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 import_string(path):
"""
根据字符串的形式去导入路径中的对象
:param path: 'src.engine.agent.AgentHandler'
:return:
"""
module_path, cls_name = path.rsplit('.', maxsplit=1)
module = importlib.import_module(module_p... | flexible | {
"blob_id": "8502ebdb13c68a9a56a1a4ba51370d8458ca81dc",
"index": 7944,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef import_string(path):\n \"\"\"\n 根据字符串的形式去导入路径中的对象\n :param path: 'src.engine.agent.AgentHandler'\n :return:\n \"\"\"\n module_path, cls_name = path.rsplit('.', ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@admin.register(Predictions)
class PredictionsAdmin(admin.ModelAdmin):
pass
<|reserved_special_token_1|>
from django.contrib import admin
from .models import Predictions
@admin.register(Predictions)
class PredictionsAdm... | flexible | {
"blob_id": "bab78e8a88f9a26cc13fe0c301f82880cee2b680",
"index": 965,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@admin.register(Predictions)\nclass PredictionsAdmin(admin.ModelAdmin):\n pass\n",
"step-3": "from django.contrib import admin\nfrom .models import Predictions\n\n\n@admin.registe... | [
0,
1,
2
] |
# coding: utf-8
# In[1]:
import pandas as pd
import os,re,sys
import numpy as np
import glob as glob
# In[2]:
def createNewDataFrame():
columns = ['document_id','content','cat','subcat']
df_ = pd.DataFrame(columns=columns)
return(df_)
# In[3]:
def getcategories(foldername):
cats = folderna... | normal | {
"blob_id": "1aa01845ab98005b1fee33b4fc153bb029e450e0",
"index": 2061,
"step-1": "<mask token>\n\n\ndef createNewDataFrame():\n columns = ['document_id', 'content', 'cat', 'subcat']\n df_ = pd.DataFrame(columns=columns)\n return df_\n\n\ndef getcategories(foldername):\n cats = foldername.split('_')\n... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def select():
result = tkinter.colorchooser.askcolor(title='内裤颜色种类', initialcolor=
'purple')
print(result)
btn1['bg'] = result[1]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
root.minsize(300, 300)
def select():
resu... | flexible | {
"blob_id": "dc261b29c1c11bb8449ff20a7f2fd120bef9efca",
"index": 6090,
"step-1": "<mask token>\n\n\ndef select():\n result = tkinter.colorchooser.askcolor(title='内裤颜色种类', initialcolor=\n 'purple')\n print(result)\n btn1['bg'] = result[1]\n\n\n<mask token>\n",
"step-2": "<mask token>\nroot.minsi... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def errorbar(t, f, s, fp=None, **kwargs):
with sb.axes_style('white'):
fig, ax = pl.subplots(1, 1, figsize=(10, 3))
ax.errorbar(t, f, s, marker='o', color='b', linestyle='none', **kwargs)
pl.setp(ax, xlim=[t.min(), t.max()], xlabel='Time [BJD]', ylabel=
... | flexible | {
"blob_id": "1e929bc3c97de859a16a4ac8d5ac2ebadefd0516",
"index": 6624,
"step-1": "<mask token>\n\n\ndef errorbar(t, f, s, fp=None, **kwargs):\n with sb.axes_style('white'):\n fig, ax = pl.subplots(1, 1, figsize=(10, 3))\n ax.errorbar(t, f, s, marker='o', color='b', linestyle='none', **kwargs)\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
class ExcelOperation:
def __init__(self, filename=None):
self.xlApp = win32com.client.Dispatch('Excel.Application')
if filename:
self.filename = filename
self.xlBook = self.xlApp.Workbooks.Open(filename)
else:
self.xlBook = ... | flexible | {
"blob_id": "b453006b4d4c5f17bb58110fe8197d7796ca0c6c",
"index": 467,
"step-1": "<mask token>\n\n\nclass ExcelOperation:\n\n def __init__(self, filename=None):\n self.xlApp = win32com.client.Dispatch('Excel.Application')\n if filename:\n self.filename = filename\n self.xlBo... | [
42,
52,
64,
71,
87
] |
import rambench
rambench.perform_benchmark()
| normal | {
"blob_id": "3d1f2130043613dc8d5bbd773edd96c87c355de9",
"index": 3455,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrambench.perform_benchmark()\n",
"step-3": "import rambench\nrambench.perform_benchmark()\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import numpy as np
import matplotlib.pyplot as plt
# some important constants
x_bound = y_bound = 1.
dx = dy = 0.05
k = 0.1
nx, ny = int(x_bound/dx), int(y_bound/dy)
dx2, dy2 = dx*dx, dy*dy
dt = (dx2 / k) / 4.0
t_end = 80 * dt
# set the grid
u0 = np.zeros((nx, ny))
u_exact = np.zeros((nx, ny))
u = np.zeros((nx, ny))... | normal | {
"blob_id": "c556aaf6aecb3c91d9574e0a158a9fa954108d70",
"index": 8193,
"step-1": "<mask token>\n\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z = 0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ((-n) ** 4 * np.pi *... | [
2,
4,
5,
6,
7
] |
#!/usr/bin/env python
import errno
import logging
import os
import re
import sys
import argparse
def parse_map(map_str):
file_map = []
for line in map_str.split('\n'):
if not line:
continue
find, replace = line.split(' -- ', 1)
file_map.append((find, replace))
return f... | normal | {
"blob_id": "03d07f5f4647e904c288e828b8f8e7de35740054",
"index": 3737,
"step-1": "<mask token>\n\n\ndef map_file(file_map, d, f):\n for find, repl in file_map:\n if '/' in find:\n source = os.path.join(d, f)\n includes_path = True\n else:\n source = f\n ... | [
8,
10,
11,
12,
14
] |
import requests
import json
def get():
market = 'Premium'
url = 'https://coinpremiums.herokuapp.com/json'
try:
result = ""
premiums = requests.get(url).json()
for exchange, exchange_currencies in premiums['premium'].items():
result += '[[{} | '.format(exchange.title()... | normal | {
"blob_id": "b5581be044013df9ff812f285f99ca67c4f96a62",
"index": 2927,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get():\n market = 'Premium'\n url = 'https://coinpremiums.herokuapp.com/json'\n try:\n result = ''\n premiums = requests.get(url).json()\n for exchan... | [
0,
1,
2,
3
] |
import rpy2.robjects as robjects
from rpy2.robjects.packages import importr
# print(robjects.__file__)
import sys
sys.path.append('./')
import importlib
import json
import os
from web_app.function.WordCould import word_img
# importlib.reload(sys)
# #sys.setdefaultencoding('gbk')
class Ubiquitination():
def __ini... | normal | {
"blob_id": "a6ae4324580a8471969e0229c02ea1670728f25b",
"index": 3767,
"step-1": "<mask token>\n\n\nclass Ubiquitination:\n <mask token>\n\n def load_R(self):\n pass\n\n def data_path(self, name):\n exp_path = './web_app/data/disease/exp_data/{}.txt'.format(name)\n clinical_path = '... | [
7,
8,
10,
12,
13
] |
# coding=utf-8
"""
Given a binary tree, find its maximum depth.
The maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.
Example
Given a binary tree as follow:
1
/ \
2 3
/ \
4 5
The maximum depth is 3.
