code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from codar.cheetah import Campaign
from codar.cheetah import parameters as p
from codar.savanna.machines import SummitNode
import copy
def get_shared_node_layout (n_writers, n_readers):
nc = SummitNode()
for i in range(n_writers):
nc.cpu[i] = "writer:{}".format(i)
for i in range(n_readers):
... | normal | {
"blob_id": "475cc5130e847b1a74a33bfa5cbc202a6bf31621",
"index": 6932,
"step-1": "<mask token>\n\n\ndef get_sweeps(ref_params_d, n_writers):\n params_d = copy.deepcopy(ref_params_d)\n params_d['writer']['nprocs'].values = [n_writers]\n params_d['writer']['decomposition'].values = [n_writers]\n all_di... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
@csrf_exempt
def login_form(request):
formulario = '<form action="login" method="POST">'
formulario += 'Nombre<br><input type="text" name="Usuario"><br>'
formulario += 'Contraseña<br><input type="password" name="Password"><br>'
formulario += '<br><input type="submit" value... | flexible | {
"blob_id": "e982fd5bed540b836fd4e2caaec033d8cbfb0e4f",
"index": 9854,
"step-1": "<mask token>\n\n\n@csrf_exempt\ndef login_form(request):\n formulario = '<form action=\"login\" method=\"POST\">'\n formulario += 'Nombre<br><input type=\"text\" name=\"Usuario\"><br>'\n formulario += 'Contraseña<br><input... | [
8,
12,
13,
14,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def fuzzy_match(pattern, instring, adj_bonus=5, sep_bonus=10, camel_bonus=
10, lead_penalty=-3, max_lead_penalty=-9, unmatched_penalty=-1):
"""Return match boolean and match score.
:param pattern: the pattern to be ... | flexible | {
"blob_id": "576bb15ad081cd368265c98875be5d032cdafd22",
"index": 4789,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fuzzy_match(pattern, instring, adj_bonus=5, sep_bonus=10, camel_bonus=\n 10, lead_penalty=-3, max_lead_penalty=-9, unmatched_penalty=-1):\n \"\"\"Return match boolean and ma... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for game in raw_scores:
game_len = len(game) + 1
total = 0
prev = None
player = 1
max_so_far = -100
min_so_far = 100
max_drop = 0
max_gain = 0
white_improve = [0]
black_improve = [0]
gam... | flexible | {
"blob_id": "ad9bb34fdb05ab885f4871693729449f3618603a",
"index": 8321,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor game in raw_scores:\n game_len = len(game) + 1\n total = 0\n prev = None\n player = 1\n max_so_far = -100\n min_so_far = 100\n max_drop = 0\n max_gain = 0\n ... | [
0,
1,
2,
3,
4
] |
import io
from flask import Flask, send_file
app = Flask(__name__)
@app.route('/')
def index():
buf = io.BytesIO()
buf.write('hello world')
buf.seek(0)
return send_file(buf,
attachment_filename="testing.txt",
as_attachment=True)
| normal | {
"blob_id": "362c4e572f0fe61b77e54ab5608d4cd052291da4",
"index": 4043,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n buf = io.BytesIO()\n buf.write('hello world')\n buf.seek(0)\n return send_file(buf, attachment_filename='testing.txt', as_attachment=True\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Apigee(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Apigee(object):
<|reserved_special_token_0|>
def __init__(self, org_name, username, password):
self.proxies = Proxi... | flexible | {
"blob_id": "656927013d9a0254e2bc4cdf05b7cfd5947feb05",
"index": 7868,
"step-1": "<mask token>\n\n\nclass Apigee(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Apigee(object):\n <mask token>\n\n def __init__(self, org_name, username, password):\n self.proxies =... | [
1,
2,
3,
4
] |
from collections import Counter
from copy import deepcopy
from itertools import count
from traceback import print_exc
#https://www.websudoku.com/?level=4
class SudukoBoard:
side=3
sz=side*side
class Cell:
def __init__(self,board,row,col):
self._values= [None] * SudukoBoard.sz
... | normal | {
"blob_id": "44d9e628e31cdb36088b969da2f6e9af1b1d3efe",
"index": 7841,
"step-1": "<mask token>\n\n\nclass SudukoBoard:\n <mask token>\n <mask token>\n\n\n class Cell:\n\n def __init__(self, board, row, col):\n self._values = [None] * SudukoBoard.sz\n self._value = None\n ... | [
6,
8,
9,
10,
11
] |
"""The prediction classes. Instances of the class are returned by
the recommender.
"""
class RelationshipPrediction(object):
"""The prediction of the predicted_relationship appearing between
the given subject-object pair.
@type subject: the domain-specific subject
@ivar subject: the subject
... | normal | {
"blob_id": "c3de9e6129bcafd863cd330ac281345fb563cc8c",
"index": 6259,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass RelationshipPrediction(object):\n <mask token>\n <mask token>\n\n def __unicode__(self):\n return u'%s <- %s: %f, %s' % (self.subject, self.object_, self.\n ... | [
0,
2,
3,
4,
6
] |
#8
def matrix(m):
for i in range(len(m)):
for j in range (len(m[0])):
m[i][j]=(m[i][j])**2
a=[[1,2,3],[4,5,6],[8,9,0]]
print('The matrix is ',a)
matrix(a)
print('The updated matrix is ',a)
| normal | {
"blob_id": "f46dd5217c8e015546d7fff7ee52569ecc2c8e41",
"index": 5487,
"step-1": "<mask token>\n",
"step-2": "def matrix(m):\n for i in range(len(m)):\n for j in range(len(m[0])):\n m[i][j] = m[i][j] ** 2\n\n\n<mask token>\n",
"step-3": "def matrix(m):\n for i in range(len(m)):\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
plastiqpublicapi
This file was automatically generated by APIMATIC v3.0 (
https://www.apimatic.io ).
