Reset23/the-stack-v2-filtered-python · Datasets at Hugging Face

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/pyobjc/pyobjc/pyobjc-core-2.5.1/PyObjCTest/test_bridges.py

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from PyObjCTools.TestSupport import * from PyObjCTest.testbndl import OC_TestClass2 import objc import collections import sys if sys.version_info[0] == 2: from UserList import UserList from UserDict import IterableUserDict else: from collections import UserDict as IterableUserDict, UserList NSMutableArray = objc.lookUpClass("NSMutableArray") NSMutableDictionary = objc.lookUpClass("NSMutableDictionary") def classOfProxy(value): return OC_TestClass2.classOfObject_(value) class TestBridges (TestCase): # NOTE: the two "register" functions from objc._bridges aren't # tested explictly, but the tests in this class do verify that # the default registrations (which are made through those two # functions) work properly. def test_xrange(self): range_type = range if sys.version_info[0] == 3 else xrange v = range_type(0, 10) self.assertTrue(issubclass(classOfProxy(v), NSMutableArray)) def test_user_collectons(self): # Note: Not "UserDict" because UserDict doesn't implement # __iter__ and hence isn't a collections.Mapping, and doesn't # implement enough API to implement the NSDictionary interface. v = IterableUserDict() self.assertTrue(issubclass(classOfProxy(v), NSMutableDictionary)) v = UserList() self.assertTrue(issubclass(classOfProxy(v), NSMutableArray)) def test_abc(self): class MySequence (collections.Sequence): def __getitem__(self, idx): raise IndexError(idx) def __len__(self): return 0 class MyDictionary (collections.Mapping): def __getitem__(self, key): raise KeyError(key) def __len__(self): return 0 def __iter__(self): return yield v = MyDictionary() self.assertTrue(issubclass(classOfProxy(v), NSMutableDictionary)) v = MySequence() self.assertTrue(issubclass(classOfProxy(v), NSMutableArray)) if __name__ == "__main__": main()

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/tests/common/test_retryutils.py

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VictorDenisov/ceph-lcm

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# -*- coding: utf-8 -*- """Tests for cephlcm.common.retryutils""" import unittest.mock import pymongo.errors import pytest from cephlcm.common import retryutils @pytest.fixture def func_always_fails(): func = unittest.mock.MagicMock() func.__name__ = "" func.side_effect = Exception return func @pytest.fixture def func_always_passed(): return unittest.mock.MagicMock() @pytest.fixture def func_pass_fail(): func = unittest.mock.MagicMock() func.__name__ = "" func.side_effect = [Exception(), True] return func @pytest.mark.parametrize("attempts, attempt", ( (0, 0), (1, 0), (1, 3), )) def test_exp_sleep_time_fails(attempts, attempt): with pytest.raises(ValueError): retryutils.exp_sleep_time(1, 10, attempts, attempt) def test_exp_sleep_time(): assert retryutils.exp_sleep_time(1, 10, 100, 1) == 1 assert retryutils.exp_sleep_time(1, 10, 100, 100) == 10 values = [ retryutils.exp_sleep_time(1, 10, 10, num) for num in range(1, 11)] for idx, less in enumerate(values, start=1): for more in values[idx:]: assert less <= more def test_simple_retry_ok(func_always_passed, func_pass_fail): for func in func_always_passed, func_pass_fail: retryutils.simple_retry()(func)() def test_simple_retry_fail(func_always_fails): with pytest.raises(Exception): retryutils.simple_retry()(func_always_fails)() def test_sleep_retry_ok_always(func_always_passed, no_sleep): retryutils.sleep_retry()(func_always_passed)() no_sleep.assert_not_called() def test_sleep_retry_ok_failed_once(func_pass_fail, no_sleep): retryutils.sleep_retry()(func_pass_fail)() assert len(no_sleep.mock_calls) == 1 def test_sleep_retry_fail(func_always_fails, no_sleep): with pytest.raises(Exception): retryutils.sleep_retry()(func_always_fails)() assert len(no_sleep.mock_calls) == 5 - 1 @pytest.mark.parametrize("exc", ( pymongo.errors.AutoReconnect, pymongo.errors.ConnectionFailure, pymongo.errors.ExecutionTimeout, pymongo.errors.CursorNotFound, pymongo.errors.ExceededMaxWaiters, pymongo.errors.NetworkTimeout, pymongo.errors.NotMasterError, pymongo.errors.ServerSelectionTimeoutError )) def test_mongo_retry_ok(exc, func_pass_fail, no_sleep): func_pass_fail.side_effect = [exc(""), True] retryutils.mongo_retry()(func_pass_fail)() @pytest.mark.parametrize("exc", ( pymongo.errors.PyMongoError, pymongo.errors.ConfigurationError, pymongo.errors.OperationFailure, pymongo.errors.WriteConcernError, pymongo.errors.WriteError, pymongo.errors.WTimeoutError, pymongo.errors.DuplicateKeyError, pymongo.errors.BulkWriteError, pymongo.errors.InvalidOperation, pymongo.errors.BSONError, pymongo.errors.InvalidName, pymongo.errors.InvalidURI, pymongo.errors.DocumentTooLarge )) def test_mongo_retry_fail(exc, func_pass_fail, no_sleep): func_pass_fail.side_effect = [exc(""), True] with pytest.raises(exc): retryutils.mongo_retry()(func_pass_fail)()

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# 파이썬은 '함수' 중심의 언어(모듈 중심). 모듈과 클래스는 별개 ## 클래스 생성 class Dog: # 클래스명은 대문자로 사용. ( ) 없이 :만 사용 ## 멤버 변수 # 변수선언 color = "" # 색 field = "" # 견종 ## 생성자 함수(init) (생성자는 함수? (o), 객체를 생성할 때 자동으로 호출되는 함수를 생성자라고 한다) def __init__(self): # 클래스안에 있는 생성자라는 표시로 변수명이 self 로 자동완성 됨 print("내가 마 생성자다 마. 내가 마 느그 객체 생성도 하고 마 그 때 호출도 하고 마 다했어 마.") ## 멤버 함수 def jump(self): print("강아지가 뛰고 있다.") def sleep(self): print("강아지가 자고 있다.") ## 출력용 함수(str) (자바의 toString() 역할) def __str__(self): # 이 클래스 내의 변수를 사용하기 위해 self.변수명 으로 사용 return self.color + ", " + self.field ## 객체 생성 dog1 = Dog() dog1.color = "빨간색" dog1.field = "토이푸들" print(dog1) dog1.jump() print("------------------------------------------------------") ## 객체 생성 dog2 = Dog() dog2.color = "까만색" dog2.field = "닥스훈트" print(dog2) dog2.sleep()

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# file /home/hep/ss4314/cmtuser/Gauss_v45r9/Gen/DecFiles/options/13102432.py generated: Fri, 27 Mar 2015 16:09:59 # # Event Type: 13102432 # # ASCII decay Descriptor: {[[B_s0]nos -> pi+ pi- (pi0 -> gamma gamma)]cc, [[B_s0]os -> pi- pi+ (pi0 -> gamma gamma)]cc} # from Configurables import Generation Generation().EventType = 13102432 Generation().SampleGenerationTool = "SignalRepeatedHadronization" from Configurables import SignalRepeatedHadronization Generation().addTool( SignalRepeatedHadronization ) Generation().SignalRepeatedHadronization.ProductionTool = "PythiaProduction" from Configurables import ToolSvc from Configurables import EvtGenDecay ToolSvc().addTool( EvtGenDecay ) ToolSvc().EvtGenDecay.UserDecayFile = "$DECFILESROOT/dkfiles/Bs_pi+pi-pi0=DecProdCut,sqDalitz.dec" Generation().SignalRepeatedHadronization.CutTool = "DaughtersInLHCb" Generation().SignalRepeatedHadronization.SignalPIDList = [ 531,-531 ] # Ad-hoc particle gun code from Configurables import ParticleGun pgun = ParticleGun("ParticleGun") pgun.SignalPdgCode = 531 pgun.DecayTool = "EvtGenDecay" pgun.GenCutTool = "DaughtersInLHCb" from Configurables import FlatNParticles pgun.NumberOfParticlesTool = "FlatNParticles" pgun.addTool( FlatNParticles , name = "FlatNParticles" ) from Configurables import MomentumSpectrum pgun.ParticleGunTool = "MomentumSpectrum" pgun.addTool( MomentumSpectrum , name = "MomentumSpectrum" ) pgun.MomentumSpectrum.PdgCodes = [ 531,-531 ] pgun.MomentumSpectrum.InputFile = "$PGUNSDATAROOT/data/Ebeam4000GeV/MomentumSpectrum_531.root" pgun.MomentumSpectrum.BinningVariables = "pteta" pgun.MomentumSpectrum.HistogramPath = "h_pteta" from Configurables import BeamSpotSmearVertex pgun.addTool(BeamSpotSmearVertex, name="BeamSpotSmearVertex") pgun.VertexSmearingTool = "BeamSpotSmearVertex" pgun.EventType = 13102432

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fabianfalon/drf-boilerplate

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"""User models admin.""" # Django from django.contrib import admin from django.contrib.auth.admin import UserAdmin # Models from .models import Profile, User class CustomUserAdmin(UserAdmin): """User model admin.""" list_display = ('email', 'username', 'first_name', 'last_name', 'is_staff',) @admin.register(Profile) class ProfileAdmin(admin.ModelAdmin): """Profile model admin.""" list_display = ('user', 'dni', 'address', 'publications_numbers', 'birthdate') search_fields = ('user__username', 'user__email', ) list_filter = ('dni',) admin.site.register(User, CustomUserAdmin)

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import json import os from bokeh.plotting import output_file, figure, save from bokeh.layouts import gridplot import src.utils.config as cfg def save_metrics(metrics: dict, save_loc: str): with open(os.path.join(save_loc, 'metrics.json'), 'w+') as f: json.dump(metrics, f, indent=2) output_file(os.path.join(save_loc, 'plt.html'), title=save_loc.split('/')[-1]) s_top = figure(width=720, height=360, title="Performance", x_axis_label='episodes', y_axis_label='reward') s_top.line(not_none(metrics['episodes'], metrics['rewards']), not_none(metrics['rewards']), legend_label="With Action Noise", line_color="orchid", line_width=3, line_alpha=0.66) s_top.line(not_none(metrics['episodes'], metrics['t_scores']), not_none(metrics['t_scores']), legend_label="Without Action Noise", line_color="royalblue", line_width=3, line_alpha=0.66) s_top.legend.location = "bottom_right" s_bot = figure(width=720, height=360, x_range=s_top.x_range, title="Loss Scores", x_axis_label="episode", y_axis_label='loss') s_bot.line(not_none(metrics['episodes'], metrics['o_loss']), not_none(metrics['o_loss']), legend_label="Observation Loss (MSE)", line_color="orchid", line_width=3, line_alpha=0.66) s_bot.line(not_none(metrics['episodes'], metrics['r_loss']), list(map(lambda x: x / cfg.action_repeat, not_none(metrics['r_loss']))), legend_label="Reward Loss (MSE)", line_color="royalblue", line_width=3, line_alpha=0.66) s_bot.line(not_none(metrics['episodes'], metrics['kl_loss']), list(map(lambda x: x / (1 + cfg.overshooting_kl_beta) - cfg.free_nats, not_none(metrics['kl_loss']))), legend_label="Complexity Loss (KL-divergence)", line_color="sienna", line_width=3, line_alpha=0.66) # s_bot.line(not_none(metrics['episodes'], metrics['p_loss']), # list(map(lambda x: x / cfg.action_repeat, not_none(metrics['p_loss']))), # legend_label="Policy Loss (MSE)", line_color="seagreen", line_width=3) p = gridplot([[s_top], [s_bot]]) save(p) pass def not_none(vlist, klist=None): if klist is None: return [x for x in vlist if x is not None] else: return [x for x, k in zip(vlist, klist) if k is not None]

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""" Ejercicio 3 =========== Escribir un programa que lea un archivo e imprima las letras en orden decreciente de frecuencia de aparición. El programa debería convertir toda la entrada a minúsculas y solo contar las letras a-z (excluir la "ñ"). No se debeen contar espacios, dígitos, signos de puntuación o cualquier otro carácter. Buscar textos en diferentes lenguas y ver cómo la frecuencia de las letras varían entre lenguajes. Comparar los resultados con las tablas que se puede encontrar en wikipedia.org/wiki/Letter_frequencies. """ import string try: fhandle = open(input("Introduzca el nombre del fichero: ")) except IOError: print("El fichero no existe") exit() full_string = fhandle.read() alphabet = dict() for letter in full_string: letter = letter.lower() if letter in string.ascii_lowercase: alphabet[letter] = alphabet.get(letter, 0) + 1 total = 0 ordered_list = [] for key, value in alphabet.items(): total += alphabet[key] ordered_list += [(value, key)] ordered_list.sort(reverse=True) for tupla in ordered_list: print("%s %.2f%%" % (tupla[1], tupla[0]*100/total))

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import re import datetime class NumericFunction(object): """ This is a class that provides a numeric function for version parts. It simply starts with the provided first_value (0 by default) and increases it following the sequence of integer numbers. The optional value of this function is equal to the first value. This function also supports alphanumeric parts, altering just the numeric part (e.g. 'r3' --> 'r4'). Only the first numeric group found in the part is considered (e.g. 'r3-001' --> 'r4-001'). """ FIRST_NUMERIC = re.compile('([^\d]*)(\d+)(.*)') def __init__(self, first_value=None): if first_value is not None: try: part_prefix, part_numeric, part_suffix = self.FIRST_NUMERIC.search( first_value).groups() except AttributeError: raise ValueError( "The given first value {} does not contain any digit".format(first_value)) else: first_value = 0 self.first_value = str(first_value) self.optional_value = self.first_value def bump(self, value): part_prefix, part_numeric, part_suffix = self.FIRST_NUMERIC.search( value).groups() bumped_numeric = int(part_numeric) + 1 return "".join([part_prefix, str(bumped_numeric), part_suffix]) class ValuesFunction(object): """ This is a class that provides a values list based function for version parts. It is initialized with a list of values and iterates through them when bumping the part. The default optional value of this function is equal to the first value, but may be otherwise specified. When trying to bump a part which has already the maximum value in the list you get a ValueError exception. """ def __init__(self, values, optional_value=None, first_value=None): if len(values) == 0: raise ValueError("Version part values cannot be empty") self._values = values if optional_value is None: optional_value = values[0] if optional_value not in values: raise ValueError("Optional value {0} must be included in values {1}".format( optional_value, values)) self.optional_value = optional_value if first_value is None: first_value = values[0] if first_value not in values: raise ValueError("First value {0} must be included in values {1}".format( first_value, values)) self.first_value = first_value def bump(self, value): try: return self._values[self._values.index(value)+1] except IndexError: raise ValueError( "The part has already the maximum value among {} and cannot be bumped.".format(self._values))

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from __future__ import absolute_import # Copyright (c) 2010-2017 openpyxl """ OOXML has non-standard escaping for characters < \031 """ import re def escape(value): r""" Convert ASCII < 31 to OOXML: \n == _x + hex(ord(\n)) +_ """ CHAR_REGEX = re.compile(r"[\001-\031]") def _sub(match): """ Callback to escape chars """ return "_x%04x_" % ord(match.group(0)) # py 2.6 return CHAR_REGEX.sub(_sub, value) def unescape(value): r""" Convert escaped strings to ASCIII: _x000a_ == \n """ ESCAPED_REGEX = re.compile("_x([0-9A-Fa-f]{4})_") def _sub(match): """ Callback to unescape chars """ return chr(int(match.group(1), 16)) if "_x" in value: value = ESCAPED_REGEX.sub(_sub, value) return value

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import random def oceni_pi(stevilo_poskusov): v_krogu = 0 for _ in range(stevilo_poskusov): x, y = random.random(), random.random() if x ** 2 + y ** 2 <= 1: v_krogu += 1 return 4 * v_krogu / stevilo_poskusov def oceni_eno_kocko(stevilo_poskusov): pogostosti = {} for _ in range(stevilo_poskusov): met = random.randint(1, 6) pogostosti[met] = pogostosti.get(met, 0) + 1 return {met: pogostost / stevilo_poskusov for met, pogostost in pogostosti.items()} def oceni_dve_kocki(stevilo_poskusov): pogostosti = {} for _ in range(stevilo_poskusov): met = random.randint(1, 6) + random.randint(1, 6) pogostosti[met] = pogostosti.get(met, 0) + 1 return {met: pogostost / stevilo_poskusov for met, pogostost in pogostosti.items()} def oceni_max_tri_kocke(stevilo_poskusov): pogostosti = {} for _ in range(stevilo_poskusov): met = max(random.randint(1, 6), random.randint(1, 6), random.randint(1, 6)) pogostosti[met] = pogostosti.get(met, 0) + 1 return {met: pogostost / stevilo_poskusov for met, pogostost in pogostosti.items()}

[ "matija@pretnar.info" ]

matija@pretnar.info

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/menu_sun_integration/infrastructure/pernod/translators/pernod_product_translator.py

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pfpacheco/menu-sun-api

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from menu_sun_api.domain.model.product.product import Product, ProductStatus from menu_sun_api.domain.model.seller.seller import Seller from menu_sun_integration.application.translators.interfaces.abstract_product_translator import \ AbstractProductTranslator from menu_sun_integration.infrastructure.pernod.presentations.product.pernod_product_get_request import \ PernodProductGetRequest from menu_sun_integration.infrastructure.pernod.presentations.product.pernod_product_response import \ PernodProductResponse from menu_sun_integration.presentations.interfaces.abstract_platform import AbstractPlatform from menu_sun_integration.presentations.interfaces.abstract_request import AbstractRequest class PernodProductTranslator(AbstractProductTranslator): def bind_product(self, product: PernodProductResponse) -> Product: status = ProductStatus.ENABLED if product.active else ProductStatus.DISABLED return Product(status=status, sku=product.sku, name=product.name, description=product.description, weight=product.weight, ean=product.ean, brand=product.brand, width=product.width, height=product.height, length=product.length) def to_seller_send_format(self, entity: AbstractPlatform) -> AbstractRequest: pass def to_seller_get_format(self, seller: Seller, **kwargs) -> PernodProductGetRequest: return PernodProductGetRequest() def to_domain_format(self, response: PernodProductResponse) -> [Product]: return self.bind_product(response)

[ "pfpacheco@gmail.com" ]

pfpacheco@gmail.com

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[]

no_license

Kazade/skivvy

9d41b0acc934e6059d60b386cc54a0638b14f7cc

41278fa66b559ee507862c729ad89028ccd5ae52

refs/heads/master

2016-09-11T04:41:31.998555

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py

import os import sys import argparse import json import re import tempfile import subprocess ENV_REGEX = r"(.+)\[(.+)\]" parser = argparse.ArgumentParser(description="underling task worker") parser.add_argument("--config", type=unicode, default="underling.json") parser.add_argument("--env", type=unicode, default="") parser.add_argument("--watch", type=bool, default=False) parser.add_argument("command", type=unicode) def locate_task(task_dirs, task_name): for task_dir in task_dirs: full_path = os.path.join(task_dir, task_name) if os.path.exists(full_path): return full_path return "" def expand_globs(inputs): pass def replace_constants(string, constants): for constant in constants: if isinstance(constants[constant], list): string = string.replace("{" + constant + "}", " ".join(constants[constant])) else: string = string.replace("{" + constant + "}", constants[constant]) return string def run_command(config, command, namespace=""): task_roots = config.get("__task_dirs__", []) constants = {} constants["PROJECT_ROOT"] = os.getcwd() new_constants = config.get("__constants__", {}) for const in new_constants: if isinstance(new_constants[const], list): new_constants[const] = [ replace_constants(x, constants) for x in new_constants[const] ] else: new_constants[const] = replace_constants(new_constants[const], constants) constants.update(new_constants) task_roots = [ replace_constants(x, constants) for x in task_roots ] commands = config.get("__commands__", {}) if command not in commands: print("Unrecognized command: %s" % command) print("Available commands: \n%s" % "\n\n".join(commands.keys())) sys.exit(1) for dependency in commands[command]: if dependency.startswith("file://"): print("Unhandled dependency type: %s" % dependency) sys.exit(1) dependency_name = dependency dependency = config.get(dependency_name) if not dependency: print("Unrecognized dependency: %s" % dependency_name) sys.exit(1) inputs = "" for task in dependency: if not isinstance(task, dict): print("Pipeline %s should be a list of tasks (dictionaries)" % dependency_name) task_name = task.get("task") has_env = re.match(ENV_REGEX, task_name) if has_env and not has_env.group(2).startswith(namespace): continue # Ignore tasks that don't have this namespace if has_env: task_name = has_env.group(1) inputs = replace_constants(task.get("input", ""), constants).split(" ") or inputs inputs = expand_globs(inputs) if inputs: constants["INPUT_FILES"] = inputs output_file = task.get("output") if not output_file: # No explicit output? Then generate a temporary file _, output_file = tempfile.mkstemp() task = locate_task(task_roots, task_name) if not task: print("Unable to find task: %s" % task_name) sys.exit(1) final_command = [ task, "--output=%s" % output_file ] for input_file in inputs: final_command.append("--input=%s" % input_file) print subprocess.check_output(final_command) inputs = output_file def load_config(config): with open(config, "r") as f: config = json.loads(f.read()) return config def main(): args = parser.parse_args() config = load_config(args.config) run_command(config, args.command) return 0 if __name__ == '__main__': sys.exit(main())

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kazade@gmail.com

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cash2one/xai

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refs/heads/master

2021-01-19T12:33:54.964379

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#calss header class _SULTANATES(): def __init__(self,): self.name = "SULTANATES" self.definitions = sultanate self.parents = [] self.childen = [] self.properties = [] self.jsondata = {} self.basic = ['sultanate']

[ "xingwang1991@gmail.com" ]

xingwang1991@gmail.com

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/tensorflow/python/distribute/multi_worker_continuous_run_test.py

