code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# Cookies Keys
class Cookies:
USER_TOKEN = "utoken"
# Session Keys
class Session:
USER_ROOT_ID = "x-root-id"
class APIStatisticsCollection:
API_ACTION = "x-stats-api-action"
DICT_PARAMS = "x-stats-param-dict"
DICT_RESPONSE = "x-stats-resp-dict"
SUCCESS = "x-stats-success"
... | normal | {
"blob_id": "d0e5a3a6db0e27ecf157294850a48a19750a5ac2",
"index": 1667,
"step-1": "<mask token>\n\n\nclass Session:\n <mask token>\n\n\n class APIStatisticsCollection:\n API_ACTION = 'x-stats-api-action'\n DICT_PARAMS = 'x-stats-param-dict'\n DICT_RESPONSE = 'x-stats-resp-dict'\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class FitTemplate:
def __init__(self, fit_function, log_dir=None):
self.fit_function = fit_function
self.parameters = Parameters()
self.fit_result = None
if log_dir is not None:
logging.basicConfig(filename=log_dir + 'log.log', level=loggin... | flexible | {
"blob_id": "9e16921d83a5f62aad694b26a92b57b97ccda461",
"index": 1651,
"step-1": "<mask token>\n\n\nclass FitTemplate:\n\n def __init__(self, fit_function, log_dir=None):\n self.fit_function = fit_function\n self.parameters = Parameters()\n self.fit_result = None\n if log_dir is no... | [
6,
7,
8,
9,
10
] |
import uuid
from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.profile import region_provider
# 注意：不要更改
from celery_tasks.sms.dysms_python.build.lib.aliyunsdkdysmsapi.request.v20170525 import SendSmsRequest
class SendMes(object):
REGION = "cn-hangzhou"
PRODUCT_NAME = "Dysmsapi"
DOMAIN = "dysmsapi.aliy... | normal | {
"blob_id": "daecbf5280c199b31f3b9d9818df245d9cd165a7",
"index": 4295,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SendMes(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n region_provider.add_endpoint(PRODUCT_NAME, REGI... | [
0,
1,
3,
4,
5
] |
from flask import Flask, render_template, url_for, request, redirect, session, flash
import os, json
from usuarios import crearUsuario, comprobarUsuario
from busqueda import filtrado
from compra import procesarCompra, Dinero
app = Flask(__name__)
catalogo_data = json.loads(open(os.path.join(app.root_path,'json/catalo... | normal | {
"blob_id": "ebb4cf1ec2baa7bd0d29e3ae88b16e65cf76a88a",
"index": 3679,
"step-1": "<mask token>\n\n\n@app.route('/info/<pelicula>', methods=['GET', 'POST'])\ndef informacionPelicula(pelicula):\n peliculas = catalogo_data['peliculas']\n if request.method == 'POST':\n return redirect(url_for('index'), ... | [
9,
12,
13,
15,
16
] |
#processes are described by generator functions
#during the lifetime of a process, the process function(generator function)
#creates events and yields them
#when a process yields an event, it gets suspended
#Simpy resumes the process when the event is triggered
#multiple processes waiting on the same event is resumed... | normal | {
"blob_id": "892eb8d1802b01c035993232cc80c710211ab102",
"index": 802,
"step-1": "<mask token>\n\n\ndef car(env):\n while True:\n print('The car will start parking at: ', env.now)\n parking_timeout = 5\n yield env.timeout(parking_timeout)\n print('The car will start driving at: ', e... | [
1,
2,
3,
4,
5
] |
def domain_name(url):
while "https://" in url or "http://" in url or "www." in url:
url = url.replace("https://", ' ') if "https://" in url else url.replace("http://", ' ') if "http://" in url else url.replace("www.", ' ')
url = list(url)
for i in range(len(url)):
if url[i] == ".":
... | normal | {
"blob_id": "2b9dfd0cfd62276330f1a4f983f318076f329437",
"index": 5026,
"step-1": "<mask token>\n",
"step-2": "def domain_name(url):\n while 'https://' in url or 'http://' in url or 'www.' in url:\n url = url.replace('https://', ' '\n ) if 'https://' in url else url.replace('http://', ' '\n... | [
0,
1,
2,
3
] |
# Import this.
| normal | {
"blob_id": "1f69bcd204c9be26756d964f4deb61296e40ff10",
"index": 9658,
"step-1": "# Import this.\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
1
]
} | [
1
] |
"""Secret Garden tests."""
from secret_garden import Decoder, SecretGarden
import random
filename = "pr08_example_data.txt"
key = "Fat Chocobo"
d = Decoder(filename, key)
s = SecretGarden(filename, key)
def test_read_from_file():
"""
Test of function of reading data from file.
:return:
"""
readi... | normal | {
"blob_id": "8cfab525ab3a86dd6964475d5621fdc7c6413e38",
"index": 8019,
"step-1": "<mask token>\n\n\ndef test_read_from_file():\n \"\"\"\n Test of function of reading data from file.\n\n :return:\n \"\"\"\n reading_file = d.read_code_from_file()\n assert type(reading_file) == list\n assert le... | [
5,
6,
7,
8,
9
] |
#打印ckpt或pb模型的tensor
# ckpt模型
#第一种方法：
from tensorflow.python.tools.inspect_checkpoint import print_tensors_in_checkpoint_file
checkpoint_path="/your/path"
print_tensors_in_checkpoint_file(checkpoint_path,tensor_name='', all_tensors=True, all_tensor_names=True)
#第二种方法：
from tensorflow.python import pywrap... | normal | {
"blob_id": "50fab726b90f65a82c1206a8c7df955a8b76da99",
"index": 1572,
"step-1": "<mask token>\n\n\ndef create_graph():\n with tf.gfile.FastGFile(out_pb_path, 'rb') as f:\n graph_def = tf.GraphDef()\n graph_def.ParseFromString(f.read())\n tf.import_graph_def(graph_def, name='')\n\n\n<mask... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def medianflt(img, i, j, msize, mr, mc):
pxls = []
for a in range(msize):
for b in range(msize):
mi = i + a - mr
mj = j + b - mc
pxls.append(img[mi][mj])
pxls.sort()
return pxls[msize * msize // 2]
def orderstatistic(img, row, ... | flexible | {
"blob_id": "cfcce8c760f6ba49ce450d78782cb8f3b5fc1188",
"index": 2857,
"step-1": "<mask token>\n\n\ndef medianflt(img, i, j, msize, mr, mc):\n pxls = []\n for a in range(msize):\n for b in range(msize):\n mi = i + a - mr\n mj = j + b - mc\n pxls.append(img[mi][mj])\n... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class DocUploadForm(forms.ModelForm):
tags = forms.ModelMultipleChoiceField(queryset=Tag.objects.all())
class Meta:
model = Document
exclude = ['organization', 'private_user', 'is_public',
'is_user_private', 'display']
class ShopForm(forms.Form):
... | flexible | {
"blob_id": "d2c5d306591216e100b5bd8e8822b24fd137d092",
"index": 9208,
"step-1": "<mask token>\n\n\nclass DocUploadForm(forms.ModelForm):\n tags = forms.ModelMultipleChoiceField(queryset=Tag.objects.all())\n\n\n class Meta:\n model = Document\n exclude = ['organization', 'private_user', 'is_p... | [
23,
24,
32,
34,
37
] |
def interseccao_chaves(lis_dic):
lista = []
for dic1 in lis_dic[0]:
for cahves in dic1:
lista.append(dic1)
for dic2 in lis_dic[1]:
for cahves in dic2:
lista.append(dic2)
return lista
| normal | {
"blob_id": "f3ff453655d7938cb417ce212f3836fabafaea43",
"index": 1696,
"step-1": "<mask token>\n",
"step-2": "def interseccao_chaves(lis_dic):\n lista = []\n for dic1 in lis_dic[0]:\n for cahves in dic1:\n lista.append(dic1)\n for dic2 in lis_dic[1]:\n for cahves in dic2:\n ... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(cv2.__version__)
<|reserved_special_token_0|>
print(image)
print(image.shape)
print(image[0])
