Datasets:
paulo037
/
starcoder

Dataset card Data Studio Files Community
1
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tools/config.py
emiliopomares/flow-separation-prediction
0
87624
import os config = { 'project_path': os.getcwd() + '/../openfoam/run/Airfoil2D_full/' }
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sge/input.py
python-sge/sge
7
91953
# This file is part of the Pygame SGE. # # The Pygame SGE is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # The Pygame SGE is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with the Pygame SGE. If not, see <http://www.gnu.org/licenses/>. """ This module provides input event classes. Input event objects are used to consolidate all necessary information about input events in a clean way. You normally don't need to use input event objects directly. Input events are handled automatically in each frame of the SGE's main loop. You only need to use input event objects directly if you take control away from the SGE's main loop, e.g. to create your own loop. """ __all__ = ["KeyPress", "KeyRelease", "MouseMove", "MouseButtonPress", "MouseButtonRelease", "JoystickAxisMove", "JoystickHatMove", "JoystickTrackballMove", "JoystickButtonPress", "JoystickButtonRelease", "JoystickEvent", "KeyboardFocusGain", "KeyboardFocusLose", "MouseFocusGain", "MouseFocusLose", "QuitRequest"] class KeyPress: """ This input event represents a key on the keyboard being pressed. .. attribute:: key The identifier string of the key that was pressed. See the table in the documentation for :mod:`sge.keyboard`. .. attribute:: char The unicode string associated with the key press, or an empty unicode string if no text is associated with the key press. See the table in the documentation for :mod:`sge.keyboard`. """ def __init__(self, key, char): self.key = key self.char = char class KeyRelease: """ This input event represents a key on the keyboard being released. .. attribute:: key The identifier string of the key that was released. See the table in the documentation for :class:`sge.input.KeyPress`. """ def __init__(self, key): self.key = key class MouseMove: """ This input event represents the mouse being moved. .. attribute:: x The horizontal relative movement of the mouse. .. attribute:: y The vertical relative movement of the mouse. """ def __init__(self, x, y): self.x = x self.y = y class MouseButtonPress: """ This input event represents a mouse button being pressed. .. attribute:: button The identifier string of the mouse button that was pressed. See the table below. ====================== ================= Mouse Button Name Identifier String ====================== ================= Left mouse button ``"left"`` Right mouse button ``"right"`` Middle mouse button ``"middle"`` Extra mouse button 1 ``"extra1"`` Extra mouse button 2 ``"extra2"`` ====================== ================= """ def __init__(self, button): self.button = button class MouseButtonRelease: """ This input event represents a mouse button being released. .. attribute:: button The identifier string of the mouse button that was released. See the table in the documentation for :class:`sge.input.MouseButtonPress`. """ def __init__(self, button): self.button = button class MouseWheelMove: """ This input event represents a mouse wheel moving. .. attribute:: x The horizontal scroll amount, where ``-1`` is to the left, ``1`` is to the right, and ``0`` is no horizontal scrolling. .. attribute:: y The vertical scroll amount, where ``-1`` is up, ``1`` is down, and ``0`` is no vertical scrolling. """ def __init__(self, x, y): self.x = x self.y = y class JoystickAxisMove: """ This input event represents a joystick axis moving. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: axis The number of the axis that moved, where ``0`` is the first axis on the joystick. .. attribute:: value The tilt of the axis as a float from ``-1`` to ``1``, where ``0`` is centered, ``-1`` is all the way to the left or up, and ``1`` is all the way to the right or down. """ def __init__(self, js_name, js_id, axis, value): self.js_name = js_name self.js_id = js_id self.axis = axis self.value = max(-1.0, min(value, 1.0)) class JoystickHatMove: """ This input event represents a joystick hat moving. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: hat The number of the hat that moved, where ``0`` is the first axis on the joystick. .. attribute:: x The horizontal position of the hat, where ``0`` is centered, ``-1`` is left, and ``1`` is right. .. attribute:: y The vertical position of the hat, where ``0`` is centered, ``-1`` is up, and ``1`` is down. """ def __init__(self, js_name, js_id, hat, x, y): self.js_name = js_name self.js_id = js_id self.hat = hat self.x = x self.y = y class JoystickTrackballMove: """ This input event represents a joystick trackball moving. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: ball The number of the trackball that moved, where ``0`` is the first trackball on the joystick. .. attribute:: x The horizontal relative movement of the trackball. .. attribute:: y The vertical relative movement of the trackball. """ def __init__(self, js_name, js_id, ball, x, y): self.js_name = js_name self.js_id = js_id self.ball = ball self.x = x self.y = y class JoystickButtonPress: """ This input event represents a joystick button being pressed. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: button The number of the button that was pressed, where ``0`` is the first button on the joystick. """ def __init__(self, js_name, js_id, button): self.js_name = js_name self.js_id = js_id self.button = button class JoystickButtonRelease: """ This input event represents a joystick button being released. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: button The number of the button that was released, where ``0`` is the first button on the joystick. """ def __init__(self, js_name, js_id, button): self.js_name = js_name self.js_id = js_id self.button = button class JoystickEvent: """ This input event represents the movement of any joystick input. This makes it possible to treat all joystick inputs the same way, which can be used to simplify things like control customization. .. attribute:: js_name The name of the joystick. .. attribute:: js_id The number of the joystick, where ``0`` is the first joystick. .. attribute:: input_type The type of joystick control that was moved. Can be one of the following: - ``"axis-"`` -- The tilt of a joystick axis to the left or up changes. - ``"axis+"`` -- The tilt of a joystick axis to the right or down changes. - ``"axis0"`` -- The tilt of a joystick axis changes. - ``"hat_left"`` -- Whether or not a joystick hat's position is to the left changes. - ``"hat_right"`` -- Whether or not a joystick hat's position is to the right changes. - ``"hat_center_x"`` -- Whether or not a joystick hat is horizontally centered changes. - ``"hat_up"`` -- Whether or not a joystick hat's position is up changes. - ``"hat_down"`` -- Whether or not a joystick hat's position is down changes. - ``"hat_center_y"`` -- Whether or not a joystick hat is vertically centered changes. - ``"trackball_left"`` -- A joystick trackball is moved left. - ``"trackball_right"`` -- A joystick trackball is moved right. - ``"trackball_up"`` -- A joystick trackball is moved up. - ``"trackball_down"`` -- A joystick trackball is moved down. - ``"button"`` -- Whether or not a joystick button is pressed changes. .. attribute:: input_id The number of the joystick control that was moved, where ``0`` is the first control of its type on the joystick. .. attribute:: value The value of the event, which is different depending on the value of :attr:`input_type`. If :attr:`input_type` is ``"trackball_left"``, ``"trackball_right"``, ``"trackball_up"``, or ``"trackball_down"``, this is the relative movement of the trackball in the respective direction. Otherwise, this is the new value of the respective control. See the documentation for :func:`sge.joystick.get_value` for more information. """ def __init__(self, js_name, js_id, input_type, input_id, value): self.js_name = js_name self.js_id = js_id self.input_type = input_type self.input_id = input_id self.value = value class KeyboardFocusGain: """ This input event represents the game window gaining keyboard focus. Keyboard focus is normally needed for keyboard input to be received. .. note:: On some window systems, such as the one used by Windows, no distinction is made between keyboard and mouse focus, but on some other window systems, such as the X Window System, a distinction is made: one window can have keyboard focus while another has mouse focus. Be careful to observe the difference; failing to do so may result in annoying bugs, and you won't notice these bugs if you are testing on a window manager that doesn't recognize the difference. """ class KeyboardFocusLose: """ This input event represents the game window losing keyboard focus. Keyboard focus is normally needed for keyboard input to be received. .. note:: See the note in the documentation for :class:`sge.input.KeyboardFocusGain`. """ class MouseFocusGain: """ This input event represents the game window gaining mouse focus. Mouse focus is normally needed for mouse input to be received. .. note:: See the note in the documentation for :class:`sge.input.KeyboardFocusGain`. """ class MouseFocusLose: """ This input event represents the game window losing mouse focus. Mouse focus is normally needed for mouse input to be received. .. note:: See the note in the documentation for :class:`sge.input.KeyboardFocusGain`. """ class WindowResize: """ This input event represents the player resizing the window. """ class QuitRequest: """ This input event represents the OS requesting for the program to close (e.g. when the user presses a "close" button on the window border). """
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qchem/qchem.py
SinaMostafanejad/MolSSI_project_FSHXF
0
79457
<filename>qchem/qchem.py from __future__ import division from qm.qm_calculator import QM_calculator from misc import call_name class QChem(QM_calculator): """ Class for common parts of Q-Chem :param string basis_set: Basis set information :param string memory: Allocatable memory in the calculation :param string qm_path: Path for Q-Chem :param integer nthreads: Number of threads in the calculation :param string version: Version of Q-Chem """ def __init__(self, basis_set, memory, qm_path, nthreads, version): # Save name of QM calculator and its method super().__init__() # Initialize Q-Chem common variables self.basis_set = basis_set self.memory = memory self.qm_path = qm_path self.nthreads = nthreads self.version = version if (self.version != "5.2"): raise ValueError (f"( {self.qm_prog}.{call_name()} ) Other version not implemented! {self.version}")
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fused_biattention.py
utahnlp/layer_augmentation_qa
6
38188
import sys import torch from torch import nn from torch.autograd import Variable from view import * from holder import * from util import * from join_table import * from trilinear_prod import * from fusion import * # fused bidir attention class FusedBiAttention(torch.nn.Module): def __init__(self, opt, shared): super(FusedBiAttention, self).__init__() self.opt = opt self.shared = shared enc_size = opt.hidden_size if 'elmo' not in opt.enc else opt.hidden_size + opt.elmo_size self.trilinear_prod = TrilinearProd(opt, enc_size) self.fusion = Fusion(opt, enc_size) self.softmax2 = nn.Softmax(2) self.phi_joiner = JoinTable(2) def biattention(self, scores, C, Q): batch_l = self.shared.batch_l context_l = self.shared.context_l enc_size = C.shape[2] # attention att1 = self.softmax2(scores) # (batch_l, context_l, max_query_l) att2 = self.softmax2(scores.transpose(1,2)) # (batch_l, max_query_l, context_l) # attend agg1 = att1.bmm(Q) # (batch_l, context_l, enc_size) agg2 = att2.bmm(C) # (batch_l, max_query_l, enc_size) agg2 = self.masked_fill_query(agg2) return att1, att2, agg1, agg2 def masked_fill_scores(self, scores): return scores * self.shared.score_mask + (self.shared.one - self.shared.score_mask) * self.shared.neg_inf def masked_fill_query(self, query): return query * self.shared.query_mask.unsqueeze(-1) # input encodings of context (C) and query (Q) # C of shape (batch_l, context_l, hidden_size) # Q of shape (batch_l, query_l, hidden_size) def forward(self, C, Q): self.update_context() batch_l = self.shared.batch_l context_l = self.shared.context_l max_query_l = self.shared.query_l.max() hidden_size = self.opt.hidden_size # get similarity score scores = self.trilinear_prod(C, Q) scores = self.masked_fill_scores(scores) # att1, att2, agg1, agg2 = self.biattention(scores, C, Q) # G = self.fusion(C, agg1) P = self.fusion(Q, agg2) P = self.masked_fill_query(P) # bookkeeping self.shared.att_soft1 = att1 self.shared.att_soft2 = att2 self.shared.G = G self.shared.P = P return att1, att2, G def update_context(self): batch_l = self.shared.batch_l context_l = self.shared.context_l max_query_l = self.shared.query_l.max() word_vec_size = self.opt.word_vec_size hidden_size = self.opt.hidden_size def begin_pass(self): pass def end_pass(self): pass
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src/residue.py
kabhel/Fold_U
0
151709
""" .. module:: Residue :synopsis: This module implements the Residue class. """ # Third-party modules import numpy as np # Local modules from src.atom import Atom class Residue: """ .. class:: Residue This class groups informations about a residue. Attributes: name (str): Name of the residue (1 letter code) ca_coords (Numpy array): 3D coordinates of the residue """ def __init__(self, name): self.name = name self.ca_atom = Atom("CA") self.cb_atom = Atom("CB") self.c_atom = Atom("C") self.n_atom = Atom("N") self.secondary_struct = None self.ss_confidence = None def __str__(self): return str(self.name) def __repr__(self): return str(self.name) def calculate_distance(self, residue, carbon): """ Calculate Euclidian distance between two residues with THE most efficient method, the Einstein summation convention with *numpy.einsum*. .. math:: distance = \sqrt{(x_a-x_b)^2+(y_a-y_b)^2+(z_a-z_b)^2} Args: residue (object): An object of the Residue class. carbon (str): Type of the carbon. Returns: float: The calculated distance. """ if carbon == "CA": a_min_b = self.ca_atom.coords - residue.ca_atom.coords elif carbon == "CB": a_min_b = self.cb_atom.coords - residue.cb_atom.coords # The Numpy's "einsum" function is the most efficient way to calculate a distance # accordingly to this benchmarking: https://stackoverflow.com/a/47775357/6401758 dist = np.sqrt(np.einsum('i,i->', a_min_b, a_min_b)) return dist
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credential_test.py
jmuema/password-locker
0
139790
import unittest # Importing the unittest module from credential import Credential # Importing the credential class class TestCredential(unittest.TestCase): ''' Test class that defines test cases for the credential class behaviours. Args: unittest.TestCase: TestCase class that helps in creating test cases ''' def setUp(self): ''' Set up method to run before each test cases. ''' self.new_credential = Credential("instagram", "ironman", "ironman20") # create credential object def test_init(self): ''' test_init test case to test if the object is initialized properly ''' self.assertEqual(self.new_credential.myaccountname,"instagram") self.assertEqual(self.new_credential.myusername,"ironman") self.assertEqual(self.new_credential.mypassword,"<PASSWORD>") def test_save_credential(self): ''' test_save_credential test case to test if the credential object is saved into the credential list ''' self.new_credential.save_credential() # saving the new credential self.assertEqual(len(Credential.credential_list),1) def tearDown(self): ''' tearDown method that does clean up after each test case has run. ''' Credential.credential_list = [] def test_save_multiple_credential(self): ''' test to check if we can check multiple objects within credenials list ''' self.new_credential.save_credential() test_credential = Credential("instagram","ironman","ironman20") # new credential test_credential.save_credential() self.assertEqual(len(Credential.credential_list),2) def test_delete_credential(self): ''' test to remove a credential from our credential list ''' self.new_credential.save_credential() test_credential = Credential("instagram","ironman","ironman20") # new credential test_credential.save_credential() self.new_credential.delete_credential()# Deleting a credential object self.assertEqual(len(Credential.credential_list),1) def test_find_credential_by_username(self): ''' test to check if we can find a credential by username and display information ''' self.new_credential.save_credential() test_credential = Credential("instagram","ironman","ironman20") # new credential test_credential.save_credential() found_credential = Credential.find_by_username("ironman") self.assertEqual(found_credential.mypassword,test_credential.mypassword) def test_credential_exists(self): ''' test to check if we can return a Boolean if we cannot find the credential. ''' self.new_credential.save_credential() test_credential = Credential("instagram","ironman","ironman20") # new credential test_credential.save_credential() credential_exists = Credential.credential_exist("ironman") self.assertTrue(credential_exists) def test_display_all_credentials(self): ''' method that returns a list of all credentials saved ''' self.assertEqual(Credential.display_credentials(),Credential.credential_list) if __name__ == '__main__': unittest.main()
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colour/models/rgb/transfer_functions/tests/test_panasonic_vlog.py
JGoldstone/colour
0
17884
<gh_stars>0 # -*- coding: utf-8 -*- """ Defines the unit tests for the :mod:`colour.models.rgb.transfer_functions.\ panasonic_vlog` module. """ import numpy as np import unittest from colour.models.rgb.transfer_functions import ( log_encoding_VLog, log_decoding_VLog, ) from colour.utilities import domain_range_scale, ignore_numpy_errors __author__ = 'Colour Developers' __copyright__ = 'Copyright (C) 2013-2021 - Colour Developers' __license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause' __maintainer__ = 'Colour Developers' __email__ = '<EMAIL>' __status__ = 'Production' __all__ = [ 'TestLogEncoding_VLog', 'TestLogDecoding_VLog', ] class TestLogEncoding_VLog(unittest.TestCase): """ Defines :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_encoding_VLog` definition unit tests methods. """ def test_log_encoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_encoding_VLog` definition. """ self.assertAlmostEqual(log_encoding_VLog(0.0), 0.125, places=7) self.assertAlmostEqual( log_encoding_VLog(0.18), 0.423311448760136, places=7) self.assertAlmostEqual( log_encoding_VLog(0.18, 12), 0.423311448760136, places=7) self.assertAlmostEqual( log_encoding_VLog(0.18, 10, False), 0.421287228403675, places=7) self.assertAlmostEqual( log_encoding_VLog(0.18, 10, False, False), 0.409009628526078, places=7) self.assertAlmostEqual( log_encoding_VLog(1.0), 0.599117700158146, places=7) def test_n_dimensional_log_encoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_encoding_VLog` definition n-dimensional arrays support. """ L_in = 0.18 V_out = log_encoding_VLog(L_in) L_in = np.tile(L_in, 6) V_out = np.tile(V_out, 6) np.testing.assert_almost_equal( log_encoding_VLog(L_in), V_out, decimal=7) L_in = np.reshape(L_in, (2, 3)) V_out = np.reshape(V_out, (2, 3)) np.testing.assert_almost_equal( log_encoding_VLog(L_in), V_out, decimal=7) L_in = np.reshape(L_in, (2, 3, 1)) V_out = np.reshape(V_out, (2, 3, 1)) np.testing.assert_almost_equal( log_encoding_VLog(L_in), V_out, decimal=7) def test_domain_range_scale_log_encoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_encoding_VLog` definition domain and range scale support. """ L_in = 0.18 V_out = log_encoding_VLog(L_in) d_r = (('reference', 1), (1, 1), (100, 100)) for scale, factor in d_r: with domain_range_scale(scale): np.testing.assert_almost_equal( log_encoding_VLog(L_in * factor), V_out * factor, decimal=7) @ignore_numpy_errors def test_nan_log_encoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_encoding_VLog` definition nan support. """ log_encoding_VLog(np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan])) class TestLogDecoding_VLog(unittest.TestCase): """ Defines :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_decoding_VLog` definition unit tests methods. """ def test_log_decoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_decoding_VLog` definition. """ self.assertAlmostEqual(log_decoding_VLog(0.125), 0.0, places=7) self.assertAlmostEqual( log_decoding_VLog(0.423311448760136), 0.18, places=7) self.assertAlmostEqual( log_decoding_VLog(0.423311448760136, 12), 0.18, places=7) self.assertAlmostEqual( log_decoding_VLog(0.421287228403675, 10, False), 0.18, places=7) self.assertAlmostEqual( log_decoding_VLog(0.409009628526078, 10, False, False), 0.18, places=7) self.assertAlmostEqual( log_decoding_VLog(0.599117700158146), 1.0, places=7) def test_n_dimensional_log_decoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_decoding_VLog` definition n-dimensional arrays support. """ V_out = 0.423311448760136 L_in = log_decoding_VLog(V_out) V_out = np.tile(V_out, 6) L_in = np.tile(L_in, 6) np.testing.assert_almost_equal( log_decoding_VLog(V_out), L_in, decimal=7) V_out = np.reshape(V_out, (2, 3)) L_in = np.reshape(L_in, (2, 3)) np.testing.assert_almost_equal( log_decoding_VLog(V_out), L_in, decimal=7) V_out = np.reshape(V_out, (2, 3, 1)) L_in = np.reshape(L_in, (2, 3, 1)) np.testing.assert_almost_equal( log_decoding_VLog(V_out), L_in, decimal=7) def test_domain_range_scale_log_decoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_decoding_VLog` definition domain and range scale support. """ V_out = 0.423311448760136 L_in = log_decoding_VLog(V_out) d_r = (('reference', 1), (1, 1), (100, 100)) for scale, factor in d_r: with domain_range_scale(scale): np.testing.assert_almost_equal( log_decoding_VLog(V_out * factor), L_in * factor, decimal=7) @ignore_numpy_errors def test_nan_log_decoding_VLog(self): """ Tests :func:`colour.models.rgb.transfer_functions.panasonic_vlog.\ log_decoding_VLog` definition nan support. """ log_decoding_VLog(np.array([-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan])) if __name__ == '__main__': unittest.main()
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get_data/__init__.py
LilySu/nyc-health-API
0
128258
from flask import Flask from flask import jsonify import pandas as pd import markdown import requests import os app = Flask(__name__) @app.route("/") def index(): with open(os.path.dirname(app.root_path) + '/README.md','r') as markdown_file: content = markdown_file.read() return markdown.markdown(content) @app.route("/boro") def boro(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/boro.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/by-age") def byage(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/by-age.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/by-sex") def bysex(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/by-sex.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/case-hosp-death") def casehospdeath(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/case-hosp-death.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/probable-confirmed-dod") def probableconfirmeddod(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/probable-confirmed-dod.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/summary") def summary(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/summary.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200 @app.route("/tests-by-zcta") def testsbyzcta(): df = pd.read_csv('https://raw.githubusercontent.com/nychealth/coronavirus-data/master/tests-by-zcta.csv') df.fillna(0, inplace=True) return jsonify(df.to_dict('records')),200
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src/cookbook/__init__.py
Vidreven/cookbook
0
114374
<reponame>Vidreven/cookbook<filename>src/cookbook/__init__.py from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from . import config URL = ( f"{config.DB_DRIVER}://{config.DB_USER}:{config.DB_PWD}" f"@{config.DB_HOST}:{config.DB_PORT}/{config.DB_NAME}" ) engine = create_engine(URL, pool_pre_ping=True) Session = sessionmaker(bind=engine)
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lib/arg.py
XanderXAJ/static-site-helpers
0
122412
import argparse import typing def generate_argument_parser(parser: argparse.ArgumentParser = None): if parser is None: parser = argparse.ArgumentParser() parser.add_argument('--log_level', help='Set logging level', default='WARNING', type=str.upper, choices=['CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG']) parser.add_argument('paths', nargs='+', metavar='path') return parser def parse_arguments(args: typing.List[str] = None, parser: argparse.ArgumentParser = None): parser = generate_argument_parser(parser=parser) return parser.parse_args(args)
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quickcert.py
dedickinson/hub-util-tls
0
149969
#!/usr/bin/env python3 # PYTHON_ARGCOMPLETE_OK import quickcert quickcert.QuickCertCli().run()
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HUGGINGFACE.py
mkingopng/NBME_score_clinical_patient_notes
1
21252
import os TRANSFORMERS = '/home/noone/documents/github/transformers' TOKENIZERS = '/home/noone/documents/github/tokenizers' DATASETS = '/home/noone/documents/github/datasets' MODELS = os.path.join(TRANSFORMERS, 'src/transformers/models') DEBERTA_V2 = os.path.join(MODELS, 'deberta_v2') DEBERTA_V3 = os.path.join(MODELS, 'deberta-v3-base') ENCODER_DECODER = os.path.join(MODELS, 'encoder_decoder') HUGGINGFACE_HUB = '/home/noone/documents/github/huggingface_hub' """ Huggingface Repos Cloned: - transformers - tokenizers = optimum - datasets - huggingface_hub - accelerate - notebooks - blog - huggingface sagemaker snowflake example - education toolkit - evaluate - knockknock - neuralcoref - mongoku - data-measurements-tool - neural compressor - allennlp - pytorch-openai-transformer-lm - pytorch pretrained bigGAN - awesome NLP discussion papers - torchMoji - naacl_transfer_learning_tutorial - """
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orio/main/tuner/tuner.py
parsabee/Orio
24
11361
<reponame>parsabee/Orio # # The tuner class to initiate the empirical performance tuning process # import re, sys, os from orio.main.util.globals import * import orio.main.dyn_loader, orio.main.tspec.tspec, orio.main.tuner.ptest_codegen, orio.main.tuner.ptest_driver #-------------------------------------------------- # the name of the module containing various search algorithms SEARCH_MOD_NAME = 'orio.main.tuner.search' #-------------------------------------------------- class PerfTuner: ''' The empirical performance tuner. This class is responsible for invoking the code generators of the annotation modules, compiling the resulting code, and interfacing with the search interface to run the tests and collect the results. ''' #------------------------------------------------- def __init__(self, odriver): '''To instantiate an empirical performance tuner object''' self.odriver = odriver self.dloader = orio.main.dyn_loader.DynLoader() self.num_params=0 self.num_configs=0 self.num_bin=0 self.num_int=0 self.tinfo = None #------------------------------------------------- def tune(self, module_body_code, line_no, cfrags): ''' Perform empirical performance tuning on the given annotated code. And return the best optimized code variant. ''' # extract the tuning information specified from the given annotation tinfo = self.__extractTuningInfo(module_body_code, line_no) self.tinfo = tinfo # determine if parallel search is required use_parallel_search = tinfo.batch_cmd != None # create a performance-testing code generator for each distinct problem size ptcodegens = [] #timing_code = '' for prob_size in self.__getProblemSizes(tinfo.iparam_params, tinfo.iparam_constraints): if self.odriver.lang == 'c': c = orio.main.tuner.ptest_codegen.PerfTestCodeGen(prob_size, tinfo.ivar_decls, tinfo.ivar_decl_file, tinfo.ivar_init_file, tinfo.ptest_skeleton_code_file, self.odriver.lang, tinfo.random_seed, use_parallel_search, tinfo.validation_file) elif self.odriver.lang == 'cuda': c = orio.main.tuner.ptest_codegen.PerfTestCodeGenCUDA(prob_size, tinfo.ivar_decls, tinfo.ivar_decl_file, tinfo.ivar_init_file, tinfo.ptest_skeleton_code_file, self.odriver.lang, tinfo.random_seed, use_parallel_search) elif self.odriver.lang == 'opencl': c = orio.main.tuner.ptest_codegen.PerfTestCodeGenOpenCL(prob_size, tinfo.ivar_decls, tinfo.ivar_decl_file, tinfo.ivar_init_file, tinfo.ptest_skeleton_code_file, self.odriver.lang, tinfo.random_seed, use_parallel_search) elif self.odriver.lang == 'fortran': c = orio.main.tuner.ptest_codegen.PerfTestCodeGenFortran(prob_size, tinfo.ivar_decls, tinfo.ivar_decl_file, tinfo.ivar_init_file, tinfo.ptest_skeleton_code_file, self.odriver.lang, tinfo.random_seed, use_parallel_search) else: err('main.tuner.tuner: unknown output language specified: %s' % self.odriver.lang) ptcodegens.append(c) # create the performance-testing driver ptdriver = orio.main.tuner.ptest_driver.PerfTestDriver(self.tinfo, use_parallel_search, self.odriver.lang, c.getTimerCode(use_parallel_search)) # get the axis names and axis value ranges to represent the search space axis_names, axis_val_ranges = self.__buildCoordSystem(tinfo.pparam_params, tinfo.cmdline_params) info('%s' % axis_names) info('%s' % axis_val_ranges) # combine the performance parameter constraints pparam_constraint = 'True' for vname, rhs in tinfo.pparam_constraints: pparam_constraint += ' and (%s)' % rhs # dynamically load the search engine class and configure it if Globals().extern: tinfo.search_algo='Extern' info('Running in %s mode' % tinfo.search_algo) info('Using parameters %s' % Globals().config) class_name = tinfo.search_algo mod_name = '.'.join([SEARCH_MOD_NAME, class_name.lower(), class_name.lower()]) search_class = self.dloader.loadClass(mod_name, class_name) # convert the search time limit (from minutes to seconds) and get the total number of # search runs search_time_limit = 60 * tinfo.search_time_limit search_total_runs = tinfo.search_total_runs search_use_z3 = tinfo.search_use_z3 search_resume = tinfo.search_resume # get the search-algorithm-specific arguments search_opts = dict(tinfo.search_opts) # perform the performance tuning for each distinct problem size optimized_code_seq = [] for ptcodegen in ptcodegens: if Globals().verbose: info('\n----- begin empirical tuning for problem size -----') # Sort y variable name... not sure it's really necessary iparams = sorted(ptcodegen.input_params[:]) for pname, pvalue in iparams: info(' %s = %s' % (pname, pvalue)) iparams = sorted(ptcodegen.input_params[:]) for pname, pvalue in iparams: Globals().metadata['size_' + pname] = pvalue debug(ptcodegen.input_params[:]) # create the search engine search_eng = search_class({'cfrags':cfrags, # code versions 'axis_names':axis_names, # performance parameter names 'axis_val_ranges':axis_val_ranges, # performance parameter values 'pparam_constraint':pparam_constraint, 'search_time_limit':search_time_limit, 'search_total_runs':search_total_runs, 'search_resume':search_resume, 'search_opts':search_opts, 'ptcodegen':ptcodegen, 'ptdriver':ptdriver, 'odriver':self.odriver, 'use_parallel_search':use_parallel_search, 'input_params':ptcodegen.input_params[:]}) # search for the best performance parameters best_perf_params, best_perf_cost = search_eng.search() # output the best performance parameters if Globals().verbose and not Globals().extern: info('----- the obtained best performance parameters -----') pparams = sorted(list(best_perf_params.items())) for pname, pvalue in pparams: info(' %s = %s' % (pname, pvalue)) # generate the optimized code using the obtained best performance parameters if Globals().extern: best_perf_params=Globals().config debug("[orio.main.tuner.tuner] Globals config: %s" % str(Globals().config), obj=self, level=6) cur_optimized_code_seq = self.odriver.optimizeCodeFrags(cfrags, best_perf_params) # check the optimized code sequence if len(cur_optimized_code_seq) != 1: err('orio.main.tuner internal error: the empirically optimized code cannot contain multiple versions') # get the optimized code optimized_code, _, externals = cur_optimized_code_seq[0] # insert comments into the optimized code to include information about # the best performance parameters and the input problem sizes iproblem_code = '' iparams = sorted(ptcodegen.input_params[:]) for pname, pvalue in iparams: if pname == '__builtins__': continue iproblem_code += ' %s = %s \n' % (pname, pvalue) pparam_code = '' pparams = sorted(list(best_perf_params.items())) for pname, pvalue in pparams: if pname == '__builtins__': continue pparam_code += ' %s = %s \n' % (pname, pvalue) info_code = '\n/**-- (Generated by Orio) \n' if not Globals().extern: info_code += 'Best performance cost: \n' info_code += ' %s \n' % best_perf_cost info_code += 'Tuned for specific problem sizes: \n' info_code += iproblem_code info_code += 'Best performance parameters: \n' info_code += pparam_code info_code += '--**/\n' optimized_code = info_code + optimized_code # store the optimized for this problem size optimized_code_seq.append((optimized_code, ptcodegen.input_params[:], externals)) # return the optimized code return optimized_code_seq # Private methods #------------------------------------------------- def __extractTuningInfo(self, code, line_no): '''Extract tuning information from the given annotation code''' # parse the code match_obj = re.match(r'^\s*import\s+spec\s+([/A-Za-z_]+);\s*$', code) # if the code contains a single import statement if match_obj: # get the specification name spec_name = match_obj.group(1) spec_file = spec_name+'.spec' try: src_dir = '/'.join(list(Globals().src_filenames.keys())[0].split('/')[:-1]) spec_file_path = os.getcwd() + '/' + src_dir + '/' + spec_file f = open(spec_file_path, 'r') tspec_code = f.read() f.close() except: err('%s: cannot open file for reading: %s' % (self.__class__, spec_file_path)) tuning_spec_dict = orio.main.tspec.tspec.TSpec().parseProgram(tspec_code) # if the tuning specification is hardcoded into the given code elif code.lstrip().startswith('spec'): tuning_spec_dict = orio.main.tspec.tspec.TSpec().parseProgram(code) else: # parse the specification code to get the tuning information tuning_spec_dict = orio.main.tspec.tspec.TSpec().parseSpec(code, line_no) # return the tuning information return tuning_spec_dict #------------------------------------------------- def __listAllCombinations(self, seqs): ''' Enumerate all combinations of the given sequences. e.g. input: [['a','b'],[1,2]] --> [['a',1],['a',2],['b',1],['b',2]] ''' # the base case if len(seqs) == 0: return [] # the recursive step trailing_combs = self.__listAllCombinations(seqs[1:]) if trailing_combs == []: trailing_combs = [[]] combs = [] for i in seqs[0]: for c in trailing_combs: combs.append([i] + c) # return the combinations return combs #------------------------------------------------- def __getProblemSizes(self, iparam_params, iparam_constraints): '''Return all valid problem sizes''' # combine the input parameter constraints iparam_constraint = 'True' for vname, rhs in iparam_constraints: iparam_constraint += ' and (%s)' % rhs # compute all possible combinations of problem sizes prob_sizes = [] pnames, pvalss = list(zip(*iparam_params)) for pvals in self.__listAllCombinations(pvalss): prob_sizes.append(list(zip(pnames, pvals))) # exclude all invalid problem sizes n_prob_sizes = [] for p in prob_sizes: try: is_valid = eval(iparam_constraint, dict(p)) except Exception as e: err('orio.main.tuner.tuner:%s: failed to evaluate the input parameter constraint expression\n --> %s: %s' % (iparam_constraint,e.__class__.__name__, e)) if is_valid: n_prob_sizes.append(p) prob_sizes = n_prob_sizes # check if the new problem sizes is empty if len(prob_sizes) == 0: err('orio.main.tuner.tuner: no valid problem sizes exist. please check the input parameter ' + 'constraints') # return all possible combinations of problem sizes return prob_sizes #------------------------------------------------- def __buildCoordSystem(self, perf_params, cmdline_params): '''Return information about the coordinate systems that represent the search space''' debug("BUILDING COORD SYSTEM", obj=self,level=3) # get the axis names and axis value ranges axis_names = [] axis_val_ranges = [] for pname, prange in perf_params: axis_names.append(pname) # BN: why on earth would someone do this????? # axis_val_ranges.append(self.__sort(prange)) axis_val_ranges.append(prange) for pname, prange in cmdline_params: axis_names.append('__cmdline_' + pname) axis_val_ranges.append(prange) self.num_params=len(axis_names) self.num_configs=1 self.num_bin=0 self.num_categorical = 0 self.num_int=self.num_params ptype=[] for vals in axis_val_ranges: self.num_configs=self.num_configs*len(vals) ptype.append('I') if type(vals[0]) == bool: self.num_bin=self.num_bin+1 ptype[len(ptype)-1]=('B') if type(vals[0]) == str: self.num_categorical = self.num_categorical+1 self.num_int -= self.num_bin self.num_int -= self.num_categorical info('Search_Space = %1.3e' % self.num_configs) info('Number_of_Parameters = %02d' % self.num_params) info('Numeric_Parameters = %02d' % self.num_int) info('Binary_Parameters = %02d' % self.num_bin) info('Categorical_Parameters = %02d' % self.num_categorical) sys.stderr.write('%s\n'% Globals().configfile) return (axis_names, axis_val_ranges)
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libcloud/extra/drivers/google.py
Scalr/libcloud
0
42226
<gh_stars>0 # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You 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. """ Module for Google Big Data Drivers. """ from libcloud.extra.drivers.google_bq_utils import QueryJob from libcloud.common.google import GoogleAuthType, GoogleBaseConnection from libcloud.common.base import BaseDriver API_VERSION = 'v2' class BQConnection(GoogleBaseConnection): """ Connection class for the BQ driver. """ def __init__(self, user_id, key, secure=None, auth_type=None, credential_file=None, **kwargs): project = kwargs.pop('project') super(BQConnection, self).__init__(user_id, key, secure=secure, auth_type=auth_type, credential_file=credential_file, **kwargs) self.request_path = '/bigquery/%s/projects/%s' % (API_VERSION, project) class BigQuery(BaseDriver): """ Google Big Query client """ connectionCls = BQConnection api_name = 'google' name = 'Big Query' default_scopes = ['https://www.googleapis.com/auth/bigquery', 'https://www.googleapis.com/auth/bigquery.insertdata', 'https://www.googleapis.com/auth/cloud-platform.read-only', 'https://www.googleapis.com/auth/devstorage.full_control', 'https://www.googleapis.com/auth/devstorage.read_only', 'https://www.googleapis.com/auth/devstorage.read_write'] def __init__(self, user_id, key, project, **kwargs): """ :param user_id: The email address (for service accounts) or Client ID (for installed apps) to be used for authentication. :type user_id: ``str`` :param key: The RSA Key (for service accounts) or file path containing key or Client Secret (for installed apps) to be used for authentication. :type key: ``str`` :keyword project: Your project name. (required) :type project: ``str`` :keyword auth_type: Accepted values are "SA" or "IA" or "GCE" ("Service Account" or "Installed Application" or "GCE" if libcloud is being used on a GCE instance with service account enabled). If not supplied, auth_type will be guessed based on value of user_id or if the code is being executed in a GCE instance. :type auth_type: ``str`` :keyword scopes: List of authorization URLs. Default is empty and grants read/write to Compute, Storage, DNS. :type scopes: ``list`` """ self.project = project if 'auth_type' not in kwargs: kwargs['auth_type'] = GoogleAuthType.SA self.scopes = kwargs.get('scopes', self.default_scopes) super(BigQuery, self).__init__(user_id, key, **kwargs) def _ex_connection_class_kwargs(self): """ Add extra parameters to auth request """ res = super(BigQuery, self)._ex_connection_class_kwargs() res['project'] = self.project res['scopes'] = self.scopes return res def list_datasets(self): """ Get list of datasets Api reference: https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list :return: list of dicts. Each dict contains two keys 'datasetId' and 'projectId' """ request = '/datasets' response = self.connection.request(request, method='GET').object return [l['datasetReference'] for l in response['datasets']] def list_tables(self, dataset_id): """ Get list of tables for dataset Api reference: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/list :param dataset_id: str. Id of dataset. :return: list of dicts. Each dict contains next keys 'datasetId', 'projectId' and 'tableId' """ request = '/datasets/%s/tables' % dataset_id response = self.connection.request(request, method='GET').object return [l['tableReference'] for l in response['tables']] def query(self, query, max_results=50000, timeout_ms=60000, use_legacy_sql=False): """ Execute query and return result. Result will be chunked. Reference: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query :param query: str. BQ query. Example: SELECT * FROM {billing_table} LIMIT 1 :param max_results: int. Page size :param timeout_ms: int. Max execution time. Default 1 min :param use_legacy_sql: bool. Specifies whether to use BigQuery's legacy SQL dialect for this query. :return: dict which represent row from result """ request = '/queries' data = {'query': query, 'useLegacySql': use_legacy_sql, 'maxResults': max_results, 'timeoutMs': timeout_ms} response = self.connection.request(request, method='POST', data=data).object query_job = QueryJob(response) return self._get_job_results(query_job, max_results, timeout_ms) def _get_job_results(self, query_job, max_results, timeout_ms): """ Deal with paginated QueryJob results Reference: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/getQueryResults :param query_job: query job object :return: generator over rows """ while True: for row in query_job.rows: yield row if not query_job.page_token: # last page break # next request data = { 'maxResults': max_results, 'pageToken': query_job.page_token, 'timeoutMs': timeout_ms } request = '/queries/' + query_job.job_id response = self.connection.request(request, method='GET', params=data).object query_job = QueryJob(response)
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ed2d/mesh.py
explosiveduck/cubix
1
1612026
<filename>ed2d/mesh.py<gh_stars>1-10 from gem import matrix from gem import vector from ed2d.opengl import gl, pgl from ed2d.assets import objloader def buffer_object(data, typeM): if data or 0: vbo = pgl.glGenBuffers(1) gl.glBindBuffer(gl.GL_ARRAY_BUFFER, vbo) pgl.glBufferData(gl.GL_ARRAY_BUFFER, data, typeM, gl.GL_STATIC_DRAW) gl.glBindBuffer(gl.GL_ARRAY_BUFFER, 0) return vbo else: return None def index_buffer_object(data, typeM): if data or 0: ibo = pgl.glGenBuffers(1) gl.glBindBuffer(gl.GL_ELEMENT_ARRAY_BUFFER, ibo) pgl.glBufferData(gl.GL_ELEMENT_ARRAY_BUFFER, data, typeM, gl.GL_STATIC_DRAW) gl.glBindBuffer(gl.GL_ELEMENT_ARRAY_BUFFER, 0) return ibo else: return None def bind_object(dataLoc, vbo, size): if (dataLoc is not None) and (vbo is not None): gl.glEnableVertexAttribArray(dataLoc) gl.glBindBuffer(gl.GL_ARRAY_BUFFER, vbo) pgl.glVertexAttribPointer(dataLoc, size, gl.GL_FLOAT, gl.GL_FALSE, 0, None) else: pass def unbind_object(dataLoc): if dataLoc is not None: gl.glBindBuffer(gl.GL_ARRAY_BUFFER, 0) gl.glDisableVertexAttribArray(dataLoc) else: pass def calc_face_normal(vertex1, vertex2, vertex3): ''' Calculate a face normal from 3 vertices. 3D Vector inputs. ''' vertex11 = vertex2 - vertex1 vertex22 = vertex3 - vertex1 normal = vertex11.cross(vertex22) normal.i_normalize() return normal # Conver matrix 4x4 to 3x3 def convertM4to3(mat): ''' Convert a 4x4 Matrix to 3x3. ''' temp = [[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]] for i in range(3): for j in range(3): temp[i][j] = mat[i][j] out = matrix.Matrix(3) out.matrix = temp return out class Indexer(object): ''' This is needed for CSG.''' def __init__(self): self.unique = [] self.indices = [] self.map = {} def add(self, obj): key = repr(obj) if not (key in self.map): self.map[key] = len(self.unique) self.unique.append(obj) return self.map[key] class MeshBase(object): def __init__(self): self.program = None self.vertLoc = None self.UVLoc = None self.colorLoc = None self.normLoc = None self.modelID = None self.texture = None self.obj2world = matrix.Matrix(4) self.matrix = matrix.Matrix(4) # Model matrix self.modelInverseTranspose = matrix.Matrix(4) self.vbos = [] self.cbos = [] self.nbos = [] def addProgram(self, program): self.program = program self.vertLoc = self.program.get_attribute(b'vertexPosition_modelspace') self.normLoc = self.program.get_attribute(b'normal_modelspace') #self.UVLoc = self.program.get_attribute(b'vertexUV') self.colorLoc = self.program.get_attribute(b'vertexColor') self.modelID = self.program.new_uniform(b'model_matrix') self.invModelLoc = self.program.new_uniform(b'gMdVw') def render(self): self.program.set_uniform_matrix(self.modelID, self.matrix) self.program.set_uniform_matrix(self.invModelLoc, self.modelInverseTranspose) i = 0 for key in self.materials: try: bind_object(self.vertLoc, self.vbos[i], 3) bind_object(self.normLoc, self.nbos[i], 3) bind_object(self.colorLoc, self.cbos[i], 3) gl.glDrawArrays(gl.GL_TRIANGLES, 0, len(self.verData[key])) unbind_object(self.colorLoc) unbind_object(self.normLoc) unbind_object(self.vertLoc) i += 1 except KeyError: pass def buffer_objects(self): if self.importedModel: for key in self.materials: try: self.vbos.append(buffer_object(self.verData[key], gl.GLfloat)) self.nbos.append(buffer_object(self.norData[key], gl.GLfloat)) self.cbos.append(buffer_object(self.colData[key], gl.GLfloat)) except KeyError: pass else: self.vbo = buffer_object(self.vertices, gl.GLfloat) self.uvbo = buffer_object(self.texCoord, gl.GLfloat) self.ibo = index_buffer_object(self.triangles, gl.GLuint) class Mesh(MeshBase): def __init__(self): super(Mesh, self).__init__() self.xPos = 0 self.yPos = 0 self.zPos = 0 self.xPosDelta = 0 self.yPosDelta = 0 self.zPosDelta = 0 self._scale = 1 self.scaleDelta = 0 self.verData = {} self.norData = {} self.colData = {} self.rect = None self.nverts = 0 self.ntris = 0 self.vertices = [] self.texCoord = [] self.normals = [] self.colors = [] self.triangles = [] self.materials = {} self.physObj = None self.importedModel = False def setColorAll(self, r, g, b): ''' This will populate the colors array with same color for every vertex. ''' if not self.colors: for i in range(self.nverts): self.colors.append([r, g, b]) else: for i in range(self.nverts): self.colors[i] = [r, g, b] def addMaterial(self, name, material): # Add a material to the mesh self.materials[name] = material def fromData(self, data, normals=None, texCoord=None): ''' This will take in any set of vertices, uv coordinates and colors arrays ''' if isinstance(data, objloader.OBJ): self.importedModel = True self.materials = data.mtlfile.data for key, value in data.fmvnig.items(): # Vertices self.verData[key] = value[0] # Normals self.norData[key] = value[2] for key, value in self.materials.items(): try: self.colData[key] = [] for i in range(len(self.verData[key])): self.colData[key].append(value.diffuse) except KeyError: pass else: self.importedModel = False self.vertices = data self.nverts = len(self.vertices) if normals is not None: self.normals = normals if texCoord is not None: self.texCoord = texCoord else: self.texCoord = self.vertices self.buffer_objects() def fromCSG(self, csg): ''' This will take in a CSG object and convert it to mesh for rendering and simulation purposes. ''' indexer = Indexer() polygons = csg.toPolygons() for i in range(len(polygons)): polygon = polygons[i] indices = [] for j in range(len(polygon.vertices)): vertex = polygon.vertices[j] vertex.color = polygon.shared or [1.0, 1.0, 1.0] index = indexer.add(vertex) indices.append(index) for k in range(2, len(indices), 1): self.triangles.append([indices[0], indices[k - 1], indices[k]]) for i in range(len(indexer.unique)): v = indexer.unique[i] self.vertices.append(v.pos.vector) self.normals.append(v.normal.vector) self.colors.append(v.color) # print("Indexer Unique Count: ", len(indexer.unique)) # print("Polygon Count: ", len(polygons)) # print("Triangles Count: ", len(self.triangles)) # print("Vertices Count: ", len(self.vertices)) self.nverts = len(self.vertices) self.ntris = len(self.triangles) self.buffer_objects() def addPhysicsObject(self, physObj): '''This will attach a physics object to the mesh.''' self.physObj = physObj self.rect = physObj.getCollisionModel().getModel() self.vertices = self.rect.getVertices() self.texCoord = self.rect.getVertices() self.matrix = self.rect.getModelMatrix() def scale(self, value): self.scaleDelta = value / self._scale self._scale = value def translate(self, x, y, z): self.xPosDelta += x - self.xPos self.yPosDelta += y - self.yPos self.zPosDelta += z - self.zPos self.xPos = x self.yPos = y self.zPos = z # TODO - Needs to be checked def rotate(self, axis, angle): self.rotationMatrix = matrix.Matrix(4).rotate(axis, angle) self.matrix *= self.rotationMatrix def update(self): if self.physObj is None: pass else: self.rect = self.physObj.getCollisionModel().getModel() self.matrix = self.rect.getModelMatrix() if self.scaleDelta: vecScale = vector.Vector( 3, data=[self.scaleDelta, self.scaleDelta, self.scaleDelta]) self.matrix.i_scale(vecScale) self.scaleDelta = 0 if self.xPosDelta or self.yPosDelta or self.zPosDelta: vecTrans = vector.Vector( 3, data=[self.xPosDelta, self.yPosDelta, self.zPosDelta]) #self.matrix.i_translate(vecTrans) self.matrix.i_translate(vecTrans) self.xPosDelta = 0 self.yPosDelta = 0 self.zPosDelta = 0 temp4x4 = self.matrix.inverse().transpose() self.modelInverseTranspose = convertM4to3(temp4x4.matrix)
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UNET_EM_DATASET/UNET_EM_DATASET_TERNARY/utility.py
hossein1387/U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation
69
34244
../UNET_EM_DATASET_BASE/utility.py
[ 1, 29772, 3904, 2544, 29918, 12665, 29918, 25832, 8127, 29911, 29918, 25416, 29914, 329, 1793, 29889, 2272, 2 ]
jax_meta/datasets/transforms/functional.py
tristandeleu/jax-meta-learning
5
189350