"""
import json
import dateutil.parser
from tests.controllers.controller_test_base import ControllerTestBase
from tests.test_helper import TestHelper
from tests.http_respon... | normal | {
"blob_id": "a4f2418e746cc43bd407b6a212de9802044351e1",
"index": 3928,
"step-1": "<mask token>\n\n\nclass CategoriesControllerTests(ControllerTestBase):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CategoriesControllerTests(ControllerTestBase):\n\n @classmethod\n def setUpCl... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
logging.basicConfig(level=logging.INFO, datefmt='%Y/%m/%d %H:%M:%S', format
='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
<|reserved_special_token_0|>
@cron_wait
async def verify_error_proxy_task():
logger.inf... | flexible | {
"blob_id": "1d529e2ea5526ddcda0d0da30ed8ed4724002c63",
"index": 7074,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(level=logging.INFO, datefmt='%Y/%m/%d %H:%M:%S', format\n ='%(asctime)s - %(name)s - %(levelname)s - %(message)s')\n<mask token>\n\n\n@cron_wait\nasync def verify_e... | [
0,
1,
2,
3,
4
] |
# operatorTest02.py
x = 5
x += 3 #복함 대입 연산자
print("x : ", x)
print("-"*30)
total = 0
total += 1
total | normal | {
"blob_id": "4f8bc19bb113c9eac7c2ac774ac7b16f569d9704",
"index": 3083,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nx += 3\nprint('x : ', x)\nprint('-' * 30)\n<mask token>\ntotal += 1\ntotal\n",
"step-3": "x = 5\nx += 3\nprint('x : ', x)\nprint('-' * 30)\ntotal = 0\ntotal += 1\ntotal\n",
"step-4": ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(f'Selamat datang di Game Tebak angka')
while nyawa > limit:
print(f'Percobaan anda tersisa {nyawa}')
jawaban = int(input('Masukkan angka 0-10 = '))
if jawaban == angka_rahasia:
print('Anda Benar')
... | flexible | {
"blob_id": "d4b01b015723950a4d8c3453d736cd64f306d27b",
"index": 2940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(f'Selamat datang di Game Tebak angka')\nwhile nyawa > limit:\n print(f'Percobaan anda tersisa {nyawa}')\n jawaban = int(input('Masukkan angka 0-10 = '))\n if jawaban == ang... | [
0,
1,
2,
3,
4
] |
users = {
'Students': [
{'first_name': 'Michael', 'last_name' : 'Jordan'},
{'first_name' : 'John', 'last_name' : 'Rosales'},
{'first_name' : 'Mark', 'last_name' : 'Guillen'},
{'first_name' : 'KB', 'last_name' : 'Tonel'}
],
'Instructors': [
{'first_name' : 'Michael', 'last_name' : 'Choi'},
... | normal | {
"blob_id": "c0f4f9eef12d99d286f5ad56f6554c5910b7cc71",
"index": 8356,
"step-1": "users = {\n 'Students': [\n {'first_name': 'Michael', 'last_name' : 'Jordan'},\n {'first_name' : 'John', 'last_name' : 'Rosales'},\n {'first_name' : 'Mark', 'last_name' : 'Guillen'},\n {'first_name' : 'KB', 'last_n... | [
0
] |
<|reserved_special_token_0|>
class BaseEncoder(nn.Module):
<|reserved_special_token_0|>
def __init__(self, **kwargs):
if len(kwargs) > 0:
raise RuntimeError('Unrecognized options: {}'.format(', '.join(
kwargs.keys())))
super(BaseEncoder, self).__init__()
<|rese... | flexible | {
"blob_id": "86ee2300b5270df3dadb22f2cfea626e6556e5db",
"index": 9951,
"step-1": "<mask token>\n\n\nclass BaseEncoder(nn.Module):\n <mask token>\n\n def __init__(self, **kwargs):\n if len(kwargs) > 0:\n raise RuntimeError('Unrecognized options: {}'.format(', '.join(\n kwarg... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Root(object):
<|reserved_special_token_0|>
def __init__(self, request):
pass
<|reserved_special_token_1|>
__author__ = 'anderson'
<|reserved_special_token_0|>
class Root(object):
__acl__ = [(Allow... | flexible | {
"blob_id": "5ee2a51ea981f0feab688d9c571620a95d89a422",
"index": 6980,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Root(object):\n <mask token>\n\n def __init__(self, request):\n pass\n",
"step-3": "__author__ = 'anderson'\n<mask token>\n\n\nclass Root(object):\n __acl__ = ... | [
0,
2,
4,
5,
6
] |
<|reserved_special_token_0|>
class Cart(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|>
<|reserved_special_token_0|>... | flexible | {
"blob_id": "ae0ccbb9b0a2c61d9ee9615ba8d0c1a186a81c34",
"index": 3177,
"step-1": "<mask token>\n\n\nclass Cart(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n ... | [
6,
8,
9,
11,
12
] |
<|reserved_special_token_0|>
class BlockwiseLayer(object):
<|reserved_special_token_0|>
def __init__(self, parent):
"""
Initialize a Blockwise Layer.
:type parent: coapserver.CoAP
:param parent: the CoAP server
"""
self._parent = parent
def handle_request... | flexible | {
"blob_id": "70d740a7003ca3f2d2cde039b2fc470ef2165e77",
"index": 7078,
"step-1": "<mask token>\n\n\nclass BlockwiseLayer(object):\n <mask token>\n\n def __init__(self, parent):\n \"\"\"\n Initialize a Blockwise Layer.\n\n :type parent: coapserver.CoAP\n :param parent: the CoAP s... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(getal1 * getal2 + getal3)
print(getal1 * (getal2 + getal3))
print(getal2 + getal3 / getal1)
print((getal2 + getal3) / getal1)
print(getal2 + getal3 % getal1)
print(abs(getal4 * getal1))
print(pow(getal3, getal5))
print(round... | flexible | {
"blob_id": "30d75aafd9612ac02557b947fc4e3c2f7322a7fd",
"index": 3555,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(getal1 * getal2 + getal3)\nprint(getal1 * (getal2 + getal3))\nprint(getal2 + getal3 / getal1)\nprint((getal2 + getal3) / getal1)\nprint(getal2 + getal3 % getal1)\nprint(abs(getal4 *... | [
0,
1,
2,
3
] |
#! /usr/bin/python3
from scapy.all import *
import sys
ip=IP(src=sys.argv[1], dst=sys.argv[2])
syn_packet = TCP(sport=52255, dport=1237, flags="S", seq=100, options=[('MSS',689),('WScale',1)])
synack_packet = sr1(ip/syn_packet)
my_ack = synack_packet.seq+1
ack_packet = TCP(sport=52255, dport=1237, flags="A", seq=101,... | normal | {
"blob_id": "acd6197e60cf59ffcaa33bb50a60a03592bb3559",
"index": 7169,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsend(ip / ack_packet)\n",
"step-3": "<mask token>\nip = IP(src=sys.argv[1], dst=sys.argv[2])\nsyn_packet = TCP(sport=52255, dport=1237, flags='S', seq=100, options=[(\n 'MSS', 689), ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def ex51():
with urllib.request.urlopen(TIME_URL) as response:
body = response.read()
parsed = json.loads(body)
date = datetime.fromisoformat(parsed['currentTime'])
stamp = date.strftime('%H:%M:%S %Z %B %m %d')
print('The current time is %s' % stamp)
<|reserv... | flexible | {
"blob_id": "e8f05a66c642ef3b570130a2996ca27efb8b0cb5",
"index": 5287,
"step-1": "<mask token>\n\n\ndef ex51():\n with urllib.request.urlopen(TIME_URL) as response:\n body = response.read()\n parsed = json.loads(body)\n date = datetime.fromisoformat(parsed['currentTime'])\n stamp = date.strfti... | [
1,
2,
3,
4,
5
] |
import secrets
from pathlib import Path
HASHCAT_WPA_CACHE_DIR = Path.home() / ".hashcat" / "wpa-server"
ROOT_PRIVATE_DIR = Path(__file__).parent.parent
WORDLISTS_DIR = ROOT_PRIVATE_DIR / "wordlists"
WORDLISTS_USER_DIR = HASHCAT_WPA_CACHE_DIR / "wordlists" # user custom wordlists
RULES_DIR = ROOT_PRIVATE_DIR / "rules... | normal | {
"blob_id": "20d480517226cb7fbced765554a02fa5cbc29033",
"index": 6491,
"step-1": "<mask token>\n\n\nclass Config:\n \"\"\" Flask application config \"\"\"\n SECRET_KEY = secrets.token_bytes(64)\n SQLALCHEMY_DATABASE_URI = 'sqlite:///{}'.format(DATABASE_PATH)\n SQLALCHEMY_TRACK_MODIFICATIONS = False\n... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get():
market = 'Premium'
url = 'https://coinpremiums.herokuapp.com/json'
try:
result = ''
premiums = requests.get(url).json()
for exchange, exchange_currencies in premiums['premium'].item... | flexible | {
"blob_id": "b5581be044013df9ff812f285f99ca67c4f96a62",
"index": 2927,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get():\n market = 'Premium'\n url = 'https://coinpremiums.herokuapp.com/json'\n try:\n result = ''\n premiums = requests.get(url).json()\n for exchan... | [
0,
1,
2,
3
] |
# =============>This is a Normal mathematical tasks<==========
x = 7
x = 7 // 3 # rounds the number = 2 ans class int
#x = 7 / 3 # gives the floating number = 2.33333335 ans class float
#x = 7 % 3 # gives the reminder = 1 ans class int
#print("x is {}" .format(x))
#print(type(x))
# ================>This is how to ... | normal | {
"blob_id": "62a7958ba5ebb6da866d6ef156e52136df22f235",
"index": 107,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('x is {}'.format(x))\nprint(type(x))\n<mask token>\nprint('x is {}'.format(x))\nprint(type(x))\n",
"step-3": "x = 7\nx = 7 // 3\n<mask token>\nx = 0.1 + 0.1 + 0.1 - 0.3\nprint('x i... | [
0,
1,
2,
3,
4
] |
# Generated by Django 2.1.3 on 2020-06-05 23:06
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('index', '0005_userip_serial_number'),
]
operations = [
migrations.AddField(
model_name='userip',
name='ip_attributio... | normal | {
"blob_id": "a90db2073d43d54cbcc04e3000e5d0f2a2da4a55",
"index": 5281,
"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 = [('index', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def fence_decipher(m: str, key: int) ->str:
chunklens = [(0) for _ in range(key)]
nfence = 0
dx = 1
for i in m:
chunklens[nfence] += 1
nfence += dx
if dx == 1 and nfence == key - 1:
... | flexible | {
"blob_id": "a8bed0b5a6a95d67b5602b395f1d0ea12cd53fb0",
"index": 9166,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fence_decipher(m: str, key: int) ->str:\n chunklens = [(0) for _ in range(key)]\n nfence = 0\n dx = 1\n for i in m:\n chunklens[nfence] += 1\n nfence += ... | [
0,
1,
2,
3,
4
] |
from bs4 import BeautifulSoup
from aiounfurl.parsers import oembed
def test_oembed_not_match(oembed_providers):
oembed_url_extractor = oembed.OEmbedURLExtractor(oembed_providers)
url = 'http://test.com'
assert oembed_url_extractor.get_oembed_url(url) is None
def test_oembed_founded(oembed_providers):
... | normal | {
"blob_id": "7b2ad0b4eca7b31b314e32ad57d51be82f0eaf61",
"index": 6979,
"step-1": "<mask token>\n\n\ndef test_oembed_founded(oembed_providers):\n oembed_url_extractor = oembed.OEmbedURLExtractor(oembed_providers)\n url = 'https://www.instagram.com/p/BNHh2YJDdcY/'\n oembed_url = oembed_url_extractor.get_o... | [
