code stringlengths 13 1.2M | order_type stringclasses 1
value | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
BLUE = "#1A94D6"
GREEN = "#73AD21"
PALE_GREEN = "#BBF864"
PALE_BLUE = "#A2C4DA"
BRIGHT_BLUE = "#04BAE3"
ORANGE = "#FF8000"
DARK_ORANGE = "#E65C00"
LIGHT_ORANGE = "#FFAA3E"
PALE_ORANGE = "#F8C381"
GUAVA = "#FF4F40"
FUSCIA = "#E22EFF"
PALE_FUSCIA = "#DFA0E9"
PURPLE = "#AE37C1"
PALE_PURPLE = "#C3AACF"
COLORS = [BLU... | normal | {
"blob_id": "6d8c32fe51fadbe6b6ee14419e1e37c65d4f57bf",
"index": 2508,
"step-1": "<mask token>\n",
"step-2": "BLUE = '#1A94D6'\nGREEN = '#73AD21'\nPALE_GREEN = '#BBF864'\nPALE_BLUE = '#A2C4DA'\nBRIGHT_BLUE = '#04BAE3'\nORANGE = '#FF8000'\nDARK_ORANGE = '#E65C00'\nLIGHT_ORANGE = '#FFAA3E'\nPALE_ORANGE = '#F8C38... | [
0,
1,
2
] |
import numpy as np
class RandomPlayer:
def __init__(self, game):
self.game = game
def play(self, board):
a = np.random.randint(self.game.getActionSize())
valids = self.game.getValidMoves(board, 1)
while valids[a] != 1:
a = np.random.randint(self.game.getActionSize(... | normal | {
"blob_id": "efe099bc5cd0319ffefd779f1e854f1a60edc5fa",
"index": 9240,
"step-1": "<mask token>\n\n\nclass MinimaxPlayer:\n\n def __init__(self, game):\n self.game = game\n\n def play(self, Board):\n key = -1\n bem = -99999999\n board = self.to_board(Board)\n print(Board)\... | [
7,
9,
14,
16,
17
] |
"""
@Description:
@Author : HCQ
@Contact_1: 1756260160@qq.com
@Project : pytorch
@File : call_test
@Time : 2022/5/24 下午10:19
@Last Modify Time @Version @Desciption
-------------------- -------- -----------
2022/5/24 下午10:19 1.0 None
"""
class Person():
def __cal... | normal | {
"blob_id": "7b1c7228c1fc9501ab857cba62a7e073691e75c9",
"index": 755,
"step-1": "<mask token>\n\n\nclass Person:\n\n def __call__(self, name):\n print('__call__' + ' Hello ' + name)\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Person:\n\n def __call__(self, name):\n ... | [
2,
3,
4,
5,
6
] |
""" DB models.
"""
from sqlalchemy import Column, Integer, String, ForeignKey, DateTime
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
from db.session import map_engine, replay_engine
MapBase = declarative_base(bind=map_engine)
ReplayBase = declarative_base(bind=replay... | normal | {
"blob_id": "6b3cb7a42c8bc665e35206b135f6aefea3439758",
"index": 7381,
"step-1": "<mask token>\n\n\nclass Line(MapBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __repr__(self):\n return (\"<Line(id='{}', len='{}', p0='{}', p1='... | [
14,
16,
17,
18,
21
] |
# -*- coding: utf-8 -*-
#COMECE AQUI ABAIXO
p1=float(input('digite o p1:'))
c1=float(input('digite o c1:'))
p2=float(input('digite o p2:'))
c2=float(input('digite o c2:'))
if p1*c1=p2*c2:
print('O')
if pi*c1>p2*c2:
print('-1')
else:
print('1') | normal | {
"blob_id": "210fcb497334ad8bf5433b917fc199c3e22f0f6e",
"index": 6978,
"step-1": "# -*- coding: utf-8 -*-\n#COMECE AQUI ABAIXO\n\np1=float(input('digite o p1:'))\nc1=float(input('digite o c1:'))\np2=float(input('digite o p2:'))\nc2=float(input('digite o c2:'))\n\nif p1*c1=p2*c2:\n print('O')\n\nif pi*c1>p2*c2... | [
0
] |
import math
import os
import sys
import pandas
import numpy as np
import seaborn as sns
import tensorflow as tf
import logging
# from utils.simulation_functions import simulation_cox_gompertz
from utils.preprocessing import formatted_data, normalize_batch, event_t_bin_prob,risk_t_bin_prob,\
batch_t_categorize, next_b... | normal | {
"blob_id": "ebebdb0e79e9d78b818dab3f93d130ccddd2914e",
"index": 1185,
"step-1": "<mask token>\n\n\ndef saveDatadic(file_path, name, dataset):\n np.save(file_path + name + '_x', dataset['x'])\n np.save(file_path + name + '_t', dataset['t'])\n np.save(file_path + name + '_e', dataset['e'])\n\n\n<mask tok... | [
7,
10,
14,
17,
18
] |
from __future__ import absolute_import
import numpy as np
import matplotlib.pyplot as pl
import seaborn as sb
sb.set_color_codes('muted')
import scipy.optimize as op
from scipy import stats
def errorbar(t, f, s, fp=None, **kwargs):
with sb.axes_style('white'):
fig, ax = pl.subplots(1, 1, figsize=(10,3))
... | normal | {
"blob_id": "1e929bc3c97de859a16a4ac8d5ac2ebadefd0516",
"index": 6624,
"step-1": "<mask token>\n\n\ndef errorbar(t, f, s, fp=None, **kwargs):\n with sb.axes_style('white'):\n fig, ax = pl.subplots(1, 1, figsize=(10, 3))\n ax.errorbar(t, f, s, marker='o', color='b', linestyle='none', **kwargs)\n ... | [
4,
5,
6,
7,
8
] |
'''code for recursuve binary search '''
def rbinarysearch(l, k, begin, end):
if(begin == end):
if(l[begin] == k):
return 1
else:
return 0
if(end-begin == 1):
if(l[end] == k) or (l[begin] == k):
return 1
else:
return 0
if(end... | normal | {
"blob_id": "7171edc3eecd2f0cdebd914e89a7a7e0353ddf63",
"index": 9209,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef rbinarysearch(l, k, begin, end):\n if begin == end:\n if l[begin] == k:\n return 1\n else:\n return 0\n if end - begin == 1:\n if ... | [
0,
1,
2,
3
] |
import numpy as np
import cv2
import colorsys
from matplotlib import pyplot as plt
img = cv2.imread('coins.jpg')
b,g,r = cv2.split(img)
rgb_img = cv2.merge([r,g,b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
# Blurring image
grayBlur = cv2.medianBlur(gray, 3)
# Binary threshold
ret, thresh = cv2.threshold(grayBl... | normal | {
"blob_id": "39dda191ab2137b5f5538660f17e39b0a1358bf4",
"index": 206,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(nodes):\n r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R, G, B]\n print(color)\n ... | [
0,
1,
2,
3,
4
] |
from abc import ABC
class Parent(ABC):
def printing(self):
print(self._words)
class Parent2(ABC):
form = "Parent2 Setup: %s"
class Child(Parent, Parent2):
def __init__(self, words):
self._words = self.form % words
super(Child, self).printing()
if __name__ == "__main__":
Child("hello world")
| normal | {
"blob_id": "9ba60270a4afcf242de53692afd8ebff7d9b37a7",
"index": 4361,
"step-1": "<mask token>\n\n\nclass Parent2(ABC):\n form = 'Parent2 Setup: %s'\n\n\nclass Child(Parent, Parent2):\n\n def __init__(self, words):\n self._words = self.form % words\n super(Child, self).printing()\n\n\n<mask t... | [
4,
6,
7,
8,
9
] |
#!/usr/bin/env python
import rospy
from op3_utils.op3_utils import *
from vision import *
import cv2
import sys
import rosnode
#Yellow >> Right
#Red >> Left
class States:
INIT = -1
GET_READY = 1
FIND_BAR = 2
WALK_2_BAR = 3
WALK_SIDEWAYS = 4
PICK_BAR = 5
WALK_WITH_BAR = 6
LIFT_BAR = 7
... | normal | {
"blob_id": "b3a2db38e2074b02c8837bfce85d06598a7b194d",
"index": 5701,
"step-1": "<mask token>\n\n\nclass States:\n INIT = -1\n GET_READY = 1\n FIND_BAR = 2\n WALK_2_BAR = 3\n WALK_SIDEWAYS = 4\n PICK_BAR = 5\n WALK_WITH_BAR = 6\n LIFT_BAR = 7\n WALK_2_FINISH = 8\n END = 99\n\n\n<ma... | [
3,
4,
5,
6,
7
] |
##Linear Queue Data Structure
#Main Queue Class
class LinearQueue():
def __init__(self, length):
#When initiating, user defines the length.
