code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
def convert_idx(text, tokens):
current = 0
spans = []
for token in tokens:
current = text.find(token, current)
if current < 0:
print('Token {} cannot be found'.format(token))
raise Exception()
spans.append((current, current + len... | flexible | {
"blob_id": "5cd9d4fe9889c4d53b50d86fa78ae84d0c242536",
"index": 3693,
"step-1": "<mask token>\n\n\ndef convert_idx(text, tokens):\n current = 0\n spans = []\n for token in tokens:\n current = text.find(token, current)\n if current < 0:\n print('Token {} cannot be found'.format(... | [
5,
6,
7,
8,
10
] |
#!/usr/bin/env python3
import numpy as np
from DMP.PIDMP import RLDMPs
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
np.random.seed(50)
dmp_y0 = np.array([-1.52017496, 0.04908739, 1.41433029])
dmp_goal = np.array([-1.50848603, 0.0591503 , 1.44347592])
load_file_name = "w_0_2_right_3... | normal | {
"blob_id": "5e6bbb10ec82e566c749dd4d794eabd2e8f7a648",
"index": 4488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.random.seed(50)\n<mask token>\nrl.load_weight(load_file_name)\n<mask token>\nprint(rl.w)\n<mask token>\nplt.scatter(x, track.y[0][:, 0], c='b', label='random')\nplt.scatter(x, track.y[... | [
0,
1,
2,
3,
4
] |
"""
======================
@author:小谢学测试
@time:2021/9/8:8:34
@email:xie7791@qq.com
======================
"""
import pytest
# @pytest.fixture()
# def login():
# print("登录方法")
# def pytest_conftest(config):
# marker_list = ["search","login"]
# for markers in marker_list:
# config.addinivalue_line("m... | normal | {
"blob_id": "b52429f936013ac60659950492b67078fabf3a13",
"index": 4042,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nimport pytest\n",
"step-3": "\"\"\"\n======================\n@author:小谢学测试\n@time:2021/9/8:8:34\n@email:xie7791@qq.com\n======================\n\"\"\"\nimport pytest\n# @pytest.fixture(... | [
0,
1,
2
] |
import vobject
import glob
import sys
vobj=vobject.readOne(open("Nelson.vcf"))
print vobj.contents
def main(args):
suma = 0
titulos = ['nombre del archivo', 'Total', 'subtotoal', 'rfc', 'fecha', 'ivaTrasladado', 'isrTrasladado', 'ivaRetenido', 'isrRetenido']
import csv
out = csv.writer(open("out.csv"... | normal | {
"blob_id": "a1115766c5f17abc1ba90a3314cb5b9c4aab73d6",
"index": 8169,
"step-1": "import vobject\nimport glob\nimport sys\n\nvobj=vobject.readOne(open(\"Nelson.vcf\"))\nprint vobj.contents\n\n\ndef main(args):\n suma = 0\n titulos = ['nombre del archivo', 'Total', 'subtotoal', 'rfc', 'fecha', 'ivaTrasladad... | [
0
] |
"""
==============================
Visualize Cylinder with Wrench
==============================
We apply a constant body-fixed wrench to a cylinder and integrate
acceleration to twist and exponential coordinates of transformation
to finally compute the new pose of the cylinder.
"""
import numpy as np
from pytransform... | normal | {
"blob_id": "2019a2a5588e57164ff4226ef3bcbbc506f2b315",
"index": 7432,
"step-1": "<mask token>\n\n\ndef animation_callback(step, cylinder, cylinder_frame, prev_cylinder2world,\n Stheta_dot, inertia_inv):\n if step == 0:\n prev_cylinder2world[:, :] = np.eye(4)\n Stheta_dot[:] = 0.0\n wrench... | [
1,
3,
4,
5,
6
] |
from functools import wraps
from flask import request, abort
# Apply Aspect Oriented Programming to server routes using roles
# e.g. we want to specify the role, perhaps supplied
# by the request or a jwt token, using a decorator
# to abstract away the authorization
# possible decorator implementation
def roles_requ... | normal | {
"blob_id": "1adaca88cf41d4e4d3a55996022278102887be07",
"index": 3707,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef roles_required(roles):\n\n def decorator(func):\n\n @wraps(func)\n def wrapper(*args, **kwargs):\n print(roles, 'required')\n print(args, kw... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def RangeExtender(filename, directory):
fileNC = nc.Dataset(directory + filename, 'r')
nu = fileNC['nu'][:]
filename, ext = os.path.splitext(filename)
fileOut = nc.Dataset(directory + filename + '_50000cm-1.nc', 'w')
nu_orig_length = len(nu)
step = abs(nu[1] - nu[0... | flexible | {
"blob_id": "f3527185117fd7205f55f47f2f08448a7d7b0100",
"index": 8143,
"step-1": "<mask token>\n\n\ndef RangeExtender(filename, directory):\n fileNC = nc.Dataset(directory + filename, 'r')\n nu = fileNC['nu'][:]\n filename, ext = os.path.splitext(filename)\n fileOut = nc.Dataset(directory + filename ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print(' sum of n numbers with help of for loop. ')
<|reserved_special_token_0|>
for num in range(0, n + 1, 1):
sum = sum + num
print('Output: SUM of first ', n, 'numbers is: ', sum)
print(' sum of n numbers with help of while loop. ')
<|reserved_special_t... | flexible | {
"blob_id": "d3c36ad36c50cd97f2101bc8df99d1961b0ad7ea",
"index": 4078,
"step-1": "<mask token>\n",
"step-2": "print(' sum of n numbers with help of for loop. ')\n<mask token>\nfor num in range(0, n + 1, 1):\n sum = sum + num\nprint('Output: SUM of first ', n, 'numbers is: ', sum)\nprint(' sum of n numbers w... | [
0,
1,
2,
3
] |
import math
def Distance(t1, t2):
RADIUS = 6371000. # earth's mean radius in km
p1 = [0, 0]
p2 = [0, 0]
p1[0] = t1[0] * math.pi / 180.
p1[1] = t1[1] * math.pi / 180.
p2[0] = t2[0] * math.pi / 180.
p2[1] = t2[1] * math.pi / 180.
d_lat = (p2[0] - p1[0])
d_lon = (p2[1] - p1[1])
... | normal | {
"blob_id": "f3f5b14917c89c5bc2866dd56e212bd3ec8af1cd",
"index": 4841,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef tile_number(lon_deg, lat_deg, zoom):\n n = 2.0 ** zoom\n xtile = int((lon_deg + 180.0) / 360.0 * n)\n ytile = int((lat_deg + 90.0) / 180.0 * n)\n return xtile, ytile\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def hello():
messagebox.showinfo('Say Hello', 'Hello World')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def hello():
messagebox.showinfo('Say Hello', 'Hello World')
<|reserved_special_token_0|>
B1.pack()
mainloop()
<|reserved_... | flexible | {
"blob_id": "61e38ae6ae2a1ed061f9893742f45b3e44f19a68",
"index": 6110,
"step-1": "<mask token>\n\n\ndef hello():\n messagebox.showinfo('Say Hello', 'Hello World')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef hello():\n messagebox.showinfo('Say Hello', 'Hello World')\n\n\n<mask token>\nB1.pack()... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .gunicorn import *
from .server_app import *
| flexible | {
"blob_id": "ed5dd954dedb00bf645f9ca14b5ca9cd122b2adc",
"index": 6183,
"step-1": "<mask token>\n",
"step-2": "from .gunicorn import *\nfrom .server_app import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
def test(x):
print x
| normal | {
"blob_id": "78e008b4a51cdbbb81dead7bc5945ee98ccad862",
"index": 8266,
"step-1": "def test(x):\n print x\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
rule run_all:
shell:
'''
echo 'Hello World!'
