text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: stefan-falk/tensor2tensor path: /tensor2tensor/bin/test.py
import os
import sys
from tensor2tensor.bin import t2t_trainer
def problem_args(problem_name):
<|fim_suffix|> return args
def main():
sys.argv += problem_args('librispeech_clean_small')
# sys.argv += problem_args('common_voice... | code_fim | hard | {
"lang": "python",
"repo": "stefan-falk/tensor2tensor",
"path": "/tensor2tensor/bin/test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>net = resnet18(num_classes = 10, norm_layer=norm_layer).to(device)
net = torch.nn.DataParallel(net)
print('Resuming from %s...' %(args.resume))
ckpt = torch.load('%s/best.pth' %(args.resume))
net.load_state_dict(ckpt['net'])
print("Starting Test Error: %.3f" % ckpt['err_cls'])
criterion = nn.CrossEntrop... | code_fim | hard | {
"lang": "python",
"repo": "eyalperry88/lethean",
"path": "/adversarial_lethean.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>criterion = nn.CrossEntropyLoss().to(device)
optimizer = optim.SGD(net.parameters(), lr=args.lr)
trset, trloader = prepare_train_data(args)
teset, teloader = prepare_test_data(args)
print("Lethean Attack")
for i in range(args.epochs):
idx = random.randint(0, len(trset) - 1)
img, lbl = trset[idx]... | code_fim | hard | {
"lang": "python",
"repo": "eyalperry88/lethean",
"path": "/adversarial_lethean.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: eyalperry88/lethean path: /adversarial_lethean.py
from __future__ import print_function
import argparse
import torch
import torch.nn as nn
import torch.optim as optim
import random
from utils.misc import *
from utils.adapt_helpers import *
from utils.rotation import rotate_batch, rotate_single_w... | code_fim | hard | {
"lang": "python",
"repo": "eyalperry88/lethean",
"path": "/adversarial_lethean.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mehulsbhatt/openag path: /models/old/records.py
import cgi
from google.appengine.api import users
from google.appengine.ext import webapp
from google.appengine.ext.webapp.util import run_wsgi_app
from google.appengine.ext import db
from models.nutrient import *
class SoilRecord(db.Model):
year=... | code_fim | medium | {
"lang": "python",
"repo": "mehulsbhatt/openag",
"path": "/models/old/records.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.year=year
class CropRecord(db.Model):
year=db.DateProperty(auto_now_add=True)
crops=db.ListProperty(db.Key)
notes=db.StringProperty()
@property
def plot(self):
Plot.gql("Where croprecord=:1",self.key())
def create(self, year):
self.year=year
def addCrop(self, crop):
... | code_fim | medium | {
"lang": "python",
"repo": "mehulsbhatt/openag",
"path": "/models/old/records.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> @property
def plot(self):
Plot.gql("Where croprecord=:1",self.key())
def create(self, year):
self.year=year
def addCrop(self, crop):
if addByKey(crop, self.crops):
self.put()<|fim_prefix|># repo: mehulsbhatt/openag path: /models/old/records.py
import cgi
from google.appengine... | code_fim | hard | {
"lang": "python",
"repo": "mehulsbhatt/openag",
"path": "/models/old/records.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_addition_input_value(self):
self.assertRaises(TypeError, add, 'ank', 6)
if __name__ == '__main__':
main()<|fim_prefix|># repo: ankitbharti1994/Python path: /UnitTestInPython/UnitTest/test_volume_cuboid.py
"""
Created on Fri Jan 07 20:53:58 2022
@author: Ankit Bharti
"""
from... | code_fim | hard | {
"lang": "python",
"repo": "ankitbharti1994/Python",
"path": "/UnitTestInPython/UnitTest/test_volume_cuboid.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> #print 'IP=' + IP
latency = ''
try:
# Use Scamper to determine the latency of the Requesting Client identified by the IP
scamperCommand = "scamper -c 'ping -c 1' -i "+IP
# Get the output of the system command
output = commands.get... | code_fim | medium | {
"lang": "python",
"repo": "soumyaramesh/Computer-Networking",
"path": "/Projects/CDN/ActiveMeasurement.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: soumyaramesh/Computer-Networking path: /Projects/CDN/ActiveMeasurement.py
# This file is used to run a program to perform Active measuremnts
import commands
import SocketServer
import sys
#Class to handle Socket request
class Handler(SocketServer.BaseRequestHandler):
<|fim_suffix|>
port =... | code_fim | hard | {
"lang": "python",
"repo": "soumyaramesh/Computer-Networking",
"path": "/Projects/CDN/ActiveMeasurement.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def main(argv):
port = int(argv[1])
addr = ('', port)
# Start an active measurement system which listenes to a given port
server = SocketServer.TCPServer(addr, Handler);
print 'Active Measurement Server Listening at ' + str(port) + "..."