print('~~~~~~~~~~~~~~~')
print(image.shape[0])
print('~~~~~~~~~~~~~~~')
print(len(image))
<|reserved_special_token_1|>
<|reserv... | flexible | {
"blob_id": "0b0ae6101fd80bdbcf37b935268f3e49230599fb",
"index": 5715,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(cv2.__version__)\n<mask token>\nprint(image)\nprint(image.shape)\nprint(image[0])\nprint('~~~~~~~~~~~~~~~')\nprint(image.shape[0])\nprint('~~~~~~~~~~~~~~~')\nprint(len(image))\n",
... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def load_a_affirm_target(gfe_path=GFE_PATH):
csv_targeta = os.path.join(gfe_path, 'a_affirmative_targets.csv')
print(gfe_path)
return pd.read_csv(csv_targeta)
def load_a_cond_data(gfe_path=GFE_PATH):
csv_pathc = os.path.join(gfe_path, 'a_conditional_datapoints.csv')
... | flexible | {
"blob_id": "2fb8bce3a64787dbaf5a3bb3da53f70005048467",
"index": 4104,
"step-1": "<mask token>\n\n\ndef load_a_affirm_target(gfe_path=GFE_PATH):\n csv_targeta = os.path.join(gfe_path, 'a_affirmative_targets.csv')\n print(gfe_path)\n return pd.read_csv(csv_targeta)\n\n\ndef load_a_cond_data(gfe_path=GFE_... | [
19,
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30,
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] |
# -*- Python -*-
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
# California Institute of Technology
# (C) 2008 All Rights Reserved
#
# {LicenseText}
#
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
#
... | normal | {
"blob_id": "721e014bc5bf53a39556e31f281b77b90508cf12",
"index": 7138,
"step-1": "<mask token>\n\n\nclass Retriever(base):\n\n def _retrieveResultsFor(self, computation):\n director = self.director\n db = director.clerk.db\n orm = director.clerk.orm\n analysisObj = orm.record2objec... | [
2,
3,
4,
5,
6
] |
from plumbum import local, FG, ProcessExecutionError
import logging
import os.path
from task import app
kubectl = local["kubectl"]
@app.task
def create_kube_from_template(file_name, *aargs):
args = {}
for a in aargs:
args.update(a)
template = open(os.path.join('..', file_name)).read() % args
logging.info... | normal | {
"blob_id": "137e80b3bfdc0dba33a3108b37d21d298a8f251d",
"index": 1544,
"step-1": "<mask token>\n\n\n@app.task\ndef delete_kube_by_name(name):\n try:\n logging.info(kubectl['delete', name]())\n return True\n except ProcessExecutionError:\n return False\n",
"step-2": "<mask token>\n\n\... | [
1,
2,
3,
4,
5
] |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
data=pd.read_csv('regression.csv')
print(data)
x=data.iloc[:,0]
y=data.iloc[:,1]
mx=data['X1'].mean()
my=data['Y'].mean()
print(mx,my)
num, den = 0,0
for i in range(len(x)):
num += (x[i] - mx)*(y[i]-my)
den += (x[i]-mx)**2
be... | normal | {
"blob_id": "ca6b064dbd8200c49665eaa944fdf1fc80c25726",
"index": 1047,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(data)\n<mask token>\nprint(mx, my)\n<mask token>\nfor i in range(len(x)):\n num += (x[i] - mx) * (y[i] - my)\n den += (x[i] - mx) ** 2\n<mask token>\nprint(beta1, beta0)\n<mas... | [
0,
1,
2,
3,
4
] |
# coding: utf-8
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import time
import random
csvfilename = 'data/0901/exp1/xiaoxiong.csv'
df = pd.read_csv(csvfilename, header=None,
names=['abstime','posx','posy','posz','roty','rotx','anim'... | normal | {
"blob_id": "d0adbcd60727c2c68e06dc5e796f2676f927c45a",
"index": 4593,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndf.head()\n<mask token>\nprint(m)\n<mask token>\nprint(mean)\nfor i in mean:\n random.seed(1)\n randomFactor = [(random.random() * 0.01 + (i - 0.005)) for _ in range(m)]\n for id... | [
0,
1,
2,
3,
4
] |
import requests
from os.path import join, exists
import os
import fitz
from tqdm import tqdm
from pathlib import Path
import tempfile
def download_pdf(url, folder, name):
r = requests.get(url, allow_redirects=True)
file_path = join(folder, name + ".pdf")
open(file_path, 'wb').write(r.content)
return f... | normal | {
"blob_id": "c6113088f45951bc4c787760b6ca0138265fb83f",
"index": 9966,
"step-1": "<mask token>\n\n\ndef download_pdf(url, folder, name):\n r = requests.get(url, allow_redirects=True)\n file_path = join(folder, name + '.pdf')\n open(file_path, 'wb').write(r.content)\n return file_path\n\n\n<mask token... | [
2,
3,
4,
5,
6
] |
import Ploneboard
import PloneboardForum
import PloneboardConversation
import PloneboardComment
| normal | {
"blob_id": "abdf5aee77ee879c50d0e605d5fd95e28a7ef7aa",
"index": 5631,
"step-1": "<mask token>\n",
"step-2": "import Ploneboard\nimport PloneboardForum\nimport PloneboardConversation\nimport PloneboardComment\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
class BaseTestCloudAuth:
"""
Required
setup: initialize test case
teardown: del items for test
decode: check decoded token and assigned info
"""
ACCESS_TOKEN = ''
SCOPE_ACCESS_TOKEN = ''
ID_TOKEN = ''
TESTCLIENT = None
<|reserved_speci... | flexible | {
"blob_id": "9a2b5b9b2b2f9532b5d0749147aca644c2ac26e3",
"index": 2878,
"step-1": "<mask token>\n\n\nclass BaseTestCloudAuth:\n \"\"\"\n Required\n setup: initialize test case\n teardown: del items for test\n decode: check decoded token and assigned info\n \"\"\"\n ACCESS_TOKEN = ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Person:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Person:
<|reserved_special_token_0|>
def GetName(self):
return self.fname + ' ' + self.lname
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "ff358136bc96fa7f3eb41d019ddfd10fc4db8f0d",
"index": 5558,
"step-1": "<mask token>\n",
"step-2": "class Person:\n <mask token>\n <mask token>\n",
"step-3": "class Person:\n <mask token>\n\n def GetName(self):\n return self.fname + ' ' + self.lname\n",
"step-4": "class Person:... | [
0,
1,
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3,
4
] |
# ================================================== #
# MAIN WINDOW #
# ================================================== #
# Author: Brady Hammond #
# Created: 11/21/2017 #
# Last Edited: N/A ... | normal | {
"blob_id": "a555226b14223dca688d10b811eb36fb229360ce",
"index": 2457,
"step-1": "<mask token>\n\n\nclass UIMainWindow(object):\n <mask token>\n\n def retranslateUI(self):\n _translate = QtCore.QCoreApplication.translate\n self.main_window.setWindowTitle(_translate('main_window',\n ... | [
4,
6,
7,
8,
9
] |
import time
from selenium import webdriver
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
def open_browser(browser="chrome"):
driver = None
if browser == "chrome":
driver = webdriver.Chrome()
elif browser == "firefox":
... | normal | {
"blob_id": "82fc86e44d02c45d7904139e4dfdff069e2bdb90",
"index": 5634,
"step-1": "<mask token>\n\n\nclass Base:\n <mask token>\n\n def open_url(self, url):\n self.driver.get(url)\n self.driver.maximize_window()\n\n def find_element(self, locator, timeout=10):\n element = WebDriverWa... | [
6,
9,
11,
12,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Trainer:
def html_escape(self, text):
html_escape_table = {'"': '"', "'": '''}
return escape(text, html_escape_table)
def train(self, preprocessedxml, xmlname):
