code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from psycopg2 import extras as ex
import psycopg2 as pg
import json
import datetime
import os
from functools import reduce
data_list = [{'projectName': '伊犁哈萨克自治州友谊医院开发区分院保洁服务项目', 'pingmu': '服务', 'purUnit': '新疆伊犁哈萨克自治州友谊医院', 'adminiArea': '新疆维吾尔自治区', 'bulletTime': '2020年09月02日 19:20', 'obtBidTime': '2020年09月02日至2020年... | normal | {
"blob_id": "e9af8f7830be7db3ca57b0a24de48ef7fcb08d6c",
"index": 8453,
"step-1": "<mask token>\n\n\ndef processJson(dic):\n dicobj = json.loads(dic)\n print(dicobj)\n for k, v in dicobj.items():\n dict_tmp = {}\n dict_tmp['file_name'] = k\n dict_tmp['urls'] = v\n print(k)\n ... | [
2,
4,
5,
6,
7
] |
from django.shortcuts import render
from django.contrib.auth.decorators import login_required
from django.views.decorators.csrf import csrf_exempt
# Create your views here.
from projects.models import Project
from django.db import connection
from .utils import namedtuplefetchall
from django.http import JsonResponse
fro... | normal | {
"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
] |
from typing import List, Tuple
import pytest
def fit_transform(*args: str) -> List[Tuple[str, List[int]]]:
if len(args) == 0:
raise TypeError('expected at least 1 arguments, got 0')
categories = args if isinstance(args[0], str) else list(args[0])
uniq_categories = set(categories)
bi... | normal | {
"blob_id": "b236abaa5e206a8244083ee7f9dcdb16741cb99d",
"index": 3072,
"step-1": "<mask token>\n\n\ndef test_str_fit_transformr():\n assert fit_transform(['Moscow', 'New York', 'Moscow', 'London']) == [(\n 'Moscow', [0, 0, 1]), ('New York', [0, 1, 0]), ('Moscow', [0, 0, 1]\n ), ('London', [1, 0,... | [
3,
4,
6,
7,
8
] |
# We don't need no stinking models but django likes this file to be there if you are an app
| normal | {
"blob_id": "a1304f290e0346e7aa2e22d9c2d3e7f735b1e8e7",
"index": 96,
"step-1": "\n# We don't need no stinking models but django likes this file to be there if you are an app\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
1
]
} | [
1
] |
from .mail_utils import send_mail
from .request_utils import get_host_url
| normal | {
"blob_id": "74b0ccb5193380ce596313d1ac3f898ff1fdd2f3",
"index": 930,
"step-1": "<mask token>\n",
"step-2": "from .mail_utils import send_mail\nfrom .request_utils import get_host_url\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import numpy as np
import initialization as init
import evaluation as eval
import selection as sel
import recombination as rec
import mutation as mut
initialize = init.permutation
evaluate = eval.custom
select = sel.rank_based
mutate = mut.swap
reproduce = rec.pairwise
crossover = rec.order
replace = sel.rank_based
par... | normal | {
"blob_id": "5eab41a2ef536365bab6f6b5ad97efb8d26d7687",
"index": 4456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor gen in range(params['gens']):\n parents = select(population, params['n_pars'])\n offspring = reproduce(params, parents, crossover)\n offspring = mutate(params, offspring)\n ... | [
0,
1,
2,
3
] |
import logging
from django.contrib.auth.models import User
import json
from django.http import HttpResponse
from enumfields.fields import EnumFieldMixin
from Api.models import Status
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def check_cookie(request):
# Post.objects.all().delete()
result = ... | normal | {
"blob_id": "2bc3b0df720788e43da3d9c28adb22b3b1be8c58",
"index": 5002,
"step-1": "<mask token>\n\n\ndef check_cookie(request):\n result = {'status': True}\n try:\n user_id = request.GET.get('user_id')\n user = User.objects.get(pk=user_id)\n cookie_status = user.profile.cookie_status\n ... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
import cgitb
import cgi
import pymysql
form = cgi.FieldStorage()
c.execute("SELECT * FROM example")
recs = c.fetchall()
records1 = """
<body>
<table>
<tbody>
<tr>
<th>Full Name</th>
<th>Average Score</th>
</tr>"""
records_dyn = [
f"<tr><td>{name}</td><td>{avg... | normal | {
"blob_id": "b5fee01582a28085983c56b9c266ef7fd5c3c927",
"index": 5132,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nc.execute('SELECT * FROM example')\n<mask token>\nprint('Content-Type:text/html; charset=utf-8')\nprint()\nfor i in records1.split('\\n'):\n print(i)\nfor i in records_dyn:\n print(... | [
0,
1,
2,
3,
4
] |
'''import pyttsx3
#engine = pyttsx3.init()
#Conficuração das vozes
#voices = engine.getProperty('voices')
#engine.setProperty('voice', voices[2].id)
engine=pyttsx3.init()
voices=engine.getProperty('voices')
engine.setProperty('voice',voices[3].id)
#Falar texto
engine.say('Olá meu nome é Jarvis. Sou uma inteligênci... | normal | {
"blob_id": "d9bf58dc76d4e8d7146fac3bb2bdfb538ebf78a5",
"index": 7102,
"step-1": "<mask token>\n",
"step-2": "'''import pyttsx3\n\n#engine = pyttsx3.init()\n\n#Conficuração das vozes\n#voices = engine.getProperty('voices')\n#engine.setProperty('voice', voices[2].id)\n\nengine=pyttsx3.init()\n\nvoices=engine.ge... | [
0,
1
] |
# -*- coding:Utf-8 -*-
from .game_action_manager import GameActionManager
from .menu_action_manager import OptionsActionManager, CharacterSelectionActionManager, MainMenuActionManager
| normal | {
"blob_id": "48294209d51fbe4dfb2a5130311a10c8a1dd027c",
"index": 9237,
"step-1": "<mask token>\n",
"step-2": "from .game_action_manager import GameActionManager\nfrom .menu_action_manager import OptionsActionManager, CharacterSelectionActionManager, MainMenuActionManager\n",
"step-3": "# -*- coding:Utf-8 -*-... | [
0,
1,
2
] |
# C8-06 p.146 Write city_country() function that takes name city and country
# Print city name then the country the city is in. call 3 times with differet pairs.
def city_country(city, country):
"""Name a city and the country it resides in seperated by a comma."""