#The head and tail pointers are set at -1 (i.e. not pointing to anything, index beginning at zero)
#The queue is set as a series of None objects in a l... | normal | {
"blob_id": "0efac7d9d1a9180eafa8c9c4e3a42b4c68e718a2",
"index": 4597,
"step-1": "class LinearQueue:\n <mask token>\n\n def enqueue(self, *args):\n for i in args:\n if not self.isFull():\n self._tail += 1\n self._queue[self._tail] = i\n else:\n ... | [
4,
6,
7,
8,
9
] |
import os
# must pip install sox
# type sudo apt install sox into cmd
duration = .2 # seconds
freq = 550 # Hz
os.system('play -nq -t alsa synth {} sine {}'.format(duration, freq))
| normal | {
"blob_id": "8397dcdcb9ec2f35dac0c26b8878a23f9149512b",
"index": 3113,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.system('play -nq -t alsa synth {} sine {}'.format(duration, freq))\n",
"step-3": "<mask token>\nduration = 0.2\nfreq = 550\nos.system('play -nq -t alsa synth {} sine {}'.format(durat... | [
0,
1,
2,
3,
4
] |
'''
Calculations used by algorithms
All calculations for training shall have a standard API that takes in `batch` from algorithm.sample() method and return np array for calculation.
`batch` is a dict containing keys to any data type you wish, e.g. {rewards: np.array([...])}
'''
from slm_lab.lib import logger, util
impo... | normal | {
"blob_id": "07095bc815f5342b66ef4ca74b769321f3ef2ec5",
"index": 7240,
"step-1": "<mask token>\n\n\ndef calc_returns(batch, gamma):\n \"\"\"\n Calculate the simple returns (full rollout) for advantage\n i.e. sum discounted rewards up till termination\n \"\"\"\n rewards = batch['rewards']\n asse... | [
3,
4,
5,
6,
7
] |
class Solution:
# complexity: 2*n^2 + 4*n^2 -> 8*n^2
def numSmallerByFrequency(self, queries: List[str], words: List[str]) -> List[int]:
# complexity: n*2*l where l is the length of the word -> 2*n^2
words_freq = {
word: word.count(min(word)) for word in words
}
quer... | normal | {
"blob_id": "e9918f4fac2e13b36d9b20ffc28dc6508aad6f9b",
"index": 2159,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def numSmallerByFrequency(self, queries: List[str], words: List[str]\n ) ->List[int]:\n words_freq = {word: word.... | [
0,
1,
2,
3
] |
class thrs:
def __init__(self, input_wave):
from numpy import mod, array, sqrt, dot,median,convolve
self.D0 = 20
self.last_det = 0
self.mu = 0.6
self.a_up = 0.2
self.a_down = 0.6
self.z_cumulative = 10
self.n_max = max(input_wave[:1000])
self... | normal | {
"blob_id": "2cdee8799678e8ead21a0f81c42eb7ce209cfec7",
"index": 7289,
"step-1": "class thrs:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class thrs:\n <mask token>\n <mask token>\n\n def getThrs(self, pos):\n if pos - self.last_det < self.D0:\n return self.n... | [
1,
2,
3,
4,
5
] |
from django.conf import settings
from django.contrib import admin
from django.urls import path, include, reverse_lazy
from django.views.generic import RedirectView, TemplateView
from mainapp.views import ShortURLRedirect
urlpatterns = [
path('', TemplateView.as_view(template_name='mainapp/index.html'), name='inde... | normal | {
"blob_id": "573674e50e05880a2822f306c125207b382d872f",
"index": 6389,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif settings.DEBUG:\n import debug_toolbar\n urlpatterns += path('__debug__/', include(debug_toolbar.urls)),\n",
"step-3": "<mask token>\nurlpatterns = [path('', TemplateView.as_vi... | [
0,
1,
2,
3,
4
] |
# coding: utf-8
# In[2]:
from HSTLens_base_classifier_resnet17_s import BaseKerasClassifier
from keras.layers import Activation, AveragePooling2D, MaxPooling2D
from keras.layers import Conv2D, ELU, Dropout, LeakyReLU
from keras.layers.normalization import BatchNormalization
class deeplens_classifier(BaseKerasCl... | normal | {
"blob_id": "6bd47fb71a32b8383a75e72111d802008bc6bc68",
"index": 3350,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass deeplens_classifier(BaseKerasClassifier):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass deeplens_classifier(BaseKerasClassifier):\n\n def _model_definition(self,... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import remctl
import json
import datetime
import time,random
import argparse
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description = "List all TCC Forge overlays"
)
parser.add_argument(
'-n',
'--now',
action = "store_false",
default = True,
dest = 'now',
help ... | normal | {
"blob_id": "1ce34bfec6a9acfeaf0d5c5835ebebed4d7ee369",
"index": 2056,
"step-1": "#!/usr/bin/env python\n\nimport remctl\nimport json\nimport datetime\nimport time,random\nimport argparse\n\nif __name__ == '__main__':\n\tparser = argparse.ArgumentParser(\n\t\tdescription = \"List all TCC Forge overlays\"\n\t)\n\... | [
0
] |
import pandas as pd
import statistics
import csv
df = pd.read_csv("height-weight.csv")
heightlist = df["Height(Inches)"].to_list()
weightlist = df["Weight(Pounds)"].to_list()
heightmean = statistics.mean(heightlist)
heightmedian = statistics.median(heightlist)
heightmode = statistics.mode(heightlist)
heigh... | normal | {
"blob_id": "3f4b05a1d0c4c2a2b085a0265bafbf89b5635e31",
"index": 8021,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(heightmean)\nprint(heightmedian)\nprint(heightmode)\nprint(heightstdev)\n<mask token>\nprint(firstpercentage)\nprint(secondpercentage)\nprint(thirdpercentage)\n",
"step-3": "<mask... | [
0,
1,
2,
3,
4
] |
from db import do_command, do_command_no_return, do_insert
def get_grocery(upc):
cmd = "SELECT name FROM grocery WHERE upc = ?"
rtVal = do_command(cmd, [upc])
length = len(rtVal)
if length > 0:
return {'success': bool(len(rtVal)), 'grocery': rtVal[0]}
return {'success': bool(len(rtVal))... | normal | {
"blob_id": "92b24fe82929ed4590e5350188673c2245136d03",
"index": 5554,
"step-1": "<mask token>\n\n\ndef get_grocery_id(upc):\n cmd = 'SELECT id FROM grocery WHERE upc = ?'\n rtVal = do_command(cmd, [upc])\n if len(rtVal) > 0:\n return rtVal[0]['id']\n else:\n return -1\n\n\n<mask token>... | [
3,
5,
6,
9,
10
] |
n=7
a=[]
for i in range(1,n+1):
print(i)
if(i<n):
print("+")
a.append(i)
print("= {}".format(sum(a)))
| normal | {
"blob_id": "de9b85c250dea15ff9201054957ebc38017a8c35",
"index": 5435,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, n + 1):\n print(i)\n if i < n:\n print('+')\n a.append(i)\nprint('= {}'.format(sum(a)))\n",
"step-3": "n = 7\na = []\nfor i in range(1, n + 1):\n pr... | [
0,
1,
2,
3
] |
# File Name: create_data.py
from sqlalchemy.orm import sessionmaker
from faker import Faker
from db_orm import Base, engine, User, Course
from sqlalchemy import MedaData
session = sessionmaker(engine)()
fake = Faker('zh-cn')
# 创建表
users_table = Table('users', metadata,
Column('id', Integer, primary_key = True),
... | normal | {
"blob_id": "6c94b487eaa179a70ea6528b0214d04d5148574f",
"index": 4070,
"step-1": "<mask token>\n\n\ndef create_users():\n for i in range(10):\n user = User(name=fake.name(), email=fake.email())\n session.add(user)\n\n\ndef create_courses():\n for user in session.query(User).all():\n fo... | [
3,
4,
5,
6,
7
] |
import datetime
from collections import defaultdict
from django.db.models import Prefetch
from urnik.models import Termin, Rezervacija, Ucilnica, DNEVI, MIN_URA, MAX_URA, Srecanje, Semester, RezervacijaQuerySet
class ProsteUcilniceTermin(Termin):
HUE_PRAZEN = 120 # zelena
HUE_POLN = 0 # rdeca
def __i... | normal | {
"blob_id": "3ce9c0aeb6b4e575fbb3fced52a86a1dcec44706",
"index": 4713,
"step-1": "<mask token>\n\n\nclass ProsteUcilnice(object):\n <mask token>\n\n def __init__(self, ucilnice):\n self.ucilnice = set(ucilnice)\n self.zasedenost_ucilnic = defaultdict(dict)\n self.rezerviranost_ucilnic ... | [
20,
22,
26,
27,
28
] |
#import os
import queue as q
#Считываем ввод
file = open('input.txt', 'r')
inp = ''
for i in file:
for j in i:
if (j != '\n'):
inp += j
else:
inp += ' '
inp += ' '
#print(inp)
file.close()
#Записываем все пути в двумерный массив
tmp = '' #Переменная для хранения текущего ... | normal | {
"blob_id": "bb847480e7e4508fbfb5e7873c4ed390943e2fcf",
"index": 3589,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in file:\n for j in i:\n if j != '\\n':\n inp += j\n else:\n inp += ' '\ninp += ' '\nfile.close()\n<mask token>\nfor i in inp:\n if i != ' ... | [
0,
1,
2,
3,
4
] |
import json
import pickle
import zlib
from diskcollections.interfaces import IHandler
class PickleHandler(IHandler):
dumps = staticmethod(pickle.dumps)
loads = staticmethod(pickle.loads)
class PickleZLibHandler(IHandler):
@staticmethod
def dumps(obj, protocol=pickle.HIGHEST_PROTOCOL, level=zlib.