2,
3,
4,
5
] |
from django.db import models
from django.utils import timezone
from django.contrib.auth.models import User, Group
# Create your models here.
def default_expiration():
return timezone.now() + timezone.timedelta(days=10)
class Category(models.Model):
name = models.CharField(max_length=200)
description = ... | normal | {
"blob_id": "33b6a4c76079ed698809b29772abb59a34831472",
"index": 5900,
"step-1": "<mask token>\n\n\nclass Survey(models.Model):\n name = models.CharField(max_length=200)\n description = models.TextField()\n category = models.ForeignKey(Category, blank=True, null=True, on_delete\n =models.CASCADE)... | [
16,
17,
18,
19,
22
] |
<|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": "d0a053faccecddc84a9556aec3dff691b171df96",
"index": 9977,
"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 = [('event', '00... | [
0,
1,
2,
3,
4
] |
'''
Project Euler
Problem #41 - Pandigital prime
David 07/06/2017
'''
import time
import math
maxPandigitalPrime = 2
def isPrime(num):
if(num<=1):
return False
elif(num==2):
return True
elif(num%2==0):
return False
else:
sqrt_num = math.sqrt(num)
bound = int(... | normal | {
"blob_id": "7ca7693b842700a7b15242b656648e8a7e58cd23",
"index": 1691,
"step-1": "<mask token>\n\n\ndef isPrime(num):\n if num <= 1:\n return False\n elif num == 2:\n return True\n elif num % 2 == 0:\n return False\n else:\n sqrt_num = math.sqrt(num)\n bound = int(s... | [
2,
3,
4,
5,
6
] |
primos = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37]
# números entre (8 - 26) e (44 - 44)
intervalo = list(range(8, 27)) + list(range(49, 50))
is_magic = []
for n in primos:
quadrado = n ** 2
if quadrado in intervalo:
is_magic.append(quadrado)
print(len(is_magic)) # 3 | normal | {
"blob_id": "b7f443521e165f327aae9ff5d7bbb7b8462abeb5",
"index": 2890,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor n in primos:\n quadrado = n ** 2\n if quadrado in intervalo:\n is_magic.append(quadrado)\nprint(len(is_magic))\n",
"step-3": "primos = [2, 3, 5, 7, 11, 13, 17, 19, 23, ... | [
0,
1,
2,
3
] |
from django.shortcuts import render, redirect
from django.contrib.auth import authenticate, logout, login
from django.contrib import messages
from django.contrib.auth.decorators import login_required
from django.utils.decorators import method_decorator
from django.views import View
class login_view(View):
template... | normal | {
"blob_id": "e4e2e8ca65d109805b267f148e8d255d81d4ee83",
"index": 1801,
"step-1": "<mask token>\n\n\nclass logout_view(View):\n\n def get(self, request):\n logout(request)\n return redirect('adminbiobses:login')\n\n\n@method_decorator(login_required, name='dispatch')\nclass index(View):\n temp... | [
5,
6,
7,
8,
11
] |
from django.db.models import Q, Avg
from django.http import JsonResponse
from rest_framework import permissions
from rest_framework.authtoken.models import Token
from rest_framework.authtoken.views import ObtainAuthToken
from rest_framework.decorators import action
from rest_framework.response import Response
from rest... | normal | {
"blob_id": "9e8b5cebd48b3b98e421c896d9835ada5ec4166e",
"index": 2740,
"step-1": "<mask token>\n\n\nclass RestaurantViewSet(ModelViewSet):\n serializer_class = RestaurantSerializer\n permission_classes = [permissions.IsAuthenticatedOrReadOnly]\n queryset = Restaurant.objects.all()\n\n def _get_recomm... | [
34,
40,
41,
42,
56
] |
import Tkinter
import random
secret = random.randint(1, 100)
### TKINTER ELEMENTS ###
window = Tkinter.Tk()
# greeting text
greeting = Tkinter.Label(window, text="Guess the secret number!")