print(f'"{city.title()}, {country.title()}"\n'... | normal | {
"blob_id": "2866ecf69969b445fb15740a507ddecb1dd1762d",
"index": 3395,
"step-1": "<mask token>\n",
"step-2": "def city_country(city, country):\n \"\"\"Name a city and the country it resides in seperated by a comma.\"\"\"\n print(f'\"{city.title()}, {country.title()}\"\\n')\n\n\n<mask token>\n",
"step-3... | [
0,
1,
2,
3
] |
#!/oasis/scratch/csd181/mdburns/python/bin/python
import sys
import pickle
import base64
from process import process
import multiprocessing as mp
EPOCH_LENGTH=.875
EPOCH_OFFSET=.125
NUM_FOLDS=5
if __name__ == "__main__":
mp.freeze_support()
p= mp.Pool(2)
for instr in sys.stdin:
this_key=''
sys.stderr.wr... | normal | {
"blob_id": "e477a59e86cfeb3f26db1442a05d0052a45c42ff",
"index": 6397,
"step-1": "#!/oasis/scratch/csd181/mdburns/python/bin/python\nimport sys\nimport pickle\nimport base64\nfrom process import process\nimport multiprocessing as mp\n\nEPOCH_LENGTH=.875\nEPOCH_OFFSET=.125\nNUM_FOLDS=5\n\nif __name__ == \"__main_... | [
0
] |
import numpy as np
import skimage
def preprocess_img(img, size):
img = np.rollaxis(img, 0, 3) # It becomes (640, 480, 3)
img = skimage.transform.resize(img, size)
img = skimage.color.rgb2gray(img)
return img
# data = minerl.data.make("MineRLNavigateDense-v0", data_dir="../dataset/navigate")
#
# # I... | normal | {
"blob_id": "9706b9ba81f41b131c364a16bb17a0c1e31e3a04",
"index": 6608,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef preprocess_img(img, size):\n img = np.rollaxis(img, 0, 3)\n img = skimage.transform.resize(img, size)\n img = skimage.color.rgb2gray(img)\n return img\n",
"step-3": ... | [
0,
1,
2,
3
] |
# !/usr/bin/env python
# -*- coding: utf-8 -*-
# tail -2 hightemp.txt
import sys
with open(sys.argv[1]) as f:
lines = f.readlines();
n = sys.argv[2];
print "".join(lines[len(lines)-int(n):]) | normal | {
"blob_id": "a1710ee228a432db92c9586ddff0bfcad1f434a8",
"index": 2088,
"step-1": "# !/usr/bin/env python\n# -*- coding: utf-8 -*-\n# tail -2 hightemp.txt\n\n\nimport sys\n\nwith open(sys.argv[1]) as f:\n lines = f.readlines();\n\nn = sys.argv[2];\n\nprint \"\".join(lines[len(lines)-int(n):])",
"step-2": nul... | [
0
] |
from datetime import datetime
import time
from os import system
import RPi.GPIO as GPIO
import firebase_admin
from firebase_admin import credentials
from firebase_admin import db
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)
GPIO.setup(21, GPIO.OUT) # este pin es de salida carro
GPIO.setup(26, GPIO.OUT) # este pin es... | normal | {
"blob_id": "0972bd1241ad91f54f8dfde6327ee226c27bf2ca",
"index": 9747,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nGPIO.setwarnings(False)\nGPIO.setmode(GPIO.BCM)\nGPIO.setup(21, GPIO.OUT)\nGPIO.setup(26, GPIO.OUT)\nGPIO.setup(19, GPIO.OUT)\nGPIO.setup(13, GPIO.OUT)\nGPIO.setup(6, GPIO.OUT)\nGPIO.setu... | [
0,
1,
2,
3,
4
] |
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import PowerTransformer
from sklearn.preprocessing import RobustScaler
from sklearn.preprocessing import Normalizer
from sklearn.preprocessing import MinMaxScaler
import pandas as pd
import numpy as np
def preprocess_transformers(y_train, tra... | normal | {
"blob_id": "890d50c741ffd576312c63dc450e274b4517bf12",
"index": 9856,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef preprocess_transformers(y_train, transf):\n if transf != 'ln':\n if transf == 'minmax':\n scaler = MinMaxScaler()\n scaler2 = MinMaxScaler()\n ... | [
0,
2,
3,
4,
5
] |
DATABASE_NAME = "user_db" | normal | {
"blob_id": "8c8bbbc682889c8d79c893f27def76ad70e8bf8d",
"index": 233,
"step-1": "<mask token>\n",
"step-2": "DATABASE_NAME = 'user_db'\n",
"step-3": "DATABASE_NAME = \"user_db\"",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
#!/usr/bin/env python
from __future__ import print_function
import weechat
import sys
import pickle
import json
import math
import os.path
from datetime import datetime
from datetime import date
from datetime import timedelta
from dateutil.parser import parse as datetime_parse
from os.path import expanduser
from goog... | normal | {
"blob_id": "0ed0fb6f9bcc768bb005222c9ae9b454f6d962ec",
"index": 9148,
"step-1": "<mask token>\n\n\ndef _load_credentials(creds_file=None):\n \"\"\"Loads the credentials from a credentials.json file or by prompting for authentication.\n Returns a credentials object to be used by the Google Sheets API.\n ... | [
7,
10,
11,
12,
13
] |
#!/usr/bin/python -tt
# snmp3_test
# Claudia
# PyCharm
__author__ = "Claudia de Luna (claudia@indigowire.net)"
__version__ = ": 1.0 $"
__date__ = "10/23/16 11:25 AM"
__copyright__ = "Copyright (c) 2015 Claudia de Luna"
__license__ = "Python"
#from __future__ import print_function
import sys
import snmp_helper
# P... | normal | {
"blob_id": "ccdae522983ddc7c02e221ab5c1bc32683358a7b",
"index": 2883,
"step-1": "#!/usr/bin/python -tt\n# snmp3_test\n# Claudia\n# PyCharm\n__author__ = \"Claudia de Luna (claudia@indigowire.net)\"\n__version__ = \": 1.0 $\"\n__date__ = \"10/23/16 11:25 AM\"\n__copyright__ = \"Copyright (c) 2015 Claudia de Lun... | [
0
] |
# Any object containing execute(self) method is considered to be IDE App
# this is Duck typing concept
class PyCharm:
def execute(self):
print("pycharm ide runnig")
class MyIde:
def execute(self):
print("MyIde running")
class Laptop:
def code(self,ide):
ide.execut... | normal | {
"blob_id": "9ab3dd87f17ac75a3831e9ec1f0746ad81fad70d",
"index": 501,
"step-1": "<mask token>\n\n\nclass MyIde:\n <mask token>\n\n\nclass Laptop:\n\n def code(self, ide):\n ide.execute()\n\n\n<mask token>\n",
"step-2": "class PyCharm:\n <mask token>\n\n\nclass MyIde:\n\n def execute(self):\n... | [
3,
5,
7,
8,
9
] |
__version__ = '1.1.3rc0'
| normal | {
"blob_id": "2e5bbc8c6a5eac2ed71c5d8619bedde2e04ee9a6",
"index": 4932,
"step-1": "<mask token>\n",
"step-2": "__version__ = '1.1.3rc0'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import numpy
#calculate field of simple
def dipole(x, y, z, dx, dy, dz, mx, my, mz):
R = (x - dx)**2 + (y - dy)**2 + (z - dz)**2
return (3.0*(x - dx) * ((x - dx)*mx + (y - dy)*my + (z - dz)*mz) / R**2.5 - mx/R**1.5,
3.0*(y - dy) * ((x - dx)*mx + (y - dy)*my + (z - dz)*mz) / R**2.5 - my/R**1.5,
... | normal | {
"blob_id": "9d37d1618fb9d00d63b7ed58290c5ba1b8f106cd",
"index": 4599,
"step-1": "import numpy \n\n#calculate field of simple \ndef dipole(x, y, z, dx, dy, dz, mx, my, mz):\n R = (x - dx)**2 + (y - dy)**2 + (z - dz)**2\n return (3.0*(x - dx) * ((x - dx)*mx + (y - dy)*my + (z - dz)*mz) / R**2.5 - mx/R**1.5... | [
0
] |
import pymysql
db= pymysql.connect(host = 'localhost',
port = 3306,
user = 'root',
password = 'Wubaba950823',
database = 'mydb',
charset = 'utf8mb4'
)
# 使用cursor()方法获取操作游标
curso... | normal | {
"blob_id": "8566e30a6450a72a0e441155321bd03363944b5a",
"index": 8236,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(sql)\ntry:\n cursor.execute(sql)\n db.commit()\nexcept:\n db.rollback()\ndb.close()\n",
"step-3": "<mask token>\ndb = pymysql.connect(host='localhost', port=3306, user='r... | [
0,
1,
2,
3,
4
] |
from day19.rules import Rule, CharacterMatch, OrRule, ListRule
def parse_rule(rules: dict, rule_str: str=None) ->Rule:
if rule_str is None:
rule_str: str = rules[0]
if '"' in rule_str:
return CharacterMatch(rule_str.strip('"'))
elif '|' in rule_str:
or_rules = [parse_rule(rules, pa... | normal | {
"blob_id": "4d4f7db6d5b4ed7eac3ced73aca76d3c952c84f4",
"index": 1456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_rule(rules: dict, rule_str: str=None) ->Rule:\n if rule_str is None:\n rule_str: str = rules[0]\n if '\"' in rule_str:\n return CharacterMatch(rule_str.s... | [
0,
1,
2,
3
] |
import matplotlib.pyplot as plt
import matplotlib
import matplotlib.colors as colors
import matplotlib.cm as cm
def plot_hist(data_list):
plt.hist(data_list, bins=500)
plt.show()
return
def compare_hits_plot(np_array, compare=False):
if compare:
clist = list(np_array[:,2])
minima, maxima = ... | normal | {
"blob_id": "b6adb956aed934451fc21e51663be36d08c5b645",
"index": 2535,
"step-1": "import matplotlib.pyplot as plt\nimport matplotlib\nimport matplotlib.colors as colors\nimport matplotlib.cm as cm\n\ndef plot_hist(data_list):\n plt.hist(data_list, bins=500)\n plt.show()\n return\n\ndef compare_hits_plot(np... | [
0
] |
import MySQLdb
import MySQLdb.cursors
from flask import _app_ctx_stack, current_app
class MySQL(object):
def __init__(self, app=None):
self.app = app
if app is not None:
self.init_app(app)
def init_app(self, app):
"""Initialize the `app` for use with this
:class:`... | normal | {
"blob_id": "db8c2f6f5da0b52c268634043e1132984f610eed",
"index": 8405,
"step-1": "<mask token>\n\n\nclass MySQL(object):\n\n def __init__(self, app=None):\n self.app = app\n if app is not None:\n self.init_app(app)\n <mask token>\n\n @property\n def connect(self):\n kw... | [
4,
5,
6,
7,
8
] |
for i in range(-10,0):
print(i,end=" ") | normal | {
"blob_id": "8d0fcf0bf5effec9aa04e7cd56b4b7098c6713cb",
"index": 70,
"step-1": "<mask token>\n",
"step-2": "for i in range(-10, 0):\n print(i, end=' ')\n",
"step-3": "for i in range(-10,0):\n print(i,end=\" \")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
# Stubs for binascii
# Based on http://docs.python.org/3.2/library/binascii.html
import sys
from typing import Union, Text
if sys.version_info < (3,):
