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<|fim_suffix|> def test03_driver_api(self): from bob.db.base.script.dbmanage import main self.assertEqual(main('biosecurid.face dumplist --self-test'.split()), 0) self.assertEqual(main('biosecurid.face dumplist --protocol=A --class=client --group=dev --purpose=enrol --client=1151 --self-test'.split()),...
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{ "lang": "python", "repo": "bioidiap/bob.db.biosecurid.face", "path": "/bob/db/biosecurid/face/test.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>urlpatterns = [path("", views.UnitsList.as_view(), name="units")]<|fim_prefix|># repo: uktrade/lite-api path: /api/staticdata/units/urls.py from django.urls import path <|fim_middle|>from api.staticdata.units import views app_name = "units"
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{ "lang": "python", "repo": "uktrade/lite-api", "path": "/api/staticdata/units/urls.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: uktrade/lite-api path: /api/staticdata/units/urls.py from django.urls import path <|fim_suffix|>app_name = "units" urlpatterns = [path("", views.UnitsList.as_view(), name="units")]<|fim_middle|>from api.staticdata.units import views
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{ "lang": "python", "repo": "uktrade/lite-api", "path": "/api/staticdata/units/urls.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.filename = value def get_data(self): with open(self.filename, 'rb') as output: return json.load(output)<|fim_prefix|># repo: AI-Pree/WebScraper path: /parsedata.py #! python # Data parser for json file import json class ParseJson(): def __init__(self, filen...
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{ "lang": "python", "repo": "AI-Pree/WebScraper", "path": "/parsedata.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return self.filename @dataFile.setter def dataFile(self, value): self.filename = value def get_data(self): with open(self.filename, 'rb') as output: return json.load(output)<|fim_prefix|># repo: AI-Pree/WebScraper path: /parsedata.py #! python # Data ...
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{ "lang": "python", "repo": "AI-Pree/WebScraper", "path": "/parsedata.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: AI-Pree/WebScraper path: /parsedata.py #! python # Data parser for json file import json class ParseJson(): def __init__(self, filename): self.filename = filename @property def dataFile(self): return self.filename <|fim_suffix|> with open(self.filename, 'rb'...
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{ "lang": "python", "repo": "AI-Pree/WebScraper", "path": "/parsedata.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # test data def function(a: int, b: int) -> int: return a + b test_header = "type_, value" test_data = [ (int, 1234567890), (float, 1.234567890), (complex, 1.2345 + 6.7890j), (str, "lorem ipsum"), (bytes, b"lorem ipsum"), (tuple, (123, 4.56, 7.8e90)), (range, range(12345...
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{ "lang": "python", "repo": "astropenguin/morecopy", "path": "/tests/test_copy.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: astropenguin/morecopy path: /tests/test_copy.py # standard library from copy import copy as stdlib_copy from types import FunctionType, LambdaType from typing import Type, TypeVar # dependencies from morecopy.copy import copy from pytest import mark # type hints T = TypeVar("T") # test data...
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{ "lang": "python", "repo": "astropenguin/morecopy", "path": "/tests/test_copy.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if type_ is FunctionType: return assert value == copy(value) assert value == stdlib_copy(value) @mark.parametrize(test_header, test_data) def test_copy_is(type_: Type[T], value: T) -> None: assert value is not copy(value) assert value is stdlib_copy(value)<|fim_prefix|># rep...
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{ "lang": "python", "repo": "astropenguin/morecopy", "path": "/tests/test_copy.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>process.inputs = cms.PSet ( fileNames = cms.vstring( 'reco_7TeV_380_pat.root' ), lumisToProcess = cms.untracked.VLuminosityBlockRange( myList ) ) process.outputs = cms.PSet ( outputName = cms.string('jetPlots.root') )<|fim_prefix|># repo: cms-sw/cmssw path: /PhysicsTools/Pat...
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{ "lang": "python", "repo": "cms-sw/cmssw", "path": "/PhysicsTools/PatExamples/bin/PatBasicFWLiteJetAnalyzer_Selector_cfg.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: cms-sw/cmssw path: /PhysicsTools/PatExamples/bin/PatBasicFWLiteJetAnalyzer_Selector_cfg.py import FWCore.ParameterSet.Config as cms process = cms.Process("FWLitePlots") #input stuff for Run/Lumi selection with the "JSON"-formatted files from the PVT group import FWCore.PythonUtilities.LumiList ...
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{ "lang": "python", "repo": "cms-sw/cmssw", "path": "/PhysicsTools/PatExamples/bin/PatBasicFWLiteJetAnalyzer_Selector_cfg.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|># Set up the parameters for the PF jet analyzer process.pfJetStudies = process.jetStudies.clone( useCalo = cms.bool(False) ) process.load('PhysicsTools.SelectorUtils.pfJetIDSelector_cfi') process.load('PhysicsTools.SelectorUtils.jetIDSelector_cfi') process.plotParameters = cms.PSet ( doTracks = cms...
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{ "lang": "python", "repo": "cms-sw/cmssw", "path": "/PhysicsTools/PatExamples/bin/PatBasicFWLiteJetAnalyzer_Selector_cfg.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if Translator._isInteger(iface.switch_port): ifaceModel.port = iface.switch_port ifaceModel.save() if not sModel.ifaces.filter(ifaceName = iface.name): sModel.ifaces.add(ifaceModel) sModel.setVMs() ...