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2020-09-06T21:00:35.848217

2019-11-08T18:03:54

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# Copyright 2019 The TensorFlow Authors. All Rights Reserved. # # 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. # ============================================================================== """Tests for continuous runs using cross-worker collective ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function import json import os from absl.testing import parameterized import numpy as np from tensorflow.python.distribute import collective_all_reduce_strategy from tensorflow.python.distribute import combinations from tensorflow.python.distribute import multi_process_runner from tensorflow.python.distribute import multi_process_runner_util from tensorflow.python.distribute import multi_worker_test_base as test_base from tensorflow.python.distribute import reduce_util from tensorflow.python.eager import context from tensorflow.python.eager import def_function from tensorflow.python.eager import test from tensorflow.python.framework import config from tensorflow.python.framework import ops from tensorflow.python.ops import array_ops # TODO(b/143286947): expand the test to cover fault tolerance and elasticity class MultiWorkerContinuousRunTest(test.TestCase, parameterized.TestCase): @combinations.generate(combinations.combine(mode=['eager'])) def testAllReduceContinuousRun(self, mode): num_workers = 5 tensor_shape = [2, 2] local_device = '/device:CPU:0' if config.list_physical_devices('GPU'): local_device = '/device:GPU:0' def worker_step_fn(): strategy = collective_all_reduce_strategy.CollectiveAllReduceStrategy() tf_config = json.loads(os.environ['TF_CONFIG']) worker_id = tf_config['task']['index'] @def_function.function def run_reduce(): with ops.device(local_device): t_in = array_ops.ones(tensor_shape) * worker_id return strategy.reduce(reduce_util.ReduceOp.MEAN, t_in, axis=None) t_out = run_reduce() # Element values from the workers are # 0, 1, ..., (num_workers - 1) expected_mean = (num_workers - 1) / 2 expected_out = np.ones(tensor_shape) * expected_mean self.assertAllClose(t_out, expected_out) def worker_fn(): gpus = config.list_physical_devices('GPU') if gpus: # Set virtual GPU with memory limit of 64MB so that multiple worker # processes can share the physical GPU config.set_logical_device_configuration( gpus[0], [context.LogicalDeviceConfiguration(64)]) for _ in range(100): worker_step_fn() # TODO(b/141948186): Remove this `with` block once b/141948186 is resolved. with multi_process_runner_util.try_run_and_except_connection_error(self): multi_process_runner.MultiProcessRunner().run( worker_fn, cluster_spec=test_base.create_cluster_spec(num_workers=num_workers)) if __name__ == '__main__': multi_process_runner.test_main()

[ "gardener@tensorflow.org" ]

gardener@tensorflow.org

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/Python_codes/p03363/s899204324.py

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Aasthaengg/IBMdataset

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2023-04-22T10:22:44.763102

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import bisect import math n = int(input()) a = list(map(int,input().split())) s = [0]*(n+1) for i,e in enumerate(a): s[i+1] = s[i] + e def comb(n,m): return math.factorial(n)//math.factorial(m)//math.factorial(n-m) ans = 0 s = sorted(s) l = 0 r = 0 #print(s) while l < n+1: while r < n+1 and s[l] == s[r]: #print(r,s[r]) r += 1 if r-l >= 2: ans += comb(r-l,2) l = r print(ans)

[ "66529651+Aastha2104@users.noreply.github.com" ]

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JingkaiTang/github-play

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2021-01-20T20:18:21.249162

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#! /usr/bin/env python def place_and_few_case(str_arg): go_next_thing_at_great_way(str_arg) print('old_work') def go_next_thing_at_great_way(str_arg): print(str_arg) if __name__ == '__main__': place_and_few_case('seem_point')

[ "jingkaitang@gmail.com" ]

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refs/heads/master

2020-07-16T18:00:05.756714

2019-09-01T22:58:39

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MIT

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import cv2 import numpy as np np.random.seed(0) # read image img = cv2.imread("imori_1.jpg") H, W, C = img.shape # Grayscale gray = 0.2126 * img[..., 2] + 0.7152 * img[..., 1] + 0.0722 * img[..., 0] gt = np.array((47, 41, 129, 103), dtype=np.float32) cv2.rectangle(img, (gt[0], gt[1]), (gt[2], gt[3]), (0,255,255), 1) def iou(a, b): area_a = (a[2] - a[0]) * (a[3] - a[1]) area_b = (b[2] - b[0]) * (b[3] - b[1]) iou_x1 = np.maximum(a[0], b[0]) iou_y1 = np.maximum(a[1], b[1]) iou_x2 = np.minimum(a[2], b[2]) iou_y2 = np.minimum(a[3], b[3]) iou_w = max(iou_x2 - iou_x1, 0) iou_h = max(iou_y2 - iou_y1, 0) area_iou = iou_w * iou_h iou = area_iou / (area_a + area_b - area_iou) return iou def hog(gray): h, w = gray.shape # Magnitude and gradient gray = np.pad(gray, (1, 1), 'edge') gx = gray[1:h+1, 2:] - gray[1:h+1, :w] gy = gray[2:, 1:w+1] - gray[:h, 1:w+1] gx[gx == 0] = 0.000001 mag = np.sqrt(gx ** 2 + gy ** 2) gra = np.arctan(gy / gx) gra[gra<0] = np.pi / 2 + gra[gra < 0] + np.pi / 2 # Gradient histogram gra_n = np.zeros_like(gra, dtype=np.int) d = np.pi / 9 for i in range(9): gra_n[np.where((gra >= d * i) & (gra <= d * (i+1)))] = i N = 8 HH = h // N HW = w // N Hist = np.zeros((HH, HW, 9), dtype=np.float32) for y in range(HH): for x in range(HW): for j in range(N): for i in range(N): Hist[y, x, gra_n[y*4+j, x*4+i]] += mag[y*4+j, x*4+i] ## Normalization C = 3 eps = 1 for y in range(HH): for x in range(HW): #for i in range(9): Hist[y, x] /= np.sqrt(np.sum(Hist[max(y-1,0):min(y+2, HH), max(x-1,0):min(x+2, HW)] ** 2) + eps) return Hist def resize(img, h, w): _h, _w = img.shape ah = 1. * h / _h aw = 1. * w / _w y = np.arange(h).repeat(w).reshape(w, -1) x = np.tile(np.arange(w), (h, 1)) y = (y / ah) x = (x / aw) ix = np.floor(x).astype(np.int32) iy = np.floor(y).astype(np.int32) ix = np.minimum(ix, _w-2) iy = np.minimum(iy, _h-2) dx = x - ix dy = y - iy out = (1-dx) * (1-dy) * img[iy, ix] + dx * (1 - dy) * img[iy, ix+1] + (1 - dx) * dy * img[iy+1, ix] + dx * dy * img[iy+1, ix+1] out[out>255] = 255 return out class NN: def __init__(self, ind=2, w=64, w2=64, outd=1, lr=0.1): self.w1 = np.random.normal(0, 1, [ind, w]) self.b1 = np.random.normal(0, 1, [w]) self.w2 = np.random.normal(0, 1, [w, w2]) self.b2 = np.random.normal(0, 1, [w2]) self.wout = np.random.normal(0, 1, [w2, outd]) self.bout = np.random.normal(0, 1, [outd]) self.lr = lr def forward(self, x): self.z1 = x self.z2 = sigmoid(np.dot(self.z1, self.w1) + self.b1) self.z3 = sigmoid(np.dot(self.z2, self.w2) + self.b2) self.out = sigmoid(np.dot(self.z3, self.wout) + self.bout) return self.out def train(self, x, t): # backpropagation output layer #En = t * np.log(self.out) + (1-t) * np.log(1-self.out) En = (self.out - t) * self.out * (1 - self.out) grad_wout = np.dot(self.z3.T, En) grad_bout = np.dot(np.ones([En.shape[0]]), En) self.wout -= self.lr * grad_wout self.bout -= self.lr * grad_bout # backpropagation inter layer grad_u2 = np.dot(En, self.wout.T) * self.z3 * (1 - self.z3) grad_w2 = np.dot(self.z2.T, grad_u2) grad_b2 = np.dot(np.ones([grad_u2.shape[0]]), grad_u2) self.w2 -= self.lr * grad_w2 self.b2 -= self.lr * grad_b2 grad_u1 = np.dot(grad_u2, self.w2.T) * self.z2 * (1 - self.z2) grad_w1 = np.dot(self.z1.T, grad_u1) grad_b1 = np.dot(np.ones([grad_u1.shape[0]]), grad_u1) self.w1 -= self.lr * grad_w1 self.b1 -= self.lr * grad_b1 def sigmoid(x): return 1. / (1. + np.exp(-x)) # crop and create database Crop_num = 200 L = 60 H_size = 32 F_n = ((H_size // 8) ** 2) * 9 db = np.zeros((Crop_num, F_n+1)) for i in range(Crop_num): x1 = np.random.randint(W-L) y1 = np.random.randint(H-L) x2 = x1 + L y2 = y1 + L crop = np.array((x1, y1, x2, y2)) _iou = iou(gt, crop) if _iou >= 0.5: cv2.rectangle(img, (x1, y1), (x2, y2), (0,0,255), 1) label = 1 else: cv2.rectangle(img, (x1, y1), (x2, y2), (255,0,0), 1) label = 0 crop_area = gray[y1:y2, x1:x2] crop_area = resize(crop_area, H_size, H_size) _hog = hog(crop_area) db[i, :F_n] = _hog.ravel() db[i, -1] = label ## train neural network nn = NN(ind=F_n, lr=0.01) for i in range(10000): nn.forward(db[:, :F_n]) nn.train(db[:, :F_n], db[:, -1][..., None]) # read detect target image img2 = cv2.imread("imori_many.jpg") H2, W2, C2 = img2.shape # Grayscale gray2 = 0.2126 * img2[..., 2] + 0.7152 * img2[..., 1] + 0.0722 * img2[..., 0] # [h, w] recs = np.array(((42, 42), (56, 56), (70, 70)), dtype=np.float32) detects = np.ndarray((0, 5), dtype=np.float32) # sliding window for y in range(0, H2, 4): for x in range(0, W2, 4): for rec in recs: dh = int(rec[0] // 2) dw = int(rec[1] // 2) x1 = max(x-dw, 0) x2 = min(x+dw, W2) y1 = max(y-dh, 0) y2 = min(y+dh, H2) region = gray2[max(y-dh,0):min(y+dh,H2), max(x-dw,0):min(x+dw,W2)] region = resize(region, H_size, H_size) region_hog = hog(region).ravel() score = nn.forward(region_hog) if score >= 0.7: cv2.rectangle(img2, (x1, y1), (x2, y2), (0,0,255), 1) detects = np.vstack((detects, np.array((x1, y1, x2, y2, score)))) print(detects) cv2.imwrite("out.jpg", img2) cv2.imshow("result", img2) cv2.waitKey(0)

[ "naga.yoshi.yoshi@gmail.com" ]

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ArietNyshanbaev/deputat

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# Импорт стандартных пакетов Django from django.contrib import admin # Импорт моделей из баззы данных from .models import Promis, PromisRank, Result, Comments class PromisAdmin(admin.ModelAdmin): """ Класс Регистрации Админки для Клеинтов """ list_display = ('title', 'person', 'date', 'is_approved') list_filter = ('date','is_approved') admin.site.register(Promis, PromisAdmin) class PromisRankAdmin(admin.ModelAdmin): """ Класс Регистрации Админки для Движимости """ list_display = ('promis', 'user') list_filter = ('promis',) admin.site.register(PromisRank, PromisRankAdmin) admin.site.register(Result) admin.site.register(Comments)

[ "ariet.nyshanbaev@iaau.edu.kg" ]

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AK-1121/code_extraction

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# How to Handle JSON with escaped Unicode characters using python json module? data = jsDat.get('data') data = data.encode('ascii', 'ignore')

[ "ubuntu@ip-172-31-7-228.us-west-2.compute.internal" ]

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/01-Supervised/17-neuralNetwork/day19/day19-1-neuralNetwork-2-MLPClassifier.py

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[]

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LeenonGo/sklearn-learn

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# -*- coding: utf-8 -*- # @Author : Lee # @Time : 2021/7/23 9:20 # @Function: https://www.scikitlearn.com.cn/0.21.3/18/#1172 # from sklearn.neural_network import MLPClassifier X = [[0., 0.], [1., 1.]] y = [0, 1] clf = MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1) clf.fit(X, y) print(clf.predict([[2., 2.], [-1., -2.]])) print([coef.shape for coef in clf.coefs_]) # clf.coefs_ 包含了构建模型的权值矩阵 # 目前， MLPClassifier 只支持交叉熵损失函数，通过运行 predict_proba 方法进行概率估计。 # 使用了通过反向传播计算得到的梯度和某种形式的梯度下降来进行训练 # 最小化交叉熵损失函数，为每个样本 x 给出一个向量形式的概率估计 P(y|x) print(clf.predict_proba([[2., 2.], [1., 2.]])) # [[1.96718015e-04 9.99803282e-01] # [1.96718015e-04 9.99803282e-01]] # 表示预测[2., 2.]为标签0的概率为1.96718015e-04，为标签1的概率为9.99803282e-01 # 此外，该模型支持多标签分类，一个样本可能属于多个类别。 # 对于每个类，原始输出经过 logistic 函数变换后，大于或等于 0.5 的值将进为 1，否则为 0。 # 对于样本的预测输出，值为 1 的索引位置表示该样本的分类类别 X = [[0., 0.], [1., 1.]] y = [[0, 1], [1, 1]] clf = MLPClassifier(solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(15,), random_state=1) clf.fit(X, y) print(clf.predict([[1., 2.]])) print(clf.predict([[0., 0.]]))

[ "yaa.lee@hotmail.com" ]

yaa.lee@hotmail.com

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''' 6. Jurnalul electronic al Anei conține, în fiecare zi, câte o frază cu informații despre cheltuielile pe care ea le-a efectuat în ziua respectivă. Scrieți un program care să citească o frază de acest tip din jurnalul Anei și apoi să afișeze suma totală cheltuită de ea în ziua respectivă. De exemplu, pentru fraza “Astăzi am cumpărat pâine de 5 RON, pe lapte am dat 10 RON, iar de 15 RON am cumpărat niște cașcaval. De asemenea, mi-am cumpărat și niște papuci cu 50 RON!”, programul trebuie să afișeze suma totală de 80 RON. Fraza se consideră corectă, adică toate numerele care apar în ea sunt numere naturale reprezentând sume cheltuite de Ana în ziua respectivă! ''' s = "Astăzi am cumpărat pâine de 5 RON, pe lapte am dat 10 RON, iar de 15 RON am cumpărat niște cașcaval. De asemenea, mi-am cumpărat și niște papuci cu 50 RON!" poz = s.find("RON") suma=0 for i in range(poz): while(not s[i:poz-1].isnumeric()): i += 1 # print(s[i:poz]) suma+=int(s[i:poz]) s = s[poz+3:] poz = s.find("RON") if(poz is -1): break print(suma)

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horjeacosmin@yahoo.com

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RuzhaK/PythonOOP

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2023-05-30T06:17:42.618984

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class Topic: def __init__(self,id, topic,storage_folder): self.id=id self.topic=topic self.storage_folder=storage_folder def edit(self,new_topic: str, new_storage_folder: str): self.topic=new_topic self.storage_folder=new_storage_folder def __repr__(self): return f"Topic {self.id}: {self.topic} in {self.storage_folder}"

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rkaraatanasova@gmail.com

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/app/email.py

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[]

no_license

kfinn6561/covid_map

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refs/heads/main

2023-03-24T19:54:35.251710

2021-03-23T10:18:23

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''' Created on 7 Jun 2020 @author: kieran ''' from flask_mail import Message from app import app,mail from threading import Thread def send_async_email(app,msg): with app.app_context(): mail.send(msg) def send_email(subject, sender, recipients, text_body, html_body): msg = Message(subject, sender=sender, recipients=recipients) msg.body = text_body msg.html = html_body Thread(target=send_async_email,args=(app,msg)).start()

[ "kieran.finn@hotmail.com" ]

kieran.finn@hotmail.com

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/register/tipmac.py

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Retenodus/Maiznet

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refs/heads/master

2021-01-24T00:02:49.168595

2012-06-25T23:13:02

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######################################################################## # vim: fileencoding=utf-8 ts=8 noexpandtab : # # ~~~~ Maiznet.fr ~~~~ # # -> register/tipmac.py # # # Copyright 2011 Grégoire Leroy <gregoire.leroy@retenodus.net> # Copyright 2011 Rémy Sanchez <remy.sanchez@hyperthese.net> # # This file is distributed under the terms of the WTFPL. For more # informations, see http://sam.zoy.org/wtfpl/COPYING ######################################################################## import socket import re from django.conf import settings def isMac(mac): """ Retourne True si la valeur est une adresse MAC, False sinon. """ X = '([a-fA-F0-9]{2}[:\-]){5}[a-fA-F0-9]{2}' # this is the regex if re.compile(X).search(mac): return True return False def ip_to_mac(ip): """ Effectue une requête auprès du serveur tipmac, et retourne la MAC correspondant à l'IP. Si la MAC est incorrecte, une exception est levée. Cette fonction dépend de paramètres à définir dans le settings.py : - **MAIZ_IP_GUEST**, la plage d'IP des invités. Si l'adresse n'est pas dans cette plage, la fonction retourne tout de suite une exception. À l'heure où ces lignes sont écrites, cette plage est 172.17.192.0/18. - **TIPMAC_SERVER**, l'adresse IP du serveur tipmac. - **TIPMAC_PORT**, le port du serveur. """ # Teste si l'adresse IP est un invité de Maiz import IPy if ip == None or IPy.IPint(settings.MAIZ_IP_GUEST).overlaps(ip) != 1: raise Exception("IP not in guest subnet") ip_server = settings.TIPMAC_SERVER port = settings.TIPMAC_PORT s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.settimeout(3) s.connect((ip_server,port)) s.send(ip) try : mac = s.recv(17) except : raise Exception("No data received") if not isMac(mac): raise Exception("Error : invalid MAC") s.close() return mac

[ "remy.sanchez@hyperthese.net" ]

remy.sanchez@hyperthese.net

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/pypureclient/flasharray/FA_2_23/models/network_interface_eth.py

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PureStorage-OpenConnect/py-pure-client

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2023-09-04T10:59:03.009972

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# coding: utf-8 """ FlashArray REST API No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) OpenAPI spec version: 2.23 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re import six import typing from ....properties import Property if typing.TYPE_CHECKING: from pypureclient.flasharray.FA_2_23 import models class NetworkInterfaceEth(object): """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'address': 'str', 'gateway': 'str', 'mac_address': 'str', 'mtu': 'int', 'netmask': 'str', 'subinterfaces': 'list[FixedReferenceNoId]', 'subnet': 'ReferenceNoId', 'subtype': 'str', 'vlan': 'int' } attribute_map = { 'address': 'address', 'gateway': 'gateway', 'mac_address': 'mac_address', 'mtu': 'mtu', 'netmask': 'netmask', 'subinterfaces': 'subinterfaces', 'subnet': 'subnet', 'subtype': 'subtype', 'vlan': 'vlan' } required_args = { } def __init__( self, address=None, # type: str gateway=None, # type: str mac_address=None, # type: str mtu=None, # type: int netmask=None, # type: str subinterfaces=None, # type: List[models.FixedReferenceNoId] subnet=None, # type: models.ReferenceNoId subtype=None, # type: str vlan=None, # type: int ): """ Keyword args: address (str): The IPv4 or IPv6 address to be associated with the specified network interface. gateway (str): The IPv4 or IPv6 address of the gateway through which the specified network interface is to communicate with the network. mac_address (str): The media access control address associated with the specified network interface. mtu (int): Maximum message transfer unit (packet) size for the network interface, in bytes. MTU setting cannot exceed the MTU of the corresponding physical interface. netmask (str): Netmask of the specified network interface that, when combined with the address of the interface, determines the network address of the interface. subinterfaces (list[FixedReferenceNoId]): List of network interfaces configured to be a subinterface of the specified network interface. subnet (ReferenceNoId): Subnet that is associated with the specified network interface. subtype (str): The subtype of the specified network interface. Only interfaces of subtype `virtual` can be created. Configurable on POST only. Valid values are `failover_bond`, `lacp_bond`, `physical`, and `virtual`. vlan (int): VLAN ID """ if address is not None: self.address = address if gateway is not None: self.gateway = gateway if mac_address is not None: self.mac_address = mac_address if mtu is not None: self.mtu = mtu if netmask is not None: self.netmask = netmask if subinterfaces is not None: self.subinterfaces = subinterfaces if subnet is not None: self.subnet = subnet if subtype is not None: self.subtype = subtype if vlan is not None: self.vlan = vlan def __setattr__(self, key, value): if key not in self.attribute_map: raise KeyError("Invalid key `{}` for `NetworkInterfaceEth`".format(key)) self.__dict__[key] = value def __getattribute__(self, item): value = object.__getattribute__(self, item) if isinstance(value, Property): raise AttributeError else: return value def __getitem__(self, key): if key not in self.attribute_map: raise KeyError("Invalid key `{}` for `NetworkInterfaceEth`".format(key)) return object.__getattribute__(self, key) def __setitem__(self, key, value): if key not in self.attribute_map: raise KeyError("Invalid key `{}` for `NetworkInterfaceEth`".format(key)) object.__setattr__(self, key, value) def __delitem__(self, key): if key not in self.attribute_map: raise KeyError("Invalid key `{}` for `NetworkInterfaceEth`".format(key)) object.__delattr__(self, key) def keys(self): return self.attribute_map.keys() def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): if hasattr(self, attr): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value if issubclass(NetworkInterfaceEth, dict): for key, value in self.items(): result[key] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, NetworkInterfaceEth): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

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/backup/user_242/ch16_2020_03_23_19_51_17_162358.py

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[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

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2023-01-31T17:19:42.050628

2020-12-16T05:21:31

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v = float(input('Qual o valor da conta?:')) def valor_da_conta(v): resultado = v * 1.1 return resultado print('Valor da conta com 10%: R$ {0:.2f}'.format(valor_da_conta(v)))

[ "you@example.com" ]

you@example.com

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/testing/scripts/.svn/text-base/xclean_unit_tests.py.svn-base

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[]

no_license

brynmathias/AnalysisV2

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ee17c019bb04243876a51c7ef7719cc58a52adea

refs/heads/master

2021-01-01T19:20:27.277628

2012-04-17T13:34:26

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#!/usr/bin/env python import setupSUSY import unittest #import xclean.clonevector_tests #import xclean.basic_tests if __name__ == '__main__': testcases=["xclean.clonevector_tests.TestCloneVector", "xclean.basic_tests.TestBasic"] suite = unittest.TestLoader().loadTestsFromNames(testcases) print "="*50 print "Cross Cleaner Unit Tests" print "="*50 unittest.TextTestRunner(verbosity=2).run(suite)

