text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|>
except:
print("something went wrong")
return command
def run_lisa():
command = take_command()
if 'play' in command:
song = command.replace('play','')
talk('hey playing' + song)
print('playing...'+ song)
pywhatkit.playon... | code_fim | hard | {
"lang": "python",
"repo": "ridgerunner03/AI_project",
"path": "/AAAA.000.000.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>max_sc = max(sc_lst)
min_sc = min(sc_lst)
sc_lst.remove(max_sc)
sc_lst.remove(min_sc)
ave_sc = sum(sc_lst) / len(sc_lst)
print('去除最高分%d，最低分%d，平均分为%d' % (max_sc, min_sc, ave_sc))
print('end')<|fim_prefix|># repo: KeasonL/CrossinCode_test100 path: /097_ScoreCounting.py
# 赛场统分
# 【问题】在编程竞赛中，有10个评委为参赛的选手打分，分数... | code_fim | hard | {
"lang": "python",
"repo": "KeasonL/CrossinCode_test100",
"path": "/097_ScoreCounting.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KeasonL/CrossinCode_test100 path: /097_ScoreCounting.py
# 赛场统分
# 【问题】在编程竞赛中，有10个评委为参赛的选手打分，分数为0 ~ 100分。
# 选手最后得分为：去掉一个最高分和一个最低分后其余8个分数的平均值。请编写一个程序实现。
<|fim_suffix|>max_sc = max(sc_lst)
min_sc = min(sc_lst)
sc_lst.remove(max_sc)
sc_lst.remove(min_sc)
ave_sc = sum(sc_lst) / len(sc_lst)
print('去除最高... | code_fim | hard | {
"lang": "python",
"repo": "KeasonL/CrossinCode_test100",
"path": "/097_ScoreCounting.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nikit34/kassa-ios-ui-tests path: /tests/shedule_page/test_001_filters.py
from time import sleep
import pytest
import allure
from app.debug_api import DebugAPI
from app.check_api import HandlersAPI
from locators.movies_details_locators import MoviesDetailsPageLocators
from locators.movies_locator... | code_fim | hard | {
"lang": "python",
"repo": "nikit34/kassa-ios-ui-tests",
"path": "/tests/shedule_page/test_001_filters.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """тапнуть на фичерс,
тапнуть на смотреть расписание,
найти кнопку отмены, кнопку карты, поле поиска"""
with allure.step('MoviesPage'):
self.movie_page = MoviesPage(driver)
self.movie_page.set_custom_wait(10)
self.movie_page.act.click_by_... | code_fim | hard | {
"lang": "python",
"repo": "nikit34/kassa-ios-ui-tests",
"path": "/tests/shedule_page/test_001_filters.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: serenapaneri/final_assignment path: /scripts/user_interface.py
#! /usr/bin/env python
# import ros stuff
import rospy
from std_srvs.srv import *
#to check if the service is active
active_ = False
def unable_service(req):
"""
This function contains the variable declared above that is
used to... | code_fim | hard | {
"lang": "python",
"repo": "serenapaneri/final_assignment",
"path": "/scripts/user_interface.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main():
"""
The main function allows the user to choose the robot's behavior.
If the service is active it call the function getInput that allows
the user to make a new choice. If it is not, it check if the selected
behavior is the second one and in that case change it with the fourth one.
"""
... | code_fim | hard | {
"lang": "python",
"repo": "serenapaneri/final_assignment",
"path": "/scripts/user_interface.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # reading the previous input
prev_input_ = rospy.get_param('/input')
input_ = prev_input_
#in order to make the user to choose one of the 5 possible inputs
while (prev_input_ == input_) or (input_ > 5 or input_ < 1):
if input_ > 5 or input_ < 1:
#in the case in which the user make another sel... | code_fim | hard | {
"lang": "python",
"repo": "serenapaneri/final_assignment",
"path": "/scripts/user_interface.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TTNguyenDev/Thesis-2020 path: /DataProcessing/medical.py
import pandas as pd
from pandas.io.json import json_normalize
import numpy as np
import warnings
import re
warnings.filterwarnings("ignore")
data_path = '/Users/trietnguyen/Documents/Thesis/Thesis-2020/References/Crawler/summaryDataJson.js... | code_fim | hard | {
"lang": "python",
"repo": "TTNguyenDev/Thesis-2020",
"path": "/DataProcessing/medical.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def rmDuplicate(df):
df.drop_duplicates(subset ='noSpace',
keep = 'first', inplace = True)
df.index = range(len(df.index))
def splitMedicine(df):
df_temp = df['name'].apply(formatName)
new_df = pd.DataFrame([[a, b, c] for a,b,c in df_temp.values], columns=['number',... | code_fim | hard | {
"lang": "python",
"repo": "TTNguyenDev/Thesis-2020",
"path": "/DataProcessing/medical.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> @staticmethod
def run():
'''
Read software name on command line and run version selection
'''
try:
opts, args = getopt.getopt(sys.argv[1:], 'h', ['help'])
except getopt.GetoptError as exception:
print('Error parsing command line: %s' ... | code_fim | hard | {
"lang": "python",
"repo": "c4s4/babel",
"path": "/bin/version",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def ask_version(self):
'''
Prompt user for software version in the list of installed versions
'''
# print version list
print('Please choose a version:')
index = 1
if self.current_version == 'current':
selected = self.SELECTED
... | code_fim | hard | {
"lang": "python",
"repo": "c4s4/babel",
"path": "/bin/version",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: c4s4/babel path: /bin/version
#!/usr/bin/env python
# encoding: UTF-8
'''
Script to select current version for a given soft (python, ruby or java).
