code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
# strspn(str1,str2)
str1 = '12345678'
str2 = '456'
# str1 and chars both in str1 and str2
print(str1 and str2)
str1 = 'cekjgdklab'
str2 = 'gka'
nPos = -1
for c in str1:
if c in str2:
nPos = str1.index(c)
break
print(nPos)
| normal | {
"blob_id": "5c30b0e952ddf2e05a7ad5f8d9bbd4f5e22f887d",
"index": 62,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(str1 and str2)\n<mask token>\nfor c in str1:\n if c in str2:\n nPos = str1.index(c)\n break\nprint(nPos)\n",
"step-3": "str1 = '12345678'\nstr2 = '456'\nprint(str1 ... | [
0,
1,
2,
3
] |
import datetime
import subprocess
from time import sleep
from flask import render_template, redirect, request, url_for, flash, abort
from dirkules import app, db, scheduler, app_version
import dirkules.manager.serviceManager as servMan
import dirkules.manager.driveManager as driveMan
import dirkules.manager.cleaning as... | normal | {
"blob_id": "ab27780b19db6854855af51eea063f07d9eb7302",
"index": 3553,
"step-1": "<mask token>\n\n\n@app.errorhandler(500)\ndef internal_server_error(e):\n return render_template('500.html', error=str(e))\n\n\n<mask token>\n\n\n@app.route('/pools', methods=['GET'])\ndef pools():\n return render_template('p... | [
5,
8,
9,
11,
13
] |
<|reserved_special_token_0|>
def prepare_dataset(dataset_path, json_path, n_mfcc=13, hop_length=512,
n_fft=2048):
data = {'mappings': [], 'labels': [], 'MFCCs': [], 'files': []}
for i, (dir_path, dir_names, filenames) in enumerate(os.walk(dataset_path)
):
if dir_path is not dataset_path:
... | flexible | {
"blob_id": "ba808d23f6a8226f40e1c214012a1535ee1e9e98",
"index": 2947,
"step-1": "<mask token>\n\n\ndef prepare_dataset(dataset_path, json_path, n_mfcc=13, hop_length=512,\n n_fft=2048):\n data = {'mappings': [], 'labels': [], 'MFCCs': [], 'files': []}\n for i, (dir_path, dir_names, filenames) in enumer... | [
1,
2,
3,
4,
5
] |
from setuptools import setup
import imp
def get_version():
ver_file = None
try:
ver_file, pathname, description = imp.find_module('__version__', ['cmakelint'])
vermod = imp.load_module('__version__', ver_file, pathname, description)
version = vermod.VERSION
return version
... | normal | {
"blob_id": "b3d9013ab6facb8dd9361e2a0715a8ed0cdfeaba",
"index": 342,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_version():\n ver_file = None\n try:\n ver_file, pathname, description = imp.find_module('__version__', [\n 'cmakelint'])\n vermod = imp.load_modu... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def sigmoid(x):
return expit(x)
def LRcost(t, pred):
pred[pred == 0.0] = 10 ** -10
cost_per_sample = -t * np.log(pred) - (1 - t) * np.log(1 - pred)
avg_cost = np.mean(cost_per_sample)
return avg_cost
def LRgradient_batch(X, y, pred):
m = X.shape[0]
grad = n... | flexible | {
"blob_id": "3accf1c066547c4939c104c36247370b4a260635",
"index": 8959,
"step-1": "<mask token>\n\n\ndef sigmoid(x):\n return expit(x)\n\n\ndef LRcost(t, pred):\n pred[pred == 0.0] = 10 ** -10\n cost_per_sample = -t * np.log(pred) - (1 - t) * np.log(1 - pred)\n avg_cost = np.mean(cost_per_sample)\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def hello():
print(_conf['greeting'])
print(_pkg_data)
print(_sys_data)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
try:
_sys_data = open(sys.prefix + '/data/data1.dat').read()
except Exception as exc:
print(exc)
_sys... | flexible | {
"blob_id": "4689ee7f7178cef16ac1f5375481a9ee8a48f924",
"index": 3780,
"step-1": "<mask token>\n\n\ndef hello():\n print(_conf['greeting'])\n print(_pkg_data)\n print(_sys_data)\n\n\n<mask token>\n",
"step-2": "<mask token>\ntry:\n _sys_data = open(sys.prefix + '/data/data1.dat').read()\nexcept Exc... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# -*- coding:utf-8 -*-
school = "Old boy"
def chang_name(name):
global school #声明全局变量
school = "Mage Linux"
print("Before change:", name, school)
name = 'Stack Cong'
age = 33
print("After change:", name)
print("School:", school)
name = "Stack"
chang_name(name)
print(na... | normal | {
"blob_id": "a9531fb020428e573d189c377652692e301ea4d3",
"index": 3026,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef chang_name(name):\n global school\n school = 'Mage Linux'\n print('Before change:', name, school)\n name = 'Stack Cong'\n age = 33\n print('After change:', name)... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def GetRadius(Ri, DV, mu):
def f(Rf):
return sqrt(mu / Ri) * (sqrt(2 * Rf / (Rf + Ri)) - 1) + sqrt(mu / Rf
) * (1 - sqrt(2 * Ri / (Rf + Ri))) - DV
return newton(f, Ri)
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "20722cf82371d176942e068e91b8fb38b4db61fd",
"index": 6951,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GetRadius(Ri, DV, mu):\n\n def f(Rf):\n return sqrt(mu / Ri) * (sqrt(2 * Rf / (Rf + Ri)) - 1) + sqrt(mu / Rf\n ) * (1 - sqrt(2 * Ri / (Rf + Ri))) - DV\n re... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SNS(email_service_interface.EmailService):
<|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 M... | flexible | {
"blob_id": "16dd73f2c85eff8d62cf0e605489d0db1616e36e",
"index": 8650,
"step-1": "<mask token>\n\n\nclass SNS(email_service_interface.EmailService):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass MockSNS(SNS):\n \"\"\"\n... | [
6,
12,
14,
15,
16
] |
<|reserved_special_token_0|>
class AsyncConsumer(AsyncWebsocketConsumer):
<|reserved_special_token_0|>
async def connect(self):
self.room_name = self.scope['url_route']['kwargs']['room_name']
self.room_group_name = 'chat_%s' % self.room_name
await self.channel_layer.group_add(self.roo... | flexible | {
"blob_id": "7955479c70de679cfb7575c8bd9208d00a4893df",
"index": 4979,
"step-1": "<mask token>\n\n\nclass AsyncConsumer(AsyncWebsocketConsumer):\n <mask token>\n\n async def connect(self):\n self.room_name = self.scope['url_route']['kwargs']['room_name']\n self.room_group_name = 'chat_%s' % s... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def main():
global device
args = parse_args()
cfg = Config.from_file(args.config)
out = cfg.train.out
if not os.path.exists(out):
os.makedirs(out)
cuda = torch.cuda.is_available()
if cuda and args.gpu >= 0:
print('# cuda available! #')
d... | flexible | {
"blob_id": "d6c06a465c36430e4f2d355450dc495061913d77",
"index": 5357,
"step-1": "<mask token>\n\n\ndef main():\n global device\n args = parse_args()\n cfg = Config.from_file(args.config)\n out = cfg.train.out\n if not os.path.exists(out):\n os.makedirs(out)\n cuda = torch.cuda.is_availa... | [
4,
6,
7,
8,
9
] |
#Exercício Python 055: Faça um programa que leia o peso de cinco pessoas. No final, mostre qual foi o maior e o menor peso lidos.