f = open('../Trai... | flexible | {
"blob_id": "22e24e8dd49367ae57d1980c4addf48d65c5e897",
"index": 7851,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Trainer:\n\n def html_escape(self, text):\n html_escape_table = {'\"': '"', \"'\": '''}\n return escape(text, html_escape_table)\n\n def train(self... | [
0,
3,
4,
6,
7
] |
<|reserved_special_token_0|>
def func(x):
return x ** c
def der_func(x):
return c * x ** (c - 1)
<|reserved_special_token_0|>
def main():
x = 100
v_min = func(x)
for i in range(10):
cur_v = func(x)
x = na_value(x)
if cur_v < v_min:
v_min = cur_v
pr... | flexible | {
"blob_id": "fa7246a4e7595393ca9aaec777fa85d782bb816e",
"index": 4815,
"step-1": "<mask token>\n\n\ndef func(x):\n return x ** c\n\n\ndef der_func(x):\n return c * x ** (c - 1)\n\n\n<mask token>\n\n\ndef main():\n x = 100\n v_min = func(x)\n for i in range(10):\n cur_v = func(x)\n x ... | [
3,
4,
5,
6,
7
] |
#!/bin/python3
import sys
from collections import deque
def connectedCell(matrix,n,m):
# Complete this function
visit = []
for j in range(n):
a = []
for i in range(m):
a.append(True)
visit.append(a)
#print(visit)
path = 0
for i in range(n):
for j in ... | normal | {
"blob_id": "25a159ca2abf0176135086324ab355d6f5d9fe9e",
"index": 5054,
"step-1": "<mask token>\n\n\ndef connectedCell(matrix, n, m):\n visit = []\n for j in range(n):\n a = []\n for i in range(m):\n a.append(True)\n visit.append(a)\n path = 0\n for i in range(n):\n ... | [
1,
2,
3,
4,
5
] |
from utilities.MatplotlibUtility import *
from utilities.PlotDefinitions.DrainSweep.OutputCurve import plot as importedOutputCurvePlot
plotDescription = {
'name':'Chip Output Curves',
'plotCategory': 'chip',
'priority': 40,
'dataFileDependencies': ['DrainSweep.json'],
'plotDefaults': {
'figsize':(2,2.5),
'co... | normal | {
"blob_id": "49ae9e90402d784fc3af3b47e96842fbfe842104",
"index": 9480,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef plot(identifiers, chipIndexes, firstRunChipHistory,\n recentRunChipHistory, specificRunChipHistory, groupedChipHistory,\n mode_parameters=None):\n if mode_parameters is N... | [
0,
1,
2,
3,
4
] |
import os
WOO_HOST = os.environ.get('WOO_HOST')
#WooCommerce key credentials
WOO_CONSUMER_KEY = os.environ.get('WOO_CONSUMER_KEY')
WOO_CONSUMER_SECRET = os.environ.get('WOO_CONSUMER_SECRET')
#XML feed fields and settings
XML_FEED_FILENAME = os.environ.get('XML_FEED_FILENAME', 'feedXML')
XML_SITE_NAME = os.environ.ge... | normal | {
"blob_id": "386fa51b9b285d36c75d6446f9348f6713e0dbaa",
"index": 2794,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n from local_settings import *\nexcept ImportError:\n pass\nif SENTRY_URL:\n import sentry_sdk\n sentry_sdk.init(SENTRY_URL)\n",
"step-3": "<mask token>\nWOO_HOST = os.... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cv2.namedWindow('mathches', 1)
cv2.imshow('mathches', a)
cv2.waitKey()
<|reserved_special_token_0|>
for m, n in matches:
if m.distance < 0.45 * n.distance:
good.append(m)
print(len(good))
<|reserved_special_token_0|>
c... | flexible | {
"blob_id": "60953878c377382f1c7f25ce284c9fa12b8eb25f",
"index": 4667,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.namedWindow('mathches', 1)\ncv2.imshow('mathches', a)\ncv2.waitKey()\n<mask token>\nfor m, n in matches:\n if m.distance < 0.45 * n.distance:\n good.append(m)\nprint(len(goo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
counts = open(sys.argv[1]).readlines()
for line in open(sys.argv[1]):
line = line.strip('\n')
url = line
try:
r = requests.get(url, verify=True, timeout=3)
print(url + ' ' + str(r.status_code))
print(str(r.tex... | flexible | {
"blob_id": "96a4659f03879e051af95b5aa9c1e1364015fb86",
"index": 8723,
"step-1": "<mask token>\n\n\ndef main():\n counts = open(sys.argv[1]).readlines()\n for line in open(sys.argv[1]):\n line = line.strip('\\n')\n url = line\n try:\n r = requests.get(url, verify=True, timeo... | [
1,
2,
3,
4,
5
] |
# Generated by Django 2.2.3 on 2019-07-14 13:34
from django.db import migrations, models
def forwards_func(apps, schema_editor):
""" Add Theater Rooms """
TheaterRoom = apps.get_model("main", "TheaterRoom")
db_alias = schema_editor.connection.alias
TheaterRoom.objects.using(db_alias).bulk_create([
... | normal | {
"blob_id": "a4b61a5a79e314e56ba25c6e2e735bd2ee4ef0d3",
"index": 4551,
"step-1": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\ndef reverse_func(apps, schema_editor):\n \"\"\" No need to do anything since the t... | [
1,
3,
4,
5,
6
] |
class Line:
def __init__(self,coor1,coor2):
self.coor1 = coor1
self.coor2 = coor2
def slope(self):
pass
def distance(self):
#x = self.coor1[0]-self.coor2[0]
#y = self.coor2[1]-self.coor2[1]
#return ((x**2)+(y**2))**0.5
return ((((self.coor2[0]-s... | normal | {
"blob_id": "f91e997b305348485698d180b97138b040285b60",
"index": 9440,
"step-1": "<mask token>\n\n\nclass Account:\n\n def __init__(self, name, balance):\n self.name = name\n self.balance = balance\n\n def deposit(self, money):\n self.balance += money\n return 'Deposit accepted'... | [
5,
15,
16,
19,
20
] |
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
from scrapy.selector import Selector
from meizi.items import MeiziItem
class MztspiderSpider(CrawlSpider):
name = 'mztspider2'
allowed_domains = ['meizitu.com']
start_urls = [... | normal | {
"blob_id": "a1ce43c3f64667619c4964bc4dc67215d3ecc1a0",
"index": 9215,
"step-1": "<mask token>\n\n\nclass MztspiderSpider(CrawlSpider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass MztspiderSpider(CrawlSpider):\n <mask token... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def blink_connected_to_wifi(pin=23):
_blink_pattern(pin, [[3, 0.5, 0.5], [4, 0.2, 0.2]])
<|reserved_special_token_0|>
def _blink_pattern(pin, pattern):
p = Pin(pin, Pin.OUT)
try:
for item in pattern:
for j in range(item[0]):
p.value(1)
... | flexible | {
"blob_id": "c0bd060990d00ab50c9f2d3060b7f975ff16e1ab",
"index": 4105,
"step-1": "<mask token>\n\n\ndef blink_connected_to_wifi(pin=23):\n _blink_pattern(pin, [[3, 0.5, 0.5], [4, 0.2, 0.2]])\n\n\n<mask token>\n\n\ndef _blink_pattern(pin, pattern):\n p = Pin(pin, Pin.OUT)\n try:\n for item in patt... | [
2,
3,
4,
5,
6
] |
class Rectangle():
def __init__(self,length,breadth):
self.length=length
self.breadth=breadth
def area(self):
return(self.length*self.breadth)
def perimeter(self):
return(2*(self.length+self.breadth))
r1=Rectangle(4,5)
r2=Rectangle(5,7)
a1=r1.area()
a2=r2.area()
p1=r1.perim... | normal | {
"blob_id": "d5691403812cd3742f8e8b74d4ca613eca784ffd",
"index": 9677,
"step-1": "class Rectangle:\n <mask token>\n <mask token>\n\n def perimeter(self):\n return 2 * (self.length + self.breadth)\n\n\n<mask token>\n",
"step-2": "class Rectangle:\n\n def __init__(self, length, breadth):\n ... | [
2,
3,
4,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
assert os.path.isdir(os.environ['OUT_DIR'])
sys.exit(subprocess.call(sys.argv[1:], env=os.environ))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
os.environ['OUT_DIR'] = os.path.abspath('.')
