text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('polls', '0014_recruitment_local_committee'),
]
operations = [
migrations.RemoveField(
model_name='registerevent',
name='question',
),
migrati... | code_fim | medium | {
"lang": "python",
"repo": "dinhkute/Incisive-AIESEC",
"path": "/webroot/Pj/mysite/mysite/polls/migrations/0015_auto_20170630_0936.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>cell = flagwidth / 2 / 15
rbig = cell * 3
rsmall = cell * 1
draw_star((-10*cell,5*cell),rbig)
draw_star((-5*cell,8*cell),rsmall,-math.tanh(3/5)*180)
draw_star((-3*cell,6*cell),rsmall,-math.tanh(1/7)*180)
draw_star((-3*cell,3*cell),rsmall,math.tanh(2/7)*180)
draw_star((-5*cell,cell),rsmall,math.tanh(4/5)*... | code_fim | hard | {
"lang": "python",
"repo": "neo20/pystudy",
"path": "/national_flag_of_China/draw.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: neo20/pystudy path: /national_flag_of_China/draw.py
from turtle import *
import math
flagwidth = 1200
setup(width=flagwidth, height=2/3*flagwidth, startx=None, starty=None)
bgcolor("red")
def draw_star(point,radius,angle=0):
<|fim_suffix|>draw_star((-10*cell,5*cell),rbig)
draw_star((-5*cell,8*c... | code_fim | hard | {
"lang": "python",
"repo": "neo20/pystudy",
"path": "/national_flag_of_China/draw.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bmoretz/Python-Playground path: /src/DoingMathInPython/ch_01/factors.py
'''
Find the factors of an integer
'''
<|fim_suffix|> b = input( 'Your Number Please:' )
b = float( b )
if( b > 0 ) and b.is_integer() :
factors( int( b ) )
else:
print( 'Please enter a positive integer' )<|fi... | code_fim | medium | {
"lang": "python",
"repo": "bmoretz/Python-Playground",
"path": "/src/DoingMathInPython/ch_01/factors.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if( b > 0 ) and b.is_integer() :
factors( int( b ) )
else:
print( 'Please enter a positive integer' )<|fim_prefix|># repo: bmoretz/Python-Playground path: /src/DoingMathInPython/ch_01/factors.py
'''
Find the factors of an integer
'''
def factors( b ) :
for i in range( 1, b + 1 ):
if b % ... | code_fim | medium | {
"lang": "python",
"repo": "bmoretz/Python-Playground",
"path": "/src/DoingMathInPython/ch_01/factors.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
If gameid does not exist in the DB, pull match from API and insert into DB. Otherwise do nothing.
:param gameid: gameid for the match to insert
"""
if Match.query.filter(Match.gameid == gameid).first():
self.logger.info("Match {} already exists in th... | code_fim | hard | {
"lang": "python",
"repo": "ematysek/Riot-API-Webapp",
"path": "/app/util/request_handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def update_leagues(self, summonerid: int):
"""
Get most recent leagues info from API for summonerid and update user_leagues table accordingly
:param summonerid: summonerid for the Summoner we want to grab updated league info for
"""
self.logger.info("Update leag... | code_fim | hard | {
"lang": "python",
"repo": "ematysek/Riot-API-Webapp",
"path": "/app/util/request_handler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ematysek/Riot-API-Webapp path: /app/util/request_handler.py
import logging
from typing import Optional
from datetime import datetime
from app.flask_models import Summoner, UserMatch, UserLeague, Match
from app.wrappers import RiotConnector
class RequestHandler:
def __init__(self, db, api_e... | code_fim | hard | {
"lang": "python",
"repo": "ematysek/Riot-API-Webapp",
"path": "/app/util/request_handler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> run, runsub = run_setup(
nfa_name=NFA_NAME_A,
pattern=stub_pattern)
self.assertFalse(run.is_halted())
run.set_halt()
self.assertTrue(run.is_halted())
self.assertEqual(1, len(runsub.halt))
with self.assertRaises(RuntimeError):
... | code_fim | hard | {
"lang": "python",
"repo": "magents-ai/bobocep",
"path": "/tests/test_bobocep/test_decider/test_runs/test_bobo_run.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: magents-ai/bobocep path: /tests/test_bobocep/test_decider/test_runs/test_bobo_run.py
import unittest
from bobocep.decider.buffers.shared_versioned_match_buffer import \
SharedVersionedMatchBuffer
from bobocep.decider.runs.bobo_run import BoboRun
from bobocep.decider.runs.run_subscriber impor... | code_fim | hard | {
"lang": "python",
"repo": "magents-ai/bobocep",
"path": "/tests/test_bobocep/test_decider/test_runs/test_bobo_run.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
emo_folder = 'data/HCP.zips/'
emo_LR_nii = 'data/timeseries/raw/face/LR'
emo_RL_nii = 'data/timeseries/raw/face/RL'
emo_both = 'data/timeseries/raw/face/both'
# unpack_HCP_zips(emo_folder, LR_path=emo_LR_nii, RL_path=emo_RL_nii)
# read in and concatenate LR-RL NIFTI files
def read_NIFTI():
global... | code_fim | hard | {
"lang": "python",
"repo": "furtherAdu/brainnetcnnVis_pytorch",
"path": "/scrap.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: furtherAdu/brainnetcnnVis_pytorch path: /scrap.py
import os
import zipfile
from os import listdir
import nibabel as nib
import numpy as np
float_formatter = "{:.3f}".format
np.set_printoptions(formatter={'float_kind': float_formatter})
# reading HCP subject-specific CIFTI files
def read_CIFTI... | code_fim | hard | {
"lang": "python",
"repo": "furtherAdu/brainnetcnnVis_pytorch",
"path": "/scrap.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Unpacks HCP emotion_face NIFTI files to new folders for each scan gradient, for each subject in zipsfolder.