"""
"""
Definition of TreeNode:
"""
class ... | normal | {
"blob_id": "262d6722f4c158d0a41b22433792cdc35651d156",
"index": 9459,
"step-1": "<mask token>\n\n\nclass Solution:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n \"\"\"\n @param root: The root of binary tree.\n @return: An integer\n \"\"\"\n\n def maxDept... | [
1,
3,
4,
5,
6
] |
# CSE 415 Winter 2019
# Assignment 1
# Jichun Li 1531264
# Part A
# 1
def five_x_cubed_plus_1(x):
return 5 * (x ** 3) + 1
#2
def pair_off(ary):
result = []
for i in range(0, int(len(ary) / 2 * 2), 2):
result.append([ary[i], ary[i + 1]])
if (int (len(ary) % 2) == 1):
result.append([ar... | normal | {
"blob_id": "681788ffe7672458e8d334316aa87936746352b1",
"index": 4054,
"step-1": "def five_x_cubed_plus_1(x):\n return 5 * x ** 3 + 1\n\n\n<mask token>\n",
"step-2": "def five_x_cubed_plus_1(x):\n return 5 * x ** 3 + 1\n\n\ndef pair_off(ary):\n result = []\n for i in range(0, int(len(ary) / 2 * 2),... | [
1,
2,
3,
4,
5
] |
import unittest
from collections import Counter
class Solution(object):
def findOriginalArray(self, changed):
"""
:type changed: List[int]
:rtype: List[int]
"""
n = len(changed)
if n % 2 != 0:
return []
freq = Counter(changed)
changed.so... | normal | {
"blob_id": "d5acda0d5d066d381a7f6310eb4fe6280d7e84de",
"index": 5309,
"step-1": "<mask token>\n\n\nclass TestSolution(unittest.TestCase):\n\n def test_findOriginalArray(self):\n solution = Solution()\n self.assertEqual(solution.findOriginalArray([1, 3, 4, 2, 6, 8]), [1,\n 3, 4])\n\n\... | [
2,
3,
5,
6
] |
import copy
from typing import List, Optional, Tuple, NamedTuple, Union, Callable
import torch
from torch import Tensor
from torch_sparse import SparseTensor
import time
import torch_quiver as qv
from torch.distributed import rpc
def subgraph_nodes_n(nodes, i):
row, col, edge_index = None, None, None
return r... | normal | {
"blob_id": "3f4f396d1d18611e0248a08b42328422ca4b8146",
"index": 4766,
"step-1": "<mask token>\n\n\nclass Adj(NamedTuple):\n adj_t: SparseTensor\n e_id: Optional[Tensor]\n size: Tuple[int, int]\n <mask token>\n\n\nclass RandomIndexSampler(torch.utils.data.Sampler):\n\n def __init__(self, num_nodes... | [
12,
15,
18,
20,
21
] |
# -*- coding: utf-8 -*-
'''
* EAFS
* Copyright (C) 2009-2011 Adam Etienne <eadam@lunasys.fr>
*
* 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 version 3.
*
* This program is distributed i... | normal | {
"blob_id": "2f5244c6144f5aafce29e5aba32bd7e3fc7ecf5b",
"index": 3632,
"step-1": "# -*- coding: utf-8 -*-\n'''\n * EAFS\n * Copyright (C) 2009-2011 Adam Etienne <eadam@lunasys.fr>\n *\n * This program is free software: you can redistribute it and/or modify\n * it under the terms of the GNU General Public License... | [
0
] |
l = input().split("+")
l.sort()
print('+'.join(l))
| normal | {
"blob_id": "30d891c18f3635b7419fa0d0539b2665ad60b22c",
"index": 4748,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nl.sort()\nprint('+'.join(l))\n",
"step-3": "l = input().split('+')\nl.sort()\nprint('+'.join(l))\n",
"step-4": "l = input().split(\"+\")\r\r\nl.sort()\r\r\nprint('+'.join(l))\r\r\n",
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(n):
a[i] = int(a[i])
for i in range(n - 1):
for j in range(n - i - 1):
if a[j] > a[j + 1]:
a[j], a[j + 1] = a[j + 1], a[j]
print('Sortes array :', a)
<|reserved_special_token_1|>
a = i... | flexible | {
"blob_id": "5c2a6802e89314c25f0264bbe2bc7ed2689a255a",
"index": 782,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n):\n a[i] = int(a[i])\nfor i in range(n - 1):\n for j in range(n - i - 1):\n if a[j] > a[j + 1]:\n a[j], a[j + 1] = a[j + 1], a[j]\nprint('Sortes ar... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
auth.set_access_token('956917059287375875-EThit80MxgQPTJlh7ZObqyHsoV8Q2D7',
'eLv893meGppqfX3xOr8SJ93kpsbZpoOiRsVM3XTgJryZM')
<|reserved_special_token_0|>
auth.set_access_token('956917059287375875-EThit80MxgQPTJlh7ZObqyHsoV8Q2D... | flexible | {
"blob_id": "b68cc09347584dfc613b2e38d036b124c9af7952",
"index": 1904,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nauth.set_access_token('956917059287375875-EThit80MxgQPTJlh7ZObqyHsoV8Q2D7',\n 'eLv893meGppqfX3xOr8SJ93kpsbZpoOiRsVM3XTgJryZM')\n<mask token>\nauth.set_access_token('956917059287375875-... | [
0,
1,
2,
3,
4
] |
from typing import List
import scrapy
from cssselect import Selector
class RwidSpider(scrapy.Spider):
name = 'rwid'
allowed_domains = ['0.0.0.0']
# REQUEST LOGIN DARI URLS
start_urls = ['http://0.0.0.0:9999/']
# LOGIN DISINI
def parse(self, response):
# apa bedanya yield & return
... | normal | {
"blob_id": "2185d332f7cd4cbf17d6b72a19297d156c2182a1",
"index": 2233,
"step-1": "<mask token>\n\n\nclass RwidSpider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n\n def parse(self, response):\n data = {'username': 'user', 'password': 'user12345'}\n return scrapy.FormReq... | [
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.test import TestCase
from collections import Counter
import generator.resume_parser as resume_parser
import os
import json
class TestResumeParser(TestCase):
def load_resume(self, resume_name):
path_to_directory = "generator/fixtures/{... | normal | {
"blob_id": "4bbfb35e4b03e2bfd46dd0fe5bfd54fb01ba11df",
"index": 1996,
"step-1": "<mask token>\n\n\nclass TestResumeParser(TestCase):\n <mask token>\n <mask token>\n\n def generate_counter(self, resume_name):\n json_file = self.load_resume(resume_name)\n return self.convert_to_counter(json... | [
10,
22,
24,
25,
26
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
##########
# websocket-client
# https://pypi.python.org/pypi/websocket-client/
# sudo -H pip install websocket-client
#####
from websocket import create_connection
ws = create_connection( "ws://192.168.1.132:81/python" )
msg = '#0000FF'
print "Envoi d’un message à l’ESP"... | normal | {
"blob_id": "3b26181097025add5919e752aa53e57eea49c943",
"index": 4923,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n##########\n# websocket-client\n# https://pypi.python.org/pypi/websocket-client/\n# sudo -H pip install websocket-client\n#####\n\nfrom websocket import create_connection\nws = crea... | [
0
] |
"""empty message
Revision ID: 0bb5933fe69f
Revises: 09c6fdb3cf81
Create Date: 2021-03-11 16:48:06.771046
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '0bb5933fe69f'
down_revision = '09c6fdb3cf81'
branch_labels = None
depends_on = None
def upgrade():
# ... | normal | {
"blob_id": "f727c0551f20fb0dc72b4d81b7b3ed8ce9b1b6f4",
"index": 2072,
"step-1": "<mask token>\n\n\ndef downgrade():\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_constraint(None, 'user', type_='unique')\n op.drop_column('user', 'money')\n",
"step-2": "<mask token>\n\n\ndef upgrade():\n... | [
1,
2,
3,
4,
5
] |
from django.views import generic
from .models import GPS
# This is the view for my home page. It is a list view because it needs to display a list of all
# of the GPS units that are currently in the database.
class HomeView(generic.ListView):
model = GPS
template_name = 'inv_templates/home.html'
context_obj... | normal | {
"blob_id": "67db3a66e5525d41de13df665167a0db2d81056e",
"index": 2721,
"step-1": "<mask token>\n\n\nclass Remove_ItemView(generic.ListView):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Update_ItemView(generic.ListView):\n model = GPS\n template_name = 'inv_templates/update_item.html'\n... | [
7,
11,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def something3():
x = session.query(models.Review).filter(models.Review.time < end_time
).count()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
something1
<|reserved_special_token_0|>
something2
<|re... | flexible | {
"blob_id": "5b91b7025b0e574d45f95a0585128018d83c17ea",
"index": 563,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef something3():\n x = session.query(models.Review).filter(models.Review.time < end_time\n ).count()\n\n\n<mask token>\n",
"step-3": "something1\n<mask token>\nsomething2\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class StonewallConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class StonewallConfig(AppConfig):
name = 'stonewall'
<|reserved_special_token_1|>
from djan... | flexible | {
"blob_id": "8364264851895ccabeb74fd3fab1d4f39da717f8",
"index": 8398,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass StonewallConfig(AppConfig):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass StonewallConfig(AppConfig):\n name = 'stonewall'\n",
"step-4": "from django.apps impo... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_nearest_method(method_name, parser):
"""
all candidates toked
all protocol untoked
input:
queries:
[
(protocol, (candidate, sen_id, start, K), (candidate, sen_id, start, K), ...)
