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<|fim_prefix|># repo: kohnakagawa/ghidra_scripts path: /ghidra9.2.1_pyi/ghidra/app/util/datatype/microsoft/MSDataTypeUtils.pyi from typing import List import ghidra.program.model.address import ghidra.program.model.data import ghidra.program.model.listing import ghidra.program.model.mem import java.lang class MSData...
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{ "lang": "python", "repo": "kohnakagawa/ghidra_scripts", "path": "/ghidra9.2.1_pyi/ghidra/app/util/datatype/microsoft/MSDataTypeUtils.pyi", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ Gets a pointer displacement data type. @param program the program for the data type. @return the pointer displacement data type. """ ... @staticmethod def getReferenceDataType(program: ghidra.program.model.listing.Program, referredToDataType: gh...
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{ "lang": "python", "repo": "kohnakagawa/ghidra_scripts", "path": "/ghidra9.2.1_pyi/ghidra/app/util/datatype/microsoft/MSDataTypeUtils.pyi", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @staticmethod def getReferencedAddress(program: ghidra.program.model.listing.Program, address: ghidra.program.model.address.Address) -> ghidra.program.model.address.Address: """ Gets the referred to address from the bytes in the program at the indicated address. If the pro...
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{ "lang": "python", "repo": "kohnakagawa/ghidra_scripts", "path": "/ghidra9.2.1_pyi/ghidra/app/util/datatype/microsoft/MSDataTypeUtils.pyi", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> # Start a search. engine.position(board) engine.go(movetime=100) if board.turn == chess.WHITE: counts["scores"].append((info_handler.info["score"][1][0]) / 100) else: counts["scores"].append((-info_handler.info["score"][1][0]) / 100) ...
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{ "lang": "python", "repo": "CoderAryanAnand/fun_projects", "path": "/Chess_analysis/analysis.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: CoderAryanAnand/fun_projects path: /Chess_analysis/analysis.py import matplotlib import matplotlib.pyplot as plt import chess import chess.svg import chess.pgn #from IPython.display import SVG pgn = open("C:/Users/Aryan Anand/Documents/12323.pgn") # n = 1 # print(n) for i in range(1, 3): ...
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{ "lang": "python", "repo": "CoderAryanAnand/fun_projects", "path": "/Chess_analysis/analysis.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ctlee/bccgc4 path: /Docking_Schrodinger_Glide_templates/Glide_SP_core_templates/Glide_SP_core_ensemble_template/grids/gen_grids.py #Code to write bash script that generates grids based off of the input files made by grid_in.py <|fim_suffix|>with open('gen_grids.sh','w') as newfile: for num ...
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{ "lang": "python", "repo": "ctlee/bccgc4", "path": "/Docking_Schrodinger_Glide_templates/Glide_SP_core_templates/Glide_SP_core_ensemble_template/grids/gen_grids.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>with open('gen_grids.sh','w') as newfile: for num in range(10): newfile.write('$SCHRODINGER/glide /scratch/jegan/GLIDE_'+dock+'_core_docking/'+method+'_docking/grids/'+method+'_grid_'+str(num)+'.in\n')<|fim_prefix|># repo: ctlee/bccgc4 path: /Docking_Schrodinger_Glide_templates/Glide_SP_core_...
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{ "lang": "python", "repo": "ctlee/bccgc4", "path": "/Docking_Schrodinger_Glide_templates/Glide_SP_core_templates/Glide_SP_core_ensemble_template/grids/gen_grids.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: vshalt/flask-reddit path: /app/community/views.py from app.community import community_blueprint from app.community.forms import NewCommunityForm, UpdateCommunityForm from app import db from app.models import Community, CommunityParticipant from flask import render_template, redirect, url_for, fla...
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{ "lang": "python", "repo": "vshalt/flask-reddit", "path": "/app/community/views.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@community_blueprint.route('/community/join/<string:name>') @login_required def join_community(name): community = Community.query.filter_by(name=name).first() if community: community_participant = CommunityParticipant.query.filter_by(user_id=current_user.id, community_id=community.id).firs...
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{ "lang": "python", "repo": "vshalt/flask-reddit", "path": "/app/community/views.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> environ['repoze.debug.canary'] = Canary() return self.app(environ, start_response) class Canary(object): pass def make_middleware(app, global_conf): """ Paste filter-app converter """ return CanaryMiddleware(app)<|fim_prefix|># repo: repoze/repoze.debug path: /repoze/debug/c...
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{ "lang": "python", "repo": "repoze/repoze.debug", "path": "/repoze/debug/canary.py", "mode": "spm", "license": "BSD-3-Clause-Modification", "source": "the-stack-v2" }
<|fim_prefix|># repo: repoze/repoze.debug path: /repoze/debug/canary.py class CanaryMiddleware: def __init__(self, app): <|fim_suffix|> """ Paste filter-app converter """ return CanaryMiddleware(app)<|fim_middle|> self.app = app def __call__(self, environ, start_response): environ['repoz...
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{ "lang": "python", "repo": "repoze/repoze.debug", "path": "/repoze/debug/canary.py", "mode": "psm", "license": "BSD-3-Clause-Modification", "source": "the-stack-v2" }
<|fim_suffix|>def make_middleware(app, global_conf): """ Paste filter-app converter """ return CanaryMiddleware(app)<|fim_prefix|># repo: repoze/repoze.debug path: /repoze/debug/canary.py class CanaryMiddleware: def __init__(self, app): self.app = app def __call__(self, environ, start_response...
