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<|fim_prefix|># repo: Osso/smartytotwig path: /tests/test_smarty_grammar.py """ It's easy to screw up other rules when modifying the underlying grammar. These unit tests test various smarty statements, to make refactoring the grammar more sane. """ from smartytotwig import parse_string from smartytotwig.twig_printer i...
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{ "lang": "python", "repo": "Osso/smartytotwig", "path": "/tests/test_smarty_grammar.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ :type sentence: str :rtype: bool """<|fim_prefix|># repo: sidmahurkar/Leetcode-Practice path: /Python/easy/1832.py class Solution(object): def checkIfPangram(self, sentence): <|fim_middle|> for i in sentence: a.append(i) ...
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{ "lang": "python", "repo": "sidmahurkar/Leetcode-Practice", "path": "/Python/easy/1832.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: sidmahurkar/Leetcode-Practice path: /Python/easy/1832.py class Solution(object): def checkIfPangram(self, sentence): <|fim_suffix|> """ :type sentence: str :rtype: bool """<|fim_middle|> for i in sentence: a.append(i) ...
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{ "lang": "python", "repo": "sidmahurkar/Leetcode-Practice", "path": "/Python/easy/1832.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>admin.site.register(Category) admin.site.register(Ingredient)<|fim_prefix|># repo: Posdelan/graphQL_cookbook path: /cookbook/cookbook/ingredients/admin.py # -*- coding: utf-8 -*- from __future__ import unicode_literals <|fim_middle|>from django.contrib import admin from cookbook.ingredients.models impor...
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{ "lang": "python", "repo": "Posdelan/graphQL_cookbook", "path": "/cookbook/cookbook/ingredients/admin.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: Posdelan/graphQL_cookbook path: /cookbook/cookbook/ingredients/admin.py # -*- coding: utf-8 -*- from __future__ import unicode_literals <|fim_suffix|>admin.site.register(Category) admin.site.register(Ingredient)<|fim_middle|>from django.contrib import admin from cookbook.ingredients.models impor...
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{ "lang": "python", "repo": "Posdelan/graphQL_cookbook", "path": "/cookbook/cookbook/ingredients/admin.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: irk2adm/pythontutor path: /11/11_Pedigree.py # Задача «Родословная: подсчет уровней» # В генеалогическом древе у каждого человека, кроме родоначальника, есть ровно один родитель. # Каждом элементу дерева сопоставляется целое неотрицательное число, называемое высотой. У родоначальника высота равна...
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{ "lang": "python", "repo": "irk2adm/pythontutor", "path": "/11/11_Pedigree.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>heights = {} for man in set(p_tree.keys()).union(set(p_tree.values())): heights[man] = height(man) for key, value in sorted(heights.items()): print(key, value)<|fim_prefix|># repo: irk2adm/pythontutor path: /11/11_Pedigree.py # Задача «Родословная: подсчет уровней» # В генеалогическом древе у к...
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{ "lang": "python", "repo": "irk2adm/pythontutor", "path": "/11/11_Pedigree.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> difference = 0 deliveries_1st = data['innings'][0]['1st innings']['deliveries'] deliveries_2nd = data['innings'][1]['2nd innings']['deliveries'] for d in deliveries_1st: for k, m in d.items(): if(m.get('extras') != None): for e in m['extras'].values(): ...
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{ "lang": "python", "repo": "amrutasawant13/python_getting_started_project", "path": "/q07_extras/build.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: amrutasawant13/python_getting_started_project path: /q07_extras/build.py # %load q07_extras/build.py # Default Imports from greyatomlib.python_getting_started.q01_read_data.build import read_data data = read_data() # Your Solution def extras_runs(data): <|fim_suffix|> difference = 0 deliv...
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{ "lang": "python", "repo": "amrutasawant13/python_getting_started_project", "path": "/q07_extras/build.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> difference = inning2_extras - inning1_extras return difference # print(inning1_extras) # print(inning2_extras) extras_runs(data)<|fim_prefix|># repo: amrutasawant13/python_getting_started_project path: /q07_extras/build.py # %load q07_extras/build.py # Default Imports from greyatomlib.pyt...
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{ "lang": "python", "repo": "amrutasawant13/python_getting_started_project", "path": "/q07_extras/build.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>total = 0 for i in range(n): if v[i] > c[i]: total += (v[i] - c[i]) print(total)<|fim_prefix|># repo: kotaro0522/python path: /procon20190427/b.py n = int(input()) v = [int(i) for i in input().split()] <|fim_middle|>c = [int(i) for i in input().split()]
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{ "lang": "python", "repo": "kotaro0522/python", "path": "/procon20190427/b.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: kotaro0522/python path: /procon20190427/b.py n = int(input()) v = [int(i) for i in input().split()] <|fim_suffix|>for i in range(n): if v[i] > c[i]: total += (v[i] - c[i]) print(total)<|fim_middle|>c = [int(i) for i in input().split()] total = 0
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{ "lang": "python", "repo": "kotaro0522/python", "path": "/procon20190427/b.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: fjl121029xx/MyPyspark path: /ml/10-lr/lr_roc_auc.py #!/usr/bin/env python # -*- coding:utf-8 -*- __author__ = 'fjl' import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.preprocessing import StandardScaler import...