greeting.pack()
# guess entry field
guess = Tkinter.Entry(window)
guess.pack()
# submit button
submit = Tkinter.Button(windo... | normal | {
"blob_id": "59eb705d6d388de9afbcc0df3003f4d4f45f1fbd",
"index": 3989,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngreeting.pack()\n<mask token>\nguess.pack()\n<mask token>\nsubmit.pack()\nwindow.mainloop()\n",
"step-3": "<mask token>\nsecret = random.randint(1, 100)\nwindow = Tkinter.Tk()\ngreeting... | [
0,
1,
2,
3,
4
] |
#Write by Jess.S 25/1/2019
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
plt.rcParams['font.sans-serif'] = ['FangSong'] # 指定默认字体
plt.rcParams['axes.unicode_minus'] = False # 解决保存图像是负号'-'显示为方块的问题
def draw_point(x,y):
plt.scatter(x, y)
plt.title('点分布图')#显示图表标题
plt.xlabel(... | normal | {
"blob_id": "1c60620814a4aea2573caf99cee87590a8d57c18",
"index": 5483,
"step-1": "<mask token>\n\n\ndef draw_point(x, y):\n plt.scatter(x, y)\n plt.title('点分布图')\n plt.xlabel('x轴')\n plt.ylabel('y轴')\n plt.grid(True)\n plt.show()\n\n\ndef draw_route(route_list, x, y):\n plt.scatter(x, y)\n ... | [
5,
6,
7,
8,
9
] |
from pyecharts import options as opts
from pyecharts.charts import *
import pandas as pd
import namemap
from pyecharts.globals import ThemeType
#
import time
import json
import requests
from datetime import datetime
import pandas as pd
import numpy as np
def read_country_code():
"""
获取... | normal | {
"blob_id": "fe3584dd858c06d66215b4a182adf87d35324975",
"index": 4486,
"step-1": "<mask token>\n\n\ndef read_country_code():\n \"\"\"\n 获取国家中英文字典\n :return:\n \"\"\"\n country_dict = {}\n for key, val in namemap.nameMap.items():\n country_dict[val] = key\n return country_dict\n\n\ndef... | [
6,
7,
8,
9,
10
] |
import sys
sys.path.append('/usr/local/anaconda3/lib/python3.6/site-packages')
from numpy import sin, linspace
x = linspace(0, 4, 101)
y = sin(x)
from numpy import sin, linspace
plt.grid()
plt.xlabel('x')
plt.ylabel('f(x)')
plt.title('Funkcija $sin(x)$ un tās izvitzījums rindā')
plt.plot(x, y2)
plt.plot(x, y2, color ... | normal | {
"blob_id": "1dcea61908753777604d99235407981e89c3b9d4",
"index": 4452,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('/usr/local/anaconda3/lib/python3.6/site-packages')\n<mask token>\nplt.grid()\nplt.xlabel('x')\nplt.ylabel('f(x)')\nplt.title('Funkcija $sin(x)$ un tās izvitzījums rindā')... | [
0,
1,
2,
3,
4
] |
import json
import unittest
from pathlib import Path
from deepdiff import DeepDiff
from electricitymap.contrib import config
CONFIG_DIR = Path(__file__).parent.parent.joinpath("config").resolve()
class ConfigTestcase(unittest.TestCase):
def test_generate_zone_neighbours_two_countries(self):
exchanges =... | normal | {
"blob_id": "22b8ecfecc0e76d758f14dea865a426db56c6343",
"index": 3538,
"step-1": "<mask token>\n\n\nclass ConfigTestcase(unittest.TestCase):\n <mask token>\n\n def test_generate_zone_neighbours_one_country_one_subzone(self):\n exchanges = {'DE->SE-SE4': {'parsers': {'exchange': 'source'}}}\n ... | [
7,
8,
10,
11,
12
] |
# -*- coding: utf-8 -*-
"""TODO
"""
import logging
import numpy
import evo.gp.support
import evo.sr
import evo.utils.stats
class RegressionFitness(evo.Fitness):
LOG = logging.getLogger(__name__ + '.RegressionFitness')
def __init__(self, train_inputs, train_output, error_fitness,
handled_e... | normal | {
"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
] |
' a test module '
__author__ = 'Aaron Jiang'
import sys
def test():
args = sys.argv
if len(args) == 1:
print('Hello World')
elif len(args) == 2:
print('Hello, %s!' % args[1])
else:
print('TOO MANY ARGUMENTS!')
if __name__ == '__main__':
test()
class Test():
count =... | normal | {
"blob_id": "ececcf40005054e26e21152bcb5e68a1bce33e88",
"index": 7947,
"step-1": "<mask token>\n\n\nclass Test:\n <mask token>\n print('called ', count)\n <mask token>\n\n\n<mask token>\n\n\nclass Screen:\n\n @property\n def width(self):\n return self._width\n\n @width.setter\n def wi... | [
12,
14,
15,
17,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
path_clusters = snakemake.input[0]
path_clusters = '/'.join(path_clusters.split('/')[:-1]) + '/'
merge_vcf = snakemake.output[0]
ref_genome = snakemake.params[0]
regions = snakemake.p... | flexible | {
"blob_id": "f6d81387f61ac4150cd6279121780b7113517b1e",
"index": 2860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n path_clusters = snakemake.input[0]\n path_clusters = '/'.join(path_clusters.split('/')[:-1]) + '/'\n merge_vcf = snakemake.output[0]\n ref_genome ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
DEBUG = True
SQLALCHEMY_DATABASE_URI = (
'postgresql://username:password@IPOrDomain/databasename')
SQLALCHEMY_TRACK_MODIFICATIONS = True
DATABASE_CONNECT_OPTIONS = {}
THREADS_PER_PAGE = 2
<|reserved_special_token_1|>
DEBUG = True
SQLALCHEMY_DATABASE_UR... | flexible | {
"blob_id": "a1b0e72b62abc89d5292f199ec5b6193b544e271",
"index": 7813,
"step-1": "<mask token>\n",
"step-2": "DEBUG = True\nSQLALCHEMY_DATABASE_URI = (\n 'postgresql://username:password@IPOrDomain/databasename')\nSQLALCHEMY_TRACK_MODIFICATIONS = True\nDATABASE_CONNECT_OPTIONS = {}\nTHREADS_PER_PAGE = 2\n",
... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def sort_position_data(pos, type='A'):
"""Sorts the position data according to player positions.
As the final matrix should contain the player according to their
position starting from left to right from back to front the indexed
ragged array list should be sorted such th... | flexible | {
"blob_id": "81ae5bbc8e3e712ee4f54656bc28f385a0b4a29f",
"index": 6059,
"step-1": "<mask token>\n\n\ndef sort_position_data(pos, type='A'):\n \"\"\"Sorts the position data according to player positions.\n\n As the final matrix should contain the player according to their\n position starting from left to ... | [
5,
8,
9,
10,
11
] |
from .proxies import Proxies
from .roles import Roles
from .products import Products
from .resourcefiles import ResourceFiles
class Apigee(object):
"""Provides easy access to all endpoint classes
Args:
domain (str): Your Auth0 domain, e.g: 'username.auth0.com'
token (str): Management API v2 ... | normal | {
"blob_id": "656927013d9a0254e2bc4cdf05b7cfd5947feb05",
"index": 7868,
"step-1": "<mask token>\n\n\nclass Apigee(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Apigee(object):\n <mask token>\n\n def __init__(self, org_name, username, password):\n self.proxies =... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class NGram(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@abc.abstractmethod
def load_text(self, text):
pass
def load_ngram(self):
counts = self.empty_count()
c = self.n
while c < len(self.text):
l = s... | flexible | {
"blob_id": "41e3c18b02f9d80f987d09227da1fbc6bde0ed1d",
"index": 4812,
"step-1": "<mask token>\n\n\nclass NGram(object):\n <mask token>\n <mask token>\n\n @abc.abstractmethod\n def load_text(self, text):\n pass\n\n def load_ngram(self):\n counts = self.empty_count()\n c = self... | [
7,
9,
11,
13,
15
] |
from .base import *
import os
SECRET_KEY = os.environ['SECRET_KEY']
ALLOWED_HOSTS = ['demo.pythonic.nl']
DEBUG = False
| normal | {
"blob_id": "e5607d9893b775b216d1790897124a673b190c26",
"index": 2085,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nSECRET_KEY = os.environ['SECRET_KEY']\nALLOWED_HOSTS = ['demo.pythonic.nl']\nDEBUG = False\n",
"step-3": "from .base import *\nimport os\nSECRET_KEY = os.environ['SECRET_KEY']\nALLOWED_... | [
0,
1,
2
] |
import fs
gInfo = {
'obj': g2.go(capUrl),
'Headers-C-T': g2.response.headers['Content-Type'],
'url': g2.response.url,
'urlDetails': g2.response.url_details()
}
capHtml = capHtml = gInfo['obj'].unicode_body(ignore_errors=True, fix_special_entities=True)
b64cap = re.findall(r'base64,(.*?)\\" id=', capHtml, re.DO... | normal | {
"blob_id": "2a5f69fbb26bd1f94c10ff0da687391bf5bd3c23",
"index": 6054,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsavecaptcha.write(b64cap[0])\nsavecaptcha.close()\n<mask token>\nf.close()\n<mask token>\nfincapfile.close()\n",
"step-3": "<mask token>\ngInfo = {'obj': g2.go(capUrl), 'Headers-C-T': g... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
TEST_HEAD = """
>>>>>>
>>>>>> Test in progress: {0}
>>>>>>"""
TEST_TAIL = '>>>>>> Test execution done, tearDown\n\r'
<|reserved_special_token_1|>
"""
ConstantsCommands.py
"""
TEST_HEAD = "\n >>>>>> " \
"\n >>>>... | flexible | {
"blob_id": "45f0a7a78184195a593061d863ff2114abe01a46",
"index": 6321,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nTEST_HEAD = \"\"\"\n >>>>>> \n >>>>>> Test in progress: {0}\n >>>>>>\"\"\"\nTEST_TAIL = '>>>>>> Test execution done, tearDown\\n\\r'\n",
"step-3": "\"\"\"\nConstantsCommands.py\n\"\"\"\... | [
0,
1,
2
] |
<|reserved_special_token_0|>
@task(max_retries=2, retry_delay=datetime.timedelta(seconds=5))
def pull_forecast(city, api_key):
"""
Extract the 5-day 3-hour forecast for the provided City.
