code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
def f(p_arg, *s_args, **kw_args):
return (s_args[0] + kw_args['py'])+p_arg
r = f(3, 2, py = 1) ## value r => 6
| normal | {
"blob_id": "4a913cfdbddb2f6b5098395814f5fc1203192b9a",
"index": 4847,
"step-1": "<mask token>\n",
"step-2": "def f(p_arg, *s_args, **kw_args):\n return s_args[0] + kw_args['py'] + p_arg\n\n\n<mask token>\n",
"step-3": "def f(p_arg, *s_args, **kw_args):\n return s_args[0] + kw_args['py'] + p_arg\n\n\nr... | [
0,
1,
2,
3
] |
#! /usr/bin/env python
from taskHandler import Location, Task, TaskFactory
import roslib; roslib.load_manifest('smart_stool')
import rospy
from geometry_msgs.msg import PoseStamped, Twist, Vector3
from nav_msgs.msg import Odometry
from kobuki_msgs.msg import BumperEvent
from move_base_msgs.msg import MoveBaseActionRes... | normal | {
"blob_id": "234112ec16af39b79849dd08769597771fa2c38f",
"index": 3425,
"step-1": "#! /usr/bin/env python\n\nfrom taskHandler import Location, Task, TaskFactory\nimport roslib; roslib.load_manifest('smart_stool')\nimport rospy\nfrom geometry_msgs.msg import PoseStamped, Twist, Vector3\nfrom nav_msgs.msg import Od... | [
0
] |
<|reserved_special_token_0|>
def SetCu2Wave():
"""Set the parameters to the two-line Cu K alpha 1+2 spectrum
"""
parmDict['wave'] = {i: v for i, v in enumerate((1.540596, 1.544493))}
parmDict['int'] = {i: v for i, v in enumerate((0.653817, 0.346183))}
parmDict['lwidth'] = {i: v for i, v in enumera... | flexible | {
"blob_id": "3b1426e0f29093e1e462765bcf1d351a064b9639",
"index": 142,
"step-1": "<mask token>\n\n\ndef SetCu2Wave():\n \"\"\"Set the parameters to the two-line Cu K alpha 1+2 spectrum\n \"\"\"\n parmDict['wave'] = {i: v for i, v in enumerate((1.540596, 1.544493))}\n parmDict['int'] = {i: v for i, v i... | [
7,
8,
9,
10,
11
] |
import random
firstNames = ("Thomas", "Daniel", "James", "Aaron", "Tommy", "Terrell", "Jack", "Joseph", "Samuel", "Quinn", "Hunter", "Vince", "Young", "Ian", "Erving", "Leo")
lastNames = ("Smith", "Johnson", "Williams", "Kline","Brown", "Garcia", "Jones", "Miller", "Davis","Williams", "Alves", "Sobronsky", "Hall"... | normal | {
"blob_id": "5607d4fea315fa7bf87337453fbef90a93a66516",
"index": 3968,
"step-1": "<mask token>\n\n\nclass profile:\n\n def __init__(self):\n self.name = firstNames[random.randrange(0, len(firstNames))\n ] + ' ' + lastNames[random.randrange(0, len(lastNames))]\n self.years = 2020\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(owog.find('e'))
print(owog.count('e'))
print(owog[2:10])
<|reserved_special_token_0|>
if a > b:
print('a too ih')
elif a == b:
print('tentsuu')
else:
print('b too ih')
<|reserved_special_token_0|>
for i in range(... | flexible | {
"blob_id": "c4ca4b5c77c3c912b44a4853be30298ec845c4fd",
"index": 243,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(owog.find('e'))\nprint(owog.count('e'))\nprint(owog[2:10])\n<mask token>\nif a > b:\n print('a too ih')\nelif a == b:\n print('tentsuu')\nelse:\n print('b too ih')\n<mask to... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def sample_1(N):
numeros = np.array([-10, -5, 3, 9])
return np.random.choice(numeros, N, p=[0.1, 0.4, 0.2, 0.3])
def sample_2(N):
return np.random.exponential(0.5, N)
def get_mean(sampling_fun, N, M):
medias = np.zeros(M)
for i in range(M):
medias[i] = np.m... | flexible | {
"blob_id": "d2d04686b3d7f8d01ca195750ca625baa06ed098",
"index": 2835,
"step-1": "<mask token>\n\n\ndef sample_1(N):\n numeros = np.array([-10, -5, 3, 9])\n return np.random.choice(numeros, N, p=[0.1, 0.4, 0.2, 0.3])\n\n\ndef sample_2(N):\n return np.random.exponential(0.5, N)\n\n\ndef get_mean(sampling... | [
3,
4,
5,
6,
7
] |
<|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": "016255d74ccf4ac547e4b212d33bb9a39295c830",
"index": 2715,
"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 = [('khovan', '0... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
def main():
A1, A2, A3 = map(int, input().split())
A=A1+A2+A3
if A >=22:
ans='bust'
else:
ans='win'
print(ans)
if __name__ == "__main__":
main()
| normal | {
"blob_id": "753e062940e0580d7d33c88c1165977142dcd202",
"index": 8060,
"step-1": "<mask token>\n",
"step-2": "def main():\n A1, A2, A3 = map(int, input().split())\n A = A1 + A2 + A3\n if A >= 22:\n ans = 'bust'\n else:\n ans = 'win'\n print(ans)\n\n\n<mask token>\n",
"step-3": "d... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(len(ss) - ss.count(' '))
<|reserved_special_token_1|>
ss = str(input())
print(len(ss) - ss.count(' '))
| flexible | {
"blob_id": "7f72f6a2ff0c7ceacb0f893d04c20402e850421a",
"index": 1840,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(len(ss) - ss.count(' '))\n",
"step-3": "ss = str(input())\nprint(len(ss) - ss.count(' '))\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
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 os import listdir
import re
import numpy as np
from sklearn.metrics import f1_score
from sklearn.naive_bayes import MultinomialNB
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.model_selection import LeaveOneOut
import matplotlib.pyplot as plt
n_gram_range = (1, 1)
alpha_smoothing = 1e-1... | normal | {
"blob_id": "8bb67317ede277e03e8cbdefefeffa3d206ece65",
"index": 9434,
"step-1": "<mask token>\n\n\ndef parse_doc_line(line):\n parsed = re.search('\\\\d[\\\\d\\\\s]+\\\\d', line)\n return 'empty' if parsed is None else parsed[0]\n\n\ndef get_roc_point(clf, x_set, y_set, threshold):\n loo = LeaveOneOut(... | [
3,
4,
5,
6,
7
] |
#
# struct_test.py
# Nazareno Bruschi <nazareno.bruschi@unibo.it>
#
# Copyright (C) 2019-2020 University of Bologna
#
# 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.o... | normal | {
"blob_id": "d8d0c181fcfc9e0692369cc7a65259c43a68e931",
"index": 5688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nPULPNNInstallPath = cwd = os.getcwd() + '/../'\nPULPNNSrcDirs = {'script': PULPNNInstallPath + 'scripts/'}\nPULPNNInstallPath32bit = cwd = os.getcwd() + '/../32bit/'\nPULPNNInstallPath64b... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for case in range(1, cases + 1):
digits = [False] * 10
n = int(rf.readline())
if n == 0:
wf.write('Case #%s: INSOMNIA\n' % case)
continue
for i in range(1, 999999):
cur = n * i
for c... | flexible | {
"blob_id": "0074b0cd1e4317e36ef4a41f8179464c2ec6c197",
"index": 8250,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor case in range(1, cases + 1):\n digits = [False] * 10\n n = int(rf.readline())\n if n == 0:\n wf.write('Case #%s: INSOMNIA\\n' % case)\n continue\n for i in r... | [
0,
1,
2
] |
from sqlalchemy import literal, Column, String, Integer, ForeignKey
from sqlalchemy.orm import relationship
from common.db import Base
class Airplane(Base):
__tablename__ = 'airplanes'
id = Column(Integer, primary_key=True)
