code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
class Solution(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution(object):
def isIsomorphic(self, s, t):
"""
:type s: str
:type t: str
:rtype: bool
"""
n1 = len(s)
n2 = len(t)
if n1 ... | flexible | {
"blob_id": "7fdddf98fc7b588e9b8816ffa22bc24f715d7efe",
"index": 5210,
"step-1": "class Solution(object):\n <mask token>\n\n\n<mask token>\n",
"step-2": "class Solution(object):\n\n def isIsomorphic(self, s, t):\n \"\"\"\n :type s: str\n :type t: str\n :rtype: bool\n \"... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
"""
Написать программу, которая принимает строку
и выводит строку без пробелов и ее длину.
Для удаления пробелов реализовать доп функцию.
""" | flexible | {
"blob_id": "1eab2ddda6fdd71db372e978caa6e7d24c7fe78e",
"index": 7724,
"step-1": "<mask token>\n",
"step-2": "\"\"\"\n Написать программу, которая принимает строку\n и выводит строку без пробелов и ее длину.\n Для удаления пробелов реализовать доп функцию.\n\"\"\"",
"step-3": null,
"step-4": null,... | [
0,
1
] |
<|reserved_special_token_0|>
class ConfigApp(admin.MConfigHandler):
<|reserved_special_token_0|>
def handleList(self, confInfo):
confDict = self.readConf('appsetup')
if None != confDict:
for stanza, settings in confDict.items():
for key, val in settings.items():
... | flexible | {
"blob_id": "8d6c58e9ef4e14a089a7eb33a92214d081ed7692",
"index": 8462,
"step-1": "<mask token>\n\n\nclass ConfigApp(admin.MConfigHandler):\n <mask token>\n\n def handleList(self, confInfo):\n confDict = self.readConf('appsetup')\n if None != confDict:\n for stanza, settings in conf... | [
3,
4,
5,
6,
7
] |
from __future__ import absolute_import, division, print_function
import numbers
import torch
from torch.distributions import constraints
from pyro.distributions.distribution import Distribution
from pyro.distributions.score_parts import ScoreParts
from pyro.distributions.util import broadcast_shape, sum_rightmost
... | normal | {
"blob_id": "0f0ea6f07f9a082042ed9aff7a95d372c32b5a13",
"index": 1897,
"step-1": "<mask token>\n\n\nclass ReshapedDistribution(TorchDistribution):\n <mask token>\n <mask token>\n\n def __init__(self, base_dist, sample_shape=torch.Size(),\n reinterpreted_batch_ndims=0):\n sample_shape = tor... | [
27,
35,
36,
39,
44
] |
###########Seq_Profile_Blast_Parser_tool################################
import csv
import time
import re
import os
import sys
from collections import Counter
import operator
from fractions import *
import glob
import ntpath
from collections import defaultdict
path = open('config.txt').read().splitlines()[0].split('... | normal | {
"blob_id": "7eb8fe491a88bcfadf2a38eaa158b74b21514a1c",
"index": 8431,
"step-1": "###########Seq_Profile_Blast_Parser_tool################################\nimport csv\nimport time\nimport re\nimport os\nimport sys\nfrom collections import Counter\nimport operator\nfrom fractions import *\nimport glob\nimport ntp... | [
0
] |
'''It can be seen that the number, 125874, and its double, 251748, contain
exactly the same digits, but in a different order.
Find the smallest positive integer, x, such that 2x, 3x, 4x, 5x, and 6x, contain
the same digits.
'''
import common
import itertools
def digits(x):
return set(int(d) for d in str(x))
commo... | normal | {
"blob_id": "2ec8b9a92f8dd42faf99f0cd569ebf356e12c1d6",
"index": 8042,
"step-1": "<mask token>\n\n\ndef digits(x):\n return set(int(d) for d in str(x))\n\n\n<mask token>\n\n\ndef euler052():\n multiples = range(2, 7)\n for i in itertools.count(10 ** 5):\n if same_digits_as_multiples(i, multiples)... | [
2,
3,
4,
5,
6
] |
n,m=map(int,input().split())
l=list(map(int,input().split()))
t=0
result=[0 for i in range(0,n)]
result.insert(0,1)
while(t<m):
#print(t)
for i in range(l[t],n+1):
result[i]=result[i]+result[i-l[t]]
t=t+1
print(result[-1])
0 1 2 3 4
1 [1,1,1,1,1]
2 [1 1 2 2 3]
3 [... | normal | {
"blob_id": "56640454efce16e0c873d557ac130775a4a2ad8d",
"index": 6734,
"step-1": "n,m=map(int,input().split())\r\nl=list(map(int,input().split()))\r\nt=0\r\nresult=[0 for i in range(0,n)]\r\nresult.insert(0,1)\r\nwhile(t<m):\r\n #print(t)\r\n for i in range(l[t],n+1):\r\n result[i]=result[i]+result[... | [
0
] |
<|reserved_special_token_0|>
def cloud(user_id):
wall = tools.get_all('wall.get', 100, {'owner_id': user_id})['items']
wall = list(filter(lambda x: datetime.fromtimestamp(x['date']).year ==
current_year, wall))
tokenizer = RegexpTokenizer('[а-яА-ЯёЁ]+')
morph = pymorphy2.MorphAnalyzer()
d... | flexible | {
"blob_id": "03ce69924c885e59e40689dc63e50d54b89649f7",
"index": 2924,
"step-1": "<mask token>\n\n\ndef cloud(user_id):\n wall = tools.get_all('wall.get', 100, {'owner_id': user_id})['items']\n wall = list(filter(lambda x: datetime.fromtimestamp(x['date']).year ==\n current_year, wall))\n tokeniz... | [
2,
4,
5,
6,
7
] |
import text
nan=""
section_words = {'start': -1, '1.1': 17, '1.2': 38, '1.3': 55, '1.4': 76, '1.5': 95, '1.6': 114, '1.7': 133, '1.8': 151, '1.9': 170, '1.10': 190, '1.11': 209, '1.12': 233, '1.13': 257, '1.14': 277, '1.15': 299, '1.16': 320, '1.17': 341, '1.18': 364, '1.19': 385, '1.20': 405, '1.21': 428, '2.1': 451, ... | normal | {
"blob_id": "8a0c0f5ca6a965e07f59a6c88d4dd335310cbdfc",
"index": 9530,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnan = ''\nsection_words = {'start': -1, '1.1': 17, '1.2': 38, '1.3': 55, '1.4': 76,\n '1.5': 95, '1.6': 114, '1.7': 133, '1.8': 151, '1.9': 170, '1.10': 190,\n '1.11': 209, '1.12': ... | [
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": "20f56ff484321a7d623cead4315e5a6b3b0653a7",
"index": 2720,
"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 = [('monitoring'... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def backend_login(title, use_auth_info, use_login_data, settings=None):
api.set_title(title.TITLE_ID_EUR, title.LATEST_VERSION)
nex_token = api.get_nex_token(title.GAME_SERVER_ID)
auth_info = None
login_data = None
if use_auth_info:
auth_info = authentication.A... | flexible | {
"blob_id": "43315abf9e096cdca89ed7f4de976d2706ff9c20",
"index": 9234,
"step-1": "<mask token>\n\n\ndef backend_login(title, use_auth_info, use_login_data, settings=None):\n api.set_title(title.TITLE_ID_EUR, title.LATEST_VERSION)\n nex_token = api.get_nex_token(title.GAME_SERVER_ID)\n auth_info = None\n... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/python
class Bob(object):
def __init__(self):
self.question_response = "Sure."
self.yell_response = "Woah, chill out!"
self.silent_response = "Fine. Be that way!"
self.whatever = "Whatever."
