(9))\n self.Button_addition.clicked.connect(lambda : self.\n accept_button_value('+'))\n self.Button_subtraction.clicked.connect(lambda : self.\n accept_button_value('-'))\n self.Button_multiplication.clicked.connect(lambda : self.\n accept_button_value('*'))\n self.Button_division.clicked.connect(lambda : self.\n accept_button_value('/'))\n self.Button_Backspace.clicked.connect(lambda : self.\n accept_button_value('Backspace'))\n self.Button_Clean.clicked.connect(lambda : self.accept_button_value\n ('Clean'))\n self.Button_Infor.clicked.connect(lambda : self.accept_button_value\n ('Infor'))\n self.Button_L_par.clicked.connect(lambda : self.accept_button_value\n ('('))\n self.Button_R_par.clicked.connect(lambda : self.accept_button_value\n (')'))\n self.Button_result.clicked.connect(lambda : self.\n calculation_results('计算结果'))\n\n def accept_button_value(self, number):\n if number == 'Clean':\n self.number_str = ''\n elif number == 'Backspace':\n self.number_str = list(self.number_str)\n if len(self.number_str) > 0:\n self.number_str.pop()\n self.number_str = ''.join(self.number_str)\n else:\n self.number_str = ''\n elif number == 'Infor':\n self.number_str = self.version\n else:\n line_edit_content = self.lineEdit.text()\n if line_edit_content.find(self.version) >= 0:\n self.number_str = ''\n self.number_str = str(self.number_str) + str(number)\n print(self.number_str)\n self.lineEdit.setText(str(self.number_str))\n\n def calculation_results(self, infor):\n line_edit_content = self.lineEdit.text()\n print(line_edit_content)\n result = 0.0\n if line_edit_content.find(self.version) >= 0:\n self.lineEdit.setText('输入错误')\n else:\n try:\n result = eval(line_edit_content)\n except:\n result = '计算错误，请检查输入'\n self.lineEdit.setText(str(result))\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n w = Calculator()\n w.show()\n sys.exit(app.exec_())\n",
"step-4": "from PyQt5.QtWidgets import QApplication, QWidget\nimport sys\n\n\nclass Calculator(QWidget):\n\n def __init__(self):\n self.number_str = ''\n self.version = '小树计算器 V1.0'\n super().__init__()\n self.resize(400, 400)\n from PyQt5.uic import loadUi\n loadUi('calculator_gui.ui', self)\n self.Button_0.clicked.connect(lambda : self.accept_button_value(0))\n self.Button_1.clicked.connect(lambda : self.accept_button_value(1))\n self.Button_2.clicked.connect(lambda : self.accept_button_value(2))\n self.Button_3.clicked.connect(lambda : self.accept_button_value(3))\n self.Button_4.clicked.connect(lambda : self.accept_button_value(4))\n self.Button_5.clicked.connect(lambda : self.accept_button_value(5))\n self.Button_6.clicked.connect(lambda : self.accept_button_value(6))\n self.Button_7.clicked.connect(lambda : self.accept_button_value(7))\n self.Button_8.clicked.connect(lambda : self.accept_button_value(8))\n self.Button_9.clicked.connect(lambda : self.accept_button_value(9))\n self.Button_addition.clicked.connect(lambda : self.\n accept_button_value('+'))\n self.Button_subtraction.clicked.connect(lambda : self.\n accept_button_value('-'))\n self.Button_multiplication.clicked.connect(lambda : self.\n accept_button_value('*'))\n self.Button_division.clicked.connect(lambda : self.\n accept_button_value('/'))\n self.Button_Backspace.clicked.connect(lambda : self.\n accept_button_value('Backspace'))\n self.Button_Clean.clicked.connect(lambda : self.accept_button_value\n ('Clean'))\n self.Button_Infor.clicked.connect(lambda : self.accept_button_value\n ('Infor'))\n self.Button_L_par.clicked.connect(lambda : self.accept_button_value\n ('('))\n self.Button_R_par.clicked.connect(lambda : self.accept_button_value\n (')'))\n self.Button_result.clicked.connect(lambda : self.\n calculation_results('计算结果'))\n\n def accept_button_value(self, number):\n if number == 'Clean':\n self.number_str = ''\n elif number == 'Backspace':\n self.number_str = list(self.number_str)\n if len(self.number_str) > 0:\n self.number_str.pop()\n self.number_str = ''.join(self.number_str)\n else:\n self.number_str = ''\n elif number == 'Infor':\n self.number_str = self.version\n else:\n line_edit_content = self.lineEdit.text()\n if line_edit_content.find(self.version) >= 0:\n self.number_str = ''\n self.number_str = str(self.number_str) + str(number)\n print(self.number_str)\n self.lineEdit.setText(str(self.number_str))\n\n def calculation_results(self, infor):\n line_edit_content = self.lineEdit.text()\n print(line_edit_content)\n result = 0.0\n if line_edit_content.find(self.version) >= 0:\n self.lineEdit.setText('输入错误')\n else:\n try:\n result = eval(line_edit_content)\n except:\n result = '计算错误，请检查输入'\n self.lineEdit.setText(str(result))\n\n\nif __name__ == '__main__':\n app = QApplication(sys.argv)\n w = Calculator()\n w.show()\n sys.exit(app.exec_())\n",
"step-5": "from PyQt5.QtWidgets import QApplication, QWidget\nimport sys\n\nclass Calculator(QWidget):\n def __init__(self):\n self.number_str = \"\"\n self.version = \"小树计算器 V1.0\"\n\n super().__init__()\n self.resize(400,400)\n\n from PyQt5.uic import loadUi # 需要导入的模块\n #loadUi(\"record.ui\", self) #加载UI文件\n loadUi(\"calculator_gui.ui\", self) #加载UI文件\n\n #信号槽---- 按键触发\n self.Button_0.clicked.connect(lambda: self.accept_button_value(0)) \n self.Button_1.clicked.connect(lambda: self.accept_button_value(1)) \n self.Button_2.clicked.connect(lambda: self.accept_button_value(2)) \n self.Button_3.clicked.connect(lambda: self.accept_button_value(3)) \n self.Button_4.clicked.connect(lambda: self.accept_button_value(4)) \n self.Button_5.clicked.connect(lambda: self.accept_button_value(5)) \n self.Button_6.clicked.connect(lambda: self.accept_button_value(6)) \n self.Button_7.clicked.connect(lambda: self.accept_button_value(7)) \n self.Button_8.clicked.connect(lambda: self.accept_button_value(8)) \n self.Button_9.clicked.connect(lambda: self.accept_button_value(9)) \n \n #功能按键触发\n self.Button_addition.clicked.connect(lambda: self.accept_button_value(\"+\"))\n self.Button_subtraction.clicked.connect(lambda: self.accept_button_value(\"-\"))\n self.Button_multiplication.clicked.connect(lambda: self.accept_button_value(\"*\"))\n self.Button_division.clicked.connect(lambda: self.accept_button_value(\"/\"))\n\n self.Button_Backspace.clicked.connect(lambda: self.accept_button_value(\"Backspace\"))\n self.Button_Clean.clicked.connect(lambda: self.accept_button_value(\"Clean\")) \n self.Button_Infor.clicked.connect(lambda: self.accept_button_value(\"Infor\"))\n self.Button_L_par.clicked.connect(lambda: self.accept_button_value(\"(\"))\n self.Button_R_par.clicked.connect(lambda: self.accept_button_value(\")\"))\n\n self.Button_result.clicked.connect(lambda: self.calculation_results(\"计算结果\"))\n\n \n\n def accept_button_value(self, number):\n if number == \"Clean\":\n self.number_str = \"\"\n elif number == \"Backspace\":\n self.number_str = list(self.number_str)\n if len(self.number_str) > 0:\n self.number_str.pop()\n self.number_str = \"\".join(self.number_str)\n else:\n self.number_str = \"\"\n elif number == \"Infor\":\n self.number_str = self.version\n else:\n line_edit_content = self.lineEdit.text()\n if line_edit_content.find(self.version) >= 0:\n self.number_str = \"\"\n self.number_str = str(self.number_str) + str(number)\n print(self.number_str)\n self.lineEdit.setText(str(self.number_str))\n\n def calculation_results(self, infor):\n line_edit_content = self.lineEdit.text()\n print(line_edit_content)\n result = 0.0\n if line_edit_content.find(self.version) >= 0:\n self.lineEdit.setText(\"输入错误\")\n else:\n try:\n result = eval(line_edit_content)\n except:\n result = \"计算错误，请检查输入\"\n self.lineEdit.setText(str(result))\n \n\n \n\nif __name__=='__main__':\n app=QApplication(sys.argv)\n w=Calculator()\n w.show()\n sys.exit(app.exec_())\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
import pymysql
conn = None
cur = None
try:
conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='root', db='test')
cur = conn.cursor()
cur.execute("SELECT user_id, user_name FROM cap_user")
row_count = cur.rowcount
# row_number = cur.rownumber
for r in cur.fetchall():
print("userId is %s, userName is %s" % r)
except Exception as e:
print(e)
finally:
if cur is not None:
cur.close()
if conn is not None:
conn.close()
|
normal
|
{
"blob_id": "e5b5874f060bdf93ac4fadaf556aa4182619d077",
"index": 2033,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd\n ='root', db='test')\n cur = conn.cursor()\n cur.execute('SELECT user_id, user_name FROM cap_user')\n row_count = cur.rowcount\n for r in cur.fetchall():\n print('userId is %s, userName is %s' % r)\nexcept Exception as e:\n print(e)\nfinally:\n if cur is not None:\n cur.close()\n if conn is not None:\n conn.close()\n",
"step-3": "<mask token>\nconn = None\ncur = None\ntry:\n conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd\n ='root', db='test')\n cur = conn.cursor()\n cur.execute('SELECT user_id, user_name FROM cap_user')\n row_count = cur.rowcount\n for r in cur.fetchall():\n print('userId is %s, userName is %s' % r)\nexcept Exception as e:\n print(e)\nfinally:\n if cur is not None:\n cur.close()\n if conn is not None:\n conn.close()\n",
"step-4": "import pymysql\nconn = None\ncur = None\ntry:\n conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd\n ='root', db='test')\n cur = conn.cursor()\n cur.execute('SELECT user_id, user_name FROM cap_user')\n row_count = cur.rowcount\n for r in cur.fetchall():\n print('userId is %s, userName is %s' % r)\nexcept Exception as e:\n print(e)\nfinally:\n if cur is not None:\n cur.close()\n if conn is not None:\n conn.close()\n",
"step-5": "import pymysql\n\n\nconn = None\ncur = None\ntry:\n conn = pymysql.connect(host='127.0.0.1', port=3306, user='root', passwd='root', db='test')\n cur = conn.cursor()\n cur.execute(\"SELECT user_id, user_name FROM cap_user\")\n row_count = cur.rowcount\n # row_number = cur.rownumber\n for r in cur.fetchall():\n print(\"userId is %s, userName is %s\" % r)\nexcept Exception as e:\n print(e)\nfinally:\n if cur is not None:\n cur.close()\n if conn is not None:\n conn.close()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# Copyright 2017-2018 Ivan Yelizariev <https://it-projects.info/team/yelizariev>
# License MIT (https://opensource.org/licenses/MIT).
from datetime import datetime, timedelta
from odoo import fields
from odoo.tests.common import TransactionCase
class TestCase(TransactionCase):
def setUp(self):
super(TestCase, self).setUp()
self.event = self.env["event.event"].create(
{
"name": "TestEvent",
"attendee_signup": True,
"create_partner": True,
"date_begin": fields.Datetime.to_string(
datetime.today() + timedelta(days=1)
),
"date_end": fields.Datetime.to_string(
datetime.today() + timedelta(days=15)
),
}
)
|
normal
|
{
"blob_id": "29ec576d1fe04108eeb03a5d1b167671d3004570",
"index": 4403,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestCase(TransactionCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestCase(TransactionCase):\n\n def setUp(self):\n super(TestCase, self).setUp()\n self.event = self.env['event.event'].create({'name': 'TestEvent',\n 'attendee_signup': True, 'create_partner': True, 'date_begin':\n fields.Datetime.to_string(datetime.today() + timedelta(days=1)),\n 'date_end': fields.Datetime.to_string(datetime.today() +\n timedelta(days=15))})\n",
"step-4": "from datetime import datetime, timedelta\nfrom odoo import fields\nfrom odoo.tests.common import TransactionCase\n\n\nclass TestCase(TransactionCase):\n\n def setUp(self):\n super(TestCase, self).setUp()\n self.event = self.env['event.event'].create({'name': 'TestEvent',\n 'attendee_signup': True, 'create_partner': True, 'date_begin':\n fields.Datetime.to_string(datetime.today() + timedelta(days=1)),\n 'date_end': fields.Datetime.to_string(datetime.today() +\n timedelta(days=15))})\n",
"step-5": "# Copyright 2017-2018 Ivan Yelizariev <https://it-projects.info/team/yelizariev>\n# License MIT (https://opensource.org/licenses/MIT).\nfrom datetime import datetime, timedelta\n\nfrom odoo import fields\nfrom odoo.tests.common import TransactionCase\n\n\nclass TestCase(TransactionCase):\n def setUp(self):\n super(TestCase, self).setUp()\n self.event = self.env[\"event.event\"].create(\n {\n \"name\": \"TestEvent\",\n \"attendee_signup\": True,\n \"create_partner\": True,\n \"date_begin\": fields.Datetime.to_string(\n datetime.today() + timedelta(days=1)\n ),\n \"date_end\": fields.Datetime.to_string(\n datetime.today() + timedelta(days=15)\n ),\n }\n )\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Part of Odoo. See LICENSE file for full copyright and licensing details.
import calendar as cal
import random
import pytz
from datetime import datetime, timedelta, time
from dateutil import rrule
from dateutil.relativedelta import relativedelta
from babel.dates import format_datetime
from odoo import api, fields, models, _
from odoo.tools.misc import get_lang
from odoo.addons.base.models.res_partner import _tz_get
from odoo.addons.http_routing.models.ir_http import slug
from odoo.exceptions import ValidationError
class CalendarAppointmentType(models.Model):
_name = "calendar.appointment.type"
_description = "Online Appointment Type"
_inherit = ['mail.thread', "website.seo.metadata", 'website.published.mixin']
_order = "sequence"
sequence = fields.Integer('Sequence')
name = fields.Char('Appointment Type', required=True, translate=True)
min_schedule_hours = fields.Float('Schedule before (hours)', required=True, default=1.0)
max_schedule_days = fields.Integer('Schedule not after (days)', required=True, default=15)
min_cancellation_hours = fields.Float('Cancel Before (hours)', required=True, default=1.0)
appointment_duration = fields.Float('Appointment Duration', required=True, default=1.0)
reminder_ids = fields.Many2many('calendar.alarm', string="Reminders")
location = fields.Char('Location', help="Location of the appointments")
message_confirmation = fields.Html('Confirmation Message', translate=True)
message_intro = fields.Html('Introduction Message', translate=True)
country_ids = fields.Many2many(
'res.country', 'website_calendar_type_country_rel', string='Restrict Countries',
help="Keep empty to allow visitors from any country, otherwise you only allow visitors from selected countries")
question_ids = fields.One2many('calendar.appointment.question', 'appointment_type_id', string='Questions', copy=True)
slot_ids = fields.One2many('calendar.appointment.slot', 'appointment_type_id', 'Availabilities', copy=True)
appointment_tz = fields.Selection(
_tz_get, string='Timezone', required=True, default=lambda self: self.env.user.tz,
help="Timezone where appointment take place")
employee_ids = fields.Many2many('hr.employee', 'website_calendar_type_employee_rel', domain=[('user_id', '!=', False)], string='Employees')
assignation_method = fields.Selection([
('random', 'Random'),
('chosen', 'Chosen by the Customer')], string='Assignment Method', default='random',
help="How employees will be assigned to meetings customers book on your website.")
appointment_count = fields.Integer('# Appointments', compute='_compute_appointment_count')
def _compute_appointment_count(self):
meeting_data = self.env['calendar.event'].read_group([('appointment_type_id', 'in', self.ids)], ['appointment_type_id'], ['appointment_type_id'])
mapped_data = {m['appointment_type_id'][0]: m['appointment_type_id_count'] for m in meeting_data}
for appointment_type in self:
appointment_type.appointment_count = mapped_data.get(appointment_type.id, 0)
def _compute_website_url(self):
super(CalendarAppointmentType, self)._compute_website_url()
for appointment_type in self:
if appointment_type.id :
appointment_type.website_url = '/calendar/%s/appointment' % (slug(appointment_type),)
@api.returns('self', lambda value: value.id)
def copy(self, default=None):
default = default or {}
default['name'] = self.name + _(' (copy)')
return super(CalendarAppointmentType, self).copy(default=default)
def action_calendar_meetings(self):
self.ensure_one()
action = self.env["ir.actions.actions"]._for_xml_id("calendar.action_calendar_event")
action['context'] = {
'default_appointment_type_id': self.id,
'search_default_appointment_type_id': self.id
}
return action
# --------------------------------------
# Slots Generation
# --------------------------------------
def _slots_generate(self, first_day, last_day, timezone):
""" Generate all appointment slots (in naive UTC, appointment timezone, and given (visitors) timezone)
between first_day and last_day (datetimes in appointment timezone)
:return: [ {'slot': slot_record, <timezone>: (date_start, date_end), ...},
... ]
"""
def append_slot(day, slot):
local_start = appt_tz.localize(datetime.combine(day, time(hour=int(slot.hour), minute=int(round((slot.hour % 1) * 60)))))
local_end = appt_tz.localize(
datetime.combine(day, time(hour=int(slot.hour), minute=int(round((slot.hour % 1) * 60)))) + relativedelta(hours=self.appointment_duration))
slots.append({
self.appointment_tz: (
local_start,
local_end,
),
timezone: (
local_start.astimezone(requested_tz),
local_end.astimezone(requested_tz),
),
'UTC': (
local_start.astimezone(pytz.UTC).replace(tzinfo=None),
local_end.astimezone(pytz.UTC).replace(tzinfo=None),
),
'slot': slot,
})
appt_tz = pytz.timezone(self.appointment_tz)
requested_tz = pytz.timezone(timezone)
slots = []
for slot in self.slot_ids.filtered(lambda x: int(x.weekday) == first_day.isoweekday()):
if slot.hour > first_day.hour + first_day.minute / 60.0:
append_slot(first_day.date(), slot)
slot_weekday = [int(weekday) - 1 for weekday in self.slot_ids.mapped('weekday')]
for day in rrule.rrule(rrule.DAILY,
dtstart=first_day.date() + timedelta(days=1),
until=last_day.date(),
byweekday=slot_weekday):
for slot in self.slot_ids.filtered(lambda x: int(x.weekday) == day.isoweekday()):
append_slot(day, slot)
return slots
def _slots_available(self, slots, first_day, last_day, employee=None):
""" Fills the slot stucture with an available employee
:param slots: slots structure generated by _slots_generate
:param first_day: start datetime in UTC
:param last_day: end datetime in UTC
:param employee: if set, only consider this employee
if not set, consider all employees assigned to this appointment type
"""
def is_work_available(start_dt, end_dt, intervals):
""" check if the slot is contained in the employee's work hours (defined by intervals)
"""
def find_start_index():
""" find the highest index of intervals for which the start_date (element [0]) is before (or at) start_dt
"""
def recursive_find_index(lower_bound, upper_bound):
if upper_bound - lower_bound <= 1:
if intervals[upper_bound][0] <= start_dt:
return upper_bound
return lower_bound
index = (upper_bound + lower_bound) // 2
if intervals[index][0] <= start_dt:
return recursive_find_index(index, upper_bound)
else:
return recursive_find_index(lower_bound, index)
if start_dt <= intervals[0][0] - tolerance:
return -1
if end_dt >= intervals[-1][1] + tolerance:
return -1
return recursive_find_index(0, len(intervals) - 1)
if not intervals:
return False
tolerance = timedelta(minutes=1)
start_index = find_start_index()
if start_index != -1:
for index in range(start_index, len(intervals)):
if intervals[index][1] >= end_dt - tolerance:
return True
if len(intervals) == index + 1 or intervals[index + 1][0] - intervals[index][1] > tolerance:
return False
return False
def is_calendar_available(slot, events, employee):
""" Returns True if the given slot doesn't collide with given events for the employee
"""
start_dt = slot['UTC'][0]
end_dt = slot['UTC'][1]
event_in_scope = lambda ev: (
fields.Date.to_date(ev.start) <= fields.Date.to_date(end_dt)
and fields.Date.to_date(ev.stop) >= fields.Date.to_date(start_dt)
)
for ev in events.filtered(event_in_scope):
if ev.allday:
# allday events are considered to take the whole day in the related employee's timezone
event_tz = pytz.timezone(ev.event_tz or employee.user_id.tz or self.env.user.tz or slot['slot'].appointment_type_id.appointment_tz or 'UTC')
ev_start_dt = datetime.combine(fields.Date.from_string(ev.start_date), time.min)
ev_stop_dt = datetime.combine(fields.Date.from_string(ev.stop_date), time.max)
ev_start_dt = event_tz.localize(ev_start_dt).astimezone(pytz.UTC).replace(tzinfo=None)
ev_stop_dt = event_tz.localize(ev_stop_dt).astimezone(pytz.UTC).replace(tzinfo=None)
if ev_start_dt < end_dt and ev_stop_dt > start_dt:
return False
elif fields.Datetime.to_datetime(ev.start) < end_dt and fields.Datetime.to_datetime(ev.stop) > start_dt:
return False
return True
workhours = {}
meetings = {}
# With context will be used in resource.calendar to force the referential user
# for work interval computing to the *user linked to the employee*
available_employees = [emp.with_context(tz=emp.user_id.tz) for emp in (employee or self.employee_ids)]
random.shuffle(available_employees)
for slot in slots:
for emp_pos, emp in enumerate(available_employees):
if emp_pos not in workhours:
workhours[emp_pos] = [
(interval[0].astimezone(pytz.UTC).replace(tzinfo=None),
interval[1].astimezone(pytz.UTC).replace(tzinfo=None))
for interval in emp.resource_calendar_id._work_intervals_batch(
first_day, last_day, resources=emp.resource_id,
)[emp.resource_id.id]
]
if is_work_available(slot['UTC'][0], slot['UTC'][1], workhours[emp_pos]):
if emp_pos not in meetings:
# note: no check is made on the attendee's status (accepted/declined/...)
meetings[emp_pos] = self.env['calendar.event'].search([
('partner_ids.user_ids', '=', emp.user_id.id),
('start', '<', fields.Datetime.to_string(last_day.replace(hour=23, minute=59, second=59))),
('stop', '>', fields.Datetime.to_string(first_day.replace(hour=0, minute=0, second=0)))
])
if is_calendar_available(slot, meetings[emp_pos], emp):
slot['employee_id'] = emp
break
def _get_appointment_slots(self, timezone, employee=None):
""" Fetch available slots to book an appointment
:param timezone: timezone string e.g.: 'Europe/Brussels' or 'Etc/GMT+1'
:param employee: if set will only check available slots for this employee
:returns: list of dicts (1 per month) containing available slots per day per week.
complex structure used to simplify rendering of template
"""
self.ensure_one()
appt_tz = pytz.timezone(self.appointment_tz)
requested_tz = pytz.timezone(timezone)
first_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(hours=self.min_schedule_hours))
last_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(days=self.max_schedule_days))
# Compute available slots (ordered)
slots = self._slots_generate(first_day.astimezone(appt_tz), last_day.astimezone(appt_tz), timezone)
if not employee or employee in self.employee_ids:
self._slots_available(slots, first_day.astimezone(pytz.UTC), last_day.astimezone(pytz.UTC), employee)
# Compute calendar rendering and inject available slots
today = requested_tz.fromutc(datetime.utcnow())
start = today
month_dates_calendar = cal.Calendar(0).monthdatescalendar
months = []
while (start.year, start.month) <= (last_day.year, last_day.month):
dates = month_dates_calendar(start.year, start.month)
for week_index, week in enumerate(dates):
for day_index, day in enumerate(week):
mute_cls = weekend_cls = today_cls = None
today_slots = []
if day.weekday() in (cal.SUNDAY, cal.SATURDAY):
weekend_cls = 'o_weekend'
if day == today.date() and day.month == today.month:
today_cls = 'o_today'
if day.month != start.month:
mute_cls = 'text-muted o_mute_day'
else:
# slots are ordered, so check all unprocessed slots from until > day
while slots and (slots[0][timezone][0].date() <= day):
if (slots[0][timezone][0].date() == day) and ('employee_id' in slots[0]):
today_slots.append({
'employee_id': slots[0]['employee_id'].id,
'datetime': slots[0][timezone][0].strftime('%Y-%m-%d %H:%M:%S'),
'hours': slots[0][timezone][0].strftime('%H:%M')
})
slots.pop(0)
dates[week_index][day_index] = {
'day': day,
'slots': today_slots,
'mute_cls': mute_cls,
'weekend_cls': weekend_cls,
'today_cls': today_cls
}
months.append({
'month': format_datetime(start, 'MMMM Y', locale=get_lang(self.env).code),
'weeks': dates
})
start = start + relativedelta(months=1)
return months
class CalendarAppointmentSlot(models.Model):
_name = "calendar.appointment.slot"
_description = "Online Appointment : Time Slot"
_rec_name = "weekday"
_order = "weekday, hour"
appointment_type_id = fields.Many2one('calendar.appointment.type', 'Appointment Type', ondelete='cascade')
weekday = fields.Selection([
('1', 'Monday'),
('2', 'Tuesday'),
('3', 'Wednesday'),
('4', 'Thursday'),
('5', 'Friday'),
('6', 'Saturday'),
('7', 'Sunday'),
], string='Week Day', required=True)
hour = fields.Float('Starting Hour', required=True, default=8.0)
@api.constrains('hour')
def check_hour(self):
if any(slot.hour < 0.00 or slot.hour >= 24.00 for slot in self):
raise ValidationError(_("Please enter a valid hour between 0:00 and 24:00 for your slots."))
def name_get(self):
weekdays = dict(self._fields['weekday'].selection)
return self.mapped(lambda slot: (slot.id, "%s, %02d:%02d" % (weekdays.get(slot.weekday), int(slot.hour), int(round((slot.hour % 1) * 60)))))
class CalendarAppointmentQuestion(models.Model):
_name = "calendar.appointment.question"
_description = "Online Appointment : Questions"
_order = "sequence"
sequence = fields.Integer('Sequence')
appointment_type_id = fields.Many2one('calendar.appointment.type', 'Appointment Type', ondelete="cascade")
name = fields.Char('Question', translate=True, required=True)
placeholder = fields.Char('Placeholder', translate=True)
question_required = fields.Boolean('Required Answer')
question_type = fields.Selection([
('char', 'Single line text'),
('text', 'Multi-line text'),
('select', 'Dropdown (one answer)'),
('radio', 'Radio (one answer)'),
('checkbox', 'Checkboxes (multiple answers)')], 'Question Type', default='char')
answer_ids = fields.Many2many('calendar.appointment.answer', 'calendar_appointment_question_answer_rel', 'question_id', 'answer_id', string='Available Answers')
class CalendarAppointmentAnswer(models.Model):
_name = "calendar.appointment.answer"
_description = "Online Appointment : Answers"
question_id = fields.Many2many('calendar.appointment.question', 'calendar_appointment_question_answer_rel', 'answer_id', 'question_id', string='Questions')
name = fields.Char('Answer', translate=True, required=True)
|
normal
|
{
"blob_id": "e03dfa0e02313c5478d4e97dcaf3bc27915bd878",
"index": 1421,
"step-1": "<mask token>\n\n\nclass CalendarAppointmentSlot(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @api.constrains('hour')\n def check_hour(self):\n if any(slot.hour < 0.0 or slot.hour >= 24.0 for slot in self):\n raise ValidationError(_(\n 'Please enter a valid hour between 0:00 and 24:00 for your slots.'\n ))\n\n def name_get(self):\n weekdays = dict(self._fields['weekday'].selection)\n return self.mapped(lambda slot: (slot.id, '%s, %02d:%02d' % (\n weekdays.get(slot.weekday), int(slot.hour), int(round(slot.hour %\n 1 * 60)))))\n\n\nclass CalendarAppointmentQuestion(models.Model):\n _name = 'calendar.appointment.question'\n _description = 'Online Appointment : Questions'\n _order = 'sequence'\n sequence = fields.Integer('Sequence')\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n name = fields.Char('Question', translate=True, required=True)\n placeholder = fields.Char('Placeholder', translate=True)\n question_required = fields.Boolean('Required Answer')\n question_type = fields.Selection([('char', 'Single line text'), ('text',\n 'Multi-line text'), ('select', 'Dropdown (one answer)'), ('radio',\n 'Radio (one answer)'), ('checkbox', 'Checkboxes (multiple answers)'\n )], 'Question Type', default='char')\n answer_ids = fields.Many2many('calendar.appointment.answer',\n 'calendar_appointment_question_answer_rel', 'question_id',\n 'answer_id', string='Available Answers')\n\n\nclass CalendarAppointmentAnswer(models.Model):\n _name = 'calendar.appointment.answer'\n _description = 'Online Appointment : Answers'\n question_id = fields.Many2many('calendar.appointment.question',\n 'calendar_appointment_question_answer_rel', 'answer_id',\n 'question_id', string='Questions')\n name = fields.Char('Answer', translate=True, required=True)\n",
"step-2": "<mask token>\n\n\nclass CalendarAppointmentType(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _get_appointment_slots(self, timezone, employee=None):\n \"\"\" Fetch available slots to book an appointment\n :param timezone: timezone string e.g.: 'Europe/Brussels' or 'Etc/GMT+1'\n :param employee: if set will only check available slots for this employee\n :returns: list of dicts (1 per month) containing available slots per day per week.\n complex structure used to simplify rendering of template\n \"\"\"\n self.ensure_one()\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n first_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n hours=self.min_schedule_hours))\n last_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n days=self.max_schedule_days))\n slots = self._slots_generate(first_day.astimezone(appt_tz),\n last_day.astimezone(appt_tz), timezone)\n if not employee or employee in self.employee_ids:\n self._slots_available(slots, first_day.astimezone(pytz.UTC),\n last_day.astimezone(pytz.UTC), employee)\n today = requested_tz.fromutc(datetime.utcnow())\n start = today\n month_dates_calendar = cal.Calendar(0).monthdatescalendar\n months = []\n while (start.year, start.month) <= (last_day.year, last_day.month):\n dates = month_dates_calendar(start.year, start.month)\n for week_index, week in enumerate(dates):\n for day_index, day in enumerate(week):\n mute_cls = weekend_cls = today_cls = None\n today_slots = []\n if day.weekday() in (cal.SUNDAY, cal.SATURDAY):\n weekend_cls = 'o_weekend'\n if day == today.date() and day.month == today.month:\n today_cls = 'o_today'\n if day.month != start.month:\n mute_cls = 'text-muted o_mute_day'\n else:\n while slots and slots[0][timezone][0].date() <= day:\n if slots[0][timezone][0].date(\n ) == day and 'employee_id' in slots[0]:\n today_slots.append({'employee_id': slots[0]\n ['employee_id'].id, 'datetime': slots[0\n ][timezone][0].strftime(\n '%Y-%m-%d %H:%M:%S'), 'hours': slots[0]\n [timezone][0].strftime('%H:%M')})\n slots.pop(0)\n dates[week_index][day_index] = {'day': day, 'slots':\n today_slots, 'mute_cls': mute_cls, 'weekend_cls':\n weekend_cls, 'today_cls': today_cls}\n months.append({'month': format_datetime(start, 'MMMM Y', locale\n =get_lang(self.env).code), 'weeks': dates})\n start = start + relativedelta(months=1)\n return months\n\n\nclass CalendarAppointmentSlot(models.Model):\n _name = 'calendar.appointment.slot'\n _description = 'Online Appointment : Time Slot'\n _rec_name = 'weekday'\n _order = 'weekday, hour'\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n weekday = fields.Selection([('1', 'Monday'), ('2', 'Tuesday'), ('3',\n 'Wednesday'), ('4', 'Thursday'), ('5', 'Friday'), ('6', 'Saturday'),\n ('7', 'Sunday')], string='Week Day', required=True)\n hour = fields.Float('Starting Hour', required=True, default=8.0)\n\n @api.constrains('hour')\n def check_hour(self):\n if any(slot.hour < 0.0 or slot.hour >= 24.0 for slot in self):\n raise ValidationError(_(\n 'Please enter a valid hour between 0:00 and 24:00 for your slots.'\n ))\n\n def name_get(self):\n weekdays = dict(self._fields['weekday'].selection)\n return self.mapped(lambda slot: (slot.id, '%s, %02d:%02d' % (\n weekdays.get(slot.weekday), int(slot.hour), int(round(slot.hour %\n 1 * 60)))))\n\n\nclass CalendarAppointmentQuestion(models.Model):\n _name = 'calendar.appointment.question'\n _description = 'Online Appointment : Questions'\n _order = 'sequence'\n sequence = fields.Integer('Sequence')\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n name = fields.Char('Question', translate=True, required=True)\n placeholder = fields.Char('Placeholder', translate=True)\n question_required = fields.Boolean('Required Answer')\n question_type = fields.Selection([('char', 'Single line text'), ('text',\n 'Multi-line text'), ('select', 'Dropdown (one answer)'), ('radio',\n 'Radio (one answer)'), ('checkbox', 'Checkboxes (multiple answers)'\n )], 'Question Type', default='char')\n answer_ids = fields.Many2many('calendar.appointment.answer',\n 'calendar_appointment_question_answer_rel', 'question_id',\n 'answer_id', string='Available Answers')\n\n\nclass CalendarAppointmentAnswer(models.Model):\n _name = 'calendar.appointment.answer'\n _description = 'Online Appointment : Answers'\n question_id = fields.Many2many('calendar.appointment.question',\n 'calendar_appointment_question_answer_rel', 'answer_id',\n 'question_id', string='Questions')\n name = fields.Char('Answer', translate=True, required=True)\n",
"step-3": "<mask token>\n\n\nclass CalendarAppointmentType(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _compute_website_url(self):\n super(CalendarAppointmentType, self)._compute_website_url()\n for appointment_type in self:\n if appointment_type.id:\n appointment_type.website_url = '/calendar/%s/appointment' % (\n slug(appointment_type),)\n <mask token>\n\n def action_calendar_meetings(self):\n self.ensure_one()\n action = self.env['ir.actions.actions']._for_xml_id(\n 'calendar.action_calendar_event')\n action['context'] = {'default_appointment_type_id': self.id,\n 'search_default_appointment_type_id': self.id}\n return action\n <mask token>\n <mask token>\n\n def _get_appointment_slots(self, timezone, employee=None):\n \"\"\" Fetch available slots to book an appointment\n :param timezone: timezone string e.g.: 'Europe/Brussels' or 'Etc/GMT+1'\n :param employee: if set will only check available slots for this employee\n :returns: list of dicts (1 per month) containing available slots per day per week.\n complex structure used to simplify rendering of template\n \"\"\"\n self.ensure_one()\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n first_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n hours=self.min_schedule_hours))\n last_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n days=self.max_schedule_days))\n slots = self._slots_generate(first_day.astimezone(appt_tz),\n last_day.astimezone(appt_tz), timezone)\n if not employee or employee in self.employee_ids:\n self._slots_available(slots, first_day.astimezone(pytz.UTC),\n last_day.astimezone(pytz.UTC), employee)\n today = requested_tz.fromutc(datetime.utcnow())\n start = today\n month_dates_calendar = cal.Calendar(0).monthdatescalendar\n months = []\n while (start.year, start.month) <= (last_day.year, last_day.month):\n dates = month_dates_calendar(start.year, start.month)\n for week_index, week in enumerate(dates):\n for day_index, day in enumerate(week):\n mute_cls = weekend_cls = today_cls = None\n today_slots = []\n if day.weekday() in (cal.SUNDAY, cal.SATURDAY):\n weekend_cls = 'o_weekend'\n if day == today.date() and day.month == today.month:\n today_cls = 'o_today'\n if day.month != start.month:\n mute_cls = 'text-muted o_mute_day'\n else:\n while slots and slots[0][timezone][0].date() <= day:\n if slots[0][timezone][0].date(\n ) == day and 'employee_id' in slots[0]:\n today_slots.append({'employee_id': slots[0]\n ['employee_id'].id, 'datetime': slots[0\n ][timezone][0].strftime(\n '%Y-%m-%d %H:%M:%S'), 'hours': slots[0]\n [timezone][0].strftime('%H:%M')})\n slots.pop(0)\n dates[week_index][day_index] = {'day': day, 'slots':\n today_slots, 'mute_cls': mute_cls, 'weekend_cls':\n weekend_cls, 'today_cls': today_cls}\n months.append({'month': format_datetime(start, 'MMMM Y', locale\n =get_lang(self.env).code), 'weeks': dates})\n start = start + relativedelta(months=1)\n return months\n\n\nclass CalendarAppointmentSlot(models.Model):\n _name = 'calendar.appointment.slot'\n _description = 'Online Appointment : Time Slot'\n _rec_name = 'weekday'\n _order = 'weekday, hour'\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n weekday = fields.Selection([('1', 'Monday'), ('2', 'Tuesday'), ('3',\n 'Wednesday'), ('4', 'Thursday'), ('5', 'Friday'), ('6', 'Saturday'),\n ('7', 'Sunday')], string='Week Day', required=True)\n hour = fields.Float('Starting Hour', required=True, default=8.0)\n\n @api.constrains('hour')\n def check_hour(self):\n if any(slot.hour < 0.0 or slot.hour >= 24.0 for slot in self):\n raise ValidationError(_(\n 'Please enter a valid hour between 0:00 and 24:00 for your slots.'\n ))\n\n def name_get(self):\n weekdays = dict(self._fields['weekday'].selection)\n return self.mapped(lambda slot: (slot.id, '%s, %02d:%02d' % (\n weekdays.get(slot.weekday), int(slot.hour), int(round(slot.hour %\n 1 * 60)))))\n\n\nclass CalendarAppointmentQuestion(models.Model):\n _name = 'calendar.appointment.question'\n _description = 'Online Appointment : Questions'\n _order = 'sequence'\n sequence = fields.Integer('Sequence')\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n name = fields.Char('Question', translate=True, required=True)\n placeholder = fields.Char('Placeholder', translate=True)\n question_required = fields.Boolean('Required Answer')\n question_type = fields.Selection([('char', 'Single line text'), ('text',\n 'Multi-line text'), ('select', 'Dropdown (one answer)'), ('radio',\n 'Radio (one answer)'), ('checkbox', 'Checkboxes (multiple answers)'\n )], 'Question Type', default='char')\n answer_ids = fields.Many2many('calendar.appointment.answer',\n 'calendar_appointment_question_answer_rel', 'question_id',\n 'answer_id', string='Available Answers')\n\n\nclass CalendarAppointmentAnswer(models.Model):\n _name = 'calendar.appointment.answer'\n _description = 'Online Appointment : Answers'\n question_id = fields.Many2many('calendar.appointment.question',\n 'calendar_appointment_question_answer_rel', 'answer_id',\n 'question_id', string='Questions')\n name = fields.Char('Answer', translate=True, required=True)\n",
"step-4": "import calendar as cal\nimport random\nimport pytz\nfrom datetime import datetime, timedelta, time\nfrom dateutil import rrule\nfrom dateutil.relativedelta import relativedelta\nfrom babel.dates import format_datetime\nfrom odoo import api, fields, models, _\nfrom odoo.tools.misc import get_lang\nfrom odoo.addons.base.models.res_partner import _tz_get\nfrom odoo.addons.http_routing.models.ir_http import slug\nfrom odoo.exceptions import ValidationError\n\n\nclass CalendarAppointmentType(models.Model):\n _name = 'calendar.appointment.type'\n _description = 'Online Appointment Type'\n _inherit = ['mail.thread', 'website.seo.metadata',\n 'website.published.mixin']\n _order = 'sequence'\n sequence = fields.Integer('Sequence')\n name = fields.Char('Appointment Type', required=True, translate=True)\n min_schedule_hours = fields.Float('Schedule before (hours)', required=\n True, default=1.0)\n max_schedule_days = fields.Integer('Schedule not after (days)',\n required=True, default=15)\n min_cancellation_hours = fields.Float('Cancel Before (hours)', required\n =True, default=1.0)\n appointment_duration = fields.Float('Appointment Duration', required=\n True, default=1.0)\n reminder_ids = fields.Many2many('calendar.alarm', string='Reminders')\n location = fields.Char('Location', help='Location of the appointments')\n message_confirmation = fields.Html('Confirmation Message', translate=True)\n message_intro = fields.Html('Introduction Message', translate=True)\n country_ids = fields.Many2many('res.country',\n 'website_calendar_type_country_rel', string='Restrict Countries',\n help=\n 'Keep empty to allow visitors from any country, otherwise you only allow visitors from selected countries'\n )\n question_ids = fields.One2many('calendar.appointment.question',\n 'appointment_type_id', string='Questions', copy=True)\n slot_ids = fields.One2many('calendar.appointment.slot',\n 'appointment_type_id', 'Availabilities', copy=True)\n appointment_tz = fields.Selection(_tz_get, string='Timezone', required=\n True, default=lambda self: self.env.user.tz, help=\n 'Timezone where appointment take place')\n employee_ids = fields.Many2many('hr.employee',\n 'website_calendar_type_employee_rel', domain=[('user_id', '!=', \n False)], string='Employees')\n assignation_method = fields.Selection([('random', 'Random'), ('chosen',\n 'Chosen by the Customer')], string='Assignment Method', default=\n 'random', help=\n 'How employees will be assigned to meetings customers book on your website.'\n )\n appointment_count = fields.Integer('# Appointments', compute=\n '_compute_appointment_count')\n\n def _compute_appointment_count(self):\n meeting_data = self.env['calendar.event'].read_group([(\n 'appointment_type_id', 'in', self.ids)], ['appointment_type_id'\n ], ['appointment_type_id'])\n mapped_data = {m['appointment_type_id'][0]: m[\n 'appointment_type_id_count'] for m in meeting_data}\n for appointment_type in self:\n appointment_type.appointment_count = mapped_data.get(\n appointment_type.id, 0)\n\n def _compute_website_url(self):\n super(CalendarAppointmentType, self)._compute_website_url()\n for appointment_type in self:\n if appointment_type.id:\n appointment_type.website_url = '/calendar/%s/appointment' % (\n slug(appointment_type),)\n\n @api.returns('self', lambda value: value.id)\n def copy(self, default=None):\n default = default or {}\n default['name'] = self.name + _(' (copy)')\n return super(CalendarAppointmentType, self).copy(default=default)\n\n def action_calendar_meetings(self):\n self.ensure_one()\n action = self.env['ir.actions.actions']._for_xml_id(\n 'calendar.action_calendar_event')\n action['context'] = {'default_appointment_type_id': self.id,\n 'search_default_appointment_type_id': self.id}\n return action\n\n def _slots_generate(self, first_day, last_day, timezone):\n \"\"\" Generate all appointment slots (in naive UTC, appointment timezone, and given (visitors) timezone)\n between first_day and last_day (datetimes in appointment timezone)\n\n :return: [ {'slot': slot_record, <timezone>: (date_start, date_end), ...},\n ... ]\n \"\"\"\n\n def append_slot(day, slot):\n local_start = appt_tz.localize(datetime.combine(day, time(hour=\n int(slot.hour), minute=int(round(slot.hour % 1 * 60)))))\n local_end = appt_tz.localize(datetime.combine(day, time(hour=\n int(slot.hour), minute=int(round(slot.hour % 1 * 60)))) +\n relativedelta(hours=self.appointment_duration))\n slots.append({self.appointment_tz: (local_start, local_end),\n timezone: (local_start.astimezone(requested_tz), local_end.\n astimezone(requested_tz)), 'UTC': (local_start.astimezone(\n pytz.UTC).replace(tzinfo=None), local_end.astimezone(pytz.\n UTC).replace(tzinfo=None)), 'slot': slot})\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n slots = []\n for slot in self.slot_ids.filtered(lambda x: int(x.weekday) ==\n first_day.isoweekday()):\n if slot.hour > first_day.hour + first_day.minute / 60.0:\n append_slot(first_day.date(), slot)\n slot_weekday = [(int(weekday) - 1) for weekday in self.slot_ids.\n mapped('weekday')]\n for day in rrule.rrule(rrule.DAILY, dtstart=first_day.date() +\n timedelta(days=1), until=last_day.date(), byweekday=slot_weekday):\n for slot in self.slot_ids.filtered(lambda x: int(x.weekday) ==\n day.isoweekday()):\n append_slot(day, slot)\n return slots\n\n def _slots_available(self, slots, first_day, last_day, employee=None):\n \"\"\" Fills the slot stucture with an available employee\n\n :param slots: slots structure generated by _slots_generate\n :param first_day: start datetime in UTC\n :param last_day: end datetime in UTC\n :param employee: if set, only consider this employee\n if not set, consider all employees assigned to this appointment type\n \"\"\"\n\n def is_work_available(start_dt, end_dt, intervals):\n \"\"\" check if the slot is contained in the employee's work hours (defined by intervals)\n \"\"\"\n\n def find_start_index():\n \"\"\" find the highest index of intervals for which the start_date (element [0]) is before (or at) start_dt\n \"\"\"\n\n def recursive_find_index(lower_bound, upper_bound):\n if upper_bound - lower_bound <= 1:\n if intervals[upper_bound][0] <= start_dt:\n return upper_bound\n return lower_bound\n index = (upper_bound + lower_bound) // 2\n if intervals[index][0] <= start_dt:\n return recursive_find_index(index, upper_bound)\n else:\n return recursive_find_index(lower_bound, index)\n if start_dt <= intervals[0][0] - tolerance:\n return -1\n if end_dt >= intervals[-1][1] + tolerance:\n return -1\n return recursive_find_index(0, len(intervals) - 1)\n if not intervals:\n return False\n tolerance = timedelta(minutes=1)\n start_index = find_start_index()\n if start_index != -1:\n for index in range(start_index, len(intervals)):\n if intervals[index][1] >= end_dt - tolerance:\n return True\n if len(intervals) == index + 1 or intervals[index + 1][0\n ] - intervals[index][1] > tolerance:\n return False\n return False\n\n def is_calendar_available(slot, events, employee):\n \"\"\" Returns True if the given slot doesn't collide with given events for the employee\n \"\"\"\n start_dt = slot['UTC'][0]\n end_dt = slot['UTC'][1]\n event_in_scope = lambda ev: fields.Date.to_date(ev.start\n ) <= fields.Date.to_date(end_dt) and fields.Date.to_date(ev\n .stop) >= fields.Date.to_date(start_dt)\n for ev in events.filtered(event_in_scope):\n if ev.allday:\n event_tz = pytz.timezone(ev.event_tz or employee.\n user_id.tz or self.env.user.tz or slot['slot'].\n appointment_type_id.appointment_tz or 'UTC')\n ev_start_dt = datetime.combine(fields.Date.from_string(\n ev.start_date), time.min)\n ev_stop_dt = datetime.combine(fields.Date.from_string(\n ev.stop_date), time.max)\n ev_start_dt = event_tz.localize(ev_start_dt).astimezone(\n pytz.UTC).replace(tzinfo=None)\n ev_stop_dt = event_tz.localize(ev_stop_dt).astimezone(pytz\n .UTC).replace(tzinfo=None)\n if ev_start_dt < end_dt and ev_stop_dt > start_dt:\n return False\n elif fields.Datetime.to_datetime(ev.start\n ) < end_dt and fields.Datetime.to_datetime(ev.stop\n ) > start_dt:\n return False\n return True\n workhours = {}\n meetings = {}\n available_employees = [emp.with_context(tz=emp.user_id.tz) for emp in\n employee or self.employee_ids]\n random.shuffle(available_employees)\n for slot in slots:\n for emp_pos, emp in enumerate(available_employees):\n if emp_pos not in workhours:\n workhours[emp_pos] = [(interval[0].astimezone(pytz.UTC)\n .replace(tzinfo=None), interval[1].astimezone(pytz.\n UTC).replace(tzinfo=None)) for interval in emp.\n resource_calendar_id._work_intervals_batch(\n first_day, last_day, resources=emp.resource_id)[emp\n .resource_id.id]]\n if is_work_available(slot['UTC'][0], slot['UTC'][1],\n workhours[emp_pos]):\n if emp_pos not in meetings:\n meetings[emp_pos] = self.env['calendar.event'].search([\n ('partner_ids.user_ids', '=', emp.user_id.id),\n ('start', '<', fields.Datetime.to_string(\n last_day.replace(hour=23, minute=59, second=59)\n )), ('stop', '>', fields.Datetime.to_string(\n first_day.replace(hour=0, minute=0, second=0)))])\n if is_calendar_available(slot, meetings[emp_pos], emp):\n slot['employee_id'] = emp\n break\n\n def _get_appointment_slots(self, timezone, employee=None):\n \"\"\" Fetch available slots to book an appointment\n :param timezone: timezone string e.g.: 'Europe/Brussels' or 'Etc/GMT+1'\n :param employee: if set will only check available slots for this employee\n :returns: list of dicts (1 per month) containing available slots per day per week.\n complex structure used to simplify rendering of template\n \"\"\"\n self.ensure_one()\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n first_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n hours=self.min_schedule_hours))\n last_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(\n days=self.max_schedule_days))\n slots = self._slots_generate(first_day.astimezone(appt_tz),\n last_day.astimezone(appt_tz), timezone)\n if not employee or employee in self.employee_ids:\n self._slots_available(slots, first_day.astimezone(pytz.UTC),\n last_day.astimezone(pytz.UTC), employee)\n today = requested_tz.fromutc(datetime.utcnow())\n start = today\n month_dates_calendar = cal.Calendar(0).monthdatescalendar\n months = []\n while (start.year, start.month) <= (last_day.year, last_day.month):\n dates = month_dates_calendar(start.year, start.month)\n for week_index, week in enumerate(dates):\n for day_index, day in enumerate(week):\n mute_cls = weekend_cls = today_cls = None\n today_slots = []\n if day.weekday() in (cal.SUNDAY, cal.SATURDAY):\n weekend_cls = 'o_weekend'\n if day == today.date() and day.month == today.month:\n today_cls = 'o_today'\n if day.month != start.month:\n mute_cls = 'text-muted o_mute_day'\n else:\n while slots and slots[0][timezone][0].date() <= day:\n if slots[0][timezone][0].date(\n ) == day and 'employee_id' in slots[0]:\n today_slots.append({'employee_id': slots[0]\n ['employee_id'].id, 'datetime': slots[0\n ][timezone][0].strftime(\n '%Y-%m-%d %H:%M:%S'), 'hours': slots[0]\n [timezone][0].strftime('%H:%M')})\n slots.pop(0)\n dates[week_index][day_index] = {'day': day, 'slots':\n today_slots, 'mute_cls': mute_cls, 'weekend_cls':\n weekend_cls, 'today_cls': today_cls}\n months.append({'month': format_datetime(start, 'MMMM Y', locale\n =get_lang(self.env).code), 'weeks': dates})\n start = start + relativedelta(months=1)\n return months\n\n\nclass CalendarAppointmentSlot(models.Model):\n _name = 'calendar.appointment.slot'\n _description = 'Online Appointment : Time Slot'\n _rec_name = 'weekday'\n _order = 'weekday, hour'\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n weekday = fields.Selection([('1', 'Monday'), ('2', 'Tuesday'), ('3',\n 'Wednesday'), ('4', 'Thursday'), ('5', 'Friday'), ('6', 'Saturday'),\n ('7', 'Sunday')], string='Week Day', required=True)\n hour = fields.Float('Starting Hour', required=True, default=8.0)\n\n @api.constrains('hour')\n def check_hour(self):\n if any(slot.hour < 0.0 or slot.hour >= 24.0 for slot in self):\n raise ValidationError(_(\n 'Please enter a valid hour between 0:00 and 24:00 for your slots.'\n ))\n\n def name_get(self):\n weekdays = dict(self._fields['weekday'].selection)\n return self.mapped(lambda slot: (slot.id, '%s, %02d:%02d' % (\n weekdays.get(slot.weekday), int(slot.hour), int(round(slot.hour %\n 1 * 60)))))\n\n\nclass CalendarAppointmentQuestion(models.Model):\n _name = 'calendar.appointment.question'\n _description = 'Online Appointment : Questions'\n _order = 'sequence'\n sequence = fields.Integer('Sequence')\n appointment_type_id = fields.Many2one('calendar.appointment.type',\n 'Appointment Type', ondelete='cascade')\n name = fields.Char('Question', translate=True, required=True)\n placeholder = fields.Char('Placeholder', translate=True)\n question_required = fields.Boolean('Required Answer')\n question_type = fields.Selection([('char', 'Single line text'), ('text',\n 'Multi-line text'), ('select', 'Dropdown (one answer)'), ('radio',\n 'Radio (one answer)'), ('checkbox', 'Checkboxes (multiple answers)'\n )], 'Question Type', default='char')\n answer_ids = fields.Many2many('calendar.appointment.answer',\n 'calendar_appointment_question_answer_rel', 'question_id',\n 'answer_id', string='Available Answers')\n\n\nclass CalendarAppointmentAnswer(models.Model):\n _name = 'calendar.appointment.answer'\n _description = 'Online Appointment : Answers'\n question_id = fields.Many2many('calendar.appointment.question',\n 'calendar_appointment_question_answer_rel', 'answer_id',\n 'question_id', string='Questions')\n name = fields.Char('Answer', translate=True, required=True)\n",
"step-5": "# -*- coding: utf-8 -*-\n# Part of Odoo. See LICENSE file for full copyright and licensing details.\n\nimport calendar as cal\nimport random\nimport pytz\nfrom datetime import datetime, timedelta, time\nfrom dateutil import rrule\nfrom dateutil.relativedelta import relativedelta\nfrom babel.dates import format_datetime\n\nfrom odoo import api, fields, models, _\nfrom odoo.tools.misc import get_lang\nfrom odoo.addons.base.models.res_partner import _tz_get\nfrom odoo.addons.http_routing.models.ir_http import slug\nfrom odoo.exceptions import ValidationError\n\n\nclass CalendarAppointmentType(models.Model):\n _name = \"calendar.appointment.type\"\n _description = \"Online Appointment Type\"\n _inherit = ['mail.thread', \"website.seo.metadata\", 'website.published.mixin']\n _order = \"sequence\"\n\n sequence = fields.Integer('Sequence')\n name = fields.Char('Appointment Type', required=True, translate=True)\n min_schedule_hours = fields.Float('Schedule before (hours)', required=True, default=1.0)\n max_schedule_days = fields.Integer('Schedule not after (days)', required=True, default=15)\n min_cancellation_hours = fields.Float('Cancel Before (hours)', required=True, default=1.0)\n appointment_duration = fields.Float('Appointment Duration', required=True, default=1.0)\n\n reminder_ids = fields.Many2many('calendar.alarm', string=\"Reminders\")\n location = fields.Char('Location', help=\"Location of the appointments\")\n message_confirmation = fields.Html('Confirmation Message', translate=True)\n message_intro = fields.Html('Introduction Message', translate=True)\n\n country_ids = fields.Many2many(\n 'res.country', 'website_calendar_type_country_rel', string='Restrict Countries',\n help=\"Keep empty to allow visitors from any country, otherwise you only allow visitors from selected countries\")\n question_ids = fields.One2many('calendar.appointment.question', 'appointment_type_id', string='Questions', copy=True)\n\n slot_ids = fields.One2many('calendar.appointment.slot', 'appointment_type_id', 'Availabilities', copy=True)\n appointment_tz = fields.Selection(\n _tz_get, string='Timezone', required=True, default=lambda self: self.env.user.tz,\n help=\"Timezone where appointment take place\")\n employee_ids = fields.Many2many('hr.employee', 'website_calendar_type_employee_rel', domain=[('user_id', '!=', False)], string='Employees')\n assignation_method = fields.Selection([\n ('random', 'Random'),\n ('chosen', 'Chosen by the Customer')], string='Assignment Method', default='random',\n help=\"How employees will be assigned to meetings customers book on your website.\")\n appointment_count = fields.Integer('# Appointments', compute='_compute_appointment_count')\n\n def _compute_appointment_count(self):\n meeting_data = self.env['calendar.event'].read_group([('appointment_type_id', 'in', self.ids)], ['appointment_type_id'], ['appointment_type_id'])\n mapped_data = {m['appointment_type_id'][0]: m['appointment_type_id_count'] for m in meeting_data}\n for appointment_type in self:\n appointment_type.appointment_count = mapped_data.get(appointment_type.id, 0)\n\n def _compute_website_url(self):\n super(CalendarAppointmentType, self)._compute_website_url()\n for appointment_type in self:\n if appointment_type.id :\n appointment_type.website_url = '/calendar/%s/appointment' % (slug(appointment_type),)\n\n @api.returns('self', lambda value: value.id)\n def copy(self, default=None):\n default = default or {}\n default['name'] = self.name + _(' (copy)')\n return super(CalendarAppointmentType, self).copy(default=default)\n\n def action_calendar_meetings(self):\n self.ensure_one()\n action = self.env[\"ir.actions.actions\"]._for_xml_id(\"calendar.action_calendar_event\")\n action['context'] = {\n 'default_appointment_type_id': self.id,\n 'search_default_appointment_type_id': self.id\n }\n return action\n\n # --------------------------------------\n # Slots Generation\n # --------------------------------------\n\n def _slots_generate(self, first_day, last_day, timezone):\n \"\"\" Generate all appointment slots (in naive UTC, appointment timezone, and given (visitors) timezone)\n between first_day and last_day (datetimes in appointment timezone)\n\n :return: [ {'slot': slot_record, <timezone>: (date_start, date_end), ...},\n ... ]\n \"\"\"\n def append_slot(day, slot):\n local_start = appt_tz.localize(datetime.combine(day, time(hour=int(slot.hour), minute=int(round((slot.hour % 1) * 60)))))\n local_end = appt_tz.localize(\n datetime.combine(day, time(hour=int(slot.hour), minute=int(round((slot.hour % 1) * 60)))) + relativedelta(hours=self.appointment_duration))\n slots.append({\n self.appointment_tz: (\n local_start,\n local_end,\n ),\n timezone: (\n local_start.astimezone(requested_tz),\n local_end.astimezone(requested_tz),\n ),\n 'UTC': (\n local_start.astimezone(pytz.UTC).replace(tzinfo=None),\n local_end.astimezone(pytz.UTC).replace(tzinfo=None),\n ),\n 'slot': slot,\n })\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n\n slots = []\n for slot in self.slot_ids.filtered(lambda x: int(x.weekday) == first_day.isoweekday()):\n if slot.hour > first_day.hour + first_day.minute / 60.0:\n append_slot(first_day.date(), slot)\n slot_weekday = [int(weekday) - 1 for weekday in self.slot_ids.mapped('weekday')]\n for day in rrule.rrule(rrule.DAILY,\n dtstart=first_day.date() + timedelta(days=1),\n until=last_day.date(),\n byweekday=slot_weekday):\n for slot in self.slot_ids.filtered(lambda x: int(x.weekday) == day.isoweekday()):\n append_slot(day, slot)\n return slots\n\n def _slots_available(self, slots, first_day, last_day, employee=None):\n \"\"\" Fills the slot stucture with an available employee\n\n :param slots: slots structure generated by _slots_generate\n :param first_day: start datetime in UTC\n :param last_day: end datetime in UTC\n :param employee: if set, only consider this employee\n if not set, consider all employees assigned to this appointment type\n \"\"\"\n\n def is_work_available(start_dt, end_dt, intervals):\n \"\"\" check if the slot is contained in the employee's work hours (defined by intervals)\n \"\"\"\n def find_start_index():\n \"\"\" find the highest index of intervals for which the start_date (element [0]) is before (or at) start_dt\n \"\"\"\n def recursive_find_index(lower_bound, upper_bound):\n if upper_bound - lower_bound <= 1:\n if intervals[upper_bound][0] <= start_dt:\n return upper_bound\n return lower_bound\n index = (upper_bound + lower_bound) // 2\n if intervals[index][0] <= start_dt:\n return recursive_find_index(index, upper_bound)\n else:\n return recursive_find_index(lower_bound, index)\n\n if start_dt <= intervals[0][0] - tolerance:\n return -1\n if end_dt >= intervals[-1][1] + tolerance:\n return -1\n return recursive_find_index(0, len(intervals) - 1)\n\n if not intervals:\n return False\n\n tolerance = timedelta(minutes=1)\n start_index = find_start_index()\n if start_index != -1:\n for index in range(start_index, len(intervals)):\n if intervals[index][1] >= end_dt - tolerance:\n return True\n if len(intervals) == index + 1 or intervals[index + 1][0] - intervals[index][1] > tolerance:\n return False\n return False\n\n def is_calendar_available(slot, events, employee):\n \"\"\" Returns True if the given slot doesn't collide with given events for the employee\n \"\"\"\n start_dt = slot['UTC'][0]\n end_dt = slot['UTC'][1]\n\n event_in_scope = lambda ev: (\n fields.Date.to_date(ev.start) <= fields.Date.to_date(end_dt)\n and fields.Date.to_date(ev.stop) >= fields.Date.to_date(start_dt)\n )\n\n for ev in events.filtered(event_in_scope):\n if ev.allday:\n # allday events are considered to take the whole day in the related employee's timezone\n event_tz = pytz.timezone(ev.event_tz or employee.user_id.tz or self.env.user.tz or slot['slot'].appointment_type_id.appointment_tz or 'UTC')\n ev_start_dt = datetime.combine(fields.Date.from_string(ev.start_date), time.min)\n ev_stop_dt = datetime.combine(fields.Date.from_string(ev.stop_date), time.max)\n ev_start_dt = event_tz.localize(ev_start_dt).astimezone(pytz.UTC).replace(tzinfo=None)\n ev_stop_dt = event_tz.localize(ev_stop_dt).astimezone(pytz.UTC).replace(tzinfo=None)\n if ev_start_dt < end_dt and ev_stop_dt > start_dt:\n return False\n elif fields.Datetime.to_datetime(ev.start) < end_dt and fields.Datetime.to_datetime(ev.stop) > start_dt:\n return False\n return True\n\n workhours = {}\n meetings = {}\n\n # With context will be used in resource.calendar to force the referential user\n # for work interval computing to the *user linked to the employee*\n available_employees = [emp.with_context(tz=emp.user_id.tz) for emp in (employee or self.employee_ids)]\n random.shuffle(available_employees)\n for slot in slots:\n for emp_pos, emp in enumerate(available_employees):\n if emp_pos not in workhours:\n workhours[emp_pos] = [\n (interval[0].astimezone(pytz.UTC).replace(tzinfo=None),\n interval[1].astimezone(pytz.UTC).replace(tzinfo=None))\n for interval in emp.resource_calendar_id._work_intervals_batch(\n first_day, last_day, resources=emp.resource_id,\n )[emp.resource_id.id]\n ]\n\n if is_work_available(slot['UTC'][0], slot['UTC'][1], workhours[emp_pos]):\n if emp_pos not in meetings:\n # note: no check is made on the attendee's status (accepted/declined/...)\n meetings[emp_pos] = self.env['calendar.event'].search([\n ('partner_ids.user_ids', '=', emp.user_id.id),\n ('start', '<', fields.Datetime.to_string(last_day.replace(hour=23, minute=59, second=59))),\n ('stop', '>', fields.Datetime.to_string(first_day.replace(hour=0, minute=0, second=0)))\n ])\n\n if is_calendar_available(slot, meetings[emp_pos], emp):\n slot['employee_id'] = emp\n break\n\n def _get_appointment_slots(self, timezone, employee=None):\n \"\"\" Fetch available slots to book an appointment\n :param timezone: timezone string e.g.: 'Europe/Brussels' or 'Etc/GMT+1'\n :param employee: if set will only check available slots for this employee\n :returns: list of dicts (1 per month) containing available slots per day per week.\n complex structure used to simplify rendering of template\n \"\"\"\n self.ensure_one()\n appt_tz = pytz.timezone(self.appointment_tz)\n requested_tz = pytz.timezone(timezone)\n first_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(hours=self.min_schedule_hours))\n last_day = requested_tz.fromutc(datetime.utcnow() + relativedelta(days=self.max_schedule_days))\n\n # Compute available slots (ordered)\n slots = self._slots_generate(first_day.astimezone(appt_tz), last_day.astimezone(appt_tz), timezone)\n if not employee or employee in self.employee_ids:\n self._slots_available(slots, first_day.astimezone(pytz.UTC), last_day.astimezone(pytz.UTC), employee)\n\n # Compute calendar rendering and inject available slots\n today = requested_tz.fromutc(datetime.utcnow())\n start = today\n month_dates_calendar = cal.Calendar(0).monthdatescalendar\n months = []\n while (start.year, start.month) <= (last_day.year, last_day.month):\n dates = month_dates_calendar(start.year, start.month)\n for week_index, week in enumerate(dates):\n for day_index, day in enumerate(week):\n mute_cls = weekend_cls = today_cls = None\n today_slots = []\n if day.weekday() in (cal.SUNDAY, cal.SATURDAY):\n weekend_cls = 'o_weekend'\n if day == today.date() and day.month == today.month:\n today_cls = 'o_today'\n if day.month != start.month:\n mute_cls = 'text-muted o_mute_day'\n else:\n # slots are ordered, so check all unprocessed slots from until > day\n while slots and (slots[0][timezone][0].date() <= day):\n if (slots[0][timezone][0].date() == day) and ('employee_id' in slots[0]):\n today_slots.append({\n 'employee_id': slots[0]['employee_id'].id,\n 'datetime': slots[0][timezone][0].strftime('%Y-%m-%d %H:%M:%S'),\n 'hours': slots[0][timezone][0].strftime('%H:%M')\n })\n slots.pop(0)\n dates[week_index][day_index] = {\n 'day': day,\n 'slots': today_slots,\n 'mute_cls': mute_cls,\n 'weekend_cls': weekend_cls,\n 'today_cls': today_cls\n }\n\n months.append({\n 'month': format_datetime(start, 'MMMM Y', locale=get_lang(self.env).code),\n 'weeks': dates\n })\n start = start + relativedelta(months=1)\n return months\n\n\nclass CalendarAppointmentSlot(models.Model):\n _name = \"calendar.appointment.slot\"\n _description = \"Online Appointment : Time Slot\"\n _rec_name = \"weekday\"\n _order = \"weekday, hour\"\n\n appointment_type_id = fields.Many2one('calendar.appointment.type', 'Appointment Type', ondelete='cascade')\n weekday = fields.Selection([\n ('1', 'Monday'),\n ('2', 'Tuesday'),\n ('3', 'Wednesday'),\n ('4', 'Thursday'),\n ('5', 'Friday'),\n ('6', 'Saturday'),\n ('7', 'Sunday'),\n ], string='Week Day', required=True)\n hour = fields.Float('Starting Hour', required=True, default=8.0)\n\n @api.constrains('hour')\n def check_hour(self):\n if any(slot.hour < 0.00 or slot.hour >= 24.00 for slot in self):\n raise ValidationError(_(\"Please enter a valid hour between 0:00 and 24:00 for your slots.\"))\n\n def name_get(self):\n weekdays = dict(self._fields['weekday'].selection)\n return self.mapped(lambda slot: (slot.id, \"%s, %02d:%02d\" % (weekdays.get(slot.weekday), int(slot.hour), int(round((slot.hour % 1) * 60)))))\n\n\nclass CalendarAppointmentQuestion(models.Model):\n _name = \"calendar.appointment.question\"\n _description = \"Online Appointment : Questions\"\n _order = \"sequence\"\n\n sequence = fields.Integer('Sequence')\n appointment_type_id = fields.Many2one('calendar.appointment.type', 'Appointment Type', ondelete=\"cascade\")\n name = fields.Char('Question', translate=True, required=True)\n placeholder = fields.Char('Placeholder', translate=True)\n question_required = fields.Boolean('Required Answer')\n question_type = fields.Selection([\n ('char', 'Single line text'),\n ('text', 'Multi-line text'),\n ('select', 'Dropdown (one answer)'),\n ('radio', 'Radio (one answer)'),\n ('checkbox', 'Checkboxes (multiple answers)')], 'Question Type', default='char')\n answer_ids = fields.Many2many('calendar.appointment.answer', 'calendar_appointment_question_answer_rel', 'question_id', 'answer_id', string='Available Answers')\n\n\nclass CalendarAppointmentAnswer(models.Model):\n _name = \"calendar.appointment.answer\"\n _description = \"Online Appointment : Answers\"\n\n question_id = fields.Many2many('calendar.appointment.question', 'calendar_appointment_question_answer_rel', 'answer_id', 'question_id', string='Questions')\n name = fields.Char('Answer', translate=True, required=True)\n",
"step-ids": [
7,
10,
12,
18,
19
]
}
|
[
7,
10,
12,
18,
19
] |
from os import read
from cryptography.fernet import Fernet
#create a key
# key = Fernet.generate_key()
#When every we run this code we will create a new key
# with open('mykey.key','wb') as mykey:
# mykey.write(key)
#To avoid create a new key and reuse the same key
with open('mykey.key','rb') as mykey:
key = mykey.read()
#print(key)
# f = Fernet(key)
# with open('Mailing Client/password.txt','rb') as original_file:
# original = original_file.read()
# #encrypt the data
# encrypted = f.encrypt(original)
# with open('encryptedpassword.txt','wb') as encrypted_password_file:
# encrypted_file = encrypted_password_file.write(encrypted)
#Decrypt Part
f = Fernet(key)
with open('encryptedpassword.txt','rb') as encrypted_password_file:
encrypte_file = encrypted_password_file.read()
decrypt = f.decrypt(encrypte_file)
with open('decryptedpassword.txt','wb') as decrypted_password_file:
decrypted_file = decrypted_password_file.write(decrypt)
|
normal
|
{
"blob_id": "df828344b81a40b7101adcc6759780ea84f2c6b4",
"index": 4698,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('mykey.key', 'rb') as mykey:\n key = mykey.read()\n<mask token>\nwith open('encryptedpassword.txt', 'rb') as encrypted_password_file:\n encrypte_file = encrypted_password_file.read()\n<mask token>\nwith open('decryptedpassword.txt', 'wb') as decrypted_password_file:\n decrypted_file = decrypted_password_file.write(decrypt)\n",
"step-3": "<mask token>\nwith open('mykey.key', 'rb') as mykey:\n key = mykey.read()\nf = Fernet(key)\nwith open('encryptedpassword.txt', 'rb') as encrypted_password_file:\n encrypte_file = encrypted_password_file.read()\ndecrypt = f.decrypt(encrypte_file)\nwith open('decryptedpassword.txt', 'wb') as decrypted_password_file:\n decrypted_file = decrypted_password_file.write(decrypt)\n",
"step-4": "from os import read\nfrom cryptography.fernet import Fernet\nwith open('mykey.key', 'rb') as mykey:\n key = mykey.read()\nf = Fernet(key)\nwith open('encryptedpassword.txt', 'rb') as encrypted_password_file:\n encrypte_file = encrypted_password_file.read()\ndecrypt = f.decrypt(encrypte_file)\nwith open('decryptedpassword.txt', 'wb') as decrypted_password_file:\n decrypted_file = decrypted_password_file.write(decrypt)\n",
"step-5": "from os import read\r\nfrom cryptography.fernet import Fernet\r\n #create a key\r\n# key = Fernet.generate_key()\r\n\r\n#When every we run this code we will create a new key \r\n# with open('mykey.key','wb') as mykey:\r\n# mykey.write(key)\r\n\r\n#To avoid create a new key and reuse the same key\r\n\r\nwith open('mykey.key','rb') as mykey:\r\n key = mykey.read()\r\n\r\n#print(key)\r\n\r\n# f = Fernet(key)\r\n\r\n# with open('Mailing Client/password.txt','rb') as original_file:\r\n# original = original_file.read()\r\n\r\n# #encrypt the data\r\n\r\n# encrypted = f.encrypt(original)\r\n\r\n# with open('encryptedpassword.txt','wb') as encrypted_password_file:\r\n# encrypted_file = encrypted_password_file.write(encrypted)\r\n\r\n#Decrypt Part\r\n\r\nf = Fernet(key)\r\n\r\nwith open('encryptedpassword.txt','rb') as encrypted_password_file:\r\n encrypte_file = encrypted_password_file.read()\r\n\r\ndecrypt = f.decrypt(encrypte_file)\r\n\r\nwith open('decryptedpassword.txt','wb') as decrypted_password_file:\r\n decrypted_file = decrypted_password_file.write(decrypt)\r\n\r\n\r\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
"""These are views that are used for viewing and editing characters."""
