code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
import sys
import pysolr
import requests
import logging
import json
import datetime
from urlparse import urlparse
from django.conf import settings
from django.utils.html import strip_tags
from aggregator.utils import mercator_to_llbbox
def get_date(layer):
"""
Returns a date for Solr. A date can be detected... | normal | {
"blob_id": "6eb59f62a1623f308e0eda4e616be4177a421179",
"index": 2254,
"step-1": "import sys\nimport pysolr\nimport requests\nimport logging\nimport json\nimport datetime\n\nfrom urlparse import urlparse\nfrom django.conf import settings\nfrom django.utils.html import strip_tags\n\nfrom aggregator.utils import m... | [
0
] |
<|reserved_special_token_0|>
def stacked_vertical():
total = Totals.get_or_insert('total')
if len(total.shirts) == 0:
shirts = sorted(T_Shirts, key=lambda shirt: shirt[0])
for shirt in shirts:
total.shirts.append(shirt[0])
total.votes.append(0)
votes = []
shirts... | flexible | {
"blob_id": "d8c9e1098dde9d61341ebc3c55eada5592f4b71a",
"index": 2891,
"step-1": "<mask token>\n\n\ndef stacked_vertical():\n total = Totals.get_or_insert('total')\n if len(total.shirts) == 0:\n shirts = sorted(T_Shirts, key=lambda shirt: shirt[0])\n for shirt in shirts:\n total.sh... | [
4,
5,
6,
7,
8
] |
<|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 = [m... | flexible | {
"blob_id": "ab5400f4b44a53cb5cc2f6394bcdb8f55fd218f0",
"index": 1813,
"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
] |
import random
import string
import steembase
import struct
import steem
from time import sleep
from time import time
from steem.transactionbuilder import TransactionBuilder
from steembase import operations
from steembase.transactions import SignedTransaction
from resultthread import MyThread
from charm.toolbox.pairingg... | normal | {
"blob_id": "a90b7e44cc54d4f96a13e5e6e2d15b632d3c4983",
"index": 290,
"step-1": "<mask token>\n\n\nclass GroupSignature:\n\n def __init__(self, groupObj):\n global util, group\n util = SecretUtil(groupObj, debug)\n self.group = groupObj\n\n def pkGen(self, h1str):\n gstr = (\n ... | [
10,
19,
22,
24,
31
] |
from dataloaders.datasets import caltech, embedding
from torch.utils.data import DataLoader
def make_data_loader(args, **kwargs):
if args.dataset == 'caltech101':
train_set = caltech.caltech101Classification(args, split='train')
val_set = caltech.caltech101Classification(args, split='val')
test_set = caltech.c... | normal | {
"blob_id": "1ea71f7b17809189eeacf19a6b7c4c7d88a5022c",
"index": 1070,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef make_id2class(args):\n if args.dataset == 'caltech101':\n return caltech.id2class\n",
"step-3": "<mask token>\n\n\ndef make_data_loader(args, **kwargs):\n if args.d... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def cos_two_terms(x):
s = 0
a = 1
s = s + a
a = -a * x ** 2 / ((2 * 0 + 1) * (2 * 0 + 2))
s = s + a
a = -a * x ** 2 / ((2 * 1 + 1) * (2 * 1 + 2))
s = s + a
a = -a * x ** 2 / ((2 * 2 + 1) * (2 * 2 + 2))
return s, abs(a)
def test_cos_Taylor():
x = 0... | flexible | {
"blob_id": "fb0dcb641dfb379751264dc0b18007f5d058d379",
"index": 3520,
"step-1": "<mask token>\n\n\ndef cos_two_terms(x):\n s = 0\n a = 1\n s = s + a\n a = -a * x ** 2 / ((2 * 0 + 1) * (2 * 0 + 2))\n s = s + a\n a = -a * x ** 2 / ((2 * 1 + 1) * (2 * 1 + 2))\n s = s + a\n a = -a * x ** 2 /... | [
2,
4,
5,
6,
7
] |
from src import npyscreen
from src.MainForm import MainForm
from src.ContactsForm import ContactsForm
from src.SendFileForm import SendFileForm
from src.MessageInfoForm import MessageInfoForm
from src.ForwardMessageForm import ForwardMessageForm
from src.RemoveMessageForm import RemoveMessageForm
class App(npyscreen.... | normal | {
"blob_id": "dc2c429bae10ee14737583a3726eff8fde8306c7",
"index": 6940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass App(npyscreen.StandardApp):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass App(npyscreen.StandardApp):\n\n def onStart(self):\n self.MainForm = self.addFor... | [
0,
1,
2,
3,
4
] |
default_app_config = 'child.apps.ChildConfig'
| normal | {
"blob_id": "290f96bb210a21183fe1e0e53219ad38ba889625",
"index": 1602,
"step-1": "<mask token>\n",
"step-2": "default_app_config = 'child.apps.ChildConfig'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def is_wall(r, c):
if r < 0 or r >= n or c < 0 or c >= n:
return True
return False
def find(r, c, cnt):
Q = []
Q.append((r, c))
visited[r][c] = 1
while Q:
tr, tc = Q.pop(0)
mine_cnt = 0
for i in range(8):
nr = tr + dr[i... | flexible | {
"blob_id": "8bce394c651931304f59bbca3e2f019212be9fc1",
"index": 4620,
"step-1": "<mask token>\n\n\ndef is_wall(r, c):\n if r < 0 or r >= n or c < 0 or c >= n:\n return True\n return False\n\n\ndef find(r, c, cnt):\n Q = []\n Q.append((r, c))\n visited[r][c] = 1\n while Q:\n tr, t... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class AdvertisementStatus(models.Model):
name = models.CharField(max_length=100)
def __str__(self):
return self.name
class Authors(models.Model):
name = models.CharField(max_length=20, db_index=True, verbose_name='ФИО')
email = models.EmailField()
phone = mo... | flexible | {
"blob_id": "c5bdbcc8ba38b02e5e5cf8b53362e87ba761443d",
"index": 8654,
"step-1": "<mask token>\n\n\nclass AdvertisementStatus(models.Model):\n name = models.CharField(max_length=100)\n\n def __str__(self):\n return self.name\n\n\nclass Authors(models.Model):\n name = models.CharField(max_length=2... | [
6,
7,
8,
10,
11
] |
##################
#Drawing Generic Rest of Board/
##################
def drawBoard(canvas,data):
canvas.create_rectangle(10,10,data.width-10,data.height-10, fill = "dark green")
canvas.create_rectangle(187, 160, 200, 550, fill = "white")
canvas.create_rectangle(187, 160, 561, 173, fill = "white")
can... | normal | {
"blob_id": "628e625be86053988cbaa3ddfe55f0538136e24d",
"index": 3599,
"step-1": "<mask token>\n",
"step-2": "def drawBoard(canvas, data):\n canvas.create_rectangle(10, 10, data.width - 10, data.height - 10, fill\n ='dark green')\n canvas.create_rectangle(187, 160, 200, 550, fill='white')\n can... | [
0,
1,
2,
3
] |
import boto3
from time import sleep
cfn = boto3.client('cloudformation')
try:
