text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> if cv2.waitKey(30) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()<|fim_prefix|># repo: xmanatee/mipt.digger.project path: /nmakeenkov_dev.py
import cv2
import rectangle_builder
cap = cv2.VideoCapture(u'data/CH0P0389.MPG')
r_b = rectangle_builder.RectangleBuilder()
while(cap.isOp... | code_fim | hard | {
"lang": "python",
"repo": "xmanatee/mipt.digger.project",
"path": "/nmakeenkov_dev.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cv2.rectangle(frame, lb, rt, (0, 200, 0), 2)
# for fr in q:
# for ch in fr:
# for c in ch[1]:
# cv2.rectangle(frame, (c[0], ch[0]), (c[1], ch[0]+1), (0,200,0))
to_show = cv2.resize(edges, (720, 405))
to_show_ = cv2.resize(frame, (720, 405))
cv2.imshow('', to_show)
cv2.imsh... | code_fim | medium | {
"lang": "python",
"repo": "xmanatee/mipt.digger.project",
"path": "/nmakeenkov_dev.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class BertAdapterTestBase(AdapterTestBase):
config_class = BertConfig
config = make_config(
BertConfig,
hidden_size=32,
num_hidden_layers=4,
num_attention_heads=4,
intermediate_size=37,
)
tokenizer_name = "bert-base-uncased"
@require_torch
class Be... | code_fim | medium | {
"lang": "python",
"repo": "cambridgeltl/autopeft",
"path": "/adapter-transformers-adapters3.1.0/tests_adapters/test_bert.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cambridgeltl/autopeft path: /adapter-transformers-adapters3.1.0/tests_adapters/test_bert.py
import unittest
from tests.models.bert.test_modeling_bert import *
from transformers import BertAdapterModel
from transformers.testing_utils import require_torch
from .methods import (
BottleneckAdap... | code_fim | hard | {
"lang": "python",
"repo": "cambridgeltl/autopeft",
"path": "/adapter-transformers-adapters3.1.0/tests_adapters/test_bert.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AddField(
model_name="hapaplacename",
name="historic",
field=models.BooleanField(
default=False,
help_text="Historischer Ort bedeutet es gibt diesen Ort heute nicht mehr",
verbose_name... | code_fim | medium | {
"lang": "python",
"repo": "acdh-oeaw/hapa",
"path": "/archiv/migrations/0003_hapaplacename_historic.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: acdh-oeaw/hapa path: /archiv/migrations/0003_hapaplacename_historic.py
# Generated by Django 3.1.6 on 2021-02-09 09:38
from django.db import migrations, models
<|fim_suffix|>
dependencies = [
("archiv", "0002_auto_20210202_1709"),
]
operations = [
migrations.AddFie... | code_fim | medium | {
"lang": "python",
"repo": "acdh-oeaw/hapa",
"path": "/archiv/migrations/0003_hapaplacename_historic.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_socket(host):
present = [
# "tcp://0.0.0.0:3000"
"tcp://127.0.0.1:3000"
]
for socket in present:
s = host.socket(socket)
assert s.is_listening<|fim_prefix|># repo: bolek2000/ansible-grafana path: /tests/test_default.py
from testinfra.utils.ansible_runn... | code_fim | hard | {
"lang": "python",
"repo": "bolek2000/ansible-grafana",
"path": "/tests/test_default.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bolek2000/ansible-grafana path: /tests/test_default.py
from testinfra.utils.ansible_runner import AnsibleRunner
testinfra_hosts = AnsibleRunner('.molecule/ansible_inventory').get_hosts('all')
def test_directories(host):
present = [
"/etc/grafana",
"/var/log/grafana",
... | code_fim | medium | {
"lang": "python",
"repo": "bolek2000/ansible-grafana",
"path": "/tests/test_default.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> present = [
# "tcp://0.0.0.0:3000"
"tcp://127.0.0.1:3000"
]
for socket in present:
s = host.socket(socket)
assert s.is_listening<|fim_prefix|># repo: bolek2000/ansible-grafana path: /tests/test_default.py
from testinfra.utils.ansible_runner import AnsibleRunner... | code_fim | medium | {
"lang": "python",
"repo": "bolek2000/ansible-grafana",
"path": "/tests/test_default.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: guzdy/tumblr_crawler path: /tumblr_crawler.py
# !/usr/bin/env python3
# -×- coding: utf-8 -*-
import sys
import configparser
import shlex
from image_downloader import ImagesDownloader
from video_downloader import VideoDownloader
def main(blogname, timesleep=0, proxies=None):
<|fim_suffix|> ... | code_fim | hard | {
"lang": "python",
"repo": "guzdy/tumblr_crawler",
"path": "/tumblr_crawler.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# main 部分， 设置 config 和 命令行参数
if __name__ == "__main__":
config_parser = configparser.ConfigParser()
config_parser.read('config.ini')
BLOGNAME = config_parser.get('USER', 'BLOGNAME')
blognames = shlex.split(BLOGNAME)
TIMEOUT = config_parser.getint('USER', 'TIMEOUT')
TIMESLEEP = con... | code_fim | hard | {
"lang": "python",
"repo": "guzdy/tumblr_crawler",
"path": "/tumblr_crawler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>ould", re.I | re.U): "which'd",
re.compile("which shall|which will", re.I | re.U): "which'll",
re.compile("which are", re.I | re.U): "which're",
re.compile("which have", re.I | re.U): "which've",
re.compile("who would|who had|who did", re.I | re.U): "who'd",
re.compile("who would have"... | code_fim | hard | {
"lang": "python",
"repo": "vatsalsaglani/nlp-text-contractions",
"path": "/NLPContractions/contraction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vatsalsaglani/nlp-text-contractions path: /NLPContractions/contraction.py
import re
from collections import defaultdict
expansionDict = {
re.compile('alright', re.I | re.U): "a'ight",
re.compile('am not|is not|has not|are not|have not|did not', re.I | re.U): "ain't",
re.compile('am n... | code_fim | hard | {
"lang": "python",
"repo": "vatsalsaglani/nlp-text-contractions",
"path": "/NLPContractions/contraction.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>): "that'll",
re.compile("that has|that is", re.I | re.U): "that's",
re.compile("that would|that had", re.I | re.U): "that'd",
re.compile("there had|there would", re.I | re.U): "there'd",
re.compile("there shall|there will", re.I | re.U): "there'll",
re.compile("there are", re.I | re.U... | code_fim | hard | {
"lang": "python",
"repo": "vatsalsaglani/nlp-text-contractions",
"path": "/NLPContractions/contraction.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yuquant/dicom_download_manager path: /datacenter/blueprints/ajax.py
# -*- coding: utf-8 -*-
"""
Author : Jason
Github : https://github.com/yuquant
Description :
"""
from flask import render_template, jsonify, Blueprint
from flask_login import current_user
from sqlalchemy import and_
from datacent... | code_fim | hard | {
"lang": "python",
"repo": "yuquant/dicom_download_manager",
"path": "/datacenter/blueprints/ajax.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> user = User.query.filter_by(username=username).first_or_404()
if not current_user.is_following(user):
return jsonify(message='Not follow yet.'), 400
current_user.unfollow(user)
return jsonify(message='Follow canceled.')