from django.contrib import messages
from django.contrib.auth.mixins import UserPassesTestMixin,\
LoginRequiredMixin, PermissionRequiredMixin
from django.db import transaction
from django.db.models import F
from django.http import HttpResponseRedirect
from django.template.loader import render_to_string
from django.urls import reverse, reverse_lazy
from django.views import View
from django.views.generic.edit import FormMixin, CreateView, UpdateView
from django.views.generic import DeleteView, DetailView, FormView, ListView
from rest_framework.status import HTTP_412_PRECONDITION_FAILED
from rest_framework.authentication import SessionAuthentication
from rest_framework.permissions import BasePermission
from rest_framework.response import Response
from rest_framework.views import APIView
from talesofvalor import get_query
from talesofvalor.events.models import Event
from talesofvalor.players.models import Registration
from talesofvalor.skills.models import Header, HeaderSkill
from .models import Character
from .forms import CharacterForm, CharacterSkillForm,\
CharacterConceptApproveForm, CharacterHistoryApproveForm
class OwnsCharacter(BasePermission):
"""
The current user is staff or owns the that is being manipulated.
"""
message = "You don't own this character"
def has_object_permission(self, request, view, obj):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
class CharacterCreateView(LoginRequiredMixin, CreateView):
model = Character
form_class = CharacterForm
def get_initial(self):
# Get the initial dictionary from the superclass method
initial = super(CharacterCreateView, self).get_initial()
# Copy the dictionary so we don't accidentally change a mutable dict
initial = initial.copy()
# default to getting the player from the query String.
try:
initial['player'] = self.request.GET['player']
except KeyError:
initial['player'] = self.request.user.player
# etc...
return initial
def get_form_kwargs(self):
kwargs = super().get_form_kwargs()
kwargs['user'] = self.request.user # pass the 'user' in kwargs
return kwargs
def get_success_url(self):
return reverse(
'characters:character_skill_update',
kwargs={'pk': self.object.pk}
)
def form_valid(self, form):
"""
If this form is valid, then add the current player to the character
if the current user is not an admin
If the user doesn't have any other active characters, set this one
to active.
"""
if not self.request.user.has_perm('players.view_any_player'):
form.instance.player = self.request.user.player
if not form.instance.player.character_set.filter(active_flag=True).exists():
form.instance.active_flag = True
messages.info(self.request, 'New Character, "{}" created.'.format(
form.instance.name
))
return super().form_valid(form)
class CharacterUpdateView(LoginRequiredMixin, UserPassesTestMixin, UpdateView):
model = Character
form_class = CharacterForm
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
def get_form_kwargs(self):
kwargs = super().get_form_kwargs()
kwargs['user'] = self.request.user # pass the 'user' in kwargs
return kwargs
def get_success_url(self):
return reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
)
class CharacterDeleteView(
PermissionRequiredMixin,
UserPassesTestMixin,
DeleteView
):
"""
Removes a character permanantly.
Removing a character may have strange effects on other views.
"""
model = Character
permission_required = ('characters.change_character', )
success_url = reverse_lazy('characters:character_list')
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
class CharacterResetView(
PermissionRequiredMixin,
UserPassesTestMixin,
View
):
"""
Resets a characters skills to none and returns their points to them.
"""
model = Character
permission_required = ('characters.change_character', )
success_url = reverse_lazy('characters:character_list')
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
def get(self, request, *args, **kwargs):
"""
Send the user back to the the originating page or back to the
character they are setting active
"""
with transaction.atomic():
character = self.model.objects.get(pk=self.kwargs['pk'])
character.cp_available += character.cp_spent
character.cp_spent = 0
character.save(update_fields=['cp_available', 'cp_spent'])
character.characterskills_set.all().delete()
character.headers.clear()
messages.info(self.request, 'Character skills reset for {}.'.format(
character.name
))
return HttpResponseRedirect(
self.request.META.get(
'HTTP_REFERER',
reverse(
'characters:character_detail',
kwargs={'pk': self.kwargs['pk']}
)
)
)
class CharacterSetActiveView(
LoginRequiredMixin,
UserPassesTestMixin,
View
):
"""
Set the active character for the characters player to the sent id.
"""
model = Character
fields = '__all__'
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
def get(self, request, *args, **kwargs):
"""
Send the user back to the the originating page or back to the
character they are setting active
"""
character = self.model.objects.get(pk=self.kwargs['pk'])
character.player.character_set.update(active_flag=False)
character.active_flag = True
character.save()
messages.info(self.request, 'Active Character changed to {}.'.format(
character.name
))
return HttpResponseRedirect(
self.request.META.get(
'HTTP_REFERER',
reverse(
'characters:character_detail',
kwargs={'pk': self.kwargs['pk']}
)
)
)
class CharacterSkillUpdateView(
LoginRequiredMixin,
UserPassesTestMixin,
FormMixin,
DetailView):
"""
Allow a user to update their chosen skills
"""
template_name = 'characters/character_skill_form.html'
form_class = CharacterSkillForm
model = Character
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
def get_success_url(self):
return reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
)
def get_form_kwargs(self):
kwargs = super().get_form_kwargs()
self.skills = Header.objects\
.order_by('hidden_flag', 'category', 'name')\
.all()
kwargs.update({'skills': self.skills})
return kwargs
def get_context_data(self, **kwargs):
context = super().get_context_data(**self.kwargs)
# remove skills not in the hash.
available_skills = self.object.skillhash.keys()
context['skills'] = filter(lambda x: x.id in available_skills or self.request.user.has_perm('player.view_any_player'), self.skills)
context['skill_hash'] = self.object.skillhash
# add the bare skills granted by the rules
context['granted_skills'] = self.object.skill_grants
return context
def post(self, request, *args, **kwargs):
self.object = self.get_object()
form = self.get_form()
if form.is_valid():
return self.form_valid(form)
else:
return self.form_invalid(form)
def form_valid(self, form):
"""
Form is valid. Save the skills to that character and remove the
appropriate number of characters points.
"""
return super().form_valid(form)
class ResetPointsView(
PermissionRequiredMixin,
View
):
"""
Resets the points for the season.
"""
permission_required = ('characters.reset_points', )
def get(self, request, *args, **kwargs):
"""
Send the user back to the the originating page or back to the main
page if the referrer isn't set.
"""
Character.objects.all().update(cp_transferred=0)
messages.info(self.request, 'Point cap reset!')
return HttpResponseRedirect(
self.request.META.get(
'HTTP_REFERER',
'/'
)
)
'''
Put the AJAX work for Characters here
'''
class CharacterAddHeaderView(APIView):
'''
Set of AJAX views for a Characters
This handles different API calls for character actions.
'''
authentication_classes = [SessionAuthentication]
permission_classes = [OwnsCharacter]
def post(self, request, format=None):
header_id = int(request.POST.get('header_id', 0))
character_id = int(request.POST.get('character_id', 0))
cp_available = int(request.POST.get('cp_available', 0))
# get the character and then see if the header is allowed
header = Header.objects.get(pk=header_id)
character = Character.objects.get(pk=character_id)
# Default to error.
content = {
'error': "prerequisites not met"
}
status = None
# if the prerequisites are met, add the header to the user and return
# the list of skills
if character.check_header_prerequisites(header):
# see if the character has enough points to add the header
if (cp_available - header.cost) >= 0:
character.cp_available -= header.cost
character.cp_spent += header.cost
character.headers.add(header)
character.save()
skill_item_template_string = render_to_string(
"characters/includes/character_skill_update_item.html",
{
'header': header,
'header_skills': header.skills.all(),
'header_costs': character.skillhash[header.id]
},
request
)
content = {
'success': header.cost * -1,
'skills': skill_item_template_string
}
else:
content = {
'error': "You don't have enough points available for this character to add this header."
}
status = HTTP_412_PRECONDITION_FAILED
else:
status = HTTP_412_PRECONDITION_FAILED
return Response(content, status)
class CharacterDropHeaderView(APIView):
'''
Set of AJAX views for a Characters
This handles different API calls for character actions.
'''
authentication_classes = [SessionAuthentication]
permission_classes = [OwnsCharacter]
def post(self, request, format=None):
header_id = int(request.POST.get('header_id', 0))
character_id = int(request.POST.get('character_id', 0))
# get the character and header
header = Header.objects.get(pk=header_id)
character = Character.objects.get(pk=character_id)
# Default to error.
content = {
'error': "Header is not already bought!"
}
status = None
# if the character has the header, drop it and refund the CP
content['header_list'] = []
if header in character.headers.all():
print(f'Header present! Dropping and adding back in {header.cost} CP...')
character.cp_available += header.cost
character.cp_spent -= header.cost
character.headers.remove(header)
skill_item_template_string = render_to_string(
"characters/includes/character_skill_update_item.html",
{
'header': header,
'header_skills': header.skills.all(),
'header_costs': character.skillhash[header.id]
},
request
)
content = {
'success': header.cost,
}
else:
status = HTTP_412_PRECONDITION_FAILED
return Response(content, status)
class CharacterAddSkillView(APIView):
'''
Set of AJAX views for a Characters
This handles different API calls for character actions.
'''
authentication_classes = [SessionAuthentication]
permission_classes = [OwnsCharacter]
def post(self, request, format=None):
skill_id = int(request.POST.get('skill_id', 0))
header_id = int(request.POST.get('header_id', 0))
character_id = int(request.POST.get('character_id', 0))
cp_available = int(request.POST.get('cp_available', 0))
try:
vector = int(request.POST.get('vector'))
except AttributeError:
return {
'error': "No change indicated"
}
# get the character and then see if the skill is allowed
header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id=header_id)
character = Character.objects.get(pk=character_id)
# check that the skill is allowed.
# if the prerequisites are met, add the header to the user and return
# the list of skills
# otherwise, return an error
content = {
'success': "testing right now"
}
status = None
if character.check_skill_prerequisites(header_skill.skill, header_skill.header):
# since vector is the direction, we want to reverse it when
# dealing with what we want to change for the available points
# see if the character has enough points to add the header
cost = character.skill_cost(header_skill) * vector
if (cp_available - cost) >= 0:
# when this is returned, change the available costs
(character_skill, created) = character.characterskills_set.get_or_create(
skill=header_skill
)
if character_skill.count and (character_skill.count + vector < 0):
content = {
'error': f"You don't have any points in {header_skill.skill}"
}
status = HTTP_412_PRECONDITION_FAILED
else:
content = {
'success': cost * -1
}
character_skill.count = F('count') + vector
character_skill.save()
character.cp_spent = F('cp_spent') + cost
character.cp_available = F('cp_available') - cost
character.save()
else:
content = {
'error': "You don't have enough points available to purchase this skill . . ."
}
status = HTTP_412_PRECONDITION_FAILED
else:
status = HTTP_412_PRECONDITION_FAILED
return Response(content, status)
class CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):
"""
Show the details for a character.
From here you can edit the details of a character or choose skills.
"""
model = Character
fields = '__all__'
def test_func(self):
if self.request.user.has_perm('players.view_any_player'):
return True
try:
player = Character.objects.get(pk=self.kwargs['pk']).player
return (player.user == self.request.user)
except Character.DoesNotExist:
return False
return False
class CharacterConceptApproveView(PermissionRequiredMixin, FormView):
"""
Approve the concept for a character.
Grant the CP for the character
Set the history approved flag.
"""
permission_required = 'players.change_any_player'
form_class = CharacterConceptApproveForm
def form_valid(self, form):
self.object = Character.objects.get(pk=form.cleaned_data['character_id'])
self.object.player.cp_available += 3
self.object.player.save(update_fields=['cp_available'])
self.object.concept_approved_flag = True
self.object.save(update_fields=['concept_approved_flag'])
messages.info(self.request, f"{self.object} concept approved!")
return super().form_valid(form)
def form_invalid(self, form):
self.object = Character.objects.get(pk=form.cleaned_data['character_id'])
for key, error in form.errors.items():
messages.error(self.request, error.as_text())
return HttpResponseRedirect(reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
))
def get_success_url(self):
return reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
)
class CharacterHistoryApproveView(PermissionRequiredMixin, FormView):
"""
Approve the history for a character.
Grant the CP for the character
Set the history approved flag.
"""
permission_required = 'players.change_any_player'
form_class = CharacterHistoryApproveForm
def form_valid(self, form):
self.object = Character.objects.get(pk=form.cleaned_data['character_id'])
self.object.player.cp_available += 3
self.object.player.save(update_fields=['cp_available'])
self.object.history_approved_flag = True
self.object.save(update_fields=['history_approved_flag'])
messages.info(self.request, f"{self.object} history approved!")
return super().form_valid(form)
def form_invalid(self, form):
self.object = Character.objects.get(pk=form.cleaned_data['character_id'])
for key, error in form.errors.items():
messages.error(self.request, error.as_text())
return HttpResponseRedirect(reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
))
def get_success_url(self):
return reverse(
'characters:character_detail',
kwargs={'pk': self.object.pk}
)
class CharacterListView(LoginRequiredMixin, ListView):
"""
Show the list of characters.
From here, you can view, edit, delete a character.
"""
model = Character
paginate_by = 25
def get_queryset(self):
queryset = super().get_queryset()
criteria = self.request.GET.get('criteria', '')
if (criteria.strip()):
entry_query = get_query(
criteria,
['name', 'description', 'concept', 'history', 'player_notes']
)
queryset = queryset.filter(entry_query)
history_approved_flag = self.request.GET.get('history_approved_flag', False)
if history_approved_flag:
queryset = queryset.filter(history_approved_flag=True)
concept_approved_flag = self.request.GET.get('concept_approved_flag', False)
if concept_approved_flag:
queryset = queryset.filter(concept_approved_flag=True)
return queryset
def get_context_data(self, **kwargs):
'''
Add the form so we can filter the characters.
'''
# get the context data to add to.
context_data = super().get_context_data(**kwargs)
context_data.update(**self.request.GET)
# return the resulting context
return context_data
class CharacterPrintListView(LoginRequiredMixin, ListView):
"""
Show a list of characters to print.
"""
model = Character
template_name = "characters/character_print_list.html"
def get_queryset(self):
queryset = super().get_queryset() # filter by event
event_id = self.kwargs.get('event_id', None)
if not event_id:
event_id = Event.next_event().id
player_ids = Registration.objects.filter(event__id=event_id).values_list('player_id', flat=True)
queryset = queryset.filter(player__id__in=player_ids, npc_flag=False, active_flag=True)
return queryset
|
normal
|
{
"blob_id": "55ea522b096b189ff67b0da0058af777b0a910e3",
"index": 4970,
"step-1": "<mask token>\n\n\nclass CharacterDropHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'Header is not already bought!'}\n status = None\n content['header_list'] = []\n if header in character.headers.all():\n print(\n f'Header present! Dropping and adding back in {header.cost} CP...'\n )\n character.cp_available += header.cost\n character.cp_spent -= header.cost\n character.headers.remove(header)\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html', {\n 'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost}\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterAddSkillView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n skill_id = int(request.POST.get('skill_id', 0))\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n try:\n vector = int(request.POST.get('vector'))\n except AttributeError:\n return {'error': 'No change indicated'}\n header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id\n =header_id)\n character = Character.objects.get(pk=character_id)\n content = {'success': 'testing right now'}\n status = None\n if character.check_skill_prerequisites(header_skill.skill,\n header_skill.header):\n cost = character.skill_cost(header_skill) * vector\n if cp_available - cost >= 0:\n character_skill, created = (character.characterskills_set.\n get_or_create(skill=header_skill))\n if (character_skill.count and character_skill.count +\n vector < 0):\n content = {'error':\n f\"You don't have any points in {header_skill.skill}\"}\n status = HTTP_412_PRECONDITION_FAILED\n else:\n content = {'success': cost * -1}\n character_skill.count = F('count') + vector\n character_skill.save()\n character.cp_spent = F('cp_spent') + cost\n character.cp_available = F('cp_available') - cost\n character.save()\n else:\n content = {'error':\n \"You don't have enough points available to purchase this skill . . .\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):\n \"\"\"\n Show the details for a character.\n\n From here you can edit the details of a character or choose skills.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterConceptApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the concept for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterConceptApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.concept_approved_flag = True\n self.object.save(update_fields=['concept_approved_flag'])\n messages.info(self.request, f'{self.object} concept approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterHistoryApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the history for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterHistoryApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.history_approved_flag = True\n self.object.save(update_fields=['history_approved_flag'])\n messages.info(self.request, f'{self.object} history approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show the list of characters.\n\n From here, you can view, edit, delete a character.\n \"\"\"\n model = Character\n paginate_by = 25\n\n def get_queryset(self):\n queryset = super().get_queryset()\n criteria = self.request.GET.get('criteria', '')\n if criteria.strip():\n entry_query = get_query(criteria, ['name', 'description',\n 'concept', 'history', 'player_notes'])\n queryset = queryset.filter(entry_query)\n history_approved_flag = self.request.GET.get('history_approved_flag',\n False)\n if history_approved_flag:\n queryset = queryset.filter(history_approved_flag=True)\n concept_approved_flag = self.request.GET.get('concept_approved_flag',\n False)\n if concept_approved_flag:\n queryset = queryset.filter(concept_approved_flag=True)\n return queryset\n\n def get_context_data(self, **kwargs):\n \"\"\"\n Add the form so we can filter the characters.\n \"\"\"\n context_data = super().get_context_data(**kwargs)\n context_data.update(**self.request.GET)\n return context_data\n\n\nclass CharacterPrintListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show a list of characters to print.\n\n \"\"\"\n model = Character\n template_name = 'characters/character_print_list.html'\n\n def get_queryset(self):\n queryset = super().get_queryset()\n event_id = self.kwargs.get('event_id', None)\n if not event_id:\n event_id = Event.next_event().id\n player_ids = Registration.objects.filter(event__id=event_id\n ).values_list('player_id', flat=True)\n queryset = queryset.filter(player__id__in=player_ids, npc_flag=\n False, active_flag=True)\n return queryset\n",
"step-2": "<mask token>\n\n\nclass CharacterSkillUpdateView(LoginRequiredMixin, UserPassesTestMixin,\n FormMixin, DetailView):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n self.skills = Header.objects.order_by('hidden_flag', 'category', 'name'\n ).all()\n kwargs.update({'skills': self.skills})\n return kwargs\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**self.kwargs)\n available_skills = self.object.skillhash.keys()\n context['skills'] = filter(lambda x: x.id in available_skills or\n self.request.user.has_perm('player.view_any_player'), self.skills)\n context['skill_hash'] = self.object.skillhash\n context['granted_skills'] = self.object.skill_grants\n return context\n\n def post(self, request, *args, **kwargs):\n self.object = self.get_object()\n form = self.get_form()\n if form.is_valid():\n return self.form_valid(form)\n else:\n return self.form_invalid(form)\n\n def form_valid(self, form):\n \"\"\"\n Form is valid. Save the skills to that character and remove the\n appropriate number of characters points.\n \"\"\"\n return super().form_valid(form)\n\n\nclass ResetPointsView(PermissionRequiredMixin, View):\n \"\"\"\n Resets the points for the season.\n \"\"\"\n permission_required = 'characters.reset_points',\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the main \n page if the referrer isn't set.\n \"\"\"\n Character.objects.all().update(cp_transferred=0)\n messages.info(self.request, 'Point cap reset!')\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER', '/'))\n\n\n<mask token>\n\n\nclass CharacterAddHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'prerequisites not met'}\n status = None\n if character.check_header_prerequisites(header):\n if cp_available - header.cost >= 0:\n character.cp_available -= header.cost\n character.cp_spent += header.cost\n character.headers.add(header)\n character.save()\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html',\n {'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost * -1, 'skills':\n skill_item_template_string}\n else:\n content = {'error':\n \"You don't have enough points available for this character to add this header.\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDropHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'Header is not already bought!'}\n status = None\n content['header_list'] = []\n if header in character.headers.all():\n print(\n f'Header present! Dropping and adding back in {header.cost} CP...'\n )\n character.cp_available += header.cost\n character.cp_spent -= header.cost\n character.headers.remove(header)\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html', {\n 'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost}\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterAddSkillView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n skill_id = int(request.POST.get('skill_id', 0))\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n try:\n vector = int(request.POST.get('vector'))\n except AttributeError:\n return {'error': 'No change indicated'}\n header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id\n =header_id)\n character = Character.objects.get(pk=character_id)\n content = {'success': 'testing right now'}\n status = None\n if character.check_skill_prerequisites(header_skill.skill,\n header_skill.header):\n cost = character.skill_cost(header_skill) * vector\n if cp_available - cost >= 0:\n character_skill, created = (character.characterskills_set.\n get_or_create(skill=header_skill))\n if (character_skill.count and character_skill.count +\n vector < 0):\n content = {'error':\n f\"You don't have any points in {header_skill.skill}\"}\n status = HTTP_412_PRECONDITION_FAILED\n else:\n content = {'success': cost * -1}\n character_skill.count = F('count') + vector\n character_skill.save()\n character.cp_spent = F('cp_spent') + cost\n character.cp_available = F('cp_available') - cost\n character.save()\n else:\n content = {'error':\n \"You don't have enough points available to purchase this skill . . .\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):\n \"\"\"\n Show the details for a character.\n\n From here you can edit the details of a character or choose skills.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterConceptApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the concept for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterConceptApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.concept_approved_flag = True\n self.object.save(update_fields=['concept_approved_flag'])\n messages.info(self.request, f'{self.object} concept approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterHistoryApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the history for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterHistoryApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.history_approved_flag = True\n self.object.save(update_fields=['history_approved_flag'])\n messages.info(self.request, f'{self.object} history approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show the list of characters.\n\n From here, you can view, edit, delete a character.\n \"\"\"\n model = Character\n paginate_by = 25\n\n def get_queryset(self):\n queryset = super().get_queryset()\n criteria = self.request.GET.get('criteria', '')\n if criteria.strip():\n entry_query = get_query(criteria, ['name', 'description',\n 'concept', 'history', 'player_notes'])\n queryset = queryset.filter(entry_query)\n history_approved_flag = self.request.GET.get('history_approved_flag',\n False)\n if history_approved_flag:\n queryset = queryset.filter(history_approved_flag=True)\n concept_approved_flag = self.request.GET.get('concept_approved_flag',\n False)\n if concept_approved_flag:\n queryset = queryset.filter(concept_approved_flag=True)\n return queryset\n\n def get_context_data(self, **kwargs):\n \"\"\"\n Add the form so we can filter the characters.\n \"\"\"\n context_data = super().get_context_data(**kwargs)\n context_data.update(**self.request.GET)\n return context_data\n\n\nclass CharacterPrintListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show a list of characters to print.\n\n \"\"\"\n model = Character\n template_name = 'characters/character_print_list.html'\n\n def get_queryset(self):\n queryset = super().get_queryset()\n event_id = self.kwargs.get('event_id', None)\n if not event_id:\n event_id = Event.next_event().id\n player_ids = Registration.objects.filter(event__id=event_id\n ).values_list('player_id', flat=True)\n queryset = queryset.filter(player__id__in=player_ids, npc_flag=\n False, active_flag=True)\n return queryset\n",
"step-3": "<mask token>\n\n\nclass CharacterResetView(PermissionRequiredMixin, UserPassesTestMixin, View):\n <mask token>\n model = Character\n permission_required = 'characters.change_character',\n success_url = reverse_lazy('characters:character_list')\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n with transaction.atomic():\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.cp_available += character.cp_spent\n character.cp_spent = 0\n character.save(update_fields=['cp_available', 'cp_spent'])\n character.characterskills_set.all().delete()\n character.headers.clear()\n messages.info(self.request, 'Character skills reset for {}.'.format\n (character.name))\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER',\n reverse('characters:character_detail', kwargs={'pk': self.\n kwargs['pk']})))\n\n\nclass CharacterSetActiveView(LoginRequiredMixin, UserPassesTestMixin, View):\n \"\"\"\n Set the active character for the characters player to the sent id.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.player.character_set.update(active_flag=False)\n character.active_flag = True\n character.save()\n messages.info(self.request, 'Active Character changed to {}.'.\n format(character.name))\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER',\n reverse('characters:character_detail', kwargs={'pk': self.\n kwargs['pk']})))\n\n\nclass CharacterSkillUpdateView(LoginRequiredMixin, UserPassesTestMixin,\n FormMixin, DetailView):\n \"\"\"\n Allow a user to update their chosen skills\n \"\"\"\n template_name = 'characters/character_skill_form.html'\n form_class = CharacterSkillForm\n model = Character\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n self.skills = Header.objects.order_by('hidden_flag', 'category', 'name'\n ).all()\n kwargs.update({'skills': self.skills})\n return kwargs\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**self.kwargs)\n available_skills = self.object.skillhash.keys()\n context['skills'] = filter(lambda x: x.id in available_skills or\n self.request.user.has_perm('player.view_any_player'), self.skills)\n context['skill_hash'] = self.object.skillhash\n context['granted_skills'] = self.object.skill_grants\n return context\n\n def post(self, request, *args, **kwargs):\n self.object = self.get_object()\n form = self.get_form()\n if form.is_valid():\n return self.form_valid(form)\n else:\n return self.form_invalid(form)\n\n def form_valid(self, form):\n \"\"\"\n Form is valid. Save the skills to that character and remove the\n appropriate number of characters points.\n \"\"\"\n return super().form_valid(form)\n\n\nclass ResetPointsView(PermissionRequiredMixin, View):\n \"\"\"\n Resets the points for the season.\n \"\"\"\n permission_required = 'characters.reset_points',\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the main \n page if the referrer isn't set.\n \"\"\"\n Character.objects.all().update(cp_transferred=0)\n messages.info(self.request, 'Point cap reset!')\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER', '/'))\n\n\n<mask token>\n\n\nclass CharacterAddHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'prerequisites not met'}\n status = None\n if character.check_header_prerequisites(header):\n if cp_available - header.cost >= 0:\n character.cp_available -= header.cost\n character.cp_spent += header.cost\n character.headers.add(header)\n character.save()\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html',\n {'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost * -1, 'skills':\n skill_item_template_string}\n else:\n content = {'error':\n \"You don't have enough points available for this character to add this header.\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDropHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'Header is not already bought!'}\n status = None\n content['header_list'] = []\n if header in character.headers.all():\n print(\n f'Header present! Dropping and adding back in {header.cost} CP...'\n )\n character.cp_available += header.cost\n character.cp_spent -= header.cost\n character.headers.remove(header)\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html', {\n 'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost}\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterAddSkillView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n skill_id = int(request.POST.get('skill_id', 0))\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n try:\n vector = int(request.POST.get('vector'))\n except AttributeError:\n return {'error': 'No change indicated'}\n header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id\n =header_id)\n character = Character.objects.get(pk=character_id)\n content = {'success': 'testing right now'}\n status = None\n if character.check_skill_prerequisites(header_skill.skill,\n header_skill.header):\n cost = character.skill_cost(header_skill) * vector\n if cp_available - cost >= 0:\n character_skill, created = (character.characterskills_set.\n get_or_create(skill=header_skill))\n if (character_skill.count and character_skill.count +\n vector < 0):\n content = {'error':\n f\"You don't have any points in {header_skill.skill}\"}\n status = HTTP_412_PRECONDITION_FAILED\n else:\n content = {'success': cost * -1}\n character_skill.count = F('count') + vector\n character_skill.save()\n character.cp_spent = F('cp_spent') + cost\n character.cp_available = F('cp_available') - cost\n character.save()\n else:\n content = {'error':\n \"You don't have enough points available to purchase this skill . . .\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):\n \"\"\"\n Show the details for a character.\n\n From here you can edit the details of a character or choose skills.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterConceptApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the concept for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterConceptApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.concept_approved_flag = True\n self.object.save(update_fields=['concept_approved_flag'])\n messages.info(self.request, f'{self.object} concept approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterHistoryApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the history for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterHistoryApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.history_approved_flag = True\n self.object.save(update_fields=['history_approved_flag'])\n messages.info(self.request, f'{self.object} history approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show the list of characters.\n\n From here, you can view, edit, delete a character.\n \"\"\"\n model = Character\n paginate_by = 25\n\n def get_queryset(self):\n queryset = super().get_queryset()\n criteria = self.request.GET.get('criteria', '')\n if criteria.strip():\n entry_query = get_query(criteria, ['name', 'description',\n 'concept', 'history', 'player_notes'])\n queryset = queryset.filter(entry_query)\n history_approved_flag = self.request.GET.get('history_approved_flag',\n False)\n if history_approved_flag:\n queryset = queryset.filter(history_approved_flag=True)\n concept_approved_flag = self.request.GET.get('concept_approved_flag',\n False)\n if concept_approved_flag:\n queryset = queryset.filter(concept_approved_flag=True)\n return queryset\n\n def get_context_data(self, **kwargs):\n \"\"\"\n Add the form so we can filter the characters.\n \"\"\"\n context_data = super().get_context_data(**kwargs)\n context_data.update(**self.request.GET)\n return context_data\n\n\nclass CharacterPrintListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show a list of characters to print.\n\n \"\"\"\n model = Character\n template_name = 'characters/character_print_list.html'\n\n def get_queryset(self):\n queryset = super().get_queryset()\n event_id = self.kwargs.get('event_id', None)\n if not event_id:\n event_id = Event.next_event().id\n player_ids = Registration.objects.filter(event__id=event_id\n ).values_list('player_id', flat=True)\n queryset = queryset.filter(player__id__in=player_ids, npc_flag=\n False, active_flag=True)\n return queryset\n",
"step-4": "<mask token>\n\n\nclass CharacterUpdateView(LoginRequiredMixin, UserPassesTestMixin, UpdateView):\n <mask token>\n <mask token>\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n kwargs['user'] = self.request.user\n return kwargs\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterDeleteView(PermissionRequiredMixin, UserPassesTestMixin,\n DeleteView):\n \"\"\"\n Removes a character permanantly.\n\n Removing a character may have strange effects on other views.\n \"\"\"\n model = Character\n permission_required = 'characters.change_character',\n success_url = reverse_lazy('characters:character_list')\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterResetView(PermissionRequiredMixin, UserPassesTestMixin, View):\n \"\"\"\n Resets a characters skills to none and returns their points to them.\n \"\"\"\n model = Character\n permission_required = 'characters.change_character',\n success_url = reverse_lazy('characters:character_list')\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n with transaction.atomic():\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.cp_available += character.cp_spent\n character.cp_spent = 0\n character.save(update_fields=['cp_available', 'cp_spent'])\n character.characterskills_set.all().delete()\n character.headers.clear()\n messages.info(self.request, 'Character skills reset for {}.'.format\n (character.name))\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER',\n reverse('characters:character_detail', kwargs={'pk': self.\n kwargs['pk']})))\n\n\nclass CharacterSetActiveView(LoginRequiredMixin, UserPassesTestMixin, View):\n \"\"\"\n Set the active character for the characters player to the sent id.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.player.character_set.update(active_flag=False)\n character.active_flag = True\n character.save()\n messages.info(self.request, 'Active Character changed to {}.'.\n format(character.name))\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER',\n reverse('characters:character_detail', kwargs={'pk': self.\n kwargs['pk']})))\n\n\nclass CharacterSkillUpdateView(LoginRequiredMixin, UserPassesTestMixin,\n FormMixin, DetailView):\n \"\"\"\n Allow a user to update their chosen skills\n \"\"\"\n template_name = 'characters/character_skill_form.html'\n form_class = CharacterSkillForm\n model = Character\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n self.skills = Header.objects.order_by('hidden_flag', 'category', 'name'\n ).all()\n kwargs.update({'skills': self.skills})\n return kwargs\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**self.kwargs)\n available_skills = self.object.skillhash.keys()\n context['skills'] = filter(lambda x: x.id in available_skills or\n self.request.user.has_perm('player.view_any_player'), self.skills)\n context['skill_hash'] = self.object.skillhash\n context['granted_skills'] = self.object.skill_grants\n return context\n\n def post(self, request, *args, **kwargs):\n self.object = self.get_object()\n form = self.get_form()\n if form.is_valid():\n return self.form_valid(form)\n else:\n return self.form_invalid(form)\n\n def form_valid(self, form):\n \"\"\"\n Form is valid. Save the skills to that character and remove the\n appropriate number of characters points.\n \"\"\"\n return super().form_valid(form)\n\n\nclass ResetPointsView(PermissionRequiredMixin, View):\n \"\"\"\n Resets the points for the season.\n \"\"\"\n permission_required = 'characters.reset_points',\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the main \n page if the referrer isn't set.\n \"\"\"\n Character.objects.all().update(cp_transferred=0)\n messages.info(self.request, 'Point cap reset!')\n return HttpResponseRedirect(self.request.META.get('HTTP_REFERER', '/'))\n\n\n<mask token>\n\n\nclass CharacterAddHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'prerequisites not met'}\n status = None\n if character.check_header_prerequisites(header):\n if cp_available - header.cost >= 0:\n character.cp_available -= header.cost\n character.cp_spent += header.cost\n character.headers.add(header)\n character.save()\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html',\n {'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost * -1, 'skills':\n skill_item_template_string}\n else:\n content = {'error':\n \"You don't have enough points available for this character to add this header.\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDropHeaderView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n content = {'error': 'Header is not already bought!'}\n status = None\n content['header_list'] = []\n if header in character.headers.all():\n print(\n f'Header present! Dropping and adding back in {header.cost} CP...'\n )\n character.cp_available += header.cost\n character.cp_spent -= header.cost\n character.headers.remove(header)\n skill_item_template_string = render_to_string(\n 'characters/includes/character_skill_update_item.html', {\n 'header': header, 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]}, request)\n content = {'success': header.cost}\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterAddSkillView(APIView):\n \"\"\"\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n \"\"\"\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n skill_id = int(request.POST.get('skill_id', 0))\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n try:\n vector = int(request.POST.get('vector'))\n except AttributeError:\n return {'error': 'No change indicated'}\n header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id\n =header_id)\n character = Character.objects.get(pk=character_id)\n content = {'success': 'testing right now'}\n status = None\n if character.check_skill_prerequisites(header_skill.skill,\n header_skill.header):\n cost = character.skill_cost(header_skill) * vector\n if cp_available - cost >= 0:\n character_skill, created = (character.characterskills_set.\n get_or_create(skill=header_skill))\n if (character_skill.count and character_skill.count +\n vector < 0):\n content = {'error':\n f\"You don't have any points in {header_skill.skill}\"}\n status = HTTP_412_PRECONDITION_FAILED\n else:\n content = {'success': cost * -1}\n character_skill.count = F('count') + vector\n character_skill.save()\n character.cp_spent = F('cp_spent') + cost\n character.cp_available = F('cp_available') - cost\n character.save()\n else:\n content = {'error':\n \"You don't have enough points available to purchase this skill . . .\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):\n \"\"\"\n Show the details for a character.\n\n From here you can edit the details of a character or choose skills.\n \"\"\"\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return player.user == self.request.user\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterConceptApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the concept for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterConceptApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.concept_approved_flag = True\n self.object.save(update_fields=['concept_approved_flag'])\n messages.info(self.request, f'{self.object} concept approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterHistoryApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the history for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterHistoryApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.history_approved_flag = True\n self.object.save(update_fields=['history_approved_flag'])\n messages.info(self.request, f'{self.object} history approved!')\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data[\n 'character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse('characters:character_detail',\n kwargs={'pk': self.object.pk}))\n\n def get_success_url(self):\n return reverse('characters:character_detail', kwargs={'pk': self.\n object.pk})\n\n\nclass CharacterListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show the list of characters.\n\n From here, you can view, edit, delete a character.\n \"\"\"\n model = Character\n paginate_by = 25\n\n def get_queryset(self):\n queryset = super().get_queryset()\n criteria = self.request.GET.get('criteria', '')\n if criteria.strip():\n entry_query = get_query(criteria, ['name', 'description',\n 'concept', 'history', 'player_notes'])\n queryset = queryset.filter(entry_query)\n history_approved_flag = self.request.GET.get('history_approved_flag',\n False)\n if history_approved_flag:\n queryset = queryset.filter(history_approved_flag=True)\n concept_approved_flag = self.request.GET.get('concept_approved_flag',\n False)\n if concept_approved_flag:\n queryset = queryset.filter(concept_approved_flag=True)\n return queryset\n\n def get_context_data(self, **kwargs):\n \"\"\"\n Add the form so we can filter the characters.\n \"\"\"\n context_data = super().get_context_data(**kwargs)\n context_data.update(**self.request.GET)\n return context_data\n\n\nclass CharacterPrintListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show a list of characters to print.\n\n \"\"\"\n model = Character\n template_name = 'characters/character_print_list.html'\n\n def get_queryset(self):\n queryset = super().get_queryset()\n event_id = self.kwargs.get('event_id', None)\n if not event_id:\n event_id = Event.next_event().id\n player_ids = Registration.objects.filter(event__id=event_id\n ).values_list('player_id', flat=True)\n queryset = queryset.filter(player__id__in=player_ids, npc_flag=\n False, active_flag=True)\n return queryset\n",
"step-5": "\"\"\"These are views that are used for viewing and editing characters.\"\"\"\n\nfrom django.contrib import messages\nfrom django.contrib.auth.mixins import UserPassesTestMixin,\\\n LoginRequiredMixin, PermissionRequiredMixin\nfrom django.db import transaction\nfrom django.db.models import F\nfrom django.http import HttpResponseRedirect\nfrom django.template.loader import render_to_string\nfrom django.urls import reverse, reverse_lazy\nfrom django.views import View\nfrom django.views.generic.edit import FormMixin, CreateView, UpdateView\nfrom django.views.generic import DeleteView, DetailView, FormView, ListView\n\nfrom rest_framework.status import HTTP_412_PRECONDITION_FAILED\nfrom rest_framework.authentication import SessionAuthentication\nfrom rest_framework.permissions import BasePermission\nfrom rest_framework.response import Response\nfrom rest_framework.views import APIView\n\n\nfrom talesofvalor import get_query\nfrom talesofvalor.events.models import Event\nfrom talesofvalor.players.models import Registration\nfrom talesofvalor.skills.models import Header, HeaderSkill\n\nfrom .models import Character\nfrom .forms import CharacterForm, CharacterSkillForm,\\\n CharacterConceptApproveForm, CharacterHistoryApproveForm\n\n\nclass OwnsCharacter(BasePermission):\n \"\"\"\n The current user is staff or owns the that is being manipulated.\n \"\"\"\n message = \"You don't own this character\"\n\n def has_object_permission(self, request, view, obj):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterCreateView(LoginRequiredMixin, CreateView):\n model = Character\n form_class = CharacterForm\n\n def get_initial(self):\n # Get the initial dictionary from the superclass method\n initial = super(CharacterCreateView, self).get_initial()\n # Copy the dictionary so we don't accidentally change a mutable dict\n initial = initial.copy()\n # default to getting the player from the query String.\n try:\n initial['player'] = self.request.GET['player']\n except KeyError:\n initial['player'] = self.request.user.player\n # etc...\n return initial\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n kwargs['user'] = self.request.user # pass the 'user' in kwargs\n return kwargs\n\n def get_success_url(self):\n return reverse(\n 'characters:character_skill_update',\n kwargs={'pk': self.object.pk}\n )\n\n def form_valid(self, form):\n \"\"\"\n If this form is valid, then add the current player to the character\n if the current user is not an admin\n\n If the user doesn't have any other active characters, set this one\n to active.\n \"\"\"\n if not self.request.user.has_perm('players.view_any_player'):\n form.instance.player = self.request.user.player\n\n if not form.instance.player.character_set.filter(active_flag=True).exists():\n form.instance.active_flag = True\n\n messages.info(self.request, 'New Character, \"{}\" created.'.format(\n form.instance.name\n ))\n return super().form_valid(form)\n\n\nclass CharacterUpdateView(LoginRequiredMixin, UserPassesTestMixin, UpdateView):\n model = Character\n form_class = CharacterForm\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n kwargs['user'] = self.request.user # pass the 'user' in kwargs\n return kwargs\n\n def get_success_url(self):\n return reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n )\n\n\nclass CharacterDeleteView(\n PermissionRequiredMixin,\n UserPassesTestMixin,\n DeleteView\n ):\n \"\"\"\n Removes a character permanantly.\n\n Removing a character may have strange effects on other views.\n \"\"\"\n\n model = Character\n permission_required = ('characters.change_character', )\n success_url = reverse_lazy('characters:character_list')\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterResetView(\n PermissionRequiredMixin,\n UserPassesTestMixin,\n View\n ):\n \"\"\"\n Resets a characters skills to none and returns their points to them.\n \"\"\"\n\n model = Character\n permission_required = ('characters.change_character', )\n success_url = reverse_lazy('characters:character_list')\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n\n with transaction.atomic():\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.cp_available += character.cp_spent\n character.cp_spent = 0\n character.save(update_fields=['cp_available', 'cp_spent'])\n character.characterskills_set.all().delete()\n character.headers.clear()\n messages.info(self.request, 'Character skills reset for {}.'.format(\n character.name\n ))\n return HttpResponseRedirect(\n self.request.META.get(\n 'HTTP_REFERER',\n reverse(\n 'characters:character_detail',\n kwargs={'pk': self.kwargs['pk']}\n )\n )\n )\n\n\nclass CharacterSetActiveView(\n LoginRequiredMixin,\n UserPassesTestMixin,\n View\n ):\n \"\"\"\n Set the active character for the characters player to the sent id.\n \"\"\"\n\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the\n character they are setting active\n \"\"\"\n\n character = self.model.objects.get(pk=self.kwargs['pk'])\n character.player.character_set.update(active_flag=False)\n character.active_flag = True\n character.save()\n messages.info(self.request, 'Active Character changed to {}.'.format(\n character.name\n ))\n return HttpResponseRedirect(\n self.request.META.get(\n 'HTTP_REFERER',\n reverse(\n 'characters:character_detail',\n kwargs={'pk': self.kwargs['pk']}\n )\n )\n )\n\n\nclass CharacterSkillUpdateView(\n LoginRequiredMixin,\n UserPassesTestMixin,\n FormMixin,\n DetailView):\n \"\"\"\n Allow a user to update their chosen skills\n \"\"\"\n\n template_name = 'characters/character_skill_form.html'\n form_class = CharacterSkillForm\n model = Character\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n def get_success_url(self):\n return reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n )\n\n def get_form_kwargs(self):\n kwargs = super().get_form_kwargs()\n self.skills = Header.objects\\\n .order_by('hidden_flag', 'category', 'name')\\\n .all()\n kwargs.update({'skills': self.skills})\n return kwargs\n\n def get_context_data(self, **kwargs):\n context = super().get_context_data(**self.kwargs)\n\n # remove skills not in the hash.\n available_skills = self.object.skillhash.keys()\n context['skills'] = filter(lambda x: x.id in available_skills or self.request.user.has_perm('player.view_any_player'), self.skills)\n context['skill_hash'] = self.object.skillhash\n # add the bare skills granted by the rules\n context['granted_skills'] = self.object.skill_grants\n return context\n\n def post(self, request, *args, **kwargs):\n self.object = self.get_object()\n form = self.get_form()\n if form.is_valid():\n return self.form_valid(form)\n else:\n return self.form_invalid(form)\n\n def form_valid(self, form):\n \"\"\"\n Form is valid. Save the skills to that character and remove the\n appropriate number of characters points.\n \"\"\"\n return super().form_valid(form)\n\n\nclass ResetPointsView(\n PermissionRequiredMixin,\n View\n ):\n \"\"\"\n Resets the points for the season.\n \"\"\"\n\n permission_required = ('characters.reset_points', )\n\n def get(self, request, *args, **kwargs):\n \"\"\"\n Send the user back to the the originating page or back to the main \n page if the referrer isn't set.\n \"\"\"\n Character.objects.all().update(cp_transferred=0)\n messages.info(self.request, 'Point cap reset!')\n return HttpResponseRedirect(\n self.request.META.get(\n 'HTTP_REFERER',\n '/'\n )\n )\n\n\n'''\nPut the AJAX work for Characters here\n'''\n\n\nclass CharacterAddHeaderView(APIView):\n '''\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n '''\n\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n # get the character and then see if the header is allowed\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n # Default to error.\n content = {\n 'error': \"prerequisites not met\"\n }\n status = None\n # if the prerequisites are met, add the header to the user and return\n # the list of skills\n if character.check_header_prerequisites(header):\n # see if the character has enough points to add the header\n if (cp_available - header.cost) >= 0:\n character.cp_available -= header.cost\n character.cp_spent += header.cost\n character.headers.add(header)\n character.save()\n skill_item_template_string = render_to_string(\n \"characters/includes/character_skill_update_item.html\",\n {\n 'header': header,\n 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]\n },\n request\n )\n content = {\n 'success': header.cost * -1,\n 'skills': skill_item_template_string\n }\n else: \n content = {\n 'error': \"You don't have enough points available for this character to add this header.\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDropHeaderView(APIView):\n '''\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n '''\n\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n # get the character and header\n header = Header.objects.get(pk=header_id)\n character = Character.objects.get(pk=character_id)\n # Default to error.\n content = {\n 'error': \"Header is not already bought!\"\n }\n status = None\n # if the character has the header, drop it and refund the CP\n content['header_list'] = []\n\n if header in character.headers.all():\n print(f'Header present! Dropping and adding back in {header.cost} CP...')\n character.cp_available += header.cost\n character.cp_spent -= header.cost\n character.headers.remove(header)\n skill_item_template_string = render_to_string(\n \"characters/includes/character_skill_update_item.html\",\n {\n 'header': header,\n 'header_skills': header.skills.all(),\n 'header_costs': character.skillhash[header.id]\n },\n request\n )\n content = {\n 'success': header.cost,\n }\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterAddSkillView(APIView):\n '''\n Set of AJAX views for a Characters\n\n This handles different API calls for character actions.\n '''\n\n authentication_classes = [SessionAuthentication]\n permission_classes = [OwnsCharacter]\n\n def post(self, request, format=None):\n skill_id = int(request.POST.get('skill_id', 0))\n header_id = int(request.POST.get('header_id', 0))\n character_id = int(request.POST.get('character_id', 0))\n cp_available = int(request.POST.get('cp_available', 0))\n try:\n vector = int(request.POST.get('vector'))\n except AttributeError:\n return {\n 'error': \"No change indicated\"\n }\n # get the character and then see if the skill is allowed\n header_skill = HeaderSkill.objects.get(skill_id=skill_id, header_id=header_id)\n character = Character.objects.get(pk=character_id)\n # check that the skill is allowed.\n # if the prerequisites are met, add the header to the user and return\n # the list of skills\n # otherwise, return an error\n content = {\n 'success': \"testing right now\"\n }\n status = None\n if character.check_skill_prerequisites(header_skill.skill, header_skill.header):\n # since vector is the direction, we want to reverse it when\n # dealing with what we want to change for the available points\n # see if the character has enough points to add the header\n cost = character.skill_cost(header_skill) * vector\n if (cp_available - cost) >= 0:\n # when this is returned, change the available costs\n (character_skill, created) = character.characterskills_set.get_or_create(\n skill=header_skill\n )\n if character_skill.count and (character_skill.count + vector < 0):\n content = {\n 'error': f\"You don't have any points in {header_skill.skill}\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else: \n content = {\n 'success': cost * -1\n }\n character_skill.count = F('count') + vector\n character_skill.save()\n character.cp_spent = F('cp_spent') + cost\n character.cp_available = F('cp_available') - cost\n character.save()\n else: \n content = {\n 'error': \"You don't have enough points available to purchase this skill . . .\"\n }\n status = HTTP_412_PRECONDITION_FAILED\n else:\n status = HTTP_412_PRECONDITION_FAILED\n return Response(content, status)\n\n\nclass CharacterDetailView(LoginRequiredMixin, UserPassesTestMixin, DetailView):\n \"\"\"\n Show the details for a character.\n\n From here you can edit the details of a character or choose skills.\n \"\"\"\n\n model = Character\n fields = '__all__'\n\n def test_func(self):\n if self.request.user.has_perm('players.view_any_player'):\n return True\n try:\n player = Character.objects.get(pk=self.kwargs['pk']).player\n return (player.user == self.request.user)\n except Character.DoesNotExist:\n return False\n return False\n\n\nclass CharacterConceptApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the concept for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterConceptApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data['character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.concept_approved_flag = True\n self.object.save(update_fields=['concept_approved_flag'])\n messages.info(self.request, f\"{self.object} concept approved!\")\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data['character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n ))\n\n def get_success_url(self):\n return reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n ) \n\n\nclass CharacterHistoryApproveView(PermissionRequiredMixin, FormView):\n \"\"\"\n Approve the history for a character.\n Grant the CP for the character\n Set the history approved flag.\n \"\"\"\n permission_required = 'players.change_any_player'\n form_class = CharacterHistoryApproveForm\n\n def form_valid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data['character_id'])\n self.object.player.cp_available += 3\n self.object.player.save(update_fields=['cp_available'])\n self.object.history_approved_flag = True\n self.object.save(update_fields=['history_approved_flag'])\n messages.info(self.request, f\"{self.object} history approved!\")\n return super().form_valid(form)\n\n def form_invalid(self, form):\n self.object = Character.objects.get(pk=form.cleaned_data['character_id'])\n for key, error in form.errors.items():\n messages.error(self.request, error.as_text())\n return HttpResponseRedirect(reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n ))\n\n def get_success_url(self):\n return reverse(\n 'characters:character_detail',\n kwargs={'pk': self.object.pk}\n ) \n\n\nclass CharacterListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show the list of characters.\n\n From here, you can view, edit, delete a character.\n \"\"\"\n\n model = Character\n paginate_by = 25\n\n def get_queryset(self):\n queryset = super().get_queryset()\n criteria = self.request.GET.get('criteria', '')\n if (criteria.strip()):\n entry_query = get_query(\n criteria,\n ['name', 'description', 'concept', 'history', 'player_notes']\n )\n queryset = queryset.filter(entry_query)\n history_approved_flag = self.request.GET.get('history_approved_flag', False)\n if history_approved_flag:\n queryset = queryset.filter(history_approved_flag=True)\n concept_approved_flag = self.request.GET.get('concept_approved_flag', False)\n if concept_approved_flag:\n queryset = queryset.filter(concept_approved_flag=True)\n return queryset\n\n def get_context_data(self, **kwargs):\n '''\n Add the form so we can filter the characters.\n '''\n # get the context data to add to.\n context_data = super().get_context_data(**kwargs)\n context_data.update(**self.request.GET)\n # return the resulting context\n return context_data\n\n\nclass CharacterPrintListView(LoginRequiredMixin, ListView):\n \"\"\"\n Show a list of characters to print.\n\n \"\"\"\n\n model = Character\n template_name = \"characters/character_print_list.html\"\n\n def get_queryset(self):\n queryset = super().get_queryset() # filter by event\n event_id = self.kwargs.get('event_id', None)\n if not event_id:\n event_id = Event.next_event().id\n player_ids = Registration.objects.filter(event__id=event_id).values_list('player_id', flat=True)\n queryset = queryset.filter(player__id__in=player_ids, npc_flag=False, active_flag=True)\n \n return queryset\n",
"step-ids": [
33,
48,
59,
68,
81
]
}
|
[
33,
48,
59,
68,
81
] |
def flat_list(array):
result = []
for element in array:
if type(element) == list:
result += flat_list(element)
else:
result.append(element)
return result
print flat_list([1, [2, 2, 2], 4])
print flat_list([-1, [1, [-2], 1], -1])
|
normal
|
{
"blob_id": "0d321193d68b463e3dd04b21ee611afdc212a22b",
"index": 4682,
"step-1": "def flat_list(array):\n result = []\n for element in array:\n if type(element) == list:\n result += flat_list(element)\n else:\n result.append(element)\n return result\n\n\nprint flat_list([1, [2, 2, 2], 4])\nprint flat_list([-1, [1, [-2], 1], -1])",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
"""This module defines simple utilities for making toy datasets to be used in testing/examples"""
##################################################
# Import Miscellaneous Assets
##################################################
import pandas as pd
###############################################
# Import Learning Assets
###############################################
from sklearn.datasets import load_breast_cancer, make_classification, load_diabetes
##################################################
# Dataset Utilities
##################################################
def get_breast_cancer_data(target="diagnosis"):
"""Get the Wisconsin Breast Cancer classification dataset, formatted as a DataFrame
Parameters
----------
target: String, default='diagnosis'
What to name the column in `df` that contains the target output values
Returns
-------
df: `pandas.DataFrame`
The breast cancer dataset, with friendly column names"""
data = load_breast_cancer()
df = pd.DataFrame(data=data.data, columns=[_.replace(" ", "_") for _ in data.feature_names])
df[target] = data.target
return df
def get_diabetes_data(target="progression"):
"""Get the SKLearn Diabetes regression dataset, formatted as a DataFrame
Parameters
----------
target: String, default='progression'
What to name the column in `df` that contains the target output values
Returns
-------
df: `pandas.DataFrame`
The diabetes dataset, with friendly column names"""
data = load_diabetes()
df = pd.DataFrame(data=data.data, columns=[_.replace(" ", "_") for _ in data.feature_names])
df[target] = data.target
return df
def get_toy_classification_data(
target="target", n_samples=300, n_classes=2, shuffle=True, random_state=32, **kwargs
):
"""Wrapper around `sklearn.datasets.make_classification` to produce a `pandas.DataFrame`"""
x, y = make_classification(
n_samples=n_samples,
n_classes=n_classes,
shuffle=shuffle,
random_state=random_state,
**kwargs
)
train_df = pd.DataFrame(data=x, columns=range(x.shape[1]))
train_df[target] = y
return train_df
|
normal
|
{
"blob_id": "285ca945696b32160175f15c4e89b3938f41ebf4",
"index": 2172,
"step-1": "<mask token>\n\n\ndef get_diabetes_data(target='progression'):\n \"\"\"Get the SKLearn Diabetes regression dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='progression'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The diabetes dataset, with friendly column names\"\"\"\n data = load_diabetes()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_diabetes_data(target='progression'):\n \"\"\"Get the SKLearn Diabetes regression dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='progression'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The diabetes dataset, with friendly column names\"\"\"\n data = load_diabetes()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_toy_classification_data(target='target', n_samples=300, n_classes=2,\n shuffle=True, random_state=32, **kwargs):\n \"\"\"Wrapper around `sklearn.datasets.make_classification` to produce a `pandas.DataFrame`\"\"\"\n x, y = make_classification(n_samples=n_samples, n_classes=n_classes,\n shuffle=shuffle, random_state=random_state, **kwargs)\n train_df = pd.DataFrame(data=x, columns=range(x.shape[1]))\n train_df[target] = y\n return train_df\n",
"step-3": "<mask token>\n\n\ndef get_breast_cancer_data(target='diagnosis'):\n \"\"\"Get the Wisconsin Breast Cancer classification dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='diagnosis'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The breast cancer dataset, with friendly column names\"\"\"\n data = load_breast_cancer()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_diabetes_data(target='progression'):\n \"\"\"Get the SKLearn Diabetes regression dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='progression'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The diabetes dataset, with friendly column names\"\"\"\n data = load_diabetes()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_toy_classification_data(target='target', n_samples=300, n_classes=2,\n shuffle=True, random_state=32, **kwargs):\n \"\"\"Wrapper around `sklearn.datasets.make_classification` to produce a `pandas.DataFrame`\"\"\"\n x, y = make_classification(n_samples=n_samples, n_classes=n_classes,\n shuffle=shuffle, random_state=random_state, **kwargs)\n train_df = pd.DataFrame(data=x, columns=range(x.shape[1]))\n train_df[target] = y\n return train_df\n",
"step-4": "<mask token>\nimport pandas as pd\nfrom sklearn.datasets import load_breast_cancer, make_classification, load_diabetes\n\n\ndef get_breast_cancer_data(target='diagnosis'):\n \"\"\"Get the Wisconsin Breast Cancer classification dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='diagnosis'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The breast cancer dataset, with friendly column names\"\"\"\n data = load_breast_cancer()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_diabetes_data(target='progression'):\n \"\"\"Get the SKLearn Diabetes regression dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='progression'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The diabetes dataset, with friendly column names\"\"\"\n data = load_diabetes()\n df = pd.DataFrame(data=data.data, columns=[_.replace(' ', '_') for _ in\n data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_toy_classification_data(target='target', n_samples=300, n_classes=2,\n shuffle=True, random_state=32, **kwargs):\n \"\"\"Wrapper around `sklearn.datasets.make_classification` to produce a `pandas.DataFrame`\"\"\"\n x, y = make_classification(n_samples=n_samples, n_classes=n_classes,\n shuffle=shuffle, random_state=random_state, **kwargs)\n train_df = pd.DataFrame(data=x, columns=range(x.shape[1]))\n train_df[target] = y\n return train_df\n",
"step-5": "\"\"\"This module defines simple utilities for making toy datasets to be used in testing/examples\"\"\"\n##################################################\n# Import Miscellaneous Assets\n##################################################\nimport pandas as pd\n\n###############################################\n# Import Learning Assets\n###############################################\nfrom sklearn.datasets import load_breast_cancer, make_classification, load_diabetes\n\n\n##################################################\n# Dataset Utilities\n##################################################\ndef get_breast_cancer_data(target=\"diagnosis\"):\n \"\"\"Get the Wisconsin Breast Cancer classification dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='diagnosis'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The breast cancer dataset, with friendly column names\"\"\"\n data = load_breast_cancer()\n df = pd.DataFrame(data=data.data, columns=[_.replace(\" \", \"_\") for _ in data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_diabetes_data(target=\"progression\"):\n \"\"\"Get the SKLearn Diabetes regression dataset, formatted as a DataFrame\n\n Parameters\n ----------\n target: String, default='progression'\n What to name the column in `df` that contains the target output values\n\n Returns\n -------\n df: `pandas.DataFrame`\n The diabetes dataset, with friendly column names\"\"\"\n data = load_diabetes()\n df = pd.DataFrame(data=data.data, columns=[_.replace(\" \", \"_\") for _ in data.feature_names])\n df[target] = data.target\n return df\n\n\ndef get_toy_classification_data(\n target=\"target\", n_samples=300, n_classes=2, shuffle=True, random_state=32, **kwargs\n):\n \"\"\"Wrapper around `sklearn.datasets.make_classification` to produce a `pandas.DataFrame`\"\"\"\n x, y = make_classification(\n n_samples=n_samples,\n n_classes=n_classes,\n shuffle=shuffle,\n random_state=random_state,\n **kwargs\n )\n train_df = pd.DataFrame(data=x, columns=range(x.shape[1]))\n train_df[target] = y\n return train_df\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
class TimeEntry:
def __init__(self, date, duration, togglproject='default toggl',
tdproject='default td', togglID='NULL', tdID='Null'):
self.duration = duration
self.date = date
self.togglProject = togglproject
self.tdProject = tdproject
self.togglID = togglID
self.tdID = tdID
|
normal
|
{
"blob_id": "bdf2c35c12820dd31bd242ce1b6dae7271ceb2b7",
"index": 8433,
"step-1": "<mask token>\n",
"step-2": "class TimeEntry:\n <mask token>\n",
"step-3": "class TimeEntry:\n\n def __init__(self, date, duration, togglproject='default toggl',\n tdproject='default td', togglID='NULL', tdID='Null'):\n self.duration = duration\n self.date = date\n self.togglProject = togglproject\n self.tdProject = tdproject\n self.togglID = togglID\n self.tdID = tdID\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
import dtw
import stats
import glob
import argparse
import matplotlib.pyplot as plt
GRAPH = False
PERCENTAGE = False
VERBOSE = False
def buildExpectations(queryPath, searchPatternPath):
"""
Based on SpeechCommand_v0.02 directory structure.