server.serve_forever()
if __name__ ==... | code_fim | medium | {
"lang": "python",
"repo": "soumyaramesh/Computer-Networking",
"path": "/Projects/CDN/ActiveMeasurement.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mathworks/sato path: /utils.py
import os
from os.path import join
import json
import pandas as pd
import time
import numpy as np
import torch
def str2bool(v):
# convert string to boolean type for argparser input
if isinstance(v, bool):
return v
if v.lower() in ('yes', 'true',... | code_fim | hard | {
"lang": "python",
"repo": "mathworks/sato",
"path": "/utils.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> return '_'.join(["{}-{}".format(k, dic[k]) for k in sorted(dic)])
def name2dic(s):
return {x.split('-')[0]:x.split('-')[1] for x in s.split('_')}
def get_valid_types(TYPENAME):
with open(join(os.environ['BASEPATH'], 'configs', 'types.json'), 'r') as typefile:
valid_types = json.l... | code_fim | hard | {
"lang": "python",
"repo": "mathworks/sato",
"path": "/utils.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NishpaVanapalli/python path: /oop1.py
##class Human:
## pass
##hb1-HB("Sudhir")
##hb2=HB("Sreenu")
<|fim_suffix|> def __init__(self,name,rollno):
self.name=name
self.rollno=rollno
std1=Student("Siva",123)<|fim_middle|>
class Student:
| code_fim | easy | {
"lang": "python",
"repo": "NishpaVanapalli/python",
"path": "/oop1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.name=name
self.rollno=rollno
std1=Student("Siva",123)<|fim_prefix|># repo: NishpaVanapalli/python path: /oop1.py
##class Human:
## pass
##hb1-HB("Sudhir")
##hb2=HB("Sreenu")
<|fim_middle|>
class Student:
def __init__(self,name,rollno):
| code_fim | easy | {
"lang": "python",
"repo": "NishpaVanapalli/python",
"path": "/oop1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Mcszorongat/PyTrnng path: /mf_iterTools.py
from itertools import count, islice
from math import sqrt
def is_prime(x):
if x<2:
return False
for i in range(2, int(sqrt(x)) + 1):
if x%i == 0:
return False
return True
def primes(x):
return islice((p for p... | code_fim | hard | {
"lang": "python",
"repo": "Mcszorongat/PyTrnng",
"path": "/mf_iterTools.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(any([True, True]))
print(any([True, False]))
print(any([False, False])) # is there a TRUE
print(all([True, True])) # are all of them TRUE
print(all([True, False]))
print(all([False, False]))
print("Is there a prime between 1328 and 1361:", any(is_prime(x) for x in range(1328, 1361)))
monday = ... | code_fim | medium | {
"lang": "python",
"repo": "Mcszorongat/PyTrnng",
"path": "/mf_iterTools.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Fufuhu/python_basic_leaning path: /ch7_practiceB.py
class Circle():
def __init__(self, radius, color="white"):
<|fim_suffix|>c1 = Circle(10, "black")
print("半径:{}, 色: {}".format(c1.radius, c1.color))<|fim_middle|> self.radius = radius
self.color = color
| code_fim | medium | {
"lang": "python",
"repo": "Fufuhu/python_basic_leaning",
"path": "/ch7_practiceB.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>c1 = Circle(10, "black")
print("半径:{}, 色: {}".format(c1.radius, c1.color))<|fim_prefix|># repo: Fufuhu/python_basic_leaning path: /ch7_practiceB.py
class Circle():
def __init__(self, radius, color="white"):
<|fim_middle|> self.radius = radius
self.color = color
| code_fim | medium | {
"lang": "python",
"repo": "Fufuhu/python_basic_leaning",
"path": "/ch7_practiceB.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>update_config(config_default, config)
config = config_default<|fim_prefix|># repo: ukaraoz/snakemake-rules path: /snakemake_rules/rules/centipede/centipede.settings.smk
# -*- snakemake -*-
#
# CENTIPEDE: Transcription factor footprinting and binding site prediction
# install.packages("CENTIPEDE", repos="... | code_fim | medium | {
"lang": "python",
"repo": "ukaraoz/snakemake-rules",
"path": "/snakemake_rules/rules/centipede/centipede.settings.smk",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ukaraoz/snakemake-rules path: /snakemake_rules/rules/centipede/centipede.settings.smk
# -*- snakemake -*-
#
# CENTIPEDE: Transcription factor footprinting and binding site prediction
# install.packages("CENTIPEDE", repos="http://R-Forge.R-project.org")
#
# http://centipede.uchicago.edu/
#
incl... | code_fim | medium | {
"lang": "python",
"repo": "ukaraoz/snakemake-rules",
"path": "/snakemake_rules/rules/centipede/centipede.settings.smk",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: HectorTa1989/802.15.4-wireless-MAC-level-performance path: /code/TestModel.py
import subprocess
import logging
import time
import argparse
import threading
import os
import matplotlib.pyplot as plt
import numpy as np
import argparse
def runWeka(wekapath, modelpath, datapath):
os.chdir(wekapa... | code_fim | hard | {
"lang": "python",
"repo": "HectorTa1989/802.15.4-wireless-MAC-level-performance",
"path": "/code/TestModel.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if k<6:
k=k+1
continue
else:
if row=='':
continue
instance, actual, predicted, error=row.split()
matrix.append([int(instance), float(actual), float(predicted)])
matrix=np.array(matrix)
matr... | code_fim | medium | {
"lang": "python",
"repo": "HectorTa1989/802.15.4-wireless-MAC-level-performance",
"path": "/code/TestModel.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: datacake/python-datacake-http-example path: /main.py
import requests
if __name__ == "__main__":
# individual datacake webhook url
# Change this to the webhook url of your datacake device/product
datacake_url = "https://api.datacake.co/integrations/api/ae6dd531-4cf6-4966-b5c9-6c43939... | code_fim | medium | {
"lang": "python",
"repo": "datacake/python-datacake-http-example",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # create api call
r = requests.post(datacake_url, json={
"number_of_persons_a": number_of_persons_a,
"number_of_persons_b": number_of_persons_b,
"additional_payload": additional_payload,
"some_data": some_data,
"a_boolean": a_boolean,
"serial": seria... | code_fim | medium | {
"lang": "python",
"repo": "datacake/python-datacake-http-example",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># In[38]:
for i in range(len(y_pred)):
print(y_pred[i])
# In[3]:
# run SVR for the AXP-...DD stocks
axp = pd.DataFrame(columns=aapl.columns)
# In[3]:
#stocks = ['AAPL','AXP','BA','CAT','CSCO','CVX','DIS','DD','GS']
stocks = ['MCD']
# In[4]:
# read indicators 09-18
ADXR = pd.read_csv('data/dj... | code_fim | hard | {
"lang": "python",
"repo": "kakaxi2/A-Hybrid-Approach-for-Generating-Investor-Views-in-Black-Litterman-Model",
"path": "/code/return_forecast.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># In[72]:
cov
# In[73]:
cov.to_csv('cov.csv')
# In[10]:
# store return prediction
result = pd.DataFrame(columns=stocks)
# In[21]:
# indicators forecast
ADXR_f = pd.read_csv('data/tesingadxr740.csv')
ATR_f = pd.read_csv('data/tesingatr740.csv')
SMA_f = pd.read_csv('data/sma_forecast.csv')
Hurst_f... | code_fim | hard | {
"lang": "python",
"repo": "kakaxi2/A-Hybrid-Approach-for-Generating-Investor-Views-in-Black-Litterman-Model",
"path": "/code/return_forecast.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kakaxi2/A-Hybrid-Approach-for-Generating-Investor-Views-in-Black-Litterman-Model path: /code/return_forecast.py
# coding: utf-8
# In[1]:
import numpy as np
import pandas as pd
from sklearn.svm import SVR
# In[2]:
from sklearn.preprocessing import StandardScaler
# In[3]:
#import matplotl... | code_fim | hard | {
"lang": "python",
"repo": "kakaxi2/A-Hybrid-Approach-for-Generating-Investor-Views-in-Black-Litterman-Model",
"path": "/code/return_forecast.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class LocationNotSet(Exception):
pass<|fim_prefix|># repo: cdunklau/seleniumclean path: /seleniumclean.py
def clear_firefox_driver_session(firefox_driver):
<|fim_middle|> firefox_driver.delete_all_cookies()
