blob_id stringlengths 40 40 | language stringclasses 1
value | repo_name stringlengths 5 133 | path stringlengths 2 333 | src_encoding stringclasses 30
values | length_bytes int64 18 5.47M | score float64 2.52 5.81 | int_score int64 3 5 | detected_licenses listlengths 0 67 | license_type stringclasses 2
values | text stringlengths 12 5.47M | download_success bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|---|
124864ab1f97c15eee48e474368a05241ceda50e | Python | sshyran/Galileo-sdk | /galileo_sdk/business/objects/exceptions.py | UTF-8 | 133 | 2.640625 | 3 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | class JobsException(Exception):
def __init__(self, job_id, msg=None):
self.job_id = job_id
super().__init__(msg)
| true |
cc6370b12ba8da581de4a976da77c8074b074afc | Python | ashemery/psut | /workshops/131214/diy5.py | UTF-8 | 476 | 3.75 | 4 | [] | no_license | #########################
# DIY 5 Answer
import random
f = open("file2.txt", "w")
for count in range(100):
rnumber = random.randint(0,99)
f.write(str(rnumber) + '\n')
f.close()
odd = []
even = []
f = open('file2.txt','r')
for line in f:
row = line.split()
for i in row:
if int(i)... | true |
ee8f604c0f22c470b4c31034ae3dcde4900fc4b0 | Python | djvita/python-control | /control/freqplot.py | UTF-8 | 15,685 | 2.53125 | 3 | [] | no_license | # freqplot.py - frequency domain plots for control systems
#
# Author: Richard M. Murray
# Date: 24 May 09
#
# This file contains some standard control system plots: Bode plots,
# Nyquist plots and pole-zero diagrams. The code for Nichols charts
# is in nichols.py.
#
# Copyright (c) 2010 by California Institute of Tec... | true |
ae377e303d5e1f96c7b96ee63e849688a87e0c18 | Python | jingxinmingzhi/jingxinmingzhi | /python/pycharm/learn/xml_learn/test/xml_xmltodict.py | UTF-8 | 3,011 | 3.5 | 4 | [] | no_license | import xmltodict
from collections import OrderedDict
with open('sample.xml', 'r+', encoding='utf-8') as fp:
#将xml文件转换成dict,默认是返回OrderedDict。其中，fp.read()返回的是str
root = xmltodict.parse(fp.read(), dict_constructor=dict)
print(root)
sample = root['root']
sample['items']['item'][0]['amount'] = 200
i... | true |
9fcd2ca1883ad775b33f2686b920a87900f23101 | Python | MrLokans/portfoliosite | /backend/apps/about_me/tests.py | UTF-8 | 2,350 | 2.578125 | 3 | [] | no_license | from django.test import TestCase
from django.urls import reverse
from .models import Project, Technology
class ProjectsAPITestCase(TestCase):
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.projects_url = reverse("projects-list")
cls.technology_url = reverse("technology-lis... | true |
e4aa8dd9442b58ee1f9c4dc5a3a5ec4bbe22dc0b | Python | venkatsvpr/Problems_Solved | /LC_Path_Crossing.py | UTF-8 | 1,291 | 3.921875 | 4 | [] | no_license | """
1496. Path Crossing
Given a string path, where path[i] = 'N', 'S', 'E' or 'W', each representing moving one unit north, south, east, or west, respectively. You start at the origin (0, 0) on a 2D plane and walk on the path specified by path.
Return True if the path crosses itself at any point, that is, if at any t... | true |
af3b2ecf40b688c83f20917a5940cb88ccb368c9 | Python | martinvw/e-ink-display | /e-ink-display/screens/screens.py | UTF-8 | 1,443 | 2.6875 | 3 | [] | no_license | import openhab
class Screen:
"""Base screen class."""
def __init__(self) -> None:
return
def refresh(self) -> None:
return
def button_2_label(self) -> str: return None
def button_2_handler(self) -> None:
return
def button_3_label(self) -> str: return None
def ... | true |
6b7370650d4a931697e3c06ad841a4ab809eb69b | Python | done-n-dusted/SpeechEmotionRecognition | /text_test/running_models_boW.py | UTF-8 | 2,622 | 2.734375 | 3 | [] | no_license | # training and testing on various model for BoW features
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
import sys
sys.path.insert(1, '../')
from STFE import Models, DataPreparer
from tensorflow.keras import optimizers
import json
def dump_dict(dict, file_name):
with open(file_n... | true |
b274965e80fef1cfbff76aa23487615474a73a35 | Python | prasanna1695/python-code | /3-2.py | UTF-8 | 1,143 | 4.46875 | 4 | [] | no_license | # How would you design a stack which, in addition to push and pop, also has a function min which returns the minimum element?
#Push, pop and min should all operate in O(1) time.
#you would simply need to store a variable called min and update it as needed.
class Stack:
def __init__(self):
self.minimum = None
se... | true |
91b8a2364a38a607900f8184bf6e400eb239ffcc | Python | MarloDelatorre/leetcode | /1046_Last_Stone_Weight.py | UTF-8 | 815 | 3.5625 | 4 | [] | no_license | from heapq import heapify, heappush, heappop
from unittest import main, TestCase
class Solution():
@staticmethod
def lastStoneWeight(stones):
heap = []
for stone in stones:
heappush(heap, -stone)
while len(heap) > 1:
stone_y, stone_x = heappop(heap), heappop(hea... | true |
d2192b2289eaaa64eea2216fa118469075afe155 | Python | bgoonz/UsefulResourceRepo2.0 | /_PYTHON/DATA_STRUC_PYTHON_NOTES/python-prac/mini-scripts/python_Join_Two_Lists__extend().txt.py | UTF-8 | 76 | 3.203125 | 3 | [
"MIT"
] | permissive | list1 = ["a", "b", "c"]
list2 = [1, 2, 3]
list1.extend(list2)
print(list1)
| true |
9982bc9a93696ba5d351ef4ac62bd2e05effdeb1 | Python | ismael-wael/Hospital-management-system-tkinter-GUI- | /managePatients.py | UTF-8 | 7,525 | 2.609375 | 3 | [] | no_license | from tkinter import *
import tkinter as tk
from tkinter import ttk
from GUI_Functions import *
import xlsxwriter
import xlrd
from helperFunctions import *
holdPatientData = []
headings = ["patient ID", "Dep. Name", "Doctor", "Name","Age",
"Gender", "Address", "Room number", "phone number", "diagnose"]
d... | true |
4f6652f3a38bf843521c85f34ed599202abc4585 | Python | miroslavpetkovic/python-meme-generator-project | /src/app.py | UTF-8 | 2,617 | 2.890625 | 3 | [] | no_license | import random
import os
import requests
from flask import Flask, render_template, abort, request
from MemeEngine import MemeEngine
from QuoteEngine import Importer
from QuoteEngine import QuoteModel
dir_path = os.path.dirname(os.path.realpath(__file__))
app = Flask(__name__, static_folder=dir_path)
meme = MemeEngin... | true |
d10b64e47a1a45c45b52bebb0c862311466b4165 | Python | MithVert/P5 | /model/categorie.py | UTF-8 | 1,288 | 2.75 | 3 | [] | no_license | import mysql.connector
class Categorie():
def __init__(self, sqlmng, idc=None, name=None):
self.sqlmng = sqlmng
self.id = idc
self.name = name
self.valid = True
def update(self):
query = (
"SELECT id, Categorie FROM Categories "
f"WHERE Categor... | true |
a401af168065db964e42d4b9b78c07ccd3b31fee | Python | melwinjose1991/LearningMachineLearning | /python/learning - tensor-flow/Basics/linear_regression.py | UTF-8 | 3,529 | 3.625 | 4 | [] | no_license | # from : https://github.com/nlintz/TensorFlow-Tutorials/blob/master/01_linear_regression.py
import tensorflow as tf
import numpy as np
'''
linspace(): Returns 101 evenly spaced samples, calculated over the interval [-1, 1].
