code stringlengths 13 6.09M | order_type stringclasses 2
values | original_example dict | step_ids listlengths 1 5 |
|---|---|---|---|
from __future__ import division, print_function, absolute_import
import numbers
import warnings
from abc import ABCMeta, abstractmethod
import numpy as np
from .base import check_frame
from skutil.base import overrides
from sklearn.externals import six
from sklearn.base import _pprint
from sklearn.utils.fixes import si... | normal | {
"blob_id": "c59707ba07c1659d94684c54cdd7bb2658cba935",
"index": 6,
"step-1": "<mask token>\n\n\nclass H2OShuffleSplit(H2OBaseShuffleSplit):\n <mask token>\n\n def _iter_indices(self, frame, y=None):\n \"\"\"Iterate the indices.\n\n Parameters\n ----------\n\n frame : H2OFrame\n... | [
21,
29,
40,
43,
47
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def multi_strassen(A, B, check_ig=True, check_quad=True, check_pot=True,
check_time=True):
def Strassen(matriz_1, matriz_2):
if matriz_1.shape[0] != 2 or matriz_1.shape[1] != 2 or matriz_2.shape[0
] ... | flexible | {
"blob_id": "6707723b3d0b42271e49c08c639afc9103066dc7",
"index": 4679,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef multi_strassen(A, B, check_ig=True, check_quad=True, check_pot=True,\n check_time=True):\n\n def Strassen(matriz_1, matriz_2):\n if matriz_1.shape[0] != 2 or matriz_1... | [
0,
1,
2,
3
] |
import logging
from queue import Queue
import concurrent.futures
"""
Post processing decorater logic for FtpDownloader
"""
class FtpDownloaderPostProcess:
def __init__(self, ftp_downloader, post_processor, num_workers=None, config_dict=None):
self.post_processor = post_processor
self.ftp_downlo... | normal | {
"blob_id": "56a41f432d332aaebbde15c52e133eee51b22ce1",
"index": 2833,
"step-1": "<mask token>\n\n\nclass FtpDownloaderPostProcess:\n <mask token>\n <mask token>\n\n @property\n def logger(self):\n return logging.getLogger(__name__)\n\n def iterate(self, *args, **kwargs):\n \"\"\"\nU... | [
4,
6,
7,
8,
9
] |
import json, requests, math, random
#import datagatherer
# Constants:
start_elo = 0 # Starting elo
decay_factor = 0.9 # Decay % between stages
k = 30 # k for elo change
d = 200 # Difference in elo for 75% expected WR
overall_weight = 0.60 # Weigts for different types o... | normal | {
"blob_id": "4f84cf80292e2764ca3e4da79858058850646527",
"index": 8862,
"step-1": "<mask token>\n\n\nclass EloCalculations:\n\n def __init__(self):\n self.teamcolors = {}\n for teamdata in colordata:\n c = teamdata['competitor']\n self.teamcolors[c['abbreviatedName']] = ['#'... | [
5,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open(model_file, 'rb') as fp:
model_data = pkl.load(fp)
<|reserved_special_token_0|>
for i in range(70563, 70564):
imgname = mpi_inf_valid['imgname'][i]
rgb_img = cv2.imread(join(ROOT, imgname))[:, :, ::-1].copy()... | flexible | {
"blob_id": "2540e2752edaedbf2a011a25cb90f220ae770757",
"index": 7611,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(model_file, 'rb') as fp:\n model_data = pkl.load(fp)\n<mask token>\nfor i in range(70563, 70564):\n imgname = mpi_inf_valid['imgname'][i]\n rgb_img = cv2.imread(join(RO... | [
0,
1,
2,
3,
4
] |
'''
Bayesian models for TWAS.
Author: Kunal Bhutani <kunalbhutani@gmail.com>
'''
from scipy.stats import norm
import pymc3 as pm
import numpy as np
from theano import shared
from scipy.stats.distributions import pareto
from scipy import optimize
import theano.tensor as t
def tinvlogit(x):
return t.exp(x) / (1 +... | normal | {
"blob_id": "057140ef1b8db340656b75b3a06cea481e3f20af",
"index": 1689,
"step-1": "<mask token>\n\n\nclass TwoStage(BayesianModel):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TwoStageBF(BayesianModel):\n \"\"\"\n Two Stage Inference.\n\n First stage: Bootstrapped ElasticNet\n Sec... | [
28,
29,
46,
49,
55
] |
import hashlib
import sys
def getHashcode(string):
for i in range(10000000000):
hash_md5 = hashlib.md5(str(i).encode('utf-8'))
res = hash_md5.hexdigest()
if res[0:len(string)] == string:
print(i)
exit()
if __name__ == '__main__':
getHashcode(sys.argv[1])
| normal | {
"blob_id": "4c8e3c21dd478606cf09f2e97dc9deed6597dae5",
"index": 4375,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef getHashcode(string):\n for i in range(10000000000):\n hash_md5 = hashlib.md5(str(i).encode('utf-8'))\n res = hash_md5.hexdigest()\n if res[0:len(string)] =... | [
0,
1,
2,
3
] |
import time
import serial
ser = serial.Serial(
port='/dev/ttyUSB0',
baudrate=9600,
parity=serial.PARITY_NONE,
stopbits=serial.STOPBITS_ONE,
bytesize=serial.EIGHTBITS,
timeout=None
)
ser.close()
ser.open()
if ser.isOpen():
print "Serial is open"
ser.flushInput()
ser.flushOutput()
while True:
mimic = ''
byt... | normal | {
"blob_id": "b112ca3dc603035f340444fa74a7941b1b95f5e5",
"index": 6877,
"step-1": "import time\nimport serial\n\nser = serial.Serial(\n\tport='/dev/ttyUSB0',\n\tbaudrate=9600,\n\tparity=serial.PARITY_NONE,\n\tstopbits=serial.STOPBITS_ONE,\n\tbytesize=serial.EIGHTBITS,\n\ttimeout=None\n)\nser.close()\nser.open()\n... | [
0
] |
from robotcar import RobotCar
import pdb
class RobotCar_Stub(RobotCar):
def forward(self):
print("Forward")
def backward(self):
print("Backward")
def left(self):
print("Left")
def right(self):
print("Right")
def stop(self):
print("Stop")
if __name__ == '__main__':
... | normal | {
"blob_id": "09b2c1e69203f440754e82506b42e7856c94639a",
"index": 8623,
"step-1": "<mask token>\n\n\nclass RobotCar_Stub(RobotCar):\n <mask token>\n\n def backward(self):\n print('Backward')\n\n def left(self):\n print('Left')\n\n def right(self):\n print('Right')\n\n def stop(... | [
5,
6,
7,
8,
9
] |
# Generated by Django 3.0.1 on 2020-01-11 09:50
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('blog', '0005_auto_20200111_1513'),
]
operations = [
migrations.AlterField(
model_name='post',
name='photo',
... | normal | {
"blob_id": "8e8c72362dfb1587150aadaa6b8a0aeb77c3641a",
"index": 1516,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Migration(migrations.Migration):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass Migration(migrations.Migration):\n dependencies = [('blog', '000... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def sol(k):
if k in dp:
return dp[k]
else:
for i in range(7, k + 1):
if dp[i - 3] == 'SK' and dp[i - 1] == 'SK' and dp[i - 4] == 'SK':
dp[i] = 'CY'
else:
dp[i] = 'SK'
return dp[k]
<|reserved_special_... | flexible | {
"blob_id": "4b85479af7d65d208fab08c10afbf66086877329",
"index": 8981,
"step-1": "<mask token>\n\n\ndef sol(k):\n if k in dp:\n return dp[k]\n else:\n for i in range(7, k + 1):\n if dp[i - 3] == 'SK' and dp[i - 1] == 'SK' and dp[i - 4] == 'SK':\n dp[i] = 'CY'\n ... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from contextlib import suppress
import asyncio
import shutil
from aiohttp import web
from bot import app
from var import var
from logger import update_logging_files
loop = asyncio.get_event_loop()
def import_handlers():
from deezer import handlers, callback_handle... | normal | {
"blob_id": "d957fd5fbcdcf2e549323677185eabb8a50536c6",
"index": 5716,
"step-1": "<mask token>\n\n\ndef import_handlers():\n from deezer import handlers, callback_handlers\n from spotify import handlers, integration, callback_handlers\n from vk import handlers, callback_handlers\n from soundcloud imp... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def clean_doc(text, language='english'):
"""
Removes unknown characters and punctuation, change capital to lower letters and remove
stop words. If stem=False
Inputs:
sentence (string): a sting to be cleaned
Returns: a string
"""
tokens = nltk.word_tokenize(text)
tokens =... | flexible | {
"blob_id": "367c3b4da38623e78f2853f9d3464a414ad049c2",
"index": 9596,
"step-1": "<mask token>\n\n\ndef clean_doc(text, language='english'):\n \"\"\"\n\tRemoves unknown characters and punctuation, change capital to lower letters and remove\n\tstop words. If stem=False\n\tInputs:\n\tsentence (string): a sting ... | [
3,
8,
10,
11,
12
] |
<|reserved_special_token_0|>
class OQtSource(object):
<|reserved_special_token_0|>
def __init__(self, *args, **kwargs):
if len(args):
self.source_id = args[0]
if len(args) > 1:
self.source_type = args[1]
if len(kwargs):
self.__dict__.update(... | flexible | {
"blob_id": "8adf8cfc72d5af955bf7509d3573a9bcc7c0845e",
"index": 7537,
"step-1": "<mask token>\n\n\nclass OQtSource(object):\n <mask token>\n\n def __init__(self, *args, **kwargs):\n if len(args):\n self.source_id = args[0]\n if len(args) > 1:\n self.source_type ... | [
2,
4,
5,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
alias_macro = {'class': 'Application', 'method': 'alias_macro', 'doc':
"""
Returns or modifies the macro of a command alias.