import numpy as np from numpy.random import default_rng def random_crop(data, size, padding, rng=default_rng()): x = rng.integers(2 * padding, size=data.shape[:-3] + (1, 1, 1)) y = rng.integers(2 * padding, size=data.shape[:-3] + (1, 1, 1)) arange = np.arange(size) rows = x + arange.reshape((size, 1, 1)) cols = y + arange.reshape((1, size, 1)) padding = (padding, padding) data = np.pad(data, ((0, 0),) * (data.ndim - 3) + (padding, padding, (0, 0))) data = np.take_along_axis(data, rows, axis=-3) data = np.take_along_axis(data, cols, axis=-2) return data def random_horizontal_flip(data, rng=default_rng()): to_flip = (rng.random(size=data.shape[:-3]) < 0.5) data[to_flip] = np.flip(data[to_flip], axis=-2) return data def normalize(data, mean, std): data -= mean data /= std return data def _blend(img1, img2, ratio): ratio = ratio.reshape((-1,) + (1,) * (img1.ndim - 1)) img1 *= ratio img1 += (1. - ratio) * img2 img1 = np.clip(img1, 0., 1., out=img1) return img1 def rgb_to_grayscale(data): col = np.array([0.2989, 0.587, 0.114], dtype=data.dtype) return np.expand_dims(data.dot(col), axis=-1) def adjust_brightness(data, factor): return _blend(data, np.zeros_like(data), factor) def adjust_saturation(data, factor): gray = rgb_to_grayscale(data) return _blend(data, gray, factor) def adjust_contrast(data, factor): mean_gray = np.mean(rgb_to_grayscale(data), axis=(-3, -2, -1), keepdims=True) return _blend(data, mean_gray, factor) def color_jitter(data, brightness, contrast, saturation, rng=default_rng()): order = np.argsort(rng.random(size=(3,) + data.shape[:-3]), axis=0) brightness = rng.uniform(1. - brightness, 1. + brightness, size=data.shape[:-3]) contrast = rng.uniform(1. - contrast, 1. + contrast, size=data.shape[:-3]) saturation = rng.uniform(1. - saturation, 1. + saturation, size=data.shape[:-3]) for transform in order: data[transform == 0] = adjust_brightness(data[transform == 0], brightness[transform == 0]) data[transform == 1] = adjust_contrast(data[transform == 1], contrast[transform == 1]) data[transform == 2] = adjust_saturation(data[transform == 2], saturation[transform == 2]) return data
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initGame.py
Sabsterrexx/PingPongGame
0
33010
#Import required Modules: import pygame import constants from paddle import Paddle from ball import Ball from score import Score from text import Text from screenState import ScreenState #This function basically executes everything in the "screenState" module's class def init(): #Initialize all the constants: screen = constants.initialize() #Making the FPS clock: clock = pygame.time.Clock() FPS = 60 #Creating paddle 1 score: paddle1Score = Score(screen) paddle1Score.x = 100 #Creating paddle 2 score: paddle2Score = Score(screen) paddle2Score.color = constants.colors["RED"] #Making 2 paddles: paddle1 = Paddle() paddle1.x = 10 paddle1.color = constants.colors["BLUE"] paddle2 = Paddle() paddle2.x = 780 paddle2.color = constants.colors["RED"] # Making the ball: ball = Ball() ball.dx = ball.speed ball.dy = ball.speed #The ball starts at the center: ball.x = constants.cx ball.y = constants.cy #The ball's intital color is blue ball.color = constants.colors["PURPLE"] #Creating the title screen's text: title_text = Text(screen) title_text.text = "Welcome to Saabit Pong Game. Difficulty keys: Easy: 1, Medium: 2, Hard: 3" #Creating the end game screen's text endScreen_text = Text(screen) endScreen_text.text = "Game Over. Press 'P' to play again" return ScreenState(screen, title_text, endScreen_text, paddle1, paddle2, ball, paddle1Score, paddle2Score, clock, FPS)
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utils/model_trainer.py
heroclass728/alpr_egyptian
0
142750
<filename>utils/model_trainer.py from darkflow.net.build import TFNet if __name__ == '__main__': options = {"model": "/media/mensa/Data/Task/EgyALPR/darkflow/cfg/yolo.cfg", "load": "/media/mensa/Data/Task/EgyALPR/darkflow/bin/yolo.weights", "batch": 8, "epoch": 100, "gpu": 0.9, "train": True, "annotation": "/media/mensa/Data/Task/EgyALPR/training_dataset/xml", "dataset": "/media/mensa/Data/Task/EgyALPR/training_dataset/images"} tf_net = TFNet(options) tf_net.train() tf_net.savepb()
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src/utils/colors.py
ShounoLab/res-net-interpretation-open
0
180623
import numpy as np def rgb2yuv(r, g, b, mode="ycbcr"): # 8 bit full scale Y Cb Cr Y = [0.299, 0.587, 0.114] U = [-0.169, -0.331, 0.5] V = [0.5, -0.419, -0.081] yuv = np.asarray([Y, U, V]) if mode == "ycbcr": return yuv.dot(np.asarray([r, g, b])) elif mode == "yuv": return yuv.dot(np.asarray([r, g, b])) - np.array([0, 128.0, 128.0]) else: return None def yuv2rgb(y, u, v): r = [1.0, 0.0, 1.402] g = [1.0, -0.344, -0.714] b = [1.0, 1.772, 0.0] rgb = np.asarray([r, g, b]) return rgb.dot(np.asarray([[y, u, v]])) def detectColormode(mode): if mode == "RGB" or mode == "RGBY": return "rgb" elif mode == "YUV" or mode == "YCbYr": return "yuv" else: raise ValueError("Unknow color mode: {}".format(mode))
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src/opencmiss/neon/ui/misc/utils.py
hsorby/neon
0
186953
<gh_stars>0 ''' Copyright 2015 University of Auckland 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 functools import wraps from PySide import QtCore, QtGui def set_wait_cursor(f): """ Decorator to a gui action method (e.g. methods in QtGui.QWidget) to set and unset a wait cursor and unset after the method is finished. """ @wraps(f) def do_wait_cursor(*a, **kw): try: QtGui.QApplication.setOverrideCursor(QtCore.Qt.WaitCursor) return f(*a, **kw) finally: # Always unset QtGui.QApplication.restoreOverrideCursor() return do_wait_cursor
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local/models.py
rodrigondec/Open_CliEng
3
124113
<gh_stars>1-10 from django.db import models # Create your models here. class Predio(models.Model): nome = models.CharField(max_length=200) descricao = models.TextField(max_length=200, null=True) def __str__(self): return self.nome class Setor(models.Model): predio = models.ForeignKey(Predio, on_delete=models.CASCADE) nome = models.CharField(max_length=200) def __str__(self): return self.nome
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tests/test_data.py
prabhathur/CF
0
152544
<filename>tests/test_data.py import pytest import dice_ml from dice_ml.utils import helpers def test_data_initiation(public_data_object, private_data_object): assert isinstance(public_data_object, dice_ml.data_interfaces.public_data_interface.PublicData), "the given parameters should instantiate PublicData class" assert isinstance(private_data_object, dice_ml.data_interfaces.private_data_interface.PrivateData), "the given parameters should instantiate PrivateData class" class TestCommonDataMethods: """ Test methods common to Public and Private data interfaces modules. """ @pytest.fixture(autouse=True) def _get_data_object(self, public_data_object, private_data_object): self.d = [public_data_object, private_data_object] def test_get_valid_mads(self): # public data for normalized in [True, False]: mads = self.d[0].get_valid_mads(normalized=normalized, display_warnings=False, return_mads=True) assert all(mads[feature] > 0 for feature in mads) # mads denotes variability in features and should be positive for DiCE. if normalized: min_value = 0 max_value = 1 errors = 0 for feature in mads: if not normalized: min_value = self.d[0].train_df[feature].min() max_value = self.d[0].train_df[feature].max() if mads[feature] > max_value - min_value: errors += 1 assert errors==0 # mads can't be larger than the feature range # private data for normalized in [True, False]: mads = self.d[1].get_valid_mads(normalized=normalized, display_warnings=False, return_mads=True) assert all(mads[feature] == 1 for feature in mads) # no mad is provided for private data by default, so a practical alternative is keeping all value at 1. Check get_valid_mads() in data interface classes for more info. @pytest.mark.parametrize( "encode_categorical, output_query", [(False, [0.068, 'Private', 'HS-grad', 'Single', 'Service', 'White', 'Female', 0.449]), (True, [0.068, 0.449, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0])] ) def test_prepare_query_instance(self, sample_adultincome_query, encode_categorical, output_query): """ Tests prepare_query_instance method that covnerts continuous features into [0,1] range and one-hot encodes categorical features. """ for d in self.d: prepared_query = d.prepare_query_instance(query_instance=sample_adultincome_query, encode=encode_categorical).iloc[0].tolist() if encode_categorical: assert output_query == pytest.approx(prepared_query, abs=1e-3) else: for ix, name in enumerate(d.feature_names): if name in d.continuous_feature_names: assert output_query[ix] == pytest.approx(prepared_query[ix], abs=1e-3) else: assert output_query[ix] == prepared_query[ix] def test_encoded_categorical_features(self): """ Tests if correct encoded categorical feature indexes are returned. Should work even when feature names are starting with common names. """ res = [] for d in self.d: d.categorical_feature_names = ['cat1', 'cat2'] d.continuous_feature_names = ['cat2_cont1', 'cont2'] d.encoded_feature_names = ['cat2_cont1', 'cont2', 'cat1_val1', 'cat1_val2', 'cat2_val1', 'cat2_val2'] res.append(d.get_encoded_categorical_feature_indexes()) assert [[2, 3], [4, 5]] == res[0] # 2,3,4,5 are correct indexes of encoded categorical features and the data object's method should not return the first continuous feature that starts with the same name. Returned value should be a list of lists. assert res[0] == res[1] def test_features_to_vary(self): """ Tests if correct indexes of features are returned. Should work even when feature names are starting with common names. """ res = [] for d in self.d: d.categorical_feature_names = ['cat1', 'cat2'] d.encoded_feature_names = ['cat2_cont1', 'cont2', 'cat1_val1', 'cat1_val2', 'cat2_val1', 'cat2_val2'] d.continuous_feature_names = ['cat2_cont1', 'cont2'] res.append(d.get_indexes_of_features_to_vary(features_to_vary=['cat2'])) assert [4, 5] == res[0] # 4,5 are correct indexes of features that can be varied and the data object's method should not return the first continuous feature that starts with the same name. assert res[0] == res[1]
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tensor2tensor/trax/rlax/ppo.py
funtion/tensor2tensor
1
4859
# coding=utf-8 # Copyright 2019 The Tensor2Tensor Authors. # # 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. """PPO in JAX. Notation: B, scalar - batch size T, scalar - number of time-steps in a trajectory, or the value of the padded time-step dimension. OBS, tuple - shape of a singular observation from the environment. Ex: For CartPole-v0 this is (4,) and Pong-v0 it's (210, 160, 3) A, scalar - Number of actions, assuming a discrete space. Policy and Value function signatures: Policy Function :: [B, T] + OBS -> [B, T, A] Value Function :: [B, T] + OBS -> [B, T, 1] Policy and Value Function :: [B, T] + OBS -> ([B, T, A], [B, T, 1]) i.e. the policy net should take a batch of *trajectories* and at each time-step in each batch deliver a probability distribution over actions. NOTE: It doesn't return logits, rather the expectation is that it returns log-probabilities instead. NOTE: The policy and value functions need to take care to not take into account future time-steps while deciding the actions (or value) for the current time-step. Policy and Value Function produces a tuple of the expected output of a policy function and a value function. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import functools import os import pickle import time from absl import logging import gym from jax import grad from jax import jit from jax import lax from jax import numpy as np from jax import random as jax_random import numpy as onp from tensor2tensor.envs import env_problem from tensor2tensor.envs import env_problem_utils from tensor2tensor.trax import jaxboard from tensor2tensor.trax import layers from tensor2tensor.trax import optimizers as trax_opt from tensor2tensor.trax import trax from tensorflow.io import gfile DEBUG_LOGGING = False GAMMA = 0.99 LAMBDA = 0.95 EPSILON = 0.1 EPOCHS = 50 # 100 NUM_OPTIMIZER_STEPS = 100 PRINT_EVERY_OPTIMIZER_STEP = 20 BATCH_TRAJECTORIES = 32 def policy_and_value_net(rng_key, batch_observations_shape, num_actions, bottom_layers_fn=None, two_towers=True): """A policy and value net function.""" # Layers. # Now, with the current logits, one head computes action probabilities and the # other computes the value function. # NOTE: The LogSoftmax instead of the Softmax because of numerical stability. net = None if not two_towers: tower = [] if bottom_layers_fn is None else bottom_layers_fn() tower.extend([ layers.Branch( layers.Serial(layers.Dense(num_actions), layers.LogSoftmax()), layers.Dense(1)) ]) net = layers.Serial(*tower) else: tower1 = [] if bottom_layers_fn is None else bottom_layers_fn() tower2 = [] if bottom_layers_fn is None else bottom_layers_fn() tower1.extend([layers.Dense(num_actions), layers.LogSoftmax()]) tower2.extend([layers.Dense(1)]) net = layers.Branch( layers.Serial(*tower1), layers.Serial(*tower2), ) assert net return net.initialize(batch_observations_shape, rng_key), net def optimizer_fun(net_params, step_size=1e-3): opt = trax_opt.Adam(step_size=step_size, b1=0.9, b2=0.999, eps=1e-08) opt_init = lambda x: (x, opt.tree_init(x)) opt_update = lambda i, g, s: opt.tree_update(i, g, s[0], s[1]) get_params = lambda x: x[0] opt_state = opt_init(net_params) return opt_state, opt_update, get_params # Should this be collect 'n' trajectories, or # Run the env for 'n' steps and take completed trajectories, or # Any other option? # TODO(afrozm): Replace this with EnvProblem? def collect_trajectories(env, policy_fun, num_trajectories=1, policy=env_problem_utils.CATEGORICAL_SAMPLING, max_timestep=None, boundary=20, epsilon=0.1, reset=True, rng=None): """Collect trajectories with the given policy net and behaviour. Args: env: A gym env interface, for now this is not-batched. policy_fun: observations(B,T+1) -> log-probabs(B,T+1, A) callable. num_trajectories: int, number of trajectories. policy: string, "greedy", "epsilon-greedy", or "categorical-sampling" i.e. how to use the policy_fun to return an action. max_timestep: int or None, the index of the maximum time-step at which we return the trajectory, None for ending a trajectory only when env returns done. boundary: int, boundary for padding, used in EnvProblem envs. epsilon: float, the epsilon for `epsilon-greedy` policy. reset: bool, true if we want to reset the envs. The envs are also reset if max_max_timestep is None or < 0 rng: jax rng, splittable. Returns: A tuple (trajectory, number of trajectories that are done) trajectory: list of (observation, action, reward) tuples, where each element `i` is a tuple of numpy arrays with shapes as follows: observation[i] = (B, T_i + 1) action[i] = (B, T_i) reward[i] = (B, T_i) """ assert isinstance(env, env_problem.EnvProblem) # This is an env_problem, run its collect function. return env_problem_utils.play_env_problem_with_policy( env, policy_fun, num_trajectories=num_trajectories, max_timestep=max_timestep, boundary=boundary, policy_sampling=policy, eps=epsilon, reset=reset, rng=rng) # This function can probably be simplified, ask how? # Can we do something much simpler than lax.pad, maybe np.pad? # Others? def get_padding_value(dtype): """Returns the padding value given a dtype.""" padding_value = None if dtype == np.uint8: padding_value = np.uint8(0) elif dtype == np.uint16: padding_value = np.uint16(0) elif dtype == np.float32 or dtype == np.float64: padding_value = 0.0 else: padding_value = 0 assert padding_value is not None return padding_value # TODO(afrozm): Use np.pad instead and make jittable? def pad_trajectories(trajectories, boundary=20): """Pad trajectories to a bucket length that is a multiple of boundary. Args: trajectories: list[(observation, actions, rewards)], where each observation is shaped (t+1,) + OBS and actions & rewards are shaped (t,), with the length of the list being B (batch size). boundary: int, bucket length, the actions and rewards are padded to integer multiples of boundary. Returns: tuple: (padding lengths, reward_mask, padded_observations, padded_actions, padded_rewards) where padded_observations is shaped (B, T+1) + OBS and padded_actions, padded_rewards & reward_mask are shaped (B, T). Where T is max(t) rounded up to an integer multiple of boundary. padded_length is how much padding we've added and reward_mask is 1s for actual rewards and 0s for the padding. """ # Let's compute max(t) over all trajectories. t_max = max(r.shape[0] for (_, _, r) in trajectories) # t_max is rounded to the next multiple of `boundary` boundary = int(boundary) bucket_length = boundary * int(np.ceil(float(t_max) / boundary)) # So all obs will be padded to t_max + 1 and actions and rewards to t_max. padded_observations = [] padded_actions = [] padded_rewards = [] padded_lengths = [] reward_masks = [] for (o, a, r) in trajectories: # Determine the amount to pad, this holds true for obs, actions and rewards. num_to_pad = bucket_length + 1 - o.shape[0] padded_lengths.append(num_to_pad) if num_to_pad == 0: padded_observations.append(o) padded_actions.append(a) padded_rewards.append(r) reward_masks.append(onp.ones_like(r, dtype=np.int32)) continue # First pad observations. padding_config = [(0, num_to_pad, 0)] for _ in range(o.ndim - 1): padding_config.append((0, 0, 0)) padding_config = tuple(padding_config) padding_value = get_padding_value(o.dtype) action_padding_value = get_padding_value(a.dtype) reward_padding_value = get_padding_value(r.dtype) padded_obs = lax.pad(o, padding_value, padding_config) padded_observations.append(padded_obs) # Now pad actions and rewards. assert a.ndim == 1 and r.ndim == 1 padding_config = ((0, num_to_pad, 0),) padded_action = lax.pad(a, action_padding_value, padding_config) padded_actions.append(padded_action) padded_reward = lax.pad(r, reward_padding_value, padding_config) padded_rewards.append(padded_reward) # Also create the mask to use later. reward_mask = onp.ones_like(r, dtype=np.int32) reward_masks.append(lax.pad(reward_mask, 0, padding_config)) return padded_lengths, np.stack(reward_masks), np.stack( padded_observations), np.stack(padded_actions), np.stack(padded_rewards) # TODO(afrozm): JAX-ify this, this is too slow for pong. def rewards_to_go(rewards, mask, gamma=0.99): r"""Computes rewards to go. Reward to go is defined as follows, the discounted reward that we have to yet collect, going forward from this point, i.e.: r2g_t = \sum_{l=0}^{\infty} (\gamma^{l} * reward_{t+l}) Args: rewards: np.ndarray of shape (B, T) of rewards. mask: np.ndarray of shape (B, T) of mask for the rewards. gamma: float, discount factor. Returns: rewards to go, np.ndarray of shape (B, T). """ B, T = rewards.shape # pylint: disable=invalid-name,unused-variable masked_rewards = rewards * mask # (B, T) # We use the following recurrence relation, derived from the equation above: # # r2g[t+1] = (r2g[t] - r[t]) / gamma # # This means we'll need to calculate r2g[0] first and then r2g[1] and so on .. # # **However** this leads to overflows for long sequences: r2g[t] - r[t] > 0 # and gamma < 1.0, so the division keeps increasing. # # So we just run the recurrence in reverse, i.e. # # r2g[t] = r[t] + (gamma*r2g[t+1]) # # This is much better, but might have lost updates since the (small) rewards # at earlier time-steps may get added to a (very?) large sum. # Compute r2g_{T-1} at the start and then compute backwards in time. r2gs = [masked_rewards[:, -1]] # Go from T-2 down to 0. for t in reversed(range(T - 1)): r2gs.append(masked_rewards[:, t] + (gamma * r2gs[-1])) # The list should have length T. assert T == len(r2gs) # First we stack them in the correct way to make it (B, T), but these are # still from newest (T-1) to oldest (0), so then we flip it on time axis. return np.flip(np.stack(r2gs, axis=1), axis=1) @jit def value_loss_given_predictions(value_prediction, rewards, reward_mask, gamma=0.99, epsilon=0.2, value_prediction_old=None): """Computes the value loss given the prediction of the value function. Args: value_prediction: np.ndarray of shape (B, T+1, 1) rewards: np.ndarray of shape (B, T) of rewards. reward_mask: np.ndarray of shape (B, T), the mask over rewards. gamma: float, discount factor. epsilon: float, clip-fraction, used if value_value_prediction_old isn't None value_prediction_old: np.ndarray of shape (B, T+1, 1) of value predictions using the old parameters. If provided, we incorporate this in the loss as well. This is from the OpenAI baselines implementation. Returns: The average L2 value loss, averaged over instances where reward_mask is 1. """ B, T = rewards.shape # pylint: disable=invalid-name assert (B, T) == reward_mask.shape assert (B, T + 1, 1) == value_prediction.shape value_prediction = np.squeeze(value_prediction, axis=2) # (B, T+1) value_prediction = value_prediction[:, :-1] * reward_mask # (B, T) r2g = rewards_to_go(rewards, reward_mask, gamma=gamma) # (B, T) loss = (value_prediction - r2g)**2 # From the baselines implementation. if value_prediction_old is not None: value_prediction_old = np.squeeze(value_prediction_old, axis=2) # (B, T+1) value_prediction_old = value_prediction_old[:, :-1] * reward_mask # (B, T) v_clipped = value_prediction_old + np.clip( value_prediction - value_prediction_old, -epsilon, epsilon) v_clipped_loss = (v_clipped - r2g)**2 loss = np.maximum(v_clipped_loss, loss) # Take an average on only the points where mask != 0. return np.sum(loss) / np.sum(reward_mask) # TODO(afrozm): JAX-ify this, this is too slow for pong. def deltas(predicted_values, rewards, mask, gamma=0.99): r"""Computes TD-residuals from V(s) and rewards. Where a `delta`, i.e. a td-residual is defined as: delta_{b,t} = r_{b,t} + \gamma * v_{b,t+1} - v_{b,t}. Args: predicted_values: ndarray of shape (B, T+1). NOTE: Expects axis 2 was squeezed. These represent V(s_bt) for b < B and t < T+1 rewards: ndarray of shape (B, T) of rewards. mask: ndarray of shape (B, T) of mask for rewards. gamma: float, discount factor. Returns: ndarray of shape (B, T) of one-step TD-residuals. """ # `d`s are basically one-step TD residuals. d = [] _, T = rewards.shape # pylint: disable=invalid-name for t in range(T): d.append(rewards[:, t] + (gamma * predicted_values[:, t + 1]) - predicted_values[:, t]) return np.array(d).T * mask def gae_advantages(td_deltas, mask, lambda_=0.95, gamma=0.99): r"""Computes the GAE advantages given the one step TD-residuals. The formula for a GAE advantage estimator is as follows: A_{bt} = \sum_{l=0}^{\infty}(\gamma * \lambda)^{l}(\delta_{b,t+l}). Internally we just call rewards_to_go, since it is the same computation. Args: td_deltas: np.ndarray of shape (B, T) of one step TD-residuals. mask: np.ndarray of shape (B, T) of mask for the residuals. It maybe the case that the `td_deltas` are already masked correctly since they are produced by `deltas(...)` lambda_: float, lambda parameter for GAE estimators. gamma: float, lambda parameter for GAE estimators. Returns: GAE advantage estimates. """ return rewards_to_go(td_deltas, mask, lambda_ * gamma) def chosen_probabs(probab_observations, actions): """Picks out the probabilities of the actions along batch and time-steps. Args: probab_observations: ndarray of shape `[B, T+1, A]`, where probab_observations[b, t, i] contains the log-probability of action = i at the t^th time-step in the b^th trajectory. actions: ndarray of shape `[B, T]`, with each entry in [0, A) denoting which action was chosen in the b^th trajectory's t^th time-step. Returns: `[B, T]` ndarray with the log-probabilities of the chosen actions. """ B, T = actions.shape # pylint: disable=invalid-name assert (B, T + 1) == probab_observations.shape[:2] return probab_observations[np.arange(B)[:, None], np.arange(T), actions] def compute_probab_ratios(p_new, p_old, actions, reward_mask): """Computes the probability ratios for each time-step in a trajectory. Args: p_new: ndarray of shape [B, T+1, A] of the log-probabilities that the policy network assigns to all the actions at each time-step in each batch using the old parameters. p_old: ndarray of shape [B, T+1, A], same as above, but using old policy network parameters. actions: ndarray of shape [B, T] where each element is from [0, A). reward_mask: ndarray of shape [B, T] masking over probabilities. Returns: probab_ratios: ndarray of shape [B, T], where probab_ratios_{b,t} = p_new_{b,t,action_{b,t}} / p_old_{b,t,action_{b,t}} """ B, T = actions.shape # pylint: disable=invalid-name assert (B, T + 1) == p_old.shape[:2] assert (B, T + 1) == p_new.shape[:2] logp_old = chosen_probabs(p_old, actions) logp_new = chosen_probabs(p_new, actions) assert (B, T) == logp_old.shape assert (B, T) == logp_new.shape # Since these are log-probabilities, we just subtract them. probab_ratios = np.exp(logp_new - logp_old) * reward_mask assert (B, T) == probab_ratios.shape return probab_ratios def clipped_probab_ratios(probab_ratios, epsilon=0.2): return np.clip(probab_ratios, 1 - epsilon, 1 + epsilon) def clipped_objective(probab_ratios, advantages, reward_mask, epsilon=0.2): return np.minimum( probab_ratios * advantages, clipped_probab_ratios(probab_ratios, epsilon=epsilon) * advantages) * reward_mask @jit def ppo_loss_given_predictions(log_probab_actions_new, log_probab_actions_old, value_predictions_old, padded_actions, padded_rewards, reward_mask, gamma=0.99, lambda_=0.95, epsilon=0.2): """PPO objective, with an eventual minus sign, given predictions.""" B, T = padded_rewards.shape # pylint: disable=invalid-name assert (B, T) == padded_actions.shape assert (B, T) == reward_mask.shape _, _, A = log_probab_actions_old.shape # pylint: disable=invalid-name assert (B, T + 1, 1) == value_predictions_old.shape assert (B, T + 1, A) == log_probab_actions_old.shape assert (B, T + 1, A) == log_probab_actions_new.shape # (B, T) td_deltas = deltas( np.squeeze(value_predictions_old, axis=2), # (B, T+1) padded_rewards, reward_mask, gamma=gamma) # (B, T) advantages = gae_advantages( td_deltas, reward_mask, lambda_=lambda_, gamma=gamma) # Normalize the advantages. advantages = (advantages - np.mean(advantages)) / np.std(advantages) # (B, T) ratios = compute_probab_ratios(log_probab_actions_new, log_probab_actions_old, padded_actions, reward_mask) assert (B, T) == ratios.shape # (B, T) objective = clipped_objective( ratios, advantages, reward_mask, epsilon=epsilon) assert (B, T) == objective.shape # () average_objective = np.sum(objective) / np.sum(reward_mask) # Loss is negative objective. return -average_objective @jit def combined_loss_given_predictions(log_probab_actions_new, log_probab_actions_old, value_prediction_new, value_prediction_old, padded_actions, padded_rewards, reward_mask, gamma=0.99, lambda_=0.95, epsilon=0.2, c1=1.0, c2=0.01): """Computes the combined (clipped loss + value loss) given predictions.""" loss_value = value_loss_given_predictions( value_prediction_new, padded_rewards, reward_mask, gamma=gamma, value_prediction_old=value_prediction_old, epsilon=epsilon) loss_ppo = ppo_loss_given_predictions( log_probab_actions_new, log_probab_actions_old, value_prediction_old, padded_actions, padded_rewards, reward_mask, gamma=gamma, lambda_=lambda_, epsilon=epsilon) entropy_bonus = masked_entropy(log_probab_actions_new, reward_mask) return (loss_ppo + (c1 * loss_value) - (c2 * entropy_bonus), loss_ppo, loss_value, entropy_bonus) @functools.partial(jit, static_argnums=(3,)) def combined_loss(new_params, log_probab_actions_old, value_predictions_old, policy_and_value_net_apply, padded_observations, padded_actions, padded_rewards, reward_mask, gamma=0.99, lambda_=0.95, epsilon=0.2, c1=1.0, c2=0.01, rng=None): """Computes the combined (clipped loss + value loss) given observations.""" log_probab_actions_new, value_predictions_new = policy_and_value_net_apply( padded_observations, new_params, rng=rng) # (combined_loss, ppo_loss, value_loss, entropy_bonus) return combined_loss_given_predictions( log_probab_actions_new, log_probab_actions_old, value_predictions_new, value_predictions_old, padded_actions, padded_rewards, reward_mask, gamma=gamma, lambda_=lambda_, epsilon=epsilon, c1=c1, c2=c2) @functools.partial(jit, static_argnums=(2, 3, 4)) def policy_and_value_opt_step(i, opt_state, opt_update, get_params, policy_and_value_net_apply, log_probab_actions_old, value_predictions_old, padded_observations, padded_actions, padded_rewards, reward_mask, c1=1.0, c2=0.01, gamma=0.99, lambda_=0.95, epsilon=0.1, rng=None): """Policy and Value optimizer step.""" # Combined loss function given the new params. def policy_and_value_loss(params): """Returns the combined loss given just parameters.""" (loss, _, _, _) = combined_loss( params, log_probab_actions_old, value_predictions_old, policy_and_value_net_apply, padded_observations, padded_actions, padded_rewards, reward_mask, c1=c1, c2=c2, gamma=gamma, lambda_=lambda_, epsilon=epsilon, rng=rng) return loss new_params = get_params(opt_state) g = grad(policy_and_value_loss)(new_params) # TODO(afrozm): Maybe clip gradients? return opt_update(i, g, opt_state) def get_time(t1, t2=None): if t2 is None: t2 = time.time() return round((t2 - t1) * 1000, 2) def approximate_kl(log_prob_new, log_prob_old, mask): """Computes the approximate KL divergence between the old and new log-probs. Args: log_prob_new: (B, T+1, A) log probs new log_prob_old: (B, T+1, A) log probs old mask: (B, T) Returns: Approximate KL. """ diff = log_prob_old - log_prob_new # Cut the last time-step out. diff = diff[:, :-1] # Mask out the irrelevant part. diff *= mask[:, :, np.newaxis] # make mask (B, T, 1) # Average on non-masked part. return np.sum(diff) / np.sum(mask) def masked_entropy(log_probs, mask): """Computes the entropy for the given log-probs. Args: log_probs: (B, T+1, A) log probs mask: (B, T) mask. Returns: Entropy. """ # Cut the last time-step out. lp = log_probs[:, :-1] # Mask out the irrelevant part. lp *= mask[:, :, np.newaxis] # make mask (B, T, 1) p = np.exp(lp) * mask[:, :, np.newaxis] # (B, T, 1) # Average on non-masked part and take negative. return -(np.sum(lp * p) / np.sum(mask)) def evaluate_policy(eval_env, get_predictions, boundary, max_timestep=20000, rng=None): """Evaluate the policy.""" avg_rewards = {} for policy in [ env_problem_utils.CATEGORICAL_SAMPLING, env_problem_utils.GUMBEL_SAMPLING, env_problem_utils.EPSILON_GREEDY ]: trajs, _ = env_problem_utils.play_env_problem_with_policy( eval_env, get_predictions, boundary=boundary, max_timestep=max_timestep, reset=True, policy_sampling=policy, rng=rng) avg_rewards[policy] = float(sum( np.sum(traj[2]) for traj in trajs)) / len(trajs) return avg_rewards def maybe_restore_params(output_dir, policy_and_value_net_params): """Maybe restore the params from the checkpoint dir. Args: output_dir: Directory where saved model checkpoints are stored. policy_and_value_net_params: Default params, returned if model is'nt found. Returns: triple (restore (bool), params, iter(int)) where iter is the epoch from which we restored the params, 0 is restore = False. """ model_files = gfile.glob(os.path.join(output_dir, "model-??????.pkl")) if not model_files: return False, policy_and_value_net_params, 0 model_file = sorted(model_files)[-1] model_file_basename = os.path.basename(model_file) # model-??????.pkl i = int(filter(str.isdigit, model_file_basename)) with gfile.GFile(model_file, "rb") as f: policy_and_value_net_params = pickle.load(f) return True, policy_and_value_net_params, i def training_loop( env=None, epochs=EPOCHS, policy_and_value_net_fun=None, policy_and_value_optimizer_fun=None, batch_size=BATCH_TRAJECTORIES, num_optimizer_steps=NUM_OPTIMIZER_STEPS, print_every_optimizer_steps=PRINT_EVERY_OPTIMIZER_STEP, target_kl=0.01, boundary=20, max_timestep=None, max_timestep_eval=20000, random_seed=None, gamma=GAMMA, lambda_=LAMBDA, epsilon=EPSILON, c1=1.0, c2=0.01, output_dir=None, eval_every_n=1000, eval_env=None, done_frac_for_policy_save=0.5, enable_early_stopping=True, env_name=None, ): """Runs the training loop for PPO, with fixed policy and value nets.""" assert env assert output_dir assert env_name gfile.makedirs(output_dir) # Create summary writers and history. train_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "train")) timing_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "timing")) eval_sw = jaxboard.SummaryWriter(os.path.join(output_dir, "eval")) train_sw.text("env_name", env_name) timing_sw.text("env_name", env_name) eval_sw.text("env_name", env_name) jax_rng_key = trax.get_random_number_generator_and_set_seed(random_seed) # Batch Observations Shape = [-1, -1] + OBS, because we will eventually call # policy and value networks on shape [B, T] +_OBS batch_observations_shape = (-1, -1) + env.observation_space.shape assert isinstance(env.action_space, gym.spaces.Discrete) num_actions = env.action_space.n jax_rng_key, key1 = jax_random.split(jax_rng_key, num=2) # Initialize the policy and value network. policy_and_value_net_params, policy_and_value_net_apply = ( policy_and_value_net_fun(key1, batch_observations_shape, num_actions)) # Maybe restore the policy params. If there is nothing to restore, then # iteration = 0 and policy_and_value_net_params are returned as is. restore, policy_and_value_net_params, iteration = ( maybe_restore_params(output_dir, policy_and_value_net_params)) if restore: logging.info("Restored parameters from iteration [%d]", iteration) # We should start from the next iteration. iteration += 1 policy_and_value_net_apply = jit(policy_and_value_net_apply) # Initialize the optimizers. policy_and_value_optimizer = ( policy_and_value_optimizer_fun(policy_and_value_net_params)) (policy_and_value_opt_state, policy_and_value_opt_update, policy_and_value_get_params) = policy_and_value_optimizer num_trajectories_done = 0 last_saved_at = 0 logging.info("Starting the PPO training loop.") for i in range(iteration, epochs): epoch_start_time = time.time() # Params we'll use to collect the trajectories. policy_and_value_net_params = policy_and_value_get_params( policy_and_value_opt_state) # A function to get the policy and value predictions. def get_predictions(observations, rng=None): """Returns log-probs, value predictions and key back.""" key, key1 = jax_random.split(rng, num=2) log_probs, value_preds = policy_and_value_net_apply( observations, policy_and_value_net_params, rng=key1) return log_probs, value_preds, key # Evaluate the policy. policy_eval_start_time = time.time() if ((i + 1) % eval_every_n == 0) or (i == epochs - 1): jax_rng_key, key = jax_random.split(jax_rng_key, num=2) logging.vlog(1, "Epoch [% 6d] evaluating policy.", i) avg_reward = evaluate_policy( eval_env, get_predictions, boundary, max_timestep=max_timestep_eval, rng=key) for k, v in avg_reward.items(): eval_sw.scalar("eval/mean_reward/%s" % k, v, step=i) logging.info("Epoch [% 6d] Policy Evaluation [%s] = %10.2f", i, k, v) policy_eval_time = get_time(policy_eval_start_time) trajectory_collection_start_time = time.time() logging.vlog(1, "Epoch [% 6d] collecting trajectories.", i) jax_rng_key, key = jax_random.split(jax_rng_key) trajs, num_done = collect_trajectories( env, policy_fun=get_predictions, num_trajectories=batch_size, max_timestep=max_timestep, boundary=boundary, rng=key, reset=(i == 0) or restore, epsilon=(10.0 / (i + 10.0))) # this is a different epsilon. trajectory_collection_time = get_time(trajectory_collection_start_time) logging.vlog(1, "Collecting trajectories took %0.2f msec.", trajectory_collection_time) avg_reward = float(sum(np.sum(traj[2]) for traj in trajs)) / len(trajs) max_reward = max(np.sum(traj[2]) for traj in trajs) min_reward = min(np.sum(traj[2]) for traj in trajs) train_sw.scalar("train/mean_reward", avg_reward, step=i) logging.vlog(1, "Rewards avg=[%0.2f], max=[%0.2f], min=[%0.2f], all=%s", avg_reward, max_reward, min_reward, [float(np.sum(traj[2])) for traj in trajs]) logging.vlog(1, "Trajectory Length average=[%0.2f], max=[%0.2f], min=[%0.2f]", float(sum(len(traj[0]) for traj in trajs)) / len(trajs), max(len(traj[0]) for traj in trajs), min(len(traj[0]) for traj in trajs)) logging.vlog(2, "Trajectory Lengths: %s", [len(traj[0]) for traj in trajs]) padding_start_time = time.time() (_, reward_mask, padded_observations, padded_actions, padded_rewards) = pad_trajectories( trajs, boundary=boundary) padding_time = get_time(padding_start_time) logging.vlog(1, "Padding trajectories took %0.2f msec.", get_time(padding_start_time)) logging.vlog(1, "Padded Observations' shape [%s]", str(padded_observations.shape)) logging.vlog(1, "Padded Actions' shape [%s]", str(padded_actions.shape)) logging.vlog(1, "Padded Rewards' shape [%s]", str(padded_rewards.shape)) # Calculate log-probabilities and value predictions of the trajectories. # We'll pass these to the loss functions so as to not get recomputed. # NOTE: # There is a slight problem here, if the policy network contains # stochasticity in the log-probabilities (ex: dropout), then calculating # these again here is not going to be correct and should be done in the # collect function. log_prob_recompute_start_time = time.time() jax_rng_key, key = jax_random.split(jax_rng_key) log_probabs_traj, value_predictions_traj, _ = get_predictions( padded_observations, rng=key) log_prob_recompute_time = get_time(log_prob_recompute_start_time) # Some assertions. B, T = padded_actions.shape # pylint: disable=invalid-name assert (B, T) == padded_rewards.shape assert (B, T) == reward_mask.shape assert (B, T + 1) == padded_observations.shape[:2] assert (B, T + 1) + env.observation_space.shape == padded_observations.shape # Linear annealing from 0.1 to 0.0 # epsilon_schedule = epsilon if epochs == 1 else epsilon * (1.0 - # (i / # (epochs - 1))) # Constant epsilon. epsilon_schedule = epsilon # Compute value and ppo losses. jax_rng_key, key1 = jax_random.split(jax_rng_key, num=2) logging.vlog(2, "Starting to compute P&V loss.") loss_compute_start_time = time.time() cur_combined_loss, cur_ppo_loss, cur_value_loss, entropy_bonus = ( combined_loss( policy_and_value_net_params, log_probabs_traj, value_predictions_traj, policy_and_value_net_apply, padded_observations, padded_actions, padded_rewards, reward_mask, gamma=gamma, lambda_=lambda_, epsilon=epsilon_schedule, c1=c1, c2=c2, rng=key1)) loss_compute_time = get_time(loss_compute_start_time) logging.vlog( 1, "Calculating P&V loss [%10.2f(%10.2f, %10.2f, %10.2f)] took %0.2f msec.", cur_combined_loss, cur_value_loss, cur_ppo_loss, entropy_bonus, get_time(loss_compute_start_time)) jax_rng_key, key1 = jax_random.split(jax_rng_key, num=2) logging.vlog(1, "Policy and Value Optimization") optimization_start_time = time.time() keys = jax_random.split(key1, num=num_optimizer_steps) for j in range(num_optimizer_steps): k1, k2, k3 = jax_random.split(keys[j], num=3) t = time.time() # Update the optimizer state. policy_and_value_opt_state = policy_and_value_opt_step( j, policy_and_value_opt_state, policy_and_value_opt_update, policy_and_value_get_params, policy_and_value_net_apply, log_probabs_traj, value_predictions_traj, padded_observations, padded_actions, padded_rewards, reward_mask, c1=c1, c2=c2, gamma=gamma, lambda_=lambda_, epsilon=epsilon_schedule, rng=k1) # Compute the approx KL for early stopping. new_policy_and_value_net_params = policy_and_value_get_params( policy_and_value_opt_state) log_probab_actions_new, _ = policy_and_value_net_apply( padded_observations, new_policy_and_value_net_params, rng=k2) approx_kl = approximate_kl(log_probab_actions_new, log_probabs_traj, reward_mask) early_stopping = enable_early_stopping and approx_kl > 1.5 * target_kl if early_stopping: logging.vlog( 1, "Early stopping policy and value optimization at iter: %d, " "with approx_kl: %0.2f", j, approx_kl) # We don't return right-away, we want the below to execute on the last # iteration. t2 = time.time() if (((j + 1) % print_every_optimizer_steps == 0) or (j == num_optimizer_steps - 1) or early_stopping): # Compute and log the loss. (loss_combined, loss_ppo, loss_value, entropy_bonus) = ( combined_loss( new_policy_and_value_net_params, log_probabs_traj, value_predictions_traj, policy_and_value_net_apply, padded_observations, padded_actions, padded_rewards, reward_mask, gamma=gamma, lambda_=lambda_, epsilon=epsilon_schedule, c1=c1, c2=c2, rng=k3)) logging.vlog(1, "One Policy and Value grad desc took: %0.2f msec", get_time(t, t2)) logging.vlog( 1, "Combined Loss(value, ppo, entropy_bonus) [%10.2f] ->" " [%10.2f(%10.2f,%10.2f,%10.2f)]", cur_combined_loss, loss_combined, loss_value, loss_ppo, entropy_bonus) if early_stopping: break optimization_time = get_time(optimization_start_time) logging.vlog( 1, "Total Combined Loss reduction [%0.2f]%%", (100 * (cur_combined_loss - loss_combined) / np.abs(cur_combined_loss))) # Save parameters every time we see the end of at least a fraction of batch # number of trajectories that are done (not completed -- completed includes # truncated and done). # Also don't save too frequently, enforce a minimum gap. # Or if this is the last iteration. policy_save_start_time = time.time() num_trajectories_done += num_done if (((num_trajectories_done >= done_frac_for_policy_save * batch_size) and (i - last_saved_at > eval_every_n)) or (i == epochs - 1)): logging.vlog(1, "Epoch [% 6d] saving model.", i) params_file = os.path.join(output_dir, "model-%06d.pkl" % i) with gfile.GFile(params_file, "wb") as f: pickle.dump(policy_and_value_net_params, f) # Reset this number. num_trajectories_done = 0 last_saved_at = i policy_save_time = get_time(policy_save_start_time) epoch_time = get_time(epoch_start_time) logging.info( "Epoch [% 6d], Reward[min, max, avg] [%5.2f,%5.2f,%5.2f], Combined" " Loss(value, ppo, entropy) [%2.5f(%2.5f,%2.5f,%2.5f)]", i, min_reward, max_reward, avg_reward, loss_combined, loss_value, loss_ppo, entropy_bonus) timing_dict = { "epoch": epoch_time, "policy_eval": policy_eval_time, "trajectory_collection": trajectory_collection_time, "padding": padding_time, "log_prob_recompute": log_prob_recompute_time, "loss_compute": loss_compute_time, "optimization": optimization_time, "policy_save": policy_save_time, } for k, v in timing_dict.items(): timing_sw.scalar("timing/%s" % k, v, step=i) max_key_len = max(len(k) for k in timing_dict) timing_info_list = [ "%s : % 10.2f" % (k.rjust(max_key_len + 1), v) for k, v in sorted(timing_dict.items()) ] logging.info("Epoch [% 6d], Timings: \n%s", i, "\n".join(timing_info_list)) # Reset restore. restore = False # Flush summary writers once in a while. if (i+1) % 1000 == 0 or i == epochs - 1: train_sw.flush() timing_sw.flush() eval_sw.flush()
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google/appengine/tools/devappserver2/http_runtime.py
airamrguez/appengine-1.8.0-golang-1.4.3-os-x-64bit
1
198422
<gh_stars>1-10 #!/usr/bin/env python # # Copyright 2007 Google Inc. # # 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. # """Serves content for "script" handlers using an HTTP runtime. http_runtime supports two ways to start the runtime instance. START_PROCESS sends the runtime_config protobuf (serialized and base64 encoded as not all platforms support binary data over stdin) to the runtime instance over stdin and requires the runtime instance to send the port it is listening on over stdout. START_PROCESS_FILE creates two temporary files and adds the paths of both files to the runtime instance command line. The first file is written by http_runtime with the runtime_config proto (serialized); the runtime instance is expected to delete the file after reading it. The second file is written by the runtime instance with the port it is listening on (the line must be newline terminated); http_runtime is expected to delete the file after reading it. TODO: convert all runtimes to START_PROCESS_FILE. """ import base64 import contextlib import httplib import logging import os import socket import subprocess import sys import time import threading import urllib import wsgiref.headers from google.appengine.tools.devappserver2 import http_runtime_constants from google.appengine.tools.devappserver2 import instance from google.appengine.tools.devappserver2 import login from google.appengine.tools.devappserver2 import safe_subprocess from google.appengine.tools.devappserver2 import tee from google.appengine.tools.devappserver2 import util START_PROCESS = -1 START_PROCESS_FILE = -2 def _sleep_between_retries(attempt, max_attempts, sleep_base): """Sleep between retry attempts. Do an exponential backoff between retry attempts on an operation. The general pattern for use is: for attempt in range(max_attempts): # Try operation, either return or break on success _sleep_between_retries(attempt, max_attempts, sleep_base) Args: attempt: Which attempt just failed (0 based). max_attempts: The maximum number of attempts that will be made. sleep_base: How long in seconds to sleep between the first and second attempt (the time will be doubled between each successive attempt). The value may be any numeric type that is convertible to float (complex won't work but user types that are sufficiently numeric-like will). """ # Don't sleep after the last attempt as we're about to give up. if attempt < (max_attempts - 1): time.sleep((2 ** attempt) * sleep_base) def _remove_retry_sharing_violation(path, max_attempts=10, sleep_base=.125): """Removes a file (with retries on Windows for sharing violations). Args: path: The filesystem path to remove. max_attempts: The maximum number of attempts to try to remove the path before giving up. sleep_base: How long in seconds to sleep between the first and second attempt (the time will be doubled between each successive attempt). The value may be any numeric type that is convertible to float (complex won't work but user types that are sufficiently numeric-like will). Raises: WindowsError: When an error other than a sharing violation occurs. """ if sys.platform == 'win32': for attempt in range(max_attempts): try: os.remove(path) break except WindowsError as e: import winerror # Sharing violations are expected to occasionally occur when the runtime # instance is context swapped after writing the port but before closing # the file. Ignore these and try again. if e.winerror != winerror.ERROR_SHARING_VIOLATION: raise _sleep_between_retries(attempt, max_attempts, sleep_base) else: logging.warn('Unable to delete %s', path) else: os.remove(path) class HttpRuntimeProxy(instance.RuntimeProxy): """Manages a runtime subprocess used to handle dynamic content.""" _VALID_START_PROCESS_FLAVORS = [START_PROCESS, START_PROCESS_FILE] def __init__(self, args, runtime_config_getter, module_configuration, env=None, start_process_flavor=START_PROCESS): """Initializer for HttpRuntimeProxy. Args: args: Arguments to use to start the runtime subprocess. runtime_config_getter: A function that can be called without arguments and returns the runtime_config_pb2.Config containing the configuration for the runtime. module_configuration: An application_configuration.ModuleConfiguration instance respresenting the configuration of the module that owns the runtime. env: A dict of environment variables to pass to the runtime subprocess. start_process_flavor: Which version of start process to start your runtime process. SUpported flavors are START_PROCESS and START_PROCESS_FILE. Raises: ValueError: An unknown value for start_process_flavor was used. """ super(HttpRuntimeProxy, self).__init__() self._host = 'localhost' self._port = None self._process = None self._process_lock = threading.Lock() # Lock to guard self._process. self._prior_error = None self._stderr_tee = None self._runtime_config_getter = runtime_config_getter self._args = args self._module_configuration = module_configuration self._env = env if start_process_flavor not in self._VALID_START_PROCESS_FLAVORS: raise ValueError('Invalid start_process_flavor.') self._start_process_flavor = start_process_flavor def _get_error_file(self): for error_handler in self._module_configuration.error_handlers or []: if not error_handler.error_code or error_handler.error_code == 'default': return os.path.join(self._module_configuration.application_root, error_handler.file) else: return None def handle(self, environ, start_response, url_map, match, request_id, request_type): """Serves this request by forwarding it to the runtime process. Args: environ: An environ dict for the request as defined in PEP-333. start_response: A function with semantics defined in PEP-333. url_map: An appinfo.URLMap instance containing the configuration for the handler matching this request. match: A re.MatchObject containing the result of the matched URL pattern. request_id: A unique string id associated with the request. request_type: The type of the request. See instance.*_REQUEST module constants. Yields: A sequence of strings containing the body of the HTTP response. """ if self._prior_error: yield self._handle_error(self._prior_error, start_response) return environ[http_runtime_constants.SCRIPT_HEADER] = match.expand(url_map.script) if request_type == instance.BACKGROUND_REQUEST: environ[http_runtime_constants.REQUEST_TYPE_HEADER] = 'background' elif request_type == instance.SHUTDOWN_REQUEST: environ[http_runtime_constants.REQUEST_TYPE_HEADER] = 'shutdown' elif request_type == instance.INTERACTIVE_REQUEST: environ[http_runtime_constants.REQUEST_TYPE_HEADER] = 'interactive' for name in http_runtime_constants.ENVIRONS_TO_PROPAGATE: if http_runtime_constants.INTERNAL_ENVIRON_PREFIX + name not in environ: value = environ.get(name, None) if value is not None: environ[ http_runtime_constants.INTERNAL_ENVIRON_PREFIX + name] = value headers = util.get_headers_from_environ(environ) if environ.get('QUERY_STRING'): url = '%s?%s' % (urllib.quote(environ['PATH_INFO']), environ['QUERY_STRING']) else: url = urllib.quote(environ['PATH_INFO']) if 'CONTENT_LENGTH' in environ: headers['CONTENT-LENGTH'] = environ['CONTENT_LENGTH'] data = environ['wsgi.input'].read(int(environ['CONTENT_LENGTH'])) else: data = '' cookies = environ.get('HTTP_COOKIE') user_email, admin, user_id = login.get_user_info(cookies) if user_email: nickname, organization = user_email.split('@', 1) else: nickname = '' organization = '' headers[http_runtime_constants.REQUEST_ID_HEADER] = request_id headers[http_runtime_constants.INTERNAL_HEADER_PREFIX + 'User-Id'] = ( user_id) headers[http_runtime_constants.INTERNAL_HEADER_PREFIX + 'User-Email'] = ( user_email) headers[ http_runtime_constants.INTERNAL_HEADER_PREFIX + 'User-Is-Admin'] = ( str(int(admin))) headers[ http_runtime_constants.INTERNAL_HEADER_PREFIX + 'User-Nickname'] = ( nickname) headers[ http_runtime_constants.INTERNAL_HEADER_PREFIX + 'User-Organization'] = ( organization) headers['X-AppEngine-Country'] = 'ZZ' connection = httplib.HTTPConnection(self._host, self._port) with contextlib.closing(connection): try: connection.connect() connection.request(environ.get('REQUEST_METHOD', 'GET'), url, data, dict(headers.items())) try: response = connection.getresponse() except httplib.HTTPException as e: # The runtime process has written a bad HTTP response. For example, # a Go runtime process may have crashed in app-specific code. yield self._handle_error( 'the runtime process gave a bad HTTP response: %s' % e, start_response) return # Ensures that we avoid merging repeat headers into a single header, # allowing use of multiple Set-Cookie headers. headers = [] for name in response.msg: for value in response.msg.getheaders(name): headers.append((name, value)) response_headers = wsgiref.headers.Headers(headers) error_file = self._get_error_file() if (error_file and http_runtime_constants.ERROR_CODE_HEADER in response_headers): try: with open(error_file) as f: content = f.read() except IOError: content = 'Failed to load error handler' logging.exception('failed to load error file: %s', error_file) start_response('500 Internal Server Error', [('Content-Type', 'text/html'), ('Content-Length', str(len(content)))]) yield content return del response_headers[http_runtime_constants.ERROR_CODE_HEADER] start_response('%s %s' % (response.status, response.reason), response_headers.items()) # Yield the response body in small blocks. while True: try: block = response.read(512) if not block: break yield block except httplib.HTTPException: # The runtime process has encountered a problem, but has not # necessarily crashed. For example, a Go runtime process' HTTP # handler may have panicked in app-specific code (which the http # package will recover from, so the process as a whole doesn't # crash). At this point, we have already proxied onwards the HTTP # header, so we cannot retroactively serve a 500 Internal Server # Error. We silently break here; the runtime process has presumably # already written to stderr (via the Tee). break except Exception: with self._process_lock: if self._process and self._process.poll() is not None: # The development server is in a bad state. Log and return an error # message. self._prior_error = ('the runtime process for the instance running ' 'on port %d has unexpectedly quit' % ( self._port)) yield self._handle_error(self._prior_error, start_response) else: raise def _handle_error(self, message, start_response): # Give the runtime process a bit of time to write to stderr. time.sleep(0.1) buf = self._stderr_tee.get_buf() if buf: message = message + '\n\n' + buf # TODO: change 'text/plain' to 'text/plain; charset=utf-8' # throughout devappserver2. start_response('500 Internal Server Error', [('Content-Type', 'text/plain'), ('Content-Length', str(len(message)))]) return message def _read_start_process_file(self, max_attempts=10, sleep_base=.125): """Read the single line response expected in the start process file. The START_PROCESS_FILE flavor uses a file for the runtime instance to report back the port it is listening on. We can't rely on EOF semantics as that is a race condition when the runtime instance is simultaneously writing the file while the devappserver process is reading it; rather we rely on the line being terminated with a newline. Args: max_attempts: The maximum number of attempts to read the line. sleep_base: How long in seconds to sleep between the first and second attempt (the time will be doubled between each successive attempt). The value may be any numeric type that is convertible to float (complex won't work but user types that are sufficiently numeric-like will). Returns: If a full single line (as indicated by a newline terminator) is found, all data read up to that point is returned; return an empty string if no newline is read before the process exits or the max number of attempts are made. """ try: for attempt in range(max_attempts): # Yes, the final data may already be in the file even though the # process exited. That said, since the process should stay alive # if it's exited we don't care anyway. if self._process.poll() is not None: return '' # On Mac, if the first read in this process occurs before the data is # written, no data will ever be read by this process without the seek. self._process.child_out.seek(0) line = self._process.child_out.read() if '\n' in line: return line _sleep_between_retries(attempt, max_attempts, sleep_base) finally: self._process.child_out.close() return '' def start(self): """Starts the runtime process and waits until it is ready to serve.""" runtime_config = self._runtime_config_getter() # TODO: Use a different process group to isolate the child process # from signals sent to the parent. Only available in subprocess in # Python 2.7. assert self._start_process_flavor in self._VALID_START_PROCESS_FLAVORS if self._start_process_flavor == START_PROCESS: serialized_config = base64.b64encode(runtime_config.SerializeToString()) with self._process_lock: assert not self._process, 'start() can only be called once' self._process = safe_subprocess.start_process( self._args, serialized_config, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=self._env, cwd=self._module_configuration.application_root) line = self._process.stdout.readline() elif self._start_process_flavor == START_PROCESS_FILE: serialized_config = runtime_config.SerializeToString() with self._process_lock: assert not self._process, 'start() can only be called once' self._process = safe_subprocess.start_process_file( args=self._args, input_string=serialized_config, env=self._env, cwd=self._module_configuration.application_root, stderr=subprocess.PIPE) line = self._read_start_process_file() _remove_retry_sharing_violation(self._process.child_out.name) # _stderr_tee may be pre-set by unit tests. if self._stderr_tee is None: self._stderr_tee = tee.Tee(self._process.stderr, sys.stderr) self._stderr_tee.start() self._prior_error = None self._port = None try: self._port = int(line) except ValueError: self._prior_error = 'bad runtime process port [%r]' % line logging.error(self._prior_error) else: # Check if the runtime can serve requests. if not self._can_connect(): self._prior_error = 'cannot connect to runtime on port %r' % self._port logging.error(self._prior_error) def _can_connect(self): connection = httplib.HTTPConnection(self._host, self._port) with contextlib.closing(connection): try: connection.connect() except socket.error: return False else: return True def quit(self): """Causes the runtime process to exit.""" with self._process_lock: assert self._process, 'module was not running' try: self._process.kill() except OSError: pass # Mac leaks file descriptors without call to join. Suspect a race # condition where the interpreter is unable to close the subprocess pipe # as the thread hasn't returned from the readline call. self._stderr_tee.join(5) self._process = None