# Get base stack outputs.
stack_id = cfn.describe_stacks(StackName='MinecraftInstance')['Stacks'][0]['StackId']
cfn.delete_stack(StackName=stack_id)
print(f"Deleting Stack: {stack_id}")
except Exception as e:
print('Some... | normal | {
"blob_id": "b3fb210bcdec2ed552c37c6221c1f0f0419d7469",
"index": 8478,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n stack_id = cfn.describe_stacks(StackName='MinecraftInstance')['Stacks'][0][\n 'StackId']\n cfn.delete_stack(StackName=stack_id)\n print(f'Deleting Stack: {stack_id}... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ListingCustomFieldsGet(Service):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ListingCustomFieldsGet(Service):
<|reserved_special_token_0|>
def reply(self):
solr_fields = {}
... | flexible | {
"blob_id": "ab352c9431fda19bc21a9f7ffa075303641cca45",
"index": 155,
"step-1": "<mask token>\n\n\nclass ListingCustomFieldsGet(Service):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ListingCustomFieldsGet(Service):\n <mask token>\n\n def reply(self):\n solr_fields = ... | [
1,
2,
3,
5,
6
] |
from datetime import datetime
import requests as req
import smtplib
import mysql.connector
#mysql constant
MYSQL_HOST='den1.mysql6.gear.host'
MYSQL_USER='winlabiot'
MYSQL_PW='winlabiot+123'
MYSQL_DB="winlabiot"
Coffee_mailing_list_table='coffee_mailing_list'
#keys in dict receive via socket
TIME='time'
AMBIENT_TEM... | normal | {
"blob_id": "5488b32970a0b734334835457c712768a756de7f",
"index": 859,
"step-1": "from datetime import datetime\nimport requests as req\n\nimport smtplib\n\nimport mysql.connector\n\n#mysql constant\nMYSQL_HOST='den1.mysql6.gear.host'\nMYSQL_USER='winlabiot'\nMYSQL_PW='winlabiot+123'\nMYSQL_DB=\"winlabiot\"\nCoff... | [
0
] |
#Tom Healy
#Adapted from Chris Albon https://chrisalbon.com/machine_learning/linear_regression/linear_regression_using_scikit-learn/
#Load the libraries we will need
#This is just to play round with Linear regression more that anything else
from sklearn.linear_model import LinearRegression
from sklearn.datasets import ... | normal | {
"blob_id": "0f257d199ad0285d8619647434451841144af66d",
"index": 9379,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwarnings.filterwarnings(action='ignore', module='scipy', message=\n '^internal gelsd')\n<mask token>\nmodel.intercept_\nprint(model.intercept_)\nmodel.coef_\nprint(model.coef_)\n",
"... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def li():
return list(map(int, stdin.readline().split()))
def mp():
return map(int, stdin.readline().split())
<|reserved_special_token_0|>
def pr(n):
return stdout.write(str(n) + '\n')
<|reserved_special_token_0|>
def solve():
def check(n):
temp = n
... | flexible | {
"blob_id": "9cd1cb84c457db64019fa542efcf6500aa8d6d42",
"index": 9275,
"step-1": "<mask token>\n\n\ndef li():\n return list(map(int, stdin.readline().split()))\n\n\ndef mp():\n return map(int, stdin.readline().split())\n\n\n<mask token>\n\n\ndef pr(n):\n return stdout.write(str(n) + '\\n')\n\n\n<mask to... | [
4,
7,
8,
9,
10
] |
from rest_framework import serializers
from users.models import bills, Userinfo
class billsSerializer(serializers.HyperlinkedModelSerializer):
class Meta:
model = bills
fields = ('bname', 'bamount', 'duedate', 'user_id')
class UserinfoSerializer(serializers.HyperlinkedModelSerializer):
class ... | normal | {
"blob_id": "124ece8f2f4ecc53d19657e2463cc608befb1ce7",
"index": 3722,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass UserinfoSerializer(serializers.HyperlinkedModelSerializer):\n\n\n class Meta:\n model = Userinfo\n fields = ('fname', 'lname', 'address', 'city', 'state', 'zipc... | [
0,
1,
2,
3,
4
] |
from django.db import models
from private_storage.fields import PrivateFileField
class PrivateFile(models.Model):
title = models.CharField("Title", max_length=200)
file = PrivateFileField("File")
class PrivateFile2(models.Model):
title = models.CharField("Title", max_length=200)
file = models.FileFi... | normal | {
"blob_id": "e12c397ca1ae91ce314cda5fe2cd8e0ec4cfa861",
"index": 2199,
"step-1": "<mask token>\n\n\nclass PrivateFile2(models.Model):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass PrivateFile(models.Model):\n <mask token>\n <mask token>\n\n\nclass PrivateFile2(models.Model):\... | [
1,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
from tensorflow.python.ops.image_ops_impl import ResizeMethod
import sflow.core as tf
from sflow.core import layer
import numpy as np
# region arg helper
def _kernel_shape(nd, k, indim, outdim):
if isinstance(k, int):
k = [k for _ in range(nd)]
k = list(k)
assert len(k) =... | normal | {
"blob_id": "940c3b4a2b96907644c0f12deddd8aba4086a0f0",
"index": 5131,
"step-1": "<mask token>\n\n\ndef _kernel_shape(nd, k, indim, outdim):\n if isinstance(k, int):\n k = [k for _ in range(nd)]\n k = list(k)\n assert len(k) == nd\n k.extend([indim, outdim])\n return k\n\n\n<mask token>\n\n... | [
22,
26,
29,
32,
39
] |
<|reserved_special_token_0|>
def test_main_cnv():
main_cnv(tarfile)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.append('../circos_report/cnv_anno2conf')
<|reserved_special_token_0|>
def test_main_cnv():
main_cnv(tarfile)
if __name__ == '__main__':
... | flexible | {
"blob_id": "3c0beb7be29953ca2d7b390627305f4541b56efa",
"index": 69,
"step-1": "<mask token>\n\n\ndef test_main_cnv():\n main_cnv(tarfile)\n\n\n<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../circos_report/cnv_anno2conf')\n<mask token>\n\n\ndef test_main_cnv():\n main_cnv(tarfile)\n\n\nif _... | [
1,
2,
3,
4,
5
] |
from djitellopy import Tello
import time
import threading
import pandas as pd
class DataTello:
def __init__(self):
# Inicia objeto de controle do Tello
self.tello = Tello()
# Array onde será armazenado a lista de dados coletado pelo Tello
self.__data = []
self.... | normal | {
"blob_id": "9e751bbddabbec7c5e997578d99ef1b8c35efe06",
"index": 8108,
"step-1": "<mask token>\n\n\nclass DataTello:\n\n def __init__(self):\n self.tello = Tello()\n self.__data = []\n self.__array = []\n self.tempoVoo = 420000\n \"\"\"\n ___Padrão para nome dos arqui... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
class MztspiderSpider(CrawlSpider):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MztspiderSpider(Cra... | flexible | {
"blob_id": "a1ce43c3f64667619c4964bc4dc67215d3ecc1a0",
"index": 9215,
"step-1": "<mask token>\n\n\nclass MztspiderSpider(CrawlSpider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass MztspiderSpider(CrawlSpider):\n <mask token... | [
1,
2,
3,
4,
5
] |
import numpy as np
from global_module.implementation_module import Autoencoder
from global_module.implementation_module import Reader
import tensorflow as tf
from global_module.settings_module import ParamsClass, Directory, Dictionary
import random
import sys
import time
class Test:
def __init__(self):
se... | normal | {
"blob_id": "e008f9b11a9b7480e9fb53391870809d6dea5497",
"index": 3953,
"step-1": "<mask token>\n\n\nclass Test:\n\n def __init__(self):\n self.iter_test = 0\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Test:\n\n def __init__(self):\n self.iter_test = 0\n\n d... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while True:
ret, frame = cap.read()
if ret:
print('Decoded frame')
cv2.imwrite('fr_' + str(count) + '.png', frame)
count += 1
else:
print("Couldn't decoded frame")
<|reserved_special_t... | flexible | {
"blob_id": "40ac3292befa2354878927ada0e10c24368a9d73",
"index": 2643,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n ret, frame = cap.read()\n if ret:\n print('Decoded frame')\n cv2.imwrite('fr_' + str(count) + '.png', frame)\n count += 1\n else:\n prin... | [
0,
1,
2,
3,
4
] |
# 효율적인 해킹
# https://www.acmicpc.net/problem/1325
from collections import deque
import sys
input = sys.stdin.readline
n, m = map(int, input().split())
graph = [[] for _ in range(n + 1)]
for _ in range(m):
a, b = map(int, input().split())
graph[b].append(a) # B를 해킹하면 A도 해킹할 수 있다
def bfs(start):
visited =... | normal | {
"blob_id": "8a631adc8d919fb1dded27177818c4cb30148e94",
"index": 610,
"step-1": "<mask token>\n\n\ndef bfs(start):\n visited = [False] * (n + 1)\n visited[start] = True\n q = deque()\n q.append(start)\n cnt = 1\n while q:\n now = q.popleft()\n for i in graph[now]:\n if ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Mish(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def forward(self, input):
"""
Forward pass of the function.