pessoas = int(input('Informe a quantidade de pessoas que deseja analisar: '))
peso = 0
maior = 0
menor = 0
for c in range(0, pessoas):
peso = float(input('Informe o peso: '))
if c ==... | normal | {
"blob_id": "78c71a4f3c4e8f24f0ae90555a3caf15f35332f6",
"index": 1774,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor c in range(0, pessoas):\n peso = float(input('Informe o peso: '))\n if c == 1:\n maior = peso\n menor = peso\n else:\n if peso > maior:\n maio... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Movie:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Movie:
def __init__(self, movieid, moviename, score, poster):
self.movieid = movieid
self.moviename = moviename
sel... | flexible | {
"blob_id": "856e62cf4cd443c7b3397e926f8fc4fece145f5b",
"index": 3447,
"step-1": "<mask token>\n",
"step-2": "class Movie:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Movie:\n\n def __init__(self, movieid, moviename, score, poster):\n self.movieid = movieid\n self.moviename = mo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Retrieving: ', url)
<|reserved_special_token_0|>
print('Retrieved', len(data), 'characters')
<|reserved_special_token_0|>
print('User count:', len(info['comments']))
<|reserved_special_token_0|>
for items in x:
y = item... | flexible | {
"blob_id": "cd175c236dd1d1c7387a21a491e80d6723f161dc",
"index": 7762,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Retrieving: ', url)\n<mask token>\nprint('Retrieved', len(data), 'characters')\n<mask token>\nprint('User count:', len(info['comments']))\n<mask token>\nfor items in x:\n y = it... | [
0,
1,
2,
3,
4
] |
from boxsdk import Client, OAuth2
import os
import sys
def ConfigObject(config_path):
"read a configuration file to retrieve access token"
configDict = {}
with open(config_path,'r') as config:
for line in config.readlines():
try:
configDict[line.split("=")[0]] = line.sp... | normal | {
"blob_id": "e76ebbe8dab2e5169ef40b559f783c49ba4de825",
"index": 1750,
"step-1": "<mask token>\n\n\ndef ConfigObject(config_path):\n \"\"\"read a configuration file to retrieve access token\"\"\"\n configDict = {}\n with open(config_path, 'r') as config:\n for line in config.readlines():\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_tensortuple():
a = torch.randn(3, 3), torch.randn(3, 3)
t = TensorTuple(a)
assert t[0].dtype == torch.float32
assert t.to(torch.int32)[0].dtype == torch.int32
<|reserved_special_token_1|>
<|reserved_s... | flexible | {
"blob_id": "c70b4ff26abe3d85e41bfc7a32cf6e1ce4c48d07",
"index": 6291,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_tensortuple():\n a = torch.randn(3, 3), torch.randn(3, 3)\n t = TensorTuple(a)\n assert t[0].dtype == torch.float32\n assert t.to(torch.int32)[0].dtype == torch.i... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class TimeUtils(object):
<|reserved_special_token_0|>
class StringUtils(object):
@staticmethod
def remove_emoji_from_string(text):
co = re.compile(u'[𐀀-\U0010ffff]')
return co.sub(u'', text)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cla... | flexible | {
"blob_id": "933f74e4fda0b30bdf70ff3f3dbde2383b10c694",
"index": 8773,
"step-1": "<mask token>\n\n\nclass TimeUtils(object):\n <mask token>\n\n\nclass StringUtils(object):\n\n @staticmethod\n def remove_emoji_from_string(text):\n co = re.compile(u'[𐀀-\\U0010ffff]')\n return co.sub(u'', te... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python
from setuptools import setup, find_packages
#if sys.argv[-1] == 'publish':
# os.system('python setup.py sdist upload')
# sys.exit()
with open('bace/__init__.py') as fid:
for line in fid:
if line.startswith('__version__'):
VERSION = line.strip().split()[-1][1:-1]
... | normal | {
"blob_id": "d28571214805df766c2cc2f45a6b5bea88d7ac18",
"index": 9371,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('bace/__init__.py') as fid:\n for line in fid:\n if line.startswith('__version__'):\n VERSION = line.strip().split()[-1][1:-1]\n break\nwith open... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def plotImage(f):
folder = 'C:/temp/'
im = imread(os.path.join(folder, f)).astype(np.float32) / 255
plt.imshow(im)
a = plt.gca()
a.get_xaxis().set_visible(False)
a.get_yaxis().set_visible(False)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reser... | flexible | {
"blob_id": "146db68fb84569b914fa741457c595108088dc63",
"index": 7199,
"step-1": "<mask token>\n\n\ndef plotImage(f):\n folder = 'C:/temp/'\n im = imread(os.path.join(folder, f)).astype(np.float32) / 255\n plt.imshow(im)\n a = plt.gca()\n a.get_xaxis().set_visible(False)\n a.get_yaxis().set_vis... | [
1,
2,
3,
4,
5
] |
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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def lambda_handler(event, context):
body = event
videoPath = str(body['videoPath'])
templatePath = str(body['templatePath'])
facePath = str(body['facePath'])
targetPeople = str(body['targetPeople'])
FACES... | flexible | {
"blob_id": "8c96c38a67c2eb97e30b325e4917ba4888731118",
"index": 7349,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef lambda_handler(event, context):\n body = event\n videoPath = str(body['videoPath'])\n templatePath = str(body['templatePath'])\n facePath = str(body['facePath'])\n ... | [
0,
1,
2,
3,
4
] |
"""""""""""""""
Write Data
"""""""""""""""
import json
from city import City
def load_json(file_name='data.json'):
with open(file_name, 'r') as json_fp:
json_data = json_fp.read()
data_arr = json.loads(json_data)
return data_arr
if __name__ == '__main__':
json_file = 'data.json'
... | normal | {
"blob_id": "63068a15d750abb29398d687495d6001ba17ab8a",
"index": 9435,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef load_json(file_name='data.json'):\n with open(file_name, 'r') as json_fp:\n json_data = json_fp.read()\n data_arr = json.loads(json_data)\n return data_arr... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Praktikum Programa Komputer ')
print('Exercise 7.21')
print('')
print('===========================')
print('Nama : Ivanindra Rizky P')
print('NIM : I0320054')
print('')
print('===========================')
print('')
<|reserved_special_token_0|>
print('... | flexible | {
"blob_id": "6b731e329eec3947a17ef8ee8280f2ddf980c81c",
"index": 7154,
"step-1": "<mask token>\n",
"step-2": "print('Praktikum Programa Komputer ')\nprint('Exercise 7.21')\nprint('')\nprint('===========================')\nprint('Nama : Ivanindra Rizky P')\nprint('NIM : I0320054')\nprint('')\nprint('===========... | [
0,
1,
2,
3,
4
] |
"""Class for better periodic call handling"""
import tornado
import tornado.gen
import logging
class YieldPeriodicCallback(object):
"""Class for better periodic call"""
def __init__(self, callback, callback_time, io_loop=None, faststart=False):
"""Init method it can be used like tornado periodic callb... | normal | {
"blob_id": "7726f8cc9adf15823cccdaa4ba316800bb134460",
"index": 1920,
"step-1": "<mask token>\n\n\nclass YieldPeriodicCallback(object):\n <mask token>\n\n def __init__(self, callback, callback_time, io_loop=None, faststart=False):\n \"\"\"Init method it can be used like tornado periodic callback, b... | [
5,
6,
7,
8,
9
] |
import argparse
from figure import Figure
from figure.Circle import Circle
