blob_id large_string | language large_string | repo_name large_string | path large_string | src_encoding large_string | length_bytes int64 | score float64 | int_score int64 | detected_licenses large list | license_type large_string | text string | download_success bool |
|---|---|---|---|---|---|---|---|---|---|---|---|
ef374502289c5bfa390c868be416d362de0ab621 | Python | carlosdlfuente/PhraseDep | /python/encoder.py | UTF-8 | 7,264 | 2.90625 | 3 | [] | no_license | """
This file implements an Encoder for lexicalized parsing.
Its job is to map between lexicalized trees and
the parts representation as annotated spans.
"""
from collections import defaultdict
import pydecode
from pydecode.encoder import StructuredEncoder
from nltk import ImmutableTree as Tree
import numpy as np
from ... | true |
9a6653c0c1e5d45956ead7d54da5fd2a77c7f0fb | Python | sam-rossin/auction-simulator | /auction_simulator.py | UTF-8 | 7,011 | 2.625 | 3 | [] | no_license | #an auction simulator
#Sam Rossin
#fall 2015
import bidding_agent
import user_interface
import card
import random
import string
import os
import inspect
import importlib
import signal
from contextlib import contextmanager
#game constants
NUM_ROUNDS = 10
STARTING_BUDGET = 1000
CARDS_PER_AGENT = 10
#scoring constants
... | true |
c55feceeb38e72e75a06e98ac0a51f3092e411e6 | Python | nasgoncalves/opentracing-tutorial | /lesson02/exercise02/__main__.py | UTF-8 | 1,490 | 2.625 | 3 | [] | no_license | import logging
import sys
import time
from jaeger_client import Config
def init_tracer(service):
logging.getLogger('').handlers = []
logging.basicConfig(format='%(message)s', level=logging.DEBUG)
config = Config(
config={
'sampler': {
'type': 'const',
... | true |
3c81f11042d68b9af9da5235784b0068c7b7dd83 | Python | heni-l/DenseNet121 | /data_load.py | UTF-8 | 2,728 | 2.609375 | 3 | [] | no_license | import torch
from PIL import Image
import numpy as np
import pandas as pd
from torchvision import transforms
from torch.utils.data import Dataset
from sklearn.model_selection import train_test_split
torch.manual_seed(1)
transform_train = transforms.Compose([
transforms.RandomCrop(32, padding=4),
tra... | true |
5d99371d591ae83303ace38f35e875e779a17fa6 | Python | JAGANPS/ml-lab | /pgm2.py | UTF-8 | 903 | 2.96875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Mon Sep 9 10:01:24 2019
@author: ADMIN
"""
from sklearn.cluster import KMeans
#from sklearn import metrics
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
data=pd.read_csv("km1.csv")
df1=pd.DataFrame(data)
print(df1)
f1=df1['Distance_Featur... | true |
5daaeaf1144217886f8faca118a5ac38e3f1593d | Python | amitpanda93/MACBackup | /Data Science/Notebooks/pandas_e2.py | UTF-8 | 431 | 2.71875 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 21 14:41:22 2019
@author: amit.panda03
"""
import pandas as pd
import numpy as np
df = pd.DataFrame([[18,10,5,11,-2],
[2,-2,9,-11,3],
[-4,6,-19,2,1],
[3,-14,1,-2,8],
[... | true |
84d1922cfb697edfc5f3e2d770e9082d9c74f998 | Python | allen-studio/learn-python3-records | /ex38.py | UTF-8 | 1,194 | 4.125 | 4 | [] | no_license | ten_things = "Apple Oranges Crows Telephone Light Sugar"
print("Wait there are not 10 things in that list. Let's fix that.")
stuff = ten_things.split(' ') # 通过split把句子的空格拆成列表
print(stuff) #打印确认已经是列表了
more_stuff = ["Day", "Night", "Song", "Frisbee",
"corn", "Banana", "Girl", "Boy"]
while len(stuff)!= 10:... | true |
75f481715ea3e94879394c0818db06452b4d91df | Python | AllenMostafa/project-euler- | /p12_Highly_divisible_triangular_number.py | UTF-8 | 1,047 | 4.375 | 4 | [] | no_license | # Project Euler --> https://projecteuler.net/problem=12
# Problem 12 : Highly divisible triangular number
#STEP 1: We want to create a function that calculates the first 7 triangular
#STEP 2: Create a function that returns the factors of each traingular
#STEP 3: store the length of the factors and when reach to to 500 ... | true |
56a6d188fc7c2db25959d16922a44b300140b322 | Python | amadeus4dev/amadeus-python | /amadeus/client/response.py | UTF-8 | 1,253 | 3.03125 | 3 | [
"MIT"
] | permissive | from amadeus.mixins.parser import Parser
class Response(Parser, object):
'''
The response object returned for every API call.
:var http_response: the raw http response
:var request: the original Request object used to make this call
:vartype request: amadeus.Request
:var result: the parsed ... | true |
2c64aa987fb60710b4c1f47d0837853f3dc232fa | Python | khlidar/Concrete_Beam_Program | /Shapes.py | UTF-8 | 5,457 | 3.46875 | 3 | [] | no_license | '''
Description:
Definition of shapes class and sup classes
Information on authors:
Name: Contribution:
--------- ------------------
Jacob Original code
Kristinn Hlidar Gretarsson Original code
Version histo... | true |
7222cb1908a1b5ef98ee5c827ad19151f97546fa | Python | tmoertel/practice | /misc/weighted_stream_selection.py | UTF-8 | 3,744 | 4.15625 | 4 | [] | no_license | """Write a function to generate a weighted random sample from a stream."""
import random
def select_weighted_value(weighted_values):
"""Return a randomly selected value from a stream of weighted values.
