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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
5cabdcb0e62b2947facad5265249672bbd5e3575 | Python | SomaIITMandi/demo1 | /subarray_with_sum2.py | UTF-8 | 504 | 3.40625 | 3 | [] | no_license | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 24 22:57:48 2019
@author: debashis
"""
arr = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
sum2 = 15
flag = 0
for i in range(len(arr)):
if flag == 1:
break
desired_sum = 0
desired_sum += arr[i]
for j in range(i, len(arr)):
if desi... | true |
a2202cd9a42a9b73b471f313bee127f177088754 | Python | Vadbeg/algorithms | /tasks/trees/binary_tree/binary_search_tree.py | UTF-8 | 5,082 | 3.53125 | 4 | [] | no_license | from typing import Union, Optional
from tasks.trees.binary_tree.traverse import traverse_inorder, traverse_depth_first
class BinarySearchTree:
def __init__(self, payload: Union[int, float]):
self.left_child: Optional['BinarySearchTree'] = None
self.right_child: Optional['BinarySearchTree'] = None... | true |
6fdb50bac74bf797220dc56995b5760c43b6450a | Python | yoonm/yoonm.github.io | /python/author_death.py | UTF-8 | 391 | 3.390625 | 3 | [] | no_license | author_year = {"Charles Dickens": "1870",
"William Thackeray": "1863",
"Anthony Trollope": "1882",
"Gerard Manley Hopkins": "1889"}
for author, year in author_year.items():
print(author + " kicked the bucket in " + year + ".")
## using a method:
# def print_the_names(name, year):
# print(author + " ... | true |
3bb8c28a3584ad704b94577ffbcd0d1819ef69eb | Python | jesstucker/exercism | /kindergarten-garden/kindergarten_garden.py | UTF-8 | 791 | 3.171875 | 3 | [] | no_license | class Garden():
def __init__(self, code, students=None):
self.code = code.splitlines()
if not students:
self.students = ['Alice', 'Bob', 'Charlie', 'David','Eve', 'Fred', 'Ginny', 'Harriet','Ileana', 'Joseph', 'Kincaid', 'Larry']
else:
self.students = sorted(students)
def plants(self, student):
plant_r... | true |
ade1c856c43daeedae79ea2a033dfc79a7b51785 | Python | dair370/seleniumProject | /eesignup.py | UTF-8 | 2,273 | 2.8125 | 3 | [] | no_license | import unittest
from selenium import webdriver
import time
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
class eesignupCase(unittest.TestCase):
def setUp(self):
self.driver = webdriver.Chr... | true |
7eec23f4073e142899f1aed92ce01d2327bfdae6 | Python | vasu589/school-admission-tool | /README.py | UTF-8 | 1,295 | 3.5 | 4 | [
"MIT"
] | permissive | #program for basic school administration tool import csv
def write_into_csv(info_list)
with open('student_info.csv','a',newline=' ')
as csv_file:
writer=csv.writer(csv_file)
if cdv_file tell()==0:
writer.writerrow("name","age","contact no","email id")
writer.writerrow... | true |
ea2e6e06e0566ea46610b4af9590de4f30680fb6 | Python | 168WenFangjun/grx | /tag/expand.py | UTF-8 | 1,749 | 3.125 | 3 | [] | no_license | import tag
import text
import lexer
import parser
import iteration
def token_class():
return ExpandTagToken
class AbstractExpandToken(lexer.AbstractToken):
def parse(self, context):
try:
start = context.defaultrange[0]
end = context.defaultrange[1]
except AttributeError:
raise Exception("expansion di... | true |
9547adbb47f20ae476b1d783687d8ad16795b31a | Python | yuly3/atcoder | /ABC/ABC195/D.py | UTF-8 | 732 | 2.796875 | 3 | [] | no_license | import sys
from bisect import bisect_left
sys.setrecursionlimit(10 ** 7)
rl = sys.stdin.readline
def solve():
N, M, Q = map(int, rl().split())
WV = [list(map(int, rl().split())) for _ in range(N)]
X = list(map(int, rl().split()))
LR = [list(map(int, rl().split())) for _ in range(Q)]
WV.sort(... | true |
0ee0077b5359d661c71957c2096fbed23a6def53 | Python | Lucasplpx/youtube-extract | /main.py | UTF-8 | 2,151 | 2.625 | 3 | [] | no_license |
from dotenv import load_dotenv
from datetime import datetime
from googleapiclient.discovery import build
import pandas as pd
import os
load_dotenv()
youTubeApiKey = os.getenv('API_KEY')
youtube = build('youtube', 'v3', developerKey=youTubeApiKey)
playListId = os.getenv('PLAY_LIST_ID')
playListName = 'NAME_PLAYLIST... | true |
7263ef9e5c7cdcde2858567a18ad76cc8511ee43 | Python | FrancoJigo/Thesis | /to_grayscale.py | UTF-8 | 345 | 2.53125 | 3 | [] | no_license | import cv2
import glob, os, errno
# Replace mydir with the directory you want
mydir = r'C:/Users/63917/Documents/Jigo/Thesis/'
for fil in glob.glob("*.jpg"):
image = cv2.imread(fil,0)
# gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # convert to greyscale
# print(image.shape)
cv2.imwrite(os.pa... | true |
b07e351fa1d20d9884faf8c913a17f11ac73cae9 | Python | boknowswiki/mytraning | /lc/python/0740_delete_and_earn.py | UTF-8 | 1,363 | 3.4375 | 3 | [] | no_license | # hash table and dp
# time O(n+k)
# space O(n+k)
class Solution:
def deleteAndEarn(self, nums: List[int]) -> int:
points = defaultdict(int)
max_number = 0
# Precompute how many points we gain from taking an element
for num in nums:
points[num] += num
max_numb... | true |
cfe78b8cdbbccd15373e346d908ff8b65942489d | Python | asogaard/AnalysisTools | /scripts/parseGRL.py | UTF-8 | 1,056 | 2.578125 | 3 | [] | no_license | import os, sys
from sys import argv
# XML parser.
import xml.etree.ElementTree as ET
# I/O
if len(argv) < 2:
print "Please specify the GRL path."
