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|>
if number <= 100:
print('Your number is smaller than equal to 100')
else:
print('Your number is greater than 100')
<|reserved_special_token_1|>
number = int(input('Enter an integer'))
if number <= 100:
print('Your n... | flexible | {
"blob_id": "9666c87b4d4dc721683ea33fdbbeadefc65a0cd1",
"index": 1860,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif number <= 100:\n print('Your number is smaller than equal to 100')\nelse:\n print('Your number is greater than 100')\n",
"step-3": "number = int(input('Enter an integer'))\nif ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def is_element(el, tag):
return isinstance(el, Tag) and el.name == tag
class ElemIterator:
def __init__(self, els):
self.els = els
self.i = 0
def peek(self):
try:
return self.els[self.i]
except IndexError:
return None... | flexible | {
"blob_id": "cb08f64d1ad7e53f1041684d4ca4ef65036c138d",
"index": 44,
"step-1": "<mask token>\n\n\ndef is_element(el, tag):\n return isinstance(el, Tag) and el.name == tag\n\n\nclass ElemIterator:\n\n def __init__(self, els):\n self.els = els\n self.i = 0\n\n def peek(self):\n try:\n... | [
10,
12,
14,
15,
16
] |
import pytest
def test_template():
assert True
| normal | {
"blob_id": "e7fa84dbc037253c7f852aa618e6ea88d1fda909",
"index": 1939,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_template():\n assert True\n",
"step-3": "import pytest\n\n\ndef test_template():\n assert True\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
... | [
0,
1,
2
] |
import numpy as np
import cv2
import os
from moviepy.editor import *
N = 1
# Initiate SIFT detector
sift = cv2.xfeatures2d.SIFT_create()
# count file number in folder frames
list = os.listdir('./frames')
number_files = len(list)
# array to store similarity of 2 consecutive frames
similarity = []
boundaries = []
ke... | normal | {
"blob_id": "397d9b1030a1ec08d04d2101f65a83547495b861",
"index": 7165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, number_files - N - 1, N):\n img1 = cv2.imread('./frames/frame%d.jpg' % i, 0)\n img2 = cv2.imread('./frames/frame%d.jpg' % (i + N), 0)\n kp1, des1 = sift.detectA... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SolverError(Exception):
pass
<|reserved_special_token_0|>
def ecos_solve(A, b, c, dim_dict, **kwargs):
"""Wraps ecos.solve for convenience."""
ecos_cones = {'l': dim_dict['l'] if 'l' in dim_dict else 0, 'q':
dim_dict['q'] if 'q' in dim_dict else []}
if '... | flexible | {
"blob_id": "00a0668d5fcb8358b4bd7736c48e4867afc0f5b6",
"index": 780,
"step-1": "<mask token>\n\n\nclass SolverError(Exception):\n pass\n\n\n<mask token>\n\n\ndef ecos_solve(A, b, c, dim_dict, **kwargs):\n \"\"\"Wraps ecos.solve for convenience.\"\"\"\n ecos_cones = {'l': dim_dict['l'] if 'l' in dim_dic... | [
2,
3,
4,
5,
6
] |
from states.state import State
class MoveDigState(State):
#init attributes of state
def __init__(self):
super().__init__("MoveDig", "ScanDig")
self.transitionReady = False
self.digSiteDistance = 0
#implementation for each state: overridden
def run(self, moveInstructions):
... | normal | {
"blob_id": "ce4ecff2012cfda4a458912713b0330a218fa186",
"index": 873,
"step-1": "<mask token>\n\n\nclass MoveDigState(State):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass MoveDigState(State):\n\n def __init__(self):\n super().__init__('MoveDig', 'ScanDi... | [
1,
2,
4,
5,
6
] |
import bz2
import json
import os
from pyspark.context import SparkContext
from pyspark.accumulators import AccumulatorParam
import numpy as np
from scipy import spatial
import pandas as pd
import re
import operator
import csv
CACHE_DIR = "D:\TwitterDatastream\PYTHONCACHE_SMALL"
EDU_DATA = 'merged.csv'
TRAIN_FEAT_CSV =... | normal | {
"blob_id": "ee58ed68d2f3c43f9611f6c6e4cd2b99adcb43d2",
"index": 2616,
"step-1": "<mask token>\n\n\nclass WordsSetAccumulatorParam(AccumulatorParam):\n\n def zero(self, v):\n return set()\n\n def addInPlace(self, acc1, acc2):\n return acc1.union(acc2)\n\n\nclass WordsDictAccumulatorParam(Accu... | [
10,
14,
15,
18,
20
] |
from battleship.board import Board
from battleship.game import Game
import string
# Board
row_num = list(string.ascii_lowercase[:10]) # A-J
col_num = 10
board = Board(row_num, col_num)
board.display_board()
# Game
guesses = 25
quit = 'q'
game = Game(guesses, quit)
game.take_shot("\nChoose a spot to fire at in enemy... | normal | {
"blob_id": "dd06847c3eb9af6e84f247f8f0dd03961d83688e",
"index": 9453,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nboard.display_board()\n<mask token>\ngame.take_shot(\"\"\"\nChoose a spot to fire at in enemy seas: \"\"\", board)\n",
"step-3": "<mask token>\nrow_num = list(string.ascii_lowercase[:10... | [
0,
1,
2,
3,
4
] |
class Solution:
<|reserved_special_token_0|>
def gameOfLife(self, board):
"""
Do not return anything, modify board in-place instead.
"""
self.gameOfLife_2(board)
def gameOfLife_1(self, board):
"""
Space complexity is O(M*N).Time complexity is O(M*N)
... | flexible | {
"blob_id": "5b6ed75279b39a1dad1bf92535c4b129bb599350",
"index": 3612,
"step-1": "class Solution:\n <mask token>\n\n def gameOfLife(self, board):\n \"\"\"\n Do not return anything, modify board in-place instead.\n \"\"\"\n self.gameOfLife_2(board)\n\n def gameOfLife_1(self, b... | [
4,
6,
7,
8,
9
] |
"""Test functions for util.mrbump_util"""
import pickle
import os
import sys
import unittest
from ample.constants import AMPLE_PKL, SHARE_DIR
from ample.util import mrbump_util
class Test(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.thisd = os.path.abspath(os.path.dirname(__file__))
... | normal | {
"blob_id": "f6dd5acc75d1a85a996629e22e81cdef316c1dcd",
"index": 8939,
"step-1": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n\n def test_final_summary(self):\n pkl = os.path.join(self.testfiles_dir, AMPLE_PKL)\n if not os.path.isfile(pkl):\n return\n wi... | [
3,
4,
5,
6,
7
] |
import csv
import os
events = {}
eventTypes = set()
eventIndices = {}
i = 0
with open('Civ VI Modding Companion - Events.csv', newline='') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='|')
for row in reader:
if i < 4:
i += 1
continue
eventName = row[3]
eventType = "GameEvents" if... | normal | {
"blob_id": "5ce98ae241c0982eeb1027ffcff5b770f94ff1a3",
"index": 77,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Civ VI Modding Companion - Events.csv', newline='') as csvfile:\n reader = csv.reader(csvfile, delimiter=',', quotechar='|')\n for row in reader:\n if i < 4:\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "1f63ce2c791f0b8763aeae15df4875769f6de848",
"index": 4942,
"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 = [('currency_ex... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Food(models.Model):
Food_ID = models.AutoField(primary_key=True)
Food_Name = models.CharField(max_length=250)
Food_Pic = models.ImageField(upload_to='Restaurants/Pictures/Food')
Food_Category_ID = models.ForeignKey(FoodCategory, on_delete=models.CASCADE
)
... | flexible | {
"blob_id": "7ea1ee7c55cd53f7137c933790c3a22957f0ffea",
"index": 4987,
"step-1": "<mask token>\n\n\nclass Food(models.Model):\n Food_ID = models.AutoField(primary_key=True)\n Food_Name = models.CharField(max_length=250)\n Food_Pic = models.ImageField(upload_to='Restaurants/Pictures/Food')\n Food_Cate... | [
2,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('o dobro deste numero é', t3 * 2)
print('O triplo deste numero é', t3 * 3)
print('E a raiz quadrada deste numero é', t3 ** (1 / 2))
<|reserved_special_token_1|>
t3 = float(input('Digite um numero: '))
print('o dobro deste... | flexible | {
"blob_id": "005ea8a1e75447b2b1c030a645bde5d0cdc8fb53",
"index": 3532,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('o dobro deste numero é', t3 * 2)\nprint('O triplo deste numero é', t3 * 3)\nprint('E a raiz quadrada deste numero é', t3 ** (1 / 2))\n",
"step-3": "t3 = float(input('Digite um nu... | [
0,
1,
2
] |
#-*- coding: utf-8 -*-
espacos = ["__1__", "__2__", "__3__", "__4__"]
facil_respostas=["ouro","leao","capsula do poder","relampago de plasma"]
media_respostas=["Ares","Saga","Gemeos","Athena"]
dificil_respostas=["Shion","Aries","Saga","Gemeos"]
def inicio_game():
apresentacao=raw_input("Bem vindo ao qui... | normal | {
"blob_id": "d205c38e18b1acf8043a5976a90939b14358dc40",
"index": 7855,
"step-1": "#-*- coding: utf-8 -*-\r\nespacos = [\"__1__\", \"__2__\", \"__3__\", \"__4__\"]\r\nfacil_respostas=[\"ouro\",\"leao\",\"capsula do poder\",\"relampago de plasma\"]\r\nmedia_respostas=[\"Ares\",\"Saga\",\"Gemeos\",\"Athena\"]\r\ndi... | [
0
] |
<|reserved_special_token_0|>
def start_button_callback(obj, w, h, amount):
_max = int(w.get()) * int(h.get())
if not (obj.validation_check(w) and obj.validation_check(h) and obj.
validation_check(amount, _max)):
ctypes.windll.user32.MessageBoxW(0, 'Wprowadź poprawne dane', 'Błąd', 1
... | flexible | {
"blob_id": "65eb7d01ccea137605d54d816b707c2cd3709931",
"index": 2067,
"step-1": "<mask token>\n\n\ndef start_button_callback(obj, w, h, amount):\n _max = int(w.get()) * int(h.get())\n if not (obj.validation_check(w) and obj.validation_check(h) and obj.\n validation_check(amount, _max)):\n ct... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def player(x, y):
screen.blit(player_image, (x, y))
def fire_bullet(x, y, n):
global bullet_fired
bullet_fired[n] = True
screen.blit(bullet_image, (x + 16, y + 10))
def add_bullet():
global num_bullet
num_bullet += 1
bullet_X.append(0)
bullet_Y.append(p... | flexible | {
"blob_id": "f5dffa3c22bb35ed07cb5ca28f2ba02ea3c07dda",
"index": 1083,
"step-1": "<mask token>\n\n\ndef player(x, y):\n screen.blit(player_image, (x, y))\n\n\ndef fire_bullet(x, y, n):\n global bullet_fired\n bullet_fired[n] = True\n screen.blit(bullet_image, (x + 16, y + 10))\n\n\ndef add_bullet():\... | [
15,
16,
18,
19,
20
] |
from django.conf.urls import url
from django.urls import path
from .views import *
from flujo.views import *
"""
URL para el Sprint crear, listar y modificar
"""
urlpatterns = [
url(r'^$', SprintListView.as_view(), name='sprint_list'),
path('create/', view=CreateSprintView.as_view(), name='create_sprint'),
... | normal | {
"blob_id": "2b1ec422a42af59a048c708f86b686eb0564b51f",
"index": 2456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', SprintListView.as_view(), name='sprint_list'),\n path('create/', view=CreateSprintView.as_view(), name='create_sprint'),\n path('modificar/<int:sprint_pk>/'... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class LibpopplerConan(ConanFile):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_t... | flexible | {
"blob_id": "848394e1e23d568f64df8a98527a8e177b937767",
"index": 3380,
"step-1": "<mask token>\n\n\nclass LibpopplerConan(ConanFile):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>... | [
6,
7,
8,
9,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(x)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
client = pymongo.MongoClient('mongodb://localhost:27017/')
db = client['Test']
col = db['C100']
x = col.find_one()
print(x)
<|reserved_special_token_1|>
impo... | flexible | {
"blob_id": "7d10fb58aa5213516c656c05966fcaad6868ae81",
"index": 1548,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(x)\n",
"step-3": "<mask token>\nclient = pymongo.MongoClient('mongodb://localhost:27017/')\ndb = client['Test']\ncol = db['C100']\nx = col.find_one()\nprint(x)\n",
"step-4": "im... | [
0,
1,
2,
3,
4
] |
import sys,argparse
import os,glob
import numpy as np
import pandas as pd
import re,bisect
from scipy import stats
import matplotlib
# matplotlib.use('Agg')
import matplotlib.pyplot as plt
matplotlib.rcParams['font.size']=11
import seaborn as sns
sns.set(font_scale=1.1)
sns.set_style("whitegrid", {'axes.grid' : False})... | normal | {
"blob_id": "4ee47435bff1b0b4a7877c06fb13d13cf53b7fce",
"index": 3910,
"step-1": "<mask token>\n\n\ndef return_dci_df(DCI_dir, subdir, hm_mark, compr_type, suffix):\n dci_file = '{}/{}/{}_{}{}.csv'.format(DCI_dir, subdir, hm_mark,\n compr_type, suffix)\n if os.path.isfile(dci_file):\n dci_df ... | [
3,
4,
5,
6,
7
] |
from textmagic.rest import TextmagicRestClient
username = 'lucychibukhchyan'
api_key = 'sjbEMjfNrrglXY4zCFufIw9IPlZ3SA'
client = TextmagicRestClient(username, api_key)
message = client.message.create(phones="7206337812", text="wow i sent a text from python!!!!")
| normal | {
"blob_id": "1ba39cfc1187b0efc7fc7e905a15de8dc7f80e0d",
"index": 8888,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nusername = 'lucychibukhchyan'\napi_key = 'sjbEMjfNrrglXY4zCFufIw9IPlZ3SA'\nclient = TextmagicRestClient(username, api_key)\nmessage = client.message.create(phones='7206337812', text=\n ... | [
0,
1,
2,
3
] |
ii = [('CookGHP3.py', 2), ('MarrFDI.py', 1), ('GodwWSL2.py', 2), (
'ChanWS.py', 6), ('SadlMLP.py', 1), ('WilbRLW.py', 1), ('AubePRP2.py',
1), ('MartHSI2.py', 1), ('WilbRLW5.py', 1), ('KnowJMM.py', 1), (
'AubePRP.py', 2), ('ChalTPW2.py', 1), ('ClarGE2.py', 2), ('CarlTFR.py',
3), ('SeniNSP.py', 4), ('Gri... | normal | {
"blob_id": "b80ccee42489aefb2858b8491008b252f6a2b9b7",
"index": 4864,
"step-1": "<mask token>\n",
"step-2": "ii = [('CookGHP3.py', 2), ('MarrFDI.py', 1), ('GodwWSL2.py', 2), (\n 'ChanWS.py', 6), ('SadlMLP.py', 1), ('WilbRLW.py', 1), ('AubePRP2.py', \n 1), ('MartHSI2.py', 1), ('WilbRLW5.py', 1), ('KnowJM... | [
0,
1
] |
<|reserved_special_token_0|>
class GroupVariable(GroupElement, Variable):
def __init__(self, g: Group, symbol: str):
GroupElement.__init__(self, g)
Variable.__init__(self, symbol)
def __hash__(self):
return hash((self.group, self.symbol))
def __eq__(self, x):
return type... | flexible | {
"blob_id": "93133b9a62d50e4e48e37721585116c1c7d70761",
"index": 2490,
"step-1": "<mask token>\n\n\nclass GroupVariable(GroupElement, Variable):\n\n def __init__(self, g: Group, symbol: str):\n GroupElement.__init__(self, g)\n Variable.__init__(self, symbol)\n\n def __hash__(self):\n r... | [
18,
31,
34,
35,
37
] |
from enum import Enum
EXIT_CODES = [
"SUCCESS",
"BUILD_FAILURE",
"PARSING_FAILURE",
"COMMAND_LINE_ERROR",
"TESTS_FAILED",
"PARTIAL_ANALYSIS_FAILURE",
"NO_TESTS_FOUND",
"RUN_FAILURE",
"ANALYSIS_FAILURE",
"INTERRUPTED",
"LOCK_HEL... | normal | {
"blob_id": "5e86e97281b9d18a06efc62b20f5399611e3510d",
"index": 8000,
"step-1": "<mask token>\n\n\nclass CPU(DistantEnum):\n k8 = 'k8'\n piii = 'piii'\n darwin = 'darwin'\n freebsd = 'freebsd'\n armeabi = 'armeabi-v7a'\n arm = 'arm'\n aarch64 = 'aarch64'\n x64_windows = 'x64_windows'\n ... | [
4,
5,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def sort_descending(numbers):
numbers.sort(reverse=True)
| flexible | {
"blob_id": "46dc9917d9b3a7caf8d7ba5024b17d3b755fc5db",
"index": 7278,
"step-1": "<mask token>\n",
"step-2": "def sort_descending(numbers):\n numbers.sort(reverse=True)\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
Generation().addTool(SignalRepeatedHadronization)
<|reserved_special_token_0|>
ToolSvc().addTool(EvtGenDecay)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
Generation().EventType = 16303... | flexible | {
"blob_id": "7cc9d445d712d485eaebd090d2485dac0c38b3fb",
"index": 5918,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nGeneration().addTool(SignalRepeatedHadronization)\n<mask token>\nToolSvc().addTool(EvtGenDecay)\n<mask token>\n",
"step-3": "<mask token>\nGeneration().EventType = 16303437\nGeneration(... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Item(object):
<|reserved_special_token_0|>
def convert_string_to_item(self, string):
tokens = str(string).split(',')
self._platform_type = tokens[0]
self._sensor_name = tokens[1]
self._topic = tokens[2]
self._frequent = int(tokens[3])... | flexible | {
"blob_id": "3375bc94d214b0b1c67986d35b0587714dd63bcd",
"index": 7723,
"step-1": "<mask token>\n\n\nclass Item(object):\n <mask token>\n\n def convert_string_to_item(self, string):\n tokens = str(string).split(',')\n self._platform_type = tokens[0]\n self._sensor_name = tokens[1]\n ... | [
13,
17,
18,
19,
20
] |
<|reserved_special_token_0|>
class Solution:
def countStudents(self, students, sandwiches) ->int:
if not students or not sandwiches:
return 0
while students:
top_san = sandwiches[0]
if top_san == students[0]:
students = students[1:]
... | flexible | {
"blob_id": "235fce2615e2a5879f455aac9bcecbc2d152679b",
"index": 4548,
"step-1": "<mask token>\n\n\nclass Solution:\n\n def countStudents(self, students, sandwiches) ->int:\n if not students or not sandwiches:\n return 0\n while students:\n top_san = sandwiches[0]\n ... | [
2,
3,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name=NagAconda.__name__, version=NagAconda.__version__, description=
'NagAconda is a Python Nagios wrapper.', long_description=open('README'
).read(), author='Steven Schlegel', author_email='steven@schlegel.tech',
... | flexible | {
"blob_id": "c3719f30bcf13061134b34b0925dfa2af4535f14",
"index": 7854,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name=NagAconda.__name__, version=NagAconda.__version__, description=\n 'NagAconda is a Python Nagios wrapper.', long_description=open('README'\n ).read(), author='Steven Schle... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 11 07:41:34 2017
@author: Gabriel
"""
months = 12
balance = 4773
annualInterestRate = 0.2
monthlyPaymentRate = 434.9
monthlyInterestRate = annualInterestRate / 12
while months > 0:
minimumMonPayment = monthlyPaymentRate * balance
monthlyUnpaidBa... | normal | {
"blob_id": "299b437c007d78c3d9a53205de96f04d2c6118e0",
"index": 7662,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile months > 0:\n minimumMonPayment = monthlyPaymentRate * balance\n monthlyUnpaidBalan = balance - monthlyPaymentRate\n balance = monthlyUnpaidBalan + monthlyInterestRate * mo... | [
0,
1,
2,
3
] |
from django.db import models
class Event(models.Model):
name = models.TextField()
host = models.TextField(null=True)
fields = models.TextField(null=True)
description = models.TextField(null=True)
date = models.TextField()
start_time = models.TextField()
end_time = models.TextField()
ba... | normal | {
"blob_id": "170716ccaaf45db2ee974de260883a8d70513f52",
"index": 7583,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Event(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask t... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Quest:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class NoobQuest(Quest):
def __init__(self):
self.quest_status = 0
self.quest_name = 'Kill the Rat!'
self.reward_gold = 250
self.reward_exp... | flexible | {
"blob_id": "4d31985cf1266619406d79a7dbae269c10f21bda",
"index": 5510,
"step-1": "<mask token>\n\n\nclass Quest:\n <mask token>\n <mask token>\n <mask token>\n\n\nclass NoobQuest(Quest):\n\n def __init__(self):\n self.quest_status = 0\n self.quest_name = 'Kill the Rat!'\n self.re... | [
5,
6,
8,
9,
10
] |
from django import forms
from django.forms import inlineformset_factory
from django.utils.translation import ugettext, ugettext_lazy as _
from django.contrib.auth.models import User
from django.conf import settings
from django.db.models import Max
from auction.models import *
from datetime import *
from decimal import ... | normal | {
"blob_id": "5215b5e4efe2e126f18b3c4457dc3e3902923d49",
"index": 6360,
"step-1": "<mask token>\n\n\nclass UserForm(forms.ModelForm):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n model = User\n fields = 'first_name', 'last_name', 'email'\n <mask token>\n <mask t... | [
10,
11,
15,
16,
17
] |
# The Minion Game
# Kevin and Stuart want to play the 'The Minion Game'.
# Your task is to determine the winner of the game and their score.
"""
Game Rules
Both players are given the same string, S.
Both players have to make substrings using the letters of the string S.
Stuart has to make words starting with consonant... | normal | {
"blob_id": "c96ebfe41b778e85e954e2b7d6de4b078e72c81f",
"index": 7203,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(len(string)):\n if string[i] in vowels:\n Kevin += len(string) - i\n else:\n Stuart += len(string) - i\nif Kevin > Stuart:\n print('Kevin', Kevin)\ne... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in r:
print(i.group(1))
provinceName = i.group(1)
provinceShortName = i.group(2)
confirmedCount = i.group(3)
iter_dict.setdefault(provinceShortName, confirmedCount)
<|reserved_special_token_1|>
<|reser... | flexible | {
"blob_id": "5aecd021297fee4407d6b529c24afb3c6398f7ba",
"index": 7205,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in r:\n print(i.group(1))\n provinceName = i.group(1)\n provinceShortName = i.group(2)\n confirmedCount = i.group(3)\n iter_dict.setdefault(provinceShortName, confirm... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class BayesNetClassifier:
def __init__(self, train_file, out_file):
self.train_file = train_file
self.out_file = out_file
self.word_count_loc = {}
self.word_probs = {}
self.l_probs = {}
self.word_counts = {}
self.common_words = ... | flexible | {
"blob_id": "dee7b12862d02837fbb0f2310b136dd768ca7bab",
"index": 3277,
"step-1": "<mask token>\n\n\nclass BayesNetClassifier:\n\n def __init__(self, train_file, out_file):\n self.train_file = train_file\n self.out_file = out_file\n self.word_count_loc = {}\n self.word_probs = {}\n ... | [
3,
6,
7,
8,
10
] |
import re
def parse_rule(rule):
elem_regex = re.compile("(\d+) (.*) bags?.*")
rule = rule[:-1]
color, inside = tuple(rule.split(" bags contain"))
result = []
for element in inside.split(","):
match = elem_regex.search(element)
if match:
result.append((match.gro... | normal | {
"blob_id": "730aaa0404a0c776ce4d3a351f292f90768b6867",
"index": 7781,
"step-1": "<mask token>\n\n\ndef get_neighbours(graph, v):\n return [color for color, _ in graph[v]]\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef parse_rule(rule):\n elem_regex = re.compile('(\\\\d+) (.*) bags?.*')\n rule... | [
1,
4,
5,
6,
7
] |
import tkinter as tk
from pickplace import PickPlace
import sys
import math
from tkinter import messagebox
import os
DEBUG = False
class GerberCanvas:
file_gto = False
file_gtp = False
units = 0
units_string = ('i', 'm')
"""
my canvas
"""
def __init__(self, frame):
self.x_fo... | normal | {
"blob_id": "6b2f10449909d978ee294a502a376c8091af06e0",
"index": 1285,
"step-1": "<mask token>\n\n\nclass GerberCanvas:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __init__(self, frame):\n self.x_format = ''\n self.y_format = ''\n self... | [
18,
19,
20,
23,
25
] |
<|reserved_special_token_0|>
class ModuloConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ModuloConfig(AppConfig):
<|reserved_special_token_0|>
<|reserved_special_token_0|>... | flexible | {
"blob_id": "31275ca9e20da9d2709ea396e55c113b3ff4f571",
"index": 7738,
"step-1": "<mask token>\n\n\nclass ModuloConfig(AppConfig):\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ModuloConfig(AppConfig):\n <mask token>\n <mask token>\n\n def ready(self):\n ... | [
1,
2,
3,
4,
5
] |
from multiprocessing import Process, Queue
def f(q):
for i in range(0,100):
print("come on baby")
q.put([42, None, 'hello'])
if __name__ == '__main__':
q = Queue()
p = Process(target=f, args=(q,))
p.start()
for j in range(0, 2000):
if j == 1800:
print(q.get())
... | normal | {
"blob_id": "c7258d77db2fe6e1470c972ddd94b2ed02f48003",
"index": 3390,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef f(q):\n for i in range(0, 100):\n print('come on baby')\n q.put([42, None, 'hello'])\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef f(q):\n for i in rang... | [
0,
1,
2,
3,
4
] |
import json
import jieba
import util
from pypinyin import pinyin, Style
class Song:
def __init__(self, songName, artistName, lyric):
self.songName = songName
self.artistName = artistName
self.lyric = lyric
self.phrasePinyinDict = util.lyricToPinYi(self.lyric)
def getSongName(se... | normal | {
"blob_id": "fa3cec0781b9ca5c1d99a7500748104d7cdce631",
"index": 130,
"step-1": "<mask token>\n\n\nclass Song:\n\n def __init__(self, songName, artistName, lyric):\n self.songName = songName\n self.artistName = artistName\n self.lyric = lyric\n self.phrasePinyinDict = util.lyricToP... | [
6,
7,
8,
9,
10
] |
import uuid
from cqlengine import columns
from cqlengine.models import Model
from datetime import datetime as dt
class MBase(Model):
__abstract__ = True
#__keyspace__ = model_keyspace
class Post(MBase):
id = columns.BigInt(index=True, primary_key=True)
user_id = columns.Integer(required=True, index=... | normal | {
"blob_id": "9cb734f67d5149b052ff1d412d446aea1654fa69",
"index": 9543,
"step-1": "<mask token>\n\n\nclass User(MBase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass UserTimeLine(MBase):\n \"\"\"\n POSTs that user will see in their timeline\n \"\"\"\... | [
30,
32,
35,
37,
41
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in f1:
f2.write(line.replace('_', '\n'))
f1.close()
f2.close()
<|reserved_special_token_0|>
open('ANSWER.txt', 'w').writelines(lines[:+1])
<|reserved_special_token_1|>
<|reserved_special_token_0|>
f1 = open('Comple... | flexible | {
"blob_id": "d02ef5fc27cde353e90dda4090905b89b5be5c49",
"index": 2897,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in f1:\n f2.write(line.replace('_', '\\n'))\nf1.close()\nf2.close()\n<mask token>\nopen('ANSWER.txt', 'w').writelines(lines[:+1])\n",
"step-3": "<mask token>\nf1 = open('Com... | [
0,
1,
2,
3,
4
] |
from collections import defaultdict
def solution(clothes):
answer = 1
hash_map = defaultdict(lambda : 0)
for value, key in clothes:
hash_map[key] += 1
for v in hash_map.values():
answer *= v + 1
return answer - 1
| normal | {
"blob_id": "601089c2555e6fc75803087ee1d8af7f8180f651",
"index": 4199,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef solution(clothes):\n answer = 1\n hash_map = defaultdict(lambda : 0)\n for value, key in clothes:\n hash_map[key] += 1\n for v in hash_map.values():\n an... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class AudioEffectsChain:
def __init__(self):
self.command = []
def equalizer(self, frequency, q=1.0, db=-3.0):
"""equalizer takes three parameters: filter center frequency in Hz, "q"
or band-width (default=1.0), and a signed number for gain or
att... | flexible | {
"blob_id": "f98f2ef0d94839711b473ad1ca32b85645d4014e",
"index": 8764,
"step-1": "<mask token>\n\n\nclass AudioEffectsChain:\n\n def __init__(self):\n self.command = []\n\n def equalizer(self, frequency, q=1.0, db=-3.0):\n \"\"\"equalizer takes three parameters: filter center frequency in Hz,... | [
22,
27,
29,
31,
42
] |
# Problem No.: 77
# Solver: Jinmin Goh
# Date: 20191230
# URL: https://leetcode.com/problems/combinations/
import sys
class Solution:
def combine(self, n: int, k: int) -> List[List[int]]:
if k == 0:
return [[]]
ans = []
for i in range(k, n + 1) :
for tem... | normal | {
"blob_id": "e4a2c605ef063eee46880515dfff05562916ab81",
"index": 9976,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass Solution:\n\n def combine(self, n: int, k: int) ->List[List[int]]:\n if k == 0:\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class SourcePanel(AbstractPanel):
def __init__(self):
super(SourcePanel, self).__init__()
def packagePath(self):
"""
This file holds the link to the active panels.
The structure is a dictionary, the key is the class name
and the values is ... | flexible | {
"blob_id": "aa0a69e3286934fcfdf31bd713eca1e8dd90aeaa",
"index": 6914,
"step-1": "<mask token>\n\n\nclass SourcePanel(AbstractPanel):\n\n def __init__(self):\n super(SourcePanel, self).__init__()\n\n def packagePath(self):\n \"\"\"\n This file holds the link to the active panels.\n ... | [
4,
5,
6,
7,
8
] |
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# ... | normal | {
"blob_id": "2ab303a2f36cdd64e2119856312dd5e38ee728d6",
"index": 9632,
"step-1": "<mask token>\n\n\nclass LoadBalancerTest(common.HeatTestCase):\n\n def setUp(self):\n super(LoadBalancerTest, self).setUp()\n self.lb_template = {'AWSTemplateFormatVersion': '2010-09-09',\n 'Description'... | [
62,
89,
97,
102,
126
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Test(unittest.TestCase):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Test(unittest.TestCase):
def test(self):
pass
<|reserved_special_token_1|>
impo... | flexible | {
"blob_id": "cb08b95e3b9c80fb74d4415b3798ddbb36cd76e7",
"index": 419,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Test(unittest.TestCase):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Test(unittest.TestCase):\n\n def test(self):\n pass\n",
"step-4": "import unittest... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class IOHandler:
<|reserved_special_token_0|>
def dump_data(self):
"""save the data contained in data_instance, checking whether the
directories already exist and asking whether to create them if not. """
while not path.isdir(self.directory):
p... | flexible | {
"blob_id": "267276eab470b5216a2102f3e7616f7aecadcfe9",
"index": 9428,
"step-1": "<mask token>\n\n\nclass IOHandler:\n <mask token>\n\n def dump_data(self):\n \"\"\"save the data contained in data_instance, checking whether the\n directories already exist and asking whether to create them if ... | [
3,
4,
5,
6,
7
] |
#Voir paragraphe "3.6 Normalizing Text", page 107 de NLP with Python
from nltk.stem.snowball import SnowballStemmer
from nltk.stem.wordnet import WordNetLemmatizer
# Il faut retirer les stopwords avant de stemmer
stemmer = SnowballStemmer("english", ignore_stopwords=True)
lemmatizer = WordNetLemmatizer()
source = ... | normal | {
"blob_id": "1f1677687ba6ca47b18728b0fd3b9926436e9796",
"index": 2949,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(stems1)\nprint(stems2)\nprint(stems3)\n",
"step-3": "<mask token>\nstemmer = SnowballStemmer('english', ignore_stopwords=True)\nlemmatizer = WordNetLemmatizer()\nsource = ['having... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with ____.____(____):
doc = ____
print(____)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
nlp = spacy.load('en_core_web_sm')
text = (
'Chick-fil-A is an American fast food restaurant chain headquartered... | flexible | {
"blob_id": "6eecf0ff1ad762089db6e9498e906e68b507370c",
"index": 1875,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith ____.____(____):\n doc = ____\n print(____)\n",
"step-3": "<mask token>\nnlp = spacy.load('en_core_web_sm')\ntext = (\n 'Chick-fil-A is an American fast food restaurant ch... | [
0,
1,
2,
3,
4
] |
#Small enough? - Beginner
# You will be given an array and a limit value.
# You must check that all values in the array are
# below or equal to the limit value. If they are,
# return true. Else, return false.
def small_enough(array, limit):
counter = ""
for arr in array:
if arr <= limit:
... | normal | {
"blob_id": "117b340b13b9b1c53d3df1646cd5924f0118ab5d",
"index": 5512,
"step-1": "<mask token>\n",
"step-2": "def small_enough(array, limit):\n counter = ''\n for arr in array:\n if arr <= limit:\n counter += 'True,'\n else:\n counter += 'False,'\n if 'False' in cou... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ciscoL2natMIB.setRevisions(('2013-04-16 00:00',))
if mibBuilder.loadTexts:
ciscoL2natMIB.setLastUpdated('201304160000Z')
if mibBuilder.loadTexts:
ciscoL2natMIB.setOrganization('Cisco Systems, Inc.')
<|reserved_special_toke... | flexible | {
"blob_id": "2fb95fa2b7062085f31c6b1dbb8c1336c3871e93",
"index": 3271,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nciscoL2natMIB.setRevisions(('2013-04-16 00:00',))\nif mibBuilder.loadTexts:\n ciscoL2natMIB.setLastUpdated('201304160000Z')\nif mibBuilder.loadTexts:\n ciscoL2natMIB.setOrganization... | [
0,
1,
2,
3
] |
#!usr/bin/env python
# -*- coding:utf-8 _*
"""
@File : build_model_2.py
@Author : ljt
@Description: xx
@Time : 2021/6/12 21:46
"""
import numpy as np
import SimpleITK as sitk
import skimage.restoration.deconvolution
from numpy.fft import fftn, ifftn
new_img = sitk.ReadImage("../../data/ground_data/new_img.nii")
s... | normal | {
"blob_id": "f84ab1530cbc6bd25c45fc607d8f1cd461b180bf",
"index": 2089,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor h in range(11, 41):\n for i in range(model_img_array.shape[0]):\n for j in range(model_img_array.shape[2]):\n dis = np.sqrt(pow(13 - i, 2) + pow(9 - j, 2))\n ... | [
0,
1,
2,
3,
4
] |
data=[1,4,2,3,6,8,9,7]
def partition(data,l,h):
i=l
j=h
pivot=data[l]
while(i<j):
while(data[i]<=pivot and i<=h-1):
i=i+1
while(data[j]>pivot and j>=l+1):
j=j-1
if(i<j):
data[i],dat... | normal | {
"blob_id": "1cd82883e9a73cfbe067d58c30659b9b2e5bf473",
"index": 9349,
"step-1": "<mask token>\n\n\ndef partition(data, l, h):\n i = l\n j = h\n pivot = data[l]\n while i < j:\n while data[i] <= pivot and i <= h - 1:\n i = i + 1\n while data[j] > pivot and j >= l + 1:\n ... | [
1,
2,
3,
4,
5
] |
# 14. Sort dataframe (birds) first by the values in the 'age' in decending order, then by the value in the 'visits' column in ascending order.
import pymongo
myclient = pymongo.MongoClient("mongodb://localhost:27017/")
mydb = myclient["divya_db"]
mycol = mydb["vani_data"]
# age column in decending order
myquery = my... | normal | {
"blob_id": "d91bacfd4b45832a79189c0f1ec4f4cb3ef14851",
"index": 2210,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(list(myquery))\n<mask token>\nprint(list(myquery))\n",
"step-3": "<mask token>\nmyclient = pymongo.MongoClient('mongodb://localhost:27017/')\nmydb = myclient['divya_db']\nmycol = ... | [
0,
1,
2,
3,
4
] |
import matplotlib.pyplot as plt
import numpy as np
import random
plt.ion()
def draw_board(grid_size, hole_pos,wall_pos):
board = np.ones((grid_size,grid_size))
board[wall_pos] = 10
board[hole_pos] = 0
return board
class Game():
"""
A class which implements the Gobble game. Initializes with a ... | normal | {
"blob_id": "a74f2050a057f579a8a8b77ac04ef09073cdb6cf",
"index": 6057,
"step-1": "<mask token>\n\n\nclass Game:\n <mask token>\n\n def __init__(self, grid_size):\n self.grid_size = grid_size\n self.start_game(grid_size)\n plt.title(\"Nate's Lame Game\")\n\n def start_game(self, grid... | [
8,
9,
10,
12,
13
] |
import collections
def range(state):
ran = state["tmp"]["analysis"]["range"]
rang = {
key : [ state["rank"][i] for i in val & ran ]
for key, val in state["tmp"]["analysis"]["keys"].items()
if val & ran
}
for item in state["tmp"]["items"]:
item.setdefault("rank", 0)
item_keys = set(item.keys())
rang_... | normal | {
"blob_id": "51868f26599c5878f8eb976d928c30d0bf61547d",
"index": 9701,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef range(state):\n ran = state['tmp']['analysis']['range']\n rang = {key: [state['rank'][i] for i in val & ran] for key, val in\n state['tmp']['analysis']['keys'].items(... | [
0,
1,
2,
3,
4
] |
from mlagents_envs.registry import default_registry
from mlagents_envs.envs.pettingzoo_env_factory import logger, PettingZooEnvFactory
# Register each environment in default_registry as a PettingZooEnv
for key in default_registry:
env_name = key
if key[0].isdigit():
env_name = key.replace("3", "Three")... | normal | {
"blob_id": "3bec28561c306a46c43dafc8bdc2e01f2ea06180",
"index": 9491,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor key in default_registry:\n env_name = key\n if key[0].isdigit():\n env_name = key.replace('3', 'Three')\n if not env_name.isidentifier():\n logger.warning(\n ... | [
0,
1,
2,
3
] |
class TestContext:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class TestContext:
<|reserved_special_token_0|>
def test_should_get_variable_from_local_state(self, fake_context):
expected = 'test'
fake_context... | flexible | {
"blob_id": "e83a9a4675e5beed938860037658d33c4d347b29",
"index": 8528,
"step-1": "class TestContext:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class TestContext:\n <mask token>\n\n def test_should_get_variable_from_local_state(self, fake_context):\n expected = 'test'\n ... | [
1,
2,
3,
4,
5
] |
import os
pil = 'y'
while(pil=='y'):
os.system("cls")
print("===============================")
print("== KALKULATOR SEDERHANA ==")
print("===============================")
print("MENU-UTAMA : ")
print("1 Penjumlahan")
print("2 Pengurangan")
print("3 Perkalian")
print("4 Pembagia... | normal | {
"blob_id": "9e7dee9c0fd4cd290f4710649ffc4a94fedf0358",
"index": 356,
"step-1": "import os\npil = 'y'\nwhile(pil=='y'):\n os.system(\"cls\")\n print(\"===============================\")\n print(\"== KALKULATOR SEDERHANA ==\")\n print(\"===============================\")\n print(\"MENU-UTAMA :... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with tf.Session() as sess:
output_1, output_2 = sess.run([output_1, output_2])
print(output_1, output_2)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
<|reserved_special_... | flexible | {
"blob_id": "da2e388c64bbf65bcef7d09d7596c2869f51524a",
"index": 4025,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith tf.Session() as sess:\n output_1, output_2 = sess.run([output_1, output_2])\nprint(output_1, output_2)\n",
"step-3": "<mask token>\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'\n<ma... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class DockerUtils:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DockerUtils:
<|reserved_special_token_0|>
@staticmethod
def remove_current_docker_container(user_id, is_retry=False):
... | flexible | {
"blob_id": "e2e2e746d0a8f6b01e6f54e930c7def2d48c2d62",
"index": 4653,
"step-1": "<mask token>\n\n\nclass DockerUtils:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass DockerUtils:\n <mask token>\n\n @staticmethod\n def remove_current_docker_container(user_id, is_retry=False)... | [
1,
2,
3,
4,
5
] |
# Generated by Django 3.0.5 on 2020-04-23 11:23
from django.conf import settings
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('review', '0002_auto_20200419_1409'),
]
operations = [
... | normal | {
"blob_id": "8471e6a3b6623236740ad5219e5038a64e0c0056",
"index": 2083,
"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
] |
# pylint: disable=wrong-import-position,wrong-import-order
from gevent import monkey
monkey.patch_all()
from gevent.pywsgi import WSGIServer
from waitlist.app import app
http_server = WSGIServer(("0.0.0.0", 5000), app)
http_server.serve_forever()
| normal | {
"blob_id": "c36625dfbd733767b09fcb5505d029ae2b16aa44",
"index": 7077,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmonkey.patch_all()\n<mask token>\nhttp_server.serve_forever()\n",
"step-3": "<mask token>\nmonkey.patch_all()\n<mask token>\nhttp_server = WSGIServer(('0.0.0.0', 5000), app)\nhttp_serve... | [
0,
1,
2,
3,
4
] |
from django import forms
from django.forms import ModelForm
from django.contrib.auth.models import User
from .models import Attendance, Holidays
#I think the update forms are not required here. They might be required in the profiles app. For this app, update attendance option can be available to the staff and faculty... | normal | {
"blob_id": "d48f02d8d5469b966f109e8652f25352bc9b3b80",
"index": 7252,
"step-1": "<mask token>\n\n\nclass AttendanceUpdateForm(ModelForm):\n\n\n class Meta:\n model = Attendance\n fields = 'enrollment_id', 'date', 'present', 'absent', 'outpass'\n",
"step-2": "<mask token>\n\n\nclass HolidaysUp... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def post_detail(request, pk):
post = get_object_or_404(Post, pk=pk)
return render(request, 'blog/post_detail.html', {'post': post})
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def list_of_posts(request... | flexible | {
"blob_id": "71a0900dc09b1ff55e4e5a4cc7cab617b9c73406",
"index": 4519,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef post_detail(request, pk):\n post = get_object_or_404(Post, pk=pk)\n return render(request, 'blog/post_detail.html', {'post': post})\n",
"step-3": "<mask token>\n\n\ndef li... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Cube:
<|reserved_special_token_0|>
def sortPieces(self):
self.pieces.sort(key=lambda x: x.location[2] * cubeSize * cubeSize +
x.location[1] * cubeSize + x.location[0])
<|reserved_special_token_0|>
def countUnmatched(self):
colorList = [R... | flexible | {
"blob_id": "1d8e48aab59869831defcccdd8902230b0f3daa7",
"index": 5368,
"step-1": "<mask token>\n\n\nclass Cube:\n <mask token>\n\n def sortPieces(self):\n self.pieces.sort(key=lambda x: x.location[2] * cubeSize * cubeSize +\n x.location[1] * cubeSize + x.location[0])\n <mask token>\n\n... | [
19,
23,
24,
26,
29
] |
data = [] ##用來裝reviews.txt的留言
count = 0 ##計數目前檔案讀取到第幾筆
with open('reviews.txt', 'r') as f:
for line in f:
data.append(line)
count += 1
if count % 1000 == 0:
print(len(data))
total = len(data)
print('檔案讀取完了,總共有', len(data), '筆資料')
print(len(data)) #印出data串列的--項目數量
print(le... | normal | {
"blob_id": "835beebe452a252fb744a06d3e6ff221469af6bf",
"index": 6699,
"step-1": "data = [] ##用來裝reviews.txt的留言\ncount = 0 ##計數目前檔案讀取到第幾筆\n\nwith open('reviews.txt', 'r') as f:\n for line in f:\n data.append(line)\n count += 1\n if count % 1000 == 0:\n print(len(data))\ntotal... | [
0
] |
import boto3
class NetworkLookup:
def __init__(self):
self.loaded = 0
self.subnets = {}
self.vpcs = {}
def load(self):
if self.loaded:
return
client = boto3.client('ec2')
# load subnets
subnets_r = client.describe_subnets()
subnets_... | normal | {
"blob_id": "767c0e6d956701fcedddb153b6c47f404dec535a",
"index": 65,
"step-1": "<mask token>\n\n\nclass NetworkLookup:\n\n def __init__(self):\n self.loaded = 0\n self.subnets = {}\n self.vpcs = {}\n\n def load(self):\n if self.loaded:\n return\n client = boto3... | [
6,
7,
9,
10,
11
] |
"""
采集端任务状态统计
直接在数据库查找数据
create by judy 2018/10/22
update by judy 2019/03/05
更改统一输出为output
"""
from datetime import datetime
import time
import traceback
import pytz
from datacontract import ETaskStatus
from datacontract.clientstatus.statustask import StatusTask
from idownclient.clientdbmanager import DbManager
from... | normal | {
"blob_id": "de0d0588106ab651a8d6141a44cd9e286b0ad3a5",
"index": 1299,
"step-1": "<mask token>\n\n\nclass ClientTaskStatus(object):\n <mask token>\n <mask token>\n\n def start(self):\n while True:\n try:\n self.get_task_status_info()\n lines = StatusTask(s... | [
2,
3,
4,
5,
6
] |
# Generated by Django 3.0 on 2019-12-15 16:20
import datetime
from django.db import migrations, models
from django.utils.timezone import utc
class Migration(migrations.Migration):
dependencies = [
('blog', '0013_auto_20191215_1619'),
]
operations = [
migrations.AlterField(
m... | normal | {
"blob_id": "38a79f5b3ce1beb3dc1758880d42ceabc800ece7",
"index": 8818,
"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 = [('blog', '001... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ExtractSubscriptionPDFView(AccountMixin):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Extract... | flexible | {
"blob_id": "431f109903e014a29aed7f125d47f327e17b9f65",
"index": 4366,
"step-1": "<mask token>\n\n\nclass ExtractSubscriptionPDFView(AccountMixin):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass ExtractSubscriptionPDFView(Account... | [
1,
4,
6,
7,
8
] |
"""Unit tests for the `esmvalcore.preprocessor._rolling_window` function."""
import unittest
import iris.coords
import iris.exceptions
import numpy as np
from cf_units import Unit
from iris.cube import Cube
from numpy.testing import assert_equal
from esmvalcore.preprocessor._rolling_window import rolling_window_stati... | normal | {
"blob_id": "9539d2a4da87af1ff90b83bbcf72dfc8ab7b6db0",
"index": 5501,
"step-1": "<mask token>\n\n\nclass TestRollingWindow(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Te... | [
1,
7,
8,
9,
11
] |
class Solution:
# @param num, a list of integer
# @return an integer
def rob(self, num):
n = len(num)
if n == 0:
return 0
if(n == 1):
return num[0]
f = [0] * n
f[0] = num[0]
f[1] = max(num[0],num[1])
for i in xrange(2,n):
... | normal | {
"blob_id": "bca0baaffefed6917939614defadf9960ffa4727",
"index": 8062,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def rob(self, num):\n n = len(num)\n if n == 0:\n return 0\n if n == 1:\n return num... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Task:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def set_subtasks(self, subtasks):
self.subtasks = subtasks
<|reserved_special_token_1|>
class Task:
def __init__(self):
self.title = ''
self.sub... | flexible | {
"blob_id": "3cf2ffbc8163c2a447016c93ff4dd13e410fff2b",
"index": 7353,
"step-1": "<mask token>\n",
"step-2": "class Task:\n <mask token>\n <mask token>\n\n def set_subtasks(self, subtasks):\n self.subtasks = subtasks\n",
"step-3": "class Task:\n\n def __init__(self):\n self.title = ... | [
0,
2,
3,
4,
5
] |
import os
import json
import requests
from fin import myBuilder, myParser
import time
def open_config():
if os.path.isfile('fin/config.json') != True:
return ('no config found')
else:
print('config found')
with open('fin/config.json') as conf:
conf = json.load(conf)
return conf
conf = open_config()
logf... | normal | {
"blob_id": "e690587c9b056f8d5a1be6dd062a2aa32e215f50",
"index": 2328,
"step-1": "<mask token>\n\n\ndef open_config():\n if os.path.isfile('fin/config.json') != True:\n return 'no config found'\n else:\n print('config found')\n with open('fin/config.json') as conf:\n conf = json.loa... | [
3,
6,
7,
9,
11
] |
from hicity.graphics.graphics import HiCityGUI
def GUI():
app = HiCityGUI()
app.mainloop()
if __name__ == '__main__':
GUI()
| normal | {
"blob_id": "dd96b7f73c07bf0c74e6ce4dbff1a9cc09729b72",
"index": 7918,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef GUI():\n app = HiCityGUI()\n app.mainloop()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef GUI():\n app = HiCityGUI()\n app.mainloop()\n\n\nif __name__ == '_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_begin_data(url):
headers = {'ser-Agent': '', 'Cookie': ''}
request = urllib2.Request(url, headers=headers)
web_data = urllib2.urlopen(request)
soup = BeautifulSoup(web_data, 'html.parser')
results = soup.select('table > tr > td > a')
answers = soup.select('... | flexible | {
"blob_id": "790110a8cba960eb19593e816b579080dfc46a4e",
"index": 4572,
"step-1": "<mask token>\n\n\ndef get_begin_data(url):\n headers = {'ser-Agent': '', 'Cookie': ''}\n request = urllib2.Request(url, headers=headers)\n web_data = urllib2.urlopen(request)\n soup = BeautifulSoup(web_data, 'html.parse... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class mainwin:
def __init__(self, master):
self.master = master
master.title
master.title('University of Utah XRD Analysis Multi-tool')
self.tab_parent = ttk.Notebook(master)
self.tab1 = ttk.Frame(self.tab_parent)
self.tab2 = ttk.Frame(... | flexible | {
"blob_id": "137ed9c36265781dbebabbd1ee0ea84c9850201a",
"index": 1642,
"step-1": "<mask token>\n\n\nclass mainwin:\n\n def __init__(self, master):\n self.master = master\n master.title\n master.title('University of Utah XRD Analysis Multi-tool')\n self.tab_parent = ttk.Notebook(mas... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "3a5d55ea5a2f4f6cf7aaf55055593db9f8bb3562",
"index": 6308,
"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 = [('descriptor'... | [
0,
1,
2,
3,
4
] |
import imgui
print("begin")
imgui.create_context()
imgui.get_io().display_size = 100, 100
imgui.get_io().fonts.get_tex_data_as_rgba32()
imgui.new_frame()
imgui.begin("Window", True)
imgui.text("HelloWorld")
imgui.end()
imgui.render()
imgui.end_frame()
print("end")
| normal | {
"blob_id": "146cae8f60b908f04bc09b10c4e30693daec89b4",
"index": 6560,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('begin')\nimgui.create_context()\n<mask token>\nimgui.get_io().fonts.get_tex_data_as_rgba32()\nimgui.new_frame()\nimgui.begin('Window', True)\nimgui.text('HelloWorld')\nimgui.end()\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def log_dir_name(learning_rate, dense_layers, nodes, activation):
"""
Creates a directory named after the set of hyperparameters that was recently selected. A helper function
to log the results of training every constructed model.
"""
s = './2_logs/lr_{0:.0e}_layers{1}_nodes{2}... | flexible | {
"blob_id": "db9068e54607e9df48328435ef07f15b4c25a6db",
"index": 7412,
"step-1": "<mask token>\n\n\ndef log_dir_name(learning_rate, dense_layers, nodes, activation):\n \"\"\"\n\tCreates a directory named after the set of hyperparameters that was recently selected. A helper function\n\tto log the results of tr... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class SpectrumMap:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class SpectrumMap2:
def __init__(self):
devices = sd.query_devices()
device = 11
... | flexible | {
"blob_id": "fbde00d727d7ea99d1a7704f46cb9850c8b210d7",
"index": 2610,
"step-1": "<mask token>\n\n\nclass SpectrumMap:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass SpectrumMap2:\n\n def __init__(self):\n devices = sd.query_devices()\n devic... | [
12,
14,
16,
18,
19
] |
from distutils.core import setup
setup(name='dcnn_visualizer', version='', packages=['dcnn_visualizer',
'dcnn_visualizer.backward_functions'], url='', license='', author=
'Aiga SUZUKI', author_email='tochikuji@gmail.com', description='',
requires=['numpy', 'chainer', 'chainercv'])
| normal | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(n - 1):
if a[i + 1] - a[i] < m:
ans += a[i + 1] - a[i]
else:
ans += m
print(ans)
<|reserved_special_token_1|>
n, m = map(int, input().split())
a = [int(input()) for _ in range(n)]
cnt, ans... | flexible | {
"blob_id": "a09bc84a14718422894127a519d67dc0c6b13bc9",
"index": 746,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(n - 1):\n if a[i + 1] - a[i] < m:\n ans += a[i + 1] - a[i]\n else:\n ans += m\nprint(ans)\n",
"step-3": "n, m = map(int, input().split())\na = [int(inp... | [
0,
1,
2,
3
] |
# -*- coding: utf-8 -*-
##################################################
# GNU Radio Python Flow Graph
# Title: channel
# Author: Maria Camila Herrera Ramos
# Generated: Thu Aug 2 18:09:17 2018
##################################################
from gnuradio import analog
from gnuradio import blocks
from gnuradio ... | normal | {
"blob_id": "8adf25fbffc14d6927d665931e54a7d699a3b439",
"index": 6202,
"step-1": "<mask token>\n\n\nclass channel(gr.hier_block2):\n <mask token>\n <mask token>\n\n def set_k(self, k):\n self.k = k\n self.channels_fading_model_0.set_K(self.k)\n\n def get_tchannel(self):\n return ... | [
5,
6,
7,
8,
10
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.11.8 on 2018-04-12 12:37
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('cstasker', '0001_initial'),
]
operations = [
migrations.AlterField(
... | normal | {
"blob_id": "2fbf312e1f8388008bb9ab9ba0ee4ccee1a8beae",
"index": 3594,
"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 = [('cstasker', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class IndexView(edit.FormView):
success_url = '/facilities'
form_class = LoginForm
template_name = 'users/index.html'
def form_valid(self, form):
username = form.cleaned_data['username']
password = form.cleaned_data['password']
user = authenticate(... | flexible | {
"blob_id": "6bd9c8e38373e696193c146b88ebf6601170cf0e",
"index": 9549,
"step-1": "<mask token>\n\n\nclass IndexView(edit.FormView):\n success_url = '/facilities'\n form_class = LoginForm\n template_name = 'users/index.html'\n\n def form_valid(self, form):\n username = form.cleaned_data['userna... | [
3,
4,
5,
6
] |
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 25 15:14:15 2020
@author: luisa
"""
horast = int(input("Horas Trabajadas: "+"\n\t\t"))
tarifa = int(input("Tarifa por hora: "+"\n\t\t"))
descu = int(input("Descuentos: "+"\n\t\t"))
resp0 = horast - descu
resp1 = (resp0 * tarifa)/2
resp2 = (horast * tarifa) ... | normal | {
"blob_id": "4d9575c178b672815bb561116689b9b0721cb5ba",
"index": 919,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif horast >= 41:\n print('Valor a Pagar: ', resp3)\nelif horast <= 40:\n print('Valor a Pagar: ', resp4)\n",
"step-3": "<mask token>\nhorast = int(input('Horas Trabajadas: ' + '\\n... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "a58949d25a719dc9ce0626948ab0397814e9ea0e",
"index": 1574,
"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 = [('analysis', ... | [
0,
1,
2,
3,
4
] |
import argparse
from time import sleep
from threading import Thread
from threading import Lock
from multiprocessing.connection import Listener
from multiprocessing.connection import Client
ADDRESS = '127.0.0.1'
PORT = 5000
# Threaded function snippet
def threaded(fn):
def wrapper(*args, **kwargs):
thread ... | normal | {
"blob_id": "c5a2c00d53111d62df413907d4ff4ca5a02d4035",
"index": 7005,
"step-1": "<mask token>\n\n\nclass Process:\n <mask token>\n <mask token>\n <mask token>\n\n def send_neighbours(self, data, exceptions=[]):\n for i in [x for x in self.neighbours if x not in exceptions]:\n self.... | [
2,
8,
9,
11,
12
] |
if __name__== '__main__':
with open('./input/day6', 'r') as f:
orbit_input = [l.strip().split(")") for l in f.readlines()]
planets = [planet[0] for planet in orbit_input]
planets1 = [planet[1] for planet in orbit_input]
planets = set(planets+planets1)
system = {}
print(orbit_input)
... | normal | {
"blob_id": "96778a238d8ed8ae764d0cf8ec184618dc7cfe18",
"index": 5790,
"step-1": "<mask token>\n",
"step-2": "if __name__ == '__main__':\n with open('./input/day6', 'r') as f:\n orbit_input = [l.strip().split(')') for l in f.readlines()]\n planets = [planet[0] for planet in orbit_input]\n plane... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with veil_component.init_component(__name__):
from .material import list_category_materials
from .material import list_material_categories
from .material import list_issue_materials
from .material import list_issue... | flexible | {
"blob_id": "acad268a228b544d60966a8767734cbf9c1237ac",
"index": 9979,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith veil_component.init_component(__name__):\n from .material import list_category_materials\n from .material import list_material_categories\n from .material import list_issue_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def expandgrid(*itrs):
product = list(itertools.product(*itrs))
return {'Var{}'.format(i + 1): [x[i] for x in product] for i in range(
len(itrs))}
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
heart.columns
<|reserved_special_t... | flexible | {
"blob_id": "0d862715524bd35347626e7708c7c8f8b370bb3a",
"index": 7769,
"step-1": "<mask token>\n\n\ndef expandgrid(*itrs):\n product = list(itertools.product(*itrs))\n return {'Var{}'.format(i + 1): [x[i] for x in product] for i in range(\n len(itrs))}\n\n\n<mask token>\n",
"step-2": "<mask token>... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class ConvolutionalNetwork(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(3, 6, 3, 1)
self.conv2 = nn.Conv2d(6, 16, 3, 1)
self.fc1 = nn.Linear(54 * 54 * 16, 120)
self.fc2 = nn.Linear(120, 84)
self.fc3 = nn.Lin... | flexible | {
"blob_id": "7821b07a49db9f3f46bedc30f2271160e281806f",
"index": 4814,
"step-1": "<mask token>\n\n\nclass ConvolutionalNetwork(nn.Module):\n\n def __init__(self):\n super().__init__()\n self.conv1 = nn.Conv2d(3, 6, 3, 1)\n self.conv2 = nn.Conv2d(6, 16, 3, 1)\n self.fc1 = nn.Linear(... | [
3,
4,
5,
6,
7
] |
class HashTable:
<|reserved_special_token_0|>
def put(self, key, data):
hashvalue = self.hashfunction(key, len(self.slots))
if self.slots[hashvalue] == None:
self.slots[hashvalue] = key
self.data[hashvalue] = data
elif self.slots[hashvalue] == key:
se... | flexible | {
"blob_id": "75741d11bebcd74b790efe7e5633d4507e65a25f",
"index": 6034,
"step-1": "class HashTable:\n <mask token>\n\n def put(self, key, data):\n hashvalue = self.hashfunction(key, len(self.slots))\n if self.slots[hashvalue] == None:\n self.slots[hashvalue] = key\n self.... | [
5,
6,
7,
8,
9
] |
<|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": "45969b346d6d5cbdef2f5d2f74270cf12024072d",
"index": 3,
"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 = [('search', '0003... | [
0,
1,
2,
3,
4
] |
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