# Python 2 accepts unicode ascii pretty much everywhere.
_Bytes = Text
_Ascii = Text
else:
# But since Python 3.3 ASCII-only unicode strings are accep... | normal | {
"blob_id": "9ba74c7ecbd20c59883aff4efdc7e0369ff65daf",
"index": 5267,
"step-1": "<mask token>\n\n\ndef a2b_base64(string: _Ascii) ->bytes:\n ...\n\n\n<mask token>\n\n\ndef a2b_qp(string: _Ascii, header: bool=...) ->bytes:\n ...\n\n\ndef b2a_qp(data: _Bytes, quotetabs: bool=..., istext: bool=..., header:\n... | [
13,
15,
16,
17,
19
] |
a=int(raw_input())
if (a%2)==0:
print("Even")
else:
print("Odd")
| normal | {
"blob_id": "00b06b5e6465bae3eab336441b283a9831bb93c0",
"index": 4531,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif a % 2 == 0:\n print('Even')\nelse:\n print('Odd')\n",
"step-3": "a = int(raw_input())\nif a % 2 == 0:\n print('Even')\nelse:\n print('Odd')\n",
"step-4": "a=int(raw_inp... | [
0,
1,
2,
3
] |
import pandas as pd
import numpy as np
import os
import matplotlib.pyplot as plt
from datetime import datetime
import statsmodels.api as sm
from quant.stock.stock import Stock
from quant.stock.date import Date
from quant.utility_fun.factor_preprocess import FactorPreProcess
from quant.utility_fun.write_excel import Wri... | normal | {
"blob_id": "1d0730e8fd120e1c4bc5b89cbd766234e1fa3bca",
"index": 2197,
"step-1": "<mask token>\n\n\ndef cal_factor_alpha_return(factor_name, beg_date, end_date, cal_period):\n group_number = 8\n year_trade_days = 242\n min_stock_number = 100\n out_path = 'E:\\\\3_Data\\\\5_stock_data\\\\3_alpha_model... | [
1,
2,
3,
4,
5
] |
# Fix a method's vtable calls + reference making
#@author simo
#@category iOS.kernel
#@keybinding R
#@toolbar logos/refs.png
#@description Resolve references for better CFG
# -*- coding: utf-8 -*-
"""
script which does the following:
- adds references to virtual method calls
- Identifies methods belong to a specific ... | normal | {
"blob_id": "30a57197e3156023ac9a7c4a5218bfe825e143d9",
"index": 5978,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n fix_extra_refs(currentAddress)\n",
"step-3": "<mask token>\nfrom utils.references import *\nif __name__ == '__main__':\n fix_extra_refs(currentAddress... | [
0,
1,
2,
3
] |
import warnings
warnings.filterwarnings('ignore', category=FutureWarning)
from cv2 import cv2
from tqdm import tqdm
import os
import pickle
import numpy as np
import csv
import sys
from collections import defaultdict
from dataset_utils import *
sys.path.append("../training")
from dataset_tools import enclosing_square... | normal | {
"blob_id": "0b7d1564ecbd78086d59629a2058716f41b4b8c8",
"index": 9686,
"step-1": "<mask token>\n\n\ndef get_emotion_label(emotion):\n return LABELS['emotion'][emotion]\n\n\ndef _load_meta_from_csv(csv_meta, output_dict):\n data = readcsv(csv_meta)\n for row in data:\n output_dict[row[0]]['gender'... | [
9,
12,
13,
18,
19
] |
import pymel.core as PM
import socket
def getShadingGroupMembership():
'''
Get a dictionary of shading group set information
{'shadingGroup': [assignmnet1, assignment2...]}
'''
result = {}
#sgs = PM.ls(sl= 1, et='shadingEngine')
sgs = PM.listConnections(s= 1, t='shadingEngine')
for sg i... | normal | {
"blob_id": "4e38ad17ad66ac71b0df3cbcaa33cb546e96ce9d",
"index": 2257,
"step-1": "import pymel.core as PM\nimport socket\n\ndef getShadingGroupMembership():\n '''\n Get a dictionary of shading group set information\n {'shadingGroup': [assignmnet1, assignment2...]}\n '''\n result = {}\n #sgs = P... | [
0
] |
#!/home/nick/.virtualenvs/twitterbots/bin/python3.5
# -*- coding: utf-8 -*-
import tweepy
import sqlite3
from configparser import ConfigParser
'''
A little OOP would be good later for
authenticated user data, c, conn, api
'''
def main():
Collector.collect()
class Collector:
# Main function
def coll... | normal | {
"blob_id": "372d8c8cb9ec8f579db8588aff7799c73c5af255",
"index": 519,
"step-1": "<mask token>\n\n\nclass Collector:\n <mask token>\n\n def get_api():\n parser = ConfigParser()\n parser.read('twitter_auth.ini')\n consumer_key = parser.get('Keys', 'consumer_key').strip(\"'\")\n co... | [
5,
9,
11,
12,
14
] |
"""
"""
import os
from alert_triage.util import filelock
MODIFIED_ALERTS_FILE = "/tmp/alert_triage_modified_alerts"
def read_modified_alert_ids():
""" Read modified alert IDs from file, then remove them from the file."""
# Return an empty list if the file doesn't exist.
if not os.path.exists(MODIFIED_AL... | normal | {
"blob_id": "90ae14d8af163343520365a5565a7c44de57059d",
"index": 5662,
"step-1": "<mask token>\n\n\ndef read_modified_alert_ids():\n \"\"\" Read modified alert IDs from file, then remove them from the file.\"\"\"\n if not os.path.exists(MODIFIED_ALERTS_FILE):\n return []\n lock = filelock.FileLoc... | [
1,
2,
3,
4,
5
] |
import os
from typing import Union, Tuple, List
import pandas as pd
from flags import FLAGS
from helpers import load_from_pickle, decode_class, sort_results_by_metric
ROOT = FLAGS.ROOT
RESULTS_FOLDER = FLAGS.RESULTS_FOLDER
FULL_PATH_TO_CHECKPOINTS = os.path.join(ROOT, RESULTS_FOLDER, "checkpoints")
def eval_resul... | normal | {
"blob_id": "5447bd3b08c22913ae50ee66ee81554d2357ef3e",
"index": 3991,
"step-1": "<mask token>\n\n\ndef eval_results(time_stamps: Union[Tuple, List], excel_file_path=os.path.\n join(FULL_PATH_TO_CHECKPOINTS, f'xVal_results.xlsx')):\n with pd.ExcelWriter(excel_file_path, mode='w') as writer:\n for ts... | [
1,
2,
3,
4,
5
] |
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import cv2
import openslide
class QualityPatch():
def __init__(self, original_img_path,label_img_path,patch_level,patch_size):
"""
parameter:
original_img_path(str): the source of image
label_img_path(s... | normal | {
"blob_id": "0ad71f02e37f2744036b134c33e037a724fd38a6",
"index": 8049,
"step-1": "<mask token>\n\n\nclass QualityPatch:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def getReleventPatches(self):\n relevent_patches = []\n for i, coor in enumerate(s... | [
3,
6,
7,
9,
10
] |
#API End Points by Mitul
import urllib.error, urllib.request, urllib.parse
import json
target = 'http://py4e-data.dr-chuck.net/json?'