@ajax_bp.route('/bar/', methods=['GET'])
def bar():
"""... | code_fim | hard | {
"lang": "python",
"repo": "yuquant/dicom_download_manager",
"path": "/datacenter/blueprints/ajax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@ajax_bp.route('/uncollect/<int:photo_id>', methods=['POST'])
def uncollect(photo_id):
if not current_user.is_authenticated:
return jsonify(message='Login required.'), 403
photo = Photo.query.get_or_404(photo_id)
if not current_user.is_collecting(photo):
return jsonify(message... | code_fim | hard | {
"lang": "python",
"repo": "yuquant/dicom_download_manager",
"path": "/datacenter/blueprints/ajax.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chrisdjscott/Atoman path: /atoman/gui/utils.py
"""
GUI utilities
@author: Chris Scott
"""
from __future__ import absolute_import
from __future__ import unicode_literals
import logging
from PySide2 import QtGui, QtCore, QtWidgets
#############################################################... | code_fim | hard | {
"lang": "python",
"repo": "chrisdjscott/Atoman",
"path": "/atoman/gui/utils.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Show (and return) a progress dialog
"""
progress = QtWidgets.QProgressDialog(parent=parent)
progress.setWindowModality(QtCore.Qt.WindowModal)
progress.setWindowTitle(title)
progress.setLabelText(label)
progress.setRange(0, 0)
progress.setMinimumDuration(0)
... | code_fim | hard | {
"lang": "python",
"repo": "chrisdjscott/Atoman",
"path": "/atoman/gui/utils.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nnuncert/nnuncert path: /nnuncert/utils/io.py
import pickle
def save_obj(obj, path: str):
"""Save some object via pickle.
Parameters
----------
obj
path : str
"""
with open(path, 'wb') as h:
pickle.dump(obj, h)
def load_obj(path: str):
"""Load object ... | code_fim | hard | {
"lang": "python",
"repo": "nnuncert/nnuncert",
"path": "/nnuncert/utils/io.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns
-------
float
Content of first line converted to float.
"""
return float(get_first_line(file))
def txt2str(file: str) -> str:
"""Load first line from .txt file as string.
Parameters
----------
file : str
Returns
-------
str
Conte... | code_fim | hard | {
"lang": "python",
"repo": "nnuncert/nnuncert",
"path": "/nnuncert/utils/io.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return None
def trace(self):
"""
Return a tuple or dict of the state of the indicator.
It is used mainly for profiling of the signals.
This method must be overrided.
"""
return tuple()<|fim_prefix|># repo: cal97g/siis path: /strategy/indicator... | code_fim | medium | {
"lang": "python",
"repo": "cal97g/siis",
"path": "/strategy/indicator/indicator.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cal97g/siis path: /strategy/indicator/indicator.py
# @date 2018-09-02
# @author Frederic SCHERMA
# @license Copyright (c) 2018 Dream Overflow
# Indicator base class
class Indicator(object):
"""
Base class for an indicator.
@todo https://www.centralcharts.com/fr/forums/12-analyse-tech... | code_fim | medium | {
"lang": "python",
"repo": "cal97g/siis",
"path": "/strategy/indicator/indicator.py",
"mode": "psm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_suffix|> def compute(self, timestamp):
return None
def trace(self):
"""
Return a tuple or dict of the state of the indicator.
It is used mainly for profiling of the signals.
This method must be overrided.