:param zipsfolder: folder containing zipped HCP task data
:param LR_path: path to save LR gradient data
:param RL_path: path to save RL gradient data
:return:
"""
... | code_fim | hard | {
"lang": "python",
"repo": "furtherAdu/brainnetcnnVis_pytorch",
"path": "/scrap.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JetBrains/intellij-community path: /python/helpers/coveragepy_new/coverage/templite.py
# Licensed under the Apache License: http://www.apache.org/licenses/LICENSE-2.0
# For details: https://github.com/nedbat/coveragepy/blob/master/NOTICE.txt
"""A simple Python template renderer, for a nano-subse... | code_fim | hard | {
"lang": "python",
"repo": "JetBrains/intellij-community",
"path": "/python/helpers/coveragepy_new/coverage/templite.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Supported constructs are extended variable access::
{{var.modifier.modifier|filter|filter}}
loops::
{% for var in list %}...{% endfor %}
and ifs::
{% if var %}...{% endif %}
Comments are within curly-hash markers::
{# This will be ignored #}
Line... | code_fim | hard | {
"lang": "python",
"repo": "JetBrains/intellij-community",
"path": "/python/helpers/coveragepy_new/coverage/templite.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dataplumber/nexus path: /analysis/webservice/algorithms/TileSearch.py
"""
Copyright (c) 2016 Jet Propulsion Laboratory,
California Institute of Technology. All rights reserved
"""
from webservice.NexusHandler import NexusHandler, nexus_handler
from webservice.webmodel import NexusResults
# @ne... | code_fim | hard | {
"lang": "python",
"repo": "dataplumber/nexus",
"path": "/analysis/webservice/algorithms/TileSearch.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def calc(self, computeOptions, **args):
minLat = computeOptions.get_min_lat()
maxLat = computeOptions.get_max_lat()
minLon = computeOptions.get_min_lon()
maxLon = computeOptions.get_max_lon()
ds = computeOptions.get_dataset()[0]
startTime = computeOption... | code_fim | hard | {
"lang": "python",
"repo": "dataplumber/nexus",
"path": "/analysis/webservice/algorithms/TileSearch.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == 'POST':
print("POST method")
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
result = open_image2(request.FILES['file'].read())
# user = CustomUser.objects.get(username=request.user.username)
return ... | code_fim | hard | {
"lang": "python",
"repo": "Zhalkhas/HMD",
"path": "/xray/views.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Zhalkhas/HMD path: /xray/views.py
from django.shortcuts import render
from .forms import UploadFileForm
from .model import open_image
from .model2 import open_image2
from accounts.models import CustomUser
def upload_file(request):
<|fim_suffix|>def upload_pneumonia(request):
if request.method... | code_fim | hard | {
"lang": "python",
"repo": "Zhalkhas/HMD",
"path": "/xray/views.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_suffix|>ath('registration_success/', views.registration_success, name='registration success')
]<|fim_prefix|># repo: 33du/blogging-with-django path: /users/urls.py
from django.urls import path
from . import views
app_name = 'users'
urlpatterns = [
<|fim_middle|> path('login/', views.log_in, name='login'),
... | code_fim | medium | {
"lang": "python",
"repo": "33du/blogging-with-django",
"path": "/users/urls.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 33du/blogging-with-django path: /users/urls.py
from django.urls import path
from . import views
app_name = 'users'
urlpatterns = [
<|fim_suffix|>ath('registration_success/', views.registration_success, name='registration success')
]<|fim_middle|> path('login/', views.log_in, name='login'),
... | code_fim | medium | {
"lang": "python",
"repo": "33du/blogging-with-django",
"path": "/users/urls.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Real-time evolution
alldata = []
for step in range(nsteps):
alldata.append([step * dt * U] + np.array(G.density).tolist())
G.many_time_steps(dt, nsteps=1, normalize_at_each_step=0, update_variables=1)
alldata.append([nsteps * dt * U] + np.array(G.density).tolist())
# Print some output and save ... | code_fim | hard | {
"lang": "python",
"repo": "tcompa/GutzwillerDynamics",
"path": "/Examples/example_3_real_time_evolution_with_fixed_parameters.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tcompa/GutzwillerDynamics path: /Examples/example_3_real_time_evolution_with_fixed_parameters.py
#!/usr/bin/env python
from __future__ import print_function
# Comment these lines if you want to use more than one core
import os
os.environ['MKL_NUM_THREADS'] = '1'
os.environ['NUMEXPR_NUM_THREADS'... | code_fim | hard | {
"lang": "python",
"repo": "tcompa/GutzwillerDynamics",
"path": "/Examples/example_3_real_time_evolution_with_fixed_parameters.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Do plot of densities
alldata = np.array(alldata).T
for i in range(L):
plt.plot(alldata[0], alldata[i + 1], alpha=0.8, label='Site %i' % i)
plt.plot(alldata[0], alldata[1:].mean(axis=0), ls='--', c='k', lw=2)
plt.xlabel('Time $t \\qquad [1/U]$', fontsize=14)
plt.ylabel('Local density $n_i(t)$', fonts... | code_fim | hard | {
"lang": "python",
"repo": "tcompa/GutzwillerDynamics",
"path": "/Examples/example_3_real_time_evolution_with_fixed_parameters.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def f3(series):
