code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
import time
import unittest
from unittest import TestCase
from selenium import webdriver
from simon.accounts.pages import LoginPage
from simon.header.pages import HeaderPage
from simon.pages import BasePage
class RegistrationBaseTestCase(TestCase):
def setUp(self):
self.driver = webdriver.Firefox()
... | normal | {
"blob_id": "380a28958fc6d1b403b29ede229860bf5f709572",
"index": 2550,
"step-1": "<mask token>\n\n\nclass LoginPageTests(RegistrationBaseTestCase):\n\n def test_can_open_whatsapp_login_page(self):\n self.assertTrue(self.login_page.is_title_matches())\n self.assertTrue(self.login_page.is_instruct... | [
8,
10,
12,
13,
14
] |
<|reserved_special_token_0|>
class Team(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __str__(self):
return self.name + ' ' + str(self.id)
class Leaderboard(models.Model):
end_date = models.DateField(auto_now=True)
submit_deadline = models.DateField(auto_n... | flexible | {
"blob_id": "dc27781d0c3129d11aa98a5889aea0383b5a49d6",
"index": 3571,
"step-1": "<mask token>\n\n\nclass Team(models.Model):\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.name + ' ' + str(self.id)\n\n\nclass Leaderboard(models.Model):\n end_date = models.DateField(auto_no... | [
8,
9,
10,
13,
15
] |
from typing import List
from uuid import uuid4
from fastapi import APIRouter, Depends, FastAPI, File, UploadFile
from sqlalchemy.orm import Session
from starlette.requests import Request
from Scripts.fastapp.common.consts import UPLOAD_DIRECTORY
from Scripts.fastapp.database.conn import db
# from Scripts.fastapp.data... | normal | {
"blob_id": "349581774cded59ece6a5e8178d116c166a4a6b3",
"index": 6841,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@router.get('/getIsPID', response_model=List[m.GetIsPID])\nasync def show_data(request: Request, ispid):\n \"\"\"\n no params\n\n :return\n\n [\n\n {\n\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Null(torch.optim.Optimizer):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class NoOp(object):
def __init__(self, parameters: typing.Iterator[torch.nn.Parameter]):
self.optimizers = [Null(parameters)]
def step(self, closure=None):
retu... | flexible | {
"blob_id": "3c7237e5770dd5552c327dbf53451a2889ea8c6b",
"index": 7198,
"step-1": "<mask token>\n\n\nclass Null(torch.optim.Optimizer):\n <mask token>\n <mask token>\n\n\nclass NoOp(object):\n\n def __init__(self, parameters: typing.Iterator[torch.nn.Parameter]):\n self.optimizers = [Null(paramete... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_param_num(param):
value = 1
try:
value = rospy.get_param(param)
if not isinstance(value, (int, float, long)):
err_msg = 'Param %s is not an number' % param
rospy.logerr(err... | flexible | {
"blob_id": "70c9d75dabfa9eac23e34f94f34d39c08e21b3c0",
"index": 6070,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_param_num(param):\n value = 1\n try:\n value = rospy.get_param(param)\n if not isinstance(value, (int, float, long)):\n err_msg = 'Param %s is n... | [
0,
2,
3,
4,
5
] |
table = None
width = 1000
height = 1000
def setup():
global table
table = loadTable("flights.csv", "header")
size(width, height)
noLoop()
noStroke()
def draw():
global table
background(255, 255, 255)
for row in table.rows():
from_x = map(row.getFloat('from_long'), -180, 1... | normal | {
"blob_id": "a2eabf4dae931d82e4e9eda87d79031711faf1aa",
"index": 2221,
"step-1": "<mask token>\n\n\ndef mouseMoved():\n redraw()\n",
"step-2": "<mask token>\n\n\ndef setup():\n global table\n table = loadTable('flights.csv', 'header')\n size(width, height)\n noLoop()\n noStroke()\n\n\n<mask t... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class CropRecord(db.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "01a6283d2331590082cdf1d409ecdb6f93459882",
"index": 4861,
"step-1": "<mask token>\n\n\nclass CropRecord(db.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CropRecord(db.Model):\n year = db... | [
1,
5,
9,
10,
11
] |
import os
from test.test_unicode_file_functions import filenames
def writeUniquerecords(dirpath,filenames):
sourcepath=os.path.join(dirpath,filenames)
with open(sourcepath,'r') as fp:
lines= fp.readlines()
destination_lines=[]
for line in lines:
if line not in destination_l... | normal | {
"blob_id": "4ed730369cf065936569a8515de44042829c2143",
"index": 1201,
"step-1": "<mask token>\n\n\ndef writeUniquerecords(dirpath, filenames):\n sourcepath = os.path.join(dirpath, filenames)\n with open(sourcepath, 'r') as fp:\n lines = fp.readlines()\n destination_lines = []\n for li... | [
1,
2,
3,
4,
5
] |
import mclient
from mclient import instruments
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
#from pulseseq import sequencer, pulselib
mpl.rcParams['figure.figsize']=[6,4]
qubit_info = mclient.get_qubit_info('qubit_info')
qubit_ef_info = mclient.get_qubit_info('qubit_ef_info')
... | normal | {
"blob_id": "ba13bcf9e89ae96e9a66a42fc4e6ae4ad33c84b4",
"index": 4497,
"step-1": "import mclient\r\nfrom mclient import instruments\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport matplotlib as mpl\r\n#from pulseseq import sequencer, pulselib\r\n\r\nmpl.rcParams['figure.figsize']=[6,4]\r\n\r\n... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def Mac(SystemArray=[], ProcessorArray=[]):
OSName = str()
OSVersionMajor = str()
OSArchitecture = str()
command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'
ProcInfo = os.popen(command).read().strip()
... | flexible | {
"blob_id": "f652fa6720582d50f57f04d82fb2f5af17859ebd",
"index": 8211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Mac(SystemArray=[], ProcessorArray=[]):\n OSName = str()\n OSVersionMajor = str()\n OSArchitecture = str()\n command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'\n... | [
0,
1,
2,
3
] |
# %%
import pandas as pd
import numpy as np
from dataprep.eda import plot
from dataprep.eda import plot_correlation
from dataprep.eda import plot_missing
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(style="whitegrid", color_codes=True)
sns.set(font_scale=1)
# %%
# Minimal Processing
wines = pd.read... | normal | {
"blob_id": "79e8ed64058dda6c8d7bacc08727bc978088ad2d",
"index": 4963,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsns.set(style='whitegrid', color_codes=True)\nsns.set(font_scale=1)\n<mask token>\nwines.columns\nwines.drop(columns='Unnamed: 0', inplace=True)\nwines.dropna(axis='index', subset=['price... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(20, 1090):
X_train.append(training_set[i - 20:i, 0])
y_train.append(training_set[i, 0])
<|reserved_special_token_0|>
classifier.add(Dense(output_dim=35, init='uniform', activation='relu',
input_dim=20))
... | flexible | {
"blob_id": "28a3763715f5405f8abe2de17ed5f9df1019278b",
"index": 6878,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(20, 1090):\n X_train.append(training_set[i - 20:i, 0])\n y_train.append(training_set[i, 0])\n<mask token>\nclassifier.add(Dense(output_dim=35, init='uniform', activat... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SimpleHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
def log_message(*args, **kwargs):
pass
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SimpleHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
... | flexible | {
"blob_id": "e839eba2514c29a8cfec462f8d5f56d1d5712c34",