"""
return tuple()<|fim_prefix|># repo: cal9... | code_fim | hard | {
"lang": "python",
"repo": "cal97g/siis",
"path": "/strategy/indicator/indicator.py",
"mode": "spm",
"license": "LicenseRef-scancode-warranty-disclaimer",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: developerdiniz/Python path: /01.Python - Orientação a Objetos/Exercicios Conta Bancaria/Exercicio_fixacao.py
'''Exercicio de fixação:
Crie um software degerenciamento bancario
Esse software poderá ser capaz de criar clientes e con<|fim_suffix|> cliente, saldo, limite, saca, depositar e consultar ... | code_fim | medium | {
"lang": "python",
"repo": "developerdiniz/Python",
"path": "/01.Python - Orientação a Objetos/Exercicios Conta Bancaria/Exercicio_fixacao.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cliente, saldo, limite, saca, depositar e consultar saldo'''<|fim_prefix|># repo: developerdiniz/Python path: /01.Python - Orientação a Objetos/Exercicios Conta Bancaria/Exercicio_fixacao.py
'''Exercicio de fixação:
Crie um software degerenciamento bancario
Esse software poderá ser capaz de criar client... | code_fim | medium | {
"lang": "python",
"repo": "developerdiniz/Python",
"path": "/01.Python - Orientação a Objetos/Exercicios Conta Bancaria/Exercicio_fixacao.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nciganovic/Blog path: /blogsite/blog/migrations/0010_blog_blog_slug.py
# Generated by Django 2.2 on 2019-05-20 17:24
<|fim_suffix|> operations = [
migrations.AddField(
model_name='blog',
name='blog_slug',
field=models.CharField(default='', max_lengt... | code_fim | medium | {
"lang": "python",
"repo": "nciganovic/Blog",
"path": "/blogsite/blog/migrations/0010_blog_blog_slug.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('blog', '0009_blog_img_name'),
]
operations = [
migrations.AddField(
model_name='blog',
name='blog_slug',
field=models.CharField(default='', max_length=200),
preserve_default=False,
),
]<|fim_prefix|... | code_fim | easy | {
"lang": "python",
"repo": "nciganovic/Blog",
"path": "/blogsite/blog/migrations/0010_blog_blog_slug.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(self,):
_BUZZWORD.__init__(self)
self.name = "BUZZWORDS"
self.specie = 'nouns'
self.basic = "buzzword"
self.jsondata = {}<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_buzzwords.py
from xai.brain.wordbase.nouns._buzzword import _BUZZWORD
<|fim_middle|>#cal... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_buzzwords.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/xai path: /xai/brain/wordbase/nouns/_buzzwords.py
from xai.brain.wordbase.nouns._buzzword import _BUZZWORD
<|fim_suffix|> def __init__(self,):
_BUZZWORD.__init__(self)
self.name = "BUZZWORDS"
self.specie = 'nouns'
self.basic = "buzzword"
self.jsondata = {}<|fim_middle|>#cal... | code_fim | easy | {
"lang": "python",
"repo": "cash2one/xai",
"path": "/xai/brain/wordbase/nouns/_buzzwords.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_read_v5_document_aktiv(datadir):
doc = DesignSpaceDocument.fromfile(datadir / "test_v5_aktiv.designspace")
assert not doc.locationLabels
assert_descriptors_equal(
doc.axes,
[
AxisDescriptor(
tag="wght",
name="Weight",
... | code_fim | hard | {
"lang": "python",
"repo": "gregdavill/KiBuzzard",
"path": "/KiBuzzard/deps/fonttools/Tests/designspaceLib/designspace_v5_test.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gregdavill/KiBuzzard path: /KiBuzzard/deps/fonttools/Tests/designspaceLib/designspace_v5_test.py
dth",
filename="Test_WghtWdth_different_from_name.ttf",
axisSubsets=[
RangeAxisSubsetDescriptor(name="Weight"),
RangeAxisSubsetD... | code_fim | hard | {
"lang": "python",
"repo": "gregdavill/KiBuzzard",
"path": "/KiBuzzard/deps/fonttools/Tests/designspaceLib/designspace_v5_test.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def chicalc(del_t,tau,ph,z,B_src,V_src,b,f_nuobs,f_err,flx_obs):
# Input Parameter #
#del_t :Duration of phase List
#tau :Timescale of expansion List
#ph :user input for phase integer
#z :redshift of the source float
#B_src :Magnetic Field Of Source float
#V_src :Volume Of Source float
#b :compressi... | code_fim | hard | {
"lang": "python",
"repo": "diveshjain-phy/zombie_galaxies",
"path": "/Abell1914/operations.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: diveshjain-phy/zombie_galaxies path: /Abell1914/operations.py
from scipy.special import gamma
#from scipy.stats import chisquare
import numpy as np
from astropy.cosmology import FlatLambdaCDM
from scipy.integrate import quad
from astropy.io import ascii
import math
import matplotlib.pyplot as plt... | code_fim | hard | {
"lang": "python",
"repo": "diveshjain-phy/zombie_galaxies",
"path": "/Abell1914/operations.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xusl/android-wilhelm path: /boot_images/core/hwengines/dmov/hal/build/SConscript
