code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
#!/usr/bin/python
# Point of origin (connector J3, pad 1, net 3V3)
x = 0.0
y = 0.0
drillDiameter = 1.0
padWidth = 1.6
from os.path import exists
from pad import *
filename="iCEstick.kicad_mod"
header = ""
footer = ""
if exists(filename):
# Read existing footprint
f = open(filename)
footprint = f.read... | normal | {
"blob_id": "c71e367ad320d7eadabbbfda728d94448db6441d",
"index": 2109,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif exists(filename):\n f = open(filename)\n footprint = f.read()\n f.close()\n headerEndIndex = footprint.find('(pad ')\n header = footprint[:headerEndIndex]\n lastPadIn... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@gen.coroutine
def pop_promotion_key(promotion_key):
conn = yield connection()
result = yield r.table('promotion_keys').get(promotion_key).delete(
return_changes=True).run(conn)
if result['changes']:
return result['changes'][0]['old_val']
return None
<|re... | flexible | {
"blob_id": "66cdfdfa797c9991e5cb169c4b94a1e7041ca458",
"index": 4772,
"step-1": "<mask token>\n\n\n@gen.coroutine\ndef pop_promotion_key(promotion_key):\n conn = yield connection()\n result = yield r.table('promotion_keys').get(promotion_key).delete(\n return_changes=True).run(conn)\n if result[... | [
1,
2,
3,
4,
5
] |
#https://codeforces.com/problemset/problem/1321/A
n=int(input())
r=list(map(int,input().split()))
b=list(map(int,input().split()))
l=[0]*n
x=0
y=0
for i in range(n):
if r[i]-b[i]==1:
x+=1
elif r[i]-b[i]==-1:
y+=1
if x==0:
print(-1)
else:
print(y//x+min(y%x+1,1))
| normal | {
"blob_id": "7aa6bba8483082354a94ed5c465e59a0fc97fe23",
"index": 1248,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n if r[i] - b[i] == 1:\n x += 1\n elif r[i] - b[i] == -1:\n y += 1\nif x == 0:\n print(-1)\nelse:\n print(y // x + min(y % x + 1, 1))\n",
"s... | [
0,
1,
2,
3
] |
import requests
import json
import datetime
from bs4 import BeautifulSoup
from pymongo import MongoClient, UpdateOne
import sys
#usage: python freesound_crawler.py [from_page] [to_page]
SOUND_URL = "https://freesound.org/apiv2/sounds/"
SEARCH_URL = "https://freesound.org/apiv2/search/text/"
AUTORIZE_URL = "https://fr... | normal | {
"blob_id": "2294dc21ede759e755e51471705fa8ef784528a7",
"index": 8707,
"step-1": "import requests\nimport json\nimport datetime\nfrom bs4 import BeautifulSoup\nfrom pymongo import MongoClient, UpdateOne\nimport sys\n\n#usage: python freesound_crawler.py [from_page] [to_page]\n\nSOUND_URL = \"https://freesound.or... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "3b42e218acf1c93fab3a0893efa8bf32a274eb23",
"index": 448,
"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 = [('interface', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pull_links(artist)
<|reserved_special_token_0|>
os.remove('./links.json')
shutil.rmtree('./songs')
<|reserved_special_token_0|>
for song in sentimentScores:
print(song + ': ')
print(sentimentScores[song])
<|reserved_spec... | flexible | {
"blob_id": "5055743c9ed8c92bcfab5379162f28315409ff91",
"index": 2200,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npull_links(artist)\n<mask token>\nos.remove('./links.json')\nshutil.rmtree('./songs')\n<mask token>\nfor song in sentimentScores:\n print(song + ': ')\n print(sentimentScores[song])... | [
0,
1,
2,
3,
4
] |
import json
from bottle import request, response, route, get, run, default_app
app = application = default_app()
@route('/candidate/hired', method=['POST'])
def update_delete_handler():
response.content_type = 'application/json'
return json.dumps({"hired": True})
def main():
run(host='localhost', port... | normal | {
"blob_id": "50e759ff24cdb8fbb5a98d9381afb13ebc1a74f1",
"index": 7317,
"step-1": "<mask token>\n\n\n@route('/candidate/hired', method=['POST'])\ndef update_delete_handler():\n response.content_type = 'application/json'\n return json.dumps({'hired': True})\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def group_by_owners(files):
print(files, type(files))
for k, v in files.items():
print(k, v)
for f in files:
print(f[0])
for g in v:
print(g)
_files = sorted(files.items(), key=operator.itemgetter(1), reverse=False)
print('Sorted: ',... | flexible | {
"blob_id": "4843239a41fe1ecff6c8c3a97aceef76a3785647",
"index": 7334,
"step-1": "<mask token>\n\n\ndef group_by_owners(files):\n print(files, type(files))\n for k, v in files.items():\n print(k, v)\n for f in files:\n print(f[0])\n for g in v:\n print(g)\n _files = so... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
plt.imshow(img_var, cmap='gray')
<|reserved_special_token_0|>
plt.imshow(filtered_image, cmap='gray')
<|reserved_special_token_0|>
plt.imshow(entropy_img)
plt.hist(entropy_img.flat, bins=100, range=(0, 7))
<|reserved_special_token... | flexible | {
"blob_id": "ab6c3d3c6faa2d1fe5e064dbdebd8904b9434f15",
"index": 5214,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nplt.imshow(img_var, cmap='gray')\n<mask token>\nplt.imshow(filtered_image, cmap='gray')\n<mask token>\nplt.imshow(entropy_img)\nplt.hist(entropy_img.flat, bins=100, range=(0, 7))\n<mask t... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
cursor.execute(sql)
db.close()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db = pymysql.connect('localhost', 'root', '', 'order_db', use_unicode=True,
charset='utf8')
cursor = db.cursor()
sql = 'DROP TABLE cus... | flexible | {
"blob_id": "1aa2bff245322a34438cc836e23f430926dfac6c",
"index": 3414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncursor.execute(sql)\ndb.close()\n",
"step-3": "<mask token>\ndb = pymysql.connect('localhost', 'root', '', 'order_db', use_unicode=True,\n charset='utf8')\ncursor = db.cursor()\nsql ... | [
0,
1,
2,
3,
4
] |
import unittest
import ConvertListToDict as cldf
class MyDictTestCase(unittest.TestCase):
def test_Dict(self):
# Testcase1 (len(keys) == len(values))
actualDict1 = cldf.ConvertListsToDict([1, 2, 3],['a','b','c'])
expectedDict1 = {1: 'a', 2: 'b', 3: 'c'}
self.assertEqual(actualDict1,... | normal | {
"blob_id": "3421c3b839721694945bdbb4f17183bceaed5296",
"index": 786,
"step-1": "<mask token>\n\n\nclass MyDictTestCase(unittest.TestCase):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass MyDictTestCase(unittest.TestCase):\n\n def test_Dict(self):\n actualDict1 = cldf.Conve... | [
1,
2,
3,
4,
5
] |
"""
*********************************************************************
* Project : POP1 (Practical Exam)
* Program name : q2.py
* Author : varunk01
* Purpose : Attempts to solve the question 2 from the exam paper
* Date created : 28/05/2018
*
* Date Author Ver Comment
* 28/05/2018 varunk... | normal | {
"blob_id": "f7d487ec99e2fa901677ab9aec0760a396722e12",
"index": 8245,
"step-1": "<mask token>\n\n\ndef get_choice(attempt):\n \"\"\"\n return an integer input from the user\n \"\"\"\n try:\n user_text = ''\n if attempt == 1:\n user_text = 'Guess a number between 0 and 99:'\n... | [
2,
3,
4,
5,
6
] |
import os
from NeuralEmulator.Configurators.NormalLeakSourceConfigurator import NormalLeakSourceConfigurator
from NeuralEmulator.Configurators.OZNeuronConfigurator import OZNeuronConfigurator
from NeuralEmulator.Configurators.PulseSynapseConfigurator import PulseSynapseConfigurator
from NeuralEmulator.NormalLeakS... | normal | {
"blob_id": "177401f25471cf1cbd32dd0770acdc12bf271361",
"index": 8030,
"step-1": "<mask token>\n\n\nclass NeuronsGenerator:\n\n def __init__(self, neuronsNumber, synapse, lowerBound=100.0 * 10 ** -3,\n upperBound=800.0 * 10 ** -3, randomVals=False):\n noramalLeakSourceConfigurator = NormalLeakSo... | [
3,
4,
5,
6,
7
] |
'''
Note: a TimeOutException appear when distance even 0.
