code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
def euler():
h = 0.1
x = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]
y_eval = [0.0]
delta_y = [0.0]
y_real = [0.0]
eps = [0.0]
for i in range(1, len(x)):
y_eval.append(y_eval[i - 1] + h * fun(x[i - 1], y_eval[i - 1]))
delta_y.append(h * fun(y_eval[i], x[i]))... | flexible | {
"blob_id": "20f0480ee7e0782b23ec8ade150cdd8d8ad718bb",
"index": 783,
"step-1": "<mask token>\n\n\ndef euler():\n h = 0.1\n x = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5]\n y_eval = [0.0]\n delta_y = [0.0]\n y_real = [0.0]\n eps = [0.0]\n for i in range(1, len(x)):\n y_eval.append(y_eval[i - 1] +... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(set(fruits))
print(fruits.count('orange'))
<|reserved_special_token_1|>
fruits = ['orange', 'apple', 'mango', 'grapes', 'banana', 'apple', 'litchi']
print(set(fruits))
print(fruits.count('orange'))
<|reserved_special_to... | flexible | {
"blob_id": "158b39a64d725bdbfc78acc346ed8335613ae099",
"index": 8367,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(set(fruits))\nprint(fruits.count('orange'))\n",
"step-3": "fruits = ['orange', 'apple', 'mango', 'grapes', 'banana', 'apple', 'litchi']\nprint(set(fruits))\nprint(fruits.count('or... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
log.initialize_logs()
run_server()
<|reserved_special_token_1|>
from warehouse.server import run_server
from warehouse.server.config import log
if __name__ == '__main__':
log.initialize_lo... | flexible | {
"blob_id": "8c8b5c1ff749a8563788b8d5be5332e273275be3",
"index": 6450,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n log.initialize_logs()\n run_server()\n",
"step-3": "from warehouse.server import run_server\nfrom warehouse.server.config import log\nif __name__ == '... | [
0,
1,
2,
3
] |
import pandas as pd
import subprocess
import statsmodels.api as sm
import numpy as np
import math
'''
This function prcesses the gene file
Output is a one-row file for a gene
Each individual is in a column
Input file must have rowname
gene: gene ENSG ID of interest
start_col: column number which the gene exp value st... | normal | {
"blob_id": "2f64aac7032ac099870269659a84b8c7c38b2bf0",
"index": 8385,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef lm_res(snps, gene, cov):\n res = pd.DataFrame(np.zeros([snps.shape[0], 2], dtype=np.float32))\n res.index = snps.index\n res.columns = ['beta', 'pval']\n for i in rang... | [
0,
1,
2,
3,
4
] |
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.transforms import Bbox
from matplotlib.path import Path
import json
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 =... | normal | {
"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
] |
"""
time: X * Y
space: worst case X * Y
"""
class Solution:
def numIslands(self, grid: List[List[str]]) -> int:
if not grid:
return 0
Y = len(grid)
X = len(grid[0])
def dfs(y, x):
if y < 0 or x < 0 or y > Y-1 or x > X-1:
... | normal | {
"blob_id": "58bd14d240242ed58dcff35fe91cebeae4899478",
"index": 9087,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def numIslands(self, grid: List[List[str]]) ->int:\n if not grid:\... | [
0,
1,
2,
3,
4
] |
from scheme import *
from tests.util import *
class TestDateTime(FieldTestCase):
def test_instantiation(self):
with self.assertRaises(TypeError):
DateTime(minimum=True)
with self.assertRaises(TypeError):
DateTime(maximum=True)
def test_processing(self):
field ... | normal | {
"blob_id": "92b22ea23ad0cf4e16c7d19d055b7ec152ca433a",
"index": 5191,
"step-1": "<mask token>\n\n\nclass TestDateTime(FieldTestCase):\n <mask token>\n <mask token>\n\n def test_utc_processing(self):\n field = DateTime(utc=True)\n self.assert_processed(field, None)\n self.assert_not... | [
3,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def most_expensive_item(products):
return max(products.items(), key=lambda p: p[1])[0]
| flexible | {
"blob_id": "f1e335d0187aeb78d857bc523eb33221fd2e7e6d",
"index": 7148,
"step-1": "<mask token>\n",
"step-2": "def most_expensive_item(products):\n return max(products.items(), key=lambda p: p[1])[0]\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
''' tk_image_view_url_io.py
display an image from a URL using Tkinter, PIL and data_stream
tested with Python27 and Python33 by vegaseat 01mar2013
'''
import io
# allows for image formats other than gif
from PIL import Image, ImageTk
try:
# Python2
import Tkinter as tk
from urllib2 import urlopen
except... | normal | {
"blob_id": "7764effac0b95ad8f62b91dd470c1d0e40704a7d",
"index": 9705,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n import Tkinter as tk\n from urllib2 import urlopen\nexcept ImportError:\n import tkinter as tk\n from urllib.request import urlopen\n<mask token>\nroot.title(sf)\n<mask... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution(object):
def nextGreaterElement(self, findNums, nums):
"""
:type findNums: List[int]
:type num... | flexible | {
"blob_id": "3abeac4fb80244d2da14e14a6048c09b0c0c1393",
"index": 6047,
"step-1": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n\n def nextGreaterElement(self, findNums, nums):\n \"\"\"\n :type findNums: ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def long_alpha(str1):
list1 = []
list2 = ''
maxi = 0
j = 0
for i in range(len(str1)):
if i == 0:
list2 += str1[i]
elif ord(str1[i - 1]) <= ord(str1[i]):
list2 += str1[i]
else:
lis... | flexible | {
"blob_id": "e7c18fa99c801fd959c868954f020d8c55babe0d",
"index": 7543,
"step-1": "<mask token>\n",
"step-2": "def long_alpha(str1):\n list1 = []\n list2 = ''\n maxi = 0\n j = 0\n for i in range(len(str1)):\n if i == 0:\n list2 += str1[i]\n elif ord(str1[i - 1]) <= ord(st... | [
0,
1,
2,
3,
4
] |
naam = raw_input("Wat is je naam?")
getal = raw_input("Geef me een getal?")