sys.exit()
if not os.path.isfile(argv[1]) :
print "Provided path '%s' doesn't point to a file." % ( argv[1] )
sys.exit()
if not argv[1].split('.')[-1] == ... | true |
97178ca38c55b79e5c4ae1168531ebe027d8ee6f | Python | Lanayaghi/pythonstack | /exam_dashboard/log_app/models.py | UTF-8 | 2,098 | 2.65625 | 3 | [] | no_license | from django.db import models
import re
class UsersManager(models.Manager):
def validator(self, post_data):
errors = {}
email_regex = re.compile(r'^[a-zA-Z0-9.+_-]+@[a-zA-Z0-9._-]+\.[a-zA-Z]+$')
if len(post_data['first_name']) < 2:
errors['first_name'] = "First name... | true |
39da6bd74f17e5d8723fa28f0ef3ea52502691b0 | Python | marekprochazka/V2_MarkoGebra | /Predecessors/list_view/NoiseRow.py | UTF-8 | 3,966 | 2.53125 | 3 | [] | no_license | from Bases import BaseRow, BaseLabel, BaseColorPicker, BaseEntry
from tkinter import StringVar, Button
from tkinter import ttk as t
from Decorators.input_checkers import noise_input_controller
from Globals.variables import Variables as V
# VALUE [id, seed, dispersion, quantity, color, marker, noise]
# VALUE IS IN FOR... | true |
313d20b728e97c95f39db9736e9b94ba79427de7 | Python | jwmcglynn/videosync | /server/tests/test_room.py | UTF-8 | 2,184 | 2.609375 | 3 | [
"ISC"
] | permissive | from models.room import Room, NoSuchRoomException
from models.user import User
from database_create import database_create
import database
import os
from nose.tools import *
k_database = "test_db.sqlitedb"
class TestRoom:
@classmethod
def setup_class(cls):
database_create(k_database)
database.con... | true |
c5c65cf3ad052956230f8e598a68d70555f9e7c2 | Python | ProfessorLinstar/Derivative-Program | /derive/functions/separateFunctions.py | UTF-8 | 2,535 | 2.515625 | 3 | [
"MIT"
] | permissive | class Separate:
def sepByAdd(inpSep,parOrder):
sep = [""]
numOfGroups=len(parOrder[1])
sepCounter = 0
if len(inpSep)==1:
return inpSep
par0List=[]
for i in range(numOfGroups):
if parOrder[1][i]==0:
par0List.append(parOrder[0]... | true |
bfdc1700b6ec4726a5ad66a360783b8316724427 | Python | SurabhiP13/Open-CV | /Face_Recognition.py | UTF-8 | 818 | 2.578125 | 3 | [] | no_license | import cv2 as cv
import numpy as np
haar_cascade=cv.CascadeClassifier('haar_face.xml')
people=[]
for i in os.listdir(r'D:\Documents\opencv\faces'):
people.append(i)
face_recognizer=cv.face.LBPHFaceRecognizer_create()
face_recognizer.read('face_trained.yml')
img=cv.imread(r'test\v.jfif')
gray = cv.cvtColor(img, ... | true |
0c997239e5fd497a3da4f535ae7fe7a3fbdaffb5 | Python | zack28/Algorithms | /Searching/linear_search.py | UTF-8 | 383 | 3.84375 | 4 | [] | no_license | def search(a,key):
i=0
while i< len(a):
if a[i] == key:
return True
globals()['pos']=i
i=i+1
return False
a=[]
n=int(input("Enter No Of Elements in the list: "))
for i in range(0,n):
ele=int(input())
a.append(ele)
print(a[0])
key=int(input("Enter The No To Be Searched: "))
if searc... | true |
e35fca0d33503c077f1416be36034d382b1b18e4 | Python | haeriamin/Hybrid-Optimization | /ref.py | UTF-8 | 1,178 | 2.6875 | 3 | [] | no_license | # Copyright (C) 2020 Amin Haeri [ahaeri92@gmail.com]
import csv
def get_exp(depth):
time = 20;22 # Exp time [sec] 45/60
fr_exp = 62.5 # Sampling frequency [Hz]
start_exp = 1
path = './input/'
filename = 'weight_calibration.csv'
f = open(path + filename, 'r')
reader = csv.reader(f)
... | true |
687b4909449877c13b0c21fbf8d85111a80063b8 | Python | inthescales/lyres-dictionary | /src/models/environment.py | UTF-8 | 578 | 2.765625 | 3 | [
"MIT"
] | permissive | class Environment:
def __init__(self, anteprev, prev, next, postnext, object_specified=False):
self.anteprev = anteprev
self.prev = prev
self.next = next
self.postnext = postnext
self.object_specified = object_specified
def is_initial(self):
return self.... | true |
65101f6ca5044f40b281b1c294aa0133b28b62d2 | Python | Anjalipatil18/ListOfAllQuestion | /occurence_list.py | UTF-8 | 335 | 3.09375 | 3 | [] | no_license | char_list = ["a", "n", "t", "a", "a", "t", "n", "n", "a", "x", "u", "g", "a", "x", "a"]
new_list=[]
i=0
while i<len(char_list):
j=0
count=0
while j<len(char_list):
if char_list[i] == char_list[j]:
count=count+1
j=j+1
if [char_list[i],count] not in new_list:
new_list.append([char_list[i],count])
i=i+1
... | true |
5f59ba658b763e6db4851d131133fef8bbae2667 | Python | ustcerlik/rookie2veteran | /frcnn/nms_.py | UTF-8 | 3,426 | 3 | 3 | [] | no_license | import numpy as np
class Nms(object):
def __init__(self, threshold, topk):
super(Nms, self).__init__()
self.threshold = threshold
self.topk = topk
def nms_core(self, b_boxes, scores):
"""
b_boxes 排序， 按照scores, mapping: index的映射
注意：nms其实是对每个类别都要做，即类别之前是独立的，就是说如... | true |
d22725cfb849159ac5a845206db32fed3e902e76 | Python | vincentmader/statistical_physics | /10/code/task02b.py | UTF-8 | 271 | 3.296875 | 3 | [] | no_license | import matplotlib.pyplot as plt
import numpy as np
from numpy import cosh, sinh
def M(x):
return cosh(x)/sinh(x) - 1/x
x = np.linspace(0, 100)
plt.plot(x, M(x))
plt.xlabel(r'$x$')
plt.ylabel(r'$\coth(x)-\frac{1}{x}$')
plt.savefig('../figures/magnetization.pdf')
| true |
f48927dba402df6e9e51d6418022511acf932566 | Python | flance3032021/car_delivery | /app.py | UTF-8 | 3,483 | 2.953125 | 3 | [] | no_license | import streamlit as st
from geopy.geocoders import Nominatim
from geopy.distance import geodesic
geolocator = Nominatim(user_agent="car_price")
st.set_page_config(page_title= 'Car Delivery Price Calculation Project', initial_sidebar_state = 'auto')
hide_streamlit_style = """
<style>
#MainMenu {visibility: hidden;}
foot... | true |
83d4a0f4ebc6bddd1642d93c470342ef3b83a3bf | Python | saibi/python | /ekiss/ekiss_login.py | UTF-8 | 8,741 | 2.59375 | 3 | [] | no_license | #!/usr/bin/python3
import requests
from bs4 import BeautifulSoup as bs
import random
import sys
from datetime import datetime
import time
Header = {
