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27 Improve Performance with Algorithm Tuning/grid_search.py | IshmaelAsabere/Machine_Learning-Various-Topics | 0 | 1600201 | <gh_stars>0
# Grid Search for Algorithm Tuning
import numpy
from pandas import read_csv
from sklearn.linear_model import RidgeClassifier
from sklearn.model_selection import GridSearchCV
filename = 'pima-indians-diabetes.data.csv'
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
dataframe = read_csv(filename, names=names)
array = dataframe.values
X = array[:,0:8]
Y = array[:,8]
alphas = numpy.array([1,0.1,0.01,0.001,0.0001,0])
param_grid = dict(alpha=alphas)
model = RidgeClassifier()
grid = GridSearchCV(estimator=model, param_grid=param_grid, cv=3)
grid.fit(X, Y)
print(grid.best_score_)
print(grid.best_estimator_.alpha)
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yank/interface_database_mixin.py | khunspoonzi/yank | 1 | 107465 | <reponame>khunspoonzi/yank
# ┌────────────────────────────────────────────────────────────────────────────────────┐
# │ GENERAL IMPORTS │
# └────────────────────────────────────────────────────────────────────────────────────┘
from datetime import datetime
# ┌────────────────────────────────────────────────────────────────────────────────────┐
# │ SQLALCHEMY IMPORTS │
# └────────────────────────────────────────────────────────────────────────────────────┘
from sqlalchemy import Boolean, DateTime, exists, Float, func, Integer, String
# ┌────────────────────────────────────────────────────────────────────────────────────┐
# │ PROJECT IMPORTS │
# └────────────────────────────────────────────────────────────────────────────────────┘
import yank.constants as _c
# ┌────────────────────────────────────────────────────────────────────────────────────┐
# │ INTERFACE DATABASE MIXIN │
# └────────────────────────────────────────────────────────────────────────────────────┘
class InterfaceDatabaseMixin:
""" Interface Database Mixin """
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ CONSTANTS │
# └────────────────────────────────────────────────────────────────────────────────┘
# Type Map
TYPE_MAP = {
str: String,
int: Integer,
float: Float,
bool: Boolean,
datetime: DateTime,
}
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ CLASS ATTRIBUTES │
# └────────────────────────────────────────────────────────────────────────────────┘
# Initialize database session
db_session = None
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ NEW │
# └────────────────────────────────────────────────────────────────────────────────┘
def new(self, **kwargs):
""" A creates a new Item using the SQLAlchemy ORM Item class """
# Get rid of all kwargs not in field map
kwargs = {k: v for k, v in kwargs.items() if k in self.field_map}
# Cast the item fields spplied as kawrgs and return an initialized Item object
return self.Item(**self.cast_fields(kwargs))
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ GET │
# └────────────────────────────────────────────────────────────────────────────────┘
def get(self, queryset=None, **kwargs):
""" Gets an item from the database based in the supplied kwargs """
# Get queryset
queryset = queryset or self.db_session.query(self.Item)
# Return filtered queryset
return queryset.filter_by(**kwargs).one()
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ COUNT │
# └────────────────────────────────────────────────────────────────────────────────┘
def count(self):
""" Returns a count of items in the database """
# Return count
return self.db_session.query(func.count(self.Item.id)).scalar()
"""
For more info on counting with SQL Alchemy:
https://stackoverflow.com/questions/10822635/get-the-number-of-rows-in-table-
using-sqlalchemy
https://stackoverflow.com/questions/14754994/why-is-sqlalchemy-count-much-slower
-than-the-raw-query
"""
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ EXISTS │
# └────────────────────────────────────────────────────────────────────────────────┘
def exists(self, **kwargs):
"""
Returns a boolean of whether an item by the filter kwargs exists in the database
"""
# Get Item
Item = self.Item
# Convert field names to field objects
kwargs = {getattr(Item, field, None): value for field, value in kwargs.items()}
# Remove null fields
kwargs = {k: v for k, v in kwargs.items() if k}
# Return boolean of whether or not the object exists
return self.db_session.query(
exists().where(*[k == v for k, v in kwargs.items()])
).scalar()
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ ALL │
# └────────────────────────────────────────────────────────────────────────────────┘
def all(self):
""" Returns a queryset of all items in the database """
# Return a queryset of all items
return self.db_session.query(self.Item).all()
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ FILTER │
# └────────────────────────────────────────────────────────────────────────────────┘
def filter(self, queryset=None, display_map=None, tuples=None, **kwargs):
"""
Returns a filtered queryset of items in the database by the provided kwargs
"""
# ┌────────────────────────────────────────────────────────────────────────────┐
# │ TUPLES │
# └────────────────────────────────────────────────────────────────────────────┘
# NOTE: A list of tuples can be used instead of kwargs for more complex logic
# e.g. author__contains=a && author__contains=b
# Using kwargs, there can only be one author__contains argument as it is a dict
# Check if tuples
if tuples:
# Iterate over tuples
for field, value in tuples:
# Get queryset
queryset = self.filter(
queryset=queryset, display_map=display_map, **{field: value}
)
# Return queryset
return queryset
# ┌────────────────────────────────────────────────────────────────────────────┐
# │ KWARGS │
# └────────────────────────────────────────────────────────────────────────────┘
# Get Item
Item = self.Item
# Get field map
field_map = self.field_map
# Initialize display map
display_map = (
{k.lower(): v for k, v in display_map.items()} if display_map else {}
)
# Get queryset
queryset = queryset or self.db_session.query(Item)
# Initialize field cache
field_cache = {}
# ┌────────────────────────────────────────────────────────────────────────────┐
# │ ITERATE OVER KWARGS │
# └────────────────────────────────────────────────────────────────────────────┘
# Iterate over kwargs
for field, value in kwargs.items():
# Initialize should negate
should_negate = False
# Check if filed starts with tilde
if field.startswith("~"):
# Set should negate to True
should_negate = True
# Replace tilde
field = field.replace("~", "", 1).strip()
# Split field by modifier
field_split = field.split("__")
# Separate field from modifier
field, modifier = (
field_split if len(field_split) == 2 else (field_split[0], None)
)
# Set modifier
modifier = modifier.lower() if modifier else ""
# Check if field not in field map
if field not in field_map:
# Get field as display
field = display_map.get(field.lower(), field)
# Continue if field not in field map
if field not in field_map:
continue
# Get field cast
field_cast = field_map[field][_c.CAST]
# Define field is string boolean
field_is_str = field_cast is str
# Add field object to field cache
field_cache[field] = field_cache.get(field, getattr(Item, field))
# Get field object
field_obj = field_cache[field]
# ┌────────────────────────────────────────────────────────────────────────┐
# │ CAST VALUE │
# └────────────────────────────────────────────────────────────────────────┘
# Check if modifier is not a multiple value operator
if modifier not in (_c.IN, _c.IIN):
# Cast value
value = self.cast_field(field, value)
# ┌────────────────────────────────────────────────────────────────────────┐
# │ SUBSTRING │
# └────────────────────────────────────────────────────────────────────────┘
# Handle case of substring
if (
modifier
in (
_c.CONTAINS,
_c.ICONTAINS,
_c.STARTSWITH,
_c.ISTARTSWITH,
_c.ENDSWITH,
_c.IENDSWITH,
)
and field_is_str
):
# ┌────────────────────────────────────────────────────────────────────┐
# │ ARGUMENT STRING │
# └────────────────────────────────────────────────────────────────────┘
# Handle case of contains
if modifier in (_c.CONTAINS, _c.ICONTAINS):
# Wrap argument string in % signs
arg_string = f"%{value}%"
# Otherwise handle case of starts with
elif modifier in (_c.STARTSWITH, _c.ISTARTSWITH):
# Add % sign to end of argument string
arg_string = f"{value}%"
# Otherwise handle case of ends with
elif modifier in (_c.ENDSWITH, _c.IENDSWITH):
# Add % sign to start of argument string
arg_string = f"%{value}"
# ┌────────────────────────────────────────────────────────────────────┐
# │ QUERY │
# └────────────────────────────────────────────────────────────────────┘
# Handle case of case-sensitive
if modifier in (_c.CONTAINS, _c.STARTSWITH, _c.ENDSWITH):
# Set query using like
query = field_obj.like(arg_string)
# Otherwise handle case of case-insensitive
elif modifier in (_c.ICONTAINS, _c.ISTARTSWITH, _c.IENDSWITH):
# Set query using ilike
query = field_obj.ilike(arg_string)
# ┌────────────────────────────────────────────────────────────────────────┐
# │ REGEX │
# └────────────────────────────────────────────────────────────────────────┘
# Otherwise handle case of regex
elif modifier == _c.REGEX and field_is_str:
# Define query
query = field_obj.op("regexp")(value)
# ┌────────────────────────────────────────────────────────────────────────┐
# │ IN │
# └────────────────────────────────────────────────────────────────────────┘
# Otherwise handle case of in
elif modifier in (_c.IN, _c.IIN):
# Convert and cast to a list of values
values = [self.cast_field(field, i.strip()) for i in value.split(",")]
# Handle case of iin
if modifier == _c.IIN and field_is_str:
# Define query
query = func.lower(field_obj).in_([i.lower() for i in values])
# Otherwise handle normal case
else:
# Define query
query = field_obj.in_(values)
# ┌────────────────────────────────────────────────────────────────────────┐
# │ EXACT │
# └────────────────────────────────────────────────────────────────────────┘
# Otherwise handle exact case
else:
# Check if modifier is iexact
if modifier == _c.IEXACT and field_is_str:
# Define query
query = func.lower(field_obj) == value.lower()
# Otherwise handle standard exact case
else:
# Define query
query = field_obj == value
# ┌────────────────────────────────────────────────────────────────────────┐
# │ NEGATE │
# └────────────────────────────────────────────────────────────────────────┘
# Check if should negate
if should_negate:
# Negagte query
query = ~query
# ┌────────────────────────────────────────────────────────────────────────┐
# │ FILTER │
# └────────────────────────────────────────────────────────────────────────┘
# Filter with query
queryset = queryset.filter(query)
# Return filtered queryset
return queryset
# ┌────────────────────────────────────────────────────────────────────────────────┐
# │ SORT │
# └────────────────────────────────────────────────────────────────────────────────┘
def sort(self, *fields, queryset=None, display_map=None):
""" Returns a queryset of items sorted by the provided fields """
# Get Item
Item = self.Item
# Initialize display map
display_map = (
{k.lower(): v for k, v in display_map.items()} if display_map else {}
)
# Initialize new fields list
_fields = []
# Iterate over fields
for field in fields:
# Initialize ascending boolean
ascending = True
# Check if field begins with negative sign
if field.startswith("-"):
# Set ascending to False
ascending = False
# Remove negative sign from string
field = field[1:]
# Get SQL Alchemy field object by field name or display
field = getattr(
Item,
field,
getattr(Item, display_map[field.lower()], None)
if field in display_map
else None,
)
# Continue if field is None
if field is None:
continue
# Apply sort direction to field object
field = field.asc() if ascending is True else field.desc()
# Add field to fields list
_fields.append(field)
# Get queryset
queryset = queryset or self.db_session.query(Item)
# Return sorted queryset
return queryset.order_by(*_fields)
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] |
exe041 - classificando Atletas.py | carlosbandelli/Exercicios_em_Python | 0 | 194174 | from datetime import date
atual = date.today().year
nascimento = int(input('Ano de nascimento: '))
idade = atual - nascimento
print(f'O atleta tem {idade} anos.')
if idade <= 9:
print('Classificação: MIRIM')
elif idade <= 14:
print ('Classificação: INFANTIL')
elif idade <= 19:
print('Classificação: JUNIOR')
elif idade <=25:
print('Classificação: SENIOR')
else:
print('Classisficação: MASTER')
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chrome/common/extensions/docs/server2/app_yaml_helper_test.py | iplo/Chain | 231 | 46368 | #!/usr/bin/env python
# Copyright 2013 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import unittest
from app_yaml_helper import AppYamlHelper
from extensions_paths import SERVER2
from host_file_system_provider import HostFileSystemProvider
from mock_file_system import MockFileSystem
from object_store_creator import ObjectStoreCreator
from test_file_system import MoveTo, TestFileSystem
from test_util import DisableLogging
_ExtractVersion, _IsGreater, _GenerateAppYaml = (
AppYamlHelper.ExtractVersion,
AppYamlHelper.IsGreater,
AppYamlHelper.GenerateAppYaml)
class AppYamlHelperTest(unittest.TestCase):
def testExtractVersion(self):
def run_test(version):
self.assertEqual(version, _ExtractVersion(_GenerateAppYaml(version)))
run_test('0')
run_test('0-0')
run_test('0-0-0')
run_test('1')
run_test('1-0')
run_test('1-0-0')
run_test('1-0-1')
run_test('1-1-0')
run_test('1-1-1')
run_test('2-0-9')
run_test('2-0-12')
run_test('2-1')
run_test('2-1-0')
run_test('2-11-0')
run_test('3-1-0')
run_test('3-1-3')
run_test('3-12-0')
def testIsGreater(self):
def assert_is_greater(lhs, rhs):
self.assertTrue(_IsGreater(lhs, rhs), '%s is not > %s' % (lhs, rhs))
self.assertFalse(_IsGreater(rhs, lhs),
'%s should not be > %s' % (rhs, lhs))
assert_is_greater('0-0', '0')
assert_is_greater('0-0-0', '0')
assert_is_greater('0-0-0', '0-0')
assert_is_greater('1', '0')
assert_is_greater('1', '0-0')
assert_is_greater('1', '0-0-0')
assert_is_greater('1-0', '0-0')
assert_is_greater('1-0-0-0', '0-0-0')
assert_is_greater('2-0-12', '2-0-9')
assert_is_greater('2-0-12', '2-0-9-0')
assert_is_greater('2-0-12-0', '2-0-9')
assert_is_greater('2-0-12-0', '2-0-9-0')
assert_is_greater('2-1', '2-0-9')
assert_is_greater('2-1', '2-0-12')
assert_is_greater('2-1-0', '2-0-9')
assert_is_greater('2-1-0', '2-0-12')
assert_is_greater('3-1-0', '2-1')
assert_is_greater('3-1-0', '2-1-0')
assert_is_greater('3-1-0', '2-11-0')
assert_is_greater('3-1-3', '3-1-0')
assert_is_greater('3-12-0', '3-1-0')
assert_is_greater('3-12-0', '3-1-3')
assert_is_greater('3-12-0', '3-1-3-0')
@DisableLogging('warning')
def testInstanceMethods(self):
test_data = {
'app.yaml': _GenerateAppYaml('1-0'),
'app_yaml_helper.py': 'Copyright notice etc'
}
updates = []
# Pass a specific file system at head to the HostFileSystemProvider so that
# we know it's always going to be backed by a MockFileSystem. The Provider
# may decide to wrap it in caching etc.
file_system_at_head = MockFileSystem(
TestFileSystem(test_data, relative_to=SERVER2))
def apply_update(update):
update = MoveTo(SERVER2, update)
file_system_at_head.Update(update)
updates.append(update)
def host_file_system_constructor(branch, revision=None):
self.assertEqual('trunk', branch)
self.assertTrue(revision is not None)
return MockFileSystem.Create(
TestFileSystem(test_data, relative_to=SERVER2), updates[:revision])
object_store_creator = ObjectStoreCreator.ForTest()
host_file_system_provider = HostFileSystemProvider(
object_store_creator,
default_trunk_instance=file_system_at_head,
constructor_for_test=host_file_system_constructor)
helper = AppYamlHelper(object_store_creator, host_file_system_provider)
def assert_is_up_to_date(version):
self.assertTrue(helper.IsUpToDate(version),
'%s is not up to date' % version)
self.assertRaises(ValueError,
helper.GetFirstRevisionGreaterThan, version)
self.assertEqual(0, helper.GetFirstRevisionGreaterThan('0-5-0'))
assert_is_up_to_date('1-0-0')
assert_is_up_to_date('1-5-0')
# Revision 1.
apply_update({
'app.yaml': _GenerateAppYaml('1-5-0')
})
self.assertEqual(0, helper.GetFirstRevisionGreaterThan('0-5-0'))
self.assertEqual(1, helper.GetFirstRevisionGreaterThan('1-0-0'))
assert_is_up_to_date('1-5-0')
assert_is_up_to_date('2-5-0')
# Revision 2.
apply_update({
'app_yaml_helper.py': 'fixed a bug'
})
self.assertEqual(0, helper.GetFirstRevisionGreaterThan('0-5-0'))
self.assertEqual(1, helper.GetFirstRevisionGreaterThan('1-0-0'))
assert_is_up_to_date('1-5-0')
assert_is_up_to_date('2-5-0')
# Revision 3.
apply_update({
'app.yaml': _GenerateAppYaml('1-6-0')
})
self.assertEqual(0, helper.GetFirstRevisionGreaterThan('0-5-0'))
self.assertEqual(1, helper.GetFirstRevisionGreaterThan('1-0-0'))
self.assertEqual(3, helper.GetFirstRevisionGreaterThan('1-5-0'))
assert_is_up_to_date('2-5-0')
# Revision 4.
apply_update({
'app.yaml': _GenerateAppYaml('1-8-0')
})
# Revision 5.
apply_update({
'app.yaml': _GenerateAppYaml('2-0-0')
})
# Revision 6.
apply_update({
'app.yaml': _GenerateAppYaml('2-2-0')
})
# Revision 7.
apply_update({
'app.yaml': _GenerateAppYaml('2-4-0')
})
# Revision 8.
apply_update({
'app.yaml': _GenerateAppYaml('2-6-0')
})
self.assertEqual(0, helper.GetFirstRevisionGreaterThan('0-5-0'))
self.assertEqual(1, helper.GetFirstRevisionGreaterThan('1-0-0'))
self.assertEqual(3, helper.GetFirstRevisionGreaterThan('1-5-0'))
self.assertEqual(5, helper.GetFirstRevisionGreaterThan('1-8-0'))
self.assertEqual(6, helper.GetFirstRevisionGreaterThan('2-0-0'))
self.assertEqual(6, helper.GetFirstRevisionGreaterThan('2-1-0'))
self.assertEqual(7, helper.GetFirstRevisionGreaterThan('2-2-0'))
self.assertEqual(7, helper.GetFirstRevisionGreaterThan('2-3-0'))
self.assertEqual(8, helper.GetFirstRevisionGreaterThan('2-4-0'))
self.assertEqual(8, helper.GetFirstRevisionGreaterThan('2-5-0'))
assert_is_up_to_date('2-6-0')
assert_is_up_to_date('2-7-0')
if __name__ == '__main__':
unittest.main()
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] |
moving_average_example.py | channolanp/QtScript | 0 | 190399 | import sys
from QtScript import QtScript
from PyQt5.QtWidgets import *
from PyQt5.QtCore import Qt
import moving_average_script
if __name__ == '__main__':
#First start off by starting the QApplication for PyQt5
app = QApplication(sys.argv)
'''
Use the QtScript class as the application window
There's a simple file selecting dialog widget that is added as the first
widget when with_file is True
'''
window = QtScript(with_file = True)
#Set the script that will trigger when "Run Script" is clicked.
#Note that this must have 1 arugment, as your config dict or throw away var
window.SetScript(moving_average_script.main)
#Here we build a bunch of UI elements and limit them however we like
filter_window = QSpinBox()
filter_window.setSingleStep(5)
filter_window.setMinimum(0)
filter_window.setMaximum(1000)
filter_window.setValue(20)
with_debounce = QCheckBox()
debounce_trigger = QDoubleSpinBox()
debounce_trigger.setSingleStep(0.5)
debounce_trigger.setMinimum(0)
debounce_trigger.setMaximum(100)
debounce_trigger.setValue(1)
debounce_window = QSpinBox()
debounce_window.setSingleStep(5)
debounce_window.setMinimum(0)
debounce_window.setMaximum(500)
debounce_window.setValue(50)
'''
Here we start adding the above widgets to the QtScript widget
Note that the first argument is the string name to be used for everything.
This name is used for all the JSON stuff, as well as the config dict that
is passed to your script
'''
window.AddWidget('Filter Window', filter_window)
window.AddWidget('Debounce Signal', with_debounce)
window.AddWidget('Debounce Value', debounce_trigger)
window.AddWidget('Debounce Window', debounce_window)
'''
Show the widget, and lock us into the event loop
'''
window.show()
app.exec_()
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infrastructure/app.py | akozd/web-service | 0 | 1606862 | <gh_stars>0
#!/usr/bin/env python3
from aws_cdk import core
from infrastructure.infrastructure_stack import InfrastructureStack
app = core.App()
InfrastructureStack(app, 'InfrastructureStack')
app.synth()
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geojson_rewind/rewind.py | chris48s/geojson-rewind | 15 | 34126 | <gh_stars>10-100
import argparse
import copy
import json
import logging
import math
import sys
RADIUS = 6378137
def rewind(geojson, rfc7946=True):
gj = copy.deepcopy(geojson)
_check_crs(geojson)
if isinstance(gj, str):
return json.dumps(_rewind(json.loads(gj), rfc7946))
else:
return _rewind(gj, rfc7946)
def _check_crs(geojson):
if (
"crs" in geojson
and "properties" in geojson["crs"]
and "name" in geojson["crs"]["properties"]
and geojson["crs"]["properties"]["name"] != "urn:ogc:def:crs:OGC:1.3:CRS84"
):
logging.warning(
"Co-ordinates in the input data are assumed to be WGS84 with "
"(lon, lat) ordering, as per RFC 7946. Input with co-ordinates "
"using any other CRS may lead to unexpected results."
)
def _rewind(gj, rfc7946):
if gj["type"] == "FeatureCollection":
gj["features"] = list(map(lambda obj: _rewind(obj, rfc7946), gj["features"]))
return gj
if gj["type"] == "GeometryCollection":
gj["geometries"] = list(
map(lambda obj: _rewind(obj, rfc7946), gj["geometries"])
)
return gj
if gj["type"] == "Feature":
gj["geometry"] = _rewind(gj["geometry"], rfc7946)
if gj["type"] in ["Polygon", "MultiPolygon"]:
return correct(gj, rfc7946)
return gj
def correct(feature, rfc7946):
if feature["type"] == "Polygon":
feature["coordinates"] = correctRings(feature["coordinates"], rfc7946)
if feature["type"] == "MultiPolygon":
feature["coordinates"] = list(
map(lambda obj: correctRings(obj, rfc7946), feature["coordinates"])
)
return feature
def correctRings(rings, rfc7946):
# change from rfc7946: True/False to clockwise: True/False here
# RFC 7946 ordering determines how we deal with an entire polygon
# but at this point we are switching to deal with individual rings
# (which in isolation are just clockwise or anti-clockwise)
clockwise = not (bool(rfc7946))
rings[0] = wind(rings[0], clockwise)
for i in range(1, len(rings)):
rings[i] = wind(rings[i], not (clockwise))
return rings
def wind(ring, clockwise):
if is_clockwise(ring) == clockwise:
return ring
return ring[::-1]
def is_clockwise(ring):
return ringArea(ring) >= 0
def ringArea(coords):
area = 0
coordsLength = len(coords)
if coordsLength > 2:
for i in range(0, coordsLength):
if i == coordsLength - 2:
lowerIndex = coordsLength - 2
middleIndex = coordsLength - 1
upperIndex = 0
elif i == coordsLength - 1:
lowerIndex = coordsLength - 1
middleIndex = 0
upperIndex = 1
else:
lowerIndex = i
middleIndex = i + 1
upperIndex = i + 2
p1 = coords[lowerIndex]
p2 = coords[middleIndex]
p3 = coords[upperIndex]
area = area + (rad(p3[0]) - rad(p1[0])) * math.sin(rad(p2[1]))
area = area * RADIUS * RADIUS / 2
return area
def rad(coord):
return coord * math.pi / 180
def main():
parser = argparse.ArgumentParser(
description="Enforce RFC 7946 ring winding order on a GeoJSON file"
)
parser.add_argument(
"file",
nargs="?",
help="Input file, if empty stdin is used",
type=argparse.FileType("r"),
default=sys.stdin,
)
args = parser.parse_args()
if args.file.isatty():
parser.print_help()
return 0
sys.stdout.write(rewind(args.file.read()))
return 0
if __name__ == "__main__":
sys.exit(main())
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python/django/app/views.py | mattiapenati/web-frameworks | 5,710 | 87665 | from django.http import HttpResponse
from django.views.decorators.csrf import csrf_exempt
def index(request):
return HttpResponse(status=200)
def get_user(request, id):
return HttpResponse(id)
@csrf_exempt
def create_user(request):
return HttpResponse(status=200)
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tests/btjanaka_test.py | btjanaka/btjanaka-pypi | 1 | 107647 | <gh_stars>1-10
"""Tests for btjanaka."""
import btjanaka
def test_calls():
"""Try calling every method."""
for name, method in btjanaka.__dict__.items():
if not name.startswith("_") and callable(method):
method()
def test_counting():
"""Test counting - copy this to README."""
nums = [
len(btjanaka.name()) - len(btjanaka.yell()), # 0
len(btjanaka.name()) // len(btjanaka.yell()), # 1
btjanaka.firstname().count("o") + len(btjanaka.name()[0]), # 2
btjanaka.lastname().count("a"), # 3
btjanaka.website().count("/") + btjanaka.website().count("n"), # 4
len(btjanaka.firstname()), # 5
btjanaka.name().count("n") * btjanaka.email().count("n"), # 6
len(btjanaka.lastname()), # 7
btjanaka.canadian().index("y")**len(btjanaka.chinese()), # 8
len(btjanaka.british()), # 9
len(btjanaka.email().replace(".", "").split("@")[1]), # 10
]
for i, n in enumerate(nums):
assert i == n
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Udemy_PythonBootcamp/Sec15_WebScraping.py | gonzalosc2/LearningPython | 0 | 11858 | ####################################
# author: <NAME>
# course: 2020 Complete Python Bootcamps: From Zero to Hero in Python
# purpose: lecture notes
# description: Section 15 - Web Scraping
# other: N/A
####################################
# RULES
# 1. always try to get permission before scraping, otherwise I might be blocked
# 2. check the laws of whatever country we are operating in (for legal issues)
# LIMITATIONS
# each website is unique -> so for each website there must exist a Python script
# an update to a website might brake my script
import requests
import bs4
# Grabbing a title
result = requests.get("http://example.com")
type(result)
result.text
# bs with lxml tranforms the previous raw html into the following
soup = bs4.BeautifulSoup(result.text,'lxml')
soup
# returns the tag we specified as a list (i.e., there might be more than one)
soup.select('title')
soup.select('title')[0].getText()
soup.select('p')
site_paragraphs = soup.select('p')
type(site_paragraphs[0]) # not a string, instead is a specialized bs object,
# which is why we can do something like call .getText()
# Grabbing a class (from CSS) using soup.select()
# 'div' : all elements with 'div' tag
# '#some_id' : elements containing id='some_id'
# '.some_class' : elements containing class='some_class'
# 'div span' : any element named span within a div element
# 'div > span' : any element named span directly within a div element, with
# nothing in between
res = requests.get("https://en.wikipedia.org/wiki/Jonas_Salk")
soup = bs4.BeautifulSoup(res.text,'lxml')
soup.select('.toctext')[0].text
soup.select('.toctext')[0].getText()
for item in soup.select('.toctext'):
print(item.text)
# Grabbing an image
#soup.select('img') # can return more than what is needeed (it will depend on
# the website)
soup.select('.thumbimage')
jonas_salk = soup.select('.thumbimage')[0]
jonas_salk['src'] # we can treat it as a dictionary
image_link = requests.get('http://upload.wikimedia.org/wikipedia/commons/thumb/3/3c/Roosevelt_OConnor.jpg/220px-Roosevelt_OConnor.jpg')
#image_link.content # raw content of the image which is a binary file
#make sure to use the same format that the image has
f = open('my_image_image.jpg','wb') # wb means write binary
f.write(image_link.content)
f.close()
# Multiple elements across multiple pages
# GOAL: get title of every book with a 2 star rating
#Check that this also work with page 1
#http://books.toscrape.com/catalogue/page-2.html
base_url = 'http://books.toscrape.com/catalogue/page-{}.html'
req = requests.get(base_url.format(1))
soup = bs4.BeautifulSoup(req.text,'lxml')
products = soup.select(".product_pod") # always check the length, in this case should be 20
example = products[0]
# one way (not useful everytime)
'star-rating Two' in str(example)
# another way (checking for the presence of a class)
example.select('.star-rating.Three') # if there is a space in a class we should add a dot
example.select('.star-rating.Two') # nothing
example.select('a')[1]['title']
two_star_titles = []
for n in range(1,51):
scrape_url = base_url.format(n)
req = requests.get(base_url.format(1))
soup = bs4.BeautifulSoup(req.text,'lxml')
books = soup.select(".product_pod")
for book in books:
if len(book.select('.star-rating.Two')) != 0:
two_star_titles.append(book.select('a')[1]['title'])
two_star_titles
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01/01_g_swap_numbers.py | srinijadharani/DataStructuresLab | 0 | 1617682 | <reponame>srinijadharani/DataStructuresLab
# 1g. Program to swap two numbers
num1 = int(input("Enter the first number: "))
num2 = int(input("Enter the second number: "))
print("The numbers before swapping are - num1: {} and num2: {}." .format(num1, num2))
# logic for swapping two numbers
num1, num2 = num2, num1
print("The numbers after swapping are - num1: {} and num2: {}." .format(num1, num2)) | [
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seqtag/model.py | fedelopez77/seqtag | 1 | 1603458 |
from torch import nn
from seqtag.embedding_model import get_embedding_model
class SequenceTaggingModel(nn.Module):
def __init__(self, args):
super().__init__()
self.embedding_model = get_embedding_model(args.language_model)
embed_size = self.embedding_model.config.hidden_size
self.dropout = nn.Dropout(args.dropout)
self.linear = nn.Linear(embed_size, args.num_labels)
def forward(self, tokens, masks):
"""
:param tokens: tensor of b, seq_len
:param masks: tensor of b, seq_len
:return: logits: b, seq_len, num_labels
"""
embeddings = self.embedding_model(tokens, attention_mask=masks)[0] # b, seq_len, emb_size
logits = self.linear(self.dropout(embeddings)) # b, seq_len, num_labels
return logits
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tests/logic/test_instruments.py | nilsholle/sampledb | 5 | 1616913 | <reponame>nilsholle/sampledb<gh_stars>1-10
# coding: utf-8
"""
"""
import pytest
import sampledb
from sampledb.models import User, UserType
from sampledb.logic import instruments, errors
def test_create_instrument():
assert len(instruments.get_instruments()) == 0
instrument = instruments.create_instrument()
assert len(instruments.get_instruments()) == 1
assert instrument == instruments.get_instrument(instrument_id=instrument.id)
assert len(instrument.responsible_users) == 0
def test_update_instrument():
instrument = instruments.create_instrument(
description_is_markdown=False,
users_can_create_log_entries=False,
users_can_view_log_entries=False,
notes_is_markdown=False,
create_log_entry_default=False,
is_hidden=False,
short_description_is_markdown=False
)
instruments.update_instrument(
instrument_id=instrument.id,
description_is_markdown=False,
users_can_create_log_entries=True,
users_can_view_log_entries=False,
notes_is_markdown=False,
create_log_entry_default=False,
is_hidden=True,
short_description_is_markdown=False
)
instrument = instruments.get_instrument(instrument_id=instrument.id)
assert instrument.description_is_markdown is False
assert instrument.users_can_create_log_entries is True
assert instrument.users_can_view_log_entries is False
assert instrument.notes_is_markdown is False
assert instrument.create_log_entry_default is False
assert instrument.is_hidden is True
assert instrument.short_description_is_markdown is False
assert len(instrument.responsible_users) == 0
def test_instrument_responsible_users():
user = User(name="Testuser", email="<EMAIL>", type=UserType.PERSON)
sampledb.db.session.add(user)
sampledb.db.session.commit()
instrument = instruments.create_instrument()
assert len(instrument.responsible_users) == 0
instruments.add_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id)
assert len(instrument.responsible_users) == 1
with pytest.raises(errors.UserAlreadyResponsibleForInstrumentError):
instruments.add_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id)
instruments.remove_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id)
assert len(instrument.responsible_users) == 0
with pytest.raises(errors.UserNotResponsibleForInstrumentError):
instruments.remove_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id)
with pytest.raises(errors.InstrumentDoesNotExistError):
instruments.add_instrument_responsible_user(instrument_id=instrument.id+1, user_id=user.id)
with pytest.raises(errors.UserDoesNotExistError):
instruments.add_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id+1)
with pytest.raises(errors.InstrumentDoesNotExistError):
instruments.remove_instrument_responsible_user(instrument_id=instrument.id+1, user_id=user.id)
with pytest.raises(errors.UserDoesNotExistError):
instruments.remove_instrument_responsible_user(instrument_id=instrument.id, user_id=user.id+1)
def test_get_missing_instrument():
instrument = instruments.create_instrument()
with pytest.raises(errors.InstrumentDoesNotExistError):
instruments.get_instrument(instrument_id=instrument.id+1)
def test_update_missing_instrument():
instrument = instruments.create_instrument()
with pytest.raises(errors.InstrumentDoesNotExistError):
instruments.update_instrument(
instrument_id=instrument.id+1
)
def test_set_instrument_responsible_users():
user1 = User(name="Testuser", email="<EMAIL>", type=UserType.PERSON)
user2 = User(name="Testuser", email="<EMAIL>", type=UserType.PERSON)
sampledb.db.session.add(user1)
sampledb.db.session.add(user2)
sampledb.db.session.commit()
instrument = instruments.create_instrument()
assert len(instrument.responsible_users) == 0
instruments.set_instrument_responsible_users(instrument.id, [user1.id])
assert len(instrument.responsible_users) == 1
assert user1 in instrument.responsible_users
instruments.set_instrument_responsible_users(instrument.id, [user2.id])
assert len(instrument.responsible_users) == 1
assert user2 in instrument.responsible_users
instruments.set_instrument_responsible_users(instrument.id, [user1.id, user2.id])
assert len(instrument.responsible_users) == 2
assert user1 in instrument.responsible_users
assert user2 in instrument.responsible_users
instruments.set_instrument_responsible_users(instrument.id, [])
assert len(instrument.responsible_users) == 0
| [
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appendix/introduction.to.programming.with.turtle/5-5-1.fill.curve.py | royqh1979/programming_with_python | 5 | 151654 | <reponame>royqh1979/programming_with_python
from easygraphics.turtle import *
def Fill(size, level):
if level == 0:
fd(size)
return
Fill(size / 3, level - 1)
lt(90)
Fill(size / 3, level - 1)
for i in range(3):
rt(90)
Fill(size / 3, level - 1)
for i in range(3):
lt(90)
Fill(size / 3, level - 1)
rt(90)
Fill(size / 3, level - 1)
def main():
create_world(800, 600)
set_speed(500)
setxy(0, -200)
Fill(400, 4);
pause()
close_world()
easy_run(main) | [
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InterviewBit/Trees/min_depth_binary_tree.py | codervikash/online-courses | 0 | 129075 | <filename>InterviewBit/Trees/min_depth_binary_tree.py<gh_stars>0
"""
Given a binary tree, find its minimum depth.
The minimum depth is the number of nodes along the shortest path from the root node down to the nearest leaf node.
NOTE : The path has to end on a leaf node.
Example :
1
/
2
min depth = 2.
"""
# Definition for a binary tree node
# class TreeNode:
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
import sys
class Solution:
# @param A : root node of tree
# @return an integer
def minDepth(self, A):
if A is None:
return 0
if A.left is None and A.right is None:
return 1
if A.left is None:
return self.minDepth(A.right) + 1
if A.right is None:
return self.minDepth(A.left) + 1
ldepth = self.minDepth(A.left)
rdepth = self.minDepth(A.right)
return min(ldepth, rdepth) + 1
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test-suite/generated-src/python/dh__set_interface_Conflict.py | ubook-editora/finn | 3 | 193405 | # AUTOGENERATED FILE - DO NOT MODIFY!
# This file generated by Djinni from test.djinni
from djinni.support import MultiSet # default imported in all files
from djinni.exception import CPyException # default imported in all files
from djinni.pycffi_marshal import CPyObject, CPyObjectProxy
from Conflict import ConflictHelper
from PyCFFIlib_cffi import ffi, lib
from djinni import exception # this forces run of __init__.py which gives cpp option to call back into py to create exception
class SetInterfaceConflictHelper:
c_data_set = MultiSet()
@staticmethod
def check_c_data_set_empty():
assert len(SetInterfaceConflictHelper.c_data_set) == 0
Conflict.check_c_data_set_empty()
@ffi.callback("size_t(struct DjinniObjectHandle *)")
def __get_size(cself):
return len(CPyObjectProxy.toPyObj(None, cself))
@ffi.callback("struct DjinniObjectHandle *()")
def __python_create():
c_ptr = ffi.new_handle(SetInterfaceConflictProxy(set()))
SetInterfaceConflictHelper.c_data_set.add(c_ptr)
return ffi.cast("struct DjinniObjectHandle *", c_ptr)
@ffi.callback("void(struct DjinniObjectHandle *, struct DjinniWrapperConflict *)")
def __python_add(cself, el):
CPyObjectProxy.toPyObj(None, cself).add(ConflictHelper.toPy(el))
@ffi.callback("void(struct DjinniObjectHandle * )")
def __delete(c_ptr):
assert c_ptr in SetInterfaceConflictHelper.c_data_set
SetInterfaceConflictHelper.c_data_set.remove(c_ptr)
@ffi.callback("struct DjinniWrapperConflict *(struct DjinniObjectHandle *)")
def __python_next(cself):
try:
_ret = ConflictHelper.fromPy(next(CPyObjectProxy.toPyIter(cself)))
assert _ret != ffi.NULL
return _ret
except Exception as _djinni_py_e:
CPyException.setExceptionFromPy(_djinni_py_e)
return ffi.NULL
@staticmethod
def _add_callbacks():
lib.set_interface_Conflict_add_callback___delete(SetInterfaceConflictHelper.__delete)
lib.set_interface_Conflict_add_callback__get_size(SetInterfaceConflictHelper.__get_size)
lib.set_interface_Conflict_add_callback__python_create(SetInterfaceConflictHelper.__python_create)
lib.set_interface_Conflict_add_callback__python_add(SetInterfaceConflictHelper.__python_add)
lib.set_interface_Conflict_add_callback__python_next(SetInterfaceConflictHelper.__python_next)
SetInterfaceConflictHelper._add_callbacks()
class SetInterfaceConflictProxy:
def iter(d):
for k in d:
yield k
def __init__(self, py_obj):
self._py_obj = py_obj
if py_obj is not None:
self._py_iter = iter(py_obj)
else:
self._py_iter = None
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] |
scripts/deposit_test.py | shiqinfeng1/alphahomora-bsc | 11 | 120778 | from brownie import accounts, interface, Contract
from brownie import (Bank, SimpleBankConfig, SimplePriceOracle, PancakeswapPool1Goblin,
StrategyAllBNBOnly, StrategyLiquidate, StrategyWithdrawMinimizeTrading, StrategyAddTwoSidesOptimal, PancakeswapGoblinConfig, TripleSlopeModel, ConfigurableInterestBankConfig, ProxyAdminImpl, TransparentUpgradeableProxyImpl)
from .utils import *
import eth_abi
def main():
admin = accounts[0]
alice = accounts[1]
triple_slope_model = TripleSlopeModel.deploy({'from': admin})
# min debt 0.2 BNB at 10 gwei gas price (killBps 5% -> at least 0.01BNB bonus)
# reserve pool bps 1000 (10%)
# kill bps 500 (5%)
bank_config = ConfigurableInterestBankConfig.deploy(
2 * 10**17, 1000, 500, triple_slope_model, {'from': admin})
proxy_admin = ProxyAdminImpl.deploy({'from': admin})
bank_impl = Bank.deploy({'from': admin})
bank = TransparentUpgradeableProxyImpl.deploy(
bank_impl, proxy_admin, bank_impl.initialize.encode_input(bank_config), {'from': admin})
bank = interface.IAny(bank)
###################################################################
# deposit & withdraw
deposit_amt = 10**18
prevBNBBal = alice.balance()
prevIbBNBBal = bank.balanceOf(alice)
bank.deposit({'from': alice, 'value': deposit_amt})
curBNBBal = alice.balance()
curIbBNBBal = bank.balanceOf(alice)
print('∆ bnb alice', curBNBBal - prevBNBBal)
print('∆ ibBNB alice', curIbBNBBal - prevIbBNBBal)
assert curBNBBal - prevBNBBal == -(curIbBNBBal - prevIbBNBBal), 'first depositor should get 1:1'
assert curBNBBal - prevBNBBal == -deposit_amt
# withdraw 1/3
prevBNBBal = alice.balance()
prevIbBNBBal = bank.balanceOf(alice)
bank.withdraw(curIbBNBBal // 3, {'from': alice})
curBNBBal = alice.balance()
curIbBNBBal = bank.balanceOf(alice)
print('∆ bnb alice', curBNBBal - prevBNBBal)
print('∆ ibBNB alice', curIbBNBBal - prevIbBNBBal)
assert curBNBBal - prevBNBBal == -(curIbBNBBal - prevIbBNBBal), 'first depositor should get 1:1'
assert curBNBBal - prevBNBBal == deposit_amt // 3
# withdraw remaining
prevBNBBal = alice.balance()
prevIbBNBBal = bank.balanceOf(alice)
bank.withdraw(curIbBNBBal, {'from': alice})
curBNBBal = alice.balance()
curIbBNBBal = bank.balanceOf(alice)
print('∆ bnb alice', curBNBBal - prevBNBBal)
print('∆ ibBNB alice', curIbBNBBal - prevIbBNBBal)
assert curBNBBal - prevBNBBal == -(curIbBNBBal - prevIbBNBBal), 'first depositor should get 1:1'
assert curBNBBal - prevBNBBal == deposit_amt - deposit_amt // 3
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] |
test/test_topology_handler.py | atlanticwave-sdx/datamodel | 0 | 115119 | <filename>test/test_topology_handler.py<gh_stars>0
import unittest
import sdxdatamodel.parsing
from sdxdatamodel.parsing.topologyhandler import TopologyHandler
from sdxdatamodel.parsing.exceptions import DataModelException
TOPOLOGY_AMLIGHT = './test/data/amlight.json'
class TestTopologyHandler(unittest.TestCase):
def setUp(self):
self.handler = TopologyHandler(TOPOLOGY_AMLIGHT) # noqa: E501
self.handler.import_topology()
def tearDown(self):
pass
def testImportTopology(self):
try:
print("Test Topology")
print(self.handler.topology)
except DataModelException as e:
print(e)
return False
return True
def testImportTopologyNodes(self):
print("Test Nodes: at least one:")
nodes=self.handler.topology.nodes
if nodes==None or len(nodes)==0:
print("Nodes are empty")
return False
print(nodes[0])
return True
def testImportTopologyLinks(self):
print("Test Links: at least one")
links=self.handler.topology.links
if links==None or len(links)==0:
print("Links are empty")
return False
print(links[0])
return True
if __name__ == '__main__':
unittest.main() | [
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] |
setup.py | lucgiffon/propol | 0 | 179187 | <filename>setup.py
from setuptools import find_packages, setup
setup(
name='src',
packages=find_packages(),
version='0.1.0',
description='Try to make projection of political parties or people in avector space in order to enable visualisation.',
author='<NAME>',
license='MIT',
entry_points={
'console_scripts': [
'vizualize=src.visualization.visualize:run',
],
},
)
| [
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MergeSortedLinkLists/MergeKsortedlinkedlists00.py | tnkteja/notthisagain | 0 | 112387 | <gh_stars>0
from heapq import heappushpop
def solution(A): | [
1,
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mt/mvae/models/ffnn_vae.py | macio232/mvae | 53 | 84152 | # Copyright 2019 <NAME>.