icao_code = Column(String(6), unique=True, nullable=False) # ICAO 24-bit identifi... | normal | {
"blob_id": "98dac1ea372f16ecdb818fbe3287ab7e51a0d67c",
"index": 7916,
"step-1": "<mask token>\n\n\nclass Airplane(Base):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, icao_code, airline, manufacturer=None, ... | [
3,
4,
5,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def steps_in_tower_of_hanoi(no_of_disks):
res = towers_of_hanoi(no_of_disks, 'A', 'C', 'B', [])
return res
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def towers_of_hanoi(n, src, dest, temp, res):
... | flexible | {
"blob_id": "f23bfef2daf8fda4249435821dbc2e0b1846e3d6",
"index": 9842,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef steps_in_tower_of_hanoi(no_of_disks):\n res = towers_of_hanoi(no_of_disks, 'A', 'C', 'B', [])\n return res\n\n\n<mask token>\n",
"step-3": "def towers_of_hanoi(n, src, des... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestCadastro(BaseTest):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestCadastro(BaseTest):
def test_cadastro_com_sucesso(self):
self.campoDeTreinament... | flexible | {
"blob_id": "4e50a7a757bacb04dc8f292bdaafb03c86042e6c",
"index": 1633,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestCadastro(BaseTest):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TestCadastro(BaseTest):\n\n def test_cadastro_com_sucesso(self):\n self.campoDeTrein... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SampleAdmin(admin.ModelAdmin):
inlines = [MultipleFileInline]
prepopulated_fields = {'slug': ('heading',)}
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class MultipleFileInline(admin.TabularInline):
model = SampleMultipleF... | flexible | {
"blob_id": "d18c45c08face08ce8f7dad915f1896c24c95cbf",
"index": 2991,
"step-1": "<mask token>\n\n\nclass SampleAdmin(admin.ModelAdmin):\n inlines = [MultipleFileInline]\n prepopulated_fields = {'slug': ('heading',)}\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass MultipleFileInline(admin.Tabula... | [
2,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class director(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<... | flexible | {
"blob_id": "006f499eed7cd5d73bb0cb9b242c90726fff35c1",
"index": 3185,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass director(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass director(models.Model)... | [
0,
1,
2,
3,
4
] |
from typing import *
class Solution:
def isMonotonic(self, A: List[int]) ->bool:
flag = 0
for i in range(1, len(A)):
diff = A[i] - A[i - 1]
if diff * flag < 0:
return False
if flag == 0:
flag = diff
return True
sl = Sol... | normal | {
"blob_id": "a55d1286485e66a64aa78259ad1b1922c5c4c831",
"index": 4385,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def isMonotonic(self, A: List[int]) ->bool:\n flag = 0\n for i in range(1, len(A)):\n diff = A[i] - A[i - 1]\n if diff * flag < 0:\n return... | [
2,
3,
4,
5
] |
from django.apps import AppConfig
class ShortenConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'shorten'
| normal | {
"blob_id": "8c2920db7fc49d56aa8da6289cd22272ed3e3283",
"index": 4402,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ShortenConfig(AppConfig):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ShortenConfig(AppConfig):\n default_auto_field = 'django.db.models.BigA... | [
0,
1,
2,
3
] |
import functools
import re
from pprint import pprint
def heading(*, marker=''):
'''
Add a new line with the same number of heading markers as the characters in the title
Need to specify marker to one of the valid rst line markups
'''
def wrapper_heading(func):
@functools.wraps(func)
... | normal | {
"blob_id": "d1b2420778e788d78be2a12a27c80f5fa1b15a0f",
"index": 465,
"step-1": "<mask token>\n\n\ndef code_pre_block(func):\n \"\"\"\n formats a code block according to rst format\n \"\"\"\n\n @functools.wraps(func)\n def wrapper(*args, **kwargs):\n block = func(*args, **kwargs)\n n... | [
7,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with tf.Session() as sess:
output = sess.run(z, feed_dict={x: 10, y: 2})
print(output)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
x = tf.placeholder(tf.int32)
y = tf.placeholder(tf.int32)
u = tf.divide(x,... | flexible | {
"blob_id": "ca91052072d7b2da5729cf55f7f4ba4b54608017",
"index": 3477,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith tf.Session() as sess:\n output = sess.run(z, feed_dict={x: 10, y: 2})\n print(output)\n",
"step-3": "<mask token>\nx = tf.placeholder(tf.int32)\ny = tf.placeholder(tf.int32)\... | [
0,
1,
2,
3,
4
] |
from flask import Flask
from flask_sqlalchemy import SQLAlchemy
from subprocess import call
app = Flask(__name__)
app.config['SECRET_KEY'] = "SuperSecretKey"
#app.config['SQLALCHEMY_DATABASE_URI'] = "postgresql://fmnibhaashbxuy:73b8e2e2485adfd45f57da653d63950b88fdcae12202a84f80c7f4c297e9e30a@ec2-23-23-222-184.compute-... | normal | {
"blob_id": "7b45c9e31bfb868b1abde6af0d8579b52f86d9c3",
"index": 5689,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp = Flask(__name__)\napp.config['SECRET_KEY'] = 'SuperSecretKey'\napp.config['SQLALCHEMY_DATABASE_URI'\n ] = 'postgresql://info2180-project1:password123@localhost/profilebook'\napp.c... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
try:
from .local_settings import *
except Exception as e:
pass
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
DATABASES = {'default': dj_database_url.config()}
SECURE_PROXY_SSL_HE... | flexible | {
"blob_id": "8bb86cae3387a0d4ce5987f3e3c458c8298174e0",
"index": 7342,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n from .local_settings import *\nexcept Exception as e:\n pass\n<mask token>\n",
"step-3": "<mask token>\nDATABASES = {'default': dj_database_url.config()}\nSECURE_PROXY_SSL_... | [
0,
1,
2,
3,
4
] |
a=list(input("enter the string or sentence to perform caesar cipher : "))
b=int(input('enter the frequency to perform ceasar cipher '))
e=[]
#print(a)
#print (a[4])
c=len(a)
#print(c)
for i in range (0,c):
d=ord(a[i])
#print(d)
if b> 0:
for j in range (1,b+1):
if a[i] >='a' ... | normal | {
"blob_id": "287d4c2d490c9dcdd7be7e86fe577139a3d30f54",
"index": 6676,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, c):\n d = ord(a[i])\n if b > 0:\n for j in range(1, b + 1):\n if a[i] >= 'a' and a[i] <= 'z' or a[i] >= 'A' and a[i] <= 'Z':\n if ... | [
0,
1,
2,
3
] |
class Member:
not_allowed_name = ["Shit", "Hell", "Baloot"]
users_num = 0
def __init__(self, first_name, middle_name, last_name, gender):
self.fname = first_name
self.mname = middle_name
self.lname = last_name
self.gender = gender
Member.users_num += 1
@classm... | normal | {
"blob_id": "f276e33cde2e043fc8f81403e499544aa816a639",
"index": 9316,
