index int64 0 100k | blob_id stringlengths 40 40 | code stringlengths 7 7.27M | steps listlengths 1 1.25k | error bool 2
classes |
|---|---|---|---|---|
8,300 | cf6d3a0fbf2a2daf8432622f780e138784ec505d | import re
IS_WITH_SINGLETON_REGEX = re.compile("(!=|==)\s*(True|False|None)")
def check_is_with_singleton(physical_line, line_number):
match_obj = IS_WITH_SINGLETON_REGEX.search(physical_line)
if match_obj is not None:
offset = match_obj.span()[0]
return (0, 12, (line_number, offset), "Use eq... | [
"import re\n\nIS_WITH_SINGLETON_REGEX = re.compile(\"(!=|==)\\s*(True|False|None)\")\n\ndef check_is_with_singleton(physical_line, line_number):\n match_obj = IS_WITH_SINGLETON_REGEX.search(physical_line)\n\n if match_obj is not None:\n offset = match_obj.span()[0]\n return (0, 12, (line_number,... | false |
8,301 | f317d67b98eab1f0f192fa41f9bcc32b0c1e8eb0 | # Run 'python setup.py build' on cmd
import sys
from cx_Freeze import setup, Executable
import os.path
PYTHON_INSTALL_DIR = os.path.dirname(os.path.dirname(os.__file__))
os.environ['TCL_LIBRARY'] = os.path.join(PYTHON_INSTALL_DIR, 'tcl', 'tcl8.6')
os.environ['TK_LIBRARY'] = os.path.join(PYTHON_INSTALL_DIR, 't... | [
"# Run 'python setup.py build' on cmd\r\n\r\nimport sys\r\nfrom cx_Freeze import setup, Executable\r\n\r\nimport os.path\r\nPYTHON_INSTALL_DIR = os.path.dirname(os.path.dirname(os.__file__))\r\nos.environ['TCL_LIBRARY'] = os.path.join(PYTHON_INSTALL_DIR, 'tcl', 'tcl8.6')\r\nos.environ['TK_LIBRARY'] = os.path.join(P... | false |
8,302 | 3b15767988f1d958fc456f7966f425f93deb9017 | """
Given two strings, a and b, that may or may not be of the same length,
determine the minimum number of character deletions required to make
a and b anagrams. Any characters can be deleted from either of the strings.
"""
from collections import Counter
import math
import os
import random
import re
import sys
# Com... | [
"\"\"\"\nGiven two strings, a and b, that may or may not be of the same length, \ndetermine the minimum number of character deletions required to make\na and b anagrams. Any characters can be deleted from either of the strings.\n\"\"\"\nfrom collections import Counter\nimport math\nimport os\nimport random\nimport ... | false |
8,303 | 97029ac9f05037bf9304dacf86c35f5534d887c4 | class Solution:
def sumSubarrayMins(self, A: List[int]) -> int:
stack = []
prev = [None] * len(A)
for i in range(len(A)):
while stack and A[stack[-1]] >= A[i]:
stack.pop()
prev[i] = stack[-1] if stack else -1
stack.append(i)
stack =... | [
"class Solution:\n def sumSubarrayMins(self, A: List[int]) -> int:\n stack = []\n prev = [None] * len(A)\n for i in range(len(A)):\n while stack and A[stack[-1]] >= A[i]:\n stack.pop()\n prev[i] = stack[-1] if stack else -1\n stack.append(i)\n ... | false |
8,304 | 56d5915d30e85285da549cc69ef25714bacc6f3a | from .alexnet import *
from .lenet import *
from .net import *
from .vae import * | [
"from .alexnet import *\nfrom .lenet import *\nfrom .net import *\nfrom .vae import *",
"from .alexnet import *\nfrom .lenet import *\nfrom .net import *\nfrom .vae import *\n",
"<import token>\n"
] | false |
8,305 | 09420360ddcf2f74c2e130b4e09ae2a959e42e50 | class Solution:
def uncommonFromSentences(self, A: str, B: str) -> List[str]:
word_count = {}
A = A.split()
B = B.split()
whole = A + B
for word in whole:
if word not in word_count:
word_count[word] = 1
else:
word_count[... | [
"class Solution:\n def uncommonFromSentences(self, A: str, B: str) -> List[str]:\n word_count = {}\n A = A.split()\n B = B.split()\n whole = A + B\n for word in whole:\n if word not in word_count:\n word_count[word] = 1\n else:\n ... | false |
8,306 | 0964121d88fad2906311de7532eac52ff784fff6 | """
Main CLI endpoint for GeoCube
"""
import importlib.metadata
import click
from click import group
import geocube.cli.commands as cmd_modules
from geocube import show_versions
CONTEXT_SETTINGS = {
"help_option_names": ["-h", "--help"],
"token_normalize_func": lambda x: x.replace("-", "_"),
}
def check_ve... | [
"\"\"\"\nMain CLI endpoint for GeoCube\n\"\"\"\nimport importlib.metadata\n\nimport click\nfrom click import group\n\nimport geocube.cli.commands as cmd_modules\nfrom geocube import show_versions\n\nCONTEXT_SETTINGS = {\n \"help_option_names\": [\"-h\", \"--help\"],\n \"token_normalize_func\": lambda x: x.rep... | false |
8,307 | dce7fd0c9ed8e1d433f9131a8d137c8dcca4ac56 | #!/bin/python3
# TODO: implement the stack O(N) version
'''
Naive: O(N^3) or sum_{k=1...N}( O(N^2 (N-K)) )
for each size N
for each window of size N in the array
traverse the window to find the max
Naive with heap: O(N^2 log N)
for each size N O(N)
traverse array and accumulate window of size N O(N... | [
"#!/bin/python3\n\n# TODO: implement the stack O(N) version\n\n'''\nNaive: O(N^3) or sum_{k=1...N}( O(N^2 (N-K)) )\n for each size N\n for each window of size N in the array\n traverse the window to find the max\n\nNaive with heap: O(N^2 log N)\n for each size N O(N)\n traverse array and accumulate win... | false |
8,308 | 758e5b9a65132c4bdee4600e79c27f9c0f272312 | import pymysql
import pymssql
import socket
import threading
from time import sleep
address = ('127.0.0.1', 20176)
usermode = {1: 'Wangcz_Students',
2: 'Wangcz_Teachers',
3: 'Wangcz_Admin'
}
def checkuser(username, password, cursor, user_db):
cursor.execute('''select * from %s... | [
"import pymysql\nimport pymssql\nimport socket\nimport threading\nfrom time import sleep\n\naddress = ('127.0.0.1', 20176)\nusermode = {1: 'Wangcz_Students',\n 2: 'Wangcz_Teachers',\n 3: 'Wangcz_Admin'\n }\n\ndef checkuser(username, password, cursor, user_db):\n\n cursor.execute(... | false |
8,309 | dc28c3426f47bef8b691a06d54713bc68696ee44 | #!/usr/bin/env python3
import numpy as np
import os
import random
import pandas as pd
def read_chunk(reader, chunk_size):
data = {}
for i in range(chunk_size):
ret = reader.read_next()
for k, v in ret.items():
if k not in data:
data[k] = []
data[k].appe... | [
"#!/usr/bin/env python3\n\nimport numpy as np\nimport os\nimport random\nimport pandas as pd\n\ndef read_chunk(reader, chunk_size):\n\n data = {}\n for i in range(chunk_size):\n ret = reader.read_next()\n for k, v in ret.items():\n if k not in data:\n data[k] = []\n ... | false |
8,310 | a5eeafef694db04770833a4063358e8f32f467b0 | import os
from typing import List, Optional, Sequence
import boto3
from google.cloud import storage
from ..globals import GLOBALS, LOGGER
def set_gcs_credentials():
if os.path.exists(GLOBALS.google_application_credentials):
return
secrets_client = boto3.client(
"secretsmanager",
reg... | [
"import os\nfrom typing import List, Optional, Sequence\n\nimport boto3\nfrom google.cloud import storage\n\nfrom ..globals import GLOBALS, LOGGER\n\n\ndef set_gcs_credentials():\n if os.path.exists(GLOBALS.google_application_credentials):\n return\n\n secrets_client = boto3.client(\n \"secretsm... | false |
8,311 | 398c28265e61831ba65b4ae2a785e57c0fa5b6d2 |
class Solution:
def toGoatLatin(self, S: str) -> str:
def exchange(str2):
if str2[0] in "aeiou":
str2 = str2+"ma"
else:
str2 = str2[1:]+str2[0]+"ma"
list2 = S.split(" ")
for i in list2:
res.append(exchange(i))
... | [
"\n\n\nclass Solution:\n def toGoatLatin(self, S: str) -> str:\n \n def exchange(str2):\n if str2[0] in \"aeiou\":\n str2 = str2+\"ma\"\n else:\n str2 = str2[1:]+str2[0]+\"ma\"\n\n list2 = S.split(\" \")\n\n for i in list2:\n ... | true |
8,312 | b16ad4bae079159da7ef88b61081d7763d4ae9a0 | #!/usr/bin/env python
##!/work/local/bin/python
##!/work/local/CDAT/bin/python
import sys,getopt
import matplotlib.pyplot as plt
def read():
x = []
y = []
for line in sys.stdin:
v1,v2 = line.split()[:2]
x.append(float(v1))
y.append(float(v2))
