code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
f=open('p102_triangles.txt')
def cross(a,b,c):
t1=b[0]-a[0]
t2=b[1]-a[1]
t3=c[0]-a[0]
t4=c[1]-a[1]
return t1*t4-t2*t3
x=[0,0]
y=[0,0]
z=[0,0]
origin=(0,0)
ans=0
for i in f.xreadlines():
x[0],x[1],y[0],y[1],z[0],z[1]=map(int,i.split(','))
area1=abs(cross(x,y,z))
area2=abs(cross(x,y,orig... | normal | {
"blob_id": "c34ff2bbb0ba743268ace77c110ce0b283a25eba",
"index": 8637,
"step-1": "f=open('p102_triangles.txt')\n\ndef cross(a,b,c):\n t1=b[0]-a[0]\n t2=b[1]-a[1]\n t3=c[0]-a[0]\n t4=c[1]-a[1]\n return t1*t4-t2*t3\n\nx=[0,0]\ny=[0,0]\nz=[0,0]\norigin=(0,0)\nans=0\nfor i in f.xreadlines():\n x[0]... | [
0
] |
'''harvestPRR: analyze Public Record Requests from CSV data provided by NextRequest
Created 27 Aug 20
@author: rik@electronicArtifacts.com
'''
from collections import defaultdict
import csv
import datetime
import json
import random
import re
import requests
import sys
import time
import urllib
import re
PRRDateFm... | normal | {
"blob_id": "b3758e42b52bb50d806832c6a3a76ae0537266de",
"index": 8043,
"step-1": "<mask token>\n\n\ndef freqHist3(tbl):\n \"\"\"python3 version\n\tASSUME: values are frequencies, returns sorted list of (val,freq) items in descending freq order\n\t\"\"\"\n from functools import cmp_to_key\n\n def cmpd1(a... | [
10,
11,
13,
14,
16
] |
#!/usr/bin/env python
number=int(input("Enter an integer"))
if number<=100:
print("Your number is smaller than equal to 100")
else:
print("Your number is greater than 100")
| normal | {
"blob_id": "9666c87b4d4dc721683ea33fdbbeadefc65a0cd1",
"index": 1860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif number <= 100:\n print('Your number is smaller than equal to 100')\nelse:\n print('Your number is greater than 100')\n",
"step-3": "number = int(input('Enter an integer'))\nif ... | [
0,
1,
2,
3
] |
"""
题目描述
HZ偶尔会拿些专业问题来忽悠那些非计算机专业的同学。
今天测试组开完会后,他又发话了:在古老的一维模式识别中,
常常需要计算连续子向量的最大和,当向量全为正数的时候,问题很好解决。
但是,如果向量中包含负数,是否应该包含某个负数,并期望旁边的正数会弥补它呢？
例如:{6,-3,-2,7,-15,1,2,2},连续子向量的最大和为8(从第0个开始,到第3个为止)。
给一个数组，返回它的最大连续子序列的和，你会不会被他忽悠住？(子向量的长度至少是1)
"""
# -*- coding:utf-8 -*-
class Solution:
def FindGreatestSumOfSubArray(self, ar... | normal | {
"blob_id": "fcca845b60b050fa5dd0a3c50b3c36c154022f07",
"index": 1467,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n\n def FindGreatestSumOfSubArray(self, array):\n dp = [array[0]]\n res = array[0]\n f... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import json
import codecs
import Levenshtein
import logging
import random
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import cross_val_score
import time
from sklearn.model_selection import KFold
import numpy as np
import s... | normal | {
"blob_id": "37804c92b69d366cc1774335b6a2295dfd5b98f3",
"index": 6592,
"step-1": "<mask token>\n\n\ndef gen_label(uid1, uid2):\n if same_line_dict[uid1].__contains__(uid2) and same_line_dict[uid2\n ].__contains__(uid1):\n return '1'\n else:\n return '-1'\n\n\n<mask token>\n\n\ndef gen_... | [
2,
5,
6,
7,
8
] |
from django.db import models
from django.utils import timezone
class Test(models.Model):
word1 = models.CharField(max_length=50)
word2 = models.CharField(max_length=50)
word3 = models.CharField(max_length=50)
answer = models.CharField(max_length=50)
#def __str__(self):
# return self.word1, ... | normal | {
"blob_id": "2a1d31b2123c11af3fce571287d3dad00a9b0086",
"index": 2820,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Test(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Test(models.Model):\n word1 = models.Char... | [
0,
1,
2,
3,
4
] |
#
# cuneiform_python.py
#
# Example showing how to create a custom Unicode set for parsing
#
# Copyright Paul McGuire, 2021
#
from typing import List, Tuple
import pyparsing as pp
class Cuneiform(pp.unicode_set):
"""Unicode set for Cuneiform Character Range"""
_ranges: List[Tuple[int, ...]] = [
(0x10... | normal | {
"blob_id": "bc1aefd0b0a87b80a10cecf00407b4608a6902b5",
"index": 3897,
"step-1": "<mask token>\n\n\nclass Cuneiform(pp.unicode_set):\n <mask token>\n _ranges: List[Tuple[int, ...]] = [(66432, 66517), (73728, 74751), (\n 74752, 74879)]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Cuneif... | [
1,
3,
4,
5,
6
] |
class Config(object):
DEBUG = False
TESTING = False
SQLALCHEMY_TRACK_MODIFICATIONS = False
class Production(Config):
SQLALCHEMY_DATABASE_URI = '<Production DB URL>'
class Development(Config):
# psql postgresql://Nghi:nghi1996@localhost/postgres
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'pos... | normal | {
"blob_id": "e99d557808c7ae32ebfef7e7fb2fddb04f45b13a",
"index": 6091,
"step-1": "<mask token>\n\n\nclass Production(Config):\n <mask token>\n\n\nclass Development(Config):\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SE... | [
5,
6,
7,
8,
9
] |
# Generated by Django 2.2.5 on 2019-10-24 05:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('student', '0008_studentbasic_stu_class_num'),
]
operations = [
migrations.AlterModelOptions(
name='onduty',
options=... | normal | {
"blob_id": "289aa48b4433be533c3916dd039136df45e0ac0b",
"index": 1073,
"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 = [('student', '... | [
0,
1,
2,
3,
4
] |
import settings
#from django.conf import settings
from django.conf.urls import patterns, include, url
from django.contrib import admin
from django.conf.urls.static import static
from django.contrib.staticfiles.urls import staticfiles_urlpatterns
#admin.autodiscover()
# Uncomment the next two lines to enable the admin... | normal | {
"blob_id": "acb85a16e45472dac61eed4162dc651f67a0e8ca",
"index": 5400,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.autodiscover()\n<mask token>\n",
"step-3": "<mask token>\nadmin.autodiscover()\nurlpatterns = patterns('', url('^media/(?P<path>.*)$',\n 'django.views.static.serve', {'document... | [
0,
1,
2,
3,
4
] |
class TrieTree(object):
def __init__(self):
self.size=0
self.childern=[None]*26
def insert(self,word):
node=self
for w in word:
index=ord(w)-97
node.size+=1
if node.childern[index]==None:
node.childern[index]=TrieTree()
... | normal | {
"blob_id": "a18fad746a1da3327d79ac0a61edd156c5fb8892",
"index": 6127,
"step-1": "\n\nclass TrieTree(object):\n def __init__(self):\n self.size=0\n self.childern=[None]*26\n def insert(self,word):\n node=self\n for w in word:\n index=ord(w)-97\n node.size+... | [
0
] |
"""
In search.py, you will implement generic search algorithms which are called
by Pacman agents (in searchAgents.py).