[ "brynmathias@gmail.com" ]

brynmathias@gmail.com

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/visual_dynamics/envs/env_spec.py

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[ "MIT" ]

permissive

saadmahboob/visual_dynamics

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90227bb0d0aebb1989117b5c25ca311655ca7cc7

refs/heads/master

2021-06-17T05:50:22.661375

2017-05-12T02:53:47

null

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null

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from visual_dynamics.spaces.base import Space from visual_dynamics.utils.config import ConfigObject class EnvSpec(ConfigObject): def __init__(self, action_space, observation_space): self._action_space = action_space self._observation_space = observation_space @property def observation_space(self): return self._observation_space @property def action_space(self): return self._action_space def _get_config(self): config = super(EnvSpec, self)._get_config() action_space = self.action_space if not isinstance(action_space, ConfigObject): action_space = Space.create(action_space) observation_space = self.observation_space if not isinstance(observation_space, ConfigObject): observation_space = Space.create(observation_space) config.update({'action_space': action_space, 'observation_space': observation_space}) return config

[ "alexleegk@gmail.com" ]

alexleegk@gmail.com

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/USBApplication/tasks/serial_task.py

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[]

no_license

bxm156/EECS398

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refs/heads/master

2021-01-01T05:36:00.159758

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from base_task import BaseTask class SerialTask(BaseTask): def set_parameters(self, param_dict): self.parameters = param_dict

[ "bxm156@case.edu" ]

bxm156@case.edu

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/wiki/middleware.py

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[]

no_license

xuguangzong/WIKI

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refs/heads/main

2023-06-26T15:29:55.675667

2021-07-23T08:39:50

386,569,512

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import time import logging from wiki.documents import ELASTICSEARCH_ENABLED, ElaspedTimeDocumentManager logger = logging.getLogger(__name__) class OnlineMiddleware(object): def __init__(self, get_response=None): self.get_response = get_response super().__init__() def __call__(self, request): """ page render time :param request: :return: """ start_time = time.time() response = self.get_response(request) http_user_agent = request.META.get('HTTP_USER_AGENT', '') if 'spider'.upper() not in http_user_agent.upper(): try: cast_time = time.time() - start_time if ELASTICSEARCH_ENABLED: time_taken = round((cast_time) * 1000, 2) url = request.path from django.utils import timezone ElaspedTimeDocumentManager.create( url=url, time_taken=time_taken, log_datetime=timezone.now(), type='wiki', useragent=http_user_agent) response.content = response.content.replace( b'<!!LOAD_TIMES!!>', str.encode(str(cast_time)[:5])) except Exception as e: logger.error("Error OnlineMiddleware: %s" % e) return response

[ "2359301733@qq.com" ]

2359301733@qq.com

d7a1d6e57acc930c4bd99451bd5df4c5e3bc6cfe

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/examples/bScript.py

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[]

no_license

chonlei/SanPy

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refs/heads/master

2023-07-11T03:46:37.249897

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import sys sys.path.append("..") # Adds higher directory to python modules path. import matplotlib matplotlib.use("TkAgg") import matplotlib.pyplot as plt from sanpy import bAnalysis # open an abf file into a bAnalysis object myFile = '../data/19114001.abf' ba = bAnalysis.bAnalysis(myFile) # detect spikes myThreshold = 100 myMedianFilter = 3 halfHeights = [20, 50, 80] ba.spikeDetect(dVthresholdPos=myThreshold, medianFilter=myMedianFilter, halfHeights=halfHeights) # ba now has a number of spikes, they are all in a list called ba.spikeDict print('number of spikes detected:', len(ba.spikeDict)) # each spike in the list is a python dictionary # lets look at one spike mySpikeNumber= 5 print(ba.spikeDict[mySpikeNumber]) # each spike has a number of keys (e.g. the name of the stat) and for each of those a 'value' for key,value in ba.spikeDict[mySpikeNumber].items(): print(key, value) for spike in ba.spikeDict: print(spike['thresholdVal']) # plot spike threshold (mV) versus spike time (seconds)

[ "robert.cudmore@gmail.com" ]

robert.cudmore@gmail.com

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/clay/helpers.py

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devildeveloper/Clay

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2021-01-18T02:27:22.094481

2013-11-18T20:24:02

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# -*- coding: utf-8 -*- from datetime import datetime import errno from fnmatch import fnmatch import io import os import shutil import unicodedata def to_unicode(txt, encoding='utf8'): if not isinstance(txt, basestring): txt = str(txt) if isinstance(txt, unicode): return txt return unicode(txt, encoding) def unormalize(text, form='NFD'): return unicodedata.normalize(form, text) def fullmatch(path, pattern): path = unormalize(path) name = os.path.basename(path) return fnmatch(name, pattern) or fnmatch(path, pattern) def read_content(path, **kwargs): kwargs.setdefault('mode', 'rt') with io.open(path, **kwargs) as f: return f.read() def make_dirs(*lpath): path = os.path.join(*lpath) try: os.makedirs(path) except OSError as e: if e.errno != errno.EEXIST: raise return path def create_file(path, content, encoding='utf8'): if not isinstance(content, unicode): content = unicode(content, encoding) with io.open(path, 'w+t', encoding=encoding) as f: f.write(content) def copy_if_updated(path_in, path_out): if os.path.exists(path_out): newt = os.path.getmtime(path_in) currt = os.path.getmtime(path_out) if currt >= newt: return shutil.copy2(path_in, path_out) def get_updated_datetime(path): ut = os.path.getmtime(path) return datetime.fromtimestamp(ut) def sort_paths_dirs_last(paths): def dirs_last(a, b): return cmp(a[0].count('/'), b[0].count('/')) or cmp(a[0], b[0]) return sorted(paths, cmp=dirs_last)

[ "juanpablo@lucumalabs.com" ]

juanpablo@lucumalabs.com

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/chapter04/demo_4.4.py

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#!/usr/bin/python2.7 # -*- coding:utf-8 -*- # Author: NetworkRanger # Date: 2018/11/5 下午10:44 # 4.4 TensorFlow上核函数的使用 # 1. 导入必要编程库，创建一个计算图会话 import matplotlib.pyplot as plt import numpy as np import tensorflow as tf from sklearn import datasets sess = tf.Session() # 2. 生成模拟数。生成的数据是一两个同心圆数据，每个不同的环代表不同的类，确保只有类-1或者1。为了让绘图方便，这里将每类数据分成x值和y值 (x_vals, y_vals) = datasets.make_circles(n_samples=500, factor=.5, noise=.1) y_vals = np.array([1 if y==1 else -1 for y in y_vals]) class1_x = [x[0] for i,x in enumerate(x_vals) if y_vals[i] == 1] class1_y = [x[1] for i,x in enumerate(x_vals) if y_vals[i] == 1] class2_x = [x[0] for i,x in enumerate(x_vals) if y_vals[i] == -1] class2_y = [x[1] for i,x in enumerate(x_vals) if y_vals[i] == -1] # 3. 声明批量大小、占位符，创建模型变量b。对于SVM算法，为了让每次迭代训练不波动，得到一个稳定的训练模型，这时批量大小得取更大。注意，本例为预测数据点声明有额外的占位符。最后创建彩色的网格来可视化不同的区域代表不同的类别 batch_size = 250 x_data = tf.placeholder(shape=[None, 2], dtype=tf.float32) y_target = tf.placeholder(shape=[None, 1], dtype=tf.float32) prediction_grid = tf.placeholder(shape=[None, 2], dtype=tf.float32) b = tf.Variable(tf.random_normal(shape=[1, batch_size])) # 4. 创建高斯核函数。该核函数用矩阵操作来表示 gamma = tf.constant(-50.0) dist = tf.reduce_mean(tf.square(x_data), 1) dist = tf.reshape(dist, [-1, 1]) sq_dists = tf.add(tf.subtract(dist, tf.multiply(2., tf.matmul(x_data, tf.transpose(x_data)))), tf.transpose(dist)) my_kernel = tf.exp(tf.multiply(gamma, tf.abs(sq_dists))) """ 注意，在sq_dists中应用广播加法和减法操作。线性核函数可以表示为: my_kernel = tf.matmul(x_data, tf.transpose(x_data))。 """ # 5. 声明对偶问题。为了最大化，这里采用最小化损失函数的负数: tf.negative() model_output = tf.matmul(b, my_kernel) first_term = tf.reduce_mean(b) b_vec_cross = tf.matmul(tf.transpose(b), b) y_target_cross = tf.matmul(y_target, tf.transpose(y_target)) second_term = tf.reduce_mean(tf.multiply(my_kernel, tf.multiply(b_vec_cross, y_target_cross))) loss = tf.negative(tf.subtract(first_term, second_term)) # 6. 创建预测函数和准确度函数。先创建一个预测核函数，但用预测数据点的核函数用模拟数据点的核函数。预测值是模型输出的符号函数值 rA = tf.reshape(tf.reduce_sum(tf.square(x_data), 1), [-1, 1]) rB = tf.reshape(tf.reduce_sum(tf.square(prediction_grid), 1), [-1, 1]) pred_sq_dist = tf.add(tf.subtract(rA, tf.multiply(2., tf.matmul(x_data, tf.transpose(prediction_grid)))), tf.transpose(rB)) pred_kernel = tf.exp(tf.multiply(gamma, tf.abs(pred_sq_dist))) prediction_output = tf.matmul(tf.multiply(tf.transpose(y_target), b), pred_kernel) prediction = tf.sign(prediction_output-tf.reduce_mean(prediction_output)) accuracy = tf.reduce_mean(tf.cast(tf.equal(tf.squeeze(prediction), tf.squeeze(y_target)), tf.float32)) """ 为了实现线性预测核函数，将预测核函数改为: pred_kernel = tf.matmul(x_data, tf.transpose(prediction_grid))。 """ # 7. 创建优化器函数，初始化所有的变量 my_opt = tf.train.GradientDescentOptimizer(0.001) train_step = my_opt.minimize(loss) init = tf.initialize_all_variables() sess.run(init) # 8. 开始迭代训练 loss_vec = [] batch_accuracy = [] for i in range(500): rand_index = np.random.choice(len(x_vals), size=batch_size) rand_x = x_vals[rand_index] rand_y = np.transpose([y_vals[rand_index]]) sess.run(train_step, feed_dict={x_data: rand_x, y_target: rand_y}) temp_loss = sess.run(loss, feed_dict={x_data: rand_x, y_target: rand_y}) loss_vec.append(temp_loss) acc_temp = sess.run(accuracy, feed_dict={x_data: rand_x, y_target: rand_y, prediction_grid: rand_x}) batch_accuracy.append(acc_temp) if (i+1) % 100 == 0: print('Step #' + str(i+1)) print('Loss = ' + str(temp_loss)) # 9. 输出结果如下 """ Step #100 Loss = -0.040872738 Step #200 Loss = -0.04066868 Step #300 Loss = -0.04294016 Step #400 Loss = -0.042239938 Step #500 Loss = -0.043024104 """ # 10. 为了能够在整个数据空间可视化分类返回结果，我们将创建预测数据点的网格，在其上进行预测 x_min, x_max = x_vals[:, 0].min() - 1, x_vals[:, 0].max() + 1 y_min, y_max = x_vals[:, 1].min() - 1, x_vals[:, 1].max() + 1 xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.02), np.arange(y_min, y_max, 0.02)) grid_points = np.c_[xx.ravel(), yy.ravel()] [grid_prediction] = sess.run(prediction, feed_dict={x_data: rand_x, y_target: rand_y, prediction_grid: grid_points}) grid_prediction = grid_prediction.reshape(xx.shape) # 11. 下面绘制预测结果、批量准确度和损失函数 plt.contourf(xx, yy, grid_prediction, cmap=plt.cm.Paired, alpha=0.8) plt.plot(class1_x, class1_y, 'ro', label='Class 1') plt.plot(class2_x, class2_y, 'kx', label='Class -1') plt.legend(loc='lower right') plt.ylim([-1.5, 1.5]) plt.xlim([-1.5, 1.5]) plt.show() plt.plot(batch_accuracy, 'k-', label='Accuracy') plt.title('Batch Accuracy') plt.xlabel('Generation') plt.ylabel('Accuracy') plt.legend(loc='lower right') plt.show() plt.plot(loss_vec, 'k-') plt.title('Loss per Generation') plt.xlabel('Generation') plt.ylabel('Loss') plt.show() # 12. 简单扼要，这里只显示训练结果图，不过也可以分开运行绘图代码展示其他效果

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# -*- coding: utf-8 -*- # For copyright and license notices, see __manifest__.py file in module root from docker_odoo_env.messages import Msg msg = Msg() class Command(object): def __init__(self, config): self._config = config def execute(self): raise NotImplementedError def show_doc(self): msg.text(self._config.args.get('command')) exit()

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# 주말과제 # dense 모델로 구성 input_shape=(28*28, ) # 인공지능계의 hello world라 불리는 mnist!!! import numpy as np import matplotlib.pyplot as plt # 1. 데이터 from tensorflow.keras.datasets import mnist (x_train, y_train), (x_test, y_test) = mnist.load_data() print(x_train.shape, y_train.shape) # (60000, 28, 28) (60000,) print(x_test.shape, y_test.shape) # (10000, 28, 28) (10000,) print(x_train[0]) print("y_train[0] : ", y_train[0]) print(x_train[0].shape) # (28, 28) # plt.imshow(x_train[0], 'gray') # plt.imshow(x_train[0]) # plt.show() x_train = x_train.reshape(60000, 28*28) x_test = x_test.reshape(10000, 28*28) # (x_test.reshape(x_test.shape[0], x_test.shape[1], x_test.shape[2], 1)) print(x_train.shape, x_test.shape) # (60000, 784) (10000, 784) # OnHotEncoding # 여러분이 하시오!!!!! from tensorflow.keras.utils import to_categorical y_train = to_categorical(y_train) y_test = to_categorical(y_test) print(y_train.shape) # (60000, 10) print(y_test.shape) # (10000, 10) # 2. 모델 구성 from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense model = Sequential() model.add(Dense(200, activation='relu', input_shape=(784,))) model.add(Dense(200, activation='relu')) model.add(Dense(200, activation='relu')) model.add(Dense(200, activation='relu')) model.add(Dense(200, activation='relu')) model.add(Dense(200, activation='relu')) model.add(Dense(10, activation='softmax')) # 실습!! 완성하시오!!! # 지표는 acc /// 0.985 이상 # 응용 # y_test 10개와 y_pred 10개를 출력하시오 # y_test[:10] = (?,?,?,?,?,?,?,?,?,?,?) # y_pred[:10] = (?,?,?,?,?,?,?,?,?,?,?) # 3. 컴파일 훈련 model.compile(loss='mse', optimizer='adam', metrics=['acc']) from tensorflow.keras.callbacks import EarlyStopping es = EarlyStopping(monitor='loss', patience=30, mode='auto') model.fit(x_train, y_train, epochs=2000, validation_split=0.2, batch_size=2000, callbacks=[es]) # 4. 평가, 예측 loss, acc = model.evaluate(x_test, y_test, batch_size=1) print("loss : ", loss) print("acc : ", acc) y_test = np.array(model.predict(x_train[:1])) print(y_test[:10]) print("============") y_pred = np.array(model.predict(x_test[:1])) print(y_pred[:10]) # keras40_mnist2_cnn # loss : 0.00260396976955235 # acc : 0.9854999780654907 # [[8.6690171e-08 2.8707976e-08 9.1137373e-09 9.6521189e-06 4.6547077e-09 # 9.9998856e-01 7.6187533e-08 5.5741470e-08 1.3864026e-06 2.0224462e-07]] # ============ # [[7.0327958e-30 2.2413428e-23 6.9391834e-21 9.2217209e-22 5.1841172e-22 # 8.7506048e-26 2.4799229e-27 1.0000000e+00 8.0364114e-26 3.3208760e-17]] # keras40_mnist3_dnn # loss : 0.005172424484044313 # acc : 0.9724000096321106 # [[9.4863184e-15 2.2668929e-19 1.8625454e-22 5.9676188e-07 2.5733180e-25 # 9.9999940e-01 1.5588427e-20 7.8994310e-23 5.6835017e-22 2.6443269e-20]] # ============ # [[3.0520350e-26 2.7246760e-23 4.5444517e-25 3.6449811e-28 1.3460386e-28 # 2.1042897e-27 6.9805158e-30 1.0000000e+00 1.8761058e-26 2.6409651e-25]]

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import _plotly_utils.basevalidators class TicksuffixValidator(_plotly_utils.basevalidators.StringValidator): def __init__( self, plotly_name="ticksuffix", parent_name="scattermapbox.marker.colorbar", **kwargs ): super(TicksuffixValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, edit_type=kwargs.pop("edit_type", "calc"), **kwargs )

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Parshwa-P3/ThePythonWorkbook-Solutions

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# Ch5Ex113.py # Author: Parshwa Patil # ThePythonWorkbook Solutions # Exercise No. 113 # Title: Formatting a List from Ch5Ex107 import inputWordList def formatWordList(words): if len(words) == 1: return str(words[0]) elif len(words) == 2: return str(words[0]) + " and " + str(words[1]) elif len(words) >= 3: res = "" for w in words[:-2]: res += str(w) + ", " res += formatWordList(words[-2:]) return res else: return "" def main(): words = inputWordList() res = formatWordList(words) print(res) if __name__ == "__main__": main()

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dougvanhorn/bots-grammars

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from bots.botsconfig import * from records004040 import recorddefs syntax = { 'version' : '00403', #version of ISA to send 'functionalgroup' : 'TP', } structure = [ {ID: 'ST', MIN: 1, MAX: 1, LEVEL: [ {ID: 'REN', MIN: 1, MAX: 1}, {ID: 'DK', MIN: 1, MAX: 1}, {ID: 'PI', MIN: 1, MAX: 8}, {ID: 'PR', MIN: 0, MAX: 200}, {ID: 'SS', MIN: 0, MAX: 1}, {ID: 'SA', MIN: 1, MAX: 1}, {ID: 'CD', MIN: 0, MAX: 150}, {ID: 'GY', MIN: 0, MAX: 150}, {ID: 'RAB', MIN: 0, MAX: 12}, {ID: 'PT', MIN: 0, MAX: 50}, {ID: 'LX', MIN: 0, MAX: 1, LEVEL: [ {ID: 'N4', MIN: 0, MAX: 1}, {ID: 'PI', MIN: 0, MAX: 15}, ]}, {ID: 'R9', MIN: 0, MAX: 10, LEVEL: [ {ID: 'R2B', MIN: 0, MAX: 10, LEVEL: [ {ID: 'R2C', MIN: 0, MAX: 10}, ]}, ]}, {ID: 'SCL', MIN: 0, MAX: 999, LEVEL: [ {ID: 'RD', MIN: 0, MAX: 6}, ]}, {ID: 'SE', MIN: 1, MAX: 1}, ]} ]

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AdamZhouSE/pythonHomework

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import math size = int(input()) tempList = input().split() intList = [] for var in tempList: intList.append(int(var)) d = {} for var in intList: if var in d.keys(): d[var] += 1 else: d[var] = 1 l = sorted(d.keys()) realD = {} for i in l: realD[i] = d[i] result = 0 resultD = {} resultD[1] = 0 resultD[2] = 0 resultD[3] = 0 for key, value in realD.items(): if key == 4: result += value if key == 2: result += value // 2 resultD[2] = value % 2 if key == 3 or key == 1: resultD[key] = value result += resultD[3] resultD[1] = resultD[1] - resultD[3] if resultD[1] <= 0: if resultD[2] == 1: result += 1 else: if resultD[2] == 1: resultD[1] -= 2 result += 1 if resultD[1] > 0: result += math.ceil(resultD[1] / 4) print(result)

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terrifyzhao/educative

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def search_rotated_with_duplicates(arr, key): start, end = 0, len(arr) - 1 while start <= end: mid = start + (end - start) // 2 if arr[mid] == key: return mid # the only difference from the previous solution, # if numbers at indexes start, mid, and end are same, we can't choose a side # the best we can do, is to skip one number from both ends as key != arr[mid] if arr[start] == arr[mid] and arr[end] == arr[mid]: start += 1 end -= 1 elif arr[start] <= arr[mid]: # left side is sorted in ascending order if key >= arr[start] and key < arr[mid]: end = mid - 1 else: # key > arr[mid] start = mid + 1 else: # right side is sorted in ascending order if key > arr[mid] and key <= arr[end]: start = mid + 1 else: end = mid - 1 # we are not able to find the element in the given array return -1 def search_rotated_with_duplicates2(arr, key): start, end = 0, len(arr) - 1 while start <= end: mid = start + (end - start) // 2 if arr[mid] == key: return mid while arr[start] == arr[mid] == arr[end]: start += 1 end -= 1 if arr[start] <= arr[mid]: if arr[start] <= key < arr[mid]: end = mid - 1 else: start = mid else: if arr[mid] < key <= arr[end]: start = mid + 1 else: end = mid return -1 def main(): print(search_rotated_with_duplicates([3, 7, 3, 3, 3], 7)) main()

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#!/usr/bin/env python # Python 2/3 compatibility from __future__ import print_function import sys PY3 = sys.version_info[0] == 3 if PY3: xrange = range import numpy as np import cv2 as cv from numpy import random def make_gaussians(cluster_n, img_size): points = [] ref_distrs = [] for _i in range(cluster_n): mean = (0.1 + 0.8*random.rand(2)) * img_size a = (random.rand(2, 2)-0.5)*img_size*0.1 cov = np.dot(a.T, a) + img_size*0.05*np.eye(2) n = 100 + random.randint(900) pts = random.multivariate_normal(mean, cov, n) points.append( pts ) ref_distrs.append( (mean, cov) ) points = np.float32( np.vstack(points) ) return points, ref_distrs def draw_gaussain(img, mean, cov, color): x, y = np.int32(mean) w, u, _vt = cv.SVDecomp(cov) ang = np.arctan2(u[1, 0], u[0, 0])*(180/np.pi) s1, s2 = np.sqrt(w)*3.0 cv.ellipse(img, (x, y), (s1, s2), ang, 0, 360, color, 1, cv.LINE_AA) def main(): cluster_n = 5 img_size = 512 print('press any key to update distributions, ESC - exit\n') while True: print('sampling distributions...') points, ref_distrs = make_gaussians(cluster_n, img_size) print('EM (opencv) ...') em = cv.ml.EM_create() em.setClustersNumber(cluster_n) em.setCovarianceMatrixType(cv.ml.EM_COV_MAT_GENERIC) em.trainEM(points) means = em.getMeans() covs = em.getCovs() # Known bug: https://github.com/opencv/opencv/pull/4232 found_distrs = zip(means, covs) print('ready!\n') img = np.zeros((img_size, img_size, 3), np.uint8) for x, y in np.int32(points): cv.circle(img, (x, y), 1, (255, 255, 255), -1) for m, cov in ref_distrs: draw_gaussain(img, m, cov, (0, 255, 0)) for m, cov in found_distrs: draw_gaussain(img, m, cov, (0, 0, 255)) cv.imshow('gaussian mixture', img) ch = cv.waitKey(0) if ch == 27: break print('Done') if __name__ == '__main__': print(__doc__) main() cv.destroyAllWindows()