def hey(self, question):
if not(question) or question.strip()=='':
... | normal | {
"blob_id": "7ff7da216bdda5c30bf7c973c82886035b31247c",
"index": 4093,
"step-1": "<mask token>\n",
"step-2": "class Bob(object):\n <mask token>\n <mask token>\n",
"step-3": "class Bob(object):\n <mask token>\n\n def hey(self, question):\n if not question or question.strip() == '':\n ... | [
0,
1,
2,
3,
4
] |
from sys import argv
from pyspark import SparkContext
import json
import re
import math
from _datetime import datetime
start_time = datetime.now()
input_file = argv[1]
model_file = argv[2]
stopwords = argv[3]
sc = SparkContext(appName='inf553')
lines = sc.textFile(input_file).map(lambda x: json.loads(x))
stopwords = sc... | normal | {
"blob_id": "e877f16e604682488d85142174ce4f3f6cee3f18",
"index": 7882,
"step-1": "<mask token>\n\n\ndef tf_idf(words):\n word_dict = {}\n for w in words:\n if w in word_dict.keys():\n word_dict[w] += 1\n else:\n word_dict[w] = 1\n max_freq = max(word_dict.values())\n ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def filter(txt):
output = []
for t in txt:
if t == '(' or t == ')' or t == '[' or t == ']':
output.append(t)
return output
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def filter(txt):
output = []
for ... | flexible | {
"blob_id": "9ca769ae8bbabee20b5dd4d75ab91d3c30e8d1bf",
"index": 8387,
"step-1": "<mask token>\n",
"step-2": "def filter(txt):\n output = []\n for t in txt:\n if t == '(' or t == ')' or t == '[' or t == ']':\n output.append(t)\n return output\n\n\n<mask token>\n",
"step-3": "def fi... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
ax.plot(times, result.expect[0])
ax.plot(times, result.expect[1])
ax.set_xlabel('Time')
ax.set_ylabel('Expectation values')
ax.legend(('Sigma-Z', 'Sigma-Y'))
plt.show()
<|reserved_special_token_1|>
times = np.linspace(0.0, 10.0... | flexible | {
"blob_id": "8474205d49aef2d18755fc1a25a82718962f4120",
"index": 6912,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nax.plot(times, result.expect[0])\nax.plot(times, result.expect[1])\nax.set_xlabel('Time')\nax.set_ylabel('Expectation values')\nax.legend(('Sigma-Z', 'Sigma-Y'))\nplt.show()\n",
"step-3... | [
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": "7d25a8eb61b6fb9069616745c2b68fd3ceeca9fb",
"index": 6600,
"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 = [('account', '... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class RedisHandler(Handler):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
async def emit(self, record: ExtendedLogRecord) ->None:
await self.redis_client.rpush(self.key, self.format(record))
async def close(self) ->None:
self.redis_client.clo... | flexible | {
"blob_id": "fe581ca8176fed01309f0d852f72564863aa0895",
"index": 8413,
"step-1": "<mask token>\n\n\nclass RedisHandler(Handler):\n <mask token>\n <mask token>\n\n async def emit(self, record: ExtendedLogRecord) ->None:\n await self.redis_client.rpush(self.key, self.format(record))\n\n async de... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def create_app(**config_overrides):
app = Flask(__name__)
app.config.from_pyfile('settings.py')
app.config.update(config_overrides)
db.init_app(app)
from user.views import user_app
app.register_blueprint(... | flexible | {
"blob_id": "8b7fb0789d197e50d7bdde2791b6fac964782469",
"index": 4001,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef create_app(**config_overrides):\n app = Flask(__name__)\n app.config.from_pyfile('settings.py')\n app.config.update(config_overrides)\n db.init_app(app)\n from user... | [
0,
1,
2,
3
] |
# Exercise 3: Write a program to prompt for a score between 0.0 and 1.0. If the score is out of range, print an error message.
# If the score is between 0.0 and 1.0, print a grade using the following table:
# Score Grade
# >= 0.9 A
# >= 0.8 B
# >= 0.7 C
# >= 0.6 D
# < 0.6 F
# Vinayak Nayak
# 27... | normal | {
"blob_id": "6f253da5dc1caa504a3a8aadae7bce6537b5c8c6",
"index": 6237,
"step-1": "<mask token>\n",
"step-2": "try:\n i = float(input('Enter the score : '))\n if i > 1 or i < 0:\n print(\"Entered score isn't valid.\")\n elif i < 0.6:\n print('Grade: F')\n elif i < 0.7:\n print('... | [
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@app.route('/')
def index():
headline = 'Hello world from a variable!'
return render_template('index.html', headline=headline)
@app.route('/bye/')
def bye():
headline = 'Goodbye!'
return render_template('index.... | flexible | {
"blob_id": "83bbb6433d1577be869bf840bdd42aa86e415da6",
"index": 9328,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n headline = 'Hello world from a variable!'\n return render_template('index.html', headline=headline)\n\n\n@app.route('/bye/')\ndef bye():\n hea... | [
0,
2,
3,
4,
5
] |
from django.contrib.staticfiles.storage import CachedFilesMixin
from storages.backends.s3boto3 import S3Boto3Storage
class CachedS3Storage(CachedFilesMixin, S3Boto3Storage):
pass
StaticRootS3BotoStorage = lambda : CachedS3Storage(location='static')
MediaRootS3BotoStorage = lambda : S3Boto3Storage(location='medi... | normal | {
"blob_id": "e99ff1c75d5108efc8d587d4533c34eeb15c6978",
"index": 9425,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CachedS3Storage(CachedFilesMixin, S3Boto3Storage):\n pass\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass CachedS3Storage(CachedFilesMixin, S3Boto3Storage):\n p... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def calculate_psf_tilts():
"""
Calculate the tilt of the psf at the center of each column
using all binned pixels in the given wavelength calibration file
for both orders and save to file
"""
for order in [1, 2]:
path = 'files/SOSS_PSF_tilt_order{}.npy'.for... | flexible | {
"blob_id": "9f478df4ff19cfe6c6559b6489c874d49377b90e",
"index": 4949,
"step-1": "<mask token>\n\n\ndef calculate_psf_tilts():\n \"\"\"\n Calculate the tilt of the psf at the center of each column\n using all binned pixels in the given wavelength calibration file\n for both orders and save to file\n ... | [
7,
10,
11,
13,
14
] |
<|reserved_special_token_0|>
class Heiyan2Spider(scrapy.Spider):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Heiyan2Spider(scrapy.Spider):
<|reserved_special... | flexible | {
"blob_id": "d13c6d71bb871496b0c6ad2451a2f561484e7c68",
"index": 9634,
"step-1": "<mask token>\n\n\nclass Heiyan2Spider(scrapy.Spider):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass Heiyan2Spider(scrapy.Spider):\n <mask token>\n <mask token... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
class GenerateMachineConfig(unittest.TestCase):
def setUp(self):
self.machine_configs = []
for machine_config_path in glob.glob(
f'{ASSETS_DIR}/openshift/99_openshift-machineconfig_99-dual-stack-*.yaml'
):
with open(machine_config_p... | flexible | {
"blob_id": "f0c082968e26d414b0dbb679d4e5077056e99979",
"index": 8653,
"step-1": "<mask token>\n\n\nclass GenerateMachineConfig(unittest.TestCase):\n\n def setUp(self):\n self.machine_configs = []\n for machine_config_path in glob.glob(\n f'{ASSETS_DIR}/openshift/99_openshift-machinec... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TooManyArgsStrategy(CommandStrategy):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TooManyArgsStrategy(CommandStrategy):
def apply(self):
print('Too man... | flexible | {
"blob_id": "afd72ce2d9598f92937f3038eb0ef49b740b9977",
"index": 6846,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TooManyArgsStrategy(CommandStrategy):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TooManyArgsStrategy(CommandStrategy):\n\n def apply(self):\n print('To... | [
