text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_suffix|> migrations.AlterField(
model_name='salary',
name='id',
field=models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'),
),
migrations.AlterField(
model_name='staff',
name='id',
... | code_fim | hard | {
"lang": "python",
"repo": "TestuUser123/smart-english",
"path": "/settings/migrations/0004_auto_20211110_0936.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gongyuchenshidage/color_preview path: /resource_rc.py
d\x11\xb9\x4d\xf4\x12\xde\x4f\x88\xe0\xc4\x83\
\x03\xa2\x00\x00\x00\x01\x62\x4b\x47\x44\x2b\x24\xb9\xe4\x08\x00\
\x00\x00\x07\x74\x49\x4d\x45\x07\xe4\x09\x04\x02\x0c\x2c\x5e\x9a\
\xf1\x93\x00\x00\x00\x89\x49\x44\x41\x54\x18\xd3\x55\xcf\xd9\x12... | code_fim | hard | {
"lang": "python",
"repo": "gongyuchenshidage/color_preview",
"path": "/resource_rc.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>d\
\xc3\xbd\xb0\x4a\xd3\xf4\x1f\xcb\x5e\x55\xf1\x50\x42\x63\x0c\x41\
\x10\x8c\x32\x17\xc5\x5a\x87\x73\x0e\x1b\x4d\x52\x39\x75\x06\x7d\
\x78\x9b\xf6\xd6\x06\x3b\xff\xb8\x89\x35\x16\x51\x21\x2a\x4d\x50\
\x89\x27\xa8\x86\xc2\x7a\xf5\x34\x13\xfd\x9c\x1b\x31\x34\xb2\xce\
\xa3\xcc\x0f\xfb\x10\x5a\x6b\xb1\xc6\x6... | code_fim | hard | {
"lang": "python",
"repo": "gongyuchenshidage/color_preview",
"path": "/resource_rc.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gongyuchenshidage/color_preview path: /resource_rc.py
\x37\x39\x32\x37\x39\
\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\
\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\
\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\x32\x37\x39\
\x32\x37\x39\x32\x37\x3... | code_fim | hard | {
"lang": "python",
"repo": "gongyuchenshidage/color_preview",
"path": "/resource_rc.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def test_column_strength(self): #随意修改测试
b = 1200
h = 1200
l0 = 5
a = 90
a_ = 90
Ec = 3.45E4 #MPa
As = 12316
As_ = 12316
n = 10
M = 2800 #kN
N = 14000
r = column_strength.solve_stress(b,h,l0,a,a_,Ec,As,As_,n... | code_fim | hard | {
"lang": "python",
"repo": "warmwaver/calla",
"path": "/test/verification/TB.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: warmwaver/calla path: /test/verification/TB.py
import unittest
import calla.test
TestCase = calla.test.TestCase
from math import pi
from calla.TB.RC_strength import *
class test(TestCase):
def test1(self):
"""
标准验证：铁路混凝土结构设计原理（容许应力计算法）.ppt 例1
"""
b = 200
... | code_fim | hard | {
"lang": "python",
"repo": "warmwaver/calla",
"path": "/test/verification/TB.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> b = 1200
h = 1200
l0 = 5
a = 90
a_ = 90
Ec = 3.45E4 #MPa
As = 12316
As_ = 12316
n = 10
M = 2800 #kN
N = 14000
r = column_strength.solve_stress(b,h,l0,a,a_,Ec,As,As_,n,M,N,0)
print('σc,σs,σs\'\n',r)
if ... | code_fim | hard | {
"lang": "python",
"repo": "warmwaver/calla",
"path": "/test/verification/TB.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # true if rec2 is below rec1
c = rec2[3] <= rec1[1]
# true if rec2 is above rec1
d = rec1[3] <= rec2[1]
return not (a or b or c or d)<|fim_prefix|># repo: jschnab/leetcode path: /overlapping_rectangles.py
# leetcode 836
# determine if two rectangles overlap
# input is two lists [x1,... | code_fim | hard | {
"lang": "python",
"repo": "jschnab/leetcode",
"path": "/overlapping_rectangles.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jschnab/leetcode path: /overlapping_rectangles.py
# leetcode 836
# determine if two rectangles overlap
# input is two lists [x1,y1,x2,y2] coordinates
# where x1,y1 are coordinates of bottom left corner
# and x2,y2 are coordinates of top right corner
<|fim_suffix|> """Determine if rectangles o... | code_fim | medium | {
"lang": "python",
"repo": "jschnab/leetcode",
"path": "/overlapping_rectangles.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> network, data, labels, verbose=True
):
'''A Function that tests
a neural network'''
return network.evaluate(
x=data,
y=labels,
verbose=verbose
)<|fim_prefix|># repo: YosriGFX/holbertonschool-machine_learning path: /supervised_learning/0x06-keras/12-test.py
#!/u... | code_fim | easy | {
"lang": "python",
"repo": "YosriGFX/holbertonschool-machine_learning",
"path": "/supervised_learning/0x06-keras/12-test.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YosriGFX/holbertonschool-machine_learning path: /supervised_learning/0x06-keras/12-test.py
#!/usr/bin/env python3
'''Testing File'''
import tensorflow.keras as K
<|fim_suffix|> network, data, labels, verbose=True
):
'''A Function that tests
a neural network'''
return network.evalu... | code_fim | easy | {
"lang": "python",
"repo": "YosriGFX/holbertonschool-machine_learning",
"path": "/supervised_learning/0x06-keras/12-test.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: rsocnam/sta211 path: /train.py
from os import path
from sklearn.model_selection import StratifiedShuffleSplit
from sklearn.pipeline import Pipeline
from sta211.datasets import load_train_dataset, load_test_dataset, find_best_train_dataset
from sklearn.model_selection import GridSearchCV
from sta2... | code_fim | hard | {
"lang": "python",
"repo": "rsocnam/sta211",
"path": "/train.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># pipes, search_grid = get_svm()
# pipe = Pipeline(pipes)
cv = StratifiedShuffleSplit(test_size=test_size, random_state=0, n_splits=5)
grid = GridSearchCV(pipe, search_grid, cv=cv, n_jobs=n_jobs, return_train_score=True, refit=True, scoring="accuracy")
grid.fit(X, y)
parameters = get_best_hyper_paramete... | code_fim | medium | {
"lang": "python",
"repo": "rsocnam/sta211",
"path": "/train.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sankar77/OOAD_Project2 path: /Project2/Project2/OOAD_Project2_p1c/ZooAnnouncer.py
