code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# -*- coding: utf-8 -*-
from datetime import datetime, timedelta
import math
import re
import copy
from lcs import lcs
# Create your models here.
keywords=["int","long","for","while","if","else","break","continue","return","true","false","double","do","signed","unsigned"]
symbol=["[","]","{","}","(",")","&","|","^",... | normal | {
"blob_id": "ebd510bcd0caded03c5bcc36a11945710d5e644b",
"index": 5591,
"step-1": "# -*- coding: utf-8 -*-\n\nfrom datetime import datetime, timedelta\nimport math\nimport re\nimport copy\nfrom lcs import lcs\n# Create your models here.\n\n\nkeywords=[\"int\",\"long\",\"for\",\"while\",\"if\",\"else\",\"break\",\... | [
0
] |
#!/usr/bin/env python
"""
Checker of generated packages.
- [x] import generated package
- [x] flake8
- [x] pyright
- [x] mypy
"""
import argparse
import json
import logging
import subprocess
import sys
import tempfile
from dataclasses import dataclass
from pathlib import Path
from typing import List, Optional
ROOT_PA... | normal | {
"blob_id": "f3466fd38ecf472a4342aad4d10410d6f2a67d47",
"index": 1779,
"step-1": "<mask token>\n\n\nclass SnapshotMismatchError(Exception):\n \"\"\"\n Main snapshot mismatch exception.\n \"\"\"\n\n\ndef setup_logging(level: int) ->logging.Logger:\n \"\"\"\n Get Logger instance.\n\n Arguments:\n... | [
13,
14,
16,
17,
19
] |
# Generated by Django 3.0.8 on 2020-07-12 19:05
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('CRUD', '0001_initial'),
]
operations = [
migrations.RenameField(
model_name='employee',
old_name='eAdddress',
ne... | normal | {
"blob_id": "b1d8a454e590dfa4afa257ca665376c320a4acb5",
"index": 5264,
"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 = [('CRUD', '000... | [
0,
1,
2,
3,
4
] |
from lib.appData import driver_queue
from lib.pyapp import Pyapp
import threading
from appium.webdriver.common.touch_action import TouchAction
from lib.logger import logger
import time
local = threading.local()
class BasePage(object):
def __init__(self, driver=None):
if driver is None:
local.d... | normal | {
"blob_id": "aa51c8f736461f147704c1ec0669c265348fcb80",
"index": 6869,
"step-1": "<mask token>\n\n\nclass QQ_Login_Page(BasePage):\n\n def login(self):\n local.pyapp.click('android=>new UiSelector().text(\"登 录\")')\n\n def username(self):\n local.pyapp.type('content=>请输入QQ号码或手机或邮箱', 340846750... | [
15,
16,
18,
20,
24
] |
n = input()
n = list(n)
n.sort()
alph = []
num = []
for i in range(n):
if i.isalpha():
alpa.append(i)
else:
num.append(i)
result.append(str(alpa))
result.append(str(num))
print(n)
| normal | {
"blob_id": "e364a4e6e1c4e0fd6805515a1149adaf92e9c8fb",
"index": 5584,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nn.sort()\n<mask token>\nfor i in range(n):\n if i.isalpha():\n alpa.append(i)\n else:\n num.append(i)\nresult.append(str(alpa))\nresult.append(str(num))\nprint(n)\n",
... | [
0,
1,
2
] |
# SPDX-FileCopyrightText: 2021 John Park for Adafruit Industries
# SPDX-License-Identifier: MIT
import time
import random
import board
import audiomp3
import audiopwmio
from adafruit_crickit import crickit
ss = crickit.seesaw # Crickit seesaw setup
button = crickit.SIGNAL1 # momentary switch to trigger animation
ss... | normal | {
"blob_id": "608c116cd42132bd63be5056f0aaf5c78933886e",
"index": 7536,
"step-1": "<mask token>\n\n\ndef open_lid():\n motor_lid.throttle = 1\n time.sleep(0.25)\n motor_lid.throttle = 0\n\n\ndef close_lid():\n motor_lid.throttle = -1\n time.sleep(0.25)\n motor_lid.throttle = 0\n\n\ndef blink(tim... | [
3,
5,
6,
7,
8
] |
# python /Users/lawrie_6strings/be_professional_pythonist/control_string.py
# -*- coding: utf-8 -*-
# 文字列を３行で書いてみたい場合
"""
どないやねん。
最近の若いもんは、
ようやるやんけ。
"""
# 文字列の特定の文字を取得したい場合は,インデックスを指定してあげることでなんとかする。
word = "what's up"
print(word[0])
# 書式化
name = "lady gaga"
print("こんにちわ、私の名前は {} です。".format(name))
"複数の文字列を挿入することもできる... | normal | {
"blob_id": "0e05eed2d6bc723fd8379e436621a6eba4aa5ab2",
"index": 1929,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(word[0])\n<mask token>\nprint('こんにちわ、私の名前は {} です。'.format(name))\n<mask token>\nprint('{}/{}/{}'.format(year, month, day))\nfor i in range(0, 5):\n print('kamyu'[i])\nprint('aldo... | [
0,
1,
2,
3
] |
import unittest2 as unittest
from zope.component import getUtility
from plone.registry.interfaces import IRegistry
from plone.testing.z2 import Browser
from plone.app.testing import SITE_OWNER_NAME, SITE_OWNER_PASSWORD
from openmultimedia.imagewatchdog.configlet import IImageWatchDogSettings
from openmultimedia.image... | normal | {
"blob_id": "ce5f91aa04065aac4d4bc7bdbaab3b74c5a85a93",
"index": 8752,
"step-1": "<mask token>\n\n\nclass TestConfiglet(unittest.TestCase):\n <mask token>\n <mask token>\n\n def test_default_config(self):\n \"\"\" Validate the default values\n \"\"\"\n registry = getUtility(IRegistr... | [
4,
6,
7,
8,
9
] |
/home/pushkar/anaconda3/lib/python3.6/_bootlocale.py | normal | {
"blob_id": "ea4e4c8067d9e910b8d4c6a1c4c01f1ef70d7341",
"index": 7410,
"step-1": "/home/pushkar/anaconda3/lib/python3.6/_bootlocale.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
# coding: utf-8
"""
Negotiation API
The <b>Negotiations API</b> gives sellers the ability to proactively send discount offers to buyers who have shown an \"interest\" in their listings. <br><br>By sending buyers discount offers on listings where they have shown an interest, sellers can increase the velocity ... | normal | {
"blob_id": "a93818440410bde004f0203f18112fa1b666959c",
"index": 9615,
"step-1": "<mask token>\n\n\nclass OfferApi(object):\n <mask token>\n <mask token>\n <mask token>\n\n def find_eligible_items_with_http_info(self, x_ebay_c_marketplace_id,\n **kwargs):\n \"\"\"find_eligible_items # ... | [
4,
5,
6,
8,
9
] |
#/usr/share/python3
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.model_selection import train_test_split
import numpy as np
import seaborn as sb
import pandas as pd
from pmlb import fetch_data, classification_dataset_names
import util
# f... | normal | {
"blob_id": "4c010f9d9e7813a4ae4f592ade60130933b51958",
"index": 6125,
"step-1": "<mask token>\n\n\ndef score_model(X, y, model):\n train_X, test_X, train_y, test_y = train_test_split(X, y)\n model.fit(train_X, train_y)\n return model.score(test_X, test_y)\n\n\n<mask token>\n\n\ndef main():\n ds_name... | [
2,
3,
4,
5,
6
] |
# Copyright (c) 2008 Johns Hopkins University.
# All rights reserved.
#
# Permission to use, copy, modify, and distribute this software and its
# documentation for any purpose, without fee, and without written
# agreement is hereby granted, provided that the above copyright
# notice, the (updated) modification history ... | normal | {
"blob_id": "4af53bf9cbe136dec7dcc609e28cdd013911c385",
"index": 7421,
"step-1": "# Copyright (c) 2008 Johns Hopkins University.\n# All rights reserved.\n#\n# Permission to use, copy, modify, and distribute this software and its\n# documentation for any purpose, without fee, and without written\n# agreement is h... | [