"""
import util
class SearchProblem:
"""
This class outlines the structure of a search problem, but doesn't implement
any of the methods (in object-oriented terminology: an abstract class... | normal | {
"blob_id": "e7b96c0161e65f3f22f2ad0832fc6d1bb529f150",
"index": 9772,
"step-1": "<mask token>\n\n\nclass SearchProblem:\n \"\"\"\n This class outlines the structure of a search problem, but doesn't implement\n any of the methods (in object-oriented terminology: an abstract class).\n\n You do not nee... | [
8,
10,
12,
13,
15
] |
#!/usr/bin/env python
#--coding: utf8--
import time
if __name__ == '__main__':
date = time.strftime('%m-%d')
if date == '03-08':
print '女神节'
elif date == '02-14':
print '情人节'
else:
print '发红包'
print '这是一个测试题' | normal | {
"blob_id": "23375760c0943ca177b7009031d9d17a91165c5c",
"index": 230,
"step-1": "#!/usr/bin/env python\n#--coding: utf8--\nimport time\n\nif __name__ == '__main__':\n date = time.strftime('%m-%d')\n if date == '03-08':\n print '女神节'\n elif date == '02-14':\n print '情人节'\n else:\n ... | [
0
] |
from models import Cell,Board
import random
from pdb import set_trace as bp
status={'end':-1}
game=None
class Game_Service(object):
def __init__(self,row_num,col_num):
self._row_num=row_num
self._col_num=col_num
mine_percent=0.3
self._mine_num=int(mine_percent*float(self._row_nu... | normal | {
"blob_id": "4af72cab6444922ca66641a08d45bcfe5a689844",
"index": 6763,
"step-1": "<mask token>\n\n\nclass Game_Service(object):\n\n def __init__(self, row_num, col_num):\n self._row_num = row_num\n self._col_num = col_num\n mine_percent = 0.3\n self._mine_num = int(mine_percent * f... | [
5,
6,
7,
9,
10
] |
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import pandas
import numpy
import json
import torch.utils.data as data
import os
import torch
def load_json(file):
with open(file) as json_file:
data = json.load(json_file)
return data
class VideoDataSet(data.Dataset):
def __init_... | normal | {
"blob_id": "e5b5a0c8c0cbe4862243548b3661057240e9d8fd",
"index": 6077,
"step-1": "<mask token>\n\n\nclass VideoDataSet(data.Dataset):\n <mask token>\n\n def check_csv(self):\n for video in self.video_list:\n if not os.path.exists(self.feature_path + 'csv_mean_' + str(\n sel... | [
17,
21,
28,
31,
32
] |
from typing import Dict, Optional
from collections import OrderedDict
import torch
import torch.nn as nn
import torch.optim as optim
import yaml
def get_device() -> torch.device:
if torch.cuda.is_available():
return torch.device("cuda")
return torch.device("cpu")
def load_yaml_config(config_path: s... | normal | {
"blob_id": "e8a36bd7826c5d71cf8012ea82df6c127dd858fc",
"index": 549,
"step-1": "<mask token>\n\n\ndef load_yaml_config(config_path: str) ->Dict:\n with open(config_path, 'r') as stream:\n return yaml.load(stream)\n\n\ndef get_optimizer(model: nn.Module, optim_config: Dict) ->optim.Optimizer:\n retu... | [
4,
5,
6,
7,
8
] |
import sys, getopt
sys.path.append('.')
import RTIMU
import os.path
import time
import math
import encoders
import motors
#right is master, left is slave
master_power = .6
slave_power = -.6
right_num_revs = 0
left_num_revs = 0
kp = .5
encoders.init()
motors.init()
en_left, en_right = encoders.read()
SETTINGS_FILE ... | normal | {
"blob_id": "00f8a56b160cab22bf73c0d2397eb2c411e8c966",
"index": 7714,
"step-1": "<mask token>\n\n\ndef adjustMotorPowers():\n global slave_power\n global en_left\n global en_right\n global kp\n error = en_right + en_left\n slave_power -= error / kp\n encoders.clear()\n time.sleep(0.1)\n\... | [
2,
3,
4,
5,
6
] |
from configparser import ConfigParser
from ef.config.components import *
from ef.config.efconf import EfConf
from ef.config.section import ConfigSection
comp_list = [BoundaryConditions, InnerRegion, OutputFile, ParticleInteractionModel,
ParticleSource, SpatialMesh, TimeGrid, ExternalFieldUniform]
def t... | normal | {
"blob_id": "edcccc673994a8de281a683b747de52d2115f89e",
"index": 347,
"step-1": "<mask token>\n\n\ndef test_components_to_conf_and_back():\n for Component in comp_list:\n x = Component()\n y = x.to_conf().make()\n assert x == y\n\n\n<mask token>\n\n\nclass TestEfConf:\n\n def test_conf... | [
4,
5,
6,
8,
9
] |
import os
import requests
def download(url: str, dest_folder: str):
#https://stackoverflow.com/a/56951135/8761164
if not os.path.exists(dest_folder):
os.makedirs(dest_folder) # create folder if it does not exist
filename = url.split('/')[-1].replace(" ", "_") # be careful with file names
fil... | normal | {
"blob_id": "0726a4fa3af196e2ba1592019f09afb0e7bb47d7",
"index": 9731,
"step-1": "<mask token>\n\n\ndef parse_lat(lat: int):\n lat_str = 'N' if lat >= 0 else 'S'\n if 10 > lat > -10:\n lat_str += '0'\n lat_str += str(abs(lat))\n return lat_str\n\n\n<mask token>\n",
"step-2": "<mask token>\n\... | [
1,
3,
4,
5,
6
] |
import cv2
import pytesseract
import os
from PIL import Image
import numpy as np
from helper_functions import Helper
class ImageData:
# multipliers to get portion of image with interval value
__bottom_thresh = 0.9
__left_thresh = 0.35
__right_thresh = 0.65
# (words, offset) to contour interval value
__words_of... | normal | {
"blob_id": "d3be26d56b3597a5d9e3a870b735a30d90d1e501",
"index": 8165,
"step-1": "<mask token>\n\n\nclass ImageData:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, image):\n self.image = image\n self._contour_interval_dist = None\... | [
6,
10,
11,
12,
17
] |
# coding=utf8
def InsertSort(array_a, n):
for i in range(1, n):
temp = array_a[i]
j = i - 1
while temp < array_a[j] and j >= 0:
array_a[j + 1] = array_a[j] # 如果小于其前驱，则从后往前寻找插入位置并后移。
j -= 1
array_a[j + 1] = temp
return array_a
def ShellSort(array_a, n):... | normal | {
"blob_id": "a01783e3687278d1ec529c5123b9151721ba3364",
"index": 3033,
"step-1": "# coding=utf8\n\ndef InsertSort(array_a, n):\n for i in range(1, n):\n temp = array_a[i]\n j = i - 1\n while temp < array_a[j] and j >= 0:\n array_a[j + 1] = array_a[j] # 如果小于其前驱，则从后往前寻找插入位置并后移。\... | [
0
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import json
import urllib2
#this is executed by a cron job on the pi inside the pooltable
secret ='secret'
baseurl='https://pooltable.mysite.com/'
url = baseurl + 'gettrans.php?secret=' + secret
req = urllib2.Request(url)
f = urllib2.urlopen(req)
response = f.read()... | normal | {
"blob_id": "9baf55eb2fb70e9fa0d92df22d307962b8d6c6d4",
"index": 5883,
"step-1": "#!/usr/bin/python\r\n# -*- coding: utf-8 -*-\r\n\r\nimport json\r\nimport urllib2\r\n#this is executed by a cron job on the pi inside the pooltable\r\nsecret ='secret'\r\nbaseurl='https://pooltable.mysite.com/'\r\nurl = baseurl + '... | [
0
] |
import os
import numpy as np
from argparse import ArgumentParser
from collections import Counter
from typing import Iterable, Dict, Any, Tuple
from utils.constants import TRAIN, VALID, TEST, SAMPLE_ID, INPUTS, OUTPUT
from utils.file_utils import make_dir
from utils.data_writer import DataWriter
WINDOW = 50
STRIDE = ... | normal | {
"blob_id": "e82dd2792ecbb8ed5a33012239102d2c6a02202b",
"index": 1749,
"step-1": "<mask token>\n\n\ndef get_partition(subject_id: int) ->str:\n if subject_id <= 10:\n return TEST\n elif subject_id <= 15:\n return VALID\n else:\n return TRAIN\n\n\ndef data_generator(input_folder: str... | [
3,
4,
5,
6,
7
] |
# !/usr/bin/env python3
# -*- coding: UTF-8 -*-
# Copyright (c) 2021 Baidu, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | normal | {
"blob_id": "129df937d7d295bae2009cfb65b2f85228206698",
"index": 8657,
"step-1": "<mask token>\n\n\nclass SGD(BasicOptimizer):\n <mask token>\n\n def __init__(self, iterations: int, circuit: BasicCircuit,\n learning_rate: float):\n \"\"\"The constructor of the SGD class\n\n Args:\n ... | [
2,
3,
4,
5,
6
] |
#cerner_2^5_2019
#Mason Seeger submission 1
from random import randint as r
import operator as o
#Only works with valid integers. A function for quick math brain training.