return x,y
#def plot(x,y):
def ... | [
"#!/usr/bin/env python\n##!/work/local/bin/python\n##!/work/local/CDAT/bin/python\n\nimport sys,getopt\nimport matplotlib.pyplot as plt\n\n\ndef read():\n\n x = []\n y = []\n for line in sys.stdin:\n v1,v2 = line.split()[:2]\n x.append(float(v1))\n y.append(float(v2))\n return x,y\n... | true |
8,313 | 19f202c32e1cf9f7ab2663827f1f98080f70b83e | from django.conf import settings
from django.http import HttpResponse, HttpResponseBadRequest, HttpResponseForbidden
from django.views.decorators.csrf import csrf_exempt
from linebot import LineBotApi, WebhookParser
from linebot.exceptions import InvalidSignatureError, LineBotApiError
from linebot.models import ... | [
"from django.conf import settings\r\nfrom django.http import HttpResponse, HttpResponseBadRequest, HttpResponseForbidden\r\nfrom django.views.decorators.csrf import csrf_exempt\r\n\r\nfrom linebot import LineBotApi, WebhookParser\r\nfrom linebot.exceptions import InvalidSignatureError, LineBotApiError\r\nfrom lineb... | false |
8,314 | fd6cf903490ff4352e4721282354a68437ecb1e0 | from socket import *
from multiprocessing import Process
import sys
ADDR = ("127.0.0.1", 8888)
udp_socket = socket(AF_INET, SOCK_DGRAM)
# udp_socket.bind(("0.0.0.0",6955)) # udp套接字在一段时间不链接后，会自动重新分配端口，所以需要绑定
def login():
while True:
name = input("请输入昵称（不能重复）")
msg = "LOGIN" + "##" + name
u... | [
"from socket import *\nfrom multiprocessing import Process\nimport sys\n\nADDR = (\"127.0.0.1\", 8888)\nudp_socket = socket(AF_INET, SOCK_DGRAM)\n# udp_socket.bind((\"0.0.0.0\",6955)) # udp套接字在一段时间不链接后，会自动重新分配端口，所以需要绑定\n\n\ndef login():\n while True:\n name = input(\"请输入昵称（不能重复）\")\n msg = \"LOGIN\... | false |
8,315 | 88445d8466d7acbf29d2525c7e322611d66494cd | import sys
if sys.version_info.major == 2:
from itertools import izip
else:
izip = zip
| [
"import sys\nif sys.version_info.major == 2:\n from itertools import izip\nelse:\n izip = zip\n\n",
"import sys\nif sys.version_info.major == 2:\n from itertools import izip\nelse:\n izip = zip\n",
"<import token>\nif sys.version_info.major == 2:\n from itertools import izip\nelse:\n izip = zi... | false |
8,316 | 6e07dcc3f3b8c7fbf8ce8d481b9612e7496967bd | Ylist = ['yes', 'Yes', 'Y', 'y']
Nlist = ['no', 'No', 'N', 'n']
America = ['America', 'america', 'amer', 'rica']
TRW = ['1775', 'The Revolutionary war', 'the Revolutionary war', 'the revolutionary war', 'The Revolutionary War',
'trw', 'Trw', 'TRW']
TCW = ['1861', 'The civil war', 'The civil War', 'The Civil... | [
"Ylist = ['yes', 'Yes', 'Y', 'y']\r\nNlist = ['no', 'No', 'N', 'n']\r\nAmerica = ['America', 'america', 'amer', 'rica']\r\nTRW = ['1775', 'The Revolutionary war', 'the Revolutionary war', 'the revolutionary war', 'The Revolutionary War',\r\n 'trw', 'Trw', 'TRW']\r\nTCW = ['1861', 'The civil war', 'The civil W... | false |
8,317 | fcd2bd91dff3193c661d71ade8039765f8498fd4 | '''
Created on Dec 18, 2011
@author: ppa
'''
import unittest
from ultrafinance.pyTaLib.indicator import Sma
class testPyTaLib(unittest.TestCase):
def setUp(self):
pass
def tearDown(self):
pass
def testSma(self):
sma = Sma(period = 3)
expectedAvgs = [1, 1.5, 2, 3, 4]
... | [
"'''\nCreated on Dec 18, 2011\n\n@author: ppa\n'''\nimport unittest\nfrom ultrafinance.pyTaLib.indicator import Sma\n\nclass testPyTaLib(unittest.TestCase):\n def setUp(self):\n pass\n\n def tearDown(self):\n pass\n\n def testSma(self):\n sma = Sma(period = 3)\n expectedAvgs = [... | false |
8,318 | 0699c9f70f1c16b4cb9837edf7a4ef27f021faec | def modCount(n, m):
if(m <= n):
inBetween = n - m
dividible = []
for x in range(m+1, n):
if(x%m == 0):
dividible.append(x)
return 'There are {} numbers between {} and {} \nand the ones that are dividible by {} are {}'.format(inBetween, m, n, m, dividib... | [
"def modCount(n, m):\n if(m <= n):\n inBetween = n - m\n dividible = []\n for x in range(m+1, n):\n if(x%m == 0):\n dividible.append(x)\n\n return 'There are {} numbers between {} and {} \\nand the ones that are dividible by {} are {}'.format(inBetween, m,... | false |
8,319 | 81c9cabaa611f8e884708d535f0b99ff83ec1c0d | from setuptools import setup
from os import path
this_directory = path.abspath(path.dirname(__file__))
with open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
setup(
name='SumoSound',
packages=['SumoSound'],
version='1.0.2',
license='MIT',
description='A pyt... | [
"from setuptools import setup\nfrom os import path\n\nthis_directory = path.abspath(path.dirname(__file__))\nwith open(path.join(this_directory, 'README.md'), encoding='utf-8') as f:\n long_description = f.read()\n\nsetup(\n name='SumoSound',\n packages=['SumoSound'],\n version='1.0.2',\n license='MIT',\n d... | false |
8,320 | edf704d720abdb09d176937664c9ba98bcd253a5 | message = input()
vowel = 'aeiouAEIOU'
consonant = 'bcdfghjklmnpqrstvwxyz'
consonant += consonant.upper()
vowel_count = 0
consonant_count = 0
for c in message:
if c in vowel:
vowel_count += 1
elif c in consonant:
consonant_count += 1
print(vowel_count, consonant_count)
| [
"message = input()\n\nvowel = 'aeiouAEIOU'\nconsonant = 'bcdfghjklmnpqrstvwxyz'\nconsonant += consonant.upper()\n\nvowel_count = 0\nconsonant_count = 0\n\nfor c in message:\n if c in vowel:\n vowel_count += 1\n elif c in consonant:\n consonant_count += 1\n\nprint(vowel_count, consonant_count)\n"... | false |
8,321 | ad9bb34fdb05ab885f4871693729449f3618603a | #Script to extract features from chess score data file stockfish.csv
import numpy as np
import pandas as pd
#Load in and format raw chess game scoring data
raw_scores = [line.strip().split(",")[1].split() for line in open("stockfish.csv")][1:]
#Initialize containers for features to extract
game_length = []
average_sc... | [
"#Script to extract features from chess score data file stockfish.csv\nimport numpy as np\nimport pandas as pd\n\n#Load in and format raw chess game scoring data\nraw_scores = [line.strip().split(\",\")[1].split() for line in open(\"stockfish.csv\")][1:]\n\n#Initialize containers for features to extract\ngame_lengt... | false |
8,322 | 45dc9d362a2ddfd408f93452bda0b7338057ca81 | from django.db import models
from django.utils import timezone
from pprint import pprint
class Cast(models.Model):
name = models.CharField(max_length=50, blank=True, null=True)
image = models.ImageField(upload_to='cast', blank=True, null=True)
description = models.CharField(max_length=400, blank=True, null... | [
"from django.db import models\nfrom django.utils import timezone\nfrom pprint import pprint\n\nclass Cast(models.Model):\n name = models.CharField(max_length=50, blank=True, null=True)\n image = models.ImageField(upload_to='cast', blank=True, null=True)\n description = models.CharField(max_length=400, blan... | false |
8,323 | 19221823f14cf06a55d445fc241fc04e64e5873c | # This is the template file for Lab #5, Task #1
import numpy
import lab5
def digitize(samples,threshold):
return 1*(samples > threshold)
class ViterbiDecoder:
# given the constraint length and a list of parity generator
# functions, do the initial set up for the decoder. The
# following useful instance ... | [
"# This is the template file for Lab #5, Task #1\nimport numpy\nimport lab5\n\ndef digitize(samples,threshold):\n\treturn 1*(samples > threshold)\n\nclass ViterbiDecoder:\n # given the constraint length and a list of parity generator\n # functions, do the initial set up for the decoder. The\n # following ... | true |
8,324 | 32227029cb4e852536611f7ae5dec5118bd5e195 | # SPDX-License-Identifier: Apache-2.0
"""
.. _example-lightgbm-pipe:
Convert a pipeline with a LightGbm model
========================================
.. index:: LightGbm
*sklearn-onnx* only converts *scikit-learn* models into *ONNX*