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EthanW1215/home-assistant

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refs/heads/master

2020-09-05T09:02:59.513681

2019-11-05T18:57:08

220,050,094

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Apache-2.0

2019-11-06T17:13:33

2019-11-06T17:13:32

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UTF-8

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py

"""Helper to check the configuration file.""" from collections import OrderedDict, namedtuple from typing import List import attr import voluptuous as vol from homeassistant import loader from homeassistant.core import HomeAssistant from homeassistant.config import ( CONF_CORE, CORE_CONFIG_SCHEMA, CONF_PACKAGES, merge_packages_config, _format_config_error, find_config_file, load_yaml_config_file, extract_domain_configs, config_per_platform, ) from homeassistant.requirements import ( async_get_integration_with_requirements, RequirementsNotFound, ) import homeassistant.util.yaml.loader as yaml_loader from homeassistant.exceptions import HomeAssistantError # mypy: allow-untyped-calls, allow-untyped-defs, no-warn-return-any CheckConfigError = namedtuple("CheckConfigError", "message domain config") @attr.s class HomeAssistantConfig(OrderedDict): """Configuration result with errors attribute.""" errors: List[CheckConfigError] = attr.ib(default=attr.Factory(list)) def add_error(self, message, domain=None, config=None): """Add a single error.""" self.errors.append(CheckConfigError(str(message), domain, config)) return self @property def error_str(self) -> str: """Return errors as a string.""" return "\n".join([err.message for err in self.errors]) async def async_check_ha_config_file(hass: HomeAssistant) -> HomeAssistantConfig: """Load and check if Home Assistant configuration file is valid. This method is a coroutine. """ config_dir = hass.config.config_dir result = HomeAssistantConfig() def _pack_error(package, component, config, message): """Handle errors from packages: _log_pkg_error.""" message = "Package {} setup failed. Component {} {}".format( package, component, message ) domain = f"homeassistant.packages.{package}.{component}" pack_config = core_config[CONF_PACKAGES].get(package, config) result.add_error(message, domain, pack_config) def _comp_error(ex, domain, config): """Handle errors from components: async_log_exception.""" result.add_error(_format_config_error(ex, domain, config), domain, config) # Load configuration.yaml try: config_path = await hass.async_add_executor_job(find_config_file, config_dir) if not config_path: return result.add_error("File configuration.yaml not found.") config = await hass.async_add_executor_job(load_yaml_config_file, config_path) except FileNotFoundError: return result.add_error(f"File not found: {config_path}") except HomeAssistantError as err: return result.add_error(f"Error loading {config_path}: {err}") finally: yaml_loader.clear_secret_cache() # Extract and validate core [homeassistant] config try: core_config = config.pop(CONF_CORE, {}) core_config = CORE_CONFIG_SCHEMA(core_config) result[CONF_CORE] = core_config except vol.Invalid as err: result.add_error(err, CONF_CORE, core_config) core_config = {} # Merge packages await merge_packages_config( hass, config, core_config.get(CONF_PACKAGES, {}), _pack_error ) core_config.pop(CONF_PACKAGES, None) # Filter out repeating config sections components = set(key.split(" ")[0] for key in config.keys()) # Process and validate config for domain in components: try: integration = await async_get_integration_with_requirements(hass, domain) except (RequirementsNotFound, loader.IntegrationNotFound) as ex: result.add_error(f"Component error: {domain} - {ex}") continue try: component = integration.get_component() except ImportError as ex: result.add_error(f"Component error: {domain} - {ex}") continue config_schema = getattr(component, "CONFIG_SCHEMA", None) if config_schema is not None: try: config = config_schema(config) result[domain] = config[domain] except vol.Invalid as ex: _comp_error(ex, domain, config) continue component_platform_schema = getattr( component, "PLATFORM_SCHEMA_BASE", getattr(component, "PLATFORM_SCHEMA", None), ) if component_platform_schema is None: continue platforms = [] for p_name, p_config in config_per_platform(config, domain): # Validate component specific platform schema try: p_validated = component_platform_schema(p_config) except vol.Invalid as ex: _comp_error(ex, domain, config) continue # Not all platform components follow same pattern for platforms # So if p_name is None we are not going to validate platform # (the automation component is one of them) if p_name is None: platforms.append(p_validated) continue try: p_integration = await async_get_integration_with_requirements( hass, p_name ) platform = p_integration.get_platform(domain) except ( loader.IntegrationNotFound, RequirementsNotFound, ImportError, ) as ex: result.add_error(f"Platform error {domain}.{p_name} - {ex}") continue # Validate platform specific schema platform_schema = getattr(platform, "PLATFORM_SCHEMA", None) if platform_schema is not None: try: p_validated = platform_schema(p_validated) except vol.Invalid as ex: _comp_error(ex, f"{domain}.{p_name}", p_validated) continue platforms.append(p_validated) # Remove config for current component and add validated config back in. for filter_comp in extract_domain_configs(config, domain): del config[filter_comp] result[domain] = platforms return result

[ "balloob@gmail.com" ]

balloob@gmail.com

d7272c54660fa14d98ac4d2516403bfb2e29ff54

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/python_visual_mpc/visual_mpc_core/agent/create_configs_agent.py

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[]

no_license

febert/robustness_via_retrying

8fe4106d7705228ff339f9643518a80c0a243d36

1def282dc22f24b72c51ff1ef9ea1a7a83291369

refs/heads/master

2020-03-31T19:33:39.664525

2018-11-07T21:52:56

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""" This agent is responsible for creating experiment configurations for benchmarks """ from .general_agent import GeneralAgent class CreateConfigAgent(GeneralAgent): def __init__(self, hyperparams): super().__init__(hyperparams) def rollout(self, policy, i_trial, i_traj): # Take the sample. self._init() agent_data, policy_outputs = {}, [] agent_data['traj_ok'] = True initial_env_obs, reset_state = self.env.reset() agent_data['reset_state'] = reset_state obs = self._post_process_obs(initial_env_obs, agent_data, initial_obs=True) for t in range(self._hyperparams['T']): self.env.move_arm() # should look into creating one "generate task" function for long term.... self.env.move_objects() try: obs = self._post_process_obs(self.env.current_obs(), agent_data) except ValueError: return {'traj_ok': False}, None, None return agent_data, obs, policy_outputs

[ "sdasari@berkeley.edu" ]

sdasari@berkeley.edu

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/LeetCode/1000.Minimum-Cost-To-Merge-Stones/Minimum-Cost-To-Merge-Stones.py

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[]

no_license

htingwang/HandsOnAlgoDS

034b5199b394ca82fd4fb16614ddabb45f3325e2

5b14b6f42baf59b04cbcc8e115df4272029b64c8

refs/heads/master

2021-07-11T15:50:30.944794

2020-09-27T05:08:02

192,391,446

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2019-07-03T04:09:35

2019-06-17T17:36:01

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UTF-8

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import heapq class Solution(object): def mergeStones(self, stones, K): """ :type stones: List[int] :type K: int :rtype: int """ n = len(stones) if (n - 1) % (K - 1): return -1 pre_sum = [0] * (n + 1) for i in range(1, n + 1): pre_sum[i] = pre_sum[i - 1] + stones[i - 1] dp = [[0] * n for _ in range(n)] for m in range(K, n + 1): for i in range(n - m + 1): j = i + m - 1 dp[i][j] = float('inf') for mid in range(i, j, K - 1): dp[i][j] = min(dp[i][j], dp[i][mid] + dp[mid + 1][j]) if (j - i) % (K - 1) == 0: dp[i][j] += (pre_sum[j + 1] - pre_sum[i]) return dp[0][n - 1]

[ "49448790+htingwang@users.noreply.github.com" ]

49448790+htingwang@users.noreply.github.com

0665059974ce35e023c58e61975a130e51d29396

6d24fb1c67771e7285dea61840f9766013589dd1

/manage.py

d7031ecdad34e4d427ed940b884e8d8c8477c930

[]

no_license

PandaBalu/gglobal

b045fb66f7daea8eeb8d6c62f5dc872ff0b1b246

c063c44c30d023bf562c0b4b39d10161540e7a92

refs/heads/master

2020-12-10T03:14:00.710720

2017-06-26T12:22:05

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null

UTF-8

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py

#!/usr/bin/env python import os import sys if __name__ == '__main__': os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.local') try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django # noqa except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise # This allows easy placement of apps within the interior # gglobal directory. current_path = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(current_path, 'gglobal')) execute_from_command_line(sys.argv)

[ "narnikgamarnikus@gmail.com" ]

narnikgamarnikus@gmail.com

3738ae3586b803368bac15fdb7da8a6778e9353d

473645b727129e33ab12b42ecece255db73dfcfc

/PatObjectOwnRefProducer/patobjectownrefproducer_cfg.py

bcd95a65ab955d338995758f308c9b88bc41d278

[]

no_license

jpata/AnalysisModules

b3c17ff60ec31b76798ff8a473397b5728e96ca7

02d9d3e28f937c683616c7be4efeddf8874f571c

refs/heads/master

2021-01-21T07:39:34.632912

2014-07-02T07:47:48

null

0

null

UTF-8

Python

false

1,644

py

import FWCore.ParameterSet.Config as cms import os inFile = os.environ["TESTING_FILE"] process = cms.Process("OWNPARTICLES") process.load("FWCore.MessageLogger.MessageLogger_cfi") process.MessageLogger=cms.Service("MessageLogger", destinations=cms.untracked.vstring('cout'), debugModules=cms.untracked.vstring('patJetsPuCleaned'), cout=cms.untracked.PSet(threshold=cms.untracked.string('DEBUG')) ) process.maxEvents = cms.untracked.PSet( input = cms.untracked.int32(-1) ) process.source = cms.Source("PoolSource", # replace 'myfile.root' with the source file you want to use fileNames = cms.untracked.vstring( inFile ) ) process.patJetsWithOwnRef = cms.EDProducer('PatObjectOwnRefProducer<pat::Jet>', src=cms.InputTag("selectedPatJets") ) process.patJetsPuCleaned = cms.EDProducer('CleanNoPUJetProducer', # jetSrc = cms.InputTag("patJetsWithOwnRef"), jetSrc = cms.InputTag("selectedPatJets"), PUidMVA = cms.InputTag("puJetMva", "fullDiscriminant", "PAT"), PUidFlag = cms.InputTag("puJetMva", "fullId", "PAT"), PUidVars = cms.InputTag("puJetId", "", "PAT"), isOriginal = cms.bool(True) ) process.simpleAnalyzer = cms.EDAnalyzer( 'SimpleEventAnalyzer', interestingCollections = cms.untracked.VInputTag([ "selectedPatJets", "patJetsWithOwnRef", ]), maxObjects=cms.untracked.uint32(1) ) process.out = cms.OutputModule("PoolOutputModule", fileName = cms.untracked.string('test.root') ) process.p = cms.Path( process.patJetsWithOwnRef * process.simpleAnalyzer * process.patJetsPuCleaned ) process.e = cms.EndPath(process.out)

[ "joosep.pata@gmail.com" ]

joosep.pata@gmail.com

dfe1d9dd9dfdd2d164927e535fef2fab31bc1835

5e8342e4f6e48688f4a0079310e8f0b5e5386044

/POO/Factura/factura.py

9f45e3faba5e32f086d57287d8428a3e6b3f8bb6

[]

no_license

fernado1981/python_

27a154406b5fba7e18da418bc5f75c58f3ccc24f

7d846cd332405464fa14707ea3f2286a918fc9de

refs/heads/master

2023-02-15T19:30:02.257345

2021-01-21T10:35:46

277,186,729

0

null

UTF-8

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978

py

from InteractuarFactura import InteractuarFactura # Escribir un programa que gestione las facturas pendientes de cobro de una empresa. # Las facturas se almacenarán en un diccionario donde la clave de cada factura será el número de factura # y el valor el coste de la factura. El programa debe preguntar al usuario si quiere añadir una nueva factura, # pagar una existente o terminar. Si desea añadir una nueva factura se preguntará por el número de factura # y su coste y se añadirá al diccionario. Si se desea pagar una factura se preguntará por el número de factura # y se eliminará del diccionario. Después de cada operación el programa debe mostrar por pantalla la cantidad # cobrada hasta el momento y la cantidad pendiente de cobro. class factura: clave = int(input("Numero de Factura: ")) valor = float(input("Coste de la factura: ")) fact = InteractuarFactura(clave, valor) fact.anadirOrden() fact.pagarOrden() fact.terminar()

[ "fernando.manrique.villanueva@gmail.com" ]

fernando.manrique.villanueva@gmail.com

0f5bee18ae85a0d5b0a6a43a1130f89838d0cf3c

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/pytorch/synaptic/gan.py

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anantguptadbl/python

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4954efbe52ff3190201a8c0836d80015d13d4d15

refs/heads/master

2022-03-23T03:52:47.956875

2022-02-24T12:26:29

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import os import numpy as np import torch import torchvision from torch import nn from torch.autograd import Variable from torch.utils.data import DataLoader from torchvision import transforms, datasets # FIRST SHAPE GAN learning_rate=0.001 n_classes=4 embedding_dim=10 latent_dim=10 # CONDITIONAL GAN class Generator(nn.Module): def __init__(self): super(Generator, self).__init__() self.label_conditioned_generator = nn.Sequential( nn.Embedding(n_classes, embedding_dim), nn.Linear(embedding_dim, 16) ) self.latent = nn.Sequential( nn.Linear(latent_dim, 4*4*512), nn.LeakyReLU(0.2, inplace=True) ) self.model = nn.Sequential(nn.ConvTranspose2d(513, 64*8, 4, 2, 1, bias=False), nn.BatchNorm2d(64*8, momentum=0.1, eps=0.8), nn.ReLU(True), nn.ConvTranspose2d(64*8, 64*4, 4, 2, 1,bias=False), nn.BatchNorm2d(64*4, momentum=0.1, eps=0.8), nn.ReLU(True), nn.ConvTranspose2d(64*4, 64*2, 4, 2, 1,bias=False), nn.BatchNorm2d(64*2, momentum=0.1, eps=0.8), nn.ReLU(True), nn.ConvTranspose2d(64*2, 64*1, 4, 2, 1,bias=False), nn.BatchNorm2d(64*1, momentum=0.1, eps=0.8), nn.ReLU(True), nn.ConvTranspose2d(64*1, 3, 4, 2, 1, bias=False), nn.Tanh() ) def forward(self, inputs): noise_vector, label = inputs label_output = self.label_conditioned_generator(label) label_output = label_output.view(-1, 1, 4, 4) latent_output = self.latent(noise_vector) latent_output = latent_output.view(-1, 512,4,4) concat = torch.cat((latent_output, label_output), dim=1) image = self.model(concat) #print(image.size()) return image class Discriminator(nn.Module): def __init__(self): super(Discriminator, self).__init__() self.label_condition_disc = nn.Sequential(nn.Embedding(n_classes, embedding_dim), nn.Linear(embedding_dim, 3*128*128)) self.model = nn.Sequential(nn.Conv2d(6, 64, 4, 2, 1, bias=False), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(64, 64*2, 4, 3, 2, bias=False), nn.BatchNorm2d(64*2, momentum=0.1, eps=0.8), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(64*2, 64*4, 4, 3,2, bias=False), nn.BatchNorm2d(64*4, momentum=0.1, eps=0.8), nn.LeakyReLU(0.2, inplace=True), nn.Conv2d(64*4, 64*8, 4, 3, 2, bias=False), nn.BatchNorm2d(64*8, momentum=0.1, eps=0.8), nn.LeakyReLU(0.2, inplace=True), nn.Flatten(), nn.Dropout(0.4), nn.Linear(4608, 1), nn.Sigmoid() ) def forward(self, inputs): img, label = inputs label_output = self.label_condition_disc(label) label_output = label_output.view(-1, 3, 128, 128) concat = torch.cat((img, label_output), dim=1) output = self.model(concat) return output batch_size=16 train_transform = transforms.Compose([ transforms.Resize(128), transforms.ToTensor(), transforms.Normalize([0.5,0.5,0.5], [0.5,0.5,0.5])]) train_dataset = datasets.ImageFolder(root='rps', transform=train_transform) train_loader = torch.utils.data.DataLoader(dataset=train_dataset, batch_size=batch_size, shuffle=True) # Models discriminator = Discriminator() generator = Generator() # Loss discriminator_loss = nn.BCELoss() generator_loss = nn.MSELoss() # Optimizers D_optimizer = torch.optim.Adam(discriminator.parameters(), lr=learning_rate, weight_decay=1e-5) G_optimizer = torch.optim.Adam(generator.parameters(), lr=learning_rate, weight_decay=1e-5) num_epochs = 200 device='cpu' for epoch in range(1, num_epochs+1): D_loss_list, G_loss_list = [], [] for index, (real_images, labels) in enumerate(train_loader): D_optimizer.zero_grad() real_images = real_images.to(device) labels = labels.to(device) labels = labels.unsqueeze(1).long() real_target = Variable(torch.ones(real_images.size(0), 1).to(device)) fake_target = Variable(torch.zeros(real_images.size(0), 1).to(device)) D_real_loss = discriminator_loss(discriminator((real_images, labels)), real_target) # print(discriminator(real_images)) #D_real_loss.backward() noise_vector = torch.randn(real_images.size(0), latent_dim, device=device) noise_vector = noise_vector.to(device) generated_image = generator((noise_vector, labels)) output = discriminator((generated_image.detach(), labels)) D_fake_loss = discriminator_loss(output, fake_target) # train with fake #D_fake_loss.backward() D_total_loss = (D_real_loss + D_fake_loss) / 2 D_loss_list.append(D_total_loss) D_total_loss.backward() D_optimizer.step() # Train generator with real labels G_optimizer.zero_grad() G_loss = generator_loss(discriminator((generated_image, labels)), real_target) G_loss_list.append(G_loss) G_loss.backward() G_optimizer.step() print("Epoch {0} Gen loss {1} Discrim loss {2}".format(epoch, G_loss, D_total_loss))

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anantguptadbl.noreply@github.com

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/MIDI Remote Scripts/Push2/observable_property_alias.py

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[]

no_license

aumhaa/livepy_diff

8e593ffb30b1e7909225352f3a0084d4de2e51e6

266a7380c4d5a162c051c23f534f74cb7eace538

refs/heads/master

2020-04-12T03:17:56.545373

2017-04-24T02:02:07

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from __future__ import absolute_import, print_function from ableton.v2.base import EventObject, Slot class ObservablePropertyAlias(EventObject): def __init__(self, alias_host, property_host = None, property_name = '', alias_name = None, getter = None, *a, **k): super(ObservablePropertyAlias, self).__init__(*a, **k) self._alias_host = alias_host self._alias_name = alias_name or property_name self._property_host = property_host self._property_name = property_name self._property_slot = None self._setup_alias(getter) def _get_property_host(self): return self._property_host def _set_property_host(self, host): self._property_host = host self._property_slot.subject = host property_host = property(_get_property_host, _set_property_host) def _setup_alias(self, getter): aliased_prop = property(getter or self._get_property) setattr(self._alias_host.__class__, self._alias_name, aliased_prop) notifier = getattr(self._alias_host, 'notify_' + self._alias_name) self._property_slot = self.register_slot(Slot(self.property_host, notifier, self._property_name)) def _get_property(self, _): return getattr(self.property_host, self._property_name, None)

[ "aumhaa@gmail.com" ]

aumhaa@gmail.com

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/179-largest-number/largest-number.py

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[]

no_license

ANDYsGUITAR/leetcode

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refs/heads/master

2020-04-01T18:24:01.072127

2019-04-04T08:38:44

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UTF-8

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py

# Given a list of non negative integers, arrange them such that they form the largest number. # # Example 1: # # # Input: [10,2] # Output: "210" # # Example 2: # # # Input: [3,30,34,5,9] # Output: "9534330" # # # Note: The result may be very large, so you need to return a string instead of an integer. # class Solution: def largestNumber(self, nums: List[int]) -> str: import functools def cmp(a,b): if int(a + b) > int(b + a): return 1 elif int(a + b) < int(b + a): return -1 else: return 0 nums = list(map(str, nums)) nums.sort(key = functools.cmp_to_key(cmp), reverse = True) return ''.join(nums) if nums[0] != '0' else '0'

[ "andyandwei@163.com" ]

andyandwei@163.com

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/apps/accounts/tests/factories/user.py

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[ "MIT" ]

permissive

jimialex/django-wise

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refs/heads/master

2023-04-30T20:59:51.625190

2021-05-10T06:55:40

null

0

null

UTF-8

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981

py

# -*- coding: utf-8 -*- import factory from faker import Factory from faker.providers import misc, person, profile from apps.accounts.models.user import User fake = Factory.create() fake.add_provider(person) fake.add_provider(profile) fake.add_provider(misc) def fake_username(): return fake.simple_profile()['username'] def generate_user_profile(): user_profile = fake.simple_profile() user_password = fake.uuid4() full_name = fake.name().split(' ') return { 'username': user_profile['username'], 'email': user_profile['mail'], 'firstName': full_name[0], 'lastName': full_name[1], 'password': user_password, } class UserFactory(factory.django.DjangoModelFactory): username = factory.LazyFunction(fake_username) email = factory.LazyFunction(fake.email) first_name = factory.LazyFunction(fake.first_name) last_name = factory.LazyFunction(fake.last_name) class Meta: model = User

[ "vicobits@gmail.com" ]

vicobits@gmail.com

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/django-stubs/forms/utils.pyi

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permissive

debuggerpk/django-stubs

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refs/heads/master

2020-04-04T08:33:52.358704

2018-09-26T19:32:19

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null

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from collections import UserList from datetime import datetime from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union from django.core.exceptions import ValidationError from django.utils.safestring import SafeText def pretty_name(name: str) -> str: ... def flatatt(attrs: Dict[str, Optional[str]]) -> SafeText: ... class ErrorDict(dict): def as_data(self) -> Dict[str, List[ValidationError]]: ... def get_json_data( self, escape_html: bool = ... ) -> Dict[str, List[Dict[str, str]]]: ... def as_json(self, escape_html: bool = ...) -> str: ... def as_ul(self) -> str: ... def as_text(self) -> str: ... class ErrorList(UserList, list): data: List[Union[django.core.exceptions.ValidationError, str]] error_class: str = ... def __init__( self, initlist: Optional[ Union[List[ValidationError], List[str], ErrorList] ] = ..., error_class: Optional[str] = ..., ) -> None: ... def as_data(self) -> List[ValidationError]: ... def get_json_data( self, escape_html: bool = ... ) -> List[Dict[str, str]]: ... def as_json(self, escape_html: bool = ...) -> str: ... def as_ul(self) -> str: ... def as_text(self) -> str: ... def __contains__(self, item: str) -> bool: ... def __eq__(self, other: Union[List[str], ErrorList]) -> bool: ... def __getitem__(self, i: Union[int, str]) -> str: ... def __reduce_ex__( self, *args: Any, **kwargs: Any ) -> Tuple[ Callable, Tuple[Type[ErrorList]], Dict[str, Union[List[ValidationError], str]], None, None, ]: ... def from_current_timezone(value: datetime) -> datetime: ... def to_current_timezone(value: datetime) -> datetime: ...