#
# 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 typing import List
import torch
import torch.nn as nn
from torch import Tensor
from .vae import ModelVAE
from ...data import VaeDataset
from ..components import Component
class FeedForwardVAE(ModelVAE):
def __init__(self, h_dim: int, components: List[Component], dataset: VaeDataset,
scalar_parametrization: bool) -> None:
super().__init__(h_dim, components, dataset, scalar_parametrization)
self.in_dim = dataset.in_dim
# 1 hidden layer encoder
self.fc_e0 = nn.Linear(dataset.in_dim, h_dim)
# 1 hidden layer decoder
self.fc_d0 = nn.Linear(self.total_z_dim, h_dim)
self.fc_logits = nn.Linear(h_dim, dataset.in_dim)
def encode(self, x: Tensor) -> Tensor:
assert len(x.shape) == 2
bs, dim = x.shape
assert dim == self.in_dim
x = x.view(bs, self.in_dim)
x = torch.relu(self.fc_e0(x))
return x.view(bs, -1)
def decode(self, concat_z: Tensor) -> Tensor:
assert len(concat_z.shape) >= 2
bs = concat_z.size(-2)
x = torch.relu(self.fc_d0(concat_z))
x = self.fc_logits(x)
x = x.view(-1, bs, self.in_dim) # flatten
return x.squeeze(dim=0) # in case we're not doing LL estimation
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] |
sample-viewer-api/src/api/elisa_parser.py | cvisb/cvisb_data | 2 | 118224 | from pyparsing import (CaselessKeyword, Optional, Forward, Regex, operatorPrecedence, opAssoc, ParserElement)
from biothings.utils.common import is_str
import re
ParserElement.enablePackrat()
and_ = CaselessKeyword("AND")
or_ = CaselessKeyword("OR")
not_ = CaselessKeyword("NOT")
keyword = and_ | or_ | not_
expression = Forward()
valid_word = Regex(r'\[\[.*?\]\]').setName("word")
valid_word.setParseAction(
lambda t : t[0].replace('\\\\',chr(127)).replace('\\','').replace(chr(127),'\\')
)
term = Forward()
word_expr = valid_word
term << word_expr
expression << operatorPrecedence(term,
[
((not_ | '!').setParseAction(lambda:"NOT"), 1, opAssoc.RIGHT),
((and_ | '&&').setParseAction(lambda:"AND"), 2, opAssoc.LEFT),
(Optional(or_ | '||').setParseAction(lambda:"OR"), 2, opAssoc.LEFT),
])
def parseElisaString(elisa):
def buildSubQuery(l):
if isinstance(l, list) and len(l) == 1 and isinstance(l[0], list):
return buildSubQuery(l[0])
if is_str(l) or (isinstance(l, list) and len(l) == 1 and is_str(l[0])):
if is_str(l):
_l = l
else:
_l = l[0]
match = re.fullmatch(r'\[\[\s*(?P<clause>.*)\s*\]\]', _l)
clause = _l
if match:
clause = match.groupdict()['clause']
return {
"nested": {
"path": "elisa",
"query": {
"query_string": {
"query": clause
}
}
}
}
# unary operator
if isinstance(l[0], str) and l[0].lower() == 'not':
# check unary operations
return {
"bool": {
"must_not": [buildSubQuery(l[1])]
}
}
if len(l) >= 3:
# assume operations are never mixed in one stage...
if l[1].lower() == 'and':
return {
"bool": {
"must": [buildSubQuery(x) for x in l[::2]]
}
}
elif l[1].lower() == 'or':
return {
"bool": {
"should": [buildSubQuery(x) for x in l[::2]]
}
}
return None
parsed_expression = expression.parseString(elisa, parseAll=True)
try:
query = buildSubQuery(parsed_expression.asList())
except Exception:
query = None
#query = buildSubQuery(parsed_expression.asList())
if query:
return {"query": query}
else:
return {"query": {"nested": {"path": "elisa", "query": {"query_string": {"query": elisa}}}}}
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] |
lightconfig/lightconfig.py | daassh/LightConfig | 2 | 32525 | <reponame>daassh/LightConfig
#!/usr/bin/env python
# coding=utf-8
# get a easy way to edit config file
"""
>>> from lightconfig import LightConfig
>>> cfg = LightConfig("config.ini")
>>> cfg.section1.option1 = "value1"
>>> print(cfg.section1.option1)
value1
>>> "section1" in cfg
True
>>> "option1" in cfg.section1
True
"""
import os
import codecs
import locale
try:
from ConfigParser import RawConfigParser as ConfigParser
except ImportError:
from configparser import RawConfigParser as ConfigParser
class ConfigParserOptionCaseSensitive(ConfigParser):
"""
add case sensitve to ConfigParser
"""
def __init__(self, defaults=None):
ConfigParser.__init__(self, defaults)
def optionxform(self, option_str):
return option_str
class LightConfig(object):
def __init__(self, config_path, try_encoding={'utf-8', 'utf-8-sig', locale.getpreferredencoding().lower()}, try_convert_digit = False):
self.__dict__['_config_path'] = config_path
self.__dict__['_try_encoding'] = try_encoding if isinstance(try_encoding, (list, tuple, set)) else [try_encoding]
self.__dict__['_try_convert_digit'] = try_convert_digit
self.__dict__['_config'] = ConfigParserOptionCaseSensitive()
if not os.path.exists(config_path):
dir_path = os.path.dirname(os.path.abspath(config_path))
if not os.path.exists(dir_path):
os.makedirs(dir_path)
open(config_path, 'a').close()
LightConfig._read(self)
self.__dict__['_cached_stamp'] = LightConfig._stamp(self)
def __str__(self):
return str(LightConfig._as_dict(self))
def __repr__(self):
return repr(LightConfig._as_dict(self))
def __iter__(self):
return iter(LightConfig._as_dict(self).items())
def __getattribute__(self, item):
if item in ('keys', '__dict__'):
return super(LightConfig, self).__getattribute__(item)
else:
return LightConfig.__getattr__(self, item)
def __getattr__(self, item):
return LightConfig.Section(self, item, self.__dict__['_try_convert_digit'])
__getitem__ = __getattr__
def __setattr__(self, name, value):
try:
value = dict(value)
except:
raise ValueError('"{}" is not dictable'.format(value))
else:
LightConfig.__dict__['__delattr__'](self, name)
section = LightConfig.Section(self, name, self.__dict__['_try_convert_digit'])
for k, v in value.items():
LightConfig.Section.__setattr__(section, k, v)
__setitem__ = __setattr__
def __delattr__(self, item):
if item in self:
self.__dict__['_config'].remove_section(item)
LightConfig._save(self)
__delitem__ = __delattr__
def __contains__(self, item):
return self.__dict__['_config'].has_section(item)
def _as_dict(self):
res = {}
for section in self.keys():
res[section] = self[section]
return res
def keys(self):
return self.__dict__['_config'].sections()
def _read(self):
for encoding in self.__dict__['_try_encoding']:
fp = codecs.open(self.__dict__['_config_path'], encoding=encoding)
try:
if 'read_file' in dir(self.__dict__['_config']):
self.__dict__['_config'].read_file(fp)
else:
self.__dict__['_config'].readfp(fp)
except:
err = True
else:
err = False
self.__dict__['_encoding'] = encoding
break
if err:
raise UnicodeError("\"{}\" codec can't decode this config file".format(', '.join(self.__dict__['_try_encoding'])))
def _save(self):
self.__dict__['_config'].write(codecs.open(self.__dict__['_config_path'], "w", encoding=self.__dict__['_encoding']))
self.__dict__['_cached_stamp'] = LightConfig._stamp(self)
def _stamp(self):
return os.stat(self.__dict__['_config_path']).st_mtime
class Section(object):
def __init__(self, conf, section, try_convert_digit):
self.__dict__['_section'] = section
self.__dict__['_conf'] = conf
self.__dict__['_try_convert_digit'] = try_convert_digit
def __str__(self):
return str(LightConfig.Section._as_dict(self))
def __repr__(self):
return repr(LightConfig.Section._as_dict(self))
def __iter__(self):
return iter(LightConfig.Section._as_dict(self).items())
def __getattribute__(self, item):
if item in ('keys', '__dict__'):
return super(LightConfig.Section, self).__getattribute__(item)
else:
return LightConfig.Section.__getattr__(self, item)
def __getattr__(self, option):
current_stamp = LightConfig._stamp(self.__dict__['_conf'])
if current_stamp != self.__dict__['_conf'].__dict__['_cached_stamp']:
LightConfig._read(self.__dict__['_conf'])
self.__dict__['_conf'].__dict__['_cached_stamp'] = current_stamp
value = self.__dict__['_conf'].__dict__['_config'].get(self.__dict__['_section'], option)
if self.__dict__['_try_convert_digit']:
try:
value = eval(value)
except:
pass
return value
__getitem__ = __getattr__
def __setattr__(self, key, value):
if not self.__dict__['_section'] in self.__dict__['_conf']:
self.__dict__['_conf'].__dict__['_config'].add_section(self.__dict__['_section'])
self.__dict__['_conf'].__dict__['_config'].set(self.__dict__['_section'], key, str(value))
LightConfig._save(self.__dict__['_conf'])
__setitem__ = __setattr__
def __delattr__(self, item):
if item in self:
self.__dict__['_conf'].__dict__['_config'].remove_option(self.__dict__['_section'], item)
LightConfig._save(self.__dict__['_conf'])
__delitem__ = __delattr__
def __contains__(self, item):
return self.__dict__['_conf'].__dict__['_config'].has_option(self.__dict__['_section'], item)
def _as_dict(self):
return dict(self.__dict__['_conf'].__dict__['_config'].items(self.__dict__['_section']))
def keys(self):
return self.__dict__['_conf'].__dict__['_config'].options(self.__dict__['_section'])
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run.py | 1008siang/Razer_UserAgent | 0 | 102233 | #%%
from user_agents import parse
user_agent = "Mozilla/5.0 (Linux; Android 10; SM-N960F Build/QP1A.190711.020; wv) AppleWebKit/537.36 (KHTML, like Gecko) Version/4.0 Chrome/78.0.3904.62 XWEB/2889 MMWEBSDK/20210902 Mobile Safari/537.36 MMWEBID/1696 MicroMessenger/8.0.15.2001(0x28000F41) Process/to"
ua = parse(user_agent)
print(ua.browser)
print(ua.os)
# %%
import csv
from user_agents import parse
reader = csv.reader(open('uaList.csv', 'r',encoding='UTF-8',errors='ignore'))
writer = csv.writer(open('uaOutput.csv', 'w'))
headers = next(reader)
headers.append("Browser")
headers.append("OperatingSystem")
writer.writerow(headers)
for row in reader:
temp = parse(row[0])
row.append(str(temp.browser))
row.append(str(temp.os))
writer.writerow(row)
# os = next(next(reader))
# os.append("OperatingSystem")
# writer.writerow(os)
# for row in reader:
# temp = parse(row[0])
# row.append(str(temp.os))
# writer.writerows(row)
# print(row)
# %%
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] |
backend/utlis/crypt.py | shuttlesworthNEO/ClashHacks-methOD | 0 | 125035 | import numpy as np
import pandas as pd
import theano
from keras.layers import Dense
from keras.models import Model,load_model
def crypto(x):
encoder = load_model("/home/vasu/all_projects/Hackathons/ClashHacks-methOD/backend/utlis/encoder.h5")
x = list(x)
for ix in range(len(x)):
x[ix] = int(x[ix], 16)
y = np.array(tuple(x))
y = y.reshape(1,16)
out = encoder.predict(y)
out = out.reshape(32,1)
cryto = []
for ix in range(out.shape[0]):
if ix%2==1:
cryto.append(str(int(out[ix])))
else:
cryto.append(str(y[0][ix/2]))
crypt_str = ""
for ix in cryto:
crypt_str += hex(int(ix)%16).split('x')[-1]
print crypt_str
return crypt_str | [
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710,
13,
12,
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29918,
710,
2
] |
Python_Exercise/py_exercise_twenty_five.py | kindyluv/My_Personal_Python_Exercises | 0 | 101274 | <reponame>kindyluv/My_Personal_Python_Exercises
price = 1000000
good_credit = True
high_income = True
if good_credit and high_income:
down_payment = 1.0 * price
print(f"eligible for loan")
else:
down_payment = 2.0 * price
print(f"ineligible for loan")
print(f"down payment is {down_payment}")
| [
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] |
ch_14/tests/test_weather_threads.py | real-slim-chadi/Python-Object-Oriented-Programming---4th-edition | 43 | 163635 | <reponame>real-slim-chadi/Python-Object-Oriented-Programming---4th-edition
"""
Python 3 Object-Oriented Programming
Chapter 14. Concurrency
"""
from pytest import *
from unittest.mock import Mock, mock_open, call
import weather_threads
def test_station():
halifax = weather_threads.Station("NS", "s0000318")
assert halifax.path == "/NS/s0000318_e.xml"
assert halifax.url == "https://dd.weather.gc.ca/citypage_weather/xml/NS/s0000318_e.xml"
@fixture
def temp_getter():
return weather_threads.TempGetter("Halifax")
@fixture
def mock_urlopen(monkeypatch):
urlopen = mock_open(
read_data="""<?xml version='1.0'?><siteData><currentConditions><temperature unitType="metric" units="C">42</temperature></currentConditions></siteData>"""
)
monkeypatch.setattr(weather_threads, 'urlopen', urlopen)
return urlopen
def test_temp_getter(temp_getter, mock_urlopen):
temp_getter.run()
assert temp_getter.temperature == "42"
mock_urlopen.assert_called_once_with(
'https://dd.weather.gc.ca/citypage_weather/xml/NS/s0000318_e.xml'
)
| [
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13,
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332,
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9294,
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13,
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1113,
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705,
1624,
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29900,
29900,
29900,
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29941,
29896,
29947,
29918,
29872,
29889,
3134,
29915,
13,
1678,
1723,
13,
2
] |
src/cogs/core/core.py | vcokltfre/Zeek | 0 | 43052 | <filename>src/cogs/core/core.py
from datetime import datetime
from os import getenv
from discord import Message, RawMessageDeleteEvent
from discord.ext import commands
from src.internal.bot import Bot
class Core(commands.Cog):
"""Core metric collection."""
def __init__(self, bot: Bot):
self.bot = bot
@staticmethod
def is_staff(member) -> bool:
return int(getenv("STAFF")) in member._roles
@commands.Cog.listener()
async def on_message(self, message: Message) -> None:
if not message.guild: return
QUERY = "INSERT INTO Messages Values ($1, $2, $3, $4, $5, $6, $7, $8);"
await self.bot.db.execute(
QUERY,
message.id,
message.channel.id,
message.channel.category.id if message.channel.category else None,
message.guild.id,
message.author.id,
self.is_staff(message.author),
message.author.bot,
message.created_at,
)
@commands.Cog.listener()
async def on_raw_message_delete(self, payload: RawMessageDeleteEvent) -> None:
if not payload.guild_id: return
QUERY = "INSERT INTO DeletedMessages VALUES ($1, $2);"
await self.bot.db.execute(
QUERY,
payload.message_id,
datetime.utcnow(),
)
@commands.command(name="stats")
@commands.is_owner()
async def stats(self, ctx: commands.Context) -> None:
M_QUERY = "SELECT COUNT(*) FROM Messages;"
DM_QUERY = "SELECT COUNT(*) FROM DeletedMessages;"
messages = await self.bot.db.fetchrow(M_QUERY)
deleted = await self.bot.db.fetchrow(DM_QUERY)
messages, deleted = messages[0], deleted[0]
await ctx.send(f"Total messages: {messages}\nDeleted messages: {deleted}")
def setup(bot: Bot):
bot.add_cog(Core(bot))
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468,
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29898,
7451,
876,
13,
2
] |
horizon/openstack_dashboard/dashboards/cdn/cdn_monitor_report/urls.py | yianjiajia/openstack_horizon | 0 | 177678 | <filename>horizon/openstack_dashboard/dashboards/cdn/cdn_monitor_report/urls.py<gh_stars>0
from django.conf.urls import patterns
from django.conf.urls import url
from .views import IndexView, ajax_view
urlpatterns = patterns('',
url(r'^$', IndexView.as_view(), name='index'),
url(r'^\?tab=monitor_report__data_statistics$', IndexView.as_view(), name='data_statistics_tab'),
url(r'^json$', ajax_view, kwargs={'tenant_id': '', 'domain_id': ''}),
)
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] |
formTest.py | faisalarkan21/mbti-test-qt | 0 | 109282 | <reponame>faisalarkan21/mbti-test-qt
__author__ = 'faisal21'
import sys
from PyQt4 import QtGui
from PyQt4.QtGui import QDialog
from PyQt4 import QtCore
from dialog import Ui_Dialog
from Tkinter import *
class Test(QtGui.QDialog,Toplevel):
def __init__(self,parent):
QtGui.QMainWindow.__init__(self,parent)
self.ui = Ui_Dialog()
self.ui.setupUi(self)
self.ui.pushButton_2.setEnabled(False)
self.backExstro()
self.backFeel()
self.backIntro()
self.backIntusi()
self.backJudg()
self.backPercep()
self.backSense()
self.backThink()
self.actTombol()
self.act()
##############################################
################InstalasiVariable###################
##############################################
def backIntusi(self):
self.Intuisi = 0
self.subIntuisi1= 0
self.subIntuisi2 = 0
self.subIntuisi3 = 0
self.subIntuisi4 = 0
self.subIntuisi5 = 0
def backSense(self):
self.Sense = 0
self.subSense1 = 0
self.subSense2 = 0
self.subSense3 = 0
self.subSense4 = 0
self.subSense5 = 0
def backExstro(self):
self.Exstro = 0
self.subExstro1 = 0
self.subExstro2 = 0
self.subExstro3 = 0
self.subExstro4 = 0
self.subExstro5 = 0
def backIntro(self):
self.Intro = 0
self.subIntro1 = 0
self.subIntro2 = 0
self.subIntro3 = 0
self.subIntro4 = 0
self.subIntro5 = 0
def backJudg(self):
self.Judg = 0
self.subJudg1 = 0
self.subJudg2 = 0
self.subJudg3 = 0
self.subJudg4 = 0
self.subJudg5 = 0
def backPercep(self):
self.Percep =0
self.subPercep1 = 0
self.subPercep2 = 0
self.subPercep3 = 0
self.subPercep4 = 0
self.subPercep5 = 0
def backThink(self):
self.Think = 0
self.subThink1 = 0
self.subThink2 = 0
self.subThink3 = 0
self.subThink4 = 0
self.subThink5 = 0
def backFeel(self):
self.Feel = 0
self.subFeel1 = 0
self.subFeel2 = 0
self.subFeel3 = 0
self.subFeel4 = 0
self.subFeel5 = 0
##############################################
################Action###################
##############################################
def actTombol (self):
self.ui.pushButton.clicked.connect(self.jumTotal)
self.ui.pushButton_2.clicked.connect(self.kalkulasi)
def act(self):
self.ui.radioButtonP1.clicked.connect(self.soal1)
self.ui.radioButtonJ1.clicked.connect(self.soal1)
self.ui.radioButtonI1.clicked.connect(self.soal2)
self.ui.radioButtonE1.clicked.connect(self.soal2)
self.ui.radioButtonT1.clicked.connect(self.soal3)
self.ui.radioButtonF1.clicked.connect(self.soal3)
self.ui.radioButtonN1.clicked.connect(self.soal4)
self.ui.radioButtonS1.clicked.connect(self.soal4)
self.ui.radioButtonJ1_2.clicked.connect(self.soal5)
self.ui.radioButtonP1_2.clicked.connect(self.soal5)
self.ui.radioButtonI1_2.clicked.connect(self.soal6)
self.ui.radioButtonE1_2.clicked.connect(self.soal6)
self.ui.radioButtonN2.clicked.connect(self.soal7)
self.ui.radioButtonS2.clicked.connect(self.soal7)
self.ui.radioButtonE2.clicked.connect(self.soal8)
self.ui.radioButtonI2.clicked.connect(self.soal8)
self.ui.radioButtonJ2.clicked.connect(self.soal9)
self.ui.radioButtonP2.clicked.connect(self.soal9)
self.ui.radioButtonF2.clicked.connect(self.soal10)
self.ui.radioButtonT2.clicked.connect(self.soal10)
self.ui.radioButtonS2_2.clicked.connect(self.soal11)
self.ui.radioButtonN2_2.clicked.connect(self.soal11)
self.ui.radioButtonT2_2.clicked.connect(self.soal12)
self.ui.radioButtonF2_2.clicked.connect(self.soal12)
self.ui.radioButtonS3.clicked.connect(self.soal13)
self.ui.radioButtonN3.clicked.connect(self.soal13)
self.ui.radioButtonJ3.clicked.connect(self.soal14)
self.ui.radioButtonP3.clicked.connect(self.soal14)
self.ui.radioButtonN3_3.clicked.connect(self.soal15)
self.ui.radioButtonS3_3.clicked.connect(self.soal15)
self.ui.radioButtonI3.clicked.connect(self.soal16)
self.ui.radioButtonE3.clicked.connect(self.soal16)
self.ui.radioButtonF3.clicked.connect(self.soal17)
self.ui.radioButtonT3.clicked.connect(self.soal17)
self.ui.radioButtonJ3_2.clicked.connect(self.soal18)
self.ui.radioButtonP3_2.clicked.connect(self.soal18)
self.ui.radioButtonE4.clicked.connect(self.soal19)
self.ui.radioButtonI4.clicked.connect(self.soal19)
self.ui.radioButtonT4.clicked.connect(self.soal20)
self.ui.radioButtonF4.clicked.connect(self.soal20)
##############################################
################ Check Button Choice ###################
##############################################
def soal1 (self):
if (self.ui.radioButtonP1.isChecked()):
self.jwb1 = 1
elif (self.ui.radioButtonJ1.isChecked()):
self.jwb1 = 2
def soal2 (self):
if (self.ui.radioButtonI1.isChecked()):
self.jwb2 = 1
elif (self.ui.radioButtonE1.isChecked()):
self.jwb2 = 2
def soal3 (self):
if (self.ui.radioButtonT1.isChecked()):
self.jwb3 = 1
elif (self.ui.radioButtonF1.isChecked()):
self.jwb3 = 2
###################
def soal4 (self):
if (self.ui.radioButtonN1.isChecked()):
self.jwb4 = 1
elif (self.ui.radioButtonS1.isChecked()):
self.jwb4 = 2
def soal5 (self):
if (self.ui.radioButtonJ1_2.isChecked()):
self.jwb5 = 1
elif (self.ui.radioButtonP1_2.isChecked()):
self.jwb5 = 2
def soal6 (self):
if (self.ui.radioButtonI1_2.isChecked()):
self.jwb6 = 1
elif (self.ui.radioButtonE1_2.isChecked()):
self.jwb6 = 2
#####################
def soal7 (self):
if (self.ui.radioButtonN2.isChecked()):
self.jwb7 = 1
elif (self.ui.radioButtonS2.isChecked()):
self.jwb7 = 2
def soal8 (self):
if (self.ui.radioButtonE2.isChecked()):
self.jwb8 = 1
elif (self.ui.radioButtonI2.isChecked()):
self.jwb8 = 2
def soal9 (self):
if (self.ui.radioButtonJ2.isChecked()):
self.jwb9 = 1
elif (self.ui.radioButtonP2.isChecked()):
self.jwb9 = 2
def soal10 (self):
if (self.ui.radioButtonF2.isChecked()):
self.jwb10 = 1
elif (self.ui.radioButtonT2.isChecked()):
self.jwb10 = 2
def soal11 (self):
if (self.ui.radioButtonS2_2.isChecked()):
self.jwb11 = 1
elif (self.ui.radioButtonN2_2.isChecked()):
self.jwb11 = 2
def soal12 (self):
if (self.ui.radioButtonT2_2.isChecked()):
self.jwb12 = 1
elif (self.ui.radioButtonF2_2.isChecked()):
self.jwb12 = 2
################
def soal13 (self):
if (self.ui.radioButtonS3.isChecked()):
self.jwb13 = 1
elif (self.ui.radioButtonN3.isChecked()):
self.jwb13 = 2
def soal14 (self):
if (self.ui.radioButtonJ3.isChecked()):
self.jwb14 = 1
elif (self.ui.radioButtonP3.isChecked()):
self.jwb14 = 2
def soal15 (self):
if (self.ui.radioButtonN3_3.isChecked()):
self.jwb15 = 1
elif (self.ui.radioButtonS3_3.isChecked()):
self.jwb15 = 2
###################
def soal16 (self):
if (self.ui.radioButtonI3.isChecked()):
self.jwb16 = 1
elif (self.ui.radioButtonE3.isChecked()):
self.jwb16 = 2
def soal17 (self):
if (self.ui.radioButtonF3.isChecked()):
self.jwb17 = 1
elif (self.ui.radioButtonT3.isChecked()):
self.jwb17 = 2
def soal18 (self):
if (self.ui.radioButtonJ3_2.isChecked()):
self.jwb18 = 1
elif (self.ui.radioButtonP3_2.isChecked()):
self.jwb18 = 2
#####################
def soal19 (self):
if (self.ui.radioButtonE4.isChecked()):
self.jwb19 = 1
elif (self.ui.radioButtonI4.isChecked()):
self.jwb19 = 2
def soal20 (self):
if (self.ui.radioButtonT4.isChecked()):
self.jwb20 = 1
elif (self.ui.radioButtonF4.isChecked()):
self.jwb20 = 2
##############################################
################subJumlah###################
##############################################
def jumSoal1 (self):
if (self.jwb1 == 1):
self.subPercep1 =+1
else :
self.subJudg1 = +1
def jumSoal2 (self):
if (self.jwb2 == 1):
self.subIntro1 =+1
else :
self.subExstro1 = +1
def jumSoal3 (self):
if (self.jwb3 == 1):
self.subThink1 =+1
else :
self.subFeel1 = +1
##############
def jumSoal4 (self):
if (self.jwb4 == 1):
self.subIntuisi1 =+1
else :
self.subSense1 = +1
def jumSoal5 (self):
if (self.jwb5 == 1):
self.subJudg2 =+1
else :
self.subPercep2 = +1
def jumSoal6 (self):
if (self.jwb6 == 1):
self.subIntro2 =+1
else :
self.subExstro2 = +1
#########################
def jumSoal7 (self):
if (self.jwb7 == 1):
self.subIntuisi2 =+1
else :
self.subSense2 = +1
def jumSoal8 (self):
if (self.jwb8 == 1):
self.subExstro3 =+1
else :
self.subIntro3 = +1
def jumSoal9 (self):
if (self.jwb9 == 1):
self.subJudg3 =+1
else :
self.subPercep3 = +1
def jumSoal10 (self):
if (self.jwb10 == 1):
self.subFeel2 =+1
else :
self.subThink2 = +1
def jumSoal11 (self):
if (self.jwb11 == 1):
self.subSense3 =+1
else :
self.subIntuisi3 = +1
def jumSoal12 (self):
if (self.jwb12 == 1):
self.subThink3 =+1
else :
self.subFeel3 = +1
def jumSoal13 (self):
if (self.jwb13 == 1):
self.subSense4 =+1
else :
self.subIntuisi4 = +1
def jumSoal14 (self):
if (self.jwb14 == 1):
self.subJudg4 =+1
else :
self.subPercep4 = +1
def jumSoal15 (self):
if (self.jwb15 == 1):
self.subIntuisi5 =+1
else :
self.subSense5 = +1
def jumSoal16 (self):
if (self.jwb16 == 1):
self.subIntro4 =+1
else :
self.subExstro4 = +1
def jumSoal17 (self):
if (self.jwb17 == 1):
self.subFeel4 =+1
else :
self.subThink4 = +1
def jumSoal18 (self):
if (self.jwb18 == 1):
self.subJudg5 =+1
else :
self.subPercep5 = +1
def jumSoal19 (self):
if (self.jwb19 == 1):
self.subExstro5 =+1
else :
self.subIntro5 = +1
def jumSoal20 (self):
if (self.jwb20 == 1):
self.subThink5 =+1
else :
self.subFeel5 = +1
##############################################
################jumlahTotal###################
##############################################
def jumTotal(self):
if ((self.ui.radioButtonP1.isChecked() or self.ui.radioButtonJ1.isChecked()) and
(self.ui.radioButtonI1.isChecked() or self.ui.radioButtonE1.isChecked()) and
(self.ui.radioButtonT1.isChecked() or self.ui.radioButtonF1.isChecked()) and
(self.ui.radioButtonN1.isChecked() or self.ui.radioButtonS1.isChecked()) and
(self.ui.radioButtonJ1_2.isChecked() or self.ui.radioButtonP1_2.isChecked()) and
(self.ui.radioButtonI1_2.isChecked() or self.ui.radioButtonE1_2.isChecked()) and
(self.ui.radioButtonN2.isChecked() or self.ui.radioButtonS2.isChecked()) and
(self.ui.radioButtonE2.isChecked() or self.ui.radioButtonI2.isChecked()) and
(self.ui.radioButtonJ2.isChecked() or self.ui.radioButtonP2.isChecked()) and
(self.ui.radioButtonF2.isChecked() or self.ui.radioButtonT2.isChecked())and
(self.ui.radioButtonS2_2.isChecked() or self.ui.radioButtonN2_2.isChecked()) and
(self.ui.radioButtonT2_2.isChecked() or self.ui.radioButtonF2_2.isChecked()) and
(self.ui.radioButtonS3.isChecked() or self.ui.radioButtonN3.isChecked()) and
(self.ui.radioButtonJ3.isChecked() or self.ui.radioButtonP3.isChecked()) and
(self.ui.radioButtonN3_3.isChecked() or self.ui.radioButtonS3_3.isChecked()) and
(self.ui.radioButtonI3.isChecked() or self.ui.radioButtonE3.isChecked()) and
(self.ui.radioButtonF3.isChecked() or self.ui.radioButtonT3.isChecked()) and
(self.ui.radioButtonJ3_2.isChecked() or self.ui.radioButtonP3_2.isChecked()) and
(self.ui.radioButtonE4.isChecked() or self.ui.radioButtonI4.isChecked()) and
(self.ui.radioButtonT4.isChecked() or self.ui.radioButtonF4.isChecked())):
self.jumSoal1()
self.jumSoal2()
self.jumSoal3()
self.jumSoal4()
self.jumSoal5()
self.jumSoal6()
self.jumSoal7()
self.jumSoal8()
self.jumSoal9()
self.jumSoal10()
self.jumSoal11()
self.jumSoal12()
self.jumSoal13()
self.jumSoal14()
self.jumSoal15()
self.jumSoal16()
self.jumSoal17()
self.jumSoal18()
self.jumSoal19()
self.jumSoal20()
self.ui.pushButton_2.setEnabled(True)
QDialog.QMessageBox.information(self, "Pehatihan", "Silahkan tekan tombol Lihat hasil","Oke")
else :
QDialog.QMessageBox.information(self, "Pehatihan", "Tolong isi semua pilihan Terlebih dahulu","Oke")
##############################################
################KalkulasiTotal###################
##############################################
def kalkulasi (self):
self.ui.pushButton_2.setEnabled(False)
self.Intro = self.subIntro1 + self.subIntro2 + self.subIntro3 +self.subIntro4+self.subIntro5
self.Exstro = self.subExstro1 + self.subExstro2 + self.subExstro3 +self.subExstro4 + self.subExstro5
self.Percep = self.subPercep1 + self.subPercep2 + self.subPercep3 +self.subPercep4 +self.subPercep5
self.Judg = self.subJudg1 + self.subJudg2 + self.subJudg3+ self.subJudg4+self.subJudg5
self.Feel = self.subFeel1 + self.subFeel2 + self.subFeel3 + self.subFeel4 + self.subFeel5
self.Think = self.subThink1 + self.subThink2+ self.subThink3 + self.subThink4 + self.subThink5
self.Sense = self.subSense1 + self.subSense2 +self.subSense3 +self.subSense4 +self.subSense5
self.Intuisi = self.subIntuisi1 + self.subIntuisi2 + self.subIntuisi3 +self.subIntuisi4 +self.subIntuisi5
if (self.Intro<self.Exstro):
self.IorE = "E"
elif (self.Intro>self.Exstro):
self.IorE = "I"
if (self.Sense < self.Intuisi):
self.SorI = "N"
else :
self.SorI = "S"
if (self.Think < self.Feel):
self.TorF = "F"
else :
self.TorF = "T"
if (self.Percep < self.Judg):
self.PorJ = "J"
else :
self.PorJ = "P"
self.ui.label_2.setText("Skor Inrovert anda adalah : %d" % self.Intro + "\n" + "Skor Extrovert anda adalah : %d" % self.Exstro +"\n"
+ "Skor Peception anda adalah : %d" % self.Percep + "\n" + "Skor Jugje anda adalah : %d" % self.Judg +"\n"+
"Skor Feel anda adalah : %d" % self.Feel + "\n" + "Skor Think anda adalah : %d" % self.Think + "\n" +
"Skor Sense anda adalah : %d" % self.Sense + "\n" + "Skor Intuisi anda adalah : %d" % self.Intuisi + "\n" + "Anda Adalah : " + self.IorE+self.SorI+self.TorF+self.PorJ )
QDialog.QMessageBox.information(self, "Pehatihan", "Selamat anda adalah seorang %s%s%s%s" % (self.IorE,self.SorI,self.TorF,self.PorJ),"Terimakasih :)")
print "nilai Inrovert anda adalah : %d" % self.Intro
print "nilai Extrovert anda adalah : %d" % self.Exstro
print "Nilai Peception anda adalah : %d" % self.Percep
print "Nilai Jugje anda adalah : %d" % self.Judg
print "Nilai Feel anda adalah : %d" % self.Feel
print "Nilai Think anda adalah : %d" % self.Think
print "Nilai Sense anda adalah : %d" % self.Sense
print "Nilai Intuisi anda adalah : %d" % self.Intuisi
##############################################
################MainExcecution###################
##############################################
if __name__ == '__main__':
app = QtGui.QApplication(sys.argv)
window = Test()
window.show()
sys.exit(app.exec_())
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entity/Server.py | FAWC-bupt/Hotel-Air-Conditioning-Dispatching-System | 1 | 154862 | import threading
from enum import IntEnum
class Mode(IntEnum):
Cold = 0
Hot = 1
class WindLevel(IntEnum):
NoWind = 0
Level_1 = 1
Level_2 = 2
Level_3 = 3
class Algorithm(IntEnum):
Priority = 0
RR = 1
class Server(object):
"""
服务器，是单例模式
"""
_instance_lock = threading.Lock()
AirCondition_num = -1
default_temp = -1
default_mode = -1
default_highest_temp = -1
default_lowest_temp = -1
default_wind_level = -1
SystemTimer = None
time_slot = -1
scheduling_algorithm = -1
tariff = -1
airCondition_list = []
user_list = []
administrator_list = []
waiter_list = []
manager_list = []
request_queue = []
request_lock = threading.Lock()
@classmethod
def instance(cls, *args, **kwargs):
with cls._instance_lock:
if not hasattr(Server, '_instance'):
Server._instance = Server()
return Server._instance
return Server._instance
def __init__(self):
self.is_on = False
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oompa/tracking/github/GitHubTracker.py | sjtsp2008/oompa | 2 | 123550 | <gh_stars>1-10
#
# GitHubTracker.py
#
"""
package oompa.tracking.github
"""
import os
import sys
import time
from datetime import datetime
from oompa.tracking.github import github_utils
from oompa.tracking.github.GitHub3Helper import GitHub3Helper
from oompa.tracking.TagManager import TagManager
from oompa.tracking.UpdateLogger import UpdateLogger
# xxx temp, during a specific problem - all projects claimed to be forked from github3.empty.Empty
import github3
class _Wrapper(dict):
pass
class GitHubTracker:
"""
support for tracking users, organizations, fork trees, etc.
"""
def __init__(self, config):
"""
XXX what is config? (a dictionary? a real config object?)
TODO: need a log
"""
self.config = config
self.githubHelper = GitHub3Helper(config)
# sometimes we want to turn this off, for testing from-scratch
self.use_etag = True
# self.use_etag = False
# self.use_etag = None
self._updateLogger = None
return
def _getUpdateLogger(self):
if self._updateLogger is not None:
return self._updateLogger
self._updateLogger = UpdateLogger(self.config)
return self._updateLogger
def getGithubURL(self, tail):
"""
return the
tail could be "<entity>" (user or org), or "<entity>/<repo>"
"""
return "https://github.com/%s" % tail
def getHTMLAnchorText(self, name):
url = self.getGithubURL(name)
return '<a href="%s" target="_blank">%s</a>' % ( url, name )
def _showEntityTags(self, entityMetadata):
"""report tags and description for the given entity in to the report
output stream
"""
self.out_stream.write("\n")
entity_url = entityMetadata.getGithubURL()
tagInfo = self._tag_mgr.getTags(entity_url)
if tagInfo is not None:
tags, description = tagInfo
# same output whether html or text (for now)
# self.out_stream.write(" tags: %s\n" % ( " ".join(tags), ))
# self.out_stream.write(" desc: %s\n" % ( description, ))
self.out_stream.write(" tags: %s desc: %s\n" % ( " ".join(tags), description ))
else:
self.out_stream.write(" no tag info yet\n")
self.out_stream.write("\n")
return
def showEntity(self, entityMetadata):
"""
entityMetadata is an oompa.tracking.github.EntityMetadata
"""
if self._showed_entity:
return
if self._format == "html":
self.out_stream.write("GitHub entity: %s - %s\n" % (
entityMetadata.kind, self.getHTMLAnchorText(entityMetadata.name), ))
else:
print("GitHub entity: %-25s (%s)" % ( entityMetadata.name, entityMetadata.kind ))
self._showEntityTags(entityMetadata)
self._showed_entity = True
return
def reportListUpdates(self, field, github_obj, entityMetadata, valueAttr):
"""fetch the list named field for the specified github_obj, and
compare with previous results (reporting new, and no-longer)
github_obj is a User or Organization
"""
# depending on field, newValue will be a list of Repository or User objects
# TODO: how do we check return code
newValue = self.githubHelper.list(field,
github_obj,
use_etag = self.use_etag)
# print("reportListUpdates: %s - %s" % ( entityMetadata.name, field, ))
# print(" new: %r" % newValue)
if newValue == "no-change":
# print (" no change since last check: %s - %s" % ( entityMetadata.name, field, ))
return
# if not newValue:
# print (" no new value: %s - %s" % ( entityMetadata.name, field, ))
# return
prevValue = entityMetadata.setdefault(field, [])
#
# note that a lot of "changes" seem to involve empty values
#
# print (" changed since last check: %s - %s" % ( entityMetadata.name, field, ))
# note: i think that newalue is a list of Repository and
# prevValue is a list of strings
if valueAttr is not None:
# XXX hack - if it's a starred repo, need to access value.repository.attr maybe support introspection?
if field == "starred_repositories" and valueAttr == "full_name":
newValue = [ getattr(value.repository, valueAttr) for value in newValue ]
else:
newValue = [ getattr(value, valueAttr) for value in newValue ]
if "" in newValue:
print(" XXX EntityMetadata.reportListUpdates - empty strings in newValue - %s - %s" % ( field, newValue ))
print(" not updating local cache")
# XXX i think that a list of all empties is a sign
# that the rpc failed (but didn't fail well)
# we should bail out and try again
# newValue = [ value for value in newValue if value != '' ]
return
pass
# ( addedValues, removedValues )
# both are sets
if "" in prevValue:
print(" reportListUpdates - empty in prevValue %s (i.e., they were stored in db): %r\n" % ( field, prevValue ))
# prevValue = [ value for value in prevValue if value != '' ]
pass
# XXX the lack of writer framework hurts here
if self._format == "html":
format_link = self.getHTMLAnchorText
else:
format_link = self.getGithubURL
diffs = entityMetadata.getListDiffs(newValue,
prevValue)
# note that we don't yet render the sets. it just to determine if we want to
# show the section header
if diffs[0] or diffs[1]:
self.showEntity(entityMetadata)
if diffs[0] or diffs[1]:
entityMetadata.diffLists(field,
newValue,
prevValue,
out_stream = self.out_stream,
format_link = format_link)
# just because i'm impatient
self.out_stream.flush()
self._getUpdateLogger().logListUpdates(entityMetadata, field, "added", diffs[0])
self._getUpdateLogger().logListUpdates(entityMetadata, field, "removed", diffs[1])
pass
entityMetadata.updateList(field, newValue)
return
def filterMetadatas(self, entityMetadatas, patterns):
"""
only yield entities that string-match lower-case
TODO: get more clever - globbing
"""
patterns = [ pattern.lower() for pattern in patterns ]
for entityMetadata in entityMetadatas:
entityNameLower = entityMetadata.name.lower()
for pattern in patterns:
if entityNameLower.find(pattern) != -1:
yield entityMetadata
break
pass
pass
return
def listTracking(self, patterns = None):
"""
yield some or all github entities (users, orgs) currenty being tracked
if patterns specified, only yield entities that string-match lower-case
"""
entityMetadatas = self.githubHelper.getEntityMetadatas(mustExist = False)
if patterns:
entityMetadatas = self.filterMetadatas(entityMetadatas, patterns)
pass
for entityMetadata in entityMetadatas:
yield "%s/%s" % ( entityMetadata.kind, entityMetadata.name )
pass
return
def getGithubObject(self, entityMetadata):
return self.githubHelper.getGithubObject(entityMetadata.name,
entityMetadata.kind)
def printRatePointsLeft(self, message):
"""sugar
"""
self.githubHelper.printRatePointsLeft(message)
return
def logAllUpdates(self, *args):
# this one will capture the updates, but not render anything
xxx
# ??? did python 2.7 actually break this?
def discoverHtmlFormat(self, *args, verbose = False):
"""
TODO: use logging package, vs print to stdout
"""
# TODO: config
reportMemberChanges_b = False
self._tag_mgr = TagManager(self.config,
tags_filename = "entity-tags.tsv")
today_yyyymmdd = datetime.today().strftime("%Y%m%d")
# XXX allow caller to override defaults
dest_folder = os.path.join(os.environ["HOME"], "oompa", "discover")
out_path = os.path.join(dest_folder, "%s.discover.html" % today_yyyymmdd)
# TODO: make sure folder exists
# set this to False if you want to be able to re-run discover from last snapshot
# XXX get from config
update_metadata = True
# update_metadata = False
if not update_metadata:
print(" *not* flushing entity meta updates yet")
print("writing to: %s" % out_path)
self.out_stream = open(out_path, "w", encoding = 'utf8')
out_stream = self.out_stream
out_stream.write('<!DOCTYPE html>\n')
out_stream.write('<meta charset="utf-8">\n')
out_stream.write('<html>\n')
out_stream.write('<head>\n')
out_stream.write('<title>Tracker Discover Report - %s</title>\n' % ( today_yyyymmdd, ))
out_stream.write('</head>\n')
out_stream.write('<body>\n')
# XXX temp - should be full html
out_stream.write('<pre>\n')
helper = self.githubHelper
# TODO: pass in an option, maybe a threshold based on number
# of repos? this is about rate limit problems for
# certain entities
if args:
print("# not showing initial repos - stil trying to figure out rate limit problem for some entities")
showRepos = False
else:
showRepos = True
for entityMetadata in helper.getEntityMetadatas(*args, mustExist = False):
#
# there are several places which may show the entity the
# first time. we only want to show once
#
self._showed_entity = False
if verbose:
print("# %-40s (%s)" % ( entityMetadata.name, entityMetadata.kind ))
# self.printRatePointsLeft(" rate points before checking entity")
github_obj = self.getGithubObject(entityMetadata)
if github_obj is None:
print("XXX no github_obj: %s %s" % ( entityMetadata.name, entityMetadata.kind ))
continue
repos = helper.getRepos(github_obj, sort = "time-newest-first")
# TODO: switch to generic listing
# TODO: support for filtering *anything* through already-known
knownRepos = entityMetadata.setdefault("repoNames", [])
newRepos = [ repo for repo in repos if repo.full_name not in knownRepos ]
if newRepos:
self.showEntity(entityMetadata)
out_stream.write(" %d new repos\n" % len(newRepos))
if showRepos:
out_stream.write("\n")
helper.printRepos(repos = newRepos,
out_stream = out_stream,
format_link = self.getHTMLAnchorText)
pass
for repo in newRepos:
entityMetadata.append("repoNames", repo.full_name)
pass
# note: this should be the *only* action in recordUpdates,
# but helper.printRepos has side-effects of
# pulling in extra info about the project (parent and source)
self._getUpdateLogger().logUpdates(entityMetadata, "repoNames", newRepos)
pass
# XXX organizations have followers_count and following_count, but no
# followers() or following()
if github_obj.type == "User":
self.reportListUpdates("followers", github_obj, entityMetadata, "login")
self.reportListUpdates("following", github_obj, entityMetadata, "login")
self.reportListUpdates("starred_repositories", github_obj, entityMetadata, "full_name")
self.reportListUpdates("subscriptions", github_obj, entityMetadata, "full_name")
elif github_obj.type == "Organization":
if reportMemberChanges_b:
self.reportListUpdates("public_members", github_obj, entityMetadata, "login")
pass
pass
if update_metadata:
entityMetadata.flush()
if self._showed_entity:
out_stream.write("\n")
pass
out_stream.write('</pre>\n')
out_stream.write('</body>\n')
out_stream.write('</html>\n')
if out_stream != sys.stdout:
out_stream.close()
pass
return
def _discoverListUpdates(self, field, github_obj, entityMetadata, valueAttr):
# depending on field, newValue will be a list of Repository or User objects
# TODO: how do we check return code?
newValue = self.githubHelper.list(field,
github_obj,
use_etag = self.use_etag)
if newValue == "no-change":
# print (" no change since last check: %s - %s" % ( entityMetadata.name, field, ))
return
prevValue = entityMetadata.setdefault(field, [])
#
# note that a lot of "changes" seem to involve empty values
#
# typically, prevValue is list of strings. extract comparable strings
# from a list of github things
if valueAttr is not None:
# TODO: unroll this, to report which objects have the empty value
newValue = [ getattr(value, valueAttr) for value in newValue ]
# note: some objects have/had empty names. work around that
if "" in newValue:
print(" XXX EntityMetadata.reportListUpdates - empty strings in newValue - %s - %s" % ( field, newValue ))
print(" not updating local cache")
# XXX i think that a list of all empties is a sign
# that the rpc failed (but didn't fail well)
# we should bail out and try again
# newValue = [ value for value in newValue if value != '' ]
return
pass
# ( addedValues, removedValues )
# both are sets
if "" in prevValue:
print(" reportListUpdates - empty in prevValue %s (i.e., they were stored in db): %r\n" % ( field, prevValue ))
# prevValue = [ value for value in prevValue if value != '' ]
pass
diffs = entityMetadata.getListDiffs(newValue,
prevValue)
if diffs[0] or diffs[1]:
for added in diffs[0]:
self._getUpdateLogger().logListUpdates(entityMetadata, field, "added", added)
pass
for removed in diffs[1]:
self._getUpdateLogger().logListUpdates(entityMetadata, field, "removed", removed)
pass
pass
entityMetadata.updateList(field, newValue)
return
def _discoverUpdates(self, *args):
"""
baby step toward separating update-harvesting from reporting
"""
updateLogger = self._getUpdateLogger()
helper = self.githubHelper
# temp, while this is still just a test
helper._etags._updateEtags = False
update_metadata = True
# update_metadata = False
for entityMetadata in helper.getEntityMetadatas(*args, mustExist = False):
print("# %-40s (%s)" % ( entityMetadata.name, entityMetadata.kind ))