'''
| normal | {
"blob_id": "c967a63d03f9f836d97ae917dba2a7bfb7a54a0e",
"index": 9673,
"step-1": "rule run_all:\n shell:\n '''\n echo 'Hello World!'\n '''\n\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def lucky(ticket):
def sum_(number):
number = str(number)
while len(number) != 6:
number = '0' + number
x = list(map(int, number))
return sum(x[:3]) == sum(x[3:])
return 'Счастливый' if sum_(ticket) == sum_... | flexible | {
"blob_id": "85ac851e28dba3816f18fefb727001b8e396cc2b",
"index": 5278,
"step-1": "<mask token>\n",
"step-2": "def lucky(ticket):\n\n def sum_(number):\n number = str(number)\n while len(number) != 6:\n number = '0' + number\n x = list(map(int, number))\n return sum(x[:... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def console_check(csl, f):
if csl == 'playstation-4':
f.write('\tdbo:computingPlatform dbpedia:PlayStation_4.')
if csl == 'playstation-3':
f.write('\tdbo:computingPlatform dbpedia:PlayStation_3.')
if csl == 'playstation-2':
f.write('\tdbo:computingPlatf... | flexible | {
"blob_id": "b290763362af96f5af03fa31f4936339cef66a1d",
"index": 2062,
"step-1": "<mask token>\n\n\ndef console_check(csl, f):\n if csl == 'playstation-4':\n f.write('\\tdbo:computingPlatform dbpedia:PlayStation_4.')\n if csl == 'playstation-3':\n f.write('\\tdbo:computingPlatform dbpedia:Pla... | [
6,
7,
8,
9,
10
] |
# encoding: utf-8
'''
Created on Nov 26, 2015
@author: tal
Based in part on:
Learn math - https://github.com/fchollet/keras/blob/master/examples/addition_rnn.py
See https://medium.com/@majortal/deep-spelling-9ffef96a24f6#.2c9pu8nlm
"""
Modified by Pavel Surmenok
'''
import argparse
import numpy as np
from keras.l... | normal | {
"blob_id": "572a098053ebae4f42cd020d1003cc18eceb6af0",
"index": 4984,
"step-1": "<mask token>\n\n\ndef generate_model(output_len, chars=None):\n \"\"\"Generate the model\"\"\"\n print('Build model...')\n chars = chars or CHARS\n model = Sequential()\n for layer_number in range(INPUT_LAYERS):\n ... | [
6,
7,
8,
10,
12
] |
from ..scope_manager import ScopeManager
from ..span import Span
from ..tracer import Tracer
from .propagator import Propagator
class MockTracer(Tracer):
def __init__(self, scope_manager: ScopeManager | None = ...) -> None: ...
def register_propagator(self, format: str, propagator: Propagator) -> None: ...
... | normal | {
"blob_id": "76d2c80c673f9a0444e72721909a51479ff35521",
"index": 1785,
"step-1": "<mask token>\n\n\nclass MockTracer(Tracer):\n\n def __init__(self, scope_manager: (ScopeManager | None)=...) ->None:\n ...\n\n def register_propagator(self, format: str, propagator: Propagator) ->None:\n ...\n ... | [
3,
4,
5,
6,
7
] |
from timemachines.skatertools.testing.allregressiontests import REGRESSION_TESTS
import time
import random
TIMEOUT = 60*5
# Regression tests run occasionally to check various parts of hyper-param spaces, etc.
if __name__=='__main__':
start_time = time.time()
elapsed = time.time()-start_time
while elapsed ... | normal | {
"blob_id": "710bb0e0efc2c4a3ba9b1ae85e1c22e81f8ca68e",
"index": 7960,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n start_time = time.time()\n elapsed = time.time() - start_time\n while elapsed < TIMEOUT:\n a_test = random.choice(REGRESSION_TESTS)\n p... | [
0,
1,
2,
3,
4
] |
# coding=utf-8
"""SCALE UI: feature tests."""
import pytest
import xpaths
from function import (
wait_on_element,
is_element_present,
wait_on_element_disappear
)
from pytest_bdd import (
given,
scenario,
then,
when,
)
@pytest.mark.dependency(name='Set_Group')
@scenario('features/NAS-T1250... | normal | {
"blob_id": "f4aaf0449bff68814090552ea4f6ccac85dacf1b",
"index": 5617,
"step-1": "<mask token>\n\n\n@given('the browser is open, navigate to the SCALE URL, and login')\ndef the_browser_is_open_navigate_to_the_scale_url_and_login(driver, nas_ip,\n root_password):\n \"\"\"the browser is open, navigate to the... | [
3,
4,
5,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def sum_numbers(numbers=None):
sum = 0
if numbers == None:
for number in range(1, 101):
sum += number
return sum
for number in numbers:
sum += number
return sum
| flexible | {
"blob_id": "a85d06d72b053b0ef6cb6ec2ba465bfb8975b28e",
"index": 3879,
"step-1": "<mask token>\n",
"step-2": "def sum_numbers(numbers=None):\n sum = 0\n if numbers == None:\n for number in range(1, 101):\n sum += number\n return sum\n for number in numbers:\n sum += num... | [
0,
1
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
created by gjwei on 3/26/17
"""
class ListNode(object):
def __init__(self, x):
self.val = x
self.next = None
a = ListNode(1)
a.next = ListNode(3)
a.next = None
print a.val
print a.next
def main():
print "hello"
a = []
for i in r... | normal | {
"blob_id": "4a0cbd59ffae4fb5ba6e3bd871231e37065d1aed",
"index": 3464,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\" \n created by gjwei on 3/26/17\n \n\"\"\"\nclass ListNode(object):\n def __init__(self, x):\n self.val = x\n self.next = None\n\n\na = ListNode(1)\na.next = L... | [
0
] |
# -*- coding: utf-8 -*-
# @time : 2021/1/10 10:25
# @Author : Owen
# @File : mainpage.py
from selenium.webdriver.common.by import By
from homework.weixin.core.base import Base
from homework.weixin.core.contact import Contact
'''
企业微信首页
'''
class MainPage(Base):
#跳转到联系人页面
def goto_contact(self):
... | normal | {
"blob_id": "7775d260f0db06fad374d9f900b03d8dbcc00762",
"index": 6504,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass MainPage(Base):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass MainPage(Base):\n\n def goto_contact(self):\n self.find(By.CSS_SELECTOR, '#menu_contacts').c... | [
0,
1,
2,
3,
4
] |
print(60 * 60)
seconds_per_hour = 60 * 60
print(24 * seconds_per_hour)
seconds_per_day = 24 * seconds_per_hour
print(seconds_per_day / seconds_per_hour)
print(seconds_per_day // seconds_per_hour)
| normal | {
"blob_id": "358879d83ed3058530031d50fb69e3ce11fbd524",
"index": 1057,
"step-1": "<mask token>\n",
"step-2": "print(60 * 60)\n<mask token>\nprint(24 * seconds_per_hour)\n<mask token>\nprint(seconds_per_day / seconds_per_hour)\nprint(seconds_per_day // seconds_per_hour)\n",
"step-3": "print(60 * 60)\nseconds_... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
MyScheduler = Scheduler()
<|reserved_special_token_1|>
from .scheduler import Scheduler
MyScheduler = Scheduler()
| flexible | {
"blob_id": "d472a15d6fa826e50a550996369b00b6c599a1c7",
"index": 5401,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nMyScheduler = Scheduler()\n",
"step-3": "from .scheduler import Scheduler\nMyScheduler = Scheduler()\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
# PySNMP SMI module. Autogenerated from smidump -f python DS0BUNDLE-MIB
# by libsmi2pysnmp-0.1.3 at Thu May 22 11:57:37 2014,
# Python version sys.version_info(major=2, minor=7, micro=2, releaselevel='final', serial=0)
# Imports
( Integer, ObjectIdentifier, OctetString, ) = mibBuilder.importSymbols("ASN1", "Integer",... | normal | {
"blob_id": "fab15d34d29301e53a26577725cdd66dca7507bc",
"index": 2330,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif mibBuilder.loadTexts:\n ds0Bundle.setOrganization('IETF Trunk MIB Working Group')\nif mibBuilder.loadTexts:\n ds0Bundle.setContactInfo(\n \"\"\" David Fowler\n\nPos... | [
0,
1,
2,
3
] |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForestClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import c... | normal | {
"blob_id": "84db1803a352e0ed8c01b7166f522d46ec89b6f5",
"index": 2487,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor train_index, test_index in kf.split(x):\n xtr = x.iloc[train_index]\n ytr = y[train_index]\n<mask token>\nif k % 2 == 0:\n k = k + 1\nelse:\n k = k\n<mask token>\nprint('S... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class TestURLs:
def test_url_1(self):
assert is_url('http://heise.de')
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def test_valid_url_https_path(self):
assert is_url('https://heise.de/thi_s&is=difficult')
... | flexible | {
"blob_id": "021f224d031477bd305644261ad4d79d9eca98b3",
"index": 5474,
"step-1": "<mask token>\n\n\nclass TestURLs:\n\n def test_url_1(self):\n assert is_url('http://heise.de')\n <mask token>\n <mask token>\n <mask token>\n\n def test_valid_url_https_path(self):\n assert is_url('http... | [
3,
4,
7,
8,
10
] |
# encoding: utf-8
# -*- coding: utf-8 -*-
"""
The flask application package.