return series.kurtosis()
def f4(series):
return series[series.notna()].kurtosis()
"""
print(timeit.timeit("f1(series)", number=10, setup=testcode))
print(timeit.timeit("f2(series)", number=10, setup=testcode))
print(timeit.timeit("f3(series)", number=10, setup=testcode))
print(... | code_fim | hard | {
"lang": "python",
"repo": "chanedwin/pandas-profiling",
"path": "/tests/performance/time_kurtosis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chanedwin/pandas-profiling path: /tests/performance/time_kurtosis.py
import timeit
testcode = """
import numpy as np
import pandas as pd
import scipy.stats
np.random.seed(12)
vals = np.random.random(1000)
series = pd.Series(vals)
series[series < 0.2] = pd.NA
def f1(series):
arr = series.va... | code_fim | medium | {
"lang": "python",
"repo": "chanedwin/pandas-profiling",
"path": "/tests/performance/time_kurtosis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(timeit.timeit("f1(series)", number=10, setup=testcode))
print(timeit.timeit("f2(series)", number=10, setup=testcode))
print(timeit.timeit("f3(series)", number=10, setup=testcode))
print(timeit.timeit("f4(series)", number=10, setup=testcode))<|fim_prefix|># repo: chanedwin/pandas-profiling path: /te... | code_fim | hard | {
"lang": "python",
"repo": "chanedwin/pandas-profiling",
"path": "/tests/performance/time_kurtosis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>tput_gp import MetaSingleOutputGPOngrid<|fim_prefix|># repo: janvanrijn/openml-multitask path: /multitask/models_ongrid/__init__.py
from .multioutput_gp import MetaMultiO<|fim_middle|>utputGPOngrid
from .randomforest import MetaRandomForestOngrid
from .sinlgeou | code_fim | medium | {
"lang": "python",
"repo": "janvanrijn/openml-multitask",
"path": "/multitask/models_ongrid/__init__.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: janvanrijn/openml-multitask path: /multitask/models_ongrid/__init__.py
from .multioutput_gp import MetaMultiO<|fim_suffix|>tput_gp import MetaSingleOutputGPOngrid<|fim_middle|>utputGPOngrid
from .randomforest import MetaRandomForestOngrid
from .sinlgeou | code_fim | medium | {
"lang": "python",
"repo": "janvanrijn/openml-multitask",
"path": "/multitask/models_ongrid/__init__.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # type: int
ENOBUFS = 105 # type: int
ENODEV = 19 # type: int
ENOENT = 2 # type: int
ENOMEM = 12 # type: int
ENOTCONN = 128 # type: int
EOPNOTSUPP = 95 # type: int
EPERM = 1 # type: int
ETIMEDOUT = 116 # type: int
errorcode = {} # type: dict<|fim_prefix|># repo: Josverl/micropython-stubber path... | code_fim | hard | {
"lang": "python",
"repo": "Josverl/micropython-stubber",
"path": "/tests/data/stub_merge/micropython-v1_18-esp32/uerrno.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Josverl/micropython-stubber path: /tests/data/stub_merge/micropython-v1_18-esp32/uerrno.py
"""
Module: 'uerrno' on micropython-v1.18-esp32
"""
# MCU: {'ver': 'v1.18', 'port': 'esp32', 'arch': 'xtensawin', 'sysname': 'esp32', 'release': '1.18.0', 'name': 'micropython', 'mpy': 10757, 'version': '1.... | code_fim | hard | {
"lang": "python",
"repo": "Josverl/micropython-stubber",
"path": "/tests/data/stub_merge/micropython-v1_18-esp32/uerrno.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> line = " Mask Flags: "
if (nMaskFlags & gdal.GMF_PER_DATASET) != 0:
line = line + "PER_DATASET "
if (nMaskFlags & gdal.GMF_ALPHA) != 0:
line = line + "ALPHA "
... | code_fim | hard | {
"lang": "python",
"repo": "nmanaud/GDAL_scripts",
"path": "/gdal2ISIS3/LMMP_gdal2PDS.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nmanaud/GDAL_scripts path: /gdal2ISIS3/LMMP_gdal2PDS.py
if dfMin is not None:
line = line + ("Min=%.3f " % dfMin)
if dfMax is not None:
line = line + ("Max=%.3f " % dfMax)
... | code_fim | hard | {
"lang": "python",
"repo": "nmanaud/GDAL_scripts",
"path": "/gdal2ISIS3/LMMP_gdal2PDS.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> if bShowMetadata:
for extra_domain in papszExtraMDDomains:
papszMetadata = hDataset.GetMetadata_List(extra_domain)
if papszMetadata is not None and len(papszMetadata) > 0 :
print( "Metadata (%s):" % extra_domain)
f... | code_fim | hard | {
"lang": "python",
"repo": "nmanaud/GDAL_scripts",
"path": "/gdal2ISIS3/LMMP_gdal2PDS.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: danielnaab/ngwmn-ui path: /server/ngwmn/__init__.py
"""
Initialize the NGWMN UI application
"""
from flask import Flask
<|fim_suffix|>app = Flask(__name__.split()[0], instance_relative_config=True)
# load configurations
app.config.from_object('config')
try:
app.config.from_pyfile('config.p... | code_fim | easy | {
"lang": "python",
"repo": "danielnaab/ngwmn-ui",
"path": "/server/ngwmn/__init__.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>app = Flask(__name__.split()[0], instance_relative_config=True)
# load configurations
app.config.from_object('config')
try:
app.config.from_pyfile('config.py')
except FileNotFoundError:
pass
from . import views<|fim_prefix|># repo: danielnaab/ngwmn-ui path: /server/ngwmn/__init__.py
"""
Initial... | code_fim | easy | {
"lang": "python",
"repo": "danielnaab/ngwmn-ui",
"path": "/server/ngwmn/__init__.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: marian-code/wikipedia-music-tags path: /wiki_music/gui_lib/custom_classes/lists.py
"""Module providing custom Qt tables, their models and views."""