if naam == "Barrie":
print "Welkom " * int(getal)
else:
print "Helaas, tot ziens" | normal | {
"blob_id": "c48d5d9e088acfed0c59e99d3227c25689d205c6",
"index": 7848,
"step-1": "naam = raw_input(\"Wat is je naam?\")\ngetal = raw_input(\"Geef me een getal?\")\nif naam == \"Barrie\":\n\tprint \"Welkom \" * int(getal)\nelse:\n\tprint \"Helaas, tot ziens\"",
"step-2": null,
"step-3": null,
"step-4": null... | [
0
] |
import requests
import os
from bs4 import BeautifulSoup
from urllib.parse import urljoin
CURRENT_DIR = os.getcwd()
DOWNLOAD_DIR = os.path.join(CURRENT_DIR, 'malware_album')
os.makedirs(DOWNLOAD_DIR, exist_ok=True)
url = 'http://old.vision.ece.ucsb.edu/~lakshman/malware_images/album/'
class Extractor(object):
"... | normal | {
"blob_id": "a53d7b4c93fa49fb0162138d4a262fe7a5546148",
"index": 5215,
"step-1": "<mask token>\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, 'html5lib')\n self.base_url = base_url\n\n def get_album... | [
9,
10,
11,
13,
14
] |
# -*- coding: utf-8 -*-
import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
class ItemCrawlSpider(CrawlSpider):
name = 'auction_crwal'
allowed_domains = ['itempage3.auction.co.kr']
def __init__(self, keyword=None, *args, **kwargs):
super(Item... | normal | {
"blob_id": "cba12d076ed8cba84501983fda9bdce8312f2618",
"index": 6337,
"step-1": "<mask token>\n\n\nclass ItemCrawlSpider(CrawlSpider):\n <mask token>\n <mask token>\n\n def __init__(self, keyword=None, *args, **kwargs):\n super(ItemCrawlSpider, self).__init__(*args, **kwargs)\n keyword.re... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def matches(needle, haystack):
for straw in haystack:
if needle == straw:
return True
return False
def appendSection(section):
if len(section) < 2:
return
if not section[0].endswith('-'):
print('warning: section name does not end with ... | flexible | {
"blob_id": "c712875273f988a3aa6dab61f79e99a077823060",
"index": 807,
"step-1": "<mask token>\n\n\ndef matches(needle, haystack):\n for straw in haystack:\n if needle == straw:\n return True\n return False\n\n\ndef appendSection(section):\n if len(section) < 2:\n return\n if ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def runall(path):
print('==========================')
"""get the current path """
abs_file_path = os.path.abspath(__file__)
parent_dir = os.path.dirname(abs_file_path)
parent_dir = os.path.dirname(parent_dir)... | flexible | {
"blob_id": "1158ab95ac67d62459284267a8cc9f587daf89b1",
"index": 9329,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef runall(path):\n print('==========================')\n \"\"\"get the current path \"\"\"\n abs_file_path = os.path.abspath(__file__)\n parent_dir = os.path.dirname(abs_... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render
from django.shortcuts import redirect
from django.http import HttpResponse
from .models import *
from django.contrib.auth import logout, authenticate, login
from django.contrib.auth.decorators import login_required
from django.template.loader import get_template
from django.template ... | normal | {
"blob_id": "e982fd5bed540b836fd4e2caaec033d8cbfb0e4f",
"index": 9854,
"step-1": "<mask token>\n\n\n@csrf_exempt\ndef login_form(request):\n formulario = '<form action=\"login\" method=\"POST\">'\n formulario += 'Nombre<br><input type=\"text\" name=\"Usuario\"><br>'\n formulario += 'Contraseña<br><input... | [
8,
12,
13,
14,
17
] |
<|reserved_special_token_0|>
def is_top_left_occupied(data, i, j):
found = False
occupied = 0
while i >= 0 and j >= 0 and not found:
occupied, found = check_seat(data, i, j)
i -= 1
j -= 1
return occupied
def is_top_occupied(data, i, j):
found = False
occupied = 0
... | flexible | {
"blob_id": "246ec0d6833c9292487cb4d381d2ae82b220677e",
"index": 3969,
"step-1": "<mask token>\n\n\ndef is_top_left_occupied(data, i, j):\n found = False\n occupied = 0\n while i >= 0 and j >= 0 and not found:\n occupied, found = check_seat(data, i, j)\n i -= 1\n j -= 1\n return ... | [
5,
10,
11,
14,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def tock(t0, dat=None):
if dat is not None:
try:
_ = dat.block_until_ready()
except AttributeError:
_ = jnp.array(dat).block_until_ready()
return time.perf_counter() - t0
<|reser... | flexible | {
"blob_id": "e58dbb4f67c93abf3564dc0f38df8852313338f0",
"index": 5520,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef tock(t0, dat=None):\n if dat is not None:\n try:\n _ = dat.block_until_ready()\n except AttributeError:\n _ = jnp.array(dat).block_until_rea... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if len(links) > 0:
for i, l in enumerate(links):
article = {'link': l, 'title': titles[i], 'source': mail_ru_link}
news.append(article)
else:
print('Error')
<|reserved_special_token_0|>
if len(links) > 0:
... | flexible | {
"blob_id": "00d2a29774a4278b1b022571b3f16c88224f08fc",
"index": 5207,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(links) > 0:\n for i, l in enumerate(links):\n article = {'link': l, 'title': titles[i], 'source': mail_ru_link}\n news.append(article)\nelse:\n print('Error')\n... | [
0,
1,
2,
3,
4
] |
# Generic function for updating Weblogic system resources
def update_system_resources(clusterName):
print "Cluster name is " + clusterName
startTransaction()
create_JMSSystemResource("/", "DummyJMSModule")
delete_JMSModule("/JMSSystemResources", "DummyJMSModule")
endTransaction()
print "update_s... | normal | {
"blob_id": "99ddc00bf1d0141118748aa98bcc3e7b8a0ff29e",
"index": 1503,
"step-1": "# Generic function for updating Weblogic system resources\ndef update_system_resources(clusterName):\n print \"Cluster name is \" + clusterName\n startTransaction()\n create_JMSSystemResource(\"/\", \"DummyJMSModule\")\n... | [
0
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import enhancedyaml
import vector
def roots_of_n_poly_eq(n, x, var_upper_bounds=tuple()):
'''find the all possible non-negative interger roots of a `n`-term polynomial equals `x`.'''
countdown = lambda: xrange(x if not var_upper_bounds else var_upper_bounds[0], -... | normal | {
"blob_id": "c6b80a7dfce501bfe91f818ac7ab45238a0a126b",
"index": 3367,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport enhancedyaml\nimport vector\n\ndef roots_of_n_poly_eq(n, x, var_upper_bounds=tuple()):\n '''find the all possible non-negative interger roots of a `n`-term polynomial equa... | [
0
] |
from StringIO import StringIO
import gzip
import urllib2
import urllib
url="http://api.syosetu.com/novelapi/api/"
get={}
get["gzip"]=5
get["out"]="json"
get["of"]="t-s-w"
get["lim"]=500
get["type"]="er"
url_values = urllib.urlencode(get)
request = urllib2.Request(url+"?"+url_values)
response = urllib2.urlopen(reque... | normal | {
"blob_id": "4b622c7f9b5caa7f88367dd1fdb0bb9e4a81477b",
"index": 2338,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif response.info().get('Content-Type') == 'application/x-gzip':\n buf = StringIO(response.read())\n f = gzip.GzipFile(fileobj=buf)\n data = f.read()\nelse:\n data = response.r... | [
0,
1,
2,
3,
4
] |
#!/bin/usr/python2.7.x
import os, re, urllib2
def main():
ip = raw_input(" Target IP : ")
check(ip)
def check(ip):
try:
print "Loading Check File Uploader...."