# Note this only works if the browser is set to a location.
firefox_driver.execute... | code_fim | hard | {
"lang": "python",
"repo": "cdunklau/seleniumclean",
"path": "/seleniumclean.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cdunklau/seleniumclean path: /seleniumclean.py
def clear_firefox_driver_session(firefox_driver):
<|fim_suffix|>
class LocationNotSet(Exception):
pass<|fim_middle|> firefox_driver.delete_all_cookies()
# Note this only works if the browser is set to a location.
firefox_driver.execute... | code_fim | hard | {
"lang": "python",
"repo": "cdunklau/seleniumclean",
"path": "/seleniumclean.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>class LocationNotSet(Exception):
pass<|fim_prefix|># repo: cdunklau/seleniumclean path: /seleniumclean.py
def clear_firefox_driver_session(firefox_driver):
<|fim_middle|> firefox_driver.delete_all_cookies()
# Note this only works if the browser is set to a location.
firefox_driver.execute_... | code_fim | hard | {
"lang": "python",
"repo": "cdunklau/seleniumclean",
"path": "/seleniumclean.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ade25/ade25.assetmanager path: /ade25/assetmanager/browser/repository.py
# -*- coding: utf-8 -*-
"""Module providing views for asset storage folder"""
from Products.Five.browser import BrowserView
from plone import api
from plone.app.contenttypes.interfaces import IImage
class AssetRepositoryVie... | code_fim | medium | {
"lang": "python",
"repo": "ade25/ade25.assetmanager",
"path": "/ade25/assetmanager/browser/repository.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def item_index(self, uid):
return len(self.contained_items(uid))
def preview_image(self, uid):
images = self.contained_items(uid)
preview = None
if len(images):
first_item = images[0].getObject()
if IImage.providedBy(first_item):
... | code_fim | hard | {
"lang": "python",
"repo": "ade25/ade25.assetmanager",
"path": "/ade25/assetmanager/browser/repository.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> images = self.contained_items(uid)
preview = None
if len(images):
first_item = images[0].getObject()
if IImage.providedBy(first_item):
preview = first_item
return preview<|fim_prefix|># repo: ade25/ade25.assetmanager path: /ade25/ass... | code_fim | hard | {
"lang": "python",
"repo": "ade25/ade25.assetmanager",
"path": "/ade25/assetmanager/browser/repository.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>print "Jeffrey K Skilling exercised stock:", enron_data["SKILLING JEFFREY K"]["exercised_stock_options"]
print "money for Lay:", enron_data["LAY KENNETH L"]["total_payments"], ", Skilling:", enron_data["SKILLING JEFFREY K"]["total_payments"], " & Fastow:", enron_data["FASTOW ANDREW S"]["total_payments"]
... | code_fim | hard | {
"lang": "python",
"repo": "Lundgren/ud120-intro-ml",
"path": "/datasets_questions/explore_enron_data.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lundgren/ud120-intro-ml path: /datasets_questions/explore_enron_data.py
#!/usr/bin/python
"""
Starter code for exploring the Enron dataset (emails + finances);
loads up the dataset (pickled dict of dicts).
The dataset has the form:
enron_data["LASTNAME FIRSTNAME MIDDLEINITIAL"]... | code_fim | hard | {
"lang": "python",
"repo": "Lundgren/ud120-intro-ml",
"path": "/datasets_questions/explore_enron_data.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> bs_year, bs_month, bs_day = _ad_to_bs(year, month, day)
formatted_date = "{}-{:02}-{:02}".format(bs_year, bs_month, bs_day)
return formatted_date<|fim_prefix|># repo: e911/pyBSDate path: /pyBSDate/BSDate.py
__author__ = 'sushil'
from .utilities import decompose_date
from .DateConverter import... | code_fim | hard | {
"lang": "python",
"repo": "e911/pyBSDate",
"path": "/pyBSDate/BSDate.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>.