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{ "lang": "python", "repo": "repoze/repoze.debug", "path": "/repoze/debug/canary.py", "mode": "spm", "license": "BSD-3-Clause-Modification", "source": "the-stack-v2" }
<|fim_prefix|># repo: kondratyev-nv/training path: /python/test/disjoint_set_tests.py import unittest import os from src.disjoint_set import DisjointSet class disjoint_set_tests(unittest.TestCase): def test_not_connected_when_set_is_empty(self): s = DisjointSet() self.assertFalse(s.is_connected(...
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{ "lang": "python", "repo": "kondratyev-nv/training", "path": "/python/test/disjoint_set_tests.py", "mode": "psm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_suffix|> s = DisjointSet() self.assertEqual(2, s.union(1, 2)) self.assertTrue(s.is_connected(1, 2)) self.assertTrue(s.is_connected(2, 1)) def test_can_connect_two_sets(self): s = DisjointSet() self.assertEqual(2, s.union(1, 2)) self.assertTrue(s.is_conne...
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{ "lang": "python", "repo": "kondratyev-nv/training", "path": "/python/test/disjoint_set_tests.py", "mode": "spm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_suffix|> s = DisjointSet() self.assertEqual(2, s.union(1, 2)) self.assertEqual(3, s.union(2, 3)) self.assertEqual(4, s.union(3, 4)) self.assertEqual(4, s.union(4, 1)) def test_can_process_large_input_from_file(self): s = DisjointSet() pairs = self.__read...
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{ "lang": "python", "repo": "kondratyev-nv/training", "path": "/python/test/disjoint_set_tests.py", "mode": "spm", "license": "Unlicense", "source": "the-stack-v2" }
<|fim_prefix|># repo: NESS-Network/WEB_TAGS path: /webtags.py from flask import Flask, render_template, request, Response, redirect import json from classes.Updater import Updater from classes.DI import DI from classes.Config import Config app = Flask(__name__) # pip install requests # pip install json-rpc @app.rou...
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{ "lang": "python", "repo": "NESS-Network/WEB_TAGS", "path": "/webtags.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @app.route('/show/<int:network_id>/<int:lang_id>/<int:type_id>/<int:tags_id>/<int:resource_id>') def show_resource(network_id, lang_id, type_id, tags_id, resource_id): rep = DI.get_repository() network = rep.get_network_name_by_id(network_id) lang = rep.get_lang_name_by_id(lang_id) type =...
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{ "lang": "python", "repo": "NESS-Network/WEB_TAGS", "path": "/webtags.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> @app.route('/langs/<int:network_id>') def show_langs(network_id): rep = DI.get_repository() langs = rep.read_langs(network_id) network = rep.get_network_name_by_id(network_id) return render_template('list/langs.html', title='Main', nav='tags', langs=langs, netwo...
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{ "lang": "python", "repo": "NESS-Network/WEB_TAGS", "path": "/webtags.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: tox-dev/tox path: /tests/config/loader/test_loader.py from __future__ import annotations from typing import TYPE_CHECKING import pytest from tox.config.cli.parse import get_options from tox.config.loader.api import Override if TYPE_CHECKING: from tox.pytest import CaptureFixture <|fim_su...
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{ "lang": "python", "repo": "tox-dev/tox", "path": "/tests/config/loader/test_loader.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> parsed, _, __, ___, ____ = get_options(flag, "magic=true") assert len(parsed.override) == 1 value = parsed.override[0] assert value.key == "magic" assert value.value == "true" assert not value.namespace assert value.append is False @pytest.mark.parametrize("flag", ["-x", "--o...
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{ "lang": "python", "repo": "tox-dev/tox", "path": "/tests/config/loader/test_loader.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def main(): """Command line execution of this building block. Please check the command line documentation.""" parser = argparse.ArgumentParser(description="Wrapper for the GROMACS make_ndx module.", formatter_class=lambda prog: argparse.RawTextHelpFormatter(pro...
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{ "lang": "python", "repo": "bioexcel/biobb_md", "path": "/biobb_md/gromacs/make_ndx.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: bioexcel/biobb_md path: /biobb_md/gromacs/make_ndx.py #!/usr/bin/env python3 """Module containing the MakeNdx class and the command line interface.""" import os import argparse from pathlib import Path from biobb_common.generic.biobb_object import BiobbObject from biobb_common.configuration impo...
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{ "lang": "python", "repo": "bioexcel/biobb_md", "path": "/biobb_md/gromacs/make_ndx.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> # Input/Output files self.io_dict = { "in": {"input_structure_path": input_structure_path, "input_ndx_path": input_ndx_path}, "out": {"output_ndx_path": output_ndx_path} } # Properties specific for BB self.selection = properties.get('selecti...
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{ "lang": "python", "repo": "bioexcel/biobb_md", "path": "/biobb_md/gromacs/make_ndx.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: maximebenoitgagne/wintertime path: /utils/python/python/tiles/variable.py les) > 0: self.tiled = True else: globpatt = base + '.meta' if debug: print 'looking for metafiles:', globpatt metafiles = glob(base + '.meta') ...
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{ "lang": "python", "repo": "maximebenoitgagne/wintertime", "path": "/utils/python/python/tiles/variable.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if trunc.endswith('/'): dvs = unknowndimvals(trunc) dimvals.update(dvs) first = dict((k,v[0]) for k,v in dvs.items()) else: dvs = unknowndimvals(trunc,sufs) dimvals.update(dv...