""",
'syntax': """
Rhino.AliasMacro (strAlias [, strMacro])
""",
'params': {(0): {'name': 'alias',... | flexible | {
"blob_id": "1574f034ff9b6ddb785e4c54758b2057009198ed",
"index": 7587,
"step-1": "<mask token>\n",
"step-2": "alias_macro = {'class': 'Application', 'method': 'alias_macro', 'doc':\n \"\"\"\n Returns or modifies the macro of a command alias.\n \"\"\",\n 'syntax': \"\"\"\n Rhino.AliasMacr... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class MonitorsS(Base):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def monitors_write_name(self, argument) ->str:
"""Sets the active Monitor object by name."""
result = ctypes.c_char_p(self.dss_obj.MonitorsS(ctype... | flexible | {
"blob_id": "f6f0dcb806fbc1e14c0907dd500fdc6a609a19f7",
"index": 5598,
"step-1": "<mask token>\n\n\nclass MonitorsS(Base):\n <mask token>\n <mask token>\n <mask token>\n\n def monitors_write_name(self, argument) ->str:\n \"\"\"Sets the active Monitor object by name.\"\"\"\n result = cty... | [
3,
4,
6,
7,
9
] |
<|reserved_special_token_0|>
def get_clusters(link, dn, inds, th=0.7):
clst = fcluster(link, criterion='distance', t=th)
return pandas.Series(index=inds, data=clst).iloc[dn['leaves']]
def draw_significant_groups(groups, dn_ax, color='white'):
for group in groups:
rect = patches.Rectangle((group[... | flexible | {
"blob_id": "bfd31d0b80511721ee5117daced04eaf63679fd8",
"index": 2230,
"step-1": "<mask token>\n\n\ndef get_clusters(link, dn, inds, th=0.7):\n clst = fcluster(link, criterion='distance', t=th)\n return pandas.Series(index=inds, data=clst).iloc[dn['leaves']]\n\n\ndef draw_significant_groups(groups, dn_ax, ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
BLUE = '#1A94D6'
GREEN = '#73AD21'
PALE_GREEN = '#BBF864'
PALE_BLUE = '#A2C4DA'
BRIGHT_BLUE = '#04BAE3'
ORANGE = '#FF8000'
DARK_ORANGE = '#E65C00'
LIGHT_ORANGE = '#FFAA3E'
PALE_ORANGE = '#F8C381'
GUAVA = '#FF4F40'
FUSCIA = '#E22EFF'
PALE_FUSCIA = '#DFA0E9'
PU... | flexible | {
"blob_id": "6d8c32fe51fadbe6b6ee14419e1e37c65d4f57bf",
"index": 2508,
"step-1": "<mask token>\n",
"step-2": "BLUE = '#1A94D6'\nGREEN = '#73AD21'\nPALE_GREEN = '#BBF864'\nPALE_BLUE = '#A2C4DA'\nBRIGHT_BLUE = '#04BAE3'\nORANGE = '#FF8000'\nDARK_ORANGE = '#E65C00'\nLIGHT_ORANGE = '#FFAA3E'\nPALE_ORANGE = '#F8C38... | [
0,
1,
2
] |
class MedianFinder:
def __init__(self):
"""
initialize your data structure here.
"""
self.minheap = []
self.maxheap = []
def addNum(self, num: int) -> None:
heapq.heappush (self.maxheap ,-heapq.heappushpop(self.minheap , num) )
if len(self.maxheap) > len... | normal | {
"blob_id": "e7699bb3f6080c78517f11445e2c48a0e40f3332",
"index": 3209,
"step-1": "class MedianFinder:\n <mask token>\n <mask token>\n <mask token>\n",
"step-2": "class MedianFinder:\n <mask token>\n <mask token>\n\n def findMedian(self) ->float:\n if len(self.maxheap) == len(self.minhe... | [
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def square_calculator(user_input):
"""
accepts input from a user to determine the square root
returns the square root of the user input
"""
precision = 1e-12
counter = 0
low = 0
high = user_input
guess = (low + high) / 2.0
... | flexible | {
"blob_id": "2bc20f3410d068e0592c8a45e3c13c0559059f24",
"index": 4498,
"step-1": "<mask token>\n",
"step-2": "def square_calculator(user_input):\n \"\"\"\n accepts input from a user to determine the square root\n returns the square root of the user input\n \"\"\"\n precision = 1e-12\n counter... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri May 24 18:46:26 2019
@author: kiran
"""
import matplotlib.pylab as plt
import pandas as pd
import numpy as np
import statsmodels as sm
from statsmodels.graphics.tsaplots import plot_acf, plot_pacf
from statsmodels.tsa.stattools import acf, pacf
from stat... | normal | {
"blob_id": "8e28135da60f8e11459697c4ae9c63e60c437d7a",
"index": 9501,
"step-1": "<mask token>\n\n\ndef stationarity_test(mylynxts):\n from statsmodels.tsa.stattools import adfuller\n print('Results of Dickey-Fuller Test:')\n df_test = adfuller(mylynxts, autolag='AIC')\n df_output = pd.Series(df_test... | [
1,
2,
3,
4,
5
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import unittest
import xmlrunner
import os
import sys
import glob
import yaml
ASSETS_DIR = ""
class GenerateMachineConfig(unittest.TestCase):
def setUp(self):
self.machine_configs = []
for machine_config_path in glob.glob(
f'{ASSETS_D... | normal | {
"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
] |
#!/usr/bin/python3
"""minimum time time to write operations of copy and paste"""
def minOperations(n):
"""
a method that calculates the fewest number of operations needed
to result in exactly n H characters in the file
"""
if n <= 1:
return 0
"""loop for n number of times"""
for i... | normal | {
"blob_id": "f14b9373e9bf1ad7fe2216dfefc1571f5380fb27",
"index": 6528,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef minOperations(n):\n \"\"\"\n a method that calculates the fewest number of operations needed\n to result in exactly n H characters in the file\n \"\"\"\n if n <= 1:... | [
0,
1,
2
] |
<|reserved_special_token_0|>
class Focusv2(nn.Cell):
def __init__(self, c1, c2, k=1, s=1, p=None, act=True):
super(Focusv2, self).__init__()
self.conv = Conv(c1 * 4, c2, k, s, p, act)
def construct(self, x):
return self.conv(x)
class SiLU(nn.Cell):
def __init__(self):
... | flexible | {
"blob_id": "1ea31a126417c2feb079339aa79f97ea9e38fa40",
"index": 6152,
"step-1": "<mask token>\n\n\nclass Focusv2(nn.Cell):\n\n def __init__(self, c1, c2, k=1, s=1, p=None, act=True):\n super(Focusv2, self).__init__()\n self.conv = Conv(c1 * 4, c2, k, s, p, act)\n\n def construct(self, x):\n ... | [
12,
21,
27,
28,
33
] |
<|reserved_special_token_0|>
class SharedSeleniumExecutionContext:
<|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_speci... | flexible | {
"blob_id": "e75fb023e2e3d3fd258a316a6827b2601c9f4b2d",
"index": 3762,
"step-1": "<mask token>\n\n\nclass SharedSeleniumExecutionContext:\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 to... | [
9,
12,
13,
14,
16
] |
<|reserved_special_token_0|>
def convert_text_to_index(sentences, vocabulary, type):
sentences_index = []
for sentence in sentences:
sentence_index = []
if type == DECODER_INPUT:
sentence_index.extend([vocabulary[STA]])
for word in sentence.split():
if vocabular... | flexible | {
"blob_id": "bd06030ace665a0686c894a863e5c779b6d0931c",
"index": 6447,
"step-1": "<mask token>\n\n\ndef convert_text_to_index(sentences, vocabulary, type):\n sentences_index = []\n for sentence in sentences:\n sentence_index = []\n if type == DECODER_INPUT:\n sentence_index.extend(... | [
3,
6,
7,
8,
9
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(heightmean)
print(heightmedian)
print(heightmode)
print(heightstdev)
<|reserved_special_token_0|>
print(firstpercentage)
print(secondpercentage)
print(thirdpercentage)
<|reserved_special_token_1|>
<|reserved_special_token... | flexible | {
"blob_id": "3f4b05a1d0c4c2a2b085a0265bafbf89b5635e31",
"index": 8021,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(heightmean)\nprint(heightmedian)\nprint(heightmode)\nprint(heightstdev)\n<mask token>\nprint(firstpercentage)\nprint(secondpercentage)\nprint(thirdpercentage)\n",