(protocol, (candidate, sen_id, start, K), (candidate, sen_id, ... | flexible | {
"blob_id": "ed2f3bbc7eb0a4d8f5ccdb7a12e00cbddab04dd0",
"index": 577,
"step-1": "<mask token>\n\n\ndef get_nearest_method(method_name, parser):\n \"\"\"\n all candidates toked\n all protocol untoked\n input:\n queries:\n [\n (protocol, (candidate, sen_id, start, K), (candidate, sen_id, s... | [
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""Form content type."""
from briefy.plone.content.interfaces import IBriefyContent
from plone.dexterity.content import Container
from zope.interface import implementer
class IForm(IBriefyContent):
"""Interface for a Composite Page."""
@implementer(IForm)
class Form(Container):
"""A ... | normal | {
"blob_id": "6e3de57f7c65e9f6195dabc3326b05744249cefe",
"index": 7991,
"step-1": "<mask token>\n\n\n@implementer(IForm)\nclass Form(Container):\n \"\"\"A Form.\"\"\"\n",
"step-2": "<mask token>\n\n\nclass IForm(IBriefyContent):\n <mask token>\n\n\n@implementer(IForm)\nclass Form(Container):\n \"\"\"A ... | [
2,
3,
4,
5,
6
] |
from os import getenv
LISTEN_IP = getenv('LISTEN_IP', '0.0.0.0')
LISTEN_PORT = int(getenv('LISTEN_PORT', 51273))
LISTEN_ADDRESS = LISTEN_IP, LISTEN_PORT
CONFIRMATION = getenv('CONFIRMATION')
if CONFIRMATION:
CONFIRMATION = CONFIRMATION.encode()
class UDPProtocol:
def __init__(self, consumer):
self... | normal | {
"blob_id": "cca543f461724c3aac8fef23ef648883962bd706",
"index": 4607,
"step-1": "<mask token>\n\n\nclass UDPProtocol:\n <mask token>\n\n def connection_made(self, transport):\n self.transport = transport\n <mask token>\n <mask token>\n <mask token>\n\n def stop(self):\n self.tran... | [
3,
5,
8,
9,
11
] |
<|reserved_special_token_0|>
def populateTimeInterval(rec):
out_ts = (rec['event_time'] - TEMP_TS) // DELTA_MINS * DELTA_MINS + TEMP_TS
rec['intvl_date'] = datetime.datetime.strftime(out_ts, '%Y-%m-%d')
rec['intvl_hhmm'] = datetime.datetime.strftime(out_ts, '%H%M')
return rec
def processBatch(data_f... | flexible | {
"blob_id": "fcccbc8d582b709aa27500ef28d86103e98eee4c",
"index": 7980,
"step-1": "<mask token>\n\n\ndef populateTimeInterval(rec):\n out_ts = (rec['event_time'] - TEMP_TS) // DELTA_MINS * DELTA_MINS + TEMP_TS\n rec['intvl_date'] = datetime.datetime.strftime(out_ts, '%Y-%m-%d')\n rec['intvl_hhmm'] = date... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def __handle_import():
import sys
import os
cur_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
lib_path = os.path.join(cur_path, '../../build/lib/')
sys.path.append(lib_path)
proto_path = os.path.join(cur_path, '... | flexible | {
"blob_id": "24595979199199ecc6bc6f3a26e0db418def8b78",
"index": 9675,
"step-1": "<mask token>\n",
"step-2": "def __handle_import():\n import sys\n import os\n cur_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))\n lib_path = os.path.join(cur_path, '../../build/lib/')\n sys.... | [
0,
1,
2
] |
#!/usr/bin/env python
"""
Author: Adam White, Matthew Schlegel, Mohammad M. Ajallooeian, Sina Ghiassian
Purpose: Skeleton code for Monte Carlo Exploring Starts Control Agent
for use on A3 of Reinforcement learning course University of Alberta Fall 2017
"""
"""
/*
* Copyright (c) HAOTIAN ZHU ,COMPUT301,... | normal | {
"blob_id": "4e02edcf8a512060fa92ede11f33993978584147",
"index": 1997,
"step-1": "\n\n\n\n#!/usr/bin/env python\n\n\"\"\"\n Author: Adam White, Matthew Schlegel, Mohammad M. Ajallooeian, Sina Ghiassian\n Purpose: Skeleton code for Monte Carlo Exploring Starts Control Agent\n\t\t for use on A3 of Reinforcemen... | [
0
] |
from django import forms
from myapp.models import Student
from myapp.models import Employee
class EmpForm(forms.ModelForm):
class Meta:
model = Student
fields = "__all__"
class StudentForm(forms.Form):
firstname = forms.CharField(label="Enter first name:", max_length=50)
lastname = forms... | normal | {
"blob_id": "0b141ecca501c21df50e76d0841dd5651274f0da",
"index": 8509,
"step-1": "<mask token>\n\n\nclass StudentForm(forms.Form):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass EmployeeForm(forms.ModelForm):\n\n\n class Meta:\n model = Employee\n fields = '__... | [
2,
3,
4,
5,
6
] |
word=input()
letter,digit=0,0
for i in word:
if('a'<=i and i<='z') or ('A'<=i and i<='Z'):
letter+=1
if '0'<=i and i<='9':
digit+=1
print("LETTERS {0} \n DIGITS {1}".format(letter,digit))
| normal | {
"blob_id": "f2a508ae99697d6ba320b158a1000379b975d568",
"index": 2227,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in word:\n if 'a' <= i and i <= 'z' or 'A' <= i and i <= 'Z':\n letter += 1\n if '0' <= i and i <= '9':\n digit += 1\nprint(\"\"\"LETTERS {0} \n DIGITS {1}\"\"\"... | [
0,
1,
2,
3
] |
# This file is part of the functional_calculator_oop.py Task
# Create a class called Calculator
class Calculator:
def Add(self, num1, num2):
return num1 + num2
def Subtract(self, num1, num2):
return num1 - num2
def Multiply(self, num1, num2):
return num1 * num2
def Divide(sel... | normal | {
"blob_id": "d2972fb7cff08e15957f9baeaa6fd9a6f5bbb006",
"index": 1127,
"step-1": "class Calculator:\n <mask token>\n\n def Subtract(self, num1, num2):\n return num1 - num2\n <mask token>\n\n def Divide(self, num1, num2):\n return num1 / num2\n\n\n<mask token>\n",
"step-2": "class Calc... | [
3,
4,
5,
6,
7
] |
from rest_framework import serializers
from plan.models import RoughRequirement, DetailedRequirement
from plan.models import OfferingCourse, FieldOfStudy, IndicatorFactor
from plan.models import BasisTemplate
class SimpleOfferingCourseSerializer(serializers.ModelSerializer):
class Meta:
model = OfferingCou... | normal | {
"blob_id": "596f7dfacc931f5e756c71b8622f4001df19934b",
"index": 5964,
"step-1": "<mask token>\n\n\nclass RequirementSerializer(serializers.ModelSerializer):\n <mask token>\n\n\n class Meta:\n model = RoughRequirement\n fields = ['id', 'index', 'title', 'description',\n 'detailed_r... | [
8,
11,
12,
13,
14
] |
# -*- coding: utf-8 -*-
# https://github.com/Raschka-research-group/coral-cnn/tree/master/model-code/resnet34
from absl import flags, app
from Rank_consistent_model_fix import *
from Rank_consistent_model import *
from random import shuffle, random
import tensorflow as tf
import numpy as np
# import cv2
import os
impo... | normal | {
"blob_id": "9ffe350ff9a568111620ef7dafef83d341f6f01e",
"index": 9409,
"step-1": "<mask token>\n\n\ndef _func(filename, label):\n image_string = tf.io.read_file(filename)\n decode_image = tf.image.decode_jpeg(image_string, channels=3)\n decode_image = tf.image.resize(decode_image, [FLAGS.img_size - 8, F... | [