"""
expectations = []
currentDirectory = ""
queryFilename = queryPath.split("/")[-1]
queryDirectory = queryPath.split("/")[-2]
queryCode = queryFilename.split("_")[0]
searchFileList = sorted(glob.glob(searchPatternPath))
for searchFile in searchFileList:
searchFilename = searchFile.split("/")[-1]
searchDirectory = searchFile.split("/")[-2]
searchCode = searchFilename.split("_")[0]
if searchDirectory != currentDirectory:
currentDirectory = searchDirectory
if searchCode == queryCode:
if currentDirectory == queryDirectory:
expectations.append([[0, 1]])
else:
expectations.append([[0, 0]])
return expectations
if __name__ == "__main__":
# Parse arguments
parser = argparse.ArgumentParser(description='Dynamic Time Warping')
parser.add_argument('-g', '--graph', action='store_true', help='Enable graph display')
parser.add_argument('-t', '--threshold', type=float, default=0.4, help='Set score threshold')
parser.add_argument('query_path')
parser.add_argument('search_pattern_path')
printGroup = parser.add_mutually_exclusive_group()
printGroup.add_argument('-p', '--percentage', action='store_true', help='Enable percentage display')
printGroup.add_argument('-v', '--verbose', action='store_true', help='Enable verbose display')
args = parser.parse_args()
GRAPH = args.graph
PERCENTAGE = args.percentage
threshold = args.threshold
VERBOSE = args.verbose
queryPath = args.query_path
searchPatternPath = args.search_pattern_path
dtw.VERBOSE = VERBOSE
stats.VERBOSE = VERBOSE
labels, sweepList, bestList = dtw.runSearch(queryPath, searchPatternPath)
results = dtw.computeResultsPrecisely(sweepList, threshold, positiveOnly=True)
for i, result in enumerate(results):
print(labels[i] + ": ", end='')
for j, (hitIndex, _) in enumerate(result):
print(hitIndex * 3, end='')
if j < len(result) - 1:
print(" | ", end='')
print()
if GRAPH:
dtw.showSweeps(labels, sweepList, bestList)
plt.show()
|
normal
|
{
"blob_id": "03fb1cf0aac0c37858dd8163562a7139ed4e1179",
"index": 776,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef buildExpectations(queryPath, searchPatternPath):\n \"\"\"\n Based on SpeechCommand_v0.02 directory structure.\n \"\"\"\n expectations = []\n currentDirectory = ''\n queryFilename = queryPath.split('/')[-1]\n queryDirectory = queryPath.split('/')[-2]\n queryCode = queryFilename.split('_')[0]\n searchFileList = sorted(glob.glob(searchPatternPath))\n for searchFile in searchFileList:\n searchFilename = searchFile.split('/')[-1]\n searchDirectory = searchFile.split('/')[-2]\n searchCode = searchFilename.split('_')[0]\n if searchDirectory != currentDirectory:\n currentDirectory = searchDirectory\n if searchCode == queryCode:\n if currentDirectory == queryDirectory:\n expectations.append([[0, 1]])\n else:\n expectations.append([[0, 0]])\n return expectations\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description='Dynamic Time Warping')\n parser.add_argument('-g', '--graph', action='store_true', help=\n 'Enable graph display')\n parser.add_argument('-t', '--threshold', type=float, default=0.4, help=\n 'Set score threshold')\n parser.add_argument('query_path')\n parser.add_argument('search_pattern_path')\n printGroup = parser.add_mutually_exclusive_group()\n printGroup.add_argument('-p', '--percentage', action='store_true', help\n ='Enable percentage display')\n printGroup.add_argument('-v', '--verbose', action='store_true', help=\n 'Enable verbose display')\n args = parser.parse_args()\n GRAPH = args.graph\n PERCENTAGE = args.percentage\n threshold = args.threshold\n VERBOSE = args.verbose\n queryPath = args.query_path\n searchPatternPath = args.search_pattern_path\n dtw.VERBOSE = VERBOSE\n stats.VERBOSE = VERBOSE\n labels, sweepList, bestList = dtw.runSearch(queryPath, searchPatternPath)\n results = dtw.computeResultsPrecisely(sweepList, threshold,\n positiveOnly=True)\n for i, result in enumerate(results):\n print(labels[i] + ': ', end='')\n for j, (hitIndex, _) in enumerate(result):\n print(hitIndex * 3, end='')\n if j < len(result) - 1:\n print(' | ', end='')\n print()\n if GRAPH:\n dtw.showSweeps(labels, sweepList, bestList)\n plt.show()\n",
"step-3": "<mask token>\nGRAPH = False\nPERCENTAGE = False\nVERBOSE = False\n\n\ndef buildExpectations(queryPath, searchPatternPath):\n \"\"\"\n Based on SpeechCommand_v0.02 directory structure.\n \"\"\"\n expectations = []\n currentDirectory = ''\n queryFilename = queryPath.split('/')[-1]\n queryDirectory = queryPath.split('/')[-2]\n queryCode = queryFilename.split('_')[0]\n searchFileList = sorted(glob.glob(searchPatternPath))\n for searchFile in searchFileList:\n searchFilename = searchFile.split('/')[-1]\n searchDirectory = searchFile.split('/')[-2]\n searchCode = searchFilename.split('_')[0]\n if searchDirectory != currentDirectory:\n currentDirectory = searchDirectory\n if searchCode == queryCode:\n if currentDirectory == queryDirectory:\n expectations.append([[0, 1]])\n else:\n expectations.append([[0, 0]])\n return expectations\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description='Dynamic Time Warping')\n parser.add_argument('-g', '--graph', action='store_true', help=\n 'Enable graph display')\n parser.add_argument('-t', '--threshold', type=float, default=0.4, help=\n 'Set score threshold')\n parser.add_argument('query_path')\n parser.add_argument('search_pattern_path')\n printGroup = parser.add_mutually_exclusive_group()\n printGroup.add_argument('-p', '--percentage', action='store_true', help\n ='Enable percentage display')\n printGroup.add_argument('-v', '--verbose', action='store_true', help=\n 'Enable verbose display')\n args = parser.parse_args()\n GRAPH = args.graph\n PERCENTAGE = args.percentage\n threshold = args.threshold\n VERBOSE = args.verbose\n queryPath = args.query_path\n searchPatternPath = args.search_pattern_path\n dtw.VERBOSE = VERBOSE\n stats.VERBOSE = VERBOSE\n labels, sweepList, bestList = dtw.runSearch(queryPath, searchPatternPath)\n results = dtw.computeResultsPrecisely(sweepList, threshold,\n positiveOnly=True)\n for i, result in enumerate(results):\n print(labels[i] + ': ', end='')\n for j, (hitIndex, _) in enumerate(result):\n print(hitIndex * 3, end='')\n if j < len(result) - 1:\n print(' | ', end='')\n print()\n if GRAPH:\n dtw.showSweeps(labels, sweepList, bestList)\n plt.show()\n",
"step-4": "import dtw\nimport stats\nimport glob\nimport argparse\nimport matplotlib.pyplot as plt\nGRAPH = False\nPERCENTAGE = False\nVERBOSE = False\n\n\ndef buildExpectations(queryPath, searchPatternPath):\n \"\"\"\n Based on SpeechCommand_v0.02 directory structure.\n \"\"\"\n expectations = []\n currentDirectory = ''\n queryFilename = queryPath.split('/')[-1]\n queryDirectory = queryPath.split('/')[-2]\n queryCode = queryFilename.split('_')[0]\n searchFileList = sorted(glob.glob(searchPatternPath))\n for searchFile in searchFileList:\n searchFilename = searchFile.split('/')[-1]\n searchDirectory = searchFile.split('/')[-2]\n searchCode = searchFilename.split('_')[0]\n if searchDirectory != currentDirectory:\n currentDirectory = searchDirectory\n if searchCode == queryCode:\n if currentDirectory == queryDirectory:\n expectations.append([[0, 1]])\n else:\n expectations.append([[0, 0]])\n return expectations\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description='Dynamic Time Warping')\n parser.add_argument('-g', '--graph', action='store_true', help=\n 'Enable graph display')\n parser.add_argument('-t', '--threshold', type=float, default=0.4, help=\n 'Set score threshold')\n parser.add_argument('query_path')\n parser.add_argument('search_pattern_path')\n printGroup = parser.add_mutually_exclusive_group()\n printGroup.add_argument('-p', '--percentage', action='store_true', help\n ='Enable percentage display')\n printGroup.add_argument('-v', '--verbose', action='store_true', help=\n 'Enable verbose display')\n args = parser.parse_args()\n GRAPH = args.graph\n PERCENTAGE = args.percentage\n threshold = args.threshold\n VERBOSE = args.verbose\n queryPath = args.query_path\n searchPatternPath = args.search_pattern_path\n dtw.VERBOSE = VERBOSE\n stats.VERBOSE = VERBOSE\n labels, sweepList, bestList = dtw.runSearch(queryPath, searchPatternPath)\n results = dtw.computeResultsPrecisely(sweepList, threshold,\n positiveOnly=True)\n for i, result in enumerate(results):\n print(labels[i] + ': ', end='')\n for j, (hitIndex, _) in enumerate(result):\n print(hitIndex * 3, end='')\n if j < len(result) - 1:\n print(' | ', end='')\n print()\n if GRAPH:\n dtw.showSweeps(labels, sweepList, bestList)\n plt.show()\n",
"step-5": "import dtw\nimport stats\n\nimport glob\nimport argparse\nimport matplotlib.pyplot as plt\n\nGRAPH = False\nPERCENTAGE = False\nVERBOSE = False\n\ndef buildExpectations(queryPath, searchPatternPath):\n \"\"\"\n Based on SpeechCommand_v0.02 directory structure.\n \"\"\"\n expectations = []\n currentDirectory = \"\"\n queryFilename = queryPath.split(\"/\")[-1]\n queryDirectory = queryPath.split(\"/\")[-2]\n queryCode = queryFilename.split(\"_\")[0]\n searchFileList = sorted(glob.glob(searchPatternPath))\n for searchFile in searchFileList:\n searchFilename = searchFile.split(\"/\")[-1]\n searchDirectory = searchFile.split(\"/\")[-2]\n searchCode = searchFilename.split(\"_\")[0]\n if searchDirectory != currentDirectory:\n currentDirectory = searchDirectory\n if searchCode == queryCode:\n if currentDirectory == queryDirectory:\n expectations.append([[0, 1]])\n else:\n expectations.append([[0, 0]])\n return expectations\n\nif __name__ == \"__main__\":\n # Parse arguments\n parser = argparse.ArgumentParser(description='Dynamic Time Warping')\n parser.add_argument('-g', '--graph', action='store_true', help='Enable graph display')\n parser.add_argument('-t', '--threshold', type=float, default=0.4, help='Set score threshold')\n parser.add_argument('query_path')\n parser.add_argument('search_pattern_path')\n\n printGroup = parser.add_mutually_exclusive_group()\n printGroup.add_argument('-p', '--percentage', action='store_true', help='Enable percentage display')\n printGroup.add_argument('-v', '--verbose', action='store_true', help='Enable verbose display')\n\n args = parser.parse_args()\n\n GRAPH = args.graph\n PERCENTAGE = args.percentage\n threshold = args.threshold\n VERBOSE = args.verbose\n queryPath = args.query_path\n searchPatternPath = args.search_pattern_path\n\n dtw.VERBOSE = VERBOSE\n stats.VERBOSE = VERBOSE\n\n labels, sweepList, bestList = dtw.runSearch(queryPath, searchPatternPath)\n\n results = dtw.computeResultsPrecisely(sweepList, threshold, positiveOnly=True)\n for i, result in enumerate(results):\n print(labels[i] + \": \", end='')\n for j, (hitIndex, _) in enumerate(result):\n print(hitIndex * 3, end='')\n if j < len(result) - 1:\n print(\" | \", end='')\n print()\n\n if GRAPH:\n dtw.showSweeps(labels, sweepList, bestList)\n\n plt.show()\n",
"step-ids": [
0,
2,
3,
4,
5
]
}
|
[
0,
2,
3,
4,
5
] |
from collections import defaultdict
# The order of the steps doesn't matter, so the distance
# function is very simple
def dist(counts):
n = abs(counts["n"] - counts["s"])
nw = abs(counts["nw"] - counts["se"])
ne = abs(counts["ne"] - counts["sw"])
return n + max(ne,nw)
if __name__ == "__main__":
counts = defaultdict(int)
with open("day11.input.txt") as f:
INPUT = f.read().strip()
dir_list = INPUT.split(",")
# The order of the steps doesn't matter so we just need
# to count each type of step
for dir in dir_list:
counts[dir] += 1
print(dist(counts))
counts = defaultdict(int)
with open("day11.input.txt") as f:
INPUT = f.read().strip()
dir_list = INPUT.split(",")
# print(dir_list)
max_d = -1
for dir in dir_list:
# Keep running counts and check for distance at every
# step to find max
counts[dir] += 1
max_d = max(max_d,dist(counts))
print("max=", max_d)
|
normal
|
{
"blob_id": "ac2e9145e3345e5448683d684b69d2356e3214ce",
"index": 9999,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef dist(counts):\n n = abs(counts['n'] - counts['s'])\n nw = abs(counts['nw'] - counts['se'])\n ne = abs(counts['ne'] - counts['sw'])\n return n + max(ne, nw)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef dist(counts):\n n = abs(counts['n'] - counts['s'])\n nw = abs(counts['nw'] - counts['se'])\n ne = abs(counts['ne'] - counts['sw'])\n return n + max(ne, nw)\n\n\nif __name__ == '__main__':\n counts = defaultdict(int)\n with open('day11.input.txt') as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(',')\n for dir in dir_list:\n counts[dir] += 1\n print(dist(counts))\n counts = defaultdict(int)\n with open('day11.input.txt') as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(',')\n max_d = -1\n for dir in dir_list:\n counts[dir] += 1\n max_d = max(max_d, dist(counts))\n print('max=', max_d)\n",
"step-4": "from collections import defaultdict\n\n\ndef dist(counts):\n n = abs(counts['n'] - counts['s'])\n nw = abs(counts['nw'] - counts['se'])\n ne = abs(counts['ne'] - counts['sw'])\n return n + max(ne, nw)\n\n\nif __name__ == '__main__':\n counts = defaultdict(int)\n with open('day11.input.txt') as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(',')\n for dir in dir_list:\n counts[dir] += 1\n print(dist(counts))\n counts = defaultdict(int)\n with open('day11.input.txt') as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(',')\n max_d = -1\n for dir in dir_list:\n counts[dir] += 1\n max_d = max(max_d, dist(counts))\n print('max=', max_d)\n",
"step-5": "from collections import defaultdict\n\n# The order of the steps doesn't matter, so the distance\n# function is very simple\ndef dist(counts):\n n = abs(counts[\"n\"] - counts[\"s\"])\n nw = abs(counts[\"nw\"] - counts[\"se\"])\n ne = abs(counts[\"ne\"] - counts[\"sw\"])\n return n + max(ne,nw)\n\nif __name__ == \"__main__\":\n counts = defaultdict(int)\n with open(\"day11.input.txt\") as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(\",\")\n # The order of the steps doesn't matter so we just need\n # to count each type of step\n for dir in dir_list:\n counts[dir] += 1\n\n print(dist(counts))\n\n counts = defaultdict(int)\n with open(\"day11.input.txt\") as f:\n INPUT = f.read().strip()\n dir_list = INPUT.split(\",\")\n # print(dir_list)\n max_d = -1\n for dir in dir_list:\n # Keep running counts and check for distance at every\n # step to find max\n counts[dir] += 1\n max_d = max(max_d,dist(counts))\n print(\"max=\", max_d)\n \n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from collections import OrderedDict
from functools import reduce
class ArcTan(nn.Module):
def __init__(self):
super(ArcTan,self).__init__()
def forward(self, x):
return torch.arctan(x) / 1.5708
class Params():
def __init__(self, dim_in=7, dim_act=6, dim_h=0, dropout=0.0):
self.dim_act = dim_act
self.dim_in = 0
self.dim_h = 0
self.dropout = 0.0
self.model_name = "DockRLParams"
self.init_params()
self.act = ArcTan()
def init_params(self):
self.params = np.random.randn(self.dim_act)
self.num_params = self.dim_act
def forward(self, obs):
return self.get_params()
def get_params(self):
return self.params
def set_params(self, params):
assert params.shape == self.params.shape
self.params = params
def reset(self):
pass
class GraphNN(nn.Module):
def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.00):
super(GraphNN, self).__init__()
self.ligand_dim = dim_in
self.dim_h = dim_h
self.dim_act = dim_act
self.model_name = "DockRLGraphNN"
# This is a guesstimate based on:
# https://pymolwiki.org/index.php/Displaying_Biochemical_Properties
self.bond_cutoff = 3.6
self.number_updates = 16
self.dropout = dropout
self.initialize_gnn()
self.reset()
my_params = self.get_params()
self.num_params = my_params.shape[0]
def initialize_gnn(self):
# vertices MLP, with 8 element key and query vectors for self-attention
self.edge_model = nn.Sequential(\
nn.Linear(self.ligand_dim, self.dim_h),\
nn.LeakyReLU(),\
nn.Linear(self.dim_h, self.dim_h),\
nn.LeakyReLU(),\
nn.Dropout(p=self.dropout),\
nn.Linear(self.dim_h, self.ligand_dim + 2 * self.dim_h)
)
self.encoder = nn.Sequential(\
nn.Linear(2*self.ligand_dim, self.ligand_dim),\
ArcTan()
)
self.action_layer = nn.Sequential(\
nn.Linear(self.ligand_dim, self.dim_h),\
nn.LeakyReLU(),\
nn.Linear(self.dim_h, self.dim_act)\
)
def get_distance(self, node_0, node_1):
return torch.sum(torch.sqrt(torch.abs(node_0 - node_1)**2))
def build_graph(self, x):
self.graph = torch.zeros(x.shape[0],x.shape[0])
for ii in range(x.shape[0]):
node_ii = x[ii, 0:3]
for jj in range(x.shape[0]):
node_jj = x[jj, 0:3]
distance = self.get_distance(node_ii, node_jj)
if distance <= self.bond_cutoff:
self.graph[ii, jj] = 1.0
self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))
def forward(self, x, return_codes=False, template=None):
if type(x) != torch.Tensor:
x = torch.Tensor(x)
if template is not None:
self.build_graph(template.detach())
else:
self.build_graph(x.detach())
new_graph = torch.Tensor() #torch.zeros_like(x)
codes = torch.Tensor() #torch.zeros(x.shape[0], self.dim_h)
temp_input = [torch.Tensor()]
#orch.Tensor() #torch.zeros(x.shape[0], self.dim_h+8+8)
for kk in range(x.shape[0]):
# loop through nodes for each node
for ll in range(x.shape[0]):
if self.graph[kk,ll]:
temp_input[-1] = torch.cat([temp_input[-1],\
self.edge_model(x[ll]).unsqueeze(0)])
keys = temp_input[-1][:,-self.dim_h*2:-self.dim_h]
queries = temp_input[-1][:,-self.dim_h:]
attention = torch.zeros(1, keys.shape[0])
for mm in range(keys.shape[0]):
attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)
attention = torch.softmax(attention, dim=1)
my_input = torch.sum(attention.T \
* temp_input[-1][:,:self.ligand_dim],dim=0)
my_input = torch.cat([x[kk], my_input])
#this is where the cell gating would happen (TODO)
codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])
new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])
#self.decoder(codes[-1]).unsqueeze(0)])
if return_codes:
return codes, new_graph
else:
return new_graph
def get_actions(self, x):
if type(x) != torch.Tensor:
x = torch.Tensor(x)
my_template = x
for ii in range(self.number_updates):
x = self.forward(x, template=my_template)
x = torch.mean(x, dim=0)
x = self.action_layer(x)
return x
def get_params(self):
params = np.array([])
for param in self.edge_model.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
for param in self.encoder.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
# for param in self.decoder.named_parameters():
# params = np.append(params, param[1].detach().numpy().ravel())
for param in self.action_layer.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
return params
def set_params(self, my_params):
if my_params is None:
my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))
param_start = 0
for name, param in self.edge_model.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
for name, param in self.encoder.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
# for name, param in self.decoder.named_parameters():
#
# param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
#
# param[:] = torch.nn.Parameter(torch.Tensor(\
# my_params[param_start:param_stop].reshape(param.shape)))
for name, param in self.action_layer.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
def reset(self):
# initialize using gated cell states here later (maybe)
pass
class MLP(nn.Module):
def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):
super(MLP, self).__init__()
self.dim_in = dim_in
self.dim_act = dim_act
self.dim_h = 32
self.dropout = dropout
self.model_name = "DockRLMLP"
self.init_params()
def init_params(self):
self.model = nn.Sequential(\
nn.Linear(self.dim_in, self.dim_h),\
nn.ReLU(),\
nn.Linear(self.dim_h, self.dim_h),\
nn.ReLU(),\
nn.Dropout(p=self.dropout),\
nn.Linear(self.dim_h, self.dim_act)\
)
self.num_params = self.get_params().shape[0]
def forward(self, x):
x = torch.Tensor(x)
if len(x.shape) == 1:
x = x.unsqueeze(0)
x = self.model(x)
return x
def get_actions(self, x):
act = self.forward(x)
act = torch.mean(act, dim=0, keepdim=True)
return act
def get_params(self):
params = np.array([])
for param in self.model.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
return params
def set_params(self, my_params):
if my_params is None:
my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))
param_start = 0
for name, param in self.model.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
def reset(self):
pass
class MRNN(nn.Module):
def __init__(self, dim_in=6, dim_act=5):
super(MRNN, self).__init__()
self.dim_in = dim_in
self.dim_act = dim_act
self.dim_h = 8
self.init_params()
def init_params(self):
self.g = nn.Sequential(OrderedDict([\
("g", nn.Linear(self.dim_h+self.dim_in, self.dim_h)),\
("act_g", nn.Sigmoid())]))
self.j = nn.Sequential(OrderedDict([\
("j", nn.Linear(self.dim_h+self.dim_in, self.dim_h)),\
("act_j", nn.Tanh())]))
self.w_h2y = nn.Sequential(OrderedDict([\
("w_h2y", nn.Linear(self.dim_h, self.dim_act))]))
self.cell_state = torch.zeros((1,self.dim_h))
self.num_params = self.get_params().shape[0]
def forward(self, x):
x = torch.Tensor(x)
if len(x.shape) == 1:
x = x.unsqueeze(0)
x = torch.cat((self.cell_state, x), axis=-1)
g_out = self.g(x)
j_out = (1.0 - g_out) * self.j(x)
self.cell_state = g_out * self.cell_state + j_out
y = self.w_h2y(self.cell_state)
return y
def get_action(self, x):
act = self.forward(x)
return act.detach().cpu().numpy()
def get_params(self):
params = np.array([])
for param in self.g.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
for param in self.j.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
for param in self.w_h2y.named_parameters():
params = np.append(params, param[1].detach().numpy().ravel())
return params
def set_params(self, my_params):
if my_params is None:
my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))
param_start = 0
for name, param in self.g.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
for name, param in self.j.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
for name, param in self.w_h2y.named_parameters():
param_stop = param_start + reduce(lambda x,y: x*y, param.shape)
param[:] = torch.nn.Parameter(torch.Tensor(\
my_params[param_start:param_stop].reshape(param.shape)))
def reset(self):
self.cell_state *= 0.
if __name__ == "__main__":
mrnn = MRNN()
temp = mrnn.forward(np.random.randn(1,6))
print(temp)
|
normal
|
{
"blob_id": "1c1673b5e54bafef9f36a2583115f8135c112ab4",
"index": 1922,
"step-1": "<mask token>\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):\n super(GraphNN, self).__init__()\n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.dim_act = dim_act\n self.model_name = 'DockRLGraphNN'\n self.bond_cutoff = 3.6\n self.number_updates = 16\n self.dropout = dropout\n self.initialize_gnn()\n self.reset()\n my_params = self.get_params()\n self.num_params = my_params.shape[0]\n\n def initialize_gnn(self):\n self.edge_model = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_h), nn.\n LeakyReLU(), nn.Dropout(p=self.dropout), nn.Linear(self.dim_h, \n self.ligand_dim + 2 * self.dim_h))\n self.encoder = nn.Sequential(nn.Linear(2 * self.ligand_dim, self.\n ligand_dim), ArcTan())\n self.action_layer = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_act))\n\n def get_distance(self, node_0, node_1):\n return torch.sum(torch.sqrt(torch.abs(node_0 - node_1) ** 2))\n\n def build_graph(self, x):\n self.graph = torch.zeros(x.shape[0], x.shape[0])\n for ii in range(x.shape[0]):\n node_ii = x[ii, 0:3]\n for jj in range(x.shape[0]):\n node_jj = x[jj, 0:3]\n distance = self.get_distance(node_ii, node_jj)\n if distance <= self.bond_cutoff:\n self.graph[ii, jj] = 1.0\n self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))\n\n def forward(self, x, return_codes=False, template=None):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n if template is not None:\n self.build_graph(template.detach())\n else:\n self.build_graph(x.detach())\n new_graph = torch.Tensor()\n codes = torch.Tensor()\n temp_input = [torch.Tensor()]\n for kk in range(x.shape[0]):\n for ll in range(x.shape[0]):\n if self.graph[kk, ll]:\n temp_input[-1] = torch.cat([temp_input[-1], self.\n edge_model(x[ll]).unsqueeze(0)])\n keys = temp_input[-1][:, -self.dim_h * 2:-self.dim_h]\n queries = temp_input[-1][:, -self.dim_h:]\n attention = torch.zeros(1, keys.shape[0])\n for mm in range(keys.shape[0]):\n attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)\n attention = torch.softmax(attention, dim=1)\n my_input = torch.sum(attention.T * temp_input[-1][:, :self.\n ligand_dim], dim=0)\n my_input = torch.cat([x[kk], my_input])\n codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])\n new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])\n if return_codes:\n return codes, new_graph\n else:\n return new_graph\n\n def get_actions(self, x):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n my_template = x\n for ii in range(self.number_updates):\n x = self.forward(x, template=my_template)\n x = torch.mean(x, dim=0)\n x = self.action_layer(x)\n return x\n\n def get_params(self):\n params = np.array([])\n for param in self.edge_model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.encoder.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.action_layer.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.edge_model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.encoder.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.action_layer.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MLP(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):\n super(MLP, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 32\n self.dropout = dropout\n self.model_name = 'DockRLMLP'\n self.init_params()\n\n def init_params(self):\n self.model = nn.Sequential(nn.Linear(self.dim_in, self.dim_h), nn.\n ReLU(), nn.Linear(self.dim_h, self.dim_h), nn.ReLU(), nn.\n Dropout(p=self.dropout), nn.Linear(self.dim_h, self.dim_act))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = self.model(x)\n return x\n\n def get_actions(self, x):\n act = self.forward(x)\n act = torch.mean(act, dim=0, keepdim=True)\n return act\n\n def get_params(self):\n params = np.array([])\n for param in self.model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MRNN(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5):\n super(MRNN, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 8\n self.init_params()\n\n def init_params(self):\n self.g = nn.Sequential(OrderedDict([('g', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_g', nn.Sigmoid())]))\n self.j = nn.Sequential(OrderedDict([('j', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_j', nn.Tanh())]))\n self.w_h2y = nn.Sequential(OrderedDict([('w_h2y', nn.Linear(self.\n dim_h, self.dim_act))]))\n self.cell_state = torch.zeros((1, self.dim_h))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = torch.cat((self.cell_state, x), axis=-1)\n g_out = self.g(x)\n j_out = (1.0 - g_out) * self.j(x)\n self.cell_state = g_out * self.cell_state + j_out\n y = self.w_h2y(self.cell_state)\n return y\n\n def get_action(self, x):\n act = self.forward(x)\n return act.detach().cpu().numpy()\n\n def get_params(self):\n params = np.array([])\n for param in self.g.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.j.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.w_h2y.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.g.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.j.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.w_h2y.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n self.cell_state *= 0.0\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Params:\n <mask token>\n\n def init_params(self):\n self.params = np.random.randn(self.dim_act)\n self.num_params = self.dim_act\n\n def forward(self, obs):\n return self.get_params()\n\n def get_params(self):\n return self.params\n <mask token>\n\n def reset(self):\n pass\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):\n super(GraphNN, self).__init__()\n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.dim_act = dim_act\n self.model_name = 'DockRLGraphNN'\n self.bond_cutoff = 3.6\n self.number_updates = 16\n self.dropout = dropout\n self.initialize_gnn()\n self.reset()\n my_params = self.get_params()\n self.num_params = my_params.shape[0]\n\n def initialize_gnn(self):\n self.edge_model = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_h), nn.\n LeakyReLU(), nn.Dropout(p=self.dropout), nn.Linear(self.dim_h, \n self.ligand_dim + 2 * self.dim_h))\n self.encoder = nn.Sequential(nn.Linear(2 * self.ligand_dim, self.\n ligand_dim), ArcTan())\n self.action_layer = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_act))\n\n def get_distance(self, node_0, node_1):\n return torch.sum(torch.sqrt(torch.abs(node_0 - node_1) ** 2))\n\n def build_graph(self, x):\n self.graph = torch.zeros(x.shape[0], x.shape[0])\n for ii in range(x.shape[0]):\n node_ii = x[ii, 0:3]\n for jj in range(x.shape[0]):\n node_jj = x[jj, 0:3]\n distance = self.get_distance(node_ii, node_jj)\n if distance <= self.bond_cutoff:\n self.graph[ii, jj] = 1.0\n self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))\n\n def forward(self, x, return_codes=False, template=None):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n if template is not None:\n self.build_graph(template.detach())\n else:\n self.build_graph(x.detach())\n new_graph = torch.Tensor()\n codes = torch.Tensor()\n temp_input = [torch.Tensor()]\n for kk in range(x.shape[0]):\n for ll in range(x.shape[0]):\n if self.graph[kk, ll]:\n temp_input[-1] = torch.cat([temp_input[-1], self.\n edge_model(x[ll]).unsqueeze(0)])\n keys = temp_input[-1][:, -self.dim_h * 2:-self.dim_h]\n queries = temp_input[-1][:, -self.dim_h:]\n attention = torch.zeros(1, keys.shape[0])\n for mm in range(keys.shape[0]):\n attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)\n attention = torch.softmax(attention, dim=1)\n my_input = torch.sum(attention.T * temp_input[-1][:, :self.\n ligand_dim], dim=0)\n my_input = torch.cat([x[kk], my_input])\n codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])\n new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])\n if return_codes:\n return codes, new_graph\n else:\n return new_graph\n\n def get_actions(self, x):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n my_template = x\n for ii in range(self.number_updates):\n x = self.forward(x, template=my_template)\n x = torch.mean(x, dim=0)\n x = self.action_layer(x)\n return x\n\n def get_params(self):\n params = np.array([])\n for param in self.edge_model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.encoder.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.action_layer.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.edge_model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.encoder.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.action_layer.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MLP(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):\n super(MLP, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 32\n self.dropout = dropout\n self.model_name = 'DockRLMLP'\n self.init_params()\n\n def init_params(self):\n self.model = nn.Sequential(nn.Linear(self.dim_in, self.dim_h), nn.\n ReLU(), nn.Linear(self.dim_h, self.dim_h), nn.ReLU(), nn.\n Dropout(p=self.dropout), nn.Linear(self.dim_h, self.dim_act))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = self.model(x)\n return x\n\n def get_actions(self, x):\n act = self.forward(x)\n act = torch.mean(act, dim=0, keepdim=True)\n return act\n\n def get_params(self):\n params = np.array([])\n for param in self.model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MRNN(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5):\n super(MRNN, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 8\n self.init_params()\n\n def init_params(self):\n self.g = nn.Sequential(OrderedDict([('g', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_g', nn.Sigmoid())]))\n self.j = nn.Sequential(OrderedDict([('j', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_j', nn.Tanh())]))\n self.w_h2y = nn.Sequential(OrderedDict([('w_h2y', nn.Linear(self.\n dim_h, self.dim_act))]))\n self.cell_state = torch.zeros((1, self.dim_h))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = torch.cat((self.cell_state, x), axis=-1)\n g_out = self.g(x)\n j_out = (1.0 - g_out) * self.j(x)\n self.cell_state = g_out * self.cell_state + j_out\n y = self.w_h2y(self.cell_state)\n return y\n\n def get_action(self, x):\n act = self.forward(x)\n return act.detach().cpu().numpy()\n\n def get_params(self):\n params = np.array([])\n for param in self.g.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.j.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.w_h2y.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.g.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.j.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.w_h2y.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n self.cell_state *= 0.0\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass ArcTan(nn.Module):\n <mask token>\n <mask token>\n\n\nclass Params:\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=0, dropout=0.0):\n self.dim_act = dim_act\n self.dim_in = 0\n self.dim_h = 0\n self.dropout = 0.0\n self.model_name = 'DockRLParams'\n self.init_params()\n self.act = ArcTan()\n\n def init_params(self):\n self.params = np.random.randn(self.dim_act)\n self.num_params = self.dim_act\n\n def forward(self, obs):\n return self.get_params()\n\n def get_params(self):\n return self.params\n\n def set_params(self, params):\n assert params.shape == self.params.shape\n self.params = params\n\n def reset(self):\n pass\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):\n super(GraphNN, self).__init__()\n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.dim_act = dim_act\n self.model_name = 'DockRLGraphNN'\n self.bond_cutoff = 3.6\n self.number_updates = 16\n self.dropout = dropout\n self.initialize_gnn()\n self.reset()\n my_params = self.get_params()\n self.num_params = my_params.shape[0]\n\n def initialize_gnn(self):\n self.edge_model = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_h), nn.\n LeakyReLU(), nn.Dropout(p=self.dropout), nn.Linear(self.dim_h, \n self.ligand_dim + 2 * self.dim_h))\n self.encoder = nn.Sequential(nn.Linear(2 * self.ligand_dim, self.\n ligand_dim), ArcTan())\n self.action_layer = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_act))\n\n def get_distance(self, node_0, node_1):\n return torch.sum(torch.sqrt(torch.abs(node_0 - node_1) ** 2))\n\n def build_graph(self, x):\n self.graph = torch.zeros(x.shape[0], x.shape[0])\n for ii in range(x.shape[0]):\n node_ii = x[ii, 0:3]\n for jj in range(x.shape[0]):\n node_jj = x[jj, 0:3]\n distance = self.get_distance(node_ii, node_jj)\n if distance <= self.bond_cutoff:\n self.graph[ii, jj] = 1.0\n self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))\n\n def forward(self, x, return_codes=False, template=None):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n if template is not None:\n self.build_graph(template.detach())\n else:\n self.build_graph(x.detach())\n new_graph = torch.Tensor()\n codes = torch.Tensor()\n temp_input = [torch.Tensor()]\n for kk in range(x.shape[0]):\n for ll in range(x.shape[0]):\n if self.graph[kk, ll]:\n temp_input[-1] = torch.cat([temp_input[-1], self.\n edge_model(x[ll]).unsqueeze(0)])\n keys = temp_input[-1][:, -self.dim_h * 2:-self.dim_h]\n queries = temp_input[-1][:, -self.dim_h:]\n attention = torch.zeros(1, keys.shape[0])\n for mm in range(keys.shape[0]):\n attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)\n attention = torch.softmax(attention, dim=1)\n my_input = torch.sum(attention.T * temp_input[-1][:, :self.\n ligand_dim], dim=0)\n my_input = torch.cat([x[kk], my_input])\n codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])\n new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])\n if return_codes:\n return codes, new_graph\n else:\n return new_graph\n\n def get_actions(self, x):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n my_template = x\n for ii in range(self.number_updates):\n x = self.forward(x, template=my_template)\n x = torch.mean(x, dim=0)\n x = self.action_layer(x)\n return x\n\n def get_params(self):\n params = np.array([])\n for param in self.edge_model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.encoder.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.action_layer.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.edge_model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.encoder.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.action_layer.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MLP(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):\n super(MLP, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 32\n self.dropout = dropout\n self.model_name = 'DockRLMLP'\n self.init_params()\n\n def init_params(self):\n self.model = nn.Sequential(nn.Linear(self.dim_in, self.dim_h), nn.\n ReLU(), nn.Linear(self.dim_h, self.dim_h), nn.ReLU(), nn.\n Dropout(p=self.dropout), nn.Linear(self.dim_h, self.dim_act))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = self.model(x)\n return x\n\n def get_actions(self, x):\n act = self.forward(x)\n act = torch.mean(act, dim=0, keepdim=True)\n return act\n\n def get_params(self):\n params = np.array([])\n for param in self.model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MRNN(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5):\n super(MRNN, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 8\n self.init_params()\n\n def init_params(self):\n self.g = nn.Sequential(OrderedDict([('g', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_g', nn.Sigmoid())]))\n self.j = nn.Sequential(OrderedDict([('j', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_j', nn.Tanh())]))\n self.w_h2y = nn.Sequential(OrderedDict([('w_h2y', nn.Linear(self.\n dim_h, self.dim_act))]))\n self.cell_state = torch.zeros((1, self.dim_h))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = torch.cat((self.cell_state, x), axis=-1)\n g_out = self.g(x)\n j_out = (1.0 - g_out) * self.j(x)\n self.cell_state = g_out * self.cell_state + j_out\n y = self.w_h2y(self.cell_state)\n return y\n\n def get_action(self, x):\n act = self.forward(x)\n return act.detach().cpu().numpy()\n\n def get_params(self):\n params = np.array([])\n for param in self.g.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.j.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.w_h2y.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.g.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.j.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.w_h2y.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n self.cell_state *= 0.0\n\n\n<mask token>\n",
"step-4": "<mask token>\n\n\nclass ArcTan(nn.Module):\n\n def __init__(self):\n super(ArcTan, self).__init__()\n <mask token>\n\n\nclass Params:\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=0, dropout=0.0):\n self.dim_act = dim_act\n self.dim_in = 0\n self.dim_h = 0\n self.dropout = 0.0\n self.model_name = 'DockRLParams'\n self.init_params()\n self.act = ArcTan()\n\n def init_params(self):\n self.params = np.random.randn(self.dim_act)\n self.num_params = self.dim_act\n\n def forward(self, obs):\n return self.get_params()\n\n def get_params(self):\n return self.params\n\n def set_params(self, params):\n assert params.shape == self.params.shape\n self.params = params\n\n def reset(self):\n pass\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):\n super(GraphNN, self).__init__()\n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.dim_act = dim_act\n self.model_name = 'DockRLGraphNN'\n self.bond_cutoff = 3.6\n self.number_updates = 16\n self.dropout = dropout\n self.initialize_gnn()\n self.reset()\n my_params = self.get_params()\n self.num_params = my_params.shape[0]\n\n def initialize_gnn(self):\n self.edge_model = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_h), nn.\n LeakyReLU(), nn.Dropout(p=self.dropout), nn.Linear(self.dim_h, \n self.ligand_dim + 2 * self.dim_h))\n self.encoder = nn.Sequential(nn.Linear(2 * self.ligand_dim, self.\n ligand_dim), ArcTan())\n self.action_layer = nn.Sequential(nn.Linear(self.ligand_dim, self.\n dim_h), nn.LeakyReLU(), nn.Linear(self.dim_h, self.dim_act))\n\n def get_distance(self, node_0, node_1):\n return torch.sum(torch.sqrt(torch.abs(node_0 - node_1) ** 2))\n\n def build_graph(self, x):\n self.graph = torch.zeros(x.shape[0], x.shape[0])\n for ii in range(x.shape[0]):\n node_ii = x[ii, 0:3]\n for jj in range(x.shape[0]):\n node_jj = x[jj, 0:3]\n distance = self.get_distance(node_ii, node_jj)\n if distance <= self.bond_cutoff:\n self.graph[ii, jj] = 1.0\n self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))\n\n def forward(self, x, return_codes=False, template=None):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n if template is not None:\n self.build_graph(template.detach())\n else:\n self.build_graph(x.detach())\n new_graph = torch.Tensor()\n codes = torch.Tensor()\n temp_input = [torch.Tensor()]\n for kk in range(x.shape[0]):\n for ll in range(x.shape[0]):\n if self.graph[kk, ll]:\n temp_input[-1] = torch.cat([temp_input[-1], self.\n edge_model(x[ll]).unsqueeze(0)])\n keys = temp_input[-1][:, -self.dim_h * 2:-self.dim_h]\n queries = temp_input[-1][:, -self.dim_h:]\n attention = torch.zeros(1, keys.shape[0])\n for mm in range(keys.shape[0]):\n attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)\n attention = torch.softmax(attention, dim=1)\n my_input = torch.sum(attention.T * temp_input[-1][:, :self.\n ligand_dim], dim=0)\n my_input = torch.cat([x[kk], my_input])\n codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])\n new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])\n if return_codes:\n return codes, new_graph\n else:\n return new_graph\n\n def get_actions(self, x):\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n my_template = x\n for ii in range(self.number_updates):\n x = self.forward(x, template=my_template)\n x = torch.mean(x, dim=0)\n x = self.action_layer(x)\n return x\n\n def get_params(self):\n params = np.array([])\n for param in self.edge_model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.encoder.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.action_layer.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.edge_model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.encoder.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.action_layer.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MLP(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):\n super(MLP, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 32\n self.dropout = dropout\n self.model_name = 'DockRLMLP'\n self.init_params()\n\n def init_params(self):\n self.model = nn.Sequential(nn.Linear(self.dim_in, self.dim_h), nn.\n ReLU(), nn.Linear(self.dim_h, self.dim_h), nn.ReLU(), nn.\n Dropout(p=self.dropout), nn.Linear(self.dim_h, self.dim_act))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = self.model(x)\n return x\n\n def get_actions(self, x):\n act = self.forward(x)\n act = torch.mean(act, dim=0, keepdim=True)\n return act\n\n def get_params(self):\n params = np.array([])\n for param in self.model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.model.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\n\nclass MRNN(nn.Module):\n\n def __init__(self, dim_in=6, dim_act=5):\n super(MRNN, self).__init__()\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 8\n self.init_params()\n\n def init_params(self):\n self.g = nn.Sequential(OrderedDict([('g', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_g', nn.Sigmoid())]))\n self.j = nn.Sequential(OrderedDict([('j', nn.Linear(self.dim_h +\n self.dim_in, self.dim_h)), ('act_j', nn.Tanh())]))\n self.w_h2y = nn.Sequential(OrderedDict([('w_h2y', nn.Linear(self.\n dim_h, self.dim_act))]))\n self.cell_state = torch.zeros((1, self.dim_h))\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n x = torch.Tensor(x)\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n x = torch.cat((self.cell_state, x), axis=-1)\n g_out = self.g(x)\n j_out = (1.0 - g_out) * self.j(x)\n self.cell_state = g_out * self.cell_state + j_out\n y = self.w_h2y(self.cell_state)\n return y\n\n def get_action(self, x):\n act = self.forward(x)\n return act.detach().cpu().numpy()\n\n def get_params(self):\n params = np.array([])\n for param in self.g.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.j.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n for param in self.w_h2y.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n return params\n\n def set_params(self, my_params):\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params\n ) * torch.sqrt(torch.tensor(self.var))\n param_start = 0\n for name, param in self.g.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.j.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n for name, param in self.w_h2y.named_parameters():\n param_stop = param_start + reduce(lambda x, y: x * y, param.shape)\n param[:] = torch.nn.Parameter(torch.Tensor(my_params[\n param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n self.cell_state *= 0.0\n\n\n<mask token>\n",
"step-5": "import torch \nimport torch.nn as nn\nimport torch.nn.functional as F\n\nimport numpy as np\n\nfrom collections import OrderedDict\nfrom functools import reduce\n\nclass ArcTan(nn.Module):\n\n def __init__(self):\n super(ArcTan,self).__init__()\n\n def forward(self, x):\n\n return torch.arctan(x) / 1.5708\n\nclass Params():\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=0, dropout=0.0):\n \n self.dim_act = dim_act\n self.dim_in = 0\n self.dim_h = 0\n self.dropout = 0.0\n self.model_name = \"DockRLParams\"\n\n self.init_params()\n self.act = ArcTan()\n\n def init_params(self):\n\n self.params = np.random.randn(self.dim_act)\n self.num_params = self.dim_act\n\n def forward(self, obs):\n return self.get_params()\n\n def get_params(self):\n return self.params\n\n def set_params(self, params):\n assert params.shape == self.params.shape\n\n self.params = params \n\n def reset(self):\n pass\n\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.00):\n super(GraphNN, self).__init__()\n \n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.dim_act = dim_act\n self.model_name = \"DockRLGraphNN\"\n # This is a guesstimate based on: \n # https://pymolwiki.org/index.php/Displaying_Biochemical_Properties\n self.bond_cutoff = 3.6\n self.number_updates = 16\n self.dropout = dropout\n\n self.initialize_gnn()\n self.reset()\n\n my_params = self.get_params()\n self.num_params = my_params.shape[0]\n\n def initialize_gnn(self):\n\n # vertices MLP, with 8 element key and query vectors for self-attention\n self.edge_model = nn.Sequential(\\\n nn.Linear(self.ligand_dim, self.dim_h),\\\n nn.LeakyReLU(),\\\n nn.Linear(self.dim_h, self.dim_h),\\\n nn.LeakyReLU(),\\\n nn.Dropout(p=self.dropout),\\\n nn.Linear(self.dim_h, self.ligand_dim + 2 * self.dim_h)\n )\n\n self.encoder = nn.Sequential(\\\n nn.Linear(2*self.ligand_dim, self.ligand_dim),\\\n ArcTan()\n )\n\n self.action_layer = nn.Sequential(\\\n nn.Linear(self.ligand_dim, self.dim_h),\\\n nn.LeakyReLU(),\\\n nn.Linear(self.dim_h, self.dim_act)\\\n )\n \n def get_distance(self, node_0, node_1):\n\n return torch.sum(torch.sqrt(torch.abs(node_0 - node_1)**2))\n\n def build_graph(self, x):\n\n self.graph = torch.zeros(x.shape[0],x.shape[0])\n\n for ii in range(x.shape[0]):\n node_ii = x[ii, 0:3]\n for jj in range(x.shape[0]):\n node_jj = x[jj, 0:3]\n\n distance = self.get_distance(node_ii, node_jj)\n if distance <= self.bond_cutoff:\n self.graph[ii, jj] = 1.0\n \n self.graph = self.graph * (1 - torch.eye(self.graph.shape[0]))\n\n def forward(self, x, return_codes=False, template=None):\n\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n\n if template is not None:\n self.build_graph(template.detach())\n else:\n self.build_graph(x.detach())\n \n new_graph = torch.Tensor() #torch.zeros_like(x)\n codes = torch.Tensor() #torch.zeros(x.shape[0], self.dim_h)\n temp_input = [torch.Tensor()] \n #orch.Tensor() #torch.zeros(x.shape[0], self.dim_h+8+8)\n\n\n for kk in range(x.shape[0]):\n # loop through nodes for each node\n for ll in range(x.shape[0]):\n if self.graph[kk,ll]:\n temp_input[-1] = torch.cat([temp_input[-1],\\\n self.edge_model(x[ll]).unsqueeze(0)])\n\n keys = temp_input[-1][:,-self.dim_h*2:-self.dim_h]\n queries = temp_input[-1][:,-self.dim_h:]\n\n attention = torch.zeros(1, keys.shape[0])\n\n for mm in range(keys.shape[0]):\n attention[:, mm] = torch.matmul(queries[mm], keys[mm].T)\n\n attention = torch.softmax(attention, dim=1)\n\n my_input = torch.sum(attention.T \\\n * temp_input[-1][:,:self.ligand_dim],dim=0)\n my_input = torch.cat([x[kk], my_input])\n\n #this is where the cell gating would happen (TODO)\n codes = torch.cat([codes, self.encoder(my_input).unsqueeze(0)])\n\n new_graph = torch.cat([new_graph, codes[-1].unsqueeze(0)])\n #self.decoder(codes[-1]).unsqueeze(0)])\n\n\n if return_codes:\n return codes, new_graph\n else:\n return new_graph\n\n\n def get_actions(self, x):\n\n if type(x) != torch.Tensor:\n x = torch.Tensor(x)\n\n my_template = x\n\n for ii in range(self.number_updates):\n x = self.forward(x, template=my_template)\n\n x = torch.mean(x, dim=0)\n\n x = self.action_layer(x)\n\n return x\n\n def get_params(self):\n params = np.array([])\n\n for param in self.edge_model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n for param in self.encoder.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n# for param in self.decoder.named_parameters():\n# params = np.append(params, param[1].detach().numpy().ravel())\n\n for param in self.action_layer.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n return params\n\n def set_params(self, my_params):\n\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))\n\n param_start = 0\n for name, param in self.edge_model.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n for name, param in self.encoder.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n# for name, param in self.decoder.named_parameters():\n#\n# param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n#\n# param[:] = torch.nn.Parameter(torch.Tensor(\\\n# my_params[param_start:param_stop].reshape(param.shape)))\n\n for name, param in self.action_layer.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n # initialize using gated cell states here later (maybe)\n pass\n\nclass MLP(nn.Module):\n def __init__(self, dim_in=6, dim_act=5, dim_h=32, dropout=0.0):\n super(MLP, self).__init__()\n\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 32\n self.dropout = dropout\n self.model_name = \"DockRLMLP\"\n\n self.init_params()\n\n def init_params(self):\n\n self.model = nn.Sequential(\\\n nn.Linear(self.dim_in, self.dim_h),\\\n nn.ReLU(),\\\n nn.Linear(self.dim_h, self.dim_h),\\\n nn.ReLU(),\\\n nn.Dropout(p=self.dropout),\\\n nn.Linear(self.dim_h, self.dim_act)\\\n )\n\n self.num_params = self.get_params().shape[0]\n\n def forward(self, x):\n\n x = torch.Tensor(x)\n\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n\n\n x = self.model(x)\n\n\n return x\n\n def get_actions(self, x):\n\n act = self.forward(x)\n act = torch.mean(act, dim=0, keepdim=True)\n return act\n\n def get_params(self):\n params = np.array([])\n\n for param in self.model.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n return params\n\n def set_params(self, my_params):\n\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))\n\n param_start = 0\n for name, param in self.model.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n pass\n\nclass MRNN(nn.Module):\n def __init__(self, dim_in=6, dim_act=5):\n super(MRNN, self).__init__()\n\n self.dim_in = dim_in\n self.dim_act = dim_act\n self.dim_h = 8\n\n self.init_params()\n\n\n def init_params(self):\n\n self.g = nn.Sequential(OrderedDict([\\\n (\"g\", nn.Linear(self.dim_h+self.dim_in, self.dim_h)),\\\n (\"act_g\", nn.Sigmoid())]))\n\n self.j = nn.Sequential(OrderedDict([\\\n (\"j\", nn.Linear(self.dim_h+self.dim_in, self.dim_h)),\\\n (\"act_j\", nn.Tanh())]))\n\n self.w_h2y = nn.Sequential(OrderedDict([\\\n (\"w_h2y\", nn.Linear(self.dim_h, self.dim_act))]))\n\n self.cell_state = torch.zeros((1,self.dim_h))\n\n self.num_params = self.get_params().shape[0]\n \n def forward(self, x):\n \n x = torch.Tensor(x)\n\n if len(x.shape) == 1:\n x = x.unsqueeze(0)\n\n x = torch.cat((self.cell_state, x), axis=-1)\n\n g_out = self.g(x) \n\n j_out = (1.0 - g_out) * self.j(x)\n\n self.cell_state = g_out * self.cell_state + j_out\n\n y = self.w_h2y(self.cell_state) \n\n return y\n \n def get_action(self, x):\n\n act = self.forward(x)\n return act.detach().cpu().numpy()\n\n def get_params(self):\n params = np.array([])\n\n for param in self.g.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n for param in self.j.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n for param in self.w_h2y.named_parameters():\n params = np.append(params, param[1].detach().numpy().ravel())\n\n return params\n\n def set_params(self, my_params):\n\n if my_params is None:\n my_params = self.init_mean + torch.randn(self.num_params) * torch.sqrt(torch.tensor(self.var))\n\n param_start = 0\n for name, param in self.g.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n for name, param in self.j.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n for name, param in self.w_h2y.named_parameters():\n\n param_stop = param_start + reduce(lambda x,y: x*y, param.shape)\n\n param[:] = torch.nn.Parameter(torch.Tensor(\\\n my_params[param_start:param_stop].reshape(param.shape)))\n\n def reset(self):\n self.cell_state *= 0. \n\n\nif __name__ == \"__main__\":\n\n mrnn = MRNN()\n\n temp = mrnn.forward(np.random.randn(1,6))\n print(temp)\n",
"step-ids": [
26,
31,
34,
35,
39
]
}
|
[
26,
31,
34,
35,
39
] |
import os, re
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': ':memory:'
}
}
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.admin',
'django.contrib.sessions',
'django.contrib.contenttypes',
'django.contrib.sites',
'maintenancemode',
)
MIDDLEWARE = (
'django.contrib.sessions.middleware.SessionMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'maintenancemode.middleware.MaintenanceModeMiddleware',
)
ROOT_URLCONF = 'maintenancemode.tests'
SITE_ID = 1
MAINTENANCE_MODE = True # or ``False`` and use ``maintenance`` command
MAINTENANCE_IGNORE_URLS = (
re.compile(r'^/ignored.*'),
)
|
normal
|
{
"blob_id": "34ecf2bd9bc72a98aba4584880a198dd24899dbe",
"index": 6218,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nDATABASES = {'default': {'ENGINE': 'django.db.backends.sqlite3', 'NAME':\n ':memory:'}}\nINSTALLED_APPS = ('django.contrib.auth', 'django.contrib.admin',\n 'django.contrib.sessions', 'django.contrib.contenttypes',\n 'django.contrib.sites', 'maintenancemode')\nMIDDLEWARE = ('django.contrib.sessions.middleware.SessionMiddleware',\n 'django.contrib.auth.middleware.AuthenticationMiddleware',\n 'maintenancemode.middleware.MaintenanceModeMiddleware')\nROOT_URLCONF = 'maintenancemode.tests'\nSITE_ID = 1\nMAINTENANCE_MODE = True\nMAINTENANCE_IGNORE_URLS = re.compile('^/ignored.*'),\n",
"step-3": "import os, re\nDATABASES = {'default': {'ENGINE': 'django.db.backends.sqlite3', 'NAME':\n ':memory:'}}\nINSTALLED_APPS = ('django.contrib.auth', 'django.contrib.admin',\n 'django.contrib.sessions', 'django.contrib.contenttypes',\n 'django.contrib.sites', 'maintenancemode')\nMIDDLEWARE = ('django.contrib.sessions.middleware.SessionMiddleware',\n 'django.contrib.auth.middleware.AuthenticationMiddleware',\n 'maintenancemode.middleware.MaintenanceModeMiddleware')\nROOT_URLCONF = 'maintenancemode.tests'\nSITE_ID = 1\nMAINTENANCE_MODE = True\nMAINTENANCE_IGNORE_URLS = re.compile('^/ignored.*'),\n",
"step-4": "import os, re\n\nDATABASES = {\n 'default': {\n 'ENGINE': 'django.db.backends.sqlite3',\n 'NAME': ':memory:'\n }\n}\n\nINSTALLED_APPS = (\n 'django.contrib.auth',\n 'django.contrib.admin',\n 'django.contrib.sessions',\n 'django.contrib.contenttypes',\n 'django.contrib.sites',\n\n 'maintenancemode',\n)\n\nMIDDLEWARE = (\n 'django.contrib.sessions.middleware.SessionMiddleware',\n 'django.contrib.auth.middleware.AuthenticationMiddleware',\n\n 'maintenancemode.middleware.MaintenanceModeMiddleware',\n)\n\nROOT_URLCONF = 'maintenancemode.tests'\n\nSITE_ID = 1\n\nMAINTENANCE_MODE = True # or ``False`` and use ``maintenance`` command\nMAINTENANCE_IGNORE_URLS = (\n re.compile(r'^/ignored.*'),\n)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
import os
my_home = os.popen("echo $MYWORK_DIR").readlines()[0][:-1]
import numpy
from sys import path, argv
path.append("D:/Github/astrophy-research/mylib")
path.append("D:/Github/astrophy-research/multi_shear_detect")
path.append('%s/work/mylib' % my_home)
from Fourier_Quad import Fourier_Quad
# import h5py
# from plot_tool import Image_Plot
import tool_box
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
numprocs = comm.Get_size()
source_num = int(argv[1])*10000
sigma_1 = float(argv[2])
sigma_2 = float(argv[3])
signal_num = numprocs
signals = numpy.linspace(-0.05, 0.05, signal_num)
itemsize = MPI.DOUBLE.Get_size()
if rank == 0:
# bytes for 10 double elements
nbytes = 2*signal_num*itemsize
else:
nbytes = 0
# on rank 0 of comm, create the contiguous shared block
win1 = MPI.Win.Allocate_shared(nbytes, itemsize, comm=comm)
buf1, itemsize = win1.Shared_query(0)
result = numpy.ndarray(buffer=buf1, dtype='d', shape=(2, signal_num)) # array filled with zero
fq = Fourier_Quad(12,123)
n = numpy.ones((source_num, ))
# for i in range(signal_num):
source = numpy.random.normal(signals[rank], sigma_1, source_num) + numpy.random.normal(-signals[rank]/100, sigma_2, source_num)
signal_est = fq.find_shear(source, n, 8,scale=100, left=-0.08, right=0.08)[:2]
result[:, rank] = signal_est
print(rank, signal_est)
comm.Barrier()
if rank == 0:
# result[2] = signals
print(signals)
print(result)
mc = numpy.array(tool_box.data_fit(signals, result[0], result[1]))
mc[0] = mc[0] - 1
print(mc)
# img = Image_Plot()
# img.subplots(1,1)
# img.axs[0][0].errorbar(signals, result[0], result[1])
# img.axs[0][0].plot([-0.06,0.06],[-0.06, 0.06])
# img.show_img()
|
normal
|
{
"blob_id": "1ffdc2845bc503c0a30407de444a152f8cc68d57",
"index": 1370,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npath.append('D:/Github/astrophy-research/mylib')\npath.append('D:/Github/astrophy-research/multi_shear_detect')\npath.append('%s/work/mylib' % my_home)\n<mask token>\nif rank == 0:\n nbytes = 2 * signal_num * itemsize\nelse:\n nbytes = 0\n<mask token>\nprint(rank, signal_est)\ncomm.Barrier()\nif rank == 0:\n print(signals)\n print(result)\n mc = numpy.array(tool_box.data_fit(signals, result[0], result[1]))\n mc[0] = mc[0] - 1\n print(mc)\n",
"step-3": "<mask token>\nmy_home = os.popen('echo $MYWORK_DIR').readlines()[0][:-1]\n<mask token>\npath.append('D:/Github/astrophy-research/mylib')\npath.append('D:/Github/astrophy-research/multi_shear_detect')\npath.append('%s/work/mylib' % my_home)\n<mask token>\ncomm = MPI.COMM_WORLD\nrank = comm.Get_rank()\nnumprocs = comm.Get_size()\nsource_num = int(argv[1]) * 10000\nsigma_1 = float(argv[2])\nsigma_2 = float(argv[3])\nsignal_num = numprocs\nsignals = numpy.linspace(-0.05, 0.05, signal_num)\nitemsize = MPI.DOUBLE.Get_size()\nif rank == 0:\n nbytes = 2 * signal_num * itemsize\nelse:\n nbytes = 0\nwin1 = MPI.Win.Allocate_shared(nbytes, itemsize, comm=comm)\nbuf1, itemsize = win1.Shared_query(0)\nresult = numpy.ndarray(buffer=buf1, dtype='d', shape=(2, signal_num))\nfq = Fourier_Quad(12, 123)\nn = numpy.ones((source_num,))\nsource = numpy.random.normal(signals[rank], sigma_1, source_num\n ) + numpy.random.normal(-signals[rank] / 100, sigma_2, source_num)\nsignal_est = fq.find_shear(source, n, 8, scale=100, left=-0.08, right=0.08)[:2]\nresult[:, rank] = signal_est\nprint(rank, signal_est)\ncomm.Barrier()\nif rank == 0:\n print(signals)\n print(result)\n mc = numpy.array(tool_box.data_fit(signals, result[0], result[1]))\n mc[0] = mc[0] - 1\n print(mc)\n",
"step-4": "import os\nmy_home = os.popen('echo $MYWORK_DIR').readlines()[0][:-1]\nimport numpy\nfrom sys import path, argv\npath.append('D:/Github/astrophy-research/mylib')\npath.append('D:/Github/astrophy-research/multi_shear_detect')\npath.append('%s/work/mylib' % my_home)\nfrom Fourier_Quad import Fourier_Quad\nimport tool_box\nfrom mpi4py import MPI\ncomm = MPI.COMM_WORLD\nrank = comm.Get_rank()\nnumprocs = comm.Get_size()\nsource_num = int(argv[1]) * 10000\nsigma_1 = float(argv[2])\nsigma_2 = float(argv[3])\nsignal_num = numprocs\nsignals = numpy.linspace(-0.05, 0.05, signal_num)\nitemsize = MPI.DOUBLE.Get_size()\nif rank == 0:\n nbytes = 2 * signal_num * itemsize\nelse:\n nbytes = 0\nwin1 = MPI.Win.Allocate_shared(nbytes, itemsize, comm=comm)\nbuf1, itemsize = win1.Shared_query(0)\nresult = numpy.ndarray(buffer=buf1, dtype='d', shape=(2, signal_num))\nfq = Fourier_Quad(12, 123)\nn = numpy.ones((source_num,))\nsource = numpy.random.normal(signals[rank], sigma_1, source_num\n ) + numpy.random.normal(-signals[rank] / 100, sigma_2, source_num)\nsignal_est = fq.find_shear(source, n, 8, scale=100, left=-0.08, right=0.08)[:2]\nresult[:, rank] = signal_est\nprint(rank, signal_est)\ncomm.Barrier()\nif rank == 0:\n print(signals)\n print(result)\n mc = numpy.array(tool_box.data_fit(signals, result[0], result[1]))\n mc[0] = mc[0] - 1\n print(mc)\n",
"step-5": "import os\nmy_home = os.popen(\"echo $MYWORK_DIR\").readlines()[0][:-1]\nimport numpy\nfrom sys import path, argv\npath.append(\"D:/Github/astrophy-research/mylib\")\npath.append(\"D:/Github/astrophy-research/multi_shear_detect\")\npath.append('%s/work/mylib' % my_home)\nfrom Fourier_Quad import Fourier_Quad\n# import h5py\n# from plot_tool import Image_Plot\nimport tool_box\nfrom mpi4py import MPI\n\ncomm = MPI.COMM_WORLD\nrank = comm.Get_rank()\nnumprocs = comm.Get_size()\n\nsource_num = int(argv[1])*10000\nsigma_1 = float(argv[2])\nsigma_2 = float(argv[3])\nsignal_num = numprocs\nsignals = numpy.linspace(-0.05, 0.05, signal_num)\n\nitemsize = MPI.DOUBLE.Get_size()\nif rank == 0:\n # bytes for 10 double elements\n nbytes = 2*signal_num*itemsize\nelse:\n nbytes = 0\n\n# on rank 0 of comm, create the contiguous shared block\nwin1 = MPI.Win.Allocate_shared(nbytes, itemsize, comm=comm)\nbuf1, itemsize = win1.Shared_query(0)\nresult = numpy.ndarray(buffer=buf1, dtype='d', shape=(2, signal_num)) # array filled with zero\n\nfq = Fourier_Quad(12,123)\nn = numpy.ones((source_num, ))\n# for i in range(signal_num):\nsource = numpy.random.normal(signals[rank], sigma_1, source_num) + numpy.random.normal(-signals[rank]/100, sigma_2, source_num)\nsignal_est = fq.find_shear(source, n, 8,scale=100, left=-0.08, right=0.08)[:2]\nresult[:, rank] = signal_est\nprint(rank, signal_est)\ncomm.Barrier()\nif rank == 0:\n # result[2] = signals\n print(signals)\n print(result)\n mc = numpy.array(tool_box.data_fit(signals, result[0], result[1]))\n mc[0] = mc[0] - 1\n print(mc)\n# img = Image_Plot()\n# img.subplots(1,1)\n# img.axs[0][0].errorbar(signals, result[0], result[1])\n# img.axs[0][0].plot([-0.06,0.06],[-0.06, 0.06])\n# img.show_img()",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
#!/usr/bin/python2.7
#
# Assignment2 Interface
#
import psycopg2
import os
import sys
import Assignment1 as a
# Donot close the connection inside this file i.e. do not perform openconnection.close()
#range__metadata = RangeRatingsMetadata
#roundR_metadata = RoundRobinRatingsMetadata
#rangetablepartition = rangeratingspart
def RangeQuery(ratingsTableName, ratingMinValue, ratingMaxValue, openconnection):
try:#Implement RangeQuery Here.
cur = openconnection.cursor()
ratings_Min = ratingMinValue
ratings_Max = ratingMaxValue
if ((0.0<=ratings_Min <= 5.0) and (0.0<=ratings_Max<= 5.0) and (ratings_Max >=ratings_Min)):
cur.execute("SELECT maxrating from rangeratingsmetadata") ### Lines to make him look at
upperbound_range = cur.fetchall() #print the last column of the select function execute above
i=0
#print upperbound_range
while(1):
#print upperbound_range[i][0]
if (ratings_Min > upperbound_range[i][0]):
i = i+1
else:
lower_bound = i
#print "the lower table index is", lower_bound
break
i = 0
while(1):
if (ratings_Max > upperbound_range[i][0]):
i = i+1
else:
upper_bound = i
#print "the upper table index is", upper_bound
break
range_list_table_lookup = range(lower_bound,upper_bound+1)
#print range_list_table_lookup
file = open("RangeQueryOut.txt","w")
for l in range_list_table_lookup:
rows = []
cur.execute('SELECT * from rangeratingspart' + str(l)) ### Lines to make him look at
rows = cur.fetchall()
#print rows
### Lines to make him look at
for row in rows:
rat = row[2]
if (ratings_Min <= rat <= ratings_Max):
file.write("{},{},{},{} \n".format("rangeratingspart" + str(l),row[0],row[1],row[2])) ### Lines to make him look at
#file.close()
cur.execute('SELECT * from RoundRobinRatingsMetadata')
numberofpartitionslist = cur.fetchall()
numberofpartitions = numberofpartitionslist[0][0]
for l in range(numberofpartitions):
cur.execute('SELECT * from RoundRobinRatingsPart' + str(l)) ### Lines to make him look at
rows = []
rows = cur.fetchall()
for row in rows:
rat = row[2]
if (ratings_Min <= rat <= ratings_Max):
file.write("{},{},{},{} \n".format("roundrobinratingspart" + str(l),row[0],row[1],row[2])) ### Lines to make him look at
file.close()
else:
print ("Please enter the valid values")
cur.close()
except Exception as E:
print E
def PointQuery(ratingsTableName, ratingValue, openconnection):
#Implement PointQuery Here.