"""
base_url = 'http://api.openweathermap.org/data/2.5/forecast?'
url = base_url + 'appid=' + api_key + '&q=' ... | flexible | {
"blob_id": "7f52354487f85a0bf1783c8aa76f228ef17e6d6b",
"index": 5119,
"step-1": "<mask token>\n\n\n@task(max_retries=2, retry_delay=datetime.timedelta(seconds=5))\ndef pull_forecast(city, api_key):\n \"\"\"\n Extract the 5-day 3-hour forecast for the provided City.\n \"\"\"\n base_url = 'http://api.... | [
2,
3,
4,
5,
6
] |
# import gmplot package
import gmplot
import numpy as np
# generate 700 random lats and lons
latitude = (np.random.random_sample(size = 700) - 0.5) * 180
longitude = (np.random.random_sample(size = 700) - 0.5) * 360
# declare the center of the map, and how much we want the map zoomed in
gmap = gmplot.GoogleMapPlotter(0... | normal | {
"blob_id": "1cc77ed1c5da025d1b539df202bbd3310a174eac",
"index": 3902,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngmap.heatmap(latitude, longitude)\ngmap.scatter(latitude, longitude, c='r', marker=True)\n<mask token>\ngmap.draw('c:\\\\users\\\\jackc\\\\desktop\\\\country_heatmap.html')\n<mask token>\... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.2 on 2016-10-14 19:37
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
... | normal | {
"blob_id": "8c05259ce577e6b6a6efdf778832e9bb817e47fd",
"index": 1414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [migrations.sw... | [
0,
1,
2,
3,
4
] |
"""
SUMMARY
Auxiliary functions, provided here to avoid clutter
"""
"""
Transforms a point (P = [x, y]) using the x, y intervals (Δxy = [Δx, Δy]) into the corresponding discrete point (D = [xd, yd])
loc_min = [x_min, y_min]
"""
def discretize_location(P, loc_min, Δxy):
x_from_start = P[0] - loc_min[0]
y_from... | normal | {
"blob_id": "8bbc929e2ff2321b97195031fa675fbdab269fcb",
"index": 3288,
"step-1": "<mask token>\n\n\ndef first_append_to_last(arr):\n return arr + [arr[0]]\n\n\n<mask token>\n\n\ndef RMS(arr):\n n = len(arr)\n sq_sum = sum(a ** 2 for a in arr)\n return (sq_sum / n) ** 0.5\n\n\n<mask token>\n\n\ndef L1... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def lexicalOrder(self, n):
"""
:type n: int
:rtype: List[int]
"""
ac... | flexible | {
"blob_id": "79f4ede16628c6fbf37dfb4fe5afb8489c120f5a",
"index": 6597,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n <mask token>\n",
"step-3": "class Solution(object):\n\n def lexicalOrder(self, n):\n \"\"\"\n :type n: int\n :rtype: List[int]\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class B:
<|reserved_special_token_0|>
class C(B, A):
print('class C')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class A:
<|reserved_special_token_0|>
class B:
def m(self):
print('Class B')
class C(B, A):
print('class C')
<|reserved... | flexible | {
"blob_id": "3d59b8d6a34935ff332028443276f161430a981c",
"index": 9687,
"step-1": "<mask token>\n\n\nclass B:\n <mask token>\n\n\nclass C(B, A):\n print('class C')\n\n\n<mask token>\n",
"step-2": "class A:\n <mask token>\n\n\nclass B:\n\n def m(self):\n print('Class B')\n\n\nclass C(B, A):\n ... | [
2,
4,
6,
7,
8
] |
from django.apps import AppConfig
class TimestechConfig(AppConfig):
name = 'TimesTech'
| normal | {
"blob_id": "94f50e371ef65e86d0d2d40a3ed16946f8811be3",
"index": 2601,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TimestechConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TimestechConfig(AppConfig):\n name = 'TimesTech'\n",
"step-4": "from django.apps impo... | [
0,
1,
2,
3
] |
import numpy as np
import pandas as pd
import time
from sklearn.metrics import log_loss
from keras.models import Sequential, Model
from keras.layers import Dense, Input
from keras.layers import Dropout
from keras.layers import Flatten
from keras.layers import LSTM
from keras.layers.convolutional import Convolution3D
f... | normal | {
"blob_id": "e3d886dedaf5b120392d0dc81c4c71398f08f8d6",
"index": 8234,
"step-1": "<mask token>\n\n\ndef base_model():\n input_shape = 1, HM_SLICES, IMG_PX_SIZE, IMG_PX_SIZE\n inputs = Input(shape=input_shape)\n conv1 = Convolution3D(32, 5, 5, 5, activation='relu')(inputs)\n drop1 = Dropout(0.2)(conv1... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
import ludwig.schema.decoders.base
import ludwig.schema.decoders.sequence_decoders
<|reserved_special_token_1|>
# Register all decoders
import ludwig.schema.decoders.base
import ludwig.schema.decoders.sequence_decoders # noqa
| flexible | {
"blob_id": "53509d826b82211bac02ea5f545802007b06781c",
"index": 1630,
"step-1": "<mask token>\n",
"step-2": "import ludwig.schema.decoders.base\nimport ludwig.schema.decoders.sequence_decoders\n",
"step-3": "# Register all decoders\nimport ludwig.schema.decoders.base\nimport ludwig.schema.decoders.sequence_... | [
0,
1,
2
] |
__author__ = 'Or'
| normal | {
"blob_id": "54c1b294d826deb43978591cad590c5e969bebd7",
"index": 6655,
"step-1": "<mask token>\n",
"step-2": "__author__ = 'Or'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def haversine(pt1, pt2):
"""
INPUT: tuples (lon1, lat1), (lon2, lat2)
OUTPUT: The great circle distance between two points
on the earth (specified in decimal degrees)
"""
lon1, lat1, lon2, lat2 = map(radians, [pt1[0], pt1[1], pt2[0], pt2[1]])
dlon = lon2 - lon... | flexible | {
"blob_id": "89ce3d3ec9691ab8f54cc0d9d008e06c65b5f2cc",
"index": 7847,
"step-1": "<mask token>\n\n\ndef haversine(pt1, pt2):\n \"\"\"\n INPUT: tuples (lon1, lat1), (lon2, lat2)\n\n OUTPUT: The great circle distance between two points\n on the earth (specified in decimal degrees)\n \"\"\"\n lon1... | [
2,
3,
4,
5,
6
] |
import nevergrad as ng
import numpy as np
import torch
from pix2latent.utils.image import binarize
class _BaseNevergradOptimizer():
"""
Base template for NeverGrad optimization. Should be used jointly with
BaseOptimizer.