from figure.Square import Square
class FCreator(object):
__types = ['square', 'circle']
def createParser(self, line: str):
parser = argparse.ArgumentParser()
parser.add_argument('-t', '--type', required=True, choices=... | normal | {
"blob_id": "086ee4de1d74654ef85bd0a169fdf49c8f52bef2",
"index": 3792,
"step-1": "<mask token>\n\n\nclass FCreator(object):\n <mask token>\n <mask token>\n\n def editParser(self, line: str):\n parser = argparse.ArgumentParser()\n parser.add_argument('-n', '--name', required=True)\n ... | [
5,
7,
8,
9,
12
] |
# Generated by Django 3.2 on 2021-04-20 13:08
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('excursions', '0003_auto_20210420_1608'),
]
operations = [
migrations.AlterField(
model_name='exscursion',
name='type',... | normal | {
"blob_id": "a048396019aa7603a20535a3ce4bc9770509097d",
"index": 2291,
"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 = [('excursions'... | [
0,
1,
2,
3,
4
] |
from .isearch import ISearcher
__all__ = ['ISearcher']
| normal | {
"blob_id": "13e2f474294edb7c78bd81456097d1389e6a0f1b",
"index": 5003,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['ISearcher']\n",
"step-3": "from .isearch import ISearcher\n__all__ = ['ISearcher']\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def dado(n):
i = 1
dos = 0
tres = 0
cuatro = 0
cinco = 0
seis = 0
siete = 0
ocho = 0
nueve = 0
diez = 0
once = 0
doce = 0
cont = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
while i <... | flexible | {
"blob_id": "2d0d73c0ea20d6736c10d5201abcfa9d561ef216",
"index": 7474,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef dado(n):\n i = 1\n dos = 0\n tres = 0\n cuatro = 0\n cinco = 0\n seis = 0\n siete = 0\n ocho = 0\n nueve = 0\n diez = 0\n once = 0\n doce = 0\n... | [
0,
1,
2,
3,
4
] |
from unittest import mock
import pytest
from lms.models import GroupInfo
from lms.services.group_info import GroupInfoService
from tests import factories
class TestGroupInfoService:
AUTHORITY = "TEST_AUTHORITY_PROVIDED_ID"
def test_upsert_group_info_adds_a_new_if_none_exists(self, db_session, svc, params):... | normal | {
"blob_id": "07452795a677836b89eef85b6fb25b33eb464d91",
"index": 1919,
"step-1": "<mask token>\n\n\nclass TestGroupInfoService:\n <mask token>\n\n def test_upsert_group_info_adds_a_new_if_none_exists(self, db_session,\n svc, params):\n course = factories.Course(authority_provided_id=self.AUTH... | [
7,
11,
13,
14,
15
] |
<|reserved_special_token_0|>
class WaypointUpdater(object):
def __init__(self):
rospy.init_node('waypoint_updater')
rospy.Subscriber('/current_pose', PoseStamped, self.pose_cb)
rospy.Subscriber('/base_waypoints', Lane, self.waypoints_cb)
rospy.Subscriber('/traffic_waypoint', Int32... | flexible | {
"blob_id": "9ad92b23b8a02204a86af599e507eb889e5bcec7",
"index": 7565,
"step-1": "<mask token>\n\n\nclass WaypointUpdater(object):\n\n def __init__(self):\n rospy.init_node('waypoint_updater')\n rospy.Subscriber('/current_pose', PoseStamped, self.pose_cb)\n rospy.Subscriber('/base_waypoin... | [
10,
15,
16,
17,
19
] |
from bs4 import BeautifulSoup
from bs4 import BeautifulSoup
import requests,pymysql,random,time
import http.cookiejar
from multiprocessing import Pool,Lock
def get_proxies_ip():
db = pymysql.connect("localhost","root","xxx","xxx",charset='utf8')
cursor = db.cursor()
sql = "SELECT * FROM proxies_info;"
... | normal | {
"blob_id": "d49aa03cd6b8ba94d68a1bc1e064f77fded65000",
"index": 8870,
"step-1": "<mask token>\n\n\ndef get_headers():\n USER_AGENTS = [\n 'Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1; AcooBrowser; .NET CLR 1.1.4322; .NET CLR 2.0.50727)'\n ,\n 'Mozilla/4.0 (compatible; MSIE 7.0... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class ThermalSpectrum(Spectrum):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@staticmethod
def units_string():
return '1/erg/cm^3'
def integrate(self, units=True, e_weight=0):
... | flexible | {
"blob_id": "8560c0068eff894e5aa1d0788bd9e5ad05c14997",
"index": 2262,
"step-1": "<mask token>\n\n\nclass ThermalSpectrum(Spectrum):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @staticmethod\n def units_string():\n return '1/erg/cm^3'\n\n def integrate(self, units=... | [
9,
12,
13,
14,
16
] |
<|reserved_special_token_0|>
class RegressionFitness(evo.Fitness):
<|reserved_special_token_0|>
def __init__(self, train_inputs, train_output, error_fitness,
handled_errors, stats: evo.utils.stats.Stats=None, store_bsfs: bool
=True, fitness_measure: evo.sr.ErrorMeasure=evo.sr.ErrorMeasure.R2)... | flexible | {
"blob_id": "e53d4bb853eb54e4dfedf7126480e2c3e1af1378",
"index": 2825,
"step-1": "<mask token>\n\n\nclass RegressionFitness(evo.Fitness):\n <mask token>\n\n def __init__(self, train_inputs, train_output, error_fitness,\n handled_errors, stats: evo.utils.stats.Stats=None, store_bsfs: bool\n =T... | [
5,
6,
7,
9,
11
] |
<|reserved_special_token_0|>
@celery_app.task(bind=True)
def debug_task(self):
print('Request: {0!r}'.format(self.request))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nightcrawler.settings')
<|reserved_special_token_0|>
celery_app.config_from_obje... | flexible | {
"blob_id": "d4bc6bfe6bef730273db38f3c99352bbc3f48a5f",
"index": 7604,
"step-1": "<mask token>\n\n\n@celery_app.task(bind=True)\ndef debug_task(self):\n print('Request: {0!r}'.format(self.request))\n",
"step-2": "<mask token>\nos.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nightcrawler.settings')\n<mask t... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ChatMessage(models.Model):
context = models.CharField(max_length=1000)
user = models.ForeignKey(User, on_delete=models.CASCADE)
chat = models.ForeignKey(Chat, on_delete=models.CASCADE)
timestamp = models.DateTimeField(auto_now_add=True)
def __str__(self):
... | flexible | {
"blob_id": "61179dc734069017adaabd53804ed0102d9416e3",
"index": 8865,
"step-1": "<mask token>\n\n\nclass ChatMessage(models.Model):\n context = models.CharField(max_length=1000)\n user = models.ForeignKey(User, on_delete=models.CASCADE)\n chat = models.ForeignKey(Chat, on_delete=models.CASCADE)\n ti... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "99154212d8d5fdb92cd972c727791158d09e3e2c",
"index": 3789,
"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 = [('civictechpr... | [
0,
1,
2,
3,
4
] |
from collections import defaultdict
class Graph:
def __init__(self):
self._graph = defaultdict(list)
self._odd_vertices = []
def add_vertex(self, v):
if not v in self._graph:
self._graph[v] = list()
def add_edge(self, v1, v2):
self._graph[v1].append(v2)
... | normal | {
"blob_id": "b4d412e8b45722a855a16dd64b7bce9b303d0ffe",
"index": 964,
"step-1": "<mask token>\n\n\nclass Graph:\n\n def __init__(self):\n self._graph = defaultdict(list)\n self._odd_vertices = []\n\n def add_vertex(self, v):\n if not v in self._graph:\n self._graph[v] = list... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
c1 = Print('HLT_HT550_HLT_HT250.pdf')
c1.open()
diffList = []
cumuList = []
histList = 'HT_Nom', 'HT_Denom'
dirs = ['HLT_HT550_v11_HLT_HT250_v11', 'HLT_HT550_v2_HLT_HT250_v2',
'HLT_HT5... | flexible | {
"blob_id": "e748420dfdb77fa8661111a92fc48b79f64bff10",