local = input('Enter location: ')
url = target + urllib.parse.urlencode({'address': local, 'key' : 42})
print('Retriving', url)
data = urllib.request.urlopen(url).read()
print('Retrive... | normal | {
"blob_id": "d34159536e860719094a36cfc30ffb5fcae72a9a",
"index": 296,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Retriving', url)\n<mask token>\nprint('Retrived', len(data), 'characters')\n<mask token>\nprint(json.dumps(js, indent=4))\nprint('Place id', js['results'][0]['place_id'])\n<mask tok... | [
0,
1,
2,
3,
4
] |
# Generated by Django 2.2.14 on 2020-08-25 17:00
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('blog', '0004_auto_20200825_1318'),
]
operations = [
migrations.RenameField(
model_name='cv',
old_name='additionalskills_tex... | normal | {
"blob_id": "e296a5bea5465c2b84e37c7d83922adb01feab70",
"index": 9828,
"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 = [('blog', '000... | [
0,
1,
2,
3,
4
] |
import csv
#ratings.csv must be in the same directory
skipped_header = False
with open("ratings.csv") as in_file:
csvreader = csv.reader(in_file)
#read each row of ratings.csv (userId,movieId,rating,timestamp)
with open("ratings_train.csv", 'w') as train_out:
with open("ratings_test.csv", 'w... | normal | {
"blob_id": "e48a6a84268a0fe64e90714bd32712665934fc39",
"index": 2223,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('ratings.csv') as in_file:\n csvreader = csv.reader(in_file)\n with open('ratings_train.csv', 'w') as train_out:\n with open('ratings_test.csv', 'w') as test_out:\n... | [
0,
1,
2,
3,
4
] |
# test_LeapYear.py
# By Alex Graalum
import unittest
import LeapYear
class test_leapyear(unittest.TestCase):
def test_four(self):
self.assertEqual(LeapYear.leapyear(2012), True)
def test_hundred(self):
self.assertEqual(LeapYear.leapyear(2100), False)
def test_fourhundred(self):
self... | normal | {
"blob_id": "29cae66fdca65020a82212e5eabbc61eb900e543",
"index": 7720,
"step-1": "<mask token>\n\n\nclass test_leapyear(unittest.TestCase):\n <mask token>\n\n def test_hundred(self):\n self.assertEqual(LeapYear.leapyear(2100), False)\n\n def test_fourhundred(self):\n self.assertEqual(LeapY... | [
4,
5,
6,
7,
8
] |
import os
from cs50 import SQL
from flask import Flask, flash, redirect, render_template, request, session
from flask_session import Session
from tempfile import mkdtemp
from werkzeug.exceptions import default_exceptions, HTTPException, InternalServerError
from werkzeug.security import check_password_hash, generate_pa... | normal | {
"blob_id": "c66f4ee5719f764c8c713c23815302c00b6fb9af",
"index": 310,
"step-1": "<mask token>\n\n\n@app.route('/buy', methods=['GET', 'POST'])\n@login_required\ndef buy():\n \"\"\"Buy shares of stock\"\"\"\n if request.method == 'POST':\n if not request.form.get('symbol'):\n return apolog... | [
3,
9,
13,
14,
15
] |
import os
import urllib.request
import zipfile
import tarfile
import matplotlib.pyplot as plt
%matplotlib inline
from PIL import Image
import numpy as np
# フォルダ「data」が存在しない場合は作成する
data_dir = "./data/"
if not os.path.exists(data_dir):
os.mkdir(data_dir)
# MNIStをダウンロードして読み込む
from sklearn.datasets import fetch_open... | normal | {
"blob_id": "6f53a989ddf179b699186a78b5d8cf6d3d08cbb2",
"index": 4756,
"step-1": "import os\nimport urllib.request\nimport zipfile\nimport tarfile\n\nimport matplotlib.pyplot as plt\n%matplotlib inline\nfrom PIL import Image\nimport numpy as np\n\n# フォルダ「data」が存在しない場合は作成する\ndata_dir = \"./data/\"\nif not os.path... | [
0
] |
#!/usr/bin/python
# -*- coding: UTF-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
import os
import unittest
import logging
from collections import Counter
from utility import token_util
class TestFileReadingFunctions(unittest.TestCase)... | normal | {
"blob_id": "7c3798aa9cc5424656572dfaa87f7acb961613eb",
"index": 8715,
"step-1": "<mask token>\n\n\nclass TestFileReadingFunctions(unittest.TestCase):\n\n def setUp(self):\n self.data_dir = os.path.join(os.path.dirname(os.path.realpath(\n __file__)), 'data')\n self.one_word_per_line_p... | [
4,
5,
6,
7,
8
] |
from collections import OrderedDict as odict
from vent.gui import styles
MONITOR = odict({
'oxygen': {
'name': 'O2 Concentration',
'units': '%',
'abs_range': (0, 100),
'safe_range': (60, 100),
'decimals' : 1
},
'temperature': {
... | normal | {
"blob_id": "941dac77fe60081ffa113c437a356d59837f5883",
"index": 5304,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nMONITOR = odict({'oxygen': {'name': 'O2 Concentration', 'units': '%',\n 'abs_range': (0, 100), 'safe_range': (60, 100), 'decimals': 1},\n 'temperature': {'name': 'Temperature', 'uni... | [
0,
1,
2,
3
] |
### Script to convert matlab structure file (/motiongan/data/style-dataset/style_motion_database.mat')
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import argparse
import math
import numpy as np
from collections import OrderedDict
import scipy.io
import pickle
from core.utils.eul... | normal | {
"blob_id": "f2dac8b454805829cf5dbe2efe3c0de805ae4cb5",
"index": 1727,
"step-1": "<mask token>\n\n\ndef load_skeleton(mat_path):\n mat_data = scipy.io.loadmat(mat_path)['skel'][0, 0]\n skeleton = OrderedDict()\n bone_names = mat_data[1].tolist()\n for i, bone in enumerate(bone_names):\n bone =... | [
3,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
"""Very basic codec tests.
:copyright: the translitcodec authors and developers, see AUTHORS.
:license: MIT, see LICENSE for more details.
"""
import codecs
import translitcodec
data = u'£ ☹ wøóf méåw'
def test_default():
assert codecs.encode(data, 'transliterate') == u'GBP :-( woof mea... | normal | {
"blob_id": "426002bf900e23fd9b1d32c484350ac854228459",
"index": 2565,
"step-1": "<mask token>\n\n\ndef test_translit_long():\n assert codecs.encode(data, 'translit/long') == u'GBP :-( woof meaaw'\n\n\ndef test_translit_short():\n assert codecs.encode(data, 'translit/short') == u'GBP :-( woof meaw'\n\n\n<m... | [
6,
8,
9,
10,
12
] |
import re
from xml.etree import ElementTree
def get_namespace(xml_path):
with open(xml_path) as f:
namespaces = re.findall(r"xmlns:(.*?)=\"(.*?)\"", f.read())
return dict(namespaces)
def get_comic_data(item, ns):
return {
"title": item.find("title").text,
"post_date": item.find("... | normal | {
"blob_id": "86a15bb2e4d59fb5c8763fa2de31164beb327685",
"index": 7928,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_namespace(xml_path):\n with open(xml_path) as f:\n namespaces = re.findall('xmlns:(.*?)=\\\\\"(.*?)\\\\\"', f.read())\n return dict(namespaces)\n\n\ndef get_comic... | [
0,
2,
3,
4,
5
] |
"""Vista de Autorizaciones (Clientes/Especialistas/Vendedores)."""