print 58*"-"
page = 1
while page <= 21:
bing = "http://www.bing.com/search?q=ip%3A" + \
ip + "+upload&count=50&first=" + str(... | normal | {
"blob_id": "21af630bf383ee1bdd0f644283f0ddadde71620a",
"index": 236,
"step-1": "#!/bin/usr/python2.7.x\r\n\r\nimport os, re, urllib2\r\n\r\ndef main():\r\n\tip = raw_input(\" Target IP : \")\r\n\tcheck(ip)\r\n\r\ndef check(ip):\r\n\ttry:\r\n\t\tprint \"Loading Check File Uploader....\"\r\n\t\tprint 58*\"-\"\r\n... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
with open('Book1.txt', 'r') as file1:
with open('20k.txt', 'r') as file2:
same = set(file1).intersection(file2)
same.discard('\n')
with open('notin20kforBook1.txt', 'w') as file_out:
for line in same:
file_out.write(line)
with open('Bo... | flexible | {
"blob_id": "21a41356fcedb36223498db0fe783e4a9e8e1ba6",
"index": 210,
"step-1": "<mask token>\n",
"step-2": "with open('Book1.txt', 'r') as file1:\n with open('20k.txt', 'r') as file2:\n same = set(file1).intersection(file2)\nsame.discard('\\n')\nwith open('notin20kforBook1.txt', 'w') as file_out:\n ... | [
0,
1,
2
] |
#!/usr/bin/env python
x *= 2
"""run = 0
while(run < 10):
[TAB]x = (first number in sequence)
[TAB](your code here)
[TAB]run += 1"""
| normal | {
"blob_id": "3e84265b7c88fc45bc89868c4339fe37dcc7d738",
"index": 1112,
"step-1": "<mask token>\n",
"step-2": "x *= 2\n<mask token>\n",
"step-3": "#!/usr/bin/env python\r\n\r\nx *= 2\r\n\r\n\"\"\"run = 0\r\nwhile(run < 10):\r\n[TAB]x = (first number in sequence)\r\n[TAB](your code here)\r\n[TAB]run += 1\"\"\"... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def test_convert_wrong_char():
txt = convert('@!*', ':icon:', ':nbsp')
assert txt == """:icon::icon::icon::nbsp:nbsp:icon::icon::icon::nbsp:nbsp:icon::icon::icon:
:nbsp:nbsp:icon::nbsp:nbsp:nbsp:nbsp:icon::nbsp:nbsp:nbsp:nbsp:icon:
:nbsp:icon::nbsp:nbsp:nbsp:nbsp:icon::nbsp:nbsp:n... | flexible | {
"blob_id": "c3bfcb971a6b08cdf98200bd2b2a8fe6ac2dd083",
"index": 6969,
"step-1": "<mask token>\n\n\ndef test_convert_wrong_char():\n txt = convert('@!*', ':icon:', ':nbsp')\n assert txt == \"\"\":icon::icon::icon::nbsp:nbsp:icon::icon::icon::nbsp:nbsp:icon::icon::icon:\n:nbsp:nbsp:icon::nbsp:nbsp:nbsp:nbsp... | [
1,
2,
3,
4,
5
] |
import math,random,numpy as np
def myt():
x=[0]*10
y=[]
for i in range(100000):
tmp = int(random.random()*10)
x[tmp] = x[tmp]+1
tmpy=[0]*10
tmpy[tmp] = 1
for j in range(10):
tmpy[j] = tmpy[j] + np.random.laplace(0,2,None)
y.append(tmpy)
result... | normal | {
"blob_id": "7b7705cdaa8483f6abbc3f4fb3fa1ca506742da8",
"index": 6042,
"step-1": "import math,random,numpy as np\n\ndef myt():\n x=[0]*10\n y=[]\n for i in range(100000):\n tmp = int(random.random()*10)\n x[tmp] = x[tmp]+1\n tmpy=[0]*10\n tmpy[tmp] = 1\n for j in range... | [
0
] |
import tensorflow as tf
import numpy as np
from datetime import datetime
import os
from CNN import CNN
from LSTM import LSTM
from BiLSTM import BiLSTM
from SLAN import Attention
from HAN2 import HierarchicalAttention
import sklearn.metrics as metrics
import DataProcessor as dp
import matplotlib.pyplot as plt
import num... | normal | {
"blob_id": "3aff6bdfd7c2ffd57af7bb5d0079a8a428e02331",
"index": 1284,
"step-1": "<mask token>\n\n\ndef evaluate(sess, data, embds, model, logdir):\n checkpoint_dir = '{}checkpoints'.format(logdir)\n saver = tf.train.Saver()\n sess.run(tf.global_variables_initializer())\n sess.run(model.embedding_ini... | [
5,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
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
| flexible | {
"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|>
class Node(object):
"""
Defines a Node Class for storing characteristics and CPT of each node
"""
def __init__(self, name):
self.parents = []
self.children = []
self.name = name
self.cpt = []
self.limit = 3
def addParent(self, ... | flexible | {
"blob_id": "eb4bc008b7e68f8a6e80e837fa970d77a5ed3547",
"index": 8218,
"step-1": "<mask token>\n\n\nclass Node(object):\n \"\"\"\n Defines a Node Class for storing characteristics and CPT of each node\n \"\"\"\n\n def __init__(self, name):\n self.parents = []\n self.children = []\n ... | [
12,
13,
15,
17,
20
] |
new_tuple = (11,12,13,14,15,16,17)
new_list = ['one' ,12,'three' ,14,'five']
print("Tuple: ",new_tuple)
print("List: ", new_list)
tuple_2= tuple (new_list)
print("Converted tuple from the list : ", tuple_2) | normal | {
"blob_id": "889fdca3f92f218e6d6fd3d02d49483f16a64899",
"index": 9117,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Tuple: ', new_tuple)\nprint('List: ', new_list)\n<mask token>\nprint('Converted tuple from the list : ', tuple_2)\n",
"step-3": "new_tuple = 11, 12, 13, 14, 15, 16, 17\nnew_list ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def CheckNumber(userInput):
""" This function returns True if userInput can be converted to a number and
returns False if it cannot. """
try:
float(userInput)
return True
except ValueError:
return False
def DateInput(message):
""" This functio... | flexible | {
"blob_id": "77e985d94d3b47539f046a3a46cb1a197cef86f4",
"index": 3409,
"step-1": "<mask token>\n\n\ndef CheckNumber(userInput):\n \"\"\" This function returns True if userInput can be converted to a number and\n returns False if it cannot. \"\"\"\n try:\n float(userInput)\n return True\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class BitfinexMMTrader:
<|reserved_special_token_0|>
def get_fees(self):
account_info = self.trade_client.account_info()
return float(account_info[0]['maker_fees'])
def get_pnl(self):
pos = max(self.buy_position, self.sell_position)
if pos == ... | flexible | {
"blob_id": "6abfd6c0a644356ae0bc75d62472b5c495118a8e",
"index": 4466,
"step-1": "<mask token>\n\n\nclass BitfinexMMTrader:\n <mask token>\n\n def get_fees(self):\n account_info = self.trade_client.account_info()\n return float(account_info[0]['maker_fees'])\n\n def get_pnl(self):\n ... | [
11,
16,
20,
21,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def func(n):
return n * 2
def my_map(f, seq):
return [f(item) for item in seq]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def func(n):
return n * 2
def my_map(f, seq):
return [f(item) for item in seq]
def main():
... | flexible | {
"blob_id": "55acae8129ddaba9a860d5d356e91f40607ac95a",
"index": 8614,
"step-1": "<mask token>\n",
"step-2": "def func(n):\n return n * 2\n\n\ndef my_map(f, seq):\n return [f(item) for item in seq]\n\n\n<mask token>\n",
"step-3": "def func(n):\n return n * 2\n\n\ndef my_map(f, seq):\n return [f(i... | [
0,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
service_account_json = path.join(path.dirname(path.abspath(__file__)),
'service_account.json')
credentials = service_account.Credentials.from_service_account_file(
service_account_json, scopes=SCOPES)
service = build('sheets', 'v4', credentials=cred... | flexible | {
"blob_id": "f9261c1844cc629c91043d1221d0b76f6e22fef6",
"index": 6157,
"step-1": "<mask token>\n\n\ndef main():\n service_account_json = path.join(path.dirname(path.abspath(__file__)),\n 'service_account.json')\n credentials = service_account.Credentials.from_service_account_file(\n service_a... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def calcLuckyNumber(x):
resultSet = set()
for i in range(30):
for j in range(30):
for k in range(30):
number = pow(3, i) * pow(5, j) * pow(7, k)
if number > 1 and number <= x:
res... | flexible | {
"blob_id": "49a9fb43f3651d28d3ffac5e33d10c428afd08fd",
"index": 6072,
"step-1": "<mask token>\n",
"step-2": "def calcLuckyNumber(x):\n resultSet = set()\n for i in range(30):\n for j in range(30):\n for k in range(30):\n number = pow(3, i) * pow(5, j) * pow(7, k)\n ... | [
0,
1,
2,
3,
4
] |
from django.urls import path, include
from .views import StatusAPIView, StateAPIView, LogAPIView
urlpatterns = [
path('status/', StatusAPIView.as_view(), name='status'),
path('log/', LogAPIView.as_view(), name='log'),
path('state/', StateAPIView.as_view(), name='state'),
]
| normal | {
"blob_id": "1ae8d78c6581d35cd82194e2565e7a11edda1487",
"index": 7265,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('status/', StatusAPIView.as_view(), name='status'),\n path('log/', LogAPIView.as_view(), name='log'), path('state/',\n StateAPIView.as_view(), name='state')]\n",... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import socket
import os
def http_header_parser(request):
headers = {}
lines = request.split('\n')[1:]
for string in lines:
first_pos = string.find(":")
headers[string[:first_pos]] = string[first_pos + 2:]
return headers
def create_response(http_code, http_co... | normal | {
"blob_id": "41350714ce13e3627b9bd56eb934846a99f8e1b3",
"index": 7047,
"step-1": "# -*- coding: utf-8 -*-\nimport socket\nimport os\n\n\ndef http_header_parser(request):\n headers = {}\n\n lines = request.split('\\n')[1:]\n for string in lines:\n first_pos = string.find(\":\")\n headers[st... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def n_grams(unigramsFile, bigramsFile, parameterization, sentences):
words = []
param = []
unigrams = []
bigrams = []
with open(parameterization) as p:
data = p.read().split()
word = data[0]
... | flexible | {
"blob_id": "87c200796e1fac508a43e899c0ed53878b8c1d88",
"index": 5244,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef n_grams(unigramsFile, bigramsFile, parameterization, sentences):\n words = []\n param = []\n unigrams = []\n bigrams = []\n with open(parameterization) as p:\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@typ.typ(items=[int])
def gnome_sort(items):
"""
>>> gnome_sort([])
[]
>>> gnome_sort([1])
[1]
>>> gnome_sort([2,1])
[1, 2]
>>> gnome_sort([1,2])
[1, 2]
>>> gnome_sort([1,2,2])
[1, 2, 2]
"""
i = 0
... | flexible | {
"blob_id": "70aba6c94b7050113adf7ae48bd4e13aa9a34587",
"index": 1023,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@typ.typ(items=[int])\ndef gnome_sort(items):\n \"\"\"\n >>> gnome_sort([])\n []\n >>> gnome_sort([1])\n [1]\n >>> gnome_sort([2,1])\n [1, 2]\n >>> gnome_sort([1,2])\n [1, ... | [
0,
1,
2
] |
import re
class CoordinatesDataParser:
def __init__(self):
return
def get_coords(self, response):
html = response.xpath('.//body').extract_first()
longitude = re.search(r'-\d+\.\d{5,}', html)
longitude = longitude.group() if longitude else None
if longitude:
... | normal | {
"blob_id": "7d5f41cfa2d5423c6db2678f1eb8160638b50c02",
"index": 1835,
"step-1": "<mask token>\n\n\nclass CoordinatesDataParser:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CoordinatesDataParser:\n\n def __init__(self):\n return\n <mask token>\n",
"step-3": "<mask ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Copyright:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def _c_cpp_formater(self):
return '/* ' + self.declaration + ' */'
for ft in _file_type['c/c++']:
_formaters[ft] = ... | flexible | {
"blob_id": "dc05a441c21a67fbb3a1975b3fccb865a32731c8",
"index": 4642,
"step-1": "<mask token>\n\n\nclass Copyright:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def _c_cpp_formater(self):\n return '/* ' + self.declaration + ' */'\n for ft in _file_type['c/c++']:\n ... | [
5,
7,
11,
12,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(a)
<|reserved_special_token_0|>
print('The result is:', a[b])
print(a[8])
print(a[-1])
print(a[0:3])
print(a[0:])
<|reserved_special_token_0|>
print(a + b)
print(b * 3)
print(a[2])
<|reserved_special_token_0|>
print(a)
print... | flexible | {
"blob_id": "f7d29dd1d990b3e07a7c07a559cf5658b6390e41",
"index": 4601,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a)\n<mask token>\nprint('The result is:', a[b])\nprint(a[8])\nprint(a[-1])\nprint(a[0:3])\nprint(a[0:])\n<mask token>\nprint(a + b)\nprint(b * 3)\nprint(a[2])\n<mask token>\nprint(a... | [
0,
1,
2,
3
] |
import os
import requests
from pprint import pprint as pp
from lxml import html
from bs4 import BeautifulSoup
from dotenv import load_dotenv
import datetime
load_dotenv()
class PrometeoAPI:
def __init__(self, user, pwd):
self.base_url = 'https://prometeoapi.com'
self.session = requests.Session()... | normal | {
"blob_id": "f3e654a589cc1c16b36203dd358671d0426556e6",
"index": 2676,
"step-1": "<mask token>\n\n\nclass PrometeoAPI:\n\n def __init__(self, user, pwd):\n self.base_url = 'https://prometeoapi.com'\n self.session = requests.Session()\n self.__user = user\n self.__pwd = pwd\n ... | [
5,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
name = socket.gethostname()
<|reserved_special_token_1|>
import socket
name = socket.gethostname()
<|reserved_special_token_1|>
#!/usr/bin/env python
import socket
name = socket.gethostname()
| flexible | {
"blob_id": "79c043fc862e77bea5adc3f1c6bb9a6272f19c75",
"index": 78,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nname = socket.gethostname()\n",
"step-3": "import socket\nname = socket.gethostname()\n",
"step-4": "#!/usr/bin/env python\n\nimport socket\n\nname = socket.gethostname()\n",
"step-5"... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_palindrome(n):
"""
What comes in: An non-negative integer n.
What goes out: Returns True if the given integer is a palindrome,
that is, if it reads the same backwards and forwards.
Returns False ... | flexible | {
"blob_id": "ca6a9656efe439c9e90f2724e38e652a09e46dae",
"index": 7686,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_palindrome(n):\n \"\"\"\n What comes in: An non-negative integer n.\n What goes out: Returns True if the given integer is a palindrome,\n that is, if it reads t... | [
0,
5,
9,
10,
11
] |
'''
Write the necessary code calculate the volume and surface area
of a cylinder with a radius of 3.14 and a height of 5. Print out the result.
'''
pi = 3.14159
r = 3.14
h = 5
volume = pi*r**2*h
surface_area = 2*pi*r**2+r*h
print(volume,surface_area) | normal | {
"blob_id": "d04e69c234f2887f5301e4348b4c4ec2ad3af7a2",
"index": 2623,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(volume, surface_area)\n",
"step-3": "<mask token>\npi = 3.14159\nr = 3.14\nh = 5\nvolume = pi * r ** 2 * h\nsurface_area = 2 * pi * r ** 2 + r * h\nprint(volume, surface_area)\n",... | [
0,
1,
2,
3
] |
import matplotlib.pyplot as plt
def visualize_data(positive_images, negative_images):
# INPUTS
# positive_images - Images where the label = 1 (True)
# negative_images - Images where the label = 0 (False)
figure = plt.figure()
count = 0
for i in range(positive_images.shape[0]):
... | normal | {
"blob_id": "ebe79cf1b54870055ce8502430f5fae833f3d96d",
"index": 3121,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef visualize_data(positive_images, negative_images):\n figure = plt.figure()\n count = 0\n for i in range(positive_images.shape[0]):\n count += 1\n figure.add_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class UserProfile(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __unicode__(self):
return '%s : %s' % (self.user, self.tiers)
@property
def list_name(self):
t = EntiteClass.objects.get(id=self.tiers)
u = User.obj... | flexible | {
"blob_id": "a094207b2cd9a5a4bd409ac8a644268f3808e346",
"index": 7023,
"step-1": "<mask token>\n\n\nclass UserProfile(models.Model):\n <mask token>\n <mask token>\n\n def __unicode__(self):\n return '%s : %s' % (self.user, self.tiers)\n\n @property\n def list_name(self):\n t = Entite... | [
3,
4,
6,
9,
10
] |
<|reserved_special_token_0|>
class Studies(db.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "06b07045fcfafd174bb78ff5c3a36bed11e36e54",
"index": 9616,
"step-1": "<mask token>\n\n\nclass Studies(db.Model):\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 <mask token>\n <mask token>\n\n d... | [
42,
44,
53,
54,
60
] |
<|reserved_special_token_0|>
class NConv2d(_ConvNd):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def init_parameters(self):
if self.init_method == 'x':
torch.nn.init.xavier_uniform_(self.weight)
elif self.init_method == 'k':
torch.nn.init.kaiming_unif... | flexible | {
"blob_id": "64b4deaad548a38ba646423d33fc6a985483a042",
"index": 3592,
"step-1": "<mask token>\n\n\nclass NConv2d(_ConvNd):\n <mask token>\n <mask token>\n\n def init_parameters(self):\n if self.init_method == 'x':\n torch.nn.init.xavier_uniform_(self.weight)\n elif self.init_me... | [
15,
17,
18,
19,
21
] |
disk = bytearray (1024*1024);
def config_complete():
pass
def open(readonly):
return 1
def get_size(h):
global disk
return len (disk)
def can_write(h):
return True
def can_flush(h):
return True
def is_rotational(h):
return False
def can_trim(h):
return True
def pread(h, count, of... | normal | {
"blob_id": "2e3c1bf0a4c88bda35a48008cace8c21e071384e",
"index": 8378,
"step-1": "<mask token>\n\n\ndef config_complete():\n pass\n\n\n<mask token>\n\n\ndef get_size(h):\n global disk\n return len(disk)\n\n\n<mask token>\n\n\ndef is_rotational(h):\n return False\n\n\ndef can_trim(h):\n return True... | [
7,
8,
11,
12,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', views.index, name='index'), path('login', views.