"step-3": "<mask... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@manufacturers_blueprint.route('/manufacturers', methods=['GET'])
def manufacturers():
manufacturers = manufacturer_repository.select_all()
return render_template('manufacturers/index.html', manufacturers=
manufacturers)
@manufacturers_blueprint.route('/manufacturers/<id... | flexible | {
"blob_id": "841e859feff2151667d70e7bf1829129d1f92cf7",
"index": 9889,
"step-1": "<mask token>\n\n\n@manufacturers_blueprint.route('/manufacturers', methods=['GET'])\ndef manufacturers():\n manufacturers = manufacturer_repository.select_all()\n return render_template('manufacturers/index.html', manufacture... | [
5,
6,
7,
9,
10
] |
#!/usr/bin/env python
import os
import sys
#from io import open
import googleapiclient.errors
import oauth2client
from googleapiclient.errors import HttpError
from . import auth
from . import lib
debug = lib.debug
# modified start
def get_youtube_handler():
"""Return the API Youtube object."""
... | normal | {
"blob_id": "65d08fe1a3f6e5cc2458209706307513d808bdb2",
"index": 3824,
"step-1": "<mask token>\n\n\ndef get_youtube_handler():\n \"\"\"Return the API Youtube object.\"\"\"\n options = {}\n home = os.path.expanduser('~')\n default_credentials = os.path.join(home, '.youtube-upload-credentials.json'\n ... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def test(a):
"""
This function return square of number
"""
return a ** 2
<|reserved_special_token_0|>
<|reserved_special_token_1|>
def test(a):
"""
This function return square of number
"""
return a ** 2
print(test(2))
h... | flexible | {
"blob_id": "7b35a7f28c11be15fe2ac8d6eae4067ac5379f3e",
"index": 3546,
"step-1": "<mask token>\n",
"step-2": "def test(a):\n \"\"\"\n This function return square of number\n \"\"\"\n return a ** 2\n\n\n<mask token>\n",
"step-3": "def test(a):\n \"\"\"\n This function return square of number... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [path('test/<str:name>/', index, name='index'), path(
'ml/setup/', setup_fraud_detection, name='fraud_detection_setup'), path
('ml/verify/', verify_testing_works, name='fraud_verification'), path(
'class/... | flexible | {
"blob_id": "263347d1d445643f9c84e36a8cbb5304581ebaf6",
"index": 3888,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [path('test/<str:name>/', index, name='index'), path(\n 'ml/setup/', setup_fraud_detection, name='fraud_detection_setup'), path\n ('ml/verify/', verify_testing_works, ... | [
0,
1,
2,
3
] |
from rest_framework import serializers
from .models import *
class VisitaSerializer(serializers.HyperlinkedModelSerializer):
class Meta:
model = Visita
fields = ('id', 'usuario', 'lugar', 'fecha_visita', 'hora_visita') | normal | {
"blob_id": "72bbd100a37a86dec7684257f2bec85d7367c009",
"index": 5810,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass VisitaSerializer(serializers.HyperlinkedModelSerializer):\n\n\n class Meta:\n model = Visita\n fields = 'id', 'usuario', 'lugar', 'fecha_visita', 'hora_visita'\... | [
0,
1,
2,
3
] |
class Data(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Time(Data):
def getTime(self):
print('Time:', self.data)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Data(object):
def __init__(self, data):
self.data = data
<|reserved_sp... | flexible | {
"blob_id": "153a33b85cf8b3ef9c742f05b460e94e0c684682",
"index": 1000,
"step-1": "class Data(object):\n <mask token>\n <mask token>\n\n\nclass Time(Data):\n\n def getTime(self):\n print('Time:', self.data)\n\n\n<mask token>\n",
"step-2": "class Data(object):\n\n def __init__(self, data):\n ... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
class Billings(BaseView):
@expose('/')
def index(self):
return redirect(url_for('.billingHistory'))
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@expose('/billingsDetail')
def billingsDetail(self):
sel... | flexible | {
"blob_id": "a9344151a997842972aa68c417a77b3ca80e6cfa",
"index": 3174,
"step-1": "<mask token>\n\n\nclass Billings(BaseView):\n\n @expose('/')\n def index(self):\n return redirect(url_for('.billingHistory'))\n <mask token>\n <mask token>\n <mask token>\n\n @expose('/billingsDetail')\n ... | [
3,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def add(n1, n2):
if n1 == '' or n2 == '':
return 'Invalid Operation'
elif n1 == None or n2 == None:
return 'Invalid Operation'
return str(int(n1) + int(n2))
<|reserved_special_token_0|>
<|reserved... | flexible | {
"blob_id": "7bcbcbe51217b2ea9044a7e4a4bebf315069c92d",
"index": 2953,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef add(n1, n2):\n if n1 == '' or n2 == '':\n return 'Invalid Operation'\n elif n1 == None or n2 == None:\n return 'Invalid Operation'\n return str(int(n1) + in... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'articles'
urlpatterns = [path('', articles_list, name='list'), path('create',
create_article, name='create'), path('<slug:slug>', article_detail,
name='detail')]
<|reserved_special_token_1|>
from django.urls... | flexible | {
"blob_id": "1c222f42c5c0178f97391f1bdc60bba110f3d118",
"index": 9866,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'articles'\nurlpatterns = [path('', articles_list, name='list'), path('create',\n create_article, name='create'), path('<slug:slug>', article_detail,\n name='detail')]\n"... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
app_name = 'jobs'
urlpatterns = [path('', job_view, name='job-index'), path('applicants/',
job_applicants_view, name='job-applicants'), path('posted/',
posted_job_view, name='job-posted'), path('business/',
bussiness_l... | flexible | {
"blob_id": "b88af16693eca10d0bd78fd706389f5468c9b99b",
"index": 144,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp_name = 'jobs'\nurlpatterns = [path('', job_view, name='job-index'), path('applicants/',\n job_applicants_view, name='job-applicants'), path('posted/',\n posted_job_view, name='jo... | [
0,
1,
2,
3
] |
from django import forms
class photoForm(forms.Form):
iso = forms.ChoiceField(label='ISO', choices=[("100", 100),
("200", 200),
("300", 300),
("400", 400),
... | normal | {
"blob_id": "19b55b2de3d2ed16275cef572e3518fbb2457f84",
"index": 8293,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass photoForm(forms.Form):\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass photoForm(forms.Form):\n iso = forms.ChoiceField(label='ISO', choices=[('1... | [
0,
1,
2,
3,
4
] |
#!/usr/bin/env python3
import fileinput
mem = [int(n.strip()) for n in next(fileinput.input()).split()]
size = len(mem)
states = set()
states.add('.'.join(str(n) for n in mem))
part2 = None
steps = 0
while True:
i = mem.index(max(mem))
x = mem[i]
mem[i] = 0
while x > 0:
i += 1
mem[i ... | normal | {
"blob_id": "0e7d4b73cedf961677e6b9ea5303cdb3a5afa788",
"index": 3521,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nstates.add('.'.join(str(n) for n in mem))\n<mask token>\nwhile True:\n i = mem.index(max(mem))\n x = mem[i]\n mem[i] = 0\n while x > 0:\n i += 1\n mem[i % size] ... | [
0,
1,
2,
3,
4
] |
name = ''
while name != 'your name' and name != 'Your name':
print('Please type your name.')