"""
#parse arguments
from flask import Flask
from flask_cors import CORS
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-t', '--testing', action='store_true') #to use the testing database
parser.add_argument('-i', ... | normal | {
"blob_id": "e403a84ec2a3104cb908933f6949458cccc791c3",
"index": 4737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('-t', '--testing', action='store_true')\nparser.add_argument('-i', '--init', action='store_true')\nparser.add_argument('-r', '--reinit', action='store_true')\n<mask to... | [
0,
1,
2,
3,
4
] |
#Importacion de Dependencias Flask
from flask import Blueprint,Flask, render_template, request,redirect,url_for,flash
#modelado de basedato.
from App import db
# Importacion de modulo de ModeloCliente
from App.Modulos.Proveedor.model import Proveedor
#Inportacion de modulo de formularioCliente
from App.Modulos.Proveedo... | normal | {
"blob_id": "99ecb927e22bc303dd9dffd2793887e7398dbb83",
"index": 3649,
"step-1": "<mask token>\n\n\n@_Proveedor.route('/Proveedor', methods=['GET', 'POST'])\ndef proveedor():\n frm = form.Fr_Proveedor(request.form)\n if request.method == 'POST':\n pr = Proveedor.query.filter_by(CI=frm.CI.data).first... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class PersonInfo(scrapy.Item):
person_id = scrapy.Field()
buy_car = scrapy.Field()
address = scrapy.Field()
class OtherItem(scrapy.Item):
"""
可以定义另外一个item
"""
user_info = scrapy.Field()
main_url = scrapy.Field()
nick_name = scrapy.Field()
... | flexible | {
"blob_id": "9dbadb2421b04961e8e813831d06abc1ff301566",
"index": 3283,
"step-1": "<mask token>\n\n\nclass PersonInfo(scrapy.Item):\n person_id = scrapy.Field()\n buy_car = scrapy.Field()\n address = scrapy.Field()\n\n\nclass OtherItem(scrapy.Item):\n \"\"\"\n 可以定义另外一个item\n \"\"\"\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('RUNNING ON CPU')
<|reserved_special_token_0|>
assert config.changePrice == True
print(config.config)
<|reserved_special_token_0|>
for t in range(993, 4592):
broker, totalOrders = broker_funcs.thresholdBrokerage(traderIDs, t,
broker, totalOr... | flexible | {
"blob_id": "21aee78e8cbb1ca150bca880e79dc0d84326e2d4",
"index": 4162,
"step-1": "<mask token>\n",
"step-2": "print('RUNNING ON CPU')\n<mask token>\nassert config.changePrice == True\nprint(config.config)\n<mask token>\nfor t in range(993, 4592):\n broker, totalOrders = broker_funcs.thresholdBrokerage(trade... | [
0,
1,
2,
3,
4
] |
import urllib.request
from bs4 import BeautifulSoup
def getTitlesFromAll(amount, rating='all'):
output = ''
for i in range(1, amount+1):
try:
if rating == 'all':
html = urllib.request.urlopen('https://habr.com/all/page'+ str(i) +'/').read()
else:
... | normal | {
"blob_id": "d6cfea95c76021bdbfbb4471878c653564c9accd",
"index": 1816,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getTitlesFromAll(amount, rating='all'):\n output = ''\n for i in range(1, amount + 1):\n try:\n if rating == 'all':\n html = urllib.request.... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def AnalyzeFrames(vidpath):
print('\nGetting video info & writing out image files for each frame...\n')
vidObj = cv2.VideoCapture(vidpath)
fps = vidObj.get(cv2.CAP_PROP_FPS)
print('Frames per second: {0}\n'.format(fps))
count = 0
jpeglist = []
success = 1
w... | flexible | {
"blob_id": "d70d3d8eef711441ac89c2d98c72a5f95e0ab20d",
"index": 5261,
"step-1": "<mask token>\n\n\ndef AnalyzeFrames(vidpath):\n print('\\nGetting video info & writing out image files for each frame...\\n')\n vidObj = cv2.VideoCapture(vidpath)\n fps = vidObj.get(cv2.CAP_PROP_FPS)\n print('Frames per... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.insert(0, os.path.dirname(__file__))
<|reserved_special_token_0|>
for volume, frequency in notes:
samples = square_wave(int(44100 / frequency // 2))
samples = gain(samples, volume)
samples = repeat(samples, qu... | flexible | {
"blob_id": "4fb563985bd99599e88676e167ee84a95b018aba",
"index": 5414,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, os.path.dirname(__file__))\n<mask token>\nfor volume, frequency in notes:\n samples = square_wave(int(44100 / frequency // 2))\n samples = gain(samples, volume)\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Postfix:
def __init__(self, regex):
self.__regex = regex.expression
self.__modr = Postfix.modRegex(self.__regex)
self.__pila = Stack()
self.__postfix = self.convertInfixToPostfix()
<|reserved_special_token_0|>
<|reserved_special_token_0|>... | flexible | {
"blob_id": "acc39044fa1ae444dd4a737ea37a0baa60a2c7bd",
"index": 4040,
"step-1": "<mask token>\n\n\nclass Postfix:\n\n def __init__(self, regex):\n self.__regex = regex.expression\n self.__modr = Postfix.modRegex(self.__regex)\n self.__pila = Stack()\n self.__postfix = self.convert... | [
4,
5,
7,
9,
11
] |
""" A set of constants to describe the package.