0,
1,
2,
3
] |
def remove_zeros(given_list):
list_without_zero = []
for element in given_list:
if element != 0:
list_without_zero.append(element)
return list_without_zero
def sort_desc(given_list):
return sorted(given_list, key=None, reverse=True)
def length_check(n, given_list):
return n >... | flexible | {
"blob_id": "0779e516e35c41acf0529961e11541dfd1320749",
"index": 6501,
"step-1": "def remove_zeros(given_list):\n list_without_zero = []\n for element in given_list:\n if element != 0:\n list_without_zero.append(element)\n return list_without_zero\n\n\ndef sort_desc(given_list):\n r... | [
5,
7,
8,
10,
11
] |
n=int(input("enter a number"))
cp=n
rev=0
sum=0
while(n>0):
rev=n%10
sum+=rev**3
n=n//10
if(cp==sum):
print("the given no is amstrong ")
else:
print("the given no is not amstrong ") | normal | {
"blob_id": "a8190c7c8926df18ee9439922ce8e3241e9a6140",
"index": 4550,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile n > 0:\n rev = n % 10\n sum += rev ** 3\n n = n // 10\nif cp == sum:\n print('the given no is amstrong ')\nelse:\n print('the given no is not amstrong ')\n",
"step-... | [
0,
1,
2,
3
] |
### Script to convert matlab structure file (/motiongan/data/style-dataset/style_motion_database.mat')
import os
import sys
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import argparse
import math
import numpy as np
from collections import OrderedDict
import scipy.io
import pickle
from core.utils.eul... | normal | {
"blob_id": "f2dac8b454805829cf5dbe2efe3c0de805ae4cb5",
"index": 1727,
"step-1": "<mask token>\n\n\ndef load_skeleton(mat_path):\n mat_data = scipy.io.loadmat(mat_path)['skel'][0, 0]\n skeleton = OrderedDict()\n bone_names = mat_data[1].tolist()\n for i, bone in enumerate(bone_names):\n bone =... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def divisible_by(numbers, divisor):
res = []
for e in numbers:
if e % divisor == 0:
res.append(e)
return res
| flexible | {
"blob_id": "d7ff5bf5d8f397500fcac30b73f469316c908f15",
"index": 5042,
"step-1": "<mask token>\n",
"step-2": "def divisible_by(numbers, divisor):\n res = []\n for e in numbers:\n if e % divisor == 0:\n res.append(e)\n return res\n",
"step-3": null,
"step-4": null,
"step-5": nul... | [
0,
1
] |
<|reserved_special_token_0|>
def loadDataSet():
"""解析文件
Return: dataMat 文档列表 [[1,x1,x2]...]； labelMat 类别标签列表[1,0,1...]
@author:VPrincekin
"""
dataMat = []
labelMat = []
fr = open('testSet.txt')
for line in fr.readlines():
lineArr = line.strip().split()
dataMat.append([... | flexible | {
"blob_id": "d47ea763ac1a4981fc5dee67cd396ad49570f923",
"index": 7821,
"step-1": "<mask token>\n\n\ndef loadDataSet():\n \"\"\"解析文件\n Return: dataMat 文档列表 [[1,x1,x2]...]； labelMat 类别标签列表[1,0,1...]\n @author:VPrincekin\n \"\"\"\n dataMat = []\n labelMat = []\n fr = open('testSet.txt')\n f... | [
4,
6,
8,
9,
11
] |
from ROOT import *
import math
import os,sys,time,glob,fnmatch
import argparse
import ROOT
import sys
sys.path.append("utils")
from moments import *
from dirhandle import *
from plothandle import *
from AnalysisGeneratorMT import *
def doAnalysis( blabla):
return blabla.DoThreatdAnalysis()
if __name__ =... | normal | {
"blob_id": "7db31940aea27c10057e2ce1e02410994bd2039b",
"index": 3328,
"step-1": "from ROOT import *\nimport math\nimport os,sys,time,glob,fnmatch\nimport argparse\nimport ROOT\nimport sys\nsys.path.append(\"utils\")\nfrom moments import *\nfrom dirhandle import *\nfrom plothandle import *\nfrom AnalysisGene... | [
0
] |
# adventofcode.com
# day19
from collections import defaultdict
INPUTFILE = 'input/input19'
TEST = False
TESTCASE = ('HOH', ['H => HO\n', 'H => OH\n', 'O => HH\n'], ['OHOH', 'HOOH', 'HHHH', 'HOHO'])
def find_idx(string, substring):
""" iterator that returns the index of the next occurence of substring
wr... | normal | {
"blob_id": "e6fa1202d829fb553423998cdbad13684405437c",
"index": 8483,
"step-1": "# adventofcode.com\n# day19\n\nfrom collections import defaultdict\n\nINPUTFILE = 'input/input19'\n\nTEST = False\nTESTCASE = ('HOH', ['H => HO\\n', 'H => OH\\n', 'O => HH\\n'], ['OHOH', 'HOOH', 'HHHH', 'HOHO'])\n\ndef find_idx(str... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
keys = {'a', 'e', 'i', 'o', 'u', 'y'}
values = [1]
dictionnaire = {cle: list(values) for cle in keys}
print('dictionnaire : ', dictionnaire)
values.append(2)
for cle in dictionna... | flexible | {
"blob_id": "468c070aebff3124927c5595d68bb94321dd75e5",
"index": 4406,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n keys = {'a', 'e', 'i', 'o', 'u', 'y'}\n values = [1]\n dictionnaire = {cle: list(values) for cle in keys}\n print('dictionnaire : ', dictionnaire... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class ConvLayer(object):
<|reserved_special_token_0|>
def apply(self, h):
if self.activation_fn == False:
if self.normalizer_fn == False:
if self.dropout == False:
h_out = slim.conv2d(h, num_outputs=self.num_outputs,
... | flexible | {
"blob_id": "9da6bfa614d64956a302abbfeeea30c0339e9db3",
"index": 5583,
"step-1": "<mask token>\n\n\nclass ConvLayer(object):\n <mask token>\n\n def apply(self, h):\n if self.activation_fn == False:\n if self.normalizer_fn == False:\n if self.dropout == False:\n ... | [
19,
21,
23,
33,
35
] |
<|reserved_special_token_0|>
def appendimages(im1, im2):
""" Return a new image that appends the two images side-by-side. """
rows1 = im1.shape[0]
rows2 = im2.shape[0]
if rows1 < rows2:
im1 = np.concatenate((im1, zeros((rows2 - rows1, im1.shape[1]))),
axis=0)
elif rows1 > rows2... | flexible | {
"blob_id": "c3e313805c6f91f9aac77922edfd09650143f905",
"index": 4862,
"step-1": "<mask token>\n\n\ndef appendimages(im1, im2):\n \"\"\" Return a new image that appends the two images side-by-side. \"\"\"\n rows1 = im1.shape[0]\n rows2 = im2.shape[0]\n if rows1 < rows2:\n im1 = np.concatenate(... | [
9,
11,
12,
15,
18
] |
# Generated by Django 3.1.6 on 2021-02-15 12:13
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Book',
fields=[
... | normal | {
"blob_id": "6239cb08509b8e84a88db95479af05845876d9b6",
"index": 1502,
"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|>
class PrivateFile2(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class PrivateFile(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class PrivateFile2(models... | flexible | {
"blob_id": "e12c397ca1ae91ce314cda5fe2cd8e0ec4cfa861",
"index": 2199,
"step-1": "<mask token>\n\n\nclass PrivateFile2(models.Model):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass PrivateFile(models.Model):\n <mask token>\n <mask token>\n\n\nclass PrivateFile2(models.Model):\... | [
1,
3,
4,
5,
6
] |
from selenium.webdriver.common.by import By
class BasePageLocators:
LOGIN_LINK = (By.CSS_SELECTOR, "#login_link")
BASKET_LINK = (By.CSS_SELECTOR, '[class="btn btn-default"]:nth-child(1)')
USER_ICON = (By.CSS_SELECTOR, ".icon-user")
class LoginPageLocators:
LOG_IN_FORM = (By.CSS_SELECTOR, "#login_for... | normal | {
"blob_id": "5d3b9005b8924da36a5885201339aa41082034cd",
"index": 8692,
"step-1": "<mask token>\n\n\nclass BasketPageLocators:\n BASKET_STATUS = By.CSS_SELECTOR, '#content_inner'\n NAME_OF_ADDED_SHIPMENT = (By.CSS_SELECTOR,\n '#messages .alert:nth-child(1) > .alertinner strong')\n PRICE_OF_ADDED_S... | [
4,
5,
6,
8,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for index in range(len(train_folder_list)):