Args:
weighted_values: an iterable stream of (w, x) pairs, where w is a
non-negative integer... | true |
e90b9efe51b16d6ffe64f9337dc516f808511d52 | Python | ana-balica/nosnore | /nosnore/core/signal.py | UTF-8 | 1,237 | 2.90625 | 3 | [] | no_license | import numpy as np
import pylab as pl
from scipy.io import wavfile
def getwavdata(filename):
return wavfile.read(filename)
def savewavdata(filename, rate, data):
wavfile.write(filename, rate, data)
class Signal(object):
def __init__(self, signal, time):
self._signal = signal
self._siz... | true |
db1f3e3e5a8e9a322e5513fac245fe40f08c86de | Python | green-fox-academy/FulmenMinis | /week-03/day-03/purple_steps.py | UTF-8 | 436 | 3.1875 | 3 | [] | no_license | from tkinter import *
root = Tk()
canvas = Canvas(root, width='300', height='300')
canvas.pack()
# reproduce this:
# [https://github.com/greenfox-academy/teaching-materials/blob/master/workshop/drawing/purple-steps/r3.png]
#19 db 11x11 px
def drawing_function(x, y):
canvas.create_rectangle(x, y, x+11, y+11, fill... | true |
1bdf6aa2cba5b399f340fa47b2591d70b4452ec3 | Python | Dnoniel-Ermolaev/python-deep-learning-test | /doge_class.py | UTF-8 | 4,960 | 2.578125 | 3 | [] | no_license | """
Classification sample
Command line to run:
python ie_classification_sample.py -i image.jpg \
-m squeezenet1.1.xml -w squeezenet1.1.bin -c imagenet_synset_words.txt
"""
import os
os.add_dll_directory("C:\\Program Files (x86)\\Intel\\openvino_2021.4.689\\deployment_tools\\ngraph\\lib")
os.add_dll_directory("C:\\... | true |
c5179166b150a9223fb60df750fbf27360af60ca | Python | 3enoit3/tools | /gen/gen.py | UTF-8 | 1,051 | 2.96875 | 3 | [] | no_license |
# Input
def split_lines(iInput):
return [l.rstrip("\n") for l in iInput.split("\n") if l]
def merge_lines(iInput, iLines = 1):
l = split_lines(iInput)
o = []
while l:
o.append( ' '.join(l[:iLines]) )
del l[:iLines]
return o
# Output
def as_input():
return lambda s, c: s
def s... | true |
69a0eee3e8f4444352d47cb1aba84b828e0eb622 | Python | AdamZhouSE/pythonHomework | /Code/CodeRecords/2916/58575/304882.py | UTF-8 | 1,317 | 2.625 | 3 | [] | no_license | n=int(input())
nums=list(map(int,input().split(" ")))
deleteNumber=0
i=len(nums)-1
while i>=5:
if nums[i]==42:
judge=False
j=i-1
while j>=4 and judge==False:
if nums[j]==23:
k=j-1
while k>=3 and judge==False:
if nums[k]==16:
... | true |
5c418bbcc2250748f3191141b20399318b86e8a9 | Python | jkuzm/2020repo | /pythonViaPycharm1/testDecorator.py | UTF-8 | 1,918 | 4.0625 | 4 | [] | no_license | def fib_gen(limit):
i,a,b =0,0,1
while(i < limit):
yield a
a,b = b,a+b
i += 1
for i in fib_gen(10):
print(i, end= " ")
print()
#simplest decorator sample from https://medium.com/@dmi3coder/pythons-decorators-vs-java-s-annotations-same-thing-2b1ef12e4dc5
def as_html(func):
def ... | true |
2f3ce1a3c8eb8c836d969001bd89eb41e1e882e8 | Python | geverartsdev/TechnofuturTIC | /Flo et toto/Pong/components/score.py | UTF-8 | 1,019 | 2.921875 | 3 | [
"MIT"
] | permissive | import pygame
from pygame.locals import Color
from Pong.constants import ECRAN
class Score(pygame.sprite.Sprite):
color = Color('green')
def __init__(self, left):
pygame.sprite.Sprite.__init__(self, self.containers)
self.font = pygame.font.Font(None, 30)
self.font.set_italic(1)
... | true |
d65157b5d744d19af3752806b7f1049f1deadab8 | Python | ahndroo/Udemy | /SupervisedML/util.py | UTF-8 | 1,335 | 3.171875 | 3 | [] | no_license | import numpy as np
import pandas as pd
def get_train_data(limit = None):
print('Reading in and transforming data...')
df = pd.read_csv('MNISTtrain.csv')
data = df.as_matrix()
np.random.shuffle(data)
X = data[:,1:] / 255.0 # normalize data
Y = data[:,0]
if limit is not None:
X, Y = X... | true |
035d72045751f6f3bb66094db564b5b45431446f | Python | hehaiyang111/MLAlgorithm | /apriori/analysisByapriori.py | UTF-8 | 564 | 2.59375 | 3 | [] | no_license | import pandas as pd
from apriori import *
# inputFile
inputFile = './menu_orders.xls'
outputFile = './apriori_rules.xls' # 结果
# 读取数据
data = pd.read_excel(inputFile,header=None)
# 把不为空的数据设置为1
ct = lambda x : pd.Series(1, index=x[pd.notnull(x)])
b = map(ct,data.as_matrix())
# 实现矩阵转换 空值用0补充
data = pd.DataFrame(list(b))... | true |
33d5c074d7b9d862bf0b524dde91030d8efc4697 | Python | rajlath/rkl_codes | /CodeForces/distance.py | UTF-8 | 325 | 3.515625 | 4 | [] | no_license | a = 10
b = 20
weakness = 0
if abs(a - b) == 1: print(1)
elif abs(a - b) == 2: print(2)
elif a == b:print(0)
else:
weakness = 0
while True:
a+=1
b-=1
weakness += 2
if a == b:
break
if abs(a - b) == 1:
weakness += 2
break
print(weakne... | true |
c82d9af22d63201f54608c413d335cc0b2997f90 | Python | ogosborne/fasta_alignment_filters | /cat_alns.py | UTF-8 | 2,499 | 3.15625 | 3 | [] | no_license | #!/usr/bin/python2
from Bio import AlignIO
import glob
from Bio.Align import MultipleSeqAlignment
from Bio.SeqRecord import SeqRecord
import argparse
import sys
parser = argparse.ArgumentParser(usage = 'python2 cat_alns.py -o STR -t STR [-i STR -h]\n\nPython 2 only\n\nRequires: Bio, glob, argparse\n\nThis program c... | true |
242a06cc55e47a16a02d345207eb79d4883539c5 | Python | andrejcermak/twitter_downloader | /dat.py | UTF-8 | 6,750 | 2.625 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import MySQLdb
import json
import oauth2 as oauth
import time
import re
import pandas as pd
from collections import defaultdict
'''
Script that downloads tweets.
user_timeline() downloads 200 tweets for given user
my_timeline() downloads 200 tweets from clients timeline
... | true |
85dfa01c7d7e90744f2d3807de29f1e91c5317eb | Python | searchlink/kr_data | /A股指数回测分析系统/H股_处理.py | UTF-8 | 8,576 | 2.53125 | 3 | [] | no_license | import time,datetime
import talib
# import numpy as np
import pandas as pd
from KRData import CNData ,HKData
# np.seterr(divide='ignore', invalid='ignore')
#
# pd_display_rows = 10
# pd_display_cols = 100
# pd_display_width = 1000
# pd.set_option('display.max_rows', 10000)
# pd.set_option('display.max_columns', 100)
#... | true |
c7c49f527ad1093e5b1010060e97f6c9de63fe47 | Python | cchaisson/Python-Challenge | /PyPoll/PyPoll_Hmwk.py | UTF-8 | 1,338 | 3.4375 | 3 | [] | no_license | #Import the os module
import os
#Module for reading CSV files
import csv
csvpath = os.path.join('..','election_data.csv')
#Lists to store data
candidate=[]
total=0
khan=0
correy=0
li=0
otooley=0
with open(csvpath,newline="") as csvfile:
csvreader = csv.reader(csvfile, delimiter=",")
csvheader = next(csvfile)
#... | true |
83917516318f1633f3cba4f3bbad639b77bc6d02 | Python | gabalese/tweet-a-book | /test/test_pyepub.py | UTF-8 | 3,633 | 2.6875 | 3 | [
"MIT"
] | permissive | import unittest
import urllib2
from tempfile import NamedTemporaryFile
from StringIO import StringIO
from src.epub import EPUB
class EpubNewTests(unittest.TestCase):
def setUp(self):
remotefile = urllib2.urlopen('http://dev.alese.it/book/urn:uuid:c72fb312-f83e-11e2-82c4-001cc0a62c0b/download')
tes... | true |
4239e00230c17a3d01c0adfc4057eac587c97da7 | Python | muftring/iu-python | /module-07/Question2.py | UTF-8 | 1,509 | 4.40625 | 4 | [] | no_license | #!/usr/bin/env python3