"index": 4128,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n c1 = Print('HLT_HT550_HLT_HT250.pdf')\n c1.open()\n diffList = []\n cumuList = []\n histList = 'HT_Nom', 'HT_Denom'\n dirs = ['HLT_HT550_v11_HLT_HT250_... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def guguPrint(n):
print('*' * 30)
for i in range(1, 10):
print('{} X {} = {}'.format(n, i, n * i))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def guguPrint(n):
print('*' * 30)
for i in range(1, 10):
print('{... | flexible | {
"blob_id": "aa2e24d80789f2a6ebd63ec42a17499f1e79ca49",
"index": 5237,
"step-1": "<mask token>\n",
"step-2": "def guguPrint(n):\n print('*' * 30)\n for i in range(1, 10):\n print('{} X {} = {}'.format(n, i, n * i))\n\n\n<mask token>\n",
"step-3": "def guguPrint(n):\n print('*' * 30)\n for ... | [
0,
1,
2,
3
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import os
# Describes where to search for the config file if no location is specified
DEFAULT_CONFIG_LOCATION = "config.json"
DEFAULT_CONFIG = {
"project": None,
"fixed_model_name": None,
"config": DEFAULT_CONFIG_LOCATION,
"data": None,
"emulate": None... | normal | {
"blob_id": "5c4c893caa19e58491e641420261bb70e7202cf0",
"index": 3566,
"step-1": "<mask token>\n\n\nclass AnnotatorConfig(object):\n <mask token>\n\n def __init__(self, filename=None):\n pass\n <mask token>\n\n def get(self, key, default=None):\n return self.__dict__.get(key, default)\n... | [
11,
13,
15,
16,
19
] |
import tensorflow as tf
from model import CabbageModel
import numpy as np
from krx import KrxCrawler
from naver_stock import StockModel as sm
from scattertest import scattertest as st
class CabbageController:
def __init__(self):
#def __init__(self, avg_temp, min_temp, max_temp, rain_fall):
#self._a... | normal | {
"blob_id": "90a220775efcc8ff9e83f1a1f011f424ddc3476d",
"index": 4487,
"step-1": "<mask token>\n\n\nclass CabbageController:\n <mask token>\n\n def service(self):\n X = tf.placeholder(tf.float32, shape=[None, 4])\n W = tf.Variable(tf.random_normal([4, 1]), name='weight')\n b = tf.Varia... | [
2,
3,
4,
5,
6
] |
# Copyright 2021 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from pants.backend.scala.goals.tailor import classify_source_files
from pants.backend.scala.target_types import (
ScalaJunitTestsGeneratorTarget,
ScalaSourcesGeneratorTarget,
... | normal | {
"blob_id": "42d2d8717ec2c25a99302e8de3090d600f8e80ff",
"index": 674,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_classify_source_files() ->None:\n scalatest_files = {'foo/bar/BazSpec.scala'}\n junit_files = {'foo/bar/BazTest.scala'}\n lib_files = {'foo/bar/Baz.scala'}\n asser... | [
0,
1,
2,
3
] |
import pymongo
myclient = pymongo.MongoClient('mongodb://localhost:27017/') #We create the database object
mydb = myclient['mydatabase'] #Create a database
mycol = mydb['customers'] #Create a collection into my mydatabase
mydict = [{"name": "Eric", "address": "Highway 37"}, {"name": "Albert", "address": "Highway 37... | normal | {
"blob_id": "6c6026a7ff0345c37e62de7c0aac0ee3bcde2c82",
"index": 5879,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(mydoc)\n",
"step-3": "<mask token>\nmyclient = pymongo.MongoClient('mongodb://localhost:27017/')\nmydb = myclient['mydatabase']\nmycol = mydb['customers']\nmydict = [{'name': 'Eri... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_pilatus_timestamp(timestamp_string):
if '.' in timestamp_string:
timestamp, milliseconds = timestamp_string.split('.')
else:
timestamp = timestamp_string
milliseconds = '000'
for forma... | flexible | {
"blob_id": "21526dabe8456c599e4409228fa69ffd0d672c5b",
"index": 4689,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_pilatus_timestamp(timestamp_string):\n if '.' in timestamp_string:\n timestamp, milliseconds = timestamp_string.split('.')\n else:\n timestamp = timestamp_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def storeInorder(root, inorder):
if root is None:
return
storeInorder(root.left, inorder)
inorder.append(root.data)
storeInorder(root.right, inorder)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def storeInorder(root... | flexible | {
"blob_id": "d2af2b25a1ba2db93c977a13fe0273919bc2e6e0",
"index": 7768,
"step-1": "<mask token>\n\n\ndef storeInorder(root, inorder):\n if root is None:\n return\n storeInorder(root.left, inorder)\n inorder.append(root.data)\n storeInorder(root.right, inorder)\n\n\n<mask token>\n",
"step-2": ... | [
1,
3,
4,
5,
6
] |
# 5.2 Training a convnet from scratch on a "small dataset" (p.131)
# Preprocessing (p.133)
# Copying images to train, validation and test directories
import os, shutil
# The path to the directory where the original dataset was uncompressed
original_dataset_dir = 'E:/train/'
# The directory where we will store our sma... | normal | {
"blob_id": "8340872f03c1bf7c1aee0c437258ac8e44e08bb8",
"index": 7313,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.mkdir(base_dir)\n<mask token>\nos.mkdir(train_dir)\n<mask token>\nos.mkdir(validation_dir)\n<mask token>\nos.mkdir(test_dir)\n<mask token>\nos.mkdir(train_cats_dir)\n<mask token>\nos.m... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "a4c4a5cc63c345d1fa8cbf426f7857a0f3d4357f",
"index": 8360,
"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 = [('FAQ', '0004... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mat_tissue.add_element('O', 0.079013)
mat_tissue.add_element('C', 0.32948)
mat_tissue.add_element('H', 0.546359)
mat_tissue.add_element('N', 0.008619)
mat_tissue.add_element('Mg', 0.036358)
mat_tissue.add_element('Cl', 0.000172)
m... | flexible | {
"blob_id": "28bf11cb4205dd186b84cc7b7c8b9009f35fe408",
"index": 7415,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmat_tissue.add_element('O', 0.079013)\nmat_tissue.add_element('C', 0.32948)\nmat_tissue.add_element('H', 0.546359)\nmat_tissue.add_element('N', 0.008619)\nmat_tissue.add_element('Mg', 0.0... | [
0,
1,
2,
3,
4
] |
from channels.generic.websocket import WebsocketConsumer, AsyncWebsocketConsumer
from asgiref.sync import async_to_sync
from channels.layers import get_channel_layer
import json
class AsyncConsumer(AsyncWebsocketConsumer):
chats = dict()
async def connect(self): # 连接时触发
self.room_name = self.scope... | normal | {
"blob_id": "7955479c70de679cfb7575c8bd9208d00a4893df",
"index": 4979,
"step-1": "<mask token>\n\n\nclass AsyncConsumer(AsyncWebsocketConsumer):\n <mask token>\n\n async def connect(self):\n self.room_name = self.scope['url_route']['kwargs']['room_name']\n self.room_group_name = 'chat_%s' % s... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def execute_file(input_fp, output_fp):
oie = OIE()
oie.extract_file(input_fp, output_fp)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def execute_file(input_fp, output_fp):
oie = OIE()
oie.extract_file(input_fp, output_fp)
... | flexible | {
"blob_id": "bc5e928305d82c92c10106fe1f69f5979d57e3d2",
"index": 5446,
"step-1": "<mask token>\n\n\ndef execute_file(input_fp, output_fp):\n oie = OIE()\n oie.extract_file(input_fp, output_fp)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef execute_file(input_fp, output_fp):\n oie = OIE()\n ... | [
1,
3,
4,
5,
6
] |
class Step:
def __init__(self, action):
self.action = action
def __str__(self) ->str:
return f'Step: {{action: {self.action.__str__()}}}'
def __repr__(self) ->str:
return f'Step: {{action: {self.action.__str__()}}}'
| normal | {
"blob_id": "9adff5da4e26088def9f0e32aa712a1f2b0336ba",
"index": 925,
"step-1": "class Step:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class Step:\n <mask token>\n <mask token>\n\n def __repr__(self) ->str:\n return f'Step: {{action: {self.action.__str__()}}}'\n",
"... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def combinacaoDeEmbralhamento(qtdeLinhas):
while True:
a = randint(0, qtdeLinhas)
b = randint(0, qtdeLinhas)
if a == b:
continue
else:
break
resp = [[a, b]]
return resp
def embaralhaMatriz(x):
for i in range(qtdeLin... | flexible | {
"blob_id": "28ed494939d0928bf3ad4f07f58186374e925426",
"index": 7024,
"step-1": "<mask token>\n\n\ndef combinacaoDeEmbralhamento(qtdeLinhas):\n while True:\n a = randint(0, qtdeLinhas)\n b = randint(0, qtdeLinhas)\n if a == b:\n continue\n else:\n break\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for ch in plainText:
ordvalue = ord(ch)
cipherValue = ordvalue + distance
if cipherValue > 127:
cipherValue = distance - (127 - ordvalue + 1)
code += chr(cipherValue)
print(code)
<|reserved_special_token_... | flexible | {
"blob_id": "bf98e81c160d13b79ebe9d6f0487b57ad64d1322",
"index": 7827,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor ch in plainText:\n ordvalue = ord(ch)\n cipherValue = ordvalue + distance\n if cipherValue > 127:\n cipherValue = distance - (127 - ordvalue + 1)\n code += chr(ciph... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class MipsVisitor:
<|reserved_special_token_0|>
def __init__(self, inherit_graph, output_file='mips_code.mips'):
self.inherit_graph, _ = inherit_graph
self.offset = dict()
self.type_index = []
self.dispatchtable_code = []
self.prototypes_co... | flexible | {
"blob_id": "63bc191a81a200d3c257de429c082cc8d13c98f4",
"index": 9952,
"step-1": "<mask token>\n\n\nclass MipsVisitor:\n <mask token>\n\n def __init__(self, inherit_graph, output_file='mips_code.mips'):\n self.inherit_graph, _ = inherit_graph\n self.offset = dict()\n self.type_index = ... | [
25,
31,
32,
48,
50
] |
x=input("Do you really want to run this program? (y/n) : ")
x=x.upper()
if x=="Y" or x=="N" or x=="Q":
while x=="Y" or x=="N" or x=="Q":
if x=="Q":
print("Exiting the Program")
import sys
sys.exit()
elif x=="N":
print("You decided to leave. See you ag... | normal | {
"blob_id": "7dff15a16ecc3ce3952f4b47290393ea3183807f",
"index": 4414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif x == 'Y' or x == 'N' or x == 'Q':\n while x == 'Y' or x == 'N' or x == 'Q':\n if x == 'Q':\n print('Exiting the Program')\n import sys\n sys.... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def readInputModel(txt, equivalentAxisFit, Settings):
psfwing_02pxscale_datatab = None
psfwing_logscale_datatab = None
componentslist = []
params = Parameters()
data = open(txt)
for line in data:
... | flexible | {
"blob_id": "219b22b6ad685fc316b1df02cc924a1cfec89f5b",
"index": 650,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef readInputModel(txt, equivalentAxisFit, Settings):\n psfwing_02pxscale_datatab = None\n psfwing_logscale_datatab = None\n componentslist = []\n params = Parameters()\n ... | [
0,
1,
2,
3
] |
"""
Implements Single Instance Learning SVM
From https://github.com/garydoranjr/misvm/blob/master/misvm/sil.py
Modified by Nicolas
"""
from __future__ import print_function, division
import numpy as np
import inspect
from sklearn.svm import LinearSVC as SVM
from milsvm.util import slices
class SIL(SVM):
"""
S... | normal | {
"blob_id": "f125269d5b52da41734ce94683139c44f0c4a66a",
"index": 3402,
"step-1": "<mask token>\n\n\nclass SIL(SVM):\n <mask token>\n <mask token>\n\n def fit(self, bags, y):\n \"\"\"\n @param bags : a sequence of n bags; each bag is an m-by-k array-like\n object contai... | [
3,
4,
7,
8,
10
] |
<|reserved_special_token_0|>
class OrderSuccessView(LoginRequiredMixin, View):
"""订单成功页面"""
def get(self, request):
"""提供订单成功页面"""
order_id = request.GET.get('order_id')
payment_amount = request.GET.get('payment_amount')
pay_method = request.GET.get('pay_method')
conte... | flexible | {
"blob_id": "0402096f215ae600318d17bc70e5e3067b0a176b",
"index": 3864,
"step-1": "<mask token>\n\n\nclass OrderSuccessView(LoginRequiredMixin, View):\n \"\"\"订单成功页面\"\"\"\n\n def get(self, request):\n \"\"\"提供订单成功页面\"\"\"\n order_id = request.GET.get('order_id')\n payment_amount = requ... | [
9,
16,
17,
19,
22
] |
<|reserved_special_token_0|>
def cumprod(arr, MOD):
L = len(arr)
Lsq = int(L ** 0.5 + 1)
arr = np.resize(arr, Lsq ** 2).reshape(Lsq, Lsq)
for n in range(1, Lsq):
arr[:, n] *= arr[:, n - 1]
arr[:, n] %= MOD
for n in range(1, Lsq):
arr[n] *= arr[n - 1, -1]
arr[n] %= M... | flexible | {
"blob_id": "43d5bf79f16e8530797cdd13cdfcc91f0d3aef5e",
"index": 8208,
"step-1": "<mask token>\n\n\ndef cumprod(arr, MOD):\n L = len(arr)\n Lsq = int(L ** 0.5 + 1)\n arr = np.resize(arr, Lsq ** 2).reshape(Lsq, Lsq)\n for n in range(1, Lsq):\n arr[:, n] *= arr[:, n - 1]\n arr[:, n] %= MO... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def isToeplitzMatrix(self, matrix: List[List[int]]) ->bool:
h = len(matrix)
w = len(matrix[0])
for curRow in range(h):
va... | flexible | {
"blob_id": "774f5d01cd274755626989c2b58bde68df349d8e",
"index": 5845,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def isToeplitzMatrix(self, matrix: List[List[int]]) ->bool:\n h = len(matrix)\n w = len(matrix[0])\n for c... | [
0,
1,
2,
3
] |
from django.db import models
from accounts.models import User
from cmdb.models.base import IDC
from cmdb.models.asset import Server, NetDevice
class CPU(models.Model):
# Intel(R) Xeon(R) Gold 5118 CPU @ 2.30GHz
version = models.CharField('型号版本', max_length=100, unique=True)
speed = models.PositiveSmallInt... | normal | {
"blob_id": "6bd423223e1ec2bb3a213158ac6da3a6483b531f",
"index": 4914,
"step-1": "<mask token>\n\n\nclass NetworkAdapter(models.Model):\n <mask token>\n <mask token>\n\n\n class Meta:\n db_table = 'cmdb_acc_network_adapter'\n verbose_name = u'配件网卡表'\n verbose_name_plural = u'配件网卡表'\... | [
15,
17,
18,
19,
27
] |
import subprocess
from dissamblerAbstract import disassemblerAbstract
#lib/ZydisDisasm -64 /home/nislab2/Desktop/DissamblerEffect/metamorphic/00fe0c08024f7db771d6711787d890a3.exe
class ZydisDisassembler(disassemblerAbstract):
def diassemble(self,filename, bits='32bit'):
"""
Disassembly executa... | normal | {
"blob_id": "fedec397ac0346bad1790315b4f85fbb1a662a4e",
"index": 9466,
"step-1": "<mask token>\n\n\nclass ZydisDisassembler(disassemblerAbstract):\n\n def diassemble(self, filename, bits='32bit'):\n \"\"\"\n Disassembly executable file return iterable instruction set.\n\n :param f... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class FaceRecognitionLib(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self):
sub_dirs = glob(FaceRecognitionLib.__data_set_dir + '/*/'... | flexible | {
"blob_id": "2d69a39be3931aa4c62cadff4cdfad76f6b32c59",
"index": 6473,
"step-1": "<mask token>\n\n\nclass FaceRecognitionLib(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self):\n sub_dirs = glob(FaceRecognitionLib.__data_set_dir + '... | [
3,
4,
5,
8,
9
] |
<|reserved_special_token_0|>
@test(depends_on_classes=[AfterConfigurationsCreation], groups=[tests.
