index int64 0 100k | blob_id stringlengths 40 40 | code stringlengths 7 7.27M | steps listlengths 1 1.25k | error bool 2
classes |
|---|---|---|---|---|
99,900 | 6ecbe2d74c2996b804b3102329f59e9e32d278c9 | SPARSE = 'Sparse_word'
PADDING = 'Padding'
TRUE = 'true'
FALSE = 'false'
DISEASE = 'disease'
CHEMICAL = 'chemical'
GENE = 'gene'
E1_B = 'entity1begin'
E1_E = 'entity1end'
E2_B = 'entity2begin'
E2_E = 'entity2end' | [
"SPARSE = 'Sparse_word'\nPADDING = 'Padding'\n\nTRUE = 'true'\nFALSE = 'false'\n\nDISEASE = 'disease'\nCHEMICAL = 'chemical'\nGENE = 'gene'\n\nE1_B = 'entity1begin'\nE1_E = 'entity1end'\nE2_B = 'entity2begin'\nE2_E = 'entity2end'",
"SPARSE = 'Sparse_word'\nPADDING = 'Padding'\nTRUE = 'true'\nFALSE = 'false'\nDISE... | false |
99,901 | 8d3b4bd3b34dd168634cf24443244c33962291f8 | from . import db
from app.models.permiso_usuario_horario import Permiso_usuario_horario
from sqlalchemy import *
from app.models.grupo import Grupo
class Grupo_alumno_horario(db.Model):
__tablename__ = 'grupo_alumno_horario'
grupo = db.relationship(Grupo,backref = __tablename__,lazy=True)
usuario_horario =... | [
"from . import db\nfrom app.models.permiso_usuario_horario import Permiso_usuario_horario \nfrom sqlalchemy import *\nfrom app.models.grupo import Grupo\nclass Grupo_alumno_horario(db.Model):\n __tablename__ = 'grupo_alumno_horario'\n grupo = db.relationship(Grupo,backref = __tablename__,lazy=True)\n usuar... | false |
99,902 | 979cfa17af2711f9389ee86eb4c1f8ac75086811 | import random
import datetime
while True:
question = input('Ask a question: ') # .split()
b = {"what" and "time": ["The time of the day is:", datetime.datetime.now().time()],
"name": ["My name is Precious!"],
"love": ["Yes, I love you", "No, I don't love you", "What is love?", "Love is wick... | [
"import random\nimport datetime\n\nwhile True:\n question = input('Ask a question: ') # .split()\n b = {\"what\" and \"time\": [\"The time of the day is:\", datetime.datetime.now().time()],\n \"name\": [\"My name is Precious!\"],\n \"love\": [\"Yes, I love you\", \"No, I don't love you\", \"... | false |
99,903 | d5ac3b91b25ed4d6e1f1722e936513848eef3641 | import block
# block (bytes) as an integer
def getWords(block):
words = [0,0,0,0]
remainder = block
for i in range(4):
word = remainder % (16 ** 4)
# insert into array starting from low order bits
words[3-i] = word
remainder //= (16 ** 4)
return words
# xor each 4 word... | [
"import block \n\n# block (bytes) as an integer\ndef getWords(block):\n words = [0,0,0,0]\n remainder = block\n for i in range(4):\n word = remainder % (16 ** 4)\n # insert into array starting from low order bits\n words[3-i] = word\n remainder //= (16 ** 4)\n return words\n\... | false |
99,904 | 03c4404901c23acadf0f12ac800fb5492ce7abbe | import os
""" Constant parameters
"""
UCR_DIR = '../../dataset/UCR_TS_Archive_2015'
""" classifiers
"""
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import LinearSVC
StandardClassifierDic = {
'LR': LogisticRegression(),
'LSVC': Linear... | [
"import os\n\n\"\"\" Constant parameters\n\"\"\"\nUCR_DIR = '../../dataset/UCR_TS_Archive_2015'\n\n\n\"\"\" classifiers\n\"\"\"\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.svm import LinearSVC\nStandardClassifierDic = {\n 'LR': LogisticRe... | false |
99,905 | 8cf6968582b9e0d0dfb124adfeaf78f9262618a2 | #! /usr/bin/python
# Single 6 faced dice
import random
print("Welcome to Dice Simulator. Press 'Enter' to start.")
Enter = input()
while Enter == "":
x = random.randint(1,6)
print(x)
if x == 6:
print ("Roll Again. Press 'Enter'")
Enter = input()
if Enter == "":
x = random... | [
"#! /usr/bin/python\n# Single 6 faced dice\nimport random\nprint(\"Welcome to Dice Simulator. Press 'Enter' to start.\")\nEnter = input()\nwhile Enter == \"\":\n x = random.randint(1,6)\n print(x)\n if x == 6:\n print (\"Roll Again. Press 'Enter'\")\n Enter = input()\n if Enter == \"\"... | false |
99,906 | c5ac9cb72b76168a706dc43f27806985d59bbb31 | import errno
import os
import re
import sass
import shutil
from cssmin import cssmin
from jsmin import jsmin
from src.lib.util.injection import *
from src.lib.util.logger import *
from src.lib.util.settings import *
class Renderer:
def __init__(self):
settings = Settings.get_instance()
cwd = os.g... | [
"import errno\nimport os\nimport re\nimport sass\nimport shutil\nfrom cssmin import cssmin\nfrom jsmin import jsmin\nfrom src.lib.util.injection import *\nfrom src.lib.util.logger import *\nfrom src.lib.util.settings import *\n\n\nclass Renderer:\n\n def __init__(self):\n settings = Settings.get_instance(... | false |
99,907 | 4712e515d3ec32bbf8ba2b506cada78cbd553fd8 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
http://selenium-python.readthedocs.io
https://realpython.com/blog/python/modern-web-automation-with-python-and-selenium/
dokumentace s příklady:
https://media.readthedocs.org/pdf/selenium-python/latest/selenium-python.pdf
"""
from selenium.webdriver import Firef... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nhttp://selenium-python.readthedocs.io\nhttps://realpython.com/blog/python/modern-web-automation-with-python-and-selenium/\n\ndokumentace s příklady:\nhttps://media.readthedocs.org/pdf/selenium-python/latest/selenium-python.pdf\n \n\"\"\"\n\nfrom selenium.... | false |
99,908 | 920e987d7aefd02603b5d96c8e593a3c80547733 | #!/usr/bin/env python3
"""
Non-interactive tests for installer.
pytest files should start from `test_`
"""
import cluster_dev as installer # pylint: disable=unused-import # noqa: WPS110, F401
# Example usage:
def func(test_param):
"""Test something."""
return test_param + 1
def test_func():
"""Functi... | [
"#!/usr/bin/env python3\n\"\"\"\nNon-interactive tests for installer.\n\npytest files should start from `test_`\n\"\"\"\nimport cluster_dev as installer # pylint: disable=unused-import # noqa: WPS110, F401\n\n# Example usage:\n\n\ndef func(test_param):\n \"\"\"Test something.\"\"\"\n return test_param + 1\n\... | false |
99,909 | 9638d2d2cc9f4777aeccfd237cae8bb14253c6b4 | #censor >> "this **** is wack ****"
text = "this hack is wack hack"
word = "hack"
def censor(text, word):
Z = []
for g in text.split():
if g != word:
Z.append(g)
elif g == word:
P = ""
for x in g:
x = "*"
P += x
Z.ap... | [
"#censor >> \"this **** is wack ****\"\n\ntext = \"this hack is wack hack\"\nword = \"hack\"\n\ndef censor(text, word):\n Z = []\n for g in text.split():\n if g != word:\n Z.append(g)\n elif g == word:\n P = \"\"\n for x in g:\n x = \"*\"\n ... | false |
99,910 | 5a8e34748e48e532036899ebea1d6c2506f8d4b7 | import copy
import random
D = list(map(int, input().split()))
q = int(input())
for x in range(q):
y, z = map(int, input().split())
while True:
r = random.randint(0,3)
if r == 0:
Dt = copy.copy(D)
temp = Dt[0]
Dt[0] = Dt[4]
Dt[4] = Dt[5]
... | [
"import copy\nimport random\n\nD = list(map(int, input().split()))\nq = int(input())\n\nfor x in range(q):\n y, z = map(int, input().split())\n while True:\n r = random.randint(0,3)\n if r == 0:\n Dt = copy.copy(D)\n temp = Dt[0]\n Dt[0] = Dt[4]\n Dt[4... | false |
99,911 | 32a73965fd70a27f68a4884a2e3738e15a5dfd05 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for `pyriskadjust` package."""
import unittest
import json
from pyriskadjust.models import model_2018_v22
class TestPyriskadjust(unittest.TestCase):
"""Tests for `pyriskadjust` package."""
def setUp(self):
"""Set up test fixtures, if any."""
... | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Tests for `pyriskadjust` package.\"\"\"\n\n\nimport unittest\nimport json\nfrom pyriskadjust.models import model_2018_v22\n\n\nclass TestPyriskadjust(unittest.TestCase):\n \"\"\"Tests for `pyriskadjust` package.\"\"\"\n\n def setUp(self):\n \"\"\... | false |
99,912 | 4c3fb19a90ebabbed4fc3193b38fec720eb27dc9 | #
# [222] Count Complete Tree Nodes
#
# https://leetcode.com/problems/count-complete-tree-nodes
#
# Medium (27.30%)
# Total Accepted:
# Total Submissions:
# Testcase Example: '[]'
#
# Given a complete binary tree, count the number of nodes.
#
# Definition of a complete binary tree from Wikipedia:
# ... | [
"#\r\n# [222] Count Complete Tree Nodes\r\n#\r\n# https://leetcode.com/problems/count-complete-tree-nodes\r\n#\r\n# Medium (27.30%)\r\n# Total Accepted: \r\n# Total Submissions: \r\n# Testcase Example: '[]'\r\n#\r\n# Given a complete binary tree, count the number of nodes.\r\n# \r\n# Definition of a complete bi... | false |
99,913 | a4aad2760de34fde725a59a148e85b86f5e6e673 | import numpy as np
from numpy import *
from numpy.linalg import inv
import MahalanobisDistance
from os import listdir
"""rawdata has n rows
## Create arr_groupvariance to store variance of each group of 5 rows (has n/5 rows)"""
arr_rawdata = genfromtxt('../../Raw Data/Truncated-Horizontal.csv',
... | [
"import numpy as np\nfrom numpy import *\nfrom numpy.linalg import inv\nimport MahalanobisDistance\nfrom os import listdir\n\n\"\"\"rawdata has n rows\n## Create arr_groupvariance to store variance of each group of 5 rows (has n/5 rows)\"\"\"\n\narr_rawdata = genfromtxt('../../Raw Data/Truncated-Horizontal.csv',\n ... | false |
99,914 | 9cd6b07d724922d9d6568483fd5cbc5a0d0c886a | import ftplib
import os
| [
"import ftplib\nimport os\n\n",
"import ftplib\nimport os\n",
"<import token>\n"
] | false |
99,915 | 5dac538485abb64388974ba3201084a779d5e9cf | # Adaptar o programa desenvolvido acima para que ela calcule o percentual dos valores positivos e
# negativos em relação ao total de valores fornecidos.
positivos, negativos = 0, 0
total = 1
num = int(input("Informe um número: "))
while (num != 0):
if num > 0:
positivos += 1
if num < 0:
negativ... | [
"# Adaptar o programa desenvolvido acima para que ela calcule o percentual dos valores positivos e\n# negativos em relação ao total de valores fornecidos.\n\npositivos, negativos = 0, 0\ntotal = 1\nnum = int(input(\"Informe um número: \"))\nwhile (num != 0):\n if num > 0:\n positivos += 1\n if num < 0:... | false |
99,916 | 2f6e85ef5154e92e270adda5b92ff5e51cf0e22f | # -*- coding: utf-8 -*-
# 震惊小伙伴的单行代码（Python篇）
# 1、让列表中的每个元素都乘以2
print map(lambda x: x * 2, range(1, 11))
# 2、求列表中的所有元素之和
print sum(range(1, 1001))
# 3、判断一个字符串中是否存在某些词
wordlist = ["scala", "akka", "play framework", "sbt", "typesafe"]
tweet = "This is an example tweet talking about scala and sbt."
print map(lambd... | [
"# -*- coding: utf-8 -*-\n\n# 震惊小伙伴的单行代码（Python篇）\n\n# 1、让列表中的每个元素都乘以2\n\nprint map(lambda x: x * 2, range(1, 11))\n\n# 2、求列表中的所有元素之和\n\nprint sum(range(1, 1001))\n\n# 3、判断一个字符串中是否存在某些词\n\nwordlist = [\"scala\", \"akka\", \"play framework\", \"sbt\", \"typesafe\"]\ntweet = \"This is an example tweet talking about s... | true |
99,917 | 9af1005a865196e45664e7a353e33c32f4814e6c | #! /usr/bin/env python2
#
# This file is part of khmer, http://github.com/ged-lab/khmer`, and is
# Copyright (C) Michigan State University, 2009-2014. It is licensed under
# the three-clause BSD license; see doc/LICENSE.txt.
# Contact: khmer-project@idyll.org
# Author Sherine Awad
import sys, getopt
import glob
from co... | [
"#! /usr/bin/env python2\n#\n# This file is part of khmer, http://github.com/ged-lab/khmer`, and is\n# Copyright (C) Michigan State University, 2009-2014. It is licensed under\n# the three-clause BSD license; see doc/LICENSE.txt.\n# Contact: khmer-project@idyll.org\n# Author Sherine Awad\nimport sys, getopt\nimport... | true |
99,918 | 09d50bcb40089bd2213279b156c77943653d631b | """
Collection of models.
""" | [
"\"\"\"\nCollection of models.\n\"\"\"",
"<docstring token>\n"
] | false |
99,919 | 1a1a1c2de774ae8c79004824678fabd5b2029a01 | # Write a Python function that takes a list of words and returns the length of the longest one
#!/Library/Frameworks/Python.framework/Versions/3.6/bin/python3.6
l=['cnxvjxnlkxnlxc','kjgnfxkjvkfjnvklxnv','xkjvbfkjbvjkxznvkjxcnvkjzcxnvjzxcnv','jfvjcgcb','ggg']
max_s=l[0]
for i in l:
if len(max_s) < len(i):
ma... | [
"# Write a Python function that takes a list of words and returns the length of the longest one\n#!/Library/Frameworks/Python.framework/Versions/3.6/bin/python3.6\nl=['cnxvjxnlkxnlxc','kjgnfxkjvkfjnvklxnv','xkjvbfkjbvjkxznvkjxcnvkjzcxnvjzxcnv','jfvjcgcb','ggg']\nmax_s=l[0]\nfor i in l:\n if len(max_s) < len(i):\... | false |
99,920 | 28d4cf5fd4193fbf8a2ccc5484fd5ac7bd7bfc1f | from abc import ABCMeta, abstractmethod
from conformal_predictors.validation import NotCalibratedError
from conformal_predictors.nc_measures import NCMeasure
import numpy as np
from decimal import *
class ConformalPredictor:
"""
Abstract class that represents the Conformal Predictors and defines their
bas... | [
"from abc import ABCMeta, abstractmethod\nfrom conformal_predictors.validation import NotCalibratedError\nfrom conformal_predictors.nc_measures import NCMeasure\nimport numpy as np\nfrom decimal import *\n\n\nclass ConformalPredictor:\n \"\"\"\n Abstract class that represents the Conformal Predictors and defi... | false |
99,921 | 855c58fd502af172bbc95e2a111edbba4f715368 | import numpy as np
import re
import nltk
from sklearn.datasets import load_files
nltk.download('stopwords' )
import pickle
from nltk.corpus import stopwords
movie_data = load_files("data/review_polarity/txt_sentoken")
X, y = movie_data.data, movie_data.target
print(type(X))
documents = []
from nltk.stem impor... | [
"import numpy as np \nimport re \nimport nltk\nfrom sklearn.datasets import load_files \nnltk.download('stopwords' )\nimport pickle \nfrom nltk.corpus import stopwords \n\n\nmovie_data = load_files(\"data/review_polarity/txt_sentoken\")\nX, y = movie_data.data, movie_data.target\n\nprint(type(X))\n\ndocuments = []\... | false |
99,922 | 48b91572a5d492e416042d0ea9800775a6257682 | """This is the class for the light powerup."""