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{ "lang": "python", "repo": "maximebenoitgagne/wintertime", "path": "/utils/python/python/tiles/variable.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> ndims = i i = 0 vardimnames = [] while re.search(r'{v%d[}:]' % i, tmpl): vardimnames.append('v%d' % i) i += 1 nvardims = i dimvals = dict( (k,kwargs.get(k, [])) for k in dimnames+vardimnames ) first = dict( (k,kwargs.get(k, ['*'])[0]) for k in dimnames+vardim...
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{ "lang": "python", "repo": "maximebenoitgagne/wintertime", "path": "/utils/python/python/tiles/variable.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> Inverts y => x. """ # During training, keep smoothed average of sample mean and variance if self.training: mean, var = y.mean(0), y.var(0) # NOTE: The momentum variable agrees with the definition in e.g. `torch.nn.BatchNorm1d` self.movin...
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{ "lang": "python", "repo": "ae-foster/pyro", "path": "/pyro/distributions/transforms/batch_norm.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ae-foster/pyro path: /pyro/distributions/transforms/batch_norm.py import torch import torch.nn as nn from torch.distributions import constraints import torch.nn.functional as F from pyro.distributions.torch_transform import TransformModule from pyro.distributions.util import copy_docs_from @co...
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{ "lang": "python", "repo": "ae-foster/pyro", "path": "/pyro/distributions/transforms/batch_norm.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def test_balance_tags(self): for test, texturize, expected in BALANCE_TESTS: result = content.balance_tags(test, texturize) if result != expected: raise ValueError(Differ(expected=expected, result=result)) def test_texturize_block(self): ...
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{ "lang": "python", "repo": "ludoo/wpkit", "path": "/wpkit/tests/wp/test_content.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: ludoo/wpkit path: /wpkit/tests/wp/test_content.py # encoding: utf-8 from django.test import TestCase from django_nose.tools import * from wpkit.wp import content from .. import Differ BALANCE_TESTS = ( ( '<p> <p>Test 0</p>', False, '<p> </p><p>Test 0</p>' ), ...
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{ "lang": "python", "repo": "ludoo/wpkit", "path": "/wpkit/tests/wp/test_content.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: ybyangjing/Faster_RCNN_SUNRGBD path: /examples/faster_rcnn/train_SUNRGBD.py """ faster_rcnn_chainercv train_SUNRGBD created by Kazunari on 2018/06/26 """ from __future__ import division import argparse import numpy as np import os.path as osp import datetime import matplotlib matplotlib.use(...
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{ "lang": "python", "repo": "ybyangjing/Faster_RCNN_SUNRGBD", "path": "/examples/faster_rcnn/train_SUNRGBD.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> train_data = SUNRGBDDataset(args.dataset_path,mode="train") test_data = SUNRGBDDataset(args.dataset_path, mode="test") sunrgbd_bbox_label_names = train_data.get_dataset_label() faster_rcnn = FasterRCNNVGG16(n_fg_class=len(sunrgbd_bbox_label_names), pretr...
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{ "lang": "python", "repo": "ybyangjing/Faster_RCNN_SUNRGBD", "path": "/examples/faster_rcnn/train_SUNRGBD.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> b+=1 if i=='x': break total=max(0,a-b) outfile=open('acadout.txt','w') outfile.write(str(total)) outfile.close()<|fim_prefix|># repo: eddiegz/Personal-C path: /AIO/academic/academic espionage.py infile=open('acadin.txt','r').readlines() a,b=0,0 for e in infile:<|fim_middle|> ...
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{ "lang": "python", "repo": "eddiegz/Personal-C", "path": "/AIO/academic/academic espionage.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: eddiegz/Personal-C path: /AIO/academic/academic espionage.py infile=open('acadin.txt','r').readlines() a,b=0,0 for e in infile:<|fim_suffix|>e=open('acadout.txt','w') outfile.write(str(total)) outfile.close()<|fim_middle|> i=e.strip() if i=='i': a+=1 elif i=='o': ...
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{ "lang": "python", "repo": "eddiegz/Personal-C", "path": "/AIO/academic/academic espionage.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def __init__(self, cluster, bind_address=None): super(FrontendStanza, self).__init__("frontend") self.header = "frontend %s" % cluster.name if not bind_address: bind_address = "" self.add_lines(cluster.haproxy.get("frontend", [])) self.add_line("bi...
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{ "lang": "python", "repo": "wglass/lighthouse", "path": "/lighthouse/haproxy/stanzas/frontend.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> self.add_lines(cluster.haproxy.get("frontend", [])) self.add_line("bind %s:%s" % (bind_address, cluster.haproxy["port"])) self.add_line("default_backend %s" % cluster.name)<|fim_prefix|># repo: wglass/lighthouse path: /lighthouse/haproxy/stanzas/frontend.py from .stanza import Sta...
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{ "lang": "python", "repo": "wglass/lighthouse", "path": "/lighthouse/haproxy/stanzas/frontend.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: wglass/lighthouse path: /lighthouse/haproxy/stanzas/frontend.py from .stanza import Stanza class FrontendStanza(Stanza): """ Stanza subclass representing a "frontend" stanza. A frontend stanza defines an address to bind to an a backend to route traffic to. A cluster can define...
