code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def problem127():
GOAL = 120000
rad = {}
for primes in genFactors(GOAL):
rad[product(primes)] = set(primes), product(set(primes))
def relprime(s, t):
return s & t == set()
found = 0
total... | flexible | {
"blob_id": "646f6a0afc3dc129250c26270dda4355b8cea080",
"index": 1003,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef problem127():\n GOAL = 120000\n rad = {}\n for primes in genFactors(GOAL):\n rad[product(primes)] = set(primes), product(set(primes))\n\n def relprime(s, t):\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class MostSpider(scrapy.Spider):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_to... | flexible | {
"blob_id": "3583ce664bc9f42ef8f751de8642997819e08e31",
"index": 7793,
"step-1": "<mask token>\n\n\nclass MostSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def downloa... | [
2,
4,
5,
6,
7
] |
import matplotlib; matplotlib.use('agg')
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
from uncertainties import ufloat
#Holt Werte aus Textdatei
I, U = np.genfromtxt('werte2.txt', unpack=True)
#Definiert Funktion mit der ihr fitten wollt (hier eine Gerade)
def f(x,... | normal | {
"blob_id": "4932a357cfd60cb65630345e75794ebf58b82c82",
"index": 8696,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmatplotlib.use('agg')\n<mask token>\n\n\ndef f(x, A, B):\n return A * x + B\n\n\n<mask token>\nplt.plot(x_plot, f(x_plot, *params), 'k-', label='Anpassungsfunktion',\n linewidth=0.5... | [
0,
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": "a5dff32dfbe93ba081144944381b96940da541ad",
"index": 7802,
"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 = [('doctor', '0... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Before PCA', final_df)
for i in pca_df.columns:
final_df[i] = pca_df[i]
print('After PCA', final_df)
<|reserved_special_token_0|>
final_df.iloc[:cut].to_csv('pca_stop_train_sig_wc.csv', header=False, index
=False)
f... | flexible | {
"blob_id": "f8bb2851192a53e94e503c0c63b17477878ad9a7",
"index": 6926,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Before PCA', final_df)\nfor i in pca_df.columns:\n final_df[i] = pca_df[i]\nprint('After PCA', final_df)\n<mask token>\nfinal_df.iloc[:cut].to_csv('pca_stop_train_sig_wc.csv', h... | [
0,
1,
2,
3,
4
] |
def merge_the_tools(string, k):
# your code goes here
num_sub_strings = len(string)/k
#print num_sub_strings
for idx in range(num_sub_strings):
print "".join(set(list(string[idx * k : (idx + 1) * k])))
| normal | {
"blob_id": "e95bda8be2294c295d89f1c035bc209128fa29c8",
"index": 228,
"step-1": "def merge_the_tools(string, k):\n # your code goes here\n num_sub_strings = len(string)/k\n #print num_sub_strings\n\n for idx in range(num_sub_strings):\n print \"\".join(set(list(string[idx * k : (idx + 1) * k])... | [
0
] |
import os
import cv2
import numpy as np
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoder
from numpy import array
import tensorflow as tf
TRAIN_DIR = 'C:/Users/vgg/untitled/MNIST/trainingSet/'
train_folder_list = array(os.listdir(TRAIN_DIR))
train_input = []
tr... | normal | {
"blob_id": "01339324ad1a11aff062e8b27efabf27c97157fb",
"index": 9908,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor index in range(len(train_folder_list)):\n path = os.path.join(TRAIN_DIR, train_folder_list[index])\n path = path + '/'\n img_list = os.listdir(path)\n for img in img_list:... | [
0,
1,
2,
3,
4
] |
#
# Copyright 2016 The BigDL Authors.
#
# 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 ... | normal | {
"blob_id": "ce69f7b7cf8c38845bfe589c83fdd6e43ab50912",
"index": 3708,
"step-1": "<mask token>\n\n\nclass Adam(Optimizer):\n <mask token>\n\n def __init__(self, learningrate: float=0.001, learningrate_decay: float\n =0.0, beta1: float=0.9, beta2: float=0.999, epsilon: float=1e-08\n ) ->None:\... | [
19,
29,
33,
35,
41
] |
<|reserved_special_token_0|>
def main():
r4m = Route4Me(API_KEY)
route = r4m.route
response = route.get_routes(limit=1, offset=0)
if isinstance(response, dict) and 'errors' in response.keys():
print('. '.join(response['errors']))
else:
route_id = response[0]['route_id']
pri... | flexible | {
"blob_id": "bc4684d255a46427f708d8ce8bda2e12fb8c8ffe",
"index": 238,
"step-1": "<mask token>\n\n\ndef main():\n r4m = Route4Me(API_KEY)\n route = r4m.route\n response = route.get_routes(limit=1, offset=0)\n if isinstance(response, dict) and 'errors' in response.keys():\n print('. '.join(respo... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
from django.shortcuts import get_object_or_404
from rest_framework import serializers
from tandlr.core.api.serializers import ModelSerializer
from tandlr.users.models import DeviceUser, User, UserSettings
from tandlr.utils.refresh_token import create_token
class LoginSerializer(serializers.S... | normal | {
"blob_id": "01900c1d14a04ee43553c8602a07e0c6ecfabded",
"index": 1803,
"step-1": "<mask token>\n\n\nclass LogoutSerializer(ModelSerializer):\n <mask token>\n <mask token>\n\n\n class Meta:\n model = DeviceUser\n fields = ['device_user_token', 'device_os', 'is_active']\n <mask token>\n ... | [
9,
11,
15,
17,
19
] |
#### про enumerate
##s = input()
##for index, letter in enumerate(s):
## print(index,':',letter)
#### то же что и
##for i in range(len(s)):
## print (i,':', s[i])
#### номер начала каждого слова
##st = input()
##for index, symbol in enumerate(st):
## if symbol == ' ' and index != len(st)-1 or index == 0 or in... | normal | {
"blob_id": "f4bfef2ee78b87184cc72666fade949f8f931fc3",
"index": 826,
"step-1": "#### про enumerate\n##s = input()\n##for index, letter in enumerate(s):\n## print(index,':',letter)\n#### то же что и\n##for i in range(len(s)):\n## print (i,':', s[i])\n\n#### номер начала каждого слова\n##st = input()\n##for... | [
1
] |
#! /usr/bin/env python
import roslib
roslib.load_manifest('learning_tf')
import rospy
import actionlib
from geometry_msgs.msg import Twist
from turtlesim.msg import Pose
from goal.msg import moveAction, moveGoal
if __name__ == '__main__':
rospy.init_node('move_client')
client = actionlib.SimpleActionClient('... | normal | {
"blob_id": "791935f63f7a0ab2755ad33369d2afa8c10dffbb",
"index": 4708,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nroslib.load_manifest('learning_tf')\n<mask token>\nif __name__ == '__main__':\n rospy.init_node('move_client')\n client = actionlib.SimpleActionClient('moveTo', turtlesim_)\n cli... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def word_count(phrase):
phrase = re.sub('\\W+|_', ' ', phrase.lower(), flags=re.UNICODE)
word_list = phrase.split()
wordfreq = [word_list.count(p) for p in word_list]
return dict(zip(word_list, wordfreq))
<|res... | flexible | {
"blob_id": "e12905efa0be7d69e2719c05b40d18c50e7e4b2e",
