code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
"""
Visualize the predictions of a GQCNN on a dataset Visualizes TP, TN, FP, FN..
Author: Vishal Satish
"""
import copy
import logging
import numpy as np
import os
import sys
from random import shuffle
import autolab_core.utils as utils
from autolab_core import YamlConfig, Point
from perception import BinaryImage, Co... | normal | {
"blob_id": "806bdb75eed91d1429d8473a50c136b58a736147",
"index": 8852,
"step-1": "\"\"\"\nVisualize the predictions of a GQCNN on a dataset Visualizes TP, TN, FP, FN..\nAuthor: Vishal Satish \n\"\"\"\nimport copy\nimport logging\nimport numpy as np\nimport os\nimport sys\nfrom random import shuffle\n\nimport aut... | [
0
] |
import numpy as np
from scipy import stats
from statarray import statdat
#a2a1 = np.loadtxt('a2a1_130707_2300.dat')
#a2a1 = np.concatenate( (a2a1, np.loadtxt('a2a1_130708_1223.dat')), axis=0 )
#a2a1 = np.loadtxt('a2a1_130708_1654.dat')
#a2a1 = np.loadtxt('a2a1_130709_0030.dat')
import matplotlib.pyplot as plt
impo... | normal | {
"blob_id": "feac1092d1aaf70eb4d4df919e434cdc1aa9c826",
"index": 9171,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrc('font', **{'family': 'serif'})\n<mask token>\nfor i, nafm in enumerate(nafms):\n detuning = 6.44\n a1, a2 = fetchdata.fetch_data_A1A2({'afmsize': nafm, 'ai': 0.0}, 'det',\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
import sys
import xlrd
import numpy as np
import matplotlib.pyplot as plt
if __name__ == "__main__":
param = sys.argv
print "Hello:" + param[0]
# ファイルのオープン
book = xlrd.open_workbook('sample.xls')
# シートの選択
sheet = book.sheet_by_name(u"Sheet1")
# sheet = book.sheet_by_index(0)
plot_x =... | normal | {
"blob_id": "dacd4334433eb323ce732c96f680fb7b9333721a",
"index": 2268,
"step-1": "# -*- coding: utf-8 -*-\n\nimport sys\nimport xlrd\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nif __name__ == \"__main__\":\n\tparam = sys.argv\n\tprint \"Hello:\" + param[0]\n\n\t# ファイルのオープン\n\tbook = xlrd.open_workboo... | [
0
] |
#!/usr/bin/env python
#coding=UTF8
'''
@author: devin
@time: 2013-11-23
@desc:
timer
'''
import threading
import time
class Timer(threading.Thread):
'''
每隔一段时间执行一遍任务
'''
def __init__(self, seconds, fun, **kwargs):
'''
seconds为间隔时间，单位为秒
fun为定时执行的任务... | normal | {
"blob_id": "4a546222082e2a25296e31f715baf594c974b7ad",
"index": 5844,
"step-1": "#!/usr/bin/env python\n#coding=UTF8\n'''\n @author: devin\n @time: 2013-11-23\n @desc:\n timer\n'''\nimport threading\nimport time\n\nclass Timer(threading.Thread):\n '''\n 每隔一段时间执行一遍任务\n '''\n def _... | [
0
] |
import numpy as np
import matplotlib.pyplot as plt
import csv
category = ["Ecological Well-being", "Health & Human Services", "Arts & Culture", "Community Building", "Environment"]
arr = np.empty((0, 6), str)
moneyGranted = [[0]*5 for _ in range(6)]
moneyRequested = [[0]*5 for _ in range(6)]
perFull = [[0]*5 f... | normal | {
"blob_id": "e7b2e716fbcaf761e119003000bf1b16af57a2b7",
"index": 7009,
"step-1": "<mask token>\n\n\ndef task5(arr):\n for row in arr:\n moneyGranted[int(row[1]) - 2015][int(row[3]) - 1] += int(row[4])\n moneyRequested[int(row[1]) - 2015][int(row[3]) - 1] += int(row[5])\n for i in range(6):\n ... | [
1,
2,
3,
4,
5
] |
class BaseService:
def __init__(self, context):
self._context = context
def post(self, path, body):
result = self._context.http.post(path, body)
return result.json()["Data"]
| normal | {
"blob_id": "5000663e3cde9c1a1100c9022707ccae13db0034",
"index": 1426,
"step-1": "<mask token>\n",
"step-2": "class BaseService:\n <mask token>\n <mask token>\n",
"step-3": "class BaseService:\n <mask token>\n\n def post(self, path, body):\n result = self._context.http.post(path, body)\n ... | [
0,
1,
2,
3,
4
] |
from datetime import datetime
class Guest:
def __init__(self, Name, FamilyName, Car, controlboard,
CarRotationManager, ID=0, linkedplatform=None,Start=0): # --Initializing Guest credentials/info---
self.Name = Name
self.FamilyName = FamilyName
self.Car = Car
... | normal | {
"blob_id": "3553fa72cb831f82a1030b9eadc9594eee1d1422",
"index": 2152,
"step-1": "<mask token>\n\n\nclass Guest:\n <mask token>\n\n def parked_and_linkedplatform_value(self):\n boolean, linkedplatform = (self.CarRotationManager.\n check_if_guest_parked(self))\n if boolean == True:\... | [
3,
4,
5,
6,
7
] |
from collections import deque
def safeInsert(graph,left,right):
if left not in graph:
graph[left] = {}
graph[left][right] = True
if right not in graph:
graph[right] = {}
graph[right][left] = True
def trace(graph,start,end):
queue = deque([start])
pred = {start:None}
while len(queue)>0:
cur = queue.poplef... | normal | {
"blob_id": "3f655a12ac45c152215949d3d8bdb71147eeb849",
"index": 3651,
"step-1": "from collections import deque\n\ndef safeInsert(graph,left,right):\n\tif left not in graph:\n\t\tgraph[left] = {}\n\tgraph[left][right] = True\n\tif right not in graph:\n\t\tgraph[right] = {}\n\tgraph[right][left] = True\n\ndef tra... | [
0
] |
#Main thread for starting the gui
import cv2
import PIL
from PIL import Image,ImageTk
from tkinter import *
from matplotlib import pyplot as pt
from matplotlib.image import imread
from control.control import Control
control=Control()
#gives the indtruction for saving the current frame
def takePicture():
global s... | normal | {
"blob_id": "8d8c211895fd43b1e2a38216693b0c00f6f76756",
"index": 5748,
"step-1": "<mask token>\n\n\ndef takePicture():\n global setImage\n setImage = True\n\n\ndef addRectangles(locations):\n _, axe = pt.subplots()\n img = imread('hola.jpg')\n cv2image = cv2.cvtColor(img, cv2.COLOR_BGR2RGBA)\n ... | [
4,
5,
6,
7,
8
] |
__all__ = '''
calc_common_prefix_length
'''.split()
import operator
import itertools
def calc_common_prefix_length(lhs_iterable, rhs_iterable, /, *, __eq__=None):
if __eq__ is None:
__eq__ = operator.__eq__
idx = -1
for a, b, idx in zip(lhs_iterable, rhs_iterable, itertools.count(0)):
... | normal | {
"blob_id": "2b73c4e07bba7ed5c89a31ebd45655eaa85dcdcc",
"index": 2689,
"step-1": "<mask token>\n\n\ndef calc_common_prefix_length(lhs_iterable, rhs_iterable, /, *, __eq__=None):\n if __eq__ is None:\n __eq__ = operator.__eq__\n idx = -1\n for a, b, idx in zip(lhs_iterable, rhs_iterable, itertools... | [
1,
2,
3,
4,
5
] |
##########################################################################
#
# Draw a 2-D plot for student registration number and the marks secured using gnuplot
#
##########################################################################
import Gnuplot
# create lists to store student marks and regno
student_reg=[... | normal | {
"blob_id": "dcbbc7098410d771a7151af7c43ac4d0e4d46f18",
"index": 9135,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, n):\n reg = int(input('Enter RegNo: '))\n student_reg.append(reg)\n marks = int(input('Enter marks: '))\n student_marks.append(marks)\n<mask token>\ngplt.tit... | [
0,
1,
2,
3,
4
] |
import sys
import os
import json
from collections import OrderedDict
from config import folder, portfolio_value
from datetime import datetime
import logging
# Logger setup
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)
def valid_date(datestring):
""" Determine if something is a valid... | normal | {
"blob_id": "0bc72a558b9bd3b5f74ce5dfce586dd66c579710",
"index": 5776,
"step-1": "<mask token>\n\n\ndef valid_date(datestring):\n \"\"\" Determine if something is a valid date \"\"\"\n try:\n datetime.strptime(datestring, '%Y-%m-%d')\n return True\n except ValueError as e:\n logger.... | [
4,
5,
6,
7,
8
] |
"""
Duck typing
Ref: http://www.voidspace.org.uk/python/articles/duck_typing.shtml
"""
##########
# mathmatic operator (syntactic sugar)
print 3 + 3
# same as >>>
print int.__add__(3, 3)
# <<<
# overload '+' operator
class Klass1(object):
def __init__(self, a, b):
self.a = a
self.b = b
def __a... | normal | {
"blob_id": "776470546585257bf06073e2d894e8a04cf2376d",
"index": 727,
"step-1": "\"\"\"\nDuck typing\nRef: http://www.voidspace.org.uk/python/articles/duck_typing.shtml\n\"\"\"\n\n##########\n# mathmatic operator (syntactic sugar)\nprint 3 + 3\n# same as >>>\nprint int.__add__(3, 3)\n# <<<\n\n# overload '+' oper... | [
0
] |
from django.contrib import admin
from pharma_models.personas.models import Persona
admin.site.register(Persona)
| normal | {
"blob_id": "59d04ebd9a45c6a179a2da1f88f728ba2af91c05",
"index": 590,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Persona)\n",
"step-3": "from django.contrib import admin\nfrom pharma_models.personas.models import Persona\nadmin.site.register(Persona)\n",
"step-4": null,
"ste... | [
0,
1,
2
] |
import requests
import json
from termcolor import cprint
from pathlib import Path
import os
def console_check(csl, f):
if csl == 'playstation-4':
f.write('\tdbo:computingPlatform dbpedia:PlayStation_4.')