#
# Michael Uftring, Indiana University
# I590 - Python, Summer 2017
#
# Assignment 7, Question 2
#
# A program which promts the user for a list of numbers, then determines if
# the list is ordered (ascending or descending) and displays the result.
#
import math
#
""" isAscend(nums): check whet... | true |
8ef5202999de5858fe7a60427571f2d6eb1e8038 | Python | kamojiro/atcoderall | /grand/025/A.py | UTF-8 | 199 | 2.921875 | 3 | [] | no_license | def kakuwa(S):
A = list(str(S))
B = [int(x) for x in A]
return sum(B)
N = int(input())
ans = 50
for i in range(1,N):
ans = min(ans, kakuwa(i) + kakuwa(N-i))
print(ans)
| true |
8b80875e5f19bf27de6058bae5a936d35935918d | Python | Joselyn19/GUI-Software-Development | /main.py | UTF-8 | 18,885 | 2.671875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from tkinter.messagebox import *
import tkinter.filedialog
from tkinter import*
import os
import socket
import webbrowser
from ftplib import FTP
import XPS_Q8_drivers
import sc10
import sys
import time
class IPSetupPage(object):# IP地址修改页面
def __ini... | true |
bc09d897c4a3111e76d9f69ff5a88cfea126b670 | Python | sidazhong/leetcode | /leetcode/easy/155_minStack.py | UTF-8 | 2,070 | 4.09375 | 4 | [] | no_license | '''
# tuple push比较上一个与当前，存最小
class MinStack(object):
def __init__(self):
self.stack=[]
def push(self, val):
if(not self.stack):
item=(val,val)
else:
item=(val,min(val,self.stack[-1][1]))
self.stack.append(item)
def pop(self):
return self.st... | true |
25ed58147387a6215a5fbf22085ecf41888a36c3 | Python | rv-kesnyder/ita-challenges-2020 | /python-week-1/07-for-loops.py | UTF-8 | 168 | 2.71875 | 3 | [] | no_license | def even_nums(numbers, even_numbers):
# numbers is the list of all numbers
# even_numbers is the empty list, that holds only the even numbers.
# Your code in here. | true |
f24e496bf3636dfa141543035c2963402d87b0f0 | Python | Cjkendel/Lower-Bound-Estimation | /main.py | UTF-8 | 601 | 2.59375 | 3 | [] | no_license | from LocalVariationalBoundsVectorized import EstimateLowerBound
from LogisticRegression import LogisticReg
if __name__ == "__main__":
#JJ Bound Estimation
lower = EstimateLowerBound(batch_size=1, full_batch=False, n_batch=False)
# lower.call_and_write_results(10000)
# Torch Logistic Regression, get p... | true |
4acf52e6238fc0108481b32f6ac9b8b6d9c84206 | Python | zgmartin/minset-cover | /min_inventory_checks.py | UTF-8 | 627 | 3.234375 | 3 | [] | no_license | from objects import Data
from algorithms import greedy
import sys
def min_inventory_check(file_name):
"""Returns a list of the minimum number of inventory checks for an input file."""
#generates usable data from JSON file
input_data = Data()
input_data.extract_data(file_name)
#runs greedy algori... | true |
82601c806636d0bce3741ddffcc1094b0579dfe2 | Python | kalloc/insanities-testing | /tests/utils/odict.py | UTF-8 | 616 | 3.109375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import unittest
from insanities.utils.odict import OrderedDict
class OrderedDictTests(unittest.TestCase):
def test_pop_with_default(self):
d = OrderedDict([('a', 'a'), ('b', 'b')])
self.assertEqual(d.pop('a', ('c', 'c')), ('a', 'a'))
self.assertEqual(len(d.items()... | true |
3a9d17d0d764972501c6303a86f648ddae245496 | Python | littlemesie/recommend-learning | /src/dssm/data_process.py | UTF-8 | 2,819 | 2.859375 | 3 | [] | no_license | import json
UNK = '[UNK]'
PAD = '[PAD]'
MAX_SEQ_LEN = 10
class Processor:
"""数据处理"""
def __init__(self, vocab_path):
self.vocab_path = vocab_path
self.vocab_map = self.load_vocab()
self.nwords = len(self.vocab_map)
def load_vocab(self):
"""加载vocab数据"""
word_dict... | true |
bc48b3c5035e9b2273aefbbf5457139e43b70128 | Python | chrisjluc/algorithms | /graphs/tests/test_topsort.py | UTF-8 | 867 | 3.203125 | 3 | [] | no_license | from graphs.topological_sort import *
from graphs import util
from graphs.graph import Graph
import unittest
graph1 = Graph()
for v in [0, 1, 2, 3, 4, 5]:
graph1.add_node(v)
graph1.add_edge(5, 2)
graph1.add_edge(5, 0)
graph1.add_edge(4, 0)
graph1.add_edge(4, 1)
graph1.add_edge(2, 3)
graph1.add_edge(3, 1)
graph2 =... | true |
881bbf4985be61764786f67b1cd7490d724e8305 | Python | ananxuan/web_crawler | /百度贴吧_spider.py | UTF-8 | 2,562 | 2.6875 | 3 | [] | no_license | # -*- coding:utf-8 -*-
import urllib
import urllib2
import re
#百度贴吧爬虫类
class BDTB:
#初始化，传入基地址，是否只看楼主参数
#URLADDR:http://tieba.baidu.com/p/3138733512?see_lz=1&pn=1
def __init__(self,baseURL, seeLZ):
self.baseURL=baseURL
self.seeLZ= '?see_lz=' +str(seeLZ)
#传入页码，获取该页帖子的代码
def getpage(self,pageNum... | true |
33a695384b9ae8f9db030ba9f993681856d81d0b | Python | bruzecruise/Intro_Biocom_ND_319_Tutorial10 | /exercise_10_B.py | UTF-8 | 4,031 | 2.703125 | 3 | [] | no_license | #Load packages
import pandas
import scipy
import scipy.integrate as si
from plotnine import *
# function
def SIR (y,t0,beta,gamma):
S = y[0]
I = y[1]
R = y[2]
dS = -1*(beta*I*S)
dI = (beta*I*S)-(gamma*I)
dR = (gamma*I)
return dS, dI, dR
# initial conditions
times = range(0,500)
NO = [999, ... | true |
3399ccffb3fa8f15d63fe0b50b6398472d9112e5 | Python | ywzyl/algorithm013 | /Week_01/twoSum.py | UTF-8 | 990 | 3.78125 | 4 | [] | no_license | class Solution:
def twoSum(self, nums, target):
# 思路：嵌套遍历，内层遍历只遍历外层index之后的列表，排除重复，时间复杂度为O(n*2)
for i in range(len(nums)):
for j in range(i+1, len(nums)):
