code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
'''
runSPP.py - wrap spp peak caller
========================================
:Tags: Python
Purpose
-------
Runs the spp peak caller.
The workflow follows the tutorial at:
http://compbio.med.harvard.edu/Supplements/ChIP-seq/tutorial.html
Usage
-----
Documentation
-------------
Requirements:
* spp >= ?
* snow >... | normal | {
"blob_id": "e886b88a0b7e8c06772fe8a9554cab1bfe9e94a7",
"index": 7208,
"step-1": "<mask token>\n\n\ndef bamToBed(infile, outfile):\n \"\"\"convert bam to bed with bedtools.\"\"\"\n statement = 'bamToBed -i %(infile)s > %(outfile)s' % locals()\n E.debug(\"executing statement '%s'\" % statement)\n retc... | [
3,
4,
5,
6,
7
] |
import os
import pandas as pd
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
name="/home/t3cms/thessel/Workflow1.5/stop_data/stop_train_sig_wc.csv"
name_bkg="/home/t3cms/thessel/Workflow1.5/stop_data/stop_train_bkg_wc.csv"
drop_cols=[0,1,2,15]
names = [i for i in range(16)]
#columns=[]... | normal | {
"blob_id": "f8bb2851192a53e94e503c0c63b17477878ad9a7",
"index": 6926,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Before PCA', final_df)\nfor i in pca_df.columns:\n final_df[i] = pca_df[i]\nprint('After PCA', final_df)\n<mask token>\nfinal_df.iloc[:cut].to_csv('pca_stop_train_sig_wc.csv', h... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_prime(num):
if num <= 1:
return False
i = 2
while i * i <= num:
if num % i == 0:
return False
i += 1
return True
<|reserved_special_token_0|>
<|reserved_special_toke... | flexible | {
"blob_id": "07fdf6605d970d2491116ad82a1119499b561d1f",
"index": 4144,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_prime(num):\n if num <= 1:\n return False\n i = 2\n while i * i <= num:\n if num % i == 0:\n return False\n i += 1\n return True\n\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class MatlabConfig(Controller):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MatlabConfig(Controller):
executable = File(Undefined, output=False, desc=
'Full path of the matlab executable')... | flexible | {
"blob_id": "4a8e8994ec8734664a5965b81da9d146d8504f8d",
"index": 6096,
"step-1": "<mask token>\n\n\nclass MatlabConfig(Controller):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass MatlabConfig(Controller):\n executable = File(Undefined, output=False, desc=\n 'Full path of t... | [
1,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def keypress():
global keys
keys['space'] = keys['quit'] = keys['next'] = False
for event in pygame.event.get():
if event.type == pygame.KEYDOWN and event.key == pygame.K_SPACE:
keys['space'] = True
elif event.type == pygame.KEYUP and event.key == p... | flexible | {
"blob_id": "aeaab602cbb9fa73992eb5259e8603ecb11ba333",
"index": 4863,
"step-1": "<mask token>\n\n\ndef keypress():\n global keys\n keys['space'] = keys['quit'] = keys['next'] = False\n for event in pygame.event.get():\n if event.type == pygame.KEYDOWN and event.key == pygame.K_SPACE:\n ... | [
1,
2,
3,
4,
5
] |
__author__ = 'Administrator'
import socket,os,time
server = socket.socket()
server.bind(("localhost",9999))
server.listen()
while True:
conn,addr = server.accept()
while True:
data = conn.recv(1024)
if not data:
break
cmd,filename = data.decode().split()
if o... | normal | {
"blob_id": "0a19efea0c8d7e5e248ca3265ffcb55604dc500c",
"index": 7576,
"step-1": "__author__ = 'Administrator'\n\nimport socket,os,time\n\nserver = socket.socket()\n\nserver.bind((\"localhost\",9999))\n\nserver.listen()\n\nwhile True:\n conn,addr = server.accept()\n\n while True:\n data = conn.recv... | [
0
] |
<|reserved_special_token_0|>
class _spectra:
def __init__(self, x, y):
self.x = x
self.y = y
<|reserved_special_token_0|>
def y(self):
return intensities
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class _spectra:
def __init_... | flexible | {
"blob_id": "8f5d9918260e2f50fb229a7067f820a186101b99",
"index": 1080,
"step-1": "<mask token>\n\n\nclass _spectra:\n\n def __init__(self, x, y):\n self.x = x\n self.y = y\n <mask token>\n\n def y(self):\n return intensities\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass... | [
3,
5,
6,
8,
11
] |
from datetime import datetime
import struct
BEACON_LENGTH = 84
EPS_LENGTH = 20
COM_LENGTH = 10
# reverse engineered
ADCS1_LENGTH = 7
ADCS2_LENGTH = 6
AIS_LENGTH = 20
class EPS(object):
def __init__(self, eps_data):
if len(eps_data) != EPS_LENGTH:
raise InputException(len(eps_data), EPS_LENGTH... | normal | {
"blob_id": "505689803c8f4490619ab1a7579fde1e2c18c538",
"index": 5532,
"step-1": "<mask token>\n\n\nclass ADCS2(object):\n\n def __init__(self, adcs2_data):\n self.gyro = tuple(struct.unpack('>hhh', adcs2_data))\n <mask token>\n\n\nclass AIS(object):\n\n def __init__(self, ais_data):\n sel... | [
8,
10,
19,
20,
21
] |
import requests
import json
l = list()
with open ( "token.txt", "r") as f:
token = f.read()
# создаем заголовок, содержащий наш токен
headers = {"X-Xapp-Token" : token}
with open('dataset_24476_4.txt', 'r') as id:
for line in id:
address = "https://api.artsy.net/api/artists/" +... | normal | {
"blob_id": "e1ecc08f66e094841647f72b78bcd29ed8d32668",
"index": 5976,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('token.txt', 'r') as f:\n token = f.read()\n headers = {'X-Xapp-Token': token}\n with open('dataset_24476_4.txt', 'r') as id:\n for line in id:\n addr... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def getTextWithoutSpaces(text):
withoutLineBreaks = text.replace('\n', '')
withoutSpaces = re.sub(' +', ' ', withoutLineBreaks)
return withoutSpaces
def getSentences(sentences, text):
data = re.findall('\\b[a-zA-Z]+|[.!?]', text)
unique_words = set(data)
sentence... | flexible | {
"blob_id": "6d7db5b9a64ec25763f5af6ceec1a46d629d549c",
"index": 472,
"step-1": "<mask token>\n\n\ndef getTextWithoutSpaces(text):\n withoutLineBreaks = text.replace('\\n', '')\n withoutSpaces = re.sub(' +', ' ', withoutLineBreaks)\n return withoutSpaces\n\n\ndef getSentences(sentences, text):\n data... | [
3,
5,
6,
7,
8
] |
from eums.test.api.api_test_helpers import create_option
from eums.test.factories.question_factory import MultipleChoiceQuestionFactory
from eums.test.api.authenticated_api_test_case import AuthenticatedAPITestCase
from eums.test.config import BACKEND_URL
from eums.models.question import MultipleChoiceQuestion
ENDPOI... | normal | {
"blob_id": "1152f144e17c11416f9ed56b4408f18615b16dc2",
"index": 5187,
"step-1": "<mask token>\n\n\nclass OptionsEndPointTest(AuthenticatedAPITestCase):\n <mask token>\n <mask token>\n\n\nclass ReceivedOptionsEndPointTest(AuthenticatedAPITestCase):\n\n def test_should_only_get_received_options(self):\n ... | [
7,
8,
9,
10,
12
] |
/Users/andreilyskov/anaconda/lib/python3.5/sre_compile.py | normal | {
"blob_id": "faf4f4d26236ac555594ef6913a0d43c3516f1f2",
"index": 2063,
"step-1": "/Users/andreilyskov/anaconda/lib/python3.5/sre_compile.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
#!/bin/python
import sys
import notify2
import subprocess
from time import sleep
def notification(message: str):
"""
Display notification to the desktop
Task:
1. show() -> it will generate a complete new pop
2. update() -> it will update the payload part of same notification pop-up, not is... | normal | {
"blob_id": "8a7904881d936a3cb421ed5550856b600894fcee",
"index": 5397,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef notification(message: str):\n \"\"\"\n Display notification to the desktop\n Task:\n 1. show() -> it will generate a complete new pop\n 2. update() -> it wi... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class MonthUnitTests(unittest.TestCase):
def test_header(self):
cal = Month(5, 2012)
result = cal.header()
self.assertEqual(' May 2012', result)
def test_header_different_month(self):
cal = Month(3, 2012)
result = cal.header()
... | flexible | {
"blob_id": "36c1d75171d772138b820651e11a3a7bc3a6521c",
"index": 8226,
"step-1": "<mask token>\n\n\nclass MonthUnitTests(unittest.TestCase):\n\n def test_header(self):\n cal = Month(5, 2012)\n result = cal.header()\n self.assertEqual(' May 2012', result)\n\n def test_header_differ... | [
13,
14,
15,
16,
17
] |
# encoding:UTF-8
# 题目：斐波那契数列。
def fib(n):
if n==1 or n==2:
return 1
return fib(n-1)+fib(n-2)
print (fib(10))
| normal | {
"blob_id": "59376f6565cd72e20087609253a41c04c6327a27",
"index": 6324,
"step-1": "<mask token>\n",
"step-2": "def fib(n):\n if n == 1 or n == 2:\n return 1\n return fib(n - 1) + fib(n - 2)\n\n\n<mask token>\n",
"step-3": "def fib(n):\n if n == 1 or n == 2:\n return 1\n return fib(n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db_handle.drop_database(DB_NAME)
<|reserved_special_token_0|>
with open(RELATIVE_CONFIG_PATH + USER_COLLECTION + '.csv', 'r') as user_fh:
for user_row in user_fh:
user_row = user_row.rstrip()
if user_row:
... | flexible | {
"blob_id": "a8b1b218e6649545000803c91c803580cfdbd4f1",
"index": 459,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb_handle.drop_database(DB_NAME)\n<mask token>\nwith open(RELATIVE_CONFIG_PATH + USER_COLLECTION + '.csv', 'r') as user_fh:\n for user_row in user_fh:\n user_row = user_row.rstri... | [
0,
1,
2,
3,
4
] |
from settings import *
helpMessage = '''
**Vocal / Musique**
`{0}join`
Va rejoindre le salon vocale dans laquelle vous êtes.
