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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
8a4d78753f8eff58504daca0eea1a2e98920bc2b | Python | strutt/seaveyMeasurements | /readS11s.py | UTF-8 | 8,279 | 2.609375 | 3 | [] | no_license | #!/usr/bin/env python2
from matplotlib import pyplot as plt
import math
import numpy as np
from glob import glob
"""
Simple script to read and draw the S11 data.
"""
def main():
filesV = glob('seaveyDataPalestine2014/S11s/*V.csv')
filesH = glob('seaveyDataPalestine2014/S11s/*H.csv')
filesV = orderGlobRes... | true |
38ece02182fed05201718de8f5d8e8d21bd846e6 | Python | SauloRicardo/trab_rec_paa | /trab_rec.py | UTF-8 | 7,074 | 2.671875 | 3 | [] | no_license | import networkx as nx
import copy
import random
import time
def rcsp(node_beg_f, node_end_f, qtd_max_res_f, k_paths, graph=nx.DiGraph()):
graph_aux = copy.deepcopy(graph)
possible_paths = {}
for nodes in range(1, graph_aux.number_of_nodes()+1):
possible_paths_aux = []
it = 0
for no... | true |
dd00c0462afec232f206ddf2b6d2ad20a7b877be | Python | rhuckleberry/DL_Phylo | /Recombination/recombination_networks/recombination_ResNet.py | UTF-8 | 6,875 | 2.71875 | 3 | [] | no_license | #!/usr/bin/env python3
"""Quartet tree classification
* Model: Convolutional neural network with basic residual connections
and batch normalization.
* Training data:
* 100000 pre-simulated trees using training1.
* Each epoch uses randomly sampled 2000 trees.
* The batch size is 16.
* Validation data: 20... | true |
c383ae7ff856ff3caed544b17456ef275daab90e | Python | frapa/tbcnn | /prepare_input.py | UTF-8 | 1,574 | 3.109375 | 3 | [
"MIT"
] | permissive | import os
import numpy as np
import imageio
def prepare(inDir, outFile):
"""Prepare input: convert to float with unit variance and zero mean,
extract labels and pack everything into a big numpy array to be used for training
outFile => path without extension (more than one file will be created)
"""
... | true |
ff19908937173367f24f3e2d29d18c4836f5e328 | Python | matt-drayton/fake-news-sentiment-analysis | /extract_training_data.py | UTF-8 | 1,475 | 3.03125 | 3 | [] | no_license | import json
from tqdm import tqdm
import pandas as pd
from utils import lemmatize_and_strip, preprocess_bulk, log
def load_training_data():
"""Parse the training data from its CSV file
Returns:
Tuple containing the pre-processed positive and negative tweets
"""
csv = pd.read_csv("training.160... | true |
8bd2fb8b587cfc5ed0d729d6560351d3084731ae | Python | shivamnegi1705/Competitive-Programming | /Leetcode/Weekly Contest 220/1696. Jump Game VI.py | UTF-8 | 469 | 2.78125 | 3 | [] | no_license | # Question Link:- https://leetcode.com/problems/jump-game-vi/
class Solution:
def maxResult(self, arr: List[int], k: int) -> int:
ans = deque([])
n = len(arr)
ans.append([0,arr[0]])
for i in range(1,n):
while i-ans[0][0]>k:
ans.popleft()
r = [... | true |
37db058bfac47ebd109ffa1dfaab18b22560e88d | Python | JoinNova/hackerrank | /ps_Lisa's Workbook.py | UTF-8 | 689 | 2.984375 | 3 | [] | no_license | #Lisa's Workbook
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the workbook function below.
def workbook(n, k, arr):
r=0;a=1
for _ in arr:
l=list(range(1,_+1))
chk=0
for i in range(_//k+1 if _%k>0else _//k):
#print(i,l[chk:chk+k])
... | true |
372ac5748d75cba514a7b6ef6331cc3735d5f566 | Python | yeonghoey/hew | /hew/stt.py | UTF-8 | 1,618 | 2.53125 | 3 | [
"MIT"
] | permissive | import wave
from google.cloud import speech_v1
from moviepy.editor import AudioFileClip
from hew.util import Scheme, tempfile_path
scheme = Scheme()
@scheme
def recognize_speech():
def f(source_path, language_code='en-US'):
wav_path = convert_to_wav(source_path)
client = speech_v1.SpeechClient(... | true |
8483a7fd5cb0ccde3f6ccc5c0b9d71b95e48b099 | Python | mljes/WiTS-TextPet | /screen_functions.py | UTF-8 | 1,101 | 2.890625 | 3 | [] | no_license | from symbols import SYMBOLS
from colors import FG_COL, BG_COL, RESET
#############################################
# SCREEN FIELDS
max_width = 44
max_height = 13
#############################################
def printOptions(type):
printFrame("TOP", max_width-2)
for item in SYMBOLS[type]:
if item != "NONE":
o... | true |
9587d90d986fa0f5928f10474721ee1843ec3b43 | Python | sedhha/URC2019 | /Focal_length_calculation/fl_C.py | UTF-8 | 466 | 2.546875 | 3 | [] | no_license | import cv2
import numpy as np
cam=cv2.VideoCapture(0)
while True:
k=cv2.waitKey(1)
if k & 0xFF==ord('q'):
break
_,frame=cam.read()
img=cv2.inRange(frame,np.array([0,0,0]),np.array([180,255,30]))
im2,contours,hierarchy = cv2.findContours(img, 1, 2)
for i in range(len(contour... | true |
b3e99a4141f733ec4e94ec86557d0d15e1299a89 | Python | Fixdq/python-learn | /weekday0520/client/core/src.py | UTF-8 | 428 | 2.53125 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# @Time : 18-5-20 下午3:09
# @Author : fixdq
# @File : src.py
# @Software: PyCharm
from core import admin,user
menu ="""
1.用户
2.管理员
"""
menu_dic = {
'1':user.view,
'2':admin.view
}
def run():
while True:
print(menu)
ch = input('>>>:').s... | true |
e9b6b2a66a01a6af19468e32710cc22ce7566fb3 | Python | redmage123/intermediatepython | /examples/circuitous7.py | UTF-8 | 1,237 | 4.125 | 4 | [] | no_license | ''' Circuitous, LLC -
An advanced circle analytics company
'''
from math import pi,sqrt # Added sqrt import for bbd_to_radius function. sq
class Circle:
''' An advanced circle analytics toolkit.
Note use of class variable version
'''
version = '0.3'
def __init__(self,radius):
... | true |
40eabf33e4f885fd907c8dfaec662e921c61360a | Python | popravich/hiku | /hiku/compat.py | UTF-8 | 2,616 | 2.59375 | 3 | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | import sys
import ast as _ast
import inspect
PY3 = sys.version_info[0] == 3
PY35 = sys.version_info >= (3, 5)
PY36 = sys.version_info >= (3, 6)
def with_metaclass(meta, *bases):
"""Create a base class with a metaclass."""