"index": 4933,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef word_count(phrase):\n phrase = re.sub('\\\\W+|_', ' ', phrase.lower(), flags=re.UNICODE)\n word_list = phrase.split()\n wordfreq = [word_list.count(p) for p in word_list]... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(int(input())):
imp = input()
if bool(re.search('[a-zA-Z0-9]{10}', imp)) and bool(re.search(
'([A-Z].*){2}', imp)) and bool(re.search('([0-9].*){3}', imp)
) and not bool(re.search('.*(.).*\\1'... | flexible | {
"blob_id": "3a5c8ee49c50820cea201c088acca32e018c1501",
"index": 3715,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(int(input())):\n imp = input()\n if bool(re.search('[a-zA-Z0-9]{10}', imp)) and bool(re.search(\n '([A-Z].*){2}', imp)) and bool(re.search('([0-9].*){3}', imp)... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def on_connect(client, userdata, flags, rc):
print('Conectado (%s)' % client._client_id)
client.subscribe(topic='unimet/#', qos=0)
def ventasTIENDA(client, userdata, message):
a = json.loads(message.payload)
print(a)
cur = conn.cursor()
sql = (
'INSERT IN... | flexible | {
"blob_id": "f1b36e3ce3189c8dca2e41664ac1a6d632d23f79",
"index": 5078,
"step-1": "<mask token>\n\n\ndef on_connect(client, userdata, flags, rc):\n print('Conectado (%s)' % client._client_id)\n client.subscribe(topic='unimet/#', qos=0)\n\n\ndef ventasTIENDA(client, userdata, message):\n a = json.loads(me... | [
3,
4,
5,
6,
7
] |
#!/usr/bin/env python
'''
State Machine for the Flare task
'''
import roslib
import rospy
import actionlib
from rospy.timer import sleep
import smach
import smach_ros
from dynamic_reconfigure.server import Server
import math
import os
import sys
import numpy as np
from bbauv_msgs.msg import *
from bbauv_msgs.srv... | normal | {
"blob_id": "0bb2a6ebbf75fae3466c34a435a531fabdc07f62",
"index": 2984,
"step-1": "<mask token>\n\n\nclass Disengage(smach.State):\n\n def __init__(self, flare_task):\n smach.State.__init__(self, outcomes=['start_complete',\n 'complete_outcome', 'aborted'])\n self.flare = flare_task\n ... | [
12,
13,
15,
16,
20
] |
# -*- coding: utf-8 -*-
"""
测试如何使用python的pymongo模块操作MongoDB
@author: hch
@date : 2020/10/8
"""
import logging
import time
import traceback
from pprint import pprint
from pymongo import MongoClient
from pymongo.cursor import Cursor
from pymongo.results import DeleteResult, InsertOneResult, UpdateResult
class MongoT... | normal | {
"blob_id": "b46fe26f1a3c9e93e735b752e54132bd95408251",
"index": 2451,
"step-1": "<mask token>\n\n\nclass MongoTest:\n <mask token>\n try:\n client = MongoClient(\n 'mongodb://root:root@localhost:27017/test?authSource=admin')\n print('init mongo client:', client)\n except Except... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(len(bull_list)):
bull_list.append(int(bull_str[i]))
<|reserved_special_token_0|>
while True:
flag += 1
for i in range(len(bull_list)):
if bull_list[i] == 1:
for j in range(bull_list.i... | flexible | {
"blob_id": "4d30f4294a9f3aab8cae20dca9d280c53b37ed25",
"index": 1471,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(len(bull_list)):\n bull_list.append(int(bull_str[i]))\n<mask token>\nwhile True:\n flag += 1\n for i in range(len(bull_list)):\n if bull_list[i] == 1:\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class DataManager(ABC):
def __init__(self):
self.__myHousekeeper = housekeeper.instance_class()
self.__config_filename = 'tickers_config.json'
self.__dir_list = ['Data', 'Tickers', 'Dummy1']
self.__upper_stages = 0
self.__tickers_config_list = ... | flexible | {
"blob_id": "e77e0791ddf211807566528e9532eebb54db43b5",
"index": 5550,
"step-1": "<mask token>\n\n\nclass DataManager(ABC):\n\n def __init__(self):\n self.__myHousekeeper = housekeeper.instance_class()\n self.__config_filename = 'tickers_config.json'\n self.__dir_list = ['Data', 'Tickers'... | [
30,
34,
35,
40,
41
] |
<|reserved_special_token_0|>
def getCursor():
cursor = db.cursor()
return cursor
class Classify(object):
def __init__(self, **args):
self.cl_name = args['cl_name']
self.cl_grade = args['cl_grade'] is None if 0 else args['cl_grade']
self.cl_fid = args['cl_fid']
if 'pictur... | flexible | {
"blob_id": "6d51a088ba81cfc64c2e2a03f98b0ee354eda654",
"index": 4292,
"step-1": "<mask token>\n\n\ndef getCursor():\n cursor = db.cursor()\n return cursor\n\n\nclass Classify(object):\n\n def __init__(self, **args):\n self.cl_name = args['cl_name']\n self.cl_grade = args['cl_grade'] is No... | [
7,
8,
9,
10,
12
] |
# Mac File
import platform
import os
def Mac(SystemArray = [], ProcessorArray = []):
# System Info
OSName = str()
OSVersionMajor = str()
OSArchitecture = str()
# Processor Info
command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'
ProcInfo = os.popen(command).read().strip()
ProcNam... | normal | {
"blob_id": "f652fa6720582d50f57f04d82fb2f5af17859ebd",
"index": 8211,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef Mac(SystemArray=[], ProcessorArray=[]):\n OSName = str()\n OSVersionMajor = str()\n OSArchitecture = str()\n command = '/usr/sbin/sysctl -n machdep.cpu.brand_string'\n... | [
0,
1,
2,
3
] |
from django.contrib import admin
from .models import Profile, Address
admin.site.register(Profile)
admin.site.register(Address)
| normal | {
"blob_id": "4cc6a9c48e174b33ed93d7bda159fcc3a7b59d4c",
"index": 6727,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Profile)\nadmin.site.register(Address)\n",
"step-3": "from django.contrib import admin\nfrom .models import Profile, Address\nadmin.site.register(Profile)\nadmin.sit... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class PeriodoUpdateView(LoginRequiredMixin, UpdateView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get_form_kwargs(self, *args, **kwargs):
kwargs = super(PeriodoUpdateView, self).get_form_kwargs(*args, **kwargs
... | flexible | {
"blob_id": "a9ebd323d4b91c7e6a7e7179329ae80e22774927",
"index": 4843,
"step-1": "<mask token>\n\n\nclass PeriodoUpdateView(LoginRequiredMixin, UpdateView):\n <mask token>\n <mask token>\n <mask token>\n\n def get_form_kwargs(self, *args, **kwargs):\n kwargs = super(PeriodoUpdateView, self).ge... | [
67,
76,
95,
101,
108
] |
<|reserved_special_token_0|>
class CoordinatesDataParser:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CoordinatesDataParser:
def __init__(self):
return
<|reserved_special_token_0|>
<|reserved_special_token_1|... | flexible | {
"blob_id": "7d5f41cfa2d5423c6db2678f1eb8160638b50c02",
"index": 1835,
"step-1": "<mask token>\n\n\nclass CoordinatesDataParser:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CoordinatesDataParser:\n\n def __init__(self):\n return\n <mask token>\n",
"step-3": "<mask ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class LR(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class RNN(nn.Module):