'''
import os
import re
import sys
import glob
import getopt
# fix input in Python 2 and 3
try:
input = raw_input # pylint: disable=redefined... | code_fim | hard | {
"lang": "python",
"repo": "c4s4/babel",
"path": "/bin/version",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: christianbillp/specialkursus path: /w1a1_test.py
import bnn
#get
#!wget http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
#!wget http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
#unzip
#!gzip -d t10k-images-idx3-ubyte.gz
#!gzip -d t10k-labels-idx1-ubyte.gz
<|fim_suffix|>print... | code_fim | hard | {
"lang": "python",
"repo": "christianbillp/specialkursus",
"path": "/w1a1_test.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print("Testing throughput")
result_W1A1 = lfcW1A1_classifier.classify_mnists("/home/xilinx/jupyter_notebooks/bnn/t10k-images-idx3-ubyte")<|fim_prefix|># repo: christianbillp/specialkursus path: /w1a1_test.py
import bnn
#get
#!wget http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
#!wget http://... | code_fim | hard | {
"lang": "python",
"repo": "christianbillp/specialkursus",
"path": "/w1a1_test.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
flair_model = FlairModel(model_path="ner", entities_to_keep=["PERSON"])
evaluator = Evaluator(model=flair_model)
evaluation_results = evaluator.evaluate_all(small_dataset)
scores = evaluator.calculate_score(evaluation_results)
assert_model_results_gt(scores, "PERSON", 0)<|fim_prefix|... | code_fim | medium | {
"lang": "python",
"repo": "microsoft/presidio-research",
"path": "/tests/test_flair_model.py",
"mode": "spm",
"license": "LicenseRef-scancode-generic-cla",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: microsoft/presidio-research path: /tests/test_flair_model.py
import sys
import pytest
from presidio_evaluator.evaluation import Evaluator
from tests.conftest import assert_model_results_gt
from presidio_evaluator.models.flair_model import FlairModel
<|fim_suffix|> flair_model = FlairModel(m... | code_fim | medium | {
"lang": "python",
"repo": "microsoft/presidio-research",
"path": "/tests/test_flair_model.py",
"mode": "psm",
"license": "LicenseRef-scancode-generic-cla",
"source": "the-stack-v2"
} |
<|fim_suffix|> flair_model = FlairModel(model_path="ner", entities_to_keep=["PERSON"])
evaluator = Evaluator(model=flair_model)
evaluation_results = evaluator.evaluate_all(small_dataset)
scores = evaluator.calculate_score(evaluation_results)
assert_model_results_gt(scores, "PERSON", 0)<|fim_prefix|>... | code_fim | medium | {
"lang": "python",
"repo": "microsoft/presidio-research",
"path": "/tests/test_flair_model.py",
"mode": "spm",
"license": "LicenseRef-scancode-generic-cla",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cash2one/Dockerfile path: /qimen_server/waybill_jd.py
# coding: utf-8
import logging
import uuid
import json
import xmltodict
import bottle
from bottle import HTTPError
from bottle.ext import sqlalchemy
from database import Base, engine
from database import JdWaybillSendResp, JdWaybillApplyResp
... | code_fim | hard | {
"lang": "python",
"repo": "cash2one/Dockerfile",
"path": "/qimen_server/waybill_jd.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> query = bottle.request.query
jd_rsp = db.query(JdWaybillSendResp).filter_by(wms_order_code=query.get('wms_order_code')).first()
if jd_rsp:
# return entities
return jd_rsp.body
return HTTPError(404, None)
def jd_get_response_normal():
code = str(uuid.uuid4()).split('-'... | code_fim | hard | {
"lang": "python",
"repo": "cash2one/Dockerfile",
"path": "/qimen_server/waybill_jd.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Beatrizpjunq/Learning_python path: /texte COHPIAH.py
# -*- coding: utf-8 -*-
"""
Created on Sat Jul 18 20:24:53 2020
@author: filip
"""
import re
texto = "Muito além, nos confins inexplorados da região mais brega da Borda Ocidental desta Galáxia, há um pequeno sol amarelo e esquecido.... | code_fim | hard | {
"lang": "python",
"repo": "Beatrizpjunq/Learning_python",
"path": "/texte COHPIAH.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def tam_medio (list_palavras): # Traço linguístico 1
palavras = lista_palavras(texto)
i = 0
soma_palavras = 0
while i < len(palavras):
x = palavras[i]
soma_palavras = soma_palavras + len(x)
i +=1
tam = soma_palavras/len(palavras)
return tam
def t... | code_fim | hard | {
"lang": "python",
"repo": "Beatrizpjunq/Learning_python",
"path": "/texte COHPIAH.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> retval = add_new_topic(request.json, ALL_DBS)
return jsonify({'return_code': retval})
@app.route('/api/1.0/<string:api_call>', methods = ['POST'])
def generic_api_call(api_call):
if not request.json:
abort(400)
param1 = request.json.get('param1', 'no param 1')
param2 = request... | code_fim | hard | {
"lang": "python",
"repo": "jillh510/video_story_arcs",
"path": "/webserver.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LHYAha/flask_demo path: /app.py
#-*- coding = utf-8-*-
#@Time : 2020/6/26 11:02
#@Author :Ella
#@File :app.py
#@Software : PyCharm
import time
import datetime
from flask import Flask,render_template,request #render_template渲染模板
app = Flask(__name__) #初始化的对象
#路由解析，通过用户访问的路径，匹配想要的函数
@app.route... | code_fim | medium | {
"lang": "python",
"repo": "LHYAha/flask_demo",
"path": "/app.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == 'POST':
result = request.form
return render_template("test/result.html",result = result)