"step-1": "class Member:\n <mask token>\n <mask token>\n\n def __init__(self, first_name, middle_name, last_name, gender):\n self.fname = first_name\n self.mname = middle_name\n self.lname = last_name\n se... | [
7,
8,
10,
11,
12
] |
"""
.. currentmodule:: jotting
.. automodule:: jotting.book
:members:
.. automodule:: jotting.to
:members:
.. automodule:: jotting.read
:members:
.. automodule:: jotting.style
:members:
"""
from .book import book
from . import style, to, read, dist
| normal | {
"blob_id": "ce6dba2f682b091249f3bbf362bead4b95fee1f4",
"index": 292,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfrom .book import book\nfrom . import style, to, read, dist\n",
"step-3": "\"\"\"\n.. currentmodule:: jotting\n\n.. automodule:: jotting.book\n :members:\n\n.. automodule:: jotting.to... | [
0,
1,
2
] |
#! /usr/bin/env python
#
# Copyright (c) 2015 Jason Ish
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this li... | normal | {
"blob_id": "41889456fbb56d263e0039716519e8959316b67e",
"index": 3473,
"step-1": "<mask token>\n\n\ndef render_timestamp(sec, usec):\n tt = time.localtime(sec)\n return '%04d-%02d-%02dT%02d:%02d:%02d.%06d%s' % (tt.tm_year, tt.tm_mon,\n tt.tm_mday, tt.tm_hour, tt.tm_min, tt.tm_sec, usec, get_tzoffset... | [
12,
15,
16,
17,
19
] |
# Python library import
import asyncio, asyncssh, logging
# Module logging logger
log = logging.getLogger(__package__)
# Debug level
# logging.basicConfig(level=logging.WARNING)
# logging.basicConfig(level=logging.INFO)
logging.basicConfig(level=logging.DEBUG)
asyncssh.set_debug_level(2)
# Declaration of constant v... | normal | {
"blob_id": "87baaf4a1b48fa248c65d26cc44e819a2ede1140",
"index": 3736,
"step-1": "<mask token>\n\n\nclass NetworkDevice:\n <mask token>\n\n def __init__(self, **kwargs):\n log.info('__init__')\n self.ip = ''\n self.username = ''\n self.password = ''\n self.device_type = '... | [
9,
10,
12,
14,
15
] |
<|reserved_special_token_0|>
def _unique_predict(solve_list):
valid_solve_list = filter(lambda x: x[0] is not None, solve_list)
valid_solve_list = sorted(valid_solve_list, key=lambda x: x[0])
unique_solve_list = list()
current_no = -1
for e in valid_solve_list:
if current_no != e[0]:
... | flexible | {
"blob_id": "00a1b5f20f15994a659eda56201ba7c45d49a4db",
"index": 4186,
"step-1": "<mask token>\n\n\ndef _unique_predict(solve_list):\n valid_solve_list = filter(lambda x: x[0] is not None, solve_list)\n valid_solve_list = sorted(valid_solve_list, key=lambda x: x[0])\n unique_solve_list = list()\n cur... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_mapped_sku(sku):
try:
cursor = connect(aws_access_key_id=config2['aws_access_key_id'],
aws_secret_access_key=config2['aws_secret_access_key'],
s3_staging_dir=config2['s3_staging_dir'],... | flexible | {
"blob_id": "6add599035573842475c7f9155c5dbbea6c96a8a",
"index": 3618,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_mapped_sku(sku):\n try:\n cursor = connect(aws_access_key_id=config2['aws_access_key_id'],\n aws_secret_access_key=config2['aws_secret_access_key'],\n ... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
admin.autodiscover()
<|reserved_special_token_0|>
urlpatterns += patterns('piston.authentication', url(
'^oauth/request_token/$', 'oauth_request_token'), url(
'^oauth/authorize/$', 'oauth_user_auth'), url('^oauth/access_to... | flexible | {
"blob_id": "266ce1aaa3283cf2aaa271a317a80c3860880a49",
"index": 4901,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.autodiscover()\n<mask token>\nurlpatterns += patterns('piston.authentication', url(\n '^oauth/request_token/$', 'oauth_request_token'), url(\n '^oauth/authorize/$', 'oauth_use... | [
0,
1,
2,
3,
4
] |
import httplib
def get_status_code(host, path="/"):
try:
connect = httplib.HTTPConnection(host)
connect.request("HEAD", path)
return connect.getresponse().status
except StandardError:
return None
if __name__ == '__main__':
print get_status_code("google.com")
| normal | {
"blob_id": "891a490410fd8c7b8879f1e71f24df2db62ff85d",
"index": 7748,
"step-1": "import httplib\n\ndef get_status_code(host, path=\"/\"):\n try:\n connect = httplib.HTTPConnection(host)\n connect.request(\"HEAD\", path)\n return connect.getresponse().status\n except StandardError:\n ... | [
0
] |
import os
import shutil
# root_path = '../from_1691'
root_path = 'C:/Users/koyou/Desktop/test'
# 실수할 수도 있으므로 dry_run 을 설정해서 로그만 찍을 것인지
# 실제 작동도 진행할 것인지 결정한다.
# dry_run = True
dry_run = False
def move_directory(input_directory_path, output_directory_path):
print("moving %s to %s" % (input_directory_path, output_d... | normal | {
"blob_id": "7de19a85a6a05bd2972b11571d5f05219c6beb1a",
"index": 916,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef move_directory(input_directory_path, output_directory_path):\n print('moving %s to %s' % (input_directory_path, output_directory_path))\n if not dry_run:\n shutil.move... | [
0,
1,
2,
3,
5
] |
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
import base64
import configobj
import datetime
import os
config = configobj.ConfigObj('.env')
port = 2525
smtp_server = "smtp.mailtrap.io"
login = config['SMTP_USERNAME']
password = config['SMTP_PASSWORD']
sender_email... | normal | {
"blob_id": "a21ac29911931bb71460175cba584e0011fa2ece",
"index": 1055,
"step-1": "<mask token>\n\n\ndef send():\n global last_index_sent\n global last_sent\n DIR = './videos'\n videosToSend = len([name for name in os.listdir(DIR) if os.path.isfile(\n os.path.join(DIR, name))])\n for i in ra... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(25000):
pval, costval = train(inputs, outputs)
print(costval)
val1.append(pval)
cost1.append(costval)
print('the final outputs are:')
for i in range(len(inputs)):
print('the output of x1=%d | x2=... | flexible | {
"blob_id": "adec7efceb038c0ecb23c256c23c2ea212752d64",
"index": 4010,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(25000):\n pval, costval = train(inputs, outputs)\n print(costval)\n val1.append(pval)\n cost1.append(costval)\nprint('the final outputs are:')\nfor i in range(l... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
command('strip', '-S', '-x', input_file(
'bin/darwin-4.2.1/release/target-os-darwin/test'))
main()
<|reserved_special_token_1|>
from MockProgram import *
command('strip', '-S', '-x', input_file(
'bin/darwin-4.2.1/releas... | flexible | {
"blob_id": "d2f77afd0d282b1fa4859c5368c9d2c745a5625e",
"index": 3293,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncommand('strip', '-S', '-x', input_file(\n 'bin/darwin-4.2.1/release/target-os-darwin/test'))\nmain()\n",
"step-3": "from MockProgram import *\ncommand('strip', '-S', '-x', input_fil... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def login_required(f):
"""
Decorate routes to require login.