def randomMath():
correct = 0
while(correct<10):
str_ops = ['+', '-', '*', '/', '%']
ops = {'+': o.add, '-': o.sub, '*': o... | normal | {
"blob_id": "12f035962925c5380c782e8fad23f16fe9fb9435",
"index": 5311,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef randomMath():\n correct = 0\n while correct < 10:\n str_ops = ['+', '-', '*', '/', '%']\n ops = {'+': o.add, '-': o.sub, '*': o.mul, '/': o.floordiv, '%': o.mo... | [
0,
1,
2,
3,
4
] |
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.initializers import RandomUniform
class Critic:
def __init__(self, obs_dim, action_dim, learning_rate=0.001):
self.obs_dim = obs_dim
self.action_dim = action_dim
self.model = self.make_network()
... | normal | {
"blob_id": "535fdee8f74b1984c5d1a5ec929310473b01239d",
"index": 1617,
"step-1": "<mask token>\n\n\nclass Critic:\n\n def __init__(self, obs_dim, action_dim, learning_rate=0.001):\n self.obs_dim = obs_dim\n self.action_dim = action_dim\n self.model = self.make_network()\n self.opti... | [
7,
8,
9,
10,
11
] |
import socket
import threading
import os
import time
import psutil
import shutil
class server:
def __init__(self):
self.commandSock = socket.socket()
self.commandPort = 8080
self.transferSock = socket.socket()
self.transferPort = 8088
self.chatSock=socket.socket()
... | normal | {
"blob_id": "4736f4e06f166b3c3fd8379a2021eb84a34fcbd3",
"index": 6099,
"step-1": "<mask token>\n\n\nclass server:\n\n def __init__(self):\n self.commandSock = socket.socket()\n self.commandPort = 8080\n self.transferSock = socket.socket()\n self.transferPort = 8088\n self.ch... | [
7,
9,
11,
15,
16
] |
import argparse
from flower_classifier import FlowerClassifier
from util import *
parser = argparse.ArgumentParser()
parser.add_argument("data_dir", help="path to training images")
parser.add_argument("--save_dir", default=".", help="path where checkpoint is saved")
parser.add_argument("--arch", default="vgg11", help=... | normal | {
"blob_id": "0c3947a1699c78080661a55bbaa9215774b4a18e",
"index": 4751,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('data_dir', help='path to training images')\nparser.add_argument('--save_dir', default='.', help=\n 'path where checkpoint is saved')\nparser.add_argument('--arch',... | [
0,
2,
3,
4,
5
] |
#!/usr/bin/env python3
import warnings
import config
import numpy as np
from latplan.model import ActionAE, default_networks
from latplan.util import curry
from latplan.util.tuning import grid_search, nn_task
import keras.backend as K
import tensorflow as tf
float_formatter = lambda x: "%.3f" % x
np.set_printo... | normal | {
"blob_id": "f1c6340880b52ba86856913f74c7d589d9b49f49",
"index": 5179,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.set_printoptions(formatter={'float_kind': float_formatter})\n<mask token>\nif __name__ == '__main__':\n import numpy.random as random\n import sys\n if len(sys.argv) == 1:\n ... | [
0,
1,
2,
3,
4
] |
from redis_db import RedisClient
from setting import TEST_URL
import requests
class Test_Proxy():
def __init__(self):
self.db=RedisClient()
def proxy_test(self, proxy):
url = TEST_URL
proxies={
"http":proxy,
"https":proxy
}
# print("{}(测试中)".form... | normal | {
"blob_id": "2cbdb828ab6e0ad44154f0c5b2a1d807fd0d2520",
"index": 8783,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Test_Proxy:\n\n def __init__(self):\n self.db = RedisClient()\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Test_Proxy:\n\n def __init__(self):\n ... | [
0,
2,
3,
4,
5
] |
from django.apps import AppConfig
class BuyerSellerAppConfig(AppConfig):
name = 'buyer_seller_app'
| normal | {
"blob_id": "0b730314fef31e7304a8f5d8bb998581b021a610",
"index": 1798,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BuyerSellerAppConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BuyerSellerAppConfig(AppConfig):\n name = 'buyer_seller_app'\n",
"step-4": "from... | [
0,
1,
2,
3
] |
from .models import CNNClassifier, load_weights, LastLayer_Alexnet, classes, MyResNet
from .transforms import image_transforms, tensor_transform
from .utils import newest_model, Dataset, load_data
| normal | {
"blob_id": "17781ae5e9c72232fbc11c7eda7daeaeb0fa3670",
"index": 9277,
"step-1": "<mask token>\n",
"step-2": "from .models import CNNClassifier, load_weights, LastLayer_Alexnet, classes, MyResNet\nfrom .transforms import image_transforms, tensor_transform\nfrom .utils import newest_model, Dataset, load_data\n"... | [
0,
1
] |
import math
import numpy
import theano
from theano import tensor as T
from utils import shared_dataset
from layer import HiddenLayer, LogisticRegressionLayer
import pickle as pkl
from mlp import MLP, Costs, NeuralActivations
DEBUGGING = False
class PostMLP(MLP):
"""Post training:- Second phase MLP.