"""
return Func.mish(input, inplace=self.inplace)
<|reserved_special_token_1|>
<|reserved_special_to... | flexible | {
"blob_id": "2deb73c7d2588ea1a5b16eb1ed617583d41f0130",
"index": 2846,
"step-1": "<mask token>\n\n\nclass Mish(nn.Module):\n <mask token>\n <mask token>\n\n def forward(self, input):\n \"\"\"\n Forward pass of the function.\n \"\"\"\n return Func.mish(input, inplace=self.inpl... | [
2,
3,
4,
5,
6
] |
from typing import Type
from sqlalchemy.exc import IntegrityError
from src.main.interface import RouteInterface as Route
from src.presenters.helpers import HttpRequest, HttpResponse
from src.presenters.errors import HttpErrors
def flask_adapter(request: any, api_route: Type[Route]) -> any:
"""Adapter pattern for ... | normal | {
"blob_id": "3212bb7df990ad7d075b8ca49a99e1072eab2a90",
"index": 595,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef flask_adapter(request: any, api_route: Type[Route]) ->any:\n \"\"\"Adapter pattern for Flask\n :param - Flask Request\n :api_route: Composite Routes\n \"\"\"\n try:\... | [
0,
1,
2,
3
] |
from pyspark.sql.types import StructType, StructField, StringType, TimestampType, IntegerType
from main.config.spark_config import SparkConfiguration
import main.config.constants as Constants
from main.connectors.kafka_connector import KafkaConnector, extract_json_data
def main():
# Configure Spark Session
co... | normal | {
"blob_id": "23099b29fb5898c2556d1612690e33860662ca35",
"index": 9846,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n config = {'spark.jars.packages':\n 'io.delta:delta-core_2.12:0.8.0,org.postgresql:postgresql:9.4.1211,org.apache.spark:spark-streaming-kafka-0-10_2.12:3.0.0,or... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def positive_words(scrape_results_df):
def text_process(text):
nopunc = [char for char in text if char not in string.punctuation]
nopunc = ''.join(nopunc)
return [word for word in nopunc.split() if word.lower() not in
stopwords.words('english')]
... | flexible | {
"blob_id": "82f86284dddf48bf2c65ddf55eb6d7a372306373",
"index": 7182,
"step-1": "<mask token>\n\n\ndef positive_words(scrape_results_df):\n\n def text_process(text):\n nopunc = [char for char in text if char not in string.punctuation]\n nopunc = ''.join(nopunc)\n return [word for word in... | [
2,
3,
4,
5,
6
] |
from tkinter import *
from tkinter import filedialog
from tkinter import scrolledtext
import tkinter as tk
import os
import sys
import subprocess
import shlex
from subprocess import check_output
import pathlib
| normal | {
"blob_id": "11576597429e119cf4887a88139df4a9e6d7eb66",
"index": 1409,
"step-1": "<mask token>\n",
"step-2": "from tkinter import *\nfrom tkinter import filedialog\nfrom tkinter import scrolledtext\nimport tkinter as tk\nimport os\nimport sys\nimport subprocess\nimport shlex\nfrom subprocess import check_outpu... | [
0,
1
] |
#Purpose: find the bonds, angles in Zr/GPTMS .xyz outpuf file from simulation
from Tkinter import Tk
from tkFileDialog import askopenfilename
Tk().withdraw()
from pylab import *
from scipy import *
from numpy import *
import numpy as np
import math
##################################################################... | normal | {
"blob_id": "82abed3a60829eeabf6b9e8b791085d130ec3dd4",
"index": 3086,
"step-1": "#Purpose: find the bonds, angles in Zr/GPTMS .xyz outpuf file from simulation \n\nfrom Tkinter import Tk\nfrom tkFileDialog import askopenfilename\nTk().withdraw()\n\nfrom pylab import *\nfrom scipy import *\nfrom numpy import *\ni... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ResPartner(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ResPartner(models.Model):
_inherit = 'res.partner'
pu... | flexible | {
"blob_id": "f26b127b4d968c1a168a57825a5acfffbf027bef",
"index": 3372,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ResPartner(models.Model):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ResPartner(models.Model):\n _inherit = 'res.partner'\n purchase_type... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_second_long(time_str=None):
if time_str is None:
return long(time.time())
time_array = time.strptime(time_str, '%Y-%m-%d %H:%M:%S')
return long(time.mktime(time_array))
<|reserved_special_token_0|>
def get_curtimestamp():
return int(time.time() * 1000)
... | flexible | {
"blob_id": "e735529eddd3a46ea335e593e5937558b50b142d",
"index": 2276,
"step-1": "<mask token>\n\n\ndef get_second_long(time_str=None):\n if time_str is None:\n return long(time.time())\n time_array = time.strptime(time_str, '%Y-%m-%d %H:%M:%S')\n return long(time.mktime(time_array))\n\n\n<mask t... | [
7,
9,
10,
11,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def threeNumberSum(array, targetSum):
array.sort()
triplet = []
for i in range(len(array) - 2):
left = i + 1
right = len(array) - 1
while left < right:
current_sum = array[i] + arr... | flexible | {
"blob_id": "240f5e9cbb38f319b6e03b1b7f9cae7655ac4385",
"index": 5258,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef threeNumberSum(array, targetSum):\n array.sort()\n triplet = []\n for i in range(len(array) - 2):\n left = i + 1\n right = len(array) - 1\n while lef... | [
0,
1,
2,
3,
4
] |
class Solution:
def letterCombinations(self, digits):
"""
:type digits: str
:rtype: List[str]
"""
if not digits:
return []
result_set = []
letters = {'2': 'abc', '3': 'def', '4': 'ghi', '5': 'jkl', '6':
'mno', '7': 'pqrs', '8': 'tuv', ... | normal | {
"blob_id": "aec311cae7cb6cbe3e3a927a133ec20a2d2afbf5",
"index": 1312,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def letterCombinations(self, digits):\n \"\"\"\n :type digits: str\n :rtype: List[str]\n \"\"\"\n ... | [
0,
1,
2
] |
import numpy as np
import sys
import os
import os.path
import json
import optparse
import time
import pandas as pd
#Randomize and split the inference set according to hor_pred
#Generate .npy file for each hp selected
#Coge valores aleatorios de la columna de etiquetas en función del horizonte de predicció... | normal | {
"blob_id": "83a92c0b645b9a2a483a01c19a47ab5c296ccbd9",
"index": 6907,
"step-1": "<mask token>\n\n\ndef addOptions(parser):\n parser.add_option('--NNfile', default='', help=\n 'Config json file for the data to pass to the model')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef addOptions(parse... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class QuotesByMonth:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class QuotesByRating:
def __init__(self):
self.chart = pygal.Histogram(title='Quotes by Rating', margin=20,
show_legend=False, style=style)
... | flexible | {
"blob_id": "6f6f57ff317d7e3c6e6ae4d450c6fdf0e22eb4eb",
"index": 7256,
"step-1": "<mask token>\n\n\nclass QuotesByMonth:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass QuotesByRating:\n\n def __init__(self):\n self.chart = pygal.Histogram(title='Quotes by Rating', margin=20,\n ... | [
9,
16,
20,
21,
23
] |
# -*- coding: utf-8 -*-
"""
:copyright: (c) 2014-2016 by Mike Taylor
:license: MIT, see LICENSE for more details.
