code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
#!/usr/bin/env python
# Sanjaya Gajurel, Computational Scientist, Case Western Reserve University, April 2015
import vtk
# ------------------------------------------------------------------------------
# Script Entry Point
# ------------------------------------------------------------------------------
if __name__ ==... | normal | {
"blob_id": "de7515cb71c8e30018b14baf8846648d0c76a592",
"index": 7461,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n print(\n 'vtkGraph: Building a graph using Unstructured Grid & dumping it in a vtk file, vertex.vtu, to be visualized using ParaView'\n )\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
board.display_board()
<|reserved_special_token_0|>
game.take_shot("""
Choose a spot to fire at in enemy seas: """, board)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
row_num = list(string.ascii_lowercase[:10])
col... | flexible | {
"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
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def generateExampleBoletoPaymentsJson(n=1, next_day=False):
boletos = generateExampleBoletosJson(n=n)
boletos = starkbank.boleto.create(boletos)
payments = []
for boleto in boletos:
payment = deepcopy(exa... | flexible | {
"blob_id": "383d3b35fbfb7921111b28c3160173ce1c200387",
"index": 637,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generateExampleBoletoPaymentsJson(n=1, next_day=False):\n boletos = generateExampleBoletosJson(n=n)\n boletos = starkbank.boleto.create(boletos)\n payments = []\n for b... | [
0,
1,
2,
3,
4
] |
pokerAssignments = {'2': 20, '3': 30, '4': 40, '5': 50, '6': 60, '7': 70, '8': 80, '9': 90, 'T': 100, 'J': 110, 'Q': 120, 'K': 130, 'A': 140, 'C': 0, 'S': 1, 'H': 2, 'D': 3} #Used to assign each card to a unique three-digit integer
configScoring = {(1, 1): 0, (1, 2): 1, (2, 2): 2, (1, 3): 3, (2, 3): 6, (1, 4): 7} #Tra... | normal | {
"blob_id": "a2a3e8d52fd467178460b178c5dbf9ccd72706e7",
"index": 8251,
"step-1": "<mask token>\n\n\ndef initialize():\n hands_file = open('euler54_poker.txt')\n hands_string = hands_file.read()\n tempList = []\n newString = hands_string.replace('\\n', ' ').replace(' ', '')\n for i in range(0, len(... | [
6,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def solution(n):
arr = [[(0) for _ in range(i + 1)] for i in range(n)]
size = n
num = 0
x = 0
y = -1
while True:
for _ in range(size):
num += 1
y += 1
arr[y][x] = num
size -= 1
... | flexible | {
"blob_id": "3c029adb59cd6db1e3d4a22e6561f5e2ae827d60",
"index": 2465,
"step-1": "<mask token>\n",
"step-2": "def solution(n):\n arr = [[(0) for _ in range(i + 1)] for i in range(n)]\n size = n\n num = 0\n x = 0\n y = -1\n while True:\n for _ in range(size):\n num += 1\n ... | [
0,
1,
2
] |
count = int(input())
for i in range(1, count + 1):
something = '='
num1, num2 = map(int, input().split())
if num1 > num2:
something = '>'
elif num1 < num2:
something = '<'
print(f'#{i} {something}')
| normal | {
"blob_id": "abcefa0a3312e158517ec8a15421d1d07220da6a",
"index": 5271,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, count + 1):\n something = '='\n num1, num2 = map(int, input().split())\n if num1 > num2:\n something = '>'\n elif num1 < num2:\n something = '<... | [
0,
1,
2
] |
from collections import Counter
import numpy as np
import random
import torch
import BidModel
from douzero.env.game import GameEnv
env_version = "3.2"
env_url = "http://od.vcccz.com/hechuan/env.py"
Card2Column = {3: 0, 4: 1, 5: 2, 6: 3, 7: 4, 8: 5, 9: 6, 10: 7,
11: 8, 12: 9, 13: 10, 14: 11, 17: 12}
Nu... | normal | {
"blob_id": "4015078ee9640c4558a4f29ebbb89f9098a31014",
"index": 5720,
"step-1": "<mask token>\n\n\nclass Env:\n <mask token>\n\n def __init__(self, objective):\n \"\"\"\n Objective is wp/adp/logadp. It indicates whether considers\n bomb in reward calculation. Here, we use dummy agents... | [
13,
24,
32,
36,
37
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
UNK_TOKEN = '<unk>'
BOS_TOKEN = '<bos>'
EOS_TOKEN = '<eos>'
PAD_TOKEN = '<pad>'
UNK_IDX = 0
LARGE_POSITIVE_FLOAT = 1e+18
LARGE_NEGATIVE_FLOAT = -LARGE_POSITIVE_FLOAT
GLOVE_NPZ_SHA1 = {'glove.42B.300d': ('glove.42B.300d.npz',
'... | flexible | {
"blob_id": "4dde161d25ed41154e13b94cc9640c6aac055f87",
"index": 6164,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nUNK_TOKEN = '<unk>'\nBOS_TOKEN = '<bos>'\nEOS_TOKEN = '<eos>'\nPAD_TOKEN = '<pad>'\nUNK_IDX = 0\nLARGE_POSITIVE_FLOAT = 1e+18\nLARGE_NEGATIVE_FLOAT = -LARGE_POSITIVE_FLOAT\nGLOVE_NPZ_SHA1... | [
0,
1,
2
] |
import random
# Imports MongoClient for base level access to the local MongoDB
from pymongo import MongoClient
# Imports datetime class to create timestamp for weather data storage
from datetime import datetime
# Importing DailyReportModel class to use the implemented method to insert data into daily_report_model ... | normal | {
"blob_id": "a8b1b218e6649545000803c91c803580cfdbd4f1",
"index": 459,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb_handle.drop_database(DB_NAME)\n<mask token>\nwith open(RELATIVE_CONFIG_PATH + USER_COLLECTION + '.csv', 'r') as user_fh:\n for user_row in user_fh:\n user_row = user_row.rstri... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
np.random.seed(123)
<|reserved_special_token_0|>
tf.enable_eager_execution()
tf.set_random_seed(123)
<|reserved_special_token_0|>
gen.add(tf.keras.layers.Dense(H, input_dim=P + R, activation=tf.keras.