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main.py
omarkhaled850/photo_shop_for_pros
0
93372
<reponame>omarkhaled850/photo_shop_for_pros<filename>main.py<gh_stars>0 # Name : <NAME> import imutils from PyQt5 import QtCore, QtGui, QtWidgets import cv2 import numpy as np from PyQt5.QtGui import QPixmap from PyQt5.QtWidgets import QAction, QFileDialog, QMainWindow, QDialog, QDialogButtonBox, QVBoxLayout, QInputDialog, \ QLineEdit # dialog message class CustomDialog(QDialog): def __init__(self, *args, **kwargs): super(CustomDialog, self).__init__(*args, **kwargs) self.setWindowTitle("HELLO!") buttons = QDialogButtonBox.Ok | QDialogButtonBox.Cancel self.buttonBox = QDialogButtonBox(buttons) self.buttonBox.accepted.connect(self.accept) self.buttonBox.rejected.connect(self.reject) self.layout = QVBoxLayout() self.layout.addWidget(self.buttonBox) self.setLayout(self.layout) # qweight class Ui_MainWindow(QMainWindow): global_img = None display_img = None def setupUi(self, MainWindow): MainWindow.setObjectName("MainWindow") MainWindow.resize(800, 500) self.centralwidget = QtWidgets.QWidget(MainWindow) self.centralwidget.setObjectName("centralwidget") self.formLayoutWidget = QtWidgets.QWidget(self.centralwidget) self.formLayoutWidget.setGeometry(QtCore.QRect(0, 0, 161, 421)) self.formLayoutWidget.setObjectName("formLayoutWidget") self.formLayout = QtWidgets.QFormLayout(self.formLayoutWidget) self.formLayout.setContentsMargins(0, 0, 0, 0) self.formLayout.setObjectName("formLayout") self.main_toolbox = QtWidgets.QToolBox(self.formLayoutWidget) self.main_toolbox.setEnabled(True) self.main_toolbox.setMouseTracking(False) self.main_toolbox.setObjectName("main_toolbox") self.page = QtWidgets.QWidget() self.page.setGeometry(QtCore.QRect(0, 0, 159, 338)) self.page.setObjectName("page") self.verticalLayoutWidget = QtWidgets.QWidget(self.page) self.verticalLayoutWidget.setGeometry(QtCore.QRect(0, -1, 160, 341)) self.verticalLayoutWidget.setObjectName("verticalLayoutWidget") self.verticalLayout = QtWidgets.QVBoxLayout(self.verticalLayoutWidget) self.verticalLayout.setContentsMargins(0, 0, 0, 0) self.verticalLayout.setObjectName("verticalLayout") self.gray_scale_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.gray_scale_btn.setObjectName("gray_scale_btn") self.verticalLayout.addWidget(self.gray_scale_btn) self.flip_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.flip_btn.setObjectName("flip_btn") self.verticalLayout.addWidget(self.flip_btn) self.rot_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.rot_btn.setObjectName("rot_btn") self.verticalLayout.addWidget(self.rot_btn) self.skewing_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.skewing_btn.setObjectName("skewing_btn") self.verticalLayout.addWidget(self.skewing_btn) self.croping_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.croping_btn.setObjectName("croping_btn") self.verticalLayout.addWidget(self.croping_btn) self.scaling_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.scaling_btn.setObjectName("scaling_btn") self.verticalLayout.addWidget(self.scaling_btn) self.translation_btn = QtWidgets.QPushButton(self.verticalLayoutWidget) self.translation_btn.setObjectName("translation_btn") self.verticalLayout.addWidget(self.translation_btn) self.main_toolbox.addItem(self.page, "") self.page_2 = QtWidgets.QWidget() self.page_2.setGeometry(QtCore.QRect(0, 0, 159, 338)) self.page_2.setObjectName("page_2") self.verticalLayoutWidget_2 = QtWidgets.QWidget(self.page_2) self.verticalLayoutWidget_2.setGeometry(QtCore.QRect(-20, 0, 187, 295)) self.verticalLayoutWidget_2.setObjectName("verticalLayoutWidget_2") self.verticalLayout_2 = QtWidgets.QVBoxLayout(self.verticalLayoutWidget_2) self.verticalLayout_2.setContentsMargins(0, 0, 0, 0) self.verticalLayout_2.setObjectName("verticalLayout_2") self.label = QtWidgets.QLabel(self.verticalLayoutWidget_2) self.label.setObjectName("label") self.verticalLayout_2.addWidget(self.label) self.negative_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.negative_btn.setObjectName("negative_btn") self.verticalLayout_2.addWidget(self.negative_btn) self.hist_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.hist_btn.setObjectName("hist_btn") self.verticalLayout_2.addWidget(self.hist_btn) self.log_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.log_btn.setObjectName("log_btn") self.verticalLayout_2.addWidget(self.log_btn) self.gamma_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.gamma_btn.setObjectName("gamma_btn") self.verticalLayout_2.addWidget(self.gamma_btn) self.blending_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.blending_btn.setObjectName("blending_btn") self.verticalLayout_2.addWidget(self.blending_btn) self.bitslicing_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.bitslicing_btn.setObjectName("bitslicing_btn") self.verticalLayout_2.addWidget(self.bitslicing_btn) self.slicing_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.slicing_btn.setObjectName("slicing_btn") self.verticalLayout_2.addWidget(self.slicing_btn) self.label_2 = QtWidgets.QLabel(self.verticalLayoutWidget_2) self.label_2.setObjectName("label_2") self.verticalLayout_2.addWidget(self.label_2) self.smoothing_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.smoothing_btn.setObjectName("smoothing_btn") self.verticalLayout_2.addWidget(self.smoothing_btn) self.sharp_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_2) self.sharp_btn.setObjectName("sharp_btn") self.verticalLayout_2.addWidget(self.sharp_btn) self.main_toolbox.addItem(self.page_2, "") self.page_3 = QtWidgets.QWidget() self.page_3.setGeometry(QtCore.QRect(0, 0, 159, 338)) self.page_3.setObjectName("page_3") self.verticalLayoutWidget_3 = QtWidgets.QWidget(self.page_3) self.verticalLayoutWidget_3.setGeometry(QtCore.QRect(-10, 0, 171, 80)) self.verticalLayoutWidget_3.setObjectName("verticalLayoutWidget_3") self.verticalLayout_3 = QtWidgets.QVBoxLayout(self.verticalLayoutWidget_3) self.verticalLayout_3.setContentsMargins(0, 0, 0, 0) self.verticalLayout_3.setObjectName("verticalLayout_3") self.threshold_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_3) self.threshold_btn.setObjectName("threshold_btn") self.verticalLayout_3.addWidget(self.threshold_btn) self.edge_btn = QtWidgets.QPushButton(self.verticalLayoutWidget_3) self.edge_btn.setObjectName("edge_btn") self.verticalLayout_3.addWidget(self.edge_btn) self.main_toolbox.addItem(self.page_3, "") self.formLayout.setWidget(0, QtWidgets.QFormLayout.SpanningRole, self.main_toolbox) self.image_out = QtWidgets.QLabel(self.centralwidget) self.image_out.setGeometry(QtCore.QRect(180, 0, 581, 441)) self.image_out.setText("") ############################################################################################## self.image_out.setPixmap(QtGui.QPixmap("")) self.image_out.setScaledContents(True) self.image_out.setObjectName("image_out") MainWindow.setCentralWidget(self.centralwidget) self.menubar = QtWidgets.QMenuBar(MainWindow) self.menubar.setGeometry(QtCore.QRect(0, 0, 800, 21)) self.menubar.setObjectName("menubar") self.menuFiles = QtWidgets.QMenu(self.menubar) self.menuFiles.setObjectName("menuFiles") MainWindow.setMenuBar(self.menubar) self.statusbar = QtWidgets.QStatusBar(MainWindow) self.statusbar.setObjectName("statusbar") MainWindow.setStatusBar(self.statusbar) self.actionOpenFile = QtWidgets.QAction(MainWindow) self.actionOpenFile.setObjectName("actionOpenFile") self.menuFiles.addAction(self.actionOpenFile) self.menubar.addAction(self.menuFiles.menuAction()) self.retranslateUi(MainWindow) self.main_toolbox.setCurrentIndex(1) QtCore.QMetaObject.connectSlotsByName(MainWindow) self.rot_btn.clicked.connect(self.rotate_fun) def retranslateUi(self, MainWindow): _translate = QtCore.QCoreApplication.translate MainWindow.setWindowTitle(_translate("MainWindow", "MainWindow")) self.gray_scale_btn.setText(_translate("MainWindow", "gray image")) self.flip_btn.setText(_translate("MainWindow", "flip image")) self.rot_btn.setText(_translate("MainWindow", "rotate image")) self.skewing_btn.setText(_translate("MainWindow", "skewing")) self.croping_btn.setText(_translate("MainWindow", "crop")) self.scaling_btn.setText(_translate("MainWindow", "scaling")) self.translation_btn.setText(_translate("MainWindow", "image translation")) self.main_toolbox.setItemText(self.main_toolbox.indexOf(self.page), _translate("MainWindow", "Image Operations")) self.label.setText(_translate("MainWindow", " 1-Point Processing")) self.hist_btn.setText(_translate("MainWindow", "histogram equalization")) self.log_btn.setText(_translate("MainWindow", "Log transformation")) self.gamma_btn.setText(_translate("MainWindow", "Power transformation")) self.blending_btn.setText(_translate("MainWindow", "Image blending")) self.bitslicing_btn.setText(_translate("MainWindow", "bite plane slicing")) self.slicing_btn.setText(_translate("MainWindow", "Image slicing")) self.negative_btn.setText(_translate("MainWindow", "negative")) self.label_2.setText(_translate("MainWindow", " 2-Neighborhood Processing")) self.smoothing_btn.setText(_translate("MainWindow", "smoothing")) self.sharp_btn.setText(_translate("MainWindow", "sharping")) self.main_toolbox.setItemText(self.main_toolbox.indexOf(self.page_2), _translate("MainWindow", "Image Enhancement")) self.threshold_btn.setText(_translate("MainWindow", "thresholding")) self.edge_btn.setText(_translate("MainWindow", "edge segmantation")) self.main_toolbox.setItemText(self.main_toolbox.indexOf(self.page_3), _translate("MainWindow", "Image Enhancement")) self.threshold_btn.setText(_translate("MainWindow", "thresholding")) self.edge_btn.setText(_translate("MainWindow", "edge segmantation")) self.main_toolbox.setItemText(self.main_toolbox.indexOf(self.page_3), _translate("MainWindow", "Image Segmentation")) self.menuFiles.setTitle(_translate("MainWindow", "Files")) self.actionOpenFile.setText(_translate("MainWindow", "OpenFile")) # connecting the open image function with the menbar button self.actionOpenFile.triggered.connect(self.open_img) # connecting buttons with functions self.gray_scale_btn.clicked.connect(self.graScaleFun) self.flip_btn.clicked.connect(self.flip_fun) self.skewing_btn.clicked.connect(self.skewing_fun) self.croping_btn.clicked.connect(self.crop_fun) self.scaling_btn.clicked.connect(self.scaling_fun) self.translation_btn.clicked.connect(self.trans_fun) self.hist_btn.clicked.connect(self.histequ_fun) self.log_btn.clicked.connect(self.log_fun) self.gamma_btn.clicked.connect(self.gammacorrection) self.blending_btn.clicked.connect(self.blend_fun) self.slicing_btn.clicked.connect(self.slicing_fun) self.negative_btn.clicked.connect(self.negative_fun) self.smoothing_btn.clicked.connect(self.smoothing_fun) self.sharp_btn.clicked.connect(self.sharp_fun) self.threshold_btn.clicked.connect(self.threshold_fun) self.edge_btn.clicked.connect(self.edge_fun) self.bitslicing_btn.clicked.connect(self.bitslicing_fun) #open a dialog fo the user to choose the image def open_img(self): imagePath, _ = QFileDialog.getOpenFileName() self.global_img = cv2.imread(imagePath) self.display_img = QPixmap(imagePath) self.image_out.setPixmap(self.display_img) self.resize(self.display_img.size()) self.adjustSize() self.image_data() def bitslicing_fun(self): lst = [] for i in range(self.global_img.shape[0]): for j in range(self.global_img.shape[1]): lst.append(np.binary_repr(self.global_img[i][j], width=8)) eight_bit_img = (np.array([int(i[0]) for i in lst], dtype=np.uint8) * 128).reshape(self.global_img.shape[0],self.global_img.shape[1]) self.global_img = eight_bit_img self.displayINlebal() def OpenTextFile(self): dialog = QtGui.QFileDialog() dialog.setWindowTitle("Choose a file to open") dialog.setFileMode(QtGui.QFileDialog.ExistingFile) dialog.setNameFilter("Text (*.txt);; All files (*.*)") dialog.setViewMode(QtGui.QFileDialog.Detail) filename = QtCore.QStringList() if (dialog.exec_()): file_name = dialog.selectedFiles() plain_text = open(file_name[0]).read() self.Editor.setPlainText(plain_text) self.file_path = str(file_name[0]) def graScaleFun(self): gray_img = cv2.cvtColor(self.global_img, cv2.COLOR_BGR2GRAY) self.global_img = gray_img cv2.imwrite('savedImage.jpg', gray_img) self.image_out.setPixmap(QtGui.QPixmap("savedImage.jpg")) self.image_out.setScaledContents(True) def negative_fun(self): height, width = self.global_img.shape self.global_img= 255 - self.global_img negative_img = self.global_img # Display the negative transformed image self.displayINlebal() def getTextForFlip(self): text, okPressed = QInputDialog.getText(self, "fliping", "type:x or y or xy", QLineEdit.Normal, "") if okPressed and text != '': print(text) return text def flip_fun(self): res = self.getTextForFlip() if res == 'x': flipedimage = cv2.flip(self.global_img, 0) elif res == 'y': flipedimage = cv2.flip(self.global_img, 1) elif res == 'xy': flipedimage = cv2.flip(self.global_img, -1) self.global_img = flipedimage self.displayINlebal() return flipedimage def getAngle(self): angle, okPressed = QInputDialog.getDouble(self, "Get double", "Value:", 10.05, -360, 360, 10) if okPressed: print(angle) return angle def rotate_fun(self): angle = self.getAngle() rotated = imutils.rotate_bound(self.global_img, angle) self.global_img = rotated self.displayINlebal() def skewing_fun(self): a1, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "x value 1st point:", 0.0, -self.global_img.shape[0], self.global_img.shape[0], 1) a2, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "y value 1st point:", 0.0, -self.global_img.shape[1], self.global_img.shape[1], 1) b1, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "x value 2nd point:", 0.0, -self.global_img.shape[0], self.global_img.shape[0], 1) #b2, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "y value 2nd point:", 0.0, -self.global_img.shape[1], self.global_img.shape[1], 1) c1, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "x value 3rd point:", 0.0, -self.global_img.shape[0], self.global_img.shape[0], 1) #c2, okPressed = QInputDialog.getDouble(self, "enter skewing destnation", "y value 3rd point:", 0.0, -self.global_img.shape[1], self.global_img.shape[1], 1) image = self.global_img src_pts = np.float32([[0, 0], [image.shape[0] - 1, 0], [0, image.shape[1] - 1]]) dst_pts = np.float32([[a1, a2], [image.shape[0]+b1, 0], [c1, image.shape[1]]]) Mat = cv2.getAffineTransform(src_pts, dst_pts) skewed = cv2.warpAffine(image, Mat, (image.shape[1], image.shape[0])) self.global_img = skewed self.displayINlebal() def crop_fun(self): a1, okPressed = QInputDialog.getInt(self, "enter croping points", "from row number:", 0, -self.global_img.shape[0], self.global_img.shape[0], 1) a2, okPressed = QInputDialog.getInt(self, "enter croping points", "to row number:", 0, -self.global_img.shape[1], self.global_img.shape[1], 1) b1, okPressed = QInputDialog.getInt(self, "enter croping points", "from col number:", 0, -self.global_img.shape[0], self.global_img.shape[0], 1) b2, okPressed = QInputDialog.getInt(self, "enter croping points", "to col number:", 0, -self.global_img.shape[1], self.global_img.shape[1], 1) self.global_img = self.global_img[a1:a2, b1:b2] self.displayINlebal() cv2.imshow("Cropped Image", self.global_img) cv2.waitKey(0) def scaling_fun(self): scaleX, okPressed = QInputDialog.getInt(self, "Get scaling value", "fx Value:", 1, -self.global_img.shape[0], self.global_img.shape[0], 1) scaleY, okPressed = QInputDialog.getInt(self, "Get scaling value", "fy Value:", 1, -self.global_img.shape[1], self.global_img.shape[1], 1) img = self.global_img # Reduce the image to 0.6 times the original scaled_img = cv2.resize(img, None, fx=scaleX, fy=scaleY, interpolation=cv2.INTER_LINEAR) self.global_img = scaled_img self.displayINlebal() cv2.imshow("Scaled Image", self.global_img) cv2.waitKey(0) def histequ_fun(self): equ = cv2.equalizeHist(self.global_img) self.global_img = equ self.displayINlebal() def trans_fun(self): # Store height and width of the image gray_img = self.global_img height, width = gray_img.shape[:2] transX, okPressed = QInputDialog.getInt(self, "Get translation value", "x Value:", 1, -self.global_img.shape[0],self.global_img.shape[0], 1) transY, okPressed = QInputDialog.getInt(self, "Get translation value", "y Value:", 1, -self.global_img.shape[1],self.global_img.shape[1], 1) T = np.float32([[1, 0, transX], [0, 1, transY]]) # We use warpAffine to transform # the image using the matrix, T trans_img = cv2.warpAffine(gray_img, T, (width, height)) self.global_img = trans_img self.displayINlebal() def blend_fun(self): factor1, okPressed = QInputDialog.getDouble(self, "1st image factor:", 0.5, 0.0, 1, 0.1) factor2, okPressed = QInputDialog.getDouble(self, "2nd image factor:", 0.5, 0.0, 1, 0.1) flipedimage = cv2.flip(self.global_img, 0) dst = cv2.addWeighted(flipedimage, factor1, self.global_img, factor2, 0) self.global_img = dst self.displayINlebal() # # Apply log transformation method def log_fun(self): c = 255 / np.log(1 + np.max(self.global_img)) log_image = c * (np.log(self.global_img + 1)) log_image = np.array(log_image, dtype=np.uint8) self.global_img = log_image self.displayINlebal() # # gamma correction def gammacorrection(self): # Apply gamma correction. gamma, okPressed = QInputDialog.getDouble(self, "enter gamma value ", "gamma<0 = darker , gamma>0 = lighter ", 0.5, 0, 4, 3) gamma_corrected = np.array(255 * (self.global_img / 255) ** gamma, dtype='uint8') self.global_img = gamma_corrected self.displayINlebal() def threshold_fun(self): threshvalue, okPressed = QInputDialog.getDouble(self, "thresholding ", "enter the threshold value:",1, 0, 255, 1) ret, thresh1 = cv2.threshold(self.global_img, threshvalue, 255, cv2.THRESH_BINARY) self.global_img = thresh1 self.displayINlebal() # grey level slicing def slicing_fun(self): # Find width and height of image row, column = self.global_img.shape # Create an zeros array to store the sliced image img1 = np.zeros((row, column), dtype='uint8') # Specify the min and max range min_range, okPressed = QInputDialog.getInt(self, "slicing data", "min range", 0, 0, 255, 1) max_range, okPressed = QInputDialog.getInt(self, "slicing data", "max range", 0, 0, 255, 1) # Loop over the input image and if pixel value lies in desired range set it to 255 otherwise set it to 0. for i in range(row): for j in range(column): if self.global_img[i, j] > max_range: img1[i, j] = 255 elif self.global_img[i, j] < min_range: img1[i, j] = 0 # Display the image self.global_img = img1 self.displayINlebal() # this function takes the user choice and give him the filter he\she wants def smoothing_fun(self): items = ("Gaussian", "Averaging", "circular","pyramidal","cone","median") item, okPressed = QInputDialog.getItem(self, "choose method", "filter:", items, 0, False) if okPressed and item: print(item) if item == 'Gaussian': print(item) if item == 'Gaussian': self.global_img = cv2.GaussianBlur(self.global_img, (5, 5), 0) self.displayINlebal() elif item == "Averaging": self.global_img = cv2.blur(self.global_img, (5, 5)) self.displayINlebal() elif item == "circular": circularKernal = np.array([[0, 1, 1, 1, 0], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [0, 1, 1, 1, 0]],np.float32) / 21 dst = cv2.filter2D(self.global_img, -1, circularKernal) self.global_img = dst self.displayINlebal() elif item == "pyramidal": pykernel = np.array([[1, 2, 3, 2, 1], [2, 4, 6, 4, 2], [3, 6, 9, 6, 3], [2, 4, 6, 4, 2], [1, 2, 3, 2, 1]],np.float32) / 81 dst = cv2.filter2D(self.global_img, -1, pykernel) self.global_img = dst self.displayINlebal() elif item == "cone": coneKernel = np.array([[0, 0, 1, 0, 0], [0, 2, 2, 2, 0], [1, 2, 5, 2, 1], [0, 2, 2, 2, 0], [0, 0, 1, 0, 0]],np.float32) / 25 dst = cv2.filter2D(self.global_img, -1, coneKernel) self.global_img = dst self.displayINlebal() elif item == "median": median = cv2.medianBlur(self.global_img, 5) self.global_img = median self.displayINlebal() def sharp_fun(self): items = ("laplacian", "sobelx", "sobely",) item, okPressed = QInputDialog.getItem(self, "choose method", "filter:", items, 0, False) if item == "sobely": sobely = cv2.Sobel(self.global_img, cv2.CV_64F, 0, 1, ksize=5) self.global_img = sobely elif item == "sobelx": sobelx = cv2.Sobel(self.global_img, cv2.CV_64F, 1, 0, ksize=5) self.global_img = sobelx elif item == "laplacian": laplacian = cv2.Laplacian(self.global_img, cv2.CV_64F) self.global_img = laplacian self.displayINlebal() def edge_fun(self): # Remove noise by blurring with a Gaussian filter blur = cv2.GaussianBlur(self.global_img, (5, 5), 0) # Apply Laplace function laplacian = cv2.Laplacian(blur, cv2.CV_64F) # converting back to uint8 abs_dst = cv2.convertScaleAbs(laplacian) self.global_img = abs_dst self.displayINlebal() # this function prints the data of any input image in console def image_data(self): print(type(self.global_img)) print('RGB shape: ') # Rows, cols, channels print(self.global_img.shape) imgshape = self.global_img.shape rows = imgshape[0] cols = imgshape[1] print(rows) print(cols) print('Gray shape:') print(self.global_img.shape) print('img.dtype: ') print(self.global_img.dtype) print('img.size: ') print(self.global_img.dtype) # this function is for displaying the image in the fram of the program not in a imshow new fram def displayINlebal(self): filename = 'savedImage.jpg' cv2.imwrite(filename, self.global_img) self.image_out.setPixmap(QtGui.QPixmap("savedImage.jpg")) self.image_out.setScaledContents(True) if __name__ == "__main__": import sys app = QtWidgets.QApplication(sys.argv) MainWindow = QtWidgets.QMainWindow() ui = Ui_MainWindow() ui.setupUi(MainWindow) MainWindow.show() sys.exit(app.exec_())
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src/setup.py
mjj4791/CCLLexer
0
155425
from setuptools import setup, find_packages setup ( name='ccllexer', packages=find_packages(), entry_points = """ [pygments.lexers] ccllexer = ccllexer.lexer:CCLLexer """, )
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scale/storage/serializers.py
stevevarner/scale
0
57585
"""Defines the serializers for Scale files and workspaces""" from __future__ import unicode_literals import rest_framework.serializers as serializers from rest_framework.fields import CharField from util.rest import ModelIdSerializer class DataTypeField(CharField): """Field for displaying the list of data type tags for a Scale file""" type_name = 'DataTypeField' type_label = 'datatype' def to_representation(self, value): """Converts the model field to a list of data type tags :param value: the comma-separated data types for the Scale file :type value: str :rtype: list of str :returns: the list of data type tags """ tags = [] if value: for tag in value.split(','): tags.append(tag) return tags class WktField(CharField): """Field for displaying geometry objects as Well Known Text""" type_name = 'WktField' type_label = 'wtk' def to_representation(self, value): """Converts the model field to WKT :param value: the associated geometry info :type value: GEOSGeometry :rtype: string :returns: the WKT representation """ if value: return value.wkt class GeoJsonField(CharField): """Field for displaying geometry objects as Well Known Text""" type_name = 'GeoJsonField' type_label = 'geojson' def to_representation(self, value): """Converts the model field to GeoJson :param value: the associated geometry info :type value: GEOSGeometry :rtype: string :returns: the GeoJson representation """ if value: return value.geojson class WorkspaceBaseSerializer(ModelIdSerializer): """Converts workspace model fields to REST output""" name = serializers.CharField() class WorkspaceSerializer(WorkspaceBaseSerializer): """Converts workspace model fields to REST output""" title = serializers.CharField() description = serializers.CharField() base_url = serializers.URLField() is_active = serializers.BooleanField() used_size = serializers.IntegerField() # TODO: BigIntegerField? total_size = serializers.IntegerField() # TODO: BigIntegerField? created = serializers.DateTimeField() archived = serializers.DateTimeField() last_modified = serializers.DateTimeField() class WorkspaceDetailsSerializer(WorkspaceSerializer): """Converts workspace model fields to REST output""" json_config = serializers.JSONField(default=dict) class ScaleFileBaseSerializerV5(ModelIdSerializer): """Converts Scale file model fields to REST output""" workspace = WorkspaceBaseSerializer() file_name = serializers.CharField() media_type = serializers.CharField() file_type = serializers.CharField() file_size = serializers.IntegerField() # TODO: BigIntegerField? data_type = DataTypeField() is_deleted = serializers.BooleanField() uuid = serializers.CharField() url = serializers.URLField() created = serializers.DateTimeField() deleted = serializers.DateTimeField() data_started = serializers.DateTimeField() data_ended = serializers.DateTimeField() source_started = serializers.DateTimeField() source_ended = serializers.DateTimeField() last_modified = serializers.DateTimeField() class ScaleFileBaseSerializerV6(ModelIdSerializer): """Converts Scale file model fields to REST output""" file_name = serializers.CharField() class ScaleFileSerializerV5(ScaleFileBaseSerializerV5): """Converts Scale file model fields to REST output""" file_path = serializers.CharField() # TODO: update to use GeoJson instead of WKT geometry = WktField() center_point = WktField() meta_data = serializers.JSONField(default=dict) countries = serializers.StringRelatedField(many=True, read_only=True) class ScaleFileSerializerV6(ScaleFileBaseSerializerV6): """Converts Scale file model fields to REST output""" from batch.serializers import BatchBaseSerializerV6 from job.serializers import JobTypeBaseSerializerV6 from recipe.serializers import RecipeTypeBaseSerializerV6 workspace = WorkspaceBaseSerializer() media_type = serializers.CharField() file_type = serializers.CharField() file_size = serializers.IntegerField() # TODO: BigIntegerField? file_path = serializers.CharField() is_deleted = serializers.BooleanField() url = serializers.URLField() created = serializers.DateTimeField() deleted = serializers.DateTimeField() data_started = serializers.DateTimeField() data_ended = serializers.DateTimeField() source_started = serializers.DateTimeField() source_ended = serializers.DateTimeField() last_modified = serializers.DateTimeField() # TODO: update to use GeoJson instead of WKT geometry = WktField() center_point = WktField() countries = serializers.StringRelatedField(many=True, read_only=True) job_type = JobTypeBaseSerializerV6() job = ModelIdSerializer() job_exe = ModelIdSerializer() job_output = serializers.CharField() recipe_type = RecipeTypeBaseSerializerV6() recipe = ModelIdSerializer() recipe_node = serializers.CharField() batch = BatchBaseSerializerV6() is_superseded = serializers.BooleanField() superseded = serializers.DateTimeField() class ScaleFileDetailsSerializerV6(ScaleFileSerializerV6): """Converts file model fields to REST output""" meta_data = serializers.JSONField(default=dict)
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models.py
nas3444/capstoneproject
0
183397
<reponame>nas3444/capstoneproject from datetime import datetime import os from sqlalchemy import Column, String, Integer, create_engine, ForeignKey from flask_sqlalchemy import SQLAlchemy import json from config import DatabaseURI from flask_migrate import Migrate # Creating DB database_path = DatabaseURI.SQLALCHEMY_DATABASE_URI db = SQLAlchemy() def setup_db(app, database_path=database_path): app.config["SQLALCHEMY_DATABASE_URI"] = database_path app.config["SQLALCHEMY_TRACK_MODIFICATIONS"] = False db.app = app db.init_app(app) db.create_all() migrate = Migrate(app, db) # Movies Model class Movie(db.Model): __tablename__ = 'movies' id = Column(Integer, primary_key=True) title = Column(String, nullable=False, unique=True) image = Column(String) release_date = Column(db.DateTime) actors = db.relationship('Actor', backref='Movie', lazy='dynamic') def __init__(self, title, image, release_date): self.title = title self.image = image self.release_date = release_date def insert(self): db.session.add(self) db.session.commit() def update(self): db.session.commit() def delete(self): db.session.delete(self) db.session.commit() def format(self): return { 'id': self.id, 'title': self.title, 'image': self.image, 'release_date': self.release_date } # Actors Model class Actor(db.Model): ___tablename___ = 'actors' id = Column(Integer, primary_key=True) name = Column(String, nullable=False, unique=True) age = Column(Integer) gender = Column(String) movie_id = db.Column(db.Integer, db.ForeignKey('movies.id')) def __init__(self, name, age, gender, movie_id): self.name = name self.age = age self.gender = gender self.movie_id = movie_id def insert(self): db.session.add(self) db.session.commit() def update(self): db.session.commit() def delete(self): db.session.delete(self) db.session.commit() def format(self): return { 'id': self.id, 'name': self.name, 'age': self.age, 'gender': self.gender, 'movie_id': self.movie_id }
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smsapi/__init__.py
maciejga/smsapi-python-client
0
93023
<reponame>maciejga/smsapi-python-client<gh_stars>0 # -*- coding: utf-8 -*- name = 'smsapi-client' version = '2.3.0' lib_info = '%s/%s' % (name, version)
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sagas/nlu/features.py
samlet/stack
3
154658
from typing import Text, Any, Dict, List, Union, Optional from jsonpath_ng import jsonpath, parse from pprint import pprint from sagas.conf.conf import cf def feats_for_path(path:Text): if path=='_': return '$.feats' prefix = '$.' suffix = '.feats' parts = path.split('/') parts_str = '.'.join([f"{t}[*]" for t in parts]) return f"{prefix}{parts_str}{suffix}" def feats_map(ft:Text) -> Dict[Text, Text]: if not ft: return {} def ensure(pair): p=pair.split('=') return (p[0],'_') if len(p)==1 else p tuples=[ensure(pair) for pair in ft.split('|')] ft_m={k:v for k,v in tuples} return ft_m def extract_feats_map(ft:Text, engine:Text) -> Dict[Text, Text]: ex_fn={'corenlp': feats_map, 'stanza': feats_map} engine=engine.split('_')[0] if engine in ex_fn: return ex_fn[engine](ft) return {} def get_feats_map(sents, lang, domain, path): domain_name=f'{domain}_domains' if domain != 'predicts' else domain from sagas.nlu.ruleset_procs import cached_chunks chunks = cached_chunks(sents, lang, cf.engine(lang)) parser = parse(feats_for_path(path)) results=[] for chunk in chunks[domain_name]: vals = [match.value for match in parser.find(chunk)] if vals: results.extend([feats_map(val) for val in vals]) return results
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school/eCornell/Python Cert/Controlling Programming Flow/for statements/exercise4/funcs.py
KyleGortych/sample_work
0
125919
""" funcs Descript: File name: funcs.py Maintainer: <NAME> created: 03-22-2022 """ def skip(s,n): """ Returns a copy of s, only including positions that are multiples of n A position is a multiple of n if pos % n == 0. Examples: skip('hello world',1) returns 'hello world' skip('hello world',2) returns 'hlowrd' skip('hello world',3) returns 'hlwl' skip('hello world',4) returns 'hor' Parameter s: the string to copy Precondition: s is a nonempty string Parameter n: the letter positions to accept Precondition: n is an int > 0 """ assert type(s) == str and len(s) != 0 assert type(n) == int and n > 0 s2 = '' idx = 0 for element in s: if idx % n == 0: s2 = s[idx] + s2 idx += 1 return s2[::-1] # pass def fixed_points(tup): """ Returns a copy of tup, including only the "fixed points". A fixed point of a tuple is an element that is equal to its position in the tuple. For example 0 and 2 are fixed points of (0,3,2). The fixed points are returned in the order that they appear in the tuple. Examples: fixed_points((0,3,2)) returns (0,2) fixed_points((0,1,2)) returns (0,1,2) fixed_points((2,1,0)) returns (1,) Parameter tup: the tuple to copy Precondition: tup is a tuple of ints """ assert type(tup) == tuple tuplist = list(tup) tuplist2 = [] idx = 0 for element in tuplist: if idx == element: tuplist2.append(tuplist[idx]) idx += 1 return tuple(tuplist2) #pass
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networkx/generators/tests/test_random_graphs.py
SultanOrazbayev/networkx
2
69006
"""Unit tests for the :mod:`networkx.generators.random_graphs` module.""" import networkx as nx import pytest _gnp_generators = [ nx.gnp_random_graph, nx.fast_gnp_random_graph, nx.binomial_graph, nx.erdos_renyi_graph, ] @pytest.mark.parametrize("generator", _gnp_generators) @pytest.mark.parametrize("directed", (True, False)) def test_gnp_generators_negative_edge_probability(generator, directed): """If the edge probability `p` is <=0, the resulting graph should have no edges.""" G = generator(10, -1.1, directed=directed) assert len(G) == 10 assert G.number_of_edges() == 0 assert G.is_directed() == directed @pytest.mark.parametrize("generator", _gnp_generators) @pytest.mark.parametrize( ("directed", "expected_num_edges"), [(False, 45), (True, 90)], ) def test_gnp_generators_greater_than_1_edge_probability( generator, directed, expected_num_edges ): """If the edge probability `p` is >=1, the resulting graph should be complete.""" G = generator(10, 1.1, directed=directed) assert len(G) == 10 assert G.number_of_edges() == expected_num_edges assert G.is_directed() == directed @pytest.mark.parametrize("generator", _gnp_generators) @pytest.mark.parametrize("directed", (True, False)) def test_gnp_generators_basic(generator, directed): """If the edge probability `p` is >0 and <1, test only the basic properties.""" G = generator(10, 0.1, directed=directed) assert len(G) == 10 assert G.is_directed() == directed @pytest.mark.parametrize("generator", _gnp_generators) def test_gnp_generators_for_p_close_to_1(generator): """If the edge probability `p` is close to 1, the resulting graph should have all edges.""" runs = 100 edges = sum( generator(10, 0.99999, directed=True).number_of_edges() for _ in range(runs) ) assert abs(edges / float(runs) - 90) <= runs * 2.0 / 100 @pytest.mark.parametrize("generator", _gnp_generators) @pytest.mark.parametrize("p", (0.2, 0.8)) @pytest.mark.parametrize("directed", (True, False)) def test_gnp_generators_edge_probability(generator, p, directed): """Test that gnp generators generate edges according to the their probability `p`.""" runs = 5000 n = 5 edge_counts = [[0] * n for _ in range(n)] for i in range(runs): G = generator(n, p, directed=directed) for (v, w) in G.edges: edge_counts[v][w] += 1 if not directed: edge_counts[w][v] += 1 for v in range(n): for w in range(n): if v == w: # There should be no loops assert edge_counts[v][w] == 0 else: # Each edge should have been generated with probability close to p assert abs(edge_counts[v][w] / float(runs) - p) <= 0.03 @pytest.mark.parametrize( "generator", [nx.gnp_random_graph, nx.binomial_graph, nx.erdos_renyi_graph] ) @pytest.mark.parametrize( ("seed", "directed", "expected_num_edges"), [(42, False, 1219), (42, True, 2454), (314, False, 1247), (314, True, 2476)], ) def test_gnp_random_graph_aliases(generator, seed, directed, expected_num_edges): """Test that aliases give the same result with the same seed.""" G = generator(100, 0.25, seed=seed, directed=directed) assert len(G) == 100 assert G.number_of_edges() == expected_num_edges assert G.is_directed() == directed class TestGeneratorsRandom: def test_random_graph(self): seed = 42 G = nx.gnm_random_graph(100, 20, seed) G = nx.gnm_random_graph(100, 20, seed, directed=True) G = nx.dense_gnm_random_graph(100, 20, seed) G = nx.watts_strogatz_graph(10, 2, 0.25, seed) assert len(G) == 10 assert G.number_of_edges() == 10 G = nx.connected_watts_strogatz_graph(10, 2, 0.1, tries=10, seed=seed) assert len(G) == 10 assert G.number_of_edges() == 10 pytest.raises( nx.NetworkXError, nx.connected_watts_strogatz_graph, 10, 2, 0.1, tries=0 ) G = nx.watts_strogatz_graph(10, 4, 0.25, seed) assert len(G) == 10 assert G.number_of_edges() == 20 G = nx.newman_watts_strogatz_graph(10, 2, 0.0, seed) assert len(G) == 10 assert G.number_of_edges() == 10 G = nx.newman_watts_strogatz_graph(10, 4, 0.25, seed) assert len(G) == 10 assert G.number_of_edges() >= 20 G = nx.barabasi_albert_graph(100, 1, seed) G = nx.barabasi_albert_graph(100, 3, seed) assert G.number_of_edges() == (97 * 3) G = nx.barabasi_albert_graph(100, 3, seed, nx.complete_graph(5)) assert G.number_of_edges() == (10 + 95 * 3) G = nx.extended_barabasi_albert_graph(100, 1, 0, 0, seed) assert G.number_of_edges() == 99 G = nx.extended_barabasi_albert_graph(100, 3, 0, 0, seed) assert G.number_of_edges() == 97 * 3 G = nx.extended_barabasi_albert_graph(100, 1, 0, 0.5, seed) assert G.number_of_edges() == 99 G = nx.extended_barabasi_albert_graph(100, 2, 0.5, 0, seed) assert G.number_of_edges() > 100 * 3 assert G.number_of_edges() < 100 * 4 G = nx.extended_barabasi_albert_graph(100, 2, 0.3, 0.3, seed) assert G.number_of_edges() > 100 * 2 assert G.number_of_edges() < 100 * 4 G = nx.powerlaw_cluster_graph(100, 1, 1.0, seed) G = nx.powerlaw_cluster_graph(100, 3, 0.0, seed) assert G.number_of_edges() == (97 * 3) G = nx.random_regular_graph(10, 20, seed) pytest.raises(nx.NetworkXError, nx.random_regular_graph, 3, 21) pytest.raises(nx.NetworkXError, nx.random_regular_graph, 33, 21) constructor = [(10, 20, 0.8), (20, 40, 0.8)] G = nx.random_shell_graph(constructor, seed) def is_caterpillar(g): """ A tree is a caterpillar iff all nodes of degree >=3 are surrounded by at most two nodes of degree two or greater. ref: http://mathworld.wolfram.com/CaterpillarGraph.html """ deg_over_3 = [n for n in g if g.degree(n) >= 3] for n in deg_over_3: nbh_deg_over_2 = [nbh for nbh in g.neighbors(n) if g.degree(nbh) >= 2] if not len(nbh_deg_over_2) <= 2: return False return True def is_lobster(g): """ A tree is a lobster if it has the property that the removal of leaf nodes leaves a caterpillar graph (Gallian 2007) ref: http://mathworld.wolfram.com/LobsterGraph.html """ non_leafs = [n for n in g if g.degree(n) > 1] return is_caterpillar(g.subgraph(non_leafs)) G = nx.random_lobster(10, 0.1, 0.5, seed) assert max(G.degree(n) for n in G.nodes()) > 3 assert is_lobster(G) pytest.raises(nx.NetworkXError, nx.random_lobster, 10, 0.1, 1, seed) pytest.raises(nx.NetworkXError, nx.random_lobster, 10, 1, 1, seed) pytest.raises(nx.NetworkXError, nx.random_lobster, 10, 1, 0.5, seed) # docstring says this should be a caterpillar G = nx.random_lobster(10, 0.1, 0.0, seed) assert is_caterpillar(G) # difficult to find seed that requires few tries seq = nx.random_powerlaw_tree_sequence(10, 3, seed=14, tries=1) G = nx.random_powerlaw_tree(10, 3, seed=14, tries=1) def test_dual_barabasi_albert(self, m1=1, m2=4, p=0.5): """ Tests that the dual BA random graph generated behaves consistently. Tests the exceptions are raised as expected. The graphs generation are repeated several times to prevent lucky shots """ seeds = [42, 314, 2718] initial_graph = nx.complete_graph(10) for seed in seeds: # This should be BA with m = m1 BA1 = nx.barabasi_albert_graph(100, m1, seed) DBA1 = nx.dual_barabasi_albert_graph(100, m1, m2, 1, seed) assert BA1.edges() == DBA1.edges() # This should be BA with m = m2 BA2 = nx.barabasi_albert_graph(100, m2, seed) DBA2 = nx.dual_barabasi_albert_graph(100, m1, m2, 0, seed) assert BA2.edges() == DBA2.edges() BA3 = nx.barabasi_albert_graph(100, m1, seed) DBA3 = nx.dual_barabasi_albert_graph(100, m1, m1, p, seed) # We can't compare edges here since randomness is "consumed" when drawing # between m1 and m2 assert BA3.size() == DBA3.size() DBA = nx.dual_barabasi_albert_graph(100, m1, m2, p, seed, initial_graph) BA1 = nx.barabasi_albert_graph(100, m1, seed, initial_graph) BA2 = nx.barabasi_albert_graph(100, m2, seed, initial_graph) assert ( min(BA1.size(), BA2.size()) <= DBA.size() <= max(BA1.size(), BA2.size()) ) # Testing exceptions dbag = nx.dual_barabasi_albert_graph pytest.raises(nx.NetworkXError, dbag, m1, m1, m2, 0) pytest.raises(nx.NetworkXError, dbag, m2, m1, m2, 0) pytest.raises(nx.NetworkXError, dbag, 100, m1, m2, -0.5) pytest.raises(nx.NetworkXError, dbag, 100, m1, m2, 1.5) initial = nx.complete_graph(max(m1, m2) - 1) pytest.raises(nx.NetworkXError, dbag, 100, m1, m2, p, initial_graph=initial) def test_extended_barabasi_albert(self, m=2): """ Tests that the extended BA random graph generated behaves consistently. Tests the exceptions are raised as expected. The graphs generation are repeated several times to prevent lucky-shots """ seeds = [42, 314, 2718] for seed in seeds: BA_model = nx.barabasi_albert_graph(100, m, seed) BA_model_edges = BA_model.number_of_edges() # This behaves just like BA, the number of edges must be the same G1 = nx.extended_barabasi_albert_graph(100, m, 0, 0, seed) assert G1.size() == BA_model_edges # More than twice more edges should have been added G1 = nx.extended_barabasi_albert_graph(100, m, 0.8, 0, seed) assert G1.size() > BA_model_edges * 2 # Only edge rewiring, so the number of edges less than original G2 = nx.extended_barabasi_albert_graph(100, m, 0, 0.8, seed) assert G2.size() == BA_model_edges # Mixed scenario: less edges than G1 and more edges than G2 G3 = nx.extended_barabasi_albert_graph(100, m, 0.3, 0.3, seed) assert G3.size() > G2.size() assert G3.size() < G1.size() # Testing exceptions ebag = nx.extended_barabasi_albert_graph pytest.raises(nx.NetworkXError, ebag, m, m, 0, 0) pytest.raises(nx.NetworkXError, ebag, 1, 0.5, 0, 0) pytest.raises(nx.NetworkXError, ebag, 100, 2, 0.5, 0.5) def test_random_zero_regular_graph(self): """Tests that a 0-regular graph has the correct number of nodes and edges. """ seed = 42 G = nx.random_regular_graph(0, 10, seed) assert len(G) == 10 assert G.number_of_edges() == 0 def test_gnm(self): G = nx.gnm_random_graph(10, 3) assert len(G) == 10 assert G.number_of_edges() == 3 G = nx.gnm_random_graph(10, 3, seed=42) assert len(G) == 10 assert G.number_of_edges() == 3 G = nx.gnm_random_graph(10, 100) assert len(G) == 10 assert G.number_of_edges() == 45 G = nx.gnm_random_graph(10, 100, directed=True) assert len(G) == 10 assert G.number_of_edges() == 90 G = nx.gnm_random_graph(10, -1.1) assert len(G) == 10 assert G.number_of_edges() == 0 def test_watts_strogatz_big_k(self): # Test to make sure than n <= k pytest.raises(nx.NetworkXError, nx.watts_strogatz_graph, 10, 11, 0.25) pytest.raises(nx.NetworkXError, nx.newman_watts_strogatz_graph, 10, 11, 0.25) # could create an infinite loop, now doesn't # infinite loop used to occur when a node has degree n-1 and needs to rewire nx.watts_strogatz_graph(10, 9, 0.25, seed=0) nx.newman_watts_strogatz_graph(10, 9, 0.5, seed=0) # Test k==n scenario nx.watts_strogatz_graph(10, 10, 0.25, seed=0) nx.newman_watts_strogatz_graph(10, 10, 0.25, seed=0) def test_random_kernel_graph(self): def integral(u, w, z): return c * (z - w) def root(u, w, r): return r / c + w c = 1 graph = nx.random_kernel_graph(1000, integral, root) graph = nx.random_kernel_graph(1000, integral, root, seed=42) assert len(graph) == 1000
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Problem116.py
Cleancode404/ProjectEuler
0
132878
<filename>Problem116.py """ Red, green or blue tiles """ def f(m, n): ways = [0] * (n + 1) for i in range(m): ways[i] = 1 for i in range(m, n + 1): ways[i] += ways[i - 1] + ways[i - m] return ways[n] - 1 if __name__ == '__main__': print(f(2, 50) + f(3, 50) + f(4, 50))
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app.py
ialjumah/python-helloworld
0
40486
<filename>app.py Volume in drive C has no label. Volume Serial Number is 30AD-FC05 Directory of C:\Users\HP\Documents\nd064_course_1-main\solutions\python-helloworld 13/07/2021 14:33 <DIR> . 13/07/2021 14:33 <DIR> .. 13/07/2021 14:34 0 app.log 13/07/2021 14:34 0 app.py 10/07/2021 23:21 175 Dockerfile 13/07/2021 14:33 159 listing 11/07/2021 13:34 485 requirements.txt 10/07/2021 23:21 94 test_with_pytest.py 11/07/2021 00:22 <DIR> __pycache__ 6 File(s) 913 bytes 3 Dir(s) 42,745,831,424 bytes free
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grafana/common/dashboards/aggregated/client_subnet_statistics_detail.py
MikeAT/visualizer
6
11476