A mul... | normal | {
"blob_id": "f9ea29f882c6491a2ac0007e4d9435c732d0967a",
"index": 8582,
"step-1": "import math\n\nimport numpy\nimport theano\n\nfrom theano import tensor as T\n\nfrom utils import shared_dataset\n\nfrom layer import HiddenLayer, LogisticRegressionLayer\nimport pickle as pkl\n\nfrom mlp import MLP, Costs, NeuralA... | [
0
] |
from urllib.parse import urlencode
from urllib.request import urlopen, Request
from datetime import datetime
#пользовательские переменные
period=7 # задаём период. Выбор из: 'tick': 1, 'min': 2, '5min': 3, '10min': 4, '15min': 5, '30min': 6, 'hour': 7, 'daily': 8, 'week': 9, 'month': 10
start = "01.01.2021" #с какой д... | normal | {
"blob_id": "9d22a90835f5cf293808ab359244fe1bde81f3e1",
"index": 2171,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor ticker in tickers:\n params = urlencode([('market', market), ('em', tickers[ticker]), (\n 'code', ticker), ('apply', 0), ('df', start_date.day), ('mf', \n start_date.... | [
0,
1,
2,
3,
4
] |
import base64
import json
from werkzeug.exceptions import Unauthorized
from ab import app
from ab.utils import logger
from ab.plugins.spring import eureka
def _login(username, password):
"""
only for test
:return the access token
"""
try:
logger.info('login as user {username}'.format(us... | normal | {
"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 time
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtSql import *
from PyQt5.QtWidgets import *
from qgis.core import QgsFeature, QgsGeometry, QgsProject
from shapely import wkb
print(__name__)
# Function definition
def TicTocGenerator():
# Generator that returns time differences
ti... | normal | {
"blob_id": "73ff1444b5ab1469b616fe449ee6ab93acbbf85a",
"index": 918,
"step-1": "import time\nfrom PyQt5.QtCore import *\nfrom PyQt5.QtGui import *\nfrom PyQt5.QtSql import *\nfrom PyQt5.QtWidgets import *\nfrom qgis.core import QgsFeature, QgsGeometry, QgsProject\nfrom shapely import wkb\n\nprint(__name__)\n\n\... | [
0
] |
from tw.core import *
| normal | {
"blob_id": "ea25aedc4728c18ac3d5da22c76cb7f1ef65e827",
"index": 4958,
"step-1": "<mask token>\n",
"step-2": "from tw.core import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from django.conf.urls import url
from django.contrib import admin
from comments.api.views import CommentListAPIView, CommentDetailAPIView
urlpatterns = [
url(r'^$', CommentListAPIView.as_view(), name='list'),
url(r'^(?P<pk>\d+)/$', CommentDetailAPIView, name='detail'),
]
| normal | {
"blob_id": "e08820ff4fb35a3770fcb110ef7181aad1abbae5",
"index": 8778,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', CommentListAPIView.as_view(), name='list'), url(\n '^(?P<pk>\\\\d+)/$', CommentDetailAPIView, name='detail')]\n",
"step-3": "from django.conf.urls import url... | [
0,
1,
2,
3
] |
from django.contrib import admin
from django.urls import path, include
from .views import hindex,galeria,mision_vision,direccion,registro,login,logout_vista,registro_insumo,admin_insumos
urlpatterns = [
path('',hindex,name='HINDEX'),
path('galeria/',galeria,name='GALE'),
path('mision/',mision_vision,name=... | normal | {
"blob_id": "dff5a46c6f1eb715fe5e1eec87e42ceb295b0eae",
"index": 4650,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', hindex, name='HINDEX'), path('galeria/', galeria,\n name='GALE'), path('mision/', mision_vision, name='MISION'), path(\n 'direccion/', direccion, name='UBICA... | [
0,
1,
2,
3
] |
import sys
import queue as q
from utils import *
LETTERS = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
lines = sys.stdin.readlines()
i_max = len(lines)
j_max = len(lines[0])
deltas = [
((0, 0), (0, 1), (0, 2)),
((0, 1), (0, 2), (0, 0)),
((0, 0), (1, 0), (2, 0)),
((1, 0), (2, 0), (0, 0)),
]
p... | normal | {
"blob_id": "973fc3a973d952cb0f192221dfda63e255e4a8a0",
"index": 2543,
"step-1": "<mask token>\n\n\ndef nextsteps(point):\n for ns in nextsteps2d(point):\n yield ns\n if point in portals:\n yield portals[point]\n\n\ndef should_visit(point):\n return lines[point[0]][point[1]] == '.'\n\n\n<m... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python3
import math
from PIL import Image as Image
# NO ADDITIONAL IMPORTS ALLOWED!
def in_bound(dim , s):
"""Get inbound pixel coordinate for out-of-bound
Args:
dim (int): Image height or width
s (int): Coordinate
Returns:
int: Inbound
"""
if s <= -1:
... | normal | {
"blob_id": "591b1a2e245ae0f3c9b2a81769bbf5988574ed07",
"index": 8253,
"step-1": "<mask token>\n\n\ndef in_bound(dim, s):\n \"\"\"Get inbound pixel coordinate for out-of-bound\n\n Args:\n dim (int): Image height or width\n s (int): Coordinate \n\n Returns:\n int: Inbound\n \"\"\"... | [
8,
10,
13,
15,
16
] |
x = int(input("Enter number:"))
y = x/2
print(y)
for i in
| normal | {
"blob_id": "79c6b7c3d23248f249b55af1d097a66a78a2c22f",
"index": 9164,
"step-1": "x = int(input(\"Enter number:\"))\ny = x/2\nprint(y)\n\nfor i in \n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
import pytest
from time import sleep
from timeflux.helpers.background import Task
class DummyWorker():
def echo(self, message='hello', delay=0, fail=False):
sleep(delay)
if fail: raise Exception('failed')
self.message = message
return(self.message)
def test_default(working_path):
... | normal | {
"blob_id": "d2e46944ab05c5e8c1979101728b7b25900be342",
"index": 415,
"step-1": "<mask token>\n\n\nclass DummyWorker:\n\n def echo(self, message='hello', delay=0, fail=False):\n sleep(delay)\n if fail:\n raise Exception('failed')\n self.message = message\n return self.me... | [
4,
5,
7,
9,
10
] |
#!/bin/python3
import sys
from collections import deque
def connectedCell(matrix,n,m):
# Complete this function
visit = []
for j in range(n):
a = []
for i in range(m):
a.append(True)
visit.append(a)
#print(visit)
path = 0
for i in range(n):
for j in ... | normal | {
"blob_id": "25a159ca2abf0176135086324ab355d6f5d9fe9e",
"index": 5054,
"step-1": "<mask token>\n\n\ndef connectedCell(matrix, n, m):\n visit = []\n for j in range(n):\n a = []\n for i in range(m):\n a.append(True)\n visit.append(a)\n path = 0\n for i in range(n):\n ... | [
1,
2,
3,
4,
5
] |
import random
'''
通用文件头，浏览器访问时随机选择
'''
user_agent = [
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"Mozilla/5.0 (Windows; U; Windows NT 6.1; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"Mozilla/5.... | normal | {
"blob_id": "5ed91b98ece3ac9525e9d2c42db9c9d9912d5ed2",
"index": 9029,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_user_agent():\n return {'User-Agent': random.choice(user_agent)}\n",
"step-3": "<mask token>\nuser_agent = [\n 'Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us... | [
0,
1,
2,
3,
4
] |
# template for "Guess the number" mini-project
# input will come from buttons and an input field
# all output for the game will be printed in the console
import simplegui
import random
import math
# initialize global variables used in your code
range = 100
guesses_made = 0
guesses_remaining = 0
highest_guess = 0
lowes... | normal | {
"blob_id": "783326ccec31dc7a0ff46c5e4b69806e99aeda57",
"index": 9136,
"step-1": "# template for \"Guess the number\" mini-project\n# input will come from buttons and an input field\n# all output for the game will be printed in the console\nimport simplegui\nimport random\nimport math\n\n# initialize global vari... | [
0
] |
'''
This module is used for handling the button.
'''
import RPi.GPIO as GPIO
from aiy.voicehat import *
class Button:
status = bool() #status indicates whether it is supposed to be on or off.
LED_pin = 25 #Pin for the LED in the button in the Google AIY kit.
button_pin = 23#... | normal | {
"blob_id": "878937e19d6a48a0d44309efbac1d41c208ce849",
"index": 6195,
"step-1": "<mask token>\n\n\nclass Button:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def read_button(self):\n self.status = GPIO.input(self.button_pin)\n\n def light(self, stat):\n if stat... | [
4,
5,
6,
7,
8
] |
# -*- coding:utf-8 -*-
'''
Created on 2013. 4. 30.
@author: Hwang-JinHwan
parsing the txt file which are generated by coping the pdf nova praxis rpg rule book
to create bootstrap document
'''
import re
import codecs
template = """
<head>
<style type="text/css">
body {{
padding-... | normal | {
"blob_id": "c036621c5f03d94987b4da004d063d11a7cc8424",
"index": 4418,
"step-1": "# -*- coding:utf-8 -*-\r\n'''\r\nCreated on 2013. 4. 30.\r\n\r\n@author: Hwang-JinHwan\r\n\r\nparsing the txt file which are generated by coping the pdf nova praxis rpg rule book \r\nto create bootstrap document\r\n'''\r\nimport re... | [
0
] |
import user
# or from user import User
from post import Post
app_user_one = user.User("rr@gg.com", "Riks R", "ppp1", "student")
app_user_one.get_user_info()
app_user_one.change_status("in job market")
app_user_one.get_user_info()
app_user_two = user.User("z43@gg.com", "Bobby L", "zz1", "student")
app_user_two.get_us... | normal | {
"blob_id": "f59db28b669a41051cc6d0d4b8e14d1c7b0edd11",
"index": 2555,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_user_one.get_user_info()\napp_user_one.change_status('in job market')\napp_user_one.get_user_info()\n<mask token>\napp_user_two.get_user_info()\n<mask token>\nnew_post.get_post_info()... | [
0,
1,
2,
3,
4
] |
import copy
from typing import List, Optional, Tuple, NamedTuple, Union, Callable
import torch
from torch import Tensor
from torch_sparse import SparseTensor
import time
import torch_quiver as qv
from torch.distributed import rpc
def subgraph_nodes_n(nodes, i):
row, col, edge_index = None, None, None
return r... | normal | {
"blob_id": "3f4f396d1d18611e0248a08b42328422ca4b8146",
"index": 4766,
"step-1": "<mask token>\n\n\nclass Adj(NamedTuple):\n adj_t: SparseTensor\n e_id: Optional[Tensor]\n size: Tuple[int, int]\n <mask token>\n\n\nclass RandomIndexSampler(torch.utils.data.Sampler):\n\n def __init__(self, num_nodes... | [
12,
15,
18,
20,
21
] |
from .tc_gcc import *
class AndroidGccToolChain(GccToolChain):
def __init__(self, name, ndkDir, gccVersionStr, platformVer, archStr, prefix = "", suffix = ""):
# TODO: non-windows host platform
hostPlatform = 'windows'
installDir = os.path.join(ndkDir, 'toolchains', prefix + gccVersionStr,... | normal | {
"blob_id": "d6574cacea693517f3eaa92b4b929c2ee73da2e4",
"index": 4421,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass AndroidGccToolChain(GccToolChain):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass AndroidGccToolChain(GccToolChain):\n\n def __init__(self, name, ndkDir, gccVersi... | [
0,
1,
2,
3,
4
] |
"""Distribution script for unitreport."""