def __init__(self, feature_nums, hidden_dims, bi_lstm, out_dims=1):
super(RNN, self).__init__()
self.feature_nums = feature_nums
self.hidden_dims = h... | flexible | {
"blob_id": "2c2b075f9ea9e8d6559e44ad09d3e7767c48205e",
"index": 6772,
"step-1": "<mask token>\n\n\nclass LR(nn.Module):\n <mask token>\n <mask token>\n\n\nclass RNN(nn.Module):\n\n def __init__(self, feature_nums, hidden_dims, bi_lstm, out_dims=1):\n super(RNN, self).__init__()\n self.fea... | [
7,
9,
10,
11,
12
] |
#-*- coding:utf-8 -*-
from xml.etree import ElementTree
from xml.etree.ElementTree import Element
_exception = None
import os
class xmlSp:
def addNode(self,parentNode,childNode):
parentNode.append(childNode)
def createChildNode(self,key,value,propertyMap={}):
element... | normal | {
"blob_id": "0470f98247f8f835c0c052b01ddd7f1f7a515ab5",
"index": 5509,
"step-1": "<mask token>\n\n\nclass xmlSp:\n\n def addNode(self, parentNode, childNode):\n parentNode.append(childNode)\n\n def createChildNode(self, key, value, propertyMap={}):\n element = Element(key, propertyMap)\n ... | [
12,
13,
15,
16,
18
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Welcome to the Band Name Generator')
<|reserved_special_token_0|>
print('Your band name could be ', Band_name)
<|reserved_special_token_1|>
print('Welcome to the Band Name Generator')
city = input('Which city did you grew up in?\n')
pet = input('W... | flexible | {
"blob_id": "19962e94afdd3edf298b28b9954f479fefa3bba8",
"index": 8656,
"step-1": "<mask token>\n",
"step-2": "print('Welcome to the Band Name Generator')\n<mask token>\nprint('Your band name could be ', Band_name)\n",
"step-3": "print('Welcome to the Band Name Generator')\ncity = input('Which city did you ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Main:
<|reserved_special_token_0|>
def processaCSV(self, filename):
with open(filename, 'r', encoding='ISO-8859-1') as input_file:
self.concessao = {}
self.expansao = {}
for line in input_file.readlines():
attribut... | flexible | {
"blob_id": "c5f46be6d7214614892d227c76c75e77433a8fa9",
"index": 9517,
"step-1": "<mask token>\n\n\nclass Main:\n <mask token>\n\n def processaCSV(self, filename):\n with open(filename, 'r', encoding='ISO-8859-1') as input_file:\n self.concessao = {}\n self.expansao = {}\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
args = argparse.Namespace()
args.notray = False
traylauncher.start(args)
<|reserved_special_token_1|>
import argparse
import traylauncher
if __name__ == '__main__':
args = argparse.Nam... | flexible | {
"blob_id": "8faaf9eb2e78b7921dd1cac4772e2415671201c7",
"index": 8481,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n args = argparse.Namespace()\n args.notray = False\n traylauncher.start(args)\n",
"step-3": "import argparse\nimport traylauncher\nif __name__ == '_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('workRecord.txt') as fp:
for line in fp.readlines():
idx = line.rfind('x', len(line) - 8, len(line))
if idx >= 0:
sum += float(line.rstrip()[idx + 1:len(line)])
else:
s... | flexible | {
"blob_id": "b838d2230cb3f3270e86807e875df4d3d55438cd",
"index": 8891,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('workRecord.txt') as fp:\n for line in fp.readlines():\n idx = line.rfind('x', len(line) - 8, len(line))\n if idx >= 0:\n sum += float(line.rstrip()[... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.1 on 2017-12-01 16:51
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('monitor', '0001_initial'),
]
operations = [
migrations.RemoveField(
... | normal | {
"blob_id": "1573af9cdf4817acbe80031e22489386ea7899cf",
"index": 4782,
"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 = [('monitor', '... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
# <nbformat>3.0</nbformat>
# <codecell>
import pylab as pl
import pymc as mc
import book_graphics
reload(book_graphics)
# <markdowncell>
# Uniform points in an $n$-dimensional ball
# =========================================
#
# This notebook implements and compares samplers ... | normal | {
"blob_id": "8283bdab023e22bba3d8a05f8bda0014ee19adee",
"index": 4286,
"step-1": "<mask token>\n\n\nclass UniformBall(mc.Gibbs):\n\n def __init__(self, stochastic, others, verbose=None):\n self.others = others\n self.conjugate = True\n mc.Gibbs.__init__(self, stochastic, verbose)\n\n d... | [
3,
6,
7,
8,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(t)
print(t[:2])
print(t[1:])
<|reserved_special_token_0|>
print(t2)
print(t3)
print(t2 + t3)
<|reserved_special_token_1|>
t = '코스모스', '민들레', '국화'
print(t)
print(t[:2])
print(t[1:])
t2 = 1, 2, 3
t3 = 4,
print(t2)
print(t3)... | flexible | {
"blob_id": "45fcafdd30f890ddf5eaa090152fde2e2da4dbef",
"index": 732,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(t)\nprint(t[:2])\nprint(t[1:])\n<mask token>\nprint(t2)\nprint(t3)\nprint(t2 + t3)\n",
"step-3": "t = '코스모스', '민들레', '국화'\nprint(t)\nprint(t[:2])\nprint(t[1:])\nt2 = 1, 2, 3\nt3 = ... | [
0,
1,
2,
3
] |
from .base import Sort
| normal | {
"blob_id": "de3a96d46b7eaf198b33efe78b21ef0207dcc609",
"index": 8424,
"step-1": "<mask token>\n",
"step-2": "from .base import Sort\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
class PlayerHand:
<|reserved_special_token_0|>
def __init__(self, concealed, exposed=None, initial_update=True):
if isinstance(concealed, str):
concealed = tiles.tiles(concealed)
if isinstance(concealed, Counter):
self._concealed = conceale... | flexible | {
"blob_id": "5b860144a592505fea3a8849f5f5429a39ab9053",
"index": 7299,
"step-1": "<mask token>\n\n\nclass PlayerHand:\n <mask token>\n\n def __init__(self, concealed, exposed=None, initial_update=True):\n if isinstance(concealed, str):\n concealed = tiles.tiles(concealed)\n if isin... | [
18,
19,
21,
23,
25
] |
import json
data = '{"var1": "harry", "var2":56}'
parsed = json.loads(data)
print(parsed['var1'])
# data2 = {"channel_name": "Chill_Out",
# "Cars": ["BMW", "Audi a8", "ferrari"],
# "fridge": ("loki", "Aalu", "pasta"),
# "isbad": False
# }
# jscomp = json.dumps(data2)
# print(jscomp)
| normal | {
"blob_id": "f0f9541eba29b4488c429c889f3b346d53d0239d",
"index": 7193,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(parsed['var1'])\n",
"step-3": "<mask token>\ndata = '{\"var1\": \"harry\", \"var2\":56}'\nparsed = json.loads(data)\nprint(parsed['var1'])\n",
"step-4": "import json\ndata = '{\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
smodelsOutput = {'OutputStatus': {'sigmacut': 0.01, 'minmassgap': 5.0,
'maxcond': 0.2, 'ncpus': 1, 'file status': 1, 'decomposition status': 1,
'warnings': 'Input file ok', 'input file':
'inputFiles/scanExample/slha/100968509.slha', 'database vers... | flexible | {
"blob_id": "94d303716eac7fa72370435fe7d4d1cdac0cdc48",
"index": 6151,