activations.elu))
gen.add... | flexible | {
"blob_id": "aba3e0907e59bc5125759e90d3c784ceb97fca80",
"index": 9941,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.random.seed(123)\n<mask token>\ntf.enable_eager_execution()\ntf.set_random_seed(123)\n<mask token>\ngen.add(tf.keras.layers.Dense(H, input_dim=P + R, activation=tf.keras.\n activati... | [
0,
1,
2,
3,
4
] |
import sys
prop = float(sys.argv[1])
def kind(n):
s = str(n)
l = len(s)
i = 0
j = i + 1
decr, bouncy, incr = False, False, False
while j < l:
a = int(s[i])
b = int(s[j])
if s[i] > s[j]:
decr = True
elif s[i] < s[j]:
incr = True
i += 1
j += 1
if decr and incr:
retu... | normal | {
"blob_id": "0de27101675eb8328d9a2831ed468a969b03e7d3",
"index": 5741,
"step-1": "<mask token>\n\n\ndef kind(n):\n s = str(n)\n l = len(s)\n i = 0\n j = i + 1\n decr, bouncy, incr = False, False, False\n while j < l:\n a = int(s[i])\n b = int(s[j])\n if s[i] > s[j]:\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class UserVetSchema(ma.Schema):
class Meta:
model = Uservet
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ma = Marshmallow()
class UserVetSchema(ma.Schema):
cla... | flexible | {
"blob_id": "677154aa99a5a4876532f3e1edfec45b1790384c",
"index": 9511,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass UserVetSchema(ma.Schema):\n\n\n class Meta:\n model = Uservet\n\n\n<mask token>\n",
"step-3": "<mask token>\nma = Marshmallow()\n\n\nclass UserVetSchema(ma.Schema):\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def fibonacci(n):
if n == 0:
return []
elif n == 1:
return [1]
elif n == 2:
return [1, 1]
else:
lista = fibonacci(n - 1)
suma = lista[len(lista) - 1] + lista[len(lista) - 2... | flexible | {
"blob_id": "03062ea08bd6ad88376f7c2aa2c89d2194ed8b2e",
"index": 1074,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fibonacci(n):\n if n == 0:\n return []\n elif n == 1:\n return [1]\n elif n == 2:\n return [1, 1]\n else:\n lista = fibonacci(n - 1)\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for onestore in chikenList:
filename = onestore + '.csv'
myframe = pd.read_csv(filename, index_col=0, encoding=myencoding)
newframe = pd.concat([newframe, myframe], axis=0, ignore_index=True)
print(newframe.info())
<|r... | flexible | {
"blob_id": "11a31d3276201105ca7485fa4e4eb711012accd5",
"index": 2190,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor onestore in chikenList:\n filename = onestore + '.csv'\n myframe = pd.read_csv(filename, index_col=0, encoding=myencoding)\n newframe = pd.concat([newframe, myframe], axis=0,... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
colors = vtk.vtkNamedColors()
Data = np.load('tessaltions_compressed.npz')
indices = meta['sorted_keys']
struct_D = {}
for i, s in enumerate(set([x[0] for x in indices])):
struct_D[s] = colors_list[i]
renderer = vtk.vtkRenderer()
renWin = vt... | flexible | {
"blob_id": "7261c5f9ac87c8337383daec312372b345ab7652",
"index": 4109,
"step-1": "<mask token>\n\n\ndef main():\n colors = vtk.vtkNamedColors()\n Data = np.load('tessaltions_compressed.npz')\n indices = meta['sorted_keys']\n struct_D = {}\n for i, s in enumerate(set([x[0] for x in indices])):\n ... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def bin_spatial(img, color_space='RGB', size=(32, 32)):
colour_dict = {'RGB': 'RGB', 'BGR': cv2.COLOR_BGR2RGB, 'HLS': cv2.
COLOR_BGR2HLS, 'HSV': cv2.COLOR_BGR2HSV, 'LUV': cv2.COLOR_BGR2LUV,
'YUV': cv2.COLOR_R... | flexible | {
"blob_id": "f178ae70ce54244624c2254d0d6256b83144db33",
"index": 5085,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef bin_spatial(img, color_space='RGB', size=(32, 32)):\n colour_dict = {'RGB': 'RGB', 'BGR': cv2.COLOR_BGR2RGB, 'HLS': cv2.\n COLOR_BGR2HLS, 'HSV': cv2.COLOR_BGR2HSV, 'LUV'... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if len(obj_list):
for obj in obj_list:
obj.print_object()
print()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
request_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)
obj_list... | flexible | {
"blob_id": "c65969bba72142f4a328f978d78e0235cd56e393",
"index": 8618,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(obj_list):\n for obj in obj_list:\n obj.print_object()\n print()\n",
"step-3": "<mask token>\nrequest_client = RequestClient(api_key=g_api_key, secret_key=g_secr... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for d in doc:
word = d.text
pos = d.pos_
dep = d.dep_
if re.search('subj', dep):
word2 = (ahref + 'http://www.superai.online/solr/search.php?query=' +
word + ahref2 + word + '</a>')
subj... | flexible | {
"blob_id": "ecc001394c1f3bba78559cba7eeb216dd3a942d8",
"index": 4711,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor d in doc:\n word = d.text\n pos = d.pos_\n dep = d.dep_\n if re.search('subj', dep):\n word2 = (ahref + 'http://www.superai.online/solr/search.php?query=' +\n ... | [
0,
1,
2,
3,
4
] |
import requests
import unittest
import time
from common import HTMLTestReport
class Get(unittest.TestCase):
TMPTOKEN = ''
TOKEN = ''
def setUp(self):
pass
# 获取临时token，opterTmpToken
def test_gettmptoken(self):
url = 'https://jdapi.jd100.com/uc/core/v1/sys/opterTmpToken'
par... | normal | {
"blob_id": "773c217f7f76bd82ed3dabf7ae1aba1871f0932f",
"index": 8539,
"step-1": "<mask token>\n\n\nclass Get(unittest.TestCase):\n <mask token>\n <mask token>\n\n def setUp(self):\n pass\n <mask token>\n\n def test_gettoken(self):\n url = 'https://jdapi.jd100.com/uc/v1/sys/opterToke... | [
6,
7,
8,
11,
12
] |
from django.contrib import admin
from students.models import Child_detail
class ChildAdmin(admin.ModelAdmin):
def queryset(self, request):
"""
Filter the Child objects to only
display those for the currently signed in user.
"""
qs = super(ChildAdmin, self).queryset(reque... | normal | {
"blob_id": "582f2e6972bad85c2aaedd248f050f708c61973b",
"index": 2332,
"step-1": "<mask token>\n\n\nclass ChildAdmin(admin.ModelAdmin):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass ChildAdmin(admin.ModelAdmin):\n\n def queryset(self, request):\n \"\"\"\n Filter th... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
from xrouter import api
api.main()
| normal | {
"blob_id": "64368679aa2e387e25a36b2f3d0312a99b819e95",
"index": 2147,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napi.main()\n",
"step-3": "from xrouter import api\napi.main()\n",
"step-4": "#!/usr/bin/env python\nfrom xrouter import api\napi.main()\n",
"step-5": null,
"step-ids": [
0,
... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for tr in root.xpath("//div[@id='verdiSection10']/div/div/table/tbody/tr")[1:]:
data = {'conviction_date': datetime.strptime(re.match(
'(\\d+/\\d+/\\d+)', tr[0].text_content().strip()).group(1),
'%d/%m/%Y'), 'b... | flexible | {
"blob_id": "e870900249b121f2416d7be543752ebf6392b6be",
"index": 6868,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor tr in root.xpath(\"//div[@id='verdiSection10']/div/div/table/tbody/tr\")[1:]:\n data = {'conviction_date': datetime.strptime(re.match(\n '(\\\\d+/\\\\d+/\\\\d+)', tr[0].text... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main():
good_car = UnreliableCar('good car', 100, 80)
bad_car = UnreliableCar('bad car', 100, 10)
for i in range(10):
print('try to drive {} km'.format(i))
print('{:10} drove {:2}km'.format(good_c... | flexible | {
"blob_id": "f29ad02f3781c7a7d2a1f0c97626dd5c7ea2417e",
"index": 7867,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n good_car = UnreliableCar('good car', 100, 80)\n bad_car = UnreliableCar('bad car', 100, 10)\n for i in range(10):\n print('try to drive {} km'.format(i))... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def func(w, rc):
return 1 / np.sqrt(1 + w ** 2 * rc ** 2)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def func(w, rc):
return 1 / np.sqrt(1 + w ** 2 * rc ** 2)
with open('data/phase.csv') as csvfile:
reader = csv.reader(csvfi... | flexible | {
"blob_id": "170d0560c40f3f642f319f6113b68ab8a6bea9ef",
"index": 468,
"step-1": "<mask token>\n\n\ndef func(w, rc):\n return 1 / np.sqrt(1 + w ** 2 * rc ** 2)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef func(w, rc):\n return 1 / np.sqrt(1 + w ** 2 * rc ** 2)\n\n\nwith open('data/phase.csv') as... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class MyGame(arcade.Window):
<|reserved_special_token_0|>
def __init__(self, width, height, title):
"""
Initializer
"""
super().__init__(width, height, title)
file_path = os.path.dirname(os.path.abspath(__file__))
os.chdir(file_path... | flexible | {
"blob_id": "28d8f9d9b39c40c43a362e57a7907c0a38a6bd05",
"index": 748,
"step-1": "<mask token>\n\n\nclass MyGame(arcade.Window):\n <mask token>\n\n def __init__(self, width, height, title):\n \"\"\"\n Initializer\n \"\"\"\n super().__init__(width, height, title)\n file_pat... | [
6,
7,
9,
12,