name = input()
print('Thanks!')
#while 1 == 2 or :
# print('Type your name')
# name = input()
# if name == 'your name':
# break
#print('Thanks!')
| normal | {
"blob_id": "f3644b42d1a6c87c6169f8d123dadf6cd209270c",
"index": 2617,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile name != 'your name' and name != 'Your name':\n print('Please type your name.')\n name = input()\nprint('Thanks!')\n",
"step-3": "name = ''\nwhile name != 'your name' and nam... | [
0,
1,
2,
3
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#from setup_env import *
#from mmlibrary import *
from astropy.coordinates import SkyCoord
import astropy.units as u
from mmlibrary import *
import numpy as np
import lal
from scipy.special import logsumexp
import cpnest, cpnest.model
# Oggetto per test: GW170817
#GW =... | normal | {
"blob_id": "fa5468741e9884f6c8bcacaf9d560b5c93ee781a",
"index": 8906,
"step-1": "<mask token>\n\n\nclass completeness(cpnest.model.Model):\n\n def __init__(self, catalog):\n self.names = ['z', 'h', 'om', 'ol']\n self.bounds = [[0.001, 0.012], [0.5, 1.0], [0.04, 1.0], [0.0, 1.0]]\n self.o... | [
2,
9,
13,
15,
16
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on 2021.03.18
setup for package.
@author: zoharslong
"""
from setuptools import setup, find_packages
from os.path import join as os_join, abspath as os_abspath, dirname as os_dirname
here = os_abspath(os_dirname(__file__))
with open(os_join(here, 'README.md')) ... | normal | {
"blob_id": "e0f7837731520ad76ca91d78c20327d1d9bb6d4f",
"index": 9970,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open(os_join(here, 'README.md')) as f:\n README = f.read()\nsetup(name='pyzohar', version='0.1.11', author='zoharslong', author_email=\n 'zoharslong@hotmail.com', description=\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class Crysdata:
def __init__(self, F, cb):
self.start = time.time()
print('Draw timer started')
self.name = F
self.cell = Cell(cb)
self.atoms = readEl(cb)
self.pos = readPos(cb)
c = self.cell
self.ftoc = self.get_fractio... | flexible | {
"blob_id": "e14319e705a3c1cdf85e0a2fe77c211e2afa9baa",
"index": 9880,
"step-1": "<mask token>\n\n\nclass Crysdata:\n\n def __init__(self, F, cb):\n self.start = time.time()\n print('Draw timer started')\n self.name = F\n self.cell = Cell(cb)\n self.atoms = readEl(cb)\n ... | [
20,
32,
41,
42,
51
] |
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | normal | {
"blob_id": "5c291dbc241a80e7f2625ba338a4b9b3a3f3b2d0",
"index": 1119,
"step-1": "<mask token>\n\n\nclass TestRedshiftCreateClusterTrigger:\n <mask token>\n\n @pytest.mark.asyncio\n @async_mock.patch(\n 'airflow.providers.amazon.aws.hooks.redshift_cluster.RedshiftHook.async_conn'\n )\n ... | [
1,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
auth = HTTPBasicAuth('cisco', 'cisco')
headers = {'Accept': 'application/json', 'Content-Type': 'application/json'
}
url = 'https://asav/api/interfaces/physical/GigabitEthernet0_API_S... | flexible | {
"blob_id": "6801d68ebcc6ff52d9be92efeeb8727997a14bbd",
"index": 523,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n auth = HTTPBasicAuth('cisco', 'cisco')\n headers = {'Accept': 'application/json', 'Content-Type': 'application/json'\n }\n url = 'https://asav/... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for one in data:
print(one)
r = requests.post('http://localhost:8080/sumari', json=one)
print(r.text)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
data = json.load(open('dummy_data/data.json'))
for one ... | flexible | {
"blob_id": "8bc40ed4fe1091ecdb40cd55ff9cf53010078823",
"index": 361,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor one in data:\n print(one)\n r = requests.post('http://localhost:8080/sumari', json=one)\n print(r.text)\n",
"step-3": "<mask token>\ndata = json.load(open('dummy_data/data.j... | [
0,
1,
2,
3,
4
] |
import random
def generate_questions(n):
for _ in range(n):
x = random.randint(11, 100)
print(x)
inp = int(input())
if inp == x ** 2:
continue
else:
print('Wrong! the right answer is: {}'.format(x ** 2))
n = int(input())
generate_questions(n)
| normal | {
"blob_id": "e98f28199075e55ddad32d9127f917c982e1e29d",
"index": 8167,
"step-1": "<mask token>\n\n\ndef generate_questions(n):\n for _ in range(n):\n x = random.randint(11, 100)\n print(x)\n inp = int(input())\n if inp == x ** 2:\n continue\n else:\n pr... | [
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@app.route('/', methods=['GET'])
def home():
return Response(response=dumps({'msg': 'App successfull'}), status=200,
mimetype='application/json')
@app.route('/spamapi/', methods=['GET', 'POST'])
def apicall():
try:
predTxt = loads(request.data)
predTxt = ... | flexible | {
"blob_id": "1552d862d3b9df45eda8c08256e8b4437ab08740",
"index": 2641,
"step-1": "<mask token>\n\n\n@app.route('/', methods=['GET'])\ndef home():\n return Response(response=dumps({'msg': 'App successfull'}), status=200,\n mimetype='application/json')\n\n\n@app.route('/spamapi/', methods=['GET', 'POST']... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def train_model(model, DEVICE, patience, n_epochs, csv_record=False):
train_losses = []
valid_losses = []
avg_train_losses = []
avg_valid_losses = []
early_stopping = EarlyStopping(patience=patience, verbose=... | flexible | {
"blob_id": "80531ac3cc247d48ee36bff581925b8f29f9e235",
"index": 8590,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef train_model(model, DEVICE, patience, n_epochs, csv_record=False):\n train_losses = []\n valid_losses = []\n avg_train_losses = []\n avg_valid_losses = []\n early_st... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class H2OShuffleSplit(H2OBaseShuffleSplit):
<|reserved_special_token_0|>
def _iter_indices(self, frame, y=None):
"""Iterate the indices.