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{ "lang": "python", "repo": "fjl121029xx/MyPyspark", "path": "/ml/10-lr/lr_roc_auc.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>if __name__ == '__main__': column = ['Sample code number', 'Clump Thickness ', 'Uniformity of Cell Size', 'Uniformity of Cell Shape', 'Marginal Adhesion', 'Single Epithelial Cell Size ', 'Bare Nuclei ', 'Bland Chromatin', 'Normal Nucleoli', 'Mitoses', 'Class'] lr = LRR...
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{ "lang": "python", "repo": "fjl121029xx/MyPyspark", "path": "/ml/10-lr/lr_roc_auc.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>#3. 훈련 model.fit(x_train, y_train) #4. 평가, 예측 acc = model.score(x_test, y_test) print("acc : ", acc) print("최적의 매개변수 : ", model.best_estimator_) # acc : 0.9666666666666667 # 최적의 매개변수 : Pipeline(steps=[('scaler', MinMaxScaler()), # ('XGB', # XGBClassifier(base_score=0...
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{ "lang": "python", "repo": "MJK0211/bit_seoul", "path": "/ml/m26_homework1_xgb_iris.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: MJK0211/bit_seoul path: /ml/m26_homework1_xgb_iris.py # pipe라인 까지 구성할 것 import numpy as np import pandas as pd from sklearn.datasets import load_iris from xgboost import XGBClassifier, XGBRegressor, plot_importance from sklearn.datasets import load_boston from sklearn.model_selection import trai...
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{ "lang": "python", "repo": "MJK0211/bit_seoul", "path": "/ml/m26_homework1_xgb_iris.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>#4. 평가, 예측 acc = model.score(x_test, y_test) print("acc : ", acc) print("최적의 매개변수 : ", model.best_estimator_) # acc : 0.9666666666666667 # 최적의 매개변수 : Pipeline(steps=[('scaler', MinMaxScaler()), # ('XGB', # XGBClassifier(base_score=0.5, booster='gbtree', # ...
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{ "lang": "python", "repo": "MJK0211/bit_seoul", "path": "/ml/m26_homework1_xgb_iris.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: abtheo/Genetic-Wifi-Optimisation path: /Genetics.py import Maps import numpy as np #CONSTANT DECLARATIONS SPOTNUM = 20 #Dimensions TILESIZE = 10 MAPWIDTH = 64 MAPHEIGHT = 64 #Constants representing map resources NONE = 0 LOW = 1 MED = 2 HIGH = 3 SPOT = 4 WALL = 5 #Class for Wifi hotspots ...
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{ "lang": "python", "repo": "abtheo/Genetic-Wifi-Optimisation", "path": "/Genetics.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>#Class comprising the population class iMap: def __init__(self,tilemap,spotList=None): if spotList == None: self.spotList = self.generateSpots(SPOTNUM) else: self.spotList = spotList self.tilemap = np.copy(tilemap) self.fitness = 0 ...
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{ "lang": "python", "repo": "abtheo/Genetic-Wifi-Optimisation", "path": "/Genetics.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: chojiwon1727/lab_python path: /lec07_file/file01.py """ os 모듈의 변수와 함수들 """ import os # CWD: Current Working Directory(현재 작업 디렉토리/폴더) print(os.getcwd()) print(os.name) if os.name == 'nt': # windows os인 경우 file_path = '.\\temp\\temp.txt' else: # windows os가 아닌 경우 file_p...
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{ "lang": "python", "repo": "chojiwon1727/lab_python", "path": "/lec07_file/file01.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>with os.scandir('.') as my_dir: for entry in my_dir: print(entry.name, '\t', entry.is_file()) # 파일(디렉토리) 이름 변경 try: os.rename('temp', 'test') except FileNotFoundError: print('temp 폴더가 없음') try: os.rmdir('test') except FileNotFoundError: print('삭제 권한 없음') try: os.mkdir('t...
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{ "lang": "python", "repo": "chojiwon1727/lab_python", "path": "/lec07_file/file01.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>if __name__ == '__main__': cmdline.execute(['scrapy', 'crawl', 'bizvibe'])<|fim_prefix|># repo: haisimao/workspace path: /Bizvibe_Selenium_scrapy/Bizvibe_scrapy/manage.py from scrapy import cmdline <|fim_middle|>cmdline.execute(['scrapy', 'crawl', 'bizvibe'])
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{ "lang": "python", "repo": "haisimao/workspace", "path": "/Bizvibe_Selenium_scrapy/Bizvibe_scrapy/manage.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: haisimao/workspace path: /Bizvibe_Selenium_scrapy/Bizvibe_scrapy/manage.py from scrapy import cmdline <|fim_suffix|>if __name__ == '__main__': cmdline.execute(['scrapy', 'crawl', 'bizvibe'])<|fim_middle|>cmdline.execute(['scrapy', 'crawl', 'bizvibe'])
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{ "lang": "python", "repo": "haisimao/workspace", "path": "/Bizvibe_Selenium_scrapy/Bizvibe_scrapy/manage.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: wangpengxu2020/TasNet path: /main.py import torch from torch import nn # from tensorboardX import SummaryWriter import time import os from MyDataset_HDF5 import MyDataset from conv_tasnet import ConvTasNet from conv_tasnet import Encoder from conv_tasnet import Decoder # class Custom...