13
] |
<|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": "760a5a168575a0ea12b93cb58c1e81e313704e35",
"index": 6276,
"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 = [('viajes', '0... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='EasyVVUQ applied to BOUT++')
parser.add_argument('--batch', '-b', help=
'Run on a batch (SLURM) system', action='store_true', default=False)
... | flexible | {
"blob_id": "416f4c6bbd2f2b9562ab2d1477df4ebc45070d8d",
"index": 5060,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description='EasyVVUQ applied to BOUT++')\n parser.add_argument('--batch', '-b', help=\n 'Run on a batch (SLURM)... | [
0,
1,
2,
3
] |
"""
Cores no terminal
"""
a = 3
b = 5
print('Os valores são \033[32m{}\033[m e \033[31m{}\033[m !!!'.format(a, b))
# Dicionário de cores:
nome = 'Kátia'
cores = {'limpa':'\033]m',
'azul':'\033[34m',
'amarelo':'\033[33m',
'pretoebranco':'\033[7;30m'}
print('Prazer em te conhe... | normal | {
"blob_id": "7bbbd30ba1578c1165ccf5c2fff22609c16dfd64",
"index": 393,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Os valores são \\x1b[32m{}\\x1b[m e \\x1b[31m{}\\x1b[m !!!'.format(a, b))\n<mask token>\nprint('Prazer em te conhecer, {}{}{}!!!'.format(cores['azul'], nome, cores[\n 'amarelo'])... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def individual(list_df: list, seaborn_context: str='poster'):
sns.set_context(seaborn_context)
for df in list_df:
df.plot()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def group(list_df: list, df_col_index: int=0, seaborn_context: str='poster'):
sns.... | flexible | {
"blob_id": "d2632461fcdc39509610b96d43dd1ec42dae362f",
"index": 5229,
"step-1": "<mask token>\n\n\ndef individual(list_df: list, seaborn_context: str='poster'):\n sns.set_context(seaborn_context)\n for df in list_df:\n df.plot()\n",
"step-2": "<mask token>\n\n\ndef group(list_df: list, df_col_ind... | [
1,
2,
3,
4
] |
from flask import Blueprint
views = Blueprint('views', __name__)
from . import routes
| normal | {
"blob_id": "139ccdaf7acb2a2d74649f0c32217d1fe71a954a",
"index": 4800,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nviews = Blueprint('views', __name__)\n<mask token>\n",
"step-3": "from flask import Blueprint\nviews = Blueprint('views', __name__)\nfrom . import routes\n",
"step-4": null,
"step-5... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
__author__ = 'wxy'
class ListProcess(object):
def __init__(self, rsp, nickname):
self.rsp = rsp
self.nickname = nickname
def get_friend_uin(self):
try:
for list in self.rsp['result']['info']:
if list['nick'] == self.nickname:
... | normal | {
"blob_id": "1154fd3883dc8856e24127d56ce6a983308dc1aa",
"index": 3683,
"step-1": "# -*- coding: utf-8 -*-\n__author__ = 'wxy'\n\nclass ListProcess(object):\n def __init__(self, rsp, nickname):\n self.rsp = rsp\n self.nickname = nickname\n\n def get_friend_uin(self):\n try:\n ... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def retry(retry_count=2, delay=5, action_description='not specified',
allowed_exceptions=()):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
for _ in range(retry_count):
... | flexible | {
"blob_id": "79e4592d5ea84cc7c97d68a9390eb5d387045cf0",
"index": 4344,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef retry(retry_count=2, delay=5, action_description='not specified',\n allowed_exceptions=()):\n\n def decorator(func):\n\n @wraps(func)\n def wrapper(*args, **kw... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from celery import Celery
app = Celery('task', include=['task.tasks'])
app.config_from_object('task.config')
if __name__ == '__main__':
app.start()
| normal | {
"blob_id": "68d9f77f91a13c73373c323ef0edbe18af9990a3",
"index": 4321,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.config_from_object('task.config')\nif __name__ == '__main__':\n app.start()\n",
"step-3": "<mask token>\napp = Celery('task', include=['task.tasks'])\napp.config_from_object('tas... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
sorts = ['selection-sort', 'insertion-sort', 'shell-sort']
for sort in sorts:
exe_path = './build/{}'.format(sort.rstrip())
if not os.path.isfile(exe_path):
raise OSError('The executable {} does not exist.'.format(exe_path))
accumula... | flexible | {
"blob_id": "501d50fa933f55c178b4b2eba6cfc5b85592beaa",
"index": 8473,
"step-1": "<mask token>\n\n\ndef main():\n sorts = ['selection-sort', 'insertion-sort', 'shell-sort']\n for sort in sorts:\n exe_path = './build/{}'.format(sort.rstrip())\n if not os.path.isfile(exe_path):\n rai... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class GeneralInformation(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Meta:
ordering = ['name']
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Ge... | flexible | {
"blob_id": "d0f83e3b7eb5e1bc81a56e46043f394757437af8",
"index": 5504,
"step-1": "<mask token>\n\n\nclass GeneralInformation(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n ordering = ['name']\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass GeneralInf... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class CRICAgent(DataSourceAgent):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def run(self):
if self.refresh_interval is None:
self.refresh_interval = 60
while True:
self.update()
time.sleep(self.refresh_interv... | flexible | {
"blob_id": "55c00ce4c1657dc5ce78e5eeccd8e9625c0590dc",
"index": 5345,
"step-1": "<mask token>\n\n\nclass CRICAgent(DataSourceAgent):\n <mask token>\n <mask token>\n\n def run(self):\n if self.refresh_interval is None:\n self.refresh_interval = 60\n while True:\n self... | [
2,
3,
4,
5,
6
] |
from entities.GpsFix import GpsFix
class Visit(object):
"""
A Visit, which represents an arrival-departure to a stay point
Attributes:
id_visit: the id of the visit itself
id_stay_point: the id of the stay point
pivot_arrival_fix: the GpsFix that corresponds to real wo... | normal | {
"blob_id": "703ed320e7c06856a0798d9c0de9aafe24458767",
"index": 7937,
"step-1": "<mask token>\n\n\nclass Visit(object):\n <mask token>\n\n def __init__(self, id_visit, id_stay_point, pivot_arrival_fix: GpsFix,\n pivot_departure_fix: GpsFix, detection_arrival_fix: GpsFix,\n detection_departur... | [
4,
5,
6,
7,
8
] |
import flask
from flask.ext.classy import FlaskView, route, request
from annotator_supreme.controllers.user_controller import UserController
from annotator_supreme.views import view_tools
from annotator_supreme.views import error_views
from flask import render_template, flash, redirect, url_for
from annotator_supreme i... | normal | {
"blob_id": "a2e77298059104b403555af95430d7995f8a697b",
"index": 1379,
"step-1": "<mask token>\n\n\nclass LoginViewWebApp(FlaskView):\n <mask token>\n\n def __init__(self):\n self.user_controller = UserController()\n\n @route('/register', methods=['GET', 'POST'])\n def register_user(self):\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for data in password:
if data != pw:
pass
else:
print('พบข้อมูลรหัสผ่านนี้')
print('แล้วเจอกันใหม่')
<|reserved_special_token_1|>
password = ['123456', '1111']
pw = input('รหัสผ่านคือ>>>')
for data in pa... | flexible | {
"blob_id": "6f05b1352e776e20d6a9e0eb457d8914cbfc2d22",
"index": 2779,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor data in password:\n if data != pw:\n pass\n else:\n print('พบข้อมูลรหัสผ่านนี้')\nprint('แล้วเจอกันใหม่')\n",
"step-3": "password = ['123456', '1111']\npw = inpu... | [
0,
1,
2,
3
] |
import pygame
import numpy as np
import random
from enum import Enum
from .config import *
class Actions(Enum):
FORWARD = 0
RIGHT = 1
LEFT = 2
BACK = 3
class MazeEnv():
''' TODO '''
def __init__(self, GW, GH, SW, SH):
global GRID_WIDTH, GRID_HEIGHT, SCREEN_WIDTH, SCREEN_HEIGHT, BOX_WID... | normal | {
"blob_id": "751d2a07b97d080988c54511ca13a97a969e06bd",
"index": 6405,
"step-1": "<mask token>\n\n\nclass MazeEnv:\n <mask token>\n\n def __init__(self, GW, GH, SW, SH):\n global GRID_WIDTH, GRID_HEIGHT, SCREEN_WIDTH, SCREEN_HEIGHT, BOX_WIDTH, BOX_HEIGHT\n GRID_WIDTH = GW\n GRID_HEIGHT... | [
9,
10,
12,
13,
14
] |
#!/usr/bin/env python
def question():
print("02. 「パトカー」＋「タクシー」＝「パタトクカシーー」")
print("「パトカー」＋「タクシー」の文字を先頭から交互に連結して文字列「パタトクカシーー」を得よ．")
def main():
str1 = "パトカー"
str2 = "タクシー"
print(''.join([x[0] + x[1] for x in zip(str1, str2)]))
if __name__ == '__main__':
question()
main()
| normal | {
"blob_id": "32869a88bb59d47281249b6ebe2357328beb0359",
"index": 3572,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main():\n str1 = 'パトカー'\n str2 = 'タクシー'\n print(''.join([(x[0] + x[1]) for x in zip(str1, str2)]))\n\n\n<mask token>\n",
"step-3": "def question():\n print('02. 「パトカ... | [
0,
1,
2,
3,
4
] |
from googleAPI.drive import *
class GoogleSheet(GoogleDrive):
"""
The base class of Google Sheet API.
It aims at dealing with the Google Sheet data extract and append.
It is not tied to a specific spreadsheet.
This class is powered by pandas. Thus, make sure the data in the
spreadshe... | normal | {
"blob_id": "9e793bd0faef65dfe8ac4b722e50d2055837449f",
"index": 4701,
"step-1": "<mask token>\n\n\nclass GoogleSheet(GoogleDrive):\n <mask token>\n <mask token>\n\n def create_spreadsheet(self, spreadsheet_name: str):\n \"\"\"\n Creates a spreadsheet, returning the newly created spreadshe... | [
4,
8,
10,
12,
13
] |
''' This module creates the models/tables in the database
catalog using sqlalchemy '''
from catalog import db
class Items(db.Model):
''' Model to store all the information about an item '''
id = db.Column(db.Integer, primary_key=True)
email = db.Column(db.String)
item = db.Column(db.... | normal | {
"blob_id": "ad622ff2e1d9286246b2175694a9ae796f8d2557",
"index": 7535,
"step-1": "<mask token>\n\n\nclass Items(db.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\n def __init__(self, email, item, descrip... | [
2,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class _WATERWAYS:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class _WATERWAYS:
def __init__(self):
self.name = 'WATERWAYS'
self.definitions = waterway
self.parents = []
self.childen = []
self.... | flexible | {
"blob_id": "33daf5753b27f6b4bcb7c98e28cf2168e7f0b403",
"index": 9541,
"step-1": "<mask token>\n",
"step-2": "class _WATERWAYS:\n <mask token>\n",
"step-3": "class _WATERWAYS:\n\n def __init__(self):\n self.name = 'WATERWAYS'\n self.definitions = waterway\n self.parents = []\n ... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_weather(request):
form = WeatherForm()
error = ''
output = {}
if request.method == 'POST':
form = WeatherForm(request.POST)
if form.is_valid():
data = form.cleaned_data
... | flexible | {
"blob_id": "be5a683309317f1f6ebc20ad3511fd2b2510e806",
"index": 5535,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_weather(request):\n form = WeatherForm()\n error = ''\n output = {}\n if request.method == 'POST':\n form = WeatherForm(request.POST)\n if form.is_va... | [
0,
1,
2,
3
] |
import requests
import json
import logging
import time
from alto.server.components.datasource import DBInfo, DataSourceAgent
class CRICAgent(DataSourceAgent):
def __init__(self, dbinfo: DBInfo, name: str, namespace='default', **cfg):
super().__init__(dbinfo, name, namespace)
self.uri = self.ensu... | normal | {
"blob_id": "55c00ce4c1657dc5ce78e5eeccd8e9625c0590dc",
"index": 5345,
"step-1": "<mask token>\n\n\nclass CRICAgent(DataSourceAgent):\n <mask token>\n <mask token>\n\n def run(self):\n if self.refresh_interval is None:\n self.refresh_interval = 60\n while True:\n self... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python3
# crits_ldap.py
# This connects to an LDAP server and pulls data about all users.
# Then, it either updates existing targets in CRITS or creates a new entry.
import json
import sys
import datetime
import logging
import logging.config
from configparser import ConfigParser
from ldap3 import Serve... | normal | {
"blob_id": "5d568c5ac9040ad93749c27bd6fe1a956e7456f7",
"index": 9016,
"step-1": "#!/usr/bin/env python3\n# crits_ldap.py\n# This connects to an LDAP server and pulls data about all users.\n# Then, it either updates existing targets in CRITS or creates a new entry.\n\nimport json\nimport sys\nimport datetime\nim... | [
0
] |
#!/usr/bin/python
import sys
def get_params(fname):
d = dict()
with open(fname) as f:
for line in f:
l = line.strip()
if (line[0] == '#'):
continue
param = line.split('=')
v = ' '.join(param[1:])
d[param[0]] = v.strip('\n')
return d
usage_text = "Compares boot configs of two kernels\n" \
"U... | normal | {
"blob_id": "d287a5128ca9352b2edc459c9e42a57ef800ec9c",
"index": 7657,
"step-1": "#!/usr/bin/python\n\nimport sys\n\ndef get_params(fname):\n\td = dict()\n\twith open(fname) as f:\n\t\tfor line in f:\n\t\t\tl = line.strip()\n\t\t\tif (line[0] == '#'):\n\t\t\t\tcontinue\n\t\t\tparam = line.split('=')\n\t\t\tv = '... | [
0
] |
<|reserved_special_token_0|>
class Client_OrderInline(admin.TabularInline):
<|reserved_special_token_0|>
class MyAdminSite(AdminSite):
site_header = 'Pizza-Day'
index_template = 'admin/index.html'
@admin.register(Product)
class ProductAdmin(admin.ModelAdmin):
class PriceListFilter(admin.SimpleLi... | flexible | {
"blob_id": "d301ffa790d6444519e354a2b6f8d65f67d380c0",
"index": 1739,
"step-1": "<mask token>\n\n\nclass Client_OrderInline(admin.TabularInline):\n <mask token>\n\n\nclass MyAdminSite(AdminSite):\n site_header = 'Pizza-Day'\n index_template = 'admin/index.html'\n\n\n@admin.register(Product)\nclass Prod... | [
16,
17,
18,
24,
25
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for word in stdin:
lst_in = word
match = re.finditer('(\\w)\\1+', lst_in)
for item in match:
lst_in = lst_in.replace(item[0], item[0][0])
print(lst_in, end='')
<|reserved_special_token_1|>
<|reserved_spe... | flexible | {
"blob_id": "5b7c04f23fb674191639e95dff8c530933379d67",
"index": 3686,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor word in stdin:\n lst_in = word\n match = re.finditer('(\\\\w)\\\\1+', lst_in)\n for item in match:\n lst_in = lst_in.replace(item[0], item[0][0])\n print(lst_in, en... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def pad_sequences_1d(sequences, dtype=torch.long, device=torch.device('cpu'
), fixed_length=None):
""" Pad a single-nested list or a sequence of n-d array (torch.tensor or np.ndarray)
into a (n+1)-d array, only allow the first dim has variable lengths.
Args:
sequen... | flexible | {
"blob_id": "788d9fa03c4311a8077d492b1a2b06d1f88826a3",
"index": 5570,
"step-1": "<mask token>\n\n\ndef pad_sequences_1d(sequences, dtype=torch.long, device=torch.device('cpu'\n ), fixed_length=None):\n \"\"\" Pad a single-nested list or a sequence of n-d array (torch.tensor or np.ndarray)\n into a (n+1... | [
3,
4,
5,
6,
7
] |
from command import Command, is_command, CommandException
from event import Event
class ItemInfo(Command):
@is_command
def item_info(self, player, *args):
if len(args) == 0:
raise CommandException(CommandException.NOT_ENOUGH_ARGUMENTS)
item_id = args[0]
if item_id in playe... | normal | {
"blob_id": "6b2bd6954f188626fa857ffc37611d3f971d22e2",
"index": 5259,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass ItemInfo(Command):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass ItemInfo(Command):\n\n @is_command\n def item_info(self, player, *args):\n if len(args... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 17 13:07:47 2020
@author: mmm
"""
n = 2
n1 = 10
for i in range(n,n1):
if n > 1:
for j in range(2,i):
if (i % j!= 0):
else:
print(i)
| normal | {
"blob_id": "1855351b20c7965a29864502e4489ab4324c7859",
"index": 4808,
"step-1": "# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Dec 17 13:07:47 2020\r\n\r\n@author: mmm\r\n\"\"\"\r\n\r\n\r\nn = 2\r\nn1 = 10\r\nfor i in range(n,n1):\r\n if n > 1:\r\n for j in range(2,i):\r\n if (i % j!=... | [
0
] |
from keras.models import Sequential
from keras.layers import Convolution2D # for 2d images
from keras.layers import MaxPool2D
from keras.layers import Flatten
from keras.layers import Dense
import tensorflow as tf
from keras_preprocessing.image import ImageDataGenerator
cnn = Sequential()
rgb = 64
# step 1: convolu... | normal | {
"blob_id": "9fa5f4b4aeb7fe42d313a0ec4e57ce15acbfcf46",
"index": 3960,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ncnn.add(Convolution2D(32, 3, 3, input_shape=(rgb, rgb, 3), activation='relu'))\ncnn.add(MaxPool2D(pool_size=(2, 2)))\ncnn.add(Flatten())\ncnn.add(Dense(output_dim=128, activation='relu'))... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def main():
if IS_TRAINING:
training_imgs_paths = list_images(TRAINING_IMGS_PATH)
train(training_imgs_paths, ENCODER_WEIGHTS_PATH, MODEL_SAVE_PATH,
autoencoder_levels=AUTUENCODER_LEVELS_TRAIN, debug=DEBUG,
logging_period=LOGGING_PERIOD)
... | flexible | {
"blob_id": "31ed798118f20005b5a26bc1fc0053b7d0a95657",
"index": 5366,
"step-1": "<mask token>\n\n\ndef main():\n if IS_TRAINING:\n training_imgs_paths = list_images(TRAINING_IMGS_PATH)\n train(training_imgs_paths, ENCODER_WEIGHTS_PATH, MODEL_SAVE_PATH,\n autoencoder_levels=AUTUENCODE... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def my_loss():
return nn.CrossEntropyLoss()
<|reserved_special_token_1|>
import torch.nn as nn
def my_loss():
return nn.CrossEntropyLoss()
| flexible | {
"blob_id": "418f2e1cbe4fb3ef369e981e72bf40eeddfd052e",
"index": 2408,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef my_loss():\n return nn.CrossEntropyLoss()\n",
"step-3": "import torch.nn as nn\n\n\ndef my_loss():\n return nn.CrossEntropyLoss()\n",
"step-4": null,
"step-5": null,
... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def main(args):
np.random.seed(args.random_seed)
tf.random.set_seed(args.random_seed)
unet_model = UnetModel(args)
unet_model.prepare_data(args)
unet_model.create_model(args)
unet_model.train(args)
un... | flexible | {
"blob_id": "588f6f78908e47e0b3f1bc42fffabad34766eede",
"index": 9815,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef main(args):\n np.random.seed(args.random_seed)\n tf.random.set_seed(args.random_seed)\n unet_model = UnetModel(args)\n unet_model.prepare_data(args)\n unet_model.cr... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_astype_invalid_nas_to_tdt64_raises():
idx = Index([NaT.asm8] * 2, dtype=object)
msg = 'Cannot cast Index to dtype timedelta64\\[ns\\]'
with pytest.raises(TypeError, match=msg):
idx.astype('m8[ns]')
... | flexible | {
"blob_id": "13b2fea09f5a4300563dd8870fe1841b47756b36",
"index": 9972,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_astype_invalid_nas_to_tdt64_raises():\n idx = Index([NaT.asm8] * 2, dtype=object)\n msg = 'Cannot cast Index to dtype timedelta64\\\\[ns\\\\]'\n with pytest.raises(T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Database(object):
def __init__(self):
self.client = MongoClient(config['db']['url'])
self.db = self.client[config['db']['name']]
<|reserved_special_token_0|>
def find(self, criteria, collection_name, projection=None, sort=None,
limit=0, cursor=F... | flexible | {
"blob_id": "bcc76e4dbcc191e7912085cbb92c5b0ebd2b047b",
"index": 6550,
"step-1": "<mask token>\n\n\nclass Database(object):\n\n def __init__(self):\n self.client = MongoClient(config['db']['url'])\n self.db = self.client[config['db']['name']]\n <mask token>\n\n def find(self, criteria, col... | [
4,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
@fixture
def authenticated_author_client(user, client: Client) ->Client:
token = Token.objects.get_or_create(user=user)[0].key
client.defaults['HTTP_AUTHORIZATION'] = f'Token {token}'
print(client)
return client
<|reserved_special_token_0|>
<|reserved_special_token_1|>... | flexible | {
"blob_id": "347d468f15dee8a8219d201251cedffe21352f7c",
"index": 8813,
"step-1": "<mask token>\n\n\n@fixture\ndef authenticated_author_client(user, client: Client) ->Client:\n token = Token.objects.get_or_create(user=user)[0].key\n client.defaults['HTTP_AUTHORIZATION'] = f'Token {token}'\n print(client)... | [
1,
2,
3,
4,
5
] |
class Solution:
def asteroidCollision(self, asteroids: List[int]) ->List[int]:
output = []
index = 0
for i in asteroids:
if len(output) == 0:
index = 0
if index == 0:
output.append(i)
index += 1
continue... | normal | {
"blob_id": "fef4749ce7b8668a5a138aa1245010866a85c853",
"index": 2485,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def asteroidCollision(self, asteroids: List[int]) ->List[int]:\n output = []\n index = 0\n for i in astero... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class s3Obj:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class s3Obj:
<|reserved_special_token_0|>
def getACL(self, client_s3):
"""
get ACL info and update the object
"""
... | flexible | {
"blob_id": "b3f376f4aec81cae853f996a74062e32bb4a8fa3",
"index": 2569,
"step-1": "<mask token>\n\n\nclass s3Obj:\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass s3Obj:\n <mask token>\n\n def getACL(self, client_s3):\n \"\"\"\n get ACL info and update the object\n ... | [
1,
2,
3,
4,
5
] |
import socket
# Packet Sniffing
# It's All Binary
# Usage: python basic_sniffer.py
# create the sniffer raw socket object
sniffer = socket.socket(socket.AF_INET,socket.SOCK_RAW, socket.IPPROTO_ICMP)
#bind it to localhost
sniffer.bind(('0.0.0.0',0))
# make sure that the IP header is included
sniffer.setsockopt(soc... | normal | {
"blob_id": "9f2a8e78aa2e3eab8f74847443dec9083603da39",
"index": 3643,
"step-1": "import socket\n\n# Packet Sniffing\n# It's All Binary\n\n# Usage: python basic_sniffer.py \n\n# create the sniffer raw socket object\nsniffer = socket.socket(socket.AF_INET,socket.SOCK_RAW, socket.IPPROTO_ICMP)\n\n#bind it to local... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
try:
print(dic[55])
except Exception as err:
print('Mensagem: ', err)
<|reserved_special_token_1|>
dic = {}
try:
print(dic[55])
except Exception as err:
print('Mensagem: ', err)
| flexible | {
"blob_id": "618aa64c08ebf8d9a0bc9662195ece2bbd485c17",
"index": 1079,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntry:\n print(dic[55])\nexcept Exception as err:\n print('Mensagem: ', err)\n",
"step-3": "dic = {}\ntry:\n print(dic[55])\nexcept Exception as err:\n print('Mensagem: ', err... | [
0,
1,
2
] |
# -------------------------------
# --------- Set Methods ---------
# -------------------------------
# difference() return the values in the first set that not in the second set
set1 ={1, 2, 3, 4, 5, 6, 7, 8 , 9}
set2 = {1, 2, 3, 4, 5, 6, "A", "B"}
print(set1)
print(set2)
print(set1.difference(set2))
print(set1-set2... | normal | {
"blob_id": "faf2f5da92cf45cfedda91955688b3ca1c7c0db9",
"index": 8280,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(set1)\nprint(set2)\nprint(set1.difference(set2))\nprint(set1 - set2)\nprint(set2.difference(set1))\nprint(set2 - set1)\nprint(set1)\nprint(set2)\nprint('*' * 40)\n<mask token>\nprin... | [
0,
1,
2,
3
] |
#!/usr/bin/python
# -*- coding: utf-8 -*-
# http://stackoverflow.com/questions/5276967/python-in-xcode-4
"""tv_write_xyzt2matlab.py: TremVibe Write Accelerometer XYZ and Timestamp to .m file"""
__author__ = "Salvador Aguinaga"
import sys
import MySQLdb
import math
from itertools import groupby
import csv
##########... | normal | {
"blob_id": "4f21fb4168ed29b9540d3ca2b8cf6ef746c30831",
"index": 6732,
"step-1": "#!/usr/bin/python\n# -*- coding: utf-8 -*-\n# http://stackoverflow.com/questions/5276967/python-in-xcode-4\n\n\"\"\"tv_write_xyzt2matlab.py: TremVibe Write Accelerometer XYZ and Timestamp to .m file\"\"\"\n__author__ = \"Salvador ... | [
0
] |
#!/usr/bin/python
import sys
BLACK = '\033[30;0m'
RED = '\033[31;0m'
GREEN = '\033[32;0m'
YELLOW = '\033[33;0m'
BLUE = '\033[34;0m'
PINK = '\033[35;0m'
CBLUE = '\033[36;0m'
WHITE = '\033[37;0m'
def colorPrint(color, str):
print(color + str + '\033[0m');
def main():
if sys.argv.__len__() < ... | normal | {
"blob_id": "a49c00dab8d445ce0b08fd31a4a41d6c8976d662",
"index": 2263,
"step-1": "<mask token>\n\n\ndef colorPrint(color, str):\n print(color + str + '\\x1b[0m')\n\n\ndef main():\n if sys.argv.__len__() < 2:\n print('Wrong usage, exit')\n return\n colorPrint(YELLOW, sys.argv[1])\n\n\n<mask... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestMian:
def test_mian(self):
MainPage().goto_marketpage().goto_search().search()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TestMian:
def test_mi... | flexible | {
"blob_id": "e1751cc6f76f56e62cd02d61db65f1c27a4ff1b9",
"index": 7351,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TestMian:\n\n def test_mian(self):\n MainPage().goto_marketpage().goto_search().search()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass TestMian:\n\n de... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
@Gtk.Template(resource_path=
'/com/github/bilelmoussaoui/Authenticator/settings.ui')
class SettingsWindow(Handy.PreferencesWindow):
<|reserved_special_token_0|>
dark_theme_switch: Gtk.Switch = Gtk.Template.Child()
night_light_switch: Gtk.Switch = Gtk.Template.Child()
l... | flexible | {
"blob_id": "a7d8efe3231b3e3b9bfc5ef64a936816e8b67d6c",
"index": 3127,
"step-1": "<mask token>\n\n\n@Gtk.Template(resource_path=\n '/com/github/bilelmoussaoui/Authenticator/settings.ui')\nclass SettingsWindow(Handy.PreferencesWindow):\n <mask token>\n dark_theme_switch: Gtk.Switch = Gtk.Template.Child()... | [
10,
11,
13,
19,
21
] |
<|reserved_special_token_0|>
def read_vivado_report(hls_dir, full_report=False):
if not os.path.exists(hls_dir):
print('Path {} does not exist. Exiting.'.format(hls_dir))
return
prj_dir = None
top_func_name = None
if os.path.isfile(hls_dir + '/build_prj.tcl'):
prj_dir, top_func... | flexible | {
"blob_id": "7d173b0571c20dc8fcae884451e8f69ba3a05763",
"index": 8087,
"step-1": "<mask token>\n\n\ndef read_vivado_report(hls_dir, full_report=False):\n if not os.path.exists(hls_dir):\n print('Path {} does not exist. Exiting.'.format(hls_dir))\n return\n prj_dir = None\n top_func_name = ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
def restart():
root.destroy()
os.startfile('data\\programs\\game with tkinter.py')
def disableButton():
global l, restartButton, start
b1.config(state='disabled')
b2.config(state='disabled')
b3.config(state='disabled')
b4.config(state='disabled')
b5.confi... | flexible | {
"blob_id": "e70c5c9a62faa4c501c0f103ce0a0a419aaf4301",
"index": 2096,
"step-1": "<mask token>\n\n\ndef restart():\n root.destroy()\n os.startfile('data\\\\programs\\\\game with tkinter.py')\n\n\ndef disableButton():\n global l, restartButton, start\n b1.config(state='disabled')\n b2.config(state=... | [
11,
12,
14,
15,
18
] |
<|reserved_special_token_0|>
class _RestrictData:
__slots__ = ()
<|reserved_special_token_0|>
class RestrictBlend:
__slots__ = 'context', 'data'
def __enter__(self):
self.data = _bpy.data
self.context = _bpy.context
_bpy.data = _data_restrict
_bpy.context = _context_re... | flexible | {
"blob_id": "aa4226c377368d1ece4e556db9b7fdd0134472c9",
"index": 5450,
"step-1": "<mask token>\n\n\nclass _RestrictData:\n __slots__ = ()\n\n\n<mask token>\n\n\nclass RestrictBlend:\n __slots__ = 'context', 'data'\n\n def __enter__(self):\n self.data = _bpy.data\n self.context = _bpy.conte... | [
6,
9,
10,
11,
13
] |
# coding: utf-8
import logging
import uuid
import json
import xmltodict
import bottle
from bottle import HTTPError
from bottle.ext import sqlalchemy
from database import Base, engine
from database import JdWaybillSendResp, JdWaybillApplyResp
jd = bottle.Bottle(catchall=False)
plugin = sqlalchemy.Plugin(
engine, ... | normal | {
"blob_id": "a93884757069393b4d96de5ec9c7d815d58a2ea5",
"index": 935,
"step-1": "<mask token>\n\n\n@jd.get('/routerjson')\ndef apply_jd_waybill(db):\n query = bottle.request.query\n if query['method'] == 'jingdong.etms.waybillcode.get':\n jd_code, resp = jd_get_response_normal()\n logging.deb... | [
4,
5,
6,
7,
8
] |
from firstfuncs_1618 import *
figdir='/home/isabela/Documents/projects/OSNAP/figures_OSNAPwide/Freshwater/Linear/'
figdir_paper='/home/isabela/Documents/projects/OSNAP/figures_OSNAPwide/Freshwater/paperfigs'
########################################################################################################
#####... | normal | {
"blob_id": "40b94a3be27ebb0d8e3e67fddabe1dc68646169c",
"index": 9881,
"step-1": "<mask token>\n\n\ndef get_U_S_T_from_WM(WM):\n U = {}\n S = {}\n T = {}\n for wm in WM.WM:\n U[str(wm.values)] = float(WM['TRANS'].sel(WM=wm).groupby(\n 'TIME.month').mean('TIME').mean(dim='month').val... | [
10,
11,
13,
14,
16
] |
import ply.lex as lex
print("hello word!")
| normal | {
"blob_id": "84d0c439fcee4339250ced11dd2264740cc20d9c",
"index": 9567,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('hello word!')\n",
"step-3": "import ply.lex as lex\nprint('hello word!')\n",
"step-4": "import ply.lex as lex\n\nprint(\"hello word!\")\n",
"step-5": null,
"step-ids": [
... | [
0,
1,
2,
3
] |
#
# Copyright John Reid 2009
#
"""
Code to handle bootstrap analyses.
"""
from itertools import cycle
import random
import bisect
def generate_bootstrap_samples(num_samples, test_universe, test_set_sizes):
"""
Yield samples that match the sizes given in test_set_sizes
"""
for sample_idx, sample_siz... | normal | {
"blob_id": "752affdfa1481b9a19a9b7dfe76f9d5d11c80073",
"index": 4678,
"step-1": "<mask token>\n\n\ndef bootstrap_p_value(bootstrap_stats, stat_value):\n \"\"\"\n Calculate the p-value for the statistic's value given the bootstrap values.\n \"\"\"\n return 1.0 - bisect.bisect_left(bootstrap_stats, st... | [
1,
2,
3,
4,
5
] |
from point import Point
from velocity import Velocity
import arcade
import config
PADDLE_WIDTH = 15
PADDLE_HEIGHT = 30
class Paddle:
def __init__(self):
self.center = Point(390, 50)
self.velocity = Velocity(0, 5)
def draw(self):
self.drawing = arcade.draw_rectangle_filled(self.center... | normal | {
"blob_id": "cb3c1adb9d91aecee5b21774d61dfe9400a330fa",
"index": 619,
"step-1": "<mask token>\n\n\nclass Paddle:\n\n def __init__(self):\n self.center = Point(390, 50)\n self.velocity = Velocity(0, 5)\n <mask token>\n\n def move_up(self):\n if self.center.y < config.SCREEN_HEIGHT - ... | [
4,
5,
6,
7,
8
] |
# Generated by Django 3.0.1 on 2020-03-20 09:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('page', '0004_auto_20200320_1521'),
]
operations = [
migrations.AddField(
model_name='menu',
name='level',
... | normal | {
"blob_id": "807b20f4912ab89bf73966961536a4cd4367f851",
"index": 6468,
"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 = [('page', '000... | [
0,
1,
2,
3,
4
] |
# Generated by Django 2.0.4 on 2018-04-30 14:01
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('base... | normal | {
"blob_id": "d13589979ba7b6facd8339111323270c9920a9bf",
"index": 8127,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n initial = T... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def rename(dir, pattern, titlePattern):
for pathAndFilename in glob.iglob(os.path.join(dir, pattern)):
title, ext = os.path.splitext(os.path.basename(pathAndFilename))
hexa = title[:2]
hexb = title[2:4]
title = title[4:] + '_' + str(int(hexa, 16)) + '_'... | flexible | {
"blob_id": "22aa6042b77c3cfd1f102a0ea22a43223e366d2f",
"index": 1476,
"step-1": "<mask token>\n\n\ndef rename(dir, pattern, titlePattern):\n for pathAndFilename in glob.iglob(os.path.join(dir, pattern)):\n title, ext = os.path.splitext(os.path.basename(pathAndFilename))\n hexa = title[:2]\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class section:
def __init__(self, i0, j0, subImg, Params):
self.Params = Params
self.subParams = {}
self.subParams['wLen'] = [6.3e-07, 5.3e-07, 4.3e-07]
self.subParams['subSize'] = subImg.shape
self.subParams['bigSize'] = [np.int(Params['size']... | flexible | {
"blob_id": "e3c9487f3221ca89b9014b2e6470ca9d4dbc925a",
"index": 2239,
"step-1": "<mask token>\n\n\nclass section:\n\n def __init__(self, i0, j0, subImg, Params):\n self.Params = Params\n self.subParams = {}\n self.subParams['wLen'] = [6.3e-07, 5.3e-07, 4.3e-07]\n self.subParams['s... | [
9,
11,
13,
15,
19
] |
from locals import *
from random import choice, randint
import pygame
from gameobjects.vector2 import Vector2
from entity.block import Block
def loadImage(filename):
return pygame.image.load(filename).convert_alpha()
class MapGrid(object):
def __init__(self, world):
self.grid = []
self.ima... | normal | {
"blob_id": "2b8f4e0c86adfbf0d4ae57f32fa244eb088f2cee",
"index": 4773,
"step-1": "\nfrom locals import *\nfrom random import choice, randint\n\nimport pygame\n\nfrom gameobjects.vector2 import Vector2\n\nfrom entity.block import Block\n\ndef loadImage(filename):\n return pygame.image.load(filename).convert_al... | [
0
] |
from PIL import Image
from random import randrange
class PileMosaic:
def __init__(self):
self.width, self.height = 2380, 2800
self.filename = "pile_mosaic.png"
self.crema = (240, 233, 227)
self.choco = (89, 62, 53)
self.luna = (43, 97, 123)
self.latte = (195, 175, 14... | normal | {
"blob_id": "a484272ace089008e27f4e00d2e641118432665e",
"index": 4592,
"step-1": "<mask token>\n\n\nclass PileMosaic:\n\n def __init__(self):\n self.width, self.height = 2380, 2800\n self.filename = 'pile_mosaic.png'\n self.crema = 240, 233, 227\n self.choco = 89, 62, 53\n s... | [
7,
8,
12,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(my_randoms)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
my_randoms = random.sample(100, 10)
print(my_randoms)
<|reserved_special_token_1|>
import random
my_randoms = random.sample(100, 10)
print(my_random... | flexible | {
"blob_id": "d39f6fca80f32a4d13764eb5cfb29999785b1d16",
"index": 1629,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(my_randoms)\n",
"step-3": "<mask token>\nmy_randoms = random.sample(100, 10)\nprint(my_randoms)\n",
"step-4": "import random\nmy_randoms = random.sample(100, 10)\nprint(my_rando... | [
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": "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
] |
from flask import Blueprint, render_template
from bashtube import cache
singlevideos = Blueprint('singlevideos', __name__, template_folder='templates')
@singlevideos.route('/')
def index():
return render_template('singlevideos/single.html')
| normal | {
"blob_id": "ee10bca1126b20378c4e9cea4d2dc7ed6a2044ab",
"index": 9187,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@singlevideos.route('/')\ndef index():\n return render_template('singlevideos/single.html')\n",
"step-3": "<mask token>\nsinglevideos = Blueprint('singlevideos', __name__, templa... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def plot_table(timestamps: dict, threadList: list, mList: list) ->None:
"""Plot standard deviation chart
Args:
k (list): Threads/Process used
deviation (list): Standard deviation of the timestamps
... | flexible | {
"blob_id": "8804bfc5bed8b93e50279f0cbab561fe09d92a64",
"index": 6522,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef plot_table(timestamps: dict, threadList: list, mList: list) ->None:\n \"\"\"Plot standard deviation chart\n\n Args:\n k (list): Threads/Process used\n deviatio... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('twitter', '0002_tweet'),
]
operations = [
migrations.CreateModel(
name='TwitterKeys',
fields=[
... | normal | {
"blob_id": "c8406db010a506b782030c5d3f84c319851e89d6",
"index": 3662,
"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 = [('twitter', '... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
"""
复习
面向对象：考虑问题从对象的角度出发.
抽象：从多个事物中，舍弃个别的/非本质的特征(不重要)，
抽出共性的本质(重要的)过程。
三大特征：
封装：将每个变化点单独分解到不同的类中。
例如：老张开车去东北
做法：定义人类，定义车类。
继承：重用现有类的功能和概念，并在此基础上进行扩展。
... | flexible | {
"blob_id": "2749a262bf8da99aa340e878c15a6dba01acc38c",
"index": 7025,
"step-1": "<mask token>\n",
"step-2": "\"\"\"\n 复习\n 面向对象：考虑问题从对象的角度出发.\n 抽象：从多个事物中，舍弃个别的/非本质的特征(不重要)，\n 抽出共性的本质(重要的)过程。\n 三大特征：\n 封装：将每个变化点单独分解到不同的类中。\n 例如：老张开车去东北\n ... | [
0,
1
] |
import re
import os
import pandas as pd
instruments_file = os.path.abspath("instruments.csv")
input_names_file = os.path.abspath("names.txt")
output_names_file = os.path.abspath("names.csv")
inst_name_file = os.path.abspath("name_instrument.csv")
reg_ex = '; |, |\\*|\n'
name_header = ["first_name", "last_name"]
def ... | normal | {
"blob_id": "8c539dbbb762717393b9a71ddca8eb3872890854",
"index": 288,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef process_names():\n \"\"\"\n Opening, reading name file and building name array.\n \"\"\"\n with open(input_names_file, 'r') as data:\n plaintext = data.read()\n ... | [
0,
1,
2,
3,
4
] |
"""
This is the main script
"""
import datetime
import sqlite3
from sqlite3 import Error
import nltk.sentiment
from chatterbot import ChatBot
from pythonosc import udp_client
def _create_connection(db_file):
""" Create a database connection to the SQLite database """
try:
conn = sqlite3.connect(db_fi... | normal | {
"blob_id": "2b8b5b893d61d11d2795f5be96fde759256a15e8",
"index": 9741,
"step-1": "<mask token>\n\n\ndef _create_connection(db_file):\n \"\"\" Create a database connection to the SQLite database \"\"\"\n try:\n conn = sqlite3.connect(db_file)\n cur = conn.cursor()\n cur.execute('CREATE ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
class GraphNN(nn.Module):
def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):
super(GraphNN, self).__init__()
self.ligand_dim = dim_in
self.dim_h = dim_h
self.dim_act = dim_act
self.model_name = 'DockRLGraphNN'
self.bond_cuto... | flexible | {
"blob_id": "1c1673b5e54bafef9f36a2583115f8135c112ab4",
"index": 1922,
"step-1": "<mask token>\n\n\nclass GraphNN(nn.Module):\n\n def __init__(self, dim_in=7, dim_act=6, dim_h=8, dropout=0.0):\n super(GraphNN, self).__init__()\n self.ligand_dim = dim_in\n self.dim_h = dim_h\n self.... | [
26,
31,
34,
35,
39
] |
#17219
tot, inp = map(int, input().split())
ID_dict = {}
for _ in range(tot):
id, pw = map(str, input().split())
ID_dict[id] = pw
for _ in range(inp):
print(ID_dict[input()]) | normal | {
"blob_id": "cf7556034020d88ddb6b71b9f908c905e2f03cdb",
"index": 4076,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(tot):\n id, pw = map(str, input().split())\n ID_dict[id] = pw\nfor _ in range(inp):\n print(ID_dict[input()])\n",
"step-3": "tot, inp = map(int, input().split())... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class CollectdCollector(Collector):
"""
Handle dispatching statistics to collectd.
"""
NAME = 'vCenter'
def __init__(self, *args, **kwargs):
super(CollectdCollector, self).__init__(*args, **kwargs)
self.sleep_time = kwargs.get('sleep_time', 20)
d... | flexible | {
"blob_id": "55f76ae1ffe0fb2d2ca2c7a20aab45ffb00cf178",
"index": 613,
"step-1": "<mask token>\n\n\nclass CollectdCollector(Collector):\n \"\"\"\n Handle dispatching statistics to collectd.\n\n \"\"\"\n NAME = 'vCenter'\n\n def __init__(self, *args, **kwargs):\n super(CollectdCollector, self... | [
11,
13,
19,
20,
24
] |
#!/usr/bin/env python
# -------------------------------------------------------------------------
# Copyright (c) Microsoft, Intel Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------... | normal | {
"blob_id": "a61132d2d504ed31d4e1e7889bde670853968559",
"index": 5739,
"step-1": "<mask token>\n\n\nclass CalibraterBase:\n\n def __init__(self, model_path: Union[str, Path], op_types_to_calibrate:\n Optional[Sequence[str]]=None, augmented_model_path=\n 'augmented_model.onnx', symmetric=False, u... | [
46,
56,
59,
60,
68
] |
import unittest
import numpy
import set_solver
class TestSets(unittest.TestCase):
def test_is_set(self):
"""Test set validator (Exercise 3a)."""
cards = numpy.array([[1, 1, 1, 2, 0], [0, 1, 2, 2, 2], [0, 1, 2, 2,
2], [0, 1, 2, 2, 2]])
self.assertTrue(set_solver.is_set(cards, [... | normal | {
"blob_id": "6065fae2a11f6b525ef10346e297505ec9d4e9d5",
"index": 8550,
"step-1": "<mask token>\n\n\nclass TestSets(unittest.TestCase):\n\n def test_is_set(self):\n \"\"\"Test set validator (Exercise 3a).\"\"\"\n cards = numpy.array([[1, 1, 1, 2, 0], [0, 1, 2, 2, 2], [0, 1, 2, 2,\n 2],... | [
2,
3,
4,
5
] |
from typing import Any, Dict
from django.http import HttpRequest, HttpResponse
from zerver.decorator import REQ, has_request_variables, webhook_view
from zerver.lib.response import json_success
from zerver.lib.webhooks.common import check_send_webhook_message, get_setup_webhook_message
from zerver.models import UserP... | normal | {
"blob_id": "f60d02fb14364fb631d87fcf535b2cb5782e728f",
"index": 6539,
"step-1": "<mask token>\n\n\n@webhook_view('Freshping')\n@has_request_variables\ndef api_freshping_webhook(request: HttpRequest, user_profile: UserProfile,\n payload: Dict[str, Any]=REQ(argument_type='body')) ->HttpResponse:\n body = ge... | [
1,
3,
4,
5,
6
] |
print("gist test file4") | normal | {
"blob_id": "ec4725b5b60d10e86b29aab3723917ace5cf52f6",
"index": 8452,
"step-1": "<mask token>\n",
"step-2": "print('gist test file4')\n",
"step-3": "print(\"gist test file4\")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
<|reserved_special_token_0|>
class AbstractLayer(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@classmethod
d... | flexible | {
"blob_id": "5a33aeffa740a41bd0bd1d80f45796ae37377a4c",
"index": 757,
"step-1": "<mask token>\n\n\nclass AbstractLayer(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @classmethod\n def filter(cls, *args, **kwa... | [
12,
17,
18,
19,
22
] |
seq = input('write a sequence of numbers: ')
print(seq.split(','))
print(tuple(seq.split(',')))
| normal | {
"blob_id": "be867d600f5f267986368f5573006f63004dbf9e",
"index": 5094,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(seq.split(','))\nprint(tuple(seq.split(',')))\n",
"step-3": "seq = input('write a sequence of numbers: ')\nprint(seq.split(','))\nprint(tuple(seq.split(',')))\n",
"step-4": null... | [
0,
1,
2
] |
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