... | normal | {
"blob_id": "60202758a0a42fc26dc1bca9f134a70f28967093",
"index": 2728,
"step-1": "<mask token>\n\n\nclass PickleZLibHandler(IHandler):\n\n @staticmethod\n def dumps(obj, protocol=pickle.HIGHEST_PROTOCOL, level=zlib.\n Z_DEFAULT_COMPRESSION):\n pickled = pickle.dumps(obj, protocol=protocol)\n ... | [
8,
9,
10,
11
] |
#!/usr/bin/python3
import i3ipc
if __name__ == "__main__":
i3 = i3ipc.Connection()
wp = [int(w["name"]) for w in i3.get_workspaces() if w["num"] != -1]
for k in range(1, 16):
if k not in wp:
i3.command("workspace {}".format(k))
break
| normal | {
"blob_id": "cd07dd596f760e232db5c0fd8e27360d61bda635",
"index": 8947,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n i3 = i3ipc.Connection()\n wp = [int(w['name']) for w in i3.get_workspaces() if w['num'] != -1]\n for k in range(1, 16):\n if k not in wp:\n ... | [
0,
1,
2,
3
] |
#! /usr/bin/env python
import RPIO
import sys
RPIO.setwarnings(False)
gpio = int(sys.argv[1])
RPIO.setup(gpio, RPIO.OUT)
input_value = RPIO.input(gpio)
print input_value | normal | {
"blob_id": "382597628b999f2984dba09405d9ff3dd2f35872",
"index": 6765,
"step-1": "#! /usr/bin/env python\n\nimport RPIO\nimport sys\n\nRPIO.setwarnings(False)\n\ngpio = int(sys.argv[1])\n\nRPIO.setup(gpio, RPIO.OUT)\ninput_value = RPIO.input(gpio)\n\nprint input_value",
"step-2": null,
"step-3": null,
"ste... | [
0
] |
from django.db.models import Model, CharField, IntegerField, ManyToManyField, ForeignKey, PROTECT
from django.core.validators import MaxValueValidator, MinValueValidator
from polymorphic.models import PolymorphicModel
from model_utils import Choices
class Tendencia(Model):
valor = CharField(max_length=16, unique=... | normal | {
"blob_id": "c07454dfb9dabb89c86f63063231ae9cf915aa38",
"index": 4116,
"step-1": "<mask token>\n\n\nclass Classe(PolymorphicModel):\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... | [
15,
20,
23,
25,
35
] |
# -*- coding: utf-8 -*-
import requests
import os
def line(body):
url = "https://notify-api.line.me/api/notify"
access_token = 'I89UnoDRgRSInUXJOTg5fAniBE08CUuxVqj8ythMLt8'
headers = {'Authorization': 'Bearer ' + access_token}
message = body
payload = {'message': message}
r = requests.post(url... | normal | {
"blob_id": "8b598703df67fb8287fe6cdccda5b73bf2892da8",
"index": 4878,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef line(body):\n url = 'https://notify-api.line.me/api/notify'\n access_token = 'I89UnoDRgRSInUXJOTg5fAniBE08CUuxVqj8ythMLt8'\n headers = {'Authorization': 'Bearer ' + acces... | [
0,
1,
2,
3,
4
] |
import src.integralimage as II
import src.adaboost as AB
import src.utils as UT
import numpy as np
if __name__ == "__main__":
pos_training_path = 'dataset-1/trainset/faces'
neg_training_path = 'dataset-1/trainset/non-faces'
pos_testing_path = 'dataset-1/testset/faces'
neg_testing_path = 'dataset-1/tes... | normal | {
"blob_id": "3f4f60ff315c8e7e4637a84629894012ed13280e",
"index": 3163,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n pos_training_path = 'dataset-1/trainset/faces'\n neg_training_path = 'dataset-1/trainset/non-faces'\n pos_testing_path = 'dataset-1/testset/faces'\n ... | [
0,
1,
2,
3
] |
import sys
import memo
from StringIO import StringIO
import inspect
alternate_dict = {}
alternate_dict['cartesian_to_polar'] = ['cartesian_to_polar','cartesianToPolar','cartesion_to_polar','Polar_Coordinates']
alternate_dict['mercator'] = ['mercator','mercator_projection','mecartor','Mercator','Mercator_projection']
... | normal | {
"blob_id": "eedd909e777a4127b5fd55108805314b3b196dd1",
"index": 5222,
"step-1": "import sys\nimport memo \nfrom StringIO import StringIO\nimport inspect\n\nalternate_dict = {}\nalternate_dict['cartesian_to_polar'] = ['cartesian_to_polar','cartesianToPolar','cartesion_to_polar','Polar_Coordinates']\nalternate_di... | [
0
] |
import numpy as np
class Adaline:
def __init__(self, eta = 0.0001, n_iter = 2000):
self.eta = eta
self.n_iter = n_iter
self.error = []
def fit(self, X, Y):
X = np.hstack((np.ones((X.shape[0],1)), X))
self.w = np.random.uniform(-1, 1, (X.shape[1], 1))
for n in ... | normal | {
"blob_id": "02e711dfc122007c74949cd9f86e2aeb9d334871",
"index": 329,
"step-1": "<mask token>\n\n\nclass Adaline:\n <mask token>\n\n def fit(self, X, Y):\n X = np.hstack((np.ones((X.shape[0], 1)), X))\n self.w = np.random.uniform(-1, 1, (X.shape[1], 1))\n for n in range(self.n_iter):\n... | [
2,
3,
4,
5,
6
] |
"""
You are given two arrays (without duplicates) nums1 and nums2 where nums1’s elements are subset of nums2. Find all the next greater numbers for nums1's elements in the corresponding places of nums2.
The Next Greater Number of a number x in nums1 is the first greater number to its right in nums2. If it does not exi... | normal | {
"blob_id": "3abeac4fb80244d2da14e14a6048c09b0c0c1393",
"index": 6047,
"step-1": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n\n def nextGreaterElement(self, findNums, nums):\n \"\"\"\n :type findNums: ... | [
1,
2,
3,
4,
5
] |
'''
236. Lowest Common Ancestor of a Binary Tree
https://leetcode.com/problems/lowest-common-ancestor-of-a-binary-tree/
Given a binary tree, find the lowest common ancestor (LCA) of two given nodes in the tree.