import logging
from typing import List, Optional
from wiki_music.gui_lib.qt_importer import (QStandardItem, QStandardItemModel,
... | code_fim | hard | {
"lang": "python",
"repo": "marian-code/wikipedia-music-tags",
"path": "/wiki_music/gui_lib/custom_classes/lists.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns
-------
List[int]
list with checked indices
"""
checked = list()
for i in range(self.rowCount()):
if bool(self.item(i, 0).checkState()):
checked.append(i)
return checked<|fim_prefix|># repo: marian-cod... | code_fim | hard | {
"lang": "python",
"repo": "marian-code/wikipedia-music-tags",
"path": "/wiki_music/gui_lib/custom_classes/lists.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Merge these two dictionaries together so the contents are in numerical order:
dict1 = {'Ten': 10, 'Twenty': 20, 'Thirty': 30}
dict2 = {'Thirty': 30, 'Fourty': 40, 'Fifty': 50}
# add code here
dict1.update(dict2)
return dict1 # return new dictionary
def access_key():
# retu... | code_fim | medium | {
"lang": "python",
"repo": "Athenian-ComputerScience-Fall2020/dictionary-practice-Milan938",
"path": "/my_code.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Athenian-ComputerScience-Fall2020/dictionary-practice-Milan938 path: /my_code.py
# Collaborators (including web sites where you got help: (enter none if you didn't need help)
# geeksforgeeks.org
def make_dict():
'''
use the following information to create a dictionary called currency:
... | code_fim | medium | {
"lang": "python",
"repo": "Athenian-ComputerScience-Fall2020/dictionary-practice-Milan938",
"path": "/my_code.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def access_key():
# return the value of the key 'Twenty'
currency = {'Ten': 10, 'Twenty': 20, 'Thirty': 30}
val = currency.get('Twenty')
# add code to assign the desired value to 'val'
return val
if __name__ == '__main__':
# Test your code with this first
# Change t... | code_fim | hard | {
"lang": "python",
"repo": "Athenian-ComputerScience-Fall2020/dictionary-practice-Milan938",
"path": "/my_code.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>log.info("running on {} processors".format(ns.numproc))
write_gaia_matches(infiles, numproc=ns.numproc, outdir=ns.dest)
log.info('Wrote sweeps files matched to Gaia to {}...t={:.1f}s'.format(ns.dest, time()-start))<|fim_prefix|># repo: rongpu/desitarget path: /bin/write_gaia_matches
#!/usr/bin/env pyth... | code_fim | hard | {
"lang": "python",
"repo": "rongpu/desitarget",
"path": "/bin/write_gaia_matches",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>from desiutil.log import get_logger
log = get_logger()
from argparse import ArgumentParser
ap = ArgumentParser(description='Match sweeps files to Gaia and rewrite files with the Gaia columns added')
ap.add_argument("src",
help="Sweeps file or root directory with sweeps files")
ap.add_arg... | code_fim | medium | {
"lang": "python",
"repo": "rongpu/desitarget",
"path": "/bin/write_gaia_matches",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rongpu/desitarget path: /bin/write_gaia_matches
#!/usr/bin/env python
import sys
from desitarget import io
from desitarget.gaiamatch import write_gaia_matches
from time import time
start = time()
#import warnings
#warnings.simplefilter('error')
import multiprocessing
nproc = multiprocessing.cp... | code_fim | hard | {
"lang": "python",
"repo": "rongpu/desitarget",
"path": "/bin/write_gaia_matches",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cjopengler/easybook path: /daily/bernoulli_distribution/loop_show.py
#!/usr/bin/env python 3
# -*- coding: utf-8 -*-
#
# Copyright (c) 2020 PanXu, Inc. All Rights Reserved
#
"""
brief
<|fim_suffix|> for i in range(10):
print(f"{i}: {m.sample()}")
def masked_sequence(length: int, pr... | code_fim | hard | {
"lang": "python",
"repo": "cjopengler/easybook",
"path": "/daily/bernoulli_distribution/loop_show.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def loop_by_class():
x = torch.tensor([0.3])
m = torch.distributions.Bernoulli()
for i in range(10):
print(f"{i}: {m.sample()}")
def masked_sequence(length: int, prob: float):
probs = torch.full((length,), prob)
masked = torch.bernoulli(probs)
print(f"mask=1的数量: {mask... | code_fim | medium | {
"lang": "python",
"repo": "cjopengler/easybook",
"path": "/daily/bernoulli_distribution/loop_show.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rodrigoieh/template-generator path: /onlinejudge_template_resources/template/generate.py
<%!
import onlinejudge_template.generator.python as python
import onlinejudge_template.generator.about as about
%>\
#!/usr/bin/env python3
# usage: $ oj generate-input 'python3 generate.py'
import ran... | code_fim | medium | {
"lang": "python",
"repo": "rodrigoieh/template-generator",
"path": "/onlinejudge_template_resources/template/generate.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>${python.generate_input(data)}
${python.write_input(data)}
if __name__ == "__main__":
main()<|fim_prefix|># repo: rodrigoieh/template-generator path: /onlinejudge_template_resources/template/generate.py
<%!