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{ "lang": "python", "repo": "wangpengxu2020/TasNet", "path": "/main.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> t1 = time.time() for epoch in range(EPOCH): for step, (s1, s2, mix) in enumerate(train_loader): # gives batch data s1 = s1.to(DEVICE) s2 = s2.to(DEVICE) mix = mix.to(DEVICE) out = TasNet(mix) # rnn DRNN # loss = loss_...
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{ "lang": "python", "repo": "wangpengxu2020/TasNet", "path": "/main.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: Athira-Vijayan/Python path: /strings/search.py #searching for a sstring in a group of strings str=[] n=int(input('How many strings?')) for i<|fim_suffix|> print('Found at',i+1) else: print('Not found') #if flag==False: # print('Not found')<|fim_middle|> in range(n): print('enetr str...
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{ "lang": "python", "repo": "Athira-Vijayan/Python", "path": "/strings/search.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>ey to search:') flag=False for i in range(len(str)): if s==str[i]: flag=True print('Found at',i+1) else: print('Not found') #if flag==False: # print('Not found')<|fim_prefix|># repo: Athira-Vijayan/Python path: /strings/search.py #searching for a sstring in a group of strings s...
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{ "lang": "python", "repo": "Athira-Vijayan/Python", "path": "/strings/search.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> print('Found at',i+1) else: print('Not found') #if flag==False: # print('Not found')<|fim_prefix|># repo: Athira-Vijayan/Python path: /strings/search.py #searching for a sstring in a group of strings str=[] n=int(input('How many strings?')) for i in range(n): print('enetr string:',end='') ...
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{ "lang": "python", "repo": "Athira-Vijayan/Python", "path": "/strings/search.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: Garavirod/Django-DRF-Projects path: /librarydj/librarydj/applications/book/migrations/0004_auto_20201119_2128.py # Generated by Django 3.1.2 on 2020-11-19 21:28 <|fim_suffix|> dependencies = [ ('book', '0003_auto_20201030_1846'), ] operations = [ migrations.AlterMode...
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{ "lang": "python", "repo": "Garavirod/Django-DRF-Projects", "path": "/librarydj/librarydj/applications/book/migrations/0004_auto_20201119_2128.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> class Migration(migrations.Migration): dependencies = [ ('book', '0003_auto_20201030_1846'), ] operations = [ migrations.AlterModelOptions( name='book', options={'ordering': ['title', 'date'], 'verbose_name': 'Libro', 'verbose_name_plural': 'Libros'},...
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{ "lang": "python", "repo": "Garavirod/Django-DRF-Projects", "path": "/librarydj/librarydj/applications/book/migrations/0004_auto_20201119_2128.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>def hitfinder1(rocket, target): if rocket.ycor() < target.ycor() + 10 and rocket.ycor() > target.ycor() - 10 : return 1 else: return 0 def gameloop(lives,level): while lives>0 and level<4: update = gamelvl(level) lives = lives - update lev...
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{ "lang": "python", "repo": "seventhridge/mat2110", "path": "/2017-Projects/3E-Aquilla-project/failed first project design.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: seventhridge/mat2110 path: /2017-Projects/3E-Aquilla-project/failed first project design.py import turtle, math turtle.setup(400,400) wn=turtle.Screen() wn.bgcolor("antique white") rocket =turtle.Turtle() target= turtle.Turtle() #def loser(): #def winner(): angle = None def fn_up(a): ...
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{ "lang": "python", "repo": "seventhridge/mat2110", "path": "/2017-Projects/3E-Aquilla-project/failed first project design.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> assert '/srv/conda/envs/notebook/etc/dask' in dask.config.paths assert dask.config.config['labextension']['factory']['class'] == 'KubeCluster' assert 'worker-template' in dask.config.config['kubernetes']<|fim_prefix|># repo: pangeo-data/pangeo-stacks path: /pangeo-esip/binder/tests/test_dask_...
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{ "lang": "python", "repo": "pangeo-data/pangeo-stacks", "path": "/pangeo-esip/binder/tests/test_dask_env.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> import dask assert '/srv/conda/envs/notebook/etc/dask' in dask.config.paths assert dask.config.config['labextension']['factory']['class'] == 'KubeCluster' assert 'worker-template' in dask.config.config['kubernetes']<|fim_prefix|># repo: pangeo-data/pangeo-stacks path: /pangeo-esip/binder...
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{ "lang": "python", "repo": "pangeo-data/pangeo-stacks", "path": "/pangeo-esip/binder/tests/test_dask_env.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: pangeo-data/pangeo-stacks path: /pangeo-esip/binder/tests/test_dask_env.py import pytest @pytest.fixture(scope='module') def client(): from dask.distributed import Client with Client(n_workers=4) as dask_client: yield dask_client def test_check_dask_version(client): <|fim_suffi...
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{ "lang": "python", "repo": "pangeo-data/pangeo-stacks", "path": "/pangeo-esip/binder/tests/test_dask_env.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: pombredanne/PowerReporter path: /plugins/__init__.py __author__ = "Tiaonmmn.ZMZ" __all__ = ['mounting', 'hashFile', 'detectOS', 'timezoneInfo', 'computerName', 'samParse', 'lastLogon', 'startTime', 'shutdownTime', 'netwo<|fim_suffix|>'customShellFolder', 'usbInfo', 'printers', 'miscFil...