'Referer' : 'http://ekiss.huvitz.com/',
'User-Agent' : 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:63.0)'
}
Agent_list = [
'Mozilla/5.0 (X11; Ubunt... | true |
3dce9f881a39e055c9be6ac5da13a6912a46c104 | Python | jafriyie1/ML-GPS-Research- | /first_model.py | UTF-8 | 4,736 | 2.78125 | 3 | [] | no_license | import tensorflow as tf
import pandas as pd
import numpy as np
from sklearn import preprocessing
# importing data and munging
constant_data = pd.read_csv('full_library_xt875.csv')
#normalizing data
#normalization = lambda df: (df - df.mean()) / (df.max() - df.min())
#constant_data = normalization(constant_data)
t_dat... | true |
ae90bf14a93511c1a961ea67081cd15a730faf34 | Python | FuckBrains/petrovich | /apps/bot/commands/ExchangeRates.py | UTF-8 | 2,220 | 2.796875 | 3 | [
"MIT"
] | permissive | from apps.bot.APIs.CBRAPI import CBRAPI
from apps.bot.classes.Exceptions import PWarning
from apps.bot.classes.common.CommonCommand import CommonCommand
class ExchangeRates(CommonCommand):
name = "курс"
help_text = "курс валют"
help_texts = [
"- курс валют",
"[количество=1] (валюта) - пере... | true |
225ea764376babfbc29d48122f211da0a540aed8 | Python | chrisemerson/adventOfCode | /2017-Python/day2/day2.py | UTF-8 | 440 | 3.203125 | 3 | [] | no_license | spreadsheet = open('input.txt', 'r')
total = 0
totalpt2 = 0
with spreadsheet as fp:
for line in fp:
numbers = list(map(int, line.strip().split("\t")))
total += max(numbers) - min(numbers)
for number in numbers:
for innernumber in numbers:
if number > innernumbe... | true |
08ea63de78d8b308bb921a4450d5ac58c2a4db1f | Python | LLCampos/pcrawler | /join_data.py | UTF-8 | 2,015 | 3.140625 | 3 | [] | no_license | import json
import os
import time
# pdata -> passatempos data
def join_pdata():
"""Joins all .json files resulting from the crawling into just one, called
complete.json.
Each higher-level name of this json is a string representing the name of a
website and the corresponding value is a list of 'passa... | true |
98d16a55576eceb16dd9dc39df3566edf32829df | Python | Ayseekinci/Python | /Python Temelleri/python object based programming/class1.py | UTF-8 | 1,014 | 4.0625 | 4 | [] | no_license | # Kullanıcıdan kısa kenarı alıp uzun kenarıda=18 alıp dikdörtgenin çevresini ve alanını hesaplanması
class dikdortgen:
kisakenar = int(input("Kısa kenar : "))
def __init__(self, uzunkenar=18):
self.uzunkenar = uzunkenar
def cevre_hesapla(self):
return 2*(self.kisakenar+self.uzunkenar)
... | true |
df2c85ebb59959d2d78d04d48639fa6ea7190f5d | Python | lolsborn/python-testdata | /testdata/factories/statistical.py | UTF-8 | 2,799 | 3.484375 | 3 | [
"MIT"
] | permissive | import math
import random
from ..base import Factory
from ..errors import InvalidTotalPrecentage
from .generic import Constant
class StatisticalPercentageFactory(Factory):
"""
Returns a different value a precentage of a time.
:param factories: a list of 2 item tuples. each tuple contains The Factory that ... | true |
3922f33c0b3f234c5e55ce709b679d51acd5e9c9 | Python | mattermost/mattermost-data-warehouse | /utils/twitter_mentions.py | UTF-8 | 4,590 | 2.671875 | 3 | [] | no_license | import os
import pandas as pd
import tweepy
from tweepy import OAuthHandler
from extract.utils import execute_query, snowflake_engine_factory
def get_twitter_mentions():
# Twitter credentials
# Obtain them from your twitter developer account
# Need to add this or another Twitter Developer API Key to Sy... | true |
be581e5c2ec87ed06181ffdd9ec7c82b846ee658 | Python | HodAlpert/Randomized | /run.py | UTF-8 | 3,730 | 3.1875 | 3 | [] | no_license | import os
from datetime import datetime
from multiprocessing import Pool
import networkx as nx
from matplotlib import pyplot as plt
from algorithm import ApproximateDistanceOracles
from common import timeit, average_difference, avg
def draw(G):
pos = nx.spring_layout(G) # positions for all nodes
# nodes
... | true |
fae9c4ca1a8a0bb804b1e6aeb47d523b188490cf | Python | bleist88/MCC | /Create.py | UTF-8 | 2,130 | 2.734375 | 3 | [] | no_license | """
MCC/Create.py
This contains the function MCC.create() which creates a new FITS Cube from
the configurations files.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from .__imports__ import *
... | true |
7a55363db7a2827a62f8879f5a95e9d5515d51a2 | Python | Randeepk1/OPENCV | /TEMPLATE_MATCHING1.py | UTF-8 | 1,290 | 2.546875 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
# In[13]:
import cv2
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
# In[14]:
# img = cv2.imread("m2.jpg",0)
img2 = cv2.resize(img,(75,110),3)
template = img[40:150,100:175]
plt.imshow(img)
# template = cv2.imread("m1.jpg",0)
# plt.subplot(111);... | true |
2944b74e05814ae3c29c0b3e578aba21bb8d109c | Python | akimi-yano/algorithm-practice | /lc/743.NetworkDelayTime.py | UTF-8 | 7,705 | 3.28125 | 3 | [] | no_license | # 743. Network Delay Time
# There are N network nodes, labelled 1 to N.
# Given times, a list of travel times as directed edges times[i] = (u, v, w),
# where u is the source node, v is the target node, and w is the time it takes
# for a signal to travel from source to target.
# Now, we send a signal from a certain ... | true |
ea1594ce9e6daf16360f8992e4db2c318b995679 | Python | koenigscode/python-introduction | /content/partials/working_with_files/with_context_manager.py | UTF-8 | 229 | 3.15625 | 3 | [] | no_license | with open("file.txt", "r") as f:
content = f.read()
print(content)
print(f"The file is {'closed' if f.closed else 'open'}")
# outside the context manager
print(f"The file is {'closed' if f.closed else 'open'}") | true |
eeac0a0df4aebdf5670ff37d7e188538d0115dbe | Python | fatgenius/tensorflow_selfstudy | /p1.py | UTF-8 | 523 | 2.78125 | 3 | [] | no_license | import tensorflow as tf
import numpy as np
x_data = np.random.rand(100)
y_data =x_data*0.1+0.2
#build linear model
b= tf.Variable(5.)