if __name__ == '__main__':
app.run(debug=True)<|fim_prefix|># repo: LHYAha/flask_demo path: /app.py
#-*- coding = utf-8-*-
#@Time : 2020/6/26 11:02
#@Author :Ella
#@File ... | code_fim | hard | {
"lang": "python",
"repo": "LHYAha/flask_demo",
"path": "/app.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''This step generates a PDS-style requirements file'''
def execute(self):
token = self.getToken()
if not token:
_logger.info('🤷♀️ No GitHub administrative token; cannot generate requirements')
return
argv = [
'requirement-report',
... | code_fim | hard | {
"lang": "python",
"repo": "nutjob4life/roundup-action",
"path": "/src/pds/roundup/step.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
logger.info("Nothing to report")
ph.save_products(products)
logger.info("Configuration saved")
else:
print("Exec this file as the main entrypoint! -> python3 init.py")<|fim_prefix|># repo: jpradass/AmazonSpider path: /init.py
from helper.logger_helper import Log
from he... | code_fim | medium | {
"lang": "python",
"repo": "jpradass/AmazonSpider",
"path": "/init.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> ph.save_products(products)
logger.info("Configuration saved")
else:
print("Exec this file as the main entrypoint! -> python3 init.py")<|fim_prefix|># repo: jpradass/AmazonSpider path: /init.py
from helper.logger_helper import Log
from helper.mail_helper import MailHelper
import spider.spider ... | code_fim | medium | {
"lang": "python",
"repo": "jpradass/AmazonSpider",
"path": "/init.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jpradass/AmazonSpider path: /init.py
from helper.logger_helper import Log
from helper.mail_helper import MailHelper
import spider.spider as spider
from configuration.configuration_handler import Configuration
from configuration.products_handler import ProductsHandler
if __name__ == "__main__":
... | code_fim | medium | {
"lang": "python",
"repo": "jpradass/AmazonSpider",
"path": "/init.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: OpenHumans/openhumans-seeq path: /openhumans_seeq/migrations/0001_initial.py
# -*- coding: utf-8 -*-
# Generated by Django 1.10.4 on 2016-12-19 15:25
from __future__ import unicode_literals
<|fim_suffix|>
class Migration(migrations.Migration):
initial = True
dependencies = [
]
... | code_fim | medium | {
"lang": "python",
"repo": "OpenHumans/openhumans-seeq",
"path": "/openhumans_seeq/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yuanyunyy/insight_project path: /test_Spark.py
def test(d_iter):
from cqlengine import columns
from cqlengine.models import Model
from cqlengine.query import ModelQuerySet
from cqlengine import connection
from cqlengine.management import sync_table
... | code_fim | hard | {
"lang": "python",
"repo": "yuanyunyy/insight_project",
"path": "/test_Spark.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> link_id = columns.Text(primary_key=True)
title = columns.Text()
permalink = columns.Text()
subreddit = columns.Text()
subreddit_id = columns.Text()
selftext = columns.Text()
created = columns.In... | code_fim | hard | {
"lang": "python",
"repo": "yuanyunyy/insight_project",
"path": "/test_Spark.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>3]) * 3
yuki[i], enemy[(i+1)%3] = max(0, yuki[i]-enemy[(i+1)%3]), max(0, enemy[(i+1)%3]-yuki[i])
for i in range(3):
ans += min(yuki[i], enemy[i])
print(ans)<|fim_prefix|># repo: knuu/competitive-programming path: /yukicoder/yuki161.py
yuki = list(map(int, input().split()))
S = input()
enemy = [S... | code_fim | medium | {
"lang": "python",
"repo": "knuu/competitive-programming",
"path": "/yukicoder/yuki161.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rhdurham/Automated-containerized-bioinformatics-workflows path: /server/main.py
import tornado.ioloop
import tornado.web
import json
import utils
class BaseHandler(tornado.web.RequestHandler):
def set_default_headers(self):
self.set_header("Access-Control-Allow-Origin", "*")
... | code_fim | hard | {
"lang": "python",
"repo": "rhdurham/Automated-containerized-bioinformatics-workflows",
"path": "/server/main.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>class SubmitHandler(BaseHandler):
def post(self):
data = tornado.escape.json_decode(self.request.body)
print(data)
folderPath = str(data['id'])
utils.mkdir(folderPath)
self.write('testing')
def make_app():
return tornado.web.Application([
(r"/packag... | code_fim | hard | {
"lang": "python",
"repo": "rhdurham/Automated-containerized-bioinformatics-workflows",
"path": "/server/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for package in packages:
name = packages[package]["name"]
version = packages[package]["version"]
try:
if version not in condaPackages[name]["versions"]:
condaPackages[name]["versions"].append(version)
except:
... | code_fim | medium | {
"lang": "python",
"repo": "rhdurham/Automated-containerized-bioinformatics-workflows",
"path": "/server/main.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: withJackson/NovelWebsite path: /scrapy/topdb/topdb/spiders/novels.py
# -*- coding: utf-8 -*-
import scrapy
import os
from topdb.items import BiqugeItem
class NovelsSpider(scrapy.Spider):
name = 'novels'
allowed_domains = ['xbiquge.la']
start_urls = ['http://www.xbiquge.la/xiaoshuo... | code_fim | hard | {
"lang": "python",
"repo": "withJackson/NovelWebsite",
"path": "/scrapy/topdb/topdb/spiders/novels.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (not os.path.exists(newname)):