path = os.path.join(TRAIN_DIR, train_folder_list[index])
path = path + '/'
img_list = os.listdir(path)
for img in img_list:
img_path = os.path.join(path, img)
... | flexible | {
"blob_id": "01339324ad1a11aff062e8b27efabf27c97157fb",
"index": 9908,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor index in range(len(train_folder_list)):\n path = os.path.join(TRAIN_DIR, train_folder_list[index])\n path = path + '/'\n img_list = os.listdir(path)\n for img in img_list:... | [
0,
1,
2,
3,
4
] |
from typing import Union, Tuple
import numpy as np
from dispim import Volume
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 a... | normal | {
"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
] |
import numpy as np
import matplotlib.pyplot as plt
from math import *
from scipy.integrate import *
from pylab import *
from scipy.integrate import quad
MHD = np.zeros((80, 90, 5), dtype=float)
BGI = np.zeros((80, 90, 5), dtype=float)
Fp = np.zeros((80), dtype=float)
AngMHD = np.zeros((90,2), dtype=floa... | normal | {
"blob_id": "660334be611c30397c2f33890e1bca1fc43bd01f",
"index": 2420,
"step-1": "<mask token>\n\n\ndef PMHD(p, chi, b):\n return b ** 2 / p * (1 + sin(chi) ** 2)\n\n\ndef xMHD(p, chi, b):\n return -b ** 2 / p ** 2 * sin(chi) * cos(chi)\n\n\n<mask token>\n\n\ndef xBGI(p, chi, b):\n Q = 0.7 * p / b ** 0.... | [
3,
5,
6,
7,
8
] |
# -*- coding: utf-8 -*-
"""
current_models - library of ionic current models implemented in Python
Created on Mon Apr 10 16:30:04 2017
@author: Oliver Britton
"""
import os
import sys
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
import seaborn as sns
" Voltage clamp generator function... | normal | {
"blob_id": "012ab947f7a2c9d44f54464b3e477582ffcf3d77",
"index": 5589,
"step-1": "<mask token>\n\n\ndef nav17vw(Y, t, voltage_clamp_func, voltage_clamp_params):\n \"\"\" Human Nav 1.7 from Vasylyev Waxman \"\"\"\n v = voltage_clamp_func(t, voltage_clamp_params)\n m = Y[0]\n h = Y[1]\n alpha_m = 10... | [
12,
13,
14,
15,
18
] |
<|reserved_special_token_0|>
def squeezenet_fire_module(input, input_channel_small=16,
input_channel_large=64):
channel_axis = 3
input = Conv2D(input_channel_small, (1, 1), padding='valid')(input)
input = Activation('relu')(input)
input_branch_1 = Conv2D(input_channel_large, (1, 1), padding='valid... | flexible | {
"blob_id": "a5f3af6fc890f61eecb35bd157fc51bb65b4c586",
"index": 3958,
"step-1": "<mask token>\n\n\ndef squeezenet_fire_module(input, input_channel_small=16,\n input_channel_large=64):\n channel_axis = 3\n input = Conv2D(input_channel_small, (1, 1), padding='valid')(input)\n input = Activation('relu'... | [
2,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
def adjustMotorPowers():
global slave_power
global en_left
global en_right
global kp
error = en_right + en_left
slave_power -= error / kp
encoders.clear()
time.sleep(0.1)
def readEncoder():
global en_left
global en_right
global right_num_revs
... | flexible | {
"blob_id": "00f8a56b160cab22bf73c0d2397eb2c411e8c966",
"index": 7714,
"step-1": "<mask token>\n\n\ndef adjustMotorPowers():\n global slave_power\n global en_left\n global en_right\n global kp\n error = en_right + en_left\n slave_power -= error / kp\n encoders.clear()\n time.sleep(0.1)\n\... | [
2,
3,
4,
5,
6
] |
import pathlib
import shutil
import os
import glob
import pandas as pd
import sqlalchemy as sqla
"""
SCRIPT TO FILL THE DATABASE FROM CSV ON MEGA IF LOSE DATA IN PARTICULAR DATE
"""
PATH = "/home/thomas/Documents/TER/AJOUTER_CSV_BDD/"
folder = "test/"
files_used = []
totalFiles = 0
contents = pathlib.Path(PATH+folder... | normal | {
"blob_id": "795936dad7a9e51edf0df66207a43ac4d97e9023",
"index": 3781,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor path in sorted(contents):\n files_used.append(path.name)\n totalFiles += 1\nprint(files_used)\nprint(totalFiles)\n<mask token>\nfor filename in files_used:\n df = pd.read_csv... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print("""
Employee Details:
Employee Id:""", id, '\nName:', employee[id][
'empname'], '\nDepartment:', employee[id]['Department'],
'\nDesignation:', DA[employee[id]['Designation Code']]['designation'],
'\nSalary:', em... | flexible | {
"blob_id": "fcb0fb439db77c4d57c449ec8f720dbd3fef5abc",
"index": 2871,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(\"\"\"\n\nEmployee Details:\nEmployee Id:\"\"\", id, '\\nName:', employee[id][\n 'empname'], '\\nDepartment:', employee[id]['Department'],\n '\\nDesignation:', DA[employee[id]... | [
0,
1,
2,
3
] |
from random import randrange
from django.core.exceptions import ValidationError
from django.contrib.auth import get_user_model
from rest_framework import serializers
from rest_framework_simplejwt.serializers import TokenObtainPairSerializer
from .models import EmailValidation
from ..emails.models import Ema... | normal | {
"blob_id": "9f34bf3a0bb24db428b7af1a354aec1d3a72df98",
"index": 359,
"step-1": "<mask token>\n\n\nclass CreatePasswordEmailValidationSerializer(serializers.Serializer):\n <mask token>\n\n def save(self):\n validation_code = randrange(10000000, 100000000)\n email = Email.objects.create(valida... | [
15,
16,
18,
19,
21
] |
# Generated by Django 2.2.10 on 2020-05-06 14:43
import django.core.validators
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('planner', '0023_auto_20191226_1330'),
]
operations = [
migrations.AddField(
model_name='employee'... | normal | {
"blob_id": "c7558486fc50623f6e64b58668153b75bb6149b9",
"index": 6613,
"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 = [('planner', '... | [
0,
1,
2,
3,
4
] |
from datetime import date
import config
import datetime
import numpy
import pandas
import data_sources
from data_sources import POPULATION, convert_to_ccaa_iso
import material_line_chart
import ministry_datasources
HEADER = '''<html>
<head>
<title>{}</title>
<script type="text/javascript" src="https://w... | normal | {
"blob_id": "4c5b3042a785342d6ef06fdc882e0dcf91a787c3",
"index": 7816,
"step-1": "<mask token>\n\n\ndef calc_accumulated_indicende_per_ccaa(report, num_days=15):\n ccaas = data_sources.get_ccaas_in_dset(report)\n dframe = report['dframe']\n num_cases = dframe['num_casos']\n ccaa_column = data_sources... | [
4,
9,
10,
11,
13
] |
from flask_wtf import FlaskForm
from wtforms import StringField, DateField, DecimalField
class HoursForm(FlaskForm):
date = StringField("Date")
begins = DecimalField("Begins")
ends = DecimalField("Ends")
class Meta:
csrf = False
| normal | {
"blob_id": "b1a808e76008edec02d37ec596461e3a00a1d349",
"index": 4553,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass HoursForm(FlaskForm):\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n csrf = False\n",
"step-3": "<mask token>\n\n\nclass HoursForm(FlaskFo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Video(ABC):
def __init__(self, filename: str, *, scale: float=1, w_stretch: float=2,
gradient: typing.Union[int, str]=0, verbose: int=False):
if not os.path.isfile(filename):
raise FileNotFound(filename)
self.filename = filename
self.... | flexible | {
"blob_id": "24368b6c607c0524f8b52b279a6dce0fde72294b",
"index": 8936,
"step-1": "<mask token>\n\n\nclass Video(ABC):\n\n def __init__(self, filename: str, *, scale: float=1, w_stretch: float=2,\n gradient: typing.Union[int, str]=0, verbose: int=False):\n if not os.path.isfile(filename):\n ... | [
4,
5,
6,
7,
8
] |
"""
Problem Link: https://practice.geeksforgeeks.org/problems/palindrome/0
Given an integer, check whether it is a palindrome or not.