k= tf.Variable(0.)
y=k*x_data+b
#build a match
loss= tf.reduce_mean(tf.square(y_data-y))
#build optimizer
optimizer =tf.train.GradientDescentOptimizer(0.2)
#build mini match
trai... | true |
d298b4bcdf7832d80637cc576dc1470196e286d1 | Python | geunhee725/snubioinfo-TermProject | /gen-candidates.py | UTF-8 | 2,637 | 2.921875 | 3 | [] | no_license | #!/usr/bin/env python3
#
# Copyright (c) 2015 Hyeshik Chang
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modi... | true |
72d6bf219c5bb0300dc72443dedb5c3ec1bfbd46 | Python | miladbohlouli/Pytorch-Tutorials | /Intermediate/CNN.py | UTF-8 | 3,613 | 2.84375 | 3 | [] | no_license | import torch
import numpy as np
import os
import torch.nn as nn
from torchvision.transforms import transforms
from torch.utils import data
import torchvision
from tqdm import *
batch_size = 64
num_epochs = 1
save_dir = "save/"
learning_rate = 0.001
load = True
train_dataset = torchvision.datasets.MNIST("../datasets",... | true |
bb363a932ba63d648a9018a12df48efd56afe5d6 | Python | haruyasu/LeetCode | /1_array_and_strings/find_pivot_index.py | UTF-8 | 461 | 3.40625 | 3 | [] | no_license | class Solution:
def pivotIndex(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
total = sum(nums)
left_sum = 0
for i, num in enumerate(nums):
if left_sum == (total - left_sum - num):
return i
left_sum += num
... | true |
4c5cda3c2267f59b9928292e3031de2c5e10dc85 | Python | pbarden/python-course | /Chapter 5/printf_string.py | UTF-8 | 77 | 3.015625 | 3 | [] | no_license | user_word = 'Amy'
user_number = 5
print('%s,%d' % (user_word, user_number))
| true |
e4ad240a085c38a076f0be842bcb893e2265e1fc | Python | tlingf/bluebook | /mean.py | UTF-8 | 227 | 2.703125 | 3 | [] | no_license | import pandas as pd
import numpy as np
import sys
fn = sys.argv[1]
data = pd.read_csv(fn)
print data
print "mean", np.mean(data["SalePrice"])
data = pd.read_csv('Train.csv')
print "mean of Train", np.mean(data["SalePrice"])
| true |
1f387bde3c85fc89f4d8816492d291b7e14b7e57 | Python | DiksonSantos/Curso_Intensivo_Python | /Pagina_272_Faça_Você_Mesmo.py | UTF-8 | 1,809 | 3.125 | 3 | [] | no_license | '''
#9.10 Importando Restaurant
#import MODULO_Classe_Restaurante_
from MODULO_Classe_Restaurante_ import * #Só funcionou Assim :/ ???
MamaMia = Restaurant("Lanchonete", "Tapioca")
print(MamaMia.name)
print(MamaMia.cuisine_type)
'''
#9.11 -> Importando ADMIN
#from MODULO_Admin import * #Hora Só f... | true |
56052746ff0e5c8bdc3b6dc21b58ea9b85d7b3ab | Python | AlJohri/chromedevtools | /chromedevtools/debugger.py | UTF-8 | 3,693 | 2.546875 | 3 | [] | no_license | """
Debugger
Debugger domain exposes JavaScript debugging capabilities. It allows setting and removing
breakpoints, stepping through execution, exploring stack traces, etc.
https://developer.chrome.com/devtools/docs/protocol/1.1/debugger
"""
from __future__ import absolute_import, division, print_function, unicode_... | true |
31f56e2961ad5135ecec68189f9e5f0dd4d05e0d | Python | gregmolskow/MarsRover | /RasPi/i2cCom.py | UTF-8 | 3,520 | 3.109375 | 3 | [] | no_license | import smbus
import time
#Functions
class SetupError(Exception):
pass
class PowerControlError(Exception):
pass
class i2cCom(object):
#This class sets up the i2c communications systems for a single device. The only shared variable
#between object instances is the "bus" variable which will not chn... | true |
f57a47d0d83e0fea4023edf3dde5c8fe7e4d027e | Python | utsuke/ddssj | /data/type_detail.py | UTF-8 | 559 | 2.640625 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import urllib
def _print(data):
if isinstance(data, unicode): data = data.encode('utf-8')
# print data
return data.strip()
if __name__ == '__main__':
type_data = {}
count = 0
for line in open('type_detail.txt'):
if not line.startswith('#'):
... | true |
dd85880bc8a52a17be5162a674750c397fe179eb | Python | Synectome/WorkTimer | /Curtain.py | UTF-8 | 3,569 | 2.765625 | 3 | [] | no_license | import os
import csv
import datetime
class states:
init_time = 0
init_break = 0
on_break = False
timing_on = False
since_start = False
time_mod = False
def task_submition(state, root_or_start=False, entr1=False, entr2=False):
logtime = datetime.datetime.now().strftime("%d/%m/%Y %H:%M:%S"... | true |
51067e2442661658d141e677dbcdea92faf5ce6d | Python | Fantomster/py | /deep_learning/validation/k-fold_cross-validation.py | UTF-8 | 683 | 2.5625 | 3 | [] | no_license | k = 4
num_validation_samples = len(data) // k
np.random.shuffle(data)
validation_scores = []
for fold in range(k):
validation_data=data[num_validation_samples * fold: num_validation_samples * (fold + 1)]
training_data=data[:num_validation_samples * fold] + data[num_validation_samples * (fold + 1):]
model... | true |
d6b876029ff06c573fee187f1cb00315e3f97207 | Python | ayouubeloua/PFE-BD | /Platform-Bigdata/dev/twitter_prod.py | UTF-8 | 1,701 | 2.578125 | 3 | [] | no_license | import tweepy
import json
import time
from kafka import KafkaProducer
def json_encod(data):
return json.dumps(data).encode('utf-8')