import ZooAnnouncerInterface
class ZooAnnouncer(ZooAnnouncerInterface):
<|fim_suffix|> print("ZooAnnouncer :" + annoucement)<|fim_middle|> def updateZoo(self,annoucement):
| code_fim | easy | {
"lang": "python",
"repo": "sankar77/OOAD_Project2",
"path": "/Project2/Project2/OOAD_Project2_p1c/ZooAnnouncer.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> print("ZooAnnouncer :" + annoucement)<|fim_prefix|># repo: sankar77/OOAD_Project2 path: /Project2/Project2/OOAD_Project2_p1c/ZooAnnouncer.py
import ZooAnnouncerInterface
<|fim_middle|>class ZooAnnouncer(ZooAnnouncerInterface):
def updateZoo(self,annoucement):
| code_fim | medium | {
"lang": "python",
"repo": "sankar77/OOAD_Project2",
"path": "/Project2/Project2/OOAD_Project2_p1c/ZooAnnouncer.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: momentum-cohort-2019-09/BugBytes path: /config/urls.py
"""config URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
... | code_fim | medium | {
"lang": "python",
"repo": "momentum-cohort-2019-09/BugBytes",
"path": "/config/urls.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Eng-Ahmad-Almohammad/math-series path: /tests/test_series.py
import math_series.series as func
""" Testing for fibonacci function """
def test_fibonacci_zero():
actual = func.fibonacci(0)
expected = 0
assert actual == expected
def test_fibonacci_one():
actual = func.fibonacci... | code_fim | medium | {
"lang": "python",
"repo": "Eng-Ahmad-Almohammad/math-series",
"path": "/tests/test_series.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_non_fibonacci_lucas_negative():
actual = func.non_fibonacci_lucas(-5,2,4)
expected = "Negative values are not allowable"
assert actual == expected
def test_non_fibonacci_lucas_else():
actual = func.non_fibonacci_lucas(3,2,4)
expected = 10
assert actual == expected<... | code_fim | hard | {
"lang": "python",
"repo": "Eng-Ahmad-Almohammad/math-series",
"path": "/tests/test_series.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if self.shuffle:
random.shuffle(self.image_names)
def __len__(self):
return self.n_samples
def __getitem__(self, index):
assert index <= len(self), 'index range error'
img_name = self.image_names[index]
# Read image and normalize its pixels to ... | code_fim | hard | {
"lang": "python",
"repo": "PanPapag/Context-Aware-Crowd-Counting",
"path": "/dataset.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PanPapag/Context-Aware-Crowd-Counting path: /dataset.py
import cv2
import random
import os
import numpy as np
import matplotlib.pyplot as plt
import torch
from torch.utils.data import Dataset
from torchvision import transforms
class ShanghaiTechPartA(Dataset):
def __init__(self, root, shu... | code_fim | hard | {
"lang": "python",
"repo": "PanPapag/Context-Aware-Crowd-Counting",
"path": "/dataset.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>@implementer(IForm)
class Form(Container):
"""A Form."""<|fim_prefix|># repo: BriefyHQ/briefy.plone path: /src/briefy/plone/content/form.py
# -*- coding: utf-8 -*-
"""Form content type."""
from briefy.plone.content.interfaces import IBriefyContent
from plone.dexterity.content import Container
from zo... | code_fim | medium | {
"lang": "python",
"repo": "BriefyHQ/briefy.plone",
"path": "/src/briefy/plone/content/form.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BriefyHQ/briefy.plone path: /src/briefy/plone/content/form.py
# -*- coding: utf-8 -*-
"""Form content type."""
from briefy.plone.content.interfaces import IBriefyContent
from plone.dexterity.content import Container
from zope.interface import implementer
class IForm(IBriefyContent):
<|fim_suffi... | code_fim | easy | {
"lang": "python",
"repo": "BriefyHQ/briefy.plone",
"path": "/src/briefy/plone/content/form.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> color = random.randrange(0,9)
mc.setBlock(x,y,z-1,38,color)
time.sleep(0.01)<|fim_prefix|># repo: wuyoujau/-PYPHOONMINECRAFT20210127 path: /practice 1.py
from mcpi.minecraft import Minecraft
<|fim_middle|>
import random,time
while True:
x,y,z = mc.player.getTilePos()
| code_fim | medium | {
"lang": "python",
"repo": "wuyoujau/-PYPHOONMINECRAFT20210127",
"path": "/practice 1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: wuyoujau/-PYPHOONMINECRAFT20210127 path: /practice 1.py
from mcpi.minecraft import Minecraft
<|fim_suffix|> color = random.randrange(0,9)
mc.setBlock(x,y,z-1,38,color)
time.sleep(0.01)<|fim_middle|>import random,time
while True:
x,y,z = mc.player.getTilePos()
| code_fim | medium | {
"lang": "python",
"repo": "wuyoujau/-PYPHOONMINECRAFT20210127",
"path": "/practice 1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jessierliu/advent-of-code-2020 path: /2/day2.py
"""
Day 2
"""
with open('input.txt', 'r') as f:
lines = f.read()
lines = lines.split('\n')[:-1]
lines = [l.split(' ') for l in lines]
valid = 0
new_valid = 0
for cur_pw in lines:
<|fim_suffix|> occurences = cur_pw[2][rule[0] - 1] + cur_pw... | code_fim | hard | {
"lang": "python",
"repo": "jessierliu/advent-of-code-2020",
"path": "/2/day2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> letter = cur_pw[1].strip(':')
amount = cur_pw[2].count(letter)
rule = cur_pw[0].split('-')
rule = [int(r) for r in rule]
if amount >= rule[0] and amount <= rule[1]:
valid += 1
occurences = cur_pw[2][rule[0] - 1] + cur_pw[2][rule[1] - 1]
if occurences.count(letter) == ... | code_fim | medium | {
"lang": "python",
"repo": "jessierliu/advent-of-code-2020",
"path": "/2/day2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def find_data():
global country_name
global city_name
global general_info
global weather_description
global formatted_general_info
city_name = str(data['name'])
country_name = str(data['sys']['country'])