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{ "lang": "python", "repo": "dana-i2cat/felix", "path": "/expedient/src/python/plugins/vt_plugin/utils/Translator.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: dana-i2cat/felix path: /expedient/src/python/plugins/vt_plugin/utils/Translator.py from vt_plugin.models import * from vt_plugin.models.Action import Action import copy, uuid from datetime import datetime from expedient.clearinghouse.aggregate.models import Aggregate from vt_plugin.models import ...
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{ "lang": "python", "repo": "dana-i2cat/felix", "path": "/expedient/src/python/plugins/vt_plugin/utils/Translator.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> @staticmethod def PopulateNewVMifaces(VMclass, VMmodel): for iface in VMclass.xen_configuration.interfaces.interface: if VMmodel.ifaces.filter(name = iface.name): ifaceModel = VMmodel.ifaces.get(name = iface.name) else: ifaceModel = i...
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{ "lang": "python", "repo": "dana-i2cat/felix", "path": "/expedient/src/python/plugins/vt_plugin/utils/Translator.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|># Needed on Windows, else output newlines will be corrupted try: import msvcrt except ImportError: pass else: msvcrt.setmode(sys.stdout.fileno(), os.O_BINARY) def encode_latin_1_unicode(x, r): bencode.encode_bytes(x.encode("latin-1"), r) # This is the most convenient place to add support for our lat...
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{ "lang": "python", "repo": "ludios/quickmunge", "path": "/bin/json-to-bencode", "mode": "spm", "license": "ISC", "source": "the-stack-v2" }
<|fim_prefix|># repo: ludios/quickmunge path: /bin/json-to-bencode #!/usr/bin/python3 -B """ Converts the first JSON item in stdin to bencode """ import os import sys from quickmunge import bencode import collections import json # Needed on Windows, else output newlines will be corrupted try: import msvcrt except ...
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{ "lang": "python", "repo": "ludios/quickmunge", "path": "/bin/json-to-bencode", "mode": "psm", "license": "ISC", "source": "the-stack-v2" }
<|fim_suffix|>if sys.argv[1:]: f = open(sys.argv[1], "rb") else: f = sys.stdin.buffer sys.stdout.buffer.write( bencode.bencode( json.loads( f.read(), object_pairs_hook=collections.OrderedDict)))<|fim_prefix|># repo: ludios/quickmunge path: /bin/json-to-bencode #!/usr/bin/python3 -B """ Converts the first ...
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{ "lang": "python", "repo": "ludios/quickmunge", "path": "/bin/json-to-bencode", "mode": "spm", "license": "ISC", "source": "the-stack-v2" }
<|fim_suffix|>class RegionFilter: def __init__(self, regions): self.regions = regions def matches(self, opportunity): if opportunity['related_region'] \ and opportunity['related_region']['title'] \ and opportunity['related_region']['title'] in self.regions: ...
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{ "lang": "python", "repo": "ozorowski/great-international-ui", "path": "/core/helpers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ozorowski/great-international-ui path: /core/helpers.py from collections import namedtuple from urllib.parse import urlencode from django.urls import reverse from django.utils import translation import requests from core import constants def create_response(status_code=200, json_payload=None):...
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{ "lang": "python", "repo": "ozorowski/great-international-ui", "path": "/core/helpers.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>class SortFilter: sort_by_with_values = [ Sort_by(title='Project name: A to Z', value='title', reverse=False), Sort_by(title='Project name: Z to A', value='title', reverse=True), Sort_by( title='Scale: Low to High', value='scale_value', reverse=False ), ...
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{ "lang": "python", "repo": "ozorowski/great-international-ui", "path": "/core/helpers.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: raznem/sac_ppo path: /rltoolkit/buffer.py import numpy as np import torch from typing import Iterable class Memory: def __init__(self): self._obs = [] self._next_obs_idx = [] self._actions = [] self._action_logprobs = [] self._rewards = [] sel...
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{ "lang": "python", "repo": "raznem/sac_ppo", "path": "/rltoolkit/buffer.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self._obs_idx[self.ts_idx] = obs_idx self._next_obs_idx[self.ts_idx] = next_obs_idx self._actions[self.ts_idx] = action self._rewards[self.ts_idx] = rew self._done[self.ts_idx] = done self.ts_idx += 1 self.current_len = max(self.ts_idx, self.current_...
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{ "lang": "python", "repo": "raznem/sac_ppo", "path": "/rltoolkit/buffer.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: bhagyakjain/debaised-analysis path: /intents/test_show.py """ Copyright 2020 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENS...
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{ "lang": "python", "repo": "bhagyakjain/debaised-analysis", "path": "/intents/test_show.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>def test_9(): """An example from "salary in various regions" to test mean vs median suggestion question :show mean of salary in each resident city """ table = pandas.read_csv('data/salary_in_various_regions.csv') query_result = show.show(table, metric='S...