'''
import smbus
import time
#slave arduino address
address_arduino = 0x04
bus = smbus.SMBus(1)
#get a measure by i2c
def getUSMeasure():
bus.write_byte(address_arduino, 1)
distance = bus.read_byte(address_arduino)
return distance
#request rotate... | normal | {
"blob_id": "6fa7aef7c2b91de409a0e8574e362efefa642ee7",
"index": 1715,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getUSMeasure():\n bus.write_byte(address_arduino, 1)\n distance = bus.read_byte(address_arduino)\n return distance\n\n\ndef forward():\n bus.write_byte(address_arduino... | [
0,
2,
3,
6,
7
] |
<|reserved_special_token_0|>
def write_to_file(file, line):
file.write(line + '\n')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
try:
import xml.etree.cElementTree as ET
except ImportError:
import xml.etree.ElementTree as ET
<|reserved_special_token_0|>
def write_to_file(file, line):
... | flexible | {
"blob_id": "04538cc5c9c68582cc9aa2959faae2d7547ab2ee",
"index": 302,
"step-1": "<mask token>\n\n\ndef write_to_file(file, line):\n file.write(line + '\\n')\n\n\n<mask token>\n",
"step-2": "try:\n import xml.etree.cElementTree as ET\nexcept ImportError:\n import xml.etree.ElementTree as ET\n<mask toke... | [
1,
3,
4,
5,
6
] |
# mathematical operators
'''
* multiply
/ divide (normal)
// divide (integer)
% modulus (remainder)
+ add
- subtract
** exponent (raise to)
'''
print(2 * 3)
# comparison operators
'''
== equal to
!= not equal to
> greater than
< less than
>= greater or equal to
<= less or equal t... | normal | {
"blob_id": "911257bad3baab89e29db3facb08ec41269b41e3",
"index": 9953,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(2 * 3)\n<mask token>\nif a >= b:\n print('You can drive the car, you are ', a)\nelse:\n print('Sorry, you are too small')\n",
"step-3": "<mask token>\nprint(2 * 3)\n<mask to... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def filter_frames(frames, method=cv2.HISTCMP_CORREL, target_size=(64, 64),
threshold=0.65):
"""Filter noisy frames out
Args:
frames (list<numpy.ndarray[H, W, 3]>): video frames
method (int, optional)... | flexible | {
"blob_id": "1da93e9113089f1a2881d4094180ba524d0d4a86",
"index": 8531,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef filter_frames(frames, method=cv2.HISTCMP_CORREL, target_size=(64, 64),\n threshold=0.65):\n \"\"\"Filter noisy frames out\n\n Args:\n frames (list<numpy.ndarray[H,... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class HBNBCommand(cmd.Cmd):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def emptyline(self):
"""Do nothing"""
pass
def do_create(self, line):
... | flexible | {
"blob_id": "7cbf2082d530c315fdcfdb94f5c6ac4755ea2081",
"index": 1267,
"step-1": "<mask token>\n\n\nclass HBNBCommand(cmd.Cmd):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def emptyline(self):\n \"\"\"Do nothing\"\"\"\n pass\n\n def do_create(... | [
9,
11,
12,
16,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^stats/$', views.get_stats, name='stats'), url(
'^follow/me/$', views.follow_me, name='follow_me'), url(
'^follower/confirm/$', views.confirm_follower, name='follower_confirm'),
url('^execute/', vie... | flexible | {
"blob_id": "33b68246dd3da9561c1d4adb5a3403cba656dcee",
"index": 9175,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^stats/$', views.get_stats, name='stats'), url(\n '^follow/me/$', views.follow_me, name='follow_me'), url(\n '^follower/confirm/$', views.confirm_follower, name=... | [
0,
1,
2,
3
] |
# Generated by Django 2.1.4 on 2019-04-17 03:56
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('historiasClinicas', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='actualizacion',
name='valor... | normal | {
"blob_id": "4aefabf064cdef963f9c62bd5c93892207c301d3",
"index": 3076,
"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 = [('historiasCl... | [
0,
1,
2,
3,
4
] |
#coding:utf-8
x = '上'
res = x.encode('gbk')
print(res, type(res))
print(res.decode('gbk'))
| normal | {
"blob_id": "3c053bf1b572759eddcd310d185f7e44d82171a5",
"index": 9153,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(res, type(res))\nprint(res.decode('gbk'))\n",
"step-3": "x = '上'\nres = x.encode('gbk')\nprint(res, type(res))\nprint(res.decode('gbk'))\n",
"step-4": "#coding:utf-8\n\nx = '上'\... | [
0,
1,
2,
3
] |
# -*- encoding: utf-8 -*-
#----------------------------------------------------------------------------
#
# Copyright (C) 2014 .
# Coded by: Borni DHIFI (dhifi.borni@gmail.com)
#
#----------------------------------------------------------------------------
import models
import wizard
import parser
# vim:expa... | normal | {
"blob_id": "a3216aa41cd28b91653b99017e21a03e43372e9b",
"index": 4137,
"step-1": "<mask token>\n",
"step-2": "import models\nimport wizard\nimport parser\n",
"step-3": "# -*- encoding: utf-8 -*-\n#----------------------------------------------------------------------------\n#\n# Copyright (C) 2014 .\n# ... | [
0,
1,
2
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import os
try:
import Image
except ImportError:
from PIL import Image
import sys
sys.path.append(os.path.abspath(os.path.join(__file__, os.pardir, os.pardir, 'DropPy.Common')))
from file_tools import get_file_paths_from_director... | normal | {
"blob_id": "df3208a00f7a5dd1ddd76542ac0de85762cc45ab",
"index": 7236,
"step-1": "<mask token>\n\n\nclass Task(object):\n <mask token>\n <mask token>\n\n @staticmethod\n def rotate_file(input_file, output_dir, degrees, expand):\n output_file_name = os.path.basename(input_file)\n output_... | [
2,
3,
4,
6,
7
] |
from flask import Flask, json, request, jsonify
from flask_sqlalchemy import SQLAlchemy
from flask_marshmallow import Marshmallow
import warnings
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql+pymysql://root:1234@localhost/escuela'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS']=False
db = SQLAlche... | normal | {
"blob_id": "5c1d1eafb913822be9b6e46b15c6886f8bf3e2e1",
"index": 3622,
"step-1": "<mask token>\n\n\nclass curso(db.Model):\n idcurso = db.Column(db.Integer, primary_key=True)\n nombre_curso = db.Column(db.String(45))\n precio = db.Column(db.Integer)\n\n def __init__(self, nombre, precio):\n se... | [
9,
10,
11,
13,
14
] |
class Odwroc():
def __init__(self,dane):
self.dane = dane
self.indeks = len(dane)
def __iter__(self):
return self
def __next__(self):
if self.indeks == 0:
raise StopIteration
self.indeks -= 1
return self.dane[self.indeks]
for i in Odwroc('Martu... | normal | {
"blob_id": "763c0baf919b48ff135f7aa18974da5b85ee40f5",
"index": 1133,
"step-1": "class Odwroc:\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Odwroc:\n\n def __init__(self, dane):\n self.dane = dane\n self.indeks = len(dane)\n <mask token>\n\n ... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for letter in 'zYxWvUtSrQpOnMlKjIhGfEdCbA':
print('{:s}'.format(letter), end='')
<|reserved_special_token_1|>
#!/usr/bin/python3
"""
list = list(range(97, 123)
for (i in list):