0
] |
# Copyright 2019-2020 the ProGraML authors.
#
# Contact Chris Cummins <chrisc.101@gmail.com>.
#
# 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... | normal | {
"blob_id": "09788cf04ab5190a33b43e3756f4dbd7d78977a5",
"index": 581,
"step-1": "<mask token>\n\n\nclass GraphTupleData(Base, sqlutil.PluralTablenameFromCamelCapsClassNameMixin):\n <mask token>\n id: int = sql.Column(sql.Integer, sql.ForeignKey('graph_tuples.id',\n onupdate='CASCADE', ondelete='CASC... | [
40,
44,
48,
54,
63
] |
from .authenticators import CookieAuthenticator, HeaderAuthenticator
from .paginators import LimitOffsetPaginator, PageNumberPaginator
from .views import * # pylint:disable=W0401
| normal | {
"blob_id": "dab53d10958b36cf75ab53bf30f744b1ed8a09b6",
"index": 6475,
"step-1": "<mask token>\n",
"step-2": "from .authenticators import CookieAuthenticator, HeaderAuthenticator\nfrom .paginators import LimitOffsetPaginator, PageNumberPaginator\nfrom .views import *\n",
"step-3": "from .authenticators impor... | [
0,
1,
2
] |
# Copyright 2016 Huawei, Inc. 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": "cc9485dea0975a0974f037b129816a9359b2b622",
"index": 2875,
"step-1": "<mask token>\n\n\nclass TestConsoleUrlShow(TestConsole):\n _server = compute_fakes.create_one_server()\n\n def setUp(self):\n super(TestConsoleUrlShow, self).setUp()\n self.sdk_client.find_server.return_value = ... | [
10,
15,
18,
19,
20
] |
def domain_sort_key(domain):
"""Key to sort hosts / domains alphabetically, by domain name."""
import re
domain_expr = r'(.*\.)?(.*\.)(.*)' # Eg: (www.)(google.)(com)
domain_search = re.search(domain_expr, domain)
if domain_search and domain_search.group(1):
# sort by domain name and then... | normal | {
"blob_id": "c581d9714681e22c75b1eeb866ea300e87b883f1",
"index": 2972,
"step-1": "<mask token>\n",
"step-2": "def domain_sort_key(domain):\n \"\"\"Key to sort hosts / domains alphabetically, by domain name.\"\"\"\n import re\n domain_expr = '(.*\\\\.)?(.*\\\\.)(.*)'\n domain_search = re.search(doma... | [
0,
1,
2,
3,
4
] |
# Copyright 2017 Battelle Energy Alliance, LLC
#
# 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 t... | normal | {
"blob_id": "5456fb2938ae4d0f69414c153390f86437088114",
"index": 4475,
"step-1": "<mask token>\n\n\nclass Metric(utils.metaclass_insert(abc.ABCMeta, BaseType)):\n <mask token>\n\n def __init__(self):\n \"\"\"\n This is the basic method initialize the metric object\n @ In, none\n @ Out... | [
4,
5,
6,
8,
9
] |
'''
Created on Jan 19, 2014
@author: felix
'''
import sys
from PyPDF2 import PdfFileReader
from pytagcloud import create_tag_image, make_tags, LAYOUT_HORIZONTAL
from pytagcloud.lang.counter import get_tag_counts
def main():
for i in range(0, len(sys.argv)):
if (sys.argv[i] == '-f'):
try:
... | normal | {
"blob_id": "899cdb5cbdbd0a57af76a5044d54e1fe2a497847",
"index": 7144,
"step-1": "'''\nCreated on Jan 19, 2014\n\n@author: felix\n'''\nimport sys\nfrom PyPDF2 import PdfFileReader\nfrom pytagcloud import create_tag_image, make_tags, LAYOUT_HORIZONTAL\nfrom pytagcloud.lang.counter import get_tag_counts\n\ndef mai... | [
0
] |
import glob
import os
import xml.etree.ElementTree as ET
file_dirs = ["train/","test/"]
for file_dir in file_dirs:
fdir = "custom_dataset/" + file_dir
for directory in os.listdir(fdir):
new_location = "/content/gdrive/My Drive/project/custom_dataset/" + file_dir + directory
xml_file... | normal | {
"blob_id": "3a053c2c8a2b9123974183e65914dc0f73d2e078",
"index": 6368,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor file_dir in file_dirs:\n fdir = 'custom_dataset/' + file_dir\n for directory in os.listdir(fdir):\n new_location = ('/content/gdrive/My Drive/project/custom_dataset/' +\n... | [
0,
1,
2,
3,
4
] |
# -*- coding: UTF-8 -*-
'''
model = DQN,DDQN,PDQN,PDDQN,DQN_PER,DDQN_PER,DQN_InAday,DQN_PER_Ipm...
'''
# -----------ContolGame------------
# CartPole - v1, MountainCar - v0, Acrobot - v1, Pendulum - v0
# from run_ContolGame import run_Game
# run_Game('DQN', 'CartPole-v1', episodes=400) # model,env,episodes
# --------... | normal | {
"blob_id": "f49a133fa94aae791ef0f1eec54cf0629f45a0ed",
"index": 5153,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrun_Game('DQN_PER', 'Breakout', lifes=5, episodes=40001)\n",
"step-3": "<mask token>\nfrom run_AtariGame import run_Game\nrun_Game('DQN_PER', 'Breakout', lifes=5, episodes=40001)\n",
... | [
0,
1,
2,
3
] |
import p01 as p
stu = p.Student()
stu.say()
p.sayHello()
| normal | {
"blob_id": "8be3a3d32da208e2f45aad61813bc6f5ea513f01",
"index": 9803,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nstu.say()\np.sayHello()\n",
"step-3": "<mask token>\nstu = p.Student()\nstu.say()\np.sayHello()\n",
"step-4": "import p01 as p\nstu = p.Student()\nstu.say()\np.sayHello()\n",
"step-... | [
0,
1,
2,
3
] |
def area (a, b):
resultado = a * b
return (resultado)
def main():
#escribe tu código abajo de esta línea
num1 = float(input("INTRODUCE LA BASE: "))
num2 = float(input("INTRODUCE LA ALTURA: "))
print ("EL AREA DEL RECTANGULO ES: ", area (num1, num2))
pass
if __name__ == '__main__':
main()
| normal | {
"blob_id": "282dbdb3a8d9ed914e8ca5c7fa74d2873920e18c",
"index": 7308,
"step-1": "<mask token>\n",
"step-2": "def area(a, b):\n resultado = a * b\n return resultado\n\n\n<mask token>\n",
"step-3": "def area(a, b):\n resultado = a * b\n return resultado\n\n\ndef main():\n num1 = float(input('IN... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
# -*- coding: UTF-8 -*-
# 可写函数说明
def sum(arg1, arg2):
# 返回2个参数的和."
total = arg1 + arg2
print "函数内 : ", total
return total;
# 调用sum函数
total = sum(10, 20);
def nop():
pass
a = nop(); | normal | {
"blob_id": "9761070a75b043f6cc9e6134e09810b215ccd0c0",
"index": 6430,
"step-1": "#!/usr/bin/python\n# -*- coding: UTF-8 -*-\n\n# 可写函数说明\ndef sum(arg1, arg2):\n # 返回2个参数的和.\"\n total = arg1 + arg2\n print \"函数内 : \", total\n return total;\n\n\n# 调用sum函数\ntotal = sum(10, 20);\n\ndef nop():\n pass\n... | [
0
] |
from tqdm import trange
import numpy as np
class GPTD_fixedGrid:
def __init__(self, env, sigma0, gamma, kernel, D, V_mu=[]):
self.env = env
self.gamma = gamma
self.sigma0 = sigma0
self.kernel = kernel.kernel
if (not V_mu):
V_mu = lambda s: np.zeros((s.sh... | normal | {
"blob_id": "92eaceb46974ba3a5944300139d5929d44673181",
"index": 1223,
"step-1": "<mask token>\n\n\nclass GPTD_fixedGrid:\n\n def __init__(self, env, sigma0, gamma, kernel, D, V_mu=[]):\n self.env = env\n self.gamma = gamma\n self.sigma0 = sigma0\n self.kernel = kernel.kernel\n ... | [
3,
5,
6,
7,
8
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Script to view and manage OPenn repositories. Use this script to list and
update OPenn primary repositories, to view repository details, and to list
documents in each repository.