from django.shortcuts import render
from dashboard.json2table import convert
from django.utils.translation import ugettext_lazy as _
from api.connection import api
from login.utils.tools import role_admin_check
from django.utils.decorators import method... | normal | {
"blob_id": "b78ad3a55eb27fd91f89c22db07fadca297640ab",
"index": 2892,
"step-1": "<mask token>\n\n\nclass Autorization:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass AutorizationClient(Autorization):\n \"\"\"\n Manejo de autorizaciones de clientes,\n se listan los clientes, en... | [
4,
5,
6,
7,
8
] |
#!/usr/bin/env python3
# -*- coding=utf-8 -*-
# description:
# author:jack
# create_time: 2017/12/30
"""
卡片基类
"""
import logging
class BaseCard(object):
def __init__(self, field=[]):
self.data = {}
self.support_set_field = field
def add_cue_words(self, arr):
"""
为卡片添加cue wor... | normal | {
"blob_id": "93e5852df00733c024a59d37699bae58bd893030",
"index": 112,
"step-1": "<mask token>\n\n\nclass BaseCard(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __getattr__(self, item):\n \"\"\"\n 添加魔术方法\n :param item:\n :return:\n \... | [
2,
3,
4,
7,
9
] |
import scrapy
from scrapy.loader import ItemLoader
class BlogSpider(scrapy.Spider):
name = 'blogspider'
start_urls = ['https://blog.scrapinghub.com']
def content_title_parser(self, mystr):
return mystr[0].split(' ')[3]
def parse(self, response):
for url in response.css('ul li a::attr... | normal | {
"blob_id": "4c79dcf394acbcc9a636bcc9b0aac13a2bafc7e3",
"index": 9249,
"step-1": "<mask token>\n\n\nclass BlogSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self, response):\n for url in response.css('ul li a::attr(\"href\")').re('.*/category/.*'):\n ... | [
4,
5,
7,
8
] |
from HurdleRace import hurdleRace
from ddt import ddt, data, unpack
import unittest
class test_AppendAndDelete3(unittest.TestCase):
def test_hurdleRace(self):
height = [1, 6, 3, 5, 2]
k = 4
sum_too_high = hurdleRace(k, height)
self.assertEqual(2, sum_too_high)
| normal | {
"blob_id": "ea86a2a9068c316d3efcbcb165a8ef3d3516ba1b",
"index": 4763,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass test_AppendAndDelete3(unittest.TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass test_AppendAndDelete3(unittest.TestCase):\n\n def test_hurdleRace(self):\... | [
0,
1,
2,
3
] |
import inaccel.coral as inaccel
import numpy as np
import time
class StereoBM:
def __init__(self, cameraMA_l=None, cameraMA_r=None, distC_l=None, distC_r=None, irA_l=None, irA_r=None, bm_state=None ):
# allocate mem for camera parameters for rectification and bm_state class
with inaccel.allocator:
if cameraMA_... | normal | {
"blob_id": "66f3590381fe96c49a8926a806b4a845f0d7e25d",
"index": 4681,
"step-1": "<mask token>\n\n\nclass StereoBM:\n <mask token>\n\n def runAsync(self, left_img, right_img):\n self.m_runStartTime = int(round(time.time() * 1000000))\n if left_img is None:\n raise RuntimeError('Inv... | [
4,
5,
6,
7,
8
] |
import os
import attr
import click
import guitarpro
import psutil
ALL = object()
@attr.s
class GPTools:
input_file = attr.ib()
output_file = attr.ib()
selected_track_numbers = attr.ib(default=None)
selected_measure_numbers = attr.ib(default=None)
selected_beat_numbers = attr.ib(default=None)
... | normal | {
"blob_id": "c6821cb8dd6f8d74ca20c03f87dae321eb869c32",
"index": 2454,
"step-1": "<mask token>\n\n\n@attr.s\nclass GPTools:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self):\n if self.input_file is None:\n self.in... | [
7,
8,
9,
11,
12
] |
# 213. 打家劫舍 II
# 你是一个专业的小偷，计划偷窃沿街的房屋，每间房内都藏有一定的现金。这个地方所有的房屋都 围成一圈 ，这意味着第一个房屋和最后一个房屋是紧挨着的。
# 同时，相邻的房屋装有相互连通的防盗系统，如果两间相邻的房屋在同一晚上被小偷闯入，系统会自动报警 。
# 给定一个代表每个房屋存放金额的非负整数数组，计算你 在不触动警报装置的情况下 ，能够偷窃到的最高金额。
class Solution:
# 86.24%, 15.46%
def rob(self, nums) -> int:
n = len(nums)
if n == 0:
... | normal | {
"blob_id": "59b2c9d279168a806e59fb7529ab12d7b86107bc",
"index": 5340,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n def helper(self, nums, n):\n if n == 1:\n return nums[0]\n dp = [0] * n\n dp[0] = nums[0]\n dp[1] = max(nums[0], nums[1])... | [
0,
2,
3,
4,
5
] |
from random import random, randint, choice
from copy import deepcopy
from math import log
"""
Обертка для функций, которые будут находиться в узлах,
представляющих функции. Его члены – имя функции, сама функция
и количество принимаемых параметров.
"""
class fwrapper:
def __init__(self, function, childcou... | normal | {
"blob_id": "89881f3cc6703b3f43f5d2dae87fa943d8a21513",
"index": 5485,
"step-1": "<mask token>\n\n\nclass fwrapper:\n\n def __init__(self, function, childcount, name):\n self.function = function\n self.childcount = childcount\n self.name = name\n\n\n<mask token>\n\n\nclass node:\n\n de... | [
23,
25,
28,
31,
34
] |
def towers_of_hanoi(n, src, dest, temp,res):
if n==1:
s = 'disk 1 from ',src,'->',dest
res.append(s)
return
towers_of_hanoi(n-1, src, temp, dest, res)
s = 'disk ',n, ' from ',src,'->',dest
res.append(s)
towers_of_hanoi(n-1, temp, dest, src, res)
return res
def steps... | normal | {
"blob_id": "f23bfef2daf8fda4249435821dbc2e0b1846e3d6",
"index": 9842,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef steps_in_tower_of_hanoi(no_of_disks):\n res = towers_of_hanoi(no_of_disks, 'A', 'C', 'B', [])\n return res\n\n\n<mask token>\n",
"step-3": "def towers_of_hanoi(n, src, des... | [
0,
1,
2,
3,
4
] |
_base_ = "../model.py"
model = dict(
type="ImageClassifier",
task="classification",
pretrained=None,
backbone=dict(),
head=dict(in_channels=-1, loss=dict(type="CrossEntropyLoss", loss_weight=1.0), topk=(1, 5)),
)
checkpoint_config = dict(type="CheckpointHookWithValResults")
| normal | {
"blob_id": "8bd5eff12e68f7145676f5e089b51376a82ab489",
"index": 3231,
"step-1": "<mask token>\n",
"step-2": "_base_ = '../model.py'\nmodel = dict(type='ImageClassifier', task='classification', pretrained=None,\n backbone=dict(), head=dict(in_channels=-1, loss=dict(type=\n 'CrossEntropyLoss', loss_weight... | [
0,
1,
2
] |
num=5
a=5
for row in range(num,0,-1):
for col in range(row,0,-1):
print(a,end="")
a-=1
print() | normal | {
"blob_id": "a567a2dc1dbb59979d849a5a772e4592910a9f27",
"index": 2783,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor row in range(num, 0, -1):\n for col in range(row, 0, -1):\n print(a, end='')\n a -= 1\n print()\n",
"step-3": "num = 5\na = 5\nfor row in range(num, 0, -1):\n for... | [
0,
1,
2,
3
] |
from airflow.plugins_manager import AirflowPlugin
from flask import Blueprint, Flask
from rest_api.log.views import views
from rest_api.route.log_route import log
from rest_api.route.mylog_route import my_log_pb
from rest_api.route.native_log_route import native_log_bp
class AirflowPlugin(AirflowPlugin):
name = "... | normal | {
"blob_id": "39f1fc04911f8d22d07532add24cd1671a569e72",
"index": 9414,
"step-1": "<mask token>\n\n\nclass AirflowPlugin(AirflowPlugin):\n name = 'airflow-plugin'\n operators = []\n hooks = []\n executors = []\n macros = []\n admin_views = []\n flask_blueprints = []\n menu_links = []\n\n\n... | [
2,
3,
4,
5,
6
] |
from django.http import HttpResponse
from django.views.decorators.http import require_http_methods
from django.shortcuts import render, redirect
from app.models import PaidTimeOff, Schedule
from django.utils import timezone
from django.contrib import messages
from app.decorators import user_is_authenticated
from app.... | normal | {
"blob_id": "7245d4db6440d38b9302907a6203c1507c373112",
"index": 6970,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef index_get(request, user_id, user, pto):\n schedules = Schedule.to_calendar(Schedule.objects.filter(pto=pto))\n context = pto.__dict__\n context.update({'schedules': sched... | [
0,
2,
3,
4,
5
] |
"""
给定两个非空链表来代表两个非负整数，位数按照逆序方式存储，它们的每个节点只存储单个数字。将这两数相加会返回一个新的链表。
你可以假设除了数字 0 之外，这两个数字都不会以零开头。
输入：(2 -> 4 -> 3) + (5 -> 6 -> 4)
输出：7 -> 0 -> 8
原因：342 + 465 = 807
"""
"""
解题思路：
先计算两个节点的值和与进位的和
然后将值对10取余存放到新的链表中
循环下去
直到l1 l2 进位都不存在
"""