# Remove this once you are done with implementation
cur = openconnection.cursor()
pointvalue = ratingValue
if ((0.0<=pointvalue<= 5.0)):
cur.execute('SELECT maxrating from RangeRatingsMetadata')
Range_upper = cur.fetchall()
i=0
while(1):
if (pointvalue > Range_upper[i][0]):
i = i+1
else:
table_suffxi = i
#print "the table suffix to look is", table_suffix
break
rows = []
cur.execute('SELECT * from rangeratingspart'+str(table_suffix))
rows = cur.fetchall()
file1 = open("PointQueryOut.txt","w")
for row in rows:
rat = row[2]
if (rat == pointvalue):
file1.write("{},{},{},{} \n".format("rangeratingspart"+str(table_suffix),row[0],row[1],row[2]))
#file1.close()
cur.execute('SELECT * from RoundRobinRatingsMetadata')
numberofpartitionslist = cur.fetchall()
numberofpartitions = numberofpartitionslist[0][0]
for l in range(numberofpartitions):
cur.execute('SELECT * from RoundRobinRatingsPart'+str(l))
rows = []
rows = cur.fetchall()
#file1 = open("PointQueryOut.txt","w")
for row in rows:
rat = row[2]
if (rat == pointvalue):
file1.write ("{},{},{},{} \n".format("roundrobinratingspart" + str(l),row[0],row[1],row[2]))
file1.close()
else:
print("please enter a valid rating value")
cur.close()
|
normal
|
{
"blob_id": "0c736bb5c88a8d7ee359e05fe12f0b77d83146c8",
"index": 3439,
"step-1": "#!/usr/bin/python2.7\n#\n# Assignment2 Interface\n#\n\nimport psycopg2\nimport os\nimport sys\nimport Assignment1 as a\n# Donot close the connection inside this file i.e. do not perform openconnection.close()\n#range__metadata = RangeRatingsMetadata\n#roundR_metadata = RoundRobinRatingsMetadata\n#rangetablepartition = rangeratingspart\ndef RangeQuery(ratingsTableName, ratingMinValue, ratingMaxValue, openconnection):\n\ttry:#Implement RangeQuery Here.\n\t\tcur = openconnection.cursor()\n\t\tratings_Min = ratingMinValue\n\t\tratings_Max = ratingMaxValue\n\t\tif ((0.0<=ratings_Min <= 5.0) and (0.0<=ratings_Max<= 5.0) and (ratings_Max >=ratings_Min)):\n\t\t\tcur.execute(\"SELECT maxrating from rangeratingsmetadata\") ### Lines to make him look at\n\t\t\tupperbound_range = cur.fetchall() #print the last column of the select function execute above\n\t\t\ti=0\n\t\t\t#print upperbound_range\n\t\t\twhile(1):\t\t\t\n\t\t\t\t#print upperbound_range[i][0]\n\t\t\t\tif (ratings_Min > upperbound_range[i][0]):\n\t\t\t\t\ti = i+1\n\t\t\t\telse:\n\t\t\t\t\tlower_bound = i\n\t\t\t\t\t#print \"the lower table index is\", lower_bound\n\t\t\t\t\tbreak\n\t\t\ti = 0\n\t\t\twhile(1):\n\t\t\t\tif (ratings_Max > upperbound_range[i][0]):\n\t\t\t\t\ti = i+1\n\t\t\t\telse:\n\t\t\t\t\tupper_bound = i\n\t\t\t\t\t#print \"the upper table index is\", upper_bound\n\t\t\t\t\tbreak\n\t\t\t\n\t\t\trange_list_table_lookup = range(lower_bound,upper_bound+1)\n\t\t\t#print range_list_table_lookup\n\t\t\tfile = open(\"RangeQueryOut.txt\",\"w\")\n\t\t\tfor l in range_list_table_lookup:\n\t\t\t\trows = []\n\t\t\t\tcur.execute('SELECT * from rangeratingspart' + str(l)) ### Lines to make him look at\n\t\t\t\trows = cur.fetchall()\n\t\t\t\t#print rows\n\t\t\t\t ### Lines to make him look at\n\t\t\t\tfor row in rows:\n\t\t\t\t\trat = row[2]\n\t\t\t\t\tif (ratings_Min <= rat <= ratings_Max):\n\t\t\t\t\t\tfile.write(\"{},{},{},{} \\n\".format(\"rangeratingspart\" + str(l),row[0],row[1],row[2])) ### Lines to make him look at\n\t\t\t#file.close()\n\t\t\tcur.execute('SELECT * from RoundRobinRatingsMetadata')\n\t\t\tnumberofpartitionslist = cur.fetchall()\n\t\t\tnumberofpartitions = numberofpartitionslist[0][0]\n\t\t\tfor l in range(numberofpartitions):\n\t\t\t\tcur.execute('SELECT * from RoundRobinRatingsPart' + str(l)) ### Lines to make him look at\n\t\t\t\trows = []\n\t\t\t\trows = cur.fetchall()\n\t\t\t\t\n\t\t\t\tfor row in rows:\n\t\t\t\t\trat = row[2]\n\t\t\t\t\tif (ratings_Min <= rat <= ratings_Max):\n\t\t\t\t\t\tfile.write(\"{},{},{},{} \\n\".format(\"roundrobinratingspart\" + str(l),row[0],row[1],row[2])) ### Lines to make him look at\n\t\t\tfile.close()\n\t\telse:\n\t\t\tprint (\"Please enter the valid values\")\n\t\t\t\n\t\tcur.close()\n\texcept Exception as E:\n\t\tprint E\n\n\n\ndef PointQuery(ratingsTableName, ratingValue, openconnection):\n\t#Implement PointQuery Here.\n\t# Remove this once you are done with implementation\n\tcur = openconnection.cursor()\n\tpointvalue = ratingValue\n\tif ((0.0<=pointvalue<= 5.0)):\n\t\tcur.execute('SELECT maxrating from RangeRatingsMetadata')\n\t\tRange_upper = cur.fetchall()\n\t\ti=0\n\t\twhile(1):\n\t\t\tif (pointvalue > Range_upper[i][0]):\n\t\t\t\ti = i+1\n\t\t\telse:\n\t\t\t\ttable_suffxi = i\n\t\t\t\t#print \"the table suffix to look is\", table_suffix\n\t\t\t\tbreak\n\t\trows = []\n\t\tcur.execute('SELECT * from rangeratingspart'+str(table_suffix))\n\t\trows = cur.fetchall()\n\t\tfile1 = open(\"PointQueryOut.txt\",\"w\")\n\t\tfor row in rows:\n\t\t\trat = row[2]\n\t\t\tif (rat == pointvalue):\n\t\t\t\tfile1.write(\"{},{},{},{} \\n\".format(\"rangeratingspart\"+str(table_suffix),row[0],row[1],row[2]))\n\t\t#file1.close()\n\t\tcur.execute('SELECT * from RoundRobinRatingsMetadata')\n\t\tnumberofpartitionslist = cur.fetchall()\n\t\tnumberofpartitions = numberofpartitionslist[0][0]\n\t\tfor l in range(numberofpartitions):\n\t\t\tcur.execute('SELECT * from RoundRobinRatingsPart'+str(l))\n\t\t\trows = []\n\t\t\trows = cur.fetchall()\n\t\t\t#file1 = open(\"PointQueryOut.txt\",\"w\")\n\t\t\tfor row in rows:\n\t\t\t\trat = row[2]\n\t\t\t\tif (rat == pointvalue):\n\t\t\t\t\tfile1.write (\"{},{},{},{} \\n\".format(\"roundrobinratingspart\" + str(l),row[0],row[1],row[2]))\n\t\tfile1.close()\n\n\n\telse:\n\t\tprint(\"please enter a valid rating value\")\n\t\t\n\tcur.close()\n\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 11 18:50:46 2019
@author: kanfar
"""
import numpy as np
import timeit
import matplotlib.pyplot as plt
from numpy import expand_dims, zeros, ones
from numpy.random import randn, randint
from keras.models import load_model
from keras.optimizers import Adam
from keras.models import Model
from keras.layers import Input, Reshape, Flatten, Concatenate
from keras.layers import Dense, Conv2D, Conv2DTranspose
from keras.layers import Dropout, LeakyReLU
class cGAN:
def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):
self.input_dim1 = input_dim1
self.input_dim2 = input_dim2
self.input_dim3 = input_dim3
self.latent_size = latent_size
def discriminator(self):
#conditional input
input_shape = (self.input_dim1, self.input_dim2, self.input_dim3)
input_cond = Input(shape = input_shape)
#generator output
input_x = Input(shape = input_shape)
merge = Concatenate()([input_x, input_cond])
#downsample
out = Conv2D(32, (3,3), strides=(2,2), padding='same')(merge)
out = LeakyReLU(alpha=0.2)(out)
out = Conv2D(32, (3,3), strides=(2,2), padding='same')(out)
out = LeakyReLU(alpha=0.2)(out)
out = Flatten()(out)
out = Dropout(0.5)(out)
y = Dense(1, activation='sigmoid')(out)
# define model
model = Model([input_x, input_cond], y)
# compile model
opt = Adam(lr=0.0002) #0.0002 and beta_1 0.5
model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])
return model
def generator(self):
#losing one pixel, figure out later
image_dim = self.input_dim1
latent_shape = self.latent_size
cond_shape = (image_dim, image_dim, self.input_dim3)
input_latent = Input(shape = (latent_shape,))
num_nodes = image_dim * image_dim
latent = Dense(num_nodes)(input_latent)
latent = LeakyReLU(alpha=0.2)(latent)
latent = Reshape((image_dim,image_dim,1))(latent)
input_cond = Input(shape = cond_shape)
cond = input_cond
merge = Concatenate()([latent,cond])
# upsample to 14x14
out = Conv2D(32, (4,4), strides=(1,1), padding='same')(merge)
out = LeakyReLU(alpha=0.2)(out)
# upsample to 28x28
out = Conv2D(32, (4,4), strides=(1,1), padding='same')(out)
out = LeakyReLU(alpha=0.2)(out)
out = Conv2D(32, (4,4), strides=(1,1), padding='same')(out)
out = LeakyReLU(alpha=0.2)(out)
# output
x = Conv2D(1, (4,4), strides=(1,1), activation='tanh', padding='same')(out) #something key that I don't understand
# define model
model = Model([input_latent, input_cond], x)
return model
def combined(self, g_model, d_model):
#model comprised of two models
# make weights in the discriminator not trainable
d_model.trainable = False
# get noise and label inputs from generator model
input_latent, input_cond = g_model.input #defining the tensors in a short way: this is saying the input to this model is the same size as input to g_model
# get image output from the generator model
x = g_model.output
#can I do x = g_model([input_latent, input_cond]) instead of the above?
# connect image output and label input from generator as inputs to discriminator
y = d_model([x, input_cond]) #why this needs to be connected but not the above???? does the first output take model input as default??????? test this
# define gan model as taking noise and label and outputting a classification
model = Model([input_latent, input_cond], y)
# compile model
opt = Adam(lr=0.0002, beta_1=0.5)
model.compile(loss='binary_crossentropy', optimizer=opt)
return model
def generate_real_samples(self, focused, defocused, n_samples):
idx = randint(0, focused.shape[0], n_samples)
x_real, input_cond = focused[idx,:,:,:], defocused[idx,:,:,:]
y_real = ones((n_samples,1))
return [x_real, input_cond], y_real
def generate_latent(self, latent_size, n_samples):
#generate points in teh latent space
total_latent = randn(latent_size*n_samples)
input_z = total_latent.reshape(n_samples, latent_size)
return input_z
def generate_fake_samples(self, generator, defocused, latent_dim, n_samples):
idx = randint(0, defocused.shape[0], n_samples)
input_cond = defocused[idx,:,:,:]
input_z = self.generate_latent(latent_dim, n_samples)
# predict outputs
x_fake = generator.predict([input_z, input_cond])
# create class labels
y_fake = zeros((n_samples, 1))
return [x_fake, input_cond], y_fake
def generate_gan_input(self, defocused, latent_dim, n_samples):
#defocused = data[1,:,:,:]
#defocused = np.expand_dims(input_cond, axis = -1)
idx = randint(0, defocused.shape[0], n_samples)
input_cond = defocused[idx,:,:,:]
input_z = self.generate_latent(latent_dim, n_samples)
# create class labels
y_gan = ones((n_samples, 1))
return [input_z, input_cond], y_gan
def train(self, g_model, d_model, gan_model, real, input_cond, latent_dim, n_epochs, n_batch, save):
bat_per_epo = int(real.shape[0] / n_batch) #check
half_batch = int(n_batch / 2)
g_loss = np.zeros(n_epochs)
d_loss_real = np.zeros(n_epochs)
d_loss_fake = np.zeros(n_epochs)
# manually enumerate epochs
for i in range(n_epochs):
start = timeit.default_timer()
# enumerate batches over the training set
print('================== Epoch %d ==================\n' % (i+1))
for j in range(bat_per_epo):
# get randomly selected 'real' samples
[x_real, input_cond_real], y_real = self.generate_real_samples(real, input_cond, half_batch)
# update discriminator model weights
d_loss_real[i], _ = d_model.train_on_batch([x_real, input_cond_real], y_real)
# generate 'fake' examples
[x_fake, input_cond_fake], y_fake = self.generate_fake_samples(g_model, input_cond, latent_dim, half_batch)
# update discriminator model weights
d_loss_fake[i], _ = d_model.train_on_batch([x_fake, input_cond_fake], y_fake)
# prepare points in latent space as input for the generator
[z_input, input_cond_gan], y_gan = self.generate_gan_input(input_cond, latent_dim, n_batch)
# update the generator via the discriminator's error
g_loss[i] = gan_model.train_on_batch([z_input, input_cond_gan], y_gan)
# summarize loss on this batch
print('Completed: %.f' % np.divide((j+1)*100,bat_per_epo) +'%')
print('Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f' %
(i+1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\n')
stop = timeit.default_timer()
print('Time: %.2f min' % ((stop - start)/60))
# save the generator model
g_model.save('./models/cgan_'+ save + '.h5') #save somewhere
# save loss history
loss = np.array([d_loss_real, d_loss_fake, g_loss])
np.save('./models/cgan_loss_' + save, loss)
def generate_fakes_givenOne(self, generator, focused, defocused, latent_dim, n_samples):
idx = randint(0, defocused.shape[0], 1)
x_real = focused[idx,:,:,:]
input_cond = defocused[idx,:,:,:] ##### should last be zero or :?
input_cond = np.repeat(input_cond, n_samples, axis=0)
input_z = self.generate_latent(latent_dim, n_samples)
x_fake = generator.predict([input_z, input_cond])
return x_real, x_fake, input_cond[0,:,:,:]
def generate_fakes_givenMany(self, generator, focused, defocused, latent_dim, n_examples):
n_samples = n_examples-2
x_real_many = np.zeros((n_examples, focused.shape[1], focused.shape[2], focused.shape[3]))
input_cond_many = np.zeros((n_examples, focused.shape[1], focused.shape[2], focused.shape[3]))
x_fake_many = np.zeros((n_examples, n_samples, focused.shape[1], focused.shape[2], focused.shape[3]))
for i in range(n_examples):
x_real_many[i,:,:,:], x_fake_many[i,:,:,:,:], input_cond_many[i,:,:,:] = self.generate_fakes_givenOne(generator, focused, defocused, latent_dim, n_samples)
return x_real_many, x_fake_many, input_cond_many
|
normal
|
{
"blob_id": "fc6c220f8a3a0e9dd1d6e6e1ca131136db8f8a58",
"index": 9155,
"step-1": "<mask token>\n\n\nclass cGAN:\n\n def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):\n self.input_dim1 = input_dim1\n self.input_dim2 = input_dim2\n self.input_dim3 = input_dim3\n self.latent_size = latent_size\n\n def discriminator(self):\n input_shape = self.input_dim1, self.input_dim2, self.input_dim3\n input_cond = Input(shape=input_shape)\n input_x = Input(shape=input_shape)\n merge = Concatenate()([input_x, input_cond])\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Flatten()(out)\n out = Dropout(0.5)(out)\n y = Dense(1, activation='sigmoid')(out)\n model = Model([input_x, input_cond], y)\n opt = Adam(lr=0.0002)\n model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[\n 'accuracy'])\n return model\n\n def generator(self):\n image_dim = self.input_dim1\n latent_shape = self.latent_size\n cond_shape = image_dim, image_dim, self.input_dim3\n input_latent = Input(shape=(latent_shape,))\n num_nodes = image_dim * image_dim\n latent = Dense(num_nodes)(input_latent)\n latent = LeakyReLU(alpha=0.2)(latent)\n latent = Reshape((image_dim, image_dim, 1))(latent)\n input_cond = Input(shape=cond_shape)\n cond = input_cond\n merge = Concatenate()([latent, cond])\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n x = Conv2D(1, (4, 4), strides=(1, 1), activation='tanh', padding='same'\n )(out)\n model = Model([input_latent, input_cond], x)\n return model\n\n def combined(self, g_model, d_model):\n d_model.trainable = False\n input_latent, input_cond = g_model.input\n x = g_model.output\n y = d_model([x, input_cond])\n model = Model([input_latent, input_cond], y)\n opt = Adam(lr=0.0002, beta_1=0.5)\n model.compile(loss='binary_crossentropy', optimizer=opt)\n return model\n\n def generate_real_samples(self, focused, defocused, n_samples):\n idx = randint(0, focused.shape[0], n_samples)\n x_real, input_cond = focused[idx, :, :, :], defocused[idx, :, :, :]\n y_real = ones((n_samples, 1))\n return [x_real, input_cond], y_real\n\n def generate_latent(self, latent_size, n_samples):\n total_latent = randn(latent_size * n_samples)\n input_z = total_latent.reshape(n_samples, latent_size)\n return input_z\n\n def generate_fake_samples(self, generator, defocused, latent_dim, n_samples\n ):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n y_fake = zeros((n_samples, 1))\n return [x_fake, input_cond], y_fake\n <mask token>\n\n def train(self, g_model, d_model, gan_model, real, input_cond,\n latent_dim, n_epochs, n_batch, save):\n bat_per_epo = int(real.shape[0] / n_batch)\n half_batch = int(n_batch / 2)\n g_loss = np.zeros(n_epochs)\n d_loss_real = np.zeros(n_epochs)\n d_loss_fake = np.zeros(n_epochs)\n for i in range(n_epochs):\n start = timeit.default_timer()\n print('================== Epoch %d ==================\\n' % (i + 1))\n for j in range(bat_per_epo):\n [x_real, input_cond_real], y_real = self.generate_real_samples(\n real, input_cond, half_batch)\n d_loss_real[i], _ = d_model.train_on_batch([x_real,\n input_cond_real], y_real)\n [x_fake, input_cond_fake], y_fake = self.generate_fake_samples(\n g_model, input_cond, latent_dim, half_batch)\n d_loss_fake[i], _ = d_model.train_on_batch([x_fake,\n input_cond_fake], y_fake)\n [z_input, input_cond_gan], y_gan = self.generate_gan_input(\n input_cond, latent_dim, n_batch)\n g_loss[i] = gan_model.train_on_batch([z_input,\n input_cond_gan], y_gan)\n print('Completed: %.f' % np.divide((j + 1) * 100,\n bat_per_epo) + '%')\n print(\n 'Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f'\n % (i + 1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\\n')\n stop = timeit.default_timer()\n print('Time: %.2f min' % ((stop - start) / 60))\n g_model.save('./models/cgan_' + save + '.h5')\n loss = np.array([d_loss_real, d_loss_fake, g_loss])\n np.save('./models/cgan_loss_' + save, loss)\n\n def generate_fakes_givenOne(self, generator, focused, defocused,\n latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], 1)\n x_real = focused[idx, :, :, :]\n input_cond = defocused[idx, :, :, :]\n input_cond = np.repeat(input_cond, n_samples, axis=0)\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n return x_real, x_fake, input_cond[0, :, :, :]\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass cGAN:\n\n def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):\n self.input_dim1 = input_dim1\n self.input_dim2 = input_dim2\n self.input_dim3 = input_dim3\n self.latent_size = latent_size\n\n def discriminator(self):\n input_shape = self.input_dim1, self.input_dim2, self.input_dim3\n input_cond = Input(shape=input_shape)\n input_x = Input(shape=input_shape)\n merge = Concatenate()([input_x, input_cond])\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Flatten()(out)\n out = Dropout(0.5)(out)\n y = Dense(1, activation='sigmoid')(out)\n model = Model([input_x, input_cond], y)\n opt = Adam(lr=0.0002)\n model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[\n 'accuracy'])\n return model\n\n def generator(self):\n image_dim = self.input_dim1\n latent_shape = self.latent_size\n cond_shape = image_dim, image_dim, self.input_dim3\n input_latent = Input(shape=(latent_shape,))\n num_nodes = image_dim * image_dim\n latent = Dense(num_nodes)(input_latent)\n latent = LeakyReLU(alpha=0.2)(latent)\n latent = Reshape((image_dim, image_dim, 1))(latent)\n input_cond = Input(shape=cond_shape)\n cond = input_cond\n merge = Concatenate()([latent, cond])\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n x = Conv2D(1, (4, 4), strides=(1, 1), activation='tanh', padding='same'\n )(out)\n model = Model([input_latent, input_cond], x)\n return model\n\n def combined(self, g_model, d_model):\n d_model.trainable = False\n input_latent, input_cond = g_model.input\n x = g_model.output\n y = d_model([x, input_cond])\n model = Model([input_latent, input_cond], y)\n opt = Adam(lr=0.0002, beta_1=0.5)\n model.compile(loss='binary_crossentropy', optimizer=opt)\n return model\n\n def generate_real_samples(self, focused, defocused, n_samples):\n idx = randint(0, focused.shape[0], n_samples)\n x_real, input_cond = focused[idx, :, :, :], defocused[idx, :, :, :]\n y_real = ones((n_samples, 1))\n return [x_real, input_cond], y_real\n\n def generate_latent(self, latent_size, n_samples):\n total_latent = randn(latent_size * n_samples)\n input_z = total_latent.reshape(n_samples, latent_size)\n return input_z\n\n def generate_fake_samples(self, generator, defocused, latent_dim, n_samples\n ):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n y_fake = zeros((n_samples, 1))\n return [x_fake, input_cond], y_fake\n <mask token>\n\n def train(self, g_model, d_model, gan_model, real, input_cond,\n latent_dim, n_epochs, n_batch, save):\n bat_per_epo = int(real.shape[0] / n_batch)\n half_batch = int(n_batch / 2)\n g_loss = np.zeros(n_epochs)\n d_loss_real = np.zeros(n_epochs)\n d_loss_fake = np.zeros(n_epochs)\n for i in range(n_epochs):\n start = timeit.default_timer()\n print('================== Epoch %d ==================\\n' % (i + 1))\n for j in range(bat_per_epo):\n [x_real, input_cond_real], y_real = self.generate_real_samples(\n real, input_cond, half_batch)\n d_loss_real[i], _ = d_model.train_on_batch([x_real,\n input_cond_real], y_real)\n [x_fake, input_cond_fake], y_fake = self.generate_fake_samples(\n g_model, input_cond, latent_dim, half_batch)\n d_loss_fake[i], _ = d_model.train_on_batch([x_fake,\n input_cond_fake], y_fake)\n [z_input, input_cond_gan], y_gan = self.generate_gan_input(\n input_cond, latent_dim, n_batch)\n g_loss[i] = gan_model.train_on_batch([z_input,\n input_cond_gan], y_gan)\n print('Completed: %.f' % np.divide((j + 1) * 100,\n bat_per_epo) + '%')\n print(\n 'Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f'\n % (i + 1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\\n')\n stop = timeit.default_timer()\n print('Time: %.2f min' % ((stop - start) / 60))\n g_model.save('./models/cgan_' + save + '.h5')\n loss = np.array([d_loss_real, d_loss_fake, g_loss])\n np.save('./models/cgan_loss_' + save, loss)\n\n def generate_fakes_givenOne(self, generator, focused, defocused,\n latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], 1)\n x_real = focused[idx, :, :, :]\n input_cond = defocused[idx, :, :, :]\n input_cond = np.repeat(input_cond, n_samples, axis=0)\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n return x_real, x_fake, input_cond[0, :, :, :]\n\n def generate_fakes_givenMany(self, generator, focused, defocused,\n latent_dim, n_examples):\n n_samples = n_examples - 2\n x_real_many = np.zeros((n_examples, focused.shape[1], focused.shape\n [2], focused.shape[3]))\n input_cond_many = np.zeros((n_examples, focused.shape[1], focused.\n shape[2], focused.shape[3]))\n x_fake_many = np.zeros((n_examples, n_samples, focused.shape[1],\n focused.shape[2], focused.shape[3]))\n for i in range(n_examples):\n x_real_many[i, :, :, :], x_fake_many[i, :, :, :, :\n ], input_cond_many[i, :, :, :] = self.generate_fakes_givenOne(\n generator, focused, defocused, latent_dim, n_samples)\n return x_real_many, x_fake_many, input_cond_many\n",
"step-3": "<mask token>\n\n\nclass cGAN:\n\n def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):\n self.input_dim1 = input_dim1\n self.input_dim2 = input_dim2\n self.input_dim3 = input_dim3\n self.latent_size = latent_size\n\n def discriminator(self):\n input_shape = self.input_dim1, self.input_dim2, self.input_dim3\n input_cond = Input(shape=input_shape)\n input_x = Input(shape=input_shape)\n merge = Concatenate()([input_x, input_cond])\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Flatten()(out)\n out = Dropout(0.5)(out)\n y = Dense(1, activation='sigmoid')(out)\n model = Model([input_x, input_cond], y)\n opt = Adam(lr=0.0002)\n model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[\n 'accuracy'])\n return model\n\n def generator(self):\n image_dim = self.input_dim1\n latent_shape = self.latent_size\n cond_shape = image_dim, image_dim, self.input_dim3\n input_latent = Input(shape=(latent_shape,))\n num_nodes = image_dim * image_dim\n latent = Dense(num_nodes)(input_latent)\n latent = LeakyReLU(alpha=0.2)(latent)\n latent = Reshape((image_dim, image_dim, 1))(latent)\n input_cond = Input(shape=cond_shape)\n cond = input_cond\n merge = Concatenate()([latent, cond])\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n x = Conv2D(1, (4, 4), strides=(1, 1), activation='tanh', padding='same'\n )(out)\n model = Model([input_latent, input_cond], x)\n return model\n\n def combined(self, g_model, d_model):\n d_model.trainable = False\n input_latent, input_cond = g_model.input\n x = g_model.output\n y = d_model([x, input_cond])\n model = Model([input_latent, input_cond], y)\n opt = Adam(lr=0.0002, beta_1=0.5)\n model.compile(loss='binary_crossentropy', optimizer=opt)\n return model\n\n def generate_real_samples(self, focused, defocused, n_samples):\n idx = randint(0, focused.shape[0], n_samples)\n x_real, input_cond = focused[idx, :, :, :], defocused[idx, :, :, :]\n y_real = ones((n_samples, 1))\n return [x_real, input_cond], y_real\n\n def generate_latent(self, latent_size, n_samples):\n total_latent = randn(latent_size * n_samples)\n input_z = total_latent.reshape(n_samples, latent_size)\n return input_z\n\n def generate_fake_samples(self, generator, defocused, latent_dim, n_samples\n ):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n y_fake = zeros((n_samples, 1))\n return [x_fake, input_cond], y_fake\n\n def generate_gan_input(self, defocused, latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n y_gan = ones((n_samples, 1))\n return [input_z, input_cond], y_gan\n\n def train(self, g_model, d_model, gan_model, real, input_cond,\n latent_dim, n_epochs, n_batch, save):\n bat_per_epo = int(real.shape[0] / n_batch)\n half_batch = int(n_batch / 2)\n g_loss = np.zeros(n_epochs)\n d_loss_real = np.zeros(n_epochs)\n d_loss_fake = np.zeros(n_epochs)\n for i in range(n_epochs):\n start = timeit.default_timer()\n print('================== Epoch %d ==================\\n' % (i + 1))\n for j in range(bat_per_epo):\n [x_real, input_cond_real], y_real = self.generate_real_samples(\n real, input_cond, half_batch)\n d_loss_real[i], _ = d_model.train_on_batch([x_real,\n input_cond_real], y_real)\n [x_fake, input_cond_fake], y_fake = self.generate_fake_samples(\n g_model, input_cond, latent_dim, half_batch)\n d_loss_fake[i], _ = d_model.train_on_batch([x_fake,\n input_cond_fake], y_fake)\n [z_input, input_cond_gan], y_gan = self.generate_gan_input(\n input_cond, latent_dim, n_batch)\n g_loss[i] = gan_model.train_on_batch([z_input,\n input_cond_gan], y_gan)\n print('Completed: %.f' % np.divide((j + 1) * 100,\n bat_per_epo) + '%')\n print(\n 'Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f'\n % (i + 1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\\n')\n stop = timeit.default_timer()\n print('Time: %.2f min' % ((stop - start) / 60))\n g_model.save('./models/cgan_' + save + '.h5')\n loss = np.array([d_loss_real, d_loss_fake, g_loss])\n np.save('./models/cgan_loss_' + save, loss)\n\n def generate_fakes_givenOne(self, generator, focused, defocused,\n latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], 1)\n x_real = focused[idx, :, :, :]\n input_cond = defocused[idx, :, :, :]\n input_cond = np.repeat(input_cond, n_samples, axis=0)\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n return x_real, x_fake, input_cond[0, :, :, :]\n\n def generate_fakes_givenMany(self, generator, focused, defocused,\n latent_dim, n_examples):\n n_samples = n_examples - 2\n x_real_many = np.zeros((n_examples, focused.shape[1], focused.shape\n [2], focused.shape[3]))\n input_cond_many = np.zeros((n_examples, focused.shape[1], focused.\n shape[2], focused.shape[3]))\n x_fake_many = np.zeros((n_examples, n_samples, focused.shape[1],\n focused.shape[2], focused.shape[3]))\n for i in range(n_examples):\n x_real_many[i, :, :, :], x_fake_many[i, :, :, :, :\n ], input_cond_many[i, :, :, :] = self.generate_fakes_givenOne(\n generator, focused, defocused, latent_dim, n_samples)\n return x_real_many, x_fake_many, input_cond_many\n",
"step-4": "<mask token>\nimport numpy as np\nimport timeit\nimport matplotlib.pyplot as plt\nfrom numpy import expand_dims, zeros, ones\nfrom numpy.random import randn, randint\nfrom keras.models import load_model\nfrom keras.optimizers import Adam\nfrom keras.models import Model\nfrom keras.layers import Input, Reshape, Flatten, Concatenate\nfrom keras.layers import Dense, Conv2D, Conv2DTranspose\nfrom keras.layers import Dropout, LeakyReLU\n\n\nclass cGAN:\n\n def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):\n self.input_dim1 = input_dim1\n self.input_dim2 = input_dim2\n self.input_dim3 = input_dim3\n self.latent_size = latent_size\n\n def discriminator(self):\n input_shape = self.input_dim1, self.input_dim2, self.input_dim3\n input_cond = Input(shape=input_shape)\n input_x = Input(shape=input_shape)\n merge = Concatenate()([input_x, input_cond])\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (3, 3), strides=(2, 2), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Flatten()(out)\n out = Dropout(0.5)(out)\n y = Dense(1, activation='sigmoid')(out)\n model = Model([input_x, input_cond], y)\n opt = Adam(lr=0.0002)\n model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[\n 'accuracy'])\n return model\n\n def generator(self):\n image_dim = self.input_dim1\n latent_shape = self.latent_size\n cond_shape = image_dim, image_dim, self.input_dim3\n input_latent = Input(shape=(latent_shape,))\n num_nodes = image_dim * image_dim\n latent = Dense(num_nodes)(input_latent)\n latent = LeakyReLU(alpha=0.2)(latent)\n latent = Reshape((image_dim, image_dim, 1))(latent)\n input_cond = Input(shape=cond_shape)\n cond = input_cond\n merge = Concatenate()([latent, cond])\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (4, 4), strides=(1, 1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n x = Conv2D(1, (4, 4), strides=(1, 1), activation='tanh', padding='same'\n )(out)\n model = Model([input_latent, input_cond], x)\n return model\n\n def combined(self, g_model, d_model):\n d_model.trainable = False\n input_latent, input_cond = g_model.input\n x = g_model.output\n y = d_model([x, input_cond])\n model = Model([input_latent, input_cond], y)\n opt = Adam(lr=0.0002, beta_1=0.5)\n model.compile(loss='binary_crossentropy', optimizer=opt)\n return model\n\n def generate_real_samples(self, focused, defocused, n_samples):\n idx = randint(0, focused.shape[0], n_samples)\n x_real, input_cond = focused[idx, :, :, :], defocused[idx, :, :, :]\n y_real = ones((n_samples, 1))\n return [x_real, input_cond], y_real\n\n def generate_latent(self, latent_size, n_samples):\n total_latent = randn(latent_size * n_samples)\n input_z = total_latent.reshape(n_samples, latent_size)\n return input_z\n\n def generate_fake_samples(self, generator, defocused, latent_dim, n_samples\n ):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n y_fake = zeros((n_samples, 1))\n return [x_fake, input_cond], y_fake\n\n def generate_gan_input(self, defocused, latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx, :, :, :]\n input_z = self.generate_latent(latent_dim, n_samples)\n y_gan = ones((n_samples, 1))\n return [input_z, input_cond], y_gan\n\n def train(self, g_model, d_model, gan_model, real, input_cond,\n latent_dim, n_epochs, n_batch, save):\n bat_per_epo = int(real.shape[0] / n_batch)\n half_batch = int(n_batch / 2)\n g_loss = np.zeros(n_epochs)\n d_loss_real = np.zeros(n_epochs)\n d_loss_fake = np.zeros(n_epochs)\n for i in range(n_epochs):\n start = timeit.default_timer()\n print('================== Epoch %d ==================\\n' % (i + 1))\n for j in range(bat_per_epo):\n [x_real, input_cond_real], y_real = self.generate_real_samples(\n real, input_cond, half_batch)\n d_loss_real[i], _ = d_model.train_on_batch([x_real,\n input_cond_real], y_real)\n [x_fake, input_cond_fake], y_fake = self.generate_fake_samples(\n g_model, input_cond, latent_dim, half_batch)\n d_loss_fake[i], _ = d_model.train_on_batch([x_fake,\n input_cond_fake], y_fake)\n [z_input, input_cond_gan], y_gan = self.generate_gan_input(\n input_cond, latent_dim, n_batch)\n g_loss[i] = gan_model.train_on_batch([z_input,\n input_cond_gan], y_gan)\n print('Completed: %.f' % np.divide((j + 1) * 100,\n bat_per_epo) + '%')\n print(\n 'Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f'\n % (i + 1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\\n')\n stop = timeit.default_timer()\n print('Time: %.2f min' % ((stop - start) / 60))\n g_model.save('./models/cgan_' + save + '.h5')\n loss = np.array([d_loss_real, d_loss_fake, g_loss])\n np.save('./models/cgan_loss_' + save, loss)\n\n def generate_fakes_givenOne(self, generator, focused, defocused,\n latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], 1)\n x_real = focused[idx, :, :, :]\n input_cond = defocused[idx, :, :, :]\n input_cond = np.repeat(input_cond, n_samples, axis=0)\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n return x_real, x_fake, input_cond[0, :, :, :]\n\n def generate_fakes_givenMany(self, generator, focused, defocused,\n latent_dim, n_examples):\n n_samples = n_examples - 2\n x_real_many = np.zeros((n_examples, focused.shape[1], focused.shape\n [2], focused.shape[3]))\n input_cond_many = np.zeros((n_examples, focused.shape[1], focused.\n shape[2], focused.shape[3]))\n x_fake_many = np.zeros((n_examples, n_samples, focused.shape[1],\n focused.shape[2], focused.shape[3]))\n for i in range(n_examples):\n x_real_many[i, :, :, :], x_fake_many[i, :, :, :, :\n ], input_cond_many[i, :, :, :] = self.generate_fakes_givenOne(\n generator, focused, defocused, latent_dim, n_samples)\n return x_real_many, x_fake_many, input_cond_many\n",
"step-5": "# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Nov 11 18:50:46 2019\n\n@author: kanfar\n\"\"\"\n\nimport numpy as np\nimport timeit\nimport matplotlib.pyplot as plt\nfrom numpy import expand_dims, zeros, ones\nfrom numpy.random import randn, randint\nfrom keras.models import load_model\nfrom keras.optimizers import Adam\nfrom keras.models import Model\nfrom keras.layers import Input, Reshape, Flatten, Concatenate\nfrom keras.layers import Dense, Conv2D, Conv2DTranspose\nfrom keras.layers import Dropout, LeakyReLU\n\nclass cGAN:\n def __init__(self, input_dim1, input_dim2, input_dim3, latent_size):\n self.input_dim1 = input_dim1\n self.input_dim2 = input_dim2\n self.input_dim3 = input_dim3\n self.latent_size = latent_size\n def discriminator(self):\n #conditional input\n input_shape = (self.input_dim1, self.input_dim2, self.input_dim3)\n input_cond = Input(shape = input_shape)\n #generator output\n input_x = Input(shape = input_shape)\n merge = Concatenate()([input_x, input_cond])\n #downsample\n out = Conv2D(32, (3,3), strides=(2,2), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n out = Conv2D(32, (3,3), strides=(2,2), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n out = Flatten()(out)\n out = Dropout(0.5)(out)\n y = Dense(1, activation='sigmoid')(out)\n # define model\n model = Model([input_x, input_cond], y)\n # compile model\n opt = Adam(lr=0.0002) #0.0002 and beta_1 0.5\n model.compile(loss='binary_crossentropy', optimizer=opt, metrics=['accuracy'])\n return model\n def generator(self):\n #losing one pixel, figure out later\n image_dim = self.input_dim1\n latent_shape = self.latent_size\n cond_shape = (image_dim, image_dim, self.input_dim3)\n \n input_latent = Input(shape = (latent_shape,))\n num_nodes = image_dim * image_dim\n latent = Dense(num_nodes)(input_latent)\n latent = LeakyReLU(alpha=0.2)(latent)\n latent = Reshape((image_dim,image_dim,1))(latent)\n \n input_cond = Input(shape = cond_shape)\n cond = input_cond\n \n merge = Concatenate()([latent,cond])\n \n # upsample to 14x14\n out = Conv2D(32, (4,4), strides=(1,1), padding='same')(merge)\n out = LeakyReLU(alpha=0.2)(out)\n # upsample to 28x28\n out = Conv2D(32, (4,4), strides=(1,1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n \n out = Conv2D(32, (4,4), strides=(1,1), padding='same')(out)\n out = LeakyReLU(alpha=0.2)(out)\n # output\n x = Conv2D(1, (4,4), strides=(1,1), activation='tanh', padding='same')(out) #something key that I don't understand\n # define model\n model = Model([input_latent, input_cond], x)\n return model\n def combined(self, g_model, d_model):\n #model comprised of two models\n # make weights in the discriminator not trainable\n d_model.trainable = False\n # get noise and label inputs from generator model\n input_latent, input_cond = g_model.input #defining the tensors in a short way: this is saying the input to this model is the same size as input to g_model\n # get image output from the generator model\n x = g_model.output\n #can I do x = g_model([input_latent, input_cond]) instead of the above?\n # connect image output and label input from generator as inputs to discriminator\n y = d_model([x, input_cond]) #why this needs to be connected but not the above???? does the first output take model input as default??????? test this\n # define gan model as taking noise and label and outputting a classification\n model = Model([input_latent, input_cond], y)\n # compile model\n opt = Adam(lr=0.0002, beta_1=0.5)\n model.compile(loss='binary_crossentropy', optimizer=opt)\n return model\n def generate_real_samples(self, focused, defocused, n_samples):\n idx = randint(0, focused.shape[0], n_samples)\n x_real, input_cond = focused[idx,:,:,:], defocused[idx,:,:,:] \n y_real = ones((n_samples,1))\n return [x_real, input_cond], y_real\n \n def generate_latent(self, latent_size, n_samples):\n #generate points in teh latent space\n total_latent = randn(latent_size*n_samples)\n input_z = total_latent.reshape(n_samples, latent_size) \n return input_z\n def generate_fake_samples(self, generator, defocused, latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx,:,:,:]\n input_z = self.generate_latent(latent_dim, n_samples)\n # predict outputs\n x_fake = generator.predict([input_z, input_cond])\n # create class labels\n y_fake = zeros((n_samples, 1))\n return [x_fake, input_cond], y_fake\n def generate_gan_input(self, defocused, latent_dim, n_samples):\n #defocused = data[1,:,:,:]\n #defocused = np.expand_dims(input_cond, axis = -1)\n idx = randint(0, defocused.shape[0], n_samples)\n input_cond = defocused[idx,:,:,:]\n input_z = self.generate_latent(latent_dim, n_samples)\n # create class labels\n y_gan = ones((n_samples, 1))\n return [input_z, input_cond], y_gan\n\n def train(self, g_model, d_model, gan_model, real, input_cond, latent_dim, n_epochs, n_batch, save):\n bat_per_epo = int(real.shape[0] / n_batch) #check\n half_batch = int(n_batch / 2)\n g_loss = np.zeros(n_epochs)\n d_loss_real = np.zeros(n_epochs)\n d_loss_fake = np.zeros(n_epochs)\n # manually enumerate epochs\n for i in range(n_epochs):\n start = timeit.default_timer()\n # enumerate batches over the training set\n print('================== Epoch %d ==================\\n' % (i+1))\n for j in range(bat_per_epo):\n # get randomly selected 'real' samples\n [x_real, input_cond_real], y_real = self.generate_real_samples(real, input_cond, half_batch)\n # update discriminator model weights\n d_loss_real[i], _ = d_model.train_on_batch([x_real, input_cond_real], y_real)\n # generate 'fake' examples\n [x_fake, input_cond_fake], y_fake = self.generate_fake_samples(g_model, input_cond, latent_dim, half_batch)\n # update discriminator model weights\n d_loss_fake[i], _ = d_model.train_on_batch([x_fake, input_cond_fake], y_fake)\n # prepare points in latent space as input for the generator\n [z_input, input_cond_gan], y_gan = self.generate_gan_input(input_cond, latent_dim, n_batch)\n # update the generator via the discriminator's error\n g_loss[i] = gan_model.train_on_batch([z_input, input_cond_gan], y_gan)\n # summarize loss on this batch\n print('Completed: %.f' % np.divide((j+1)*100,bat_per_epo) +'%')\n print('Epoch %d:: d_loss_real = %.3f, d_loss_fake = %.3f g_loss = %.3f' %\n (i+1, d_loss_real[i], d_loss_fake[i], g_loss[i]) + '\\n')\n stop = timeit.default_timer()\n print('Time: %.2f min' % ((stop - start)/60)) \n # save the generator model\n g_model.save('./models/cgan_'+ save + '.h5') #save somewhere\n # save loss history\n loss = np.array([d_loss_real, d_loss_fake, g_loss])\n np.save('./models/cgan_loss_' + save, loss)\n def generate_fakes_givenOne(self, generator, focused, defocused, latent_dim, n_samples):\n idx = randint(0, defocused.shape[0], 1)\n x_real = focused[idx,:,:,:]\n input_cond = defocused[idx,:,:,:] ##### should last be zero or :?\n input_cond = np.repeat(input_cond, n_samples, axis=0)\n input_z = self.generate_latent(latent_dim, n_samples)\n x_fake = generator.predict([input_z, input_cond])\n return x_real, x_fake, input_cond[0,:,:,:]\n def generate_fakes_givenMany(self, generator, focused, defocused, latent_dim, n_examples):\n n_samples = n_examples-2\n x_real_many = np.zeros((n_examples, focused.shape[1], focused.shape[2], focused.shape[3]))\n input_cond_many = np.zeros((n_examples, focused.shape[1], focused.shape[2], focused.shape[3]))\n x_fake_many = np.zeros((n_examples, n_samples, focused.shape[1], focused.shape[2], focused.shape[3]))\n \n for i in range(n_examples):\n x_real_many[i,:,:,:], x_fake_many[i,:,:,:,:], input_cond_many[i,:,:,:] = self.generate_fakes_givenOne(generator, focused, defocused, latent_dim, n_samples)\n return x_real_many, x_fake_many, input_cond_many\n \n ",
"step-ids": [
10,
11,
12,
13,
14
]
}
|
[
10,
11,
12,
13,
14
] |
import datetime
from django.views.generic import DetailView, ListView
from django.core.exceptions import ObjectDoesNotExist
from django.http import HttpResponseRedirect, Http404
from django.shortcuts import get_list_or_404, render_to_response, get_object_or_404
from django.template import RequestContext
from django.core.urlresolvers import reverse
from django.conf import settings
from farm.models import Animal, Breed, Product, Milking
from notes.forms import BriefNoteForm
class BreedDetailView(DetailView):
model = Breed
def get_queryset(self, *args, **kwargs):
return Breed.objects.filter(genus__slug=self.kwargs['genus_slug'])
class ProductDetailView(DetailView):
model = Product
def get_queryset(self, *args, **kwargs):
return Product.objects.filter(type__slug=self.kwargs['type_slug'])
class MilkingListView(ListView):
model = Animal
def get_queryset(self, *args, **kwargs):
try:
animal = Animal.objects.get(self.kwargs.get('slug', None))
qs = Milking.objects.filter(animal__primary_breed__genus__slug=self.kwargs['genus_slug'], animal__primary_breed__slug=self.kwargs['breed_slug'], animal__slug=self.kwargs['slug'])
except:
try:
qs = Milking.objects.filter(animal__primary_breed__genus__slug=self.kwargs['genus_slug'], animal__primary_breed__slug=self.kwargs['breed_slug'], animal__uuid__contains=self.kwargs['slug'])
except:
qs = None
return qs
class AnimalDetailView(DetailView):
model = Animal
def get_queryset(self, *args, **kwargs):
return Animal.objects.filter(primary_breed__genus__slug=self.kwargs['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])
def get_object(self, queryset=None):
if queryset is None:
queryset = self.get_queryset()
pk = self.kwargs.get('pk', None)
slug_or_uuid = self.kwargs.get('slug', None)
if pk is not None:
queryset = queryset.filter(pk=pk)
# Next, try looking up by slug.
elif slug_or_uuid is not None:
try:
obj = queryset.filter(uuid__contains=slug_or_uuid)[0]
except:
try:
obj = queryset.get(slug=slug_or_uuid)
except ObjectDoesNotExist:
raise Http404(_(u"No %(verbose_name)s found matching the query") %
{'verbose_name': queryset.model._meta.verbose_name})
# If none of those are defined, it's an error.
else:
raise AttributeError(u"Generic detail view %s must be called with "
u"either an object pk or a slug."