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{ "lang": "python", "repo": "wglass/lighthouse", "path": "/lighthouse/haproxy/stanzas/frontend.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> profiles=Profile.objects.all() followers=Following.objects.filter(username=request.user.username) # print(followers) followings=Following.objects.filter(followed=request.user.username) return render(request,"profile.html", {'profiles':profiles,'followers':followers, 'following':f...
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{ "lang": "python", "repo": "Koech-code/Instagram", "path": "/instagram/views.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: Koech-code/Instagram path: /instagram/views.py from django.http import HttpResponseRedirect, Http404 from django.shortcuts import render, redirect from .models import Following, Image, Profile from django.contrib.auth.models import User from django.contrib.auth.decorators import login_required fr...
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{ "lang": "python", "repo": "Koech-code/Instagram", "path": "/instagram/views.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def to_csv(self, data, label): with open(f"{label}.csv", 'w', newline="") as myfile: wr = csv.writer(myfile) for item in data: wr.writerow([item[0], item[1]]) def show(self): plt.show()<|fim_prefix|># repo: swifmaneum/ContainerPacking path:...
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{ "lang": "python", "repo": "swifmaneum/ContainerPacking", "path": "/src/Plotter.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> """ Add a list of tuples (x, y) as a line plot, see https://stackoverflow.com/a/18458953/5730444""" plt.figure(figure_number) plt.plot(*zip(*data), label=label, marker='.', linestyle="") plt.legend(loc="upper left") def to_csv(self, data, label): with open(f"{...
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{ "lang": "python", "repo": "swifmaneum/ContainerPacking", "path": "/src/Plotter.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: swifmaneum/ContainerPacking path: /src/Plotter.py import csv import matplotlib.pyplot as plt class Plotter(object): def add_figure(self, title, x_label, y_label): figure = plt.figure() plt.grid() plt.title(title) plt.xlabel(x_label) plt.ylabel(y_labe...
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{ "lang": "python", "repo": "swifmaneum/ContainerPacking", "path": "/src/Plotter.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> dev_type = data.get("dev_type") devices = [] if dev_type == "light": devices.append(TuyaLight(data, api)) elif dev_type == "climate": devices.append(TuyaClimate(data, api)) elif dev_type == "scene": devices.append(TuyaScene(data, api)) elif dev_type == "fan...
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{ "lang": "python", "repo": "ollo69/tuyaha", "path": "/tuyaha/devices/factory.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: ollo69/tuyaha path: /tuyaha/devices/factory.py from tuyaha.devices.climate import TuyaClimate from tuyaha.devices.cover import TuyaCover from tuyaha.devices.fan import TuyaFanDevice from tuyaha.devices.light import TuyaLight from tuyaha.devices.lock import TuyaLock from tuyaha.devices.scene impor...
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{ "lang": "python", "repo": "ollo69/tuyaha", "path": "/tuyaha/devices/factory.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if dev_type == "light": devices.append(TuyaLight(data, api)) elif dev_type == "climate": devices.append(TuyaClimate(data, api)) elif dev_type == "scene": devices.append(TuyaScene(data, api)) elif dev_type == "fan": devices.append(TuyaFanDevice(data, api)) ...
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{ "lang": "python", "repo": "ollo69/tuyaha", "path": "/tuyaha/devices/factory.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>if ('POLVO' in x) == True and ('POLVO' in y) == False: #Peixe ODEIA polvos points = points - 1000 if ('POLVO' in y) == True and ('POLVO' in x) == False: points = points + 1000 if ('POLVO' in x) == True and ('POLVO' in y) == True: points = 5000 print('\033[33m—'*32) if points != 5000: ...
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{ "lang": "python", "repo": "LuckyCards/Curso-Python3", "path": "/Aleatorios/PeixeBurro.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: LuckyCards/Curso-Python3 path: /Aleatorios/PeixeBurro.py from time import sleep print('\n') print('\033[33m—'*32) print('\033[36m PERGUNTE AO PEIXE v0.2Alpha') print('\033[33m—'*32, '\033[m\n') x = str(input('Digite uma palavra: ')).strip().upper() y = str(input('Digite outra palavra: ')).strip(...
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{ "lang": "python", "repo": "LuckyCards/Curso-Python3", "path": "/Aleatorios/PeixeBurro.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def remove_vm_hdd(vmuuid, vminfo, hdduuid): cmd = ' '.join([ 'VBoxManage', 'storageattach {vm}', '--storagectl {sctl}', '--medium {med}', '--device {dev}', '--port {port}', '--type hdd', ]) command = ShellCommand( cmd, vm=...
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{ "lang": "python", "repo": "neuroticnerd/boxbox", "path": "/boxbox/virtualbox.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: neuroticnerd/boxbox path: /boxbox/virtualbox.py """ need to check out https://github.com/VRGhost/vbox """ import re import os from subprocess import CalledProcessError from .shellcommand import ShellCommand from . import utils re_sctl = r'(?P<sctl>.{0,}?)\s*\((?P<device>\d+),\s*(?P<port>\d+)\)...
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{ "lang": "python", "repo": "neuroticnerd/boxbox", "path": "/boxbox/virtualbox.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|>def get_vm_info(vmname): showvm = 'VBoxManage showvminfo {vmname}' command = ShellCommand(showvm, vmname=vmname).grep(vmname).grep('vmdk') utils.debug(command.prompt) utils.debug(command) vminfomatch = re_vm.match(command.out) if vminfomatch is None: utils.error('ERROR: can...