os.makedirs(newname)
if(not os.path.exists(newname+'/'+ str(i) + ".txt")):
yield scrapy.Request(url, meta={'chaptername':chaptername,'tag':classname,'name':name,'author':author,'index':i}, callback=self.detail_parse... | code_fim | hard | {
"lang": "python",
"repo": "withJackson/NovelWebsite",
"path": "/scrapy/topdb/topdb/spiders/novels.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>[i-1]*A[i]),A[i]))
Min.append(min(min(Max[i-1]*A[i],Min[i-1]*A[i]),A[i]))
tmax=Max[0]
for i in range(0,size):
if Max[i]>tmax:
tmax=Max[i]
return tmax<|fim_prefix|># repo: talentlei/leetcode path: /python/151-160/Maximum Product Subarray.py
... | code_fim | hard | {
"lang": "python",
"repo": "talentlei/leetcode",
"path": "/python/151-160/Maximum Product Subarray.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: talentlei/leetcode path: /python/151-160/Maximum Product Subarray.py
def maxProduct(self, A):
size= len(A)
if size==1:
return A[0]
Max=<|fim_suffix|>[i-1]*A[i]),A[i]))
Min.append(min(min(Max[i-1]*A[i],Min[i-1]*A[i]),A[i]))
tmax=Max[0]
... | code_fim | hard | {
"lang": "python",
"repo": "talentlei/leetcode",
"path": "/python/151-160/Maximum Product Subarray.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> for i in range(0,size):
if Max[i]>tmax:
tmax=Max[i]
return tmax<|fim_prefix|># repo: talentlei/leetcode path: /python/151-160/Maximum Product Subarray.py
def maxProduct(self, A):
size= len(A)
if size==1:
return A[0]
Max=[... | code_fim | hard | {
"lang": "python",
"repo": "talentlei/leetcode",
"path": "/python/151-160/Maximum Product Subarray.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jamesilloyd/IP_Festo_Fetch.ai path: /MESA_Models/main.py
from mesa.visualization.modules import CanvasGrid
from mesa.visualization.ModularVisualization import ModularServer
from mesa.visualization.modules import ChartModule
from mesa.batchrunner import BatchRunner
from agentPortrayal import agent... | code_fim | hard | {
"lang": "python",
"repo": "jamesilloyd/IP_Festo_Fetch.ai",
"path": "/MESA_Models/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
server = ModularServer(MASArchitecture,
[grid,
chart,
chart2,
chart3,
chart4,
averageMessagesSentChart,
... | code_fim | hard | {
"lang": "python",
"repo": "jamesilloyd/IP_Festo_Fetch.ai",
"path": "/MESA_Models/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> 'Average successful satisfaction score':metrics.averageSuccessfulSatisfactionScore,
'Average satisfaction score':metrics.averageSatisfactionScore,
'% Cheap orders with cheap machines':metrics.cheapO... | code_fim | hard | {
"lang": "python",
"repo": "jamesilloyd/IP_Festo_Fetch.ai",
"path": "/MESA_Models/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: EuKudryashova/interrupt path: /test.py
import mock
def exc():
print 'here should raise'
<|fim_suffix|>
def test_recursion():
global exc
exc = mock.Mock(side_effect = [StandardError, StandardError, mock.DEFAULT])
recursion()
test_recursion()<|fim_middle|>def recursion():
try... | code_fim | medium | {
"lang": "python",
"repo": "EuKudryashova/interrupt",
"path": "/test.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_recursion():
global exc
exc = mock.Mock(side_effect = [StandardError, StandardError, mock.DEFAULT])
recursion()
test_recursion()<|fim_prefix|># repo: EuKudryashova/interrupt path: /test.py
import mock
def exc():
print 'here should raise'
<|fim_middle|>def recursion():
try... | code_fim | medium | {
"lang": "python",
"repo": "EuKudryashova/interrupt",
"path": "/test.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_recursion():
global exc
exc = mock.Mock(side_effect = [StandardError, StandardError, mock.DEFAULT])
recursion()
test_recursion()<|fim_prefix|># repo: EuKudryashova/interrupt path: /test.py
import mock
def exc():
print 'here should raise'
def recursion():
<|fim_middle|> try:... | code_fim | medium | {
"lang": "python",
"repo": "EuKudryashova/interrupt",
"path": "/test.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
]
operations = [
migrations.CreateModel(
name='Customer',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('created', models.DateTimeField(verbose_name=... | code_fim | hard | {
"lang": "python",
"repo": "SamuelDauzon/Improllow-up",
"path": "/customers/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
dependencies = [
]
operations = [
migrations.CreateModel(
name='Customer',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('created', models.DateTimeField(verbose_name... | code_fim | hard | {
"lang": "python",
"repo": "SamuelDauzon/Improllow-up",
"path": "/customers/migrations/0001_initial.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: SamuelDauzon/Improllow-up path: /customers/migrations/0001_initial.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
<|fim_suffix|> operations = [
migrations.CreateModel(
name='Customer',
fields=[
... | code_fim | hard | {
"lang": "python",
"repo": "SamuelDauzon/Improllow-up",
"path": "/customers/migrations/0001_initial.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Barsom/my-first-blog path: /home/migrations/0011_auto_20170512_2248.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-05-12 20:48
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
<|fim_suffix|> dependencies... | code_fim | medium | {
"lang": "python",
"repo": "Barsom/my-first-blog",
"path": "/home/migrations/0011_auto_20170512_2248.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.AlterField(