Micropub Tools
"""
import requests
from bs4 import BeautifulSoup, SoupStrainer
try: # Python v3
from urllib.parse import urlparse, urljoin
except ImportError:
from urlparse import urlparse, urlj... | normal | {
"blob_id": "1bb82a24faed6079ec161d95eff22aa122295c13",
"index": 3982,
"step-1": "<mask token>\n\n\ndef setParser(htmlParser='html5lib'):\n global _html_parser\n _html_parser = htmlParser\n\n\ndef discoverEndpoint(domain, endpoint, content=None, look_in={'name':\n 'link'}, test_urls=True, validateCerts=... | [
2,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class AttachmentTestCase(BaseTestCase):
def set_up(self):
BaseTestCase.set_up(self)
self.init_data = dict(content='Important attachment content.',
file_name='test_file1.txt', description='A test file.', size=14,
author='user1', time=None)
... | flexible | {
"blob_id": "41681a80807800efc06b3912533d739dab2cd085",
"index": 1999,
"step-1": "<mask token>\n\n\nclass AttachmentTestCase(BaseTestCase):\n\n def set_up(self):\n BaseTestCase.set_up(self)\n self.init_data = dict(content='Important attachment content.',\n file_name='test_file1.txt', ... | [
5,
10,
11,
12,
14
] |
class Node(object):
def __init__(self, d, n=None):
self.data = d
self.next_node = n
def get_data(self):
return self.data
def set_data(self, d):
self.data = d
def get_next(self):
return self.next_node
def set_next(self, n):
self.next_node=n
class... | normal | {
"blob_id": "de3e952ad43fe7e323e8f975a45bbd4eec7192db",
"index": 3481,
"step-1": "class Node(object):\n\n def __init__(self, d, n=None):\n self.data = d\n self.next_node = n\n\n def get_data(self):\n return self.data\n\n def set_data(self, d):\n self.data = d\n\n def get_n... | [
0
] |
#!python3
import configparser
parser = configparser.ConfigParser()
parser.read("sim.conf")
print(parser.get("config", "option1"))
print(parser.get("config", "option2"))
print(parser.get("config", "option3"))
| normal | {
"blob_id": "cf5ab10ce743aa261867501e93f498022e5908fe",
"index": 7360,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.read('sim.conf')\nprint(parser.get('config', 'option1'))\nprint(parser.get('config', 'option2'))\nprint(parser.get('config', 'option3'))\n",
"step-3": "<mask token>\nparser = con... | [
0,
1,
2,
3,
4
] |
"""storeproject URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-... | normal | {
"blob_id": "4a8fa195a573f8001e55b099a8882fe71bcca233",
"index": 8335,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrouter.register('users', views.CategoryView)\n<mask token>\nif settings.DEBUG:\n urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT\n )\n",
"step-3": ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@app.route('/')
def show_home():
return render_template('index.html')
@app.route('/addhost', methods=['GET', 'POST'])
def hosts():
if request.method == 'POST':
db = mongo_login()
hosts_collection = db.hosts
host = request.form.to_dict()
hosts_coll... | flexible | {
"blob_id": "ad813216ba8162a7089340c677e47c3e656f7c95",
"index": 6198,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef show_home():\n return render_template('index.html')\n\n\n@app.route('/addhost', methods=['GET', 'POST'])\ndef hosts():\n if request.method == 'POST':\n db = mongo_login()\n ... | [
6,
7,
10,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(num1)
print(num2)
print(add)
print(sub)
print(mul)
print(div)
print(mod)
print(exp)
print(fd)
<|reserved_special_token_1|>
num1 = 101
num2 = 20
add = num1 + num2
sub = num1 - num2
mul = num1 * num2
div = num1 / num2
mod =... | flexible | {
"blob_id": "3ffbef142d8fb53b734567ebea874f9c59ff9a9e",
"index": 1455,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(num1)\nprint(num2)\nprint(add)\nprint(sub)\nprint(mul)\nprint(div)\nprint(mod)\nprint(exp)\nprint(fd)\n",
"step-3": "num1 = 101\nnum2 = 20\nadd = num1 + num2\nsub = num1 - num2\nm... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Graph:
def __init__(self, V: int, W: int):
self.V = V
self.E = 0
self.adj = []
self.W = W
for i in range(V):
nears = []
self.adj.append(nears)
def AddEdge(self, v: int, w: int):
self.adj[v].append(w)
... | flexible | {
"blob_id": "b6d8a918659f733919fe3bb4be9037e36ad32386",
"index": 272,
"step-1": "<mask token>\n\n\nclass Graph:\n\n def __init__(self, V: int, W: int):\n self.V = V\n self.E = 0\n self.adj = []\n self.W = W\n for i in range(V):\n nears = []\n self.adj.a... | [
14,
17,
18,
19,
24
] |
import bs4
from urllib.request import urlopen as uReq
from bs4 import BeautifulSoup as soup
import pandas as pd
import time
from urllib.request import Request
import requests
import json
import re
import sys
def compare(mystring):
def usd_to_ngn():
print("Getting USD to NGN Rate")
r... | normal | {
"blob_id": "d96038a715406388b4de4611391dee18fc559d5a",
"index": 2693,
"step-1": "<mask token>\n\n\ndef compare(mystring):\n\n def usd_to_ngn():\n print('Getting USD to NGN Rate')\n req = requests.get(\n 'http://free.currconv.com/api/v7/convert?q=USD_NGN&apiKey=5029a99b396929294f63'\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def broadcast(msg, prefix=''):
"""Broadcasts a message to all the clients."""
for sock in clients:
sock.send(bytes(prefix, 'utf8') + msg)
def broadcast_file(msg):
for sock in clients:
sock.send(msg)
def private_message(address, message):
message = '<pri... | flexible | {
"blob_id": "9f02313b6f91f83e3a8b4af8d9447b1d8f3558f6",
"index": 4430,
"step-1": "<mask token>\n\n\ndef broadcast(msg, prefix=''):\n \"\"\"Broadcasts a message to all the clients.\"\"\"\n for sock in clients:\n sock.send(bytes(prefix, 'utf8') + msg)\n\n\ndef broadcast_file(msg):\n for sock in cli... | [
5,
6,
7,
8,
9
] |
#!/usr/bin/python
#
# Dividend!
#
import os
import sys
import urllib2
import math
import numpy
from pylab import *
#
# Dividend adjusted! ... | normal | {
"blob_id": "6454790c98b254edeead4e68ef7f5760c9105a57",
"index": 433,
"step-1": "#!/usr/bin/python\n#\n# Dividend!\n#\n\nimport os\nimport sys\nimport urllib2\nimport math\nimport numpy\nfrom pylab import *\n\n# ... | [
0
] |
<|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": "e6884afaae15e903c62eecb3baec868548998080",
"index": 2106,
"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 = [('words', '00... | [
0,
1,
2,
3,
4
] |
""" Problem statement:
https://leetcode.com/problems/contains-duplicate-ii/description/
Given an array of integers and an integer k, find out whether
there are two distinct indices i and j in the array such that nums[i] = nums[j]
and the absolute difference between i and j is at most k.