if csl == 'playstation-3':
f.write('\tdbo:computingPlatform dbpedia:PlayStation... | normal | {
"blob_id": "b290763362af96f5af03fa31f4936339cef66a1d",
"index": 2062,
"step-1": "<mask token>\n\n\ndef console_check(csl, f):\n if csl == 'playstation-4':\n f.write('\\tdbo:computingPlatform dbpedia:PlayStation_4.')\n if csl == 'playstation-3':\n f.write('\\tdbo:computingPlatform dbpedia:Pla... | [
6,
7,
8,
9,
10
] |
# import necessary modules
import cv2
import xlsxwriter
import statistics
from matplotlib import pyplot as plt
import math
import tqdm
import numpy as np
import datetime
def getDepths(imgs, img_names, intersectionCoords, stakeValidity, templateIntersections,
upperBorder, tensors, actualTensors, intersectionDist, b... | normal | {
"blob_id": "24a538dcc885b37eb0147a1ee089189f11b20f8a",
"index": 7945,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getDepths(imgs, img_names, intersectionCoords, stakeValidity,\n templateIntersections, upperBorder, tensors, actualTensors,\n intersectionDist, blobDistTemplate, debug, debu... | [
0,
1,
2,
3
] |
class Helper:
def __init__(self):
self.commands = ["help",
"lottery",
"poll",
"polling",
"prophecy",
"roll",
"team",
"ub"]
... | normal | {
"blob_id": "fdf76ff20260c25d95a9bf751fa78156071a7825",
"index": 7487,
"step-1": "class Helper:\n <mask token>\n <mask token>\n\n def display_command(self, command):\n if command not in self.commands:\n return \"That command doesn't exist :/\"\n result = f'__**Command: {command[... | [
2,
3,
4,
5,
6
] |
"""
An wrapper around openid's fetcher to be used in django.
"""
from openid import fetchers
class UrlfetchFetcher(fetchers.HTTPFetcher):
def fetch(self, url, body=None, headers=None):
return fetchers.fetch(body, headers)
| normal | {
"blob_id": "14e247b7b586242bfc17507fece3c60b7b8a3025",
"index": 9604,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass UrlfetchFetcher(fetchers.HTTPFetcher):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass UrlfetchFetcher(fetchers.HTTPFetcher):\n\n def fetch(self, url, body=None, h... | [
0,
1,
2,
3,
4
] |
#
# @lc app=leetcode id=14 lang=python3
#
# [14] Longest Common Prefix
#
# https://leetcode.com/problems/longest-common-prefix/description/
#
# algorithms
# Easy (34.95%)
# Likes: 2372
# Dislikes: 1797
# Total Accepted: 718.5K
# Total Submissions: 2M
# Testcase Example: '["flower","flow","flight"]'
#
# Write a f... | normal | {
"blob_id": "80be5f49a179eebc4915bf734a8e362cc2f2ef7c",
"index": 3213,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution:\n\n def longestCommonPrefix(self, strs: [str]) ->str:\n if not strs:\n return ''\n strs.... | [
0,
1,
2,
3,
4
] |
from kivy.app import App
from kivy.uix.floatlayout import FloatLayout
class LayoutWindow(FloatLayout):
pass
class floatlayoutApp(App):
def build(self):
return LayoutWindow()
if __name__== "__main__":
display = floatlayoutApp()
display.run() | normal | {
"blob_id": "2af8677e76b77b9bfa579012a85ea331c0c7f390",
"index": 136,
"step-1": "<mask token>\n\n\nclass floatlayoutApp(App):\n\n def build(self):\n return LayoutWindow()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass LayoutWindow(FloatLayout):\n pass\n\n\nclass floatlayoutApp(App):\n\n ... | [
2,
3,
4,
5,
6
] |
import tornado
import copy
class DjangoHandler(tornado.web.RequestHandler):
async def reroute(self):
http = tornado.httpclient.AsyncHTTPClient()
new_request = copy.deepcopy(self.request)
url_obj = copy.urlparse(new_request.url)
new_request.url = f"{url_obj.scheme}://localhost:9000... | normal | {
"blob_id": "6960fc6d949512ffc783b085041f86cb791160a3",
"index": 1500,
"step-1": "<mask token>\n\n\nclass DjangoHandler(tornado.web.RequestHandler):\n\n async def reroute(self):\n http = tornado.httpclient.AsyncHTTPClient()\n new_request = copy.deepcopy(self.request)\n url_obj = copy.urlp... | [
1,
3,
4,
5,
6
] |
import pandas as pd
from greyatomlib.pandas_project.q01_read_csv_data_to_df.build import read_csv_data_to_df
def get_runs_counts_by_match():
ipl_df = read_csv_data_to_df("data/ipl_dataset.csv")
df1 = pd.DataFrame(ipl_df[['match_code','runs','venue']])
df2 = df1.groupby(['match_code','runs'], as_index=Fals... | normal | {
"blob_id": "4f06d87ec79c20206ff45ba72ab77844076be553",
"index": 9707,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_runs_counts_by_match():\n ipl_df = read_csv_data_to_df('data/ipl_dataset.csv')\n df1 = pd.DataFrame(ipl_df[['match_code', 'runs', 'venue']])\n df2 = df1.groupby(['mat... | [
0,
1,
2,
3,
4
] |
import turtle
import random
import winsound
import sys
""" new_game = False
def toggle_new_game():
global new_game
if new_game == False:
new_game = True
else:
new_game = False """
wn = turtle.Screen()
wn.title("MaskUp")
wn.bgcolor("green")
wn.bgpic("retro_city_title... | normal | {
"blob_id": "1593280a29b13461b13d8b2805d9ac53ce94c759",
"index": 2948,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwn.title('MaskUp')\nwn.bgcolor('green')\nwn.bgpic('retro_city_title_page.gif')\nwn.setup(width=800, height=600)\nwn.tracer(0)\nwn.register_shape('human.gif')\n\n\ndef game_loop():\n sc... | [
0,
2,
3,
4,
5
] |
import wizard
import report
| normal | {
"blob_id": "9d07fd14825ed1e0210fa1f404939f68a3bb039c",
"index": 4762,
"step-1": "<mask token>\n",
"step-2": "import wizard\nimport report\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from abc import ABC, abstractmethod
from raspberry_home.view.geometry import *
from raspberry_home.view.renderable import Renderable
class View(Renderable, ABC):
@abstractmethod
def content_size(self, container_size: Size) ->Size:
pass
| normal | {
"blob_id": "913ff9b811d3abbe43bda0554e40a6a2c87053be",
"index": 4449,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass View(Renderable, ABC):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass View(Renderable, ABC):\n\n @abstractmethod\n def content_size(self, container_size: Size)... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import scrapy
import json, time, sys, random, re, pyssdb
from scrapy.utils.project import get_project_settings
from spider.items import GoodsSalesItem
goods_list = []
'''获取店铺内产品信息'''
class PddMallGoodsSpider(scrapy.Spider):
name = 'pdd_mall_goods'
mall_id_hash = 'pdd_mall_id_ha... | normal | {
"blob_id": "f33190df35a6b0b91c4dd2d6a58291451d06e29a",
"index": 3529,