`{0}leave`
Va partir du salon vocale dans laquelle vous êtes.
`{0}play [YouTube Url]` *ou* `{0}play [musique ou video à rechercher]`
Commencera à jouer l'audio de la vidéo / chans... | normal | {
"blob_id": "f7283750923e1e430ff1f648878bbb9a0c73d2c4",
"index": 7880,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nhelpMessage = (\n \"\"\"\n**Vocal / Musique**\n\n`{0}join`\nVa rejoindre le salon vocale dans laquelle vous êtes.\n\n`{0}leave`\nVa partir du salon vocale dans laquelle vous êtes.\n\n`... | [
0,
1,
2,
3
] |
import pickle
import select
import socket
import sys
from threading import Thread
from typing import Dict, Tuple
import pygame
from pygame.locals import *
import c
from models import *
class Game:
location: list[int, int] = [c.WIDTH / 2, c.HEIGHT / 2]
velocity: list[int, int] = [0, 0]
current_player: Pl... | normal | {
"blob_id": "418798369578e80ecbf82da802b23dc6ca922569",
"index": 7107,
"step-1": "<mask token>\n\n\nclass Game:\n location: list[int, int] = [c.WIDTH / 2, c.HEIGHT / 2]\n velocity: list[int, int] = [0, 0]\n current_player: Player = None\n other_players: Dict[str, Tuple[Player, Tuple[int, int]]] = {}\... | [
10,
11,
12,
14,
15
] |
#--------------------------------------------------------------------------------
# G e n e r a l I n f o r m a t i o n
#--------------------------------------------------------------------------------
# Name: Exercise 2.6 - Planetary Orbits
#
# Usage: Calculate information for planetary orbits
#
# Description: ... | normal | {
"blob_id": "83b65b951b06b117c2e85ba348e9b591865c1c2e",
"index": 3145,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('v2: {0}\\tL2: {1}'.format(v2, L2))\n<mask token>\nprint('T: {0}\\te:{1}'.format(T, e))\n",
"step-3": "L1 = float(input('Enter distance to the sun: '))\nv1 = float(input('Enter ve... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_timestamp_from_interval(interval_number):
return interval_number * interval_length_minutes * 60
def get_datetime_from_utc_timestamp(utc_timestamp):
return datetime.datetime.utcfromtimestamp(utc_timestamp).replace(tzinfo
=datetime.timezone.utc)
<|reserved_specia... | flexible | {
"blob_id": "f3bfa30f51c4a91844457c72fbf2b2b8368d8476",
"index": 1874,
"step-1": "<mask token>\n\n\ndef get_timestamp_from_interval(interval_number):\n return interval_number * interval_length_minutes * 60\n\n\ndef get_datetime_from_utc_timestamp(utc_timestamp):\n return datetime.datetime.utcfromtimestamp(... | [
2,
3,
4,
5,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^porta/list$', porta_list, name='porta_list'), url(
'^porta/detail/(?P<pk>\\d+)$', porta_detail, name='porta_detail'), url(
'^porta/new/$', porta_new, name='porta_new'), url(
'^porta/update/(?P<pk>\... | flexible | {
"blob_id": "5e355732f07029aa644617ac9b5e9ad50ee9397f",
"index": 1161,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^porta/list$', porta_list, name='porta_list'), url(\n '^porta/detail/(?P<pk>\\\\d+)$', porta_detail, name='porta_detail'), url(\n '^porta/new/$', porta_new, name... | [
0,
1,
2,
3
] |
import sys
a = 3
b = 4
c = 5.66
d = 8.0
e = complex(c,d)
f = complex(float(a),float(b))
print("a is type:",type(a))
print("c is type:",type(c))
print("e is type:",type(e))
print(a + b)
print(d / c)
print(b / a)
#2个除约成整型
print(b // a)
print(e)
print(e + f)
print(sys.float_info) | normal | {
"blob_id": "2876c9f8db0395143b165b855b22e364e3cc8121",
"index": 9008,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('a is type:', type(a))\nprint('c is type:', type(c))\nprint('e is type:', type(e))\nprint(a + b)\nprint(d / c)\nprint(b / a)\nprint(b // a)\nprint(e)\nprint(e + f)\nprint(sys.float_... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_body() ->None:
for func in (weight, shower, food, water):
assert ilen(func()) >= 1
<|reserved_special_token_1|>
from more_itertools import ilen
from my.body import weight, shower, food, water
def test_b... | flexible | {
"blob_id": "e06b740f27e41b9f120c962fd76a38a29d54af3c",
"index": 973,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_body() ->None:\n for func in (weight, shower, food, water):\n assert ilen(func()) >= 1\n",
"step-3": "from more_itertools import ilen\nfrom my.body import weight, ... | [
0,
1,
2
] |
from models import Cell,Board
import random
from pdb import set_trace as bp
status={'end':-1}
game=None
class Game_Service(object):
def __init__(self,row_num,col_num):
self._row_num=row_num
self._col_num=col_num
mine_percent=0.3
self._mine_num=int(mine_percent*float(self._row_nu... | normal | {
"blob_id": "4af72cab6444922ca66641a08d45bcfe5a689844",
"index": 6763,
"step-1": "<mask token>\n\n\nclass Game_Service(object):\n\n def __init__(self, row_num, col_num):\n self._row_num = row_num\n self._col_num = col_num\n mine_percent = 0.3\n self._mine_num = int(mine_percent * f... | [
5,
6,
7,
9,
10
] |
<|reserved_special_token_0|>
class Place(models.Model):
name = models.CharField(max_length=50)
address = models.CharField(max_length=80)
def __str__(self):
return self.name
class Restaurant(models.Model):
place = models.OneToOneField(Place, on_delete=models.CASCADE,
primary_key=True... | flexible | {
"blob_id": "8afce5b47c7c9c67a8be493f7f4de1510352b1c7",
"index": 4559,
"step-1": "<mask token>\n\n\nclass Place(models.Model):\n name = models.CharField(max_length=50)\n address = models.CharField(max_length=80)\n\n def __str__(self):\n return self.name\n\n\nclass Restaurant(models.Model):\n p... | [
10,
12,
16,
17,
21
] |
from keras.models import load_model
from DataManager import *
def loadModel(name):
model = load_model('./Model/%s.h5' % name)
return model
def predict(tag):
test = getPIData(tag, '2019-11-05', '2019-11-06')
test_arg = addFeature(test)
test_norm = normalize(test_arg)
X_test, Y_test = buildTra... | normal | {
"blob_id": "a6154c5d855dc53d73db08bbb5b5d7437056e156",
"index": 1566,
"step-1": "<mask token>\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n return model\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef loadModel(name):\n model = load_model('./Model/%s.h5' % name)\n ... | [
1,
2,
3,
4
] |
ID = '113'
TITLE = 'Path Sum II'
DIFFICULTY = 'Medium'
URL = 'https://oj.leetcode.com/problems/path-sum-ii/'
BOOK = False
PROBLEM = r"""Given a binary tree and a sum, find all root-to-leaf paths where each path's
sum equals the given sum.