DBAAS_API_CONFIGURATIONS])
class ListConfigurations(ConfigurationsTestBase):
@test
def test_configurations_list(self):
result = instance_info.dbaas.configurations.list()
for conf in result:... | flexible | {
"blob_id": "120021e44f6df9745db35ea2f38f25acecca9252",
"index": 3201,
"step-1": "<mask token>\n\n\n@test(depends_on_classes=[AfterConfigurationsCreation], groups=[tests.\n DBAAS_API_CONFIGURATIONS])\nclass ListConfigurations(ConfigurationsTestBase):\n\n @test\n def test_configurations_list(self):\n ... | [
29,
40,
43,
52,
53
] |
#classes that store values related to levels
from mg_cus_struct import *
from mg_movement import *
import copy
class BulletTemplate(object) :
def __init__(self, animationName, initialVelocity, hitbox) :
self._spawningCycle = 0
self._animationName = animationName
self._initialVelocity = init... | normal | {
"blob_id": "519746450826d02230a492a99e0b518602d53fcb",
"index": 9932,
"step-1": "<mask token>\n\n\nclass BulletSpawnerTemplate(object):\n <mask token>\n <mask token>\n\n def setRounds(self, rounds):\n self._rounds = rounds\n <mask token>\n\n def setInBetweenTimer(self, delay):\n sel... | [
16,
19,
22,
25,
26
] |
# -*- coding:utf-8 -*-
# Copyright 2015 NEC Corporation. #
# #
# Licensed under the Apache License, Version 2.0 (the "License"); #
# you may not use this file except in compliance with the License... | normal | {
"blob_id": "b220189d506737bf8cff9e600d1cfd4d7bc8435d",
"index": 1434,
"step-1": "# -*- coding:utf-8 -*-\n\n# Copyright 2015 NEC Corporation. #\n# #\n# Licensed under the Apache License, Version 2.0 ... | [
0
] |
# -*- coding: utf-8 -*-
from django.http import Http404
from django.shortcuts import render,render_to_response, get_object_or_404, redirect, HttpResponse
from django.core.context_processors import csrf
from django.views.decorators.csrf import csrf_protect, csrf_exempt
from django.template import RequestContext,Context... | normal | {
"blob_id": "fb16009985ee7fe4a467a94160f593723b5aaf03",
"index": 7964,
"step-1": "# -*- coding: utf-8 -*- \nfrom django.http import Http404\nfrom django.shortcuts import render,render_to_response, get_object_or_404, redirect, HttpResponse\nfrom django.core.context_processors import csrf\nfrom django.views.decora... | [
0
] |
<|reserved_special_token_0|>
def jsons_to_table(dir_jsons, dir_out, name, format='html'):
"""
Extracts the informations stored in the JSON files and stores creates an HTML-table for them.
:param dir_jsons: directory of JSON files
:param dir_out: output directory of the HTML-table
:param name: na... | flexible | {
"blob_id": "d6e836140b1f9c955711402111dc07e74b4a23b1",
"index": 1621,
"step-1": "<mask token>\n\n\ndef jsons_to_table(dir_jsons, dir_out, name, format='html'):\n \"\"\"\n Extracts the informations stored in the JSON files and stores creates an HTML-table for them.\n\n :param dir_jsons: directory of JS... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
# Part of Odoo. See LICENSE file for full copyright and licensing details.
import calendar as cal
import random
import pytz
from datetime import datetime, timedelta, time
from dateutil import rrule
from dateutil.relativedelta import relativedelta
from babel.dates import format_datetime
from od... | normal | {
"blob_id": "e03dfa0e02313c5478d4e97dcaf3bc27915bd878",
"index": 1421,
"step-1": "<mask token>\n\n\nclass CalendarAppointmentSlot(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 @api.constrains('hour')\n def ch... | [
7,
10,
12,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@login_required(login_url='/accounts/login/')
def postpoject(request):
if request.method == 'POST':
postform = PostForm(request.POST, request.FILES)
if postform.is_valid:
pro = postform.save(commi... | flexible | {
"blob_id": "67de51e2a176907fd89793bd3ec52f898130e104",
"index": 3713,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@login_required(login_url='/accounts/login/')\ndef postpoject(request):\n if request.method == 'POST':\n postform = PostForm(request.POST, request.FILES)\n if postfor... | [
0,
3,
4,
5,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_current_user(s: str=None, required=True):
"""
get current user by request auth header
:param s:
:return:
{'code': 'SUCCESS', 'nickName': 'gs1', 'appName': '__base__',
'tenantId': '650', 't... | flexible | {
"blob_id": "342063b37038c804c2afa78091b1f1c2facbc560",
"index": 3102,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_current_user(s: str=None, required=True):\n \"\"\"\n get current user by request auth header\n :param s:\n :return:\n {'code': 'SUCCESS', 'nickName': 'gs1',... | [
0,
1,
2,
3,
4
] |
import json
from logger import logger
def parse_json(text):
start = text.find("{")
end = text.find("}") + 1
try:
data = json.loads(text[start:end])
return data
except Exception:
logger.error("json解析失败：%s" % text)
| normal | {
"blob_id": "9f8fbfb8a9c849ca0e8881c479800c8e190e4a1c",
"index": 6485,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_json(text):\n start = text.find('{')\n end = text.find('}') + 1\n try:\n data = json.loads(text[start:end])\n return data\n except Exception:\n ... | [
0,
1,
2,
3
] |
#!c:\Python\python.exe
# Fig 35.16: fig35_16.py
# Program to display CGI environment variables
import os
import cgi
print "Content-type: text/html"
print
print """<!DOCTYPE html PUBLIC
"-//W3C//DTD XHTML 1.0 Transitional//EN"
"DTD/xhtml1-transitional.dtd">"""
print """
<html xmlns = "http://www... | normal | {
"blob_id": "61b28088e4344d8a94006e5c04c189a44bbb6ff3",
"index": 3334,
"step-1": "#!c:\\Python\\python.exe\r\n# Fig 35.16: fig35_16.py\r\n# Program to display CGI environment variables\r\n\r\nimport os\r\nimport cgi\r\n\r\nprint \"Content-type: text/html\"\r\nprint\r\n\r\nprint \"\"\"<!DOCTYPE html PUBLIC\r\n ... | [
0
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright 2020-2021 by Murray Altheim. All rights reserved. This file is part
# of the Robot Operating System project, released under the MIT License. Please
# see the LICENSE file included as part of this package.
#
# author: Murray Altheim
# created: 2020-04-15
# ... | normal | {
"blob_id": "3a6038cb80548b98fc7e4a328092f1dc1ffd6dfd",
"index": 1154,
"step-1": "<mask token>\n\n\nclass ConfigLoader:\n <mask token>\n\n def __init__(self, level):\n self._log = Logger('configloader', level)\n self._log.info('ready.')\n\n def configure(self, filename='config.yaml'):\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Board:
<|reserved_special_token_0|>
def draw_squares(self, win):
win.fill(GREY)
for row in range(ROWS):
for col in range(row % 2, COLS, 2):
pygame.draw.rect(win, WHITE, (row * SQUARE_SIZE, col *
SQUARE_SIZE, SQ... | flexible | {
"blob_id": "b80b997f802c7ed4f0a838030703a314f2383c9d",
"index": 5226,
"step-1": "<mask token>\n\n\nclass Board:\n <mask token>\n\n def draw_squares(self, win):\n win.fill(GREY)\n for row in range(ROWS):\n for col in range(row % 2, COLS, 2):\n pygame.draw.rect(win, W... | [
8,
9,
11,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
"""Файл, который запускается при python qtester
""" | flexible | {
"blob_id": "90fc6590dab51141124ca73082b8d937008ae782",
"index": 7400,
"step-1": "<mask token>\n",
"step-2": "\"\"\"Файл, который запускается при python qtester\n\"\"\"",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
#!/usr/bin/python
"""
Starter code for exploring the Enron dataset (emails + finances);
loads up the dataset (pickled dict of dicts).