but many libraries implement *scikit-learn* API so that their models
can be inclu... | [
"# SPDX-License-Identifier: Apache-2.0\n\n\n\"\"\"\n.. _example-lightgbm-pipe:\n\nConvert a pipeline with a LightGbm model\n========================================\n\n.. index:: LightGbm\n\n*sklearn-onnx* only converts *scikit-learn* models into *ONNX*\nbut many libraries implement *scikit-learn* API so that their... | false |
8,325 | 1e292872c0c3c7f4ec0115f0769f9145ef595ead | # -*- coding: utf-8 -*-
# __author__ = 'XingHuan'
# 3/27/2018
import os
import imageio
import time
os.environ['IMAGEIO_FFMPEG_EXE'] = 'D:/Program Files/ffmpeg-3.4/bin/ffmpeg.exe'
reader = imageio.get_reader('test1080.mov')
print reader
fps = reader.get_meta_data()['fps']
print fps
# for i, im in enumerate(reader)... | [
"# -*- coding: utf-8 -*-\n# __author__ = 'XingHuan'\n# 3/27/2018\n\nimport os\nimport imageio\nimport time\n\nos.environ['IMAGEIO_FFMPEG_EXE'] = 'D:/Program Files/ffmpeg-3.4/bin/ffmpeg.exe'\n\n\nreader = imageio.get_reader('test1080.mov')\nprint reader\nfps = reader.get_meta_data()['fps']\nprint fps\n\n\n# for i, i... | true |
8,326 | e265b2b2ccc0841ccb8b766de4ae2a869f2d280d | import tensorflow as tf
from keras import layers, Model, Input
from keras.utils import Progbar, to_categorical
from keras.datasets.mnist import load_data
import numpy as np
import matplotlib.pyplot as plt
import config
import datetime
img_height, img_width, _ = config.IMAGE_SHAPE
(X, Y), (_, _) = load_data()
X = X.re... | [
"import tensorflow as tf\nfrom keras import layers, Model, Input\nfrom keras.utils import Progbar, to_categorical\nfrom keras.datasets.mnist import load_data\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport config\nimport datetime\n\nimg_height, img_width, _ = config.IMAGE_SHAPE\n\n(X, Y), (_, _) = load... | false |
8,327 | 950b2906853c37cdeaa8ed1076fff79dbe99b6f8 | import typing
import torch.nn as nn
from .torch_utils import get_activation, BatchNorm1d
from dna.models.torch_modules.torch_utils import PyTorchRandomStateContext
class Submodule(nn.Module):
def __init__(
self, layer_sizes: typing.List[int], activation_name: str, use_batch_norm: bool, use_skip: bo... | [
"import typing\n\nimport torch.nn as nn\n\nfrom .torch_utils import get_activation, BatchNorm1d\nfrom dna.models.torch_modules.torch_utils import PyTorchRandomStateContext\n\n\nclass Submodule(nn.Module):\n\n def __init__(\n self, layer_sizes: typing.List[int], activation_name: str, use_batch_norm: bo... | false |
8,328 | 4e94e9e2b45d3786aa86be800be882cc3d5a80b5 | """
table.py [-m] base1 base2 ... baseN
Combines output from base1.txt, base2.txt, etc., which are created by
the TestDriver (such as timcv.py) output, and displays tabulated
comparison statistics to stdout. Each input file is represented by
one column in the table.
Optional argument -m shows a final column with the m... | [
"\"\"\"\ntable.py [-m] base1 base2 ... baseN\nCombines output from base1.txt, base2.txt, etc., which are created by\nthe TestDriver (such as timcv.py) output, and displays tabulated\ncomparison statistics to stdout. Each input file is represented by\none column in the table.\nOptional argument -m shows a final col... | false |
8,329 | 0ac471d2cb30a21c1246106ded14cdc4c06d2d40 | #!/usr/bin/env python3
from collections import OrderedDict
import torch.nn as nn
from fairseq.models import FairseqMultiModel, register_model
from pytorch_translate import common_layers, utils
@register_model("multilingual")
class MultilingualModel(FairseqMultiModel):
"""
To use, you must extend this class ... | [
"#!/usr/bin/env python3\n\nfrom collections import OrderedDict\n\nimport torch.nn as nn\nfrom fairseq.models import FairseqMultiModel, register_model\nfrom pytorch_translate import common_layers, utils\n\n\n@register_model(\"multilingual\")\nclass MultilingualModel(FairseqMultiModel):\n \"\"\"\n To use, you m... | false |
8,330 | 4dda122a8c3a2aab62bb202945f6fb9cb73cf772 | from numpy import sqrt
def Schout2ConTank(a, b, d):
# This function converts parameters from Schoutens notation to Cont-Tankov
# notation
## Code
th = d * b / sqrt(a ** 2 - b ** 2)
k = 1 / (d * sqrt(a ** 2 - b ** 2))
s = sqrt(d / sqrt(a ** 2 - b ** 2))
return th, k, s
| [
"from numpy import sqrt\n\n\ndef Schout2ConTank(a, b, d):\n # This function converts parameters from Schoutens notation to Cont-Tankov\n # notation\n\n ## Code\n th = d * b / sqrt(a ** 2 - b ** 2)\n k = 1 / (d * sqrt(a ** 2 - b ** 2))\n s = sqrt(d / sqrt(a ** 2 - b ** 2))\n return th, k, s\n",
... | false |
8,331 | c9f1768e2f2dd47d637c2e577067eb6cd163e972 | from functools import partial
def power_func(x, y, a=1, b=0):
return a*x**y + b
new_func = partial(power_func, 2, a=4)
print(new_func(4, b=1))
print(new_func(1))
| [
"from functools import partial\n\n\ndef power_func(x, y, a=1, b=0):\n return a*x**y + b\n\n\nnew_func = partial(power_func, 2, a=4)\n\nprint(new_func(4, b=1))\nprint(new_func(1))\n",
"from functools import partial\n\n\ndef power_func(x, y, a=1, b=0):\n return a * x ** y + b\n\n\nnew_func = partial(power_fun... | false |
8,332 | 7eefcfdb9682cb09ce2d85d11aafc04977016ba4 | from urllib import request, parse
import pandas as pd
import json
import os
class BusInfo:
url = 'https://api-tokyochallenge.odpt.org/api/v4/odpt:Bus'
url_busstop = 'https://api-tokyochallenge.odpt.org/api/v4/odpt:BusstopPole.json'
url_routes = 'https://api-tokyochallenge.odpt.org/api/v4/odpt:BusroutePatt... | [
"from urllib import request, parse\nimport pandas as pd\nimport json\nimport os\n\nclass BusInfo:\n\n url = 'https://api-tokyochallenge.odpt.org/api/v4/odpt:Bus'\n url_busstop = 'https://api-tokyochallenge.odpt.org/api/v4/odpt:BusstopPole.json'\n url_routes = 'https://api-tokyochallenge.odpt.org/api/v4/odp... | false |
8,333 | 7e23f5598ccfe9aff74d43eb662f860b0404b7ec | #!/usr/bin/env python
"""
A package that determines the current day of the week.
"""
from datetime import date
import calendar
# Set the first day of the week as Sunday.
calendar.firstday(calendar.SUNDAY)
def day_of_the_week(arg):
"""
Returns the current day of the week.
"""
if arg == "day":
... | [
"#!/usr/bin/env python\n\n\"\"\"\nA package that determines the current day of the week.\n\"\"\"\n\nfrom datetime import date \nimport calendar\n\n# Set the first day of the week as Sunday.\n\ncalendar.firstday(calendar.SUNDAY)\n\ndef day_of_the_week(arg):\n\n\t\"\"\"\n\tReturns the current day of the week.\n\t\"\"... | true |
8,334 | 61c2a6499dd8de25045733f9061d660341501314 | #!/usr/bin/python2
import gmpy2
p = 24659183668299994531
q = 28278904334302413829
e = 11
c = 589000442361955862116096782383253550042
t = (p-1)*(q-1)
n = p*q
# returns d such that e * d == 1 modulo t, or 0 if no such y exists.
d = gmpy2.invert(e,t)
# Decryption
m = pow(c,d,n)
print "Solved ! m = %d" % m
| [
"#!/usr/bin/python2\nimport gmpy2\n\np = 24659183668299994531\nq = 28278904334302413829\ne = 11\nc = 589000442361955862116096782383253550042\nt = (p-1)*(q-1)\nn = p*q\n\n# returns d such that e * d == 1 modulo t, or 0 if no such y exists.\nd = gmpy2.invert(e,t)\n\n# Decryption\nm = pow(c,d,n)\nprint \"Solved ! ... | true |
8,335 | 4a8fa195a573f8001e55b099a8882fe71bcca233 | """storeproject URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-... | [
"\"\"\"storeproject URL Configuration\n\nThe `urlpatterns` list routes URLs to views. For more information please see:\n https://docs.djangoproject.com/en/3.1/topics/http/urls/\nExamples:\nFunction views\n 1. Add an import: from my_app import views\n 2. Add a URL to urlpatterns: path('', views.home, name... | false |
8,336 | 8c71bc5d53bf5c4cb20784659eddf8a97efb86ef | # #----------------------------------------#