"step-1": "<mask token>\n",
"step-2": "smodelsOutput = {'OutputStatus': {'sigmacut': 0.01, 'minmassgap': 5.0,\n 'maxcond': 0.2, 'ncpus': 1, 'file status': 1, 'decomposition status': 1,\n 'warnings': 'Input file ok', 'input file':\n ... | [
0,
1
] |
<|reserved_special_token_0|>
def format(t):
A = str(t // 600)
tem = t // 10
tem = tem % 60
B = str(tem // 10)
C = str(tem % 10)
D = str(t % 10)
return A + ':' + B + C + '.' + D
<|reserved_special_token_0|>
def reset():
global successcount, totalstopcount, count, F
count = 0
... | flexible | {
"blob_id": "bb198978ffc799bb43acf870467496e1dcc54d4b",
"index": 3710,
"step-1": "<mask token>\n\n\ndef format(t):\n A = str(t // 600)\n tem = t // 10\n tem = tem % 60\n B = str(tem // 10)\n C = str(tem % 10)\n D = str(t % 10)\n return A + ':' + B + C + '.' + D\n\n\n<mask token>\n\n\ndef res... | [
4,
5,
6,
7,
10
] |
import dash
import dash_html_components as html
app = dash.Dash(__name__)
app.layout = html.H1("Hello dashboard")
if __name__ == "__main__":
app.run_server(debug=False, port=8080, host="127.0.0.1")
| normal | {
"blob_id": "b66f588149d160c119f9cc24af3acb9f64432d6e",
"index": 6014,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n app.run_server(debug=False, port=8080, host='127.0.0.1')\n",
"step-3": "<mask token>\napp = dash.Dash(__name__)\napp.layout = html.H1('Hello dashboard')\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(s)
<|reserved_special_token_1|>
s = 'Daum KaKao'
s = s[5:] + ' ' + s[:4]
print(s)
<|reserved_special_token_1|>
s = 'Daum KaKao'
# s_split = s.split()
# s = s_split[1] + ' ' + s_split[0]
s = s[5:] + ' ' + s[:4]
print(s) | flexible | {
"blob_id": "32c62bb8b6e4559bb7dfc67f4311bc8e71e549c9",
"index": 6942,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(s)\n",
"step-3": "s = 'Daum KaKao'\ns = s[5:] + ' ' + s[:4]\nprint(s)\n",
"step-4": "s = 'Daum KaKao'\n# s_split = s.split()\n# s = s_split[1] + ' ' + s_split[0]\ns = s[5:] + ' ... | [
0,
1,
2,
3
] |
import time
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtSql import *
from PyQt5.QtWidgets import *
from qgis.core import QgsFeature, QgsGeometry, QgsProject
from shapely import wkb
print(__name__)
# Function definition
def TicTocGenerator():
# Generator that returns time differences
ti... | normal | {
"blob_id": "73ff1444b5ab1469b616fe449ee6ab93acbbf85a",
"index": 918,
"step-1": "import time\nfrom PyQt5.QtCore import *\nfrom PyQt5.QtGui import *\nfrom PyQt5.QtSql import *\nfrom PyQt5.QtWidgets import *\nfrom qgis.core import QgsFeature, QgsGeometry, QgsProject\nfrom shapely import wkb\n\nprint(__name__)\n\n\... | [
0
] |
# coding=utf-8
# __author__ = 'liwenxuan'
import random
chars = "1234567890ABCDEF"
ids = ["{0}{1}{2}{3}".format(i, j, k, l) for i in chars for j in chars for k in chars for l in chars]
def random_peer_id(prefix="F"*8, server_id="0000"):
"""
用于生成随机的peer_id(后四位随机)
:param prefix: 生成的peer_id的前八位, 测试用prefix为... | normal | {
"blob_id": "c77ca4aa720b172d75aff2ceda096a4969057a00",
"index": 9735,
"step-1": "# coding=utf-8\n# __author__ = 'liwenxuan'\n\nimport random\n\nchars = \"1234567890ABCDEF\"\nids = [\"{0}{1}{2}{3}\".format(i, j, k, l) for i in chars for j in chars for k in chars for l in chars]\n\n\ndef random_peer_id(prefix=\"F... | [
0
] |
<|reserved_special_token_0|>
def register(request):
if request.method == 'GET':
return render(request, 'home/home.html')
else:
name = request.POST['name']
username = request.POST['uname']
email = request.POST['email']
password = request.POST['password']
if name ... | flexible | {
"blob_id": "4cb601d7fc4023e145c6d510d27507214ddbd2d3",
"index": 809,
"step-1": "<mask token>\n\n\ndef register(request):\n if request.method == 'GET':\n return render(request, 'home/home.html')\n else:\n name = request.POST['name']\n username = request.POST['uname']\n email = r... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def permissao():
editor = False
for row in session.auth.user_groups:
grupo = session.auth.user_groups[row]
if grupo == 'gerenciador' or grupo == 'administrador':
editor = True
return editor
<|reserved_special_token_1|... | flexible | {
"blob_id": "70de2bed00aabe3805c3a19da004713d4109568a",
"index": 9036,
"step-1": "<mask token>\n",
"step-2": "def permissao():\n editor = False\n for row in session.auth.user_groups:\n grupo = session.auth.user_groups[row]\n if grupo == 'gerenciador' or grupo == 'administrador':\n ... | [
0,
1,
2
] |
#!/usr/bin/python
import sys, os, glob, numpy
wd = os.path.dirname(os.path.realpath(__file__))
sys.path.append(wd + '/python_speech_features')
from features import mfcc, logfbank
import scipy.io.wavfile as wav
DIR = '/home/quiggles/Desktop/513music/single-genre/classify-me/subset'
OUTDIR = wd + '/songdata/subset'
#... | normal | {
"blob_id": "cca1a491e2a48b4b0c7099a6c54e528158ef30bb",
"index": 5189,
"step-1": "<mask token>\n\n\ndef getMFCC(rate, sig):\n mfcc_feat = mfcc(sig, rate)\n return numpy.concatenate(getQuartileMeans(mfcc_feat))\n\n\ndef getLogFBank(rate, sig):\n logfbank_feat = logfbank(sig, rate)\n return numpy.conca... | [
3,
7,
8,
9,
10
] |
def postfix(expression):
operators, stack = '+-*/', []
for item in expression.split():
if item not in operators:
stack.append(item)
else:
operand_1, operand_2 = stack.pop(), stack.pop()
stack.append(str(eval(operand_2 + item + operand_1)))
return int(float... | normal | {
"blob_id": "3ae0149af78216d6cc85313ebaa6f7cd99185c05",
"index": 531,
"step-1": "<mask token>\n",
"step-2": "def postfix(expression):\n operators, stack = '+-*/', []\n for item in expression.split():\n if item not in operators:\n stack.append(item)\n else:\n operand_1,... | [
0,
1
] |
<|reserved_special_token_0|>
def generate_questions(n):
for _ in range(n):
x = random.randint(11, 100)
print(x)
inp = int(input())
if inp == x ** 2:
continue
else:
print('Wrong! the right answer is: {}'.format(x ** 2))
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "e98f28199075e55ddad32d9127f917c982e1e29d",
"index": 8167,
"step-1": "<mask token>\n\n\ndef generate_questions(n):\n for _ in range(n):\n x = random.randint(11, 100)\n print(x)\n inp = int(input())\n if inp == x ** 2:\n continue\n else:\n pr... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_iam_token(iam_url, oauth_token):
response = post(iam_url, json={'yandexPassportOauthToken': oauth_token})
json_data = json.loads(response.text)
if json_data is not None and 'iamToken' in json_data:
return json_data['iamToken']
return None
<|reserved_speci... | flexible | {
"blob_id": "360063940bb82defefc4195a5e17c9778b47e9e5",
"index": 792,
"step-1": "<mask token>\n\n\ndef get_iam_token(iam_url, oauth_token):\n response = post(iam_url, json={'yandexPassportOauthToken': oauth_token})\n json_data = json.loads(response.text)\n if json_data is not None and 'iamToken' in json... | [