assert os.path.isdir(os.... | flexible | {
"blob_id": "be238268b9fdd565f3cb0770839789b702940ef9",
"index": 8248,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nassert os.path.isdir(os.environ['OUT_DIR'])\nsys.exit(subprocess.call(sys.argv[1:], env=os.environ))\n",
"step-3": "<mask token>\nos.environ['OUT_DIR'] = os.path.abspath('.')\nassert os... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
CONSUMER_KEY = ''
CONSUMER_SECRET = ''
<|reserved_special_token_0|>
TOKENS_PATH = '/tmp/twitter-tokens.json'
REDIRECT_TO = ''
FLASK_SECRET = 'S$2[ShC-=BKKOQ.Z-|fa 6f;,5 <[QngmG)}5,s%0vX>B}?o-0X9PM;.dN{jo7'
<|reserved_special_tok... | flexible | {
"blob_id": "9cc64edc81ab39b0ab2cd47661c9809545b03ac6",
"index": 3230,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nCONSUMER_KEY = ''\nCONSUMER_SECRET = ''\n<mask token>\nTOKENS_PATH = '/tmp/twitter-tokens.json'\nREDIRECT_TO = ''\nFLASK_SECRET = 'S$2[ShC-=BKKOQ.Z-|fa 6f;,5 <[QngmG)}5,s%0vX>B}?o-0X9PM;.... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
ret, frame = cap.read()
frame = np.float32(frame) / 255
average_stack = average_stack * frames + frame
frames += 1.0
average_stack = average_stack / frames
cv2.imshow('frame', np.uint8(average_s... | flexible | {
"blob_id": "7fd89272d3d3584f35fd8f552cb7b14e57b7ed1b",
"index": 1591,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n ret, frame = cap.read()\n frame = np.float32(frame) / 255\n average_stack = average_stack * frames + frame\n frames += 1.0\n average_stack = average_stack / f... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
if __name__ == '__main__':
import sys
import os
sys.path.insert(0, os.path.abspath('config'))
import configure
configure_options = [
'CC=icc',
'CXX=icpc',
'FC=ifort',
'--with-blas-lapack-dir=/soft/com/packages/intel/13/update5/mkl/',
'--with-mkl_pardiso-dir=/soft/com/pack... | normal | {
"blob_id": "43eb221758ebcf1f01851fc6cda67b72f32a73c7",
"index": 6992,
"step-1": "<mask token>\n",
"step-2": "if __name__ == '__main__':\n import sys\n import os\n sys.path.insert(0, os.path.abspath('config'))\n import configure\n configure_options = ['CC=icc', 'CXX=icpc', 'FC=ifort',\n '... | [
0,
1,
2
] |
from dependency_injector import containers, providers
from src.repositories import MemcachedRepository
from src.services import FibonacciService
class Container(containers.DeclarativeContainer):
config = providers.Configuration()
cache_repository = providers.Singleton(MemcachedRepository,
... | normal | {
"blob_id": "e8ba1ae98b247eaf90d83339e5fdc27287a70c73",
"index": 2561,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Container(containers.DeclarativeContainer):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Container(containers.DeclarativeContai... | [
0,
1,
2,
3,
4
] |
import requests
import json
base_url = f"https://api.telegram.org/bot"
def get_url(url):
response = requests.get(url)
content = response.content.decode("utf8")
return content
def get_json_from_url(url):
content = get_url(url)
js = json.loads(content)
return js
def get_updates(TOKEN):
... | normal | {
"blob_id": "501614f9c7df3c862c9951ea343964b6ed47e74a",
"index": 3204,
"step-1": "<mask token>\n\n\ndef get_url(url):\n response = requests.get(url)\n content = response.content.decode('utf8')\n return content\n\n\ndef get_json_from_url(url):\n content = get_url(url)\n js = json.loads(content)\n ... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class User:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Customer(User):
def __init__(self, name, email, age):
self.name = name
self.email = email
self.age = age
self.balance = 0
def ge... | flexible | {
"blob_id": "ea045d04b40341f34c780dceab1f21df93b7207a",
"index": 7689,
"step-1": "<mask token>\n\n\nclass User:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Customer(User):\n\n def __init__(self, name, email, age):\n self.name = name\n self.email = email\n self.age = a... | [
4,
5,
8,
10,
11
] |
<|reserved_special_token_0|>
def smart_open(file, mode='rt', encoding='utf-8'):
"""Convenience function for reading compressed or plain text files.
:param file: The file to read.
:param mode: The file mode (read, write).
:param encoding: The file encoding.
"""
if file.endswith('.gz'):
... | flexible | {
"blob_id": "8adcd75e925fe0c5a50b2fc7dc8c472a9610b4f2",
"index": 9575,
"step-1": "<mask token>\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n ... | [
27,
29,
31,
37,
42
] |
from django.shortcuts import render,redirect
from . import download_function
from django.http import HttpResponse
# Create your views here.
def download(request):
if request.method == "GET":
session = request.GET['session']
title = request.GET['download_title']
download_quality = request.GET... | normal | {
"blob_id": "339506777f5471ec99b39c67c28df8ec3d06ce19",
"index": 3084,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef download(request):\n if request.method == 'GET':\n session = request.GET['session']\n title = request.GET['download_title']\n download_quality = request.GE... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Processing:
<|reserved_special_token_0|>
@property
def vocab_size(self):
return self.__vocab_size
def normalize(self, s):
s = s.lower()
replacements = ('á', 'a'), ('é', 'e'), ('í', 'i'), ('ó', 'o'), ('ú',
'u'), ('ñ', 'n')
... | flexible | {
"blob_id": "326b2dcbef339aeb196bef23debad75fa079b121",
"index": 6435,
"step-1": "<mask token>\n\n\nclass Processing:\n <mask token>\n\n @property\n def vocab_size(self):\n return self.__vocab_size\n\n def normalize(self, s):\n s = s.lower()\n replacements = ('á', 'a'), ('é', 'e'... | [
12,
16,
17,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open(os.path.join(os.path.dirname(__file__), 'README.rst')) as readme:
README = readme.read()
os.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir)))
setup(name='django-themes', version=__version__,... | flexible | {
"blob_id": "6e557c2b85031a0038afd6a9987e3417b926218f",
"index": 6184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(os.path.join(os.path.dirname(__file__), 'README.rst')) as readme:\n README = readme.read()\nos.chdir(os.path.normpath(os.path.join(os.path.abspath(__file__), os.pardir)))\nse... | [
0,
1,
2,
3
] |
## 허프변환에 의한 직선 검출
# cv2.HoughLines(image, rho, theta, threshold, lines=None, srn=None, stn=None, min-theta=None, max-theta=None) => lines
# image : 에지 입력 영상(Canny 연산을 이용한 에지 영상)
# rho(로우) : 축적 배열에서 rho 값의 간격(보통 1.0 사용)
# theta(세타) : 축적 배열에서 theta 값의 간격(보통 np.pi/180)
# rho, theta 값이 커지면 축적배열의 크기는 작아지고, 값이 작으면 축적배... | normal | {
"blob_id": "ff7cb8261f3abb70599725fe7c598c571d037226",
"index": 9535,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif src is None:\n print('Image load failed')\n sys.exit()\n<mask token>\nif lines is not None:\n for i in range(lines.shape[0]):\n pt1 = lines[i][0][0], lines[i][0][1]\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_should_config_start_correctly():
c = Config(mock)
assert c._entities == mock['entities']
assert c._synonimous == mock['synonimous']
assert c.templates == mock['templates']
assert c.get_value('synonim... | flexible | {
"blob_id": "987f8ce668f2002b731822fa5f3de143a80aaafe",
"index": 9807,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_should_config_start_correctly():\n c = Config(mock)\n assert c._entities == mock['entities']\n assert c._synonimous == mock['synonimous']\n assert c.templates == ... | [
0,
1,
2,
3,
4
] |
import unittest
from common.ReqLogin import req
import os
import yaml
from common import util
from TestCase.runnerBase import TestInterfaceCase
import paramunittest
PATH = lambda p: os.path.abspath(
os.path.join(os.path.dirname(__file__), p)
)
def getYam(homeyaml):
try:
with open(homeyaml, encoding='ut... | normal | {
"blob_id": "aea196566bbbe9d37bf03b9b17a4062659a27bb6",
"index": 1446,
"step-1": "<mask token>\n\n\nclass UserinfoTest(TestInterfaceCase):\n\n def setUp(self):\n login = req.reqData(req)\n self.infoma = {}\n self.response = ''\n self.infoma['id'] = x['testinfo'][0]['id']\n s... | [
10,
11,
13,
15,
17
] |
from haven import haven_utils as hu
import itertools, copy
EXP_GROUPS = {}
EXP_GROUPS['starter_issam'] = hu.cartesian_exp_group({
'batch_size': 32,
'opt': {'name': 'adamW', 'lr': 0.0001, 'wd': 1e-6},
'model': {'name': 'resnext50_32x4d_ssl'},
... | normal | {
"blob_id": "dafefc65335a0d7e27057f51b43e52b286f5bc6b",
"index": 6067,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nEXP_GROUPS = {}\nEXP_GROUPS['starter_issam'] = hu.cartesian_exp_group({'batch_size': 32,\n 'opt': {'name': 'adamW', 'lr': 0.0001, 'wd': 1e-06}, 'model': {'name':\n 'resnext50_32x4d_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def add_frame_id(video, output_dir):
reader = cv2.VideoCapture(video)
if not reader.isOpened():
return -1
os.makedirs(output_dir, exist_ok=True)
frame_count = int(reader.get(cv2.CAP_PROP_FRAME_COUNT))
for frame_id in tqdm(range(frame_count)):
has_frame,... | flexible | {
"blob_id": "f8f538773693b9d9530775094d9948626247a3bb",
"index": 6950,
"step-1": "<mask token>\n\n\ndef add_frame_id(video, output_dir):\n reader = cv2.VideoCapture(video)\n if not reader.isOpened():\n return -1\n os.makedirs(output_dir, exist_ok=True)\n frame_count = int(reader.get(cv2.CAP_PR... | [
2,
3,
4,
5,
6
] |
"""Get pandas dataframes for a given data and month.
