code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
import os
import sys
from tensor2tensor.bin import t2t_trainer
def problem_args(problem_name):
args = [
'--generate_data',
'--model=transformer',
'--hparams_set=transformer_librispeech_v1',
'--problem=%s' % problem_name,
'--data_dir=/tmp/refactor_test/problems/%s/data' % problem_name,
'--t... | normal | {
"blob_id": "cc5ad95419571d3eb2689b428e5805ad69958806",
"index": 4796,
"step-1": "<mask token>\n\n\ndef problem_args(problem_name):\n args = ['--generate_data', '--model=transformer',\n '--hparams_set=transformer_librispeech_v1', '--problem=%s' %\n problem_name, '--data_dir=/tmp/refactor_test/pr... | [
1,
2,
3,
4,
5
] |
# -*- coding: utf-8 -*-
from django.db import models
from filebrowser.fields import FileBrowseField
from localisations.models import Ville, Lieu
from model_utils.managers import InheritanceManager
from services.models import Service
from equipements.models import Equipement
from localisations.models import Ville
from d... | normal | {
"blob_id": "596fe474ae60dd6a06123df6fe246f7e947b3482",
"index": 1760,
"step-1": "<mask token>\n\n\nclass SaisonCulturelle(Saison):\n\n def __unicode__(self):\n return self.nom\n\n\nclass Festival(Saison):\n saison_culture = models.ForeignKey(SaisonCulturelle)\n\n def __unicode__(self):\n ... | [
30,
33,
34,
36,
39
] |
# Return min number of hacks (swap of adjacent instructions)
# in p so that total damage <= d.
# If impossible, return -1
def min_hacks(d, p):
# list containing number of shoot commands per
# damage level. Each element is represents a
# damage level; 1, 2, 4, 8, ... and so on.
shots = [0]
damage = 0
for c ... | normal | {
"blob_id": "607700faebc2018327d66939419cc24a563c3900",
"index": 6515,
"step-1": "<mask token>\n",
"step-2": "def min_hacks(d, p):\n shots = [0]\n damage = 0\n for c in p:\n if c == 'S':\n shots[-1] += 1\n damage += 2 ** (len(shots) - 1)\n else:\n shots.a... | [
0,
1,
2,
3,
4
] |
""""
You are given a tree-like data structure represented as nested dictionaries.
Implement a function collect_leaves that accepts a tree and returns a list of all its leaves. A leaf is a bottom-most node in a tree.
Implement a kind of unit tests via assert operator.
"""
from typing import Union
def collect... | normal | {
"blob_id": "603cce951dd0f78ef3ca9dce587042b3b7f6b449",
"index": 8001,
"step-1": "<mask token>\n\n\ndef collect_leaves(u: Union[dict, list]) ->list:\n flatten_list = []\n if isinstance(u, dict):\n for item in u.values():\n flatten_list.extend(collect_leaves(item))\n return flatten_... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@router.post('/create-job', response_model=ShowJob)
def create_job(job: JobCreate, db: Session=Depends(get_db), current_user:
User=Depends(get_current_user_from_token)):
owner_id = current_user.id
job = create_new_job(job=job, db=db, owner_id=owner_id)
return job
@router... | flexible | {
"blob_id": "e8092faed22607f9c8f18a79709022037ff647bf",
"index": 9625,
"step-1": "<mask token>\n\n\n@router.post('/create-job', response_model=ShowJob)\ndef create_job(job: JobCreate, db: Session=Depends(get_db), current_user:\n User=Depends(get_current_user_from_token)):\n owner_id = current_user.id\n ... | [
4,
5,
6,
7,
8
] |
import openpyxl as opx
import pyperclip
from openpyxl import Workbook
from openpyxl.styles import PatternFill
wb = Workbook(write_only=True)
ws = wb.create_sheet()
def parseSeq(lines,seqName):
'''splits each column'''
data = []
for line in lines: data.append(line.split(' '))
'''remov... | normal | {
"blob_id": "19e387cb731dad21e5ee50b0a9812df984c13f3b",
"index": 7890,
"step-1": "<mask token>\n\n\ndef parseSeq(lines, seqName):\n \"\"\"splits each column\"\"\"\n data = []\n for line in lines:\n data.append(line.split(' '))\n \"\"\"removes any spaces\"\"\"\n for i in range(len(data)):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
admin.autodiscover()
<|reserved_special_token_0|>
dajaxice_autodiscover()
<|reserved_special_token_0|>
urlpatterns += staticfiles_urlpatterns()
urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
<|reser... | flexible | {
"blob_id": "68a503b2a94304530e20d79baf9fb094024ba67e",
"index": 539,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.autodiscover()\n<mask token>\ndajaxice_autodiscover()\n<mask token>\nurlpatterns += staticfiles_urlpatterns()\nurlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Vasicek:
def __init__(self, rs, vol):
self.t = rs.columns
self.ps = rs[-1:]
self.sigma = vol
<|reserved_special_token_0|>
def loss(self, x):
self.a = x[0]
self.b = x[1]
self.sim_rs = apply(self.get_TheoreticalP, self.ps)
... | flexible | {
"blob_id": "b6470ffda9040223951a99abc600ce1e99fe146b",
"index": 7902,
"step-1": "<mask token>\n\n\nclass Vasicek:\n\n def __init__(self, rs, vol):\n self.t = rs.columns\n self.ps = rs[-1:]\n self.sigma = vol\n <mask token>\n\n def loss(self, x):\n self.a = x[0]\n self... | [
3,
5,
6,
8,
9
] |
class Solution:
def containsDuplicate(self, nums) -> bool:
d = {} # store the elements which already exist
for elem in nums:
if elem in d:
return True
else:
d[elem] = 1
return False
print(Solution().containsDuplicate([0])) | normal | {
"blob_id": "89256a38208be92f87115b110edc986cebc95306",
"index": 8440,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution:\n\n def containsDuplicate(self, nums) ->bool:\n d = {}\n for elem in nums:\n if elem in ... | [
0,
1,
2,
3,
4
] |
#!/bin/env python
import sys
import os
import collections
import re
import json
import urllib
import urllib.request
import uuid
import time
PROCESSOR_VERSION = "0.1"
def process(trace_dir, out_dir):
#order files
trace_files = os.listdir(trace_dir)
trace_files = sorted(trace_files)
if trace_files[0] ==... | normal | {
"blob_id": "4b83887e8d8e5c5dc7065354d24044d3c3a48714",
"index": 3387,
"step-1": "<mask token>\n\n\ndef process(trace_dir, out_dir):\n trace_files = os.listdir(trace_dir)\n trace_files = sorted(trace_files)\n if trace_files[0] == 'error.log':\n print('Rotating to properly order logs.')\n t... | [
2,
3,
4,
5,
6
] |
from django.urls import path
from admin_panel import views
urlpatterns = [path('admin_panel/', views.AdminPanel.as_view(), name=
'admin_panel'), path('admin_panel/connection/', views.Connection.
as_view(), name='connect_group-teacher'), path(
'admin_panel/connection/<str:choiced_departament>', views.Connect... | normal | {
"blob_id": "34a7fd66a9e2eae25994336f22a76c24c11a6e1b",
"index": 7408,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('admin_panel/', views.AdminPanel.as_view(), name=\n 'admin_panel'), path('admin_panel/connection/', views.Connection.\n as_view(), name='connect_group-teacher'),... | [
0,
1,
2
] |
from rdflib import Graph
from rdflib.plugins.sparql import prepareQuery
def is_file_ontology(file_path):
"""
Method that, given a file, returns its URI.