For full list of available optimizers
> https://github.com... | normal | {
"blob_id": "4a136a6284add3bcbd7f9546e18e79151cea685f",
"index": 623,
"step-1": "<mask token>\n\n\nclass _BaseNevergradOptimizer:\n <mask token>\n\n def __init__(self, method):\n self.method = method\n self.valid_methods = [x[0] for x in ng.optimizers.registry.items()]\n self.sequentia... | [
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
assert len(sys.argv
) == 3, 'jsonsubschema cli takes exactly two arguments lhs_schema and rhs_schema'
s1_file = sys.argv[1]
s2_file = sys.argv[2]
with open(s1_file, 'r') as f1:
s1 = js... | flexible | {
"blob_id": "ba78a1e29736c4f109a0efc6f5b9993994661058",
"index": 3527,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n assert len(sys.argv\n ) == 3, 'jsonsubschema cli takes exactly two arguments lhs_schema and rhs_schema'\n s1_file = sys.argv[1]\n s2_file = sys.argv[2]\n... | [
0,
1,
2,
3,
4
] |
from eboss_qso.fits.joint import run_joint_mcmc_fit
from eboss_qso.measurements.utils import make_hash
import os.path as osp
import os
from glob import glob
ARGS = [(False, 1.0),
(False, 1.6),
(True, 1.6),
(True, 1.0)
]
ITERATIONS = 500
WALKERS = 100
def main(argnum, kmin):
z_we... | normal | {
"blob_id": "a40c87fe4b805495e5bd30155faa861cbe16c368",
"index": 6123,
"step-1": "<mask token>\n\n\ndef main(argnum, kmin):\n z_weighted, p = ARGS[argnum]\n kws = {}\n kws['version'] = 'v1.9f'\n kws['krange'] = '%s-0.3' % kmin\n kws['params'] = 'basemodel-N-fnl'\n kws['zrange'] = '0.8-2.2'\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@login_required
@csrf_exempt
def social(request):
if request.method == 'POST':
data = request.POST
project_id = int(json.loads(data.get('projid')))
head = data.get('head')
head = json.loads(he... | flexible | {
"blob_id": "c2839046592469dfae7526f72be947126960ba19",
"index": 621,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@login_required\n@csrf_exempt\ndef social(request):\n if request.method == 'POST':\n data = request.POST\n project_id = int(json.loads(data.get('projid')))\n he... | [
0,
1,
2,
3
] |
# Generated by Django 2.2.5 on 2019-10-09 12:06
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import mptt.fields
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MOD... | normal | {
"blob_id": "5485fe4f612ededc11e3a96dfd546e97a56cbe2a",
"index": 3316,
"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
] |
class Solution:
def merge(self, nums1, m, nums2, n):
"""
Do not return anything, modify nums1 in-place instead.
"""
if n == 0:
nums1 = nums1
if nums1[m-1] <= nums2[0]:
for i in range(n):
nums1[m+i] = nums2[i]
... | normal | {
"blob_id": "4f13e2858d9cf469f14026808142886e5c3fcc85",
"index": 28,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution:\n\n def merge(self, nums1, m, nums2, n):\n \"\"\"\n Do not return anything, modify nums1 in-place ins... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def primeiras_ocorrencias(str):
dic = {}
for i, letra in enumerate(str):
if letra not in dic:
dic[letra] = i
return dic
| flexible | {
"blob_id": "bb1a6815649eb9e79e2ab1e110ea8acd8adce5aa",
"index": 3379,
"step-1": "<mask token>\n",
"step-2": "def primeiras_ocorrencias(str):\n dic = {}\n for i, letra in enumerate(str):\n if letra not in dic:\n dic[letra] = i\n return dic\n",
"step-3": null,
"step-4": null,
"s... | [
0,
1
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 22 18:05:44 2018
@author: Administrator
"""
from sklearn.model_selection import cross_val_score, train_test_split
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import StratifiedKFold
from sklearn.m... | normal | {
"blob_id": "aaa0ac5e31e2c10b5baba6077e952fff1a92ef82",
"index": 882,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('cross-vali score is: {}'.format(score.mean()))\n<mask token>\nfor train_index, test_index in kfold.split(iris.data, iris.target):\n print(train_index, test_index)\n<mask token>\n... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def crop_image_center(file, crop_left, crop_right, crop_top, crop_bottom):
img = Image.open(file)
x, y = img.size
box = (crop_left, crop_top, x - crop_left - crop_right, y - crop_top -
crop_bottom)
crop = img.crop(box)
crop.save(file)
def create_empty_folder(... | flexible | {
"blob_id": "a9876c61578a53f29865062c0915db622aaaba72",
"index": 6916,
"step-1": "<mask token>\n\n\ndef crop_image_center(file, crop_left, crop_right, crop_top, crop_bottom):\n img = Image.open(file)\n x, y = img.size\n box = (crop_left, crop_top, x - crop_left - crop_right, y - crop_top -\n crop... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Todo(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Todo(models.Model):
title = models.CharField(max_length=200)
... | flexible | {
"blob_id": "4b075d8211d7047f6f08fe6f6f55e4703bdb6f1f",
"index": 3164,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Todo(models.Model):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Todo(models.Model):\n title = models.CharField(max_length=200)\n completed... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python3
"""
module that has
fucntions that
shows attributes
"""
def lookup(obj):
"""
function that returns attributes and methods of an object
"""
return(dir(obj))
| normal | {
"blob_id": "67380fb8b1557b0ed6779009e5f9ae93fd81aedd",
"index": 8753,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef lookup(obj):\n \"\"\"\n function that returns attributes and methods of an object\n \"\"\"\n return dir(obj)\n",
"step-3": "#!/usr/bin/python3\n\"\"\"\nmodule that h... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def wrong_subtraction(n, k):
output = n
for i in range(k):
string_n = str(output)
if string_n[len(string_n) - 1] == '0':
output = int(string_n[:-1])
else:
output -= 1
return output
<|reserved_special_token_0|>
<|reserved_spec... | flexible | {
"blob_id": "166a8cd0e09fbec739f43019659eeaf98b1d4fa4",
"index": 4446,
"step-1": "<mask token>\n\n\ndef wrong_subtraction(n, k):\n output = n\n for i in range(k):\n string_n = str(output)\n if string_n[len(string_n) - 1] == '0':\n output = int(string_n[:-1])\n else:\n ... | [
1,
2,
3,
4,
5
] |
# Simulador de sistema M/M/1.
#
# Variables de respuesta:
# - Demora promedio por cliente
# - Número promedio de clientes en cola
# - Utilización promedio de cliente
#
# Funciones:
# arribo()
# partida()
# nuevoEvento()
# medidasDesempeño()
# generarTiempoExponencial(t)
# generarHi... | normal | {
"blob_id": "62cc731982846f08b3f3caace5df1bfafd421869",
"index": 1701,
"step-1": "<mask token>\n\n\ndef arribo():\n global reloj\n global tiempoUltEvento\n global estadoServ\n global tiempoServicioTotal\n global areaQ\n global numCliEnCola\n global cola\n global tiempoLibre\n global co... | [
6,
7,
8,
9,
10
] |
from kivy.uix.button import Button
from kivy.uix.gridlayout import GridLayout
from kivy.uix.floatlayout import FloatLayout
from kivy.uix.label import Label
from kivy.app import App
import webbrowser
a=0.0
b="?"