*get_dataframes(csvfile, spec=SPEC)* is a function to get dataframes
from *csvfile* connection under *spec* parsing instruction.
*Vintage* class addresses dataset by year and month:
Vintage(year, month).save()
Vintage(year, month).validate()
*Collecti... | normal | {
"blob_id": "e78c4f65d84d5b33debb415005e22f926e14d7d4",
"index": 1203,
"step-1": "<mask token>\n\n\nclass Vintage:\n <mask token>\n\n def __init__(self, year, month):\n self.year, self.month = year, month\n self.csv = LocalCSV(year, month)\n <mask token>\n <mask token>\n <mask token>... | [
9,
13,
14,
15,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Welcome aboard, Oleksij!')
| flexible | {
"blob_id": "2b1ec29d665aa93cd53644b62efcd1305b34e13e",
"index": 2636,
"step-1": "<mask token>\n",
"step-2": "print('Welcome aboard, Oleksij!')\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def fileMD(self):
salt_ = os.urandom(32).hex()
hash_object = hashlib.md5()
hash_object.update(('%s%s' % (salt_, self.theFile)).encode('utf-8'))
print('MD5 Hash: ' + hash_object.hexdigest())
<|reserved_special_t... | flexible | {
"blob_id": "bc9718fa57046888961d1b5245abefa8f752e983",
"index": 8103,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fileMD(self):\n salt_ = os.urandom(32).hex()\n hash_object = hashlib.md5()\n hash_object.update(('%s%s' % (salt_, self.theFile)).encode('utf-8'))\n print('MD5 Hash: ' ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class ClassRoom:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def Name2Id(room_id, name):
bool_n = bool(re.match('教\\d{1}-\\d{3}', name))
bool_id = bool(re.match('B\\d{1}R\\d{3}', room_id))
if not (bool_id ... | flexible | {
"blob_id": "8dae8a89d08bc522f9a5fdde8aeb9e322fafcbec",
"index": 3251,
"step-1": "<mask token>\n\n\nclass ClassRoom:\n <mask token>\n <mask token>\n <mask token>\n\n def Name2Id(room_id, name):\n bool_n = bool(re.match('教\\\\d{1}-\\\\d{3}', name))\n bool_id = bool(re.match('B\\\\d{1}R\\... | [
7,
8,
10,
11,
12
] |
import shelve
def quantity_posts():
try:
data = shelve.open('data')
except Exception:
print(Exception)
else:
for key, value in sorted(data.items()):
print(key, ': \t', value, '\n')
finally:
data.close()
if __name__ == "__main__":
print('b... | normal | {
"blob_id": "41c44b32ce3329cbba5b9b336c4266bb20de31f0",
"index": 5151,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef quantity_posts():\n try:\n data = shelve.open('data')\n except Exception:\n print(Exception)\n else:\n for key, value in sorted(data.items()):\n ... | [
0,
1,
2,
3,
4
] |
import os,sys,glob
sys.path.append("../../../../libs/VASNet/")
from VASNet_frame_scoring_lib import *
sys.path.append("../../../config")
from config import *
if __name__ == '__main__':
#************************************************************************
# Purpose: frame scoring (Summarizing Videos with A... | normal | {
"blob_id": "ce97da4aab2b9de40267730168690475c899526d",
"index": 3924,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../../../../libs/VASNet/')\n<mask token>\nsys.path.append('../../../config')\n<mask token>\nif __name__ == '__main__':\n path_pretrained_model = cfg.PATH_DRDSN_PRETRAI... | [
0,
1,
2,
3
] |
#from graph import *
#ex = open('ex_K.py', 'r')
#ex.read()
import ex_K
ex = ex_K
print "digraph K {"
print (str(ex.K))
print "}"
| normal | {
"blob_id": "44dbb7587530fac9e538dfe31c7df15b1a016251",
"index": 7091,
"step-1": "#from graph import *\r\n#ex = open('ex_K.py', 'r')\r\n#ex.read()\r\nimport ex_K\r\nex = ex_K\r\n\r\nprint \"digraph K {\"\r\nprint (str(ex.K))\r\nprint \"}\"\r\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": n... | [
0
] |
# -*- coding: utf-8 -*-
#
# RPi.Spark KeyButton Demo
#
# Author: Kunpeng Zhang
# 2018.6.6
#
# See LICENSE for details.
from time import sleep
import RPi.GPIO as GPIO
from JMRPiSpark.Drives.Key.RPiKeyButtons import RPiKeyButtons
from JMRPiSpark.Drives.Key.RPiKeyButtons import DEF_BOUNCE_TIME_SHORT_MON
from JMRPiSpark.... | normal | {
"blob_id": "50c274e0365f2556a46eb58edcd1f0a7301e89db",
"index": 8716,
"step-1": "<mask token>\n\n\nclass demo:\n <mask token>\n\n def __init__(self):\n self._myKey = RPiKeyButtons()\n\n def _getKeyButtonName(self, keyBtn):\n if keyBtn == CONFIG_KEY.BUTTON_ACT_A:\n return 'BUTTO... | [
6,
12,
15,
16,
17
] |
import tensorflow as tf
import numpy as np
def safe_nanmax(x):
with np.warnings.catch_warnings():
np.warnings.filterwarnings('ignore',
r'All-NaN (slice|axis) encountered')
return np.nanmax(x)
def safe_nanargmax(x):
try:
return np.nanargmax(x)
ex... | normal | {
"blob_id": "16bf4583b872f038edccbac4e567c1854d65e216",
"index": 4962,
"step-1": "<mask token>\n\n\nclass OfflineMetric:\n\n def __init__(self, *args, **kwargs):\n self.__name__ = self.name()\n <mask token>\n\n def handle_batch(self, model, x, labels, pred):\n raise NotImplementedError()\n... | [
18,
20,
32,
39,
46
] |
<|reserved_special_token_0|>
class NamingConvention:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class NamingConvention:
<|reserved_special_token_0|>
def __init__(self):
namingconventions = os.path.join(os.path.dirna... | flexible | {
"blob_id": "d2a153fffccd4b681eebce823e641e195197cde7",
"index": 54,
"step-1": "<mask token>\n\n\nclass NamingConvention:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass NamingConvention:\n <mask token>\n\n def __init__(self):\n namingconventions = os.path.join(os.path.d... | [
1,
2,
3,
4,
5
] |
'''
Problem Description
Given two numbers n1 and n2
1. Find prime numbers between n1 and n2, then
2. Make all possible unique combinations of numbers from the prime
numbers list you found in step 1.