[ "maxim.kurnikov@gmail.com" ]

maxim.kurnikov@gmail.com

82e4a2ec6b46eff9f8e2a406b016bbc33060b85f

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/python/小练习/socket.py

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lvhanzhi/Python

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2020-03-25T23:34:00.919197

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# 1、买手机 import socket phone = socket.socket(socket.AF_INET, socket.SOCK_STREAM) # tcp称为流式协议,udp称为数据报协议SOCK_DGRAM # print(phone) # 2、插入/绑定手机卡 # phone.setsockopt(socket.SOL_SOCKET,socket.SO_REUSEADDR,1) phone.bind(('127.0.0.1', 8080)) # 3、开机 phone.listen(5) # 半连接池，限制的是请求数 # 4、等待电话连接 print('start....') while True: # 连接循环 conn, client_addr = phone.accept() # （三次握手建立的双向连接，（客户端的ip，端口）） # print(conn) print('已经有一个连接建立成功', client_addr) # 5、通信：收\发消息 while True: # 通信循环 try: print('服务端正在收数据...') data = conn.recv(1024) # 最大接收的字节数，没有数据会在原地一直等待收，即发送者发送的数据量必须>0bytes # print('===>') if len(data) == 0: break # 在客户端单方面断开连接，服务端才会出现收空数据的情况 print('来自客户端的数据', data) conn.send(data.upper()) except ConnectionResetError: break # 6、挂掉电话连接 conn.close() # 7、关机 phone.close() print('aaa') def foo(): pass from b import foo foo() 圣诞快乐国际旅客的世界观的雷锋精神的理解老师是DLGKLFDNHJGLADF IF 报头

[ "1541860665@qq.com" ]

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/test/test_related_permission_model.py

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CU-CommunityApps/ct-cloudcheckr-cmx-client

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# coding: utf-8 """ CloudCheckr API CloudCheckr API # noqa: E501 OpenAPI spec version: v1 Contact: support@cloudcheckr.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import cloudcheckr_cmx_client from cloudcheckr_cmx_client.models.related_permission_model import RelatedPermissionModel # noqa: E501 from cloudcheckr_cmx_client.rest import ApiException class TestRelatedPermissionModel(unittest.TestCase): """RelatedPermissionModel unit test stubs""" def setUp(self): pass def tearDown(self): pass def testRelatedPermissionModel(self): """Test RelatedPermissionModel""" # FIXME: construct object with mandatory attributes with example values # model = cloudcheckr_cmx_client.models.related_permission_model.RelatedPermissionModel() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "pea1@cornell.edu" ]

pea1@cornell.edu

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from pyidml.fields import * from pyidml.models import Element, Properties class Tags(Element): DOMVersion = StringField() class XMLTagProperties(Properties): TagColor = StringField() # TODO InDesignUIColorType_TypeDef class XMLTag(Element): Self = StringField(required=True) Name = StringField(required=True) Properties = EmbeddedDocumentField(XMLTagProperties)

[ "ben@firshman.co.uk" ]

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from itertools import permutations def possible_permutations(data): result = permutations(data) for el in result: yield [*el] [print(n) for n in possible_permutations([1, 2, 3])]

[ "martinkypar@gmail.com" ]

martinkypar@gmail.com

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/django/django-instagram-clone_kindfamily/instaclone-backend/accounts/admin.py

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anifilm/webapp

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2023-08-29T18:33:00.323248

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from django.contrib import admin from .models import Profile, Follow class FollowInline(admin.TabularInline): model = Follow fk_name = 'from_user' @admin.register(Profile) class ProfileAdmin(admin.ModelAdmin): list_display = ['id', 'nickname', 'user'] list_display_links = ['nickname', 'user'] search_fields = ['nickname'] inlines = [FollowInline] @admin.register(Follow) class FollowAdmin(admin.ModelAdmin): list_display = ['from_user', 'to_user', 'created_at'] list_display_links = ['from_user', 'to_user', 'created_at']

[ "anifilm02@gmail.com" ]

anifilm02@gmail.com

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/amatino/ledger_order.py

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2022-07-19T12:24:06.587840

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""" Amatino API Python Bindings Ledger Order Module Author: hugh@amatino.io """ from enum import Enum class LedgerOrder(Enum): OLDEST_FIRST = True YOUNGEST_FIRST = False

[ "hugh.jeremy@gmail.com" ]

hugh.jeremy@gmail.com

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/kratos/python_scripts/application_generator/classes/variableCreator.py

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2020-04-27T17:10:10.357084

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from __future__ import print_function, absolute_import, division from utils.constants import ctab class VariableCreator(object): def __init__(self, name, vtype, is3D=False): ''' Creates a variable for an application Input ----- - name: string name of the variable - vtype: string type of the variable - is3D:: boolean determines if the variable is vectorial(True) or scalar(False, default) NOTE: This will be could be replaced by VariableCreator3D at some point. ''' self.defineString = 'KRATOS_DEFINE_VARIABLE( {type}, {name} )\n'.format(type=vtype, name=name) self.createString = 'KRATOS_CREATE_VARIABLE( {type}, {name} )\n'.format(type=vtype, name=name) self.registerString = ctab + 'KRATOS_REGISTER_VARIABLE( {name} )\n'.format(name=name) self.registerPythonString = ctab + 'KRATOS_REGISTER_IN_PYTHON_VARIABLE(m, {name} )\n'.format(name=name) # String changes if is a 3D variable if is3D: self.defineString = 'KRATOS_DEFINE_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.createString = 'KRATOS_CREATE_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.registerString = ctab + 'KRATOS_REGISTER_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.registerPythonString = ctab + 'KRATOS_REGISTER_IN_PYTHON_3D_VARIABLE_WITH_COMPONENTS(m, {name} )\n'.format(name=name) class VariableCreator3D(object): def __init__(self, name): ''' Creates a 3D variable for an application. All 3D variables are "double" by definition Input ----- - name: string name of the variable ''' self.defineString = 'KRATOS_DEFINE_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.createString = 'KRATOS_CREATE_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.registerString = ctab + 'KRATOS_REGISTER_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name) self.registerPythonString = ctab + 'KRATOS_REGISTER_IN_PYTHON_3D_VARIABLE_WITH_COMPONENTS( {name} )\n'.format(name=name)

[ "roigcarlo@gmail.com" ]

roigcarlo@gmail.com

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/qa/rpc-tests/smartfees.py

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2021-10-09T15:32:34.396521

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#!/usr/bin/env python2 # Copyright (c) 2014 The Bitcredit Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. # # Test fee estimation code # from test_framework import BitcreditTestFramework from bitcreditrpc.authproxy import AuthServiceProxy, JSONRPCException from util import * class EstimateFeeTest(BitcreditTestFramework): def setup_network(self): self.nodes = [] self.nodes.append(start_node(0, self.options.tmpdir, ["-debug=mempool", "-debug=estimatefee", "-relaypriority=0"])) # Node1 mines small-but-not-tiny blocks, and allows free transactions. # NOTE: the CreateNewBlock code starts counting block size at 1,000 bytes, # so blockmaxsize of 2,000 is really just 1,000 bytes (room enough for # 6 or 7 transactions) self.nodes.append(start_node(1, self.options.tmpdir, ["-blockprioritysize=1500", "-blockmaxsize=2000", "-debug=mempool", "-debug=estimatefee", "-relaypriority=0"])) connect_nodes(self.nodes[1], 0) # Node2 is a stingy miner, that # produces very small blocks (room for only 3 or so transactions) node2args = [ "-blockprioritysize=0", "-blockmaxsize=1500", "-debug=mempool", "-debug=estimatefee", "-relaypriority=0"] self.nodes.append(start_node(2, self.options.tmpdir, node2args)) connect_nodes(self.nodes[2], 0) self.is_network_split = False self.sync_all() def run_test(self): # Prime the memory pool with pairs of transactions # (high-priority, random fee and zero-priority, random fee) min_fee = Decimal("0.001") fees_per_kb = []; for i in range(12): (txid, txhex, fee) = random_zeropri_transaction(self.nodes, Decimal("1.1"), min_fee, min_fee, 20) tx_kbytes = (len(txhex)/2)/1000.0 fees_per_kb.append(float(fee)/tx_kbytes) # Mine blocks with node2 until the memory pool clears: count_start = self.nodes[2].getblockcount() while len(self.nodes[2].getrawmempool()) > 0: self.nodes[2].setgenerate(True, 1) self.sync_all() all_estimates = [ self.nodes[0].estimatefee(i) for i in range(1,20) ] print("Fee estimates, super-stingy miner: "+str([str(e) for e in all_estimates])) # Estimates should be within the bounds of what transactions fees actually were: delta = 1.0e-6 # account for rounding error for e in filter(lambda x: x >= 0, all_estimates): if float(e)+delta < min(fees_per_kb) or float(e)-delta > max(fees_per_kb): raise AssertionError("Estimated fee (%f) out of range (%f,%f)"%(float(e), min_fee_kb, max_fee_kb)) # Generate transactions while mining 30 more blocks, this time with node1: for i in range(30): for j in range(random.randrange(6-4,6+4)): (txid, txhex, fee) = random_transaction(self.nodes, Decimal("1.1"), Decimal("0.0"), min_fee, 20) tx_kbytes = (len(txhex)/2)/1000.0 fees_per_kb.append(float(fee)/tx_kbytes) self.nodes[1].setgenerate(True, 1) self.sync_all() all_estimates = [ self.nodes[0].estimatefee(i) for i in range(1,20) ] print("Fee estimates, more generous miner: "+str([ str(e) for e in all_estimates])) for e in filter(lambda x: x >= 0, all_estimates): if float(e)+delta < min(fees_per_kb) or float(e)-delta > max(fees_per_kb): raise AssertionError("Estimated fee (%f) out of range (%f,%f)"%(float(e), min_fee_kb, max_fee_kb)) # Finish by mining a normal-sized block: while len(self.nodes[0].getrawmempool()) > 0: self.nodes[0].setgenerate(True, 1) self.sync_all() final_estimates = [ self.nodes[0].estimatefee(i) for i in range(1,20) ] print("Final fee estimates: "+str([ str(e) for e in final_estimates])) if __name__ == '__main__': EstimateFeeTest().main()

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you@example.com

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2023-07-28T06:54:44.797222

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import discord from discord.ext import commands from discord.utils import get class c301(commands.Cog, name="c301"): def __init__(self, bot: commands.Bot): self.bot = bot @commands.command(name='Mage\'s_Magic', aliases=['c301']) async def example_embed(self, ctx): embed = discord.Embed(title='Mage\'s Magic', color=0x1D9E74) embed.set_thumbnail(url='https://www.duelingbook.com/images/custom-pics/2300000/2361242.jpg') embed.add_field(name='Status (Archetype)', value='Casual:3/Tournament:3', inline=True) embed.add_field(name='Type', value='Spell/Quick-Play', inline=False) embed.add_field(name='Card Effect', value='Target 1 Set Spell/Trap you control; banish that target, then banish 2 Spell/Traps on the field. You cannot activate the targeted card this Chain.', inline=False) embed.set_footer(text='Set Code: ANCF') await ctx.send(embed=embed) def setup(bot: commands.Bot): bot.add_cog(c301(bot))

[ "professorsean3@gmail.com" ]

professorsean3@gmail.com

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2021-01-18T05:16:16.285330

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''' Create a SCP side-channel to transfer a file to remote network device. SCP requires a separate SSH connection. Currently only supports Cisco IOS. ''' from __future__ import print_function from __future__ import unicode_literals import re import os import hashlib import paramiko import scp class SCPConn(object): ''' Establish an SCP channel to the remote network ''' def __init__(self, ssh_conn): self.ssh_ctl_chan = ssh_conn self.establish_scp_conn() def establish_scp_conn(self): ''' Establish the SCP connection ''' self.scp_conn = paramiko.SSHClient() self.scp_conn.set_missing_host_key_policy(paramiko.AutoAddPolicy()) self.scp_conn.connect(hostname=self.ssh_ctl_chan.ip, port=self.ssh_ctl_chan.port, username=self.ssh_ctl_chan.username, password=self.ssh_ctl_chan.password, look_for_keys=False, allow_agent=False, timeout=8) self.scp_client = scp.SCPClient(self.scp_conn.get_transport()) def scp_transfer_file(self, source_file, dest_file): ''' Transfer file using SCP Must close the SCP connection to get the file to write to the remote filesystem ''' self.scp_client.put(source_file, dest_file) def close(self): ''' Close the SCP connection ''' self.scp_conn.close() class FileTransfer(object): ''' Class to manage SCP file transfer and associated SSH control channel ''' def __init__(self, ssh_conn, source_file, dest_file, file_system="flash:"): ''' Establish a SCP connection to the remote network device ''' self.ssh_ctl_chan = ssh_conn self.source_file = source_file self.source_md5 = self.file_md5(source_file) self.dest_file = dest_file self.file_system = file_system src_file_stats = os.stat(source_file) self.file_size = src_file_stats.st_size def __enter__(self): '''Context manager setup''' self.establish_scp_conn() return self def __exit__(self, exc_type, exc_value, traceback): '''Context manager cleanup''' self.close_scp_chan() if exc_type is not None: raise exc_type(exc_value) def establish_scp_conn(self): '''Establish SCP connection''' self.scp_conn = SCPConn(self.ssh_ctl_chan) def close_scp_chan(self): '''Close the SCP connection to the remote network device''' self.scp_conn.close() self.scp_conn = None def verify_space_available(self, search_pattern=r"(.*) bytes available "): ''' Verify sufficient space is available on remote network device Return a boolean ''' remote_cmd = "show {0}".format(self.file_system) remote_output = self.ssh_ctl_chan.send_command(remote_cmd) match = re.search(search_pattern, remote_output) space_avail = int(match.group(1)) if space_avail > self.file_size: return True return False def check_file_exists(self, remote_cmd=""): ''' Check if the dest_file exists on the remote file system Return a boolean ''' if not remote_cmd: remote_cmd = "dir flash:/{0}".format(self.dest_file) remote_out = self.ssh_ctl_chan.send_command(remote_cmd) search_string = r"Directory of .*{0}".format(self.dest_file) if 'Error opening' in remote_out: return False elif re.search(search_string, remote_out): return True else: raise ValueError("Unexpected output from check_file_exists") @staticmethod def file_md5(file_name): ''' Compute MD5 hash of file ''' with open(file_name, "rb") as f: file_contents = f.read() file_hash = hashlib.md5(file_contents).hexdigest() return file_hash @staticmethod def process_md5(md5_output, pattern=r"= (.*)"): ''' Process the string to retrieve the MD5 hash Output from Cisco IOS: .MD5 of flash:file_name Done! verify /md5 (flash:file_name) = 410db2a7015eaa42b1fe71f1bf3d59a2 ''' match = re.search(pattern, md5_output) if match: return match.group(1) else: raise ValueError("Invalid output from MD5 command: {0}".format(md5_output)) def compare_md5(self, base_cmd='verify /md5', delay_factor=8): ''' Calculate remote MD5 and compare to source MD5 Default command is Cisco specific This command can be CPU intensive on the remote device Return boolean ''' remote_md5_cmd = "{0} {1}{2}".format(base_cmd, self.file_system, self.dest_file) dest_md5 = self.ssh_ctl_chan.send_command(remote_md5_cmd, delay_factor=delay_factor) dest_md5 = self.process_md5(dest_md5) if self.source_md5 != dest_md5: return False else: return True def transfer_file(self): ''' SCP transfer source_file to Cisco IOS device Verifies MD5 of file on remote device or generates an exception ''' self.scp_conn.scp_transfer_file(self.source_file, self.dest_file) # Must close the SCP connection to get the file written to the remote filesystem (flush) self.scp_conn.close() def verify_file(self): ''' Verify the file has been transferred correctly ''' return self.compare_md5() def enable_scp(self, cmd=None): ''' Enable SCP on remote device. Defaults to Cisco IOS command ''' if cmd is None: cmd = ['ip scp server enable'] elif not hasattr(cmd, '__iter__'): cmd = [cmd] self.ssh_ctl_chan.send_config_set(cmd) def disable_scp(self, cmd=None): ''' Disable SCP on remote device. Defaults to Cisco IOS command ''' if cmd is None: cmd = ['no ip scp server enable'] elif not hasattr(cmd, '__iter__'): cmd = [cmd] self.ssh_ctl_chan.send_config_set(cmd)

[ "ktbyers@twb-tech.com" ]

ktbyers@twb-tech.com

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# -*- coding: utf-8 -*- from openerp import models, fields class TempdbTdc(models.Model): _name = 'tempdb.tdc' _description = 'Load tempdb_tdc in recup nom apporteur' name = fields.Char(string='Name') statut = fields.Char(string='Statut') agence = fields.Char(string='Agence', size=4) old = fields.Char(string='Old', size=8) new = fields.Char(string='New', size=16) titre = fields.Char(string='Titre', size=16)

[ "aroodoo@asus.aro" ]

aroodoo@asus.aro

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/Se2iP/usr/lib/enigma2/python/Plugins/Extensions/IPTVPlayer/tsiplayer/addons/resources/hosters/dustreaming.py

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[]

no_license

lexlong2007/eePlugins

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refs/heads/master

2022-03-09T05:37:37.567937

2022-02-27T01:44:25

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null

2020-04-04T14:03:29

null

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2,140

py

#-*- coding: utf-8 -*- #Vstream https://github.com/Kodi-vStream/venom-xbmc-addons from Plugins.Extensions.IPTVPlayer.tsiplayer.addons.resources.lib.handler.requestHandler import cRequestHandler from Plugins.Extensions.IPTVPlayer.tsiplayer.addons.resources.hosters.hoster import iHoster from Plugins.Extensions.IPTVPlayer.tsiplayer.addons.resources.lib.comaddon import dialog import json class cHoster(iHoster): def __init__(self): self.__sDisplayName = 'Dustreaming' self.__sFileName = self.__sDisplayName self.__sHD = '' def getDisplayName(self): return self.__sDisplayName def setDisplayName(self, sDisplayName): self.__sDisplayName = sDisplayName + ' [COLOR skyblue]' + self.__sDisplayName + '[/COLOR]' def setFileName(self, sFileName): self.__sFileName = sFileName def getFileName(self): return self.__sFileName def getPluginIdentifier(self): return 'dustreaming' def setHD(self, sHD): self.__sHD = '' def getHD(self): return self.__sHD def isDownloadable(self): return True def setUrl(self, sUrl): self.__sUrl = str(sUrl) def getMediaLink(self): return self.__getMediaLinkForGuest() def __getMediaLinkForGuest(self): api_call = '' sUrl = self.__sUrl.replace('/v/', '/api/source/') oRequest = cRequestHandler(sUrl) oRequest.setRequestType(cRequestHandler.REQUEST_TYPE_POST) oRequest.addHeaderEntry('Referer', self.__sUrl) oRequest.addParameters('r', '') oRequest.addParameters('d', 'dustreaming.fr') sHtmlContent = oRequest.request() page = json.loads(sHtmlContent) if page: url = [] qua = [] for x in page['data']: url.append(x['file']) qua.append(x['label']) if (url): api_call = dialog().VSselectqual(qua, url) if (api_call): return True, api_call return False, False

[ "zdzislaw22@windowslive.com" ]

zdzislaw22@windowslive.com

25daeb07963fe92517947f4aa8197cc45303103d

68e65df90da9169733025dfede0a8b30a5e3d7e3

/Inheritance_and_More_on_OOPS/11_practice_test2.py

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[]

no_license

shubam-garg/Python-Beginner

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refs/heads/main

2023-05-06T07:11:29.943475

2021-05-29T20:35:59

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''' create a class pets from class animals and further create class dog from pets, add a method bark to class dog ''' class animals: animaltype="Mammal" class pets(animals): petcolor="Black" class dog(pets): @staticmethod def bark(): print("dog") d=dog() d.bark()

[ "81907680+shubam-garg@users.noreply.github.com" ]

81907680+shubam-garg@users.noreply.github.com

ca6db4381b477d224e0c52a8e60201f6444ddf5d

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/app/views/reports/integration/advantage_payroll/advantage_payroll_client_setup_csv.py

fcfcf75d4a02f73167a6dcc346bf96726af2ace1

[]

no_license

smoothbenefits/BenefitMY_Python

52745a11db2cc9ab394c8de7954974e6d5a05e13

b7e8474a728bc22778fd24fe88d1918945a8cfc8

refs/heads/master

2021-03-27T15:57:34.798289

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from rest_framework.response import Response from django.http import HttpResponse from django.http import Http404 from app.views.reports.report_export_view_base import ReportExportViewBase from app.service.Report.integration.advantage_payroll.advantage_payroll_company_setup_csv_service \ import AdvantagePayrollCompanySetupCsvService class AdvantagePayrollClientSetupCsvView(ReportExportViewBase): def get(self, request, company_id, format=None): csv_service = AdvantagePayrollCompanySetupCsvService() response = HttpResponse(content_type='text/csv') response['Content-Disposition'] = 'attachment; filename=client_setup.csv' csv_service.get_report(company_id, response) return response