"""
import os
import sys
import argparse
import logging
sys.path.insert(0, os.path.abspa... | normal | {
"blob_id": "e3071643548bb3a4e8d0a5710820ad39b8a6b04b",
"index": 5057,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Script to view and manage OPenn repositories. Use this script to list and\nupdate OPenn primary repositories, to view repository details, and to list\ndocuments in each reposi... | [
0
] |
file = open('../_datasets/moby_dick.txt', mode='r')
print(file.read())
print(file.closed)
file.close()
print(file.closed)
| normal | {
"blob_id": "dfe0ee5bbb906e5a23adcf06d2d704700fa1567d",
"index": 1179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(file.read())\nprint(file.closed)\nfile.close()\nprint(file.closed)\n",
"step-3": "file = open('../_datasets/moby_dick.txt', mode='r')\nprint(file.read())\nprint(file.closed)\nfile... | [
0,
1,
2
] |
import cv2
import numpy as np
from math import *
def appendimages(im1,im2):
""" Return a new image that appends the two images side-by-side. """
# select the image with the fewest rows and fill in enough empty rows
rows1 = im1.shape[0]
rows2 = im2.shape[0]
if rows1 < rows2:
im1 = np.concat... | normal | {
"blob_id": "c3e313805c6f91f9aac77922edfd09650143f905",
"index": 4862,
"step-1": "<mask token>\n\n\ndef appendimages(im1, im2):\n \"\"\" Return a new image that appends the two images side-by-side. \"\"\"\n rows1 = im1.shape[0]\n rows2 = im2.shape[0]\n if rows1 < rows2:\n im1 = np.concatenate(... | [
9,
11,
12,
15,
18
] |
"""
This file is part of the tractor library.
See LICENSE.txt for licensing, CONTRIBUTORS.txt for contributor information.
Created on Jan 06, 2012.
"""
from StringIO import StringIO
from datetime import datetime
from tractor.attachment import AttachmentWrapper
from tractor.attachment import Base64Converter
from tract... | normal | {
"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
] |
'''
Copyright (c) 2011 Jacob K. Schoen (jacob.schoen@gmail.com)
Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify,... | normal | {
"blob_id": "e2e3b63deba20cd87fdfca81a9f67fa24891a1e0",
"index": 6416,
"step-1": "<mask token>\n\n\ndef _getAlbums(conn, smugmug, lock):\n albums = smugmug.albums_get(Extras='LastUpdated')\n for album in albums['Albums']:\n myLogger.debug(album)\n title = album['Title']\n cat = None\n ... | [
5,
6,
7,
8,
9
] |
from customer_service.model.customer import Customer
def get_customer(customer_id, customer_repository):
return customer_repository.fetch_by_id(customer_id)
def create_customer(first_name, surname, customer_repository):
customer = Customer(first_name=first_name, surname=surname)
customer_repository.stor... | normal | {
"blob_id": "f5e60f2d384242b9675e756f67391ea09afcc262",
"index": 5408,
"step-1": "<mask token>\n\n\ndef update_customer(first_name, surname, cid, customer_repository):\n customer = customer_repository.fetch_by_id(cid)\n customer.first_name = first_name\n customer.surname = surname\n customer_reposito... | [
1,
2,
3,
4
] |
'''Autogenerated by xml_generate script, do not edit!'''
from OpenGL import platform as _p, arrays
from OpenGL.constant import Constant as _C
# End users want this...
from OpenGL.raw.GLES2 import _errors
# Code generation uses this
from OpenGL.raw.GLES2 import _types as _cs
_EXTENSION_NAME = 'GLES2_NV_viewport_array'
... | normal | {
"blob_id": "9535973f9714926269490b8550a67c74d04d8f0a",
"index": 834,
"step-1": "<mask token>\n\n\n@_f\n@_p.types(None, _cs.GLuint, _cs.GLsizei, arrays.GLfloatArray)\ndef glDepthRangeArrayfvNV(first, count, v):\n pass\n\n\n@_f\n@_p.types(None, _cs.GLuint, _cs.GLfloat, _cs.GLfloat)\ndef glDepthRangeIndexedfNV(... | [
11,
12,
13,
14,
16
] |
from django.urls import path
from . import views # 현재 패키지에서 views 모듈을 가져옴
urlpatterns = [
path('', views.home, name='home'),
path('ppt1',views.ppt1,name='ppt1'),
path('ppt2',views.ppt2,name='ppt2'),
] | normal | {
"blob_id": "9db1887c5379623687d1dea343d72122bab66303",
"index": 2143,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.home, name='home'), path('ppt1', views.ppt1,\n name='ppt1'), path('ppt2', views.ppt2, name='ppt2')]\n",
"step-3": "from django.urls import path\nfrom . ... | [
0,
1,
2,
3
] |
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("")
if __name__ == '__main__':
n = int(input(("Enter height of the triangle: ")))
pattern4(n)
| normal | {
"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
] |
from .__init__ import *
def surfaceAreaCone(maxRadius=20, maxHeight=50, unit='m'):
a = random.randint(1, maxHeight)
b = random.randint(1, maxRadius)
slopingHeight = math.sqrt(a**2 + b**2)
problem = f"Surface area of cone with height = {a}{unit} and radius = {b}{unit} is"
ans = int(math.pi * b * s... | normal | {
"blob_id": "3e19ede2112a109a776b607e927e2f0a095ba5cc",
"index": 7677,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef surfaceAreaCone(maxRadius=20, maxHeight=50, unit='m'):\n a = random.randint(1, maxHeight)\n b = random.randint(1, maxRadius)\n slopingHeight = math.sqrt(a ** 2 + b ** 2)\... | [
0,
1,
2,
3,
4
] |
from django.db import models
from django.contrib.auth.models import User
from django.db.models.deletion import CASCADE
class Profile(models.Model):
user = models.OneToOneField(User, on_delete=CASCADE)
# portfolio = models.ManyToOneRel(User, on_delete=)
def __str__(self):
return f"{self.user.user... | normal | {
"blob_id": "51ff1181f0ddac3a8f7cbd9f9d2eedae29a6c559",
"index": 6654,
"step-1": "<mask token>\n\n\nclass Profile(models.Model):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Profile(models.Model):\n <mask token>\n\n def __str__(self):\n return f'{self.user.username} P... | [
1,
2,
3,
4,
5
] |
from .exenv import *
| normal | {
"blob_id": "9fea76b1612bd02f512072692090f8ef60e8a0fe",
"index": 1498,
"step-1": "<mask token>\n",
"step-2": "from .exenv import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
#!/usr/bin/env python
"""
This code is fot testing the region growing.
"""
import os
import sys
import time
import nibabel as nib
import region_growing as rg
import matplotlib.pyplot as plt
import numpy as np
img = nib.load("zstat1.nii.gz")
data = img.get_data()
#test coor [36,60,28] [21,39,30] [23,38,30]
coor = [23,... | normal | {
"blob_id": "6bcddd1b2ec8653400f710e5cab552d4bec75b6b",
"index": 1162,
"step-1": "#!/usr/bin/env python\n\"\"\"\nThis code is fot testing the region growing.\n\"\"\"\nimport os\nimport sys\nimport time\nimport nibabel as nib\nimport region_growing as rg\nimport matplotlib.pyplot as plt \nimport numpy as np\n\nim... | [
0
] |
// Time Complexity : O(n)
// Space Complexity : O(n)
// Did this code successfully run on Leetcode : Yes
// // Any problem you faced while coding this : No
// Your code here along with comments explaining your approach
class Solution:
def productExceptSelf(self, nums: List[int]) -> List[int]:
res=[]
... | normal | {
"blob_id": "23bcef07326db084d4e0e6337beb00faba329193",
"index": 1834,
"step-1": "// Time Complexity : O(n)\n// Space Complexity : O(n)\n// Did this code successfully run on Leetcode : Yes\n// // Any problem you faced while coding this : No\n\n// Your code here along with comments explaining your approach\nclass... | [
0
] |
from django.apps import AppConfig
class CheckoutConfig(AppConfig):
name = "checkout"
# Override the ready method and import the signals module
# so that update_on_save and update_on_delete will be called
# after an OrderLineItem model instance is saved or deleted
def ready(self):
import c... | normal | {
"blob_id": "74e3f4cd7b09d9b96feb3f927a509b113481eaed",
"index": 7575,
"step-1": "<mask token>\n\n\nclass CheckoutConfig(AppConfig):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CheckoutConfig(AppConfig):\n <mask token>\n\n def ready(self):\n import checkout.signals\n... | [
1,
2,
3,
4,
5
] |
from django.test import TestCase
from stack_it.models import Image
class TextPageContentModelTest(TestCase):
def test_instance(self):
file = Image.create_empty_image_file(name='hello.jpg')
image = Image.objects.create(image=file, alt="World")
self.assertEqual(Image.objects.count(), 1)
... | normal | {
"blob_id": "5287bd1847848aa527df8ce57e896bc30c70b43c",
"index": 4432,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TextPageContentModelTest(TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TextPageContentModelTest(TestCase):\n\n def test_instance(self):\n file ... | [