3. From this new list, again find all prime numbers.
4. Find smallest (a) and largest (b) number from the 2nd gener... | normal | {
"blob_id": "fe5050fdf010ce1c4d458b8a52ac92485a7d8cea",
"index": 5706,
"step-1": "<mask token>\n\n\ndef isPrime(n):\n if n <= 1:\n return False\n if n <= 3:\n return True\n if n % 2 == 0 or n % 3 == 0:\n return False\n i = 5\n while i * i <= n:\n if n % i == 0 or n % (i... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python3
# encoding: utf-8
"""
@author: ShuoChang
@license: (C) MIT.
@contact: changshuo@bupt.edu.cn
@software: CRNN_STN_SEQ
@file: decoder_base.py
@time: 2019/7/22 17:21
@blog: https://www.zhihu.com/people/chang-shuo-59/activities
"""
from abc import ABCMeta
from abc import abstractmethod
class DecoderBas... | normal | {
"blob_id": "0d8a26ef4077b40e8255d5bb2ce9217b51118780",
"index": 7364,
"step-1": "<mask token>\n\n\nclass DecoderBase(object):\n <mask token>\n <mask token>\n\n def __init__(self):\n self._predictor = 'decoder'\n self._label = None\n pass\n\n @abstractmethod\n def set_label(se... | [
4,
5,
7,
8,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for s1, s2 in zip(A[:-1], A[1:]):
if s1 < s2:
stockNum = g // s1
g += stockNum * (s2 - s1)
print(g)
<|reserved_special_token_1|>
n = int(input())
A = list(map(int, input().split()))
g = 1000
for s1, s2 in zi... | flexible | {
"blob_id": "da903409d75ba2a07443317e30bce568444fbca5",
"index": 9956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor s1, s2 in zip(A[:-1], A[1:]):\n if s1 < s2:\n stockNum = g // s1\n g += stockNum * (s2 - s1)\nprint(g)\n",
"step-3": "n = int(input())\nA = list(map(int, input().sp... | [
0,
1,
2
] |
#!/usr/bin/python
# coding=UTF-8
import sys
import subprocess
import os
def printReportTail(reportHtmlFile):
reportHtmlFile.write("""
</body>
</html>
""")
def printReportHead(reportHtmlFile):
reportHtmlFile.write("""<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" ... | normal | {
"blob_id": "b5cbb73c152dd60e9063d5a19f6182e2264fec6d",
"index": 15,
"step-1": "#!/usr/bin/python\n# coding=UTF-8\n\nimport sys\nimport subprocess\nimport os\n\ndef printReportTail(reportHtmlFile):\n reportHtmlFile.write(\"\"\"\n</body>\n</html>\n\"\"\")\n\ndef printReportHead(reportHtmlFile):\n reportHtml... | [
0
] |
import ROOT
from PhysicsTools.NanoAODTools.postprocessing.framework.datamodel import Collection
from PhysicsTools.NanoAODTools.postprocessing.framework.eventloop import Module
from TreeProducer import *
from TreeProducerCommon import *
from CorrectionTools.PileupWeightTool import *
from CorrectionTools.BTaggingTool i... | normal | {
"blob_id": "1721bba2cae1e330bffeb9df05341df9522ff885",
"index": 4394,
"step-1": "import ROOT\nfrom PhysicsTools.NanoAODTools.postprocessing.framework.datamodel import Collection \nfrom PhysicsTools.NanoAODTools.postprocessing.framework.eventloop import Module\n\nfrom TreeProducer import *\nfrom TreeProducerComm... | [
0
] |
# -*- coding: utf-8 -*-
import logging
from django.shortcuts import render, redirect, HttpResponse
from django.core.urlresolvers import reverse
from django.conf import settings
from django.contrib.auth import logout, login, authenticate
from django.contrib.auth.hashers import make_password
from django.core.paginator im... | normal | {
"blob_id": "0b1e6a95ee008c594fdcff4e216708c003c065c8",
"index": 4873,
"step-1": "# -*- coding: utf-8 -*-\nimport logging\nfrom django.shortcuts import render, redirect, HttpResponse\nfrom django.core.urlresolvers import reverse\nfrom django.conf import settings\nfrom django.contrib.auth import logout, login, au... | [
0
] |
def coroutine(func):
def start_coroutine(*args, **kwargs):
cr = func(*args, **kwargs)
next(cr) #cr.send(None)
return cr
return start_coroutine
@coroutine
def grep(pattern):
print('start grep')
try:
while True:
line = yield
if pattern in line:
print(line)
except GeneratorExit:
print('stop grep'... | normal | {
"blob_id": "bebe098c5abb579eb155a1dc325347d100ddfa8f",
"index": 1805,
"step-1": "def coroutine(func):\n\n def start_coroutine(*args, **kwargs):\n cr = func(*args, **kwargs)\n next(cr)\n return cr\n return start_coroutine\n\n\n<mask token>\n",
"step-2": "def coroutine(func):\n\n d... | [
1,
2,
3,
4,
6
] |
from django.contrib import admin
from .models import Recipe, Ingredient, ChosenIngredient, timezone
# Register your models here.)
admin.site.register(Ingredient)
admin.site.site_header = "Chef's Apprentice Admin"
admin.site.site_title = "Chef's Apprentice Admin Portal"
admin.site.index_title = "Welcome to Chef's Appre... | normal | {
"blob_id": "65bb3743ca569c295d85016c82c4f6f043778d3f",
"index": 8848,
"step-1": "<mask token>\n\n\nclass RecipeAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n model = Recipe\n\n def make_visible(self, request, queryset):\n ... | [
3,
5,
6,
8,
10
] |
<|reserved_special_token_0|>
class Submit(webapp2.RequestHandler):
<|reserved_special_token_0|>
def post(self):
if self.request.get('submit'):
updated_handphone = self.request.get('handphone')
updated_tickets_csjh = self.request.get('tickets_csjh')
updated_tickets_... | flexible | {
"blob_id": "aeef27d667f95e3818f73533439385ea949b96a4",
"index": 2445,
"step-1": "<mask token>\n\n\nclass Submit(webapp2.RequestHandler):\n <mask token>\n\n def post(self):\n if self.request.get('submit'):\n updated_handphone = self.request.get('handphone')\n updated_tickets_cs... | [
2,
8,
11,
12,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "722739086d2777085fdbfdbddef205aaf025580d",
"index": 4291,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('user', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
print('Output')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
print('Output')
<|reserved_special_token_0|>
if __name__ == '__main__':
main()
<|reserved_special_token_0|>
print('Run time: {}'.format(end -... | flexible | {
"blob_id": "cdb07241e08f8ac85a427c5b2bc3effca3917c85",
"index": 2188,
"step-1": "<mask token>\n\n\ndef main():\n print('Output')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n print('Output')\n\n\n<mask token>\nif __name__ == '__main__':\n main()\n<mask token>\nprint('Run time: {}'.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
__all__ = ['average', 'extract_ocean_scalar', 'git', 'gmeantools', 'merge',
'netcdf', 'xrtools']
<|reserved_special_token_1|>
<|reserved_special_token_0|>
from . import average
from . import extract_ocean_scalar
from . impo... | flexible | {
"blob_id": "ab6450ee9038e0c58ca8becf6d2518d5e00b9c90",
"index": 9393,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['average', 'extract_ocean_scalar', 'git', 'gmeantools', 'merge',\n 'netcdf', 'xrtools']\n",