1,
2,
3,
5,
6
] |
# coding:utf-8
def application(env,handle_headers):
status="200"
response_headers=[
('Server','')
]
return "" | normal | {
"blob_id": "8c318d7152bfdf2bc472258eb87dfa499b743193",
"index": 797,
"step-1": "<mask token>\n",
"step-2": "def application(env, handle_headers):\n status = '200'\n response_headers = [('Server', '')]\n return ''\n",
"step-3": "# coding:utf-8\n\n\ndef application(env,handle_headers):\n status=\"... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Ui_Form1(QtGui.QWidget):
def __init__(self):
QtGui.QWidget.__init__(self)
self.setupUi(self)
if os.path.exists(os.getcwd() + '\\settings.ini') and os.path.getsize(
os.getcwd() + '\\settings.ini') > 0:
with open(os.getcwd() + '\\se... | flexible | {
"blob_id": "cef4568b4568bceeedca6d57c0ccacfaae67c061",
"index": 147,
"step-1": "<mask token>\n\n\nclass Ui_Form1(QtGui.QWidget):\n\n def __init__(self):\n QtGui.QWidget.__init__(self)\n self.setupUi(self)\n if os.path.exists(os.getcwd() + '\\\\settings.ini') and os.path.getsize(\n ... | [
15,
20,
21,
22,
28
] |
#!/usr/bin/env python
# coding: utf-8
import numpy as np
import copy
import sys
def mutate(genotype_in, mut_matrix):
genotype_out = np.zeros(8)
for i in range(8):
rand_vec = np.random.choice(8, size=int(genotype_in[i]), p=mut_matrix[i,:])
genotype_out+=np.bincount(rand_vec, minlength=8)
r... | normal | {
"blob_id": "9065842a8e90c833278547310f027bc63c7a9a47",
"index": 7557,
"step-1": "<mask token>\n\n\ndef mutate(genotype_in, mut_matrix):\n genotype_out = np.zeros(8)\n for i in range(8):\n rand_vec = np.random.choice(8, size=int(genotype_in[i]), p=\n mut_matrix[i, :])\n genotype_ou... | [
7,
8,
10,
11,
12
] |
<|reserved_special_token_0|>
def press(key):
logging.info(key)
def work():
with Listener(on_press=press) as listener:
listener.join()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
logging.basicConfig(format='%(asctime)s:%(message)s')
<|reserved_special_t... | flexible | {
"blob_id": "3dc2d9a5e37ce1f546c0478de5a0bb777238ad00",
"index": 4306,
"step-1": "<mask token>\n\n\ndef press(key):\n logging.info(key)\n\n\ndef work():\n with Listener(on_press=press) as listener:\n listener.join()\n\n\n<mask token>\n",
"step-2": "<mask token>\nlogging.basicConfig(format='%(ascti... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', views.index, name='index'), path('sign', views.sign,
name='sign'), path('reset_password/', auth_views.PasswordResetView.
as_view(template_name='password_reset.html'), name='password_reset'),
pat... | flexible | {
"blob_id": "7e35c35c8ef443155c45bdbff4ce9ad07b99f144",
"index": 9983,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.index, name='index'), path('sign', views.sign,\n name='sign'), path('reset_password/', auth_views.PasswordResetView.\n as_view(template_name='password_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_application_name(default=_marker, prompt=True):
global _selected_app
result = None
try:
result = fileoperations.get_config_setting('global', 'application_name'
)
except NotInitializedError:
if prompt:
result = _get_applicatio... | flexible | {
"blob_id": "653c8db6741a586694d91bd9928d8326cce9e41d",
"index": 6373,
"step-1": "<mask token>\n\n\ndef get_application_name(default=_marker, prompt=True):\n global _selected_app\n result = None\n try:\n result = fileoperations.get_config_setting('global', 'application_name'\n )\n e... | [
2,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 22 20:21:16 2018
@author: Yijie
"""
#Q4:
#(1)
yours = ['Yale','MIT','Berkeley']
mine = ['Harvard','CAU','Stanford']
ours1 = mine + yours
ours2=[]
ours2.append(mine)
ours2.append(yours)
print(ours1)
print(ours2)
# Difference:the print out results indicate that the list 'o... | normal | {
"blob_id": "bf65d4a4e066e3e06b888d4b9ed49e10e66b4e78",
"index": 8145,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nours2.append(mine)\nours2.append(yours)\nprint(ours1)\nprint(ours2)\n<mask token>\nprint(ours1)\nprint(ours2)\n",
"step-3": "<mask token>\nyours = ['Yale', 'MIT', 'Berkeley']\nmine = ['... | [
0,
1,
2,
3
] |
# from suiron.core.SuironIO import SuironIO
# import cv2
# import os
# import time
# import json
# import numpy as np
# suironio = SuironIO(serial_location='/dev/ttyUSB0', baudrate=57600, port=5050)
# if __name__ == "__main__":
# while True:
# # suironio.record_inputs()
# print('turn90')
# suiro... | normal | {
"blob_id": "bf8ffe603b7c1e90deed6a69500ea5b7671e7270",
"index": 879,
"step-1": "<mask token>\n\n\ndef visualize_data(filename, width=72, height=48, depth=3, cnn_model=None):\n \"\"\"\n When cnn_model is specified it'll show what the cnn_model predicts (red)\n as opposed to what inputs it actually recei... | [
1,
2,
3,
4,
5
] |
# ------------------------------------------------------------
# calclex.py
#
# tokenizer for a simple expression evaluator for
# numbers and +,-,*,/
# ------------------------------------------------------------
import ply.lex as lex
# Regular expression rules for simple tokens
t_PLUS = r'\+'
t_MINUS = r'-'... | normal | {
"blob_id": "1530f1711be6313b07df680721daf4cb0a84edc0",
"index": 5502,
"step-1": "# ------------------------------------------------------------\n# calclex.py\n#\n# tokenizer for a simple expression evaluator for\n# numbers and +,-,*,/\n# ------------------------------------------------------------\nimport ply.l... | [
0
] |
<|reserved_special_token_0|>
class MongoTest:
<|reserved_special_token_0|>
try:
client = MongoClient(
'mongodb://root:root@localhost:27017/test?authSource=admin')
print('init mongo client:', client)
except Exception as e:
logging.exception(e)
@classmethod
def g... | flexible | {
"blob_id": "b46fe26f1a3c9e93e735b752e54132bd95408251",
"index": 2451,
"step-1": "<mask token>\n\n\nclass MongoTest:\n <mask token>\n try:\n client = MongoClient(\n 'mongodb://root:root@localhost:27017/test?authSource=admin')\n print('init mongo client:', client)\n except Except... | [
6,
7,
8,
9,
10
] |
import unittest
from unittest.mock import ANY, MagicMock, call
from streamlink import Streamlink
from streamlink.plugins.funimationnow import FunimationNow
from tests.plugins import PluginCanHandleUrl
class TestPluginCanHandleUrlFunimationNow(PluginCanHandleUrl):
__plugin__ = FunimationNow
should_match = [
... | normal | {
"blob_id": "266add60be2b6c2de5d53504cbabf754aa62d1b0",
"index": 9806,
"step-1": "<mask token>\n\n\nclass TestPluginFunimationNow(unittest.TestCase):\n\n def test_arguments(self):\n from streamlink_cli.main import setup_plugin_args\n session = Streamlink()\n parser = MagicMock()\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class MemorizeFormatter(Formatter):
"""Customize the Formatter to record used and unused kwargs."""
def __init__(self):
"""Initialize the MemorizeFormatter."""