0,
1,
2,
3,
4
] |
import queue
from enum import IntEnum
from time import sleep
import keyboard
# I know, I copy pasted this horrobly written class
# again...
# and again.. I should really write a proper intcode computer
class IntCodeComputer:
def __init__(self, code):
self.defaultCode = code
self.runningCode = self... | normal | {
"blob_id": "6eac04bc10ef712ab4e2cde4730950ddcbe42585",
"index": 8983,
"step-1": "<mask token>\n\n\nclass IntCodeComputer:\n\n def __init__(self, code):\n self.defaultCode = code\n self.runningCode = self.defaultCode.copy()\n self.instructionPointer = 0\n self.outputQueue = queue.Q... | [
5,
8,
9,
10,
12
] |
from redis3barScore import StudyThreeBarsScore
from redisUtil import RedisTimeFrame
def test_score1() -> None:
package = {'close': 13.92,
'high': 14.57,
'low': 12.45,
'open': 13.4584,
'symbol': 'FANG',
'timestamp': 1627493640000000000,
... | normal | {
"blob_id": "ec64ddd01034debadb6674e71125f673f5de8367",
"index": 567,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_score1() ->None:\n package = {'close': 13.92, 'high': 14.57, 'low': 12.45, 'open': 13.4584,\n 'symbol': 'FANG', 'timestamp': 1627493640000000000, 'trade_count': \n ... | [
0,
1,
2,
3
] |
from arcgis.geocoding import geocode
from arcgis.gis import GIS
import pandas as pd
import Point_v1
"""
This module is used to get the location information of different companies from arcgis API.
"""
def crawl(file):
gis = GIS()
map = gis.map("United States")
map
# read all kinds of job files
jo... | normal | {
"blob_id": "902159d9ad3a1e36b69142518007b5d4bcaef0f3",
"index": 1320,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef crawl(file):\n gis = GIS()\n map = gis.map('United States')\n map\n job_df = pd.read_csv(Point_v1.CONSULTING_FILE).append(pd.read_csv(\n Point_v1.DS_FILE)).appe... | [
0,
1,
2,
3
] |
#!/usr/bin/python
#Program for functions pay scale from user input
hrs = raw_input("Enter Hours:")
h = float(hrs)
rate = raw_input("Enter Rate:")
r = float(rate)
def computepay(h,r):
if (h>40) :
pay = (40*r)+(h-40)*1.5*r
else:
pay = (h*r)
return pay
print computepay(h,r)
| normal | {
"blob_id": "8f30de819412b03ef12009320978cb1becd85131",
"index": 2767,
"step-1": "#!/usr/bin/python\n#Program for functions pay scale from user input\n\nhrs = raw_input(\"Enter Hours:\")\n\nh = float(hrs)\n\nrate = raw_input(\"Enter Rate:\")\n\nr = float(rate)\n\n\n\ndef computepay(h,r):\n\n if (h>40) : \n\n ... | [
0
] |
def test(a):
"""
This function return square of number
"""
return (a**2)
print(test(2))
help(test)
test.__doc__
| normal | {
"blob_id": "7b35a7f28c11be15fe2ac8d6eae4067ac5379f3e",
"index": 3546,
"step-1": "<mask token>\n",
"step-2": "def test(a):\n \"\"\"\n This function return square of number\n \"\"\"\n return a ** 2\n\n\n<mask token>\n",
"step-3": "def test(a):\n \"\"\"\n This function return square of number... | [
0,
1,
2,
3
] |
from matplotlib import pyplot as plt
import pandas as pd
import numpy as np
from sklearn.cluster import KMeans
cols = ['Clump Thickness', 'Uniformity of Cell Size', 'Uniformity of Cell Shape',
'Marginal Adhesion', 'Single Epithelial Cell Size', 'Bare Nuclei', 'Bland Chromatin',
... | normal | {
"blob_id": "ff331dc0c72378222db9195cce7c794f93799401",
"index": 5833,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndata.replace(to_replace='?', value=np.nan, inplace=True)\ndata.dropna(inplace=True)\n<mask token>\nkms.fit(data_train)\nprint(kms.predict(data_test))\nplt.figure()\n",
"step-3": "<mask ... | [
0,
1,
2,
3,
4
] |
# Bisection recursion algo for sqrt of 2
def bisectionSqrt(x, epsilon = 0.01, low = None, high = None):
"""
Performs a recursive bisection search to find the
square root of x, within epsilon
"""
if low == None:
low = 0.0
if high == None:
high = x
midPoint = (high + low)/2.0
# If the difference of the ... | normal | {
"blob_id": "d332ddd6c66bb22d60190ab8f94931eac6fd2394",
"index": 8482,
"step-1": "# Bisection recursion algo for sqrt of 2\n\ndef bisectionSqrt(x, epsilon = 0.01, low = None, high = None):\n\t\"\"\" \n\t\tPerforms a recursive bisection search to find the\n\t\tsquare root of x, within epsilon\n\t\"\"\"\n\n\tif lo... | [
0
] |
env = 'DEV' ## this had to be in uppercase
platform = 'hive'
from datahub.emitter.kafka_emitter import DatahubKafkaEmitter, KafkaEmitterConfig
from datahub.emitter.rest_emitter import DatahubRestEmitter
from datahub.ingestion.extractor.schema_util import *
from datahub.metadata.schema_classes import (
DatasetSn... | normal | {
"blob_id": "7ad5e803afa42790e878bfb923eddcfde2d21928",
"index": 1501,
"step-1": "<mask token>\n\n\ndef add_owner_mce(m) ->MetadataChangeEventClass:\n entity = m['Table']\n schema = m['Schema']\n dataset_name = f'{schema}.{entity}'\n owners = [OwnerClass(owner=owner, type=OwnershipTypeClass.DATAOWNER... | [
2,
3,
4,
5,
6
] |
import uuid
from website.util import api_v2_url
from django.db import models
from osf.models import base
from website.security import random_string
from framework.auth import cas
from website import settings
from future.moves.urllib.parse import urljoin
def generate_client_secret():
return random_string(lengt... | normal | {
"blob_id": "8186b7bddbdcdd730a3f79da1bd075c25c0c3998",
"index": 3131,
"step-1": "<mask token>\n\n\nclass ApiOAuth2Application(base.ObjectIDMixin, base.BaseModel):\n \"\"\"Registration and key for user-created OAuth API applications\n\n This collection is also used by CAS to create the master list of avail... | [
17,
18,
21,
25,
26
] |
#Merge Sort
#O(nlogn)
#Merge Part
from __future__ import division #use for python2
def merge(A, B): #Merge A[0:m], B[0,n]
(C, m, n) = ([], len(A), len(B))
(i, j) = (0, 0) #Current positions in A, B
while (i + j) < (m + n): #i+j is no. of elements merged so far
... | normal | {
"blob_id": "7b4c2689ad1d4601a108dd8aa6e3c4d1e9730dc5",
"index": 5257,
"step-1": "<mask token>\n\n\ndef merge(A, B):\n C, m, n = [], len(A), len(B)\n i, j = 0, 0\n while i + j < m + n:\n if i == m:\n C.append(B[j])\n j = j + 1\n elif j == n:\n C.append(A[i]... | [
1,
2,
3,
4,
5
] |
/Users/AbbyPennington/anaconda/lib/python3.5/os.py | normal | {
"blob_id": "8c4006ed8f4b1744f0316a61d95458b227653fee",
"index": 5887,
"step-1": "/Users/AbbyPennington/anaconda/lib/python3.5/os.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
def distribution():
##testing_results = pd.read_csv('https://raw.githubusercontent.com/dsfsi/covid19za/master/data/covid19za_timeline_testing.csv')
confirmed_results = pd.read_csv('https://raw.githubusercontent.com/dsf... | normal | {
"blob_id": "38be4e75c2311a1e5a443d39a414058dc4d1879b",
"index": 2320,