model_name='classroom',
name='subject5teacher',
field=models.ForeignKey(default=None, on_delete=django.db.models.deletion.CASCADE, related_name='+', to='home.Teacher', verbose_name='Chemistry'),
),
]<|f... | code_fim | medium | {
"lang": "python",
"repo": "Barsom/my-first-blog",
"path": "/home/migrations/0011_auto_20170512_2248.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> yolo.getObject(frame, labelWant="", drawBox=True, bold=1, textsize=0.6, bcolor=(0,0,255), tcolor=(255,255,255))
print ("Object counts:", yolo.objCounts)
cv2.imshow("Frame", imutils.resize(frame, width=850))
if(video_out!=""):
out.write(frame)
k = cv2.wa... | code_fim | hard | {
"lang": "python",
"repo": "cflin-cjcu/mytools",
"path": "/yolo/tutorial_pydarknet.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cflin-cjcu/mytools path: /yolo/tutorial_pydarknet.py
from yoloPydarknet import pydarknetYOLO
import cv2
import imutils
import time
yolo = pydarknetYOLO(obdata="../darknet/cfg/coco.data", weights="yolov3.weights",
cfg="../darknet/cfg/yolov3.cfg")
video_out = "yolo_output.avi"
<|fim_suffix|>... | code_fim | hard | {
"lang": "python",
"repo": "cflin-cjcu/mytools",
"path": "/yolo/tutorial_pydarknet.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NeuralEnsemble/python-neo path: /neo/test/iotest/test_exampleio.py
"""
Tests of neo.io.exampleio
"""
import pathlib
import unittest
from neo.io.exampleio import ExampleIO # , HAVE_SCIPY
from neo.test.iotest.common_io_test import BaseTestIO
from neo.test.iotest.tools import get_test_file_full_p... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/python-neo",
"path": "/neo/test/iotest/test_exampleio.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_read_block(self):
r = ExampleIO(filename=None)
bl = r.read_block(lazy=True)
#assert len(bl.list_units) == 3
#assert len(bl.channel_indexes) == 1 + 1 # signals grouped + units grouped
def test_read_segment_with_time_slice(self):
r = ExampleIO(filen... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/python-neo",
"path": "/neo/test/iotest/test_exampleio.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> assert spikes_full.size > spikes_slice.size
assert np.all(spikes_slice >= t_start)
assert np.all(spikes_slice <= t_stop)
assert spikes_slice.t_start == t_start
assert spikes_slice.t_stop == t_stop
assert event_full.size > event_slice.size
assert np.... | code_fim | hard | {
"lang": "python",
"repo": "NeuralEnsemble/python-neo",
"path": "/neo/test/iotest/test_exampleio.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: iddoberger/python3_exceptions path: /exceptions_tree.py
from graphviz import Digraph
dot = Digraph()
dot.edge("BaseException", "SystemExit")
dot.edge("BaseException", "KeyboardInterrupt")
dot.edge("BaseException", "GeneratorExit")
dot.edge("BaseException", "Exception")
dot.edge("Exception", "St... | code_fim | hard | {
"lang": "python",
"repo": "iddoberger/python3_exceptions",
"path": "/exceptions_tree.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>e("ConnectionError", "ConnectionAbortedError")
dot.edge("ConnectionError", "ConnectionRefusedError")
dot.edge("ConnectionError", "ConnectionResetError")
dot.edge("OSError", "FileExistsError")
dot.edge("OSError", "FileNotFoundError")
dot.edge("OSError", "InterruptedError")
dot.edge("OSError", "IsADirectory... | code_fim | hard | {
"lang": "python",
"repo": "iddoberger/python3_exceptions",
"path": "/exceptions_tree.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> input_items = ['orgoccupancycount', 'occupancycount'],
factor = 2,
output_items = ['adjusted_orgoccupancycount', 'adjusted_occupancycount']
)
df = fn.execute_local_test(db=db, db_schema=db_schema, generate_days=1,to_csv=True)
print(df)<|fim_prefix|># repo: prasanthgelli/analytics... | code_fim | hard | {
"lang": "python",
"repo": "prasanthgelli/analytics_service",
"path": "/scripts/local_test_of_function.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: prasanthgelli/analytics_service path: /scripts/local_test_of_function.py
import datetime as dt
import json
import pandas as pd
import numpy as np
from sqlalchemy import Column, Integer, String, Float, DateTime, Boolean, func
from iotfunctions.base import BaseTransformer
from iotfunctions.metadata... | code_fim | hard | {
"lang": "python",
"repo": "prasanthgelli/analytics_service",
"path": "/scripts/local_test_of_function.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>from custom.multiplybyfactor import MultiplyByFactor
fn = MultiplyByFactor(
input_items = ['orgoccupancycount', 'occupancycount'],
factor = 2,
output_items = ['adjusted_orgoccupancycount', 'adjusted_occupancycount']
)
df = fn.execute_local_test(db=db, db_schema=db_schema, generat... | code_fim | medium | {
"lang": "python",
"repo": "prasanthgelli/analytics_service",
"path": "/scripts/local_test_of_function.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jakecerwin/I3 path: /parse_stream.py
from kafka import KafkaConsumer
import csv
users = set()
# returns string of title given a ConsumerRecord
def parse_cr(cr):
binary = cr.value
string = binary.decode('utf-8')
# [time, user id, GET request]
return string.split(',')
# returns ... | code_fim | hard | {
"lang": "python",
"repo": "jakecerwin/I3",
"path": "/parse_stream.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> else:
popularity[title] = 1
dates.add(date)
return popularity
def gather_titles():
consumer = KafkaConsumer(
'movielog',
bootstrap_servers=['localhost:9092'],