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{ "lang": "python", "repo": "neuroticnerd/boxbox", "path": "/boxbox/virtualbox.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: jlgarridol/sslearn path: /sslearn/utils.py import numpy as np import os import math import pandas as pd from statsmodels.stats.proportion import proportion_confint from sklearn.tree import DecisionTreeClassifier from sklearn.base import ClassifierMixin def safe_division(dividend, divisor, eps...
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{ "lang": "python", "repo": "jlgarridol/sslearn", "path": "/sslearn/utils.py", "mode": "psm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> if base_classifier is None: return DecisionTreeClassifier() elif can_be_list and (type(base_classifier) == list or type(base_classifier) == tuple): if collection_size is not None: if len(base_classifier) != collection_size: raise AttributeError(f"base_c...
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{ "lang": "python", "repo": "jlgarridol/sslearn", "path": "/sslearn/utils.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_suffix|> classes = np.unique(y_label) proportion = calculate_prior_probability(y_label) factor = 1/min(proportion.values()) number_per_class = dict() for c in classes: number_per_class[c] = math.ceil(proportion[c] * factor) return number_per_class def check_classifier(base_classi...
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{ "lang": "python", "repo": "jlgarridol/sslearn", "path": "/sslearn/utils.py", "mode": "spm", "license": "BSD-3-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: inesp/blog-structuring-old-python path: /main.py from city import City from zoo import Zoo <|fim_suffix|>assert vienna.zoo assert isinstance(vienna.zoo, Zoo) assert vienna.zoo.size == 130 assert vienna.zoo._owner_name == "Mrs Zoo Keeper" print( f"City: {vienna.name}\n" f"Zoo owner: {vi...
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{ "lang": "python", "repo": "inesp/blog-structuring-old-python", "path": "/main.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|>print( f"City: {vienna.name}\n" f"Zoo owner: {vienna.zoo._owner_name}\n" f"Zoo's size: {vienna.zoo.size}\n" f"Zoo's animals: {', '.join([animal.name for animal in vienna.zoo.animals])}" )<|fim_prefix|># repo: inesp/blog-structuring-old-python path: /main.py from city import City from zoo ...
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{ "lang": "python", "repo": "inesp/blog-structuring-old-python", "path": "/main.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> """ From platform.py: _supported_dists = ( 'SuSE', 'debian', 'fedora', 'redhat', 'centos', 'mandrake', 'mandriva', 'rocks', 'slackware', 'yellowdog', 'gentoo', 'UnitedLinux', 'turbolinux', 'arch', 'mageia') """ return distro.linux_distribution(full_distribution_...
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{ "lang": "python", "repo": "AbnormalSec/darkbox", "path": "/darkbox/util/osutil.py", "mode": "spm", "license": "WTFPL", "source": "the-stack-v2" }
<|fim_prefix|># repo: AbnormalSec/darkbox path: /darkbox/util/osutil.py """darkbox.util.osutil""" import distro import platform def get_platform(): <|fim_suffix|>def get_distro(): """ From platform.py: _supported_dists = ( 'SuSE', 'debian', 'fedora', 'redhat', 'centos', 'mandrake', 'mand...
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{ "lang": "python", "repo": "AbnormalSec/darkbox", "path": "/darkbox/util/osutil.py", "mode": "psm", "license": "WTFPL", "source": "the-stack-v2" }
<|fim_suffix|> if isinstance(txt, str): txt = txt.lower() if txt in ["maxy", "mxy", "n", "⊤"]: return Edge.MaxY elif txt in ["maxx", "mxx", "e", "⊣"]: return Edge.MaxX elif txt in ["miny", "mny", "s", "⊥"]: return Edge.MinY elif txt in ["min...
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{ "lang": "python", "repo": "rohernandezz/coldtype", "path": "/coldtype/geometry/edge.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: rohernandezz/coldtype path: /coldtype/geometry/edge.py from enum import Enum class Edge(Enum): MaxY = 1 MaxX = 2 MinY = 3 MinX = 4 CenterY = 5 CenterX = 6 def PairFromCompass(cmp): if isinstance(cmp, Edge): return None if isinstance(cmp, ...
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{ "lang": "python", "repo": "rohernandezz/coldtype", "path": "/coldtype/geometry/edge.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: BonsaiAI/ray path: /python/ray/util/serialization.py import ray def register_serializer(cls, *, serializer, deserializer): """Use the given serializer to serialize instances of type ``cls``, and use the deserializer to deserialize the serialized object. <|fim_suffix|> Args: ...
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{ "lang": "python", "repo": "BonsaiAI/ray", "path": "/python/ray/util/serialization.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> Args: cls: A Python class/type. """ context = ray.worker.global_worker.get_serialization_context() context._unregister_cloudpickle_reducer(cls)<|fim_prefix|># repo: BonsaiAI/ray path: /python/ray/util/serialization.py import ray def register_serializer(cls, *, serializer, deseri...
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{ "lang": "python", "repo": "BonsaiAI/ray", "path": "/python/ray/util/serialization.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> if filter(event): return handler(event, context) return handle<|fim_prefix|># repo: linuxbasic/async_event_bus path: /async_event_bus/event_handler.py from async_event_bus.types import EventHandler, FilterFunction, EventHandlerFunction, Context, EventGenerator, Event def define_...