According to the definition of LCA on Wikipedia:
“The lowest common ancestor is defined between two nodes p... | normal | {
"blob_id": "ec9184fa3562ef6015801edf316faa0097d1eb57",
"index": 4821,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def postorder(self, node: 'TreeNode', p: 'TreeNode', q: 'TreeNode'\n ... | [
0,
1,
2,
3,
4
] |
from simple_avk.AVK import SimpleAVK
from simple_avk.exceptions import MethodError, LongpollError
| normal | {
"blob_id": "2bccfba2448059a41185b117b224813e344b50f8",
"index": 5673,
"step-1": "<mask token>\n",
"step-2": "from simple_avk.AVK import SimpleAVK\nfrom simple_avk.exceptions import MethodError, LongpollError\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
from solution import find_days
import pudb
def test():
T = [1, 2, 3, 1, 0, 4]
# pudb.set_trace()
res = find_days(T)
assert res == [1, 1, 3, 2, 1, 0]
| normal | {
"blob_id": "db36c82717aa0bacffce7a3e2724ed2bb586c7fb",
"index": 7862,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test():\n T = [1, 2, 3, 1, 0, 4]\n res = find_days(T)\n assert res == [1, 1, 3, 2, 1, 0]\n",
"step-3": "from solution import find_days\nimport pudb\n\n\ndef test():\n ... | [
0,
1,
2,
3
] |
"""deserialization tools"""
import typing as t
from datetime import datetime
from functools import partial
from toolz import compose, flip, valmap
from valuable import load, xml
from . import types
registry = load.PrimitiveRegistry({
bool: dict(true=True, false=False).__getitem__,
datetime: partial(flip(... | normal | {
"blob_id": "2dcb2d8d41096f0affe569d8ddbdd190885d5f14",
"index": 4738,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nregistry = load.PrimitiveRegistry({bool: dict(true=True, false=False).\n __getitem__, datetime: partial(flip(datetime.strptime),\n '%Y-%m-%dT%H:%M:%S%z'), str: str.strip, **{c: c fo... | [
0,
1,
2,
3
] |
import tkinter
from tkinter import ttk, filedialog, messagebox
import serial.tools.list_ports
from PIL import ImageTk, Image
from read_bytes import read
root = tkinter.Tk()
root.title('ChadBotX')
# Define constants for mode selection
MODE_RECORD = 1
MODE_PLAYBACK = 2
# Define gui state
portname = tkinter.StringVar(r... | normal | {
"blob_id": "6455741bbda42b9d84428545ddd50a5d1b54a7ba",
"index": 1376,
"step-1": "<mask token>\n\n\ndef get_ports():\n ports = serial.tools.list_ports.comports()\n ports_str = []\n for port in ports:\n ports_str.append(port.device)\n return ports_str\n\n\ndef start():\n opt_mode = mode.get(... | [
2,
4,
5,
6,
7
] |
import xml.etree.ElementTree as ET
#tree = ET.parse('rutas/rutas_prueba.xml')
#treeToAdd = ET.parse('rutas/rutas_prueba_agregar.xml')
#root = tree.getroot()
#git rootToAdd = treeToAdd.getroot()
#for child in root:
# for test in child:
# print(test.tag, test.attrib)
#for elem in root.iter():
# print(... | normal | {
"blob_id": "b4b7e20c9558bd1b29a1c1fa24bfca8a2d292b27",
"index": 398,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor root in rootsToAdd:\n for elem in root:\n root1.append(elem)\nrutas0k_10k.write('rutas/rutas0k-110k.xml')\n",
"step-3": "<mask token>\nrutas0k_10k = ET.parse('rutas/rutas0k... | [
0,
1,
2,
3,
4
] |
# 5/1/2020
# Import median function from numpy
import numpy as np
from numpy import median
# Plot the median number of absences instead of the mean
sns.catplot(x="romantic", y="absences",
data=student_data,
kind="point",
hue="school",
ci=None,
estimator = median)
# S... | normal | {
"blob_id": "11072601e31ceba13f8adf6c070f84ca5add35e9",
"index": 3300,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsns.catplot(x='romantic', y='absences', data=student_data, kind='point',\n hue='school', ci=None, estimator=median)\nplt.show()\n",
"step-3": "import numpy as np\nfrom numpy import m... | [
0,
1,
2,
3
] |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sun Jul 8 18:04:13 2018
@author: zhangchi
"""
class Solution(object):
def transpose(self, A):
"""
:type A: List[List[int]]
:rtype: List[List[int]]
"""
row = len(A[0])
result = [[] for _ in range(row)]
... | normal | {
"blob_id": "3882aaf94b19967a1d1eff23fa4862ea71de3b38",
"index": 7014,
"step-1": "#!/usr/bin/env python2\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Jul 8 18:04:13 2018\n\n@author: zhangchi\n\"\"\"\n\nclass Solution(object):\n def transpose(self, A):\n \"\"\"\n :type A: List[List[int]]\n ... | [
0
] |
#finding postgresql info
import re
import subprocess
def get_postgre_version():
p = subprocess.Popen("psql --version",stdout=subprocess.PIPE,shell=True)
k = re.findall(r'psql\s+\(PostgreSQL\)\s+(.*)',p.stdout.read())
postgre_version = k[0]
return postgre_version
version=get_postgre_version()
print ver... | normal | {
"blob_id": "e6b84a2190a84c871e7191ef49fb7ee8b8148c9a",
"index": 7062,
"step-1": "#finding postgresql info\nimport re\nimport subprocess\ndef get_postgre_version():\n p = subprocess.Popen(\"psql --version\",stdout=subprocess.PIPE,shell=True)\n k = re.findall(r'psql\\s+\\(PostgreSQL\\)\\s+(.*)',p.stdout.rea... | [
0
] |
from difflib import SequenceMatcher
import csv
naam = "straat"
def similar(a, b):
return SequenceMatcher(None, a, b).ratio()
f = open("straten.txt", "r")
f.readline()
names = f.readlines()
for name in names:
if similar(name[:-1].lower(),naam.lower()) > 0.7:
sim = similar(name[:-1].lower(),naam.lower(... | normal | {
"blob_id": "2f1193e3ab5e0527ab5f89141613eddb18b5f61d",
"index": 2787,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef similar(a, b):\n return SequenceMatcher(None, a, b).ratio()\n\n\n<mask token>\nf.readline()\n<mask token>\nfor name in names:\n if similar(name[:-1].lower(), naam.lower()) >... | [
0,
2,
3,
4,
5
] |
import pycmc
# open project, get Crag, CragVolumes, and intensity images
crag = ...
cragVolumes = ...
raw = ...
membrane = ...
nodeFeatures = ...
edgeFeatures = ...
statisticsFeatureProvider = pycmc.StatisticsFeatureProvider(cragVolumes, raw, "raw")
shapeFeatureProvider = pycmc.ShapeFeatureProvider(cragVolumes)
... | normal | {
"blob_id": "37d817436ce977339594867ef917177e7371a212",
"index": 6847,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfeatureProvider.add(shapeFeatureProvider)\nfeatureProvider.add(statisticsFeatureProvider)\n<mask token>\nfeatureExtractor.extractFeatures(nodeFeatures, edgeFeatures, featureProvider)\n",
... | [
0,
1,
2,
3,
4
] |
# Taken from: https://github.com/flyyufelix/cnn_finetune/blob/master/vgg16.py
# based on: https://gist.github.com/baraldilorenzo/07d7802847aaad0a35d3
# -*- coding: utf-8 -*-
import keras
import itertools
import sys
from sklearn.metrics import confusion_matrix
import numpy as np
import matplotlib
import ma... | normal | {
"blob_id": "906b7f02d6a7968bbf4780e682d4f9a92526326a",
"index": 9123,
"step-1": "\r\n# Taken from: https://github.com/flyyufelix/cnn_finetune/blob/master/vgg16.py \r\n# based on: https://gist.github.com/baraldilorenzo/07d7802847aaad0a35d3\r\n\r\n# -*- coding: utf-8 -*-\r\nimport keras\r\nimport itertools\r\nimp... | [
0
] |
import wfdb as wf
import numpy as np
from scipy import signal as ss
from datasets import mitdb as dm
from matplotlib import pyplot as plt
def show_path(path):
""" As a plot """
# Read in the data
record = wf.rdsamp(path)
annotation = wf.rdann(path, 'atr')
data = record.p_signals
cha = data[:, 0... | normal | {
"blob_id": "4ba722e685c7608fcfd5111131c96847c0408a02",
"index": 1905,
"step-1": "import wfdb as wf\nimport numpy as np\nfrom scipy import signal as ss\nfrom datasets import mitdb as dm\nfrom matplotlib import pyplot as plt\n\ndef show_path(path):\n \"\"\" As a plot \"\"\"\n # Read in the data\n record ... | [
0
] |
# -*- coding:utf-8 -*-
'''
Created on 2018/2/23
@author : xxfore
'''
import time
import sys
import re
sys.dont_write_bytecode = True
class TimeUtils(object):
@staticmethod
def convert_timestamp_to_date(timestamp):
time_local = time.localtime(timestamp)
dt = time.strftime("%Y-%m-%d %H:%M:%S",t... | normal | {
"blob_id": "933f74e4fda0b30bdf70ff3f3dbde2383b10c694",
"index": 8773,
"step-1": "<mask token>\n\n\nclass TimeUtils(object):\n <mask token>\n\n\nclass StringUtils(object):\n\n @staticmethod\n def remove_emoji_from_string(text):\n co = re.compile(u'[𐀀-\\U0010ffff]')\n return co.sub(u'', te... | [
3,
4,
5,
6,
7
] |
#
# @lc app=leetcode.cn id=2006 lang=python3
#
# [2006] 差的绝对值为 K 的数对数目
#
# @lc code=start
class Solution:
def countKDifference(self, nums: List[int], k: int) -> int:
def abs(x,y):
if(x-y>=0):
return x-y
else:
return y-x
ret = 0
for i... | normal | {
"blob_id": "351b2c2a18473e6ac541a96165c69c836ea101de",
"index": 846,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def countKDifference(self, nums: List[int], k: int) ->int:\n\n def abs(x, y):\n if x - y >= 0:\n ... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class Event(models.Model):
name = models.CharField('Назва', max_length=200)
date = models.DateField('Дата')
address = models.CharField('Адреса', max_length=255, blank=True, null=True)... | normal | {
"blob_id": "137f9310256f66ccd9fbe6626659c3c4daea0efc",
"index": 8949,
"step-1": "<mask token>\n\n\nclass Atendent(models.Model):\n user = models.ForeignKey(User)\n event = models.ForeignKey(Event, null=True, blank=True)\n state = models.IntegerField(null=True, blank=True)\n",