login_view, name='login'), path('logout', views.logout_view, name=
'logout'), path('menu', views.menu, name='menu'), path('add_item',
views.add_i... | flexible | {
"blob_id": "9be6940fc6f405db652d478f9a74fcf56d8a0ad7",
"index": 3470,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.index, name='index'), path('login', views.\n login_view, name='login'), path('logout', views.logout_view, name=\n 'logout'), path('menu', views.menu, n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def make_noises(bs):
return mx.nd.random_normal(0, 1, shape=(bs, 512), ctx=CTX, dtype='float32'
).reshape((bs, 512, 1, 1))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mx.random.seed(5)
logger.basicConfig(level=logger.INFO, filena... | flexible | {
"blob_id": "c14d76493cd3dacc55c993f588dec555b7a4a13c",
"index": 4192,
"step-1": "<mask token>\n\n\ndef make_noises(bs):\n return mx.nd.random_normal(0, 1, shape=(bs, 512), ctx=CTX, dtype='float32'\n ).reshape((bs, 512, 1, 1))\n\n\n<mask token>\n",
"step-2": "<mask token>\nmx.random.seed(5)\nlogger.b... | [
1,
3,
4,
5,
6
] |
'''
A prime number is a natural number greater than 1 that has no positive divisors other than 1 and itself. Given two integers A and B,
print the number of primes between them, inclusively.
'''
a = int(input())
b = int(input())
count = 0
for i in range(a, b+1):
true_prime = True
for num in range(2, i):
... | normal | {
"blob_id": "ed4c97913a9dba5cf6be56050a8d2ce24dbd6033",
"index": 1870,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(a, b + 1):\n true_prime = True\n for num in range(2, i):\n if i % num == 0:\n true_prime = False\n if true_prime:\n count += 1\nprint(coun... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ok_(is_inf_rigid(fw_2d, 2))
ok_(not is_inf_rigid(fw_3d, 3))
ok_(is_inf_rigid(fw_1d, 1))
<|reserved_special_token_0|>
print(len(rand_fw.nodes))
draw_framework(rand_fw)
<|reserved_special_token_0|>
print(R)
print(f)
print(R.dot(f))
... | flexible | {
"blob_id": "4e31619efcaf6eeab3b32116b21e71de8202aee2",
"index": 8646,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nok_(is_inf_rigid(fw_2d, 2))\nok_(not is_inf_rigid(fw_3d, 3))\nok_(is_inf_rigid(fw_1d, 1))\n<mask token>\nprint(len(rand_fw.nodes))\ndraw_framework(rand_fw)\n<mask token>\nprint(R)\nprint(... | [
0,
1,
2,
3,
4
] |
# Copyright 2019 PerfKitBenchmarker Authors. All rights reserved.
#
# 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 appli... | normal | {
"blob_id": "9cebce7f97a1848885883692cd0f494cce6bae7f",
"index": 5263,
"step-1": "<mask token>\n\n\nclass RedshiftClusterSubnetGroup(resource.BaseResource):\n <mask token>\n\n def __init__(self, cmd_prefix):\n super(RedshiftClusterSubnetGroup, self).__init__(user_managed=False)\n self.cmd_pre... | [
4,
5,
6,
7,
8
] |
from .. import dataclass # trigger the register in the dataclass package
| normal | {
"blob_id": "681750dbf489a6a32e9ef1d6f64d493cc252b272",
"index": 6386,
"step-1": "<mask token>\n",
"step-2": "from .. import dataclass\n",
"step-3": "from .. import dataclass # trigger the register in the dataclass package\r\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
forbidden = ['Key.esc', 'Key.cmd', 'Key.cmd_r', 'Key.menu', 'Key.pause',
'Key.scroll_lock', 'Key.print_screen', 'Key.enter', 'Key.space',
'Key.backspace', 'Key.ctrl_l', 'Key.ctrl_r', 'Key.alt_l', 'Key.alt_gr',
'Key.caps_lock', 'Key.num_lock', 'Key.tab', 'Key.shift', 'Key.shift_r',
'Key.insert', 'Key.del... | normal | {
"blob_id": "995dc34ea32de4566e2804b6797d9b551b733ff3",
"index": 3406,
"step-1": "<mask token>\n",
"step-2": "forbidden = ['Key.esc', 'Key.cmd', 'Key.cmd_r', 'Key.menu', 'Key.pause',\n 'Key.scroll_lock', 'Key.print_screen', 'Key.enter', 'Key.space',\n 'Key.backspace', 'Key.ctrl_l', 'Key.ctrl_r', 'Key.alt... | [
0,
1
] |
import sys; input = sys.stdin.readline
from collections import deque
from itertools import combinations
from copy import deepcopy
n, m = map(int, input().split())
graph = [list(map(int,input().split())) for i in range(n)]
virus_lst = []
for i in range(n):
for j in range(n):
if graph[i][j]==2:
g... | normal | {
"blob_id": "0e3bf0ddd654b92b2cd962a2f3935c639eeb0695",
"index": 2155,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bfs(start_nodes, g):\n dq = deque()\n dq.extend(start_nodes)\n for i, j in start_nodes:\n g[i][j] = -1\n while dq:\n y, x = dq.popleft()\n for k i... | [
0,
1,
2,
3,
5
] |
#!/usr/bin/python3
"""
This module add a better setattr function
"""
def add_attribute(obj, name, value):
""" add an attribute to a class if possible"""
if hasattr(obj, "__dict__"):
setattr(obj, name, value)
else:
raise TypeError("can't add new attribute")
| normal | {
"blob_id": "bee7f3acdb103f3c20b6149407854c83ad367a6b",
"index": 2621,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add_attribute(obj, name, value):\n \"\"\" add an attribute to a class if possible\"\"\"\n if hasattr(obj, '__dict__'):\n setattr(obj, name, value)\n else:\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def log(text, level=2, outFile='log.txt'):
text = str(text)
if level == 0:
return True
if level == 3:
with open(outFile, 'a') as logger:
logger.write(text)
logger.close()
... | flexible | {
"blob_id": "015b06d7f08f9de60a46d8428820333621732c53",
"index": 6425,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef log(text, level=2, outFile='log.txt'):\n text = str(text)\n if level == 0:\n return True\n if level == 3:\n with open(outFile, 'a') as logger:\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def objective(params):
train = create_set(base_path=BASE_PATH + SET, conf=CONF, key=DSKEY,
redo=False)
test = train.query('train == 0')
train.query('train == 1', inplace=True)
X = train[FEATURES + ['session_id']]
y = train['label']
del train
gc.collect(... | flexible | {
"blob_id": "daf070291bbf59a7a06b129bbde5fd79b5cd46ad",
"index": 6715,
"step-1": "<mask token>\n\n\ndef objective(params):\n train = create_set(base_path=BASE_PATH + SET, conf=CONF, key=DSKEY,\n redo=False)\n test = train.query('train == 0')\n train.query('train == 1', inplace=True)\n X = trai... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class _VL53L1:
<|reserved_special_token_0|>
def set_range(self, rng):
if rng < 4 and rng >= 0:
self.tof.set_range()
else:
raise Exception('Invalid range: 1 - short, 2 - med, 3 - long')
<|reserved_special_token_0|>
def read(self):