% self.__class__.__name__)
return obj
def get_context_data(self, **kwargs):
context = super(AnimalDetailView, self).get_context_data(**kwargs)
context['note_form'] = BriefNoteForm()
return context
|
normal
|
{
"blob_id": "3ecc9ce82d9c902958a4da51ce7ee3c39b064b2b",
"index": 3591,
"step-1": "<mask token>\n\n\nclass MilkingListView(ListView):\n <mask token>\n\n def get_queryset(self, *args, **kwargs):\n try:\n animal = Animal.objects.get(self.kwargs.get('slug', None))\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=\n self.kwargs['genus_slug'], animal__primary_breed__slug=self\n .kwargs['breed_slug'], animal__slug=self.kwargs['slug'])\n except:\n try:\n qs = Milking.objects.filter(animal__primary_breed__genus__slug\n =self.kwargs['genus_slug'], animal__primary_breed__slug\n =self.kwargs['breed_slug'], animal__uuid__contains=self\n .kwargs['slug'])\n except:\n qs = None\n return qs\n\n\nclass AnimalDetailView(DetailView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n return Animal.objects.filter(primary_breed__genus__slug=self.kwargs\n ['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])\n\n def get_object(self, queryset=None):\n if queryset is None:\n queryset = self.get_queryset()\n pk = self.kwargs.get('pk', None)\n slug_or_uuid = self.kwargs.get('slug', None)\n if pk is not None:\n queryset = queryset.filter(pk=pk)\n elif slug_or_uuid is not None:\n try:\n obj = queryset.filter(uuid__contains=slug_or_uuid)[0]\n except:\n try:\n obj = queryset.get(slug=slug_or_uuid)\n except ObjectDoesNotExist:\n raise Http404(_(\n u'No %(verbose_name)s found matching the query') %\n {'verbose_name': queryset.model._meta.verbose_name})\n else:\n raise AttributeError(\n u'Generic detail view %s must be called with either an object pk or a slug.'\n % self.__class__.__name__)\n return obj\n\n def get_context_data(self, **kwargs):\n context = super(AnimalDetailView, self).get_context_data(**kwargs)\n context['note_form'] = BriefNoteForm()\n return context\n",
"step-2": "<mask token>\n\n\nclass ProductDetailView(DetailView):\n <mask token>\n\n def get_queryset(self, *args, **kwargs):\n return Product.objects.filter(type__slug=self.kwargs['type_slug'])\n\n\nclass MilkingListView(ListView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n try:\n animal = Animal.objects.get(self.kwargs.get('slug', None))\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=\n self.kwargs['genus_slug'], animal__primary_breed__slug=self\n .kwargs['breed_slug'], animal__slug=self.kwargs['slug'])\n except:\n try:\n qs = Milking.objects.filter(animal__primary_breed__genus__slug\n =self.kwargs['genus_slug'], animal__primary_breed__slug\n =self.kwargs['breed_slug'], animal__uuid__contains=self\n .kwargs['slug'])\n except:\n qs = None\n return qs\n\n\nclass AnimalDetailView(DetailView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n return Animal.objects.filter(primary_breed__genus__slug=self.kwargs\n ['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])\n\n def get_object(self, queryset=None):\n if queryset is None:\n queryset = self.get_queryset()\n pk = self.kwargs.get('pk', None)\n slug_or_uuid = self.kwargs.get('slug', None)\n if pk is not None:\n queryset = queryset.filter(pk=pk)\n elif slug_or_uuid is not None:\n try:\n obj = queryset.filter(uuid__contains=slug_or_uuid)[0]\n except:\n try:\n obj = queryset.get(slug=slug_or_uuid)\n except ObjectDoesNotExist:\n raise Http404(_(\n u'No %(verbose_name)s found matching the query') %\n {'verbose_name': queryset.model._meta.verbose_name})\n else:\n raise AttributeError(\n u'Generic detail view %s must be called with either an object pk or a slug.'\n % self.__class__.__name__)\n return obj\n\n def get_context_data(self, **kwargs):\n context = super(AnimalDetailView, self).get_context_data(**kwargs)\n context['note_form'] = BriefNoteForm()\n return context\n",
"step-3": "<mask token>\n\n\nclass BreedDetailView(DetailView):\n <mask token>\n\n def get_queryset(self, *args, **kwargs):\n return Breed.objects.filter(genus__slug=self.kwargs['genus_slug'])\n\n\nclass ProductDetailView(DetailView):\n model = Product\n\n def get_queryset(self, *args, **kwargs):\n return Product.objects.filter(type__slug=self.kwargs['type_slug'])\n\n\nclass MilkingListView(ListView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n try:\n animal = Animal.objects.get(self.kwargs.get('slug', None))\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=\n self.kwargs['genus_slug'], animal__primary_breed__slug=self\n .kwargs['breed_slug'], animal__slug=self.kwargs['slug'])\n except:\n try:\n qs = Milking.objects.filter(animal__primary_breed__genus__slug\n =self.kwargs['genus_slug'], animal__primary_breed__slug\n =self.kwargs['breed_slug'], animal__uuid__contains=self\n .kwargs['slug'])\n except:\n qs = None\n return qs\n\n\nclass AnimalDetailView(DetailView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n return Animal.objects.filter(primary_breed__genus__slug=self.kwargs\n ['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])\n\n def get_object(self, queryset=None):\n if queryset is None:\n queryset = self.get_queryset()\n pk = self.kwargs.get('pk', None)\n slug_or_uuid = self.kwargs.get('slug', None)\n if pk is not None:\n queryset = queryset.filter(pk=pk)\n elif slug_or_uuid is not None:\n try:\n obj = queryset.filter(uuid__contains=slug_or_uuid)[0]\n except:\n try:\n obj = queryset.get(slug=slug_or_uuid)\n except ObjectDoesNotExist:\n raise Http404(_(\n u'No %(verbose_name)s found matching the query') %\n {'verbose_name': queryset.model._meta.verbose_name})\n else:\n raise AttributeError(\n u'Generic detail view %s must be called with either an object pk or a slug.'\n % self.__class__.__name__)\n return obj\n\n def get_context_data(self, **kwargs):\n context = super(AnimalDetailView, self).get_context_data(**kwargs)\n context['note_form'] = BriefNoteForm()\n return context\n",
"step-4": "import datetime\nfrom django.views.generic import DetailView, ListView\nfrom django.core.exceptions import ObjectDoesNotExist\nfrom django.http import HttpResponseRedirect, Http404\nfrom django.shortcuts import get_list_or_404, render_to_response, get_object_or_404\nfrom django.template import RequestContext\nfrom django.core.urlresolvers import reverse\nfrom django.conf import settings\nfrom farm.models import Animal, Breed, Product, Milking\nfrom notes.forms import BriefNoteForm\n\n\nclass BreedDetailView(DetailView):\n model = Breed\n\n def get_queryset(self, *args, **kwargs):\n return Breed.objects.filter(genus__slug=self.kwargs['genus_slug'])\n\n\nclass ProductDetailView(DetailView):\n model = Product\n\n def get_queryset(self, *args, **kwargs):\n return Product.objects.filter(type__slug=self.kwargs['type_slug'])\n\n\nclass MilkingListView(ListView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n try:\n animal = Animal.objects.get(self.kwargs.get('slug', None))\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=\n self.kwargs['genus_slug'], animal__primary_breed__slug=self\n .kwargs['breed_slug'], animal__slug=self.kwargs['slug'])\n except:\n try:\n qs = Milking.objects.filter(animal__primary_breed__genus__slug\n =self.kwargs['genus_slug'], animal__primary_breed__slug\n =self.kwargs['breed_slug'], animal__uuid__contains=self\n .kwargs['slug'])\n except:\n qs = None\n return qs\n\n\nclass AnimalDetailView(DetailView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n return Animal.objects.filter(primary_breed__genus__slug=self.kwargs\n ['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])\n\n def get_object(self, queryset=None):\n if queryset is None:\n queryset = self.get_queryset()\n pk = self.kwargs.get('pk', None)\n slug_or_uuid = self.kwargs.get('slug', None)\n if pk is not None:\n queryset = queryset.filter(pk=pk)\n elif slug_or_uuid is not None:\n try:\n obj = queryset.filter(uuid__contains=slug_or_uuid)[0]\n except:\n try:\n obj = queryset.get(slug=slug_or_uuid)\n except ObjectDoesNotExist:\n raise Http404(_(\n u'No %(verbose_name)s found matching the query') %\n {'verbose_name': queryset.model._meta.verbose_name})\n else:\n raise AttributeError(\n u'Generic detail view %s must be called with either an object pk or a slug.'\n % self.__class__.__name__)\n return obj\n\n def get_context_data(self, **kwargs):\n context = super(AnimalDetailView, self).get_context_data(**kwargs)\n context['note_form'] = BriefNoteForm()\n return context\n",
"step-5": "import datetime\nfrom django.views.generic import DetailView, ListView\n\nfrom django.core.exceptions import ObjectDoesNotExist\nfrom django.http import HttpResponseRedirect, Http404\nfrom django.shortcuts import get_list_or_404, render_to_response, get_object_or_404\nfrom django.template import RequestContext\nfrom django.core.urlresolvers import reverse\nfrom django.conf import settings\n\nfrom farm.models import Animal, Breed, Product, Milking\nfrom notes.forms import BriefNoteForm\n\nclass BreedDetailView(DetailView):\n model = Breed\n\n def get_queryset(self, *args, **kwargs):\n return Breed.objects.filter(genus__slug=self.kwargs['genus_slug'])\n\nclass ProductDetailView(DetailView):\n model = Product\n\n def get_queryset(self, *args, **kwargs):\n return Product.objects.filter(type__slug=self.kwargs['type_slug'])\n\nclass MilkingListView(ListView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n try:\n animal = Animal.objects.get(self.kwargs.get('slug', None))\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=self.kwargs['genus_slug'], animal__primary_breed__slug=self.kwargs['breed_slug'], animal__slug=self.kwargs['slug'])\n except:\n try:\n qs = Milking.objects.filter(animal__primary_breed__genus__slug=self.kwargs['genus_slug'], animal__primary_breed__slug=self.kwargs['breed_slug'], animal__uuid__contains=self.kwargs['slug'])\n except:\n qs = None\n return qs\n\nclass AnimalDetailView(DetailView):\n model = Animal\n\n def get_queryset(self, *args, **kwargs):\n return Animal.objects.filter(primary_breed__genus__slug=self.kwargs['genus_slug'], primary_breed__slug=self.kwargs['breed_slug'])\n\n def get_object(self, queryset=None):\n if queryset is None:\n queryset = self.get_queryset()\n\n pk = self.kwargs.get('pk', None)\n slug_or_uuid = self.kwargs.get('slug', None)\n if pk is not None:\n queryset = queryset.filter(pk=pk)\n\n # Next, try looking up by slug.\n elif slug_or_uuid is not None:\n try:\n obj = queryset.filter(uuid__contains=slug_or_uuid)[0]\n except:\n try:\n obj = queryset.get(slug=slug_or_uuid)\n except ObjectDoesNotExist:\n raise Http404(_(u\"No %(verbose_name)s found matching the query\") %\n {'verbose_name': queryset.model._meta.verbose_name})\n\n # If none of those are defined, it's an error.\n else:\n raise AttributeError(u\"Generic detail view %s must be called with \"\n u\"either an object pk or a slug.\"\n % self.__class__.__name__)\n\n return obj\n\n def get_context_data(self, **kwargs):\n context = super(AnimalDetailView, self).get_context_data(**kwargs)\n context['note_form'] = BriefNoteForm()\n return context\n",
"step-ids": [
7,
10,
13,
15,
16
]
}
|
[
7,
10,
13,
15,
16
] |
#!/usr/bin/env python
import sys, re
window = 2
for line in sys.stdin:
line = line.strip()
twits = line.split()
i = 0
while i <len(twits):
j = 0
while j <len(twits):
if i!= j:
print("%s%s\t%d" % (twits[i]+' ', twits[j], 1))
j+=1
i+=1
|
normal
|
{
"blob_id": "e884825325ceb401142cab0618d9d4e70e475cf5",
"index": 893,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in sys.stdin:\n line = line.strip()\n twits = line.split()\n i = 0\n while i < len(twits):\n j = 0\n while j < len(twits):\n if i != j:\n print('%s%s\\t%d' % (twits[i] + ' ', twits[j], 1))\n j += 1\n i += 1\n",
"step-3": "<mask token>\nwindow = 2\nfor line in sys.stdin:\n line = line.strip()\n twits = line.split()\n i = 0\n while i < len(twits):\n j = 0\n while j < len(twits):\n if i != j:\n print('%s%s\\t%d' % (twits[i] + ' ', twits[j], 1))\n j += 1\n i += 1\n",
"step-4": "import sys, re\nwindow = 2\nfor line in sys.stdin:\n line = line.strip()\n twits = line.split()\n i = 0\n while i < len(twits):\n j = 0\n while j < len(twits):\n if i != j:\n print('%s%s\\t%d' % (twits[i] + ' ', twits[j], 1))\n j += 1\n i += 1\n",
"step-5": "#!/usr/bin/env python\n\nimport sys, re\n\nwindow = 2\n\nfor line in sys.stdin:\n line = line.strip()\n twits = line.split()\n i = 0\n while i <len(twits):\n j = 0\n while j <len(twits):\n if i!= j:\n print(\"%s%s\\t%d\" % (twits[i]+' ', twits[j], 1))\n j+=1\n i+=1",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'qtGSD_DESIGN.ui'
#
# Created by: PyQt4 UI code generator 4.11.4
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(s):
return s
try:
_encoding = QtGui.QApplication.UnicodeUTF8
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig, _encoding)
except AttributeError:
def _translate(context, text, disambig):
return QtGui.QApplication.translate(context, text, disambig)
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName(_fromUtf8("MainWindow"))
MainWindow.resize(661, 728)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(MainWindow.sizePolicy().hasHeightForWidth())
MainWindow.setSizePolicy(sizePolicy)
MainWindow.setMinimumSize(QtCore.QSize(100, 100))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
MainWindow.setFont(font)
MainWindow.setAutoFillBackground(False)
MainWindow.setTabShape(QtGui.QTabWidget.Rounded)
self.centralwidget = QtGui.QWidget(MainWindow)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().hasHeightForWidth())
self.centralwidget.setSizePolicy(sizePolicy)
self.centralwidget.setMinimumSize(QtCore.QSize(100, 100))
self.centralwidget.setMaximumSize(QtCore.QSize(1000, 1000))
self.centralwidget.setObjectName(_fromUtf8("centralwidget"))
self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)
self.verticalLayout.setObjectName(_fromUtf8("verticalLayout"))
self.groupBox_3 = QtGui.QGroupBox(self.centralwidget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Expanding)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().hasHeightForWidth())
self.groupBox_3.setSizePolicy(sizePolicy)
font = QtGui.QFont()
font.setBold(False)
font.setItalic(False)
font.setWeight(50)
self.groupBox_3.setFont(font)
self.groupBox_3.setLayoutDirection(QtCore.Qt.LeftToRight)
self.groupBox_3.setAutoFillBackground(True)
self.groupBox_3.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)
self.groupBox_3.setObjectName(_fromUtf8("groupBox_3"))
self.gridLayout = QtGui.QGridLayout(self.groupBox_3)
self.gridLayout.setSizeConstraint(QtGui.QLayout.SetNoConstraint)
self.gridLayout.setObjectName(_fromUtf8("gridLayout"))
self.MainVertLayout = QtGui.QVBoxLayout()
self.MainVertLayout.setSizeConstraint(QtGui.QLayout.SetMaximumSize)
self.MainVertLayout.setContentsMargins(-1, 10, -1, -1)
self.MainVertLayout.setSpacing(0)
self.MainVertLayout.setObjectName(_fromUtf8("MainVertLayout"))
self.gridLayout.addLayout(self.MainVertLayout, 0, 0, 1, 1)
self.verticalLayout.addWidget(self.groupBox_3)
self.groupBox = QtGui.QGroupBox(self.centralwidget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().hasHeightForWidth())
self.groupBox.setSizePolicy(sizePolicy)
self.groupBox.setMinimumSize(QtCore.QSize(100, 200))
font = QtGui.QFont()
font.setBold(False)
font.setItalic(False)
font.setWeight(50)
self.groupBox.setFont(font)
self.groupBox.setWhatsThis(_fromUtf8(""))
self.groupBox.setObjectName(_fromUtf8("groupBox"))
self.horizontalLayoutWidget_6 = QtGui.QWidget(self.groupBox)
self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(17, 101, 594, 32))
self.horizontalLayoutWidget_6.setObjectName(_fromUtf8("horizontalLayoutWidget_6"))
self.horizontalLayout_9 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_6)
self.horizontalLayout_9.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_9.setObjectName(_fromUtf8("horizontalLayout_9"))
self.label_7 = QtGui.QLabel(self.horizontalLayoutWidget_6)
self.label_7.setMinimumSize(QtCore.QSize(0, 30))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.label_7.setFont(font)
self.label_7.setObjectName(_fromUtf8("label_7"))
self.horizontalLayout_9.addWidget(self.label_7)
self.browserButton_7 = QtGui.QPushButton(self.horizontalLayoutWidget_6)
self.browserButton_7.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.browserButton_7.sizePolicy().hasHeightForWidth())
self.browserButton_7.setSizePolicy(sizePolicy)
self.browserButton_7.setMinimumSize(QtCore.QSize(80, 15))
self.browserButton_7.setObjectName(_fromUtf8("browserButton_7"))
self.horizontalLayout_9.addWidget(self.browserButton_7)
self.filePathEdit_7 = QtGui.QLineEdit(self.horizontalLayoutWidget_6)
self.filePathEdit_7.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.filePathEdit_7.sizePolicy().hasHeightForWidth())
self.filePathEdit_7.setSizePolicy(sizePolicy)
self.filePathEdit_7.setMinimumSize(QtCore.QSize(400, 30))
self.filePathEdit_7.setObjectName(_fromUtf8("filePathEdit_7"))
self.horizontalLayout_9.addWidget(self.filePathEdit_7)
self.horizontalLayoutWidget_9 = QtGui.QWidget(self.groupBox)
self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(17, 25, 592, 32))
self.horizontalLayoutWidget_9.setObjectName(_fromUtf8("horizontalLayoutWidget_9"))
self.horizontalLayout_10 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_9)
self.horizontalLayout_10.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_10.setObjectName(_fromUtf8("horizontalLayout_10"))
self.label_11 = QtGui.QLabel(self.horizontalLayoutWidget_9)
self.label_11.setMinimumSize(QtCore.QSize(0, 30))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.label_11.setFont(font)
self.label_11.setObjectName(_fromUtf8("label_11"))
self.horizontalLayout_10.addWidget(self.label_11)
self.browserButton = QtGui.QPushButton(self.horizontalLayoutWidget_9)
self.browserButton.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.browserButton.sizePolicy().hasHeightForWidth())
self.browserButton.setSizePolicy(sizePolicy)
self.browserButton.setMinimumSize(QtCore.QSize(80, 15))
self.browserButton.setObjectName(_fromUtf8("browserButton"))
self.horizontalLayout_10.addWidget(self.browserButton)
self.filePathEdit_3 = QtGui.QLineEdit(self.horizontalLayoutWidget_9)
self.filePathEdit_3.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Expanding)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.filePathEdit_3.sizePolicy().hasHeightForWidth())
self.filePathEdit_3.setSizePolicy(sizePolicy)
self.filePathEdit_3.setMinimumSize(QtCore.QSize(400, 30))
self.filePathEdit_3.setObjectName(_fromUtf8("filePathEdit_3"))
self.horizontalLayout_10.addWidget(self.filePathEdit_3)
self.horizontalLayoutWidget_10 = QtGui.QWidget(self.groupBox)
self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(17, 63, 592, 32))
self.horizontalLayoutWidget_10.setObjectName(_fromUtf8("horizontalLayoutWidget_10"))
self.horizontalLayout_11 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_10)
self.horizontalLayout_11.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_11.setObjectName(_fromUtf8("horizontalLayout_11"))
self.label_12 = QtGui.QLabel(self.horizontalLayoutWidget_10)
self.label_12.setMinimumSize(QtCore.QSize(0, 30))
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.label_12.setFont(font)
self.label_12.setObjectName(_fromUtf8("label_12"))
self.horizontalLayout_11.addWidget(self.label_12)
self.browserButton_3 = QtGui.QPushButton(self.horizontalLayoutWidget_10)
self.browserButton_3.setEnabled(True)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.browserButton_3.sizePolicy().hasHeightForWidth())
self.browserButton_3.setSizePolicy(sizePolicy)
self.browserButton_3.setMinimumSize(QtCore.QSize(80, 15))
self.browserButton_3.setObjectName(_fromUtf8("browserButton_3"))
self.horizontalLayout_11.addWidget(self.browserButton_3)
self.filePathEdit_5 = QtGui.QLineEdit(self.horizontalLayoutWidget_10)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.filePathEdit_5.sizePolicy().hasHeightForWidth())
self.filePathEdit_5.setSizePolicy(sizePolicy)
self.filePathEdit_5.setMinimumSize(QtCore.QSize(400, 30))
self.filePathEdit_5.setObjectName(_fromUtf8("filePathEdit_5"))
self.horizontalLayout_11.addWidget(self.filePathEdit_5)
self.runButton = QtGui.QPushButton(self.groupBox)
self.runButton.setGeometry(QtCore.QRect(520, 140, 85, 50))
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.runButton.sizePolicy().hasHeightForWidth())
self.runButton.setSizePolicy(sizePolicy)
self.runButton.setMinimumSize(QtCore.QSize(80, 50))
self.runButton.setIconSize(QtCore.QSize(24, 24))
self.runButton.setObjectName(_fromUtf8("runButton"))
self.verticalLayout.addWidget(self.groupBox)
self.groupBox_2 = QtGui.QGroupBox(self.centralwidget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().hasHeightForWidth())
self.groupBox_2.setSizePolicy(sizePolicy)
self.groupBox_2.setMinimumSize(QtCore.QSize(100, 225))
font = QtGui.QFont()
font.setBold(False)
font.setItalic(False)
font.setWeight(50)
self.groupBox_2.setFont(font)
self.groupBox_2.setAutoFillBackground(True)
self.groupBox_2.setObjectName(_fromUtf8("groupBox_2"))
self.horizontalLayoutWidget_4 = QtGui.QWidget(self.groupBox_2)
self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(17, 25, 591, 32))
self.horizontalLayoutWidget_4.setObjectName(_fromUtf8("horizontalLayoutWidget_4"))
self.horizontalLayout_6 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_4)
self.horizontalLayout_6.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_6.setObjectName(_fromUtf8("horizontalLayout_6"))
self.label_3 = QtGui.QLabel(self.horizontalLayoutWidget_4)
font = QtGui.QFont()
font.setBold(False)
font.setWeight(50)
self.label_3.setFont(font)
self.label_3.setObjectName(_fromUtf8("label_3"))
self.horizontalLayout_6.addWidget(self.label_3)
self.browserButton_4 = QtGui.QPushButton(self.horizontalLayoutWidget_4)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.browserButton_4.sizePolicy().hasHeightForWidth())
self.browserButton_4.setSizePolicy(sizePolicy)
self.browserButton_4.setObjectName(_fromUtf8("browserButton_4"))
self.horizontalLayout_6.addWidget(self.browserButton_4)
self.loadButton = QtGui.QPushButton(self.horizontalLayoutWidget_4)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.loadButton.sizePolicy().hasHeightForWidth())
self.loadButton.setSizePolicy(sizePolicy)
self.loadButton.setObjectName(_fromUtf8("loadButton"))
self.horizontalLayout_6.addWidget(self.loadButton)
self.filePathEdit_4 = QtGui.QLineEdit(self.horizontalLayoutWidget_4)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.filePathEdit_4.sizePolicy().hasHeightForWidth())
self.filePathEdit_4.setSizePolicy(sizePolicy)
self.filePathEdit_4.setMinimumSize(QtCore.QSize(300, 30))
self.filePathEdit_4.setObjectName(_fromUtf8("filePathEdit_4"))
self.horizontalLayout_6.addWidget(self.filePathEdit_4)
self.horizontalLayoutWidget_2 = QtGui.QWidget(self.groupBox_2)
self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(17, 63, 481, 29))
self.horizontalLayoutWidget_2.setObjectName(_fromUtf8("horizontalLayoutWidget_2"))
self.horizontalLayout_2 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_2)
self.horizontalLayout_2.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_2.setObjectName(_fromUtf8("horizontalLayout_2"))
self.label_4 = QtGui.QLabel(self.horizontalLayoutWidget_2)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.label_4.sizePolicy().hasHeightForWidth())
self.label_4.setSizePolicy(sizePolicy)
self.label_4.setObjectName(_fromUtf8("label_4"))
self.horizontalLayout_2.addWidget(self.label_4)
self.comboBox = QtGui.QComboBox(self.horizontalLayoutWidget_2)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.comboBox.sizePolicy().hasHeightForWidth())
self.comboBox.setSizePolicy(sizePolicy)
self.comboBox.setObjectName(_fromUtf8("comboBox"))
self.horizontalLayout_2.addWidget(self.comboBox)
self.plotButton = QtGui.QPushButton(self.horizontalLayoutWidget_2)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().hasHeightForWidth())
self.plotButton.setSizePolicy(sizePolicy)
self.plotButton.setObjectName(_fromUtf8("plotButton"))
self.horizontalLayout_2.addWidget(self.plotButton)
self.horizontalLayoutWidget_3 = QtGui.QWidget(self.groupBox_2)
self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(17, 100, 481, 29))
self.horizontalLayoutWidget_3.setObjectName(_fromUtf8("horizontalLayoutWidget_3"))
self.horizontalLayout_3 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_3)
self.horizontalLayout_3.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_3.setObjectName(_fromUtf8("horizontalLayout_3"))
self.label_5 = QtGui.QLabel(self.horizontalLayoutWidget_3)
self.label_5.setObjectName(_fromUtf8("label_5"))
self.horizontalLayout_3.addWidget(self.label_5)
self.comboBox_R1 = QtGui.QComboBox(self.horizontalLayoutWidget_3)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.comboBox_R1.sizePolicy().hasHeightForWidth())
self.comboBox_R1.setSizePolicy(sizePolicy)
self.comboBox_R1.setMinimumSize(QtCore.QSize(0, 0))
self.comboBox_R1.setObjectName(_fromUtf8("comboBox_R1"))
self.horizontalLayout_3.addWidget(self.comboBox_R1)
self.label = QtGui.QLabel(self.horizontalLayoutWidget_3)
self.label.setEnabled(False)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Preferred)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.label.sizePolicy().hasHeightForWidth())
self.label.setSizePolicy(sizePolicy)
self.label.setMinimumSize(QtCore.QSize(30, 0))
self.label.setMaximumSize(QtCore.QSize(30, 29))
font = QtGui.QFont()
font.setBold(True)
font.setItalic(True)
font.setUnderline(False)
font.setWeight(75)
self.label.setFont(font)
self.label.setAutoFillBackground(True)
self.label.setLineWidth(5)
self.label.setAlignment(QtCore.Qt.AlignCenter)
self.label.setObjectName(_fromUtf8("label"))
self.horizontalLayout_3.addWidget(self.label)
self.comboBox_R2 = QtGui.QComboBox(self.horizontalLayoutWidget_3)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.comboBox_R2.sizePolicy().hasHeightForWidth())
self.comboBox_R2.setSizePolicy(sizePolicy)
self.comboBox_R2.setObjectName(_fromUtf8("comboBox_R2"))
self.horizontalLayout_3.addWidget(self.comboBox_R2)
self.plotRangeButton = QtGui.QPushButton(self.horizontalLayoutWidget_3)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.plotRangeButton.sizePolicy().hasHeightForWidth())
self.plotRangeButton.setSizePolicy(sizePolicy)
self.plotRangeButton.setObjectName(_fromUtf8("plotRangeButton"))
self.horizontalLayout_3.addWidget(self.plotRangeButton)
self.horizontalLayoutWidget_7 = QtGui.QWidget(self.groupBox_2)
self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(17, 140, 481, 29))
self.horizontalLayoutWidget_7.setObjectName(_fromUtf8("horizontalLayoutWidget_7"))
self.horizontalLayout_5 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_7)
self.horizontalLayout_5.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout_5.setObjectName(_fromUtf8("horizontalLayout_5"))
self.label_8 = QtGui.QLabel(self.horizontalLayoutWidget_7)
self.label_8.setObjectName(_fromUtf8("label_8"))
self.horizontalLayout_5.addWidget(self.label_8)
self.comboBox_2 = QtGui.QComboBox(self.horizontalLayoutWidget_7)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.comboBox_2.sizePolicy().hasHeightForWidth())
self.comboBox_2.setSizePolicy(sizePolicy)
self.comboBox_2.setObjectName(_fromUtf8("comboBox_2"))
self.horizontalLayout_5.addWidget(self.comboBox_2)
self.checkBox = QtGui.QCheckBox(self.horizontalLayoutWidget_7)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.checkBox.sizePolicy().hasHeightForWidth())
self.checkBox.setSizePolicy(sizePolicy)
self.checkBox.setObjectName(_fromUtf8("checkBox"))
self.horizontalLayout_5.addWidget(self.checkBox)
self.plotImageButton = QtGui.QPushButton(self.horizontalLayoutWidget_7)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.plotImageButton.sizePolicy().hasHeightForWidth())
self.plotImageButton.setSizePolicy(sizePolicy)
self.plotImageButton.setMinimumSize(QtCore.QSize(80, 15))
self.plotImageButton.setObjectName(_fromUtf8("plotImageButton"))
self.horizontalLayout_5.addWidget(self.plotImageButton)
self.clearPlotButton = QtGui.QPushButton(self.groupBox_2)
self.clearPlotButton.setGeometry(QtCore.QRect(520, 140, 85, 50))
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.clearPlotButton.sizePolicy().hasHeightForWidth())
self.clearPlotButton.setSizePolicy(sizePolicy)
self.clearPlotButton.setMinimumSize(QtCore.QSize(80, 50))
self.clearPlotButton.setObjectName(_fromUtf8("clearPlotButton"))
self.horizontalLayoutWidget = QtGui.QWidget(self.groupBox_2)
self.horizontalLayoutWidget.setGeometry(QtCore.QRect(17, 180, 481, 29))
self.horizontalLayoutWidget.setObjectName(_fromUtf8("horizontalLayoutWidget"))
self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)
self.horizontalLayout.setSizeConstraint(QtGui.QLayout.SetFixedSize)
self.horizontalLayout.setObjectName(_fromUtf8("horizontalLayout"))
self.label_9 = QtGui.QLabel(self.horizontalLayoutWidget)
self.label_9.setObjectName(_fromUtf8("label_9"))
self.horizontalLayout.addWidget(self.label_9)
self.pushButton = QtGui.QPushButton(self.horizontalLayoutWidget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().hasHeightForWidth())
self.pushButton.setSizePolicy(sizePolicy)
self.pushButton.setMinimumSize(QtCore.QSize(80, 15))
self.pushButton.setObjectName(_fromUtf8("pushButton"))
self.horizontalLayout.addWidget(self.pushButton)
self.plotStripsButton = QtGui.QPushButton(self.horizontalLayoutWidget)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)
sizePolicy.setHorizontalStretch(0)
sizePolicy.setVerticalStretch(0)
sizePolicy.setHeightForWidth(self.plotStripsButton.sizePolicy().hasHeightForWidth())
self.plotStripsButton.setSizePolicy(sizePolicy)
self.plotStripsButton.setMinimumSize(QtCore.QSize(80, 15))
self.plotStripsButton.setObjectName(_fromUtf8("plotStripsButton"))
self.horizontalLayout.addWidget(self.plotStripsButton)
self.verticalLayout.addWidget(self.groupBox_2)
MainWindow.setCentralWidget(self.centralwidget)
self.statusbar = QtGui.QStatusBar(MainWindow)
self.statusbar.setObjectName(_fromUtf8("statusbar"))
MainWindow.setStatusBar(self.statusbar)
self.toolBar = QtGui.QToolBar(MainWindow)
self.toolBar.setObjectName(_fromUtf8("toolBar"))
MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)
self.menuBar = QtGui.QMenuBar(MainWindow)
self.menuBar.setGeometry(QtCore.QRect(0, 0, 661, 22))
self.menuBar.setObjectName(_fromUtf8("menuBar"))
MainWindow.setMenuBar(self.menuBar)
self.actionOpen = QtGui.QAction(MainWindow)
self.actionOpen.setVisible(True)
self.actionOpen.setObjectName(_fromUtf8("actionOpen"))
self.actionQuit = QtGui.QAction(MainWindow)
self.actionQuit.setObjectName(_fromUtf8("actionQuit"))
self.retranslateUi(MainWindow)
QtCore.QMetaObject.connectSlotsByName(MainWindow)
def retranslateUi(self, MainWindow):
MainWindow.setWindowTitle(_translate("MainWindow", "MainWindow", None))
self.groupBox_3.setTitle(_translate("MainWindow", "PLOT WINDOW", None))
self.groupBox.setTitle(_translate("MainWindow", " BINARY DATA CONVERSION", None))
self.label_7.setText(_translate("MainWindow", " OUTPUT FILE ", None))
self.browserButton_7.setText(_translate("MainWindow", "Browse", None))
self.filePathEdit_7.setText(_translate("MainWindow", "D:\\detdev\\maia\\python\\", None))
self.label_11.setText(_translate("MainWindow", " DECODER FILE", None))
self.browserButton.setText(_translate("MainWindow", "Browse", None))
self.filePathEdit_3.setText(_translate("MainWindow", "D:\\detdev\\maia\\python\\qtGSD\\gsd_parse.out", None))
self.label_12.setText(_translate("MainWindow", " INPUT FILE ", None))
self.browserButton_3.setText(_translate("MainWindow", "Browse", None))
self.filePathEdit_5.setText(_translate("MainWindow", "D:\\detdev\\maia\\python\\", None))
self.runButton.setText(_translate("MainWindow", "Run", None))
self.groupBox_2.setTitle(_translate("MainWindow", " PLOT DATA", None))
self.label_3.setText(_translate("MainWindow", " DATA FILE ", None))
self.browserButton_4.setText(_translate("MainWindow", "Browse", None))
self.loadButton.setText(_translate("MainWindow", "Load", None))
self.filePathEdit_4.setText(_translate("MainWindow", "D:\\detdev\\maia\\python\\", None))
self.label_4.setText(_translate("MainWindow", " PLOT STRIP ", None))
self.plotButton.setText(_translate("MainWindow", "Plot", None))
self.label_5.setText(_translate("MainWindow", " PLOT SERIES", None))
self.label.setText(_translate("MainWindow", "to", None))
self.plotRangeButton.setText(_translate("MainWindow", "Plot", None))
self.label_8.setText(_translate("MainWindow", " PLOT SPECTRA AS 2-D IMAGE", None))
self.checkBox.setText(_translate("MainWindow", "Log", None))
self.plotImageButton.setText(_translate("MainWindow", "Plot Image", None))
self.clearPlotButton.setText(_translate("MainWindow", "Clear", None))
self.label_9.setText(_translate("MainWindow", " PLOT TOTAL COUNTS vs STRIP", None))
self.pushButton.setText(_translate("MainWindow", "Update", None))
self.plotStripsButton.setText(_translate("MainWindow", "Plot Strips", None))
self.toolBar.setWindowTitle(_translate("MainWindow", "toolBar", None))
self.actionOpen.setText(_translate("MainWindow", "Open", None))
self.actionQuit.setText(_translate("MainWindow", "Quit", None))
|
normal
|
{
"blob_id": "9dde8e5fd0e83860ee86cf5402ab6eeb5b07ab2c",
"index": 7761,
"step-1": "<mask token>\n\n\nclass Ui_MainWindow(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Ui_MainWindow(object):\n\n def setupUi(self, MainWindow):\n MainWindow.setObjectName(_fromUtf8('MainWindow'))\n MainWindow.resize(661, 728)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(MainWindow.sizePolicy().\n hasHeightForWidth())\n MainWindow.setSizePolicy(sizePolicy)\n MainWindow.setMinimumSize(QtCore.QSize(100, 100))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n MainWindow.setFont(font)\n MainWindow.setAutoFillBackground(False)\n MainWindow.setTabShape(QtGui.QTabWidget.Rounded)\n self.centralwidget = QtGui.QWidget(MainWindow)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().\n hasHeightForWidth())\n self.centralwidget.setSizePolicy(sizePolicy)\n self.centralwidget.setMinimumSize(QtCore.QSize(100, 100))\n self.centralwidget.setMaximumSize(QtCore.QSize(1000, 1000))\n self.centralwidget.setObjectName(_fromUtf8('centralwidget'))\n self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)\n self.verticalLayout.setObjectName(_fromUtf8('verticalLayout'))\n self.groupBox_3 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().\n hasHeightForWidth())\n self.groupBox_3.setSizePolicy(sizePolicy)\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_3.setFont(font)\n self.groupBox_3.setLayoutDirection(QtCore.Qt.LeftToRight)\n self.groupBox_3.setAutoFillBackground(True)\n self.groupBox_3.setAlignment(QtCore.Qt.AlignLeading | QtCore.Qt.\n AlignLeft | QtCore.Qt.AlignVCenter)\n self.groupBox_3.setObjectName(_fromUtf8('groupBox_3'))\n self.gridLayout = QtGui.QGridLayout(self.groupBox_3)\n self.gridLayout.setSizeConstraint(QtGui.QLayout.SetNoConstraint)\n self.gridLayout.setObjectName(_fromUtf8('gridLayout'))\n self.MainVertLayout = QtGui.QVBoxLayout()\n self.MainVertLayout.setSizeConstraint(QtGui.QLayout.SetMaximumSize)\n self.MainVertLayout.setContentsMargins(-1, 10, -1, -1)\n self.MainVertLayout.setSpacing(0)\n self.MainVertLayout.setObjectName(_fromUtf8('MainVertLayout'))\n self.gridLayout.addLayout(self.MainVertLayout, 0, 0, 1, 1)\n self.verticalLayout.addWidget(self.groupBox_3)\n self.groupBox = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().\n hasHeightForWidth())\n self.groupBox.setSizePolicy(sizePolicy)\n self.groupBox.setMinimumSize(QtCore.QSize(100, 200))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox.setFont(font)\n self.groupBox.setWhatsThis(_fromUtf8(''))\n self.groupBox.setObjectName(_fromUtf8('groupBox'))\n self.horizontalLayoutWidget_6 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(17, 101, 594,\n 32))\n self.horizontalLayoutWidget_6.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_6'))\n self.horizontalLayout_9 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_6)\n self.horizontalLayout_9.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_9.setObjectName(_fromUtf8('horizontalLayout_9'))\n self.label_7 = QtGui.QLabel(self.horizontalLayoutWidget_6)\n self.label_7.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_7.setFont(font)\n self.label_7.setObjectName(_fromUtf8('label_7'))\n self.horizontalLayout_9.addWidget(self.label_7)\n self.browserButton_7 = QtGui.QPushButton(self.horizontalLayoutWidget_6)\n self.browserButton_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_7.sizePolicy().\n hasHeightForWidth())\n self.browserButton_7.setSizePolicy(sizePolicy)\n self.browserButton_7.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_7.setObjectName(_fromUtf8('browserButton_7'))\n self.horizontalLayout_9.addWidget(self.browserButton_7)\n self.filePathEdit_7 = QtGui.QLineEdit(self.horizontalLayoutWidget_6)\n self.filePathEdit_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_7.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_7.setSizePolicy(sizePolicy)\n self.filePathEdit_7.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_7.setObjectName(_fromUtf8('filePathEdit_7'))\n self.horizontalLayout_9.addWidget(self.filePathEdit_7)\n self.horizontalLayoutWidget_9 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(17, 25, 592, 32)\n )\n self.horizontalLayoutWidget_9.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_9'))\n self.horizontalLayout_10 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_9)\n self.horizontalLayout_10.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_10.setObjectName(_fromUtf8('horizontalLayout_10')\n )\n self.label_11 = QtGui.QLabel(self.horizontalLayoutWidget_9)\n self.label_11.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_11.setFont(font)\n self.label_11.setObjectName(_fromUtf8('label_11'))\n self.horizontalLayout_10.addWidget(self.label_11)\n self.browserButton = QtGui.QPushButton(self.horizontalLayoutWidget_9)\n self.browserButton.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton.sizePolicy().\n hasHeightForWidth())\n self.browserButton.setSizePolicy(sizePolicy)\n self.browserButton.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton.setObjectName(_fromUtf8('browserButton'))\n self.horizontalLayout_10.addWidget(self.browserButton)\n self.filePathEdit_3 = QtGui.QLineEdit(self.horizontalLayoutWidget_9)\n self.filePathEdit_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_3.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_3.setSizePolicy(sizePolicy)\n self.filePathEdit_3.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_3.setObjectName(_fromUtf8('filePathEdit_3'))\n self.horizontalLayout_10.addWidget(self.filePathEdit_3)\n self.horizontalLayoutWidget_10 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(17, 63, 592,\n 32))\n self.horizontalLayoutWidget_10.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_10'))\n self.horizontalLayout_11 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_10)\n self.horizontalLayout_11.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_11.setObjectName(_fromUtf8('horizontalLayout_11')\n )\n self.label_12 = QtGui.QLabel(self.horizontalLayoutWidget_10)\n self.label_12.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_12.setFont(font)\n self.label_12.setObjectName(_fromUtf8('label_12'))\n self.horizontalLayout_11.addWidget(self.label_12)\n self.browserButton_3 = QtGui.QPushButton(self.horizontalLayoutWidget_10\n )\n self.browserButton_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_3.sizePolicy().\n hasHeightForWidth())\n self.browserButton_3.setSizePolicy(sizePolicy)\n self.browserButton_3.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_3.setObjectName(_fromUtf8('browserButton_3'))\n self.horizontalLayout_11.addWidget(self.browserButton_3)\n self.filePathEdit_5 = QtGui.QLineEdit(self.horizontalLayoutWidget_10)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_5.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_5.setSizePolicy(sizePolicy)\n self.filePathEdit_5.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_5.setObjectName(_fromUtf8('filePathEdit_5'))\n self.horizontalLayout_11.addWidget(self.filePathEdit_5)\n self.runButton = QtGui.QPushButton(self.groupBox)\n self.runButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.runButton.sizePolicy().\n hasHeightForWidth())\n self.runButton.setSizePolicy(sizePolicy)\n self.runButton.setMinimumSize(QtCore.QSize(80, 50))\n self.runButton.setIconSize(QtCore.QSize(24, 24))\n self.runButton.setObjectName(_fromUtf8('runButton'))\n self.verticalLayout.addWidget(self.groupBox)\n self.groupBox_2 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().\n hasHeightForWidth())\n self.groupBox_2.setSizePolicy(sizePolicy)\n self.groupBox_2.setMinimumSize(QtCore.QSize(100, 225))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_2.setFont(font)\n self.groupBox_2.setAutoFillBackground(True)\n self.groupBox_2.setObjectName(_fromUtf8('groupBox_2'))\n self.horizontalLayoutWidget_4 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(17, 25, 591, 32)\n )\n self.horizontalLayoutWidget_4.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_4'))\n self.horizontalLayout_6 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_4)\n self.horizontalLayout_6.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_6.setObjectName(_fromUtf8('horizontalLayout_6'))\n self.label_3 = QtGui.QLabel(self.horizontalLayoutWidget_4)\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_3.setFont(font)\n self.label_3.setObjectName(_fromUtf8('label_3'))\n self.horizontalLayout_6.addWidget(self.label_3)\n self.browserButton_4 = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_4.sizePolicy().\n hasHeightForWidth())\n self.browserButton_4.setSizePolicy(sizePolicy)\n self.browserButton_4.setObjectName(_fromUtf8('browserButton_4'))\n self.horizontalLayout_6.addWidget(self.browserButton_4)\n self.loadButton = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.loadButton.sizePolicy().\n hasHeightForWidth())\n self.loadButton.setSizePolicy(sizePolicy)\n self.loadButton.setObjectName(_fromUtf8('loadButton'))\n self.horizontalLayout_6.addWidget(self.loadButton)\n self.filePathEdit_4 = QtGui.QLineEdit(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_4.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_4.setSizePolicy(sizePolicy)\n self.filePathEdit_4.setMinimumSize(QtCore.QSize(300, 30))\n self.filePathEdit_4.setObjectName(_fromUtf8('filePathEdit_4'))\n self.horizontalLayout_6.addWidget(self.filePathEdit_4)\n self.horizontalLayoutWidget_2 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(17, 63, 481, 29)\n )\n self.horizontalLayoutWidget_2.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_2'))\n self.horizontalLayout_2 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_2)\n self.horizontalLayout_2.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_2.setObjectName(_fromUtf8('horizontalLayout_2'))\n self.label_4 = QtGui.QLabel(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label_4.sizePolicy().\n hasHeightForWidth())\n self.label_4.setSizePolicy(sizePolicy)\n self.label_4.setObjectName(_fromUtf8('label_4'))\n self.horizontalLayout_2.addWidget(self.label_4)\n self.comboBox = QtGui.QComboBox(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox.sizePolicy().\n hasHeightForWidth())\n self.comboBox.setSizePolicy(sizePolicy)\n self.comboBox.setObjectName(_fromUtf8('comboBox'))\n self.horizontalLayout_2.addWidget(self.comboBox)\n self.plotButton = QtGui.QPushButton(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().\n hasHeightForWidth())\n self.plotButton.setSizePolicy(sizePolicy)\n self.plotButton.setObjectName(_fromUtf8('plotButton'))\n self.horizontalLayout_2.addWidget(self.plotButton)\n self.horizontalLayoutWidget_3 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(17, 100, 481,\n 29))\n self.horizontalLayoutWidget_3.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_3'))\n self.horizontalLayout_3 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_3)\n self.horizontalLayout_3.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_3.setObjectName(_fromUtf8('horizontalLayout_3'))\n self.label_5 = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label_5.setObjectName(_fromUtf8('label_5'))\n self.horizontalLayout_3.addWidget(self.label_5)\n self.comboBox_R1 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R1.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R1.setSizePolicy(sizePolicy)\n self.comboBox_R1.setMinimumSize(QtCore.QSize(0, 0))\n self.comboBox_R1.setObjectName(_fromUtf8('comboBox_R1'))\n self.horizontalLayout_3.addWidget(self.comboBox_R1)\n self.label = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label.setEnabled(False)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label.sizePolicy().\n hasHeightForWidth())\n self.label.setSizePolicy(sizePolicy)\n self.label.setMinimumSize(QtCore.QSize(30, 0))\n self.label.setMaximumSize(QtCore.QSize(30, 29))\n font = QtGui.QFont()\n font.setBold(True)\n font.setItalic(True)\n font.setUnderline(False)\n font.setWeight(75)\n self.label.setFont(font)\n self.label.setAutoFillBackground(True)\n self.label.setLineWidth(5)\n self.label.setAlignment(QtCore.Qt.AlignCenter)\n self.label.setObjectName(_fromUtf8('label'))\n self.horizontalLayout_3.addWidget(self.label)\n self.comboBox_R2 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R2.setSizePolicy(sizePolicy)\n self.comboBox_R2.setObjectName(_fromUtf8('comboBox_R2'))\n self.horizontalLayout_3.addWidget(self.comboBox_R2)\n self.plotRangeButton = QtGui.QPushButton(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotRangeButton.sizePolicy().\n hasHeightForWidth())\n self.plotRangeButton.setSizePolicy(sizePolicy)\n self.plotRangeButton.setObjectName(_fromUtf8('plotRangeButton'))\n self.horizontalLayout_3.addWidget(self.plotRangeButton)\n self.horizontalLayoutWidget_7 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(17, 140, 481,\n 29))\n self.horizontalLayoutWidget_7.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_7'))\n self.horizontalLayout_5 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_7)\n self.horizontalLayout_5.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_5.setObjectName(_fromUtf8('horizontalLayout_5'))\n self.label_8 = QtGui.QLabel(self.horizontalLayoutWidget_7)\n self.label_8.setObjectName(_fromUtf8('label_8'))\n self.horizontalLayout_5.addWidget(self.label_8)\n self.comboBox_2 = QtGui.QComboBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_2.setSizePolicy(sizePolicy)\n self.comboBox_2.setObjectName(_fromUtf8('comboBox_2'))\n self.horizontalLayout_5.addWidget(self.comboBox_2)\n self.checkBox = QtGui.QCheckBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.checkBox.sizePolicy().\n hasHeightForWidth())\n self.checkBox.setSizePolicy(sizePolicy)\n self.checkBox.setObjectName(_fromUtf8('checkBox'))\n self.horizontalLayout_5.addWidget(self.checkBox)\n self.plotImageButton = QtGui.QPushButton(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotImageButton.sizePolicy().\n hasHeightForWidth())\n self.plotImageButton.setSizePolicy(sizePolicy)\n self.plotImageButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotImageButton.setObjectName(_fromUtf8('plotImageButton'))\n self.horizontalLayout_5.addWidget(self.plotImageButton)\n self.clearPlotButton = QtGui.QPushButton(self.groupBox_2)\n self.clearPlotButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.clearPlotButton.sizePolicy().\n hasHeightForWidth())\n self.clearPlotButton.setSizePolicy(sizePolicy)\n self.clearPlotButton.setMinimumSize(QtCore.QSize(80, 50))\n self.clearPlotButton.setObjectName(_fromUtf8('clearPlotButton'))\n self.horizontalLayoutWidget = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget.setGeometry(QtCore.QRect(17, 180, 481, 29))\n self.horizontalLayoutWidget.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget'))\n self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)\n self.horizontalLayout.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout.setObjectName(_fromUtf8('horizontalLayout'))\n self.label_9 = QtGui.QLabel(self.horizontalLayoutWidget)\n self.label_9.setObjectName(_fromUtf8('label_9'))\n self.horizontalLayout.addWidget(self.label_9)\n self.pushButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().\n hasHeightForWidth())\n self.pushButton.setSizePolicy(sizePolicy)\n self.pushButton.setMinimumSize(QtCore.QSize(80, 15))\n self.pushButton.setObjectName(_fromUtf8('pushButton'))\n self.horizontalLayout.addWidget(self.pushButton)\n self.plotStripsButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotStripsButton.sizePolicy().\n hasHeightForWidth())\n self.plotStripsButton.setSizePolicy(sizePolicy)\n self.plotStripsButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotStripsButton.setObjectName(_fromUtf8('plotStripsButton'))\n self.horizontalLayout.addWidget(self.plotStripsButton)\n self.verticalLayout.addWidget(self.groupBox_2)\n MainWindow.setCentralWidget(self.centralwidget)\n self.statusbar = QtGui.QStatusBar(MainWindow)\n self.statusbar.setObjectName(_fromUtf8('statusbar'))\n MainWindow.setStatusBar(self.statusbar)\n self.toolBar = QtGui.QToolBar(MainWindow)\n self.toolBar.setObjectName(_fromUtf8('toolBar'))\n MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)\n self.menuBar = QtGui.QMenuBar(MainWindow)\n self.menuBar.setGeometry(QtCore.QRect(0, 0, 661, 22))\n self.menuBar.setObjectName(_fromUtf8('menuBar'))\n MainWindow.setMenuBar(self.menuBar)\n self.actionOpen = QtGui.QAction(MainWindow)\n self.actionOpen.setVisible(True)\n self.actionOpen.setObjectName(_fromUtf8('actionOpen'))\n self.actionQuit = QtGui.QAction(MainWindow)\n self.actionQuit.setObjectName(_fromUtf8('actionQuit'))\n self.retranslateUi(MainWindow)\n QtCore.QMetaObject.connectSlotsByName(MainWindow)\n\n def retranslateUi(self, MainWindow):\n MainWindow.setWindowTitle(_translate('MainWindow', 'MainWindow', None))\n self.groupBox_3.setTitle(_translate('MainWindow', 'PLOT WINDOW', None))\n self.groupBox.setTitle(_translate('MainWindow',\n ' BINARY DATA CONVERSION', None))\n self.label_7.setText(_translate('MainWindow', ' OUTPUT FILE ', None))\n self.browserButton_7.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_7.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_11.setText(_translate('MainWindow', ' DECODER FILE', None))\n self.browserButton.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_3.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\qtGSD\\\\gsd_parse.out', None))\n self.label_12.setText(_translate('MainWindow', ' INPUT FILE ',\n None))\n self.browserButton_3.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_5.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.runButton.setText(_translate('MainWindow', 'Run', None))\n self.groupBox_2.setTitle(_translate('MainWindow', ' PLOT DATA', None))\n self.label_3.setText(_translate('MainWindow', ' DATA FILE ', None))\n self.browserButton_4.setText(_translate('MainWindow', 'Browse', None))\n self.loadButton.setText(_translate('MainWindow', 'Load', None))\n self.filePathEdit_4.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_4.setText(_translate('MainWindow', ' PLOT STRIP ', None))\n self.plotButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_5.setText(_translate('MainWindow', ' PLOT SERIES', None))\n self.label.setText(_translate('MainWindow', 'to', None))\n self.plotRangeButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_8.setText(_translate('MainWindow',\n ' PLOT SPECTRA AS 2-D IMAGE', None))\n self.checkBox.setText(_translate('MainWindow', 'Log', None))\n self.plotImageButton.setText(_translate('MainWindow', 'Plot Image',\n None))\n self.clearPlotButton.setText(_translate('MainWindow', 'Clear', None))\n self.label_9.setText(_translate('MainWindow',\n ' PLOT TOTAL COUNTS vs STRIP', None))\n self.pushButton.setText(_translate('MainWindow', 'Update', None))\n self.plotStripsButton.setText(_translate('MainWindow',\n 'Plot Strips', None))\n self.toolBar.setWindowTitle(_translate('MainWindow', 'toolBar', None))\n self.actionOpen.setText(_translate('MainWindow', 'Open', None))\n self.actionQuit.setText(_translate('MainWindow', 'Quit', None))\n",