'''
trX = np.linspace(-1, 1, 101)
print(trX)
'''
randn(): Return a sample (or samples) from t... | true |
c78751529ba42622d1110bd1267e453478c57ac9 | Python | p-jacquot/ISN | /test.py | UTF-8 | 2,633 | 2.578125 | 3 | [] | no_license | # Créé par PJACQUOT, le 21/03/2016 en Python 3.2
import pygame
from jeu import Jeu
from fenetre import Fenetre
from molecule import Molecule
from dialogue import Dialog
from niveau import Niveau
import constantes
from pattern import *
import pickle
import niveau
def testplay():
jeu.moleculeJoueur = Molecule('hyd... | true |
1876e5b09b664ef0b353670e137950d3e1270558 | Python | wammar/wammar-utils | /convert-conll-format-to-sent-per-line.py | UTF-8 | 1,451 | 3.015625 | 3 | [] | no_license | import io
import argparse
# parse/validate arguments
argparser = argparse.ArgumentParser()
argparser.add_argument("-i", "--input_filename", required=True)
argparser.add_argument("-o", "--output_filename", required=True)
argparser.add_argument("-d", "--delimiter", default="_")
argparser.add_argument("-c", "--columns", ... | true |
fcd3e0cde7fec1d734cb945d7041906be2618a09 | Python | Deepaklal123/Python | /Chapter_02/prac_q_04_input_function.py | UTF-8 | 220 | 3.6875 | 4 | [] | no_license | #Author: Deepak Lal
# Sukkur IBA University
a= input(" Enter your name ") #This alwaays takes inpt as string
print(a)
num1= input(" Enter your age ") #This alwaays takes inpt as string
num1=int(num1)
print(num1) | true |
998e4c5ab35b65a3e242d0ef51809c2211d9861b | Python | gz5678/CrypticCrosswordSolver | /CrypticSolver.py | UTF-8 | 3,713 | 3.84375 | 4 | [] | no_license | import string
from SolutionFormat import SolutionFormat
from ClueSolver import solve
def CrypticSolver():
print_header()
run = True
while run:
# Get the clue, strip punctuation and change to lower case
clue_str = input("Insert the clue:\n").translate(str.maketrans('', '', string.punctuati... | true |
4c432c358c6749b558bb294829cc4b3187b4cfdd | Python | ChernenkoSergey/Supervised-and-Unsupervised-Learning-with-Python | /Раздел 5 Создание систем рекомендаций/pipeline_trainer.py | UTF-8 | 3,473 | 2.984375 | 3 | [] | no_license | from sklearn.datasets import samples_generator
from sklearn.feature_selection import SelectKBest, f_regression
from sklearn.pipeline import Pipeline
from sklearn.ensemble import ExtraTreesClassifier
# Генерируем некоторые помеченные образцы данных для обучения и тестирования
# Scikit-learn имеет встроенную функцию, ко... | true |
fb3464cda5378ddbe8a14e0e8718c2f4b948f605 | Python | austinlyons/computer-science | /heap/python/heap.py | UTF-8 | 4,375 | 3.828125 | 4 | [] | no_license | from math import floor
class Heap:
def _left(self, i):
return 2*i + 1
def _right(self, i):
return 2*i + 2
def _parent(self, i):
return int(floor((i-1)/2))
def _swap(self, A, i, j):
temp = A[i]
A[i] = A[j]
A[j] = temp
def _valid(self, i):
i... | true |
c50bf8fcaf38c8f91d3f1743062e2597c1ee27b7 | Python | foersterrobert/Pokemon-TD | /bullet.py | UTF-8 | 958 | 3.21875 | 3 | [] | no_license | from settings import *
import pygame
class Bullet:
def __init__(self, screen, x, y, ex, ey, bsize, imgB=None):
self.screen = screen
self.x = x
self.y = y
self.ex = ex
self.ey = ey
self.bsize = bsize
self.imgB = imgB
self.image = None
if self.i... | true |
541096039db4bb40bcadf12285b0e936fef5d98d | Python | haoruizh/CS322Project | /chatProject/server/User_dic.py | UTF-8 | 959 | 2.6875 | 3 | [] | no_license | from socket import *
import json
import os
import openpyxl
class User:
filename = 'C://Users/Jihui/Documents/GitHub/CS322Project/chatProject/server/user.txt'
user_info = {}
def __init__(self):
pass
def show_profile(self, userName):
print(self.user_info[userName])
return self.u... | true |
83dc2ad21ac34878de0b801df102eb7803fa31d3 | Python | anthony-chang/machine-learning-playground | /housingPrices.py | UTF-8 | 655 | 2.953125 | 3 | [] | no_license | # https://www.hackerrank.com/challenges/predicting-house-prices/problem
from sklearn import linear_model
import numpy as np
features, N = (int(n) for n in input().split())
x_train = []
y_train = []
x_test = []
x_train = [0 for i in range(N)]
for i in range(N):
x_train[i] = list(map(float, input().split()))
x_tra... | true |
cb788dbfc49bdf215aedd7f3e1dc90fe8a5b7077 | Python | kate-codebook/movie_recommendersys | /itemBased.py | UTF-8 | 1,213 | 3.28125 | 3 | [] | no_license | import pandas as pd
import ast
def create_item_based_rating(movies): # movies type dict
movies = str(movies)
rating_data = pd.read_csv('ratings.csv')
movie_data = pd.read_csv('movies.csv')
user_movie_rating = pd.merge(rating_data, movie_data, on='movieId')
user_movie_rating_p = user_movie_rating.... | true |
90b1d8b52dbaa41f051a98d21c16bbf64d04a5b0 | Python | ungerw/class-work | /ch6ex5.py | UTF-8 | 97 | 2.59375 | 3 | [] | no_license | str = 'X-DSPAM-Confidence:0.8475'
mark = str.find(':')
number = float(str[mark+1:])
print(number) | true |