# 3.4
#
# Question:
# Write a program which can map() to make a list whose elements are square of elements in [1,2,3,4,5,6,7,8,9,10].
#
| [
"#\t#----------------------------------------#\n#\t3.4\n#\t\n#\tQuestion:\n#\tWrite a program which can map() to make a list whose elements are square of elements in [1,2,3,4,5,6,7,8,9,10].\n#\t\n",
""
] | false |
8,337 | 98fb70e1911522365292c86603481656e7b86d73 | from django.contrib import admin
from .models import CarouselImage, Budget
admin.site.register(CarouselImage)
admin.site.register(Budget)
| [
"from django.contrib import admin\nfrom .models import CarouselImage, Budget\n\nadmin.site.register(CarouselImage)\n\nadmin.site.register(Budget)\n",
"from django.contrib import admin\nfrom .models import CarouselImage, Budget\nadmin.site.register(CarouselImage)\nadmin.site.register(Budget)\n",
"<import token>\... | false |
8,338 | 30986eb0a6cd82f837dd14fb383529a6a41def9a | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('auth', '0001_initial'),
('c4c_app', '0006_c4cjob_complete'),
]
operations = [
migrations.AlterModelOptions(
... | [
"# -*- coding: utf-8 -*-\nfrom __future__ import unicode_literals\n\nfrom django.db import models, migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('auth', '0001_initial'),\n ('c4c_app', '0006_c4cjob_complete'),\n ]\n\n operations = [\n migrations.AlterMod... | false |
8,339 | e560f2f202e477822729d1361b8d7ef7831a00e6 | # ------------------------------------------
#
# Project: VEXcode VR Maze Solver
# Author: Hyunwoo Choi
# Created: January 12 2021
# Description: Solves a VEXcode VR maze using the right hand rule
#
# ------------------------------------------
# Library imports
from vexcode import *
#main
def main... | [
"# ------------------------------------------\n# \n# \tProject: VEXcode VR Maze Solver\n#\tAuthor: Hyunwoo Choi\n#\tCreated: January 12 2021\n#\tDescription: Solves a VEXcode VR maze using the right hand rule\n# \n# ------------------------------------------\n\n# Library imports\nfrom vexcode impor... | false |
8,340 | 800573786913ff2fc37845193b5584a0a815533f | # use local image
import io
import os
from google.cloud import vision
from google.oauth2 import service_account
creds = service_account.Credentials.from_service_account_file('./key.json')
client = vision.ImageAnnotatorClient(
credentials=creds,
)
# The name of the image file to annotate
file_name = os.path.joi... | [
"# use local image\n\nimport io\nimport os\n\nfrom google.cloud import vision\nfrom google.oauth2 import service_account\n\ncreds = service_account.Credentials.from_service_account_file('./key.json')\n\nclient = vision.ImageAnnotatorClient(\n credentials=creds,\n)\n\n# The name of the image file to annotate\nfil... | false |
8,341 | 75837ab778e94693151de1c17b59e12f8b2336d3 | def divide(file):
index = 0
head = ''
while True:
if file[index].isnumeric():
head_index = index
break
if file[index].isalpha():
head += file[index].lower()
else:
head += file[index]
index += 1
while True:
if index ... | [
"def divide(file):\n index = 0\n head = ''\n while True:\n\n if file[index].isnumeric():\n head_index = index\n break\n if file[index].isalpha():\n head += file[index].lower()\n else:\n head += file[index]\n index += 1\n while True:... | false |
8,342 | b7632cc7d8fc2f9096f7a6bb61c471dc61689f70 | import pandas as pd
import numpy as np
import urllib.request
import urllib.parse
import json
def predict(input_text):
URL = "http://127.0.0.1:8000/api/v1/predict/"
values = {
"format": "json",
"input_text": input_text,
}
data = urllib.parse.urlencode({'input_text': i... | [
"import pandas as pd\r\nimport numpy as np\r\nimport urllib.request\r\nimport urllib.parse\r\nimport json\r\n\r\ndef predict(input_text):\r\n URL = \"http://127.0.0.1:8000/api/v1/predict/\"\r\n values = {\r\n \"format\": \"json\",\r\n \"input_text\": input_text,\r\n }\r\n data = ur... | false |
8,343 | 1c8145007edb09d77a3b15de5c34d0bc86c0ba97 | import argparse # for handling command line arguments
import collections # for container types like OrderedDict
import configparser
import hashlib # for SHA-1
import os
import re
import sys
import zlib # git compresses everything using zlib
argparser = argparse.ArgumentParser(description="The stupid content tracker")
... | [
"import argparse # for handling command line arguments\nimport collections # for container types like OrderedDict\nimport configparser\nimport hashlib # for SHA-1\nimport os\nimport re\nimport sys\nimport zlib # git compresses everything using zlib\n\nargparser = argparse.ArgumentParser(description=\"The stupid con... | true |
8,344 | 257a4d0b0c713624ea8452dbfd6c5a96c9a426ad | import pymysql
import logging
import socket
from models.platformconfig import Pconfig
class ncbDB(Pconfig):
# I have to retrieve basic configuration attributes, listed below, from system config file
# on ApplSrv, for example : /etc/ncb_applsrv/ncb_applsrv.conf
hostname = None
conferenceMediaStoragePa... | [
"import pymysql\nimport logging\nimport socket\nfrom models.platformconfig import Pconfig\n\n\nclass ncbDB(Pconfig):\n # I have to retrieve basic configuration attributes, listed below, from system config file\n # on ApplSrv, for example : /etc/ncb_applsrv/ncb_applsrv.conf\n\n hostname = None\n conferen... | false |
8,345 | 15ca54aff4c688733c9c514ba5856e6bf29a3292 | """
Compare 1-D analytical sphere solution to 1-D numerical and 3-D Comsol solutions
for transient heat conduction in solid sphere with constant k and Cp.
Assumptions:
Convection boundary condition at surface.
Symmetry about the center of the solid.
Heat transfer via radiation assumed to be negligable.
Particle does n... | [
"\"\"\"\nCompare 1-D analytical sphere solution to 1-D numerical and 3-D Comsol solutions\nfor transient heat conduction in solid sphere with constant k and Cp.\n\nAssumptions:\nConvection boundary condition at surface.\nSymmetry about the center of the solid.\nHeat transfer via radiation assumed to be negligable.\... | false |
8,346 | 3b41bd59c133bb04dae3aa48dc0699388d5bf3d4 | import os
import json
import random
chapter_mode = True
setname = 'test_other'
use_chapter = '_chapter'
minlen = 1000
maxlen = 1000
context = '_1000'
info_json = 'bookinfo{}_{}{}.json'.format(use_chapter, setname, context)
book_ID_mapping = {}
with open('speaker_book.txt') as fin:
for line in fin:
elems ... | [
"import os\nimport json\nimport random\n\n\nchapter_mode = True\nsetname = 'test_other'\nuse_chapter = '_chapter'\nminlen = 1000\nmaxlen = 1000\ncontext = '_1000'\n\ninfo_json = 'bookinfo{}_{}{}.json'.format(use_chapter, setname, context)\nbook_ID_mapping = {}\nwith open('speaker_book.txt') as fin:\n for line in... | false |
8,347 | 27fc11ae68531c7dbafdcf134f0eef019210e2de | from django import forms
from django.forms import widgets
from tsuru_dashboard import settings
import requests
class ChangePasswordForm(forms.Form):
old = forms.CharField(widget=forms.PasswordInput())
new = forms.CharField(widget=forms.PasswordInput())
confirm = forms.CharField(widget=forms.PasswordInput... | [
"from django import forms\nfrom django.forms import widgets\nfrom tsuru_dashboard import settings\n\nimport requests\n\n\nclass ChangePasswordForm(forms.Form):\n old = forms.CharField(widget=forms.PasswordInput())\n new = forms.CharField(widget=forms.PasswordInput())\n confirm = forms.CharField(widget=form... | false |
8,348 | 73e6930c6866d3ccdbccec925bfc5e7e4702feb9 | """
eulerian_path.py
An Eulerian path, also called an Euler chain, Euler trail, Euler walk, or "Eulerian" version of any of these
variants, is a walk on the graph edges of a graph which uses each graph edge in the original graph exactly once.