7,
8,
9,
10,
12
] |
# -*- coding: utf-8 -*-
'''
Created on Dec 22, 2014
@author: Alan Tai
'''
from handlers.handler_webapp2_extra_auth import BaseHandler
from models.models_porn_info import WebLinkRoot, WebLinkPornTemp, WebLinkPorn,\
Tag
from dictionaries.dict_key_value_pairs import KeyValuePairsGeneral
from bs4 import BeautifulSoup
... | normal | {
"blob_id": "f6cebf6ec848a06f81c4e1f584ebb83f4d9ff47c",
"index": 3549,
"step-1": "# -*- coding: utf-8 -*-\n'''\nCreated on Dec 22, 2014\n\n@author: Alan Tai\n'''\nfrom handlers.handler_webapp2_extra_auth import BaseHandler\nfrom models.models_porn_info import WebLinkRoot, WebLinkPornTemp, WebLinkPorn,\\\n Tag... | [
0
] |
#!/usr/bin/python3
#start up curses
import curses
HEIGHT = 24
WIDTH = 80
TESTING = True
curses.initscr()
stdscr = curses.newwin(HEIGHT, WIDTH, 0, 0)
curses.noecho() #don't echo keys
stdscr.keypad(1)
#function for displaying other players decision
#statement is the number of the other player's death funciton returne... | normal | {
"blob_id": "a6f03340c2f60c061977fed6807703cdaeb1b7fd",
"index": 7976,
"step-1": "<mask token>\n\n\ndef decision(statement, player):\n stdscr.clear()\n stdscr.border(0)\n stdscr.timeout(-1)\n decision = 'play again' if statement == 1 else 'return to main menu'\n stdscr.addstr(3, 5, 'Your Partner h... | [
4,
5,
8,
9,
10
] |
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from database_setup import Base, Country, TouristPlaces, Users
# Create database and create a shortcut for easier to update database
engine = create_engine('sqlite:///country_catalog.db')
Base.metadata.bind = engine
DBSession = sessionmaker(b... | normal | {
"blob_id": "21b9844fce10d16a14050a782ce7e15e3f6fb657",
"index": 5737,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsession.add(user_1)\nsession.commit()\n<mask token>\nsession.add(country_1)\nsession.commit()\n<mask token>\nsession.add(country_2)\nsession.commit()\n<mask token>\nsession.add(country_3)... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name='dcnn_visualizer', version='', packages=['dcnn_visualizer',
'dcnn_visualizer.backward_functions'], url='', license='', author=
'Aiga SUZUKI', author_email='tochikuji@gmail.com', description='',
requires=['nu... | flexible | {
"blob_id": "b9a75f4e106efade3a1ebdcfe66413107d7eccd0",
"index": 7884,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='dcnn_visualizer', version='', packages=['dcnn_visualizer',\n 'dcnn_visualizer.backward_functions'], url='', license='', author=\n 'Aiga SUZUKI', author_email='tochikuji@... | [
0,
1,
2
] |
from django.db import models
from utils.models import BaseModel
# Create your models here.
class ContentCategory(BaseModel):
'''广告内容类别'''
name = models.CharField(verbose_name='名称',max_length=50)
key = models.CharField(verbose_name='类别键名',max_length=50)
class Meta:
db_table = 'tb_content_catego... | normal | {
"blob_id": "fd96bf5595ce6ec1f95d0f7a9d1c4ff582826ac0",
"index": 1439,
"step-1": "<mask token>\n\n\nclass ContentCategory(BaseModel):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n db_table = 'tb_content_category'\n verbose_name = '广告内容类别'\n verbose_name_plural ... | [
5,
6,
7,
8,
10
] |
import matplotlib.pyplot as pt
import numpy as np
from scipy.optimize import leastsq
####################################
# Setting up test data
def norm(x, media, sd):
norm = []
for i in range(x.size):
norm += [1.0/(sd*np.sqrt(2*np.pi))*np.exp(-(x[i] - media)**2/(2*sd**2))]
return np.array(norm)... | normal | {
"blob_id": "b3ce17401476afe2edfda3011d5602ba492cd705",
"index": 5817,
"step-1": "<mask token>\n\n\ndef res(p, y, x):\n m, dm, sd1, sd2 = p\n m1 = m\n m2 = m1 + m\n y_fit = norm(x, m1, sd1) + norm(x, m2, sd2)\n error = y - y_fit\n return error\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n... | [
1,
2,
3,
4,
5
] |
import config
import math
import pygame
import utils
class Rocket:
def __init__(self):
self.x = config.initialPosition['x']*config.game['scale'] + config.game['width']/2;
self.y = config.game['height'] - config.game['floorHeight'] - config.initialPosition['y']*config.game['scale'];
self.angle = config.initial... | normal | {
"blob_id": "7a1a9d2e773fb783d8522f1ea51e753d5d3782e9",
"index": 7517,
"step-1": "<mask token>\n\n\nclass Rocket:\n <mask token>\n <mask token>\n\n def update(self, x, y, angle, leftPower, rightPower):\n self.x = x * config.game['scale'] + config.game['width'] / 2\n self.y = config.game['h... | [
2,
3,
4,
5,
6
] |
print(input()in[str(i**i+i)for i in range(11)])
num = int(input())
suma = 0
x = 0
while(suma < num):
x += 1
suma = x**x + x
print(True if suma == num else False
| normal | {
"blob_id": "20fe9b68e65f6f017897bfa8e99d0c21ba1617fb",
"index": 1522,
"step-1": "print(input()in[str(i**i+i)for i in range(11)])\n\n\n\nnum = int(input())\nsuma = 0\nx = 0\nwhile(suma < num):\n x += 1\n suma = x**x + x\nprint(True if suma == num else False\n\n\n",
"step-2": null,
"step-3": null,
"st... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def domain_name(url):
while 'https://' in url or 'http://' in url or 'www.' in url:
url = url.replace('https://', ' '
) if 'https://' in url else url.replace('http://', ' '
) if 'http://' in url else url.replace('www.', ' '... | flexible | {
"blob_id": "2b9dfd0cfd62276330f1a4f983f318076f329437",
"index": 5026,
"step-1": "<mask token>\n",
"step-2": "def domain_name(url):\n while 'https://' in url or 'http://' in url or 'www.' in url:\n url = url.replace('https://', ' '\n ) if 'https://' in url else url.replace('http://', ' '\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .dependencies import have
from .syntax import PythonHighlighter
from .utils import count_locations, image_path, interface_style, natural_sort
<|reserved_special_token_1|>
# © MNELAB developers
#
# License: BSD (3-clause)
from .dependencies import hav... | flexible | {
"blob_id": "837534ebc953dae966154921709398ab2b2e0b33",
"index": 578,
"step-1": "<mask token>\n",
"step-2": "from .dependencies import have\nfrom .syntax import PythonHighlighter\nfrom .utils import count_locations, image_path, interface_style, natural_sort\n",
"step-3": "# © MNELAB developers\n#\n# License:... | [
0,
1,
2
] |
# This script allows you to copy all files with a certain extention to a new folder without integrating the sub folders
# Created by Maurice de Kleijn Vrije Universiteit Amsterdam Spatial Information laboratory for the datamanagement of the the archaological project Barin Hoyuk
# 22062016 Python 2.7
import shutil