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{ "lang": "python", "repo": "linuxbasic/async_event_bus", "path": "/async_event_bus/event_handler.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: linuxbasic/async_event_bus path: /async_event_bus/event_handler.py from async_event_bus.types import EventHandler, FilterFunction, EventHandlerFunction, Context, EventGenerator, Event <|fim_suffix|> def handle(event: Event) -> EventGenerator: if filter(event): return handl...
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{ "lang": "python", "repo": "linuxbasic/async_event_bus", "path": "/async_event_bus/event_handler.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: vaexio/vaex path: /packages/vaex-astro/vaex/astro/votable.py import astropy.io.votable import vaex from vaex.dataset import DatasetFile from vaex.dataset_misc import _try_unit class VOTable(DatasetFile): snake_name = "votable" def __init__(self, filename, fs_options={}, fs=None): <|fim_suffix...
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{ "lang": "python", "repo": "vaexio/vaex", "path": "/packages/vaex-astro/vaex/astro/votable.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> for field in self.first_table.fields: name = field.name data = self.first_table.array[name] type = self.first_table.array[name].dtype clean_name = name if field.ucd: self.ucds[clean_name] = field.ucd if field.unit: unit = _try_unit(field.unit) if unit: self.units[clean...
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{ "lang": "python", "repo": "vaexio/vaex", "path": "/packages/vaex-astro/vaex/astro/votable.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> return ['csat-collect', self.key, model.example, ] def build_parser(self, base): from . import graphs parser = super(ExampleGraphsCollector, self).build_parser(base) parser.add_argument('graph_name') parser.add_argument('-l', '--list', action=ListAction, ...
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{ "lang": "python", "repo": "GaretJax/csat", "path": "/csat/collectors/examples/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def get_model(self): from . import models return models.ExamplesConfig def get_command(self, model): return ['csat-collect', self.key, model.example, ] def build_parser(self, base): from . import graphs parser = super(ExampleGraphsCollector, self).buil...
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{ "lang": "python", "repo": "GaretJax/csat", "path": "/csat/collectors/examples/__init__.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: GaretJax/csat path: /csat/collectors/examples/__init__.py import argparse from csat.acquisition import base __version__ = '0.1.0' class ListAction(argparse.Action): def __init__(self, option_strings, dest, const, default=None, required=False, help=None, metavar=None): ...
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{ "lang": "python", "repo": "GaretJax/csat", "path": "/csat/collectors/examples/__init__.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>@Client.on_message(filters.command('stats')) async def give_sysinfo(client, message): splatform = platform.system() platform_release = platform.release() platform_version = platform.version() architecture = platform.machine() hostname = socket.gethostname() ip_address = socket.geth...
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{ "lang": "python", "repo": "decentboyy/PatriciaVideoPlayer", "path": "/player/modules/stats.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>**PlatForm :** `{splatform}` **PlatForm - Release :** `{platform_release}` **PlatFork - Version :** `{platform_version}` **Architecture :** `{architecture}` **Hostname :** `{hostname}` **IP :** `{ip_address}` **Mac :** `{mac_address}` **Processor :** `{processor}` **Ram : ** `{ram}` **CPU :** `{cpu_len}` ...
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{ "lang": "python", "repo": "decentboyy/PatriciaVideoPlayer", "path": "/player/modules/stats.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: decentboyy/PatriciaVideoPlayer path: /player/modules/stats.py import platform import re import socket import sys import time import uuid from datetime import datetime from os import environ, execle, path, remove from player.helpers.decorators import humanbytes import psutil from pyrogram import ...
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{ "lang": "python", "repo": "decentboyy/PatriciaVideoPlayer", "path": "/player/modules/stats.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> sql = """INSERT INTO lagou_it\ SET position_name=%s,company_name=%s,company_size=%s,city=%s,industry=%s,salary=%s,jobnature=%s,education=%s,workyear=%s""" for x in range(0, len(result)): cursor.execute(sql,(result[x][0],result[x][1],result[x][2],result[x][3],result[x][4],resu...
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{ "lang": "python", "repo": "lfthwjx/DataManipulation", "path": "/Project/Recruit/lagou_it.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: lfthwjx/DataManipulation path: /Project/Recruit/lagou_it.py __author__ = 'Jun Wang' # -*- coding:utf-8 -*- import json,urllib2,sys, MySQLdb # import pandas as pd reload(sys) sys.setdefaultencoding('utf8') # from pandas import DataFrame,Series db = MySQLdb.connect(host="localhost",user="r...
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{ "lang": "python", "repo": "lfthwjx/DataManipulation", "path": "/Project/Recruit/lagou_it.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> condition = eval(FILTER_CODE.format(data['condition'])) try: action_strings = data['actions'] except KeyError: action_strings = [] actions = [] for action_string in action_strings: _LOG.debug('parsing action: %s', action_string)...
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{ "lang": "python", "repo": "mbdevpl/maildaemon", "path": "/maildaemon/message_filter.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_prefix|># repo: mbdevpl/maildaemon path: /maildaemon/message_filter.py """Filter that is applied on e-mail messages.""" import functools import logging import operator import re import typing as t from .message import Message from .connection import Connection from .filter_actions import mark, move _LOG = log...
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{ "lang": "python", "repo": "mbdevpl/maildaemon", "path": "/maildaemon/message_filter.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def __init__( self, connections: t.List[Connection], condition: t.List[t.List[t.Tuple[str, t.Callable[[str], bool]]]], actions: t.List[t.Tuple[t.Callable[[t.Any], None], t.Sequence[t.Any]]]): self._connections = connections self._condition = conditio...