if (i % 2 == 0):
i = (i - 32)
"""
... | flexible | {
"blob_id": "55a061a1c0cd20e5ab7413c671bc03573de1bbdf",
"index": 7754,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor letter in 'zYxWvUtSrQpOnMlKjIhGfEdCbA':\n print('{:s}'.format(letter), end='')\n",
"step-3": "#!/usr/bin/python3\n\"\"\"\nlist = list(range(97, 123)\nfor (i in list):\n if (i ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Cliente:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def BD(self):
conectar = Base_de_datos.BaseDeDatos()
comando = ("INSERT INTO public.cliente(id, nombre) VALUES('" + self
.id.get() + "','" + self.nombre.get() + "')")
... | flexible | {
"blob_id": "63d9aa55463123f32fd608ada83e555be4b5fe2c",
"index": 6946,
"step-1": "<mask token>\n\n\nclass Cliente:\n <mask token>\n <mask token>\n\n def BD(self):\n conectar = Base_de_datos.BaseDeDatos()\n comando = (\"INSERT INTO public.cliente(id, nombre) VALUES('\" + self\n .... | [
2,
5,
6,
7,
8
] |
from django.urls import path
from rest_framework.routers import DefaultRouter
from . import views
app_name = "rooms"
router = DefaultRouter()
router.register("", views.RoomViewSet)
urlpatterns = router.urls
#
# urlpatterns = [
# # path("list/", views.ListRoomsView.as_view()),
# # path("list/", views.rooms_vie... | normal | {
"blob_id": "96708216c5ffa56a60475b295c21b18225e6eed9",
"index": 6056,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrouter.register('', views.RoomViewSet)\n<mask token>\n",
"step-3": "<mask token>\napp_name = 'rooms'\nrouter = DefaultRouter()\nrouter.register('', views.RoomViewSet)\nurlpatterns = rou... | [
0,
1,
2,
3,
4
] |
import ttk
import Tkinter as tk
from rwb.runner.log import RobotLogTree, RobotLogMessages
from rwb.lib import AbstractRwbGui
from rwb.widgets import Statusbar
from rwb.runner.listener import RemoteRobotListener
NAME = "monitor"
HELP_URL="https://github.com/boakley/robotframework-workbench/wiki/rwb.monitor-User-Guide"... | normal | {
"blob_id": "572d58eec652207e6ec5a5e1d4c2f4310f2a70f3",
"index": 1665,
"step-1": "import ttk\nimport Tkinter as tk\nfrom rwb.runner.log import RobotLogTree, RobotLogMessages\nfrom rwb.lib import AbstractRwbGui\nfrom rwb.widgets import Statusbar\n\nfrom rwb.runner.listener import RemoteRobotListener\n\nNAME = \"m... | [
0
] |
<|reserved_special_token_0|>
def addOptions(parser):
parser.add_option('--NNfile', default='', help=
'Config json file for the data to pass to the model')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def addOptions(parser):
parser.add_option('--NNfile',... | flexible | {
"blob_id": "83a92c0b645b9a2a483a01c19a47ab5c296ccbd9",
"index": 6907,
"step-1": "<mask token>\n\n\ndef addOptions(parser):\n parser.add_option('--NNfile', default='', help=\n 'Config json file for the data to pass to the model')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef addOptions(parse... | [
1,
2,
3,
4,
5
] |
def solution(n, money):
save = [0] * (n+1)
save[0] = 1
for i in range(len(money)):
for j in range(1, n+1):
if j - money[i] >= 0:
save[j] += (save[j - money[i]] % 1000000007)
return save[n] | normal | {
"blob_id": "deeba82536d0366b3793bcbe78f78e4cfeabb612",
"index": 6241,
"step-1": "<mask token>\n",
"step-2": "def solution(n, money):\n save = [0] * (n + 1)\n save[0] = 1\n for i in range(len(money)):\n for j in range(1, n + 1):\n if j - money[i] >= 0:\n save[j] += sav... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class FtpDownloaderPostProcess:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@property
def logger(self):
return logging.getLogger(__name__)
def iterate(self, *args, **kwargs):
"""
Uses worker queues to perform the postprocessing
:... | flexible | {
"blob_id": "56a41f432d332aaebbde15c52e133eee51b22ce1",
"index": 2833,
"step-1": "<mask token>\n\n\nclass FtpDownloaderPostProcess:\n <mask token>\n <mask token>\n\n @property\n def logger(self):\n return logging.getLogger(__name__)\n\n def iterate(self, *args, **kwargs):\n \"\"\"\nU... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .auth import Auth
from .banDetection import BanDetectionThread
from .botLogging import BotLoggingThread
from .clientLauncher import ClientLauncher
from .log import LogThread, Log
from .mainThread import MainThread
from .nexonServer import NexonServer
fro... | flexible | {
"blob_id": "b7038ad73bf0e284474f0d89d6c34967d39541c0",
"index": 6566,
"step-1": "<mask token>\n",
"step-2": "from .auth import Auth\nfrom .banDetection import BanDetectionThread\nfrom .botLogging import BotLoggingThread\nfrom .clientLauncher import ClientLauncher\nfrom .log import LogThread, Log\nfrom .mainTh... | [
0,
1
] |
<|reserved_special_token_0|>
def getScale(NumFrame, t_gt, seq_num):
txt_file = open('/media/cordin/새 볼륨/rosbag/dataset/poses/{0:02d}.txt'.
format(seq_num))
x_prev = float(t_gt[0])
y_prev = float(t_gt[1])
z_prev = float(t_gt[2])
line = txt_file.readlines()
line_sp = line[NumFrame].split... | flexible | {
"blob_id": "73e7e43e9cfb3c0884480809bc03ade687d641d6",
"index": 733,
"step-1": "<mask token>\n\n\ndef getScale(NumFrame, t_gt, seq_num):\n txt_file = open('/media/cordin/새 볼륨/rosbag/dataset/poses/{0:02d}.txt'.\n format(seq_num))\n x_prev = float(t_gt[0])\n y_prev = float(t_gt[1])\n z_prev = f... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
import socket
import datetime as dt
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.animation import FuncAnimation
from matplotlib import style
import pickle
# Create figure for plotting
time_list = []
gain_list = []
HOST = '127.0.0.1' # Standard loopba... | normal | {
"blob_id": "a4d5064decdc9963dae1712c7c6918b3e5902bf2",
"index": 9825,
"step-1": "<mask token>\n\n\ndef recieve_data():\n while True:\n data = conn.recv(1024)\n if not data:\n break\n conn.sendall(data)\n msg = pickle.loads(data)\n time = float(msg[0])\n ga... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def test_version():
assert __version__ == '0.1.0'
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_version():
assert __version__ == '0.1.0'
@pytest.mark.vcr()
def test_asteroid_closest_approach():
asteroid_json = asteroid... | flexible | {
"blob_id": "7dd4dc60b23c72ba450025bececb0e6d89df69c3",
"index": 8263,
"step-1": "<mask token>\n\n\ndef test_version():\n assert __version__ == '0.1.0'\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_version():\n assert __version__ == '0.1.0'\n\n\n@pytest.mark.vcr()\ndef test_asteroid_closest... | [
1,
2,
3,
4
] |
##########################################################################
#
# Copyright (c) 2007-2013, Image Engine Design Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redis... | normal | {
"blob_id": "d4c297af395581c6d955eb31a842ab86e599d23c",
"index": 4576,
"step-1": "<mask token>\n\n\nclass TestMotionPrimitive(unittest.TestCase):\n <mask token>\n\n def testItems(self):\n m = IECoreScene.MotionPrimitive()\n m[0] = IECoreScene.PointsPrimitive(1)\n m[1] = IECoreScene.Poi... | [