Formatter.__init__(self)
self._used_kwargs = {}
self._unused_kwargs = {}
def check_... | flexible | {
"blob_id": "773fc4660def134410eca92886b2629be6977f74",
"index": 4095,
"step-1": "<mask token>\n\n\nclass MemorizeFormatter(Formatter):\n \"\"\"Customize the Formatter to record used and unused kwargs.\"\"\"\n\n def __init__(self):\n \"\"\"Initialize the MemorizeFormatter.\"\"\"\n Formatter._... | [
10,
11,
12,
13,
15
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('', views.home, name='VitaminSHE-home'), path('signup/',
views.signup, name='VitaminSHE-signup'), path('login/', views.login,
name='VitaminSHE-login'), path('healthcheck/', views.healthcheck, name=
... | flexible | {
"blob_id": "33aa5c5ab75a26705875b55baf61f7f996cb69cd",
"index": 1280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('', views.home, name='VitaminSHE-home'), path('signup/',\n views.signup, name='VitaminSHE-signup'), path('login/', views.login,\n name='VitaminSHE-login'), path(... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class TestTicketFunctions1(unittest.TestCase):
def setUp(self):
self.required_keys = constants.IMPORT_TABLE_STRUCTURE['required']
self.optional_keys = constants.IMPORT_TABLE_STRUCTURE['optional']
self.keywords = constants.IMPORT_TABLE_STRUCTURE['keywords']
... | flexible | {
"blob_id": "d8ba2557e20920eaadd2fd35f0ebdf1b4a5b33da",
"index": 9010,
"step-1": "<mask token>\n\n\nclass TestTicketFunctions1(unittest.TestCase):\n\n def setUp(self):\n self.required_keys = constants.IMPORT_TABLE_STRUCTURE['required']\n self.optional_keys = constants.IMPORT_TABLE_STRUCTURE['opt... | [
22,
24,
27,
39,
40
] |
from sqlalchemy import Column, ForeignKey
from sqlalchemy.types import Integer, Text, String, DateTime, Float
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
Model = declarative_base()
class User(Model):
__tablename__ = "users"
id = Column(Integer,
... | normal | {
"blob_id": "e73c4a99c421b3eca08c941ff1f83cb03faee97d",
"index": 2558,
"step-1": "<mask token>\n\n\nclass User(Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Product(Model):\n __tablename__ = 'products'\n id = Column(Integer, p... | [
7,
8,
9,
10,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
df_filtro.groupby('Dia')['Quantidade de pessoas'].mean().plot(x='Dia', y=
'Quantidade de pessoas')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
mongo_client = MongoClient('localhost', 27018)
mongo_db = mongo_cl... | flexible | {
"blob_id": "9d4559a363c4fd6f9a22dc493a7aaa0a22386c21",
"index": 8071,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndf_filtro.groupby('Dia')['Quantidade de pessoas'].mean().plot(x='Dia', y=\n 'Quantidade de pessoas')\n",
"step-3": "<mask token>\nmongo_client = MongoClient('localhost', 27018)\nmong... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(L5)
<|reserved_special_token_0|>
print(L5)
print(L5[1:4])
L5.append(30)
print(L5)
L5.remove(30)
print(L5)
<|reserved_special_token_0|>
print(L6[1::2])
print(L6[::2])
<|reserved_special_token_1|>
L5 = [0] * 10
print(L5)
L5... | flexible | {
"blob_id": "052824082854c5f7721efb7faaf5a794e9be2789",
"index": 6517,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(L5)\n<mask token>\nprint(L5)\nprint(L5[1:4])\nL5.append(30)\nprint(L5)\nL5.remove(30)\nprint(L5)\n<mask token>\nprint(L6[1::2])\nprint(L6[::2])\n",
"step-3": "L5 = [0] * 10\nprint... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
import datetime
from urllib import parse
import scrapy
from scrapy import Request
from BrexitNews.items import BrexitNewsItem
def check_url(url):
if url is not None:
url = url.strip()
if url != '' and url != 'None':
return True
return False
class Theguar... | normal | {
"blob_id": "8180dac5d33334d7f16ab6bef41f1fe800879ca7",
"index": 2255,
"step-1": "<mask token>\n\n\nclass TheguardianSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def article(self, response):\n brexit_news = BrexitNewsItem()\n title = response... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
import tensorflow as tf
from yolov3 import *
from predict import predict
from load import Weight_loader
class Yolo(Yolov3):
sess = tf.Session()
def __init__(self, input=None, weight_path=None, is_training=False):
self.is_training = is_training
try:
self... | normal | {
"blob_id": "f3d34379cc7fbfe211eeebec424112f3da0ab724",
"index": 7999,
"step-1": "<mask token>\n\n\nclass Yolo(Yolov3):\n <mask token>\n <mask token>\n <mask token>\n\n def freeze(self):\n graph_def = tf.graph_util.convert_variables_to_constants(sess=self.\n sess, input_graph_def=tf... | [
3,
4,
6,
7,
8
] |
# -*- coding: utf-8 -*-
# Item pipelines
import logging
import hashlib
from wsgiref.handlers import format_date_time
import time
import itertools
import psycopg2
from psycopg2.extensions import AsIs
from psycopg2.extras import Json
import requests
from scrapy import signals
from scrapy.pipelines.files import FilesPip... | normal | {
"blob_id": "d08e4c85890dab7cb421fa994ef1947d8919d58f",
"index": 8547,
"step-1": "<mask token>\n\n\nclass UpYunStore(object):\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, uri):\n assert uri.startswith('upyun://')\n self.session = requests.Session()\n self.b... | [
7,
8,
11,
14,
20
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(n):
if r[i] - b[i] == 1:
x += 1
elif r[i] - b[i] == -1:
y += 1
if x == 0:
print(-1)
else:
print(y // x + min(y % x + 1, 1))
<|reserved_special_token_1|>
n = int(input())
r = list(m... | flexible | {
"blob_id": "7aa6bba8483082354a94ed5c465e59a0fc97fe23",
"index": 1248,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n if r[i] - b[i] == 1:\n x += 1\n elif r[i] - b[i] == -1:\n y += 1\nif x == 0:\n print(-1)\nelse:\n print(y // x + min(y % x + 1, 1))\n",
"s... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def match_regex(filename, regex):
with open(filename) as file:
lines = file.readlines()
for line in reversed(lines):
match = re.match(regex, line)
if match:
regex = yield match.groups()[0]
<|reserved_special_token_0|>
<|reserved_special_toke... | flexible | {
"blob_id": "a36a553342cfe605a97ddc0f636bbb73b683f6a6",
"index": 1239,
"step-1": "<mask token>\n\n\ndef match_regex(filename, regex):\n with open(filename) as file:\n lines = file.readlines()\n for line in reversed(lines):\n match = re.match(regex, line)\n if match:\n regex ... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def banner():
os.system('clear')
os.system('cat banner/banner.txt')
print('')
print('SSHSploit Framework v1.0')
print('------------------------')
print('')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def banner():
... | flexible | {
"blob_id": "caf83d35ce6e0bd4e92f3de3a32221705a529ec1",
"index": 9467,
"step-1": "<mask token>\n\n\ndef banner():\n os.system('clear')\n os.system('cat banner/banner.txt')\n print('')\n print('SSHSploit Framework v1.0')\n print('------------------------')\n print('')\n\n\n<mask token>\n",
"st... | [
1,
2,
4,
5,
6
] |
<|reserved_special_token_0|>
@app.route('/')
def index():
return render_template('a.html')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@app.route('/')
def index():
return render_template('a.html')
@app.route('/insert', methods=['POST'])
def insert():
fir... | flexible | {
"blob_id": "af9430caff843242381d7c99d76ff3c964915700",
"index": 6753,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('a.html')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('a.html')\n\n\n@app.route('/insert... | [
1,
2,
3,
4,
5
] |
from objet import Objet
class Piece(Objet):
""" Représente une piece qui permet d'acheter dans la boutique """
def ramasser(self, joueur):
joueur.addPiece()
def depenser(self,joueur):
joueur.depenserPiece()
def description(self):
return "Vous avez trouvé une piece... | normal | {
"blob_id": "b6898b923e286c66673df1e07105adf789c3151c",
"index": 6335,
"step-1": "<mask token>\n\n\nclass Piece(Objet):\n <mask token>\n\n def ramasser(self, joueur):\n joueur.addPiece()\n\n def depenser(self, joueur):\n joueur.depenserPiece()\n <mask token>\n",
"step-2": "<mask token... | [
3,
4,
5,
6,
7
] |
import tweepy
import time
import twitter_credentials as TC
auth = tweepy.OAuthHandler(TC.CONSUMER_KEY, TC.CONSUMER_SECRET)
auth.set_access_token(TC.ACCESS_TOKEN, TC.ACCESS_TOKEN_SECRET)
api = tweepy.API(auth)
count = 1
# Query to get 50 tweets with either Indiana or Weather in them
for tweet in tweepy.Cursor(api.sea... | normal | {
"blob_id": "4da1a97c2144c9aaf96e5fe6508f8b4532b082d4",
"index": 7861,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nauth.set_access_token(TC.ACCESS_TOKEN, TC.ACCESS_TOKEN_SECRET)\n<mask token>\nfor tweet in tweepy.Cursor(api.search, q='Indiana OR Weather').items(50):\n print(str(count) + '. ' + twee... | [
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": "36bdd6f7c130914856ddf495c50f928405c345aa",
"index": 6646,
"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 = [('mocbackend'... | [
0,
1,
2,
3,
4
] |
import sys, os
def resource_path(relative_path):
""" Get absolute path to resource, works for dev and for PyInstaller """
try:
# PyInstaller creates a temp folder and stores path in _MEIPASS
base_path = sys._MEIPASS
except Exception:
base_path = os.path.abspath(".")