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{ "lang": "python", "repo": "pombredanne/PowerReporter", "path": "/plugins/__init__.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>'customShellFolder', 'usbInfo', 'printers', 'miscFiles', 'remoteLogin', 'defaultBrowser']<|fim_prefix|># repo: pombredanne/PowerReporter path: /plugins/__init__.py __author__ = "Tiaonmmn.ZMZ" __all__ = ['mounting', 'hashFile', 'detectOS', 'timezoneInfo'<|fim_middle|>, 'computerName', 'samParse', 'lastLog...
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{ "lang": "python", "repo": "pombredanne/PowerReporter", "path": "/plugins/__init__.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: alex-wenzel/oasis path: /backend/alembic/versions/69b610fddc4b_remove_first_name_and_user_name_from_.py """Remove first name and user name from users Revision ID: 69b610fddc4b Revises: 91a50206245d Create Date: 2020-08-08 06:02:19.659170 <|fim_suffix|>def upgrade(): # ### commands auto gene...
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{ "lang": "python", "repo": "alex-wenzel/oasis", "path": "/backend/alembic/versions/69b610fddc4b_remove_first_name_and_user_name_from_.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>def downgrade(): # ### commands auto generated by Alembic - please adjust! ### op.add_column( "users", sa.Column("username", mysql.VARCHAR(length=64), nullable=True) ) op.add_column( "users", sa.Column("first_name", mysql.VARCHAR(length=128), nullable=True), ) ...
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{ "lang": "python", "repo": "alex-wenzel/oasis", "path": "/backend/alembic/versions/69b610fddc4b_remove_first_name_and_user_name_from_.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>c2 = TCanvas("c2", "ratio 2") c2.Clear() rp2 = TRatioPlot(h2,h2) rp2.Draw() g2 = rp2.GetLowerRefGraph() g2.SetLineColor(ROOT.kBlue) g2.SetFillColor(ROOT.kBlue) #g2.SetFillColorAlpha(ROOT.,0.5) g2.SetLineWidth(2) h0.SetTitle("") h0.GetXaxis().SetTitle("p_{T}^{min} [TeV]") h0.GetYaxis().SetTitle("#sigma ...
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{ "lang": "python", "repo": "selvaggi/PlottingMacros", "path": "/macros/dijetJesBands.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: selvaggi/PlottingMacros path: /macros/dijetJesBands.py import ROOT from ROOT import TFile, TRatioPlot, TCanvas, gPad, TLegend import numpy as np import math from array import array try: input = raw_input except: pass def fillTH1errors(h,hup,hdown): for i in xrange(0,h.GetNbinsX()): ...
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{ "lang": "python", "repo": "selvaggi/PlottingMacros", "path": "/macros/dijetJesBands.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: Adhokshajan/CovidTracker path: /CovidTracker/main.py from tkinter import font from tkinter.constants import NONE import requests import bs4 import tkinter as tk def get_html_data(url): data = requests .get(url) return data def get_covid_data(): url = "https://www.worl...
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{ "lang": "python", "repo": "Adhokshajan/CovidTracker", "path": "/CovidTracker/main.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> root = tk.Tk() root.geometry("900x700") root.title("Covid Tracker") f = ("poppins" , 25 , "bold") banner = tk.PhotoImage(file="image.png") bannerlabel = tk.Label(root , image=banner) bannerlabel.pack() textfield = tk.Entry(root, width = 50 ) textfield.pack() mainlabel = ...
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{ "lang": "python", "repo": "Adhokshajan/CovidTracker", "path": "/CovidTracker/main.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>g = T.grad(z, [x]) g_f = function([x], g) print("Original:", f([[1, 2, 3]]) ) print("Original Gradient:", g_f([[1, 2, 3]]) )<|fim_prefix|># repo: zfy1989lee/MachineLearning path: /05Deep Learning with Python- A Hands-on Introduction/ch4Introduction to Theano/i10gradients.py import theano.tensor as T fro...
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{ "lang": "python", "repo": "zfy1989lee/MachineLearning", "path": "/05Deep Learning with Python- A Hands-on Introduction/ch4Introduction to Theano/i10gradients.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: zfy1989lee/MachineLearning path: /05Deep Learning with Python- A Hands-on Introduction/ch4Introduction to Theano/i10gradients.py import theano.tensor as T from theano import function from theano import shared import numpy x = T.dmatrix('x') y = shared(numpy.array([[4, 5, 6]])) z = T.sum(((x * x...
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{ "lang": "python", "repo": "zfy1989lee/MachineLearning", "path": "/05Deep Learning with Python- A Hands-on Introduction/ch4Introduction to Theano/i10gradients.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: nandansn/pythonlab path: /durgasoft/chapter47/random-example.py from random import * for i in range(10): print(random()) <|fim_suffix|>for i in range(10): print(uniform(i,10)) #generate the float value, within the range. not inclusive of start and end values. for i in range(10)...
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{ "lang": "python", "repo": "nandansn/pythonlab", "path": "/durgasoft/chapter47/random-example.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>for i in range(10): print(uniform(i,10)) #generate the float value, within the range. not inclusive of start and end values. for i in range(10): print('random numbers') print(randrange(1,11,3)) # generate the random number with step value<|fim_prefix|># repo: nandansn/pythonlab path: /d...