"step-2": "<mask token>\... | [
2,
4,
5,
6,
7
] |
# Copyright (c) 2021 Cisco and/or its affiliates.
#
# SPDX-License-Identifier: Apache-2.0 OR GPL-2.0-or-later
#
# Licensed under the Apache License 2.0 or
# GNU General Public License v2.0 or later; you may not use this file
# except in compliance with one of these Licenses. You
# may obtain a copy of the Licenses at:... | normal | {
"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
] |
# -*- coding: utf-8 -*-
import scrapy
class QuoteesxtractorSpider(scrapy.Spider):
name = 'quoteEsxtractor'
allowed_domains = ['quotes.toscrape.com']
start_urls = ['http://quotes.toscrape.com/']
def parse(self, response):
for quote in response.css('.quote') :
# print(quote.getall()... | normal | {
"blob_id": "ce26ad27b7729164e27c845e2803a670b506bad8",
"index": 580,
"step-1": "<mask token>\n\n\nclass QuoteesxtractorSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass QuoteesxtractorSpider(scrapy.Spider):\n <mask token>\n... | [
1,
2,
3,
4,
5
] |
import numpy as np
# Read in training data and labels
# Some useful parsing functions
# male/female -> 0/1
def parseSexLabel(string):
if (string.startswith('male')):
return 0
if (string.startswith('female')):
return 1
print("ERROR parsing sex from " + string)
# child/teen/adult/senior ->... | normal | {
"blob_id": "6822a0a194e8b401fecfed2b617ddd5489302389",
"index": 4718,
"step-1": "<mask token>\n\n\ndef parseSexLabel(string):\n if string.startswith('male'):\n return 0\n if string.startswith('female'):\n return 1\n print('ERROR parsing sex from ' + string)\n\n\n<mask token>\n\n\ndef pars... | [
2,
3,
4,
5,
7
] |
from django.urls import path
from admin_panel import views
urlpatterns = [path('admin_panel/', views.AdminPanel.as_view(), name=
'admin_panel'), path('admin_panel/connection/', views.Connection.
as_view(), name='connect_group-teacher'), path(
'admin_panel/connection/<str:choiced_departament>', views.Connect... | normal | {
"blob_id": "34a7fd66a9e2eae25994336f22a76c24c11a6e1b",
"index": 7408,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('admin_panel/', views.AdminPanel.as_view(), name=\n 'admin_panel'), path('admin_panel/connection/', views.Connection.\n as_view(), name='connect_group-teacher'),... | [
0,
1,
2
] |
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
AWS_KEY = '****'
AWS_SECRET = '****'
def handler(event, context):
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', aws_access_key_id=AWS_KEY , aws_secret_access_key=AWS_SECRET)
table = dynamo... | normal | {
"blob_id": "511ea9eb1dc234a488c19f9ee9fbd40f81955d54",
"index": 5172,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef handler(event, context):\n dynamodb = boto3.resource('dynamodb', region_name='us-west-2',\n aws_access_key_id=AWS_KEY, aws_secret_access_key=AWS_SECRET)\n table = dyn... | [
0,
1,
2,
3,
4
] |
def get_bios_boot_order(self):
result = {
}
boot_device_list = []
boot_device_details = []
key = 'Bios'
bootsources = 'BootSources'
response = self.get_request((self.root_uri + self.systems_uri))
if (response['ret'] is False):
return response
result['ret'] = True
... | normal | {
"blob_id": "bbe7df31a44ccf51c305cd620dc7c4155b7e1a97",
"index": 2668,
"step-1": "<mask token>\n",
"step-2": "def get_bios_boot_order(self):\n result = {}\n boot_device_list = []\n boot_device_details = []\n key = 'Bios'\n bootsources = 'BootSources'\n response = self.get_request(self.root_ur... | [
0,
1,
2
] |
version https://git-lfs.github.com/spec/v1
oid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49
size 964
| normal | {
"blob_id": "42187f460a64572d2581ed5baec41eaff47466f8",
"index": 8672,
"step-1": "version https://git-lfs.github.com/spec/v1\noid sha256:91f725dc0dba902c5c2c91c065346ab402c8bdbf4b5b13bdaec6773df5d06e49\nsize 964\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]... | [
0
] |
from kraken.core.maths import Vec3, Vec3, Euler, Quat, Xfo
from kraken.core.objects.components.base_example_component import BaseExampleComponent
from kraken.core.objects.attributes.attribute_group import AttributeGroup
from kraken.core.objects.attributes.scalar_attribute import ScalarAttribute
from kraken.core.objec... | normal | {
"blob_id": "20167058697450f342c2ac3787bd1721f860dc58",
"index": 3169,
"step-1": "<mask token>\n\n\nclass SimpleControlComponentGuide(SimpleControlComponent):\n <mask token>\n\n def __init__(self, name='SimpleControl', parent=None):\n Profiler.getInstance().push(\n 'Construct Simple Contr... | [
12,
15,
17,
18,
20
] |
print("hello world")
print("welcome to london") | normal | {
"blob_id": "cd322f9771f1ac90931a7229ffd5effd1cae1a54",
"index": 7207,
"step-1": "<mask token>\n",
"step-2": "print('hello world')\nprint('welcome to london')\n",
"step-3": "print(\"hello world\")\nprint(\"welcome to london\")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
#Testing Operating System Descriptions
#OS : LMDE 4 Debbie
#Version: 4.6.7
#Kernal Version : 4.19.0-8-amd64
#Scripting Langages : Python3
#----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------... | normal | {
"blob_id": "422491852b80c2fc4a2e73c01fd01acaad4cf9c8",
"index": 7573,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nregr.fit(X_train, y_train)\nprint(regr.score(X_test, y_test))\n<mask token>\nprint('Mean Absolute Error:', metrics.mean_absolute_error(y_test, y_pred))\nprint('Mean Squared Error:', metri... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
import rospy
from mark1.srv import WordCount, WordCountResponse
s= set('',)
def count_words(request):
s.update(set( request.words.split() ))
print s
return WordCountResponse( len( request.words.split()))
rospy.init_node('mark_service_server')
service = rospy.Service('Word_count', W... | normal | {
"blob_id": "e90e4d2c777554999ab72d725d7e57bdfd508d3a",
"index": 3966,
"step-1": "#!/usr/bin/env python\nimport rospy\nfrom mark1.srv import WordCount, WordCountResponse\n\ns= set('',)\n\ndef count_words(request):\n s.update(set( request.words.split() ))\n print s\n return WordCountResponse( len( reques... | [
0
] |
"""
Auteur:Fayçal Chena
Date : 07 avril 2020
Consignes :
Écrire une fonction alea_dice(s) qui génère trois nombres (pseudo) aléatoires à l’aide
de la fonction randint du module random, représentant trois dés (à six faces avec
les valeurs de 1 à 6), et qui renvoie la valeur booléenne True si les dés forment un 421,
et l... | normal | {
"blob_id": "ad5a9e353d065eee477381aa6b1f233f975ea0ed",
"index": 3374,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef foo_6(x, y):\n return y, x\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef foo_6(x, y):\n return y, x\n\n\n<mask token>\nfoo_6(a, b)\nprint(a, b)\n",
"step-4": "<... | [
0,
1,
2,
3,
4
] |
from peewee import BlobField
class BytesField(BlobField):
"""This is a BlobField adapted to our needs
Default BlobField returns memoryview when getting data from the db. We want bytes.