'''
x, y = 2.4, 6.4
perimeter = (x*2)+(y*2)
area = x*y
print("Perimeter is "+str(perimeter) + ", Area is " + str(area))<|fim_prefix|># repo: TankFairy/python_fundamentals path: /01_07_area_perimeter.py
'''
Write the necessary code to display the area and perimet<|fim_middle|>er of a rectangle that ha... | code_fim | medium | {
"lang": "python",
"repo": "TankFairy/python_fundamentals",
"path": "/01_07_area_perimeter.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: TankFairy/python_fundamentals path: /01_07_area_perimeter.py
'''
Write the necessary code to display the area and perimeter of a rectangle that has a width of 2.4 and a height of 6.4<|fim_suffix|>nt("Perimeter is "+str(perimeter) + ", Area is " + str(area))<|fim_middle|>.
'''
x, y = 2.4, 6.4
pe... | code_fim | medium | {
"lang": "python",
"repo": "TankFairy/python_fundamentals",
"path": "/01_07_area_perimeter.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DRMPN/PythonCode path: /CodeWars/6kyu/multi_tap_keypad.py
def presses(phrase):
keyboard = [
'1',
'ABC2',
'DEF3',
'GHI4',
'JKL5',
<|fim_suffix|>= 0
for lttr in phrase.upper():
for key in keyboard:
try:
i = key.i... | code_fim | hard | {
"lang": "python",
"repo": "DRMPN/PythonCode",
"path": "/CodeWars/6kyu/multi_tap_keypad.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> i += 1
amount += i
except ValueError:
pass
return amount<|fim_prefix|># repo: DRMPN/PythonCode path: /CodeWars/6kyu/multi_tap_keypad.py
def presses(phrase):
keyboard = [
'1',
'ABC2',
'DEF3',
'GHI4',
... | code_fim | hard | {
"lang": "python",
"repo": "DRMPN/PythonCode",
"path": "/CodeWars/6kyu/multi_tap_keypad.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: zlodiak/lessons path: /python/EXAMPLES/projects/parse_html/5_forum_new/quantity.py
import shelve
def quantity_posts():
<|fim_suffix|>if __name__ == "__main__":
print('begin')
quantity_posts()
print('end')<|fim_middle|> try:
data = shelve.open('data')
except Exc... | code_fim | hard | {
"lang": "python",
"repo": "zlodiak/lessons",
"path": "/python/EXAMPLES/projects/parse_html/5_forum_new/quantity.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == "__main__":
print('begin')
quantity_posts()
print('end')<|fim_prefix|># repo: zlodiak/lessons path: /python/EXAMPLES/projects/parse_html/5_forum_new/quantity.py
import shelve
def quantity_posts():
<|fim_middle|> try:
data = shelve.open('data')
except E... | code_fim | hard | {
"lang": "python",
"repo": "zlodiak/lessons",
"path": "/python/EXAMPLES/projects/parse_html/5_forum_new/quantity.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: mohsenmalmir/NoEmuRL path: /noemurl/app.py
# =============================================================================
# Created By : Mohsen Malmir
# Created Date: Fri Nov 09 8:10 PM EST 2018
# Purpose : this file implements the gui handling to interact with emulators
# =================... | code_fim | hard | {
"lang": "python",
"repo": "mohsenmalmir/NoEmuRL",
"path": "/noemurl/app.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
This function scans all the open windows and returns a handle to the first known
and supported emulator-game pair.
Args:
None
Returns:
"""
# get a list of all open windows
windows = CGWindowListCopyWindowInfo(kCGWindowListOptionOnScreenOnly&kCGWindowLis... | code_fim | medium | {
"lang": "python",
"repo": "mohsenmalmir/NoEmuRL",
"path": "/noemurl/app.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while i > 0:
print(i,end='')
i -= 1
print()<|fim_prefix|># repo: chris-r-harwell/HackerRankPython path: /triangleQuest2-3.py
#!/bin/env python3
"""
https://www.hackerrank.com/challenges/triangle-quest-2
INPUT:
integer N
where 0 < N < 10
OUTPUT:
print palindromic triangle of s... | code_fim | medium | {
"lang": "python",
"repo": "chris-r-harwell/HackerRankPython",
"path": "/triangleQuest2-3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: chris-r-harwell/HackerRankPython path: /triangleQuest2-3.py
#!/bin/env python3
"""
https://www.hackerrank.com/challenges/triangle-quest-2
INPUT:
integer N
where 0 < N < 10
<|fim_suffix|> e.g.for N=5
1
121
12321
1234321
123454321
"""
for i in range(1, int(input()) + 1):
j = 1
while j ... | code_fim | easy | {
"lang": "python",
"repo": "chris-r-harwell/HackerRankPython",
"path": "/triangleQuest2-3.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nukevoid/dgus_hass_connection path: /dgus/sensor.py
import logging
from .const import (
DOMAIN,
CONF_SCREENS
)
from typing import Any, Callable, Dict, Optional
from homeassistant.helpers.entity import Entity
from homeassistant.helpers.typing import (
ConfigType,
DiscoveryInfoType,... | code_fim | hard | {
"lang": "python",
"repo": "nukevoid/dgus_hass_connection",
"path": "/dgus/sensor.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> def state_listener(self, entity, old_state, new_state):
settings = self._state_track_settings[entity]
if settings['type'] == 'int':
StateConverters.send_int(
new_state, settings, self._protocol.protocol)
elif settings['type'] == 'map':
St... | code_fim | hard | {
"lang": "python",
"repo": "nukevoid/dgus_hass_connection",
"path": "/dgus/sensor.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def seam_carve(image, mode, mask):
if mode == 'horizontal shrink':
return cut(image, mask)
elif mode == 'vertical shrink':
transposed_image, transposed_mask, transposed_seam_mask = cut(
np.transpose(image, (1, 0, 2)), mask.T if mask is not None else None
)
... | code_fim | hard | {
"lang": "python",
"repo": "asntr/DAS",
"path": "/CV/hw3/seam_carve.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: asntr/DAS path: /CV/hw3/seam_carve.py