Don't put any code in here, because it must be safe to execute in setup.py. """
__title__ = 'space_tracer' # => name in setup.py
__version__ = '4.10.2'
__author__ = "Don Kirkby"
__author_email__ = "donkirkby@gmail.com"
__description__ = "Trade time for space when debug... | normal | {
"blob_id": "6cb29ebd9c0f2660d0eb868bec87ffd97cf4d198",
"index": 6262,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__title__ = 'space_tracer'\n__version__ = '4.10.2'\n__author__ = 'Don Kirkby'\n__author_email__ = 'donkirkby@gmail.com'\n__description__ = 'Trade time for space when debugging your code.'... | [
0,
1,
2
] |
class Coms:
def __init__(self, name, addr, coord):
self.name = name
self.addr = addr
self.coord = coord
def getString(self):
return "회사명\n"+self.name+"\n\n주소\n"+self.addr
def getTeleString(self):
return "회사명 : " + self.name + ", 주소 : " + self.addr
class Jobs:
d... | normal | {
"blob_id": "bcc24d5f97e46433acb8bcfb08fe582f51eb28ce",
"index": 2932,
"step-1": "<mask token>\n\n\nclass Jobs:\n\n def __init__(self, name, type, experience, education, keyword, salary,\n url, start, end):\n self.name = name\n self.type = type\n self.experience = experience\n ... | [
4,
5,
6,
7,
9
] |
import pandas as pd
from fbprophet import Prophet
import os
from utils.json_utils import read_json, write_json
from sklearn.model_selection import train_test_split
import numpy as np
from sklearn.metrics import mean_absolute_error
root_dir = "/home/charan/Documents/workspaces/python_workspaces/Data/ADL_Project/"
final... | normal | {
"blob_id": "25dd7ea4a154e5693c65f8c42107224efee42516",
"index": 4533,
"step-1": "<mask token>\n\n\ndef mean_absolute_percentage_error(y_true, y_pred):\n y_true, y_pred = np.array(y_true), np.array(y_pred)\n return np.mean(np.abs((y_true - y_pred) / y_true)) * 100\n\n\n<mask token>\n",
"step-2": "<mask t... | [
1,
2,
3,
4,
5
] |
from microbit import *
import speech
while True:
speech.say("I am a DALEK - EXTERMINATE", speed=120, pitch=100, throat=100, mouth=200) #kokeile muuttaa parametrejä
| normal | {
"blob_id": "dad78d7948fb1038f9cf66732f39c18a18f2a3c8",
"index": 5233,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n speech.say('I am a DALEK - EXTERMINATE', speed=120, pitch=100, throat=\n 100, mouth=200)\n",
"step-3": "from microbit import *\nimport speech\nwhile True:\n s... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 20 17:13:46 2017
@author: pmonnot
"""
import blpapi
import datetime
# Create a Session
session = blpapi.Session()
# Start a Session
if not session.start():
print "Failed to start session."
if not session.openService("//blp/refdata"):
print "Faile... | normal | {
"blob_id": "a8a2d672369f61c6412229380cc6097d152ba126",
"index": 9883,
"step-1": "# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Feb 20 17:13:46 2017\r\n\r\n@author: pmonnot\r\n\"\"\"\r\n\r\nimport blpapi\r\nimport datetime\r\n\r\n# Create a Session\r\nsession = blpapi.Session()\r\n# Start a Session\r\nif n... | [
0
] |
print ("Hello Workls!")
| normal | {
"blob_id": "c52d1c187edb17e85a8e2b47aa6731bc9a41ab1b",
"index": 561,
"step-1": "<mask token>\n",
"step-2": "print('Hello Workls!')\n",
"step-3": "print (\"Hello Workls!\")\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_pixel_pixelMatchesColor():
"""屏幕像素获取、屏幕像素匹配"""
print(pixelMatchesColor(44, 107, (148, 212, 234), tolerance=20))
print(pixelMatchesColor(44, 107, (100, 212, 234), tolerance=20))
<|reserved_special_token_0|>... | flexible | {
"blob_id": "c15faf9df8fa2e1ad89ea2c922ab0551eaa69d3f",
"index": 1936,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_pixel_pixelMatchesColor():\n \"\"\"屏幕像素获取、屏幕像素匹配\"\"\"\n print(pixelMatchesColor(44, 107, (148, 212, 234), tolerance=20))\n print(pixelMatchesColor(44, 107, (100, 21... | [
0,
1,
2,
3,
4
] |
#dict1 = {"я":"i","люблю":"love","Питон":"Рython"}
#user_input = input("---->")
#print(dict1[user_input])
#list1 =[i for i in range(0,101) if i%7 ==0 if i%5 !=0]
#print(list1)
#stroka = "я обычная строка быть которая должна быть длиннее чем десять символ"
#stroka1=stroka.split()
#dict1={}
#for i in stroka1:
# ... | normal | {
"blob_id": "c0512a90b6a4e50c41d630f6853d1244f78debfb",
"index": 4350,
"step-1": "#dict1 = {\"я\":\"i\",\"люблю\":\"love\",\"Питон\":\"Рython\"}\n#user_input = input(\"---->\")\n#print(dict1[user_input])\n\n\n#list1 =[i for i in range(0,101) if i%7 ==0 if i%5 !=0]\n#print(list1)\n\n\n\n#stroka = \"я обычная стро... | [
1
] |
<|reserved_special_token_0|>
def get_links_from_markdown(path, name):
try:
with open(path, 'r') as file:
md = file.read()
html = markdown.markdown(md)
soup = BeautifulSoup(html, 'html.parser')
return soup.find_all('a')
except PermissionError:
pri... | flexible | {
"blob_id": "274185896ab5c11256d69699df69fc2c0dde4f2d",
"index": 987,
"step-1": "<mask token>\n\n\ndef get_links_from_markdown(path, name):\n try:\n with open(path, 'r') as file:\n md = file.read()\n html = markdown.markdown(md)\n soup = BeautifulSoup(html, 'html.parser... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ceis_arquivo.reset_index()
ceis_arquivo.info()
<|reserved_special_token_0|>
ceis_sp.to_csv('ceis_sp.csv')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ceis_arquivo = pd.read_csv('20180225_CEIS.csv', sep=';', encodi... | flexible | {
"blob_id": "d2325b07d11e64df0b26d0de9992a6f496e92a30",
"index": 2879,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nceis_arquivo.reset_index()\nceis_arquivo.info()\n<mask token>\nceis_sp.to_csv('ceis_sp.csv')\n",
"step-3": "<mask token>\nceis_arquivo = pd.read_csv('20180225_CEIS.csv', sep=';', encodi... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
ii = [('CoolWHM.py', 1), ('SoutRD.py', 1), ('BrewDTO.py', 2), (
'FitzRNS2.py', 1), ('LyelCPG3.py', 1), ('TaylIF.py', 2)]
| flexible | {
"blob_id": "fbba928d51ccd08dbac25fcf2098be3a0d494d34",
"index": 6659,
"step-1": "<mask token>\n",
"step-2": "ii = [('CoolWHM.py', 1), ('SoutRD.py', 1), ('BrewDTO.py', 2), (\n 'FitzRNS2.py', 1), ('LyelCPG3.py', 1), ('TaylIF.py', 2)]\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0,
1
] |
#
# @lc app=leetcode.cn id=784 lang=python3
#
# [784] 字母大小写全排列
#
# @lc code=start
# 回溯法 --> 通过 64 ms 13.5 MB
class Solution:
def __init__(self):
self.result = []
def letterCasePermutation(self, S: str) -> List[str]:
arr = list(S)
self.backtracing(arr, 0)
return self.result
... | normal | {
"blob_id": "632c690261b31c7ac0e1d90c814e3b9a7a0dcb29",
"index": 7663,
"step-1": "class Solution:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class Solution:\n <mask token>\n <mask token>\n\n def backtracing(self, arr, start):\n if start == len(arr):\n self.r... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class System:
<|reserved_special_token_0|>
def bind_manager(self, manager):
self.manager = manager
<|reserved_special_token_0|>
def process(self, entity, deltaTime):
pass
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def update_en... | flexible | {
"blob_id": "14f7f31fa64799cdc08b1363b945da50841d16b5",
"index": 3020,
"step-1": "<mask token>\n\n\nclass System:\n <mask token>\n\n def bind_manager(self, manager):\n self.manager = manager\n <mask token>\n\n def process(self, entity, deltaTime):\n pass\n <mask token>\n <mask tok... | [
13,
14,
17,
18,
24
] |
<|reserved_special_token_0|>
def bar():
print('Explicit context to bar')
gevent.sleep(0)
print('Implicit contenxt switch back to bar')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def foo():
print('Running in foo')
gevent.sleep(0)
print('Explici... | flexible | {
"blob_id": "7f131e17f4fbd7d6b333a51dae557ddb07c30046",
"index": 9077,
"step-1": "<mask token>\n\n\ndef bar():\n print('Explicit context to bar')\n gevent.sleep(0)\n print('Implicit contenxt switch back to bar')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef foo():\n print('Running in foo')... | [
1,
2,
3,
4,
5
] |
cijferICOR = float(input('Wat is je cijfer voor ICOR?: '))
x = 30
beloningICOR = cijferICOR * x
beloning = 'beloning €'
print(beloning, beloningICOR)
cijferPROG = float(input('Wat is je cijfer voor PROG: '))
beloningPROG = cijferPROG * x
print(beloning, beloningPROG)
cijferCSN = float(input('Wat is je cijfer voor CSN?:... | normal | {
"blob_id": "74bca94cbcba0851e13d855c02fbc13fb0b09e6a",
"index": 4263,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(beloning, beloningICOR)\n<mask token>\nprint(beloning, beloningPROG)\n<mask token>\nprint(beloning, beloningCSN)\n<mask token>\nprint('de gemiddelde beloning is:€ ', gemiddelde / 3)... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
"""
Created on Sat Sep 29 19:10:06 2018
@author: labuser
"""
# 2018-09-29
import os
import numpy as np
from scipy.stats import cauchy
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
import pandas as pd
def limit_scan(fname, ax):
data = pd.read_csv(fname, sep='\t', ... | normal | {
"blob_id": "aee8fa7bc1426945d61421fc72732e43ddadafa1",
"index": 3191,
"step-1": "<mask token>\n\n\ndef cauchy_model(x, a, loc, scale, y0):\n return a * cauchy.pdf(x, loc, scale) + y0\n\n\ndef cauchy_fit(x, y, d):\n if d is -1:\n a0 = -(max(y) - min(y)) * (max(x) - min(x)) / 10\n loc0 = x[np.... | [
4,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def PrintaLog(texto):
t = time.time()
logtime = time.ctime(t)
stringprint = '%s %s\n' % (logtime, texto)
f = open('/var/log/patriot', 'a')
f.write(stringprint)
f.flush()
f.close()
def PrintaMSG(texto):
command = 'python3 alertiqt.py "' + texto + '"'
p... | flexible | {
"blob_id": "fde62dd3f5ee3cc0a1568b037ada14835c327046",
"index": 6298,
"step-1": "<mask token>\n\n\ndef PrintaLog(texto):\n t = time.time()\n logtime = time.ctime(t)\n stringprint = '%s %s\\n' % (logtime, texto)\n f = open('/var/log/patriot', 'a')\n f.write(stringprint)\n f.flush()\n f.close... | [
4,
6,
9,
10,
11
] |
import json
import glob
import sys
searchAreaName = sys.argv[1]
# searchAreaName = "slovenia_177sqkm_shards/20161220-162010-c9e0/slovenia_177sqkm_predicted/predict_slovenia_177sqkm_shard"
print('./{0}_??.txt'.format(searchAreaName))
all_predicts = glob.glob('./{0}_??.txt'.format(searchAreaName))
def getBboxes(bboxes):... | normal | {
"blob_id": "8f9d823785d42d02a0a3d901d66b46a5cd59cdd7",
"index": 7465,
"step-1": "<mask token>\n\n\ndef getBboxes(bboxes):\n return [bb for bb in bboxes if sum(bb) > 0.0]\n\n\n<mask token>\n",
"step-2": "<mask token>\nprint('./{0}_??.txt'.format(searchAreaName))\n<mask token>\n\n\ndef getBboxes(bboxes):\n ... | [
1,
2,
3,
4,
5
] |
<|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": "ac664cd7d62f89399e37f74e0234b3ad244fe460",
"index": 6158,
"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 = [('tutorials',... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def tm():
for i in range(3):
print(time.ctime())
time.sleep(2)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def tm():
for i in range(3):
print(time.ctime())
time.sleep(2)
<|reserved_special_token_0|... | flexible | {
"blob_id": "9d7bc2d93b855fbd22a4707a6237ac51069beb53",
"index": 9385,
"step-1": "<mask token>\n\n\ndef tm():\n for i in range(3):\n print(time.ctime())\n time.sleep(2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef tm():\n for i in range(3):\n print(time.ctime())\n ti... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def max_digit(number: int) ->int:
return max(int(i) for i in str(number))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def max_digit(number: int) ->int:
return max(int(i) ... | flexible | {
"blob_id": "b25e9374458ead85535495e77a5c64117a8b1808",
"index": 5761,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef max_digit(number: int) ->int:\n return max(int(i) for i in str(number))\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef max_digit(number: int) ->int:\n return max(i... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def notify_no_new_mapping_found():
email_str = """
<p>Python script does not find any new creative names from keepingtrac data.
Stage 2 of processing RenTrak data will begin when we load new data to RenTrak tables.
</p>
<p><b>No further action on your p... | flexible | {
"blob_id": "71c6d5e385e3db8444d7ef8b0231e72db8538eb7",
"index": 8106,
"step-1": "<mask token>\n\n\ndef notify_no_new_mapping_found():\n email_str = \"\"\"\n <p>Python script does not find any new creative names from keepingtrac data.\n Stage 2 of processing RenTrak data will begin when we load ... | [
4,
6,
7,
8,
10
] |
from whylogs.core.annotation_profiling import Rectangle
def test_rect():
rect = Rectangle([[0, 0], [10, 10]], confidence=0.8, labels=[{"name": "test"}])
test = Rectangle([[0, 0], [5, 5]])
assert rect.area == 100
assert rect.intersection(test) == 25
assert rect.iou(test) == 25 / 100.0
def test_r... | normal | {
"blob_id": "b65d25198d55ab4a859b9718b7b225fa92c13a2b",
"index": 1202,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_rect():\n rect = Rectangle([[0, 0], [10, 10]], confidence=0.8, labels=[{'name':\n 'test'}])\n test = Rectangle([[0, 0], [5, 5]])\n assert rect.area == 100\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
logger.setLevel(logging.DEBUG)
<|reserved_special_token_0|>
model.fit(X=train, eval_data=val, batch_end_callback=mx.callback.