#weather_description = data['weather']['description']
for key, val... | code_fim | hard | {
"lang": "python",
"repo": "Xetera/ThiccBot.py",
"path": "/musicbot/APIPractice.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Xetera/ThiccBot.py path: /musicbot/APIPractice.py
# name: Ali
# date: 7/12/2016
# description: uses openweathermap.org's api to get weather data about
# the city that is inputted
# unbreakable? = idk
import json
import urllib2
from collections import OrderedDict
from pprint import pprint
api_key... | code_fim | medium | {
"lang": "python",
"repo": "Xetera/ThiccBot.py",
"path": "/musicbot/APIPractice.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> connectapi()
if "name" in data:
find_data()
print "\n%r in %r:\n"% (city_name, country_name)
print """General info:"""
pprint(general_info)
print "\nWeather Description:\n\tidk why it doesn't let me take this data so annoying\n"
else:
print "Some... | code_fim | hard | {
"lang": "python",
"repo": "Xetera/ThiccBot.py",
"path": "/musicbot/APIPractice.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> try:
# subprocess.call(['curl', '-o', path , bug.get_src()])
subprocess.call(['wget', '-t', '1', '-q', '-T', '3', '-O', path , bug.get_src()])
subpr_out = subprocess.check_output(['file', '-b', path]).strip()
except Exception as e :
LOG.debug('Exception captured %s\n\n' % ... | code_fim | hard | {
"lang": "python",
"repo": "keeshen/info-manip",
"path": "/adwords_expt/lib/ad_grabber_util.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keeshen/info-manip path: /adwords_expt/lib/ad_grabber_util.py
hin this current session
# Global location, added when an ad is matched with existing ads in DB
fwtr.write('#UID, Ad-Company, Ad-Filetype, Height, Width, Rel-Location, src\n')
for bug in ads.keys():
height, width = bug.get... | code_fim | hard | {
"lang": "python",
"repo": "keeshen/info-manip",
"path": "/adwords_expt/lib/ad_grabber_util.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: keeshen/info-manip path: /adwords_expt/lib/ad_grabber_util.py
cPickle
import logging
LOG = logging.getLogger("logAdGrabber")
ADREGEX = AdRegEx()
def check_duplicate(fp1, fp2):
"""takes two files, does a diff on them, returns True if same"""
try:
subprocess.check_output(['diff', fp1, fp2... | code_fim | hard | {
"lang": "python",
"repo": "keeshen/info-manip",
"path": "/adwords_expt/lib/ad_grabber_util.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: owenonline/MARL-Behavior-Research-Project path: /experiment results/python/regression_training/correlation_assessment_agent3_2.py
import tensorflow as tf
import csv
from tensorflow.keras import layers
from tensorflow.keras.layers.experimental import preprocessing
import pandas as pd
import numpy ... | code_fim | hard | {
"lang": "python",
"repo": "owenonline/MARL-Behavior-Research-Project",
"path": "/experiment results/python/regression_training/correlation_assessment_agent3_2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>test_features=np.array(test_features)
test_labels=np.array(test_labels)
#make model
#message=tf.keras.Input(shape=(1,100))
#predictor_layer=tf.keras.layers.Dense(6,activation='relu',use_bias=True)(message)
#linear_model=tf.keras.Model(inputs=message,outputs=predictor_layer)
normalizer=preprocessing.Nor... | code_fim | hard | {
"lang": "python",
"repo": "owenonline/MARL-Behavior-Research-Project",
"path": "/experiment results/python/regression_training/correlation_assessment_agent3_2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kireevys/operation_and_article path: /app/logick/catalogs_logick.py
from app.models.tables import Warehouse, Contractor, Articles
class ContractorTools(Contractor):
"""
Работа со справочником КА
"""
@staticmethod
def add_contractor(**kwargs):
ca = Contractor(**kwarg... | code_fim | hard | {
"lang": "python",
"repo": "kireevys/operation_and_article",
"path": "/app/logick/catalogs_logick.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> def delete_warehouse(self, id_ws, name):
ws = super().select_expression(id_ws=id_ws)[0]
for child in super().select_expression(id_higher=id_ws):
for child_child in super().select_expression(id_higher=child.id_ws.value):
child_child.delete_data()
... | code_fim | hard | {
"lang": "python",
"repo": "kireevys/operation_and_article",
"path": "/app/logick/catalogs_logick.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Работа со справочником МХ
"""
def set_new_name(self, id_ws, name):
"""
Переименовывает переданный МХ
"""
ws = super().select_expression(id_ws=id_ws)[0]
ws.name.set_value(name)
ws.update_data()
return True
def delete_warehous... | code_fim | hard | {
"lang": "python",
"repo": "kireevys/operation_and_article",
"path": "/app/logick/catalogs_logick.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
class Auction(models.Model):
title = models.CharField(max_length=20)
current_price = models.DecimalField(max_digits=10, decimal_places=2, default=0,
null=True, blank=True, verbose_name="current bid")
updated_time = models.DateTimeField(auto_now_add=Fals... | code_fim | hard | {
"lang": "python",
"repo": "dawitnida/Pythonidae",
"path": "/YAAS/models.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dawitnida/Pythonidae path: /YAAS/models.py
from django.db import models
from django.contrib.auth.models import User
from django.utils.encoding import smart_unicode
from django.core.validators import MinValueValidator
from django.utils import timezone
from concurrency.fields import IntegerVersionF... | code_fim | hard | {
"lang": "python",
"repo": "dawitnida/Pythonidae",
"path": "/YAAS/models.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>int("Your total score is: " + str(total_crew_none) + ".")