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{ "lang": "python", "repo": "mbdevpl/maildaemon", "path": "/maildaemon/message_filter.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def NMI(A, B, explation=False): if explation: print("the more the better") total = len(A) A_ids = set(A) B_ids = set(B) A_index_map = index_hash_map(A) B_index_map = index_hash_map(B) # 互信息计算 MI = 0 for idA in A_ids: for idB in B_ids: idAOcc...
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{ "lang": "python", "repo": "luluyao9494/PyTls", "path": "/PyTls/matht.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def JSD(prob1, prob2): ''' :desc 衡量prob1 和 prob2两个分布的相似程度 :param prob1: :param prob2: :return: ''' if len(prob1) != len(prob2): raise ValueError("input should be the same length") prob1_norm = sum(abs(p) for p in prob1) prob2_norm = sum(abs(p) for p in prob2) ...
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{ "lang": "python", "repo": "luluyao9494/PyTls", "path": "/PyTls/matht.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: luluyao9494/PyTls path: /PyTls/matht.py #!/usr/bin/env python # -*- coding: utf-8 -*- ''' @File : matht.py @Author: sladesha @Date : 2019/7/22 0:15 @Desc : ''' import math from .typet import is_type import sys from .listt import index_hash_map, Pi from math import log from math import e __E...
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{ "lang": "python", "repo": "luluyao9494/PyTls", "path": "/PyTls/matht.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> link = '{{' + link + '}}' return link def delinktemp(link): import re link = re.compile(r'\{\{(.*?)\}\}', re.IGNORECASE).sub(r'\1', str(link)) return link def addsection(page, content, summary): site = wikipedia.getSite() wppage = wikipedia.Page(site, page) text = wppage.get() text = text + conte...
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{ "lang": "python", "repo": "edgarskos/legobot-old", "path": "/legoktm.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: edgarskos/legobot-old path: /legoktm.py #!usr/bin/python # # (C) Legoktm 2008-2011, MIT License # import wikipedia, pagegenerators, catlib import re, sys from wikipedia import * #status updater #syntax: legoktm.newstatus("Status", "User:Username/Status", "[y]es/[n]o prompt) site = wikipedia.getSi...
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{ "lang": "python", "repo": "edgarskos/legobot-old", "path": "/legoktm.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> site = wikipedia.getSite() wppage = wikipedia.Page(site, page) text = wppage.get() text = text + content wikipedia.showDiff(wppage.get(), text) try: page.put(text, summary, minorEdit=False) except wikipedia.NoPage: page.put(text, summary, minorEdit=False) except wikipedia.IsRedirectPage: ret...
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{ "lang": "python", "repo": "edgarskos/legobot-old", "path": "/legoktm.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: gbip/Geotrek-admin path: /geotrek/core/tests/test_filters.py from unittest import skipIf from django.conf import settings from django.contrib.gis.geos import LineString, Point from django.test import TestCase from geotrek.land.tests.test_filters import LandFiltersTest from geotrek.core.factori...
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{ "lang": "python", "repo": "gbip/Geotrek-admin", "path": "/geotrek/core/tests/test_filters.py", "mode": "psm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_suffix|> data = {'is_valid': True} qs = TrekFilterSet(data=data).qs self.assertIn(self.trek, qs) self.assertEqual(qs.count(), 2) data = {'is_valid': False} qs = TrekFilterSet(data=data).qs self.assertEqual(qs.count(), 1) geom = LineString(Point(7001...
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{ "lang": "python", "repo": "gbip/Geotrek-admin", "path": "/geotrek/core/tests/test_filters.py", "mode": "spm", "license": "BSD-2-Clause", "source": "the-stack-v2" }
<|fim_prefix|># repo: jdraiv/lock path: /decorators/auth_decorators.py from functools import wraps from sanic.response import redirect <|fim_suffix|> if json_token != None and refresh_token != None: response = await f(request, *args, **kwargs) return response ...
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{ "lang": "python", "repo": "jdraiv/lock", "path": "/decorators/auth_decorators.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> if json_token != None and refresh_token != None: response = await f(request, *args, **kwargs) return response return redirect('/') return decorated_function return decorator<|fim_prefix|># repo: jdraiv/lock path: /decorators/auth_decor...
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{ "lang": "python", "repo": "jdraiv/lock", "path": "/decorators/auth_decorators.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: bigrepedge/labpipestest path: /app/api/am_machine/machine_systems_simulation/filesystem.py import os from opcua import ua from .base import BasicSystem class FileSystem(BasicSystem): ua_dir_type = 13353 ua_file_type = 11575 def __init__(self, data_handler, inputs=None, outputs=No...
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{ "lang": "python", "repo": "bigrepedge/labpipestest", "path": "/app/api/am_machine/machine_systems_simulation/filesystem.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> def recursive_file_list(self, parent_path, parent_node): for ent in os.listdir(parent_path): ent_path = os.path.join(self.mnt_dir, ent) print(ent_path) rel_path = '/{}'.format(os.path.relpath(ent_path, os.path.abspath('.'))) if os.path.isfile(ent...