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{ "lang": "python", "repo": "nandansn/pythonlab", "path": "/durgasoft/chapter47/random-example.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>def neighbor(network, geometry, throat_prop='', mode='min', **kwargs): r""" Adopt the minimum seed value from the neighboring throats """ Ps = geometry.pores() data = geometry[throat_prop] neighborTs = network.find_neighbor_throat...
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{ "lang": "python", "repo": "gitter-badger/OpenPNM", "path": "/OpenPNM/Geometry/models/pore_misc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def random(geometry, seed=None, num_range=[0,1], **kwargs): r""" Assign random number to pore bodies note: should this be called 'poisson'? """ range_size = num_range[1]-num_range[0] range_min = num_range[0] _sp.random.seed(seed) value = _...
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{ "lang": "python", "repo": "gitter-badger/OpenPNM", "path": "/OpenPNM/Geometry/models/pore_misc.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gitter-badger/OpenPNM path: /OpenPNM/Geometry/models/pore_misc.py r""" =============================================================================== pore_misc -- miscillaneous and generic functions to apply to pores ===============================================================================...
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{ "lang": "python", "repo": "gitter-badger/OpenPNM", "path": "/OpenPNM/Geometry/models/pore_misc.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: SemaMolchanov/self_study path: /Algorithms and Data Structures/Algorithms/Sorting Algorithms/selection_sort.py def find_smallest(arr): smallest_element = arr[0] smallest_index = 0 for i in range(1, len(arr)): if arr[i] < smallest: smallest = arr[i] s...
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{ "lang": "python", "repo": "SemaMolchanov/self_study", "path": "/Algorithms and Data Structures/Algorithms/Sorting Algorithms/selection_sort.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>numbers = list(map(int, input().split())) print(selection_sort(numbers))<|fim_prefix|># repo: SemaMolchanov/self_study path: /Algorithms and Data Structures/Algorithms/Sorting Algorithms/selection_sort.py def find_smallest(arr): smallest_element = arr[0] smallest_index = 0 for i in range(...
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{ "lang": "python", "repo": "SemaMolchanov/self_study", "path": "/Algorithms and Data Structures/Algorithms/Sorting Algorithms/selection_sort.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> sorted_arr = [] for i in range(len(arr)): smallest = find_smallest(arr) sorted_arr.append(arr.pop(smallest)) return sorted_arr numbers = list(map(int, input().split())) print(selection_sort(numbers))<|fim_prefix|># repo: SemaMolchanov/self_study path: /Algorithms and Data St...
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{ "lang": "python", "repo": "SemaMolchanov/self_study", "path": "/Algorithms and Data Structures/Algorithms/Sorting Algorithms/selection_sort.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: asiqurrahman/Trading-Web path: /users/migrations/0002_profile_title2.py # Generated by Django 3.1.5 on 2021-03-14 16:41 from django.db import migrations, models import django.utils.timezone <|fim_suffix|> dependencies = [ ('users', '0001_initial'), ] operations = [ ...
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{ "lang": "python", "repo": "asiqurrahman/Trading-Web", "path": "/users/migrations/0002_profile_title2.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> dependencies = [ ('users', '0001_initial'), ] operations = [ migrations.AddField( model_name='profile', name='title2', field=models.CharField(default=django.utils.timezone.now, max_length=100), ), ]<|fim_prefix|># repo: asiqurrah...
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{ "lang": "python", "repo": "asiqurrahman/Trading-Web", "path": "/users/migrations/0002_profile_title2.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>@app.after_request def add_header(response): response.cache_control.max_age = 31536000 if 'service-worker.js' in request.path: response.cache_control.max_age = 0 return response @app.route('/', methods=["GET"]) def get_home(): # needs the index to be in the dist folder to work ...
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{ "lang": "python", "repo": "jzlotek/drexel-tms-parser", "path": "/src/webapp.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> return response @app.route('/', methods=["GET"]) def get_home(): # needs the index to be in the dist folder to work return send_from_directory('../dist', 'index.html') @app.route('/static/<path:path>', methods=["GET"]) def get_file_static(path): # needs the index to be in the dist folder...
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{ "lang": "python", "repo": "jzlotek/drexel-tms-parser", "path": "/src/webapp.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>if not os.path.exists(load_results_dir): os.makedirs(load_results_dir) #Fixed random seeds. rng = np.random.RandomState(args.seed) theano_rng = MRG_RandomStreams(rng.randint(2 ** 15)) lasagne.random.set_rng(np.random.RandomState(rng.randint(2 ** 15))) #Load Terraria dataset. if tdg_train: print...
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{ "lang": "python", "repo": "samanthastahlke/terraria-deligan", "path": "/SpriteGAN/dg_terraria.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> for i, p in enumerate(gen_params): p.set_value(param_dict[fepoch][i]) print("Loaded generator parameters.") noise = theano_rng.normal(size=noise_dim) sample_input = th.tensor.zeros(noise_dim) print("Setting up sampling...") gen_layers[0].input...
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{ "lang": "python", "repo": "samanthastahlke/terraria-deligan", "path": "/SpriteGAN/dg_terraria.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: samanthastahlke/terraria-deligan path: /SpriteGAN/dg_terraria.py # DeLiGAN implementation for the Terraria dataset. # Based heavily on the code from Gurumurthy, Sarvadevabhatla, and Babu (2017). import argparse import time import numpy as np import theano as th import theano.tensor as T from the...