4,
5,
6,
7,
8
] |
import pygame
from math import sqrt, sin, cos
from numpy import arctan
from os import path
# try these colors or create your own!
# each valid color is 3-tuple with values in range [0, 255]
BLACK = (0, 0, 0)
WHITE = (255, 255, 255)
WHITEGRAY = (192, 192, 192)
RED = (255, 0, 0)
MIDRED = (192, 0, 0)
DARKRED = (128, 0, 0... | normal | {
"blob_id": "838279b4f8d9e656c2f90ff06eaff3bd9c12bbef",
"index": 3265,
"step-1": "<mask token>\n\n\ndef next_point(p1, p2):\n diff_x = p1[0] - p2[0]\n diff_y = p1[1] - p2[1]\n angle = arctan(abs(diff_x) / abs(diff_y))\n new_diff_x = int(sin(angle) * curr_length)\n new_diff_y = int(cos(angle) * cur... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
greeting.pack()
<|reserved_special_token_0|>
guess.pack()
<|reserved_special_token_0|>
submit.pack()
window.mainloop()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
secret = random.randint(1, 100)
window = Tkinter.T... | flexible | {
"blob_id": "59eb705d6d388de9afbcc0df3003f4d4f45f1fbd",
"index": 3989,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ngreeting.pack()\n<mask token>\nguess.pack()\n<mask token>\nsubmit.pack()\nwindow.mainloop()\n",
"step-3": "<mask token>\nsecret = random.randint(1, 100)\nwindow = Tkinter.Tk()\ngreeting... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ClusterMonitor:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ClusterMonitor:
def __init__(self, cluster):
self.cluster = cluster
self.token = self.cluster.get_cluster_token... | flexible | {
"blob_id": "da41f26489c477e0df9735606457bd4ee4e5a396",
"index": 4465,
"step-1": "<mask token>\n\n\nclass ClusterMonitor:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ClusterMonitor:\n\n def __init__(self, cluster):\n self.cluster = cluster\n self.token = self.clu... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class TestForms(TestCase):
<|reserved_special_token_0|>
def test_wrong_data_ResearchFormMKI_form(self):
with open(os.path.abspath(os.curdir) + 'Test.txt', 'wb') as f:
f.write(b'ABOBA')
with open(os.path.abspath(os.curdir) + 'Test.txt', 'rb') as f:
... | flexible | {
"blob_id": "c5d0b23396e084ad6ffade15b3aa3c59b6be3cc0",
"index": 2706,
"step-1": "<mask token>\n\n\nclass TestForms(TestCase):\n <mask token>\n\n def test_wrong_data_ResearchFormMKI_form(self):\n with open(os.path.abspath(os.curdir) + 'Test.txt', 'wb') as f:\n f.write(b'ABOBA')\n w... | [
5,
6,
7,
8,
9
] |
from __future__ import absolute_import
import itertools
from django.contrib import messages
from django.core.context_processors import csrf
from django.db import transaction
from django.http import HttpResponseRedirect
from django.views.decorators.cache import never_cache
from django.utils.decorators import method_de... | normal | {
"blob_id": "46f218829e1bf324d4c50ea0ff7003bc48b64e2a",
"index": 4258,
"step-1": "<mask token>\n\n\nclass AccountNotificationView(BaseView):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass AccountNotificationView(BaseView):\n <mask token>\n\n @method_decorator(never_cache)\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def index() ->dict:
return {}
<|reserved_special_token_0|>
@pytest.fixture
def client(app):
return TestClient(app)
def test_request_id_can_be_autogenerated(client):
response = client.get('/')
assert response.headers['x-request-id']
assert RequestId.get_request_id... | flexible | {
"blob_id": "f41ab6813fb7067089abe223b9006adde40630cd",
"index": 1941,
"step-1": "<mask token>\n\n\ndef index() ->dict:\n return {}\n\n\n<mask token>\n\n\n@pytest.fixture\ndef client(app):\n return TestClient(app)\n\n\ndef test_request_id_can_be_autogenerated(client):\n response = client.get('/')\n a... | [
6,
9,
10,
11,
12
] |
#!/usr/bin/env python
#_*_coding:utf-8_*_
#作者:Paul哥
from fabric.api import settings,run,cd,env,hosts
from fabric.colors import *
env.hosts=['192.168.75.130:22']
env.password='hello123'
env.user='root'
def test():
with cd('/home'):
print yellow(run('ls -l'))
test()
| normal | {
"blob_id": "6b45541c54f1a4ce94d6bd457701ecd1b90a4c4c",
"index": 1129,
"step-1": "#!/usr/bin/env python\n#_*_coding:utf-8_*_\n#作者:Paul哥\n\n\n\nfrom fabric.api import settings,run,cd,env,hosts\nfrom fabric.colors import *\n\nenv.hosts=['192.168.75.130:22']\nenv.password='hello123'\nenv.user='root'\ndef test():\n\... | [
0
] |
import numpy as np
import pytest
import torch
from ignite.contrib.metrics.regression import MeanNormalizedBias
from ignite.engine import Engine
from ignite.exceptions import NotComputableError
def test_zero_sample():
m = MeanNormalizedBias()
with pytest.raises(
NotComputableError, match=r"MeanNormali... | normal | {
"blob_id": "452f35fe2ae9609949a3f92ad7768fc37094a2f1",
"index": 3786,
"step-1": "<mask token>\n\n\ndef test_zero_sample():\n m = MeanNormalizedBias()\n with pytest.raises(NotComputableError, match=\n 'MeanNormalizedBias must have at least one example before it can be computed'\n ):\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
def run():
rand_seed = None
stderr_filename = None
stdout_filename = None
if len(sys.argv) >= 4:
rand_seed = int(sys.argv[3])
if len(sys.argv) >= 3:
stderr_filename = sys.argv[2]
if len(sys.argv) >= 2:
stdout_filename = sys.argv[1]
stdou... | flexible | {
"blob_id": "b7db0d2f4bbbc2c7763b9d2e6bede74979b65161",
"index": 4283,
"step-1": "<mask token>\n\n\ndef run():\n rand_seed = None\n stderr_filename = None\n stdout_filename = None\n if len(sys.argv) >= 4:\n rand_seed = int(sys.argv[3])\n if len(sys.argv) >= 3:\n stderr_filename = sys... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SuiteResultDTO:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "84c3427a994bd6c57d9fa8449e4fc7a3de801170",
"index": 9271,
"step-1": "<mask token>\n\n\nclass SuiteResultDTO:\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 ... | [
13,
14,
15,
16,
21
] |
<|reserved_special_token_0|>
class UserSerializer(serializers.ModelSerializer):
pointseau = serializers.PrimaryKeyRelatedField(many=True, queryset=
PointEau.objects.all())
class Meta:
model = User
fields = 'id', 'username', 'pointseau'
<|reserved_special_token_1|>
<|reserved_speci... | flexible | {
"blob_id": "51f171b3847b3dbf5657625fdf3b7fe771e0e004",
"index": 4743,
"step-1": "<mask token>\n\n\nclass UserSerializer(serializers.ModelSerializer):\n pointseau = serializers.PrimaryKeyRelatedField(many=True, queryset=\n PointEau.objects.all())\n\n\n class Meta:\n model = User\n fiel... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def euler_29(max_a, max_b):
gen = (a ** b for a, b in itertools.product(range(2, max_a + 1), range(
2, max_b + 1)))
return len(set(gen))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_s... | flexible | {
"blob_id": "c93bd042340a6e1d0124d8f6176bdf17ab56e405",
"index": 2229,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef euler_29(max_a, max_b):\n gen = (a ** b for a, b in itertools.product(range(2, max_a + 1), range(\n 2, max_b + 1)))\n return len(set(gen))\n\n\n<mask token>\n",
"st... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(0, 46):
cnt_number.append(0)
for i in range(0, len(df2)):
for j in range(0, 7):
cnt_index = df2[i][j]
cnt_number[int(cnt_index)] += 1
for k in range(1, 46):
print('%5d -> %3d times' % (k,... | flexible | {
"blob_id": "b257e36b3cb4bda28cf18e192aa95598105f5ae9",
"index": 2705,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, 46):\n cnt_number.append(0)\nfor i in range(0, len(df2)):\n for j in range(0, 7):\n cnt_index = df2[i][j]\n cnt_number[int(cnt_index)] += 1\nfor k in... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(1, N + 1, 1):
NUM = int(input('ingrese un numero entero '))
if NUM > 0:
SP += NUM
CP += 1
else:
SO += NUM
<|reserved_special_token_0|>
print(
f'hay {CP} numeros positivos, el ... | flexible | {
"blob_id": "efc0b8f1c4887810a9c85e34957d664b01c1e92e",