def search_for_hashtags(consumer_key, consumer_secret, access_token, access_token_secret, hashtag_phrase):
#create authentication for accessing Twitter
auth = tweepy.OAuthHandle... | true |
8dcf3c903cc484a307beaf8257b3808005173c3f | Python | rbaral/PythonDataAnalysis | /edu/fiu/rb/pandas/testgroup.py | UTF-8 | 4,243 | 3.546875 | 4 | [] | no_license | __author__ = 'rbaral'
#ref:http://www.shanelynn.ie/summarising-aggregation-and-grouping-data-in-python-pandas/
'''
Analyze the US baby names from the
SSA dataset. Can be used to analyze for different
metrics as provided in https://www.ssa.gov/oact/babynames/decades/names2010s.html
'''
'''
TODOS:
1) given a year, find... | true |
d5a6910f3c94cb0ba38711ef27f547e83f598755 | Python | Abhi24krishna/Semantic-Code-Clone-Detection | /test_case_1.py | UTF-8 | 170 | 3.046875 | 3 | [] | no_license | a = 235
b = 51
c = a
p = a < b
q = a < c
if p:
y=0
print(y)
if q:
x=2
print(x)
else:
l=3
print(l)
a = 235
b = 51
c = 47
print(a,b,c)
| true |
fba0210cfd50112892b763f2b080c740e2f18d05 | Python | k-takata/minpac | /tools/dl-vim-kt.py | UTF-8 | 4,565 | 2.65625 | 3 | [
"MIT",
"Vim"
] | permissive | #!/usr/bin/python3
# Download the latest vim-kt from the GitHub releases
import argparse
import calendar
import io
import json
import os
import sys
import time
import urllib.request, urllib.error
# Repository Name
repo_name = 'k-takata/vim-kt'
gh_releases_url = 'https://api.github.com/repos/' + repo_name + '/release... | true |
b5bd50171776c66f31a749b2d6ba90fcc57204c2 | Python | jacobandreas/bright | /brightengine.py | UTF-8 | 3,685 | 3 | 3 | [] | no_license | from math import *
from numpy import *
class World(object):
def __init__(self, dimensions, c):
self.dimensions = dimensions
self.c = c
def AddVelocities(self, v1, v2):
if not v2.any():
return v1
par = dot(v1, v2) / dot(v2, v2) * v2
perp = v1 - par
... | true |
dd381e6b8253cfeaffd129024ad8343a0c3e6bfb | Python | juranga/ntps | /Infrastructure/PacketLibrary/Packet.py | UTF-8 | 5,034 | 2.8125 | 3 | [] | no_license | from Infrastructure.PacketLibrary.Dissector import Dissector
from collections import defaultdict
from scapy.all import *
"""
As it currently stands, the Ether layer has to be dissected in a different way than every other layer.
This is because the Ether class in scapy does not have a "haslayer" function, and thus must... | true |
d76ba238499b268a22c20d609340ae641981ac9b | Python | forhadmethun/my-data-structure | /linked_list/CircularLinkList.py | UTF-8 | 774 | 3.859375 | 4 | [] | no_license | class Node:
def __init__(self, data = None):
self.data = data
self.next = None
class CircularLinkList:
def __init__(self):
self.head = None
def insert(self,data):
self.newNode = Node(data)
if(self.head == None):
self.head = self.newNode
se... | true |
89fa1821722bbf711698dd0c8b4ce0fcbfb94112 | Python | burglarhobbit/machine-reading-comprehension | /S-NET/nmt_snet_ans_syn/nmt/analyze_dataset_2.py | UTF-8 | 19,361 | 3.0625 | 3 | [
"Apache-2.0"
] | permissive | import tensorflow as tf
import random
from tqdm import tqdm
import spacy
import json
from collections import Counter
import numpy as np
from nltk.tokenize.moses import MosesDetokenizer
import string
import re
nlp = spacy.blank("en")
def word_tokenize(sent):
doc = nlp(sent)
return [token.text for token in doc]
def ... | true |
bf5d18d9dd89a0fed88bac64d6aaf8d1a261d678 | Python | KimKeunSoo/Algorithm | /Programmers/해쉬/Level2_전화번호 목록/solution.py | UTF-8 | 297 | 2.796875 | 3 | [] | no_license | def solution(phone_book):
for index1, num in enumerate(phone_book):
for index2, num_punk in enumerate(phone_book):
if index1 == index2:
continue
else:
if num_punk.startswith(num):
return False
return True | true |
004655b01e807dc4066fc9b9119123dc12b0c48a | Python | coderguanmingyang/LeetCode-GMY | /Group-Anagrams.py | UTF-8 | 1,118 | 4.21875 | 4 | [] | no_license | # -*- coding:utf-8 -*-
'''
Given an array of strings, group anagrams together.
Example:
Input: ["eat", "tea", "tan", "ate", "nat", "bat"],
Output:
[
["ate","eat","tea"],
["nat","tan"],
["bat"]
]
Note:
All inputs will be in lowercase.
The order of your output does not matter.
'''
##Solutio... | true |
7ac3e170a6cf9940b4d20e9b937f40c9e2a30844 | Python | simpleoier/espnet | /egs2/reazonspeech/asr1/local/data.py | UTF-8 | 1,543 | 2.671875 | 3 | [
"Apache-2.0"
] | permissive | import os
import sys
from datasets import load_dataset
from reazonspeech.text import normalize
def save_kaldi_format(outdir, ds):
os.makedirs(outdir, exist_ok=True)
with open(os.path.join(outdir, "text"), "w") as fp_text, open(
os.path.join(outdir, "wav.scp"), "w"
) as fp_wav, open(os.path.join(o... | true |
b544f47b8da6f4173f6c854ae95f37a3baae5704 | Python | vidyasagarr7/DataStructures-Algos | /GeeksForGeeks/Arrays/SmallestPositiveMissing.py | UTF-8 | 2,671 | 3.78125 | 4 | [] | no_license |
"""
Find the smallest positive number missing from an unsorted array
You are given an unsorted array with both positive and negative elements.
You have to find the smallest positive number missing from the array in O(n) time using
constant extra space. You can modify the original array.