# This requires a bit of explanation: the basic idea is to make a dummy
# metaclas... | true |
53b43a41321f5039785df5b05d9e38442d8b7a0e | Python | lyqtiffany/learngit | /caiNiao/sanShiSiShi/siShiQiExchange.py | UTF-8 | 182 | 3.59375 | 4 | [] | no_license | def exchange(a, b):
a, b = b, a
return a, b
if __name__ == '__main__':
x = 12
y = 65
x, y = exchange(x, y)
print('x value is %d'%x, 'y value change to %d'%y) | true |
33ae7c9f65c1462e20cf31b50507a4e2a51c791e | Python | webclinic017/fa-absa-py3 | /Extensions/Advanced Corporate Actions/FPythonCode/FCorpActionPayoutViewer.py | UTF-8 | 2,739 | 2.546875 | 3 | [] | no_license | """ Compiled: 2020-09-18 10:38:49 """
#__src_file__ = "extensions/advanced_corporate_actions/./etc/FCorpActionPayoutViewer.py"
import acm
import FUxCore
def SelectFirstItem(objList, itemList):
if objList:
firstItem = objList[0]
itemList.SetData(firstItem)
def RemoveItem(objList, itemList, item):... | true |
9e6008d1e9c926ccb5f9d8c85af83a9bfb7bce3b | Python | Timpryor91/tims_shoes | /classes/event_class.py | UTF-8 | 19,776 | 2.734375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
@author: timpr
"""
from datetime import datetime, timedelta
import random as rand
from classes.customer_class import Customer
class EventsTable(object):
"""
An event table class, corresponding to a MySQL table used to store events on Tim's Shoes website
"""
def __init_... | true |
095a5cec3d6dc8109af29d10ebc708b4f149fdd2 | Python | Grace-JingXiao/AVEC_2017_DDS_CNN_Research | /Pretreatment/Text/Step3_Digital.py | UTF-8 | 1,623 | 2.5625 | 3 | [] | no_license | import os
import numpy
if __name__ == '__main__':
loadpath = 'D:/PythonProjects_Data/AVEC2017_Data/Text_Step1_RawText/'
savepath = 'D:/PythonProjects_Data/AVEC2017_Data/Text_Step3_Digital/'
dictionaryData = numpy.genfromtxt(fname='Dictionary.csv', dtype=str, delimiter=',')
dictionary = {}
for samp... | true |
30364047be721bc5c400ff68515627e9c0a142cd | Python | melexis/xunit2rst | /tests/prefix_test.py | UTF-8 | 6,000 | 2.671875 | 3 | [
"Apache-2.0"
] | permissive | #!/usr/bin/env python3
''' Test suite for functions that set the prefix and prefix_set variables '''
import unittest
from pathlib import Path
from mlx.xunit2rst import build_prefix_and_set, parse_xunit_root, verify_prefix_set, ITEST, UTEST, QTEST
TEST_IN_DIR = Path(__file__).parent / 'test_in'
class TestPrefix(unit... | true |
a1b20a6b219678546700b96074b57f6c623cebe9 | Python | josiah-wolf-oberholtzer/tloen | /tloen/textui/__main__.py | UTF-8 | 511 | 2.71875 | 3 | [
"MIT"
] | permissive | import urwid
def on_a_press(*args, **kwargs):
list_walker.append(button_row)
def on_b_press(*args, **kwargs):
list_walker[2:] = []
button_row = urwid.LineBox(
urwid.Columns(
[
urwid.Button("add more", on_press=on_a_press),
urwid.Button("remove one", on_press=on_b_press)... | true |
ec0710fb25faee72d6b18bb03b5ef720e71540fe | Python | TINY-KE/floorplan-MapGeneralization | /misc/plot_graph_with_labels.py | UTF-8 | 1,468 | 2.765625 | 3 | [] | no_license | import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib.figure import figaspect
import matplotlib
matplotlib.use('TKAgg')
import os
import argparse
#GRAPH_PATH = r"C:\Users\Chrips\Aalborg Universitet\Frederik Myrup Thiesson - data\data_... | true |
83b8558b6e1c5f86fa9bb857061d8cb34cc3752f | Python | jankeromnes/Python-Calc | /algeb/AbsVal.py | UTF-8 | 1,284 | 3.078125 | 3 | [
"MIT"
] | permissive | import re
def absVal():
main = {
}
main1 = {
}
while True:
def r():
print('desired syntax: |(equ here)|')
str1 = input('what is the equ?: ')
equ = re.findall(r'\|.*\|', str1)
equp2 = re.findall(r'.*', str1)
str(equp2)
#this takes the syntax of the equasion ie. |1 + 1| so thay it can ... | true |
58f1c8e1ebbe8656f2fdaa4518f2746f523a0625 | Python | cassebas/run-co-runners | /experiment/notebook_mälardalen-bsort-pi3.py | UTF-8 | 4,985 | 2.6875 | 3 | [] | no_license | # ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.6.0
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
import pandas as pd
impor... | true |
a8aaf450fe18797fc1787c3df8f08011167f1caa | Python | durden/spygit | /spygitapp/pep8.py | UTF-8 | 2,884 | 2.71875 | 3 | [] | no_license | from django.shortcuts import render_to_response
import os
import string
import tempfile
from fnmatch import fnmatch
from models import Error, Run, File, RunError, Line
def add_file_to_set(myset, dirname, fnames):
"""Used with os.path.walk to make a list of all files"""
for filename in fnames:
name ... | true |
4434de27b97c07a22797f04745a9dd747ebd7942 | Python | ProjectLSD/Noise-Reduction-Playground | /ops/mixer.py | UTF-8 | 702 | 2.765625 | 3 | [] | no_license | from pydub import AudioSegment
import random
def generate_rand_frequency():
audio = AudioSegment.from_wav("basictone.wav") # import in the file with a tone of 440 Hz
octaves = random.randint(-30, 30) / 10 #generates a random number from -3 to 3
new_sample_rate = int(audio.frame_rate * (2.0 ** octaves))
... | true |
19cc618422c842ef13cab81b4504229ab99bcbee | Python | lzx3x3/Algorithm-CSE6140 | /CSE6140_HW4/Hongsup_OH_CSE6140_programming/Plot_divide_dynamic.py | UTF-8 | 621 | 3.390625 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
#the number of k
k = [10,1000,2000,3000,4000,5000,6000,7000,8000,9000,10000]
#Divide and Conquer
dc = [0.168,43.55,68.7,103.64,132,159,200,224,269.1,275.8,328]
#Dynamic Programming
dp = [0.048,10.554,18.889,29.50,32.329,36.6,38.2,46.3,52.4,54.6,71]
#Plot Gr... | true |
18f8757d2b722e4870ee9241c7017434e82df5f4 | Python | jvanvari/LeetCode | /python-solutions/trees/BFS/994_rotting_oranges.py | UTF-8 | 1,357 | 3.515625 | 4 | [] | no_license | from typing import List
# problem of graph traversal and zigzag order traversal where you keep track of levels
class Solution:
def orangesRotting(self, grid: List[List[int]]) -> int:
rows = len(grid)
cols = len(grid[0])
queue = []
mins = 0 # levels
for i in range(rows)... | true |
7c72cfbacf81d4709a42760afb949fb1d13d0958 | Python | Jagrmi-C/jagrmitest | /coursera_/queue4.py | UTF-8 | 400 | 3.21875 | 3 | [
"MIT"
] | permissive | from queue import Queue
from threading import Thread
def worker(q, n):
while True:
item = q.get()
if item is None:
break
print("process data:", n, item)
q = Queue(5)
th1 = Thread(target=worker, args=(q, 1))
th2 = Thread(target=worker, args=(q, 2))
th1.start(); th2.start()
fo... | true |
af042215ab562f2d98bab8e8ffbc617607601c10 | Python | alainaahuja/face_recognition | /face_matching.py | UTF-8 | 2,322 | 3.15625 | 3 | [] | no_license | #importing desired modules/libraries
from tkinter import *
from tkinter import filedialog
import face_recognition
#function command for first variable; gives path for first choice
def browsingPIC1():
fileVarPIC1=filedialog.askopenfilename( filetypes=(("Alaina's stuff",".gif"),("All files","*.*")))
global enc... | true |
f42f197213e57c8ee9f802598135609a28e91df4 | Python | Shikhar0907/Algo-and-data-structure-questions | /Amazon_interview/amazon practice/anagrm maximum subset.py | UTF-8 | 431 | 3.421875 | 3 | [] | no_license | def anagram(string):
max_num = 0
string = string.split()
for i in range(len(string)):
string[i] = ''.join(sorted(string[i]))
temp = {}
for item in string:
if item not in temp:
temp[item] = 1
else:
temp[item] += 1
print(max(temp.items(), key = lamb... | true |
082d4e850468c3d5ea20431a1b59c062c6bbd81c | Python | AprajitaChhawi/365DaysOfCode.MAY | /Day 24 strong number.py | UTF-8 | 679 | 3.546875 | 4 | [] | no_license | #User function Template for python3
class Solution:
def fact(self,n):
fac=1
for i in range(2,n+1):
fac=fac*i
return fac
def isStrong(self, N):
s=0
num=N
while(num!=0):
temp=num%10;
s=s+ob.fact(temp)
num=int(num/10)
... | true |
bef3d1abd584e898424c12ea699eca28bc807f0c | Python | robinhouston/maze-experiments | /pylib-mazer/mazer/generate.py | UTF-8 | 2,103 | 3.671875 | 4 | [] | no_license | """
Maze generation algorithms.
"""
from mazer.maze import (Maze, DIRECTIONS, RELATIVE_DIRECTIONS, N, E, S, W, random_direction)
import random
def recursive_backtracking(maze):
"""Complete the maze using the recursive backtracking algorithm.
"""
directions = [ d for d in RELATIVE_DIRECTIONS ]
random.shuffle(d... | true |
c171bf574918a08a6ce6089fe0e60f9aeb36c179 | Python | akingyin1987/pytest | /mypy14.py | UTF-8 | 833 | 3.8125 | 4 | [] | no_license | # 工厂模式
class CarFactory:
def create_car(self, brand):
if brand == "奔驰":
return Benz()
elif brand == "宝马":
return BMW()
elif brand == "比亚迪":
return BYD()
else:
return "无品牌无法创建"
class Benz:
pass
class BMW:
pass
class BYD... | true |
4f0e8029dfb7ac16369555191937bfe22633404f | Python | BorisDundakov/Python---Fundamentals | /07. Dictionaries - Lab/keys itteration.py | UTF-8 | 639 | 3.859375 | 4 | [] | no_license | # # # squares = {1: 1, 2: 4, 3: 9}
# # #
# # # for each_key in squares.keys():
# # # print(each_key, end=" ")
# #
# #
# # squares = {1: "Ferrari", 2: "Lamborghini", 3: "McLaren"}
# #
# # for (key, value) in squares.items():
# # print(f"Key: {key}, Value: {value}")
#
#
# # my_dict = {1: "Hello", 2: "World"}
# #
... | true |
290e44b7c21941a8aa1f07e4e21270cec42750ce | Python | yavoratanassov/softuni_python_fundamentals | /11_lists_basics_excercices/invert_values.py | UTF-8 | 174 | 3.453125 | 3 | [] | no_license | numbers = input().split()
opposite_numbers = []
for n in range(len(numbers)):
number = int(numbers[n]) * -1
opposite_numbers.append(number)
print(opposite_numbers) | true |
a770f07b5d65290639f203c9dd8ab69b7ee2495f | Python | yishuen/python-flask-app-HTML-templates-lab-nyc-career-ds-102218 | /test/index_test.py | UTF-8 | 2,298 | 2.6875 | 3 | [] | no_license | import unittest, sys
sys.path.insert(0, '..')
from app import app
class HTMLTemplateTestCase(unittest.TestCase):
testy = app.test_client()
def test_index_status_code(self):
response = self.testy.get('/')
self.assertEqual(response.status_code, 200)
def test_index_html(self):
respon... | true |
5e42cdd6de7c95d8b0690093fa841b7243c31f26 | Python | Annajose23/pythonLearning | /mostFrequent.py | UTF-8 | 326 | 3.421875 | 3 | [] | no_license | def mostFrequent(arr):
arr_freq = {}
for item in arr:
if item in arr_freq:
arr_freq[item] = arr_freq[item] + 1
else:
arr_freq[item] = 1
arr_sorted = sorted(arr_freq.items(), key=lambda kv: kv[1], reverse=True)
print(arr_sorted[0][0])
mostFrequent([4,1,3,3,2,1... | true |
685e9e377faccb765bd47ca768790ca8d6dce019 | Python | MivlaM/AIVirtualAssistant | /Mivbot.py | UTF-8 | 9,949 | 2.984375 | 3 | [] | no_license |
import pyttsx3 # pip install pyttsx3
import datetime
import speech_recognition as sr #Pip install speech recognition
import wikipedia #pip install wikipedia
import webbrowser as wb
import psutil #pip install psutil
import pyjokes #pip install pyjokes
import os
import pyautogui #pip install pyautogui
import random
imp... | true |
0524578214dd63e46f6496fff74c5b6050142c79 | Python | geekhub-python/akvarium-2-0-valiknet18 | /aquarium_test.py | UTF-8 | 2,603 | 2.703125 | 3 | [] | no_license | import unittest
import occupants
from random import choice
from aquarium import Aquarium, AquariumFilter, FishCreator
class TestAquarium(unittest.TestCase):
OCCUPANTS_MAX_COUNT = 200
OCCUPANTS_MIN_COUNT = 20
def setUp(self):
self.aquarium = Aquarium()
def test_occupants_length(self):
... | true |
9a8fe880ff7121eb5078b1bfa24f7f6d594677db | Python | ehsanik/dogTorch | /models/resnet18_image2imu.py | UTF-8 | 3,540 | 2.609375 | 3 | [
"MIT"
] | permissive | """
=================
This model is a non-recurrent model for Inferring the action of the dog using a Resnet-18 network. Given two images, infer the imu changes corresponding to those two frames.