import numpy as np
def get_mask(mask):
r = mask[:, :, 0]
g = mask[:, :, 1]
return r // (r.max() or 1) * -1 + g // (g.max() or 1)
def calculate_brightness(image):
weights = np.array([0.299, 0.587, 0.114])
brightness_matrix = (image*weig... | code_fim | hard | {
"lang": "python",
"repo": "asntr/DAS",
"path": "/CV/hw3/seam_carve.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>e.register(Profile)
# Register your models here.<|fim_prefix|># repo: ohyoungjooung2/jango_blog path: /users/admin.py
from django.contrib import admin
from .models i<|fim_middle|>mport Profile
from django.contrib.admin.templatetags.admin_list import admin_actions
admin.sit | code_fim | medium | {
"lang": "python",
"repo": "ohyoungjooung2/jango_blog",
"path": "/users/admin.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ohyoungjooung2/jango_blog path: /users/admin.py
from django.contrib import admin
from .models import Profile
from django.contrib.admin.template<|fim_suffix|>e.register(Profile)
# Register your models here.<|fim_middle|>tags.admin_list import admin_actions
admin.sit | code_fim | easy | {
"lang": "python",
"repo": "ohyoungjooung2/jango_blog",
"path": "/users/admin.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> csvwriter = csv.writer(csv_file, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
csvwriter.writerow(['reflective', 'transitive'])
for trial_id in trial_sets.top_ids:
wrist_oxygen, fingertip_oxygen, transitive_oxygen = dl.load_all_oxygen(trial_id)
for oF, oT in zip(f... | code_fim | hard | {
"lang": "python",
"repo": "jipson7/PPGDataAnalysis",
"path": "/examine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jipson7/PPGDataAnalysis path: /examine.py
import data
import numpy as np
import matplotlib.pyplot as plt
import xgboost as xgb
import pandas as pd
import csv
from matplotlib2tikz import save as tikz_save
import trial_sets
def print_stats(trial_id, dl):
wrist_device, _, true_device = dl.lo... | code_fim | hard | {
"lang": "python",
"repo": "jipson7/PPGDataAnalysis",
"path": "/examine.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
trial_ids = trial_sets.top_ids
dl = data.DataLoader(window_size=100, threshold=2.0, algo_name='enhanced', features='comprehensive')
for trial_id in trial_ids:
print("Trial {}".format(trial_id))
training_ids = trial_ids.copy()
training_ids.remove(trial_id)
vi... | code_fim | hard | {
"lang": "python",
"repo": "jipson7/PPGDataAnalysis",
"path": "/examine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def gamewon(self,board):
global grid,winner
val=0
for row in range(0,3):
if((grid[row][0]==grid[row][1]==grid[row][2]) and grid[row][0] is not None):
logging.info("ROW no. {0} wins".format(row))
winner=grid[row... | code_fim | hard | {
"lang": "python",
"repo": "nirvik/pygame-bomberman-streaming",
"path": "/game.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> grid[col][row]=piece
def clickboard(self,board):
global grid,XO,OX
d=TTTError(1,"SPACE OCCUPIED ALREADY")
(mouseX,mouseY)=pygame.mouse.get_pos()
(self.col,self.row)=self.boardpos(mouseY,mouseX)
try:
if (grid[self.row][self.col]=='X' or grid[self.row][sel... | code_fim | hard | {
"lang": "python",
"repo": "nirvik/pygame-bomberman-streaming",
"path": "/game.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nirvik/pygame-bomberman-streaming path: /game.py
import pygame
from pygame.locals import *
import threading
from load import *
import time
import socket as sck
import sys
port=8767
grid=[[None,None,None],[None,None,None],[None,None,None]]
XO='X'
OX='X'
winner=None
coordinate1=600
coordinate2=20... | code_fim | hard | {
"lang": "python",
"repo": "nirvik/pygame-bomberman-streaming",
"path": "/game.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> class_bag = self.calc_cost(Y_out, Y)
corr = class_bag['problem_cor']+class_bag['test_cor']+class_bag['treatment_cor']
tot = class_bag['total']
loss_list += [loss.item()]
seq_length += [Y.shape[0]]
if (batch_... | code_fim | hard | {
"lang": "python",
"repo": "shahakshay11/medical-entity-extraction-nlp",
"path": "/code/dnc_code/tasks/ner_task_bio.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shahakshay11/medical-entity-extraction-nlp path: /code/dnc_code/tasks/ner_task_bio.py
f the file: " + file + " ************\n")
for x in file_lines:
print("------------------------------------------------------------")
print("File Lines No: " + str(counter))
... | code_fim | hard | {
"lang": "python",
"repo": "shahakshay11/medical-entity-extraction-nlp",
"path": "/code/dnc_code/tasks/ner_task_bio.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: shahakshay11/medical-entity-extraction-nlp path: /code/dnc_code/tasks/ner_task_bio.py
lf.labelDict['i-test'] = 3 # Test - Inside
self.labelDict['b-treatment'] = 4 # Treatment - Beginning
self.labelDict['i-treatment'] = 5 # Treatment - Inside
self.labelDict['o'] ... | code_fim | hard | {
"lang": "python",
"repo": "shahakshay11/medical-entity-extraction-nlp",
"path": "/code/dnc_code/tasks/ner_task_bio.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return np.zeros(self.get_n_dimensions(), dtype=np.uint32)
def iterate_indices(self, indices):
""" iterate given indices [i1, i2, ...] by one.
For easier iteration. The convention here is arbitrary, but its the
order the arrays would be traversed in a series of nested ... | code_fim | hard | {
"lang": "python",
"repo": "wisecg/pygama",
"path": "/pygama/dsp/dsp_optimize.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> """ iterate given indices [i1, i2, ...] by one.