Parameters
----------
frame : H2OFrame
The frame to split
y : string, optional (default=... | flexible | {
"blob_id": "c59707ba07c1659d94684c54cdd7bb2658cba935",
"index": 6,
"step-1": "<mask token>\n\n\nclass H2OShuffleSplit(H2OBaseShuffleSplit):\n <mask token>\n\n def _iter_indices(self, frame, y=None):\n \"\"\"Iterate the indices.\n\n Parameters\n ----------\n\n frame : H2OFrame\n... | [
21,
29,
40,
43,
47
] |
<|reserved_special_token_0|>
class Metric(utils.metaclass_insert(abc.ABCMeta, BaseType)):
<|reserved_special_token_0|>
def __init__(self):
"""
This is the basic method initialize the metric object
@ In, none
@ Out, none
"""
BaseType.__init__(self)
self.type = sel... | flexible | {
"blob_id": "5456fb2938ae4d0f69414c153390f86437088114",
"index": 4475,
"step-1": "<mask token>\n\n\nclass Metric(utils.metaclass_insert(abc.ABCMeta, BaseType)):\n <mask token>\n\n def __init__(self):\n \"\"\"\n This is the basic method initialize the metric object\n @ In, none\n @ Out... | [
4,
5,
6,
8,
9
] |
from django.forms import ModelForm
from django import forms
from models import *
from django.forms.widgets import *
class CommentForm(ModelForm):
# tags = TagField(widget=TagAutocomplete())
class Meta:
model=Comment
# fields = ('title', 'description', 'tags', 'enable_comments', 'owner')#, 'first_card' )
# w... | normal | {
"blob_id": "81535b43437f9bcb18973ceaa5c3340ad9bd4f0f",
"index": 4170,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass CommentForm(ModelForm):\n\n\n class Meta:\n model = Comment\n",
"step-3": "from django.forms import ModelForm\nfrom django import forms\nfrom models import *\nfrom d... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class FxBuySell(FxMainPage):
<|reserved_special_token_0|>
def buy(self, amount):
self.log.info('--> ' + inspect.stack()[0][3] + ' started')
if self.driver.find_element_by_xpath(
"//div[@class='visible-input']//input[contains(@id, 'uniqName')]"):
... | flexible | {
"blob_id": "5850be6aef6e4adb36a122cb8e5ffe044b1c9009",
"index": 4589,
"step-1": "<mask token>\n\n\nclass FxBuySell(FxMainPage):\n <mask token>\n\n def buy(self, amount):\n self.log.info('--> ' + inspect.stack()[0][3] + ' started')\n if self.driver.find_element_by_xpath(\n \"//div[... | [
3,
5,
8,
9,
11
] |
def gen_metadata(fn):
metadata = {}
lines = open(fn,'r').readlines()
for line in lines:
line = line.rstrip()
if len(line) == 0:
continue
elif line.startswith('#'):
continue
elif line.startswith('%'):
continue
else:
# Special case RingThresh
firstWord = line.split()[0]
if line.startswith('... | normal | {
"blob_id": "5066c2a5219cf1b233b4985efc7a4eb494b784ca",
"index": 7363,
"step-1": "<mask token>\n",
"step-2": "def gen_metadata(fn):\n metadata = {}\n lines = open(fn, 'r').readlines()\n for line in lines:\n line = line.rstrip()\n if len(line) == 0:\n continue\n elif lin... | [
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": "f2c96b3133137019dc6bd462f096f3b4c5f12648",
"index": 6635,
"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 = [('registered_... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def firstMissingPositive(self, nums: List[int]) ->int:
if not nums:
return 1
maxnum = max(nums)
if maxnum < 1:
... | flexible | {
"blob_id": "09905d4b5ad2e59578d874db171aafb6c42db105",
"index": 8609,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def firstMissingPositive(self, nums: List[int]) ->int:\n if not nums:\n return 1\n maxnum = max(nums)\... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
with open('Aparcamientos.json') as data_file:
data = json.load(data_file)
for x in data['docs']:
if x['TIPOLOGIA'] == 'Cubierto':
print(x['NOMBRE'])
elif x['TIPOLOGIA'] == 'Pabellón de deportes':
print(... | flexible | {
"blob_id": "d111f93144a1d2790470365d0ca31bcea17713d7",
"index": 8766,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwith open('Aparcamientos.json') as data_file:\n data = json.load(data_file)\nfor x in data['docs']:\n if x['TIPOLOGIA'] == 'Cubierto':\n print(x['NOMBRE'])\n elif x['TIPOL... | [
0,
1,
2,
3
] |
#!/usr/bin/env python3
from nmigen import *
from nmigen.build import *
from nmigen_boards.icebreaker import ICEBreakerPlatform
class SSDigitDecoder(Elaboratable):
def __init__(self):
self.i_num = Signal(4)
self.o_disp = Signal(7)
self.lut = {
0: 0b011_1111,
1: 0b000... | normal | {
"blob_id": "74bb511a9ec272020693db65a2e708f3db56931e",
"index": 9954,
"step-1": "<mask token>\n\n\nclass SSDigitDecoder(Elaboratable):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Blinky(Elaboratable):\n\n def __init__(self):\n self.dd0 = SSDigitDecoder()\n self.dd1 = SSDigi... | [
4,
6,
7,
8,
10
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def init_zero_arrays():
radius_arr = np.zeros((ITERATIONS_NUM, TIMESTEPS_NUMB))
dot_radius_arr = np.zeros((ITERATIONS_NUM, TIMESTEPS_NUMB))
dotdot_radius_arr = np.zeros((ITERATIONS_NUM, TIMESTEPS_NUMB))
delta_rad... | flexible | {
"blob_id": "e652196f9c74be6f05c6148de152996e449670ea",
"index": 3059,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef init_zero_arrays():\n radius_arr = np.zeros((ITERATIONS_NUM, TIMESTEPS_NUMB))\n dot_radius_arr = np.zeros((ITERATIONS_NUM, TIMESTEPS_NUMB))\n dotdot_radius_arr = np.zeros... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class JamfExtensionAttributeUploader(JamfUploaderBase):
description = (
'A processor for AutoPkg that will upload an Extension Attribute item to a Jamf Cloud or on-prem server.'
)
input_variables = {'JSS_URL': {'required': True, 'description':
'URL to a Jam... | flexible | {
"blob_id": "31f91e67d0adde0a984a6d162ea5607f06e9208e",
"index": 9876,
"step-1": "<mask token>\n\n\nclass JamfExtensionAttributeUploader(JamfUploaderBase):\n description = (\n 'A processor for AutoPkg that will upload an Extension Attribute item to a Jamf Cloud or on-prem server.'\n )\n input... | [
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
def create_train_kmeans(data, number_of_clusters):
k = KMeans(n_clusters=number_of_clusters, n_jobs=-1, random_state=728)
start = time.time()
k.fit(data)
end = time.time()
print('Training took {} seconds'.format(end - start))
return k
<|reserved_special_token_0|>... | flexible | {
"blob_id": "9c8a213fc8a7397662eebb74d6ee1ad34cb884d9",
"index": 1420,
"step-1": "<mask token>\n\n\ndef create_train_kmeans(data, number_of_clusters):\n k = KMeans(n_clusters=number_of_clusters, n_jobs=-1, random_state=728)\n start = time.time()\n k.fit(data)\n end = time.time()\n print('Training ... | [
1,
3,
4,
6,
7
] |
<|reserved_special_token_0|>
def model_crossover(weights1, weights2):
new_weights = []
assert len(weights1) == len(weights2)
if random.uniform(0, 1) > 0.3:
print('crossover')
for layer in range(len(weights1)):
if layer % 2 == 0:
new_weights.append(weights1[layer... | flexible | {
"blob_id": "bbd5eb1f80843efdd2709aa19a65bf325a88f473",
"index": 8856,
"step-1": "<mask token>\n\n\ndef model_crossover(weights1, weights2):\n new_weights = []\n assert len(weights1) == len(weights2)\n if random.uniform(0, 1) > 0.3:\n print('crossover')\n for layer in range(len(weights1)):... | [
3,
4,
5,
6,
7
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def optimal_points(segments):
segments = sorted(segments, key=attrgetter('end'), reverse=True)
points = []
while len(segments) > 0:
segement = segments.pop()
point = segement.end
while len(seg... | flexible | {
"blob_id": "c007dc2416d3f7c883c44dea5471927ea6f816d6",
"index": 3973,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef optimal_points(segments):\n segments = sorted(segments, key=attrgetter('end'), reverse=True)\n points = []\n while len(segments) > 0:\n segement = segments.pop()\n... | [
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
def getWeightMap():
with open(os.path.join(os.path.dirname(__file__),
'../cells/cubor-base.dict.yaml'), 'r', encoding='utf8') as base:
_lines = base.readlines()
for wunit in _lines:
units = wunit.split('\t')
if len(units) == 3 and len(un... | flexible | {
"blob_id": "e50c1ef7368aabf53bc0cfd45e19101fa1519a1f",
"index": 6245,
"step-1": "<mask token>\n\n\ndef getWeightMap():\n with open(os.path.join(os.path.dirname(__file__),\n '../cells/cubor-base.dict.yaml'), 'r', encoding='utf8') as base:\n _lines = base.readlines()\n for wunit in _lines:... | [
4,
5,
7,
8,
9
] |
'''
The MIT License (MIT)
Copyright (c) 2016 WavyCloud
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, p... | normal | {
"blob_id": "1947bd280234189ed35277c449cd708a204ea7a4",
"index": 6651,
"step-1": "<mask token>\n\n\ndef create_backup(ServerName=None, Description=None):\n \"\"\"\n Creates an application-level backup of a server. While the server is BACKING_UP , the server can not be modified and no additional backup can ... | [
11,
12,
16,
19,
20
] |
<|reserved_special_token_0|>
class SQLSaver(SaverInterface):
def connect(self):
self.logging.info('Logging to %s@%s:%s -p %s', self.config.SQL_USER,
self.config.SQL_HOST, self.config.SQL_DATABASE, self.config.