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{ "lang": "python", "repo": "bhagyakjain/debaised-analysis", "path": "/intents/test_show.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>def test_4(): """An example from the IPL dataset question :show all matches where Royal Challengers Bangalore won the match in season 2008 """ table = pandas.read_csv('data/matches.csv') query_result = show.show(table, slices=[('season', Filters.EQUAL_TO...
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{ "lang": "python", "repo": "bhagyakjain/debaised-analysis", "path": "/intents/test_show.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: fbenites/TRANSLIT path: /code/prepare_geonames.py import shelve import pandas as pd geonames = pd.read_csv("../data/geonames/alternateNamesV2.txt", sep='\t', error_bad_lines=False) <|fim_suffix|>names_clean={} languages=set() for key in skeys: for data in names[key]: if type(data...
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{ "lang": "python", "repo": "fbenites/TRANSLIT", "path": "/code/prepare_geonames.py", "mode": "psm", "license": "CC0-1.0", "source": "the-stack-v2" }
<|fim_suffix|>names_clean={} languages=set() for key in skeys: for data in names[key]: if type(data[0]) is not float: if len(data[0])==2: languages.add(data[0]) if key not in names_clean: names_clean[key]=[data] else: ...
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{ "lang": "python", "repo": "fbenites/TRANSLIT", "path": "/code/prepare_geonames.py", "mode": "spm", "license": "CC0-1.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: fatestigma/gaia-visualization path: /model.py bel_location = """ SELECT DISTINCT ?label ?start ?end ?justificationType WHERE { ?justification a aida:TextJustification ; skos:prefLabel ?label ; aida:source ?source ; a...
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{ "lang": "python", "repo": "fatestigma/gaia-visualization", "path": "/model.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @property def type_text(self): _, text = split_uri(self.type) return text @property def target(self): if self.__target is None: self._init_member() return self.__target @property def qid(self): if self.__qid is None and self.tar...
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{ "lang": "python", "repo": "fatestigma/gaia-visualization", "path": "/model.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: fatestigma/gaia-visualization path: /model.py = 0 for label, start, end, j in sparql.query(query_label_location, namespaces, {'source': Literal(doc_id)}): doc_recover += ' ' * (int(start)-lend) if json.loads(j).get('justificationType') == 'pronominal_mention': doc...
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{ "lang": "python", "repo": "fatestigma/gaia-visualization", "path": "/model.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def HitTest(self, pos): # Handle socket hittest for socket in self._sockets: if socket.HitTest(pos - self.pos): return socket def EditParameter(self, idname, value): pass def InitHeaderColor(self): self._headercolor = NODE_CATEGORY_...
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{ "lang": "python", "repo": "Correct-Syntax/gsnodegraph", "path": "/gsnodegraph/node/node.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Correct-Syntax/gsnodegraph path: /gsnodegraph/node/node.py # ---------------------------------------------------------------------------- # GS Nodegraph Copyright 2019-2021 by Noah Rahm and contributors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this fil...
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{ "lang": "python", "repo": "Correct-Syntax/gsnodegraph", "path": "/gsnodegraph/node/node.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def get_name(self): return self.player_name['name_input'] def __str__(self): return f'{self.player_score}'<|fim_prefix|># repo: alan-dx/snake-game path: /app/player_pk/player_class.py class Player(): def __init__(self, name): self.player_score = 0 self.player_...
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{ "lang": "python", "repo": "alan-dx/snake-game", "path": "/app/player_pk/player_class.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __str__(self): return f'{self.player_score}'<|fim_prefix|># repo: alan-dx/snake-game path: /app/player_pk/player_class.py class Player(): def __init__(self, name): <|fim_middle|> self.player_score = 0 self.player_name = name def increase_score(self): self.p...
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{ "lang": "python", "repo": "alan-dx/snake-game", "path": "/app/player_pk/player_class.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: alan-dx/snake-game path: /app/player_pk/player_class.py class Player(): def __init__(self, name): self.player_score = 0 self.player_name = name <|fim_suffix|> def __str__(self): return f'{self.player_score}'<|fim_middle|> def increase_score(self): self.p...
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{ "lang": "python", "repo": "alan-dx/snake-game", "path": "/app/player_pk/player_class.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> assert len(correlate(self.rand1, self.channels, 1)) == 1 # If the arrays are the same, an error should be raised with pytest.raises(ValueError): correlate(self.im, self.channels, 1) def test_fit_clusters(self): # If 1 cluster is passed, the outpu...
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{ "lang": "python", "repo": "Software-Engineering-BBSRC-Group-6/auto-coloc-gui", "path": "/coloc/tests/test-vis.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def test_compare_dists(self): clust1 = [(1,1),(10,10),(20,20),(40,40)] clust2 = [(1,1),(10,10),(20,20)] with pytest.raises(ValueError): compare_dists(clust1, clust2, 5) def test_run_visualiser(self): # If source file does not exist, raise er...
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{ "lang": "python", "repo": "Software-Engineering-BBSRC-Group-6/auto-coloc-gui", "path": "/coloc/tests/test-vis.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Software-Engineering-BBSRC-Group-6/auto-coloc-gui path: /coloc/tests/test-vis.py import pytest import numpy as np import matplotlib.pyplot as plt try: from ..backend.Visualiser import correlate, fit_clusters, run_visualiser, annotate, scaled_dist, compare_dists except ModuleNotFoundError: ...