if inp_crew == "one":
inp_crew_one = input("Which die do you want to keep? ")
roll1_crew_one = random.randint(1, 6)
print(roll1_crew_one)
... | code_fim | hard | {
"lang": "python",
"repo": "conuma/Python-Coursework",
"path": "/INST326/onumajuru_catherine_hw3_ex3.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: conuma/Python-Coursework path: /INST326/onumajuru_catherine_hw3_ex3.py
import random
def multi():
scc = [6, 5, 4]
sc = [6, 5]
cc = [5, 4]
crew = [4]
captain = [5]
ship = [6]
n = 0
while n <= 2:
inp = input("Hit enter to roll")
if inp == "":
... | code_fim | hard | {
"lang": "python",
"repo": "conuma/Python-Coursework",
"path": "/INST326/onumajuru_catherine_hw3_ex3.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>df_filtro.groupby('Dia')['Quantidade de pessoas'].mean().plot(x='Dia', y= 'Quantidade de pessoas')<|fim_prefix|># repo: fabiohmoreira/shalenne path: /Ler_dados_Mongo.py
import pandas as pd
from pymongo import MongoClient
import numpy as np
<|fim_middle|>mongo_client = MongoClient('localhost', 27018)
mon... | code_fim | hard | {
"lang": "python",
"repo": "fabiohmoreira/shalenne",
"path": "/Ler_dados_Mongo.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fabiohmoreira/shalenne path: /Ler_dados_Mongo.py
import pandas as pd
from pymongo import MongoClient
import numpy as np
mongo_client = MongoClient('localhost', 27018)
mongo_db = mongo_client['ProjetoIN242']
mongo_collection = mongo_db['contadorpessoas']
<|fim_suffix|>df = pd.DataFrame.from_reco... | code_fim | easy | {
"lang": "python",
"repo": "fabiohmoreira/shalenne",
"path": "/Ler_dados_Mongo.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>df_filtro = df[['Entrada','Dia', 'Quantidade de pessoas']] ##seleção de colunas
df_filtro.groupby('Dia')['Quantidade de pessoas'].mean().plot(x='Dia', y= 'Quantidade de pessoas')<|fim_prefix|># repo: fabiohmoreira/shalenne path: /Ler_dados_Mongo.py
import pandas as pd
from pymongo import MongoClient
im... | code_fim | medium | {
"lang": "python",
"repo": "fabiohmoreira/shalenne",
"path": "/Ler_dados_Mongo.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> r = requests.post("{0}/indicators/".format(self.url), data=data,
verify=self.verify, proxies=self.proxies)
if r.status_code == 200:
log.debug("Indicator uploaded successfully - {}".format(value))
ind = json.loads(r.text)
return ... | code_fim | hard | {
"lang": "python",
"repo": "IntegralDefense/ptauto",
"path": "/lib/critsapi/critsapi.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> dic = corpora.Dictionary(docs)
corp = [dic.doc2bow(text) for text in docs]
tfidf = models.TfidfModel(corp)
corpus_tfidf = tfidf[corp]
model = models.ldamodel.LdaModel(corpus_tfidf, num_topics=num_topics, id2word=dic, update_every=1, passes=100)
print("LDA model")
topics_f... | code_fim | hard | {
"lang": "python",
"repo": "dhanashriOstwal/electionSentimentAnalysis",
"path": "/Python Scripts/postElection.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> num_topics=3
num_top_words=10
clf = decomposition.NMF(n_components=num_topics, random_state=1)
doctopic = clf.fit_transform(dtm)
print num_topics, clf.reconstruction_err_
topic_words = []
for topic in clf.components_:
word_idx = np.argsort(topic)[::-1][0:nu... | code_fim | hard | {
"lang": "python",
"repo": "dhanashriOstwal/electionSentimentAnalysis",
"path": "/Python Scripts/postElection.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: dhanashriOstwal/electionSentimentAnalysis path: /Python Scripts/postElection.py
# -*- coding: utf-8 -*-
from sklearn.feature_extraction.text import TfidfVectorizer
import sentimentAnalysis as sA
import sys
import os
import numpy as np
from sklearn import decomposition
from gensim import ... | code_fim | hard | {
"lang": "python",
"repo": "dhanashriOstwal/electionSentimentAnalysis",
"path": "/Python Scripts/postElection.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>bikerawdata = BikeRawData()
bikerawdata.add_system(city_label='taipei', bikesharesystem_data=taipei_system)
bikerawdata.add_parser(city_label='taipei', parser_func=parse_taipei_file)
bikerawdata.add_system(city_label='helsinki', bikesharesystem_data=helsinki_system)
bikerawdata.add_parser(city_label='hels... | code_fim | hard | {
"lang": "python",
"repo": "anderzzz/viral-bikers",
"path": "/dataset_creators/__init__.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>def compile_data(city_labels=None):
'''Compile all data into common structure
'''
pass
def compile_and_save_data(f_out, city_labels=None):
'''Compile and save all data
'''
pass<|fim_prefix|># repo: anderzzz/viral-bikers path: /dataset_creators/__init__.py
'''Instantiate data pa... | code_fim | hard | {
"lang": "python",
"repo": "anderzzz/viral-bikers",
"path": "/dataset_creators/__init__.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: anderzzz/viral-bikers path: /dataset_creators/__init__.py
'''Instantiate data parsers for all cities.
If additional city parsers are added, the `bikerrawdata` instance in this file should be updated.