# Copyright 2021 Internet Corporation for Assigned Names and Numbers. # # This Source Code Form is subject to the terms of the Mozilla Public # License, v. 2.0. If a copy of the MPL was not distributed with this # file, you can obtain one at https://mozilla.org/MPL/2.0/. # # Developed by Sinodun IT (sinodun.com) # # Aggregation client subnet statistics import textwrap import grafanalib.core as GCore import grafanacommon as GCommon def query_classification_chart(chart_title, yaxis_label, prefix_field, agginfo, nodesel): return GCommon.BarChart( title = chart_title, orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( barmode = GCommon.BAR_CHART_LAYOUT_MODE_STACK, showlegend = True, xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = yaxis_label, ), ), traces = [ GCommon.BarChartTrace( name = 'AForA', x = 'AForA', y = 'AForAPrefix', text = 'AForA', ), GCommon.BarChartTrace( name = 'AForRoot', x = 'AForRoot', y = 'AForRootPrefix', text = 'AForRoot', ), GCommon.BarChartTrace( name = 'FunnyQueryClass', x = 'FunnyQueryClass', y = 'FunnyQueryClassPrefix', text = 'FunnyQueryClass', ), GCommon.BarChartTrace( name = 'FunnyQueryType', x = 'FunnyQueryType', y = 'FunnyQueryTypePrefix', text = 'FunnyQueryType', ), GCommon.BarChartTrace( name = 'Localhost', x = 'Localhost', y = 'LocalhostPrefix', text = 'Localhost', ), GCommon.BarChartTrace( name = 'NonAuthTld', x = 'NonAuthTld', y = 'NonAuthTldPrefix', text = 'NonAuthTld', ), GCommon.BarChartTrace( name = 'Ok', x = 'Ok', y = 'OkPrefix', text = 'Ok', ), GCommon.BarChartTrace( name = 'RFC1918Ptr', x = 'RFC1918Ptr', y = 'RFC1918PtrPrefix', text = 'RFC1918Ptr', ), GCommon.BarChartTrace( name = 'RootServersNet', x = 'RootServersNet', y = 'RootServersNetPrefix', text = 'RootServersNet', ), GCommon.BarChartTrace( name = 'SrcPortZero', x = 'SrcPortZero', y = 'SrcPortZeroPrefix', text = 'SrcPortZero', ), ], targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS AForAPrefix, AForA, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(AForACount)/($to - $from) AS AForA FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'A' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS AForRootPrefix, AForRoot, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(AForRootCount)/($to - $from) AS AForRoot FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'B' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS FunnyQueryClassPrefix, FunnyQueryClass, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(FunnyQueryClassCount)/($to - $from) AS FunnyQueryClass FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'C' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS FunnyQueryTypePrefix, FunnyQueryType, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(FunnyQueryTypeCount)/($to - $from) AS FunnyQueryType FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count DESC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'D' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS LocalhostPrefix, Localhost, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(LocalhostCount)/($to - $from) AS Localhost FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'E' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS NonAuthTldPrefix, NonAuthTld, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(NonAuthTldCount)/($to - $from) AS NonAuthTld FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'F' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS OkPrefix, Ok, TotalCount FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS TotalCount, sum(Count - (AForACount + AForRootCount + FunnyQueryClassCount + FunnyQueryTypeCount + LocalhostCount + NonAuthTldCount + RFC1918PtrCount + RootServersNetCount + SrcPortZeroCount))/($to - $from) AS Ok FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY TotalCount DESC LIMIT 40 ) ORDER BY TotalCount ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'G' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS RFC1918PtrPrefix, RFC1918Ptr, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(RFC1918PtrCount)/($to - $from) AS RFC1918Ptr FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'H' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS RootServersNetPrefix, RootServersNet, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(RootServersNetCount)/($to - $from) AS RootServersNet FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'I' ), GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Prefix AS SrcPortZeroPrefix, SrcPortZero, Count FROM ( SELECT {prefix_field} AS Prefix, sum(Count) AS Count, sum(SrcPortZeroCount)/($to - $from) AS SrcPortZero FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY Count DESC LIMIT 40 ) ORDER BY Count ASC """.format( prefix_field=prefix_field, nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'J' ), ], ) def dash(myuid, agginfo, nodesel, **kwargs): return GCommon.Dashboard( title = "Client subnet statistics detail", tags = [ agginfo['graph_tag'] ], uid = myuid, rows = [ GCore.Row( height = GCore.Pixels(50), panels = [ GCommon.HTMLPanel('grafana/common/dashboards/aggregated/client_subnet_statistics_header.html', transparent=True), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ GCommon.BarChart( title = 'Clients by fixed subnet', orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = 'Fixed Subnet', ), ), traces = [ GCommon.BarChartTrace( name = 'Subnet', color = '#A352CC', x = 'QPS', y = 'Subnet', text = 'QPS', ), ], targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'BusiestClientSubnets' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Subnet, QPS FROM ( SELECT Prefix AS Subnet, sum(Count)/($to - $from) AS QPS FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY QPS DESC LIMIT 30 ) ORDER BY QPS ASC""".format( nodesel=nodesel)), refId = 'A' ) ], ), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ GCommon.BarChart( title = 'RCODE by clients by ASN', orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( barmode = GCommon.BAR_CHART_LAYOUT_MODE_STACK, showlegend = True, xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = 'ASN', ), ), autotrace = True, targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'BusiestClientSubnets' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT notEmpty(rcodeText) ? rcodeText : concat('RCODE', toString(rcode)) AS DisplayRcode, sum(rcodeCount) / ($to - $from) AS rcodeCount, ClientASN FROM ( SELECT ClientASN, rcode, sum(rcodeCount) AS rcodeCount, any(sCount) AS sCount FROM ( SELECT ClientASN, sum(RcodeMap.Count) AS sCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY ClientASN ORDER BY sCount DESC, ClientASN ASC LIMIT 30 ) AS ClientASNCounts ALL LEFT JOIN ( SELECT ClientASN, RcodeMap.ResponseRcode AS rcode, sum(RcodeMap.Count) AS rcodeCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY ClientASN, rcode UNION ALL ( SELECT ClientASN, rcode, CAST(0 AS UInt64) AS rcodeCount FROM ( SELECT 0 AS Zero, ClientASN FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY ClientASN ) AS ZeroClientASN ALL LEFT JOIN ( SELECT 0 AS Zero, RcodeMap.ResponseRcode AS rcode FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY rcode ) AS ZeroRcode USING Zero ) ) AS ClientASNRcodeCounts USING ClientASN GROUP BY ClientASN, rcode ) AS ClientASNRcodeCountsTotal ALL INNER JOIN ( SELECT value_name AS rcodeText, toUInt16(value) AS rcode FROM {nodeinfo_database}.iana_text WHERE registry_name = 'RCODE' ) AS ClientASNNameCountsTotal USING rcode GROUP BY ClientASN, rcode, rcodeText ORDER BY sum(sCount) ASC, rcodeText ASC, ClientASN DESC""".format( nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'A' ) ], ), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ GCommon.BarChart( title = 'RCODE by clients by AS subnet', orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( barmode = GCommon.BAR_CHART_LAYOUT_MODE_STACK, showlegend = True, xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = 'AS Subnet', ), ), autotrace = True, targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'BGPPrefix' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT notEmpty(rcodeText) ? rcodeText : concat('RCODE', toString(rcode)) AS DisplayRcode, sum(rcodeCount) / ($to - $from) AS rcodeCount, Prefix FROM ( SELECT Prefix, rcode, sum(rcodeCount) AS rcodeCount, any(sCount) AS sCount FROM ( SELECT Prefix, sum(RcodeMap.Count) AS sCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY sCount DESC, Prefix ASC LIMIT 30 ) AS PrefixCount ALL LEFT JOIN ( SELECT Prefix, RcodeMap.ResponseRcode AS rcode, sum(RcodeMap.Count) AS rcodeCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix, rcode UNION ALL ( SELECT Prefix, rcode, CAST(0 AS UInt64) AS rcodeCount FROM ( SELECT 0 AS Zero, Prefix FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ) AS ZeroPrefox ALL LEFT JOIN ( SELECT 0 AS Zero, RcodeMap.ResponseRcode AS rcode FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY rcode ) AS ZeroRcode USING Zero ) ) AS PrefixRcodeCounts USING Prefix GROUP BY Prefix, rcode ) AS PrefixRcodeCountsTotal ALL INNER JOIN ( SELECT value_name AS rcodeText, toUInt16(value) AS rcode FROM {nodeinfo_database}.iana_text WHERE registry_name = 'RCODE' ) AS PrefixNameCountsTotal USING rcode GROUP BY Prefix, rcode, rcodeText ORDER BY sum(sCount) ASC, rcodeText ASC, Prefix DESC""".format( nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'A' ) ], ), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ GCommon.BarChart( title = 'RCODE by clients by fixed subnet', orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( barmode = GCommon.BAR_CHART_LAYOUT_MODE_STACK, showlegend = True, xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = 'Fixed Subnet', ), ), autotrace = True, targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'BusiestClientSubnets' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT notEmpty(rcodeText) ? rcodeText : concat('RCODE', toString(rcode)) AS DisplayRcode, sum(rcodeCount) / ($to - $from) AS rcodeCount, Prefix FROM ( SELECT Prefix, rcode, sum(rcodeCount) AS rcodeCount, any(sCount) AS sCount FROM ( SELECT Prefix, sum(RcodeMap.Count) AS sCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ORDER BY sCount DESC, Prefix ASC LIMIT 30 ) AS PrefixCount ALL LEFT JOIN ( SELECT Prefix, RcodeMap.ResponseRcode AS rcode, sum(RcodeMap.Count) AS rcodeCount FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix, rcode UNION ALL ( SELECT Prefix, rcode, CAST(0 AS UInt64) AS rcodeCount FROM ( SELECT 0 AS Zero, Prefix FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY Prefix ) AS ZeroPrefix ALL LEFT JOIN ( SELECT 0 AS Zero, RcodeMap.ResponseRcode AS rcode FROM $table ARRAY JOIN RcodeMap WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY rcode ) AS ZeroRcode USING Zero ) ) AS PrefixRcodeCounts USING Prefix GROUP BY Prefix, rcode ) AS PrefixRcodeCountsTotal ALL INNER JOIN ( SELECT value_name AS rcodeText, toUInt16(value) AS rcode FROM {nodeinfo_database}.iana_text WHERE registry_name = 'RCODE' ) AS PrefixNameCountsTotal USING rcode GROUP BY Prefix, rcode, rcodeText ORDER BY sum(sCount) ASC, rcodeText ASC, Prefix DESC""".format( nodesel=nodesel, nodeinfo_database=agginfo['nodeinfo_database'])), refId = 'A' ) ], ), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ GCommon.BarChart( title = 'Root abusers by fixed subnet', orientation = GCommon.BAR_CHART_ORIENTATION_HORIZONTAL, layout = GCommon.BarChartLayout( xaxis = GCommon.BarChartAxis( title = 'Queries per second', ), yaxis = GCommon.BarChartAxis( autotick = False, axtype = GCommon.BAR_CHART_AXIS_TYPE_CATEGORY, tickmargin = 110, title = 'Fixed Subnet', ), ), traces = [ GCommon.BarChartTrace( name = 'Subnet', color = '#A352CC', x = 'QPS', y = 'Subnet', text = 'QPS', ), ], targets = [ GCommon.ClickHouseTableTarget( database = agginfo['database'], table = 'QueryClassifications' + agginfo['table_suffix'], round = agginfo['round'], query = textwrap.dedent("""\ SELECT Subnet, QPS FROM ( SELECT FixedPrefix AS Subnet, sum(RootAbuseCount)/($to - $from) AS QPS FROM $table WHERE $timeFilter AND NodeID IN {nodesel} GROUP BY FixedPrefix ORDER BY QPS DESC LIMIT 40 ) ORDER BY QPS ASC""".format( nodesel=nodesel)), refId = 'A' ) ], ), ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ query_classification_chart( 'Query classification by busiest fixed subnet', 'Fixed Subnet', 'FixedPrefix', agginfo, nodesel) ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ query_classification_chart( 'Query classification by busiest ASN', 'ASN', 'ClientASN', agginfo, nodesel) ], ), GCore.Row( height = GCore.Pixels(GCore.DEFAULT_ROW_HEIGHT.num * 2), panels = [ query_classification_chart( 'Query classification by busiest AS subnet', 'AS subnet', 'ASPrefix', agginfo, nodesel) ], ), ] )
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742, 13, 462, 4706, 525, 3289, 1014, 1212, 742, 13, 462, 4706, 525, 3289, 23095, 742, 13, 462, 4706, 946, 29887, 3888, 29892, 13, 462, 4706, 7573, 295, 29897, 13, 18884, 21251, 13, 9651, 10353, 13, 4706, 4514, 13, 1678, 1723, 13, 2 ]
era_interim/Save_Min_Geop_Height_in_area_polygon_and_Above_Oro_era_i.py
peterwilletts24/Python-Scripts
4
1614619
import cPickle as pickle from shapely.geometry import Point, Polygon import numpy as np from netCDF4 import Dataset from scipy.interpolate import griddata p_lev = 925 geopotential, longitude_dom, latitude_dom, time_dom, time_hour = pickle.load\ (open('/nfs/a90/eepdw/Data/Saved_data/era_i/era_i_emb_time_update_large_geopotential.p', 'rb')) pressure_levels = pickle.load(open('/nfs/a90/eepdw/Data/Saved_data/era_i/era_i_emb_pressure_levels.p', 'rb')) # Monsoon Trough and Ganga Basin combined polygon = Polygon(((73., 21.), (83., 16.), (87., 22.), (90.,22.), (90.,23.8), (83., 24.2), (76.3, 28.))) # Ganga Basin #polygon = Polygon(((87., 22), (75., 27), (76.3, 30.), (83, 26.2), (90, 25.8), (90., 22))) lons_data= longitude_dom[0] lats_data = latitude_dom[0] lons_data,lats_data = np.meshgrid(lons_data, lats_data) # Find points that are within defined polygon points = np.array([[long,lat] for long, lat in zip(lons_data.flatten(), lats_data.flatten())]) intersects = np.array(map(polygon.intersects, map(Point, points))).reshape(lons_data.shape) p_lev_idx = np.where(pressure_levels==p_lev) geopotential_polygon = geopotential[:, p_lev_idx, intersects] # Do the same for surface geopotential (still in netcdf format) #nc = Dataset('/nfs/a90/eepdw/Data/Era_Interim/LandSeaMask/Land_Sea_Mask.nc') nc = Dataset('/nfs/a90/eepdw/Data/Era_Interim/Orography/era_i_geopotential.nc') ''' ECMWF give orography as geopotential, which is apparently converted to height by using the WMO gravity constant 9.80665. Ithought latitude would affect it as well but no mention http://www.ecmwf.int/en/geopotential-defined-units-m2/s2-both-pressure-levels-and-surface-orography-how-can-height-metres ''' lons,lats = np.meshgrid(nc.variables['longitude'][:], nc.variables['latitude'][:]) oro_regrid = griddata((lats.flatten(), lons.flatten()), nc.variables['z'][:].flatten(), (lats_data,lons_data), method='linear') oro_polygon = oro_regrid[intersects] vals = np.where(geopotential_polygon>(oro_polygon/9.80665), geopotential_polygon, np.nan) min_geop_full_time = np.min(vals,axis=-1)[:,0] day_mean_min_geop = [np.mean(min_geop_full_time[np.where(time_dom==day)]) for day in np.unique(time_dom)] np.savez( '/nfs/a90/eepdw/Data/Era_Interim/Era_interim_TimeVar_on_p_levs_mean_by_day_land_domain_'\ 'constrain__and_oro_not_greater_than_data_monsoon_trough_%s' % p_lev, data=day_mean_min_geop, time_coords=np.unique(time_dom), pressures=pressure_levels[p_lev_idx])
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tests/test_show.py
domi007/pigskin
6
10398
from collections import OrderedDict import pytest import vcr try: # Python 2.7 # requests's ``json()`` function returns strings as unicode (as per the # JSON spec). In 2.7, those are of type unicode rather than str. basestring # was created to help with that. # https://docs.python.org/2/library/functions.html#basestring basestring = basestring except NameError: basestring = str @pytest.mark.incremental class TestShow(object): """These don't require authentication to Game Pass.""" @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_desc(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.desc, basestring) # content is not required @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_logo(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.logo, basestring) assert show.logo @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_name(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.name, basestring) assert show.name @vcr.use_cassette('public_API/europe_show_seasons.yaml') @staticmethod def test_seasons(gp): shows = gp.shows for s in shows: show = shows[s] assert type(show.seasons) is OrderedDict assert show.seasons prev = 9999 for s in show.seasons: season = show.seasons[s] # TODO: assert it has content # TODO: assert is type season # make sure the years look sane-ish assert int(s) > 2000 and int(s) < 2050 # make sure it's sorted high to low assert int(prev) > int(s) prev = s
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backend/app/utils/fields/project.py
LiXuanqi/NuaaOversea-flask-react
0
154739
#!/usr/bin/env python # encoding: utf-8 """ File name: project.py Function Des: ... ~~~~~~~~~~ author: 1_x7 <<EMAIL>> <http://lixuanqi.github.io> """ from flask_restful import fields project_single_fields = { 'id': fields.Integer, 'name': fields.String, 'value': fields.Integer } projects_fields = { 'projects': fields.List(fields.Nested(project_single_fields)) }
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apps/backend/tests/components/collections/agent/utils.py
ZhuoZhuoCrayon/bk-nodeman
0
135061
# -*- coding: utf-8 -*- """ TencentBlueKing is pleased to support the open source community by making 蓝鲸智云-节点管理(BlueKing-BK-NODEMAN) available. Copyright (C) 2017-2021 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://opensource.org/licenses/MIT 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 from django.conf import settings from mock import MagicMock from apps.backend.api.constants import JobDataStatus, JobIPStatus from apps.backend.subscription import tools from apps.node_man import constants as const from apps.node_man import models DEFAULT_CREATOR = "admin" DEFAULT_BIZ_ID_NAME = {"bk_biz_id": "10", "bk_biz_name": "测试Pipeline原子专用"} DEFAULT_CLOUD_NAME = "直连区域" DEFAULT_AP_ID = const.DEFAULT_AP_ID DEFAULT_NODE_TYPE = "INSTANCE" DEFAULT_OBJ_TYPE = "HOST" DEFAULT_INSTANCE_ID = "host|instance|host|127.0.0.1-0-0" CALLBACK_URL = "http://127.0.0.1/backend" # ---------订阅任务id参数-------------- SUBSCRIPTION_ID = 61 SUBSCRIPTION_INSTANCE_RECORD_ID = 95 SUBSCRIPTION_TASK_ID = 91 JOB_ID = 56 JOB_TASK_ID = 100 BK_HOST_ID = 23333 # 当前原子任务id JOB_TASK_PIPELINE_ID = "1ae89ce9deec319bbd8727a0c4b2ca82" # 安装线的pipeline id INSTANCE_RECORD_ROOT_PIPELINE_ID = "98d467d07e453e1b9f24e77c8c6743fb" # 测试伪造ip TEST_IP = "127.0.0.1" # Job作业实例id JOB_INSTANCE_ID = 10000 # ---------mock path-------------- SSH_MAN_MOCK_PATH = "apps.backend.components.collections.agent.SshMan" CLIENT_V2_MOCK_PATH = "apps.backend.components.collections.agent.client_v2" JOB_CLIENT_MOCK_PATH = "apps.backend.api.job.get_client_by_user" JOB_VERSION_MOCK_PATH = "apps.backend.api.job.settings.JOB_VERSION" POLLING_TIMEOUT_MOCK_PATH = "apps.backend.components.collections.job.POLLING_TIMEOUT" # 目标主机信息 INSTANCE_INFO = { "key": "", "port": 22, "ap_id": const.DEFAULT_AP_ID, "account": "root", "os_type": const.OsType.LINUX, "login_ip": "", "password": "<PASSWORD>", "username": DEFAULT_CREATOR, "auth_type": const.AuthType.PASSWORD, "bk_biz_id": DEFAULT_BIZ_ID_NAME["bk_biz_id"], "is_manual": False, "retention": 1, "bk_os_type": const.BK_OS_TYPE[const.OsType.LINUX], "bk_biz_name": DEFAULT_BIZ_ID_NAME["bk_biz_name"], "bk_cloud_id": const.DEFAULT_CLOUD, "bk_cloud_name": DEFAULT_CLOUD_NAME, "host_node_type": const.NodeType.AGENT, "bk_host_innerip": TEST_IP, "bk_host_outerip": "", "bk_supplier_account": "0", "peer_exchange_switch_for_agent": 1, } ACT_INPUTS = { "host_info": dict(list(INSTANCE_INFO.items()) + [("bt_speed_limit", "None")]), # 注册后会填充该值 "bk_host_id": "", "description": "安装....", "blueking_language": "zh-hans", } HOST_PARAMS = { "bk_host_id": BK_HOST_ID, "bk_biz_id": DEFAULT_BIZ_ID_NAME["bk_biz_id"], "bk_cloud_id": const.DEFAULT_CLOUD, "inner_ip": TEST_IP, "outer_ip": None, "login_ip": TEST_IP, "data_ip": None, "os_type": "LINUX", "node_type": const.NodeType.AGENT, "node_from": "NODE_MAN", "ap_id": const.DEFAULT_AP_ID, "upstream_nodes": [], "is_manual": 0, "extra_data": {"bt_speed_limit": None, "peer_exchange_switch_for_agent": 1}, } IDENTITY_DATA_PARAMS = { "bk_host_id": BK_HOST_ID, "auth_type": const.AuthType.PASSWORD, "account": "root", "password": "<PASSWORD>", "port": 22, "key": "aes_str:::LXqh", "extra_data": {}, "retention": 1, } SUBSCRIPTION_PARAMS = { "id": SUBSCRIPTION_ID, "object_type": DEFAULT_OBJ_TYPE, "node_type": DEFAULT_NODE_TYPE, # 对于Pipeline原子的测试都只用一台主机 "nodes": [ { "ip": INSTANCE_INFO["bk_host_innerip"], "bk_cloud_id": const.DEFAULT_CLOUD, "instance_info": INSTANCE_INFO, "bk_supplier_account": "0", } ], "creator": DEFAULT_CREATOR, } SUBSCRIPTION_TASK_PARAMS = { "id": SUBSCRIPTION_TASK_ID, "subscription_id": SUBSCRIPTION_ID, # 根据实际创建进行修改 "scope": { "nodes": [ { "ip": INSTANCE_INFO["bk_host_innerip"], "bk_cloud_id": const.DEFAULT_CLOUD, "instance_info": INSTANCE_INFO, "bk_supplier_account": "0", } ], "node_type": DEFAULT_NODE_TYPE, "object_type": DEFAULT_OBJ_TYPE, "need_register": True, }, "actions": { # 每台主机都有一个实例id，最后根据补参重新生成 DEFAULT_INSTANCE_ID: { # 默认安装任务 "agent": const.JobType.INSTALL_AGENT } }, # 是否为自动触发 "is_auto_trigger": 0, } JOB_PARAMS = { "id": JOB_ID, "created_by": DEFAULT_CREATOR, "job_type": const.JobType.INSTALL_AGENT, "subscription_id": SUBSCRIPTION_ID, # 根据实际创建进行修改 # Pipeline原子默认只有一个安装任务 "task_id_list": [SUBSCRIPTION_TASK_ID], "status": const.JobStatusType.RUNNING, "global_params": {}, "statistics": {"total_count": 1, "failed_count": 0, "pending_count": 1, "running_count": 0, "success_count": 0}, "bk_biz_scope": [DEFAULT_BIZ_ID_NAME["bk_biz_id"]], "error_hosts": [], } JOB_TASK_PARAMS = { "id": JOB_TASK_ID, "job_id": JOB_ID, # 没有注册到cmdb之前是空 "bk_host_id": BK_HOST_ID, "instance_id": DEFAULT_INSTANCE_ID, "pipeline_id": JOB_TASK_PIPELINE_ID, "status": const.StatusType.RUNNING, "current_step": "正在安装", } SUBSCRIPTION_INSTANCE_RECORD_PARAMS = { "id": SUBSCRIPTION_INSTANCE_RECORD_ID, "task_id": SUBSCRIPTION_TASK_ID, "subscription_id": SUBSCRIPTION_ID, "instance_id": DEFAULT_INSTANCE_ID, # 安装时，注册到cmdb后会插入bk_host_id "instance_info": {"host": INSTANCE_INFO}, "steps": [ { "id": "agent", "type": const.NodeType.AGENT, "action": const.JobType.INSTALL_AGENT, "extra_info": {}, "pipeline_id": "3341978fe1f33b2b99615818df5c7a89", } ], "pipeline_id": INSTANCE_RECORD_ROOT_PIPELINE_ID, } JOB_INSTANCE_ID_METHOD_RETURN = { "result": True, "code": 0, "message": "success", "data": {"job_instance_name": "API Quick Distribution File1521101427176", "job_instance_id": JOB_INSTANCE_ID}, } JOB_GET_INSTANCE_LOG_RETURN = { "result": True, "code": 0, "message": "", "data": [ { "is_finished": True, "step_instance_id": 90000, "name": "test", "status": JobDataStatus.SUCCESS, "step_results": [ { "ip_status": JobIPStatus.SUCCESS, "tag": "xxx", "ip_logs": [ { "retry_count": 0, "total_time": 60.599, "start_time": "2020-08-05 14:39:30 +0800", "end_time": "2020-08-05 14:40:31 +0800", "ip": TEST_IP, "bk_cloud_id": 0, "error_code": 0, "exit_code": 0, "log_content": "success", } ], } ], } ], } GET_JOB_INSTANCE_STATUS_V2_C_RETURN = { "is_finished": False, "job_instance": { "job_instance_id": JOB_INSTANCE_ID, "bk_biz_id": DEFAULT_BIZ_ID_NAME["bk_biz_id"], "name": "API Quick execution script1521089795887", "operator": DEFAULT_CREATOR, "bk_job_id": 4355, "create_time": "2018-03-15 12:56:35 +0800", "status": JobDataStatus.PENDING, }, } # 适用于 client_v2 JOB_INSTANCE_ID_METHOD_V2_C_RETURN = JOB_INSTANCE_ID_METHOD_RETURN["data"] class SshManMockClient: def __init__( self, get_and_set_prompt_return=None, send_cmd_return_return=None, safe_close_return=None, ssh_return=None, ): self.get_and_set_prompt = MagicMock(return_value=get_and_set_prompt_return) self.send_cmd = MagicMock(return_value=send_cmd_return_return) self.safe_close = MagicMock(return_value=safe_close_return) self.ssh = MagicMock(return_value=ssh_return) class GseMockClient: def __init__(self, get_agent_status_return=None, get_agent_info_return=None): self.gse = MagicMock() self.gse.get_agent_status = MagicMock(return_value=get_agent_status_return) self.gse.get_agent_info = MagicMock(return_value=get_agent_info_return) class CMDBMockClient: def __init__( self, add_host_to_resource_result=None, search_business_result=None, list_biz_hosts_result=None, list_hosts_without_biz_result=None, find_host_biz_relations_result=None, ): self.cc = MagicMock() self.cc.add_host_to_resource = MagicMock(return_value=add_host_to_resource_result) self.cc.search_business = MagicMock(return_value=search_business_result) self.cc.list_biz_hosts = MagicMock(return_value=list_biz_hosts_result) self.cc.list_hosts_without_biz = MagicMock(return_value=list_hosts_without_biz_result) self.cc.find_host_biz_relations = MagicMock(return_value=find_host_biz_relations_result) class JobMockClient: def __init__( self, fast_execute_script_return=None, get_job_instance_log_return=None, fast_push_file_return=None, push_config_file_return=None, get_job_instance_status_return=None, ): self.job = MagicMock() self.job.fast_execute_script = MagicMock(return_value=fast_execute_script_return) self.job.get_job_instance_log = MagicMock(return_value=get_job_instance_log_return) self.job.fast_push_file = MagicMock(return_value=fast_push_file_return) self.job.push_config_file = MagicMock(return_value=push_config_file_return) self.job.get_job_instance_status = MagicMock(return_value=get_job_instance_status_return) class AgentTestObjFactory: @classmethod def replace_obj_attr_values(cls, obj, obj_attr_values): # 原地修改 if obj_attr_values is None: return obj for attr, value in obj_attr_values.items(): if attr not in obj: continue obj[attr] = value @classmethod def inputs(cls, attr_values=None, instance_info_attr_values=None): instance_info = copy.deepcopy(INSTANCE_INFO) inputs = copy.deepcopy(ACT_INPUTS) cls.replace_obj_attr_values(instance_info, instance_info_attr_values) inputs["host_info"] = dict(list(instance_info.items()) + [("bt_speed_limit", "None")]) if "bt_speed_limit" in instance_info_attr_values: inputs["host_info"]["bt_speed_limit"] = instance_info_attr_values["bt_speed_limit"] cls.replace_obj_attr_values(inputs, attr_values) return inputs @classmethod def subscription_obj(cls, obj_attr_values=None, instance_info_attr_values=None, is_obj=False): instance_info = copy.deepcopy(INSTANCE_INFO) subscription_params = copy.deepcopy(SUBSCRIPTION_PARAMS) cls.replace_obj_attr_values(instance_info, instance_info_attr_values) if instance_info_attr_values is not None: subscription_params["nodes"][0]["instance_info"] = instance_info subscription_params["nodes"][0]["ip"] = instance_info["bk_host_innerip"] cls.replace_obj_attr_values(subscription_params, obj_attr_values) if not is_obj: subscription_params.pop("id", None) return models.Subscription(**subscription_params) if is_obj else subscription_params @classmethod def subscription_task_obj(cls, obj_attr_values=None, instance_info_attr_values=None, is_obj=False): instance_info = copy.deepcopy(INSTANCE_INFO) subscription_task_params = copy.deepcopy(SUBSCRIPTION_TASK_PARAMS) cls.replace_obj_attr_values(instance_info, instance_info_attr_values) if instance_info_attr_values is not None: subscription_task_params["scope"]["nodes"][0]["instance_info"] = instance_info subscription_task_params["scope"]["nodes"][0]["ip"] = instance_info["bk_host_innerip"] instance_id = tools.create_node_id( { "object_type": DEFAULT_OBJ_TYPE, "node_type": DEFAULT_NODE_TYPE, "bk_cloud_id": instance_info["bk_cloud_id"], "ip": instance_info["bk_host_innerip"], } ) subscription_task_params["actions"].pop(DEFAULT_INSTANCE_ID) subscription_task_params["actions"] = {instance_id: {"agent": const.JobType.INSTALL_AGENT}} cls.replace_obj_attr_values(subscription_task_params, obj_attr_values) if not is_obj: subscription_task_params.pop("id", None) return models.SubscriptionTask(**subscription_task_params) if is_obj else subscription_task_params @classmethod def subscription_instance_record_obj(cls, obj_attr_values=None, instance_info_attr_values=None, is_obj=False): instance_info = copy.deepcopy(INSTANCE_INFO) subscription_instance_record_params = copy.deepcopy(SUBSCRIPTION_INSTANCE_RECORD_PARAMS) cls.replace_obj_attr_values(instance_info, instance_info_attr_values) if instance_info_attr_values is not None: subscription_instance_record_params["instance_info"]["host"] = instance_info subscription_instance_record_params["instance_id"] = tools.create_node_id( { "object_type": DEFAULT_OBJ_TYPE, "node_type": DEFAULT_NODE_TYPE, "bk_cloud_id": instance_info["bk_cloud_id"], "ip": instance_info["bk_host_innerip"], } ) cls.replace_obj_attr_values(subscription_instance_record_params, obj_attr_values) return ( models.SubscriptionInstanceRecord(**subscription_instance_record_params) if is_obj else subscription_instance_record_params ) @classmethod def job_obj(cls, obj_attr_values=None, is_obj=False): job_params = copy.deepcopy(JOB_PARAMS) cls.replace_obj_attr_values(job_params, obj_attr_values) if not is_obj: job_params.pop("id", None) return models.Job(**job_params) if is_obj else job_params @classmethod def job_task_obj(cls, obj_attr_values=None, is_obj=False): job_task_params = copy.deepcopy(JOB_TASK_PARAMS) cls.replace_obj_attr_values(job_task_params, obj_attr_values) if not is_obj: job_task_params.pop("id", None) return models.JobTask(**job_task_params) if is_obj else job_task_params @classmethod def identity_data_obj(cls, obj_attr_values=None, is_obj=False): identity_data_params = copy.deepcopy(IDENTITY_DATA_PARAMS) cls.replace_obj_attr_values(identity_data_params, obj_attr_values) if not is_obj: identity_data_params.pop("id", None) return models.IdentityData(**identity_data_params) if is_obj else identity_data_params @classmethod def host_obj(cls, obj_attr_values=None, is_obj=False): host_params = copy.deepcopy(HOST_PARAMS) cls.replace_obj_attr_values(host_params, obj_attr_values) if not is_obj: host_params.pop("id", None) return models.Host(**host_params) if is_obj else host_params @classmethod def init_db(cls): # 初始化callback_url settings.BKAPP_NODEMAN_CALLBACK_URL = CALLBACK_URL settings.BKAPP_NODEMAN_OUTER_CALLBACK_URL = CALLBACK_URL subscription_params = cls.subscription_obj() subscription = models.Subscription.objects.create(**subscription_params) subscription_task_params = cls.subscription_task_obj(obj_attr_values={"subscription_id": subscription.id}) subscription_task = models.SubscriptionTask.objects.create(**subscription_task_params) subscription_instance_record_params = cls.subscription_instance_record_obj( obj_attr_values={"subscription_id": subscription.id, "task_id": subscription_task.id} ) subscription_instance_record = models.SubscriptionInstanceRecord.objects.create( **subscription_instance_record_params ) job_params = cls.job_obj( obj_attr_values={"subscription_id": subscription.id, "task_id_list": [subscription_task.id]} ) job = models.Job.objects.create(**job_params) job_task_params = cls.job_task_obj({"job_id": job.id}) job_task = models.JobTask.objects.create(**job_task_params) host_params = cls.host_obj() host = models.Host.objects.create(**host_params) identity_data_params = cls.identity_data_obj() models.IdentityData.objects.create(**identity_data_params) return { "subscription_id": subscription.id, "subscription_task_id": subscription_task.id, "subscription_instance_record_id": subscription_instance_record.id, "job_id": job.id, "job_task_id": job_task.id, "bk_host_id": host.bk_host_id, }
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dsharpy/tools.py
parttimenerd/dsharpy
1
94166
""" Utilities not directly related to formulas or CNFs """ import logging import math import os import re import shutil import subprocess import tempfile from typing import TYPE_CHECKING, Dict, Set, Tuple, Iterable from dsharpy.preprocess import preprocess_c_code from pathlib import Path from tempfile import NamedTemporaryFile from typing import List, Union, Any logging.basicConfig(level=logging.WARNING) def pprint(x: Any): import prettyprinter prettyprinter.install_extras(exclude=['ipython', 'ipython_repr_pretty']) prettyprinter.pprint(x) class Tool: OUTPUT_PREFIX = "__out" def __init__(self, name: str, binary: str): self.name = name self.binary_path = Path(binary.replace("TOOLS", str(Path(__file__).parent.parent.absolute() / "tools"))) assert self._check_binary(), f"Binary for {name} ({self.binary_path}) not found" def _check_binary(self): try: subprocess.run([str(self.binary_path), "-h"], check=True, capture_output=False, stdout=subprocess.DEVNULL) return True except subprocess.CalledProcessError: return False def _process(self, arguments: List[Any], env_vars: Dict[str, Any], interpreter: str = None, cwd: Path = None) -> str: env = os.environ.copy() for key, value in env_vars.items(): env[key] = str(value) cmd = ([interpreter] if interpreter else []) + [str(self.binary_path)] + [str(x) for x in arguments] logging.info(cmd) res = subprocess.run(cmd, stdout=subprocess.PIPE, bufsize=-1, stderr=subprocess.PIPE, env=env, cwd=str(cwd) if cwd else os.getcwd()) err = res.stderr.decode() out = res.stdout.decode() if "Failed" in err or "Usage" in err or "ERROR" in err or "exception" in err \ or " failed" in err or "segmentation fault" in err \ or "segmentation fault" in out or res.returncode != 0: logging.error(out) logging.error(err) for argument in arguments: if str(argument).endswith(".cpp") and isinstance(argument, Path) and argument.exists(): logging.error(argument.read_text()) raise RuntimeError(f"{self.name}: " + err) return out @staticmethod def _preprocess(tmp_dir: Path, code: Union[str, Path]) -> Path: code: str = code if isinstance(code, str) else code.read_text() with NamedTemporaryFile(suffix=".cpp", dir=tmp_dir, delete=False) as f: f.write(preprocess_c_code(code, Tool.OUTPUT_PREFIX).encode()) f.flush() return Path(f.name) class ModelChecker(Tool): def __init__(self, name: str, binary: str, unwind: int, bit_width: int = 32): super(ModelChecker, self).__init__(name, binary) self.unwind = unwind self.bit_width = bit_width self._problem_line_re = re.compile('((p cnf)|(c __rel__ p)) [0-9]+ [0-9]+\n') def setup_for(self, lc: "LeakageComputer"): pass def _is_problem_line(self, line: str) -> bool: return bool(self._problem_line_re.match(line)) def _filter_lines(self, lines: List[str]) -> Iterable[str]: has_seen_problem_line = False for line in lines: if not has_seen_problem_line: if self._is_problem_line(line): yield line has_seen_problem_line = True continue if line.startswith("c ") or line.endswith(" 0\n"): yield line def process(self, tmp_dir: Path, code: Union[str, Path]) -> Path: code = Tool._preprocess(tmp_dir, code) with NamedTemporaryFile(suffix=".cnf", dir=tmp_dir, delete=False) as f: f.writelines(l.encode() for l in self._filter_lines(self._process(self._arguments(code), self._env_vars(code)).splitlines(keepends=True))) return Path(f.name) def _env_vars(self, code: Path) -> Dict[str, Any]: return {} def _arguments(self, code: Path) -> List[Any]: return [] class CBMCBase(ModelChecker): def __init__(self, name: str, unwind: int = 32, bit_width: int = 32): super(CBMCBase, self).__init__(name, f"TOOLS/{name}/build/bin/cbmc", unwind, bit_width) def setup_for(self, lc: "LeakageComputer"): assert not lc.requires_rel() def _env_vars(self, code: Path) -> Dict[str, Any]: return {} def _arguments(self, code: Path) -> List[Any]: return [code, f"--{self.bit_width}", "--unwind", self.unwind, "--dimacs", "--partial-loops"] class CBMC(CBMCBase): def __init__(self, unwind: int = 32, bit_width: int = 32): super(CBMC, self).__init__("cbmc", unwind, bit_width) class ModifiedCBMC(CBMCBase): """ CBMC with loop and recursion approximation """ def __init__(self, unwind: int = 32, bit_width: int = 32): super(ModifiedCBMC, self).__init__("modified_cbmc", unwind + 2, bit_width) assert self.unwind >= 1 self.real_unwind = unwind self.only_rel = False def setup_for(self, lc: "LeakageComputer"): self.only_rel = lc.requires_rel() def _env_vars(self, code: Path) -> Dict[str, Any]: return {"REC": self.real_unwind - 1, **({"RELATIONS": "1", "OMIT_SAT": "1"} if self.only_rel else {})} class LeakageComputer(Tool): def __init__(self, name: str, binary: str, output_method: str = "main"): super(LeakageComputer, self).__init__(name, binary) self.output_method = output_method def requires_rel(self) -> bool: raise NotImplementedError() def process(self, cnf_file: Path) -> float: return self._parse_output(self._process(self._arguments(cnf_file), env_vars={})) def _arguments(self, cnf_file: Path) -> List[Any]: raise NotImplementedError() def _parse_output(self, out: str) -> float: raise NotImplementedError() class RelationsCutter(LeakageComputer): def __init__(self, output_method: str = "main", input_prefixes: List[str] = None): super(RelationsCutter, self).__init__("relationscutter", "TOOLS/relationscutter/build/relationscutter", output_method) self.input_prefixes = input_prefixes or ["symex::nondet"] def requires_rel(self) -> bool: return True def _arguments(self, cnf_file: Path) -> List[Any]: return [cnf_file, "--method", self.output_method, "--input", ",".join(self.input_prefixes), "--output", Tool.OUTPUT_PREFIX] def _parse_output(self, out: str) -> float: return float(out.split("Leakage: ")[1].split("\n")[0]) class ApproxFlow(LeakageComputer): """ Reimplementation of ApproxFlow, it is far simpler as the code preprocessing is simpler Based on https://github.com/parttimenerd/approxflow/blob/master/ApproxFlow.py """ def __init__(self, output_method: str = "main", epsilon: float = 0.8, delta: float = 0.2): super(ApproxFlow, self).__init__("approxflow", "TOOLS/approxmc", output_method) self.delta = delta self.epsilon = epsilon def requires_rel(self) -> bool: return False def _get_ind_vars(self, cnf_file: Path) -> Set[int]: # based on https://github.com/parttimenerd/approxflow/blob/master/ApproxFlow.py # search for __out…!i@j#k, and assume only k changes re_to_match = re.compile(f"({Tool.OUTPUT_PREFIX}[0-9]*)![0-9]+@[0-9]+#[0-9]+") variables: Dict[str, Tuple[int, Set[int]]] = {} max_lits = None for line in cnf_file.open(): if line.startswith("c") and (" " + self.output_method + "::") in line: match = re_to_match.search(line) if match: assert (len(match.groups()) == 1) variable, ijk = match.group(0).split(Tool.OUTPUT_PREFIX, maxsplit=1)[1].split("!", maxsplit=1) new_k = int(ijk.split("#")[1]) old_k = variables[variable][0] if variable in variables else -1 sat_vars = {abs(int(var)) for var in line.split()[2:] if var.lower() not in ["true", "false"]} if new_k > old_k: variables[variable] = (new_k, sat_vars) if new_k == old_k: variables[variable][1].update(sat_vars) return {x for _, v in variables.items() for x in v[1]} def _arguments(self, cnf_file: Path) -> List[Any]: with NamedTemporaryFile(suffix=".cnf", dir=cnf_file.parent, delete=False) as f: shutil.copy(cnf_file, f.name) with Path(f.name).open("a") as of: of.write(f"c ind {' '.join(map(str, self._get_ind_vars(cnf_file)))} 0\n") return ["--input", f.name] def _parse_output(self, out: str) -> float: [multiplier, power] = out.split("Number of solutions is:")[1].split("\n")[0].split("*", 1) [base, exponent] = power.split("**") multiplier = int(multiplier) base = int(base) exponent = int(exponent) solutions = multiplier * base ** exponent return math.log(solutions, 2) def process(model_checker: ModelChecker, leakage_computer: LeakageComputer, code: Union[str, Path]) -> float: model_checker.setup_for(leakage_computer) with tempfile.TemporaryDirectory() as tmp_dir: return leakage_computer.process(model_checker.process(tmp_dir, code)) MODEL_CHECKERS = { "modified_cbmc": lambda unwind, **kwargs: ModifiedCBMC(unwind, **kwargs), "cbmc": lambda unwind, **kwargs: CBMC(unwind, **kwargs) } LEAKAGE_COMPUTERS = { "approxflow": lambda **kwargs: ApproxFlow(**kwargs), "relationscutter": lambda **kwargs: RelationsCutter(**kwargs) }
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os_migrate/plugins/modules/import_workload_create_instance.py
jbadiapa/os-migrate
35
13458
#!/usr/bin/python from __future__ import (absolute_import, division, print_function) __metaclass__ = type ANSIBLE_METADATA = { 'metadata_version': '1.1', 'status': ['preview'], 'supported_by': 'community' } DOCUMENTATION = ''' --- module: import_workload_create_instance short_description: Create NBD exports of OpenStack volumes extends_documentation_fragment: openstack version_added: "2.9.0" author: "OpenStack tenant migration tools (@os-migrate)" description: - "Take an instance from an OS-Migrate YAML structure, and export its volumes over NBD." options: auth: description: - Dictionary with parameters for chosen auth type on the destination cloud. required: true type: dict auth_type: description: - Auth type plugin for destination OpenStack cloud. Can be omitted if using password authentication. required: false type: str region_name: description: - Destination OpenStack region name. Can be omitted if using default region. required: false type: str availability_zone: description: - Availability zone. required: false type: str cloud: description: - Ignored. Present for backwards compatibility. required: false type: raw validate_certs: description: - Validate HTTPS certificates when logging in to OpenStack. required: false type: bool data: description: - Data structure with server parameters as loaded from OS-Migrate workloads YAML file. required: true type: dict block_device_mapping: description: - A block_device_mapping_v2 structure from the transfer_volumes module. - Used to attach destination volumes to the new instance in the right order. required: true type: list elements: dict ''' EXAMPLES = ''' main.yml: - name: validate loaded resources os_migrate.os_migrate.validate_resource_files: paths: - "{{ os_migrate_data_dir }}/workloads.yml" register: workloads_file_validation when: import_workloads_validate_file - name: read workloads resource file os_migrate.os_migrate.read_resources: path: "{{ os_migrate_data_dir }}/workloads.yml" register: read_workloads - name: get source conversion host address os_migrate.os_migrate.os_conversion_host_info: auth: auth_url: https://src-osp:13000/v3 username: migrate password: <PASSWORD> project_domain_id: default project_name: migration-source user_domain_id: default server_id: ce4dda96-5d8e-4b67-aee2-9845cdc943fe register: os_src_conversion_host_info - name: get destination conversion host address os_migrate.os_migrate.os_conversion_host_info: auth: auth_url: https://dest-osp:13000/v3 username: migrate password: <PASSWORD> project_domain_id: default project_name: migration-destination user_domain_id: default server_id: 2d2afe57-ace5-4187-8fca-5f10f9059ba1 register: os_dst_conversion_host_info - name: import workloads include_tasks: workload.yml loop: "{{ read_workloads.resources }}" workload.yml: - block: - name: preliminary setup for workload import os_migrate.os_migrate.import_workload_prelim: auth: auth_url: https://dest-osp:13000/v3 username: migrate password: <PASSWORD> project_domain_id: default project_name: migration-destination user_domain_id: default validate_certs: False src_conversion_host: "{{ os_src_conversion_host_info.openstack_conversion_host }}" src_auth: auth_url: https://src-osp:13000/v3 username: migrate password: <PASSWORD> project_domain_id: default project_name: migration-source user_domain_id: default src_validate_certs: False data: "{{ item }}" data_dir: "{{ os_migrate_data_dir }}" register: prelim - debug: msg: - "{{ prelim.server_name }} log file: {{ prelim.log_file }}" - "{{ prelim.server_name }} progress file: {{ prelim.state_file }}" when: prelim.changed - name: expose source volumes os_migrate.os_migrate.import_workload_export_volumes: auth: "{{ os_migrate_src_auth }}" auth_type: "{{ os_migrate_src_auth_type|default(omit) }}" region_name: "{{ os_migrate_src_region_name|default(omit) }}" validate_certs: "{{ os_migrate_src_validate_certs|default(omit) }}" ca_cert: "{{ os_migrate_src_ca_cert|default(omit) }}" client_cert: "{{ os_migrate_src_client_cert|default(omit) }}" client_key: "{{ os_migrate_src_client_key|default(omit) }}" conversion_host: "{{ os_src_conversion_host_info.openstack_conversion_host }}" data: "{{ item }}" log_file: "{{ os_migrate_data_dir }}/{{ prelim.server_name }}.log" state_file: "{{ os_migrate_data_dir }}/{{ prelim.server_name }}.state" ssh_key_path: "{{ os_migrate_conversion_keypair_private_path }}" register: exports when: prelim.changed - name: transfer volumes to destination os_migrate.os_migrate.import_workload_transfer_volumes: auth: "{{ os_migrate_dst_auth }}" auth_type: "{{ os_migrate_dst_auth_type|default(omit) }}" region_name: "{{ os_migrate_dst_region_name|default(omit) }}" validate_certs: "{{ os_migrate_dst_validate_certs|default(omit) }}" ca_cert: "{{ os_migrate_dst_ca_cert|default(omit) }}" client_cert: "{{ os_migrate_dst_client_cert|default(omit) }}" client_key: "{{ os_migrate_dst_client_key|default(omit) }}" data: "{{ item }}" conversion_host: "{{ os_dst_conversion_host_info.openstack_conversion_host }}" ssh_key_path: "{{ os_migrate_conversion_keypair_private_path }}" transfer_uuid: "{{ exports.transfer_uuid }}" src_conversion_host_address: "{{ os_src_conversion_host_info.openstack_conversion_host.address }}" volume_map: "{{ exports.volume_map }}" state_file: "{{ os_migrate_data_dir }}/{{ prelim.server_name }}.state" log_file: "{{ os_migrate_data_dir }}/{{ prelim.server_name }}.log" register: transfer when: prelim.changed - name: create destination instance os_migrate.os_migrate.import_workload_create_instance: auth: "{{ os_migrate_dst_auth }}" auth_type: "{{ os_migrate_dst_auth_type|default(omit) }}" region_name: "{{ os_migrate_dst_region_name|default(omit) }}" validate_certs: "{{ os_migrate_dst_validate_certs|default(omit) }}" ca_cert: "{{ os_migrate_dst_ca_cert|default(omit) }}" client_cert: "{{ os_migrate_dst_client_cert|default(omit) }}" client_key: "{{ os_migrate_dst_client_key|default(omit) }}" data: "{{ item }}" block_device_mapping: "{{ transfer.block_device_mapping }}" register: os_migrate_destination_instance when: prelim.changed rescue: - fail: msg: "Failed to import {{ item.params.name }}!" ''' RETURN = ''' server_id: description: The ID of the newly created server. returned: On successful creation of migrated server on destination cloud. type: str sample: 059635b7-451f-4a64-978a-7c2e9e4c15ff ''' from ansible.module_utils.basic import AnsibleModule # Import openstack module utils from ansible_collections.openstack.cloud.plugins as per ansible 3+ try: from ansible_collections.openstack.cloud.plugins.module_utils.openstack \ import openstack_full_argument_spec, openstack_cloud_from_module except ImportError: # If this fails fall back to ansible < 3 imports from ansible.module_utils.openstack \ import openstack_full_argument_spec, openstack_cloud_from_module from ansible_collections.os_migrate.os_migrate.plugins.module_utils import server def run_module(): argument_spec = openstack_full_argument_spec( auth=dict(type='dict', no_log=True, required=True), data=dict(type='dict', required=True), block_device_mapping=dict(type='list', required=True, elements='dict'), ) result = dict( changed=False, ) module = AnsibleModule( argument_spec=argument_spec, ) sdk, conn = openstack_cloud_from_module(module) block_device_mapping = module.params['block_device_mapping'] ser_server = server.Server.from_data(module.params['data']) sdk_server = ser_server.create(conn, block_device_mapping) # Some info (e.g. flavor ID) will only become available after the # server is in ACTIVE state, we need to wait for it. sdk_server = conn.compute.wait_for_server(sdk_server, failures=['ERROR'], wait=600) dst_ser_server = server.Server.from_sdk(conn, sdk_server) if sdk_server: result['changed'] = True result['server'] = dst_ser_server.data result['server_id'] = sdk_server.id module.exit_json(**result) def main(): run_module() if __name__ == '__main__': main()
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pathlib__examples/syntax_path.py
DazEB2/SimplePyScripts
117
187826
<filename>pathlib__examples/syntax_path.py #!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'ipetrash' # C:\Windows\System32\Boot import pathlib path = pathlib.Path('C:/') / 'Windows' / 'System32' / 'Boot' print(path) # C:\Windows\System32\Boot
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dialogs/mmread.py
swprojects/Serial-Sequence-Creator
1
192505