"index": 7413,
"step-1": "<mask token>\n\n\nclass SimpleHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):\n\n def log_message(*args, **kwargs):\n pass\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass SimpleHTTPRequestHandler(http... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def pdf_to_png(filename):
doc = fitz.open('pdf_files\\{}'.format(filename))
zoom = 4
page = doc.loadPage(0)
mat = fitz.Matrix(zoom, zoom)
pix = page.getPixmap(matrix=mat)
new_filename = filename.replace('pdf', 'png')
pix.writePNG('photo_files\\{}'.format(new_fi... | flexible | {
"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
] |
"""
Generates a temperature celsius to fahrenheit conversion table
AT
11-10-2018
"""
__author__ = "Aspen Thompson"
header = "| Celsius | Fahrenheit |"
line = "-" * len(header)
print("{0}\n{1}\n{0}".format(line, header))
for i in range(-10, 31):
print("| {:^7} | {:^10.10} |".format(i, i * 1.8 + 32))
| normal | {
"blob_id": "591d0a166af5b8d0bed851c2f56ecc3da4f3a5eb",
"index": 4367,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('{0}\\n{1}\\n{0}'.format(line, header))\nfor i in range(-10, 31):\n print('| {:^7} | {:^10.10} |'.format(i, i * 1.8 + 32))\n",
"step-3": "<mask token>\n__author__ = 'Aspen Thom... | [
0,
1,
2,
3
] |
from PyQt5.QtWidgets import QApplication, QWidget
import sys
class Calculator(QWidget):
def __init__(self):
self.number_str = ""
self.version = "小树计算器 V1.0"
super().__init__()
self.resize(400,400)
from PyQt5.uic import loadUi # 需要导入的模块
#loadUi("record.ui", self) ... | normal | {
"blob_id": "4df9af863a857c3bbc3c266d745a49b6ef78ba9b",
"index": 1994,
"step-1": "<mask token>\n\n\nclass Calculator(QWidget):\n <mask token>\n\n def accept_button_value(self, number):\n if number == 'Clean':\n self.number_str = ''\n elif number == 'Backspace':\n self.nu... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('README.rst') as f:
long_description = f.read()
setup(name='logging_exceptions', version='0.1.8', py_modules=[
'logging_exceptions'], author='Bernhard C. Thiel', author_email=
'thiel@tbi.univie.ac.at', descri... | flexible | {
"blob_id": "7f7adc367e4f3b8ee721e42f5d5d0770f40828c9",
"index": 9365,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('README.rst') as f:\n long_description = f.read()\nsetup(name='logging_exceptions', version='0.1.8', py_modules=[\n 'logging_exceptions'], author='Bernhard C. Thiel', auth... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class CNN:
def __init__(self, inputSize, hitLearn=0.1, momentum=0.9, weigthDecay=
0.5, multip=1.0):
file = '%s/%s' % (DIR_LIBRARY, 'gpu_function.cl')
file = file.encode('utf-8')
self.cnn = c_Pointer()
clib.createCnnWrapper(c.addressof(self.cnn)... | flexible | {
"blob_id": "32db21ed7f57f29260d70513d8c34de53adf12d7",
"index": 5740,
"step-1": "<mask token>\n\n\nclass CNN:\n\n def __init__(self, inputSize, hitLearn=0.1, momentum=0.9, weigthDecay=\n 0.5, multip=1.0):\n file = '%s/%s' % (DIR_LIBRARY, 'gpu_function.cl')\n file = file.encode('utf-8')\n... | [
7,
12,
20,
21,
27
] |
import json
from test.test_basic import BaseCase
class TestUserRegister(BaseCase):
"""
TestClass to test the register function.
"""
def test_successful_register(self):
# Given
payload = json.dumps({
"username": "userjw",
"password": "1q2w3e4r"
})
... | normal | {
"blob_id": "486362463dc07bdafea85de39a4a6d58cb8c8f26",
"index": 9643,
"step-1": "<mask token>\n\n\nclass TestUserRegister(BaseCase):\n <mask token>\n <mask token>\n\n def test_signup_with_non_existing_field(self):\n payload = json.dumps({'username': 'userjw', 'password': '1q2w3e4r',\n ... | [
3,
5,
6,
8,
9
] |
"""
Version information for NetworkX, created during installation.
Do not add this file to the repository.
"""
import datetime
version = '2.3'
date = 'Thu Apr 11 20:57:18 2019'
# Was NetworkX built from a development version? If so, remember that the major
# and minor versions reference the "target" (rather than "... | normal | {
"blob_id": "814191a577db279389975e5a02e72cd817254275",
"index": 9444,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nversion = '2.3'\ndate = 'Thu Apr 11 20:57:18 2019'\ndev = False\nversion_info = 'networkx', '2', '3', None\ndate_info = datetime.datetime(2019, 4, 11, 20, 57, 18)\nvcs_info = None, (None,... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def LDOS_up(omega, E, u, Damping):
t = sum(u ** 2 / (omega - E + 1.0j * Damping))
tt = -1 / pi * np.imag(t)
return tt
def LDOS_down(omega, E, v, Damping):
t = sum(v ** 2 / (omega + E + 1.0j * Damping))
tt = -1 / pi * np.imag(t)
return tt
<|reserved_special_toke... | flexible | {
"blob_id": "f2ad95574b65b4d3e44b85c76f3a0150a3275cec",
"index": 2356,
"step-1": "<mask token>\n\n\ndef LDOS_up(omega, E, u, Damping):\n t = sum(u ** 2 / (omega - E + 1.0j * Damping))\n tt = -1 / pi * np.imag(t)\n return tt\n\n\ndef LDOS_down(omega, E, v, Damping):\n t = sum(v ** 2 / (omega + E + 1.0... | [
2,
3,
4,
5,
6
] |
import csv
import os
with open("sample.csv") as rf:
csv_reader=csv.DictReader(rf)
with open("sample1.csv","w") as wf:
csv_headers=['fname','lname','email']
if os.path.isfile('sample1.csv'):
q=input("File already exists. Do you want to overwrite?")
if q.lower()=='yes':... | normal | {
"blob_id": "43196258b61801799b8d6b7d23f5816d84cb5dff",
"index": 7294,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('sample.csv') as rf:\n csv_reader = csv.DictReader(rf)\n with open('sample1.csv', 'w') as wf:\n csv_headers = ['fname', 'lname', 'email']\n if os.path.isfile... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def vel_det(file, legend_label, line_color):
fps = 60
data_df = pd.read_hdf(path_or_buf=file)
bodyparts = data_df.columns.get_level_values(1)
coords = data_df.columns.get_level_values(2)
bodyparts2plot = bodyparts
scorer = data_df.columns.get_level_values(0)[0]
... | flexible | {
"blob_id": "ba5171d3de87ec01770a7174d9783d5058b0fced",
"index": 9896,
"step-1": "<mask token>\n\n\ndef vel_det(file, legend_label, line_color):\n fps = 60\n data_df = pd.read_hdf(path_or_buf=file)\n bodyparts = data_df.columns.get_level_values(1)\n coords = data_df.columns.get_level_values(2)\n b... | [
1,
2,
3,
4,
5
] |
from django.http import HttpResponse
from django.shortcuts import render_to_response
from django.template import RequestContext
from django.db.models import Q
from cvmo import settings
from cvmo.context.models import ContextDefinition, Machines, ClusterDefinition, MarketplaceContextEntry
from cvmo.context.plugins im... | normal | {
"blob_id": "4db8b4403dd9064b7d5f935d4b9d111508c965fb",
"index": 1268,
"step-1": "<mask token>\n\n\ndef dashboard(request):\n context = {'context_list': ContextDefinition.objects.filter(Q(owner=\n request.user) & Q(inherited=False) & Q(abstract=False)).order_by(\n '-public', 'name'), 'full_abstr... | [
1,
3,
4,
5,
6
] |
import requests
import sxtwl
import datetime
from datetime import date
import lxml
from lxml import etree
# 日历中文索引
ymc = [u"十一", u"十二", u"正", u"二", u"三", u"四", u"五", u"六", u"七", u"八", u"九", u"十"]
rmc = [u"初一", u"初二", u"初三", u"初四", u"初五", u"初六", u"初七", u"初八", u"初九", u"初十", \
u"十一", u"十二", u"十三", u"十四", u"十五", u"十... | normal | {
"blob_id": "e1d0648825695584d3ea518db961a9178ea0c66a",
"index": 50,