# repos is a special kind of list - has an api, vs just a field to query
# TODO: switch to generic listing. (is that possible?)
# TODO: we should also record "gone" repos
github_obj = self.getGithubObject(entityMetadata)
# repos = helper.getRepos(github_obj, sort = "time-newest-first")
repos = helper.getRepos(github_obj)
# TODO: support for filtering *anything* through already-known
knownRepos = entityMetadata.setdefault("repoNames", [])
newRepos = [ repo for repo in repos if repo.full_name not in knownRepos ]
if newRepos:
for repo in newRepos:
# actually update, so that we don't re-alert
entityMetadata.append("repoNames", repo.full_name)
# need to do this to pull in proper "pedigree" (forked from, (parent, source) ...)
# XXX we don't have a good place to put that data right now
repo.refresh()
extra_d = {}
extra_d["full_name"] = repo.full_name
if repo.parent is not None:
extra_d["parent"] = repo.parent.full_name
if repo.source != repo.parent:
extra_d["source"] = repo.source.full_name
pass
pass
updateLogger.logListUpdate(entityMetadata,
"repoNames",
"added",
**extra_d)
pass
pass
# XXX organizations have followers_count and following_count, but no
# followers() or following()
if github_obj.type == "User":
self._discoverListUpdates("followers", github_obj, entityMetadata, "login")
self._discoverListUpdates("following", github_obj, entityMetadata, "login")
self._discoverListUpdates("starred_repositories", github_obj, entityMetadata, "full_name")
self._discoverListUpdates("subscriptions", github_obj, entityMetadata, "full_name")
elif github_obj.type == "Organization":
self._discoverListUpdates("public_members", github_obj, entityMetadata, "login")
# are these not part of organization?
# self._discoverListUpdates("followers", github_obj, entityMetadata, "login")
# self._discoverListUpdates("following", github_obj, entityMetadata, "login")
# self._discoverListUpdates("starred_repositories", github_obj, entityMetadata, "full_name")
# self._discoverListUpdates("subscriptions", github_obj, entityMetadata, "full_name")
pass
if update_metadata:
entityMetadata.flush()
pass
pass
self.githubHelper._etags._updateEtags = True
return
def discover(self, *args, format = None, verbose = False):
"""either add new github entities (users/groups) to the set you
are tracking (if you specify args), or get an update on the
entities you are already tracking
"""
# XXX should use a Writer framework, but i don't expect this to live long - will
# go to a db and web server soon
# XXX cheating
self._format = format
if format == "html":
self.discoverHtmlFormat(*args, verbose = verbose)
return
# XXX temp
# self.out_stream = sys
helper = self.githubHelper
# TODO: pass in an option, maybe a threshold based on number
# of repos? this is about rate limit problems for
# certain entities
if args:
print("# not showing initial repos - stil trying to figure out rate limit problem for some entities")
showRepos = False
else:
showRepos = True
for entityMetadata in helper.getEntityMetadatas(*args, mustExist = False):
# XXX
self._showed_entity = False
if verbose:
self.showEntity(entityMetadata)
self.printRatePointsLeft(" rate points before checking entity")
pass
github_obj = self.getGithubObject(entityMetadata)
repos = helper.getRepos(github_obj, sort = "time-newest-first")
# TODO: switch to generic listing
# TODO: support for filtering *anything* through already-known
knownRepos = entityMetadata.setdefault("repoNames", [])
newRepos = [ repo for repo in repos if repo.full_name not in knownRepos ]
if newRepos:
self.showEntity(entityMetadata)
print(" %d new repos" % len(newRepos))
if showRepos:
helper.printRepos(repos = newRepos)
pass
if newRepos:
for repo in newRepos:
entityMetadata.append("repoNames", repo.full_name)
pass
pass
# XXX organizations have followers_count and following_count, but no
# followers() or following()
if github_obj.type == "User":
self.reportListUpdates("followers", github_obj, entityMetadata, "login")
self.reportListUpdates("following", github_obj, entityMetadata, "login")
self.reportListUpdates("starred_repositories", github_obj, entityMetadata, "full_name")
elif github_obj.type == "Organization":
self.reportListUpdates("public_members", github_obj, entityMetadata, "login")
pass
entityMetadata.flush()
pass
return
def reportUpdateHTML(self, *args, start_date = None, end_date = None):
"""
generate html discovery report over some date range from update logs
"""
from oompa.tracking.github.EntityMetadata import EntityMetadata
# XXX cheating
self._format = format
# TODO: config
reportMemberChanges_b = False
self._tag_mgr = TagManager(self.config,
tags_filename = "entity-tags.tsv")
updateLogger = self._getUpdateLogger()
helper = self.githubHelper
# TODO: use real dateteimes (assuming strings)
if start_date == end_date:
date_range_str = start_date
else:
date_range_str = "%s-%s" % ( start_date, end_date )
# XXX allow caller to override defaults
dest_folder = os.path.join(os.environ["HOME"], "oompa", "discover")
out_path = os.path.join(dest_folder, "%s.discover.html" % date_range_str)
if not os.path.exists(dest_folder):
os.mkdir(dest_folder)
print("writing to: %s" % out_path)
# format_link = helper.getGithubURL
format_link = self.getHTMLAnchorText
self.out_stream = open(out_path, "w", encoding = 'utf8')
out_stream = self.out_stream
out_stream.write('<!DOCTYPE html>\n')
out_stream.write('<meta charset="utf-8">\n')
out_stream.write('<html>\n')
out_stream.write('<head>\n')
out_stream.write('<title>Tracker Discover Report - %s</title>\n' % ( date_range_str, ))
out_stream.write('</head>\n')
out_stream.write('<body>\n')
# XXX temp
out_stream.write('<pre>\n')
# TODO: if args, pass in a filter
updates = updateLogger.getUpdates(start_date = start_date,
end_date = end_date)
by_entity = updateLogger.organizeUpdatesByEntity(updates)
for entity_info in sorted(by_entity.keys()):
kind, name = entity_info
entityMetadata = EntityMetadata(kind, name, None)
# print("# %-40s (%s)" % ( entityMetadata.name, entityMetadata.kind ))
self.out_stream.write("%s - %s\n" % ( entityMetadata.kind, self.getHTMLAnchorText(entityMetadata.name), ))
self._showEntityTags(entityMetadata)
updates_for_entity = by_entity[entity_info]
# i'm not sure if i need kind and field, or just field
by_field = updateLogger.organizeUpdatesByField(updates_for_entity)
fields = sorted(by_field.keys())
for field in fields:
out_stream.write(" %s\n" % field)
out_stream.write("\n")
updates_for_field = by_field[field]
if field == "repoNames":
for update in updates_for_field:
repo_url = format_link(update["full_name"])
out_stream.write(" repo: %s\n" % repo_url)
if update.get("parent"):
out_stream.write(" forked: %s\n" % format_link(update["parent"]))
if update.get("source") != update.get("parent"):
out_stream.write(" source: %s\n" % format_link(update["source"]))
pass
pass
out_stream.write("\n")
# TODO: README
pass
pass
else:
for update in updates_for_field:
out_stream.write(" %-8s %s\n" % ( update["action"], format_link(update["full_name"]) ))
pass
out_stream.write("\n")
pass
pass
out_stream.write("\n")
pass
out_stream.write('</pre>\n')
out_stream.write('</body>\n')
out_stream.write('</html>\n')
if out_stream != sys.stdout:
out_stream.close()
pass
return
def removeEntities(self, entities):
"""entities is list of entity specs - user/...,
org[anization]/..., or un-qualified entity name
"""
return self.githubHelper.removeEntities(entities)
def close(self):
self.githubHelper.close()
if self._updateLogger is not None:
self._updateLogger.close()
return
pass
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] |
gwv/validators/illegal.py | kurgm/gwv | 1 | 55743 | <gh_stars>1-10
from gwv.dump import Dump
import gwv.filters as filters
from gwv.helper import isKanji
from gwv.helper import isYoko
from gwv.kagedata import KageData
from gwv.validators import Validator
from gwv.validators import ErrorCodes
error_codes = ErrorCodes(
UNKNOWN_STROKE_TYPE="0", # 未定義の筆画
TOO_FEW_COLUMNS="1", # 列不足
TOO_MANY_NONZERO_COLUMNS="2", # 列余分（非ゼロ）
TOO_MANY_ZERO_COLUMNS="3", # 列余分（ゼロ値）
WRONG_NUMBER_OF_COLUMNS="4", # 列数異常（99）
INVALID_DATA_0="5", # 不正なデータ（0）
UNKNOWN_STROKE_FORM="6", # 未定義の形状の組み合わせ
ALIAS_11_COLUMNS="7", # エイリアスに11列
VERTCONN_IN_HORI_LINE="10", # 横画に接続(縦)型
HORICONN_IN_VERT_LINE="11", # 縦画に接続(横)型
HORIZONTAL_ORE_FIRST="30", # 折れの前半が横
VERTICAL_ORE_LAST="31", # 折れの後半が縦
HORIZONTAL_OTSU_FIRST="40", # 乙の前半が横
LEFTWARD_OTSU_LAST="41", # 乙の後半が左向き
BUHIN_ICHI="9", # 部品位置
)
keijoKumiawase = {
tuple([int(x) for x in keijoStr.split(":")])
for keijoStr in (
"0:0:0,0:-1:-1,0:99:1,0:99:2,0:99:3,0:98:0,0:97:0,"
"1:0:0,1:0:13,1:0:2,1:0:23,1:0:24,1:0:313,1:0:32,1:0:4,1:12:0,1:12:13,"
"1:12:23,1:12:24,1:12:313,1:12:32,1:12:413,1:2:0,1:2:2,1:22:0,1:22:13,"
"1:22:23,1:22:24,1:22:313,1:22:32,1:22:4,1:22:413,1:32:0,1:32:13,"
"1:32:23,1:32:24,1:32:313,1:32:32,1:32:4,1:32:413,"
"2:0:5,2:0:7,2:12:7,2:22:4,2:22:5,2:22:7,2:32:4,2:32:5,2:32:7,2:7:0,"
"2:7:4,2:7:8,"
"3:0:0,3:0:5,3:12:0,3:12:5,3:22:5,3:32:0,3:32:5,"
"4:0:0,4:0:5,4:22:0,4:22:5,"
"6:0:5,6:0:7,6:12:7,6:22:4,6:22:5,6:22:7,6:32:4,6:32:5,6:32:7,6:7:0,"
"6:7:4,6:7:8,"
"7:0:7,7:12:7,7:32:7,"
"9:0:0"
",7:22:7,3:22:0,1:0:413" # グリフエディタではエラーになるが……
",2:27:0,6:27:0" # 屋根付き細入り
).split(",")
}
hikanjiKeijoKumiawase = {
tuple([int(x) for x in keijoStr.split(":")])
for keijoStr in [
"2:32:0", # 曲線、接続→右払い
"6:32:0", # 複曲線、接続→右払い
"2:32:8", # 曲線、接続→止め
"6:32:8" # 複曲線、接続→止め
]
}
# {筆画タイプ: データ列数}
datalens = {
1: 7,
2: 9,
3: 9,
4: 9,
6: 11,
7: 11,
9: 7
}
class IllegalValidator(Validator):
name = "illegal"
@filters.check_only(-filters.is_of_category({"user-owned"}))
def is_invalid(self, name: str, related: str, kage: KageData, gdata: str,
dump: Dump):
isKanjiGlyph = isKanji(name)
for line in kage.lines:
lendata = len(line.data)
stype = line.stroke_type
try:
sttType = line.head_type
except IndexError:
sttType = 0
try:
endType = line.tail_type
except IndexError:
endType = 0
coords = line.coords
if not isKanjiGlyph:
stype = stype % 100 if stype >= 0 else stype
sttType = sttType % 100 if sttType >= 0 else sttType
endType = endType % 100 if endType >= 0 else endType
if stype == 99:
if lendata not in (8, 11):
# 列数異常（99）
return [
error_codes.WRONG_NUMBER_OF_COLUMNS,
[line.line_number, line.strdata]]
if lendata == 11 and kage.is_alias:
# エイリアスに11列
return [
error_codes.ALIAS_11_COLUMNS,
[line.line_number, line.strdata]]
elif stype == 0:
if lendata not in (4, 7):
# 列数異常（0）
return [
error_codes.WRONG_NUMBER_OF_COLUMNS,
[line.line_number, line.strdata]]
else:
if stype not in datalens:
# 未定義の筆画
return [
error_codes.UNKNOWN_STROKE_TYPE,
[line.line_number, line.strdata]]
l = datalens[stype]
if lendata < l:
# 列不足
return [
error_codes.TOO_FEW_COLUMNS,
[line.line_number, line.strdata]]
if lendata > l:
if any(n != 0 for n in line.data[l:]):
# 列余分（非ゼロ）
return [
error_codes.TOO_MANY_NONZERO_COLUMNS,
[line.line_number, line.strdata]]
# 列余分（ゼロ値）
return [
error_codes.TOO_MANY_ZERO_COLUMNS,
[line.line_number, line.strdata]]
if stype == 0:
if (line.data[1] == 0 and line.data[3] != 0) or \
(line.data[1] == -1 and line.data[3] != -1):
# 不正なデータ（0）
return [
error_codes.INVALID_DATA_0,
[line.line_number, line.strdata]]
elif stype == 1:
if sttType in (2, 12, 22, 32) or \
endType in (2, 32, 13, 23, 24, 313, 413):
if isYoko(*coords[0], *coords[1]):
if sttType > 2 or endType > 2: # not in (0, 2)
# 横画に接続(縦)型
return [
error_codes.VERTCONN_IN_HORI_LINE,
[line.line_number, line.strdata]]
elif sttType == 2 or endType == 2:
# 縦画に接続(横)型
return [
error_codes.HORICONN_IN_VERT_LINE,
[line.line_number, line.strdata]]
elif stype == 9:
# 部品位置
return [
error_codes.BUHIN_ICHI, [line.line_number, line.strdata]]
elif stype == 2:
pass
elif stype == 3:
if isYoko(*coords[0], *coords[1]):
# 折れの前半が横
return [
error_codes.HORIZONTAL_ORE_FIRST,
[line.line_number, line.strdata]]
if line.tail_type == 5 and coords[2][0] - coords[1][0] == 0:
# 折れの後半が縦
return [
error_codes.VERTICAL_ORE_LAST,
[line.line_number, line.strdata]]
elif stype == 4:
if isYoko(*coords[0], *coords[1]):
# 乙の前半が横
return [
error_codes.HORIZONTAL_OTSU_FIRST,
[line.line_number, line.strdata]]
if line.tail_type == 5 and coords[2][0] - coords[1][0] <= 0:
# 乙の後半が左向き
return [
error_codes.LEFTWARD_OTSU_LAST,
[line.line_number, line.strdata]]
if stype != 99:
strokeKeijo = (stype, sttType, endType)
if strokeKeijo not in keijoKumiawase and (
isKanjiGlyph or
strokeKeijo not in hikanjiKeijoKumiawase):
# 未定義の形状の組み合わせ
return [
error_codes.UNKNOWN_STROKE_FORM,
[line.line_number, line.strdata]]
return False
def record(self, glyphname, error):
key = error[0]
if key not in self.results:
self.results[key] = []
self.results[key].append([glyphname, ":".join(
error[1][1].split(":", 3)[:3])] + error[1:])
def get_result(self):
for val in self.results.values():
val.sort(key=lambda r: r[1])
return super(IllegalValidator, self).get_result()
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cubi_tk/snappy/itransfer_common.py | LaborBerlin/cubi-tk | 0 | 145728 | <filename>cubi_tk/snappy/itransfer_common.py
"""Common code for ``cubi-tk snappy itransfer-*`` commands."""
import argparse
import datetime
import glob
import os
import typing
from ctypes import c_ulonglong
from multiprocessing import Value
from multiprocessing.pool import ThreadPool
from subprocess import check_output, SubprocessError, check_call, STDOUT
import sys
import attr
from biomedsheets import io_tsv, shortcuts
from biomedsheets.naming import NAMING_ONLY_SECONDARY_ID
from logzero import logger
from retrying import retry
import tqdm
from ..exceptions import MissingFileException
from ..common import check_irods_icommands, sizeof_fmt
#: Default number of parallel transfers.
DEFAULT_NUM_TRANSFERS = 8
@attr.s(frozen=True, auto_attribs=True)
class TransferJob:
"""Encodes a transfer job from the local file system to the remote iRODS collection."""
#: Source path.
path_src: str
#: Destination path.
path_dest: str
#: Number of bytes to transfer.
bytes: int
command: typing.Optional[str] = None
def to_oneline(self):
return "%s -> %s (%s) [%s]" % (self.path_src, self.path_dest, self.bytes, self.command)
@retry(wait_fixed=1000, stop_max_attempt_number=5)
def _wait_until_ils_succeeds(path):
check_output(["ils", path], stderr=STDOUT)
@retry(wait_fixed=1000, stop_max_attempt_number=5)
def irsync_transfer(job: TransferJob, counter: Value, t: tqdm.tqdm):
"""Perform one piece of work and update the global counter."""
mkdir_argv = ["imkdir", "-p", os.path.dirname(job.path_dest)]
logger.debug("Creating directory when necessary: %s", " ".join(mkdir_argv))
try:
check_output(mkdir_argv)
except SubprocessError as e: # pragma: nocover
logger.error("Problem executing imkdir: %s (probably retrying)", e)
raise
_wait_until_ils_succeeds(os.path.dirname(job.path_dest))
irsync_argv = ["irsync", "-a", "-K", job.path_src, "i:%s" % job.path_dest]
logger.debug("Transferring file: %s", " ".join(irsync_argv))
try:
check_output(irsync_argv)
except SubprocessError as e: # pragma: nocover
logger.error("Problem executing irsync: %s (probably retrying)", e)
raise
with counter.get_lock():
counter.value += job.bytes
t.update(counter.value)
def check_args(args):
"""Argument checks that can be checked at program startup but that cannot be sensibly checked with ``argparse``."""
def load_sheet_tsv(args):
"""Load sample sheet."""
logger.info(
"Loading %s sample sheet from %s.",
args.tsv_shortcut,
getattr(args.biomedsheet_tsv, "name", "stdin"),
)
load_tsv = getattr(io_tsv, "read_%s_tsv_sheet" % args.tsv_shortcut)
return load_tsv(args.biomedsheet_tsv, naming_scheme=NAMING_ONLY_SECONDARY_ID)
def load_sheets_tsv(args):
"""Load multiple sample sheets."""
result = []
for path in args.biomedsheet_tsv:
logger.info(
"Loading %s sample sheet from %s.",
args.tsv_shortcut,
getattr(args.biomedsheet_tsv, "name", "stdin"),
)
load_tsv = getattr(io_tsv, "read_%s_tsv_sheet" % args.tsv_shortcut)
result.append(load_tsv(path, naming_scheme=NAMING_ONLY_SECONDARY_ID))
return result
class SnappyItransferCommandBase:
"""Base class for itransfer commands."""
#: The command name.
command_name: typing.Optional[str] = None
#: The step folder name to create.
step_name: typing.Optional[str] = None
#: Whether or not to fix .md5 files on the fly.
fix_md5_files: bool = False
#: Whether to look into largest start batch in family.
start_batch_in_family: bool = False
def __init__(self, args):
#: Command line arguments.
self.args = args
@classmethod
def setup_argparse(cls, parser: argparse.ArgumentParser) -> None:
"""Setup common arguments for itransfer commands."""
parser.add_argument(
"--hidden-cmd", dest="snappy_cmd", default=cls.run, help=argparse.SUPPRESS
)
parser.add_argument(
"--num-parallel-transfers",
type=int,
default=DEFAULT_NUM_TRANSFERS,
help="Number of parallel transfers, defaults to %s" % DEFAULT_NUM_TRANSFERS,
)
parser.add_argument(
"--tsv-shortcut",
default="germline",
choices=("germline", "cancer"),
help="The shortcut TSV schema to use.",
)
parser.add_argument(
"--start-batch",
default=0,
type=int,
help="Batch to start the transfer at, defaults to 0.",
)
parser.add_argument(
"--base-path",
default=os.getcwd(),
required=False,
help="Base path of project (contains 'ngs_mapping/' etc.), defaults to current path.",
)
parser.add_argument(
"--remote-dir-date",
default=datetime.date.today().strftime("%Y-%m-%d"),
help="Date to use in remote directory, defaults to YYYY-MM-DD of today.",
)
parser.add_argument(
"--remote-dir-pattern",
default="{library_name}/%s/{date}" % cls.step_name,
help="Pattern to use for constructing remote pattern",
)
parser.add_argument(
"biomedsheet_tsv",
type=argparse.FileType("rt"),
help="Path to biomedsheets TSV file to load.",
)
parser.add_argument("irods_dest", help="path to iRODS collection to write to.")
@classmethod
def run(
cls, args, _parser: argparse.ArgumentParser, _subparser: argparse.ArgumentParser
) -> typing.Optional[int]:
"""Entry point into the command."""
return cls(args).execute()
def check_args(self, args):
"""Called for checking arguments, override to change behaviour."""
# Check presence of icommands when not testing.
if "pytest" not in sys.modules: # pragma: nocover
check_irods_icommands(warn_only=False)
res = 0
if not os.path.exists(args.base_path): # pragma: nocover
logger.error("Base path %s does not exist", args.base_path)
res = 1
return res
def _build_family_max_batch(self, sheet, batch_key, family_key):
family_max_batch = {}
for donor in sheet.bio_entities.values():
if batch_key in donor.extra_infos and family_key in donor.extra_infos:
family_id = donor.extra_infos[family_key]
batch_no = donor.extra_infos[batch_key]
family_max_batch[family_id] = max(family_max_batch.get(family_id, 0), batch_no)
return family_max_batch
def _batch_of(self, donor, family_max_batch, batch_key, family_key):
if batch_key in donor.extra_infos:
batch = donor.extra_infos[batch_key]
else:
batch = 0
if self.start_batch_in_family and family_key in donor.extra_infos:
family_id = donor.extra_infos[family_key]
batch = max(batch, family_max_batch[family_id])
return batch
def yield_ngs_library_names(
self, sheet, min_batch=None, batch_key="batchNo", family_key="familyId"
):
"""Yield all NGS library names from sheet.
When ``min_batch`` is given then only the donors for which the ``extra_infos[batch_key]`` is greater than
``min_batch`` will be used.
This function can be overloaded, for example to only consider the indexes.
"""
family_max_batch = self._build_family_max_batch(sheet, batch_key, family_key)
# Process all libraries and filter by family batch ID.
for donor in sheet.bio_entities.values():
if min_batch is not None:
batch = self._batch_of(donor, family_max_batch, batch_key, family_key)
if batch < min_batch:
logger.debug(
"Skipping donor %s because %s = %d < min_batch = %d",
donor.name,
batch_key,
batch,
min_batch,
)
continue
for bio_sample in donor.bio_samples.values():
for test_sample in bio_sample.test_samples.values():
for library in test_sample.ngs_libraries.values():
yield library.name
def build_base_dir_glob_pattern(
self, library_name: str
) -> typing.Tuple[str, str]: # pragma: nocover
"""Build base dir and glob pattern to append."""
raise NotImplementedError("Abstract method called!")
def build_jobs(self, library_names) -> typing.Tuple[TransferJob, ...]:
"""Build file transfer jobs."""
transfer_jobs = []
for library_name in library_names:
base_dir, glob_pattern = self.build_base_dir_glob_pattern(library_name)
glob_pattern = os.path.join(base_dir, glob_pattern)
logger.debug("Glob pattern for library %s is %s", library_name, glob_pattern)
for glob_result in glob.glob(glob_pattern, recursive=True):
rel_result = os.path.relpath(glob_result, base_dir)
real_result = os.path.realpath(glob_result)
if real_result.endswith(".md5"):
continue # skip, will be added automatically
elif not os.path.isfile(real_result):
continue # skip if did not resolve to file
remote_dir = os.path.join(
self.args.irods_dest,
self.args.remote_dir_pattern.format(
library_name=library_name, date=self.args.remote_dir_date
),
)
if not os.path.exists(real_result): # pragma: nocover
raise MissingFileException("Missing file %s" % real_result)
if (
not os.path.exists(real_result + ".md5") and not self.fix_md5_files
): # pragma: nocover
raise MissingFileException("Missing file %s" % (real_result + ".md5"))
for ext in ("", ".md5"):
try:
size = os.path.getsize(real_result + ext)
except OSError: # pragma: nocover
size = 0
transfer_jobs.append(
TransferJob(
path_src=real_result + ext,
path_dest=os.path.join(remote_dir, rel_result + ext),
bytes=size,
)
)
return tuple(sorted(transfer_jobs))
def _execute_md5_files_fix(
self, transfer_jobs: typing.Tuple[TransferJob, ...]
) -> typing.Tuple[TransferJob, ...]:
"""Create missing MD5 files."""
ok_jobs = []
todo_jobs = []
for job in transfer_jobs:
if not os.path.exists(job.path_src):
todo_jobs.append(job)
else:
ok_jobs.append(job)
total_bytes = sum([os.path.getsize(j.path_src[: -len(".md5")]) for j in todo_jobs])
logger.info(
"Computing MD5 sums for %s files of %s with up to %d processes",
len(todo_jobs),
sizeof_fmt(total_bytes),
self.args.num_parallel_transfers,
)
logger.info("Missing MD5 files:\n%s", "\n".join(map(lambda j: j.path_src, todo_jobs)))
counter = Value(c_ulonglong, 0)
with tqdm.tqdm(total=total_bytes, unit="B", unit_scale=True) as t:
if self.args.num_parallel_transfers == 0: # pragma: nocover
for job in todo_jobs:
compute_md5sum(job, counter, t)
else:
pool = ThreadPool(processes=self.args.num_parallel_transfers)
for job in todo_jobs:
pool.apply_async(compute_md5sum, args=(job, counter, t))
pool.close()
pool.join()
# Finally, determine file sizes after done.
done_jobs = [
TransferJob(
path_src=j.path_src,
path_dest=j.path_dest,
bytes=os.path.getsize(j.path_src),
command=j.command,
)
for j in todo_jobs
]
return tuple(sorted(done_jobs + ok_jobs))
def execute(self) -> typing.Optional[int]:
"""Execute the transfer."""
res = self.check_args(self.args)
if res: # pragma: nocover
return res
logger.info("Starting cubi-tk snappy %s", self.command_name)
logger.info(" args: %s", self.args)
sheet = load_sheet_tsv(self.args)
library_names = list(self.yield_ngs_library_names(sheet, min_batch=self.args.start_batch))
logger.info("Libraries in sheet:\n%s", "\n".join(sorted(library_names)))
transfer_jobs = self.build_jobs(library_names)
logger.debug("Transfer jobs:\n%s", "\n".join(map(lambda x: x.to_oneline(), transfer_jobs)))
if self.fix_md5_files:
transfer_jobs = self._execute_md5_files_fix(transfer_jobs)
total_bytes = sum([job.bytes for job in transfer_jobs])
logger.info(
"Transferring %d files with a total size of %s",
len(transfer_jobs),
sizeof_fmt(total_bytes),
)
counter = Value(c_ulonglong, 0)
with tqdm.tqdm(total=total_bytes, unit="B", unit_scale=True) as t:
if self.args.num_parallel_transfers == 0: # pragma: nocover
for job in transfer_jobs:
irsync_transfer(job, counter, t)
else:
pool = ThreadPool(processes=self.args.num_parallel_transfers)
for job in transfer_jobs:
pool.apply_async(irsync_transfer, args=(job, counter, t))
pool.close()
pool.join()
logger.info("All done")
return None
class IndexLibrariesOnlyMixin:
"""Mixin for ``SnappyItransferCommandBase`` that only considers libraries of indexes."""
def yield_ngs_library_names(
self, sheet, min_batch=None, batch_key="batchNo", family_key="familyId"
):
family_max_batch = self._build_family_max_batch(sheet, batch_key, family_key)
shortcut_sheet = shortcuts.GermlineCaseSheet(sheet)
for pedigree in shortcut_sheet.cohort.pedigrees:
donor = pedigree.index
if min_batch is not None:
batch = self._batch_of(donor, family_max_batch, batch_key, family_key)
if batch < min_batch:
logger.debug(
"Skipping donor %s because %s = %d < min_batch = %d",
donor.name,
batch_key,
donor.extra_infos[batch_key],
min_batch,
)
continue
yield donor.dna_ngs_library.name
@attr.s(frozen=True, auto_attribs=True)
class FileWithSize:
"""Pair of path with size."""
#: Path to file.
path: str
#: File size.
bytes: int
def compute_md5sum(job: TransferJob, counter: Value, t: tqdm.tqdm) -> None:
"""Compute MD5 sum with ``md5sum`` command."""
dirname = os.path.dirname(job.path_src)
filename = os.path.basename(job.path_src)[: -len(".md5")]
path_md5 = job.path_src
md5sum_argv = ["md5sum", filename]
logger.debug("Computing MD5sum %s > %s", " ".join(md5sum_argv), filename + ".md5")
try:
with open(path_md5, "wt") as md5f:
check_call(md5sum_argv, cwd=dirname, stdout=md5f)
except SubprocessError as e: # pragma: nocover
logger.error("Problem executing md5sum: %s", e)
logger.info("Removing file after error: %s", path_md5)
try:
os.remove(path_md5)
except OSError as e_rm: # pragma: nocover
logger.error("Could not remove file: %s", e_rm)
raise e
with counter.get_lock():
counter.value += os.path.getsize(job.path_src[: -len(".md5")])
t.update(counter.value)
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] |
faro/utils.py | cgiraldo/FARO | 0 | 27904 | import re
import gensim.utils as gensim_utils
def normalize_text_proximity(message):
""" Clean text of dots between words
Keyword arguments:
message -- a plain sentence or paragraph
"""
sent = message.lower()
sent = sent.replace("á", "a")
sent = sent.replace("é", "e")
sent = sent.replace("í", "i")
sent = sent.replace("ó", "o")
sent = sent.replace("ú", "u")
sent = re.sub(r'(?i)(?<=[a-z])\.(?=[a-z])', "", sent)
return sent
def clean_text(message):
""" Delete extra characters from text before validation
Keyword arguments:
message -- a plain sentence or paragraph
"""
sent = re.sub(r'[\-_*+,\(\).:]{1,}', "", message)
sent = re.sub(r'[ ]{1,}', "", sent)
sent = re.sub(r'(?i)\bnº', "", sent)
return sent
def preprocess_text(message):
""" Delete some artifacts from text
Keyword arguments:
message -- a plain sentence or paragraph
"""
uni_message = gensim_utils.to_unicode(message)
uni_message = uni_message.replace("\t", " ")
uni_message = uni_message.replace("\r\n", " ")
uni_message = uni_message.replace("\r", " ")
uni_message = uni_message.replace("\n", " ")
return uni_message
def word2features(sent, i):
""" Extract features of a node in the "sent" list for a CRF
Keyword arguments:
sent -- a list of triples <word, PoS tag, label>
i -- index of the node to extract the featues
"""
word = sent[i][0]
postag = sent[i][1]
features = {
'bias': 1.0,
'word': word,
'word.lower()': word.lower(),
'word.istitle()': word.istitle(),
'word[-3:]': word[-3:],
'word[:3]': word[:3],
'word.isdigit()': word.isdigit(),
'postag': postag,
}
if i > 0:
word1 = sent[i-1][0]
postag1 = sent[i-1][1]
features.update({
'-1:word': word1,
'-1:word.lower()': word1.lower(),
'-1:word.istitle': word1.istitle(),
'-1:postag': postag1,
})
else:
features['BOS'] = True
# EXTRA
if i > 2:
word1 = sent[i-2][0]
postag1 = sent[i-2][1]
features.update({
'-2:word': word1,
'-2:word.lower()': word1.lower(),
'-2:word.istitle': word1.istitle(),
'-2:word.postag': postag1,
})
if i > 3:
word1 = sent[i-3][0]
postag1 = sent[i-3][1]
features.update({
'-3:word': word1,
'-3:word.lower()': word1.lower(),
'-3:word.istitle': word1.istitle(),
'-3:word.postag': postag1,
})
if i > 2:
word0 = sent[i][0]
postag0 = sent[i][1]
word1 = sent[i-1][0]
postag1 = sent[i-1][1]
features.update({
'-01:word': word1 + word0,
'-01:word.lower()': (word1 + " " + word0).lower(),
'-01:word0_postag1': postag1 + word0,
'-01:word1_postag0': postag0 + word1,
})
if i > 3:
word0 = sent[i][0]
word1 = sent[i-2][0]
postag0 = sent[i][1]
postag1 = sent[i-2][1]
features.update({
'-02:word': word1 + word0,
'-02:word.lower()': (word1 + " " + word0).lower(),
'-02:word0_postag1': postag1 + word0,
'-02:word1_postag0': postag0 + word1,
})
if i < len(sent) - 2:
word1 = sent[i+2][0]
postag1 = sent[i+2][1]
features.update({
'+2:word': word1,
'+2:word.lower()': word1.lower(),
'+2:word.istitle': word1.istitle(),
'+2:word.postag': postag1,
})
if i < len(sent)-1:
word1 = sent[i+1][0]
postag1 = sent[i+1][1]
features.update({
'+1:word': word1,
'+1:word.lower()': word1.lower(),
'+1:word.istitle()': word1.istitle(),
'+1:postag': postag1,
})
else:
features['EOS'] = True
return features
def char2features_mail(sent, i):
""" Extract features of a node (for the mail CRF)
Keyword arguments:
sent -- a list of pairs <word, label>
i -- index of the node to extract the featues
"""
word = sent[i][0]
features = {
'bias': 1.0,
'char.lower()': word.lower(),
}
if i > 0:
word1 = sent[i-1][0]
features.update({
'-1:char.lower()': word1.lower(),
})
else:
features['BOS'] = True
if i < len(sent)-1:
word1 = sent[i+1][0]
features.update({
'+1:char.lower()': word1.lower(),
})
else:
features['EOS'] = True
# EXTRA
if i > 2:
word1 = sent[i-2][0]
features.update({
'-2:char.lower()': word1.lower(),
})
if i > 3:
word1 = sent[i-3][0]
features.update({
'-3:char.lower()': word1.lower(),
})
if i > 4:
word1 = sent[i-4][0]
features.update({
'-4:char.lower()': word1.lower(),
})
if i > 5:
word1 = sent[i-5][0]
features.update({
'-5:char.lower()': word1.lower(),
})
if i > 6:
word1 = sent[i-6][0]
features.update({
'-6:char.lower()': word1.lower(),
})
if i > 7:
word1 = sent[i-7][0]
features.update({
'-7:char.lower()': word1.lower(),
})
if i > 8:
word1 = sent[i-8][0]
features.update({
'-8:char.lower()': word1.lower(),
})
if i < len(sent) - 2:
word1 = sent[i+2][0]
features.update({
'+2:char.lower()': word1.lower(),
})
if i < len(sent) - 3:
word1 = sent[i+3][0]
features.update({
'+3:char.lower()': word1.lower(),
})
if i < len(sent) - 4:
word1 = sent[i+4][0]
features.update({
'+4:char.lower()': word1.lower(),
})
if i < len(sent) - 5:
word1 = sent[i+5][0]
features.update({
'+5:char.lower()': word1.lower(),
})
if i < len(sent) - 6:
word1 = sent[i+6][0]
features.update({
'+6:char.lower()': word1.lower(),
})
if i < len(sent) - 7:
word1 = sent[i+7][0]
features.update({
'+7:char.lower()': word1.lower(),
})
if i < len(sent) - 8:
word1 = sent[i+8][0]
features.update({
'+8:char.lower()': word1.lower(),
})
return features
def char2features_space(sent, i):
""" Extract features of a node (for the whitespace-CRF detector)
Keyword arguments:
sent -- a list of pairs <word, label>
i -- index of the node to extract the featues
"""
word = sent[i][0]
features = {
'bias': 1.0,
'char': word,
'char.lower()': word.lower(),
}
if i > 0:
word1 = sent[i-1][0]
features.update({
'-1:char': word1,
'-1:char.lower()': word1.lower(),
'-1:char.isdigit()': word1.isdigit(),
})
else:
features['BOS'] = True
if i < len(sent)-1:
word1 = sent[i+1][0]
features.update({
'+1:char': word1,
'+1:char.lower()': word1.lower(),
'+1:char.isdigit()': word1.isdigit(),
})
else:
features['EOS'] = True
# EXTRA
if i > 2:
word1 = sent[i-2][0]
features.update({
'-2:char': word1,
'-2:char.lower()': word1.lower(),
'-2:char.isdigit()': word1.isdigit(),
})
if i > 2:
word1 = sent[i-2][0]
word2 = sent[i-1][0]
features.update({
'-21:char.lower()': word1.lower() + word2.lower(),
'-21:char.isdigit()': word1.isdigit() and word2.isdigit(),
})
if i > 3:
word1 = sent[i-3][0]
features.update({
'-3:char': word1,
'-3:char.lower()': word1.lower(),
'-3:char.isdigit()': word1.isdigit(),
})
if i > 3:
word1 = sent[i-3][0]
word2 = sent[i-2][0]
features.update({
'-32:char.lower()': word1.lower() + word2.lower(),
'-32:char.isdigit()': word1.isdigit() and word2.isdigit(),
})
if i < len(sent) - 2:
word1 = sent[i+2][0]
features.update({
'+2:char': word1,
'+2:char.lower()': word1.lower(),
'+2:char.isdigit()': word1.isdigit(),
})
if i < len(sent) - 2:
word1 = sent[i+1][0]
word2 = sent[i+2][0]
features.update({
'+21:char.lower()': word1.lower() + word2.lower(),
'+21:char.isdigit()': word1.isdigit() and word2.isdigit(),
})
if i < len(sent) - 3:
word1 = sent[i+3][0]
features.update({
'+3:char': word1,
'+3:char.lower()': word1.lower(),
'+3:char.isdigit()': word1.isdigit(),
})
if i < len(sent) - 3:
word1 = sent[i+2][0]
word2 = sent[i+3][0]
features.update({
'+32:char.lower()': word1.lower() + word2.lower(),
'+32:char.isdigit()': word1.isdigit() and word2.isdigit(),
})
if i < len(sent) - 3:
word0 = sent[i][0]
word1 = sent[i+1][0]
word2 = sent[i+2][0]
features.update({
'+02:lower()': (word0 + word1 + word2).lower(),
'+02:isdigit()': (word0 + word1 + word2).isdigit(),
})
return features
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htvlearn/plots/base_plot.py | joaquimcampos/HTV-Learn | 1 | 1611972 | <gh_stars>1-10
import os
import copy
import numpy as np
import plotly.graph_objects as go
import plotly.io as pio
import matplotlib.cm as cm
from htvlearn.data import Data
class BasePlot():
colorscale = 'coolwarm' # default colorscale
def __init__(self,
data_obj=None,
log_dir=None,
**kwargs):
"""
Args:
data_obj (Data):
None (if not plotting data samples) or
object of class Data (see htvlearn.data).
log_dir (str):
Log directory for html images. If None, the images are only
shown but not saved in html format.