import random
import pygame
import os
from .entity import Entity
DIRECTORY = os.path.abspath(os.getcwd())
POWERUP_DIR = DIRECTORY+"/players_images/powerups/flash.png"
POWERUPSIZE = 20
class Flash(Entity):
"""get the size"""
def __init__(self, name):
Ent... | [
"\"\"\"This is the class for the light powerup.\"\"\"\nimport random\nimport pygame\nimport os\nfrom .entity import Entity\n\n\nDIRECTORY = os.path.abspath(os.getcwd())\nPOWERUP_DIR = DIRECTORY+\"/players_images/powerups/flash.png\"\n\nPOWERUPSIZE = 20\n\nclass Flash(Entity):\n \"\"\"get the size\"\"\"\n def ... | false |
99,923 | 3e9df2ef61ea6d62d1e7508de18431b8f05023e6 | #tokenizing and covertint to lower-case
import nltk.tokenize
raw = open("E:\\dataset.txt").read()
raw = raw.lower()
docs = nltk.tokenize.sent_tokenize(raw)
docs = docs[0].split('\n')
#pre-processing punctuations
from string import punctuation as punc
for d in docs:
for ch in d:
if ch in punc:
d... | [
"#tokenizing and covertint to lower-case\nimport nltk.tokenize\nraw = open(\"E:\\\\dataset.txt\").read()\nraw = raw.lower()\ndocs = nltk.tokenize.sent_tokenize(raw)\ndocs = docs[0].split('\\n')\n\n#pre-processing punctuations\nfrom string import punctuation as punc\nfor d in docs:\n for ch in d:\n if ch i... | false |
99,924 | ddf5d72696f6e1c5e40685902336c88167dfc065 | def solution(tickets):
tck = dict()
for t1, t2 in tickets:
if t1 in tck.keys():
tck[t1].append(t2)
else:
tck[t1] = [t2]
for k in tck.keys():
tck[k].sort()
st = ['ICN']
res = []
while st:
top = st[-1]
... | [
"def solution(tickets): \n tck = dict()\n \n for t1, t2 in tickets:\n if t1 in tck.keys():\n tck[t1].append(t2)\n else:\n tck[t1] = [t2]\n \n for k in tck.keys():\n tck[k].sort()\n \n st = ['ICN']\n res = []\n \n while st:\n top = st... | false |
99,925 | 3e2838efdd4efa8a6b5ac227504030fa64388877 | import keras
from keras.models import Sequential
from keras.layers import Conv2D,MaxPooling2D,Flatten,Dense,Dropout
import cv2
import numpy as np
model2 = Sequential()
model2.add(Conv2D(filters = 16,kernel_size=2,padding='same',activation='relu',input_shape=(100,100,3)))
model2.add(MaxPooling2D(pool_size=2))
model2.ad... | [
"import keras\nfrom keras.models import Sequential\nfrom keras.layers import Conv2D,MaxPooling2D,Flatten,Dense,Dropout\nimport cv2\nimport numpy as np\n\nmodel2 = Sequential()\nmodel2.add(Conv2D(filters = 16,kernel_size=2,padding='same',activation='relu',input_shape=(100,100,3)))\nmodel2.add(MaxPooling2D(pool_size=... | false |
99,926 | f7407cf768d072a19b7086a40f29a633c5a6fe6c | import sqlite3
#function for creating table to store user
def make_user():
conn = sqlite3.connect("app.db")
cur = conn.cursor()
sql = 'CREATE TABLE IF NOT EXISTS user(Email TEXT, Name TEXT, Password TEXT)'
cur.execute(sql)
conn.commit()
#function to insert values into user table
def insert(table... | [
"import sqlite3\n\n#function for creating table to store user\ndef make_user():\n conn = sqlite3.connect(\"app.db\")\n cur = conn.cursor()\n\n sql = 'CREATE TABLE IF NOT EXISTS user(Email TEXT, Name TEXT, Password TEXT)'\n cur.execute(sql)\n conn.commit()\n\n#function to insert values into user table... | false |
99,927 | 28f11c9882baa46236557fa8d18e38805c3a9546 |
def part_1():
bag_rules = {}
direct_bags = set([])
for line in open("input.txt"):
# Using :-1 instead of rstrip as it is faster
line = line[:-1]
splitln = line.split(' bags contain ')
bag_type = splitln[0]
rules = {}
for bag_rule in splitln[1].split(', '):
... | [
"\n\ndef part_1():\n bag_rules = {}\n direct_bags = set([])\n for line in open(\"input.txt\"):\n # Using :-1 instead of rstrip as it is faster\n line = line[:-1]\n splitln = line.split(' bags contain ')\n bag_type = splitln[0]\n rules = {}\n for bag_rule in splitln... | false |
99,928 | 40f53e254466550f08cf627a46b5c247fabe1901 | # using `value_counts`
result = df['Position'].value_counts()
display(Markdown("Using `value_counts`:"))
display(result)
# using `groupby`
result = df.groupby(['Position'])['Position'].count()
display(Markdown("Using `groupby`:"))
display(result)
# using `pivot_table`
# NOTE: This is not the correct way to get the re... | [
"# using `value_counts`\nresult = df['Position'].value_counts()\ndisplay(Markdown(\"Using `value_counts`:\"))\ndisplay(result)\n\n# using `groupby`\nresult = df.groupby(['Position'])['Position'].count()\ndisplay(Markdown(\"Using `groupby`:\"))\ndisplay(result)\n\n# using `pivot_table`\n# NOTE: This is not the corre... | false |
99,929 | 9e087bb6d6705bb8ed469ffaa6434279fb0e6f59 | # 오답
import sys
sys.stdin=open('input.txt','r')
# 수정 본 실행시간 반으로 줄어듬
for t in range(1,int(input())+1):
n, k = map(int,input().split());cnt=0
L=[*map(int,input().split())];q=[(0,-1)]
while q:
a,b=q.pop()
for id,v in enumerate(L):
if id>b:
a+=v
if a>... | [
"# 오답\nimport sys\nsys.stdin=open('input.txt','r')\n\n# 수정 본 실행시간 반으로 줄어듬\nfor t in range(1,int(input())+1):\n n, k = map(int,input().split());cnt=0\n L=[*map(int,input().split())];q=[(0,-1)]\n while q:\n a,b=q.pop()\n for id,v in enumerate(L):\n if id>b:\n a+=v\n ... | false |
99,930 | 72926b4c8bff521c7247bccdb71ed130917b250e | #!/usr/bin/env python
# coding:utf-8
"""
@Version: V1.0
@Author: willson
@License: Apache Licence
@Contact: willson.wu@goertek.com
@Site: goertek.com
@Software: PyCharm
@File: __init__.py.py
@Time: 19-1-26 上午9:48
"""
from flask_security.utils import encrypt_password
from myApp import app, store_datastore
from myApp.m... | [
"#!/usr/bin/env python\n# coding:utf-8\n\"\"\"\n@Version: V1.0\n@Author: willson\n@License: Apache Licence\n@Contact: willson.wu@goertek.com\n@Site: goertek.com\n@Software: PyCharm\n@File: __init__.py.py\n@Time: 19-1-26 上午9:48\n\"\"\"\n\nfrom flask_security.utils import encrypt_password\n\nfrom myApp import app, st... | false |
99,931 | a6b3c1423b21c66a94297434a968a8e91d0307bf | nome = input('Digite seu nome completo: ').strip()
print(nome.upper())
print(nome.lower())
print(len(nome.replace(' ', '')))
nome_separado = nome.split()
print(len(nome_separado[0]))
print(nome_separado[0], nome_separado[len(nome_separado) - 1]) # EXTRA - Imprimindo Primeiro e Ultimo Nome | [
"nome = input('Digite seu nome completo: ').strip()\n\nprint(nome.upper())\nprint(nome.lower())\nprint(len(nome.replace(' ', '')))\n\nnome_separado = nome.split()\n\nprint(len(nome_separado[0]))\n\nprint(nome_separado[0], nome_separado[len(nome_separado) - 1]) # EXTRA - Imprimindo Primeiro e Ultimo Nome",
"nome =... | false |
99,932 | 72a96a4c7c6e745aaf52f3c3bb32e6a19c5a79d0 | # coding=utf-8
"""Plot Tools."""
import matplotlib.pyplot as plt
from sklearn.metrics import auc, roc_curve
import numpy as np
def plot_roc_curve(y_true, y_pred_prob, show_threshold=False, **params):
"""
A function plot Roc AUC.
Parameters:
y_true: Array
... | [
"# coding=utf-8\n\"\"\"Plot Tools.\"\"\"\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import auc, roc_curve\nimport numpy as np\n\n\ndef plot_roc_curve(y_true, y_pred_prob, show_threshold=False, **params):\n \"\"\"\n A function plot Roc AUC.\n Parameters:\n ... | false |
99,933 | 152867d01dd1309a9472762c4e421a2ff7c7105e | #
# @lc app=leetcode id=935 lang=python3
#
# [935] Knight Dialer
#
# @lc code=start
# TAGS: Dynamic Programming
import sys
sys.setrecursionlimit(5010)
class Solution:
# 2800 ms, 24.18%. Time and Space: O(N). Recursion with memoization
def knightDialer(self, n: int) -> int:
future_moves = {1: [6, 8], 2... | [
"#\n# @lc app=leetcode id=935 lang=python3\n#\n# [935] Knight Dialer\n#\n\n# @lc code=start\n# TAGS: Dynamic Programming\nimport sys\nsys.setrecursionlimit(5010)\nclass Solution:\n\n # 2800 ms, 24.18%. Time and Space: O(N). Recursion with memoization\n def knightDialer(self, n: int) -> int:\n future_mo... | false |
99,934 | bc6a79ed2d6197db15cc9d34198313b3f24e681b | from __future__ import annotations
import os
from xml.etree import ElementTree
from cloudshell.layer_one.core.helper.xml_helper import XMLHelper
from cloudshell.layer_one.core.response.command_response import CommandResponse
ElementTree.register_namespace(
"", "http://schemas.qualisystems.com/ResourceManagement/... | [
"from __future__ import annotations\n\nimport os\nfrom xml.etree import ElementTree\n\nfrom cloudshell.layer_one.core.helper.xml_helper import XMLHelper\nfrom cloudshell.layer_one.core.response.command_response import CommandResponse\n\nElementTree.register_namespace(\n \"\", \"http://schemas.qualisystems.com/Re... | false |
99,935 | 71ddbe711aeabf84ecf9c32197ac4e17b21ddba4 | from django.contrib import admin
from . models import csv_data
from . models import temp_ssdata
# Register your models here.
admin.site.register(csv_data)
admin.site.register(temp_ssdata) | [
"from django.contrib import admin\nfrom . models import csv_data\nfrom . models import temp_ssdata\n# Register your models here.\n\nadmin.site.register(csv_data)\nadmin.site.register(temp_ssdata)",
"from django.contrib import admin\nfrom .models import csv_data\nfrom .models import temp_ssdata\nadmin.site.registe... | false |
99,936 | 0892d2bd363ae7a15e05aab651e5310ccb23362a | import numpy as np
import pandas as pd
from scipy import stats
from util.caching import cache_today
# FIXME: There are more exact significance tests with more resolving power for our
# cases, e.g. Barnard's or Boschloo's tests.
def binomial_pv(counts=None, frequencies=None, table=None, chi_min=10, **kwargs):
if ... | [
"import numpy as np\nimport pandas as pd\nfrom scipy import stats\n\nfrom util.caching import cache_today\n\n\n# FIXME: There are more exact significance tests with more resolving power for our\n# cases, e.g. Barnard's or Boschloo's tests.\ndef binomial_pv(counts=None, frequencies=None, table=None, chi_min=10, **kw... | false |
99,937 | 662cb7300294342a812a13cf2132502ee45aad7c | import sys, os
from lxml import objectify
usage = """
Usage is:
py admx2oma.py <your.admx> <ADMX-OMA-URI>
<ADMX-OMA-URI> : The OMA-URI you specifyed in Intune when ingesting admx file
Take care, the OMA-URI is case sensitive.