SQL_PASSWD)
self.db = mysql.connector.connect(host=self.config.... | flexible | {
"blob_id": "e695b9458c0e98521e560dbb291f6f05bda1549f",
"index": 421,
"step-1": "<mask token>\n\n\nclass SQLSaver(SaverInterface):\n\n def connect(self):\n self.logging.info('Logging to %s@%s:%s -p %s', self.config.SQL_USER,\n self.config.SQL_HOST, self.config.SQL_DATABASE, self.config.\n ... | [
10,
11,
12,
13,
16
] |
list = [3, 1, 2, 5, 4, 7, 6]
def sort(list):
for i in range(len(list) - 1):
if list[i] > list[i + 1]:
a = list[i]
list[i] = list[i + 1]
list[i + 1] = a
print(list)
sort(list)
| normal | {
"blob_id": "219929d52b5f1a0690590e83b41d2b4f0b2b3a51",
"index": 336,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef sort(list):\n for i in range(len(list) - 1):\n if list[i] > list[i + 1]:\n a = list[i]\n list[i] = list[i + 1]\n list[i + 1] = a\n ... | [
0,
1,
2,
3
] |
from django.conf.urls import url
from .views.show import show_article, show_articles, export_db
urlpatterns = [
url(r'^$', show_articles, name='index'),
url(r'^article/$', show_article, name='article'),
url(r'^export/$', export_db, name='article'),
]
| normal | {
"blob_id": "9fdc7c1eb68a92451d41313861164a915b85fcee",
"index": 8988,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^$', show_articles, name='index'), url('^article/$',\n show_article, name='article'), url('^export/$', export_db, name='article')]\n",
"step-3": "from django.conf... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=
'Run learning of simple CNN implementation')
parser.add_argument('--model_name', type=str, default='', help=
'Name of the model from ... | flexible | {
"blob_id": "604c94e50b1fb9b5e451c4432113498410a4ac1f",
"index": 5262,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n parser = argparse.ArgumentParser(description=\n 'Run learning of simple CNN implementation')\n parser.add_argument('--model_name', type=str, defa... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class editForm(forms.ModelForm):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Meta:
model = User
fields = 'userna... | flexible | {
"blob_id": "ae8add3adc336c9404cd2aeab4aff81c94c8884e",
"index": 7174,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass editForm(forms.ModelForm):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n model = User\n fields = 'username', 'firs... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Migration(migrations.Migration):
dependencies = [(... | flexible | {
"blob_id": "257f18db95e069c037341d2af372269e988b0a80",
"index": 536,
"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 = [('asset', '000... | [
0,
1,
2,
3,
4
] |
import numpy as np
from sklearn.preprocessing import OneHotEncoder
def formator(value):
return "%.2f" % value
def features_preprocessor(datasetLocation):
data = np.genfromtxt(datasetLocation,delimiter=",",usecols=range(41)) ##!!! usecols = range(41)
encoder = OneHotEncoder(categorical_features=[1,2,3])
encoder.fi... | normal | {
"blob_id": "f50c9aec85418553f4724146045ab7c3c60cbb80",
"index": 4404,
"step-1": "import numpy as np\nfrom sklearn.preprocessing import OneHotEncoder\n\ndef formator(value):\n\treturn \"%.2f\" % value\n\ndef features_preprocessor(datasetLocation):\n\tdata = np.genfromtxt(datasetLocation,delimiter=\",\",usecols=r... | [
0
] |
import sys
import memo
from StringIO import StringIO
import inspect
alternate_dict = {}
alternate_dict['cartesian_to_polar'] = ['cartesian_to_polar','cartesianToPolar','cartesion_to_polar','Polar_Coordinates']
alternate_dict['mercator'] = ['mercator','mercator_projection','mecartor','Mercator','Mercator_projection']
... | normal | {
"blob_id": "eedd909e777a4127b5fd55108805314b3b196dd1",
"index": 5222,
"step-1": "import sys\nimport memo \nfrom StringIO import StringIO\nimport inspect\n\nalternate_dict = {}\nalternate_dict['cartesian_to_polar'] = ['cartesian_to_polar','cartesianToPolar','cartesion_to_polar','Polar_Coordinates']\nalternate_di... | [
0
] |
<|reserved_special_token_0|>
def parse_args():
"""[summary]
Returns:
[type]: [description]
"""
parser = argparse.ArgumentParser()
parser.add_argument('--train_dir', help=
'directory containing spacenet7 train dataset', default=
'/data/spacenet7/spacenet7/train/')
parse... | flexible | {
"blob_id": "71eadf5073b5ed13c7d4a58b2aeb52f550a32238",
"index": 3104,
"step-1": "<mask token>\n\n\ndef parse_args():\n \"\"\"[summary]\n\n Returns:\n [type]: [description]\n \"\"\"\n parser = argparse.ArgumentParser()\n parser.add_argument('--train_dir', help=\n 'directory containin... | [
1,
2,
3,
4,
5
] |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
#
# Code generated by aaz-dev-tools
# --------------------------------... | normal | {
"blob_id": "8197d918b86f0e38fb4320434b61aa4186853af9",
"index": 1131,
"step-1": "<mask token>\n\n\n@register_command('sig gallery-application version show')\nclass Show(AAZCommand):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n ... | [
5,
8,
9,
10,
16
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def rob(self, num):
n = len(num)
if n == 0:
return 0
if n == 1:
return num[0]
f = [0] * n
f[0... | flexible | {
"blob_id": "bca0baaffefed6917939614defadf9960ffa4727",
"index": 8062,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def rob(self, num):\n n = len(num)\n if n == 0:\n return 0\n if n == 1:\n return num... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class ZakerNewsTab(models.Model):
code = models.IntegerField(blank=True, null=True)
tabName = models.CharField(db_column='tabName', max_length=20, blank=
True, null=True)
class Meta:
managed = False
db_table = 'zaker_news_tab'
class BxtZbgg(models.M... | flexible | {
"blob_id": "951fafe9f1b9a3273f30d101831d1e59e26fe85d",
"index": 1535,
"step-1": "<mask token>\n\n\nclass ZakerNewsTab(models.Model):\n code = models.IntegerField(blank=True, null=True)\n tabName = models.CharField(db_column='tabName', max_length=20, blank=\n True, null=True)\n\n\n class Meta:\n ... | [
4,
7,
8,
9,
10
] |
from faker import Faker
from generators.uniform_distribution_gen import UniformDistributionGen
from generators.random_relation_gen import RandomRelationGen
from base.field_base import FieldBase
from generators.normal_distribution_gen import NormalDistributionGen
from generators.first_name_generator import FirstNameGene... | normal | {
"blob_id": "0926606a222e1277935a48ba7f0ea886fb4e298a",
"index": 5234,
"step-1": "<mask token>\n\n\nclass A:\n <mask token>\n\n\nclass B:\n\n def __init__(self) ->None:\n self.alpha: str = ''\n self.C: C = None\n\n\nclass C:\n\n def __init__(self) ->None:\n self.alpha: str = ''\n ... | [
5,
6,
7,
8,
9
] |
from django.shortcuts import render, render_to_response, get_object_or_404, redirect