1210dcf6d176ad6bc7941c1c25bafc38ce022fcf | Python | msetkin/udacity_streaming | /consumers/models/lines.py | UTF-8 | 2,126 | 2.671875 | 3 | [] | no_license | """Contains functionality related to Lines"""
import json
import logging
from models import Line
from ksql import TURNSTILE_SUMMARY_TABLE
logger = logging.getLogger(__name__)
class Lines:
"""Contains all train lines"""
def __init__(self):
"""Creates the Lines object"""
self.red_line = Line(... | true |
d397eaf5dd020a8124d1a7f68af30c3339ad6a93 | Python | dingzhaohan/deep_research | /spiders/git/git/spiders/littlegit.py | UTF-8 | 3,366 | 2.640625 | 3 | [
"Apache-2.0"
] | permissive | # -*- coding: utf-8 -*-
import scrapy
from git.items import GitItem
import pandas as pd
import json
import time
import datetime
# df = pd.read_json("/home/zhaohan/Desktop/research/lastdata_papers_with_code_repo.json")
df = pd.read_json('/Users/zhaohan/Desktop/deep_research/data/links-between-papers-and-code.json')
'''
... | true |
100f0252883b40d7eb2501a04338306c06ed6794 | Python | SimmonsChen/LeetCode | /公司真题/顺丰/不要1.py | UTF-8 | 1,027 | 3.40625 | 3 | [] | no_license | def helper(n):
while n > 0:
if n % 10 != 1:
return False
n = n // 10
return True
def isHaveOne(n):
if n == 1: return True
if n < 10: return False
cur = n # 保留原数字
tar = []
while cur > 0:
t = cur % 10
if t == 1: return True
tar.append(t)
... | true |
d12747e228c13b95ea4c87b58b391179d65d8220 | Python | iblezya/Python | /Semana 2/Cuarentena/cond8.py | UTF-8 | 859 | 3.78125 | 4 | [] | no_license | Nombre = str(input('Ingrese el nombre del producto: '))
while (True):
try:
Precio = float(input('Ingrese el precio del producto(S/.): '))
Cantidad = int(input('Ingrese la cantidad de productos: '))
Monto = Precio*Cantidad
if Cantidad >= 100:
MontoFinal = 0.... | true |
69d0d49788987a148607933c3f188bea27469e90 | Python | muskanmahajan37/python-scic | /sesion_3/resorte.py | UTF-8 | 294 | 2.96875 | 3 | [] | no_license | import math
A = 10
j = 1
k = 3
m = 1
def xf(t):
w = (k / m) ** 0.5
return A * math.sin(w * t + j)
f = open("resorte.csv", "w")
n = 100
t_min = 0
t_max = 4
for i in range(n):
t = t_min + (t_max - t_min) / (n - 1) * i
x = xf(t)
f.write("{}, {}\n".format(t, x))
f.close() | true |
d1e2a7a35b02158767334621fab48c736e364d3d | Python | barry-jin/array-api-tests | /array_api_tests/special_cases/test_atan2.py | UTF-8 | 12,415 | 3.03125 | 3 | [
"MIT"
] | permissive | """
Special cases tests for atan2.
These tests are generated from the special cases listed in the spec.
NOTE: This file is generated automatically by the generate_stubs.py script. Do
not modify it directly.
"""
from ..array_helpers import (NaN, assert_exactly_equal, exactly_equal, greater, infinity, isfinite,
... | true |
4a86bb3dfb25dd90f71c488dcc084e913df87edc | Python | Zararthustra/holbertonschool-higher_level_programming | /0x0F-python-object_relational_mapping/9-model_state_filter_a.py | UTF-8 | 789 | 2.59375 | 3 | [] | no_license | #!/usr/bin/python3
"""
lists all State objects that contain the letter a from
the database hbtn_0e_6_usa
"""
import sqlalchemy
import sys
from sqlalchemy.orm import sessionmaker
from sqlalchemy import create_engine
from model_state import Base, State
if __name__ == "__main__":
username = sys.argv[1]
password =... | true |
a7e21e100a132df9a3ed88666c965a0ce6e6807d | Python | delaven007/AI | /2/5-ridge-岭回归2.py | UTF-8 | 1,035 | 3.046875 | 3 | [] | no_license | import numpy as np
import sklearn.linear_model as lm
import matplotlib.pyplot as mp
# 采集数据
x, y = np.loadtxt('./data/ml_data/abnormal.txt', delimiter=',', usecols=(0,1), unpack=True)
x = x.reshape(-1, 1)
# 创建线性回归模型
model = lm.LinearRegression()
# 训练模型
model.fit(x, y)
# 根据输入预测输出
pred_y1 = model.predict(x)
# 创建岭回归模型
mode... | true |
a59a298ad1e8b4273f4bcc5d264b84d72eec2688 | Python | decentjik1128/python_code | /ch_1/pythonic_code/list_comprehensions.py | UTF-8 | 793 | 3.828125 | 4 | [] | no_license | #List Comprehension
result = [i for i in range(10)]
print(result)
#조건을 만족할 때만 추가
result = [i for i in range(10) if i%2 == 0]
print(result)
#이중 for문 방식
word_1 = 'Hello'
word_2 = 'World'
#1차원 방
result = [i+j for i in word_1 for j in word_2]
print(result)
case_1 = ['A', 'B', 'C']
case_2 = ['D', 'E', 'A']
#1차원 방식
result... | true |
899323fab920fa2c86edc03662a8fdab5cca0ac3 | Python | mwstobo/rent-toronto | /cache.py | UTF-8 | 1,049 | 2.90625 | 3 | [
"MIT"
] | permissive | """Caching for advert ids"""
from typing import List
import redis
import config
REDIS_POOL = redis.ConnectionPool(host=config.REDIS_HOST, decode_responses=True)
ADVERT_IDS_KEY = "adverts"
ADVERT_INFO_KEY = "advert_info"
def contains_id(advert_id: str) -> bool:
"""Check if this advert is in the cache"""
cl... | true |
f949490feda8260fcbd2bfd44409522012978172 | Python | tessyoncom/lessons | /greet.py | UTF-8 | 98 | 2.71875 | 3 | [] | no_license | tes = 'Hello, World!'
print(tes)
if 5<10:
print("hurry, I know maths!")