return os.p... | normal | {
"blob_id": "5fb3905abf958f0a8be41cd6ad07efb2a0cf6c66",
"index": 7542,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef resource_path(relative_path):\n \"\"\" Get absolute path to resource, works for dev and for PyInstaller \"\"\"\n try:\n base_path = sys._MEIPASS\n except Exception... | [
0,
1,
2,
3,
4
] |
#! /usr/bin/env python
from game_calc import *
def game(screen, clock):
running = True
time = 0
WHITE = (255,255,255)
BLUE = (0,0,205)
upper_border = pygame.Rect(12,44,1000,20)
right_border = pygame.Rect(992,60,20,648)
left_border = pygame.Rect(12,60,20,648)
down_border = pygame.Rect(12... | normal | {
"blob_id": "83815acb0520c1f8186b0b5c69f8597b1b6a552a",
"index": 8051,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef game(screen, clock):\n running = True\n time = 0\n WHITE = 255, 255, 255\n BLUE = 0, 0, 205\n upper_border = pygame.Rect(12, 44, 1000, 20)\n right_border = pygam... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# looping.py
#
# Copyright 2012 Jelle Smet <development@smetj.net>
#
# 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
# the Free Software Foundation; either version 3 of ... | normal | {
"blob_id": "8c86c0969c47a59db5bd147d3e051a29118d6bf2",
"index": 9855,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#\n# looping.py\n# \n# Copyright 2012 Jelle Smet <development@smetj.net>\n# \n# This program is free software; you can redistribute it and/or modify\n# it under the terms of the... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('Hello Workls!')
<|reserved_special_token_1|>
print ("Hello Workls!")
| flexible | {
"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
] |
from twitter.MyStreamListener import MyStreamListener
import tweepy
from threading import Thread
class TwitterWorker(Thread):
def __init__(self):
Thread.__init__(self)
CONSUMER_KEY = 'IwZZeJHjLXq55ewwQwD0SogHU'
CONSUMER_SECRET = '80kELQhDGNvLNFfNZ7qliIbzAoA3tsgQ... | normal | {
"blob_id": "c475e095571b211693e66583637442edbf72c260",
"index": 7741,
"step-1": "<mask token>\n\n\nclass TwitterWorker(Thread):\n <mask token>\n\n def run(self):\n streamListener = MyStreamListener()\n self.stream = tweepy.Stream(auth=self.api.auth, listener=streamListener\n )\n ... | [
2,
3,
4,
5,
6
] |
from datetime import datetime
from app.commands import backfill_performance_platform_totals, backfill_processing_time
# This test assumes the local timezone is EST
def test_backfill_processing_time_works_for_correct_dates(mocker, notify_api):
send_mock = mocker.patch("app.commands.send_processing_time_for_start_... | normal | {
"blob_id": "fcb1285648f6728e3dad31ad4b602fa4e5c5b422",
"index": 9230,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_backfill_totals_works_for_correct_dates(mocker, notify_api):\n send_mock = mocker.patch(\n 'app.commands.send_total_sent_notifications_to_performance_platform')\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
AuthorPath = 'data/Author.csv'
PaperPath = 'buff/Paper.TitleCut.csv'
PaperAuthorPath = 'data/PaperAuthor.csv'
AffilListPath = 'buff/AffilList2.csv'
StopwordPath = 'InternalData/en.lst'
| flexible | {
"blob_id": "690e7cc9047b3a445bf330524df52e2b359f1f13",
"index": 958,
"step-1": "<mask token>\n",
"step-2": "AuthorPath = 'data/Author.csv'\nPaperPath = 'buff/Paper.TitleCut.csv'\nPaperAuthorPath = 'data/PaperAuthor.csv'\nAffilListPath = 'buff/AffilList2.csv'\nStopwordPath = 'InternalData/en.lst'\n",
"step-3... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if openFileDialog.ShowModal() == wx.ID_CANCEL:
raise ValueError('HDF5 file is not selected')
<|reserved_special_token_0|>
del app
with h5py.File(hist_filename, 'r') as F:
for histogram in F['histograms'].values():
... | flexible | {
"blob_id": "c4898f3298c2febed476f99fe08bc5386527a47e",
"index": 9344,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif openFileDialog.ShowModal() == wx.ID_CANCEL:\n raise ValueError('HDF5 file is not selected')\n<mask token>\ndel app\nwith h5py.File(hist_filename, 'r') as F:\n for histogram in F[... | [
0,
1,
2,
3,
4
] |
from django.core.urlresolvers import reverse
from django.contrib.auth.decorators import login_required
from django.http import HttpResponse, HttpResponseRedirect, HttpResponseForbidden, HttpResponseServerError
from django.shortcuts import render
from django.template import RequestContext
import json
import datetime
... | normal | {
"blob_id": "d583661accce8c058f3e6b8568a09b4be1e58e4e",
"index": 4877,
"step-1": "<mask token>\n\n\ndef lookup_and_render(request):\n try:\n dbres = esgfDatabaseManager.lookupUserSubscriptions(request.user)\n except Exception as e:\n error_cond = str(e)\n print(traceback.print_exc())\n... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class ChunkProcessor:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ChunkProcessor:
<|reserved_special_token_0|>
def chunkify(self, img_file, product_name, ch... | flexible | {
"blob_id": "303e1b95c2ca60041a34b8c09e013849112a108d",
"index": 3475,
"step-1": "<mask token>\n\n\nclass ChunkProcessor:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ChunkProcessor:\n <mask token>\n\n def chunkify(self, img_file, product_name, chunk_size=2... | [
1,
2,
3,
5,
6
] |
def domain_sort_key(domain):
"""Key to sort hosts / domains alphabetically, by domain name."""