"step-3": "<mask token>\ntry:\n _fromUtf8 = QtCore.QString.fromUtf8\nexcept AttributeError:\n\n def _fromUtf8(s):\n return s\ntry:\n _encoding = QtGui.QApplication.UnicodeUTF8\n\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig, _encoding)\nexcept AttributeError:\n\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig)\n\n\nclass Ui_MainWindow(object):\n\n def setupUi(self, MainWindow):\n MainWindow.setObjectName(_fromUtf8('MainWindow'))\n MainWindow.resize(661, 728)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(MainWindow.sizePolicy().\n hasHeightForWidth())\n MainWindow.setSizePolicy(sizePolicy)\n MainWindow.setMinimumSize(QtCore.QSize(100, 100))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n MainWindow.setFont(font)\n MainWindow.setAutoFillBackground(False)\n MainWindow.setTabShape(QtGui.QTabWidget.Rounded)\n self.centralwidget = QtGui.QWidget(MainWindow)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().\n hasHeightForWidth())\n self.centralwidget.setSizePolicy(sizePolicy)\n self.centralwidget.setMinimumSize(QtCore.QSize(100, 100))\n self.centralwidget.setMaximumSize(QtCore.QSize(1000, 1000))\n self.centralwidget.setObjectName(_fromUtf8('centralwidget'))\n self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)\n self.verticalLayout.setObjectName(_fromUtf8('verticalLayout'))\n self.groupBox_3 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().\n hasHeightForWidth())\n self.groupBox_3.setSizePolicy(sizePolicy)\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_3.setFont(font)\n self.groupBox_3.setLayoutDirection(QtCore.Qt.LeftToRight)\n self.groupBox_3.setAutoFillBackground(True)\n self.groupBox_3.setAlignment(QtCore.Qt.AlignLeading | QtCore.Qt.\n AlignLeft | QtCore.Qt.AlignVCenter)\n self.groupBox_3.setObjectName(_fromUtf8('groupBox_3'))\n self.gridLayout = QtGui.QGridLayout(self.groupBox_3)\n self.gridLayout.setSizeConstraint(QtGui.QLayout.SetNoConstraint)\n self.gridLayout.setObjectName(_fromUtf8('gridLayout'))\n self.MainVertLayout = QtGui.QVBoxLayout()\n self.MainVertLayout.setSizeConstraint(QtGui.QLayout.SetMaximumSize)\n self.MainVertLayout.setContentsMargins(-1, 10, -1, -1)\n self.MainVertLayout.setSpacing(0)\n self.MainVertLayout.setObjectName(_fromUtf8('MainVertLayout'))\n self.gridLayout.addLayout(self.MainVertLayout, 0, 0, 1, 1)\n self.verticalLayout.addWidget(self.groupBox_3)\n self.groupBox = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().\n hasHeightForWidth())\n self.groupBox.setSizePolicy(sizePolicy)\n self.groupBox.setMinimumSize(QtCore.QSize(100, 200))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox.setFont(font)\n self.groupBox.setWhatsThis(_fromUtf8(''))\n self.groupBox.setObjectName(_fromUtf8('groupBox'))\n self.horizontalLayoutWidget_6 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(17, 101, 594,\n 32))\n self.horizontalLayoutWidget_6.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_6'))\n self.horizontalLayout_9 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_6)\n self.horizontalLayout_9.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_9.setObjectName(_fromUtf8('horizontalLayout_9'))\n self.label_7 = QtGui.QLabel(self.horizontalLayoutWidget_6)\n self.label_7.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_7.setFont(font)\n self.label_7.setObjectName(_fromUtf8('label_7'))\n self.horizontalLayout_9.addWidget(self.label_7)\n self.browserButton_7 = QtGui.QPushButton(self.horizontalLayoutWidget_6)\n self.browserButton_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_7.sizePolicy().\n hasHeightForWidth())\n self.browserButton_7.setSizePolicy(sizePolicy)\n self.browserButton_7.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_7.setObjectName(_fromUtf8('browserButton_7'))\n self.horizontalLayout_9.addWidget(self.browserButton_7)\n self.filePathEdit_7 = QtGui.QLineEdit(self.horizontalLayoutWidget_6)\n self.filePathEdit_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_7.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_7.setSizePolicy(sizePolicy)\n self.filePathEdit_7.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_7.setObjectName(_fromUtf8('filePathEdit_7'))\n self.horizontalLayout_9.addWidget(self.filePathEdit_7)\n self.horizontalLayoutWidget_9 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(17, 25, 592, 32)\n )\n self.horizontalLayoutWidget_9.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_9'))\n self.horizontalLayout_10 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_9)\n self.horizontalLayout_10.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_10.setObjectName(_fromUtf8('horizontalLayout_10')\n )\n self.label_11 = QtGui.QLabel(self.horizontalLayoutWidget_9)\n self.label_11.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_11.setFont(font)\n self.label_11.setObjectName(_fromUtf8('label_11'))\n self.horizontalLayout_10.addWidget(self.label_11)\n self.browserButton = QtGui.QPushButton(self.horizontalLayoutWidget_9)\n self.browserButton.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton.sizePolicy().\n hasHeightForWidth())\n self.browserButton.setSizePolicy(sizePolicy)\n self.browserButton.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton.setObjectName(_fromUtf8('browserButton'))\n self.horizontalLayout_10.addWidget(self.browserButton)\n self.filePathEdit_3 = QtGui.QLineEdit(self.horizontalLayoutWidget_9)\n self.filePathEdit_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_3.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_3.setSizePolicy(sizePolicy)\n self.filePathEdit_3.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_3.setObjectName(_fromUtf8('filePathEdit_3'))\n self.horizontalLayout_10.addWidget(self.filePathEdit_3)\n self.horizontalLayoutWidget_10 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(17, 63, 592,\n 32))\n self.horizontalLayoutWidget_10.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_10'))\n self.horizontalLayout_11 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_10)\n self.horizontalLayout_11.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_11.setObjectName(_fromUtf8('horizontalLayout_11')\n )\n self.label_12 = QtGui.QLabel(self.horizontalLayoutWidget_10)\n self.label_12.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_12.setFont(font)\n self.label_12.setObjectName(_fromUtf8('label_12'))\n self.horizontalLayout_11.addWidget(self.label_12)\n self.browserButton_3 = QtGui.QPushButton(self.horizontalLayoutWidget_10\n )\n self.browserButton_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_3.sizePolicy().\n hasHeightForWidth())\n self.browserButton_3.setSizePolicy(sizePolicy)\n self.browserButton_3.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_3.setObjectName(_fromUtf8('browserButton_3'))\n self.horizontalLayout_11.addWidget(self.browserButton_3)\n self.filePathEdit_5 = QtGui.QLineEdit(self.horizontalLayoutWidget_10)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_5.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_5.setSizePolicy(sizePolicy)\n self.filePathEdit_5.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_5.setObjectName(_fromUtf8('filePathEdit_5'))\n self.horizontalLayout_11.addWidget(self.filePathEdit_5)\n self.runButton = QtGui.QPushButton(self.groupBox)\n self.runButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.runButton.sizePolicy().\n hasHeightForWidth())\n self.runButton.setSizePolicy(sizePolicy)\n self.runButton.setMinimumSize(QtCore.QSize(80, 50))\n self.runButton.setIconSize(QtCore.QSize(24, 24))\n self.runButton.setObjectName(_fromUtf8('runButton'))\n self.verticalLayout.addWidget(self.groupBox)\n self.groupBox_2 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().\n hasHeightForWidth())\n self.groupBox_2.setSizePolicy(sizePolicy)\n self.groupBox_2.setMinimumSize(QtCore.QSize(100, 225))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_2.setFont(font)\n self.groupBox_2.setAutoFillBackground(True)\n self.groupBox_2.setObjectName(_fromUtf8('groupBox_2'))\n self.horizontalLayoutWidget_4 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(17, 25, 591, 32)\n )\n self.horizontalLayoutWidget_4.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_4'))\n self.horizontalLayout_6 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_4)\n self.horizontalLayout_6.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_6.setObjectName(_fromUtf8('horizontalLayout_6'))\n self.label_3 = QtGui.QLabel(self.horizontalLayoutWidget_4)\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_3.setFont(font)\n self.label_3.setObjectName(_fromUtf8('label_3'))\n self.horizontalLayout_6.addWidget(self.label_3)\n self.browserButton_4 = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_4.sizePolicy().\n hasHeightForWidth())\n self.browserButton_4.setSizePolicy(sizePolicy)\n self.browserButton_4.setObjectName(_fromUtf8('browserButton_4'))\n self.horizontalLayout_6.addWidget(self.browserButton_4)\n self.loadButton = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.loadButton.sizePolicy().\n hasHeightForWidth())\n self.loadButton.setSizePolicy(sizePolicy)\n self.loadButton.setObjectName(_fromUtf8('loadButton'))\n self.horizontalLayout_6.addWidget(self.loadButton)\n self.filePathEdit_4 = QtGui.QLineEdit(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_4.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_4.setSizePolicy(sizePolicy)\n self.filePathEdit_4.setMinimumSize(QtCore.QSize(300, 30))\n self.filePathEdit_4.setObjectName(_fromUtf8('filePathEdit_4'))\n self.horizontalLayout_6.addWidget(self.filePathEdit_4)\n self.horizontalLayoutWidget_2 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(17, 63, 481, 29)\n )\n self.horizontalLayoutWidget_2.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_2'))\n self.horizontalLayout_2 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_2)\n self.horizontalLayout_2.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_2.setObjectName(_fromUtf8('horizontalLayout_2'))\n self.label_4 = QtGui.QLabel(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label_4.sizePolicy().\n hasHeightForWidth())\n self.label_4.setSizePolicy(sizePolicy)\n self.label_4.setObjectName(_fromUtf8('label_4'))\n self.horizontalLayout_2.addWidget(self.label_4)\n self.comboBox = QtGui.QComboBox(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox.sizePolicy().\n hasHeightForWidth())\n self.comboBox.setSizePolicy(sizePolicy)\n self.comboBox.setObjectName(_fromUtf8('comboBox'))\n self.horizontalLayout_2.addWidget(self.comboBox)\n self.plotButton = QtGui.QPushButton(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().\n hasHeightForWidth())\n self.plotButton.setSizePolicy(sizePolicy)\n self.plotButton.setObjectName(_fromUtf8('plotButton'))\n self.horizontalLayout_2.addWidget(self.plotButton)\n self.horizontalLayoutWidget_3 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(17, 100, 481,\n 29))\n self.horizontalLayoutWidget_3.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_3'))\n self.horizontalLayout_3 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_3)\n self.horizontalLayout_3.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_3.setObjectName(_fromUtf8('horizontalLayout_3'))\n self.label_5 = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label_5.setObjectName(_fromUtf8('label_5'))\n self.horizontalLayout_3.addWidget(self.label_5)\n self.comboBox_R1 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R1.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R1.setSizePolicy(sizePolicy)\n self.comboBox_R1.setMinimumSize(QtCore.QSize(0, 0))\n self.comboBox_R1.setObjectName(_fromUtf8('comboBox_R1'))\n self.horizontalLayout_3.addWidget(self.comboBox_R1)\n self.label = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label.setEnabled(False)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label.sizePolicy().\n hasHeightForWidth())\n self.label.setSizePolicy(sizePolicy)\n self.label.setMinimumSize(QtCore.QSize(30, 0))\n self.label.setMaximumSize(QtCore.QSize(30, 29))\n font = QtGui.QFont()\n font.setBold(True)\n font.setItalic(True)\n font.setUnderline(False)\n font.setWeight(75)\n self.label.setFont(font)\n self.label.setAutoFillBackground(True)\n self.label.setLineWidth(5)\n self.label.setAlignment(QtCore.Qt.AlignCenter)\n self.label.setObjectName(_fromUtf8('label'))\n self.horizontalLayout_3.addWidget(self.label)\n self.comboBox_R2 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R2.setSizePolicy(sizePolicy)\n self.comboBox_R2.setObjectName(_fromUtf8('comboBox_R2'))\n self.horizontalLayout_3.addWidget(self.comboBox_R2)\n self.plotRangeButton = QtGui.QPushButton(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotRangeButton.sizePolicy().\n hasHeightForWidth())\n self.plotRangeButton.setSizePolicy(sizePolicy)\n self.plotRangeButton.setObjectName(_fromUtf8('plotRangeButton'))\n self.horizontalLayout_3.addWidget(self.plotRangeButton)\n self.horizontalLayoutWidget_7 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(17, 140, 481,\n 29))\n self.horizontalLayoutWidget_7.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_7'))\n self.horizontalLayout_5 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_7)\n self.horizontalLayout_5.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_5.setObjectName(_fromUtf8('horizontalLayout_5'))\n self.label_8 = QtGui.QLabel(self.horizontalLayoutWidget_7)\n self.label_8.setObjectName(_fromUtf8('label_8'))\n self.horizontalLayout_5.addWidget(self.label_8)\n self.comboBox_2 = QtGui.QComboBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_2.setSizePolicy(sizePolicy)\n self.comboBox_2.setObjectName(_fromUtf8('comboBox_2'))\n self.horizontalLayout_5.addWidget(self.comboBox_2)\n self.checkBox = QtGui.QCheckBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.checkBox.sizePolicy().\n hasHeightForWidth())\n self.checkBox.setSizePolicy(sizePolicy)\n self.checkBox.setObjectName(_fromUtf8('checkBox'))\n self.horizontalLayout_5.addWidget(self.checkBox)\n self.plotImageButton = QtGui.QPushButton(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotImageButton.sizePolicy().\n hasHeightForWidth())\n self.plotImageButton.setSizePolicy(sizePolicy)\n self.plotImageButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotImageButton.setObjectName(_fromUtf8('plotImageButton'))\n self.horizontalLayout_5.addWidget(self.plotImageButton)\n self.clearPlotButton = QtGui.QPushButton(self.groupBox_2)\n self.clearPlotButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.clearPlotButton.sizePolicy().\n hasHeightForWidth())\n self.clearPlotButton.setSizePolicy(sizePolicy)\n self.clearPlotButton.setMinimumSize(QtCore.QSize(80, 50))\n self.clearPlotButton.setObjectName(_fromUtf8('clearPlotButton'))\n self.horizontalLayoutWidget = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget.setGeometry(QtCore.QRect(17, 180, 481, 29))\n self.horizontalLayoutWidget.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget'))\n self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)\n self.horizontalLayout.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout.setObjectName(_fromUtf8('horizontalLayout'))\n self.label_9 = QtGui.QLabel(self.horizontalLayoutWidget)\n self.label_9.setObjectName(_fromUtf8('label_9'))\n self.horizontalLayout.addWidget(self.label_9)\n self.pushButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().\n hasHeightForWidth())\n self.pushButton.setSizePolicy(sizePolicy)\n self.pushButton.setMinimumSize(QtCore.QSize(80, 15))\n self.pushButton.setObjectName(_fromUtf8('pushButton'))\n self.horizontalLayout.addWidget(self.pushButton)\n self.plotStripsButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotStripsButton.sizePolicy().\n hasHeightForWidth())\n self.plotStripsButton.setSizePolicy(sizePolicy)\n self.plotStripsButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotStripsButton.setObjectName(_fromUtf8('plotStripsButton'))\n self.horizontalLayout.addWidget(self.plotStripsButton)\n self.verticalLayout.addWidget(self.groupBox_2)\n MainWindow.setCentralWidget(self.centralwidget)\n self.statusbar = QtGui.QStatusBar(MainWindow)\n self.statusbar.setObjectName(_fromUtf8('statusbar'))\n MainWindow.setStatusBar(self.statusbar)\n self.toolBar = QtGui.QToolBar(MainWindow)\n self.toolBar.setObjectName(_fromUtf8('toolBar'))\n MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)\n self.menuBar = QtGui.QMenuBar(MainWindow)\n self.menuBar.setGeometry(QtCore.QRect(0, 0, 661, 22))\n self.menuBar.setObjectName(_fromUtf8('menuBar'))\n MainWindow.setMenuBar(self.menuBar)\n self.actionOpen = QtGui.QAction(MainWindow)\n self.actionOpen.setVisible(True)\n self.actionOpen.setObjectName(_fromUtf8('actionOpen'))\n self.actionQuit = QtGui.QAction(MainWindow)\n self.actionQuit.setObjectName(_fromUtf8('actionQuit'))\n self.retranslateUi(MainWindow)\n QtCore.QMetaObject.connectSlotsByName(MainWindow)\n\n def retranslateUi(self, MainWindow):\n MainWindow.setWindowTitle(_translate('MainWindow', 'MainWindow', None))\n self.groupBox_3.setTitle(_translate('MainWindow', 'PLOT WINDOW', None))\n self.groupBox.setTitle(_translate('MainWindow',\n ' BINARY DATA CONVERSION', None))\n self.label_7.setText(_translate('MainWindow', ' OUTPUT FILE ', None))\n self.browserButton_7.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_7.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_11.setText(_translate('MainWindow', ' DECODER FILE', None))\n self.browserButton.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_3.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\qtGSD\\\\gsd_parse.out', None))\n self.label_12.setText(_translate('MainWindow', ' INPUT FILE ',\n None))\n self.browserButton_3.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_5.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.runButton.setText(_translate('MainWindow', 'Run', None))\n self.groupBox_2.setTitle(_translate('MainWindow', ' PLOT DATA', None))\n self.label_3.setText(_translate('MainWindow', ' DATA FILE ', None))\n self.browserButton_4.setText(_translate('MainWindow', 'Browse', None))\n self.loadButton.setText(_translate('MainWindow', 'Load', None))\n self.filePathEdit_4.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_4.setText(_translate('MainWindow', ' PLOT STRIP ', None))\n self.plotButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_5.setText(_translate('MainWindow', ' PLOT SERIES', None))\n self.label.setText(_translate('MainWindow', 'to', None))\n self.plotRangeButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_8.setText(_translate('MainWindow',\n ' PLOT SPECTRA AS 2-D IMAGE', None))\n self.checkBox.setText(_translate('MainWindow', 'Log', None))\n self.plotImageButton.setText(_translate('MainWindow', 'Plot Image',\n None))\n self.clearPlotButton.setText(_translate('MainWindow', 'Clear', None))\n self.label_9.setText(_translate('MainWindow',\n ' PLOT TOTAL COUNTS vs STRIP', None))\n self.pushButton.setText(_translate('MainWindow', 'Update', None))\n self.plotStripsButton.setText(_translate('MainWindow',\n 'Plot Strips', None))\n self.toolBar.setWindowTitle(_translate('MainWindow', 'toolBar', None))\n self.actionOpen.setText(_translate('MainWindow', 'Open', None))\n self.actionQuit.setText(_translate('MainWindow', 'Quit', None))\n",
"step-4": "from PyQt4 import QtCore, QtGui\ntry:\n _fromUtf8 = QtCore.QString.fromUtf8\nexcept AttributeError:\n\n def _fromUtf8(s):\n return s\ntry:\n _encoding = QtGui.QApplication.UnicodeUTF8\n\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig, _encoding)\nexcept AttributeError:\n\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig)\n\n\nclass Ui_MainWindow(object):\n\n def setupUi(self, MainWindow):\n MainWindow.setObjectName(_fromUtf8('MainWindow'))\n MainWindow.resize(661, 728)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(MainWindow.sizePolicy().\n hasHeightForWidth())\n MainWindow.setSizePolicy(sizePolicy)\n MainWindow.setMinimumSize(QtCore.QSize(100, 100))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n MainWindow.setFont(font)\n MainWindow.setAutoFillBackground(False)\n MainWindow.setTabShape(QtGui.QTabWidget.Rounded)\n self.centralwidget = QtGui.QWidget(MainWindow)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().\n hasHeightForWidth())\n self.centralwidget.setSizePolicy(sizePolicy)\n self.centralwidget.setMinimumSize(QtCore.QSize(100, 100))\n self.centralwidget.setMaximumSize(QtCore.QSize(1000, 1000))\n self.centralwidget.setObjectName(_fromUtf8('centralwidget'))\n self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)\n self.verticalLayout.setObjectName(_fromUtf8('verticalLayout'))\n self.groupBox_3 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().\n hasHeightForWidth())\n self.groupBox_3.setSizePolicy(sizePolicy)\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_3.setFont(font)\n self.groupBox_3.setLayoutDirection(QtCore.Qt.LeftToRight)\n self.groupBox_3.setAutoFillBackground(True)\n self.groupBox_3.setAlignment(QtCore.Qt.AlignLeading | QtCore.Qt.\n AlignLeft | QtCore.Qt.AlignVCenter)\n self.groupBox_3.setObjectName(_fromUtf8('groupBox_3'))\n self.gridLayout = QtGui.QGridLayout(self.groupBox_3)\n self.gridLayout.setSizeConstraint(QtGui.QLayout.SetNoConstraint)\n self.gridLayout.setObjectName(_fromUtf8('gridLayout'))\n self.MainVertLayout = QtGui.QVBoxLayout()\n self.MainVertLayout.setSizeConstraint(QtGui.QLayout.SetMaximumSize)\n self.MainVertLayout.setContentsMargins(-1, 10, -1, -1)\n self.MainVertLayout.setSpacing(0)\n self.MainVertLayout.setObjectName(_fromUtf8('MainVertLayout'))\n self.gridLayout.addLayout(self.MainVertLayout, 0, 0, 1, 1)\n self.verticalLayout.addWidget(self.groupBox_3)\n self.groupBox = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().\n hasHeightForWidth())\n self.groupBox.setSizePolicy(sizePolicy)\n self.groupBox.setMinimumSize(QtCore.QSize(100, 200))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox.setFont(font)\n self.groupBox.setWhatsThis(_fromUtf8(''))\n self.groupBox.setObjectName(_fromUtf8('groupBox'))\n self.horizontalLayoutWidget_6 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(17, 101, 594,\n 32))\n self.horizontalLayoutWidget_6.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_6'))\n self.horizontalLayout_9 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_6)\n self.horizontalLayout_9.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_9.setObjectName(_fromUtf8('horizontalLayout_9'))\n self.label_7 = QtGui.QLabel(self.horizontalLayoutWidget_6)\n self.label_7.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_7.setFont(font)\n self.label_7.setObjectName(_fromUtf8('label_7'))\n self.horizontalLayout_9.addWidget(self.label_7)\n self.browserButton_7 = QtGui.QPushButton(self.horizontalLayoutWidget_6)\n self.browserButton_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_7.sizePolicy().\n hasHeightForWidth())\n self.browserButton_7.setSizePolicy(sizePolicy)\n self.browserButton_7.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_7.setObjectName(_fromUtf8('browserButton_7'))\n self.horizontalLayout_9.addWidget(self.browserButton_7)\n self.filePathEdit_7 = QtGui.QLineEdit(self.horizontalLayoutWidget_6)\n self.filePathEdit_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_7.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_7.setSizePolicy(sizePolicy)\n self.filePathEdit_7.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_7.setObjectName(_fromUtf8('filePathEdit_7'))\n self.horizontalLayout_9.addWidget(self.filePathEdit_7)\n self.horizontalLayoutWidget_9 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(17, 25, 592, 32)\n )\n self.horizontalLayoutWidget_9.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_9'))\n self.horizontalLayout_10 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_9)\n self.horizontalLayout_10.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_10.setObjectName(_fromUtf8('horizontalLayout_10')\n )\n self.label_11 = QtGui.QLabel(self.horizontalLayoutWidget_9)\n self.label_11.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_11.setFont(font)\n self.label_11.setObjectName(_fromUtf8('label_11'))\n self.horizontalLayout_10.addWidget(self.label_11)\n self.browserButton = QtGui.QPushButton(self.horizontalLayoutWidget_9)\n self.browserButton.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton.sizePolicy().\n hasHeightForWidth())\n self.browserButton.setSizePolicy(sizePolicy)\n self.browserButton.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton.setObjectName(_fromUtf8('browserButton'))\n self.horizontalLayout_10.addWidget(self.browserButton)\n self.filePathEdit_3 = QtGui.QLineEdit(self.horizontalLayoutWidget_9)\n self.filePathEdit_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_3.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_3.setSizePolicy(sizePolicy)\n self.filePathEdit_3.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_3.setObjectName(_fromUtf8('filePathEdit_3'))\n self.horizontalLayout_10.addWidget(self.filePathEdit_3)\n self.horizontalLayoutWidget_10 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(17, 63, 592,\n 32))\n self.horizontalLayoutWidget_10.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_10'))\n self.horizontalLayout_11 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_10)\n self.horizontalLayout_11.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_11.setObjectName(_fromUtf8('horizontalLayout_11')\n )\n self.label_12 = QtGui.QLabel(self.horizontalLayoutWidget_10)\n self.label_12.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_12.setFont(font)\n self.label_12.setObjectName(_fromUtf8('label_12'))\n self.horizontalLayout_11.addWidget(self.label_12)\n self.browserButton_3 = QtGui.QPushButton(self.horizontalLayoutWidget_10\n )\n self.browserButton_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_3.sizePolicy().\n hasHeightForWidth())\n self.browserButton_3.setSizePolicy(sizePolicy)\n self.browserButton_3.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_3.setObjectName(_fromUtf8('browserButton_3'))\n self.horizontalLayout_11.addWidget(self.browserButton_3)\n self.filePathEdit_5 = QtGui.QLineEdit(self.horizontalLayoutWidget_10)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_5.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_5.setSizePolicy(sizePolicy)\n self.filePathEdit_5.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_5.setObjectName(_fromUtf8('filePathEdit_5'))\n self.horizontalLayout_11.addWidget(self.filePathEdit_5)\n self.runButton = QtGui.QPushButton(self.groupBox)\n self.runButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.runButton.sizePolicy().\n hasHeightForWidth())\n self.runButton.setSizePolicy(sizePolicy)\n self.runButton.setMinimumSize(QtCore.QSize(80, 50))\n self.runButton.setIconSize(QtCore.QSize(24, 24))\n self.runButton.setObjectName(_fromUtf8('runButton'))\n self.verticalLayout.addWidget(self.groupBox)\n self.groupBox_2 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().\n hasHeightForWidth())\n self.groupBox_2.setSizePolicy(sizePolicy)\n self.groupBox_2.setMinimumSize(QtCore.QSize(100, 225))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_2.setFont(font)\n self.groupBox_2.setAutoFillBackground(True)\n self.groupBox_2.setObjectName(_fromUtf8('groupBox_2'))\n self.horizontalLayoutWidget_4 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(17, 25, 591, 32)\n )\n self.horizontalLayoutWidget_4.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_4'))\n self.horizontalLayout_6 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_4)\n self.horizontalLayout_6.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_6.setObjectName(_fromUtf8('horizontalLayout_6'))\n self.label_3 = QtGui.QLabel(self.horizontalLayoutWidget_4)\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_3.setFont(font)\n self.label_3.setObjectName(_fromUtf8('label_3'))\n self.horizontalLayout_6.addWidget(self.label_3)\n self.browserButton_4 = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_4.sizePolicy().\n hasHeightForWidth())\n self.browserButton_4.setSizePolicy(sizePolicy)\n self.browserButton_4.setObjectName(_fromUtf8('browserButton_4'))\n self.horizontalLayout_6.addWidget(self.browserButton_4)\n self.loadButton = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.loadButton.sizePolicy().\n hasHeightForWidth())\n self.loadButton.setSizePolicy(sizePolicy)\n self.loadButton.setObjectName(_fromUtf8('loadButton'))\n self.horizontalLayout_6.addWidget(self.loadButton)\n self.filePathEdit_4 = QtGui.QLineEdit(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_4.sizePolicy().\n hasHeightForWidth())\n self.filePathEdit_4.setSizePolicy(sizePolicy)\n self.filePathEdit_4.setMinimumSize(QtCore.QSize(300, 30))\n self.filePathEdit_4.setObjectName(_fromUtf8('filePathEdit_4'))\n self.horizontalLayout_6.addWidget(self.filePathEdit_4)\n self.horizontalLayoutWidget_2 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(17, 63, 481, 29)\n )\n self.horizontalLayoutWidget_2.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_2'))\n self.horizontalLayout_2 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_2)\n self.horizontalLayout_2.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_2.setObjectName(_fromUtf8('horizontalLayout_2'))\n self.label_4 = QtGui.QLabel(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label_4.sizePolicy().\n hasHeightForWidth())\n self.label_4.setSizePolicy(sizePolicy)\n self.label_4.setObjectName(_fromUtf8('label_4'))\n self.horizontalLayout_2.addWidget(self.label_4)\n self.comboBox = QtGui.QComboBox(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox.sizePolicy().\n hasHeightForWidth())\n self.comboBox.setSizePolicy(sizePolicy)\n self.comboBox.setObjectName(_fromUtf8('comboBox'))\n self.horizontalLayout_2.addWidget(self.comboBox)\n self.plotButton = QtGui.QPushButton(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().\n hasHeightForWidth())\n self.plotButton.setSizePolicy(sizePolicy)\n self.plotButton.setObjectName(_fromUtf8('plotButton'))\n self.horizontalLayout_2.addWidget(self.plotButton)\n self.horizontalLayoutWidget_3 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(17, 100, 481,\n 29))\n self.horizontalLayoutWidget_3.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_3'))\n self.horizontalLayout_3 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_3)\n self.horizontalLayout_3.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_3.setObjectName(_fromUtf8('horizontalLayout_3'))\n self.label_5 = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label_5.setObjectName(_fromUtf8('label_5'))\n self.horizontalLayout_3.addWidget(self.label_5)\n self.comboBox_R1 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R1.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R1.setSizePolicy(sizePolicy)\n self.comboBox_R1.setMinimumSize(QtCore.QSize(0, 0))\n self.comboBox_R1.setObjectName(_fromUtf8('comboBox_R1'))\n self.horizontalLayout_3.addWidget(self.comboBox_R1)\n self.label = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label.setEnabled(False)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label.sizePolicy().\n hasHeightForWidth())\n self.label.setSizePolicy(sizePolicy)\n self.label.setMinimumSize(QtCore.QSize(30, 0))\n self.label.setMaximumSize(QtCore.QSize(30, 29))\n font = QtGui.QFont()\n font.setBold(True)\n font.setItalic(True)\n font.setUnderline(False)\n font.setWeight(75)\n self.label.setFont(font)\n self.label.setAutoFillBackground(True)\n self.label.setLineWidth(5)\n self.label.setAlignment(QtCore.Qt.AlignCenter)\n self.label.setObjectName(_fromUtf8('label'))\n self.horizontalLayout_3.addWidget(self.label)\n self.comboBox_R2 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_R2.setSizePolicy(sizePolicy)\n self.comboBox_R2.setObjectName(_fromUtf8('comboBox_R2'))\n self.horizontalLayout_3.addWidget(self.comboBox_R2)\n self.plotRangeButton = QtGui.QPushButton(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotRangeButton.sizePolicy().\n hasHeightForWidth())\n self.plotRangeButton.setSizePolicy(sizePolicy)\n self.plotRangeButton.setObjectName(_fromUtf8('plotRangeButton'))\n self.horizontalLayout_3.addWidget(self.plotRangeButton)\n self.horizontalLayoutWidget_7 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(17, 140, 481,\n 29))\n self.horizontalLayoutWidget_7.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget_7'))\n self.horizontalLayout_5 = QtGui.QHBoxLayout(self.\n horizontalLayoutWidget_7)\n self.horizontalLayout_5.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_5.setObjectName(_fromUtf8('horizontalLayout_5'))\n self.label_8 = QtGui.QLabel(self.horizontalLayoutWidget_7)\n self.label_8.setObjectName(_fromUtf8('label_8'))\n self.horizontalLayout_5.addWidget(self.label_8)\n self.comboBox_2 = QtGui.QComboBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_2.sizePolicy().\n hasHeightForWidth())\n self.comboBox_2.setSizePolicy(sizePolicy)\n self.comboBox_2.setObjectName(_fromUtf8('comboBox_2'))\n self.horizontalLayout_5.addWidget(self.comboBox_2)\n self.checkBox = QtGui.QCheckBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.checkBox.sizePolicy().\n hasHeightForWidth())\n self.checkBox.setSizePolicy(sizePolicy)\n self.checkBox.setObjectName(_fromUtf8('checkBox'))\n self.horizontalLayout_5.addWidget(self.checkBox)\n self.plotImageButton = QtGui.QPushButton(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotImageButton.sizePolicy().\n hasHeightForWidth())\n self.plotImageButton.setSizePolicy(sizePolicy)\n self.plotImageButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotImageButton.setObjectName(_fromUtf8('plotImageButton'))\n self.horizontalLayout_5.addWidget(self.plotImageButton)\n self.clearPlotButton = QtGui.QPushButton(self.groupBox_2)\n self.clearPlotButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.clearPlotButton.sizePolicy().\n hasHeightForWidth())\n self.clearPlotButton.setSizePolicy(sizePolicy)\n self.clearPlotButton.setMinimumSize(QtCore.QSize(80, 50))\n self.clearPlotButton.setObjectName(_fromUtf8('clearPlotButton'))\n self.horizontalLayoutWidget = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget.setGeometry(QtCore.QRect(17, 180, 481, 29))\n self.horizontalLayoutWidget.setObjectName(_fromUtf8(\n 'horizontalLayoutWidget'))\n self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)\n self.horizontalLayout.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout.setObjectName(_fromUtf8('horizontalLayout'))\n self.label_9 = QtGui.QLabel(self.horizontalLayoutWidget)\n self.label_9.setObjectName(_fromUtf8('label_9'))\n self.horizontalLayout.addWidget(self.label_9)\n self.pushButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().\n hasHeightForWidth())\n self.pushButton.setSizePolicy(sizePolicy)\n self.pushButton.setMinimumSize(QtCore.QSize(80, 15))\n self.pushButton.setObjectName(_fromUtf8('pushButton'))\n self.horizontalLayout.addWidget(self.pushButton)\n self.plotStripsButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.\n QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotStripsButton.sizePolicy().\n hasHeightForWidth())\n self.plotStripsButton.setSizePolicy(sizePolicy)\n self.plotStripsButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotStripsButton.setObjectName(_fromUtf8('plotStripsButton'))\n self.horizontalLayout.addWidget(self.plotStripsButton)\n self.verticalLayout.addWidget(self.groupBox_2)\n MainWindow.setCentralWidget(self.centralwidget)\n self.statusbar = QtGui.QStatusBar(MainWindow)\n self.statusbar.setObjectName(_fromUtf8('statusbar'))\n MainWindow.setStatusBar(self.statusbar)\n self.toolBar = QtGui.QToolBar(MainWindow)\n self.toolBar.setObjectName(_fromUtf8('toolBar'))\n MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)\n self.menuBar = QtGui.QMenuBar(MainWindow)\n self.menuBar.setGeometry(QtCore.QRect(0, 0, 661, 22))\n self.menuBar.setObjectName(_fromUtf8('menuBar'))\n MainWindow.setMenuBar(self.menuBar)\n self.actionOpen = QtGui.QAction(MainWindow)\n self.actionOpen.setVisible(True)\n self.actionOpen.setObjectName(_fromUtf8('actionOpen'))\n self.actionQuit = QtGui.QAction(MainWindow)\n self.actionQuit.setObjectName(_fromUtf8('actionQuit'))\n self.retranslateUi(MainWindow)\n QtCore.QMetaObject.connectSlotsByName(MainWindow)\n\n def retranslateUi(self, MainWindow):\n MainWindow.setWindowTitle(_translate('MainWindow', 'MainWindow', None))\n self.groupBox_3.setTitle(_translate('MainWindow', 'PLOT WINDOW', None))\n self.groupBox.setTitle(_translate('MainWindow',\n ' BINARY DATA CONVERSION', None))\n self.label_7.setText(_translate('MainWindow', ' OUTPUT FILE ', None))\n self.browserButton_7.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_7.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_11.setText(_translate('MainWindow', ' DECODER FILE', None))\n self.browserButton.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_3.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\qtGSD\\\\gsd_parse.out', None))\n self.label_12.setText(_translate('MainWindow', ' INPUT FILE ',\n None))\n self.browserButton_3.setText(_translate('MainWindow', 'Browse', None))\n self.filePathEdit_5.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.runButton.setText(_translate('MainWindow', 'Run', None))\n self.groupBox_2.setTitle(_translate('MainWindow', ' PLOT DATA', None))\n self.label_3.setText(_translate('MainWindow', ' DATA FILE ', None))\n self.browserButton_4.setText(_translate('MainWindow', 'Browse', None))\n self.loadButton.setText(_translate('MainWindow', 'Load', None))\n self.filePathEdit_4.setText(_translate('MainWindow',\n 'D:\\\\detdev\\\\maia\\\\python\\\\', None))\n self.label_4.setText(_translate('MainWindow', ' PLOT STRIP ', None))\n self.plotButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_5.setText(_translate('MainWindow', ' PLOT SERIES', None))\n self.label.setText(_translate('MainWindow', 'to', None))\n self.plotRangeButton.setText(_translate('MainWindow', 'Plot', None))\n self.label_8.setText(_translate('MainWindow',\n ' PLOT SPECTRA AS 2-D IMAGE', None))\n self.checkBox.setText(_translate('MainWindow', 'Log', None))\n self.plotImageButton.setText(_translate('MainWindow', 'Plot Image',\n None))\n self.clearPlotButton.setText(_translate('MainWindow', 'Clear', None))\n self.label_9.setText(_translate('MainWindow',\n ' PLOT TOTAL COUNTS vs STRIP', None))\n self.pushButton.setText(_translate('MainWindow', 'Update', None))\n self.plotStripsButton.setText(_translate('MainWindow',\n 'Plot Strips', None))\n self.toolBar.setWindowTitle(_translate('MainWindow', 'toolBar', None))\n self.actionOpen.setText(_translate('MainWindow', 'Open', None))\n self.actionQuit.setText(_translate('MainWindow', 'Quit', None))\n",
"step-5": "# -*- coding: utf-8 -*-\n\n# Form implementation generated from reading ui file 'qtGSD_DESIGN.ui'\n#\n# Created by: PyQt4 UI code generator 4.11.4\n#\n# WARNING! All changes made in this file will be lost!\n\nfrom PyQt4 import QtCore, QtGui\n\ntry:\n _fromUtf8 = QtCore.QString.fromUtf8\nexcept AttributeError:\n def _fromUtf8(s):\n return s\n\ntry:\n _encoding = QtGui.QApplication.UnicodeUTF8\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig, _encoding)\nexcept AttributeError:\n def _translate(context, text, disambig):\n return QtGui.QApplication.translate(context, text, disambig)\n\nclass Ui_MainWindow(object):\n def setupUi(self, MainWindow):\n MainWindow.setObjectName(_fromUtf8(\"MainWindow\"))\n MainWindow.resize(661, 728)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(MainWindow.sizePolicy().hasHeightForWidth())\n MainWindow.setSizePolicy(sizePolicy)\n MainWindow.setMinimumSize(QtCore.QSize(100, 100))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n MainWindow.setFont(font)\n MainWindow.setAutoFillBackground(False)\n MainWindow.setTabShape(QtGui.QTabWidget.Rounded)\n self.centralwidget = QtGui.QWidget(MainWindow)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.centralwidget.sizePolicy().hasHeightForWidth())\n self.centralwidget.setSizePolicy(sizePolicy)\n self.centralwidget.setMinimumSize(QtCore.QSize(100, 100))\n self.centralwidget.setMaximumSize(QtCore.QSize(1000, 1000))\n self.centralwidget.setObjectName(_fromUtf8(\"centralwidget\"))\n self.verticalLayout = QtGui.QVBoxLayout(self.centralwidget)\n self.verticalLayout.setObjectName(_fromUtf8(\"verticalLayout\"))\n self.groupBox_3 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_3.sizePolicy().hasHeightForWidth())\n self.groupBox_3.setSizePolicy(sizePolicy)\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_3.setFont(font)\n self.groupBox_3.setLayoutDirection(QtCore.Qt.LeftToRight)\n self.groupBox_3.setAutoFillBackground(True)\n self.groupBox_3.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter)\n self.groupBox_3.setObjectName(_fromUtf8(\"groupBox_3\"))\n self.gridLayout = QtGui.QGridLayout(self.groupBox_3)\n self.gridLayout.setSizeConstraint(QtGui.QLayout.SetNoConstraint)\n self.gridLayout.setObjectName(_fromUtf8(\"gridLayout\"))\n self.MainVertLayout = QtGui.QVBoxLayout()\n self.MainVertLayout.setSizeConstraint(QtGui.QLayout.SetMaximumSize)\n self.MainVertLayout.setContentsMargins(-1, 10, -1, -1)\n self.MainVertLayout.setSpacing(0)\n self.MainVertLayout.setObjectName(_fromUtf8(\"MainVertLayout\"))\n self.gridLayout.addLayout(self.MainVertLayout, 0, 0, 1, 1)\n self.verticalLayout.addWidget(self.groupBox_3)\n self.groupBox = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox.sizePolicy().hasHeightForWidth())\n self.groupBox.setSizePolicy(sizePolicy)\n self.groupBox.setMinimumSize(QtCore.QSize(100, 200))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox.setFont(font)\n self.groupBox.setWhatsThis(_fromUtf8(\"\"))\n self.groupBox.setObjectName(_fromUtf8(\"groupBox\"))\n self.horizontalLayoutWidget_6 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_6.setGeometry(QtCore.QRect(17, 101, 594, 32))\n self.horizontalLayoutWidget_6.setObjectName(_fromUtf8(\"horizontalLayoutWidget_6\"))\n self.horizontalLayout_9 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_6)\n self.horizontalLayout_9.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_9.setObjectName(_fromUtf8(\"horizontalLayout_9\"))\n self.label_7 = QtGui.QLabel(self.horizontalLayoutWidget_6)\n self.label_7.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_7.setFont(font)\n self.label_7.setObjectName(_fromUtf8(\"label_7\"))\n self.horizontalLayout_9.addWidget(self.label_7)\n self.browserButton_7 = QtGui.QPushButton(self.horizontalLayoutWidget_6)\n self.browserButton_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_7.sizePolicy().hasHeightForWidth())\n self.browserButton_7.setSizePolicy(sizePolicy)\n self.browserButton_7.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_7.setObjectName(_fromUtf8(\"browserButton_7\"))\n self.horizontalLayout_9.addWidget(self.browserButton_7)\n self.filePathEdit_7 = QtGui.QLineEdit(self.horizontalLayoutWidget_6)\n self.filePathEdit_7.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_7.sizePolicy().hasHeightForWidth())\n self.filePathEdit_7.setSizePolicy(sizePolicy)\n self.filePathEdit_7.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_7.setObjectName(_fromUtf8(\"filePathEdit_7\"))\n self.horizontalLayout_9.addWidget(self.filePathEdit_7)\n self.horizontalLayoutWidget_9 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_9.setGeometry(QtCore.QRect(17, 25, 592, 32))\n self.horizontalLayoutWidget_9.setObjectName(_fromUtf8(\"horizontalLayoutWidget_9\"))\n self.horizontalLayout_10 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_9)\n self.horizontalLayout_10.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_10.setObjectName(_fromUtf8(\"horizontalLayout_10\"))\n self.label_11 = QtGui.QLabel(self.horizontalLayoutWidget_9)\n self.label_11.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_11.setFont(font)\n self.label_11.setObjectName(_fromUtf8(\"label_11\"))\n self.horizontalLayout_10.addWidget(self.label_11)\n self.browserButton = QtGui.QPushButton(self.horizontalLayoutWidget_9)\n self.browserButton.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton.sizePolicy().hasHeightForWidth())\n self.browserButton.setSizePolicy(sizePolicy)\n self.browserButton.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton.setObjectName(_fromUtf8(\"browserButton\"))\n self.horizontalLayout_10.addWidget(self.browserButton)\n self.filePathEdit_3 = QtGui.QLineEdit(self.horizontalLayoutWidget_9)\n self.filePathEdit_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Expanding)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_3.sizePolicy().hasHeightForWidth())\n self.filePathEdit_3.setSizePolicy(sizePolicy)\n self.filePathEdit_3.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_3.setObjectName(_fromUtf8(\"filePathEdit_3\"))\n self.horizontalLayout_10.addWidget(self.filePathEdit_3)\n self.horizontalLayoutWidget_10 = QtGui.QWidget(self.groupBox)\n self.horizontalLayoutWidget_10.setGeometry(QtCore.QRect(17, 63, 592, 32))\n self.horizontalLayoutWidget_10.setObjectName(_fromUtf8(\"horizontalLayoutWidget_10\"))\n self.horizontalLayout_11 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_10)\n self.horizontalLayout_11.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_11.setObjectName(_fromUtf8(\"horizontalLayout_11\"))\n self.label_12 = QtGui.QLabel(self.horizontalLayoutWidget_10)\n self.label_12.setMinimumSize(QtCore.QSize(0, 30))\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_12.setFont(font)\n self.label_12.setObjectName(_fromUtf8(\"label_12\"))\n self.horizontalLayout_11.addWidget(self.label_12)\n self.browserButton_3 = QtGui.QPushButton(self.horizontalLayoutWidget_10)\n self.browserButton_3.setEnabled(True)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_3.sizePolicy().hasHeightForWidth())\n self.browserButton_3.setSizePolicy(sizePolicy)\n self.browserButton_3.setMinimumSize(QtCore.QSize(80, 15))\n self.browserButton_3.setObjectName(_fromUtf8(\"browserButton_3\"))\n self.horizontalLayout_11.addWidget(self.browserButton_3)\n self.filePathEdit_5 = QtGui.QLineEdit(self.horizontalLayoutWidget_10)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_5.sizePolicy().hasHeightForWidth())\n self.filePathEdit_5.setSizePolicy(sizePolicy)\n self.filePathEdit_5.setMinimumSize(QtCore.QSize(400, 30))\n self.filePathEdit_5.setObjectName(_fromUtf8(\"filePathEdit_5\"))\n self.horizontalLayout_11.addWidget(self.filePathEdit_5)\n self.runButton = QtGui.QPushButton(self.groupBox)\n self.runButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.runButton.sizePolicy().hasHeightForWidth())\n self.runButton.setSizePolicy(sizePolicy)\n self.runButton.setMinimumSize(QtCore.QSize(80, 50))\n self.runButton.setIconSize(QtCore.QSize(24, 24))\n self.runButton.setObjectName(_fromUtf8(\"runButton\"))\n self.verticalLayout.addWidget(self.groupBox)\n self.groupBox_2 = QtGui.QGroupBox(self.centralwidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Preferred, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.groupBox_2.sizePolicy().hasHeightForWidth())\n self.groupBox_2.setSizePolicy(sizePolicy)\n self.groupBox_2.setMinimumSize(QtCore.QSize(100, 225))\n font = QtGui.QFont()\n font.setBold(False)\n font.setItalic(False)\n font.setWeight(50)\n self.groupBox_2.setFont(font)\n self.groupBox_2.setAutoFillBackground(True)\n self.groupBox_2.setObjectName(_fromUtf8(\"groupBox_2\"))\n self.horizontalLayoutWidget_4 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_4.setGeometry(QtCore.QRect(17, 25, 591, 32))\n self.horizontalLayoutWidget_4.setObjectName(_fromUtf8(\"horizontalLayoutWidget_4\"))\n self.horizontalLayout_6 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_4)\n self.horizontalLayout_6.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_6.setObjectName(_fromUtf8(\"horizontalLayout_6\"))\n self.label_3 = QtGui.QLabel(self.horizontalLayoutWidget_4)\n font = QtGui.QFont()\n font.setBold(False)\n font.setWeight(50)\n self.label_3.setFont(font)\n self.label_3.setObjectName(_fromUtf8(\"label_3\"))\n self.horizontalLayout_6.addWidget(self.label_3)\n self.browserButton_4 = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.browserButton_4.sizePolicy().hasHeightForWidth())\n self.browserButton_4.setSizePolicy(sizePolicy)\n self.browserButton_4.setObjectName(_fromUtf8(\"browserButton_4\"))\n self.horizontalLayout_6.addWidget(self.browserButton_4)\n self.loadButton = QtGui.QPushButton(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.loadButton.sizePolicy().hasHeightForWidth())\n self.loadButton.setSizePolicy(sizePolicy)\n self.loadButton.setObjectName(_fromUtf8(\"loadButton\"))\n self.horizontalLayout_6.addWidget(self.loadButton)\n self.filePathEdit_4 = QtGui.QLineEdit(self.horizontalLayoutWidget_4)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.filePathEdit_4.sizePolicy().hasHeightForWidth())\n self.filePathEdit_4.setSizePolicy(sizePolicy)\n self.filePathEdit_4.setMinimumSize(QtCore.QSize(300, 30))\n self.filePathEdit_4.setObjectName(_fromUtf8(\"filePathEdit_4\"))\n self.horizontalLayout_6.addWidget(self.filePathEdit_4)\n self.horizontalLayoutWidget_2 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_2.setGeometry(QtCore.QRect(17, 63, 481, 29))\n self.horizontalLayoutWidget_2.setObjectName(_fromUtf8(\"horizontalLayoutWidget_2\"))\n self.horizontalLayout_2 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_2)\n self.horizontalLayout_2.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_2.setObjectName(_fromUtf8(\"horizontalLayout_2\"))\n self.label_4 = QtGui.QLabel(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label_4.sizePolicy().hasHeightForWidth())\n self.label_4.setSizePolicy(sizePolicy)\n self.label_4.setObjectName(_fromUtf8(\"label_4\"))\n self.horizontalLayout_2.addWidget(self.label_4)\n self.comboBox = QtGui.QComboBox(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox.sizePolicy().hasHeightForWidth())\n self.comboBox.setSizePolicy(sizePolicy)\n self.comboBox.setObjectName(_fromUtf8(\"comboBox\"))\n self.horizontalLayout_2.addWidget(self.comboBox)\n self.plotButton = QtGui.QPushButton(self.horizontalLayoutWidget_2)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotButton.sizePolicy().hasHeightForWidth())\n self.plotButton.setSizePolicy(sizePolicy)\n self.plotButton.setObjectName(_fromUtf8(\"plotButton\"))\n self.horizontalLayout_2.addWidget(self.plotButton)\n self.horizontalLayoutWidget_3 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_3.setGeometry(QtCore.QRect(17, 100, 481, 29))\n self.horizontalLayoutWidget_3.setObjectName(_fromUtf8(\"horizontalLayoutWidget_3\"))\n self.horizontalLayout_3 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_3)\n self.horizontalLayout_3.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_3.setObjectName(_fromUtf8(\"horizontalLayout_3\"))\n self.label_5 = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label_5.setObjectName(_fromUtf8(\"label_5\"))\n self.horizontalLayout_3.addWidget(self.label_5)\n self.comboBox_R1 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R1.sizePolicy().hasHeightForWidth())\n self.comboBox_R1.setSizePolicy(sizePolicy)\n self.comboBox_R1.setMinimumSize(QtCore.QSize(0, 0))\n self.comboBox_R1.setObjectName(_fromUtf8(\"comboBox_R1\"))\n self.horizontalLayout_3.addWidget(self.comboBox_R1)\n self.label = QtGui.QLabel(self.horizontalLayoutWidget_3)\n self.label.setEnabled(False)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Preferred)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.label.sizePolicy().hasHeightForWidth())\n self.label.setSizePolicy(sizePolicy)\n self.label.setMinimumSize(QtCore.QSize(30, 0))\n self.label.setMaximumSize(QtCore.QSize(30, 29))\n font = QtGui.QFont()\n font.setBold(True)\n font.setItalic(True)\n font.setUnderline(False)\n font.setWeight(75)\n self.label.setFont(font)\n self.label.setAutoFillBackground(True)\n self.label.setLineWidth(5)\n self.label.setAlignment(QtCore.Qt.AlignCenter)\n self.label.setObjectName(_fromUtf8(\"label\"))\n self.horizontalLayout_3.addWidget(self.label)\n self.comboBox_R2 = QtGui.QComboBox(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Minimum, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_R2.sizePolicy().hasHeightForWidth())\n self.comboBox_R2.setSizePolicy(sizePolicy)\n self.comboBox_R2.setObjectName(_fromUtf8(\"comboBox_R2\"))\n self.horizontalLayout_3.addWidget(self.comboBox_R2)\n self.plotRangeButton = QtGui.QPushButton(self.horizontalLayoutWidget_3)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotRangeButton.sizePolicy().hasHeightForWidth())\n self.plotRangeButton.setSizePolicy(sizePolicy)\n self.plotRangeButton.setObjectName(_fromUtf8(\"plotRangeButton\"))\n self.horizontalLayout_3.addWidget(self.plotRangeButton)\n self.horizontalLayoutWidget_7 = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget_7.setGeometry(QtCore.QRect(17, 140, 481, 29))\n self.horizontalLayoutWidget_7.setObjectName(_fromUtf8(\"horizontalLayoutWidget_7\"))\n self.horizontalLayout_5 = QtGui.QHBoxLayout(self.horizontalLayoutWidget_7)\n self.horizontalLayout_5.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout_5.setObjectName(_fromUtf8(\"horizontalLayout_5\"))\n self.label_8 = QtGui.QLabel(self.horizontalLayoutWidget_7)\n self.label_8.setObjectName(_fromUtf8(\"label_8\"))\n self.horizontalLayout_5.addWidget(self.label_8)\n self.comboBox_2 = QtGui.QComboBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.comboBox_2.sizePolicy().hasHeightForWidth())\n self.comboBox_2.setSizePolicy(sizePolicy)\n self.comboBox_2.setObjectName(_fromUtf8(\"comboBox_2\"))\n self.horizontalLayout_5.addWidget(self.comboBox_2)\n self.checkBox = QtGui.QCheckBox(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.checkBox.sizePolicy().hasHeightForWidth())\n self.checkBox.setSizePolicy(sizePolicy)\n self.checkBox.setObjectName(_fromUtf8(\"checkBox\"))\n self.horizontalLayout_5.addWidget(self.checkBox)\n self.plotImageButton = QtGui.QPushButton(self.horizontalLayoutWidget_7)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotImageButton.sizePolicy().hasHeightForWidth())\n self.plotImageButton.setSizePolicy(sizePolicy)\n self.plotImageButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotImageButton.setObjectName(_fromUtf8(\"plotImageButton\"))\n self.horizontalLayout_5.addWidget(self.plotImageButton)\n self.clearPlotButton = QtGui.QPushButton(self.groupBox_2)\n self.clearPlotButton.setGeometry(QtCore.QRect(520, 140, 85, 50))\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.clearPlotButton.sizePolicy().hasHeightForWidth())\n self.clearPlotButton.setSizePolicy(sizePolicy)\n self.clearPlotButton.setMinimumSize(QtCore.QSize(80, 50))\n self.clearPlotButton.setObjectName(_fromUtf8(\"clearPlotButton\"))\n self.horizontalLayoutWidget = QtGui.QWidget(self.groupBox_2)\n self.horizontalLayoutWidget.setGeometry(QtCore.QRect(17, 180, 481, 29))\n self.horizontalLayoutWidget.setObjectName(_fromUtf8(\"horizontalLayoutWidget\"))\n self.horizontalLayout = QtGui.QHBoxLayout(self.horizontalLayoutWidget)\n self.horizontalLayout.setSizeConstraint(QtGui.QLayout.SetFixedSize)\n self.horizontalLayout.setObjectName(_fromUtf8(\"horizontalLayout\"))\n self.label_9 = QtGui.QLabel(self.horizontalLayoutWidget)\n self.label_9.setObjectName(_fromUtf8(\"label_9\"))\n self.horizontalLayout.addWidget(self.label_9)\n self.pushButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.pushButton.sizePolicy().hasHeightForWidth())\n self.pushButton.setSizePolicy(sizePolicy)\n self.pushButton.setMinimumSize(QtCore.QSize(80, 15))\n self.pushButton.setObjectName(_fromUtf8(\"pushButton\"))\n self.horizontalLayout.addWidget(self.pushButton)\n self.plotStripsButton = QtGui.QPushButton(self.horizontalLayoutWidget)\n sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)\n sizePolicy.setHorizontalStretch(0)\n sizePolicy.setVerticalStretch(0)\n sizePolicy.setHeightForWidth(self.plotStripsButton.sizePolicy().hasHeightForWidth())\n self.plotStripsButton.setSizePolicy(sizePolicy)\n self.plotStripsButton.setMinimumSize(QtCore.QSize(80, 15))\n self.plotStripsButton.setObjectName(_fromUtf8(\"plotStripsButton\"))\n self.horizontalLayout.addWidget(self.plotStripsButton)\n self.verticalLayout.addWidget(self.groupBox_2)\n MainWindow.setCentralWidget(self.centralwidget)\n self.statusbar = QtGui.QStatusBar(MainWindow)\n self.statusbar.setObjectName(_fromUtf8(\"statusbar\"))\n MainWindow.setStatusBar(self.statusbar)\n self.toolBar = QtGui.QToolBar(MainWindow)\n self.toolBar.setObjectName(_fromUtf8(\"toolBar\"))\n MainWindow.addToolBar(QtCore.Qt.TopToolBarArea, self.toolBar)\n self.menuBar = QtGui.QMenuBar(MainWindow)\n self.menuBar.setGeometry(QtCore.QRect(0, 0, 661, 22))\n self.menuBar.setObjectName(_fromUtf8(\"menuBar\"))\n MainWindow.setMenuBar(self.menuBar)\n self.actionOpen = QtGui.QAction(MainWindow)\n self.actionOpen.setVisible(True)\n self.actionOpen.setObjectName(_fromUtf8(\"actionOpen\"))\n self.actionQuit = QtGui.QAction(MainWindow)\n self.actionQuit.setObjectName(_fromUtf8(\"actionQuit\"))\n\n self.retranslateUi(MainWindow)\n QtCore.QMetaObject.connectSlotsByName(MainWindow)\n\n def retranslateUi(self, MainWindow):\n MainWindow.setWindowTitle(_translate(\"MainWindow\", \"MainWindow\", None))\n self.groupBox_3.setTitle(_translate(\"MainWindow\", \"PLOT WINDOW\", None))\n self.groupBox.setTitle(_translate(\"MainWindow\", \" BINARY DATA CONVERSION\", None))\n self.label_7.setText(_translate(\"MainWindow\", \" OUTPUT FILE \", None))\n self.browserButton_7.setText(_translate(\"MainWindow\", \"Browse\", None))\n self.filePathEdit_7.setText(_translate(\"MainWindow\", \"D:\\\\detdev\\\\maia\\\\python\\\\\", None))\n self.label_11.setText(_translate(\"MainWindow\", \" DECODER FILE\", None))\n self.browserButton.setText(_translate(\"MainWindow\", \"Browse\", None))\n self.filePathEdit_3.setText(_translate(\"MainWindow\", \"D:\\\\detdev\\\\maia\\\\python\\\\qtGSD\\\\gsd_parse.out\", None))\n self.label_12.setText(_translate(\"MainWindow\", \" INPUT FILE \", None))\n self.browserButton_3.setText(_translate(\"MainWindow\", \"Browse\", None))\n self.filePathEdit_5.setText(_translate(\"MainWindow\", \"D:\\\\detdev\\\\maia\\\\python\\\\\", None))\n self.runButton.setText(_translate(\"MainWindow\", \"Run\", None))\n self.groupBox_2.setTitle(_translate(\"MainWindow\", \" PLOT DATA\", None))\n self.label_3.setText(_translate(\"MainWindow\", \" DATA FILE \", None))\n self.browserButton_4.setText(_translate(\"MainWindow\", \"Browse\", None))\n self.loadButton.setText(_translate(\"MainWindow\", \"Load\", None))\n self.filePathEdit_4.setText(_translate(\"MainWindow\", \"D:\\\\detdev\\\\maia\\\\python\\\\\", None))\n self.label_4.setText(_translate(\"MainWindow\", \" PLOT STRIP \", None))\n self.plotButton.setText(_translate(\"MainWindow\", \"Plot\", None))\n self.label_5.setText(_translate(\"MainWindow\", \" PLOT SERIES\", None))\n self.label.setText(_translate(\"MainWindow\", \"to\", None))\n self.plotRangeButton.setText(_translate(\"MainWindow\", \"Plot\", None))\n self.label_8.setText(_translate(\"MainWindow\", \" PLOT SPECTRA AS 2-D IMAGE\", None))\n self.checkBox.setText(_translate(\"MainWindow\", \"Log\", None))\n self.plotImageButton.setText(_translate(\"MainWindow\", \"Plot Image\", None))\n self.clearPlotButton.setText(_translate(\"MainWindow\", \"Clear\", None))\n self.label_9.setText(_translate(\"MainWindow\", \" PLOT TOTAL COUNTS vs STRIP\", None))\n self.pushButton.setText(_translate(\"MainWindow\", \"Update\", None))\n self.plotStripsButton.setText(_translate(\"MainWindow\", \"Plot Strips\", None))\n self.toolBar.setWindowTitle(_translate(\"MainWindow\", \"toolBar\", None))\n self.actionOpen.setText(_translate(\"MainWindow\", \"Open\", None))\n self.actionQuit.setText(_translate(\"MainWindow\", \"Quit\", None))\n\n",
"step-ids": [
1,
3,
4,
5,
6
]
}
|
[
1,
3,
4,
5,
6
] |
# RSA key
modulus_size = 2048
(n, e) = (0, 0) # Not being initialize here
# modulus size in bytes
k = modulus_size // 8
# keep track of the oracle calls
queries = 0
print_queries_every = 1
number_of_time_to_confirm_conforming = 10
# Choose to use OpenSSL encrypt function or our own implementations
encrypt_openssl = True
# start timer
t_start = 0 # Not being initialize here
# Current Working Directory of the project
cwd = ""
# Server info
host = '10.0.0.1'
port = 4430
sock = 0 # Not being initialize here
max_message_size = 2048
|
normal
|
{
"blob_id": "415d58e502e8a33f7a37c4fb2da34e838246ea9c",
"index": 2057,
"step-1": "<mask token>\n",
"step-2": "modulus_size = 2048\nn, e = 0, 0\nk = modulus_size // 8\nqueries = 0\nprint_queries_every = 1\nnumber_of_time_to_confirm_conforming = 10\nencrypt_openssl = True\nt_start = 0\ncwd = ''\nhost = '10.0.0.1'\nport = 4430\nsock = 0\nmax_message_size = 2048\n",
"step-3": "\n# RSA key\nmodulus_size = 2048\n(n, e) = (0, 0) # Not being initialize here\n\n# modulus size in bytes\nk = modulus_size // 8\n\n# keep track of the oracle calls\nqueries = 0\nprint_queries_every = 1\nnumber_of_time_to_confirm_conforming = 10\n\n# Choose to use OpenSSL encrypt function or our own implementations\nencrypt_openssl = True\n\n# start timer\nt_start = 0 # Not being initialize here\n\n# Current Working Directory of the project\ncwd = \"\"\n\n# Server info\nhost = '10.0.0.1'\nport = 4430\nsock = 0 # Not being initialize here\nmax_message_size = 2048\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
"""
A module for constants.