"""
class Solution:
def c... | normal | {
"blob_id": "33c241747062ab0d374082d2a8179335503fa212",
"index": 3320,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def containsNearbyDuplicate(self, nums, k):\n \"\"\" Time complexi... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Sampler:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@classmethod
def standard_normal(cls, size=1):
return list(itertools.islice(cls.randn_gen, size))
@classmethod
def randn(cls):
return next(cl... | flexible | {
"blob_id": "ddeff852e41b79fb71cea1e4dc71248ddef85d79",
"index": 7033,
"step-1": "<mask token>\n\n\nclass Sampler:\n <mask token>\n <mask token>\n <mask token>\n\n @classmethod\n def standard_normal(cls, size=1):\n return list(itertools.islice(cls.randn_gen, size))\n\n @classmethod\n ... | [
4,
7,
9,
10
] |
import torch
import util
import numpy as np
import argparse
import losses
args = argparse.Namespace()
args.device = torch.device('cpu')
args.num_mixtures = 20
args.init_mixture_logits = np.ones(args.num_mixtures)
args.softmax_multiplier = 0.5
args.relaxed_one_hot = False
args.temperature = None
temp = np.arange(args.... | normal | {
"blob_id": "8f558593e516aa4a769b7c5e1c95c8bc23a36420",
"index": 1232,
"step-1": "<mask token>\n\n\ndef get_grads_correct(seed):\n util.set_seed(seed)\n theta_grads_correct = []\n phi_grads_correct = []\n log_weight, log_q = losses.get_log_weight_and_log_q(generative_model,\n inference_network... | [
5,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
def getSize():
x = driver.get_window_size()['width']
y = driver.get_window_size()['height']
return x, y
<|reserved_special_token_0|>
def swipeUp(t):
l = getSize()
x1 = int(l[0] * 0.5)
y1 = int(l[1] * 0.75)
y2 = int(l[1] * 0.25)
driver.swipe(x1, y1, x1, ... | flexible | {
"blob_id": "6e614d1235a98ef496956001eef46b4447f0bf9b",
"index": 4677,
"step-1": "<mask token>\n\n\ndef getSize():\n x = driver.get_window_size()['width']\n y = driver.get_window_size()['height']\n return x, y\n\n\n<mask token>\n\n\ndef swipeUp(t):\n l = getSize()\n x1 = int(l[0] * 0.5)\n y1 = ... | [
3,
4,
5,
6,
7
] |
import numpy as np
from sklearn.decomposition import PCA
import pandas as pd
from numpy.testing import assert_array_almost_equal
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn import decomposition
from sklearn import datasets
def transform(x):
if x == 'Kama':
return 0
elif x =... | normal | {
"blob_id": "ef04e808a2a0e6570b28ef06784322e0b2ca1f8f",
"index": 4774,
"step-1": "<mask token>\n\n\ndef transform(x):\n if x == 'Kama':\n return 0\n elif x == 'Rosa':\n return 1\n else:\n return 2\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef transform(x):\n if x == 'K... | [
1,
2,
3,
4,
5
] |
#coding=utf-8
i=1
s=0
while s<=8848:
s=s+(2**i)*0.2*10**(-3)
i=i+1
print '对折次数:',i
| normal | {
"blob_id": "98a384392d0839ddf12f3374c05929bc5e32987b",
"index": 9242,
"step-1": "#coding=utf-8\ni=1\ns=0\nwhile s<=8848:\n\ts=s+(2**i)*0.2*10**(-3)\n\ti=i+1\nprint '对折次数:',i\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class UrlPath:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class UrlPath:
@staticmethod
def combine(*args):
result = ''
for path in args:
result += path if path.endswith('/') else '{}/'.format(path)
... | flexible | {
"blob_id": "aa579025cacd11486a101b2dc51b5ba4997bf84a",
"index": 95,
"step-1": "<mask token>\n",
"step-2": "class UrlPath:\n <mask token>\n",
"step-3": "class UrlPath:\n\n @staticmethod\n def combine(*args):\n result = ''\n for path in args:\n result += path if path.endswith... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def generate(root: Dict):
relations: List[Dict] = []
subj = DPHelper.get_subject(root)
obj = DPHelper.get_object(root)
if subj is not None and DPHelper.is_proper_noun(subj
) and obj is not None and DPHelp... | flexible | {
"blob_id": "5923a12378225fb6389e7e0275af6d4aa476fe87",
"index": 1635,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generate(root: Dict):\n relations: List[Dict] = []\n subj = DPHelper.get_subject(root)\n obj = DPHelper.get_object(root)\n if subj is not None and DPHelper.is_proper_n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def index(request):
print(request.session)
today = datetime.datetime.now()
return render(request, 'index.html', {'today': today.strftime('%d-%m=%Y')})
def isFileOpen(request):
stack = request.session['stack']
if stack > 0 and request.session.get('name'
) != N... | flexible | {
"blob_id": "3378ce72ae67d09258554048138b7f9023000922",
"index": 6619,
"step-1": "<mask token>\n\n\ndef index(request):\n print(request.session)\n today = datetime.datetime.now()\n return render(request, 'index.html', {'today': today.strftime('%d-%m=%Y')})\n\n\ndef isFileOpen(request):\n stack = requ... | [
12,
14,
15,
17,
19
] |
# Copyright 2010 Google Inc.
#
# 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 applicable law or agreed to in writing,... | normal | {
"blob_id": "e11c479a99ab68755de8ab565e3d360d557129cf",
"index": 6036,
"step-1": "# Copyright 2010 Google Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://w... | [
0
] |
print('-' * 60)
print(
'Welcome to CLUB425, the most lit club in downtown ACTvF. Before you can enter, I need you yo answer some question...'
)
print()
age = input('What is your age today? ')
age = int(age)
if age >= 21:
print('Cool, come on in.')
else:
print(
'Your gonna need to back up. This c... | normal | {
"blob_id": "19ffac718008c7c9279fb8cbc7608597d2d3e708",
"index": 3937,
"step-1": "<mask token>\n",
"step-2": "print('-' * 60)\nprint(\n 'Welcome to CLUB425, the most lit club in downtown ACTvF. Before you can enter, I need you yo answer some question...'\n )\nprint()\n<mask token>\nif age >= 21:\n pri... | [
0,
1,
2
] |
def solution(num):
if num < 10:
num = str(num) + str(0)
else:
num = str(num)
cycle_val = 0
new_num = ""
temp_num = num[:]
while new_num != num:
sum_num = int(temp_num[0]) + int(temp_num[1])
new_num = temp_num[-1] + str(int(temp_num[0]) + int(tem... | normal | {
"blob_id": "cec772f1e470aae501aa7c638ec4cbb565848804",
"index": 9258,
"step-1": "<mask token>\n",
"step-2": "def solution(num):\n if num < 10:\n num = str(num) + str(0)\n else:\n num = str(num)\n cycle_val = 0\n new_num = ''\n temp_num = num[:]\n while new_num != num:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class fake_logger(object):
def __init__(self):
self.msg = None
def info(self, msg, *args):
pass
def warn(self, msg, *args):
self.msg = msg.reason
class TestRequestData(object):
def test_read_url(self, monkeypatch):
monkeypatch.setattr(... | flexible | {
"blob_id": "2bbfbc597a4e1f8b46f58a4c6002a9943eff557a",
"index": 5644,
"step-1": "<mask token>\n\n\nclass fake_logger(object):\n\n def __init__(self):\n self.msg = None\n\n def info(self, msg, *args):\n pass\n\n def warn(self, msg, *args):\n self.msg = msg.reason\n\n\nclass TestRequ... | [
7,
9,
10,
12,
14
] |
# This file is used to run a program to perform Active measuremnts
import commands
import SocketServer
import sys
#Class to handle Socket request
class Handler(SocketServer.BaseRequestHandler):
def handle(self):