"""
self.data = data_obj
self.log_dir = log_dir
if self.log_dir is not None and not os.path.isdir(self.log_dir):
raise NotADirectoryError(
f'log_dir "{self.log_dir}" is not a valid directory')
def verify_data_obj(self):
"""Verify that a data object exists and is valid"""
if self.data is None:
raise ValueError('A data object does not exist.')
elif not isinstance(self.data, Data):
raise ValueError(f'data_obj is of type {type(self.data)}.')
@classmethod
def map_val2color(cls, val, vmin, vmax, colorscale=None):
"""
Map a value to a color in the colormap.
Args:
val (float):
value in [vmin, vmax] to map to color.
vmin, vmax (float):
min and max ranges for val.
colorscale (str):
matplotlib colorscale or None (use default).
Returns:
rgb color.
"""
colorsc = colorscale if colorscale is not None else cls.colorscale
cmap = cm.get_cmap(colorsc)
if vmin > vmax:
raise ValueError('incorrect relation between vmin and vmax')
t = 0.
if not np.allclose(vmin, vmax):
t = (val - vmin) / float((vmax - vmin)) # normalize val
R, G, B, alpha = cmap(t)
return 'rgb(' + '{:d}'.format(int(R * 255 + 0.5)) + ',' + '{:d}'\
.format(int(G * 255 + 0.5)) +\
',' + '{:d}'.format(int(B * 255 + 0.5)) + ')'
@classmethod
def map_val2color2d(cls, val, vmin, vmax):
"""
Map a 2D value to an rgb color. The R and G channels have
an independent and direct correspondence to each element in
the 2D value. The B channel is kept fixed.
Args:
val (float):
value s.t. val[i] in [vmin[i], vmax[i]], i=1,2,
to be mapped to an rgb color. The R, G channels are set
by val.
vmin, vmax (2d array):
min and max ranges for each element in val.
Returns:
rgb color.
"""
if vmin[0] > vmax[0] or vmin[1] > vmax[1]:
raise ValueError('incorrect relation between vmin and vmax')
t = np.zeros(2)
# normalize val
if not np.allclose(vmin[0], vmax[0]):
t[0] = (val[0] - vmin[0]) / float((vmax[0] - vmin[0]))
if not np.allclose(vmin[1], vmax[1]):
t[1] = (val[1] - vmin[1]) / float((vmax[1] - vmin[1]))
R, G = t[1], t[0]
B = 0.4
return 'rgb(' + '{:d}'.format(int(R * 255 + 0.5)) + ',' + '{:d}'\
.format(int(G * 255 + 0.5)) +\
',' + '{:d}'.format(int(B * 255 + 0.5)) + ')'
@classmethod
def map_array2color(cls, array, min=None, max=None):
"""
Map an array of values to colors.
Args:
array (1d array):
array of values to map to colors. size: (N,)
min, max (float):
If not None, set the ranges for the values in array.
Returns:
1d array of rgb colors. size: (N,)
"""
if min is None:
min = array.min()
if max is None:
max = array.max()
return np.array([cls.map_val2color(val, min, max) for val in array])
@classmethod
def map_array2color2d(cls, array, min=None, max=None):
"""
Map a 2D array of values to colors.
Args:
array (2d array):
array of values to map to colors. size: (N x 2).
min, max (2d array):
If not None, sets the ranges for the values in array.
Returns:
1d array of rgb colors. size: (N,)
"""
if array.shape[1] != 2:
raise ValueError(f"array has shape {array.shape}.")
if min is None:
if min.shape != (2, ):
raise ValueError(f'min has shape {min.shape}')
min = array.amin(axis=0)
if max is None:
if max.shape != (2, ):
raise ValueError(f'max has shape {max.shape}')
max = array.amax(axis=0)
return np.array([cls.map_val2color2d(val, min, max) for val in array])
@classmethod
def get_normal_facecolor(cls, affine_coeff, max=None):
"""
Get facecolor of simplices according to their normals.
Args:
affine_coeff (array):
affine coefficients of the simplices.
size: (number of simplices, 3).
max (2d array):
If not None, sets the max ranges for the values in
affine_coeff[:, 0:2].
Returns:
facecolor (1d array):
1d array of rgb colors whose size is the number of simplices.
"""
if not affine_coeff.shape[1] == 3:
raise ValueError(f"affine_coeff has shape {affine_coeff.shape}.")
if max is None:
max = np.array([1.75, 1.75])
facecolor = \
cls.map_array2color2d(-affine_coeff[:, 0:2], min=-max, max=max)
return facecolor
@staticmethod
def get_scatter3d(x, y, z, marker_size=2):
r"""
Get a scatter 3D plot (f: \R^2 \to \R)
Args:
x, y (1d array):
positions of the samples.
z (1d array):
values of the samples.
Returns:
A plotly.graph_objects.Scatter3D object.
"""
data = go.Scatter3d(x=x,
y=y,
z=z,
mode='markers',
marker=dict(size=marker_size,
color='black'),
opacity=0.8)
return data
def plot_fig(self,
fig,
filename=None,
num_subplots=1,
view=None,
**kwargs):
"""
Plot figure.
Args:
fig:
instance of plotly.graph_objects.Figure to plot.
filename (str):
Figure filename.
num_subplots (int):
Number of figure subplots.
view (str):
If None, a default view is used.
Otherwise can be set to "up" "side".
"""
assert isinstance(fig, go.Figure), f'fig is of type {type(fig)}.'
assert view in [None, 'up', 'side'], f'view "{view}" is invalid.'
ax_dict = dict(linecolor='#000000',
linewidth=4,
showgrid=False,
showticklabels=False,
tickfont=dict(size=15),
gridcolor='#000000',
gridwidth=0.3,
title='',
showbackground=True)
fig_dict = dict(
scene_aspectmode='data',
scene=dict(xaxis=copy.deepcopy(ax_dict),
yaxis=copy.deepcopy(ax_dict),
zaxis=copy.deepcopy(ax_dict),
camera=dict(up=dict(x=0, y=0, z=1),
center=dict(x=0, y=0, z=0))),
font=dict(size=20),
)
fig_dict['scene']['xaxis']['title'] = 'x'
fig_dict['scene']['yaxis']['title'] = 'y'
fig_dict['scene']['zaxis']['title'] = 'z'
if view == 'up':
fig_dict['scene']['zaxis']['visible'] = False
fig_dict['scene']['camera']['eye'] = dict(x=0, y=0, z=3)
fig_dict['scene']['camera']['up'] = dict(x=0, y=1, z=0)
elif view == 'side':
fig_dict['scene']['camera']['eye'] = dict(x=1.2, y=0.3, z=0.4)
else:
# default
fig_dict['scene']['camera']['eye'] = dict(x=1.5, y=1.9, z=1.7)
for i in range(2, num_subplots + 1):
fig_dict['scene' + str(i)] = fig_dict['scene'].copy()
fig.update_layout(**fig_dict)
if self.log_dir is None:
fig.show()
else:
self.export_fig(fig, filename, self.log_dir)
@staticmethod
def export_fig(fig, filename, log_dir):
"""
Plot html figure and export to log_dir.
Args:
fig:
instance of plotly.graph_objects.Figure to plot.
filename (str):
Figure filename.
log_dir (str):
Log directory where figure is exported to.
"""
assert isinstance(fig, go.Figure), f'fig is of type {type(fig)}.'
if not os.path.isdir(log_dir):
raise NotADirectoryError(
f'log_dir "{log_dir}" is not a valid directory')
file_path = os.path.join(f'{log_dir}', f'{filename}')
pio.write_html(fig, file=f'{file_path}.html', auto_open=True)
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] |
examples/color_example.py | plezmo/python-sdk-examples | 0 | 132051 | # Copyright (c) 2019 Gunakar Pvt Ltd
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted (subject to the limitations in the disclaimer
# below) 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 Gunakar Pvt Ltd/Plezmo 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 must only be used with Plezmo elements manufactured by
# Gunakar Pvt Ltd.
# * Any software provided in binary or object form under this license must not be
# reverse engineered, decompiled, modified and/or disassembled.
# NO EXPRESS OR IMPLIED LICENSES TO ANY PARTY'S PATENT RIGHTS ARE GRANTED BY
# THIS LICENSE. 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.
# Tests functionality of light element
import time
import traceback
from plezmo import *
from plezmo.utils.logger import Logger
from plezmo.elements.element_types import PlezmoElementType
from plezmo.elements.plezmo_color import *
import utils
logger = Logger()
def globalExceptionHandler(e):
logger.info("###### Got exception {}".format(e))
# Init bluetooth communication
def init(color_name):
# Register global exception handler
registerExceptionHandler(globalExceptionHandler)
# Elements to connect
elementList = [{"name" : color_name, "type": PlezmoElementType.COLOR}]
connectedElements = []
try:
# connect to elements one by one
for e in elementList:
plezmoApi.connect(e["name"], e["type"])
# keep track of connected elements
connectedElements.append(e["name"])
return True
except Exception as e:
# Disconnect and stop program if connection to element fails
logger.error("Failed to connect to element, ex {}".format(e))
#traceback.print_exc()
# Disconnect already connected elements
for e in connectedElements:
plezmoApi.disconnect(e["name"])
return False
# Main logic of the program
def main(color_name):
# Init bluetooth communication
success = init(color_name)
if success != True:
# Bluetooth communication cannobe enabled, quit.
plezmoApi.close()
logger.error("Could not connect to all the required elements")
return
# Register event handlers
try:
# Event handler to call when color sensor detects GREEN color
Color.onColorChange(color_name, green_handler, ColorSensorColor.GREEN)
# Event handler to call when color sensor detects RED color
Color.onColorChange(color_name, red_handler, ColorSensorColor.RED)
logger.info("Event handlers for color detection registered. Take the Color sensor in front of RED/GREEN color to see the event handlers working.")
time.sleep(10)
# Event handler to call when color sensor detects darkness
Color.onLightEvent(color_name, darkness_handler, ColorSensorLightState.DARK)
# Event handler to call when color sensor detects brightness
Color.onLightEvent(color_name, brightness_handler, ColorSensorLightState.BRIGHT)
logger.info("Event handlers darkness/brightness detection registered. Take the Color sensor to dark/bright locations to see the event handlers working.")
time.sleep(10)
comp = Color.getLightValueLux(color_name)
logger.info("Light lux value is {}".format(comp))
comp = Color.getLightComponentValueInLux(color_name, LightComponent.GREEN)
logger.info("Green component is {}".format(comp))
light = Color.getLightValuePercent(color_name)
logger.info("Detected light value in percent is {}".format(light))
logger.info("Checking getColor() functionality. Keep the color sensor facing any basic color")
time.sleep(5)
color = Color.getColor(color_name)
logger.info("Detected color is {}".format(color))
logger.info("Waiting for color change, change color in front of color element to different colors")
Color.waitForColorChange(color_name)
logger.info("Color changed")
logger.info("Waiting for color to change to RED. Bring RED color in front of color element.")
Color.waitForColorToChangeTo(color_name, ColorSensorColor.RED)
logger.info("Color changed to RED")
time.sleep(5)
logger.info("Waiting for DARK. Take color element to dark location.")
Color.waitForLightEvent(color_name, ColorSensorLightState.DARK)
logger.info("It is dark")
time.sleep(2)
except Exception as e:
logger.error("Failed to run Color commands {}, ex {}".format(color_name, e))
#traceback.print_exc()
finally:
# Program completed, disconnect elements and quit
plezmoApi.disconnect(color_name)
time.sleep(1)
plezmoApi.close()
# Event handler whenever color sensor detects GREEN color
@PlezmoEventHandler
def green_handler():
logger.info("Got green color change event")
# Event handler whenever color sensor detects RED color
@PlezmoEventHandler
def red_handler():
logger.info("Got red color change event")
# Event handler whenever color sensor detects darkness
@PlezmoEventHandler
def darkness_handler():
logger.info("Got darkness event")
# Event handler whenever color sensor detects brightness
@PlezmoEventHandler
def brightness_handler():
logger.info("Got brightness event")
# Program starts here
if __name__ == "__main__":
color_name = utils.extract_element_name()
if color_name == None:
logger.error("Color element name is mandatory, e.g. # python color_example.py Color")
else:
main(color_name) | [
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] |
codeferm/observer.py | Kulanx/sleeping_quality_evaluator | 64 | 1605629 | <reponame>Kulanx/sleeping_quality_evaluator<filename>codeferm/observer.py<gh_stars>10-100
"""
Created on Apr 14, 2017
@author: sgoldsmith
Copyright (c) <NAME>
All rights reserved.
"""
class observer(object):
"""A class of thing that observes an Observable.
The Observable will call the Observer"s observeEvent() method.
"""
def observeEvent(self, **kwargs):
raise NotImplementedError("Please override in the derived class")
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snn_lib/optimizers.py | zhongyuchen/snn-iir | 5 | 85796 | <reponame>zhongyuchen/snn-iir<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
# File Name : optimizers.py
# Author: <NAME>
# Email: <EMAIL>
# Description: optimizers.
"""
import torch
import omegaconf
from omegaconf import OmegaConf
def get_optimizer(params, conf):
optimizer_conf = conf['optimizer']
optimizer_choice = optimizer_conf['optimizer_choice']
if optimizer_choice == 'Adam':
lr = optimizer_conf['Adam']['lr']
print('optimizer:', optimizer_conf['optimizer_choice'], 'lr:', lr)
return torch.optim.Adam(params, lr)
elif optimizer_choice == 'AdamW':
lr = optimizer_conf['AdamW']['lr']
print('optimizer:', optimizer_conf['optimizer_choice'], 'lr:', lr)
return torch.optim.AdamW(params, lr)
elif optimizer_choice == 'SGD':
lr = lr = optimizer_conf['SGD']['lr']
print('optimizer:', optimizer_conf['optimizer_choice'], 'lr:', lr)
return torch.optim.SGD(params, lr)
else:
raise Exception('optimizer', optimizer_conf['optimizer_choice'] ,'not implemented.')
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] |
essentials_kit_management/tests/interactors/test_get_pay_through_details_interactor.py | RajeshKumar1490/iB_hubs_mini_project | 0 | 187132 | <gh_stars>0
from mock import create_autospec
from essentials_kit_management.interactors.\
get_pay_through_details_interactor import GetPayThroughDetailsInteractor
from essentials_kit_management.interactors.storages.storage_interface \
import StorageInterface
from essentials_kit_management.interactors.presenters.presenter_interface \
import PresenterInterface
def test_get_pay_through_details_interactor_returns_upi_id():
#Arrange
storage = create_autospec(StorageInterface)
presenter = create_autospec(PresenterInterface)
interactor = GetPayThroughDetailsInteractor(
storage=storage, presenter=presenter
)
mock_upi_id = "8247088772@SBI"
mock_presenter_response = {'upi_id': mock_upi_id}
storage.get_upi_id.return_value = mock_upi_id
presenter.get_pay_through_details_response.return_value = \
mock_presenter_response
#Act
upi_id_response = interactor.get_pay_through_details()
#Assert
assert upi_id_response == mock_presenter_response
storage.get_upi_id.assert_called_once()
presenter.get_pay_through_details_response.assert_called_once_with(
upi_id=mock_upi_id
)
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] |
l3ns/swarm/subnet.py | rukmarr/l3ns | 3 | 72336 | from .. import ldc
from .node import SwarmNode
class SwarmSubnet(ldc.DockerSubnet):
def __init__(self, *args, size: int = 510, **kwargs):
self._cluster_hosts = {}
self._offset = size
super().__init__(*args, size=size*2, **kwargs)
def add_node(self, node: 'SwarmNode'):
ip_address = self._get_host_ip()
# docker swarm overlay requires additional ip address for lode balancer each cluster node (cluster_host in l3ns)
if not isinstance(node, ldc.DockerNode) and node.cluster_host.address not in self._hosts:
self._cluster_hosts[node.cluster_host.address] = self._hosts.pop(0)
self._nodes_dict[ip_address] = node
if node not in self._network:
self._network.add_node(node)
node.add_interface(ip_address, self)
def _get_host_ip(self):
# Since we don't have control over ip management for lode balancers, first free ip of the docker network
# ip range will be used for each swarm node. Since it's not possible to control starting order of the nodes,
# it's easier to just make network twice as large and give out addresses only from the second half
return str(self._hosts.pop(self._offset+1))
def start(self):
if self.started:
return self.docker_network
self.docker_network = self._client.networks.create(
self.name,
driver='overlay',
attachable=True,
ipam=self._make_ipam_config())
if not self.docker_network.attrs['Driver']:
raise Exception('Error: IPAM customisation failed for swarm network {}, check if other networks overlap ip pool'.format(self.name))
self.started = True
self.loaded = True
print('[swarm] subnet', self.name, 'started')
return self.docker_network
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] |
ABC/206/a_1.py | fumiyanll23/AtCoder | 0 | 100195 | def main():
# input
N = int(input())
# compute
N = int(1.08*N)
# output
if N < 206:
print('Yay!')
elif N == 206:
print('so-so')
else:
print(':(')
if __name__ == '__main__':
main()
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OpenCV/Histogramas/h6.py | matewszz/Python | 0 | 31235 | <reponame>matewszz/Python
import dlib
import cv2
image = cv2.imread("../testeOpenCV.jpg")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
hogFaceDetector = dlib.get_frontal_face_detector()
faces = hogFaceDetector(gray, 1)
for (i, rect) in enumerate(faces):
x = rect.left()
y = rect.top()
w = rect.right() - x
h = rect.bottom() - y
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Image", image)
k = cv2.waitKey() | [
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dash_docs/chapters/dash_vtk/click_hover/index.py | wesleyacheng/dash-docs | 379 | 103544 | import dash_html_components as html
import dash_vtk
from dash_docs import tools
from dash_docs import styles
from dash_docs import reusable_components as rc
examples = tools.load_examples(__file__)
layout = html.Div([
rc.Markdown('''
# Click and Hover Callbacks
It's possible to create callbacks based on user clicks and hovering. First, you need to specify the `pickingModes` prop in
`dash_vtk.View` to be a list of modes you want to capture. The following values are accepted:
* `"click"`
* `"hover"`
Afterwards, you need to create callbacks where the inputs and states include one of the following read-only properties of `dash_vtk.View`.
* `clickInfo`: Called when the user clicks on an object.
* `hoverInfo`: Called when the user hovers over an object.
> The full documentation for `dash_vtk.View` can be found in the [API reference](/vtk/reference).
## Callback structure
You can notice that the `clickInfo` or `hoverInfo` data will be a dictionary with various keys describing the picked object. The keys include:
* `displayPosition`: The x,y,z coordinate with on the user's screen.
* `ray`: A line between two points in 3D space (xyz1, xyz2) that represent the mouse position. It covers the full space under the 2D mouse position.
* `representationId`: The ID assigned to the `dash_vtk.GeometryRepresentation` containing your object.
* `worldPosition`: The x, y, z coordinates in the 3D environment that you are rendering where the ray hit the object. It corresponds to the 3D coordinate on the surface of the object under your mouse.
'''),
rc.Markdown('''
## Output `clickInfo` to `html.Pre`
The following example shows you how to concisely display the output of `clickInfo` inside an `html.Pre`:
'''),
html.Details(open=False, children=[
html.Summary('View full code'),
rc.Markdown(
examples['t07_click_info.py'][0],
style=styles.code_container
),
]),
html.Div(
examples['t07_click_info.py'][1],
className='example-container'
),
rc.Markdown('''
## Update representation state with `hoverInfo`
You can also construct more complex hover callbacks, which would affect the `actor` and `state` of your geometry representations.
In the [terrain mesh demo](https://dash-gallery.plotly.host/dash-vtk-explorer/pyvista-terrain-following-mesh), whenever you hover
over the surface, a callback is fired and the output is displayed on your screen:
The full code can be found [here](https://github.com/plotly/dash-vtk/tree/master/demos/pyvista-terrain-following-mesh), but the
following snippet summarizes what is needed to capture hover events in the image above:
```py
# ...
vtk_view = dash_vtk.View(
id="vtk-view",
pickingModes=["hover"],
children=[
dash_vtk.GeometryRepresentation(id="vtk-representation", ...),
dash_vtk.GeometryRepresentation(
id="pick-rep",
children=[
dash_vtk.Algorithm(id="pick-sphere", ...)
],
# ...
),
],
)
app.layout = html.Div([
# ...,
vtk_view,
# ...
])
@app.callback(
[
Output("tooltip", "children"),
Output("pick-sphere", "state"),
Output("pick-rep", "actor"),
],
[Input("vtk-view", "clickInfo"), Input("vtk-view", "hoverInfo")],
)
def onInfo(clickData, hoverData):
info = hoverData if hoverData else clickData
if info:
if (
"representationId" in info
and info["representationId"] == "vtk-representation"
):
return (
[json.dumps(info, indent=2)],
{"center": info["worldPosition"]},
{"visibility": True},
)
return dash.no_update, dash.no_update, dash.no_update
return [""], {}, {"visibility": False}
```
You can also use `hoverInfo` to update the state of another geometry representation. The image below shows how to update a cone position, orientation and size in order to probe the race car object:
Learn more by reading the [source code](https://github.com/plotly/dash-sample-apps/tree/master/apps/dash-vehicle-geometry) or trying out the [Vehicle Geometry app](https://dash-gallery.plotly.host/dash-vehicle-geometry/).
'''),
])
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] |
braistow method.py | pramotharun/Numerical-Methods-with-Python | 0 | 161634 | <gh_stars>0
#Bairstow Method
import numpy as np
n = int(input("Degree of polynomial"))
p = float(input("P value"))
q = float(input("q value"))
no_iterations = int(input("number of iterations"))
a = np.zeros((n+2,1))
b = np.zeros((n+2,1))
c = np.zeros((n+2,1))
j = n+1
for i in range(n+1):
a[i] = float(input("Enter coefficients of a:"))
for x in range(no_iterations):
#setting initial values for b:
b[0]= 0
b[1]=a[0]
for k in range(n+2):
if k==0 or k==1:
pass
else:
b[k]=a[k-1]-(p*b[k-1])-(q*b[k-2])
#setting initial values for c:
c[0]= 0
c[1]=b[1]
for m in range(n+2):
if m==0 or m==1:
pass
else:
c[m]=b[m]-(p*c[m-1])-(q*c[m-2])
print("a:\n")
print(np.transpose(a) )
print("\n")
print("-p*b\n")
print(-p*np.transpose(b))
print("\n")
print("-q*b\n")
print(-q*np.transpose(b) )
print("\n")
print("b:\n")
print(np.transpose(b) )
print("\n")
print("-p*c\n")
print(-p*np.transpose(c) )
print("\n")
print("-q*c\n")
print(-q*np.transpose(c) )
print("\n")
print("c:\n")
print(np.transpose(c) )
print("\n")
print("dp=")
dp = ((b[j-1]*c[j-2])-b[j]*c[j-3])/((c[j-2]*c[j-2])-c[j-3]*(c[j-1]-b[j-1]))
print(dp )
print("\n")
print("dq=")
dq = ((b[j]*c[j-2])-b[j-1]*(c[j-1]-b[j-1]))/((c[j-2]*c[j-2])-c[j-3]*(c[j-1]-b[j-1]))
print(dq )
print("\n")
p = p + dp
q = q + dq
print("newp=")
print(p )
print("\n")
print("newq=")
print(q )
print("\n")
print("____________next iteration__________________")
print("\n")
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python_plot.py | prusinski/NU_REU_git_NZP | 0 | 114202 | <filename>python_plot.py
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
#plot exponential curve from 0 to 2pi
t = np.linspace(0,2*np.pi,100)
plt.plot(t,np.exp(t),'m', label = 'Exponential Curve')
plt.title('Plot of $e^x$')
plt.xlabel('t (s)')
plt.ylabel('$y(t)$')
plt.legend()
plt.grid()
plt.text(2.5,0.25,'This is a \nExponential Curve!', fontsize = 16)
plt.text(1,-0.5,'Cool!', fontsize = 16)
plt.show()
| [
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day 12/Martijn - Python/passage_pathing.py | AE-nv/aedvent-code-2021 | 1 | 175111 | def append_node_to_dict(node1, node2, dict_connections):
if not node1 in dict_connections:
dict_connections[node1] = [node2]
else:
node_connections = dict_connections[node1]
if not node2 in node_connections:
node_connections.append(node2)
dict_connections[node1] = node_connections
return dict_connections
def parse_connections(connection, dict_connections):
splitted = connection.split('-')
node1 = splitted[0]
node2 = splitted[1]
dict_connections = append_node_to_dict(node1, node2, dict_connections)
dict_connections = append_node_to_dict(node2, node1, dict_connections)
return dict_connections
def find_paths(start, length, dict_connections, paths):
for path in paths:
last_node = path[-1]
def can_visit(node, path):
check = False
if node.isupper():
check = True
elif not node in path:
check = True
elif node.islower() and node != 'end' and node != 'start':
lowercase_nodes = [node for node in path if node.islower()]
set_lowercase_nodes = set(lowercase_nodes)
if (len(lowercase_nodes) == len(set_lowercase_nodes)):
check = True
return check
def find_paths(graph, start, end, path=[]):
path = path + [start]
if start == end:
return [path]
paths = []
for node in graph[start]:
if can_visit(node, path):
newpaths = find_paths(graph, node, end, path)
for newpath in newpaths:
paths.append(newpath)
return paths
if __name__ == '__main__':
input = open('./day 12/Martijn - Python/input.txt').readlines()
connections = [line.strip() for line in input]
dict_connections = {}
for x in range(0, len(connections)):
dict_connections = parse_connections(connections[x], dict_connections)
paths = find_paths(dict_connections, 'start', 'end')
print(len(paths)) | [
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NasUnet/util/datasets/__init__.py | mlvc-lab/Segmentation-NAS | 4 | 135180 | <gh_stars>1-10
from torchvision.datasets import *
from .base import *
from .coco import COCOSegmentation
from .ade20k import ADE20KSegmentation
from .pascal_voc import VOCSegmentation
from .pascal_aug import VOCAugSegmentation
from .pcontext import ContextSegmentation
from .minc import MINCDataset
from .ultrasound_nerve import UltraNerve
from .bladder import Bladder
from .chaos import CHAOS
from .promise12 import Promise12
from .camvid import CamVid
datasets = {
'coco': COCOSegmentation,
'ade20k': ADE20KSegmentation,
'pascal_voc': VOCSegmentation,
'pascal_aug': VOCAugSegmentation,
'pcontext': ContextSegmentation,
'minc': MINCDataset,
'cifar10': CIFAR10,
'ultrasound_nerve': UltraNerve,
'bladder': Bladder,
'chaos' : CHAOS,
'promise12': Promise12,
'camvid': CamVid
}
acronyms = {
'coco': 'coco',
'pascal_voc': 'voc',
'pascal_aug': 'voc',
'pcontext': 'pcontext',
'ade20k': 'ade',
'citys': 'citys',
'minc': 'minc',
'cifar10': 'cifar10',
'ultrasound_nerve': 'ultrasound_nerve',
'bladder': 'bladder',
'chaos': 'chaos',
'promise12': 'promise12',
'camvid': 'camvid'
}
dir = '/train_tiny_data/imgseg/'
#=
#dir = '../../../training_data/imageSeg/'
def get_dataset(name, path=dir, **kwargs):
return datasets[name.lower()](root = path, **kwargs)
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compare_mt/sign_utils.py | maks5507/compare-mt | 401 | 1615077 | ########################################################################################
# Compare two systems using bootstrap resampling #
# adapted from https://github.com/neubig/util-scripts/blob/master/paired-bootstrap.py #
# #
# See, e.g. the following paper for references #
# #
# Statistical Significance Tests for Machine Translation Evaluation #
# <NAME> #
# http://www.aclweb.org/anthology/W04-3250 #
# #
########################################################################################
import numpy as np
def eval_with_paired_bootstrap(ref, outs, src,
scorer,
compare_directions=[(0, 1)],
num_samples=1000, sample_ratio=0.5,
cache_stats=None):
"""
Evaluate with paired boostrap.
This compares several systems, performing a signifiance tests with
paired bootstrap resampling to compare the accuracy of the specified systems.
Args:
ref: The correct labels
outs: The output of systems
src: The source corpus
scorer: The scorer
compare_directions: A string specifying which two systems to compare
num_samples: The number of bootstrap samples to take
sample_ratio: The ratio of samples to take every time
cache_stats: The precomputed statistics
Returns:
A tuple containing the win ratios, statistics for systems
"""
sys_scores = [[] for _ in outs]
wins = [[0, 0, 0] for _ in compare_directions] if compare_directions is not None else None
n = len(ref)
ids = list(range(n))
if cache_stats is None:
cache_stats = [scorer.cache_stats(ref, out, src=src) for out in outs]
sample_size = int(n*sample_ratio)
for _ in range(num_samples):
# Subsample the gold and system outputs (with replacement)
reduced_ids = np.random.choice(ids, size=sample_size, replace=True)
# Calculate accuracy on the reduced sample and save stats
if cache_stats[0]:
sys_score, _ = zip(*[scorer.score_cached_corpus(reduced_ids, cache_stat) for cache_stat in cache_stats])
else:
reduced_ref = [ref[i] for i in reduced_ids]
reduced_outs = [[out[i] for i in reduced_ids] for out in outs]
reduced_src = [src[i] for i in reduced_ids]
sys_score, _ = zip(*[scorer.score_corpus(reduced_ref, reduced_out, reduced_src) for reduced_out in reduced_outs])
if wins is not None:
for i, compare_direction in enumerate(compare_directions):
left, right = compare_direction
if sys_score[left] > sys_score[right]:
wins[i][0] += 1
if sys_score[left] < sys_score[right]:
wins[i][1] += 1
else:
wins[i][2] += 1
for i in range(len(outs)):
sys_scores[i].append(sys_score[i])
# Print win stats
wins = [[x/float(num_samples) for x in win] for win in wins] if wins is not None else None
# Print system stats
sys_stats = []
for i in range(len(outs)):
sys_scores[i].sort()
sys_stats.append({
'mean':np.mean(sys_scores[i]),
'median':np.median(sys_scores[i]),
'lower_bound':sys_scores[i][int(num_samples * 0.025)],
'upper_bound':sys_scores[i][int(num_samples * 0.975)]
})
return wins, sys_stats
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] |
arxpy/differential/difference.py | hukaisdu/ArxPy | 25 | 95392 | """Manipulate differences."""
import collections
from arxpy.bitvector import core
from arxpy.bitvector import operation
from arxpy.bitvector import extraop
def _tuplify(seq):
if isinstance(seq, collections.abc.Sequence):
return tuple(seq)
else:
return tuple([seq])
class Difference(object):
"""Represent differences.
The *difference* between two `Term` :math:`x` and :math:`y`
is defined as :math:`\\alpha = y - x`,
where the *difference operation* :math:`-`
is a bit-vector `Operation`. In other words, the pair
:math:`(x, x + \\alpha)` has difference :math:`\\alpha`,
where :math:`+` is the inverse of the difference operation.
The most common difference used in differential cryptanalysis
is the XOR difference `XorDiff` (where the difference operation
is `BvXor`). Other examples are the additive difference
(where the difference operation is `BvSub`) or the rotational-XOR
difference `RXDiff`.
Note that arithmetic with differences is not supported.
For example, two `Difference` objects ``d1`` and ``d2``
cannot be XORed, i.e., ``d1 ^ d2``.
This can be done instead by performing the arithmetic with
the difference values and converting the resulting
`Term` to a difference, that is, ``Difference(d1.val ^ d2.val)``
This class is not meant to be instantiated but to provide a base
class for the different types of differences.
Attributes:
val: a `Term` representing the value of the difference.
diff_op: the difference `Operation`.
inv_diff_op: the inverse of the difference operation.
"""
diff_op = None
inv_diff_op = None
def __init__(self, value):
assert isinstance(value, core.Term)
self.val = value
def __str__(self):
"""Return the non-verbose string representation."""
return "{}({})".format(type(self).__name__, str(self.val))
__repr__ = __str__
def __hash__(self):
return hash(self.val)
def __eq__(self, other):
if isinstance(other, type(self)):
return self.val == other.val
else:
return False
def xreplace(self, rule):
"""Replace occurrences of differences within the expression.
The argument ``rule`` is a dict-like object representing
the replacement rule.
This method is similar to SymPy `xreplace
<https://docs.sympy.org/latest/modules/core.html?highlight=xreplace#
sympy.core.basic.Basic.xreplace>`_ but with the restriction that
only differences objects are allowed in ``rule``.
"""
for d in rule:
assert isinstance(d, type(self)) and isinstance(rule[d], type(self))
rule = {d.val: rule[d].val for d in rule}
return type(self)(self.val.xreplace(rule))
def vrepr(self):
"""Return a verbose string representation."""
return "{}({})".format(type(self).__name__, self.val.vrepr())
@classmethod
def from_pair(cls, x, y):
"""Return the `Difference` :math:`\\alpha = y - x` given two `Term`."""
assert isinstance(x, core.Term)
assert isinstance(y, core.Term)
return cls(cls.diff_op(x, y)) # The order of the operands is important
def get_pair_element(self, x):
"""Return the `Term` :math:`y` such that :math:`y = \\alpha + x`."""
assert isinstance(x, core.Term)
return self.inv_diff_op(x, self.val)
@classmethod
def derivative(cls, op, input_diff):
"""Return the derivative of ``op`` at the point ``input_diff``.
The derivative of an `Operation` :math:`f`
at the point :math:`\\alpha` (also called the input difference)
is defined as :math:`f_{\\alpha} (x) = f(x + \\alpha) - f(x)`.
Note that :math:`f_{\\alpha} (x)` is the difference of
:math:`(f(x), f(x + \\alpha))`.
If :math:`f` has multiple operands, :math:`\\alpha` is a list
containing the `Difference` of each operand and the
computation :math:`x + \\alpha` is defined component-wise, that is,
:math:`x = (x_1, \dots, x_n)`, :math:`\\alpha = (\\alpha_1, \dots, \\alpha_n)`,
and :math:`x + \\alpha = (x_1 + \\alpha_1, \dots, x_n + \\alpha_n)`.
For some operations, there is a unique output difference :math:`\\beta`
for every input difference :math:`\\alpha`, that is, :math:`f_{\\alpha}(x) = \\beta`
is a constant function. In this case, this method returns the `Difference`
:math:`\\beta`. Otherwise, it returns a `Derivative` object representing
:math:`f_{\\alpha}`.
Operations with scalar operands are not supported, but these
operands can be removed with `make_partial_operation` and
the derivative of the resulting operator can then be computed.
Args:
op: a bit-vector operator
input_diff: a list containing the difference of each operand
"""
raise NotImplementedError("subclasses need to override this method")
class XorDiff(Difference):
"""Represent XOR differences.
The XOR difference of two `Term` is given by the XOR
of the terms. In other words, the *difference operation*
of `XorDiff` is the `BvXor` (see `Difference`).
>>> from arxpy.bitvector.core import Constant, Variable
>>> from arxpy.differential.difference import XorDiff
>>> x, y = Constant(0b000, 3), Constant(0b000, 3)
>>> alpha = XorDiff.from_pair(x, y)
>>> alpha
XorDiff(0b000)
>>> alpha.get_pair_element(x)
0b000
>>> x, y = Constant(0b010, 3), Constant(0b101, 3)
>>> alpha = XorDiff.from_pair(x, y)
>>> alpha
XorDiff(0b111)
>>> alpha.get_pair_element(x)
0b101
>>> k = Variable("k", 8)
>>> alpha = XorDiff.from_pair(k, k)
>>> alpha
XorDiff(0x00)
>>> alpha.get_pair_element(k)
k
"""
diff_op = operation.BvXor
inv_diff_op = operation.BvXor
@classmethod
def derivative(cls, op, input_diff):
"""Return the derivative of ``op`` at the point ``input_diff``.
See `Difference.derivative` for more information.
>>> from arxpy.bitvector.core import Variable, Constant
>>> from arxpy.bitvector.operation import BvAdd, BvXor, RotateLeft, BvSub
>>> from arxpy.bitvector.extraop import make_partial_operation
>>> from arxpy.differential.difference import XorDiff
>>> d1, d2 = XorDiff(Variable("d1", 8)), XorDiff(Variable("d2", 8))
>>> XorDiff.derivative(BvXor, [d1, d2])
XorDiff(d1 ^ d2)
>>> Xor1 = make_partial_operation(BvXor, tuple([None, Constant(1, 8)]))
>>> XorDiff.derivative(Xor1, d1)
XorDiff(d1)
>>> Rotate1 = make_partial_operation(RotateLeft, tuple([None, 1]))
>>> XorDiff.derivative(Rotate1, d1)
XorDiff(d1 <<< 1)
>>> XorDiff.derivative(BvAdd, [d1, d2])
XDA(XorDiff(d1), XorDiff(d2))
>>> XorDiff.derivative(BvSub, [d1, d2])
XDS(XorDiff(d1), XorDiff(d2))
>>> CteAdd1 = make_partial_operation(BvAdd, tuple([None, Constant(1, 8)]))
>>> XorDiff.derivative(CteAdd1, d1)
XDCA_0x01(XorDiff(d1))
"""
input_diff = _tuplify(input_diff)
assert len(input_diff) == sum(op.arity)
msg = "invalid arguments: op={}, input_diff={}".format(
op.__name__,
[d.vrepr() if isinstance(d, core.Term) else d for d in input_diff])
if not all(isinstance(diff, cls) for diff in input_diff):
raise ValueError(msg)
if op == operation.BvNot:
return input_diff[0]
if op == operation.BvXor:
return cls(op(*[d.val for d in input_diff]))
if op == operation.Concat:
return cls(op(*[d.val for d in input_diff]))
if op == operation.BvAdd:
from arxpy.differential import derivative
return derivative.XDA(input_diff)
if op == operation.BvSub:
from arxpy.differential import derivative
return derivative.XDS(input_diff)
if issubclass(op, extraop.PartialOperation):
if op.base_op == operation.BvXor:
assert len(input_diff) == 1
d1 = input_diff[0]
val = op.fixed_args[0] if op.fixed_args[0] is not None else op.fixed_args[1]
d2 = cls.from_pair(val, val)
input_diff = [d1, d2]
return cls(op.base_op(*[d.val for d in input_diff]))
if op.base_op == operation.BvAnd:
assert len(input_diff) == 1
d1 = input_diff[0]
val = op.fixed_args[0] if op.fixed_args[0] is not None else op.fixed_args[1]
if isinstance(val, core.Constant):
return cls(op.base_op(d1.val, val))
if op.base_op in [operation.RotateLeft, operation.RotateRight]:
if op.fixed_args[0] is None and op.fixed_args[1] is not None:
assert len(input_diff) == 1
d = input_diff[0]
return cls(op.base_op(d.val, op.fixed_args[1]))
else:
raise ValueError(msg)
if op.base_op in [operation.BvShl, operation.BvLshr]:
if op.fixed_args[0] is None and op.fixed_args[1] is not None:
assert len(input_diff) == 1
d = input_diff[0]
return cls(op.base_op(d.val, op.fixed_args[1]))
else:
raise ValueError(msg)
if op.base_op == operation.Extract:
if op.fixed_args[0] is None and op.fixed_args[1] is not None and op.fixed_args[2] is not None:
assert len(input_diff) == 1
d = input_diff[0]
return cls(op.base_op(d.val, op.fixed_args[1], op.fixed_args[2]))
else:
raise ValueError(msg)
if op.base_op == operation.Concat:
assert len(input_diff) == 1
d1 = input_diff[0]
if op.fixed_args[0] is not None:
val = op.fixed_args[0]
input_diff = [cls.from_pair(val, val), d1]
else:
val = op.fixed_args[1]
input_diff = [d1, cls.from_pair(val, val)]
return cls(op.base_op(*[d.val for d in input_diff]))
if op.base_op == operation.BvAdd:
assert len(input_diff) == 1
d = input_diff[0]
cte = op.fixed_args[0] if op.fixed_args[0] is not None else op.fixed_args[1]
from arxpy.differential import derivative
return derivative.XDCA(d, cte)
else:
raise ValueError(msg)
if hasattr(op, "xor_derivative"):
return op.xor_derivative(input_diff)
raise ValueError(msg)
class RXOp(operation.Operation):
"""The difference operation of `RXDiff`."""
arity = [2, 0]
is_symmetric = False
is_simple = True
@classmethod
def condition(cls, x, y):
return x.width == y.width
@classmethod
def output_width(cls, x, y):
return x.width
@classmethod
def eval(cls, x, y):
return operation.RotateLeft(x, 1) ^ y
class RXInvOp(operation.Operation):
"""The inverse of the difference operation of `RXDiff`."""
arity = [2, 0]
is_symmetric = False
is_simple = True
@classmethod
def condition(cls, x, d):
return x.width == d.width
@classmethod
def output_width(cls, x, d):
return x.width
@classmethod
def eval(cls, x, d):
return operation.RotateLeft(x, 1) ^ d
class RXDiff(Difference):
"""Represent rotational-XOR (RX) differences.
The pair ``(x, (x <<< 1) ^ d)`` has RX difference ``d``.
In other words, the RX difference of two `Term` ``x`` and ``y``
is defined as ``(x <<< 1) ^ y``.
See `Difference` for more information.
>>> from arxpy.bitvector.core import Constant, Variable
>>> from arxpy.differential.difference import RXDiff
>>> x, y = Constant(0b000, 3), Constant(0b000, 3)
>>> alpha = RXDiff.from_pair(x, y)
>>> alpha
RXDiff(0b000)
>>> alpha.get_pair_element(x)
0b000
>>> x, y = Constant(0b000, 3), Constant(0b001, 3)
>>> alpha = RXDiff.from_pair(x, y)
>>> alpha
RXDiff(0b001)
>>> alpha.get_pair_element(x)
0b001
>>> k = Variable("k", 8)
>>> alpha = RXDiff.from_pair(k, k)
>>> alpha
RXDiff(k ^ (k <<< 1))
>>> alpha.get_pair_element(k)
k
"""
diff_op = RXOp
inv_diff_op = RXInvOp
@classmethod
def derivative(cls, op, input_diff):
"""Return the derivative of ``op`` at the point ``input_diff``.
See `Difference.derivative` for more information.