"step-1": "<mask token>\n\n\ndef distribution_plot():\n confirmed_results = pd.read_csv(\n 'https://raw.githubusercontent.com/dsfsi/covid19za/master/data/covid19za_timeline_confirmed.csv'\n )\n trial = pd.notnull(confirmed... | [
2,
3,
4,
5,
6
] |
import random
from datetime import datetime
from slackbot.bot import respond_to
from .term_model import Term, Response
from ..botmessage import botsend, botwebapi
# すでに存在するコマンドは無視する
RESERVED = (
'drive', 'manual', 'jira', 'wikipedia', 'plusplus',
'translate', '翻訳',
'weather', '天気',
'term',
'shuff... | normal | {
"blob_id": "86e97e7eaf0d23ccf4154b5ffc853c5aee966326",
"index": 5769,
"step-1": "<mask token>\n\n\n@respond_to('^term\\\\s+([\\\\w-]+)$')\n@respond_to('^term\\\\s+create\\\\s+([\\\\w-]+)$')\n@respond_to('^term\\\\s+add\\\\s+([\\\\w-]+)$')\ndef term_create(message, command):\n \"\"\"\n 指定されたコマンドを生成する\n ... | [
7,
9,
12,
15,
19
] |
# generated from catkin/cmake/template/order_packages.context.py.in
source_root_dir = "/home/songsong/image_transport_ws/src"
whitelisted_packages = "".split(';') if "" != "" else []
blacklisted_packages = "".split(';') if "" != "" else []
underlay_workspaces = "/home/songsong/image_transport_ws/devel;/home/songsong/pi... | normal | {
"blob_id": "86ca94820c05b3f63f4a733b6d1fa7eb9dea6a5d",
"index": 325,
"step-1": "<mask token>\n",
"step-2": "source_root_dir = '/home/songsong/image_transport_ws/src'\nwhitelisted_packages = ''.split(';') if '' != '' else []\nblacklisted_packages = ''.split(';') if '' != '' else []\nunderlay_workspaces = (\n ... | [
0,
1,
2
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
db = {
'host': "localhost",
'user': "root",
'passwd': "m74e71",
'database': "dw_toner"
}
data_inicial = '1990-01-01'
ano_final = 2018
feriados = "feriados.csv"
meses_de_ferias = (1, 2, 7, 12) #Janeiro, Fevereiro, Julho, Dezembro
dias_final_semana = (1, ... | normal | {
"blob_id": "360881cecbad88ea5d150548fba6a39d8dc30681",
"index": 8598,
"step-1": "<mask token>\n",
"step-2": "db = {'host': 'localhost', 'user': 'root', 'passwd': 'm74e71', 'database':\n 'dw_toner'}\ndata_inicial = '1990-01-01'\nano_final = 2018\nferiados = 'feriados.csv'\nmeses_de_ferias = 1, 2, 7, 12\ndia... | [
0,
1,
2
] |
Max = 100010
a = [0 for i in range(Max)]
p = []
for i in range(2,Max):
if a[i ] == 0:
p.append(i)
j = i * i
while j < Max:
a[j ] = 1
j = j + i
cnt,j = 0,1
n = int(input())
while p[j] <= n :
if p[j ] - p[j-1] == 2: cnt = cnt + 1
j = j + 1
print(cnt) | normal | {
"blob_id": "e828c2792d508ba41c5dca3f4a255eee2611c333",
"index": 3565,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(2, Max):\n if a[i] == 0:\n p.append(i)\n j = i * i\n while j < Max:\n a[j] = 1\n j = j + i\n<mask token>\nwhile p[j] <= n:\n ... | [
0,
1,
2,
3
] |
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
] |
#
# LeetCode
# ver.Python
#
# Created by GGlifer
#
# Open Source
"""
21. Merge Two Sorted Lists
"""
from typing import List
import sys
# Definition for singly-linked list.
class ListNode:
def __init__(self, val=0, next=None):
self.val = val
self.next = next
class Solution:
def mergeTwoList... | normal | {
"blob_id": "2730b2a1016f306936dcac3c3b44a3fd7194bac6",
"index": 7216,
"step-1": "<mask token>\n\n\nclass ListNode:\n\n def __init__(self, val=0, next=None):\n self.val = val\n self.next = next\n\n\nclass Solution:\n\n def mergeTwoLists(self, l1: ListNode, l2: ListNode) ->ListNode:\n r... | [
4,
6,
7,
8,
9
] |
from random import randrange
from django.core.exceptions import ValidationError
from django.contrib.auth import get_user_model
from rest_framework import serializers
from rest_framework_simplejwt.serializers import TokenObtainPairSerializer
from .models import EmailValidation
from ..emails.models import Ema... | normal | {
"blob_id": "9f34bf3a0bb24db428b7af1a354aec1d3a72df98",
"index": 359,
"step-1": "<mask token>\n\n\nclass CreatePasswordEmailValidationSerializer(serializers.Serializer):\n <mask token>\n\n def save(self):\n validation_code = randrange(10000000, 100000000)\n email = Email.objects.create(valida... | [
15,
16,
18,
19,
21
] |
from django.conf.urls import url
from django.urls import path
from .views import *
from flujo.views import *
"""
URL para el Sprint crear, listar y modificar
"""
urlpatterns = [
url(r'^$', SprintListView.as_view(), name='sprint_list'),
path('create/', view=CreateSprintView.as_view(), name='create_sprint'),
... | normal | {
"blob_id": "2b1ec422a42af59a048c708f86b686eb0564b51f",
"index": 2456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', SprintListView.as_view(), name='sprint_list'),\n path('create/', view=CreateSprintView.as_view(), name='create_sprint'),\n path('modificar/<int:sprint_pk>/'... | [
0,
1,
2,
3
] |
# - *- coding: utf- 8 - *-
import RPi.GPIO as io
import time
import math
io.setmode(io.BOARD)
hz = 50
dt = 1/hz
kr = 48
enc_res = 0.01636246
num_samples = 100
special_words = ['BackSpace', 'Tab', 'Enter', 'Cap', 'Shift2', 'Ctrl1',
'WIN1', 'Alt1', 'Alt2', 'WIN2', 'MClick', 'Ctrl2', 'Shift1', '\\']
L1... | normal | {
"blob_id": "ce1ef1ce538b8753af9e4b3e8e88f4cde9a2d860",
"index": 9620,
"step-1": "# - *- coding: utf- 8 - *-\r\n\r\nimport RPi.GPIO as io\r\nimport time\r\nimport math\r\n\r\nio.setmode(io.BOARD)\r\n\r\nhz = 50\r\ndt = 1/hz\r\nkr = 48\r\nenc_res = 0.01636246\r\nnum_samples = 100\r\nspecial_words = ['BackSpace', ... | [
0
] |
from django import forms
from .models import BlogPost
class BlogPostForm(forms.ModelForm):
class Meta:
model = BlogPost
fields = '__all__'
| normal | {
"blob_id": "c4624425f57211e583b5fbaec3943539ce6fea6f",
"index": 88,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BlogPostForm(forms.ModelForm):\n\n\n class Meta:\n model = BlogPost\n fields = '__all__'\n",
"step-3": "from django import forms\nfrom .models import BlogPost\n... | [
0,
1,
2
] |
import requests
from SPARQLWrapper import SPARQLWrapper, JSON
from rdflib import Graph
from plenum.server.plugin.graphchain.graph_store import GraphStore
from plenum.server.plugin.graphchain.logger import get_debug_logger
logger = get_debug_logger()
class StardogGraphStore(GraphStore):
def __init__(self, ts_db_... | normal | {
"blob_id": "a42a94798d176e20646d41cf0f4b7e4f99e0790b",
"index": 105,
"step-1": "<mask token>\n\n\nclass StardogGraphStore(GraphStore):\n <mask token>\n\n def check_whether_db_exists(self):\n logger.debug(\"Checking whether a triple store with db '{}' exists...\"\n .format(self._node_ts_u... | [
4,
5,
6,
7,
8
] |
from setuptools import setup, find_packages
def find_version():
with open('pytest_defer.py') as fp:
for line in fp:
if '__version__' in line:
version = line.split('=')[-1].strip()
return version[1:-1] # trim ''
with open('README.md') as fp:
long_desc = fp... | normal | {