"step-3": "<mask token>\nfrom . import average\nfrom . import extract_ocean_sca... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cv2.line(image, (0, 0), (512, 0), (255, 255, 255), 5)
cv2.line(image, (0, 50), (512, 50), (255, 255, 255), 5)
cv2.rectangle(image, (256, 0), (400, 256), (0, 255, 0), 3)
<|reserved_special_token_0|>
cv2.putText(image, 'ROS OpenCV',... | flexible | {
"blob_id": "f6c5c2180a1a4b05b3f103c330b455e7387713a6",
"index": 8125,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncv2.line(image, (0, 0), (512, 0), (255, 255, 255), 5)\ncv2.line(image, (0, 50), (512, 50), (255, 255, 255), 5)\ncv2.rectangle(image, (256, 0), (400, 256), (0, 255, 0), 3)\n<mask token>\nc... | [
0,
1,
2,
3,
4
] |
from os import listdir
from os.path import isfile, join
from datetime import date
mypath = '/Users/kachunfung/python/codewars/'
onlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]
py_removed = [i.replace('.py','') for i in onlyfiles]
file_counter_removed = py_removed.remove('file_counter')
day_removed... | normal | {
"blob_id": "592d5074eeca74a5845d26ee2ca6aba8c3d0f989",
"index": 8929,
"step-1": "from os import listdir\nfrom os.path import isfile, join\nfrom datetime import date\n\nmypath = '/Users/kachunfung/python/codewars/'\nonlyfiles = [f for f in listdir(mypath) if isfile(join(mypath, f))]\n\npy_removed = [i.replace('.... | [
0
] |
<|reserved_special_token_0|>
class Scrapper:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Scrapper:
<|reserved_special_token_0|>
def scrapper(prov):
scrapper = importlib.import_module('scrappers.{}'.format(prov)... | flexible | {
"blob_id": "67e06b6dddbd3f26295eaff921d1ad4a8b0e5487",
"index": 5580,
"step-1": "<mask token>\n\n\nclass Scrapper:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Scrapper:\n <mask token>\n\n def scrapper(prov):\n scrapper = importlib.import_module('scrappers.{}'.format... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
logging.basicConfig(level=logging.INFO)
<|reserved_special_token_0|>
for extension in rdf_file_extension.keys():
files_to_check = '**/*' + extension
for filename in glob.iglob(root_path + files_to_check, recursive=True):
... | flexible | {
"blob_id": "fe406f40b48bf4982e7a48737b6b30514ae1fa71",
"index": 7915,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(level=logging.INFO)\n<mask token>\nfor extension in rdf_file_extension.keys():\n files_to_check = '**/*' + extension\n for filename in glob.iglob(root_path + fil... | [
0,
1,
2,
3,
4
] |
from .compat import reverse, action
from rest_framework.response import Response
from rest_framework.viewsets import ModelViewSet
from rest_framework import pagination
from rest_framework import renderers
from . import registry
from .serializers import RunSerializer, RecordSerializer
from .models import Run
from .setti... | normal | {
"blob_id": "11a0c3307994a90d1d4de67d442ffa355e11e13b",
"index": 6836,
"step-1": "<mask token>\n\n\nclass RunViewSet(ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @property\n def template_na... | [
11,
13,
17,
18,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
def cal_sum(self, root, L, R, result):
if not root:
return result
... | flexible | {
"blob_id": "8e1de62f2490d2276a834ae1ab0f1958649fa821",
"index": 5503,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n <mask token>\n",
"step-3": "class Solution:\n <mask token>\n\n def cal_sum(self, root, L, R, result):\n if not root:\n return result\n ... | [
0,
1,
2,
3,
4
] |
import sys
from domain import *
from fuzzy_set import *
from parser import *
class FuzzyControler(object):
def __init__(self, angle_rules, acc_rules, domains_angle, domains_acc):
self.angle_rules = angle_rules
self.acc_rules = acc_rules
self.domains_angle = domains_angle
self.domains_acc = domains_acc
s... | normal | {
"blob_id": "7451b09c54734fb02167d43b96df972420d86853",
"index": 7776,
"step-1": "import sys\n\nfrom domain import *\nfrom fuzzy_set import *\nfrom parser import *\n\nclass FuzzyControler(object):\n\n\tdef __init__(self, angle_rules, acc_rules, domains_angle, domains_acc):\n\n\t\tself.angle_rules = angle_rules\n... | [
0
] |
class Sala:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Sala:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __str__(self):
return str(self.numero)
<|reserved_special_token_1|>
class Sala:... | flexible | {
"blob_id": "e41df44db92e2ef7f9c20a0f3052e1c8c28b76c7",
"index": 6174,
"step-1": "class Sala:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class Sala:\n <mask token>\n <mask token>\n\n def __str__(self):\n return str(self.numero)\n",
"step-3": "class Sala:\n <mask t... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# Andre Anjos <andre.anjos@idiap.ch>
# Sat Dec 17 14:41:56 2011 +0100
#
# Copyright (C) 2011-2013 Idiap Research Institute, Martigny, Switzerland
"""Run tests on the libsvm machine infrastructure.
"""
import os
import numpy
import tempfile
import pkg_resources
imp... | normal | {
"blob_id": "c24be05700e5ee043d09d6f2e78cb3de1e7088f1",
"index": 6242,
"step-1": "<mask token>\n\n\ndef F(f):\n \"\"\"Returns the test file on the \"data\" subdirectory\"\"\"\n return pkg_resources.resource_filename(__name__, os.path.join('data', f))\n\n\n<mask token>\n\n\ndef load_expected(filename):\n ... | [
8,
9,
12,
13,
17
] |
import pymysql
from app_module.models import User, Vehicle, Address, Customer, Location, Coupon, VehicleClass, Corporation, Corporate
from datetime import datetime
HOSTNAME = 'localhost'
USERNAME = 'root'
PASSWORD = '123456'
DATABASE = 'proj_p2'
def get_connection():
my_sql_connection = pymysql.connect(host=HOST... | normal | {
"blob_id": "62bad8eeb3b51a5012dad761a60639d36429d8e8",
"index": 7660,
"step-1": "<mask token>\n\n\ndef run_query(query, args=None):\n conn = get_connection()\n cur = conn.cursor()\n cur.execute(query, args)\n rs = cur.fetchall()\n if len(rs) != 0:\n return rs\n conn.commit()\n cur.cl... | [
25,
27,
37,
40,
41
] |
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torchvision import datasets, transforms, models
from torchvision.utils import make_grid
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os
from PIL import Image
from... | normal | {
"blob_id": "7821b07a49db9f3f46bedc30f2271160e281806f",
"index": 4814,
"step-1": "<mask token>\n\n\nclass ConvolutionalNetwork(nn.Module):\n\n def __init__(self):\n super().__init__()\n self.conv1 = nn.Conv2d(3, 6, 3, 1)\n self.conv2 = nn.Conv2d(6, 16, 3, 1)\n self.fc1 = nn.Linear(... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for c in range(0, 7):
pe1 = int(input('Digite o ano de nascimento: '))
pe1 = 2019 - pe1
if pe1 >= 21:
num1 = num1 + 1
print(f'Entre as 7 pessoas, {num1} pessoas são maiores de idade.')