=================
"""
import torch
import torch.nn as nn
import pdb
from torchvision.models import resnet18 as torchvisio... | true |
c946ca5c86aa1be91d1ba845d0fd4c9b27da199f | Python | Hdwig/Math | /Lesson_3_1.py | UTF-8 | 215 | 3.171875 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
x = np.arange(-10, 10)
ys = 5 * x + 3
ym = 7 * x + 4
yl = 0 * x + 7
plt.xlabel("x")
plt.ylabel("y")
plt.grid(True)
plt.plot(x, ys)
plt.plot(x, ym)
plt.plot(x, yl)
| true |
15eeb2aa75d6332fa2dd280a8fa84718d15667e3 | Python | Ansore/super_resolution | /images_to_tfrecord.py | UTF-8 | 1,451 | 2.59375 | 3 | [
"MIT"
] | permissive | from configs import *
import os
import numpy as np
from PIL import Image
import tensorflow as tf
def scan_file(path):
result = []
for filename in os.listdir(path):
if filename.endswith('.png'):
filename = path + '/' + filename
result.append(filename)
return result
def image... | true |
edf7256452ef397cd8f46fccabab0e04182eed80 | Python | merissab44/superHero | /ability.py | UTF-8 | 330 | 3.578125 | 4 | [] | no_license | import random
class Ability:
def __init__(self, name, max_damage):
# initialized values that will be passed when
# we call the class
self.name = name
self.max_damage = max_damage
def attack(self):
random_value = random.randint(0, int(self.max_damage))
return ran... | true |
06e89ce84ac1b87267f827031f050104b8497e32 | Python | robertdavidwest/forexpricecomparison | /app/db_create.py | UTF-8 | 877 | 2.828125 | 3 | [] | no_license | # db_create.py
from datetime import datetime
from views import db
from models import FXQuotes
if __name__ == '__main__':
# create the database and the db table
db.create_all()
# add one row of sample data - this is actual data
quote_time = datetime(year=2015, month=9, day=30,
... | true |
92244fdcac2ac00ce7f02270a6548ee6344d130c | Python | edimaudo/Python-projects | /visualization/scatterplot.py | UTF-8 | 445 | 3.390625 | 3 | [] | no_license | import matplotlib.pyplot as plt
X = [590,540,740,130,810,300,320,230,470,620,770,250]
Y = [32,36,39,52,61,72,77,75,68,57,48,48]
#scatter plot
plt.scatter(X, Y, s=60, c='red', marker='^')
#change axes ranges
plt.xlim(0,1000)
plt.ylim(0,100)
#add title
plt.title('Relationship Between Temperature and Iced Coffee Sales... | true |
a21574955b9b8042dfb5d6a3ae95b982880acfc6 | Python | isseikz/Multicopter | /sub_system/logger.py | UTF-8 | 3,440 | 2.609375 | 3 | [
"MIT"
] | permissive | """Logger"""
import numpy as np
import matplotlib.pyplot as plt
import math
class Logger(object):
"""docstring for Logger."""
def __init__(self):
super(Logger, self).__init__()
self.log_tim = []
self.log_pos = []
self.log_vel = []
self.log_acc = []
self.log_ang... | true |
0438493823e3ec18b7afc63351293e25a25349b6 | Python | priyalorha/jesse | /jesse/models/FuturesExchange.py | UTF-8 | 7,369 | 2.6875 | 3 | [
"MIT"
] | permissive | import jesse.helpers as jh
import jesse.services.logger as logger
from jesse.exceptions import NegativeBalance, InsufficientMargin
from jesse.models import Order
from jesse.enums import sides, order_types
from jesse.libs import DynamicNumpyArray
import numpy as np
from jesse.services import selectors
from .Exchange imp... | true |
53a878a603e3afb0010cab1057849b1fb2f490dc | Python | DarthGecko/orthometer | /intronitator.py | UTF-8 | 11,832 | 2.609375 | 3 | [] | no_license | # Nick Weiner 2017
# introninator.py
# Getting introns from FASTA files made by phytozomedler
import re
from Bio import SeqIO
from Bio.Seq import Seq
from Bio import motifs
don_len = 5
acc_len = 8
# Things to work out:
# How are we storing the data on the introns? In RAM or ROM?
# Make a FASTA file of introns?
# Set... | true |
2c557903a396e2830cc1f890eb008ed2045ed46d | Python | vijaykanth1729/FLASK-REST-FRAMEWORK | /app2.py | UTF-8 | 2,240 | 2.59375 | 3 | [] | no_license | from flask import Flask, jsonify, request
from flask_restful import Resource,Api
from flask_marshmallow import Marshmallow
from flask_sqlalchemy import SQLAlchemy
import os
import datetime
basedir = os.path.abspath(os.path.dirname(__file__))
app = Flask(__name__)
api = Api(app)
app.config['SQLALCHEMY_DATABASE_URI'] =... | true |
809860db3fb709c0e3f5f875f384de5ff9c8bd17 | Python | daodao10/rq-bak | /dao_adjust_position_impl.py | UTF-8 | 5,145 | 2.546875 | 3 | [] | no_license | '''=============调仓制器============='''
from dao_strategy_base import *
import dao_strategy_util as dutil
'''---------------再平衡规则--------------'''
class Rebalance(Adjust_position):
def __init__(self, params):
self.max_position_count = params.get('max_position_count', 3)
self.max_weight_per_position = ... | true |
4b9d3f8a00e359d2ce669576ddabe7bad530f4da | Python | minuso/leetcode | /0543/diameterOfBinaryTree.py | UTF-8 | 364 | 3.125 | 3 | [] | no_license | def diameterOfBinaryTree(self, root: TreeNode) -> int:
self.res = 0
def height(root):
if not root: return 0 # height of each leaf is 1
hl, hr = height(root.left), height(root.right)
self.res = max(self.res, hl + hr) # maintain longest length
return max(hl, hr) + 1
... | true |
8117da39ffa71af50f87b0617a43ae22db72ad0c | Python | mukul1729/Settings_Preferences | /python/Euler/euler2.py | UTF-8 | 215 | 3.375 | 3 | [] | no_license | first = 1
second = 1
third = 0
sum = 0
for a in range(100):
third = first + second
if third % 2 == 0 and sum <= 4000000:
sum = sum + third
first = second
second = third
print(sum)
| true |
0395a187108233cf9af5c410e0a4d056c323b3c5 | Python | suguke/gait-control-direct-id-paper | /src/example_mean_gain_plots.py | UTF-8 | 3,044 | 2.578125 | 3 | [
"CC-BY-4.0",
"CC0-1.0"
] | permissive | #!/usr/bin/env python
"""This script plots the mean of the identified joint isolated gains from
all valid trials. The gains must be precomputed. It currently does not
include trials from Subject 9 because it has odd ankle joint torques."""