print("program ends")
| true |
cb99f15517f56a5d6a8d6374a0274c0b58a7ef12 | Python | DiniH1/python_engineer89_basics | /variables.py | UTF-8 | 1,597 | 4.75 | 5 | [] | no_license | # lets test
print("Hello Dini H")
#print func used to display outcome provided in the string
#Variables
#python variables as a place holder to store data
# it could me a string "anything between these quotations"
# integers/numbers
#Syntax to create a variable name of the variable = value of the variable
#foolow your ... | true |
662a4b1ae882a22b1448d866d24e781b22072fa2 | Python | RajeshDas7/webscraping | /tweeter/twitter_fetch_hashtag.py | UTF-8 | 921 | 2.75 | 3 | [] | no_license | import tweepy
consumer_key = "nvEV4sEBSWM3HjwkcPu9ug6VR"
consumer_secret = "3I6VFDNLbRGGkq7um1RqouLFs7EArViu3KoKMdN72QzN2i7Mwm"
access_token = "1086269917295390720-rwbnIFrN2tjmQNjmr4dh849WH2Aewk"
access_token_secret = "hwweAzNe6ltT9MaFHRaFTk7ZJPd04a6HdFHuDUDEKniyH"
import csv
# import pandas as pd
auth = t... | true |
3128c86386e2f379053ea5f73dc056f6d5c39370 | Python | coti/adventofcode | /day13/day13part1.py | UTF-8 | 2,163 | 2.96875 | 3 | [] | no_license | #!/usr/bin/env python
import sys
import itertools
def parseFile( line ):
line = line.split( '.\n' )[0]
tab = line.split( ' ' )
a = tab[0]
b = tab[-1]
h = -1
try:
h = int(tab[3])
except ValueError:
print "happyness", tab[3], "error"
return None
if tab[2] == "lose... | true |
be3521d923cfa433022aa5f8f4290b6a7d8bae1c | Python | StoneCong/tools | /teaching_kids/001.your_name.py | UTF-8 | 116 | 3.765625 | 4 | [] | no_license | # this will ask for your name and then print it out for you.
name = input("What is your name? ")
print("Hi,", name)
| true |
c9a5faff9139475cc1deb3ca4a09f1d8989460eb | Python | ishine/SpectralCluster | /tests/utils_test.py | UTF-8 | 2,849 | 2.640625 | 3 | [
"Apache-2.0"
] | permissive | import unittest
import numpy as np
from spectralcluster import utils
class TestComputeAffinityMatrix(unittest.TestCase):
"""Tests for the compute_affinity_matrix function."""
def test_4by2_matrix(self):
matrix = np.array([[3, 4], [-4, 3], [6, 8], [-3, -4]])
affinity = utils.compute_affinity_matrix(matri... | true |
a9710c0f4a245cd63a4bd92fa919ff228a1766f4 | Python | vectominist/MedNLP | /src/model/qa_model_rulebase_2.py | UTF-8 | 3,969 | 2.546875 | 3 | [
"MIT"
] | permissive | '''
File [ src/model/qa_model_rulebase_2.py ]
Author [ Chun-Wei Ho & Heng-Jui Chang (NTUEE) ]
Synopsis [ New rule-based QA method ]
'''
import numpy as np
import tqdm
import edit_distance
import re
import multiprocessing as mp
inv_chars = '錯|誤|有誤|不|沒|(非(?!常|洲))|(無(?!套))'
def is_inv(sent: str):
... | true |
9439da95bdf627509cf8fe25d37f12226346b06e | Python | dawidbrzozowski/sentiment_analysis | /text_clsf_lib/preprocessing/vectorization/data_vectorizers.py | UTF-8 | 933 | 3.125 | 3 | [] | no_license | from text_clsf_lib.preprocessing.vectorization.output_vectorizers import OutputVectorizer
from text_clsf_lib.preprocessing.vectorization.text_vectorizers import TextVectorizer
class DataVectorizer:
"""
This class is meant to vectorize X and y (texts and outputs).
To perform that, it uses TextVectorizer an... | true |
f5f25b3ed4946536b875ae34afa736b28792f7b6 | Python | mrirecon/SSA-FARY | /SupFig4/plot.py | UTF-8 | 2,900 | 2.515625 | 3 | [] | no_license | #!/usr/bin/env python3
# Copyright 2020. Uecker Lab, University Medical Center Goettingen.
#
# Author: Sebastian Rosenzweig, 2020
# sebastian.rosenzweig@med.uni-goettingen.de
#
# Script to reproduce SupFig4 of the following manuscript:
#
# Rosenzweig S et al.
# Cardiac and Respiratory Self-Gating in Radial MRI using an... | true |
8683e4b2fb78ec57c1566e971614ab1878b9433c | Python | VP-0822/miniexcel | /src/excel.py | UTF-8 | 2,200 | 2.875 | 3 | [] | no_license | import JSONDeserializer
import workbook
class WorkbookHandler:
'This class handles workbook opening/closing jobs.'
#dictionary to maintain opened workbooks against thier file paths
opened_workbooks = {}
def __init__(self, workbook_name):
self.workbook_name = workbook_name
self.w... | true |
2d1ec10a765c9ae7deee7b322729adf03793c09b | Python | pcicales/MICCAI_2021_aglom | /utils/eval_utils.py | UTF-8 | 10,030 | 2.78125 | 3 | [] | no_license | import torch
import numpy as np
import matplotlib.pyplot as plt
# from sklearn.utils.multiclass import unique_labels
import os
def get_binary_accuracy(y_true, y_prob):
assert y_true.ndim == 1 and y_true.size() == y_prob.size()
y_prob = y_prob > 0.5
return (y_true == y_prob).sum().item() / y_true.size(0)
d... | true |
d13f8aa0f2fb53bb59ac4258abaa6cefe7dc6ce1 | Python | ssj24/TIL | /03_django/03_django_form/articles/templatetags/make_link.py | UTF-8 | 862 | 2.765625 | 3 | [] | no_license | from django import template
register = template.Library() # 기존 템플릿 라이브러리에
@register.filter
def hashtag_link(word):
# word는 article 객체가 들어갈 건데
# article의 content들만 모두 가져와서 그 중 해시태그에만 링크를 붙인다
content = word.content + ' ' # 공백으로 구분하기 때문
hashtags = word.hashtags.all()
for hashtag in hashtags:
... | true |
88e3daf1fd0e0a363f2749b1b434bfd2fb3a426a | Python | offbynull/offbynull.github.io | /docs/data/learn/Bioinformatics/input/ch4_code/src/helpers/HashableCollections.py | UTF-8 | 935 | 2.921875 | 3 | [] | no_license | from collections import Counter
class HashableCounter(Counter):
def __init__(self, v=None):
if v is None:
super().__init__()
else:
super().__init__(v)
def __hash__(self):
return hash(tuple(sorted(self.items())))
class HashableList(list):
def __init__(self... | true |
bb378cc47edd1ec722339c192c645b36c7fa5ba6 | Python | chenshanghao/Interview_preparation | /Leetcode_250/Problem_70/my_solution.py | UTF-8 | 501 | 3.453125 | 3 | [] | no_license | class Solution(object):
def climbStairs(self, n):
"""
:type n: int
:rtype: int
"""
# Question 1: would n be smaller than 1 ?
# Question 2: would n be larger than maxint
# In Python 3, this question doesn't apply. The plain int type is unbounded.
... | true |
d3c4fb21c01d834e1dfabe7ceb04e1cce801fca3 | Python | jianhui-ben/leetcode_python | /2013. Detect Squares.py | UTF-8 | 1,406 | 4.34375 | 4 | [] | no_license | # 2013. Detect Squares
# You are given a stream of points on the X-Y plane. Design an algorithm that:
#
# Adds new points from the stream into a data structure. Duplicate points are allowed and should be treated as different points.