"step-1": "<mask token>\n\n\ndef china_lunar():\n today = str(date.today())\n today_list = today.split('-')\n lunar_day = lunar.getDayBySolar(int(datetime.datetime.now().year), int(\n datetime.datetime.now().month), int(datetime... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
def householder_reflection(A):
size = len(A)
Q = np.identity(size)
R = np.copy(A)
for i in range(size - 1):
x = R[i:, i]
e = np.zeros_like(x)
e[0] = np.linalg.norm(x)
u = x - e
v = u / np.linalg.norm(u)
Q_count = np.identity(... | flexible | {
"blob_id": "0d1fda864edc73cc6a9853727228c6fa3dfb19a1",
"index": 3039,
"step-1": "<mask token>\n\n\ndef householder_reflection(A):\n size = len(A)\n Q = np.identity(size)\n R = np.copy(A)\n for i in range(size - 1):\n x = R[i:, i]\n e = np.zeros_like(x)\n e[0] = np.linalg.norm(x)... | [
1,
2,
3,
4,
5
] |
# Takes in a word and makes a list containing individual characters
def split(word):
return [char for char in word]
# Removes empty strings from a list
def removeEmptyStrings(lst):
while "" in lst:
lst.remove("")
ints = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
tokenList = []
class Token:... | normal | {
"blob_id": "8d5b75dc945844d48f52159be08fc1e6aa51fdf5",
"index": 497,
"step-1": "<mask token>\n\n\nclass Lexer:\n\n def __init__(self, items):\n self.items = split(items)\n self.index = 0\n self.item = ''\n self.stringOn = False\n self.stringList = ''\n self.intOn = F... | [
8,
10,
14,
18,
19
] |
#proper clarification for requirement is required
import boto3
s3_resource = boto3.resource('s3')
s3_resource.create_bucket(Bucket=YOUR_BUCKET_NAME, CreateBucketConfiguration={'LocationConstraint': 'eu-west-1'})
s3_resource.Bucket(first_bucket_name).upload_file(Filename=first_file_name, Key=first_file_name)
s3_resource... | normal | {
"blob_id": "44097da54a0bb03ac14196712111a1489a956689",
"index": 5387,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ns3_resource.create_bucket(Bucket=YOUR_BUCKET_NAME,\n CreateBucketConfiguration={'LocationConstraint': 'eu-west-1'})\ns3_resource.Bucket(first_bucket_name).upload_file(Filename=first_fi... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python
L=['ABC','ABC']
con1=[]
for i in range (0,len(L[1])):
#con.append(L[1][i])
con=[]
for j in range (0, len(L)):
print(L[j][i])
con.append(L[j][i])
con1.append(con)
con2=[]
for k in range (0,len(con1)):
if con1[k].count('A')==2:
con2.append('a')
elif con1[k].count('B')... | normal | {
"blob_id": "beb9fe8e37a4f342696a90bc624b263e341e4de5",
"index": 5459,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, len(L[1])):\n con = []\n for j in range(0, len(L)):\n print(L[j][i])\n con.append(L[j][i])\n con1.append(con)\n<mask token>\nfor k in range(0, len... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Vehicle(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Vehicle(object):
<|reserved_special_token_0|>
def __init__(self, registration_number):
self.registration_number = r... | flexible | {
"blob_id": "8b9336113f64a88eeabe6e45021938fac9efd1c6",
"index": 6442,
"step-1": "<mask token>\n",
"step-2": "class Vehicle(object):\n <mask token>\n <mask token>\n",
"step-3": "class Vehicle(object):\n <mask token>\n\n def __init__(self, registration_number):\n self.registration_number = ... | [
0,
1,
2,
3
] |
from os import environ
from flask import Flask
from flask_restful import Api
from flask_migrate import Migrate
from applications.db import db
from applications.gamma_api import add_module_gamma
app = Flask(__name__)
app.config["DEBUG"] = True
app.config['SQLALCHEMY_DATABASE_URI'] = environ.get('DATABASE')
app.config... | normal | {
"blob_id": "fbb081fd52b14336ab4537bb795105bcd6a03070",
"index": 3045,
"step-1": "<mask token>\n\n\n@app.before_first_request\ndef create_tables():\n pass\n\n\n<mask token>\n",
"step-2": "<mask token>\ndb.init_app(app)\n<mask token>\n\n\n@app.before_first_request\ndef create_tables():\n pass\n\n\nadd_mod... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class MonteCarloGameDriver:
def __init__(self):
self.default_moves = np.array(['w', 'a', 's', 'd'])
self.probability_distribution = np.array([0.25, 0.25, 0.25, 0.25])
<|reserved_special_token_0|>
def simulate(self, game, simulation_size):
from collect... | flexible | {
"blob_id": "aeb986360c6990f9375f2552cbdeef595af815b4",
"index": 6432,
"step-1": "<mask token>\n\n\nclass MonteCarloGameDriver:\n\n def __init__(self):\n self.default_moves = np.array(['w', 'a', 's', 'd'])\n self.probability_distribution = np.array([0.25, 0.25, 0.25, 0.25])\n <mask token>\n\n... | [
5,
6,
7,
8,
9
] |
from django.shortcuts import render, get_object_or_404, redirect
from django.contrib.contenttypes.models import ContentType
from User.forms import EditProfileForm
from User import forms
from django.db.models import Q
from django.contrib import messages
from django.urls import reverse
from django.http import HttpRespons... | normal | {
"blob_id": "e9fab2bb49cfda00b8cfedafab0009f691d11ec9",
"index": 9924,
"step-1": "<mask token>\n\n\ndef post_create(request):\n form = PostForm(request.POST or None, request.FILES or None)\n if request.method == 'POST':\n user = request.POST.get('user')\n title = request.POST.get('title')\n ... | [
5,
6,
7,
8,
10
] |
from rest_framework import status
from rest_framework.response import Response
from rest_framework.decorators import api_view, permission_classes
from rest_framework.permissions import IsAuthenticated
from playlist.models import Song, AccountSong, Genre, AccountGenre
from account.models import Account
from play... | normal | {
"blob_id": "ff53a549222b0d5e2fcb518c1e44b656c45ce76e",
"index": 5183,
"step-1": "<mask token>\n\n\n@api_view(['POST'])\n@permission_classes((IsAuthenticated,))\ndef create_account_genre_view(request):\n title = request.data.get('title', '0')\n try:\n genre = Genre.objects.get(title=title)\n exce... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
@app.route('/login/')
def login():
return render_template('login.html', name=None)
@app.route('/chat/')
def chat():
return render_template('chat.html', name=None)
@app.route('/messages/')
def msg_search():
return render_template('search.html', name=None)
<|reserved_speci... | flexible | {
"blob_id": "a945d7f673d009a59e597cd3c99a886094ea9e57",
"index": 2639,
"step-1": "<mask token>\n\n\n@app.route('/login/')\ndef login():\n return render_template('login.html', name=None)\n\n\n@app.route('/chat/')\ndef chat():\n return render_template('chat.html', name=None)\n\n\n@app.route('/messages/')\nde... | [
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def make_id2class(args):
if args.dataset == 'caltech101':
return caltech.id2class
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def make_data_loader(args, **kwargs):
if args.dataset == 'caltech10... | flexible | {
"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
] |
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 21 09:46:47 2020
@author: Carlos Jose Munoz
"""
# se importa el modelo y vista para que sesten comunicados por medio del controlador
from Modelo import ventanadentrada
from Vista import Ventanainicio,dosventana
import sys
from PyQt5.QtWidgets import QApplication
clas... | normal | {
"blob_id": "3329db63552592aabb751348efc5d983f2cc3f36",
"index": 1828,
"step-1": "<mask token>\n\n\nclass Controlador(object):\n\n def __init__(self, vista, modelo, vista2):\n self._mi_vista = vista\n self._mi_modelo = modelo\n self._mi2_ventana = vista2\n\n def recibirruta(self, r):\n... | [