... | flexible | {
"blob_id": "c6d9b971ab6919846807b740313d450d086ecc23",
"index": 7643,
"step-1": "<mask token>\n\n\nclass _VL53L1:\n <mask token>\n\n def set_range(self, rng):\n if rng < 4 and rng >= 0:\n self.tof.set_range()\n else:\n raise Exception('Invalid range: 1 - short, 2 - med,... | [
3,
4,
5,
6,
7
] |
def add_route_distance(routes, cities, source):
c = source.split()
citykey = c[0] + ':' + c[2]
cities.add(c[0])
routes[citykey] = c[4]
def get_route_distance(routes, source, dest):
if (source+":"+dest in routes):
return routes[source+":"+dest]
else:
return routes[dest+":"+sourc... | normal | {
"blob_id": "810e9e4b18ff8cb388f9e16607b8ab3389a9831d",
"index": 7402,
"step-1": "<mask token>\n\n\ndef get_route_distance(routes, source, dest):\n if source + ':' + dest in routes:\n return routes[source + ':' + dest]\n else:\n return routes[dest + ':' + source]\n\n\n<mask token>\n",
"step... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def getIntersection(a, b):
intersection = [0, 0, 0, 0]
if b[0] <= a[0] and a[0] <= b[2]:
intersection[0] = a[0]
elif a[0] <= b[0] and b[0] <= a[2]:
intersection[0] = b[0]
else:
return 0
if b[1] <= a[1] and a[1] <= b[3]:
intersection[1] =... | flexible | {
"blob_id": "f8a31cdf5f55b5aed33a407d2c008ba9b969d655",
"index": 9493,
"step-1": "<mask token>\n\n\ndef getIntersection(a, b):\n intersection = [0, 0, 0, 0]\n if b[0] <= a[0] and a[0] <= b[2]:\n intersection[0] = a[0]\n elif a[0] <= b[0] and b[0] <= a[2]:\n intersection[0] = b[0]\n else... | [
3,
5,
6,
7,
8
] |
#!/usr/bin/env python
# coding: utf-8
# Predicting Surviving the Sinking of the Titanic
# -----------------------------------------------
#
#
# This represents my first attempt at training up some classifiers for the titanic dataset.
# In[ ]:
# data analysis and wrangling
import pandas as pd
import numpy as np
i... | normal | {
"blob_id": "05f143e28ff9c7397376ad598529c1dfb7528ee3",
"index": 7269,
"step-1": "<mask token>\n\n\ndef get_na(dataset):\n na_males = dataset[dataset.Sex == 'male'].loc[:, 'AgeGroup'].isnull().sum()\n na_females = dataset[dataset.Sex == 'female'].loc[:, 'AgeGroup'].isnull(\n ).sum()\n return {'ma... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Context(Base):
def __init__(self, dataset='', capsys=None):
super(Context, self).__init__(capsys=capsys)
self.dataset = ''
self.dataset = dataset
def get_dataset(self):
return self... | flexible | {
"blob_id": "0e6e84a31b626639e2aa149fd1ef89f3ef251cd7",
"index": 207,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Context(Base):\n\n def __init__(self, dataset='', capsys=None):\n super(Context, self).__init__(capsys=capsys)\n self.dataset = ''\n self.dataset = datase... | [
0,
4,
5,
6,
7
] |
# DISCLAIMER
# The "Math" code was taken from http://depado.markdownblog.com/2015-09-29-mistune-parser-syntax-highlighter-mathjax-support-and-centered-images
# The HighlightRenderer code was taken from https://github.com/rupeshk/MarkdownHighlighter
# MarkdownHighlighter is a simple syntax highlighter for Markdown syn... | normal | {
"blob_id": "a6c45ab3df0a692cd625d8203e1152e942a4cd6c",
"index": 5908,
"step-1": "<mask token>\n\n\nclass MathBlockLexer(mistune.BlockLexer):\n <mask token>\n\n def __init__(self, rules=None, **kwargs):\n if rules is None:\n rules = MathBlockGrammar()\n super(MathBlockLexer, self).... | [
15,
17,
19,
24,
25
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
const.API_PROFILE_URL = 'https://api.line.me/v2/profile'
const.API_NOTIFICATIONTOKEN_URL = (
'https://api.line.me/message/v3/notifier/token')
const.API_ACCESSTOKEN_URL = 'https://api.line.me/v2/oauth/accessToken'
const.API_SEN... | flexible | {
"blob_id": "25fcf162306b3d6d6307e703a7d829754cba2778",
"index": 2347,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nconst.API_PROFILE_URL = 'https://api.line.me/v2/profile'\nconst.API_NOTIFICATIONTOKEN_URL = (\n 'https://api.line.me/message/v3/notifier/token')\nconst.API_ACCESSTOKEN_URL = 'https://a... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
with open('vocabulary.txt', 'r') as f:
for line in f:
information = line.strip().split(': ')
question = information[1]
answer = information[0]
my_answer = input(f'{question}:')
if my_answer == answer:
pr... | flexible | {
"blob_id": "34009d1aa145f4f5c55d0c5f5945c3793fbc6429",
"index": 7823,
"step-1": "<mask token>\n",
"step-2": "with open('vocabulary.txt', 'r') as f:\n for line in f:\n information = line.strip().split(': ')\n question = information[1]\n answer = information[0]\n my_answer = input... | [
0,
1,
2
] |
from app import db
from datetime import datetime
from sqlalchemy.orm import validates
class Posts(db.Model):
id = db.Column(db.BigInteger, primary_key=True, autoincrement=True)
title = db.Column(db.String(200))
content = db.Column(db.Text)
category = db.Column(db.String(100))
created_date = db.Column(db.Date... | normal | {
"blob_id": "29298ee7ddb4e524a23000abf86854d72f49954c",
"index": 1850,
"step-1": "<mask token>\n\n\nclass Posts(db.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __repr__(self):\n return '<Posts {}>'.format(s... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pygame.init()
pygame.camera.init()
<|reserved_special_token_0|>
print(camlist)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pygame.init()
pygame.camera.init()
camlist = pygame.camera.list_cameras()
print(camlist)
... | flexible | {
"blob_id": "aae280e049c00e70e2214662a07eee8bfa29227e",
"index": 6632,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npygame.init()\npygame.camera.init()\n<mask token>\nprint(camlist)\n",
"step-3": "<mask token>\npygame.init()\npygame.camera.init()\ncamlist = pygame.camera.list_cameras()\nprint(camlist... | [
0,
1,
2,
3,
4
] |
# orm/relationships.py
# Copyright (C) 2005-2023 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# This module is part of SQLAlchemy and is released under
# the MIT License: https://www.opensource.org/licenses/mit-license.php
"""Heuristics related to join conditions as used in
:func:`_orm.relationship`.... | normal | {
"blob_id": "5f8303ce91c5de779bbddbaafb3fb828596babe5",
"index": 8669,
"step-1": "<mask token>\n\n\nclass JoinCondition:\n primaryjoin_initial: Optional[ColumnElement[bool]]\n primaryjoin: ColumnElement[bool]\n secondaryjoin: Optional[ColumnElement[bool]]\n secondary: Optional[FromClause]\n prop: ... | [