For example:
Given the below binary tree and `sum = 22`,
... | normal | {
"blob_id": "9a62a57f6d9af7ef09c8ed6e78a100df7978da6e",
"index": 8631,
"step-1": "<mask token>\n",
"step-2": "ID = '113'\nTITLE = 'Path Sum II'\nDIFFICULTY = 'Medium'\nURL = 'https://oj.leetcode.com/problems/path-sum-ii/'\nBOOK = False\nPROBLEM = \"\"\"Given a binary tree and a sum, find all root-to-leaf paths... | [
0,
1,
2
] |
def printPar():
for i in range(len(par)):
print "par[{0:d}] = {1:d}".format(i,par[i])
def printImpar():
for i in range(len(impar)):
print "impar[{0:d}] = {1:d}".format(i,impar[i])
par = []
impar = []
for i in range(15):
n= int(raw_input())
if n%2 == 0:
if len(par)<4:
... | normal | {
"blob_id": "7e33475a6ab7ad0d1e9d7d00b8443329e265fe69",
"index": 6793,
"step-1": "def printPar():\n for i in range(len(par)):\n print \"par[{0:d}] = {1:d}\".format(i,par[i])\ndef printImpar():\n for i in range(len(impar)):\n print \"impar[{0:d}] = {1:d}\".format(i,impar[i])\npar = []\nimpar =... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
default_args = {'owner': 'Jaimin', 'depends_on_past': False, 'start_date':
datetime.now(), 'email': ['airflow@airflow.com'], 'email_on_failure':
False, 'email_on_retry': False, 'retries': 1, 'retry_delay': timedelta(
... | flexible | {
"blob_id": "49492ad1a1734be02ebefb77095fd560a7a7efd8",
"index": 7155,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndefault_args = {'owner': 'Jaimin', 'depends_on_past': False, 'start_date':\n datetime.now(), 'email': ['airflow@airflow.com'], 'email_on_failure': \n False, 'email_on_retry': False,... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def find_jobs():
html_text = requests.get(
'https://www.timesjobs.com/candidate/job-search.html?searchType=personalizedSearch&from=submit&txtKeywords=python&txtLocation='
).text
soup = BeautifulSoup(html_text, 'lxml')
jobs = soup.find_all('li', class_='clearfix... | flexible | {
"blob_id": "92b71c67130cd37b2143fbd9ad71fe9a18b3f7e8",
"index": 2622,
"step-1": "<mask token>\n\n\ndef find_jobs():\n html_text = requests.get(\n 'https://www.timesjobs.com/candidate/job-search.html?searchType=personalizedSearch&from=submit&txtKeywords=python&txtLocation='\n ).text\n soup = ... | [
1,
2,
3,
4,
5
] |
import random
import torch
import numpy as np
from torch.autograd import Variable
class SupportSetManager(object):
FIXED_FIRST = 0
RANDOM = 1
def __init__(self, datasets, config, sample_per_class):
self.config = config
(TEXT, LABEL, train, dev, test) = datasets[0]
self.TEXT = TEXT
... | normal | {
"blob_id": "13a2814e8744c6c09906d790185ed44fc2b3f23e",
"index": 3642,
"step-1": "<mask token>\n\n\nclass SupportSetManager(object):\n <mask token>\n <mask token>\n\n def __init__(self, datasets, config, sample_per_class):\n self.config = config\n TEXT, LABEL, train, dev, test = datasets[0... | [
6,
8,
9,
10,
12
] |
# -*- coding: utf-8 -*-
#COMECE AQUI ABAIXO
p1=float(input('digite o p1:'))
c1=float(input('digite o c1:'))
p2=float(input('digite o p2:'))
c2=float(input('digite o c2:'))
if p1*c1=p2*c2:
print('O')
if pi*c1>p2*c2:
print('-1')
else:
print('1') | normal | {
"blob_id": "210fcb497334ad8bf5433b917fc199c3e22f0f6e",
"index": 6978,
"step-1": "# -*- coding: utf-8 -*-\n#COMECE AQUI ABAIXO\n\np1=float(input('digite o p1:'))\nc1=float(input('digite o c1:'))\np2=float(input('digite o p2:'))\nc2=float(input('digite o c2:'))\n\nif p1*c1=p2*c2:\n print('O')\n\nif pi*c1>p2*c2... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
bind = '0.0.0.0:' + str(os.environ.get('MAESTRO_PORT', 5005))
workers = os.environ.get('MAESTRO_GWORKERS', 2)
<|reserved_special_token_1|>
import os
bind = '0.0.0.0:' + str(os.environ.get('MAESTRO_PORT', 5005))
workers = os.env... | flexible | {
"blob_id": "818e6842d4a1f8978ec14bca06981ec933c00376",
"index": 6280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbind = '0.0.0.0:' + str(os.environ.get('MAESTRO_PORT', 5005))\nworkers = os.environ.get('MAESTRO_GWORKERS', 2)\n",
"step-3": "import os\nbind = '0.0.0.0:' + str(os.environ.get('MAESTRO_... | [
0,
1,
2,
3
] |
from django import forms
from django.forms import ModelForm, fields, widgets
from .models import NewsStory
class StoryForm(ModelForm):
class Meta:
model = NewsStory
fields = ['title' , 'pub_date' , 'content']
widgets = {
'pub_date': forms.DateInput(format=('%m/%d/%Y'), attrs={'c... | normal | {
"blob_id": "47a5ddcea2f6d8ce80793192d26c98ccc0e0340d",
"index": 1771,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass StoryForm(ModelForm):\n\n\n class Meta:\n model = NewsStory\n fields = ['title', 'pub_date', 'content']\n widgets = {'pub_date': forms.DateInput(format='... | [
0,
1,
2,
3
] |
import requests
import json, csv
import pandas as pd
API_KEY = 'AIzaSyALrKc3-W0u_Ku-J2OpyjnqFhV5wKlwKGs'
list_video_id = ['7cmvABXyUC0', '9eH-7x7swEM', 'JndzGxbwvG0', 'l0P5_E6J_g0']
fieldnames = ['videoid', 'viewCount', 'likeCount', 'dislikeCount', 'favoriteCount', 'commentCount']
rows = []
for video_id in list_video_... | normal | {
"blob_id": "3c341b17f260cc745c8659ee769493216522ac19",
"index": 2073,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor video_id in list_video_id:\n url = ('https://www.googleapis.com/youtube/v3/videos?id=' + video_id +\n '&part=statistics&key=' + API_KEY)\n response = requests.get(url).js... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
import sys
sys.path.insert(0, '../../common/python/')
from primality import prime_factors
"""
phi(n) = n*sum_{p|n} (1 - 1/p)
1/phi(n) = (1/n)*sum_{p|n} p/(p - 1)
n/phi(n) = sum_{p|n} p/(p - 1)
"""
def n_over_phi(n):
top = 1
bot = 1
pfactors = prime_factors(n)
for p, count i... | normal | {
"blob_id": "2d248ac1df1845bc5a2ee62a7171c1c47ca6d0ca",
"index": 3665,
"step-1": "<mask token>\n\n\ndef n_over_phi(n):\n top = 1\n bot = 1\n pfactors = prime_factors(n)\n for p, count in pfactors.items():\n top *= p\n bot *= p - 1\n return top / bot\n\n\ndef maximise_n_over_phi(upto)... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
np.random.seed(5)
<|reserved_special_token_0|>
model.add(Dense(64, input_dim=input_data_number, activation='relu'))
model.add(Dense(64, activation='relu'))
model.add(Dense(7, activation='softmax'))
model.compile(optimizer='adam', ... | flexible | {
"blob_id": "bfa5739949c26758e3762fcff8347d23ad70f704",
"index": 6114,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.random.seed(5)\n<mask token>\nmodel.add(Dense(64, input_dim=input_data_number, activation='relu'))\nmodel.add(Dense(64, activation='relu'))\nmodel.add(Dense(7, activation='softmax'))\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def getLettercount(mess):
charcount = getCanditatemap()
for char in mess:
if char in charcount:
charcount[char] += 1
return charcount
<|reserved_special_token_0|>
def englishFreqMatch(message):
matchscore = 0
freqOrder = getFreqOrder(message.low... | flexible | {
"blob_id": "63a9060e9933cc37b7039833be5f071cc7bf45bf",
"index": 7873,
"step-1": "<mask token>\n\n\ndef getLettercount(mess):\n charcount = getCanditatemap()\n for char in mess:\n if char in charcount:\n charcount[char] += 1\n return charcount\n\n\n<mask token>\n\n\ndef englishFreqMatc... | [