# Get the IP of the client
IP = self.request.recv(1024)
#print 'IP=' + IP
... | normal | {
"blob_id": "c853f922d1e4369df9816d150e5c0abc729b325c",
"index": 4902,
"step-1": "# This file is used to run a program to perform Active measuremnts\n\n\nimport commands\nimport SocketServer\nimport sys\n\n#Class to handle Socket request\nclass Handler(SocketServer.BaseRequestHandler):\n\n def handle(self):\n... | [
0
] |
<|reserved_special_token_0|>
class ConnectionManager:
<|reserved_special_token_0|>
def handle(self, msg):
if msg['type'] in {'register', 'heartbeat'}:
self.store.reg_hb(**msg['payload'])
elif msg['type'] == 'result':
self.store.result(msg['payload'])
return 'se... | flexible | {
"blob_id": "03b38e6e2d0097d5d361b0794aba83b8e430323d",
"index": 4370,
"step-1": "<mask token>\n\n\nclass ConnectionManager:\n <mask token>\n\n def handle(self, msg):\n if msg['type'] in {'register', 'heartbeat'}:\n self.store.reg_hb(**msg['payload'])\n elif msg['type'] == 'result'... | [
3,
4,
7,
8,
10
] |
import tensorflow as tf
import numpy as np
import tensorflow_datasets as tfds
print(tf.__version__)
imdb, info = tfds.load("imdb_reviews", with_info=True, as_supervised=True)
train_data = imdb['train']
test_data = imdb['test']
# 25000 in each set
training_sentences = []
training_labels = []
testing_sentences = []
... | normal | {
"blob_id": "921c45af3ba34a1b12657bf4189fc8dd66fa44a6",
"index": 3860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(tf.__version__)\n<mask token>\nfor s, l in train_data:\n training_sentences.append(str(s.numpy()))\n training_labels.append(l.numpy())\nfor s, l in test_data:\n testing_sen... | [
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_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "a7d7408808f28343a51ff6522c5e14747c8c6e43",
"index": 9819,
"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 = [('s1app', '00... | [
0,
1,
2,
3,
4
] |
import cv2, os, fitz, shutil
import numpy as np
from PIL import Image
from pytesseract import pytesseract
from PIL import UnidentifiedImageError
pytesseract.tesseract_cmd = 'C:\\Program Files (x86)\\Tesseract-OCR\\tesseract.exe'
config = r'--oem 3 --psm'
# Возвращает путь к картинке, созданной на основе 1 ... | normal | {
"blob_id": "84980b8923fa25664833f810a906d27531145141",
"index": 1066,
"step-1": "<mask token>\n\n\ndef pdf_to_png(filename):\n doc = fitz.open('pdf_files\\\\{}'.format(filename))\n zoom = 4\n page = doc.loadPage(0)\n mat = fitz.Matrix(zoom, zoom)\n pix = page.getPixmap(matrix=mat)\n new_filena... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class FileBlobstore:
<|reserved_special_token_0|>
def _csum_to_name(self, csum):
"""Return string name of link relative to root"""
return _checksum_to_path(csum)
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "4fb1ece28cd7c6e2ac3a479dcbf81ee09ba14223",
"index": 3096,
"step-1": "<mask token>\n\n\nclass FileBlobstore:\n <mask token>\n\n def _csum_to_name(self, csum):\n \"\"\"Return string name of link relative to root\"\"\"\n return _checksum_to_path(csum)\n <mask token>\n <mask to... | [
8,
12,
16,
20,
27
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(c + a * y * y / b)
<|reserved_special_token_1|>
a, b, c, y = 4.4, 0.0, 4.2, 3.0
print(c + a * y * y / b)
| flexible | {
"blob_id": "2c43ede960febfb273f1c70c75816848768db4e5",
"index": 6599,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(c + a * y * y / b)\n",
"step-3": "a, b, c, y = 4.4, 0.0, 4.2, 3.0\nprint(c + a * y * y / b)\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Profile(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Profile(models.Model):
user = models.OneToOneField(User... | flexible | {
"blob_id": "3e7df9a733c94b89d22d10883844c438444d5e2c",
"index": 8010,
"step-1": "<mask token>\n\n\nclass Profile(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Profile(models.Model):\n user = models.OneToOneField(User, on_delete... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def obj_rec(obj, t, flag=0, acc=''):
v_obj = type(obj)
r = ''
if type(obj) not in [dict, list, map]:
ref_url = re.findall('\\((http.*?)\\)', obj)
ref_title = re.findall('\\[[^\\[\\]]*\\]', obj)
if ref_url:
url = ref_url[len(ref_url) - 1].str... | flexible | {
"blob_id": "739921a6a09edbb81b442f4127215746c601a69a",
"index": 4990,
"step-1": "<mask token>\n\n\ndef obj_rec(obj, t, flag=0, acc=''):\n v_obj = type(obj)\n r = ''\n if type(obj) not in [dict, list, map]:\n ref_url = re.findall('\\\\((http.*?)\\\\)', obj)\n ref_title = re.findall('\\\\[[... | [
1,
2,
3,
4,
5
] |
"""
We have created mash sketches of the GPDB database, the MGV database, and the SDSU phage, and
this will figure out the top hits and summarize their familes.
"""
import os
import sys
import argparse
def best_hits(distf, maxscore, verbose=False):
"""
Find the best hits
"""
bh = {}
allph = set()... | normal | {
"blob_id": "22523304c9e2ce1339a7527cdbd67a81c780d806",
"index": 1090,
"step-1": "<mask token>\n\n\ndef best_hits(distf, maxscore, verbose=False):\n \"\"\"\n Find the best hits\n \"\"\"\n bh = {}\n allph = set()\n with open(distf, 'r') as din:\n for li in din:\n p = li.strip()... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def test_app_models():
assert models.ComponentsApp.allowed_subpage_models() == [models.
ComponentsApp, models.BannerComponent]
<|reserved_special_token_0|>
@pytest.mark.django_db
def test_set_slug(en_locale):
instance = models.ComponentsApp.objects.create(title_en_gb='... | flexible | {
"blob_id": "b1622aa65422fcb69a16ad48a26fd9ed05b10382",
"index": 8882,
"step-1": "<mask token>\n\n\ndef test_app_models():\n assert models.ComponentsApp.allowed_subpage_models() == [models.\n ComponentsApp, models.BannerComponent]\n\n\n<mask token>\n\n\n@pytest.mark.django_db\ndef test_set_slug(en_loca... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/python
#
# Author: Johnson Kachikaran (johnsoncharles26@gmail.com)
# Date: 7th August 2016
# Google Drive API:
# https://developers.google.com/drive/v3/reference/
# https://developers.google.com/resources/api-libraries/documentation/drive/v3/python/latest/
"""
Includes functions to integrate with a u... | normal | {
"blob_id": "033719313f92aaf3c62eb1b07a9aa08f13c7bb6e",
"index": 2600,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_metadata(file_id, user_settings=None):\n \"\"\"\n Obtains the metadata of a file\n\n :param str file_id: the identifier of the file whose metadata is needed\n :par... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from mathgraph3D.core.plot import *
from mathgraph3D.core.functions import *
| flexible | {
"blob_id": "b58cc08f8f10220373fa78f5d7249bc883b447bf",
"index": 6991,
"step-1": "<mask token>\n",
"step-2": "from mathgraph3D.core.plot import *\nfrom mathgraph3D.core.functions import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from pyNastran.bdf.fieldWriter import print_card
from pyNastran.bdf.bdfInterface.assign_type import (integer, integer_or_blank,
double_or_blank, string_or_blank)
class NLPARM(object):
"""
Defines a set of parameters for nonlinear static analysis iteration
strategy.