>>> from arxpy.bitvector.core import Variable, Constant
>>> from arxpy.bitvector.operation import BvAdd, BvXor, RotateLeft
>>> from arxpy.bitvector.extraop import make_partial_operation
>>> from arxpy.differential.difference import RXDiff
>>> d1, d2 = RXDiff(Variable("d1", 8)), RXDiff(Variable("d2", 8))
>>> RXDiff.derivative(BvXor, [d1, d2])
RXDiff(d1 ^ d2)
>>> Xor1 = make_partial_operation(BvXor, tuple([None, Constant(1, 8)]))
>>> RXDiff.derivative(Xor1, d1)
RXDiff(0x03 ^ d1)
>>> Rotate1 = make_partial_operation(RotateLeft, tuple([None, 1]))
>>> RXDiff.derivative(Rotate1, d1)
RXDiff(d1 <<< 1)
>>> RXDiff.derivative(BvAdd, [d1, d2])
RXDA(RXDiff(d1), RXDiff(d2))
"""
input_diff = _tuplify(input_diff)
assert len(input_diff) == sum(op.arity)
msg = "invalid arguments: op={}, input_diff={}".format(
op.__name__,
[d.vrepr() if isinstance(d, core.Term) else d for d in input_diff])
if not all(isinstance(diff, cls) for diff in input_diff):
raise ValueError(msg)
if op == operation.BvNot:
return input_diff[0]
if op == operation.BvXor:
return cls(op(*[d.val for d in input_diff]))
if op == operation.BvAdd:
from arxpy.differential import derivative
return derivative.RXDA(input_diff)
# Concact, BvSub
if issubclass(op, extraop.PartialOperation):
if op.base_op == operation.BvXor:
assert len(input_diff) == 1
d1 = input_diff[0]
val = op.fixed_args[0] if op.fixed_args[0] is not None else op.fixed_args[1]
d2 = cls.from_pair(val, val)
input_diff = [d1, d2]
return cls(op.base_op(*[d.val for d in input_diff]))
if op.base_op in [operation.RotateLeft, operation.RotateRight]:
if op.fixed_args[0] is None and op.fixed_args[1] is not None:
assert len(input_diff) == 1
d = input_diff[0]
return cls(op.base_op(d.val, op.fixed_args[1]))
else:
raise ValueError(msg)
# BvShl, Extract
if hasattr(op, "rx_derivative"):
return op.rx_derivative(input_diff)
raise ValueError(msg)
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] |
research/object_detection/kshitij_inference.py | nikhalster/models | 0 | 140830 | <filename>research/object_detection/kshitij_inference.py
import pathlib
import cv2
import numpy as np
import os
import six.moves.urllib as urllib
import sys
import tarfile
import tensorflow as tf
import zipfile
from collections import defaultdict
from io import StringIO
from matplotlib import pyplot as plt
from PIL import Image
from utils import ops as utils_ops
from utils import label_map_util
from utils import visualization_utils as vis_util
PATH_TO_LABELS = '/home/nikhal/PycharmProjects/models/research/object_detection/data/mscoco_label_map.pbtxt'
PATH_TO_TEST_IMAGES_DIR = pathlib.Path('/home/nikhal/Pictures')
TEST_IMAGE_PATHS = sorted(list(PATH_TO_TEST_IMAGES_DIR.glob("*.jpg")))
category_index = label_map_util.create_category_index_from_labelmap(PATH_TO_LABELS, use_display_name=True)
def load_model():
# base_url = 'http://download.tensorflow.org/models/object_detection/'
# model_file = model_name + '.tar.gz'
# model_dir = tf.keras.utils.get_file(
# fname=model_name,
# origin=base_url + model_file,
# untar=True)
# model_dir = pathlib.Path(model_dir)/"saved_model"
model = tf.saved_model.load(str("/home/nikhal/Models/faster_rcnn_resnet50_coco_2018_01_28/saved_model"))
model = model.signatures['serving_default']
return model
def run_inference_for_single_image(model, image):
image = np.asarray(image)
# The input needs to be a tensor, convert it using `tf.convert_to_tensor`.
input_tensor = tf.convert_to_tensor(image)
# The model expects a batch of images, so add an axis with `tf.newaxis`.
input_tensor = input_tensor[tf.newaxis, ...]
# Run inference
output_dict = model(input_tensor)
# All outputs are batches tensors.
# Convert to numpy arrays, and take index [0] to remove the batch dimension.
# We're only interested in the first num_detections.
num_detections = int(output_dict.pop('num_detections'))
output_dict = {key: value[0, :num_detections].numpy()
for key, value in output_dict.items()}
output_dict['num_detections'] = num_detections
# detection_classes should be ints.
output_dict['detection_classes'] = output_dict['detection_classes'].astype(np.int64)
# Handle models with masks:
if 'detection_masks' in output_dict:
# Reframe the the bbox mask to the image size.
detection_masks_reframed = utils_ops.reframe_box_masks_to_image_masks(
output_dict['detection_masks'], output_dict['detection_boxes'],
image.shape[0], image.shape[1])
detection_masks_reframed = tf.cast(detection_masks_reframed > 0.5,
tf.uint8)
output_dict['detection_masks_reframed'] = detection_masks_reframed.numpy()
return output_dict
def show_inference(model, image_path, path):
# the array based representation of the image will be used later in order to prepare the
# result image with boxes and labels on it.
image_np = image_path #np.array(Image.open(image_path))
# Actual detection.
output_dict = run_inference_for_single_image(model, image_np)
# Visualization of the results of a detection.
vis_util.visualize_boxes_and_labels_on_image_array(
image_np,
output_dict['detection_boxes'],
output_dict['detection_classes'],
output_dict['detection_scores'],
category_index,
instance_masks=output_dict.get('detection_masks_reframed', None),
use_normalized_coordinates=True,
line_thickness=8,
savepath=path)
return Image.fromarray(image_np)
def main():
path = "/home/nikhal/2018-03-07/"
detection_model = load_model()
for folder in os.listdir(path):
for avifile in os.listdir(path + folder):
if avifile[-3:] == "avi":
print(avifile)
os.makedirs(os.path.join(path,folder,avifile[:-4]))
cap = cv2.VideoCapture(os.path.join(path , folder,avifile))
counter = 0
# with detection_model.as_default():
while (cap.isOpened()):
save_path = os.path.join(path , folder , avifile[:-4] , str(counter))
print(counter)
ret, frame = cap.read()
if ret == True:
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
show_inference(detection_model, frame, save_path)
counter += 1
else:
break
cap.release()
main()
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2
] |
tests/test_load_spec.py | rai-project/scope_plot | 0 | 179865 | <gh_stars>0
import os
from scope_plot.specification import Specification
FIXTURES_DIR = os.path.join(
os.path.dirname(os.path.realpath(__file__)), "..", "__fixtures")
def test_bokeh_errorbar_spec():
figure_spec = Specification.load_yaml(
os.path.join(FIXTURES_DIR, "bokeh_errorbar.yml"))
assert figure_spec.ty() == "errorbar"
def test_bokeh_bar_spec():
figure_spec = Specification.load_yaml(
os.path.join(FIXTURES_DIR, "bokeh_bar.yml"))
assert figure_spec.ty() == "bar"
def test_bokeh_subplots_spec():
figure_spec = Specification.load_yaml(
os.path.join(FIXTURES_DIR, "bokeh_subplots.yml"))
assert figure_spec.subplots[0].ty() == "errorbar"
def test_matplotlib_regplot_spec():
figure_spec = Specification.load_yaml(
os.path.join(FIXTURES_DIR, "matplotlib_regplot.yml"))
assert figure_spec.ty() == "regplot"
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] |
algorithms/algorithms/searching/binary_search/problems/search_in_rotated_sorted_array.py | givek/algorithms | 0 | 150802 | <filename>algorithms/algorithms/searching/binary_search/problems/search_in_rotated_sorted_array.py
# Link: https://leetcode.com/problems/search-in-rotated-sorted-array/
# Time: O(LogN)
# Space: O(1)
# As the given array is rotated sorted, binary search cannot be applied directly.
def search(nums, target):
start, end = 0, len(nums) - 1
while start <= end:
mid = (start + end) // 2
if target == nums[mid]:
return mid
if nums[start] <= nums[mid]: # the array is sorted from start to mid.
if nums[start] <= target < nums[mid]:
# as the target lies between start and mid, reduce the search window.
end = mid - 1
else:
# if target does not lie between start and mid, search from (mid + 1) - end.
start = mid + 1
else: # here the array is sorted from mid to end.
if nums[mid] < target <= nums[end]:
# as the target lies between mid and end, reduce the search window.
start = mid + 1
else:
# the target does not lie between mid and end, search from start - (mid - 1)
end = mid - 1
return -1
def main():
nums = [3, 5, 1]
target = 3
print(search(nums, target))
if __name__ == "__main__":
main()
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tests/grab_upload_file.py | alexey-v-paramonov/grab | 0 | 195127 | <gh_stars>0
# coding: utf-8
import os
from grab import UploadContent, UploadFile
from tests.util import build_grab, temp_file, BaseGrabTestCase
class TestUploadContent(BaseGrabTestCase):
def setUp(self):
self.server.reset()
def prepare_form_grab(self):
url = self.server.get_url()
html = (
'<form action="%s" method="post" enctype="multipart/form-data">'
'<input type="file" name="image">'
'</form>' % url
).encode('ascii')
grab = build_grab(html, charset='utf-8')
return grab
# *******************
# UploadContent Tests
# *******************
def test_upload_content_filename(self):
grab = self.prepare_form_grab()
data = b'foo'
upload_data = UploadContent(data, filename='avatar.jpg')
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadContent))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
self.assertEqual('avatar.jpg',
self.server.request['files']['image'][0]['filename'])
self.assertEqual(
'image/jpeg',
self.server.request['files']['image'][0]['content_type'])
def test_upload_content_random_filename(self):
grab = self.prepare_form_grab()
data = b'foo'
upload_data = UploadContent(data)
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadContent))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
self.assertEqual(
10, len(self.server.request['files']['image'][0]['filename']))
self.assertEqual(
'application/octet-stream',
self.server.request['files']['image'][0]['content_type'])
def test_upload_content_content_type(self):
grab = self.prepare_form_grab()
data = b'foo'
upload_data = UploadContent(data,
content_type='application/grab')
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadContent))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
self.assertEqual(
10, len(self.server.request['files']['image'][0]['filename']))
self.assertEqual(
'application/grab',
self.server.request['files']['image'][0]['content_type'])
# ****************
# UploadFile Tests
# ****************
def test_upload_file(self):
with temp_file() as file_path:
grab = self.prepare_form_grab()
data = b'foo'
with open(file_path, 'wb') as out:
out.write(data)
upload_data = UploadFile(file_path)
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadFile))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
_, filename = os.path.split(file_path)
self.assertEqual(
filename,
self.server.request['files']['image'][0]['filename'],
)
self.assertEqual(
'application/octet-stream',
self.server.request['files']['image'][0]['content_type'])
def test_upload_file_custom_filename(self):
with temp_file() as file_path:
grab = self.prepare_form_grab()
data = b'foo'
with open(file_path, 'wb') as out:
out.write(data)
upload_data = UploadFile(file_path, filename='avatar.jpg')
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadFile))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
self.assertEqual(
'avatar.jpg',
self.server.request['files']['image'][0]['filename'],
)
self.assertEqual(
'image/jpeg',
self.server.request['files']['image'][0]['content_type'])
def test_upload_file_custom_content_type(self):
with temp_file() as file_path:
grab = self.prepare_form_grab()
data = b'foo'
with open(file_path, 'wb') as out:
out.write(data)
upload_data = UploadFile(file_path, filename='avatar.jpg',
content_type='application/grab')
grab.doc.set_input('image', upload_data)
grab.doc.submit(make_request=False)
post = dict(grab.config['multipart_post'])
self.assertTrue(isinstance(post['image'], UploadFile))
grab.doc.submit()
self.assertEqual(data,
self.server.request['files']['image'][0]['body'])
self.assertEqual(
'avatar.jpg',
self.server.request['files']['image'][0]['filename'],
)
self.assertEqual(
'application/grab',
self.server.request['files']['image'][0]['content_type'])
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] |
test/unit/common/test_header_key_dict.py | OyTao/swift-learning | 0 | 140227 | <reponame>OyTao/swift-learning<gh_stars>0
# Copyright (c) 2012 OpenStack Foundation
#
# 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 unittest
from swift.common.header_key_dict import HeaderKeyDict
class TestHeaderKeyDict(unittest.TestCase):
def test_case_insensitive(self):
headers = HeaderKeyDict()
headers['Content-Length'] = 0
headers['CONTENT-LENGTH'] = 10
headers['content-length'] = 20
self.assertEqual(headers['Content-Length'], '20')
self.assertEqual(headers['content-length'], '20')
self.assertEqual(headers['CONTENT-LENGTH'], '20')
def test_setdefault(self):
headers = HeaderKeyDict()
# it gets set
headers.setdefault('x-rubber-ducky', 'the one')
self.assertEqual(headers['X-Rubber-Ducky'], 'the one')
# it has the right return value
ret = headers.setdefault('x-boat', 'dinghy')
self.assertEqual(ret, 'dinghy')
ret = headers.setdefault('x-boat', 'yacht')
self.assertEqual(ret, 'dinghy')
# shouldn't crash
headers.setdefault('x-sir-not-appearing-in-this-request', None)
def test_del_contains(self):
headers = HeaderKeyDict()
headers['Content-Length'] = 0
self.assertIn('Content-Length', headers)
del headers['Content-Length']
self.assertNotIn('Content-Length', headers)
def test_update(self):
headers = HeaderKeyDict()
headers.update({'Content-Length': '0'})
headers.update([('Content-Type', 'text/plain')])
self.assertEqual(headers['Content-Length'], '0')
self.assertEqual(headers['Content-Type'], 'text/plain')
def test_set_none(self):
headers = HeaderKeyDict()
headers['test'] = None
self.assertNotIn('test', headers)
headers['test'] = 'something'
self.assertEqual('something', headers['test']) # sanity check
headers['test'] = None
self.assertNotIn('test', headers)
def test_init_from_dict(self):
headers = HeaderKeyDict({'Content-Length': 20,
'Content-Type': 'text/plain'})
self.assertEqual('20', headers['Content-Length'])
self.assertEqual('text/plain', headers['Content-Type'])
headers = HeaderKeyDict(headers)
self.assertEqual('20', headers['Content-Length'])
self.assertEqual('text/plain', headers['Content-Type'])
def test_set(self):
# mappings = ((<tuple of input vals>, <expected output val>), ...)
mappings = (((1.618, '1.618', b'1.618', u'1.618'), '1.618'),
((20, '20', b'20', u'20'), '20'),
((True, 'True', b'True', u'True'), 'True'),
((False, 'False', b'False', u'False'), 'False'))
for vals, expected in mappings:
for val in vals:
headers = HeaderKeyDict(test=val)
actual = headers['test']
self.assertEqual(expected, actual,
'Expected %s but got %s for val %s' %
(expected, actual, val))
self.assertIsInstance(
actual, str,
'Expected type str but got %s for val %s of type %s' %
(type(actual), val, type(val)))
def test_get(self):
headers = HeaderKeyDict()
headers['content-length'] = 20
self.assertEqual(headers.get('CONTENT-LENGTH'), '20')
self.assertEqual(headers.get('something-else'), None)
self.assertEqual(headers.get('something-else', True), True)
def test_keys(self):
headers = HeaderKeyDict()
headers['content-length'] = 20
headers['cOnTent-tYpe'] = 'text/plain'
headers['SomeThing-eLse'] = 'somevalue'
self.assertEqual(
set(headers.keys()),
set(('Content-Length', 'Content-Type', 'Something-Else')))
def test_pop(self):
headers = HeaderKeyDict()
headers['content-length'] = 20
headers['cOntent-tYpe'] = 'text/plain'
self.assertEqual(headers.pop('content-Length'), '20')
self.assertEqual(headers.pop('Content-type'), 'text/plain')
self.assertEqual(headers.pop('Something-Else', 'somevalue'),
'somevalue')
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] |
src/data/preprocessors/__init__.py | paulwarkentin/tf-ssd-vgg | 5 | 20928 | ##
## /src/data/preprocessors/__init__.py
##
## Created by <NAME> <<EMAIL>> on 15/07/2018.
## Updated by <NAME> <<EMAIL>> on 15/07/2018.
##
from .bbox_preprocessor import BBoxPreprocessor
from .default_preprocessor import DefaultPreprocessor
from .image_preprocessor import ImagePreprocessor
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store/templatetags/diffsize.py | Wikidata/editgroups | 11 | 1610395 | from django import template
from django.utils.html import escape
from django.utils.safestring import mark_safe
register = template.Library()
@register.filter(is_safe=True)
def diffsize(edit):
if type(edit) == int:
diffsize = edit
else:
diffsize = edit['newlength'] - edit['oldlength']
diffstr = '+{:,}'.format(diffsize) if diffsize > 0 else '{:,}'.format(diffsize)
if diffsize >= 500:
span = '<strong class="mw-plusminus-pos">%s</strong>' % diffstr
elif diffsize > 0:
span = '<span class="mw-plusminus-pos">%s</span>' % diffstr
elif diffsize == 0:
span = '<span>%s</span>' % diffstr
elif diffsize > -500:
span = '<span class="mw-plusminus-neg">%s</span>' % diffstr
else:
span = '<strong class="mw-plusminus-neg">%s</strong>' % diffstr
return mark_safe(span)
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python/testData/resolve/multiFile/reimportExported/ReimportExported.py | jnthn/intellij-community | 2 | 106041 | <filename>python/testData/resolve/multiFile/reimportExported/ReimportExported.py
import mypackage.foo
mypackage.bar.dostuff()
# <ref>
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pokemon_go_hunter/watch_twitter.py | juharris/pokemon-go-hunter | 0 | 120350 | <filename>pokemon_go_hunter/watch_twitter.py
import logging
import os
import re
import time
import twitter
import yaml
from pushbullet import Pushbullet
def get_config():
config_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), '../config.yaml')
with open(config_path) as f:
return yaml.load(f)
def get_twitter_api(config):
api_config = config['API']
twitter_api_config = api_config['Twitter']
return twitter.Api(consumer_key=twitter_api_config['consumer key'],
consumer_secret=twitter_api_config['consumer secret'],
access_token_key=twitter_api_config['access token key'],
access_token_secret=twitter_api_config['access token secret'])
def get_pushbullet_api(config):
api_config = config['API']
pushbullet_api_config = api_config['Pushbullet']
return Pushbullet(api_key=pushbullet_api_config['api key'],
encryption_password=pushbullet_api_config['encryption password'])
def get_pushbullet_device(pb, config):
devices = pb.devices
result = None
for d in devices:
if d.nickname == config['API']['Pushbullet']['device name']:
result = d
assert result is not None, "Couldn't find Pushbullet device."
return result
_config = get_config()
_twitter_api = get_twitter_api(_config)
_pb = get_pushbullet_api(_config)
_device = get_pushbullet_device(_pb, _config)
def main(screen_name: str,
pattern,
callback,
period_s: int = 61):
logging.info("Waiting for tweets.")
since_id = None
while True:
try:
statuses = _twitter_api.GetUserTimeline(screen_name=screen_name,
since_id=since_id,
trim_user=True)
except:
logging.exception("Error getting tweets.")
time.sleep(period_s / 4)
continue
for status in statuses:
if since_id is None:
since_id = status.id
else:
since_id = max(since_id, status.id)
text = status.text
m = pattern.search(text)
logging.debug(text)
if m:
try:
callback(status)
except:
logging.exception("Callback failed.")
time.sleep(period_s)
def notify(status):
text = status.text
for url in status.urls:
text = text.replace(url.url, url.expanded_url)
logging.info("Sending: \"%s\".", text)
_pb.push_sms(_device, 'TODO', text)
if __name__ == '__main__':
logging.basicConfig(format='%(asctime)s [%(levelname)s] - %(name)s:%(filename)s:%(funcName)s\n%(message)s',
level=logging.INFO)
# TODO Read from config.
# Example.
main(screen_name='montrealpokemap',
pattern=re.compile(r'\b(Unown)\b', re.IGNORECASE),
callback=notify)
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] |
scvelo/tools/utils.py | gokceneraslan/scvelo | 0 | 137772 | <filename>scvelo/tools/utils.py
from scipy.sparse import csr_matrix, issparse
import matplotlib.pyplot as pl
import pandas as pd
import numpy as np
import warnings
warnings.simplefilter("ignore")
def round(k, dec=2, as_str=None):
if isinstance(k, (list, tuple, np.record, np.ndarray)):
return [round(ki, dec) for ki in k]
if "e" in f"{k}":
k_str = f"{k}".split("e")
result = f"{np.round(np.float(k_str[0]), dec)}1e{k_str[1]}"
return f"{result}" if as_str else np.float(result)
result = np.round(np.float(k), dec)
return f"{result}" if as_str else result
def mean(x, axis=0):
return x.mean(axis).A1 if issparse(x) else x.mean(axis)
def make_dense(X):
XA = X.A if issparse(X) and X.ndim == 2 else X.A1 if issparse(X) else X
if XA.ndim == 2:
XA = XA[0] if XA.shape[0] == 1 else XA[:, 0] if XA.shape[1] == 1 else XA
return np.array(XA)
def sum_obs(A):
"""summation over axis 0 (obs) equivalent to np.sum(A, 0)"""
if issparse(A):
return A.sum(0).A1
else:
return np.einsum("ij -> j", A) if A.ndim > 1 else np.sum(A)
def sum_var(A):
"""summation over axis 1 (var) equivalent to np.sum(A, 1)"""
if issparse(A):
return A.sum(1).A1
else:
return np.sum(A, axis=1) if A.ndim > 1 else np.sum(A)
def prod_sum_obs(A, B):
"""dot product and sum over axis 0 (obs) equivalent to np.sum(A * B, 0)"""
if issparse(A):
return A.multiply(B).sum(0).A1
else:
return np.einsum("ij, ij -> j", A, B) if A.ndim > 1 else (A * B).sum()
def prod_sum_var(A, B):
"""dot product and sum over axis 1 (var) equivalent to np.sum(A * B, 1)"""
if issparse(A):
return A.multiply(B).sum(1).A1
else:
return np.einsum("ij, ij -> i", A, B) if A.ndim > 1 else (A * B).sum()
def norm(A):
"""computes the L2-norm along axis 1
(e.g. genes or embedding dimensions) equivalent to np.linalg.norm(A, axis=1)
"""
if issparse(A):
return np.sqrt(A.multiply(A).sum(1).A1)
else:
return np.sqrt(np.einsum("ij, ij -> i", A, A) if A.ndim > 1 else np.sum(A * A))
def vector_norm(x):
"""computes the L2-norm along axis 1
(e.g. genes or embedding dimensions) equivalent to np.linalg.norm(A, axis=1)
"""
return np.sqrt(np.einsum("i, i -> ", x, x))
def R_squared(residual, total):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
r2 = np.ones(residual.shape[1]) - prod_sum_obs(
residual, residual
) / prod_sum_obs(total, total)
r2[np.isnan(r2)] = 0
return r2
def cosine_correlation(dX, Vi):
dx = dX - dX.mean(-1)[:, None]
Vi_norm = vector_norm(Vi)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
if Vi_norm == 0:
result = np.zeros(dx.shape[0])
else:
result = np.einsum("ij, j", dx, Vi) / (norm(dx) * Vi_norm)[None, :]
return result
def normalize(X):
with warnings.catch_warnings():
warnings.simplefilter("ignore")
if issparse(X):
return X.multiply(csr_matrix(1.0 / np.abs(X).sum(1)))
else:
return X / X.sum(1)
def scale(X, min=0, max=1):
idx = np.isfinite(X)
if any(idx):
X = X - X[idx].min() + min
xmax = X[idx].max()
X = X / xmax * max if xmax != 0 else X * max
return X
def get_indices(dist, n_neighbors=None, mode_neighbors="distances"):
from ..preprocessing.neighbors import compute_connectivities_umap
D = dist.copy()
D.data += 1e-6
n_counts = sum_var(D > 0)
n_neighbors = (
n_counts.min() if n_neighbors is None else min(n_counts.min(), n_neighbors)
)
rows = np.where(n_counts > n_neighbors)[0]
cumsum_neighs = np.insert(n_counts.cumsum(), 0, 0)
dat = D.data
for row in rows:
n0, n1 = cumsum_neighs[row], cumsum_neighs[row + 1]
rm_idx = n0 + dat[n0:n1].argsort()[n_neighbors:]
dat[rm_idx] = 0
D.eliminate_zeros()
D.data -= 1e-6
if mode_neighbors == "distances":
indices = D.indices.reshape((-1, n_neighbors))
elif mode_neighbors == "connectivities":
knn_indices = D.indices.reshape((-1, n_neighbors))
knn_distances = D.data.reshape((-1, n_neighbors))
_, conn = compute_connectivities_umap(
knn_indices, knn_distances, D.shape[0], n_neighbors
)
indices = get_indices_from_csr(conn)
return indices, D
def get_indices_from_csr(conn):
# extracts indices from connectivity matrix, pads with nans
ixs = np.ones((conn.shape[0], np.max((conn > 0).sum(1)))) * np.nan
for i in range(ixs.shape[0]):
cell_indices = conn[i, :].indices
ixs[i, : len(cell_indices)] = cell_indices
return ixs
def get_iterative_indices(
indices,
index,
n_recurse_neighbors=2,
max_neighs=None,
):
def iterate_indices(indices, index, n_recurse_neighbors):
if n_recurse_neighbors > 1:
index = iterate_indices(indices, index, n_recurse_neighbors - 1)
ix = np.append(index, indices[index]) # direct and indirect neighbors
if np.isnan(ix).any():
ix = ix[~np.isnan(ix)]
return ix.astype(int)
indices = np.unique(iterate_indices(indices, index, n_recurse_neighbors))
if max_neighs is not None and len(indices) > max_neighs:
indices = np.random.choice(indices, max_neighs, replace=False)
return indices
def geometric_matrix_sum(C, n_power=2): # computes C + C^2 + C^3 + ...
C_n = (
geometric_matrix_sum(C, n_power - 1) if n_power > 2 else C if n_power > 1 else 0
)
return C + C.dot(C_n)
def groups_to_bool(adata, groups, groupby=None):
groups = [groups] if isinstance(groups, str) else groups
if isinstance(groups, (list, tuple, np.ndarray, np.record)):
groupby = (
groupby
if groupby in adata.obs.keys()
else "clusters"
if "clusters" in adata.obs.keys()
else "louvain"
if "louvain" in adata.obs.keys()
else None
)
if groupby is not None:
groups = np.array([key in groups for key in adata.obs[groupby]])
else:
raise ValueError("groupby attribute not valid.")
return groups
def most_common_in_list(lst):
lst = [item for item in lst if item is not np.nan and item != "nan"]
lst = list(lst)
return max(set(lst), key=lst.count)
def randomized_velocity(adata, vkey="velocity", add_key="velocity_random"):
V_rnd = adata.layers[vkey].copy()
for i in range(V_rnd.shape[1]):
np.random.shuffle(V_rnd[:, i])
V_rnd[:, i] = V_rnd[:, i] * np.random.choice(
np.array([+1, -1]), size=V_rnd.shape[0]
)
adata.layers[add_key] = V_rnd
from .velocity_graph import velocity_graph
from .velocity_embedding import velocity_embedding
velocity_graph(adata, vkey=add_key)
velocity_embedding(adata, vkey=add_key, autoscale=False)
def extract_int_from_str(array):
def str_to_int(item):
num = "".join(filter(str.isdigit, item))
num = int(num) if len(num) > 0 else -1
return num
if isinstance(array, str):
nums = str_to_int(array)
elif len(array) > 1 and isinstance(array[0], str):
nums = []
for item in array:
nums.append(str_to_int(item))
else:
nums = array
nums = pd.Categorical(nums) if array.dtype == "category" else np.array(nums)
return nums
def strings_to_categoricals(adata):
"""Transform string annotations to categoricals."""
from pandas.api.types import is_string_dtype, is_integer_dtype, is_bool_dtype
from pandas import Categorical
def is_valid_dtype(values):
return (
is_string_dtype(values) or is_integer_dtype(values) or is_bool_dtype(values)
)
df = adata.obs
df_keys = [key for key in df.columns if is_valid_dtype(df[key])]
for key in df_keys:
c = df[key]
c = Categorical(c)
if 1 < len(c.categories) < min(len(c), 100):
df[key] = c
df = adata.var
df_keys = [key for key in df.columns if is_string_dtype(df[key])]
for key in df_keys:
c = df[key].astype("U")
c = Categorical(c)
if 1 < len(c.categories) < min(len(c), 100):
df[key] = c
def merge_groups(adata, key, map_groups, key_added=None, map_colors=None):
strings_to_categoricals(adata)
if len(map_groups) != len(adata.obs[key].cat.categories):
map_coarse = {}
for c in adata.obs[key].cat.categories:
for group in map_groups:
if any(cluster == c for cluster in map_groups[group]):
map_coarse[c] = group
if c not in map_coarse:
map_coarse[c] = c
map_groups = map_coarse
if key_added is None:
key_added = f"{key}_coarse"
from pandas.api.types import CategoricalDtype
adata.obs[key_added] = adata.obs[key].map(map_groups).astype(CategoricalDtype())
old_categories = adata.obs[key].cat.categories
new_categories = adata.obs[key_added].cat.categories
# map_colors is passed
if map_colors is not None:
old_colors = None
if f"{key}_colors" in adata.uns:
old_colors = adata.uns[f"{key}_colors"]
new_colors = []
for group in adata.obs[key_added].cat.categories:
if group in map_colors:
new_colors.append(map_colors[group])
elif group in old_categories and old_colors is not None:
new_colors.append(old_colors[old_categories.get_loc(group)])
else:
raise ValueError(f"You didn't specify a color for {group}.")
adata.uns[f"{key_added}_colors"] = new_colors
# map_colors is not passed
elif f"{key}_colors" in adata.uns:
old_colors = adata.uns[f"{key}_colors"]
inverse_map_groups = {g: [] for g in new_categories}
for old_group in old_categories:
inverse_map_groups[map_groups[old_group]].append(old_group)
new_colors = []
for group in new_categories:
# take the largest of the old groups
old_group = (
adata.obs[key][adata.obs[key].isin(inverse_map_groups[group])]
.value_counts()
.index[0]
)
new_colors.append(old_colors[old_categories.get_loc(old_group)])
adata.uns[f"{key_added}_colors"] = new_colors
def cutoff_small_velocities(
adata, vkey="velocity", key_added="velocity_cut", frac_of_max=0.5, use_raw=False
):
x = adata.layers["spliced"] if use_raw else adata.layers["Ms"]
y = adata.layers["unspliced"] if use_raw else adata.layers["Mu"]
x_max = x.max(0).A[0] if issparse(x) else x.max(0)
y_max = y.max(0).A[0] if issparse(y) else y.max(0)
xy_norm = x / np.clip(x_max, 1e-3, None) + y / np.clip(y_max, 1e-3, None)
W = xy_norm >= np.percentile(xy_norm, 98, axis=0) * frac_of_max
adata.layers[key_added] = csr_matrix(W).multiply(adata.layers[vkey]).tocsr()
from .velocity_graph import velocity_graph
from .velocity_embedding import velocity_embedding
velocity_graph(adata, vkey=key_added, approx=True)
velocity_embedding(adata, vkey=key_added)
def make_unique_list(key, allow_array=False):
from pandas import unique, Index
if isinstance(key, Index):
key = key.tolist()
is_list = (
isinstance(key, (list, tuple, np.record))
if allow_array
else isinstance(key, (list, tuple, np.ndarray, np.record))
)
is_list_of_str = is_list and all(isinstance(item, str) for item in key)
return (
unique(key) if is_list_of_str else key if is_list and len(key) < 20 else [key]
)
def test_bimodality(x, bins=30, kde=True, plot=False):
"""Test for bimodal distribution."""
from scipy.stats import gaussian_kde, norm
lb, ub = np.min(x), np.percentile(x, 99.9)
grid = np.linspace(lb, ub if ub <= lb else np.max(x), bins)
kde_grid = (
gaussian_kde(x)(grid) if kde else np.histogram(x, bins=grid, density=True)[0]
)
idx = int(bins / 2) - 2
idx += np.argmin(kde_grid[idx : idx + 4])
peak_0 = kde_grid[:idx].argmax()
peak_1 = kde_grid[idx:].argmax()
kde_peak = kde_grid[idx:][
peak_1
] # min(kde_grid[:idx][peak_0], kde_grid[idx:][peak_1])
kde_mid = kde_grid[idx:].mean() # kde_grid[idx]
t_stat = (kde_peak - kde_mid) / np.clip(np.std(kde_grid) / np.sqrt(bins), 1, None)
p_val = norm.sf(t_stat)
grid_0 = grid[:idx]
grid_1 = grid[idx:]
means = [
(grid_0[peak_0] + grid_0[min(peak_0 + 1, len(grid_0) - 1)]) / 2,
(grid_1[peak_1] + grid_1[min(peak_1 + 1, len(grid_1) - 1)]) / 2,
]
if plot:
color = "grey"
if kde:
pl.plot(grid, kde_grid, color=color)
pl.fill_between(grid, 0, kde_grid, alpha=0.4, color=color)
else:
pl.hist(x, bins=grid, alpha=0.4, density=True, color=color)
pl.axvline(means[0], color=color)
pl.axvline(means[1], color=color)
pl.axhline(kde_mid, alpha=0.2, linestyle="--", color=color)
pl.show()
return t_stat, p_val, means # ~ t_test (reject unimodality if t_stat > 3)
def random_subsample(adata, fraction=0.1, return_subset=False, copy=False):
adata_sub = adata.copy() if copy else adata
p, size = fraction, adata.n_obs
subset = np.random.choice([True, False], size=size, p=[p, 1 - p])
adata_sub._inplace_subset_obs(subset)
return adata_sub if copy else subset if return_subset else None
def get_duplicates(array):
from collections import Counter
return np.array([item for (item, count) in Counter(array).items() if count > 1])
def corrcoef(x, y, mode="pearsons"):
from scipy.stats import pearsonr, spearmanr
corr, _ = spearmanr(x, y) if mode == "spearmans" else pearsonr(x, y)
return corr
def vcorrcoef(X, y, mode="pearsons", axis=-1):
"""Pearsons/Spearmans correlation coefficients.
Use Pearsons / Spearmans to test for linear / monotonic relationship.
Arguments
----------
X: `np.ndarray`
Data vector or matrix
y: `np.ndarray`
Data vector or matrix
mode: 'pearsons' or 'spearmans' (default: `'pearsons'`)
Which correlation metric to use.
"""
if issparse(X):
X = np.array(X.A)
if issparse(y):
y = np.array(y.A)
if axis == 0:
if X.ndim > 1:
X = np.array(X.T)
if y.ndim > 1:
y = np.array(y.T)
if X.shape[axis] != y.shape[axis]:
X = X.T
if mode in {"spearmans", "spearman"}:
from scipy.stats.stats import rankdata
X = np.apply_along_axis(rankdata, axis=-1, arr=X)
y = np.apply_along_axis(rankdata, axis=-1, arr=y)
Xm = np.array(X - (np.nanmean(X, -1)[:, None] if X.ndim > 1 else np.nanmean(X, -1)))
ym = np.array(y - (np.nanmean(y, -1)[:, None] if y.ndim > 1 else np.nanmean(y, -1)))
corr = np.nansum(Xm * ym, -1) / np.sqrt(
np.nansum(Xm ** 2, -1) * np.nansum(ym ** 2, -1)
)
return corr
def isin(x, y):
return np.array(pd.DataFrame(x).isin(y)).flatten()
def indices_to_bool(indices, n):
return isin(np.arange(n), indices)
def convolve(adata, x):
from ..preprocessing.neighbors import get_connectivities
conn = get_connectivities(adata)
if isinstance(x, str) and x in adata.layers.keys():
x = adata.layers[x]
if x.ndim == 1:
return conn.dot(x)
idx_valid = ~np.isnan(x.sum(0))
Y = np.ones(x.shape) * np.nan
Y[:, idx_valid] = conn.dot(x[:, idx_valid])
return Y
def get_extrapolated_state(adata, vkey="velocity", dt=1, use_raw=None, dropna=True):
"""Get extrapolated cell state."""