"""
# fin adding notes for keys and uncomment
KEYS = [
"CM",
"GM"
# ,
# "DM",
# "AM",
# "EM",
# "BM",
# "FSM",
# "CSM",
# "Am",
# "Em",
# "Bm",
# "FSm",
# "CSm",
# "GSm",
# "DSm",
# "ASm",
]
NOTES_FOR_KEY = {
"CM": [
21,
23,
24,
26,
28,
29,
31,
33,
35,
36,
38,
40,
41,
43,
45,
47,
48,
50,
52,
53,
55,
57,
59,
60,
62,
64,
65,
67,
69,
71,
72,
74,
76,
77,
79,
81,
83,
84,
86,
88,
89,
91,
93,
95,
96,
98,
100,
101,
103,
105,
107,
108,
],
"GM": [
21,
23,
24,
26,
28,
30,
31,
33,
35,
36,
38,
40,
42,
43,
45,
47,
48,
50,
52,
54,
55,
57,
59,
60,
62,
64,
66,
67,
69,
71,
72,
74,
76,
78,
79,
81,
83,
84,
86,
88,
90,
91,
93,
95,
96,
98,
100,
102,
103,
105,
107,
108,
],
"DM": [],
"AM": [],
"EM": [],
"BM": [],
"FSM": [],
"CSM": [],
"Am": [],
"Em": [],
"Bm": [],
"FSm": [],
"CSm": [],
"GSm": [],
"DSm": [],
"ASm": [],
}
TONIC_NOTE_FOR_KEY = {
"CM": 60,
"GM": 67,
"DM": None,
"AM": None,
"EM": None,
"BM": None,
"FSM": None,
"CSM": None,
"Am": None,
"Em": None,
"Bm": None,
"FSm": None,
"CSm": None,
"GSm": None,
"DSm": None,
"ASm": None,
}
# add more chords later
STEPS_FOR_CHORD = {"major_triad": [0, 4, 7]}
# constants for value function
# add more complex rewards
NOTE_IN_KEY_REWARD = 1
NOTE_IN_CHORDS_REWARD = 1
SUPER_CONSONANT_INTERVAL_REWARD = 3
CONSONANT_INTERVAL_REWARD = 2
SOMEWHAT_CONSONANT_INTERVAL_REWARD = 1
DISSONANT_INTERVAL_REWARD = -2
SOMEWHAT_DISSONANT_INTERVAL_REWARD = -1
CENTRICITY_FACTOR = 1 # reward is number of times note occured before * CENTRICITY_FACTOR
|
normal
|
{
"blob_id": "dd7ade05ef912f7c094883507768cc21f95f31f6",
"index": 533,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nKEYS = ['CM', 'GM']\nNOTES_FOR_KEY = {'CM': [21, 23, 24, 26, 28, 29, 31, 33, 35, 36, 38, 40, 41,\n 43, 45, 47, 48, 50, 52, 53, 55, 57, 59, 60, 62, 64, 65, 67, 69, 71, 72,\n 74, 76, 77, 79, 81, 83, 84, 86, 88, 89, 91, 93, 95, 96, 98, 100, 101, \n 103, 105, 107, 108], 'GM': [21, 23, 24, 26, 28, 30, 31, 33, 35, 36, 38,\n 40, 42, 43, 45, 47, 48, 50, 52, 54, 55, 57, 59, 60, 62, 64, 66, 67, 69,\n 71, 72, 74, 76, 78, 79, 81, 83, 84, 86, 88, 90, 91, 93, 95, 96, 98, 100,\n 102, 103, 105, 107, 108], 'DM': [], 'AM': [], 'EM': [], 'BM': [], 'FSM':\n [], 'CSM': [], 'Am': [], 'Em': [], 'Bm': [], 'FSm': [], 'CSm': [],\n 'GSm': [], 'DSm': [], 'ASm': []}\nTONIC_NOTE_FOR_KEY = {'CM': 60, 'GM': 67, 'DM': None, 'AM': None, 'EM':\n None, 'BM': None, 'FSM': None, 'CSM': None, 'Am': None, 'Em': None,\n 'Bm': None, 'FSm': None, 'CSm': None, 'GSm': None, 'DSm': None, 'ASm': None\n }\nSTEPS_FOR_CHORD = {'major_triad': [0, 4, 7]}\nNOTE_IN_KEY_REWARD = 1\nNOTE_IN_CHORDS_REWARD = 1\nSUPER_CONSONANT_INTERVAL_REWARD = 3\nCONSONANT_INTERVAL_REWARD = 2\nSOMEWHAT_CONSONANT_INTERVAL_REWARD = 1\nDISSONANT_INTERVAL_REWARD = -2\nSOMEWHAT_DISSONANT_INTERVAL_REWARD = -1\nCENTRICITY_FACTOR = 1\n",
"step-3": "\"\"\"\nA module for constants.\n\n\"\"\"\n\n# fin adding notes for keys and uncomment \nKEYS = [\n \"CM\",\n \"GM\"\n # ,\n # \"DM\",\n # \"AM\",\n # \"EM\",\n # \"BM\",\n # \"FSM\",\n # \"CSM\",\n # \"Am\",\n # \"Em\",\n # \"Bm\",\n # \"FSm\",\n # \"CSm\",\n # \"GSm\",\n # \"DSm\",\n # \"ASm\",\n]\n\nNOTES_FOR_KEY = {\n \"CM\": [\n 21,\n 23,\n 24,\n 26,\n 28,\n 29,\n 31,\n 33,\n 35,\n 36,\n 38,\n 40,\n 41,\n 43,\n 45,\n 47,\n 48,\n 50,\n 52,\n 53,\n 55,\n 57,\n 59,\n 60,\n 62,\n 64,\n 65,\n 67,\n 69,\n 71,\n 72,\n 74,\n 76,\n 77,\n 79,\n 81,\n 83,\n 84,\n 86,\n 88,\n 89,\n 91,\n 93,\n 95,\n 96,\n 98,\n 100,\n 101,\n 103,\n 105,\n 107,\n 108,\n ],\n \"GM\": [\n 21,\n 23,\n 24,\n 26,\n 28,\n 30,\n 31,\n 33,\n 35,\n 36,\n 38,\n 40,\n 42,\n 43,\n 45,\n 47,\n 48,\n 50,\n 52,\n 54,\n 55,\n 57,\n 59,\n 60,\n 62,\n 64,\n 66,\n 67,\n 69,\n 71,\n 72,\n 74,\n 76,\n 78,\n 79,\n 81,\n 83,\n 84,\n 86,\n 88,\n 90,\n 91,\n 93,\n 95,\n 96,\n 98,\n 100,\n 102,\n 103,\n 105,\n 107,\n 108,\n ],\n \"DM\": [],\n \"AM\": [],\n \"EM\": [],\n \"BM\": [],\n \"FSM\": [],\n \"CSM\": [],\n \"Am\": [],\n \"Em\": [],\n \"Bm\": [],\n \"FSm\": [],\n \"CSm\": [],\n \"GSm\": [],\n \"DSm\": [],\n \"ASm\": [],\n}\n\nTONIC_NOTE_FOR_KEY = {\n \"CM\": 60,\n \"GM\": 67,\n \"DM\": None,\n \"AM\": None,\n \"EM\": None,\n \"BM\": None,\n \"FSM\": None,\n \"CSM\": None,\n \"Am\": None,\n \"Em\": None,\n \"Bm\": None,\n \"FSm\": None,\n \"CSm\": None,\n \"GSm\": None,\n \"DSm\": None,\n \"ASm\": None,\n}\n\n# add more chords later\nSTEPS_FOR_CHORD = {\"major_triad\": [0, 4, 7]}\n\n\n\n# constants for value function\n# add more complex rewards\nNOTE_IN_KEY_REWARD = 1\nNOTE_IN_CHORDS_REWARD = 1\nSUPER_CONSONANT_INTERVAL_REWARD = 3\nCONSONANT_INTERVAL_REWARD = 2\nSOMEWHAT_CONSONANT_INTERVAL_REWARD = 1\nDISSONANT_INTERVAL_REWARD = -2\nSOMEWHAT_DISSONANT_INTERVAL_REWARD = -1\nCENTRICITY_FACTOR = 1 # reward is number of times note occured before * CENTRICITY_FACTOR",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
from django.shortcuts import render,redirect
from django.http import HttpResponseRedirect
from . import forms,models
from django.contrib.auth.models import Group
from django.contrib import auth
from django.contrib.auth.decorators import login_required,user_passes_test
from datetime import datetime,timedelta,date
from django.core.mail import send_mail
from librarymanagement.settings import EMAIL_HOST_USER
from django.contrib import messages
#from django.contib.auth.models import user, auth
def home_view(request):
if request.user.is_authenticated:
return HttpResponseRedirect('afterlogin')
return render(request,'library/index.html')
# for showing blog content to users
#for showing signup/login button for student
def studentclick_view(request):
if request.user.is_authenticated:
return HttpResponseRedirect('afterlogin')
return render(request,'library/student_click.html')
#for showing signup/login button for teacher
def adminclick_view(request):
if request.user.is_authenticated:
return HttpResponseRedirect('afterlogin')
return render(request,'library/admin_click.html')
def adminsignup_view(request):
form=forms.AdminSigupForm()
if request.method=='POST':
form=forms.AdminSigupForm(request.POST)
if form.is_valid():
user=form.save()
user.set_password(user.password)
user.save()
my_admin_group = Group.objects.get_or_create(name='ADMIN')
my_admin_group[0].user_set.add(user)
return HttpResponseRedirect('adminlogin')
return render(request,'library/admin_signup.html',{'form':form})
def studentsignup_view(request):
form1=forms.StudentUserForm()
form2=forms.StudentExtraForm()
mydict={'form1':form1,'form2':form2}
if request.method=='POST':
form1=forms.StudentUserForm(request.POST)
form2=forms.StudentExtraForm(request.POST)
if form1.is_valid() and form2.is_valid():
user=form1.save()
user.set_password(user.password)
user.save()
f2=form2.save(commit=False)
f2.user=user
user2=f2.save()
my_student_group = Group.objects.get_or_create(name='STUDENT')
my_student_group[0].user_set.add(user)
return HttpResponseRedirect('studentlogin')
return render(request,'library/student_signup.html',context=mydict)
def is_admin(user):
return user.groups.filter(name='ADMIN').exists()
def afterlogin_view(request):
if is_admin(request.user):
return render(request,'library/admin_afterlogin.html')
else:
return render(request,'library/student_afterlogin.html')
@login_required(login_url='adminlogin')
@user_passes_test(is_admin)
def addbook_view(request):
#now it is empty book form for sending to html
form=forms.BookForm()
if request.method=='POST':
#now this form have data from html
form=forms.BookForm(request.POST)
if form.is_valid():
user=form.save()
return render(request,'library/book_added.html')
return render(request,'library/add_book.html',{'form':form})
@login_required(login_url='adminlogin')
@user_passes_test(is_admin)
def viewbook_view(request):
books=models.Book.objects.all()
return render(request,'library/view_book.html',{'books':books})
@login_required(login_url='adminlogin')
@user_passes_test(is_admin)
def issuebook_view(request):
form=forms.IssuedBookForm()
if request.method=='POST':
#now this form have data from html
form=forms.IssuedBookForm(request.POST)
if form.is_valid():
obj=models.IssuedBook()
obj.enrollment=request.POST.get('enrollment2')
obj.isbn=request.POST.get('isbn2')
obj.save()
return render(request,'library/book_issued.html')
return render(request,'library/issue_book.html',{'form':form})
@login_required(login_url='adminlogin')
@user_passes_test(is_admin)
def viewissuedbook_view(request):
issuedbooks=models.IssuedBook.objects.all()
li=[]
for lb in issuedbooks:
issdate=str(lb.issuedate.day)+'-'+str(lb.issuedate.month)+'-'+str(lb.issuedate.year)
expdate=str(lb.expirydate.day)+'-'+str(lb.expirydate.month)+'-'+str(lb.expirydate.year)
#fine calculation
days=(date.today()-lb.issuedate)
print(date.today())
d=days.days
fine=0
if d>20:
day=d-20
fine=day*10
books=list(models.Book.objects.filter(isbn=lb.isbn))
students=list(models.StudentExtra.objects.filter(enrollment=lb.enrollment))
i=0
for l in books:
t=(students[i].get_name,students[i].enrollment,books[i].name,books[i].author,issdate,expdate,fine)
i=i+1
li.append(t)
return render(request,'library/view_issued_book.html',{'li':li})
@login_required(login_url='adminlogin')
@user_passes_test(is_admin)
def viewstudent_view(request):
students=models.StudentExtra.objects.all()
return render(request,'library/view_student.html',{'students':students})
@login_required(login_url='studentlogin')
def viewissuedbookbystudent(request):
student=models.StudentExtra.objects.filter(user_id=request.user.id)
issuedbook=models.IssuedBook.objects.filter(enrollment=student[0].enrollment)
li1=[]
li2=[]
for ib in issuedbook:
books=models.Book.objects.filter(isbn=ib.isbn)
for book in books:
t=(request.user,student[0],book.name,book.author)
li1.append(t)
issdate=str(ib.issuedate.day)+'-'+str(ib.issuedate.month)+'-'+str(ib.issuedate.year)
expdate=str(ib.expirydate.day)+'-'+str(ib.expirydate.month)+'-'+str(ib.expirydate.year)
#fine calculation
days=(date.today()-ib.issuedate)
print(date.today())
d=days.days
fine=0
if d>20:
day=d-20
fine=day*10
t=(issdate,expdate,fine)
li2.append(t)
return render(request,'library/view_issued_book_bystudent.html',{'li1':li1,'li2':li2})
def aboutus_view(request):
return render(request,'library/about_us.html')
def contactus_view(request):
sub = forms.ContactusForm()
if request.method == 'POST':
sub = forms.ContactusForm(request.POST)
if sub.is_valid():
email = sub.cleaned_data['Email']
name=sub.cleaned_data['Name']
message = sub.cleaned_data['Message']
send_mail(str(name)+' || '+str(email),message, EMAIL_HOST_USER, ['[email protected]'], fail_silently = False)
return render(request, 'library/contact_us_success.html')
return render(request, 'library/contact_us.html', {'form':sub})
@login_required(login_url='studentlogin')
def viewbook_view(request):
books=models.Book.objects.all()
return render(request,'library/view_book.html',{'books':books})
def blog_view(request):
return render(request,'library/blogs.html')
|
normal
|
{
"blob_id": "ce9e1ac0f1596ba4db904289f91f5ab95c2de4b8",
"index": 7642,
"step-1": "<mask token>\n\n\ndef home_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/index.html')\n\n\n<mask token>\n\n\ndef studentsignup_view(request):\n form1 = forms.StudentUserForm()\n form2 = forms.StudentExtraForm()\n mydict = {'form1': form1, 'form2': form2}\n if request.method == 'POST':\n form1 = forms.StudentUserForm(request.POST)\n form2 = forms.StudentExtraForm(request.POST)\n if form1.is_valid() and form2.is_valid():\n user = form1.save()\n user.set_password(user.password)\n user.save()\n f2 = form2.save(commit=False)\n f2.user = user\n user2 = f2.save()\n my_student_group = Group.objects.get_or_create(name='STUDENT')\n my_student_group[0].user_set.add(user)\n return HttpResponseRedirect('studentlogin')\n return render(request, 'library/student_signup.html', context=mydict)\n\n\n<mask token>\n\n\ndef afterlogin_view(request):\n if is_admin(request.user):\n return render(request, 'library/admin_afterlogin.html')\n else:\n return render(request, 'library/student_afterlogin.html')\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef addbook_view(request):\n form = forms.BookForm()\n if request.method == 'POST':\n form = forms.BookForm(request.POST)\n if form.is_valid():\n user = form.save()\n return render(request, 'library/book_added.html')\n return render(request, 'library/add_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n<mask token>\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewstudent_view(request):\n students = models.StudentExtra.objects.all()\n return render(request, 'library/view_student.html', {'students': students})\n\n\n<mask token>\n\n\ndef aboutus_view(request):\n return render(request, 'library/about_us.html')\n\n\n<mask token>\n\n\n@login_required(login_url='studentlogin')\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef home_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/index.html')\n\n\n<mask token>\n\n\ndef studentsignup_view(request):\n form1 = forms.StudentUserForm()\n form2 = forms.StudentExtraForm()\n mydict = {'form1': form1, 'form2': form2}\n if request.method == 'POST':\n form1 = forms.StudentUserForm(request.POST)\n form2 = forms.StudentExtraForm(request.POST)\n if form1.is_valid() and form2.is_valid():\n user = form1.save()\n user.set_password(user.password)\n user.save()\n f2 = form2.save(commit=False)\n f2.user = user\n user2 = f2.save()\n my_student_group = Group.objects.get_or_create(name='STUDENT')\n my_student_group[0].user_set.add(user)\n return HttpResponseRedirect('studentlogin')\n return render(request, 'library/student_signup.html', context=mydict)\n\n\ndef is_admin(user):\n return user.groups.filter(name='ADMIN').exists()\n\n\ndef afterlogin_view(request):\n if is_admin(request.user):\n return render(request, 'library/admin_afterlogin.html')\n else:\n return render(request, 'library/student_afterlogin.html')\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef addbook_view(request):\n form = forms.BookForm()\n if request.method == 'POST':\n form = forms.BookForm(request.POST)\n if form.is_valid():\n user = form.save()\n return render(request, 'library/book_added.html')\n return render(request, 'library/add_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef issuebook_view(request):\n form = forms.IssuedBookForm()\n if request.method == 'POST':\n form = forms.IssuedBookForm(request.POST)\n if form.is_valid():\n obj = models.IssuedBook()\n obj.enrollment = request.POST.get('enrollment2')\n obj.isbn = request.POST.get('isbn2')\n obj.save()\n return render(request, 'library/book_issued.html')\n return render(request, 'library/issue_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewissuedbook_view(request):\n issuedbooks = models.IssuedBook.objects.all()\n li = []\n for lb in issuedbooks:\n issdate = str(lb.issuedate.day) + '-' + str(lb.issuedate.month\n ) + '-' + str(lb.issuedate.year)\n expdate = str(lb.expirydate.day) + '-' + str(lb.expirydate.month\n ) + '-' + str(lb.expirydate.year)\n days = date.today() - lb.issuedate\n print(date.today())\n d = days.days\n fine = 0\n if d > 20:\n day = d - 20\n fine = day * 10\n books = list(models.Book.objects.filter(isbn=lb.isbn))\n students = list(models.StudentExtra.objects.filter(enrollment=lb.\n enrollment))\n i = 0\n for l in books:\n t = students[i].get_name, students[i].enrollment, books[i\n ].name, books[i].author, issdate, expdate, fine\n i = i + 1\n li.append(t)\n return render(request, 'library/view_issued_book.html', {'li': li})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewstudent_view(request):\n students = models.StudentExtra.objects.all()\n return render(request, 'library/view_student.html', {'students': students})\n\n\n<mask token>\n\n\ndef aboutus_view(request):\n return render(request, 'library/about_us.html')\n\n\n<mask token>\n\n\n@login_required(login_url='studentlogin')\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef home_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/index.html')\n\n\n<mask token>\n\n\ndef adminclick_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/admin_click.html')\n\n\n<mask token>\n\n\ndef studentsignup_view(request):\n form1 = forms.StudentUserForm()\n form2 = forms.StudentExtraForm()\n mydict = {'form1': form1, 'form2': form2}\n if request.method == 'POST':\n form1 = forms.StudentUserForm(request.POST)\n form2 = forms.StudentExtraForm(request.POST)\n if form1.is_valid() and form2.is_valid():\n user = form1.save()\n user.set_password(user.password)\n user.save()\n f2 = form2.save(commit=False)\n f2.user = user\n user2 = f2.save()\n my_student_group = Group.objects.get_or_create(name='STUDENT')\n my_student_group[0].user_set.add(user)\n return HttpResponseRedirect('studentlogin')\n return render(request, 'library/student_signup.html', context=mydict)\n\n\ndef is_admin(user):\n return user.groups.filter(name='ADMIN').exists()\n\n\ndef afterlogin_view(request):\n if is_admin(request.user):\n return render(request, 'library/admin_afterlogin.html')\n else:\n return render(request, 'library/student_afterlogin.html')\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef addbook_view(request):\n form = forms.BookForm()\n if request.method == 'POST':\n form = forms.BookForm(request.POST)\n if form.is_valid():\n user = form.save()\n return render(request, 'library/book_added.html')\n return render(request, 'library/add_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef issuebook_view(request):\n form = forms.IssuedBookForm()\n if request.method == 'POST':\n form = forms.IssuedBookForm(request.POST)\n if form.is_valid():\n obj = models.IssuedBook()\n obj.enrollment = request.POST.get('enrollment2')\n obj.isbn = request.POST.get('isbn2')\n obj.save()\n return render(request, 'library/book_issued.html')\n return render(request, 'library/issue_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewissuedbook_view(request):\n issuedbooks = models.IssuedBook.objects.all()\n li = []\n for lb in issuedbooks:\n issdate = str(lb.issuedate.day) + '-' + str(lb.issuedate.month\n ) + '-' + str(lb.issuedate.year)\n expdate = str(lb.expirydate.day) + '-' + str(lb.expirydate.month\n ) + '-' + str(lb.expirydate.year)\n days = date.today() - lb.issuedate\n print(date.today())\n d = days.days\n fine = 0\n if d > 20:\n day = d - 20\n fine = day * 10\n books = list(models.Book.objects.filter(isbn=lb.isbn))\n students = list(models.StudentExtra.objects.filter(enrollment=lb.\n enrollment))\n i = 0\n for l in books:\n t = students[i].get_name, students[i].enrollment, books[i\n ].name, books[i].author, issdate, expdate, fine\n i = i + 1\n li.append(t)\n return render(request, 'library/view_issued_book.html', {'li': li})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewstudent_view(request):\n students = models.StudentExtra.objects.all()\n return render(request, 'library/view_student.html', {'students': students})\n\n\n@login_required(login_url='studentlogin')\ndef viewissuedbookbystudent(request):\n student = models.StudentExtra.objects.filter(user_id=request.user.id)\n issuedbook = models.IssuedBook.objects.filter(enrollment=student[0].\n enrollment)\n li1 = []\n li2 = []\n for ib in issuedbook:\n books = models.Book.objects.filter(isbn=ib.isbn)\n for book in books:\n t = request.user, student[0], book.name, book.author\n li1.append(t)\n issdate = str(ib.issuedate.day) + '-' + str(ib.issuedate.month\n ) + '-' + str(ib.issuedate.year)\n expdate = str(ib.expirydate.day) + '-' + str(ib.expirydate.month\n ) + '-' + str(ib.expirydate.year)\n days = date.today() - ib.issuedate\n print(date.today())\n d = days.days\n fine = 0\n if d > 20:\n day = d - 20\n fine = day * 10\n t = issdate, expdate, fine\n li2.append(t)\n return render(request, 'library/view_issued_book_bystudent.html', {\n 'li1': li1, 'li2': li2})\n\n\ndef aboutus_view(request):\n return render(request, 'library/about_us.html')\n\n\ndef contactus_view(request):\n sub = forms.ContactusForm()\n if request.method == 'POST':\n sub = forms.ContactusForm(request.POST)\n if sub.is_valid():\n email = sub.cleaned_data['Email']\n name = sub.cleaned_data['Name']\n message = sub.cleaned_data['Message']\n send_mail(str(name) + ' || ' + str(email), message,\n EMAIL_HOST_USER, ['[email protected]'], fail_silently\n =False)\n return render(request, 'library/contact_us_success.html')\n return render(request, 'library/contact_us.html', {'form': sub})\n\n\n@login_required(login_url='studentlogin')\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\ndef blog_view(request):\n return render(request, 'library/blogs.html')\n",
"step-4": "from django.shortcuts import render, redirect\nfrom django.http import HttpResponseRedirect\nfrom . import forms, models\nfrom django.contrib.auth.models import Group\nfrom django.contrib import auth\nfrom django.contrib.auth.decorators import login_required, user_passes_test\nfrom datetime import datetime, timedelta, date\nfrom django.core.mail import send_mail\nfrom librarymanagement.settings import EMAIL_HOST_USER\nfrom django.contrib import messages\n\n\ndef home_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/index.html')\n\n\ndef studentclick_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/student_click.html')\n\n\ndef adminclick_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request, 'library/admin_click.html')\n\n\ndef adminsignup_view(request):\n form = forms.AdminSigupForm()\n if request.method == 'POST':\n form = forms.AdminSigupForm(request.POST)\n if form.is_valid():\n user = form.save()\n user.set_password(user.password)\n user.save()\n my_admin_group = Group.objects.get_or_create(name='ADMIN')\n my_admin_group[0].user_set.add(user)\n return HttpResponseRedirect('adminlogin')\n return render(request, 'library/admin_signup.html', {'form': form})\n\n\ndef studentsignup_view(request):\n form1 = forms.StudentUserForm()\n form2 = forms.StudentExtraForm()\n mydict = {'form1': form1, 'form2': form2}\n if request.method == 'POST':\n form1 = forms.StudentUserForm(request.POST)\n form2 = forms.StudentExtraForm(request.POST)\n if form1.is_valid() and form2.is_valid():\n user = form1.save()\n user.set_password(user.password)\n user.save()\n f2 = form2.save(commit=False)\n f2.user = user\n user2 = f2.save()\n my_student_group = Group.objects.get_or_create(name='STUDENT')\n my_student_group[0].user_set.add(user)\n return HttpResponseRedirect('studentlogin')\n return render(request, 'library/student_signup.html', context=mydict)\n\n\ndef is_admin(user):\n return user.groups.filter(name='ADMIN').exists()\n\n\ndef afterlogin_view(request):\n if is_admin(request.user):\n return render(request, 'library/admin_afterlogin.html')\n else:\n return render(request, 'library/student_afterlogin.html')\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef addbook_view(request):\n form = forms.BookForm()\n if request.method == 'POST':\n form = forms.BookForm(request.POST)\n if form.is_valid():\n user = form.save()\n return render(request, 'library/book_added.html')\n return render(request, 'library/add_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef issuebook_view(request):\n form = forms.IssuedBookForm()\n if request.method == 'POST':\n form = forms.IssuedBookForm(request.POST)\n if form.is_valid():\n obj = models.IssuedBook()\n obj.enrollment = request.POST.get('enrollment2')\n obj.isbn = request.POST.get('isbn2')\n obj.save()\n return render(request, 'library/book_issued.html')\n return render(request, 'library/issue_book.html', {'form': form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewissuedbook_view(request):\n issuedbooks = models.IssuedBook.objects.all()\n li = []\n for lb in issuedbooks:\n issdate = str(lb.issuedate.day) + '-' + str(lb.issuedate.month\n ) + '-' + str(lb.issuedate.year)\n expdate = str(lb.expirydate.day) + '-' + str(lb.expirydate.month\n ) + '-' + str(lb.expirydate.year)\n days = date.today() - lb.issuedate\n print(date.today())\n d = days.days\n fine = 0\n if d > 20:\n day = d - 20\n fine = day * 10\n books = list(models.Book.objects.filter(isbn=lb.isbn))\n students = list(models.StudentExtra.objects.filter(enrollment=lb.\n enrollment))\n i = 0\n for l in books:\n t = students[i].get_name, students[i].enrollment, books[i\n ].name, books[i].author, issdate, expdate, fine\n i = i + 1\n li.append(t)\n return render(request, 'library/view_issued_book.html', {'li': li})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewstudent_view(request):\n students = models.StudentExtra.objects.all()\n return render(request, 'library/view_student.html', {'students': students})\n\n\n@login_required(login_url='studentlogin')\ndef viewissuedbookbystudent(request):\n student = models.StudentExtra.objects.filter(user_id=request.user.id)\n issuedbook = models.IssuedBook.objects.filter(enrollment=student[0].\n enrollment)\n li1 = []\n li2 = []\n for ib in issuedbook:\n books = models.Book.objects.filter(isbn=ib.isbn)\n for book in books:\n t = request.user, student[0], book.name, book.author\n li1.append(t)\n issdate = str(ib.issuedate.day) + '-' + str(ib.issuedate.month\n ) + '-' + str(ib.issuedate.year)\n expdate = str(ib.expirydate.day) + '-' + str(ib.expirydate.month\n ) + '-' + str(ib.expirydate.year)\n days = date.today() - ib.issuedate\n print(date.today())\n d = days.days\n fine = 0\n if d > 20:\n day = d - 20\n fine = day * 10\n t = issdate, expdate, fine\n li2.append(t)\n return render(request, 'library/view_issued_book_bystudent.html', {\n 'li1': li1, 'li2': li2})\n\n\ndef aboutus_view(request):\n return render(request, 'library/about_us.html')\n\n\ndef contactus_view(request):\n sub = forms.ContactusForm()\n if request.method == 'POST':\n sub = forms.ContactusForm(request.POST)\n if sub.is_valid():\n email = sub.cleaned_data['Email']\n name = sub.cleaned_data['Name']\n message = sub.cleaned_data['Message']\n send_mail(str(name) + ' || ' + str(email), message,\n EMAIL_HOST_USER, ['[email protected]'], fail_silently\n =False)\n return render(request, 'library/contact_us_success.html')\n return render(request, 'library/contact_us.html', {'form': sub})\n\n\n@login_required(login_url='studentlogin')\ndef viewbook_view(request):\n books = models.Book.objects.all()\n return render(request, 'library/view_book.html', {'books': books})\n\n\ndef blog_view(request):\n return render(request, 'library/blogs.html')\n",
"step-5": "from django.shortcuts import render,redirect\nfrom django.http import HttpResponseRedirect\nfrom . import forms,models\nfrom django.contrib.auth.models import Group\nfrom django.contrib import auth\nfrom django.contrib.auth.decorators import login_required,user_passes_test\nfrom datetime import datetime,timedelta,date\nfrom django.core.mail import send_mail\nfrom librarymanagement.settings import EMAIL_HOST_USER\nfrom django.contrib import messages\n#from django.contib.auth.models import user, auth\n\n\ndef home_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request,'library/index.html')\n\n# for showing blog content to users\n\n\n#for showing signup/login button for student\ndef studentclick_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request,'library/student_click.html')\n\n#for showing signup/login button for teacher\ndef adminclick_view(request):\n if request.user.is_authenticated:\n return HttpResponseRedirect('afterlogin')\n return render(request,'library/admin_click.html')\n\n\n\ndef adminsignup_view(request):\n form=forms.AdminSigupForm()\n if request.method=='POST':\n form=forms.AdminSigupForm(request.POST)\n if form.is_valid():\n user=form.save()\n user.set_password(user.password)\n user.save()\n\n\n my_admin_group = Group.objects.get_or_create(name='ADMIN')\n my_admin_group[0].user_set.add(user)\n\n return HttpResponseRedirect('adminlogin')\n return render(request,'library/admin_signup.html',{'form':form})\n\n\n\n\n\n\ndef studentsignup_view(request):\n form1=forms.StudentUserForm()\n form2=forms.StudentExtraForm()\n mydict={'form1':form1,'form2':form2}\n if request.method=='POST':\n form1=forms.StudentUserForm(request.POST)\n form2=forms.StudentExtraForm(request.POST)\n if form1.is_valid() and form2.is_valid():\n user=form1.save()\n user.set_password(user.password)\n user.save()\n f2=form2.save(commit=False)\n f2.user=user\n user2=f2.save()\n\n my_student_group = Group.objects.get_or_create(name='STUDENT')\n my_student_group[0].user_set.add(user)\n\n return HttpResponseRedirect('studentlogin')\n return render(request,'library/student_signup.html',context=mydict)\n\n\n\n\ndef is_admin(user):\n return user.groups.filter(name='ADMIN').exists()\n\ndef afterlogin_view(request):\n if is_admin(request.user):\n return render(request,'library/admin_afterlogin.html')\n else:\n return render(request,'library/student_afterlogin.html')\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef addbook_view(request):\n #now it is empty book form for sending to html\n form=forms.BookForm()\n if request.method=='POST':\n #now this form have data from html\n form=forms.BookForm(request.POST)\n if form.is_valid():\n user=form.save()\n return render(request,'library/book_added.html')\n return render(request,'library/add_book.html',{'form':form})\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewbook_view(request):\n books=models.Book.objects.all()\n return render(request,'library/view_book.html',{'books':books})\n\n\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef issuebook_view(request):\n form=forms.IssuedBookForm()\n if request.method=='POST':\n #now this form have data from html\n form=forms.IssuedBookForm(request.POST)\n if form.is_valid():\n obj=models.IssuedBook()\n obj.enrollment=request.POST.get('enrollment2')\n obj.isbn=request.POST.get('isbn2')\n obj.save()\n return render(request,'library/book_issued.html')\n return render(request,'library/issue_book.html',{'form':form})\n\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewissuedbook_view(request):\n issuedbooks=models.IssuedBook.objects.all()\n li=[]\n for lb in issuedbooks:\n issdate=str(lb.issuedate.day)+'-'+str(lb.issuedate.month)+'-'+str(lb.issuedate.year)\n expdate=str(lb.expirydate.day)+'-'+str(lb.expirydate.month)+'-'+str(lb.expirydate.year)\n #fine calculation\n days=(date.today()-lb.issuedate)\n print(date.today())\n d=days.days\n fine=0\n if d>20:\n day=d-20\n fine=day*10\n\n\n books=list(models.Book.objects.filter(isbn=lb.isbn))\n students=list(models.StudentExtra.objects.filter(enrollment=lb.enrollment))\n i=0\n for l in books:\n t=(students[i].get_name,students[i].enrollment,books[i].name,books[i].author,issdate,expdate,fine)\n i=i+1\n li.append(t)\n\n return render(request,'library/view_issued_book.html',{'li':li})\n\n@login_required(login_url='adminlogin')\n@user_passes_test(is_admin)\ndef viewstudent_view(request):\n students=models.StudentExtra.objects.all()\n return render(request,'library/view_student.html',{'students':students})\n\n\n@login_required(login_url='studentlogin')\ndef viewissuedbookbystudent(request):\n student=models.StudentExtra.objects.filter(user_id=request.user.id)\n issuedbook=models.IssuedBook.objects.filter(enrollment=student[0].enrollment)\n\n li1=[]\n\n li2=[]\n for ib in issuedbook:\n books=models.Book.objects.filter(isbn=ib.isbn)\n for book in books:\n t=(request.user,student[0],book.name,book.author)\n li1.append(t)\n issdate=str(ib.issuedate.day)+'-'+str(ib.issuedate.month)+'-'+str(ib.issuedate.year)\n expdate=str(ib.expirydate.day)+'-'+str(ib.expirydate.month)+'-'+str(ib.expirydate.year)\n \n #fine calculation\n days=(date.today()-ib.issuedate)\n print(date.today())\n d=days.days\n fine=0\n if d>20:\n day=d-20\n fine=day*10\n t=(issdate,expdate,fine)\n li2.append(t)\n\n return render(request,'library/view_issued_book_bystudent.html',{'li1':li1,'li2':li2})\n\ndef aboutus_view(request):\n return render(request,'library/about_us.html')\n\ndef contactus_view(request):\n sub = forms.ContactusForm()\n if request.method == 'POST':\n sub = forms.ContactusForm(request.POST)\n if sub.is_valid():\n email = sub.cleaned_data['Email']\n name=sub.cleaned_data['Name']\n message = sub.cleaned_data['Message']\n send_mail(str(name)+' || '+str(email),message, EMAIL_HOST_USER, ['[email protected]'], fail_silently = False)\n return render(request, 'library/contact_us_success.html')\n return render(request, 'library/contact_us.html', {'form':sub})\n\n\n@login_required(login_url='studentlogin')\ndef viewbook_view(request):\n books=models.Book.objects.all()\n return render(request,'library/view_book.html',{'books':books})\n\n\ndef blog_view(request):\n return render(request,'library/blogs.html')",
"step-ids": [
8,
11,
15,
18,
19
]
}
|
[
8,
11,
15,
18,
19
] |
from brie.config import ldap_config
from brie.model.ldap import *
from brie.lib.log_helper import BrieLogging
import datetime
import smtplib
class Residences:
@staticmethod
def get_dn_by_name(user_session, name):
result = user_session.ldap_bind.search_first(ldap_config.liste_residence_dn, "(cn=" + name + ")")
if result is None:
return None
#end if
return result.uniqueMember.first()
#end def
@staticmethod
def get_name_by_dn(user_session, dn):
result = user_session.ldap_bind.search_first(ldap_config.liste_residence_dn, "(uniqueMember=" + dn + ")")
if result is None:
return None
#end if
return result.cn.first()
#end def
@staticmethod
def get_residences(user_session):
return user_session.ldap_bind.search(ldap_config.liste_residence_dn, "(objectClass=groupOfUniqueNames)")
#end def
#end class
class CotisationComputes:
@staticmethod
def current_year():
now = datetime.datetime.now()
if now.month > 8:
return now.year + 1
return now.year
#end def
@staticmethod
def registration_current_year():
now = datetime.datetime.now()
if now.month > 8:
return now.year
return now.year - 1
#end def
@staticmethod
def get_available_months(start, end, paid_months = []):
next_months_available = []
if start > 12 or end > 12:
raise Exception("invalid start or end")
if start > 8 and end > 8:
next_months_available = range(start, end + 1)
elif start <= 8 and end < 9:
next_months_available = range(start, end + 1)
elif start > 8:
next_months_available = range(start, 13) + range(1, end + 1 )
else:
raise Exception("invalid start and end")
#end if
if paid_months == []:
return next_months_available
BrieLogging.get().debug(next_months_available)
available_months = [
month
for month in next_months_available
if month not in paid_months
]
return available_months
#end def
@staticmethod
def is_valid_month(month):
now = datetime.datetime.now()
if now.month > 8:
return (month >= now.month and month < 13) or (month >= 1 and month < 9)
else:
return month >= now.month and month < 9
#end if
#end def
@staticmethod
def price_to_pay(year_price, month_price, already_paid, number_months_to_pay):
months_price = number_months_to_pay * month_price
BrieLogging.get().debug("already paid : " + str(already_paid))
BrieLogging.get().debug("months price : " + str(months_price))
if already_paid + months_price > year_price:
months_price = max(0, year_price - already_paid)
return months_price
#end def
@staticmethod
def anniversary_from_ldap_items(ldap_cotisations):
result = []
months = []
SORT_ORDER = {9: 0, 10: 1, 11: 2, 12: 3, 1: 4, 2: 5, 3: 6, 4: 7, 5: 8, 6: 9, 7: 10, 8: 11}
for cotisation in ldap_cotisations:
cotisation_months = []
anniversary_data = cotisation.get("x-time").first()
anniversary_datetime = datetime.datetime.strptime(anniversary_data,
"%Y-%m-%d %H:%M:%S.%f")
for month in cotisation.get("x-validMonth").all():
months.append(int(month))
cotisation_months.append(int(month))
#end for
cotisation_months.sort(key=lambda val: SORT_ORDER[val])
result.append((anniversary_datetime, cotisation_months))
#end for
anniversary = 0
# tri par ordre d'inscription
result = sorted(result)
previousMonth = -1
months.sort(key=lambda val: SORT_ORDER[val])
#on scanne chaque cotisation
for resultat in result:
#si on n'est pas la premiere cotisation et que les cotisations sont sans interruptions (pas de mois manquants)
#la date anniversaire reste la meme
if previousMonth != -1 and ( (resultat[1][0] == 1 and previousMonth == 12) or (resultat[1][0] == previousMonth + 1) ):
previousMonth = resultat[1][-1]
continue;
#sinon on recalcule la date anniversaire
else :
previousMonth = resultat[1][-1]
#end if
anniversary_day = resultat[0].day
anniversary_month = months[-1] + 1
if anniversary_month == 13:
anniversary_month = 1
if anniversary_month > 9 or resultat[0].month < 9:
#on reste avec une annee d'anniversaire sur l'annee de la cotisation si l'anniversaire est entre septembre et decembre, mais on met aussi l'annee_anniversaire la meme annee que la cotisation si on a cotise entre janvier et aout
anniversary_year = resultat[0].year
else :
#sinon, c'est qu'on a cotise entre septembre et decembre et que notre fin de cotisation est l'annee suivante, donc on fait un +1
anniversary_year = resultat[0].year + 1
anniversary = datetime.datetime.strptime(str(anniversary_year) + "-" + str(anniversary_month) + "-1 0:0", "%Y-%m-%d %H:%M") + datetime.timedelta(days=(anniversary_day - 1))
#end for
if anniversary == 0:
anniversary = datetime.datetime(1999, 1, 31, 12, 0)
return anniversary
#end def
@staticmethod
# fonction de renvoi de la date anniversaire qui est la date actuelle au cas ou il n'a pas cotise depuis 30 jours, sinon date anniversaire actuelle
def generate_new_anniversary_from_ldap_items(ldap_cotisations):
anniversary = CotisationComputes.anniversary_from_ldap_items(ldap_cotisations)
now = datetime.datetime.now()
if anniversary == 0 or (now - anniversary).days > 30:
return now
else :
return anniversary
#end if
#end def
@staticmethod
# old = SDF or no cotisation this year
def is_old_member(member_dn, user_session, residence_dn, cotisations = None):
if cotisations is None:
current_year = CotisationComputes.current_year()
cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)
#end if
#en septembre, on ne met pas de membre en old afin que les anciens ne soient pas deconnectes
return Room.get_by_member_dn(user_session, residence_dn, member_dn) == None or (datetime.datetime.now().month != 9 and cotisations == [])
#end def
@staticmethod
# no cotisation for the new year and last year august didn't payed
def is_member_to_delete(member, user_session, residence_dn):
current_year = CotisationComputes.current_year()
cotisations_this_year = Cotisation.cotisations_of_member(user_session, member.dn, current_year)
cotisations_previous_year = Cotisation.cotisations_of_member(user_session, member.dn, current_year - 1)
if cotisations_this_year == [] and cotisations_previous_year == []:
return True
now = datetime.datetime.now()
if now.month < 9:
last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)
else:
last_year = datetime.datetime(now.year, 8, 31, 12, 0)
#end if
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations_previous_year)
#end if
#si il a pas cotise cette annee et qu'il n'avait pas pris jusqua fin aout l'an dernier
delta = (last_year - anniversary)
return cotisations_this_year == [] and (delta.days > 7 or Room.get_by_member_dn(user_session, residence_dn, member.dn) == None)
#end def
@staticmethod
# 7 days grace period
def is_cotisation_was_paid_last_year(member_dn, user_session, residence_dn, cotisations = None, anniversary = None):
if cotisations is None:
current_year = CotisationComputes.current_year() - 1
#end if
now = datetime.datetime.now()
if now.month < 9:
last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)
else:
last_year = datetime.datetime(now.year, 8, 31, 12, 0)
#end if
if cotisations is None:
cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)
#end if
if anniversary is None:
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)
#end if
delta = (last_year - anniversary)
return delta.days <= 7
#end def
@staticmethod
# 7 days grace period
def is_cotisation_paid(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):
if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):
return False
if cotisations is None:
current_year = CotisationComputes.current_year()
#end if
now = datetime.datetime.now()
if cotisations is None:
cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)
#end if
if anniversary is None:
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)
#end if
delta = (now - anniversary)
if delta.days > 7 and now.month == 9 and CotisationComputes.is_cotisation_was_paid_last_year(member_dn, user_session, residence_dn):
#le membre etait a jour en aout, on lui autorise un delai de paiement en septembre - pas de deconnexion
return True
#end if
return delta.days <= 7
#end def
@staticmethod
# less than a month late but more than a week
def is_cotisation_late(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):
if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):
return False
if cotisations is None:
current_year = CotisationComputes.current_year()
#end if
now = datetime.datetime.now()
if cotisations is None:
cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)
#end if
if anniversary is None:
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)
#end if
delta = (now - anniversary)
#print("[DEBUG] cotisation en retard pour l'utilisateur "+ member.dn +" now="+ str(now) +" anniversary="+ str(anniversary) +" delta="+ str(delta))
return delta.days <= 30 and delta.days > 7
#end def
def cotisation_late_reminder(member_dn, user_session, residence_dn):
member = Member.get_by_dn(user_session,member_dn)
from_mail = "[email protected]"
to_mail = [member.mail.first()]
residence_name = Residences.get_name_by_dn(user_session,residence_dn).decode("utf-8").encode("ascii", "ignore")
#end def
@staticmethod
# more than a month late
def is_no_cotisation(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):
if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):
return False
if cotisations is None:
current_year = CotisationComputes.current_year()
#end if
now = datetime.datetime.now()
if cotisations is None:
cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)
#end if
if anniversary is None:
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)
#end if
delta = (now - anniversary)
return delta.days > 30
#end def
@staticmethod
def members_status_from_residence(user_session, residence_dn):
members = Member.get_all(user_session, residence_dn)
old_members = []
cotisation_paid_members = []
cotisation_late_members = []
no_cotisation_members = []
for member in members:
current_year = CotisationComputes.current_year()
cotisations = Cotisation.cotisations_of_member(user_session, member.dn, current_year)
if CotisationComputes.is_old_member(member.dn, user_session, residence_dn, cotisations):
old_members.append(member)
elif CotisationComputes.is_cotisation_paid(member.dn, user_session, residence_dn, cotisations):
cotisation_paid_members.append(member)
elif CotisationComputes.is_cotisation_late(member.dn, user_session, residence_dn, cotisations):
cotisation_late_members.append(member)
#print("[DEBUG] cotisation en retard pour l'utilisateur "+ member.dn)
elif CotisationComputes.is_no_cotisation(member.dn, user_session, residence_dn, cotisations):
no_cotisation_members.append(member)
else:
BrieLogging.get().warn("aurore_helper:336 member with weird status !")
#end if
#end for
return dict(old_members=old_members, cotisation_paid_members=cotisation_paid_members, cotisation_late_members=cotisation_late_members, no_cotisation_members=no_cotisation_members)
#end def
@staticmethod
def members_status_from_list_cotisations(user_session, residence_dn, cotisations):
members_dict = dict()
for cotisation in cotisations:
cotisation_dn = cotisation.dn.split(",")
member_dn = ""
for i in range(3, len(cotisation_dn)):
if i != 3:
member_dn += ","
#end if
member_dn += cotisation_dn[i]
#end for
if not member_dn in members_dict:
members_dict[member_dn] = [cotisation]
else:
members_dict[member_dn].append(cotisation)
#end if
#end for
BrieLogging.get().debug(str(datetime.datetime.now()) + "members_status_from_list_cotisations:" + str(len(members_dict)))
old_members = []
cotisation_paid_members = []
cotisation_late_members = []
no_cotisation_members = []
#on va verifier en un block quels sont les old_members
for member_dn, cotisations in members_dict.iteritems():
old_members.append(member_dn)
#end for
rooms = Room.get_rooms(user_session, residence_dn)
for room in rooms:
#pour chaque chambre, on check si il a un proprietaire, et si ce dernier a des cotisations
if room.has("x-memberIn") and room.get("x-memberIn").first() in members_dict and room.get("x-memberIn").first() in old_members:
#si oui, bah on le retire des old_members
old_members.remove(room.get("x-memberIn").first())
#endif
#endfor
for member_dn, cotisations in members_dict.iteritems():
anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)
if CotisationComputes.is_cotisation_paid(member_dn, user_session, residence_dn, cotisations, anniversary, False):
cotisation_paid_members.append(member_dn)
elif CotisationComputes.is_cotisation_late(member_dn, user_session, residence_dn, cotisations, anniversary, False):
cotisation_late_members.append(member_dn)
#print("[DEBUG] cotisation en retard pour l'utilisateur "+ member.dn)
elif CotisationComputes.is_no_cotisation(member_dn, user_session, residence_dn, cotisations, anniversary, False):
no_cotisation_members.append(member_dn)
else:
BrieLogging.get().debug("aurore_helper:393 : member with weird status !")
#end if
#end for
return dict(old_members=old_members, cotisation_paid_members=cotisation_paid_members, cotisation_late_members=cotisation_late_members, no_cotisation_members=no_cotisation_members)
#end def
#end class
|
normal
|
{
"blob_id": "d726e468a9df26f1bcb8a016812b87fad7b41aa8",
"index": 8089,
"step-1": "<mask token>\n\n\nclass CotisationComputes:\n\n @staticmethod\n def current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year + 1\n return now.year\n\n @staticmethod\n def registration_current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year\n return now.year - 1\n <mask token>\n\n @staticmethod\n def is_valid_month(month):\n now = datetime.datetime.now()\n if now.month > 8:\n return (month >= now.month and month < 13 or month >= 1 and \n month < 9)\n else:\n return month >= now.month and month < 9\n\n @staticmethod\n def price_to_pay(year_price, month_price, already_paid,\n number_months_to_pay):\n months_price = number_months_to_pay * month_price\n BrieLogging.get().debug('already paid : ' + str(already_paid))\n BrieLogging.get().debug('months price : ' + str(months_price))\n if already_paid + months_price > year_price:\n months_price = max(0, year_price - already_paid)\n return months_price\n\n @staticmethod\n def anniversary_from_ldap_items(ldap_cotisations):\n result = []\n months = []\n SORT_ORDER = {(9): 0, (10): 1, (11): 2, (12): 3, (1): 4, (2): 5, (3\n ): 6, (4): 7, (5): 8, (6): 9, (7): 10, (8): 11}\n for cotisation in ldap_cotisations:\n cotisation_months = []\n anniversary_data = cotisation.get('x-time').first()\n anniversary_datetime = datetime.datetime.strptime(anniversary_data,\n '%Y-%m-%d %H:%M:%S.%f')\n for month in cotisation.get('x-validMonth').all():\n months.append(int(month))\n cotisation_months.append(int(month))\n cotisation_months.sort(key=lambda val: SORT_ORDER[val])\n result.append((anniversary_datetime, cotisation_months))\n anniversary = 0\n result = sorted(result)\n previousMonth = -1\n months.sort(key=lambda val: SORT_ORDER[val])\n for resultat in result:\n if previousMonth != -1 and (resultat[1][0] == 1 and \n previousMonth == 12 or resultat[1][0] == previousMonth + 1):\n previousMonth = resultat[1][-1]\n continue\n else:\n previousMonth = resultat[1][-1]\n anniversary_day = resultat[0].day\n anniversary_month = months[-1] + 1\n if anniversary_month == 13:\n anniversary_month = 1\n if anniversary_month > 9 or resultat[0].month < 9:\n anniversary_year = resultat[0].year\n else:\n anniversary_year = resultat[0].year + 1\n anniversary = datetime.datetime.strptime(str(anniversary_year) +\n '-' + str(anniversary_month) + '-1 0:0', '%Y-%m-%d %H:%M'\n ) + datetime.timedelta(days=anniversary_day - 1)\n if anniversary == 0:\n anniversary = datetime.datetime(1999, 1, 31, 12, 0)\n return anniversary\n\n @staticmethod\n def generate_new_anniversary_from_ldap_items(ldap_cotisations):\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n ldap_cotisations)\n now = datetime.datetime.now()\n if anniversary == 0 or (now - anniversary).days > 30:\n return now\n else:\n return anniversary\n <mask token>\n <mask token>\n <mask token>\n\n @staticmethod\n def is_cotisation_paid(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n if (delta.days > 7 and now.month == 9 and CotisationComputes.\n is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn)):\n return True\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_late(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days <= 30 and delta.days > 7\n <mask token>\n\n @staticmethod\n def is_no_cotisation(member_dn, user_session, residence_dn, cotisations\n =None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days > 30\n <mask token>\n\n @staticmethod\n def members_status_from_list_cotisations(user_session, residence_dn,\n cotisations):\n members_dict = dict()\n for cotisation in cotisations:\n cotisation_dn = cotisation.dn.split(',')\n member_dn = ''\n for i in range(3, len(cotisation_dn)):\n if i != 3:\n member_dn += ','\n member_dn += cotisation_dn[i]\n if not member_dn in members_dict:\n members_dict[member_dn] = [cotisation]\n else:\n members_dict[member_dn].append(cotisation)\n BrieLogging.get().debug(str(datetime.datetime.now()) +\n 'members_status_from_list_cotisations:' + str(len(members_dict)))\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member_dn, cotisations in members_dict.iteritems():\n old_members.append(member_dn)\n rooms = Room.get_rooms(user_session, residence_dn)\n for room in rooms:\n if room.has('x-memberIn') and room.get('x-memberIn').first(\n ) in members_dict and room.get('x-memberIn').first(\n ) in old_members:\n old_members.remove(room.get('x-memberIn').first())\n for member_dn, cotisations in members_dict.iteritems():\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n if CotisationComputes.is_cotisation_paid(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_paid_members.append(member_dn)\n elif CotisationComputes.is_cotisation_late(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_late_members.append(member_dn)\n elif CotisationComputes.is_no_cotisation(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n no_cotisation_members.append(member_dn)\n else:\n BrieLogging.get().debug(\n 'aurore_helper:393 : member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n",
"step-2": "<mask token>\n\n\nclass CotisationComputes:\n\n @staticmethod\n def current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year + 1\n return now.year\n\n @staticmethod\n def registration_current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year\n return now.year - 1\n <mask token>\n\n @staticmethod\n def is_valid_month(month):\n now = datetime.datetime.now()\n if now.month > 8:\n return (month >= now.month and month < 13 or month >= 1 and \n month < 9)\n else:\n return month >= now.month and month < 9\n\n @staticmethod\n def price_to_pay(year_price, month_price, already_paid,\n number_months_to_pay):\n months_price = number_months_to_pay * month_price\n BrieLogging.get().debug('already paid : ' + str(already_paid))\n BrieLogging.get().debug('months price : ' + str(months_price))\n if already_paid + months_price > year_price:\n months_price = max(0, year_price - already_paid)\n return months_price\n\n @staticmethod\n def anniversary_from_ldap_items(ldap_cotisations):\n result = []\n months = []\n SORT_ORDER = {(9): 0, (10): 1, (11): 2, (12): 3, (1): 4, (2): 5, (3\n ): 6, (4): 7, (5): 8, (6): 9, (7): 10, (8): 11}\n for cotisation in ldap_cotisations:\n cotisation_months = []\n anniversary_data = cotisation.get('x-time').first()\n anniversary_datetime = datetime.datetime.strptime(anniversary_data,\n '%Y-%m-%d %H:%M:%S.%f')\n for month in cotisation.get('x-validMonth').all():\n months.append(int(month))\n cotisation_months.append(int(month))\n cotisation_months.sort(key=lambda val: SORT_ORDER[val])\n result.append((anniversary_datetime, cotisation_months))\n anniversary = 0\n result = sorted(result)\n previousMonth = -1\n months.sort(key=lambda val: SORT_ORDER[val])\n for resultat in result:\n if previousMonth != -1 and (resultat[1][0] == 1 and \n previousMonth == 12 or resultat[1][0] == previousMonth + 1):\n previousMonth = resultat[1][-1]\n continue\n else:\n previousMonth = resultat[1][-1]\n anniversary_day = resultat[0].day\n anniversary_month = months[-1] + 1\n if anniversary_month == 13:\n anniversary_month = 1\n if anniversary_month > 9 or resultat[0].month < 9:\n anniversary_year = resultat[0].year\n else:\n anniversary_year = resultat[0].year + 1\n anniversary = datetime.datetime.strptime(str(anniversary_year) +\n '-' + str(anniversary_month) + '-1 0:0', '%Y-%m-%d %H:%M'\n ) + datetime.timedelta(days=anniversary_day - 1)\n if anniversary == 0:\n anniversary = datetime.datetime(1999, 1, 31, 12, 0)\n return anniversary\n\n @staticmethod\n def generate_new_anniversary_from_ldap_items(ldap_cotisations):\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n ldap_cotisations)\n now = datetime.datetime.now()\n if anniversary == 0 or (now - anniversary).days > 30:\n return now\n else:\n return anniversary\n <mask token>\n\n @staticmethod\n def is_member_to_delete(member, user_session, residence_dn):\n current_year = CotisationComputes.current_year()\n cotisations_this_year = Cotisation.cotisations_of_member(user_session,\n member.dn, current_year)\n cotisations_previous_year = Cotisation.cotisations_of_member(\n user_session, member.dn, current_year - 1)\n if cotisations_this_year == [] and cotisations_previous_year == []:\n return True\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations_previous_year)\n delta = last_year - anniversary\n return cotisations_this_year == [] and (delta.days > 7 or Room.\n get_by_member_dn(user_session, residence_dn, member.dn) == None)\n <mask token>\n\n @staticmethod\n def is_cotisation_paid(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n if (delta.days > 7 and now.month == 9 and CotisationComputes.\n is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn)):\n return True\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_late(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days <= 30 and delta.days > 7\n <mask token>\n\n @staticmethod\n def is_no_cotisation(member_dn, user_session, residence_dn, cotisations\n =None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days > 30\n <mask token>\n\n @staticmethod\n def members_status_from_list_cotisations(user_session, residence_dn,\n cotisations):\n members_dict = dict()\n for cotisation in cotisations:\n cotisation_dn = cotisation.dn.split(',')\n member_dn = ''\n for i in range(3, len(cotisation_dn)):\n if i != 3:\n member_dn += ','\n member_dn += cotisation_dn[i]\n if not member_dn in members_dict:\n members_dict[member_dn] = [cotisation]\n else:\n members_dict[member_dn].append(cotisation)\n BrieLogging.get().debug(str(datetime.datetime.now()) +\n 'members_status_from_list_cotisations:' + str(len(members_dict)))\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member_dn, cotisations in members_dict.iteritems():\n old_members.append(member_dn)\n rooms = Room.get_rooms(user_session, residence_dn)\n for room in rooms:\n if room.has('x-memberIn') and room.get('x-memberIn').first(\n ) in members_dict and room.get('x-memberIn').first(\n ) in old_members:\n old_members.remove(room.get('x-memberIn').first())\n for member_dn, cotisations in members_dict.iteritems():\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n if CotisationComputes.is_cotisation_paid(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_paid_members.append(member_dn)\n elif CotisationComputes.is_cotisation_late(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_late_members.append(member_dn)\n elif CotisationComputes.is_no_cotisation(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n no_cotisation_members.append(member_dn)\n else:\n BrieLogging.get().debug(\n 'aurore_helper:393 : member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n",
"step-3": "<mask token>\n\n\nclass CotisationComputes:\n\n @staticmethod\n def current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year + 1\n return now.year\n\n @staticmethod\n def registration_current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year\n return now.year - 1\n\n @staticmethod\n def get_available_months(start, end, paid_months=[]):\n next_months_available = []\n if start > 12 or end > 12:\n raise Exception('invalid start or end')\n if start > 8 and end > 8:\n next_months_available = range(start, end + 1)\n elif start <= 8 and end < 9:\n next_months_available = range(start, end + 1)\n elif start > 8:\n next_months_available = range(start, 13) + range(1, end + 1)\n else:\n raise Exception('invalid start and end')\n if paid_months == []:\n return next_months_available\n BrieLogging.get().debug(next_months_available)\n available_months = [month for month in next_months_available if \n month not in paid_months]\n return available_months\n\n @staticmethod\n def is_valid_month(month):\n now = datetime.datetime.now()\n if now.month > 8:\n return (month >= now.month and month < 13 or month >= 1 and \n month < 9)\n else:\n return month >= now.month and month < 9\n\n @staticmethod\n def price_to_pay(year_price, month_price, already_paid,\n number_months_to_pay):\n months_price = number_months_to_pay * month_price\n BrieLogging.get().debug('already paid : ' + str(already_paid))\n BrieLogging.get().debug('months price : ' + str(months_price))\n if already_paid + months_price > year_price:\n months_price = max(0, year_price - already_paid)\n return months_price\n\n @staticmethod\n def anniversary_from_ldap_items(ldap_cotisations):\n result = []\n months = []\n SORT_ORDER = {(9): 0, (10): 1, (11): 2, (12): 3, (1): 4, (2): 5, (3\n ): 6, (4): 7, (5): 8, (6): 9, (7): 10, (8): 11}\n for cotisation in ldap_cotisations:\n cotisation_months = []\n anniversary_data = cotisation.get('x-time').first()\n anniversary_datetime = datetime.datetime.strptime(anniversary_data,\n '%Y-%m-%d %H:%M:%S.%f')\n for month in cotisation.get('x-validMonth').all():\n months.append(int(month))\n cotisation_months.append(int(month))\n cotisation_months.sort(key=lambda val: SORT_ORDER[val])\n result.append((anniversary_datetime, cotisation_months))\n anniversary = 0\n result = sorted(result)\n previousMonth = -1\n months.sort(key=lambda val: SORT_ORDER[val])\n for resultat in result:\n if previousMonth != -1 and (resultat[1][0] == 1 and \n previousMonth == 12 or resultat[1][0] == previousMonth + 1):\n previousMonth = resultat[1][-1]\n continue\n else:\n previousMonth = resultat[1][-1]\n anniversary_day = resultat[0].day\n anniversary_month = months[-1] + 1\n if anniversary_month == 13:\n anniversary_month = 1\n if anniversary_month > 9 or resultat[0].month < 9:\n anniversary_year = resultat[0].year\n else:\n anniversary_year = resultat[0].year + 1\n anniversary = datetime.datetime.strptime(str(anniversary_year) +\n '-' + str(anniversary_month) + '-1 0:0', '%Y-%m-%d %H:%M'\n ) + datetime.timedelta(days=anniversary_day - 1)\n if anniversary == 0:\n anniversary = datetime.datetime(1999, 1, 31, 12, 0)\n return anniversary\n\n @staticmethod\n def generate_new_anniversary_from_ldap_items(ldap_cotisations):\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n ldap_cotisations)\n now = datetime.datetime.now()\n if anniversary == 0 or (now - anniversary).days > 30:\n return now\n else:\n return anniversary\n <mask token>\n\n @staticmethod\n def is_member_to_delete(member, user_session, residence_dn):\n current_year = CotisationComputes.current_year()\n cotisations_this_year = Cotisation.cotisations_of_member(user_session,\n member.dn, current_year)\n cotisations_previous_year = Cotisation.cotisations_of_member(\n user_session, member.dn, current_year - 1)\n if cotisations_this_year == [] and cotisations_previous_year == []:\n return True\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations_previous_year)\n delta = last_year - anniversary\n return cotisations_this_year == [] and (delta.days > 7 or Room.\n get_by_member_dn(user_session, residence_dn, member.dn) == None)\n\n @staticmethod\n def is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn, cotisations=None, anniversary=None):\n if cotisations is None:\n current_year = CotisationComputes.current_year() - 1\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = last_year - anniversary\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_paid(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n if (delta.days > 7 and now.month == 9 and CotisationComputes.\n is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn)):\n return True\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_late(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days <= 30 and delta.days > 7\n\n def cotisation_late_reminder(member_dn, user_session, residence_dn):\n member = Member.get_by_dn(user_session, member_dn)\n from_mail = '[email protected]'\n to_mail = [member.mail.first()]\n residence_name = Residences.get_name_by_dn(user_session, residence_dn\n ).decode('utf-8').encode('ascii', 'ignore')\n\n @staticmethod\n def is_no_cotisation(member_dn, user_session, residence_dn, cotisations\n =None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days > 30\n\n @staticmethod\n def members_status_from_residence(user_session, residence_dn):\n members = Member.get_all(user_session, residence_dn)\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member in members:\n current_year = CotisationComputes.current_year()\n cotisations = Cotisation.cotisations_of_member(user_session,\n member.dn, current_year)\n if CotisationComputes.is_old_member(member.dn, user_session,\n residence_dn, cotisations):\n old_members.append(member)\n elif CotisationComputes.is_cotisation_paid(member.dn,\n user_session, residence_dn, cotisations):\n cotisation_paid_members.append(member)\n elif CotisationComputes.is_cotisation_late(member.dn,\n user_session, residence_dn, cotisations):\n cotisation_late_members.append(member)\n elif CotisationComputes.is_no_cotisation(member.dn,\n user_session, residence_dn, cotisations):\n no_cotisation_members.append(member)\n else:\n BrieLogging.get().warn(\n 'aurore_helper:336 member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n\n @staticmethod\n def members_status_from_list_cotisations(user_session, residence_dn,\n cotisations):\n members_dict = dict()\n for cotisation in cotisations:\n cotisation_dn = cotisation.dn.split(',')\n member_dn = ''\n for i in range(3, len(cotisation_dn)):\n if i != 3:\n member_dn += ','\n member_dn += cotisation_dn[i]\n if not member_dn in members_dict:\n members_dict[member_dn] = [cotisation]\n else:\n members_dict[member_dn].append(cotisation)\n BrieLogging.get().debug(str(datetime.datetime.now()) +\n 'members_status_from_list_cotisations:' + str(len(members_dict)))\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member_dn, cotisations in members_dict.iteritems():\n old_members.append(member_dn)\n rooms = Room.get_rooms(user_session, residence_dn)\n for room in rooms:\n if room.has('x-memberIn') and room.get('x-memberIn').first(\n ) in members_dict and room.get('x-memberIn').first(\n ) in old_members:\n old_members.remove(room.get('x-memberIn').first())\n for member_dn, cotisations in members_dict.iteritems():\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n if CotisationComputes.is_cotisation_paid(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_paid_members.append(member_dn)\n elif CotisationComputes.is_cotisation_late(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_late_members.append(member_dn)\n elif CotisationComputes.is_no_cotisation(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n no_cotisation_members.append(member_dn)\n else:\n BrieLogging.get().debug(\n 'aurore_helper:393 : member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n",
"step-4": "<mask token>\n\n\nclass CotisationComputes:\n\n @staticmethod\n def current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year + 1\n return now.year\n\n @staticmethod\n def registration_current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year\n return now.year - 1\n\n @staticmethod\n def get_available_months(start, end, paid_months=[]):\n next_months_available = []\n if start > 12 or end > 12:\n raise Exception('invalid start or end')\n if start > 8 and end > 8:\n next_months_available = range(start, end + 1)\n elif start <= 8 and end < 9:\n next_months_available = range(start, end + 1)\n elif start > 8:\n next_months_available = range(start, 13) + range(1, end + 1)\n else:\n raise Exception('invalid start and end')\n if paid_months == []:\n return next_months_available\n BrieLogging.get().debug(next_months_available)\n available_months = [month for month in next_months_available if \n month not in paid_months]\n return available_months\n\n @staticmethod\n def is_valid_month(month):\n now = datetime.datetime.now()\n if now.month > 8:\n return (month >= now.month and month < 13 or month >= 1 and \n month < 9)\n else:\n return month >= now.month and month < 9\n\n @staticmethod\n def price_to_pay(year_price, month_price, already_paid,\n number_months_to_pay):\n months_price = number_months_to_pay * month_price\n BrieLogging.get().debug('already paid : ' + str(already_paid))\n BrieLogging.get().debug('months price : ' + str(months_price))\n if already_paid + months_price > year_price:\n months_price = max(0, year_price - already_paid)\n return months_price\n\n @staticmethod\n def anniversary_from_ldap_items(ldap_cotisations):\n result = []\n months = []\n SORT_ORDER = {(9): 0, (10): 1, (11): 2, (12): 3, (1): 4, (2): 5, (3\n ): 6, (4): 7, (5): 8, (6): 9, (7): 10, (8): 11}\n for cotisation in ldap_cotisations:\n cotisation_months = []\n anniversary_data = cotisation.get('x-time').first()\n anniversary_datetime = datetime.datetime.strptime(anniversary_data,\n '%Y-%m-%d %H:%M:%S.%f')\n for month in cotisation.get('x-validMonth').all():\n months.append(int(month))\n cotisation_months.append(int(month))\n cotisation_months.sort(key=lambda val: SORT_ORDER[val])\n result.append((anniversary_datetime, cotisation_months))\n anniversary = 0\n result = sorted(result)\n previousMonth = -1\n months.sort(key=lambda val: SORT_ORDER[val])\n for resultat in result:\n if previousMonth != -1 and (resultat[1][0] == 1 and \n previousMonth == 12 or resultat[1][0] == previousMonth + 1):\n previousMonth = resultat[1][-1]\n continue\n else:\n previousMonth = resultat[1][-1]\n anniversary_day = resultat[0].day\n anniversary_month = months[-1] + 1\n if anniversary_month == 13:\n anniversary_month = 1\n if anniversary_month > 9 or resultat[0].month < 9:\n anniversary_year = resultat[0].year\n else:\n anniversary_year = resultat[0].year + 1\n anniversary = datetime.datetime.strptime(str(anniversary_year) +\n '-' + str(anniversary_month) + '-1 0:0', '%Y-%m-%d %H:%M'\n ) + datetime.timedelta(days=anniversary_day - 1)\n if anniversary == 0:\n anniversary = datetime.datetime(1999, 1, 31, 12, 0)\n return anniversary\n\n @staticmethod\n def generate_new_anniversary_from_ldap_items(ldap_cotisations):\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n ldap_cotisations)\n now = datetime.datetime.now()\n if anniversary == 0 or (now - anniversary).days > 30:\n return now\n else:\n return anniversary\n\n @staticmethod\n def is_old_member(member_dn, user_session, residence_dn, cotisations=None):\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n return Room.get_by_member_dn(user_session, residence_dn, member_dn\n ) == None or datetime.datetime.now(\n ).month != 9 and cotisations == []\n\n @staticmethod\n def is_member_to_delete(member, user_session, residence_dn):\n current_year = CotisationComputes.current_year()\n cotisations_this_year = Cotisation.cotisations_of_member(user_session,\n member.dn, current_year)\n cotisations_previous_year = Cotisation.cotisations_of_member(\n user_session, member.dn, current_year - 1)\n if cotisations_this_year == [] and cotisations_previous_year == []:\n return True\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations_previous_year)\n delta = last_year - anniversary\n return cotisations_this_year == [] and (delta.days > 7 or Room.\n get_by_member_dn(user_session, residence_dn, member.dn) == None)\n\n @staticmethod\n def is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn, cotisations=None, anniversary=None):\n if cotisations is None:\n current_year = CotisationComputes.current_year() - 1\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = last_year - anniversary\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_paid(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n if (delta.days > 7 and now.month == 9 and CotisationComputes.\n is_cotisation_was_paid_last_year(member_dn, user_session,\n residence_dn)):\n return True\n return delta.days <= 7\n\n @staticmethod\n def is_cotisation_late(member_dn, user_session, residence_dn,\n cotisations=None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days <= 30 and delta.days > 7\n\n def cotisation_late_reminder(member_dn, user_session, residence_dn):\n member = Member.get_by_dn(user_session, member_dn)\n from_mail = '[email protected]'\n to_mail = [member.mail.first()]\n residence_name = Residences.get_name_by_dn(user_session, residence_dn\n ).decode('utf-8').encode('ascii', 'ignore')\n\n @staticmethod\n def is_no_cotisation(member_dn, user_session, residence_dn, cotisations\n =None, anniversary=None, verification_old_member=True):\n if verification_old_member and CotisationComputes.is_old_member(\n member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n now = datetime.datetime.now()\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session,\n member_dn, current_year)\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n delta = now - anniversary\n return delta.days > 30\n\n @staticmethod\n def members_status_from_residence(user_session, residence_dn):\n members = Member.get_all(user_session, residence_dn)\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member in members:\n current_year = CotisationComputes.current_year()\n cotisations = Cotisation.cotisations_of_member(user_session,\n member.dn, current_year)\n if CotisationComputes.is_old_member(member.dn, user_session,\n residence_dn, cotisations):\n old_members.append(member)\n elif CotisationComputes.is_cotisation_paid(member.dn,\n user_session, residence_dn, cotisations):\n cotisation_paid_members.append(member)\n elif CotisationComputes.is_cotisation_late(member.dn,\n user_session, residence_dn, cotisations):\n cotisation_late_members.append(member)\n elif CotisationComputes.is_no_cotisation(member.dn,\n user_session, residence_dn, cotisations):\n no_cotisation_members.append(member)\n else:\n BrieLogging.get().warn(\n 'aurore_helper:336 member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n\n @staticmethod\n def members_status_from_list_cotisations(user_session, residence_dn,\n cotisations):\n members_dict = dict()\n for cotisation in cotisations:\n cotisation_dn = cotisation.dn.split(',')\n member_dn = ''\n for i in range(3, len(cotisation_dn)):\n if i != 3:\n member_dn += ','\n member_dn += cotisation_dn[i]\n if not member_dn in members_dict:\n members_dict[member_dn] = [cotisation]\n else:\n members_dict[member_dn].append(cotisation)\n BrieLogging.get().debug(str(datetime.datetime.now()) +\n 'members_status_from_list_cotisations:' + str(len(members_dict)))\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member_dn, cotisations in members_dict.iteritems():\n old_members.append(member_dn)\n rooms = Room.get_rooms(user_session, residence_dn)\n for room in rooms:\n if room.has('x-memberIn') and room.get('x-memberIn').first(\n ) in members_dict and room.get('x-memberIn').first(\n ) in old_members:\n old_members.remove(room.get('x-memberIn').first())\n for member_dn, cotisations in members_dict.iteritems():\n anniversary = CotisationComputes.anniversary_from_ldap_items(\n cotisations)\n if CotisationComputes.is_cotisation_paid(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_paid_members.append(member_dn)\n elif CotisationComputes.is_cotisation_late(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n cotisation_late_members.append(member_dn)\n elif CotisationComputes.is_no_cotisation(member_dn,\n user_session, residence_dn, cotisations, anniversary, False):\n no_cotisation_members.append(member_dn)\n else:\n BrieLogging.get().debug(\n 'aurore_helper:393 : member with weird status !')\n return dict(old_members=old_members, cotisation_paid_members=\n cotisation_paid_members, cotisation_late_members=\n cotisation_late_members, no_cotisation_members=\n no_cotisation_members)\n",
"step-5": "from brie.config import ldap_config\nfrom brie.model.ldap import *\nfrom brie.lib.log_helper import BrieLogging\nimport datetime\nimport smtplib\n\nclass Residences:\n \n @staticmethod\n def get_dn_by_name(user_session, name):\n result = user_session.ldap_bind.search_first(ldap_config.liste_residence_dn, \"(cn=\" + name + \")\")\n\n if result is None:\n return None\n #end if\n\n return result.uniqueMember.first()\n #end def\n\n @staticmethod\n def get_name_by_dn(user_session, dn):\n result = user_session.ldap_bind.search_first(ldap_config.liste_residence_dn, \"(uniqueMember=\" + dn + \")\")\n\n if result is None:\n return None\n #end if\n \n return result.cn.first()\n #end def\n \n @staticmethod\n def get_residences(user_session):\n return user_session.ldap_bind.search(ldap_config.liste_residence_dn, \"(objectClass=groupOfUniqueNames)\")\n #end def\n#end class\n\nclass CotisationComputes:\n \n @staticmethod\n def current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year + 1\n\n return now.year\n #end def\n\n @staticmethod\n def registration_current_year():\n now = datetime.datetime.now()\n if now.month > 8:\n return now.year\n\n return now.year - 1\n #end def\n\n @staticmethod\n def get_available_months(start, end, paid_months = []):\n next_months_available = []\n\n if start > 12 or end > 12:\n raise Exception(\"invalid start or end\")\n\n if start > 8 and end > 8:\n next_months_available = range(start, end + 1)\n elif start <= 8 and end < 9:\n next_months_available = range(start, end + 1)\n elif start > 8:\n next_months_available = range(start, 13) + range(1, end + 1 )\n else:\n raise Exception(\"invalid start and end\")\n #end if\n\n if paid_months == []:\n return next_months_available\n\n BrieLogging.get().debug(next_months_available)\n available_months = [\n month\n for month in next_months_available\n if month not in paid_months\n ]\n\n return available_months\n\n #end def\n\n @staticmethod\n def is_valid_month(month):\n now = datetime.datetime.now()\n if now.month > 8:\n return (month >= now.month and month < 13) or (month >= 1 and month < 9)\n else:\n return month >= now.month and month < 9\n #end if\n #end def\n\n @staticmethod\n def price_to_pay(year_price, month_price, already_paid, number_months_to_pay):\n \n months_price = number_months_to_pay * month_price\n BrieLogging.get().debug(\"already paid : \" + str(already_paid))\n BrieLogging.get().debug(\"months price : \" + str(months_price))\n if already_paid + months_price > year_price:\n months_price = max(0, year_price - already_paid)\n\n return months_price\n #end def\n\n @staticmethod\n def anniversary_from_ldap_items(ldap_cotisations):\n result = []\n months = []\n SORT_ORDER = {9: 0, 10: 1, 11: 2, 12: 3, 1: 4, 2: 5, 3: 6, 4: 7, 5: 8, 6: 9, 7: 10, 8: 11}\n for cotisation in ldap_cotisations:\n cotisation_months = []\n anniversary_data = cotisation.get(\"x-time\").first()\n anniversary_datetime = datetime.datetime.strptime(anniversary_data,\n \"%Y-%m-%d %H:%M:%S.%f\") \n for month in cotisation.get(\"x-validMonth\").all():\n months.append(int(month)) \n cotisation_months.append(int(month))\n #end for\n cotisation_months.sort(key=lambda val: SORT_ORDER[val])\n result.append((anniversary_datetime, cotisation_months))\n #end for\n\n anniversary = 0\n # tri par ordre d'inscription\n result = sorted(result)\n previousMonth = -1\n months.sort(key=lambda val: SORT_ORDER[val])\n #on scanne chaque cotisation\n for resultat in result:\n #si on n'est pas la premiere cotisation et que les cotisations sont sans interruptions (pas de mois manquants)\n #la date anniversaire reste la meme\n if previousMonth != -1 and ( (resultat[1][0] == 1 and previousMonth == 12) or (resultat[1][0] == previousMonth + 1) ):\n previousMonth = resultat[1][-1]\n continue;\n #sinon on recalcule la date anniversaire\n else : \n previousMonth = resultat[1][-1]\n #end if\n anniversary_day = resultat[0].day\n anniversary_month = months[-1] + 1\n if anniversary_month == 13:\n anniversary_month = 1\n if anniversary_month > 9 or resultat[0].month < 9:\n #on reste avec une annee d'anniversaire sur l'annee de la cotisation si l'anniversaire est entre septembre et decembre, mais on met aussi l'annee_anniversaire la meme annee que la cotisation si on a cotise entre janvier et aout\n anniversary_year = resultat[0].year\n else :\n #sinon, c'est qu'on a cotise entre septembre et decembre et que notre fin de cotisation est l'annee suivante, donc on fait un +1\n anniversary_year = resultat[0].year + 1\n anniversary = datetime.datetime.strptime(str(anniversary_year) + \"-\" + str(anniversary_month) + \"-1 0:0\", \"%Y-%m-%d %H:%M\") + datetime.timedelta(days=(anniversary_day - 1))\n #end for\n\n if anniversary == 0:\n anniversary = datetime.datetime(1999, 1, 31, 12, 0)\n\n return anniversary\n #end def\n\n @staticmethod\n # fonction de renvoi de la date anniversaire qui est la date actuelle au cas ou il n'a pas cotise depuis 30 jours, sinon date anniversaire actuelle\n def generate_new_anniversary_from_ldap_items(ldap_cotisations):\n anniversary = CotisationComputes.anniversary_from_ldap_items(ldap_cotisations)\n now = datetime.datetime.now()\n if anniversary == 0 or (now - anniversary).days > 30:\n return now\n else : \n return anniversary\n #end if\n #end def\n\n @staticmethod\n # old = SDF or no cotisation this year\n def is_old_member(member_dn, user_session, residence_dn, cotisations = None):\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)\n #end if\n #en septembre, on ne met pas de membre en old afin que les anciens ne soient pas deconnectes\n return Room.get_by_member_dn(user_session, residence_dn, member_dn) == None or (datetime.datetime.now().month != 9 and cotisations == [])\n #end def\n\n @staticmethod\n # no cotisation for the new year and last year august didn't payed\n def is_member_to_delete(member, user_session, residence_dn):\n current_year = CotisationComputes.current_year()\n cotisations_this_year = Cotisation.cotisations_of_member(user_session, member.dn, current_year)\n cotisations_previous_year = Cotisation.cotisations_of_member(user_session, member.dn, current_year - 1)\n\n if cotisations_this_year == [] and cotisations_previous_year == []:\n return True\n\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n #end if\n\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations_previous_year)\n #end if\n\n #si il a pas cotise cette annee et qu'il n'avait pas pris jusqua fin aout l'an dernier\n delta = (last_year - anniversary)\n return cotisations_this_year == [] and (delta.days > 7 or Room.get_by_member_dn(user_session, residence_dn, member.dn) == None)\n\n #end def\n\n @staticmethod\n # 7 days grace period\n def is_cotisation_was_paid_last_year(member_dn, user_session, residence_dn, cotisations = None, anniversary = None):\n if cotisations is None:\n current_year = CotisationComputes.current_year() - 1\n #end if\n\n now = datetime.datetime.now()\n if now.month < 9:\n last_year = datetime.datetime(now.year - 1, 8, 31, 12, 0)\n else:\n last_year = datetime.datetime(now.year, 8, 31, 12, 0)\n #end if\n\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)\n #end if\n\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)\n #end if\n\n delta = (last_year - anniversary)\n return delta.days <= 7\n #end def\n\n @staticmethod\n # 7 days grace period\n def is_cotisation_paid(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):\n if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n #end if\n now = datetime.datetime.now()\n\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)\n #end if\n\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)\n #end if\n\n delta = (now - anniversary)\n if delta.days > 7 and now.month == 9 and CotisationComputes.is_cotisation_was_paid_last_year(member_dn, user_session, residence_dn):\n #le membre etait a jour en aout, on lui autorise un delai de paiement en septembre - pas de deconnexion\n return True\n #end if\n\n return delta.days <= 7\n #end def\n\n @staticmethod\n # less than a month late but more than a week\n def is_cotisation_late(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):\n if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n #end if\n now = datetime.datetime.now()\n\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)\n #end if\n\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)\n #end if\n\n delta = (now - anniversary)\n #print(\"[DEBUG] cotisation en retard pour l'utilisateur \"+ member.dn +\" now=\"+ str(now) +\" anniversary=\"+ str(anniversary) +\" delta=\"+ str(delta))\n return delta.days <= 30 and delta.days > 7\n #end def\n\n def cotisation_late_reminder(member_dn, user_session, residence_dn):\n member = Member.get_by_dn(user_session,member_dn)\n from_mail = \"[email protected]\"\n to_mail = [member.mail.first()]\n residence_name = Residences.get_name_by_dn(user_session,residence_dn).decode(\"utf-8\").encode(\"ascii\", \"ignore\")\n #end def\n\n @staticmethod\n # more than a month late\n def is_no_cotisation(member_dn, user_session, residence_dn, cotisations = None, anniversary = None, verification_old_member = True):\n if verification_old_member and CotisationComputes.is_old_member(member_dn, user_session, residence_dn, cotisations):\n return False\n if cotisations is None:\n current_year = CotisationComputes.current_year()\n #end if\n now = datetime.datetime.now()\n\n if cotisations is None:\n cotisations = Cotisation.cotisations_of_member(user_session, member_dn, current_year)\n #end if\n\n if anniversary is None:\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)\n #end if\n \n delta = (now - anniversary)\n return delta.days > 30\n #end def\n\n @staticmethod\n def members_status_from_residence(user_session, residence_dn):\n members = Member.get_all(user_session, residence_dn)\n\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n for member in members:\n current_year = CotisationComputes.current_year()\n cotisations = Cotisation.cotisations_of_member(user_session, member.dn, current_year)\n if CotisationComputes.is_old_member(member.dn, user_session, residence_dn, cotisations):\n old_members.append(member)\n elif CotisationComputes.is_cotisation_paid(member.dn, user_session, residence_dn, cotisations):\n cotisation_paid_members.append(member)\n elif CotisationComputes.is_cotisation_late(member.dn, user_session, residence_dn, cotisations):\n cotisation_late_members.append(member)\n #print(\"[DEBUG] cotisation en retard pour l'utilisateur \"+ member.dn)\n elif CotisationComputes.is_no_cotisation(member.dn, user_session, residence_dn, cotisations):\n no_cotisation_members.append(member)\n else:\n BrieLogging.get().warn(\"aurore_helper:336 member with weird status !\")\n #end if\n\n #end for\n return dict(old_members=old_members, cotisation_paid_members=cotisation_paid_members, cotisation_late_members=cotisation_late_members, no_cotisation_members=no_cotisation_members)\n #end def\n\n @staticmethod\n def members_status_from_list_cotisations(user_session, residence_dn, cotisations):\n members_dict = dict()\n for cotisation in cotisations:\n cotisation_dn = cotisation.dn.split(\",\")\n member_dn = \"\"\n for i in range(3, len(cotisation_dn)):\n if i != 3:\n member_dn += \",\"\n #end if\n member_dn += cotisation_dn[i]\n #end for\n if not member_dn in members_dict:\n members_dict[member_dn] = [cotisation]\n else:\n members_dict[member_dn].append(cotisation)\n #end if\n #end for\n\n BrieLogging.get().debug(str(datetime.datetime.now()) + \"members_status_from_list_cotisations:\" + str(len(members_dict)))\n\n old_members = []\n cotisation_paid_members = []\n cotisation_late_members = []\n no_cotisation_members = []\n\n #on va verifier en un block quels sont les old_members\n for member_dn, cotisations in members_dict.iteritems():\n old_members.append(member_dn)\n #end for\n rooms = Room.get_rooms(user_session, residence_dn)\n for room in rooms:\n #pour chaque chambre, on check si il a un proprietaire, et si ce dernier a des cotisations\n if room.has(\"x-memberIn\") and room.get(\"x-memberIn\").first() in members_dict and room.get(\"x-memberIn\").first() in old_members:\n #si oui, bah on le retire des old_members\n old_members.remove(room.get(\"x-memberIn\").first())\n #endif\n #endfor\n\n\n for member_dn, cotisations in members_dict.iteritems():\n anniversary = CotisationComputes.anniversary_from_ldap_items(cotisations)\n if CotisationComputes.is_cotisation_paid(member_dn, user_session, residence_dn, cotisations, anniversary, False):\n cotisation_paid_members.append(member_dn)\n elif CotisationComputes.is_cotisation_late(member_dn, user_session, residence_dn, cotisations, anniversary, False):\n cotisation_late_members.append(member_dn)\n #print(\"[DEBUG] cotisation en retard pour l'utilisateur \"+ member.dn)\n elif CotisationComputes.is_no_cotisation(member_dn, user_session, residence_dn, cotisations, anniversary, False):\n no_cotisation_members.append(member_dn)\n else:\n BrieLogging.get().debug(\"aurore_helper:393 : member with weird status !\")\n #end if\n\n #end for\n return dict(old_members=old_members, cotisation_paid_members=cotisation_paid_members, cotisation_late_members=cotisation_late_members, no_cotisation_members=no_cotisation_members)\n #end def\n\n#end class\n",
"step-ids": [
11,
12,
16,
17,
23
]
}
|
[
11,
12,
16,
17,
23
] |
import markovify
import argparse
import sqlite3
import time
modelFile = './data/model.json'
corpusFile = './data/corpus.txt'
dbFile = './data/tweets.sqlite3'
def generate():
generate_count = 168
model_json = open(modelFile, 'r').read()
model = markovify.Text.from_json(model_json)
conn = sqlite3.connect(dbFile)
c = conn.cursor()
for i in range(generate_count):
content = model.make_short_sentence(140)
generated_timestamp = int(time.time())
if content:
c.execute('INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)', (content,generated_timestamp))
print(content)
print(generated_timestamp)
print('----------')
conn.commit()
conn.close()
def make_model():
corpus = open(corpusFile).read()
text_model = markovify.Text(corpus, state_size=4)
model_json = text_model.to_json()
f = open(modelFile, mode='w')
f.write(model_json)
f.close()
def full_gen():
corpus = open(corpusFile).read()
model = markovify.Text(corpus, state_size=4)
generate_count = 168
conn = sqlite3.connect(dbFile)
c = conn.cursor()
for i in range(generate_count):
content = model.make_short_sentence(140, max_overlap_ratio=.8)
generated_timestamp = int(time.time())
if content:
c.execute('INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)', (content,generated_timestamp))
print(content)
print(generated_timestamp)
print('----------')
conn.commit()
conn.close()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--model", action="store_true", default=False, help="Create Model JSON")
parser.add_argument("--gen", action="store_true", default=False, help="Generate from stored Model")
parser.add_argument("--full", action="store_true", default=False, help="Full Geneate")
args = parser.parse_args()
if args.gen:
generate()
elif args.model:
make_model()
else:
full_gen()
|
normal
|
{
"blob_id": "cc71c0cc1ec21dc465486fb5894c4d389c39bd62",
"index": 8164,
"step-1": "<mask token>\n\n\ndef make_model():\n corpus = open(corpusFile).read()\n text_model = markovify.Text(corpus, state_size=4)\n model_json = text_model.to_json()\n f = open(modelFile, mode='w')\n f.write(model_json)\n f.close()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef generate():\n generate_count = 168\n model_json = open(modelFile, 'r').read()\n model = markovify.Text.from_json(model_json)\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\ndef make_model():\n corpus = open(corpusFile).read()\n text_model = markovify.Text(corpus, state_size=4)\n model_json = text_model.to_json()\n f = open(modelFile, mode='w')\n f.write(model_json)\n f.close()\n\n\ndef full_gen():\n corpus = open(corpusFile).read()\n model = markovify.Text(corpus, state_size=4)\n generate_count = 168\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140, max_overlap_ratio=0.8)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--model', action='store_true', default=False, help\n ='Create Model JSON')\n parser.add_argument('--gen', action='store_true', default=False, help=\n 'Generate from stored Model')\n parser.add_argument('--full', action='store_true', default=False, help=\n 'Full Geneate')\n args = parser.parse_args()\n if args.gen:\n generate()\n elif args.model:\n make_model()\n else:\n full_gen()\n",
"step-3": "<mask token>\nmodelFile = './data/model.json'\ncorpusFile = './data/corpus.txt'\ndbFile = './data/tweets.sqlite3'\n\n\ndef generate():\n generate_count = 168\n model_json = open(modelFile, 'r').read()\n model = markovify.Text.from_json(model_json)\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\ndef make_model():\n corpus = open(corpusFile).read()\n text_model = markovify.Text(corpus, state_size=4)\n model_json = text_model.to_json()\n f = open(modelFile, mode='w')\n f.write(model_json)\n f.close()\n\n\ndef full_gen():\n corpus = open(corpusFile).read()\n model = markovify.Text(corpus, state_size=4)\n generate_count = 168\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140, max_overlap_ratio=0.8)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--model', action='store_true', default=False, help\n ='Create Model JSON')\n parser.add_argument('--gen', action='store_true', default=False, help=\n 'Generate from stored Model')\n parser.add_argument('--full', action='store_true', default=False, help=\n 'Full Geneate')\n args = parser.parse_args()\n if args.gen:\n generate()\n elif args.model:\n make_model()\n else:\n full_gen()\n",
"step-4": "import markovify\nimport argparse\nimport sqlite3\nimport time\nmodelFile = './data/model.json'\ncorpusFile = './data/corpus.txt'\ndbFile = './data/tweets.sqlite3'\n\n\ndef generate():\n generate_count = 168\n model_json = open(modelFile, 'r').read()\n model = markovify.Text.from_json(model_json)\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\ndef make_model():\n corpus = open(corpusFile).read()\n text_model = markovify.Text(corpus, state_size=4)\n model_json = text_model.to_json()\n f = open(modelFile, mode='w')\n f.write(model_json)\n f.close()\n\n\ndef full_gen():\n corpus = open(corpusFile).read()\n model = markovify.Text(corpus, state_size=4)\n generate_count = 168\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n for i in range(generate_count):\n content = model.make_short_sentence(140, max_overlap_ratio=0.8)\n generated_timestamp = int(time.time())\n if content:\n c.execute(\n 'INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)'\n , (content, generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n conn.commit()\n conn.close()\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argument('--model', action='store_true', default=False, help\n ='Create Model JSON')\n parser.add_argument('--gen', action='store_true', default=False, help=\n 'Generate from stored Model')\n parser.add_argument('--full', action='store_true', default=False, help=\n 'Full Geneate')\n args = parser.parse_args()\n if args.gen:\n generate()\n elif args.model:\n make_model()\n else:\n full_gen()\n",
"step-5": "import markovify\nimport argparse\nimport sqlite3\nimport time\n\nmodelFile = './data/model.json'\ncorpusFile = './data/corpus.txt'\ndbFile = './data/tweets.sqlite3'\n\ndef generate():\n generate_count = 168\n model_json = open(modelFile, 'r').read()\n model = markovify.Text.from_json(model_json)\n\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n\n for i in range(generate_count):\n content = model.make_short_sentence(140)\n generated_timestamp = int(time.time())\n\n if content:\n c.execute('INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)', (content,generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n\n conn.commit()\n\n conn.close()\n\ndef make_model():\n corpus = open(corpusFile).read()\n\n text_model = markovify.Text(corpus, state_size=4)\n model_json = text_model.to_json()\n\n f = open(modelFile, mode='w')\n f.write(model_json)\n f.close()\n\n\ndef full_gen():\n corpus = open(corpusFile).read()\n\n model = markovify.Text(corpus, state_size=4)\n\n generate_count = 168\n\n conn = sqlite3.connect(dbFile)\n c = conn.cursor()\n\n for i in range(generate_count):\n content = model.make_short_sentence(140, max_overlap_ratio=.8)\n generated_timestamp = int(time.time())\n\n if content:\n c.execute('INSERT INTO tweets (content,generated_timestamp) VALUES (?,?)', (content,generated_timestamp))\n print(content)\n print(generated_timestamp)\n print('----------')\n\n conn.commit()\n\n conn.close()\n\n\n\nif __name__ == \"__main__\":\n parser = argparse.ArgumentParser()\n parser.add_argument(\"--model\", action=\"store_true\", default=False, help=\"Create Model JSON\")\n parser.add_argument(\"--gen\", action=\"store_true\", default=False, help=\"Generate from stored Model\")\n parser.add_argument(\"--full\", action=\"store_true\", default=False, help=\"Full Geneate\")\n args = parser.parse_args()\n if args.gen:\n generate()\n elif args.model:\n make_model()\n else:\n full_gen()\n",
"step-ids": [
1,
4,
5,
6,
7
]
}
|
[
1,
4,
5,
6,
7
] |
import json
from pets.pet import Pet
from store_requests.store import Store
from user_requests.user import User
SUCCESS = 200
NotFound = 404
url_site = 'https://petstore.swagger.io/v2'
new_username = "Khrystyna"
new_id = 12345
invalid_new_id = 1234
error_message = "oops we have a problem!"