impo... | normal | {
"blob_id": "778cf8064fa45e3e25a66f2165dcf6885c72fb8a",
"index": 634,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.system('dir ' + org_GIS + '*' + ext + ' /s/d/b >' + org_GIS + 'tempext.txt')\n<mask token>\nfor line in lines:\n ln = line.rstrip('\\n')\n shutil.copy(ln, outputfolder)\nfile1.clo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
with open('rosalind_ba3d.txt', 'r') as f:
kmer_length = int(f.readline().strip())
seq = f.readline().strip()
<|reserved_special_token_0|>
for offset in range(len(seq) - kmer_length + 1):
prefix = seq[offset:offset + kmer_length - 1]
suffix = s... | flexible | {
"blob_id": "050f060bb9d3d46f8b87c9802356bd0da8f926f8",
"index": 6244,
"step-1": "<mask token>\n",
"step-2": "with open('rosalind_ba3d.txt', 'r') as f:\n kmer_length = int(f.readline().strip())\n seq = f.readline().strip()\n<mask token>\nfor offset in range(len(seq) - kmer_length + 1):\n prefix = seq[... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class ConsoleLogger:
<|reserved_special_token_0|>
def set_level(self, level):
self.logger.setLevel(level)
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "5299f2c66fd287be667ecbe11b8470263eafab5c",
"index": 702,
"step-1": "<mask token>\n\n\nclass ConsoleLogger:\n <mask token>\n\n def set_level(self, level):\n self.logger.setLevel(level)\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __... | [
3,
6,
7,
8,
11
] |
#Task 4 - writing a code that prints all the commit message from repository
import requests
r = requests.get('https://api.github.com/repos/smeiklej/secu2002_2017/commits')
text = r.json()
#asking the code to print out the commit message for all rows in the text
for row in text:
print row['commit']['message']
| normal | {
"blob_id": "d07046e33bbfa404c354fef3e8990a3fa0203060",
"index": 1843,
"step-1": "#Task 4 - writing a code that prints all the commit message from repository\nimport requests\nr = requests.get('https://api.github.com/repos/smeiklej/secu2002_2017/commits')\ntext = r.json()\n\n#asking the code to print out the com... | [
0
] |
'''
Created on May 18, 2010
@author: Abi.Mohammadi & Majid.Vesal
'''
from threading import current_thread
import copy
import time
from deltapy.core import DeltaException, Context
import deltapy.security.services as security_services
import deltapy.security.session.services as session_services
import deltapy.unique... | normal | {
"blob_id": "80469fd945a21c1bd2b5590047016a4b60880c88",
"index": 7006,
"step-1": "<mask token>\n\n\nclass Session:\n <mask token>\n\n\n class StateEnum:\n \"\"\"\n A class for defining session state.\n \"\"\"\n ACTIVE = 'Active'\n INACTIVE = 'Inactive'\n CLOSED = '... | [
18,
21,
25,
28,
31
] |
<|reserved_special_token_0|>
def arribo():
global reloj
global tiempoUltEvento
global estadoServ
global tiempoServicioTotal
global areaQ
global numCliEnCola
global cola
global tiempoLibre
global completaronDemora
listaEventos[0] = reloj + generarTiempoExponencial(tiempoEntreArr... | flexible | {
"blob_id": "62cc731982846f08b3f3caace5df1bfafd421869",
"index": 1701,
"step-1": "<mask token>\n\n\ndef arribo():\n global reloj\n global tiempoUltEvento\n global estadoServ\n global tiempoServicioTotal\n global areaQ\n global numCliEnCola\n global cola\n global tiempoLibre\n global co... | [
6,
7,
8,
9,
10
] |
"""This is a collection of utilities for httpy and httpy applications.
"""
import cgi
import linecache
import mimetypes
import os
import stat
import sys
from Cookie import SimpleCookie
from StringIO import StringIO
from urllib import unquote
from httpy.Response import Response
def uri_to_fs(config, resource_uri_pat... | normal | {
"blob_id": "472cdca501890d1d07c7363a48532ed3a184727c",
"index": 8516,
"step-1": "\"\"\"This is a collection of utilities for httpy and httpy applications.\n\"\"\"\n\nimport cgi\nimport linecache\nimport mimetypes\nimport os\nimport stat\nimport sys\nfrom Cookie import SimpleCookie\nfrom StringIO import StringIO... | [
0
] |
decoded = ["0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p"... | normal | {
"blob_id": "23236cd8262eb414666db88215c01d973abf1d97",
"index": 1247,
"step-1": "<mask token>\n\n\ndef decode(value):\n out_value = ''\n char = [value[i:i + 2] for i in range(0, len(value), 2)]\n for i in range(0, len(char)):\n out_value += decoded[encoded.index(char[i])]\n return out_value\n... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_runs_counts_by_match():
ipl_df = read_csv_data_to_df('data/ipl_dataset.csv')
df1 = pd.DataFrame(ipl_df[['match_code', 'runs', 'venue']])
df2 = df1.groupby(['match_code', 'runs'], as_index=False).count()
d... | flexible | {
"blob_id": "4f06d87ec79c20206ff45ba72ab77844076be553",
"index": 9707,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_runs_counts_by_match():\n ipl_df = read_csv_data_to_df('data/ipl_dataset.csv')\n df1 = pd.DataFrame(ipl_df[['match_code', 'runs', 'venue']])\n df2 = df1.groupby(['mat... | [
0,
1,
2,
3,
4
] |
from bisect import bisect_left as bisect
while True:
xp, yp = set(), set()
veneer = []
W, H = map(int, input().split())
if not W:
break
N = int(input())
for i in range(N):
x1, y1, x2, y2 = map(int, input().split())
veneer.append((x1, y1, x2, y2))
xp.add(x1)
... | normal | {
"blob_id": "e0fbb5ad6d822230865e34c1216b355f700e5cec",
"index": 7822,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile True:\n xp, yp = set(), set()\n veneer = []\n W, H = map(int, input().split())\n if not W:\n break\n N = int(input())\n for i in range(N):\n x1, y1, ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('SYL_2整型数组_12 合并排序数组')
| flexible | {
"blob_id": "571636be9d213d19bddfd1d04688bc0955c9eae5",
"index": 4427,
"step-1": "<mask token>\n",
"step-2": "print('SYL_2整型数组_12 合并排序数组')\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
"""
Platformer Game
"""
import arcade
import os
from Toad_arcade import Toad
# Constants
SCREEN_WIDTH = 1920
SCREEN_HEIGHT = 1080
SCREEN_TITLE = "PyToads - Battletoads reimplementation"
# Constants used to scale our sprites from their original size
CHARACTER_SCALING = 1
TILE_SCALING = 0.5
COIN_SCALING = 0.5
MOVEMENT_S... | normal | {
"blob_id": "28d8f9d9b39c40c43a362e57a7907c0a38a6bd05",
"index": 748,
"step-1": "<mask token>\n\n\nclass MyGame(arcade.Window):\n <mask token>\n\n def __init__(self, width, height, title):\n \"\"\"\n Initializer\n \"\"\"\n super().__init__(width, height, title)\n file_pat... | [
6,
7,
9,
12,
13
] |
"""Resolwe collection serializer."""