<your.admx> : The admx file you ingested
"""
def run():
if len(s... | [
"import sys, os\nfrom lxml import objectify\n\nusage = \"\"\"\nUsage is:\npy admx2oma.py <your.admx> <ADMX-OMA-URI>\n<ADMX-OMA-URI> : The OMA-URI you specifyed in Intune when ingesting admx file\n Take care, the OMA-URI is case sensitive.\n<your.admx> : The admx file you ingested\n\n\"\"\"\n\n... | false |
99,938 | 082d740bfa2ed2fcb4fba11d6f269a715abd1354 | # -*- coding: utf-8 -*-
import sys
import os
import re
import time
"""
Python Nagios extensions
"""
__author__ = "Drew Stinnett"
__copyright__ = "Copyright 2008, Drew Stinnett"
__credits__ = ["Drew Stinnett", "Pall Sigurdsson"]
__license__ = "GPL"
__version__ = "0.4"
__maintainer__ = "Pall Sigurdsson"
__email__ = "p... | [
"# -*- coding: utf-8 -*-\n\nimport sys\nimport os\nimport re\nimport time\n\n\"\"\"\nPython Nagios extensions\n\"\"\"\n\n__author__ = \"Drew Stinnett\"\n__copyright__ = \"Copyright 2008, Drew Stinnett\"\n__credits__ = [\"Drew Stinnett\", \"Pall Sigurdsson\"]\n__license__ = \"GPL\"\n__version__ = \"0.4\"\n__maintain... | true |
99,939 | 88215fda2071e16e59da7f27e603ebff1a9fe7d5 | from http import HTTPStatus
from peewee import DoesNotExist, IntegrityError
from playhouse.shortcuts import dict_to_model, model_to_dict
from api.helpers import add_extra_info_to_dict, to_utc_datetime
from api.models import DataSource, DataSourceToken, User
class UserService():
def get_user_by_id(self, user_id:... | [
"from http import HTTPStatus\n\nfrom peewee import DoesNotExist, IntegrityError\nfrom playhouse.shortcuts import dict_to_model, model_to_dict\n\nfrom api.helpers import add_extra_info_to_dict, to_utc_datetime\nfrom api.models import DataSource, DataSourceToken, User\n\n\nclass UserService():\n def get_user_by_id... | false |
99,940 | 416fe1a39b6acd1cfc63b9be8932965ec9792a9d | #Makes dataset for tensorflow (possibility, might not do it)
def NNDataSet(num_testers,mispercievedSeq, mispercievedRan):
AOIfile=open("AOIMetricsSequential.csv","r")
#AOIfileR=open("AOIMetricsRandom.csv","r")
file = open("NN_SVMData/EmotionDataSequentialAll.csv","w")
fileP = open("NN_SVMData/EmotionDataSequential... | [
"#Makes dataset for tensorflow (possibility, might not do it)\n\ndef NNDataSet(num_testers,mispercievedSeq, mispercievedRan):\n\tAOIfile=open(\"AOIMetricsSequential.csv\",\"r\")\n\t#AOIfileR=open(\"AOIMetricsRandom.csv\",\"r\")\n\tfile = open(\"NN_SVMData/EmotionDataSequentialAll.csv\",\"w\")\n\tfileP = open(\"NN_S... | false |
99,941 | 2ce0664d4e0f8860873e7d894279ce767377328e | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import json
from flask import Blueprint, url_for, render_template, request, abort, flash, session, redirect
from web.wxtranstypes.utils import utils_show_transtypes
mod = Blueprint('wxtranstypes', __name__, url_prefix='/wxtranstypes')
@mod.route('/show_transtypes', metho... | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nimport json\nfrom flask import Blueprint, url_for, render_template, request, abort, flash, session, redirect\nfrom web.wxtranstypes.utils import utils_show_transtypes\n\nmod = Blueprint('wxtranstypes', __name__, url_prefix='/wxtranstypes')\n\n\n@mod.route('/show_tran... | false |
99,942 | 38fde5ecf1bf15d737e1a886c5dca0c1893fc149 | # This is an auto-generated Django model module.
# You'll have to do the following manually to clean this up:
# * Rearrange models' order
# * Make sure each model has one field with primary_key=True
# * Make sure each ForeignKey has `on_delete` set to the desired behavior.
# * Remove `managed = False` lines if ... | [
"# This is an auto-generated Django model module.\n# You'll have to do the following manually to clean this up:\n# * Rearrange models' order\n# * Make sure each model has one field with primary_key=True\n# * Make sure each ForeignKey has `on_delete` set to the desired behavior.\n# * Remove `managed = False`... | false |
99,943 | 1fd18338067e28ab48a9a83f5ced26e69a1d58b1 | # -*-coding: utf-8-*- ; -*-Python-*-
# Copyright © 2022-2023 Tom Fontaine
# Title: colors.py
# Date: 25-Apr-2022
colors = {'CSI': chr(27) + '[',
'CSI24': chr(27) + '[38;5;',
'NORMAL': '0',
'BOLD': '1',
'BLACK': '30',
'RED': '31',
'GR... | [
"# -*-coding: utf-8-*- ; -*-Python-*-\n\n# Copyright © 2022-2023 Tom Fontaine\n\n# Title: colors.py\n# Date: 25-Apr-2022\n\n\ncolors = {'CSI': chr(27) + '[',\n 'CSI24': chr(27) + '[38;5;',\n\n 'NORMAL': '0',\n 'BOLD': '1',\n\n 'BLACK': '30',\n 'RED': ... | false |
99,944 | b36f307d81187eb662470628aa84f86295a91297 | __copyright__ = """
This file is part of stellar-py, Stellar Python Client.
Copyright 2018 CSIRO Data61
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apach... | [
"__copyright__ = \"\"\"\n\n This file is part of stellar-py, Stellar Python Client.\n\n Copyright 2018 CSIRO Data61\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n\n ... | false |
99,945 | 5058f568f278e7e87e07d0523d58293fdc1e1ddc | def add(x, y):
return x + y
def minus(x, y):
return x - y
def multiple(x, y):
return x * y
def divide(x, y):
if y == 0:
print("error!")
return
else:
return x / y | [
"def add(x, y):\n\treturn x + y\n\ndef minus(x, y):\n\treturn x - y\n\ndef multiple(x, y):\n\treturn x * y\n\ndef divide(x, y):\n\tif y == 0:\n\t\tprint(\"error!\")\n\t\treturn\n\telse:\n\t\treturn x / y",
"def add(x, y):\n return x + y\n\n\ndef minus(x, y):\n return x - y\n\n\ndef multiple(x, y):\n retu... | false |
99,946 | 926f55a6fc19dcf95339aae1e16f5d10cbd977ac | import math
from abc import ABCMeta, abstractmethod
from collections import Iterable
# from __future__ import annotations
'''
This whole thing is a bit much...