7,
8,
9,
10,
12
] |
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
#
# This code is sample only. Not for use in production.
#
# Author: Babu Srinivasan
# Contact: babusri@amazon.com, babu.b.srinivasan@gmail.com
#
# Spark Streaming ETL script
# Input:
# 1/ Kinesis Data Strea... | normal | {
"blob_id": "fcccbc8d582b709aa27500ef28d86103e98eee4c",
"index": 7980,
"step-1": "<mask token>\n\n\ndef populateTimeInterval(rec):\n out_ts = (rec['event_time'] - TEMP_TS) // DELTA_MINS * DELTA_MINS + TEMP_TS\n rec['intvl_date'] = datetime.datetime.strftime(out_ts, '%Y-%m-%d')\n rec['intvl_hhmm'] = date... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class Shape(ABC):
@abstractmethod
def area(self):
pass
<|reserved_special_token_0|>
class Square(Shape):
def __init__(self, length):
self.length = length
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class... | flexible | {
"blob_id": "520b9246c3c617b18ca57f31ff51051cc3ff51ca",
"index": 5517,
"step-1": "<mask token>\n\n\nclass Shape(ABC):\n\n @abstractmethod\n def area(self):\n pass\n <mask token>\n\n\nclass Square(Shape):\n\n def __init__(self, length):\n self.length = length\n\n\n<mask token>\n",
"ste... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class PersistableClassificationModel(Classification):
<|reserved_special_token_0|>
def __init__(self, output_dir, origin):
self.originModel = origin
if not os.path.isdir(output_dir):
os.mkdir(output_dir)
self.path_to_persist = os.path.join(outp... | flexible | {
"blob_id": "a4697f0a0d0cc264b28a58bcc28528c221b4cb49",
"index": 3807,
"step-1": "<mask token>\n\n\nclass PersistableClassificationModel(Classification):\n <mask token>\n\n def __init__(self, output_dir, origin):\n self.originModel = origin\n if not os.path.isdir(output_dir):\n os.... | [
3,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^buildings_csv/$', buildings_upload, name=
'buildings_upload'), url('^keytype_csv/$', keytype_upload, name=
'keytype_upload'), url('^key_csv/$', key_upload, name='key_upload'),
url('^keystatus_csv/$... | flexible | {
"blob_id": "4a0d8e6b6205fa57b8614857e1462203a2a7d2c5",
"index": 3002,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^buildings_csv/$', buildings_upload, name=\n 'buildings_upload'), url('^keytype_csv/$', keytype_upload, name=\n 'keytype_upload'), url('^key_csv/$', key_upload, ... | [
0,
1,
2,
3
] |
"""
Copyright © 2017 Bilal Elmoussaoui <bil.elmoussaoui@gmail.com>
This file is part of Authenticator.
Authenticator is free software: you can redistribute it and/or
modify it under the terms of the GNU General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at ... | normal | {
"blob_id": "a7d8efe3231b3e3b9bfc5ef64a936816e8b67d6c",
"index": 3127,
"step-1": "<mask token>\n\n\n@Gtk.Template(resource_path=\n '/com/github/bilelmoussaoui/Authenticator/settings.ui')\nclass SettingsWindow(Handy.PreferencesWindow):\n <mask token>\n dark_theme_switch: Gtk.Switch = Gtk.Template.Child()... | [
10,
11,
13,
19,
21
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while m != 0:
m = int(input())
if m > maximum:
maximum = m
count = 1
elif m == maximum:
count += 1
print(count)
<|reserved_special_token_1|>
count = 0
maximum = -1
m = -1
while m != 0:
m ... | flexible | {
"blob_id": "0e1ea8c7fba90c1b5d18eaa399b91f237d4defee",
"index": 2568,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile m != 0:\n m = int(input())\n if m > maximum:\n maximum = m\n count = 1\n elif m == maximum:\n count += 1\nprint(count)\n",
"step-3": "count = 0\nmaxi... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('register/', register, name='register'), path(
'channel/', channel, name='channel'), path('login/', auth_views.
LoginView.as_view(template_name='user/login.html'), name='login'), path
('logout/', au... | flexible | {
"blob_id": "d76c1507594bb0c1ed7a83e6c5961097c7fbf54a",
"index": 9859,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('register/', register, name='register'), path(\n 'channel/', channel, name='channel'), path('login/', auth_views.\n LoginView.as_view(template_name='user/login.h... | [
0,
1,
2,
3
] |
"""
All rights reserved to cnvrg.io
http://www.cnvrg.io
cnvrg.io - Projects Example
last update: Nov 07, 2019.
-------------
rnn.py
==============================================================================
"""
import argparse
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow i... | normal | {
"blob_id": "fbac2d66f4d69a52c3df5d665b622659e4d8dacd",
"index": 5733,
"step-1": "<mask token>\n\n\ndef cast_types(args):\n args.epochs = int(args.epochs)\n args.batch_size = int(args.batch_size)\n args.input_shape = args.input_shape.split(' ')\n for num in args.input_shape:\n if num != '':\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def check_cookie(request):
result = {'status': True}
try:
user_id = request.GET.get('user_id')
user = User.objects.get(pk=user_id)
cookie_status = user.profile.cookie_status
if cookie_status is Status.DEACTIVATE:
result['cookie_status'] ... | flexible | {
"blob_id": "2bc3b0df720788e43da3d9c28adb22b3b1be8c58",
"index": 5002,
"step-1": "<mask token>\n\n\ndef check_cookie(request):\n result = {'status': True}\n try:\n user_id = request.GET.get('user_id')\n user = User.objects.get(pk=user_id)\n cookie_status = user.profile.cookie_status\n ... | [
1,
2,
3,
4,
5
] |
from Adafruit_LSM9DS0 import Adafruit_LSM9DS0
import math
imu = Adafruit_LSM9DS0()
pi = 3.14159265358979323846 # Written here to increase performance/ speed
r2d = 57.2957795 # 1 radian in degrees
loop = 0.05 #
tuning = 0.98 # Constant for tuning Complimentary filter
# Converting accelerometer readings to degrees
ax ... | normal | {
"blob_id": "973a58013160cbc71ca46f570bde61eaff87f6a7",
"index": 7489,
"step-1": "from Adafruit_LSM9DS0 import Adafruit_LSM9DS0\nimport math\n\nimu = Adafruit_LSM9DS0()\n\npi = 3.14159265358979323846 # Written here to increase performance/ speed\nr2d = 57.2957795 # 1 radian in degrees\nloop = 0.05 #\ntuning = 0.... | [
0
] |
<|reserved_special_token_0|>
def generateLog(ctime1, request_obj):
log_file.write(ctime1 + '\t')
log_file.write('Status code: ' + str(request_obj.status_code))
log_file.write('\n')
def is_internet():
"""Internet function"""
print(time.ctime())
current_time = time.ctime()
try:
r =... | flexible | {
"blob_id": "f229f525c610d9925c9300ef22208f9926d6cb69",
"index": 9985,
"step-1": "<mask token>\n\n\ndef generateLog(ctime1, request_obj):\n log_file.write(ctime1 + '\\t')\n log_file.write('Status code: ' + str(request_obj.status_code))\n log_file.write('\\n')\n\n\ndef is_internet():\n \"\"\"Internet ... | [
2,
3,
4,
5,
6
] |
"""Unit test for int install
"""
import math
import pytest
ROUND_OFF_ERROR = 0.001
def int_installs(x):
try:
return int(x.replace(',', '').replace('+', ''))
except:
raise ValueError("Cannot transform to int.")