2,
3,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def oddCells(self, m, n, indices):
"""
:type m: int
:type n: int
:type indices: List[List[int]]
:rtyp... | flexible | {
"blob_id": "148b849ae43617dde8dbb0c949defa2f390ce5cd",
"index": 9902,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def oddCells(self, m, n, indices):\n \"\"\"\n :type m: int\n :type n: int\n :type i... | [
0,
1,
2
] |
import tkinter.ttk
import tkinter as tk
def update_info(info_t, data):
# temp = info_t.selection_set("x")
# print(temp)
# info_t.delete(temp)
# temp = info_t.selection_set("y")
# info_t.delete(temp)
pass
def path_to_string(s):
res = ""
for i in range(len(s)-1):
res += str(s[i... | normal | {
"blob_id": "a4d47b9a28ec66f6a0473498674ebc538d909519",
"index": 5111,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef path_to_string(s):\n res = ''\n for i in range(len(s) - 1):\n res += str(s[i][0])\n res += ', '\n res += str(s[i][1])\n res += ' > '\n res += ... | [
0,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(libras)
<|reserved_special_token_1|>
quilogramas = float(input('Insira o peso em Kg:'))
libras = quilogramas / 0, 45
print(libras)
<|reserved_special_token_1|>
quilogramas = float ( input ( "Insira o peso em Kg:" ))
... | flexible | {
"blob_id": "9c35e64fd773c79dc20e6b388478e892bda85788",
"index": 1599,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(libras)\n",
"step-3": "quilogramas = float(input('Insira o peso em Kg:'))\nlibras = quilogramas / 0, 45\nprint(libras)\n",
"step-4": "quilogramas = float ( input ( \"Insira o ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def request_dyn():
logger.info('dyn: 开始测试请求')
postUrl = '%s/raframework/browse/dyn' % serverUrl
postData = {'page': '/conf/CDSConfig.jsp', 'amp': '', 'action':
'returnXML', 'LOCALE_LANGUAGE': 'en_US', 'rightToLeft': 'false',
'accessibilityMode': 'false', 'theme... | flexible | {
"blob_id": "c5d92ec592250d5bc896d32941364b92ff1d21e9",
"index": 3793,
"step-1": "<mask token>\n\n\ndef request_dyn():\n logger.info('dyn: 开始测试请求')\n postUrl = '%s/raframework/browse/dyn' % serverUrl\n postData = {'page': '/conf/CDSConfig.jsp', 'amp': '', 'action':\n 'returnXML', 'LOCALE_LANGUAGE... | [
3,
5,
6,
8,
9
] |
from external.odds.betclic.api import get_odds
# FDJ parsing is broken - their UI has been refactored with JS framework &
# protected async JSON API usage (requires HEADERS) and more complex to isolate & group match odds
# hence move to another betting website - which is still full html rendered
| normal | {
"blob_id": "8b583ee55df409020a605b467479236e610a2efe",
"index": 3646,
"step-1": "<mask token>\n",
"step-2": "from external.odds.betclic.api import get_odds\n",
"step-3": "from external.odds.betclic.api import get_odds\n\n# FDJ parsing is broken - their UI has been refactored with JS framework &\n# protected... | [
0,
1,
2
] |
# -*- encoding: utf-8 -*-
from django.conf.urls import patterns, url
urlpatterns = patterns('apps.profiles.views',
url(r'^$', 'index', name='profiles'),
# Show a specific profile.
url(r'^view/(?P<username>[a-zA-Z0-9_-]+)/$', 'view_profile', name='profiles_view'),
url(r'^edit/$', 'edit_profile', name... | normal | {
"blob_id": "5707e24596dfe2d85e9a7caa93aa3e253a41ae40",
"index": 6620,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('apps.profiles.views', url('^$', 'index', name=\n 'profiles'), url('^view/(?P<username>[a-zA-Z0-9_-]+)/$', 'view_profile',\n name='profiles_view'), url('^edit... | [
0,
1,
2,
3
] |
# 4, [[1,0],[2,0],[3,1],[3,2]]
# 3->1->0
# \ ^
# \ |
# \> 2
# 1,0,2,3
# stack 3
#
# 0 1 2 3
# 1,0
# stack 1
# 0
#
# def findOrder(numCourses, prerequisites):
# if len(prerequisites) == 0:
# order = []
# for i in range(0, numCourses):
# order.append(i)
# return or... | normal | {
"blob_id": "56892e125934d5de937b92a08bd7707c12c70928",
"index": 689,
"step-1": "<mask token>\n",
"step-2": "def findOrder(numCourses, prerequisites):\n if len(prerequisites) == 0:\n order = []\n for i in range(0, numCourses):\n order.append(i)\n return order\n edges = {}\... | [
0,
1,
2,
3
] |
# Generated by Django 2.1.7 on 2020-01-09 08:19
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('goods', '0004_auto_20200109_0713'),
]
operations = [
migrations.AlterField(
model_name='banner',
name='show_type',
... | normal | {
"blob_id": "b7687240413441e1d3ed0085e5953f8089cbf4c9",
"index": 9303,
"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 = [('goods', '00... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
class FizzBuzz:
def convert(self, number):
# raise NotImplementedError
# for number in range(1, 101):
if number%3 == 0 and number%5 != 0:
return ("Fizz")
elif number%3 != 0 and number%5 == 0:
return("Buzz")
... | normal | {
"blob_id": "fb9d639bca59ecb081e7d9f30f97bdcd35627d34",
"index": 6124,
"step-1": "<mask token>\n",
"step-2": "class FizzBuzz:\n <mask token>\n",
"step-3": "class FizzBuzz:\n\n def convert(self, number):\n if number % 3 == 0 and number % 5 != 0:\n return 'Fizz'\n elif number % 3... | [
0,
1,
2,
3
] |
# Author: Charse
# py 列表的使用
import copy
name = ["111", "222", "333", "444", "555"]
# 从列表中取得元素
print(name[0], name[2]) # 111 333
print(name[1:3]) # 切片 ['222', '333']
print(name[:3]) # ['111', '222', '333'] 与下标从0开始是一样的
print(name[0:3]) # ['111', '222', '333']
print(name[-2:]) # ['444', '555'] 与name
# 往列表中添加... | normal | {
"blob_id": "d517c1e2eb4d37a2584f1603c704efce6834df92",
"index": 7443,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(name[0], name[2])\nprint(name[1:3])\nprint(name[:3])\nprint(name[0:3])\nprint(name[-2:])\nname.append('666')\nname.insert(1, '999')\nprint(name)\n<mask token>\nprint(name)\nname.pop... | [
0,
1,
2,
3,
4
] |
from django import forms
from .models import Recipe, Ingredient, Category, Tag
from blog.widgets import CustomClearableFileInput
class NewCategoriesForm(forms.ModelForm):
friendly_name = forms.CharField(label='... or add your own category',
required=False)
class Meta():
... | normal | {
"blob_id": "7484bd9012bc9952b679073ae036de4554d362be",
"index": 5175,
"step-1": "<mask token>\n\n\nclass IngredientForm(forms.ModelForm):\n\n\n class Meta:\n model = Ingredient\n exclude = 'recipe',\n labels = {'quantity': 'Qty'}\n\n def __init__(self, *args, **kwargs):\n super... | [
6,
7,
9,
12,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .slinklist import SingleLinkedList
| flexible | {
"blob_id": "2a5d498a386190bdd2c05bc2b14db0fecd707162",
"index": 1128,
"step-1": "<mask token>\n",
"step-2": "from .slinklist import SingleLinkedList\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# coding=utf-8
# Copyright 2019 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | normal | {
"blob_id": "f253816d08407950caad28f1ce630ac2b099aa70",
"index": 3241,
"step-1": "<mask token>\n\n\ndef make_experiment_dir(postfix):\n home = os.path.expanduser('~')\n exp_dir = os.path.join(home, postfix)\n mkdir_p(exp_dir)\n return exp_dir\n\n\ndef save_fig(folder, filename):\n if folder is Non... | [
10,
12,
13,
14,
16
] |
def fibonacci(num):
f_1 = 0
f_2 = 1
answer = 0
for i in range(num-1):