To make the assignment interesting I decided to practice object hierarchies and inheritance,
and potentially generate some code I could reuse later with Katis... | [
"import math\nfrom abc import ABCMeta, abstractmethod\nfrom collections import Iterable\n\n# from __future__ import annotations\n\n'''\nThis whole thing is a bit much...\nTo make the assignment interesting I decided to practice object hierarchies and inheritance,\nand potentially generate some code I could reuse la... | false |
99,947 | ded367d0159f7c1a72f7adea7494f61ae658b1cf | import json
def load_information(key):
f = open('doc\print_info.json',)
data = json.load(f)
if key:
data = [x for x in data if x['modelo'] == key or x['ip'] == key or x['nombre'] == key or x['sise'] == key ]
f.close()
return data | [
"import json\n\ndef load_information(key):\n f = open('doc\\print_info.json',)\n data = json.load(f)\n \n if key:\n data = [x for x in data if x['modelo'] == key or x['ip'] == key or x['nombre'] == key or x['sise'] == key ]\n f.close()\n return data",
"import json\n\n\ndef load_information... | false |
99,948 | 1210c4d499c02cf9861b97261033b2d12f2c78d7 | #!/usr/bin/env python3
import csv, json
from sys import argv
try:
filename = argv[1]
except IndexError:
print("No input given")
exit()
try:
f = open(filename, 'r')
blockdata = csv.reader(f, delimiter=',')
timestamp = []
height = []
nonce = []
diff = []
for row in blockdata:
... | [
"#!/usr/bin/env python3\n\nimport csv, json\nfrom sys import argv\n\ntry:\n filename = argv[1]\nexcept IndexError:\n print(\"No input given\")\n exit()\n\ntry:\n f = open(filename, 'r')\n blockdata = csv.reader(f, delimiter=',')\n\n timestamp = []\n height = []\n nonce = []\n diff = []\n\... | false |
99,949 | 840acc471ea55a84186b25ca07ddcf7c006a60a9 | #!/usr/bin/python
from __future__ import print_function
import dbus
import sys
import time
import gobject
from dbus.mainloop.glib import DBusGMainLoop
WPAS_DBUS_SERVICE = "fi.w1.wpa_supplicant1"
WPAS_DBUS_INTERFACE = "fi.w1.wpa_supplicant1"
WPAS_DBUS_OPATH = "/fi/w1/wpa_supplicant1"
WPAS_DBUS_INTERFACES_INTERFACE = "... | [
"#!/usr/bin/python\n\nfrom __future__ import print_function\nimport dbus\nimport sys\nimport time\nimport gobject\nfrom dbus.mainloop.glib import DBusGMainLoop\n\nWPAS_DBUS_SERVICE = \"fi.w1.wpa_supplicant1\"\nWPAS_DBUS_INTERFACE = \"fi.w1.wpa_supplicant1\"\nWPAS_DBUS_OPATH = \"/fi/w1/wpa_supplicant1\"\nWPAS_DBUS_I... | true |
99,950 | d1434f8fdd0b75ff8a13226f18b60b5281a4ebca | n,m= map(int,input().split())
from collections import Counter
arr = list(map(int,input().split()))
d = Counter(arr)
flag = 0
for i in range(n):
temp = m - arr[i]
if d[temp]:
if arr[i]==temp and d[temp]==1:
continue
print("YES")
flag = 1
break
if flag==0:
pr... | [
"n,m= map(int,input().split())\nfrom collections import Counter\narr = list(map(int,input().split()))\nd = Counter(arr)\n\n\nflag = 0\nfor i in range(n):\n temp = m - arr[i]\n if d[temp]:\n if arr[i]==temp and d[temp]==1:\n continue\n print(\"YES\")\n flag = 1\n break\ni... | false |
99,951 | 9921f7fe70280babd2fd29783676d605356081ba | from socket import AF_INET, socket, SOCK_STREAM
s = socket(AF_INET, SOCK_STREAM)
s.connect(('localhost', 8888))
msg = 'Привет, сервер!'
s.send(msg.encode('utf-8'))
data = s.recv(4096)
print(data.decode('utf-8'))
s.close()
# print(tame_data.decode('utf-8')) | [
"from socket import AF_INET, socket, SOCK_STREAM\n\ns = socket(AF_INET, SOCK_STREAM)\ns.connect(('localhost', 8888))\n\nmsg = 'Привет, сервер!'\ns.send(msg.encode('utf-8'))\ndata = s.recv(4096)\nprint(data.decode('utf-8'))\ns.close()\n\n# print(tame_data.decode('utf-8'))",
"from socket import AF_INET, socket, SOC... | false |
99,952 | 31ac9e6651e11458654adebc13e85b45bde2c54a | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 12 12:16:58 2019
@author: vladgriguta
Downloads the spectra of the objects in a multi-threading manner, allowing
for fast download of data.
"""
import os
NUM_CPUS = 2 # defaults to all available
def get_address_lists(n_lists,file='../download_ur... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Mar 12 12:16:58 2019\n\n@author: vladgriguta\n\nDownloads the spectra of the objects in a multi-threading manner, allowing\nfor fast download of data.\n\n\"\"\"\nimport os\nNUM_CPUS = 2 # defaults to all available\n\ndef get_address_lists(n_l... | false |
99,953 | a2455fb96660a919f5b4987e501c3064e431222a | #! python3
#bullet adder -adds bullets before lines
import pyperclip
pyperclip.copy('hello dear\n what\n')
text = pyperclip.paste()
#seperate lines
lines = text.split('\n')
for i in range(len(lines)):
lines[i] = '*'+lines[i]
text = '\n'.join(lines)
pyperclip.copy(text)
| [
"#! python3\r\n#bullet adder -adds bullets before lines\r\n\r\nimport pyperclip\r\npyperclip.copy('hello dear\\n what\\n')\r\n\t\r\ntext = pyperclip.paste()\r\n\r\n#seperate lines \r\nlines = text.split('\\n')\r\nfor i in range(len(lines)):\r\n\tlines[i] = '*'+lines[i]\r\ntext = '\\n'.join(lines)\r\npyperclip.copy(... | false |
99,954 | 9e73be09c9861d7ba881c2fbcca7f25da2f55c32 | import tensorflow.keras
from PIL import Image
import numpy as np
np.set_printoptions(suppress=True)
model = tensorflow.keras.models.load_model('keras_model.h5')
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
image = Image.open(r'15.jpeg')
image = image.resize((224, 224))
image_array = np.asarray(image)... | [
"import tensorflow.keras\nfrom PIL import Image\nimport numpy as np\n\nnp.set_printoptions(suppress=True)\n\nmodel = tensorflow.keras.models.load_model('keras_model.h5')\n\n\ndata = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)\nimage = Image.open(r'15.jpeg')\nimage = image.resize((224, 224))\nimage_array = ... | false |
99,955 | 4fcbdf96cfe5016835eb3c2443211a5070821279 | # -*- coding: utf-8 -*-
from odoo import models, fields, api, _
class HrExpenseAdvanceLine(models.Model):
_name = "hr.expense.advance.line"
_description = "Expense Advance Line"
name = fields.Char(string="Description",
required=True)
advance_id = fields.Many2one(string="Advance Reference",
... | [
"# -*- coding: utf-8 -*-\n\nfrom odoo import models, fields, api, _\n\nclass HrExpenseAdvanceLine(models.Model):\n _name = \"hr.expense.advance.line\"\n _description = \"Expense Advance Line\"\n\n name = fields.Char(string=\"Description\",\n required=True)\n advance_id = fields.Many2one(string=\"... | false |
99,956 | 39f02872715e2a7cfd7779b83e80a0ffdbd6b3c8 | # Copyright 2020 Red Hat, 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 obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | [
"# Copyright 2020 Red Hat, 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.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to... | false |
99,957 | dff58769b0084bf6f2da86ec47ed0ac6c336bf15 | import numpy as np
def find_rank(arr):
a = np.array(arr)
r = np.array(a.argsort().argsort(), dtype=float)
f = a==a
for i in xrange(len(a)):
if not f[i]:
continue
s = a == a[i]
ls = np.sum(s)
if ls > 1:
tr = np.sum(r[s])
r[s] = float(t... | [
"import numpy as np\n\ndef find_rank(arr):\n a = np.array(arr)\n r = np.array(a.argsort().argsort(), dtype=float)\n f = a==a\n for i in xrange(len(a)):\n if not f[i]: \n continue\n s = a == a[i]\n ls = np.sum(s)\n if ls > 1:\n tr = np.sum(r[s])\n ... | true |
99,958 | cdb44b7ac0fb0d4e24786741de3ccb3440aff67e | from django.db import models
from djongo import models as djongo_models
class CourseScore(models.Model):
course_name = models.CharField(max_length=4)
student_name = models.CharField(max_length=16)
score = models.IntegerField()
# the manager for postgres
objects = models.Manager()
# the djong... | [
"from django.db import models\nfrom djongo import models as djongo_models\n\n\nclass CourseScore(models.Model):\n\n course_name = models.CharField(max_length=4)\n student_name = models.CharField(max_length=16)\n score = models.IntegerField()\n\n # the manager for postgres\n objects = models.Manager()... | false |
99,959 | 679181c622282ca8b33b2217fd94336431b9d23a | def left_child(root):
return root * 2 + 1
def right_child(root):
return root * 2 + 2
def parent(child):
return (child - 1)// 2
def shift_down(a, start, end):
root = start
while True:
child = left_child(root)
if child > end:
return
swap = root
if a[s... | [
"def left_child(root):\n return root * 2 + 1\n\n\ndef right_child(root):\n return root * 2 + 2\n\n\ndef parent(child):\n return (child - 1)// 2\n\n\ndef shift_down(a, start, end):\n root = start\n\n while True:\n child = left_child(root)\n if child > end:\n return\n sw... | false |
99,960 | 9a24790d67d5a53c540fafa734240354fb7a684e | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from efficient_apriori import apriori
# header=None，不将第一行作为head
dataset = pd.read_csv('./Market_Basket_Optimisation.csv', header = None)
# shape为(7501,20)
print(dataset.shape)
# 将数据存放到transactions中
transactions = []
for i in range(0, ... | [
"import pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom efficient_apriori import apriori\r\n\r\n# header=None，不将第一行作为head\r\ndataset = pd.read_csv('./Market_Basket_Optimisation.csv', header = None) \r\n# shape为(7501,20)\r\nprint(dataset.shape)\r\n\r\n# 将数据存放到transactions中\r\ntransactio... | false |
99,961 | 13f7e99aedb4b5a049a53f68738d5447f9ca63c2 | import pprint
import os
import sqlite3
from td.client import TDClient
from datetime import datetime
pp = pprint.PrettyPrinter()
conn = sqlite3.connect(os.environ.get('DB_NAME'))