def test_int_install_1():
"""Unit test to showcase functionality of int... | normal | {
"blob_id": "b874bfe9590a3eaff4298d6f9cc72be92000dc30",
"index": 1108,
"step-1": "<mask token>\n\n\ndef int_installs(x):\n try:\n return int(x.replace(',', '').replace('+', ''))\n except:\n raise ValueError('Cannot transform to int.')\n\n\ndef test_int_install_1():\n \"\"\"Unit test to sho... | [
2,
4,
5,
6,
7
] |
# These are instance types to make available to all AWS EC2 systems, except the .
# PostgreSQL server, until the auto tuning playbook can tune for systems that
# small.
AWSGlobalInstanceChoices = [
't2.nano', 't2.micro',
't3.nano', 't3.micro',
't3a.nano', 't3a.micro',
]
class SpecValidator:
... | normal | {
"blob_id": "4db93bdab2d73e7226dcad61827f5faea8513767",
"index": 9888,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SpecValidator:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass SpecValidator:\n\n def __init__(self, type=None, default=None, choices=[], min=Non... | [
0,
1,
2,
3,
4
] |
import os
from google.cloud import bigquery
def csv_loader(data, context):
client = bigquery.Client()
dataset_id = os.environ['DATASET']
dataset_ref = client.dataset(dataset_id)
job_config = bigquery.LoadJobConfig()
job_config.schema = [
bigquery.SchemaField('id'... | normal | {
"blob_id": "01467a4dad3255a99025c347469881a71ffbae7c",
"index": 8179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef csv_loader(data, context):\n client = bigquery.Client()\n dataset_id = os.environ['DATASET']\n dataset_ref = client.dataset(dataset_id)\n job_config = bigquery.LoadJob... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Game(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Player(models.Model):
... | flexible | {
"blob_id": "2fd33439d4403ec72f890a1d1b4f35f2b38d033b",
"index": 9268,
"step-1": "<mask token>\n\n\nclass Game(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Player(models.Model):\n \"\"\" Model that descr... | [
4,
7,
9,
10,
11
] |
#manual forward propagation
#based on a course I got from Datacamp.com 'Deep Learning in Python'
#python3 ~/Documents/pyfiles/dl/forward.py
#imports
import numpy as np
#we are going to simulate a neural network forward propagation algorithm
#see the picture forwardPropagation.png for more info
#the basics are it mov... | normal | {
"blob_id": "6a09311b5b3b876fd94ed0a9cce30e070528f22c",
"index": 2993,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(weights)\n<mask token>\nprint(hidden_layer_vals)\n<mask token>\nprint(output_val)\n<mask token>\n",
"step-3": "<mask token>\ninput_data = np.array([2, 3])\nweights = {'node_0': np... | [
0,
1,
2,
3,
4
] |
from bs4 import BeautifulSoup
import requests
res = requests.get('http://quotes.toscrape.com/')
#print(res.content)
#proper ordered printing
#print(res.text)
#lxml -> parser library
soup = BeautifulSoup(res.text , 'lxml')
#print(soup)
quote = soup.find_all('div',{'class' : 'quote'})
with open('Quotes.txt... | normal | {
"blob_id": "777c08876a2de803fc95de937d9e921044545ef8",
"index": 3674,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Quotes.txt', 'w') as ff:\n for q in quote:\n msg = q.find('span', {'class': 'text'})\n print(msg.text)\n ff.write(msg.text)\n author = q.find('sm... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class CpmsConnector:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, config):
"""initialize with config
config(dict): must supply username, api_key, api_url
"""
self.username = config['username']
self.api_ke... | flexible | {
"blob_id": "5bd2cf2ae68708d2b1dbbe0323a5f83837f7b564",
"index": 7842,
"step-1": "<mask token>\n\n\nclass CpmsConnector:\n <mask token>\n <mask token>\n\n def __init__(self, config):\n \"\"\"initialize with config\n config(dict): must supply username, api_key, api_url\n \"\"\"\n ... | [
13,
16,
17,
19,
20
] |
# [SIG Python Task 1]
"""
Tasks to performs:
a) Print 'Hello, World! From SIG Python - <your name>' to the screen
b) Calculate Volume of a Sphere
c) Create a customised email template for all students,
informing them about a workshop.
PS: This is called a docstring... and it will not be interepreted
... | normal | {
"blob_id": "150e0180567b74dfcd92a6cd95cf6c6bf36f6b5d",
"index": 4228,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('hello, World! From SIG Python - Gaurangi Rawat')\n<mask token>\nprint('volume=', volume)\n<mask token>\nprint(email_msg)\n",
"step-3": "<mask token>\nprint('hello, World! From SI... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MovieSerializer(serializers.Serializer):
<|reserved_special_token_0|>
class FilmSerializer(serializers.ModelSerializer):
class Meta:
model = Movie
fields = '__all__'
<|reserved_special_token_1... | flexible | {
"blob_id": "0509afdce0d28cc04f4452472881fe9c5e4fbcc4",
"index": 7825,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass MovieSerializer(serializers.Serializer):\n <mask token>\n\n\nclass FilmSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Movie\n fields = ... | [
0,
2,
3,
4
] |
import torch
from torch import nn
import torch.nn.functional as F
import numpy as np
from config_pos import config
from backbone.resnet50 import ResNet50
from backbone.fpn import FPN
from module.rpn import RPN
from layers.pooler import roi_pooler
from det_oprs.bbox_opr import bbox_transform_inv_opr
from det_oprs.bbox_... | normal | {
"blob_id": "6ac13665c2348bf251482f250c0fcc1fc1a8af75",
"index": 4721,
"step-1": "<mask token>\n\n\nclass Network(nn.Module):\n\n def __init__(self):\n super().__init__()\n self.resnet50 = ResNet50(config.backbone_freeze_at, False)\n self.FPN = FPN(self.resnet50, 2, 6)\n self.RPN =... | [
5,
6,
7,
8,
11
] |
#!/usr/local/bin/python
import cgi
import pymysql
import pymysql.cursors
import binascii
import os
from mylib import siteLines
import threading
def checkStringLine(ip, host, pagel, objects, title):
onlyIp = ip.split(":")[0]
connection = siteLines()
with connection.cursor() as cursor:
#... | normal | {
"blob_id": "6c5c07dadbe7ec70a210ee42e756be0d710c0993",
"index": 5272,
"step-1": "<mask token>\n\n\ndef checkStringLine(ip, host, pagel, objects, title):\n onlyIp = ip.split(':')[0]\n connection = siteLines()\n with connection.cursor() as cursor:\n sql = f\"SELECT `IP` FROM `sites` WHERE `IP`='{o... | [
1,
2,
4,
5,
6
] |
# 12.02.17
"""
nomencalura
a__b__c
a: parametro
t-temperatura
tm-temperatura minima
tM-teperatura massima
b: intervallo di tempo
a-anno
c: tabella fonte dati
g-giornaliero
"""
import db_02 as DB
def t_tm_tM__a__g(db, anno):
cmd = """
SELECT data, t, tmin, tmax
FROM Giornaliero
WHERE strft... | normal | {
"blob_id": "26b0a762b8eb30f0ef3c5a914f032c2a7d24f750",
"index": 5606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef t_tm_tM__a__g(db, anno):\n cmd = (\n \"\\nSELECT data, t, tmin, tmax\\nFROM Giornaliero\\nWHERE strftime('%Y') = '{}'\\n \"\n .format(anno))\n dati = db.cur... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@application.route('/')
def hello_world():
return jsonify({'Hello': 'World'})
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
load_dotenv(dotenv_path='./.env')
<|reserved_special_token_0|>
@application.route('/')
def hello_world():
ret... | flexible | {
"blob_id": "72e03e7199044f3ed1d562db622a7b884fa186b0",
"index": 2206,
"step-1": "<mask token>\n\n\n@application.route('/')\ndef hello_world():\n return jsonify({'Hello': 'World'})\n\n\n<mask token>\n",
"step-2": "<mask token>\nload_dotenv(dotenv_path='./.env')\n<mask token>\n\n\n@application.route('/')\nde... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class NestableBlueprint(Blueprint):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class NestableBlueprint(Blueprint):
def register_blueprint(self, blueprint, **options):
... | flexible | {
"blob_id": "2c505f3f1dfdefae8edbea0916873229bcda901f",
"index": 764,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NestableBlueprint(Blueprint):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass NestableBlueprint(Blueprint):\n\n def register_blueprint(self, blueprint, **options):\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_logger():
_logger = logging.getLogger('EduNLP')
_logger.setLevel(logging.INFO)
_logger.propagate = False
ch = logging.StreamHandler()
ch.setFormatter(logging.Formatter('[%(name)s, %(levelname)s] %(mes... | flexible | {
"blob_id": "41f71589d3fb9f5df218d8ffa0f608a890c73ad2",
"index": 8486,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_logger():\n _logger = logging.getLogger('EduNLP')\n _logger.setLevel(logging.INFO)\n _logger.propagate = False\n ch = logging.StreamHandler()\n ch.setFormatter(... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class TestFeatureReader(unittest.TestCase):
<|reserved_special_token_0|>
def testRFEFull(self):
feat = ['column1', 'column2', 'column3']
read_data = 'Header\n---- column1\n---- column2\n---- column3\n'
mock_open = mock.mock_open(read_data=read_data)
... | flexible | {
"blob_id": "5436e9270e61f5f9ab41fc1f35a80f4b8def65ee",
"index": 2048,
"step-1": "<mask token>\n\n\nclass TestFeatureReader(unittest.TestCase):\n <mask token>\n\n def testRFEFull(self):\n feat = ['column1', 'column2', 'column3']\n read_data = 'Header\\n---- column1\\n---- column2\\n---- colum... | [
14,
16,
17,
18,
19
] |
<|reserved_special_token_0|>
def detail(request, post_id):
po = get_object_or_404(post, pk=post_id)
ratelist = [1, 2, 3, 4, 5]
return render(request, 'detail.html', {'post': po, 'ratelist': ratelist})
@login_required(login_url='/login/')
def delet(request, post_id):
po = get_object_or_404(post, pk=p... | flexible | {
"blob_id": "2b88bec388f3872b63d6bfe200e973635bb75054",
"index": 5418,
"step-1": "<mask token>\n\n\ndef detail(request, post_id):\n po = get_object_or_404(post, pk=post_id)\n ratelist = [1, 2, 3, 4, 5]\n return render(request, 'detail.html', {'post': po, 'ratelist': ratelist})\n\n\n@login_required(login... | [
2,
4,
5,
6,
7
] |
#Bingo Game
#Anthony Swift
#06/05/2019
'''
A simple bingo game. Player is presented with a randomly generated grid of numbers.