"blob_id": "7903484b4a36d4b6ea03b9eaf3bf2b2e056baad8",
"index": 8148,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef find_version():\n with open('pytest_defer.py') as fp:\n for line in fp:\n if '__version__' in line:\n version = line.split('=')[-1].strip()\n ... | [
0,
1,
2,
3,
4
] |
import pygame
from config import *
from Map import *
from NeuralNetwork import *
class Pacman(object):
RADIUS = int(TILE_WIDTH/2)
def __init__(self, mapa, neural_net):
self.mapa = mapa
self.pos_x = 11
self.pos_y = 17
self.vel_x = 1
self.vel_y = 0
self.isAlive ... | normal | {
"blob_id": "d3b5d87b56421940449fdef48be6da9fa650dd90",
"index": 1756,
"step-1": "<mask token>\n\n\nclass Pacman(object):\n <mask token>\n\n def __init__(self, mapa, neural_net):\n self.mapa = mapa\n self.pos_x = 11\n self.pos_y = 17\n self.vel_x = 1\n self.vel_y = 0\n ... | [
7,
8,
10,
11,
12
] |
start=0
last=100
middle=50
counter=1
print(" Guess a number between 0 and 100")
condition = int(input("Is your guess " + str(middle) + "? (0 means it's too low, 1 means it's your guess and 2 means it's too high) "))
while condition != 1:
counter += 1
if condition == 0:
last = middle
elif conditio... | normal | {
"blob_id": "42d03aabef7d75c813f30bb6d8a835d76fd1fc83",
"index": 603,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(' Guess a number between 0 and 100')\n<mask token>\nwhile condition != 1:\n counter += 1\n if condition == 0:\n last = middle\n elif condition == 2:\n start = ... | [
0,
1,
2,
3
] |
def memo(fn):
cache = {}
missed = object()
def query(*args):
result = cache.get(args, missed)
if result is missed:
result = cache[args] = fn(*args)
return result
return query
@memo
def cal_edit_distance(ori, tar):
def edit_tuple(old, distance, path):
r... | normal | {
"blob_id": "88390f411af90d494284617ef8f5fb0e9bb8890e",
"index": 8039,
"step-1": "def memo(fn):\n cache = {}\n missed = object()\n\n def query(*args):\n result = cache.get(args, missed)\n if result is missed:\n result = cache[args] = fn(*args)\n return result\n return ... | [
2,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import (
StackingClassifier,
RandomForestClassifier
)
import pandas as pd
from sklearn.metrics import f1_score
# feel free to import any sklearn model here
from sklearn.linear_model import LogisticRegression
from ... | normal | {
"blob_id": "cf65966f5daf88bdefc7a8aa2ff80835cff0d0b6",
"index": 4627,
"step-1": "<mask token>\n\n\ndef load_data():\n \"\"\"\n Helper function for loading in the data\n\n ------\n # of training samples: 419\n # of testing samples: 150\n ------\n \"\"\"\n df = pd.read_csv('../../Data/brea... | [
1,
2,
3,
4,
5
] |
from django.test import TestCase
from .models import Seller, Product
from rest_framework.test import APIClient
import json
class SellerModelTests(TestCase):
def test_class_str(self):
seller = Seller()
seller.name = "Bruna"
self.assertEquals(seller.__str__(), "Bruna")
def test_to_dic... | normal | {
"blob_id": "71ab4ada4062ecde1463f2a766b5951860d0f2fb",
"index": 7250,
"step-1": "<mask token>\n\n\nclass ProductModelTests(TestCase):\n <mask token>\n <mask token>\n\n\nclass SellerViewTests(TestCase):\n\n @classmethod\n def setUpTestData(cls):\n Seller.objects.create(name='Bruna', email='bru... | [
9,
10,
13,
16,
17
] |
# -*- coding: utf-8 -*-
from yuancloud import models, fields, api, _
import yuancloud.addons.decimal_precision as dp
from yuancloud.exceptions import UserError
from yuancloud.osv import fields as old_fields
class event_event(models.Model):
_inherit = 'event.event'
event_ticket_ids = fields.One2many(
... | normal | {
"blob_id": "bddba2fd710829db17c6419878ce535df0aba01c",
"index": 2760,
"step-1": "<mask token>\n\n\nclass event_ticket(models.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>... | [
7,
12,
14,
19,
20
] |
# Python implementation of Bubble Sort
def bubbleSort(arr):
k = len(arr)
# Traverse through all elements
for i in range(k):
# Last i elements are already in correct place
for j in range(0, k - i - 1):
# Swap if element is greater than next element
if arr[j] > arr[j ... | normal | {
"blob_id": "178f9dcd9cbea140abebd509b56979417b5d7503",
"index": 6785,
"step-1": "<mask token>\n",
"step-2": "def bubbleSort(arr):\n k = len(arr)\n for i in range(k):\n for j in range(0, k - i - 1):\n if arr[j] > arr[j + 1]:\n arr[j], arr[j + 1] = arr[j + 1], arr[j]\n\n\n... | [
0,
1,
2,
3,
4
] |
import time
t0 = time.time()
while abs(t0 - time.time() < 60):
pass
| normal | {
"blob_id": "9a0e37aaa41f3b21ed7ad11096cd6c5dd0bb8564",
"index": 5608,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile abs(t0 - time.time() < 60):\n pass\n",
"step-3": "<mask token>\nt0 = time.time()\nwhile abs(t0 - time.time() < 60):\n pass\n",
"step-4": "import time\nt0 = time.time()\nwh... | [
0,
1,
2,
3
] |
import sqlite3
conn = sqlite3.connect("19-BD/prove.db")
cursor = conn.cursor()
dipendenti = [
("Sofia","commessa"),
("Diego","tecnico"),
("Lucia","cassiera"),
("Luca","Magazziniere"),
("Pablo","Capo reparto")
]
cursor.executemany("INSERT INTO persone VALUES (null,?,?)", dipendenti)
conn.commit()
... | normal | {
"blob_id": "3e1ca6ed4668e75a62baa65ef44346dd86a16491",
"index": 3093,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncursor.executemany('INSERT INTO persone VALUES (null,?,?)', dipendenti)\nconn.commit()\nconn.close()\n",
"step-3": "<mask token>\nconn = sqlite3.connect('19-BD/prove.db')\ncursor = conn... | [
0,
1,
2,
3,
4
] |
from django.shortcuts import render
from rest_framework.response import Response
from .serializers import *
from rest_framework import generics, status
class HistoryMyList(generics.ListCreateAPIView):
serializer_class = HistorySer
queryset = History.objects.all()
class HistoryListView(generics.GenericAPIVie... | normal | {
"blob_id": "8edca4c50e48734073e80de85088964837247696",
"index": 2597,
"step-1": "<mask token>\n\n\nclass HistoryListView(generics.GenericAPIView):\n <mask token>\n\n def post(self, request):\n serializer_class = self.serializer_class(data=request.data)\n serializer_class.is_valid(raise_excep... | [
8,
9,
11,
12
] |
# -*- coding: utf-8 -*-
import threading
import time
def work():
i = 0
while i < 10:
print 'I am working..'
time.sleep(0.5)
i += 1
t = threading.Thread(target=work)
# Daemon 설정
#t.setDaemon(True)
t.daemon = True # 혹인 이렇게도 가능
t.start()
print 'main thread finished'
| normal | {
"blob_id": "f77df47fdb72ba50331b8b5d65984efaec474057",
"index": 4049,
"step-1": "# -*- coding: utf-8 -*-\n\nimport threading\nimport time\n\ndef work():\n i = 0\n while i < 10:\n print 'I am working..'\n time.sleep(0.5)\n i += 1\n\nt = threading.Thread(target=work)\n# Daemon 설정\n#t.se... | [