auto_offset_reset='earliest',
group_id='jcerwin-new',
e... | code_fim | hard | {
"lang": "python",
"repo": "jakecerwin/I3",
"path": "/parse_stream.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PulakMajumdar81/Daily-DSA-prep path: /reversePolishNotation.py
class Solution:
def evalRPN(self, tokens: List[str]) -> int:
def operation(op1,op2,op):
<|fim_suffix|> stack = []
for char in tokens:
if char in ["+", "-", "*", "/"]:
op2 = ... | code_fim | hard | {
"lang": "python",
"repo": "PulakMajumdar81/Daily-DSA-prep",
"path": "/reversePolishNotation.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> stack = []
for char in tokens:
if char in ["+", "-", "*", "/"]:
op2 = stack.pop()
op1 = stack.pop()
res = operation(op1,op2,char)
stack.append(int(res))
else:
stack.append(int(ch... | code_fim | hard | {
"lang": "python",
"repo": "PulakMajumdar81/Daily-DSA-prep",
"path": "/reversePolishNotation.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if (not numpy.isnan(result[1])) and result[1] < 10000:
rmean = result[1]
else:
rmean = 0.0
if (not numpy.isnan(result[2])) and result[1] < 10000:
rmedian = result[2]
else:
rmedian = 0.0
tc_means.append(rmean)
tc_medians.append(rmedian)
ofi... | code_fim | hard | {
"lang": "python",
"repo": "Ada520/Topic-Distance-and-Coherence",
"path": "/coh_wn_random.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>tc = WordNetEvaluator()
tc_means = []
tc_medians = []
words_list = []
ofilemean = open(dname + "/"+tcmethod+"_mean_rand_"+str(word_count)+".txt", "w")
ofilemedian = open(dname + "/"+tcmethod+"_median_rand_"+str(word_count)+".txt", "w")
if ic:
if dname == "reuters_LDA":
src_ic = wn.ic(reuter... | code_fim | hard | {
"lang": "python",
"repo": "Ada520/Topic-Distance-and-Coherence",
"path": "/coh_wn_random.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JayjeetAtGithub/spack path: /var/spack/repos/builtin/packages/r-dt/package.py
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.package im... | code_fim | medium | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/r-dt/package.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> Data objects in R can be rendered as HTML tables using the JavaScript
library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables'
library has been included in this R package. The package name 'DT' is an
abbreviation of 'DataTables'."""
cran = "DT"
version("0.23", s... | code_fim | medium | {
"lang": "python",
"repo": "JayjeetAtGithub/spack",
"path": "/var/spack/repos/builtin/packages/r-dt/package.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Azure/azure-cli path: /src/azure-cli/azure/cli/command_modules/vm/aaz/latest/sig/gallery_application/version/_show.py
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/vm/aaz/latest/sig/gallery_application/version/_show.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def url(self):
return self.client.format_url(
"/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Compute/galleries/{galleryName}/applications/{galleryApplicationName}/versions/{galleryApplicationVersionName}",
... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/vm/aaz/latest/sig/gallery_application/version/_show.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> cls._schema_on_200 = AAZObjectType()
_schema_on_200 = cls._schema_on_200
_schema_on_200.id = AAZStrType(
flags={"read_only": True},
)
_schema_on_200.location = AAZStrType(
flags={"required": True},
)
... | code_fim | hard | {
"lang": "python",
"repo": "Azure/azure-cli",
"path": "/src/azure-cli/azure/cli/command_modules/vm/aaz/latest/sig/gallery_application/version/_show.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> moduleRef = f"{bRep}{org}/{repo}{relative}"
if moduleRef in self.seen:
return True
if org is None or repo is None:
relativeBare = relative.removeprefix("/")
repoLocation = relativeBare
mLocations.append(relativeBare)
(com... | code_fim | hard | {
"lang": "python",
"repo": "annotation/text-fabric",
"path": "/tf/advanced/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: annotation/text-fabric path: /tf/advanced/data.py
from ..core.helpers import itemize
from ..core.files import backendRep, expandDir, prefixSlash, normpath
from .helpers import splitModRef
from .repo import checkoutRepo
from .links import provenanceLink
# GET DATA FOR MAIN SOURCE AND ALL MODULES... | code_fim | hard | {
"lang": "python",
"repo": "annotation/text-fabric",
"path": "/tf/advanced/data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> seen.add(moduleRef)
if isBase:
app.repoLocation = repoLocation
info = {}
for item in (
("doi", None),
("corpus", f"{org}/{repo}{relative}"),
):
(key, default) = item
info[key] = (
getattr(a... | code_fim | hard | {
"lang": "python",
"repo": "annotation/text-fabric",
"path": "/tf/advanced/data.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> diffusion_flux,
field,
prefactor,
):
# define kernel support for kernel
diffusion_flux_pyst_mpi_kernel_2d.kernel_support = (
gen_diffusion_flux_pyst_mpi_kernel_2d.kernel_support
)
# define variable for use later
ghost_size = g... | code_fim | hard | {
"lang": "python",
"repo": "fankiat/sopht-mpi",
"path": "/sopht_mpi/numeric/eulerian_grid_ops/stencil_ops_2d/diffusion_flux_mpi_2d.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fankiat/sopht-mpi path: /sopht_mpi/numeric/eulerian_grid_ops/stencil_ops_2d/diffusion_flux_mpi_2d.py
"""MPI-supported kernels for computing diffusion flux in 2D."""