"index": 1453,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, N + 1, 1):\n NUM = int(input('ingrese un numero entero '))\n if NUM > 0:\n SP += NUM\n CP += 1\n else:\n SO += NUM\n<mask token>\nprint(\n ... | [
0,
1,
2,
3
] |
from django.views.generic import TemplateView, FormView, CreateView, ListView
from .models import Order
from .form import OrderForm
class OrdersListView(ListView):
template_name = 'orders/index.html'
queryset = Order.objects.all()
context_object_name = 'order_list'
class OrderCreateView(CreateView):
... | normal | {
"blob_id": "afd184962e8e69843ca518e140d5fdde3d7c9ed2",
"index": 7456,
"step-1": "<mask token>\n\n\nclass OrderCreateView(CreateView):\n template_name = 'orders/form.html'\n form_class = OrderForm\n success_url = '/'\n",
"step-2": "<mask token>\n\n\nclass OrdersListView(ListView):\n <mask token>\n ... | [
2,
3,
4,
5
] |
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
] |
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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CAresRecipe(GnuRecipe):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CAresRecipe(GnuRecipe):
def __init__(self, *args, **kwargs):
super(CAresRecipe, sel... | flexible | {
"blob_id": "bf7676dc2c47d9cd2f1ce2d436202ae2c5061265",
"index": 8634,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CAresRecipe(GnuRecipe):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass CAresRecipe(GnuRecipe):\n\n def __init__(self, *args, **kwargs):\n super(CAresRecipe... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def increment(number: int) ->int:
"""Increment a number.
Args:
number (int): The number to increment.
Returns:
int: The incremented number.
"""
return number + 1
| flexible | {
"blob_id": "b0cc2efda4d6586b66e04b41dfe1bbce8d009e2e",
"index": 6871,
"step-1": "<mask token>\n",
"step-2": "def increment(number: int) ->int:\n \"\"\"Increment a number.\n\n Args:\n number (int): The number to increment.\n\n Returns:\n int: The incremented number.\n \"\"\"\n retu... | [
0,
1
] |
import pickle
from absl import flags
from absl import app
from absl import logging
import time
import numpy as np
FLAGS = flags.FLAGS
flags.DEFINE_string('sent2vec_dir', '2020-04-10/sent2vec/', 'out path')
flags.DEFINE_integer('num_chunks', 36, 'how many files')
flags.DEFINE_string('out_dir', '2020-04-10/', 'out pat... | normal | {
"blob_id": "8aa35bcaa4e564306125b37c70a8a92f26da736d",
"index": 7418,
"step-1": "<mask token>\n\n\ndef load_all_vectors(num_chunks):\n all_vectors = []\n meta_data = []\n for chunk_id in range(num_chunks):\n logging.info('Processing file %s', chunk_id)\n t = time.time()\n vectors =... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class MyIde:
<|reserved_special_token_0|>
class Laptop:
def code(self, ide):
ide.execute()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class PyCharm:
<|reserved_special_token_0|>
class MyIde:
def execute(self):
print('MyIde running'... | flexible | {
"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
] |
<|reserved_special_token_0|>
class Collector:
<|reserved_special_token_0|>
def get_api():
parser = ConfigParser()
parser.read('twitter_auth.ini')
consumer_key = parser.get('Keys', 'consumer_key').strip("'")
consumer_secret = parser.get('Secrets', 'consumer_secret').strip("'")
... | flexible | {
"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
] |
<|reserved_special_token_0|>
def backup_db(cursor):
for table in tables_schema:
backup_table(cursor, table)
def backup_table(cursor, table):
cursor.execute(f'{tables_schema[table]}' +
f"INTO OUTFILE '/tmp/{table.lower()}_data.csv' " +
"FIELDS TERMINATED BY ',' " + "LINES TERMINATED B... | flexible | {
"blob_id": "fd76a7dd90bac7c7ba9201b6db62e6cb3eedeced",
"index": 4390,
"step-1": "<mask token>\n\n\ndef backup_db(cursor):\n for table in tables_schema:\n backup_table(cursor, table)\n\n\ndef backup_table(cursor, table):\n cursor.execute(f'{tables_schema[table]}' +\n f\"INTO OUTFILE '/tmp/{ta... | [
4,
5,
6,
7,
9
] |
<|reserved_special_token_0|>
class Player:
def __init__(self, name, location):
self.name = name
self.location = location
self.square = None
self.money = 0
self.quest = None
self.job = None
self.phase = 'day'
self.equipped_weapon = None
self.... | flexible | {
"blob_id": "535c0975c688a19963e4c53f6029626d286b41d6",
"index": 5630,
"step-1": "<mask token>\n\n\nclass Player:\n\n def __init__(self, name, location):\n self.name = name\n self.location = location\n self.square = None\n self.money = 0\n self.quest = None\n self.job... | [
23,
31,
32,
38,
42
] |
<|reserved_special_token_0|>
class bcolors:
RED = '\x1b[31m'
GREEN = '\x1b[32m'
NORMAL = '\x1b[0m'
def check_result(title, map1, map2):
result = True
print(title)
for y in range(0, common.constants.MAP_HEIGHT):
v = ''
for x in range(0, common.constants.MAP_WIDTH):
... | flexible | {
"blob_id": "602d2c545c6e3eabe5c6285d2ab0c7f4216a00f5",
"index": 1563,
"step-1": "<mask token>\n\n\nclass bcolors:\n RED = '\\x1b[31m'\n GREEN = '\\x1b[32m'\n NORMAL = '\\x1b[0m'\n\n\ndef check_result(title, map1, map2):\n result = True\n print(title)\n for y in range(0, common.constants.MAP_HE... | [
3,
4,
5,
6,
7
] |
import json
import os
import pickle
import random
import urllib.request
from pathlib import Path
import tensorflow as tf
from matplotlib import pyplot as plt
class CNN(object):
def __init__(self):
self.model = tf.keras.Sequential([
tf.keras.layers.Conv2D(32, (3, 3), activation='relu', input_... | normal | {
"blob_id": "9535335c70129f997d7b8739444a503d0b984ac8",
"index": 9753,
"step-1": "<mask token>\n\n\nclass CNN(object):\n\n def __init__(self):\n self.model = tf.keras.Sequential([tf.keras.layers.Conv2D(32, (3, 3),\n activation='relu', input_shape=(150, 150, 1)), tf.keras.layers.\n ... | [
12,
13,
14,
15,
16
] |
from django.contrib import admin
from django.urls import path, include
from accounts import views
urlpatterns = [
path('google/login', views.google_login),
path('google/callback/', views.google_callback),
path('accounts/google/login/finish/', views.GoogleLogin.as_view(), name = 'google_login_todjango'),
]... | normal | {
"blob_id": "68319663aad13b562e56b8ee25f25c7b548417df",
"index": 4739,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('google/login', views.google_login), path(\n 'google/callback/', views.google_callback), path(\n 'accounts/google/login/finish/', views.GoogleLogin.as_view(), na... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Entity(Agent):
<|reserved_special_token_0|>
def __init__(self, unique_id, model):
super().__init__(unique_id, model)
self.type = ''
self.position = ''
self.log = []
self.move_probability = None
self.retire_probability = None
... | flexible | {
"blob_id": "68b967ecf18d576758cf05e889919944cfc34dcd",
"index": 250,
"step-1": "<mask token>\n\n\nclass Entity(Agent):\n <mask token>\n\n def __init__(self, unique_id, model):\n super().__init__(unique_id, model)\n self.type = ''\n self.position = ''\n self.log = []\n se... | [
5,
6,
7,
9,
10
] |
#/usr/share/python3
from sklearn.linear_model import LogisticRegression
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.model_selection import train_test_split
import numpy as np
import seaborn as sb
import pandas as pd
from pmlb import fetch_data, classification_dataset_names
import util
# f... | normal | {
"blob_id": "4c010f9d9e7813a4ae4f592ade60130933b51958",
"index": 6125,
"step-1": "<mask token>\n\n\ndef score_model(X, y, model):\n train_X, test_X, train_y, test_y = train_test_split(X, y)\n model.fit(train_X, train_y)\n return model.score(test_X, test_y)\n\n\n<mask token>\n\n\ndef main():\n ds_name... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class WINRM(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def connect(self):
"""
Method to connect to a Windows machine.