# builtin
import os
# external
import numpy as np
from scipy.constants import... | true |
c8bb2555489806df3f9c710abc4d05af7d4d3b9e | Python | vwarner1411/openrvdas-1 | /logger/readers/network_reader.py | UTF-8 | 2,823 | 2.65625 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
import logging
import socket
import sys
sys.path.append('.')
from logger.utils.formats import Text
from logger.readers.reader import Reader
BUFFER_SIZE = 4096
################################################################################
# Read to the specified file. If filename is empty, ... | true |
5cbd645273a1d8e5be4fe983267a9c6ee60bc209 | Python | H-Cong/LeetCode | /152_MaximumProductSubarray/152_MaximumProductSubarray_2.py | UTF-8 | 1,168 | 3.421875 | 3 | [] | no_license | class Solution:
def maxProduct(self, nums: List[int]) -> int:
if not nums: return None
curr_max = nums[0]
curr_min = nums[0]
ans = curr_max
for i in range(1, len(nums)):
temp_max = max(nums[i], nums[i]*curr_max, nums[i]*curr_min)
curr_min = mi... | true |
a8a2093fee616ea5a5fc8629de0a5eaf2af80898 | Python | SeveralCamper/USE-2020-2021 | /16 задание/РекурсФункцСТекст_011.py | UTF-8 | 459 | 3.984375 | 4 | [] | no_license | # Задание 16 № 11347
# Ниже на пяти языках программирования записан рекурсивный алгоритм F.
# Чему равна сумма напечатанных на экране чисел при выполнении вызова F(10)?
count = 0
def F(n):
if n > 2:
global count
count += n
print(n)
F(n - 3)
F(n - 4)
print(F(10), count)
# ... | true |
19abe0a590230023d4e7ad61587796d573f023f9 | Python | lufeng0614/leetcode | /leetcode-349.py | UTF-8 | 773 | 3.8125 | 4 | [] | no_license |
给定两个数组，编写一个函数来计算它们的交集。
示例 1:
输入: nums1 = [1,2,2,1], nums2 = [2,2]
输出: [2,2]
示例 2:
输入: nums1 = [4,9,5], nums2 = [9,4,9,8,4]
输出: [4,9]
说明：
输出结果中每个元素出现的次数，应与元素在两个数组中出现的次数一致。
我们可以不考虑输出结果的顺序。
========================================================================
class Solution(object):
def intersect(self, n... | true |
3ef7a9af6293aec84092afa67ff607757ccf3c67 | Python | jdenoc/meta-search | /cgi/engine_searcher.py | UTF-8 | 3,253 | 3.46875 | 3 | [] | no_license | #!/usr/bin/python
##
## Filename: engine_searcher.py
## Version: 6.5.4
## This file opens search engine webpages and takes the links from them.
## This file contains functions that:
## opens sites, retrieves site code, closes site & then returns site code
## recieves the strings found in the sites & then trims them ... | true |
4330303575a8508180fa48e049ae71d9ca1ac46e | Python | michaelb/point-clustering | /generation_test.py | UTF-8 | 1,432 | 3.03125 | 3 | [] | no_license | #!/usr/bin/env python3
"""
Module de création de fichiers d'ensembles de test
"""
from math import floor, sqrt
from random import random
import numpy as np
def generation_fichier(nb_points, distance_liaison, chemin="qg2 > gq1.pts"):
with open(chemin, "w") as fichier:
fichier.write(str(distance_liaison) + ... | true |
2cf0d370c351d4e2c1831fb6e05d3cd582b070b9 | Python | gordian-biotechnology/arboreto | /scripts/run_diff_seeds_dream5_standardized.py | UTF-8 | 2,918 | 2.625 | 3 | [
"BSD-3-Clause"
] | permissive | """
Python script for running Arboreto multiple times on the DREAM5 dataset,
initialized with a different random seed for each run.
The objective is to assess the stability of the inference quality of GRNBoost2
compared with GENIE3/Arboreto and the GENIE3 results as reported in the Dream5 paper.
"""
import pandas as ... | true |
7cf04d1c5245584073def0da55639f4bb8ed396d | Python | alex-rt/DistributedSystem | /processing.py | UTF-8 | 2,244 | 2.5625 | 3 | [] | no_license | #!/usr/bin/env python
# coding: utf-8
# In[1]:
#MASSIVE DATA MANAGEMENT
#PARCIAL 2
#ALEJANDRO RODRIGUEZ TRILLO
#ANDRESS ARANA BEJAR
import pymongo
import numpy as np
import pandas as pd
myclient = pymongo.MongoClient("mongodb://localhost:27017/")
mydb = myclient["Parcial1"]
mycol = mydb["alejandro_rodriguez_co... | true |
af6fcee9518d537c001aeae5bd62f9fa7c240130 | Python | mohmah7/osajana_kehitaminen-korkeakoulu | /harij08/L08T05.py | UTF-8 | 699 | 3.90625 | 4 | [] | no_license | first_number = input("Please input number :")
if first_number > 0:
first_number = first_number
else:
first_number = 0;
second_number = input("Please input number :")
if second_number > 0:
second_number = second_number
else:
second_number =0
third_number = input("Please input number :")
if third_number > 0:
thi... | true |
06308053fe2bdf77f62ec4cda964e54e8b668a0a | Python | CCedricYoung/bitesofpy | /333/test_metropolis_hastings.py | UTF-8 | 2,020 | 3.234375 | 3 | [] | no_license | import math
import numpy as np
import pytest
from metropolis_hastings import metropolis_hastings
np.random.seed(42)
def norm_dist(x, mean, std):
"""Gaussian normal probability distribution."""
return np.exp(-0.5 * (x - mean) ** 2 / std ** 2)
def standard_norm_dist(x):
"""Gaussian norm... | true |
4fd4f9708b5e36d88a486f99d728710a26307ed4 | Python | ripsj/logic | /DeterminadorDireccion.py | UTF-8 | 811 | 4.03125 | 4 | [] | no_license |
def esPar(num):
if (num % 2) == 0:
return True
else:
return False
T = int(input("How many matrices would you like to test?"))
arregloPares = []
for x in range(T):
arregloPares.append(input("Enter 'N' and 'M' values for matrix number " + str(x+1) + ", spaced by a whitespace: "))
f... | true |
87155d69da09ab877704089ee80120d5858ed152 | Python | SamLR/MuSIC5_offline_analysis | /MuSIC5_offline_analysis/scripts/rates_from_count.py | WINDOWS-1252 | 4,396 | 2.671875 | 3 | [] | no_license | #!/usr/bin/python
# -*- coding: utf-8 -*-
"""
Calculate simulated muon rates based on truth count of number of muons
of each type.