<gh_stars>1-10 """ Description: Requirements: pySerial, wxPython Phoenix glossary and of other descriptions: DMM - digital multimeter PSU - power supply SBC - single board computer INS - general instrument commands GEN - general sequence instructions """ import json import logging import serial import serialfunctions as sf import sys import time import wx import theme from wx.lib.pubsub import setuparg1 from wx.lib.pubsub import pub import base # from wx.lib.agw import spinctrl OHM = "Ω" MULTIMETER_SCPI = [(), (), (), (),] INSTRUCTIONS = [("DMM", "Voltage", "Read Voltage"), ("INS", "General", "Reset Instrument"), ("INS", "General", "Power Off Instrument"), ("PSU", "Current", "Set Current Limit"), ("PSU", "Voltage", "Set Voltage"), ("PSU", "Voltage", "Step Voltage"), ("SBC", "CAN", "Send Message")] #------------------------------------------------# # add action to sequence pop-up frames #------------------------------------------------# class AddStepVoltage(wx.Dialog): def __init__(self, parent): wx.Dialog.__init__(self, parent, title="Step Voltage") panel = wx.Panel(self) sizer = wx.BoxSizer(wx.VERTICAL) hsizer = wx.BoxSizer(wx.HORIZONTAL) sbox = wx.StaticBox(panel, label="Test Setup: Step Voltage") sbox_sizer = wx.StaticBoxSizer(sbox, wx.HORIZONTAL) grid = wx.GridBagSizer(5,5) row = 0 row += 1 #let's start at 1, to give some space lbl_psu = wx.StaticText(panel, label="Power Supply:") choices = [] self.cbox_psu = wx.ComboBox(panel, choices=choices) grid.Add(lbl_psu, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.cbox_psu, pos=(row,1), span=(0,3), flag=wx.ALL|wx.EXPAND, border=5) grid.AddGrowableCol(1) row += 1 lbl_initial = wx.StaticText(panel, label="Initial Voltage:") self.spin_initial = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_initial2 = wx.SpinCtrl(panel, max=99, min=0, size=(50, -1)) self.spin_initial.Bind(wx.EVT_SPINCTRL, self.OnSpinInitial) self.spin_initial2.Bind(wx.EVT_SPINCTRL, self.OnSpinInitial) self.lbl_voltage = wx.StaticText(panel, label="0.0v") grid.Add(lbl_initial, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.spin_initial, pos=(row,1), flag=wx.ALL, border=5) grid.Add(self.spin_initial2, pos=(row,2), flag=wx.ALL, border=5) grid.Add(self.lbl_voltage, pos=(row,3), flag=wx.ALL, border=5) row += 1 lbl_final = wx.StaticText(panel, label="Final Voltage (Limit):") self.spin_final = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_final2 = wx.SpinCtrl(panel, max=99, min=0, size=(50, -1)) self.spin_final.Bind(wx.EVT_SPINCTRL, self.OnSpinFinal) self.spin_final2.Bind(wx.EVT_SPINCTRL, self.OnSpinFinal) self.lbl_voltage2 = wx.StaticText(panel, label="0.0v") grid.Add(lbl_final, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.spin_final, pos=(row,1), flag=wx.ALL, border=5) grid.Add(self.spin_final2, pos=(row,2), flag=wx.ALL, border=5) grid.Add(self.lbl_voltage2, pos=(row,3), flag=wx.ALL, border=5) row += 1 lbl_step = wx.StaticText(panel, label="Voltage Increment/Decrement:") self.spin_step = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_step2 = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_step.Bind(wx.EVT_SPINCTRL, self.OnSpinStep) self.spin_step2.Bind(wx.EVT_SPINCTRL, self.OnSpinStep) self.lbl_step2 = wx.StaticText(panel, label="0.0v") grid.Add(lbl_step, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.spin_step, pos=(row,1), flag=wx.ALL, border=5) grid.Add(self.spin_step2, pos=(row,2), flag=wx.ALL, border=5) grid.Add(self.lbl_step2, pos=(row,3), flag=wx.ALL, border=5) row += 1 lbl_step_delay = wx.StaticText(panel, label="Increment/decrement delay (ms):") self.spin_step_delay = wx.SpinCtrl(panel, max=0, min=0, size=(50, -1)) grid.Add(lbl_step_delay, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.spin_step_delay, pos=(row,1), span=(0,2), flag=wx.ALL, border=5) row += 1 lbl_repeat = wx.StaticText(panel, label="Repeat:") spin_repeat = wx.SpinCtrl(panel, max=999, min=0, size=(50, -1)) grid.Add(lbl_repeat, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(spin_repeat, pos=(row,1), flag=wx.ALL|wx.EXPAND, border=5) row += 1 # hsizer = wx.BoxSizer(wx.HORIZONTAL) lbl_read = wx.StaticText(panel, label="Read Voltage:") choices = ["Choose on execution"] self.cbox_read = wx.ComboBox(panel, choices=choices, value=choices[0]) grid.Add(lbl_read, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid.Add(self.cbox_read, pos=(row,1), span=(0,3), flag=wx.ALL|wx.EXPAND, border=5) sbox_sizer.Add(grid, 1, wx.ALL|wx.EXPAND, 0) sbox_sizer.AddSpacer(20) #rhs staticboxsizer sbox2 = wx.StaticBox(panel, label="Pass/Fail Condition") sbox_sizer2 = wx.StaticBoxSizer(sbox2, wx.HORIZONTAL) vsizer = wx.BoxSizer(wx.VERTICAL) vsizer.AddSpacer(20) grid2 = wx.GridBagSizer(2,2) row = 0 vars = ["V - Voltage reading (V)", "I - Current reading (A)", "R - Resistance reading (%s)" %OHM] conditions = ["in range", "not in range", "in % range", "not in % range", "> (greater than)", ">= (greater than/equal to)", "< (less than)", "<= (less than/equal to)"] self.cbox_var = wx.ComboBox(panel, choices=vars, name="reading", style=wx.CB_READONLY) self.cbox_var.Bind(wx.EVT_COMBOBOX, self.OnComboBox) self.cbox_var.SetSelection(0) self.cbox_conditions = wx.ComboBox(panel, choices=conditions, name="condition", style=wx.CB_READONLY) self.cbox_conditions.Bind(wx.EVT_COMBOBOX, self.OnComboBox) self.cbox_conditions.SetSelection(0) grid2.Add(self.cbox_var, pos=(row,1), span=(0, 0), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.cbox_conditions, pos=(row,2), span=(0, 0), flag=wx.ALL|wx.EXPAND, border=5) row += 1 lbl_testvar_a = wx.StaticText(panel, label="Value 1:") self.spin_var_a = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_var_a.Bind(wx.EVT_SPINCTRL, self.OnSpinVarA) self.spin_var_a2 = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_var_a2.Bind(wx.EVT_SPINCTRL, self.OnSpinVarA) self.lbl_var_a = wx.StaticText(panel, label="0.0V") grid2.Add(lbl_testvar_a, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.spin_var_a, pos=(row,1), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.spin_var_a2, pos=(row,2), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.lbl_var_a, pos=(row,3), flag=wx.ALL|wx.EXPAND, border=5) row += 1 lbl_testvar_b = wx.StaticText(panel, label="Value 2:") self.spin_var_b = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_var_b.Bind(wx.EVT_SPINCTRL, self.OnSpinVarB) self.spin_var_b2 = wx.SpinCtrl(panel, max=30, min=0, size=(50, -1)) self.spin_var_b2.Bind(wx.EVT_SPINCTRL, self.OnSpinVarB) self.lbl_var_b = wx.StaticText(panel, label="0.0V") grid2.Add(lbl_testvar_b, pos=(row,0), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.spin_var_b, pos=(row,1), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.spin_var_b2, pos=(row,2), flag=wx.ALL|wx.EXPAND, border=5) grid2.Add(self.lbl_var_b, pos=(row,3), flag=wx.ALL|wx.EXPAND, border=5) grid2.AddGrowableCol(0) vsizer.Add(grid2, 0, wx.ALL|wx.EXPAND, 5) vsizer.Add(wx.StaticLine(panel), 0, wx.ALL|wx.EXPAND, 5) hsizer_radios = wx.BoxSizer(wx.HORIZONTAL) lbl_fail = wx.StaticText(panel, label="On Test Failure:") hsizer_radios.Add(lbl_fail, 0, wx.ALL|wx.EXPAND, 5) for label in ["Continue", "Stop", "Ask on failure"]: radio = wx.RadioButton(panel, label=label) radio.Bind(wx.EVT_RADIOBUTTON, self.OnRadioButton) hsizer_radios.Add(radio, 0, wx.ALL|wx.EXPAND, 5) vsizer.Add(hsizer_radios, 0, wx.ALL|wx.EXPAND, 5) sbox_sizer2.Add(vsizer, 1, wx.ALL|wx.EXPAND, 5) # add static boxes to hsizer hsizer.Add(sbox_sizer, 0, wx.ALL|wx.EXPAND, 5) hsizer.Add(sbox_sizer2, 0, wx.ALL|wx.EXPAND, 5) #----- hsizer2 = wx.BoxSizer(wx.HORIZONTAL) hsizer2.AddStretchSpacer() btn_cancel = wx.Button(panel, label="Cancel") btn_cancel.Bind(wx.EVT_BUTTON, self.OnButton) btn_confirm = wx.Button(panel, label="Confirm") btn_confirm.Bind(wx.EVT_BUTTON, self.OnButton) hsizer2.Add(btn_cancel, 0, wx.ALL|wx.EXPAND, 5) hsizer2.Add(btn_confirm, 0, wx.ALL|wx.EXPAND, 5) #add to main sizer sizer.Add(hsizer, 0, wx.ALL|wx.EXPAND, 2) sizer.Add(hsizer2, 0, wx.ALL|wx.EXPAND, 5) panel.SetSizer(sizer) w, h = sizer.Fit(self) # self.SetSize((w, h*1.5)) # self.SetMinSize((w, h*1.5)) # self.SetMaxSize(sizer.Fit(self)) try: self.SetIcon(theme.GetIcon("psu_png")) except: pass # self.Bind(wx.EVT_KEY) def OnSpinInitial(self, event=None): v0 = self.spin_initial.GetValue() v1 = self.spin_initial2.GetValue() label = str(v0) + "." + str(v1) + "v" self.lbl_voltage.SetLabel(label) def OnSpinFinal(self, event=None): v0 = self.spin_final.GetValue() v1 = self.spin_final2.GetValue() label = str(v0) + "." + str(v1) + "v" self.lbl_voltage2.SetLabel(label) def OnSpinVarA(self, event): v0 = self.spin_var_a.GetValue() v1 = self.spin_var_a2.GetValue() unit = self.lbl_var_a.GetLabel()[-1] label = str(v0) + "." + str(v1) + unit self.lbl_var_a.SetLabel(label) def OnSpinVarB(self, event): v0 = self.spin_var_b.GetValue() v1 = self.spin_var_b2.GetValue() unit = self.lbl_var_b.GetLabel()[-1] label = str(v0) + "." + str(v1) + unit self.lbl_var_b.SetLabel(label) def OnSpinStep(self, event=None): v0 = self.spin_step.GetValue() v1 = self.spin_step2.GetValue() label = str(v0) + "." + str(v1) + "v" self.lbl_step2.SetLabel(label) def OnComboBox(self, event): e = event.GetEventObject() name = e.GetName() value = e.GetStringSelection() if name == "reading": if "Voltage" in value: unit = "V" elif "Current" in value: unit = "A" elif "Resistance" in value: unit = OHM #change unit accordingly label = self.lbl_var_a.GetLabel() if label[-1] == "%": return label = label[:-1] + unit self.lbl_var_a.SetLabel(label) label = self.lbl_var_b.GetLabel() label = label[:-1] + unit self.lbl_var_b.SetLabel(label) elif name == "condition": if "%" in value: self.spin_var_b.Disable() self.spin_var_b2.Disable() label = self.lbl_var_a.GetLabel() if not label.endswith("%"): label = label[:-1] + "%" self.lbl_var_a.SetLabel(label) label = self.lbl_var_b.GetLabel() if not label.endswith("%"): label = label[:-1] + "%" self.lbl_var_b.SetLabel(label) return elif value in ["in range","not in range"]: self.spin_var_b.Enable() self.spin_var_b2.Enable() else: self.spin_var_b.Disable() self.spin_var_b2.Disable() label = self.lbl_var_a.GetLabel() if label.endswith("%"): value = self.cbox_var.GetStringSelection() if "Voltage" in value: unit = "V" elif "Current" in value: unit = "A" elif "Resistance" in value: unit = OHM label = label[:-1] + unit self.lbl_var_a.SetLabel(label) label = self.lbl_var_b.GetLabel() label = label[:-1] + unit self.lbl_var_b.SetLabel(label) def OnRadioButton(self, event): e = event.GetEventObject() label = e.GetLabel() self.on_failure = label def OnButton(self, event): e = event.GetEventObject() label = e.GetLabel() id = e.GetId() if label == "Add": test = self.cbox_conditions.GetValue() test += self.lbl_var_a.GetLabel() test += self.lbl_var_b.GetLabel() failure = self.on_failure self.list_passfail.Append([test,failure]) if label == "Cancel": self.EndModal(id) elif label == "Confirm": data = {"action": "Step Voltage", "psu":self.cbox_psu.GetValue(), "v0":self.lbl_voltage.GetLabel()[1:-1], "v1":self.lbl_voltage2.GetLabel()[1:-1], "step":self.lbl_step2.GetLabel()[3:-1], "delay":self.spin_step_delay.GetValue(), "repeat":self.cbox_read.GetValue(), "read":self.cbox_read.GetValue()} self.EndModal(id) class AddSetVoltage(wx.Frame): def __init__(self): wx.Frame.__init__(self, parent=None, title="Set Voltage")
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test/test_jit_disabled.py
xiaohanhuang/pytorch
183
136402
# Owner(s): ["oncall: jit"] import sys import os import contextlib import subprocess from torch.testing._internal.common_utils import TestCase, run_tests, TemporaryFileName @contextlib.contextmanager def _jit_disabled(): cur_env = os.environ.get("PYTORCH_JIT", "1") os.environ["PYTORCH_JIT"] = "0" try: yield finally: os.environ["PYTORCH_JIT"] = cur_env class TestJitDisabled(TestCase): """ These tests are separate from the rest of the JIT tests because we need run a new subprocess and `import torch` with the correct environment variables set. """ def compare_enabled_disabled(self, src): """ Runs the script in `src` with PYTORCH_JIT enabled and disabled and compares their stdout for equality. """ # Write `src` out to a temporary so our source inspection logic works # correctly. with TemporaryFileName() as fname: with open(fname, 'w') as f: f.write(src) with _jit_disabled(): out_disabled = subprocess.check_output([ sys.executable, fname]) out_enabled = subprocess.check_output([ sys.executable, fname]) self.assertEqual(out_disabled, out_enabled) def test_attribute(self): _program_string = """ import torch class Foo(torch.jit.ScriptModule): def __init__(self, x): super(Foo, self).__init__() self.x = torch.jit.Attribute(x, torch.Tensor) def forward(self, input): return input s = Foo(torch.ones(2, 3)) print(s.x) """ self.compare_enabled_disabled(_program_string) def test_script_module_construction(self): _program_string = """ import torch class AModule(torch.jit.ScriptModule): def __init__(self): super(AModule, self).__init__() @torch.jit.script_method def forward(self, input): pass AModule() print("Didn't throw exception") """ self.compare_enabled_disabled(_program_string) def test_recursive_script(self): _program_string = """ import torch class AModule(torch.nn.Module): def __init__(self): super(AModule, self).__init__() def forward(self, input): pass sm = torch.jit.script(AModule()) print("Didn't throw exception") """ self.compare_enabled_disabled(_program_string) if __name__ == '__main__': run_tests()
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scripts/repo-format.py
vxfury/tabulate
28
195288
#!/usr/local/bin/python3 # -*- coding: UTF-8 -*- import os import re import sys import time import subprocess import multiprocessing import git import typing import itertools import argparse import string import math import tty import ctypes import termios import xml.etree.ElementTree as ET COPYRIGHT = b"""/** * Copyright 2022 <NAME>(<EMAIL>) * * 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 * * https://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. */\n\n""" # tqdm has bugs. # CSI sequence: https://www.liquisearch.com/ansi_escape_code/csi_codes class ProgressBar: """ Progress Bar ... Attributes ---------- disable: bool True to disable progress bar (default False) position: tuple(int, int) the number of legs the animal has (default 4) progress: float[0.0, 100.0] percentage of progress max_width: int max width of entire progress bar (default terminal.columns) bar_width: int bar width of progress bar (default max_width // 2) Methods ------- advance(progress) Inc progress and refresh display set_progress(progress) Set progress and refresh display set_args(**kwargs) Set arguments and refresh display add_args(**kwargs) Add arguments and refresh display clear() Clear display once time """ def __init__( self, format: str = "{progress} {elapsed} | {bar} | {remaining}", position: tuple[int, int] = None, disable: bool = False, leave: bool = True, total: float = 100.0, max_width: int = 0, bar_width: int = 0, file=sys.stdout, keep_cursor_hidden: bool = False, manager: multiprocessing.Manager = None, **kwargs, ): """ format: progress bar format, internal keys: progress, elapsed, bar, remaining position: position of bar disable: True to hide the progress bar leave: True to leave the progress bar after exit total: max size to advance max_width: max width of entire progress bar bar_width: bar width file: destination of progress bar (default sys.stdout) keep_cursor_hidden: True to keep cursor hidden after exit manager: multiprocessing support kwargs: custom key-value pairs """ self.__file = file self.__leave = leave self.__total = total self.__format = format self.__kwargs = kwargs self.__starttime = time.time() self.__keep_cursor_hidden = keep_cursor_hidden self.__lock = None if manager is None else manager.Lock() self.__progress = 0.0 if manager is None else manager.Value(ctypes.c_float, 0.0) self.disable = disable self.position = position self.max_width = max_width if max_width else os.get_terminal_size().columns - 8 self.bar_width = bar_width if bar_width != 0 and bar_width < self.max_width else self.max_width // 2 self.__display() # CSI?25l: Hides the cursor def __del__(self): if not self.disable: outputs = "" if self.position: # `CSI n ; m H`: Moves the cursor to row n, column m outputs += f"\x1B[{self.position[0]};{self.position[1]}H" if not self.__leave: # `CSI n k`: Erases part of the line outputs += "\x1B[2K" # n=2, clear entire line else: outputs += "\x1B[E" if not self.__keep_cursor_hidden: # `CSI ? 25 h``: Shows the cursor outputs += "\x1B[?25h" self.__write(outputs + "\r") def clear(self): """ clear display once time """ if not self.disable: outputs = "" if self.position: # `CSI n ; m H`: Moves the cursor to row n, column m outputs += f"\x1B[{self.position[0]};{self.position[1]}H" outputs += "\x1B[2K\r" # n=2, clear entire line self.__write(outputs) def advance(self, step): """ advance progress by <100.0 * step / total> """ if self.__lock: self.__lock.acquire() last_progress = self.progress if last_progress != self.__inc_progress(100.0 * step / self.__total): self.__display() if self.__lock: self.__lock.release() @property def progress(self): """ get progress """ if isinstance(self.__progress, float): return self.__progress else: return self.__progress.value @progress.setter def progress(self, val): self.set_progress(val) def __set_progress(self, progress): if isinstance(self.__progress, float): self.__progress = min(progress, 100.0) return self.__progress else: self.__progress.value = min(progress, 100.0) return self.__progress.value def __inc_progress(self, progress): if isinstance(self.__progress, float): self.__progress = min(self.__progress + progress, 100.0) return self.__progress else: self.__progress.value = min(self.__progress.value + progress, 100.0) return self.__progress.value def set_progress(self, progress): """ set progress to <progress> """ if self.__lock: self.__lock.acquire() if self.progress != self.__set_progress(progress): self.__display() if self.__lock: self.__lock.release() def set_args(self, **kwargs): if kwargs != self.__kwargs: self.__kwargs = kwargs self.__display() def add_args(self, **kwargs): self.__kwargs.update(kwargs) self.__display() def __display(self): def format_time(t): """ Formats a number of seconds as a clock time, [H:]MM:SS """ mins, s = divmod(int(t), 60) h, m = divmod(mins, 60) if mins == 0 and t > 0.1 and s == 0: s = 1 if h: return "{0:d}:{1:02d}:{2:02d}".format(h, m, s) else: return "{0:02d}:{1:02d}".format(m, s) def format_bar(p, w): l = int(w * p / 100.0) if p < 99.9 else w return ">" * l + " " * (w - l) def format_all(format, **kwargs): class BlankFormatter(string.Formatter): def __init__(self, default=""): self.default = default def get_value(self, key, args, kwds): if isinstance(key, str): return kwds.get(key, self.default) else: return string.Formatter.get_value(key, args, kwds) text = BlankFormatter().format(format, **kwargs).rstrip() while text.endswith(":"): text = text[: len(text) - 1].rstrip() return text if not self.disable: now = time.time() self.__kwargs["progress"] = "{0:5.1f}%".format(self.progress) self.__kwargs["bar"] = format_bar(self.progress, self.bar_width) self.__kwargs["elapsed"] = format_time(now - self.__starttime) self.__kwargs["remaining"] = ( format_time((now - self.__starttime) * (100 - self.progress) / self.progress) if self.progress else "--:--" ) outputs = "\x1B[?25l" if self.position: # `CSIn;mH`: Moves the cursor to row n, column m outputs += f"\x1B[s\x1B[{self.position[0]};{self.position[1]}H" else: outputs += "\r" line = format_all(self.__format, **self.__kwargs) if self.max_width != 0: if len(line) > self.max_width: truncated = "..." if self.max_width >= len(truncated): line = line[: (self.max_width - len(truncated))] + truncated + "\x1b[0m" else: line = line[: self.max_width] + "\x1b[0m" outputs += line + "\x1B[0K" if self.position: outputs += "\x1B[u" self.__write(outputs) def __write(self, str): file = self.__file if self.__file else sys.stdout file.write(str) file.flush() @staticmethod def getpos(): buf = "" stdin = sys.stdin.fileno() tattr = termios.tcgetattr(stdin) try: tty.setcbreak(stdin, termios.TCSANOW) sys.stdout.write("\x1b[6n") sys.stdout.flush() while True: buf += sys.stdin.read(1) if buf[-1] == "R": break finally: termios.tcsetattr(stdin, termios.TCSANOW, tattr) # reading the actual values, but what if a keystroke appears while reading # from stdin? As dirty work around, getpos() returns if this fails: None try: matches = re.match(r"^\x1b\[(\d*);(\d*)R", buf) groups = matches.groups() except AttributeError: return None return (int(groups[0]), int(groups[1])) class ProgressBars: def __init__( self, format, size, max_width=os.get_terminal_size().columns, bar_width=0, disable=False, leave=False, initial_pos=None, overall_total=0, manager: multiprocessing.Manager = None, ): offset = 0 if overall_total != 0: self.overall = ProgressBar( leave=True, disable=disable, total=overall_total, file=None, max_width=max_width, bar_width=bar_width, position=initial_pos, keep_cursor_hidden=True, manager=manager, ) offset = 1 else: self.overall = None self.bars = [ ProgressBar( format, disable=disable, file=None, max_width=max_width, bar_width=bar_width, leave=True, # keep bar if not all bars end position=((initial_pos[0] + i), initial_pos[1]) if initial_pos else None, keep_cursor_hidden=True, manager=manager, ) for i in range(offset, size + offset) ] self.__leave = leave self.disable = disable self.initial_pos = initial_pos def __del__(self): off = 0 if self.overall is None else 1 if self.__leave: off += len(self.bars) self.bars = [] else: [bar.clear() for bar in self.bars] if not self.disable: outputs = "" if self.initial_pos: # `CSI n ; m H`: Moves the cursor to row n, column m outputs += f"\x1B[2K\x1B[{self.initial_pos[0] + off};{self.initial_pos[1]}H" outputs += "\x1B[?25h" sys.stdout.write(outputs) sys.stdout.flush() def __getitem__(self, index): return self.bars[index % len(self.bars)] """a replacement instance within a single file""" class Replacement: def __init__(self, offset, length, content, path=None): self.offset = offset self.length = length self.content = content self.path = path def __hash__(self): return hash((self.offset, self.length)) def __eq__(self, other): return (self.offset, self.length) == (other.offset, other.length) def __repr__(self): return f"offset={self.offset} " f"length={self.length} content={self.content}" def get_affected_commit(self, file, repo: git.Repo, blame_info, bar: ProgressBar): def offset_to_line(file, offset): file.seek(0) content = file.read(offset) return content.decode("utf-8", "ignore").count("\n") + 1 def map_of_line_commit(blame_info): result = {} current_line = 0 for one_blame in blame_info: for one_line in one_blame[1]: current_line += 1 result[current_line] = one_blame return result first_line_offset = offset_to_line(file, self.offset) last_line_offset = offset_to_line(file, max(self.offset, self.offset + self.length - 1)) # fetch blame information for this replacement. original_blames = [] line_commit_map = map_of_line_commit(blame_info) for i in range(first_line_offset, last_line_offset + 1): if i >= len(line_commit_map): # apply blame of first line if out of range, the last line mostly original_blames.append(line_commit_map[1][0]) continue if line_commit_map[i][0] not in original_blames: original_blames.append(line_commit_map[i][0]) if len(original_blames) > 1 and original_blames[0].author != original_blames[1].author: bar.add_args( desc=f"\x1B[33m{first_line_offset}-{last_line_offset} modified by {list(map(lambda b: str(b.author), original_blames))}. regard as modified by {original_blames[-1].author}\x1B[0m" ) return original_blames[-1] """apply replacement onto file.""" def apply(self, file): # seek to offset + length where content is untouched by self file.seek(self.offset + self.length) # read till the EOF b = file.read() # then insert 'content' at the start and write back file.seek(self.offset) file.write(self.content + b) # truncate unnecessary content in case content is shorter than origin file.truncate() def _filter_trivial_blame(self, blame): for line in blame[1]: if not line.isspace() and len(line) and not self.filter_trivial_line(line): return True return False """tells base class if given source line is considered trivial""" def filter_trivial_line(self, line): return False class ReplacementGenerator: """generates replacements for a file.""" def generate(self, file, *args, **kwargs) -> typing.List[Replacement]: pass class ClangFormatReplacement(Replacement): trivial_line_pattern = re.compile(r"^[\{\}\[\]\(\);]+$") def filter_trivial_line(self, line): # in C-like languages, braces ({}), brackets ([]), parentheses (()) # and semicolon (;) are often arranged into a single line in favor of # some codestyles, on which blame infomation is usually useless. l = line.translate(dict.fromkeys(map(ord, string.whitespace))) return self.__class__.trivial_line_pattern.match(l) class ClangFormatXMLReplacementGenerator(ReplacementGenerator): def generate(self, file, bar: ProgressBar) -> typing.List[Replacement]: file.seek(0, os.SEEK_END) size = file.tell() bar.add_args(desc="generate clang-format XML replacements ...") output = subprocess.check_output( ("clang-format", "--output-replacements-xml", "--style=file", file.name) ).decode("utf-8") bar.set_progress(100 * (1024 + size * 2 / 4) / (1024 + size + 4096)) def add_copyrigth_auto(file, result): file.seek(0) if len(COPYRIGHT) > 0 and b"Copyright" not in file.read(300): if len(result) > 0 and result[0].offset == 0: result[0].content = COPYRIGHT + result[0].content else: r = ClangFormatReplacement(0, 0, COPYRIGHT) result.insert(0, r) result = [] xml_root = ET.fromstring(output) for r in xml_root.iterfind("replacement"): offset = int(r.get("offset")) length = int(r.get("length")) byte_content = bytes(r.text or "", encoding="utf-8") bar.add_args(desc=f"replacement of lines {offset}-{offset + length}") bar.set_progress(100 * (1024 + (offset + length) * 3 / 5) / (1024 + size + 4096)) # clang-format produces replacements overlapped with original text, which results in # multi-commit blame results. remove overlapped areas for better result. i = len(byte_content) if i > 0: i = i - 1 file.seek(offset + length - 1) while i >= 0 and length > 0 and file.read(1)[0] == byte_content[i]: i = i - 1 length = length - 1 file.seek(offset + length - 1) byte_content = byte_content[: i + 1] i = 0 file.seek(offset) while i < len(byte_content) and length > 0 and file.read(1)[0] == byte_content[i]: i = i + 1 length = length - 1 offset = offset + 1 file.seek(offset) byte_content = byte_content[i:] result.append(ClangFormatReplacement(offset, length, byte_content)) add_copyrigth_auto(file, result) bar.set_progress(100 * (1024 + size * 3 / 5) / (1024 + size + 4096)) return result # binary search def binary_search(arr, comparator): return _binary_search(arr, 0, len(arr) - 1, comparator) def _binary_search(arr, l, r, comparator): if r < l: return -1 mid = int(l + (r - l) / 2) compare = comparator(arr[mid]) if compare == 0: return mid elif compare < 0: return _binary_search(arr, l, mid - 1, comparator) else: return _binary_search(arr, mid + 1, r, comparator) def generate_replacements(repo: git.Repo, path, limit, bar: ProgressBar, overall_bar: ProgressBar): replacements_by_paths = {} replacements_by_affected_commits = {} bar.set_args( file=f"{os.path.relpath(path, os.path.dirname(repo.common_dir) if repo else os.getcwd())}", desc="...", ) try: size = os.path.getsize(path) if size > limit * 1024: bar.add_args(desc=f"\x1B[33m{size // 1024}KB, more than {limit} KB, skipped\x1B[0m") return None, None if size <= 1: bar.add_args(desc=f"\x1B[33mempty file, skipped\x1B[0m") return None, None bar.set_progress(100 * 1024 / (1024 + size / 4096)) with open(path, mode="rb") as file: bar.add_args(desc=f"generate replacements") replacements_for_cur_file = ClangFormatXMLReplacementGenerator().generate(file, bar=bar) if not replacements_for_cur_file: bar.add_args(desc=f"no replacements found") return None, None replacements_for_cur_file.sort(key=lambda r: r.offset) replacements_by_paths[path] = replacements_for_cur_file if repo: try: blame_info = repo.blame(repo.head.commit, file.name) except git.exc.GitCommandError as e: if "is outside repository" in e.stderr: # file not in repository, ignore bar.add_args(desc="outside repository") return replacements_by_paths, None else: return replacements_by_paths, None # fetch blame information for each replacement, # then make a <affected_commits> -> <replacements> map. for r in replacements_for_cur_file: r.path = path affected_commit = r.get_affected_commit(file, repo, blame_info, bar) # affected_commits = blame_result[1] if len(blame_result[1]) else blame_result[0] # affected_commits = list(map(lambda b: b[0].binsha.hex(), affected_commits)) affected_commit = affected_commit.binsha.hex() replacements = replacements_by_affected_commits.get(affected_commit, []) replacements.append(r) replacements_by_affected_commits[affected_commit] = replacements except PermissionError as e: bar.add_args(desc=f"\x1B[33mpermission denied, skipped\x1B[0m") finally: overall_bar.advance(1) bar.set_progress(100.0) return ( replacements_by_paths, replacements_by_affected_commits if len(replacements_by_affected_commits) != 0 else None, ) def repo_format_main(initial_pos): starttime = time.time() # arguments parser parser = argparse.ArgumentParser( description="Generate and apply replacements for existing Git " "repository, without altering future blame results" ) parser.add_argument("--repo", required=False, help="path to git repository, sub-path is acceptable") parser.add_argument("--path", required=False, help="path to format, default is path to repo") parser.add_argument("--exclude", required=False, help="directory don't format") parser.add_argument("--no-commit", "-n", action="store_true", help="no commit, just format file") parser.add_argument("--copyright", required=False, help="copyright") parser.add_argument( "--dry-run", required=False, default=False, action="store_true", help="calculate files those will be formated but no formating actually", ) parser.add_argument( "--jobs", "-j", required=False, default=multiprocessing.cpu_count(), help="jobs to do formatting" ) parser.add_argument("--limit", required=False, default=256, help="max KB of file to format") parser.add_argument( "--quiet", required=False, default=False, action="store_true", help="quiet mode", ) parser.add_argument("--author", required=False, default=os.getlogin(), help="author for unkown commits") parser.add_argument( "--filter-by-author", required=False, default=None, help="only format commits by specified author" ) # BEGIN OF MAIN: validate given arguments. args = parser.parse_args() if args.copyright is not None: COPYRIGHT = args.copyright repo = git.Repo(args.repo, search_parent_directories=True) if args.repo else None format_path = os.path.expanduser(args.repo if args.path is None else args.path) if not os.path.isabs(format_path): format_path = os.path.join(os.getcwd(), format_path) files = [] if os.path.isdir(format_path): for root, dirs, file_list in os.walk(format_path): def need_exclude(root, excludes): for dir in excludes: if os.path.abspath(os.path.join(format_path, dir)).startswith( os.path.abspath(os.path.expanduser(root)) ): return True return False if args.exclude and need_exclude(root, args.exclude.split(",")): # print(f"Exclude {root}, {args.exclude}") continue for filename in file_list: if filename.endswith((".cpp", ".cc", ".h", ".hpp", ".c")): files.append(os.path.join(root, filename)) elif os.path.isfile(format_path): files.append(format_path) # process files specified in arguments. new commits will be created during processing, # so we cache current head for accurate blaming results. with multiprocessing.Pool(processes=int(args.jobs)) as pool: manager = multiprocessing.Manager() size = min(int(args.jobs), multiprocessing.cpu_count() // 2, len(files)) bars = ProgressBars( "{progress} {elapsed} | {file}: {desc}", size, leave=False, disable=bool(args.quiet), initial_pos=(initial_pos[0] + 1, initial_pos[1]), overall_total=len(files), manager=manager, ) results = pool.starmap_async( generate_replacements, [(repo, path, int(args.limit), bars[i], bars.overall) for i, path in enumerate(files)], ).get() pool.close() pool.join() del bars # delete bars for elegant print replacements_by_paths = {} replacements_by_paths_only = {} replacements_by_affected_commits = {} for replacements_by_path, replacements_by_affected_commit in results: if replacements_by_path and replacements_by_affected_commit is None: replacements_by_paths_only.update(replacements_by_path) else: if replacements_by_path: replacements_by_paths.update(replacements_by_path) if replacements_by_affected_commit: for affected_commit in replacements_by_affected_commit.keys(): if not affected_commit in replacements_by_affected_commits.keys(): replacements_by_affected_commits[affected_commit] = [] replacements_by_affected_commits[affected_commit].extend( replacements_by_affected_commit[affected_commit] ) if repo and not args.dry_run: # combine affected commits with same author. replacements_by_authors = {} affected_commits_by_authors = {} for commit_hex, replacements in replacements_by_affected_commits.items(): first_commit = repo.commit(commit_hex) author = first_commit.author affected_commits = affected_commits_by_authors.get(author, set()) affected_commits.add(commit_hex) affected_commits_by_authors[author] = affected_commits for author, commits_by_author in affected_commits_by_authors.items(): affected_commits = set() replacements = [] if args.filter_by_author and author != author: continue for one_commit in commits_by_author: affected_commits.add(one_commit) replacements.extend(replacements_by_affected_commits[one_commit]) replacements_by_authors[tuple(affected_commits)] = replacements # apply replacements, one affected commit(s) by one. for commits, replacements in replacements_by_authors.items(): file_paths = set() for r in replacements: with open(r.path, mode="rb+") as file: r.apply(file) file_paths.add(file.name) length_delta = len(r.content) - r.length replacements_in_same_file = replacements_by_paths[r.path] if length_delta != 0 and len(replacements_in_same_file): # apply replacement each time, and adjuest offset of replacements after it index = binary_search(replacements_in_same_file, lambda re: r.offset - re.offset) for re in itertools.islice(replacements_in_same_file, index, None): re.offset = re.offset + length_delta # remove current replacement for future better search performance. del replacements_in_same_file[index] replacements_by_paths[r.path] = replacements_in_same_file if not args.no_commit and len(file_paths) != 0: repo.index.add(file_paths, False) # done with current commit, make new one first_commit = repo.commit(commits[0]) # multiple commits are affected: # lossless replacement is impossible (automatically). # explicitly create a new commit and try to retain infomation # from original commits as much as possible. commit_msg = f"repo-format: reformat and keep blame info" repo.index.commit(commit_msg, author=first_commit.author) if not args.dry_run and replacements_by_paths_only: file_paths = set(replacements_by_paths_only.keys()) for path, replacements in replacements_by_paths_only.items(): for r in replacements: with open(path, mode="rb+") as file: r.apply(file) file_paths.add(file.name) length_delta = len(r.content) - r.length replacements_in_same_file = replacements_by_paths_only[path] if length_delta != 0 and len(replacements_in_same_file): # apply replacement each time, and adjuest offset of replacements after it index = binary_search(replacements_in_same_file, lambda re: r.offset - re.offset) for re in itertools.islice(replacements_in_same_file, index, None): re.offset = re.offset + length_delta # remove current replacement for future better search performance. del replacements_in_same_file[index] replacements_by_paths[path] = replacements_in_same_file if repo and not args.no_commit and len(file_paths) != 0: repo.index.add(file_paths, False) commit_msg = f"repo-format: format uncommit codes" repo.git.commit("-m", commit_msg, author=args.author) print( f"Time elapsed: {round(time.time() - starttime, 2)} s." + f" {len(list(filter(lambda r: r[0] is not None, results)))} of {len(files)} file(s) " + ("can be formatted." if args.dry_run else "formatted.") ) import random def progress_bar_main(): bar = ProgressBar(leave=True, widht=90, total=500, bar_width=60) for i in range(0, 500): bar.advance(1) time.sleep(0.005) def progress_bar_test(length, bar, overall_bar): remain = length while remain > 0: len = random.randint(0, remain) remain -= len time.sleep(0.001) bar.set_progress(100 * (length - remain) / length) overall_bar.advance(1) def progress_bars_main(initial_pos): manager = multiprocessing.Manager() with multiprocessing.Pool(processes=6) as pool: size = 3 total = 10000 initial_pos = initial_pos bars = ProgressBars( "{progress} {elapsed} | {bar} | {remaining}", size, leave=True, initial_pos=(initial_pos[0] + 1, initial_pos[1]), overall_total=total, manager=manager, ) pool.starmap_async( progress_bar_test, [(random.randint(1000, 10000), bars[i], bars.overall) for i in range(total)], ).get() pool.close() pool.join() if __name__ == "__main__": initial_pos = ProgressBar.getpos() # initial_pos = (initial_pos[0] - 1, initial_pos[1]) repo_format_main(initial_pos) # progress_bar_main() # progress_bars_main(initial_pos) """ .clang-format --- Language: Cpp AccessModifierOffset: '-2' AlignAfterOpenBracket: Align AlignConsecutiveMacros: 'true' AlignConsecutiveAssignments: 'false' AlignConsecutiveDeclarations: 'false' AlignEscapedNewlines: Left AlignOperands: 'true' AlignTrailingComments: 'true' AllowAllArgumentsOnNextLine: 'true' AllowAllConstructorInitializersOnNextLine: 'true' AllowAllParametersOfDeclarationOnNextLine: 'true' AllowShortBlocksOnASingleLine: 'false' AllowShortCaseLabelsOnASingleLine: 'false' AllowShortFunctionsOnASingleLine: Empty AllowShortIfStatementsOnASingleLine: WithoutElse AllowShortLambdasOnASingleLine: None AllowShortLoopsOnASingleLine: 'true' AlwaysBreakAfterDefinitionReturnType: None AlwaysBreakAfterReturnType: None AlwaysBreakBeforeMultilineStrings: 'false' AlwaysBreakTemplateDeclarations: 'Yes' BinPackArguments: 'true' BinPackParameters: 'true' BraceWrapping: AfterCaseLabel: 'false' AfterClass: 'false' AfterControlStatement: 'false' AfterEnum: 'false' AfterFunction: 'true' AfterNamespace: 'true' AfterObjCDeclaration: 'false' AfterStruct: 'false' AfterUnion: 'false' AfterExternBlock: 'false' BeforeCatch: 'false' BeforeElse: 'false' IndentBraces: 'false' SplitEmptyFunction: 'true' SplitEmptyRecord: 'true' SplitEmptyNamespace: 'true' BreakBeforeBinaryOperators: NonAssignment BreakBeforeBraces: Custom BreakBeforeTernaryOperators: 'true' BreakConstructorInitializers: BeforeColon BreakInheritanceList: BeforeColon BreakStringLiterals: 'true' ColumnLimit: '120' CompactNamespaces: 'false' ConstructorInitializerAllOnOneLineOrOnePerLine: 'true' ConstructorInitializerIndentWidth: '4' ContinuationIndentWidth: '4' Cpp11BracedListStyle: 'true' DerivePointerAlignment: 'false' DisableFormat: 'false' ExperimentalAutoDetectBinPacking: 'false' FixNamespaceComments: 'true' ForEachMacros: ['foreach', 'FOREACH', 'RANGES_FOR', 'hlist_for_each_entry_continue', 'hlist_for_each_entry', 'hlist_for_each_entry_from', 'hlist_for_each_entry_safe', 'hlist_for_each_safe', 'list_for_each_entry', 'list_for_each_entry_continue', 'list_for_each_entry_continue_reverse', 'list_for_each_entry_from', 'list_for_each_entry_reverse', 'list_for_each_entry_safe', 'list_for_each_entry_safe_continue', 'list_for_each_entry_safe_from', 'list_for_each_entry_safe_reverse', 'list_for_each_from', 'list_for_each_prev', 'list_for_each_prev_safe', 'list_for_each_safe'] TypenameMacros: ['STACK_OF', 'LIST'] IncludeBlocks: Regroup IncludeIsMainRegex: '([-_](test|unittest))?$' IndentCaseLabels: 'true' IndentPPDirectives: None IndentWidth: '4' IndentWrappedFunctionNames: 'false' KeepEmptyLinesAtTheStartOfBlocks: 'false' MaxEmptyLinesToKeep: '3' NamespaceIndentation: None PenaltyBreakAssignment: '2' PenaltyBreakBeforeFirstCallParameter: '1' PenaltyBreakComment: '300' PenaltyBreakFirstLessLess: '120' PenaltyBreakString: '1000' PenaltyBreakTemplateDeclaration: '10' PenaltyExcessCharacter: '1000000' PenaltyReturnTypeOnItsOwnLine: '500' PointerAlignment: Right RawStringFormats: - Language: Cpp Delimiters: - 'cc' - 'CC' - 'cpp' - 'Cpp' - 'CPP' - 'c++' - 'C++' CanonicalDelimiter: '' BasedOnStyle: google - Language: TextProto Delimiters: - 'pb' - 'PB' - 'proto' - 'PROTO' EnclosingFunctions: - EqualsProto - EquivToProto - PARSE_PARTIAL_TEXT_PROTO - PARSE_TEST_PROTO - PARSE_TEXT_PROTO - ParseTextOrDie - ParseTextProtoOrDie CanonicalDelimiter: '' BasedOnStyle: google ReflowComments: 'true' SortIncludes: 'false' SortUsingDeclarations: 'false' SpaceAfterCStyleCast: 'false' SpaceAfterLogicalNot: 'false' SpaceAfterTemplateKeyword: 'true' SpaceBeforeAssignmentOperators: 'true' SpaceBeforeCpp11BracedList: 'false' SpaceBeforeCtorInitializerColon: 'true' SpaceBeforeInheritanceColon: 'true' SpaceBeforeParens: ControlStatements SpaceBeforeRangeBasedForLoopColon: 'true' SpaceInEmptyParentheses: 'false' SpacesBeforeTrailingComments: '1' SpacesInAngles: 'false' SpacesInCStyleCastParentheses: 'false' SpacesInContainerLiterals: 'false' SpacesInParentheses: 'false' SpacesInSquareBrackets: 'false' Standard: Auto StatementMacros: ['__maybe_unused'] TabWidth: '4' UseTab: Never ... """
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Python programming/tail.py
fredffsixty/Medical_Imaging
0
179038
""" tail.py stringa [-c] carattere | [-]numero stampa la sottostringa a partire dall'ultima occorrenza di carattere, opzionalmente specificato con il parametro '-c', ovvero stampa la sottostringa a partire dalla posizione specificata da numero eventualmente anche negativo """ import sys def lastIndexOf(s, c): """ lastIndexOf(stringa, carattere) restituisce un intero nell'intervallo 0 - len(stringa) che corrisponde all'indice dell'ultima occorrenza di carattere in stringa. Se il risultato è esattamente len(stringa) allora carattere non è presente in stringa. """ index = s[::-1].find(c) if index == -1: return len(s) else: return len(s) - 1 - index def main(): if (len(sys.argv) < 3 or len(sys.argv) > 4): print('Argomenti errati\n\nUtilizzo: tail2.py stringa [-c] carattere | [-]numero') sys.exit() elif len(sys.argv) == 3 and \ not(sys.argv[2].isdigit() or (sys.argv[2][0]=='-' and sys.argv[2][1::].isdigit())) and \ len(sys.argv[2])!=1: print('Argomenti errati\n\nUtilizzo: tail2.py stringa [-c] carattere | [-]numero') sys.exit() elif len(sys.argv) == 4 and sys.argv[2]!='-c': print('Argomenti errati\n\nUtilizzo: tail2.py stringa [-c] carattere | [-]numero') sys.exit() else: if sys.argv[2].isdigit() or (sys.argv[2][0]=='-' and sys.argv[2][1::].isdigit()): index = int(sys.argv[2]) if index < -len(sys.argv[1]) or index >= len(sys.argv[1]): print('Indice specificato fuori dal range\n\n') sys.exit() else: print(sys.argv[1][index::]) else: if sys.argv[2] == '-c': position = lastIndexOf(sys.argv[1],sys.argv[3]) else: position = lastIndexOf(sys.argv[1],sys.argv[2]) if position == len(sys.argv[1]): print('Il carattere non è presente nella stringa\n\n') sys.exit() else: print(sys.argv[1][position::]) if __name__ == '__main__': main()
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readthedocs/core/history.py
ashlyrclark/readthedocs.org
0
83195
<gh_stars>0 import logging from functools import partial from django import forms from django.db import models from django.utils.translation import ugettext_lazy as _ from simple_history.admin import SimpleHistoryAdmin from simple_history.models import HistoricalRecords from simple_history.utils import update_change_reason log = logging.getLogger(__name__) def set_change_reason(instance, reason): """ Set the change reason for the historical record created from the instance. This method should be called before calling ``save()`` or ``delete``. It sets `reason` to the `_change_reason` attribute of the instance, that's used to create the historical record on the save/delete signals. https://django-simple-history.readthedocs.io/en/latest/historical_model.html#change-reason # noqa """ instance._change_reason = reason def safe_update_change_reason(instance, reason): """ Wrapper around update_change_reason to catch exceptions. .. warning:: The implementation of django-simple-history's `update_change_reason` is very brittle, as it queries for a previous historical record that matches the attributes of the instance to update the ``change_reason``, which could end up updating the wrong record, or not finding it. If you already have control over the object, use `set_change_reason` before updating/deleting the object instead. That's more safe, since the attribute is passed to the signal and used at the creation time of the record. https://django-simple-history.readthedocs.io/en/latest/historical_model.html#change-reason # noqa """ try: update_change_reason(instance=instance, reason=reason) except Exception: log.exception( 'An error occurred while updating the change reason of the instance: obj=%s', instance, ) class ExtraFieldsHistoricalModel(models.Model): """ Abstract model to allow history models track extra data. Extra data includes: - User information to retain after they have been deleted - IP & browser """ extra_history_user_id = models.IntegerField( _('ID'), blank=True, null=True, db_index=True, ) extra_history_user_username = models.CharField( _('username'), max_length=150, null=True, db_index=True, ) extra_history_ip = models.CharField( _('IP address'), blank=True, null=True, max_length=250, ) extra_history_browser = models.CharField( _('Browser user-agent'), max_length=250, blank=True, null=True, ) class Meta: abstract = True ExtraHistoricalRecords = partial(HistoricalRecords, bases=[ExtraFieldsHistoricalModel]) """Helper partial to use instead of HistoricalRecords.""" class ExtraSimpleHistoryAdmin(SimpleHistoryAdmin): """Set the change_reason on the model changed through this admin view.""" change_reason = None def get_change_reason(self): if self.change_reason: return self.change_reason klass = self.__class__.__name__ return f'origin=admin class={klass}' def save_model(self, request, obj, form, change): if obj: set_change_reason(obj, self.get_change_reason()) super().save_model(request, obj, form, change) def delete_model(self, request, obj): if obj: set_change_reason(obj, self.get_change_reason()) super().delete_model(request, obj) class SimpleHistoryModelForm(forms.ModelForm): """Set the change_reason on the model changed through this form.""" change_reason = None def get_change_reason(self): if self.change_reason: return self.change_reason klass = self.__class__.__name__ return f'origin=form class={klass}' def save(self, commit=True): if self.instance: set_change_reason(self.instance, self.get_change_reason()) return super().save(commit=commit) class UpdateChangeReasonPostView: """ Set the change_reason on the model changed through the POST method of this view. Use this class for views that don't use a form, like ``DeleteView``. """ change_reason = None def get_change_reason(self): if self.change_reason: return self.change_reason klass = self.__class__.__name__ return f'origin=form class={klass}' def get_object(self): obj = super().get_object() set_change_reason(obj, self.get_change_reason()) return obj
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src/dagos/core/package_managers.py
DAG-OS/dagos
0
165812
from __future__ import annotations import os import textwrap import typing as t from dagos.platform.command_runner import CommandRunner class PackageManagerRegistry(type): """A metaclass responsible for registering supported package managers.""" managers: t.List[PackageManager] = [] def __call__(cls, *args: t.Any, **kwds: t.Any) -> t.Any: manager = super().__call__(*args, **kwds) if cls not in cls.managers: cls.managers.append(manager) return manager @classmethod def find(cls, name: str) -> t.Optional[PackageManager]: for manager in cls.managers: # TODO: Use a classproperty from boltons? if manager.name() == name: return manager return None class PackageManager(metaclass=PackageManagerRegistry): """A base class for all supported package managers. Since the package manager may reside on a remote platform, e.g., within a container image, implementing classes should not interact with the system themselves but rather return commands to influence it.""" @classmethod def name(cls) -> str: """The name of the package manager, defaults to the lower case class name.""" return str(cls.__name__).lower() def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: """Install the provided packages via the provided command_runner. Args: packages (t.List[str]): A list of packages to install. command_runner (CommandRunner): A command runner instance to use for installing. """ # TODO: Check root privileges? Enable/disable via flag in class? raise NotImplementedError def clean(self, command_runner: CommandRunner) -> None: """Generate command line call for cleaning any redundant files of this manager.""" return None def refresh(self, command_runner: CommandRunner) -> None: """Refresh metadata from remote repository.""" raise NotImplementedError class Apt(PackageManager): def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: self.refresh(command_runner) command_runner.run( f"apt install -y --no-install-recommends {' '.join(packages)}" ) def clean(self, command_runner: CommandRunner) -> None: command_runner.run("apt clean") def refresh(self, command_runner: CommandRunner) -> None: command_runner.run("apt update") class Dnf(PackageManager): def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: command_runner.run(f"dnf install -y {' '.join(packages)}") def clean(self, command_runner: CommandRunner) -> None: command_runner.run("dnf clean all") class Yum(PackageManager): def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: command_runner.run(f"yum install -y {' '.join(packages)}") class Pip(PackageManager): def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: # TODO: How to handle different python versions? command_runner.run(f"pip install {' '.join(packages)}") class Choco(PackageManager): def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: command_runner.run(f"choco install --yes {' '.join(packages)}") class Sdkman(PackageManager): @classmethod def name(cls) -> str: return "sdk" def install(self, packages: t.List[str], command_runner: CommandRunner) -> None: # In order to use sdk from the command line one needs to source its init script. # This is not possible through the subprocess module. Therefore we use a temporary # bash script in its stead. tmp_file = f"/tmp/sdk-install-script-{os.getpid()}.sh" script = textwrap.dedent( f"""\ #!/bin/bash source $HOME/.sdkman/bin/sdkman-init.sh """ ) for package in packages: script += f"sdk install {package}\n" command_runner.run(f"""bash -c 'echo "{script}" > {tmp_file}'""") command_runner.run(f"chmod +x {tmp_file}") command_runner.run(f".{tmp_file}") command_runner.run(f"rm {tmp_file}") Apt() Dnf() Yum() Sdkman()
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infobip/api/model/sms/mt/logs/SMSLog.py
ubidreams/infobip-api-python-client
0
1609322