[ "jeffzhang_misc@hotmail.com" ]

jeffzhang_misc@hotmail.com

ab58404bbcdbd307415fd151a7e798392d35f0f6

25872e1ba4f86cbbf77d0130f341b21e5dd9e692

/GameOfLife.py

00600969a68b00f6a35c13b6dc1b798ddd428888

[]

no_license

zongxinwu92/leetcode

dc3d209e14532b9b01cfce6d4cf6a4c2d7ced7de

e1aa45a1ee4edaf72447b771ada835ad73e7f508

refs/heads/master

2021-06-10T21:46:23.937268

2017-01-09T09:58:49

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py

''' Created on 1.12.2017 @author: Jesse '''''' According to the Wikipedia s article: "The Game of Life, also known simply as Life, is a cellular automaton devised by the British mathematician John Horton Conway in 1970." Given a board with m by n cells, each cell has an initial state live (1) or dead (0). Each cell interacts with its eight neighbors (horizontal, vertical, diagonal) using the following four rules (taken from the above Wikipedia article): Any live cell with fewer than two live neighbors dies, as if caused by under-population. Any live cell with two or three live neighbors lives on to the next generation. Any live cell with more than three live neighbors dies, as if by over-population.. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction. Write a function to compute the next state (after one update) of the board given its current state. Follow up: Could you solve it in-place? Remember that the board needs to be updated at the same time: You cannot update some cells first and then use their updated values to update other cells. In this question, we represent the board using a 2D array. In principle, the board is infinite, which would cause problems when the active area encroaches the border of the array. How would you address these problems? Credits:Special thanks to @jianchao.li.fighter for adding this problem and creating all test cases." '''

[ "darrencheng0817@gmail.com" ]

darrencheng0817@gmail.com

f97ae739b9877f4e5efd4375b1584c6b49da597b

857d8f44ee11e7bf6972486e6be875aec9fff819

/mythx_cli/formatter/util.py

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[ "MIT" ]

permissive

s0b0lev/mythx-cli

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refs/heads/master

2022-04-10T21:18:20.506815

2020-03-27T10:32:23

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"""Utility functions for handling API requests and responses.""" from typing import List, Union import click from mythx_models.response import DetectedIssuesResponse, Severity SEVERITY_ORDER = ( Severity.UNKNOWN, Severity.NONE, Severity.LOW, Severity.MEDIUM, Severity.HIGH, ) def get_source_location_by_offset(source: str, offset: int) -> int: """Retrieve the Solidity source code location based on the source map offset. :param source: The Solidity source to analyze :param offset: The source map's offset :return: The offset's source line number equivalent """ return source.encode("utf-8")[0:offset].count("\n".encode("utf-8")) + 1 def generate_dashboard_link(uuid: str) -> str: """Generate a MythX dashboard link for an analysis job. This method will generate a link to an analysis job on the official MythX dashboard production setup. Custom deployment locations are currently not supported by this function (but available at mythx.io). :param uuid: The analysis job's UUID :return: The analysis job's dashboard link """ return "https://dashboard.mythx.io/#/console/analyses/{}".format(uuid) def normalize_swc_list(swc_list: Union[str, List[str], None]) -> List[str]: """Normalize a list of SWC IDs. This method normalizes a list of SWC ID definitions, making SWC-101, swc-101, and 101 equivalent. :param swc_list: The list of SWC IDs as strings :return: The normalized SWC ID list as SWC-XXX """ if not swc_list: return [] if type(swc_list) == str: swc_list = swc_list.split(",") swc_list = [str(x).strip().upper() for x in swc_list] swc_list = ["SWC-{}".format(x) if not x.startswith("SWC") else x for x in swc_list] return swc_list def set_ci_failure() -> None: """Based on the current context, set the return code to 1. This method sets the return code to 1. It is called by the respective subcommands (analyze and report) in case a severe issue has been found (as specified by the user) if the CI flag is passed. This will make the MythX CLI fail when running on a CI server. If no context is available, this function assumes that it is running outside a CLI scenario (e.g. a test setup) and will not do anything. """ try: ctx = click.get_current_context() if ctx.obj["ci"]: ctx.obj["retval"] = 1 except RuntimeError: # skip failure when there is no active click context # i.e. the method has been called outside the click # application. pass def filter_report( resp: DetectedIssuesResponse, min_severity: Union[str, Severity] = None, swc_blacklist: Union[str, List[str]] = None, swc_whitelist: Union[str, List[str]] = None, ) -> DetectedIssuesResponse: """Filter issues based on an SWC blacklist and minimum severity. This will remove issues of a specific SWC ID or with a too low severity from the issue reports of the passed :code:`DetectedIssuesResponse` object. The SWC blacklist can be a list of strings in the format "SWC-000" or a comma-separated string. "SWC" is case-insensitive and normalized. The SWC whitelist works in a similar way, just including selected SWCs into the resulting response object. :param resp: The issue report of an analysis job :param min_severity: Ignore SWC IDs below the designated level :param swc_blacklist: A comma-separated list of SWC IDs to ignore :param swc_whitelist: A comma-separated list of SWC IDs to include :return: The filtered issue report """ min_severity = Severity(min_severity.title()) if min_severity else Severity.UNKNOWN swc_blacklist = normalize_swc_list(swc_blacklist) swc_whitelist = normalize_swc_list(swc_whitelist) new_issues = [] for report in resp.issue_reports: for issue in report.issues: is_severe = SEVERITY_ORDER.index(issue.severity) >= SEVERITY_ORDER.index( min_severity ) not_blacklisted = issue.swc_id not in swc_blacklist is_whitelisted = issue.swc_id in swc_whitelist if swc_whitelist else True if all((is_severe, is_whitelisted, not_blacklisted)): new_issues.append(issue) set_ci_failure() report.issues = new_issues return resp

[ "dmuhs@protonmail.ch" ]

dmuhs@protonmail.ch

ca42bf7575d962f0e1942732e0aa257c00973a2a

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/data/output/4_original

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[]

no_license

KqSMea8/pythonanalyzer

6a8adbf945d8d2febcf3e1084bb9d673f89210d7

d4ac77ed1644081e028c791d9b64e9dfebad06e8

refs/heads/master

2020-05-19T21:08:10.645730

2019-05-06T14:45:57

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null

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#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "twobuntu.settings") from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)

[ "rares.begu@gmail.com" ]

rares.begu@gmail.com

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707d702cd2628938829bbab2275da9a52c88666b

/pamlJob.py

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[]

no_license

MaciekZZZ/project-lazarus

682a7f87ed2f2c857bd839abea0360505156ead6

e5b34a4b98c7b064044b98a58a329bf954e65560

refs/heads/master

2021-01-01T18:42:04.760323

2015-03-15T13:51:56

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############################################################################## # # PamlJob class: # a class containing the logic for writing codeml and baseml *.ctl files, # and logic to parse and store the results from codeml and baseml. # # # Author: Victor Hanson-Smith # Contact: victorhs@cs.uoregon.edu # ############################################################################### import os, re, time class PamlJob: def __init__(self): self.treeNumber = None self.treePath = None self.alignmentPath = None self.executionDirectory = None self.controlPath = None self.estimate_branch_lengths = False self.among_site_rate_variation = False self.fix_asrv = False self.alpha = 1.0 self.ncat_gamma = 4 self.cleandata = 0 # # Call this method after the method named self.startJob is finished. # This method verifies that PAML built the correct files. # # If PAML job finished correctly, then this method will return True # If we discover any errors in the PAML output, then this method will return an error message (i.e. a string) # def verifyResults(self): # does the file named 'rst' exist? if False == os.path.exists(self.executionDirectory + "/rst"): return "The PAML job on tree " + self.treeNumber.__str__() + " did not produce a file named 'rst'. I was expecting to find this file at " + self.executionDirectory + "/rst" # does the file named 'out.paml' exist? if False == os.path.exists(self.executionDirectory + "/out.paml"): return "The PAML job on tree " + self.treeNumber.__str__() + " did not produce a file named 'out.paml'. I was expecting to find this file at " + self.executionDirectory + "/out.paml" return True class CodemlJob(PamlJob): def __init__(self): PamlJob.__init__(self) self.modelPath = None # # This method assumes the following variables are instantiated: # self.treePath, self.treeNumber, self.alignmentPath, self.codemlControlPath, and self.executionDirectory # def startJob(self): self.writeControlFile() previous_directory = os.getcwd() os.chdir(self.executionDirectory) os.system("codeml") os.chdir(previous_directory) # # This is a helper method for self.startJob # This method writes codeml.ctl into self.executionDirectory # def writeControlFile(self): self.controlPath = self.executionDirectory + "/codeml.ctl" f = open(self.controlPath, "w") f.write("*\n") f.write("* This file was auto-generated by Lazarus. " + time.localtime().__str__() + "\n") f.write("*\n") f.write("* For more information about the parameters in this file,\n* please consult the official PAML documenation.\n") f.write("*\n") # remove the path to the alignment (We want just the filename) a = self.alignmentPath tokens = a.split("/") alignmentPath = tokens[ tokens.__len__() - 1] f.write("seqfile = " + alignmentPath + "\n") # remove the path to the tree (We want just the filename) a = self.treePath tokens = a.split("/") treePath = tokens[ tokens.__len__() -1 ] f.write("treefile = " + treePath + "\n") f.write("outfile = out.paml\n") f.write("noisy = 3\n") f.write("verbose = 9\n") f.write("runmode = 0\n") f.write("seqtype = 2\n") f.write("aaRatefile = model.dat\n") f.write("model = 3\n") if self.fix_asrv == False: f.write("fix_alpha = 0\n") else: f.write("fix_alpha = 1\n") if self.among_site_rate_variation: f.write("alpha = " + self.alpha.__str__() + "\n") f.write("ncatG = 4\n") else: f.write("alpha = 0\n") f.write("RateAncestor = 2\n") f.write("Small_Diff = 1.0e-6\n") f.write("cleandata = " + self.cleandata.__str__() + "\n") # remove sites with "X" or "?" or other ambiguity f.write("method = 1\n") if self.estimate_branch_lengths == False: f.write("fix_blength = 2\n") # fix the branch lengths at their values in the tree file. else: f.write("fix_blength = 1\n") # use the branch lengths as a starting value for the Ml search f.close() class BasemlJob(PamlJob): def __init__(self): PamlJob.__init__(self) self.modelName = None # # This method assumes the following variables are instantiated: # self.treePath, self.treeNumber, self.alignmentPath, self.codemlControlPath, and self.executionDirectory # def startJob(self): self.writeControlFile() previous_directory = os.getcwd() os.chdir(self.executionDirectory) os.system("baseml") os.chdir(previous_directory) def get_number_for_model(self, modelName): if modelName == "JC69": return 0 elif modelName == "K80": return 1 elif modelName == "F81": return 2 elif modelName == "F84": return 3 elif modelName == "HKY85": return 4 elif modelName == "T92": return 5 elif modelName == "TN93": return 6 elif modelName == "REV": return 7 elif modelName == "UNREST": return 8 elif modelName == "REVu": return 9 elif modelName == "UNRESTu": return 10 # # This is a helper method for self.startJob # This method writes baseml.ctl into self.executionDirectory # def writeControlFile(self): self.controlPath = self.executionDirectory + "/baseml.ctl" f = open(self.controlPath, "w") f.write("*\n") f.write("* This file was auto-generated by Lazarus. " + time.localtime().__str__() + "\n") f.write("*\n") f.write("* For more information about the parameters in this file,\n* please consult the official PAML documenation.\n") f.write("*\n") # remove the path to the alignment (We want just the filename) a = self.alignmentPath tokens = a.split("/") alignmentPath = tokens[ tokens.__len__() - 1] f.write("seqfile = " + alignmentPath + "\n") # remove the path to the tree (We want just the filename) a = self.treePath tokens = a.split("/") treePath = tokens[ tokens.__len__() -1 ] f.write("treefile = " + treePath + "\n") f.write("outfile = out.paml\n") f.write("noisy = 3\n") f.write("verbose = 9\n") f.write("runmode = 0\n") modelnumber = self.get_number_for_model(self.modelName) f.write("model = " + modelnumber.__str__() + "\n") if self.fix_asrv == False: f.write("fix_alpha = 0\n") else: f.write("fix_alpha = 1\n") if self.among_site_rate_variation: f.write("alpha = " + self.alpha.__str__() + "\n") f.write("ncatG = 4\n") else: f.write("alpha = 0\n") f.write("RateAncestor = 2\n") f.write("Small_Diff = 1.0e-6\n") f.write("cleandata = " + self.cleandata.__str__() + "\n") # remove sites with "X" or "?" or other ambiguity f.write("method = 1\n") if self.estimate_branch_lengths == False: f.write("fix_blength = 2\n") # fix the branch lengths at their values in the tree file. else: f.write("fix_blength = 1\n") # use the branch lengths as a starting value for the Ml search f.close()

[ "victorhansonsmith@gmail.com" ]

victorhansonsmith@gmail.com

8c4fd996268da9a039352a06d3bf2b53964c5823

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/tests/model_control/detailed/transf_Integration/model_control_one_enabled_Integration_MovingAverage_Seasonal_MonthOfYear_LSTM.py

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permissive

jmabry/pyaf

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refs/heads/master

2020-03-20T02:14:12.597970

2018-12-17T22:08:11

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py

import pyaf.tests.model_control.test_ozone_custom_models_enabled as testmod testmod.build_model( ['Integration'] , ['MovingAverage'] , ['Seasonal_MonthOfYear'] , ['LSTM'] );

[ "antoine.carme@laposte.net" ]

antoine.carme@laposte.net

ba2ffe1645eb7f733945e851d169d43d91d13d2c

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/saas/settings.py

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[ "MIT" ]

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robert871126/bk-iam-saas

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refs/heads/master

2023-08-23T19:23:01.987394

2021-10-22T09:45:28

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# -*- coding: utf-8 -*- """ TencentBlueKing is pleased to support the open source community by making 蓝鲸智云-权限中心(BlueKing-IAM) 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 http://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. 请不要修改该文件如果你需要对settings里的内容做修改，config/default.py 文件中添加即可如有任何疑问，请联系【蓝鲸助手】 """ import os # V3判断环境的环境变量为BKPAAS_ENVIRONMENT if "BKPAAS_ENVIRONMENT" in os.environ: ENVIRONMENT = os.getenv("BKPAAS_ENVIRONMENT", "dev") # V2判断环境的环境变量为BK_ENV else: PAAS_V2_ENVIRONMENT = os.environ.get("BK_ENV", "development") ENVIRONMENT = {"development": "dev", "testing": "stag", "production": "prod"}.get(PAAS_V2_ENVIRONMENT) DJANGO_CONF_MODULE = "config.{env}".format(env=ENVIRONMENT) try: _module = __import__(DJANGO_CONF_MODULE, globals(), locals(), ["*"]) except ImportError as e: raise ImportError("Could not import config '%s' (Is it on sys.path?): %s" % (DJANGO_CONF_MODULE, e)) for _setting in dir(_module): if _setting == _setting.upper(): locals()[_setting] = getattr(_module, _setting)

[ "zhu327@gmail.com" ]

zhu327@gmail.com

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e04dbc32247accf073e3089ed4013427ad182c7c

/ATC001/A.py

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[]

no_license

twobooks/atcoder_training

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aa81799ec87cc9c9d76de85c55e99ad5fa7676b5

refs/heads/master

2021-10-28T06:33:19.459975

2021-10-20T14:16:57

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# 深さ優先探索 import sys sys.setrecursionlimit(1000000) H,W = list(map(int,input().split())) S = [] for i in range(H): s = input() S.append(s) for i in range(H): for j in range(W): if S[i][j]=="s": si,sj = i,j if S[i][j]=="g": gi,gj = i,j visited = [] for i in range(H): visited.append([False]*W) def dfs(i,j): visited[i][j] = True for i2,j2 in [[i+1,j],[i-1,j],[i,j+1],[i,j-1]]: if not (0<=i2<H and 0<=j2<W): continue if S[i2][j2]=="#": continue if not visited[i2][j2]: dfs(i2,j2) dfs(si,sj) if visited[gi][gj]: print("Yes") else: print("No")

[ "twobookscom@gmail.com" ]

twobookscom@gmail.com

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refs/heads/master

2020-03-31T01:37:25.441270

2018-10-05T19:42:22

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7

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bazel

# -*- python -*- load( "//attic:build_macros.bzl", "add_attic_aliases", ) load("//tools/lint:lint.bzl", "add_lint_tests") load("//multibody/rigid_body_plant:warning.bzl", "WARNING") # For side effect. package(default_visibility = ["//visibility:public"]) add_attic_aliases([ "shapes", "test_models", ]) add_lint_tests()

[ "jeremy.nimmer@tri.global" ]

jeremy.nimmer@tri.global

04a1ac59ec41153c92aff505a32d2c7f77a81895

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/pychron/pyscripts/tasks/pyscript_plugin.py

374747cc5a5e87b032cd0e4c3bc54be69e15aac7

[ "Apache-2.0" ]

permissive

OSUPychron/pychron

d2da9051b68024200d0009de634da810ccef2a0d

fe0ba9daff9548fa8bebab26db66a1cefff7c1d6

refs/heads/master

2021-01-14T12:47:26.389887

2015-12-18T22:27:02

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# =============================================================================== # Copyright 2013 Jake Ross # # 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. # =============================================================================== # ============= enthought library imports ======================= import os from envisage.ui.tasks.task_factory import TaskFactory from envisage.ui.tasks.task_extension import TaskExtension from pyface.tasks.action.schema_addition import SchemaAddition from pyface.tasks.action.task_action import TaskAction from pyface.tasks.action.schema import SMenu # ============= standard library imports ======================== # ============= local library imports ========================== from pychron.envisage.tasks.base_task_plugin import BaseTaskPlugin from pychron.paths import paths from pychron.pyscripts.tasks.pyscript_actions import OpenPyScriptAction, \ NewPyScriptAction, OpenHopsEditorAction, NewHopsEditorAction from pychron.pyscripts.tasks.pyscript_preferences import PyScriptPreferencesPane from pychron.pyscripts.tasks.visual_el_programmer.actions import OpenVisualELScriptAction, NewVisualELScriptAction class PyScriptPlugin(BaseTaskPlugin): id = 'pychron.pyscript.plugin' def _actions_default(self): return [('pychron.open_pyscript', 'Ctrl+Shift+O', 'Open PyScript'), ('pychron.new_pyscript', 'Ctrl+Shift+N', 'New PyScript'),] def _task_extensions_default(self): def _replace_action(): return TaskAction(name='Replace', method='replace') exts = [ TaskExtension( task_id='pychron.pyscript.task', actions=[SchemaAddition( id='Edit', factory=lambda: SMenu(id='Edit', name='Edit'), path='MenuBar'), SchemaAddition(id='replace', path='MenuBar/Edit', factory=_replace_action)]), TaskExtension( actions=[ SchemaAddition(id='open_hops_editor', path='MenuBar/file.menu/Open', factory=OpenHopsEditorAction), SchemaAddition(id='new_hops_editor', path='MenuBar/file.menu/New', factory=NewHopsEditorAction), SchemaAddition(id='open_script', path='MenuBar/file.menu/Open', factory=OpenPyScriptAction), SchemaAddition(id='new_script', path='MenuBar/file.menu/New', factory=NewPyScriptAction), SchemaAddition(id='new_visual', path='MenuBar/file.menu/New', factory=NewVisualELScriptAction), SchemaAddition(id='open_visual', path='MenuBar/file.menu/Open', factory=OpenVisualELScriptAction)])] return exts def _tasks_default(self): return [TaskFactory(id='pychron.pyscript.task', name='PyScript', factory=self._task_factory, task_group='experiment', image='script'), TaskFactory(id='pychron.pyscript.visual_el_programmer', name='Visual Programmer', factory=self._visual_task_factory, task_group='experiment')] def _visual_task_factory(self): from pychron.pyscripts.tasks.visual_el_programmer.visual_el_programmer_task import VisualElProgrammerTask return VisualElProgrammerTask() def _task_factory(self): from pychron.pyscripts.tasks.pyscript_task import PyScriptTask return PyScriptTask() def _preferences_panes_default(self): return [PyScriptPreferencesPane] def _preferences_default(self): return ['file://{}'.format(os.path.join(paths.preferences_dir, 'script.ini'))] # ============= EOF =============================================

[ "jirhiker@gmail.com" ]

jirhiker@gmail.com

93bb1b68101317784173698ba340d4098e7a5b85

1518483f16e735453a0e154a6619a4f5228874f6

/tests/test_decisiontree.py

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[ "MIT" ]

permissive

jdvelasq/decisions-tree

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54f886e82784c4061200d843841ef600b0ac366b

refs/heads/master

2023-06-04T03:47:45.741438

2021-06-28T13:46:40

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"""Tests """ from decisions_tree.decision_tree import DecisionTree def test_terminal_node_creation(): """test""" tree = DecisionTree() tree.terminal_node() assert tree.data[0].type == "TERMINAL" assert tree.data[0].expr is None assert tree.data[0].id == 0