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{ "lang": "python", "repo": "samanthastahlke/terraria-deligan", "path": "/SpriteGAN/dg_terraria.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> Ymean[i] = np.mean(y) Ynorm[i, idx] = y - Ymean[i] return Ynorm, Ymean<|fim_prefix|># repo: junwon1994/Coursera-ML path: /ex8/normalizeRatings.py import numpy as np def normalizeRatings(Y, R): <|fim_middle|> """normalized Y so that each movie has a rating of 0 on average, an...
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{ "lang": "python", "repo": "junwon1994/Coursera-ML", "path": "/ex8/normalizeRatings.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Jyotirm0y/kattis path: /imageprocessing.py h, w, n, m = map(int, input().split()) image = [] for _ in range(h): image.append(list(map(int, input().split()))) <|fim_suffix|>r = [[0 for i in range(w-m+1)] for j in range(h-n+1)] for j in range(h-n+1): for i in range(w-m+1): for y i...
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{ "lang": "python", "repo": "Jyotirm0y/kattis", "path": "/imageprocessing.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>r = [[0 for i in range(w-m+1)] for j in range(h-n+1)] for j in range(h-n+1): for i in range(w-m+1): for y in range(n): for x in range(m): r[j][i] += image[j+y][i+x] * kernel[y][x] for row in r: print(' '.join([str(x) for x in row]))<|fim_prefix|># repo: Jyotirm...
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{ "lang": "python", "repo": "Jyotirm0y/kattis", "path": "/imageprocessing.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> print(self.data) s1=Stack([3]) s1.push([4]) s1.printStack() s1.push([6,7]) s1.printStack() print(s1.pop()) s1.printStack() ''' append adds its argument as a single element to the end of a list. The length of the list itself will increase by one. extend iterates over its argument adding each elem...
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{ "lang": "python", "repo": "mike03052000/python", "path": "/Training/HackRank/Level-1/Stack-1.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: mike03052000/python path: /Training/HackRank/Level-1/Stack-1.py class Stack(): def __init__(self,n): self.data=[] self.data.extend(n) def pop(self): return self.data.pop() <|fim_suffix|># Extends list by appending elements from the iterable. x = [1, 2, 3] x.exte...
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{ "lang": "python", "repo": "mike03052000/python", "path": "/Training/HackRank/Level-1/Stack-1.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: feieryouyiji/subject_share path: /subject_orm/curd.py async def execute(sql, args, autocommit=True): log(sql) global __pool with (await __pool) as conn: if not autocommit:<|fim_suffix|>s) affect = cur.rowcount await cur.close() if not auto...
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{ "lang": "python", "repo": "feieryouyiji/subject_share", "path": "/subject_orm/curd.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> except BaseException as e: if not autocommit: await conn.rollback() raise e return affect<|fim_prefix|># repo: feieryouyiji/subject_share path: /subject_orm/curd.py async def execute(sql, args, autocommit=True): log(sql) global __pool with ...
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{ "lang": "python", "repo": "feieryouyiji/subject_share", "path": "/subject_orm/curd.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: oskarkk/minecraft-tg path: /users.py filename = 'data/users.csv' def get(): try: with open(filename, 'r+') as f: # remove newlines just in case x = f.read().replace('\n', '') # if empty file return empty list, # not list with an empty ...
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{ "lang": "python", "repo": "oskarkk/minecraft-tg", "path": "/users.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def remove(id): id = str(id) id_list = get() # do antyhing only if user is on the list if id in id_list: id_list.remove(id) save(id_list)<|fim_prefix|># repo: oskarkk/minecraft-tg path: /users.py filename = 'data/users.csv' def get(): try: with open(filename,...
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{ "lang": "python", "repo": "oskarkk/minecraft-tg", "path": "/users.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> baseline, follow_up = load((bl[number], fu[number])) mask, affine = load_mask(la[number]) baseline = central_crop(baseline) follow_up = central_crop(follow_up) mask = central_crop(mask) my_model = gessert_net(fusion_type='stack') lr_schedule = tf.keras.optimizers.schedules.Ex...
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{ "lang": "python", "repo": "vganapati/New_lesion_segmentation_MS", "path": "/results.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: vganapati/New_lesion_segmentation_MS path: /results.py import pickle import os import numpy as np import matplotlib.pyplot as plt from itertools import islice from matplotlib.ticker import MaxNLocator from model import gessert_net from preprocess import show_slices, get_filenames import nibabel a...
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{ "lang": "python", "repo": "vganapati/New_lesion_segmentation_MS", "path": "/results.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def run(self): # Initialize networktables team = "" while team == "": team = input("Enter team number or 'sim': ") if team == "sim": NetworkTables.initialize(server="localhost") else: NetworkTables.startClientTeam(int(team))...
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{ "lang": "python", "repo": "Oblarg/robot-characterization", "path": "/arm-characterization/data_logger.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # Use listeners to receive the data NetworkTables.addConnectionListener( self.connectionListener, immediateNotify=True ) NetworkTables.addEntryListener(self.valueChanged) # Wait for a connection notification, then continue on the path print("Wai...