store_inventory = {
"1": 1,
"4444": 2,
"teste": 1,
"string": 6738,
"Operated": 4,
"pending": 56,
"Not-Operated": 10,
"available": 4800,
"waiting list": 1,
"Unavailable": 1,
"Shortlisted": 1,
"Sold": 1,
"availasdfsadfasdfble": 1,
"not available": 1,
"Available": 1,
"YAI3424forYAI3373": 1,
"ok": 1,
"KBMAvailable": 3,
"onwork": 1,
"sold": 87,
"ddd": 1,
"Nonavailable": 1,
"Offline": 1,
"straight": 2,
"pendin": 1,
"sts": 1,
"onhold": 3,
"status": 5,
"xavailable": 1
}
Category_Dict = dict(id=36,
name='Rexy')
tag_dict = dict(id=4,
name='Dog')
PetObject = Pet(id=456,
category=Category_Dict,
name="Xixi",
photo_urls=["https://www.what-dog.net/Images/faces2/scroll001.jpg"],
tags=[tag_dict],
status='sold')
DataJsonForPets = json.dumps(PetObject.__dict__)
store = Store(id=12,
petId=12,
quantity=2,
ship_date="2018-09-12T13:52:49.901Z",
status="placed",
complete=True)
data_json_for_store = json.dumps(store.__dict__)
user = User(id=3,
username="Nini",
first_name="Vira",
last_name="Budda",
email="[email protected]",
password="1234567",
phone="55455545",
user_status=1)
data_json_for_user = json.dumps(user.__dict__)
|
normal
|
{
"blob_id": "54ed0683d0f8d907c27e2f3809f9533556593392",
"index": 5546,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nSUCCESS = 200\nNotFound = 404\nurl_site = 'https://petstore.swagger.io/v2'\nnew_username = 'Khrystyna'\nnew_id = 12345\ninvalid_new_id = 1234\nerror_message = 'oops we have a problem!'\nstore_inventory = {'1': 1, '4444': 2, 'teste': 1, 'string': 6738,\n 'Operated': 4, 'pending': 56, 'Not-Operated': 10, 'available': 4800,\n 'waiting list': 1, 'Unavailable': 1, 'Shortlisted': 1, 'Sold': 1,\n 'availasdfsadfasdfble': 1, 'not available': 1, 'Available': 1,\n 'YAI3424forYAI3373': 1, 'ok': 1, 'KBMAvailable': 3, 'onwork': 1, 'sold':\n 87, 'ddd': 1, 'Nonavailable': 1, 'Offline': 1, 'straight': 2, 'pendin':\n 1, 'sts': 1, 'onhold': 3, 'status': 5, 'xavailable': 1}\nCategory_Dict = dict(id=36, name='Rexy')\ntag_dict = dict(id=4, name='Dog')\nPetObject = Pet(id=456, category=Category_Dict, name='Xixi', photo_urls=[\n 'https://www.what-dog.net/Images/faces2/scroll001.jpg'], tags=[tag_dict\n ], status='sold')\nDataJsonForPets = json.dumps(PetObject.__dict__)\nstore = Store(id=12, petId=12, quantity=2, ship_date=\n '2018-09-12T13:52:49.901Z', status='placed', complete=True)\ndata_json_for_store = json.dumps(store.__dict__)\nuser = User(id=3, username='Nini', first_name='Vira', last_name='Budda',\n email='[email protected]', password='1234567', phone='55455545',\n user_status=1)\ndata_json_for_user = json.dumps(user.__dict__)\n",
"step-3": "import json\nfrom pets.pet import Pet\nfrom store_requests.store import Store\nfrom user_requests.user import User\nSUCCESS = 200\nNotFound = 404\nurl_site = 'https://petstore.swagger.io/v2'\nnew_username = 'Khrystyna'\nnew_id = 12345\ninvalid_new_id = 1234\nerror_message = 'oops we have a problem!'\nstore_inventory = {'1': 1, '4444': 2, 'teste': 1, 'string': 6738,\n 'Operated': 4, 'pending': 56, 'Not-Operated': 10, 'available': 4800,\n 'waiting list': 1, 'Unavailable': 1, 'Shortlisted': 1, 'Sold': 1,\n 'availasdfsadfasdfble': 1, 'not available': 1, 'Available': 1,\n 'YAI3424forYAI3373': 1, 'ok': 1, 'KBMAvailable': 3, 'onwork': 1, 'sold':\n 87, 'ddd': 1, 'Nonavailable': 1, 'Offline': 1, 'straight': 2, 'pendin':\n 1, 'sts': 1, 'onhold': 3, 'status': 5, 'xavailable': 1}\nCategory_Dict = dict(id=36, name='Rexy')\ntag_dict = dict(id=4, name='Dog')\nPetObject = Pet(id=456, category=Category_Dict, name='Xixi', photo_urls=[\n 'https://www.what-dog.net/Images/faces2/scroll001.jpg'], tags=[tag_dict\n ], status='sold')\nDataJsonForPets = json.dumps(PetObject.__dict__)\nstore = Store(id=12, petId=12, quantity=2, ship_date=\n '2018-09-12T13:52:49.901Z', status='placed', complete=True)\ndata_json_for_store = json.dumps(store.__dict__)\nuser = User(id=3, username='Nini', first_name='Vira', last_name='Budda',\n email='[email protected]', password='1234567', phone='55455545',\n user_status=1)\ndata_json_for_user = json.dumps(user.__dict__)\n",
"step-4": "import json\n\nfrom pets.pet import Pet\nfrom store_requests.store import Store\nfrom user_requests.user import User\n\nSUCCESS = 200\nNotFound = 404\nurl_site = 'https://petstore.swagger.io/v2'\nnew_username = \"Khrystyna\"\nnew_id = 12345\ninvalid_new_id = 1234\nerror_message = \"oops we have a problem!\"\nstore_inventory = {\n \"1\": 1,\n \"4444\": 2,\n \"teste\": 1,\n \"string\": 6738,\n \"Operated\": 4,\n \"pending\": 56,\n \"Not-Operated\": 10,\n \"available\": 4800,\n \"waiting list\": 1,\n \"Unavailable\": 1,\n \"Shortlisted\": 1,\n \"Sold\": 1,\n \"availasdfsadfasdfble\": 1,\n \"not available\": 1,\n \"Available\": 1,\n \"YAI3424forYAI3373\": 1,\n \"ok\": 1,\n \"KBMAvailable\": 3,\n \"onwork\": 1,\n \"sold\": 87,\n \"ddd\": 1,\n \"Nonavailable\": 1,\n \"Offline\": 1,\n \"straight\": 2,\n \"pendin\": 1,\n \"sts\": 1,\n \"onhold\": 3,\n \"status\": 5,\n \"xavailable\": 1\n}\n\nCategory_Dict = dict(id=36,\n name='Rexy')\ntag_dict = dict(id=4,\n name='Dog')\nPetObject = Pet(id=456,\n category=Category_Dict,\n name=\"Xixi\",\n photo_urls=[\"https://www.what-dog.net/Images/faces2/scroll001.jpg\"],\n tags=[tag_dict],\n status='sold')\nDataJsonForPets = json.dumps(PetObject.__dict__)\n\nstore = Store(id=12,\n petId=12,\n quantity=2,\n ship_date=\"2018-09-12T13:52:49.901Z\",\n status=\"placed\",\n complete=True)\ndata_json_for_store = json.dumps(store.__dict__)\n\nuser = User(id=3,\n username=\"Nini\",\n first_name=\"Vira\",\n last_name=\"Budda\",\n email=\"[email protected]\",\n password=\"1234567\",\n phone=\"55455545\",\n user_status=1)\ndata_json_for_user = json.dumps(user.__dict__)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#part-handler
# vi: syntax=python ts=4
#
# Copyright (C) 2012 Silpion IT-Solutions GmbH
#
# Author: Malte Stretz <[email protected]>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 3, as
# published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import os
import StringIO
import tarfile
CACHE_DIR = '/var/cache/cloud'
def list_types():
return(['application/tar'])
def handle_part(data, ctype, filename, payload):
if ctype == ('application/tar'):
dir = "%s/%s" % (CACHE_DIR, os.path.splitext(filename)[0])
if not os.path.exists(dir):
os.makedirs(dir)
buf = StringIO.StringIO(payload)
tar = tarfile.open(name=filename, fileobj=buf)
tar.extractall(dir)
tar.close()
buf.close()
|
normal
|
{
"blob_id": "98b27c268fe1f47a899269e988ddf798faf827df",
"index": 8401,
"step-1": "<mask token>\n\n\ndef list_types():\n return ['application/tar']\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef list_types():\n return ['application/tar']\n\n\ndef handle_part(data, ctype, filename, payload):\n if ctype == 'application/tar':\n dir = '%s/%s' % (CACHE_DIR, os.path.splitext(filename)[0])\n if not os.path.exists(dir):\n os.makedirs(dir)\n buf = StringIO.StringIO(payload)\n tar = tarfile.open(name=filename, fileobj=buf)\n tar.extractall(dir)\n tar.close()\n buf.close()\n",
"step-3": "<mask token>\nCACHE_DIR = '/var/cache/cloud'\n\n\ndef list_types():\n return ['application/tar']\n\n\ndef handle_part(data, ctype, filename, payload):\n if ctype == 'application/tar':\n dir = '%s/%s' % (CACHE_DIR, os.path.splitext(filename)[0])\n if not os.path.exists(dir):\n os.makedirs(dir)\n buf = StringIO.StringIO(payload)\n tar = tarfile.open(name=filename, fileobj=buf)\n tar.extractall(dir)\n tar.close()\n buf.close()\n",
"step-4": "import os\nimport StringIO\nimport tarfile\nCACHE_DIR = '/var/cache/cloud'\n\n\ndef list_types():\n return ['application/tar']\n\n\ndef handle_part(data, ctype, filename, payload):\n if ctype == 'application/tar':\n dir = '%s/%s' % (CACHE_DIR, os.path.splitext(filename)[0])\n if not os.path.exists(dir):\n os.makedirs(dir)\n buf = StringIO.StringIO(payload)\n tar = tarfile.open(name=filename, fileobj=buf)\n tar.extractall(dir)\n tar.close()\n buf.close()\n",
"step-5": "#part-handler\n# vi: syntax=python ts=4\n#\n# Copyright (C) 2012 Silpion IT-Solutions GmbH\n#\n# Author: Malte Stretz <[email protected]>\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the GNU General Public License version 3, as\n# published by the Free Software Foundation.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITHOUT ANY WARRANTY; without even the implied warranty of\n# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n# GNU General Public License for more details.\n#\n# You should have received a copy of the GNU General Public License\n# along with this program. If not, see <http://www.gnu.org/licenses/>.\n\nimport os\nimport StringIO\nimport tarfile\n\nCACHE_DIR = '/var/cache/cloud'\n\ndef list_types():\n return(['application/tar'])\n\ndef handle_part(data, ctype, filename, payload):\n if ctype == ('application/tar'):\n dir = \"%s/%s\" % (CACHE_DIR, os.path.splitext(filename)[0])\n if not os.path.exists(dir):\n os.makedirs(dir)\n buf = StringIO.StringIO(payload)\n tar = tarfile.open(name=filename, fileobj=buf)\n tar.extractall(dir)\n tar.close()\n buf.close()\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
#Credits To @maxprogrammer007 (for editing)
# Ported for Ultroid < https://github.com/TeamUltroid/Ultroid >
import os
import sys
import logging
from telethon import events
import asyncio
from userbot.utils import admin_cmd
from userbot import ALIVE_NAME
import random, re
from userbot import CMD_HELP
from collections import deque
import importlib.util
import random
DEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else "Cat"
@borg.on(admin_cmd(pattern="stupid$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
await event.edit("brain")
animation_chars = [
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <)🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i %14 ])
@borg.on(admin_cmd(pattern=f"bombs$", outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n")
await asyncio.sleep(1)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n")
await asyncio.sleep(0.5)
await event.edit("`RIP PLOXXX......`")
await asyncio.sleep(2)
@borg.on(admin_cmd(pattern=f"kill$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.7
animation_ttl = range(0, 12)
await event.edit("ready to die dude.....")
animation_chars = [
"Ｆｉｉｉｉｉｒｅ",
"(　･ิω･ิ)︻デâ•ä¸€-->",
"---->____________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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"------>__________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â _____",
"-------------->â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â ____",
"------------------>",
"------>;(^。^)ノ",
"(￣ー￣) DEAD",
"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern="ding$"))
async def _(event):
animation_interval = 0.3
animation_ttl = range(0, 30)
animation_chars = [
"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴",
"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴",
"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜",
"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜"
]
if event.fwd_from:
return
await event.edit("ding..dong..ding..dong ...")
await asyncio.sleep(4)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern=f"hypno$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 15)
await event.edit("hypo....")
animation_chars = [
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛",
"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛",
"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜",
"[👉🔴👈])"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 15])
@borg.on(admin_cmd(pattern="gangasta$"))
async def _(event):
await event.edit("EVERyBOdy")
await asyncio.sleep(0.3)
await event.edit("iZ")
await asyncio.sleep(0.2)
await event.edit("GangSTur")
await asyncio.sleep(0.5)
await event.edit("UNtIL ")
await asyncio.sleep(0.2)
await event.edit("I")
await asyncio.sleep(0.3)
await event.edit("ArRivE")
await asyncio.sleep(0.3)
await event.edit("🔥🔥🔥")
await asyncio.sleep(0.3)
await event.edit("EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥")
@borg.on(admin_cmd(pattern=f"charging$"))
async def timer_blankx(e):
txt=e.text[10:] + '\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` '
j=10
k=j
for j in range(j):
await e.edit(txt + str(k))
k=k+10
await asyncio.sleep(1)
await asyncio.sleep(1)
await e.edit("`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) ", link_preview=True)
@borg.on(admin_cmd("bigoof"))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 7)
await event.edit("â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›")
animation_chars = [
"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ ",
"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 7])
@borg.on(admin_cmd(pattern="g1 ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1)
await event.edit(pay)
@borg.on(admin_cmd(pattern="uff ?(.*)"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = [
"U",
"Uf",
"Uff",
"Ufffff",
"Uffffff",
"Ufffffff",
"Uffffffff",
"Ufffffffff",
"Uffffffffff",
"Ufffffffffff",
"Uffffffffffff",
"Ufffffffffffff",
"Uffffffffffffff"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern="ctext ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*8, paytext*8)
await event.edit(pay)
@borg.on(admin_cmd(pattern="ftext ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*6, paytext*6, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2)
await event.edit(pay)
@borg.on(admin_cmd(outgoing=True, pattern="kf$(.*)"))
async def _(event):
r = random.randint(0, 3)
logger.debug(r)
if r == 0:
await event.edit("â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›")
else:
r == 1
await event.edit("â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯")
@borg.on(admin_cmd(pattern="f (.*)"))
async def payf(e):
paytext = e.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*5, paytext*1,paytext*1, paytext*4, paytext*1, paytext*1, paytext*1)
await e.edit(pay)
@borg.on(admin_cmd(pattern=f"loading$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"â–®",
"â–¯",
"â–¬",
"â–",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"square$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"â—§",
"â—¨",
"â—§",
"â—¨",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"up$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"╹",
"â•»",
"╹",
"â•»",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"round$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"âš«",
"⬤",
"â—",
"∘",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"hart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 20)
animation_chars = [
"🖤",
"â¤ï¸",
"🖤",
"â¤ï¸",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"anim$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 11)
animation_chars = [
"ðŸ˜",
"😧",
"😡",
"😢",
"‎**HellBoy Bolte Public**",
"ðŸ˜",
"😧",
"😡",
"😢",
"[PAPA HERE](https://t.me/Kraken_The_BadASS)",
"__**Good to See you Guys....**__"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"fnl$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = [
"ðŸ˜ðŸ¿",
"ðŸ˜ðŸ¾",
"ðŸ˜ðŸ½",
"ðŸ˜ðŸ¼",
"‎ðŸ˜",
"**Good to See you Guys....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"monkey$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = [
"ðŸµ",
"🙉",
"🙈",
"🙊",
"🖕‎ðŸµðŸ–•",
"**Good to See you Guys....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"herber$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 11)
animation_chars = [
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"hand$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
animation_chars = [
"👈",
"👉",
"â˜ï¸",
"👆",
"🖕",
"👇",
"✌ï¸",
"🤞",
"🖖",
"🤘",
"🤙",
"ðŸ–ï¸",
"👌"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f"gsg$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = [
"🔟",
"9ï¸âƒ£",
"8ï¸âƒ£",
"7ï¸âƒ£",
"6ï¸âƒ£",
"5ï¸âƒ£",
"4ï¸âƒ£",
"3ï¸âƒ£",
"2ï¸âƒ£",
"1ï¸âƒ£",
"0ï¸âƒ£",
"🆘"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern=r"theart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 54)
animation_chars = [
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 18])
@borg.on(admin_cmd(pattern=r"fdance"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 5)
await event.edit("Connecting..")
animation_chars = [
"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n",
"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n",
"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n",
"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n",
"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@borg.on(admin_cmd(pattern=f"snake$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 27)
await event.edit("snake..")
animation_chars = [
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 27])
@borg.on(admin_cmd(pattern=f"human$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
await event.edit("human...")
animation_chars = [
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=f"mc$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 28)
await event.edit("mc..")
animation_chars = [
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 28])
@borg.on(admin_cmd(pattern="virus$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 30)
await event.edit("Injecting virus....")
animation_chars = [
"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸",
"â—¼ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=r"repe$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.2
animation_ttl = range(0, 30)
await event.edit("repe")
animation_chars = [
"**r**",
"**ra**",
"**rap**",
"**rape**",
"**rape_**",
"**rape_t**",
"**rape_tr**",
"**rape_tra**",
"**rape_trai**",
"**rape_train**",
"**ape_train🚅**",
"**pe_train🚅🚃🚃**",
"**e_train🚅🚃🚃🚃**",
"**_train🚅🚃🚃🚃🚃**",
"**train🚅🚃🚃🚃🚃🚃**",
"**rain🚅🚃🚃🚃🚃🚃🚃**",
"**ain🚅🚃🚃🚃🚃🚃🚃🚃**",
"**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**",
"**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**",
"🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃",
"🚃🚃🚃",
"🚃🚃",
"🚃",
"**rApEd**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=f"isro$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 24)
await event.edit("Connecting..")
animation_chars = [
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛",
"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"__Signal Lost....__"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 24])
@borg.on(admin_cmd(pattern=f"nakal$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 6)
await event.edit("nakal")
animation_chars = [
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"music$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.5
animation_ttl = range(0, 11)
await event.edit("starting player...")
animation_chars = [
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"squ$",outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(6)
@borg.on(admin_cmd(pattern=r"star$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🦋✨🦋✨🦋✨🦋✨"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"boxs"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🟥🟧🟨🟩🟦🟪🟫⬛⬜"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"rain$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🌬â˜ï¸ðŸŒ©ðŸŒ¨ðŸŒ§ðŸŒ¦ðŸŒ¥â›…🌤"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"clol$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🤔ðŸ§ðŸ¤¨ðŸ¤”ðŸ§ðŸ¤¨"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"odra$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🚶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"deploy$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 3
animation_ttl = range(0, 12)
await event.edit("Deploying...")
animation_chars = [
"**Heroku Connecting To Latest Github Build **",
f"**Build started by user** @Kraken_The_BadASS",
f"**Deploy** `535a74f0` for user by my master!!",
"**Restarting Heroku Server...**",
"**State changed from up to starting**",
"**Stopping all processes with SIGTERM**",
"**Process exited with** `status 143`",
"**Starting process with command** `python3 -m stdborg`",
"**State changed from starting to up**",
"__INFO:Userbot:Logged in as 557667062__",
"__INFO:Userbot:Successfully loaded all plugins__",
"**Build Succeeded**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern="dump ?(.*)"))
async def _(message):
try:
obj = message.pattern_match.group(1)
if len(obj) != 3:
raise IndexError
inp = ' '.join(obj)
except IndexError:
inp = "🥞 🎂 ðŸ«"
u, t, g, o, s, n = inp.split(), '🗑', '<(^_^ <)', '(> ^_^)>', '⠀ ', '\n'
h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]
for something in reversed([y for y in ([''.join(x) for x in (
f + (s, g, s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t),
f[:i] + (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''), o, f[i], s, t),
f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i] + (s * 3 + s * f.count(''), o, t),
f[:i] + (s * 3 + s * f.count(''), g, t))] for i, f in enumerate(reversed(h)))]):
for something_else in something:
await asyncio.sleep(0.3)
try:
await message.edit(something_else)
except errors.MessageIdInvalidError:
return
@borg.on(admin_cmd(pattern="fleaveme$"))
async def _(event):
animation_interval = 1
animation_ttl = range(0, 10)
animation_chars = [
"⬛⬛⬛\n⬛⬛⬛\n⬛⬛⬛",
"⬛⬛⬛\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸",
"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸",
"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸"
]
if event.fwd_from:
return
await event.edit("fleaveme....")
await asyncio.sleep(2)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern="loveu", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 70)
await event.edit("loveu")
animation_chars = [
"😀",
"👩â€ðŸŽ¨",
"ðŸ˜",
"😂",
"🤣",
"😃",
"😄",
"😅",
"😊",
"☺",
"🙂",
"🤔",
"🤨",
"ðŸ˜",
"😑",
"😶",
"😣",
"😥",
"😮",
"ðŸ¤",
"😯",
"😴",
"😔",
"😕",
"☹",
"ðŸ™",
"😖",
"😞",
"😟",
"😢",
"ðŸ˜",
"🤯",
"💔",
"â¤",
"i Love Youâ¤",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 35])
@borg.on(admin_cmd(pattern=f"plane", outgoing=True))
async def _(event):
if event.fwd_from:
retun
await event.edit("✈-------------")
await event.edit("-✈------------")
await event.edit("--✈-----------")
await event.edit("---✈----------")
await event.edit("----✈---------")
await event.edit("-----✈--------")
await event.edit("------✈-------")
await event.edit("-------✈------")
await event.edit("--------✈-----")
await event.edit("---------✈----")
await event.edit("----------✈---")
await event.edit("-----------✈--")
await event.edit("------------✈-")
await event.edit("-------------✈")
await asyncio.sleep(3)
await event.delete()
@borg.on(admin_cmd(pattern=r"pulis"))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 12)
await event.edit("Pulis")
animation_chars = [
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
f"{DEFAULTUSER} **Police iz Here**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern=f"jio$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 19)
await event.edit("jio network boosting...")
animation_chars = [
"`Connecting To JIO NETWORK ....`",
"`â–ˆ â–‡ â–† â–… â–„ â–‚ â–`",
"`â–’ â–‡ â–† â–… â–„ â–‚ â–`",
"`â–’ â–’ â–† â–… â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–… â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`",
"*Optimising JIO NETWORK...*",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`",
"`â– â–’ â–’ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–’ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–„ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–„ â–… â–’ â–’ â–’`",
"`â– â–‚ â–„ â–… â–† â–’ â–’`",
"`â– â–‚ â–„ â–… â–† â–‡ â–’`",
"`â– â–‚ â–„ â–… â–† â–‡ â–ˆ`",
"**JIO NETWORK Boosted....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 19])
@borg.on(admin_cmd(pattern=f"solarsystem", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 80)
await event.edit("solarsystem")
animation_chars = [
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=r"lul$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("😂🤣😂🤣😂🤣"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"nothappy$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern="clock$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•ðŸ•›"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"muah$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("😗😙😚😚😘"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern="heart$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("â¤ï¸ðŸ§¡ðŸ’›ðŸ’šðŸ’™ðŸ’œðŸ–¤"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern="gym$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"earth$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸŒðŸŒðŸŒŽðŸŒŽðŸŒðŸŒðŸŒðŸŒŽ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern="moon$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🌗🌘🌑🌒🌓🌔🌕🌖"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"candy$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸ¦ðŸ§ðŸ©ðŸªðŸŽ‚ðŸ°ðŸ§ðŸ«ðŸ¬ðŸ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"smoon$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 101)
await event.edit("smoon..")
animation_chars = [
"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗",
"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘",
"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑",
"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒",
"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓",
"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔",
"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕",
"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=f"tmoon$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 117)
await event.edit("tmoon")
animation_chars = [
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 32])
@borg.on(admin_cmd(pattern=f"clown$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.50
animation_ttl = range(0, 16)
animation_chars = [
"COMMAND CREATE BY @Kraken_The_BadASS",
"🤡ï¸",
"🤡🤡",
"🤡🤡🤡",
"🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡",
"🤡🤡🤡",
"🤡🤡",
"🤡",
"You",
"You Are",
"You Are A",
"You Are A Clown 🤡"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=r"aheart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.3
animation_ttl = range(0, 50)
animation_chars = [
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"💔",
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"💔"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 20])
|
normal
|
{
"blob_id": "51cff2f7dd1fd10c6f447d62db3e98075caebe51",
"index": 1708,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\[email protected](admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\[email protected](admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\[email protected](admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\[email protected](admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\[email protected](admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\[email protected](admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\[email protected](admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\[email protected](admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\[email protected](admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\[email protected](admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\[email protected](admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\[email protected](admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\[email protected](admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\[email protected](admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\[email protected](admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\[email protected](admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\[email protected](admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\[email protected](admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\[email protected](admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\[email protected](admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-3": "<mask token>\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'\n\n\[email protected](admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\[email protected](admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\[email protected](admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\[email protected](admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\[email protected](admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\[email protected](admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\[email protected](admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\[email protected](admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\[email protected](admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\[email protected](admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\[email protected](admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\[email protected](admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\[email protected](admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\[email protected](admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\[email protected](admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\[email protected](admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\[email protected](admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\[email protected](admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\[email protected](admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\[email protected](admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-4": "import os\nimport sys\nimport logging\nfrom telethon import events\nimport asyncio\nfrom userbot.utils import admin_cmd\nfrom userbot import ALIVE_NAME\nimport random, re\nfrom userbot import CMD_HELP\nfrom collections import deque\nimport importlib.util\nimport random\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'\n\n\[email protected](admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\[email protected](admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\[email protected](admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\[email protected](admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\[email protected](admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\[email protected](admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\[email protected](admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\[email protected](admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\[email protected](admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\[email protected](admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\[email protected](admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\[email protected](admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\[email protected](admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\[email protected](admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\[email protected](admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\[email protected](admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\[email protected](admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\[email protected](admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\[email protected](admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\[email protected](admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\[email protected](admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\[email protected](admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\[email protected](admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\[email protected](admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\[email protected](admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\[email protected](admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\[email protected](admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\[email protected](admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\[email protected](admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\[email protected](admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\[email protected](admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\[email protected](admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-5": "#Credits To @maxprogrammer007 (for editing)\n# Ported for Ultroid < https://github.com/TeamUltroid/Ultroid > \n\n\nimport os\nimport sys\nimport logging\nfrom telethon import events\nimport asyncio\nfrom userbot.utils import admin_cmd\nfrom userbot import ALIVE_NAME\nimport random, re\nfrom userbot import CMD_HELP\nfrom collections import deque\nimport importlib.util\nimport random\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else \"Cat\"\n\[email protected](admin_cmd(pattern=\"stupid$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit(\"brain\")\n animation_chars = [ \n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <)🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n(> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n <(^_^ <)🗑\",\n ]\n for i in animation_ttl:\n \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i %14 ])\n\t\t\[email protected](admin_cmd(pattern=f\"bombs$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\n\")\n await asyncio.sleep(1)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💥💥💥💥 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💥💥💥💥 \\n💥💥💥💥 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n😵😵😵😵 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"`RIP PLOXXX......`\")\n await asyncio.sleep(2)\n \n \n \[email protected](admin_cmd(pattern=f\"kill$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit(\"ready to die dude.....\")\n animation_chars = [\n\n \"Ｆｉｉｉｉｉｒｅ\",\n \"(　･ิω･ิ)︻デâ•ä¸€-->\", \n \"---->____________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â \",\n \"------>__________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â ____\",\n \"------------------>\", \n \"------>;(^。^)ノ\",\n \"(￣ー￣) DEAD\",\n \"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\\n '#Sad_Reacts_Online'\\n\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n \[email protected](admin_cmd(pattern=\"ding$\"))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30) \n animation_chars = [\n \n \"🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬛⬜⬜⬜\\n🔴⬜⬜⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬛⬜⬜\\n⬜⬜🔴⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬜⬛⬜\\n⬜⬜⬜⬜🔴\",\n \"⬜⬜⬛⬛🔴\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\", \n \"⬜⬜⬛⬜⬜\\n⬜⬜⬜⬛⬜\\n⬜⬜⬜⬜🔴\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬛⬜⬜\\n⬜⬜🔴⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬛⬜⬜⬜\\n🔴⬜⬜⬜⬜\",\n \"🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\",\n\t \"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\n \n ]\n if event.fwd_from:\n return\n await event.edit(\"ding..dong..ding..dong ...\")\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n \[email protected](admin_cmd(pattern=f\"hypno$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit(\"hypo....\")\n animation_chars = [\n \n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬛⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬛⬛⬛⬜⬜\\n⬜⬜⬛⬜⬛⬜⬜\\n⬜⬜⬛⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\",\n \"⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\", \n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬛\\n⬛⬜⬛⬜⬛\\n⬛⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜\\n⬜⬛⬜\\n⬜⬜⬜\",\n \"[👉🔴👈])\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\t\t\t\t\[email protected](admin_cmd(pattern=\"gangasta$\"))\nasync def _(event):\n await event.edit(\"EVERyBOdy\")\n await asyncio.sleep(0.3)\n await event.edit(\"iZ\")\n await asyncio.sleep(0.2)\n await event.edit(\"GangSTur\")\n await asyncio.sleep(0.5)\n await event.edit(\"UNtIL \")\n await asyncio.sleep(0.2)\n await event.edit(\"I\")\n await asyncio.sleep(0.3)\n await event.edit(\"ArRivE\")\n await asyncio.sleep(0.3)\n await event.edit(\"🔥🔥🔥\")\n await asyncio.sleep(0.3)\n await event.edit(\"EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥\")\t\t\n\[email protected](admin_cmd(pattern=f\"charging$\"))\nasync def timer_blankx(e):\n txt=e.text[10:] + '\\n\\n`Tesla Wireless Charging (beta) Started...\\nDevice Detected: Nokia 1100\\nBattery Percentage:` '\n j=10\n k=j\n for j in range(j):\n await e.edit(txt + str(k))\n k=k+10\n await asyncio.sleep(1)\n await asyncio.sleep(1) \n await e.edit(\"`Tesla Wireless Charging (beta) Completed...\\nDevice Detected: Nokia 1100 (Space Grey Varient)\\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \", link_preview=True)\n\n\[email protected](admin_cmd(\"bigoof\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \\n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \\n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \\n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \\n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \\nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\")\n animation_chars = [\n \"â•â”â”â”╮╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”╯╰╯ \",\n \"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃┃┃ \\n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\n ]\n \n for i in animation_ttl: \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\[email protected](admin_cmd(pattern=\"g1 ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1)\n await event.edit(pay)\n\[email protected](admin_cmd(pattern=\"uff ?(.*)\")) \nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1 \n animation_ttl = range(0, 13) \n animation_chars = [\n \"U\",\n \"Uf\", \n \"Uff\",\n \"Ufffff\",\n \"Uffffff\",\n \"Ufffffff\",\n \"Uffffffff\",\n \"Ufffffffff\",\n \"Uffffffffff\", \n \"Ufffffffffff\",\n \"Uffffffffffff\",\n \"Ufffffffffffff\",\n \"Uffffffffffffff\"\n ]\n for i in animation_ttl: \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\[email protected](admin_cmd(pattern=\"ctext ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*8, paytext*8)\n await event.edit(pay)\n \[email protected](admin_cmd(pattern=\"ftext ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*6, paytext*6, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2)\n await event.edit(pay) \n\[email protected](admin_cmd(outgoing=True, pattern=\"kf$(.*)\"))\nasync def _(event): \n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\"â”â”â”â”┓\\n┃â”â”â”â”›\\n┃┗â”â”┓\\n┃â”â”â”â”›\\n┃┃\\nâ”—â”›\")\n else:\n r == 1 \n await event.edit(\"â•â”â”â”â•®\\n┃â•â”â”╯\\n┃╰â”â”â•®\\n┃â•â”â”╯\\n┃┃\\n╰╯\") \n\[email protected](admin_cmd(pattern=\"f (.*)\"))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*5, paytext*1,paytext*1, paytext*4, paytext*1, paytext*1, paytext*1)\n await e.edit(pay)\n\[email protected](admin_cmd(pattern=f\"loading$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"â–®\",\n \"â–¯\",\n \"â–¬\",\n \"â–\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\[email protected](admin_cmd(pattern=f\"square$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"â—§\",\n \"â—¨\",\n \"â—§\",\n \"â—¨\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\[email protected](admin_cmd(pattern=f\"up$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"╹\",\n \"â•»\",\n \"╹\",\n \"â•»\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n \[email protected](admin_cmd(pattern=f\"round$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"âš«\",\n \"⬤\",\n \"â—\",\n \"∘\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\[email protected](admin_cmd(pattern=f\"hart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = [\n \"🖤\",\n \"â¤ï¸\",\n \"🖤\",\n \"â¤ï¸\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\[email protected](admin_cmd(pattern=f\"anim$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = [\n \"ðŸ˜\",\n \"😧\",\n \"😡\",\n \"😢\",\n \"‎**HellBoy Bolte Public**\",\n \"ðŸ˜\",\n \"😧\",\n \"😡\",\n \"😢\",\n \"[PAPA HERE](https://t.me/Kraken_The_BadASS)\",\n \"__**Good to See you Guys....**__\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n \[email protected](admin_cmd(pattern=f\"fnl$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = [\n \"ðŸ˜ðŸ¿\",\n \"ðŸ˜ðŸ¾\",\n \"ðŸ˜ðŸ½\",\n \"ðŸ˜ðŸ¼\",\n \"‎ðŸ˜\",\n \"**Good to See you Guys....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\[email protected](admin_cmd(pattern=f\"monkey$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = [\n \"ðŸµ\",\n \"🙉\",\n \"🙈\",\n \"🙊\",\n \"🖕‎ðŸµðŸ–•\",\n \"**Good to See you Guys....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n \[email protected](admin_cmd(pattern=f\"herber$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 10%\\n\\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 5.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.13GB\\n **🔹used:** 33.77GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 158.98GB\\n **🔹recv:** 146.27GB\\n **🔹sent_packets:** 84518799\\n **🔹recv_packets:** 159720314\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 30%\\n\\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 20.4%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 7.18GB\\n **🔹used:** 28.26GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 146.27GB\\n **🔹recv:** 124.33GB\\n **🔹sent_packets:** 54635686\\n **🔹recv_packets:** 143565654\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 60%\\n\\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 60.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 6.52GB\\n **🔹used:** 35.78GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 124.33GB\\n **🔹recv:** 162.48GB\\n **🔹sent_packets:** 25655655\\n **🔹recv_packets:** 165289456\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 100%\\n\\n â—â—â—â—â—â—â—â—â—â—\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 100.0%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 9.81GB\\n **🔹used:** 30.11GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 162.48GB\\n **🔹recv:** 175.75GB\\n **🔹sent_packets:** 56565435\\n **🔹recv_packets:** 135345655\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 70%\\n\\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 80.4%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 5.76GB\\n **🔹used:** 29.35GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 175.75GB\\n **🔹recv:** 118.55GB\\n **🔹sent_packets:** 36547698\\n **🔹recv_packets:** 185466554\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 60%\\n\\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 62.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.23GB\\n **🔹used:** 33.32GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 118.55GB\\n **🔹recv:** 168.65GB\\n **🔹sent_packets:** 24786554\\n **🔹recv_packets:** 156745865\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 30%\\n\\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 30.6%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 9.75GB\\n **🔹used:** 36.54GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 168.65GB\\n **🔹recv:** 128.35GB\\n **🔹sent_packets:** 56565435\\n **🔹recv_packets:** 1475823589\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 10%\\n\\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 10.2%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 10.20GB\\n **🔹used:** 25.40GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 128.35GB\\n **🔹recv:** 108.31GB\\n **🔹sent_packets:** 54635686\\n **🔹recv_packets:** 157865426\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 100%\\n\\n â—â—â—â—â—â—â—â—â—â—\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 100.0%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 5.25GB\\n **🔹used:** 31.14GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 108.31GB\\n **🔹recv:** 167.17GB\\n **🔹sent_packets:** 84518799\\n **🔹recv_packets:** 124575356\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 70%\\n\\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 76.2%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.01GB\\n **🔹used:** 33.27GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 167.17GB\\n **🔹recv:** 158.98GB\\n **🔹sent_packets:** 36547698\\n **🔹recv_packets:** 165455856\\n\\n\\n**===================**\\n\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\[email protected](admin_cmd(pattern=f\"hand$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = [\n \"👈\",\n \"👉\",\n \"â˜ï¸\",\n \"👆\",\n \"🖕\",\n \"👇\",\n \"✌ï¸\",\n \"🤞\",\n \"🖖\",\n \"🤘\",\n \"🤙\",\n \"ðŸ–ï¸\",\n \"👌\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\[email protected](admin_cmd(pattern=f\"gsg$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = [\n \"🔟\",\n \"9ï¸âƒ£\",\n \"8ï¸âƒ£\",\n \"7ï¸âƒ£\",\n \"6ï¸âƒ£\",\n \"5ï¸âƒ£\",\n \"4ï¸âƒ£\",\n \"3ï¸âƒ£\",\n \"2ï¸âƒ£\",\n \"1ï¸âƒ£\",\n \"0ï¸âƒ£\",\n \"🆘\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\[email protected](admin_cmd(pattern=r\"theart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = [\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n \[email protected](admin_cmd(pattern=r\"fdance\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5) \n await event.edit(\"Connecting..\")\n animation_chars = [\n \n \"⠀⠀⠀⣶⣿⣶\\n⠀⠀⠀⣿⣿⣿⣀\\n⠀⣀⣿⣿⣿⣿⣿⣿\\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\\n⠛⠛⠛⣿⣿⣿⣿⠿\\n⠀⠀⠀⠀⣿⣿⣿\\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\\n⠀⣿⣿⣿⣿⣿⣿⠉\\n⣿⣿⣿⣿⣿⣿\\n⣿⣿⣶⣿⣿\\n⠉⠛⣿⣿⣶⣤\\n⠀⠀⠉⠿⣿⣿⣤\\n⠀⠀⣀⣤⣿⣿⣿\\n⠀⠒⠿⠛⠉⠿⣿\\n⠀⠀⠀⠀⠀⣀⣿⣿\\n⠀⠀⠀⠀⣶⠿⠿⠛\\n\",\n \"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\\n\",\n \"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\\n⠀⠀⠀⠀⠀⠀⣿⠛\\n⠀⠀⠀⠀⠀⠀â£â£¶\\n\",\n \"⠀⠀⠀⠀⠀⠀⣶⣿⣶\\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\\n\",\n \"⠀⠀⠀⠀⠀⠀⣤⣶⣶\\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\\n\", \n\n\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5]) \[email protected](admin_cmd(pattern=f\"snake$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit(\"snake..\")\n animation_chars = [\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27]) \n \n \[email protected](admin_cmd(pattern=f\"human$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit(\"human...\")\n animation_chars = [\n \n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛🚗\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛🚗⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛🚗⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🚗⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛🚗⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛🚗⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🚗⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜😊⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬛⬜⬛\\n⬛⬛⬜⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬛😊⬛⬜⬛\\n⬛⬛⬜⬜⬜⬛⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬛⬜⬜⬜⬛⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\", \n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜😊⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16]) \n \n \[email protected](admin_cmd(pattern=f\"mc$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit(\"mc..\")\n animation_chars = [\n\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28]) \n\t\t\[email protected](admin_cmd(pattern=\"virus$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit(\"Injecting virus....\")\n animation_chars = [\n \"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸\",\n \"â—¼ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\[email protected](admin_cmd(pattern=r\"repe$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit(\"repe\")\n animation_chars = [\n \n \"**r**\",\n \"**ra**\",\n \"**rap**\",\n \"**rape**\",\n \"**rape_**\", \n \"**rape_t**\",\n \"**rape_tr**\",\n \"**rape_tra**\",\n \"**rape_trai**\",\n \"**rape_train**\",\n \"**ape_train🚅**\",\n \"**pe_train🚅🚃🚃**\",\n \"**e_train🚅🚃🚃🚃**\",\n \"**_train🚅🚃🚃🚃🚃**\",\n \"**train🚅🚃🚃🚃🚃🚃**\",\n \"**rain🚅🚃🚃🚃🚃🚃🚃**\",\n \"**ain🚅🚃🚃🚃🚃🚃🚃🚃**\",\n \"**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**\",\n \"**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**\",\n \"🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃\",\n \"🚃🚃🚃\",\n \"🚃🚃\",\n \"🚃\",\n \"**rApEd**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\[email protected](admin_cmd(pattern=f\"isro$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit(\"Connecting..\")\n animation_chars = [\n \n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n🚀⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛🚀⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🚀⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🚀⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\", \n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛🚀⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛🚀\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"🛸⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n🛸⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛🛸⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🛸⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🛸⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\",\n \"⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"__Signal Lost....__\"\n\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\t\n\[email protected](admin_cmd(pattern=f\"nakal$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit(\"nakal\")\n animation_chars = [\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\", \n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\t\n\t\t\[email protected](admin_cmd(pattern=f\"music$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit(\"starting player...\")\n animation_chars = [\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\", \n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\t\t\n\[email protected](admin_cmd(pattern=f\"squ$\",outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n\n\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n \\tâ–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ \\tâ–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\") \n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1) \n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(6)\t\n\t\[email protected](admin_cmd(pattern=r\"star$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🦋✨🦋✨🦋✨🦋✨\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\[email protected](admin_cmd(pattern=r\"boxs\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🟥🟧🟨🟩🟦🟪🟫⬛⬜\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\[email protected](admin_cmd(pattern=f\"rain$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🌬â˜ï¸ðŸŒ©ðŸŒ¨ðŸŒ§ðŸŒ¦ðŸŒ¥â›…🌤\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\[email protected](admin_cmd(pattern=r\"clol$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🤔ðŸ§ðŸ¤¨ðŸ¤”ðŸ§ðŸ¤¨\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\n\[email protected](admin_cmd(pattern=r\"odra$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🚶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\n\t\t\[email protected](admin_cmd(pattern=r\"deploy$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit(\"Deploying...\")\n animation_chars = [\n \n \"**Heroku Connecting To Latest Github Build **\",\n f\"**Build started by user** @Kraken_The_BadASS\",\n f\"**Deploy** `535a74f0` for user by my master!!\",\n \"**Restarting Heroku Server...**\",\n \"**State changed from up to starting**\", \n \"**Stopping all processes with SIGTERM**\",\n \"**Process exited with** `status 143`\",\n \"**Starting process with command** `python3 -m stdborg`\",\n \"**State changed from starting to up**\",\n \"__INFO:Userbot:Logged in as 557667062__\",\n \"__INFO:Userbot:Successfully loaded all plugins__\",\n \"**Build Succeeded**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12]) \n\n\[email protected](admin_cmd(pattern=\"dump ?(.*)\"))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = \"🥞 🎂 ðŸ«\"\n u, t, g, o, s, n = inp.split(), '🗑', '<(^_^ <)', '(> ^_^)>', 'â € ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (\n f + (s, g, s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t),\n f[:i] + (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''), o, f[i], s, t),\n f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i] + (s * 3 + s * f.count(''), o, t),\n f[:i] + (s * 3 + s * f.count(''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\t\[email protected](admin_cmd(pattern=\"fleaveme$\"))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = [\n \n \"⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛\",\n \"⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â¬›\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬛⬛\", \n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬛↘ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬇ï¸â†˜ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬅ï¸ðŸ”„âž¡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\",\n \"↖ï¸â¬†ï¸â†—ï¸\\n⬅ï¸ðŸ”„âž¡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\"\n ]\n if event.fwd_from:\n return\n await event.edit(\"fleaveme....\")\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\t\t\[email protected](admin_cmd(pattern=\"loveu\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit(\"loveu\")\n animation_chars = [\n \"😀\",\n \"👩â€ðŸŽ¨\",\n \"ðŸ˜\", \n \"😂\",\n \"🤣\",\n \"😃\",\n \"😄\",\n \"😅\",\n \"😊\",\n \"☺\",\n \"🙂\", \n \"🤔\",\n \"🤨\",\n \"ðŸ˜\",\n \"😑\",\n \"😶\",\n \"😣\",\n \"😥\",\n \"😮\", \n \"ðŸ¤\",\n \"😯\",\n \"😴\",\n \"😔\",\n \"😕\",\n \"☹\",\n \"ðŸ™\",\n \"😖\", \n \"😞\",\n \"😟\",\n \"😢\",\n \"ðŸ˜\",\n \"🤯\",\n \"💔\",\n \"â¤\",\n \"i Love Youâ¤\", \n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n \[email protected](admin_cmd(pattern=f\"plane\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit(\"✈-------------\")\n await event.edit(\"-✈------------\")\n await event.edit(\"--✈-----------\")\n await event.edit(\"---✈----------\")\n await event.edit(\"----✈---------\")\n await event.edit(\"-----✈--------\")\n await event.edit(\"------✈-------\")\n await event.edit(\"-------✈------\")\n await event.edit(\"--------✈-----\") \n await event.edit(\"---------✈----\")\n await event.edit(\"----------✈---\")\n await event.edit(\"-----------✈--\")\n await event.edit(\"------------✈-\")\n await event.edit(\"-------------✈\")\n await asyncio.sleep(3)\n await event.delete() \n \n \[email protected](admin_cmd(pattern=r\"pulis\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit(\"Pulis\")\n animation_chars = [\n \n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\", \n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n f\"{DEFAULTUSER} **Police iz Here**\"\n\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12]) \n\n\t\[email protected](admin_cmd(pattern=f\"jio$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit(\"jio network boosting...\")\n animation_chars = [\n \"`Connecting To JIO NETWORK ....`\",\n \"`â–ˆ â–‡ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–‡ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–’ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–… â–„ â–‚ â–`\", \n \"`â–’ â–’ â–’ â–’ â–„ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`\",\n \"*Optimising JIO NETWORK...*\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`\",\n \"`â– â–’ â–’ â–’ â–’ â–’ â–’`\", \n \"`â– â–‚ â–’ â–’ â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–’ â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–‡ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–‡ â–ˆ`\",\n \"**JIO NETWORK Boosted....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19]) \n \n \[email protected](admin_cmd(pattern=f\"solarsystem\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit(\"solarsystem\")\n animation_chars = [\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\", \n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\[email protected](admin_cmd(pattern=r\"lul$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"😂🤣😂🤣😂🤣\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\n \[email protected](admin_cmd(pattern=r\"nothappy$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\[email protected](admin_cmd(outgoing=True, pattern=\"clock$\"))\nasync def _(event):\n\t if event.fwd_from:\n\t\t return\n\t deq = deque(list(\"🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•ðŸ•›\"))\n\t for _ in range(48):\n\t\t await asyncio.sleep(0.1)\n\t\t await event.edit(\"\".join(deq))\n\t\t deq.rotate(1)\n \[email protected](admin_cmd(pattern=r\"muah$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"😗😙😚😚😘\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\n \[email protected](admin_cmd(pattern=\"heart$\"))\t\t\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"â¤ï¸ðŸ§¡ðŸ’›ðŸ’šðŸ’™ðŸ’œðŸ–¤\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1) \n \n\t\t\[email protected](admin_cmd(pattern=\"gym$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n \[email protected](admin_cmd(pattern=f\"earth$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸŒðŸŒðŸŒŽðŸŒŽðŸŒðŸŒðŸŒðŸŒŽ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n \[email protected](admin_cmd(outgoing=True, pattern=\"moon$\"))\nasync def _(event):\n\t if event.fwd_from:\n\t\t return\n\t deq = deque(list(\"🌗🌘🌑🌒🌓🌔🌕🌖\"))\n\t for _ in range(48):\n\t\t await asyncio.sleep(0.1)\n\t\t await event.edit(\"\".join(deq))\n\t\t deq.rotate(1)\n\t\t\t\[email protected](admin_cmd(pattern=r\"candy$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸ¦ðŸ§ðŸ©ðŸªðŸŽ‚ðŸ°ðŸ§ðŸ«ðŸ¬ðŸ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\t\n \[email protected](admin_cmd(pattern=f\"smoon$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit(\"smoon..\")\n animation_chars = [\n\n \"🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\",\n \"🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\", \n \"🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\",\n \"🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\",\n \"🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\",\n \"🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\",\n \"🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\",\n \"🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n \[email protected](admin_cmd(pattern=f\"tmoon$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit(\"tmoon\")\n animation_chars = [\n\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\[email protected](admin_cmd(pattern=f\"clown$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.50\n animation_ttl = range(0, 16)\n animation_chars = [\n \n\n \"COMMAND CREATE BY @Kraken_The_BadASS\",\n \"🤡ï¸\",\n \"🤡🤡\",\n \"🤡🤡🤡\",\n \"🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡🤡🤡\", \n \"🤡🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡\",\n \"🤡🤡🤡\",\n \"🤡🤡\",\n \"🤡\",\n \"You\",\n \"You Are\",\n \"You Are A\",\n \"You Are A Clown 🤡\"\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\[email protected](admin_cmd(pattern=r\"aheart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = [\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"💔\",\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"💔\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20]) \n \n \n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
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