44,
79,
88,
99,
100
] |
#This program is a nice example of a core algorithm
#Remove Individual Digits
# To remove individual digits you use two operations
# 1 MOD:
# mod return the remainder after division. 5%2 = 1.
# If we mod by 10 we get the units digit. 723%10 = 3
# 2 Integer Division:
# Integer division is when we divide and remove de... | normal | {
"blob_id": "2a95a68d8570a314b2b6e5731d7a695e5d7e7b30",
"index": 6261,
"step-1": "<mask token>\n\n\ndef isHarshad(n):\n if n % findSum(n) == 0:\n return True\n return False\n\n\ndef findHarshad(low, high):\n low = 500\n high = 525\n streak = 0\n maxStreak = 0\n for i in range(low, hig... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def LinuxSysInfo():
return sysinfo.collect()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def LinuxSysInfo():
return sysinfo.collect()
def WindowsSysInfo():
from windows import sysinfo as win_sysinfo
return win_sysinfo.col... | flexible | {
"blob_id": "30a2e4aa88b286179e2870205e90fab4a7474e12",
"index": 2969,
"step-1": "<mask token>\n\n\ndef LinuxSysInfo():\n return sysinfo.collect()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef LinuxSysInfo():\n return sysinfo.collect()\n\n\ndef WindowsSysInfo():\n from windows import sysinfo ... | [
1,
2,
3,
4,
5
] |
<|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": "ae82ecadb61fd87afbc83926b9dc9d5f7e8c35a0",
"index": 4194,
"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 = [('product', '... | [
0,
1,
2,
3,
4
] |
from .queue_worker import QueueWorker
import threading
class WorkersOrchestrator:
@classmethod
def worker_func(cls, worker):
worker.start_consumption()
def run_orchestrator(self, num_of_workers):
worker_list = []
for i in range(num_of_workers):
worker_list.append(Queu... | normal | {
"blob_id": "6a4a5eac1b736ee4f8587adba298571f90df1cf9",
"index": 8864,
"step-1": "<mask token>\n\n\nclass WorkersOrchestrator:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass WorkersOrchestrator:\n\n @classmethod\n def worker_func(cls, worker):\n worker.start_consumption... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def search4vowels(word):
""" Return sny vowels founded in a supplied word."""
vowels = set('aeiou')
found = vowels.intersection(set(word))
for vowels in found:
print(vowels)
<|reserved_special_token_1|>
def search4vowels(word):
... | flexible | {
"blob_id": "8a21a7005fb17cc82759079022b540cf4fd062c5",
"index": 3458,
"step-1": "<mask token>\n",
"step-2": "def search4vowels(word):\n \"\"\" Return sny vowels founded in a supplied word.\"\"\"\n vowels = set('aeiou')\n found = vowels.intersection(set(word))\n for vowels in found:\n print... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(x * y)
<|reserved_special_token_1|>
x, y = [float(x) for x in raw_input().split(' ')]
print(x * y)
<|reserved_special_token_1|>
x, y = [float(x) for x in raw_input().split(" ")]
print(x*y) | flexible | {
"blob_id": "1ed7fb0dd5f0fa5e60c855eceaaf3259092918ef",
"index": 1240,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(x * y)\n",
"step-3": "x, y = [float(x) for x in raw_input().split(' ')]\nprint(x * y)\n",
"step-4": "x, y = [float(x) for x in raw_input().split(\" \")]\nprint(x*y)",
"step-5"... | [
0,
1,
2,
3
] |
#import os
import queue as q
#Считываем ввод
file = open('input.txt', 'r')
inp = ''
for i in file:
for j in i:
if (j != '\n'):
inp += j
else:
inp += ' '
inp += ' '
#print(inp)
file.close()
#Записываем все пути в двумерный массив
tmp = '' #Переменная для хранения текущего ... | normal | {
"blob_id": "bb847480e7e4508fbfb5e7873c4ed390943e2fcf",
"index": 3589,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in file:\n for j in i:\n if j != '\\n':\n inp += j\n else:\n inp += ' '\ninp += ' '\nfile.close()\n<mask token>\nfor i in inp:\n if i != ' ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', admin.site.urls), path('upload/', include(
'links.urls'))]
<|reserved_special_token_1|>
from django.contrib import admin
from django.urls import include, path
urlpatterns = [path('', admin.site.urls)... | flexible | {
"blob_id": "45e8bdacad4ed293f7267d96abc9cbe8c8e192ae",
"index": 4148,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', admin.site.urls), path('upload/', include(\n 'links.urls'))]\n",
"step-3": "from django.contrib import admin\nfrom django.urls import include, path\nurlpatter... | [
0,
1,
2,
3
] |
<|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": "c0cabf2b6f7190aefbaefa197a9008de3a344147",
"index": 2082,
"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', '005... | [
0,
1,
2,
3,
4
] |
<|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_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.... | flexible | {
"blob_id": "8cec6778f530cb06e4f6cb2e6e9b6cb192d20f97",
"index": 3280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class FeedOnlyAutonomousMode(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def OnEnable(self):
"""
This function is called when Autonomous mode is enabled. You should
initialize things neede... | flexible | {
"blob_id": "3596ef12ce407a8d84319daa38a27a99ed0de763",
"index": 5208,
"step-1": "<mask token>\n\n\nclass FeedOnlyAutonomousMode(object):\n <mask token>\n <mask token>\n <mask token>\n\n def OnEnable(self):\n \"\"\"\n This function is called when Autonomous mode is enabled. You shou... | [
3,
4,
5,
6,
7
] |
import os
import unittest
from mock import Mock
from tfsnippet.utils import *
class HumanizeDurationTestCase(unittest.TestCase):
cases = [
(0.0, '0 sec'),
(1e-8, '1e-08 sec'),
(0.1, '0.1 sec'),
(1.0, '1 sec'),
(1, '1 sec'),
(1.1, '1.1 secs'),
(59, '59 secs... | normal | {
"blob_id": "9189c1dd21b0858df3138bcf4fc7568b378e6271",
"index": 885,
"step-1": "<mask token>\n\n\nclass NotSetTestCase(unittest.TestCase):\n <mask token>\n\n\nclass _CachedPropertyHelper(object):\n\n def __init__(self, value):\n self.value = value\n\n @cached_property('_cached_value')\n def c... | [
11,
12,
13,
18,
22
] |
import sys
sys.stdin = open('4828.txt', 'r')
sys.stdout = open('4828_out.txt', 'w')
T = int(input())
for test_case in range(1, T + 1):
N = int(input())
l = list(map(int, input().split()))
min_v = 1000001
max_v = 0
i = 0
while i < N:
if l[i] < min_v:
min_v = l[i]
if l[... | normal | {
"blob_id": "2b5df70c75f2df174991f6b9af148bdcf8751b61",
"index": 4275,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor test_case in range(1, T + 1):\n N = int(input())\n l = list(map(int, input().split()))\n min_v = 1000001\n max_v = 0\n i = 0\n while i < N:\n if l[i] < min_v:... | [
0,
1,
2,
3
] |
def SimpleSymbols(str):
if str[0].isalpha() and str[-1].isalpha():
return "false"
for i in range(0, len(str)):
if str[i].isalpha():
if str[i-1] == '+' and str[i+1] == '+':
return "true"
return "false"
# keep this function call here
# to see how to enter arguments in Python scrol... | normal | {
"blob_id": "d3a22cad850e895950ce322aac393b31758a2237",