if nums[i] + nums[j] == target:
return [i, j]
return []
def twoSumT(self, nums, tar... | true |
aa24e792ae5d84148feb9fba91257416d5aedd39 | Python | shen-huang/selfteaching-python-camp | /19100402/Autumn0808/1001S01E05_array.py | UTF-8 | 642 | 4.125 | 4 | [] | no_license | mylist = [0,1,2,3,4,5,6,7,8,9]
print(mylist)
#将mylist数组反转
list1 = mylist[::-1]
print(list1)
#反转后的数组拼接成字符串
##用map()将list1中的元素一一映射为str并拼接成新的字符串
str1 = "".join(map(str,list1))
print(str1)
#用字符串切片的方式取出第三到八个字符，包含三和八
str2 = str1[2:7]
print(str2)
#将获得的字符串进行反转
str3 = str2[::-1]
print(str3)
#将结果转换为int类型
str4 = int(str3)
print(s... | true |
1663fb886939d93213ea426d65f00d9740476bc9 | Python | sungguenja/studying | /sort/퀵정렬.py | UTF-8 | 710 | 3.59375 | 4 | [] | no_license | def quick_sort(a,low,high):
if low < high:
pivot = partition(a,low,high)
quick_sort(a,low,pivot-1)
quick_sort(a,pivot+1,high)
def partition(a,pivot,high):
print("start partition",a,pivot,high)
i = pivot + 1
j = high
while True:
while i<high and a[i] < a[pivot]:
... | true |
26a6060ac8f32b1277ac8bf5cf2b3ba31d6ff938 | Python | Atsuhiko/Web-App | /facial-expression/second Iisan/app/app.py | UTF-8 | 4,245 | 2.53125 | 3 | [] | no_license | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
import os
import random
from flask import Flask, make_response,render_template, request, redirect, url_for, send_from_directory, g, flash, jsonify
from keras.preprocessing.image import load_img
import numpy as np
import cv2
import matplotlib.pyplot as plt
from tensorflow.... | true |
c85796971dddb19c55f4a959bf8a4ea62d15067a | Python | yearfunla/ML5155 | /sampling.py | UTF-8 | 6,091 | 2.703125 | 3 | [] | no_license | """
Course: CSI5155
Tiffany Nien Fang Cheng
Group 33
Student ID: 300146741
"""
import json
import numpy as np
import pandas as pd
from scipy.io import arff as af
import arff
from sklearn.impute import SimpleImputer
from imblearn.over_sampling import SMOTE, ADASYN
from sklearn import svm, preprocessing
from sklearn.mode... | true |
967b60ef865868e98c9e1257b114f023bba8fea5 | Python | ZhengJiaCode/Selection_strength_evolvability | /2020sel_Scripts/8_frequencyOfU.py | UTF-8 | 2,519 | 2.625 | 3 | [] | no_license | #This program is used for calculating the frequency of sequences carrying both G66S and Y204 during phase II evolution
import os
import csv
import sys
import re
GList=['II-1','II-2','II-3','II-4']
GSea=['phase-II_1st','phase-II_2nd','phase-II_3rd','phase-II_4th']
#the following codes are used for grouping sequences f... | true |
0375f0a058ff4d9ab7ce7ff2653f1e5e13d0548f | Python | MIKOLAJW197/cityParking | /prog.py | UTF-8 | 3,276 | 2.8125 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import thread
import time
import Adafruit_BBIO.GPIO as GPIO
import Adafruit_BBIO.PWM as PWM
from flask import Flask, jsonify
from flask import request
from flask_cors import CORS, cross_origin
# Configuration czujnika odleglosci
GPIO.setup("P9_12", GPIO.OUT, initial=GPIO... | true |
e2c38b8d182f49f96e020ceb3d3f7a00c3a84d24 | Python | 1cg2cg3cg/BOJ | /1065_한수.py | UTF-8 | 418 | 3.234375 | 3 | [] | no_license | import sys
N = int(sys.stdin.readline().strip())
number = 0
if N < 100 :
number = N
print(N)
else :
number = 99
for i in range(100, N+1) :
A = str(i)
Dif = []
for j in range(1, len(A)) :
Dif.append(int(A[j]) - int(A[j-1]))
Di... | true |
96418dc8f0152c90c5bb19c04f27eff92d251e83 | Python | Isen-kun/Python-Programming | /Sem_3_Lab/05.01.21/asign.py | UTF-8 | 893 | 4.59375 | 5 | [] | no_license | def rect_area():
l = int(input("Enter rectangle's length: "))
b = int(input("Enter rectangle's breadth: "))
ar = l * b
print("The area of rectangle is", ar)
def tri_area():
h = int(input("Enter triangle's height length: "))
b = int(input("Enter triangle's breadth length: "))
ar = 0.5 * b *... | true |
72bd593fc69430dbae7ec98dbfc64e5cacc253bc | Python | sindish/unitedwelearn | /object_detection/detectron2/datasets/prepare_bdd100k.py | UTF-8 | 3,208 | 2.6875 | 3 | [
"Apache-2.0"
] | permissive | import cv2
import json
from pathlib import Path
def convert_bdd_coco_format(split) -> None:
data_folder = Path("/media/deepstorage01/datasets_external/BDD100K")
json_file = data_folder / "bdd100k_labels_release" / f"bdd100k_labels_images_{split}.json"
image_root = Path("/media/deepstorage01/datasets_exte... | true |
58b367f5a0259a9ac38fde53d66fe137503aa409 | Python | HardikSingh97/hebi-python-examples | /kits/arm/ex_teach_repeat_armApi_w_gripper.py | UTF-8 | 4,370 | 2.75 | 3 | [] | no_license | #!/usr/bin/env python3
import arm
import hebi
from hebi.util import create_mobile_io
from time import sleep
# Set up arm
family_name = "Arm"
module_names = ["J1_base", "J2_shoulder", "J3_elbow", "J4_wrist1", "J5_wrist2", "J6_wrist3"]
hrdf = "hrdf/A-2085-06G.hrdf"
gripper_name = "gripperSpool"
p = arm.ArmParams(fami... | true |
0f6dc96354cfa59ccadadf8b57986175224132b2 | Python | Menci/TuringAdvancedProgramming19A | /Task 2/evaluator-checker/expression.py | UTF-8 | 1,623 | 3.25 | 3 | [] | no_license | from math import copysign
from utils import float_to_string
class Expression:
def __init__(self, type, rng, value=None, operator=None, left_operand=None, right_operand=None):
self.type = type
self.value = value
self.operator = operator
self.left_operand = left_operand
self.... | true |