Input:
The first line of input contains an integer T denoting the number of test cases.
For each test case there will be single line containing single integer N.
Output:
Print "Yes" ... | normal | {
"blob_id": "ea12ede51881f6e826a044df5d7aba457c434658",
"index": 6050,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(int(input())):\n n = int(input())\n temp = n\n rev = 0\n while temp:\n rev = rev * 10 + temp % 10\n temp //= 10\n print('Yes' if rev == n else ... | [
0,
1,
2
] |
"""
This handy script will download all wallpapears from simpledesktops.com
Requirements
============
BeautifulSoup - http://www.crummy.com/software/BeautifulSoup/
Python-Requests - http://docs.python-requests.org/en/latest/index.html
Usage
=====
cd /path/to/the/script/
python simpledesktops.py
"""
from StringIO imp... | normal | {
"blob_id": "452d5d98b6c0b82a1f4ec18f29d9710a8c0f4dc9",
"index": 7371,
"step-1": "\"\"\"\nThis handy script will download all wallpapears from simpledesktops.com\n\nRequirements\n============\nBeautifulSoup - http://www.crummy.com/software/BeautifulSoup/\nPython-Requests - http://docs.python-requests.org/en/late... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(N):
n = int(input())
arr = collections.defaultdict(list)
parent = [i for i in range(n + 1)]
for i in range(n - 1):
a, b = map(int, input().split())
arr[a].append(b)
parent[b] ... | flexible | {
"blob_id": "d60a2d4c819f701e8e439b8839415aa2838df185",
"index": 6415,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(N):\n n = int(input())\n arr = collections.defaultdict(list)\n parent = [i for i in range(n + 1)]\n for i in range(n - 1):\n a, b = map(int, input().spli... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Logins(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Logins(models.Model):
create... | flexible | {
"blob_id": "9a55ccf758b4b2cc440153ab3b1f97823863a848",
"index": 165,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Logins(models.Model):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Logins(models.Model):\n created = models.DateTimeField(aut... | [
0,
1,
2,
3,
4
] |
#! /usr/bin/env python
import sys
import socket
def handle_connection(sock):
do_close = False
while 1:
try:
data = sock.recv(4096)
if not data: # closed! stop monitoring this socket.
do_close = True
break
print 'd... | normal | {
"blob_id": "fde4c10e2ed0ed38d683a220e2985c3f3f336601",
"index": 7258,
"step-1": "#! /usr/bin/env python\nimport sys\nimport socket\n\ndef handle_connection(sock):\n do_close = False\n \n while 1:\n try:\n data = sock.recv(4096)\n if not data: # closed! stop ... | [
0
] |
<|reserved_special_token_0|>
class BaseSaver:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|re... | flexible | {
"blob_id": "83fe635e35711c2c41d043a59d00a50cc87e69fa",
"index": 7696,
"step-1": "<mask token>\n\n\nclass BaseSaver:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token... | [
8,
15,
21,
22,
24
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print(180 / 4)
| flexible | {
"blob_id": "509129052f97bb32b4ba0e71ecd7b1061d5f8da2",
"index": 38,
"step-1": "<mask token>\n",
"step-2": "print(180 / 4)\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
} | [
0,
1
] |
#d
#b
#c
#b,c | normal | {
"blob_id": "8ecd1d6b43027153e05c771eb7183c062319eebc",
"index": 2716,
"step-1": "#d\n#b\n#c\n#b,c",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
1
]
} | [
1
] |
# -*- coding: utf-8 -*-
class Config(object):
def __init__(self):
self.config_dict = {
"data_path": {
# "vocab_path": "../data/cnews/cnews.vocab.txt",
"vocab_path": "../data/rumor/cnews.vocab.txt",
# "trainingSet_path": "../data/cnews/cnews.trai... | normal | {
"blob_id": "9cb4e550a0d19b44ec8357882f353b04748b213b",
"index": 2589,
"step-1": "<mask token>\n",
"step-2": "class Config(object):\n <mask token>\n <mask token>\n",
"step-3": "class Config(object):\n <mask token>\n\n def get(self, section, name):\n return self.config_dict[section][name]\n... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class TflearnDataSourceExtraTemplate(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class TflearnDataSourceExtraTemplate(object):
<|reserved_special_token_0|>
def __init__(self, rewrite_data... | flexible | {
"blob_id": "70c084dab8469ca34b0e3e5174101111e695f1ca",
"index": 6638,
"step-1": "<mask token>\n",
"step-2": "class TflearnDataSourceExtraTemplate(object):\n <mask token>\n <mask token>\n",
"step-3": "class TflearnDataSourceExtraTemplate(object):\n <mask token>\n\n def __init__(self, rewrite_data... | [
0,
1,
2,
3
] |
"""