import onlinejudge_template.generator.python as python
import onlinejudge_template.ge... | code_fim | medium | {
"lang": "python",
"repo": "rodrigoieh/template-generator",
"path": "/onlinejudge_template_resources/template/generate.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stringertheory/names path: /poem_ids.py
EARLY = "10"
CHICAGO = "2043"
TRW = "174770"
WOODS = "171621"
ROAD = "173536"
SHAKE18 = 45<|fim_suffix|>RUS = "175887"
PLATH = "178960"
PRELUTSKY = "177537"
TENNYSON = "174586"
WORDSWORTH = "174790"
BLANK = "248540"
RHYMES = "174972"
SYLLABIC = "248426"
ROB... | code_fim | medium | {
"lang": "python",
"repo": "stringertheory/names",
"path": "/poem_ids.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>90"
BLANK = "248540"
RHYMES = "174972"
SYLLABIC = "248426"
ROBOTS = "250556"
POEM_ID = SHEL<|fim_prefix|># repo: stringertheory/names path: /poem_ids.py
EARLY = "10"
CHICAGO = "2043"
TRW = "174770"
WOODS = "171621"
ROAD = "173536"
SHAKE18 = 45<|fim_middle|>087
SHAKE33 = "174360"
STATS = 42724
LONG = "174... | code_fim | medium | {
"lang": "python",
"repo": "stringertheory/names",
"path": "/poem_ids.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: paulfitz/sheetsite path: /sheetsite/destination/ftp.py
import os
import subprocess
def write_destination_ftp(params, state):
out<|fim_suffix|>, '--binary', '-u', '-nc', output_file, url]
print(' '.join(cmd))
out = subprocess.check_output(cmd)
print("ftp: {}".format(out))
retu... | code_fim | medium | {
"lang": "python",
"repo": "paulfitz/sheetsite",
"path": "/sheetsite/destination/ftp.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>= subprocess.check_output(cmd)
print("ftp: {}".format(out))
return True<|fim_prefix|># repo: paulfitz/sheetsite path: /sheetsite/destination/ftp.py
import os
import subprocess
def write_destination_ftp(params, state):
out<|fim_middle|>put_file = state['output_file']
url = params['url']
... | code_fim | medium | {
"lang": "python",
"repo": "paulfitz/sheetsite",
"path": "/sheetsite/destination/ftp.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: victor3rc/lux path: /lux/extensions/rest/backends/browser.py
from pulsar.utils.httpurl import is_absolute_uri
from lux import Parameter
from lux.extensions.angular import add_ng_modules
from .. import AuthBackend, luxrest
from ..views import Login, SignUp, ForgotPassword
class BrowserBackend(... | code_fim | hard | {
"lang": "python",
"repo": "victor3rc/lux",
"path": "/lux/extensions/rest/backends/browser.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def on_html_document(self, app, request, doc):
if is_absolute_uri(app.config['API_URL']):
add_ng_modules(doc, ('lux.restapi', 'lux.users'))
else:
add_ng_modules(doc, ('lux.webapi', 'lux.users'))<|fim_prefix|># repo: victor3rc/lux path: /lux/extensions/rest/back... | code_fim | hard | {
"lang": "python",
"repo": "victor3rc/lux",
"path": "/lux/extensions/rest/backends/browser.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fogstream/fs-pochta-api path: /pochta/api/orders.py
from __future__ import annotations
from typing import TYPE_CHECKING, List
from pochta.helpers import Order
from pochta.utils import HTTPMethod
if TYPE_CHECKING:
from pochta import Delivery
class Orders:
"""
Методы API Заказов.
... | code_fim | hard | {
"lang": "python",
"repo": "fogstream/fs-pochta-api",
"path": "/pochta/api/orders.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> https://otpravka.pochta.ru/specification#/orders-search_order_byid
:param order_id: Внутренний идентификатор отправления
:return: Результат операции
"""
url = f'/1.0/backlog/{order_id}'
res = self._client.request(HTTPMethod.GET, url)
return res.jso... | code_fim | hard | {
"lang": "python",
"repo": "fogstream/fs-pochta-api",
"path": "/pochta/api/orders.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xius666/email-management-system path: /phase1.py
import sys
import re
def cut(line, key):
array=line.split('</'+key+'>')[0].split('<'+key+'>')[1]
return array
def phase1(file,terms,emails,dates,recs):
for x in range(2):
file.readline()
while True:
line=file.readline()
if line.strip()=='... | code_fim | hard | {
"lang": "python",
"repo": "xius666/email-management-system",
"path": "/phase1.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return returnl
def main(path):
path='./'+path
file=open(path,'r')
#open all the files with write mode
terms = open('terms.txt', 'w')
emails = open('emails.txt', 'w')
dates = open('dates.txt', 'w')
recs = open('recs.txt', 'w')
phase1(file,terms,emails,dates,recs)
terms.close()
emails.close()
da... | code_fim | hard | {
"lang": "python",
"repo": "xius666/email-management-system",
"path": "/phase1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
#replace all the specail char with space
term = term.replace(''', ' ').replace('"', ' ').replace('&', ' ').replace('<',' ').replace('>',' ').replace('
',' ')
term = re.sub(r'[&][#][0-9]+[;]','', term)
correct='0123456789abcdefghijklmnopqrstuvwxyz-_'
term=term.lower()
for a i... | code_fim | hard | {
"lang": "python",
"repo": "xius666/email-management-system",
"path": "/phase1.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: luungoc2005/chatbot_test path: /testbot/transform.py
from .NLTKPreprocessor import NLTKPreprocessor
from .entities.Stanford_NER import Stanford_NER_Chunker, load_stanford_tagger
from .entities.NLTK_NER import NLTK_NER_Chunker
from sklearn.feature_extraction.text import TfidfVectorizer
from recurr... | code_fim | hard | {
"lang": "python",
"repo": "luungoc2005/chatbot_test",
"path": "/testbot/transform.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # preprocessed = preprocessor.transform([text])
chunked = chunker.transform([text])
named_entities = []
for sentence in chunked:
for (text, tag) in sentence:
item = {
'text': text,
'entity': tag,
}
if tag in [... | code_fim | hard | {
"lang": "python",
"repo": "luungoc2005/chatbot_test",
"path": "/testbot/transform.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def tokenize_text(text):
global STOPWORDS
r = RecurringEvent(now_date=datetime.now(pytz.utc))
load_stanford_tagger()
chunker = Stanford_NER_Chunker()
# chunker = NLTK_NER_Chunker()
# preprocessor = NLTKPreprocessor() # default stopwords
if len(STOPWORDS) == 0:
STOPWORDS... | code_fim | medium | {
"lang": "python",
"repo": "luungoc2005/chatbot_test",
"path": "/testbot/transform.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Get all co-authors
contributors = git(
"log", f"{base}..{head}", "--format=%(trailers:key=Co-authored-by)"
)
coauthors = []
for coauthor in contributors:
if coauthor and not re.search("@google.com", coauthor):
coauthors.append(
" ".join(re.sub(r"Co-authored-by: |<.*?... | code_fim | hard | {
"lang": "python",
"repo": "bazelbuild/bazel",
"path": "/scripts/release/relnotes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Assuming HEAD is on the current (to-be-released) release, find the merge