<|fim_suffix|> '''Compile all data into common structure
'''
pass
def compile_and_... | code_fim | hard | {
"lang": "python",
"repo": "anderzzz/viral-bikers",
"path": "/dataset_creators/__init__.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: susanbruce707/hexatrigesimal-to-decimal-calculator path: /base_36.py
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 19 09:41:08 2018
hexatrigesimal to decimal calculator,
base 36 encoding; use of letters with digits.
@author: susan
"""
## create a dictionary as reference for BASE 36 calcul... | code_fim | hard | {
"lang": "python",
"repo": "susanbruce707/hexatrigesimal-to-decimal-calculator",
"path": "/base_36.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
process valid user input or
terminate program on failed input.
"""
num = enter_num()
if num is not None:
num_lst = mk_num_lst(num)
dec = convert(num_lst)
print("decimal value of BASE 36 number", num, "is", dec)
else:
print("user ter... | code_fim | hard | {
"lang": "python",
"repo": "susanbruce707/hexatrigesimal-to-decimal-calculator",
"path": "/base_36.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sirfragles/iotsite path: /external_api/urls.py
from rest_framework.urlpatterns import format_suffix_patterns
from django.urls import path
from external_api import views
<|fim_suffix|>urlpatterns = format_suffix_patterns(urlpatterns)<|fim_middle|>urlpatterns = [
path('darksky/', views.DarkSky... | code_fim | medium | {
"lang": "python",
"repo": "sirfragles/iotsite",
"path": "/external_api/urls.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>urlpatterns = format_suffix_patterns(urlpatterns)<|fim_prefix|># repo: sirfragles/iotsite path: /external_api/urls.py
from rest_framework.urlpatterns import format_suffix_patterns
from django.urls import path
from external_api import views
<|fim_middle|>urlpatterns = [
path('darksky/', views.DarkSky... | code_fim | medium | {
"lang": "python",
"repo": "sirfragles/iotsite",
"path": "/external_api/urls.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: leeexing/Time-2016.11.30 path: /py/basics/scope.py
"""
作用域
在Python中，当引用一个变量的时候，对这个【变量的搜索】是按照
本地作用域(Local)、
嵌套作用域(Enclosing function locals)、
全局作用域(Global)、
内置作用域(builtins模块)
的顺序来进行的，
即所谓的LEGB规则。
然而当在一个【函数内部为一个变量赋值】时，并不是按照上面所说LEGB规则来首先找到变量，之后为该变量赋值。在Python中，在函数中为一个变量赋值时，有下面这样一条规则
“当在函数中给一个变量名赋值... | code_fim | medium | {
"lang": "python",
"repo": "leeexing/Time-2016.11.30",
"path": "/py/basics/scope.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>y = 100
def func_y():
global y
y = 101
func_y()
print(y)
def func_z():
z = 520
def foo():
z = 521
foo()
print(z)
func_z()
def func_e():
count = 0
def foo():
nonlocal count
count = 12
foo()
print(count)
func_e()
"""
使用global关键字修饰的变量之前可以并不存在... | code_fim | medium | {
"lang": "python",
"repo": "leeexing/Time-2016.11.30",
"path": "/py/basics/scope.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: liukai234/python_course_record path: /流程控制/常用迭代工具函数.py
# zip(),可以压缩 N 个列表成为一个zip对象（可迭代对象）。
a =['a', 'b', 'c']
b =[1, 2, 3]
[x for x in zip(a, b)] # [('a', 1), ('b', 2), ('c', 3)]
<|fim_suffix|># sorted() 接受一个可迭代对象，返回其升序。可传参数，reverse=True,key=?(排序关键字)
for book in sorted(books, reverse=True, key=... | code_fim | hard | {
"lang": "python",
"repo": "liukai234/python_course_record",
"path": "/流程控制/常用迭代工具函数.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># sorted() 接受一个可迭代对象，返回其升序。可传参数，reverse=True,key=?(排序关键字)
for book in sorted(books, reverse=True, key=len):
print(book)<|fim_prefix|># repo: liukai234/python_course_record path: /流程控制/常用迭代工具函数.py
# zip(),可以压缩 N 个列表成为一个zip对象（可迭代对象）。
a =['a', 'b', 'c']
b =[1, 2, 3]
[x for x in zip(a, b)] # [('a', 1), ... | code_fim | medium | {
"lang": "python",
"repo": "liukai234/python_course_record",
"path": "/流程控制/常用迭代工具函数.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|># reversed() 实现反向遍历,参数可以是各种序列
[y for y in reversed(b)] # [3, 2, 1]
# sorted() 接受一个可迭代对象，返回其升序。可传参数，reverse=True,key=?(排序关键字)
for book in sorted(books, reverse=True, key=len):
print(book)<|fim_prefix|># repo: liukai234/python_course_record path: /流程控制/常用迭代工具函数.py
# zip(),可以压缩 N 个列表成为一个zip对象（可迭代对象）。
... | code_fim | hard | {
"lang": "python",
"repo": "liukai234/python_course_record",
"path": "/流程控制/常用迭代工具函数.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WeiS49/Python-Crash-Course path: /python_work/ch6/6.2 alien2.py
alien_0 = {} # 声明一个空字典
alien_0['color'] = 'green' # 向空字典中添加值
alien_0['points'] = 5
print(alien_0)
<|fim_suffix|>print(f"The alien is now {alien_0['color']}")<|fim_middle|>x = alien_0['color']
print(f"\nThe alien is {alien_0['co... | code_fim | medium | {
"lang": "python",
"repo": "WeiS49/Python-Crash-Course",
"path": "/python_work/ch6/6.2 alien2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>print(f"The alien is now {alien_0['color']}")<|fim_prefix|># repo: WeiS49/Python-Crash-Course path: /python_work/ch6/6.2 alien2.py
alien_0 = {} # 声明一个空字典
alien_0['color'] = 'green' # 向空字典中添加值
alien_0['points'] = 5
print(alien_0)
x = alien_0['color']
<|fim_middle|>print(f"\nThe alien is {alien_0['co... | code_fim | medium | {
"lang": "python",
"repo": "WeiS49/Python-Crash-Course",
"path": "/python_work/ch6/6.2 alien2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Cool-Cooler/CoolInference path: /app/app.py
#coding: utf-8
from flask import Flask, redirect, url_for, request
from werkzeug.utils import secure_filename
import torch, torchvision
# Setup detectron2 logger
import detectron2
from detectron2.utils.logger import setup_logger
setup_logger()
# imp... | code_fim | hard | {
"lang": "python",
"repo": "Cool-Cooler/CoolInference",
"path": "/app/app.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> return response
@app.route("/infer", methods=['POST'])
def infer():
file = request.files['fimg']
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
return detect_object(file... | code_fim | hard | {
"lang": "python",
"repo": "Cool-Cooler/CoolInference",
"path": "/app/app.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # filterout bana and orage