Speedometer(batch_size, 50), epoch_end_callback=mx.callback.
do_checkpoint(model_prefix))
<|re... | flexible | {
"blob_id": "e82b9aa0f7dc669b3d5622c093b766c7e168221c",
"index": 5757,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlogger.setLevel(logging.DEBUG)\n<mask token>\nmodel.fit(X=train, eval_data=val, batch_end_callback=mx.callback.\n Speedometer(batch_size, 50), epoch_end_callback=mx.callback.\n do_c... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
class Vertex():
def __init__(self, key):
self.id = key
self.connections = {}
def add_neighbor(self, nbr, weight=0):
self.connections[nbr] = weight
def get_connections(self):
return self.connections.keys()
def get_id(sel... | normal | {
"blob_id": "3af78dcc0bb0b6f253af01d2945ad6ada02ca7a0",
"index": 7270,
"step-1": "class Vertex:\n <mask token>\n <mask token>\n\n def get_connections(self):\n return self.connections.keys()\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Graph:\n\n def __init__(self):\n ... | [
10,
12,
13,
15,
17
] |
from pytube import YouTube, Playlist
import json
import sys
import os
import urllib.request
p = os.path.abspath('appdata')
def collect(yt, dir):
code = yt.thumbnail_url
urllib.request.urlretrieve(code, os.path.join(dir, yt.title + '.jpg'))
out = yt.streams.filter(only_audio=True, file_extension='mp4').ord... | normal | {
"blob_id": "06dd963b62c0a746438dcf01c67ef5de1a4c5e8f",
"index": 1558,
"step-1": "<mask token>\n\n\ndef collect(yt, dir):\n code = yt.thumbnail_url\n urllib.request.urlretrieve(code, os.path.join(dir, yt.title + '.jpg'))\n out = yt.streams.filter(only_audio=True, file_extension='mp4').order_by(\n ... | [
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.insert(0, '.')
<|reserved_special_token_1|>
import sys
sys.path.insert(0, '.')
<|reserved_special_token_1|>
import sys
sys.path.insert(0, ".") | flexible | {
"blob_id": "b95eadd60093d5235dc0989205edff54ef611215",
"index": 2399,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, '.')\n",
"step-3": "import sys\nsys.path.insert(0, '.')\n",
"step-4": "\nimport sys\n\nsys.path.insert(0, \".\")",
"step-5": null,
"step-ids": [
0,
1,
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class CRUD(models.Model):
user = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.CASCADE
)
name = models.TextField(blank=True, null=True)
content = models.TextField(blank=True, null=True)
image = models.ImageField(upload_to=upload_updated_image, null=T... | flexible | {
"blob_id": "5749f30d1a1efd5404654d755bca4515adcf4bca",
"index": 1810,
"step-1": "<mask token>\n\n\nclass CRUD(models.Model):\n user = models.ForeignKey(settings.AUTH_USER_MODEL, on_delete=models.CASCADE\n )\n name = models.TextField(blank=True, null=True)\n content = models.TextField(blank=True,... | [
4,
8,
9,
10,
11
] |
import wizard
import report
| normal | {
"blob_id": "9d07fd14825ed1e0210fa1f404939f68a3bb039c",
"index": 4762,
"step-1": "<mask token>\n",
"step-2": "import wizard\nimport report\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Plugin_OBJ:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Plugin_OBJ:
def __init__(self, fhdhr, plugin_utils):
self.fhdhr = fhdhr
self.plugin_uti... | flexible | {
"blob_id": "ee0cf2325c94821fa9f5115e8848c71143eabdbf",
"index": 4775,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Plugin_OBJ:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Plugin_OBJ:\n\n def __init__(self, fhdhr, plugin_utils):\n self.fhdhr = fhdhr\n self.plug... | [
0,
1,
2,
3,
4
] |
import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from azavg_util import plot_azav
from binormalized_cbar import MidpointNormalize
from diagnostic_reading import ReferenceState
dirname = sys.argv[1]
datadir = dirname + '/data/'
plotdir = dirname + '/plots/'
if (not os.path.isdir(plotdir)):
... | normal | {
"blob_id": "e5c30488c8c1682171c57a11a8ecedc5ccd4d851",
"index": 5607,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif not os.path.isdir(plotdir):\n os.makedirs(plotdir)\n<mask token>\nplot_azav(fig, ax, ro_m, rr, cost, sint, contours=False, notfloat=False,\n units='')\nplt.title('$({\\\\rm{Ro}}_... | [
0,
1,
2,
3,
4
] |
from import_.Import import Import
from classifier.Classifier import Classifier
from export.Export import Export
from preprocessing.PreProcess import PreProcess
def main():
date_column = "date of last vet visit"
target = "age at death"
export_file_dir = "./output/"
export_model_dir = "./model/xgb_mode... | normal | {
"blob_id": "696b9db78cc7f6002eb39b640e0e5b2b53e52e91",
"index": 8448,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n date_column = 'date of last vet visit'\n target = 'age at death'\n export_file_dir = './output/'\n export_model_dir = './model/xgb_model.dat'\n import_ = ... | [
0,
1,
2,
3,
4
] |
from microbit import *
import radio
radio.on()
# receiver will show the distance to the beacon
# the number of receivers should be easily adjustable
while True:
message=radio.receive_full()
# the stronger the signal the higher the number
if message:
strength = message[1]+100
displaystrength... | normal | {
"blob_id": "dffa5e2f34788c6f5a5ccc7d8375317a830288b5",
"index": 7994,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nradio.on()\nwhile True:\n message = radio.receive_full()\n if message:\n strength = message[1] + 100\n displaystrength = int(strength / 10 + 1)\n display.show(s... | [
0,
1,
2,
3
] |
from prediction_model import PredictionModel
import util.nlp as nlp
import re
class NLPPredictionModel(object):
def getPasswordProbabilities(self, sweetwordList):
# can not deal with sweetword that contains no letters
result = []
for s in sweetwordList:
words = re.findall(r"[... | normal | {
"blob_id": "1c01fbf7eafd49ada71cb018a62ead5988dcf251",
"index": 2968,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass NLPPredictionModel(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass NLPPredictionModel(object):\n\n def getPasswordProbabilities(self, sweetwordList):\n ... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
Created on Tue Jul 18 13:39:05 2017
@author: jaredhaeme15
"""
import cv2
import numpy as np
from collections import deque
import imutils
import misc_image_tools
frameFileName = r"H:\Summer Research 2017\Whirligig Beetle pictures and videos\large1.mp4"
cap = cv2.VideoCapture(r"H:\Summer ... | normal | {
"blob_id": "5ccfad17ede9f685ea9ef9c514c0108a61c2dfd6",
"index": 8699,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile 1:\n successFlag, frame = cap.read()\n if not successFlag:\n cv2.waitKey(0)\n break\n lower_hsv_thresholdcr = np.array([0, 250, 250])\n upper_hsv_threshold... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
COPY_GOOGLE_DOC_KEY = '1CdafeVmmtNa_PMV99TapPHvLUVzYz0xkvHcpINQtQ6c'
DEPLOY_SLUG = 'al-qassemi'
NUM_SLIDES_AFTER_CONTENT = 2
AUDIO = True
VIDEO = False
FILMSTRIP = False
PROGRESS_BAR = False
<|reserved_special_token_1|>
COPY_GOOGLE_DOC_KEY = '1CdafeVmmtNa_... | flexible | {
"blob_id": "f398b724fc28bc25ddb8baf492f34075db0c1f61",
"index": 7703,
"step-1": "<mask token>\n",
"step-2": "COPY_GOOGLE_DOC_KEY = '1CdafeVmmtNa_PMV99TapPHvLUVzYz0xkvHcpINQtQ6c'\nDEPLOY_SLUG = 'al-qassemi'\nNUM_SLIDES_AFTER_CONTENT = 2\nAUDIO = True\nVIDEO = False\nFILMSTRIP = False\nPROGRESS_BAR = False\n",
... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def on_connect(client, userdata, flags, rc):
"""0: Connection successful
1: Connection refused - incorrect protocol version
2: Connection refused - invalid client identifier
3: Connection refused - server unavailable
4: Connection refused - bad username or password
... | flexible | {
"blob_id": "f3664f5f69207c3f2dcec96c90cd220003da0904",
"index": 4142,
"step-1": "<mask token>\n\n\ndef on_connect(client, userdata, flags, rc):\n \"\"\"0: Connection successful\n 1: Connection refused - incorrect protocol version\n 2: Connection refused - invalid client identifier\n 3: Connection re... | [
2,
3,
5,
6,
7
] |
<|reserved_special_token_0|>
@gapit_test('vkCmdCopyQueryPoolResults_test')