# Create a new session, credentials path is required.
TDSession = TDClient(
client_id=os.environ.get('CLIENT_ID'),
redirect_uri='htt... | [
"import pprint\nimport os\nimport sqlite3\nfrom td.client import TDClient\nfrom datetime import datetime\n\npp = pprint.PrettyPrinter()\nconn = sqlite3.connect(os.environ.get('DB_NAME'))\n\n# Create a new session, credentials path is required.\nTDSession = TDClient(\n client_id=os.environ.get('CLIENT_ID'),\n ... | false |
99,962 | 940f3a3a5c7936bf4e7e429e3c3088d09a64f6dd | # coding=utf-8
import requests
from bs4 import BeautifulSoup
url = "http://www.mysoal.com/moments/9JjqHTN2OEvnFeXZO4uUGT8LLOx4I-xJZOlQeYp6Cs0"
page = requests.get(url).text
soup = BeautifulSoup(page,"lxml")
tayara_listing = soup.find("div", class_="moment")
tayara_item = tayara_listing.find_all("div", class_="moment... | [
"# coding=utf-8\nimport requests\nfrom bs4 import BeautifulSoup\n\nurl = \"http://www.mysoal.com/moments/9JjqHTN2OEvnFeXZO4uUGT8LLOx4I-xJZOlQeYp6Cs0\"\npage = requests.get(url).text\nsoup = BeautifulSoup(page,\"lxml\")\n\ntayara_listing = soup.find(\"div\", class_=\"moment\")\ntayara_item = tayara_listing.find_all... | false |
99,963 | 4df299857e9abc20bc162ef283ae3679251ed32d | reddit_categories = ['hot', 'new', 'controversial', 'rising', 'top']
async def get_subreddit_json(session, subreddit, category):
return await get_json(session, 'https://www.reddit.com/r/' + subreddit + '/' + category + '/.json')
async def get_json(session, url):
async with session.get(url) as resp:
re... | [
"reddit_categories = ['hot', 'new', 'controversial', 'rising', 'top']\n\nasync def get_subreddit_json(session, subreddit, category):\n return await get_json(session, 'https://www.reddit.com/r/' + subreddit + '/' + category + '/.json')\n\nasync def get_json(session, url):\n async with session.get(url) as resp:... | false |
99,964 | b015a5d7a956c836722b262426b7a89bcce907e2 | import sys
import requests
import json
from requests import Request, Session
from requests.auth import HTTPBasicAuth
import argparse
from SwarmClient import Swarm
from JiraClient import Jira
import Config
if __name__ == '__main__':
swarm = Swarm()
jira = Jira()
parser = argparse.ArgumentParser( epilog="WA... | [
"import sys\nimport requests\nimport json\nfrom requests import Request, Session\nfrom requests.auth import HTTPBasicAuth\nimport argparse\nfrom SwarmClient import Swarm\nfrom JiraClient import Jira\nimport Config\n\n\nif __name__ == '__main__':\n swarm = Swarm()\n jira = Jira()\n parser = argparse.Argumen... | true |
99,965 | b6051496357dabc0ede873ceebb4054ff46e4d3d | from django.conf.urls import url
from user.views import login, login_validate, join_page, about
urlpatterns = [
url(r'^login/$', login),
url(r'^login/validate/$', login_validate),
url(r'^join/$', join_page),
url(r'^about/$', about),
] | [
"from django.conf.urls import url\r\n\r\nfrom user.views import login, login_validate, join_page, about\r\n\r\nurlpatterns = [\r\n url(r'^login/$', login),\r\n url(r'^login/validate/$', login_validate),\r\n url(r'^join/$', join_page),\r\n url(r'^about/$', about),\r\n]",
"from django.conf.urls import u... | false |
99,966 | 19110b2767433c84dfab6ba28892923b00e99776 | import tensorflow as tf
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.layers import Embedding, LSTM, Dense, Bidirectional ,Dropout
from tensorflow.keras.preprocessing.text import Tokenizer
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import A... | [
"import tensorflow as tf\n\nfrom tensorflow.keras.preprocessing.sequence import pad_sequences\nfrom tensorflow.keras.layers import Embedding, LSTM, Dense, Bidirectional ,Dropout\nfrom tensorflow.keras.preprocessing.text import Tokenizer\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.optimize... | false |
99,967 | 810fc5480d25b8f00fd47a7215f87e017848077e | # the square root function using Newton’s method. In this case, Newton’s method is to approximate sqrt(x) by picking a starting point z and then repeating:
# z_next = z - ((z*z - x) / (2 * z))
# Author: Adrian Sypos
# Date: 23/09/2017
import math
x = 20.0
z_next = lambda z: (z - ((z*z - x) / (2 * z)))
current = 1.0... | [
"# the square root function using Newton’s method. In this case, Newton’s method is to approximate sqrt(x) by picking a starting point z and then repeating:\n# z_next = z - ((z*z - x) / (2 * z))\n# Author: Adrian Sypos\n# Date: 23/09/2017\n\nimport math\n\nx = 20.0\n\nz_next = lambda z: (z - ((z*z - x) / (2 * z)))\... | false |
99,968 | a270c3749a4fda58bd1f8624fdd2f75d8e4cbdd0 | from __future__ import print_function, division
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim import lr_scheduler
from torch.autograd import Variable
import numpy as np
import torchvision
from torchvision import datasets, models, transforms
import matplotlib.pyplot as plt
import time
i... | [
"from __future__ import print_function, division\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.autograd import Variable\nimport numpy as np\nimport torchvision\nfrom torchvision import datasets, models, transforms\nimport matplotlib.pyplot as plt... | false |
99,969 | a452badb12abe9b1df7bf66963285c6aa93f0dbd | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 5 17:09:33 2022
@author: Santi
Extrae multiples espectros adquiridos en Bruker Avance II
"""
# import nmrglue as ng
import matplotlib.pyplot as plt
import numpy as np
import scipy.integrate
from Datos import *
from Espectro import autophase
from scipy.stats import linr... | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Sep 5 17:09:33 2022\n\n@author: Santi\n\nExtrae multiples espectros adquiridos en Bruker Avance II\n\"\"\"\n\n# import nmrglue as ng\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.integrate\nfrom Datos import *\nfrom Espectro import autophase\nfr... | false |
99,970 | 7913ca2d7d428c4b4851e7ad52ccfc578e1a5f65 | # -*- coding: utf-8 -*-
"""
Created on Tue Feb 28 16:06:17 2023
@author: Gilles.DELBECQ
"""
import sys, struct, math, os, time
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal as sp
def read_data(filename):
"""Reads Intan Technologies RHD2000 data file generated by evaluation board GUI.
... | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Feb 28 16:06:17 2023\n\n@author: Gilles.DELBECQ\n\"\"\"\n\nimport sys, struct, math, os, time\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport scipy.signal as sp\n\n\ndef read_data(filename):\n \"\"\"Reads Intan Technologies RHD2000 data file generat... | false |
99,971 | cd6b1c8c1dae53c95f77b4af60fd401ff6c71285 | import numpy as np
import base64
import cv2
import os
class LSB:
# to get object's format, size, data
def get_object_info(self, file, itype):
try:
file_format = os.path.splitext(file)[-1].lower()
size = os.path.getsize(file)
name = os.path.basename(file)
... | [
"import numpy as np\nimport base64\nimport cv2\nimport os\n\nclass LSB:\n # to get object's format, size, data \n def get_object_info(self, file, itype):\n try:\n file_format = os.path.splitext(file)[-1].lower()\n size = os.path.getsize(file)\n name = os.path.basename(f... | false |
99,972 | 260c40c7fd9ebff889f88d9a3f6e3c6d183d4cb4 | from bootstrap import db
from um import models
# Contact 1
u1 = models.Contact('Contact 1', 'user1@example.com')
db.session.add(u1)
db.session.commit()
# Contact 1 properties
p = models.Property('first_name', 'Peter', u1.id)
p1 = models.Property('last_name', 'Wanowan', u1.id)
p2 = models.Property('email', 'peter.wano... | [
"from bootstrap import db\nfrom um import models\n\n# Contact 1\nu1 = models.Contact('Contact 1', 'user1@example.com')\ndb.session.add(u1)\ndb.session.commit()\n\n# Contact 1 properties\np = models.Property('first_name', 'Peter', u1.id)\np1 = models.Property('last_name', 'Wanowan', u1.id)\np2 = models.Property('ema... | false |
99,973 | 8cdf2354dead12b292b47a12663748c0c1c09351 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__all__ = ['NameSpace', 'ns']
from .utils import UnicodeDict
class NameSpace(dict):
@classmethod
def instance(cls):
if not hasattr(cls, "_instance"):
cls._instance = cls()
return cls._instance
def __getattr__(self, key):
... | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n__all__ = ['NameSpace', 'ns']\n\nfrom .utils import UnicodeDict\n\n\nclass NameSpace(dict):\n @classmethod\n def instance(cls):\n if not hasattr(cls, \"_instance\"):\n cls._instance = cls()\n return cls._instance\n\n def __getattr_... | false |
99,974 | 758f6328f197e4fbcbf52ac5c91ed68c3e8fc112 | # class first_class:
# age = 10
# name = 'gilbert'
# p1 = first_class()
# print(p1.name)
# class meth:
# def __init__(self, name='gilbert', age=25):
# self.name = name
# self.age = age
# def get_name(self):
# print(f'hello {self.name} your age is {self.age}')
# p1 = meth('... | [
"# class first_class:\n# age = 10\n# name = 'gilbert'\n# p1 = first_class()\n# print(p1.name)\n\n# class meth:\n# def __init__(self, name='gilbert', age=25):\n# self.name = name\n# self.age = age\n \n# def get_name(self):\n# print(f'hello {self.name} your age is {self.age}... | false |
99,975 | 83e2fe37bdc51475c914af611b671b6995efe890 | # 手机号规则
REGEX_MOBILE = "^1[3578]\d{9}$|^147\d{8}$|^176\d{8}$"
# 代拿费
AGENCY_FEE = 2.0
#退货服务费
SERVER_FEE = 2.0
# 首重件数 2
FIRST_WEIGHT = 2
# 发件人姓名
sender_name = ""
# 发件人手机
sender_phone = ""
# 发件人地址
sender_address = ""
| [
"# 手机号规则\nREGEX_MOBILE = \"^1[3578]\\d{9}$|^147\\d{8}$|^176\\d{8}$\"\n\n# 代拿费\nAGENCY_FEE = 2.0\n#退货服务费\nSERVER_FEE = 2.0\n\n# 首重件数 2\nFIRST_WEIGHT = 2\n\n# 发件人姓名\nsender_name = \"\"\n\n# 发件人手机\nsender_phone = \"\"\n\n# 发件人地址\n\nsender_address = \"\"\n",
"REGEX_MOBILE = '^1[3578]\\\\d{9}$|^147\\\\d{8}$|^176\\\\d{... | false |
99,976 | afab7a1a1d16c3af1bbdb8cf3a9e4c9c91f95cdb | #!/usr/bin/env python
import socket
import struct
class KongsbergEM:
def __init__(self,port=16112):
self.insock = socket.socket(type=socket.SOCK_DGRAM)
self.insock.bind(('',port))
def getPacket(self):
data,addr = self.insock.recvfrom(10000)
start,dgram_type = struct.unpack('<B... | [
"#!/usr/bin/env python\n\nimport socket\nimport struct\n\nclass KongsbergEM:\n def __init__(self,port=16112):\n self.insock = socket.socket(type=socket.SOCK_DGRAM)\n self.insock.bind(('',port))\n\n def getPacket(self):\n data,addr = self.insock.recvfrom(10000)\n start,dgram_type = ... | true |
99,977 | 3c08cca562db78861ec754eb2b7caae4c8ed1eed | import os
from google.cloud import storage
from google.cloud.storage import Bucket
def connect_to_bucket(bucket_name: str) -> Bucket:
"""
@param bucket_name: name of the bucket of the save location
@return: bucket object provided by GCP
"""
storage_client = storage.Client(project='your-project-na... | [
"import os\n\nfrom google.cloud import storage\nfrom google.cloud.storage import Bucket\n\n\ndef connect_to_bucket(bucket_name: str) -> Bucket:\n \"\"\"\n @param bucket_name: name of the bucket of the save location\n @return: bucket object provided by GCP\n \"\"\"\n storage_client = storage.Client(pr... | false |
99,978 | 1e8adf8bc9b96b3e32cd95ca0a739125c72dc17e | import unittest
class TestAbs(unittest.TestCase):
def test_abs1(self):
self.assertEqual(abs(-42), 42, "Should be absolute value of a number")
def test_abs2(self):
self.assertEqual(abs(-15), 15, "Should be absolute value of a number")
def test_abs3(self):
self.assertEqual(abs(-8),... | [
"import unittest\n\n\nclass TestAbs(unittest.TestCase):\n def test_abs1(self):\n self.assertEqual(abs(-42), 42, \"Should be absolute value of a number\")\n\n def test_abs2(self):\n self.assertEqual(abs(-15), 15, \"Should be absolute value of a number\")\n\n def test_abs3(self):\n self.... | false |
99,979 | 8975603a891221ec894f5616bfb377a4f87fb13a | from flask import Flask
from config import Configuration
from routes import myMainRouter
app = Flask(__name__)
app.config.from_object(Configuration)
app.register_blueprint(myMainRouter.bp)
| [
"from flask import Flask\nfrom config import Configuration\nfrom routes import myMainRouter\n\napp = Flask(__name__)\napp.config.from_object(Configuration)\napp.register_blueprint(myMainRouter.bp)\n",
"from flask import Flask\nfrom config import Configuration\nfrom routes import myMainRouter\napp = Flask(__name__... | false |
99,980 | 214a6862dc0b1d7822a34ad1c8a1b0381f8f7c6b | import os
from motor import MotorClient
from tornado.options import define, options
from tornado.web import Application
from app.api.urls import urls
def is_debug():
try:
debug = os.environ['DEBUG']
return debug.lower() in ("true", "t", "1")
except KeyError:
return False
def load_c... | [
"import os\n\nfrom motor import MotorClient\nfrom tornado.options import define, options\nfrom tornado.web import Application\n\nfrom app.api.urls import urls\n\n\ndef is_debug():\n try:\n debug = os.environ['DEBUG']\n return debug.lower() in (\"true\", \"t\", \"1\")\n except KeyError:\n ... | false |
99,981 | f66069ad599747f10ba260f0062d271cf2c0d5a4 | from __future__ import print_function
for col in range(8):
for row in range(col):
for left in range(col - row):
print (' ', end='')
print('#')
| [
"from __future__ import print_function\n\nfor col in range(8):\n for row in range(col):\n for left in range(col - row):\n print (' ', end='')\n print('#')\n",
"from __future__ import print_function\nfor col in range(8):\n for row in range(col):\n for left in range(col - row):... | false |
99,982 | 62f85ea9566ba2ebacb3dddcb746bb287ad8b54d | import torch
def to_categorical(in_content, num_classes=None):
if num_classes is None:
num_classes = int(in_content.max()) + 1
shape = in_content.shape[0], num_classes, *in_content.shape[2:]
temp = torch.zeros(shape).transpose(0, 1)
for i in range(num_classes):
temp[i, (... | [
"import torch\n\n\ndef to_categorical(in_content, num_classes=None):\n if num_classes is None:\n num_classes = int(in_content.max()) + 1\n \n shape = in_content.shape[0], num_classes, *in_content.shape[2:]\n \n temp = torch.zeros(shape).transpose(0, 1)\n \n for i in range(num_classes):\n... | false |
99,983 | dc72077499ff0254bca3244a8a5cef8d72016ef8 | from .pulsesms import PulseCrypt, PulseSMSAPI
| [
"from .pulsesms import PulseCrypt, PulseSMSAPI\n",
"<import token>\n"
] | false |
99,984 | ee7c3dbe415b89a834f9023426e9a6dd026f1021 | import json
import requests
with open('config.json') as config_file:
es_config = json.load(config_file)
def saveVegaLiteVis(index, visName, altairChart, resultSize=100, timeField="timestamp", verify=True):
chart_json = json.loads(altairChart.to_json())
chart_json['data']['url'] = {
"%context%": Tru... | [
"import json\nimport requests\n\nwith open('config.json') as config_file:\n es_config = json.load(config_file)\n\n\ndef saveVegaLiteVis(index, visName, altairChart, resultSize=100, timeField=\"timestamp\", verify=True):\n chart_json = json.loads(altairChart.to_json())\n chart_json['data']['url'] = {\n ... | false |
99,985 | 398200b8e922a026827c981e4f14b16bea7eb366 | from django.urls import include, path
from . import views
urlpatterns = [
path('',include("lenus_app.urls")),
path("signup/",views.signup,name="signup" ),
path("logout/",views.logout_request,name="logout" ),
path("login/",views.user_login,name="login" ),