data_set = MetadataCatalog.get(cfg.DATASETS.TRAIN[0])
# print(data_set.thing_classes)
pred_inst = outputs["instances"].to("cpu")
show_inst = []
pred_res = []
for tc in app.config['THING_CLASSES']:
if tc not in data_set.thing_classes:
... | code_fim | hard | {
"lang": "python",
"repo": "Cool-Cooler/CoolInference",
"path": "/app/app.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: luisalourenco/AdventOfCode2019 path: /03/part2.py
import sys
filepath = 'input.txt'
def intersection(list1, list2):
return set(list1).intersection(list2)
def computeSteps(x, y, step, steps):
# build dictionary with steps for each point
curr = 0
if (x,y) in steps:
... | code_fim | hard | {
"lang": "python",
"repo": "luisalourenco/AdventOfCode2019",
"path": "/03/part2.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> commonPoints = intersection(point1, point2)
min = sys.maxsize
for k in commonPoints:
val = steps.get(k)
if val < min:
min = val
print(min)<|fim_prefix|># repo: luisalourenco/AdventOfCode2019 path: /03/part2.py
import sys
filepath = 'input.txt'
... | code_fim | hard | {
"lang": "python",
"repo": "luisalourenco/AdventOfCode2019",
"path": "/03/part2.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> mpi_size = MPI.COMM_WORLD.Get_size()
# Log stats.
# XXX shouldn't call np.mean on variable length lists
duration = time.time() - start_time
if nb_epochs and nb_epoch_cycles and nb_train_steps > 0:
#stats = agent.get_stats()
... | code_fim | hard | {
"lang": "python",
"repo": "jramak/prosthetic-ddpg",
"path": "/baselines/ddpg/training.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if worth_keeping and rank == 0 and nb_epochs and nb_epoch_cycles and nb_train_steps and nb_rollout_steps:
logger.info('Saving model to', saved_model_dir + saved_model_basename + '-' + str(epoch))
saver.save(sess, saved_model_path, global_step=epoch, write_meta_g... | code_fim | hard | {
"lang": "python",
"repo": "jramak/prosthetic-ddpg",
"path": "/baselines/ddpg/training.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jramak/prosthetic-ddpg path: /baselines/ddpg/training.py
reward_scale=reward_scale)
logger.info('Using agent with the following configuration:')
logger.info(str(agent.__dict__.items()))
# Set up logging stuff only for a single worker.
saved_model_dir = 'saved-models/'
... | code_fim | hard | {
"lang": "python",
"repo": "jramak/prosthetic-ddpg",
"path": "/baselines/ddpg/training.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: philipdongfei/Violent-Python-A-Cookbook-for-Hackers path: /interceptThread.py
#!/usr/bin/env python3
class interceptThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
self.curPkt = None
self.seq = 0
self.foundUAV = False
def run(... | code_fim | medium | {
"lang": "python",
"repo": "philipdongfei/Violent-Python-A-Cookbook-for-Hackers",
"path": "/interceptThread.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> radio = dup.dupRadio(self.curPkt)
dot11 = dup.dupDot11(self.curPkt)
snap = dup.dupSNAP(self.curPkt)
llc = dup.dupLLC(self.curPkt)
ip = dup.dupIP(self.curPkt)
udp = dup.dupUDP(self.curPkt)
raw = Raw(load=cmd)
injectPkt = radio / dot11 / llc / ... | code_fim | hard | {
"lang": "python",
"repo": "philipdongfei/Violent-Python-A-Cookbook-for-Hackers",
"path": "/interceptThread.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jesserowan/ajax_notes path: /apps/notes/views.py
from django.shortcuts import render, redirect
from django.contrib import messages
from .models import *
from django.views.decorators.csrf import csrf_exempt
def index(request):
notes = Note.objects.all().order_by('-created_at')
context = {... | code_fim | hard | {
"lang": "python",
"repo": "jesserowan/ajax_notes",
"path": "/apps/notes/views.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == "POST":
note = Note.objects.get(id=id)
note.description = request.POST['edit_description']
note.save()
context = {
"notes": Note.objects.all().order_by('-created_at')
}
return render(request, 'notes/notes_index.html', context)<|fim_prefi... | code_fim | hard | {
"lang": "python",
"repo": "jesserowan/ajax_notes",
"path": "/apps/notes/views.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> if request.method == 'POST':
note = Note.objects.get(id=id)
note.delete()
context = {
"notes": Note.objects.all().order_by('-created_at')
}
return render(request, 'notes/notes_index.html', context)
def edit(request, id):
if request.method == "POST":
not... | code_fim | hard | {
"lang": "python",
"repo": "jesserowan/ajax_notes",
"path": "/apps/notes/views.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: llgeek/leetcode path: /907_SumOfSubarrayMinimums/solution_1.py
class Solution:
def sumSubarrayMins(self, A: List[int]) -> int:
stack = []
prev = [None] * len(A)
for i in range(len(A)):
<|fim_suffix|>
nex = [None] * len(A)
for i in range(len(A... | code_fim | hard | {
"lang": "python",
"repo": "llgeek/leetcode",
"path": "/907_SumOfSubarrayMinimums/solution_1.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>nex[i] = stack[-1] if stack else len(A)
stack.append(i)
return sum((i - prev[i]) * (nex[i] - i) * A[i] for i in range(len(A))) % (10 ** 9 + 7)<|fim_prefix|># repo: llgeek/leetcode path: /907_SumOfSubarrayMinimums/solution_1.py
class Solution:
def sumSubarrayMins(self, A: List[int]... | code_fim | hard | {
"lang": "python",
"repo": "llgeek/leetcode",
"path": "/907_SumOfSubarrayMinimums/solution_1.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''accesseur qui retourne la largeur de la grille'''
return self.largeur
def get_hauteur(self):
'''accesseur qui permet de récupérer la valeur de la hauteur de la grille'''
return self.hauteur
@staticmethod
def est_voisins(i,j,x,y,instance):
... | code_fim | hard | {
"lang": "python",
"repo": "elias-blm/jeudelavie",
"path": "/jeuVie_Belloumi.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: elias-blm/jeudelavie path: /jeuVie_Belloumi.py
but ordonnée et un autre abscisse). En effet, ce sont les deux éléments du jeu.