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{ "lang": "python", "repo": "Software-Engineering-BBSRC-Group-6/auto-coloc-gui", "path": "/coloc/tests/test-vis.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: T4rk1n/dazzler path: /tests/apps/pages/storage.py """ Page storage of dazzler Created 2019-07-17 """ import json from dazzler.components import core from dazzler.system import Page, Trigger, BindingContext page = Page( __name__, core.Container([ core.Button('Set local', identity...
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{ "lang": "python", "repo": "T4rk1n/dazzler", "path": "/tests/apps/pages/storage.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @page.bind(Trigger('session-btn', 'clicks')) async def on_clicks_session(ctx: BindingContext): data = await ctx.get_session_storage('data') if not data: data = {'clicks': 0} data['clicks'] += 1 await ctx.set_session_storage('data', data) await ctx.set_aspect('session-output', ...
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{ "lang": "python", "repo": "T4rk1n/dazzler", "path": "/tests/apps/pages/storage.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> temps_l = temps[stationName] temps_l.sort(key=lambda tup: tup[0]) date_temp = [i[0] for i in temps_l] date_dji = [i[0] for i in dji] date_unif = [filter(lambda x: x in date_dji, [sublist]) for sublist in date_temp] date_unif = [i[0] for i in date_unif if len(i)>0] if len(date_...
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{ "lang": "python", "repo": "ppaulojr/CrazyCorrelation", "path": "/weather/correlation.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> plt.show() def main (param = "print"): djil = readDownJones("DJCA_2014.csv") djil.sort(key=lambda tup: tup[0]) temps = readTemps("2014_TMAX_US.csv") if (param == "print"): print "Station, Correlation, #Samples" for i in temps.keys(): if len(temps[i])>1...
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{ "lang": "python", "repo": "ppaulojr/CrazyCorrelation", "path": "/weather/correlation.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ppaulojr/CrazyCorrelation path: /weather/correlation.py #!/usr/bin/env python # -*- coding: utf-8 -*- import math from datetime import datetime import matplotlib.pyplot as plt import matplotlib.lines as mlines def string2Date(s): return datetime.strptime("-".join([s[:4],s[4:6],s[6:]]),"%Y-%m...
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{ "lang": "python", "repo": "ppaulojr/CrazyCorrelation", "path": "/weather/correlation.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: TavOexe/algorithmic_complexity path: /mazebuilder.py import random import numpy as np import algorithmic_complexity.disjointset as ds def makeMaze(rows, cols: int): maze = np.zeros((rows*2 + 1, cols*2+1)) maze[1::2, 1::2] = 1 maze[ 1][ 0] = 3 maze[-2][-1] = 3 <|fim_suffix|> ...
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{ "lang": "python", "repo": "TavOexe/algorithmic_complexity", "path": "/mazebuilder.py", "mode": "psm", "license": "CC0-1.0", "source": "the-stack-v2" }
<|fim_suffix|> s = ds.DisjointSet(len(walls)) random.shuffle(walls) while len(walls) > 0: e1, e2 = walls.pop() r1, c1 = e1 // cols, e1 % cols r2, c2 = e2 // cols, e2 % cols if not s.sameset(e1, e2): if r1 == r2 and c1 < c2: maze[r1*2+1][c1*2+2] = 1 ...
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{ "lang": "python", "repo": "TavOexe/algorithmic_complexity", "path": "/mazebuilder.py", "mode": "spm", "license": "CC0-1.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Monika-After-Story/MonikaModDev path: /tools/spritemaker.py same as other :param other: the StaticSprite to compare to :returns: False if not None and does not match, True otherwise """ if self.sweatdrop is None: return True return self.sweatd...
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{ "lang": "python", "repo": "Monika-After-Story/MonikaModDev", "path": "/tools/spritemaker.py", "mode": "psm", "license": "LicenseRef-scancode-warranty-disclaimer", "source": "the-stack-v2" }
<|fim_suffix|> def run_lstc_show(sprite_db, sprite_db_keys, ss_filter): """ Show sprites, based on filter """ # filter valid sprites filtered = filter( ss_filter.filter, SortedKeySpriteDBIter(sprite_db, sprite_db_keys) ) # show codes menutils.paginate( "Sprite Co...
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{ "lang": "python", "repo": "Monika-After-Story/MonikaModDev", "path": "/tools/spritemaker.py", "mode": "spm", "license": "LicenseRef-scancode-warranty-disclaimer", "source": "the-stack-v2" }
<|fim_prefix|># repo: Monika-After-Story/MonikaModDev path: /tools/spritemaker.py up """ self.mouth = self._get_smap(self.MTH, code, None) def __fmt_flt(self, msg_arr, string, value): """ adds appropraitely formatted filter string to msg arr """ if value is None: ...
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{ "lang": "python", "repo": "Monika-After-Story/MonikaModDev", "path": "/tools/spritemaker.py", "mode": "psm", "license": "LicenseRef-scancode-warranty-disclaimer", "source": "the-stack-v2" }
<|fim_suffix|> """DO NOT MODIFY THIS FUNCTION. Turns a concatenated string of integers separated by commas into an array of integers. (Inverse of array_to_concatenated_string). """ return np.array([int(x) for x in string.split(",")]) def parse_input(giant_string): """DO NOT MODIFY THI...