This method is in a separate file in case we want to extract additional metadata if required
Parameters
----------
@param file_path: path of ... | normal | {
"blob_id": "c327f8f7aece1a9c25079613809df52e9a8e7a52",
"index": 8763,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef is_file_ontology(file_path):\n \"\"\"\n Method that, given a file, returns its URI.\n This method is in a separate file in case we want to extract additional metadata if ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class MD(BaseEstimator, TransformerMixin):
<|reserved_special_token_0|>
def _init_graph(self):
"""
Init a tensorflow Graph containing: input data, variables, model, loss, optimizer
"""
self.graph = tf.Graph()
with self.graph.as_default():
... | flexible | {
"blob_id": "a9947884e805cc8fcb6bff010a5f6e0ff0bb01fe",
"index": 8393,
"step-1": "<mask token>\n\n\nclass MD(BaseEstimator, TransformerMixin):\n <mask token>\n\n def _init_graph(self):\n \"\"\"\n Init a tensorflow Graph containing: input data, variables, model, loss, optimizer\n \"\"\"... | [
4,
8,
9,
11,
13
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
workdir = './model/adamW-BCE/model_seresnext50_32x4d_i768_runmila_2fold_50ep'
seed = 300
n_fold = 2
epoch = 50
resume_from = None
batch_size = 32
num_workers = 32
imgsize = 768, 768
loss = dict(name='BCEWithLogitsLoss', params=dict())
optim = dict(name='AdamW... | flexible | {
"blob_id": "8030bdb6c9f0b7114916d7abc245ff680d1fc917",
"index": 6790,
"step-1": "<mask token>\n",
"step-2": "workdir = './model/adamW-BCE/model_seresnext50_32x4d_i768_runmila_2fold_50ep'\nseed = 300\nn_fold = 2\nepoch = 50\nresume_from = None\nbatch_size = 32\nnum_workers = 32\nimgsize = 768, 768\nloss = dict... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class mutasibankjurnal(ReportXlsx):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class mutasibankjurnal(ReportXlsx):
def generate_xlsx_report(self, workbook, data, wizard):
bold = workbook.add_f... | flexible | {
"blob_id": "950929edc82bf78ee33df117fba370b937255adc",
"index": 1703,
"step-1": "<mask token>\n\n\nclass mutasibankjurnal(ReportXlsx):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass mutasibankjurnal(ReportXlsx):\n\n def generate_xlsx_report(self, workbook, data, wizard):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class SingleTouchReading:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __init__(self, ribbon):
self.ribbon = ribbon
self.read_raw_lower()
self.read_raw_upper()
self.process_readings()
def prepare_to_read(self):
act... | flexible | {
"blob_id": "06caee24b9d0bb78e646f27486b9a3a0ed5f2502",
"index": 6796,
"step-1": "<mask token>\n\n\nclass SingleTouchReading:\n <mask token>\n <mask token>\n\n def __init__(self, ribbon):\n self.ribbon = ribbon\n self.read_raw_lower()\n self.read_raw_upper()\n self.process_re... | [
20,
32,
40,
43,
50
] |
from turtle import *
import time
import random
colormode(255)
class Ball(Turtle):
def __init__(self, x,y,dx,dy,r):
Turtle.__init__(self)
self.pu()
self.goto(x,y)
self.dx = dx
self.dy = dy
self.r = r
self.shape("circle")
self.shapesize(r/10)
r ... | normal | {
"blob_id": "17cd6746e58a7f33bc239c1420d51c6810ed02d8",
"index": 3575,
"step-1": "<mask token>\n\n\nclass Ball(Turtle):\n\n def __init__(self, x, y, dx, dy, r):\n Turtle.__init__(self)\n self.pu()\n self.goto(x, y)\n self.dx = dx\n self.dy = dy\n self.r = r\n s... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
output.write("""{}
{}
{}
{}
{}
{}
{}
""".format(line1, line2, line3, line4,
line5, line6, line7))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
bank_data = 'Resources/budget_data.csv'
bank_df = pd.read_csv(bank_... | flexible | {
"blob_id": "1ad694c68ef264c6fbba4f4b9c069f22818d2816",
"index": 9973,
"step-1": "<mask token>\n",
"step-2": "<mask token>\noutput.write(\"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n\"\"\".format(line1, line2, line3, line4,\n line5, line6, line7))\n",
"step-3": "<mask token>\nbank_data = 'Resources/budget_data.csv'\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Ui_MainWindow(QMainWindow):
threads = []
keywordJudge = ''
def __init__(self):
super(Ui_MainWindow, self).__init__()
self.buy_succeed_count = 0
for func in [self.output_buy_record, self.output_login_status, self
.output_register_recor... | flexible | {
"blob_id": "bc0846397a5ad73b1c4b85e12864b27ef4fd08d7",
"index": 5358,
"step-1": "<mask token>\n\n\nclass Ui_MainWindow(QMainWindow):\n threads = []\n keywordJudge = ''\n\n def __init__(self):\n super(Ui_MainWindow, self).__init__()\n self.buy_succeed_count = 0\n for func in [self.o... | [
25,
26,
30,
32,
33
] |
def tetrahedron_filled(tetrahedrons, water):
var=0
br=0
tetrahedrons.sort()
for numbers in tetrahedrons:
v=(tetrahedrons[var]**3*(2**0.5))/12000
if v<water:
br=br+1
water=water-v
var=var+1
print (br)
print (tetrahedron_filled([1000,10],10)) | normal | {
"blob_id": "c926e16ef2daa5978b6c71e7794721d320bb9b1e",
"index": 1224,
"step-1": "<mask token>\n",
"step-2": "def tetrahedron_filled(tetrahedrons, water):\n var = 0\n br = 0\n tetrahedrons.sort()\n for numbers in tetrahedrons:\n v = tetrahedrons[var] ** 3 * 2 ** 0.5 / 12000\n if v < w... | [
0,
1,
2,
3
] |
#! /usr/bin/env python
from thor.tree import TreeNode
class Solution(object):
def postorder_traversal(self, root: TreeNode):
if not root:
return []
else:
return self.postorder_traversal(root.left) + self.postorder_traversal(root.right) + [root.val]
| normal | {
"blob_id": "1d314a04625cfadf574f122b95577c1e677a8b35",
"index": 3247,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution(object):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution(object):\n\n def postorder_traversal(self, root: TreeNode):\n if not root:\n ... | [
0,
1,
2,
3,
4
] |
# Generated by Django 3.1.1 on 2020-10-10 07:38
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('socialapp', '0004_mesage... | normal | {
"blob_id": "38751da57ad7c786e9fc0722faf065380e5f7e60",
"index": 4994,
"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 = [migrations.sw... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def std_dev(L, is_sample=0):
"""calculate standard deviation of given List"""
return math.sqrt(variance(L, is_sample))
def z_score(num, mean, std_dev):
"""calculate z-score given sample size, mean and standard deviation"""
return (num - mean) / std_dev
<|reserved_speci... | flexible | {
"blob_id": "34acb6da1dc9403a311ce3bca0a828a77b7b36da",
"index": 7403,
"step-1": "<mask token>\n\n\ndef std_dev(L, is_sample=0):\n \"\"\"calculate standard deviation of given List\"\"\"\n return math.sqrt(variance(L, is_sample))\n\n\ndef z_score(num, mean, std_dev):\n \"\"\"calculate z-score given sampl... | [
7,
14,
15,
17,
19
] |
<|reserved_special_token_0|>
def cauchy_model(x, a, loc, scale, y0):