#===============================================================================
#
# HAL DMOV Libs
#
# GENERAL DESCRIPTION
# HAL DMOV Libs build script
#
# Copyright (c) 2009-2011 by QUALCOMM, Incorporated.
# All ... | code_fim | hard | {
"lang": "python",
"repo": "xusl/android-wilhelm",
"path": "/boot_images/core/hwengines/dmov/hal/build/SConscript",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> haldmov_qdsp6sw_obj = env.Object(HAL_DMOV_QDSP6SW_SOURCES)
haldmov_qdsp6sw_lib = env.Library('${BUILDPATH}/HALdmov_qdsp6sw', haldmov_qdsp6sw_obj)
haldmov_apps_obj = env.Object(HAL_DMOV_APPS_SOURCES)
haldmov_apps_lib = env.Library('${BUILDPATH}/HALdmov_apps', haldmov_apps_obj)
... | code_fim | hard | {
"lang": "python",
"repo": "xusl/android-wilhelm",
"path": "/boot_images/core/hwengines/dmov/hal/build/SConscript",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> env.AddLibsToImage(['MODEM_IMAGE', 'CBSP_MODEM_IMAGE','CBSP_QDSP6_SW_IMAGE','OSBL_BOOT_IMAGE', 'TZOS_IMAGE'],
[haldmov_lib])
if env['HAL_PLATFORM'] in ['8660','8960']:
env.AddLibsToImage(['NAND_TOOLS_IMAGE'],[haldmov_lib])
env.AddLibsToImage(['APPS_IMAGE', 'CBSP_APPS_IMAG... | code_fim | hard | {
"lang": "python",
"repo": "xusl/android-wilhelm",
"path": "/boot_images/core/hwengines/dmov/hal/build/SConscript",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> X1.append((mapping_c[choice(C)],mapping_cr[p],mapping_c[choice(C)]))
Y1.append(0)
except KeyError:
pass
distRt = defaultdict(int)
for s,p,o,score in Tg:
X2.append((mapping_t[s],mapping_tr[p],mapping_t[o]))
Y2.append(float(s... | code_fim | hard | {
"lang": "python",
"repo": "NIVA-Knowledge-Graph/NIVAUC",
"path": "/models/model_LP.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NIVA-Knowledge-Graph/NIVAUC path: /models/model_LP.py
### dense model
from keras import Model
from keras.layers import Dense, Dropout, BatchNormalization, Embedding, Multiply,Activation, Reshape, Concatenate, Lambda
from keras.utils import plot_model
import numpy as np
from random import choic... | code_fim | hard | {
"lang": "python",
"repo": "NIVA-Knowledge-Graph/NIVAUC",
"path": "/models/model_LP.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> pbar.update(1)
cvscores = np.asarray(cvscores)
for i,n in enumerate(model.metrics_names):
print(mode,n,"%.2f (+/- %.2f)" % (np.mean(cvscores[:,i]), np.std(cvscores[:,i])))
else:
model = LinkPredict(input_dim=[N,M,Nr,M... | code_fim | hard | {
"lang": "python",
"repo": "NIVA-Knowledge-Graph/NIVAUC",
"path": "/models/model_LP.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>sno = []
data = pd.read_csv("only_tweets.csv")
gs = goslate.Goslate()
for i in data:
text = gs.translate(i,"en")
with open("Translated.csv", "w") as csv_file:
writer = csv.writer(csv_file)
writer.writerow([sno,text])<|fim_prefix|># repo: JagadishSivakumar/Sentiment-Analysis-Globe ... | code_fim | hard | {
"lang": "python",
"repo": "JagadishSivakumar/Sentiment-Analysis-Globe",
"path": "/ml-core/translator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
sno = []
data = pd.read_csv("only_tweets.csv")
gs = goslate.Goslate()
for i in data:
text = gs.translate(i,"en")
with open("Translated.csv", "w") as csv_file:
writer = csv.writer(csv_file)
writer.writerow([sno,text])<|fim_prefix|># repo: JagadishSivakumar/Sentiment-Analysis-Globe ... | code_fim | hard | {
"lang": "python",
"repo": "JagadishSivakumar/Sentiment-Analysis-Globe",
"path": "/ml-core/translator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JagadishSivakumar/Sentiment-Analysis-Globe path: /ml-core/translator.py
from googletrans import Translator
import csv
import pandas as pd
data = pd.read_csv("only_tweets.csv")
translator = Translator()
'''text =
for i in data[2]:
translated = translator.traslate(i)
print(translated) ... | code_fim | hard | {
"lang": "python",
"repo": "JagadishSivakumar/Sentiment-Analysis-Globe",
"path": "/ml-core/translator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: oeg-upm/ttla path: /experiments/loader.py
import sys
import os
proj_path = (os.path.join(os<|fim_suffix|>ir))
# print("detect init project path: "+str(proj_path))
sys.path.append(proj_path)
import commons<|fim_middle|>.path.dirname(os.path.realpath(__file__)), os.pard | code_fim | easy | {
"lang": "python",
"repo": "oeg-upm/ttla",
"path": "/experiments/loader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>j_path))
sys.path.append(proj_path)
import commons<|fim_prefix|># repo: oeg-upm/ttla path: /experiments/loader.py
import sys
import os
proj_path = (os.path.join(os<|fim_middle|>.path.dirname(os.path.realpath(__file__)), os.pardir))
# print("detect init project path: "+str(pro | code_fim | medium | {
"lang": "python",
"repo": "oeg-upm/ttla",
"path": "/experiments/loader.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: oeg-upm/ttla path: /experiments/loader.py
import sys
import os
proj_path = (os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pard<|fim_suffix|>j_path))
sys.path.append(proj_path)
import commons<|fim_middle|>ir))
# print("detect init project path: "+str(pro | code_fim | easy | {
"lang": "python",
"repo": "oeg-upm/ttla",
"path": "/experiments/loader.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> env = make(ENV_NAMES[name])
agent = AGENTS[name]()
env.reset()
state = env.unwrapped.state
for i in range(3):
action = agent.get_action(state)
_, _, done, info = env.step(action)
state = info["state"]
env.render()
if done:
break<|fim... | code_fim | medium | {
"lang": "python",
"repo": "frostburn/gym_puyopuyo",
"path": "/tests/test_agent.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: frostburn/gym_puyopuyo path: /tests/test_agent.py
import pytest
from gym import make
from gym_puyopuyo.agent import AGENTS
from gym_puyopuyo.env import ENV_NAMES
<|fim_suffix|> env = make(ENV_NAMES[name])
agent = AGENTS[name]()
env.reset()
state = env.unwrapped.state
for i i... | code_fim | medium | {
"lang": "python",
"repo": "frostburn/gym_puyopuyo",
"path": "/tests/test_agent.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if pattern is not None:
filter_p = pattern + self.extension
else:
filter_p = '.*' + self.extension
self.filter_p = filter_p
gs.debug('Filter: {}'.format(filter_p), 1)
self.files = self.__filter(filter_p)
if self.files is []:
... | code_fim | hard | {
"lang": "python",
"repo": "ibaris/gscpy",
"path": "/gscpy/i_import/i_dr_import.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ibaris/gscpy path: /gscpy/i_import/i_dr_import.py