Player is asked to enter the number called out by the caller, each time a number is called out.
A chip ('X') is placed on the grid when the number entered (that has been called) match... | normal | {
"blob_id": "7be62ce45f815c4f4cf32df696cc444f92ac6d5c",
"index": 8901,
"step-1": "<mask token>\n\n\ndef welcome():\n print('\\nWelcome to the Bingo Game.')\n\n\ndef initialise_grid():\n grid = [['', '', '', '', ''], ['', '', '', '', ''], ['', '', '', '', ''\n ], ['', '', '', '', ''], ['', '', '', ''... | [
14,
15,
16,
17,
18
] |
from . import views
from django.urls import path, re_path
app_name = "blogs"
urlpatterns = [
path('', views.index, name='index'),
re_path(r'^blogs/(?P<blog_id>\d+)/$', views.blog, name='blog'),
path('new_blog/', views.new_blog, name='new_blog'),
re_path(r'^edit_blog/(?P<blog_id>\d+)/$', views.edit_blog, name='edit_bl... | normal | {
"blob_id": "d73491d6673abdabad85176c5f75a191995c806d",
"index": 1260,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'blogs'\nurlpatterns = [path('', views.index, name='index'), re_path(\n '^blogs/(?P<blog_id>\\\\d+)/$', views.blog, name='blog'), path(\n 'new_blog/', views.new_blog, nam... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def update_key(data_base, url, kkey):
keys_saved = regex.get_data('<key>\\s(.+?)\\s<', data_base[url]['key'])
if kkey not in keys_saved:
data_base[url]['key'] = data_base[url]['key'][:-1]
data_base[url]['... | flexible | {
"blob_id": "50a5d3431693b402c15b557357eaf9a85fc02b0b",
"index": 2921,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef update_key(data_base, url, kkey):\n keys_saved = regex.get_data('<key>\\\\s(.+?)\\\\s<', data_base[url]['key'])\n if kkey not in keys_saved:\n data_base[url]['key'] =... | [
0,
7,
8,
9,
11
] |
<|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": "1e83fedb8a5ed51704e991aeaa4bde20d5316d11",
"index": 2351,
"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 = [('account', '... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class EventMQTTHandler(BaseMQTTHandler):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, mqtt_server, qos=QOS_0, callback_ms=None):
super(EventMQTTHandler, self).__init__(mqtt_server)
callback_ms = ... | flexible | {
"blob_id": "b3f72bc12f85724ddcdaf1c151fd2a68b29432e8",
"index": 6545,
"step-1": "<mask token>\n\n\nclass EventMQTTHandler(BaseMQTTHandler):\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, mqtt_server, qos=QOS_0, callback_ms=None):\n super(EventMQTTHandler, self).__init__(m... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def setup(data):
common.access_golem(data.env.url, data.env.admin)
api.project.using_project('test_builder_code')
data.test = api.test.create_access_test_code(data.project)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def setup(... | flexible | {
"blob_id": "d4cdc4f1995eab7f01c970b43cb0a3c5ed4a2711",
"index": 3673,
"step-1": "<mask token>\n\n\ndef setup(data):\n common.access_golem(data.env.url, data.env.admin)\n api.project.using_project('test_builder_code')\n data.test = api.test.create_access_test_code(data.project)\n\n\n<mask token>\n",
"... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Note:
num: int
@classmethod
def choice(cls, *args: int):
return Note(choice(args))
@classmethod
def from_midi(cls, midi: int, root: int):
note = midi_to_note.get(midi % root)
if isinstance(note, int):
return cls(note)
... | flexible | {
"blob_id": "d70f77713abf4b35db9de72c1edbf4bf4580b2a4",
"index": 8795,
"step-1": "<mask token>\n\n\nclass Note:\n num: int\n\n @classmethod\n def choice(cls, *args: int):\n return Note(choice(args))\n\n @classmethod\n def from_midi(cls, midi: int, root: int):\n note = midi_to_note.ge... | [
24,
26,
28,
33,
34
] |
d = {
1 : 'I',
5 : 'V',
10: 'X',
50: 'L',
100: 'C',
500: 'D',
1000: 'M'
}
e = {
'I': 1,
'V': 5,
'X': 10,
'L': 50,
'C': 100,
'D': 500,
... | normal | {
"blob_id": "1a29b3138f6a33fbe2781f044c1bcccd03ecd48d",
"index": 7590,
"step-1": "<mask token>\n\n\ndef convert2numeral(rom):\n cur = 0\n num = 0\n while cur < len(rom):\n if cur + 1 == len(rom):\n num += e[rom[cur]]\n elif e[rom[cur]] > e[rom[cur + 1]]:\n num += e[ro... | [
1,
2,
3,
4,
5
] |
from jox_api import label_image,Mysql,Utils
from jox_config import api_base_url
import json
class Menu():
def __init__(self):
self.mysqlClass = Mysql.MySQL()
self.timeClass = Utils.Time()
def get_menu(self,type,openid):
try:
if type == 'mine':
self.sql = "SEL... | normal | {
"blob_id": "4fa9d16f979acf3edce05a209e1c6636e50fc315",
"index": 222,
"step-1": "<mask token>\n\n\nclass Menu:\n <mask token>\n\n def get_menu(self, type, openid):\n try:\n if type == 'mine':\n self.sql = (\n \"SELECT * FROM get_menu WHERE openid='%s' ord... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
#allisnone 20200403
#https://github.com/urllib3/urllib3/issues/1434
#https://github.com/dopstar/requests-ntlm2
#https://github.com/requests/requests-ntlm
#base on python3
#if you request https website, you need to add ASWG CA to following file:
#/root/.pyenv/versio... | normal | {
"blob_id": "a7fae2da8abba6e05b4fc90dec8826194d189853",
"index": 2758,
"step-1": "<mask token>\n\n\ndef get_random_ip_or_user(start, end, prefix='172.16.90.', type='ip'):\n if type == 'ip' and max(start, end) > 255:\n end = 255\n i = random.randint(start, end)\n return prefix + str(i)\n\n\ndef ge... | [
6,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
class Replacer:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __new__(cls, *args, **kwargs):
subs = WeightedList(cls.__subclasses__(), [sub.subclass_weight for
sub in cls.__subclasses__()])
if subs and cls.go_deeper(subs):
... | flexible | {
"blob_id": "3a878c91218dfbf23477ae5b7561e9eecfcd1350",
"index": 5053,
"step-1": "<mask token>\n\n\nclass Replacer:\n <mask token>\n <mask token>\n\n def __new__(cls, *args, **kwargs):\n subs = WeightedList(cls.__subclasses__(), [sub.subclass_weight for\n sub in cls.__subclasses__()])\... | [
7,
10,
11,
13,
15
] |
"""
Quick select (randomized selection algorithm)
- based on quick sort (ch8_sorting); used to obtain the ith-smallest element in an unordered list of items (e.g.numbers)
"""
def swap(unsorted_array, a, b):
temp = unsorted_array[a]
unsorted_array[a] = unsorted_array[b]
unsorted_array[b] = temp
def part... | normal | {
"blob_id": "f9234741c6356b4677b5d32ffea86549d001c258",
"index": 5625,