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{ "lang": "python", "repo": "Oblarg/robot-characterization", "path": "/arm-characterization/data_logger.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Oblarg/robot-characterization path: /arm-characterization/data_logger.py #!/usr/bin/env python3 # # Adapted from the pynetworktables json_logger example program # # While this is designed to work with the robot.py example in this directory, # because the transport uses NetworkTables you can use i...
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{ "lang": "python", "repo": "Oblarg/robot-characterization", "path": "/arm-characterization/data_logger.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: moff4/KFrame path: /kframe/plugins/cache.py #!/usr/bin/env python3 import time import json from threading import Thread from ..base.plugin import Plugin class Cache(Plugin): """ kwargs: auto_clean_in_new_thread - if True -> create new thread timeout - inter...
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{ "lang": "python", "repo": "moff4/KFrame", "path": "/kframe/plugins/cache.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def clean(self, nodename: str) -> int: """ delete old rows from node return number of deleted rows """ if nodename not in self._d: return 0 k = len(self._d[nodename]) _time = time.time() for key in list(self._d[nodenam...
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{ "lang": "python", "repo": "moff4/KFrame", "path": "/kframe/plugins/cache.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: chicagomegagames/my_kind_of_town_scripts path: /distributions.py from collections import OrderedDict import random # height and weight numbers derived from (with minor changes) # https://www2.census.gov/library/publications/2010/compendia/statab/130ed/tables/11s0205.pdf male_heights = OrderedDi...
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{ "lang": "python", "repo": "chicagomegagames/my_kind_of_town_scripts", "path": "/distributions.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> for i in range(0, len(reversed_keys) - 1): a = reversed_keys[i] b = reversed_keys[i + 1] percent = int(data[a] * 10) - int(data[b] * 10) for j in range(0, percent): sample.append(a) return sample male_height_samples = create_sample(male_heights) male...
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{ "lang": "python", "repo": "chicagomegagames/my_kind_of_town_scripts", "path": "/distributions.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: Jokel64/parcelcopter path: /ref_codes/object_det_color_server.py #! /usr/bin/env python2 import rospy import numpy as np import cv2 from sub_topics.sub_zed_image_color import ZED_Image_Color from sub_topics.sub_zed_depth_image import ZED_Depth_Image from sub_topics.sub_zed_point_cloud import Z...
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{ "lang": "python", "repo": "Jokel64/parcelcopter", "path": "/ref_codes/object_det_color_server.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> def srv_callback(self, request): # call to cal the pix positin self.object_detection() # response of the server response = ObjectLocationResponse() # string loc_type # --- # bool success # float64 distance # object_det_srv_msg/P...
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{ "lang": "python", "repo": "Jokel64/parcelcopter", "path": "/ref_codes/object_det_color_server.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: jsaric/quiz-manager path: /gui/windows/overview_window.py from PyQt5.QtWidgets import QMainWindow, QTableView, QHeaderView from models.league_results_model import LeagueResultsModel <|fim_suffix|> super(LeagueOverviewWindow, self).__init__(parent) self.resize(900, 600) sel...
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{ "lang": "python", "repo": "jsaric/quiz-manager", "path": "/gui/windows/overview_window.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> super(LeagueOverviewWindow, self).__init__(parent) self.resize(900, 600) self.table_view = QTableView() self.table_view.setModel(LeagueResultsModel(league)) self.setCentralWidget(self.table_view) self.table_view.resizeColumnsToContents() self.table_v...
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{ "lang": "python", "repo": "jsaric/quiz-manager", "path": "/gui/windows/overview_window.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: sebbacon/PublicMail path: /mail/management/commands/sample.py import os from django.core.management.base import BaseCommand from django.core.management.base import CommandError from django.db import transaction class Command(BaseCommand): def handle(self, *args, **options): <|fim_suffix|> ...
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{ "lang": "python", "repo": "sebbacon/PublicMail", "path": "/mail/management/commands/sample.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> transaction.enter_transaction_management() transaction.managed(True) transaction.commit()<|fim_prefix|># repo: sebbacon/PublicMail path: /mail/management/commands/sample.py import os from django.core.management.base import BaseCommand from django.core.management.base import Comma...
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{ "lang": "python", "repo": "sebbacon/PublicMail", "path": "/mail/management/commands/sample.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> if not args or (args and args[0] not in ('load')): raise CommandError("USAGE: ./manage.py %s load" % \ os.path.basename(__file__).split('.')[0]) transaction.enter_transaction_management() transaction.managed(True) transaction.commit()<|fim_p...
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{ "lang": "python", "repo": "sebbacon/PublicMail", "path": "/mail/management/commands/sample.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: diazona/Modulo path: /modulo/actions/__init__.py alue> is a deterministic function of the argument. It returns True from handles(req) for all requests, but if its constituent class (the parameter given in cls) doesn't actually handle the request, attempting to create an instance of Op...
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{ "lang": "python", "repo": "diazona/Modulo", "path": "/modulo/actions/__init__.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: diazona/Modulo path: /modulo/actions/__init__.py ass(cls, Action): return NotImplemented elif cls.__name__.startswith('OptAction'): return cls else: return type('OptAction_%s' % hash_iterable([cls]), (OptAction,), {'handler_class': cls}) class ActionMetaclass(type...