For easier iteration. The convention here is arbitrary, but its the
order the arrays would be traversed in a series of nested for loops in
the order appearin in dims (first dimension is first for loop, etc):
Return F... | code_fim | hard | {
"lang": "python",
"repo": "wisecg/pygama",
"path": "/pygama/dsp/dsp_optimize.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> a_plot.addSimple(plot.PlotCell( calc.sma((sd.Vs,sd.dates),20 )))
arr_obv = calc.obv((sd.Cs,sd.Vs,sd.dates) )
a_plot.addSimple(plot.PlotCell( arr_obv))
a_plot.addSimple(plot.PlotCell( calc.sma(arr_obv, 20),overlay=True))
a_plot.addSimple(plo... | code_fim | hard | {
"lang": "python",
"repo": "rcshadman/workspace_python",
"path": "/port_loader.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rcshadman/workspace_python path: /port_loader.py
import stock as stk
import portfolio as portf
import plot
import sys
import cmd
import os
import decision as des
class CLI(cmd.Cmd):
def __init__(self):
cmd.Cmd.__init__(self)
self.prompt = '$> '
self.stk_data_c... | code_fim | hard | {
"lang": "python",
"repo": "rcshadman/workspace_python",
"path": "/port_loader.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>## ------------- Simple Gradients ------------- ##
print("# ------------- Simple Gradients ------------- #")
# out.backward() is equivalent to doing out.backward(torch.Tensor([1.0]))
out.backward()
print("dout/dx \n", x.grad) # gradient of z = 3(x+2)^2, dout/dx = 3/2(x+2), x=1
## ------------- Crazy Grad... | code_fim | medium | {
"lang": "python",
"repo": "youngguncho/pytorch-studies",
"path": "/pytorch_basic/main_autograd.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: youngguncho/pytorch-studies path: /pytorch_basic/main_autograd.py
from __future__ import print_function # Should comes first than torch
import torch
from torch.autograd import Variable
##
## Autograd.Variable is the central class of the package. It wraps a Tensor, and supports nearly all of oper... | code_fim | medium | {
"lang": "python",
"repo": "youngguncho/pytorch-studies",
"path": "/pytorch_basic/main_autograd.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 520In7/as-tool path: /as_perf_logcat_count/logcat_time.py
# -*- coding: utf-8 -*-
# !/usr/bin/python
import re
import sys
import xlwt
import os
'''
python logcat_time.py config_file logcat_file
'''
config_file = sys.argv[1]
logcat_file = sys.argv[2]
turns_time = 0
turn_compelete_flag = 0
def ... | code_fim | hard | {
"lang": "python",
"repo": "520In7/as-tool",
"path": "/as_perf_logcat_count/logcat_time.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def caculate_tag_distance(str1, str2):
f = open(logcat_file)
finish_time = ''
start_time = ''
turn_times = 0
for line in f:
turn_compelete_flag = False
if str1 in line:
turn_compelete_flag = False
start_time = line.split()[1]
if str2 in l... | code_fim | hard | {
"lang": "python",
"repo": "520In7/as-tool",
"path": "/as_perf_logcat_count/logcat_time.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: johannakarras/Deep-Neural-Networks-for-Black-Hole-Imaging path: /RML/data_term_functions.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Jun 14 20:35:10 2020
@author: Johanna
"""
import numpy as np
############################################################################... | code_fim | hard | {
"lang": "python",
"repo": "johannakarras/Deep-Neural-Networks-for-Black-Hole-Imaging",
"path": "/RML/data_term_functions.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>###############################################################################
# Log Closure Amplitude Functions
###############################################################################
def compute_lgcamp(X, Amatrices):
''' Compute log closure amplitude of image vector X '''
a1 = np.ab... | code_fim | hard | {
"lang": "python",
"repo": "johannakarras/Deep-Neural-Networks-for-Black-Hole-Imaging",
"path": "/RML/data_term_functions.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: milospjanic/FibonacciDictionary path: /FibonacciDictionary.py
Dict={0:0, 1:1}
def fibo(n):
if n not in Dict:
val=fibo(n-1)+fibo(n-2)
Dict[n]=val
return Dict[n]
n=int(input("Enter the value of n:"))
print("Fibonacci(", n,")= ", fibo(n))
<|fim_suffix|># check if the number ... | code_fim | medium | {
"lang": "python",
"repo": "milospjanic/FibonacciDictionary",
"path": "/FibonacciDictionary.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># check if the number of terms is valid
if nterms <= 0:
print("Plese enter a positive integer")
else:
print("Fibonacci sequence:")
for i in range(nterms):```
print(fibo(i), end=" , ")<|fim_prefix|># repo: milospjanic/FibonacciDictionary path: /FibonacciDictionary.py
Dict={0:0, 1:1}
def fi... | code_fim | medium | {
"lang": "python",
"repo": "milospjanic/FibonacciDictionary",
"path": "/FibonacciDictionary.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>class THROW:
# Raise an exception of given type with given arguments
# Example:
# THROW(
# 'org/python/exceptions/AttributeError',
# ['Ljava/lang/String;', JavaOpcodes.LDC_W("Invalid attribute")],
# )
def __init__(self, exception_class, *exception_args):
... | code_fim | hard | {
"lang": "python",
"repo": "dibyadas/voc",
"path": "/voc/python/types/java.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: davidmeunier79/neuropype_ephy path: /neuropype_ephy/interfaces/mne/Inverse_solution.py
# -*- coding: utf-8 -*-
"""
Created on Mon May 2 17:24:00 2016
@author: pasca
"""
# -*- coding: utf-8 -*-
import os.path as op
from nipype.utils.filemanip import split_filename as split_f
from nipype.inter... | code_fim | hard | {
"lang": "python",
"repo": "davidmeunier79/neuropype_ephy",
"path": "/neuropype_ephy/interfaces/mne/Inverse_solution.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> events_id = traits.Dict(None, desc='the id of all events to consider.', mandatory=False)
t_min = traits.Float(None, desc='start time before event', mandatory=False)
t_max = traits.Float(None, desc='end time after event', mandatory=False)
class NoiseCovarianceConnOutputSpec(TraitedSpec):
... | code_fim | hard | {
"lang": "python",
"repo": "davidmeunier79/neuropype_ephy",