n=0.0
k=""
g=""
class ghetto(GridLayout):
def matCallback(self,a):
webbrowser.open_n... | normal | {
"blob_id": "39affe139eec4cf6877646188839d79ed575235c",
"index": 8952,
"step-1": "<mask token>\n\n\nclass ghetto(GridLayout):\n <mask token>\n\n def biyoCallback(self, a):\n webbrowser.open_new(\n 'https://us04web.zoom.us/j/8651192984?pwd=cFV0bUNPTXRUOGVPZWw4dEhDQm0vUT09'\n )\n... | [
11,
12,
15,
17,
18
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(n):
x, x1 = [int(i) for i in input().strip().split(' ')]
x, x1 = x - 1, x1 - 1
t[i] = [x, x1]
<|reserved_special_token_0|>
while len(res) < n:
a = res[-1]
b = t[a][0]
c = t[a][1]
if c not... | flexible | {
"blob_id": "0e3c6e14ff184401a3f30a6198306a17686e6ebe",
"index": 2382,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n x, x1 = [int(i) for i in input().strip().split(' ')]\n x, x1 = x - 1, x1 - 1\n t[i] = [x, x1]\n<mask token>\nwhile len(res) < n:\n a = res[-1]\n b = t[... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
while index < len(array):
count = 0
while count <= len(array) - 2:
if count == len(array) - 1:
break
if array[count] > array[count + 1]:
sift = array[count]
array[count] ... | flexible | {
"blob_id": "fc8976141a19afd099f92cbbdb578e9c620cb745",
"index": 5075,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile index < len(array):\n count = 0\n while count <= len(array) - 2:\n if count == len(array) - 1:\n break\n if array[count] > array[count + 1]:\n ... | [
0,
1,
2,
3
] |
import random
import matplotlib.pyplot as plt
import numpy as np
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 <= n:
r1 = random.randint(1,6)... | normal | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
dataloader = ALF200KLoader(path='data/processed/dataset-lfm-genres.pickle',
load_feature_groups=['rhymes', 'statistical', 'statistical_time',
'explicitness', 'audio'], text_vectorizers=lda() + tfidf(), target=
genre_ta... | flexible | {
"blob_id": "473c653da54ebdb7fe8a9eefc166cab167f43357",
"index": 3994,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndataloader = ALF200KLoader(path='data/processed/dataset-lfm-genres.pickle',\n load_feature_groups=['rhymes', 'statistical', 'statistical_time',\n 'explicitness', 'audio'], text_vect... | [
0,
1,
2,
3
] |
# coding: utf-8
from __future__ import (
absolute_import,
division,
print_function,
unicode_literals,
)
import time
from urllib import urlencode
from urlparse import parse_qs, urlparse, urlunparse
from flask import current_app as app
from flask import url_for
from jose import jwt
from oauth2client.cl... | normal | {
"blob_id": "fe73a80b15cad025a33930ddd9abb31524cd0244",
"index": 9404,
"step-1": "<mask token>\n\n\ndef create_oauth_flow():\n \"\"\"Prepare Google OAuth workflow from config file.\"\"\"\n app.flow = flow_from_clientsecrets(str(Path(app.config['ROOT_DIR'],\n 'configs/client_secrets.json')), scope=['... | [
4,
5,
6,
7,
8
] |
from unittest import TestCase
from unittest.mock import patch, mock_open, call
from network_simulator.exceptions.device_exceptions import DeviceAlreadyRegisteredException, UnknownDeviceException
from network_simulator.service import NetworkSimulatorService
from network_simulator.service.network_simulator_service impor... | normal | {
"blob_id": "8e854398084e89b0b8436d6b0a2bf8f36a9c7bd5",
"index": 187,
"step-1": "<mask token>\n\n\nclass TestNetworkSimulatorService(TestCase):\n\n @patch(\n 'network_simulator.service.network_topology_handler.write_network_topology_to_file'\n )\n def setUp(self, write_network_topology_to_fil... | [
5,
6,
7,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@public
def Main() ->int:
a = 'just a test'
return len(a)
<|reserved_special_token_1|>
from boa3.builtin import public
@public
def Main() ->int:
a = 'just a test'
return len(a)
| flexible | {
"blob_id": "e44e19dbeb6e1e346ca371ca8730f53ee5b95d47",
"index": 5402,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@public\ndef Main() ->int:\n a = 'just a test'\n return len(a)\n",
"step-3": "from boa3.builtin import public\n\n\n@public\ndef Main() ->int:\n a = 'just a test'\n retur... | [
0,
1,
2
] |
dic = {}
try:
print(dic[55])
except Exception as err:
print('Mensagem: ', err)
| normal | {
"blob_id": "618aa64c08ebf8d9a0bc9662195ece2bbd485c17",
"index": 1079,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n print(dic[55])\nexcept Exception as err:\n print('Mensagem: ', err)\n",
"step-3": "dic = {}\ntry:\n print(dic[55])\nexcept Exception as err:\n print('Mensagem: ', err... | [
0,
1,
2
] |
from flask_restful import Resource, reqparse
import sqlite3
from flask_jwt import jwt_required
from models.item_model import ItemModel
from flask_sqlalchemy import SQLAlchemy
from d import db
from models.store_model import StoreModel
class Modell(Resource):
def get(self, name):
item = Store... | normal | {
"blob_id": "5616ec135a2233e742ff3b2b1f378ec12298b935",
"index": 9578,
"step-1": "<mask token>\n\n\nclass Modell(Resource):\n <mask token>\n <mask token>\n\n def put(self, name):\n item = StoreModel.find_by_name(name)\n item.save_to_db()\n return item.json()\n <mask token>\n\n\nc... | [
4,
5,
6,
8,
9
] |
from mbc import MBC
import random
import sys
from typing import Dict
from interface import Interface
from reg import Register, HandlerProxy
# I/O Registers
IE = 0xFFFF
DIV = 0xFF04
TIMA= 0xFF05
TMA = 0xFF06
TAC = 0xFF07
IF = 0xFF0F
LY = 0xFF44
class MMU():
#0000 3FFF 16KB ROM bank 00 From cartridge, usual... | normal | {
"blob_id": "1a7363736076620b7704d7264b2f0bb24514165c",
"index": 9816,
"step-1": "<mask token>\n\n\nclass MMU:\n <mask token>\n\n def dma(self, val: int) ->None:\n dest = 65024\n offset = val * 256\n for n in range(160):\n self.mem[dest + n] = self.mem[n + offset]\n <mask... | [
4,
6,
7,
8,
9
] |
import pygame
import wave
import threading
import numpy as np
import pylab
import struct
import io
from PIL import Image
import sounddevice as sd
# 处理音频频谱
# voice.wav 格式：8000 rate 16bit 单声道
class SpectrumMap:
def __init__(self):
FILENAME = 'Sound/SoundResource/voice.wav'
self.wavefile = wave.open(... | normal | {
"blob_id": "fbde00d727d7ea99d1a7704f46cb9850c8b210d7",
"index": 2610,
"step-1": "<mask token>\n\n\nclass SpectrumMap:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass SpectrumMap2:\n\n def __init__(self):\n devices = sd.query_devices()\n devic... | [
12,
14,
16,
18,
19
] |
from django import forms
from .models import Note
class NoteForm(forms.ModelForm):
class Meta:
model = Note
fields = ['title', 'text']
class NoteFullForm(NoteForm):
note_id = forms.IntegerField(required=False)
images = forms.FileField(widget=forms.ClearableFileInput(attrs={
'mu... | normal | {
"blob_id": "e0fd9663a5635873f4ffc0f73aff5106c0933781",
"index": 9180,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NoteFullForm(NoteForm):\n note_id = forms.IntegerField(required=False)\n images = forms.FileField(widget=forms.ClearableFileInput(attrs={\n 'multiple': True}), requ... | [
0,
2,
3,
4
] |
from timeit import default_timer as timer
import numpy as np
bets1 = [ # lowest config possible
0.00000001,
0.00000004,
0.0000001,
0.0000005,
0.00000150,
0.00000500,
0.00001000
]
bets2 = [ # 2 is 10x 1
0.0000001,
0.0000004,
0.000001,
0.000005,
0.0000150,
0.0000500,... | normal | {
"blob_id": "4c66ab6110e81bb88fc6916a1695e0f23e6e0e9d",
"index": 6754,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor seed in range(start_position, start_position + max_seeds):\n cur_wins = 0\n max_wins = 0\n cur_losses = 0\n max_losses = 0\n win_streak = []\n loss_streak = []\n ... | [
0,
1,
2,
3,
4
] |
from Player import Player
class GameSequence:
'''
GameSequence summary: Keeps track of player turn sequence and Game end
Functionalities
-start game
-must start turns
-change turns
-end turns
-end game
'''
def __init__(self, ArrayofPlaye... | normal | {
"blob_id": "bdfd941be29a31d6c1bbedd270dadac844f49fc4",
"index": 1198,
"step-1": "<mask token>\n\n\nclass GameSequence:\n <mask token>\n <mask token>\n\n def changeMode(self, number):\n self.currentMode = self.modes[number]\n\n def startGame(self):\n self.currentTurn = 0\n \"\"\"... | [
6,
7,
8,
9,
11
] |
n = int(input())
num = list(map(int, input().split()))
plus_cnt = 0
div_max = 0
for i in num:
div = 0
while i > 0:
if i % 2 == 0:
i //= 2
div += 1
else:
i -= 1
plus_cnt += 1
div_max = max(div_max, div)
print(plus_cnt + div_max)
| normal | {
"blob_id": "9247896850e5282265cd08240f6f505e675ce5f0",
"index": 5904,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in num:\n div = 0\n while i > 0:\n if i % 2 == 0:\n i //= 2\n div += 1\n else:\n i -= 1\n plus_cnt += 1\n div_max ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class dequeue:
def __init__(self):
self.front = None
self.last = None
self.count = 0
def add_front(self, data):
new_nodef = Node(data)
if self.front == None:
self.front = self.last = new_nodef
self.count += 1
... | flexible | {
"blob_id": "2f6e0b6a7e14ac9c5a38db6fd2b1cf23cff7144e",
"index": 172,
"step-1": "<mask token>\n\n\nclass dequeue:\n\n def __init__(self):\n self.front = None\n self.last = None\n self.count = 0\n\n def add_front(self, data):\n new_nodef = Node(data)\n if self.front == Non... | [