[ "jdvelasq@unal.edu.co" ]

jdvelasq@unal.edu.co

066317e9308f2b0748697df1abf9aad98c762cc9

e7fab7a59d8d1a3ee5528e5e7505e428764636cd

/rich/bar.py

65a28dfc8d9b0b5300b60feea35c82b079b2dc12

[ "MIT" ]

permissive

diek/rich

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refs/heads/master

2021-05-19T11:24:57.445723

2020-03-31T15:49:31

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from typing import Union from .console import Console, ConsoleOptions, RenderResult from .measure import Measurement from .segment import Segment from .style import StyleType class Bar: """Renders a (progress) bar. Args: total (float, optional): Number of steps in the bar. Defaults to 100. completed (float, optional): Number of steps completed. Defaults to 0. width (int, optional): Width of the bar, or ``None`` for maximum width. Defaults to None. style (StyleType, optional): Style for the bar background. Defaults to "bar.back". complete_style (StyleType, optional): Style for the completed bar. Defaults to "bar.complete". finished_style (StyleType, optional): Style for a finished bar. Defaults to "bar.done". """ def __init__( self, total: float = 100, completed: float = 0, width: int = None, style: StyleType = "bar.back", complete_style: StyleType = "bar.complete", finished_style: StyleType = "bar.finished", ): self.total = total self.completed = completed self.width = width self.style = style self.complete_style = complete_style self.finished_style = finished_style def __repr__(self) -> str: return f"<Bar {self.completed!r} of {self.total!r}>" @property def percentage_completed(self) -> float: """Calculate percentage complete.""" completed = (self.completed / self.total) * 100.0 completed = min(100, max(0.0, completed)) return completed def update_progress(self, completed: float, total: float = None) -> None: """Update progress with new values. Args: completed (float): Number of steps completed. total (float, optional): Total number of steps, or ``None`` to not change. Defaults to None. """ self.completed = completed self.total = total if total is not None else self.total def __console__(self, console: Console, options: ConsoleOptions) -> RenderResult: completed = min(self.total, max(0, self.completed)) width = min(self.width or options.max_width, options.max_width) bar = "━" half_bar_right = "╸" half_bar_left = "╺" complete_halves = int(width * 2 * completed / self.total) bar_count = complete_halves // 2 half_bar_count = complete_halves % 2 style = console.get_style(self.style) complete_style = console.get_style( self.complete_style if self.completed < self.total else self.finished_style ) if bar_count: yield Segment(bar * bar_count, complete_style) if half_bar_count: yield Segment(half_bar_right * half_bar_count, complete_style) remaining_bars = width - bar_count - half_bar_count if remaining_bars: if not half_bar_count and bar_count: yield Segment(half_bar_left, style) remaining_bars -= 1 if remaining_bars: yield Segment(bar * remaining_bars, style) def __measure__(self, console: Console, max_width: int) -> Measurement: if self.width is not None: return Measurement(self.width, self.width) return Measurement(4, max_width) if __name__ == "__main__": # pragma: no cover console = Console() bar = Bar(width=50, total=100) import time console.show_cursor(False) for n in range(0, 101, 1): bar.update_progress(n) console.print(bar) console.file.write("\r") time.sleep(0.05) console.show_cursor(True) console.print()

[ "willmcgugan@gmail.com" ]

willmcgugan@gmail.com

15906a69c4081328b1d41f3787ea24a51ec6661e

2ff7e53d5e512cd762217ca54317982e07a2bb0c

/eve-8.51.857815/eve/client/script/ui/eveUIProcs.py

9b8e14ca0f30664bf20829b79156c71b233b36df

[]

no_license

nanxijw/Clara-Pretty-One-Dick

66d3d69426642b79e8fd4cc8e0bec23adeeca6d6

50de3488a2140343c364efc2615cf6e67f152be0

refs/heads/master

2021-01-19T09:25:07.555284

2015-02-17T21:49:33

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#Embedded file name: eve/client/script/ui\eveUIProcs.py import uthread import eve.common.script.sys.eveCfg as util import locks import random import svc import carbonui.const as uiconst import localization class EveUIProcSvc(svc.uiProcSvc): """ Manages ActionProcs for UI systems (camera, audio, and UI). """ __guid__ = 'svc.eveUIProcSvc' __replaceservice__ = 'uiProcSvc' __startupdependencies__ = ['cmd'] def Run(self, *args): """ Run the service. First calls into the base, then does local stuff. """ svc.uiProcSvc.Run(self, *args) self.uiCallbackDict = {None: self._NoneKeyIsInvalid_Callback, 'OpenCharacterCustomization': self.__OpenCharacterCustomization_Callback, 'CorpRecruitment': self._CorpRecruitment_Callback, 'OpenCorporationPanel_Planets': self._OpenCorporationPanel_Planets_Callback, 'OpenAuraInteraction': self.cmd.OpenAuraInteraction, 'ExitStation': self.cmd.CmdExitStation, 'OpenFitting': self.cmd.OpenFitting, 'OpenShipHangar': self.cmd.OpenShipHangar, 'OpenCargoBay': self.cmd.OpenCargoHoldOfActiveShip, 'OpenDroneBay': self.cmd.OpenDroneBayOfActiveShip, 'OpenMarket': self.cmd.OpenMarket, 'OpenAgentFinder': self.cmd.OpenAgentFinder, 'OpenStationDoor': self.__OpenStationDoor_Callback, 'EnterHangar': self.cmd.CmdEnterHangar, 'GiveNavigationFocus': self._GiveNavigationFocus_Callback} def _PerformUICallback(self, callbackKey): callback = self.uiCallbackDict.get(callbackKey, None) if callback is not None: uthread.worker('_PerformUICallback_%s' % callbackKey, self._PerformUICallbackTasklet, callbackKey, callback) return True self.LogError('ActionObject.PerformUICallback: Unknown callbackKey', callbackKey) return False def _PerformUICallbackTasklet(self, callbackKey, callback): try: callback() except TypeError as e: self.LogError('ActionObject.PerformUICallback: callbackKey "%s" is associated with a non-callable object: %s' % (callbackKey, callback), e) def _NoneKeyIsInvalid_Callback(self): self.LogError('PerformUICallback called from ActionObject without the callbackKey property (it was None)!') def _CorpRecruitment_Callback(self): if util.IsNPC(session.corpid): self.cmd.OpenCorporationPanel_RecruitmentPane() else: self.cmd.OpenCorporationPanel() def _GiveNavigationFocus_Callback(self): """ Gives the charControl layer application focus """ sm.GetService('navigation').Focus() def _OpenCorporationPanel_Planets_Callback(self): with locks.TempLock('OpenCorporationPanel_Planets', locks.RLock): if sm.GetService('planetSvc').GetMyPlanets(): self.cmd.OpenPlanets() else: systemData = sm.GetService('map').GetSolarsystemItems(session.solarsystemid2) systemPlanets = [] for orbitalBody in systemData: if orbitalBody.groupID == const.groupPlanet: systemPlanets.append(orbitalBody) planetID = systemPlanets[random.randrange(0, len(systemPlanets))].itemID sm.GetService('planetUI').Open(planetID) if not settings.user.suppress.Get('suppress.PI_Info', None): ret, supp = sm.GetService('gameui').MessageBox(localization.GetByLabel('UI/PI/IntroText'), title=localization.GetByLabel('UI/Generic/Information'), buttons=uiconst.OK, modal=False, icon=uiconst.INFO, suppText=localization.GetByLabel('UI/Shared/Suppress1')) if supp: settings.user.suppress.Set('suppress.PI_Info', supp) def __OpenStationDoor_Callback(self): """ Put up a "coming soon" message for establishments """ uicore.Message('CaptainsQuartersStationDoorClosed') def __OpenCharacterCustomization_Callback(self): """ Prompts the user before entering character customization. """ if getattr(sm.GetService('map'), 'busy', False): return if uicore.Message('EnterCharacterCustomizationCQ', {}, uiconst.YESNO, uiconst.ID_YES) == uiconst.ID_YES: self.cmd.OpenCharacterCustomization()

[ "billchang.e@gmail.com" ]

billchang.e@gmail.com

9b744106637d8aa581bb460af23d834cce11ef2d

1a7487e3d8129c3e469b4faabf7daf0284a2cb15

/vedastr/models/bodies/sequences/transformer/decoder.py

5d7daa881078194722165ae99efbb4c5acd6c5e2

[ "Apache-2.0" ]

permissive

kkalla/vedastr

67715bfc05c4ab633fe20f82193e13c21a951a82

d9e237fb8fbd79d36ed314bf9f902796ec210fb4

refs/heads/master

2023-01-03T09:01:18.960161

2020-11-02T09:01:35

284,680,371

0

Apache-2.0

2020-11-02T09:01:37

2020-08-03T11:20:00

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UTF-8

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import logging import torch.nn as nn from .position_encoder import build_position_encoder from .unit import build_decoder_layer from ..registry import SEQUENCE_DECODERS from vedastr.models.weight_init import init_weights logger = logging.getLogger() @SEQUENCE_DECODERS.register_module class TransformerDecoder(nn.Module): def __init__(self, decoder_layer, num_layers, position_encoder=None): super(TransformerDecoder, self).__init__() if position_encoder is not None: self.pos_encoder = build_position_encoder(position_encoder) self.layers = nn.ModuleList([build_decoder_layer(decoder_layer) for _ in range(num_layers)]) logger.info('TransformerDecoder init weights') init_weights(self.modules()) @property def with_position_encoder(self): return hasattr(self, 'pos_encoder') and self.pos_encoder is not None def forward(self, tgt, src, tgt_mask=None, src_mask=None): if self.with_position_encoder: tgt = self.pos_encoder(tgt) for layer in self.layers: tgt = layer(tgt, src, tgt_mask, src_mask) return tgt

[ "jun.sun@media-smart.cn" ]

jun.sun@media-smart.cn

60c4aecd5a79cd0c5d197007fbce2340680664f7

28c79c447c75e2cd4522c93072d99797c71aae63

/BMO/pyamazon.py

e63d235103fe3f405e3f2ffe52a0af6dcf70c3d7

[]

no_license

tsuyukimakoto/bmo

bee8802455a376026879a02f0c12e0c988dbdc20

7593eb6ff9d7061d218e9082f122d11d04533c45

refs/heads/master

2020-03-23T01:38:25.669405

2010-09-23T05:46:12

140,928,630

0

null

UTF-8

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false

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py

# -*- coding: utf8 -*- # # pyamazon.py # pyshelf # # Created by makoto tsuyuki on 07/11/04. # Copyright (c) 2007 everes.net All rights reserved. # from datetime import datetime import httplib, urllib from xml.etree import ElementTree class Item(object): def __init__(self, asin='', sales_rank=0, image='', isbn='', price=0, formattedPrice='', publisher='', title=''): self.asin = asin self.sales_rank = sales_rank self.image = image self.isbn=isbn self.price=price self.formattedPrice = formattedPrice self.publisher=publisher self.title = title self.recommends = [] self.authors = [] def toXml(self): tmp = u'''<?xml version="1.0" encoding="utf-8"?> <ebmo> <title>%(title)s</title> <asin>%(asin)s</asin> <price>%(price)s</price> <author>%(authors)s</author> <rank>%(rank)s</rank> <recommends>%(recs)s</recommends> <created>%(create_date)s</created> </ebmo>''' d = datetime.now() create_date = '%4d-%02d-%02d %02d:%02d:%02d' % (d.year, d.month, d.day, d.hour, d.minute, d.second) return tmp % dict(title=self.title, asin=self.asin, price=self.formattedPrice, authors=u','.join([u'%s' % a for a in self.authors]), rank=self.sales_rank, recs=u'\n'.join( [u'<recommend><rasin>%s</rasin><rtitle>%s</rtitle></recommend>' % (r.asin, r.title) for r in self.recommends]), create_date=create_date) def __unicode__(self): tmp = ''' Title: %(title)s Asin: %(asin)s Price: %(price)s Author: %(authors)s Rank: %(rank)s Recommends: %(recs)s''' return tmp % dict(title=self.title, asin=self.asin, price=self.formattedPrice, authors=u','.join([a for a in self.authors]), rank=self.sales_rank, recs=u'\n'.join( [u'%s(%s)' % (r.title, r.asin,) for r in self.recommends])) class PylibAPIError(Exception): def __init__(self, message): self.message = message def __unicode__(self): return self.message class PylibNotFoundError(Exception): def __init__(self, message): self.message = message def __unicode__(self): return self.message class Recommend(object): def __init__(self, asin, title): self.asin = asin self.title = title def __unicode__(self): return'%s(%s)' % (self.title, self.asin, ) xml = '' def parseXML(xml): def getImageURL(item): node = item.find('LargeImage') if node is not None: return node.find('URL').text return '' def isValid(items): valid = items.find('Request').find('IsValid').text if valid == 'True': return True return False root = ElementTree.fromstring(xml) #print xml items = root.find('Items') if not items: raise PylibAPIError('No Items') if not isValid(items): errors = items.find('Request').find('Errors') error_message = '' errorlist = errors.findall('Error') for e in errorlist: error_message += '%s: %s\n' % (e.find('Code').text, e.find('Message').text) raise PylibAPIError(error_message) item = items.find('Item') if not item: raise PylibNotFoundError('Your request item is not found at Amazon.co.jp') asin = item.find('ASIN') is not None and item.find('ASIN').text or '' sales_rank = item.find('SalesRank') is not None and item.find('SalesRank').text or '' image = getImageURL(item) attributes = item.find('ItemAttributes') author = attributes.findall('Author') isbn = attributes.find('ISBN') is not None and attributes.find('ISBN').text or '' lp = attributes.find('ListPrice') price = lp is not None and lp.find('Amount') and lp.find('Amount').text or '' formattedPrice = lp is not None and lp.find('FormattedPrice') is not None and lp.find('FormattedPrice').text or '' publisher = attributes.find('Publisher') is not None and attributes.find('Publisher').text or '' title = attributes.find('Title').text recommends = [] authors = [] obj = Item(asin=asin, sales_rank=sales_rank, image=image, isbn=isbn, price=price, formattedPrice=formattedPrice, publisher=publisher, title = title) for a in author: authors.append(a.text) if item.find('SimilarProducts') is not None: for p in item.find('SimilarProducts'): r = Recommend(p.find('ASIN').text, p.find('Title').text) recommends.append(r) obj.authors = authors obj.recommends = recommends return obj def getBook(api_key, barcode): return getMedia(api_key, barcode, searchIndex='Books', type='ISBN') def getMusic(api_key, barcode): return getMedia(api_key, barcode, searchIndex='Music', type='UPC') def getVideo(api_key, barcode): return getMedia(api_key, barcode, searchIndex='Video', type='UPC') def getGame(api_key, barcode): return getMedia(api_key, barcode, searchIndex='VideoGames', type='UPC') VERSION = '0.1' API_SERVER = 'ecs.amazonaws.jp:80' def getMedia(api_key, barcode, searchIndex='Book', type='ISBN'): param = {'Service': 'AWSECommerceService', 'AWSAccessKeyId': api_key, 'Operation': 'ItemLookup', 'SearchIndex': searchIndex, 'ItemId': barcode, 'IdType': type, 'ResponseGroup': 'Medium,Reviews,SalesRank,Similarities', 'Version': '2007-10-29'} headers = {"Content-type": "application/x-www-form-urlencoded", "Accept" : "text/plain", "User-agent" : "pylibrary/%s" % (VERSION)} params = urllib.urlencode(param) conn = httplib.HTTPConnection(API_SERVER) conn.request("POST", "/onca/xml", params, headers) response = conn.getresponse() xml = response.read() xml = xml.replace('xmlns="http://webservices.amazon.com/AWSECommerceService/2007-10-29"', '') conn.close() return parseXML(xml) #try: # b = getGame(API_KEY, '4976219754576') #except Exception, e: # print unicode(e)

[ "mtsuyuki@gmail.com" ]

mtsuyuki@gmail.com

b03809df39fd0f8958db0be4187d666d5eb404a3

f340b9f47aaf11d95911074efd16e2878b4608c5

/200119/Word_Ladder_II.py

2e7dde5aba0ce910314145023958a13983352978

[]

no_license

Jsonghh/leetcode

150020d1250a7e13e7387a545b4eb7df0de8f90b

3a83c0b0bcc43f458f7fc54764f60e1104fcc12e

refs/heads/master

2020-11-25T03:12:48.842151

2020-02-11T02:56:58

228,475,001

0

null

UTF-8

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1,596

py

class Solution: def findLadders(self, beginWord: str, endWord: str, wordList: List[str]) -> List[List[str]]: if endWord not in wordList: return [] d = {} results = [] wordList = set(wordList) wordList.add(beginWord) self.bfs(beginWord, endWord, wordList, d) self.dfs(beginWord, endWord, wordList, d, [beginWord], results) return results # use bfs to record the distance to endWord def bfs(self, s, e, l, d): d[e] = 1 q = [e] while q: cur = q.pop(0) for nw in self.fnws(cur, l): if nw in d: continue d[nw] = d[cur] + 1 q.append(nw) # use dfs to update cur_path and append valid paths to the ans def dfs(self, cur, e, l, d, path, results): if cur == e: results.append(list(path)) return for nw in self.fnws(cur, l): if nw not in d or d[nw] != d[cur] - 1: continue path.append(nw) self.dfs(nw, e, l, d, path, results) path.pop() # find possbile next words according to the wordlist def fnws(self, w, l): aph = 'abcdefghijklmnopqrstuvwxyz' nws = [] for i in range(len(w)): for c in aph: if c == w[i]: continue nw = w[:i] + c + w[i + 1:] if nw not in l: continue nws.append(nw) return nwscd

[ "jiesonghe@outlook.com" ]

jiesonghe@outlook.com

3828b38f141bfab5bd065764b8b7c70f84420fc1

e818cf45e9c2f081bb64954f515540bdab25b9d1

/polls/views.py

1e01d3456a36915082fb8d3b3294ec716d39e2bd

[]

no_license

Timothy-py/Polls-API

bfccefbfe0da4ccbc4d8fd39ba4fe14e66b3227d

d354795e4bba43c99bab71020693568e625d677c

refs/heads/master

2020-09-23T22:30:48.575799

2019-12-12T15:07:54

225,603,867

0

null

UTF-8

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727

py

from django.shortcuts import render, get_object_or_404 from .models import Poll from django.http import JsonResponse # Create your views here. def polls_list(request): MAX_OBJECT = 20 polls = Poll.objects.all()[:MAX_OBJECT] data = { "results": list( polls.values("question", "created_by__username", "pub_date") ) } return JsonResponse(data) def polls_detail(request, pk): poll = get_object_or_404(Poll, pk=pk) data = { "results": { "question": poll.question, "created_by": poll.created_by.username, "pub_date": poll.pub_date } } return JsonResponse(data)

[ "adeyeyetimothy33@gmail.com" ]

adeyeyetimothy33@gmail.com

3af06f91d8ff98ed52d65a90a64b68decc2c5ee6

8e84a9e8ecd1c34655abb1c13953847d09a0cfa9

/flaskify/users/utils.py

28dfead42bc9769dda9dcdb2b41b8d19382b5b1b

[]

no_license

pzrsa/flaskify

7e691003c52120024a118f1d4da423dcaf71bf65

2048f985ac146d705ccf0ebecc4aff7557941b90

refs/heads/main

2023-05-29T02:09:05.945742

2021-06-05T12:41:08

342,721,492

0

null

UTF-8

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false

976

py

import os import secrets from flask import current_app, url_for from flask_mail import Message from flaskify import mail from PIL import Image def save_picture(form_picture): random_hex = secrets.token_hex(8) _, f_ext = os.path.splitext(form_picture.filename) picture_fn = random_hex + f_ext picture_path = os.path.join( current_app.root_path, 'static/profile_pics', picture_fn) output_size = (125, 125) i = Image.open(form_picture) i.thumbnail(output_size) i.save(picture_path) return picture_fn def send_reset_email(user): token = user.get_reset_token() msg = Message('Password Reset Request', sender='noreply@demo.com', recipients=[user.email]) msg.body = f"""To reset your password, please visit this link: {url_for('users.reset_token', token=token, _external=True)} If you did not make this request, don't worry. Just ignore this email and no changes will be made. """ mail.send(msg)

[ "parsamesg@gmail.com" ]

parsamesg@gmail.com

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/cov_search/migrations/0002_auto_20150629_0427.py

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[]

no_license

dgrant/city_of_vancouver_programs_search

7295de3aad1ab3885c9b30e086230a6fff740791

33dfca03ccd434b39f01981890b195b384c1a2e0

refs/heads/master

2023-07-09T09:59:03.417301

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2023-09-05T20:01:58

2015-07-01T09:03:22

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py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('cov_search', '0001_initial'), ] operations = [ migrations.AlterField( model_name='season', name='name', field=models.CharField(unique=True, max_length=30), ), ]

[ "davidgrant@gmail.com" ]

davidgrant@gmail.com

e06dfef674f9aeccead93fa370a718e85f13e148

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/azure-mgmt-monitor/azure/mgmt/monitor/models/sender_authorization_py3.py

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lmazuel/azure-sdk-for-python

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refs/heads/master

2022-08-16T02:32:14.070707

2018-03-29T17:16:15

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# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class SenderAuthorization(Model): """the authorization used by the user who has performed the operation that led to this event. This captures the RBAC properties of the event. These usually include the 'action', 'role' and the 'scope'. :param action: the permissible actions. For instance: microsoft.support/supporttickets/write :type action: str :param role: the role of the user. For instance: Subscription Admin :type role: str :param scope: the scope. :type scope: str """ _attribute_map = { 'action': {'key': 'action', 'type': 'str'}, 'role': {'key': 'role', 'type': 'str'}, 'scope': {'key': 'scope', 'type': 'str'}, } def __init__(self, *, action: str=None, role: str=None, scope: str=None, **kwargs) -> None: super(SenderAuthorization, self).__init__(**kwargs) self.action = action self.role = role self.scope = scope

[ "lmazuel@microsoft.com" ]

lmazuel@microsoft.com

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/moodledata/vpl_data/18/usersdata/63/6289/submittedfiles/maiormenor.py

c4ed26b8ed5ca3e8a1e42c244d6514c6f567a004

[]

no_license

rafaelperazzo/programacao-web

95643423a35c44613b0f64bed05bd34780fe2436

170dd5440afb9ee68a973f3de13a99aa4c735d79

refs/heads/master

2021-01-12T14:06:25.773146

2017-12-22T16:05:45

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# -*- coding: utf-8 -*- from __future__ import division import math a = input('Digite o número 1: ') b = input('Digite o número 2: ') c = input('Digite o número 3: ') d = input('Digite o número 4: ') e = input('Digite o número 5: ') if a<b and a<c and a<d and a<e: print('%d : %a') if b<a and b<c and b<d and b<e: print('%d : %b') if c<a and c<b and c<d and c<e: print('%d : %c') if d<a and d<b and d<c and d<e: print('%d : %d') if e<a and e<b and e<c and e<d: print('%d : %e') if a>b and a>c and a>d and a>e: print('%d : %a') if b>a and b>c and b>d and b>e: print('%d : %b') if c>a and c>b and c>d and c>e: print('%d : %c') if d>a and d>b and d>c and d>e: print('%d : %d') if e>a and e>b and e>c and e>d: print('%d : %e')