The dataset has the form:
enron_data["LASTNAME FIRSTNAME MIDDLEINITIAL"] = { features_dict }
{features_dict} is a dictionary of features associated with that pers... | normal | {
"blob_id": "c5d224a3d63d0d67bc7a48fecec156cca41cdcf7",
"index": 5129,
"step-1": "#!/usr/bin/python\n\n\"\"\" \n Starter code for exploring the Enron dataset (emails + finances);\n loads up the dataset (pickled dict of dicts).\n\n The dataset has the form:\n enron_data[\"LASTNAME FIRSTNAME MIDDLEINIT... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if len(s) < 26:
for i in range(26):
c = chr(ord('a') + i)
if c not in s:
print(s + c)
exit()
else:
for i in reversed(range(1, 26)):
if s[i - 1] < s[i]:
s1 = s[0:i... | flexible | {
"blob_id": "9931fc25118981bcce80cffd3fda9dc99d951bf5",
"index": 180,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(s) < 26:\n for i in range(26):\n c = chr(ord('a') + i)\n if c not in s:\n print(s + c)\n exit()\nelse:\n for i in reversed(range(1, 26)):\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('admin/', admin.site.urls), path('api/', include(
'api.urls')), path('api/adv/', include('adventure.urls'))]
<|reserved_special_token_1|>
from django.contrib import admin
from django.urls import path, in... | flexible | {
"blob_id": "a14114f9bb677601e6d75a72b84ec128fc9bbe61",
"index": 71,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('admin/', admin.site.urls), path('api/', include(\n 'api.urls')), path('api/adv/', include('adventure.urls'))]\n",
"step-3": "from django.contrib import admin\nfrom... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def saveDatadic(file_path, name, dataset):
np.save(file_path + name + '_x', dataset['x'])
np.save(file_path + name + '_t', dataset['t'])
np.save(file_path + name + '_e', dataset['e'])
<|reserved_special_token_0|>
def encoder_z(mu_logvar, epsilon=None):
mu, logvar = tf.... | flexible | {
"blob_id": "ebebdb0e79e9d78b818dab3f93d130ccddd2914e",
"index": 1185,
"step-1": "<mask token>\n\n\ndef saveDatadic(file_path, name, dataset):\n np.save(file_path + name + '_x', dataset['x'])\n np.save(file_path + name + '_t', dataset['t'])\n np.save(file_path + name + '_e', dataset['e'])\n\n\n<mask tok... | [
7,
10,
14,
17,
18
] |
class Solution:
def validIPAddress(self, IP):
"""
:type IP: str
:rtype: str
"""
def validateIPv4(IP):
digits = IP.split('.')
if len(digits) != 4:
return False
for digitstr in digits:
if len(digitstr)... | normal | {
"blob_id": "6216a5e45fee8ade5ec9072c42c1b08f3b0f4c65",
"index": 2433,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def validIPAddress(self, IP):\n \"\"\"\n :type IP: str\n :rtype: str\n \"\"\"\n\n def valida... | [
0,
1,
2,
3
] |
from collections import deque
def safeInsert(graph,left,right):
if left not in graph:
graph[left] = {}
graph[left][right] = True
if right not in graph:
graph[right] = {}
graph[right][left] = True
def trace(graph,start,end):
queue = deque([start])
pred = {start:None}
while len(queue)>0:
cur = queue.poplef... | normal | {
"blob_id": "3f655a12ac45c152215949d3d8bdb71147eeb849",
"index": 3651,
"step-1": "from collections import deque\n\ndef safeInsert(graph,left,right):\n\tif left not in graph:\n\t\tgraph[left] = {}\n\tgraph[left][right] = True\n\tif right not in graph:\n\t\tgraph[right] = {}\n\tgraph[right][left] = True\n\ndef tra... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def check_is_with_singleton(physical_line, line_number):
match_obj = IS_WITH_SINGLETON_REGEX.search(physical_line)
if match_obj is not None:
offset = match_obj.span()[0]
return 0, 12, (line_number, offset... | flexible | {
"blob_id": "cf6d3a0fbf2a2daf8432622f780e138784ec505d",
"index": 8300,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef check_is_with_singleton(physical_line, line_number):\n match_obj = IS_WITH_SINGLETON_REGEX.search(physical_line)\n if match_obj is not None:\n offset = match_obj.span... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python3
import sys
import math
class parameter :
opt = 0
xp = 0
yp = 0
zp = 0
xv = 0
yv = 0
zv = 0
p = 0
def check_args() :
try :
int(sys.argv[1])
int(sys.argv[2])
int(sys.argv[3])
int(sys.argv[4])
int(sys.argv[5])
int(sys... | normal | {
"blob_id": "d1af148bc6b27d38052f2e57f1c610c86eccebef",
"index": 7757,
"step-1": "<mask token>\n\n\nclass parameter:\n opt = 0\n xp = 0\n yp = 0\n zp = 0\n xv = 0\n yv = 0\n zv = 0\n p = 0\n\n\n<mask token>\n\n\ndef help():\n if len(sys.argv) == 2 and sys.argv[1] == '-h':\n prin... | [
5,
7,
8,
11,
12
] |
"""
@version:
author:yunnaidan
@time: 2019/07/22
@file: download_mseed.py
@function:
"""
from obspy.clients.fdsn import Client
from obspy.core import UTCDateTime
import numpy as np
import obspy
import os
import re
import time
import glob
import shutil
import platform
import subprocess
import multiprocessing
def load_... | normal | {
"blob_id": "34db3c9998e1d7647dd954e82e18147504cc74fc",
"index": 6736,
"step-1": "<mask token>\n\n\ndef load_stations(filename):\n with open(filename, 'r') as f:\n sta_data = f.readlines()\n sta_list = []\n for l in range(1, len(sta_data)):\n sta_info = sta_data[l]\n net_name = re.s... | [
3,
5,
6,
7,
9
] |
from tracking.centroidtracker import CentroidTracker
from tracking.trackableobject import TrackableObject
import tensornets as nets
import cv2
import numpy as np
import time
import dlib
import tensorflow.compat.v1 as tf
import os
# For 'disable_v2_behavior' see https://github.com/theislab/scgen/issues/14
tf.disable_v2... | normal | {
"blob_id": "7b01e81c3e31e0a315ee01f36bf1b1f7384a9d10",
"index": 3597,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntf.disable_v2_behavior()\n<mask token>\nprint('Loading video {video_path}...'.format(video_path=video_path))\nif not os.path.exists(video_path):\n print('File does not exist. Exited.')... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns.append(path('sub/', include(
'sandbox.staticpages_testapp.sub_urls')))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
staticpages_loader = StaticpagesLoader()
urlpatterns = [path('admin/', admin.site.... | flexible | {
"blob_id": "333914f99face050376e4713ca118f2347e50018",
"index": 989,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns.append(path('sub/', include(\n 'sandbox.staticpages_testapp.sub_urls')))\n",
"step-3": "<mask token>\nstaticpages_loader = StaticpagesLoader()\nurlpatterns = [path('admin/... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while num <= 100:
if num % 4 == 0 and num % 6 == 0:
print(num)
break
num += 1
<|reserved_special_token_1|>
num = 1
while num <= 100:
if num % 4 == 0 and num % 6 == 0:
print(num)
break... | flexible | {
"blob_id": "d04506e67071abf36d43a828d90fbe0f14230103",
"index": 3208,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile num <= 100:\n if num % 4 == 0 and num % 6 == 0:\n print(num)\n break\n num += 1\n",
"step-3": "num = 1\nwhile num <= 100:\n if num % 4 == 0 and num % 6 == 0... | [