# Definition for singly-linked list.
class ListNode:
def __init__(self, x):
... | normal | {
"blob_id": "80f681eb99d1e3f64cacd23ce0a4b10a74a79fe8",
"index": 4223,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n\n def addTwoNumbers(self, l1, l2):\n \"\"\"\n :type l1: ListNode\n :type l2: ListNode\n :rtype:... | [
1,
2,
3,
4,
5
] |
from collections import OrderedDict
class LRU_Cache(object):
def __init__(self, capacity):
# Initialize class variables
self.size = capacity
self.jar = OrderedDict()
pass
def get(self, key):
# Retrieve item from provided key. Return -1 if nonexistent.
if key not ... | normal | {
"blob_id": "3c88e13e8796c5f39180a9a514f0528a074460a6",
"index": 2198,
"step-1": "<mask token>\n\n\nclass LRU_Cache(object):\n\n def __init__(self, capacity):\n self.size = capacity\n self.jar = OrderedDict()\n pass\n\n def get(self, key):\n if key not in self.jar:\n ... | [
6,
8,
10,
11,
12
] |
from queuingservices.managers.queue_lifecycle_manager import QueueLifecycleManager
from queuingservices.managers.queue_publisher_manager import QueuePublisherManager
from queuingservices.managers.queue_subscriber_manager import QueueSubscriberManager
class QueueMaster(QueueSubscriberManager, QueuePublisherManager,
... | normal | {
"blob_id": "b2b961c6ff1d975d80a84be361321ab44dc026a0",
"index": 2134,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass QueueMaster(QueueSubscriberManager, QueuePublisherManager,\n QueueLifecycleManager):\n <mask token>\n pass\n",
"step-3": "<mask token>\n\n\nclass QueueMaster(QueueSub... | [
0,
1,
2,
3
] |
from django.shortcuts import render
from .forms import TeacherForm,Teacher
from django.http import HttpResponse
def add_teacher(request):
if request.method=="POST":
form=TeacherForm(request.POST)
if form.is_valid():
form.save()
return redirect("list_teachers")
else:
return HttpResponse("in... | normal | {
"blob_id": "cf97c87400649dd15e5d006707f9adfbd0c91b2c",
"index": 4118,
"step-1": "<mask token>\n\n\ndef teacher_detail(request, pk):\n teacher = Teacher.objects.get(pk=pk)\n return render(request, 'teacher_detail.html', {'teacher': teacher})\n\n\ndef edit_teacher(request, pk):\n teacher = Teacher.object... | [
2,
3,
4,
5,
6
] |
import rambench
rambench.perform_benchmark()
| normal | {
"blob_id": "3d1f2130043613dc8d5bbd773edd96c87c355de9",
"index": 3455,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrambench.perform_benchmark()\n",
"step-3": "import rambench\nrambench.perform_benchmark()\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
#!/usr/bin/python
import pyglet
from pyglet.gl import *
win = pyglet.window.Window()
@win.event
def on_draw():
# Clear buffers
glClear(GL_COLOR_BUFFER_BIT)
# Draw outlines only
glPolygonMode(GL_FRONT_AND_BACK, GL_LINE)
# Draw some stuff
glBegin(GL_TRIANGLES)
glVertex3i(0, 0, 0)
glVertex3i(300, 0, 0)
glVe... | normal | {
"blob_id": "86c4193ec0fee8a0c06858913ec8153fcf0df6d9",
"index": 4114,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@win.event\ndef on_draw():\n glClear(GL_COLOR_BUFFER_BIT)\n glPolygonMode(GL_FRONT_AND_BACK, GL_LINE)\n glBegin(GL_TRIANGLES)\n glVertex3i(0, 0, 0)\n glVertex3i(300, 0,... | [
0,
2,
3,
4,
5
] |
import re
text = 'Macademia nuts, Honey tuile, Cocoa powder, Pistachio nuts'
search_pattern = re.compile('nuts')
search_match_object = search_pattern.search(text)
if search_match_object:
print(search_match_object.span())
print(search_match_object.start())
print(search_match_object.end())
print(search_... | normal | {
"blob_id": "ef5d235f09eea827b240290218c397f880f1046d",
"index": 4433,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif search_match_object:\n print(search_match_object.span())\n print(search_match_object.start())\n print(search_match_object.end())\n print(search_match_object.group())\nprint... | [
0,
1,
2,
3,
4
] |
import inputoutput
def xor_encryption(source, destination, key):
"""
Returns text encrypted or decrypted with xor
Keyword arguments:
source - path to file with text to be encrypted
destination - path to the file where you want to save the result
key - encryption key
"""
text = inputou... | normal | {
"blob_id": "81774d3b4d9fbf22ed19e1cba7ec5e8e3707f51a",
"index": 2076,
"step-1": "<mask token>\n\n\ndef xor_encryption(source, destination, key):\n \"\"\"\n Returns text encrypted or decrypted with xor\n\n Keyword arguments:\n source - path to file with text to be encrypted\n destination - path to... | [
1,
2,
3,
4,
5
] |
aes_key = 'eR5ceExL4IpUUY2lqALN7gLXzo11jlXPOwTwFGwOO3h='
| normal | {
"blob_id": "7112348631bc60767bfb79c7f6966fc9189c522b",
"index": 7901,
"step-1": "<mask token>\n",
"step-2": "aes_key = 'eR5ceExL4IpUUY2lqALN7gLXzo11jlXPOwTwFGwOO3h='\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
import datetime
def days_count(year, month, hour):
point = datetime.datetime(year, month, hour, 0, 0, 0, 000000)
now = datetime.datetime.now()
interval_day = point - now
return interval_day.days
messages = {
'猫钰钰 五月有砖搬': '距离 猫钰钰 上岗还有 {} 天'.format(days_count(2019, 6, 1)), # 6.1 上岗
'AD Zh': '... | normal | {
"blob_id": "82ce6304977d468945526824ade1500e10d25d09",
"index": 2872,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef days_count(year, month, hour):\n point = datetime.datetime(year, month, hour, 0, 0, 0, 0)\n now = datetime.datetime.now()\n interval_day = point - now\n return interva... | [
0,
1,
2,
3,
4
] |
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# from sklearn import tree
# import joblib
music_data = pd.read_csv(r"C:\Users\junha\PythonProjects\predict_music_preferences\music.csv")
# print(music_dat... | normal | {
"blob_id": "8dbcd7bba09f8acff860890d8201e016b587796d",
"index": 6149,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmodel.fit(X_train, y_train)\n<mask token>\nprint(predictions)\n<mask token>\nprint(score)\n",
"step-3": "<mask token>\nmusic_data = pd.read_csv(\n 'C:\\\\Users\\\\junha\\\\PythonProj... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from django.conf.urls import patterns, url
from customer_support.views import update_existing_subscriber, \
add_new_subscriber
from .views import (EditSubscriberView,
DeActivateSubscriberView,
ReActivateSubscriberView,
SupportSub... | normal | {
"blob_id": "fb4818e742ed3c7d131c426811f839dbe70f03de",
"index": 2650,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('', url(regex='new_subscriber/$', view=\n add_new_subscriber, name='support.new_subscriber'), url(regex=\n 'update_subscriber/(?P<pk>\\\\d+)/$', view=update_e... | [
0,
1,
2,
3
] |
#!/usr/bin/python
import RPi.GPIO as GPIO
GPIO.setmode(GPIO.BCM)
ledPin = 4
pinOn = False
GPIO.setup(ledPin, GPIO.OUT)
GPIO.output(ledPin, GPIO.LOW)
def print_pin_status(pin_number):
GPIO.setup(pin_number, GPIO.IN)
value = GPIO.input(pin_number)
print(f'Current Value of {pin_number} is {value}')
G... | normal | {
"blob_id": "492c416becc44deaafef519eae8c9a82ac00cc0e",
"index": 8632,
"step-1": "<mask token>\n\n\ndef print_pin_status(pin_number):\n GPIO.setup(pin_number, GPIO.IN)\n value = GPIO.input(pin_number)\n print(f'Current Value of {pin_number} is {value}')\n GPIO.setup(pin_number, GPIO.OUT)\n\n\n<mask t... | [
1,
2,
3,
4,
5
] |
from nmigen import *
class Top(Elaboratable):
def __init__(self):
self.counter = Signal(3)
self.led = Signal()
def elaborate(self, platform):
m = Module()
m.d.comb += self.led.eq(self.counter[2])
m.d.sync += self.counter.eq(self.counter + 1)