# Given a query point, counts the number of ways to choose three points from the data s... | true |
5540d0a34c9c5ecb8073e3c270f44d7c05145f7c | Python | kiligsmile/python | /05_高级数据类型/sml_16_字符串判断方法.py | UTF-8 | 374 | 3.921875 | 4 | [] | no_license | # 1.判断空白字符
space_str = " "
print(space_str.isspace())
space_str = "a"
print(space_str.isspace())
space_str = "\t\n"
print(space_str.isspace())
# 1>都不能判断小数
# num_str="1.1"
# 2>unicode字符串
num_str = "\u00b2"
# 3>中文数字
num_str = "一千零一"
print(num_str)
print(num_str.isdecimal())
print(num_str.isdigit())
print(num_str.isnumer... | true |
46a745821501963813500cfb57708797a3896abb | Python | thevalzo/dataAnalytics2018 | /focused_crawler/focused_crawler/spiders/GDB_spyder.py | UTF-8 | 3,376 | 2.53125 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import scrapy
import unidecode
import MySQLdb
from bs4 import BeautifulSoup
class GDBSpider(scrapy.Spider):
# Spyder name
name = "GDB"
db = ""
def start_requests(self):
#Keywords to search in the search engine of GDB
#keywords=["brescia"]
keywords = ... | true |
ab12a5d11ddc81bd90c421af7bf8f99426a16345 | Python | antofik/captcha | /statistics.py | UTF-8 | 1,326 | 2.78125 | 3 | [] | no_license | import os
import json
from library import *
try:
with open('cache.txt', 'r') as f:
cache = json.loads(f.read()) or {}
except Exception,e:
cache = {}
if not os.path.exists("letters"):
os.makedirs("letters")
s = {}
def check(image, index):
global cache
global s
im... | true |
59cbb3aff9665ad2d7bfdf30db8be4d2329f27ed | Python | JosephLevinthal/Research-projects | /5 - Notebooks e Data/1 - Análises numéricas/Arquivos David/Atualizados/logDicas-master/data/2019-1/226/users/4162/codes/1800_2568.py | UTF-8 | 213 | 2.71875 | 3 | [] | no_license | from numpy import*
m = int(input("tamanho:"))
f = zeros(m, dtype=int)
d = "*"
e = "*"
g = ""
o = ""
for i in range(size(f)):
e = "*"
d = "*"
g = g + o
d = "*"*m
e = "*"*m
print(d+o+e)
m = m - 1
o = o +"oo" | true |
993d210b2086cefc927fefb05c593c920726aa68 | Python | ForceCry/iem | /scripts/coop/compute_climate.py | UTF-8 | 3,858 | 2.546875 | 3 | [] | no_license | # Computes the Climatology and fills out the table!
import mx.DateTime
import iemdb
import psycopg2.extras
import network
import sys
nt = network.Table(("IACLIMATE", "MNCLIMATE", "NDCLIMATE", "SDCLIMATE",
"NECLIMATE", "KSCLIMATE", "MOCLIMATE", "ILCLIMATE", "WICLIMATE",
"MICLIMATE", "INCLIMATE", "OHCLIMATE", "KYCLIM... | true |
6e015350a30b5a7e234623d7f771745ff1278133 | Python | HanifanNahwi/Python-Projects-Protek | /Chapter 8/Project13.py | UTF-8 | 735 | 3.078125 | 3 | [] | no_license | nilai = [{'nim' : 'A01', 'nama' : 'Amir', 'mid' : 50, 'uas' : 80},
{'nim' : 'A02', 'nama' : 'Budi', 'mid' : 40, 'uas' : 90},
{'nim' : 'A03', 'nama' : 'Cici', 'mid' : 50, 'uas' : 50},
{'nim' : 'A04', 'nama' : 'Dedi', 'mid' : 20, 'uas' : 30},
{'nim' : 'A05', 'nama' : 'Fifi', 'mid' ... | true |
76012fa4f7af19a8315927d4e5e62797be029cc9 | Python | LorenzoPratesi/DataSecurity | /Set_1/text_frequency.py | UTF-8 | 5,330 | 3.5 | 4 | [] | no_license | import re
import math
import matplotlib.pyplot as plot
def get_text():
return open("texts/Moby_Dick_chapter_one.txt", 'r').read().replace('\n', '')
def trim_text(text):
text = text.upper() # conversione in maiuscolo
text = re.sub(r"['\",.;:_@#()”“’—?!&$\n]+ *", " ", text) # conversione dei caratteri s... | true |
b30ba08b9a017e7baa2c097816b427bff1ce30de | Python | tmibvishal/healTrip | /auth_queries.py | UTF-8 | 1,695 | 2.78125 | 3 | [] | no_license | import db
def new_user(username, email, password):
if(username=='admin'):
db.commit("insert into users(uname,email,pass,is_admin) values(%s, %s, %s, %s)", (username, email, password, True))
else:
db.commit("insert into users(uname,email,pass,is_admin) values(%s, %s, %s, %s)", (username, email, ... | true |
6d8c9be56d6e219218a9b5f19451edefbe551c92 | Python | devin-liu/LTV | /CohortAnalysis.py | UTF-8 | 3,017 | 3.171875 | 3 | [] | no_license | # Import modules
import pandas as pd
import numpy as np
from datetime import datetime, timedelta, date
# Load in data set by reading the CSV
my_data = pd.read_csv('MRR Company Data Set.csv')
def get_datetime_from_string(date_string):
return datetime.strptime(date_string, '%m/%d/%y')
def get_order_period_from_date... | true |
703d36e44d1f053dfadf455aab11a46307603f49 | Python | barrosfabio/result-analysis | /convert_to_one.py | UTF-8 | 1,565 | 2.609375 | 3 | [] | no_license | import pandas as pd
import os
columns = ['none', 'ros', 'smote', 'borderline', 'adasyn', 'smote-enn', 'smote-tomek']
def write_df_csv(path, results_df):
final_results_df = pd.DataFrame(columns=columns)
final_results_df['none'] = results_df.iloc[:,0]
final_results_df['ros'] = results_df.iloc[:,1]
final... | true |
ad2867a3ba17b7310c7d9ade5cfcedadcb540e89 | Python | Ran4/py-contract-disallower | /tests/test.py | UTF-8 | 1,332 | 3.015625 | 3 | [] | no_license | import unittest
from disallower import disallow, require, Warn, Ignore
from base import ContractWarning, ContractException
## Predicate functions:
def negative_values(x: int) -> bool:
return x < 0
def valid_lang(s: str) -> bool:
return s.lower() in ["sv", "en"]
## Test function definitions:
@disallow(age=n... | true |
1c5f970757b4fe8a79d0220f0dd3dffbf5683dd2 | Python | ntpz/rbm2m | /rbm2m/action/record_importer.py | UTF-8 | 3,718 | 2.75 | 3 | [
"Apache-2.0"
] | permissive | # -*- coding: utf-8 -*-
import logging
from record_manager import RecordManager
from scan_manager import ScanManager
import scraper
from rbm2m.util import to_str
logger = logging.getLogger(__name__)
class RecordImporter(object):
def __init__(self, session, scan):
self.session = session
self.sc... | true |
8c612752cbc0760323bb904bd4539a881a99bf10 | Python | harris-ippp/hw-6-linapp | /e2.py | UTF-8 | 1,036 | 2.765625 | 3 | [] | no_license | #!/usr/bin/env python
from bs4 import BeautifulSoup
import requests
url_va = 'http://historical.elections.virginia.gov/elections/search/year_from:1924/year_to:2016/office_id:1/stage:General'
req_va = requests.get(url_va)
html_va = req_va.content #getting the contents of the website
soup = BeautifulSoup(html_v... | true |
76446456c548660d046f8658ec3687591e281ce4 | Python | chrispun0518/personal_demo | /leetcode/88. Merge Sorted Array.py | UTF-8 | 874 | 2.859375 | 3 | [] | no_license | class Solution(object):
def merge(self, nums1, m, nums2, n):
"""
:type nums1: List[int]
:type m: int
:type nums2: List[int]
:type n: int
:rtype: None Do not return anything, modify nums1 in-place instead.