"step-1": "<mask token>\n\n\nclass PddMallGoodsSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def start_requests(self):\n mall... | [
3,
4,
5,
9,
10
] |
__author__ = 'piotrek'
import os
import zipfile
import tarfile
from PyQt5 import QtWidgets
from PyQt5 import QtGui
from PyQt5 import QtCore
from Widgets.list_view import ListView
from Threads.PackThread import PackThread
class CreateArchive(QtWidgets.QDialog):
def __init__(self, model, index, path, parent=Non... | normal | {
"blob_id": "7a41826f65f2f55b4c678df2ac06027df6ca50d4",
"index": 3623,
"step-1": "<mask token>\n\n\nclass CreateArchive(QtWidgets.QDialog):\n <mask token>\n <mask token>\n\n def create_components(self):\n self.option_widget = QtWidgets.QWidget()\n self.name_lbl = QtWidgets.QLabel('Nazwa')\... | [
9,
10,
15,
16,
18
] |
import base64
code=b'CmltcG9ydCBweW1vbmdvCmltcG9ydCByYW5kb20KaW1wb3J0IHJlCmltcG9ydCBzdHJpbmcKaW1wb3J0IHN5cwppbXBvcnQgZ2V0b3B0CmltcG9ydCBwcHJpbnQKCiMgQ29weXJpZ2h0IDIwMTUKIyBNb25nb0RCLCBJbmMuCiMgQXV0aG9yOiBBbmRyZXcgRXJsaWNoc29uICAgYWplQDEwZ2VuLmNvbQojCiMgSWYgeW91IGFyZSBhIHN0dWRlbnQgYW5kIHJlYWRpbmcgdGhpcyBjb2RlLCB0dXJuIGJ... | normal | {
"blob_id": "c7f26978333c7e6cccf7451ea5d10511a66b62c2",
"index": 1908,
"step-1": "<mask token>\n",
"step-2": "<mask token>\neval(compile(base64.b64decode(code), '<string>', 'exec'))\n",
"step-3": "<mask token>\ncode = (\n b'CmltcG9ydCBweW1vbmdvCmltcG9ydCByYW5kb20KaW1wb3J0IHJlCmltcG9ydCBzdHJpbmcKaW1wb3J0IH... | [
0,
1,
2,
3,
4
] |
/home/lidija/anaconda3/lib/python3.6/sre_constants.py | normal | {
"blob_id": "700b0b12c75fa502da984319016f6f44bc0d52cc",
"index": 5126,
"step-1": "/home/lidija/anaconda3/lib/python3.6/sre_constants.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
#-*- coding: utf-8 -*-
from SPARQLWrapper import SPARQLWrapper, SPARQLWrapper2, JSON
import time, random
# testes
NOW=time.time()
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setQuery("""
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
SELECT ?label
WHERE { <http://dbpedia.org/resource/L... | normal | {
"blob_id": "c5b50420788ddde7483a46c66aca3922ddb47952",
"index": 6199,
"step-1": "<mask token>\n\n\ndef document_features(documento):\n features = {}\n for palavra in palavras_escolhidas:\n features['contains(%s)' % (palavra,)] = palavra in documento\n return features\n\n\n<mask token>\n",
"ste... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
#Title: ActFax 4.31 Local Privilege Escalation Exploit
#Author: Craig Freyman (@cd1zz)
#Discovered: July 10, 2012
#Vendor Notified: June 12, 2012
#Description: http://www.pwnag3.com/2012/08/actfax-local-privilege-escalation.html
#msfpayload windows/exec CMD=cmd.exe R | msfencode -e x86/alpha_u... | normal | {
"blob_id": "1b7048ef17b3512b9944ce7e197db27f4fd1aed0",
"index": 1687,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nf.write(\n 'User Name\\tEntire User Name\\tPassword\\tAlias-Names\\tGroup\\tDirect Dialing\\tCost Account\\tPermissions\\tComments\\tUser-Defined\\tPredefined Settings\\tName 1\\tName ... | [
0,
1,
2,
3
] |
"""
Contains derivative computation for BSSN formulation of ET equations.
"""
# first derivative
import cog
D = ["alpha", "beta0", "beta1", "beta2",
"B0", "B1", "B2",
"chi", "Gt0", "Gt1", "Gt2", "K",
"gt0", "gt1", "gt2", "gt3", "gt4", "gt5",
"At0", "At1", "At2", "At3", "At4", "At5" ]
# cust... | normal | {
"blob_id": "20a238826640099e6c69aaa383c5fa7e9b02b13b",
"index": 5614,
"step-1": "<mask token>\n\n\ndef allocDerivMemory():\n for deriv in FUNC_D_I:\n cog.outl('\\t double* ' + deriv +\n ' = (double*)malloc(sizeof(double)*n);')\n for deriv in FUNC_D_IJ:\n cog.outl('\\t double* ' + ... | [
3,
4,
5,
6,
7
] |
from . import *
from rest_framework import permissions
from core.serializers import CategorySerializer
from core.models.category_model import Category
class CategoryViewSet(viewsets.ModelViewSet):
serializer_class = CategorySerializer
queryset = Category.objects.all()
def get_permissions(self):
... | normal | {
"blob_id": "5723e7889663142832a8131bb5f4c35d29692a49",
"index": 6325,
"step-1": "<mask token>\n\n\nclass CategoryViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CategoryViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask tok... | [
1,
2,
3,
4,
5
] |
#!d:\python_projects\env2\scripts\python.exe
# EASY-INSTALL-DEV-SCRIPT: 'Django==2.1.dev20180209010235','django-admin.py'
__requires__ = 'Django==2.1.dev20180209010235'
__import__('pkg_resources').require('Django==2.1.dev20180209010235')
__file__ = 'D:\\python_projects\\ENV2\\django\\django\\bin\\django-admin.py'
exec(... | normal | {
"blob_id": "4bbf0a0fadc506ad3674912f1885525a94b5b1e9",
"index": 2807,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__import__('pkg_resources').require('Django==2.1.dev20180209010235')\n<mask token>\nexec(compile(open(__file__).read(), __file__, 'exec'))\n",
"step-3": "__requires__ = 'Django==2.1.dev... | [
0,
1,
2,
3
] |
#dict1 = {"я":"i","люблю":"love","Питон":"Рython"}
#user_input = input("---->")
#print(dict1[user_input])
#list1 =[i for i in range(0,101) if i%7 ==0 if i%5 !=0]
#print(list1)
#stroka = "я обычная строка быть которая должна быть длиннее чем десять символ"
#stroka1=stroka.split()
#dict1={}
#for i in stroka1:
# ... | normal | {
"blob_id": "c0512a90b6a4e50c41d630f6853d1244f78debfb",
"index": 4350,
"step-1": "#dict1 = {\"я\":\"i\",\"люблю\":\"love\",\"Питон\":\"Рython\"}\n#user_input = input(\"---->\")\n#print(dict1[user_input])\n\n\n#list1 =[i for i in range(0,101) if i%7 ==0 if i%5 !=0]\n#print(list1)\n\n\n\n#stroka = \"я обычная стро... | [
1
] |
import pandas as pd
import copy as cp
import numpy as np
from autoencoder import *
from encoding import smtEncoding
import matplotlib
import matplotlib.pyplot as plt
from data_generator import *
from marabou_encoding import marabouEncoding
def main():
'''
Trains an autoencoder on (generated) data and checks advers... | normal | {
"blob_id": "44e1208a2165fe68f71d0aa49baa29b26c961e02",
"index": 5681,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n \"\"\"\n\tTrains an autoencoder on (generated) data and checks adversarial robustness\n\t\"\"\"\n architecture = [10, 5, 10]\n print('----------Training autoenc... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
"""Server that accepts and executes control-type commands on the bot."""