import setuptools
with open("README.md", "r") as f:
long_description = f.read()
setuptools.setup(
name="unitreport",
version="0.1.1",
author="annahadji",
author_email="annahadji@users.noreply.github.com",
description="A small unittest-based tool for ge... | normal | {
"blob_id": "7a243f5e24d81d3395cc790dface5e795b9c04e6",
"index": 4495,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('README.md', 'r') as f:\n long_description = f.read()\nsetuptools.setup(name='unitreport', version='0.1.1', author='annahadji',\n author_email='annahadji@users.noreply.git... | [
0,
1,
2,
3
] |
import pickle
import numpy as np
in_dir = "C:\\Users\\ganga\\Github\\Generative-Models\\Project\\Data\\Dynamics\\"
out_dir = f"C:\\Users\\ganga\\Github\\Generative-Models\\Project\\Data\\Dynamics\\"
# Read frames
train_frames = pickle.load( open(in_dir +'\\train_frames.pkl' , 'rb' ))
test_frames = pickle.load( open(... | normal | {
"blob_id": "e048170775c589cf0a9fb3d54c72dab4df3f1bcb",
"index": 7558,
"step-1": "<mask token>\n\n\ndef sigmoid(x):\n return 0.5 * (1 + np.tanh(0.5 * x))\n\n\ndef bernoulli_array(prob_array, dim):\n sample = np.zeros(dim)\n uni_sample = np.random.uniform(0, 1, dim)\n diff = uni_sample - prob_array\n ... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python3
import datetime, random
class State(object):
def __init__(self, name):
self.name = name
def __str__(self):
return self.name
class State_New(State):
def __init__(self):
super(State_New, self).__init__("New")
class State_Underway(State):
def __init__(sel... | normal | {
"blob_id": "e40b34f0ee51cc14615c6225a7676929e6d2876a",
"index": 2975,
"step-1": "<mask token>\n\n\nclass State_Underway(State):\n\n def __init__(self):\n super(State_Underway, self).__init__('Underway')\n\n\nclass State_Paused(State):\n\n def __init__(self):\n super(State_Paused, self).__ini... | [
25,
26,
30,
31,
34
] |
class Solution(object):
def checkSubarraySum(self, nums, k):
if not nums or len(nums) == 1:
return False
sum_array = [0] * (len(nums) + 1)
for i, num in enumerate(nums):
sum_array[i + 1] = sum_array[i] + num
if k == 0:
if sum_array[-1] == 0:
... | normal | {
"blob_id": "033973ddc81a5fdf0e40009c4f321215fe3f4217",
"index": 6779,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n",
"step-3": "class Solution(object):\n\n def checkSubarraySum(self, nums, k):\n if not nums or len(nums) == 1:\n return False\n ... | [
0,
1,
2
] |
__author__ = 'Freek'
__build__ = 'versie 1.0'
from iNStagram.file_io.fileio import lees_stationgegevens
from iNStagram.api_requests.app_requests import request_instagram
from tkinter import *
startscherm = Tk()
startscherm.title('Foto of video in de buurt!')
startscherm.minsize(width=790, height=600, )
startscherm.c... | normal | {
"blob_id": "2804d49fc9f0e40859de1e8eb4f04a849639b1d4",
"index": 8277,
"step-1": "<mask token>\n\n\ndef weergeef_instagram_links():\n \"\"\"\n Geeft de bijbehorende station dict uit de lijst van alle stations (in de NS API)\n :param stationnaam: geef ofwel kort, middel als lange stationnaam om de bijbeh... | [
1,
2,
3,
4,
5
] |
#! python3
import os
import shutil
import re
import argparse
def create_test_file(filename):
with open(filename, "w") as f:
f.write("foobar")
def create_test_files(test_dir, file_prefix):
if os.path.exists(test_dir):
shutil.rmtree(test_dir)
os.mkdir(test_dir)
for i in range(1, 10):
... | normal | {
"blob_id": "db684185c2b0a26cb101dc40090c84b64c554eeb",
"index": 2595,
"step-1": "<mask token>\n\n\ndef create_test_file(filename):\n with open(filename, 'w') as f:\n f.write('foobar')\n\n\n<mask token>\n\n\ndef main():\n parser = argparse.ArgumentParser(description='Filling In The Gaps program')\n ... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
import sys
from static_pipeline import render
from static_pipeline.lib import argparse
if __name__ == "__main__":
""" Use argparse to decide what to do
"""
# set up arg parsing
parser = argparse.ArgumentParser(
description='render and rearrange files ' \
... | normal | {
"blob_id": "348676e43e4dfbbe7cd0c0527acb8c613d3d1ebc",
"index": 6301,
"step-1": "#!/usr/bin/env python\nimport sys\nfrom static_pipeline import render\nfrom static_pipeline.lib import argparse\n\nif __name__ == \"__main__\":\n \"\"\" Use argparse to decide what to do\n \"\"\"\n # set up arg parsing\n ... | [
0
] |
def largestVar(s: str):
freq = {i:0 for i in range(26)}
for i in range(len(s)):
freq[(int) (chr(i) - 'a')] += 1
max_var = 0
for a in range(26):
for b in range(26):
left_a = freq[a]
left_b = freq[b]
| normal | {
"blob_id": "4bd2923381cd3ead9a5605363a86f41b3743bf27",
"index": 7223,
"step-1": "<mask token>\n",
"step-2": "def largestVar(s: str):\n freq = {i: (0) for i in range(26)}\n for i in range(len(s)):\n freq[int(chr(i) - 'a')] += 1\n max_var = 0\n for a in range(26):\n for b in range(26):... | [
0,
1,
2
] |
#Displaying multiple images using matplotlib
import pandas as pd
import numpy as np
import cv2
import matplotlib.pyplot as plt
def main():
imgpath1="C:\Shreyas\OpenCv\DIP_OpenCV\lena.png"
imgpath2="C:\Shreyas\OpenCv\DIP_OpenCV\lena.png"
img1=cv2.imread(imgpath1,1)
img2=cv2.imread(imgpath2,... | normal | {
"blob_id": "2867a7b24b4911b2936cb34653fa57431c14d6a3",
"index": 7319,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n imgpath1 = 'C:\\\\Shreyas\\\\OpenCv\\\\DIP_OpenCV\\\\lena.png'\n imgpath2 = 'C:\\\\Shreyas\\\\OpenCv\\\\DIP_OpenCV\\\\lena.png'\n img1 = cv2.imread(imgpath1, 1)... | [
0,
1,
2,
3,
4
] |
"""
This is a big integer challenge. You are given an integer which is a **perfect
square**. It is composed of 40 or more digits. Compose a function which will
find the exact square root of this integer.