2. Schreiben Sie die Anzahl von symmetrischen Paaren (xy) und (yx).
"""
def symetrisch(x, y):
"""
bestimmt weder zwei zweistellige Zahlen x und y symetrisch sind
:param x: ein Element der Liste
:param y: ein Element der Liste
:return: True- wenn x und y symetrisch
False - sonst
... | normal | {
"blob_id": "2c6dc4d55f64d7c3c01b3f504a72904451cb4610",
"index": 6532,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef symetrisch(x, y):\n \"\"\"\n bestimmt weder zwei zweistellige Zahlen x und y symetrisch sind\n :param x: ein Element der Liste\n :param y: ein Element der Liste\n :... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Circle:
<|reserved_special_token_0|>
def __init__(self, radius=1):
self.radius = radius
self.area = radius * radius * Circle.pi
def get_circumference(self):
return self.radius * Circle.pi * 2
<|reserved_special_token_0|>
class Animal:
d... | flexible | {
"blob_id": "c8137aacfb0f35c9630515442d5bdda870e9908a",
"index": 4827,
"step-1": "<mask token>\n\n\nclass Circle:\n <mask token>\n\n def __init__(self, radius=1):\n self.radius = radius\n self.area = radius * radius * Circle.pi\n\n def get_circumference(self):\n return self.radius *... | [
10,
11,
13,
16,
18
] |
def filter(txt): # can be improved using regular expression
output = []
for t in txt:
if t == "(" or t == ")" or t == "[" or t == "]":
output.append(t)
return output
result = []
while True:
raw_input = input()
line = filter(raw_input)
if raw_input != ".":
stack = []
err = False
for l in line:
... | normal | {
"blob_id": "9ca769ae8bbabee20b5dd4d75ab91d3c30e8d1bf",
"index": 8387,
"step-1": "<mask token>\n",
"step-2": "def filter(txt):\n output = []\n for t in txt:\n if t == '(' or t == ')' or t == '[' or t == ']':\n output.append(t)\n return output\n\n\n<mask token>\n",
"step-3": "def fi... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
admin.site.register(statuses)
admin.site.register(sites)
admin.site.register(redirects)
<|reserved_special_token_1|>
from django.contrib import admin
from main_app.models import sites, statuses, redirects
admin.site.register(st... | flexible | {
"blob_id": "2b8ca0c8c7878536da4f31652976988cdba62d89",
"index": 491,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(statuses)\nadmin.site.register(sites)\nadmin.site.register(redirects)\n",
"step-3": "from django.contrib import admin\nfrom main_app.models import sites, statuses, re... | [
0,
1,
2,
3
] |
from math import ceil
n, k = map(int, input().split())
d = list(map(int, input().split()))
packs = [0]*k
for i in d:
packs[i%k] += 1
counter = packs[0]//2
if (k % 2) == 0:
counter += packs[k//2]//2
for i in range(1, ceil(k/2)):
counter += min(packs[i], packs[k-i])
print(counter*2)
| normal | {
"blob_id": "2226382c494af33957a44d9f1682f7deacf574a2",
"index": 2075,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in d:\n packs[i % k] += 1\n<mask token>\nif k % 2 == 0:\n counter += packs[k // 2] // 2\nfor i in range(1, ceil(k / 2)):\n counter += min(packs[i], packs[k - i])\nprint(cou... | [
0,
1,
2,
3,
4
] |
[Interactive Programming with Python - Part 1]
[Arithmetic Expressions]
# numbers - two types, an integer or a decimal number
# two correspending data types int() and float()
print 3, -1, 3.14159, -2.8
# we can convert between data types using int() and float()
# note that int() take the "whole" part of a decimal n... | normal | {
"blob_id": "f1396179152641abf76256dfeab346907cb1e386",
"index": 2738,
"step-1": "[Interactive Programming with Python - Part 1]\n\n[Arithmetic Expressions]\n\n# numbers - two types, an integer or a decimal number\n# two correspending data types int() and float()\n\nprint 3, -1, 3.14159, -2.8\n\n# we can convert... | [
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def compute(plus, minus, total, inp):
if plus == 1 and minus == 0:
print(total)
return
elif plus == 1 and minus == 1:
print('Impossible')
return
elif abs(plus - minus) > total:
... | flexible | {
"blob_id": "d29c8ec737b8e962d381c8fdd0999e7e01847836",
"index": 5274,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef compute(plus, minus, total, inp):\n if plus == 1 and minus == 0:\n print(total)\n return\n elif plus == 1 and minus == 1:\n print('Impossible')\n ... | [
0,
2,
3,
4,
5
] |
from core.detector import Detector
from utils.augmentations import *
from torchvision.transforms.transforms import Compose
from config.mask_config import *
from config.train_config import model_info
np.random.seed(3)
colors = np.random.randint(128, 256, (100, 3))
def to_image(det):
size = 512
val_trans = [... | normal | {
"blob_id": "97e7ca02d85267492a0dcbbda9d8754a0a3735a5",
"index": 5315,
"step-1": "<mask token>\n\n\ndef to_image(det):\n size = 512\n val_trans = [Normalization([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]\n val_trans = Compose(val_trans)\n for i in range(5, 200):\n path = f'D:/temp_data/mask/test/{i}.j... | [
2,
3,
4,
5,
6
] |
from Store import Store
from MusicProduct import MusicProduct
class MusicStore(Store):
def make_product(self, name):
'''Overides from parent - return a new MusicProduct Object'''
| normal | {
"blob_id": "0a50b31155afce2558ec066267a9fd0c56964759",
"index": 5653,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass MusicStore(Store):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass MusicStore(Store):\n\n def make_product(self, name):\n \"\"\"Overides from parent - retur... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def analyze_commit(row):
row['conventional'] = row['lax'] = False
m = re.search(STRICT, row['subj'])
if m:
row['conventional'] = True
else:
m = re.search(LAX, row['subj'])
if m:
row['lax'] = True
if m:
row['label'] = m['label... | flexible | {
"blob_id": "16446c2c5612a14d4364cbefb949da0b473f7454",
"index": 7934,
"step-1": "<mask token>\n\n\ndef analyze_commit(row):\n row['conventional'] = row['lax'] = False\n m = re.search(STRICT, row['subj'])\n if m:\n row['conventional'] = True\n else:\n m = re.search(LAX, row['subj'])\n ... | [
2,
6,
7,
8,
9
] |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
from django.conf import settings
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.Create... | normal | {
"blob_id": "deb8ee1d6327a6406244147a819821e8d2b2890e",
"index": 1385,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [migrations.sw... | [
0,
1,
2,
3,
4
] |
def main():
x = float(input("Coordenada x: "))
y = float(input("Coordenada y: "))
if 1 <= y <= 2 and -3 <= x <= 3:
print("dentro")
elif (4 <= y <= 5 or 6 <= x <= 7) and ( -4 <= x <= -3 or -2 <= x <= -1 or 1 <= x <= 2 or 3 <= x <= 4):
print("dentro")
e... | normal | {
"blob_id": "06cb832c3adae95fcd1d1d2d0663641d3ac671ef",
"index": 9132,
"step-1": "<mask token>\n",
"step-2": "def main():\n x = float(input('Coordenada x: '))\n y = float(input('Coordenada y: '))\n if 1 <= y <= 2 and -3 <= x <= 3:\n print('dentro')\n elif (4 <= y <= 5 or 6 <= x <= 7) and (-4... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class k_box:
def __init__(self, string=0, file=0):
if string != 0:
if not len(string) == 64:
raise Exception('Bad len')
self.__priv_key = bytes.fromhex(string)
else:
self.__priv_key = secrets.randbits(256).to_bytes(3... | flexible | {
"blob_id": "1ff2f06349ab1906a1649bdb83828fbdb3cf584f",
"index": 4516,
"step-1": "<mask token>\n\n\nclass k_box:\n\n def __init__(self, string=0, file=0):\n if string != 0:\n if not len(string) == 64:\n raise Exception('Bad len')\n self.__priv_key = bytes.fromhex(st... | [
9,
12,
14,
16,
18
] |
from typing import List, Callable
#: A list of int
T = List[int]
C = Callable[[int], None] # a generic alias not having a doccomment
| normal | {
"blob_id": "aaee69d339cf1c14e54366633155ee57026e6487",
"index": 2071,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nT = List[int]\nC = Callable[[int], None]\n",
"step-3": "from typing import List, Callable\nT = List[int]\nC = Callable[[int], None]\n",
"step-4": "from typing import List, Callable\n\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class BaseHandler(tornado.web.RequestHandler):
<|reserved_special_token_0|>
class CondaHandler(BaseHandler):
def get(self, filePath):
with open('packages/conda/' + filePath) as f:
data = json.load(f)
condaPackages = {}
packages = data['packag... | flexible | {
"blob_id": "44a9bb4d74d2e694f252d8726647bca13baa4df5",
"index": 853,