import logging
from rest_framework import serializers
from resolwe.flow.models import Collection, Data, DescriptorSchema
from resolwe.rest.fields import ProjectableJSONField
from .base import ResolweBaseSerializer
from .descriptor import DescriptorSchemaSerializer
from .fields im... | normal | {
"blob_id": "d6f8ec0fd8be0fa7019a84af47d08ab8b5b32d92",
"index": 1449,
"step-1": "<mask token>\n\n\nclass BaseCollectionSerializer(ResolweBaseSerializer):\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_status(self, coll... | [
6,
8,
9,
11,
12
] |
#https://www.geeksforgeeks.org/count-of-substrings-of-length-k-with-exactly-k-distinct-characters/
#https://www.geeksforgeeks.org/count-number-of-substrings-with-exactly-k-distinct-characters/
| normal | {
"blob_id": "2ca40a53291a62bbdb4386decc5a2dfa84431836",
"index": 6630,
"step-1": "#https://www.geeksforgeeks.org/count-of-substrings-of-length-k-with-exactly-k-distinct-characters/\n#https://www.geeksforgeeks.org/count-number-of-substrings-with-exactly-k-distinct-characters/\n",
"step-2": null,
"step-3": nul... | [
1
] |
<|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": "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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def attttaaaaacccckkkk():
enemy = hero.findNearest(hero.findEnemies())
if enemy:
if enemy and hero.isReady('cleave'):
hero.cleave(enemy)
else:
hero.attack(enemy)
<|reserved_special_token_0|>
<|reserved_speci... | flexible | {
"blob_id": "ce365e011d8cc88d9aa6b4df18ea3f4e70d48f5c",
"index": 4887,
"step-1": "<mask token>\n",
"step-2": "def attttaaaaacccckkkk():\n enemy = hero.findNearest(hero.findEnemies())\n if enemy:\n if enemy and hero.isReady('cleave'):\n hero.cleave(enemy)\n else:\n hero... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from .routes import generate_routes
| flexible | {
"blob_id": "06339e9cd506f147d03c54aee82473e233b4ec2e",
"index": 8853,
"step-1": "<mask token>\n",
"step-2": "from .routes import generate_routes\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def get_user(user_id=None, **kwargs):
if user_id is not None:
return User.query.get(user_id)
username = kwargs.pop('username')
if username is not None:
return User.query.filter_by(username=username).first()
raise NotImplementedError
<|reserved_special_tok... | flexible | {
"blob_id": "49c15f89225bb1dd1010510fe28dba34f6a8d085",
"index": 4866,
"step-1": "<mask token>\n\n\ndef get_user(user_id=None, **kwargs):\n if user_id is not None:\n return User.query.get(user_id)\n username = kwargs.pop('username')\n if username is not None:\n return User.query.filter_by(... | [
1,
2,
3,
4,
5
] |
# ============================================================================
# Archivo cnn_sisben.py
# autor Johan S. Mendez, Jose D. Mendez
# fecha 27/Agos/2020
# Clasificacion de beneficiarios del nuevo sistema de clasificacion del sisben
# agrupado en 4 grandes grupos de beneficiarios, se utiliza un red neuronal
... | normal | {
"blob_id": "bfb52a5ee6d88d63c4ef89dae26bb8cbecb091c6",
"index": 4200,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nseed(1)\n<mask token>\nset_random_seed(2)\nprint('\\x1b[91m Lectura de datos \\x1b[0m')\n<mask token>\nmodel.add(Conv1D(64, 32, input_shape=(x_train.shape[1], 1), activation='elu'))\nmode... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class NumericKeyboard(Bubble):
def on_touch_up(self, touch):
app = App.get_running_app()
if not self.collide_point(*touch.pos
) and not self.parent.collide_point(*touch.pos):
self.parent.remove_widget(self.parent.bubb)
app.root.ids.... | flexible | {
"blob_id": "7da8a074704b1851ac352477ef72a4c11cea1a0b",
"index": 6737,
"step-1": "<mask token>\n\n\nclass NumericKeyboard(Bubble):\n\n def on_touch_up(self, touch):\n app = App.get_running_app()\n if not self.collide_point(*touch.pos\n ) and not self.parent.collide_point(*touch.pos):\... | [
5,
9,
10,
11,
16
] |
<|reserved_special_token_0|>
def get_grads_correct(seed):
util.set_seed(seed)
theta_grads_correct = []
phi_grads_correct = []
log_weight, log_q = losses.get_log_weight_and_log_q(generative_model,
inference_network, obs, num_particles)
optimizer_phi.zero_grad()
optimizer_theta.zero_grad... | flexible | {
"blob_id": "8f558593e516aa4a769b7c5e1c95c8bc23a36420",
"index": 1232,
"step-1": "<mask token>\n\n\ndef get_grads_correct(seed):\n util.set_seed(seed)\n theta_grads_correct = []\n phi_grads_correct = []\n log_weight, log_q = losses.get_log_weight_and_log_q(generative_model,\n inference_network... | [
5,
6,
8,
9,
10
] |
# -*- coding: utf-8 -*-
__author__ = 'virtual'
statuses = {
None: {'name': 'None', },
-1: { 'name': 'unknown', },
0: { 'name': '',},
1: { 'name': 'Новый',},
2: { 'name': '',},
3: { 'name': 'Активный', },
4: { 'name': 'Приостановленный',},
5: { 'name': 'Заблокированный', },
6: { 'n... | normal | {
"blob_id": "a847fc32af2602db3b5545c15186c0209eb8ae8d",
"index": 4008,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_status_name(status):\n return '[%d]%s' % (status, statuses[status]['name'])\n",
"step-3": "__author__ = 'virtual'\nstatuses = {None: {'name': 'None'}, (-1): {'name': 'unk... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if len(argv) == 2:
docdir = argv[1]
<|reserved_special_token_0|>
spot.InsertBefore('Hello COM client world!')
newdoc.SaveAs(docdir + 'pycom.doc')
newdoc.SaveAs(docdir + 'copy.doc')
newdoc.Close()
<|reserved_special_token_0|>
f... | flexible | {
"blob_id": "df19aa720993c2385a6d025cf7ec8f3935ee4191",
"index": 9343,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(argv) == 2:\n docdir = argv[1]\n<mask token>\nspot.InsertBefore('Hello COM client world!')\nnewdoc.SaveAs(docdir + 'pycom.doc')\nnewdoc.SaveAs(docdir + 'copy.doc')\nnewdoc.Close... | [
0,
1,
2,
3,
4
] |
from bottle import response,request,route,run
from json import dumps
import ConfigParser
import pickle
import pandas as pd
import numpy as np
from sklearn.pipeline import Pipeline
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.cross_... | normal | {
"blob_id": "f0b5ad49fc47adc54fb16a151b4a0ed563f53a42",
"index": 9482,
"step-1": "from bottle import response,request,route,run\nfrom json import dumps\nimport ConfigParser\nimport pickle\nimport pandas as pd\nimport numpy as np\nfrom sklearn.pipeline import Pipeline\nfrom sklearn.feature_extraction.text import ... | [
0
] |
<|reserved_special_token_0|>
class Post(models.Model):
blog = models.ForeignKey(Blog, on_delete=models.DO_NOTHING)
user = models.ForeignKey(User, on_delete=models.CASCADE)
header = models.CharField(max_length=50)
text = models.CharField(max_length=2048)
create_date = models.DateTimeField(auto_now=... | flexible | {
"blob_id": "de77edaccdaada785f41828135ad2da4ae2b403e",
"index": 725,
"step-1": "<mask token>\n\n\nclass Post(models.Model):\n blog = models.ForeignKey(Blog, on_delete=models.DO_NOTHING)\n user = models.ForeignKey(User, on_delete=models.CASCADE)\n header = models.CharField(max_length=50)\n text = mod... | [
6,
8,
9,
10,
11
] |
# -*- coding: utf-8 -*-
"""
Created on Thu May 24 18:18:36 2018
@author: Nicole
"""
from __future__ import division
import Rod
import matplotlib.pyplot as plt
import math
class Truss:
def __init__(self,node1,node2,size,result,ax):
self.node1=node1
self.node2=node2
self.rod=Rod.Rod(node1,... | normal | {
"blob_id": "f01a1b6d0de4ba685c489af2742159447f943d2d",
"index": 5605,
"step-1": "<mask token>\n\n\nclass Truss:\n\n def __init__(self, node1, node2, size, result, ax):\n self.node1 = node1\n self.node2 = node2\n self.rod = Rod.Rod(node1, node2, result)\n self.size = size\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class NSDescriptorsViewSet(viewsets.ModelViewSet):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def get_success_headers(self, data):
return {'Location': data['_links']['self']}
def list(self, request, *args, **kwargs)... | flexible | {
"blob_id": "5e2fcc6379a8ecee0378d26108e4deab9d17dba6",
"index": 7483,
"step-1": "<mask token>\n\n\nclass NSDescriptorsViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n\n def get_success_headers(self, data):\n return {'Location': data['_links']['self']}\n\n def ... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__all__ = ['Swarmpose']
<|reserved_special_token_1|>
#a list of functions/Classes to be inported when a user imports * from swarmpose
__all__ = ['Swarmpose'] | flexible | {
"blob_id": "e375501e6b815530e61af9181d4cade83d4588ca",
"index": 8762,
"step-1": "<mask token>\n",
"step-2": "__all__ = ['Swarmpose']\n",
"step-3": "#a list of functions/Classes to be inported when a user imports * from swarmpose\n__all__ = ['Swarmpose']",
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def fun_nthfibonaccinumber(n):
n1 = 1
n2 = 1
if n == 0:
return n2
else:
for i in range(0, n - 1):
sum = n1 + n2
n1 = n2
n2 = sum
return n2
<|reserved_special_token_1|>
# Background: Th... | flexible | {
"blob_id": "40744a8530df28f0bd8648900beb8a66e2d44cd0",
"index": 7730,
"step-1": "<mask token>\n",
"step-2": "def fun_nthfibonaccinumber(n):\n n1 = 1\n n2 = 1\n if n == 0:\n return n2\n else:\n for i in range(0, n - 1):\n sum = n1 + n2\n n1 = n2\n n2 =... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with webdriver.Chrome() as browser:
browser.get('http://suninjuly.github.io/selects1.html')
time.sleep(1)
x = int(browser.find_element_by_id('num1').text)
y = int(browser.find_element_by_id('num2').text)
sum_xy... | flexible | {
"blob_id": "42be9077ec51a9be1d4923011a38cd64d829f876",
"index": 1529,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith webdriver.Chrome() as browser:\n browser.get('http://suninjuly.github.io/selects1.html')\n time.sleep(1)\n x = int(browser.find_element_by_id('num1').text)\n y = int(brow... | [
0,
1,
2,
3
] |
#! /usr/bin/env python3
import sys
def stage_merge_checksums(
old_survey=None,
survey=None,
brickname=None,
**kwargs):
'''
For debugging / special-case processing, read previous checksums, and update them with
current checksums values, then write out the result.