http://flask.pocoo.org/docs/1.0/patterns/viewdecorators/
"""
@wraps(f)
def decorated_function(*args, **kwargs):
if session.get('user_id') is None:
return redirect('/sign_in')
... | flexible | {
"blob_id": "1a4da621add157fa6d1f578370d64594b102eeb5",
"index": 4245,
"step-1": "<mask token>\n\n\ndef login_required(f):\n \"\"\"\n Decorate routes to require login.\n\n http://flask.pocoo.org/docs/1.0/patterns/viewdecorators/\n \"\"\"\n\n @wraps(f)\n def decorated_function(*args, **kwargs):\... | [
3,
4,
5,
6,
7
] |
# SPDX-FileCopyrightText: 2021 John Park for Adafruit Industries
# SPDX-License-Identifier: MIT
import time
import random
import board
import audiomp3
import audiopwmio
from adafruit_crickit import crickit
ss = crickit.seesaw # Crickit seesaw setup
button = crickit.SIGNAL1 # momentary switch to trigger animation
ss... | normal | {
"blob_id": "608c116cd42132bd63be5056f0aaf5c78933886e",
"index": 7536,
"step-1": "<mask token>\n\n\ndef open_lid():\n motor_lid.throttle = 1\n time.sleep(0.25)\n motor_lid.throttle = 0\n\n\ndef close_lid():\n motor_lid.throttle = -1\n time.sleep(0.25)\n motor_lid.throttle = 0\n\n\ndef blink(tim... | [
3,
5,
6,
7,
8
] |
#!usr/bin/python
# -*- coding:utf8 -*-
import time
import random
import asyncio
async def consumer(queue, name):
while True:
val = await queue.get()
print(f'{name} get a val: {val} at {time.strftime("%X")}')
await asyncio.sleep(1)
async def producer(queue, name):
for i in range(20):
... | normal | {
"blob_id": "e1172e2d9f20e56241829b3e4ccb4bcf6b5440be",
"index": 9233,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nasync def consumer(queue, name):\n while True:\n val = await queue.get()\n print(f\"{name} get a val: {val} at {time.strftime('%X')}\")\n await asyncio.sleep(1... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class TestHand(unittest.TestCase):
def test_max_straight(self):
cards = map(makeCard, ['10S', '6S', '9S', '8S', '7S'])
straight = max_straight(cards)
self.assertEqual(straight, sorted(map(makeCard, ['10S', '6S', '9S',
'8S', '7S']), reverse=True))
... | flexible | {
"blob_id": "5b8d1bd026e97bb7508a500048f940abf0253471",
"index": 9698,
"step-1": "<mask token>\n\n\nclass TestHand(unittest.TestCase):\n\n def test_max_straight(self):\n cards = map(makeCard, ['10S', '6S', '9S', '8S', '7S'])\n straight = max_straight(cards)\n self.assertEqual(straight, so... | [
5,
6,
7,
8,
9
] |
'''
使用random模块，如何产生 50~150之间的数？
'''
import random
num1 = random.randint(50,151)
print(num1) | normal | {
"blob_id": "7d3355ee775f759412308ab68a7aa409b9c74b20",
"index": 708,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(num1)\n",
"step-3": "<mask token>\nnum1 = random.randint(50, 151)\nprint(num1)\n",
"step-4": "<mask token>\nimport random\nnum1 = random.randint(50, 151)\nprint(num1)\n",
"step... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(packages=find_packages(), setup_requires=['flask'], name='mith1')
<|reserved_special_token_1|>
from setuptools import setup, find_packages
setup(packages=find_packages(), setup_requires=['flask'], name='mith1')
<|reserv... | flexible | {
"blob_id": "a5a7cd112faad1096ce4c6f04b2179fbdf732702",
"index": 1479,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(packages=find_packages(), setup_requires=['flask'], name='mith1')\n",
"step-3": "from setuptools import setup, find_packages\nsetup(packages=find_packages(), setup_requires=['flas... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Sender:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def send_frame(self, frame):
self.receiver.receiver_frame(frame)... | flexible | {
"blob_id": "ecbcd023b8fec5763c6ff7f4cd0999426fae4a50",
"index": 9093,
"step-1": "<mask token>\n\n\nclass Sender:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def send_frame(self, frame):\n self.receiver.receiver_frame(frame)\n p... | [
5,
7,
8,
10,
11
] |
from .Buzzer import BuzzerController
from .Card import CardScanner
from .RFID import RFIDController
from .Servo import ServoController
__all__ = ["BuzzerController", "CardScanner", "RFIDController", "ServoController"]
| normal | {
"blob_id": "8fa78824a38a3b0c1f51aceacab671f987ea2705",
"index": 9635,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__all__ = ['BuzzerController', 'CardScanner', 'RFIDController',\n 'ServoController']\n",
"step-3": "from .Buzzer import BuzzerController\nfrom .Card import CardScanner\nfrom .RFID im... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def solution(X, Y, D):
xy = Y - X
if xy == 0:
return 0
jumps = math.ceil(xy / D)
return jumps
<|reserved_special_token_1|>
import math
def solution(X, Y, D):
xy = Y - X
if xy == 0:
re... | flexible | {
"blob_id": "bdf819d8a5bc3906febced785c6d95db7dc3a603",
"index": 2376,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solution(X, Y, D):\n xy = Y - X\n if xy == 0:\n return 0\n jumps = math.ceil(xy / D)\n return jumps\n",
"step-3": "import math\n\n\ndef solution(X, Y, D):\n ... | [
0,
1,
2,
3
] |
# This implementation of EPG takes data as XML and produces corresponding pseudonymized data
from lxml import etree
from utils import generalize_or_supress
from hashlib import sha256
from count import getLast, saveCount
import pickle
from hmac import new
from random import random
from json import loads
from bigchain i... | normal | {
"blob_id": "8f554166c28fe4c9a093568a97d39b6ba515241b",
"index": 3196,
"step-1": "<mask token>\n\n\ndef EPGAD(ReportPath, Hi=None, GUi=None):\n if Hi == None:\n Hi = sha256(str(random()).encode()).hexdigest()\n jsn = open(ReportPath, 'rt').read()\n jsnld = loads(jsn)\n print('Report Loaded')\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def train_model_snapshot(model, criterion, lr, dataloaders, dataset_sizes,
device, num_cycles, num_epochs_per_cycle):
since = time.time()
best_model_wts = copy.deepcopy(model.state_dict())
best_acc = 0.0
best_loss = 1000000.0
model_w_arr = []
prob = torch.zeros... | flexible | {
"blob_id": "d807a363c08d117c848ffdc0a768c696ea7746bd",
"index": 1787,
"step-1": "<mask token>\n\n\ndef train_model_snapshot(model, criterion, lr, dataloaders, dataset_sizes,\n device, num_cycles, num_epochs_per_cycle):\n since = time.time()\n best_model_wts = copy.deepcopy(model.state_dict())\n best... | [
2,
3,
4,
5,
6
] |
# Standard library
# Third party library
# Local library
from warehouse.server import run_server
from warehouse.server.config import log
if __name__ == "__main__":
log.initialize_logs()
run_server()
| normal | {
"blob_id": "8c8b5c1ff749a8563788b8d5be5332e273275be3",
"index": 6450,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n log.initialize_logs()\n run_server()\n",
"step-3": "from warehouse.server import run_server\nfrom warehouse.server.config import log\nif __name__ == '... | [
0,
1,
2,
3
] |
n = int(input())
if n % 10 == 1 and (n < 11 or n > 20):
print(n, "korova")
elif n % 10 > 1 and n % 10 < 5 and (n < 11 or n > 20):
print(n, "korovy")
else:
print(n, "korov")
| normal | {
"blob_id": "78037d936ee5f9b31bf00263885fbec225a4f8f2",
"index": 2191,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif n % 10 == 1 and (n < 11 or n > 20):\n print(n, 'korova')\nelif n % 10 > 1 and n % 10 < 5 and (n < 11 or n > 20):\n print(n, 'korovy')\nelse:\n print(n, 'korov')\n",
"step-3"... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
[print(i) for i in sentence if len(i) < 5]
<|reserved_special_token_1|>
sentence = 'Practice Problems to Drill List Comprehension in Your Head.'