"""
try:
self.host_win_ip = 'http://' + self.host_ip + ':5985/wsman'
self.... | flexible | {
"blob_id": "96ac9088650490a7da00c7a20f634b76e673ca2d",
"index": 1174,
"step-1": "<mask token>\n\n\nclass WINRM(object):\n <mask token>\n <mask token>\n\n def connect(self):\n \"\"\"\n Method to connect to a Windows machine.\n \"\"\"\n try:\n self.host_win_ip =... | [
3,
4,
5,
6,
7
] |
from __future__ import annotations
from typing import TYPE_CHECKING
from datetime import datetime
from sqlalchemy import Column, ForeignKey, String, DateTime, Float, Integer
from sqlalchemy.orm import relationship
from app.db.base_class import Base
if TYPE_CHECKING:
from .account import Account # noqa: F401
... | normal | {
"blob_id": "60d8276a5715899823b12ffdf132925c6f2693bd",
"index": 8675,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Voucher(Base):\n __tablename__ = 't_juju_voucher'\n code = Column(String(100), index=True, unique=True)\n serial_no = Column(String(120), index=True, unique=True)\n ... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
SSMDocumentName = 'AWS-RunPowerShellScript'
InstanceId = ['i-081a7260c79feb260']
Querytimeoutseconds = 3600
OutputS3BucketName = 'hccake'
OutputS3KeyPrefix = 'log_'
region_name = 'us-east-2'
aws_access_key_id = ''
aws_secret_access_key = ''
workingdirectory =... | flexible | {
"blob_id": "e55fe845c18ff70ba12bb7c2db28ceded8ae9129",
"index": 1580,
"step-1": "<mask token>\n",
"step-2": "SSMDocumentName = 'AWS-RunPowerShellScript'\nInstanceId = ['i-081a7260c79feb260']\nQuerytimeoutseconds = 3600\nOutputS3BucketName = 'hccake'\nOutputS3KeyPrefix = 'log_'\nregion_name = 'us-east-2'\naws_... | [
0,
1,
2
] |
from urllib.request import urlopen
from bs4 import BeautifulSoup
import json
def get_webcasts(year):
url = "https://www.sans.org/webcasts/archive/" + str(year)
page = urlopen(url)
soup = BeautifulSoup(page, 'html.parser')
table = soup.find('table', {"class": "table table-bordered table-striped"})
... | normal | {
"blob_id": "14971842092c7aa41477f28cec87628a73a8ffd6",
"index": 8407,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_webcasts(year):\n url = 'https://www.sans.org/webcasts/archive/' + str(year)\n page = urlopen(url)\n soup = BeautifulSoup(page, 'html.parser')\n table = soup.find(... | [
0,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.6 on 2017-10-27 21:59
from __future__ import unicode_literals
from django.db import migrations, models
import django.db.models.deletion
import phonenumber_field.modelfields
class Migration(migrations.Migration):
dependencies = [
('regions', '0002_auto_2... | normal | {
"blob_id": "1330addd53c6187a41dfea6957bf47aaecca1135",
"index": 7180,
"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 = [('regions', '... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def parse_msg(msg):
line_org = msg.split('\n')
N = len(line_org) - 2
line = line_org[N]
return line
def get_vals(msg):
rhs = msg.split('=')
try:
nums = rhs[1].split('/')
min_num = float(nums[0])
ave_num = float(nums[1])
max_num = f... | flexible | {
"blob_id": "3f2221f5f3a699020dd5986acb793e3083976dff",
"index": 7176,
"step-1": "<mask token>\n\n\ndef parse_msg(msg):\n line_org = msg.split('\\n')\n N = len(line_org) - 2\n line = line_org[N]\n return line\n\n\ndef get_vals(msg):\n rhs = msg.split('=')\n try:\n nums = rhs[1].split('/'... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def integrate_sine(f, a, b, n=2):
I_t = trapezoidal(f, a, b, n)
I_m = midpoint()
return None
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def integrate_sine(f, a, b, n... | flexible | {
"blob_id": "d99278c8f539322fd83ae5459c3121effc044b88",
"index": 5193,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef integrate_sine(f, a, b, n=2):\n I_t = trapezoidal(f, a, b, n)\n I_m = midpoint()\n return None\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef integrate_sine(f, ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def plot3D(xValues, labels, figure=0):
minClass = min(labels)
numberOfClasses = int(max(labels) - minClass)
fig = plt.figure(figure)
ax = plt.axes(projection='3d')
colors = ['r', 'b', 'y', 'c', 'm']
for i... | flexible | {
"blob_id": "8dfd92ab0ce0e71b41ce94bd8fcf057c8995a2a4",
"index": 1668,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef plot3D(xValues, labels, figure=0):\n minClass = min(labels)\n numberOfClasses = int(max(labels) - minClass)\n fig = plt.figure(figure)\n ax = plt.axes(projection='3d')... | [
0,
1,
2,
3
] |
#loadconc.py - possibly these classes will be added to ajustador/loader.py when ready
# -*- coding:utf-8 -*-
from __future__ import print_function, division
import numpy as np
from ajustador import xml,nrd_fitness
import glob
import os
import operator
msec_per_sec=1000
nM_per_uM=1000
nM_per_mM=1e6
class trace(ob... | normal | {
"blob_id": "20649decd3ff21b1aa814d0a04180195cac3629b",
"index": 498,
"step-1": "<mask token>\n\n\nclass CSV_conc(object):\n <mask token>\n <mask token>\n\n\nclass CSV_conc_set(object):\n\n def __init__(self, rootname, stim_time=0, features=[]):\n self.stim_time = stim_time * msec_per_sec\n ... | [
3,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def execute():
for ps in frappe.get_all('Property Setter', filters={'property': '_idx'
}, fields=['doc_type', 'value']):
custom_fields = frappe.get_all('Custom Field', filters={'dt': ps.