'''
... | normal | {
"blob_id": "a98d03b169b59704b3b592cee0b59f5389fd77b3",
"index": 8899,
"step-1": "<mask token>\n\n\ndef main():\n import argparse\n parser = argparse.ArgumentParser()\n parser.add_argument('--old-output', required=True, help=\n '\"Old\" output directory to read old checksum file from.')\n pars... | [
1,
2,
3,
4,
5
] |
from flask import render_template, request, redirect, url_for
from flask_login import current_user
from application import app, db, login_required
from application.auth.models import User
from application.memes.models import Meme
from application.comments.forms import CommentForm
# only a dummy new comment form
@app... | normal | {
"blob_id": "fe1d47b63e88935f8b2eb4bac883f3028d6f560b",
"index": 4515,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/comments/new/')\n@login_required(role='ANY')\ndef comments_form():\n return render_template('comments/new.html', form=CommentForm())\n",
"step-3": "from flask import... | [
0,
1,
2,
3
] |
v0 = 5
g = 9.81
t = 0.6
y = v0 * t - 0.5 * g * t ** 2
print(y)
| normal | {
"blob_id": "378032a8d02bc49e5ed8ebccbeddfbb281c2cbd7",
"index": 6231,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(y)\n",
"step-3": "v0 = 5\ng = 9.81\nt = 0.6\ny = v0 * t - 0.5 * g * t ** 2\nprint(y)\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class OfflineMetric:
def __init__(self, *args, **kwargs):
self.__name__ = self.name()
<|reserved_special_token_0|>
def handle_batch(self, model, x, labels, pred):
raise NotImplementedError()
def result(self):
raise NotImplementedError()
<|res... | flexible | {
"blob_id": "16bf4583b872f038edccbac4e567c1854d65e216",
"index": 4962,
"step-1": "<mask token>\n\n\nclass OfflineMetric:\n\n def __init__(self, *args, **kwargs):\n self.__name__ = self.name()\n <mask token>\n\n def handle_batch(self, model, x, labels, pred):\n raise NotImplementedError()\n... | [
18,
20,
32,
39,
46
] |
import os
import numpy
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
def plotObject(obj):
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x,y,z = numpy.nonzero(obj>0)
ax.scatter(x,y,z,c='r',s=10)
xb,yb,zb = numpy.nonzero(obj<0)
ax.scatter(xb,yb,zb,c='b',s=1)
plt.show()
c... | normal | {
"blob_id": "8475792cc2d55f030f0bd9e7d0240e3b59ed996b",
"index": 7774,
"step-1": "<mask token>\n\n\nclass GridData:\n\n def __init__(self, datafile, labelfile):\n f = open(datafile, 'rb')\n f2 = open(labelfile, 'r')\n self.samples = []\n self.labels = []\n self.label_names =... | [
2,
4,
5,
7,
8
] |
"""
db.集合.update()
"""
"""
实例 被替换了
> db.test1000.update({'name':'dapeng'},{'name':'大鹏'})
WriteResult({ "nMatched" : 1, "nUpserted" : 0, "nModified" : 1 })
> db.test1000.find()
{ "_id" : ObjectId("5c35549d7ad0cf935d3c150d"), "name" : "大鹏" }
{ "_id" : ObjectId("5c3554f37ad0cf935d3c150e"), "nInserted" : 1 }
{ "_id" : Obj... | normal | {
"blob_id": "7d8c2aa5674704d4443034c29bbdc715da9fd567",
"index": 5022,
"step-1": "<mask token>\n",
"step-2": "\"\"\"\ndb.集合.update()\n\n\"\"\"\n\"\"\"\n实例 被替换了\n> db.test1000.update({'name':'dapeng'},{'name':'大鹏'})\nWriteResult({ \"nMatched\" : 1, \"nUpserted\" : 0, \"nModified\" : 1 })\n> db.test1000.find()\n... | [
0,
1
] |
<|reserved_special_token_0|>
def latinize_word(word):
"""performs bee latin on a word"""
if word[0].lower() in 'bcdfghjklmnpqrstvwxyz':
word = word[1:] + word[0] + 'uzz'
else:
word += 'buzz'
return word.lower()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_s... | flexible | {
"blob_id": "5810739300067e8f207d09bf971484a278372a9a",
"index": 5246,
"step-1": "<mask token>\n\n\ndef latinize_word(word):\n \"\"\"performs bee latin on a word\"\"\"\n if word[0].lower() in 'bcdfghjklmnpqrstvwxyz':\n word = word[1:] + word[0] + 'uzz'\n else:\n word += 'buzz'\n return ... | [
1,
2,
3,
4,
5
] |
import requests
from requests.auth import HTTPBasicAuth
def __run_query(self, query):
URL = 'https://api.github.com/graphql'
request = requests.post(URL, json=query,auth=HTTPBasicAuth('gleisonbt', 'Aleister93'))
if request.status_code == 200:
return request.json()
else:
... | normal | {
"blob_id": "fa511411e59880fd80fba0ccc49c95d42cb4b78d",
"index": 6962,
"step-1": "<mask token>\n\n\ndef __run_query(self, query):\n URL = 'https://api.github.com/graphql'\n request = requests.post(URL, json=query, auth=HTTPBasicAuth('gleisonbt',\n 'Aleister93'))\n if request.status_code == 200:\n... | [
1,
2,
3,
4,
5
] |
# type: ignore[no-redef]
import pytest
@pytest.mark.asyncio
@pytest.mark.core
async def test_async_executor(executor):
def func():
pass
result = await executor.run(func)
assert result is None
def func():
return 1
result = await executor.run(func)
assert result == 1
def ... | normal | {
"blob_id": "67b483d9d002cc66dd368cf53fdc49ebb7b4f4d4",
"index": 9556,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@pytest.mark.asyncio\n@pytest.mark.core\nasync def test_async_executor(executor):\n\n def func():\n pass\n result = await executor.run(func)\n assert result is None\n\... | [
0,
1,
2,
3
] |
import numpy
from math import cos, sin, radians, tan
class Window:
# construtor
def __init__(self, world, xyw_min=None, xyw_max=None):
self.world = world
# caso em q é None
if xyw_min is None or xyw_max is None:
self.xyw_min = (-100, -100)
self.xyw_max = (100, 10... | normal | {
"blob_id": "deb0cd745eae97a6dbabdfab37e1c6d75e5372f0",
"index": 8422,
"step-1": "<mask token>\n\n\nclass Window:\n\n def __init__(self, world, xyw_min=None, xyw_max=None):\n self.world = world\n if xyw_min is None or xyw_max is None:\n self.xyw_min = -100, -100\n self.xyw_... | [
15,
16,
18,
20,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
prov_config.enable_ssl(leaf_domain_label=https_cert)
<|reserved_special_token_0|>
aks_service.wait_for_deployment(show_output=True)
print(aks_service.state)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
workspace_na... | flexible | {
"blob_id": "2941ecde72325d46b5c3899d4b1a213daff67147",
"index": 2613,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprov_config.enable_ssl(leaf_domain_label=https_cert)\n<mask token>\naks_service.wait_for_deployment(show_output=True)\nprint(aks_service.state)\n",
"step-3": "<mask token>\nworkspace_na... | [
0,
1,
2,
3,
4
] |
import re
print("Welcome to the Python Calculator")
print("To stop calculator type: quit")
previous = 0
run = True
def perform_math():
'''(numbers) -> numbers
accepts numbers from the user and performs continuous
mathematical equations on them.