0,
1,
2,
3
] |
import packaging.requirements
import pydantic
import pytest
from prefect.software.pip import PipRequirement, current_environment_requirements
class TestPipRequirement:
def is_packaging_subclass(self):
r = PipRequirement("prefect")
assert isinstance(r, packaging.requirements.Requirement)
def ... | normal | {
"blob_id": "64366e8532ffe05db7e7b7313e1d573c78a4e030",
"index": 796,
"step-1": "<mask token>\n\n\nclass TestPipRequirement:\n\n def is_packaging_subclass(self):\n r = PipRequirement('prefect')\n assert isinstance(r, packaging.requirements.Requirement)\n\n def test_can_be_used_in_pydantic_mod... | [
6,
7,
8,
10,
11
] |
# Error using ncdump - NetCDF4 Python
ncdump -h filename
| normal | {
"blob_id": "12f0eeeb81fe611d88e33fd2e8df407e289fb582",
"index": 1255,
"step-1": "# Error using ncdump - NetCDF4 Python\nncdump -h filename\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
from models.bearing_registry import BearingRegistry
from models.faction import Faction
from models.maneuver import Maneuver
import time
class Activation:
"""
This class represents the Activation phase of a turn
"""
def __init__(self, game):
"""
Constructor
game: Th... | normal | {
"blob_id": "0774bad4082e0eb04ae3f7aa898c0376147e9779",
"index": 2645,
"step-1": "<mask token>\n\n\nclass Activation:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Activation:\n <mask token>\n\n def __init__(self, game):\n \"\"\"\n Constructor\... | [
1,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 14 22:09:56 2014
@author: duhan
"""
#arrayMapPath = r'/usr/local/lib/python2.7/dist-packages/ticketpitcher/data/3'
arrayMapPath = r'C:\Python27\Lib\site-packages\ticketpitcher\data'
#tempPath = r'/tmp/'
tempPath = 'd:\\temp\\'
| normal | {
"blob_id": "9627e8a468d3a75787c5a9e01856913fc8beb3c4",
"index": 1868,
"step-1": "<mask token>\n",
"step-2": "<mask token>\narrayMapPath = 'C:\\\\Python27\\\\Lib\\\\site-packages\\\\ticketpitcher\\\\data'\ntempPath = 'd:\\\\temp\\\\'\n",
"step-3": "# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Nov 14 22:09... | [
0,
1,
2
] |
lista = [x for x in range(11)] ##todo: wazne
kwadraty = [i**2 for i in lista]
kwadraty = [(i, i**2, i**3) for i in range(-10, 11)]
zbior_wyr = {'aa', '1233', '111111'}
slownik = {i : len(i)for i in zbior_wyr}
print(kwadraty, slownik, sep='\n') | normal | {
"blob_id": "248b9b9d613f71e0130353f0792083b7d3f6ccd6",
"index": 7000,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(kwadraty, slownik, sep='\\n')\n",
"step-3": "lista = [x for x in range(11)]\nkwadraty = [(i ** 2) for i in lista]\nkwadraty = [(i, i ** 2, i ** 3) for i in range(-10, 11)]\nzbior_... | [
0,
1,
2,
3
] |
from pythonforandroid.recipe import CompiledComponentsPythonRecipe
from multiprocessing import cpu_count
from os.path import join
class NumpyRecipe(CompiledComponentsPythonRecipe):
version = '1.18.1'
url = 'https://pypi.python.org/packages/source/n/numpy/numpy-{version}.zip'
site_packages_name = 'numpy'
... | normal | {
"blob_id": "610610e7e49fc98927a4894efe62686e26e0cb83",
"index": 3502,
"step-1": "<mask token>\n\n\nclass NumpyRecipe(CompiledComponentsPythonRecipe):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def build_compiled_components(self, arch):\n ... | [
3,
4,
5,
6,
7
] |
import os.path
import numpy as np
import matplotlib.pyplot as plt
import util
import collections
def learn_distributions(file_lists_by_category):
"""
Estimate the parameters p_d, and q_d from the training set
Input
-----
file_lists_by_category: A two-element list. The first element is a list of
... | normal | {
"blob_id": "7ed84706ace2cbf523021887df1e13d113f9ce4c",
"index": 4172,
"step-1": "<mask token>\n\n\ndef learn_distributions(file_lists_by_category):\n \"\"\"\n Estimate the parameters p_d, and q_d from the training set\n\n Input\n -----\n file_lists_by_category: A two-element list. The first eleme... | [
1,
2,
3,
4,
5
] |
class Rectangulo:
<|reserved_special_token_0|>
def calcular_area(self):
return self.base * self.altura
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Rectangulo:
def __init__(self, base, altura):
self.base = base
self.altura = altura
def calcular_area(sel... | flexible | {
"blob_id": "2e60781da004fb86d3a33deae970c1faf2a5037d",
"index": 5793,
"step-1": "class Rectangulo:\n <mask token>\n\n def calcular_area(self):\n return self.base * self.altura\n\n\n<mask token>\n",
"step-2": "class Rectangulo:\n\n def __init__(self, base, altura):\n self.base = base\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class QuestionVectorTask(luigi.Task):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def output(self):
return luigi.LocalTarget('./cache/question_distance/%s.npy' % self.
dataset)
<|reserved_special_token_0|>... | flexible | {
"blob_id": "ae6a6f7622bf98c094879efb1b9362a915a051b8",
"index": 1175,
"step-1": "<mask token>\n\n\nclass QuestionVectorTask(luigi.Task):\n <mask token>\n <mask token>\n <mask token>\n\n def output(self):\n return luigi.LocalTarget('./cache/question_distance/%s.npy' % self.\n datase... | [
7,
8,
11,
12,
13
] |
import sys
import time
from PyQt5.QtGui import *
from PyQt5.QtCore import *
from PyQt5.QtWidgets import *
from PyQt5 import *
class PromptMessage(QWidget):
def __init__(self, parent = None):
super(PromptMessage,self).__init__(parent)
self.m_show_tm = QTimer()
self.m_stay_tm = QTimer()
... | normal | {
"blob_id": "18a49d46b39fe6e00e2ad137984cceab82f1e94b",
"index": 2422,
"step-1": "<mask token>\n\n\nclass PromptMessage(QWidget):\n <mask token>\n <mask token>\n <mask token>\n\n def on_move(self):\n self.m_desktop_height = self.m_desktop_height - 10\n self.move(self.m_point.x(), self.m... | [
2,
4,
6,
7,
10
] |
##############################################
# Binary Tree #
# by Vishal Nirmal #
# #
# A Binary Tree ADT implementation. #
##############################################
class BinaryTree:
def __init_... | normal | {
"blob_id": "3eaced9609c7adfa5457d7dcad8b2dfaeb697b16",
"index": 3220,
"step-1": "class BinaryTree:\n\n def __init__(self, data=None):\n self.data = data\n self.left = None\n self.right = None\n\n def insert(self, data):\n if self.data != None:\n arr = [self]\n ... | [
12,
15,
18,
19,
22
] |
import simple_map
import pickle
import os
import argparse
import cv2
argparser = argparse.ArgumentParser()
argparser.add_argument("--src", type=str, required=True,
help="source directory")
argparser.add_argument("--dst", type=str, required=True,
help="destination directory")
ar... | normal | {
"blob_id": "a8c59f97501b3f9db30c98e334dbfcffffe7accd",
"index": 6557,
"step-1": "<mask token>\n\n\ndef get_reference():\n json = sorted([os.path.join(args.ref, file) for file in os.listdir(args\n .ref) if file.endswith('.json')])[0]\n smap = simple_map.SimpleMap(json)\n return smap.northing, sma... | [
2,
3,
5,
6,
7
] |
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