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{ "lang": "python", "repo": "bigrepedge/labpipestest", "path": "/app/api/am_machine/machine_systems_simulation/filesystem.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> self.mnt_node = base_node.add_object(ua.NodeId('/mnt', 26), 'mnt', objecttype=self.ua_dir_type) self.recursive_file_list(self.mnt_dir, self.mnt_node) def recursive_file_list(self, parent_path, parent_node): for ent in os.listdir(parent_path): ent_path = os.path.joi...
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{ "lang": "python", "repo": "bigrepedge/labpipestest", "path": "/app/api/am_machine/machine_systems_simulation/filesystem.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|># lets do imputing print("confusion matrix") print(metrics.confusion_matrix(y_test,predicted)) print(metrics.classification_report(y_test, predicted)) # try random forest model to improve accuracy from sklearn.ensemble import RandomForestClassifier rf_model = RandomForestClassifier(random_state=42) rf_m...
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{ "lang": "python", "repo": "sudeep0901/python", "path": "/src/ML Algorithms/1.ml_diabetes.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>import matplotlib.pyplot as plt plt.plot(C_values,recall_scores) plt.xlabel("C value") plt.ylabel("recall score") plt.show() # still 61% may be due to imb alance in dataset # 65% DIABETICS AND 35% non diabetic and is imbalance of classes # enabeld wieght hyperparameter to handle unbalance #balanced we...
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{ "lang": "python", "repo": "sudeep0901/python", "path": "/src/ML Algorithms/1.ml_diabetes.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: sudeep0901/python path: /src/ML Algorithms/1.ml_diabetes.py import numpy as np import pandas as pd import matplotlib as mlp import matplotlib.pyplot as plt # https://github.com/JerryKurata/MachineLearningWithPython/ diabetes_data = pd.read_csv(r'src/ML Algorithms/1.ml.pima-data.csv') # ticket_d...
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{ "lang": "python", "repo": "sudeep0901/python", "path": "/src/ML Algorithms/1.ml_diabetes.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: okffi/tietopyynto path: /froide/publicbody/views.py from django.shortcuts import render, redirect, get_object_or_404 from django.views.decorators.http import require_POST from django.utils.translation import ugettext_lazy as _, ungettext from django.contrib import messages from django.conf import...
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{ "lang": "python", "repo": "okffi/tietopyynto", "path": "/froide/publicbody/views.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|>def show_publicbody(request, slug): obj = get_object_or_404(PublicBody, slug=slug) context = { 'object': obj, 'foirequests': FoiRequest.published.filter( public_body=obj).order_by('-last_message')[:10], 'resolutions': FoiRequest.published.get_resolution_count_by...
code_fim
hard
{ "lang": "python", "repo": "okffi/tietopyynto", "path": "/froide/publicbody/views.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> add_arg = self.add_argument add_arg('--dir', type=str, help='set project path where is the database. Default to ' 'current directory') def execute(self, args): persistence.connect_existing(args.dir or os.getcwd()) print_msg('trials ...
code_fim
medium
{ "lang": "python", "repo": "paopao74cn/noworkflow", "path": "/capture/noworkflow/now/cmd/cmd_list.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_suffix|> persistence.connect_existing(args.dir or os.getcwd()) print_msg('trials available in the provenance store:', True) for trial in persistence.load('trial'): text = ' Trial {id}: {script} {arguments}'.format(**trial) indent = text.index(': ') + 2 p...
code_fim
hard
{ "lang": "python", "repo": "paopao74cn/noworkflow", "path": "/capture/noworkflow/now/cmd/cmd_list.py", "mode": "spm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: paopao74cn/noworkflow path: /capture/noworkflow/now/cmd/cmd_list.py # Copyright (c) 2014 Universidade Federal Fluminense (UFF) # Copyright (c) 2014 Polytechnic Institute of New York University. # This file is part of noWorkflow. # Please, consult the license terms in the LICENSE file. from __fut...
code_fim
hard
{ "lang": "python", "repo": "paopao74cn/noworkflow", "path": "/capture/noworkflow/now/cmd/cmd_list.py", "mode": "psm", "license": "MIT", "source": "the-stack-v2" }
<|fim_prefix|># repo: bozzzzo/quark path: /quarkc/test/emit/expected/py/use-class-before-def/pkg/__init__.py from quark_runtime import * import quark.reflect import use_class_before_def_md class Bar(object): def _init(self): pass def __init__(self): self._init() <|fim_suffix|> return u"pkg.B...
code_fim
medium
{ "lang": "python", "repo": "bozzzzo/quark", "path": "/quarkc/test/emit/expected/py/use-class-before-def/pkg/__init__.py", "mode": "psm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def _init(self): self.name = None def __init__(self): self._init() def _getClass(self): return u"pkg.Foo" def _getField(self, name): if ((name) == (u"name")): return (self).name return None def _setField(self, name, value): if ((...
code_fim
hard
{ "lang": "python", "repo": "bozzzzo/quark", "path": "/quarkc/test/emit/expected/py/use-class-before-def/pkg/__init__.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }
<|fim_suffix|> def _getField(self, name): return None def _setField(self, name, value): pass Bar.pkg_Bar_ref = use_class_before_def_md.Root.pkg_Bar_md class Foo(object): def _init(self): self.name = None def __init__(self): self._init() def _getClass(self): return u...
code_fim
medium
{ "lang": "python", "repo": "bozzzzo/quark", "path": "/quarkc/test/emit/expected/py/use-class-before-def/pkg/__init__.py", "mode": "spm", "license": "Apache-2.0", "source": "the-stack-v2" }