<|reserved_special_toke... | flexible | {
"blob_id": "251d589a5815d77d2bc375d8d4a7d41e79a2a5cd",
"index": 5303,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor c in range(0, 7):\n pe1 = int(input('Digite o ano de nascimento: '))\n pe1 = 2019 - pe1\n if pe1 >= 21:\n num1 = num1 + 1\nprint(f'Entre as 7 pessoas, {num1} pessoas s... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def split_page(result_obj):
"""
分页模块，后台传入一个分页结果集就可以
:param result_obj:
:return:
"""
return_str = '<nav>'
return_str += "<ul class='pagination pull-right'>"
if result_obj.has_previous():
return_str += '<li>'
return_str += "<a href='?page=" +... | flexible | {
"blob_id": "c2c51dcd05c21e91e591de25fc2de034c88c48a1",
"index": 9052,
"step-1": "<mask token>\n\n\ndef split_page(result_obj):\n \"\"\"\n 分页模块，后台传入一个分页结果集就可以\n :param result_obj:\n :return:\n \"\"\"\n return_str = '<nav>'\n return_str += \"<ul class='pagination pull-right'>\"\n if resul... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 6 10:05:25 2019
@author: MCA
"""
import smtplib, ssl
from email import encoders
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email.mime.multipart import MIMEMultipart
import os,sys
import time
def loadFiles(su... | normal | {
"blob_id": "b310c35b781e3221e2dacc7717ed77e20001bafa",
"index": 5109,
"step-1": "<mask token>\n\n\ndef loadFiles(subdir, filetype):\n \"\"\"\n example:\n dirs = [\"dir1\", \"dir2\"]\n file_type = \".dat\"\n files, keys, data = loadFiles(dirs[0], file_type)\n \n \"\"\"\n dirname = os.path... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class HTTPClient(abc.ABC):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@abc.abstractmethod
def post(self, url: str, **kwargs: Dict[str, Any]) ->Any:
""... | flexible | {
"blob_id": "1a126ba7e73eb2e7811ab32146fe5aee6c6b30f9",
"index": 4290,
"step-1": "<mask token>\n\n\nclass HTTPClient(abc.ABC):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @abc.abstractmethod\n def post(self, url: str, **kwargs: Dict[str, Any]) ->Any:\n ... | [
8,
10,
11,
14,
15
] |
nome = str(input('Digite um nome completo: ')).lower()
silva = 'silva' in nome
if silva == True:
print('Existe Silva nesse nome')
else:
print('Não há Silva nesse nome')
| normal | {
"blob_id": "faebefcadbc184fab29deb2988089223a8f09e7e",
"index": 8219,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif silva == True:\n print('Existe Silva nesse nome')\nelse:\n print('Não há Silva nesse nome')\n",
"step-3": "nome = str(input('Digite um nome completo: ')).lower()\nsilva = 'silv... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def start_thread(target):
thread = threading.Thread(target=target)
thread.daemon = True
thread.start()
<|reserved_special_token_0|>
def receive_data():
while True:
data = sock.recv(1024).decode()
print('decoded is', data)
if data == 'button':
... | flexible | {
"blob_id": "cc924892afe179e55166ea9b237b2bfe8ea900df",
"index": 2120,
"step-1": "<mask token>\n\n\ndef start_thread(target):\n thread = threading.Thread(target=target)\n thread.daemon = True\n thread.start()\n\n\n<mask token>\n\n\ndef receive_data():\n while True:\n data = sock.recv(1024).dec... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def getDistanceByHaversine(loc1, loc2):
"""Haversine formula - give coordinates as a 2D numpy array of
(lat_denter link description hereecimal,lon_decimal) pairs"""
lat1 = loc1[1]
lon1 = loc1[0]
lat2 = loc2[1]
lon2 = loc2[0]
lon1 = lon1 * sp.pi / 180.0
lon2... | flexible | {
"blob_id": "d2e3ac490ce5fdc20976567fa320a9e6a53cbe34",
"index": 1037,
"step-1": "<mask token>\n\n\ndef getDistanceByHaversine(loc1, loc2):\n \"\"\"Haversine formula - give coordinates as a 2D numpy array of\n (lat_denter link description hereecimal,lon_decimal) pairs\"\"\"\n lat1 = loc1[1]\n lon1 = ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class PraiseHistory(TimeStampedModel):
class Meta:
verbose_name = '칭찬 내역'
verbose_name_plural = verbose_name
praise = models.ForeignKey(Praise, verbose_name='칭찬')
choices = JSONField(verbose_name='칭찬 대상 목록')
sender_key = models.CharField(verbose_name='보낸 ... | flexible | {
"blob_id": "a4db12fee72989f983c1069839dc0a5ede4561a3",
"index": 686,
"step-1": "<mask token>\n\n\nclass PraiseHistory(TimeStampedModel):\n\n\n class Meta:\n verbose_name = '칭찬 내역'\n verbose_name_plural = verbose_name\n praise = models.ForeignKey(Praise, verbose_name='칭찬')\n choices = JSON... | [
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def extract_gpx_data(gpx_file_path, attribute='elevation'):
"""Reads in a GPX file and returns a list of values
for a specified GPX attribute.
Parameters
----------
gpx_file_path : str
File path to t... | flexible | {
"blob_id": "cc6d18785eff0406ff7f38f18f15476375e31b76",
"index": 9254,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef extract_gpx_data(gpx_file_path, attribute='elevation'):\n \"\"\"Reads in a GPX file and returns a list of values\n for a specified GPX attribute.\n\n Parameters\n ----... | [
0,
1,
2,
3
] |
from django import forms
from django.conf import settings
class SurveyFeedback(forms.Form):
CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',
'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',
'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]
radioFeedback = forms.C... | normal | {
"blob_id": "a9b7abaaaa811cf12a15def1f2dd21f95bac3d62",
"index": 6310,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n CHOICES = [('Very Sat... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def play():
print('playing tank games...')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def play():
print('playing tank games...')
print('runing tank now!!!')
<|reserved_special_token_1|>
def play():
print("playing tank game... | flexible | {
"blob_id": "8c7fe90972feec19e280d3bccd39391af666608a",
"index": 9410,
"step-1": "<mask token>\n",
"step-2": "def play():\n print('playing tank games...')\n\n\n<mask token>\n",
"step-3": "def play():\n print('playing tank games...')\n\n\nprint('runing tank now!!!')\n",
"step-4": "def play():\n pri... | [
0,
1,
2,
3
] |
from pyspark.sql import SparkSession, Row, functions, Column
from pyspark.sql.types import *
from pyspark.ml import Pipeline, Estimator
from pyspark.ml.feature import SQLTransformer, VectorAssembler
from pyspark.ml.evaluation import RegressionEvaluator
from pyspark.ml.tuning import TrainValidationSplit, ParamGridBuild... | normal | {
"blob_id": "3852ff2f3f4ac889256bd5f4e36a86d483857cef",
"index": 6534,
"step-1": "<mask token>\n\n\ndef get_data(inputloc, tablename='data'):\n data = spark.read.csv(inputloc, schema=schema)\n data.createOrReplaceTempView(tablename)\n return data\n\n\n<mask token>\n\n\ndef resolved_max(df):\n df_max ... | [
4,
5,
6,
7,
8
] |
import json
import os
from six import iteritems
from ..exceptions import ColinConfigException
from ..constant import CONFIG_DIRECTORY, JSON
from ..loader import load_check_implementation
from ..target import is_compatible
class Config(object):
def __init__(self, name=None):
"""
Load config for ... | normal | {
"blob_id": "7bb9455e6f0c15ab0be6963cff06ff41df73e6e0",
"index": 2583,
"step-1": "<mask token>\n\n\nclass Config(object):\n\n def __init__(self, name=None):\n \"\"\"\n Load config for colin.\n\n :param name: str (name of the config file (without .json), default is \"default\"\n \"\... | [
6,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def cLineGraph(j_file):
data = []
with open(j_file) as f:
for line in f:
data.append(json.loads(line))
data = data[0]
in_other = 0
in_picture = 1
in_text = 2
values = []
time =... | flexible | {
"blob_id": "319af5232c043d77a9d63ab1efa62d857da6db23",
"index": 1508,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef cLineGraph(j_file):\n data = []\n with open(j_file) as f:\n for line in f:\n data.append(json.loads(line))\n data = data[0]\n in_other = 0\n in_pi... | [
0,
1,
2,
3
] |
# 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
def overlap_rect(rec1, rec2):
"""Determine if rectangles overlap."""
# true if rec2 is left of rec1
a = rec... | normal | {
"blob_id": "0ef03ed455938bd2001581986c38104bfac395ce",
"index": 8078,
"step-1": "<mask token>\n",
"step-2": "def overlap_rect(rec1, rec2):\n \"\"\"Determine if rectangles overlap.\"\"\"\n a = rec2[2] <= rec1[0]\n b = rec1[2] <= rec2[0]\n c = rec2[3] <= rec1[1]\n d = rec1[3] <= rec2[1]\n retu... | [
0,
1,
2
] |
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