"""
pt1 = m - 1
pt2 = n - 1
poi... | true |
981b7e93b10f53cbd6223640e3312bc297d3a1d9 | Python | csvoss/onelinerizer | /tests/try_except.py | UTF-8 | 1,212 | 3.484375 | 3 | [
"MIT"
] | permissive | try:
print 'try 0'
except AssertionError:
print 'except 0'
else:
print 'else 0'
try:
print 'try 1'
assert False
except AssertionError:
print 'except 1'
else:
print 'else 1'
try:
try:
print 'try 2'
assert False
except ZeroDivisionError:
print 'wrong except 2'... | true |
49f680989861bf1a247746e373567db6702c89fa | Python | MyungSeKyo/algorithms | /백준/1748.py | UTF-8 | 538 | 3.28125 | 3 | [] | no_license | import sys
input = sys.stdin.readline
n = input().strip()
digits = len(n) - 1
n = int(n)
ret = 0
for i in range(digits):
ret += 9 * (10 ** i) * (i + 1)
ret += (n - (10 ** digits - 1)) * (digits + 1)
print(ret)
MAX = '100000000' # 9자리
sum_lst = [0]
len_all = 0
for i in range(1, len(MAX)+1) :
len_all += 9... | true |
5eb1cb5f27bc80d8cbcff76719fc6d453ec7d806 | Python | skosarew/EpamPython2019 | /06-advanced-python/hw/task1.py | UTF-8 | 2,123 | 3.625 | 4 | [] | no_license | """
E - dict(<V> : [<V>, <V>, ...])
Ключ - строка, идентифицирующая вершину графа
значение - список вершин, достижимых из данной
Сделать так, чтобы по графу можно было итерироваться(обходом в ширину)
"""
import collections
class GraphIterator(collections.abc.Iterator):
def __init__(self, collection):
self... | true |
1efc8f1b8fc85ff891d7835868c1627a7bb65f1c | Python | nicokiritan/sosc-sosw-modder | /ypac_unpack.py | UTF-8 | 792 | 2.859375 | 3 | [] | no_license |
import os
import sys
import exg
if len(sys.argv) < 3:
print("Drag&drop .dat and .hed")
input()
exit()
dat_path = ""
hed_path = ""
drop_files = sys.argv[1:]
for drop_file in drop_files:
if drop_file[-4:] == ".dat":
dat_path = drop_file
elif drop_file[-4:] == ".hed":
hed_path = drop_file
if dat_pat... | true |
172fc50d89794ed365517792ae75be9650c0d13b | Python | s0ap/arpmRes | /arpym/estimation/fit_factor_analysis.py | UTF-8 | 1,973 | 2.6875 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
from arpym.estimation.factor_analysis_paf import factor_analysis_paf
from arpym.estimation.factor_analysis_mlf import factor_analysis_mlf
from arpym.statistics.meancov_sp import meancov_sp
def fit_factor_analysis(x, k_, p=None, method='PrincAxFact'):... | true |
8a875241356049a99d00341a59c5dbca861bba4b | Python | anakka6/algorithms | /algorithms/add_lists_reverse.py | UTF-8 | 2,314 | 3.859375 | 4 | [] | no_license | '''Add 342 and 465 and print 807, The lists are set up as 2->4->3 and 5->6->4. The output should be 7->0->8.'''
class Node():
def __init__(self, data):
self.data = data
self.next = None
class LinkedList():
def __init__(self, head=None):
self.head = head
def append(s... | true |
117d0cffb5a9faa7b0918ae98a8f4ecb2e38a041 | Python | GinkgoX/MachineLearning | /KNN/digitsRecognize.py | UTF-8 | 1,435 | 3.203125 | 3 | [] | no_license | import operator
import numpy as np
from os import listdir
from sklearn.neighbors import KNeighborsClassifier as kNN
'''
Function : img2vector(filename)
Description : to covert img(in filename) to vector
Args : filename
Rets : vectorImg
'''
def img2vector(filename):
vectorImg = np.zeros((1, 1024))
fr = open(filen... | true |
f64b6129e5015f95b71e756b183ea5598b93a179 | Python | khygu0919/codefight | /Intro/allLongestStrings.py | UTF-8 | 307 | 3.53125 | 4 | [] | no_license | '''
Given an array of strings, return another array containing all of its longest strings.
'''
def allLongestStrings(inputArray):
b=[]
c=0
for i in inputArray:
b.append(len(i))
c=max(b)
b=[]
for j in inputArray:
if len(j)==c:
b.append(j)
return b
| true |
07a08414711196f8ea857bc69f1a93a544b8b717 | Python | elezbar/Python_Tetris | /test.py | UTF-8 | 180 | 3 | 3 | [] | no_license | s = [{"name": "A", "parents": []}, {"name": "B", "parents": ["A", "C"]}, {"name": "C", "parents": ["A"]}]
def parr(d,p, i = 1):
for k in d:
if p in k[parents]
| true |
715417861c882a0e110f52f7287b320219dd9b24 | Python | gcastroid/img2mif | /img2mif.py | UTF-8 | 2,024 | 3.359375 | 3 | [
"MIT"
] | permissive | from PIL import Image
import sys
# read the arguments
img_file = sys.argv[1]
out_file = sys.argv[2]
# read the image
image = Image.open(img_file)
pixels = image.load()
h_pixels, v_pixels = image.size
# calc the number of address bits and the memory depth
h_bits = (h_pixels - 1).bit_length()
v_bits = (... | true |
c5c04301b377f99cf2b9420248d2a3ab1c913267 | Python | Melkemann84/ProjectEuler | /projectEuler_04.py | UTF-8 | 820 | 4.1875 | 4 | [] | no_license | import time
# https://projecteuler.net/problem=4
''' Larges palindrome product
A palindromic number reads the same both ways. The largest palindrome made from the product of two 2-digit numbers is 9009 = 91 × 99.