"""
def adapt(self, value):
if value and isinstance(value, memoryview):
return value.tobytes()
... | normal | {
"blob_id": "b11869076c2c8d6207df861cd1d0b0434b3f9477",
"index": 9836,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass BytesField(BlobField):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass BytesField(BlobField):\n <mask token>\n\n def adapt(self, value):\n ... | [
0,
1,
2,
3,
4
] |
# Import the SDK
import json
import boto3
from botocore.exceptions import ClientError
import uuid
#dbclient = boto3.client('dynamodb')
dbresource = boto3.resource('dynamodb', region_name='eu-west-1')
rekclient = boto3.client('rekognition','eu-west-1')
collection_name = 'swiftarycelebrity'
ScannedFacestable = dbresour... | normal | {
"blob_id": "6369c692e358c0dfd1193c6e961ecf9b521ea9ba",
"index": 4649,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor Images in Faces:\n lv_FaceId = Images['FaceId']\n lv_ImageId = Images['ImageId']\n lv_ExternalImageId = Images['ExternalImageId'],\n lv_Names = ExternalImageId.split('_')\... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
#coding=utf-8
from datetime import *
import unittest
def getSnapshot(historyData, id):
data = historyData.split('\n')
lines = len(data)
if lines < 2 :
return 'Input is too short!'
index = 0
curid = ''
idlist = dict()
recordtime = ''
animal_pos = dict()
f... | normal | {
"blob_id": "ddbcc8e768f93a0b4f8776b19e752c57feb5bbf9",
"index": 6362,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getSnapshot(historyData, id):\n data = historyData.split('\\n')\n lines = len(data)\n if lines < 2:\n return 'Input is too short!'\n index = 0\n curid = ''\n... | [
0,
1,
2,
3
] |
import argparse
import logging
import enum
from abc import ABCMeta, abstractmethod
from nmigen import *
from ....gateware.pads import *
from ....gateware.i2c import I2CTarget
from ... import *
class Event(enum.IntEnum):
START = 0x10
STOP = 0x20
RESTART = 0x30
WRITE = 0x40
READ = 0x50
... | normal | {
"blob_id": "0f2882971f08450e970e188ed2a06ae1683c682c",
"index": 7552,
"step-1": "<mask token>\n\n\nclass I2CTargetApplet(GlasgowApplet, name='i2c-target'):\n logger = logging.getLogger(__name__)\n help = 'accept I²C transactions'\n description = \"\"\"\n Process transactions on the I²C bus as a soft... | [
7,
12,
13,
16,
18
] |
# -*- coding: utf-8 -*-
'''
LE JEU DE LA VIE
Mini projet numéro 2 de NSI
Modélisation Objet :
Q1) On peut dégager, au premier abord : une classe cellule (avec un attribut état et un autre voisins) et une classe grille (avec un attribut ordonnée et un autre abscisse). En effet, ce sont les deux éléments du jeu.... | normal | {
"blob_id": "cef904b70eb9a997c3c48884ee34665a77e18897",
"index": 8465,
"step-1": "<mask token>\n\n\nclass Cellule:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def basculer(self):\n \"\"\"mutateur qui change l'état actuel de la cellule ... | [
20,
23,
24,
28,
32
] |
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 22 18:05:44 2018
@author: Administrator
"""
from sklearn.model_selection import cross_val_score, train_test_split
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import StratifiedKFold
from sklearn.m... | normal | {
"blob_id": "aaa0ac5e31e2c10b5baba6077e952fff1a92ef82",
"index": 882,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('cross-vali score is: {}'.format(score.mean()))\n<mask token>\nfor train_index, test_index in kfold.split(iris.data, iris.target):\n print(train_index, test_index)\n<mask token>\n... | [
0,
2,
3,
4,
5
] |
import json
from datetime import datetime, timedelta
from itertools import product
from django.db.models import QuerySet
import pytz
from model_mommy import mommy
from ...views import get_authors, get_featured_challenges, get_term_of_user
class TestNonMiscView:
"""Test for non view functions in ideax.views (... | normal | {
"blob_id": "8d6e4d06e390b4a45e576239189745c2e37217c5",
"index": 2699,
"step-1": "<mask token>\n\n\nclass TestNonMiscView:\n <mask token>\n <mask token>\n\n def test_get_term_of_user(self, rf, db):\n mommy.make('Use_Term', term='EULA Test', final_date=datetime.now(\n pytz.UTC) + timede... | [
5,
6,
7,
9,
10
] |
#!/usr/bin/env python
###############################################################################
# Copyright 2017 The Apollo 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 ... | normal | {
"blob_id": "4b552731fcfc661c7ad2d63c7c47f79c43a8ae5e",
"index": 4839,
"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\n @classmethod\n def get_pb(cls):\n \"\"\"Get a pb instance from the... | [
4,
6,
7,
9,
10
] |
import urllib.request, urllib.parse, urllib.error
from urllib.request import urlopen
import xml.etree.ElementTree as ET
import ssl
# # Ignore SSL certificate errors
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE
url = input('Enter a URL: ')
# if len(url) < 1 : url = 'ht... | normal | {
"blob_id": "3b8c4f19e28e54e651862ec9b88b091c9faff02b",
"index": 9525,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(url) < 1:\n url = 'http://py4e-data.dr-chuck.net/comments_70857.xml'\n<mask token>\nprint(len(xml))\n<mask token>\nprint('Comment count:', len(lst))\n<mask token>\nfor item in l... | [
0,
1,
2,
3,
4
] |
import os
import redis
import requests
import lxml.html
ads_api_url = "http://adslabs.org/adsabs/api/search/"
ads_html_url = "http://labs.adsabs.harvard.edu/adsabs/abs/"
rdb = redis.Redis()
def get_dev_key():
# Credit: Andy Casey
ads_dev_key_filename = os.path.abspath(
os.path.expanduser("~/.ads/dev... | normal | {
"blob_id": "9e314cdf4ef09ecf4a4b43358ae32f76c40aaea8",
"index": 8037,
"step-1": "<mask token>\n\n\ndef get_dev_key():\n ads_dev_key_filename = os.path.abspath(os.path.expanduser('~/.ads/dev_key')\n )\n if os.path.exists(ads_dev_key_filename):\n with open(ads_dev_key_filename, 'r') as fp:\n ... | [
2,
3,
4,
5,
6
] |
import smtplib
import os
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from datetime import datetime
from threading import Thread
FROM = os.getenv('EMAIL_FROM')
TO = os.getenv('EMAIL_TO')
HOST = os.getenv('EMAIL_HOST')
PORT = os.getenv('EMAIL_PORT')
PASSWORD = os.getenv('EMAIL_PAS... | normal | {
"blob_id": "60c3f6775d5112ff178bd3774c776819573887bb",
"index": 9367,
"step-1": "<mask token>\n\n\ndef _send(body, subject):\n msg = MIMEMultipart()\n msg['From'] = FROM\n msg['To'] = TO\n msg['Subject'] = subject\n msg.attach(MIMEText(body, 'plain'))\n server = smtplib.SMTP(host=HOST, port=in... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
"""
This is the very first A.I. in this series.
The vision is to devlop 'protocol droid' to talk to, to help with tasks, and with whom to play games.
The droid will be able to translate langages and connect ppl.