class FifthToEighthQueryResultsIn64BitWithWaitBitCopyWithZeroOffsets(GapitTest
):
<|reserved_special_token_0|>
@gapit_test('vkCmdCopyQueryPoolResults_test')
class AllFourQueryResultsIn32BitAnd12StrideWithPartialAndAvailabilityBitWith... | flexible | {
"blob_id": "c2f6fa4d9a6e2ee5f0593bef775ce8f811225613",
"index": 2047,
"step-1": "<mask token>\n\n\n@gapit_test('vkCmdCopyQueryPoolResults_test')\nclass FifthToEighthQueryResultsIn64BitWithWaitBitCopyWithZeroOffsets(GapitTest\n ):\n <mask token>\n\n\n@gapit_test('vkCmdCopyQueryPoolResults_test')\nclass All... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
PROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))
EMOTICONS = {'O:)': 'angel', 'o:)': 'angel', 'O:-)': 'angel', 'o:-)':
'angel', 'o:-3': 'angel', 'o:3': 'angel', 'O;^)': 'angel', '>:[':
'annoyed/disappointed', ':-(... | flexible | {
"blob_id": "3f3ed0165120dc135a4ce1f282dbdf9dad57adf8",
"index": 980,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nPROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))\nEMOTICONS = {'O:)': 'angel', 'o:)': 'angel', 'O:-)': 'angel', 'o:-)':\n 'angel', 'o:-3': 'angel', 'o:3': 'angel', 'O;^)': 'ang... | [
0,
1,
2,
3
] |
<|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": "b6a0a49e05fbc0ac7673d6c9e8ca4d263c8bb5cd",
"index": 7132,
"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 = [('service', '... | [
0,
1,
2,
3,
4
] |
import utils
from problems_2019 import intcode
def run(commands=None):
memory = utils.get_input()[0]
initial_inputs = intcode.commands_to_input(commands or [])
program = intcode.Program(memory, initial_inputs=initial_inputs, output_mode=intcode.OutputMode.BUFFER)
while True:
_, return_signal... | normal | {
"blob_id": "e3aa38b5d01823ed27bca65331e9c7315238750a",
"index": 8974,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@utils.part\ndef part_1():\n commands = ['south', 'take food ration', 'west', 'north', 'north',\n 'east', 'take astrolabe', 'west', 'south', 'south', 'east', 'north',\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(tp + (4,))
<|reserved_special_token_1|>
tp = 1, 2, 3
print(tp + (4,))
| flexible | {
"blob_id": "8e9db58488f6ee8aa0d521a19d9d89504d119076",
"index": 6689,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(tp + (4,))\n",
"step-3": "tp = 1, 2, 3\nprint(tp + (4,))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class TFCompile(TFLayer):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class TFComModel(TFModel, TFCompile):
"""
基于TensorFlow的复合模型，即使用一个算子构建模型的和模型的编译
"""
def build_model(self):
raise NotImplementedError
... | flexible | {
"blob_id": "cdabb4a118cb0ef55c271a446fa190a457ebe142",
"index": 7383,
"step-1": "<mask token>\n\n\nclass TFCompile(TFLayer):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TFComModel(TFModel, TFCompile):\n \"\"\"\n 基于TensorFlow的复合模型，即使用一个算子构建模型的和模型的编译\n \"\"\"\n\n def build_model(s... | [
5,
8,
10,
11,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for video_id in list_video_id:
url = ('https://www.googleapis.com/youtube/v3/videos?id=' + video_id +
'&part=statistics&key=' + API_KEY)
response = requests.get(url).json()
for i in response['items']:
r... | flexible | {
"blob_id": "3c341b17f260cc745c8659ee769493216522ac19",
"index": 2073,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor video_id in list_video_id:\n url = ('https://www.googleapis.com/youtube/v3/videos?id=' + video_id +\n '&part=statistics&key=' + API_KEY)\n response = requests.get(url).js... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def is_bad_version(v):
return version_api.is_bad(v)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def is_bad_version(v):
return version_api.is_bad(v)
def first_bad_version(n):
version_api.n = n
api_calls_count = 0
left,... | flexible | {
"blob_id": "df4c03d9faedf2d347593825c7221937a75a9c10",
"index": 5360,
"step-1": "<mask token>\n\n\ndef is_bad_version(v):\n return version_api.is_bad(v)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_bad_version(v):\n return version_api.is_bad(v)\n\n\ndef first_bad_version(n):\n version_ap... | [
1,
2,
3,
4,
5
] |
__title__ = 'pyaddepar'
__version__ = '0.6.0'
__author__ = 'Thomas Schmelzer'
__license__ = 'MIT'
__copyright__ = 'Copyright 2019 by Lobnek Wealth Management'
| normal | {
"blob_id": "cc985ae061c04696dbf5114273befd62321756ae",
"index": 9569,
"step-1": "<mask token>\n",
"step-2": "__title__ = 'pyaddepar'\n__version__ = '0.6.0'\n__author__ = 'Thomas Schmelzer'\n__license__ = 'MIT'\n__copyright__ = 'Copyright 2019 by Lobnek Wealth Management'\n",
"step-3": null,
"step-4": null... | [
0,
1
] |
<|reserved_special_token_0|>
def tf_idf(words):
word_dict = {}
for w in words:
if w in word_dict.keys():
word_dict[w] += 1
else:
word_dict[w] = 1
max_freq = max(word_dict.values())
for w in words:
word_dict[w] = word_dict[w] / max_freq * math.log(N / n_d... | flexible | {
"blob_id": "e877f16e604682488d85142174ce4f3f6cee3f18",
"index": 7882,
"step-1": "<mask token>\n\n\ndef tf_idf(words):\n word_dict = {}\n for w in words:\n if w in word_dict.keys():\n word_dict[w] += 1\n else:\n word_dict[w] = 1\n max_freq = max(word_dict.values())\n ... | [
2,
3,
4,
5,
6
] |
#função: Definir se o número inserido é ímpar ou par
#autor: João Cândido
p = 0
i = 0
numero = int(input("Insira um número: "))
if numero % 2 == 0:
p = numero
print (p, "é um número par")
else:
i = numero
print (i, "é um número ímpar") | normal | {
"blob_id": "382bc321c5fd35682bc735ca4d6e293d09be64ec",
"index": 9990,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif numero % 2 == 0:\n p = numero\n print(p, 'é um número par')\nelse:\n i = numero\n print(i, 'é um número ímpar')\n",
"step-3": "p = 0\ni = 0\nnumero = int(input('Insira um... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class LoLServerStatusHandler(Handler):
def load_servers(self):
servers_filepath = os.path.join(os.path.dirname(__file__),
'../../data/lol/status.json')
return load_json(servers_filepath)
def get_filepath(self, server):
return '/lol/{region}/st... | flexible | {
"blob_id": "493552469943e9f9f0e57bf92b874c8b67943de5",
"index": 6751,
"step-1": "<mask token>\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(server... | [
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'qtGSD_DESIGN.ui'
#
# Created by: PyQt4 UI code generator 4.11.4
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore, QtGui
try:
_fromUtf8 = QtCore.QString.fromUtf8
except AttributeError:
def _fromUtf8(... | normal | {
"blob_id": "9dde8e5fd0e83860ee86cf5402ab6eeb5b07ab2c",
"index": 7761,
"step-1": "<mask token>\n\n\nclass Ui_MainWindow(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Ui_MainWindow(object):\n\n def setupUi(self, MainWindow):\n MainWindow.setObjectName(_fromUtf8('M... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class ImageSelection:
def __init__(self, path):
self.path = path
def brightness_check(self, image):
"""count function to set value of brightness, 0 - full black, 100 - full bright"""
with Image.open(image).convert('L') as img:
z = ImageStat.St... | flexible | {
"blob_id": "897075810912e8360aa5cdedda3f12ce7c868263",
"index": 4547,
"step-1": "<mask token>\n\n\nclass ImageSelection:\n\n def __init__(self, path):\n self.path = path\n\n def brightness_check(self, image):\n \"\"\"count function to set value of brightness, 0 - full black, 100 - full brigh... | [
5,
6,
7,
8,
9
] |
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
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2014 Vincent Celis
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the righ... | normal | {
"blob_id": "a61bc654eecb4e44dce3e62df752f80559a2d055",
"index": 9184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nROUTE_LIST = [webapp2.Route('/api/history<name:/(?:[a-zA-Z0-9_-]+/?)*>',\n handler=handlers.HistoryApi, name='historyApi'), webapp2.Route(\n '/api<name:/(?:[a-zA-Z0-9_-]+/?)*>', han... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def gauss_seidel(relax, est, stop):
"""
Método iterativo de Gauss-Seidel para o sistema linear do trabalho.