A connected graph has an Eulerian path iff it has at most two graph vertices ... | [
"\"\"\"\neulerian_path.py\nAn Eulerian path, also called an Euler chain, Euler trail, Euler walk, or \"Eulerian\" version of any of these\nvariants, is a walk on the graph edges of a graph which uses each graph edge in the original graph exactly once.\nA connected graph has an Eulerian path iff it has at most two g... | false |
8,349 | c00a8bfec46ed829e413257bf97c44add564080d | #!/usr/bin/env python
import rospy
import rosnode
import csv
import datetime
import rosbag
import sys
import os
import matplotlib.pyplot as plt
import argparse
import math
from math import hypot
import numpy as np
from sensor_msgs.msg import LaserScan
from std_msgs.msg import String
import yaml as yaml
start_time = Non... | [
"#!/usr/bin/env python\nimport rospy\nimport rosnode\nimport csv\nimport datetime\nimport rosbag\nimport sys\nimport os\nimport matplotlib.pyplot as plt\nimport argparse\nimport math\nfrom math import hypot\nimport numpy as np\nfrom sensor_msgs.msg import LaserScan\nfrom std_msgs.msg import String\nimport yaml as y... | true |
8,350 | a52762fb13c04ced07a41a752578c4173d1eac42 | from queue import Queue
class Node():
def __init__(self, value, left=None, right=None):
self.value = value
self.left = left
self.right = right
def array_to_tree_dfs(array):
n = len(array)
if n>0:
root = Node(array[0])
def dfs(node, index):
# if index >= n:
... | [
"from queue import Queue\n\nclass Node():\n def __init__(self, value, left=None, right=None):\n self.value = value\n self.left = left\n self.right = right\n\n\ndef array_to_tree_dfs(array):\n n = len(array)\n if n>0:\n root = Node(array[0])\n\n def dfs(node, index):\n ... | false |
8,351 | 12396130dc52866cc54d6dc701cf0f9a41a168b6 | from PyInstaller.utils.hooks import collect_data_files
hiddenimports = ['sklearn.utils.sparsetools._graph_validation',
'sklearn.utils.sparsetools._graph_tools',
'sklearn.utils.lgamma',
'sklearn.utils.weight_vector']
datas = collect_data_files('sklearn') | [
"from PyInstaller.utils.hooks import collect_data_files\n\nhiddenimports = ['sklearn.utils.sparsetools._graph_validation',\n 'sklearn.utils.sparsetools._graph_tools',\n 'sklearn.utils.lgamma',\n 'sklearn.utils.weight_vector']\n\ndatas = collect_data_files('sklearn')",... | false |
8,352 | 8ca16947054b681a5f43d8b8029191d031d3a218 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author: Swking
@File : ZDT.py
@Date : 2018/12/28
@Desc :
"""
import numpy as np
class ZDT1:
def __init__(self):
self.dimension = 30
self.objFuncNum = 2
self.isMin = True
self.min = np.zeros(self.dimension)
self.max = np.zeros(self.dimension) + 1
self.s... | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@Author: Swking\n@File : ZDT.py\n@Date : 2018/12/28\n@Desc : \n\"\"\"\nimport numpy as np\nclass ZDT1:\n\tdef __init__(self):\n\t\tself.dimension = 30\n\t\tself.objFuncNum = 2\n\t\tself.isMin = True\n\t\tself.min = np.zeros(self.dimension)\n\t\tself.max = ... | false |
8,353 | 55ffcf5e6120cc07da461e30979dd8a36a599bee | #-------------------------------------------------------------------------------
# rtlconverter.py
#
# PyCoRAM RTL Converter
#
# Copyright (C) 2013, Shinya Takamaeda-Yamazaki
# License: Apache 2.0
#-------------------------------------------------------------------------------
import sys
import os
import subprocess
im... | [
"#-------------------------------------------------------------------------------\n# rtlconverter.py\n# \n# PyCoRAM RTL Converter\n#\n# Copyright (C) 2013, Shinya Takamaeda-Yamazaki\n# License: Apache 2.0\n#-------------------------------------------------------------------------------\nimport sys\nimport os\nimpor... | false |
8,354 | 2e6f04c3ff3e47a2c3e9f6a7d93e7ce2955a2756 | from __future__ import print_function
from __future__ import absolute_import
from builtins import str
from builtins import range
from builtins import object
import hashlib
from xml.sax.saxutils import escape
from struct import unpack, pack
import textwrap
import json
from .anconf import warning, error, CONF, enable_c... | [
"from __future__ import print_function\nfrom __future__ import absolute_import\n\nfrom builtins import str\nfrom builtins import range\nfrom builtins import object\nimport hashlib\nfrom xml.sax.saxutils import escape\nfrom struct import unpack, pack\nimport textwrap\n\nimport json\nfrom .anconf import warning, erro... | false |
8,355 | 1deab16d6c574bf532c561b8d6d88aac6e5d996c | # Importing datasets wrangling libraries
import numpy as np
import pandas as pd
incd_data = pd.read_csv('data/Cancer/incd.csv', usecols=['State', 'FIPS', 'Age-Adjusted Incidence Rate([rate note]) - cases per 100,000', 'Average Annual Count', 'Recent Trend'])
print(incd_data.columns)
| [
"# Importing datasets wrangling libraries\nimport numpy as np\nimport pandas as pd\n\nincd_data = pd.read_csv('data/Cancer/incd.csv', usecols=['State', 'FIPS', 'Age-Adjusted Incidence Rate([rate note]) - cases per 100,000', 'Average Annual Count', 'Recent Trend'])\nprint(incd_data.columns)\n",
"import numpy as np... | false |
8,356 | c0f4f9eef12d99d286f5ad56f6554c5910b7cc71 | users = {
'Students': [
{'first_name': 'Michael', 'last_name' : 'Jordan'},
{'first_name' : 'John', 'last_name' : 'Rosales'},
{'first_name' : 'Mark', 'last_name' : 'Guillen'},
{'first_name' : 'KB', 'last_name' : 'Tonel'}
],
'Instructors': [
{'first_name' : 'Michael', 'last_name' : 'Choi'},
... | [
"users = {\n 'Students': [\n {'first_name': 'Michael', 'last_name' : 'Jordan'},\n {'first_name' : 'John', 'last_name' : 'Rosales'},\n {'first_name' : 'Mark', 'last_name' : 'Guillen'},\n {'first_name' : 'KB', 'last_name' : 'Tonel'}\n ],\n 'Instructors': [\n {'first_name' : 'Michael', 'last_name... | true |
8,357 | 4d0b08f8ca77d188aa218442ac0689fd2c057a89 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import os, shutil, time, pickle, warnings, logging
import yaml
from sklearn import preprocessing
from sklearn.model_selection import StratifiedKFold, KFold
from sklearn import metrics
from scipy.special import erfinv
from scipy.stats import mode
wa... | [
"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport os, shutil, time, pickle, warnings, logging\nimport yaml\nfrom sklearn import preprocessing\nfrom sklearn.model_selection import StratifiedKFold, KFold\nfrom sklearn import metrics\nfrom scipy.special import erfinv\nfrom scipy.stats i... | false |
8,358 | 84d096a51fa052ee210e975ab61c0cbbf05bc5ae | class Day8MemoryManeuver:
def __init__(self, use_reference_count=False):
"""
Args:
use_reference_count (bool):
True: If an entry has child nodes, the meta data are referring to the results of
the child node
False: Sum all meta data up
... | [
"class Day8MemoryManeuver:\n def __init__(self, use_reference_count=False):\n \"\"\"\n Args:\n use_reference_count (bool):\n True: If an entry has child nodes, the meta data are referring to the results of\n the child node\n False: Sum all... | false |
8,359 | e18ebf961c2daa7dd127d08f85edb6ea519e3470 | #!/usr/bin/python
"""
Expression Parser Tree for fully parenthesized input expression
"""
from bintree import BinaryTree
from stackModule import Stack
def buildParseTree(expression):
expList = expression.split()
empTree = BinaryTree('')
parentStack = Stack()
parentStack.push(empTree)
currentNode ... | [
"#!/usr/bin/python\n\n\"\"\"\nExpression Parser Tree for fully parenthesized input expression\n\"\"\"\n\nfrom bintree import BinaryTree\nfrom stackModule import Stack\n\ndef buildParseTree(expression):\n expList = expression.split()\n empTree = BinaryTree('')\n parentStack = Stack()\n parentStack.push(e... | true |
8,360 | a4c4a5cc63c345d1fa8cbf426f7857a0f3d4357f | # Generated by Django 3.2.4 on 2021-06-16 13:41
import ckeditor.fields
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('FAQ', '0004_auto_20210616_1253'),
]
operations = [
migrations.RemoveField(
model_name='question',
nam... | [
"# Generated by Django 3.2.4 on 2021-06-16 13:41\n\nimport ckeditor.fields\nfrom django.db import migrations\n\n\nclass Migration(migrations.Migration):\n\n dependencies = [\n ('FAQ', '0004_auto_20210616_1253'),\n ]\n\n operations = [\n migrations.RemoveField(\n model_name='questio... | false |
8,361 | ad94118b43e130aec5df3976fd0460164de17511 | #!/usr/bin/python
# coding: utf-8
# # import re
# # import urllib
# #
# #
# # def getHtml(url):
# # page = urllib.urlopen(url)
# # html = page.read()
# # return html
# #
# #
# # def getMp4(html):
# # r = r"href='(http.*\.mp4)'"
# # re_mp4 = re.compile(r)
# # mp4List = re.findall(re_mp4, html)
... | [
"#!/usr/bin/python\n# coding: utf-8\n\n\n# # import re\n# # import urllib\n# #\n# #\n# # def getHtml(url):\n# # page = urllib.urlopen(url)\n# # html = page.read()\n# # return html\n# #\n# #\n# # def getMp4(html):\n# # r = r\"href='(http.*\\.mp4)'\"\n# # re_mp4 = re.compile(r)\n# # mp4List = ... | false |
8,362 | 28851979c8f09f3cd1c0f4507eeb5ac2e2022ea0 | '''
Run from the command line with arguments of the CSV files you wish to convert.
There is no error handling so things will break if you do not give it a well
formatted CSV most likely.
USAGE: python mycsvtomd.py [first_file.csv] [second_file.csv] ...
OUTPUT: first_file.md second_file.md ...