from sopht.numeric.eulerian_grid_ops.stencil_ops_2d import (
gen_diffusion_flux_pyst_kernel_2d,
gen_set_fixed_val_pyst_kerne... | code_fim | hard | {
"lang": "python",
"repo": "fankiat/sopht-mpi",
"path": "/sopht_mpi/numeric/eulerian_grid_ops/stencil_ops_2d/diffusion_flux_mpi_2d.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.options=forcebalance.parser.gen_opts_defaults.copy()
self.options.update({
'root': os.getcwd() + '/test/files',
'penalty_additive': 0.01,
'jobtype': 'NEWTON',
'forcefield': ['cc-pvdz-overlap-original.gbs']})
os.ch... | code_fim | hard | {
"lang": "python",
"repo": "yudongqiu/forcebalance",
"path": "/src/tests/test_objective.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yudongqiu/forcebalance path: /src/tests/test_objective.py
from __future__ import absolute_import
from builtins import str
from builtins import object
import unittest
import sys, os, re
import forcebalance
import abc
import numpy
from __init__ import ForceBalanceTestCase
class TestImplemented(For... | code_fim | hard | {
"lang": "python",
"repo": "yudongqiu/forcebalance",
"path": "/src/tests/test_objective.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = [
url(r'^admin/', admin.site.urls),
url(r'^doc_u/', schema_view),
url(r'^', include('o.urls', )),
url(r'^api/', include('restapi.urls', namespace='res')),
]<|fim_prefix|># repo: cucy/2017 path: /django rest api 示例6 高级封装 view set/zrddjangol/zrddjangol/urls.py
from django.con... | code_fim | medium | {
"lang": "python",
"repo": "cucy/2017",
"path": "/django rest api 示例6 高级封装 view set/zrddjangol/zrddjangol/urls.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cucy/2017 path: /django rest api 示例6 高级封装 view set/zrddjangol/zrddjangol/urls.py
from django.conf.urls import url, include
from django.contrib import admin
<|fim_suffix|>urlpatterns = [
url(r'^admin/', admin.site.urls),
url(r'^doc_u/', schema_view),
url(r'^', include('o.urls', )),
... | code_fim | medium | {
"lang": "python",
"repo": "cucy/2017",
"path": "/django rest api 示例6 高级封装 view set/zrddjangol/zrddjangol/urls.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> training_set_inputs = array(
[
[normalized_set['input1'][0], normalized_set['input2'][0], normalized_set['input3'][0]],
[normalized_set['input1'][1], normalized_set['input2'][1], normalized_set['input3'][1]],
[normalized_set['input1'][2], normalized_set['inp... | code_fim | hard | {
"lang": "python",
"repo": "careywadawi/ANN-AI",
"path": "/neural_network.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: careywadawi/ANN-AI path: /neural_network.py
from numpy import exp, array, dot
from read import normalized
class NeuralNetwork():
def __init__(self, layer1, layer2):
self.layer1 = layer1
self.layer2 = layer2
def __sigmoid(self, x):
return 1 / (1 + exp(-x))
d... | code_fim | hard | {
"lang": "python",
"repo": "careywadawi/ANN-AI",
"path": "/neural_network.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> layer2 = array([[0.5, 0.1]]).T
neural_network = NeuralNetwork(layer1, layer2)
neural_network.print_weights()
training_set_inputs = array(
[
[normalized_set['input1'][0], normalized_set['input2'][0], normalized_set['input3'][0]],
[normalized_set['input1'][... | code_fim | hard | {
"lang": "python",
"repo": "careywadawi/ANN-AI",
"path": "/neural_network.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def createHypenEmbed(word):
'''
Handle outlier language with hyphen
'''
word_whole = re.sub('-', '', word)
if word_whole in word_dict:
return [word_dict[word_whole]]
else:
# [TODO] should the hyphenated word be
# split into two words or kept as an
... | code_fim | hard | {
"lang": "python",
"repo": "catli/seinfeld-attention",
"path": "/seq2seq/process_data.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: catli/seinfeld-attention path: /seq2seq/process_data.py
'''
Create a dictionary of fasttext embedding, stored locally
fasttext import. This will hopefully make it easier to load
and train data.