S = adata.layers["spliced" if use_raw else "Ms"]
if dropna:
St = S + dt * adata.layers[vkey]
St = St[:, np.isfinite(np.sum(St, 0))]
else:
St = S + dt * np.nan_to_num(adata.layers[vkey])
return St
def get_plasticity_score(adata):
idx_top_genes = np.argsort(adata.var["gene_count_corr"].values)[::-1][:200]
Ms = np.array(adata.layers["Ms"][:, idx_top_genes])
return scale(np.mean(Ms / np.max(Ms, axis=0), axis=1))
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29890,
943,
29922,
29906,
29892,
13,
1678,
4236,
29918,
484,
1141,
29879,
29922,
8516,
29892,
13,
1125,
13,
1678,
822,
13649,
29918,
513,
1575,
29898,
513,
1575,
29892,
2380,
29892,
302,
29918,
276,
2764,
344,
29918,
484,
1141,
29890,
943,
1125,
13,
4706,
565,
302,
29918,
276,
2764,
344,
29918,
484,
1141,
29890,
943,
1405,
29871,
29896,
29901,
13,
9651,
2380,
353,
13649,
29918,
513,
1575,
29898,
513,
1575,
29892,
2380,
29892,
302,
29918,
276,
2764,
344,
29918,
484,
1141,
29890,
943,
448,
29871,
29896,
29897,
13,
4706,
474,
29916,
353,
7442,
29889,
4397,
29898,
2248,
29892,
16285,
29961,
2248,
2314,
29871,
396,
1513,
322,
26377,
22092,
943,
13,
4706,
565,
7442,
29889,
275,
13707,
29898,
861,
467,
1384,
7295,
13,
9651,
474,
29916,
353,
474,
29916,
29961,
30022,
9302,
29889,
275,
13707,
29898,
861,
4638,
13,
4706,
736,
474,
29916,
29889,
579,
668,
29898,
524,
29897,
13,
13,
1678,
16285,
353,
7442,
29889,
13092,
29898,
1524,
403,
29918,
513,
1575,
29898,
513,
1575,
29892,
2380,
29892,
302,
29918,
276,
2764,
344,
29918,
484,
1141,
29890,
943,
876,
13,
1678,
565,
4236,
29918,
484,
1141,
29879,
338,
451,
6213,
322,
7431,
29898,
513,
1575,
29897,
1405,
4236,
29918,
484,
1141,
29879,
29901,
13,
4706,
16285,
353,
7442,
29889,
8172,
29889,
16957,
29898,
513,
1575,
29892,
4236,
29918,
484,
1141,
29879,
29892,
5191,
29922,
8824,
29897,
13,
1678,
736,
16285,
13,
13,
13,
1753,
26224,
29918,
5344,
29918,
2083,
29898,
29907,
29892,
302,
29918,
13519,
29922,
29906,
1125,
29871,
396,
2912,
267,
315,
718,
315,
29985,
29906,
718,
315,
29985,
29941,
718,
2023,
13,
1678,
315,
29918,
29876,
353,
313,
13,
4706,
26224,
29918,
5344,
29918,
2083,
29898,
29907,
29892,
302,
29918,
13519,
448,
29871,
29896,
29897,
565,
302,
29918,
13519,
1405,
29871,
29906,
1683,
315,
565,
302,
29918,
13519,
1405,
29871,
29896,
1683,
29871,
29900,
13,
1678,
1723,
13,
1678,
736,
315,
718,
315,
29889,
6333,
29898,
29907,
29918,
29876,
29897,
13,
13,
13,
1753,
6471,
29918,
517,
29918,
11227,
29898,
7221,
29892,
6471,
29892,
2318,
1609,
29922,
8516,
1125,
13,
1678,
6471,
353,
518,
13155,
29962,
565,
338,
8758,
29898,
13155,
29892,
851,
29897,
1683,
6471,
13,
1678,
565,
338,
8758,
29898,
13155,
29892,
313,
1761,
29892,
18761,
29892,
7442,
29889,
299,
2378,
29892,
7442,
29889,
11651,
22164,
13,
4706,
2318,
1609,
353,
313,
13,
9651,
2318,
1609,
13,
9651,
565,
2318,
1609,
297,
594,
532,
29889,
26290,
29889,
8149,
580,
13,
9651,
1683,
376,
695,
504,
414,
29908,
13,
9651,
565,
376,
695,
504,
414,
29908,
297,
594,
532,
29889,
26290,
29889,
8149,
580,
13,
9651,
1683,
376,
29880,
5128,
475,
29908,
13,
9651,
565,
376,
29880,
5128,
475,
29908,
297,
594,
532,
29889,
26290,
29889,
8149,
580,
13,
9651,
1683,
6213,
13,
4706,
1723,
13,
4706,
565,
2318,
1609,
338,
451,
6213,
29901,
13,
9651,
6471,
353,
7442,
29889,
2378,
4197,
1989,
297,
6471,
363,
1820,
297,
594,
532,
29889,
26290,
29961,
27789,
24960,
13,
4706,
1683,
29901,
13,
9651,
12020,
7865,
2392,
703,
27789,
5352,
451,
2854,
23157,
13,
1678,
736,
6471,
13,
13,
13,
1753,
1556,
29918,
9435,
29918,
262,
29918,
1761,
29898,
20155,
1125,
13,
1678,
24471,
353,
518,
667,
363,
2944,
297,
24471,
565,
2944,
338,
451,
7442,
29889,
13707,
322,
2944,
2804,
376,
13707,
3108,
13,
1678,
24471,
353,
1051,
29898,
20155,
29897,
13,
1678,
736,
4236,
29898,
842,
29898,
20155,
511,
1820,
29922,
20155,
29889,
2798,
29897,
13,
13,
13,
1753,
4036,
1891,
29918,
955,
25245,
29898,
7221,
29892,
325,
1989,
543,
955,
25245,
613,
788,
29918,
1989,
543,
955,
25245,
29918,
8172,
29908,
1125,
13,
1678,
478,
29918,
29878,
299,
353,
594,
532,
29889,
29277,
29961,
29894,
1989,
1822,
8552,
580,
13,
1678,
363,
474,
297,
3464,
29898,
29963,
29918,
29878,
299,
29889,
12181,
29961,
29896,
29962,
1125,
13,
4706,
7442,
29889,
8172,
29889,
845,
21897,
29898,
29963,
29918,
29878,
299,
7503,
29892,
474,
2314,
13,
4706,
478,
29918,
29878,
299,
7503,
29892,
474,
29962,
353,
478,
29918,
29878,
299,
7503,
29892,
474,
29962,
334,
7442,
29889,
8172,
29889,
16957,
29898,
13,
9651,
7442,
29889,
2378,
4197,
29974,
29896,
29892,
448,
29896,
11724,
2159,
29922,
29963,
29918,
29878,
299,
29889,
12181,
29961,
29900,
29962,
13,
4706,
1723,
13,
1678,
594,
532,
29889,
29277,
29961,
1202,
29918,
1989,
29962,
353,
478,
29918,
29878,
299,
13,
13,
1678,
515,
869,
955,
25245,
29918,
4262,
1053,
12885,
29918,
4262,
13,
1678,
515,
869,
955,
25245,
29918,
17987,
8497,
1053,
12885,
29918,
17987,
8497,
13,
13,
1678,
12885,
29918,
4262,
29898,
7221,
29892,
325,
1989,
29922,
1202,
29918,
1989,
29897,
13,
1678,
12885,
29918,
17987,
8497,
29898,
7221,
29892,
325,
1989,
29922,
1202,
29918,
1989,
29892,
1120,
14174,
744,
29922,
8824,
29897,
13,
13,
13,
1753,
6597,
29918,
524,
29918,
3166,
29918,
710,
29898,
2378,
1125,
13,
1678,
822,
851,
29918,
517,
29918,
524,
29898,
667,
1125,
13,
4706,
954,
353,
376,
1642,
7122,
29898,
4572,
29898,
710,
29889,
275,
26204,
29892,
2944,
876,
13,
4706,
954,
353,
938,
29898,
1949,
29897,
565,
7431,
29898,
1949,
29897,
1405,
29871,
29900,
1683,
448,
29896,
13,
4706,
736,
954,
13,
13,
1678,
565,
338,
8758,
29898,
2378,
29892,
851,
1125,
13,
4706,
954,
29879,
353,
851,
29918,
517,
29918,
524,
29898,
2378,
29897,
13,
1678,
25342,
7431,
29898,
2378,
29897,
1405,
29871,
29896,
322,
338,
8758,
29898,
2378,
29961,
29900,
1402,
851,
1125,
13,
4706,
954,
29879,
353,
5159,
13,
4706,
363,
2944,
297,
1409,
29901,
13,
9651,
954,
29879,
29889,
4397,
29898,
710,
29918,
517,
29918,
524,
29898,
667,
876,
13,
1678,
1683,
29901,
13,
4706,
954,
29879,
353,
1409,
13,
1678,
954,
29879,
353,
10518,
29889,
29907,
20440,
936,
29898,
1949,
29879,
29897,
565,
1409,
29889,
29881,
1853,
1275,
376,
7320,
29908,
1683,
7442,
29889,
2378,
29898,
1949,
29879,
29897,
13,
1678,
736,
954,
29879,
13,
13,
13,
1753,
6031,
29918,
517,
29918,
29883,
20440,
936,
29879,
29898,
7221,
1125,
13,
1678,
9995,
13372,
1347,
25495,
304,
11608,
936,
29879,
1213,
15945,
13,
1678,
515,
11701,
29889,
2754,
29889,
8768,
1053,
338,
29918,
1807,
29918,
29881,
1853,
29892,
338,
29918,
16031,
29918,
29881,
1853,
29892,
338,
29918,
11227,
29918,
29881,
1853,
13,
1678,
515,
11701,
1053,
315,
20440,
936,
13,
13,
1678,
822,
338,
29918,
3084,
29918,
29881,
1853,
29898,
5975,
1125,
13,
4706,
736,
313,
13,
9651,
338,
29918,
1807,
29918,
29881,
1853,
29898,
5975,
29897,
470,
338,
29918,
16031,
29918,
29881,
1853,
29898,
5975,
29897,
470,
338,
29918,
11227,
29918,
29881,
1853,
29898,
5975,
29897,
13,
4706,
1723,
13,
13,
1678,
4489,
353,
594,
532,
29889,
26290,
13,
1678,
4489,
29918,
8149,
353,
518,
1989,
363,
1820,
297,
4489,
29889,
13099,
565,
338,
29918,
3084,
29918,
29881,
1853,
29898,
2176,
29961,
1989,
2314,
29962,
13,
1678,
363,
1820,
297,
4489,
29918,
8149,
29901,
13,
4706,
274,
353,
4489,
29961,
1989,
29962,
13,
4706,
274,
353,
315,
20440,
936,
29898,
29883,
29897,
13,
4706,
565,
29871,
29896,
529,
7431,
29898,
29883,
29889,
20683,
29897,
529,
1375,
29898,
2435,
29898,
29883,
511,
29871,
29896,
29900,
29900,
1125,
13,
9651,
4489,
29961,
1989,
29962,
353,
274,
13,
13,
1678,
4489,
353,
594,
532,
29889,
1707,
13,
1678,
4489,
29918,
8149,
353,
518,
1989,
363,
1820,
297,
4489,
29889,
13099,
565,
338,
29918,
1807,
29918,
29881,
1853,
29898,
2176,
29961,
1989,
2314,
29962,
13,
1678,
363,
1820,
297,
4489,
29918,
8149,
29901,
13,
4706,
274,
353,
4489,
29961,
1989,
1822,
579,
668,
703,
29965,
1159,
13,
4706,
274,
353,
315,
20440,
936,
29898,
29883,
29897,
13,
4706,
565,
29871,
29896,
529,
7431,
29898,
29883,
29889,
20683,
29897,
529,
1375,
29898,
2435,
29898,
29883,
511,
29871,
29896,
29900,
29900,
1125,
13,
9651,
4489,
29961,
1989,
29962,
353,
274,
13,
13,
13,
1753,
10366,
29918,
13155,
29898,
7221,
29892,
1820,
29892,
2910,
29918,
13155,
29892,
1820,
29918,
23959,
29922,
8516,
29892,
2910,
29918,
27703,
29922,
8516,
1125,
13,
1678,
6031,
29918,
517,
29918,
29883,
20440,
936,
29879,
29898,
7221,
29897,
13,
1678,
565,
7431,
29898,
1958,
29918,
13155,
29897,
2804,
7431,
29898,
7221,
29889,
26290,
29961,
1989,
1822,
4117,
29889,
20683,
1125,
13,
4706,
2910,
29918,
1111,
7989,
353,
6571,
13,
4706,
363,
274,
297,
594,
532,
29889,
26290,
29961,
1989,
1822,
4117,
29889,
20683,
29901,
13,
9651,
363,
2318,
297,
2910,
29918,
13155,
29901,
13,
18884,
565,
738,
29898,
19594,
1275,
274,
363,
9867,
297,
2910,
29918,
13155,
29961,
2972,
29962,
1125,
13,
462,
1678,
2910,
29918,
1111,
7989,
29961,
29883,
29962,
353,
2318,
13,
9651,
565,
274,
451,
297,
2910,
29918,
1111,
7989,
29901,
13,
18884,
2910,
29918,
1111,
7989,
29961,
29883,
29962,
353,
274,
13,
4706,
2910,
29918,
13155,
353,
2910,
29918,
1111,
7989,
13,
13,
1678,
565,
1820,
29918,
23959,
338,
6213,
29901,
13,
4706,
1820,
29918,
23959,
353,
285,
29908,
29912,
1989,
2403,
1111,
7989,
29908,
13,
13,
1678,
515,
11701,
29889,
2754,
29889,
8768,
1053,
315,
20440,
936,
29928,
1853,
13,
13,
1678,
594,
532,
29889,
26290,
29961,
1989,
29918,
23959,
29962,
353,
594,
532,
29889,
26290,
29961,
1989,
1822,
1958,
29898,
1958,
29918,
13155,
467,
579,
668,
29898,
29907,
20440,
936,
29928,
1853,
3101,
13,
1678,
2030,
29918,
20683,
353,
594,
532,
29889,
26290,
29961,
1989,
1822,
4117,
29889,
20683,
13,
1678,
716,
29918,
20683,
353,
594,
532,
29889,
26290,
29961,
1989,
29918,
23959,
1822,
4117,
29889,
20683,
13,
13,
1678,
396,
2910,
29918,
27703,
338,
4502,
13,
1678,
565,
2910,
29918,
27703,
338,
451,
6213,
29901,
13,
4706,
2030,
29918,
27703,
353,
6213,
13,
4706,
565,
285,
29908,
29912,
1989,
2403,
27703,
29908,
297,
594,
532,
29889,
6948,
29901,
13,
9651,
2030,
29918,
27703,
353,
594,
532,
29889,
6948,
29961,
29888,
29908,
29912,
1989,
2403,
27703,
3108,
13,
4706,
716,
29918,
27703,
353,
5159,
13,
4706,
363,
2318,
297,
594,
532,
29889,
26290,
29961,
1989,
29918,
23959,
1822,
4117,
29889,
20683,
29901,
13,
9651,
565,
2318,
297,
2910,
29918,
27703,
29901,
13,
18884,
716,
29918,
27703,
29889,
4397,
29898,
1958,
29918,
27703,
29961,
2972,
2314,
13,
9651,
25342,
2318,
297,
2030,
29918,
20683,
322,
2030,
29918,
27703,
338,
451,
6213,
29901,
13,
18884,
716,
29918,
27703,
29889,
4397,
29898,
1025,
29918,
27703,
29961,
1025,
29918,
20683,
29889,
657,
29918,
2029,
29898,
2972,
29897,
2314,
13,
9651,
1683,
29901,
13,
18884,
12020,
7865,
2392,
29898,
29888,
29908,
3492,
3282,
29915,
29873,
6084,
263,
2927,
363,
426,
2972,
1836,
1159,
13,
4706,
594,
532,
29889,
6948,
29961,
29888,
29908,
29912,
1989,
29918,
23959,
2403,
27703,
3108,
353,
716,
29918,
27703,
13,
13,
1678,
396,
2910,
29918,
27703,
338,
451,
4502,
13,
1678,
25342,
285,
29908,
29912,
1989,
2403,
27703,
29908,
297,
594,
532,
29889,
6948,
29901,
13,
4706,
2030,
29918,
27703,
353,
594,
532,
29889,
6948,
29961,
29888,
29908,
29912,
1989,
2403,
27703,
3108,
13,
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16402,
29918,
1958,
29918,
13155,
353,
426,
29887,
29901,
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363,
330,
297,
716,
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20683,
29913,
13,
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363,
2030,
29918,
2972,
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1958,
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13155,
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1958,
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13155,
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1025,
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2972,
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1822,
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716,
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13,
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363,
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297,
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20683,
29901,
13,
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396,
2125,
278,
10150,
310,
278,
2030,
6471,
13,
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2030,
29918,
2972,
353,
313,
13,
18884,
594,
532,
29889,
26290,
29961,
1989,
3816,
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1989,
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275,
262,
29898,
262,
3901,
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1958,
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13155,
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13,
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1767,
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2798,
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13,
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2248,
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13,
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657,
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2029,
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2972,
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13,
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594,
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6948,
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29888,
29908,
29912,
1989,
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27703,
3108,
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716,
29918,
27703,
13,
13,
13,
1753,
5700,
2696,
29918,
9278,
29918,
955,
542,
1907,
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13,
1678,
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325,
1989,
543,
955,
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613,
1820,
29918,
23959,
543,
955,
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29918,
7582,
613,
285,
945,
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29918,
3317,
29922,
29900,
29889,
29945,
29892,
671,
29918,
1610,
29922,
8824,
13,
1125,
13,
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594,
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29277,
3366,
1028,
506,
287,
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565,
671,
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13,
13,
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921,
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3317,
353,
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3317,
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29900,
467,
29909,
29961,
29900,
29962,
565,
1721,
5510,
29898,
29916,
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1683,
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3317,
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29900,
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13,
1678,
343,
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3317,
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343,
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467,
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29962,
565,
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5510,
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343,
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3317,
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29900,
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13,
13,
1678,
921,
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29918,
12324,
353,
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847,
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24049,
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29916,
29918,
3317,
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29871,
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29899,
29941,
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6213,
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718,
343,
847,
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24049,
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29891,
29918,
3317,
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29896,
29872,
29899,
29941,
29892,
6213,
29897,
13,
1678,
399,
353,
921,
29891,
29918,
12324,
6736,
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29889,
25376,
488,
29898,
3594,
29918,
12324,
29892,
29871,
29929,
29947,
29892,
9685,
29922,
29900,
29897,
334,
285,
945,
29918,
974,
29918,
3317,
13,
13,
1678,
594,
532,
29889,
29277,
29961,
1989,
29918,
23959,
29962,
353,
5939,
29878,
29918,
5344,
29898,
29956,
467,
18056,
368,
29898,
7221,
29889,
29277,
29961,
29894,
1989,
14664,
517,
2395,
29878,
580,
13,
13,
1678,
515,
869,
955,
25245,
29918,
4262,
1053,
12885,
29918,
4262,
13,
1678,
515,
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955,
25245,
29918,
17987,
8497,
1053,
12885,
29918,
17987,
8497,
13,
13,
1678,
12885,
29918,
4262,
29898,
7221,
29892,
325,
1989,
29922,
1989,
29918,
23959,
29892,
2134,
29916,
29922,
5574,
29897,
13,
1678,
12885,
29918,
17987,
8497,
29898,
7221,
29892,
325,
1989,
29922,
1989,
29918,
23959,
29897,
13,
13,
13,
1753,
1207,
29918,
13092,
29918,
1761,
29898,
1989,
29892,
2758,
29918,
2378,
29922,
8824,
1125,
13,
1678,
515,
11701,
1053,
5412,
29892,
11374,
13,
13,
1678,
565,
338,
8758,
29898,
1989,
29892,
11374,
1125,
13,
4706,
1820,
353,
1820,
29889,
25027,
391,
580,
13,
1678,
338,
29918,
1761,
353,
313,
13,
4706,
338,
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29898,
1989,
29892,
313,
1761,
29892,
18761,
29892,
7442,
29889,
11651,
876,
13,
4706,
565,
2758,
29918,
2378,
13,
4706,
1683,
338,
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29898,
1989,
29892,
313,
1761,
29892,
18761,
29892,
7442,
29889,
299,
2378,
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29889,
11651,
876,
13,
1678,
1723,
13,
1678,
338,
29918,
1761,
29918,
974,
29918,
710,
353,
338,
29918,
1761,
322,
599,
29898,
275,
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29898,
667,
29892,
851,
29897,
363,
2944,
297,
1820,
29897,
13,
1678,
736,
313,
13,
4706,
5412,
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1989,
29897,
565,
338,
29918,
1761,
29918,
974,
29918,
710,
1683,
1820,
565,
338,
29918,
1761,
322,
7431,
29898,
1989,
29897,
529,
29871,
29906,
29900,
1683,
518,
1989,
29962,
13,
1678,
1723,
13,
13,
13,
1753,
1243,
29918,
29890,
326,
397,
2877,
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29916,
29892,
289,
1144,
29922,
29941,
29900,
29892,
26109,
29922,
5574,
29892,
6492,
29922,
8824,
1125,
13,
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9995,
3057,
363,
289,
326,
397,
284,
4978,
1213,
15945,
13,
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515,
4560,
2272,
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16202,
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330,
17019,
29918,
29895,
311,
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6056,
13,
13,
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27981,
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13069,
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1195,
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29916,
511,
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25376,
488,
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29916,
29892,
29871,
29929,
29929,
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29929,
29897,
13,
1678,
6856,
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1915,
3493,
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27728,
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13069,
565,
13069,
5277,
27981,
1683,
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3317,
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29916,
511,
289,
1144,
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26109,
29918,
7720,
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313,
13,
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330,
17019,
29918,
29895,
311,
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29916,
5033,
7720,
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565,
26109,
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29882,
391,
13342,
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29916,
29892,
289,
1144,
29922,
7720,
29892,
9027,
29922,
5574,
9601,
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29962,
13,
1678,
1723,
13,
13,
1678,
22645,
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29890,
1144,
847,
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29906,
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448,
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29906,
13,
1678,
22645,
4619,
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1191,
1195,
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29895,
311,
29918,
7720,
29961,
13140,
584,
22645,
718,
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29946,
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13,
13,
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19224,
29918,
29900,
353,
26109,
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7720,
7503,
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19224,
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7720,
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412,
557,
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3816,
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19224,
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4514,
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1375,
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7503,
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1402,
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6056,
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4668,
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7503,
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17531,
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518,
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313,
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7979,
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5589,
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14811,
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9027,
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1004,
550,
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1165,
7760,
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29895,
311,
29918,
6563,
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15595,
29922,
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29906,
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6276,
342,
1508,
543,
489,
613,
2927,
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2780,
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4294,
580,
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13,
1678,
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260,
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6112,
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282,
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791,
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260,
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313,
276,
622,
443,
326,
397,
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565,
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6112,
1405,
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29941,
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13,
13,
13,
1753,
4036,
29918,
1491,
11249,
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15958,
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29900,
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736,
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6484,
29922,
8824,
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3509,
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8824,
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13,
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] |
ktaned/bomb.py | MartinHarding/ktaned | 1 | 18282 | <reponame>MartinHarding/ktaned
import random
class Bomb(object):
"""Represents the Bomb context that modules should compute against"""
def __init__(self):
super(Bomb, self).__init__()
self.valid_battery_types = ['AA', 'D']
self.valid_ports = ['DVI-D', 'Parallel', 'PS/2',
'RJ-45', 'Serial', 'Stereo RCA']
self.valid_indicator_labels = ['SND', 'CLR', 'CAR',
'IND', 'FRQ', 'SIG',
'NSA', 'MSA', 'TRN',
'BOB', 'FRK']
self.reset() # Sets up defaults for bomb
def add_battery_pack(self, battery_type, quantity):
"""Add battery pack to bomb (required for certain modules)
Args:
battery_type (string): type of battery in the pack
quantity (int): number batteries in the pack
"""
if battery_type not in self.valid_battery_types:
raise Exception('Battery type ({}) must be one of {}'
.format(battery_type, self.valid_battery_types))
if quantity < 1:
raise Exception('Battery packs must have at least one battery')
self.battery_packs.append({'type': battery_type, 'quantity': quantity})
def set_battery_packs(self, battery_packs):
"""Set battery packs on the bomb (replaces existing battery packs)
Args:
battery_packs (list): list of dicts representing battery packs
"""
self.battery_packs = []
for battery_pack in battery_packs:
self.add_battery_pack(battery_pack['type'],
battery_pack['quantity'])
self.batteries = self.get_battery_count()
def get_battery_count(self):
"""Set battery packs on the bomb (replaces existing battery packs)
Returns:
battery_count (int): sum total of batteries accross all types
"""
return sum([d['quantity'] for d in self.battery_packs])
def add_port(self, port):
"""Add port to bomb (required for certain modules)
Args:
port (string): name of port
"""
if port not in self.valid_ports:
raise Exception('Port ({}) must be one of {}'
.format(port, self.valid_ports))
self.ports.append(port)
def set_ports(self, ports):
"""Set ports on the bomb (replaces existing ports)
Args:
ports (list): list of ports
"""
self.ports = []
for port in ports:
self.add_port(port)
def add_indicator(self, label, lit):
"""Add indicator to bomb (required for certain modules)
Args:
label (string): label for the indicator
lit (boolean): whether the indicator is lit (True) or not (False)
"""
if label not in self.valid_indicator_labels:
raise ValueError('Indicator "label" property must be one of {}'
.format(self.valid_indicator_labels))
if lit not in [True, False]:
raise ValueError('Indicator "lit" property must be boolean')
self.indicators.append({'label': label, 'lit': lit})
def set_indicators(self, indicators):
"""Set indicators on the bomb (replaces existing indicators)
Args:
indicators (list): list of dicts representing indicators
"""
self.indicators = []
for indicator in indicators:
self.add_indicator(indicator['label'], indicator['lit'])
def get_indicator_labels(self, lit=None):
"""Retrieve the label strings of the indicators on the bomb
Args:
indicators (list): list of indicator labels
lit (mixed): optional bool that filters by lit or unlit indicators
Returns:
list: a list of strings representing indicator labels
"""
indicator_labels = []
for indicator in self.indicators:
if lit is None or indicator['lit'] is lit:
indicator_labels.append(indicator['label'])
return indicator_labels
def check_serial_for_vowel(self):
"""Check whether the serial set contains a vowel
Returns:
bool: True if contains a vowel
"""
if not hasattr(self, 'serial') or self.serial is None:
raise Exception('Must set serial before checking for vowel')
if set(self.serial) & set('aeiou'):
return True
else:
return False
def check_serial_ends_odd(self):
"""Check whether the serial ends in an odd or even number
Returns:
bool: True if ends in odd
"""
if not hasattr(self, 'serial') or self.serial is None:
raise Exception('Must set serial before checking ends in odd')
try:
last_character_as_int = int(self.serial[-1])
except Exception as e:
return False
return bool(last_character_as_int % 2)
def add_strikes(self, strikes=1):
"""Add one or more strikes (mistake) to the bomb context
Args:
strikes (int): number of strikes to add (defaults to 1)
"""
self.strikes += strikes
if self.strikes > 2:
self.explode()
def set_strikes(self, strikes):
"""Add one or more strikes (mistake) to the bomb context
Args:
strikes (int): what number to set the strikes at
"""
self.strikes = strikes
if self.strikes > 2:
self.explode()
def reset(self):
"""Reset bomb properties to their default values (called in __init__,
but may be useful for starting over"""
self.ports = []
self.indicators = []
self.battery_packs = []
self.strikes = 0
self.serial = None
def explode(self):
"""Raise an error if the bomb explodes."""
raise Exception('Kaboom! You have exploded.')
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src/repnano/models/training_loop.py | organic-chemistry/RepNano | 5 | 78302 | <gh_stars>1-10
import subprocess
import argparse
import os
import json
import pandas as pd
import ast
parser = argparse.ArgumentParser()
parser.add_argument('--dataset', type=str)
parser.add_argument('--training_info', type=str)
parser.add_argument('--not_do', dest="do",action="store_false")
parser.add_argument('--noerror', dest="error",action="store_false")
parser.add_argument('--restart', dest="restart",action="store_true")
parser.add_argument('--training_repertory',default=None)
parser.add_argument('--root_training_dataset',default=None)
args = parser.parse_args()
with open(args.training_info,"r") as f:
training = json.loads("".join(f.readlines()))
training_repertory = training.get("training_repertory",args.training_repertory)
if training_repertory == None:
print("training repertory must be defined")
raise
if args.training_repertory != None and training_repertory != args.training_repertory:
print("Two different rep defined (one in json, one in command line)")
raise
os.makedirs(training_repertory,exist_ok=True)
dataset = pd.read_csv(args.dataset,sep=";")
for i in range(training["nloop"]):
if i == 0:
input_folder = args.root_training_dataset
else:
input_folder = output_folder
model_folder = f"{training_repertory}/model_from_initial_loop{i}/"
output_folder = f"{training_repertory}/training_from_initial_network_{i}/"
add=""
if i == training["nloop"]-1:
add = " --lstm"
elif i == training["nloop"]-2:
add = " --lstm "
percent_training = " ".join(training["training_key"])
if type(training["validation_key"]) == float:
percent_val = True
percent_validation = training["validation_key"]
else:
percent_val = False
percent_validation= " ".join(training["validation_key"])
mods = ast.literal_eval(dataset["mods"][0])
mods = ' '.join(mods)
if training.get("transition_matrix","") != "":
add += f" --transition_matrix {training['transition_matrix']}"
if not os.path.exists(model_folder) or (args.restart and i==training["nloop"]-1):
if "max_len" in training:
m = training["max_len"]
add += f" --max_len {m} "
if i >= training["nloop"]-1 and args.error:
add += " --error"
if args.restart:
add += f"--weights {model_folder}/weights.hdf5"
if not percent_val:
add += f" --percents_validation {percent_validation} "
else:
add += f" --validation {percent_validation} "
cmd = f"python src/repnano/models/train_simple.py --root_data {input_folder} --root_save {model_folder} --percents_training {percent_training} --mods {mods}" + add
#cmd = f"python src/repnano/models/train_simple.py --root_data {input_folder} --root_save {model_folder} --percents_training 0 --percents_validation 0 --error"
print(cmd)
if args.do:
subprocess.run(cmd, shell=True, check=True)
"""
try:
cmd = f"python3 preprocess_dataset.py --type dv --model {model_folder}/weights.hdf5 --output_dv {output_folder} --root_d /scratch/jarbona/data_Repnano/ --root_p data/preprocessed/ --ref /scratch/jarbona/repnanoV10/data/S288C_reference_sequence_R64-2-1_20150113.fa"
print(cmd)
subprocess.run(cmd, shell=True, check=True)
except:
"""
if not os.path.exists(output_folder):
add=""
if "max_len" in training:
m = training["max_len"]
add += f" --max_len {m}"
if training.get("transition_matrix", "") != "":
add += f" --transition_matrix {training['transition_matrix']}"
cmd = f"python3 misc/preprocess_dataset.py --minimum_percent_highsample {training.get('minimum_percent_highsample',0.5)} --type dv --model {model_folder}/weights.hdf5 --out {output_folder} --dataset {args.dataset} " + add
print(cmd)
if args.do:
subprocess.run(cmd, shell=True, check=True)
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flask_vises/__init__.py | rexzhang/flask-vises | 4 | 97641 | <reponame>rexzhang/flask-vises
#!/usr/bin/env python
# coding=utf-8
__version__ = "2.1.4"
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LAMP4SSCtests/ssc_problem_test.py | osmanmusa/learned_iterative_algorithms | 2 | 147791 | <reponame>osmanmusa/learned_iterative_algorithms<filename>LAMP4SSCtests/ssc_problem_test.py<gh_stars>1-10
#!/usr/bin/python
from __future__ import division
from __future__ import print_function
"""
This file serves as an example of how to
a) select a problem to be solved
b) select a network type
c) train the network to minimize recovery MSE
"""
import numpy as np
import math
import numpy.linalg as la
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # BE QUIET!!!!
os.environ['KMP_DUPLICATE_LIB_OK']='True'
import tensorflow as tf
np.random.seed(1) # numpy is good about making repeatable output
tf.set_random_seed(1) # on the other hand, this is basically useless (see issue 9171)
# import our problems, networks and training modules
from tools import problems,networks,train
# Evaluating (fixed-)GAMP in TensorFlow
# For debugging purposes I initialize a session here - Intialize the Session
sess = tf.Session()
# MC is the number of transmitted messages (Monte Carlo simulations)
MC = 10
# L is the number of sections
L = 4
bps = 4
# B is the size of the section
B = np.power(2, bps)
# R is the rate of the code, bits per channel use
R = 1.0
n = int(L*bps / R)
# N is the length of a uncoded SSC message
N = B * L
noise_var = 1.
# Create the basic problem structure.
prob = problems.ssc_problem(n = n, L=L, bps=bps, MC=MC, SNR_dB=8)
r_ = prob.xgen_ + tf.random_normal((N, MC), stddev=math.sqrt(noise_var))
r_rs_ = tf.reshape(tf.transpose(r_ ), (-1,B))
messages_hat_ = tf.reshape(tf.arg_max(r_rs_, 1), (MC,L))
x_hat_ = tf.one_hot(messages_hat_, depth=B)
x_hat_ = tf.transpose(tf.reshape(x_hat_, [MC, N]))
# BLER_ = 1 - tf.reduce_mean(tf.dtypes.cast(prob.messages_ == messages_hat_, dtype = tf.uint8))
error_matrix_ = tf.dtypes.cast(tf.math.equal(prob.messages_, tf.dtypes.cast(messages_hat_, tf.int32)), dtype = tf.float64)
BLER_ = 1 - tf.reduce_mean(error_matrix_)
sess = tf.Session()
messages, xgen, x_hat, messages_hat, BLER_tf, r, r_rs = sess.run([prob.messages_, prob.xgen_, x_hat_, messages_hat_, BLER_,r_, r_rs_])
BLER = 1 - np.mean((messages==messages_hat))
# print('xgen=\n',xgen)
# print('x_hat=\n',x_hat)
print('xgen.shape=\n',xgen.shape)
print('x_hat.shape=\n',x_hat.shape)
print('r.shape=\n',r.shape)
print('r_rs.shape=\n',r_rs.shape)
print('messages=\n',messages)
print('messages_hat=\n',messages_hat)
print('BLER=\n',BLER)
print('BLER_tf=\n',BLER_tf)
messages, xgen, ygen = sess.run([prob.messages_, prob.xgen_, prob.ygen_])
# print('messages=\n',messages)
# print('xgen=\n',xgen)
# print('ygen=\n',ygen)
# print('xgen.shape=\n',xgen.shape)
# print('ygen.shape=\n',ygen.shape)
sess.close() | [
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5-gui.py | theseana/pesteh | 1 | 44977 | <reponame>theseana/pesteh
from tkinter import *
root = Tk()
root.config(bg='yellow')
l1 = Label(root, text='Hello World!', bg='magenta')
l1.pack(side=LEFT)
b1 = Button(root, text='Click Me Please!', bg='cyan')
b1.pack(side=LEFT)
l2 = Label(root, text='Ta-Da!', bg='green')
l2.pack(side=LEFT)
root.mainloop()
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unit_tests/test_actions_service.py | canonical/charm-ceph-osd | 17 | 94928 | # Copyright 2020 Canonical Ltd
#
# 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 mock
from contextlib import contextmanager
from actions import service
from hooks import utils
from test_utils import CharmTestCase
class CompletedProcessMock:
def __init__(self, stdout=b'', stderr=b''):
self.stdout = stdout
self.stderr = stderr
class ServiceActionTests(CharmTestCase):
_PRESENT_SERVICES = [
"[email protected]",
"[email protected]",
"[email protected]",
]
_TARGET_ALL = 'ceph-osd.target'
_CHECK_CALL_TIMEOUT = 300
def __init__(self, methodName='runTest'):
super(ServiceActionTests, self).__init__(methodName)
def setUp(self, obj=None, patches=None):
super(ServiceActionTests, self).setUp(
service,
['subprocess', 'function_fail',
'log', 'assess_status', 'shutil']
)
present_services = '\n'.join(self._PRESENT_SERVICES).encode('utf-8')
self.shutil.which.return_value = '/bin/systemctl'
self.subprocess.check_call.return_value = None
self.subprocess.run.return_value = CompletedProcessMock(
stdout=present_services)
@contextmanager
def func_call_arguments(self, osds=None):
with mock.patch("utils.function_get") as mock_function_get:
self._func_args = {'osds': osds}
mock_function_get.side_effect = \
lambda arg: self._func_args.get(arg)
yield
def assert_action_start_fail(self, msg):
self.assert_function_fail(service.START, msg)
def assert_action_stop_fail(self, msg):
self.assert_function_fail(service.STOP, msg)
def assert_function_fail(self, action, msg):
expected_error = "Action '{}' failed: {}".format(action, msg)
self.function_fail.assert_called_with(expected_error)
@staticmethod
def call_action_start():
service.main(['start'])
@staticmethod
def call_action_stop():
service.main(['stop'])
def test_systemctl_execute_all(self):
action = 'start'
services = utils.ALL
expected_call = mock.call(['systemctl', action, self._TARGET_ALL],
timeout=self._CHECK_CALL_TIMEOUT)
service.systemctl_execute(action, services)
self.subprocess.check_call.assert_has_calls([expected_call])
def systemctl_execute_specific(self):
action = 'start'
services = ['[email protected]', '[email protected]']
systemctl_call = ['systemctl', action] + services
expected_call = mock.call(systemctl_call,
timeout=self._CHECK_CALL_TIMEOUT)
service.systemctl_execute(action, services)
self.subprocess.check_call.assert_has_calls([expected_call])
def test_id_translation(self):
service_ids = {1, utils.ALL, 2}
expected_names = [
'[email protected]',
utils.ALL,
'[email protected]',
]
service_names = service.osd_ids_to_service_names(service_ids)
self.assertEqual(sorted(service_names), sorted(expected_names))
def test_skip_service_presence_check(self):
service_list = [utils.ALL]
service.check_service_is_present(service_list)
self.subprocess.run.assert_not_called()
def test_raise_all_missing_services(self):
missing_service_id = '99,100'
missing_list = []
for id_ in missing_service_id.split(','):
missing_list.append("ceph-osd@{}.service".format(id_))
service_list_cmd = ['systemctl', 'list-units', '--full', '--all',
'--no-pager', '-t', 'service']
err_msg = 'Some services are not present on this ' \
'unit: {}'.format(missing_list)
with self.assertRaises(RuntimeError, msg=err_msg):
service.check_service_is_present(missing_list)
self.subprocess.run.assert_called_with(service_list_cmd,
stdout=self.subprocess.PIPE,
timeout=30)
def test_fail_execute_unknown_action(self):
action = 'foo'
err_msg = 'Unknown action "{}"'.format(action)
with self.assertRaises(RuntimeError, msg=err_msg):
service.execute_action(action)
@mock.patch.object(service, 'systemctl_execute')
def test_execute_action(self, _):
with self.func_call_arguments(osds=utils.ALL):
service.execute_action(service.START)
service.systemctl_execute.assert_called_with(service.START,
[utils.ALL])
service.execute_action(service.STOP)
service.systemctl_execute.assert_called_with(service.STOP,
[utils.ALL])
@mock.patch.object(service, 'execute_action')
def test_action_stop(self, execute_action):
self.call_action_stop()
execute_action.assert_called_with(service.STOP)
@mock.patch.object(service, 'execute_action')
def test_action_start(self, execute_action):
self.call_action_start()
execute_action.assert_called_with(service.START)
def test_actions_requires_systemd(self):
"""Actions will fail if systemd is not present on the system"""
self.shutil.which.return_value = None
expected_error = 'This action requires systemd'
with self.func_call_arguments(osds='all'):
self.call_action_start()
self.assert_action_start_fail(expected_error)
self.call_action_stop()
self.assert_action_stop_fail(expected_error)
self.subprocess.check_call.assert_not_called()
def test_unknown_action(self):
action = 'foo'
err_msg = 'Action {} undefined'.format(action)
service.main([action])
self.function_fail.assert_called_with(err_msg)
@mock.patch.object(service, 'execute_action')
def test_action_failure(self, start_function):
err_msg = 'Test Error'
service.execute_action.side_effect = RuntimeError(err_msg)
self.call_action_start()
self.assert_action_start_fail(err_msg)
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] |
svc_tools/decorators.py | tylerwince/svc-tools | 0 | 141978 | """Decorators that enable easy modifications to function behavior."""
import logging
import time
from functools import wraps
from typing import Callable
LOG = logging.getLogger("svc_tools")
def timer(log_level: Callable):
"""Time a function and log the time it took to execute.
If you want to know how long a function takes to execute
ang log alongside your application logs, then decorate
your function with this.
:param log_level: logging method to use in call
:returns: Whatever your original function returns
Usage ::
>>> from svc_tools import timer
>>> from time import sleep
>>> import logging
>>> @timer(logging.warning)
>>> def myFunc(sleep_time):
... # whatever you want to time
... sleep(sleep_time)
>>> myFunc(10)
WARNING:root:myFunc took 10.000502109527588 to run.
"""
def decorator(func):
"""Decorate the original function."""
@wraps(func)
def new_timed_func(*args, **kwargs):
"""Do the timing."""
start_time = time.time()
returned_value = func(*args, **kwargs)
total_time = time.time() - start_time
log_level(f"{func.__name__} took {total_time} to run.")
return returned_value
return new_timed_func
return decorator
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datalad/customremotes/tests/test_archives.py | yarikoptic/datalad | 0 | 1602593 | <gh_stars>0
# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
# ex: set sts=4 ts=4 sw=4 noet:
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
# See COPYING file distributed along with the datalad package for the
# copyright and license terms.
#
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
"""Tests for customremotes archives providing dl+archive URLs handling"""
from ..archives import ArchiveAnnexCustomRemote
from ..base import AnnexExchangeProtocol
from ...support.annexrepo import AnnexRepo
from ...consts import ARCHIVES_SPECIAL_REMOTE
from ...tests.utils import *
from ...cmd import Runner, GitRunner
from ...utils import _path_
from . import _get_custom_runner
# both files will have the same content
# fn_inarchive_obscure = 'test.dat'
# fn_extracted_obscure = 'test2.dat'
fn_inarchive_obscure = get_most_obscure_supported_name()
fn_archive_obscure = fn_inarchive_obscure.replace('a', 'b') + '.tar.gz'
fn_extracted_obscure = fn_inarchive_obscure.replace('a', 'z')
#import line_profiler
#prof = line_profiler.LineProfiler()
# TODO: with_tree ATM for archives creates this nested top directory
# matching archive name, so it will be a/d/test.dat ... we don't want that probably
@with_tree(
tree=(('a.tar.gz', {'d': {fn_inarchive_obscure: '123'}}),
('simple.txt', '123'),
(fn_archive_obscure, (('d', ((fn_inarchive_obscure, '123'),)),)),
(fn_extracted_obscure, '123')))
@with_tempfile()
def check_basic_scenario(fn_archive, fn_extracted, direct, d, d2):
annex = AnnexRepo(d, runner=_get_custom_runner(d), direct=direct)
annex.init_remote(
ARCHIVES_SPECIAL_REMOTE,
['encryption=none', 'type=external', 'externaltype=%s' % ARCHIVES_SPECIAL_REMOTE,
'autoenable=true'
])
assert annex.is_special_annex_remote(ARCHIVES_SPECIAL_REMOTE)
# We want two maximally obscure names, which are also different
assert(fn_extracted != fn_inarchive_obscure)
annex.add(fn_archive, commit=True, msg="Added tarball")
annex.add(fn_extracted, commit=True, msg="Added the load file")
# Operations with archive remote URL
annexcr = ArchiveAnnexCustomRemote(path=d)
# few quick tests for get_file_url
eq_(annexcr.get_file_url(archive_key="xyz", file="a.dat"), "dl+archive:xyz#path=a.dat")
eq_(annexcr.get_file_url(archive_key="xyz", file="a.dat", size=999), "dl+archive:xyz#path=a.dat&size=999")
# see https://github.com/datalad/datalad/issues/441#issuecomment-223376906
# old style
eq_(annexcr._parse_url("dl+archive:xyz/a.dat#size=999"), ("xyz", "a.dat", {'size': 999}))
eq_(annexcr._parse_url("dl+archive:xyz/a.dat"), ("xyz", "a.dat", {})) # old format without size
# new style
eq_(annexcr._parse_url("dl+archive:xyz#path=a.dat&size=999"), ("xyz", "a.dat", {'size': 999}))
eq_(annexcr._parse_url("dl+archive:xyz#path=a.dat"), ("xyz", "a.dat", {})) # old format without size
file_url = annexcr.get_file_url(
archive_file=fn_archive,
file=fn_archive.replace('.tar.gz', '') + '/d/'+fn_inarchive_obscure)
annex.add_url_to_file(fn_extracted, file_url, ['--relaxed'])
annex.drop(fn_extracted)
list_of_remotes = annex.whereis(fn_extracted, output='descriptions')
in_('[%s]' % ARCHIVES_SPECIAL_REMOTE, list_of_remotes)
assert_false(annex.file_has_content(fn_extracted))
annex.get(fn_extracted)
assert_true(annex.file_has_content(fn_extracted))
annex.rm_url(fn_extracted, file_url)
assert_false(annex.drop(fn_extracted)['success'])
annex.add_url_to_file(fn_extracted, file_url)
annex.drop(fn_extracted)
annex.get(fn_extracted)
annex.drop(fn_extracted) # so we don't get from this one next
# Let's create a clone and verify chain of getting file through the tarball
cloned_annex = AnnexRepo.clone(d, d2,
runner=_get_custom_runner(d2),
direct=direct)
# we still need to enable manually atm that special remote for archives
# cloned_annex.enable_remote('annexed-archives')
assert_false(cloned_annex.file_has_content(fn_archive))
assert_false(cloned_annex.file_has_content(fn_extracted))
cloned_annex.get(fn_extracted)
assert_true(cloned_annex.file_has_content(fn_extracted))
# as a result it would also fetch tarball
assert_true(cloned_annex.file_has_content(fn_archive))
# Check if protocol was collected
if os.environ.get('DATALAD_TESTS_PROTOCOLREMOTE'):
assert_is_instance(annex.cmd_call_wrapper.protocol, AnnexExchangeProtocol)
protocol_file = _path_(annex.path,
'.git/bin/git-annex-remote-datalad-archive')
ok_file_has_content(protocol_file, "VERSION 1", re_=True, match=False)
ok_file_has_content(protocol_file, "GETAVAILABILITY", re_=True, match=False)
ok_file_has_content(protocol_file, "#!/bin/bash", re_=True, match=False)
else:
assert_false(isinstance(annex.cmd_call_wrapper.protocol, AnnexExchangeProtocol))
# verify that we can drop if original archive gets dropped but available online:
# -- done as part of the test_add_archive_content.py
# verify that we can't drop a file if archive key was dropped and online archive was removed or changed size! ;)
@with_tree(
tree={'a.tar.gz': {'d': {fn_inarchive_obscure: '123'}}}
)
def test_annex_get_from_subdir(topdir):
from datalad.api import add_archive_content
annex = AnnexRepo(topdir, init=True)
annex.add('a.tar.gz', commit=True)
add_archive_content('a.tar.gz', annex=annex, delete=True)
fpath = opj(topdir, 'a', 'd', fn_inarchive_obscure)
with chpwd(opj(topdir, 'a', 'd')):
runner = Runner()
runner(['git', 'annex', 'drop', fn_inarchive_obscure]) # run git annex drop
assert_false(annex.file_has_content(fpath)) # and verify if file deleted from directory
runner(['git', 'annex', 'get', fn_inarchive_obscure]) # run git annex get
assert_true(annex.file_has_content(fpath)) # and verify if file got into directory
def test_get_git_environ_adjusted():
gitrunner = GitRunner()
env = {"GIT_DIR": "../../.git", "GIT_WORK_TREE": "../../", "TEST_VAR": "Exists"}
# test conversion of relevant env vars from relative_path to correct absolute_path
adj_env = gitrunner.get_git_environ_adjusted(env)
assert_equal(adj_env["GIT_DIR"], abspath(env["GIT_DIR"]))
assert_equal(adj_env["GIT_WORK_TREE"], abspath(env["GIT_WORK_TREE"]))
# test if other environment variables passed to function returned unaltered
assert_equal(adj_env["TEST_VAR"], env["TEST_VAR"])
# test import of sys_env if no environment passed to function
sys_env = gitrunner.get_git_environ_adjusted()
assert_equal(sys_env["PWD"], os.environ.get("PWD"))
def test_basic_scenario():
yield check_basic_scenario, 'a.tar.gz', 'simple.txt', False
if not on_windows:
yield check_basic_scenario, 'a.tar.gz', 'simple.txt', True
#yield check_basic_scenario, 'a.tar.gz', fn_extracted_obscure, False
#yield check_basic_scenario, fn_archive_obscure, 'simple.txt', False
yield check_basic_scenario, fn_archive_obscure, fn_extracted_obscure, False
def test_no_rdflib_loaded():
# rely on rdflib polluting stdout to see that it is not loaded whenever we load this remote
# since that adds 300ms delay for no immediate use
from ...cmd import Runner
runner = Runner()
with swallow_outputs() as cmo:
runner.run([sys.executable, '-c', 'import datalad.customremotes.archives, sys; print([k for k in sys.modules if k.startswith("rdflib")])'],
log_stdout=False, log_stderr=False)
# print cmo.out
assert_not_in("rdflib", cmo.out)
assert_not_in("rdflib", cmo.err)
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house_prices_regression_model/predict.py | jmonsalverodilla/house_prices_regression_model | 0 | 48650 | import typing as t
import numpy as np
import pandas as pd
from house_prices_regression_model import __version__ as VERSION
from house_prices_regression_model.processing.data_manager import load_pipeline
from house_prices_regression_model.config.core import load_config_file, SETTINGS_PATH
from house_prices_regression_model.processing.data_validation import validate_inputs
# Config files
config = load_config_file(SETTINGS_PATH)
PIPELINE_ARTIFACT_NAME = config["PIPELINE_ARTIFACT_NAME"]
pipeline_file_name = f"{PIPELINE_ARTIFACT_NAME}_v{VERSION}.pkl"
cb_pipe = load_pipeline(file_name=pipeline_file_name)
#Function
def make_prediction(*,input_data: t.Union[pd.DataFrame, dict],) -> list:
"""Make a prediction using a saved model pipeline."""