'''
import sys
import cs... | [
"'''\nRun from the command line with arguments of the CSV files you wish to convert.\nThere is no error handling so things will break if you do not give it a well\nformatted CSV most likely.\n\nUSAGE: python mycsvtomd.py [first_file.csv] [second_file.csv] ...\n\nOUTPUT: first_file.md second_file.md ...\n'''\nimport... | true |
8,363 | 37fdfddb471e2eec9e5867d685c7c56fc38c5ae7 | import json
import logging
import os
import sys
from io import StringIO
import pytest
from allure.constants import AttachmentType
from utils.tools import close_popups
_beautiful_json = dict(indent=2, ensure_ascii=False, sort_keys=True)
# LOGGING console ##############################################################... | [
"import json\nimport logging\nimport os\nimport sys\nfrom io import StringIO\n\nimport pytest\nfrom allure.constants import AttachmentType\n\nfrom utils.tools import close_popups\n\n_beautiful_json = dict(indent=2, ensure_ascii=False, sort_keys=True)\n\n# LOGGING console ############################################... | false |
8,364 | 9320926c9eb8a03d36446f3692f11b242c4fc745 | #!/usr/bin/env python3
# coding=utf-8
# date 2020-10-22 10:54:38
# author calllivecn <c-all@qq.com>
import sys
import random
import asyncio
import argparse
def httpResponse(msg):
response = [
"HTTP/1.1 200 ok",
"Server: py",
"Content-Type: text/plain",
"Content-Le... | [
"#!/usr/bin/env python3\n# coding=utf-8\n# date 2020-10-22 10:54:38\n# author calllivecn <c-all@qq.com>\n\n\nimport sys\nimport random\nimport asyncio\nimport argparse\n\n\ndef httpResponse(msg):\n response = [\n \"HTTP/1.1 200 ok\",\n \"Server: py\",\n \"Content-Type: text/plain... | false |
8,365 | 90a402cccf383ed6a12b70ecdc3de623e6e223f9 | def ex7(*siruri, x=1, flag=True):
res = ()
for sir in siruri:
chars = []
for char in sir:
if ord(char) % x == (not flag):
chars.append(char)
res += (chars,)
return res
print(ex7("test", "hello", "lab002", x=2, flag=False))
| [
"def ex7(*siruri, x=1, flag=True):\n res = ()\n for sir in siruri:\n chars = []\n for char in sir:\n if ord(char) % x == (not flag):\n chars.append(char)\n res += (chars,)\n\n return res\n\n\nprint(ex7(\"test\", \"hello\", \"lab002\", x=2, flag=False))\n",
"... | false |
8,366 | 6e73625adc10064cdb1b5f0546a4fc7320e9f5dc | from django import template
import random
register = template.Library()
@register.simple_tag
def random_quote():
"""Returns a random quote to be displayed on the community sandwich page"""
quotes = [
"Growth is never by mere chance; it is the result of forces working together.\n-James Cash Penney",
... | [
"from django import template\n\nimport random\n\nregister = template.Library()\n\n\n@register.simple_tag\ndef random_quote():\n \"\"\"Returns a random quote to be displayed on the community sandwich page\"\"\"\n quotes = [\n \"Growth is never by mere chance; it is the result of forces working together.... | false |
8,367 | 158b39a64d725bdbfc78acc346ed8335613ae099 | #common method to delete data from a list
fruits=['orange','apple','mango','grapes','banana','apple','litchi']
#l=[]
#[l.append(i) for i in fruits if i not in l]
#print(l)
print(set(fruits))
print(fruits.count("orange"))
#pop method in a list used to delete last mathod from a lis... | [
"#common method to delete data from a list\r\nfruits=['orange','apple','mango','grapes','banana','apple','litchi']\r\n#l=[]\r\n\r\n#[l.append(i) for i in fruits if i not in l]\r\n\r\n#print(l)\r\nprint(set(fruits))\r\n\r\nprint(fruits.count(\"orange\"))\r\n\r\n\r\n\r\n\r\n \r\n \r\n#pop method in a lis... | false |
8,368 | 802eb0502c5eddcabd41b2d438bf53a5d6fb2c82 | from django.db import models
from NavigantAnalyzer.common import convert_datetime_string
import json
# A custom view-based model for flat outputs - RÖ - 2018-10-24
# Don't add, change or delete fields without editing the view in the Db
class Results_flat(models.Model):
race_id = models.IntegerField()
race_name... | [
"from django.db import models\nfrom NavigantAnalyzer.common import convert_datetime_string\nimport json\n\n# A custom view-based model for flat outputs - RÖ - 2018-10-24\n# Don't add, change or delete fields without editing the view in the Db\nclass Results_flat(models.Model):\n race_id = models.IntegerField()\n... | false |
8,369 | 77ae3ef1f6f267972a21f505caa7be29c19a6663 | from models import Session, FacebookUser, FacebookPage, FacebookGroup
from lib import get_scraper, save_user, save_page
import logging
logging.basicConfig(level=logging.DEBUG)
session = Session()
scraper = get_scraper(True)
for user in session.query(FacebookUser).filter(FacebookUser.data=="todo").filter("username ~ '... | [
"from models import Session, FacebookUser, FacebookPage, FacebookGroup\nfrom lib import get_scraper, save_user, save_page\n\nimport logging\nlogging.basicConfig(level=logging.DEBUG)\nsession = Session()\nscraper = get_scraper(True)\n\nfor user in session.query(FacebookUser).filter(FacebookUser.data==\"todo\").filte... | true |
8,370 | b0a49f5876bc3837b69a6dc274f9587a37351495 | import myThread
def main():
hosts={"127.0.0.1":"carpenter"}
myThread.messageListenThread(hosts)
if __name__ == '__main__':
main() | [
"import myThread\r\n\r\ndef main():\r\n\thosts={\"127.0.0.1\":\"carpenter\"}\r\n\tmyThread.messageListenThread(hosts)\r\n\r\n\r\nif __name__ == '__main__':\r\n\tmain()",
"import myThread\n\n\ndef main():\n hosts = {'127.0.0.1': 'carpenter'}\n myThread.messageListenThread(hosts)\n\n\nif __name__ == '__main__... | false |
8,371 | f039ab104093eb42c3f5d3c794710a0997e85387 | # coding: utf-8
# Aluno: Héricles Emanuel
# Matrícula: 117110647
# Atividade: É quadrado Mágico?
def eh_quadrado_magico(m):
somas_all = []
eh_magico = True
soma = 0
for e in range(len(m[0])):
soma += m[0][e]
# Linhas
for i in range(len(m)):
somados = 0
for e in range(len(m[i])):
somados += (m[i][e])
s... | [
"# coding: utf-8\n# Aluno: Héricles Emanuel\n# Matrícula: 117110647\n# Atividade: É quadrado Mágico?\n\ndef eh_quadrado_magico(m):\n\tsomas_all = []\n\teh_magico = True\n\tsoma = 0\n\tfor e in range(len(m[0])):\n\t\tsoma += m[0][e]\n\n# Linhas\n\tfor i in range(len(m)):\n\t\tsomados = 0\n\t\tfor e in range(len(m[i]... | true |
8,372 | 14e304f30364932910986f2dda48223b6d4b01c0 | from tqdm import tqdm
import fasttext
import codecs
import os
import hashlib
import time
def make_save_folder(prefix="", add_suffix=True) -> str:
"""
1. 現在時刻のハッシュをsuffixにした文字列の生成
2. 生成した文字列のフォルダが無かったら作る
:param prefix:save folderの系統ラベル
:param add_suffix: suffixを付与するかを選ぶフラグ, True: 付与, False: 付与しない
... | [
"from tqdm import tqdm\nimport fasttext\nimport codecs\nimport os\nimport hashlib\nimport time\n\n\ndef make_save_folder(prefix=\"\", add_suffix=True) -> str:\n \"\"\"\n 1. 現在時刻のハッシュをsuffixにした文字列の生成\n 2. 生成した文字列のフォルダが無かったら作る\n :param prefix:save folderの系統ラベル\n :param add_suffix: suffixを付与するかを選ぶフラグ, T... | false |
8,373 | 96936b7f6553bee06177eb66a2e63064c1bf51a6 | from __future__ import unicode_literals
import requests
try:
import json
except ImportError:
import simplejson as json
def main(app, data):
MEDIUM_API_ENDPOINT = 'https://medium.com/{0}/latest?format=json'
r = requests.get(MEDIUM_API_ENDPOINT.format(data.get('username')))
response_content = r.... | [
"from __future__ import unicode_literals\n\nimport requests\n\ntry:\n import json\nexcept ImportError:\n import simplejson as json\n\n\ndef main(app, data):\n MEDIUM_API_ENDPOINT = 'https://medium.com/{0}/latest?format=json'\n\n r = requests.get(MEDIUM_API_ENDPOINT.format(data.get('username')))\n\n r... | false |
8,374 | 36fb0d936be5c5d305c4076fd1c497664c9b770a | # -*- coding: utf-8 -*-
from ..general.utils import log_errors
from googleapiclient import discovery
from oauth2client.client import SignedJwtAssertionCredentials
from django.conf import settings
from celery import shared_task
from logging import getLogger
import httplib2
_logger = getLogger(__name__)
def create_ev... | [