answer = f_1 + f_2
f_1 = f_2
f_2 = answer
return answer
# 아래는 테스트로 출력해 보기 위한 코드입니다.
print(fibonacci(3))
| normal | {
"blob_id": "c3d0a9bdbfd5b6f2b960ee2c1f11ec4acf508310",
"index": 8458,
"step-1": "<mask token>\n",
"step-2": "def fibonacci(num):\n f_1 = 0\n f_2 = 1\n answer = 0\n for i in range(num - 1):\n answer = f_1 + f_2\n f_1 = f_2\n f_2 = answer\n return answer\n\n\n<mask token>\n",... | [
0,
1,
2,
3
] |
function handler(event, context, callback){
var
AWS = require("aws-sdk"),
DDB = new AWS.DynamoDB({
apiVersion: "2012-08-10",
region: "us-east-1"
}),
city_str = event.city_str.toUpperCase(),
data = {
city_str: city_str,
... | normal | {
"blob_id": "7bac3b224586f8c42a104123432a7321a1251369",
"index": 7115,
"step-1": "function handler(event, context, callback){\r\n var \r\n AWS = require(\"aws-sdk\"),\r\n DDB = new AWS.DynamoDB({\r\n apiVersion: \"2012-08-10\",\r\n region: \"us-east-1\"\r\n }),\r\n ... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
try:
img = cv.imread(imgpath)
newimg1 = jarvis_judice_ninke_1(img) * 255
newimg2 = jarvis_judice_ninke_2(img) * 255
cv.imshow('Imagem original', img)
cv.imshow('Jarvis, Judice e Ninke metodo 1', newimg1)
cv... | flexible | {
"blob_id": "bf764457e6af25d2d9406b18af51f63b36ab823a",
"index": 8564,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n img = cv.imread(imgpath)\n newimg1 = jarvis_judice_ninke_1(img) * 255\n newimg2 = jarvis_judice_ninke_2(img) * 255\n cv.imshow('Imagem original', img)\n cv.imshow('J... | [
0,
1,
2,
3,
4
] |
from django.forms import ModelForm, ChoiceField, Form, FileField, ModelChoiceField, HiddenInput, ValidationError
from market.models import *
class OrderForm(ModelForm):
"""Order form used in trader view."""
# from http://stackoverflow.com/questions/1697702/how-to-pass-initial-parameter-to-djangos-modelform-ins... | normal | {
"blob_id": "044e3479c32357e22ca3165d8601d8bd2a439fcb",
"index": 2329,
"step-1": "<mask token>\n\n\nclass OrderForm(ModelForm):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n model = Order\n fields = 'stock', 'order... | [
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@admin.register(User)
class AuthorizationUserAdmin(admin.ModelAdmin):
<|reserved_special_token_0|>
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@admin.register(User)
class AuthorizationUserAdmin(ad... | flexible | {
"blob_id": "d3585e7b761fa7b2eeaacf09f84bb6a4abc1cf02",
"index": 6806,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@admin.register(User)\nclass AuthorizationUserAdmin(admin.ModelAdmin):\n <mask token>\n pass\n",
"step-3": "<mask token>\n\n\n@admin.register(User)\nclass AuthorizationUserAdm... | [
0,
1,
2,
3,
4
] |
import math as m
import functions_by_alexandra as fba
import funs
from functions_by_alexandra import User, a
from pkg import bps, geom
print(type(funs))
print(type(funs.add ))
#
# print(add(2,3))
print("Result: ", funs.add(10, 20))
print("Result: ", fba.add(10,20))
print(type(fba ))
print(a )
print(m... | normal | {
"blob_id": "b53b0e6ff14750bbba3c2e5e2ea2fc5bb1abccec",
"index": 3135,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(type(funs))\nprint(type(funs.add))\nprint('Result: ', funs.add(10, 20))\nprint('Result: ', fba.add(10, 20))\nprint(type(fba))\nprint(a)\nprint(m.pi)\n<mask token>\nprint(p)\nprint(b... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
#-*- coding : utf-8 -*-
import string
import keyword
alphas = string.letters + '_'
nums = string.digits
keywords = keyword.kwlist
checklst = alphas + nums
print 'Welcome to the Identifier Checker v1.0'
myInput = raw_input('Identifier to test? ')
if myInput in keywords:
print 'Okay as a keywor... | normal | {
"blob_id": "2420c835ff91c1269cb16fca2e60e191e1e8ce13",
"index": 6457,
"step-1": "#!/usr/bin/env python\n#-*- coding : utf-8 -*-\n\nimport string\nimport keyword\n\nalphas = string.letters + '_'\nnums = string.digits\nkeywords = keyword.kwlist\nchecklst = alphas + nums\n\nprint 'Welcome to the Identifier Checker... | [
0
] |
import os
import sys
import time
import json
import socket
from urllib import request, parse
from concurrent.futures import ThreadPoolExecutor
from multiprocessing import Process
import psutil
from daemon import DaemonBase
from host_performence import *
class MyDaemon(DaemonBase):
"""Real Daemon class"""
d... | normal | {
"blob_id": "6e253747182716f84aa6326aafe15ff82be17378",
"index": 1351,
"step-1": "<mask token>\n\n\nclass MyDaemon(DaemonBase):\n <mask token>\n\n def __init__(self, api_url, monitor_port, pidfile, stdin='/dev/null',\n stdout='/dev/null', stderr='/dev/null'):\n self.api_url = api_url\n ... | [
4,
5,
7,
8,
9
] |
<|reserved_special_token_0|>
class WindowFeatureExtractor(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def transform(self, X, y=None):
return self.vectorizer.transform(X, y)
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "48677d73f6489ce789884a9dff5d50c23f47d8b3",
"index": 260,
"step-1": "<mask token>\n\n\nclass WindowFeatureExtractor(object):\n <mask token>\n <mask token>\n <mask token>\n\n def transform(self, X, y=None):\n return self.vectorizer.transform(X, y)\n <mask token>\n <mask token>... | [
2,
7,
8,
9,
10
] |
""" Soil and water decomposition rates """
import math
from water_balance import WaterBalance
from utilities import float_eq, float_lt, float_le, float_gt, float_ge, clip
__author__ = "Martin De Kauwe"
__version__ = "1.0 (25.02.2011)"
__email__ = "mdekauwe@gmail.com"
class DecompFactors(object):
""" Calcula... | normal | {
"blob_id": "74f3b4001a0520a25a314ff537719b679ba0fca4",
"index": 2578,
"step-1": "<mask token>\n\n\nclass DecompFactors(object):\n <mask token>\n\n def __init__(self, control, params, state, fluxes, met_data):\n \"\"\"\n Parameters\n ----------\n control : integers, structure\n ... | [
2,
5,
6,
7,
8
] |
from django.db import models
from django.contrib.auth.models import User, Group
from userena.models import UserenaBaseProfile