"""
from ValueWithError import ValueWithError
from root_utilities import make_canvas
from ROOT import TGraphErrors
from array import array
from time import sleep
# g4bl = True
g4bl = F... | true |
974a98368a93e7d04ced6cf06c706dcdeda7d442 | Python | GuangyuanZhao/ee239as | /packages/geomag/emm.py | UTF-8 | 7,882 | 2.65625 | 3 | [] | no_license | # encoding: utf-8
# module geomag.emm
# from C:\Users\qinli\AppData\Local\Programs\Python\Python36\lib\site-packages\geomag\emm.cp36-win_amd64.pyd
# by generator 1.145
# no doc
# imports
import builtins as __builtins__ # <module 'builtins' (built-in)>
import ntpath as path # C:\Users\qinli\AppData\Local\Programs\Pytho... | true |
09404fe514830fd880f6eecd28b8c272e893d8d7 | Python | zchauvin/tictactoe | /tester.py | UTF-8 | 3,314 | 3.75 | 4 | [] | no_license | from Computer import Computer
from Board import Board
import unittest
from typing import List
N = 3
class TestComputer(unittest.TestCase):
def test_x_computer_never_loses(self):
board = Board(N)
c = Computer('x', 'o')
self.helper(board, c, True)
def test_o_computer_never_loses(self):... | true |
9203cd2ba10e9780887779818eb9b5e0f3b146e3 | Python | mdilauro39/ifdytn210 | /practicaIIII/funcionmax.py | UTF-8 | 218 | 3.859375 | 4 | [] | no_license | n1= int(raw_input("ingrese primer numero"))
n2= int(raw_input("ingrese segundo numero"))
def numgrande(a,b):
if a > b:
return a
if b > a:
return b
if a == b:
return "a y b iguales"
print numgrande(n1,n2,n3)
| true |
8fa525cfee21cae9a8d89c94633008a249954b51 | Python | jeffdeng1314/CS16x | /cs160_series/python_cs1/integral_calculator.py | UTF-8 | 3,289 | 4.21875 | 4 | [] | no_license | import math
def f1(x):
return 5 * math.pow(x, 4) + 3 * math.pow(x, 3) - 10 * x + 2
def f2(x):
return math.pow(x, 2) - 10
def f3(x):
return 40 * x + 5
def f4(x):
return math.pow(x, 3)
def f5(x):
return 20 * math.pow(x, 2) + 10 * x - 2
"""
ft: function type
mt: method type: 1 - rectangle, 2 - trapezoid, 3 ... | true |
466cca9ddd2ec1746e4a00a0ce59f0ce24d007b7 | Python | JiwoonKim/Book-review-website | /application.py | UTF-8 | 8,683 | 2.890625 | 3 | [] | no_license | import os
from flask import Flask, session, render_template, request, jsonify
from flask_session import Session
from sqlalchemy import create_engine
from sqlalchemy.orm import scoped_session, sessionmaker
from helpers import *
import requests
app = Flask(__name__)
# Check for environment variable
if not os.getenv(... | true |
5dbf7e9a9610d3299b8b3e43d1bd10ab60d93d71 | Python | DobrovolskayaValentinaAI182/homework | /first.py | UTF-8 | 1,856 | 3.578125 | 4 | [] | no_license | from random import randrange
import time
from datetime import datetime
#buble
my_list = [ randrange(0, 15) for i in range(10) ]
max_list = len( my_list )
i = 0
while i < max_list:
j = 0
while j < max_list-i-1:
if my_list[ j ] > my_list[ j + 1 ]:
my_list[ j ], my_list[ j + 1] = my_list[... | true |
9c495135ab9a2398c6a1e14de03486c6e9b2f260 | Python | Justin-mario/python_excercises | /Self_Check_Excercises/wind_chill_temperature.py | UTF-8 | 329 | 3.71875 | 4 | [] | no_license |
temperature = eval(input("Input Temperature Between -58F and 41f: "))
velocity_of_wind = eval(input("Input velocity: "))
wind_chill_temperature = 35.74 + (0.6215 * temperature) - 35.75 * (velocity_of_wind ** 0.16) \
+ 0.4275 * temperature * (velocity_of_wind ** 0.16)
print(f'{wind_chill_temper... | true |
c75b50b21770c8d46f850ca03ad9ed775a8029b8 | Python | pntgoswami18/tutBotKhamen | /bot.py | UTF-8 | 7,203 | 3.09375 | 3 | [] | no_license | import os
import discord
import random
from dotenv import load_dotenv
from discord.ext import commands
from discord import DMChannel
# pull values frm .env file
load_dotenv()
TOKEN = os.getenv('DISCORD_TOKEN')
GUILD = os.getenv('DISCORD_GUILD')
client = discord.Client()
bot = commands.Bot(command_prefix='!')
@clie... | true |
0d54c25260e20edad7bc33f085b00fd7dfc21684 | Python | toxicthunder69/Iteration | /Starter Exercises/ContinuousMessage.py | UTF-8 | 189 | 3.546875 | 4 | [] | no_license | #Joseph Everden
#09/10/14
#Continuous message
num = 0
while num >= 20 or num <= 10:
num = int(input("Enter a number between 10 and 20: "))
print("You entered {0} which is valid!".format(num))
| true |
190004cd644c6757c46c3ec1918c5d9206ac80f2 | Python | Cristopher-12/AplicacionesWebOrientadasaServicios | /google_books/index.py | UTF-8 | 1,484 | 2.8125 | 3 | [] | no_license | import web
import requests
import json
render = web.template.render("google_books/")
class Index():
def GET(self):
datos = None
return render.index(datos)
def POST(self):
form = web.input()
book_name = form.book_name
result = requests.get("https://www.googleapis.com/books/v1/volumes?q="+boo... | true |
89ffcc60bae2a7717793a4fd72ca281e9bd25d6d | Python | alfir777/skillbox_course_python-basic | /lesson_005/painting/wall.py | UTF-8 | 1,957 | 3.328125 | 3 | [] | no_license | # -*- coding: utf-8 -*-
# (цикл for)
import time
import simple_draw as sd
def wall(coord_x=300, coord_y=100, height=201):
x = 30
y = 15
step_y = coord_y
for _ in range(0, height, y):
step_x = coord_x
if (step_y / 5) % 2:
for _ in range(0, height, x):
poin... | true |
478f4e3f7fb3ce9e04ab0b0160b699e39bb649d7 | Python | serenafr/linklinkgo | /boards.py | UTF-8 | 1,870 | 3.53125 | 4 | [] | no_license | import random
class Board(object):
def __init__(self, kinds, pairsPerKind, interval):
self.interval = interval
self.kinds = kinds
self.pairsPerKind = pairsPerKind
self.tiles = None
self.GenTiles()
def GenTiles(self):
'generate a new game'
self.tiles = []
for i in xrange(self.kinds)... | true |
34424b93f79daebbae1f47d6079aea120a69e562 | Python | yangmyongho/3_Python | /chap03_DataStr_exams/exam04.py | UTF-8 | 602 | 3.78125 | 4 | [] | no_license | '''
step05 문제
문) 다음 movie 객체를 대상으로 평점 8이상인 영화 제목과 누적관객수를 출력하시오.