[ "rafael.mota@ufca.edu.br" ]

rafael.mota@ufca.edu.br

e6c0583c3b6f7c457ae78296d323d908036191f0

d697fe447506ce4c179d1c77144f84b525304cec

/ch4_populations_cdf.py

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[]

no_license

leosartaj/thinkstats

a97004d1e906660877d1244844f22ab01b13d7d6

6345d88e113fa4b347bd45d519c0fb6813402cab

refs/heads/master

2021-01-10T08:44:09.168668

2015-12-07T04:28:05

47,359,632

0

null

UTF-8

Python

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264

py

import sys import populations import Cdf import myplot def main(filename): pops = populations.ReadData(filename) cdf = Cdf.MakeCdfFromList(pops) myplot.Cdf(cdf, transform='pareto') myplot.Show() if __name__ == '__main__': main(sys.argv[1])

[ "singhsartaj94@gmail.com" ]

singhsartaj94@gmail.com

6b824b3f9703c6ad5c7f14d9619e1ae1dba1d2c3

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/tests/test_common.py

2e006a77d00e10bda67230d546cefc19bece66e9

[]

no_license

Pebaz/mini-rh-project

bdaeef15e1872c7411f274f2949c49d4cb0fdb50

d4b219ddb725cf53d08ed46abf3f973d06cc03ce

refs/heads/master

2020-07-01T18:45:49.437877

2019-08-15T02:12:33

201,260,751

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""" This needs to be imported on every test file so that the test files can import modules from the `rh` package. """ import sys sys.path.append('.') from rh.data import * top_10_genres_by_profit = get_top_10_genres_by_profit() top_10_actors_by_profit = get_top_10_actors_by_profit() top_10_directors_by_profit = get_top_10_directors_by_profit()

[ "pebazium@gmail.com" ]

pebazium@gmail.com

96519c0d5f429ea1fea9725f22f98c7d3c367fc6

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/tests/test_project.py

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permissive

gzcf/polyaxon-schemas

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a381280cd7535f64158d52f0a9eff2afec997d90

refs/heads/master

2020-03-10T04:55:48.023279

2018-04-12T12:47:53

129,204,842

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MIT

2018-04-12T06:37:36

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# -*- coding: utf-8 -*- from __future__ import absolute_import, division, print_function import uuid from unittest import TestCase from marshmallow import ValidationError from tests.utils import assert_equal_dict from polyaxon_schemas.experiment import ExperimentConfig from polyaxon_schemas.project import ExperimentGroupConfig, ProjectConfig from polyaxon_schemas.utils import local_now class TestProjectConfigs(TestCase): def test_validate_project_name_config(self): config_dict = {'name': 'test sdf', 'description': '', 'is_public': True} with self.assertRaises(ValidationError): ProjectConfig.from_dict(config_dict) def test_project_config(self): config_dict = { 'name': 'test', 'description': '', 'is_public': True, 'has_code': True, 'has_tensorboard': True, 'num_experiments': 0, 'num_independent_experiments': 0, 'num_experiment_groups': 0, 'created_at': local_now().isoformat(), 'updated_at': local_now().isoformat() } config = ProjectConfig.from_dict(config_dict) config_to_dict = config.to_dict() config_to_dict.pop('experiment_groups', None) config_to_dict.pop('experiments', None) config_to_dict.pop('has_notebook', None) config_to_dict.pop('unique_name', None) config_to_dict.pop('user', None) config_to_dict.pop('uuid', None) assert config_to_dict == config_dict config_dict.pop('description') config_dict.pop('updated_at') config_dict.pop('has_code') config_to_dict = config.to_light_dict() config_to_dict.pop('has_notebook', None) config_to_dict.pop('unique_name', None) assert config_to_dict == config_dict config_to_dict = config.to_dict(humanize_values=True) assert config_to_dict.pop('created_at') == 'a few seconds ago' assert config_to_dict.pop('updated_at') == 'a few seconds ago' config_to_dict = config.to_light_dict(humanize_values=True) assert config_to_dict.pop('created_at') == 'a few seconds ago' def test_project_experiments_and_groups_config(self): uuid_value = uuid.uuid4().hex config_dict = {'name': 'test', 'description': '', 'is_public': True, 'experiment_groups': [ ExperimentGroupConfig(content='content', uuid=uuid_value, project=uuid_value).to_dict()], 'experiments': [ ExperimentConfig(config={}, uuid=uuid_value, project=uuid_value).to_dict()]} config = ProjectConfig.from_dict(config_dict) assert_equal_dict(config_dict, config.to_dict()) config_dict.pop('description') config_dict.pop('experiment_groups') config_dict.pop('experiments') assert_equal_dict(config_dict, config.to_light_dict()) def test_experiment_group_config(self): uuid_value = uuid.uuid4().hex config_dict = {'sequence': 1, 'content': 'some content', 'uuid': uuid_value, 'project': uuid_value, 'project_name': 'user.name', 'num_experiments': 0, 'created_at': local_now().isoformat(), 'updated_at': local_now().isoformat(), 'experiments': [ ExperimentConfig(config={}, uuid=uuid_value, experiment_group=uuid_value, project=uuid_value).to_dict()]} config = ExperimentGroupConfig.from_dict(config_dict) config_to_dict = config.to_dict() config_to_dict.pop('concurrency', None) config_to_dict.pop('description', None) config_to_dict.pop('num_failed_experiments', None) config_to_dict.pop('num_pending_experiments', None) config_to_dict.pop('num_running_experiments', None) config_to_dict.pop('num_scheduled_experiments', None) config_to_dict.pop('num_stopped_experiments', None) config_to_dict.pop('num_succeeded_experiments', None) config_to_dict.pop('unique_name', None) config_to_dict.pop('user', None) assert config_to_dict == config_dict config_dict.pop('content') config_dict.pop('uuid') config_dict.pop('project') config_dict.pop('updated_at') config_dict.pop('sequence') config_dict.pop('experiments') config_dict.pop('project_name') assert_equal_dict(config_dict, config.to_light_dict()) config_to_dict = config.to_dict(humanize_values=True) assert config_to_dict.pop('created_at') == 'a few seconds ago' assert config_to_dict.pop('updated_at') == 'a few seconds ago' config_to_dict = config.to_light_dict(humanize_values=True) assert config_to_dict.pop('created_at') == 'a few seconds ago'

[ "mouradmourafiq@gmail.com" ]

mouradmourafiq@gmail.com

8c9dc482eca7116299722e5d57d347fbc4a3126c

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/kagenomise/products/vocabulary/clothing_sizes.py

cdce81b68c21b87136cab1515c946cbf0052a496

[]

no_license

kagesenshi/kagenomise.products

cbe29c424b94e8917203254824a3e878aa69f439

3eb9e3a74d472e0bd7daa03e1dae4e5aa34a7818

refs/heads/master

2021-01-15T10:47:49.199010

2013-05-19T10:58:42

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from five import grok from zope.schema.interfaces import IContextSourceBinder from zope.schema.vocabulary import SimpleVocabulary, SimpleTerm from zope.schema.interfaces import IVocabularyFactory from zope.component import getUtility from z3c.formwidget.query.interfaces import IQuerySource class ClothingSizes(grok.GlobalUtility): grok.name('kagenomise.products.clothing_sizes') grok.implements(IVocabularyFactory) def __call__(self, context): return SimpleVocabulary.fromValues( ['S','M','L','XL','XXL', 'XXXL'] )

[ "izhar@inigo-tech.com" ]

izhar@inigo-tech.com

c8334fd40f30e0a61067cbccc1a7767772698b3a

9f6fda1683fd3993c62b7c04cbbe54d3f8b932f2

/Demo/MysqlDemo/demo.py

e4fb2e7d0fc14756ace4fc3e8faed6dc79e57f53

[]

no_license

dajun928/Demo

89f457bd324f1903ac217223a6f712af18e10bef

8318cee62b0508c76ab1106961c0247b5f511e94

refs/heads/master

2020-03-22T14:28:14.714335

2018-07-08T16:59:51

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null

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# -*- coding:utf-8 -*- import MySQLdb conn = MySQLdb.connect(host='127.0.0.1', port=3306, user='root', passwd='1234', db='test') cur = conn.cursor() # import records # # db = records.Database('mysql://root:1234@127.0.0.1:3306/test') # rows = db.query('select * from stu') # or db.query_file('sqls/active-users.sql') # print rows.dataset

[ "1663177102@qq.com" ]

1663177102@qq.com

99fab05bc0eea137e4094a3a35c913987d061372

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/app/models.py

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[ "MIT" ]

permissive

MichelAtieno/Personal-Blog

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refs/heads/master

2020-03-28T15:38:29.031020

2018-09-17T11:45:02

148,611,954

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null

UTF-8

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from . import db, login_manager from flask_login import UserMixin from werkzeug.security import generate_password_hash,check_password_hash @login_manager.user_loader def load_user(user_id): return User.query.get(int(user_id)) class User(UserMixin,db.Model): __tablename__ = 'users' id = db.Column(db.Integer,primary_key = True) username = db.Column(db.String(255)) email = db.Column(db.String(255)) pass_secure = db.Column(db.String(255)) @property def password(self): raise AttributeError('You cannot read the password attribute') @password.setter def password(self, password): self.pass_secure = generate_password_hash(password) def verify_password(self,password): return check_password_hash(self.pass_secure,password) def __repr__(self): return f'User {self.username}' class Subscribers(db.Model): __tablename__='subscribers' id = db.Column(db.Integer,primary_key = True) email = db.Column(db.String(255)) def save_subscriber(self): db.session.add(self) db.session.commit() @classmethod def get_subscribers(cls): subscribers=Subscribers.query.all() return subscribers def __repr__(self): return f'Subscribers {self.email}' class BlogPost(db.Model): __tablename__='blogs' id = db.Column(db.Integer,primary_key = True) title = db.Column(db.String()) blog_post = db.Column(db.String) blog_pic = db.Column(db.String) photo_url = db.Column(db.String) comment = db.relationship('Comment',backref='blog',lazy='dynamic') user_id = db.Column(db.Integer, db.ForeignKey('users.id')) def save_blog(self): db.session.add(self) db.session.commit() @classmethod def get_blog(cls,id): blog = BlogPost.query.filter_by(id = id).first() return blog @classmethod def get_all_blogs(cls): blogs = BlogPost.query.order_by('-id').all() return blogs class Comment(db.Model): __tablename__='comments' id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String()) comment_content = db.Column(db.String()) blog_id = db.Column(db.Integer, db.ForeignKey('blogs.id')) user_id = db.Column(db.Integer, db.ForeignKey('users.id')) def save_comment(self): db.session.add(self) db.session.commit() @classmethod def get_single_comment(cls,id_blog,id): comment = Comment.query.filter_by(blog_id=id_blog,id=id).first() return comment @classmethod def get_all_comments(cls,id): comments = Comment.query.filter_by(blog_id=id).order_by('-id').all() return comments

[ "mishqamish@gmail.com" ]

mishqamish@gmail.com

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/config/settings.py

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leroyg/build-a-saas-app-with-flask

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refs/heads/master

2020-12-25T21:55:36.551160

2015-10-29T15:10:05

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# -*- coding: utf-8 -*- from os import path from datetime import timedelta from celery.schedules import crontab # This value is used for the following properties, # it really should be your module's name. # Database name # Cache redis prefix APP_NAME = 'catwatch' APP_ROOT = path.join(path.dirname(path.abspath(__file__)), '..') # App settings, most settings you see here will change in production. SECRET_KEY = 'pickabettersecret' DEBUG = True TESTING = False LOG_LEVEL = 'DEBUG' # You will need to disable this to get Stripe's webhooks to work because you'll # likely end up using tunneling tooling such as ngrok so the endpoints are # reachable outside of your private network. # # The problem with this is, Flask won't allow any connections to the ngrok # url with the SERVER_NAME set to localhost:8000. However if you comment out # the SERVER_NAME below then webbooks will work but now url_for will not work # inside of email templates. # # A better solution will turn up in the future. SERVER_NAME = 'localhost:8000' # Public build path. Files in this path will be accessible to the internet. PUBLIC_BUILD_PATH = path.join(APP_ROOT, 'build', 'public') # Flask-Webpack (assets) settings. WEBPACK_MANIFEST_PATH = path.join(APP_ROOT, 'build', 'manifest.json') # Babel i18n translations. ACCEPT_LANGUAGES = ['en', 'es'] LANGUAGES = { 'en': 'English', 'es': u'Español' } BABEL_DEFAULT_LOCALE = 'en' # Seed settings. SEED_ADMIN_EMAIL = 'dev@localhost.com' # Database settings, # The username and password must match what's in docker-compose.yml for dev. db_uri = 'postgresql://catwatch:bestpassword@localhost:5432/{0}' SQLALCHEMY_DATABASE_URI = db_uri.format(APP_NAME) SQLALCHEMY_POOL_SIZE = 5 # Cache settings. CACHE_TYPE = 'redis' CACHE_REDIS_URL = 'redis://localhost:6379/0' CACHE_KEY_PREFIX = APP_NAME # Celery settings. CELERY_BROKER_URL = 'redis://localhost:6379/0' CELERY_RESULT_BACKEND = 'redis://localhost:6379/0' CELERY_REDIS_MAX_CONNECTIONS = 5 CELERY_ACCEPT_CONTENT = ['json'] CELERY_TASK_SERIALIZER = 'json' CELERY_RESULT_SERIALIZER = 'json' # Celery recurring scheduled tasks. CELERYBEAT_SCHEDULE = { 'mark-soon-to-expire-credit-cards': { 'task': 'catwatch.blueprints.billing.tasks.mark_old_credit_cards', 'schedule': crontab(hour=12, minute=1) }, 'mark-invalid-coupons': { 'task': 'catwatch.blueprints.billing.tasks.expire_old_coupons', 'schedule': crontab(hour=12, minute=2) }, } # Login settings. REMEMBER_COOKIE_DURATION = timedelta(days=90) # Mail settings. MAIL_DEFAULT_SENDER = 'support@catwatch.com' MAIL_SERVER = 'smtp.gmail.com' MAIL_PORT = 587 MAIL_USE_TLS = True MAIL_USE_SSL = False MAIL_USERNAME = 'you@gmail.com' MAIL_PASSWORD = 'awesomepassword' # External end points. ENDPOINT_CADVISOR = 'http://localhost:8080/containers/' ENDPOINT_FLOWER = 'http://localhost:8081' # Stripe settings. # # API keys, NOTE: you should NOT supply them in this config, put them # in an instance config file, such as: instance/settings.py # # They are only listed below to act as documentation. STRIPE_SECRET_KEY = None STRIPE_PUBLISHABLE_KEY = None # The Stripe API version to use. More information can be found on their docs: # https://stripe.com/docs/api/python#versioning STRIPE_API_VERSION = '2015-01-26' # Documentation for each plan field below can be found on Stripe's API docs: # https://stripe.com/docs/api#create_plan # # After supplying both API keys and plans, you must sync the plans by running: # run stripe sync_plans # # If you are using TEST keys then the plans will be set to livemode: False # If you are using REAL keys then the plans be set to livemode: True # # What the above means is, when you ship your app in production you must sync # your plans at least once to activate them on your real keys. STRIPE_PLANS = { '0': { 'id': 'bronze', 'name': 'Bronze', 'amount': 100, 'currency': 'usd', 'interval': 'month', 'interval_count': 1, 'trial_period_days': 14, 'statement_descriptor': 'BRONZE MONTHLY' }, '1': { 'id': 'gold', 'name': 'Gold', 'amount': 500, 'currency': 'usd', 'interval': 'month', 'interval_count': 1, 'trial_period_days': 14, 'statement_descriptor': 'GOLD MONTHLY', 'metadata': { 'recommended': True } }, '2': { 'id': 'platinum', 'name': 'Platinum', 'amount': 1000, 'currency': 'usd', 'interval': 'month', 'interval_count': 1, 'trial_period_days': 14, 'statement_descriptor': 'PLATINUM MONTHLY' } } # Twitter settings. # # API keys, NOTE: you should NOT supply them in this config, put them # in an instance config file, such as: instance/settings.py # # They are only listed below to act as documentation. TWITTER_CONSUMER_KEY = None TWITTER_CONSUMER_SECRET = None TWITTER_ACCESS_TOKEN = None TWITTER_ACCESS_SECRET = None # Broadcast (websocket server) settings. # # NOTE: you should NOT supply the PUSH_TOKEN/BROADCAST_INTERNAL_URL here, # put them in an instance config file, such as: instance/settings.py BROADCAST_PUBLIC_URL = 'http://localhost:4242/stream' BROADCAST_INTERNAL_URL = None BROADCAST_PUSH_TOKEN = None

[ "nick.janetakis@gmail.com" ]

nick.janetakis@gmail.com

3fb6fa665a6e2c6aba0084149a226f9dde2c26d5

8466ebe93688e1dbf60fce7dec98caa8399877ae

/python/19-counting-sundays.py

36ac9e6c3bb5d746f46c6e9658438b2b106cd394

[]

no_license

alextanhongpin/project-euler

1b524ea98234bd334fbd3b6a582c35713ab5e810

87311c95fdc7f3ef59344b5d8a0b0a0e70b439a1

refs/heads/master

2020-05-24T00:08:25.376061

2017-03-27T07:29:54

84,804,081

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false

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""" Problem 19 - Counting Sundays """ from datetime import date # Monday is 0, # Sunday is 6 def main(): start = date(1901, 1, 1) end = date(2000, 12, 31) number_of_months = (end.year - start.year + 1) * 12 is_sunday = 0 start_year = 1901 for month in range(number_of_months): current_month = (month + 1) % 12 if date(start_year, 12 if current_month is 0 else current_month, 1).weekday() == 6: print date(start_year, 12 if current_month is 0 else current_month, 1) is_sunday += 1 if current_month == 0: start_year += 1 print "The number of sundays that fell for the first of the month is:", is_sunday if __name__ == '__main__': import timeit ITERATIONS = 100 MESSAGE = "Function takes {} s to complete." print MESSAGE.format(timeit.timeit("main()", number=ITERATIONS, setup="from __main__ import main") / ITERATIONS)

[ "alextan220990@gmail.com" ]

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# Generated by Django 3.1.7 on 2021-04-01 21:42 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('accounts', '0021_auto_20210401_2127'), ] operations = [ migrations.AlterField( model_name='userlocation', name='user', field=models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, related_name='location', to=settings.AUTH_USER_MODEL, verbose_name='Пользователь'), ), ]

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# -*- coding: utf-8 -*- """Identity Services Engine getActiveList data model. Copyright (c) 2021 Cisco and/or its affiliates. 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 import json from builtins import * import fastjsonschema from ciscoisesdk.exceptions import MalformedRequest class JSONSchemaValidatorA6C71A1E4D2597EA1B5533E9F1B438F(object): """getActiveList request schema definition.""" def __init__(self): super(JSONSchemaValidatorA6C71A1E4D2597EA1B5533E9F1B438F, self).__init__() self._validator = fastjsonschema.compile(json.loads( '''{ "$schema": "http://json-schema.org/draft-04/schema#", "properties": { "noOfActiveSession": { "type": "integer" } }, "required": [ "noOfActiveSession" ], "type": "object" }'''.replace("\n" + ' ' * 16, '') )) def validate(self, request): try: self._validator(request) except fastjsonschema.exceptions.JsonSchemaException as e: raise MalformedRequest( '{} is invalid. Reason: {}'.format(request, e.message) )

[ "wastorga@altus.co.cr" ]

wastorga@altus.co.cr

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/nagerep/urls.py

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fishilico/nagerep

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from django.conf.urls import patterns, include, url # Enable the admin from django.contrib import admin admin.autodiscover() urlpatterns = patterns('', )

[ "nicolas.iooss_git@polytechnique.org" ]

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/optic_store/patches/v0_8/correct_return_dn_ref_si.py

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# -*- coding: utf-8 -*- # Copyright (c) 2019, 9T9IT and contributors # For license information, please see license.txt from __future__ import unicode_literals import frappe def execute(): dnis = frappe.db.sql( """ SELECT dni.name AS name, fdni.against_sales_invoice AS against_sales_invoice, fdni.si_detail AS si_detail FROM `tabDelivery Note Item` AS dni LEFT JOIN `tabDelivery Note` AS dn ON dn.name = dni.parent LEFT JOIN `tabSales Invoice` AS si ON si.name = dni.against_sales_invoice LEFT JOIN `tabDelivery Note Item` AS fdni ON fdni.parent = dn.return_against AND fdni.idx = dni.idx WHERE dn.docstatus < 2 AND dn.is_return = 1 AND si.is_return = 1 """, as_dict=1, ) for dni in dnis: frappe.db.set_value( "Delivery Note Item", dni.get("name"), "against_sales_invoice", dni.get("against_sales_invoice"), ) frappe.db.set_value( "Delivery Note Item", dni.get("name"), "si_detail", dni.get("si_detail") )

[ "sun@libermatic.com" ]

sun@libermatic.com

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/hw1_code/k.py

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[]

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fredshentu/cs189

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refs/heads/master

2021-01-10T22:54:06.812233

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from mnist import MNIST import sklearn.metrics as metrics import numpy as np NUM_CLASSES = 10 def load_dataset(): mndata = MNIST('./data/') X_train, labels_train = map(np.array, mndata.load_training()) X_test, labels_test = map(np.array, mndata.load_testing()) X_train = X_train/255.0 X_test = X_test/255.0 X_train = np.matrix.transpose(X_train) X_test = np.matrix.transpose(X_test) return (X_train, labels_train), (X_test, labels_test) def train(X_train, y_train, reg=0): ''' Build a model from X_train -> y_train ''' XXt=np.dot(X_train,np.matrix.transpose(X_train)) inverse = np.linalg.inv( XXt + 0.1*np.identity(784)) return np.dot(inverse,np.dot(X_train,one_hot(y_train))) def one_hot(labels_train): '''Convert categorical labels 0,1,2,....9 to standard basis vectors in R^{10} ''' return np.array([[1 if i == labels_train[k] else 0 for i in range(10)] for k in range(len(labels_train))]) #actually this way we get the transposition of Y def predict(model, X): ''' From model and data points, output prediction vectors ''' pred=np.dot(np.matrix.transpose(model),X) return [np.argmax(i) for i in np.matrix.transpose(pred)]#get a single array of the prediction y if __name__ == "__main__": (X_train, labels_train), (X_test, labels_test) = load_dataset() model = train(X_train, labels_train) y_train = one_hot(labels_train) y_test = one_hot(labels_test) pred_labels_train = predict(model, X_train) pred_labels_test = predict(model, X_test) print("Train accuracy: {0}".format(metrics.accuracy_score(labels_train, pred_labels_train))) print("Test accuracy: {0}".format(metrics.accuracy_score(labels_test, pred_labels_test)))

[ "fred960315@gmail.com" ]

fred960315@gmail.com