from django.db.models.signals import post_save
from tastypie.models import create_api_key
class UserProfile(UserenaBaseProfile):
# user reference
user = models.OneToOneField(User)
... | normal | {
"blob_id": "6e6f153857879da625f57f0382f1997fcae4f6c8",
"index": 6041,
"step-1": "<mask token>\n\n\nclass UserProfile(UserenaBaseProfile):\n user = models.OneToOneField(User)\n facebook_id = models.CharField(max_length=128, blank=True, null=True)\n\n\n class Meta:\n permissions = ('change_profile... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def connect(hostip=hostip, hostport=hostport):
server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
IP_address = hostip
Port = hostport
server.connect((IP_address, Port))
return server
def terminal_mode():
server = connect()
server.send(bytes('Connected... | flexible | {
"blob_id": "5cdf8cd4bfebb9aab2e8f421047fc1ba3190d566",
"index": 3451,
"step-1": "<mask token>\n\n\ndef connect(hostip=hostip, hostport=hostport):\n server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n IP_address = hostip\n Port = hostport\n server.connect((IP_address, Port))\n return serv... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def _insert_grace_notes(song):
for phrase in song.phrases:
for pe in phrase.phrase_elements:
if type(pe) != Segment:
continue
segment = pe
initial_len = len(segment... | flexible | {
"blob_id": "ac83d7d39319c08c35302abfb312ebee463b75b2",
"index": 5130,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef _insert_grace_notes(song):\n for phrase in song.phrases:\n for pe in phrase.phrase_elements:\n if type(pe) != Segment:\n continue\n ... | [
0,
1,
3,
4,
6
] |
numbers = [1, 1, 1, 1, 1]
new_numbers = [2, 2, 2, 3, 3]
print(numbers + new_numbers)
print(numbers * 5)
| normal | {
"blob_id": "843df062702c9abf34cf14d911d927d786f1d912",
"index": 1573,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(numbers + new_numbers)\nprint(numbers * 5)\n",
"step-3": "numbers = [1, 1, 1, 1, 1]\nnew_numbers = [2, 2, 2, 3, 3]\nprint(numbers + new_numbers)\nprint(numbers * 5)\n",
"step-4"... | [
0,
1,
2
] |
import os, re
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': ':memory:'
}
}
INSTALLED_APPS = (
'django.contrib.auth',
'django.contrib.admin',
'django.contrib.sessions',
'django.contrib.contenttypes',
'django.contrib.sites',
'maintenancemode'... | normal | {
"blob_id": "34ecf2bd9bc72a98aba4584880a198dd24899dbe",
"index": 6218,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nDATABASES = {'default': {'ENGINE': 'django.db.backends.sqlite3', 'NAME':\n ':memory:'}}\nINSTALLED_APPS = ('django.contrib.auth', 'django.contrib.admin',\n 'django.contrib.sessions'... | [
0,
1,
2,
3
] |
import requests
import datetime
import time
from tqdm import tqdm
import json
import logging
logging.basicConfig(filename='logo.log', level=logging.DEBUG, filemode='w')
logging.debug('debug message')
logging.info('info message')
# from pprint import pprint
id_vk = input('введите id пользователя вк: ')
token_vk = input... | normal | {
"blob_id": "a22bc3bdb5e35060eff7f523b90d605ff2dd3878",
"index": 9581,
"step-1": "<mask token>\n\n\ndef ya_headers():\n return {'Content-type': 'application/json', 'Authorization': 'OAuth {}'\n .format(token_ya)}\n\n\ndef put_folder(path):\n url = 'https://cloud-api.yandex.net/v1/disk/resources/'\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
@implementer(IMicrosite)
class Microsite(Container):
<|reserved_special_token_0|>
def getLocallyAllowedTypes(self):
"""
By now we allow all allowed types without constrain.
TODO: fully implement ISelectableConstrainTypes
"""
portal_types = ... | flexible | {
"blob_id": "3d5d88edca5d746b830363cc9451bda94c1d7aa4",
"index": 2905,
"step-1": "<mask token>\n\n\n@implementer(IMicrosite)\nclass Microsite(Container):\n <mask token>\n\n def getLocallyAllowedTypes(self):\n \"\"\"\n By now we allow all allowed types without constrain.\n TODO: fully i... | [
2,
3,
4,
5,
6
] |
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
#loading data from CSV
training_data_df = pd.read_csv("sales_data_training.csv")
test_data_df = pd.read_csv("sales_data_test.csv")
#scaler
scaler = MinMaxScaler(feature_range=(0,1))
#scale both inputs and outputs
scaled_training = scaler.fit_transfor... | normal | {
"blob_id": "050e2207ac7331444d39305869c4b25bcbc53907",
"index": 244,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\n 'Note: total_earnings values were scaled by multiplying by {:.10f} and adding {:.6f}'\n .format(scaler.scale_[8], scaler.min_[8]))\n<mask token>\nscaled_training_df.to_csv('... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def canonicalize_name(name):
return _canonicalize_regex.sub('-', name).lower()
def page_index(packages):
yield PAGE_FMT
for p in packages:
name = p.name
url = name
yield ENTRY_FMT.format(url=canonicalize_name(p.name), name=name)
def page_package(pac... | flexible | {
"blob_id": "bd25b97de78f04510e43f13d356eb6c0025e223d",
"index": 8121,
"step-1": "<mask token>\n\n\ndef canonicalize_name(name):\n return _canonicalize_regex.sub('-', name).lower()\n\n\ndef page_index(packages):\n yield PAGE_FMT\n for p in packages:\n name = p.name\n url = name\n yi... | [
5,
6,
7,
8,
10
] |
<|reserved_special_token_0|>
def is_feasible(weights, flow, max_weight):
"""Test whether set of guessed weights is feasible."""
min_weights = [1] + weights
max_weights = [max_weight] + list(reversed(weights))
for i in range(1, len(min_weights)):
min_weights[i] = min_weights[i] if min_weights[i... | flexible | {
"blob_id": "1b4c9841fd10d065983974e93fe5dcbe048c1281",
"index": 4180,
"step-1": "<mask token>\n\n\ndef is_feasible(weights, flow, max_weight):\n \"\"\"Test whether set of guessed weights is feasible.\"\"\"\n min_weights = [1] + weights\n max_weights = [max_weight] + list(reversed(weights))\n for i i... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
u"""Hellweg execution template.
:copyright: Copyright (c) 2017 RadiaSoft LLC. All Rights Reserved.