#!/usr/bin/env python
############################################################################
#
# MODULE: i.dr.import
# AUTHOR(S): Ismail Baris
# PURPOSE: Import data into a mapset from a file with considering a certain pattern.
#... | code_fim | hard | {
"lang": "python",
"repo": "ibaris/gscpy",
"path": "/gscpy/i_import/i_dr_import.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __import_file(self, filename, module, args):
mapname = os.path.splitext(os.path.basename(filename))[0]
gs.message(_('Processing <{}>...').format(mapname))
if module == 'r.import':
args['resolution_value'] = self.__raster_resolution(filename)
try:
... | code_fim | hard | {
"lang": "python",
"repo": "ibaris/gscpy",
"path": "/gscpy/i_import/i_dr_import.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: blufzzz/pytorch-hebbian path: /pytorch_hebbian/nn/layers.py
import torch
from torch import nn
class Flatten(nn.Module):
def forward(self, x: torch.Tensor):
<|fim_suffix|> def forward(self, x: torch.Tensor):
return torch.relu(x) ** self.n<|fim_middle|> return x.view(x.size(... | code_fim | medium | {
"lang": "python",
"repo": "blufzzz/pytorch-hebbian",
"path": "/pytorch_hebbian/nn/layers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return torch.relu(x) ** self.n<|fim_prefix|># repo: blufzzz/pytorch-hebbian path: /pytorch_hebbian/nn/layers.py
import torch
from torch import nn
class Flatten(nn.Module):
def forward(self, x: torch.Tensor):
return x.view(x.size(0), -1)
class RePU(nn.ReLU):
def __init__(self, ... | code_fim | medium | {
"lang": "python",
"repo": "blufzzz/pytorch-hebbian",
"path": "/pytorch_hebbian/nn/layers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cprint('\nlooking for updates ,please wait !',"yellow")
github_url = 'https://github.com/hamzaubi/EgyBest-Downloader'
r = requests.get(github_url)
soup = BeautifulSoup(r.text, "html.parser")
try:
github_version = soup.select_one("#readme > div.Box-body > article > h1").text.spl... | code_fim | medium | {
"lang": "python",
"repo": "hamzaubi/EgyBest-Downloader",
"path": "/Core/UpdateChecker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: hamzaubi/EgyBest-Downloader path: /Core/UpdateChecker.py
import requests
from bs4 import BeautifulSoup
from termcolor import cprint
<|fim_suffix|> cprint('\nlooking for updates ,please wait !',"yellow")
github_url = 'https://github.com/hamzaubi/EgyBest-Downloader'
r = requests.get(git... | code_fim | medium | {
"lang": "python",
"repo": "hamzaubi/EgyBest-Downloader",
"path": "/Core/UpdateChecker.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gistable/gistable path: /all-gists/4004663/snippet.py
def customized(default=None, template=None):
def decorator(method):
@functools.wraps(method)
def wrapper(self, *args, **kargs):
self.template = default
if self.current_user:
self.temp... | code_fim | medium | {
"lang": "python",
"repo": "gistable/gistable",
"path": "/all-gists/4004663/snippet.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class MainHandler(tornado.web.RequestHandler):
@customized(default='index.html', template='user.index.html')
def get(self):
self.render(self.template)<|fim_prefix|># repo: gistable/gistable path: /all-gists/4004663/snippet.py
def customized(default=None, template=None):
def decorator(... | code_fim | hard | {
"lang": "python",
"repo": "gistable/gistable",
"path": "/all-gists/4004663/snippet.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: thomasavare/history-of-interpretation path: /saliency/integrated_gradients_test.py
# Copyright 2019 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of th... | code_fim | medium | {
"lang": "python",
"repo": "thomasavare/history-of-interpretation",
"path": "/saliency/integrated_gradients_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
To run:
"python -m saliency.integrated_gradients_test" from the PAIR-code/saliency
directory.