This will also be used to store the
Steps to clean scripts (codify):
1) ... | code_fim | hard | {
"lang": "python",
"repo": "catli/seinfeld-attention",
"path": "/seq2seq/process_data.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def hello_http(request):
request_args = request.args
#'words', 'lang-from', 'lang-to', 'by', 'reverse'
if request_args and 'words' in request_args:
words = json.loads(request_args['words'])
if isinstance(words, list) and len(words) > 0:
target = request_args.get('... | code_fim | hard | {
"lang": "python",
"repo": "littealeaf28/flashcard-abc",
"path": "/python/src/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> #'words', 'lang-from', 'lang-to', 'by', 'reverse'
if request_args and 'words' in request_args:
words = json.loads(request_args['words'])
if isinstance(words, list) and len(words) > 0:
target = request_args.get('target', 'es')
by_str = request_args.get('by',... | code_fim | medium | {
"lang": "python",
"repo": "littealeaf28/flashcard-abc",
"path": "/python/src/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: littealeaf28/flashcard-abc path: /python/src/main.py
from flask import escape
import pandas as pd
import json
import requests
with open('result.csv', newline='') as f:
df = pd.read_csv(f)
def get_level_diff(word, only_common=False):
if only_common:
word_df = df[(df['word']==word... | code_fim | medium | {
"lang": "python",
"repo": "littealeaf28/flashcard-abc",
"path": "/python/src/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> operations = [
migrations.CreateModel(
name='N_lostandfound',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('date', models.DateTimeField(auto_now_add=True)),
(... | code_fim | hard | {
"lang": "python",
"repo": "onthir/warhawks",
"path": "/notification/migrations/0003_n_lostandfound.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: onthir/warhawks path: /notification/migrations/0003_n_lostandfound.py
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-06-07 12:30
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
<|fim_s... | code_fim | hard | {
"lang": "python",
"repo": "onthir/warhawks",
"path": "/notification/migrations/0003_n_lostandfound.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: monntauk/proyecto path: /Entrega3/MiProyecto/core/forms.py
from django import forms
from django.forms import ModelForm
from .models import Noticia
<|fim_suffix|> class Meta:
model = Noticia
fields = ['idNoticia','resumen','titulo','categoria']<|fim_middle|>class NoticiaForm(Mo... | code_fim | easy | {
"lang": "python",
"repo": "monntauk/proyecto",
"path": "/Entrega3/MiProyecto/core/forms.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> model = Noticia
fields = ['idNoticia','resumen','titulo','categoria']<|fim_prefix|># repo: monntauk/proyecto path: /Entrega3/MiProyecto/core/forms.py
from django import forms
from django.forms import ModelForm
from .models import Noticia
class NoticiaForm(ModelForm):
<|fim_middle|> cl... | code_fim | easy | {
"lang": "python",
"repo": "monntauk/proyecto",
"path": "/Entrega3/MiProyecto/core/forms.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def productExceptSelf(self, nums: List[int]) -> List[int]:
output = []
prod = 1
# First generate the products to the left of the current element
for num in nums:
output.append(prod)
prod *= num
prod = 1
# Now, generate and multip... | code_fim | medium | {
"lang": "python",
"repo": "abhijitdey/coding-practice",
"path": "/facebook/arrays_and_strings/14_product_of_array_except_self.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: abhijitdey/coding-practice path: /facebook/arrays_and_strings/14_product_of_array_except_self.py
from typing import List
"""
1. Generate an array containing the products of all elements to the left of current element
2. Similarly, start from the last element and generate an array containing the ... | code_fim | medium | {
"lang": "python",
"repo": "abhijitdey/coding-practice",
"path": "/facebook/arrays_and_strings/14_product_of_array_except_self.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> prod = 1
# Now, generate and multiply the product to the right of current element
for k in range(len(nums) - 1, -1, -1):
output[k] = output[k] * prod
prod *= nums[k]
return output<|fim_prefix|># repo: abhijitdey/coding-practice path: /facebook/arra... | code_fim | hard | {
"lang": "python",
"repo": "abhijitdey/coding-practice",
"path": "/facebook/arrays_and_strings/14_product_of_array_except_self.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vanderson-henrique/trybe-exercises path: /COMPUTER-SCIENCE/BLOCO_39/39_3/conteudo/exercicio1.py
'''
Exercício 1: Estenda a classe Stack , que escrevemos durante as explicações do
conteúdo, adicionando uma nova função chamada min_value() que irá retornar o
menor valor inteiro presente na pilha.
''... | code_fim | hard | {
"lang": "python",
"repo": "vanderson-henrique/trybe-exercises",
"path": "/COMPUTER-SCIENCE/BLOCO_39/39_3/conteudo/exercicio1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
content_stack = Other_Operations_Stack()
content_stack.push(1)
content_stack.push(-2)
content_stack.push(3)
print(content_stack.min_value()) # saída: -2<|fim_prefix|># repo: vanderson-henrique/trybe-exercises path: /COMPUTER-SCIENCE/BLOCO_39/39_3/conteudo/exercicio1.py
'''
Exercício 1: Estenda a classe... | code_fim | medium | {
"lang": "python",
"repo": "vanderson-henrique/trybe-exercises",
"path": "/COMPUTER-SCIENCE/BLOCO_39/39_3/conteudo/exercicio1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: JoOkuma/torch-em path: /experiments/mito-em/prepare_train_data.py
import os
import z5py
from shutil import copytree, copyfile
ROOT = '/g/kreshuk/pape/Work/data/mito_em/data'
SCRATCH = '/scratch/pape/mito_em/data'
def create_file(out_path, ref_path):
os.makedirs(out_path, exist_ok=True)
... | code_fim | hard | {
"lang": "python",
"repo": "JoOkuma/torch-em",
"path": "/experiments/mito-em/prepare_train_data.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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