from .models import Club
from .forms import InputForm
# Create your views here.
def base(request):
return render(request, 'VICHealth_app/base.html')
def index(request):
return render(request, 'VICHealth_app/index.html')
def ... | normal | {
"blob_id": "b0818b545ab47c27c705f2ccfa3b9edb741602f7",
"index": 4757,
"step-1": "<mask token>\n\n\ndef base(request):\n return render(request, 'VICHealth_app/base.html')\n\n\n<mask token>\n\n\ndef check_activity_level(request):\n return render(request, 'VICHealth_app/check_activity_level.html')\n\n\n<mask... | [
2,
3,
5,
6,
7
] |
#https://www.acmicpc.net/problem/2581
def isPrime(x):
if x==1:
return False
for d in range(1,int(x**0.5)):
if x==d+1:
continue
if x%(d+1)==0:
return False
else:
return True
N=int(input())
M=int(input())
sum=0
min=10001
for x in range(N,M+1):
if i... | normal | {
"blob_id": "37d465043eddd34c4453fd7e31b08d0ba58b725f",
"index": 4351,
"step-1": "<mask token>\n",
"step-2": "def isPrime(x):\n if x == 1:\n return False\n for d in range(1, int(x ** 0.5)):\n if x == d + 1:\n continue\n if x % (d + 1) == 0:\n return False\n e... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
np.random.seed(seed)
<|reserved_special_token_0|>
np.random.seed(params['seed'])
<|reserved_special_token_0|>
for i in range(n_goals):
sp_name = possible_objects[i]
if use_dataset_goals:
object_locations[sp_name] =... | flexible | {
"blob_id": "34a456efc72b303aed5f722bb415d30ff62addab",
"index": 7391,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nnp.random.seed(seed)\n<mask token>\nnp.random.seed(params['seed'])\n<mask token>\nfor i in range(n_goals):\n sp_name = possible_objects[i]\n if use_dataset_goals:\n object_lo... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def get(isamAppliance, check_mode=False, force=False):
"""
Get information on existing snapshots
"""
return isamAppliance.invoke_get('Retrieving snapshots', '/snapshots')
<|reserved_special_token_0|>
def search(isamAppliance, comment, check_mode=False, force=False):
... | flexible | {
"blob_id": "23066cd644826bcfef1ef41f154924ac89e12069",
"index": 2081,
"step-1": "<mask token>\n\n\ndef get(isamAppliance, check_mode=False, force=False):\n \"\"\"\n Get information on existing snapshots\n \"\"\"\n return isamAppliance.invoke_get('Retrieving snapshots', '/snapshots')\n\n\n<mask token... | [
9,
12,
13,
14,
17
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def processToken(token):
idPattern1 = re.compile('^([$]|[|]|[a-z])[A-Z0-9]*$')
idPattern2 = re.compile('^([|][A-Z0-9]*[|])$')
intPattern = re.compile('^(%)([0-9]|[A-Fa-f])+$')
fpPattern = re.compile('^[0-9]+[.][0... | flexible | {
"blob_id": "6d543e9e24debaff7640006a3836c59ec0096255",
"index": 5205,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef processToken(token):\n idPattern1 = re.compile('^([$]|[|]|[a-z])[A-Z0-9]*$')\n idPattern2 = re.compile('^([|][A-Z0-9]*[|])$')\n intPattern = re.compile('^(%)([0-9]|[A-Fa-... | [
0,
1,
3,
4,
5
] |
<|reserved_special_token_0|>
class BatchViewSet(viewsets.ModelViewSet):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def perform_destroy(self, instance):
"""
perform_destroy is used to performance a logic delete
"""
instance.is... | flexible | {
"blob_id": "3d0fe0c11e62a03b4701efb19e1c15272ccc985e",
"index": 3315,
"step-1": "<mask token>\n\n\nclass BatchViewSet(viewsets.ModelViewSet):\n <mask token>\n <mask token>\n <mask token>\n\n def perform_destroy(self, instance):\n \"\"\"\n perform_destroy is used to performance a logic ... | [
2,
3,
4,
5,
6
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
urlpatterns = [url('^api/price/(?P<pk>[0-9]+)$', views.product_price), url(
'^api/price_history/(?P<pk>[0-9]+)$', views.product_history)]
urlpatterns = format_suffix_patterns(urlpatterns)
<|reserved_special_token_1|>
from d... | flexible | {
"blob_id": "9816a8265bcdb8c099f599efbe1cfe1a554e71f5",
"index": 8396,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nurlpatterns = [url('^api/price/(?P<pk>[0-9]+)$', views.product_price), url(\n '^api/price_history/(?P<pk>[0-9]+)$', views.product_history)]\nurlpatterns = format_suffix_patterns(urlpat... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def makeimage(text, point_size=100, width=30):
tw = textwrap.TextWrapper(width=width)
text = '\n'.join(a.replace('\\n', '\n') for a in tw.wrap(text))
filename = ''.join(c for c in text.replace(' ', '-') if c.isalpha() or
c.isdigit() or c in ['-', '_'])
os.system(CO... | flexible | {
"blob_id": "a486ec6b27a6b84e454a1bed096be9fe22d91612",
"index": 1561,
"step-1": "<mask token>\n\n\ndef makeimage(text, point_size=100, width=30):\n tw = textwrap.TextWrapper(width=width)\n text = '\\n'.join(a.replace('\\\\n', '\\n') for a in tw.wrap(text))\n filename = ''.join(c for c in text.replace('... | [
2,
3,
4,
5,
6
] |
#!/usr/bin/env python
# coding=utf-8
operators = ['-', '~', '++', '--', '*', '!', '/', '*', '%', '+', '-',
'>', '>=', '<', '<=', '==', '!=', '&&', '||', '=']
types = ['int ', 'double ', 'float ', 'char ']
toDelete = types + ['struct ']
toRepleace = [('printf(', 'print('), ('++', ' += 1'), ('--', ' -= 1')... | normal | {
"blob_id": "082e3350c5827ff2ca909084f2d6a206ae21a7e6",
"index": 3240,
"step-1": "<mask token>\n\n\ndef isChar(c):\n return c > 'a' and c < 'z' or c > 'A' and c < 'Z'\n\n\ndef isOperator(c):\n return c in operators\n\n\ndef isDefun(line):\n return '(' in line and ')' in line and sum([(i in line) for i i... | [
10,
12,
15,
16,
17
] |
<|reserved_special_token_0|>
def decode_contract_call(contract_abi: list, call_data: str):
call_data_bin = decode_hex(call_data)
method_signature = call_data_bin[:4]
for description in contract_abi:
if description.get('type') != 'function':
continue
method_name = normalize_abi_... | flexible | {
"blob_id": "6437cb90ebaed7cf59df780062ebccf77fcef084",
"index": 4123,
"step-1": "<mask token>\n\n\ndef decode_contract_call(contract_abi: list, call_data: str):\n call_data_bin = decode_hex(call_data)\n method_signature = call_data_bin[:4]\n for description in contract_abi:\n if description.get(... | [
1,
2,
3,
4,
5
] |
import os, sys
top=sys.argv[1]
max=int(sys.argv[2])
cnts={}
for d, dirs, files in os.walk(top):
for f in files:
i=f.find(".")