Onde relax é o fator de relaxação, est é o valor inicial, stop é o
critério de parada, n é a qu... | flexible | {
"blob_id": "51540a80c7b29dc0bbb6342ee45008108d54b6f2",
"index": 714,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef gauss_seidel(relax, est, stop):\n \"\"\"\n Método iterativo de Gauss-Seidel para o sistema linear do trabalho.\n Onde relax é o fator de relaxação, est é o valor ini... | [
0,
1,
2,
3
] |
import MySQLdb
import MySQLdb.cursors
from flask import _app_ctx_stack, current_app
class MySQL(object):
def __init__(self, app=None):
self.app = app
if app is not None:
self.init_app(app)
def init_app(self, app):
"""Initialize the `app` for use with this
:class:`... | normal | {
"blob_id": "db8c2f6f5da0b52c268634043e1132984f610eed",
"index": 8405,
"step-1": "<mask token>\n\n\nclass MySQL(object):\n\n def __init__(self, app=None):\n self.app = app\n if app is not None:\n self.init_app(app)\n <mask token>\n\n @property\n def connect(self):\n kw... | [
4,
5,
6,
7,
8
] |
# -*- coding:ascii -*-
from mako import runtime, filters, cache
UNDEFINED = runtime.UNDEFINED
__M_dict_builtin = dict
__M_locals_builtin = locals
_magic_number = 10
_modified_time = 1428612037.145222
_enable_loop = True
_template_filename = 'C:\\Users\\Cody\\Desktop\\Heritage\\chf\\templates/account.rentalcart.html'
_t... | normal | {
"blob_id": "57967f36a45bb3ea62708bbbb5b2f4ddb0f4bb16",
"index": 29,
"step-1": "<mask token>\n\n\ndef _mako_get_namespace(context, name):\n try:\n return context.namespaces[__name__, name]\n except KeyError:\n _mako_generate_namespaces(context)\n return context.namespaces[__name__, nam... | [
3,
5,
6,
7,
8
] |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from abc import ABCMeta, abstractmethod
import numpy as np
from deeprl.trainers import BaseTrainer
from deeprl.callbacks import EGreedyDecay
from deeprl.policy import EGreedyPolicy
class BaseDQNTrainer(BaseTra... | normal | {
"blob_id": "8bf0141cee2832134d61e49652330c7d21583dcd",
"index": 5201,
"step-1": "<mask token>\n\n\nclass BaseDQNTrainer(BaseTrainer):\n <mask token>\n <mask token>\n <mask token>\n\n def update_model(self, batch):\n batch_s = np.array([i[0] for i in batch])\n batch_a = np.array([i[1] f... | [
3,
4,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^admin/', admin.site.urls), url('^logout/$', auth_views
.logout, {'next_page': '/'}, name='logout'), url('^$', index_view, name
='index'), url('^login/$', login_view, name='login'), url('^register/$',
... | flexible | {
"blob_id": "06627821c09d02543974a3c90664e84e11c980ed",
"index": 7631,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^admin/', admin.site.urls), url('^logout/$', auth_views\n .logout, {'next_page': '/'}, name='logout'), url('^$', index_view, name\n ='index'), url('^login/$', lo... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class InvalidUsage(Exception):
status_code = 400
def __init__(self, message, status_code=None, payload=None):
Exception.__init__(self)
self.message = message
if status_code is not None:
self.status_code = status_code
self.payload = payl... | flexible | {
"blob_id": "8980ac4db2657d3dbd2b70b33a4d13a077d4590e",
"index": 2266,
"step-1": "<mask token>\n\n\nclass InvalidUsage(Exception):\n status_code = 400\n\n def __init__(self, message, status_code=None, payload=None):\n Exception.__init__(self)\n self.message = message\n if status_code i... | [
7,
9,
10,
11,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
import brainlit.algorithms.generate_fragments
from brainlit.algorithms.generate_fragments import *
| flexible | {
"blob_id": "a52743fc911beb7e51644073131b25c177d4ad29",
"index": 852,
"step-1": "<mask token>\n",
"step-2": "import brainlit.algorithms.generate_fragments\nfrom brainlit.algorithms.generate_fragments import *\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def convolve(image, fltr):
r_p = 0
c_p = 0
conv_list = []
while r_p + 1 <= image.shape[0] - 1:
while c_p + 1 <= image.shape[1] - 1:
x = np.sum(np.multiply(image[r_p:r_p + 2, c_p:c_p + 2], fltr))
conv_list.append(x)
c_p += 1
... | flexible | {
"blob_id": "aea92827753e12d2dc95d63ddd0fe4eb8ced5d14",
"index": 3815,
"step-1": "<mask token>\n\n\ndef convolve(image, fltr):\n r_p = 0\n c_p = 0\n conv_list = []\n while r_p + 1 <= image.shape[0] - 1:\n while c_p + 1 <= image.shape[1] - 1:\n x = np.sum(np.multiply(image[r_p:r_p + ... | [
1,
2,
3,
4,
5
] |
<|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": "d69bffb85d81ab3969bfe7dfe2759fa809890208",
"index": 503,
"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 = [('articals', '... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def ratio(area, width, height):
ratio = float(width) / float(height)
if ratio < 1:
ratio = 1 / ratio
if (area < 1063.62 or area > 73862.5) or (ratio < 3 or ratio > 6):
return False
return True
<... | flexible | {
"blob_id": "ab610af97d2b31575ea496b8fddda693353da8eb",
"index": 2870,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef ratio(area, width, height):\n ratio = float(width) / float(height)\n if ratio < 1:\n ratio = 1 / ratio\n if (area < 1063.62 or area > 73862.5) or (ratio < 3 or rat... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
while True:
print('running')
<|reserved_special_token_1|>
while True:
print("running")
| flexible | {
"blob_id": "8917481957ecd4c9692cfa93df0b759feaa344af",
"index": 4944,
"step-1": "<mask token>\n",
"step-2": "while True:\n print('running')\n",
"step-3": "while True:\n print(\"running\")\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
def longestSubstring(self, s: str, k: int) ->int:
def helper(s, k):
if... | flexible | {
"blob_id": "6ba830aafbe8e4b42a0b927328ebcad1424cda5e",
"index": 8381,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n <mask token>\n",
"step-3": "class Solution:\n <mask token>\n\n def longestSubstring(self, s: str, k: int) ->int:\n\n def helper(s, k):\n ... | [
0,
1,
2,
3,
4
] |
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