precondition input must be numbers and m... | normal | {
"blob_id": "4122da21abab462a28c925c1afa5792ec729a75a",
"index": 5087,
"step-1": "<mask token>\n\n\ndef perform_math():\n \"\"\"(numbers) -> numbers\n\n accepts numbers from the user and performs continuous\n mathematical equations on them.\n\n precondition input must be numbers and mathematical sign... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def summarize(text):
sentences_token = sent_tokenize(text)
vectorizer = CountVectorizer(min_df=1, decode_error='replace')
sent_bow = vectorizer.fit_transform(sentences_token)
transformer = TfidfTransformer(norm='... | flexible | {
"blob_id": "b75ebcd278ae92274bbbe8d1ce5cb3bb7fa14a2c",
"index": 9637,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef summarize(text):\n sentences_token = sent_tokenize(text)\n vectorizer = CountVectorizer(min_df=1, decode_error='replace')\n sent_bow = vectorizer.fit_transform(sentences_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class State_Underway(State):
def __init__(self):
super(State_Underway, self).__init__('Underway')
class State_Paused(State):
def __init__(self):
super(State_Paused, self).__init__('Paused')
class State_Completed(State):
def __init__(self):
super(... | flexible | {
"blob_id": "e40b34f0ee51cc14615c6225a7676929e6d2876a",
"index": 2975,
"step-1": "<mask token>\n\n\nclass State_Underway(State):\n\n def __init__(self):\n super(State_Underway, self).__init__('Underway')\n\n\nclass State_Paused(State):\n\n def __init__(self):\n super(State_Paused, self).__ini... | [
25,
26,
30,
31,
34
] |
class State(object):
def __init__(self, stateName, stateLevel):
self.stateName = stateName;
self.stateLevel = stateLevel;
| normal | {
"blob_id": "73082ed2824ee65f7f4cbac47b9ebad19cec4196",
"index": 7226,
"step-1": "class State(object):\ndef __init__(self, stateName, stateLevel):\n self.stateName = stateName;\n self.stateLevel = stateLevel;\t\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
... | [
0
] |
<|reserved_special_token_0|>
def read_csv_json(file_name) ->pandas.DataFrame:
if file_name.endswith('json') or file_name.endswith('jsonl'):
df = pandas.read_json(file_name, lines=True)
elif file_name.endswith('csv'):
df = pandas.read_csv(file_name)
else:
raise NotImplementedError
... | flexible | {
"blob_id": "23f491bbf26ede9052ecdab04b8c00cc78db5a7e",
"index": 8831,
"step-1": "<mask token>\n\n\ndef read_csv_json(file_name) ->pandas.DataFrame:\n if file_name.endswith('json') or file_name.endswith('jsonl'):\n df = pandas.read_json(file_name, lines=True)\n elif file_name.endswith('csv'):\n ... | [
9,
13,
16,
18,
19
] |
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey, Float
from sqlalchemy.orm import relationship, backref
ORMBase = declarative_base()
def create_all(engine):
ORMBase.metadata.create_all(engine)
| normal | {
"blob_id": "c7ca8235864ce5de188c4aa2feb9ad82d4fa9b0f",
"index": 4023,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef create_all(engine):\n ORMBase.metadata.create_all(engine)\n",
"step-3": "<mask token>\nORMBase = declarative_base()\n\n\ndef create_all(engine):\n ORMBase.metadata.create_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_rect():
rect = Rectangle([[0, 0], [10, 10]], confidence=0.8, labels=[{'name':
'test'}])
test = Rectangle([[0, 0], [5, 5]])
assert rect.area == 100
assert rect.intersection(test) == 25
assert ... | flexible | {
"blob_id": "b65d25198d55ab4a859b9718b7b225fa92c13a2b",
"index": 1202,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_rect():\n rect = Rectangle([[0, 0], [10, 10]], confidence=0.8, labels=[{'name':\n 'test'}])\n test = Rectangle([[0, 0], [5, 5]])\n assert rect.area == 100\n ... | [
0,
1,
2,
3,
4
] |
"""
opsi-utils
Test utilities
"""
import os
import tempfile
from contextlib import contextmanager
from pathlib import Path
from typing import Generator
@contextmanager
def temp_context() -> Generator[Path, None, None]:
origin = Path().absolute()
try:
with tempfile.TemporaryDirectory(ignore_cleanup_errors=True) ... | normal | {
"blob_id": "3c2a611fd001f145703853f5ecfe70d0e93844e4",
"index": 4665,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@contextmanager\ndef temp_context() ->Generator[Path, None, None]:\n origin = Path().absolute()\n try:\n with tempfile.TemporaryDirectory(ignore_cleanup_errors=True\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def df_to_sql_T_1(filefullpath, sheet, row_name):
excel_df = pd.read_excel(filefullpath, sheetname=sheet)
excel_df = excel_df.dropna(how='all')
excel_df = excel_df.dropna(axis=1, how='all')
excel_df = excel_df.T
excel_df.columns = excel_df.loc[row_name]
excel_df = ... | flexible | {
"blob_id": "d261efa72e1ab77507a1fd84aa2e462c6969af56",
"index": 6579,
"step-1": "<mask token>\n\n\ndef df_to_sql_T_1(filefullpath, sheet, row_name):\n excel_df = pd.read_excel(filefullpath, sheetname=sheet)\n excel_df = excel_df.dropna(how='all')\n excel_df = excel_df.dropna(axis=1, how='all')\n exc... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name='RBM', version='0.0.1', description=
'Restricted Boltzmann Machines', long_description='README',
install_requires=['numpy', 'pandas'])
<|reserved_special_token_1|>
from distutils.core import setup
setup(name=... | flexible | {
"blob_id": "fab7ee8a7336ba2c044adce4cc8483af78b775ba",
"index": 1827,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='RBM', version='0.0.1', description=\n 'Restricted Boltzmann Machines', long_description='README',\n install_requires=['numpy', 'pandas'])\n",
"step-3": "from distutils... | [
0,
1,
2,
3
] |
#coding=utf-8
import unittest,time,os
from time import sleep
from appium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from HTMLTestRunner import HTMLTestRunner
from appium.webdriver.common.touch_action import TouchAction
from pub_Student import login,logout
# Returns ... | normal | {
"blob_id": "8d7697a0e49dc9e966b9657171c66ccda57279d6",
"index": 1930,
"step-1": "<mask token>\n\n\nclass TestStudent(unittest.TestCase):\n\n def setUp(self):\n desired_caps = {}\n desired_caps['platformName'] = 'Android'\n desired_caps['platformVersion'] = '7.0'\n desired_caps['au... | [
5,
6,
7,
8,
9
] |
from rest_framework import serializers, viewsets, routers
from lamp_control.models import Lamp
class LampSerializer(serializers.HyperlinkedModelSerializer):
class Meta:
model = Lamp
fields = '__all__'
class LampViewSet(viewsets.ModelViewSet):
serializer_class = LampSerializer
queryset ... | normal | {
"blob_id": "aff1d702e591efcfc0fc93150a3fbec532408137",
"index": 55,
"step-1": "<mask token>\n\n\nclass LampViewSet(viewsets.ModelViewSet):\n serializer_class = LampSerializer\n queryset = Lamp.objects.all()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass LampSerializer(serializers.HyperlinkedMo... | [
2,
3,
5,
6,
7
] |
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