import sys
import os
from inspect import getmembers, ismethod
from simplejson.decoder import JSONDecodeError
import zmq
import signal
# This is required to make imports work
sys.path = [os.getcwd()] + sys.path
import bot.l... | normal | {
"blob_id": "ddb81e3ce0df44ee503c558b68b41c35935358a0",
"index": 8663,
"step-1": "<mask token>\n\n\nclass CtrlServer(object):\n <mask token>\n <mask token>\n <mask token>\n\n def assign_subsystems(self):\n \"\"\"Instantiates and stores references to bot subsystems.\n\n :returns: Dict of... | [
10,
13,
16,
18,
19
] |
from funct import read_excel
import requests
import unittest
import HTMLTestReportCN
class v2exapi(unittest.TestCase):
def test_node_api(self):
url = "https://www.v2ex.com/api/nodes/show.json"
#querystring = {"name":"php"}
a=read_excel("xx.xlsx",0,0)
for node_name in a:
#fo... | normal | {
"blob_id": "5cd573f2b7f91a8b20e96deb1004c0ef7fc62398",
"index": 8072,
"step-1": "<mask token>\n\n\nclass v2exapi(unittest.TestCase):\n\n def test_node_api(self):\n url = 'https://www.v2ex.com/api/nodes/show.json'\n a = read_excel('xx.xlsx', 0, 0)\n for node_name in a:\n respon... | [
2,
3,
4,
5,
6
] |
import glob
from PIL import Image
from PIL.ExifTags import TAGS, GPSTAGS
from pyproj import Proj
from osgeo import gdal, osr
from PyQt4.QtCore import QFile, QFileInfo
import os
from os import walk
#slika="c:\slike\Zito\DJI_0060.jpg"
#georef_slika="c:\Slike\Zito\Georeferencirana.tif"
radni_dir = 'c:/slike/Zito... | normal | {
"blob_id": "e92d770f9d2176b4943653b09ac1069fa3301e46",
"index": 1931,
"step-1": "import glob\r\nfrom PIL import Image\r\nfrom PIL.ExifTags import TAGS, GPSTAGS\r\nfrom pyproj import Proj\r\nfrom osgeo import gdal, osr\r\nfrom PyQt4.QtCore import QFile, QFileInfo\r\nimport os\r\nfrom os import walk\r\n#slika=\"c... | [
0
] |
#!/usr/bin/python
##
# @file
# This file is part of SeisSol.
#
# @author Sebastian Rettenberger (rettenbs AT in.tum.de, http://www5.in.tum.de/wiki/index.php/Sebastian_Rettenberger,_M.Sc.)
#
# @section LICENSE
# Copyright (c) 2013, SeisSol Group
# All rights reserved.
#
# Redistribution and use in source and binary for... | normal | {
"blob_id": "91e1ac12ba99a8efd8f7f26310244d83bdd4aa52",
"index": 2510,
"step-1": "<mask token>\n\n\nclass Partitioner:\n <mask token>\n\n def __init__(self, mesh, partitions, tmpdir):\n metisMesh = tmpdir.path(METIS_MESH)\n metis.MeshWriter(metisMesh, mesh.elements())\n metisGraph = tm... | [
3,
4,
5,
6,
7
] |
# vim:fileencoding=utf-8:noet
from __future__ import absolute_import, unicode_literals, print_function
import os
BINDINGS_DIRECTORY = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'bindings')
TMUX_CONFIG_DIRECTORY = os.path.join(BINDINGS_DIRECTORY, 'tmux')
DEFAULT_SYSTEM_CONFIG_DIR = None
| normal | {
"blob_id": "c435b0f162512bb2bc0c35e1817f64c5ef9ff7bc",
"index": 1871,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nBINDINGS_DIRECTORY = os.path.join(os.path.dirname(os.path.abspath(__file__)\n ), 'bindings')\nTMUX_CONFIG_DIRECTORY = os.path.join(BINDINGS_DIRECTORY, 'tmux')\nDEFAULT_SYSTEM_CONFIG_DI... | [
0,
1,
2,
3
] |
import json
import logging
import os
import sys
from io import StringIO
import pytest
from allure.constants import AttachmentType
from utils.tools import close_popups
_beautiful_json = dict(indent=2, ensure_ascii=False, sort_keys=True)
# LOGGING console ##############################################################... | normal | {
"blob_id": "37fdfddb471e2eec9e5867d685c7c56fc38c5ae7",
"index": 8363,
"step-1": "<mask token>\n\n\nclass CustomLogger(logging.Logger):\n <mask token>\n\n @staticmethod\n def format_message(message):\n return json.dumps(message, **_beautiful_json) if isinstance(message,\n (dict, list, ... | [
10,
13,
14,
15,
16
] |
from django.db import models
from home.models import MainUser
from product.models import Product
# Create your models here.
class Cart(models.Model):
user = models.ForeignKey(MainUser,on_delete=models.CASCADE)
item = models.ForeignKey(Product, on_delete=models.CASCADE)
quantity = models.PositiveIntegerFiel... | normal | {
"blob_id": "454d210c1b1a41e4a645ef7ccb24f80ee20a451c",
"index": 2224,
"step-1": "<mask token>\n\n\nclass Cart(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def get_total(self):\n total = self.item.price ... | [
4,
5,
6,
7,
8
] |
def main():
piso = largura * comprimento
volume_sala = largura * comprimento * altura
area = 2 * altura * largura + 2 * altura * comprimento
print(piso)
print(volume_sala)
print(area)
altura = float(input(""))
largura = float(input(""))
comprimento = float(input(""))
if __name__ == '__main__':... | normal | {
"blob_id": "d78fd8ebf9ef55700a25a9ce96d9094f1bfa564e",
"index": 6455,
"step-1": "<mask token>\n",
"step-2": "def main():\n piso = largura * comprimento\n volume_sala = largura * comprimento * altura\n area = 2 * altura * largura + 2 * altura * comprimento\n print(piso)\n print(volume_sala)\n ... | [
0,
1,
2,
3,
4
] |
"""Wrapper over the command line migrate tool to better work with
config files."""