"step-1": "<mask token>\n\n\nclass BaseHandler(tornado.web.RequestHandler):\n <mask token>\n\n\nclass CondaHandler(BaseHandler):\n\n def get(self, filePath):\n with open('packages/conda/' + filePath) as f:\n data = json... | [
5,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
sys.path.append(dir_path)
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'gulishop.settings')
<|reserved_special_token_0|>
django.setup()
<|reserved_special_token_0|>
for lev1 in row_data:
cat1 = GoodsCategory()
cat1.name... | flexible | {
"blob_id": "35ae9c86594b50bbe4a67d2cc6b20efc6f6fdc64",
"index": 295,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsys.path.append(dir_path)\nos.environ.setdefault('DJANGO_SETTINGS_MODULE', 'gulishop.settings')\n<mask token>\ndjango.setup()\n<mask token>\nfor lev1 in row_data:\n cat1 = GoodsCategory... | [
0,
1,
2,
3,
4
] |
#the initial DNA sequence
dnaSequence = 'ACTGATCGATTACGTATAGTAGAATTCTATCATACATATATATCGATGCGTTCAT'
#seperating the DNA sequence at the specified location
firstFragment = 'ACTGATCGATTACGTATAGTAGAATTCTATCATACATATATATCGATGCGTTCAT' [0:22]
secondFragment = 'ACTGATCGATTACGTATAGTAGAATTCTATCATACATATATATCGATGCGTTCAT' [23:100]
... | normal | {
"blob_id": "7dc99d33023dbb13938ac413af7d3e9471fdbc3d",
"index": 126,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('the original DNA sequence is', dnaSequence)\nprint('the first fragment is', firstFragment, 'and is', firstFragmentLen,\n 'letters long')\nprint('the second fragment is', secondFr... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def selectionSort(arr, low, high):
for i in range(len(arr)):
mini = i
for j in range(i + 1, len(arr)):
if arr[mini] > arr[j]:
mini = j
arr[i], arr[mini] = arr[mini], arr[i]
return arr
| flexible | {
"blob_id": "c91be6cc332139c5b1e7ee5a3512482d0f8620b1",
"index": 7322,
"step-1": "<mask token>\n",
"step-2": "def selectionSort(arr, low, high):\n for i in range(len(arr)):\n mini = i\n for j in range(i + 1, len(arr)):\n if arr[mini] > arr[j]:\n mini = j\n arr[... | [
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def project_query_lz_main(question):
txt_line = ReadTxtName(PROJECT_NAMES)
for project_name in txt_line:
if project_name in question:
GV.SHOW = True
return '我们觉得您是想查' + project_name + '项目的... | flexible | {
"blob_id": "92bbccfbfebf905965c9cb0f1a85ffaa7d0cf6b5",
"index": 3796,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef project_query_lz_main(question):\n txt_line = ReadTxtName(PROJECT_NAMES)\n for project_name in txt_line:\n if project_name in question:\n GV.SHOW = True\n ... | [
0,
1,
2,
3,
4
] |
#TODO: allow workers to pull this from cache
RABBITMQ_IP = '172.23.105.82'
OBJECT_CACHE_IP = "172.23.105.69"
OBJECT_CACHE_PORT = "11911"
SERIESLY_IP = ''
COUCHBASE_IP = '172.23.105.54'
COUCHBASE_PORT = '8091'
COUCHBASE_USER = "Administrator"
COUCHBASE_PWD = "password"
SSH_USER = "root"
SSH_PASSWORD = "password"
WORKER... | normal | {
"blob_id": "e70ebd9bb9cd7027772ec117cb91349afba7ab10",
"index": 6390,
"step-1": "<mask token>\n",
"step-2": "RABBITMQ_IP = '172.23.105.82'\nOBJECT_CACHE_IP = '172.23.105.69'\nOBJECT_CACHE_PORT = '11911'\nSERIESLY_IP = ''\nCOUCHBASE_IP = '172.23.105.54'\nCOUCHBASE_PORT = '8091'\nCOUCHBASE_USER = 'Administrator... | [
0,
1,
2
] |
# -*- coding: utf-8 -*-
##############################################################################
#
# OpenERP, Open Source Management Solution
# Copyright (c) 2010-2014 Elico Corp. All Rights Reserved.
# Alex Duan <alex.duan@elico-corp.com>
#
# This program is free software: you can redistribute it and... | normal | {
"blob_id": "19d86c64876575ed9b3f5e33dd44e7633c96e696",
"index": 2401,
"step-1": "<mask token>\n\n\nclass product_product(orm.Model):\n <mask token>\n <mask token>\n <mask token>\n\n def _get_sale_quotation_qty(self, cr, uid, product_id, context=None):\n \"\"\"get all qty of the product in all... | [
2,
6,
8,
9,
10
] |
from sqlitedict import SqliteDict
import sys
import socket
import urllib
import argparse
import zlib, pickle, sqlite3
import random
from datetime import datetime
import time
from urllib.parse import urlparse
import hashlib
import subprocess
import requests
from multiprocessing import Pool
def gz_encode(obj):
retur... | normal | {
"blob_id": "295d6a66335491b406f47212064da9fd5fca6eb6",
"index": 6812,
"step-1": "<mask token>\n\n\ndef gz_decode(obj):\n return pickle.loads(zlib.decompress(bytes(obj)))\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef gz_encode(obj):\n return sqlite3.Binary(zlib.compress(pickle.dumps(obj, pickle.... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def Ret_Sister_Same_Rank(string, nodes_file, names_file):
print(string)
interest_taxid = Str_To_Taxid(string, names_file)
print(interest_taxid)
up_taxid = Return_Parent(interest_taxid, nodes_file)
up_taxid = up_taxid.strip()
interest_taxid = interest_taxid.strip()
... | flexible | {
"blob_id": "5c1324207e24f2d723be33175101102bd97fe7a2",
"index": 4860,
"step-1": "<mask token>\n\n\ndef Ret_Sister_Same_Rank(string, nodes_file, names_file):\n print(string)\n interest_taxid = Str_To_Taxid(string, names_file)\n print(interest_taxid)\n up_taxid = Return_Parent(interest_taxid, nodes_fi... | [
2,
15,
18,
21,
27
] |
<|reserved_special_token_0|>
@app.route('/unlock')
def web_unlock():
if not (request.args.get('token') and request.args.get('state')):
return 'Error'
else:
with shelve.open('Settings.conf') as settings:
if 'token' in settings:
token = settings['token']
e... | flexible | {
"blob_id": "ee0f90b84df73ae5783ca0b8a52fe6fe9c979f15",
"index": 2576,
"step-1": "<mask token>\n\n\n@app.route('/unlock')\ndef web_unlock():\n if not (request.args.get('token') and request.args.get('state')):\n return 'Error'\n else:\n with shelve.open('Settings.conf') as settings:\n ... | [
2,
3,
4,
5,
6
] |
#! /usr/bin/python
# -*- coding: utf8 -*-
# vim: tabstop=8 expandtab shiftwidth=4 softtabstop=4
import unittest
from pyama.filereader import FileReader,Segment
class TestFileReader(unittest.TestCase):
def test_reads_file(self):
reader = FileReader(
"sample_reader_test.txt",
regexe... | normal | {
"blob_id": "92dc0bd3cfcddd98f99d8152d0221f047beb4fb0",
"index": 9492,
"step-1": "<mask token>\n\n\nclass TestFileReader(unittest.TestCase):\n\n def test_reads_file(self):\n reader = FileReader('sample_reader_test.txt', regexes=[(\n 'name=\"(\\\\w+)\"', 'END SEGMENT'), ('\\\\s*\\\\*\\\\s*STA... | [
2,
3,
4,
5,
6
] |
from mf_app import db
from mf_app.models import User
db.create_all()
#test input data
admin = User('admin', 'admin@admin.com', 'admin')
guest = User('guest', 'guest@guest.com', 'guest')
db.session.add(admin)
db.session.add(guest)
db.session.commit()
users = User.query.all()
print(users) | normal | {
"blob_id": "99c2bd56deccc327faf659e91fc1fd0f6ff7a219",
"index": 3932,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ndb.create_all()\n<mask token>\ndb.session.add(admin)\ndb.session.add(guest)\ndb.session.commit()\n<mask token>\nprint(users)\n",
"step-3": "<mask token>\ndb.create_all()\nadmin = User('... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for _ in range(int(input())):
n = int(input())
xco, yco = [], []
flagx, flagy, xans, yans = 1, 1, 0, 0
for x in range(4 * n - 1):
x, y = input().split()
xco.append(int(x))
yco.append(int(y))... | flexible | {
"blob_id": "d3b0a1d8b9f800c5d34732f4701ea2183405e5b4",
"index": 9523,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(int(input())):\n n = int(input())\n xco, yco = [], []\n flagx, flagy, xans, yans = 1, 1, 0, 0\n for x in range(4 * n - 1):\n x, y = input().split()\n ... | [
0,
1,
2
] |
# generated from catkin/cmake/template/order_packages.context.py.in
source_root_dir = "/home/songsong/image_transport_ws/src"
whitelisted_packages = "".split(';') if "" != "" else []
blacklisted_packages = "".split(';') if "" != "" else []
underlay_workspaces = "/home/songsong/image_transport_ws/devel;/home/songsong/pi... | normal | {
"blob_id": "86ca94820c05b3f63f4a733b6d1fa7eb9dea6a5d",
"index": 325,
"step-1": "<mask token>\n",
"step-2": "source_root_dir = '/home/songsong/image_transport_ws/src'\nwhitelisted_packages = ''.split(';') if '' != '' else []\nblacklisted_packages = ''.split(';') if '' != '' else []\nunderlay_workspaces = (\n ... | [
0,
1,
2
] |
from guet.commands.strategies.strategy import CommandStrategy
class TooManyArgsStrategy(CommandStrategy):
def apply(self):
print('Too many arguments.')