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{ "lang": "python", "repo": "lockwo/quantum_computation", "path": "/Pennylane/circuit_training_500_template.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: lockwo/quantum_computation path: /Pennylane/circuit_training_500_template.py #! /usr/bin/python3 import sys import pennylane as qml import numpy as np def classify_data(X_train, Y_train, X_test): """Develop and train your very own variational quantum classifier. Use the prov...
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{ "lang": "python", "repo": "lockwo/quantum_computation", "path": "/Pennylane/circuit_training_500_template.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for W in weights: layer(W) return qml.expval(qml.PauliZ(0)) def variational_classifier(var, x): weights = var[0] bias = var[1] return circuit(weights, x) + bias def square_loss(labels, predictions): loss = 0 ...
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{ "lang": "python", "repo": "lockwo/quantum_computation", "path": "/Pennylane/circuit_training_500_template.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: huihonkit/csci4140prj path: /app.py #! /usr/bin/env python import BaseHTTPServer import CGIHTTPServer import webbrowser import sqlite3 <|fim_suffix|>httpd = server_class(server_address, handler_class) url = 'http://localhost:{0}/{1}'.format(PORT, script_path) httpd.serve_forever()<|fim_middle...
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{ "lang": "python", "repo": "huihonkit/csci4140prj", "path": "/app.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>url = 'http://localhost:{0}/{1}'.format(PORT, script_path) httpd.serve_forever()<|fim_prefix|># repo: huihonkit/csci4140prj path: /app.py #! /usr/bin/env python import BaseHTTPServer import CGIHTTPServer import webbrowser import sqlite3 PORT = 8080 script_path = "cgi-bin/index.py" server_class = Bas...
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{ "lang": "python", "repo": "huihonkit/csci4140prj", "path": "/app.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>server_class = BaseHTTPServer.HTTPServer handler_class = CGIHTTPServer.CGIHTTPRequestHandler server_address = ("", PORT) httpd = server_class(server_address, handler_class) url = 'http://localhost:{0}/{1}'.format(PORT, script_path) httpd.serve_forever()<|fim_prefix|># repo: huihonkit/csci4140prj path:...
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{ "lang": "python", "repo": "huihonkit/csci4140prj", "path": "/app.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|><<<<<<< HEAD class Vec2: def __init__(self, x, y): self.x = x self.y = y v1 = Vec2(12, 45) # constructor is called ======= class Vec2: def __init__(self, x, y): self.x = x self.y = y v1 = Vec2(12, 45) # constructor is called >>>>>>> 23fb4d348bb9c7b7b3...
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{ "lang": "python", "repo": "bgoonz/UsefulResourceRepo2.0", "path": "/GIT-USERS/TOM-Lambda/CSEUFLEX_Intro_Python_GP/day3.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: bgoonz/UsefulResourceRepo2.0 path: /GIT-USERS/TOM-Lambda/CSEUFLEX_Intro_Python_GP/day3.py # lets talk about classes # holds data # methods to act upon that data # class called Vec2 # hold x and y as integers # constructor that can take in x and y # class Vec2 { <<<<<<< HEAD # constructor(x...
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{ "lang": "python", "repo": "bgoonz/UsefulResourceRepo2.0", "path": "/GIT-USERS/TOM-Lambda/CSEUFLEX_Intro_Python_GP/day3.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: allansid/DotaScene path: /Program/fileOutputFunctions.py # coding: utf-8 # Owner: Vinícius Aguiar de Oliveira # Program I'm coding to learn the dota2api and maybe use it afterwards as an opening to start on the e-sports scence, you never know. ##################IMPORTS##################### impor...
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{ "lang": "python", "repo": "allansid/DotaScene", "path": "/Program/fileOutputFunctions.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> with open(jsonDirectory) as loadFile: data = json.load(loadFile) loadFile.close() return data def jsonWriteFile(jsonDirectory, data): with open(jsonDirectory, 'w') as writeFile: json.dump(data, writeFile, indent = 4, sort_keys = True) writeFile.close def optionOneWrite(name, content...
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{ "lang": "python", "repo": "allansid/DotaScene", "path": "/Program/fileOutputFunctions.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> with open(fileDirectory + str(name) + ".txt", writer) as toCreate: toCreate.write(content) toCreate.close() def updateAdminFile(content): with open(adminDirectory, 'a') as writeFile: writeFile.write(content) writeFile.close<|fim_prefix|># repo: allansid/DotaScene path: /Program/fileOutputFunctio...
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{ "lang": "python", "repo": "allansid/DotaScene", "path": "/Program/fileOutputFunctions.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>predictions = list() for t in range(len(testData)): model = ARIMA(history, order=(1,1,1)) # Here we must calculate the order with the AIC number but we choose one model_fit = model.fit(trend='nc', disp=False) ar_coef, ma_coef = model_fit.arparams, model_fit.maparams resid = model_fit.resid #residue fo...