f8dd9b0b915846d859f03adea7c4b10b6856b361 | Python | vikpe/pydynamiccalc | /custom/calculators.py | UTF-8 | 368 | 2.953125 | 3 | [] | no_license | from pykm.calculators import AbstractPriceCalculator
class DiscountForGoblinsCalculator(AbstractPriceCalculator):
GOBLIN_FACTOR: float = 0.8
@classmethod
def calculate_price(cls, card_info: dict) -> float:
price = card_info["price"]
if "goblin" in card_info["name"].lower():
p... | true |
471df3e26d733174abf4948c3a990e62fe86ac66 | Python | ECE-492-W2020-Group-6/smart-blinds-rpi | /scripts/check_motor_interactive.py | UTF-8 | 1,712 | 3 | 3 | [
"MIT"
] | permissive | """
Date: Feb 26, 2020
Author: Ishaat Chowdhury
Contents: Motor test script
"""
from easydriver.easydriver import EasyDriver, PowerState, MicroStepResolution, StepDirection
from gpiozero.pins.rpigpio import RPiGPIOFactory
from gpiozero import Device
import time
import RPi.GPIO as rpigpio
if __name__ == "__main__":
... | true |
de79984049b64957e0f971ba0b116b5573913eac | Python | Hyunwoo29/keras01 | /ml/m21_pickle.py | UTF-8 | 1,529 | 2.640625 | 3 | [] | no_license | from os import scandir
from xgboost import XGBRegressor
from sklearn.datasets import load_boston
from sklearn.model_selection import train_test_split
import numpy as np
from sklearn.metrics import r2_score
from sklearn.preprocessing import MinMaxScaler, StandardScaler
#1.데이터
datasets = load_boston()
x = datasets["data... | true |
39d76b252e7c8486f008f9c9ffbe420803aa73dd | Python | fanyuguang/lstm-text-classification | /tfrecords_utils.py | UTF-8 | 4,770 | 2.5625 | 3 | [] | no_license | #!/usr/bin/env Python
# -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
import os
import tensorflow as tf
import data_utils
FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_string('tfrecords_path', 'data/tfrecords/', 'tfrecords directory')
tf.app.flags.DEFINE_integer('batch... | true |
6d89d0e082692b421ad1e8c244ab8d8c3326798f | Python | kjans123/CPS_testing | /maxDifference02.py | UTF-8 | 271 | 2.953125 | 3 | [] | no_license | def maxFindDiff(inputList):
diffList = []
for i in range(len(inputList)):
if i != (len(inputList)-1):
oneDiff = abs(inputList[i] - inputList[i+1])
diffList.append(oneDiff)
maxxVal = round(max(diffList), 5)
return maxxVal
| true |
444e53533bed6a74c96970699edd277373b72272 | Python | croptek/sensors | /test/RHT03-tmp&hum/RHT03-tmp&hum.py | UTF-8 | 1,348 | 2.828125 | 3 | [] | no_license | #!/usr/bin/env python
import sys
#import redis
import Adafruit_DHT
import time
confDoc = open('config.txt','r')
sysName = confDoc.readline().rstrip()
tmpSensorName = confDoc.readline().rstrip()
humSensorName = confDoc.readline().rstrip()
pin = int(confDoc.readline())
updateRate = int(confDoc.readline())
redisName = ... | true |
ef8e69ab6081c4db76f0af1a89b42c6f76b01673 | Python | SamProkopchuk/maps20 | /D.py | UTF-8 | 301 | 3.171875 | 3 | [] | no_license | import math as m
for i in range(int(input())):
n, l, d, g = list(map(int, input().split()))
# n = sides
# l = side length
# d = expansion distance
# g = land grabs
apothem = l/2*m.tan(m.pi*(n-2)/(2*n))
area = 0.5*n * l *apothem
ds = g*d
area += (ds)**2*m.pi
area += n * l * ds
print(area)
| true |
2174fc702399b702d9324ce564fc2d461bf1e208 | Python | rushkock/project | /project/data/scripts/convertCSV2JSONus.py | UTF-8 | 1,042 | 3.140625 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python
# Name: Ruchella Kock
# Student number: 12460796
"""
This script transforms the us csv datafiles to a JSON file
"""
import pandas as pd
def main():
columns = ["FIPS", "State", "Substate Region", "Small Area Estimate",
"95% CI (Lower)", "95% CI (Upper)"]
# choose column nam... | true |
4072f3124a82c0a1d17fe3c9fbeeedd0babd7eef | Python | Manon-des-sources/C003-python | /NoteBook/3001-lesson_codes/23-002-dice.py | UTF-8 | 942 | 3.859375 | 4 | [] | no_license | # coding=utf-8
#!python3
# =======================================================================
"""
来源：
问题：
接口：
说明：
"""
# =======================================================================
# modules section
import random
# 用一个11面的骰子、代替两个6面的骰子，投出2-12 之间的数值
totals = [0,0,0,0, 0,0,0,0, 0,0,0,0, 0]
for i in rang... | true |
cc083918fe768c6d0a4193a3db884590eadfc7ef | Python | drestion/leetcode | /python/ContainsDuplicate.py | UTF-8 | 670 | 3.421875 | 3 | [] | no_license | class Solution:
# def containsDuplicate(self, nums: List[int]) -> bool:
# # brutal force is O(n2) as it needs to check at least two elements
# # to speed up, needs memory, with hash
# num_dict = {}
# for n in nums:
# if n in num_dict.keys():
# ret... | true |
5fab2aa8384c6585fe746d079a7524cf449530a1 | Python | daniellealll/rootcow | /admin/services/instituicao_service.py | UTF-8 | 1,350 | 2.578125 | 3 | [] | no_license | from admin.models.instituicao import Instituicao
from admin.dao import instituicao_dao
def listar():
instituicoes = []
instituicoes_bd = instituicao_dao.listar()
for instituicao_bd in instituicoes_bd:
instituicoes.append(Instituicao(instituicao_bd['nome'], instituicao_bd['telefone'], instituicao_b... | true |
a3008a097955b83e56ca6b7ace08373da99fdb68 | Python | Pavlenkovv/e-commerce | /HW5/Task_2/fraction.py | UTF-8 | 1,986 | 3.765625 | 4 | [] | no_license | """Создайте класс «Правильная дробь» и реализуйте методы сравнения,
сложения, вычитания и произведения для экземпляров этого класса."""