"""
def testIntegratedGradientsGetMask(self):
with tf.Graph().as_default() as graph:
x = tf.placeholder(shape=[None, 3], dtype=tf.float32)
y = 5 * x[:, 0] + x[:, 0] * x[:, 1] + tf... | code_fim | medium | {
"lang": "python",
"repo": "thomasavare/history-of-interpretation",
"path": "/saliency/integrated_gradients_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return short_url.process_url(url, request, userID)<|fim_prefix|># repo: Pravv/PrvHosting path: /controllers/short_url.py
from flask import redirect, request
from models import short_url
<|fim_middle|>
def handle_short_url(userID):
url = request.args.get('url')
if url is None:
return ... | code_fim | medium | {
"lang": "python",
"repo": "Pravv/PrvHosting",
"path": "/controllers/short_url.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Pravv/PrvHosting path: /controllers/short_url.py
from flask import redirect, request
from models import short_url
<|fim_suffix|> url = request.args.get('url')
if url is None:
return redirect(request.host_url, code=302)
return short_url.process_url(url, request, userID)<|fim_... | code_fim | easy | {
"lang": "python",
"repo": "Pravv/PrvHosting",
"path": "/controllers/short_url.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.context = context
try:
tempdir = context.tempdir
if tempdir is None:
raise Exception()
except:
raise Exception("Context does not contain info about tempdir")
def __enter__(self):
self.context.cwd = os.getcwd()
... | code_fim | hard | {
"lang": "python",
"repo": "tmancal74/quantarhei",
"path": "/quantarhei/testing/behave.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def cleanup_temp_dir(context):
"""Cleans up temporary directory
"""
try:
os.chdir(context.cwd)
except:
print("Current working file record does not exist")
try:
context.tempdir.cleanup()
except:
print("Temporary directory cannot be cleaned up - do... | code_fim | hard | {
"lang": "python",
"repo": "tmancal74/quantarhei",
"path": "/quantarhei/testing/behave.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: tmancal74/quantarhei path: /quantarhei/testing/behave.py
# -*- coding: utf-8 -*-
"""
Support module for tests using `behave` package
"""
# standard imports
import os
import tempfile
import re
from subprocess import check_output
# non-standard imports
import pkg_resources
def quantarhei_... | code_fim | hard | {
"lang": "python",
"repo": "tmancal74/quantarhei",
"path": "/quantarhei/testing/behave.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("done")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--data_file', default = "training_set_rel3.tsv",
help = "name of .tsv file containing essay data")
parser.add_argument('--out_file', default = "training_set_rel3_x.tsv"... | code_fim | hard | {
"lang": "python",
"repo": "16lemoing/automated-essay-scoring",
"path": "/bin/compute_x_features.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> print(f"saving to {out_file}")
data.to_csv(out_file, sep = "\t")
print("done")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--data_file', default = "training_set_rel3.tsv",
help = "name of .tsv file containing essay da... | code_fim | hard | {
"lang": "python",
"repo": "16lemoing/automated-essay-scoring",
"path": "/bin/compute_x_features.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 16lemoing/automated-essay-scoring path: /bin/compute_x_features.py
# -*- coding: utf-8 -*-
import sys
sys.path.append("../src")
import argparse
from pathlib import Path
import pandas as pd
from spellchecker import SpellChecker
from nltk.tokenize.treebank import TreebankWordDetokenizer
from strin... | code_fim | hard | {
"lang": "python",
"repo": "16lemoing/automated-essay-scoring",
"path": "/bin/compute_x_features.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eslammohamed13/microblog path: /microblog-01-hello-world/src/models/Roles.py
import testdata
# Models declared
<|fim_suffix|> '''
Roles
'''
id = testdata.CountingFactory(10)
name = testdata.FakeDataFactory('name')
displayname = testdata.RandomLengthStringFactory()
des... | code_fim | medium | {
"lang": "python",
"repo": "eslammohamed13/microblog",
"path": "/microblog-01-hello-world/src/models/Roles.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''
Roles
'''
id = testdata.CountingFactory(10)
name = testdata.FakeDataFactory('name')
displayname = testdata.RandomLengthStringFactory()
description = testdata.RandomLengthStringFactory()<|fim_prefix|># repo: eslammohamed13/microblog path: /microblog-01-hello-world/src/model... | code_fim | medium | {
"lang": "python",
"repo": "eslammohamed13/microblog",
"path": "/microblog-01-hello-world/src/models/Roles.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: linsomniac/spawk path: /spawk/input.py
#!/usr/bin/env python3
# vim: ts=4 sw=4 ai et
class FileFollower:
'''Iterator that follows the changes to a file "tail -F"-like.
This iterator will produce all the lines in a file and then monitor
for changes to the file and produce new lines a... | code_fim | hard | {
"lang": "python",
"repo": "linsomniac/spawk",
"path": "/spawk/input.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> :param filename: Name of the file to follow.
:param sleep_time: (float) Time to sleep between polls of the file.
'''
def __init__(self, filename, sleep_time=1):
self.filename = filename
self.sleep_time = sleep_time
def _follow(self):
'''INTERNAL: Generator that... | code_fim | hard | {
"lang": "python",
"repo": "linsomniac/spawk",
"path": "/spawk/input.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: learningequality/kolibri path: /kolibri/core/tasks/main.py
import logging
from django.utils.functional import SimpleLazyObject
from kolibri.core.tasks.storage import Storage
from kolibri.core.tasks.utils import db_connection
from kolibri.core.tasks.worker import Worker
from kolibri.utils import... | code_fim | hard | {
"lang": "python",
"repo": "learningequality/kolibri",
"path": "/kolibri/core/tasks/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def initialize_workers():
logger.info("Starting async task workers.")
return Worker(
connection=connection,
regular_workers=conf.OPTIONS["Tasks"]["REGULAR_PRIORITY_WORKERS"],
high_workers=conf.OPTIONS["Tasks"]["HIGH_PRIORITY_WORKERS"],
)<|fim_prefix|># repo: learningequ... | code_fim | hard | {
"lang": "python",
"repo": "learningequality/kolibri",
"path": "/kolibri/core/tasks/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def __job_storage():
return Storage(
connection=connection,
)
# This storage instance should be used to access job_storage db.
job_storage = SimpleLazyObject(__job_storage)
""" :type: Storage """
def initialize_workers():
logger.info("Starting async task workers.")