return m
| normal | {
"blob_id": "22b6ea64cdb109e1c6b2536b50935d09d37a7e1a",
"index": 3057,
"step-1": "<mask token>\n\n\nclass Top(Elaboratable):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Top(Elaboratable):\n <mask token>\n\n def elaborate(self, platform):\n m = Module()\n m.d.c... | [
1,
2,
3,
4
] |
import os
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import distance
with open('input.txt', 'r') as f:
data = f.read()
res = [i for i in data.splitlines()]
print(res)
newHold = []
for line in res:
newHold.append((tuple(int(i) for i in line.split(', '))))
print(newHold)
mapper = np.... | normal | {
"blob_id": "47476fbb78ca8ce14d30bf226795bbd85b5bae45",
"index": 6939,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('input.txt', 'r') as f:\n data = f.read()\n<mask token>\nprint(res)\n<mask token>\nfor line in res:\n newHold.append(tuple(int(i) for i in line.split(', ')))\nprint(newHol... | [
0,
1,
2,
3,
4
] |
import tensorflow as tf
def data_rescale(x):
return tf.subtract(tf.divide(x, 127.5), 1)
def inverse_rescale(y):
return tf.round(tf.multiply(tf.add(y, 1), 127.5))
| normal | {
"blob_id": "1a09b38838f40c4c6049da8e6a72ba3d56806c07",
"index": 3703,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef inverse_rescale(y):\n return tf.round(tf.multiply(tf.add(y, 1), 127.5))\n",
"step-3": "<mask token>\n\n\ndef data_rescale(x):\n return tf.subtract(tf.divide(x, 127.5), 1)\... | [
0,
1,
2,
3
] |
'''
Created on 2018-9-8
@author: weij
'''
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os.path
import sys
import time
import numpy as np
from numpy import shape
from scipy import linalg
from sklearn import datas... | normal | {
"blob_id": "49995e60b817e2c5a2ea7e85e4fe96ca95363cb2",
"index": 2148,
"step-1": "<mask token>\n\n\ndef test_linearSVC(*data):\n X_train, X_test, y_train, y_test = data\n cls = svm.LinearSVC()\n cls.fit(X_train, y_train)\n print('Coefficients:%s,Intercept:%s' % (cls.coef_, cls.intercept_))\n print... | [
5,
6,
7,
8,
10
] |
# Generated by Django 3.2.7 on 2021-10-01 08:36
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('app', '0005_alter_users_is_active'),
]
operations = [
migrations.AlterModelManagers(
name='users',
managers=[
],... | normal | {
"blob_id": "6670295241516664e30c7db5cd3b5e2fb6c4fb05",
"index": 1985,
"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 = [('app', '0005... | [
0,
1,
2,
3,
4
] |
old_file = open("new.csv", "r")
new_file = open("new1,csv", "w")
for line in old_file.readlines():
cleaned_line =line.replace(',','.')
new_file.write(cleaned_line)
old_file.close
new_file.close | normal | {
"blob_id": "b3d26d01d45c073192d06c8e94c06f7eae267b14",
"index": 968,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in old_file.readlines():\n cleaned_line = line.replace(',', '.')\n new_file.write(cleaned_line)\nold_file.close\nnew_file.close\n",
"step-3": "old_file = open('new.csv', '... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
import sys
def solve():
numEngines = int(sys.stdin.readline())
engines = []
for _ in range(numEngines):
engine = sys.stdin.readline()
engines.append(engine)
numQueries = int(sys.stdin.readline())
queries = []
for _ in range(numQueries):
query = sys.stdin.readline()
queries.append(... | normal | {
"blob_id": "174f5b04f02ec0c9651d5e34c8b04df8bfd4dff4",
"index": 1943,
"step-1": "#!/usr/bin/env python\n\nimport sys\n\ndef solve():\n\tnumEngines = int(sys.stdin.readline())\n\tengines = []\n\tfor _ in range(numEngines):\n\t\tengine = sys.stdin.readline()\n\t\tengines.append(engine)\n\n\tnumQueries = int(sys.s... | [
0
] |
from oscar.app import Shop
from apps.catalogue.app import application as catalogue_app
class BaseApplication(Shop):
catalogue_app = catalogue_app
application = BaseApplication()
| normal | {
"blob_id": "c8bb6ead7e305f466e24b47811d6ed38c8cfec0a",
"index": 2691,
"step-1": "<mask token>\n\n\nclass BaseApplication(Shop):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass BaseApplication(Shop):\n catalogue_app = catalogue_app\n\n\n<mask token>\n",
"step-3": "<mask token>\n... | [
1,
2,
3,
4
] |
import dash_html_components as html
import dash_core_components as dcc
import dash_daq as daq
import dash_bootstrap_components as dbc
import src.common.common_layout as layout_common
def build_navbar():
return html.Div(
id="banner",
children=[
html.Div(
id="banner-text... | normal | {
"blob_id": "f9dd20a3b72c0c8e72029459244486f31eaff536",
"index": 9411,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generate_modal():\n return html.Div(id='markdown', className='modal', children=html.Div(id=\n 'markdown-container', className='markdown-container', children=[\n h... | [
0,
1,
2,
3,
4
] |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
# __author__ = "Sponge_sy"
# Date: 2021/9/11
import numpy
from tqdm import tqdm
from bert4keras.tokenizers import Tokenizer
from bert4keras.models import build_transformer_model
from bert4keras.snippets import sequence_padding, DataGenerator
from utils import *
class d... | normal | {
"blob_id": "5cb390b06026bc0899c0b10dc93f3ec1f2ffefa6",
"index": 9727,
"step-1": "<mask token>\n\n\nclass data_generator(DataGenerator):\n <mask token>\n\n def __init__(self, pattern='', is_pre=True, *args, **kwargs):\n super(data_generator, self).__init__(*args, **kwargs)\n self.pattern = pa... | [
3,
4,
6,
7,
8
] |
import _thread
import os
from queue import Queue
from threading import Thread
import random
import io
import vk_api
from vk_api.longpoll import VkLongPoll, VkEventType
from datetime import datetime, timedelta
import time
from nltk.tokenize import RegexpTokenizer
from nltk.corpus import stopwords
from wordcloud import W... | normal | {
"blob_id": "03ce69924c885e59e40689dc63e50d54b89649f7",
"index": 2924,
"step-1": "<mask token>\n\n\ndef cloud(user_id):\n wall = tools.get_all('wall.get', 100, {'owner_id': user_id})['items']\n wall = list(filter(lambda x: datetime.fromtimestamp(x['date']).year ==\n current_year, wall))\n tokeniz... | [
2,
4,
5,
6,
7
] |
# Generated by Django 2.0.7 on 2018-09-27 13:40
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('education', '0005_auto_20180927_1041'),
]
operations = [
migrations.RemoveField(
model_name='educationgroup',
name='... | normal | {
"blob_id": "8ff7ace102b781b35fff0671e2c606bf662e2767",
"index": 9851,
"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 = [('education',... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import rospy
import rosnode
import csv
import datetime
import rosbag
import sys
import os
import matplotlib.pyplot as plt
import argparse
import math
from math import hypot
import numpy as np
from sensor_msgs.msg import LaserScan
from std_msgs.msg import String
import yaml as yaml
start_time = Non... | normal | {
"blob_id": "c00a8bfec46ed829e413257bf97c44add564080d",
"index": 8349,
"step-1": "#!/usr/bin/env python\nimport rospy\nimport rosnode\nimport csv\nimport datetime\nimport rosbag\nimport sys\nimport os\nimport matplotlib.pyplot as plt\nimport argparse\nimport math\nfrom math import hypot\nimport numpy as np\nfrom... | [
0
] |
import numpy as np
count = 0 # счетчик попыток
number = np.random.randint(1, 101) # загадали число
print("Загадано число от 1 до 100")
def game_core_v3(number):
'''Сначала устанавливаем любое random число, а потом уменьшаем или увеличиваем его в зависимости от того, больше оно или меньше нужного.