### Examples
square_root(152415787532388367501905199875019052100) ➞ 12345678901234567890
square_ro... | normal | {
"blob_id": "f9b53df799b3e6b71282c84a625ea5915ccb8014",
"index": 1966,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef square_root(n):\n start = 1\n end = n\n if n == 0 or n == 1:\n return n\n while start <= end:\n mid = (start + end) // 2\n if mid * mid == n:\n ... | [
0,
1,
2
] |
lista = []
z = 0
j = 9
for i in range(0, 10):
lista.append(int(input()))
while z < j:
c = lista[z]
lista[z] = lista[j]
lista[j] = c
z += 1
j -= 1
print(lista)
| normal | {
"blob_id": "01ede703e36268dc9b3331b21726c24674a43817",
"index": 1338,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, 10):\n lista.append(int(input()))\nwhile z < j:\n c = lista[z]\n lista[z] = lista[j]\n lista[j] = c\n z += 1\n j -= 1\nprint(lista)\n",
"step-3": "li... | [
0,
1,
2
] |
from base_page import Base_Page
import locators
class Product_Object:
"Page Object for the table"
#locators
def get_all_text(self):
"Get the text within the table"
table_text = []
row_doms = self.get_elements(self.rows_xpath)
for index,row_dom in enumerate(row_doms):
... | normal | {
"blob_id": "aebc8665a97ab0a71b1d8a920b5cbf2643254883",
"index": 479,
"step-1": "<mask token>\n\n\nclass Product_Object:\n <mask token>\n\n def get_all_text(self):\n \"\"\"Get the text within the table\"\"\"\n table_text = []\n row_doms = self.get_elements(self.rows_xpath)\n for... | [
4,
6,
8,
11,
12
] |
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
] |
import urllib.request
import json
import dml, prov.model
import datetime, uuid
import geojson
# import csv
"""
Skelton file provided by lapets@bu.edu
Heavily modified by bmroach@bu.edu
City of Boston Open Spaces (Like parks, etc)
Development notes:
"""
class retrieve_open_space(dml.Algorithm):
contributor = '... | normal | {
"blob_id": "2c82dd33180a7442607e5cbedf8846bd72b37150",
"index": 9914,
"step-1": "<mask token>\n\n\nclass retrieve_open_space(dml.Algorithm):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @staticmethod\n def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=Non... | [
2,
3,
4,
5,
6
] |
from sklearn.base import BaseEstimator
class movingAverage(BaseEstimator):
'''Implements a moving average.'''
def __init__(self, lag):
self.lag = lag
def movingAverage(self, periods=5):
'''Implements a naiveLV forecast.'''
try:
# sets data
x = self.data['Values']
d = ... | normal | {
"blob_id": "f4e45c19105d4ee1520acc0cd61dadfe27904d0f",
"index": 8134,
"step-1": "from sklearn.base import BaseEstimator\n\n\nclass movingAverage(BaseEstimator):\n '''Implements a moving average.'''\n\n def __init__(self, lag):\n self.lag = lag\n\ndef movingAverage(self, periods=5):\n '''Implemen... | [
0
] |
#!/usr/local/bin/python3
from sys import stdin
import argparse
# Default values
alignment = 'l'
border = 'none'
stretch_factor = '1.0'
toprule = ''
# Default options
custom_header = False
standalone = False
stretch = False
booktabs = False
# Parsing command-line options
parser = argparse.ArgumentParser('<stdin> | cs... | normal | {
"blob_id": "591ac07e735e08bcafa8274eb1a1547a01261f55",
"index": 8430,
"step-1": "<mask token>\n\n\ndef rule(type):\n if booktabs:\n if type == 'top':\n return '\\\\toprule'\n if type == 'mid':\n return '\\\\midrule'\n if type == 'bottom':\n return '\\\\bo... | [
2,
3,
4,
5,
6
] |
# Copyright 2013 Rackspace Hosting Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | normal | {
"blob_id": "cf931da4c06e16fe6f6da5eb1826d8b7a59c1f7b",
"index": 9057,
"step-1": "<mask token>\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = ... | [
37,
43,
48,
57,
67
] |
# encoding: utf-8
"""
File: demo.py
Author: Rock Johnson
Description: 此文件为案例文件
"""
import sys
sys.path.append('../')
try:
from panicbuying.panic import Panic
except:
from panicbuying.panicbuying.panic import Panic
def main():
'''
公共参数:
store: 商城或书店名称(小米|文泉), browser: 浏览器(目前只支持Chrome),
versio... | normal | {
"blob_id": "2f8dff78f5bc5ed18df97e2574b47f0a7711d372",
"index": 547,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n \"\"\"\n 公共参数:\n store: 商城或书店名称(小米|文泉), browser: 浏览器(目前只支持Chrome),\n version: 浏览器版本号, quit: 运行完后是否退出浏览器(默认不退出),\n hidden: 是否启用界面(默认启用),\n\n 商城抢购:\n u... | [
0,
1,
2,
3,
4
] |
# 使用celery
from django.conf import settings
from django.core.mail import send_mail
from django.template import loader,RequestContext
from celery import Celery
import time
# 在任务处理者一
#
# 端加的代码
import os
import django
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "dailyfresh.settings")
django.setup()
from goods.models ... | normal | {
"blob_id": "7f7d087b7001cd7df01d4f22e056809be5a35568",
"index": 9584,
"step-1": "<mask token>\n\n\n@app.task\ndef generate_static_index_html():\n \"\"\"产生首页静态页面\"\"\"\n types = GoodsType.objects.all()\n goods_banners = IndexGoodsBanner.objects.all().order_by('index')\n promotion_banners = IndexPromo... | [
1,
2,
4,
5,
6
] |
'''
Given an array of ints length 3, return an array with the elements "rotated
left" so {1, 2, 3} yields {2, 3, 1}.
rotate_left3([1, 2, 3]) → [2, 3, 1]
rotate_left3([5, 11, 9]) → [11, 9, 5]
rotate_left3([7, 0, 0]) → [0, 0, 7]
'''
#卡了很久，还是列表的基本操作不太熟
#参考：https://zhidao.baidu.com/question/1244520812319200859.html
def r... | normal | {
"blob_id": "b7ebee3c96fd9cd3d8ddc69838363925085a944d",
"index": 1347,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef rotate_left3(nums):\n if len(nums) < 3:\n return 0\n nums.append(nums[0])\n del nums[0]\n return nums\n",
"step-3": "'''\nGiven an array of ints length 3, ret... | [
0,
1,
2
] |
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'AND BREAK CHAR COLON COMA CTE_F CTE_I CTE_STRING DETERMINANT DIFFERENT DIVIDE DO DOUBLEEQUAL ELSE EQUAL FLOAT FROM FUNCTION ID IF INPUT INT INVERSA LBRACE LCORCH LOWERE... | normal | {
"blob_id": "160f272edd8283ea561552f22c71967db4a1660a",
"index": 7983,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _k, _v in _lr_action_items.items():\n for _x, _y in zip(_v[0], _v[1]):\n if not _x in _lr_action:\n _lr_action[_x] = {}\n _lr_action[_x][_k] = _y\ndel _lr_... | [
0,
1,
2,
3
] |
class Odwroc():
def __init__(self,dane):
self.dane = dane
self.indeks = len(dane)
def __iter__(self):
return self
def __next__(self):
if self.indeks == 0:
raise StopIteration
self.indeks -= 1
return self.dane[self.indeks]
for i in Odwroc('Martu... | normal | {
"blob_id": "763c0baf919b48ff135f7aa18974da5b85ee40f5",
"index": 1133,
"step-1": "class Odwroc:\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Odwroc:\n\n def __init__(self, dane):\n self.dane = dane\n self.indeks = len(dane)\n <mask token>\n\n ... | [
1,
3,
4,
5,
6
] |
"""
This is the main script
"""
import datetime
import sqlite3
from sqlite3 import Error
import nltk.sentiment
from chatterbot import ChatBot
from pythonosc import udp_client
def _create_connection(db_file):
""" Create a database connection to the SQLite database """
try:
conn = sqlite3.connect(db_fi... | normal | {
"blob_id": "2b8b5b893d61d11d2795f5be96fde759256a15e8",
"index": 9741,
"step-1": "<mask token>\n\n\ndef _create_connection(db_file):\n \"\"\" Create a database connection to the SQLite database \"\"\"\n try:\n conn = sqlite3.connect(db_file)\n cur = conn.cursor()\n cur.execute('CREATE ... | [
2,
3,
4,
5,
6
] |
"""Unit tests for the `esmvalcore.preprocessor._rolling_window` function."""