return Worke... | code_fim | medium | {
"lang": "python",
"repo": "learningequality/kolibri",
"path": "/kolibri/core/tasks/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> See Also
--------
:py:class:`~autogluon.eda.visualization.dataset.DatasetStatistics`
:py:class:`~autogluon.eda.visualization.missing.MissingValues`
"""
def can_handle(self, state: AnalysisState, args: AnalysisState) -> bool:
return True
def _fit(self, state: AnalysisS... | code_fim | hard | {
"lang": "python",
"repo": "stjordanis/autogluon",
"path": "/eda/src/autogluon/eda/analysis/missing.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: stjordanis/autogluon path: /eda/src/autogluon/eda/analysis/missing.py
from typing import Any, Dict
from .base import AbstractAnalysis, AnalysisState
__all__ = ["MissingValuesAnalysis"]
class MissingValuesAnalysis(AbstractAnalysis):
"""
Analyze dataset's missing value counts and freque... | code_fim | medium | {
"lang": "python",
"repo": "stjordanis/autogluon",
"path": "/eda/src/autogluon/eda/analysis/missing.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: doomdagger/tweetmap2 path: /application.py
#!/usr/bin/env python
# The main file, start our application here
<|fim_suffix|>__author__ = "He Li, Haoxiang Xu"
logging.basicConfig(filename='tweetmap2.log', level=logging.DEBUG)
if __name__ == '__main__':
io.run(app, host='0.0.0.0', port=5000, d... | code_fim | easy | {
"lang": "python",
"repo": "doomdagger/tweetmap2",
"path": "/application.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>from tweetmap import app, io
__author__ = "He Li, Haoxiang Xu"
logging.basicConfig(filename='tweetmap2.log', level=logging.DEBUG)
if __name__ == '__main__':
io.run(app, host='0.0.0.0', port=5000, debug=True)<|fim_prefix|># repo: doomdagger/tweetmap2 path: /application.py
#!/usr/bin/env python
# The... | code_fim | easy | {
"lang": "python",
"repo": "doomdagger/tweetmap2",
"path": "/application.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aiogram/aiogram path: /aiogram/types/callback_query.py
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Optional
from pydantic import Field
from .base import TelegramObject
if TYPE_CHECKING:
from ..methods import AnswerCallbackQuery
from .message import Messag... | code_fim | hard | {
"lang": "python",
"repo": "aiogram/aiogram",
"path": "/aiogram/types/callback_query.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def answer(
self,
text: Optional[str] = None,
show_alert: Optional[bool] = None,
url: Optional[str] = None,
cache_time: Optional[int] = None,
**kwargs: Any,
) -> AnswerCallbackQuery:
"""
Shortcut for method :class:`aiogram.methods.ans... | code_fim | hard | {
"lang": "python",
"repo": "aiogram/aiogram",
"path": "/aiogram/types/callback_query.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
# Test rotations
# Create more text objects
AddOperator("Reflect")
reflect = ReflectAttributes()
reflect.reflections=(1, 1, 0, 0, 0, 0, 0, 0)
SetOperatorOptions(reflect)
text.text="Left"
text.position=(-20, -5, 10)
text.rotations=(0,0,90)
text.heightMode = text.Relative
DrawPlots()
ResetView()
Test("tex... | code_fim | hard | {
"lang": "python",
"repo": "visit-dav/visit",
"path": "/src/test/tests/rendering/text3d.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: visit-dav/visit path: /src/test/tests/rendering/text3d.py
# ----------------------------------------------------------------------------
# CLASSES: nightly
#
# Test Case: text3d.py
#
# Tests: mesh - 2D curvilinear, single domain
# plots - Pseudocolor
# ... | code_fim | hard | {
"lang": "python",
"repo": "visit-dav/visit",
"path": "/src/test/tests/rendering/text3d.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>extendedApplTable = MibTable((1, 3, 6, 1, 4, 1, 334, 3, 1, 1, 1), )
if mibBuilder.loadTexts: extendedApplTable.setStatus('mandatory')
if mibBuilder.loadTexts: extendedApplTable.setDescription('The table holding information specific to an Application for which extended information is available.')
extendedA... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/EXTENDED-MADMAN-MIB.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp-with-texts/EXTENDED-MADMAN-MIB.py
dConnectFailureReason, mtaGroupIndex = mibBuilder.importSymbols("MTA-MIB", "mtaGroupInboundRejectionReason", "mtaGroupName", "mtaGroupOutboundConnectFailureReason", "mtaGroupIndex")
applName, applOperStatus, applIndex,... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/EXTENDED-MADMAN-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: agustinhenze/mibs.snmplabs.com path: /pysnmp-with-texts/EXTENDED-MADMAN-MIB.py
son", "mtaGroupName", "mtaGroupOutboundConnectFailureReason", "mtaGroupIndex")
applName, applOperStatus, applIndex, applLastChange = mibBuilder.importSymbols("NETWORK-SERVICES-MIB", "applName", "applOperStatus", "applI... | code_fim | hard | {
"lang": "python",
"repo": "agustinhenze/mibs.snmplabs.com",
"path": "/pysnmp-with-texts/EXTENDED-MADMAN-MIB.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BA1RY/posture-aid path: /config.py
class PostureAidConfig:
__conf = {
"PAD_X": 30,
"PAD_Y": 30,
"MODEL": 101,
"CAM_ID": 0,
"CORRECT_POS": (0,0,0,0),
"SCALE_FACTOR": 0.7125,
"ALARM_FILE": './data/audio/alarm_audio.wav'
}
__setters... | code_fim | medium | {
"lang": "python",
"repo": "BA1RY/posture-aid",
"path": "/config.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def set(key, value):
if key in PostureAidConfig.__setters:
PostureAidConfig.__conf[key] = value
else:
raise KeyError("Key not accepted in set() method")<|fim_prefix|># repo: BA1RY/posture-aid path: /config.py
class PostureAidConfig:
__conf... | code_fim | medium | {
"lang": "python",
"repo": "BA1RY/posture-aid",