:license: http://www.apache.org/licenses/LICENSE-2.0.html
"""
from __future__ import absolute_import, division, print_function
from pykern import pkcollections
from pykern import pkio
from pyker... | normal | {
"blob_id": "9e6fd6620b4ec6a574d7948fb0d14b0a2ad0d24e",
"index": 5240,
"step-1": "<mask token>\n\n\ndef background_percent_complete(report, run_dir, is_running):\n if is_running:\n return {'percentComplete': 0, 'frameCount': 0}\n dump_file = _dump_file(run_dir)\n if os.path.exists(dump_file):\n ... | [
22,
26,
32,
36,
37
] |
from django.contrib.auth.models import User
from rest_framework.serializers import ModelSerializer
from app_calendar.models import Holiday, Country, Event, User
class CountrySerializer(ModelSerializer):
class Meta:
model = Country
fields = '__all__'
class UserSerializer(ModelSerializer):
... | normal | {
"blob_id": "5b366b0f6813f686600df9da4a17f190f034a10c",
"index": 2046,
"step-1": "<mask token>\n\n\nclass EventSerializer(ModelSerializer):\n\n\n class Meta:\n model = Event\n fields = '__all__'\n\n\nclass HolidaySerializerRead(ModelSerializer):\n country = CountrySerializer()\n\n\n class ... | [
4,
5,
6,
7
] |
<|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": "1ce7b292f89fdf3f978c75d4cdf65b6991f71d6f",
"index": 7499,
"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 = [('core', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def index_page(url):
res = requests.get(url)
res.encoding = res.apparent_encoding
next_page(res.text)
def next_page(html):
data = json.loads(html)
for i in data['data']['list']:
img_url = i['cover']
img_name = i['title']
get_img(img_url, img_n... | flexible | {
"blob_id": "ff8b6bc607dac889da05b9f7e9b3595151153614",
"index": 7358,
"step-1": "<mask token>\n\n\ndef index_page(url):\n res = requests.get(url)\n res.encoding = res.apparent_encoding\n next_page(res.text)\n\n\ndef next_page(html):\n data = json.loads(html)\n for i in data['data']['list']:\n ... | [
3,
4,
5,
6,
7
] |
import logging
import argparse
import getpass
import errno
import re
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
import dns.resolver
class Mail(object):
def __init__(self, recipient=None, sender=None, subject=None, body=None):
self.recipient = recipi... | normal | {
"blob_id": "3a678f9b5274f008a510a23b2358fe2a506c3221",
"index": 4061,
"step-1": "<mask token>\n\n\nclass Mail(object):\n <mask token>\n <mask token>\n\n @property\n def message(self):\n m = MIMEMultipart('alternative')\n m['Subject'] = self.subject\n m['From'] = self.sender\n ... | [
5,
6,
7,
8,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
engine.setProperty('rate', 150)
<|reserved_special_token_0|>
print(rate)
<|reserved_special_token_0|>
while i < l:
engine.save_to_file(a[i], 'TTS/trump/{}.mp3'.format(str(i)))
engine.runAndWait()
if i + 3 < l:
... | flexible | {
"blob_id": "32f4f7ad61b99848c907e092c5ed7a839f0b352b",
"index": 6399,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nengine.setProperty('rate', 150)\n<mask token>\nprint(rate)\n<mask token>\nwhile i < l:\n engine.save_to_file(a[i], 'TTS/trump/{}.mp3'.format(str(i)))\n engine.runAndWait()\n if i... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ErrorReport:
<|reserved_special_token_0|>
def startLog(self):
timestamp = str(datetime.datetime.now())
fileName = 'Log_' + timestamp + '.txt.'
self.logFile = open(fileName, 'w')
def endLog(self):
self.logFile.close()
def writeError(... | flexible | {
"blob_id": "6abc8b97117257e16da1f7b730b09ee0f7bd4c6e",
"index": 4715,
"step-1": "<mask token>\n\n\nclass ErrorReport:\n <mask token>\n\n def startLog(self):\n timestamp = str(datetime.datetime.now())\n fileName = 'Log_' + timestamp + '.txt.'\n self.logFile = open(fileName, 'w')\n\n ... | [
4,
6,
7,
8,
9
] |
import numpy as np
import argparse
import torch
from gridworlds.envs import GridWorldEnv, generate_obs_dict
from gridworlds.constants import possible_objects
import nengo_spa as spa
from collections import OrderedDict
from spatial_semantic_pointers.utils import encode_point, ssp_to_loc, get_heatmap_vectors
import mat... | normal | {
"blob_id": "34a456efc72b303aed5f722bb415d30ff62addab",
"index": 7391,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.random.seed(seed)\n<mask token>\nnp.random.seed(params['seed'])\n<mask token>\nfor i in range(n_goals):\n sp_name = possible_objects[i]\n if use_dataset_goals:\n object_lo... | [
0,
1,
2,
3,
4
] |
def create_meme(word):
return f'this is your meme NEW VERSION {word}'
| normal | {
"blob_id": "32b3e65add5fb44320898b682e8f94f1460a32e7",
"index": 628,
"step-1": "<mask token>\n",
"step-2": "def create_meme(word):\n return f'this is your meme NEW VERSION {word}'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# -*- coding: utf-8 -*-
from celery import shared_task
from djcelery.models import PeriodicTask, CrontabSchedule
import datetime
from django.db.models import Max, Count
from services import *
# 测试任务
@shared_task()
def excute_sql(x,y):
print "%d * %d = %d" % (x, y, x * y)
return x * y
# 监控任务：查询数据库并进行告警
@sha... | normal | {
"blob_id": "6f259210cbe8969046cba1031ab42d77e913abea",
"index": 6265,
"step-1": "# -*- coding: utf-8 -*-\nfrom celery import shared_task\nfrom djcelery.models import PeriodicTask, CrontabSchedule\nimport datetime\nfrom django.db.models import Max, Count\n\nfrom services import *\n\n\n# 测试任务\n@shared_task()\ndef... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import BaggingClassifier
from sklearn.ensemble import RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
<|reserved_special_token_1|>
###
# This Python module cont... | flexible | {
"blob_id": "5029f3e2000c25d6044f93201c698773e310d452",
"index": 3391,
"step-1": "<mask token>\n",
"step-2": "from sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import BaggingClassifier\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.neighbors import KNeighborsClassifier\... | [
0,
1,
2
] |
def squirrel_play(temp, is_summer):
if is_summer == True:
if 60 <= temp <= 100:
return True
else:
return False
if is_summer == False:
if 60 <= temp <= 90:
return True
else:
return False
| normal | {
"blob_id": "48755cf48c6696259d0c319d382021f33751ac01",
"index": 9497,
"step-1": "<mask token>\n",
"step-2": "def squirrel_play(temp, is_summer):\n if is_summer == True:\n if 60 <= temp <= 100:\n return True\n else:\n return False\n if is_summer == False:\n if 6... | [
0,
1
] |
#!/usr/bin/env python
from program_class import Program
import tmdata
import os
def main():
""""""
args1 = {"progname" : "whoami",
"command" : "/usr/bin/whoami",
"procnum" : 1,
"autolaunch" : True,
"starttime" : 5,
"restart" : "never",
"retries" : 2,
"stopsig" : "SSIG",
"stoptime" : 10,
"e... | normal | {
"blob_id": "c58f40d369388b94778e8583176f1ba8b81d0c5e",
"index": 4083,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n \"\"\"\"\"\"\n args1 = {'progname': 'whoami', 'command': '/usr/bin/whoami', 'procnum':\n 1, 'autolaunch': True, 'starttime': 5, 'restart': 'never',\n ... | [
0,
1,
2,
3,
4
] |
from sklearn.linear_model import LinearRegression, LogisticRegression
import numpy as np
import pickle
import os
def Run(datasetFile):
# Get file from user
userFile = open(datasetFile, "r")
# Starter list of all instances of the data file
instanceList = []
instanceCount = 0
featureCou... | normal | {
"blob_id": "ee7efea569b685ad8d6922e403421227e9ea6922",
"index": 6277,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Run(datasetFile):\n userFile = open(datasetFile, 'r')\n instanceList = []\n instanceCount = 0\n featureCount = 0\n for instance in userFile:\n tempStr = inst... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2018-06-07 12:30
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependenc... | normal | {
"blob_id": "c6c13ab24e4907eecf1db4fded28d4fc8126c834",
"index": 1170,
"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 = [migrations.sw... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def quitScreen():
messagebox.showinfo('collecting data', '點擊視窗開始分析')
root.destroy()
root2 = Tk()