Q2) On pourrait donner une méthode pour changer l’état de la cellule, une autre pour obtenir son état. Une autre pour définir les voisins et encore une pour les obteni... | code_fim | hard | {
"lang": "python",
"repo": "elias-blm/jeudelavie",
"path": "/jeuVie_Belloumi.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> '''constructeur qui initialise les variables'''
self.__actuel= False
self.__futur= False
self.__voisins= None
def est_vivant(self):
'''accesseur qui retourne l'état actuel de la cellule'''
return self.__actuel
def set_voisins(self,... | code_fim | hard | {
"lang": "python",
"repo": "elias-blm/jeudelavie",
"path": "/jeuVie_Belloumi.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # Normalise dataset
print("Normalising dataset")
cats = pre_process.normalise(cats)
print("""
Cats dataset
{0}
""".format(cats.head()))
# PREDICTION
print("Prediction Starting")
cats_pred = Classifier.predict(export_model_dir, cats)
# EXPORTING
pr... | code_fim | hard | {
"lang": "python",
"repo": "Lee-SL/machineLearningCodeChallenge",
"path": "/predict.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # process date to keep year only
print("Processing date column to keep year only")
pre_process.strip_year(cats, date_column)
# Storing numerical columns in the background
pre_process.get_numerical_cols(cats)
# Convert all columns to float data type
print("Convert all columns ... | code_fim | hard | {
"lang": "python",
"repo": "Lee-SL/machineLearningCodeChallenge",
"path": "/predict.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Lee-SL/machineLearningCodeChallenge path: /predict.py
from import_.Import import Import
from classifier.Classifier import Classifier
from export.Export import Export
from preprocessing.PreProcess import PreProcess
def main():
date_column = "date of last vet visit"
target = "age at deat... | code_fim | hard | {
"lang": "python",
"repo": "Lee-SL/machineLearningCodeChallenge",
"path": "/predict.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: 221810306002/Problem-solving-and-programming-june-2019 path: /Untitled.py
#!/usr/bin/env python
# coding: utf-8
# In[5]:
import re
def phonenumbervalidate(phone):
pattern ='^[6-9][0-9]{9}$'
phone =str(phone)
if re.match(pattern,phone):
return True
return False
print(ph... | code_fim | hard | {
"lang": "python",
"repo": "221810306002/Problem-solving-and-programming-june-2019",
"path": "/Untitled.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
number =str(number)
pattern ="^[1][5][2][u][1][A][0][1-9][0-6][0-9]"
if re.match(pattern,number):
return True
return False
print(phonenumbervalidate("152u1A0555"))
print(phonenumbervalidate("152u1A0485"))
# In[ ]:<|fim_prefix|># repo: 221810306002/Problem-solving-and-pr... | code_fim | medium | {
"lang": "python",
"repo": "221810306002/Problem-solving-and-programming-june-2019",
"path": "/Untitled.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>uwkhk", "emodbyb", "ztahsya",
"ieiqm", "lfoquh", "emznnq", "pnhlgut", "pgvads", "cqsjx", "lxnjei", "zpque", "rdjbiyb", "sxedpu", "potnqva",
"iirkn", "rjmnrxd", "ksgcd", "waeymnh", "tizdz", "kproa", "wpttygd", "lvyze", "peewvgm", "fwtyzbw", "zitkk",
"gfgqr", "udgvlz", "swqspo", "... | code_fim | hard | {
"lang": "python",
"repo": "forrest0402/leetcode",
"path": "/python/820. Short Encoding of Words.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: forrest0402/leetcode path: /python/820. Short Encoding of Words.py
, "vtsqk", "ipkld", "yfhim", "ebaegdc", "ubhrh", "ldejv", "mtflwy", "ocpyj", "yopgqs", "fkjxxd",
"njnnwr", "nylkeb", "taymdqv", "ekpznq", "cbzobmg", "bucdds", "qjozu", "uvpghor", "obhnu", "ljkxbg", "uqrxjtf",
"xw... | code_fim | hard | {
"lang": "python",
"repo": "forrest0402/leetcode",
"path": "/python/820. Short Encoding of Words.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: forrest0402/leetcode path: /python/820. Short Encoding of Words.py
"upphc", "agydg", "cjmwk", "rhxbqh",
"tpgozdd", "qyqoy", "zjqutw", "qoohqny", "nsiacwz", "xupin", "criuvs", "eswjeft", "pdmevn", "zvogq", "lrrvo",
"qhfqqpw", "ktudfg", "ijvmi", "neyjjdx", "rllpi", "vllvaa", "ese... | code_fim | hard | {
"lang": "python",
"repo": "forrest0402/leetcode",
"path": "/python/820. Short Encoding of Words.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> maybe_download('https://s3.amazonaws.com/text-datasets/babi_tasks_1-20_v1-2.tar.gz', 'datasets', 11745123)
file = tarfile.open("datasets/babi_tasks_1-20_v1-2.tar.gz", "r:gz")
file.extractall("datasets")
file.close()
print("Some housekeeping...")