doc_type}... | flexible | {
"blob_id": "6f951815d0edafb08e7734d0e95e6564ab1be1f7",
"index": 2375,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef execute():\n for ps in frappe.get_all('Property Setter', filters={'property': '_idx'\n }, fields=['doc_type', 'value']):\n custom_fields = frappe.get_all('Custom ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@app.route('/')
@app.route('/index')
def index():
return 'Hello world'
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@app.route('/')
@app.route('/index')
def index():
retur... | flexible | {
"blob_id": "9d8c4bf9f9279d5e30d0e9742cdd31713e5f4b9e",
"index": 2104,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\n@app.route('/index')\ndef index():\n return 'Hello world'\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\n@app.route('/')\n@app.route('/index')\ndef index():\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class UppercaseBrandFeed(CSVMerchantFeed):
def get_brand(self, obj):
return obj.brand.upper()
class CSVMerchantFeedTest(TestCase):
def test_csv_empty(self):
feed = CSVMerchantFeed([])
output = feed.get_content()
self.assertEquals(output, CSV_HEA... | flexible | {
"blob_id": "924fd89a835528fa28e1226912a2e4be9c4e1d5d",
"index": 152,
"step-1": "<mask token>\n\n\nclass UppercaseBrandFeed(CSVMerchantFeed):\n\n def get_brand(self, obj):\n return obj.brand.upper()\n\n\nclass CSVMerchantFeedTest(TestCase):\n\n def test_csv_empty(self):\n feed = CSVMerchantFe... | [
10,
13,
14,
16,
17
] |
"""Test suite for phlsys_tryloop."""
from __future__ import absolute_import
import datetime
import itertools
import unittest
import phlsys_tryloop
# =============================================================================
# TEST PLAN
# -----------------------------------------... | normal | {
"blob_id": "87130c2bbf919cacd3d5dd823cd310dcad4dc790",
"index": 8157,
"step-1": "\"\"\"Test suite for phlsys_tryloop.\"\"\"\n\nfrom __future__ import absolute_import\n\nimport datetime\nimport itertools\nimport unittest\n\nimport phlsys_tryloop\n\n# ==============================================================... | [
0
] |
import numpy as np
import matplotlib as plt
import math
from DoublePendulum import DP #imports useful modules and double pendulum class from DoublePendulum.py
import json
import pandas as pd
import copy
from pathlib import Path
#accessing config file
with open('config.json') as config_file:
initdata = ... | normal | {
"blob_id": "c2b6e51622681ac916e860ed4ff5715808dff102",
"index": 9725,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('config.json') as config_file:\n initdata = json.load(config_file)\n<mask token>\npend.updCartesian()\npend.updEnergies()\n<mask token>\nif method == 1:\n for n in range(n... | [
0,
1,
2,
3,
4
] |
from django import forms
BET_CHOICES = (
('1', 'Will rise'),
('x', 'Will stay'),
('2', 'Will fall'),
)
class NormalBetForm(forms.Form):
song = forms.CharField()
data = forms.ChoiceField(BET_CHOICES)
| normal | {
"blob_id": "2f6d51d5c14ddc1f6cd60ab9f3b5d4a879d14af0",
"index": 4590,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NormalBetForm(forms.Form):\n song = forms.CharField()\n data = forms.ChoiceField(BET_CHOICES)\n",
"step-3": "<mask token>\nBET_CHOICES = ('1', 'Will rise'), ('x', 'Will ... | [
0,
2,
3,
4,
5
] |
# Benthic Parameters - USEPA OPP defaults from EXAMS
benthic_params = {
"depth": 0.05, # benthic depth (m)
"porosity": 0.65, # benthic porosity
"bulk_density": 1, # bulk density, dry solid mass/total vol (g/cm3)
"froc": 0, # benthic organic carbon fraction
"doc": 5, # benthic dissolved organic ... | normal | {
"blob_id": "5890525b16b42578ac06e7ab2170c5613feea0a5",
"index": 6494,
"step-1": "<mask token>\n\n\ndef partition_benthic(reach, runoff, runoff_mass, erosion_mass):\n from .parameters import soil, stream_channel, benthic\n try:\n reach = self.region.flow_file.fetch(reach)\n q, v, l = reach.q,... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def modify(nyt_url, jh_url):
try:
nyt_df = pd.read_csv(nyt_url, header=0, names=['Date', 'Cases',
'Deaths'], dtype={'Cases': 'Int64', 'Deaths': 'Int64'})
nyt_df['Date'] = pd.to_datetime(nyt_df['Da... | flexible | {
"blob_id": "c60971b3b0649fce8c435813de4a738f4eacda27",
"index": 4377,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef modify(nyt_url, jh_url):\n try:\n nyt_df = pd.read_csv(nyt_url, header=0, names=['Date', 'Cases',\n 'Deaths'], dtype={'Cases': 'Int64', 'Deaths': 'Int64'})\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Card_profile(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_t... | flexible | {
"blob_id": "01153a695b4744465b706acb4c417217c5e3cefd",
"index": 3516,
"step-1": "<mask token>\n\n\nclass Card_profile(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/python3
# Distributed with a free-will license.
# Use it any way you want, profit or free, provided it fits in the licenses of its associated works.
# ADC121C_MQ131
# This code is designed to work with the ADC121C_I2CGAS_MQ131 I2C Mini Module available from ControlEverything.com.
# https://www.controleveryth... | normal | {
"blob_id": "678189ac5b0105c90178647843335f9d4402dc66",
"index": 1416,
"step-1": "<mask token>\n\n\ndef getOzoneData():\n data = bus.read_i2c_block_data(80, 0, 2)\n raw_adc = (data[0] & 15) * 256 + data[1]\n ppm = 1.99 * raw_adc / 4096.0 + 0.01\n return ppm\n\n\n<mask token>\n",
"step-2": "<mask to... | [
1,
2,
3,
4,
5
] |
#
# romaO
# www.fabiocrameri.ch/colourmaps
from matplotlib.colors import LinearSegmentedColormap
cm_data = [[0.45137, 0.22346, 0.34187],
[0.45418, 0.22244, 0.3361],
[0.45696, 0.22158, 0.33043],
[0.45975, 0.2209, 0.32483],
... | normal | {
"blob_id": "5082182af5a08970568dc1ab7a53ee5337260687",
"index": 45,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n import matplotlib.pyplot as plt\n import numpy as np\n try:\n from viscm import viscm\n viscm(romaO_map)\n except ImportError:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class TestUserRegister(BaseCase):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def test_signup_with_non_existing_field(self):
payload = json.dumps({'username': 'userjw', 'password': '1q2w3e4r',
'email': 'foo@bar.de'})
response = self.a... | flexible | {
"blob_id": "486362463dc07bdafea85de39a4a6d58cb8c8f26",
"index": 9643,
"step-1": "<mask token>\n\n\nclass TestUserRegister(BaseCase):\n <mask token>\n <mask token>\n\n def test_signup_with_non_existing_field(self):\n payload = json.dumps({'username': 'userjw', 'password': '1q2w3e4r',\n ... | [
3,
5,
6,
8,
9
] |
from .login import LoginTask
from .tag_search import TagSearchTask
from .timeline import TimelineTask
from .get_follower import GetFollowerTask
from .followback import FollowBackTask
from .unfollow import UnFollowTask
| normal | {
"blob_id": "e899b093152ee0923f1e5ad3b5719bbf9eb4339c",
"index": 7466,
"step-1": "<mask token>\n",
"step-2": "from .login import LoginTask\nfrom .tag_search import TagSearchTask\nfrom .timeline import TimelineTask\nfrom .get_follower import GetFollowerTask\nfrom .followback import FollowBackTask\nfrom .unfollo... | [