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{ "lang": "python", "repo": "lilstipher/DatascienceChallenge3", "path": "/temperature/temperature.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>"""Seabold, Skipper, and Josef Perktold. “Statsmodels: Econometric and statistical modeling with python. ” Proceedings of the 9th Python in Science Conference. 2010.""" """We follow this course for modeling ARIMA model : https://machinelearningmastery.com/make-manual-predictions-arima-models-python/ manu...
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{ "lang": "python", "repo": "lilstipher/DatascienceChallenge3", "path": "/temperature/temperature.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: lilstipher/DatascienceChallenge3 path: /temperature/temperature.py from pandas import Series #For plot time ourdataset from 2004 to 2016 from matplotlib import pyplot from statsmodels.tsa.arima_model import ARIMA #Library for Modeling our prediction problem from sklearn.metrics import mean_square...
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{ "lang": "python", "repo": "lilstipher/DatascienceChallenge3", "path": "/temperature/temperature.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: lightstep/ls-trace-py path: /tests/test_hook.py import mock from ddtrace.compat import reload_module from ddtrace.utils.hook import ( register_post_import_hook, deregister_post_import_hook, ) from tests.subprocesstest import SubprocessTestCase, run_in_subprocess @run_in_subprocess cla...
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{ "lang": "python", "repo": "lightstep/ls-trace-py", "path": "/tests/test_hook.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def test_hook_exception(self): """ Test that when a hook throws an exception that it is caught and logged as a warning. """ def test_hook(module): raise Exception('test_hook_failed') register_post_import_hook('tests.utils.test_module', test_h...
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{ "lang": "python", "repo": "lightstep/ls-trace-py", "path": "/tests/test_hook.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.methods_configs = [ { 'name': 'EI', 'model_type' : model_type, 'initial_design_numdata' : initial_design_numdata, 'initial_design_type' : initial_design_type, ...
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{ "lang": "python", "repo": "puneetjain-iclp/GPyOpt", "path": "/GPyOpt/testing/functional_tests/test_acquisitions_evaluations.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> # -- Problem setup np.random.seed(1) n_inital_design = 5 input_dim = 5 f_bounds = (-5,5) self.f_inits = samples_multidimensional_uniform([f_bounds]*input_dim,n_inital_design) self.f_inits = self.f_inits.reshape(input_dim, self.f_inits.shape[-1]) ...
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{ "lang": "python", "repo": "puneetjain-iclp/GPyOpt", "path": "/GPyOpt/testing/functional_tests/test_acquisitions_evaluations.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: puneetjain-iclp/GPyOpt path: /GPyOpt/testing/functional_tests/test_acquisitions_evaluations.py # Copyright (c) 2016, the GPyOpt Authors # Licensed under the BSD 3-clause license (see LICENSE.txt) import numpy as np import GPyOpt from GPyOpt.util.general import samples_multidimensional_uniform ...
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{ "lang": "python", "repo": "puneetjain-iclp/GPyOpt", "path": "/GPyOpt/testing/functional_tests/test_acquisitions_evaluations.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>eck_output('cmd /c -C --np %s' % keyword, shell=True) print(r) return r<|fim_prefix|># repo: maou-shonen/LINE-chat-bot path: /module/google.py import subprocess import os def google_search(keyword): print(os.getcwd(<|fim_middle|>)) r = subprocess.run(['E:\\GoogleDrive\\codes\\Lin...
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{ "lang": "python", "repo": "maou-shonen/LINE-chat-bot", "path": "/module/google.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: maou-shonen/LINE-chat-bot path: /module/google.py import subprocess import os def google_search(keyword): print(os.getcwd(<|fim_suffix|>p', keyword], stdout=subprocess.PIPE).commun icate() #r = subprocess.check_output('cmd /c -C --np %s' % keyword, shell=True) print(r) ...
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{ "lang": "python", "repo": "maou-shonen/LINE-chat-bot", "path": "/module/google.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: facebookresearch/mmf path: /mmf/models/vilbert.py # Take the dot product between "query2" and "key1" to get the raw # attention scores for value 1. attention_scores1 = torch.matmul(query_layer2, key_layer1.transpose(-1, -2)) attention_scores1 = attention_scores1 / ...
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{ "lang": "python", "repo": "facebookresearch/mmf", "path": "/mmf/models/vilbert.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: facebookresearch/mmf path: /mmf/models/vilbert.py d( self, txt_embedding: Tensor, image_embedding: Tensor, txt_attention_mask: Tensor, txt_attention_mask2: Tensor, image_attention_mask: Tensor, co_attention_mask: Tensor, output_all_e...
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{ "lang": "python", "repo": "facebookresearch/mmf", "path": "/mmf/models/vilbert.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> self, input_ids: Tensor, image_feature: Tensor, image_location: Tensor, token_type_ids: Tensor, attention_mask: Tensor, image_attention_mask: Tensor, masked_lm_labels: Optional[Tensor] = None, image_label: Optional[Tensor] = None, ...
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{ "lang": "python", "repo": "facebookresearch/mmf", "path": "/mmf/models/vilbert.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: timothyb89/tracking path: /tracking/main.py import cv2 from Queue import Queue from threading import Thread from vision import preprocess, find_edges, find_circles from point import find_points from cluster import find_clusters class TrackingThread(Thread): def __init__(self, camera_id, ...