sentence = sentence.split()
sentence = [i.replace('.', '') for i in sentence]
[pri... | flexible | {
"blob_id": "c0e349be45cd964e8e398baaed64eae792189dd1",
"index": 5723,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n[print(i) for i in sentence if len(i) < 5]\n",
"step-3": "sentence = 'Practice Problems to Drill List Comprehension in Your Head.'\nsentence = sentence.split()\nsentence = [i.replace('.... | [
0,
1,
2,
3
] |
###############################################################################
# #
# This program is free software: you can redistribute it and/or modify #
# it under the terms of the GNU General Public License as published by ... | normal | {
"blob_id": "53909b750f259b67b061ba26d604e0c2556376df",
"index": 9560,
"step-1": "<mask token>\n\n\nclass CurationLists(object):\n <mask token>\n <mask token>\n\n def pseudo_tree(self, gids, out_tree):\n \"\"\"Create pseudo-tree with the specified genome IDs.\"\"\"\n pseudo_tree = '('\n ... | [
4,
5,
6,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
model.fit
<|reserved_special_token_0|>
model.save('./T_100_Modelo_C64k33_C128k33_d025_D256_d05_D5.h5')
plt.plot(history.history['accuracy'], label='accuracy')
plt.plot(history.history['val_accuracy'], label='validation accuracy')
... | flexible | {
"blob_id": "d2f760b821fc5c599cda1091334364e18234ab06",
"index": 4222,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmodel.fit\n<mask token>\nmodel.save('./T_100_Modelo_C64k33_C128k33_d025_D256_d05_D5.h5')\nplt.plot(history.history['accuracy'], label='accuracy')\nplt.plot(history.history['val_accuracy']... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Student:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Student:
def __init__(self, name, rollno):
self.name = name
self.rollno = rollno
<|reserved_special_token_0|>
<|reser... | flexible | {
"blob_id": "97656bca3ce0085fb2f1167d37485fb7ee812730",
"index": 4825,
"step-1": "<mask token>\n",
"step-2": "class Student:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Student:\n\n def __init__(self, name, rollno):\n self.name = name\n self.rollno = rollno\n\n\n<mask token>\n",... | [
0,
1,
2,
3,
4
] |
<|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": "c0bf146ebfdb54cce80ef85c4c7f4a61632e67d4",
"index": 3371,
"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 = [('myapp', '00... | [
0,
1,
2,
3,
4
] |
import os
def savelesson(text):
os.path.expanduser("~/.buzzers/lessons")
def getlessonlist():
path = os.path.expanduser("~/.buzzers")
dirs = os.walk(os.path.expanduser("~/.buzzers/lessons"))
#"/home/loadquo/files/lhsgghc/Programs/PCSoftware/src/admin/lessons")
lessons = []
for root, d, fs in dirs:
... | normal | {
"blob_id": "de003440be513d53b87f526ea95c0fbbc4a9f66f",
"index": 2584,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getlessonlist():\n path = os.path.expanduser('~/.buzzers')\n dirs = os.walk(os.path.expanduser('~/.buzzers/lessons'))\n lessons = []\n for root, d, fs in dirs:\n ... | [
0,
1,
2,
3,
4
] |
from django.urls import re_path
from .consumers import ChatConsumer, ChatLobbyConsumer
websocket_urlpatterns = [
re_path(r'ws/chat/(?P<room_id>\w+)/$', ChatConsumer),
re_path(r'ws/lobby/$', ChatLobbyConsumer),
] | normal | {
"blob_id": "1bd1769f94b93e0bb674adfd1bb96c778708f6d8",
"index": 5593,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwebsocket_urlpatterns = [re_path('ws/chat/(?P<room_id>\\\\w+)/$',\n ChatConsumer), re_path('ws/lobby/$', ChatLobbyConsumer)]\n",
"step-3": "from django.urls import re_path\nfrom .con... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('haiku.txt', 'w') as file:
file.write('This is the line 1 of the haiku\n')
file.write('Following the line 2 of the haiku\n')
file.write('Finishing off with the line 3 of the haiku\n')
with open('haiku.txt', '... | flexible | {
"blob_id": "cde2454c68a0d6a0c86b7d647e41a86d3aa97a0d",
"index": 8267,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('haiku.txt', 'w') as file:\n file.write('This is the line 1 of the haiku\\n')\n file.write('Following the line 2 of the haiku\\n')\n file.write('Finishing off with the ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class BadArgumentException(Exception):
def __init__(self, msg):
self.msg = msg
def __str__(self):
return self.msg
class TooManyArgumentsException(Exception):
def __init__(self, msg):
self.msg = msg
def __str__(self):
return self.msg
... | flexible | {
"blob_id": "eed79a3895975a0475c0b192bd8a42e80def2e78",
"index": 2502,
"step-1": "<mask token>\n\n\nclass BadArgumentException(Exception):\n\n def __init__(self, msg):\n self.msg = msg\n\n def __str__(self):\n return self.msg\n\n\nclass TooManyArgumentsException(Exception):\n\n def __init_... | [
25,
26,
29,
31,
32
] |
<|reserved_special_token_0|>
class Test(unittest.TestCase):
<|reserved_special_token_0|>
def test_final_summary(self):
pkl = os.path.join(self.testfiles_dir, AMPLE_PKL)
if not os.path.isfile(pkl):
return
with open(pkl, 'rb') as f:
if sys.version_info.major == 3... | flexible | {
"blob_id": "f6dd5acc75d1a85a996629e22e81cdef316c1dcd",
"index": 8939,
"step-1": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n\n def test_final_summary(self):\n pkl = os.path.join(self.testfiles_dir, AMPLE_PKL)\n if not os.path.isfile(pkl):\n return\n wi... | [
3,
4,
5,
6,
7
] |
#implement variable!
import numpy as np
class Variable:
def __init__(self, data):
self.data = data
class Function:
'''
Base class
specific functions are implemented in the inherited class
'''
def __call__(self, input):
x = input.data #data extract
y = self.foward(x)
... | normal | {
"blob_id": "9efd83524ebb598f30c8fb6c0f9f0c65333578e6",
"index": 6292,
"step-1": "<mask token>\n\n\nclass Function:\n <mask token>\n <mask token>\n\n def foward(self, x):\n raise NotImplementedError()\n\n\nclass Square(Function):\n\n def foward(self, x):\n return x ** 2\n\n\nclass Exp(F... | [
6,
10,
11,
12,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
logging.basicConfig(stream=sys.stdout, format=
'[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',
level=logging.DEBUG)
client = docker.from_env()
logging.i... | flexible | {
"blob_id": "a5c9ff1fe250310216e2eaa7a6ff5cc76fc10f94",
"index": 4324,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logging.basicConfig(stream=sys.stdout, format=\n '[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',\n level=logging.DEBUG... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
{'ivy': {'svm': ({'kernel': 'rbf', 'C': 10.0}, 0.03448275862068966,
0.03508771929824561), 'tuned_ensemble': ({'svm__C': 100000.0,
'rf__n_estimators': 101, 'cart__min_samples_leaf': 7,
'knn__n_neighbors': 2, 'rf__random_state': 1542, 'cart__max_de... | flexible | {
"blob_id": "fa02fb701b59728671a7e87147adaeb33422dcdb",
"index": 1600,
"step-1": "<mask token>\n",
"step-2": "{'ivy': {'svm': ({'kernel': 'rbf', 'C': 10.0}, 0.03448275862068966, \n 0.03508771929824561), 'tuned_ensemble': ({'svm__C': 100000.0,\n 'rf__n_estimators': 101, 'cart__min_samples_leaf': 7,\n '... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class People:
<|reserved_special_token_0|>
def eat(self):
pass
print('%s is eating...' % self.name)
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Man(People):
def __init__(self, name, age, money):
super(Man, self).__init__(... | flexible | {
"blob_id": "6fdc9b2091652b05d6c1207d2f78b75c880fadda",
"index": 9084,
"step-1": "<mask token>\n\n\nclass People:\n <mask token>\n\n def eat(self):\n pass\n print('%s is eating...' % self.name)\n <mask token>\n <mask token>\n\n\nclass Man(People):\n\n def __init__(self, name, age, mo... | [
8,
10,
11,
12,
14
] |
import streamlit as st
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
username=st.text_input ("username")
upload=st.file_uploader("uploadfile",type=['csv'])
button=st.button("submit")
if button==True:
df=pd.read_csv(upload)
st.write(df.head())
fig = plt.figu... | normal | {
"blob_id": "72f1547ea7de78a5fe4b583523e592fa25c0ee77",
"index": 2467,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif button == True:\n df = pd.read_csv(upload)\n st.write(df.head())\n fig = plt.figure()\n my = fig.add_subplot(1, 1, 1)\n my.scatter(df['sepal.length'], df['petal.length']... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name='zuknuft', version='0.1', author='riotbib', author_email=
'riotbib@github', scripts=['zukunft.py'], install_requires=['bottle'])
<|reserved_special_token_1|>
from distutils.core import setup
setup(name='zuknuft',... | flexible | {
"blob_id": "638842cda666100ce197437cb354f66de77eb328",
"index": 8065,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='zuknuft', version='0.1', author='riotbib', author_email=\n 'riotbib@github', scripts=['zukunft.py'], install_requires=['bottle'])\n",
"step-3": "from distutils.core impor... | [
0,
1,
2,
3
] |
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | normal | {
"blob_id": "9ce406124d36c2baf09cf0d95fceb2ad63948919",
"index": 4801,
"step-1": "<mask token>\n\n\nclass UnexpectedFormatError(AttributeError):\n pass\n\n\n<mask token>\n\n\ndef get_meals(_mensa, date=None):\n result = requests.get(\n f'https://osnabrueck.my-mensa.de/essen.php?v=5121119&hyp=1&lang=... | [
6,
7,
8,
9,
10
] |
import numpy as np
#!pip install pygame
import pygame
#from copy import deepcopy
pygame.init()