Find the largest palindrome made from the product of two 3-digit numbers.
'''
def isPalindrome(num):
... | true |
95bc83ce3b68800ca1ee1ac892aff276274c3787 | Python | GyuReeKim/DailyCode | /July/code_0714_1.py | UTF-8 | 2,394 | 4.4375 | 4 | [] | no_license | # if문을 활용한 선택 프로그램 작성
import random
print("게임 이름을 입력하세요.")
game_name = input()
hunter = ["타격감", "솔플", "운영"]
survivor = ["멘탈", "팀워크", "스릴", "뚝배기"]
# 랜덤 추출1
hunt_random1 = random.choice(hunter)
surv_random1 = random.choice(survivor)
# 질문1
print(f"당신에게는 {hunt_random1}과 {surv_random1} 중에 어떤 것이 중요합니까?")
print(f"{hunt_ra... | true |
4b0bdefee6479b70711da69cfccc8739ca61f69f | Python | pchatanan/AllState | /src/AllState.py | UTF-8 | 19,852 | 3.171875 | 3 | [] | no_license |
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
# Print all rows and columns. Dont hide any
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
# Disable SettingWithCopyWarning
pd.option... | true |
b6aaacd39fb2e27ab205d5d724e079ea3ba7a982 | Python | aljeshishe/tickets | /proxies/parse.py | UTF-8 | 508 | 2.59375 | 3 | [] | no_license | import sys
import json
import re
from collections import defaultdict
d = defaultdict(lambda: defaultdict(int))
with open(sys.argv[1]) as f:
for line in f:
protos, domen = re.match('.+\[(.+)\].+ (.+)>', line).groups()
protos = protos.split(', ')
print(protos, domen)
for proto in prot... | true |
4ef264f871bfafdb542384612ecff49659b5b2e2 | Python | benpmeredith/Ames_Iowa_Exercise | /lib/__init__.py | UTF-8 | 583 | 2.671875 | 3 | [] | no_license | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import tqdm
import warnings
warnings.filterwarnings('ignore')
np.random.seed(42)
from IPython.display import display
from bs4 import BeautifulSoup
import csv
print('Pandas Initiated')
print('Numpy Initiated')
print('M... | true |
212c18ac96bf1804d5ba1172d4b71705400144de | Python | pablo-solis/VARDER | /utilsVAR.py | UTF-8 | 10,075 | 2.609375 | 3 | [] | no_license | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import nltk
import yfinance as yf
# from nltk.sentiment.vader import SentimentIntensityAnalyzer
import io
import base64
import re
import seaborn as sns
# import bls
# Import Statsmodels
from statsmodels.tsa.api import VAR
from random import choic... | true |
57aa59e3207780fe30917d50be4f7db06003f95a | Python | JohnCorley/PythonLearning | /FirstExample.py | UTF-8 | 601 | 4.25 | 4 | [] | no_license | Garage = "Tesla", "Lexus", "Bike"
for each_car in Garage:
print(each_car)
print('He said \"Hello There\"')
print(4**4)
count = 0
while count < 10:
print("The count is ",count)
count += 1
for y in range(1,100,7):
print ("Y is :",y)
count=int(input("Enter Count"))
if count < y:
print ("Count ... | true |
1b230ed871a9c39da46b3884badc0af5651434bd | Python | mercurialjc/cryptopals | /implement_pkcs7_padding.py | UTF-8 | 910 | 3.984375 | 4 | [] | no_license | #!/usr/bin/env python
"""Implement PKCS#7 padding
A block cipher transforms a fixed-sized block (usually 8 or 16 bytes) of plaintext into ciphertext. But we almost never want to transform a single block; we encrypt irregularly-sized messages.
One way we account for irregularly-sized messages is by padding, creating a... | true |
652dfa5591681ac300a834e68b0884eeb2351367 | Python | PencilCode/pencilcode | /content/lib/pencilcode.py | UTF-8 | 7,259 | 2.875 | 3 | [
"MIT",
"BSD-3-Clause"
] | permissive | import pencilcode_internal
# The SpriteObject class wraps a jQuery-turtle object so it can be used in Python.
# This includes Turtle, Sprite, Piano, and Pencil objects.
class SpriteObject():
def __init__(self, jsSpriteObject):
self.jsSpriteObject = jsSpriteObject
###################
## Move Comman... | true |
36fc8273143ca086da34d4d34cd140e1a32c7765 | Python | Charleo85/SIS-Rebuild | /misc/data/hello.py | UTF-8 | 851 | 2.8125 | 3 | [
"BSD-3-Clause"
] | permissive | from pyspark import SparkContext
sc = SparkContext("spark://spark-master:7077", "PopularItems")
data = sc.textFile("/tmp/data/inputs/sample.in", 2) # each worker loads a piece of the data file
pairs = data.map(lambda line: line.split(",")) # tell each worker to split each line of it's partition
pages = pairs.m... | true |
f93b3a6286ea77881d77265a76c4b36daac7c99d | Python | crystalee01/read112 | /read112code.py | UTF-8 | 12,719 | 3.46875 | 3 | [] | no_license | from cmu_112_graphics import *
from texttospeech import *
from tkinter import *
import random, math
from PIL import Image
import string
'''
Goal: make educational app for children with dyslexia
Features:
- generate random words with confusing vowels and playback separate phonetic sounds
- highlight; lots of colors... | true |
8ba6f3b56c4603d64614b137859efbcdd275c35c | Python | felipesteodoro/tdc2020sp | /template_simple_ga_feature_selection.py | UTF-8 | 4,269 | 2.53125 | 3 | [] | no_license |
import random
import numpy as np
#pip install deap
from deap import base
from deap import creator
from deap import algorithms
from deap import tools
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn import metrics
from sklearn.metrics i... | true |
aa0435b4dd54a4d902dd9318f965c2f04582b32b | Python | chahinMalek/automata | /main.py | UTF-8 | 546 | 2.78125 | 3 | [] | no_license | from automata import Alphabet
from automata import Nfa
al = Alphabet({'a', 'b'})
n = Nfa(3, al, 0, 0)
n.add_transition(0, 1, 'b')
n.add_transition(0, 2, None)
n.add_transition(1, 1, 'a')
n.add_transition(1, 2, 'a')
n.add_transition(1, 2, 'b')
n.add_transition(2, 0, 'a')