<출력 결과>
영화제목 : 광해
영화제목 : 관상
누적 관객수 = 2,100
'''
movie = {'광해' : [9.24, 1200], '공작' : [7.86, 500], '관상' : [8.01, 900]}
# 내가한 1
for i in movie :
print(i, end=' : ')
print(movie[i])
# 내가한 2
su = 0
for i in movie.keys() :
... | true |
143ef18ac271b8ba2533fae646aabfd7f599674d | Python | CLeDoPbIT/telegram_bot_face_recognition | /project/bot_self_check.py | UTF-8 | 1,377 | 2.609375 | 3 | [] | no_license | import apiai, json
import photo_proc
txt_request = apiai.ApiAI('733a0aad1eb0479c88c862e1ec1a26e7').text_request() # Токен API к Dialogflow
txt_request.lang = 'ru' # На каком языке будет послан запрос
txt_request.session_id = 'Comparator3000' # ID Сессии диалога (нужно, чтобы потом учить бота)
txt_request.query = 'Ты з... | true |
4e9cac388fa214eb1856275e9e02d0540e12280e | Python | petterin/amaer | /amaer.py | UTF-8 | 4,162 | 3.296875 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python
# AMAer ("Adjacency Matrix-er") turns a CSV list into an adjacency matrix.
# Usage instructions: python amaer.py --help
#
# https://github.com/petterin/amaer
#
# Copyright (c) 2013 Petteri Noponen (Licensed under the MIT License.)
import argparse
import csv
import os
import sys
import time
def ... | true |
a3c1401a7cb47247fd98f91f1c0e683a7c982760 | Python | Serasar/leverx_homework_2 | /task_2.py | UTF-8 | 2,679 | 3.015625 | 3 | [] | no_license | class Version:
def __init__(self, version):
self.version = version
self.__version_int = 0
self.STRING_WORTH = {"a": 1, "b": 2, "alpha": -2, "beta": -1, "r": -5}
self.MAJOR_WORTH = 100
self.MINOR_WORTH = 10
self.PATCH_WORTH = 0.1
self.version_to_int()
def ... | true |
763b0b494a5bcf723a05b3bb7e0110ded4535132 | Python | Aasthaengg/IBMdataset | /Python_codes/p03816/s466111035.py | UTF-8 | 99 | 2.71875 | 3 | [] | no_license | N = input()
A = map(int, raw_input().split())
ans = len(set(A))
if ans%2==0:
ans -= 1
print ans
| true |
8937656571224085957c9f315d2d269865b0d300 | Python | MuqadirHussain/python-instagram-bot | /Bot.py | UTF-8 | 2,191 | 2.625 | 3 | [] | no_license | from selenium import webdriver
import os
import csv
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver.chrome.options import Options
def read_data(path):
try:
if (os.path.exists(path)):
tagsArray=[]
with open(path,'r') as csvfile:
... | true |
557fcfb2b2fe40732519990f2f59cfdaf8e24177 | Python | RunTimeError2/Hand-on-ML-with-sklearn-and-TF | /ex02_chap3/multi_output.py | UTF-8 | 2,178 | 3.03125 | 3 | [] | no_license | import numpy as np
from sklearn.datasets import fetch_mldata
import matplotlib
import matplotlib.pyplot as plt
from sklearn.linear_model import SGDClassifier
from sklearn.model_selection import StratifiedKFold
from sklearn.base import clone
from sklearn.model_selection import cross_val_score, cross_val_predict
from skl... | true |
95b1746ee696f3c6de0ecf9469a8d82f141daa18 | Python | daniellopes04/uva-py-solutions | /list4/10541 - Stripe.py | UTF-8 | 669 | 3.53125 | 4 | [] | no_license | # -*- coding: UTF-8 -*-
def rectangles(n, k):
if k == n:
return 1
if k > n:
return 0
d = max(k, n - k)
q = min(k, n - k)
numerator = 1
for n in range(d + 1, n + 1):
numerator *= n
denominator = 1
for d in range(1, q + 1):
denominator *= d
ret... | true |
60f6efc871a2b70f1bd7bc032eade4c664124878 | Python | gruiick/openclassrooms-py | /01-Apprenez/2.01.py | UTF-8 | 820 | 3.46875 | 3 | [
"BSD-2-Clause"
] | permissive | #!/usr/bin/env python3
# coding: utf-8
# $Id: 2.01.py 1.2 $
# SPDX-License-Identifier: BSD-2-Clause
chaine = str() # chaîne vide, même résultat que chaine = ""
#while chaine.lower() != 'q':
#print("hit 'Q' to quit")
#chaine = input()
print('Thx')
print('Thx'.upper())
print('majuscules'.upper())
print(' s... | true |
277afb49b1cb9a729e8f0852b2777936f934a22c | Python | empracine/test-epcath | /TimePeriod.py | UTF-8 | 30,741 | 2.515625 | 3 | [] | no_license | import copy
import random
from Schedule import *
from operator import itemgetter
############################################################################################################################################################################################################
################################... | true |
25a6e6a306f09b7ed5cdeb0fa86013e4bd727793 | Python | Min-h-96/BST-calc | /BST-calc-1.py | UTF-8 | 3,238 | 3.953125 | 4 | [] | no_license | import sys
def postfix(list):
# 숫자와 연산자를 각각 구분을 한다
for i in range(len(list)):
operands = []
operator = []
for i in list:
if ord(i) >= 48:
operands.append(i)
else:
operator.append(i)
lst_postfix = [operands[0]]
for... | true |
3456a0f06147b3344aee6baddf14dfdba710e16f | Python | ittoyou/2-1807 | /16day/3-生成器.py | UTF-8 | 233 | 3.03125 | 3 | [] | no_license | '''
def test():
a,b = 0,1
for i in range(10):
a,b = b,a+b
yield b
t = test()
for i in t:
print(i)
'''
def test():
a,b = 0,1
for i in range(10):
a,b = b,a+b
yield b
t = test()
for i in t:
print(i)
| true |
34d30a3c5b544a0d58d2b569f9ddad9312dcf14b | Python | ChJL/LeetCode | /easy/599. Minimum Index Sum of Two Lists.py | UTF-8 | 545 | 3.046875 | 3 | [] | no_license | class Solution:
def findRestaurant(self, list1: List[str], list2: List[str]) -> List[str]:
d1 = {}
d2 = {}
count = 0
for i in list1:
d1[i] = count
count += 1
count = 0
for i in list2:
if i in d1:
d2[i] = count + d1[i... | true |
9a2bf64c4a3530f6c97b00aae02ee3d35d733835 | Python | Leader0721/Python_Spider | /douyu/douyu.py | UTF-8 | 1,286 | 3.03125 | 3 | [] | no_license | # coding=utf-8
# 爬取斗鱼颜值妹子图片
import os
import re
from urllib import request
import time
from bs4 import BeautifulSoup
# 定义为方法
def getHTML(url):
page = request.urlopen(url)
html = page.read()
return html
# 图片存放路径
FOLDER_SAVE = r'E:/Sprider/douyu'
# 开始根据链接爬图片保存数据
def getImage(html):
if not os.path.ex... | true |
b58b2870f853c351a1a275d6321619a4414b958c | Python | enabhishek94/SeleniumFramework_Python | /Dummy/BaseTest.py | UTF-8 | 648 | 2.5625 | 3 | [] | no_license | import unittest
from Library import *
import pytest
class BaseTest(unittest.TestCase):
def setUp(self):
print("\n Running setup")
driver_path = "C:\\Users\\abc\\Desktop\\Python P\\chromedriver.exe"
self.driver = webdriver.Chrome(executable_path=driver_path)
self.driver.get("https:/... | true |
3399bb41b056c3881890b343e3cc725cc12a7fe9 | Python | mcauser/CircuitPython_TerminalPixels | /circuitpython_terminalpixels.py | UTF-8 | 1,319 | 3.1875 | 3 | [
"MIT"
] | permissive |
from math import ceil
import sys
class FakePixel:
def __init__(self, n=80, x=1, y=1, rows=1, auto_write=True):
self.n = n
self.bpp = 3
self._x = x
self._y = y
self._rows = rows
self._chars_per_row = n // rows
self.pixels = [(0, 0, 0)] * n
self.auto... | true |
b889584694fd98ac354136c81b576ae1cae796ee | Python | borescht/HoQuNM | /hoqunm/data_tools/analysis.py | UTF-8 | 51,708 | 2.515625 | 3 | [
"MIT"
] | permissive | """Provide methodologies for analysing the provided data."""
import json
import logging
from collections import Counter
from datetime import date, datetime, timedelta
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
import graphviz
import matplotlib.pyplot as plt
import numpy as np
import ... | true |
220782e6d68217ed4677ddf90ae3d0964c3bb3ae | Python | IKyriem/Ejercicios-procesamiento-de-imagenes | /tarea.py | UTF-8 | 276 | 2.625 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as pyplot
import cv2
#Carga de imagen a color
img = cv2.imread('2C1.jpg', 1)
[B, G, R] = cv2.split(img)
cv2.imshow ('imageR', R)
cv2.imshow ('imageG', G)
cv2.imshow ('imageB',B)
cv2.waitKey(0)
cv2.destroyAllWindows()
| true |
5ea8278a46f6919fd0e35af636b65fe11522791b | Python | zctao/GLIB_Aurora | /PyChips_1_4_1/scripts/glib_icap_jump_to_image.py | UTF-8 | 4,249 | 2.59375 | 3 | [] | no_license | ##===================================================================================================##
##==================================== Script Information ===========================================##
##===================================================================================================##
## ... | true |
52ab0375a54ef8c2e04d83fcc2634d11cf192590 | Python | Juan8bits/low_level_programming | /0x1C-makefiles/5-island_perimeter.py | UTF-8 | 1,613 | 3.890625 | 4 | [] | no_license | #!/usr/bin/python3
""" Islander perimeter """
def island_perimeter(grid):
""" function that returns the perimeter of the
island described in grid.
Conditions:
- Grid is a list of list of integers.
- 0 represents a water zone.
- 1 represents a land zone
- One cell is a ... | true |
494bd38d3f3d370098e8c11e672901c7f619dd73 | Python | a1742861031/faceRecognition | /flask-face-recognition-manage-system/controller/api_1_0/passport.py | UTF-8 | 3,493 | 2.546875 | 3 | [] | no_license | from . import api
from flask import current_app, jsonify, make_response, request, session
from .. import redis_store
from .. import models, db
from sqlalchemy.exc import IntegrityError
from werkzeug.security import generate_password_hash, check_password_hash
@api.route('/users', methods=["POST"])
def registe... | true |
d276cd96b0a93aca3693bbcedd06664254ef5b85 | Python | tshidhore/solver-codes | /ME614/homeworkHPC/code/p3.py | UTF-8 | 1,828 | 2.546875 | 3 | [] | no_license | import os
import sys
import numpy as np # library to handle arrays like Matlab
import scipy.sparse as scysparse
from matplotlib import pyplot as plt
from mpi4py import MPI
import pickle
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
size1 = comm.Get_size()
N = ((10**5)+1)*np.ones(1,dtype=np.float128)
e_tr = np.zero... | true |
b07aa6e4556561a02878255178fa1bb52d023c3b | Python | shivatharun/NLP | /Functional_API_Keras/5_Shared_Input_layer.py | UTF-8 | 852 | 2.609375 | 3 | [] | no_license | # Shared Input Layer model
from keras.models import Model
from keras.layers import Input, Dense, Flatten
from keras.utils import plot_model
from keras.layers.convolutional import Conv2D
from keras.layers.pooling import MaxPooling2D
from keras.layers.merge import concatenate
visible = Input(shape=(64,64,1))
conv1 = Co... | true |
1cf8687770a7c3c62d1edb55d6ebefccd3c413bd | Python | TenzinJhopee/GamestonkTerminal | /gamestonk_terminal/cryptocurrency/onchain/ethgasstation_model.py | UTF-8 | 1,549 | 3 | 3 | [
"MIT"
] | permissive | import pandas as pd
import requests
def get_gwei_fees() -> pd.DataFrame:
"""Returns the most recent Ethereum gas fees in gwei
[Source: https://ethgasstation.info]
Parameters
----------
Returns
-------
pd.DataFrame
four gas fees and durations
(fees for slow, average, f... | true |