return a * cauchy.pdf(x, loc, scale) + y0
def cauchy_fit(x, y, d):
if d is -1:
a0 = -(max(y) - min(y)) * (max(x) - min(x)) / 10
loc0 = x[np.argmin(y)]
scale0 = (max(x) - min(x)) / 10
y00 = max(y)
elif d ... | flexible | {
"blob_id": "aee8fa7bc1426945d61421fc72732e43ddadafa1",
"index": 3191,
"step-1": "<mask token>\n\n\ndef cauchy_model(x, a, loc, scale, y0):\n return a * cauchy.pdf(x, loc, scale) + y0\n\n\ndef cauchy_fit(x, y, d):\n if d is -1:\n a0 = -(max(y) - min(y)) * (max(x) - min(x)) / 10\n loc0 = x[np.... | [
4,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
def get(restaurant_id):
with thrift_client('ers') as ers:
cert = ers.get_restaurant_certification(restaurant_id)
cert.comment = cert.comment.encode('utf-8')
return cert
<|reserved_special_token_0|>
def add(cert):
with thrift_client('ers') as ers:
ers.ad... | flexible | {
"blob_id": "746971cd6c5bf65268e89303c8f4ce98a56eb111",
"index": 8011,
"step-1": "<mask token>\n\n\ndef get(restaurant_id):\n with thrift_client('ers') as ers:\n cert = ers.get_restaurant_certification(restaurant_id)\n cert.comment = cert.comment.encode('utf-8')\n return cert\n\n\n<mask token>\n\... | [
4,
5,
6,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
random.seed(1)
np.random.seed(1)
tf.random.set_random_seed(1)
<|reserved_special_token_0|>
for i in range(1, 6):
df = pd.read_csv(random_sample_save_folder_path +
'power_demand_sample%i.csv' % i, index_col=0)
regi... | flexible | {
"blob_id": "d78ac5188cad104ee1b3e214898c41f843b6d8c0",
"index": 5185,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrandom.seed(1)\nnp.random.seed(1)\ntf.random.set_random_seed(1)\n<mask token>\nfor i in range(1, 6):\n df = pd.read_csv(random_sample_save_folder_path + \n 'power_demand_sample%... | [
0,
1,
2,
3,
4
] |
# Libraries
from sqlalchemy import Column, ForeignKey, Integer, String
from sqlalchemy.ext.associationproxy import association_proxy
from sqlalchemy.orm import relationship
# Taskobra
from taskobra.orm.base import ORMBase
from taskobra.orm.relationships import SystemComponent
class System(ORMBase):
__tablename__ ... | normal | {
"blob_id": "2fc2fd6631cee5f3737dadaac1a115c045af0986",
"index": 5058,
"step-1": "<mask token>\n\n\nclass System(ORMBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def add_component(self, component):\n for system_component in self.s... | [
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
def index(request):
posts = Post.objects.order_by('-created_at').filter(status='Published')
paginator = Paginator(posts, 9)
page = request.GET.get('page')
post_listings = paginator.get_page(page)
context = {'posts': post_listings}
return render(request, 'hub/index.... | flexible | {
"blob_id": "ee3718dee869a58089e897489af2eec3ff72be56",
"index": 3478,
"step-1": "<mask token>\n\n\ndef index(request):\n posts = Post.objects.order_by('-created_at').filter(status='Published')\n paginator = Paginator(posts, 9)\n page = request.GET.get('page')\n post_listings = paginator.get_page(pag... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
def article_list(request):
articles = Article.objects.all()
return render(request, 'board/list.html', {'articles': articles})
def article_detail(request, article_id):
article = get_object_or_404(Article, id=article_id)
comments = article.comment_set.all()
return rend... | flexible | {
"blob_id": "6946601050802aaaa559d25612d0d4f5116559eb",
"index": 1845,
"step-1": "<mask token>\n\n\ndef article_list(request):\n articles = Article.objects.all()\n return render(request, 'board/list.html', {'articles': articles})\n\n\ndef article_detail(request, article_id):\n article = get_object_or_40... | [
5,
6,
7,
8,
9
] |
# -*- coding: utf-8 -*-
"""
ORIGINAL PROGRAM SOURCE CODE:
1: from __future__ import division, print_function, absolute_import
2:
3: import os
4: from os.path import join
5:
6: from scipy._build_utils import numpy_nodepr_api
7:
8:
9: def configuration(parent_package='',top_path=None):
10: from numpy.distutils.... | normal | {
"blob_id": "4453b8176cda60a3a8f4800860b87bddfdb6cafa",
"index": 7963,
"step-1": "<mask token>\n\n\n@norecursion\ndef configuration(localization, *varargs, **kwargs):\n global module_type_store\n str_32070 = get_builtin_python_type_instance(stypy.reporting.\n localization.Localization(__file__, 9, 3... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for classifier in classifiers:
classifier.fit(training_data[:1500], validation_data[:1500])
expected = validation_data[681:]
predicted = classifier.predict(training_data[681:])
print('Classification report for clas... | flexible | {
"blob_id": "3024359710148bfbb15677973555f214b1f878b7",
"index": 1521,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor classifier in classifiers:\n classifier.fit(training_data[:1500], validation_data[:1500])\n expected = validation_data[681:]\n predicted = classifier.predict(training_data[68... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_lang_dirs(path):
languages = []
for name in os.listdir(path):
dir_path = os.path.join(path, name)
if os.path.isdir(dir_path):
cards_file = os.path.join(dir_path, 'cards_' + name + '.json')
sets_file = os.path.join(dir_path, 'sets_' +... | flexible | {
"blob_id": "cc1b3c3c65e8832316f72cbf48737b21ee4a7799",
"index": 3887,
"step-1": "<mask token>\n\n\ndef get_lang_dirs(path):\n languages = []\n for name in os.listdir(path):\n dir_path = os.path.join(path, name)\n if os.path.isdir(dir_path):\n cards_file = os.path.join(dir_path, 'c... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
class RoRo(Monument):
def set_adm_location(self):
counties = self.data_files['counties']
self.set_from_dict_match(counties, 'iso_code', 'judetul_iso',
'located_adm')
<|reserved_special_token_0|>
def set_heritage_id(self):
self.add_statemen... | flexible | {
"blob_id": "5f8a9d82a3245671b438475d1fac7be4db769fbe",
"index": 8493,
"step-1": "<mask token>\n\n\nclass RoRo(Monument):\n\n def set_adm_location(self):\n counties = self.data_files['counties']\n self.set_from_dict_match(counties, 'iso_code', 'judetul_iso',\n 'located_adm')\n <mas... | [
4,
5,
8,
9,
11
] |
<|reserved_special_token_0|>
class MultiSpeakerBRIR(SimpleFreeFieldHRIR):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def add_metadata(self, database):
super().add_metadata(database)
database.Data.Type = 'FIRE'
database.Room.Type = 'r... | flexible | {
"blob_id": "e30bd33ae18881307e7cf4f60d3c60eae91573bc",
"index": 181,
"step-1": "<mask token>\n\n\nclass MultiSpeakerBRIR(SimpleFreeFieldHRIR):\n <mask token>\n <mask token>\n <mask token>\n\n def add_metadata(self, database):\n super().add_metadata(database)\n database.Data.Type = 'FIR... | [
2,
3,
4,
5,
6
] |
from .base import BaseLevel
from map_objects import DefinedMap
from entity.monster import Daemon
from entity.weapons import Axe
class FinalLevel(BaseLevel):
def __init__(self):
lvl_map = DefinedMap('levels/demon_lair.xp')
super().__init__(lvl_map.width, lvl_map.height)
self.map = lvl_map
... | normal | {
"blob_id": "7ba8f0bd962413f6ff825df27330447b11360f10",
"index": 6089,
"step-1": "<mask token>\n\n\nclass FinalLevel(BaseLevel):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass FinalLevel(BaseLevel):\n\n def __init__(self):\n lvl_map = DefinedMap('levels/demon_lair.xp')\n ... | [
1,
2,
3,
4
] |
# !/usr/bin/python
# sudo mn --custom _mininet_topo.py --topo mytopo,5
# sudo mn --custom _mininet_topo.py --topo mytopo,3 --test simpletest
# or just run this python file
from mininet.topo import Topo
from mininet.net import Mininet
from mininet.util import dumpNodeConnections
from mininet.log import setLogLevel
fro... | normal | {
"blob_id": "8fd74287fbc653ea3ed4aa76a272486aa29185cf",
"index": 1032,
"step-1": "# !/usr/bin/python\n\n# sudo mn --custom _mininet_topo.py --topo mytopo,5\n# sudo mn --custom _mininet_topo.py --topo mytopo,3 --test simpletest\n# or just run this python file\n\nfrom mininet.topo import Topo\nfrom mininet.net imp... | [
0
] |
<|reserved_special_token_0|>
class AEalLayerColorTemplate(alShadersTemplate):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class AEalLayerColorTemplate(alShadersTemplate):
<|reserved_special_token_... | flexible | {
"blob_id": "c847e7abe36b62c4518bb535789064e22b5f1db7",
"index": 5750,
"step-1": "<mask token>\n\n\nclass AEalLayerColorTemplate(alShadersTemplate):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass AEalLayerColorTemplate(alShadersTemplate):\n <mask token>\n <ma... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@conf
def load_debug_linux_x64_settings(conf):
"""
Setup all compiler and linker settings shared over all linux_x64 configurations for
the 'debug' configuration
"""
v = conf.env
load_linux_x64_common_settings(v)
@conf
def load_profile_linux_x64_settings(conf):
"""
Se... | flexible | {
"blob_id": "5848273a76995825f01df53d6beed534e6f9f9fe",
"index": 8730,
"step-1": "<mask token>\n\n\n@conf\ndef load_debug_linux_x64_settings(conf):\n \"\"\"\n\tSetup all compiler and linker settings shared over all linux_x64 configurations for\n\tthe 'debug' configuration\n\t\"\"\"\n v = conf.env\n load... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(amount_of_bullets):
print(i)
baraban[i] = 1
print('Посмотрите на барабан', baraban)
<|reserved_special_token_0|>
for i in range(how_much):
random.shuffle(baraban)
if baraban[0] == 1:
print('Б... | flexible | {
"blob_id": "6c0080aa62579b4cbdaf3a55102924bfe31ffb40",
"index": 8107,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(amount_of_bullets):\n print(i)\n baraban[i] = 1\nprint('Посмотрите на барабан', baraban)\n<mask token>\nfor i in range(how_much):\n random.shuffle(baraban)\n if... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
pathlib.Path(DIR).mkdir(parents=True, exist_ok=True)
print('--------Query Topshot GraphQL Endpoint--------')
for setsId in setsIdList:
for setId in setsId:
count += 1
query = gql(
"""
{
... | flexible | {
"blob_id": "df518fd719b7eafffd8fee92c926d4d24b65ce18",
"index": 7877,
"step-1": "<mask token>\n",
"step-2": "<mask token>\npathlib.Path(DIR).mkdir(parents=True, exist_ok=True)\nprint('--------Query Topshot GraphQL Endpoint--------')\nfor setsId in setsIdList:\n for setId in setsId:\n count += 1\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if v % 4 == 0:
print('Yeah!')
else:
print('End of the program')
<|reserved_special_token_1|>
v = 426
if v % 4 == 0:
print('Yeah!')
else:
print('End of the program')
<|reserved_special_token_1|>
v = 426
# prin... | flexible | {
"blob_id": "ceca1be15aded0a842c5f2c6183e4f54aba4fd24",
"index": 6752,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif v % 4 == 0:\n print('Yeah!')\nelse:\n print('End of the program')\n",
"step-3": "v = 426\nif v % 4 == 0:\n print('Yeah!')\nelse:\n print('End of the program')\n",
"step... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class TeamWordBinding(ResourceBinding):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@classmethod
def group_names(self, instance, action):
return [str(instance.user.group.team)]
de... | flexible | {
"blob_id": "c2e0f2eda6ef44a52ee4e192b8eb71bde0a69bff",
"index": 8954,
"step-1": "<mask token>\n\n\nclass TeamWordBinding(ResourceBinding):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @classmethod\n def group_names(self, instance, action):\n return [str(instance.user.... | [
13,
14,
15,
17,
18
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
curforth.execute(sql)
<|reserved_special_token_0|>
for record in result:
print(record)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
forth = sqlite3.connect('databaserupin.db')
sql = 'SELECT * from rupin;'
curfo... | flexible | {
"blob_id": "a7f082737bf476a4bc6a40c962764c05bed9ee14",
"index": 9247,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncurforth.execute(sql)\n<mask token>\nfor record in result:\n print(record)\n",
"step-3": "<mask token>\nforth = sqlite3.connect('databaserupin.db')\nsql = 'SELECT * from rupin;'\ncur... | [
0,
1,
2,
3,
4
] |
# https://leetcode-cn.com/problems/zigzag-conversion/
# 6. Z 字形变换
class Solution:
def convert(self, s: str, numRows: int) -> str:
res = ''
for i in range(numRows):
pass
return res
| normal | {
"blob_id": "aa952e8f9a1855b5578cb26d6e5aca42605ee585",
"index": 5454,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def convert(self, s: str, numRows: int) ->str:\n res = ''\n for i in range(numRows):\n pass\n r... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
n = int(input())
a_list = list(map(int, input().split()))
a_list_reversed, num_reverse = bubble_sort(a_list, n)
print(' '.join(map(str, a_list_reversed)))
print(num_reverse)
<|reserved_special_t... | flexible | {
"blob_id": "fef1273552350bfaf075d90279c9f10a965cae25",
"index": 2939,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n n = int(input())\n a_list = list(map(int, input().split()))\n a_list_reversed, num_reverse = bubble_sort(a_list, n)\n print(' '.join(map(str, a_list_reversed... | [
0,
1,
2,
3,
4
] |
import os
# must pip install sox
# type sudo apt install sox into cmd
duration = .2 # seconds
freq = 550 # Hz
os.system('play -nq -t alsa synth {} sine {}'.format(duration, freq))
| normal | {
"blob_id": "8397dcdcb9ec2f35dac0c26b8878a23f9149512b",
"index": 3113,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nos.system('play -nq -t alsa synth {} sine {}'.format(duration, freq))\n",
"step-3": "<mask token>\nduration = 0.2\nfreq = 550\nos.system('play -nq -t alsa synth {} sine {}'.format(durat... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@pytest.fixture()
def test_data():
"""Return data used for tests in this file."""
x = np.array([8, 67, 79, 10, 52, 53, 98, 34, 15, 58], dtype=float)
y = np.array([24, 87, 48, 94, 98, 66, 14, 24, 60, 16], dtype=float)
z = np.array([0.064, 4.489, 6.241, 0.1, 2.704, 2.809, 9.... | flexible | {
"blob_id": "9e987e057ee5322765415b84e84ef3c4d2827742",
"index": 5466,
"step-1": "<mask token>\n\n\n@pytest.fixture()\ndef test_data():\n \"\"\"Return data used for tests in this file.\"\"\"\n x = np.array([8, 67, 79, 10, 52, 53, 98, 34, 15, 58], dtype=float)\n y = np.array([24, 87, 48, 94, 98, 66, 14, ... | [
7,
9,
10,
11,
13
] |
<|reserved_special_token_0|>
def walkDockerfiles(path, splitFirt=True):
""" 遍历目录中的所有dockerfile
Arguments:
path {string} -- 目录路径
Keyword Arguments:
splitFirt {bool} -- 去除文件开头的path (default: {True})
Returns:
array -- dockerfile文件列表
"""
files_list = []
i... | flexible | {
"blob_id": "400f9b6fb0ab73a920e6b73373615b2f8d1103bb",
"index": 2301,
"step-1": "<mask token>\n\n\ndef walkDockerfiles(path, splitFirt=True):\n \"\"\" 遍历目录中的所有dockerfile\n \n Arguments:\n path {string} -- 目录路径\n \n Keyword Arguments:\n splitFirt {bool} -- 去除文件开头的path (default: {True... | [
3,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
class MTCNN:
def __init__(self, device=None, model=None):
if device is None:
device = 'cuda' if torch.cuda.is_available() else 'cpu'
self.device = device
url = 'https://github.com/deepware/dFace/raw/master/models/mtcnn.pt'
if model is None:... | flexible | {
"blob_id": "865121e7eb5f9c70adf44d33d21f30c22f13ec56",
"index": 7012,
"step-1": "<mask token>\n\n\nclass MTCNN:\n\n def __init__(self, device=None, model=None):\n if device is None:\n device = 'cuda' if torch.cuda.is_available() else 'cpu'\n self.device = device\n url = 'https... | [
17,
18,
19,
21,
23
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Book(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Book(models.Model):
title = models.TextField(max_length=32, blank=False, null=False)
<|reserve... | flexible | {
"blob_id": "8286407987301ace7af97d6acdcf6299ce3d8525",
"index": 5440,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Book(models.Model):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Book(models.Model):\n title = models.TextField(max_length=32, blank=False, null=False)\n",
"s... | [
0,
1,
2,
3,
4
] |
from django.http import HttpResponseRedirect
from django.shortcuts import render
from django.views.generic import TemplateView
from pos.service.sumup import API_URL, create_checkout
from pos.models.sumup import SumUpAPIKey, SumUpOnline
from pos.forms import RemotePayForm
from pos.models.user import User
class Remote... | normal | {
"blob_id": "731d2891bbc29879fd8900a11077c93550e4e88d",
"index": 4251,
"step-1": "<mask token>\n\n\nclass RemotePayView(TemplateView):\n template_name = 'remotepay/pay.djhtml'\n\n\n<mask token>\n\n\ndef pay_callback(request, checkoutid):\n t = SumUpOnline.objects.get(transaction_id=checkoutid)\n if t.st... | [
3,
4,
7,
8,
9
] |
import os
from apps.app_base.app_utils.cryp_key import decrypt, get_secret_key
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
SECRET_KEY = get_secret_key
DEBUG = True
ALLOWED_HOSTS = ['.localhost', '127.0.0.1', '[::1]']
# Application definition
INSTALLED_APPS = [
'corsheaders',
'd... | normal | {
"blob_id": "027a049ffced721f2cd697bc928bfdf718630623",
"index": 4692,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nBASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))\nSECRET_KEY = get_secret_key\nDEBUG = True\nALLOWED_HOSTS = ['.localhost', '127.0.0.1', '[::1]']\nINSTALLED_APPS = [... | [
0,
1,
2,
3
] |
from . import *
from rest_framework import permissions
from core.serializers import CategorySerializer
from core.models.category_model import Category
class CategoryViewSet(viewsets.ModelViewSet):
serializer_class = CategorySerializer
queryset = Category.objects.all()
def get_permissions(self):
... | normal | {
"blob_id": "5723e7889663142832a8131bb5f4c35d29692a49",
"index": 6325,
"step-1": "<mask token>\n\n\nclass CategoryViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CategoryViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask tok... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def evaluate(model, test_features, test_labels):
predictions = model.predict(test_features)
errors = abs(predictions - test_labels)
mape = 100 * np.mean(errors / test_labels)
accuracy = 100 - mape
print('平均气温误差.', np.mean(errors))
print('Accuracy = {:0.2f}%.'.forma... | flexible | {
"blob_id": "de4e14a4fa8520c1aae60805084224337dd9620c",
"index": 9009,
"step-1": "<mask token>\n\n\ndef evaluate(model, test_features, test_labels):\n predictions = model.predict(test_features)\n errors = abs(predictions - test_labels)\n mape = 100 * np.mean(errors / test_labels)\n accuracy = 100 - m... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class FundOperationCreateView(CreateView):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def form_valid(self, form):
context = self.get_context_data()
... | flexible | {
"blob_id": "3c2fb3d09edab92da08ac8850f650a2fa22fad92",
"index": 8806,
"step-1": "<mask token>\n\n\nclass FundOperationCreateView(CreateView):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def form_valid(self, form):\n context = self.get_context_data()\n ... | [
9,
10,
11,
12,
14
] |
class MyClass:
name = "alice"
def set_name(self, name):
self.name = name
def get_name(self):
return self.name
def say_hello(self):
self.greet = "Hello"
def say_hi(self):
print("HI~~~~~")
p1 = MyClass()
p2 = MyClass()
print(p1.name)
p1.s... | normal | {
"blob_id": "babb5ac680c74e19db5c86c2c3323e8285d169ff",
"index": 9939,
"step-1": "class MyClass:\n <mask token>\n\n def set_name(self, name):\n self.name = name\n\n def get_name(self):\n return self.name\n\n def say_hello(self):\n self.greet = 'Hello'\n\n def say_hi(self):\n ... | [
5,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
LOGIN_USERNAME = 'YOUR_USERNAME'
LOGIN_PASSWORD = 'YOUR_PASSWORD'
| flexible | {
"blob_id": "5a092150896e4082431849828793f86adcd2211c",
"index": 8202,
"step-1": "<mask token>\n",
"step-2": "LOGIN_USERNAME = 'YOUR_USERNAME'\nLOGIN_PASSWORD = 'YOUR_PASSWORD'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
# -*- coding: utf-8 -*-
import datetime
from unittest.mock import patch
from odoo.tests import common
import odoo
from .common import RunbotCase
class TestSchedule(RunbotCase):
def setUp(self):
# entering test mode to avoid that the _schedule method commits records
registry = odoo.registry()
... | normal | {
"blob_id": "aa515b1b919eb557cd8c7e5f4d22773980b5af96",
"index": 8213,
"step-1": "<mask token>\n\n\nclass TestSchedule(RunbotCase):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TestSchedule(RunbotCase):\n <mask token>\n\n @patch('odoo.addons.runbot.models.build.os.path.getmt... | [
1,
2,
3,
4,
5
] |
import subprocess
import glob
import os
import time
import sys
import xml.etree.ElementTree as ET
import getpass
import psutil
if len(sys.argv)==1:
photoscanname = r"C:\Program Files\Agisoft\PhotoScan Pro\photoscan.exe"
scriptname = r"C:\Users\slocumr\github\SimUAS\batchphotoscan\agiproc.py"
#xmlnames ... | normal | {
"blob_id": "00f95733505b3e853a76bbdd65439bcb230fa262",
"index": 3345,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(sys.argv) == 1:\n photoscanname = 'C:\\\\Program Files\\\\Agisoft\\\\PhotoScan Pro\\\\photoscan.exe'\n scriptname = (\n 'C:\\\\Users\\\\slocumr\\\\github\\\\SimUAS\\\\... | [
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": "5cd767564e8a261561e141abeebb5221cb3ef2c2",
"index": 6919,
"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 = [('presentes',... | [
0,
1,
2,
3,
4
] |
import random
#quicksort a list of objects based on keys, which can be any of 3 values
# done in O(n) time in one pass, and O(1) additional space complexity
def quicksort(x, pivot_index):
key1_idx, key2_idx, key3_idx = 0, 0, len(x)
key1_val, key2_val= 'key1', 'key2'
while key2_idx < key3_idx:
if x... | normal | {
"blob_id": "f193094c551df2a32860948b1a8710b53ca0dfb6",
"index": 2413,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef quicksort(x, pivot_index):\n key1_idx, key2_idx, key3_idx = 0, 0, len(x)\n key1_val, key2_val = 'key1', 'key2'\n while key2_idx < key3_idx:\n if x[key2_idx]['key']... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python
from svg_ros.srv import *
import rospy
from std_msgs.msg import String
from geometry_msgs.msg import Twist
from math import *
import roslib
from nav_msgs.msg import Odometry
#Global variables
base_distance_x0=0
base_distance_y0=0
base_angle_0=0
base_distance_x1=0
base_distance_y1=0
base_angle_1=... | normal | {
"blob_id": "402acaa263ee620fbd9bf7d271dce2e5de4eeae0",
"index": 2005,
"step-1": "#!/usr/bin/env python\nfrom svg_ros.srv import *\nimport rospy\nfrom std_msgs.msg import String\nfrom geometry_msgs.msg import Twist\nfrom math import *\nimport roslib\nfrom nav_msgs.msg import Odometry\n\n\n#Global variables\nbase... | [
0
] |
from django.urls import path
from . import apiviews
from rest_framework.authtoken.views import obtain_auth_token
urlpatterns = [path('contacts', apiviews.ContactsView.as_view(), name=
'contacts'), path('contact/<int:pk>', apiviews.ContactView.as_view(),
name='contact'), path('signup', apiviews.create_user_with_... | normal | {
"blob_id": "5f56838ad0717c4f7a2da6b53f586a88b0166113",
"index": 8629,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('contacts', apiviews.ContactsView.as_view(), name=\n 'contacts'), path('contact/<int:pk>', apiviews.ContactView.as_view(),\n name='contact'), path('signup', apiv... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('faculty.csv') as facultycsv:
emails = list()
for line in facultycsv:
line = line.split(',')
if line[0] == 'name':
continue
try:
email = line[3].rstrip()
... | flexible | {
"blob_id": "5af5c10c149c7b0e2a969be7895780d26a4294d0",
"index": 7326,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('faculty.csv') as facultycsv:\n emails = list()\n for line in facultycsv:\n line = line.split(',')\n if line[0] == 'name':\n continue\n try... | [
0,
1,
2,
3
] |
# Copyright (c) 2011-2014 by California Institute of Technology
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice,... | normal | {
"blob_id": "707c83bc83f606b570af973094574e6675cfc83f",
"index": 8793,
"step-1": "<mask token>\n\n\nclass Ridge(object):\n \"\"\"A ridge.\n\n Attributes:\n\n - `E_r`: Equality set of a facet\n\n - `ar, br`: Affine hull of the facet\n s.t. P_{E_0} = P intersection {x | ar x = br}.\n \"\"\"\n\n... | [
7,
9,
16,
18,
20
] |
# coding: utf-8
import sys
#from operator import itemgetter
sysread = sys.stdin.readline
read = sys.stdin.read
from heapq import heappop, heappush
from collections import defaultdict
sys.setrecursionlimit(10**7)
import math
#from itertools import product#accumulate, combinations, product
#import bisect# lower_bound etc... | normal | {
"blob_id": "f73a3bd7665ac9cc90085fcac2530c93bef69d3d",
"index": 6705,
"step-1": "<mask token>\n\n\ndef run():\n mod = 1000000007\n N, *AB = map(int, read().split())\n A_B = []\n INF = float('inf')\n zerozero = 0\n for i in range(N):\n a = AB[2 * i]\n b = AB[2 * i + 1]\n if... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Conexion:
def __init__(self, direccion, destino):
self.set_direccion(direccion)
self.set_destino(destino)
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def set_direccion(self, direccion):
self._direccion = direccion
<|reserve... | flexible | {
"blob_id": "f59e61977f7c72ab191aadccbd72d23f831b3a1c",
"index": 7050,
"step-1": "<mask token>\n\n\nclass Conexion:\n\n def __init__(self, direccion, destino):\n self.set_direccion(direccion)\n self.set_destino(destino)\n <mask token>\n <mask token>\n\n def set_direccion(self, direccion... | [
20,
22,
25,
26,
27
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = patterns('', url('^$', 'analyze.views.analyze', name='analyze'))
<|reserved_special_token_1|>
from django.conf.urls import patterns, include, url
from django.contrib.auth.decorators import login_required
from djan... | flexible | {
"blob_id": "035de226c2d2ee85cb7e319de35fb09b21bc523d",
"index": 9061,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = patterns('', url('^$', 'analyze.views.analyze', name='analyze'))\n",
"step-3": "from django.conf.urls import patterns, include, url\nfrom django.contrib.auth.decorators im... | [
0,
1,
2,
3
] |
import logging, os, zc.buildout, sys, shutil
class ZipEggs:
def __init__(self, buildout, name, options):
self.name, self.options = name, options
if options['target'] is None:
raise zc.buildout.UserError('Invalid Target')
if options['source'] is None:
raise zc.buildou... | normal | {
"blob_id": "e7bec9018f25ba9e3c3ae8a5bbe11f8bc4b54a04",
"index": 5714,
"step-1": "import logging, os, zc.buildout, sys, shutil\n\nclass ZipEggs:\n def __init__(self, buildout, name, options):\n self.name, self.options = name, options\n if options['target'] is None:\n raise zc.buildout... | [
0
] |
# Example solution for HW 5
# %%
# Import the modules we will use
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# %%
# ** MODIFY **
# Set the file name and path to where you have stored the data
filename = 'streamflow_week5.txt' #modified filename
filepath = os.path.join('../data', ... | normal | {
"blob_id": "5024db0538f0022b84c203882df9c35979ba978a",
"index": 4571,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(os.getcwd())\nprint(filepath)\n<mask token>\nprint(data.tail(14))\nprint(data.tail(14).describe())\nprint(data.tail(7).describe())\n<mask token>\nprint(data_2019['flow'].describe())... | [
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": "1aaace83af0235341d10b8ac3b47d00a944dac37",
"index": 1422,
"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 = [('story1', '0... | [
0,
1,
2,
3,
4
] |
from nltk.tokenize import RegexpTokenizer
from stop_words import get_stop_words
from nltk.stem.porter import PorterStemmer
from gensim import corpora, models
import gensim
tokenizer = RegexpTokenizer(r'\w+')
# create English stop words list
en_stop = get_stop_words('en')
# Create p_stemmer of class PorterStemmer
p_s... | normal | {
"blob_id": "3035ac8044b5629d0b5de7934e46890ad36ed551",
"index": 7798,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in doc_set:\n raw = i.lower()\n tokens = tokenizer.tokenize(raw)\n stopped_tokens = [i for i in tokens if not i in en_stop]\n stemmed_tokens = [p_stemmer.stem(i) for i i... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def readadc(adcnum, clockpin, mosipin, misopin, cspin):
if adcnum > 7 or adcnum < 0:
return -1
GPIO.output(cspin, True)
GPIO.output(clockpin, False)
GPIO.output(cspin, False)
commandout = adcnum
commandout |= 24
commandout <<= 3
for i in range(5):
... | flexible | {
"blob_id": "fcdb43e36a4610ca0201a27d82b1a583f1482878",
"index": 8924,
"step-1": "<mask token>\n\n\ndef readadc(adcnum, clockpin, mosipin, misopin, cspin):\n if adcnum > 7 or adcnum < 0:\n return -1\n GPIO.output(cspin, True)\n GPIO.output(clockpin, False)\n GPIO.output(cspin, False)\n comm... | [
4,
5,
6,
7,
10
] |
<|reserved_special_token_0|>
def rotate(files, dst, value=90):
for file_ in files:
img = Image.open(file_)
img = img.rotate(value)
name = '{}{}{}'.format(dst, os.sep, os.path.basename(file_))
img.save(name)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_s... | flexible | {
"blob_id": "cd104eec21be8a59e8fb3bd8ab061dd357fc126a",
"index": 667,
"step-1": "<mask token>\n\n\ndef rotate(files, dst, value=90):\n for file_ in files:\n img = Image.open(file_)\n img = img.rotate(value)\n name = '{}{}{}'.format(dst, os.sep, os.path.basename(file_))\n img.save(n... | [
1,
2,
3,
4,
5
] |
import os, argparse,collections
defaults ={'color':'red','user':'guest'}
parser=argparse.ArgumentParser()
parser.add_argument('-u','--user')
parser.add_argument('-c','--color')
#a simple Namespace object will be built up from attributes parsed out of the command lin
namespace= parser.parse_args()
command_line_args= ... | normal | {
"blob_id": "3c31e3f2a6f320bc5ae33f0ba1d234a089371899",
"index": 9199,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nparser.add_argument('-u', '--user')\nparser.add_argument('-c', '--color')\n<mask token>\nprint(combined['color'])\nprint(combined['user'])\n",
"step-3": "<mask token>\ndefaults = {'colo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def hash_string(input_string: str) ->str:
return hashlib.sha256(input_string.encode('utf-8')).hexdigest()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def hash_string(input_st... | flexible | {
"blob_id": "670a23aa910a6709735281b7e64e5254a19277c6",
"index": 7924,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef hash_string(input_string: str) ->str:\n return hashlib.sha256(input_string.encode('utf-8')).hexdigest()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef hash_string(inp... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def func(i):
if i % 2 != 0:
return False
visited = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
temp = i
while i:
x = i % 10
if visited[x] == 1 or x == 0:
break
visited[x] = 1
i = int(i / 10)
if i == 0... | flexible | {
"blob_id": "1a8c9be389aad37a36630a962c20a0a36c449bdd",
"index": 3809,
"step-1": "<mask token>\n",
"step-2": "def func(i):\n if i % 2 != 0:\n return False\n visited = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n temp = i\n while i:\n x = i % 10\n if visited[x] == 1 or x == 0:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def isPentagon(item):
num = math.floor(math.sqrt(item * 2 // 3)) + 1
if num * (3 * num - 1) // 2 == item:
return True
return False
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def isPentagon(item):
num = math.floor(m... | flexible | {
"blob_id": "0aec3fbc9f4b9f33aee021fa417c43f0feb0e3d1",
"index": 3296,
"step-1": "<mask token>\n\n\ndef isPentagon(item):\n num = math.floor(math.sqrt(item * 2 // 3)) + 1\n if num * (3 * num - 1) // 2 == item:\n return True\n return False\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef i... | [
1,
3,
4,
5,
6
] |
""""Module for miscellaneous behavior stuff
For example, stuff like extracting lick times or choice times.
TrialSpeak shouldn't depend on stuff like that.
# Also get the pldf and use that to get lick times
ldf = ArduFSM.TrialSpeak.read_logfile_into_df(bdf.loc[idx, 'filename'])
# Get the lick times
... | normal | {
"blob_id": "78761eda403ad8f54187e5858a23c23d3dd79b09",
"index": 8821,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_choice_times(behavior_filename, verbose=False):\n \"\"\"Calculates the choice time for each trial in the logfile\"\"\"\n state_num2names = MCwatch.behavior.db.get_state_... | [
0,
1,
2,
3,
4
] |
import re
import ngram
import smoothedNgram
def split_into_sentences(text):
text = text.lower()
sentences = re.split(r'(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', text)
getSentences(sentences,text)
return sentences
def getTextWithoutSpaces(text):
withoutLineBreaks = text.replace("\n", "")
withoutS... | normal | {
"blob_id": "6d7db5b9a64ec25763f5af6ceec1a46d629d549c",
"index": 472,
"step-1": "<mask token>\n\n\ndef getTextWithoutSpaces(text):\n withoutLineBreaks = text.replace('\\n', '')\n withoutSpaces = re.sub(' +', ' ', withoutLineBreaks)\n return withoutSpaces\n\n\ndef getSentences(sentences, text):\n data... | [
3,
5,
6,
7,
8
] |
# Copyright 2021-2022 Huawei Technologies Co., Ltd
#
# 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 agre... | normal | {
"blob_id": "8ae10aada79b0a687732e341d275eb3823ec0e4a",
"index": 9475,
"step-1": "<mask token>\n\n\nclass BucketDatasetGenerator:\n \"\"\"\n Provide data distribution of different gears for the bert network.\n\n Args:\n data_set (Dataset): The training dataset.\n batch_size (Int): The trai... | [
8,
11,
12,
13,
14
] |
import random
def multi():
scc = [6, 5, 4]
sc = [6, 5]
cc = [5, 4]
crew = [4]
captain = [5]
ship = [6]
n = 0
while n <= 2:
inp = input("Hit enter to roll")
if inp == "":
roll5 = random.choices(range(1, 7), k=5)
print(roll5)
if set(scc)... | normal | {
"blob_id": "bb540ba4cd96e2485e77ba099f0a1a9ea03e1120",
"index": 8144,
"step-1": "<mask token>\n\n\ndef multi():\n scc = [6, 5, 4]\n sc = [6, 5]\n cc = [5, 4]\n crew = [4]\n captain = [5]\n ship = [6]\n n = 0\n while n <= 2:\n inp = input('Hit enter to roll')\n if inp == '':... | [
1,
2,
3,
4,
5
] |
#----------------------------
# |
# Instagram Bot- Devesh Kr. Verma
# instagram- @felon_tpf
# |
#----------------------------
from selenium import webdriver
from time import sleep
from selenium.webdriver.common.keys import Keys
import random
import string
from time import sleep
from selenium import we... | normal | {
"blob_id": "6d18aa585c656b244d1e4272caa8419c04b20b6c",
"index": 2363,
"step-1": "<mask token>\n\n\ndef start():\n username = browser.find_element_by_name('username')\n username.send_keys('Username')\n password = browser.find_element_by_name('password')\n password.send_keys('Password')\n nextButto... | [
1,
3,
4,
5,
6
] |
from dataclasses import dataclass
from datetime import date
@dataclass
class Book:
id: int
title: str
author: str
genre: str
published: date
status: str = 'Available'
def __str__(self):
return f'{self.id}: {self.title} by {self.author}'
def get_more_information(self):
... | normal | {
"blob_id": "dc13ca17bff8e2a5254c7758bd7274926bafd454",
"index": 5312,
"step-1": "<mask token>\n\n\n@dataclass\nclass Book:\n id: int\n title: str\n author: str\n genre: str\n published: date\n status: str = 'Available'\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\n@dat... | [
1,
2,
3,
4,
5
] |
import torch
from training import PointNetTrain, PointAugmentTrain, Model
#from PointAugment.Augment.config import opts
from data_utils.dataloader import DataLoaderClass
from mpl_toolkits import mplot3d
import matplotlib.pyplot as plt
import numpy as np
import yaml
def visualize_batch(pointclouds, pred_labels, labels,... | normal | {
"blob_id": "0ced42c8bfaad32fc2b397326150e6c7bc5cedab",
"index": 4991,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef visualize_batch(pointclouds, pred_labels, labels, categories):\n batch_size = len(pointclouds)\n fig = plt.figure(figsize=(8, batch_size / 2))\n ncols = 5\n nrows = ma... | [
0,
1,
2,
3,
4
] |
import RPi.GPIO as GPIO
import numpy as np
import array
import time
import json
import LED_GPIO as led
import BUTTON_GPIO as btn
import parseJson as gjs
rndBtnState = False
interval = .1
rndbtn = gjs.getJsonRnd()
gpioValues = gjs.getJsonData()
strArray = gpioValues[0]
btnArray = gpioValues[1]
ledArray = gpioValue... | normal | {
"blob_id": "1b741b34649193b64479724670244d258cfbbdfc",
"index": 5055,
"step-1": "import RPi.GPIO as GPIO\nimport numpy as np\nimport array\nimport time\nimport json\n\nimport LED_GPIO as led \nimport BUTTON_GPIO as btn\nimport parseJson as gjs\n\nrndBtnState = False\ninterval = .1\n\nrndbtn = gjs.getJsonRnd()\n... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setuptools.setup(name='cppersist', install_requires=['Eve'])
<|reserved_special_token_1|>
import setuptools
setuptools.setup(name='cppersist', install_requires=['Eve'])
| flexible | {
"blob_id": "4f1956b34ac3b55b2d40220b79816c139b4a2f5c",
"index": 9574,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetuptools.setup(name='cppersist', install_requires=['Eve'])\n",
"step-3": "import setuptools\nsetuptools.setup(name='cppersist', install_requires=['Eve'])\n",
"step-4": null,
"step... | [
0,
1,
2
] |
import socket
END = bytearray()
END.append(255)
print(END[0])
def recvall(sock): # Odbiór danych
BUFF_SIZE = 4096 # 4 KiB
data = b''
while True: # odbieramy dane, pakiety 4KiB
part = sock.recv(BUFF_SIZE)
data += part
if len(part) < BUFF_SIZE:
# 0 lub koniec danych
... | normal | {
"blob_id": "aa13278a4686e9bab7948c2f212f87f9bd6eee00",
"index": 969,
"step-1": "<mask token>\n\n\ndef recvall(sock):\n BUFF_SIZE = 4096\n data = b''\n while True:\n part = sock.recv(BUFF_SIZE)\n data += part\n if len(part) < BUFF_SIZE:\n break\n return data\n\n\n<mask... | [
5,
6,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
import FWCore.ParameterSet.Config as cms
from RecoTracker.MeasurementDet.UpdaterService_cfi import *
from RecoTracker.MeasurementDet.MeasurementTrackerESProducer_cfi import *
| flexible | {
"blob_id": "e79505e802a06f091bbb12708c45e04c4e80da60",
"index": 7618,
"step-1": "<mask token>\n",
"step-2": "import FWCore.ParameterSet.Config as cms\nfrom RecoTracker.MeasurementDet.UpdaterService_cfi import *\nfrom RecoTracker.MeasurementDet.MeasurementTrackerESProducer_cfi import *\n",
"step-3": null,
... | [
0,
1
] |
<|reserved_special_token_0|>
class Autoencoder(function.Function):
<|reserved_special_token_0|>
def hidden(self, x):
h = _Encoder(self.W, self.b1)(x)
if self.activation is not None:
h = self.activation(h)
h.unchain_backward()
return h
@property
def paramet... | flexible | {
"blob_id": "97eb599ae8bf726d827d6f8313b7cf2838f9c125",
"index": 4098,
"step-1": "<mask token>\n\n\nclass Autoencoder(function.Function):\n <mask token>\n\n def hidden(self, x):\n h = _Encoder(self.W, self.b1)(x)\n if self.activation is not None:\n h = self.activation(h)\n h... | [
11,
13,
14,
15,
17
] |
# Copyright (c) 2022, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | normal | {
"blob_id": "dccdca65cce2959b07657636e23e7c9ab8a4f96c",
"index": 1382,
"step-1": "<mask token>\n\n\nclass MoneyFst(GraphFst):\n <mask token>\n\n def __init__(self, decimal: GraphFst, deterministic: bool=True):\n super().__init__(name='money', kind='verbalize', deterministic=\n determinist... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def n_gram_hash(hash_bits=16, ngram_length=1, skip_length=0, all_lengths=
True, seed=314489979, ordered=True, invert_hash=0, **params):
"""
**Description**
Extracts NGrams from text and convert them to vector... | flexible | {
"blob_id": "fb1974ad7ac9ae54344812814cb95a7fccfefc66",
"index": 5880,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef n_gram_hash(hash_bits=16, ngram_length=1, skip_length=0, all_lengths=\n True, seed=314489979, ordered=True, invert_hash=0, **params):\n \"\"\"\n **Description**\n ... | [
0,
1,
2,
3
] |
'''
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.
Note: A leaf is a node with no children.
'''
# Definition for a binary tree node.
class TreeNode(object):
def __init__(self, x):
self.val... | normal | {
"blob_id": "fa081ccd8081f5c3319f482b7d8abd7415d8e757",
"index": 1273,
"step-1": "'''\nGiven a binary tree, find its maximum depth.\n\nThe maximum depth is the number of nodes along the longest path from the root node down to the farthest leaf node.\n\nNote: A leaf is a node with no children.\n\n'''\n\n\n\n# Def... | [
0
] |
# Generated by Django 3.0.4 on 2020-03-29 19:51
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('index', '0003_auto_20200330_0444'),
]
operations = [
migrations.AlterField(
model_name='information',
name='comment'... | normal | {
"blob_id": "72c1226d40b3cdce29ef28493344c3cf68892149",
"index": 6001,
"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 = [('index', '00... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class tgApp(object):
def __init__(self):
builder = gtk.Builder()
builder.add_from_file('../tg.glade')
self.window = builder.get_object('window1')
self.text_area = builder.get_object('text_entry')
self.window.show()
self.opcao = ''
... | flexible | {
"blob_id": "6b6fac3bfb1b1478dd491fc4dd9c45a19aeb7bd8",
"index": 6102,
"step-1": "<mask token>\n\n\nclass tgApp(object):\n\n def __init__(self):\n builder = gtk.Builder()\n builder.add_from_file('../tg.glade')\n self.window = builder.get_object('window1')\n self.text_area = builder... | [
6,
8,
9,
10,
12
] |
from selenium import webdriver;
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.support.select import Select
from webdriver_manager.chrome import ChromeDriverManager
from selenium.webdriver.common.keys import Keys
import time
driver = webdriver.Chrome(Chr... | normal | {
"blob_id": "1a1a217b382f3c58c6c4cd3c1c3f556ae945f5a7",
"index": 7850,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndriver.implicitly_wait(10)\ndriver.maximize_window()\ndriver.get('http://demo.automationtesting.in/Register.html')\n<mask token>\nactions.move_to_element(interactions).move_to_element(dra... | [
0,
1,
2,
3,
4
] |
import sys, string, math
s = input()
print(ord(s))
| normal | {
"blob_id": "ade300f2921ca860bbe92aa351df2c88238b7996",
"index": 6039,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(ord(s))\n",
"step-3": "<mask token>\ns = input()\nprint(ord(s))\n",
"step-4": "import sys, string, math\ns = input()\nprint(ord(s))\n",
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2,
3
] |
from setuptools import setup, find_packages
def find_version():
with open('pytest_defer.py') as fp:
for line in fp:
if '__version__' in line:
version = line.split('=')[-1].strip()
return version[1:-1] # trim ''
with open('README.md') as fp:
long_desc = fp... | normal | {
"blob_id": "7903484b4a36d4b6ea03b9eaf3bf2b2e056baad8",
"index": 8148,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef find_version():\n with open('pytest_defer.py') as fp:\n for line in fp:\n if '__version__' in line:\n version = line.split('=')[-1].strip()\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class NeuralNetworkClassifier:
<|reserved_special_token_0|>
def fit(self, X_train, Y_train):
num_input_dimensions = X_train.shape[1]
self._num_classes = Y_train.shape[1]
training_set_size = X_train.shape[0]
self._W_1 = 1 / np.sqrt(self._hidden_unit... | flexible | {
"blob_id": "6199a2ac12e80395f4a7a54877c5b639315e64aa",
"index": 7702,
"step-1": "<mask token>\n\n\nclass NeuralNetworkClassifier:\n <mask token>\n\n def fit(self, X_train, Y_train):\n num_input_dimensions = X_train.shape[1]\n self._num_classes = Y_train.shape[1]\n training_set_size = ... | [
9,
15,
19,
21,
26
] |
import logging
from django.contrib.auth.models import User
import json
from django.http import HttpResponse
from enumfields.fields import EnumFieldMixin
from Api.models import Status
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def check_cookie(request):
# Post.objects.all().delete()
result = ... | normal | {
"blob_id": "2bc3b0df720788e43da3d9c28adb22b3b1be8c58",
"index": 5002,
"step-1": "<mask token>\n\n\ndef check_cookie(request):\n result = {'status': True}\n try:\n user_id = request.GET.get('user_id')\n user = User.objects.get(pk=user_id)\n cookie_status = user.profile.cookie_status\n ... | [
1,
2,
3,
4,
5
] |
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