# n: Nfa = Nfa(2, al, 0, 0)
# n.add_transiti... | true |
32851ce2d3bc79cd24acf298faf62738df4c9376 | Python | comojin1994/Algorithm_Study | /Uijeong/Python/SM/test4.py | UTF-8 | 832 | 3.21875 | 3 | [] | no_license | import sys
input = sys.stdin.readline
def binary_search(arr, key):
lower = 0
upper = len(arr) - 1
while lower <= upper:
mid = (lower + upper) // 2
if key <= arr[mid]:
upper = mid - 1
else:
lower = mid + 1
return lower
if __name__ == "__main__":
N = i... | true |
a3904dcb5bcc3be09aa51b4b6f1afa577abd8117 | Python | akaped/pygments-styles | /themes/vividchalk.py | UTF-8 | 1,176 | 2.546875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Vividchalk Colorscheme
~~~~~~~~~~~~~~~~~~~~~~
Converted by Vim Colorscheme Converter
"""
from pygments.style import Style
from pygments.token import Token, Comment, Name, Keyword, Generic, Number, Operator, String
class VividchalkStyle(Style):
background_color = '#000000'
... | true |
8c1b0c7373b4c24b7907c9e7a4bc7251c3b9605e | Python | MarkCBell/bigger | /bigger/draw.py | UTF-8 | 17,958 | 2.8125 | 3 | [
"MIT"
] | permissive | """ A module for making images of laminations. """
from __future__ import annotations
import os
from copy import deepcopy
from math import sin, cos, pi, ceil
from typing import Any, Generic, Optional, TypeVar
from PIL import Image, ImageDraw, ImageFont # type: ignore
import bigger
from bigger.types import Edge, Co... | true |
050fec0ac2fd0eb74e694485b79c7b6da7369525 | Python | ScottLiao920/Arduino_Hourglass | /gy521/calibration.py | UTF-8 | 1,555 | 3.234375 | 3 | [
"Apache-2.0"
] | permissive | import serial
import io
from sympy import *
def getparas():
x = 0
y = 0
z = 0
for i in range(5):
x += float(sio.readline())
y += float(sio.readline())
z += float(sio.readline())
print("AcX AcY AcZ")
print(x,y,z)
x = x/5.00
y = y/5.00
... | true |
56014991cfe57f34749b7f8b2c5897c8a5b1ee4c | Python | nanakwame667/Wine-Quality-Prediction | /PROJECT_FILES/utils.py | UTF-8 | 2,089 | 2.71875 | 3 | [] | no_license | import time
import pandas as pd
# models
from sklearn.linear_model import LinearRegression, LogisticRegression
from sklearn.ensemble import RandomForestClassifier
from sklearn.preprocessing import StandardScaler
from sklearn.tree import DecisionTreeClassifier
from sklearn.svm import SVC
from sklearn.metrics import co... | true |
7cb7af696f740899d577af67074e035905dcbf3c | Python | lrdmic/Pycharm-Projects | /26_listas.py | UTF-8 | 1,765 | 4.46875 | 4 | [] | no_license | # LISTAS
# Una lista es una coleccion de elementos, las listas estan ordenadas, y son mutables.
numeros = [5, 2, 23, 55, 1, 9, 6]
frutas = ["Manzanas", "Peras", "Uvas", "Naranjas", "Mandarinas", "Bananas", "Kiwi"]
print("LISTA ORIGINAL DE FRUTAS:")
print(frutas)
print()
# print(frutas[-1])
# print(frutas[-3])
# print(... | true |
d6cdb9b5554288077e4fa1a58d6e8b7578966da7 | Python | robintema/django-likeable | /likeable/models.py | UTF-8 | 2,766 | 2.8125 | 3 | [
"Apache-2.0"
] | permissive | #
# django-likeable
#
# See LICENSE for licensing details.
#
from django.db import models
from django.conf import settings
from django.contrib.contenttypes.models import ContentType
from django.contrib.contenttypes import generic
from django.utils.translation import ugettext as _
class Like(models.Model):
"""
... | true |
a68baa0e0cfc18f29974563c6b276f1bf7dd753d | Python | ashwinpn/Computer-Vision | /mesh/src/nerf/tree.py | UTF-8 | 13,843 | 2.875 | 3 | [
"MIT"
] | permissive | import torch
class Node:
def __init__(self, config, bounds, depth):
self.config = config
self.bounds = bounds
self.depth = depth
self.max_depth = self.config.tree.max_depth
if self.depth == 0:
self.count = self.config.tree.subdivision_outer_count
else:
... | true |
7d437cf3d540feba8b44cf58fdabb34ac8380261 | Python | mateuscmartins-1/Space_Run | /tela_inicial.py | UTF-8 | 848 | 2.625 | 3 | [
"CC-BY-4.0"
] | permissive | import pygame
from config import FPS, QUIT, INTRODUCTION
from assets import MUSICA_ENTRADA, load_assets
def tela_inicial(janela):
assets = load_assets()
clock = pygame.time.Clock()
tela_de_inicio = pygame.image.load('imgs/Spacerun.png').convert()
tela_de_inicio_rect = tela_de_inicio.get_rect()
jogo... | true |
23cc903479cba9587bad7e7a3a7f5675cf0f0445 | Python | MarshallMoler/django_project | /meiduo_mall/meiduo_mall/apps/users/utils.py | UTF-8 | 799 | 2.828125 | 3 | [] | no_license | from django.contrib.auth.backends import ModelBackend
import re
from .models import User
def get_user_account(account):
'''判断account是否是手机号,并返回user'''
try:
if re.match('^1[3-9]\d{9}$',account):
# 根据手机号获得用户名
user = User.objects.get(mobile=account)
else:
# 根据用户... | true |
90d7f20d2b670bdaca28a5c84ffb93b671b412a2 | Python | kexinshine/leetcode | /287.寻找重复数.py | UTF-8 | 302 | 2.578125 | 3 | [] | no_license | #
# @lc app=leetcode.cn id=287 lang=python3
#
# [287] 寻找重复数
#
# @lc code=start
class Solution:
def findDuplicate(self, nums: List[int]) -> int:
n=len(nums)
d=[0]*n
for i in nums:
d[i]+=1
if d[i]>1:
return i
# @lc code=end
| true |
461af85e3a77e2f97bf2261adf8296012543c389 | Python | juliafealves/tst-lp1 | /unidade-3/ano-bissexto/ano_bissexto.py | UTF-8 | 300 | 3.59375 | 4 | [] | no_license | # coding: utf-8
# Aluno: Júlia Alves
# Matricula: 117211383
# Atividade: Ano Bissexto - Unidade 3
ano = int(raw_input())
mensagem = "não é bissexto"
# Verifica se o ano é bissexto.
if (ano % 400 == 0) or (ano % 4 == 0 and ano % 100 != 0):
mensagem = "é bissexto"
print "%i %s" % (ano, mensagem) | true |