"""
import speech_recognition as sr
import pyttsx3
import pywhatkit
... | normal | {
"blob_id": "f5d353694a719472320f4d6fa28bc9d2cc5a69b0",
"index": 951,
"step-1": "<mask token>\n\n\ndef talk(text):\n engine.say('heyo' + text)\n engine.runAndWait()\n\n\ndef take_command():\n try:\n with sr.Microphone() as source:\n print('listening....')\n voice = listener.... | [
2,
4,
5,
6,
7
] |
import os
import sys
import pytest
def run_test(file_name, capture_stdout=True, allure_dir=None):
cmd = [
file_name, "-vvv",
]
if capture_stdout:
cmd.append("-s")
test_name = os.path.splitext(os.path.basename(file_name))[0]
alluredir = os.path.normpath("%s/%s/" % (allure_dir or "... | normal | {
"blob_id": "7e7a50cb8e66a71c1df2d61241f8a55c042b7d59",
"index": 2664,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef run_test(file_name, capture_stdout=True, allure_dir=None):\n cmd = [file_name, '-vvv']\n if capture_stdout:\n cmd.append('-s')\n test_name = os.path.splitext(os.pa... | [
0,
1,
2,
3
] |
import pulumi
import pulumi_aws as aws
bar = aws.elasticache.get_replication_group(replication_group_id="example")
| normal | {
"blob_id": "4bf140ae01f2eaa0c67f667766c3ec921d552066",
"index": 6073,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nbar = aws.elasticache.get_replication_group(replication_group_id='example')\n",
"step-3": "import pulumi\nimport pulumi_aws as aws\nbar = aws.elasticache.get_replication_group(replicati... | [
0,
1,
2,
3
] |
####
# This is the script for storing the schema of your TerminusDB
# database for your project.
# Use 'terminusdb commit' to commit changes to the database and
# use 'terminusdb sync' to change this file according to
# the exsisting database schema
####
from typing import List
from terminusdb_client.woqlschema impor... | normal | {
"blob_id": "f702cdef3782ddc96244f3cf8e2026581d60baa9",
"index": 1537,
"step-1": "<mask token>\n\n\nclass State(DocumentTemplate):\n _key = ValueHashKey()\n country: 'Country'\n name: str\n",
"step-2": "<mask token>\n\n\nclass Address(DocumentTemplate):\n <mask token>\n city: 'City'\n coordin... | [
2,
13,
14,
15,
16
] |
# encoding: utf-8
'''🤠 PDS Roundup: A step takes you further towards a complete roundup'''
from enum import Enum
from .util import commit, invoke
import logging, github3, tempfile, zipfile, os
_logger = logging.getLogger(__name__)
class Step(object):
'''An abstract step; executing steps comprises a roundup'''... | normal | {
"blob_id": "21e86e4719cda5c40f780aca6e56eb13c8c9b8e5",
"index": 988,
"step-1": "<mask token>\n\n\nclass StepName(Enum):\n <mask token>\n null = 'null'\n unitTest = 'unitTest'\n integrationTest = 'integrationTest'\n changeLog = 'changeLog'\n requirements = 'requirements'\n docs = 'docs'\n ... | [
15,
20,
21,
25,
27
] |
class Rover(object):
DIRECTIONS = 'NESW'
MOVEMENTS = {
'N': (0, 1),
'E': (1, 0),
'S': (0, -1),
'W': (-1, 0)
}
def __init__(self, init_string, plateau_dimensions):
'''
give the rover a sense of the plateau it's on
'''
max_x, max_y = p... | normal | {
"blob_id": "1f49d2341f0bcc712baede28f41c208a01b92e6d",
"index": 2998,
"step-1": "class Rover(object):\n\n DIRECTIONS = 'NESW'\n MOVEMENTS = {\n 'N': (0, 1),\n 'E': (1, 0),\n 'S': (0, -1),\n 'W': (-1, 0)\n }\n\n def __init__(self, init_string, plateau_dimensions):\n ... | [
0
] |
from turtle import Turtle
class Paddle(Turtle):
def __init__(self, x_position, y_position):
super().__init__()
self.shape('square')
self.shapesize(stretch_wid=5, stretch_len=1)
self.penup()
self.color("white")
self.goto(x=x_position, y=y_position)
self.speed... | normal | {
"blob_id": "f49b80d0b8b42bafc787a36d0a8be98ab7fa53e7",
"index": 3558,
"step-1": "<mask token>\n\n\nclass Paddle(Turtle):\n <mask token>\n\n def up(self):\n y_pos = self.ycor()\n x_pos = self.xcor()\n self.goto(y=y_pos + 20, x=x_pos)\n\n def down(self):\n y_pos = self.ycor()\... | [
3,
4,
5,
6,
7
] |
import numpy as np
import cv2
import os
from moviepy.editor import *
N = 1
# Initiate SIFT detector
sift = cv2.xfeatures2d.SIFT_create()
# count file number in folder frames
list = os.listdir('./frames')
number_files = len(list)
# array to store similarity of 2 consecutive frames
similarity = []
boundaries = []
ke... | normal | {
"blob_id": "397d9b1030a1ec08d04d2101f65a83547495b861",
"index": 7165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, number_files - N - 1, N):\n img1 = cv2.imread('./frames/frame%d.jpg' % i, 0)\n img2 = cv2.imread('./frames/frame%d.jpg' % (i + N), 0)\n kp1, des1 = sift.detectA... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 17 22:28:30 2019
@author: donsdev
"""
arr = []
sub = []
n = int(input())
while n > 0:
arr.append(n)
n-=1
while len(arr) + len(sub) > 1:
while len(arr) > 1:
arr.pop()
sub.append(arr.pop())
arr = sub[::-1] + arr
su... | normal | {
"blob_id": "d5d31920f7fd4ed2913c5880dba61c2015181be9",
"index": 5760,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile n > 0:\n arr.append(n)\n n -= 1\nwhile len(arr) + len(sub) > 1:\n while len(arr) > 1:\n arr.pop()\n sub.append(arr.pop())\n arr = sub[::-1] + arr\n sub ... | [
0,
1,
2,
3
] |
import os
import sys
from tensor2tensor.bin import t2t_trainer
def problem_args(problem_name):
args = [
'--generate_data',
'--model=transformer',
'--hparams_set=transformer_librispeech_v1',
'--problem=%s' % problem_name,
'--data_dir=/tmp/refactor_test/problems/%s/data' % problem_name,
'--t... | normal | {
"blob_id": "cc5ad95419571d3eb2689b428e5805ad69958806",
"index": 4796,
"step-1": "<mask token>\n\n\ndef problem_args(problem_name):\n args = ['--generate_data', '--model=transformer',\n '--hparams_set=transformer_librispeech_v1', '--problem=%s' %\n problem_name, '--data_dir=/tmp/refactor_test/pr... | [
1,
2,
3,
4,
5
] |
""" Tests for `yatsm.utils`
"""
import numpy as np
import pytest
from yatsm import utils
@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])
def test_distribute_jobs_interlaced(nrow, njob):
assigned = []
for i in range(njob):
assigned.extend(utils.distribute_jobs(i, njob, nrow, i... | normal | {
"blob_id": "a513dfd84b5d9267b7e96fedc88e5b6dabeea19e",
"index": 640,
"step-1": "<mask token>\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_job... | [
4,
6,
7,
8,
9
] |
from google.cloud import vision
from google.cloud.vision import types
from google.oauth2 import service_account
import os
# import re
import io
import pdf2image
import tempfile
import datetime
# Google API
credentials = service_account.Credentials.from_service_account_file("APIKey.json")
client = vision.ImageAnnot... | normal | {
"blob_id": "be69a9981fe6b53c3b9c4d2893913e4f9f7efb26",
"index": 6697,
"step-1": "<mask token>\n\n\ndef boxes_to_obj(self, bound):\n return {'x1': bound.vertices[0].x, 'x2': bound.vertices[1].x, 'y1':\n bound.vertices[0].y, 'y2': bound.vertices[2].y}\n\n\ndef generateTempFolder(self, prifx, src):\n ... | [
3,
5,
6,
7,
8
] |
import os
from PIL import Image
import cv2
import shutil
root = './train'
save_path = './thumbnail'
for r, d, files in os.walk(root):
if files != []:
for i in files:
fp = os.path.join(r, i)
label = i.split('_')[0]
dst = os.path.join(save_path, label)
if not o... | normal | {
"blob_id": "cc19ff829cc4a11c3dc873353fa2194ec9a87718",
"index": 8584,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor r, d, files in os.walk(root):\n if files != []:\n for i in files:\n fp = os.path.join(r, i)\n label = i.split('_')[0]\n dst = os.path.join(s... | [
0,
1,
2,
3,
4
] |
from sqlalchemy import Boolean, Column, ForeignKey, Integer, String, DATE
from sqlalchemy.orm import relationship
from database import Base
class User(Base):
__tablename__ = "users"
username = Column(String, primary_key=True, index=True)
email = Column(String, unique=True, index=True)
name = Column(... | normal | {
"blob_id": "acf69cd714f04aeceb4be39b8a7b2bc5d77cd69f",
"index": 3307,