if i ==-1: i=0
suf=f[i:]
rec=cnts.setdefault(suf, [0,0])
fn=d+'/'+f
if os.path.islink(fn):
sz=0
else:
sz=o... | normal | {
"blob_id": "06aa2d261e31dfe2f0ef66dca01c1fe3db1ca94e",
"index": 7940,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor d, dirs, files in os.walk(top):\n for f in files:\n i = f.find('.')\n if i == -1:\n i = 0\n suf = f[i:]\n rec = cnts.setdefault(suf, [0, 0])\... | [
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
@login_required
def lessons_overview(request):
if request.method == 'POST':
if request.user.is_staff:
school_class = SchoolClass.objects.get(id=request.POST['class_id'])
school_class.password = request.POST['class_pwd']
school_class.save()
... | flexible | {
"blob_id": "ee417c5fff858d26ca60a78dffe4cff503a6f2b5",
"index": 6824,
"step-1": "<mask token>\n\n\n@login_required\ndef lessons_overview(request):\n if request.method == 'POST':\n if request.user.is_staff:\n school_class = SchoolClass.objects.get(id=request.POST['class_id'])\n sc... | [
7,
8,
9,
10,
11
] |
def slope_distance(baseElev, elv2, dist_betwn_baseElev_elv2, projectedDistance):
# Calculate the slope and distance between two Cartesian points.
#
# Input:
# For 2-D graphs,
# dist_betwn_baseElev_elv2, Distance between two elevation points (FLOAT)
# baseElev, Elevation of first ... | normal | {
"blob_id": "65b30bbe737b331447235b5c640e9c3f7f6d6f8c",
"index": 5851,
"step-1": "<mask token>\n",
"step-2": "def slope_distance(baseElev, elv2, dist_betwn_baseElev_elv2, projectedDistance\n ):\n import math\n numer = elv2 - baseElev\n denom = dist_betwn_baseElev_elv2\n print(numer, denom)\n ... | [
0,
1,
2
] |
import re
#lines = open("input.1").read()
lines = open("input.2").read()
lines = lines.splitlines()
moves = {}
moves["nw"] = [-1, -1]
moves["ne"] = [ 0, -1]
moves["w"] = [-1, 0]
moves["e"] = [ 1, 0]
moves["sw"] = [ 0, 1]
moves["se"] = [ 1, 1]
tiles = {}
def fliptile(tile):
if tile == "B":
tile = "... | normal | {
"blob_id": "167c36627c7c3377266bde266e610792ba29b3e4",
"index": 3808,
"step-1": "import re\n\n#lines = open(\"input.1\").read()\nlines = open(\"input.2\").read()\nlines = lines.splitlines()\n\nmoves = {}\nmoves[\"nw\"] = [-1, -1]\nmoves[\"ne\"] = [ 0, -1]\nmoves[\"w\"] = [-1, 0]\nmoves[\"e\"] = [ 1, 0]\nmov... | [
0
] |
<|reserved_special_token_0|>
def check_passport(text):
arr = text.split()
dct = {}
for elem in arr:
key = elem.split(':')[0]
val = elem.split(':')[1]
dct[key] = val
try:
if len(dct['byr']) != 4 or int(dct['byr']) < 1920 or int(dct['byr']
) > 2002:
... | flexible | {
"blob_id": "166329c967e83806e3482179a56ac7e5541d5010",
"index": 1589,
"step-1": "<mask token>\n\n\ndef check_passport(text):\n arr = text.split()\n dct = {}\n for elem in arr:\n key = elem.split(':')[0]\n val = elem.split(':')[1]\n dct[key] = val\n try:\n if len(dct['byr'... | [
1,
2,
3,
4,
5
] |
# python /Users/lawrie_6strings/be_professional_pythonist/control_string.py
# -*- coding: utf-8 -*-
# 文字列を３行で書いてみたい場合
"""
どないやねん。
最近の若いもんは、
ようやるやんけ。
"""
# 文字列の特定の文字を取得したい場合は,インデックスを指定してあげることでなんとかする。
word = "what's up"
print(word[0])
# 書式化
name = "lady gaga"
print("こんにちわ、私の名前は {} です。".format(name))
"複数の文字列を挿入することもできる... | normal | {
"blob_id": "0e05eed2d6bc723fd8379e436621a6eba4aa5ab2",
"index": 1929,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(word[0])\n<mask token>\nprint('こんにちわ、私の名前は {} です。'.format(name))\n<mask token>\nprint('{}/{}/{}'.format(year, month, day))\nfor i in range(0, 5):\n print('kamyu'[i])\nprint('aldo... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Event(models.Model):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
... | flexible | {
"blob_id": "170716ccaaf45db2ee974de260883a8d70513f52",
"index": 7583,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Event(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask t... | [
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class CartAdmin(admin.ModelAdmin):
<|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 CartAdmin(admin.ModelAdmin):
list_display = 'user_i... | flexible | {
"blob_id": "222948fb0a991bb6d7faa186c7442a303b88290b",
"index": 7184,
"step-1": "<mask token>\n\n\nclass CartAdmin(admin.ModelAdmin):\n <mask token>\n <mask token>\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass CartAdmin(admin.ModelAdmin):\n list_display = 'user_id', 'good... | [
1,
2,
3,
4,
5
] |
# Python implementation of Bubble Sort
def bubbleSort(arr):
k = len(arr)
# Traverse through all elements
for i in range(k):
# Last i elements are already in correct place
for j in range(0, k - i - 1):
# Swap if element is greater than next element
if arr[j] > arr[j ... | normal | {
"blob_id": "178f9dcd9cbea140abebd509b56979417b5d7503",
"index": 6785,
"step-1": "<mask token>\n",
"step-2": "def bubbleSort(arr):\n k = len(arr)\n for i in range(k):\n for j in range(0, k - i - 1):\n if arr[j] > arr[j + 1]:\n arr[j], arr[j + 1] = arr[j + 1], arr[j]\n\n\n... | [
0,
1,
2,
3,
4
] |
#print 'g'
class Client:
def __init__(self, mechanize, WEBSERVICE_IP,WEBSERVICE_PORT, FORM_INPUT_PATH, dat , data_id = 'data', rasp_id_id = 'rasp_id',password = 'pass'):
self.WEBSERVICE_PORT = WEBSERVICE_PORT
self.mechanize = mechanize
self.WEBSERVICE_IP = WEBSERVICE_IP
self.FORM_INPUT_P... | normal | {
"blob_id": "3366d1d4ecc4cc9f971dff0c8adfbadc5511cc9e",
"index": 5403,
"step-1": "#print 'g'\nclass Client:\n def __init__(self, mechanize, WEBSERVICE_IP,WEBSERVICE_PORT, FORM_INPUT_PATH, dat , data_id = 'data', rasp_id_id = 'rasp_id',password = 'pass'):\n self.WEBSERVICE_PORT = WEBSERVICE_PORT\n ... | [
0
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
CELERY_TIMEZONE = 'Asia/Shanghai'
# CELERY_RESULT_BACKEND='redis://localhost:6379/1'
# BROKER_URL='redis://localhost:6379/2'
BROKER_BACKEND = 'mongodb' # mongodb作为任务队列（或者说是缓存）
<<<<<<< HEAD
BROKER_URL = 'mongodb://10.6.0.149:27017/' ... | normal | {
"blob_id": "9f01483aaa744972fae358577e6f093bd491f357",
"index": 7514,
"step-1": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import\n\nCELERY_TIMEZONE = 'Asia/Shanghai'\n# CELERY_RESULT_BACKEND='redis://localhost:6379/1'\n# BROKER_URL='redis://localhost:6379/2'\nBROKER_BACKEN... | [
0
] |
"""
Name: Thomas Scola
lab1.py
Problem: This function calculates the area of a rectangle
"""
'''def calc_area():'''
def calc_rec_area():
length = eval(input("Enter the length: "))
width = eval(input("Enter the width: "))
area = length * width
print("Area =", area)
def calc_rec_vol():... | normal | {
"blob_id": "076e10b3741542b7137f6ac517dba482f545b123",
"index": 2154,
"step-1": "<mask token>\n\n\ndef calc_rec_area():\n length = eval(input('Enter the length: '))\n width = eval(input('Enter the width: '))\n area = length * width\n print('Area =', area)\n\n\ndef calc_rec_vol():\n lengthh = eval... | [
2,
3,
4,
5,
6
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.