#-----------
# Modifications (Matthieu, 15/04):
# Modification de la représentation du terrain du jeu. Il est maintenant représenté par une seule liste.
# un seul identifiant par coupe semble plus simple à gérer qu'un... | normal | {
"blob_id": "576d6bec4a91ba6f0597b76a5da5ad3ef6562b19",
"index": 9592,
"step-1": "<mask token>\n\n\nclass terrainDeJeu:\n\n def __init__(self, nCoupes, profondeur, nGrainesParCoupelle=4):\n self.plateau = np.full(2 * nCoupes, nGrainesParCoupelle)\n self.nGrainesParCoupelleInit = nGrainesParCoupe... | [
14,
20,
21,
24,
26
] |
import string
import random
import os
from threading import Thread
class Process(Thread):
def __init__(self):
Thread.__init__(self)
def run(self):
while True:
prenom = id_generator(random.randint(4, 8))
nom = id_generator(random.randint(4, 8))
password = id_... | normal | {
"blob_id": "b9c058bdb04df93beb379d05939b00f4db423cd3",
"index": 452,
"step-1": "import string\nimport random\nimport os\nfrom threading import Thread\n\nclass Process(Thread):\n def __init__(self):\n Thread.__init__(self)\n\n def run(self):\n while True:\n prenom = id_generator(ra... | [
0
] |
<|reserved_special_token_0|>
def who_win_line(line):
elements = set(line)
if '.' in elements:
return '.'
elements.discard('T')
if len(elements) >= 2:
return 'D'
else:
return elements.pop()
def who_win_tic_tac_toe(original_rows):
board_full = True
rows = [row[0:TTT... | flexible | {
"blob_id": "2e041e33b5c34c2bddc72b36ff641817f1e21db2",
"index": 3735,
"step-1": "<mask token>\n\n\ndef who_win_line(line):\n elements = set(line)\n if '.' in elements:\n return '.'\n elements.discard('T')\n if len(elements) >= 2:\n return 'D'\n else:\n return elements.pop()\n... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def dataframe_to_numpy(dataframe):
numpy_array = dataframe.to_numpy()
return numpy_array
<|reserved_special_token_0|>
def data_slice(data, num_of_data):
data = data[:, 1:num_of_data + 1]
return data
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def loa... | flexible | {
"blob_id": "b63dc8b9aa2f0593a4a7eb52a722a9c4da6c9e08",
"index": 7804,
"step-1": "<mask token>\n\n\ndef dataframe_to_numpy(dataframe):\n numpy_array = dataframe.to_numpy()\n return numpy_array\n\n\n<mask token>\n\n\ndef data_slice(data, num_of_data):\n data = data[:, 1:num_of_data + 1]\n return data\... | [
2,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def HP(Di, beta):
"""
Function that calculates shannon entropy
"""
P = np.exp(-Di * beta)
sumP = np.sum(P)
Pi = P / sumP
Hi = -np.sum(Pi * np.log2(Pi))
return Hi, Pi
<|reserved_special_token_1|>... | flexible | {
"blob_id": "0b05b027e3c3147aa2b9c35a0bdc33633ba6e658",
"index": 7129,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef HP(Di, beta):\n \"\"\"\n Function that calculates shannon entropy\n \"\"\"\n P = np.exp(-Di * beta)\n sumP = np.sum(P)\n Pi = P / sumP\n Hi = -np.sum(Pi * np.... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
@given('I want to send an integer')
def step_impl(context):
pass
<|reserved_special_token_0|>
@given('I want to send two integers with one channel')
def step_impl(context):
pass
@given('I want to send two floats with one channel')
def step_impl(context):
pass
<|reserve... | flexible | {
"blob_id": "3770e59c5bd6837a0fb812f80c6549024e06a9e4",
"index": 5957,
"step-1": "<mask token>\n\n\n@given('I want to send an integer')\ndef step_impl(context):\n pass\n\n\n<mask token>\n\n\n@given('I want to send two integers with one channel')\ndef step_impl(context):\n pass\n\n\n@given('I want to send t... | [
8,
10,
12,
13,
15
] |
"""
챕터: day4
주제: 반복문(for문)
문제: 1에서 100까지 합을 구하여 출력하시오.
작성자: 한현수
작성일: 2018.9.20.