"step-1": "<mask token>\n\n\nclass Documents(Base):\n __tablename__ = 'documents'\n id = Column(Integer, primary_key=True, index=True)\n name_doc = Column(String, index=True)\n exp = Column(DATE, index=True)\n notif = Column(In... | [
2,
3,
4,
5,
6
] |
import os
import multiprocessing
import time
import psycopg2
#os.system("myproject1\\runscrapy2.py")
#from scrapy import cmdline
#os.system("scrapy crawl parts")
#cmdline.execute("cd myproject1".split())
#cmdline.execute("myproject1\\runscrapy.bat".split())
# start = time.perf_counter()
connection = psycopg2.conne... | normal | {
"blob_id": "8e0d729fa55aabede123d89a507296b7d8a45c8b",
"index": 1705,
"step-1": "<mask token>\n\n\ndef urls():\n os.system('urls.bat')\n\n\ndef urls_1():\n os.system('urls_1.bat')\n\n\n<mask token>\n\n\ndef urls_3():\n os.system('urls_3.bat')\n\n\ndef urls_4():\n os.system('urls_4.bat')\n\n\ndef url... | [
39,
53,
59,
67,
75
] |
"""Handles loading and tokenising of datasets"""
import enum
import numpy as np
import os.path
import pickle
from tqdm import tqdm
import nltk
from nltk import WordPunctTokenizer
nltk.download('punkt')
from nltk.tokenize import word_tokenize
from lib.utils import DATASETS_BASE_PATH, SAVED_POS_BASE_PATH
from lib.pos im... | normal | {
"blob_id": "0150e1db3ef2f6c07280f21971b43ac71fc4cada",
"index": 8984,
"step-1": "<mask token>\n\n\nclass DatasetType(enum.Enum):\n \"\"\"\n Represents the type of dataset\n \"\"\"\n TRAIN = 0\n VAL = 1\n TEST = 2\n\n\nclass Language(enum.Enum):\n \"\"\"\n Represents the dataset language\... | [
7,
8,
11,
12,
13
] |
# -*- coding: utf-8 -*-
# Copyright (c) 2017 Feng Shuo
#
# 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
from itertools impo... | normal | {
"blob_id": "a299bd230a25a646060f85cffc8e84c534e2f805",
"index": 8185,
"step-1": "# -*- coding: utf-8 -*-\n# Copyright (c) 2017 Feng Shuo\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a cop... | [
0
] |
#!/usr/bin/env python
# Sanjaya Gajurel, Computational Scientist, Case Western Reserve University, April 2015
import vtk
# ------------------------------------------------------------------------------
# Script Entry Point
# ------------------------------------------------------------------------------
if __name__ ==... | normal | {
"blob_id": "de7515cb71c8e30018b14baf8846648d0c76a592",
"index": 7461,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n print(\n 'vtkGraph: Building a graph using Unstructured Grid & dumping it in a vtk file, vertex.vtu, to be visualized using ParaView'\n )\n ... | [
0,
1,
2,
3
] |
def assert_number(arg):
if not isinstance(arg, (int, float)):
raise TypeError(f"Expected number, got {type(arg)}")
| normal | {
"blob_id": "2de62c73507acac597d70557adfe8286e2f28a1f",
"index": 5569,
"step-1": "<mask token>\n",
"step-2": "def assert_number(arg):\n if not isinstance(arg, (int, float)):\n raise TypeError(f'Expected number, got {type(arg)}')\n",
"step-3": "def assert_number(arg):\n if not isinstance(arg, (in... | [
0,
1,
2
] |
#coding=utf-8
import unittest,time,os
from time import sleep
from appium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from HTMLTestRunner import HTMLTestRunner
from appium.webdriver.common.touch_action import TouchAction
from pub_Student import login,logout
# Returns ... | normal | {
"blob_id": "8d7697a0e49dc9e966b9657171c66ccda57279d6",
"index": 1930,
"step-1": "<mask token>\n\n\nclass TestStudent(unittest.TestCase):\n\n def setUp(self):\n desired_caps = {}\n desired_caps['platformName'] = 'Android'\n desired_caps['platformVersion'] = '7.0'\n desired_caps['au... | [
5,
6,
7,
8,
9
] |
#!/usr/bin/python2.7
import sys
import datetime
import psycopg2
import json
import collections
from pprint import pprint
from pyral import Rally, rallyWorkset
import copy
import os
import argparse
from ConfigParser import SafeConfigParser
import traceback
global rally
global server_name
"""
WARNING: This was hacked... | normal | {
"blob_id": "be0afa5184f753ed5f9a483379a4d81cd7af4886",
"index": 6845,
"step-1": "#!/usr/bin/python2.7\nimport sys\nimport datetime\nimport psycopg2\nimport json\nimport collections\nfrom pprint import pprint\nfrom pyral import Rally, rallyWorkset\nimport copy\nimport os\nimport argparse\nfrom ConfigParser impor... | [
0
] |
from vkaudiotoken import get_vk_official_token
import requests
import json
import telebot
import urllib
import sys
#check start args
try:
if len(sys.argv) != 4:
raise Exception
botApiKey = sys.argv[1]
login = sys.argv[2]
password = sys.argv[3]
except:
print('Not enough arguments')
pr... | normal | {
"blob_id": "47817d6cf58ac54e501ed24ae3ababc821bdd5c8",
"index": 1949,
"step-1": "<mask token>\n\n\ndef getTracks(result):\n data = json.loads(result.content.decode('utf-8'))\n tracks = data['response']['items']\n tracks.reverse()\n return tracks\n\n\ndef getMp3FromM3u8(url):\n if url.find('index.... | [
3,
4,
5,
6,
7
] |
from flask import Flask, render_template
from flask_sqlalchemy import SQLAlchemy
app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'mysql+mysqldb://sql3354595:7Haz6Ng1fm@sql3.freemysqlhosting.net/sql3354595'
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
app.config['SECRET_KEY'] = 'mysecret'
db = S... | normal | {
"blob_id": "d7240703bc4cf9b566e7b50a536c83497cd8c6d7",
"index": 7116,
"step-1": "<mask token>\n\n\nclass TipoUsuarios(db.Model):\n id = db.Column(db.Integer, primary_key=True, nullable=False)\n texto = db.Column(db.String(50))\n usuarios = db.relationship('Usuarios', backref='tipo', lazy='dynamic')\n\n... | [
7,
8,
10,
11,
12
] |
import numpy as np
from scipy.linalg import solve
from matplotlib import pylab as plt
def f(x):
return (np.sin(x / 5) * np.exp(x / 10) + 5 * np.exp(-x / 2))
xx = np.arange(1, 15, 0.1)
yy = f(xx)
# 1 степень
x = np.array([1,15])
y = f(x)
A = np.array([[1,1], [1,15]])
w = solve(A, y)
y1 = w[0] +... | normal | {
"blob_id": "a610ccf4fe154ee12de9212a10958fda2000b425",
"index": 7122,
"step-1": "<mask token>\n\n\ndef f(x):\n return np.sin(x / 5) * np.exp(x / 10) + 5 * np.exp(-x / 2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef f(x):\n return np.sin(x / 5) * np.exp(x / 10) + 5 * np.exp(-x / 2)\n\n\n<mask t... | [
1,
2,
3,
4,
5
] |
import serial
from settings import *
class CommunicationController:
def __init__(self):
global board
board = serial.Serial(ROBOT_SERIAL, BAUDRATE, serial.EIGHTBITS, timeout=0)
self.count = 0
print("Communication controller")
def sendCommand(self, right, back, left):
self... | normal | {
"blob_id": "48291ab3deb1ca1ba672d3e642d55635a7270171",
"index": 955,
"step-1": "<mask token>\n\n\nclass CommunicationController:\n <mask token>\n\n def sendCommand(self, right, back, left):\n self.count += 1\n if self.count >= BUFFER_RESET_BOUND:\n board.reset_output_buffer()\n ... | [
2,
3,
4,
5,
6
] |
version https://git-lfs.github.com/spec/v1
oid sha256:a2959c4cccf29b3797cc2e2dcef87ddb5a0779d9fb992bb38e190b791ae37eb0
size 88352
| normal | {
"blob_id": "932bb7c9dbf3e97c966d2d7d537e747756831e30",
"index": 608,
"step-1": "version https://git-lfs.github.com/spec/v1\noid sha256:a2959c4cccf29b3797cc2e2dcef87ddb5a0779d9fb992bb38e190b791ae37eb0\nsize 88352\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
... | [
0
] |
"""Those things that are core to tests.
This module provides the most fundamental test entities, which include such
things as:
- Tests
- Suites
- Test states
"""
from __future__ import print_function
__docformat__ = "restructuredtext"
import os
import textwrap
import time
import weakref
import inspect
from clevers... | normal | {
"blob_id": "cac9d84f20a79b115c84ff4fe8cf4640182a42d7",
"index": 754,
"step-1": "<mask token>\n\n\nclass Test(TestItem):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def abortRun(self):\n self._runHistory.pop()\n <m... | [
33,
64,
81,
104,
122
] |
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