"""
def segregate(input_list)... | true |
2c75e109fe62bf8670aa70b31059385f9b80da6a | Python | NPScript/pysqrt | /pysqrt/__init__.py | UTF-8 | 2,989 | 3.59375 | 4 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
class sqrt:
def __init__(self, number, max):
"""
Documentation of the algorithm
can be found here: https://en.wikipedia.org/wiki/Shifting_nth_root_algorithm
"""
self.max = max # set maximal size after t... | true |
3fdfdf01b40c695dc0071b4a6bcc8b9de6f66690 | Python | marceltoben/evandrix.github.com | /py/django_tools/feincms/feincms/utils/__init__.py | UTF-8 | 7,341 | 2.671875 | 3 | [
"BSD-2-Clause"
] | permissive | # ------------------------------------------------------------------------
# coding=utf-8
# ------------------------------------------------------------------------
"""
Prefilled attributes
====================
The two functions prefilled_attribute and prefill_entry_list help you avoid
massive amounts of database qu... | true |
17cf71b86ca9a88299bd3245617b5a779bf1bf82 | Python | RozenAstrayChen/ML-course | /ex1/ex1_1.py | UTF-8 | 1,233 | 3.421875 | 3 | [] | no_license | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from linear_reg import computeCost, gradientDescent, predict
data = pd.read_csv('ex1data1.txt', header = None) #read from dataset
X = data.iloc[:,0] # read first column
y = data.iloc[:,1] # read second column
m = len(y) # number of training example... | true |
9098c02fe54a113e8df065b19ba4edd2cdb9a682 | Python | fusichang107117/image_utils | /read_mp4.py | UTF-8 | 3,962 | 2.78125 | 3 | [] | no_license | import cv2
import os
def get_frames_by_second(video_path, start = 0, end = 0, interval = 0, width = 0, height = 0):
cap = cv2.VideoCapture(video_path)
# Find OpenCV version
(major_ver, minor_ver, subminor_ver) = (cv2.__version__).split('.')
fps = 0
if int(major_ver) < 3:
fps = cap.get(cv2.c... | true |
934689e2fe58eba112e8ba1ba9c48abf05777868 | Python | Lyther/Gomoku | /tools/convert.py | UTF-8 | 717 | 2.90625 | 3 | [] | no_license | import generate
SIZE = 15
def main(content):
steps = []
pre_index = 0
index = 0
for i in content:
if i >= 'a' and i <= 'z':
if index == 0:
pass
else:
steps.append(content[pre_index:index])
pre_index = index
index += 1
steps.append(content[pre_index:index])
output(steps)
def output(steps):
... | true |
ea64170da29cca45df1d4f3ea069af1ff30787b3 | Python | tjwudi/pythonic | /jsontest.py | UTF-8 | 80 | 2.84375 | 3 | [] | no_license | import json
x = {
'y': [1, 2, 3],
'z': 'Hello'
}
print json.dumps(x)
| true |
57103851feea037858c81147f8e64a0bec16c9d6 | Python | christian-miljkovic/jarvis | /jarvis/crud/items.py | UTF-8 | 2,892 | 2.84375 | 3 | [] | no_license | from asyncpg import Connection
from typing import List, Union
from jarvis.models import Beer, Wine, Liquor
async def create_item(
conn: Connection, item: Union[Beer, Liquor, Wine]
) -> Union[Beer, Liquor, Wine, None]:
item_type = str(item)
model_mapping = {"beer": Beer, "wine": Wine, "liquor": Liquor}
... | true |
80ab0c2c6cf91ba33526acc185234ef0ec5421d6 | Python | sommerpi/mappee-web-map | /mappee-web-map.py | UTF-8 | 1,764 | 3.0625 | 3 | [] | no_license | import folium
import pandas
# load volcanoes data
DATA = pandas.read_csv("volcanoes.txt")
LAT = list(DATA["LAT"])
LON = list(DATA["LON"])
ELEV = list(DATA["ELEV"])
NAME = list(DATA["NAME"])
# create map
MAP = folium.Map(location=[38.58, -99.09], zoom_start=5, tiles="Stamen Terrain")
# produce colour based on elevati... | true |
49f6744864fa649a6bff08d4aea03c9c7d6743f6 | Python | kiboliu/Small-Programs | /Snake/game.py | UTF-8 | 7,455 | 3.25 | 3 | [] | no_license | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sun Nov 26 17:50:40 2017
@author: liuzhangqian
"""
import random, sys, time, pygame
from pygame.locals import *
#screen refresh rate, equal to the move speed of snake
FPS = 5
WINDOWWIDTH = 640
WINDOWHEIGHT = 480
#size of grid
CELLSIZE = 20
assert WINDO... | true |
14aa25c3fdc60f1732509ba005e1f01376b02e04 | Python | mayur2402/python | /PFile.py | UTF-8 | 189 | 3.125 | 3 | [] | no_license | print("Enter file name")
name = input()
fp = open(name,"w+")
print("Enter data to store in file")
Adata = input()
fp.write(Adata)
pos = fp.seek(0,0)
Ddata = fp.read(len(name))
print(Ddata)
| true |
e7d79dc84d9ec39220e9da882757f7c220122f55 | Python | ruizhang84/full-stack-udacity | /catalog/lotsofitems.py | UTF-8 | 1,124 | 2.71875 | 3 | [] | no_license | from sqlalchemy import create_engine, desc
from sqlalchemy.orm import sessionmaker
from datetime import datetime
from db_catalog import Base, Category, Item, User
engine = create_engine('sqlite:///catalog.db')
Base.metadata.bind = engine
DBSession = sessionmaker(bind=engine)
session = DBSession()
category1 = Categor... | true |
0538ccdbfdaf9aa8c5014141baaebfb25c07a7da | Python | paulmwangi556/Object-Oriented-Programming-II | /Quizzes/Python_Loops_Quiz/grading_system.py | UTF-8 | 550 | 3.71875 | 4 | [
"Unlicense"
] | permissive |
print(
"""
GRADING SYSTEM
(enter q to quit)
"""
)
def start():
score = input("Enter Score: ")
if score.lower() == 'q':
pass
else:
score = int(score)
if score in range(70, 100):
print("Grade: A")
start()
elif score in range(60, 69):
print("Grade: B")
start()
elif score in range(50, 59):
... | true |
a475a3d44f56f236afd0708738793231d6d3915b | Python | sail-y/python | /base/fileOp/fileTest.py | UTF-8 | 793 | 2.921875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = 'xiaomai'
f = open('/Users/xiaomai/test.txt', 'r')
for line in f.readlines():
print(line.strip()) # 把末尾的'\n'删掉
f.close()
try:
f = open('/Users/xiaomai/test.txt', 'r')
print f.read()
finally:
if f:
f.close()
# with语句来自动帮我们调用close()方法：... | true |
d59678ed478cc71c391ea982c1dfaa4843dab754 | Python | LXiong/PythonNetwork | /chapter1/1_13b_echo_client.py | UTF-8 | 870 | 3 | 3 | [] | no_license | import socket
import argparse
import sys
host = 'localhost'
def echo_client(port):
"""A echo client"""
# Create a TCP/TP client
try:
sock = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
server_address = (host,port)
sock.connect(server_address)
data = 'Hi,I\'m echo client... | true |
84ff7bbf494788a7f29fe52b99127ec849a1332e | Python | hector81/Aprendiendo_Python | /Archivos/txt/Ejercicio_Dia3.py | UTF-8 | 3,832 | 3.625 | 4 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | # FUNCIONES
def introducirNumero():
while True:
try:
opcion = int(input("Por una opción: "))
if opcion > 0 and opcion < 6:
return opcion
break
else:
print("Las opciones son del 1 al 5")
except Value... | true |
aecc3f0cc1ec54c64d094203e35bf36245c5d5d1 | Python | lostarray/LeetCode | /204_Count_Primes.py | UTF-8 | 1,119 | 3.703125 | 4 | [] | no_license | # Description:
#
# Count the number of prime numbers less than a non-negative number, n.
#
# Tags: Hash Table, Math
# Difficulty: Easy
class Solution(object):
def countPrimes(self, n):
"""
:type n: int
:rtype: int
"""
if n <= 2:
return 0
prime = [True] ... | true |
96fdbc7537410d8f968fd1a7fa53799461899eff | Python | anguyener/reu2018 | /face_processor.py | UTF-8 | 869 | 2.625 | 3 | [] | no_license | import cv2 as cv
import os
from converter import createCSV
def processFaces(img_dirs):
image_width = 48
d = int(image_width/2)
for dir in img_dirs:
for img_file in os.listdir(dir):
img = cv.imread(os.path.join(dir, img_file), 0)
top_left = img[0:d, 0:d]
cv.imwri... | true |
ae74b1bd07c4986e5effd664fee99ed87a187fe1 | Python | palmerjh/Leiter-Summer-2016 | /sim_alg_analyses/algorithm_comparison.py | UTF-8 | 2,814 | 3.203125 | 3 | [] | no_license | import numpy as np
import csv
trials = 100
n = 100
# creates random matrix from two-humped distribution skewed towards 0.0 and 1.0
def randMatrix():
#return np.matrix(np.random.rand(n,n))
m = np.matrix(np.random.normal(0.0,0.25,n**2))
for j in range(n**2):
e = m.item(j)
if e < 0:
... | true |
34ebb4419bf7deaa5d5076f6d2df0c63df9c3e33 | Python | kerrblackhole/Leetcode-Code-Backup | /spiral-matrix/spiral-matrix.py | UTF-8 | 1,061 | 2.984375 | 3 | [] | no_license | class Solution:
def spiralOrder(self, matrix: List[List[int]]) -> List[int]:
out = []
while len(matrix) > 0:
for i in range(4):
if i == 0:
for i in matrix[0]:
out.append(i)
del matrix[0]
elif ... | true |
7b5650a0ce53ab096c3c5c90bec52303fa4ac874 | Python | gourxb/RBI-ML-course | /Day 2/perceptron.py | UTF-8 | 607 | 3.03125 | 3 | [] | no_license | import numpy as np
from matplotlib import pyplot as plt
from sklearn.linear_model import Perceptron
X = np.array([
[0, 0],
[0, 1],
[1, 0],
[1, 1]
])
Y = np.array([0, 1, 1, 0])
clf = Perceptron(tol=1e-3, random_state=23, max_iter=3, penalty='l1')
clf.fit(X,Y)
print(clf.predict([[0... | true |
cfd27799c66f0e86f10cb338e897a4041d5f9e24 | Python | WladimirTavares/fup | /busca_binaria/busca_binaria/busca_binaria.py | UTF-8 | 616 | 3.59375 | 4 | [] | no_license |
def busca_binaria(vetor, n, item):
inicio = 0
fim = n - 1
contador = 0
while inicio <= fim:
meio = (inicio + fim)//2
contador = contador + 1
#print ("inicio %d, fim %d, meio %d, contador %d" % (inicio, fim, meio, contador) )
if vetor[meio] == item:
return contador
e... | true |
d6fb133ee2540ecb2f126be709a4e96c9a9d6cbf | Python | JonathanLaneMcDonald/maigo | /game.py | UTF-8 | 1,009 | 2.5625 | 3 | [] | no_license |
class GameStatus:
in_progress = 0
player_1_wins = 1
player_2_wins = 2
nobody_wins = 3
killed = 4
class TeachableGame:
@staticmethod
def get_feature_dimensions():
raise Exception("not implemented")
@staticmethod
def get_action_space():
raise Exception("not implemented")
@staticmethod
def get_name()... | true |
572e5233d8f5b1fe9ca6d60888cd2c50b86af27c | Python | flaviapb/Jogos | /Jogo Advinhação/jogoadvinhacao.py | UTF-8 | 1,236 | 4.125 | 4 | [] | no_license | "Desenvolvido por Flávia"
from random import randint
print('''=============================================================================================
\n Olá usuário, eu sou o computador, e quero interagir um pouco com você!!
Dica: Vou pensar num número de 0,10, topa advinhar??? \n
====... | true |
d2c5285e16c998f872d19210c421803ad0182b02 | Python | marblefactory/RRN_Test | /real_data_example/dataset.py | UTF-8 | 1,937 | 3.28125 | 3 | [] | no_license | import gspread
from oauth2client.service_account import ServiceAccountCredentials
from typing import List
from abc import abstractclassmethod
import numpy as np
class Dataset:
"""
Represents a collection of data and its corresponding target category.