0,
1
] |
<|reserved_special_token_0|>
class Banana(object):
id = 10
<|reserved_special_token_0|>
def template_village_file(tick):
"""
Creates a template villages.dat file that i can modify later on
"""
cat = nbt.NBTFile()
cat2 = cat['data'] = nbt.TAG_Compound()
cat2['Villages'] = nbt.TAG_List(B... | flexible | {
"blob_id": "4e9674ea46bdf930d1e99bcda56eaa300c84deef",
"index": 7196,
"step-1": "<mask token>\n\n\nclass Banana(object):\n id = 10\n\n\n<mask token>\n\n\ndef template_village_file(tick):\n \"\"\"\n Creates a template villages.dat file that i can modify later on\n \"\"\"\n cat = nbt.NBTFile()\n ... | [
14,
15,
19,
21,
23
] |
import copy
import math
import operator
import numpy as np, pprint
def turn_left(action):
switcher = {
(-1, 0): (0, -1),
(0, 1): (-1, 0),
(1, 0): (0, 1),
(0, -1): (1, 0)
}
return switcher.get(action)
def turn_right(action):
switcher = {
(-1, 0): (0, 1),
... | normal | {
"blob_id": "e1c68c7eb899718dd1c28dc6e95d5538c2b8ad74",
"index": 4510,
"step-1": "import copy\nimport math\nimport operator\n\nimport numpy as np, pprint\n\n\ndef turn_left(action):\n switcher = {\n (-1, 0): (0, -1),\n (0, 1): (-1, 0),\n (1, 0): (0, 1),\n (0, -1): (1, 0)\n\n }\n... | [
0
] |
<|reserved_special_token_0|>
@app.route('/', methods=['POST'])
def hello_world():
if request.method == 'POST':
json_data = request.get_data().decode('utf-8')
_data = json.loads(json_data)
orderNo = _data['orderNo']
name = _data['name']
idcard = _data['idcard']
mobil... | flexible | {
"blob_id": "4652cd5548b550cc21d126fc4fbe3e316ecb71b2",
"index": 143,
"step-1": "<mask token>\n\n\n@app.route('/', methods=['POST'])\ndef hello_world():\n if request.method == 'POST':\n json_data = request.get_data().decode('utf-8')\n _data = json.loads(json_data)\n orderNo = _data['order... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db.drop_all()
db.create_all()
User.query.delete()
Feedback.query.delete()
<|reserved_special_token_0|>
db.session.add(john)
db.session.commit()
<|reserved_special_token_0|>
db.session.add(feed)
db.session.commit()
<|reserved_spe... | flexible | {
"blob_id": "d520f9d681125937fbd9dff316bdc5f922f25ff3",
"index": 8050,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb.drop_all()\ndb.create_all()\nUser.query.delete()\nFeedback.query.delete()\n<mask token>\ndb.session.add(john)\ndb.session.commit()\n<mask token>\ndb.session.add(feed)\ndb.session.commi... | [
0,
1,
2,
3,
4
] |
from urllib.request import urlopen
from bs4 import BeautifulSoup
import re
url = input('Enter - ')
html = urlopen(url).read()
soup = BeautifulSoup(html, "html.parser")
tags = soup.find_all('tr', {'id': re.compile(r'nonplayingnow.*')})
for i in tags:
casa = i.find("td", {'class': re.compile(r'team-home')}).find(... | normal | {
"blob_id": "d07a26a69ccbbccf61402632dd6011315e0d61ed",
"index": 2710,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in tags:\n casa = i.find('td', {'class': re.compile('team-home')}).find('a')\n visitante = i.find('td', {'class': re.compile('team-away')}).find('a')\n print('Partido-> ' +... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def Main():
try:
radius = float(input('Please enter the radius: '))
area = math.pi * radius ** 2
print('Area =', area)
except:
print('You did not enter a number')
<|reserved_special_toke... | flexible | {
"blob_id": "33c4e0504425c5d22cefb9b4c798c3fd56a63771",
"index": 3641,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Main():\n try:\n radius = float(input('Please enter the radius: '))\n area = math.pi * radius ** 2\n print('Area =', area)\n except:\n print('You... | [
0,
1,
2,
3,
4
] |
import os
from datetime import timedelta
ROOT_PATH = os.path.split(os.path.abspath(__name__))[0]
DEBUG = True
JWT_SECRET_KEY = 'shop'
# SQLALCHEMY_DATABASE_URI = 'sqlite:///{}'.format(
# os.path.join(ROOT_PATH, 's_shop_flask.db'))
SQLALCHEMY_TRACK_MODIFICATIONS = False
user = 'shop'
passwd = 'shopadmin'
db = 'shop... | normal | {
"blob_id": "3908d303d0e41677aae332fbdbe9b681bffe5391",
"index": 1044,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nROOT_PATH = os.path.split(os.path.abspath(__name__))[0]\nDEBUG = True\nJWT_SECRET_KEY = 'shop'\nSQLALCHEMY_TRACK_MODIFICATIONS = False\nuser = 'shop'\npasswd = 'shopadmin'\ndb = 'shopdb'\... | [
0,
1,
2,
3
] |
cars=100
drivers=30
passengers=70
print "There are",cars,"cars available."
print "There are only",drivers,"drivers available."
print "Each driver needs to drive",passengers/drivers-1,"passengers."
| normal | {
"blob_id": "b1a1287c2c3b624eb02f2955760f6e9eca8cdcf9",
"index": 1241,
"step-1": "cars=100\ndrivers=30\npassengers=70\nprint \"There are\",cars,\"cars available.\"\nprint \"There are only\",drivers,\"drivers available.\"\nprint \"Each driver needs to drive\",passengers/drivers-1,\"passengers.\"\n",
"step-2": n... | [
0
] |
from scipy.io import wavfile
import numpy
from matplotlib import pyplot as plt
import librosa
import noisereduce
def loadWavFile(fileName, filePath, savePlot, maxAudioLength, reduceNoise = True):
# Read file
# rate, data = wavfile.read(filePath)
# print(filePath, rate, data.shape, "audio length", data.shap... | normal | {
"blob_id": "07ac061d7d1eaf23b6c95fbcbf6753f25e568188",
"index": 157,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef loadWavFile(fileName, filePath, savePlot, maxAudioLength, reduceNoise=True\n ):\n data, rate = librosa.load(filePath, sr=None)\n if reduceNoise:\n noiseRemovedData ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def cal_factor_alpha_return(factor_name, beg_date, end_date, cal_period):
group_number = 8
year_trade_days = 242
min_stock_number = 100
out_path = 'E:\\3_Data\\5_stock_data\\3_alpha_model\\'
alpha_remove_extreme_value = True
alpha_standard = True
alpha_industry... | flexible | {
"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
] |
import datetime
import hashlib
import json
from flask import Flask, jsonify, request
import requests
from uuid import uuid4
from urllib.parse import urlparse
from Crypto.PublicKey import RSA
# Part 1 - Building a Blockchain
class Blockchain:
#chain(emptylist) , farmer_details(emptylist), nodes(set), cre... | normal | {
"blob_id": "f8c222b1a84a092a3388cb801a88495bc227b1d5",
"index": 9748,
"step-1": "<mask token>\n\n\nclass Blockchain:\n\n def __init__(self):\n self.chain = []\n self.farmer_details = []\n self.create_block(proof=1, previous_hash='0')\n self.nodes = set()\n\n def create_block(se... | [
13,
15,
16,
18,
21
] |
<|reserved_special_token_0|>
class TrafficScriptArg:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get_arg(self, arg_name):
"""Get argument value.
:param arg_name: Argument name.
:type arg_name: str
:returns: Argument value.
:rtype: str
"""... | flexible | {
"blob_id": "ea6d726e8163ed0f93b8078323fa5f4e9115ad73",
"index": 1639,
"step-1": "<mask token>\n\n\nclass TrafficScriptArg:\n <mask token>\n <mask token>\n\n def get_arg(self, arg_name):\n \"\"\"Get argument value.\n\n :param arg_name: Argument name.\n :type arg_name: str\n :... | [
2,
3,
4,
5,
6
] |
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