"# -*- coding: utf-8 -*-\n\nfrom ..general.utils import log_errors\n\nfrom googleapiclient import discovery\nfrom oauth2client.client import SignedJwtAssertionCredentials\nfrom django.conf import settings\nfrom celery import shared_task\nfrom logging import getLogger\nimport httplib2\n\n_logger = getLogger(__name__... | false |
8,375 | 64935ae910d5f330722b637dcc5794e7e07ab52d | from eval_lib.classification_results import analyze_one_classification_result
from eval_lib.classification_results import ClassificationBatches
from eval_lib.cloud_client import CompetitionDatastoreClient
from eval_lib.cloud_client import CompetitionStorageClient
from eval_lib.dataset_helper import DatasetMetadata
from... | [
"from eval_lib.classification_results import analyze_one_classification_result\nfrom eval_lib.classification_results import ClassificationBatches\nfrom eval_lib.cloud_client import CompetitionDatastoreClient\nfrom eval_lib.cloud_client import CompetitionStorageClient\nfrom eval_lib.dataset_helper import DatasetMeta... | false |
8,376 | 7491a17256b9bc7af0953202e45f0fd9d5c34c40 | import ctypes
import time
from order_queue.order import Order
class stock(ctypes.Structure):
_fields_ = [('stock_id', ctypes.c_int), ('order_type',ctypes.c_int),('Time',ctypes.c_char * 40),('user_id',ctypes.c_int),('volume',ctypes.c_int),
('price',ctypes.c_double)
]
class exchange(ctypes.St... | [
"import ctypes\nimport time\nfrom order_queue.order import Order\n\nclass stock(ctypes.Structure):\n _fields_ = [('stock_id', ctypes.c_int), ('order_type',ctypes.c_int),('Time',ctypes.c_char * 40),('user_id',ctypes.c_int),('volume',ctypes.c_int),\n ('price',ctypes.c_double)\n ]\nclass excha... | false |
8,377 | 443ce5c2ec86b9f89ad39ef2ac6772fa002e7e16 | class NumMatrix(object):
def __init__(self, matrix):
if matrix:
self.dp = [[0] * (len(matrix[0]) + 1) for i in range(len(matrix)+1)]
for i in xrange(1,len(matrix)+1):
for j in xrange(1,len(matrix[0])+1):
self.dp[i][j] = self.dp[i-1][j] + self.... | [
"class NumMatrix(object):\n\n def __init__(self, matrix):\n if matrix:\n self.dp = [[0] * (len(matrix[0]) + 1) for i in range(len(matrix)+1)]\n for i in xrange(1,len(matrix)+1):\n for j in xrange(1,len(matrix[0])+1):\n self.dp[i][j] = self.dp[i-1... | true |
8,378 | 2e3c1bf0a4c88bda35a48008cace8c21e071384e | disk = bytearray (1024*1024);
def config_complete():
pass
def open(readonly):
return 1
def get_size(h):
global disk
return len (disk)
def can_write(h):
return True
def can_flush(h):
return True
def is_rotational(h):
return False
def can_trim(h):
return True
def pread(h, count, of... | [
"disk = bytearray (1024*1024);\n\ndef config_complete():\n pass\n\ndef open(readonly):\n return 1\n\ndef get_size(h):\n global disk\n return len (disk)\n\ndef can_write(h):\n return True\n\ndef can_flush(h):\n return True\n\ndef is_rotational(h):\n return False\n\ndef can_trim(h):\n return T... | false |
8,379 | dfd2b515e08f285345c750bf00f6a55f43d60039 | """David's first approach when I exposed the problem.
Reasonable to add in the comparison?
"""
import numpy as np
from sklearn.linear_model import RidgeCV
from sklearn.model_selection import ShuffleSplit
def correlation(x, y):
a = (x - x.mean(0)) / x.std(0)
b = (y - y.mean(0)) / y.std(0)
return a.T @ b / ... | [
"\"\"\"David's first approach when I exposed the problem.\nReasonable to add in the comparison?\n\"\"\"\nimport numpy as np\nfrom sklearn.linear_model import RidgeCV\nfrom sklearn.model_selection import ShuffleSplit\n\n\ndef correlation(x, y):\n a = (x - x.mean(0)) / x.std(0)\n b = (y - y.mean(0)) / y.std(0)\... | false |
8,380 | 7e985f55271c8b588abe54a07d20b89b2a29ff0d | from codecool_class import CodecoolClass
from mentor import Mentor
from student import Student
codecool_bp = CodecoolClass.create_local
| [
"from codecool_class import CodecoolClass\nfrom mentor import Mentor\nfrom student import Student\n\ncodecool_bp = CodecoolClass.create_local\n",
"from codecool_class import CodecoolClass\nfrom mentor import Mentor\nfrom student import Student\ncodecool_bp = CodecoolClass.create_local\n",
"<import token>\ncodec... | false |
8,381 | 6ba830aafbe8e4b42a0b927328ebcad1424cda5e | class Solution:
'''
先遍历整个string，并记录最小的character的出现次数。
如果最小character出现次数都不小于k，那么说明整个string就是满足条件的longest substring，返回原string的长度即可；
如果character的出现次数小于k，假设这个character是c，因为满足条件的substring永远不会包含c，所以满足条件的substring一定是在以c为分割参考下的某个substring中。所以我们需要做的就是把c当做是split的参考，在得到的String[]中再次调用我们的method，找到最大的返回值即可。
'''
... | [
"class Solution:\n '''\n 先遍历整个string，并记录最小的character的出现次数。\n 如果最小character出现次数都不小于k，那么说明整个string就是满足条件的longest substring，返回原string的长度即可；\n 如果character的出现次数小于k，假设这个character是c，因为满足条件的substring永远不会包含c，所以满足条件的substring一定是在以c为分割参考下的某个substring中。所以我们需要做的就是把c当做是split的参考，在得到的String[]中再次调用我们的method，找到最大的返回值即可。\... | false |
8,382 | ae7a2de8742e353818d4f5a28feb9bce04d787bb | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 13 17:34:32 2019
@author: fanlizhou
Analyze codon usage of sequence from 'SP_gene_seq.txt' and 'LP_gene_seq.txt'
Plot heatmap of amino acid usage and codon usage
Plot codon usage in each gene for each amino acid. Genes were arranged so that
the ge... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n\"\"\"\nCreated on Wed Mar 13 17:34:32 2019\n\n@author: fanlizhou\n\nAnalyze codon usage of sequence from 'SP_gene_seq.txt' and 'LP_gene_seq.txt'\nPlot heatmap of amino acid usage and codon usage\nPlot codon usage in each gene for each amino acid. Genes were arran... | false |
8,383 | e0c6fb414d87c0a6377538089226e37b044edc70 | from django.shortcuts import render
from django_filters.rest_framework import DjangoFilterBackend
from django.views.decorators.csrf import csrf_exempt
from rest_framework.parsers import JSONParser
from django.http import JsonResponse, Http404
from .serializers import *
from .models import *
from .filter import *
from r... | [
"from django.shortcuts import render\nfrom django_filters.rest_framework import DjangoFilterBackend\nfrom django.views.decorators.csrf import csrf_exempt\nfrom rest_framework.parsers import JSONParser\nfrom django.http import JsonResponse, Http404\nfrom .serializers import *\nfrom .models import *\nfrom .filter imp... | false |
8,384 | 3001534be3364be1148cd51a4a943fd8c975d87e | from flask import (Flask,
render_template,
request,
url_for,
redirect,
flash,
jsonify)
app = Flask(__name__)
@app.route('/', methods=['GET'])
def showHomepage():
return render_template('home.html')
if __name__ == '__main__':
print('app started')
app.secret_key = 'secretkey'
app.run(debug=True)
| [
"from flask import (Flask,\n\trender_template,\n\trequest,\n\turl_for,\n\tredirect,\n\tflash,\n\tjsonify)\n\napp = Flask(__name__)\n\n@app.route('/', methods=['GET'])\ndef showHomepage():\n\treturn render_template('home.html')\n\n\nif __name__ == '__main__':\n\tprint('app started')\n\tapp.secret_key = 'secretkey'\n... | false |
8,385 | 2f64aac7032ac099870269659a84b8c7c38b2bf0 | import pandas as pd
import subprocess
import statsmodels.api as sm
import numpy as np
import math
'''
This function prcesses the gene file
Output is a one-row file for a gene
Each individual is in a column
Input file must have rowname
gene: gene ENSG ID of interest
start_col: column number which the gene exp value st... | [
"import pandas as pd\nimport subprocess\nimport statsmodels.api as sm\nimport numpy as np\nimport math\n\n'''\nThis function prcesses the gene file\nOutput is a one-row file for a gene\nEach individual is in a column\n\nInput file must have rowname\ngene: gene ENSG ID of interest\nstart_col: column number which the... | false |
8,386 | edc66bdc365f9c40ee33249bd2d02c0c5f28256a | import torch
import torch.nn as nn
class ReconstructionLoss(nn.Module):
def __init__(self, config):
super(ReconstructionLoss, self).__init__()
self.velocity_dim = config.velocity_dim
def forward(self, pre_seq, gt_seq):
MSE_loss = nn.MSELoss()
rec_loss = MSE_loss(pre_seq[:, 1:-... | [
"import torch\nimport torch.nn as nn\n\n\nclass ReconstructionLoss(nn.Module):\n def __init__(self, config):\n super(ReconstructionLoss, self).__init__()\n self.velocity_dim = config.velocity_dim\n\n def forward(self, pre_seq, gt_seq):\n MSE_loss = nn.MSELoss()\n rec_loss = MSE_los... | false |