from math import gcd
class Fraction:
def __init__(self, a, b):
if not isinstance(a, int):
raise TypeError('a')
if not isinstance(b, int):
... | true |
15d06a5a751c33bb07ac2c767d280f2fd973bfce | Python | evershinemj/python | /songlist.py | UTF-8 | 592 | 3.703125 | 4 | [] | no_license | #!/usr/bin/env python3
# encoding=utf-8
# from collections import Iterable
# this form of import doesn't raise warning
from collections.abc import Iterable
class Songlist(Iterable):
'''
the advantage of inheriting collections.Iterable
is that is you do not implement __init__, an
exception will be ra... | true |
6ca7352f65a3849abdfb9bcdffb44b1f794629c0 | Python | RawitSHIE/Algorithms-Training-Python | /python/Time Machine r.py | UTF-8 | 283 | 3.25 | 3 | [] | no_license | """calendar"""
def main():
"""step"""
month = str(input())
step = int(input())%12
almonth = "JANFEBMARAPRMAYJUNJULAUGSEPOCTNOVDECJANFEBMARAPRMAYJUNJULAUGSEPOCTNOVDEC"
loca = almonth.find(month)
pos = (loca+2)+((step*3)-2)
print(almonth[pos:pos+3])
main()
| true |
20eda7d2c70ff03c184743d576da4260f9aea285 | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_206/1219.py | UTF-8 | 912 | 2.96875 | 3 | [] | no_license |
import argparse
def solve():
pass
def main(f_in, f_out):
t = int(f_in.readline().strip())
for case in range(1, t+1):
d, n = f_in.readline().strip().split()
d = int(d)
n = int(n)
horses = []
for r in range(n):
k, s = f_in.readline().strip().split()
horses.append([int(k), int(s)])
... | true |
47a3f84c74dfaa6c87e829e14b1fc0cd6a677f6a | Python | ess2/AlgoritmosBioinspirados | /Bioinspirada/MiniProjeto1/bin/8QueensAlgorithm.py | UTF-8 | 5,195 | 3.34375 | 3 | [] | no_license | import numpy
import random
import time
max_fitness = 28
qt_exec = 20
qt_population = 200
def main():
for f in range(qt_exec):
inicio = time.time()
population = list()
qtFitness = 0
#Gera a população
for i in range(qt_population):
a = random.sample(range(1,9), 8... | true |
b448ace50aa4bda118e828de85f77c0b45ec2d52 | Python | DveloperY0115/texture_fields | /mesh2tex/layers.py | UTF-8 | 6,396 | 2.65625 | 3 | [
"MIT"
] | permissive | import torch.nn as nn
import numpy as np
import torch.nn.functional as F
class ResnetBlockFC(nn.Module):
def __init__(self, size_in, size_out=None, size_h=None):
super().__init__()
# Attributes
if size_out is None:
size_out = size_in
if size_h is None:
size... | true |
dd6b08775ffd8e91771148e3d8732a04cf6b10a5 | Python | kmader/qbi-2019-py | /Exercises/06-AdvShape.py | UTF-8 | 4,955 | 3.234375 | 3 | [
"Apache-2.0"
] | permissive | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import numpy as np
import skimage.transform
import scipy
from scipy import ndimage
import matplotlib.pyplot as plt
from skimage.morphology import medial_axis, watershed
create_dist_map = lambda img, mask=None: medial_axis(img, mask, return_distance=True)[1]
import os
f... | true |
b7651d001bb3086119389b656717604e1145ef66 | Python | daydreamerli/python_study | /Dp_coinchange_error.py | UTF-8 | 1,984 | 3.53125 | 4 | [] | no_license | import timeit
# Function to create the matrix we'll use for the optimization
def _change_matrix(coin_set, change_amount):
matrix = [[0 for m in range(change_amount + 1)] for m in range(len(coin_set) + 1)]
for i in range(change_amount + 1):
matrix[0][i] = i
return matrix
# Function we'll use to opt... | true |
5cd4fa29bef4f15a41945a739f1efe0134264549 | Python | kq-li/stuy | /pclassic/2016s/PClassic2016Stubs/stubs/JediAcademy.py | UTF-8 | 409 | 2.875 | 3 | [] | no_license | # Change the body of this method
def best_grouping(scores, G):
return 0
if __name__ == "__main__":
with open("JediAcademyIN.txt", "r") as f:
while True:
s = f.readline()
if s == "":
break
data = s.split("--")
scores = [int(x) for x in data... | true |
57559136d818776996ca53830a22f476507126d6 | Python | maratserik/NN-clothes-classification | /learning.py | UTF-8 | 1,512 | 3.140625 | 3 | [] | no_license | import tensorflow as tf
from tensorflow import keras
import numpy as np
import matplotlib.pyplot as plt
fashion_mnist = keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
class_names = np.array(['T-shirt/top', 'Trouser', 'Pullover', 'Dress',
... | true |
df5f8fbe064ca1e2aa4ce17a18e0e79361c39a12 | Python | ultrabug/py3status | /py3status/output.py | UTF-8 | 6,764 | 3.265625 | 3 | [] | permissive | import sys
from json import dumps
class OutputFormat:
"""
A base class for formatting the output of py3status for various
different consumers
"""
@classmethod
def instance_for(cls, output_format):
"""
A factory for OutputFormat objects
"""
supported_output_form... | true |
98c0fde4c69912b7882e5cacb02a8c2cd95d4795 | Python | fyeee/reproducing-machine-learning-algorithms | /DecisionTree/DecisionTree.py | UTF-8 | 3,830 | 3.1875 | 3 | [] | no_license | import math
# for testing the algo
from sklearn import datasets
from sklearn.model_selection import train_test_split
class DecisionTreeClassifier:
def __init__(self, max_depth=None):
self.max_depth = max_depth
self.root = None
def fit(self, X, y, node={}, depth=0):
if node is None:
... | true |
3036fd76a93061a8cbcadf7a6afa2f5d450725ea | Python | anshsaikia/GSSDeliverables-YesProject | /VE-Tests/tests_framework/ui_building_blocks/KSTB/fullcontent.py | UTF-8 | 22,773 | 2.546875 | 3 | [] | no_license |
from tests_framework.ui_building_blocks.screen import Screen
import logging
import tests_framework.ui_building_blocks.KSTB.constants as CONSTANTS
from math import ceil
from time import sleep
class Fullcontent(Screen):
def __init__(self, test):
Screen.__init__(self, test, "full_content")
def navigate... | true |
aeb8cf183547020684e968d00a677f5cda3d1c8a | Python | PeterZhouSZ/feasible-form-parameter-design | /relational_lsplines/test_idea.py | UTF-8 | 4,057 | 2.796875 | 3 | [] | no_license | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Fri Mar 3 13:41:20 2017
@author: luke
Testing examples from
Interval Constraint Logic Programming
by Frederic Benhamou
"""
#import numpy as np
from extended_interval_arithmetic import ia
#from hull_inference_ob_graph import Hull as... | true |
183278c0f49c3a3bf5446875008eb1e4359343dc | Python | ZoneTsuyoshi/Data_Assimilation | /phase2/source/kalman.py | UTF-8 | 39,204 | 2.609375 | 3 | [] | no_license | '''