import subprocess
import sys
from alembic.migration import MigrationContext
from ..lib.alembic import bootstrap_db
from ..lib.sqla import create_engine
from ..models import DBSession as db
def main():
if len(sys.argv) < 3:
... | normal | {
"blob_id": "7b459cf321f351e1485a9aef0ca23067f411e430",
"index": 7446,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n if len(sys.argv) < 3:\n sys.stderr.write(\n 'Usage: %s CONFIG_URI {bootstrap | ALEMBIC_OPTS}\\n' % sys.argv[0])\n sys.exit(1)\n config_uri... | [
0,
1,
2,
3
] |
from locations.storefinders.stockinstore import StockInStoreSpider
class ScooterHutAUSpider(StockInStoreSpider):
name = "scooter_hut_au"
item_attributes = {"brand": "Scooter Hut", "brand_wikidata": "Q117747623"}
api_site_id = "10112"
api_widget_id = "119"
api_widget_type = "product"
api_origin... | normal | {
"blob_id": "e37f4422c1063df50453f7abf72a0a9a31156d8b",
"index": 899,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ScooterHutAUSpider(StockInStoreSpider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\... | [
0,
1,
2,
3,
4
] |
import shlex
class MockSOLR(object):
class MockHits(list):
@property
def hits(self):
return len(self)
@property
def docs(self):
return self
def __init__(self):
self.db = {}
def add(self, objects):
for o in objects:
o['... | normal | {
"blob_id": "4774c1f4eafc0132bab0073b60c4bcad6b69380d",
"index": 9068,
"step-1": "<mask token>\n\n\nclass MockSOLR(object):\n\n\n class MockHits(list):\n\n @property\n def hits(self):\n return len(self)\n\n @property\n def docs(self):\n return self\n <mask ... | [
3,
5,
6,
7,
8
] |
import xdrlib,sys
import xlrd
def open_excel(file='D:\基金公司\数据库-制表符\资产组合-基金公司维度.xlsx'):
try:
data=xlrd.open_workbook('D:\基金公司\数据库-制表符\资产组合-基金公司维度.xlsx')
return data
except Exception as e:
print (str(e))
def excel_table_byindex(file='D:\基金公司\数据库-制表符\资产组合-基金公司维度.xlsx',colnameindex=0,by_inde... | normal | {
"blob_id": "d211594a034489d36a5648bf0b926fbd734fd0df",
"index": 6928,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef excel_table_byindex(file='D:\\\\基金公司\\\\数据库-制表符\\\\资产组合-基金公司维度.xlsx',\n colnameindex=0, by_index=0):\n data = open_excel(file='D:\\\\基金公司\\\\数据库-制表符\\\\资产组合-基金公司维度.xlsx')\n ... | [
0,
1,
2,
3,
4
] |
import ZooAnnouncerInterface
class ZooAnnouncer(ZooAnnouncerInterface):
def updateZoo(self,annoucement):
print("ZooAnnouncer :" + annoucement) | normal | {
"blob_id": "be9c21ee04a612f711a1e6a82ea9478c77b62a82",
"index": 8112,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ZooAnnouncer(ZooAnnouncerInterface):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ZooAnnouncer(ZooAnnouncerInterface):\n\n def updateZoo(self, annoucement):\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding:utf-8 -*-
'''
Created on 2016��4��8��
@author: liping
'''
import sys
from PyQt4 import QtGui,QtCore
class QuitButton(QtGui.QWidget):
def __init__(self,parent = None):
QtGui.QWidget.__init__(self,parent)
self.setGeometry(300,300,250,150)
self.setWindowTitle('quitButto... | normal | {
"blob_id": "5a3431b79b8f42b3042bb27d787d0d92891a7415",
"index": 3947,
"step-1": "<mask token>\n\n\nclass QuitButton(QtGui.QWidget):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass QuitButton(QtGui.QWidget):\n\n def __init__(self, parent=None):\n QtGui.QWidget.__init__(self... | [
1,
3,
4,
5,
6
] |
"""
Base cache mechanism
"""
import time
import string
import codecs
import pickle
from functools import wraps
from abc import ABCMeta, abstractmethod
from asyncio import iscoroutinefunction
class BaseCache(metaclass=ABCMeta):
"""Base cache class."""
@abstractmethod
def __init__(self, kvstore, makekey, li... | normal | {
"blob_id": "e810cde7f77d36c6a43f8c277b66d038b143aae6",
"index": 6746,
"step-1": "<mask token>\n\n\nclass BaseCache(metaclass=ABCMeta):\n <mask token>\n\n @abstractmethod\n def __init__(self, kvstore, makekey, lifetime, fail_silent):\n self._kvstore = kvstore\n self._makekey = makekey\n ... | [
3,
4,
5,
6,
7
] |
import nltk
tw_dict = {'created_at':[],
'id':[],
'id_str':[],
'full_text':[],
'entities':[],
'source':[],
'user':[],
'lang':[]}
def Preprocessing(instancia):
# Remove caracteres indesejados.
instancia = re... | normal | {
"blob_id": "bffd211a2d2dc3dd9b596f69909be7f0437ab0c8",
"index": 9322,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Preprocessing(instancia):\n instancia = re.sub('#\\\\S+', '', instancia)\n instancia = re.sub('@\\\\S+', '', instancia).lower().replace('.', ''\n ).replace(';', '').r... | [
0,
1,
2,
3,
4
] |
t = eval(input())
while t:
t -= 1
y = []
z = []
x = str(input())
for i in range(len(x)):
if (not int(i)%2):
y.append(x[i])
else:
z.append(x[i])
print("".join(y) + " " + "".join(z))
| normal | {
"blob_id": "ac32fb5fcd71790f9dbf0794992a9dc92a202c9b",
"index": 7972,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile t:\n t -= 1\n y = []\n z = []\n x = str(input())\n for i in range(len(x)):\n if not int(i) % 2:\n y.append(x[i])\n else:\n z.appen... | [
0,
1,
2,
3
] |
# Copyright 2015 The TensorFlow Authors. 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 applica... | normal | {
"blob_id": "bf51da12632013c62aa543ae7f02415057138c7a",
"index": 694,
"step-1": "<mask token>\n\n\ndef get_qa_set(directory, jsonl_file):\n \"\"\"Download the WMT en-fr training corpus to directory unless it's there.\"\"\"\n set_name = os.path.splitext(os.path.basename(jsonl_file))[0]\n set_path = os.pa... | [
2,
3,
7,
8,
10
] |
import collections
import itertools
from . import stats
__all__ = [
'Party',
'HoR',
'Coalition'
]
Party = collections.namedtuple('Party', 'name,votes,seats')
class HoR(object):
"""House of Representatives"""
def __init__(self, parties, name='HoR'):
self.name = name
self._parties... | normal | {
"blob_id": "4c927f14065d0557dbe7b371002e133c351d3478",
"index": 6933,
"step-1": "<mask token>\n\n\nclass HoR(object):\n <mask token>\n\n def __init__(self, parties, name='HoR'):\n self.name = name\n self._parties = tuple(sorted(parties, key=lambda p: (p.seats, p.\n votes), reverse... | [
31,
32,
34,
36,
39
] |
# https://www.acmicpc.net/problem/20540
# 각 지표의 반대되는 지표를 저장한 dictionary
MBTI_reverse_index = {
'E': 'I',
'I': 'E',
'S': 'N',
'N': 'S',
'T': 'F',
'F': 'T',
'J': 'P',
'P': 'J'
}
# 연길이의 MBTI 4글자를 대문자로 입력
yeongil_MBTI = input()
# 연길이 MBTI의 각 지표에 반대되는 지표를 출력
for i in yeongil_MBTI:
prin... | normal | {
"blob_id": "c247b218267fc7c2bee93053dd90b2806572eaf2",
"index": 4234,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in yeongil_MBTI:\n print(MBTI_reverse_index[i], end='')\n",
"step-3": "MBTI_reverse_index = {'E': 'I', 'I': 'E', 'S': 'N', 'N': 'S', 'T': 'F', 'F':\n 'T', 'J': 'P', 'P': 'J'... | [
0,
1,
2,
3
] |
#
# o o
# 8
# .oPYo. .oPYo. odYo. o8P o8 .oPYo. odYo. .oPYo. .oPYo.
# Yb.. 8oooo8 8' `8 8 8 8oooo8 8' `8 8 ' 8oooo8
# 'Yb. 8. 8 8 8 8 8. 8 8 8 . 8.
# `YooP' `Yooo' 8 8 8 ... | normal | {
"blob_id": "c6357e6e0656388fc3fd849879aa6000e0bee1ee",
"index": 1553,
"step-1": "#\n# o o \n# 8 \n# .oPYo. .oPYo. odYo. o8P o8 .oPYo. odYo. .oPYo. .oPYo. \n# Yb.. 8oooo8 8' `8 8 8 8oooo8 8' `8 8 ' 8... | [
0
] |
import tensorflow as tf
import csv
from tensorflow.keras import layers
from tensorflow.keras.layers.experimental import preprocessing
import pandas as pd
import numpy as np
import random
import matplotlib.pyplot as plt
import math
def plot_loss(history):
plt.plot(history.history['loss'], label='loss')
plt.plot(his... | normal | {
"blob_id": "196147d7b2b0cf7176b5baa50d7e7618f88df493",
"index": 7911,
"step-1": "<mask token>\n\n\ndef plot_loss(history):\n plt.plot(history.history['loss'], label='loss')\n plt.plot(history.history['val_loss'], label='val_loss')\n plt.ylim([0, 10])\n plt.xlabel('Epoch')\n plt.ylabel('Error')\n ... | [
1,
2,
3,
4,
5
] |
import os
import shutil
import configparser
beatmap_dir = os.path.abspath(os.environ['LOCALAPPDATA']+'\\osu!\\Songs\\')
beatmaps = []
bm_osu = []
with os.scandir(os.path.abspath(beatmap_dir)) as it:
for entry in it:
if entry.is_dir():
try:
beatmap_id = int(str(entry.name).split... | normal | {
"blob_id": "cd34f9ef100ae6d116f02258d22c114ec3f3e3e6",
"index": 1581,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith os.scandir(os.path.abspath(beatmap_dir)) as it:\n for entry in it:\n if entry.is_dir():\n try:\n beatmap_id = int(str(entry.name).split(' ')[0])\n... | [
0,
1,
2,
3,
4
] |
from abc import abstractmethod
from suzieq.shared.sq_plugin import SqPlugin
class InventoryAsyncPlugin(SqPlugin):
"""Plugins which inherit this class will have methods 'run'
Once the controller check that the object inherit this class, it launches
a new task executing the run method.