path("profile/",views.profile,name="profile"... | [
"from django.urls import include, path\nfrom . import views\n\nurlpatterns = [\n path('',include(\"lenus_app.urls\")),\n path(\"signup/\",views.signup,name=\"signup\" ),\n path(\"logout/\",views.logout_request,name=\"logout\" ),\n path(\"login/\",views.user_login,name=\"login\" ),\n path(\"profile/\"... | false |
99,986 | 04c6a30f1065d5ca42507121d89d73b73d846bc5 | """
Module: DMS Project Wide Context Processors
Project: Adlibre DMS
Copyright: Adlibre Pty Ltd 2012
License: See LICENSE for license information
"""
import os
from django.conf import settings
from core.models import CoreConfiguration
def theme_template_base(context):
""" Returns Global Theme Base Template """
... | [
"\"\"\"\nModule: DMS Project Wide Context Processors\nProject: Adlibre DMS\nCopyright: Adlibre Pty Ltd 2012\nLicense: See LICENSE for license information\n\"\"\"\n\nimport os\n\nfrom django.conf import settings\nfrom core.models import CoreConfiguration\n\ndef theme_template_base(context):\n \"\"\" Returns Globa... | false |
99,987 | cb6d64a8495022b4962c51eae9bef5adf47dc6fa | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 29 12:44:18 2021
@author: tai
"""
'''
Evaluate Object Detection Model:
1. Get all bounding box prediction on our test set
Table:
Image_name Confidence_value TP_or_FP
image1 0.3 FP
image3
2. Sort by descendi... | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Apr 29 12:44:18 2021\n\n@author: tai\n\"\"\"\n\n'''\nEvaluate Object Detection Model:\n1. Get all bounding box prediction on our test set\nTable:\n Image_name Confidence_value TP_or_FP\n image1 0.3 FP\n image3... | false |
99,988 | 32d715dbe1764e86f9d5c2bee93bbbda2ec3515f | import pulumi_aws as aws
import pulumi
import os
import mimetypes
config = pulumi.Config()
site_dir = config.get("site")
bucket = aws.s3.Bucket(resource_name="pulumi-demo",
bucket="pulumi-demo",
tags={
"Owner": "pulumi-demo",
... | [
"import pulumi_aws as aws\nimport pulumi\nimport os\nimport mimetypes\n\nconfig = pulumi.Config()\nsite_dir = config.get(\"site\")\n\nbucket = aws.s3.Bucket(resource_name=\"pulumi-demo\",\n bucket=\"pulumi-demo\",\n tags={\n \"Owner\": \"pulumi-d... | false |
99,989 | 0b67714bf9b60e63e48586ac2a1e50468a918752 | import pprint
import re
from collections import defaultdict
__author__ = 'ronanbrady2'
# Prints all street suffixes, e.g. Lane, Avenue, to allow audit analysis
def printAllStreetSuffixes(db):
pipeline = [
{ "$group" : {
"_id" : "$address.street" ,
"coun... | [
"import pprint\nimport re\nfrom collections import defaultdict\n\n__author__ = 'ronanbrady2'\n\n# Prints all street suffixes, e.g. Lane, Avenue, to allow audit analysis\ndef printAllStreetSuffixes(db):\n pipeline = [\n { \"$group\" : {\n \"_id\" : \"$address.street\" ,\n ... | false |
99,990 | 9a75c2b9fed227b660a688bd3adf5b837e85af9e | class node():
def __init__(self):
self.child = [None]*26
self.flag = False
class trie():
def __init__(self):
self.root = node()
def gethash(self, key):
return ord(key)-ord("a")
def add(self, key):
nex = self.root
for char in list(key):
index = self.gethash(char)
#if index is none, create new n... | [
"class node():\n\tdef __init__(self):\n\t\tself.child = [None]*26\n\t\tself.flag = False\n\nclass trie():\n\tdef __init__(self):\n\t\tself.root = node()\n\t\n\tdef gethash(self, key):\n\t\treturn ord(key)-ord(\"a\")\n\n\tdef add(self, key):\n\t\tnex = self.root\n\t\tfor char in list(key):\n\t\t\tindex = self.gethas... | false |
99,991 | 07191eaf858d411c733666dea85de3400d32ca6d | taille = int(input("Saisir la taille du triangle: "))
for i in range (taille,0,-1):
print("*"*i)
| [
"taille = int(input(\"Saisir la taille du triangle: \"))\r\nfor i in range (taille,0,-1):\r\n print(\"*\"*i)\r\n ",
"taille = int(input('Saisir la taille du triangle: '))\nfor i in range(taille, 0, -1):\n print('*' * i)\n",
"<assignment token>\nfor i in range(taille, 0, -1):\n print('*' * i)\n",
"<as... | false |
99,992 | edcf3b16203c006e5bd9382593a8584de26114d5 | import common
import edify_generator
def AddAssertions(info):
edify = info.script
for i in xrange(len(edify.script)):
if ");" in edify.script[i] and ("ro.product.device" in edify.script[i] or "ro.build.product" in edify.script[i]):
edify.script[i] = edify.script[i].replace(");", ' || getpro... | [
"import common\nimport edify_generator\n\ndef AddAssertions(info):\n edify = info.script\n for i in xrange(len(edify.script)):\n if \");\" in edify.script[i] and (\"ro.product.device\" in edify.script[i] or \"ro.build.product\" in edify.script[i]):\n edify.script[i] = edify.script[i].replace... | false |
99,993 | 4d5f8cb419277b87cad42a09632e81d63367fdcb | """Using datetime to make an app that will ask us math questions
and time our answers.
"""
from quiz import Quiz
# create class to keep track of quiz scores over time?
def main():
while True:
quiz_prompt = input('Do you want a math quiz? y/n')
if quiz_prompt.lower()[0] == 'y':
quiz... | [
"\"\"\"Using datetime to make an app that will ask us math questions\nand time our answers.\n\"\"\"\nfrom quiz import Quiz\n \n \n# create class to keep track of quiz scores over time?\ndef main():\n while True:\n quiz_prompt = input('Do you want a math quiz? y/n')\n if quiz_prompt.lower()[0] == ... | false |
99,994 | c3b34cf17b04a9611e348363537371ead6cefe2a | # koomar is a simple IRC bot written for fun.
# Grab your updates from: http://github.com/anandkunal/koomar/
# Peep the IRC RFC: http://www.irchelp.org/irchelp/rfc/rfc.html
import datetime
import random
import socket
import re
import time
import lib
from lib import Message, flatten
server = "irc.freenode.net"
channe... | [
"# koomar is a simple IRC bot written for fun.\n# Grab your updates from: http://github.com/anandkunal/koomar/\n# Peep the IRC RFC: http://www.irchelp.org/irchelp/rfc/rfc.html\n\nimport datetime\nimport random\nimport socket\nimport re\nimport time\n\nimport lib\nfrom lib import Message, flatten\n\nserver = \"irc.f... | false |
99,995 | c11fd5bcba3242216a26bba364888ca95160da35 | # -*- coding: utf-8 -*-
# encoding=utf8
import sys
from flask import Flask, render_template, request, redirect, url_for, session
import sqlite3
import datetime
import os
import random
import re
##burasi hacky. py3 de gerekmiyor ve bu da onerilmiyor
reload(sys)
sys.setdefaultencoding('utf8')
app = Fl... | [
"# -*- coding: utf-8 -*-\r\n# encoding=utf8 \r\nimport sys\r\nfrom flask import Flask, render_template, request, redirect, url_for, session\r\nimport sqlite3\r\nimport datetime\r\nimport os\r\nimport random\r\nimport re\r\n\r\n##burasi hacky. py3 de gerekmiyor ve bu da onerilmiyor\r\nreload(sys) \r\nsys.setdefaul... | true |
99,996 | eca1c5bec2249f529d878c3b9768c4611ccb1e64 | from selenium import webdriver
import requests
from selenium.webdriver.common.keys import Keys
import time
from bs4 import BeautifulSoup
import urlparse, random
import argparse,os
key = "badoo.com"
driver = webdriver.PhantomJS()
driver.set_window_size(1280,800)
driver.get('https://badoo.com/')
Main_win... | [
"from selenium import webdriver\r\nimport requests\r\nfrom selenium.webdriver.common.keys import Keys\r\nimport time\r\nfrom bs4 import BeautifulSoup\r\nimport urlparse, random\r\nimport argparse,os\r\nkey = \"badoo.com\"\r\ndriver = webdriver.PhantomJS()\r\n\r\ndriver.set_window_size(1280,800)\r\ndriver.get('https... | true |
99,997 | 0a03e7274a1d30e2b4f509d3cab8d600eda1cf0f | def process_dict(my_dict):
for key, value in my_dict.items():
if key.startswith("melon"):
print(sorted(value))
process_dict({"elon": [3, 1, 2], "melon": 4})
| [
"def process_dict(my_dict):\n for key, value in my_dict.items():\n if key.startswith(\"melon\"):\n print(sorted(value))\n\n\nprocess_dict({\"elon\": [3, 1, 2], \"melon\": 4})\n",
"def process_dict(my_dict):\n for key, value in my_dict.items():\n if key.startswith('melon'):\n ... | false |
99,998 | 455799a224a29da1b46ae3727166c3b65d08225e | # -*- coding: utf-8 -*-
# BSD 3-Clause License
#
# Copyright (c) 2017 xxxx
# All rights reserved.
# Copyright 2021 Huawei Technologies Co., Ltd
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of so... | [
"# -*- coding: utf-8 -*-\n# BSD 3-Clause License\n#\n# Copyright (c) 2017 xxxx\n# All rights reserved.\n# Copyright 2021 Huawei Technologies Co., Ltd\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are met:\n#\n# * Redist... | false |
99,999 | ab30a233e125889b97c957820961dc8c749c0b0e | # RECURSION
def fact(n):
result = 1
if n > 1:
for f in range(2, n+1):
result *= f
return result
def factorial(n):
if n <= 1:
return 1
else:
return n * factorial(n-1)
def fib(n):
if n < 2:
return n
else:
return fib(n-1) + fib(n-2)
def ... | [
"# RECURSION\n\ndef fact(n):\n result = 1\n if n > 1:\n for f in range(2, n+1):\n result *= f\n return result\n\n\ndef factorial(n):\n if n <= 1:\n return 1\n else:\n return n * factorial(n-1)\n\ndef fib(n):\n if n < 2:\n return n\n else:\n return f... | false |
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