8,
10,
12,
13,
15
] |
from django.db import models
#from publicservants import models
from django.utils.encoding import smart_unicode
# Create your models here.
class Score(models.Model):
#score ID - publicservant ID plus score
#sID = models.ManyToOneRel(field=PublicServant.psID)
#PS Score at time t
pst = models.Inte... | normal | {
"blob_id": "8c166dd4cb091dcd2d80b5ae3085b5dee77564e0",
"index": 1227,
"step-1": "<mask token>\n\n\nclass Score(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask t... | [
1,
2,
3,
4,
5
] |
"""A simple script to create a motion plan."""
import os
import json
import logging
from logging.config import dictConfig
import argparse
import numpy as np
from opentrons_hardware.hardware_control.motion_planning import move_manager
from opentrons_hardware.hardware_control.motion_planning.types import (
AxisConst... | normal | {
"blob_id": "b7d75c2523dba0baaf06ba270045a4a344b8156c",
"index": 3023,
"step-1": "<mask token>\n\n\ndef main() ->None:\n \"\"\"Entry point.\"\"\"\n parser = argparse.ArgumentParser(description='Motion planning script.')\n parser.add_argument('--params-file-path', '-p', type=str, required=\n False... | [
1,
2,
3,
4,
5
] |
#ERP PROJECT
import pyrebase
import smtplib
config = {
"apiKey": "apiKey",
"authDomain": "erproject-dd24e-default-rtdb.firebaseapp.com",
"databaseURL": "https://erproject-dd24e-default-rtdb.firebaseio.com",
"storageBucket": "erproject-dd24e-default-rtdb.appspot.com"
}
firebase = pyrebase.initialize_app(conf... | normal | {
"blob_id": "3e7e6d7a0137d91dc7437ff91a39d7f8faad675e",
"index": 7075,
"step-1": "<mask token>\n\n\ndef j():\n global i\n import pandas as pd\n st1.update({i: st})\n data = pd.DataFrame(st1)\n print(data)\n data.to_csv('student.csv')\n fa1.update({i: fa})\n data1 = pd.DataFrame(fa1)\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pygame.init()
<|reserved_special_token_0|>
pygame.display.set_caption("Omar's Simulation")
screen.fill(background_colour)
<|reserved_special_token_0|>
for i in range(population_size):
robots.append(Robot(175, 300, 10, 360, 9, ... | flexible | {
"blob_id": "cbcbc0d01c32693ebbdbcf285efdc8e521c447ee",
"index": 3998,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npygame.init()\n<mask token>\npygame.display.set_caption(\"Omar's Simulation\")\nscreen.fill(background_colour)\n<mask token>\nfor i in range(population_size):\n robots.append(Robot(175... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def DFS(x):
if x > 7:
return
else:
DFS(x * 2)
print(x)
DFS(x * 2 + 1)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def DFS(x):
if x > 7:
return
else:
DFS(x * 2)
print(x)... | flexible | {
"blob_id": "1cc8695aa694359314b6d478fe6abed29fdc6c91",
"index": 3309,
"step-1": "<mask token>\n",
"step-2": "def DFS(x):\n if x > 7:\n return\n else:\n DFS(x * 2)\n print(x)\n DFS(x * 2 + 1)\n\n\n<mask token>\n",
"step-3": "def DFS(x):\n if x > 7:\n return\n el... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Descuento(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __str__(self):
return self.codigo_descuento
class Venta(models.Model):
descripcion = models.CharField(max_length=100)
total_venta = models.IntegerField()
def __... | flexible | {
"blob_id": "0e19d7251db3382c34ad2d38a7984b65325ecfbf",
"index": 7584,
"step-1": "<mask token>\n\n\nclass Descuento(models.Model):\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.codigo_descuento\n\n\nclass Venta(models.Model):\n descripcion = models.CharField(max_length=100... | [
22,
29,
33,
34,
40
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
img = np.array([[1, 2], [1, 3], [1, 4]])
print(img.tolist())
sys.stdout.flush()
<|reserved_special_token_1|>
import numpy as np
import sys
import os
import cv2
if __name__ == '__main__':
... | flexible | {
"blob_id": "54833c19d68bb7a1817639ef761367ce75a3a46f",
"index": 9200,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n img = np.array([[1, 2], [1, 3], [1, 4]])\n print(img.tolist())\n sys.stdout.flush()\n",
"step-3": "import numpy as np\nimport sys\nimport os\nimpor... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Solution:
def maximalSquare(self, matrix: List[List[str]]) ->int:
... | flexible | {
"blob_id": "e5d31a2ea4a8615d24626be2414f5ae49b9cd6a1",
"index": 184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def maximalSquare(self, matrix: List[List[str]]) ->int:\n if not ma... | [
0,
1,
2,
3
] |
# %% import libs
import os
import argparse
import logging as logger
import mxnet as mx
import tqdm
from mxnet import autograd
from mxnet import gluon
from gluoncv.utils import makedirs
import datasets as gan_datasets
from utils import vis, get_cpus, TrainingHistory
import models
mx.random.seed(5)
logger.basicConfig(l... | normal | {
"blob_id": "c14d76493cd3dacc55c993f588dec555b7a4a13c",
"index": 4192,
"step-1": "<mask token>\n\n\ndef make_noises(bs):\n return mx.nd.random_normal(0, 1, shape=(bs, 512), ctx=CTX, dtype='float32'\n ).reshape((bs, 512, 1, 1))\n\n\n<mask token>\n",
"step-2": "<mask token>\nmx.random.seed(5)\nlogger.b... | [
1,
3,
4,
5,
6
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
def calcLuckyNumber(x):
resultSet = set()
for i in range(30):
for j in range(30):
for k in range(30):
number = pow(3, i) * pow(5, j) * pow(7, k)
if number > 1 and number <= x:
resultSet.add(nu... | normal | {
"blob_id": "49a9fb43f3651d28d3ffac5e33d10c428afd08fd",
"index": 6072,
"step-1": "<mask token>\n",
"step-2": "def calcLuckyNumber(x):\n resultSet = set()\n for i in range(30):\n for j in range(30):\n for k in range(30):\n number = pow(3, i) * pow(5, j) * pow(7, k)\n ... | [
0,
1,
2,
3,
4
] |
""" AuthService class module.
"""
from urllib.parse import urlencode
from http.client import HTTPConnection, HTTPResponse, HTTPException
from dms2021sensor.data.rest.exc import NotFoundError
class AuthService():
""" REST client to connect to the authentication service.
"""
def __init__(self, host: str, ... | normal | {
"blob_id": "1438a268780217e647999ba031aa4a50a6912d2f",
"index": 3069,
"step-1": "<mask token>\n\n\nclass AuthService:\n <mask token>\n <mask token>\n\n def __get_connection(self) ->HTTPConnection:\n \"\"\" Creates a new connection to the authentication server.\n ---\n Returns:\n ... | [
2,
3,
5,
6,
7
] |
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