import re
domain_expr = r'(.*\.)?(.*\.)(.*)' # Eg: (www.)(google.)(com)
domain_search = re.search(domain_expr, domain)
if domain_search and domain_search.group(1):
# sort by domain name and then... | normal | {
"blob_id": "c581d9714681e22c75b1eeb866ea300e87b883f1",
"index": 2972,
"step-1": "<mask token>\n",
"step-2": "def domain_sort_key(domain):\n \"\"\"Key to sort hosts / domains alphabetically, by domain name.\"\"\"\n import re\n domain_expr = '(.*\\\\.)?(.*\\\\.)(.*)'\n domain_search = re.search(doma... | [
0,
1,
2,
3,
4
] |
from Domain.Librarie import vanzare_obiect, get_id, get_titlu, get_gen, get_pret, get_tip_reducere
def inverse_create(lst_vanzari, id_carte):
new_vanzari = []
for carte in lst_vanzari:
if get_id(carte) != id_carte:
new_vanzari.append(carte)
return new_vanzari
def get_by_id(id, lista):... | normal | {
"blob_id": "498d07421d848332ad528ef3d3910d70312b5f55",
"index": 2606,
"step-1": "<mask token>\n\n\ndef get_by_id(id, lista):\n \"\"\"\n ia vanzarea cu id-ul dat dintr-o lista\n :param id: id-ul vanzarii - string\n :param lista: lista de vanzari\n :return: vanzarea cu id-ul dat sau None daca nu ex... | [
4,
5,
6,
7,
8
] |
from dataclasses import dataclass
from typing import Optional
@dataclass
class Music(object):
url: str
title: Optional[str] = None
| normal | {
"blob_id": "2506c5b042f04d1490ba2199a71e38829d4a0adc",
"index": 5738,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@dataclass\nclass Music(object):\n url: str\n title: Optional[str] = None\n",
"step-3": "from dataclasses import dataclass\nfrom typing import Optional\n\n\n@dataclass\nclass ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
seed = 8912312
np.random.seed(8912312)
u = 0
sigma = 1
cdf = nur.gaussian_cdf
num_samples = np.logspace(1, 5, num=50)
sample_size = int(100000.0)
my_k = np.zeros(50)
my_p = np.zero... | flexible | {
"blob_id": "0158141832423b567f252e38640e384cdf340f8b",
"index": 7105,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n seed = 8912312\n np.random.seed(8912312)\n u = 0\n sigma = 1\n cdf = nur.gaussian_cdf\n num_samples = np.logspace(1, 5, num=50)\n sample_size = int(... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_route_distance(routes, source, dest):
if source + ':' + dest in routes:
return routes[source + ':' + dest]
else:
return routes[dest + ':' + source]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def add_route_distance(routes, cities, source)... | flexible | {
"blob_id": "810e9e4b18ff8cb388f9e16607b8ab3389a9831d",
"index": 7402,
"step-1": "<mask token>\n\n\ndef get_route_distance(routes, source, dest):\n if source + ':' + dest in routes:\n return routes[source + ':' + dest]\n else:\n return routes[dest + ':' + source]\n\n\n<mask token>\n",
"step... | [
1,
2,
3,
4,
5
] |
from rest_framework import serializers
from core.models import Curriculo
class CurriculoSerializer(serializers.ModelSerializer):
class Meta:
model = Curriculo
fields = ('id','name', 'description','image','create_at','update_at') | normal | {
"blob_id": "029f4f015f558dbd4d6096b00c53f5f0fe69883d",
"index": 1322,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CurriculoSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = Curriculo\n fields = 'id', 'name', 'description', 'image', 'create_at', 'update_at... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def setup_fake_data() ->None:
clear_db()
fake_users = [User(username='sunmi', registration_status=
RegistrationStatus.Registered, selected_fiat_currency=FiatCurrency.
USD, selected_language='en', password... | flexible | {
"blob_id": "a6bd10723bd89dd08605f7a4abf17ccf9726b3f5",
"index": 8937,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef setup_fake_data() ->None:\n clear_db()\n fake_users = [User(username='sunmi', registration_status=\n RegistrationStatus.Registered, selected_fiat_currency=FiatCurrenc... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class CNN(nn.Module):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class CNN(nn.Module):
def __init__(self, fragment_length, conv_layers_num, conv_kernel_size,
pool_kernel_size, fc_size, conv_... | flexible | {
"blob_id": "415a6cf1c3f633a863851a4a407d416355398b39",
"index": 7732,
"step-1": "<mask token>\n\n\nclass CNN(nn.Module):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CNN(nn.Module):\n\n def __init__(self, fragment_length, conv_layers_num, conv_kernel_size,\n pool_kernel... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Signup(Auth):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class UserViewSet(APIView):
authentication_classes = [CustomBearerAuthentication]
permission_classes = [IsAuthenticated]
def get(self, request, format=None):
queryset = User.object... | flexible | {
"blob_id": "b2eb2d006d6285947cc5392e290af50f25a9f566",
"index": 4724,
"step-1": "<mask token>\n\n\nclass Signup(Auth):\n <mask token>\n <mask token>\n\n\nclass UserViewSet(APIView):\n authentication_classes = [CustomBearerAuthentication]\n permission_classes = [IsAuthenticated]\n\n def get(self, ... | [
12,
14,
16,
18,
22
] |
<|reserved_special_token_0|>
class Logger:
<|reserved_special_token_0|>
def __init__(self, filepath):
"""
Constructor
:param filepath:
"""
self.filepath = filepath
self.logger = logging.getLogger('util')
self.logger.setLevel(logging.DEBUG)
self.... | flexible | {
"blob_id": "45d57f8392b89776f9349c32b4bb2fa71a4aaa83",
"index": 8610,
"step-1": "<mask token>\n\n\nclass Logger:\n <mask token>\n\n def __init__(self, filepath):\n \"\"\"\n Constructor\n :param filepath:\n \"\"\"\n self.filepath = filepath\n self.logger = logging.... | [
2,
3,
4,
5,
6
] |
<|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": "b7687240413441e1d3ed0085e5953f8089cbf4c9",
"index": 9303,
"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 = [('goods', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(response.text)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
url = 'http://39.108.188.34:9090/spider/zhongdengdengji.go'
input = {'timelimit': '1年', 'title': 'GD20190305001', 'maincontractno':
'YT201812280... | flexible | {
"blob_id": "ad024a2001dc6a6fa3a2a9c1b51f79132e914897",
"index": 7592,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(response.text)\n",
"step-3": "<mask token>\nurl = 'http://39.108.188.34:9090/spider/zhongdengdengji.go'\ninput = {'timelimit': '1年', 'title': 'GD20190305001', 'maincontractno':\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class InstitutionViewSet(viewsets.ModelViewSet):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|res... | flexible | {
"blob_id": "4c43c181dbba1680e036750a2a2ea1185bbe91da",
"index": 3218,
"step-1": "<mask token>\n\n\nclass InstitutionViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def get_permi... | [
5,
8,
10,
11,
13
] |
class Person:
<|reserved_special_token_0|>
def get_name(self):
return self.name
def greet(self):
print(f'こんにちは。私は{self.name}です。')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Person:
def set_name(self, name):
self.name = name
def get_name(self):
... | flexible | {
"blob_id": "321dc411b003949a6744216a13c59c70d919a675",
"index": 8402,
"step-1": "class Person:\n <mask token>\n\n def get_name(self):\n return self.name\n\n def greet(self):\n print(f'こんにちは。私は{self.name}です。')\n\n\n<mask token>\n",
"step-2": "class Person:\n\n def set_name(self, name)... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class JobGroupManager(object):
<|reserved_special_token_0|>
def GetJobGroup(self, group_id):
with self._lock:
for group in self.all_job_groups:
if group.id == group_id:
return group
return None
<|reserved_spe... | flexible | {
"blob_id": "720ec6c222659a13d4a0f3cf9096b70ce6e2b2b3",
"index": 175,
"step-1": "<mask token>\n\n\nclass JobGroupManager(object):\n <mask token>\n\n def GetJobGroup(self, group_id):\n with self._lock:\n for group in self.all_job_groups:\n if group.id == group_id:\n ... | [
3,
6,
7,
8,
9
] |
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