8,387 | 9ca769ae8bbabee20b5dd4d75ab91d3c30e8d1bf | 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:
... | [
"def filter(txt): # can be improved using regular expression\n\toutput = []\n\tfor t in txt:\n\t\tif t == \"(\" or t == \")\" or t == \"[\" or t == \"]\":\n\t\t\toutput.append(t)\n\treturn output\n\nresult = []\nwhile True:\n\traw_input = input()\n\tline = filter(raw_input)\n\t\n\tif raw_input != \".\":\n\t\tstack ... | false |
8,388 | a8659ca7d7a5870fc6f62b3dfee1779e33373e7b | #!/usr/bin/python2.7
'''USAGE: completeness.py BLAST_output (tab formatted)
Prints % completeness based on marker gene BLAST of caled genes from a genome
Markers from Lan et al. (2016)
'''
import sys
with open(sys.argv[1],'r') as blastOut:
geneHits = []
orgHits = []
hits = 0.0
for line in blastOut:
hits += 1.0
... | [
"#!/usr/bin/python2.7\n'''USAGE: completeness.py BLAST_output (tab formatted)\nPrints % completeness based on marker gene BLAST of caled genes from a genome\nMarkers from Lan et al. (2016)\n'''\nimport sys\n\nwith open(sys.argv[1],'r') as blastOut:\n\n\tgeneHits = []\n\torgHits = []\n\thits = 0.0\n\tfor line in bla... | false |
8,389 | dc2c9293040204f0ec2156c41b8be624f4e5cf99 | # 라이브러리 환경
import pandas as pd
import numpy as np
# sklearn 테이터셋에서 iris 데이터셋 로딩
from sklearn import datasets
iris = datasets.load_iris()
# iris 데이터셋은 딕셔너리 형태이므로, key 값 확인
'''
print(iris.keys())
print(iris['DESCR'])
print("데이터 셋 크기:", iris['target'])
print("데이터 셋 내용:\n", iris['target'])
'''
# data 속성의 데이터셋 크기
print("... | [
"# 라이브러리 환경\nimport pandas as pd\nimport numpy as np\n\n# sklearn 테이터셋에서 iris 데이터셋 로딩\nfrom sklearn import datasets\niris = datasets.load_iris()\n\n# iris 데이터셋은 딕셔너리 형태이므로, key 값 확인\n'''\nprint(iris.keys())\nprint(iris['DESCR'])\nprint(\"데이터 셋 크기:\", iris['target'])\nprint(\"데이터 셋 내용:\\n\", iris['target'])\n'''\n\n... | false |
8,390 | 4c9a3983180cc75c39da41f7f9b595811ba0dc35 | import urllib.request
from urllib.request import Request, urlopen
import json
from requests import get
from requests.exceptions import RequestException
from contextlib import closing
from bs4 import BeautifulSoup
"""
Web Scraper ======================================================================
"""
... | [
"import urllib.request\r\nfrom urllib.request import Request, urlopen\r\nimport json\r\n\r\nfrom requests import get\r\nfrom requests.exceptions import RequestException\r\nfrom contextlib import closing\r\nfrom bs4 import BeautifulSoup\r\n\r\n\"\"\"\r\nWeb Scraper ===================================================... | false |
8,391 | e11a04cad967ae377449aab8b12bfde23e403335 | import webbrowser
import time
total = 3
count = 0
while count<total:
webbrowser.open('https://www.youtube.com/watch?v=GoSBNNgf_Vc')
time.sleep(5*60*60)
count+=1
| [
"import webbrowser\nimport time\n\n\n\ntotal = 3\ncount = 0\nwhile count<total:\n\twebbrowser.open('https://www.youtube.com/watch?v=GoSBNNgf_Vc')\n\ttime.sleep(5*60*60)\n\tcount+=1\n",
"import webbrowser\nimport time\ntotal = 3\ncount = 0\nwhile count < total:\n webbrowser.open('https://www.youtube.com/watch?v... | false |
8,392 | 689c6c646311eba1faa93cc72bbe1ee4592e45bc | #!/usr/bin/env python3
from typing import ClassVar, List
print(1, 2)
# Annotated function (Issue #29)
def foo(x: int) -> int:
return x + 1
# Annotated variables #575
CONST: int = 42
class Class:
cls_var: ClassVar[str]
def m(self):
xs: List[int] = []
# True and False are keywords in Python ... | [
"#!/usr/bin/env python3\nfrom typing import ClassVar, List\n\nprint(1, 2)\n\n\n# Annotated function (Issue #29)\ndef foo(x: int) -> int:\n return x + 1\n\n\n# Annotated variables #575\nCONST: int = 42\n\n\nclass Class:\n cls_var: ClassVar[str]\n\n def m(self):\n xs: List[int] = []\n\n\n# True and Fa... | false |
8,393 | a9947884e805cc8fcb6bff010a5f6e0ff0bb01fe | import math
import numpy as np
# import tkinter
import tensorflow as tf
from matplotlib import axis
import os
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.cluster import KMeans
from sklearn.metrics import confusion_matrix
class MD(BaseEstimator, TransformerMixin):
def __init__(self, data,... | [
"import math\nimport numpy as np\n# import tkinter\nimport tensorflow as tf\nfrom matplotlib import axis\nimport os\nfrom sklearn.base import BaseEstimator, TransformerMixin\nfrom sklearn.cluster import KMeans\nfrom sklearn.metrics import confusion_matrix\n\n\nclass MD(BaseEstimator, TransformerMixin):\n def __i... | false |
8,394 | 86f33895e9ae0e026d7d6e40e611796b2dc2c713 | """@brief the routes for Flask application
"""
import hashlib
import json
import time
import requests
from flask import render_template, url_for
from soco import SoCo
from app import app
app.config.from_pyfile("settings.py")
sonos = SoCo(app.config["SPEAKER_IP"])
def gen_sig():
"""@brief return the MD5 checksum... | [
"\"\"\"@brief the routes for Flask application\n\"\"\"\nimport hashlib\nimport json\nimport time\n\nimport requests\nfrom flask import render_template, url_for\nfrom soco import SoCo\nfrom app import app\n\napp.config.from_pyfile(\"settings.py\")\nsonos = SoCo(app.config[\"SPEAKER_IP\"])\n\n\ndef gen_sig():\n \"... | false |
8,395 | 4a14265a9a2338be66e31110bba696e224b6a70f | from django.shortcuts import render
from django.http import HttpResponse
from chats.models import Chat
from usuario.models import Usuario
# Create your views here.
def chat(request):
chat_list = Chat.objects.order_by("id_chat")
chat_dict = {'chat': chat_list}
return render(request,'chats/Chat.html', ... | [
"from django.shortcuts import render\nfrom django.http import HttpResponse\nfrom chats.models import Chat\nfrom usuario.models import Usuario\n\n# Create your views here.\ndef chat(request):\n \n chat_list = Chat.objects.order_by(\"id_chat\")\n chat_dict = {'chat': chat_list}\n\n return render(request,'... | false |
8,396 | 9816a8265bcdb8c099f599efbe1cfe1a554e71f5 | from django.conf.urls import url
from price_App import views
from rest_framework.urlpatterns import format_suffix_patterns
urlpatterns = [
url(r'^api/price/(?P<pk>[0-9]+)$', views.product_price),
url(r'^api/price_history/(?P<pk>[0-9]+)$', views.product_history),]
urlpatterns = format_suffix... | [
"from django.conf.urls import url \nfrom price_App import views\nfrom rest_framework.urlpatterns import format_suffix_patterns\n\nurlpatterns = [ \n \turl(r'^api/price/(?P<pk>[0-9]+)$', views.product_price),\n url(r'^api/price_history/(?P<pk>[0-9]+)$', views.product_history),] \n\nurlpatterns =... | false |
8,397 | 76a22408bb423d9a5bc5bc007decdbc7c6cc98f7 | """
Neuraxle Tensorflow V1 Utility classes
=========================================
Neuraxle utility classes for tensorflow v1.
..
Copyright 2019, Neuraxio Inc.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obta... | [
"\"\"\"\nNeuraxle Tensorflow V1 Utility classes\n=========================================\nNeuraxle utility classes for tensorflow v1.\n\n..\n Copyright 2019, Neuraxio Inc.\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License... | false |
8,398 | 8364264851895ccabeb74fd3fab1d4f39da717f8 | from django.apps import AppConfig
class StonewallConfig(AppConfig):
name = 'stonewall'
| [
"from django.apps import AppConfig\r\n\r\n\r\nclass StonewallConfig(AppConfig):\r\n name = 'stonewall'\r\n",
"from django.apps import AppConfig\n\n\nclass StonewallConfig(AppConfig):\n name = 'stonewall'\n",
"<import token>\n\n\nclass StonewallConfig(AppConfig):\n name = 'stonewall'\n",
"<import toke... | false |
8,399 | e6010ec05ec24dcd2a44e54ce1b1f11000e775ce | #########################################################################
# 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... | [
"#########################################################################\n# Licensed to the Apache Software Foundation (ASF) under one or more\n# contributor license agreements. See the NOTICE file distributed with\n# this work for additional information regarding copyright ownership.\n# The ASF licenses this fi... | false |
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