"path": "/neuropype_ephy/interfaces/mne/Inverse_solution.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: varunbelgaonkar/Beginner-Python-projects path: /calculator.py
from tkinter import *
root = Tk()
root.title("Calculator")
e = Entry(root, width = 50, borderwidth = 5)
e.grid(row = 0, column = 0, columnspan = 4, padx = 10, pady = 20)
def button_click(number):
digit = e.get()
e.delete... | code_fim | hard | {
"lang": "python",
"repo": "varunbelgaonkar/Beginner-Python-projects",
"path": "/calculator.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def clear():
e.delete(0, END)
#creating buttons
button_1 = Button(root, text = "1", height = 5, width = 10,command = lambda:button_click(1))
button_2 = Button(root, text = "2", height = 5, width = 10, command = lambda:button_click(2))
button_3 = Button(root, text = "3", height = 5, width = 10, ... | code_fim | hard | {
"lang": "python",
"repo": "varunbelgaonkar/Beginner-Python-projects",
"path": "/calculator.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: haakensonb/advent_2017 path: /day_5/twisty_maze.py
# maze = [0, 3, 0, 1, -3]
with open('./day_5/input.txt') as f:
maze = f.readlines()
f.close
maze = [int(line.strip()) for line in maze]
# I think I will just expand on the original functions
# from now on rather than separating part one from... | code_fim | medium | {
"lang": "python",
"repo": "haakensonb/advent_2017",
"path": "/day_5/twisty_maze.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> end = len(maze) - 1
step_counter = 0
offset = 0
while True:
cur_index = offset
offset = offset + maze[cur_index]
if maze[cur_index] >= 3:
maze[cur_index] = maze[cur_index] - 1
else:
maze[cur_index] = maze[cur_index] + 1
step_... | code_fim | medium | {
"lang": "python",
"repo": "haakensonb/advent_2017",
"path": "/day_5/twisty_maze.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: llyuer/Tigress_protection path: /symbolic_expressions/sample20-virt-random-opcodes-false.py
#!/usr/bin/env python2
## -*- coding: utf-8 -*-
import sys
def sx(bits, value):
sign_bit = 1 << (bits - 1)
return (value & (sign_bit - 1)) - (value & sign_bit)
SymVar_0 = int(sys.argv[1])
ref_26... | code_fim | hard | {
"lang": "python",
"repo": "llyuer/Tigress_protection",
"path": "/symbolic_expressions/sample20-virt-random-opcodes-false.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> ref_62587 # MOV operation
ref_72083 = ref_72007 # MOV operation
ref_72095 = ref_71084 # MOV operation
ref_72097 = (ref_72083 >> ((ref_72095 & 0xFF) & 0x3F)) # SHR operation
ref_72198 = ref_72097 # MOV operation
ref_72210 = ref_69493 # MOV operation
ref_72212 = (ref_72210 | ref_72198) # OR operation
ref_7... | code_fim | hard | {
"lang": "python",
"repo": "llyuer/Tigress_protection",
"path": "/symbolic_expressions/sample20-virt-random-opcodes-false.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: clintreyes/num_model path: /ch3/integrate_sine.py
from trapezoidal import trapezoidal
from midpoint import midpoint
from math import pi, sin
<|fim_suffix|> I_t = trapezoidal(f, a, b, n)
I_m = midpoint()
return None
a = 0.0; b = pi
f = lambda x: sin(x)<|fim_middle|>def integrate_sine(... | code_fim | easy | {
"lang": "python",
"repo": "clintreyes/num_model",
"path": "/ch3/integrate_sine.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> I_t = trapezoidal(f, a, b, n)
I_m = midpoint()
return None
a = 0.0; b = pi
f = lambda x: sin(x)<|fim_prefix|># repo: clintreyes/num_model path: /ch3/integrate_sine.py
from trapezoidal import trapezoidal
from midpoint import midpoint
from math import pi, sin
<|fim_middle|>def integrate_sine(... | code_fim | easy | {
"lang": "python",
"repo": "clintreyes/num_model",
"path": "/ch3/integrate_sine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>a = 0.0; b = pi
f = lambda x: sin(x)<|fim_prefix|># repo: clintreyes/num_model path: /ch3/integrate_sine.py
from trapezoidal import trapezoidal
from midpoint import midpoint
from math import pi, sin
<|fim_middle|>def integrate_sine(f, a, b, n = 2):
I_t = trapezoidal(f, a, b, n)
I_m = midpoint()... | code_fim | medium | {
"lang": "python",
"repo": "clintreyes/num_model",
"path": "/ch3/integrate_sine.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Pvredev/Sentiment-Analysis-for-Trading path: /stop_words.py
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
#Print Stop words
stop_words = set(stopwords.words("english"))
print(stop_words)
example_text = "This is general sentence to just clarify if stop words ar... | code_fim | medium | {
"lang": "python",
"repo": "Pvredev/Sentiment-Analysis-for-Trading",
"path": "/stop_words.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>words = word_tokenize(example_text)
filtered_sentence = []
for w in words:
for w not in stop_words:
filtered_sentence.append(w)
#print filtered sentences
print(filtered_sentence)
#print in a line
filtered_sentence1 = [w for w in words if not w in stop_words]
#print filtered se... | code_fim | hard | {
"lang": "python",
"repo": "Pvredev/Sentiment-Analysis-for-Trading",
"path": "/stop_words.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> #if divisible by 400, definitely a leap year
if date % 400 == 0: return True
#if divisible by 100 (and not 400), not a leap year
elif date % 100 == 0: return False
#divisible by 4 and not by 100? leap year
elif date % 4 == 0: return True
#otherwise not a leap year
else : return False<|fim_prefi... | code_fim | easy | {
"lang": "python",
"repo": "itsolutionscorp/AutoStyle-Clustering",
"path": "/all_data/exercism_data/python/leap/1a0bb11019da44c5815327d64bbc04a6.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: itsolutionscorp/AutoStyle-Clustering path: /all_data/exercism_data/python/leap/1a0bb11019da44c5815327d64bbc04a6.py
#returns true if given date is a leap year, false otherwise
<|fim_suffix|> #if divisible by 400, definitely a leap year
if date % 400 == 0: return True
#if divisible by 100 (and ... | code_fim | easy | {
"lang": "python",
"repo": "itsolutionscorp/AutoStyle-Clustering",
"path": "/all_data/exercism_data/python/leap/1a0bb11019da44c5815327d64bbc04a6.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def fix_line_endings(fname, eol=b'\n'):
"""Change all line endings to ``eol``.