"step-1": "<mask token>\n\n\ndef swap(unsorted_array, a, b):\n temp = unsorted_array[a]\n unsorted_array[a] = unsorted_array[b]\n unsorted_array[b] = temp\n\n\n<mask token>\n\n\ndef quick_select_helper(unsorted_array, left, right, k)... | [
3,
4,
5,
6,
7
] |
#颜色选择对话框
import tkinter
import tkinter.colorchooser
root = tkinter.Tk()
root.minsize(300,300)
#添加颜色选择按钮
def select():
#打开颜色选择器
result = tkinter.colorchooser.askcolor(title = '内裤颜色种类',initialcolor = 'purple')
print(result)
#改变按钮颜色
btn1['bg'] = result[1]
btn1 = tkinter.Button(root,text = '请选择你的内裤颜色... | normal | {
"blob_id": "dc261b29c1c11bb8449ff20a7f2fd120bef9efca",
"index": 6090,
"step-1": "<mask token>\n\n\ndef select():\n result = tkinter.colorchooser.askcolor(title='内裤颜色种类', initialcolor=\n 'purple')\n print(result)\n btn1['bg'] = result[1]\n\n\n<mask token>\n",
"step-2": "<mask token>\nroot.minsi... | [
1,
2,
3,
4,
5
] |
# Generated by Django 2.2.5 on 2020-01-05 04:05
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='News',
fields=[
('id', models.AutoField(aut... | normal | {
"blob_id": "d40e1cfa2ef43f698e846c25ac9f5471d69e71a0",
"index": 5253,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(N):
mix_ind = np.random.choice(len(mix_prob), p=mix_prob)
data_point = np.random.multivariate_normal(clust_means[mix_ind],
clust_gammas[mix_ind])
data_set.append(data_point)
true_labels.appen... | flexible | {
"blob_id": "5807d1c2318ffa19d237d77fbe3f4c1d51da8601",
"index": 7634,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(N):\n mix_ind = np.random.choice(len(mix_prob), p=mix_prob)\n data_point = np.random.multivariate_normal(clust_means[mix_ind],\n clust_gammas[mix_ind])\n da... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Agent(object):
<|reserved_special_token_0|>
def __init__(self, q, epsilon=0.8, discount=0.9, learningRate=0.5,
traceDecay=0.3):
possibleChangesPerMagnet = 0.01, 0.001, 0, -0.01, -0.001
self.actionSet = tuple(torch.tensor((x, y), dtype=torch.float) fo... | flexible | {
"blob_id": "63edbbbad9561ddae005d2b5e22a089819dc34c5",
"index": 1821,
"step-1": "<mask token>\n\n\nclass Agent(object):\n <mask token>\n\n def __init__(self, q, epsilon=0.8, discount=0.9, learningRate=0.5,\n traceDecay=0.3):\n possibleChangesPerMagnet = 0.01, 0.001, 0, -0.01, -0.001\n ... | [
8,
9,
10,
12,
13
] |
<|reserved_special_token_0|>
def energy2(n):
return (n * h / L) ** 2 / (8 * m) * convert
def factorial(n):
out = 1
for x in range(n):
out = out * (x + 1)
return out
<|reserved_special_token_0|>
def configs(x, elvl, particle='boson', out=None):
"""
Generate configs for bosons or f... | flexible | {
"blob_id": "42f656898481768ea0bf1ca0b6afbe06de9dd597",
"index": 4132,
"step-1": "<mask token>\n\n\ndef energy2(n):\n return (n * h / L) ** 2 / (8 * m) * convert\n\n\ndef factorial(n):\n out = 1\n for x in range(n):\n out = out * (x + 1)\n return out\n\n\n<mask token>\n\n\ndef configs(x, elvl,... | [
7,
10,
12,
14,
15
] |
from data import constants
from data.action import Action
from data.point import Point
class MoveActorsAction(Action):
"""A code template for moving actors. The responsibility of this class of
objects is move any actor that has a velocity more than zero.
Stereotype:
Controller
Attributes:... | normal | {
"blob_id": "3be7183b5c1d86ee0ebfdea89c6459efe89510f8",
"index": 6103,
"step-1": "<mask token>\n\n\nclass MoveActorsAction(Action):\n <mask token>\n\n def execute(self, cast):\n \"\"\"Executes the action using the given actors.\n\n Args:\n cast (dict): The game actors {key: tag, va... | [
2,
3,
4,
5,
6
] |
from django.test import TestCase, Client
from django.urls import reverse
from django.contrib.auth import get_user_model
from tweets.models import Tweet
from ..models import UserProfile
User = get_user_model()
class TestAccountsViews(TestCase):
def setUp(self):
self.username = 'masterbdx'
self.ema... | normal | {
"blob_id": "888a5847beca2470f4063da474da1f05079abca9",
"index": 5579,
"step-1": "<mask token>\n\n\nclass TestAccountsViews(TestCase):\n <mask token>\n <mask token>\n\n def test_logout_view(self):\n response = self.client.get(reverse('accounts:logout'))\n self.assertEqual(response.status_c... | [
9,
10,
11,
12,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def e_greedy(steps: [Step], actions: [Action], value_estimator:
ValueEstimator, e: float) ->int:
return random.sample(actions, 1) if random.uniform(0, 1) < e else greedy(
steps, actions, value_estimator)
<|rese... | flexible | {
"blob_id": "eab45dafd0366af8ab904eb33719b86777ba3d65",
"index": 2925,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef e_greedy(steps: [Step], actions: [Action], value_estimator:\n ValueEstimator, e: float) ->int:\n return random.sample(actions, 1) if random.uniform(0, 1) < e else greedy(\n ... | [
0,
1,
2,
3,
4
] |
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
] |
<|reserved_special_token_0|>
class Ui_KEY(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Ui_KEY(object):
def setupUi(self, KEY):
KEY.setObjectName('KEY')
KEY.resize(419, 106)
self.Key1 = QtWid... | flexible | {
"blob_id": "1dab0084666588f61d0f9f95f88f06ed9d884e5b",
"index": 3892,
"step-1": "<mask token>\n\n\nclass Ui_KEY(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Ui_KEY(object):\n\n def setupUi(self, KEY):\n KEY.setObjectName('KEY')\n KEY.resize(419, 106)\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class AcademyConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class AcademyConfig(AppConfig):
name = 'academy'
verbose_na... | flexible | {
"blob_id": "619d2df45d0823930484f030a9a78e71ec718cb7",
"index": 6661,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AcademyConfig(AppConfig):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AcademyConfig(AppConfig):\n name = 'academy'\n verbose_name = u'Акад... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import sys
sys.path.append('./spec')
# FIXME: make the spec file an argument to this script
from dwarf3 import *
def mandatory_fragment(mand):
if mand:
return "mandatory"
else:
return "optional"
def super_attrs(tag):
#sys.stderr.write("Calculating super attrs for... | normal | {
"blob_id": "223d96806631e0d249e8738e9bb7cf5b1f48a8c1",
"index": 4252,
"step-1": "#!/usr/bin/env python\n\nimport sys\n\nsys.path.append('./spec')\n\n# FIXME: make the spec file an argument to this script\nfrom dwarf3 import *\n\ndef mandatory_fragment(mand):\n if mand: \n return \"mandatory\"\n els... | [
0
] |
<|reserved_special_token_0|>