+--------+--------+------+-----... | normal | {
"blob_id": "7701a98d836dc9551a4e2eb4b7d9c10307b3f665",
"index": 1411,
"step-1": "<mask token>\n\n\nclass NLPARM(object):\n <mask token>\n <mask token>\n\n def __init__(self):\n pass\n\n def add(self, card=None, comment=''):\n if comment:\n self._comment = comment\n se... | [
6,
7,
8,
9,
10
] |
from flask import Flask, render_template
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql+mysqldb://sql3354595:7Haz6Ng1fm@sql3.freemysqlhosting.net/sql3354595'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
app.config['SECRET_KEY'] = 'mysecret'
db = S... | normal | {
"blob_id": "d7240703bc4cf9b566e7b50a536c83497cd8c6d7",
"index": 7116,
"step-1": "<mask token>\n\n\nclass TipoUsuarios(db.Model):\n id = db.Column(db.Integer, primary_key=True, nullable=False)\n texto = db.Column(db.String(50))\n usuarios = db.relationship('Usuarios', backref='tipo', lazy='dynamic')\n\n... | [
7,
8,
10,
11,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(z.shape)
print(x.shape)
assert z.shape == x.shape
<|reserved_special_token_1|>
<|reserved_special_token_0|>
x = np.random.random_sample(10 * 32 * 1024)
w = windowed(x, n=1024, step=128)
z = DisaggregationManager._overlap_... | flexible | {
"blob_id": "6d4950ca61cd1e2ee7ef8b409577e9df2d65addd",
"index": 4462,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(z.shape)\nprint(x.shape)\nassert z.shape == x.shape\n",
"step-3": "<mask token>\nx = np.random.random_sample(10 * 32 * 1024)\nw = windowed(x, n=1024, step=128)\nz = Disaggregation... | [
0,
1,
2,
3
] |
def maior(a,b):
if a > b:
return a
else:
return b
a = int(input("Digite o 1 valor: "))
b = int(input("Digite o 2 valor: "))
print(maior(a,b))
| normal | {
"blob_id": "f4ca7f31000a1f649876b19ef937ece9958dd60f",
"index": 5352,
"step-1": "<mask token>\n",
"step-2": "def maior(a, b):\n if a > b:\n return a\n else:\n return b\n\n\n<mask token>\n",
"step-3": "def maior(a, b):\n if a > b:\n return a\n else:\n return b\n\n\n<ma... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('O valor inteiro é %d' % b)
print('O valor decimal é %.6f' % c)
<|reserved_special_token_1|>
a = float(input('Digite um número:'))
b = a - a % 1
c = a % 1
print('O valor inteiro é %d' % b)
print('O valor decimal é %.6f' %... | flexible | {
"blob_id": "1b09b18926dc95d4c4b3088f45088f12c162ccb3",
"index": 5465,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('O valor inteiro é %d' % b)\nprint('O valor decimal é %.6f' % c)\n",
"step-3": "a = float(input('Digite um número:'))\nb = a - a % 1\nc = a % 1\nprint('O valor inteiro é %d' % b)\... | [
0,
1,
2,
3
] |
# 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 applicable law or agreed to in writing, software
# distributed under t... | normal | {
"blob_id": "2bf057621df3b860c8f677baf54673d2da8c2bd1",
"index": 5804,
"step-1": "<mask token>\n\n\nclass TestCOEClusters(base.TestCase):\n <mask token>\n\n def get_mock_url(self, service_type=\n 'container-infrastructure-management', base_url_append=None, append\n =None, resource=None):\n ... | [
3,
5,
6,
7,
8
] |
#!/usr/bin/env python
# encoding: utf-8
# -*- coding: utf-8 -*-
# @contact: ybsdeyx@foxmail.com
# @software: PyCharm
# @time: 2019/3/6 9:59
# @author: Paulson●Wier
# @file: 5_词向量.py
# @desc:
# （1）Word2Vec
from gensim.models import Word2Vec
import jieba
# 定义停用词、标点符号
punctuation = ['、','）','（','，',",", "。", ":", ";",... | normal | {
"blob_id": "5c61ec549a3e78da4ea8a18bb4f8382f2b5c2cfa",
"index": 4438,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('sentences:\\n', sentences)\n<mask token>\nfor sentence in sentences:\n words = []\n for word in sentence:\n if word not in punctuation:\n words.append(word)... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class IssueTitleFactory(factory.Factory):
"""
``issue`` must be provided
"""
FACTORY_FOR = models.IssueTitle
language = factory.SubFactory(LanguageFactory)
title = u'Bla'
class IssueFactory(factory.Factory):
FACTORY_FOR = models.Issue
total_documents = 16... | flexible | {
"blob_id": "44d87f112ab60a202e4c8d64d7aec6f4f0d10578",
"index": 31,
"step-1": "<mask token>\n\n\nclass IssueTitleFactory(factory.Factory):\n \"\"\"\n ``issue`` must be provided\n \"\"\"\n FACTORY_FOR = models.IssueTitle\n language = factory.SubFactory(LanguageFactory)\n title = u'Bla'\n\n\ncla... | [
22,
39,
42,
45,
47
] |
from django.apps import AppConfig
class AutomationserverConfig(AppConfig):
name = 'automationserver'
| normal | {
"blob_id": "3153218fe1d67fdc1c1957ffcfdb380688c159c1",
"index": 6483,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AutomationserverConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AutomationserverConfig(AppConfig):\n name = 'automationserver'\n",
"step-4": "... | [
0,
1,
2,
3
] |
from nltk.tokenize import RegexpTokenizer
token = RegexpTokenizer(r'\w+')
from nltk.corpus import stopwords
# with open('microsoft.txt','r+',encoding="utf-8") as file:
# text = file.read()
# text = '''
# Huawei Technologies founder and CEO Ren Zhengfei said on Thursday the Chinese company is willing to license its... | normal | {
"blob_id": "aed6e1966d9e4ce7250ae3cacaf8854cab4b590c",
"index": 3513,
"step-1": "<mask token>\n\n\ndef word_freq_improved_summarize(text):\n sen = text.split('.')\n small = [s.lower() for s in sen]\n punc_free = []\n for p in small:\n punc_free.extend(token.tokenize(p))\n stop_words = set(... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Logger:
<|reserved_special_token_0|>
def __init__(self, file_path, print_too=True, override=False):
"""Create a new Logger.
Args:
file_path: String, the full path to the target file.