Kalman Filter のクラス
pykalman を参考にして作成する
pykalman では欠測値に対応できていないので，欠測にも対応できるクラス作成がメインテーマ
-> と思っていたけど，マスク処理で対応している
-> 欠測値(NaN)の場合は自動でマスク処理するようなコードを追加すれば拡張の意義がある
18.03.13
行列の特定の要素を最適化できる EM Algorithm に改変
18.03.17
メモリ効率化を行う
- 不要なメモリを保存しないようにする
- pykalman もカルマンゲイン等でメモリが喰われているため，それらも節約する
- デフォルトで np.float32 を使用してメモリ節約
... | true |
902c2a8fbb0fc2cd2eb8d4353e6e37aa2d7f7255 | Python | koking0/Algorithm | /Interview/JD/JD2-抛小球/solve.py | UTF-8 | 166 | 3.203125 | 3 | [] | no_license | class Balls:
def calcDistance(self, A, B, C, D):
return 3 * (A + B + C + D)
if __name__ == '__main__':
print(Balls().calcDistance(100, 90, 80, 70))
| true |
f09f97284b978dc953a9299e42b9e6466ada3a26 | Python | takecap/70puzzles | /src/q07.py | UTF-8 | 738 | 3.75 | 4 | [] | no_license | # Q07 日付の２進数変換
# 年月日をYYYYMMDDの８桁の整数で表したとき、これを２進数に変換して逆に並べ、
# さらに１０進数に戻したとき、元の日付と同じ日付になるものを探してください。
# 探索する期間は19641010 〰 20200724とします。
from datetime import date
from datetime import timedelta
# dt: datetime.date を２進数に変換して返す
def date2bin(dt):
date_str = dt.strftime('%Y%m%d')
return bin(int(date_str))[2:]
def main()... | true |
a709a5540df63fb94564aeb15a9877b634190e37 | Python | bongho/codewar | /Build_Tower.py | UTF-8 | 415 | 3.34375 | 3 | [] | no_license | def tower_builder(n_floors):
floors = []
n = n_floors
for i in range(n_floors):
print(i)
n -= 1
floors.append(' ' * n + '*' * (i * 2 + 1) + ' ' * n)
return floors
def tower_builder(n):
return [("*" * (i*2-1)).center(n*2-1) for i in range(1, n+1)]
def tower_buil... | true |
51071575356ec18dd7c1052239e290b2e2015306 | Python | joohyun333/programmers | /백준/투포인터/수고르기.py | UTF-8 | 396 | 3.015625 | 3 | [] | no_license | import sys
input = sys.stdin.readline
num = []
N, M = map(int, input().split())
for i in range(N):
num.append(int(input()))
num.sort()
start = end = 0
min_result = sys.maxsize
while end<N and start <= end:
distance = num[end] - num[start]
if distance >=M :
if min_result> distance:
min_r... | true |
cb67199473c1cbcbe8260232357653b949126b9f | Python | sijichun/MathStatsCode | /code_in_notes/MCMC_independent_mh.py | UTF-8 | 594 | 2.96875 | 3 | [] | no_license | ## mcmc_independent_mh.py
##独立的MCMC算法，输入：
## N_samples : 抽样次数
## pai(x) : 目标密度函数
## q(y) : 工具密度函数
## q_sampler : 给定x，从q中抽样的函数
## x0 : 初始值
from numpy import random as nprd
def MH_independent(N_samples, pai, q, q_sampler, x0):
X = []
x = x0
for i in range(N_samples):
... | true |
3d7f34be3b3e8b6c86a8af1977fef8333bc7e4ef | Python | ulbergc/EQlocator | /Processing/tools.py | UTF-8 | 2,759 | 2.859375 | 3 | [] | no_license | '''
Helper tools for process_data.py
Read and write datasets with Spark
Filename: tools.py
Cohort: Insight Data Engineering SEA '19C
Name: Carl Ulberg
'''
import pyspark.sql.types as T
from pyspark.sql import SQLContext
from pyspark.sql.functions import countDistinct
import os
def read_data(spark):
'''
Read... | true |
d95136a7973f954feae348ededae8a1f49a0c4e2 | Python | loganyu/leetcode | /problems/1347_minimum_number_of_steps_to_make_two_strings_anagram.py | UTF-8 | 1,118 | 3.8125 | 4 | [] | no_license | '''
You are given two strings of the same length s and t. In one step you can choose any character of t and replace it with another character.
Return the minimum number of steps to make t an anagram of s.
An Anagram of a string is a string that contains the same characters with a different (or the same) ordering.
... | true |
cf361a0a26de4d4cff39cfb45d53ab251a650cf3 | Python | Vyalkoff/Codewars | /vowel_counter.py | UTF-8 | 250 | 3.375 | 3 | [] | no_license | def get_count(input_str):
num_vowels = 0
list_vowels = ['a', 'e', 'i', 'o', 'u']
for i in input_str:
if i in list_vowels:
num_vowels += 1
return num_vowels
print(get_count('o a kak ushakov lil vo kashu kakao'))
| true |
46a485720df409b95c58a9a9924d1b8ea7e76ff1 | Python | 11Vladimir/algoritm | /lesson_3/task_9.py | UTF-8 | 647 | 3.90625 | 4 | [] | no_license | #!/usr/bin/python3.8
# 9. Найти максимальный элемент среди минимальных элементов столбцов матрицы.
from random import random
M = 10
N = 5
def matrix():
arr = []
for _ in range(N):
b = []
for _ in range(M):
n = int(random() * 200)
b.append(n)
arr.append(b)
... | true |
2f3c16f1e0f2e95d1f3f058dd4f98efd42a87035 | Python | Rakshit-Bhatt/Practice_Codes | /demo_codes/HACKERRANK/itertools_product.py | UTF-8 | 597 | 3.6875 | 4 | [] | no_license | from itertools import product
#timeit() module to test the time lapse
import timeit
def cart_product(list1, list2):
return (product(list1 , list2))
if __name__=="__main__":
a=[int(item) for item in input("Enter values for first list: ").split()]
b=[int(item) for item in input("Enter values fo... | true |
53b19f07da4bae654cfcc6d262566f8fe5c04cb1 | Python | DeadHeadRussell/iacd_projects | /interactive_map/csv_trim.py | UTF-8 | 479 | 3.0625 | 3 | [] | no_license | #!/usr/bin/python
import csv
input_name = 'usa_hotels.csv'
columns = ['id', 'latitude', 'longitude']
delimiter = '\t'
reader = csv.reader(file(input_name), delimiter=delimiter)
header = reader.next()
column_ids = []
id = 0
for row in header:
if row in columns:
column_ids.append(id)
id += 1
print delimiter... | true |
0f2664fb0852800fc5bb86f8963b419bcfdd3597 | Python | ChinaChenp/Knowledge | /interview/interview_python/mianshixinde/lesson2/2.2.py | UTF-8 | 779 | 4.40625 | 4 | [] | no_license | #寻找和为定值的两个数
#输入一个数组和一个数字，在数组中查找两个数，使得它们的和正好是输入的那个数字。
#要求时间复杂度是O(N)。如果有多对数字的和等于输入的数字，输出任意一对即可。
#例如输入数组1、2、4、7、11、15和数字15。由于4+11=15，因此输出4和11。
#默认升序
def two_number(arr, need):
beg, end = 0, len(arr) - 1
while beg < end:
#print(beg, end, arr[beg], arr[end])
total = arr[beg] + arr[end]
if to... | true |
2fb01107c035ce7e13d71ff8c89cbb1d1df594d1 | Python | jtbish/ppl-da | /ppl/rng.py | UTF-8 | 256 | 2.59375 | 3 | [] | no_license | import numpy as np
_rng = np.random.RandomState()
_has_been_seeded = False
def seed_rng(seed):
seed = int(seed)
_rng.seed(seed)
global _has_been_seeded
_has_been_seeded = True
def get_rng():
assert _has_been_seeded
return _rng
| true |
d52b78db0f093a05132c0044f7c7c41d7daf7a6a | Python | CateGitau/Python_programming | /ace_python_interview/sort_search/find_max_product.py | UTF-8 | 1,605 | 4.28125 | 4 | [] | no_license | '''
Implement a function find_max_prod(lst) that takes a list of numbers and returns a maximum product pair.