df = pd.DataFrame(input_data)
validated_df, error_dict = validate_inputs(input_data=df)
errors_list = list(error_dict.values())
results = {'model_output': None}
if error_dict == {}:
log_predictions = cb_pipe.predict(validated_df)
predictions = [np.exp(pred) for pred in log_predictions]
results['model_output'] = predictions
else:
results['model_output'] = 'Errors making prediction:' + ' '.join(map(str, errors_list))
return results
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mmaction/models/tenons/backbones/__init__.py | arpanmangal/coinaction | 1 | 123738 | <reponame>arpanmangal/coinaction
from .bninception import BNInception
from .resnet import ResNet
from .inception_v1_i3d import InceptionV1_I3D
from .resnet_i3d import ResNet_I3D
from .resnet_s3d import ResNet_S3D
__all__ = [
'BNInception',
'ResNet',
'InceptionV1_I3D',
'ResNet_I3D',
'ResNet_S3D',
]
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loss/sequence_elbo.py | Wu-Chenyang/SMC-POMDP | 0 | 65767 | <reponame>Wu-Chenyang/SMC-POMDP<filename>loss/sequence_elbo.py
import torch
import torch.nn as nn
import torch.nn.functional as F
import pyro.distributions as D
from pyro.distributions.kl import kl_divergence
from typing import NamedTuple
import math
def sequence_elbo(proposal: nn.Module, model: nn.Module, batched_data: NamedTuple):
# Dimensionality Analysis
#
# Observations: [batch_size, sequence_length, obs_dim]
# Weights: [num_particles, batch_size, num_timesteps, 1]
# Final Weights: [num_particles, batch_size, 1]
# LSTM State: [num_particles, batch_size, hidden_dim]
# Current States: [num_particles, batch_size, state_dim]
# Current Observations: [1, batch_size, obs_dim]
# Proposal Log Probabilities: [num_particles, batch_size, num_timesteps, 1]
# Log Likelihood: [batch_size, 1]
# observations = model.encode(batched_data.observations)
observations = batched_data.observations
actions = batched_data.actions
categories = batched_data.prior_mixtures
batch_size, seq_len, _ = observations.shape
batch_shape = (batch_size,)
kld_loss = torch.tensor([0.0], device=observations.device)
nll_loss = torch.tensor([0.0], device=observations.device)
kwargs = proposal.reset(observations, actions, batch_shape)
proposal_distribution, kwargs = proposal.prior_proposal(categories, batch_shape, **kwargs)
# proposal_distribution, kwargs = proposal.prior_proposal(observations, batch_shape, **kwargs)
current_states = proposal_distribution.rsample()
prior_distribution, kwargs = model.prior(categories, batch_shape, **kwargs)
kld_loss += torch.mean(kl_divergence(proposal_distribution, prior_distribution))
# observation_distribution, kwargs= model.observation(current_states, **kwargs)
# nll_loss -= observation_distribution.log_prob(current_observations)
for i in range(seq_len):
current_observations = observations[None, :, i, :]
current_actions = actions[None, :, i, :]
previous_states = current_states
proposal_distribution, kwargs = proposal.transition_proposal(current_states, current_actions, current_observations, i, **kwargs)
current_states = proposal_distribution.rsample()
transition_distribution, kwargs= model.transition(previous_states, current_actions, **kwargs)
kld_loss += torch.mean(kl_divergence(proposal_distribution, transition_distribution))
observation_distribution, kwargs = model.observation(current_actions, current_states, **kwargs)
nll_loss -= torch.mean(observation_distribution.log_prob(current_observations))
kld_loss /= seq_len
nll_loss /= seq_len
return kld_loss, nll_loss | [
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tests/migrations/0014_auto_20200327_1152.py | intellineers/django-bridger | 2 | 53099 | <filename>tests/migrations/0014_auto_20200327_1152.py
# Generated by Django 2.2.11 on 2020-03-27 10:52
import django_fsm
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("tests", "0013_auto_20200219_1324"),
]
operations = [
migrations.AlterField(
model_name="modeltest",
name="status_field",
field=django_fsm.FSMField(
choices=[("status1", "Status1"), ("status2", "Status2"), ("status3", "Status3"),],
default="status1",
max_length=50,
verbose_name="Status",
),
),
]
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] |
multiprobe/data/language.py | h324yang/multiprobe | 0 | 199684 | from dataclasses import dataclass
from collections import defaultdict
from functools import lru_cache
from typing import Dict, List
import json
import warnings
from scipy.spatial import distance as spd
from torch.distributions.categorical import Categorical
from tqdm import tqdm
import joblib
import langdetect
import numpy as np
import torch
import yaml
from multiprobe.utils import jsd_, chunk
class LanguageFamilyData(object):
def __init__(self, family_map):
self.family_map = family_map
self.code_family_map = defaultdict(lambda: 'none')
for family, languages in family_map.items():
for lang, data in languages.items():
self.code_family_map[data['code']] = family
@property
def families(self):
return list(self.family_map.keys())
def find_family(self, lang_code):
return self.code_family_map[lang_code]
@classmethod
def from_yaml(cls, filename):
with open(filename) as f:
family_map = yaml.load(f)
return cls(family_map)
def safe_js(p, q):
js_dist = spd.jensenshannon(p, q, 2.0)
# SciPy has numerical issues
if np.isnan(js_dist):
js_dist = 0
return js_dist
def sum_js(p_list, q_list, verbose=True):
with warnings.catch_warnings():
warnings.filterwarnings('ignore')
return sum(safe_js(p, q) for p, q in zip(p_list, q_list))
def sum_js_cuda(p_list, q_list):
dist = 0
for p, q in tqdm(zip(p_list, q_list), position=1):
js_dist = jsd_(torch.Tensor(p).cuda(), torch.Tensor(q).cuda()).cpu().item()
dist += js_dist
return dist
@dataclass
class TokenLanguageStatistics(object):
data: Dict[str, Dict[str, int]]
vocab: Dict[str, int]
languages: List[str]
@classmethod
def from_file(cls, path):
with open(path) as f:
data = json.load(f)
languages = sorted(data['languages'])
return cls(data['statistics'], data['vocab'], languages)
def compute_distribution(self, tokens, weights=None):
probs = []
new_weights = []
for token, weight in zip(tokens, weights):
token_probs = np.zeros(len(self.languages))
if token not in self.data:
continue
for language, count in self.data[token].items():
token_probs[self.languages.index(language)] += count
if np.sum(token_probs) > 0:
token_probs = token_probs / np.sum(token_probs)
probs.append(token_probs)
new_weights.append(weight)
if len(probs) == 0:
raise ValueError('No counts found for those tokens.')
if weights is None:
probs = np.mean(np.array(probs), 0)
else:
weights = np.array(new_weights)
probs = np.array(probs)
probs = np.sum(np.repeat(np.expand_dims(weights, 1), probs.shape[1], 1) * probs, 0) / np.sum(weights)
return Categorical(probs=torch.Tensor(probs))
@lru_cache(maxsize=1000000)
def detect_language(string):
return langdetect.detect(string)
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522,
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2
] |
examples/custom_detection_video.py | vickyvava/ImageAI | 7,141 | 85187 | <filename>examples/custom_detection_video.py
from imageai.Detection.Custom import CustomVideoObjectDetection
import os
execution_path = os.getcwd()
video_detector = CustomVideoObjectDetection()
video_detector.setModelTypeAsYOLOv3()
video_detector.setModelPath("hololens-ex-60--loss-2.76.h5") # download via https://github.com/OlafenwaMoses/ImageAI/releases/download/essential-v4/hololens-ex-60--loss-2.76.h5
video_detector.setJsonPath("detection_config.json") # download via https://github.com/OlafenwaMoses/ImageAI/releases/download/essential-v4/detection_config.json
video_detector.loadModel()
video_detector.detectObjectsFromVideo(input_file_path="holo1.mp4",
output_file_path=os.path.join(execution_path, "holo1-detected3"),
frames_per_second=20,
minimum_percentage_probability=40,
log_progress=True) | [
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dsl/utils/filter_freq.py | juditacs/dsl | 2 | 145204 | <filename>dsl/utils/filter_freq.py
from os import listdir, path
from argparse import ArgumentParser
from collections import defaultdict
from dsl.features.featurize import Tokenizer, WordNgram
def parse_args():
p = ArgumentParser()
p.add_argument('--train', type=str)
p.add_argument('--train-out', type=str)
p.add_argument('--test', type=str)
p.add_argument('--test-out', type=str)
p.add_argument('--topn', type=int, default=100)
p.add_argument('--N', type=int, default=1, help='N of wordngram counter')
p.add_argument('--mode', choices=['keep', 'remove'], default='keep')
return p.parse_args()
def read_topn_in_dir(basedir, counters, topn=100):
topwords = {}
for fn in sorted(listdir(basedir)):
with open(path.join(basedir, fn)) as f:
counters[fn].count_words_in_stream(f)
topwords[fn] = counters[fn].get_topn_words(topn)
return topwords
def filter_dir_to_top(indir, outdir, topwords, tokenizer):
for fn in sorted(listdir(indir)):
infile = open(path.join(indir, fn))
outfile = open(path.join(outdir, fn), 'w')
for sentence in tokenizer.tokenize_stream(infile):
outfile.write(' '.join(filter(lambda x: x in topwords[fn], sentence)).encode('utf8') + '\n')
infile.close()
outfile.close()
def main():
args = parse_args()
t = Tokenizer()
counters = defaultdict(lambda: WordNgram(t, N=args.N))
topn = read_topn_in_dir(args.train, counters, args.topn)
filter_dir_to_top(args.train, args.train_out, topn, t)
filter_dir_to_top(args.test, args.test_out, topn, t)
if __name__ == '__main__':
main()
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Taller Funciones/Untitled-2.py | SantiVillarreal/Taller_Estructuras | 0 | 78523 |
"""
Entradas:
lista-->list-->lista
elemento->str-->elemento
Salidas
lista-->lista
"""
frutas = open('frutas.txt', 'r')
lista_frutas = []
for i in frutas:
lista_frutas.append(i)
def eliminar_un_caracter(lista: list, elemento: str):
auxilar = []
for i in lista:
a = i.replace(elemento, "")
auxilar.append(a)
return auxilar
if __name__ == "__main__":
nueva = eliminar_un_caracter(lista_frutas, ("a"))
print(nueva) | [
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trac/trac/web/tests/wikisyntax.py | HelionDevPlatform/bloodhound | 84 | 103686 | <reponame>HelionDevPlatform/bloodhound
import unittest
from trac.wiki.tests import formatter
TEST_CASES = """
============================== htdocs: links resolver
htdocs:release-1.0.tar.gz
[htdocs:release-1.0.tar.gz Release 1.0]
------------------------------
<p>
<a href="/chrome/site/release-1.0.tar.gz">htdocs:release-1.0.tar.gz</a>
</p>
<p>
<a href="/chrome/site/release-1.0.tar.gz">Release 1.0</a>
</p>
------------------------------
"""
def suite():
return formatter.suite(TEST_CASES, file=__file__)
if __name__ == '__main__':
unittest.main(defaultTest='suite')
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src/main/python/fontspecs.py | sourcery-ai-bot/retcom | 10 | 1600553 | <filename>src/main/python/fontspecs.py
from fontTools.ttLib import TTFont
from fontTools.ttLib.tables._c_m_a_p import CmapSubtable
def fetchFontSpec(path):
font = TTFont(path)
cmap = font['cmap']
t = cmap.getcmap(3,1).cmap
s = font.getGlyphSet()
unitsPerEm = font['head'].unitsPerEm
return {
'font' : font,
't' : t,
's' : s,
'upm' : unitsPerEm
}
def getCharDimensions(char, ptSize, fontSpec):
t = fontSpec['t']
s = fontSpec['s']
upm = fontSpec['upm']
oc = ord(char)
if oc in t and t[oc] in s:
w = s[t[oc]].width
else:
w = s['.notdef'].width
return [w*ptSize/upm, ptSize]
def getTextDimensions(text, ptSize, fontSpec, dim=[0,0]):
lines = text.split('\n')
if len(lines) == 1:
w = 0
t = fontSpec['t']
s = fontSpec['s']
upm = fontSpec['upm']
for c in text:
oc = ord(c)
if oc in t and t[oc] in s:
w += s[t[oc]].width
else:
w += s['.notdef'].width
dim0_new = w*ptSize/upm
if dim0_new > dim[0]:
dim[0] = dim0_new
dim[1] += ptSize
else:
for line in lines:
dim = getTextDimensions(line, ptSize, fontSpec, dim)
return dim
HALF2FULLWIDTH = dict((i, i + 0xFEE0) for i in range(0x21, 0x7F))
FULL2HALFWIDTH = dict((i + 0xFEE0, i) for i in range(0x21, 0x7F))
def half2fullWidth(txt:str):
return txt.translate(HALF2FULLWIDTH)
def full2halfWidth(txt:str):
return txt.translate(FULL2HALFWIDTH)
class FontGeom(object):
def __init__(self, path, ptSize=12):
self.path = path
self.fontSpec = fetchFontSpec(path)
self.ptSize = ptSize
def getTextDimensions(self, text, ptSize=None):
if not ptSize:
ptSize = self.ptSize
return getTextDimensions(text, ptSize, self.fontSpec, [0,0])
def getTextWidth(self, text, ptSize=None):
self.getTextDimensions(text, ptSize)[0]
def getTextHeight(self, text, ptSize=None):
self.getTextDimensions(text, ptSize)[1]
def getTextAspectRatio(self, text, ptSize=None, order='w/h'):
w, h = self.getTextDimensions(text, ptSize)
return eval(order)
def getCharDimensions(self, char, ptSize=None):
if not ptSize:
ptSize = self.ptSize
return getCharDimensions(char, ptSize, self.fontSpec)
def getCharAspectRatio(self, char, ptSize=None, order='w/h'):
w, h = self.getTextDimensions(char, ptSize)
return eval(order)
if __name__ == "__main__":
text = 'This is a test\nABCDEFGHIJKLMNOPQRSTUVW'
fontSpec = fetchFontSpec('/Library/Fonts/Courier New.ttf')
print(getTextDimensions(text, 12, fontSpec, [0,0]))
fg = FontGeom('/Library/Fonts/Courier New.ttf', 12)
print(fg.getTextDimensions(text))
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] |
exe 6.py | LucasGabrielTheodoro/Lista-de-python | 0 | 147658 | <gh_stars>0
n1 = int(input('Digite o preço do primeiro produto: '))
n2 = int(input('Digite o preço do segundo número: '))
desconto1= ((n1 * 8) / 100) - n1
desconto2= ((n2 * 11) / 100) - n2
total = (desconto1 + desconto2) *-1
print ('Com o desconto no primeiro produto de 8% e de 11% no segundo produt, o total vai ser de {}'.format (total)) | [
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2
] |
ecs/docstash/tests/urls.py | programmierfabrik/ecs | 9 | 1611155 | import json
from django.conf.urls import url
from django.http import HttpResponse
from ecs.docstash.decorators import with_docstash
@with_docstash()
def simple_post_view(request):
if request.method == 'POST':
request.docstash.value = request.POST.dict()
request.docstash.save()
return HttpResponse(json.dumps(request.docstash.value), content_type='text/json')
urlpatterns = (
url(r'^simple_post/(?:(?P<docstash_key>.*)/)?$', simple_post_view),
)
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2
] |
src/SparseSC/cli/scgrad.py | wofein/SparseSC | 34 | 118344 | #!/usr/bin/env python
"""
A service like daemon for calculating components of the gradient
"""
# pylint: disable=invalid-name, unused-import, multiple-imports
import platform
import numpy as np
import uuid
import sys, time, os, atexit, json
from SparseSC.cli.daemon import Daemon
from yaml import load, dump
import tempfile
try:
from yaml import CLoader as Loader, CDumper as Dumper
except ImportError:
from yaml import Loader, Dumper
# pluck = lambda d, *args: (d[arg] for arg in args)
def pluck(d, *args):
"""
pluckr
"""
# print("hello pluckr"); sys.stdout.flush()
out = [None] * len(args)
for i, key in enumerate(args):
# print("key: " + key); sys.stdout.flush()
try:
out[i] = d[key]
except KeyError:
raise RuntimeError("no such key '{}'".format(key))
return out
def grad_part(common, part, k):
"""
Calculate a single component of the gradient
"""
N0, N1, in_controls, splits, w_pen, treated_units, Y_treated, Y_control, dA_dV_ki, dB_dV_ki = pluck(
common,
"N0",
"N1",
"in_controls",
"splits",
"w_pen",
"treated_units",
"Y_treated",
"Y_control",
"dA_dV_ki",
"dB_dV_ki",
)
in_controls2 = [np.ix_(i, i) for i in in_controls]
A, weights, b_i = pluck(part, "A", "weights", "b_i")
dA_dV_ki_k, dB_dV_ki_k = dA_dV_ki[k], dB_dV_ki[k]
dPI_dV = np.zeros((N0, N1)) # stupid notation: PI = W.T
try:
for i, (_, (_, test)) in enumerate(zip(in_controls, splits)):
dA = dA_dV_ki_k[i]
dB = dB_dV_ki_k[i]
try:
b = np.linalg.solve(A[in_controls2[i]], dB - dA.dot(b_i[i]))
except np.linalg.LinAlgError as exc:
print("Unique weights not possible.")
if w_pen == 0:
print("Try specifying a very small w_pen rather than 0.")
raise exc
dPI_dV[np.ix_(in_controls[i], treated_units[test])] = b
# einsum is faster than the equivalent (Ey * Y_control.T.dot(dPI_dV).T.getA()).sum()
return 2 * np.einsum(
"ij,kj,ki->", (weights.T.dot(Y_control) - Y_treated), Y_control, dPI_dV
)
except Exception as err:
print("{}: {}".format(err.__class__.__name__, getattr(err, "message", "<>")))
raise RuntimeError("bye from scgrad")
DAEMON_FIFO = "/tmp/sc-daemon.fifo"
DAEMON_PID = "/tmp/sc-gradient-daemon.pid"
#-- print("DAEMON_FIFO: " + DAEMON_FIFO)
#-- print("DAEMON_PID: " + DAEMON_PID)
_CONTAINER_OUTPUT_FILE = "output.yaml" # Standard Output file
_GRAD_COMMON_FILE = "common.yaml"
_GRAD_PART_FILE = "part.yaml"
_BASENAMES = [_GRAD_COMMON_FILE, _GRAD_PART_FILE, _CONTAINER_OUTPUT_FILE]
class TestDaemon(Daemon):
"""
A daemon which calculates Sparse SC gradient components
"""
def run(self):
print("run says hi: ")
sys.stdout.flush()
# pylint: disable=no-self-use
while True:
with open(DAEMON_FIFO, "r") as fifo:
try:
params = fifo.read()
print("run says hi: " + params)
sys.stdout.flush()
tmpdirname, return_fifo, k = json.loads(params)
common_file, part_file, out_file = [
os.join(tmpdirname, name) for name in _BASENAMES
]
print([common_file, part_file, out_file, return_fifo, k])
sys.stdout.flush()
except: # pylint: disable=bare-except
# SOMETHING WENT WRONG, RESPOND WITH A NON-ZERO
try:
with open(return_fifo, "w") as rf:
rf.write("1")
except: # pylint: disable=bare-except
pass
else:
print("daemon something went wrong: ")
sys.stdout.flush()
else:
# SEND THE SUCCESS RESPONSE
print("daemon all done: ")
sys.stdout.flush()
with open(return_fifo, "w") as rf:
rf.write("0")
class GradientDaemon(Daemon):
"""
A daemon which calculates Sparse SC gradient components
"""
def run(self):
# pylint: disable=no-self-use
while True:
with open(DAEMON_FIFO, "r") as fifo:
try:
params = fifo.read()
print("params: " + params)
sys.stdout.flush()
tmpdirname, return_fifo, k = json.loads(params)
print(_BASENAMES)
for file in os.listdir(tmpdirname):
print(file)
common_file, part_file, out_file = [
os.path.join(tmpdirname, name) for name in _BASENAMES
]
print([common_file, part_file, out_file, return_fifo, k])
sys.stdout.flush()
# LOAD IN THE INPUT FILES
with open(common_file, "r") as fp:
common = load(fp, Loader=Loader)
with open(part_file, "r") as fp:
part = load(fp, Loader=Loader)
# DO THE WORK
print("about to do work: ")
sys.stdout.flush()
grad = grad_part(common, part, int(k))
print("did work: ")
sys.stdout.flush()
# DUMP THE RESULT TO THE OUTPUT FILE
with open(out_file, "w") as fp:
fp.write(dump(grad, Dumper=Dumper))
except Exception as err: # pylint: disable=bare-except
# SOMETHING WENT WRONG, RESPOND WITH A NON-ZERO
try:
with open(return_fifo, "w") as rf:
rf.write("1")
except: # pylint: disable=bare-except
print("double failed...: ")
sys.stdout.flush()
else:
print(
"failed with {}: {}",
err.__class__.__name__,
getattr(err, "message", "<>"),
)
sys.stdout.flush()
else:
# SEND THE SUCCESS RESPONSE
print("success...: ")
sys.stdout.flush()
with open(return_fifo, "w") as rf:
rf.write("0")
print("and wrote about it...: ")
sys.stdout.flush()
def main(test=False): # pylint: disable=inconsistent-return-statements
"""
read in the contents of the inputs yaml file
"""
try:
os.fork # pylint: disable=no-member
except NameError:
raise RuntimeError(
"scgrad.py depends on os.fork, which is not available on this system."
)
ARGS = sys.argv[1:]
if ARGS[0] == "scgrad.py":
ARGS.pop(0)
WorkerDaemon = TestDaemon if test else GradientDaemon
# --------------------------------------------------
# Daemon controllers
# --------------------------------------------------
if ARGS[0] == "start":
print("starting daemon")
daemon = WorkerDaemon(DAEMON_PID, DAEMON_FIFO)
daemon.start()
return "0"
if ARGS[0] == "status":
if not os.path.exists(DAEMON_PID):
print("Daemon not running")
return '0'
with open(DAEMON_PID,'w') as fh:
_pid = fh.read()
pids = [pid for pid in os.listdir('/proc') if pid.isdigit()]
if _pid in pids:
print("daemon process (pid {}) is running".format(_pid))
else:
print("daemon process (pid {}) NOT is running".format(_pid))
return '0'
if ARGS[0] == "stop":
print("stopping daemon")
daemon = WorkerDaemon(DAEMON_PID, DAEMON_FIFO)
daemon.stop()
return "0"
if ARGS[0] == "restart":
print("restaring daemon")
daemon = WorkerDaemon(DAEMON_PID, DAEMON_FIFO)
daemon.restart()
return "0"
# --------------------------------------------------
# Gradient job
# --------------------------------------------------
try:
with open(DAEMON_PID, "r") as pf:
pid = int(pf.read().strip())
except IOError:
pid = None
if not pid:
raise RuntimeError("please start the daemon")
assert (
len(ARGS) == 4
), "ssc.py expects 4 parameters, including a commonfile, partfile, outfile and the component index"
try:
int(ARGS[3])
except ValueError:
raise ValueError("The args[3] must be an integer")
# CREATE THE RESPONSE FIFO
RETURN_FIFO = os.path.join("/tmp/sc-" + str(uuid.uuid4()) + ".fifo")
os.mkfifo(RETURN_FIFO) # pylint: disable=no-member
def cleanup():
os.remove(RETURN_FIFO)
atexit.register(cleanup)
# SEND THE ARGS TO THE DAEMON
with open(DAEMON_FIFO, "w") as d_send:
d_send.write(json.dumps(ARGS + [RETURN_FIFO]))
# LISTEN FOR THE RESPONSE
with open(RETURN_FIFO, "r") as d_return:
response = d_return.read()
print("daemon sent response: {}".format(response))
return response
if __name__ == "__main__":
print("hi from scgrad", sys.argv)
condition_flag = main(test=False)
if condition_flag == "0":
print("Test Daemon worked!")
else:
print("Something went wrong: {}".format(condition_flag))
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explainaboard/loaders/__init__.py | hwidjaja/ExplainaBoard | 0 | 137344 | <reponame>hwidjaja/ExplainaBoard
from explainaboard.loaders import (
aspect_based_sentiment_classification,
conditional_generation,
extractive_qa,
file_loader,
kg_link_tail_prediction,
language_modeling,
loader,
loader_registry,
named_entity_recognition,
qa_multiple_choice,
text_classification,
text_pair_classification,
word_segmentation,
)
get_datalab_loader = loader_registry.get_datalab_loader
get_custom_dataset_loader = loader_registry.get_custom_dataset_loader
DatalabLoaderOption = file_loader.DatalabLoaderOption
__all__ = [
'aspect_based_sentiment_classification',
'conditional_generation',
'extractive_qa',
'kg_link_tail_prediction',
'language_modeling',
'loader',
'named_entity_recognition',
'qa_multiple_choice',
'text_classification',
'text_pair_classification',
'word_segmentation',
]
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apps/contrib/api/responses.py | jimialex/django-wise-template-mysql | 2 | 126699 | <reponame>jimialex/django-wise-template-mysql
# -*- coding: utf-8 -*-
from rest_framework import status as status_code
from rest_framework.response import Response
from django.utils.translation import ugettext_lazy as _
class DoneResponse(Response): # noqa: D107
"""Base class for REST Exceptions based on CEH from @vicobits."""
def __init__(self, detail=None, code=None, status=None): # noqa: D107
response = {
'message': detail if detail else _('Successful operation!'),
'code': code if code else 'successful_action',
}
status = status or status_code.HTTP_200_OK
super().__init__(data=response, status=status)
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config.py | julienc91/slasher | 0 | 117510 | <filename>config.py
# -*- coding: utf-8 -*-
# --- Slack configuration ---
# get your own at https://api.slack.com/docs/oauth-test-tokens
SLACK_TOKEN = "<PASSWORD>"
# the channel Slasher will send its messages to
SLACK_CHANNEL = "#random"
# Slasher's username
SLACK_USERNAME = "Slasher"
# Slasher's icon
SLACK_USER_EMOJI = ":robot_face:"
# --- Giphy configuration ---
GIPHY_TAGS = ["fireworks", "guitar"]
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atlasclient/client.py | LALAYANG/atlasclient | 21 | 82743 | # 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 copy
import functools
import io
import json
import logging
import tarfile
import requests
from atlasclient import models, utils, base, exceptions
from atlasclient.exceptions import handle_response
LOG = logging.getLogger(__name__)
LOG.addHandler(utils.NullHandler())
# this defines where the Atlas client delegates to for actual logic
ENTRY_POINTS = {'entity_guid': models.EntityGuid,
'typedefs': models.TypeDef,
'entity_post': models.EntityPost,
'entity_bulk': models.EntityBulk,
'entity_bulk_classification': models.EntityBulkClassification,
'entity_unique_attribute': models.EntityUniqueAttribute,
'typedefs_headers': models.TypeDefHeader,
'classificationdef_guid': models.ClassificationDefGuid,
'classificationdef_name': models.ClassificationDefName,
'entitydef_guid': models.EntityDefGuid,
'entitydef_name': models.EntityDefName,
'enumdef_guid': models.EnumDefGuid,
'enumdef_name': models.EnumDefName,
'relationshipdef_guid': models.RelationshipDefGuid,
'relationshipdef_name': models.RelationshipDefName,
'structdef_guid': models.StructDefGuid,
'structdef_name': models.StructDefName,
'typedef_guid': models.TypeDefGuid,
'typedef_name': models.TypeDefName,
'lineage_guid': models.LineageGuid,
'search_attribute': models.SearchAttribute,
'search_basic': models.SearchBasic,
'search_dsl': models.SearchDsl,
'search_fulltext': models.SearchFulltext,
'relationship': models.Relationship,
'relationship_guid': models.RelationshipGuid,
'search_saved': models.SearchSaved,
'admin_metrics': models.AdminMetrics
}
class Atlas(object):
"""The Atlas client
This is the entry point to the Atlas API. Create this client and then
use one of the entry points to start hitting Atlas object collections.
"""
def __init__(self, host, port=None, username=None, password=<PASSWORD>,
identifier=None, protocol=None, validate_ssl=True,
timeout=10, max_retries=5, auth=None):
self.base_url = utils.generate_base_url(host, port=port, protocol=protocol)
if identifier is None:
identifier = 'python-atlasclient'
self.client = HttpClient(host=self.base_url, username=username,
password=password, identifier=identifier,
validate_ssl=validate_ssl, timeout=timeout,
max_retries=max_retries, auth=auth)
self._version = None
def __dir__(self):
d1 = {}
d1.update(self.__dict__)
d1.update(ENTRY_POINTS)
return d1.keys()
def check_version(self):
if self.version < base.OLDEST_SUPPORTED_VERSION:
raise exceptions.ClientError(
"Version %s unsupported, must be %s or higher"
% (utils.version_str(self.version),
utils.version_str(base.OLDEST_SUPPORTED_VERSION)))
return
def __getattr__(self, attr):
if attr in ENTRY_POINTS:
rel_class = ENTRY_POINTS[attr]
return rel_class.collection_class(self, rel_class)
if getattr(requests, attr):
# forward get/post/put/head/delete to the http client
return getattr(self.client, attr)
raise AttributeError(attr)
class HttpClient(object):
"""Our HTTP based REST client.
It handles some of the dirty work like automatic serialization/deserialization
of JSON data, converting error responses to exceptions, etc. For the most
part it should mimic a requests client. You can call methods like get, post,
put, delete, and head and expect them to work the same way. But instead of
a response object, you get a dictionary. A response of None means no response
was supplied by the API. This should be uncommon except for error cases, but
cases do exist either due to Atlas bugs or other mitigating circumstances.
"""
def __init__(self, host, username, password, identifier, validate_ssl=True,
timeout=10, max_retries=5, auth=None):
basic_token = utils.generate_http_basic_token(username=username, password=password)
self.request_params = {
'headers': {'X-Requested-By': identifier,
'Authorization': 'Basic {}'.format(basic_token)},
#'auth': (username, password),
'verify': validate_ssl,
'timeout': timeout,
}
# automatically retry requests on connection errors
self.session = requests.Session()
self.session.auth = auth
adapter = requests.adapters.HTTPAdapter(max_retries=max_retries)
self.session.mount(host, adapter)
def request(self, method, url, content_type=None, **kwargs):
# doing it this way keeps the magic for following redirects intact
requests_method = getattr(self.session, method)
params = copy.deepcopy(self.request_params)
params.update(kwargs)
if content_type is not None:
params['headers']['Content-type'] = content_type
else:
params['headers']['Content-type'] = 'application/json'
LOG.debug("Request headers: %s", params['headers'])
if 'data' in params and isinstance(params['data'], dict):
params['data'] = json.dumps(params['data'], cls=AtlasJsonEncoder)
LOG.debug("Request body: %s", params['data'])
elif 'data' in params and isinstance(params['data'], str):
params['data'] = json.dumps(params['data'])
elif 'data' in params and isinstance(params['data'], list):
params['data'] = json.dumps(params['data'])
response = requests_method(url, **params)
# any error responses will generate exceptions here
handle_response(response)
LOG.debug("Response headers: %s", response.headers)
LOG.debug("Response: %s", response.text)
if response.headers.get('content-length') is None:
# Log bad methods so we can report them
LOG.debug("Missing content-length for %s %s: %s", method,
url, response.headers.get('content-type'))
# there is no consistent way to determine response type
# so assume json if it's not an empty string
if response.text:
if response.headers.get('content-type') == 'application/x-ustar':
tarstream = io.BytesIO(response.content)
tarstream.seek(0)
return tarfile.open(fileobj=tarstream)
elif 'application/json' not in response.headers.get('content-type'):
# Log bad methods so we can report them
LOG.debug("Wrong response content-type for %s %s: %s", method,
url, response.headers.get('content-type'))
return response.json()
return {}
def __getattr__(self, attr):
if getattr(requests, attr):
return functools.partial(self.request, attr)
raise AttributeError(attr)
class AtlasJsonEncoder(json.JSONEncoder):
"""Converts Atlas model objects into dictionaries that can be JSON-encoded
This allows for passing in models and ModelCollections into related objects'
create/update methods and having it handle the conversion automatically.
"""
def default(self, obj): # pylint: disable=method-hidden
if isinstance(obj, base.ModelCollection):
dicts = []
for model in obj:
dicts.append(model.to_json_dict())
return dicts
elif isinstance(obj, base.Model):
return obj.to_json_dict()
# Let the base class default method raise the TypeError
return super(AtlasJsonEncoder, self).default(obj)
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games/HangMan/hangman.py | sudhanvalalit/python | 0 | 1604145 | <reponame>sudhanvalalit/python
import random
from words import words
import string
from hangman_visual import lives_visual_dict
def get_valid_word(words):
word = random.choice(words)
while '-' in word or ' ' in word:
word = random.choice(words)
return word.upper()
def hangman():
word = get_valid_word(words)
word_letters = set(word)
alphabet = set(string.ascii_uppercase)
used_letters = set()
lives = 6
# get user input
while len(word_letters) > 0 and lives > 0:
# print used letters
print(f'You have {lives} lives left and you have used these letters: ', ' '.join(
used_letters))
# what current word is
word_list = [
letter if letter in used_letters else '-' for letter in word]
print('Current word: ', ' '.join(word_list))
user_letter = input('Guess a letter: ').upper()
if user_letter in alphabet - used_letters:
used_letters.add(user_letter)
if user_letter in word_letters:
word_letters.remove(user_letter)
else:
lives -= 1 # takes away a life
print("Letter is not in the word.")
print(lives_visual_dict.get(lives))
elif user_letter in used_letters:
print('You have already used that character. Please try again.')
else:
print('Invalid character. Please try again.')
# gets here when word letters array is empty
if lives == 0:
print(f"You died. The word was {word}")
else:
print(f'You guessed the word {word} !!')
if __name__ == '__main__':
validation = True
while validation:
hangman()
response = input("Do you want to play again? (yes/no) ").upper()
if response == "NO":
validation = False
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cbcPaddingAttack.py | danielverd/crypto-projects | 0 | 42969 | from modesOfOperation import CBCCipher
import sys
BLOCK_SIZE = 16
def blocks(l, n):
for i in range(0, len(l), n):
yield l[i:i + n]
def attack(cbc,ciphertext):
message = bytearray(b'')
blockGen = blocks(ciphertext,BLOCK_SIZE)
ctextBlocks = []
for i in blockGen:
ctextBlocks.append(i)
padBlock = ctextBlocks[len(ctextBlocks)-2]
for i in range(BLOCK_SIZE):
padBlock[i] = 72
if cbc.decrypt(bytearray(b''.join(ctextBlocks))) is False:
padlength = BLOCK_SIZE - i
break
ctextBlocks = []
blockGen = blocks(ciphertext,BLOCK_SIZE)
for i in blockGen:
ctextBlocks.append(i)
probeBlocks = ctextBlocks.copy()
delta1 = bytearray(BLOCK_SIZE)
for j in range(padlength):
delta1[BLOCK_SIZE - (1 + j)] = padlength
for i in reversed(range(BLOCK_SIZE - padlength)):
delta2 = bytearray(BLOCK_SIZE)
for j in range(BLOCK_SIZE - i):
delta2[BLOCK_SIZE - (1 + j)] = (BLOCK_SIZE - i)
for j in range(256):
cipherInter = probeBlocks.copy()
delta2[i] = j
delta = bytearray(bytes([a ^ b for (a,b) in zip(delta1, delta2)]))
block = cipherInter[len(cipherInter) - 2]
probe = bytearray(bytes([a ^ b for (a,b) in zip(block, delta)]))
cipherInter[len(cipherInter) - 2] = probe
if cbc.decrypt(bytearray(b''.join(cipherInter))) is not False:
sol1 = (BLOCK_SIZE - i)
sol2 = j
sol = sol1 ^ sol2
delta1[i] = sol
message = sol.to_bytes(1,'little') + message
break
probeBlocks = ctextBlocks.copy()
while len(probeBlocks)>2:
probeBlocks = probeBlocks.copy()[:-1]
delta1 = bytearray(BLOCK_SIZE)
for i in reversed(range(BLOCK_SIZE)):
delta2 = bytearray(BLOCK_SIZE)
for j in range(BLOCK_SIZE - (i+1)):
delta2[BLOCK_SIZE - (1 + j)] = (BLOCK_SIZE - i)
for j in range(256):
cipherInter = probeBlocks.copy()
delta2[i] = j
delta = bytearray(bytes([a ^ b for (a,b) in zip(delta1, delta2)]))
block = cipherInter[len(cipherInter)-2]
probe = bytearray(bytes([a ^ b for (a,b) in zip(block, delta)]))
cipherInter[len(cipherInter)-2] = probe
if cbc.decrypt(bytearray(b''.join(cipherInter))) is not False:
sol1 = BLOCK_SIZE - i
sol2 = j
sol = sol1 ^ sol2
delta1[i] = sol
message = sol.to_bytes(1,'little') + message
return message
if __name__ == "__main__":
key = <KEY>'
text = bytearray('go canes','utf-8')
cbc = CBCCipher(key)
ciphertext = cbc.encrypt(text)
#print(ciphertext)
broken = attack(cbc,ciphertext)
#print(broken)
print('-----Equality between text and broken message-----')
print(broken == text)
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topgun/__init__.py | muntumdwara/TopGun | 0 | 60258 | <reponame>muntumdwara/TopGun<gh_stars>0
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
TopGun
@author: Viper
"""
# Useful Medium post on Python importing within __init__.py
# https://towardsdatascience.com/whats-init-for-me-d70a312da583
### DON'T FORGET TO UPDATE SUB __INIT__.py files ###
# General
from .utilities import *
from .reporting import Reporting
# Models
from .models import *
# Charting
from .charting import *
# Optimisation
from .optimiser import * | [
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exercises/alphametics/alphametics.py | kishankj/python | 1,177 | 104772 | def solve(puzzle):
pass
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Ene-Jun-2019/Luis Ornelas/Segundo Parcial/Ejercicio 3/Ejercicio3-Parcial2-DB.py | Arbupa/DAS_Sistemas | 41 | 164623 | import sqlite3
conexion = sqlite3.connect('RandUser.db')
cursor = conexion.cursor()
cursor.execute('''
CREATE TABLE Users(
Gender TEXT NOT NULL,
First TEXT NOT NULL,
Last TEXT NOT NULL,
Location TEXT NOT NULL,
Email TEXT NOT NULL)
''')
conexion.close()
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authnz/tests.py | NERSC/newt-2.0 | 11 | 142683 | from django.test import TestCase
from django.conf import settings
import json
from newt.tests import MyTestClient, newt_base_url, login
class AuthTests(TestCase):
fixtures = ["test_fixture.json"]
def setUp(self):
self.client = MyTestClient()
def test_login(self):
# Should not be logged in
r = self.client.get(newt_base_url + "/auth")
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], False)
# Should be logged in
r = self.client.post(newt_base_url + "/auth", data=login)
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], True)
self.assertEquals(json_response['output']['username'], login['username'])
# Loggen in self.client should return user info
r = self.client.get(newt_base_url + "/auth")
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], True)
self.assertEquals(json_response['output']['username'], login['username'])
def test_logout(self):
# Should be logged in
r = self.client.post(newt_base_url + "/auth", data=login)
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], True)
self.assertEquals(json_response['output']['username'], login['username'])
r = self.client.delete(newt_base_url + "/auth")
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], False)
r = self.client.get(newt_base_url + "/auth")
self.assertEquals(r.status_code, 200)
json_response = r.json()
self.assertEquals(json_response['output']['auth'], False)
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data/vctk.py | Jackson-Kang/VQVC-Pytorch | 13 | 79939 | from utils.path import *
from utils.audio.tools import get_mel
from tqdm import tqdm
import numpy as np
import glob, os, sys
from multiprocessing import Pool
from scipy.io.wavfile import write
import librosa, ffmpeg
from sklearn.preprocessing import StandardScaler
def job(wav_filename):
original_wav_filename, prepro_wav_dir, sampling_rate = wav_filename
filename = original_wav_filename.split("/")[-1]
new_wav_filename = get_path(prepro_wav_dir, filename)
if not os.path.exists(new_wav_filename):
try:
out, err = (ffmpeg
.input(original_wav_filename)
.output(new_wav_filename, acodec='pcm_s16le', ac=1, ar=sampling_rate)
.overwrite_output()
.run(capture_stdout=True, capture_stderr=True))
except ffmpeg.Error as err:
print(err.stderr, file=sys.stderr)
raise
def preprocess(data_path, prepro_wav_dir, prepro_path, mel_path, sampling_rate, n_workers=10, filter_length=1024, hop_length=256, trim_silence=True, top_db=60):
p = Pool(n_workers)
mel_scaler = StandardScaler(copy=False)
prepro_wav_dir = create_dir(prepro_wav_dir)
wav_paths=[[filename, prepro_wav_dir, sampling_rate] for filename in list(glob.glob(get_path(data_path, "wav48", "**", "*.wav")))]
print("\t[LOG] converting wav format...")
with tqdm(total=len(wav_paths)) as pbar:
for _ in tqdm(p.imap_unordered(job, wav_paths)):
pbar.update()
print("\t[LOG] saving mel-spectrogram...")
with tqdm(total=len(wav_paths)) as pbar:
for wav_filename in tqdm(glob.glob(get_path(prepro_wav_dir, "*.wav"))):
mel_filename = wav_filename.split("/")[-1].replace("wav", "npy")
mel_savepath = get_path(mel_path, mel_filename)
mel_spectrogram, _ = get_mel(wav_filename, trim_silence=trim_silence, frame_length=filter_length, hop_length=hop_length, top_db=top_db)
mel_scaler.partial_fit(mel_spectrogram)
np.save(mel_savepath, mel_spectrogram)
np.save(get_path(prepro_path, "mel_stats.npy"), np.array([mel_scaler.mean_, mel_scaler.scale_]))
print("Done!")
def split_unseen_speakers(prepro_mel_dir):
print("[LOG] 6 UNSEEN speakers: \n\t p226(Male, English, Surrey) \n\t p256(Male, English, Birmingham) \
\n\t p266(Female, Irish, Athlone) \n\t p297(Female, American, Newyork) \
\n\t p323 (Female, SouthAfrican, Pretoria)\n\t p376(Male, Indian)")
unseen_speaker_list = ["p226", "p256", "p266", "p297", "p323", "p376"]
seen_speaker_files, unseen_speaker_files = [], []
preprocessed_file_list = glob.glob(get_path(prepro_mel_dir, "*.npy"))
for preprocessed_mel_file in preprocessed_file_list:
speaker = preprocessed_mel_file.split("/")[-1].split("_")[0]
if speaker in unseen_speaker_list:
unseen_speaker_files.append(preprocessed_mel_file)
else:
seen_speaker_files.append(preprocessed_mel_file)
return seen_speaker_files, unseen_speaker_files
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] |
yt_dlp/extractor/archiveorg.py | mrBliss/yt-dlp | 80 | 11346 | <filename>yt_dlp/extractor/archiveorg.py
# coding: utf-8
from __future__ import unicode_literals
import re
import json
from .common import InfoExtractor
from .youtube import YoutubeIE, YoutubeBaseInfoExtractor
from ..compat import (
compat_urllib_parse_unquote,
compat_urllib_parse_unquote_plus,
compat_HTTPError
)
from ..utils import (
bug_reports_message,
clean_html,
dict_get,
extract_attributes,
ExtractorError,
get_element_by_id,
HEADRequest,
int_or_none,
KNOWN_EXTENSIONS,
merge_dicts,
mimetype2ext,
orderedSet,
parse_duration,
parse_qs,
str_to_int,
str_or_none,
traverse_obj,
try_get,
unified_strdate,
unified_timestamp,
urlhandle_detect_ext,
url_or_none
)
class ArchiveOrgIE(InfoExtractor):
IE_NAME = 'archive.org'
IE_DESC = 'archive.org video and audio'
_VALID_URL = r'https?://(?:www\.)?archive\.org/(?:details|embed)/(?P<id>[^?#]+)(?:[?].*)?$'
_TESTS = [{
'url': 'http://archive.org/details/XD300-23_68HighlightsAResearchCntAugHumanIntellect',
'md5': '8af1d4cf447933ed3c7f4871162602db',
'info_dict': {
'id': 'XD300-23_68HighlightsAResearchCntAugHumanIntellect',
'ext': 'ogv',
'title': '1968 Demo - FJCC Conference Presentation Reel #1',
'description': 'md5:da45c349df039f1cc8075268eb1b5c25',
'release_date': '19681210',
'timestamp': 1268695290,
'upload_date': '20100315',
'creator': 'SRI International',
'uploader': '<EMAIL>',
},
}, {
'url': 'https://archive.org/details/Cops1922',
'md5': '0869000b4ce265e8ca62738b336b268a',
'info_dict': {
'id': 'Cops1922',
'ext': 'mp4',
'title': 'Buster Keaton\'s "Cops" (1922)',
'description': 'md5:43a603fd6c5b4b90d12a96b921212b9c',
'uploader': '<EMAIL>',
'timestamp': 1387699629,
'upload_date': "20131222",
},
}, {
'url': 'http://archive.org/embed/XD300-23_68HighlightsAResearchCntAugHumanIntellect',
'only_matching': True,
}, {
'url': 'https://archive.org/details/Election_Ads',
'md5': '284180e857160cf866358700bab668a3',
'info_dict': {
'id': 'Election_Ads/Commercial-JFK1960ElectionAdCampaignJingle.mpg',
'title': 'Commercial-JFK1960ElectionAdCampaignJingle.mpg',
'ext': 'mp4',
},
}, {
'url': 'https://archive.org/details/Election_Ads/Commercial-Nixon1960ElectionAdToughonDefense.mpg',
'md5': '7915213ef02559b5501fe630e1a53f59',
'info_dict': {
'id': 'Election_Ads/Commercial-Nixon1960ElectionAdToughonDefense.mpg',
'title': 'Commercial-Nixon1960ElectionAdToughonDefense.mpg',
'ext': 'mp4',
'timestamp': 1205588045,
'uploader': '<EMAIL>',
'description': '1960 Presidential Campaign Election Commercials <NAME>, <NAME>',
'upload_date': '20080315',
},
}, {
'url': 'https://archive.org/details/gd1977-05-08.shure57.stevenson.29303.flac16',
'md5': '7d07ffb42aba6537c28e053efa4b54c9',
'info_dict': {
'id': 'gd1977-05-08.shure57.stevenson.29303.flac16/gd1977-05-08d01t01.flac',
'title': 'Turning',
'ext': 'flac',
},
}, {
'url': 'https://archive.org/details/gd1977-05-08.shure57.stevenson.29303.flac16/gd1977-05-08d01t07.flac',
'md5': 'a07cd8c6ab4ee1560f8a0021717130f3',
'info_dict': {
'id': 'gd1977-05-08.shure57.stevenson.29303.flac16/gd1977-05-08d01t07.flac',
'title': 'Deal',
'ext': 'flac',
'timestamp': 1205895624,
'uploader': '<EMAIL>',
'description': 'md5:6a31f1996db0aa0fc9da6d6e708a1bb0',
'upload_date': '20080319',
'location': 'Barton Hall - Cornell University',
},
}, {
'url': 'https://archive.org/details/lp_the-music-of-russia_various-artists-a-askaryan-alexander-melik',
'md5': '7cb019baa9b332e82ea7c10403acd180',
'info_dict': {
'id': 'lp_the-music-of-russia_various-artists-a-askaryan-alexander-melik/disc1/01.01. Bells Of Rostov.mp3',
'title': 'Bells Of Rostov',
'ext': 'mp3',
},
}, {
'url': 'https://archive.org/details/lp_the-music-of-russia_various-artists-a-askaryan-alexander-melik/disc1/02.02.+Song+And+Chorus+In+The+Polovetsian+Camp+From+%22Prince+Igor%22+(Act+2%2C+Scene+1).mp3',
'md5': '1d0aabe03edca83ca58d9ed3b493a3c3',
'info_dict': {
'id': 'lp_the-music-of-russia_various-artists-a-askaryan-alexander-melik/disc1/02.02. Song And Chorus In The Polovetsian Camp From "Prince Igor" (Act 2, Scene 1).mp3',
'title': 'Song And Chorus In The Polovetsian Camp From "Prince Igor" (Act 2, Scene 1)',
'ext': 'mp3',
'timestamp': 1569662587,
'uploader': '<EMAIL>',
'description': 'md5:012b2d668ae753be36896f343d12a236',
'upload_date': '20190928',
},
}]
@staticmethod
def _playlist_data(webpage):
element = re.findall(r'''(?xs)
<input
(?:\s+[a-zA-Z0-9:._-]+(?:=[a-zA-Z0-9:._-]*|="[^"]*"|='[^']*'|))*?