"""
lines = [chomp(line) for line in open(fname, 'rb').readlines()]
with open(fname, 'wb') as fp:
for line in lines:
fp.write(line + eol)
def copy(ctx, source, dest, force=False):
"""Co... | code_fim | hard | {
"lang": "python",
"repo": "datakortet/dk-tasklib",
"path": "/dktasklib/concat.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: datakortet/dk-tasklib path: /dktasklib/concat.py
# -*- coding: utf-8 -*-
from __future__ import print_function
import os
import sys
from dkfileutils.path import Path
def line_endings(fname):
"""Return all line endings in the file.
"""
_endings = {line[-2:] for line in open(fname, '... | code_fim | hard | {
"lang": "python",
"repo": "datakortet/dk-tasklib",
"path": "/dktasklib/concat.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Buradaki Try Except istisna blokları datalar kaydedilirken varsa oluşan hataları ayıklayarak bizlere mesaj olarak döner
try:
session.add(ım_db)
session.commit()
except:
session.rollback()
raise
finally:
... | code_fim | hard | {
"lang": "python",
"repo": "yusufhandogan/IMDB-TOP-250-DATA-CRAWLING-PROJECT-WITH-PYTHON-SCRAPY",
"path": "/IMDB/IMDB/pipelines.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> ım_db.IMDB_RATING = item["IMDB_RATING"]
# Buradaki Try Except istisna blokları datalar kaydedilirken varsa oluşan hataları ayıklayarak bizlere mesaj olarak döner
try:
session.add(ım_db)
session.commit()
except:
session.rollbac... | code_fim | hard | {
"lang": "python",
"repo": "yusufhandogan/IMDB-TOP-250-DATA-CRAWLING-PROJECT-WITH-PYTHON-SCRAPY",
"path": "/IMDB/IMDB/pipelines.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yusufhandogan/IMDB-TOP-250-DATA-CRAWLING-PROJECT-WITH-PYTHON-SCRAPY path: /IMDB/IMDB/pipelines.py
from sqlalchemy.orm import sessionmaker
from IMDB.spiders.models import IMDB_DATABASE, db_connect, create_table
class ScrapySpiderPipeline(object):
# Bu Fonksiyon Veritabanı bağlantısını v... | code_fim | hard | {
"lang": "python",
"repo": "yusufhandogan/IMDB-TOP-250-DATA-CRAWLING-PROJECT-WITH-PYTHON-SCRAPY",
"path": "/IMDB/IMDB/pipelines.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>#the angle of rotation around the axis
float32 angle
================================================================================
MSG: geometry_msgs/Point32
# This contains the position of a point in free space(with 32 bits of precision).
# It is recommeded to use Point wherever possible instead of P... | code_fim | hard | {
"lang": "python",
"repo": "brennand/ics_bioloid_fuerte",
"path": "/KDL/arm_navigation_msgs/src/arm_navigation_msgs/srv/_GetPlanningScene.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brennand/ics_bioloid_fuerte path: /KDL/arm_navigation_msgs/src/arm_navigation_msgs/srv/_GetPlanningScene.py
diff.allowed_collision_matrix.entries:
length = len(val1.enabled)
buff.write(_struct_I.pack(length))
pattern = '<%sB'%length
buff.write(val1.enabled.tostring... | code_fim | hard | {
"lang": "python",
"repo": "brennand/ics_bioloid_fuerte",
"path": "/KDL/arm_navigation_msgs/src/arm_navigation_msgs/srv/_GetPlanningScene.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>out))-deleted_length_after]
# real_result=str(stdout.decode("utf-8")).replace("Microsoft Windows [Version 10.0.10586]\r\n(c) 2015 Microsoft Corporation. All rights reserved.\r\n\r\n","")
# real_result=real_result.replace(">More?","")
# print(real_result)
# return real_resul... | code_fim | hard | {
"lang": "python",
"repo": "AlBannaTechno/AbtTerminal",
"path": "/Depricated_.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: AlBannaTechno/AbtTerminal path: /Depricated_.py
# ""
# "deb_char_cont_x9875"
# # def watch_edit_text(self): # execute when test edited
# # logging.info("TQ : " + str(len(self.te_sql_cmd.toPlainText())))
# # logging.info("TE : " + str(len(self.cmd_last_text)))
# # logging.info("LEN : ... | code_fim | hard | {
"lang": "python",
"repo": "AlBannaTechno/AbtTerminal",
"path": "/Depricated_.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def check(data):
global ss
global s
for line in data:
s += int(line)
if ss.get(s, False):
return s
ss[s] = True
return None
v = check(data)
print('after first pass:', s)
while v is None:
v = check(data)
print('first duplicate:', v)<|fim_prefix|>#... | code_fim | easy | {
"lang": "python",
"repo": "jtrinklein/advent-of-code",
"path": "/2018/01-main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
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