# base with the last release so that we know which commits to generate notes
# for.
merge_base = git("merge-base", "HEAD", last_release)[0]
print("Baseline: ", merge_base)
# Generate notes for all commits from last bra... | code_fim | hard | {
"lang": "python",
"repo": "bazelbuild/bazel",
"path": "/scripts/release/relnotes.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bazelbuild/bazel path: /scripts/release/relnotes.py
# Copyright 2022 The Bazel Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http... | code_fim | hard | {
"lang": "python",
"repo": "bazelbuild/bazel",
"path": "/scripts/release/relnotes.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OsodracPT/Python-Facial-Recognition path: /identify.py
import face_recognition
from PIL import Image, ImageDraw
image_of_bill = face_recognition.load_image_file('./img/known/Bill Gates.jpg')
bill_face_encoding = face_recognition.face_encodings(image_of_bill)[0]
image_of_steve = face_recognition... | code_fim | hard | {
"lang": "python",
"repo": "OsodracPT/Python-Facial-Recognition",
"path": "/identify.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Draw the box
draw.rectangle(((left, top), (rigth, bottom)), outline=(0, 0, 0))
# Draw the label
text_width, text_heigth = draw.textsize(name)
draw.rectangle(((left, bottom - text_heigth - 10),
(rigth, bottom)), fill=(0, 0, 0), outline=(0, 0, 0))
draw.text((le... | code_fim | hard | {
"lang": "python",
"repo": "OsodracPT/Python-Facial-Recognition",
"path": "/identify.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> image1 = sb.training.Image(400, 400)
image1.ctx.set_source_rgb(0, 0, 0)
image1.ctx.rectangle(0, 0, 100, 100)
image1.ctx.fill()
image2 = sb.training.Image(400, 400)
image2.copy_image(image1)
arr1 = image1.to_array()
arr2 = image2.to_array()
... | code_fim | medium | {
"lang": "python",
"repo": "ahmedkhalf/Shape-Bruteforce",
"path": "/tests/test_training.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ahmedkhalf/Shape-Bruteforce path: /tests/test_training.py
import shape_bruteforce as sb
import unittest
import numpy as np
class TestImage(unittest.TestCase):
<|fim_suffix|> image1 = sb.training.Image(400, 400)
image1.ctx.set_source_rgb(0, 0, 0)
image1.ctx.rectangle(0, 0,... | code_fim | hard | {
"lang": "python",
"repo": "ahmedkhalf/Shape-Bruteforce",
"path": "/tests/test_training.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tamjankowska/jets path: /library/migrations/0007_location_continent.py
# Generated by Django 3.1.4 on 2020-12-01 16:13
from django.db import migrations, models
<|fim_suffix|> dependencies = [
('library', '0006_auto_20201201_1413'),
]
operations = [
migrations.AddFie... | code_fim | easy | {
"lang": "python",
"repo": "tamjankowska/jets",
"path": "/library/migrations/0007_location_continent.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
('library', '0006_auto_20201201_1413'),
]
operations = [
migrations.AddField(
model_name='location',
name='continent',
field=models.CharField(default='', max_length=16),
preserve_default=False,
),
]<... | code_fim | medium | {
"lang": "python",
"repo": "tamjankowska/jets",
"path": "/library/migrations/0007_location_continent.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> for region in ACCOUNTS.keys():
result = get_stabilityai_image_uri(region=region, version=version)
expected = expected_uris.stabilityai_framework_uri(
"stabilityai-pytorch-inference",
ACCOUNTS[region],
SAI_VERSIONS_MAPPING[version],
region... | code_fim | hard | {
"lang": "python",
"repo": "aws/sagemaker-python-sdk",
"path": "/tests/unit/sagemaker/image_uris/test_stabilityai.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>@pytest.mark.parametrize("version", SAI_VERSIONS)
def test_stabilityai_image_uris(version):
for region in ACCOUNTS.keys():
result = get_stabilityai_image_uri(region=region, version=version)
expected = expected_uris.stabilityai_framework_uri(
"stabilityai-pytorch-inference",... | code_fim | hard | {
"lang": "python",
"repo": "aws/sagemaker-python-sdk",
"path": "/tests/unit/sagemaker/image_uris/test_stabilityai.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aws/sagemaker-python-sdk path: /tests/unit/sagemaker/image_uris/test_stabilityai.py
# Copyright Amazon.com, Inc. or its affiliates. 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. A copy of... | code_fim | hard | {
"lang": "python",
"repo": "aws/sagemaker-python-sdk",
"path": "/tests/unit/sagemaker/image_uris/test_stabilityai.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class QueryNeedyStudyRoomHandling(ErrorResponseBase):
class Config:
schema_extra = {
'example': {
"detail": [
{
"loc": [
"query",
"skip"
],
... | code_fim | hard | {
"lang": "python",
"repo": "YAPP-18th/ML-Team-Backend",