import unittest
import iris.coords
import iris.exceptions
import numpy as np
from cf_units import Unit
from iris.cube import Cube
from numpy.testing import assert_equal
from esmvalcore.preprocessor._rolling_window import rolling_window_stati... | normal | {
"blob_id": "9539d2a4da87af1ff90b83bbcf72dfc8ab7b6db0",
"index": 5501,
"step-1": "<mask token>\n\n\nclass TestRollingWindow(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Te... | [
1,
7,
8,
9,
11
] |
# DO NOT EDIT THIS FILE!
#
# Python module managedElementManager generated by omniidl
import omniORB
omniORB.updateModule("managedElementManager")
# ** 1. Stub files contributing to this module
import managedElementManager_idl
# ** 2. Sub-modules
# ** 3. End
| normal | {
"blob_id": "7727896d4e1b2b415c398b206f9fb7e228e6f26d",
"index": 8602,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nomniORB.updateModule('managedElementManager')\n<mask token>\n",
"step-3": "import omniORB\nomniORB.updateModule('managedElementManager')\nimport managedElementManager_idl\n",
"step-4"... | [
0,
1,
2,
3
] |
# coding=utf-8
"""
author = jamon
""" | normal | {
"blob_id": "00790b9d2648d19a37d1d1864e7fdeab0f59f764",
"index": 4266,
"step-1": "<mask token>\n",
"step-2": "# coding=utf-8\n\"\"\"\nauthor = jamon\n\"\"\"",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from enum import Enum
from roll.input import Input
from roll.network import Server, Client
from assets.game_projects.fighter.src.game_properties import GameProperties
from assets.game_projects.fighter.src.network_message import NetworkMessage
class InputBuffer:
"""
Responsible for collecting game input from... | normal | {
"blob_id": "4789546128263bd298f8f5827734f8402747b9ac",
"index": 67,
"step-1": "<mask token>\n\n\nclass OutgoingNetworkInputBuffer(InputBuffer):\n <mask token>\n <mask token>\n\n\nclass IncomingNetworkInputBuffer(InputBuffer):\n\n def __init__(self, frame_limit=12):\n super().__init__(left_action... | [
5,
12,
13,
15,
21
] |
from django.shortcuts import *
from shop.models import *
from django.db import transaction
from django.core.exceptions import *
@transaction.atomic
def computers(request):
ctx = {}
computer = Computer.objects.all()
ctx['brand'] = Brand.objects.all()
if request.method == 'POST':
if request.POST['computer_i... | normal | {
"blob_id": "18689741a33e6d17e694ee0619a1f36d8d178cbb",
"index": 3223,
"step-1": "<mask token>\n\n\n@transaction.atomic\ndef computers(request):\n ctx = {}\n computer = Computer.objects.all()\n ctx['brand'] = Brand.objects.all()\n if request.method == 'POST':\n if request.POST['computer_id'] !... | [
1,
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
"""
Created on Sat Oct 20 07:48:47 2018
@author: hfuji
"""
import os
from PIL import Image
import glob
import shutil
src_jpg_dir = 'D:/Develop/data/VOCdevkit/VOC2007/JPEGImages/'
dst_bmp_dir = 'D:/Temp/'
jpg_files = glob.glob(src_jpg_dir + '*.jpg')
cnt = 0
for jpg_file in ... | normal | {
"blob_id": "a57059927a7bd3311c1d104bfc80877912c7d995",
"index": 125,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor jpg_file in jpg_files:\n basename = os.path.basename(jpg_file)\n if int(basename[:-4]) % 10 == 0:\n cnt += 1\n dirname = os.path.dirname(jpg_file)\n dirs = d... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/python3
"""1. Divide a matrix """
def matrix_divided(matrix, div):
"""Divides a Matrix
Args:
matrix: A list of lists of ints or floats
div: a non zero int or float
Exceptions:
TypeError: if the matrix and/or div is not as stated or the matrix elements
are not of the... | normal | {
"blob_id": "95c5971a102fb2ed84ab0de0471278d0167d8359",
"index": 22,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef matrix_divided(matrix, div):\n \"\"\"Divides a Matrix\n\n Args:\n matrix: A list of lists of ints or floats\n div: a non zero int or float\n\n Exceptions:\n TypeEr... | [
0,
1,
2
] |
# Generated by Django 3.2.3 on 2021-06-19 11:27
import django.core.validators
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='BillDetail',
... | normal | {
"blob_id": "b7a8e4105f1c1c532eaae27afae14e9a4f2ddfba",
"index": 2915,
"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
] |
import os
import shutil
def flatCopyWithExt(srcDir, dstDir, ext):
if not os.path.exists(dstDir):
os.makedirs(dstDir)
for basename in os.listdir(srcDir):
if basename.endswith(ext):
pathname = os.path.join(srcDir, basename)
if os.path.isfile(pathname):
shutil.copy2(pathname, dstDir)
def move... | normal | {
"blob_id": "649c0c0f170b50fe51f5eaf11908e968f66625c9",
"index": 5925,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef moveSDLIncludes():\n flatCopyWithExt('./ext/SDL2/core/code/include/',\n './ext/SDL2/core/include/', '.h')\n flatCopyWithExt('./ext/SDL2/SDL2-image/code/',\n '.... | [
0,
1,
2,
3,
4
] |
import torch
import torch.nn as nn
import torch.optim as optim
import torchtext
import absl.flags
import absl.app
import pickle
import yaml
import numpy as np
from tqdm import tqdm
from core import model
import core.dnc.explanation
from core import functions
from core.config import ControllerConfig, MemoryConfig, Train... | normal | {
"blob_id": "00dbcae2d3941c9ef4c8b6753b8f6f7a46417400",
"index": 5110,
"step-1": "<mask token>\n\n\ndef run_explanations(network, explanation_module, data_iterator):\n network.eval()\n best_accuracy = 0\n worst_accuracy = 0\n best_correct = 0\n worst_correct = 0\n covered = 0\n total = 0\n ... | [
3,
5,
6,
7,
9
] |
# -*- coding: utf-8 -*-
# Project = https://github.com/super-l/search-url.git
# Author = superl
# Blog = www.superl.org QQ:86717375
# Team = Code Security Team(C.S.T) | 铭剑创鼎
import urllib2
import re
import ConfigParser
from lib.filter import *
from lib.getdata import *
from lib.count import *
from lib.status... | normal | {
"blob_id": "b724b04c6303cc9021539ad7df5a198000491029",
"index": 5436,
"step-1": "<mask token>\n\n\nclass Baidu:\n <mask token>\n <mask token>\n\n def __init__(self, count):\n cfg = ConfigParser.ConfigParser()\n cfg.read('config/setting.conf')\n self.baidu_page_size = int(cfg.get('s... | [
2,
3,
4,
5,
6
] |
# B. A New Technique
# TLE (Time limit exceeded)
from sys import stdin, stdout
t = int(input())
for _ in range(t):
n, m = map(int, input().split())
rows = [0] * n
a_column = list()
for r in range(n):
tmp = list(input().split())
rows[r] = tmp
a_column.append(tmp[0])
sorte... | normal | {
"blob_id": "9004314951f77b14bab1aba9ae93eb49c8197a8d",
"index": 4409,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(t):\n n, m = map(int, input().split())\n rows = [0] * n\n a_column = list()\n for r in range(n):\n tmp = list(input().split())\n rows[r] = tmp\n ... | [
0,
1,
2,
3,
4
] |
from cache_replacement.double_linked_list import DoubleLinkedList
from cache_replacement.node import Node
class LRUCache:
def __init__(self, capacity):
self.capacity = capacity
self.size = 0
self.cache_map = {}
self.cache_list = DoubleLinkedList(capacity=capacity)
def get(sel... | normal | {
"blob_id": "898ff6e38e80419d61ec4bbde827e8ca729eb19a",
"index": 5202,
"step-1": "<mask token>\n\n\nclass LRUCache:\n <mask token>\n <mask token>\n\n def put(self, key, value):\n if key in self.cache_map:\n old_node = self.cache_map.get(key)\n self.cache_list.remove(old_node... | [
2,
3,
4,
5
] |
# Generated by Django 3.2.4 on 2021-06-16 13:41
import ckeditor.fields