# -*- coding: utf-8 -*- """This is a generated class and is not intended for modification! """ from datetime import datetime from infobip.util.models import DefaultObject, serializable from infobip.api.model.Error import Error from infobip.api.model.Status import Status from infobip.api.model.Price import Price class SMSLog(DefaultObject): @property @serializable(name="bulkId", type='basestring') def bulk_id(self): """ Property is of type: 'basestring' """ return self.get_field_value("bulk_id") @bulk_id.setter def bulk_id(self, bulk_id): """ Property is of type: 'basestring' """ self.set_field_value("bulk_id", bulk_id) def set_bulk_id(self, bulk_id): self.bulk_id = bulk_id return self @property @serializable(name="messageId", type='basestring') def message_id(self): """ Property is of type: 'basestring' """ return self.get_field_value("message_id") @message_id.setter def message_id(self, message_id): """ Property is of type: 'basestring' """ self.set_field_value("message_id", message_id) def set_message_id(self, message_id): self.message_id = message_id return self @property @serializable(name="to", type='basestring') def to(self): """ Property is of type: 'basestring' """ return self.get_field_value("to") @to.setter def to(self, to): """ Property is of type: 'basestring' """ self.set_field_value("to", to) def set_to(self, to): self.to = to return self @property @serializable(name="from", type='basestring') def from_(self): """ Property is of type: 'basestring' """ return self.get_field_value("from_") @from_.setter def from_(self, from_): """ Property is of type: 'basestring' """ self.set_field_value("from_", from_) def set_from_(self, from_): self.from_ = from_ return self @property @serializable(name="text", type='basestring') def text(self): """ Property is of type: 'basestring' """ return self.get_field_value("text") @text.setter def text(self, text): """ Property is of type: 'basestring' """ self.set_field_value("text", text) def set_text(self, text): self.text = text return self @property @serializable(name="sentAt", type=datetime) def sent_at(self): """ Property is of type: datetime """ return self.get_field_value("sent_at") @sent_at.setter def sent_at(self, sent_at): """ Property is of type: datetime """ self.set_field_value("sent_at", sent_at) def set_sent_at(self, sent_at): self.sent_at = sent_at return self @property @serializable(name="doneAt", type=datetime) def done_at(self): """ Property is of type: datetime """ return self.get_field_value("done_at") @done_at.setter def done_at(self, done_at): """ Property is of type: datetime """ self.set_field_value("done_at", done_at) def set_done_at(self, done_at): self.done_at = done_at return self @property @serializable(name="smsCount", type=int) def sms_count(self): """ Property is of type: int """ return self.get_field_value("sms_count") @sms_count.setter def sms_count(self, sms_count): """ Property is of type: int """ self.set_field_value("sms_count", sms_count) def set_sms_count(self, sms_count): self.sms_count = sms_count return self @property @serializable(name="mccMnc", type='basestring') def mcc_mnc(self): """ Property is of type: 'basestring' """ return self.get_field_value("mcc_mnc") @mcc_mnc.setter def mcc_mnc(self, mcc_mnc): """ Property is of type: 'basestring' """ self.set_field_value("mcc_mnc", mcc_mnc) def set_mcc_mnc(self, mcc_mnc): self.mcc_mnc = mcc_mnc return self @property @serializable(name="price", type=Price) def price(self): """ Property is of type: Price """ return self.get_field_value("price") @price.setter def price(self, price): """ Property is of type: Price """ self.set_field_value("price", price) def set_price(self, price): self.price = price return self @property @serializable(name="status", type=Status) def status(self): """ Property is of type: Status """ return self.get_field_value("status") @status.setter def status(self, status): """ Property is of type: Status """ self.set_field_value("status", status) def set_status(self, status): self.status = status return self @property @serializable(name="error", type=Error) def error(self): """ Property is of type: Error """ return self.get_field_value("error") @error.setter def error(self, error): """ Property is of type: Error """ self.set_field_value("error", error) def set_error(self, error): self.error = error return self @property @serializable(name="callbackData", type='basestring') def callback_data(self): """ Property is of type: 'basestring' """ return self.get_field_value("callback_data") @callback_data.setter def callback_data(self, callback_data): """ Property is of type: 'basestring' """ self.set_field_value("callback_data", callback_data) def set_callback_data(self, callback_data): self.callback_data = callback_data return self
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envec/multipart.py
jwodder/envec
0
130164
from enum import Enum import itertools import json import warnings from ._util import cheap_repr, for_json class CardClass(Enum): normal = 1 split = 2 flip = 3 double_faced = 4 BFM = 5 def for_json(self): return self.name class MultipartDB: DEFAULT_DATAFILE = 'data/multipart.json' def __init__(self, infile=None): if infile is None: infile = open(self.DEFAULT_DATAFILE) with infile: data = json.load(infile) self.sourcefile = infile.name self.byName = {} self.byClass = {} for cclass in CardClass: if cclass == CardClass.normal: continue classed = data.get(cclass.name, []) self.byClass[cclass] = classed for entry in classed: entry["cardClass"] = cclass for name in (entry["primary"], entry["secondary"]): if name in self.byName: warnings.warn('%s: name appears more than once in' ' multipart file; subsequent appearance' ' ignored' % (name,)) else: self.byName[name] = entry def cardClass(self, name): try: entry = self.byName[name] except KeyError: return CardClass.normal else: return entry["cardClass"] def isPrimary(self, name): try: return self.byName[name]["primary"] == name except KeyError: return False def isSecondary(self, name): try: return self.byName[name]["secondary"] == name except KeyError: return False def isSplit(self, name): return self.cardClass(name) == CardClass.split def isFlip(self, name): return self.cardClass(name) == CardClass.flip def isDouble(self, name): return self.cardClass(name) == CardClass.double_faced def isMultipart(self, name): return self.cardClass(name) != CardClass.normal def primaries(self): for entry in self: yield entry["primary"] def secondaries(self): for entry in self: yield entry["secondary"] def alternate(self, name): try: entry = self.byName[name] except KeyError: return None else: return entry["secondary" if entry["primary"] == name else "primary"] def __iter__(self): return itertools.chain.from_iterable(self.byClass.values()) def __len__(self): return sum(map(len, self.byClass.values())) def __repr__(self): return cheap_repr(self) def for_json(self): return for_json(vars(self), trim=True)
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splot.py
delvallem/specDS
0
184444
''' Spectra plottings ''' import numpy as np import matplotlib.pyplot as plt def singles(wn, spec): ''' Individual spectra plot. Parameters ---------- wn : ndarray Wavenumber of shape [n_points]. spec : ndarray Spectra of shape [n_spectra, n_points]. Returns ------- None. ''' fig, ax = plt.subplots() plt.xlabel('Wavenumber ($\mathrm{cm^{-1}}$)') plt.ylabel('Absorbance') plt.xlim(np.ceil(wn.max()), np.floor(wn.min())) plt.plot(wn, spec.T) plt.grid(False) def means(wn, spec, label=False, std=False): ''' Mean spectra plot. If label is passed, one mean per group. If std, plot mean + standard deviation. Parameters ---------- wn : ndarray Wavenumber of shape [n_points]. spec : ndarray Spectra of shape [n_spectra, n_points]. label : list of str, optional Labels of shape [n_sepctra]. The default is False. std : boolean, optional If True, plot mean + standard deviation. The default is False. Returns ------- None. ''' if label: label_set = list(set(label)) specmean = [] specstd = [] for i in range(len(label_set)): mask = [None]*len(label) for j in range(len(label)): mask[j] = (label[j] == label_set[i]) specmean += [np.mean(spec[mask,:], axis=0)] specstd += [np.std(spec[mask,:], axis=0)] specmean = np.array(specmean) specstd = np.array(specstd) else: specmean = np.mean(spec, axis=0) specstd = np.std(spec, axis=0) fig, ax = plt.subplots() plt.grid() plt.xlabel('Wavenumber ($\mathrm{cm^{-1}}$)') plt.ylabel('Absorbance') plt.xlim(np.ceil(wn.max()), np.floor(wn.min())) plt.plot(wn, specmean.T) if std: if len(specstd.shape) == 1: plt.fill_between(wn, (specmean-1*specstd), (specmean+1*specstd), alpha=0.25) else: for i in range(specstd.shape[0]): plt.fill_between(wn, (specmean[i,:]-1*specstd[i,:]), (specmean[i,:]+1*specstd[i,:]), alpha=0.25) if label: plt.legend(label_set) plt.grid(False) def img(values, n_sample, fpa_size): ''' Plot images given values such as area, intensities. Parameters ---------- values : ndarray Values to be plotted as image n_sample : int Sample to be plotted fpa_size : int Size of the FPA. Returns ------- None. ''' # Reshape to an image of shape fpa_size x fpa_size values_img = np.reshape( values[0+(fpa_size*fpa_size*n_sample) :fpa_size*fpa_size+(fpa_size*fpa_size*n_sample)], (fpa_size,fpa_size) ) # Define zero (outliers) as black cmap = plt.cm.jet cmap.set_under(color='black') # Define the scale min as the values_img min vmin = np.min(values_img[np.nonzero(values_img)])-0.000001 # Plot image fig, ax = plt.subplots() plt.imshow(values_img, cmap=cmap, vmin=vmin) ax.axes.get_xaxis().set_visible(False) ax.axes.get_yaxis().set_visible(False) plt.colorbar()
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simple_object_detection/utils/video/sequence.py
RubenEu/simple-object-detection
0
82467
<gh_stars>0 from typing import List, Tuple, Optional import cv2 from simple_object_detection.exceptions import SimpleObjectDetectionException from simple_object_detection.typing import Image, VideoProperties class StreamSequence: """Clase para cargar los frames de una secuencia de vídeo. Se utiliza la notación de acceso a un objeto ``object[item]``. Así se puede ir cargando el vídeo poco a poco sin llegar a saturar la memoria RAM. TODO: - Ir marcando los que se han visto. - Crear un hilo que vaya trayendo los nuevos a memoria. - Etc. Etc. Optimizar esto! - Implementar __iter__. (PEP 234) - Configuración de espacio de color (RGB actualmente). """ def __init__(self, video_path: str, cache_size: int = 100): # Abrir el stream con OpenCV. self.stream = self._open_video_stream(video_path) # Información del vídeo. self.width: int = int(self.stream.get(cv2.CAP_PROP_FRAME_WIDTH)) self.height: int = int(self.stream.get(cv2.CAP_PROP_FRAME_HEIGHT)) self._fps: float = float(self.stream.get(cv2.CAP_PROP_FPS)) self._num_frames_available: int = int(self.stream.get(cv2.CAP_PROP_FRAME_COUNT)) # Caching (Almacena el número del frame y la imagen). self._cache: List[Tuple[int, Image]] = [(..., ...)] * cache_size # Inicio y fin del vídeo. self._start_frame = 0 self._end_frame = self._num_frames_available - 1 def __del__(self) -> None: """Libera el recurso del vídeo cargado y elimina el objeto también. """ if hasattr(self, 'stream') and self.stream.isOpened(): self.stream.release() del self.stream def __getitem__(self, item: int) -> Image: """Obtiene el frame item-ésimo. Si se ha establecido un frame inicial o final distinto con los métodos ``set_start_frame`` o ``set_end_frame``, el frame 0 será el del límite inferior y el frame último el del límite superior, actuando como si el stream de vídeo introducido estuviese acotado por ellos y no por los originales. TODO: Cachear. Cargar chunk. Etc. Etc. Mostrar rendimiento haciendo caching. https://medium.com/fintechexplained/advanced-python-how-to-implement-caching-in-python-application-9d0a4136b845 TODO: Añadir slicing: https://www.geeksforgeeks.org/implementing-slicing-in-__getitem__/#:~:text=slice%20is%20a%20constructor%20in,can%20be%20defined%20inside%20it.&text=Parameter%3A,constructor%20to%20create%20slice%20object. """ # Comprobación del ítem. if not isinstance(item, int): raise TypeError() # Calcular el índice del frame. fid = self._calculate_frame_index(item) # Extraer el frame buscado. frame_bgr = self._get_frame(fid) # Comprobar el valor de salida. frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB) return frame_rgb def __len__(self) -> int: """Devuelve el número de frames de la secuencia (usando los limites establecidos o iniciales) """ return self.num_frames def set_start_frame(self, frame: int) -> None: """Establece el frame inicial. Realiza la comprobación de que sea superior a 0 y que no sea superior o igual al frame final. :param frame: frame inicial. :return: None. """ if frame < 0: raise SimpleObjectDetectionException('No se puede establecer un frame inicial inferior' 'a 0.') elif frame >= self._end_frame: raise SimpleObjectDetectionException('No se puede establecer un frame igual o superior' 'al frame final.') self._start_frame = frame def set_end_frame(self, frame: int) -> None: """Establece el frame final. Realiza la comprobación de que no sea superior o igual a la cantidad de frames disponibles. Además comprueba también que no sea inferior o igual al frame inicial. :param frame: frame final. :return: None. """ if frame >= self._num_frames_available: raise SimpleObjectDetectionException('No se puede establecer un frame final superior o' 'igual a la cantidad de frames disponibles.') elif frame <= self._start_frame: raise SimpleObjectDetectionException('No se puede establecer un frame final menor o' 'igual que el frame inicial.') self._end_frame = frame def _calculate_frame_index(self, fid: int) -> int: """Si se ha establecido un límite inferior o superior distinto, recalcula. Comprueba que el índice está entre 0 y el número de frames disponibles. :param fid: :return: índice calculado del frame. """ calculated_fid = self._start_frame + fid # Comprobar que está en el intervalo especificado. if not self._start_frame <= calculated_fid <= self._end_frame: raise IndexError(f'El frame {calculated_fid} está fuera del intervalo' f'[{self._start_frame}, {self._end_frame}].') return calculated_fid def _get_frame(self, fid: int) -> Image: """Extrae el frame fid-ésimo de la secuencia de vídeo. Primeramente busca si está en caché, si lo encuentra, lo devuelve. Si se produce un *miss*, trae a caché el tamaño de bloque epecificado por ``cache_size`` y devuelve el frame buscado. :param fid: número del frame. :return: frame. """ # Comprobación del índice. if fid >= self.num_frames_available: raise IndexError('Se ha excedido el límite.') # Buscar en caché primero. cached = self._search_in_cache(fid) if cached is None: return self._pull_to_cache(fid) return cached def _search_in_cache(self, fid: int) -> Optional[Image]: """Busca en la caché el frame especificado. Si no lo encuentra, devuelve None. :param fid: número del frame. :return: frame buscado si es encontrado, si no, None. """ expected_index = fid % len(self._cache) frame_id, frame = self._cache[expected_index] if frame_id == fid: return frame return None def _pull_to_cache(self, fid: int) -> Image: """Trae a caché el lote de frames donde se encuentra el frame fid-ésimo. Además, devuelve el frame fid-ésimo. :param fid: número del frame para traer a caché. :return: frame fid-ésimo. """ # Establecer en el frame que se busca. retval = self.stream.set(cv2.CAP_PROP_POS_FRAMES, float(fid)) if not retval: raise Exception('Ocurrió un error al posicionar el número de frame.') # Iterar mientras haya frames disponibles.from actual_frame_id = fid # Añadir los siguientes frames que quepan la caché. while actual_frame_id < self.num_frames_available: # Capturar frame a frame. actual_frame_id = int(self.stream.get(cv2.CAP_PROP_POS_FRAMES)) ret, frame = self.stream.read() # Comprobar si se ha leído el frame correctamente. if not ret: break # Añadir a la caché self._cache[actual_frame_id % len(self._cache)] = (actual_frame_id, frame) # Comprobar si se ha rellenado la caché. if (actual_frame_id + 1) % len(self._cache) == 0: break # Devolver el frame que se buscaba. return self._cache[fid % len(self._cache)][1] @staticmethod def _open_video_stream(video_path: str) -> cv2.VideoCapture: """Abre el streaming del vídeo. :param video_path: ruta al archivo del vídeo. :return: stream del vídeo. """ cap = cv2.VideoCapture(video_path) # Comprobar si el vídeo está disponible. if not cap.isOpened(): raise Exception(f'The {video_path} can\'t be opened or doesn\'t exists.') return cap @property def fps(self) -> float: """Número de frames por segundo de la secuencia de vídeo.""" return self._fps @fps.setter def fps(self, value: float) -> None: """Modificar el número de frames por segundo de la secuencia de vídeo. Utilizar únicamente para labores de depuración. Modificar este valor puede llevar a comportamientos inesperados. :param value: nuevo valor de fps. :return: None. """ self._fps = value @property def num_frames_available(self) -> int: """Número de frames total disponibles en la secuencia de vídeo. :return: número de frames total disponible """ return self._num_frames_available @num_frames_available.setter def num_frames_available(self, value: int) -> None: """Establecer el número de frames disponibles. Utilizar úniacmente para labores de depuración. :param value: cantidad de frames disponibles. :return: """ self._num_frames_available = value @property def num_frames(self) -> int: """Cálculo del número de frames teniendo en cuenta el frame inicial y final establecido. :return: número de frames con los límites establecidos. """ return self._end_frame - self._start_frame + 1 def properties(self) -> VideoProperties: """Devuelve una tupla con las propiedades del vídeo. La tupla tiene la estructura (width, height, fps, num_frames). :return: propiedades del vídeo. """ return VideoProperties(self.width, self.height, self.fps, self.num_frames) class StreamSequenceWriter: """Clase para la escritura de una secuencia de imágenes en un archivo de vídeo. """ def __init__(self, file_output: str, properties: VideoProperties): fourcc = cv2.VideoWriter_fourcc(*'DIVX') width, height, fps, _ = properties self._stream = cv2.VideoWriter(file_output, fourcc, fps, (width, height)) def __del__(self): """Cierra la conexión con el archivo y elimina la instancia del stream. """ self.release() del self._stream def write(self, frame: Image) -> None: """Escribe un frame al final de la secuencia de vídeo. :param frame: imagen para escribir. :return: None. """ # Convertir la imagen a BGR porque cv2 trabaja con ese espacio de colores. frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR) # Escribir el frame. self._stream.write(frame) def release(self) -> None: """Cierra la conexión con el archivo. """ if hasattr(self, '_stream') and self._stream.isOpened(): self._stream.release() @staticmethod def save_sequence(sequence: StreamSequence, file_output: str, properties: VideoProperties = None) -> None: """Guarda una secuencia de vídeo frame a frame en un archivo. En esencia, lo que hace es copiar lo que entra por un stream de entrada y guardarlo en un archivo a través de un stream de salida. Este método tiene propósito de depuración y comprobación. :param sequence: secuencia de vídeo. :param file_output: archivo de salida. :param properties: propiedades del vídeo de salida. Si es None se obtienen de la secuencia de entrada. :return: None. """ # Si no se pasaron propiedades, obtenerlas de la secuencia properties = sequence.properties() # Abrir el stream. output_stream = StreamSequenceWriter(file_output, properties) # Guardar todos los frames de la secuencia. for frame in sequence: output_stream.write(frame)
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scripts/elements_monitoring.py
LoSk-p/robonomics_vacuum
0
176955
#!/usr/bin/env python3 import rospy import rospkg import typing as tp import yaml from robonomics_vacuum.srv import Element from std_msgs.msg import String from miio import RoborockVacuum import os import datetime from robonomics_vacuum.utils import read_config class ElementsMonitoring: def __init__(self) -> None: rospy.init_node("elements_monitoring") address = rospy.get_param("~address") token = rospy.get_param("~token") self.config_name = rospy.get_param("~config_name") self.vacuum = RoborockVacuum(address, token) history = self.vacuum.clean_history() rospack = rospkg.RosPack() self.path = rospack.get_path('robonomics_vacuum') self.default_elements = read_config(f"{self.path}/config/config{self.config_name}.yaml") if not os.path.exists(f"{self.path}/data/cleaning_info{self.config_name}.yaml"): elements = {'number_cleaning': history.count, 'elements': []} for element in self.default_elements['elements']: elements['elements'].append({'name': element['name'], 'time_from_last_replace': 0}) self.rewrite_yaml(path=f"{self.path}/data/cleaning_info{self.config_name}.yaml", data=elements) rospy.Service("replace_element", Element, self.replace_element) self.pub_datalog = rospy.Publisher("datalog", String, queue_size=10) def rewrite_yaml(self, path: str, data: tp.List) -> None: with open(path, 'w') as f: yaml.dump(data, f, default_flow_style=False) def replace_element(self, req) -> None: rospy.loginfo(f"type req: {type(req)}") elements = read_config(f"{self.path}/data/cleaning_info{self.config_name}.yaml") for element in elements['elements']: if element['name'] == req.element: element['time_from_last_replace'] = 0 self.rewrite_yaml(path=f"{self.path}/data/cleaning_info{self.config_name}.yaml", data=elements) return "OK" def spin(self) -> None: rate = rospy.Rate(1) while not rospy.is_shutdown(): rate.sleep() history = self.vacuum.clean_history() config = read_config(f"{self.path}/data/cleaning_info{self.config_name}.yaml") clean_time = datetime.timedelta(hours=0, minutes=0, seconds=0) if history.count > config['number_cleaning']: for i in range(history.count - config['number_cleaning']): clean = self.vacuum.clean_details(history.ids[-1-i]) clean_time += clean.duration elements = config for element in elements['elements']: last_delta = int(element['time_from_last_replace']) last_delta += clean_time.seconds element['time_from_last_replace'] = last_delta for default_element in self.default_elements['elements']: if element['name'] == default_element['name']: if element['time_from_last_replace']/3600 > default_element['working_time']: self.pub_datalog.publish(f"You should replace element {element['name']}") elements['number_cleaning'] = history.count self.rewrite_yaml(path=f"{self.path}/data/cleaning_info{self.config_name}.yaml", data=elements) if __name__ == '__main__': ElementsMonitoring().spin()
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mgmt/src/constants.py
pcaruana/sombrio
0
1122
#! /usr/bin/env python3 """ constants.py - Contains all constants used by the device manager Author: - <NAME> (<EMAIL> at <EMAIL> dot <EMAIL>) Date: 12/3/2016 """ number_of_rows = 3 # total number rows of Index Servers number_of_links = 5 # number of links to be sent to Crawler number_of_chunks = 5 # number of chunks to be sent to Index Builder number_of_comps = 10 # number of components managed by each watchdog
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handle.py
zhuangdx/timer_deleter
0
132418
#!/usr/bin/env python3 # -*- coding: utf-8 -*- # @Time : 2018/10/31 16:32 # @Author : duoxuan·zhuang # @File : handle.py """ 从配置文件读取指定路径，删除超过时间的过期指定类型文件 （适用于linux） 逻辑： 1.读取配置文件---多个路径 2.遍历路径，读取类型，时间 3.获取过期文件数量-删除文件 4.获取空文件夹数量-删除空文件夹 """ import datetime import json import logging import logging.config import os import sys from utils import os_tools logging.config.fileConfig("./conf/log.conf") # 获取文件数量 check_file_count = ' | wc -l' day_find = ' -mtime +%s ' # 获取7天前的文件 get_file_s = "find %s" # 指定文件类型 filter_type = ' -name "%s" ' # 筛选空文件夹 empty_folder = " -maxdepth 1 -type d -empty " # 删除 delete_cmd = " -exec rm -rf {} \;" class CosSyncConfig(object): """从本地json文件读取配置""" def __init__(self, config_path=u'config.json'): if not os.path.isfile(config_path): self.init_config_err = u'配置文件 %s 不存在' % config_path self.init_config_flag = False return config_file = open(config_path, 'r', encoding="utf-8") try: config_str = config_file.read() self.config_json = json.loads(config_str) except json.decoder.JSONDecodeError: self.init_config_err = u'配置文件格式无法识别' self.init_config_flag = False return finally: config_file.close() valid_config_key_arr = ['路径', '文件类型', '过期时间'] for json1 in self.config_json: for config_key in valid_config_key_arr: if config_key not in json1.keys(): self.init_config_err = u'没有配置key %s' % config_key self.init_config_flag = False return self.init_config_flag = True self.init_config_err = u'' def is_valid_config(self): return self.init_config_flag def get_err_msg(self): return self.init_config_err def run_shell_8_result(shell_str): """ 运行命令行，返回运行结果 :param shell_str: :return: """ return os_tools.run_cmd_block(shell_str) def get_cmd_count(cmd_str): """ 获取该命令的结果行数--int :param cmd_str: :return: """ cmd_str_count = cmd_str + check_file_count rr = run_shell_8_result(cmd_str_count) rr_list = rr.split() return int(rr_list[0]) def get_file_7_day(path, _type='', day='7'): """ 筛选过期文件，1.先获取文件并删除 2.查找空文件夹并删除 :param path: :param _type: :param day: :return: """ if day == '0': cmd_str = get_file_s % path + filter_type % _type else: cmd_str = get_file_s % path + day_find % day + filter_type % _type logging.info(cmd_str) count_f = get_cmd_count(cmd_str) if count_f: logging.info('文件数量：%d', count_f) logging.info('过期文件：') logging.info('\n' + run_shell_8_result(cmd_str)) logging.info('\n' + run_shell_8_result(cmd_str + delete_cmd)) # 删除空文件夹 cmd_str_empty = get_file_s % path + empty_folder count_f = get_cmd_count(cmd_str_empty) if len(os.listdir(path)) > 0 and count_f: logging.info('空文件夹数量：%d', count_f) logging.info('具体文件夹：') logging.info('\n' + run_shell_8_result(cmd_str_empty)) logging.info('\n' + run_shell_8_result(cmd_str_empty + delete_cmd)) def main(conf_file="conf/config.json"): logging.info('** %s', datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')) config = CosSyncConfig(conf_file) if not config.is_valid_config(): logging.error('wrong config: ' + config.get_err_msg()) logging.info("\n\n") sys.exit(1) for onejson in config.config_json: folder_path = onejson['路径'] file_type = onejson['文件类型'] file_time = onejson['过期时间'] if os.path.exists(folder_path): get_file_7_day(path=folder_path, _type=file_type, day=file_time) else: logging.warning("不存在 %s", folder_path) logging.info("\n\n") if __name__ == "__main__": main()
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salesforce/campaign.py
DemocracyLab/DemocracyLab-CivicTechExchange
0
67808
from common.helpers.collections import omit_falsy from common.models import Tag from .client import SalesforceClient import json import requests import threading ''' Project model maps to the Campaign object in Salesforce ''' client = SalesforceClient() def run(request): response = SalesforceClient().send(request) def save(project: object): data = { "ownerid": client.owner_id, "Project_Owner__r": { "platform_id__c": project.project_creator.id }, "recordtypeid": "01246000000uOeRAAU", "name": project.project_name, "isactive": project.is_searchable, "project_url__c": project.project_url, "description_action__c": project.project_description_actions, "description_solution__c": project.project_description_solution, "short_description__c": project.project_short_description, "description": project.project_description, "issue_area__c": Tag.tags_field_descriptions(project.project_issue_area), "stage__c": Tag.tags_field_descriptions(project.project_stage), "type": Tag.tags_field_descriptions(project.project_organization_type), "technologies__c": Tag.tags_field_descriptions(project.project_technologies) } if project.project_date_created: data['startdate'] = project.project_date_created.strftime('%Y-%m-%d') req = requests.Request( method="PATCH", url=f'{client.campaign_endpoint}/platform_id__c/{project.id}', data=json.dumps(data) ) thread = threading.Thread(target=run, args=(req,)) thread.daemon = True thread.start() def delete(project: object): req = requests.Request( method="DELETE", url=f'{client.campaign_endpoint}/platform_id__c/{project.id}' ) thread = threading.Thread(target=run, args=(req,)) thread.daemon = True thread.start()
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exercise/ch04/mini_batch.py
HFTshoon/deep-learning-from-scratch
0
189872
<reponame>HFTshoon/deep-learning-from-scratch import sys,os sys.path.append(os.pardir) from dataset.mnist import load_mnist import numpy as np (x_train,t_train),(x_test,t_test)=load_mnist(normalize=True,one_hot_label=True) print(x_train.shape) print(t_train.shape) train_size = x_train.shape[0] batch_size=10 batch_mask=np.random.choice(train_size,batch_size) print(batch_mask) x_batch=x_train[batch_mask] t_batch=t_train[batch_mask]
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avatar2/protocols/jlink.py
ispras/avatar2
415
115861
import sys import pylink from time import sleep from threading import Thread, Event, Condition import logging import re if sys.version_info < (3, 0): import Queue as queue # __class__ = instance.__class__ else: import queue from avatar2.archs.arm import ARM from avatar2.targets import TargetStates from avatar2.message import AvatarMessage, UpdateStateMessage, BreakpointHitMessage class JLinkProtocol(Thread): """Main class for the JLink bprotocol, via pylink-square :ivar serial: The serial number of the JLink to connect to :ivar device: The JLink device name for the target :ivar avatar: the avatar object :ivar origin: the target utilizing this protocol """ def __init__(self, serial="12345678", device="ARM7", avatar=None, origin=None): self._shutdown = Event() self.avatar = avatar self.origin = origin self.jlink = pylink.JLink() self.jlink.open(serial) self.log = logging.getLogger('%s.%s' % (origin.log.name, self.__class__.__name__) ) if origin else \ logging.getLogger(self.__class__.__name__) Thread.__init__(self) self.connect(device=device) def __del__(self): self.shutdown() def connect(self, device="ARM7"): # Todo add a time out here while True: try: self.jlink.connect(device, verbose=True) self.jlink.ir_len() break except pylink.errors.JLinkException: self.log.info("Connection failed, trying again...") sleep(0.25) self.log.info("Connected to JLink target") self.start() return True def reset(self, halt=True): self.log.info("Resetting target") return self.jlink.reset(halt=halt) def shutdown(self): self._shutdown.set() def update_target_regs(self): """ This function will try to update the TargetRegs based on the list of registers known to gdb. """ regs = {} for idx in self.jlink.register_list(): name = self.jlink.register_name(idx) regs[name] = idx if hasattr(self.origin, 'regs'): self.origin.regs._update(regs) def run(self): # Target state management thread # This thread needs to poll for the halted state # of the target # JLink is lame and doesn't let you do this asynch # Also, not all targets produce a "moe" (Mode of Entry) # so we have to actually do that here. try: while not self._shutdown.is_set(): is_halted = self.jlink.halted() if is_halted and self.origin.state == TargetStates.RUNNING: # We just halted # But did we hit a BP? self.log.debug("JLink Target is halting...") avatar_msg = UpdateStateMessage(self.origin, TargetStates.STOPPED) self.avatar.fast_queue.put(avatar_msg) self.origin.wait() self.log.debug("JLink target has halted") pc = self.get_pc() if self.jlink.breakpoint_find(pc): self.log.debug("JLink Target hit breakpoint %d" % self.jlink.breakpoint_find(pc)) avatar_msg = BreakpointHitMessage(self.origin, self.jlink.breakpoint_find(pc), pc) self.avatar.queue.put(avatar_msg) elif not is_halted and self.origin.state == TargetStates.STOPPED: self.log.debug("About to resume target.") avatar_msg = UpdateStateMessage(self.origin, TargetStates.RUNNING) self.avatar.fast_queue.put(avatar_msg) while self.origin.state != TargetStates.RUNNING: pass self.log.debug("JLink target has resumed") except: self.log.exception("JLink target errored") finally: self.log.info("JLink target exiting") self.jlink.close() def set_breakpoint(self, line, hardware=False, temporary=False, regex=False, condition=None, ignore_count=0, thread=0, pending=False): """Inserts a breakpoint :param bool hardware: Hardware breakpoint :param bool temporary: Tempory breakpoint :param str regex: If set, inserts breakpoints matching the regex :param str condition: If set, inserts a breakpoint with specified condition :param int ignore_count: Amount of times the bp should be ignored :param int thread: Threadno in which this breakpoints should be added :returns: The number of the breakpoint """ # TODO: Hw/Sw breakpoint control self.log.info("Setting breakpoint at %#08x" % line) ret = self.jlink.breakpoint_set(line) self.log.info("Got BP ID %d" % ret) return ret def set_watchpoint(self, variable, write=True, read=False): return self.jlink.watchpoint_set(variable, write=write, read=read) def remove_breakpoint(self, bkpt): """Deletes a breakpoint""" # TODO: Check this return self.jlink.breakpoint_clear(bkpt) def write_memory(self, address, wordsize, val, num_words=1, raw=False): """Writes memory :param address: Address to write to :param wordsize: the size of the write (1, 2, 4 or 8) :param val: the written value :type val: int if num_words == 1 and raw == False list if num_words > 1 and raw == False str or byte if raw == True :param num_words: The amount of words to read :param raw: Specifies whether to write in raw or word mode :returns: True on success else False """ if raw: new_val = [] if not len(val): raise ValueError("val had zero length") new_val = [ord(v) for v in val] val = new_val try: self.jlink.memory_write(address, contents) return True except pylink.JLinkException: return False def read_memory(self, address, wordsize=4, num_words=1, raw=False): """reads memory :param address: Address to write to :param wordsize: the size of a read word (1, 2, 4 or 8) :param num_words: the amount of read words :param raw: Whether the read memory should be returned unprocessed :return: The read memory """ ret = self.jlink.memory_read(address, num_units=num_words, nbits=wordsize) if raw: raw_mem = "".join([newint.to_bytes(i, length=int(math.ceil(i.bit_length() / 8.0))) for i in ret]) return raw_mem return ret def read_register(self, reg): the_reg = tolower(reg) the_idx = -1 for idx in self.jlink.register_list(): if the_reg == self.jlink.register_name(idx): the_idx = idx break return self.register_read(the_idx) def get_pc(self): # Get PC a shitty way for idx in self.jlink.register_list(): if "PC" in self.jlink.register_name(idx): return self.jlink.register_read(idx) def write_register(self, reg, val): """Set one register on the target :returns: True on success""" the_reg = tolower(reg) the_idx = -1 for idx in self.jlink.register_list(): if the_reg == self.jlink.register_name(idx): the_idx = idx break return self.jlink.register_write(the_idx, val) def step(self): """Step one instruction on the target :returns: True on success""" return self.jlink.step() def cont(self): """Continues the execution of the target :returns: True on success""" self.log.info("Resuming target...") return self.jlink.restart() def stop(self): """Stops execution of the target :returns: True on success""" self.log.info("Stopping target...") return self.jlink.halt() def set_endianness(self, endianness='little'): if 'little' in endianness: self.jlink.set_little_endian() elif "big" in endianness: self.jlink.set_big_endian()
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pollapp/forms.py
pesusieni999/mtgwebsite
0
175085
<reponame>pesusieni999/mtgwebsite<filename>pollapp/forms.py """ Define forms for Polls application. """ from django import forms from .models import Poll, PollAnswer __author__ = "pesusieni999" __copyright__ = "Copyright 2017, MtG website Project" __credits__ = ["pesusieni999"] __license__ = "MIT" __version__ = "0.0.1" __maintainer__ = "pesusieni999" __email__ = "<EMAIL>" __status__ = "Development" class PollForm(forms.ModelForm): """ Form for creating and modifying Polls. """ class Meta: model = Poll POLL_TYPE_CHOICES = ((True, 'Single selection'), (False, 'Multiple selection')) POLL_PUBLIC_CHOICES = ((True, 'Public'), (False, 'Private')) fields = ('name', 'question', 'single_selection', 'public') labels = { 'single_selection': 'Vote type', 'public': 'Vote publicity' } widgets = { 'name': forms.TextInput(attrs={'class': 'form-control form-field'}), 'question': forms.Textarea(attrs={'class': 'form-control form-field'}), 'public': forms.Select( choices=POLL_PUBLIC_CHOICES, attrs={'class': 'form-control form-field'} ), 'single_selection': forms.Select( choices=POLL_TYPE_CHOICES, attrs={'class': 'form-control form-field'} ), # 'end_time': forms.DateTimeInput(attrs={'class': 'datetimepicker'}), } class PollOptionForm(forms.Form): """ Form for defining poll options (that can be voted). """ text = forms.CharField( max_length=128, label="Option", widget=forms.TextInput(attrs={'class': 'form-control form-field'}) ) class VoteForm(forms.Form): """ Form for voting. """ def __init__(self, *args, **kwargs): # TODO: Add initialization with polls options. # TODO: Need poll options, and if poll allows multiple choices. super(VoteForm, self).__init__(*args, **kwargs)
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crisiscleanup/calls/migrations/0011_merge_20180122_2308.py
CrisisCleanup/wcicp-call-service
0
13871
# -*- coding: utf-8 -*- # Generated by Django 1.11.6 on 2018-01-22 23:08 from __future__ import unicode_literals from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('calls', '0010_auto_20180119_2117'), ('calls', '0007_auto_20180122_2157'), ] operations = [ ]
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kitsune/gallery/models.py
jgmize/kitsune
0
25810
<gh_stars>0 from datetime import datetime from django.conf import settings from django.contrib.auth.models import User from django.db import models from kitsune.sumo.models import ModelBase, LocaleField from kitsune.sumo.urlresolvers import reverse from kitsune.sumo.utils import auto_delete_files class Media(ModelBase): """Generic model for media""" title = models.CharField(max_length=255, db_index=True) created = models.DateTimeField(default=datetime.now, db_index=True) updated = models.DateTimeField(default=datetime.now, db_index=True) updated_by = models.ForeignKey(User, null=True) description = models.TextField(max_length=10000) locale = LocaleField(default=settings.GALLERY_DEFAULT_LANGUAGE, db_index=True) is_draft = models.NullBooleanField(default=None, null=True, editable=False) class Meta(object): abstract = True ordering = ['-created'] unique_together = (('locale', 'title'), ('is_draft', 'creator')) def __unicode__(self): return '[%s] %s' % (self.locale, self.title) @auto_delete_files class Image(Media): creator = models.ForeignKey(User, related_name='gallery_images') file = models.ImageField(upload_to=settings.GALLERY_IMAGE_PATH, max_length=settings.MAX_FILEPATH_LENGTH) thumbnail = models.ImageField( upload_to=settings.GALLERY_IMAGE_THUMBNAIL_PATH, null=True, max_length=settings.MAX_FILEPATH_LENGTH) def get_absolute_url(self): return reverse('gallery.media', args=['image', self.id]) def thumbnail_url_if_set(self): """Returns self.thumbnail, if set, else self.file""" return self.thumbnail.url if self.thumbnail else self.file.url @auto_delete_files class Video(Media): creator = models.ForeignKey(User, related_name='gallery_videos') webm = models.FileField(upload_to=settings.GALLERY_VIDEO_PATH, null=True, max_length=settings.MAX_FILEPATH_LENGTH) ogv = models.FileField(upload_to=settings.GALLERY_VIDEO_PATH, null=True, max_length=settings.MAX_FILEPATH_LENGTH) flv = models.FileField(upload_to=settings.GALLERY_VIDEO_PATH, null=True, max_length=settings.MAX_FILEPATH_LENGTH) poster = models.ImageField(upload_to=settings.GALLERY_VIDEO_THUMBNAIL_PATH, max_length=settings.MAX_FILEPATH_LENGTH, null=True) thumbnail = models.ImageField( upload_to=settings.GALLERY_VIDEO_THUMBNAIL_PATH, null=True, max_length=settings.MAX_FILEPATH_LENGTH) def get_absolute_url(self): return reverse('gallery.media', args=['video', self.id]) def thumbnail_url_if_set(self): """Returns self.thumbnail.url, if set, else default thumbnail URL""" progress_url = settings.GALLERY_VIDEO_THUMBNAIL_PROGRESS_URL return self.thumbnail.url if self.thumbnail else progress_url
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tests/test020_get_webhooks.py
Sila-Money/sila-sdk-python
4
189321
<gh_stars>1-10 import unittest from silasdk.users import User from tests.test_config import (app, user_handle, eth_private_key) class Test020GetWebhooksTest(unittest.TestCase): def test_001_get_webhooks_200(self): payload = { "user_handle": user_handle } response = User.get_webhooks(app, payload, eth_private_key) self.assertTrue(response["success"]) def test_002_get_webhooks_400(self): payload = { "user_handle": '' } response = User.get_webhooks(app, payload, eth_private_key) self.assertFalse(response["success"]) def test_001_retry_webhook_200(self): payload = { "user_handle": user_handle } response = User.get_webhooks(app, payload, eth_private_key) if response.get("webhooks"): event_uuid = response["webhooks"][0].get("uuid") payload = { "user_handle": user_handle, "message": "header_msg", "event_uuid":event_uuid } response = User.retry_webhook(app, payload, eth_private_key) self.assertTrue(response["success"]) if __name__ == "__main__": unittest.main()
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weaver/execute.py
crim-ca/weaver
16
85689
EXECUTE_MODE_AUTO = "auto" EXECUTE_MODE_ASYNC = "async" EXECUTE_MODE_SYNC = "sync" EXECUTE_MODE_OPTIONS = frozenset([ EXECUTE_MODE_AUTO, EXECUTE_MODE_ASYNC, EXECUTE_MODE_SYNC, ]) EXECUTE_CONTROL_OPTION_ASYNC = "async-execute" EXECUTE_CONTROL_OPTION_SYNC = "sync-execute" EXECUTE_CONTROL_OPTIONS = frozenset([ EXECUTE_CONTROL_OPTION_ASYNC, EXECUTE_CONTROL_OPTION_SYNC, ]) EXECUTE_RESPONSE_RAW = "raw" EXECUTE_RESPONSE_DOCUMENT = "document" EXECUTE_RESPONSE_OPTIONS = frozenset([ EXECUTE_RESPONSE_RAW, EXECUTE_RESPONSE_DOCUMENT, ]) EXECUTE_TRANSMISSION_MODE_VALUE = "value" EXECUTE_TRANSMISSION_MODE_REFERENCE = "reference" EXECUTE_TRANSMISSION_MODE_OPTIONS = frozenset([ EXECUTE_TRANSMISSION_MODE_VALUE, EXECUTE_TRANSMISSION_MODE_REFERENCE, ])
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venv/lib/python3.6/site-packages/ansible_collections/cisco/iosxr/plugins/module_utils/network/iosxr/facts/static_routes/static_routes.py
usegalaxy-no/usegalaxy
1
128880
# # -*- coding: utf-8 -*- # Copyright 2019 Red Hat # GNU General Public License v3.0+ # (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt) """ The iosxr static_routes fact class It is in this file the configuration is collected from the device for a given resource, parsed, and the facts tree is populated based on the configuration. """ from __future__ import absolute_import, division, print_function __metaclass__ = type import re from copy import deepcopy from ansible_collections.ansible.netcommon.plugins.module_utils.network.common import ( utils, ) from ansible_collections.cisco.iosxr.plugins.module_utils.network.iosxr.argspec.static_routes.static_routes import ( Static_routesArgs, ) class Static_routesFacts(object): """ The iosxr static_routes fact class """ def __init__(self, module, subspec="config", options="options"): self._module = module self.argument_spec = Static_routesArgs.argument_spec spec = deepcopy(self.argument_spec) if subspec: if options: facts_argument_spec = spec[subspec][options] else: facts_argument_spec = spec[subspec] else: facts_argument_spec = spec self.generated_spec = utils.generate_dict(facts_argument_spec) def get_device_data(self, connection): return connection.get_config(flags="router static") def populate_facts(self, connection, ansible_facts, data=None): """ Populate the facts for static_routes :param connection: the device connection :param ansible_facts: Facts dictionary :param data: previously collected conf :rtype: dictionary :returns: facts """ if not data: data = self.get_device_data(connection) objs = [] if "No such configuration" not in data: for entry in re.compile(r"(\s) vrf").split(data): obj = self.render_config(self.generated_spec, entry) if obj: objs.append(obj) ansible_facts["ansible_network_resources"].pop("static_routes", None) facts = {} facts["static_routes"] = [] params = utils.validate_config(self.argument_spec, {"config": objs}) for cfg in params["config"]: facts["static_routes"].append(utils.remove_empties(cfg)) ansible_facts["ansible_network_resources"].update(facts) return ansible_facts def render_config(self, spec, conf): """ Render config as dictionary structure and delete keys from spec for null values :param spec: The facts tree, generated from the argspec :param conf: The configuration :rtype: dictionary :returns: The generated config """ config = deepcopy(spec) entry_list = conf.split(" address-family") config["address_families"] = [] if "router static" not in entry_list[0]: config["vrf"] = entry_list[0].replace("!", "").strip() for item in entry_list[1:]: routes = [] address_family = {"routes": []} address_family["afi"], address_family["safi"] = self.parse_af(item) destinations = re.findall(r"((?:\S+)/(?:\d+)) (?:.*)", item, re.M) for dest in set(destinations): route = {"next_hops": []} route["dest"] = dest regex = r"%s .+$" % dest cfg = re.findall(regex, item, re.M) for route_entry in cfg: exit_point = {} exit_point["forward_router_address"] = self.parse_faddr( route_entry ) exit_point["interface"] = self.parse_intf(route_entry) exit_point["admin_distance"] = self.parse_admin_distance( route_entry ) for x in [ "tag", "tunnel-id", "metric", "description", "track", "vrflabel", "dest_vrf", ]: exit_point[x.replace("-", "_")] = self.parse_attrib( route_entry, x.replace("dest_vrf", "vrf") ) route["next_hops"].append(exit_point) routes.append(route) address_family["routes"] = sorted( routes, key=lambda i: i["dest"] ) config["address_families"].append(address_family) return utils.remove_empties(config) def parse_af(self, item): match = re.search(r"(?:\s*)(\w+)(?:\s*)(\w+)", item, re.M) if match: return match.group(1), match.group(2) def parse_faddr(self, item): for x in item.split(" "): if (":" in x or "." in x) and "/" not in x: return x def parse_intf(self, item): inf_search_strs = [ r" ((\w+)((?:\d)/(?:\d)/(?:\d)/(?:\d+)))", r" (([a-zA-Z]+)(?:\d+))", ] for i in inf_search_strs: match = re.search(i, item, re.M) if match: return match.group(1) def parse_attrib(self, item, attrib): match = re.search(r" %s (\S+)" % attrib, item) if match: val = match.group(1).strip("'") if attrib in ["tunnel-id", "vrflabel", "tag", "metric"]: val = int(val) return val def parse_admin_distance(self, item): split_item = item.split(" ") for item in [ "vrf", "metric", "tunnel-id", "vrflabel", "track", "tag", "description", ]: try: del split_item[split_item.index(item) + 1] del split_item[split_item.index(item)] except ValueError: continue try: return [ i for i in split_item if "." not in i and ":" not in i and ord(i[0]) > 48 and ord(i[0]) < 57 ][0] except IndexError: return None
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ex066.py
thiagobachiega/python
0
115502
<reponame>thiagobachiega/python num = soma = cont = 0 while True: num = int(input('Digite um número: ')) if num == 999: break soma = soma + num cont = cont + 1 print(f'A soma dos {cont} números digitados é: {soma}')
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streams/blog/migrations/0012_auto_20200928_1212.py
Engerrs/ckan.org
1
9300
<filename>streams/blog/migrations/0012_auto_20200928_1212.py # Generated by Django 3.1.1 on 2020-09-28 12:12 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0011_blogpostpage_featured'), ] operations = [ migrations.RemoveField( model_name='blogpostpage', name='date', ), migrations.AddField( model_name='blogpostpage', name='created', field=models.DateTimeField(blank=True, default=datetime.datetime.now), ), ]
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sitri/providers/contrib/ini.py
Elastoo-Team/sitri
11
12172
import configparser import os import typing from sitri.providers.base import ConfigProvider class IniConfigProvider(ConfigProvider): """Config provider for Initialization file (Ini).""" provider_code = "ini" def __init__( self, ini_path: str = "./config.ini", ): """ :param ini_path: path to ini file """ self.configparser = configparser.ConfigParser() with open(os.path.abspath(ini_path)) as f: self.configparser.read_file(f) self._sections = None @property def sections(self): if not self._sections: self._sections = list(self.configparser.keys()) return self._sections def get(self, key: str, section: str, **kwargs) -> typing.Optional[typing.Any]: # type: ignore """Get value from ini file. :param key: key or path for search :param section: section of ini file """ if section not in self.sections: return None return self.configparser[section].get(key) def keys(self, section: str, **kwargs) -> typing.List[str]: # type: ignore """Get keys of section. :param section: section of ini file """ if section not in self.sections: return [] return list(self.configparser[section].keys())
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LocStat/pipelines/output.py
nhtoshiaki/LocStat
0
15359
# -*- coding: utf-8 -*- import items class TxtFileWriter: """ Write the repository representation in the file. """ def __init__(self, file_path): self.file_path = file_path def __enter__(self): self.file = open(self.file_path, 'w', encoding='utf-8') return self def __exit__(self, *args): if self.file and not self.file.closed: self.file.close() @property def file_path(self): return self._file_path @file_path.setter def file_path(self, file_path): self._file_path = file_path @property def file(self): return self._file @file.setter def file(self, file): self._file = file @property def closed(self): if self.file: return self.file.closed else: return True def write(self, root_dir_item): if self.file and not self.file.closed: self.file.write(f'Repositorio: ' f'{root_dir_item["repository_relurl"]}\n') self.file.write(f'Total de linhas: ' f'{root_dir_item["amount_lines"]}\n') self.file.write(f'Total de bytes: ' f'{root_dir_item["amount_bytes"]}\n') self.file.write('\n') self.write_extension_statistic(root_dir_item) self.file.write('\n') self.write_tree_structure(root_dir_item) def write_extension_statistic(self, root_dir_item): """ Writes the table with the number of lines and bytes for each file extension. """ if self.file and not self.file.closed: self.file.write(f'{"Extensao":<10} | {"Linhas":^15} | ' f'{"Bytes":^15}\n') self.file.write(f'{"":=<11}|{"":=^17}|{"":=^16}\n') if 'index' in root_dir_item: for ext, info in root_dir_item['index'].items(): if len(ext) == 0: ext = '<outros>' amount_lines, amount_bytes = 0, 0 perc_lines, perc_bytes = 0, 0 if 'amount_lines' in info: amount_lines = info['amount_lines'] if 'amount_bytes' in info: amount_bytes = info['amount_bytes'] if 'amount_lines' in root_dir_item and \ root_dir_item['amount_lines'] != 0: perc_lines = int(100 * amount_lines / root_dir_item['amount_lines']) if 'amount_bytes' in root_dir_item and \ root_dir_item['amount_bytes'] != 0: perc_bytes = int(100 * amount_bytes / root_dir_item['amount_bytes']) self.file.write(f'{ext:<10} | {amount_lines:>7} ' f'({perc_lines:>3} %) | ' f'{amount_bytes:>6} ' f'({perc_bytes:>3} %)\n') def write_tree_structure(self, root_dir_item): """ Writes the repository file structure. """ def _tree_structure(file_item, depth): """ Recursive function to create the file structure. """ structure = '' for i in range(depth - 1): structure += '| ' structure += '|-- ' if 'name' in file_item: if isinstance(file_item, items.DirectoryItem): structure += f'[{file_item["name"]}]\n' if 'children' in file_item \ and type(file_item['children']) is list: for child in file_item['children']: structure += \ _tree_structure(child, depth + 1) elif isinstance(file_item, items.TextFileItem): structure += f'{file_item["name"]}' if 'amount_lines' in file_item: structure += f' ({file_item["amount_lines"]} linhas)' structure += '\n' return structure if self.file and not self.file.closed: structure = '' if 'repository_name' in root_dir_item: structure += f'[{root_dir_item["repository_name"]}]\n' if 'children' in root_dir_item and type(root_dir_item['children'])\ is list: for child in root_dir_item['children']: structure += _tree_structure(child, 1) self.file.write(structure)
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获取新冠肺炎实时数据/paqufeiyang.py