"path": "/config.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return PostureAidConfig.__conf[key]
@staticmethod
def set(key, value):
if key in PostureAidConfig.__setters:
PostureAidConfig.__conf[key] = value
else:
raise KeyError("Key not accepted in set() method")<|fim_prefix|># repo: BA1RY/posture-aid path: ... | code_fim | medium | {
"lang": "python",
"repo": "BA1RY/posture-aid",
"path": "/config.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: m-star18/atcoder path: /submissions/arc011/b.py
import sys
read = sys.stdin.buffer.read
readline = sys.stdin.buffer.readline
readlines = sys.stdin.buffer.readlines
sys.setrecursionlimit(10 ** 7)
n = int(readline())
w = list(readline().rstrip().decode().split())
check = [('z', 'r'), ('b', 'c'), (... | code_fim | medium | {
"lang": "python",
"repo": "m-star18/atcoder",
"path": "/submissions/arc011/b.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>', 'x'), ('p', 'm'), ('h', 'k'), ('n', 'g')]
ans = []
for ww in w:
ww = ww.lower()
memo = ''
for m in ww:
for i, num in enumerate(check):
if m in num:
memo += str(i)
break
if memo != '':
ans.append(memo)
print(' '.join(ans))<|fim_... | code_fim | medium | {
"lang": "python",
"repo": "m-star18/atcoder",
"path": "/submissions/arc011/b.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|># True/False file exists
def file_exists(path):
if os.path.isfile(os.path.abspath(path)):
return True
return False
# True/False directory exists
def dir_exists(path):
if os.path.isdir(os.path.abspath(path)):
return True
return False
# True/False directory and or file exists
def dir_or_file_exist... | code_fim | hard | {
"lang": "python",
"repo": "ZachisGit/ImageTranslation-MultidirectionalAutoencoders",
"path": "/ai_lab/storagemanager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ZachisGit/ImageTranslation-MultidirectionalAutoencoders path: /ai_lab/storagemanager.py
import os
# None if file doesnt exist
# abspath(file) if it exists
def check_file_path(path):
if os.path.isfile(os.path.abspath(path)):
return os.path.abspath(path)
return None
# None if directory doesnt... | code_fim | medium | {
"lang": "python",
"repo": "ZachisGit/ImageTranslation-MultidirectionalAutoencoders",
"path": "/ai_lab/storagemanager.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if os.path.isfile(os.path.abspath(path)):
return True
return False
# True/False directory exists
def dir_exists(path):
if os.path.isdir(os.path.abspath(path)):
return True
return False
# True/False directory and or file exists
def dir_or_file_exists(path):
if os.path.isdir(os.path.abspath(path)... | code_fim | medium | {
"lang": "python",
"repo": "ZachisGit/ImageTranslation-MultidirectionalAutoencoders",
"path": "/ai_lab/storagemanager.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/pulumi-azure-native path: /sdk/python/pulumi_azure_native/dataprotection/outputs.py
duration_in_days: Optional[float] = None,
state: Optional[str] = None):
"""
Soft delete related settings
:param float retention_duration_in_days: Soft delete retenti... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/dataprotection/outputs.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def __init__(__self__, *,
repeating_time_intervals: Sequence[str],
time_zone: Optional[str] = None):
"""
Schedule for backup
:param Sequence[str] repeating_time_intervals: ISO 8601 repeating time interval format
:param str time_zone: Ti... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/dataprotection/outputs.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: pulumi/pulumi-azure-native path: /sdk/python/pulumi_azure_native/dataprotection/outputs.py
ts the type of secret store
:param str uri: Uri to get to the resource
:param str value: Gets or sets value stored in secret store resource
"""
pulumi.set(__self__, "secret_s... | code_fim | hard | {
"lang": "python",
"repo": "pulumi/pulumi-azure-native",
"path": "/sdk/python/pulumi_azure_native/dataprotection/outputs.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # print('covered_branches', covered_branches)
for branch_lineno in goal_branch:
if not branch_lineno in covered_branches:
break
else:
# print('Terminated: goal_branch is '
# + str(goal_branch)
# + ', covered_branches are '
# + str(covered_branches))
# the branch is fully... | code_fim | hard | {
"lang": "python",
"repo": "MisterAI/AutoTeSG",
"path": "/DistanceCalculator.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MisterAI/AutoTeSG path: /DistanceCalculator.py
#!/usr/bin/python
import sys
import astor
from CodeRunner import runCode
from CustomExceptions import *
class DistanceCalculator():
def normalise_branch_distance(self, branch_distance):
try:
return 1 - pow(1.001, -branch_distance)
except Ov... | code_fim | hard | {
"lang": "python",
"repo": "MisterAI/AutoTeSG",
"path": "/DistanceCalculator.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>img = np.zeros((source.shape[0]*data['dims'][0], source.shape[1]*data['dims'][1], 3), np.uint8)
y = 0
for row in source:
x = 0
for pix in row: # bgr
pal_key = palette_oct.get((int(pix[2]/32), int(pix[1]/32), int(pix[0]/32)))
if pal_key is None:
pal_key = palette_quad.... | code_fim | hard | {
"lang": "python",
"repo": "Iapetus-11/photo-mosaic-generator",
"path": "/compiler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#cv2.imshow('image', source)
#cv2.waitKey(0)
xi = data['dims'][1]
yi = data['dims'][1]
img = np.zeros((source.shape[0]*data['dims'][0], source.shape[1]*data['dims'][1], 3), np.uint8)
y = 0
for row in source:
x = 0
for pix in row: # bgr
pal_key = palette_oct.get((int(pix[2]/32), int(pix[... | code_fim | hard | {
"lang": "python",
"repo": "Iapetus-11/photo-mosaic-generator",
"path": "/compiler.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.