"""
async d... | normal | {
"blob_id": "8b49aa63cc6e4490b7b22cd304dbba132962c870",
"index": 9049,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass InventoryAsyncPlugin(SqPlugin):\n <mask token>\n\n async def run(self):\n \"\"\"Background task to launch in order to execute the plugin\"\"\"\n try:\n ... | [
0,
1,
2,
3
] |
"""
This is a post login API and hence would have APIDetails and SessionDetails in the request object
-------------------------------------------------------------------------------------------------
Step 1: find if user's ip address is provided in the request object, if yes then got to step 2 else goto step 4
Step 2: ... | normal | {
"blob_id": "d7daf9b26f0b9f66b15b8533df032d17719e548b",
"index": 3343,
"step-1": "<mask token>\n",
"step-2": "\"\"\"\nThis is a post login API and hence would have APIDetails and SessionDetails in the request object\n----------------------------------------------------------------------------------------------... | [
0,
1
] |
import sys
from photo_dl.request import request
from photo_dl.request import MultiRequest
class Jav_ink:
def __init__(self):
self.parser_name = 'jav_ink'
self.domain = 'https://www.jav.ink'
self.album_flag = {}
@staticmethod
def category2albums(category_url):
category_url ... | normal | {
"blob_id": "9fff345dedcfc7051a258bc471acf07aece95bcf",
"index": 9319,
"step-1": "<mask token>\n\n\nclass Jav_ink:\n\n def __init__(self):\n self.parser_name = 'jav_ink'\n self.domain = 'https://www.jav.ink'\n self.album_flag = {}\n <mask token>\n\n def album2photos(self, album_url,... | [
3,
4,
5,
6,
7
] |
w = int(input("Width ?"))
h= int(input("Height ?"))
for b in range(1,w+1):
print ("*", end='')
print("")
for i in range(1,h-1):
print ("*", end='')
for j in range(1,w-1):
print (" ", end='')
print ("*", end='')
print("")
for b in range(1,w+1):
print ("*", end='')
print("") | normal | {
"blob_id": "32b961f3971819fdbbe1a30fd7cf1883353c1854",
"index": 2294,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor b in range(1, w + 1):\n print('*', end='')\nprint('')\nfor i in range(1, h - 1):\n print('*', end='')\n for j in range(1, w - 1):\n print(' ', end='')\n print('*', ... | [
0,
1,
2,
3
] |
#!/bin/python3
import sys
def fibonacciModified(t1, t2, n):
ti = t1
ti_1 = t2
for i in range (2, n):
ti_2 = ti + ti_1**2
ti = ti_1
ti_1 = ti_2
return ti_2
if __name__ == "__main__":
t1, t2, n = input().strip().split(' ')
t1, t2, n = [int(t1), int(t2), int(n)]
resul... | normal | {
"blob_id": "3838df627318b25767738da912f44e494cef40f3",
"index": 6833,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fibonacciModified(t1, t2, n):\n ti = t1\n ti_1 = t2\n for i in range(2, n):\n ti_2 = ti + ti_1 ** 2\n ti = ti_1\n ti_1 = ti_2\n return ti_2\n\n\n<... | [
0,
1,
2,
3,
4
] |
import numpy as np
import cv2
from camera import load_K, load_camera_dist, load_camera_ret
def undistort_img(img):
'''
Return an undistorted image given previous calibrated parameters
References from OpenCV docs
'''
ret = load_camera_ret()
K = load_K()
dist = load_camera_dist()
h,w = img.sha... | normal | {
"blob_id": "844c630d3fe2dda833064556228b524608cfece9",
"index": 4671,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef undistort_img(img):\n \"\"\"\n Return an undistorted image given previous calibrated parameters \n References from OpenCV docs\n \"\"\"\n ret = load_camera_ret()\n K =... | [
0,
1,
2,
3
] |
from scipy.stats import rv_discrete
import torch
import torch.nn.functional as F
import numpy as np
from utils import *
def greedy_max(doc_length,px,sentence_embed,sentences,device,sentence_lengths,length_limit=200,lamb=0.2):
'''
prob: sum should be 1
sentence embed: [doc_length, embed_dim]
'''
x = list(range(do... | normal | {
"blob_id": "cc6e827eec5256ce0dbe13958b6178c59bcd94a7",
"index": 8802,
"step-1": "<mask token>\n\n\ndef compute_reward(score_batch, input_lengths, output, sentences_batch,\n reference_batch, device, sentence_lengths_batch, number_of_sample=5,\n lamb=0.1):\n reward_batch = []\n rl_label_batch = torch.... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
import sys
PY2 = sys.version_info[0] == 2
if PY2:
text_type = unicode
string_types = basestring,
else:
text_type = str
string_types = str,
def with_metaclass(meta, *bases):
# This requires a bit of explanation: the basic idea is to make a dummy
# met... | normal | {
"blob_id": "414cb9a173ac70ad9ad1fc540aec569321fd3f8b",
"index": 9477,
"step-1": "<mask token>\n\n\ndef with_metaclass(meta, *bases):\n\n\n class metaclass(meta):\n\n def __new__(cls, name, this_bases, d):\n return meta(name, bases, d)\n return type.__new__(metaclass, 'temporary_class', (... | [
1,
2,
3,
4,
5
] |
class Wspak:
"""Iterator zwracający wartości w odwróconym porządku"""
def __init__(self, data):
self.data = data
self.index = -2
self.i=len(data)-1
def __iter__(self):
return self
def __next__(self):
if self.index >= self.i:
raise StopIteration
... | normal | {
"blob_id": "ea1d62c4a8c406dde9bb138ee045be5e682fdbfe",
"index": 566,
"step-1": "class Wspak:\n <mask token>\n\n def __init__(self, data):\n self.data = data\n self.index = -2\n self.i = len(data) - 1\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Wspak:\n... | [
2,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
# Copyright 2015 Donne Martin. 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. A copy of
# the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "lice... | normal | {
"blob_id": "a649139a600cb506056a20e00089a07ec9244394",
"index": 858,
"step-1": "<mask token>\n\n\nclass Config(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask t... | [
13,
15,
16,
18,
22
] |
count = 0
maximum = -1
m = -1
while m != 0:
m = int(input())
if m > maximum:
maximum = m
count = 1
elif m == maximum:
count += 1
print(count)
| normal | {
"blob_id": "0e1ea8c7fba90c1b5d18eaa399b91f237d4defee",
"index": 2568,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile m != 0:\n m = int(input())\n if m > maximum:\n maximum = m\n count = 1\n elif m == maximum:\n count += 1\nprint(count)\n",
"step-3": "count = 0\nmaxi... | [
0,
1,
2
] |
5 1
6 1x
1112#Desember@@@@@ | normal | {
"blob_id": "b324c520400f04719b17121b0b4c2d23915e8841",
"index": 2666,
"step-1": "5 1\r\n6 1x\r\n1112#Desember@@@@@",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
from math import ceil, log2, sqrt
def constructST(s, start, end, st, i):
if start == end:
st[i] = 0
openst[i] = 1 if s[start] == '(' else 0
closedst[i] = 1 if s[start] == ')' else 0
return st[i], openst[i], closedst[i]
else:
mid = (start+end)//2
st[i], openst[i], closedst[i] = constructST(s, ... | normal | {
"blob_id": "ccc74f58eff3bb00f0be8c2c963de4208b7f0933",
"index": 9125,
"step-1": "<mask token>\n\n\ndef constructST(s, start, end, st, i):\n if start == end:\n st[i] = 0\n openst[i] = 1 if s[start] == '(' else 0\n closedst[i] = 1 if s[start] == ')' else 0\n return st[i], openst[i],... | [
2,
3,
4,
5,
6
] |
import docker
import logging
import sys
if __name__ == '__main__':
# setting up logger
logging.basicConfig(stream=sys.stdout,
format='[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',
level=logging.DEBUG)
# get the docker client
clie... | normal | {
"blob_id": "a5c9ff1fe250310216e2eaa7a6ff5cc76fc10f94",
"index": 4324,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logging.basicConfig(stream=sys.stdout, format=\n '[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',\n level=logging.DEBUG... | [
0,
1,
2,
3
] |
import numpy as np
mydict = {}
mylist0 = np.array([1, 2, 3, 4, 5])
mylist1 = np.array([2, 3, 4, 5, 6])
print(mydict)
print(mylist0)
print(mylist1)
for c in ('0', '1'):
if c in mydict:
mydict[c] += mylist0
else:
mydict[c] = mylist0
print(mydict)
for c in ('0', '1'):
if c in mydict:
my... | normal | {
"blob_id": "6e5b8be6182f39f185f4547f0abd84a4e404bf34",
"index": 1861,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(mydict)\nprint(mylist0)\nprint(mylist1)\nfor c in ('0', '1'):\n if c in mydict:\n mydict[c] += mylist0\n else:\n mydict[c] = mylist0\nprint(mydict)\nfor c in ('0... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals, absolute_import
from datetime import datetime
try:
from unittest.mock import patch
except ImportError:
from mock import patch
import pytest
from django.test import TestCase
try:
from django.test import override_settings
except ImportError:
... | normal | {
"blob_id": "71f9d9d7973809654db3ea613073f2d431f2d65f",
"index": 1510,
"step-1": "<mask token>\n\n\n@override_settings(USE_TZ=False)\nclass TestEmailUserManager(TestCase):\n\n def setUp(self):\n self.email = 'user@example.com'\n self.password = 'default'\n\n def test_private_create_user_witho... | [
7,
9,
10,
11,
12
] |
def regexp_engine(pattern, letter):
return pattern in ('', '.', letter)
def match_regexp(pattern, substring):
if not pattern: # pattern is empty always True
return True
if substring: # if string is not empty try the regexp engine
if regexp_engine(pattern[0], substring[0]): # if reg and ... | normal | {
"blob_id": "fbfc1749252cf8cbd9f8f72df268284d3e05d6dc",
"index": 8024,
"step-1": "<mask token>\n\n\ndef match_regexp(pattern, substring):\n if not pattern:\n return True\n if substring:\n if regexp_engine(pattern[0], substring[0]):\n return match_regexp(pattern[1:], substring[1:])\... | [
1,
2,
3,
4,
5
] |
'''
You're playing casino dice game. You roll a die once. If you reroll, you earn the amount equal to the number on your second roll otherwise, you earn the amount equal to the number on your first roll.
Assuming you adopt a profit-maximizing strategy, what would be the expected amount of money you would win?
This qu... | normal | {
"blob_id": "e5d704541acd0f68a7885d7323118e1552e064c9",
"index": 6170,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor threshold in range(1, 6):\n rolls = np.random.randint(1, 7, size=10 ** 7)\n rerolls = np.random.randint(1, 7, size=10 ** 7)\n avg_roll = np.mean(np.where(rolls <= threshold, ... | [
0,
1,
2,
3
] |
import pandas as pd
from sklearn.tree import DecisionTreeClassifier # Import Decision Tree Classifier
from sklearn.model_selection import train_test_split # Import train_test_split function
from sklearn import metrics #Import scikit-learn metrics module for accuracy calculation
from sklearn.tree import DecisionTreeRegr... | normal | {
"blob_id": "1e34087719f6fd0456d2722edbd0a7af68d37e4c",
"index": 1577,
"step-1": "<mask token>\n\n\ndef read_atomic_data(path):\n if not path or not os.path.exists(path) or not os.path.isfile(path):\n print('To begin with, your path to data should be proper!')\n sys.exit(1)\n df = pd.read_csv... | [
2,
3,
4,
5,
6
] |
import tensorflow as tf
from typing import Optional, Tuple, Union, Callable
_data_augmentation = tf.keras.Sequential(
[
tf.keras.layers.experimental.preprocessing.RandomFlip("horizontal"),
tf.keras.layers.experimental.preprocessing.RandomRotation(0.2),
]
)
def _freeze_model(
model: tf.ker... | normal | {
"blob_id": "86d42716e05155f9e659b22c42635a8f5b8c4a60",
"index": 753,
"step-1": "<mask token>\n\n\ndef generate_model(base_model: tf.keras.Model, img_shape: Tuple[Optional[\n int], Optional[int], Optional[int]], freeze: Union[bool, int, float]=\n False, preprocess_input: Optional[Callable]=None, use_data_a... | [
1,
2,
3,
4,
5
] |
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to us... | normal | {
"blob_id": "b77c40c89c88b49c851e9a14c67cf0799d6de847",
"index": 9235,
"step-1": "<mask token>\n\n\ndef register(locator: str, entry_point, **kwargs):\n \"\"\"Register an AgentSpec with the zoo.\n\n In order to load a registered AgentSpec it needs to be reachable from a\n directory contained in the PYTH... | [
2,
3,
4,
5,
6
] |
"""Command 'run' module."""
import click
from loguru import logger
from megalus.main import Megalus
@click.command()
@click.argument("command", nargs=1, required=True)
@click.pass_obj
def run(meg: Megalus, command: str) -> None:
"""Run selected script.
:param meg: Megalus instance
:param command: comma... | normal | {
"blob_id": "23a4ca8eec50e6ab72be3f1b1077c61f676b3cce",
"index": 5777,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@click.command()\n@click.argument('command', nargs=1, required=True)\n@click.pass_obj\ndef run(meg: Megalus, command: str) ->None:\n \"\"\"Run selected script.\n\n :param meg: M... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
import pandas
from matplotlib import pyplot as plt
from sklearn.tree import DecisionTreeRegressor
from sklearn.ensemble import AdaBoostRegressor
import numpy as np
from sklearn.metrics import mean_absolute_error, mean_squared_error
from math import sqrt
def main():
df = pandas.read_csv("201... | normal | {
"blob_id": "e35dbcdef8779ffabc34b5e5c543e35b29523971",
"index": 7989,
"step-1": "<mask token>\n\n\ndef make_scatter(df):\n plt.figure(figsize=(8, 6))\n plt.plot(df['Start station number'], df['Counts'], 'o')\n plt.xlabel('Station')\n plt.ylabel('Counts')\n plt.show()\n return\n\n\ndef train_pr... | [
3,
4,
5,
6,
7
] |
import requests
from bs4 import BeautifulSoup
class Book:
def __init__(self, url):
self.url = url
self.title = ""
self.category = ""
self.upc=""
self.price_including_tax=""
self.price_excluding_tax=""
self.number_available=""
self.description=""
... | normal | {
"blob_id": "3dc83168264fbb4f9b0ab2980b845dffdc4417bb",
"index": 7588,
"step-1": "<mask token>\n\n\nclass Book:\n\n def __init__(self, url):\n self.url = url\n self.title = ''\n self.category = ''\n self.upc = ''\n self.price_including_tax = ''\n self.price_excluding_... | [
11,
12,
13,
15,
16
] |
import pygame
from pygame.sprite import Sprite
import spritesheet
class Bunker(Sprite):
def __init__(self, ai_settings, bunker_x, bunker_y, screen, images):
"""Initialize the ship and set its starting position"""
super(Bunker, self).__init__()
self.screen = screen
self.images = ima... | normal | {
"blob_id": "d088aadc4d88267b908c4f6de2928c812ef36739",
"index": 1603,
"step-1": "<mask token>\n\n\nclass Bunker(Sprite):\n <mask token>\n <mask token>\n\n def blitme(self):\n \"\"\"Draw the ship at its current location\"\"\"\n self.screen.blit(self.image, self.rect)\n",
"step-2": "<mask... | [
2,
3,
4,
5,
6
] |
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
from app import app
layout = html.Div([
html.H3('Node 6'),
dcc.Dropdown(
id='node-6-dropdown',
options=[
{'label': 'Node 6 - {}'.format(i), 'value': i} for ... | normal | {
"blob_id": "632b90ea5a2ac35539e589af297c04b31bbf02d0",
"index": 3443,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.callback(Output('node-6-display-value', 'children'), [Input(\n 'node-6-dropdown', 'value')])\ndef display_value(value):\n return 'You have selected \"{}\"'.format(value)\n"... | [
0,
1,
2,
3,
4
] |
valor1=input("Ingrese Primera Cantidad ")
valor2=input("Ingrese Segunda Cantidad ")
Total = valor1 + valor2
print "El total es: " + str(Total)
| normal | {
"blob_id": "5c179752f4c4e1d693346c6edddd79211a895735",
"index": 8685,
"step-1": "valor1=input(\"Ingrese Primera Cantidad \")\nvalor2=input(\"Ingrese Segunda Cantidad \")\nTotal = valor1 + valor2\nprint \"El total es: \" + str(Total)\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"... | [
0
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, with_statement
"""
cosi299a- Cinderella
alexluu@brandeis.edu
"""
def truecase_is(string):
""" -> lower/title/upper/other """
if string.islower():
return 'l'
if string.istitle():
return 't'
if string... | normal | {
"blob_id": "75ddcdd4e80b962198ff9de1d996837927c3ac1a",
"index": 824,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef truecase_is(string):\n \"\"\" -> lower/title/upper/other \"\"\"\n if string.islower():\n return 'l'\n if string.istitle():\n return 't'\n if string.isuppe... | [
0,
3,
4,
5,
6
] |
from .personal_questions import *
from .survey_questions import *
| normal | {
"blob_id": "a8f2d527e9824d3986f4bb49c3cc75fd0d999bf7",
"index": 3290,
"step-1": "<mask token>\n",
"step-2": "from .personal_questions import *\nfrom .survey_questions import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019/6/26 16:11
# @Author : Micky
# @Site :
# @File : 01_压缩相关知识.py
# @Software: PyCharm
import numpy as np
from PIL import Image
from scipy import misc
if __name__ == '__main__':
# 图像加载
image = Image.open('../datas/xiaoren.png')
# 图像转换为num... | normal | {
"blob_id": "176120d4f40bc02b69d7283b7853b74adf369141",
"index": 4726,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n image = Image.open('../datas/xiaoren.png')\n img = np.asarray(image)\n print(img.shape)\n imageNew = np.zeros((600, 100, 3))\n imageNew = image... | [