"""
result = 0
for i in range(101):
result += i
print(result) | normal | {
"blob_id": "d2754099adebdb4bd2b028fdf9015571ad773754",
"index": 9313,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(101):\n result += i\nprint(result)\n",
"step-3": "<mask token>\nresult = 0\nfor i in range(101):\n result += i\nprint(result)\n",
"step-4": "\"\"\"\n챕터: day4\n주제:... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class DateTimeEncoder(json.JSONEncoder):
def default(self, z):
if isinstance(z, datetime.datetime):
return str(z)
else:
return super().default(z)
<|reserved_special_token_0|>
def FindWorkload(waclient, workloadName):
try:
respon... | flexible | {
"blob_id": "c5e003d625d7798eaf4ef5bca28f6311edccb316",
"index": 7235,
"step-1": "<mask token>\n\n\nclass DateTimeEncoder(json.JSONEncoder):\n\n def default(self, z):\n if isinstance(z, datetime.datetime):\n return str(z)\n else:\n return super().default(z)\n\n\n<mask token... | [
13,
15,
16,
18,
19
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_token_from_request(request):
token_tuple = request.COOKIES.get('money_api_token')
matches = re.search('(<Token: (\\S*)>)', token_tuple)
token = matches.groups(0)[1]
return token
<|reserved_special_token... | flexible | {
"blob_id": "2187f38dc9b14ecc355e98fe15d36fdefd548f04",
"index": 1159,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_token_from_request(request):\n token_tuple = request.COOKIES.get('money_api_token')\n matches = re.search('(<Token: (\\\\S*)>)', token_tuple)\n token = matches.groups... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class GIFTCommand(BaseInterface):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, **inputs):
super(GIFTComm... | flexible | {
"blob_id": "fef1cf75de8358807f29cd06d2338e087d6f2d23",
"index": 9162,
"step-1": "<mask token>\n\n\nclass GIFTCommand(BaseInterface):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, **inputs):\n super(GIFTCommand, self).... | [
8,
10,
15,
16,
18
] |
__author__ = 'Administrator'
class People:
def __init__(self,name,age):
self.name = name
self.age = age
def eat(self):
pass
print("%s is eating..." % self.name)
def sleep(self):
print("%s is sleeping..." % self.name)
def talk(self):
print("%s is talki... | normal | {
"blob_id": "6fdc9b2091652b05d6c1207d2f78b75c880fadda",
"index": 9084,
"step-1": "<mask token>\n\n\nclass People:\n <mask token>\n\n def eat(self):\n pass\n print('%s is eating...' % self.name)\n <mask token>\n <mask token>\n\n\nclass Man(People):\n\n def __init__(self, name, age, mo... | [
8,
10,
11,
12,
14
] |
from pydub import AudioSegment
import sys
import tensorflow as tf
import numpy as np
from adwtmk.audio import Audio
from adwtmk.encoder import *
from adwtmk.decoder import *
class DAE(object):
def __init__(self,model_name):
self.model_name = model_name
self.process = 0
self.loss = 0
... | normal | {
"blob_id": "6f53702d9265a7fc57d2ec2e47dc35a0bc7a9f87",
"index": 9012,
"step-1": "<mask token>\n\n\nclass DAE(object):\n <mask token>\n <mask token>\n\n def fast_training(self, sound):\n self.core_size = 100\n self.batch_size = 1000\n self.Epoches = 50\n self._main(sound, 100... | [
4,
6,
9,
10,
12
] |
from django.contrib import admin
from django.urls import path
from django.conf.urls import url
from . import views
urlpatterns = [
path('admin/', admin.site.urls),
path(r'', views.index, name='index'),
]
| normal | {
"blob_id": "b0fad3847519bb18365a8cd4226d06e9d96a8308",
"index": 1258,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('admin/', admin.site.urls), path('', views.index, name=\n 'index')]\n",
"step-3": "from django.contrib import admin\nfrom django.urls import path\nfrom django.con... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
COG_QUOTAS = (30, 25, 20, 15, 10, 5, 2, 1), (45, 40, 35, 30, 25, 20, 15, 10)
COG_UNSEEN = 1
COG_BATTLED = 2
COG_DEFEATED = 3
COG_COMPLETE1 = 4
COG_COMPLETE2 = 5
<|reserved_special_token_1|>
# Fuck you Disyer. Stealing my fucking paypal. GET FUCKED: toontow... | flexible | {
"blob_id": "fdb680f12dfb4b29f25cfe4f7af80469dc4294cf",
"index": 2437,
"step-1": "<mask token>\n",
"step-2": "COG_QUOTAS = (30, 25, 20, 15, 10, 5, 2, 1), (45, 40, 35, 30, 25, 20, 15, 10)\nCOG_UNSEEN = 1\nCOG_BATTLED = 2\nCOG_DEFEATED = 3\nCOG_COMPLETE1 = 4\nCOG_COMPLETE2 = 5\n",
"step-3": "# Fuck you Disyer.... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Variables:
size: bytes
name: str
class cstruct:
structname: string
<|reserved_special_token_0|>
def cpreprosscssor():
maintokens = lexer(mainfile)
return
def cprocessor():
return
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserve... | flexible | {
"blob_id": "24187284ff3e03cf79b8545415005c71f9355ddc",
"index": 9062,
"step-1": "<mask token>\n\n\nclass Variables:\n size: bytes\n name: str\n\n\nclass cstruct:\n structname: string\n\n\n<mask token>\n\n\ndef cpreprosscssor():\n maintokens = lexer(mainfile)\n return\n\n\ndef cprocessor():\n r... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),
'../sherlock')))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import sys
import os
import subprocess as sp
from time import sleep
sys.p... | flexible | {
"blob_id": "8f7b1313ba31d761edcadac7b0d04b62f7af8dff",
"index": 4759,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__),\n '../sherlock')))\n",
"step-3": "<mask token>\nimport sys\nimport os\nimport subprocess as sp\nfrom time i... | [
0,
1,
2,
3
] |
import unittest
import math
from python.src.sort.insertion import Insertion
from python.src.sort.selection import Selection
from python.src.sort.shell import Shell
from python.test.util.utilities import Utilities
class ElementarySortTest(unittest.TestCase):
def setUp(self):
self.n = 1000
def test_in... | normal | {
"blob_id": "779ef8942bfb55bf017a8da9dfe34c03ac574a9a",
"index": 2591,
"step-1": "<mask token>\n\n\nclass ElementarySortTest(unittest.TestCase):\n <mask token>\n\n def test_insertion_sort(self):\n insertion = Insertion()\n actual = Utilities.generate_random_array(self.n)\n expected = l... | [
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class ComposePipelines:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ComposePipelines:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __ca... | flexible | {
"blob_id": "13c55c313c740edce48fc979e8956fdd018e8aab",
"index": 9716,
"step-1": "<mask token>\n\n\nclass ComposePipelines:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ComposePipelines:\n <mask token>\n <mask token>\n\n def __call__(self, image):\n ... | [
1,
2,
3,
4,
5
] |
import os
import datetime
import traceback
import json
import requests
import logging
from model import Product
from naver_api import naver_client_id, naver_client_secret
DEBUG = False
if not DEBUG:
logging.getLogger('boto3').setLevel(logging.WARNING)
logging.getLogger('botocore').setLevel(logging.WARNING)
... | normal | {
"blob_id": "76905171602cbeb53903a4b0259685288da3a083",
"index": 6365,
"step-1": "<mask token>\n\n\ndef lambda_handler(event, context):\n products = list(Product.scan(Product.do_crawl == True))\n for product in products:\n product.search_lowest_price()\n print('{} product(s) crawled'.format(len(p... | [
1,
2,
3,
4,
5
] |
import time
from selenium import webdriver
import os
from selenium.webdriver.common.by import By
with open("file.txt", "w") as file:
content = file.write("Tanyuhich")
try:
browser = webdriver.Chrome()
browser.get("http://suninjuly.github.io/file_input.html")
input1 = browser.find_element_by_name('... | normal | {
"blob_id": "03270285c6dc99d8dcb9804270421f36b573048c",
"index": 2863,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('file.txt', 'w') as file:\n content = file.write('Tanyuhich')\ntry:\n browser = webdriver.Chrome()\n browser.get('http://suninjuly.github.io/file_input.html')\n inpu... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(html.decode('utf-8'))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