0
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.shortcuts import render
from django.http import JsonResponse
from knowdb.models import Knowledge
import random
# Create your views here.
def answer(request):
ret = {}
data = Knowledge.objects.all()
num = random.choice(range(1,int... | normal | {
"blob_id": "eb558644283d992af2c324d457dbe674b714235f",
"index": 735,
"step-1": "# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.shortcuts import render\nfrom django.http import JsonResponse\nfrom knowdb.models import Knowledge\n\nimport random\n# Create your views here.\n\ndef an... | [
0
] |
from flask import Flask, request
from flask import render_template
import sqlite3
import datetime
app = Flask(__name__)
@app.route('/')
def index(date = ""):
date = request.args.get('date')
if not date:
now = datetime.datetime.now()
date = "%02d.%02d.%04d" % (now.day, now.month, now.year)
... | normal | {
"blob_id": "f6fe33e04ccdca1d9714caec412478d0cfc8b363",
"index": 5559,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index(date=''):\n date = request.args.get('date')\n if not date:\n now = datetime.datetime.now()\n date = '%02d.%02d.%04d' % (now.day, now.month, now.year)\n conn = sqli... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 16 16:11:46 2021
@author: Suman
"""
import numpy as np
import cv2
rect = (0,0,0,0)
startPoint = False
endPoint = False
def mark_object(event,x,y,flags,params):
global rect,startPoint,endPoint
# get mouse click
if event == cv2.EVENT_LB... | normal | {
"blob_id": "0f3e19b02dbe508bc4e0ef7879af81a9eabfd8c9",
"index": 6141,
"step-1": "<mask token>\n\n\ndef mark_object(event, x, y, flags, params):\n global rect, startPoint, endPoint\n if event == cv2.EVENT_LBUTTONDOWN:\n if startPoint == True and endPoint == True:\n startPoint = False\n ... | [
1,
2,
3,
4,
5
] |
from rllab.algos.trpo import TRPO
from rllab.baselines.linear_feature_baseline import LinearFeatureBaseline
from rllab.envs.gym_env import GymEnv
from rllab.envs.normalized_env import normalize
from rllab.misc.instrument import run_experiment_lite
from rllab.policies.gaussian_mlp_policy import GaussianMLPPolicy
from rl... | normal | {
"blob_id": "9f479ad2acf4f6deb0ca4db606c3d804979c10bd",
"index": 3804,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef run_task(*_):\n env = normalize(GymEnv('DartWalker2d-v1', record_video=False))\n policy_sep = GaussianHLCPolicy(env_spec=env.spec, hidden_sizes=(64, 32),\n sub_out_di... | [
0,
1,
2,
3,
4
] |
from django.urls import path
from .views import *
urlpatterns = [path('country', Country_Data, name='country_data'), path(
'tours', Scrape_Data, name='scrape_data'), path('draws', Draw_Data,
name='Draw_data')]
| normal | {
"blob_id": "b39c783cbaff2915c8864ce0b081b5bf052baee5",
"index": 6731,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('country', Country_Data, name='country_data'), path(\n 'tours', Scrape_Data, name='scrape_data'), path('draws', Draw_Data,\n name='Draw_data')]\n",
"step-3": "... | [
0,
1,
2
] |
from matplotlib import pyplot as plt
# Function for testing
# Maps x => x*x
def calculate(x):
return x * x
inputs = [-0.5, -0.4, -0.3, -0.2, -0.1, 0, 0.1, 0.2, 0.3, 0.4, 0.5]
outputs = [calculate(x) for x in inputs]
plt.plot(inputs, outputs)
plt.savefig("plot.png") | normal | {
"blob_id": "1b3891565f776064cfcca02fb22ea65853f7e66f",
"index": 3629,
"step-1": "<mask token>\n\n\ndef calculate(x):\n return x * x\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef calculate(x):\n return x * x\n\n\n<mask token>\nplt.plot(inputs, outputs)\nplt.savefig('plot.png')\n",
"step-3": "<... | [
1,
2,
3,
4,
5
] |
import sys
import numpy as np
####################################################################################################
### These functions all perform QA checks on input files.
### These should catch many errors, but is not exhaustive.
#####################################################################... | normal | {
"blob_id": "7413c06a990894c34ee5174d84f0e3bd20abf51f",
"index": 3294,
"step-1": "<mask token>\n\n\ndef check_controls(subpuc_names, subpuc_controls):\n if len(subpuc_names) == len(subpuc_controls):\n pass\n else:\n sys.exit(\n 'There is an issue with your subpuc_controls.csv file.... | [
3,
5,
6,
7,
8
] |
# Generated by Django 3.1.1 on 2020-12-02 19:50
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('element', '0011_suggestion_suggestion_type'),
('bot', '0001_initial'),
]
operations = [
migrations.AddField(
model_name=... | normal | {
"blob_id": "43ae01ffe35c6c4491f3f7e480dd6f5c1be86eb2",
"index": 2475,
"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 = [('element', '... | [
0,
1,
2,
3,
4
] |
# from django.test import TestCase ,LiveServerTestCase,Client
# from MeetUps.models import*
# from django.shortcuts import reverse
# from .forms import RegistrationForm
# class MeetUpViewTest(TestCase):
# @classmethod
# def setupTestDat(cls):
# #create or get all meetups
# d... | normal | {
"blob_id": "9156ee034ceb8a39fc1eb3a18c1597c737814c72",
"index": 692,
"step-1": "# from django.test import TestCase ,LiveServerTestCase,Client\n\n# from MeetUps.models import*\n# from django.shortcuts import reverse\n# from .forms import RegistrationForm\n\n# class MeetUpViewTest(TestCase):\n\n# @classmetho... | [
1
] |
{
# Theme information
'name' : 'Clarico CMS Blocks',
'category' : 'Website',
'version' : '1.0',
'summary': '13 CMS Building Blocks',
'description': """""",
# Dependencies
'depends': [
'snippet_style_1',
'snippet_style_2',
'snippet_style_3',
'snippet_style_4'... | normal | {
"blob_id": "34f98d4a6a15c9a7b42f237cab204b736dc97136",
"index": 1372,
"step-1": "<mask token>\n",
"step-2": "{'name': 'Clarico CMS Blocks', 'category': 'Website', 'version': '1.0',\n 'summary': '13 CMS Building Blocks', 'description': '', 'depends': [\n 'snippet_style_1', 'snippet_style_2', 'snippet_sty... | [
0,
1,
2
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 26 23:42:11 2018
@author: pohsuanh
Fully Covolutional Network FCN-32s.