"path": "/app/schemas/study_rooms/handling.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YAPP-18th/ML-Team-Backend path: /app/schemas/study_rooms/handling.py
from app.schemas.responses import ErrorResponseBase
class NotFoundStudyRoomHandling(ErrorResponseBase):
class Config:
schema_extra = {
'example': {
"detail": [
{
... | code_fim | hard | {
"lang": "python",
"repo": "YAPP-18th/ML-Team-Backend",
"path": "/app/schemas/study_rooms/handling.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: andrewmcnaught1/duedilv3 path: /duedil/resources/pro/company/accounts/financial.py
from __future__ import unicode_literals
from .... import ProResource
class AccountDetailsFinancial(ProResource):
full_endpoint = True
attribute_names = [
'id',
# string Accounts ID
... | code_fim | hard | {
"lang": "python",
"repo": "andrewmcnaught1/duedilv3",
"path": "/duedil/resources/pro/company/accounts/financial.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>liabilities',
# integer Miscellaneous liabilities
'months',
# integer Months included in accounts
'net_cashflow_from_financing',
# integer Net cashflow from financing
'net_change_in_cash',
# integer Net change in cash
'net_fees_and_commission... | code_fim | hard | {
"lang": "python",
"repo": "andrewmcnaught1/duedilv3",
"path": "/duedil/resources/pro/company/accounts/financial.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pancodia/django-ckeditor5 path: /ckeditor5/__init__.py
# -*- coding: utf-8 -*-
# @Author: panc25
# @Date: <|fim_suffix|> @Last Modified time: 2018-09-06 15:08:56
VERSION = (0, 0, 1)
__version__ = '.'.join(map(str, VERSION))<|fim_middle|> 2018-09-05 13:49:43
# @Last Modified by: panc25
# | code_fim | easy | {
"lang": "python",
"repo": "pancodia/django-ckeditor5",
"path": "/ckeditor5/__init__.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> (0, 0, 1)
__version__ = '.'.join(map(str, VERSION))<|fim_prefix|># repo: pancodia/django-ckeditor5 path: /ckeditor5/__init__.py
# -*- coding: utf-8 -*-
# @Author: panc25
# @Date: <|fim_middle|> 2018-09-05 13:49:43
# @Last Modified by: panc25
# @Last Modified time: 2018-09-06 15:08:56
VERSION = | code_fim | medium | {
"lang": "python",
"repo": "pancodia/django-ckeditor5",
"path": "/ckeditor5/__init__.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pdales/xseis path: /pyinclude/xseis/xplot3d.py
""" utils."""
import numpy as np
# import math
# from scipy.fftpack import fft, ifft, fftfreq
# import os
# import pickle
import matplotlib.pyplot as plt
from mayavi import mlab
# import matplotlib.gridspec as gridspec
# import subprocess
# import h... | code_fim | hard | {
"lang": "python",
"repo": "pdales/xseis",
"path": "/pyinclude/xseis/xplot3d.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
shape, origin, spacing = gdef[:3], gdef[3:6], gdef[6]
grid = output.reshape(shape)
lims = np.zeros((3, 2))
lims[:, 0] = origin
lims[:, 1] = origin + shape * spacing
lims[0] -= lims[0, 0]
lims[1] -= lims[1, 0]
fig = mlab.figure(size=(1000, 901))
ranges = list(lims.flatten())
src = mlab_contour... | code_fim | hard | {
"lang": "python",
"repo": "pdales/xseis",
"path": "/pyinclude/xseis/xplot3d.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if not self.moving:
return
# compute next position of ball at current velocity
newx = self.x + self.vx
newy = self.y + self.vy
#detect vertical bounce
if newy + Ball.RADIUS > HEIGHT - BORDER \
or newy - Ball.RADIUS < BORDER:
... | code_fim | hard | {
"lang": "python",
"repo": "agryman/sean",
"path": "/pong/pong722.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agryman/sean path: /pong/pong722.py
# 7.2.2 The Paddle class
import pygame
pygame.init()
BORDER = 10
WIDTH = 800
HEIGHT = 400
VELOCITY = 4
BLACK = pygame.Color('black')
WHITE = pygame.Color('white')
screen = pygame.display.set_mode((WIDTH, HEIGHT))
screen.fill(BLACK)
pygame.draw.rect(screen... | code_fim | hard | {
"lang": "python",
"repo": "agryman/sean",
"path": "/pong/pong722.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def rightStripCurlyBraces(line):
"""
Returns line but with curly braces right stripped off.
"""
match = rstrip_regex.match(line)
if not match: return line
return match.groups()[0]
if __name__ == "__main__":
test_lines = """
36 1001 {NLHEAD... | code_fim | medium | {
"lang": "python",
"repo": "cedadev/nappy",
"path": "/nappy/utils/right_strip.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cedadev/nappy path: /nappy/utils/right_strip.py
#!/usr/bin/env python
"""
right_strip.py
==============
Holds the rightStripCurlyBraces() function used to right strip any curly braces
annotations from lines in a text file.
<|fim_suffix|>
if __name__ == "__main__":
test_lines = """
36... | code_fim | hard | {
"lang": "python",
"repo": "cedadev/nappy",
"path": "/nappy/utils/right_strip.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Returns line but with curly braces right stripped off.