root2.destroy()
def getTextInput():
global result, result2
result = text.get(1.0, tk.END + '-1c')
result2 = text2.get(1.0, tk.END + '-1c')
<|reserved_special_to... | flexible | {
"blob_id": "a126b1775ffe1ba1aebc288ce17fac8ada0b0756",
"index": 312,
"step-1": "<mask token>\n\n\ndef quitScreen():\n messagebox.showinfo('collecting data', '點擊視窗開始分析')\n root.destroy()\n root2 = Tk()\n root2.destroy()\n\n\ndef getTextInput():\n global result, result2\n result = text.get(1.0, ... | [
5,
6,
8,
9,
10
] |
import sys
import os
# Module "sys"
#
# See docs for the sys module: https://docs.python.org/3.7/library/sys.html
# Print out the command line arguments in sys.argv, one per line:
# Print out the plaform from sys:
# for arg in sys.argv:
# print(arg)
# Print out the Python version from sys:print(sys.platform)
... | normal | {
"blob_id": "3fed96e9bedb157a14cf9c441de5aae8b4f6edc8",
"index": 8664,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('platform: ' + sys.platform + '\\n' + 'maxsize: ' + str(sys.maxsize) +\n '\\n' + 'argv: ' + str(sys.argv))\nprint('Process ID: ' + str(os.getpid()) + '\\n' + 'cwd: ' + os.getcwd(... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class showpng(Thread):
def __init__(self, data):
Thread.__init__(self)
self.data = data
def run(self):
img = Image.open(BytesIO(self.data))
img.show()
def islogin(session):
try:
session.cookies.load(ignore_discard=True)
except Ex... | flexible | {
"blob_id": "c268c61e47698d07b7c1461970dc47242af55777",
"index": 1637,
"step-1": "<mask token>\n\n\nclass showpng(Thread):\n\n def __init__(self, data):\n Thread.__init__(self)\n self.data = data\n\n def run(self):\n img = Image.open(BytesIO(self.data))\n img.show()\n\n\ndef isl... | [
4,
5,
7,
8,
9
] |
# Generated by Django 2.2 on 2021-01-31 14:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('app', '0004_product_pr_number'),
]
operations = [
migrations.RemoveField(
model_name='payment',
name='PA_id',
... | normal | {
"blob_id": "388772386f25d6c2f9cc8778b7ce1b2ad0920851",
"index": 6986,
"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 = [('app', '0004... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def caesar(plaintext, key):
if int(key) < 0:
return
plaintext_ascii = [(ord(char) + int(key)) for char in plaintext]
for ascii in plaintext_ascii:
if ascii < 97 and ascii > 90 or ascii > 122:
... | flexible | {
"blob_id": "9a7c6998e9e486f0497d3684f9c7a422c8e13521",
"index": 7076,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef caesar(plaintext, key):\n if int(key) < 0:\n return\n plaintext_ascii = [(ord(char) + int(key)) for char in plaintext]\n for ascii in plaintext_ascii:\n if ... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import os, glob, sys, math, time, argparse
import ROOT
from ROOT import TFile, TTree, TH2D
def main():
parser = argparse.ArgumentParser(description='Program that takes as an argument a pattern of LEAF rootfiles (* wildcards work) enclosed by quotation marks ("<pattern>") and creates a root... | normal | {
"blob_id": "44c04cf79d02823318b06f02af13973960413bea",
"index": 6915,
"step-1": "#!/usr/bin/env python\n\nimport os, glob, sys, math, time, argparse\nimport ROOT\nfrom ROOT import TFile, TTree, TH2D\n\n\n\ndef main():\n parser = argparse.ArgumentParser(description='Program that takes as an argument a pattern... | [
0
] |
<|reserved_special_token_0|>
class SSLTransport:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __exit__(self, *_):
self.close()
def fileno(self):
return self.socket.fileno()
def read(self, len=1024... | flexible | {
"blob_id": "78d59e903fecd211aa975ae4c8dc01b17c8fad44",
"index": 8471,
"step-1": "<mask token>\n\n\nclass SSLTransport:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __exit__(self, *_):\n self.close()\n\n def fileno(self):\n return self.socket.fileno()\n\n ... | [
19,
23,
27,
28,
30
] |
from manimlib.imports import *
import math
class A_Swerve(Scene):
def construct(self):
chassis = Square(side_length=2, stroke_width=0, fill_color=GRAY, fill_opacity=1).shift(2*RIGHT)
fr = Dot().shift(UP+3*RIGHT)
fl = Dot().shift(UP+RIGHT)
rl = Dot().shift(DOWN+RIGHT)
rr = Dot().shift(DOWN+3*RIGH... | normal | {
"blob_id": "bdde3a3725510d4a83b09421e4b8538a38e29584",
"index": 8196,
"step-1": "<mask token>\n\n\nclass A_Swerve(Scene):\n\n def construct(self):\n chassis = Square(side_length=2, stroke_width=0, fill_color=GRAY,\n fill_opacity=1).shift(2 * RIGHT)\n fr = Dot().shift(UP + 3 * RIGHT)\... | [
2,
3,
4,
5,
6
] |
from django.shortcuts import render, HttpResponse, redirect
from .models import Book, Author # This is the models.py Database
# Create your views here.
def main(request):
context = {
"the_books" : Book.objects.all(), #Book Class model.py
}
return render(request, "index.html", context)
def book(re... | normal | {
"blob_id": "02bec34b138d53235dc944adeae8ccb8d6b3d340",
"index": 4424,
"step-1": "<mask token>\n\n\ndef book(request):\n Book.objects.create(title=request.POST['b_title'], desc=request.POST[\n 'b_desc'])\n return redirect('/')\n\n\ndef author(request):\n context = {'the_auths': Author.objects.all... | [
5,
6,
7,
8,
9
] |
#dependencies go here
import numpy as np
import datetime as dt
from datetime import timedelta
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func
from flask import Flask, jsonify
#Set up the engine to connect to HW8 datab... | normal | {
"blob_id": "7ab964352c1d51b70e3a1a7bf0a624f2d96cfd55",
"index": 8168,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef home():\n \"\"\"List all available api routes.\"\"\"\n return (\n f'Available Routes:<br/>/api/v1.0/precipitation<br/>/api/v1.0/stations<br/>/api/v1.0/tobs<br/>/api/v1.0/<start><b... | [
3,
6,
7,
9,
10
] |
<|reserved_special_token_0|>
class BusInfo:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@staticmethod
def init():
apiKey = os.getenv('BUS_TOKEN')
... | flexible | {
"blob_id": "7eefcfdb9682cb09ce2d85d11aafc04977016ba4",
"index": 8332,
"step-1": "<mask token>\n\n\nclass BusInfo:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @staticmethod\n def init():\n apiKey = os.getenv('BUS_TOKEN')\n Bu... | [
5,
6,
7,
8,
9
] |
'''
Trolls are attacking your comment section!
A common way to deal with this situation is to remove all of the vowels from the trolls' comments, neutralizing the threat.
Your task is to write a function that takes a string and return a new string with all vowels removed.
For example, the string "This website is for... | normal | {
"blob_id": "4dea0967a0ee3e9eb3b46145739dfeb233f3a120",
"index": 5307,
"step-1": "<mask token>\n\n\ndef disemvowel(s):\n return s.translate(None, 'aeiouAEIOU')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef disemvowel(string):\n returnString = ''\n vowels = ['a', 'e', 'i', 'o', 'u']\n upper... | [
1,
2,
3,
4,
5
] |
import sys
from io import BytesIO
import telegram
from flask import Flask, request, send_file
from fsm import TocMachine
API_TOKEN = '375541027:AAFvLkySNkMSGgOl7PtsPIsJgnxophQpllQ'
WEBHOOK_URL = 'https://a140f4ad.ngrok.io/show-fsm'
app = Flask(__name__)
bot = telegram.Bot(token=API_TOKEN)
machine = TocMachine(
... | normal | {
"blob_id": "984efa858e782777472d84aab85471616a05b0e0",
"index": 2886,
"step-1": "<mask token>\n\n\ndef _set_webhook():\n status = bot.set_webhook(WEBHOOK_URL)\n if not status:\n print('Webhook setup failed')\n sys.exit(1)\n else:\n print('Your webhook URL has been set to \"{}\"'.fo... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def bfs(graph, start):
queue = [start]
queued = list()
path = list()
while queue:
print('Queue is: %s' % queue)
vertex = queue.pop(0)
print('Processing %s' % vertex)
for candidate in graph[vertex]:
i... | flexible | {
"blob_id": "7bb49712c4ef482c64f3c2a457a766de691ba7c3",
"index": 9427,
"step-1": "<mask token>\n",
"step-2": "def bfs(graph, start):\n queue = [start]\n queued = list()\n path = list()\n while queue:\n print('Queue is: %s' % queue)\n vertex = queue.pop(0)\n print('Processing %s... | [
0,
1
] |
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