print_too: Bool, whether or not to also print logger i... | flexible | {
"blob_id": "1355c3abfd2683f6dc869703fdb79a04e264099c",
"index": 3421,
"step-1": "<mask token>\n\n\nclass Logger:\n <mask token>\n\n def __init__(self, file_path, print_too=True, override=False):\n \"\"\"Create a new Logger.\n\n Args:\n file_path: String, the full path to the target ... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
__author__ = 'ghou'
from datetime import datetime
bGameValid = True
dAskUserInfo = {}
gAccMode = 0
#============UserSyncResource2.py===================
#============前端资源热更白名单测试功能================
#============去读配置表config.xml==================
#============大于配置标号的热更内容只有... | normal | {
"blob_id": "2e075c3ee6b245b1ffd0bb8c4e205199f794da76",
"index": 5725,
"step-1": "<mask token>\n",
"step-2": "__author__ = 'ghou'\n<mask token>\nbGameValid = True\ndAskUserInfo = {}\ngAccMode = 0\ngWhiteTestResourceVersion = None\ngInvalidClientVersion = None\n",
"step-3": "__author__ = 'ghou'\nfrom datetime... | [
0,
1,
2,
3
] |
#Main thread for starting the gui
import cv2
import PIL
from PIL import Image,ImageTk
from tkinter import *
from matplotlib import pyplot as pt
from matplotlib.image import imread
from control.control import Control
control=Control()
#gives the indtruction for saving the current frame
def takePicture():
global s... | normal | {
"blob_id": "8d8c211895fd43b1e2a38216693b0c00f6f76756",
"index": 5748,
"step-1": "<mask token>\n\n\ndef takePicture():\n global setImage\n setImage = True\n\n\ndef addRectangles(locations):\n _, axe = pt.subplots()\n img = imread('hola.jpg')\n cv2image = cv2.cvtColor(img, cv2.COLOR_BGR2RGBA)\n ... | [
4,
5,
6,
7,
8
] |
from .simulator import SpatialSIRSimulator as Simulator
from .util import Prior
from .util import PriorExperiment
from .util import Truth
from .util import log_likelihood
| normal | {
"blob_id": "4f06eddfac38574a0ae3bdd0ea2ac81291380166",
"index": 9987,
"step-1": "<mask token>\n",
"step-2": "from .simulator import SpatialSIRSimulator as Simulator\nfrom .util import Prior\nfrom .util import PriorExperiment\nfrom .util import Truth\nfrom .util import log_likelihood\n",
"step-3": null,
"s... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
TEST_NAME = 'read_only'
VM_NAME = '{0}_vm_%s'.format(TEST_NAME)
VM_COUNT = 2
DISK_NAMES = dict()
DISK_TIMEOUT = 600
SPARSE = True
DIRECT_LUNS = UNUSED_LUNS
DIRECT_LUN_ADDRESSES = UNUSED_LUN_ADDRESSES
DIRECT_LUN_TARGETS = UNUSED_LU... | flexible | {
"blob_id": "ecdc8f5f76b92c3c9dcf2a12b3d9452166fcb706",
"index": 1098,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nTEST_NAME = 'read_only'\nVM_NAME = '{0}_vm_%s'.format(TEST_NAME)\nVM_COUNT = 2\nDISK_NAMES = dict()\nDISK_TIMEOUT = 600\nSPARSE = True\nDIRECT_LUNS = UNUSED_LUNS\nDIRECT_LUN_ADDRESSES = U... | [
0,
1,
2,
3
] |
from django.shortcuts import render, get_object_or_404, redirect
from django.utils import timezone
from .models import Group,SQLlist
from .forms import GroupForm
from .oraConnect import *
from .utils import IfNoneThenNull
########################### Группы ############################
def group_list(request):
grou... | normal | {
"blob_id": "b9fe758d5fe12b5a15097c0e5a33cb2d57edfdd2",
"index": 7484,
"step-1": "<mask token>\n\n\ndef group_list(request):\n groups = Group.objects.all()\n return render(request, 'group_list.html', {'groups': groups})\n\n\n<mask token>\n\n\ndef group_add(request):\n if request.method == 'POST':\n ... | [
4,
6,
8,
10,
11
] |
#Copyright 2008, Meka Robotics
#All rights reserved.
#http://mekabot.com
#Redistribution and use in source and binary forms, with or without
#modification, are permitted.
#THIS SOFTWARE IS PROVIDED BY THE Copyright HOLDERS AND CONTRIBUTORS
#"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
#LIMITED... | normal | {
"blob_id": "b227f222569761493f50f9dfee32f21e0e0a5cd6",
"index": 4400,
"step-1": "#Copyright 2008, Meka Robotics\n#All rights reserved.\n#http://mekabot.com\n\n#Redistribution and use in source and binary forms, with or without\n#modification, are permitted. \n\n\n#THIS SOFTWARE IS PROVIDED BY THE Copyright HOL... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
codecool_bp = CodecoolClass.create_local
<|reserved_special_token_1|>
from codecool_class import CodecoolClass
from mentor import Mentor
from student import Student
codecool_bp = CodecoolClass.create_local
| flexible | {
"blob_id": "7e985f55271c8b588abe54a07d20b89b2a29ff0d",
"index": 8380,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncodecool_bp = CodecoolClass.create_local\n",
"step-3": "from codecool_class import CodecoolClass\nfrom mentor import Mentor\nfrom student import Student\ncodecool_bp = CodecoolClass.cre... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class FaceTrigger(CascadeBase):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class FaceTrigger(CascadeBase):
def build_network(self):
net = lasagne.layers.batch_nor... | flexible | {
"blob_id": "1dd5c25cd3b7bc933ba0b63d9a42fdddc92b8531",
"index": 8737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass FaceTrigger(CascadeBase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass FaceTrigger(CascadeBase):\n\n def build_network(self):\n net = lasagne.layers.batc... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
SetOption('num_jobs', 4)
SetOption('implicit_cache', 1)
<|reserved_special_token_0|>
buildVariables.Add(PathVariable('QTDIR', 'Qt4 root directory',
'/usr/share/qt4', PathVariable.PathIsDir))
buildVariables.Add(PathVariable('OG... | flexible | {
"blob_id": "595912753d778a0fa8332f0df00e06a9da5cde93",
"index": 447,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nSetOption('num_jobs', 4)\nSetOption('implicit_cache', 1)\n<mask token>\nbuildVariables.Add(PathVariable('QTDIR', 'Qt4 root directory',\n '/usr/share/qt4', PathVariable.PathIsDir))\nbuil... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def GUI():
app = HiCityGUI()
app.mainloop()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def GUI():
app = HiCityGUI()
app.mainloop()
if __name__ == '__main__':
... | flexible | {
"blob_id": "dd96b7f73c07bf0c74e6ce4dbff1a9cc09729b72",
"index": 7918,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GUI():\n app = HiCityGUI()\n app.mainloop()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef GUI():\n app = HiCityGUI()\n app.mainloop()\n\n\nif __name__ == '_... | [
0,
1,
2,
3
] |
import json
from jsonargparse import ArgumentParser, ActionConfigFile
import yaml
from typing import List, Dict
import glob
import os
import pathlib
import pdb
import subprocess
import copy
from io import StringIO
from collections import defaultdict
import torch
from spacy.tokenizer import Tokenizer
from spacy.... | normal | {
"blob_id": "04aacf9461ade2e229076ffdf85aca913037edad",
"index": 642,
"step-1": "<mask token>\n\n\nclass NavigationTransformerTrainer(TransformerTrainer):\n\n def __init__(self, dataset_reader: NavigationDatasetReader, encoder:\n TransformerEncoder, optimizer: torch.optim.Optimizer, scheduler:\n ... | [
10,
11,
12,
13,
15
] |
class NlpUtility():
"""
Utility methods to get particular parts of speech from a token set
"""
def get_nouns(self, tokens):
nouns = []
for word, pos in tokens:
if pos == "NN":
nouns.push(word)
def get_verbs(self, tokens):
verbs = []
for word, pos in tokens:
if pos == "VB":
nouns.push(word)
... | normal | {
"blob_id": "c6502ea2b32ad90c76b6dfaf3ee3218d029eba15",
"index": 56,
"step-1": "class NlpUtility:\n <mask token>\n\n def get_nouns(self, tokens):\n nouns = []\n for word, pos in tokens:\n if pos == 'NN':\n nouns.push(word)\n <mask token>\n <mask token>\n\n d... | [
4,
5,
6,
7,
8
] |
from django.db.models.signals import post_save
from django.dispatch import receiver
from django.contrib.auth import get_user_model
from .models import Profile
User = get_user_model()
# this wan't run on creating superuser
@receiver(post_save, sender=User)
def save_profile(sender, created, instance, **kwargs):
if ... | normal | {
"blob_id": "4f93af104130f5a7c853ee0e7976fd52847e588a",
"index": 4988,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@receiver(post_save, sender=User)\ndef save_profile(sender, created, instance, **kwargs):\n if created:\n profile = Profile.objects.create(user=instance)\n profile.sa... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def pattern4(n):
"""
n: length of the base of the triangle ie. the max number
of starts it will contain.
"""
for row in range(1, n + 1):
for col in range(1, row + 1):
print('*', end='')
print('')
<|reserved_special_to... | flexible | {
"blob_id": "d77036ed07231719358658a42dc14d20453bd792",
"index": 7563,
"step-1": "<mask token>\n",
"step-2": "def pattern4(n):\n \"\"\"\n\tn: length of the base of the triangle ie. the max number\n\t\tof starts it will contain.\n\t\"\"\"\n for row in range(1, n + 1):\n for col in range(1, row + 1)... | [
0,
1,
2,
3
] |
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