0,
1,
2,
3
] |
# Copyright (C) 2011 Ruckus Wireless, Inc. All rights reserved.
# Please make sure the following module docstring is accurate since it will be used in report generation.
"""
Description:
@author: Chris Wang
@contact: cwang@ruckuswireless.com
@since: Aug-09, 2010
Prerequisite (Assumptions about the sta... | normal | {
"blob_id": "25288a6dd0552d59f8c305bb8edbbbed5d464d5b",
"index": 9997,
"step-1": "# Copyright (C) 2011 Ruckus Wireless, Inc. All rights reserved.\n# Please make sure the following module docstring is accurate since it will be used in report generation.\n\n\"\"\"\n Description: \n @author: Chris Wang\n @con... | [
0
] |
from functools import reduce
import confuse
config = confuse.Configuration('SleepCycleWebhooks')
config.set_file('config.yaml')
def get(path):
return reduce(lambda view, part: view[part], path.split('.'), config).get()
| normal | {
"blob_id": "16879598a8b1a0b23c5ea6de18f8fb0b0b77201c",
"index": 1360,
"step-1": "<mask token>\n\n\ndef get(path):\n return reduce(lambda view, part: view[part], path.split('.'), config).get()\n",
"step-2": "<mask token>\nconfig.set_file('config.yaml')\n\n\ndef get(path):\n return reduce(lambda view, par... | [
1,
2,
3,
4
] |
import time
import torch
from torch.utils.data import DataLoader
from nn_model import NNModel
def train(dataset: 'Dataset', epochs: int=10):
loader = DataLoader(dataset, batch_size=2, shuffle=True)
model = NNModel(n_input=2, n_output=3)
# model.to(device='cpu')
optimizer = torch.optim.Adam(model.p... | normal | {
"blob_id": "68bcb76a9c736e21cc1f54c6343c72b11e575b5d",
"index": 5093,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef train(dataset: 'Dataset', epochs: int=10):\n loader = DataLoader(dataset, batch_size=2, shuffle=True)\n model = NNModel(n_input=2, n_output=3)\n optimizer = torch.optim.A... | [
0,
1,
2,
3
] |
# Copyright (C) 2019 Catalyst Cloud Ltd
#
# 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 applicable la... | normal | {
"blob_id": "cc23eeed44ff66d68c700163cca8b9f4986d497d",
"index": 7681,
"step-1": "<mask token>\n\n\nclass BaseTask(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mas... | [
14,
17,
18,
20,
26
] |
run=[] #Creating a empty list
no_players=int(input("enter the number of the players in the team :"))
for i in range (no_players):
run_score=int(input("Enter the runs scored by the player "+str(i+1)+":"))
run.append(run_score)
#code for the average score of the team
def average(run):
print("________... | normal | {
"blob_id": "3d7ca468a1f7aa1602bff22167e9550ad515fa79",
"index": 4777,
"step-1": "<mask token>\n\n\ndef average(run):\n print('____________________________________')\n sum = 0\n for i in range(0, len(run)):\n sum += run[i]\n avg = sum / len(run)\n print('Average score of the team is :',... | [
4,
5,
6,
7,
8
] |
# Copyright 2023 Sony Group Corporation.
#
# 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 applicable law or agreed to ... | normal | {
"blob_id": "32f10c3e73a3d792416f6b2841a80f8b3c390e8c",
"index": 9194,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef ref_mod2(x0, x1, fmod):\n if x0.dtype == np.float32 or fmod == True:\n return np.fmod(x0, x1)\n else:\n return np.mod(x0, x1)\n\n\n@pytest.mark.parametrize('ct... | [
0,
2,
3,
4,
5
] |
from django.apps import AppConfig
class ActivityConfig(AppConfig):
name = 'apps.activity'
| normal | {
"blob_id": "2a69aa0cd9d0e39ad82d6a354e956bdad0648797",
"index": 2252,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ActivityConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ActivityConfig(AppConfig):\n name = 'apps.activity'\n",
"step-4": "from django.apps im... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.3 on 2018-12-20 13:06
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('login', '0006_usermovies_img'),
]
operations = [
migrations.AddField(
... | normal | {
"blob_id": "e67cbddf10440e8a31373e05a82840677d3045f5",
"index": 4388,
"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 = [('login', '00... | [
0,
1,
2,
3,
4
] |
def sort_descending(numbers):
numbers.sort(reverse=True)
| normal | {
"blob_id": "46dc9917d9b3a7caf8d7ba5024b17d3b755fc5db",
"index": 7278,
"step-1": "<mask token>\n",
"step-2": "def sort_descending(numbers):\n numbers.sort(reverse=True)\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# Lists are sequence of objects
# Mutable
# Lists are represented within square brackets and items are seperated by commas
#-----------------------------------Lists-----------------------------------#
# Lists of Numbers
print("\n1. Lists of Numbers")
print("\t" + str([1,2,3]))
# Lists of Strings
print("\n2. Lists of ... | normal | {
"blob_id": "4d35bb83378805daf4392a1752386ab1403404e0",
"index": 1530,
"step-1": "<mask token>\n",
"step-2": "print(\"\"\"\n1. Lists of Numbers\"\"\")\nprint('\\t' + str([1, 2, 3]))\nprint(\"\"\"\n2. Lists of Strings\"\"\")\nprint('\\t' + str(['Lemon', 'Mango', 'Papaya']))\n<mask token>\nprint('\\tMy favorite ... | [
0,
1,
2,
3
] |
import boto3
import time
import datetime
from datetime import date
import sqlite3
import logging
import logging.handlers
from decimal import *
### LOGS CONFIGURATION ###
LOG_FILENAME = '/home/pi/Thermostat/alexaThermostat/logs/alexaThermostat.out'
# Set up a specific logger with our desired output level
my_logger = l... | normal | {
"blob_id": "fcc75550e1317a15c36bc8100c28af59b68e1381",
"index": 1571,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmy_logger.setLevel(logging.DEBUG)\n<mask token>\nhandler.setFormatter(formatter)\nmy_logger.addHandler(handler)\n<mask token>\nwhile 1:\n c.execute(\n 'SELECT * FROM TEMP_HIST W... | [
0,
1,
2,
3,
4
] |
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