| normal | {
"blob_id": "afd72ce2d9598f92937f3038eb0ef49b740b9977",
"index": 6846,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass TooManyArgsStrategy(CommandStrategy):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TooManyArgsStrategy(CommandStrategy):\n\n def apply(self):\n print('To... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def shiftZeroesToEnd(myArray):
zeroCounter = 0
shiftedArray = []
for item in myArray:
if (str(item) == '0' or str(item) == '0.0') and type(item) is not str:
zeroCounter += 1
else:
shiftedArray.append(item)
... | flexible | {
"blob_id": "4a9c42727a28e19cf1eebcf72784b85bbae695bf",
"index": 3429,
"step-1": "<mask token>\n",
"step-2": "def shiftZeroesToEnd(myArray):\n zeroCounter = 0\n shiftedArray = []\n for item in myArray:\n if (str(item) == '0' or str(item) == '0.0') and type(item) is not str:\n zeroCou... | [
0,
1,
2,
3
] |
def parse_detail_for_one_course(page, course, no_info_course):
print(f'{course["name"]} is processing**: {course["url"]}')
map = {"Locatie": "location",
"Location": "location",
"Startdatum": "effective_start_date",
"Start date": "effective_start_date",
"Duur": "durati... | normal | {
"blob_id": "0f4fa9f8835ae22032af9faa6c7cb10af3facd79",
"index": 5389,
"step-1": "<mask token>\n",
"step-2": "def parse_detail_for_one_course(page, course, no_info_course):\n print(f\"{course['name']} is processing**: {course['url']}\")\n map = {'Locatie': 'location', 'Location': 'location', 'Startdatum'... | [
0,
1,
2
] |
def clear_firefox_driver_session(firefox_driver):
firefox_driver.delete_all_cookies()
# Note this only works if the browser is set to a location.
firefox_driver.execute_script('window.localStorage.clear();')
firefox_driver.execute_script('window.sessionStorage.clear();')
class LocationNotSet(Exception... | normal | {
"blob_id": "6d0b9523668bd0b302fdbc196d3d7ff25be10b23",
"index": 5045,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass LocationNotSet(Exception):\n pass\n",
"step-3": "def clear_firefox_driver_session(firefox_driver):\n firefox_driver.delete_all_cookies()\n firefox_driver.execute_scri... | [
0,
1,
2,
3
] |
# Create your views here.
from django.shortcuts import render_to_response, Http404, render
from django.template import RequestContext
from books.models import Book
from django.http import HttpResponse, HttpResponseRedirect
import urllib, urllib2
import json
def incr_reads(request, book_id):
if request.POST:
... | normal | {
"blob_id": "bcbcb4ea3a3b8b5c11e9b107103418ae79a3921c",
"index": 3628,
"step-1": "<mask token>\n\n\ndef incr_reads(request, book_id):\n if request.POST:\n try:\n readers = Book.objects.get(id=book_id).incr_reads()\n return HttpResponse(readers)\n except Book.DoesNotExist:\n... | [
2,
3,
4,
5,
6
] |
# Core Packages
import difflib
import tkinter as tk
from tkinter import *
from tkinter import ttk
from tkinter.scrolledtext import *
import tkinter.filedialog
import PyPDF2
from tkinter import filedialog
import torch
import json
from transformers import T5Tokenizer, T5ForConditionalGeneration, T5Config
# ... | normal | {
"blob_id": "e3dece36ba3e5b3df763e7119c485f6ed2155098",
"index": 795,
"step-1": "<mask token>\n\n\ndef get_summary():\n model = T5ForConditionalGeneration.from_pretrained('t5-small')\n tokenizer = T5Tokenizer.from_pretrained('t5-small')\n device = torch.device('cpu')\n text = str(url_display1.get('1.... | [
8,
9,
13,
14,
15
] |
# -*- coding: utf-8 -*-
# Generated by Django 1.10.6 on 2017-04-03 14:45
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('productores', '0002_auto_20170327_0841'),
]
operations = [
migrations.AddFi... | normal | {
"blob_id": "2f7be68f08716d5d04d064d81eecb53eb9b80174",
"index": 7635,
"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 = [('productores... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(kamus)
print(kamus['ayah'])
print(
"""
Data ini dikirimkan server gojek, memberikan info driver di sekitar pemakai aplikasi"""
)
<|reserved_special_token_0|>
print(data_server_gojek)
print(f"Driver di sekitar sini {d... | flexible | {
"blob_id": "67b101df690bbe9629db2cabf0060c0f2aad9722",
"index": 2389,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(kamus)\nprint(kamus['ayah'])\nprint(\n \"\"\"\nData ini dikirimkan server gojek, memberikan info driver di sekitar pemakai aplikasi\"\"\"\n )\n<mask token>\nprint(data_server_... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Scraper:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Entry:
folder = None
date = None
sunspots = -1
image_path = None
counted_sunspots... | flexible | {
"blob_id": "c55991e738c89ee09dabd79d514e710e0fcbac85",
"index": 422,
"step-1": "<mask token>\n\n\nclass Scraper:\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Entry:\n folder = None\n date = None\n sunspots = -1\n image_path = None\n counted_... | [
10,
11,
12,
17,
18
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def my_square_root(a, x):
e = 0.0001
while True:
y = (x + a / x) / 2
if abs(y - x) < e:
return y
break
x = y
<|reserved_special_token_0|>
<|reserved_special_token_1|>
... | flexible | {
"blob_id": "c9f4ae94dc901d34a3c0fb4371c8d35a7fe94507",
"index": 5095,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef my_square_root(a, x):\n e = 0.0001\n while True:\n y = (x + a / x) / 2\n if abs(y - x) < e:\n return y\n break\n x = y\n\n\n<mask ... | [
0,
1,
2,
3,
4
] |
##outcome: Hello, my name is B-max
print("Hello", end="")
print(", my name ", end="")
print("is B-max", end="")
print()
##outcome: ****************************************
for i in range(40):
print('*', end="")
print()
##outcome: x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*x*
for i in range(20):
print("x*", en... | normal | {
"blob_id": "41aebc4ee9cb058c3351029773be05cdc4f84ffa",
"index": 7282,
"step-1": "<mask token>\n",
"step-2": "print('Hello', end='')\nprint(', my name ', end='')\nprint('is B-max', end='')\nprint()\nfor i in range(40):\n print('*', end='')\nprint()\nfor i in range(20):\n print('x*', end='')\nprint()\nfor... | [
0,
1,
2
] |
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