13060923171/xianmu
29
1616487
<filename>获取新冠肺炎实时数据/paqufeiyang.py<gh_stars>10-100 import requests from lxml import etree import json import time import threading headers = { "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.62 Safari/537.36" } News_set = set() #单线程版，获取网易新闻里面新冠肺炎的实时数据 def getData(): url = "https://wp.m.163.com/163/page/news/virus_report/index.html?_nw_=1&_anw_=1" html = requests.get(url,headers=headers) soup = etree.HTML(html.text) #先是获取相应数据，这里是时间和数据 current_time =soup.xpath('//div[@class = "cover_time"]/text()')[0] cover_data = soup.xpath('//div[@class = "cover_data_china"]/div[starts-with(@class,"cover")]') #开始一个无限循环 while 1: #进行不断爬取，从而达到我们的目的，实时获取数据 for cover in cover_data: title = cover.xpath('h4/text()')[0] number = cover.xpath('div[@class = "number"]/text()')[0] result = current_time+" "+title+" "+ number if result not in News_set: News_set.add(result) print(result,end=" ") #间隔时间为60秒 time.sleep(60) #多线程版，百度版新冠肺炎实时数据 def getNews(): url = "https://opendata.baidu.com/data/inner?tn=reserved_all_res_tn&dspName=iphone&from_sf=1&dsp=iphone&resource_id=28565&alr=1&query=%E8%82%BA%E7%82%8E&cb=jsonp_1588237477067_8878" html = requests.get(url,headers=headers) html_text = html.text #用获取json开始的位置 start = html_text.find('{"ResultCode"') #获取json末尾的位置 end = html_text.find(r'recall_srcids\u0000\u0000"}')+len(r'recall_srcids\u0000\u0000"}') #把json给拼接起来，并且把json转化为python的形式 json_data = json.loads(html_text[start:end]) #最新的数据，用json来定位 data_new = json_data['Result'][0]["DisplayData"]["result"]['items'] #写一个循环函数来达到我们的目的 while 1: for data in data_new: new_title = data["eventDescription"] new_time = data["eventTime"] new_url = data['eventUrl'] local_time = time.localtime(int(new_time)) current_time = time.strftime("%Y-%m-%d %H-%M-%S",local_time) result = new_title+current_time+" "+new_url if result not in News_set: News_set.add(result) print(result) time.sleep(60) def xingXi(): print("新冠肺炎情况：") #单线程开启网易新闻的新冠肺炎的实时情况 print("实时新闻:") getNews() #多线程开启百度新冠肺炎的实时情况 print("百度提供实时新闻") threading.Thread(target=getNews().start()) if __name__ == '__main__': xingXi()
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salt/matchers/nodegroup_match.py
casselt/salt
0
1603574
# -*- coding: utf-8 -*- ''' This is the default nodegroup matcher. ''' from __future__ import absolute_import, print_function, unicode_literals import salt.utils.minions # pylint: disable=3rd-party-module-not-gated import salt.loader def match(tgt, nodegroups): ''' This is a compatibility matcher and is NOT called when using nodegroups for remote execution, but is called when the nodegroups matcher is used in states ''' if tgt in nodegroups: matchers = salt.loader.matchers(__opts__) return matchers['compound_match.match']( salt.utils.minions.nodegroup_comp(tgt, nodegroups) ) return False
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tests/integration/test_github.py
Hojang2/ogr
0
133628
<gh_stars>0 import os import unittest import pytest from github import GithubException from ogr import GithubService from ogr.abstract import PRStatus, IssueStatus from ogr.persistent_storage import PersistentObjectStorage from ogr.exceptions import GithubAPIException DATA_DIR = "test_data" PERSISTENT_DATA_PREFIX = os.path.join( os.path.dirname(os.path.realpath(__file__)), DATA_DIR ) class GithubTests(unittest.TestCase): def setUp(self): self.token = os.environ.get("GITHUB_TOKEN") self.user = os.environ.get("GITHUB_USER") test_name = self.id() or "all" persistent_data_file = os.path.join( PERSISTENT_DATA_PREFIX, f"test_github_data_{test_name}.yaml" ) PersistentObjectStorage().storage_file = persistent_data_file if PersistentObjectStorage().is_write_mode and ( not self.user or not self.token ): raise EnvironmentError("please set GITHUB_TOKEN GITHUB_USER env variables") self.service = GithubService(token=self.token) self.ogr_project = self.service.get_project( namespace="packit-service", repo="ogr" ) self.ogr_fork = self.service.get_project( namespace="packit-service", repo="ogr", is_fork=True ) self.hello_world_project = self.service.get_project( namespace="packit-service", repo="hello-world" ) self.not_forked_project = self.service.get_project( namespace="fedora-modularity", repo="fed-to-brew" ) def tearDown(self): PersistentObjectStorage().dump() class Comments(GithubTests): def test_pr_comments(self): pr_comments = self.ogr_project.get_pr_comments(9) assert pr_comments assert len(pr_comments) == 2 assert pr_comments[0].comment.endswith("fixed") assert pr_comments[1].comment.startswith("LGTM") def test_pr_comments_reversed(self): pr_comments = self.ogr_project.get_pr_comments(9, reverse=True) assert pr_comments assert len(pr_comments) == 2 assert pr_comments[0].comment.startswith("LGTM") def test_pr_comments_filter(self): pr_comments = self.ogr_project.get_pr_comments(9, filter_regex="fixed") assert pr_comments assert len(pr_comments) == 1 assert pr_comments[0].comment.startswith("@TomasTomecek") pr_comments = self.ogr_project.get_pr_comments( 9, filter_regex="LGTM, nicely ([a-z]*)" ) assert pr_comments assert len(pr_comments) == 1 assert pr_comments[0].comment.endswith("done!") def test_pr_comments_search(self): comment_match = self.ogr_project.search_in_pr(9, filter_regex="LGTM") assert comment_match assert comment_match[0] == "LGTM" comment_match = self.ogr_project.search_in_pr( 9, filter_regex="LGTM, nicely ([a-z]*)" ) assert comment_match assert comment_match[0] == "LGTM, nicely done" class GenericCommands(GithubTests): def test_description(self): description = self.ogr_project.get_description() assert description.startswith("One Git library to Rule") def test_branches(self): branches = self.ogr_project.get_branches() assert branches assert set(branches) == {"master"} def test_git_urls(self): urls = self.ogr_project.get_git_urls() assert urls assert len(urls) == 2 assert "git" in urls assert "ssh" in urls assert urls["git"] == "https://github.com/packit-service/ogr.git" assert urls["ssh"].endswith("[email protected]:packit-service/ogr.git") def test_username(self): # changed to check just lenght, because it is based who regenerated data files assert len(self.service.user.get_username()) > 3 def test_email(self): test_str = self.service.user.get_email() assert test_str assert len(test_str) > 0 assert "@" in test_str assert "." in test_str def test_get_file(self): file_content = self.ogr_project.get_file_content(".git_archival.txt") assert file_content assert isinstance(file_content, str) assert "ref-names:" in file_content def test_nonexisting_file(self): with self.assertRaises(FileNotFoundError): self.ogr_project.get_file_content(".blablabla_nonexisting_file") def test_parent_project(self): assert self.ogr_fork.parent.namespace == "packit-service" assert self.ogr_fork.parent.repo == "ogr" @unittest.skip("get_commit_flags not implemented") def test_commit_flags(self): flags = self.ogr_project.get_commit_flags( commit="29ca3caefc781b4b41245df3e01086ffa4b4639e" ) assert isinstance(flags, list) assert len(flags) == 0 def test_get_sha_from_tag(self): assert ( self.ogr_project.get_sha_from_tag("0.0.1") == "29ca3caefc781b4b41245df3e01086ffa4b4639e" ) with pytest.raises(GithubAPIException) as ex: self.ogr_project.get_sha_from_tag("future") assert "not found" in str(ex.value) def test_get_tag_from_tag_name(self): tag = self.ogr_project.get_tag_from_tag_name("0.0.1") assert tag.name == "0.0.1" assert tag.commit_sha == "29ca3caefc781b4b41245df3e01086ffa4b4639e" def test_get_tag_from_nonexisting_tag_name(self): assert not self.ogr_project.get_tag_from_tag_name("future") def test_get_owners(self): owners = self.ogr_project.get_owners() assert ["packit-service"] == owners def test_issue_permissions(self): users = self.ogr_project.who_can_close_issue() assert "lachmanfrantisek" in users issue = self.ogr_project.get_issue_info(1) assert self.ogr_project.can_close_issue("lachmanfrantisek", issue) assert not self.ogr_project.can_close_issue("marusinm", issue) def test_pr_permissions(self): users = self.ogr_project.who_can_merge_pr() assert "lachmanfrantisek" in users assert self.ogr_project.can_merge_pr("lachmanfrantisek") assert not self.ogr_project.can_merge_pr("marusinm") class Issues(GithubTests): def test_issue_list(self): issue_list = self.ogr_fork.get_issue_list() assert isinstance(issue_list, list) assert not issue_list issue_list_all = self.ogr_project.get_issue_list(status=IssueStatus.all) assert issue_list_all assert len(issue_list_all) >= 45 issue_list_closed = self.ogr_project.get_issue_list(status=IssueStatus.closed) assert issue_list_closed assert len(issue_list_closed) >= 35 issue_list = self.ogr_project.get_issue_list() assert issue_list assert len(issue_list) >= 3 def test_issue_info(self): issue_info = self.ogr_project.get_issue_info(issue_id=4) assert issue_info assert issue_info.title.startswith("Better name") assert issue_info.status == IssueStatus.closed def test_issue_labels(self): labels = self.ogr_project.get_issue_labels(issue_id=4) assert not labels self.ogr_project.add_issue_labels(issue_id=4, labels=["test_lb1", "test_lb2"]) labels = self.ogr_project.get_issue_labels(issue_id=4) assert len(labels) == 2 assert labels[0].name == "test_lb1" assert labels[1].name == "test_lb2" class PullRequests(GithubTests): def test_pr_list(self): pr_list = self.ogr_fork.get_pr_list() assert isinstance(pr_list, list) pr_list_all = self.ogr_project.get_pr_list(status=PRStatus.all) assert pr_list_all assert len(pr_list_all) >= 75 pr_list_closed = self.ogr_project.get_pr_list(status=PRStatus.closed) assert pr_list_closed assert len(pr_list_closed) >= 70 closed_pr_numbers = [] for closed_pr in pr_list_closed: closed_pr_numbers.append(closed_pr.id) assert 93 in closed_pr_numbers pr_list_merged = self.ogr_project.get_pr_list(status=PRStatus.merged) assert pr_list_merged assert len(pr_list_merged) >= 1 closed_pr_numbers = [] for closed_pr in pr_list_merged: closed_pr_numbers.append(closed_pr.id) assert 93 not in closed_pr_numbers pr_list = self.ogr_project.get_pr_list() assert pr_list assert len(pr_list) >= 1 def test_pr_info(self): pr_info = self.ogr_project.get_pr_info(pr_id=1) assert pr_info assert pr_info.title == "WIP: API" assert pr_info.status == PRStatus.merged def test_all_pr_commits(self): commits = self.ogr_project.get_all_pr_commits(pr_id=1) assert len(commits) == 3 assert commits[0] == "431f4a7c5cce24c3035b17c5131a3918ab989bd0" assert commits[2] == "5d6cc05d30ef0a0d69bb42bdcaad187408a070b0" def test_update_pr_info(self): pr_info = self.ogr_project.get_pr_info(pr_id=1) orig_title = pr_info.title orig_description = pr_info.description self.ogr_project.update_pr_info( pr_id=1, title="changed", description="changed description" ) pr_info = self.ogr_project.get_pr_info(pr_id=1) assert pr_info.title == "changed" assert pr_info.description == "changed description" self.ogr_project.update_pr_info( pr_id=1, title=orig_title, description=orig_description ) pr_info = self.ogr_project.get_pr_info(pr_id=1) assert pr_info.title == orig_title assert pr_info.description == orig_description def test_pr_labels(self): labels = self.ogr_project.get_pr_labels(pr_id=1) assert not labels self.ogr_project.add_pr_labels(pr_id=1, labels=["test_lb1", "test_lb2"]) labels = self.ogr_project.get_pr_labels(pr_id=1) assert len(labels) == 2 assert labels[0].name == "test_lb1" assert labels[1].name == "test_lb2" class Releases(GithubTests): def test_get_release(self): release = self.hello_world_project.get_release(tag_name="0.4.1") assert release.title == "test" assert release.body == "testing release" def test_get_releases(self): releases = self.ogr_project.get_releases() assert releases assert len(releases) >= 9 def test_create_release(self): count_before = len(self.hello_world_project.get_releases()) release = self.hello_world_project.create_release( tag="0.5.0", name="test", message="testing release" ) count_after = len(self.hello_world_project.get_releases()) assert release.tag_name == "0.5.0" assert release.title == "test" assert release.body == "testing release" assert count_before + 1 == count_after def test_edit_release(self): release = self.hello_world_project.get_release(tag_name="0.1.0") origin_name = release.title origin_message = release.body release.edit_release( name=f"{origin_name}-changed", message=f"{origin_message}-changed" ) assert release.title == f"{origin_name}-changed" assert release.body == f"{origin_message}-changed" def test_latest_release(self): release = self.ogr_project.get_latest_release() assert release.tag_name == "0.5.0" assert release.title == "0.5.0" assert "New Features" in release.body class Forks(GithubTests): def test_fork(self): assert self.ogr_fork.is_fork is True fork_description = self.ogr_fork.get_description() assert fork_description @unittest.skip( "not working with yaml file because it check exception within setup" ) def test_nonexisting_fork(self): self.ogr_nonexisting_fork = self.service.get_project( repo="omfeprkfmwpefmwpefkmwpeofjwepof", is_fork=True ) with self.assertRaises(GithubException) as ex: self.ogr_nonexisting_fork.get_description() s = str(ex.value.args) assert "Not Found" in s assert "404" in s def test_get_fork(self): fork = self.ogr_project.get_fork() assert fork assert fork.get_description() def test_is_fork(self): assert not self.ogr_project.is_fork is_forked = self.ogr_project.is_forked() assert isinstance(is_forked, bool) # `is True` is here on purpose: we want to be sure that .is_forked() returns True object # because Tomas had his crazy ideas and wanted to return GitProject directly, # stop that madman assert is_forked is True fork = self.ogr_project.get_fork(create=False) assert fork assert fork.is_fork def test_create_fork(self): not_existing_fork = self.not_forked_project.get_fork(create=False) assert not not_existing_fork assert not self.not_forked_project.is_forked() old_forks = self.not_forked_project.service.user.get_forks() self.not_forked_project.fork_create() assert self.not_forked_project.get_fork().get_description() assert self.not_forked_project.is_forked() new_forks = self.not_forked_project.service.user.get_forks() assert len(old_forks) == len(new_forks) - 1
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day05/05_hydrothermal_venture.py
KDawid/AdventOfCode2021
0
1608832
import re class LineSegment: X1_GROUP = 'x1' X2_GROUP = 'x2' Y1_GROUP = 'y1' Y2_GROUP = 'y2' INPUT_PATTERN = rf'(?P<{X1_GROUP}>\d+),(?P<{Y1_GROUP}>\d+) -> (?P<{X2_GROUP}>\d+),(?P<{Y2_GROUP}>\d+)' MATCHER = re.compile(INPUT_PATTERN) def __init__(self, str): m = self.MATCHER.match(str) if m: self.x1 = int(m.group(self.X1_GROUP)) self.x2 = int(m.group(self.X2_GROUP)) self.y1 = int(m.group(self.Y1_GROUP)) self.y2 = int(m.group(self.Y2_GROUP)) else: raise IOError(f'Could not parse input: {str}') def get_points(self): raise NotImplementedError('This method shall be implemented') @staticmethod def _generate_straight_line_points(point1, point2): p1, p2 = (point1, point2) if point1 < point2 else (point2, point1) return [num for num in range(p1, p2+1)] def __str__(self): return f'({self.x1}, {self.y1}) -> ({self.x2}, {self.y2})' class StraightLineSegment(LineSegment): def __init__(self, str): super().__init__(str) def get_points(self): if self.x1 == self.x2: return [(self.x1, y) for y in self._generate_straight_line_points(self.y1, self.y2)] if self.y1 == self.y2: return [(x, self.y1) for x in self._generate_straight_line_points(self.x1, self.x2)] print('Points only can be generated for straight lines') return [] class DiagonalLineSegment(LineSegment): def __init__(self, str): super().__init__(str) def get_points(self): if self.x1 == self.x2: return [(self.x1, y) for y in self._generate_straight_line_points(self.y1, self.y2)] if self.y1 == self.y2: return [(x, self.y1) for x in self._generate_straight_line_points(self.x1, self.x2)] return self.__generate_diagonal_points() def __generate_diagonal_points(self): if abs(self.x2 - self.x1) != abs(self.y2 - self.y1): print(f'Error! This does ot seem diagonal: {self}') x, y = self.x1, self.y1 x_direction = 1 if self.x1 < self.x2 else -1 y_direction = 1 if self.y1 < self.y2 else -1 res = [(x, y)] for _ in range(abs(self.x1-self.x2)): x += x_direction y += y_direction res.append((x, y)) return res class OceanMap: def __init__(self): self.points = dict() def add(self, coordinates): if coordinates not in self.points: self.points[coordinates] = 1 else: self.points[coordinates] += 1 def get_dangerous_num(self, level=2): return sum(value >= level for value in self.points.values()) def __str__(self): x_max = max([p[0] for p in self.points]) y_max = max([p[1] for p in self.points]) res = '' for y in range(y_max+1): line = '' for x in range(x_max+1): line += str(self.points[(x, y)]) if (x, y) in self.points else '.' res += line + '\n' return res def first_task(file_path): data = read_straight_line_data(file_path) map = OceanMap() for d in data: for point in d.get_points(): map.add(point) # print(map) return map.get_dangerous_num(level=2) def read_straight_line_data(file_path): with open(file_path) as f: return [StraightLineSegment(line.strip()) for line in f.readlines()] def second_task(file_path): data = read_data(file_path) map = OceanMap() for d in data: for point in d.get_points(): map.add(point) # print(map) return map.get_dangerous_num(level=2) def read_data(file_path): with open(file_path) as f: return [DiagonalLineSegment(line.strip()) for line in f.readlines()] if __name__ == '__main__': FILE_PATH = 'input.txt' res_1 = first_task(FILE_PATH) print(res_1) res_2 = second_task(FILE_PATH) print(res_2)
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data_io/export_camera_poses.py
tumcms/aerial2pdsm
0
20670
<gh_stars>0 import plyfile from config import SparseModel, project_path from colmap_scripts.read_model import Image import numpy as np project = SparseModel("/home/felix/pointclouds/_working/2019_11_07_Muenchen_26_10_2018", model_path="/home/felix/pointclouds/_working/2019_11_07_Muenchen_26_10_2018/sparse/1") images = project.images cameras = project.cameras poses = [] dt = np.dtype([('x', np.float64), ('y', np.float64), ('z', np.float64), ('img', np.int32)]) for nr, img in images.items(): R = img.qvec2rotmat() T = img.tvec cp = np.dot(-R.T, T) pose = (cp[0], cp[1], cp[2], nr) poses.append(pose) vertex = np.array(poses, dtype=dt) v = plyfile.PlyElement.describe(vertex, "vertices") plyfile.PlyData([v], text=True).write(project.model_path + "/camera_locations.ply")
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easytoken/blob.py
sayanmondal2098/tokenizer
3
40386
import sys import json import nltk import nltk from nltk.corpus import stopwords from nltk.tokenize import word_tokenize, sent_tokenize class Partsofspeech(): def pos(txt): tokens = nltk.word_tokenize(txt) return (nltk.pos_tag(tokens)) # stop_words = set(stopwords.words('english'))
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predix/admin/eventhub.py
BLaurent/predixpy
28
52388
<gh_stars>10-100 import os import predix.config import predix.security.uaa import predix.admin.service import predix.data.eventhub class EventHub(object): """ Event Hub is a publisher/subscriber framework for getting information in, out and around the predix cloud """ def __init__(self, plan_name=None, name=None, uaa=None, *args, **kwargs): self.service_name = 'predix-event-hub' self.plan_name = plan_name or 'Tiered' self.use_class = predix.data.eventhub.Eventhub self.service = predix.admin.service.PredixService(self.service_name, self.plan_name, name=name, uaa=uaa) def exists(self): """ Returns whether or not this service already exists. """ return self.service.exists() def create(self): """ Create an instance of the Time Series Service with the typical starting settings. """ self.service.create() os.environ[predix.config.get_env_key(self.use_class, 'host')] = self.get_eventhub_host() os.environ[predix.config.get_env_key(self.use_class, 'port')] = self.get_eventhub_grpc_port() os.environ[predix.config.get_env_key(self.use_class, 'wss_publish_uri')] = self.get_publish_wss_uri() os.environ[predix.config.get_env_key(self.use_class, 'zone_id')] = self.get_zone_id() def grant_client(self, client_id, publish=False, subscribe=False, publish_protocol=None, publish_topics=None, subscribe_topics=None, scope_prefix='predix-event-hub', **kwargs): """ Grant the given client id all the scopes and authorities needed to work with the eventhub service. """ scopes = ['openid'] authorities = ['uaa.resource'] zone_id = self.get_zone_id() # always must be part of base user scope scopes.append('%s.zones.%s.user' % (scope_prefix, zone_id)) authorities.append('%s.zones.%s.user' % (scope_prefix, zone_id)) if publish_topics is not None or subscribe_topics is not None: raise Exception("multiple topics are not currently available in preidx-py") if publish_topics is None: publish_topics = ['topic'] if subscribe_topics is None: subscribe_topics = ['topic'] if publish: # we are granting just the default topic if publish_protocol is None: scopes.append('%s.zones.%s.grpc.publish' % (scope_prefix, zone_id)) authorities.append('%s.zones.%s.grpc.publish' % (scope_prefix, zone_id)) scopes.append('%s.zones.%s.wss.publish' % (scope_prefix, zone_id)) authorities.append('%s.zones.%s.wss.publish' % (scope_prefix, zone_id)) else: scopes.append('%s.zones.%s.%s.publish' % (scope_prefix, zone_id, publish_protocol)) authorities.append('%s.zones.%s.%s.publish' % (scope_prefix, zone_id, publish_protocol)) # we are requesting multiple topics for topic in publish_topics: if publish_protocol is None: scopes.append('%s.zones.%s.%s.grpc.publish' % (scope_prefix, zone_id, topic)) scopes.append('%s.zones.%s.%s.wss.publish' % (scope_prefix, zone_id, topic)) scopes.append('%s.zones.%s.%s.user' % (scope_prefix, zone_id, topic)) authorities.append('%s.zones.%s.%s.grpc.publish' % (scope_prefix, zone_id, topic)) authorities.append('%s.zones.%s.%s.wss.publish' % (scope_prefix, zone_id, topic)) authorities.append('%s.zones.%s.%s.user' % (scope_prefix, zone_id, topic)) else: scopes.append('%s.zones.%s.%s.%s.publish' % (scope_prefix, zone_id, topic, publish_protocol)) authorities.append('%s.zones.%s.%s.%s.publish' % (scope_prefix, zone_id, topic, publish_protocol)) if subscribe: # we are granting just the default topic scopes.append('%s.zones.%s.grpc.subscribe' % (scope_prefix, zone_id)) authorities.append('%s.zones.%s.grpc.subscribe' % (scope_prefix, zone_id)) # we are requesting multiple topics for topic in subscribe_topics: scopes.append('%s.zones.%s.%s.grpc.subscribe' % (scope_prefix, zone_id, topic)) authorities.append('%s.zones.%s.%s.grpc.subscribe' % (scope_prefix, zone_id, topic)) self.service.uaa.uaac.update_client_grants(client_id, scope=scopes, authorities=authorities) return self.service.uaa.uaac.get_client(client_id) def get_eventhub_host(self): """ returns the publish grpc endpoint for ingestion. """ for protocol in self.service.settings.data['publish']['protocol_details']: if protocol['protocol'] == 'grpc': return protocol['uri'][0:protocol['uri'].index(':')] def get_eventhub_grpc_port(self): for protocol in self.service.settings.data['publish']['protocol_details']: if protocol['protocol'] == 'grpc': return str(protocol['uri'][(protocol['uri'].index(':') + 1):]) def get_publish_wss_uri(self): """ returns the publish grpc endpoint for ingestion. """ for protocol in self.service.settings.data['publish']['protocol_details']: if protocol['protocol'] == 'wss': return protocol['uri'] def get_zone_id(self): return self.service.settings.data['publish']['zone-http-header-value'] def get_subscribe_uri(self): return self.service.settings.data['subscribe']['protocol_details'][0]['uri'] def make_topic(self, broker_uri, topic_name): raise Exception('make topic has not been implemented yet') def add_to_manifest(self, manifest): """ Add useful details to the manifest about this service so that it can be used in an application. :param manifest: An predix.admin.app.Manifest object instance that manages reading/writing manifest config for a cloud foundry app. """ # Add this service to list of services manifest.add_service(self.service.name) # Add environment variables manifest.add_env_var(predix.config.get_env_key(self.use_class, 'host'), self.get_eventhub_host()) manifest.add_env_var(predix.config.get_env_key(self.use_class, 'port'), self.get_eventhub_grpc_port()) manifest.add_env_var(predix.config.get_env_key(self.use_class, 'wss_publish_uri'), self.get_publish_wss_uri()) manifest.add_env_var(predix.config.get_env_key(self.use_class, 'zone_id'), self.get_zone_id()) manifest.write_manifest()
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580, 13, 2 ]
tnp/__init__.py
hydiant/tnp
295
1609886
version = '0.1.1'
[ 1, 1873, 353, 525, 29900, 29889, 29896, 29889, 29896, 29915, 13, 2 ]
aos/external_systems.py
azdolinski/apstra-api-python
1
96144
<filename>aos/external_systems.py # Copyright 2020-present, Apstra, Inc. All rights reserved. # # This source code is licensed under End User License Agreement found in the # LICENSE file at http://www.apstra.com/eula import logging from dataclasses import dataclass from .aos import AosSubsystem from typing import Optional, List, Generator logger = logging.getLogger(__name__) class AosExternalSystems(AosSubsystem): """ Management of AOS Resource elements: - Providers - External Routers - Virtual Infra Managers """ def __init__(self, rest): super().__init__(rest) self.external_router = AosExternalRouter(rest) # Resources @dataclass class AosResource: display_name: str id: str @dataclass class ExternalRouter(AosResource): asn: int address: str @classmethod def from_json(cls, d): if d is None: return None return ExternalRouter( id=d["id"], display_name=d.get("display_name", ""), asn=d.get("asn"), address=d.get("address"), ) class AosExternalRouter(AosSubsystem): def create(self, name: str, asn: int, address: str) -> ExternalRouter: ext_rtr = { "display_name": name, "id": name, "asn": asn, "address": address, } created = self.rest.json_resp_post( "/api/resources/external-routers", data=ext_rtr ) return self.get(created["id"]) def delete(self, ext_rtr_id: str) -> None: self.rest.delete(f"/api/resources/external-routers/{ext_rtr_id}") def get(self, rtr_id: str) -> Optional[ExternalRouter]: return ExternalRouter.from_json( self.rest.json_resp_get(f"/api/resources/external-routers/{rtr_id}") ) def iter_all(self) -> Generator[ExternalRouter, None, None]: rtrs = self.rest.json_resp_get("/api/resources/external-routers") if rtrs: for r in rtrs["items"]: yield ExternalRouter.from_json(r) def find_by_name(self, rtr_name: str) -> List[ExternalRouter]: return [r for r in self.iter_all() if r.display_name == rtr_name]
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art/attacks/fast_gradient.py
yalechang/adversarial-robustness-toolbox
1
156793
<reponame>yalechang/adversarial-robustness-toolbox # MIT License # # Copyright (C) IBM Corporation 2018 # # Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated # documentation files (the "Software"), to deal in the Software without restriction, including without limitation the # rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit # persons to whom the Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all copies or substantial portions of the # Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE # WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from __future__ import absolute_import, division, print_function, unicode_literals from keras import backend as k import numpy as np import tensorflow as tf from art.attacks.attack import Attack class FastGradientMethod(Attack): """ This attack was originally implemented by Goodfellow et al. (2015) with the infinity norm (and is known as the "Fast Gradient Sign Method"). This implementation extends the attack to other norms, and is therefore called the Fast Gradient Method. Paper link: https://arxiv.org/abs/1412.6572 """ attack_params = ['ord', 'eps', 'y', 'y_val', 'targeted', 'clip_min', 'clip_max'] def __init__(self, classifier, sess=None, ord=np.inf, eps=.3, y=None, targeted=False, clip_min=0, clip_max=1): """ Create a FastGradientMethod instance. :param classifier: A trained model. :type classifier: :class:`Classifier` :param sess: The session to run graphs in. :type sess: `tf.Session` :param ord: Order of the norm. Possible values: np.inf, 1 or 2. :type ord: `int` :param eps: Attack step size (input variation) :type eps: `float` :param y: A placeholder for the model labels. Only provide this parameter if you'd like to use true labels when crafting adversarial samples. Otherwise, model predictions are used as labels to avoid the "label leaking" effect (explained in this paper: https://arxiv.org/abs/1611.01236). Default is `None`. Labels should be one-hot-encoded. :type y: `np.ndarray` :param targeted: Should the attack target one specific class :type targeted: `bool` :param clip_min: Minimum input component value. :type clip_min: `float` :param clip_max: Maximum input component value. :type clip_max: `float` """ super(FastGradientMethod, self).__init__(classifier, sess) kwargs = {'ord': ord, 'eps': eps, 'targeted': targeted, 'clip_min': clip_min, 'clip_max': clip_max, 'y': y} self.set_params(**kwargs) def generate_graph(self, x_op, eps_op, **kwargs): """ Generate symbolic graph for adversarial examples and return. :param x_op: The model's symbolic inputs. :type x_op: `tf.Placeholder` :param eps_op: The placeholder for input variation (noise amplitude) :type eps_op: `tf.Placeholder` :param ord: Order of the norm (mimics Numpy). Possible values: np.inf, 1 or 2. :type ord: `int` :param y: (optional) A placeholder for the model labels. Only provide this parameter if you'd like to use true labels when crafting adversarial samples. Otherwise, model predictions are used as labels to avoid the "label leaking" effect (explained in this paper: https://arxiv.org/abs/1611.01236). Default is `None`. Labels should be one-hot-encoded. :type y: `np.ndarray` :param clip_min: Minimum input component value. :type clip_min: `float` :param clip_max: Maximum input component value. :type clip_max: `float` :return: The computation graph for producing adversarial examples. :rtype: `tf.Tensor` """ self.set_params(**kwargs) preds = self.classifier._get_predictions(x_op, log=False) if not hasattr(self, 'y') or self.y is None: # Use model predictions as correct outputs preds_max = tf.reduce_max(preds, 1, keep_dims=True) y = tf.to_float(tf.equal(preds, preds_max)) y = tf.stop_gradient(y) else: y = self.y y = y / tf.reduce_sum(y, 1, keep_dims=True) loss = tf.nn.softmax_cross_entropy_with_logits(logits=preds, labels=y) if self.targeted: loss = -loss grad, = tf.gradients(loss, x_op) # Apply norm bound if self.ord == np.inf: grad = tf.sign(grad) elif self.ord == 1: ind = list(range(1, len(x_op.get_shape()))) grad = grad / tf.reduce_sum(tf.abs(grad), reduction_indices=ind, keep_dims=True) elif self.ord == 2: ind = list(range(1, len(x_op.get_shape()))) grad = grad / tf.sqrt(tf.reduce_sum(tf.square(grad), reduction_indices=ind, keep_dims=True)) # Apply perturbation and clip x_adv_op = x_op + eps_op * grad if self.clip_min is not None and self.clip_max is not None: x_adv_op = tf.clip_by_value(x_adv_op, self.clip_min, self.clip_max) return x_adv_op def minimal_perturbations(self, x, x_val, eps_step=0.1, eps_max=1., **kwargs): """Iteratively compute the minimal perturbation necessary to make the class prediction change. Stop when the first adversarial example was found. :param x: A placeholder for the input. :type x: `tf.Placeholder` :param x_val: An array with the original inputs. :type x_val: `np.ndarray` :param eps_step: The increase in the perturbation for each iteration :type eps_step: `float` :param eps_max: The maximum accepted perturbation :type eps_max: `float` :param kwargs: Other parameters to send to `generate_graph` :type kwargs: `dict` :return: An array holding the adversarial examples. :rtype: `np.ndarray` """ k.set_learning_phase(0) y = np.argmax(self.model.predict(x_val), 1) adv_x = x_val.copy() curr_indexes = np.arange(len(adv_x)) eps = tf.placeholder(tf.float32, None) adv_x_op = self.generate_graph(x, eps, **kwargs) adv_y = tf.argmax(self.model(adv_x_op), 1) eps_val = eps_step while len(curr_indexes) != 0 and eps_val <= eps_max: # Adversarial crafting new_adv_x, new_y = self.sess.run([adv_x_op, adv_y], {x: x_val[curr_indexes], eps: eps_val}) # Update adv_x[curr_indexes] = new_adv_x curr_indexes = np.where(y[curr_indexes] == new_y)[0] eps_val += eps_step return adv_x def generate(self, x_val, **kwargs): """Generate adversarial samples and return them in an array. :param x_val: An array with the original inputs. :type x_val: `np.ndarray` :param eps: Attack step size (input variation) :type eps: `float` :param ord: Order of the norm (mimics Numpy). Possible values: np.inf, 1 or 2. :type ord: `int` :param y: A placeholder for the model labels. Only provide this parameter if you'd like to use true labels when crafting adversarial samples. Otherwise, model predictions are used as labels to avoid the "label leaking" effect (explained in this paper: https://arxiv.org/abs/1611.01236). Default is None. Labels should be one-hot-encoded. :type y: `np.ndarray` :param clip_min: Minimum input component value. :type clip_min: `float` :param clip_max: Maximum input component value. :type clip_max: `float` :return: An array holding the adversarial examples. :rtype: `np.ndarray` """ input_shape = [None] + list(x_val.shape[1:]) self._x = tf.placeholder(tf.float32, shape=input_shape) k.set_learning_phase(0) # Return adversarial examples computed with minimal perturbation if option is active if "minimal" in kwargs and kwargs["minimal"]: return self.minimal_perturbations(self._x, x_val, **kwargs) # Generate computation graph eps = tf.placeholder(tf.float32, None) self._x_adv = self.generate_graph(self._x, eps, **kwargs) # Run symbolic graph without or with true labels if 'y_val' not in kwargs or kwargs['y_val'] is None: feed_dict = {self._x: x_val, eps: self.eps} else: # Verify label placeholder was given in params if using true labels if self.y is None: raise Exception("True labels given but label placeholder not given.") feed_dict = {self._x: x_val, self.y: kwargs['y_val'], eps: self.eps} return self.sess.run(self._x_adv, feed_dict=feed_dict) def set_params(self, **kwargs): """Take in a dictionary of parameters and applies attack-specific checks before saving them as attributes. :param ord: Order of the norm. Possible values: np.inf, 1 or 2. :type ord: `int` :param eps: Attack step size (input variation) :type eps: `float` :param y: (optional) A placeholder for the model labels. Only provide this parameter if you'd like to use true labels when crafting adversarial samples. Otherwise, model predictions are used as labels to avoid the "label leaking" effect (explained in this paper: https://arxiv.org/abs/1611.01236). Default is None. Labels should be one-hot-encoded. :type y: `np.ndarray` :param targeted: Should the attack target one specific class :type targeted: `bool` :param clip_min: Minimum input component value. :type clip_min: `float` :param clip_max: Maximum input component value. :type clip_max: `float` """ # Save attack-specific parameters super(FastGradientMethod, self).set_params(**kwargs) # Check if order of the norm is acceptable given current implementation if self.ord not in [np.inf, int(1), int(2)]: raise ValueError("Norm order must be either np.inf, 1, or 2.") if self.clip_min is not None and self.clip_max is not None: if self.eps <= self.clip_min or self.eps > self.clip_max: raise ValueError('The amount of perturbation has to be in the data range.') return True
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scripts/m2.py
byu-iot-security/cheeziot_webserver
2
67220
import pymongo import os import datetime from base64 import decodestring from bson.objectid import ObjectId from pymongo import MongoClient config_file = open("config", 'r') collection = '' database = '' #Parse the configuration (config) file for line in config_file: field,val = line.split("=") if(field == "COLLECTION"): collection = val.rstrip() elif(field == "DATABASE"): database = val.rstrip() print collection print database client = MongoClient('localhost', 27017) # TODO: Only retrieve records with image data # Assume that all records have an image, for now # Get a hardcoded entry # entry = client[database][collection].find_one({"_id": ObjectId("58a61687870a765994850d5a")}) # Sort from newest to oldest based on the kaa timestamp, and return the newest record # For sorting nested fields, see http://stackoverflow.com/questions/12031507/mongodb-sorting-by-nested-object-value entry = client[database][collection].find().sort("header.timestamp", pymongo.DESCENDING).limit(1)[0] # Get the most recent image record according to _id # The _id field will contain an implicit timestamp in it # See http://stackoverflow.com/questions/4421207/mongodb-how-to-get-the-last-n-records # entry = client[database][collection].find().sort("_id", pymongo.DESCENDING).limit(1)[0] # NOTE: find_one() and find().limit(1) aren't perfectly interchangeable # See http://dba.stackexchange.com/questions/7573/difference-between-mongodbs-find-and-findone-calls # # Other tests # cursor = client[database][collection].find().sort("_id", pymongo.DESCENDING) # cursor = client[database][collection].find() # print cursor[0].get("_id") print "-----------------------" print entry.get("_id") person_name = entry.get("event").get("person_name") if person_name: name = person_name.rstrip() else: name = "?" if os.path.isfile("public/faces.html"): os.remove("public/faces.html") #construct the faces.html page to be served to a client. last_seen = open("public/faces.html", "w") last_seen.write("<!doctype html>\n") last_seen.write(" <head>\n") last_seen.write(" <title>Faces of the Clyde</title>\n") last_seen.write(" </head>\n") last_seen.write(" <body>\n") last_seen.write(" <img src=\"images/faces.png\">\n") last_seen.write(" <div>\n") last_seen.write(" <img src=\"images/test_out.bmp\" width=\"200\" height=\"200\">\n") name_string = " <font size = \"6\" face=\"Courier New\">" + name + "</b>\n" last_seen.write(" </div>\n") last_seen.write(" <div>\n") last_seen.write(name_string) last_seen.write(" </div>\n") last_seen.write(" </body>\n") last_seen.write("</html>\n") last_seen.close() raw_image_data = entry.get("event").get("image_data") #if test_out.bmp already exists, delete it if os.path.isfile("public/images/test_out.bmp"): os.remove("public/images/test_out.bmp") f = file("public/images/test_out.bmp", "wb") for i in raw_image_data: f.write(decodestring(i))
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examples/python/EventBuilder.py
jstrube/lcio
0
132809
<filename>examples/python/EventBuilder.py ''' Created on May 17, 2013 Example for creating LCIO events and filling them with MCParticles and SimTrackerHits. @author: <a href="mailto:<EMAIL>"><NAME></a> ''' from pyLCIO import EVENT, IMPL, IOIMPL, UTIL from ROOT import TVector3, TLorentzVector, TRandom3, TMath from time import time import sys, math def generateEvents( outputFileName, nEvents ): random = TRandom3( 12345 ) # define a particle source sourcePosition = TVector3( 0., 0., 0. ) sourceSpreadXY = 10. pdgid = 13 charge = -1. mass = 0.105658 momentum = TVector3( 0.3, 0.1, 10. ) runNumber = 321 # define a detector with positions for the tracker planes detectorName = 'ToyTracker' trackerPlanePositions = [] hitResolution = 0.01 planeNormal = TVector3( 0., 0., 1. ) for planeZ in [ 100., 250., 480., 510., 640. ]: trackerPlanePositions.append( TVector3( 0., 0., planeZ ) ) # create a writer and open the output file writer = IOIMPL.LCFactory.getInstance().createLCWriter() writer.open( outputFileName, EVENT.LCIO.WRITE_NEW ) # create a run header and add it to the file (optional) run = IMPL.LCRunHeaderImpl() run.setRunNumber( runNumber ) run.setDetectorName( detectorName ) run.setDescription( 'This is a test run' ) writer.writeRunHeader( run ) for iEvent in xrange( nEvents ): # create an event and set its parameters event = IMPL.LCEventImpl() event.setEventNumber( iEvent ) event.setDetectorName( detectorName ) event.setRunNumber( runNumber ) event.setTimeStamp( int( time() * 1000000000. ) ) # create the mc particle collection mcParticles = IMPL.LCCollectionVec( EVENT.LCIO.MCPARTICLE ) # calculate the origin of the particle x = random.Gaus( sourcePosition.x(), sourceSpreadXY ) y = random.Gaus( sourcePosition.y(), sourceSpreadXY ) z = sourcePosition.z() origin = TVector3( x, y, z ) # create a particle mcParticle = IMPL.MCParticleImpl() mcParticle.setPDG( pdgid ) mcParticle.setMass( mass ) mcParticle.setMomentumVec( momentum ) mcParticle.setGeneratorStatus( 1 ) mcParticle.setVertexVec( origin ) mcParticle.setTime( 0. ) mcParticles.addElement( mcParticle ) # create a tracker hit collection trackerHits = IMPL.LCCollectionVec( EVENT.LCIO.SIMTRACKERHIT ) trackerHits.setFlag( UTIL.set_bit( trackerHits.getFlag(), EVENT.LCIO.THBIT_MOMENTUM ) ) # create an IDEncoder to store hit IDs # defines the tags and the number of bits for the different bit fields encodingString = 'system:3,layer:6' idEncoder = UTIL.CellIDEncoder( IMPL.SimTrackerHitImpl )( encodingString, trackerHits ) # add a hit for each layer for planePosition in trackerPlanePositions: # calculate the intersection with the plane distance = ( planePosition - origin ).Dot( planeNormal ) / momentum.Dot( planeNormal ) intersect = TVector3( momentum ) intersect.SetMag( distance ) # smear the hit position with the resolution hitX = random.Gaus( intersect.x(), hitResolution ) hitY = random.Gaus( intersect.x(), hitResolution ) hitPosition = TVector3( hitX, hitY, intersect.z() ) # build the tracker hit trackerHit = IMPL.SimTrackerHitImpl() trackerHit.setPositionVec( hitPosition ) trackerHit.setMomentumVec( momentum ) trackerHit.setMCParticle( mcParticle ) trackerHit.setTime( distance / TMath.C() ) trackerHit.setEDep( 0.1 ) # set the cell ID idEncoder.reset() idEncoder['layer'] = trackerPlanePositions.index( planePosition ) idEncoder['system'] = 1 idEncoder.setCellID( trackerHit ) trackerHits.addElement( trackerHit ) event.addCollection( mcParticles, EVENT.LCIO.MCPARTICLE ) event.addCollection( trackerHits, 'SimTrackerHits' ) writer.writeEvent( event ) writer.flush() writer.close() def usage(): print 'Generates an MCParticle with associated SimTrackerHits for each event' print 'Usage:\n python %s <outputFile> <nEvents>' % ( sys.argv[0] ) if __name__ == '__main__': if len( sys.argv ) < 3: usage() sys.exit( 1 ) generateEvents( sys.argv[1], int( sys.argv[2] ) )
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759/Employee Free Time.py
cccccccccccccc/Myleetcode
0
20318
<filename>759/Employee Free Time.py<gh_stars>0 from typing import List import heapq # Definition for an Interval. class Interval: def __init__(self, start: int = None, end: int = None): self.start = start self.end = end class Solution: def employeeFreeTime(self, schedule: '[[Interval]]') -> '[Interval]': allinterval = [] heapq.heapify(allinterval) ans = [] for i,e in enumerate(schedule): heapq.heappush(allinterval,(e[0].start,e[0].end,i,0)) interval = Interval() flag = False freetime = [] while len(allinterval)>0: cur = heapq.heappop(allinterval) id = cur[2] idx = cur[3] if flag == False: interval = Interval(cur[0],cur[1]) flag = True else: if cur[0]>interval.end: freetime.append(Interval(interval.end,cur[0])) interval.start = cur[0] interval.end = cur[1] else: interval.end = max(interval.end,cur[1]) if len(schedule[id])-1>idx: heapq.heappush(allinterval,(schedule[id][idx+1].start,schedule[id][idx+1].end,id,idx+1)) return freetime i1 = Interval(1,2) i2 = Interval(6,7) i3 = Interval(2,4) i4 = Interval(2,5) i5 = Interval(9,12) A = Solution() print(A.employeeFreeTime([[i1,i2],[i3],[i4,i5]]))
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tests/data/Kind/Operations.py
aalireza/arep
1
162098
x = 1 + 2 * 3 - 3 ** 5 / 2 y = 3 ** 5 - 2 z = x / y zz = x // y z -= z zz += zz xx = -x xx %= 10 if type(x) is int: print(x and y)
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voxel_globe/websockets/views.py
ngageoint/voxel-globe
28
150204
from django.shortcuts import render ### Rest API setup import rest_framework.routers import rest_framework.viewsets import rest_framework.filters from voxel_globe.websockets.serializers import LogMessageSerializer from voxel_globe.websockets.models import LogMessage router = rest_framework.routers.DefaultRouter() class LogMessageViewSet(rest_framework.viewsets.ModelViewSet): queryset = LogMessage.objects.all() serializer_class = LogMessageSerializer filter_backends = (rest_framework.filters.DjangoFilterBackend,) filter_fields = ['message_text', 'message_type', 'task_id'] def get_queryset(self): return super(LogMessageViewSet, self).get_queryset().filter(owner=self.request.user)
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twistedlilypad/packets/message_event_packet.py
flaminscotsman/TwistedLilypad
1
60939
<reponame>flaminscotsman/TwistedLilypad from codecs import lookup from struct import unpack_from, pack from .abstract_packet import AbstractPacket, AbstractPacketCodec from twistedlilypad.utilities import varint_prefixed_string_encoder, varint_prefixed_string_parser utf8_decoder = lookup('UTF_8').decode utf8_encoder = lookup('UTF_8').encode class PacketMessageEvent(AbstractPacket): opcode = 0x03 _message = None def __init__(self, sender, channel, payload): self.sender = sender self.channel = channel self.payload = payload def __eq__(self, other): if not isinstance(other, PacketMessageEvent): return NotImplemented return self.sender == other.sender and \ self.channel == other.channel and \ self.payload == other.payload @property def payloadSize(self): return len(self.payload) @property def message(self): if self._message is None: self._message = utf8_decoder(self.payload)[0] return self._message @message.setter def message(self, message): self._message = message self.payload = utf8_encoder(message)[0] class PacketMessageEventCodec(AbstractPacketCodec): @staticmethod def encode(packet): return varint_prefixed_string_encoder(packet.sender) + \ varint_prefixed_string_encoder(packet.channel) + \ pack('>H', packet.payloadSize) + \ packet.payload @staticmethod def decode(payload): sender, payload = varint_prefixed_string_parser(payload) channel, payload = varint_prefixed_string_parser(payload) payloadSize = unpack_from('>H', payload)[0] payload = payload[2:2 + payloadSize] return PacketMessageEvent(sender, channel, payload)
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spiral.py
Shubhra1906/pyturtle
0
133165
<gh_stars>0 import turtle import colorsys t=turtle.Turtle() s=turtle.Screen() s.bgcolor('black') t.speed(0) n=36 h=0 for i in range(360): c=colorsys.hsv_to_rgb(h, 1, 0.8) h+=1/n t.color(c) t.circle(180) t.left(10)
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jj/middlewares/_base_middleware.py
TeoDV/jj
0
92336
from typing import Type, Union from ..apps import AbstractApp from ..handlers import HandlerFunction from ._abstract_middleware import AbstractMiddleware from ._middleware_type import MiddlewareType __all__ = ("BaseMiddleware", "AppOrHandler",) AppOrHandler = Union[Type[AbstractApp], HandlerFunction] class BaseMiddleware(AbstractMiddleware): def on_app(self, app: Type[AbstractApp]) -> None: pass def on_handler(self, handler: HandlerFunction) -> None: pass def _call_hooks(self, app_or_handler: AppOrHandler) -> None: if isinstance(app_or_handler, type) and issubclass(app_or_handler, AbstractApp): return self.on_app(app_or_handler) return self.on_handler(app_or_handler) def _register_middleware(self, app_or_handler: AppOrHandler, middleware: MiddlewareType) -> None: old_middlewares = self._resolver.get_attribute("middlewares", app_or_handler, []) new_middlewares = old_middlewares + [middleware] self._resolver.register_attribute("middlewares", new_middlewares, app_or_handler) def __call__(self, app_or_handler: AppOrHandler) -> AppOrHandler: self._call_hooks(app_or_handler) self._register_middleware(app_or_handler, self._do) return app_or_handler
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rrs/tools/rrs_maintainer_history.py
WindRiver-OpenSourceLabs/layerindex-web
0
13540