Функция... | normal | {
"blob_id": "66474b8cdca9a4aa48b8dc710d161a3a16495aed",
"index": 6438,
"step-1": "<mask token>\n\n\ndef game_core_v3(number):\n \"\"\"Сначала устанавливаем любое random число, а потом уменьшаем или увеличиваем его в зависимости от того, больше оно или меньше нужного.\n Функция принимает загаданное число... | [
2,
3,
4,
5,
6
] |
import threading
import serial
import time
bno = serial.Serial('/dev/ttyUSB0', 115200, timeout=.5)
compass_heading = -1.0
def readBNO():
global compass_heading
try:
bno.write(b'g')
response = bno.readline().decode()
if response != '':
compass_heading = float(response.split(... | normal | {
"blob_id": "63a7225abc511b239a69f625b12c1458c75b4090",
"index": 8904,
"step-1": "<mask token>\n\n\ndef readContinuous():\n while True:\n readBNO()\n time.sleep(0.1)\n\n\n<mask token>\n\n\ndef get_heading():\n return compass_heading\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef rea... | [
2,
3,
4,
5,
7
] |
import numpy as np
import copy
'''
本脚本主要用来实现决策树的相关内容。
constrcut_tree:该函数是构建决策树的主要函数
其输入：数据集X:n*p n:样本数，p-1维特征，p为样本类别,
以及属性信息label:属性名称,p-1一维数组，label表示的是此时X每一列对应的属性名称
决策结构用字典来表示，例如{attribution1:{0:{attribution2:{}},1:{attribution3:{}}}
'''
def construct_tree(X,label):
classList = [sample[-1] for sample in X]
... | normal | {
"blob_id": "ff66b33a133b627ba2329434d6c1649c94b6ec78",
"index": 8188,
"step-1": "<mask token>\n\n\ndef return_major(Y):\n label_count = {}\n for i in Y:\n label_count[i] = label_count.get(i, 0) + 1\n sorted_class = sorted(label_count.items(), key=operator.itemgetter(1),\n reverse=True)\n ... | [
3,
4,
5,
6,
7
] |
from django.db import models
# Create your models here.
class Tutorial(models.Model):
web_title = models.CharField(max_length=200)
web_content = models.TextField()
web_published = models.DateTimeField("date published")
def __str__(self):
return self.web_title
| normal | {
"blob_id": "32499688db51f701173ec0ea212c483bf902c109",
"index": 3048,
"step-1": "<mask token>\n\n\nclass Tutorial(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Tutorial(models.Model):\n <mask token>\n <mask token>\n <mask... | [
1,
2,
3,
4,
5
] |
class Node:
def __init__(self,data):
self.data = data
self.next = None
self.prev = None
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 ==... | normal | {
"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
] |
# coding=utf-8
class HtmlDownload(object):
"""docstring for HtmlDownload"""
def html_download(city, keyWords, pages):
# root URL
paras = {
'jl': city,
'kw': keyWords,
'pages': pages,
'isadv': 0
}
url = "http://sou.zhaopin.com/jobs/searchresult.ashx?" + urlencode... | normal | {
"blob_id": "e33aca56e4c9f82779278e836308c2e22d3356e2",
"index": 3770,
"step-1": "<mask token>\n",
"step-2": "class HtmlDownload(object):\n <mask token>\n <mask token>\n",
"step-3": "class HtmlDownload(object):\n <mask token>\n\n def html_download(city, keyWords, pages):\n paras = {'jl': c... | [
0,
1,
2,
3,
4
] |
from __future__ import unicode_literals
from django.db import models
# Create your models here.
class Group(models.Model):
name = models.CharField(max_length=200, db_index=True)
loan_eligibility = models.CharField(max_length=200, db_index=True)
account_number = models.CharField(max_length=200, db_index=Tr... | normal | {
"blob_id": "0c8b58acf33bdfa95984d29a75ae01e49d0da149",
"index": 9202,
"step-1": "<mask token>\n\n\nclass Member(models.Model):\n name = models.CharField(max_length=200, db_index=True)\n age = models.CharField(max_length=200)\n phone = models.CharField(max_length=200)\n address1 = models.CharField(ma... | [
2,
3,
4,
5,
6
] |
from django.contrib import admin
from .models import Game, Scrap
admin.site.register(Game)
admin.site.register(Scrap)
| normal | {
"blob_id": "7e328992392a4ff2b0e23920a8907e38f63fcff0",
"index": 7168,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Game)\nadmin.site.register(Scrap)\n",
"step-3": "from django.contrib import admin\nfrom .models import Game, Scrap\nadmin.site.register(Game)\nadmin.site.register(Sc... | [
0,
1,
2
] |
from django import forms
from .models import Profile
class ImageForm(forms.ModelForm):
userimage = forms.ImageField(required=False, error_messages={'invalid':("Image file only")}, widget=forms.FileInput)
class Meta:
model = Profile
fields = ['userimage',]
| normal | {
"blob_id": "9081d0f75ac53ab8d0bafb39cd46a2fec8a5135f",
"index": 3813,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ImageForm(forms.ModelForm):\n <mask token>\n\n\n class Meta:\n model = Profile\n fields = ['userimage']\n",
"step-3": "<mask token>\n\n\nclass ImageForm(fo... | [
0,
1,
2,
3,
4
] |
from OTXv2 import OTXv2
from pandas.io.json import json_normalize
from datetime import datetime, timedelta
import getopt
import sys
from sendemail import sendemail
from main import otx
import csv
import pandas as pd
from pandas import read_csv
import os.path
def tools():
search = str(input('Please enter search: '... | normal | {
"blob_id": "659f45d2c6c7138f26b4a8d15d1710ae60450b08",
"index": 6278,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef tools():\n search = str(input('Please enter search: '))\n search.strip()\n pulsesJSON = otx.search_pulses(search, 40)\n for aPulse in pulsesJSON['results']:\n n... | [
0,
1,
2,
3
] |
# Generated by Django 2.2.2 on 2019-07-30 01:25
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('usuarios', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='usuario',
name='inicio',
... | normal | {
"blob_id": "5e4a334b373d912ba37b18f95e4866450bda5570",
"index": 3938,
"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 = [('usuarios', ... | [
0,
1,
2,
3,
4
] |
# import libraries
import sys
import pandas as pd
import numpy as n
from sqlalchemy import create_engine
def load_data(messages_filepath, categories_filepath):
"""
This function loads the message and categories files and
merge them and return the new dataframe for the project
"""
# Read messages an... | normal | {
"blob_id": "4642537f8af1f060f5ee43cc9e98bd07be6a558c",
"index": 124,
"step-1": "# import libraries\nimport sys\nimport pandas as pd\nimport numpy as n\nfrom sqlalchemy import create_engine\n\ndef load_data(messages_filepath, categories_filepath):\n \"\"\"\n This function loads the message and categories f... | [
0
] |
from selenium import webdriver
import time
import xlwt
from JD_PhoneNo import get_phone_no
book = xlwt.Workbook(encoding="utf-8")
sheet1=book.add_sheet("Sheet 1")
browser = webdriver.Firefox()
browser.get("https://www.zomato.com/bhopal/dinner")
z_hotel_list = []
z_address_list = []
z_phone_list = []
z_rating... | normal | {
"blob_id": "96425986305171a9d23231f60b35dcbcbbd12d2d",
"index": 7995,
"step-1": "<mask token>\n\n\ndef traverse(a, b):\n temp = []\n for i in range(a, b, 1):\n a = str(i)\n button = browser.find_element_by_link_text(a)\n button.click()\n name_list = browser.find_elements_by_cla... | [
1,
2,
3,
4,
5
] |
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