if not os.path.exists("datasets/babi... | code_fim | medium | {
"lang": "python",
"repo": "alexvlis/memN2N",
"path": "/memn2n/babi_utils.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: alexvlis/memN2N path: /memn2n/babi_utils.py
# Get Facebook's bAbi dataset
from utils import maybe_download
from shutil import rmtree
import os
import tarfile
<|fim_suffix|> maybe_download('https://s3.amazonaws.com/text-datasets/babi_tasks_1-20_v1-2.tar.gz', 'datasets', 11745123)
file = ta... | code_fim | medium | {
"lang": "python",
"repo": "alexvlis/memN2N",
"path": "/memn2n/babi_utils.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def execute(event, context):
print(event)
pass
# payload = {'Bucket': BUCKET_GLOBAL, 'Key': 'EEVC.TXT'}
# process(bucket=payload['Bucket'], key=payload['Key'])
#
# payload = {'Bucket': BUCKET_GLOBAL, 'Key': 'EEVD.TXT'}
# process(bucket=payload['Bucket'], key=payload['Key'])
... | code_fim | hard | {
"lang": "python",
"repo": "BrunoIstvan/localstack-aws-lambda-s3-sqs",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: BrunoIstvan/localstack-aws-lambda-s3-sqs path: /main.py
from os import environ
from process import process
from s3Service import put_object
environ['ACCESS_KEY'] = '1234567890'
environ['SECRET_KEY'] = '1234567890'
environ['ENDPOINT_URL'] = 'http://localhost:4566'
environ['REGION'] = 'us-east-1'
... | code_fim | medium | {
"lang": "python",
"repo": "BrunoIstvan/localstack-aws-lambda-s3-sqs",
"path": "/main.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> # payload = {'Bucket': BUCKET_GLOBAL, 'Key': 'EEVC.TXT'}
# process(bucket=payload['Bucket'], key=payload['Key'])
#
# payload = {'Bucket': BUCKET_GLOBAL, 'Key': 'EEVD.TXT'}
# process(bucket=payload['Bucket'], key=payload['Key'])
#
# payload = {'Bucket': BUCKET_GLOBAL, 'Key': 'EE... | code_fim | medium | {
"lang": "python",
"repo": "BrunoIstvan/localstack-aws-lambda-s3-sqs",
"path": "/main.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> #new_js_line = json.dumps(js) + "\n"
#new_json_file.write(new_js_line)
#continue
imgName = js["image_key"]
select_class = getRegionClass(done_root_dir, base_file_id, imgName)
if select_class == None:
new_json_file.write(line + '\n') #
#print('Not ... | code_fim | hard | {
"lang": "python",
"repo": "katerinahan/script",
"path": "/phone_smoke_zhenghua/smoke_check/add_common_box_smoke_region.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: katerinahan/script path: /phone_smoke_zhenghua/smoke_check/add_common_box_smoke_region.py
import os
import sys
import glob
import shutil
import json
import codecs
from collections import OrderedDict
def getRegionClass(image_path, data_id, imgName):
region_class = ['nosmoke_background', 'nosmok... | code_fim | hard | {
"lang": "python",
"repo": "katerinahan/script",
"path": "/phone_smoke_zhenghua/smoke_check/add_common_box_smoke_region.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> imgName = js["image_key"]
select_class = getRegionClass(done_root_dir, base_file_id, imgName)
if select_class == None:
new_json_file.write(line + '\n') #
#print('Not Found: ', done_root_dir, base_file_id, imgName)
continue
#print select_class
new_commo... | code_fim | hard | {
"lang": "python",
"repo": "katerinahan/script",
"path": "/phone_smoke_zhenghua/smoke_check/add_common_box_smoke_region.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gregsab/Multiflashcards path: /fcset.py
import urllib, json
from PyQt4.QtCore import QRectF, Qt
from PyQt4.Qt import QPrinter, QPainter, QFont, QBrush, QColor, QPen, QImage
from PyQt4.QtGui import QApplication
# bkgimg = QImage()
# bkgimg.load("KosyMost.jpg", format = "jpg")
#
# print bkgimg
... | code_fim | hard | {
"lang": "python",
"repo": "gregsab/Multiflashcards",
"path": "/fcset.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|> background(painter, bkgimg)
painter.setPen(penHText);
painter.setFont(QFont("Arial", 24, QFont.Bold));
painter.drawText(q, Qt.AlignCenter | Qt.TextWordWrap, qa['q'])
painter.drawText(a, Qt.AlignCenter | Qt.TextWordWrap, qa['a'][0])
printer.newPage()
painter.end()<|fim_prefix|>... | code_fim | hard | {
"lang": "python",
"repo": "gregsab/Multiflashcards",
"path": "/fcset.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_suffix|>for qa in data['flashcards']:
print "%s -> %s" % (qa['q'], qa['a'][0])
# painter.drawText(painter.device().width()/2, 500, qa['q'])
background(painter, bkgimg)
painter.setPen(penHText);
painter.setFont(QFont("Arial", 24, QFont.Bold));
painter.drawText(q, Qt.AlignCenter, qa['q'])
... | code_fim | hard | {
"lang": "python",
"repo": "gregsab/Multiflashcards",
"path": "/fcset.py",
"mode": "spm",
"license": "unknown",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: aaronspurgeon/hashtables-flex path: /applications/word_count/word_count.py
def word_count(s):
# Your code here
cache = {}
ignore = '":;,.-+=/\\|[]{}()*^&'
lower = s.lower()
<|fim_suffix|>if __name__ == "__main__":
print(word_count(""))
print(word_count("Hello"))
print... | code_fim | hard | {
"lang": "python",
"repo": "aaronspurgeon/hashtables-flex",
"path": "/applications/word_count/word_count.py",
"mode": "psm",
"license": "unknown",
"source": "the-stack-v2"
} |
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