seesion = requests.Session()
header = {'User-Agent':
'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/... | flexible | {
"blob_id": "8c652f30cd256912512b6b91d1682af7da0ff915",
"index": 8265,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(html.decode('utf-8'))\n",
"step-3": "<mask token>\nseesion = requests.Session()\nheader = {'User-Agent':\n 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like... | [
0,
1,
2,
3
] |
def prime_sieve(n):
if n==2: return [2]
elif n<2: return []
s=range(3,n+1,2)
mroot = n ** 0.5
half=(n+1)/2-1
i=0
m=3
while m <= mroot:
if s[i]:
j=(m*m-3)/2
s[j]=0
while j<half:
s[j]=0
j+=m
i=i+1
m=2*i+3
return [2]+[x for x in s if x]
ps = prime_sieve(1000000)
def get_primes_upto(n):
... | normal | {
"blob_id": "5771f49ad5254588f1683a8d45aa81ce472bb562",
"index": 30,
"step-1": "\ndef prime_sieve(n): \n\tif n==2: return [2]\n\telif n<2: return []\n\ts=range(3,n+1,2)\n\tmroot = n ** 0.5\n\thalf=(n+1)/2-1\n\ti=0\n\tm=3\n\twhile m <= mroot:\n\t\tif s[i]:\n\t\t\tj=(m*m-3)/2\n\t\t\ts[j]=0\n\t\t\twhile j<half:\n\t... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def lower_upper_confidence_intervals(avg, SD):
lower = avg - 2 * SD
upper = avg + 2 * SD
return lower, upper
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.append... | flexible | {
"blob_id": "d423b0bc6cd9ea9795317750141ad5f5eab01636",
"index": 1886,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef lower_upper_confidence_intervals(avg, SD):\n lower = avg - 2 * SD\n upper = avg + 2 * SD\n return lower, upper\n\n\n<mask token>\n",
"step-3": "<mask token>\nsys.path.a... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ax.plot(data['Date'], data['HCHFI'], label='HCHFI')
ax.plot(data['Date'], data['SHA'] / 2.67547, label='SSE Composite Index')
ax.plot(data['Date'], data['Hushen300 Index'] / 3.20393, label=
'Hushen300 Index')
plt.xlabel('Time/... | flexible | {
"blob_id": "91df15d6d89d070677704572d35218558317a6ec",
"index": 117,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nax.plot(data['Date'], data['HCHFI'], label='HCHFI')\nax.plot(data['Date'], data['SHA'] / 2.67547, label='SSE Composite Index')\nax.plot(data['Date'], data['Hushen300 Index'] / 3.20393, lab... | [
0,
1,
2,
3,
4
] |
import torch
import torch.nn.functional as F
import csv
class Net(torch.nn.Module):
def __init__(self, n_feature, n_hidden, n_output):
super(Net, self).__init__()
self.hidden = torch.nn.Linear(n_feature, n_hidden)
self.predict = torch.nn.Linear(n_hidden, n_output)
def forward(self, x... | normal | {
"blob_id": "e221553f866de8b3e175197a40982506bf8c1ef9",
"index": 205,
"step-1": "<mask token>\n\n\nclass Net(torch.nn.Module):\n\n def __init__(self, n_feature, n_hidden, n_output):\n super(Net, self).__init__()\n self.hidden = torch.nn.Linear(n_feature, n_hidden)\n self.predict = torch.n... | [
3,
4,
5,
6,
7
] |
SQL_INSERCION_COCHE = "INSERT INTO tabla_coches(marca, modelo, color, motor, precio) VALUES (%s,%s,%s,%s,%s);"
SQL_LISTADO_COCHES = "SELECT * FROM tabla_coches;"
| normal | {
"blob_id": "fd41e6d8530d24a8a564572af46078be77e8177f",
"index": 6573,
"step-1": "<mask token>\n",
"step-2": "SQL_INSERCION_COCHE = (\n 'INSERT INTO tabla_coches(marca, modelo, color, motor, precio) VALUES (%s,%s,%s,%s,%s);'\n )\nSQL_LISTADO_COCHES = 'SELECT * FROM tabla_coches;'\n",
"step-3": "SQL_INS... | [
0,
1,
2
] |
from math import sqrt
from Engine.regulators.PID import PID
from Engine.regulators.regulator_base_class import RegulatorBaseClass
from Engine.robot import Robot, MAX_LINEAR_ACCELERATION, MAX_ANGULAR_SPEED
from Util import Pose
from Util.geometry import clamp, normalize
from Util.pose import Position
from config.config... | normal | {
"blob_id": "98bf0a332a6753e500b24bed2af16fe4a1cb9568",
"index": 1560,
"step-1": "<mask token>\n\n\nclass RealVelocityController(RegulatorBaseClass):\n settings = {'kp': 10, 'ki': 0, 'kd': 1}\n v_d = 4\n emergency_break_constant = 0.4\n emergency_break_safety_factor = 1\n\n def __init__(self):\n ... | [
10,
11,
13,
14,
15
] |
no = int(input("Enter a number: "))
no = str(no)
rev = no[::-1]
if no==rev:
print(f"{no}--->{rev} Input is a palindrome")
else:
print(f"{no}--->{rev} Input is not a palindrome")
| normal | {
"blob_id": "020a41e7d3cc3f5adf3a38a6852dac6037595372",
"index": 2043,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif no == rev:\n print(f'{no}--->{rev} Input is a palindrome')\nelse:\n print(f'{no}--->{rev} Input is not a palindrome')\n",
"step-3": "no = int(input('Enter a number: '))\nno = s... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(friends)
print(friends[0])
print(friends[-1])
print(friends[-2])
<|reserved_special_token_1|>
friends = ['Vino', 'Ammu', 'Appu']
print(friends)
print(friends[0])
print(friends[-1])
print(friends[-2])
<|reserved_special_... | flexible | {
"blob_id": "8050b757c20da7ad8dd3c12a30b523b752d6a3ff",
"index": 9457,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(friends)\nprint(friends[0])\nprint(friends[-1])\nprint(friends[-2])\n",
"step-3": "friends = ['Vino', 'Ammu', 'Appu']\nprint(friends)\nprint(friends[0])\nprint(friends[-1])\nprint... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def add_logs_to_response(response):
response['logs'] = ClientLogger.get_logs()
ClientLogger.clear_logs()
return response
@app.route('/generate/melody', methods=['POST', 'OPTIONS'])
@crossdomain(origin='*')
def generate_melody():
ClientLogger.log('Generating new melody...... | flexible | {
"blob_id": "471cab65aac29f5b47de0ffef8f032dbbadf8dd0",
"index": 1877,
"step-1": "<mask token>\n\n\ndef add_logs_to_response(response):\n response['logs'] = ClientLogger.get_logs()\n ClientLogger.clear_logs()\n return response\n\n\n@app.route('/generate/melody', methods=['POST', 'OPTIONS'])\n@crossdomai... | [
6,
8,
9,
11,
12
] |
<|reserved_special_token_0|>
class BinaryTree:
<|reserved_special_token_0|>
def __init__(self, rootObj):
self.key = rootObj
self.leftChild = None
self.rightChild = None
self.parent = None
def insertLeft(self, newNode):
if self.leftChild == None:
self.l... | flexible | {
"blob_id": "5f48c7a68cb9734d84dee2cf8ff4d7be490cf328",
"index": 2888,
"step-1": "<mask token>\n\n\nclass BinaryTree:\n <mask token>\n\n def __init__(self, rootObj):\n self.key = rootObj\n self.leftChild = None\n self.rightChild = None\n self.parent = None\n\n def insertLeft(... | [
12,
19,
30,
31,
37
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('n:', end='')
<|reserved_special_token_0|>
print('a:', end='')
<|reserved_special_token_0|>
for i in range(n):
for j in range(i + 1, n):
for k in range(j + 1, n):
ai, aj, ak = sorted([a[i], a[j], a[k]])
if ai + aj > a... | flexible | {
"blob_id": "130f49028833bf57d7e4f9fbb0764801c3508c3b",
"index": 3055,
"step-1": "<mask token>\n",
"step-2": "print('n:', end='')\n<mask token>\nprint('a:', end='')\n<mask token>\nfor i in range(n):\n for j in range(i + 1, n):\n for k in range(j + 1, n):\n ai, aj, ak = sorted([a[i], a[j], ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for p in palabras:
print(palabras[p])
<|reserved_special_token_1|>
frase = 'todos somos promgramadores'
palabras = frase.split()
for p in palabras:
print(palabras[p])
<|reserved_special_token_1|>
frase = "todos somos... | flexible | {
"blob_id": "00c57e7e26a3181ab23697a25257aca479d9ee05",
"index": 5755,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor p in palabras:\n print(palabras[p])\n",
"step-3": "frase = 'todos somos promgramadores'\npalabras = frase.split()\nfor p in palabras:\n print(palabras[p])\n",
"step-4": "fra... | [
0,
1,
2,
3
] |
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