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{ "lang": "python", "repo": "timothyb89/tracking", "path": "/tracking/main.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def show_dummy(thread, frame, iterations = 1): """ Processes the given frame in the given TrackingThread for some number of iterations. Useful for simulating against a still image when a tracking history is needed. :param thread: a TrackingThread instance :param frame: the frame t...
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{ "lang": "python", "repo": "timothyb89/tracking", "path": "/tracking/main.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: meidli/libbgp path: /libbgp/bgp/ciscorouterefresh.py # Copyright 2015-2017 Cisco Systems, Inc. # 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...
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{ "lang": "python", "repo": "meidli/libbgp", "path": "/libbgp/bgp/ciscorouterefresh.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @classmethod def unpack(cls, data, length, capability): afi, res, safi = struct.unpack("!HBB", data) return cls(value=str(Family(afi, safi)), length=length) @classmethod def pack(cls, data, capability): afi, safi = Family.str_2_int(data) if afi and safi: ...
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{ "lang": "python", "repo": "meidli/libbgp", "path": "/libbgp/bgp/ciscorouterefresh.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> @classmethod def pack(cls, data, capability): afi, safi = Family.str_2_int(data) if afi and safi: msg_body = struct.pack('!H', afi) + b'\x00' + struct.pack('!B', safi) return cls(value=data, hex_value=msg_body) else: raise RuntimeError('A...
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{ "lang": "python", "repo": "meidli/libbgp", "path": "/libbgp/bgp/ciscorouterefresh.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: pmacosta/pre-commit-hooks path: /pre_commit_hooks/identity.py #!/usr/bin/env python # identity.py # Copyright (c) 2019 Pablo Acosta-Serafini # See LICENSE for details # pylint: disable=C0111 # Standard library imports from __future__ import print_function import argparse import os import re impo...
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{ "lang": "python", "repo": "pmacosta/pre-commit-hooks", "path": "/pre_commit_hooks/identity.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> """Return value of Git configuration field/token.""" stdout, _ = subprocess.Popen( ["git", "config", token], stdout=subprocess.PIPE, stderr=subprocess.PIPE ).communicate() return _tostr(stdout).strip() def _tostr(line): # pragma: no cover return ( line if isi...
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{ "lang": "python", "repo": "pmacosta/pre-commit-hooks", "path": "/pre_commit_hooks/identity.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> """Script entry point.""" parser = argparse.ArgumentParser() parser.add_argument( "-a", "--author-file", help="Author(s) file", nargs=1, required=True ) parser.add_argument("files", nargs="*", help="Files in commit") args = parser.parse_args(argv) author_file = args.aut...
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{ "lang": "python", "repo": "pmacosta/pre-commit-hooks", "path": "/pre_commit_hooks/identity.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: wsstriving/Vivi_3.0 path: /models/Seq2seq_7/modules.py import math import torch from torch.nn import Module, Parameter import torch.nn.functional as F from torch.autograd import Variable def clip_grad(v, min, max): v_tmp = v.expand_as(v) v_tmp.register_hook(lambda g: g.clamp(min, max))...
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{ "lang": "python", "repo": "wsstriving/Vivi_3.0", "path": "/models/Seq2seq_7/modules.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> class LSTMPCell(RNNCellBase): def __init__(self, input_size, hidden_size, recurrent_size, bias=True, grad_clip=None): super(LSTMPCell, self).__init__() self.input_size = input_size self.hidden_size = hidden_size self.recurrent_size = recurrent_size self.grad_c...
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{ "lang": "python", "repo": "wsstriving/Vivi_3.0", "path": "/models/Seq2seq_7/modules.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>intersphinx_mapping = { 'python': ('https://docs.python.org/3/', None), 'sphinx': ('https://www.sphinx-doc.org/en/master/', None), 'fitlins': ('https://fitlins.readthedocs.io/en/latest/', None), 'pyNS': ('https://pyns.readthedocs.io/en/latest/', None), 'neuroscout': ('https://neuroscou...
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{ "lang": "python", "repo": "neuroscout/neuroscout-cli", "path": "/docs/source/conf.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: neuroscout/neuroscout-cli path: /docs/source/conf.py # Configuration file for the Sphinx documentation builder. import os import sys sys.path.insert(0, os.path.abspath('../../')) from neuroscout_cli import __version__ # -- Project information <|fim_suffix|>version = __version__ # -- General c...
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{ "lang": "python", "repo": "neuroscout/neuroscout-cli", "path": "/docs/source/conf.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: aideenf/machnamh path: /machnamh/demo_data.py ded a law school accredited by the American Bar Association(ABA). </li> <li><b>Region_first:</b> The geographic region in which the first BAR exam was taken. The jurisdictions used in this study match those used by the Law School Admission C...
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{ "lang": "python", "repo": "aideenf/machnamh", "path": "/machnamh/demo_data.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> <p>A 2014 report showed that black children although accounting for only 18% of preschoolers account for 48% of children suspended more than once a seperat study suggests that teachers “increased the severity of suggested disciplinary actions when the race of the teachers didn’t match that of the ch...
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{ "lang": "python", "repo": "aideenf/machnamh", "path": "/machnamh/demo_data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> If we follow the timelines of the educational path in the USA, which is reflected in this database, the chronology of academic milestones and their corresponding measurements are, first the undergraduate grade point average(UGPA), followed by the LSAT which is the standardised test necessary to ...