class Ubiquitination:
<|reserved_special_token_0|>
def load_R(self):
pass
def data_path(self, name):
exp_path = './web_app/data/disease/exp_data/{}.txt'.format(name)
clinical_path = './web_app/data/disease/clinical/{}.txt'.format(name)
ubiquit... | flexible | {
"blob_id": "a6ae4324580a8471969e0229c02ea1670728f25b",
"index": 3767,
"step-1": "<mask token>\n\n\nclass Ubiquitination:\n <mask token>\n\n def load_R(self):\n pass\n\n def data_path(self, name):\n exp_path = './web_app/data/disease/exp_data/{}.txt'.format(name)\n clinical_path = '... | [
7,
8,
10,
12,
13
] |
<|reserved_special_token_0|>
class RandomIPv4Waiter(WaiterInterface):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def generator(self):
while self.limit_generate != 0:
randomIPv4 = generateRandomIPv4()
yield randomIPv4, self.ports
if self.limit_gen... | flexible | {
"blob_id": "bd3b1263d7d657fe2edd3c7198f63821a3d1d1e5",
"index": 319,
"step-1": "<mask token>\n\n\nclass RandomIPv4Waiter(WaiterInterface):\n <mask token>\n <mask token>\n\n def generator(self):\n while self.limit_generate != 0:\n randomIPv4 = generateRandomIPv4()\n yield ra... | [
2,
4,
5,
6,
7
] |
#!/usr/bin/env python
import rospy
import cv2
from geometry_msgs.msg import PoseStamped
class PositionReader:
def __init__(self):
self.image_sub = rospy.Subscriber(
"/visp_auto_tracker/object_position", PoseStamped, self.callback)
self.pub = rospy.Publisher('object_position', PoseSta... | normal | {
"blob_id": "26ac0c94d0ab70d90854ca2c913ef0f633b54a3c",
"index": 4527,
"step-1": "<mask token>\n\n\nclass PositionReader:\n\n def __init__(self):\n self.image_sub = rospy.Subscriber('/visp_auto_tracker/object_position',\n PoseStamped, self.callback)\n self.pub = rospy.Publisher('objec... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def twitter_auth():
consumer_key = 'IqsuEo5xfTdWwjD1GZNSA'
consumer_secret = 'dtYmqEekw53kia3MJhvDagdByWGxuTiqJfcdGkXw8A'
request_token_url = 'https://api.twitter.com/oauth/request_token'
access_token_url = 'http://api.twitter.com/oauth/access_token'
authorize_url = 'h... | flexible | {
"blob_id": "afa20d7e9c7843a03090c00cc888d44a77fc29f3",
"index": 9205,
"step-1": "<mask token>\n\n\ndef twitter_auth():\n consumer_key = 'IqsuEo5xfTdWwjD1GZNSA'\n consumer_secret = 'dtYmqEekw53kia3MJhvDagdByWGxuTiqJfcdGkXw8A'\n request_token_url = 'https://api.twitter.com/oauth/request_token'\n acces... | [
4,
6,
8,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if apiKey == '<your api key>' and sys.argv[1]:
apiKey = sys.argv[1]
<|reserved_special_token_0|>
print(json.dumps(r.json()))
<|reserved_special_token_0|>
print(r.json()['total'])
for i in np.arange(0, len(r.json()['rows'])):
... | flexible | {
"blob_id": "b4593b3229b88db26c5e200431d00838c357c8e0",
"index": 2359,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif apiKey == '<your api key>' and sys.argv[1]:\n apiKey = sys.argv[1]\n<mask token>\nprint(json.dumps(r.json()))\n<mask token>\nprint(r.json()['total'])\nfor i in np.arange(0, len(r.js... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
import math
from PIL import Image as Image
# NO ADDITIONAL IMPORTS ALLOWED!
def in_bound(dim , s):
"""Get inbound pixel coordinate for out-of-bound
Args:
dim (int): Image height or width
s (int): Coordinate
Returns:
int: Inbound
"""
if s <= -1:
... | normal | {
"blob_id": "591b1a2e245ae0f3c9b2a81769bbf5988574ed07",
"index": 8253,
"step-1": "<mask token>\n\n\ndef in_bound(dim, s):\n \"\"\"Get inbound pixel coordinate for out-of-bound\n\n Args:\n dim (int): Image height or width\n s (int): Coordinate \n\n Returns:\n int: Inbound\n \"\"\"... | [
8,
10,
13,
15,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DummyTriggerFactory(DjangoModelFactory):
class Meta:
model = DummyTrigger
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "813354c9c294c0323c1b54cda7074fbffa49cdb3",
"index": 442,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass DummyTriggerFactory(DjangoModelFactory):\n\n\n class Meta:\n model = DummyTrigger\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask tok... | [
0,
1,
2,
3
] |
from time import sleep
import requests
import json
import pymysql
db = pymysql.connect(host="localhost", user="root", password="root", db="xshop", port=33061)
def getCursor():
cursor = db.cursor()
return cursor
class Classify(object):
def __init__(self, **args):
self.cl_name = args['cl_name']
... | normal | {
"blob_id": "6d51a088ba81cfc64c2e2a03f98b0ee354eda654",
"index": 4292,
"step-1": "<mask token>\n\n\ndef getCursor():\n cursor = db.cursor()\n return cursor\n\n\nclass Classify(object):\n\n def __init__(self, **args):\n self.cl_name = args['cl_name']\n self.cl_grade = args['cl_grade'] is No... | [
7,
8,
9,
10,
12
] |
#Matthew Shrago
#implementation of bisection search.
import math
low = 0
high = 100
ans = int((high + low)/2)
print "Please think of a number between 0 and 100!"
while ans != 'c':
#print high, low
print "Is your secret number " + str(ans) + "?",
number = raw_input("Enter 'h' to indicate the guess is too hi... | normal | {
"blob_id": "39abda1dd8b35889405db1b3971917d2a34180e3",
"index": 6428,
"step-1": "#Matthew Shrago\n#implementation of bisection search.\nimport math\nlow = 0\nhigh = 100\nans = int((high + low)/2)\n\nprint \"Please think of a number between 0 and 100!\"\nwhile ans != 'c':\n #print high, low\n print \"Is yo... | [
0
] |
from django.apps import AppConfig
class BuyerSellerAppConfig(AppConfig):
name = 'buyer_seller_app'
| normal | {
"blob_id": "0b730314fef31e7304a8f5d8bb998581b021a610",
"index": 1798,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BuyerSellerAppConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BuyerSellerAppConfig(AppConfig):\n name = 'buyer_seller_app'\n",
"step-4": "from... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def write_video(fps, input_folder='output', video_name='video.mp4'):
fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')
video = cv2.VideoWriter(video_name, fourcc, fps, (1280, 720))
path = os.getcwd()
files = os... | flexible | {
"blob_id": "ca0c38cf2a55b2311a254b09cb693516c3d0ab10",
"index": 1763,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef write_video(fps, input_folder='output', video_name='video.mp4'):\n fourcc = cv2.VideoWriter_fourcc('m', 'p', '4', 'v')\n video = cv2.VideoWriter(video_name, fourcc, fps, (12... | [
0,
1,
2,
3,
4
] |
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