'''
# Decimal library to assign infinite numbers
from decimal import Decimal
#brute force approach
'''O(n^2)'''
def find_max_prod(lst):
"""
Finds the pair having maximum product in a given list
:pa... | true |
1aaea7829d891409223664cd2ffc97281ba0a80b | Python | whistle-boy/TIL-and-TIW | /python_nado_coding/practice11-3.py | UTF-8 | 2,510 | 3.34375 | 3 | [] | no_license | ####### pip 로 패키지 설치하기
# 구글에서 pypi 검색
# beautifulsup4 4.8.2
# pip install beautifulsoup4 아래 창에 넣고 설치
from bs4 import BeautifulSoup
soup = BeautifulSoup("<p>Some<b>bad<i>HTML")
print(soup.prettify())
# pip list 현재 설치되어있는 리스트 확인가능
# pip show beautifulsoup4 설치되어있는 패키지 정보확인
# pip install --upgrade beautifu... | true |
b41418bd45fda79cfee4042b22988f60137e434f | Python | sowrd299/SillyRobots | /localTextPlayerController.py | UTF-8 | 2,346 | 3.59375 | 4 | [] | no_license | from playerGameController import PlayerGameController
from boardTextDisplay import BoardTextDisplay
class LocalTextPlayerController(PlayerGameController):
'''
A player controller for local, human players
playing with a text-based interface
'''
card_chars_disp = "AbCdEFghIJklMNO" # characters to r... | true |
cdf17767876180682da2be56aaeba4fd3c39d24b | Python | jstrasburger/Tweet_Sentiment_Analysis | /team.py | UTF-8 | 4,811 | 3.140625 | 3 | [
"MIT"
] | permissive | import dash_html_components as html
import dash_bootstrap_components as dbc
import os
import base64
### IMAGES ###
j_strasburger = "static/img/j_strasburger.jpg" # replace with your own image
jack_image = base64.b64encode(open(j_strasburger, 'rb').read())
luis_v = "static/img/luis_v.jpeg" # replace with your own im... | true |
23b8b3401a55afae68248e9bd0fe7fe0564ecc29 | Python | LikeLionSCH/9th_ASSIGNMENT | /20_이예빈/session03/3.py | UTF-8 | 735 | 4.25 | 4 | [
"MIT"
] | permissive | list=[] # 빈 리스트 생성
sum=0 # 총합 sum 초깃값
for i in range(7): # 총 7개의 상품에 대한 가격 입력 받음
print(i, end="")
n=int(input("번째 상품 가격: "))
sum+=n # 입력 받은 가격을 sum에 저장
list.append(n) # 리스트의 끝에 요소 n값을 추가
print(list)
# 전체 상품 구매 불가능한 경우
price=int(input("가지고 있는 돈을 입력하세요 >> "))
if price<sum:
print("돈이 모자랍니다. ", end=""... | true |
72b879f2a4c4d5d89d43a0d819d143f732606264 | Python | rkhal101/Thesis-Test-Results | /wapiti/wavsep/configured/report/extract-urls.py | UTF-8 | 1,080 | 2.578125 | 3 | [] | no_license | import itertools
input_file_loc = "/Users/ranakhalil/Desktop/git/Thesis/results/wapiti/wavsep/configured/report/wapiti-wavsep-configured.txt"
output_file_loc = "/Users/ranakhalil/Desktop/git/Thesis/results/wapiti/wavsep/wapiti-wavsep-configured.csv"
lines = []
new_vuln_string = "**************************************... | true |
41b33f6d91698868bb44727224c92d3d340743c6 | Python | taoste/dirtysalt | /codes/leetcode/combinations.py | UTF-8 | 622 | 2.984375 | 3 | [] | no_license | #!/usr/bin/env python
# coding:utf-8
# Copyright (C) dirlt
class Solution(object):
def combine(self, n, k):
"""
:type n: int
:type k: int
:rtype: List[List[int]]
"""
res = []
def f(idx, r):
if len(r) == k:
res.append(r[:])
... | true |
930110825171484f4635326371b7d3e0301eaf4e | Python | DruiadinMonk/OHLC_Candles | /OHLC.py | UTF-8 | 777 | 4.1875 | 4 | [] | no_license | # Creating a cndle (OHLC) price chart.
import random
prices_1 = [1.0000]
prices_2 = []
base_1 = 100
base_2 = 10
# Generate random prices in the 10'000's place.
for x in range(100):
r1 = random.randint(-5, 5) / 10000
r2 = round(r1 + prices_1[x], 4)
prices_1.append(r2)
# 2. For lo... | true |
a90de5a7f58af22ee5a75b2bd64af7dae466d9f9 | Python | pankas87/Project-Euler---Python | /Problem-6/run.py | UTF-8 | 252 | 3.21875 | 3 | [] | no_license | edge = 100
sum = edge * (edge + 1) / 2
sum_squares = (2 * edge + 1) * (edge + 1) * edge / 6
print('sum', sum)
print('sum_squared', sum * sum)
print('sum_squares', sum_squares)
print('sum_squared - sum_squares', sum * sum - sum_squares ) | true |
c375be29d567426312ab5b8c4297d9abb0549117 | Python | korz/ml-in-csharp | /src/Python/xor.py | UTF-8 | 1,254 | 3.03125 | 3 | [] | no_license | import numpy as np
from keras.models import Sequential
from keras.optimizers import Adam
from keras.layers.core import Dense
from keras.models import model_from_json
from keras import backend as K
def main():
#Get Training Data
input = np.array([ [0, 0], [0, 1], [1, 0], [1, 1] ])
output = np.array([ 0, 1,... | true |
57ef705fe19007ceb2a046933eaeb3f9ecd509ee | Python | martey/django-redis-cache | /tests/benchmark.py | UTF-8 | 2,779 | 3.015625 | 3 | [
"BSD-3-Clause"
] | permissive | """
A quick and dirty benchmarking script. GitPython is an optional dependency
which you can use to change branches via the command line.
Usage::
python benchmark.py
python benchmark.py master
python benchamrk.py some-branch
"""
import os
import sys
from time import time
from django.core import cache
fr... | true |