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{ "lang": "python", "repo": "diazona/Modulo", "path": "/modulo/actions/__init__.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> def derive(cls, <property1>, <property2>, ..., **kwargs): return super(<class>, cls).derive(<property1>=<property1>, <property2>=<property2>, ..., **kwargs) Just replace ``property1``, ``property2``, etc. in all three spots with the name of each property, and `...
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{ "lang": "python", "repo": "diazona/Modulo", "path": "/modulo/actions/__init__.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: ruhee/advent-of-code-2017 path: /06/run.py #! /usr/bin/python import csv from itertools import cycle, islice with open('input.tsv', 'r') as tsvfile: reader = csv.reader(tsvfile, delimiter='\t') for row in reader: row = [int(item) for item in row] results = [] current_item = 0 ...
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{ "lang": "python", "repo": "ruhee/advent-of-code-2017", "path": "/06/run.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> for i, v in islice(cycle(enumerate(current_list, current_item+1)), current_value): index_to_modify = i if i > (len(current_list) - 1): index_to_modify = i - len(current_list) current_list[index_to_modify] += 1 results.append(list(current_list)) num_of_...
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{ "lang": "python", "repo": "ruhee/advent-of-code-2017", "path": "/06/run.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> """ Returns the value to which the specified key is mapped, or -1 if this map contains no mapping for the key """ idx = key % 1000 if not self.map[idx]: return -1 else: curr = self.map[idx] while curr: if c...
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{ "lang": "python", "repo": "akauntotesuto888/Leetcode-Lintcode-Python", "path": "/706.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> def remove(self, key: int) -> None: """ Removes the mapping of the specified value key if this map contains a mapping for the key """ idx = key % 1000 if not self.map[idx]: return elif self.map[idx].key == key: self.map[idx] = sel...
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{ "lang": "python", "repo": "akauntotesuto888/Leetcode-Lintcode-Python", "path": "/706.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: akauntotesuto888/Leetcode-Lintcode-Python path: /706.py class Node: def __init__(self, key, val): self.key = key self.val = val self.next = None class MyHashMap: def __init__(self): """ Initialize your data structure here. """ sel...
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hard
{ "lang": "python", "repo": "akauntotesuto888/Leetcode-Lintcode-Python", "path": "/706.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> n1, k1 = map(int, input().split()) lst1 = list(map(int, input().split())) print(*trees_interval(n1, k1, lst1))<|fim_prefix|># repo: darioradio1man/yandex_training path: /lesson5/cut_trees.py from collections import * def trees_interval(n, k, lst): left = 0 segments = Counter() best_resolut...
code_fim
hard
{ "lang": "python", "repo": "darioradio1man/yandex_training", "path": "/lesson5/cut_trees.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: darioradio1man/yandex_training path: /lesson5/cut_trees.py from collections import * def trees_interval(n, k, lst): left = 0 segments = Counter() best_resolutions = [0, n] <|fim_suffix|> n1, k1 = map(int, input().split()) lst1 = list(map(int, input().split())) print(*trees_interval...
code_fim
hard
{ "lang": "python", "repo": "darioradio1man/yandex_training", "path": "/lesson5/cut_trees.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>n1, k1 = map(int, input().split()) lst1 = list(map(int, input().split())) print(*trees_interval(n1, k1, lst1))<|fim_prefix|># repo: darioradio1man/yandex_training path: /lesson5/cut_trees.py from collections import * def trees_interval(n, k, lst): left = 0 segments = Counter() best_resoluti...
code_fim
hard
{ "lang": "python", "repo": "darioradio1man/yandex_training", "path": "/lesson5/cut_trees.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|> ('item_group', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='requests', to='item.ItemGroup')), ('requested_by', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='requests', to=settings.AUTH_USER_MODEL)), ('req...
code_fim
hard
{ "lang": "python", "repo": "VikasKumarRoy/Inventory-Manager-API", "path": "/item/migrations/0001_initial.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: VikasKumarRoy/Inventory-Manager-API path: /item/migrations/0001_initial.py # -*- coding: utf-8 -*- # Generated by Django 1.11.16 on 2020-03-13 05:55 from __future__ import unicode_literals from django.conf import settings from django.db import migrations, models import django.db.models.deletion ...
code_fim
hard
{ "lang": "python", "repo": "VikasKumarRoy/Inventory-Manager-API", "path": "/item/migrations/0001_initial.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_prefix|># repo: JMLizano/AOC2019 path: /day10/part1.py import math from collections import namedtuple, defaultdict from heapq import heappush, heappop from typing import Generator, Tuple, List, Set _INPUT_FILE = 'input.txt' Point = namedtuple('Point', ['x', 'y']) def read_input(input_file: str) -> Generator...
code_fim
hard
{ "lang": "python", "repo": "JMLizano/AOC2019", "path": "/day10/part1.py", "mode": "psm", "license": "unknown", "source": "the-stack-v2" }
<|fim_suffix|>if __name__ == '__main__': asteroids = list(read_input(input_file=_INPUT_FILE)) angles = {ast: compute_visibility_angles(ast, asteroids) for ast in asteroids} space_station_location = max(angles.items(), key=lambda x: len(x[1])) print(f"Best position for space station location: {space_stat...
code_fim
medium
{ "lang": "python", "repo": "JMLizano/AOC2019", "path": "/day10/part1.py", "mode": "spm", "license": "unknown", "source": "the-stack-v2" }