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{ "lang": "python", "repo": "aideenf/machnamh", "path": "/machnamh/demo_data.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: pmchozas/termitup path: /modules_api/frecuency.py def frecuency(freqlist, cleanlist): listmax=list() i=int() while(len(listmax) <301): spl=freqlist[i].split(',') freq=spl[0] term=spl[1] if(term in cleanlist): listmax.append(freqlist[i]) i=i+1 return(listmax) <|fim_suffix|> ...
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{ "lang": "python", "repo": "pmchozas/termitup", "path": "/modules_api/frecuency.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>def frequencyTerm(freqlist, termin): freqTerm=int() for i in freqlist: spl=i.split(',') freq=spl[0] term=spl[1][:-1] if(termin in term): freqTerm=freq return(freqTerm)<|fim_prefix|># repo: pmchozas/termitup path: /modules_api/frecuency.py def frecuency(freqlist, cleanlist): listmax=lis...
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{ "lang": "python", "repo": "pmchozas/termitup", "path": "/modules_api/frecuency.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> freqTerm=int() for i in freqlist: spl=i.split(',') freq=spl[0] term=spl[1][:-1] if(termin in term): freqTerm=freq return(freqTerm)<|fim_prefix|># repo: pmchozas/termitup path: /modules_api/frecuency.py def frecuency(freqlist, cleanlist): listmax=list() i=int() while(len(listmax) <301...
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{ "lang": "python", "repo": "pmchozas/termitup", "path": "/modules_api/frecuency.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def serialize_for_event(self): d = super().serialize_for_event() d["root"] = self.root return d def download_all_catalog(self): filepath = self.get_all_catalog_local_path() r = requests.get(os.path.join(self.root, "catalogs/all")) if not r.status_co...
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{ "lang": "python", "repo": "ankurvaishley/zentral", "path": "/zentral/contrib/monolith/repository_backends/http.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> url = os.path.join(self.root, section, name) if cache_server: url = cache_server.get_cache_url(url) return HttpResponseRedirect(url)<|fim_prefix|># repo: ankurvaishley/zentral path: /zentral/contrib/monolith/repository_backends/http.py import os.path from django.http i...
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{ "lang": "python", "repo": "ankurvaishley/zentral", "path": "/zentral/contrib/monolith/repository_backends/http.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: ankurvaishley/zentral path: /zentral/contrib/monolith/repository_backends/http.py import os.path from django.http import HttpResponseRedirect import requests from zentral.contrib.monolith.exceptions import RepositoryError from .base import BaseRepository class Repository(BaseRepository): de...
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{ "lang": "python", "repo": "ankurvaishley/zentral", "path": "/zentral/contrib/monolith/repository_backends/http.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: SBEMimage/SBEMimage path: /src/sem_control.py _limits: range of the SEM XY motors in micrometres # [x_min, x_max, y_min, y_max] self.stage_limits = json.loads( self.syscfg['stage']['sem_stage_limits']) # speed in microns/second of X and Y stage motors s...
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{ "lang": "python", "repo": "SBEMimage/SBEMimage", "path": "/src/sem_control.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: SBEMimage/SBEMimage path: /src/sem_control.py T License. # See LICENSE.txt in the project root folder. # ============================================================================== """This module provides the commands to operate the SEM. Only the functions that are actually required in SBEM...
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{ "lang": "python", "repo": "SBEMimage/SBEMimage", "path": "/src/sem_control.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """Set the scan rotation angle (in degrees).""" raise NotImplementedError def acquire_frame(self, save_path_filename, extra_delay=0): """Acquire a full frame and save it to save_path_filename. All imaging parameters must be applied BEFORE calling this function. ...
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{ "lang": "python", "repo": "SBEMimage/SBEMimage", "path": "/src/sem_control.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def say(text: str): args = text.split(' ', 1) if len(args) == 1 or len(args[1]) == 0: logger.info('say <message>') else: if pcrc.is_online(): pcrc.chat(args[1]) else: logger.warning('PCRC is not online, cannot chat') def whitelist_commands(text: str, config: Config): whitelist = config....
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{ "lang": "python", "repo": "Fallen-Breath/PCRC", "path": "/pcrc/cli_entry.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: Fallen-Breath/PCRC path: /pcrc/cli_entry.py import sys import time from logging import Logger from pcrc import constant from pcrc.config import SettableOptions, Config from pcrc.pcrc_client import PcrcClient from pcrc.protocol import SUPPORTED_MINECRAFT_VERSIONS pcrc = PcrcClient() logger: Logg...
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{ "lang": "python", "repo": "Fallen-Breath/PCRC", "path": "/pcrc/cli_entry.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if pcrc.has_authenticated(): if warn_if_already_auth: logger.warning('Minecraft authentication is already done') else: pcrc.authenticate() def say(text: str): args = text.split(' ', 1) if len(args) == 1 or len(args[1]) == 0: logger.info('say <message>') else: if pcrc.is_online(): pcrc...
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{ "lang": "python", "repo": "Fallen-Breath/PCRC", "path": "/pcrc/cli_entry.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }