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|>
__title__ = 'space_tracer'
__version__ = '4.10.2'
__author__ = 'Don Kirkby'
__author_email__ = 'donkirkby@gmail.com'
__description__ = 'Trade time for space when debugging your code.'
__url__ = 'https://donkirkby.github.io/live-py... | flexible | {
"blob_id": "6cb29ebd9c0f2660d0eb868bec87ffd97cf4d198",
"index": 6262,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n__title__ = 'space_tracer'\n__version__ = '4.10.2'\n__author__ = 'Don Kirkby'\n__author_email__ = 'donkirkby@gmail.com'\n__description__ = 'Trade time for space when debugging your code.'... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def load_data(train_source, train_dist, test_source, test_dist, max_len,
vocab_size):
"""
fin = open(test_source, "r")
data2 = fin.read()
fin.close()
fout = open(train_source, "a")
fout.write(data2)
fout.close()
fin = open(test_dist, "r")
data2 = f... | flexible | {
"blob_id": "2962ef1d7ecd4e8d472b9dc36664e4e8745391fd",
"index": 3616,
"step-1": "<mask token>\n\n\ndef load_data(train_source, train_dist, test_source, test_dist, max_len,\n vocab_size):\n \"\"\"\n fin = open(test_source, \"r\")\n data2 = fin.read()\n fin.close()\n fout = open(train_source, \"... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if CURRENT_PYTHON < REQUIRED_PYTHON:
sys.stderr.write(
"""==========================
Unsupported Python Version
==========================
This version of MDSANIMA requires Python {}.{}
but you're trying to install it ... | flexible | {
"blob_id": "2827a56c12c1e15a6fe26ce182aa07d76735d77f",
"index": 407,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif CURRENT_PYTHON < REQUIRED_PYTHON:\n sys.stderr.write(\n \"\"\"==========================\nUnsupported Python Version\n==========================\nThis version of MDSANIMA requ... | [
0,
1,
2,
3,
4
] |
from django.test import TestCase, Client
from pdf_crawler.models import Document
from rest_framework.reverse import reverse
class TestCase(TestCase):
client = Client()
def setUp(self):
Document.objects.create(name='First').save()
def test_endpoints(self):
"""
test for endpoints
... | normal | {
"blob_id": "0d28ab54f08301d9788ca9a5e46d522e043e9507",
"index": 4474,
"step-1": "<mask token>\n\n\nclass TestCase(TestCase):\n <mask token>\n\n def setUp(self):\n Document.objects.create(name='First').save()\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TestCase(TestCase):\n <mask t... | [
2,
3,
4,
5
] |
import sys
from collections import namedtuple
from PyQt5.QtWidgets import QApplication, QWidget, QMainWindow, \
QHBoxLayout, QStackedWidget, QListWidget, QListWidgetItem
from PyQt5.QtCore import Qt, QSize
from runWidget import RunWidget
from recordWidget import RecordWidget
def QListWidget_qss():
return ... | normal | {
"blob_id": "252a6b97f108b7fdc165ccb2a7f61ce31f129d3d",
"index": 8693,
"step-1": "<mask token>\n\n\nclass MainCentralWidget(QWidget):\n\n def __init__(self):\n super().__init__()\n tab_bar = self.getTabBar(('录制', '运行'))\n tab_page = self.getTabPage()\n tab_bar.currentRowChanged.con... | [
5,
6,
7,
9,
10
] |
#1.문자열에 홑따옴표 포함기키기 : 쌍따옴표
print("Python's Data Type")
#2.문자열에 쌍따옴표 포함시키기 : 홑따옴표
print('"Python is very easy" he said.')
#멀티라인(여러줄)표현하기
#1. 연속된 쌍따옴표 3개 사용하기
print("""No pain
No gain""")
#2. 연속된 쌍따옴표 3개 사용하기
print('''No pain
No gain''')
#3.이스케이프 코드 \n 삽입하기
print("No pain \n No gain")
"""
이스케이프(es... | normal | {
"blob_id": "eb81f1825c4ac8e20dde1daefbdad22f588e696e",
"index": 9431,
"step-1": "<mask token>\n",
"step-2": "print(\"Python's Data Type\")\nprint('\"Python is very easy\" he said.')\nprint(\"\"\"No pain\n No gain\"\"\")\nprint(\"\"\"No pain\n No gain\"\"\")\nprint(\"\"\"No pain \n No gain\"\... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def setup(bot):
bot.add_cog(EmbedPeek(bot))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
__red_end_user_data_statement__ = (
'This cog does not persistently store data or metadata about users.')
def set... | flexible | {
"blob_id": "b66142e0b674d3920b8e3ad74e0d0b753f0a78c3",
"index": 3471,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef setup(bot):\n bot.add_cog(EmbedPeek(bot))\n",
"step-3": "<mask token>\n__red_end_user_data_statement__ = (\n 'This cog does not persistently store data or metadata about u... | [
0,
1,
2,
3,
4
] |
# -*- coding: utf-8 -*-
from wordcloud import WordCloud, ImageColorGenerator
import numpy as np
from PIL import Image
def word2cloud(text: str, mask_image: Image=None):
if mask_image == None:
wc = WordCloud(font_path='simhei.ttf', width=800, height=600, mode='RGBA',
background_color=... | normal | {
"blob_id": "f9310aa6c26ec10041dac272fa17ac21f74c21ac",
"index": 9326,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef word2cloud(text: str, mask_image: Image=None):\n if mask_image == None:\n wc = WordCloud(font_path='simhei.ttf', width=800, height=600, mode=\n 'RGBA', backgr... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def configure_log(log_file, verbose=False):
filename = log_file
if log_file == 'STDOUT':
handler = logging.StreamHandler(sys.stdout)
elif log_file == 'STDERR':
handler = logging.StreamHandler(sys.stderr)
else:
handler = TimedRotatingFileHandler(file... | flexible | {
"blob_id": "3a96ede91069df0c71905415e598dbbd9d3056fd",
"index": 9730,
"step-1": "<mask token>\n\n\ndef configure_log(log_file, verbose=False):\n filename = log_file\n if log_file == 'STDOUT':\n handler = logging.StreamHandler(sys.stdout)\n elif log_file == 'STDERR':\n handler = logging.St... | [
7,
11,
12,
14,
16
] |
<|reserved_special_token_0|>
def init():
gpio.setmode(gpio.BCM)
gpio.setup(26, gpio.OUT)
gpio.setup(19, gpio.OUT)
gpio.setup(13, gpio.OUT)
gpio.setup(6, gpio.OUT)
def turn_left(tf):
gpio.output(26, False)
gpio.output(19, True)
gpio.output(13, False)
gpio.output(6, True)
sleep... | flexible | {
"blob_id": "a7cbd595b86908fb399bf11e1522588e0b0475c3",
"index": 9226,
"step-1": "<mask token>\n\n\ndef init():\n gpio.setmode(gpio.BCM)\n gpio.setup(26, gpio.OUT)\n gpio.setup(19, gpio.OUT)\n gpio.setup(13, gpio.OUT)\n gpio.setup(6, gpio.OUT)\n\n\ndef turn_left(tf):\n gpio.output(26, False)\n ... | [
4,
6,
7,
8,
10
] |
from phylo_utils.data import fixed_equal_nucleotide_frequencies
from phylo_utils.substitution_models.tn93 import TN93
class K80(TN93):
_name = 'K80'
_freqs = fixed_equal_nucleotide_frequencies.copy()
def __init__(self, kappa, scale_q=True):
super(K80, self).__init__(kappa, kappa, 1, self._freqs, ... | normal | {
"blob_id": "0f0595793e98187c6aaf5b1f4b59affb06bb598e",
"index": 3159,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass K80(TN93):\n <mask token>\n <mask token>\n\n def __init__(self, kappa, scale_q=True):\n super(K80, self).__init__(kappa, kappa, 1, self._freqs, scale_q=scale_q\n... | [
0,
2,
3,
4
] |
indelCost = 1
swapCost = 13
subCost = 12
noOp = 0
def alignStrings(x,y):
nx = len(x)
ny = len(y)
S = matrix(nx+1, ny+1) #??
for i in range (nx+1)
for j in range (ny+1)
if i == 0: #if the string is empty
S[i][j] = j #this will put all the letters from j in i
elif j == 0: #if the second string ... | normal | {
"blob_id": "65aa85675393efa1a0d8e5bab4b1dbf388018c58",
"index": 261,
"step-1": "\nindelCost = 1\nswapCost = 13\nsubCost = 12\nnoOp = 0\n\t\ndef alignStrings(x,y):\n\t\n\tnx = len(x)\n\tny = len(y)\n\tS = matrix(nx+1, ny+1) #?? \n\t\n\tfor i in range (nx+1)\n\t\tfor j in range (ny+1)\n\t\t\tif i == 0:\t#if the s... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_logs(ip_addr, pem_file, log_dir):
pem = paramiko.RSAKey.from_private_key_file(pem_file)
client = paramiko.SSHClient()
client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
client.connect(hostname=i... | flexible | {
"blob_id": "a1df804325a074ed980ec864c72fe231e2968997",
"index": 4024,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_logs(ip_addr, pem_file, log_dir):\n pem = paramiko.RSAKey.from_private_key_file(pem_file)\n client = paramiko.SSHClient()\n client.set_missing_host_key_policy(paramik... | [
0,
1,
2,
3,
4
] |
# Chris DeBoever
# cdeboeve@ucsd.edu
import sys, argparse, pdb, glob, os, re
import numpy as np
from bisect import bisect_left
from scipy.stats import binom
### helper functions ###
def find_lt(a,x):
"""
Find rightmost value less than x in list a
Input: list a and value x
Output: rightmost value les... | normal | {
"blob_id": "da751e96c225ebc2d30f3cce01ba2f64d0a29257",
"index": 3763,
"step-1": "<mask token>\n\n\ndef find_lt(a, x):\n \"\"\"\n Find rightmost value less than x in list a\n Input: list a and value x\n Output: rightmost value less than x in a\n \"\"\"\n i = bisect_left(a, x)\n if i:\n ... | [
7,
8,
9,
11,
12
] |
'''
fibonacci(6) => [1, 1, 2, 3, 5, 8]
fibonacci(7) => [1, 1, 2, 3, 5, 8, 13]
'''
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]
lista... | normal | {
"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
] |
def check_bit4(input):
mas=0b1000
desired=input & mas
if desired>0:
return "om"
else :
return "off"
| normal | {
"blob_id": "29dc940292a6805aabfa5bed22bb75d31140c83f",
"index": 3257,
"step-1": "<mask token>\n",
"step-2": "def check_bit4(input):\n mas = 8\n desired = input & mas\n if desired > 0:\n return 'om'\n else:\n return 'off'\n",
"step-3": "def check_bit4(input):\n\tmas=0b1000\n\tdesire... | [
0,
1,
2
] |
#define the simple_divide function here
def simple_divide(item, denom):
# start a try-except block
try:
return item/denom
except ZeroDivisionError:
return 0
def fancy_divide(list_of_numbers, index):
denom = list_of_numbers[index]
return [simple_divide(item, denom) for item in lis... | normal | {
"blob_id": "1fbdb0b40f0d65fffec482b63aa2192968b01d4b",
"index": 9766,
"step-1": "def simple_divide(item, denom):\n try:\n return item / denom\n except ZeroDivisionError:\n return 0\n\n\n<mask token>\n",
"step-2": "def simple_divide(item, denom):\n try:\n return item / denom\n ... | [
1,
2,
3,
4,
5
] |
import openpyxl
class TestXLUtility:
def __init__(self, driver):
self.driver = driver
def getRowCount(file, sheetname):
workbook = openpyxl.load_workbook(file)
#sheet = workbook.get_sheet_by_name(sheetname)
sheet = workbook[sheetname]
return(sheet.max_row)
def get... | normal | {
"blob_id": "adae4f9ebcbbb775fc40278ceec9a0cc30c0a503",
"index": 1541,
"step-1": "<mask token>\n\n\nclass TestXLUtility:\n <mask token>\n\n def getRowCount(file, sheetname):\n workbook = openpyxl.load_workbook(file)\n sheet = workbook[sheetname]\n return sheet.max_row\n <mask token>... | [
2,
4,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Classifier(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Classifier(object):
<|reserved_special_token_0|>
def __init__(self, classifier, scaler, orient, color_space,
pix... | flexible | {
"blob_id": "9188d58a6d9e832b8908b823d57249fcdd80ff51",
"index": 171,
"step-1": "<mask token>\n",
"step-2": "class Classifier(object):\n <mask token>\n <mask token>\n",
"step-3": "class Classifier(object):\n <mask token>\n\n def __init__(self, classifier, scaler, orient, color_space,\n pix... | [
0,
1,
2,
3
] |
# -*- coding: UTF-8 -*-
'''
model = DQN,DDQN,PDQN,PDDQN,DQN_PER,DDQN_PER,DQN_InAday,DQN_PER_Ipm...
'''
# -----------ContolGame------------
# CartPole - v1, MountainCar - v0, Acrobot - v1, Pendulum - v0
# from run_ContolGame import run_Game
# run_Game('DQN', 'CartPole-v1', episodes=400) # model,env,episodes
# --------... | normal | {
"blob_id": "f49a133fa94aae791ef0f1eec54cf0629f45a0ed",
"index": 5153,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nrun_Game('DQN_PER', 'Breakout', lifes=5, episodes=40001)\n",
"step-3": "<mask token>\nfrom run_AtariGame import run_Game\nrun_Game('DQN_PER', 'Breakout', lifes=5, episodes=40001)\n",
... | [
0,
1,
2,
3
] |
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
BATCH_START=0
TIME_STEPS=20
BATCH_SIZE=50
INPUT_SIZE=1
OUTPUT_SIZE=1
CELL_SIZE=10
LR=0.006
#generate data
def get_batch():
global BATCH_START,TIME_STEPS
xs=np.arange(BATCH_START,BATCH_START+TIME_STEPS*BATCH_SIZE).reshape((BATCH_SIZE,T... | normal | {
"blob_id": "e54078f21176bbb7accb4164e7b56633b13cc693",
"index": 8803,
"step-1": "<mask token>\n\n\nclass LSTMRNN(object):\n\n def __init__(self, n_steps, input_size, output_size, cell_size, batch_size\n ):\n self.n_steps = n_steps\n self.input_size = input_size\n self.output_size ... | [
8,
11,
12,
13,
14
] |
text=open('mytext.txt','w')
x=text.write("I like coding\nit is a new part\nof my life!!!")
text=open('mytext.txt')
read=text.readlines()
i=0
counter=0
total=0
print("number of lines :"+str(len(read)))
while i<=len(read)-1:
counter=counter+read[i].count('\n') + read[i].count(' ')
total+=len(read[i])-read[i].cou... | normal | {
"blob_id": "5ad8db85f4f705173cf5d0649af6039ebe1544b2",
"index": 7488,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('number of lines :' + str(len(read)))\nwhile i <= len(read) - 1:\n counter = counter + read[i].count('\\n') + read[i].count(' ')\n total += len(read[i]) - read[i].count('\\n')... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__version__ = '0.2.11'
<|reserved_special_token_0|>
<|reserved_special_token_1|>
__version__ = '0.2.11'
from climlab.utils import constants
from climlab.utils import thermo, legendre
from climlab.model.column import GreyRadiationModel, RadiativeConvectiveM... | flexible | {
"blob_id": "8251a9c798b3cdc2f374d0a0406ccfaa11b7c5e3",
"index": 5699,
"step-1": "<mask token>\n",
"step-2": "__version__ = '0.2.11'\n<mask token>\n",
"step-3": "__version__ = '0.2.11'\nfrom climlab.utils import constants\nfrom climlab.utils import thermo, legendre\nfrom climlab.model.column import GreyRadia... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Content-type: text/html\n')
<|reserved_special_token_0|>
if 'echooUser' in str(os.environ):
userName = EchooFunctions.getUserName()
userName = userName[0]
userID = EchooFunctions.getUserID(cursor, userName)
<|re... | flexible | {
"blob_id": "dc88686d3cbb4223b4de6847bf4fc29b93054b00",
"index": 495,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Content-type: text/html\\n')\n<mask token>\nif 'echooUser' in str(os.environ):\n userName = EchooFunctions.getUserName()\n userName = userName[0]\n userID = EchooFunctions.... | [
0,
1,
2,
3,
4
] |
"""
Stirng - Liste - Dosya
- Fonksiyon yazıyoruz.
- Bu fonksiyon iki parametre alacak. (dosya, string)
1. sorun : Dosyanın içinde string var ise True döndürecek yok ise False
2. sorun : Dosyanın içinde string bulunursa ilk bulunduğu konumu return edecek
3. sorun : Dosyanın içerisinde yazdığımız strinng kaç k... | normal | {
"blob_id": "0d3cc85cd18ee197b24c8b01b71afe82110bfad2",
"index": 3487,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef fonkString(text, string):\n if string in text:\n print('TRUE')\n print(text.index(string), '. sirada ilk', string, 'bulundu')\n print(text.count(string), '... | [
0,
1,
2,
3
] |
__version__ = "alph 1.0"
| normal | {
"blob_id": "2c4eb07a32c6903ae31006f42c13c55e6cc42eb5",
"index": 5245,
"step-1": "<mask token>\n",
"step-2": "__version__ = 'alph 1.0'\n",
"step-3": "__version__ = \"alph 1.0\"\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
} | [
0,
1,
2
] |
import numpy as np
import tensorflow as tf
class LocNet:
def __init__(self, scope, buttom_layer):
self.scope = scope
with tf.variable_scope(scope) as scope:
self.build_graph(buttom_layer)
self.gt_loc = tf.placeholder(dtype=tf.float32, shape=(None,4),name='gt_loc')
... | normal | {
"blob_id": "dd4dc1c4a0dc47711d1d0512ef3f6b7908735766",
"index": 3149,
"step-1": "<mask token>\n\n\nclass LocNet:\n\n def __init__(self, scope, buttom_layer):\n self.scope = scope\n with tf.variable_scope(scope) as scope:\n self.build_graph(buttom_layer)\n self.gt_loc = tf.... | [
2,
3,
4,
5,
6
] |
n=int(input())
k=[4,7,47,74,44,77,444,447,474,477,777,774,747,7444]
f=0
for i in k:
if(n%i==0):
f=1
print("YES")
break;
if(f==0):
print("NO")
| normal | {
"blob_id": "6161653fb789040d084e475e0ae25921e2e0676b",
"index": 2496,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in k:\n if n % i == 0:\n f = 1\n print('YES')\n break\nif f == 0:\n print('NO')\n",
"step-3": "n = int(input())\nk = [4, 7, 47, 74, 44, 77, 444, 447, 47... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class netdespatch_config(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_... | flexible | {
"blob_id": "407f549cf68660c8f8535ae0bed373e2f54af877",
"index": 5731,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass netdespatch_config(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>... | [
0,
1,
2,
3,
4
] |
#create a list
a = [2,3,4,5,6,7,8,9,10]
print(a)
#indexing
b = int(input('Enter indexing value:'))
print('The result is:',a[b])
print(a[8])
print(a[-1])
#slicing
print(a[0:3])
print(a[0:])
#conconteation
b=[20,30]
print(a+b)
#Repetition
print(b*3)
#updating
print(a[2])
a[2]=100
print(a)
#membership
print(5 in a)
... | normal | {
"blob_id": "f7d29dd1d990b3e07a7c07a559cf5658b6390e41",
"index": 4601,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(a)\n<mask token>\nprint('The result is:', a[b])\nprint(a[8])\nprint(a[-1])\nprint(a[0:3])\nprint(a[0:])\n<mask token>\nprint(a + b)\nprint(b * 3)\nprint(a[2])\n<mask token>\nprint(a... | [
0,
1,
2,
3
] |
import hashlib
md5 = hashlib.md5(b'Najmul')
print(md5.hexdigest())
sha1 = hashlib.sha1(b'Najmul')
print(sha1.hexdigest())
sha224 = hashlib.sha224(b'Najmul')
print(sha224.hexdigest())
sha256 = hashlib.sha256(b'Najmul')
print(sha256.hexdigest())
sha384 = hashlib.sha384(b'Najmul')
print(sha384.hexdigest())
sha512 = hashli... | normal | {
"blob_id": "ab4c668c8a167f8c387199b7aa49aa742d563250",
"index": 1698,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(md5.hexdigest())\n<mask token>\nprint(sha1.hexdigest())\n<mask token>\nprint(sha224.hexdigest())\n<mask token>\nprint(sha256.hexdigest())\n<mask token>\nprint(sha384.hexdigest())\n<... | [
0,
1,
2,
3
] |
from CTO import CTO
#from UI import UIManager
from Cidades import Cidades
from Database import Database
from datetime import datetime
class Main:
def __init__(self, cidade_filename="", dados_filename=""):
#cidade_filename, dados_filename = UIManager().get_filenames()
print("cidade: " + cidade_fil... | normal | {
"blob_id": "c5f46be6d7214614892d227c76c75e77433a8fa9",
"index": 9517,
"step-1": "<mask token>\n\n\nclass Main:\n <mask token>\n\n def processaCSV(self, filename):\n with open(filename, 'r', encoding='ISO-8859-1') as input_file:\n self.concessao = {}\n self.expansao = {}\n ... | [
4,
5,
6,
7,
8
] |
from typing import Dict, List
from .power_bi_querier import PowerBiQuerier
class DeathsByEthnicity(PowerBiQuerier):
def __init__(self) ->None:
self.source = 'd'
self.name = 'deaths by race'
self.property = 'race'
super().__init__()
def _parse_data(self, response_json: Dict[st... | normal | {
"blob_id": "d975b74370acc72101f808e70bef64cee39a5ab8",
"index": 6204,
"step-1": "<mask token>\n\n\nclass DeathsByEthnicity(PowerBiQuerier):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass DeathsByEthnicity(PowerBiQuerier):\n <mask token>\n\n def _parse_data(self, response_json... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class NavigationTransformerTrainer(TransformerTrainer):
def __init__(self, dataset_reader: NavigationDatasetReader, encoder:
TransformerEncoder, optimizer: torch.optim.Optimizer, scheduler:
Scheduler, num_epochs: int, num_blocks: int, device: torch.device,
che... | flexible | {
"blob_id": "04aacf9461ade2e229076ffdf85aca913037edad",
"index": 642,
"step-1": "<mask token>\n\n\nclass NavigationTransformerTrainer(TransformerTrainer):\n\n def __init__(self, dataset_reader: NavigationDatasetReader, encoder:\n TransformerEncoder, optimizer: torch.optim.Optimizer, scheduler:\n ... | [
10,
11,
12,
13,
15
] |
#Интегрирование точного решения кинетик затухания люминесценции символьным методом
#Из за сложности получаемых уравнений. Последующий подбор коэффициентов методом МНК
# и печать результата
#
import sympy as sym
def del_flu_sym(x ,t = 1 ,Ka = 1, Ktt = 0.5):
intens = x**2
return intens
x = sym.Symbol('x')
t ... | normal | {
"blob_id": "903a431ac39734338b4d464629b4b04a87dc9e8e",
"index": 1776,
"step-1": "<mask token>\n\n\ndef del_flu_sym(x, t=1, Ka=1, Ktt=0.5):\n intens = x ** 2\n return intens\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef del_flu_sym(x, t=1, Ka=1, Ktt=0.5):\n intens = x ** 2\n return intens\... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class Notifier(object):
<|reserved_special_token_0|>
def __init__(self):
pass
<|reserved_special_token_0|>
@abc.abstractmethod
def send(self, msg):
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Notifier(object):
<|reser... | flexible | {
"blob_id": "f25351a3cb7bf583152baa8e7ec47b0f2161cb9c",
"index": 761,
"step-1": "<mask token>\n\n\nclass Notifier(object):\n <mask token>\n\n def __init__(self):\n pass\n <mask token>\n\n @abc.abstractmethod\n def send(self, msg):\n pass\n",
"step-2": "<mask token>\n\n\nclass Notif... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
data.head()
<|reserved_special_token_0|>
sb.catplot(x='Age', y='Sex', hue='Survived', col='Embarked', notch=False,
palette='Set2', data=data, kind='box', height=4, aspect=0.7)
sb.catplot(x='Age', y='Sex', hue='Survived', col='... | flexible | {
"blob_id": "41006ff35299aa72b69c6dc1c71a45b44dca7d6c",
"index": 1184,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndata.head()\n<mask token>\nsb.catplot(x='Age', y='Sex', hue='Survived', col='Embarked', notch=False,\n palette='Set2', data=data, kind='box', height=4, aspect=0.7)\nsb.catplot(x='Age',... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def about(request):
teams = Team.objects.all()
return render(request, 'pages/about.html', {'teams': teams})
<|reserved_special_token_0|>
def contact(request):
if request.method == 'POST':
name = request.POST['name']
email = request.POST['email']
sub... | flexible | {
"blob_id": "eca40c37e0e437a5f4e5643f5fb7cd3e38605471",
"index": 2417,
"step-1": "<mask token>\n\n\ndef about(request):\n teams = Team.objects.all()\n return render(request, 'pages/about.html', {'teams': teams})\n\n\n<mask token>\n\n\ndef contact(request):\n if request.method == 'POST':\n name = ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for ln in fh:
if ln.startswith('From'):
if ln.startswith('From:'):
continue
else:
word = ln.split()
lst1.append(word[1])
for word in lst1:
data[word] = data.get(word, 0) ... | flexible | {
"blob_id": "4fba13d051a3aceb393a4473cdbf6d4fc684c7ac",
"index": 9473,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor ln in fh:\n if ln.startswith('From'):\n if ln.startswith('From:'):\n continue\n else:\n word = ln.split()\n lst1.append(word[1])\nfor... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_mysql_uri(user, password, host, database):
return f'mysql+pymysql://{user}:{password}@{host}/{database}'
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_os_env_value(key):
return os.getenv(key)
def get_mysql_uri(user,... | flexible | {
"blob_id": "8247b045a5aed4d0f3db6bc2c0edd985f2c4ba30",
"index": 5305,
"step-1": "<mask token>\n\n\ndef get_mysql_uri(user, password, host, database):\n return f'mysql+pymysql://{user}:{password}@{host}/{database}'\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_os_env_value(key):\n return os.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
metadata.create_all(engine)
if not os.path.exists(SQLALCHEMY_MIGRATE_REPO):
api.create(SQLALCHEMY_MIGRATE_REPO, 'database repository')
api.version_control(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_MIGRATE_REPO)
else:
api.ver... | flexible | {
"blob_id": "9bbf0953d228c970764b8ba94675346820bc5d90",
"index": 3006,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nmetadata.create_all(engine)\nif not os.path.exists(SQLALCHEMY_MIGRATE_REPO):\n api.create(SQLALCHEMY_MIGRATE_REPO, 'database repository')\n api.version_control(SQLALCHEMY_DATABASE_U... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get_browser_driver():
"""获取浏览器服务 使用后记得 driver.quit() 否则容易引起状态污染"""
try:
driver = webdriver.PhantomJS(service_args=['--load-images=no'])
except WebDriverException:
chrome_options = webdriver.ChromeOptions()
chrome_profile = {'profile.managed_default_... | flexible | {
"blob_id": "5ab877ef15cdcd52463b1567c28327dc2eeea2de",
"index": 1204,
"step-1": "<mask token>\n\n\ndef get_browser_driver():\n \"\"\"获取浏览器服务 使用后记得 driver.quit() 否则容易引起状态污染\"\"\"\n try:\n driver = webdriver.PhantomJS(service_args=['--load-images=no'])\n except WebDriverException:\n chrome_... | [
1,
2,
3,
4,
5
] |
def ehcf(a, b):
p1, q1, h1, p2, q2, h2 = 1, 0, a, 0, 1, b
from math import floor
while h2 != 0:
r = floor(h1/h2)
p3 = p1-r*p2
q3 = q1-r*q2
h3 = h1-r*h2
p1,q1,h1,p2,q2,h2 = p2,q2,h2,p3,q3,h3
return (p1, q1, h1)
def findinverse(k, p):
l = ehcf(k,p)[0] % p
return l | normal | {
"blob_id": "d7b426727e11833b3825baac7b379f5ce44ea491",
"index": 5495,
"step-1": "<mask token>\n",
"step-2": "def ehcf(a, b):\n p1, q1, h1, p2, q2, h2 = 1, 0, a, 0, 1, b\n from math import floor\n while h2 != 0:\n r = floor(h1 / h2)\n p3 = p1 - r * p2\n q3 = q1 - r * q2\n h... | [
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": "ffd11d49f8499b4bfec8f17d07b66d899dd23d2e",
"index": 6924,
"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 = [('Cbrowser', ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Task:
<|reserved_special_token_0|>
def __init__(self):
"""
Create the object
:rtype: object
"""
self.queue = list()
self.pending = []
self.complete = []
self.failed = []
self.url_map = {}
self.c... | flexible | {
"blob_id": "63ee99012089dcb0e5b41860c95e13fff52c6731",
"index": 1546,
"step-1": "<mask token>\n\n\nclass Task:\n <mask token>\n\n def __init__(self):\n \"\"\"\n Create the object\n :rtype: object\n \"\"\"\n self.queue = list()\n self.pending = []\n self.com... | [
8,
9,
12,
13,
14
] |
from .start_node import StartNode
from .character_appearance import CharacterAppearance
from .character_disappearance import CharacterDisappearance
from .replica import Replica
from .end_node import EndNode
from .choice import Choice
from .set_landscape import SetLandscape
from .add_item import AddItem
from .switch_by_... | normal | {
"blob_id": "cd6e15daa2360ead47f0bac95843b1c030164996",
"index": 6879,
"step-1": "<mask token>\n",
"step-2": "from .start_node import StartNode\nfrom .character_appearance import CharacterAppearance\nfrom .character_disappearance import CharacterDisappearance\nfrom .replica import Replica\nfrom .end_node impor... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if sys.version_info.major == 2:
from itertools import izip
else:
izip = zip
<|reserved_special_token_1|>
import sys
if sys.version_info.major == 2:
from itertools import izip
else:
izip = zip
| flexible | {
"blob_id": "88445d8466d7acbf29d2525c7e322611d66494cd",
"index": 8315,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif sys.version_info.major == 2:\n from itertools import izip\nelse:\n izip = zip\n",
"step-3": "import sys\nif sys.version_info.major == 2:\n from itertools import izip\nelse:\... | [
0,
1,
2
] |
# Copyright (c) 2008 Johns Hopkins University.
# All rights reserved.
#
# Permission to use, copy, modify, and distribute this software and its
# documentation for any purpose, without fee, and without written
# agreement is hereby granted, provided that the above copyright
# notice, the (updated) modification history ... | normal | {
"blob_id": "f614287a2a118484b67f2b16e429a3335416d186",
"index": 3738,
"step-1": "# Copyright (c) 2008 Johns Hopkins University.\n# All rights reserved.\n#\n# Permission to use, copy, modify, and distribute this software and its\n# documentation for any purpose, without fee, and without written\n# agreement is h... | [
0
] |
from flask import Blueprint, request, jsonify
from to_dict import *
from validacao import *
import sqlite3
from migration import conectar, create_database
from contextlib import closing
aluno = Blueprint("aluno", __name__)
@aluno.route("/hello")
def hello():
return "Hello, aluno"
@aluno.route("/reseta", methods ... | normal | {
"blob_id": "5068336ca1a180e09a7efd41eea596cdcebb33ae",
"index": 5586,
"step-1": "<mask token>\n\n\n@aluno.route('/hello')\ndef hello():\n return 'Hello, aluno'\n\n\n@aluno.route('/reseta', methods=['POST'])\ndef reseta():\n sqlaluno = 'DELETE FROM aluno'\n sqldisciplina = 'DELETE FROM disciplina'\n ... | [
6,
7,
8,
9,
10
] |
import platform
import keyboard
import threading
import atexit
from threading import Timer
triggerCount = 0
triggerTimer = -1
result = None
def cleanup ():
print 'cleanup before exit'
clearTimer()
keyboard
triggerCount = 0
def clearTimer ():
global triggerTimer
global triggerCount
try:
... | normal | {
"blob_id": "9e8ed462e429d6c6c0fe232431ee1e98721863e9",
"index": 6148,
"step-1": "import platform\nimport keyboard\nimport threading\nimport atexit\nfrom threading import Timer\n\ntriggerCount = 0\ntriggerTimer = -1\n\nresult = None\n\ndef cleanup ():\n print 'cleanup before exit'\n clearTimer()\n keybo... | [
0
] |
'''
Дано предложение, в котором имеются буквы с и т. Определить, какая из них встречается
позже (при просмотре слова слева направо). Если таких букв несколько, то должны
учитываться последние из них. Оператор цикла с условием не использовать.
'''
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
if __name__ == '__main__'... | normal | {
"blob_id": "4bad45f8c135463fadea9b3eed52ab045a51e8db",
"index": 2520,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n text = input('Введите предложение: ')\n x1 = text.index('с')\n x2 = text.index('т')\n if x1 > x2:\n print(\"Бурква 'с' встречается позже\")... | [
0,
1,
2
] |
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
dataset = pd.read_csv('mgdata.dat.csv')
training_set = dataset.iloc[:1100, 1:2].values
X_train=[]
y_train=[]
for i in range(20,1090):
X_train.append(training_set[i-20:i,0])
y_train.append(training_set[i,0])
X_train=np.asarray... | normal | {
"blob_id": "28a3763715f5405f8abe2de17ed5f9df1019278b",
"index": 6878,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(20, 1090):\n X_train.append(training_set[i - 20:i, 0])\n y_train.append(training_set[i, 0])\n<mask token>\nclassifier.add(Dense(output_dim=35, init='uniform', activat... | [
0,
1,
2,
3,
4
] |
#Author: Abeer Rafiq
#Modified: 11/23/2019 3:00pm
#Importing Packages
import socket, sys, time, json, sqlite3
import RPi.GPIO as GPIO
from datetime import datetime, date
#Creating a global server class
class GlobalServer:
#The constructor
def __init__(self, port, room_ip_addrs,
app_ip_addrs):... | normal | {
"blob_id": "7ce679d5b889493f278de6deca6ec6bdb7acd3f5",
"index": 910,
"step-1": "#Author: Abeer Rafiq\n#Modified: 11/23/2019 3:00pm\n\n#Importing Packages\nimport socket, sys, time, json, sqlite3\nimport RPi.GPIO as GPIO\nfrom datetime import datetime, date\n\n#Creating a global server class\nclass GlobalServer:... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if m < n:
if m - x < x:
x = m - x
if n - y < y:
y = n - y
else:
if n - x < x:
x = n - x
if m - y < y:
y = m - y
if x < y:
print(x)
else:
print(y)
<|reserved_special_token_1... | flexible | {
"blob_id": "002cced6d24a4790d29f195355c795d609f744a7",
"index": 9134,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif m < n:\n if m - x < x:\n x = m - x\n if n - y < y:\n y = n - y\nelse:\n if n - x < x:\n x = n - x\n if m - y < y:\n y = m - y\nif x < y:\n pr... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class MockResponseError(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class MockResponseParsed(object):
HOV = list()
def __init__(self):
self.HOV.append(('FODT', '010107'))
self.HOV.append(('PERS', '5... | flexible | {
"blob_id": "bbff797fab4ac7dc7e6adb81c0eeda561f8ee147",
"index": 9603,
"step-1": "<mask token>\n\n\nclass MockResponseError(object):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass MockResponseParsed(object):\n HOV = list()\n\n def __init__(self):\n self.HOV.append(('FODT', '010107'... | [
17,
24,
26,
29,
30
] |
<|reserved_special_token_0|>
def read_input():
with open('../input/day12.txt') as f:
lines = f.readlines()
m = re.search('initial state:\\s([\\.#]+)', lines[0])
initial_state = m.groups()[0]
prog = re.compile('([\\.#]{5})\\s=>\\s([\\.#])')
rules = []
for i in range(2, len(lines)):
... | flexible | {
"blob_id": "27f001f4e79291825c56642693894375fef3e66a",
"index": 1647,
"step-1": "<mask token>\n\n\ndef read_input():\n with open('../input/day12.txt') as f:\n lines = f.readlines()\n m = re.search('initial state:\\\\s([\\\\.#]+)', lines[0])\n initial_state = m.groups()[0]\n prog = re.compile(... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class SmartChineseAnalyzer:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class SmartChineseAnalyzer:
<|reserved_special_token_0|>
def create_components(self, filename):
if self.stopwords:
... | flexible | {
"blob_id": "e486e0ab91a8f5671435f5bbcf5340a62a970d3a",
"index": 8670,
"step-1": "<mask token>\n",
"step-2": "class SmartChineseAnalyzer:\n <mask token>\n <mask token>\n",
"step-3": "class SmartChineseAnalyzer:\n <mask token>\n\n def create_components(self, filename):\n if self.stopwords:\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class LoadStudentsTTable(LoadTable):
<|reserved_special_token_0|>
def __init__(self, tails):
"""
Parameters
----------
tails : int
1 or 2.
"""
if tails == 1:
LoadTable.__init__(self, os.path.join(p,
... | flexible | {
"blob_id": "adb6e33dc665f88c82fcc399688a8dbd67b1e3e3",
"index": 9894,
"step-1": "<mask token>\n\n\nclass LoadStudentsTTable(LoadTable):\n <mask token>\n\n def __init__(self, tails):\n \"\"\"\n\n Parameters\n ----------\n tails : int\n 1 or 2.\n \"\"\"\n ... | [
8,
18,
19,
21,
23
] |
<|reserved_special_token_0|>
class TextDataset(BaseDataset):
def __init__(self, source_sentences: Union[Iterable, Sized],
target_sentences: Union[Iterable, Sized], shuffle: bool=True,
word_frequency_threshold: int=2):
super().__init__(source_sentences, target_sentences, shuffle)
s... | flexible | {
"blob_id": "e5d7cc65041d65f915d4882b4fdad5bebf79a067",
"index": 204,
"step-1": "<mask token>\n\n\nclass TextDataset(BaseDataset):\n\n def __init__(self, source_sentences: Union[Iterable, Sized],\n target_sentences: Union[Iterable, Sized], shuffle: bool=True,\n word_frequency_threshold: int=2):\... | [
12,
19,
20,
22,
27
] |
<|reserved_special_token_0|>
def mkdir_tree(source):
if source is None:
source = 'default'
base_dirs = ['../data/clf_meta/%s/' % source]
print('base_dirsssssss', base_dirs)
for base_dir in base_dirs:
if not os.path.exists(base_dir):
print('mkdir', base_dir)
os.m... | flexible | {
"blob_id": "11ca13aca699b1e0744243645b3dbcbb0dacdb7e",
"index": 9588,
"step-1": "<mask token>\n\n\ndef mkdir_tree(source):\n if source is None:\n source = 'default'\n base_dirs = ['../data/clf_meta/%s/' % source]\n print('base_dirsssssss', base_dirs)\n for base_dir in base_dirs:\n if n... | [
3,
4,
5,
6,
7
] |
#coding=utf-8
import pandas as pd
# 学生成绩表
df_grade = pd.read_excel("学生成绩表.xlsx")
df_grade.head()
# 学生信息表
df_sinfo = pd.read_excel("学生信息表.xlsx")
df_sinfo.head()
# 只筛选第二个表的少量的列
df_sinfo = df_sinfo[["学号", "姓名", "性别"]]
df_sinfo.head()
# join
df_merge = pd.merge(left=df_grade, right=df_sinfo, left_on="学号", right_on="学... | normal | {
"blob_id": "f6c48731b2a4e0a6f1f93034ee9d11121c2d0427",
"index": 6810,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndf_grade.head()\n<mask token>\ndf_sinfo.head()\n<mask token>\ndf_sinfo.head()\n<mask token>\ndf_merge.head()\n<mask token>\nfor name in ['姓名', '性别'][::-1]:\n new_columns.remove(name)\n... | [
0,
1,
2,
3,
4
] |
# Copyright 2014 Charles Noneman
#
# 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 writin... | normal | {
"blob_id": "9a7908212bf13565109cd4d9ab6de65909bc6910",
"index": 3606,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef run():\n \"\"\"Runs all of the tests\"\"\"\n subsuite_list = []\n for _, modname, _ in pkgutil.iter_modules(test.__path__):\n if modname.startswith('test_'):\n ... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class UserStatusAPIView(StatusAPIView):
serializer_class = StatusInlineUserSerializer
search_fields = 'id',
def get_queryset(self, *args, **kwargs):
username = self.kwargs.get('username')
if username is None:
return Status.objects.none()
re... | flexible | {
"blob_id": "472a79767f5dc7dc3cd03d89999d322b3885dcbf",
"index": 1220,
"step-1": "<mask token>\n\n\nclass UserStatusAPIView(StatusAPIView):\n serializer_class = StatusInlineUserSerializer\n search_fields = 'id',\n\n def get_queryset(self, *args, **kwargs):\n username = self.kwargs.get('username')... | [
4,
6,
7,
8,
9
] |
# Make an array of dictionaries. Each dictionary should have keys:
#
# lat: the latitude
# lon: the longitude
# name: the waypoint name
#
# Make up three entries of various values.
waypoints = [
{ 'lat': 106.72888 },
{ 'lon': 0.69622 },
{ 'name': 'Kepulauan Riau' }
]
# Write a loop that prints out all the... | normal | {
"blob_id": "5eee3953193e0fc9f44b81059ce66997c22bc8f1",
"index": 6960,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor dict in waypoints:\n print(dict)\n",
"step-3": "waypoints = [{'lat': 106.72888}, {'lon': 0.69622}, {'name': 'Kepulauan Riau'}]\nfor dict in waypoints:\n print(dict)\n",
"ste... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def learn_distributions(file_lists_by_category):
"""
Estimate the parameters p_d, and q_d from the training set
Input
-----
file_lists_by_category: A two-element list. The first element is a list of
spam files, and the second element is a list of ham files.
O... | flexible | {
"blob_id": "7ed84706ace2cbf523021887df1e13d113f9ce4c",
"index": 4172,
"step-1": "<mask token>\n\n\ndef learn_distributions(file_lists_by_category):\n \"\"\"\n Estimate the parameters p_d, and q_d from the training set\n\n Input\n -----\n file_lists_by_category: A two-element list. The first eleme... | [
1,
2,
3,
4,
5
] |
from setuptools import setup
setup(name = "dragonfab",
version = "1.3.0",
description = "Fabric support",
author = "Joel Pitt",
author_email = "joel@joelpitt.com",
url = "https://github.com/ferrouswheel/dragonfab",
install_requires = ['fabric', 'pip>=1.4', 'wheel'],
packages = ['dragonfab']... | normal | {
"blob_id": "61135a10adefd6ba8ffd63e997fa91ce9c78de06",
"index": 6444,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='dragonfab', version='1.3.0', description='Fabric support',\n author='Joel Pitt', author_email='joel@joelpitt.com', url=\n 'https://github.com/ferrouswheel/dragonfab', in... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
'''
Can you print numbers from 1 to 100 without using any loop.
'''
# Use Recursion | flexible | {
"blob_id": "cc703690151acd17430b5a9715e71a694fdeca10",
"index": 2116,
"step-1": "<mask token>\n",
"step-2": "'''\nCan you print numbers from 1 to 100 without using any loop.\n'''\n\n# Use Recursion",
"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|>
sys.path.append('../')
<|reserved_special_token_0|>
if __name__ == '__main__':
fn = 'input.txt'
with open(fn) as f:
program = Program([int(i) for i in f.readline().split(',')])
program.run()
result ... | flexible | {
"blob_id": "a54c8ab63c1e0f50d254d6c97ca3f167db7142e9",
"index": 4956,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append('../')\n<mask token>\nif __name__ == '__main__':\n fn = 'input.txt'\n with open(fn) as f:\n program = Program([int(i) for i in f.readline().split(',')])\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class ObjectValidationErrors(Exception):
def __init__(self, errors):
self.errors = errors
def _get_directory():
p = os.path.dirname(__file__)
p = os.path.join(p, os.pardir, os.pardir, 'schema')
p = os.path.abspath(p)
return p
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "c4f39f9212fbe0f591543d143cb8f1721c1f8e1e",
"index": 7056,
"step-1": "<mask token>\n\n\nclass ObjectValidationErrors(Exception):\n\n def __init__(self, errors):\n self.errors = errors\n\n\ndef _get_directory():\n p = os.path.dirname(__file__)\n p = os.path.join(p, os.pardir, os.pardir... | [
3,
5,
6,
7,
8
] |
__author__ = 'Freek'
__build__ = 'versie 1.0'
from iNStagram.file_io.fileio import lees_stationgegevens
from iNStagram.api_requests.app_requests import request_instagram
from tkinter import *
startscherm = Tk()
startscherm.title('Foto of video in de buurt!')
startscherm.minsize(width=790, height=600, )
startscherm.c... | normal | {
"blob_id": "2804d49fc9f0e40859de1e8eb4f04a849639b1d4",
"index": 8277,
"step-1": "<mask token>\n\n\ndef weergeef_instagram_links():\n \"\"\"\n Geeft de bijbehorende station dict uit de lijst van alle stations (in de NS API)\n :param stationnaam: geef ofwel kort, middel als lange stationnaam om de bijbeh... | [
1,
2,
3,
4,
5
] |
import sys, os
sys.path.append(os.path.abspath('../models'))
from GANSynth import flags as lib_flags
from GANSynth import generate_util as gu
from GANSynth import model as lib_model
from GANSynth import util
from GANSynth import train_util
import tensorflow as tf
import numpy as np
import json
from models.G... | normal | {
"blob_id": "f13a2820fe1766354109d1163c7e6fe887cd6f34",
"index": 7051,
"step-1": "<mask token>\n\n\nclass GANSynthWrapper(GenerativeModel):\n\n def __init__(self, ckpt_path, data_size, use_approx=True):\n super(GANSynthWrapper, self).__init__(use_approx=use_approx)\n self.latent_size = 256\n ... | [
7,
8,
9,
10,
11
] |
<|reserved_special_token_0|>
class BebopNmpcControl:
<|reserved_special_token_0|>
def set_bebop_odom(self, odom_msg):
if self.received_first_odom_ is False:
self.received_first_odom_ = True
rospy.loginfo('First odometry received!')
self.odom_received_time_ = rospy.Time... | flexible | {
"blob_id": "76d0dd2d6b2d580900283f2623f05dd02a70fcd8",
"index": 6825,
"step-1": "<mask token>\n\n\nclass BebopNmpcControl:\n <mask token>\n\n def set_bebop_odom(self, odom_msg):\n if self.received_first_odom_ is False:\n self.received_first_odom_ = True\n rospy.loginfo('First ... | [
10,
12,
13,
15,
18
] |
#!/usr/bin/env python
from __future__ import division
import sys
import math
logs = sys.stderr
from collections import defaultdict
import time
from mytime import Mytime
import gflags as flags
FLAGS=flags.FLAGS
flags.DEFINE_string("weights", None, "weights file (feature instances and weights)", short_name="w")
flag... | normal | {
"blob_id": "e5fd0fc13a39444a934eea3bd24056073d28eff2",
"index": 9869,
"step-1": "#!/usr/bin/env python\n\nfrom __future__ import division\n\nimport sys\nimport math\nlogs = sys.stderr\nfrom collections import defaultdict\n\nimport time\nfrom mytime import Mytime\n\nimport gflags as flags\nFLAGS=flags.FLAGS\n\nf... | [
0
] |
<|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": "59596c69df6a2c453fd147a9c8a2c7d47ed79fb3",
"index": 3222,
"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 = [('core', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def greatestCommonFactor(posInt1, posInt2):
range_posInt1 = list(range(1, posInt1 + 1))
factors_posInt1 = []
for i in range_posInt1:
if posInt1 % i == 0:
factors_posInt1.append(i)
range_posInt2 = list(range(1, posInt2 + 1))... | flexible | {
"blob_id": "a3f6ea649fc5e60b0f8353b1404912d060686b99",
"index": 9550,
"step-1": "<mask token>\n",
"step-2": "def greatestCommonFactor(posInt1, posInt2):\n range_posInt1 = list(range(1, posInt1 + 1))\n factors_posInt1 = []\n for i in range_posInt1:\n if posInt1 % i == 0:\n factors_po... | [
0,
1,
2,
3
] |
from os.path import abspath, dirname, join, basename
import numpy as np
import cv2
import xiuminglib as xm
logger, thisfile = xm.config.create_logger(abspath(__file__))
class EXR():
"""Reads EXR files.
EXR files can be generic or physically meaningful, such as depth, normal, etc.
When data loaded are p... | normal | {
"blob_id": "b9cce77d4d2b9ff5563d17927e21166f9c870e3d",
"index": 5220,
"step-1": "<mask token>\n\n\nclass EXR:\n \"\"\"Reads EXR files.\n\n EXR files can be generic or physically meaningful, such as depth, normal, etc.\n When data loaded are physically meaningful, these methods assume the EXR files\n ... | [
7,
9,
10,
11,
12
] |
import pprint
class ErrorResponseCollection(object):
def __init__(self, status, message, param = "message"):
self.status = status
self.message = message
self.param = param
def as_md(self):
return '\n\n> **%s**\n\n```\n{\n\n\t"%s": "%s"\n\n}\n\n```' % \
... | normal | {
"blob_id": "ade4d797a83eaa06e8bde90972a56376d7e0f55a",
"index": 6086,
"step-1": "<mask token>\n\n\nclass ErrorResponseCollection(object):\n <mask token>\n <mask token>\n\n\n<mask token>\n\n\nclass ResponseCollection(object):\n\n def __init__(self, message=None, data=None):\n self.message = messa... | [
4,
5,
6,
7,
9
] |
# collectd-vcenter - vcenter.py
#
# Author : Loic Lambiel @ exoscale
# Contributor : Josh VanderLinden
# Description : This is a collectd python module to gather stats from Vmware
# vcenter
import logging
import ssl
import time
from pysphere import VIServer
try:
import collectd
COLLECTD_ENABLED... | normal | {
"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
] |
<|reserved_special_token_0|>
@app.route('/QAsearch', methods=['POST', 'GET'])
def QAsearch():
"""Renders the QAsearch page."""
question = ''
form = QuestionForm()
question = form.question.data
if form.validate_on_submit():
return redirect(url_for('answer', word=question))
return render... | flexible | {
"blob_id": "3457a7c080da041ad279239bd6a3d214a3b8e49f",
"index": 6695,
"step-1": "<mask token>\n\n\n@app.route('/QAsearch', methods=['POST', 'GET'])\ndef QAsearch():\n \"\"\"Renders the QAsearch page.\"\"\"\n question = ''\n form = QuestionForm()\n question = form.question.data\n if form.validate_... | [
9,
10,
11,
12,
13
] |
<|reserved_special_token_0|>
class BasicModel(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def updateModel(self, X, Y):
"""
Updates the model with new observations.
"""
self.X = X
self.Y = Y
def get_X(self... | flexible | {
"blob_id": "88071df9367804b1c6e2b1c80da178ab7658e7a4",
"index": 3861,
"step-1": "<mask token>\n\n\nclass BasicModel(object):\n <mask token>\n <mask token>\n <mask token>\n\n def updateModel(self, X, Y):\n \"\"\"\n Updates the model with new observations.\n \"\"\"\n self.X... | [
7,
8,
9,
10,
12
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@app.route('/comments/<article_id>', methods=['POST'])
def get_comments(article_id):
comments_range = request.form.get('comments_for_single')
try:
temp_list = json.loads(comments_range)
if isinstance(temp... | flexible | {
"blob_id": "016c004fd95d901a6d55b6f7460397223a6baa3b",
"index": 1881,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/comments/<article_id>', methods=['POST'])\ndef get_comments(article_id):\n comments_range = request.form.get('comments_for_single')\n try:\n temp_list = json... | [
0,
1,
2,
3,
4
] |
from django.utils import timezone
from factory import DjangoModelFactory
from djtriggers.tests.models import DummyTrigger
class DummyTriggerFactory(DjangoModelFactory):
class Meta:
model = DummyTrigger
trigger_type = 'dummy_trigger_test'
source = 'tests'
date_received = timezone.now()
da... | normal | {
"blob_id": "813354c9c294c0323c1b54cda7074fbffa49cdb3",
"index": 442,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass DummyTriggerFactory(DjangoModelFactory):\n\n\n class Meta:\n model = DummyTrigger\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask tok... | [
0,
1,
2,
3
] |
from .data_processing import make_request_data, clear_request_data, get_token_from_text
from .review import Review
| normal | {
"blob_id": "5d654c056e6ef01e72821427c4f8dcb285755ee9",
"index": 2933,
"step-1": "<mask token>\n",
"step-2": "from .data_processing import make_request_data, clear_request_data, get_token_from_text\nfrom .review import Review\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
... | [
0,
1
] |
<|reserved_special_token_0|>
def get_bits(x):
return np.where(x < 0, 0, 1)
<|reserved_special_token_0|>
def mkdir(file_path):
folder = os.path.dirname(file_path)
if not os.path.exists(folder):
os.makedirs(folder)
<|reserved_special_token_0|>
def concatenate(total, part):
return part if... | flexible | {
"blob_id": "74ffbd55867c4b2c6ccbef7d94e0c65aef139057",
"index": 7602,
"step-1": "<mask token>\n\n\ndef get_bits(x):\n return np.where(x < 0, 0, 1)\n\n\n<mask token>\n\n\ndef mkdir(file_path):\n folder = os.path.dirname(file_path)\n if not os.path.exists(folder):\n os.makedirs(folder)\n\n\n<mask ... | [
7,
9,
11,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
any([(p in s) for p in patterns for s in strings])
<|reserved_special_token_1|>
# Find a list of patterns in a list of string in python
any([ p in s for p in patterns for s in strings ])
| flexible | {
"blob_id": "c0b6c0636d1900a31cc455795838eb958d1daf65",
"index": 9421,
"step-1": "<mask token>\n",
"step-2": "any([(p in s) for p in patterns for s in strings])\n",
"step-3": "# Find a list of patterns in a list of string in python\nany([ p in s for p in patterns for s in strings ])\n",
"step-4": null,
"... | [
0,
1,
2
] |
<|reserved_special_token_0|>
def AddOverflow(h):
nxbins = h.GetXaxis().GetNbins()
nybins = h.GetYaxis().GetNbins()
idxx = 0.0
idxy = nybins + 1
for ix in range(nxbins):
idxx = ix + 1
ovf_bincont = h.GetBinContent(idxx, idxy)
last_bincont = h.GetBinContent(idxx, nybins)
... | flexible | {
"blob_id": "b49696d6cac5fbf97172aa7cf16903d002262b5c",
"index": 1940,
"step-1": "<mask token>\n\n\ndef AddOverflow(h):\n nxbins = h.GetXaxis().GetNbins()\n nybins = h.GetYaxis().GetNbins()\n idxx = 0.0\n idxy = nybins + 1\n for ix in range(nxbins):\n idxx = ix + 1\n ovf_bincont = h.... | [
1,
2,
3,
4,
5
] |
#-------------------------------------------------------------------------------
# rtlconverter.py
#
# PyCoRAM RTL Converter
#
# Copyright (C) 2013, Shinya Takamaeda-Yamazaki
# License: Apache 2.0
#-------------------------------------------------------------------------------
import sys
import os
import subprocess
im... | normal | {
"blob_id": "55ffcf5e6120cc07da461e30979dd8a36a599bee",
"index": 8353,
"step-1": "<mask token>\n\n\nclass RtlConverter(object):\n\n def __init__(self, filelist, topmodule='userlogic', include=None,\n define=None, single_clock=False):\n self.filelist = filelist\n self.topmodule = topmodule... | [
7,
8,
9,
10,
11
] |
# coding: utf-8
# Copyright 2020. ThingsBoard
# #
# 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
# #
# Unl... | normal | {
"blob_id": "9b30075183cf9611307afa74aa45979872e7e9d5",
"index": 8132,
"step-1": "<mask token>\n\n\nclass DeviceControllerApi(DeviceControllerApi):\n <mask token>\n <mask token>\n\n def claim_device_using_post(self, device_name, **kwargs):\n \"\"\"claimDevice # noqa: E501\n\n This method ... | [
10,
11,
13,
14,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(my_list)
print(lista_impares)
print('')
<|reserved_special_token_0|>
print(my_list)
print(lista_pares)
<|reserved_special_token_1|>
my_list = [1, 4, 5, 6, 9, 13, 19, 21]
lista_impares = [num for num in my_list if num % 2 ... | flexible | {
"blob_id": "e1913c80375e4871119182d0267e9f228818624f",
"index": 4309,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(my_list)\nprint(lista_impares)\nprint('')\n<mask token>\nprint(my_list)\nprint(lista_pares)\n",
"step-3": "my_list = [1, 4, 5, 6, 9, 13, 19, 21]\nlista_impares = [num for num in m... | [
0,
1,
2,
3
] |
import FWCore.ParameterSet.Config as cms
import FWCore.ParameterSet.VarParsing as VarParsing
options = VarParsing.VarParsing()
options.register(
'file','',VarParsing.VarParsing.multiplicity.singleton,
VarParsing.VarParsing.varType.string,
'File path for storing output')
options.parseArguments()
file_path = options.f... | normal | {
"blob_id": "6aff61ce5cef537e6b1b19e382d8bf80e3a61693",
"index": 1423,
"step-1": "<mask token>\n",
"step-2": "<mask token>\noptions.register('file', '', VarParsing.VarParsing.multiplicity.singleton,\n VarParsing.VarParsing.varType.string, 'File path for storing output')\noptions.parseArguments()\n<mask toke... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in sys.stdin:
edges = [int(x) for x in line.split('x')]
edges.sort()
ribbon = sum(x * 2 for x in edges[:2])
l, w, h = edges
bow = l * w * h
total += bow + ribbon
print(total)
<|reserved_special_t... | flexible | {
"blob_id": "ed85cb61f4bc8bf758dafb10ffbabf87fb4521d0",
"index": 9281,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in sys.stdin:\n edges = [int(x) for x in line.split('x')]\n edges.sort()\n ribbon = sum(x * 2 for x in edges[:2])\n l, w, h = edges\n bow = l * w * h\n total +=... | [
0,
1,
2,
3,
4
] |
import psycopg2
from .configuration import ConfigurationException
DB_CONNECT_STRING = "host='{host}' dbname='{dbname}' user='{user}' password='{passwd}'"
class DBItemCompany:
def __init__(self, _id, tweeter, category, categoryUrl, provenScore, ranking, location, url, categoryId):
self.id = _id
se... | normal | {
"blob_id": "31b87a3ceca1f48665ecc9754d5f87bb9b7bbf13",
"index": 7579,
"step-1": "<mask token>\n\n\nclass DBException(Exception):\n \"\"\"\n Represents a generic exception thrown by the Database Manager\n \"\"\"\n pass\n\n\nclass DBManager:\n\n def __init__(self, cfg):\n self.cfg = cfg\n ... | [
15,
17,
18,
19,
22
] |
# config {stack,buffer,label}
def get_features_da(config,sent_dict):
features = []
# TODO Improve Features
if len(config[0]) > 0:
# Top of stack.
top = config[0][-1]
top_stk_token_feature = 'TOP_STK_TOKEN_'+str(sent_dict['FORM'][top].lower())
features.append(t... | normal | {
"blob_id": "e0ce8a8ad9c842b013bbb1ea1c585b6c4c2a68f5",
"index": 2868,
"step-1": "<mask token>\n",
"step-2": "def get_features_da(config, sent_dict):\n features = []\n if len(config[0]) > 0:\n top = config[0][-1]\n top_stk_token_feature = 'TOP_STK_TOKEN_' + str(sent_dict['FORM'][\n ... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
from gym_mag.envs.mag_control_env import MagControlEnv
| flexible | {
"blob_id": "dd7896e3beb5e33282b38efe0a4fc650e629b185",
"index": 5081,
"step-1": "<mask token>\n",
"step-2": "from gym_mag.envs.mag_control_env import MagControlEnv\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
<|reserved_special_token_0|>
def get_files1(dirname, size_in_kb):
"""Return files in dirname that are >= size_in_kb"""
for file in glob.glob(os.path.join(dirname, '*')):
if os.stat(file).st_size >= size_in_kb * ONE_KB:
yield file
<|reserved_special_token_1|>
<|reserved_special_token_0|>... | flexible | {
"blob_id": "0dec0f04cfe891eea74ef45484fa7433e3429dcd",
"index": 7570,
"step-1": "<mask token>\n\n\ndef get_files1(dirname, size_in_kb):\n \"\"\"Return files in dirname that are >= size_in_kb\"\"\"\n for file in glob.glob(os.path.join(dirname, '*')):\n if os.stat(file).st_size >= size_in_kb * ONE_KB... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def extract_3d(data: np.ndarray, center: np.ndarray, half_size: int):
"""
Extract an area around a point in a 3d numpy array, zero padded as necessary such that the specified point is at the
center
:param data: The numpy array to extract from
:param center: The point ... | flexible | {
"blob_id": "26f486131bdf514cd8e41f75d414fe647eaf1140",
"index": 9243,
"step-1": "<mask token>\n\n\ndef extract_3d(data: np.ndarray, center: np.ndarray, half_size: int):\n \"\"\"\n Extract an area around a point in a 3d numpy array, zero padded as necessary such that the specified point is at the\n cent... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
@pytest.mark.skipif('connection.vendor == "mysql"', reason=MYSQL_REASON)
def test_invalid_regex():
exception = IntegrityError if connection.vendor == 'sqlite' else DataError
with pytest.raises(exception):
Page.objects.create(url='(?P<match>.*)')
<|reserved_special_token_... | flexible | {
"blob_id": "96065e7e61b63f915561f117d71092e4bfb9a5da",
"index": 1149,
"step-1": "<mask token>\n\n\n@pytest.mark.skipif('connection.vendor == \"mysql\"', reason=MYSQL_REASON)\ndef test_invalid_regex():\n exception = IntegrityError if connection.vendor == 'sqlite' else DataError\n with pytest.raises(excepti... | [
1,
3,
4,
5,
7
] |
/Users/AbbyPennington/anaconda/lib/python3.5/os.py | normal | {
"blob_id": "8c4006ed8f4b1744f0316a61d95458b227653fee",
"index": 5887,
"step-1": "/Users/AbbyPennington/anaconda/lib/python3.5/os.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
} | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SpotAdmin(LeafletGeoAdmin):
pass
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SpotAdmin(LeafletGeoAdmin):
pass
admin.site.register(Spot, SpotAdmin)
<|reser... | flexible | {
"blob_id": "7633944366c6655306bc41087b19a474e9c414b5",
"index": 7688,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SpotAdmin(LeafletGeoAdmin):\n pass\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass SpotAdmin(LeafletGeoAdmin):\n pass\n\n\nadmin.site.register(Spot, SpotAdmin)\... | [
0,
1,
2,
3
] |
import xml.etree.ElementTree as ET
class Stage:
def __init__(self, costumes, sounds, variables, blocks, scripts, sprites):
self.costumes = costumes
self.sounds = sounds
self.variables = variables
self.blocks = blocks
self.scripts = scripts
self.sprites = sprites
... | normal | {
"blob_id": "575768c200ad81f878c132d68569c84f497091f2",
"index": 8137,
"step-1": "<mask token>\n\n\nclass Sprite:\n\n def __init__(self, name: str, index: str, xCoord: int, yCoord: int,\n heading: int, scale: float, volume: int, pan: int, rotation: int,\n draggable: bool, hidden: bool, costumes:... | [
2,
3,
4,
5
] |
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