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('FAQ', '0004_auto_20210616_1253'),
]
operations = [
migrations.RemoveField(
model_name='question',
nam... | normal | {
"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
] |
from pyrogram import Client, filters
from pyrogram.errors import MessageNotModified
from db.models import *
@Client.on_callback_query(filters.regex('^change_lg_'))
async def on_change_language(_, callback):
settings_id = int(callback.data.split('_')[2])
with db_session:
settings = SettingsInstance.g... | normal | {
"blob_id": "dd053da45d2577772414b1373ba324b0bfdc0d94",
"index": 6605,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@Client.on_callback_query(filters.regex('^change_lg_'))\nasync def on_change_language(_, callback):\n settings_id = int(callback.data.split('_')[2])\n with db_session:\n ... | [
0,
1,
2,
3
] |
from function import *
from .propogation import optimize
from .initialize import initialize_with_zeros
def predict(weight, intercept, x_vector):
"""
Predict whether the label is 0 or 1 using learned logistic regression parameters (w, b)
Arguments:
w -- weights, a numpy array of size (num_px * num_px ... | normal | {
"blob_id": "63360ec9693a916375b49d0881008b1d7d4ec953",
"index": 4546,
"step-1": "<mask token>\n\n\nclass Logistic(object):\n <mask token>\n\n def __init__(self, *args, **kwargs):\n \"\"\"\n Initializing the model parameter\n :param args:\n :param kwargs:\n X_train,\n... | [
3,
4,
5,
6,
7
] |
#Script to retrieve relevant files and paths, supply to cx_Freeze to compile into executeable
import os
# import cx_Freeze
files_list = []
dir_path = os.path.dirname(os.path.realpath(__file__))+str('/')
print(dir_path)
for root, directories, filenames in os.walk(str(dir_path)):
for file in filenames:
pat... | normal | {
"blob_id": "430dccf1001af43c2a713b08dc05d8f04818aa1f",
"index": 5597,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dir_path)\nfor root, directories, filenames in os.walk(str(dir_path)):\n for file in filenames:\n path = os.path.join(root, file)\n if path.find('/.') == -1 and pat... | [
0,
1,
2,
3,
4
] |
import pickle
from generation_code import serial_filename
import serial_output_code
import numpy as np
from shutil import copyfile
from os import remove
# This file is only temporary, mostly to be used when updating the
# reference output from a regression test, to ensure that, in all
# aspects that are in common with... | normal | {
"blob_id": "6acb253189798c22d47feb3d61ac68a1851d22ba",
"index": 1619,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n copyfile(serial_filename(), temp_filename)\n serial_output_code.serial_output_code()\n with open(serial_filename(), 'rb') as f:\n qmc_out = pickle.load(f)\n with... | [
0,
1,
2,
3,
4
] |
# importing libraries
import cv2
import numpy as np
import argparse
aq = argparse.ArgumentParser()
aq.add_argument('-i', '--input', required=True, help="input image path")
aq.add_argument('-o', '--output', help="path where you want to download the image")
args = vars(aq.parse_args())
# reading image
img = cv2.... | normal | {
"blob_id": "10cefb1cf2392fdcd368f11d0d69774a9ffa73ec",
"index": 2816,
"step-1": "<mask token>\n",
"step-2": "<mask token>\naq.add_argument('-i', '--input', required=True, help='input image path')\naq.add_argument('-o', '--output', help=\n 'path where you want to download the image')\n<mask token>\nif args[... | [
0,
1,
2,
3,
4
] |
from crispy_forms.bootstrap import FormActions
from crispy_forms.helper import FormHelper
from crispy_forms.layout import Layout, Div, Submit
from django import forms
from django.forms import RadioSelect
from django.urls import reverse
from core.models import Person, Datapackage
from core.utils import cancel_button
... | normal | {
"blob_id": "5a59108084d943f6faa07ffea1467dc19c3dd790",
"index": 1101,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass DatapackageModelForm(forms.ModelForm):\n\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n self.helper = FormHelper(self)\n se... | [
0,
2,
3,
5,
6
] |
import requests
import logging
import json
class Handler(object):
def __init__(self):
"""
This class is used to handle interaction towards coffee interface.
"""
super(Handler, self).__init__()
logging.warning('Initializing coffeeHandler....')
# get an active token ... | normal | {
"blob_id": "00228facd19c72bebd9afbbe52597e390233d41e",
"index": 5822,
"step-1": "<mask token>\n\n\nclass Handler(object):\n <mask token>\n\n def get_rsp_from_url(self, url, params=None, method='get', data=None):\n logging.warning(\n 'when using method {}, header is:\\n {} \\n data is: \\... | [
4,
6,
8,
9,
10
] |
import tensorflow as tf
import numpy as np
import tensorflow_datasets as tfds
print(tf.__version__)
imdb, info = tfds.load("imdb_reviews", with_info=True, as_supervised=True)
train_data = imdb['train']
test_data = imdb['test']
# 25000 in each set
training_sentences = []
training_labels = []
testing_sentences = []
... | normal | {
"blob_id": "921c45af3ba34a1b12657bf4189fc8dd66fa44a6",
"index": 3860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(tf.__version__)\n<mask token>\nfor s, l in train_data:\n training_sentences.append(str(s.numpy()))\n training_labels.append(l.numpy())\nfor s, l in test_data:\n testing_sen... | [
0,
1,
2,
3,
4
] |
from .dataset_readers import *
from .models import *
| normal | {
"blob_id": "bc8bf06f1adedeb7b364308591bff09ac42d6c29",
"index": 3702,
"step-1": "<mask token>\n",
"step-2": "from .dataset_readers import *\nfrom .models import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import math
def solve():
a = int(input())
b = int(input())
return math.sqrt(a * a + b * b)
print(solve())
| normal | {
"blob_id": "a22d38f7e8122d6339d1beab3bf08fa41c36d61d",
"index": 9648,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solve():\n a = int(input())\n b = int(input())\n return math.sqrt(a * a + b * b)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef solve():\n a = int(input())\n... | [
0,
1,
2,
3
] |
import numpy as np
import cv2
print("read imafe from file" )
img = cv2.imread("panda.jpg")
print("create a window holder for the image")
cv2.namedWindow("Image",cv2.WINDOW_NORMAL)
print ('display the image ')
cv2.imshow("Image",img)
print ('press a key inside the image to make a copy')
cv2.waitKey(0)
| normal | {
"blob_id": "7cf6a4b8057280b38572dd92693013724751c47f",
"index": 9502,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('read imafe from file')\n<mask token>\nprint('create a window holder for the image')\ncv2.namedWindow('Image', cv2.WINDOW_NORMAL)\nprint('display the image ')\ncv2.imshow('Image', i... | [
0,
1,
2,
3,
4
] |
# Author: Cristian Steib
#
#
# -*- encoding: utf-8 -*-
import pilasengine
class consoleColors:
HEADER = '\033[95m'
OKBLUE = '\033[94m'
OKGREEN = '\033[92m'
WARNING = '\033[93m'
FAIL = '\033[91m'
ENDC = '\033[0m'
BOLD = '\033[1m'
UNDERLINE = '\033[4m'
class BotonComando():
'''
... | normal | {
"blob_id": "266b8958b761ee7266a8098aeaecb8b6c2a24a2a",
"index": 1757,
"step-1": "<mask token>\n\n\nclass BotonComando:\n <mask token>\n\n def __init__(self, *args, **kwargs):\n self.pilas = args[0] if len(args) and type(args[0]\n ) is pilasengine.Pilas else kwargs['pilas'] if kwargs.get(... | [
10,
12,
13,
14,
19
] |
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