\s+class=['"]?js-play8-playlist['"]?
(?:\s+[a-zA-Z0-9:._-]+(?:=[a-zA-Z0-9:._-]*|="[^"]*"|='[^']*'|))*?
\s*/>
''', webpage)[0]
return json.loads(extract_attributes(element)['value'])
def _real_extract(self, url):
video_id = compat_urllib_parse_unquote_plus(self._match_id(url))
identifier, entry_id = (video_id.split('/', 1) + [None])[:2]
# Archive.org metadata API doesn't clearly demarcate playlist entries
# or subtitle tracks, so we get them from the embeddable player.
embed_page = self._download_webpage(
'https://archive.org/embed/' + identifier, identifier)
playlist = self._playlist_data(embed_page)
entries = {}
for p in playlist:
# If the user specified a playlist entry in the URL, ignore the
# rest of the playlist.
if entry_id and p['orig'] != entry_id:
continue
entries[p['orig']] = {
'formats': [],
'thumbnails': [],
'artist': p.get('artist'),
'track': p.get('title'),
'subtitles': {}}
for track in p.get('tracks', []):
if track['kind'] != 'subtitles':
continue
entries[p['orig']][track['label']] = {
'url': 'https://archive.org/' + track['file'].lstrip('/')}
metadata = self._download_json(
'http://archive.org/metadata/' + identifier, identifier)
m = metadata['metadata']
identifier = m['identifier']
info = {
'id': identifier,
'title': m['title'],
'description': clean_html(m.get('description')),
'uploader': dict_get(m, ['uploader', 'adder']),
'creator': m.get('creator'),
'license': m.get('licenseurl'),
'release_date': unified_strdate(m.get('date')),
'timestamp': unified_timestamp(dict_get(m, ['publicdate', 'addeddate'])),
'webpage_url': 'https://archive.org/details/' + identifier,
'location': m.get('venue'),
'release_year': int_or_none(m.get('year'))}
for f in metadata['files']:
if f['name'] in entries:
entries[f['name']] = merge_dicts(entries[f['name']], {
'id': identifier + '/' + f['name'],
'title': f.get('title') or f['name'],
'display_id': f['name'],
'description': clean_html(f.get('description')),
'creator': f.get('creator'),
'duration': parse_duration(f.get('length')),
'track_number': int_or_none(f.get('track')),
'album': f.get('album'),
'discnumber': int_or_none(f.get('disc')),
'release_year': int_or_none(f.get('year'))})
entry = entries[f['name']]
elif f.get('original') in entries:
entry = entries[f['original']]
else:
continue
if f.get('format') == 'Thumbnail':
entry['thumbnails'].append({
'id': f['name'],
'url': 'https://archive.org/download/' + identifier + '/' + f['name'],
'width': int_or_none(f.get('width')),
'height': int_or_none(f.get('width')),
'filesize': int_or_none(f.get('size'))})
extension = (f['name'].rsplit('.', 1) + [None])[1]
if extension in KNOWN_EXTENSIONS:
entry['formats'].append({
'url': 'https://archive.org/download/' + identifier + '/' + f['name'],
'format': f.get('format'),
'width': int_or_none(f.get('width')),
'height': int_or_none(f.get('height')),
'filesize': int_or_none(f.get('size')),
'protocol': 'https'})
# Sort available formats by filesize
for entry in entries.values():
entry['formats'] = list(sorted(entry['formats'], key=lambda x: x.get('filesize', -1)))
if len(entries) == 1:
# If there's only one item, use it as the main info dict
only_video = entries[list(entries.keys())[0]]
if entry_id:
info = merge_dicts(only_video, info)
else:
info = merge_dicts(info, only_video)
else:
# Otherwise, we have a playlist.
info['_type'] = 'playlist'
info['entries'] = list(entries.values())
if metadata.get('reviews'):
info['comments'] = []
for review in metadata['reviews']:
info['comments'].append({
'id': review.get('review_id'),
'author': review.get('reviewer'),
'text': str_or_none(review.get('reviewtitle'), '') + '\n\n' + review.get('reviewbody'),
'timestamp': unified_timestamp(review.get('createdate')),
'parent': 'root'})
return info
class YoutubeWebArchiveIE(InfoExtractor):
IE_NAME = 'web.archive:youtube'
IE_DESC = 'web.archive.org saved youtube videos'
_VALID_URL = r"""(?x)^
(?:https?://)?web\.archive\.org/
(?:web/)?
(?:(?P<date>[0-9]{14})?[0-9A-Za-z_*]*/)? # /web and the version index is optional
(?:https?(?::|%3[Aa])//)?
(?:
(?:\w+\.)?youtube\.com(?::(?:80|443))?/watch(?:\.php)?(?:\?|%3[fF])(?:[^\#]+(?:&|%26))?v(?:=|%3[dD]) # Youtube URL
|(?:wayback-fakeurl\.archive\.org/yt/) # Or the internal fake url
)
(?P<id>[0-9A-Za-z_-]{11})(?:%26|\#|&|$)
"""
_TESTS = [
{
'url': 'https://web.archive.org/web/20150415002341/https://www.youtube.com/watch?v=aYAGB11YrSs',
'info_dict': {
'id': 'aYAGB11YrSs',
'ext': 'webm',
'title': 'Team Fortress 2 - Sandviches!',
'description': 'md5:4984c0f9a07f349fc5d8e82ab7af4eaf',
'upload_date': '20110926',
'uploader': 'Zeurel',
'channel_id': 'UCukCyHaD-bK3in_pKpfH9Eg',
'duration': 32,
'uploader_id': 'Zeurel',
'uploader_url': 'http://www.youtube.com/user/Zeurel'
}
}, {
# Internal link
'url': 'https://web.archive.org/web/2oe/http://wayback-fakeurl.archive.org/yt/97t7Xj_iBv0',
'info_dict': {
'id': '97t7Xj_iBv0',
'ext': 'mp4',
'title': 'Why Machines That Bend Are Better',
'description': 'md5:00404df2c632d16a674ff8df1ecfbb6c',
'upload_date': '20190312',
'uploader': 'Veritasium',
'channel_id': 'UCHnyfMqiRRG1u-2MsSQLbXA',
'duration': 771,
'uploader_id': '1veritasium',
'uploader_url': 'http://www.youtube.com/user/1veritasium'
}
}, {
# Video from 2012, webm format itag 45. Newest capture is deleted video, with an invalid description.
# Should use the date in the link. Title ends with '- Youtube'. Capture has description in eow-description
'url': 'https://web.archive.org/web/20120712231619/http://www.youtube.com/watch?v=AkhihxRKcrs&gl=US&hl=en',
'info_dict': {
'id': 'AkhihxRKcrs',
'ext': 'webm',
'title': 'Limited Run: Mondo\'s Modern Classic 1 of 3 (SDCC 2012)',
'upload_date': '20120712',
'duration': 398,
'description': 'md5:ff4de6a7980cb65d951c2f6966a4f2f3',
'uploader_id': 'machinima',
'uploader_url': 'http://www.youtube.com/user/machinima'
}
}, {
# FLV video. Video file URL does not provide itag information
'url': 'https://web.archive.org/web/20081211103536/http://www.youtube.com/watch?v=jNQXAC9IVRw',
'info_dict': {
'id': 'jNQXAC9IVRw',
'ext': 'flv',
'title': 'Me at the zoo',
'upload_date': '20050423',
'channel_id': 'UC4QobU6STFB0P71PMvOGN5A',
'duration': 19,
'description': 'md5:10436b12e07ac43ff8df65287a56efb4',
'uploader_id': 'jawed',
'uploader_url': 'http://www.youtube.com/user/jawed'
}
}, {
'url': 'https://web.archive.org/web/20110712231407/http://www.youtube.com/watch?v=lTx3G6h2xyA',
'info_dict': {
'id': 'lTx3G6h2xyA',
'ext': 'flv',
'title': 'Madeon - Pop Culture (live mashup)',
'upload_date': '20110711',
'uploader': 'Madeon',
'channel_id': 'UCqMDNf3Pn5L7pcNkuSEeO3w',
'duration': 204,
'description': 'md5:f7535343b6eda34a314eff8b85444680',
'uploader_id': 'itsmadeon',
'uploader_url': 'http://www.youtube.com/user/itsmadeon'
}
}, {
# First capture is of dead video, second is the oldest from CDX response.
'url': 'https://web.archive.org/https://www.youtube.com/watch?v=1JYutPM8O6E',
'info_dict': {
'id': '1JYutPM8O6E',
'ext': 'mp4',
'title': 'Fake Teen Doctor Strikes AGAIN! - Weekly Weird News',
'upload_date': '20160218',
'channel_id': 'UCdIaNUarhzLSXGoItz7BHVA',
'duration': 1236,
'description': 'md5:21032bae736421e89c2edf36d1936947',
'uploader_id': 'MachinimaETC',
'uploader_url': 'http://www.youtube.com/user/MachinimaETC'
}
}, {
# First capture of dead video, capture date in link links to dead capture.
'url': 'https://web.archive.org/web/20180803221945/https://www.youtube.com/watch?v=6FPhZJGvf4E',
'info_dict': {
'id': '6FPhZJGvf4E',
'ext': 'mp4',
'title': 'WTF: Video Games Still Launch BROKEN?! - T.U.G.S.',
'upload_date': '20160219',
'channel_id': 'UCdIaNUarhzLSXGoItz7BHVA',
'duration': 798,
'description': 'md5:a1dbf12d9a3bd7cb4c5e33b27d77ffe7',
'uploader_id': 'MachinimaETC',
'uploader_url': 'http://www.youtube.com/user/MachinimaETC'
},
'expected_warnings': [
r'unable to download capture webpage \(it may not be archived\)'
]
}, { # Very old YouTube page, has - YouTube in title.
'url': 'http://web.archive.org/web/20070302011044/http://youtube.com/watch?v=-06-KB9XTzg',
'info_dict': {
'id': '-06-KB9XTzg',
'ext': 'flv',
'title': 'New Coin Hack!! 100% Safe!!'
}
}, {
'url': 'web.archive.org/https://www.youtube.com/watch?v=dWW7qP423y8',
'info_dict': {
'id': 'dWW7qP423y8',
'ext': 'mp4',
'title': 'It\'s Bootleg AirPods Time.',
'upload_date': '20211021',
'channel_id': 'UC7Jwj9fkrf1adN4fMmTkpug',
'channel_url': 'http://www.youtube.com/channel/UC7Jwj9fkrf1adN4fMmTkpug',
'duration': 810,
'description': 'md5:7b567f898d8237b256f36c1a07d6d7bc',
'uploader': 'DankPods',
'uploader_id': 'UC7Jwj9fkrf1adN4fMmTkpug',
'uploader_url': 'http://www.youtube.com/channel/UC7Jwj9fkrf1adN4fMmTkpug'
}
}, {
# player response contains '};' See: https://github.com/ytdl-org/youtube-dl/issues/27093
'url': 'https://web.archive.org/web/20200827003909if_/http://www.youtube.com/watch?v=6Dh-RL__uN4',
'info_dict': {
'id': '6Dh-RL__uN4',
'ext': 'mp4',
'title': 'bitch lasagna',
'upload_date': '20181005',
'channel_id': 'UC-lHJZR3Gqxm24_Vd_AJ5Yw',
'channel_url': 'http://www.youtube.com/channel/UC-lHJZR3Gqxm24_Vd_AJ5Yw',
'duration': 135,
'description': 'md5:2dbe4051feeff2dab5f41f82bb6d11d0',
'uploader': 'PewDiePie',
'uploader_id': 'PewDiePie',
'uploader_url': 'http://www.youtube.com/user/PewDiePie'
}
}, {
'url': 'https://web.archive.org/web/http://www.youtube.com/watch?v=kH-G_aIBlFw',
'only_matching': True
}, {
'url': 'https://web.archive.org/web/20050214000000_if/http://www.youtube.com/watch?v=0altSZ96U4M',
'only_matching': True
}, {
# Video not archived, only capture is unavailable video page
'url': 'https://web.archive.org/web/20210530071008/https://www.youtube.com/watch?v=lHJTf93HL1s&spfreload=10',
'only_matching': True
}, { # Encoded url
'url': 'https://web.archive.org/web/20120712231619/http%3A//www.youtube.com/watch%3Fgl%3DUS%26v%3DAkhihxRKcrs%26hl%3Den',
'only_matching': True
}, {
'url': 'https://web.archive.org/web/20120712231619/http%3A//www.youtube.com/watch%3Fv%3DAkhihxRKcrs%26gl%3DUS%26hl%3Den',
'only_matching': True
}, {
'url': 'https://web.archive.org/web/20060527081937/http://www.youtube.com:80/watch.php?v=ELTFsLT73fA&search=soccer',
'only_matching': True
}, {
'url': 'https://web.archive.org/http://www.youtube.com:80/watch?v=-05VVye-ffg',
'only_matching': True
}
]
_YT_INITIAL_DATA_RE = r'(?:(?:(?:window\s*\[\s*["\']ytInitialData["\']\s*\]|ytInitialData)\s*=\s*({.+?})\s*;)|%s)' % YoutubeBaseInfoExtractor._YT_INITIAL_DATA_RE
_YT_INITIAL_PLAYER_RESPONSE_RE = r'(?:(?:(?:window\s*\[\s*["\']ytInitialPlayerResponse["\']\s*\]|ytInitialPlayerResponse)\s*=[(\s]*({.+?})[)\s]*;)|%s)' % YoutubeBaseInfoExtractor._YT_INITIAL_PLAYER_RESPONSE_RE
_YT_INITIAL_BOUNDARY_RE = r'(?:(?:var\s+meta|</script|\n)|%s)' % YoutubeBaseInfoExtractor._YT_INITIAL_BOUNDARY_RE
_YT_DEFAULT_THUMB_SERVERS = ['i.ytimg.com'] # thumbnails most likely archived on these servers
_YT_ALL_THUMB_SERVERS = orderedSet(
_YT_DEFAULT_THUMB_SERVERS + ['img.youtube.com', *[f'{c}{n or ""}.ytimg.com' for c in ('i', 's') for n in (*range(0, 5), 9)]])
_WAYBACK_BASE_URL = 'https://web.archive.org/web/%sif_/'
_OLDEST_CAPTURE_DATE = 20050214000000
_NEWEST_CAPTURE_DATE = 20500101000000
def _call_cdx_api(self, item_id, url, filters: list = None, collapse: list = None, query: dict = None, note='Downloading CDX API JSON'):
# CDX docs: https://github.com/internetarchive/wayback/blob/master/wayback-cdx-server/README.md
query = {
'url': url,
'output': 'json',
'fl': 'original,mimetype,length,timestamp',
'limit': 500,
'filter': ['statuscode:200'] + (filters or []),
'collapse': collapse or [],
**(query or {})
}
res = self._download_json('https://web.archive.org/cdx/search/cdx', item_id, note, query=query)
if isinstance(res, list) and len(res) >= 2:
# format response to make it easier to use
return list(dict(zip(res[0], v)) for v in res[1:])
elif not isinstance(res, list) or len(res) != 0:
self.report_warning('Error while parsing CDX API response' + bug_reports_message())
def _extract_yt_initial_variable(self, webpage, regex, video_id, name):
return self._parse_json(self._search_regex(
(r'%s\s*%s' % (regex, self._YT_INITIAL_BOUNDARY_RE),
regex), webpage, name, default='{}'), video_id, fatal=False)
def _extract_webpage_title(self, webpage):
page_title = self._html_search_regex(
r'<title>([^<]*)</title>', webpage, 'title', default='')
# YouTube video pages appear to always have either 'YouTube -' as prefix or '- YouTube' as suffix.
return self._html_search_regex(
r'(?:YouTube\s*-\s*(.*)$)|(?:(.*)\s*-\s*YouTube$)',
page_title, 'title', default='')
def _extract_metadata(self, video_id, webpage):
search_meta = ((lambda x: self._html_search_meta(x, webpage, default=None)) if webpage else (lambda x: None))
player_response = self._extract_yt_initial_variable(
webpage, self._YT_INITIAL_PLAYER_RESPONSE_RE, video_id, 'initial player response') or {}
initial_data = self._extract_yt_initial_variable(
webpage, self._YT_INITIAL_DATA_RE, video_id, 'initial player response') or {}
initial_data_video = traverse_obj(
initial_data, ('contents', 'twoColumnWatchNextResults', 'results', 'results', 'contents', ..., 'videoPrimaryInfoRenderer'),
expected_type=dict, get_all=False, default={})
video_details = traverse_obj(
player_response, 'videoDetails', expected_type=dict, get_all=False, default={})
microformats = traverse_obj(
player_response, ('microformat', 'playerMicroformatRenderer'), expected_type=dict, get_all=False, default={})
video_title = (
video_details.get('title')
or YoutubeBaseInfoExtractor._get_text(microformats, 'title')
or YoutubeBaseInfoExtractor._get_text(initial_data_video, 'title')
or self._extract_webpage_title(webpage)
or search_meta(['og:title', 'twitter:title', 'title']))
channel_id = str_or_none(
video_details.get('channelId')
or microformats.get('externalChannelId')
or search_meta('channelId')
or self._search_regex(
r'data-channel-external-id=(["\'])(?P<id>(?:(?!\1).)+)\1', # @b45a9e6
webpage, 'channel id', default=None, group='id'))
channel_url = f'http://www.youtube.com/channel/{channel_id}' if channel_id else None
duration = int_or_none(
video_details.get('lengthSeconds')
or microformats.get('lengthSeconds')
or parse_duration(search_meta('duration')))
description = (
video_details.get('shortDescription')
or YoutubeBaseInfoExtractor._get_text(microformats, 'description')
or clean_html(get_element_by_id('eow-description', webpage)) # @9e6dd23
or search_meta(['description', 'og:description', 'twitter:description']))
uploader = video_details.get('author')
# Uploader ID and URL
uploader_mobj = re.search(
r'<link itemprop="url" href="(?P<uploader_url>https?://www\.youtube\.com/(?:user|channel)/(?P<uploader_id>[^"]+))">', # @fd05024
webpage)
if uploader_mobj is not None:
uploader_id, uploader_url = uploader_mobj.group('uploader_id'), uploader_mobj.group('uploader_url')
else:
# @a6211d2
uploader_url = url_or_none(microformats.get('ownerProfileUrl'))
uploader_id = self._search_regex(
r'(?:user|channel)/([^/]+)', uploader_url or '', 'uploader id', default=None)
upload_date = unified_strdate(
dict_get(microformats, ('uploadDate', 'publishDate'))
or search_meta(['uploadDate', 'datePublished'])
or self._search_regex(
[r'(?s)id="eow-date.*?>(.*?)</span>',
r'(?:id="watch-uploader-info".*?>.*?|["\']simpleText["\']\s*:\s*["\'])(?:Published|Uploaded|Streamed live|Started) on (.+?)[<"\']'], # @7998520
webpage, 'upload date', default=None))
return {
'title': video_title,
'description': description,
'upload_date': upload_date,
'uploader': uploader,
'channel_id': channel_id,
'channel_url': channel_url,
'duration': duration,
'uploader_url': uploader_url,
'uploader_id': uploader_id,
}
def _extract_thumbnails(self, video_id):
try_all = 'thumbnails' in self._configuration_arg('check_all')
thumbnail_base_urls = ['http://{server}/vi{webp}/{video_id}'.format(
webp='_webp' if ext == 'webp' else '', video_id=video_id, server=server)
for server in (self._YT_ALL_THUMB_SERVERS if try_all else self._YT_DEFAULT_THUMB_SERVERS) for ext in (('jpg', 'webp') if try_all else ('jpg',))]
thumbnails = []
for url in thumbnail_base_urls:
response = self._call_cdx_api(
video_id, url, filters=['mimetype:image/(?:webp|jpeg)'],
collapse=['urlkey'], query={'matchType': 'prefix'})
if not response:
continue
thumbnails.extend(
{
'url': (self._WAYBACK_BASE_URL % (int_or_none(thumbnail_dict.get('timestamp')) or self._OLDEST_CAPTURE_DATE)) + thumbnail_dict.get('original'),
'filesize': int_or_none(thumbnail_dict.get('length')),
'preference': int_or_none(thumbnail_dict.get('length'))
} for thumbnail_dict in response)
if not try_all:
break
self._remove_duplicate_formats(thumbnails)
return thumbnails
def _get_capture_dates(self, video_id, url_date):
capture_dates = []
# Note: CDX API will not find watch pages with extra params in the url.
response = self._call_cdx_api(
video_id, f'https://www.youtube.com/watch?v={video_id}',
filters=['mimetype:text/html'], collapse=['timestamp:6', 'digest'], query={'matchType': 'prefix'}) or []
all_captures = sorted([int_or_none(r['timestamp']) for r in response if int_or_none(r['timestamp']) is not None])
# Prefer the new polymer UI captures as we support extracting more metadata from them
# WBM captures seem to all switch to this layout ~July 2020
modern_captures = list(filter(lambda x: x >= 20200701000000, all_captures))
if modern_captures:
capture_dates.append(modern_captures[0])
capture_dates.append(url_date)
if all_captures:
capture_dates.append(all_captures[0])
if 'captures' in self._configuration_arg('check_all'):
capture_dates.extend(modern_captures + all_captures)
# Fallbacks if any of the above fail
capture_dates.extend([self._OLDEST_CAPTURE_DATE, self._NEWEST_CAPTURE_DATE])
return orderedSet(capture_dates)
def _real_extract(self, url):
url_date, video_id = self._match_valid_url(url).groups()
urlh = None
try:
urlh = self._request_webpage(
HEADRequest('https://web.archive.org/web/2oe_/http://wayback-fakeurl.archive.org/yt/%s' % video_id),
video_id, note='Fetching archived video file url', expected_status=True)
except ExtractorError as e:
# HTTP Error 404 is expected if the video is not saved.
if isinstance(e.cause, compat_HTTPError) and e.cause.code == 404:
self.raise_no_formats(
'The requested video is not archived, indexed, or there is an issue with web.archive.org',
expected=True)
else:
raise
capture_dates = self._get_capture_dates(video_id, int_or_none(url_date))
self.write_debug('Captures to try: ' + ', '.join(str(i) for i in capture_dates if i is not None))
info = {'id': video_id}
for capture in capture_dates:
if not capture:
continue
webpage = self._download_webpage(
(self._WAYBACK_BASE_URL + 'http://www.youtube.com/watch?v=%s') % (capture, video_id),
video_id=video_id, fatal=False, errnote='unable to download capture webpage (it may not be archived)',
note='Downloading capture webpage')
current_info = self._extract_metadata(video_id, webpage or '')
# Try avoid getting deleted video metadata
if current_info.get('title'):
info = merge_dicts(info, current_info)
if 'captures' not in self._configuration_arg('check_all'):
break
info['thumbnails'] = self._extract_thumbnails(video_id)
if urlh:
url = compat_urllib_parse_unquote(urlh.url)
video_file_url_qs = parse_qs(url)
# Attempt to recover any ext & format info from playback url & response headers
format = {'url': url, 'filesize': int_or_none(urlh.headers.get('x-archive-orig-content-length'))}
itag = try_get(video_file_url_qs, lambda x: x['itag'][0])
if itag and itag in YoutubeIE._formats:
format.update(YoutubeIE._formats[itag])
format.update({'format_id': itag})
else:
mime = try_get(video_file_url_qs, lambda x: x['mime'][0])
ext = (mimetype2ext(mime)
or urlhandle_detect_ext(urlh)
or mimetype2ext(urlh.headers.get('x-archive-guessed-content-type')))
format.update({'ext': ext})
info['formats'] = [format]
if not info.get('duration'):
info['duration'] = str_to_int(try_get(video_file_url_qs, lambda x: x['dur'][0]))
if not info.get('title'):
info['title'] = video_id
return info
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lib/crd.py | TierMobility/aws-auth-operator | 8 | 175919 | <filename>lib/crd.py
from typing import List, Dict
from lib.constants import CRD_GROUP, CRD_VERSION, CRD_KIND
def build_aws_auth_mapping(mappings: List, name: str) -> Dict:
return {
"apiVersion": CRD_GROUP + "/" + CRD_VERSION,
"kind": CRD_KIND,
"metadata": {"annotations": {}, "labels": {}, "name": name,},
"spec": {"mappings": mappings},
}
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generate_images.py | gracecarrillo/github-readme-stats | 0 | 156922 | #!/usr/bin/python3
import asyncio
import os
import re
import aiohttp
from github_stats import Stats
################################################################################
# Helper Functions
################################################################################
def generate_output_folder() -> None:
"""
Create the output folder if it does not already exist
"""
if not os.path.isdir("generated"):
os.mkdir("generated")
################################################################################
# Individual Image Generation Functions
################################################################################
async def generate_overview(s: Stats) -> None:
"""
Generate an SVG badge with summary statistics
:param s: Represents user's GitHub statistics
"""
with open("templates/overview.svg", "r") as f:
output = f.read()
output = re.sub("{{ name }}", await s.name, output)
output = re.sub("{{ stars }}", f"{await s.stargazers:,}", output)
output = re.sub("{{ forks }}", f"{await s.forks:,}", output)
output = re.sub("{{ contributions }}", f"{await s.total_contributions:,}",
output)
changed = (await s.lines_changed)[0] + (await s.lines_changed)[1]
output = re.sub("{{ lines_changed }}", f"{changed:,}", output)
output = re.sub("{{ views }}", f"{await s.views:,}", output)
output = re.sub("{{ repos }}", f"{len(await s.repos):,}", output)
generate_output_folder()
with open("generated/overview.svg", "w") as f:
f.write(output)
async def generate_languages(s: Stats) -> None:
"""
Generate an SVG badge with summary languages used
:param s: Represents user's GitHub statistics
"""
with open("templates/languages.svg", "r") as f:
output = f.read()
progress = ""
lang_list = ""
sorted_languages = sorted((await s.languages).items(), reverse=True,
key=lambda t: t[1].get("size"))
delay_between = 150
for i, (lang, data) in enumerate(sorted_languages):
color = data.get("color")
color = color if color is not None else "#000000"
progress += (f'<span style="background-color: {color};'
f'width: {data.get("prop", 0):0.3f}%;" '
f'class="progress-item"></span>')
lang_list += f"""
<li style="animation-delay: {i * delay_between}ms;">
<svg xmlns="http://www.w3.org/2000/svg" class="octicon" style="fill:{color};"
viewBox="0 0 16 16" version="1.1" width="16" height="16"><path
fill-rule="evenodd" d="M8 4a4 4 0 100 8 4 4 0 000-8z"></path></svg>
<span class="lang">{lang}</span>
<span class="percent">{data.get("prop", 0):0.2f}%</span>
</li>
"""
output = re.sub(r"{{ progress }}", progress, output)
output = re.sub(r"{{ lang_list }}", lang_list, output)
generate_output_folder()
with open("generated/languages.svg", "w") as f:
f.write(output)
################################################################################
# Main Function
################################################################################
async def main() -> None:
"""
Generate all badges
"""
access_token = os.getenv("ACCESS_TOKEN")
if not access_token:
# access_token = os.getenv("GITHUB_TOKEN")
raise Exception("A personal access token is required to proceed!")
user = os.getenv("GITHUB_ACTOR")
exclude_repos = os.getenv("EXCLUDED")
exclude_repos = ({x.strip() for x in exclude_repos.split(",")}
if exclude_repos else None)
exclude_langs = os.getenv("EXCLUDED_LANGS")
exclude_langs = ({x.strip() for x in exclude_langs.split(",")}
if exclude_langs else None)
# Convert a truthy value to a Boolean
ignore_forked_repos = os.getenv("EXCLUDE_FORKED_REPOS")
ignore_forked_repos = (not not ignore_forked_repos
and ignore_forked_repos.strip().lower() != "false")
async with aiohttp.ClientSession() as session:
s = Stats(user, access_token, session, exclude_repos=exclude_repos,
exclude_langs=exclude_langs,
ignore_forked_repos=ignore_forked_repos)
await asyncio.gather(generate_languages(s), generate_overview(s))
if __name__ == "__main__":
asyncio.run(main())
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] |
experiments/counters.py | PetrDlouhy/django-experiments | 237 | 76462 | from django.utils.functional import cached_property
from redis.exceptions import ConnectionError, ResponseError
from experiments.redis_client import get_redis_client
COUNTER_CACHE_KEY = 'experiments:participants:%s'
COUNTER_FREQ_CACHE_KEY = 'experiments:freq:%s'
class Counters(object):
@cached_property
def _redis(self):
return get_redis_client()
def increment(self, key, participant_identifier, count=1):
if count == 0:
return
try:
cache_key = COUNTER_CACHE_KEY % key
freq_cache_key = COUNTER_FREQ_CACHE_KEY % key
new_value = self._redis.hincrby(cache_key, participant_identifier, count)
# Maintain histogram of per-user counts
if new_value > count:
self._redis.hincrby(freq_cache_key, new_value - count, -1)
self._redis.hincrby(freq_cache_key, new_value, 1)
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
pass
def clear(self, key, participant_identifier):
try:
# Remove the direct entry
cache_key = COUNTER_CACHE_KEY % key
pipe = self._redis.pipeline()
freq, _ = pipe.hget(cache_key, participant_identifier).hdel(cache_key, participant_identifier).execute()
# Remove from the histogram
freq_cache_key = COUNTER_FREQ_CACHE_KEY % key
self._redis.hincrby(freq_cache_key, freq or 0, -1)
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
pass
def get(self, key):
try:
cache_key = COUNTER_CACHE_KEY % key
return self._redis.hlen(cache_key)
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
return 0
def get_frequency(self, key, participant_identifier):
try:
cache_key = COUNTER_CACHE_KEY % key
freq = self._redis.hget(cache_key, participant_identifier)
return int(freq) if freq else 0
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
return 0
def get_frequencies(self, key):
try:
freq_cache_key = COUNTER_FREQ_CACHE_KEY % key
# In some cases when there are concurrent updates going on, there can
# briefly be a negative result for some frequency count. We discard these
# as they shouldn't really affect the result, and they are about to become
# zero anyway.
return dict((int(k), int(v)) for (k, v) in self._redis.hgetall(freq_cache_key).items() if int(v) > 0)
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
return dict()
def reset(self, key):
try:
cache_key = COUNTER_CACHE_KEY % key
self._redis.delete(cache_key)
freq_cache_key = COUNTER_FREQ_CACHE_KEY % key
self._redis.delete(freq_cache_key)
return True
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
return False
def reset_pattern(self, pattern_key):
#similar to above, but can pass pattern as arg instead
try:
cache_key = COUNTER_CACHE_KEY % pattern_key
for key in self._redis.keys(cache_key):
self._redis.delete(key)
freq_cache_key = COUNTER_FREQ_CACHE_KEY % pattern_key
for key in self._redis.keys(freq_cache_key):
self._redis.delete(key)
return True
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
return False
def reset_prefix(self, key_prefix):
# Delete all data in redis for a given key prefix
from experiments.utils import grouper
try:
for key_pattern in [COUNTER_CACHE_KEY, COUNTER_FREQ_CACHE_KEY]:
match = "%s:*" % (key_pattern % key_prefix)
key_iter = self._redis.scan_iter(match)
# Delete keys in groups of 1000 to prevent problems with long
# running experiments having many participants
for keys in grouper(key_iter, 1000):
# The last group will be padded with None to reach the specified batch
# size, so these are filtered out here
self._redis.delete(*filter(None, keys))
except (ConnectionError, ResponseError):
# Handle Redis failures gracefully
pass
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galaxy/main/migrations/0063_remove_deprecated_role_fields.py | tima/galaxy | 0 | 185327 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('main', '0062_move_repository_counters'),
]
operations = [
migrations.RemoveField(model_name='role', name='average_score'),
migrations.RemoveField(model_name='role', name='bayesian_score'),
migrations.RemoveField(model_name='role', name='num_ratings'),
]
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tests/observers/k8s_api_test.py | superhsuSFX/signalfx-agent | 1 | 199511 | from functools import partial as p
import pytest
import yaml
from tests.helpers.assertions import has_all_dims, has_datapoint, has_dim_key
from tests.helpers.kubernetes.utils import add_pod_spec_annotations
from tests.helpers.util import wait_for
from tests.paths import TEST_SERVICES_DIR
@pytest.mark.kubernetes
def test_k8s_api_observer_basic(k8s_cluster):
nginx_yaml = TEST_SERVICES_DIR / "nginx/nginx-k8s.yaml"
with k8s_cluster.create_resources([nginx_yaml]):
config = f"""
observers:
- type: k8s-api
monitors:
- type: collectd/nginx
discoveryRule: 'discovered_by == "k8s-api" && kubernetes_namespace == "{k8s_cluster.test_namespace}" && port == 80 && container_spec_name == "nginx"'
url: "http://{{{{.Host}}}}:{{{{.Port}}}}/nginx_status"
"""
with k8s_cluster.run_agent(config) as agent:
assert wait_for(p(has_datapoint, agent.fake_services, dimensions={"plugin": "nginx"}))
@pytest.mark.kubernetes
def test_config_from_annotations(k8s_cluster):
nginx_yaml = TEST_SERVICES_DIR / "nginx/nginx-k8s.yaml"
nginx_with_annotations = yaml.dump_all(
add_pod_spec_annotations(
yaml.safe_load_all(nginx_yaml.read_bytes()),
{
"agent.signalfx.com/monitorType.http": "collectd/nginx",
"agent.signalfx.com/config.80.extraDimensions": "{source: myapp}",
"agent.signalfx.com/config.80.disableEndpointDimensions": "true",
},
)
)
with k8s_cluster.create_resources([nginx_with_annotations]):
config = f"""
observers:
- type: k8s-api
monitors: []
"""
with k8s_cluster.run_agent(config) as agent:
assert wait_for(p(has_datapoint, agent.fake_services, dimensions={"plugin": "nginx", "source": "myapp"}))
for dp in agent.fake_services.datapoints:
if not has_all_dims(dp, {"source": "myapp"}):
continue
assert not has_dim_key(dp, "kubernetes_pod_uid")
@pytest.mark.kubernetes
def test_k8s_annotations_in_discovery(k8s_cluster):
nginx_yaml = TEST_SERVICES_DIR / "nginx/nginx-k8s.yaml"
with k8s_cluster.create_resources([nginx_yaml]):
config = """
observers:
- type: k8s-api
monitors:
- type: collectd/nginx
discoveryRule: 'Get(kubernetes_annotations, "allowScraping") == "true" && port == 80'
"""
with k8s_cluster.run_agent(config) as agent:
assert wait_for(p(has_datapoint, agent.fake_services, dimensions={"plugin": "nginx"}))
@pytest.mark.kubernetes
def test_k8s_annotations_with_alt_ports(k8s_cluster):
consul_yaml = list(yaml.safe_load_all((TEST_SERVICES_DIR / "consul/k8s.yaml").read_bytes()))
# Remove the declared port so we make sure the additionalPortAnnotations is
# what is causing it to be discovered.
consul_yaml[0]["spec"]["template"]["spec"]["containers"][0]["ports"] = []
with k8s_cluster.create_resources([yaml.dump_all(consul_yaml)]):
config = """
observers:
- type: k8s-api
additionalPortAnnotations:
- prometheus.io/port
monitors:
- type: prometheus-exporter
discoveryRule: 'Get(kubernetes_annotations, "prometheus.io/scrape") == "true" && Get(kubernetes_annotations, "prometheus.io/port") == ToString(port)'
configEndpointMappings:
metricPath: 'Get(kubernetes_annotations, "prometheus.io/path", "/metrics")'
"""
with k8s_cluster.run_agent(config) as agent:
assert wait_for(p(has_datapoint, agent.fake_services, metric_name="consul_runtime_malloc_count"))
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] |
lib/segmentation/algorithm.py | rusty1s/embedded_gcnn | 74 | 50455 | <reponame>rusty1s/embedded_gcnn<gh_stars>10-100
import numpy as np
from skimage import color, segmentation
def slic(image, num_segments, compactness=10, max_iterations=10, sigma=0):
image = _preprocess(image)
return segmentation.slic(image, num_segments, compactness, max_iterations,
sigma)
def slic_fixed(num_segments, compactness=10, max_iterations=10, sigma=0):
def slic_image(image):
return slic(image, num_segments, compactness, max_iterations, sigma)
return slic_image
def quickshift(image, ratio=1, kernel_size=5, max_dist=1, sigma=0):
image = _preprocess(image)
return segmentation.quickshift(
image, ratio, kernel_size, max_dist, sigma=sigma)
def quickshift_fixed(ratio=1, kernel_size=5, max_dist=1, sigma=0):
def quickshift_image(image):
return quickshift(image, ratio, kernel_size, max_dist, sigma)
return quickshift_image
def felzenszwalb(image, scale=1, min_size=1, sigma=0):
image = _preprocess(image)
return segmentation.felzenszwalb(image, scale, sigma, min_size)
def felzenszwalb_fixed(scale=1, min_size=1, sigma=0):
def felzenszwalb_image(image):
return felzenszwalb(image, scale, min_size, sigma)
return felzenszwalb_image
def _preprocess(image):
if len(image.shape) == 2 or image.shape[2] == 1:
return color.gray2rgb(
np.reshape(image, (image.shape[0], image.shape[1])))
else:
return image
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] |
allocate/__init__.py | BraeWebb/allocate | 0 | 75297 | <filename>allocate/__init__.py
"""
Tutor allocation algorithm for allocating tutors to the optimal sessions.
"""
__author__ = "<NAME>, <NAME>"
__all__ = ['allocation', 'doodle', 'model', 'solver', 'csvalidator']
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