"""
# An array containing an array of words in eac... | true |
41691242911da09a2c142a369cdceb881c9a85c6 | Python | FrozenYogurtPuff/transformers-ner | /examples/app.py | UTF-8 | 588 | 2.796875 | 3 | [] | no_license | from infer_softmax_ner import predict
from flask import Flask, request
app = Flask(__name__)
@app.route('/api/predict', methods=['POST'])
def main():
if request and request.is_json:
data = request.json
else:
data = [{'sent': 'Teacher Y asks student A to fill out a loan form and write down th... | true |
1d67549ec083cfb238151e0a2ecdc952d5fda275 | Python | pepsionly/ssserver | /application/redisclient/model/__init__.py | UTF-8 | 1,195 | 2.953125 | 3 | [] | no_license | import abc
import json
from json import JSONDecodeError
import redis
class RedisColumn:
def __init__(self, no_null=False):
self.no_null = no_null
class RedisModel(abc.ABC):
obj = {}
def __init__(self, obj):
"""
@param obj:
"""
self.obj = obj
assert (sel... | true |
7c7b710911a3cf8c7b6b8039e045f1bcf78a0fba | Python | AymunTariq/AI-Labs | /Lab2.py | UTF-8 | 2,283 | 3.375 | 3 | [] | no_license | import numpy as np
import math
class Complex():
def __init__(self, r, i):
self.Real = r
self.Imaginary = i
def magnitude(self):
mag = math.sqrt((self.Real)**2 + (self.Imaginary)**2)
return print(mag)
def orientation(self):
if(self.Imaginary ==0):
print("... | true |
c53db22ae5920adae1bb47a85b82e9d2f690158b | Python | timpark0807/self-taught-swe | /Algorithms/Leetcode/535 - Encode and Decode TinyURL.py | UTF-8 | 1,241 | 3.640625 | 4 | [] | no_license | import secrets
class Codec:
"""
long2short = {url:hash}
short2long = {hash:url}
long_url = https://leetcode.com/problems/design-tinyurl
short_url = http://tinyurl.com/4e9iAk
1. Take long url
ex: https://leetcode.com/problems/design-tinyurl
2. Create a hash, associate... | true |
2e0f3e8d7a724fe02c27a44ef4de31187bbdc30c | Python | ccrain78990s/Python-Exercise | /0330 測驗及資料庫SQL指令/0330期中小測驗/02-while5x5.py | UTF-8 | 183 | 3.859375 | 4 | [
"MIT"
] | permissive | x=1
while x<=5:
print(x)
y = 1
while y <=5:
print(y)
print(x, "*", y, "=", x * y) # 只要x等於4 y等於4 就不印
y = y + 1
x = x + 1 | true |
08fae614c3df91f91f6788b56fedd9bc160759ba | Python | benjaminhuanghuang/ben-leetcode | /1415_The_k-th_Lexicographical_String_of_All_Happy_Strings_of_Length_n/solution.py | UTF-8 | 288 | 2.859375 | 3 | [] | no_license | '''
1415. The k-th Lexicographical String of All Happy Strings of Length n
Level: Medium
https://leetcode.com/problems/the-k-th-lexicographical-string-of-all-happy-strings-of-length-n
'''
'''
Solution:
'''
class Solution:
def getHappyString(self, n: int, k: int) -> str:
| true |
83c14a5eed99cdabbbd8883b95269692589c55d5 | Python | aviaryapi/AviaryFxPython | /example/cgi-bin/AviaryFX.py | UTF-8 | 14,425 | 2.734375 | 3 | [] | no_license | '''
AviaryFX Python SDK
@version: 1.0
@author: Bruce Drummond
@contact: http://www.aviary.com
'''
import time
import hashlib
import urllib
import urllib2
from xml.dom import minidom
import os
from urllib2 import URLError
class AviaryFX(object):
'''
Class holding the methods to use the AviaryFX API - upload, ... | true |
1e3e1dbe2ea4953613620feccc09773e53ccb70a | Python | cwishart1/Ops301d2-Challenges | /Challenge6-printTree | UTF-8 | 629 | 3.765625 | 4 | [] | no_license | #!/usr/bin/env python3
# Script Name: Challenge6-printTree
# Class Name: Ops 301
# Author Name: Cody Wishart
# Date of latest revision: 3/9/21
# Purpose: Use os walk to print dir tree
# Import Library
import os
# Declaration of variables
u... | true |
a6cf0d71a3aa3467be4d8ef54f4a02730113c997 | Python | dykim822/Python | /ch04/lotto2.py | UTF-8 | 249 | 3.34375 | 3 | [] | no_license | from random import randint
lotto = set() # 중복 안되게 하기 위해 set
while len(lotto) < 6:
ran = randint(1, 45) # 1 ~ 45 사이의 정수 random 생성(1, 45도 포함)
lotto.add(ran)
print("로또번호 : ", sorted(lotto)) | true |
10447f4867d69b05d81e630c761afb0109b2d42b | Python | zzhwang/docker_file | /kafaka/project/producer.py | UTF-8 | 586 | 2.546875 | 3 | [] | no_license | from confluent_kafka import Producer
import requests
#producer配置，dict格式
p = Producer({'bootstrap.servers':'192.168.1.88:19092,192.168.1.88:29092,192.168.1.88:39092'})
#回调函数
def delivery_report(err, msg):
if err is not None:
print('Message delivery failed: {}'.format(err))
else:
print('Message ... | true |
1c63070e0089979e48457c5dbad66aaed781797e | Python | veraxrl/the-sheldon-machine | /lstm.py | UTF-8 | 1,970 | 2.875 | 3 | [
"Apache-2.0"
] | permissive | import torch
import torch.nn as nn
import torch.autograd as autograd
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from model_embeddings import ModelEmbeddings
class LSTMClassifier(nn.Module):
def __init__(self, vocab, embed_size, hidden_size, output_size,... | true |
0b3ddc8c5c7285e03b7d2a941bf2232b79bcd4e2 | Python | 17mcpc14/recommend | /4step/strip.py | UTF-8 | 525 | 2.5625 | 3 | [] | no_license | import glob
import sys
def read_raw():
f = open('quarterly-data/2005-3')
lines = f.readlines()
lines.pop(0)
f.close()
new_file = 0
for line in lines :
individual_rating = line.split(",")
userid = individual_rating[1]
movieid = individual_rating[0]
r... | true |
4bc51dcda8d452fa58996bd93d7dfb14656c8324 | Python | DarkHian/Parcial | /ejercico ex1-parametros.py | UTF-8 | 642 | 3.796875 | 4 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 23 18:58:32 2021
@author: Brahian
"""
def mostrar_mayor(v1,v2,v3,v4):
print("El valor mayor de los tres numeros es")
if v1>v2 and v1>v3:
print(v1)
else:
if v2>v3 and v2>v4:
print(v2)
else:
... | true |
51fe0e54e9f4edc9c8aab7e8ce60261b022b0d05 | Python | cgmoganedi/PythonBasics | /a_Python3.6Essentials/1.4 - data analysis with pandas/pandas-0.3.py | UTF-8 | 302 | 3.015625 | 3 | [] | no_license | import numpy as np
import pandas as pd
# working with 3D data
randItems1 = np.random.randn(4, 3)
randItems2 = np.random.randn(4, 2)
dataDict = {
'item1': pd.DataFrame(randItems1),
'item2': pd.DataFrame(randItems1)
}
dataPanel = pd.Panel(dataDict)
print(dataPanel)
print(dataPanel['item2']) | true |
fcfdfd4042093757d33993872a0890859825b000 | Python | shuw/nengo | /simulator-ui/python/nef/functions.py | UTF-8 | 2,887 | 2.5625 | 3 | [] | no_license | from ca.nengo.math.impl import AbstractFunction, PiecewiseConstantFunction
class PythonFunction(AbstractFunction):
serialVersionUID=1
def __init__(self,func,dimensions=1,time=False,index=None,use_cache=False):
AbstractFunction.__init__(self,dimensions)
PythonFunctionCache.transientFunctions[sel... | true |