FCN-32s network is based on VGG-16
"""
import os
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import data_load
from datetime import datetime
... | normal | {
"blob_id": "df6fa0409500f97e5afde8f97796d6ed0cc4d746",
"index": 1330,
"step-1": "<mask token>\n\n\ndef fcn_model_fn(features, labels, mode):\n L2 = tf.contrib.layers.l2_regularizer(scale=0.1)\n trainable = False\n if mode == tf.estimator.ModeKeys.TRAIN:\n trainable = True\n seed = 2019\n w... | [
1,
2,
3,
4,
5
] |
# V0
class Codec:
def encode(self, strs):
s = ""
for i in strs:
s += str(len(i)) + "#" + i
return s
def decode(self, s):
i, str = 0, []
while i < len(s):
sharp = s.find("#", i)
l = int(s[i:sharp])
str.append(s[sharp + 1:sh... | normal | {
"blob_id": "b94392c9c6547415326d80ff0923cb8ba9251783",
"index": 5724,
"step-1": "<mask token>\n\n\nclass Codec:\n <mask token>\n\n def decode(self, s):\n \"\"\"Decodes a single string to a list of strings.\n \n :type s: str\n :rtype: List[str]\n \"\"\"\n i, str = ... | [
5,
6,
7,
8,
10
] |
# question 1d
# points: 6
import sys
import numpy as np
from astropy.stats import kuiper
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import handin2 as nur
def main():
seed = 8912312
np.random.seed(8912312)
u = 0
sigma = 1
cdf = nur.gaussian_cdf
num_samples = np.lo... | normal | {
"blob_id": "0158141832423b567f252e38640e384cdf340f8b",
"index": 7105,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n seed = 8912312\n np.random.seed(8912312)\n u = 0\n sigma = 1\n cdf = nur.gaussian_cdf\n num_samples = np.logspace(1, 5, num=50)\n sample_size = int(... | [
0,
1,
2,
3,
4
] |
import sys
import unittest
import random
from k_order_statistic import k_order_statistic
test_case_find = [([0], 0, 0), ([-1, -1, -1, -1], 3, -1), ([-1, -1, -1, -1],
1, -1), ([-1, 0, 3, -10], 3, 3), ([-1, -2, -3, -4, -5], 0, -5), ([1, 2,
3, 4, 5], 1, 2), ([True, False, True], 2, True), ([sys.maxsize], 0, sys
... | normal | {
"blob_id": "b93cd5ad957da37b1a4cca1d465a67723110e926",
"index": 2813,
"step-1": "<mask token>\n\n\nclass TestKOrderStatistic(unittest.TestCase):\n\n def test_find(self):\n for a, k, ans in test_case_find:\n self.assertEqual(k_order_statistic(a, k), ans)\n <mask token>\n",
"step-2": "<m... | [
2,
3,
4,
5
] |
#----------------------------
# |
# Instagram Bot- Devesh Kr. Verma
# instagram- @felon_tpf
# |
#----------------------------
from selenium import webdriver
from time import sleep
from selenium.webdriver.common.keys import Keys
import random
import string
from time import sleep
from selenium import we... | normal | {
"blob_id": "6d18aa585c656b244d1e4272caa8419c04b20b6c",
"index": 2363,
"step-1": "<mask token>\n\n\ndef start():\n username = browser.find_element_by_name('username')\n username.send_keys('Username')\n password = browser.find_element_by_name('password')\n password.send_keys('Password')\n nextButto... | [
1,
3,
4,
5,
6
] |
import numpy as np
def calculate_distance_for_tour(tour, node_id_to_location_dict):
length = 0
num = 0
for i in tour:
j = tour[num - 1]
distance = np.linalg.norm(node_id_to_location_dict[i] - node_id_to_location_dict[j])
length += distance
num += 1
return length
def... | normal | {
"blob_id": "67d79a5c9eceef9f1ed69f79d6a9d1f421f3246c",
"index": 2757,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef calculate_distance_for_tour(tour, node_id_to_location_dict):\n length = 0\n num = 0\n for i in tour:\n j = tour[num - 1]\n distance = np.linalg.norm(node_id... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
import socket
import sys
from ctypes import *
import re
if len(sys.argv) == 3:
TCP_IP = sys.argv[1]
TCP_PORT = int(sys.argv[2])
else:
TCP_IP = "127.0.0.1"
TCP_PORT = 5005
BUFFER_SIZE = 1024
MESSAGE = "Hello, World!\n"
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
print "Connecting to " ... | normal | {
"blob_id": "f570d7e723fd0bec8c51022912a7dab4795fad43",
"index": 2049,
"step-1": "#!/usr/bin/python\n\nimport socket\nimport sys\nfrom ctypes import *\nimport re\n\nif len(sys.argv) == 3:\n\tTCP_IP = sys.argv[1]\n\tTCP_PORT = int(sys.argv[2])\nelse:\n\tTCP_IP = \"127.0.0.1\"\n\tTCP_PORT = 5005\n\nBUFFER_SIZE = 1... | [
0
] |
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from WeatherDL.data_maker import dataset_maker
from WeatherDL.model_maker import model_3
# Extract data from data_maker
X, y = dataset_maker(window=5, forecast_day=1)
(X_train, X_test, y_train, y_test) = train_test_split(X, y, test_s... | normal | {
"blob_id": "011dd579bb076ec094e9e3085aa321883c484f1c",
"index": 5296,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(model.summary())\n<mask token>\nplt.plot(history.history['loss'])\nplt.plot(history.history['val_loss'])\nplt.title('MSE')\nplt.legend(['Train', 'Test'], loc='upper right')\nplt.sho... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
__author__ = 'greghines'
import numpy as np
import matplotlib.pyplot as plt
import csv
import sys
import os
import pymongo
import matplotlib.cbook as cbook
import cPickle as pickle
sys.path.append("/home/greg/github/pyIBCC/python")
import ibcc
client = pymongo.MongoClient()
db = client['condor... | normal | {
"blob_id": "c025fccad9d37dff4db3a10455cbe7d92917d8f6",
"index": 6341,
"step-1": "#!/usr/bin/env python\n__author__ = 'greghines'\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport csv\nimport sys\nimport os\nimport pymongo\nimport matplotlib.cbook as cbook\nimport cPickle as pickle\n\nsys.path.append(... | [
0
] |
# -*- coding: utf-8 -*-
__author__ = 'Yun'
__project__ = 'DjangoBookTest2'
# from django.template import Template, Context
# from django.template.loader import get_template
# from django.http import HttpResponse
from django.shortcuts import render_to_response
import datetime
def current_datetime(request):
# now ... | normal | {
"blob_id": "ef6f55bf27982f53441215da6822cfcdc80706a5",
"index": 240,
"step-1": "<mask token>\n\n\ndef display_meta(request):\n context_dict = {'meta_dict': request.META}\n return render_to_response('display_meta.html', context_dict)\n",
"step-2": "<mask token>\n\n\ndef current_datetime(request):\n cu... | [
1,
2,
3,
4,
5
] |
__author__ = 'aniket'
import freenect
import cv2
import numpy as np
kernel = nfrp.ones((5,5),np.uint8)
freenect.C
def grayscale():
maske = np.zeros((480,640,3))
a = freenect.sync_get_depth(format=freenect.DEPTH_MM)[0]
mask = a == 0
a[mask] = 8000
mask1 = a > 1000
b = freenect.sync_get_video()... | normal | {
"blob_id": "9540319cf192add1fb24375a35d70ea8e3031a72",
"index": 7455,
"step-1": "<mask token>\n\n\ndef grayscale():\n maske = np.zeros((480, 640, 3))\n a = freenect.sync_get_depth(format=freenect.DEPTH_MM)[0]\n mask = a == 0\n a[mask] = 8000\n mask1 = a > 1000\n b = freenect.sync_get_video()[0... | [
1,
2,
3,
4,
5
] |
from django.shortcuts import render,redirect,get_object_or_404
from .models import Blog,UseCase,Comment
from courses.models import offerings
from django.contrib.auth.models import User
from django.contrib import auth
from django.contrib.auth.decorators import login_required
from django.utils import timezone
from django... | normal | {
"blob_id": "70fcf25cd7d70972e8042dc882f6ecb12d36461a",
"index": 3353,
"step-1": "<mask token>\n\n\ndef blogs(request):\n only_pub_blog = Blog.objects.filter(status=1)\n return render(request, 'dlblog/blogs.html', {'blog': only_pub_blog})\n\n\n<mask token>\n\n\n@login_required\ndef newblog(request):\n r... | [
5,
6,
7,
8,
9
] |
#!/usr/bin/env python
from io import StringIO
import sys
from contextlib import redirect_stdout
import pytest
# test input_name():
from mailroom3 import input_name
def test_1(monkeypatch): # tests "list"
monkeypatch.setattr('builtins.input', lambda x: "list")
f = StringIO()
with redirect_stdout(f):
... | normal | {
"blob_id": "286a47cece7002a88f34ace3e08d013e2d14801a",
"index": 2793,
"step-1": "<mask token>\n\n\ndef test_1(monkeypatch):\n monkeypatch.setattr('builtins.input', lambda x: 'list')\n f = StringIO()\n with redirect_stdout(f):\n input_name()\n testdata = f.getvalue()\n assert testdata == '\... | [
9,
11,
14,
17,
20
] |
"""
Modulo collection - Counter
Collections -> High-performance Container Datatypes
Counter -> Recebe um interável como parametro e cria um objeto do tipo Collections Counter
que é parecido com um dicionario, contendo como chave o elemento da lista passada como
parametro e como valor a quantidade de ocorrencia... | normal | {
"blob_id": "4989d01f31ca034aacdda28eff56adb2e0bb15da",
"index": 1889,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(f'resultado: {resultado} || seu tipo: {type(resultado)}')\nprint('--------------\\n')\nprint(f\"\"\"Nasca de bacana: \n {Counter('Nasca de bacana')}\"\"\")\nprint('--------------\\n... | [
0,
1,
2,
3,
4
] |
from genericentity import GenericEntity as GEntity
import random as ran
class GenericBreeder(object):
"""description of class: its a classy class"""
def __init__(self,nlifesize,nparentsize,nlowestscore):
self.Reset(nlifesize,nparentsize,nlowestscore)
def Reset(self,nlifesize,nparentsize,nlowe... | normal | {
"blob_id": "753617c189a88adee8430e994aa597c9db9410fe",
"index": 6143,
"step-1": "<mask token>\n\n\nclass GenericBreeder(object):\n <mask token>\n\n def __init__(self, nlifesize, nparentsize, nlowestscore):\n self.Reset(nlifesize, nparentsize, nlowestscore)\n\n def Reset(self, nlifesize, nparents... | [
8,
10,
13,
14,
15
] |
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