"""
match = rstrip_regex.match(line)
if not match: return line
return match.groups()[0]
if __name__ == "__main__":
test_lines = """
36 1001 {NLHEAD FFI}
MDB {remove me}
34... | code_fim | medium | {
"lang": "python",
"repo": "cedadev/nappy",
"path": "/nappy/utils/right_strip.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>arange(-n/2, 0), data[:,2][int(n/2):]/data[:,2].max(), 'bx')
plt.plot(np.arange(-n/2, 0), np.flip(data[:,0][:int(n/2)]/data[:,0].max(), 0), 'ko')
plt.legend(loc='best')
plt.show()<|fim_prefix|># repo: PacktPublishing/High-Performance-Scientific-Computing-With-C path: /Section 2/video3/plot_ft... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/High-Performance-Scientific-Computing-With-C",
"path": "/Section 2/video3/plot_ft.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>t')
plt.plot(np.arange(0, n/2), data[:,0][:int(n/2)]/data[:,0].max(), 'ko', label='Function')
plt.plot(np.arange(-n/2, 0), data[:,1][int(n/2):]/data[:,1].max(), 'rx')
plt.plot(np.arange(-n/2, 0), data[:,2][int(n/2):]/data[:,2].max(), 'bx')
plt.plot(np.arange(-n/2, 0), np.flip(data[:,0][:in... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/High-Performance-Scientific-Computing-With-C",
"path": "/Section 2/video3/plot_ft.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PacktPublishing/High-Performance-Scientific-Computing-With-C path: /Section 2/video3/plot_ft.py
#!/usr/bin/env python3
from sys import argv
import numpy as np
import matplotlib.pyplot as plt
if __name__ == "__main__":
data = np.genfromtxt(argv[1])
n = data.shape[0]
plt.plo<|fim_suffi... | code_fim | medium | {
"lang": "python",
"repo": "PacktPublishing/High-Performance-Scientific-Computing-With-C",
"path": "/Section 2/video3/plot_ft.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not nums:
return [[]]
else:
res = []
for i, c in enumerate(nums):
if c in d:
continue
else:
d[c] = True
rest_perms = self.permuteUnique(nums[:i] + nums[i + 1:])
... | code_fim | hard | {
"lang": "python",
"repo": "mahimadubey/leetcode-python",
"path": "/permutations_ii/solution.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mahimadubey/leetcode-python path: /permutations_ii/solution.py
"""
Given a collection of numbers that might contain duplicates, return all
possible unique permutations.
<|fim_suffix|> def permuteUnique(self, nums):
"""
:type nums: List[int]
:rtype: List[List[int]]
... | code_fim | hard | {
"lang": "python",
"repo": "mahimadubey/leetcode-python",
"path": "/permutations_ii/solution.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DedSecInside/Awesome-Scripts path: /Misc/Get_Location_Info/script.py
#!/usr/bin/env python3
# Created by `Fenil Gandhi`
# 20 October, 2018
"""
A simple script that prints location of user based on active internet connection
"""
import requests
def getLocationInfo():
"""
Returns the lo... | code_fim | medium | {
"lang": "python",
"repo": "DedSecInside/Awesome-Scripts",
"path": "/Misc/Get_Location_Info/script.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Main function.
Args:
"""
print('Fetching your location details based on your isp.')
data = getLocationInfo()
print(
'',
'-----------------------------------------------------------------------',
'%-12s : %24s' % ("GLOBAL IP", data.get("query")),
... | code_fim | medium | {
"lang": "python",
"repo": "DedSecInside/Awesome-Scripts",
"path": "/Misc/Get_Location_Info/script.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Hridoy-31/Python-Programming-University-of-Michigan path: /Getting Started With Python/Assignment 3-1.py
hrs = input("Enter Hours:")
hrs = float(hrs)
<|fim_suffix|>if (hrs <= 40):
pay = hrs*rph
print(pay)
else:
extrahour = (hrs - 40)
pay = (40 * rph) + (extrahour * 1.5 * rph)
... | code_fim | easy | {
"lang": "python",
"repo": "Hridoy-31/Python-Programming-University-of-Michigan",
"path": "/Getting Started With Python/Assignment 3-1.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>if (hrs <= 40):
pay = hrs*rph
print(pay)
else:
extrahour = (hrs - 40)
pay = (40 * rph) + (extrahour * 1.5 * rph)
print(pay)<|fim_prefix|># repo: Hridoy-31/Python-Programming-University-of-Michigan path: /Getting Started With Python/Assignment 3-1.py
hrs = input("Enter Hours:")
hrs = f... | code_fim | easy | {
"lang": "python",
"repo": "Hridoy-31/Python-Programming-University-of-Michigan",
"path": "/Getting Started With Python/Assignment 3-1.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cephdon/TikiBot path: /TikiBot/dispensing_screen.py
try: # Python 2
from Tkinter import * # noqa
except ImportError: # Python 3
from tkinter import * # noqa
import time
from rectbutton import RectButton
UPDATE_MS = 20
DISPLAY_MS = 125
class DispensingScreen(Frame):
def __init... | code_fim | hard | {
"lang": "python",
"repo": "cephdon/TikiBot",
"path": "/TikiBot/dispensing_screen.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.grid_columnconfigure(0, weight=1)
self.grid_rowconfigure(0, weight=1)
recipe.startDispensing(amount)
self.pid = self.after(UPDATE_MS, self.update_screen)
def update_screen(self):
self.pid = None
recipe = self.recipe
recipe.updateDispensing(... | code_fim | hard | {
"lang": "python",
"repo": "cephdon/TikiBot",
"path": "/TikiBot/dispensing_screen.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: typemytype/booleanOperations path: /Lib/booleanOperations/flatten.py
one, I use the original logic.
if fp is None:
fp = flatSegment[-1]
# flat segment only contains two intersection points or one intersection point and on... | code_fim | hard | {
"lang": "python",
"repo": "typemytype/booleanOperations",
"path": "/Lib/booleanOperations/flatten.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Reverse the points. This differs from the
reversal point pen in RoboFab in that it doesn't
worry about maintaing the start point position.
That has no benefit within the context of this module.
"""
# copy the points
points = _copyPoints(points)
# find the first on c... | code_fim | hard | {
"lang": "python",
"repo": "typemytype/booleanOperations",
"path": "/Lib/booleanOperations/flatten.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
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