#!/usr/bin/env python3 # Standalone script which rebuilds the history of maintainership # # Copyright (C) 2015 Intel Corporation # Author: <NAME> <<EMAIL>> # # Licensed under the MIT license, see COPYING.MIT for details import sys import os.path import optparse import logging sys.path.insert(0, os.path.realpath(os.path.join(os.path.dirname(__file__)))) from common import common_setup, get_logger, DryRunRollbackException common_setup() from layerindex import utils, recipeparse utils.setup_django() from django.db import transaction import settings from layerindex.models import Recipe, LayerBranch, LayerItem from rrs.models import MaintenancePlan, Maintainer, RecipeMaintainerHistory, RecipeMaintainer, RecipeMaintenanceLink from django.core.exceptions import ObjectDoesNotExist # FIXME we shouldn't be hardcoded to expect RECIPE_MAINTAINER to be set in this file, # as it may be in the recipe in future MAINTAINERS_INCLUDE_PATH = 'conf/distro/include/maintainers.inc' """ Try to get recipe maintainer from line, if not found return None """ def get_recipe_maintainer(line, logger): import re regex = re.compile('^RECIPE_MAINTAINER_pn-(?P<pn>.*)\s=\s"(?P<name>.+) <(?P<email>.*)>"$') match = regex.search(line) if match: return (match.group('pn'), match.group('name'), match.group('email')) else: logger.debug("line (%s) don\'t match" % (line)) return None """ Get commit information from text. Returns author_name, author_email, date and title. """ def get_commit_info(info, logger): import re from datetime import datetime from email.utils import parsedate_tz, mktime_tz author_regex = re.compile("^Author: (?P<name>.*) <(?P<email>.*)>$") date_regex = re.compile("^Date: (?P<date>.*)$") title_regex = re.compile("^ (?P<title>.*)$") lines = info.split('\n') author_name = author_regex.search(lines[1]).group('name') author_email = author_regex.search(lines[1]).group('email') date_str = date_regex.search(lines[2]).group('date') date = datetime.utcfromtimestamp(mktime_tz(parsedate_tz(date_str))) title = title_regex.search(lines[4]).group('title') return (author_name, author_email, date, title) def maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir): maintainers_full_path = os.path.join(layerdir, MAINTAINERS_INCLUDE_PATH) if not os.path.exists(maintainers_full_path): logger.warning('Maintainer style is maintainers.inc for plan %s but no maintainers.inc exists in for %s' % (maintplan, layerbranch)) return logger.debug('Checking maintainers.inc history for %s' % layerbranch) commits = utils.runcmd("git log --format='%%H' --reverse --date=rfc origin/master %s" % os.path.join(layerbranch.vcs_subdir, MAINTAINERS_INCLUDE_PATH), repodir, logger=logger) no_maintainer, _ = Maintainer.objects.get_or_create(name='No maintainer') try: with transaction.atomic(): for commit in commits.strip().split("\n"): if RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch, sha1=commit): continue logger.debug("Analysing commit %s ..." % (commit)) (author_name, author_email, date, title) = \ get_commit_info(utils.runcmd("git show " + commit, repodir, logger=logger), logger) author = Maintainer.create_or_update(author_name, author_email) rms = RecipeMaintainerHistory(title=title, date=date, author=author, sha1=commit, layerbranch=layerbranch) rms.save() utils.runcmd("git checkout %s -f" % commit, repodir, logger=logger) lines = [line.strip() for line in open(maintainers_full_path)] for line in lines: res = get_recipe_maintainer(line, logger) if res: (pn, name, email) = res qry = Recipe.objects.filter(pn = pn, layerbranch = layerbranch) if qry: m = Maintainer.create_or_update(name, email) rm = RecipeMaintainer() rm.recipe = qry[0] rm.maintainer = m rm.history = rms rm.save() logger.debug("%s: Change maintainer to %s in commit %s." % \ (pn, m.name, commit)) else: logger.debug("%s: Not found in %s." % \ (pn, layerbranch)) # set missing recipes to no maintainer for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: Not found maintainer in commit %s set to 'No maintainer'." % \ (recipe.pn, rms.sha1)) # set new recipes to no maintainer if don't have one rms = RecipeMaintainerHistory.get_last(layerbranch) for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: New recipe linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: New recipe not found maintainer set to 'No maintainer'." % \ (recipe.pn)) if options.dry_run: raise DryRunRollbackException except DryRunRollbackException: pass """ Recreate Maintainership history from the beginning """ def maintainer_history(options, logger): fetchdir = settings.LAYER_FETCH_DIR if options.plan: maintplans = MaintenancePlan.objects.filter(id=int(options.plan)) if not maintplans.exists(): logger.error('No maintenance plan with ID %s found' % options.plan) sys.exit(1) else: maintplans = MaintenancePlan.objects.filter(updates_enabled=True) if not maintplans.exists(): logger.error('No enabled maintenance plans found') sys.exit(1) lockfn = os.path.join(fetchdir, "layerindex.lock") lockfile = utils.lock_file(lockfn) if not lockfile: logger.error("Layer index lock timeout expired") sys.exit(1) try: for maintplan in maintplans: for item in maintplan.maintenanceplanlayerbranch_set.all(): layerbranch = item.layerbranch if options.fullreload and not options.dry_run: RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch).delete() urldir = str(layerbranch.layer.get_fetch_dir()) repodir = os.path.join(fetchdir, urldir) layerdir = os.path.join(repodir, layerbranch.vcs_subdir) if maintplan.maintainer_style == 'I': # maintainers.inc maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir) elif maintplan.maintainer_style == 'L': # Layer-wide, don't need to do anything logger.debug('Skipping maintainer processing for %s - plan %s maintainer style is layer-wide' % (layerbranch, maintplan)) else: raise Exception('Unknown maintainer style %s for maintenance plan %s' % (maintplan.maintainer_style, maintplan)) finally: utils.unlock_file(lockfile) if __name__=="__main__": parser = optparse.OptionParser(usage = """%prog [options]""") parser.add_option("-p", "--plan", help="Specify maintenance plan to operate on (default is all plans that have updates enabled)", action="store", dest="plan", default=None) parser.add_option("--fullreload", help="Reload upgrade data from scratch", action="store_true", dest="fullreload", default=False) parser.add_option("-d", "--debug", help = "Enable debug output", action="store_const", const=logging.DEBUG, dest="loglevel", default=logging.INFO) parser.add_option("--dry-run", help = "Do not write any data back to the database", action="store_true", dest="dry_run", default=False) logger = get_logger("MaintainerUpdate", settings) options, args = parser.parse_args(sys.argv) logger.setLevel(options.loglevel) maintainer_history(options, logger)
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data/logs_model/logs_producer/kafka_logs_producer.py
anwarchk/quay
1
195823
import logging from kafka.errors import KafkaError, KafkaTimeoutError from kafka import KafkaProducer from data.logs_model.shared import epoch_ms from data.logs_model.logs_producer.interface import LogProducerInterface from data.logs_model.logs_producer.util import logs_json_serializer from data.logs_model.logs_producer import LogSendException logger = logging.getLogger(__name__) DEFAULT_MAX_BLOCK_SECONDS = 5 class KafkaLogsProducer(LogProducerInterface): """ Log producer writing log entries to a Kafka stream. """ def __init__(self, bootstrap_servers=None, topic=None, client_id=None, max_block_seconds=None): self.bootstrap_servers = bootstrap_servers self.topic = topic self.client_id = client_id self.max_block_ms = (max_block_seconds or DEFAULT_MAX_BLOCK_SECONDS) * 1000 self._producer = KafkaProducer(bootstrap_servers=self.bootstrap_servers, client_id=self.client_id, max_block_ms=self.max_block_ms, value_serializer=logs_json_serializer) def send(self, logentry): try: # send() has a (max_block_ms) timeout and get() has a (max_block_ms) timeout # for an upper bound of 2x(max_block_ms) before guaranteed delivery future = self._producer.send(self.topic, logentry.to_dict(), timestamp_ms=epoch_ms(logentry.datetime)) record_metadata = future.get(timeout=self.max_block_ms) assert future.succeeded except KafkaTimeoutError as kte: logger.exception('KafkaLogsProducer timeout sending log to Kafka: %s', kte) raise LogSendException('KafkaLogsProducer timeout sending log to Kafka: %s' % kte) except KafkaError as ke: logger.exception('KafkaLogsProducer error sending log to Kafka: %s', ke) raise LogSendException('KafkaLogsProducer error sending log to Kafka: %s' % ke) except Exception as e: logger.exception('KafkaLogsProducer exception sending log to Kafka: %s', e) raise LogSendException('KafkaLogsProducer exception sending log to Kafka: %s' % e)
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Character.py
AvenirX/Meicraft
0
170075
# toImpr remove import? from Skill import the_skill class Hero: def __init__(self, name, type_): self.name = name self.type_ = type_ self.level = 1 self.EXP = 0 self.__HP = 5 # self.__STR = 2 # self.__AGI = 1 # self.__INT = 1 self.__STA = 1 self.HP = 0 # self.STR = 0 # self.AGI = 0 # self.INT = 0 self.STA = 0 self.SKILLBOOK = ['attack', 'prep', 'defend'] self.money = 0 self.equipments = { # 'weapon': None, # 'armour': None, # 'jewelry': None } self.inventory = [] self.loot = self.inventory self.reset_status() self.alive = True def __repr__(self): return self.name def change_name(self, new_name): self.name = new_name def reset_status(self): # self.STR = self.__STR # self.AGI = self.__AGI # self.INT = self.__INT self.STA = self.__STA self.HP = self.__HP + self.STA * 1 def is_alive(self): return True if self.alive else False def increase_hp(self, amount): self.HP += amount def add_exp(self, amount): self.EXP += amount print('{p} gets {e} EXP'.format(p=self.name, e=amount)) # self.level_up() # # def level_up(self): # while self.EXP > level_exp[self.level]: # self.EXP -= level_exp[self.level] # self.level += 1 # # self.__HP += 1 # self.__STR += 2 # self.__AGI += 1 # self.__INT += 1 # self.__STA += 1 # # self.reset_status() # print('\t\t\t\t\t\t\t\t\t\tHERO [{p}] LEVEL UP!'.format(p=self.name)) # return # def acquire_item(self, item_id): # item = the_item(item_id)() # self.put_in_item(item) def put_in_item(self, item): if item not in self.inventory: self.inventory.append(item) def take_out_item(self, item): self.inventory.remove(item) def equip_item(self, item): if item in self.inventory and item.equipment: self.take_out_item(item) self.equipments[item.category] = item def unequip_item(self, item): if self.equipments[item.category]: self.equipments[item.category] = None self.put_in_item(item) # def increase_level(self, n): # self.level += n # print('{p} level is increased by {n}'.format(p=self.name, n=n)) # toImpr new report according to new inventory # def report_wealth(self): # print('{p} has {e} EXP, {m} money'.format( # p=self.name, # e=self.EXP, # m=self.money # )) # # print('Bag:\n-----------') # if self.inventory: # for item in self.inventory: # print('{i} x {n}'.format(i=item, n=self.inventory[item])) # else: # print('Empty') # print('-----------') def add_money(self, amount): self.money += amount print('{p} gets {m} money'.format(p=self.name, m=amount)) # # level_exp = { # 1: 20, # 2: 40, # 3: 80, # 4: 160 # } class Fighter(Hero): def __init__(self, name, type_='STR', is_npc=False): super(Fighter, self).__init__(name, type_) self.PHASE = '' self.MP = 0 self.BATTLESKILLBOOK = {} self.is_npc = is_npc self.died_turn = 9999 self.lethal_projectiles = [] self.score = 0 self.kills = 0 self.survive_turns = 0 self.last_move = None self.incoming_projectiles = None self.init_turn() print('Fighter [{name}({type_})] initialized'.format( name=self.name, type_=self.type_), end=' ') print(self.BATTLESKILLBOOK) def init_battle(self): self.load_battle_skills() self.score = 0 self.kills = 0 self.survive_turns = 0 def load_battle_skills(self): for skill_id in self.SKILLBOOK: skill = the_skill(skill_id)(self) self.BATTLESKILLBOOK[skill.key] = skill for category, equipment in self.equipments.items(): if category in ['weapon', 'armour', 'jewelry']: skill_id = equipment.skill skill = the_skill(skill_id)(self) self.BATTLESKILLBOOK[skill.key] = skill # def init_skills(self): # self.BATTLESKILLBOOK = {'A': the_skill('attack')(self), # 'A2': the_skill('attack2')(self), # 'D': the_skill('defend')(self), # 'P': the_skill('prep')(self)} def init_turn(self): self.incoming_projectiles = { 'potion': {'heal': [], 'damage': [], 'fill': [], 'drain': []}, 'arrow': {'heal': [], 'damage': [], 'fill': [], 'drain': []} } self.last_move = '...' if self.is_alive(): self.survive_turns += 1 # toImpr move to turns over self.gain_score(1) def get_available_skills(self): available_skills = [] for skill_key in self.BATTLESKILLBOOK: if self.BATTLESKILLBOOK[skill_key].is_available(): available_skills.append(skill_key) else: continue return available_skills # toImpr move to Hero def increase_mp(self, amount): self.MP += amount def gain_score(self, amount): self.score += amount def set_phase(self, phase_type): self.PHASE = phase_type def killed_someone(self): # toImpr move magical nb to global setting # toImpr scoring move to turns over? self.gain_score(3) self.kills += 1 def go_die(self, turn): self.alive = False self.died_turn = turn self.lethal_projectiles = self.incoming_projectiles['arrow']['damage'] def report_status(self): print('[{n}]: {hp} HP {mp} MP {s}' .format(n=self.name, hp=self.HP, mp=self.MP, s=str(self.BATTLESKILLBOOK.keys())))
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apps/views.py
Edwardhgj/meiduo
0
7292
<reponame>Edwardhgj/meiduo from django.shortcuts import render from django.http import HttpResponse from django.contrib.auth.hashers import check_password, make_password from django.views import View from utils.response_code import RET, error_map from rest_framework.views import APIView from rest_framework.response import Response from apps.serializers import * from datetime import datetime # Create your views here. # 展示登陆页 def login(request): return render(request, 'admin/login.html') # 提交登陆 import json class SubmitLogin(View): def post(self, request): #反射 mes = {} name = request.POST.get('name') passwd = request.POST.get('passwd') # print(name,passwd) if not all([name, passwd]): mes['code'] = RET.DATAERR mes['message'] = error_map[RET.DATAERR] else: # 查询name admin = Sadmin.objects.filter(username=name).first() print(admin.username) if admin: # 比较密码 if check_password(passwd, admin.password): # 登陆成功 request.session['admin_id'] = admin.id mes['code'] = RET.OK mes['message'] = error_map[RET.OK] else: mes['code'] = RET.PWDERR mes['message'] = error_map[RET.PWDERR] else: mes['code'] = RET.USERERR mes['message'] = error_map[RET.USERERR] print('sdfsdfssdf') return HttpResponse(json.dumps(mes)) # 注册 def reg(request): password = <PASSWORD>_password('<PASSWORD>') admin = Sadmin(username='admin', password=password, is_admin=True) admin.save() return HttpResponse('ok') # 展示首页 def index(request): admin_id = request.session.get('admin_id') if admin_id: admin = Sadmin.objects.get(id=admin_id) return render(request, 'admin/index.html', locals()) # 展示分类页面 def showCate(request): return render(request, "admin/cate_list.html") # 展示新闻页面 def showNews(request): return render(request, "admin/news_list.html") #展示焦点图页面 def bannersCate(request): return render(request, "admin/point_list.html") #展示标签页面 def tagCate(request): return render(request, "admin/tag_list.html") #展示商品页面 def goodsCate(request): return render(request, "admin/goods_list.html") #展示商品页面 def newsCate(request): return render(request, "admin/news_list.html") #展示焦点图页面 def bannersCate(request): return render(request, "admin/point_list.html") # 分类列表 class CateList(APIView): def get(self, request): cate = Cate.objects.all() c = CateModelSerializer(cate, many=True) mes = {} mes['code'] = RET.OK mes['cateList'] = c.data return Response(mes) #标签列表 class TagList(APIView): def get(self, request): tags = Tags.objects.all() c = TagModelSerializer(tags, many=True) mes = {} mes['code'] = RET.OK mes['tagList'] = c.data return Response(mes) # 商品列表 class GoodsList(APIView): def get(self, request): goods = Goods.objects.all() g = GoodsModelSerializer(goods, many=True) mes = {} mes['code'] = RET.OK mes['goodsList'] = g.data return Response(mes) #新闻列表 class NewsList(APIView): def get(self, request): news = News.objects.all() n=NewsModelSerializer(news,many=True) mes = {} mes['code'] = RET.OK mes['newsList'] = n.data return Response(mes) #焦点图列表 class BannersList(APIView): def get(self, request): banners = Banners.objects.all() n=BannersModelSerializer(banners,many=True) mes = {} mes['code'] = RET.OK mes['bannersList'] = n.data return Response(mes) # 添加分类页面 def addCate(request): # 获取一级分类 cate = Cate.objects.filter(pid=0).all() id=request.GET.get('id') try: #修改 one_cate=Cate.objects.get(id=id) print(one_cate) except: id="" return render(request, "admin/add_cate.html", locals()) # 添加标签页面 def addTag(request): # print('sdf') cate_list = Cate.objects.all() id=request.GET.get('id') try: #修改 one_tag=Tags.objects.get(id=id) except: id="" return render(request, "admin/add_tag.html", locals()) # 添加商品页面 def addGoods(request): # print('ceshi') # 获取所有商品 goods = Goods.objects.all() cates = Cate.objects.all() tag_list=Tags.objects.all() id=request.GET.get('id') print(id) try: one_goods=Goods.objects.get(id=id) # print(one_goods) except: id="" return render(request, "admin/add_goods.html", locals()) # 添加商品页面 def addNews(request): # print('ceshi') # 获取所有商品 news = News.objects.all() #修改时需要传id id=request.GET.get('id') print(id) try: one_news=News.objects.get(id=id) # print(one_goods) except: id="" return render(request, "admin/add_news.html", locals()) # 添加焦点图页面 def addBanners(request): # print('ceshi') # 获取所有商品 banners = Banners.objects.all() #修改时需要传id id=request.GET.get('id') print(id) try: one_banner=Banners.objects.get(id=id) # print(one_goods) except: id="" return render(request, "admin/add_banners.html", locals()) from day01.settings import UPLOADFILES import os # 上传图片方法 def upload_img(img): if img: f = open(os.path.join(UPLOADFILES, '', img.name),'wb') for chunk in img.chunks(): f.write(chunk) f.close() img=datetime.now().strftime("%Y-%m-%d-%H-%M-%S")+img.name return 'http://127.0.0.1:8000/static/upload/'+img return ' ' #富文本上传图片 def addnews_upload(request): files = request.FILES.get('file') path = upload_img(files) mes = { 'path': path, 'error': False } return HttpResponse(json.dumps(mes)) # 增加分类接口 class SubmitAddCate(APIView): def post(self, request): content = request.data print(content) # 上传图片 img = request.FILES.get('img') path=upload_img(img) content['picture']=path try: pid=int(content['pid']) except: pid=0 # 通过pic构造top_id，type if pid == 0: type = 1 top_id = 0 else: cate = Cate.objects.get(id=pid) type = cate.type + 1 if cate.top_id==0: top_id = cate.id else: top_id = cate.top_id print(top_id,pid,type) content['type'] = type content['top_id'] = top_id try: id=int(content['id']) except: id=0 if id>0: cc=Cate.objects.get(id=id) c=CateSerializer(cc,data=content) #修改 else: c = CateSerializer(data=content) mes={} if c.is_valid(): try: c.save() mes['code'] = RET.OK except: mes['code'] = RET.DATAERR else: print(c.errors) mes['code'] = RET.DATAERR return Response(mes) #删除分类 def deleteCate(request): id=request.GET.get('id') Cate.objects.get(id=id).delete() return render(request, "admin/cate_list.html") # 增加标签接口 class SubmitAddTag(APIView): def post(self, request): content = request.data print(content) try: id = int(content['id']) # 取出id print(id) print('di 到这了') except: id = 0 if id > 0: dd = Tags.objects.get(id=id) d = TagSerializer(dd, data=content) # 修改 else: d = TagSerializer(data=content) mes = {} if d.is_valid(): try: d.save() mes['code'] = RET.OK except: mes['code'] = RET.DATAERR else: mes['code'] = RET.DATAERR return Response(mes) #删除标签 def deleteTag(request): id=request.GET.get('id') Cate.objects.get(id=id).delete() return render(request, "admin/tag_list.html") # 增加商品接口 class SubmitAddGoods(APIView): def post(self, request): # print('eerw') content = request.data print(content) print(content['id']) print(content['cid_id']) # 上传图片 img = request.FILES.get('img') path=upload_img(img) content['picture']=path one_cate=Cate.objects.get(id=int(content['cid_id'])) print(one_cate) content['top_id'] = one_cate.top_id try: print('测试代码') id=int(content['id']) print(id) except: id=0 if id>0: # 修改商品 instance = Goods.objects.get(id=id) c = GoodsSerializer(instance, data=content) else: c = GoodsSerializer(data=content) mes={} if c.is_valid(): c.save() mes['code'] = RET.OK else: print(c.errors) mes['code'] = RET.DATAERR return Response(mes) #删除商品 def deleteGoods(request): id=request.GET.get('id') Goods.objects.get(id=id).delete() return render(request, "admin/goods_list.html") #添加新闻接口 class SubmitAddNews(APIView): def post(self,request): content=request.data print(content) try: id = int(content['id']) # 取出id except: id = 0 if id > 0: print(id) nn = News.objects.get(id=id) d = NewsSerializer(nn, data=content) # 修改 else: d = NewsSerializer(data=content) mes = {} if d.is_valid(): try: d.save() mes['code'] = RET.OK except: mes['code'] = RET.DATAERR else: mes['code'] = RET.DATAERR return Response(mes) #删除新闻 def deleteNews(request): id=request.GET.get('id') News.objects.get(id=id).delete() return render(request,"admin/news_list.html") #删除焦点图 def deleteBanners(request): id=request.GET.get('id') Banners.objects.get(id=id).delete() return render(request,"admin/point_list.html") #添加焦点图接口 class SubmitAddBanner(APIView): def post(self,request): content=request.data print(content) try: id = int(content['id']) # 取出id except: id = 0 if id > 0: print(id) nn = Banners.objects.get(id=id) d = BannersSerializer(nn, data=content) # 修改 else: d = BannersSerializer(data=content) mes = {} if d.is_valid(): try: d.save() mes['code'] = RET.OK except: mes['code'] = RET.DATAERR else: mes['code'] = RET.DATAERR return Response(mes) def user_count(request): return render(request,'admin/user_count.html')
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n_step_sarsa.py
SuperSaiyan-God/Reinforcement-Learning
0
47375
import numpy as np import gym poleThetaSpace = np.linspace(-0.209, 0.209, 10) poleThetaVelSpace = np.linspace(-4, 4, 10) cartPosSpace = np.linspace(-2.4, 2.4, 10) cartVelSpace = np.linspace(-4, 4, 10) def get_state(observation): cartX, cartXdot, cartTheta, cartThetaDot = observation cartX = int(np.digitize(cartX, cartPosSpace)) cartXdot = int(np.digitize(cartXdot, cartVelSpace)) cartTheta = int(np.digitize(cartTheta, poleThetaSpace)) cartThetaDot = int(np.digitize(cartThetaDot, poleThetaVelSpace)) return (cartX, cartXdot, cartTheta, cartThetaDot) def choose_action(q, obs, eps, n_actions=2): state = get_state(obs) if np.random.random() < eps: action = np.random.choice([i for i in range(n_actions)]) else: action_values = [q[(state, a)] for a in range(n_actions)] action = np.argmax(action_values) return action if __name__ == '__main__': env = gym.make('CartPole-v0') alpha = 0.1 gamma = 0.9 epsilon = 1.0 states = [] for i in range(len(cartPosSpace)+1): for j in range(len(cartVelSpace)+1): for k in range(len(poleThetaSpace)+1): for l in range(len(poleThetaVelSpace)+1): states.append((i,j,k,l)) Q = {} for s in states: for a in range(2): Q[(s, a)] = 0.0 n = 16 state_memory = np.zeros((n, 4)) action_memory = np.zeros(n) reward_memory = np.zeros(n) scores = [] n_episodes = 50000 for i in range(n_episodes): done = False score = 0 t = 0 T = np.inf observation = env.reset() action = choose_action(Q, observation, epsilon) action_memory[t%n] = action state_memory[t%n] = observation while not done: observation, reward, done, info = env.step(action) score += reward state_memory[(t+1)%n] = observation reward_memory[(t+1)%n] = reward if done: T = t + 1 #print('episode ends at step', t) action = choose_action(Q, observation, epsilon) action_memory[(t+1)%n] = action tau = t - n + 1 if tau >= 0: G = [gamma**(j-tau-1)*reward_memory[j%n] \ for j in range(tau+1, min(tau+n, T)+1)] G = np.sum(G) if tau + n < T: s = get_state(state_memory[(tau+n)%n]) a = int(action_memory[(tau+n)%n]) G += gamma**n * Q[(s,a)] s = get_state(state_memory[tau%n]) a = action_memory[tau%n] Q[(s,a)] += alpha*(G-Q[(s,a)]) #print('tau ', tau, '| Q %.2f' % \ # Q[(get_state(state_memory[tau%n]), action_memory[tau%n])]) t += 1 for tau in range(t-n+1, T): G = [gamma**(j-tau-1)*reward_memory[j%n] \ for j in range(tau+1, min(tau+n, T)+1)] G = np.sum(G) if tau + n < T: s = get_state(state_memory[(tau+n)%n]) a = int(action_memory[(tau+n)%n]) G += gamma**n * Q[(s,a)] s = get_state(state_memory[tau%n]) a = action_memory[tau%n] Q[(s,a)] += alpha*(G-Q[(s,a)]) #print('tau ', tau, '| Q %.2f' % \ # Q[(get_state(state_memory[tau%n]), action_memory[tau%n])]) scores.append(score) avg_score = np.mean(scores[-1000:]) epsilon = epsilon -2 / n_episodes if epsilon > 0 else 0 if i % 1000 == 0: print('episode ', i, 'avg_score %.1f' % avg_score, 'epsilon %.2f' % epsilon)
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smedl/parser/smedl_semantics.py
PRECISE/SMEDL
0
68114
# Copyright (c) 2021 The Trustees of the University of Pennsylvania # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. """ SMEDL file semantic actions """ from smedl.structures import monitor, expr from . import common_semantics from .exceptions import TypeMismatch, NameNotDefined class SmedlSemantics(common_semantics.CommonSemantics): """Semantic actions for SMEDL parsing""" def __init__(self, path): """Do some basic initialization path - The directory the .smedl file resides in""" self.path = path # self.monitor is created in declaration() def start(self, ast): """Return the MonitorSpec object""" return self.monitor def declaration(self, ast): """Create the MonitorSpec object""" self.monitor = monitor.MonitorSpec(ast, self.path) return ast def helper_definition(self, ast): """Add a helper file""" self.monitor.add_helper(ast) return ast def _initial_value_matches(self, var_type, value_type): if var_type is expr.SmedlType.INT: # Float is normally permitted for assignment to int, but if used # for initialization, something is likely wrong. return value_type in ['int', 'char'] elif var_type is expr.SmedlType.FLOAT: return value_type in ['float', 'int', 'char'] elif var_type is expr.SmedlType.CHAR: return value_type in ['char', 'int'] elif var_type is expr.SmedlType.STRING: return value_type == 'string' elif var_type is expr.SmedlType.POINTER: return value_type == 'null' elif var_type is expr.SmedlType.OPAQUE: # TODO Should we allow opaques to be initialized like strings? return False def state_declaration(self, ast): """Add a state variable to the monitor""" var_name = ast.name var_type = ast.type value = ast.value # Check type of the initial value if (value is not None and not self._initial_value_matches(var_type, value.type)): raise TypeMismatch( "State var {} initialized to incompatible value {}.".format( var_name, value.value)) # Add to the monitor (and check if already declared) if value is None: self.monitor.add_state_var(var_name, var_type) else: self.monitor.add_state_var(var_name, var_type, value.value) return ast def event_declaration(self, ast): """Add events from an event declaration to the monitor""" ev_type = ast.type # One declaration can declare multiple events for signature in ast.signatures: ev_name = signature.name ev_params = signature.params self.monitor.add_event(ev_type, ev_name, ev_params) return ast def scenario(self, ast): """Add a scenario to the monitor""" # Create an empty scenario scenario = monitor.Scenario(ast.name) # Populate the states and transitions of the scenario for transition in ast.transitions: # Get else state and actions if transition.else_step is not None: else_state = transition.else_step.else_state else_actions = transition.else_step.else_actions else: else_state = None else_actions = None # Loop over the steps in the transition and add to the scenario from_state = transition.start_state for step in transition.steps.step_list[:-1]: # All steps except the last one go to an implicit state to_state = scenario.get_implicit_state() event_name = step.event.name condition = step.condition actions = step.actions scenario.add_step( from_state, event_name, condition, to_state, actions, else_state, else_actions) from_state = to_state # Do the last iteration separately - # to_state = transition.end_state step = transition.steps.step_list[-1] to_state = transition.steps.end_state event_name = step.event.name condition = step.condition actions = step.actions scenario.add_step( from_state, event_name, condition, to_state, actions, else_state, else_actions) # If a final state was given, check if it exists and add it if ast.final_state is not None: scenario.add_final_state(ast.final_state) # Add the scenario to the monitor self.monitor.add_scenario(scenario) return ast def step_definition_list(self, ast): """Transform the AST into a list of steps (ast.step_list) and an end state (ast.end_state). Also store whether there is a single or multiple steps in the transition, as else_preproc will need this to determine whether to allow else actions to use event parameter bindings.""" step_list = [ast.step] if ast.rest is None: self.multiple_steps = False else: self.multiple_steps = True step_list.extend(ast.rest.step_list) ast['end_state'] = ast.rest.end_state del ast['rest'] del ast['step'] ast['step_list'] = step_list return ast def step_definition(self, ast): """Step definitions may not have actions, in which case the actions key will store None. In that case, convert it to an empty list.""" if ast.actions is None: ast['actions'] = [] return ast def else_definition(self, ast): """Else definitions may not have actions, in which case the actions key will store None. In that case, convert it to an empty list.""" if ast.else_actions is None: ast['else_actions'] = [] return ast def else_preproc(self, ast): """If there are multiple steps in this transition, clear the event parameter bindings before processing the else actions.""" if self.multiple_steps: self.current_event = None self.current_event_params = [] return ast def step_event_definition(self, ast): """Store the parameter name bindings for the current event so they are available to actions and conditions in this step.""" self.current_event = ast.name self.current_event_params = ast.params # Will be a list of (str) names # Verify that event exists and that the parameter count matches if ast.name in self.monitor.imported_events: if len(self.monitor.imported_events[ast.name]) != len(ast.params): raise NameNotDefined("{} event has incorrect number of " "parameters".format(ast.name)) elif ast.name in self.monitor.internal_events: if len(self.monitor.internal_events[ast.name]) != len(ast.params): raise NameNotDefined("{} event has incorrect number of " "parameters".format(ast.name)) elif ast.name in self.monitor.exported_events: if len(self.monitor.exported_events[ast.name]) != len(ast.params): raise NameNotDefined("{} event has incorrect number of " "parameters".format(ast.name)) else: raise NameNotDefined("{} event is not an imported, internal, or" "exported event.".format(ast.name)) return ast def action_inner_list(self, ast): """Convert action_inner_lists into an actual list""" if ast.first is None: result = [] else: result = [ast.first] if ast.rest is not None: result.extend(ast.rest) return result def assignment(self, ast): """Verify that the state variable exists and the type matches the expression, then create the AssignmentAction""" # Verify that the state variable exists try: state_var = self.monitor.state_vars[ast.target] except KeyError: raise NameNotDefined("{} is not a state variable".format( ast.target)) # Check type try: ast.value.assignment_type_check(state_var.type) except TypeMismatch: raise TypeMismatch( "Expression of type {} cannot be assigned to state variable " "{} of incompatible type {}".format( ast.value.type, ast.target, state_var.type)) # Create AssignmentAction return monitor.AssignmentAction(ast.target, ast.value) def increment(self, ast): """Verify that the state variable exists and is numeric or pointer, then create the IncrementAction""" # Verify that the state variable exists try: state_var = self.monitor.state_vars[ast.target] except KeyError: raise NameNotDefined("{} is not a state variable".format( ast.target)) # Check type if state_var.type not in [ expr.SmedlType.INT, expr.SmedlType.FLOAT, expr.SmedlType.CHAR, # TODO Allow pointer increment and decrement? If so, should we # also allow +/- on pointers? expr.SmedlType.POINTER]: raise TypeMismatch( "Cannot increment state variable {} of type {}" .format(ast.target, state_var.type)) # Create action return monitor.IncrementAction(ast.target) def decrement(self, ast): """Verify that the state variable exists and is numeric or pointer, then create the DecrementAction""" # Verify that the state variable exists try: state_var = self.monitor.state_vars[ast.target] except KeyError: raise NameNotDefined("{} is not a state variable".format( ast.target)) # Check type if state_var.type not in [ expr.SmedlType.INT, expr.SmedlType.FLOAT, expr.SmedlType.CHAR, # TODO Allow pointer increment and decrement? If so, should we # also allow +/- on pointers? expr.SmedlType.POINTER]: raise TypeMismatch( "Cannot decrement state variable {} of type {}" .format(ast.target, state_var.type)) # Create action return monitor.DecrementAction(ast.target) def raise_stmt(self, ast): """Verify that the event is an internal or exported event and do type checking on the parameters, then create the RaiseAction""" # Check that the event is internal or exported and the parameter count # matches if ast.event in self.monitor.exported_events: if len(self.monitor.exported_events[ast.event]) != len(ast.params): raise NameNotDefined("{} event has incorrect number of " "parameters".format(ast.event)) else: event_params = self.monitor.exported_events[ast.event] elif ast.event in self.monitor.internal_events: if len(self.monitor.internal_events[ast.event]) != len(ast.params): raise NameNotDefined("{} event has incorrect number of " "parameters".format(ast.event)) else: event_params = self.monitor.internal_events[ast.event] else: raise NameNotDefined("{} event is not an exported or internal " "event.".format(ast.event)) # Type check the parameters for i in range(len(ast.params)): ast.params[i].assignment_type_check(event_params[i]) # Create the RaiseAction return monitor.RaiseAction(ast.event, ast.params) def call_stmt(self, ast): """Create the CallAction""" # Calling a helper function as an action should be discouraged and # potentially depecated. Its only use would be functions with side # effects. # There is little verification we can do besides the type checking # already done by Expressions, so simply create the action. return monitor.CallAction(ast.function, ast.params) # Expressions and type checking ########################################### # Note: All type_ parameters should be either a SmedlType, "null", or None. # None if it is a helper function or an expression with a helper function # (as we cannot type check these); "null" if it is a null pointer (valid # for either POINTER or OPAQUE types; SmedlType otherwise. def literal(self, ast): """Convert a literal to an expr.Literal""" if ast.type in ["int", "char"]: # C treats both of these as int literals return expr.Literal(ast.value, expr.SmedlType.INT) elif ast.type == "float": return expr.Literal(ast.value, expr.SmedlType.FLOAT) elif ast.type == "string": return expr.Literal(ast.value, expr.SmedlType.STRING) elif ast.type == "null": return expr.Literal(ast.value, "null") def helper_call(self, ast): """Convert a helper function call to an expr.HelperCall""" return expr.HelperCall(ast.function, ast.params) def var_or_param(self, ast): """Convert a state variable or event parameter to an expr.StateVar or expr.EventParam""" try: param_idx = self.current_event_params.index(ast) if self.current_event in self.monitor.imported_events: param_type = self.monitor.imported_events[ self.current_event][param_idx] elif self.current_event in self.monitor.internal_events: param_type = self.monitor.internal_events[ self.current_event][param_idx] return expr.EventParam(param_idx, param_type) except ValueError: # Not an event parameter. Must be a state variable. try: state_var = self.monitor.state_vars[ast] type_ = state_var.type return expr.StateVar(ast, type_) except KeyError: raise NameNotDefined("Variable {} is not an event parameter " "or state variable.".format(ast)) def parenthesized(self, ast): """Parenthesize an expression""" ast.parenthesize() return ast def unary_expr(self, ast): """Type check the unary_expr and create a UnaryOp""" if isinstance(ast, expr.Expression): return ast # This also does type checking return expr.UnaryOp(ast[0], ast[1]) def expression(self, ast): """Type check all binary expressions and create BinaryOps from them""" # This will receive a "tree" of 3-tuples where first element is the # operator, second is the left operand, and third is the right operand. # This must be processed recursively. if isinstance(ast, expr.Expression): return ast left = self.expression(ast[1]) right = self.expression(ast[2]) # This also does type checking return expr.BinaryOp(ast[0], left, right) ########################################################################### def signed_literal(self, ast): """Signed literals are only used for state initialization. Join the signed variants into single strings.""" if ast.type == 'signed_int': val = ast.value del ast['type'] del ast['value'] ast['type'] = 'int' ast['value'] = ''.join(val) elif ast.type == 'signed_float': val = ast.value del ast['type'] del ast['value'] ast['type'] = 'float' ast['value'] = ''.join(val) return ast
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client/__init__.py
georgemunyoro/code-jam
1
174772
"""A TUI client to the snake game.""" # This file exists to denote to Python that the folder is a package.
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PrelimDataAnalysis.py
Cian-Byrne/ML_Yacht_Performance
0
102251
import seaborn as sns import pickle import os import matplotlib.pyplot as plt import numpy as np import pandas as pd %matplotlib qt sns.set() # -------------------------------------------------------------------------------------------------- # Import both datasets separately dfTP = pd.DataFrame() dfTP = dfTP.append(pd.read_csv(r'Data/Labeled_all_VPP_waves.csv')) dfTP = dfTP[(dfTP['label'] == 'UW') | (dfTP['label'] == 'DW')] dfSwan = pd.DataFrame() dfSwan = dfSwan.append(pd.read_csv(r'Data/Swan45_DataCombined.csv')) dfSwan = dfSwan[(dfSwan['label'] == 'UW') | (dfSwan['label'] == 'DW')] # -------------------------------------------------------------------------------------------------- # Plotting functions def plot_polar_raw(df): fig = plt.figure(figsize=(12, 8)) ax = fig.add_subplot(111, polar=True) ax.scatter(df.abs_Twa*np.pi/180, df.Bsp, c=df.Tws, cmap='Blues', label='Raw Data') ax.set_thetamin(0) ax.set_thetamax(180) ax.set_theta_direction(-1) ax.set_theta_offset(np.pi/2) ax.set_rmax(df.Bsp.max()+1.5) plt.legend() plt.show() return def plot_polar_3d(df): fig = plt.figure(figsize=(10, 8), dpi=100) ax = fig.add_subplot(111, projection='3d') ax.scatter(df.Bsp, df.abs_Twa, df.Tws, c='b', label='Polar Plot') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) plt.show() return def WindDist_Plot(df,): # Tp-Hs plot ax = sns.jointplot(x=df.Tws, y=df.Twa, kind='hex').set_axis_labels("Tws", "Twa") ax.ax_joint.grid() ax.ax_joint.set_xlim([5, 25]) ax.ax_joint.set_ylim([-180, 180]) plt.tight_layout() plt.show() return # -------------------------------------------------------------------------------------------------- # Import ORC Swan model pickleIn = open('Models/ORC_Swan45_Rbf.pickle', 'rb') rbf_swan = pickle.load(pickleIn) pickleIn.close() def ORC(X): return rbf_swan(X[:, 0], X[:, 1]) # -------------------------------------------------------------------------------------------------- # Plots for the TP52 dataset # Polar plot colored by TWS plot_polar_raw(dfTP) # 3d plot colored by wave parameters fig = plt.figure(figsize=(8, 3), dpi=100) ax = fig.add_subplot(141, projection='3d') ax.scatter(dfTP.Bsp, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Heel_ampl, cmap='Blues', label='Colored by Heel_ampl') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(142, projection='3d') ax.scatter(dfTP.Bsp, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Trim_ampl, cmap='Reds', label='Colored by Trim_ampl') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(143, projection='3d') ax.scatter(dfTP.Bsp, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Heel_freq, cmap='Greens', label='Colored by Heel_Freq') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(144, projection='3d') ax.scatter(dfTP.Bsp, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Trim_freq, cmap='Purples', label='Colored by Trim_freq') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) plt.tight_layout() plt.legend() plt.show() dfTP.columns # plot model residuals fig = plt.figure(figsize=(8, 3), dpi=100) ax = fig.add_subplot(141, projection='3d') ax.scatter(dfTP.VPP_Bsp_error, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Heel_ampl, cmap='Blues', label='Colored by Heel_ampl') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(142, projection='3d') ax.scatter(dfTP.VPP_Bsp_error, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Trim_ampl, cmap='Reds', label='Colored by Trim_ampl') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(143, projection='3d') ax.scatter(dfTP.VPP_Bsp_error, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Heel_freq, cmap='Greens', label='Colored by Heel_Freq') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) ax = fig.add_subplot(144, projection='3d') ax.scatter(dfTP.VPP_Bsp_error, dfTP.abs_Twa, dfTP.Tws, c=dfTP.Trim_freq, cmap='Purples', label='Colored by Trim_freq') ax.set_xlabel('Bsp', fontsize=12) ax.set_ylabel('Twa', fontsize=12) ax.set_zlabel('Tws', fontsize=12) plt.tight_layout() plt.legend() plt.show() plt.hist(dfTP.VPP_Bsp_error) # ------------- # Histogram plots of wave parameters bins = 50 fig = plt.figure(figsize=(12, 8)) ax = fig.add_subplot(141) ax.set_title('Heel_ampl') ax.hist(dfTP.Heel_ampl, bins=bins) ax = fig.add_subplot(142) ax.set_title('Heel_freq') ax.hist(dfTP.Heel_freq, bins=bins) ax = fig.add_subplot(143) ax.set_title('Trim_ampl') ax.hist(dfTP.Trim_ampl, bins=bins) ax = fig.add_subplot(144) ax.set_title('Trim_freq') ax.hist(dfTP.Trim_freq, bins=bins) # --------------------------------- # Distribution of wind conditions WindDist_Plot(dfTP) # -------------------------------------------------------------------------------------------------- # plots for Swan45 Data plot_polar_raw(dfSwan) plot_polar_3d(dfSwan) WindDist_Plot(dfSwan) # -------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------- # -------------------------------------------------------------------------------------------------- # --------------------------------------------------------------------------------------------------
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covid/migrations/0023_spammer.py
vivekkhimani/LifeNest
2
1604526
<reponame>vivekkhimani/LifeNest # Generated by Django 3.2.3 on 2021-05-26 05:24 from django.db import migrations, models import django.db.models.deletion import phonenumber_field.modelfields class Migration(migrations.Migration): dependencies = [ ('covid', '0022_delete_spammer'), ] operations = [ migrations.CreateModel( name='Spammer', fields=[ ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('phone', phonenumber_field.modelfields.PhoneNumberField(max_length=20, region=None)), ('reason', models.CharField(help_text='Please explain the reason for marking this number as spam.', max_length=500)), ('reporter', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='covid.participant')), ], ), ]
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src/compas_rv2/datastructures/meshmixin.py
tkmmark/compas-RV2
0
177908
<filename>src/compas_rv2/datastructures/meshmixin.py from __future__ import print_function from __future__ import absolute_import from __future__ import division # from compas.utilities import pairwise from compas.geometry import angle_vectors __all__ = ['MeshMixin'] class MeshMixin(object): """Mixin for all mesh-based data structure in RV2.""" def edge_loop(self, uv): if self.is_edge_on_boundary(*uv): return self._edge_loop_on_boundary(uv) edges = [] current, previous = uv edges.append((previous, current)) while True: if current == uv[1]: break if self.vertex_attribute(current, 'is_fixed'): break nbrs = self.vertex_neighbors(current, ordered=True) if len(nbrs) != 4: break i = nbrs.index(previous) previous = current current = nbrs[i - 2] edges.append((previous, current)) edges[:] = [(u, v) for v, u in edges[::-1]] if edges[0][0] == edges[-1][1]: return edges previous, current = uv while True: if self.vertex_attribute(current, 'is_fixed'): break nbrs = self.vertex_neighbors(current, ordered=True) if len(nbrs) != 4: break i = nbrs.index(previous) previous = current current = nbrs[i - 2] edges.append((previous, current)) return edges def _edge_loop_on_boundary(self, uv): edges = [] current, previous = uv edges.append((previous, current)) while True: if current == uv[1]: break if self.vertex_attribute(current, 'is_fixed'): break nbrs = self.vertex_neighbors(current) if len(nbrs) == 2: break nbr = None for temp in nbrs: if temp == previous: continue if self.is_edge_on_boundary(current, temp): nbr = temp break if nbr is None: break previous, current = current, nbr edges.append((previous, current)) edges[:] = [(u, v) for v, u in edges[::-1]] if edges[0][0] == edges[-1][1]: return edges previous, current = uv while True: if self.vertex_attribute(current, 'is_fixed'): break nbrs = self.vertex_neighbors(current) if len(nbrs) == 2: break nbr = None for temp in nbrs: if temp == previous: continue if self.is_edge_on_boundary(current, temp): nbr = temp break if nbr is None: break previous, current = current, nbr edges.append((previous, current)) return edges def edge_strip(self, uv): edges = [] v, u = uv while True: edges.append((u, v)) fkey = self.halfedge[u][v] if fkey is None: break vertices = self.face_vertices(fkey) if len(vertices) != 4: break i = vertices.index(u) u = vertices[i - 1] v = vertices[i - 2] edges[:] = [(u, v) for v, u in edges[::-1]] u, v = uv while True: fkey = self.halfedge[u][v] if fkey is None: break vertices = self.face_vertices(fkey) if len(vertices) != 4: break i = vertices.index(u) u = vertices[i - 1] v = vertices[i - 2] edges.append((u, v)) return edges def vertices_on_edge_loop(self, uv): edges = self.edge_loop(uv) if len(edges) == 1: return edges[0] vertices = [edge[0] for edge in edges] if edges[-1][1] != edges[0][0]: vertices.append(edges[-1][1]) return vertices def corner_vertices(self, tol=160): vkeys = [] for key in self.vertices_on_boundary(): if self.vertex_degree(key) == 2: vkeys.append(key) else: nbrs = [] for nkey in self.vertex_neighbors(key): if self.is_edge_on_boundary(key, nkey): nbrs.append(nkey) u = (self.edge_vector(key, nbrs[0])) v = (self.edge_vector(key, nbrs[1])) if angle_vectors(u, v, deg=True) < tol: vkeys.append(key) return vkeys # def faces_on_edge_loop(self, uv): # pass # def faces_on_edge_strip(self, uv): # pass # def continuous_vertices_on_boundary(self, uv): # vertices = [] # current, previous = uv # vertices.append(current) # if not self.vertex_attribute(current, 'is_fixed'): # while True: # nbrs = self.vertex_neighbors(current) # for nbr in nbrs: # if nbr == previous: # continue # if self.is_edge_on_boundary(current, nbr): # vertices.append(nbr) # break # if vertices[-1] == vertices[0]: # break # if self.vertex_attribute(vertices[-1], 'is_fixed'): # break # previous = current # current = nbr # vertices[:] = vertices[::-1] # previous, current = uv # vertices.append(current) # if not self.vertex_attribute(current, 'is_fixed'): # while True: # nbrs = self.vertex_neighbors(current) # for nbr in nbrs: # if nbr == previous: # continue # if self.is_edge_on_boundary(current, nbr): # vertices.append(nbr) # break # if vertices[-1] == vertices[0]: # break # if self.vertex_attribute(vertices[-1], 'is_fixed'): # break # previous = current # current = nbr # return vertices # def continuous_vertices(self, uv): # """Ordered vertices along the direction of an edge. # Note that the direction of an edge only makes sense in a quad patch # of the diagram. Therefore, the search in either direction of the edge # stops if the next encountered vertex is not 4-valent, or if it is on # the boundary of the diagram. # Parameters # ---------- # uv : tuple # The edge identifier. # Returns # ------- # list # Ordered vertices along the direction of the edge. # The first vertex is the vertex at the end of the u-direction. # The last vertex is the vertex at the end of the v-direction. # """ # valency = 4 # if self.is_edge_on_boundary(*uv): # valency = 3 # vertices = [] # current, previous = uv # while True: # vertices.append(current) # nbrs = self.vertex_neighbors(current, ordered=True) # if len(nbrs) != valency: # break # i = nbrs.index(previous) # previous = current # current = nbrs[i - 2] # if valency == 3 and not self.is_edge_on_boundary(previous, current): # current = nbrs[i - 1] # vertices[:] = vertices[::-1] # previous, current = uv # while True: # vertices.append(current) # nbrs = self.vertex_neighbors(current, ordered=True) # if len(nbrs) != valency: # break # i = nbrs.index(previous) # previous = current # current = nbrs[i - 2] # if valency == 3 and not self.is_edge_on_boundary(previous, current): # current = nbrs[i - 1] # return vertices # def continuous_edges(self, uv): # """Ordered edges along the direction of an edge. # Note that the direction of an edge only makes sense in a quadpatch # of the diagram. Therefore, the search in either direction of the edges # stops if the opposite vertex of the next encountered edge is not # 4-valent or if it lies on the boundary of the diagram. # Parameters # ---------- # uv : tuple # The edge identifier. # Returns # ------- # list # A list of ordered edge identifiers. # Edges are aligned head-to-tail. # Therefore, the orientation of the edges is not necessarily the same as in the diagram. # The first edge is the edge at the end of the u-direction. # The last edge is the edge at the end of the # """ # vertices = self.continuous_vertices(uv) # return list(pairwise(vertices)) # def parallel_edges(self, uv): # """Edges parallel to an edge. # Parallel edges only exist in a quadpatch of the diagram. # The search in either direction stops as soon as the next edge # is adjacent to a face that is not a quadrilateral or if it is on # the boundary of the diagram. # Parameters # ---------- # uv : tuple # The edge identifier. # Returns # ------- # list # A list of parallel edges. # """ # edges = [] # v, u = uv # while True: # fkey = self.halfedge[u][v] # if fkey is None: # break # vertices = self.face_vertices(fkey) # if len(vertices) != 4: # break # edges.append((u, v)) # i = vertices.index(u) # u = vertices[i - 1] # v = vertices[i - 2] # edges[:] = edges[::-1] # u, v = uv # while True: # fkey = self.halfedge[u][v] # if fkey is None: # break # vertices = self.face_vertices(fkey) # if len(vertices) != 4: # break # edges.append((u, v)) # i = vertices.index(u) # u = vertices[i - 1] # v = vertices[i - 2] # return edges # def parallel_faces(self, uv): # """The faces along the direction of parallel edges. # Parameters # ---------- # uv : tuple # The edge identifier. # Returns # ------- # list # A list of parallel faces. # """ # faces = [] # v, u = uv # while True: # fkey = self.halfedge[u][v] # if fkey is None: # break # vertices = self.face_vertices(fkey) # if len(vertices) != 4: # break # faces.append(fkey) # i = vertices.index(u) # u = vertices[i - 1] # v = vertices[i - 2] # faces[:] = faces[::-1] # u, v = uv # while True: # fkey = self.halfedge[u][v] # if fkey is None: # break # vertices = self.face_vertices(fkey) # if len(vertices) != 4: # break # faces.append(fkey) # i = vertices.index(u) # u = vertices[i - 1] # v = vertices[i - 2] # return faces # ============================================================================== # Main # ============================================================================== if __name__ == '__main__': pass
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configs/mmdet/detection/detection_tensorrt_static-300x300.py
zhiqwang/mmdeploy
746
774
<reponame>zhiqwang/mmdeploy _base_ = ['../_base_/base_tensorrt_static-300x300.py']
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testfile.py
jordanwimb/kbpython
0
86819
<filename>testfile.py print("Hellllo")
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tests/encoding/test_lib.py
Defense-Cyber-Crime-Center/dfvfs
2
54845
# -*- coding: utf-8 -*- """Shared test cases.""" import unittest class DecoderTestCase(unittest.TestCase): """The unit test case for decoder object implementions."""
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