"index": 7157,
"step-1": "def SimpleSymbols(str): \n if str[0].isalpha() and str[-1].isalpha():\n return \"false\"\n for i in range(0, len(str)):\n if str[i].isalpha():\n if str[i-1] == '+' and str[i+1] == '+':\n return \"true\"\n retur... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('/Users/neeraj.joshi/Downloads/index.html') as html_file:
soup = BeautifulSoup(html_file, 'lxml')
<|reserved_special_token_0|>
for tree in soup.find_all('tr'):
data = []
for todd in tree.find_all('td'):
... | flexible | {
"blob_id": "47be41bd5838b828acdc90c3ef5abdeec9da1e85",
"index": 1579,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('/Users/neeraj.joshi/Downloads/index.html') as html_file:\n soup = BeautifulSoup(html_file, 'lxml')\n<mask token>\nfor tree in soup.find_all('tr'):\n data = []\n for to... | [
0,
1,
2,
3,
4
] |
import torch
import torch.nn as nn
class ReconstructionLoss(nn.Module):
def __init__(self, config):
super(ReconstructionLoss, self).__init__()
self.velocity_dim = config.velocity_dim
def forward(self, pre_seq, gt_seq):
MSE_loss = nn.MSELoss()
rec_loss = MSE_loss(pre_seq[:, 1:-... | normal | {
"blob_id": "edc66bdc365f9c40ee33249bd2d02c0c5f28256a",
"index": 8386,
"step-1": "<mask token>\n\n\nclass VelocityLoss(nn.Module):\n\n def __init__(self, _mean, _std, config):\n super(VelocityLoss, self).__init__()\n self._mean = _mean\n self._std = _std\n self.device = config.devi... | [
14,
18,
19,
23,
24
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created for COMP5121 Lab on 2017 JUN 24
@author: King
"""
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
import sklearn.metrics as metrics
from sklearn.metrics import accuracy_score
data = [[... | normal | {
"blob_id": "33365d5ce5d2a7d28b76a7897de25e1f35d28855",
"index": 6269,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmodel.fit(data_train, label_train)\n<mask token>\nprint(model.score(data_test, label_test))\nprint(accuracy_score(label_test, predictions))\nprint(accuracy_score(label_test, predictions, ... | [
0,
1,
2,
3,
4
] |
from django.conf.urls import patterns, include, url
from django.contrib import admin
from metainfo.views import DomainListView
urlpatterns = patterns('',
# Examples:
# url(r'^$', 'metapull.views.home', name='home'),
# url(r'^blog/', include('blog.urls')),
url(r'^$', DomainListView.as_view()),
url(... | normal | {
"blob_id": "1599f5e49ec645b6d448e74719e240343077aedd",
"index": 5464,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('', url('^$', DomainListView.as_view()), url(\n '^admin/', include(admin.site.urls)), url('^domains/', include(\n 'metainfo.urls', namespace='domains')))\n",
... | [
0,
1,
2,
3
] |
#
# purpose: setup file to install the compiled-language python libraries
# usage: python setup.py config_fc --f90flags="-O2 -fopenmp" install --prefix=$PWD
#
from numpy.distutils.core import Extension
c_array_sqrt = Extension (name = "c_array_sqrt_omp",
sources = ["./src/c_array_sqrt_omp.... | normal | {
"blob_id": "c24bf42cfeaa1fb8ac188b9e08146762e0e86fed",
"index": 1542,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n from numpy.distutils.core import setup\n setup(name='array-sqrt-openmp', description=\n 'Illustration of Python extensions using OpenMP', author=... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class GeneralizedRCNN(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class GeneralizedRCNN(nn.Module):
def __init__(self, backbone, rpn, roi_heads, transform):
super(GeneralizedRCNN,... | flexible | {
"blob_id": "83ecb6b6237d7ee61f762b191ebc891521067a41",
"index": 9206,
"step-1": "<mask token>\n\n\nclass GeneralizedRCNN(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass GeneralizedRCNN(nn.Module):\n\n def __init__(self, backbone, rpn, roi_heads, transform):\n s... | [
1,
2,
3,
4,
5
] |
import boto3
from botocore.exceptions import ClientError
import logging
import subprocess
import string
import random
import time
import os
import sys
import time
import json
from ProgressPercentage import *
import logging
def upload_file(file_name, object_name=None):
RESULT_BUCKET_NAME = "worm4047bucket2"
s... | normal | {
"blob_id": "f405a3e9ccabbba6719f632eb9c51809b8deb319",
"index": 999,
"step-1": "<mask token>\n\n\ndef upload_file(file_name, object_name=None):\n RESULT_BUCKET_NAME = 'worm4047bucket2'\n s3_client = get_client('s3')\n max_retries = 5\n while max_retries > 0:\n try:\n response = s3_... | [
4,
5,
6,
7,
8
] |
class TrieTree(object):
def __init__(self):
self.size=0
self.childern=[None]*26
def insert(self,word):
node=self
for w in word:
index=ord(w)-97
node.size+=1
if node.childern[index]==None:
node.childern[index]=TrieTree()
... | normal | {
"blob_id": "a18fad746a1da3327d79ac0a61edd156c5fb8892",
"index": 6127,
"step-1": "\n\nclass TrieTree(object):\n def __init__(self):\n self.size=0\n self.childern=[None]*26\n def insert(self,word):\n node=self\n for w in word:\n index=ord(w)-97\n node.size+... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(my_file.readlines())
my_file.close()
<|reserved_special_token_0|>
for i in range(5):
new_file.write('new line ' + str(i + 1) + '\n')
new_file.close()
<|reserved_special_token_0|>
new_file.writelines(a)
new_file.close()
... | flexible | {
"blob_id": "d44f8a2dee35d76c152695d49d73f74e9c25bfa9",
"index": 3015,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(my_file.readlines())\nmy_file.close()\n<mask token>\nfor i in range(5):\n new_file.write('new line ' + str(i + 1) + '\\n')\nnew_file.close()\n<mask token>\nnew_file.writelines(a)... | [
0,
1,
2,
3
] |
#!/usr/bin/python
"""Source base class.
Based on the OpenSocial ActivityStreams REST API:
http://opensocial-resources.googlecode.com/svn/spec/2.0.1/Social-API-Server.xml#ActivityStreams-Service
"""
__author__ = ['Ryan Barrett <activitystreams@ryanb.org>']
import datetime
try:
import json
except ImportError:
imp... | normal | {
"blob_id": "29428e9ca4373c9f19d1412046ebe4fc3b1c48e3",
"index": 6300,
"step-1": "<mask token>\n\n\nclass Source(object):\n <mask token>\n\n def __init__(self, handler):\n self.handler = handler\n\n def get_activities(self, user_id=None, group_id=None, app_id=None,\n activity_id=None, star... | [
5,
6,
7,
8,
10
] |
<|reserved_special_token_0|>
def get_json_buques(centerx, centery, zoom):
count = 0
while True:
ignore = False
count += 1
print(centerx, centery, zoom)
out = check_output(['phantomjs', 'GetBarcos.js', str(centerx), str(
centery), str(zoom)])
links = json.loa... | flexible | {
"blob_id": "9ba5af7d2b6d4f61bb64a055efb15efa8e08d35c",
"index": 5379,
"step-1": "<mask token>\n\n\ndef get_json_buques(centerx, centery, zoom):\n count = 0\n while True:\n ignore = False\n count += 1\n print(centerx, centery, zoom)\n out = check_output(['phantomjs', 'GetBarcos.... | [
1,
2,
3,
4,
5
] |
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