seq_id stringlengths 4 11 | text stringlengths 113 2.92M | repo_name stringlengths 4 125 ⌀ | sub_path stringlengths 3 214 | file_name stringlengths 3 160 | file_ext stringclasses 18
values | file_size_in_byte int64 113 2.92M | program_lang stringclasses 1
value | lang stringclasses 93
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21414167412 | # -*- coding: utf-8 -*-
import tkinter as tk
from typing import List
from ParseError import ParseError
from geometry_syntax import GeometrySyntax
from oval_parameters import OvalParameters
from preview import Preview
class Application(tk.Frame):
_syntax_error_tag = "syntax_error"
def __init__(self, master,... | paper-lark/pythondev | 05_SshAndSmartWidgets/src/application.py | application.py | py | 3,767 | python | en | code | 0 | github-code | 1 |
11710769912 | #author: Samet Kalkan
import numpy as np
from keras.models import Sequential
from keras.layers import Conv2D, MaxPooling2D, Flatten, Dropout, Dense
from keras.utils import np_utils
from keras.callbacks import ModelCheckpoint
from keras import regularizers
from keras import backend as K
np.random.seed(0)
... | baker12355/weather_prediction | CNN_train.py | CNN_train.py | py | 2,813 | python | en | code | 0 | github-code | 1 |
7565321283 | import tempfile
import subprocess
import os
import yaml
import codecs
import logging
class FileService(object):
METAPATH_KEY = "_metapath"
def __init__(self, logger=None):
self.logger = logger or logging.getLogger(__name__)
def edit_temp_file(self, initial_text):
"""Edits a temp file in ... | withrocks/transcribe-cli | transcribe_cli/file_svc.py | file_svc.py | py | 2,483 | python | en | code | 1 | github-code | 1 |
24776414641 | # coding: utf-8
"""
该文件主要是对数据进行预处理，将评分数据按照8：2分为训练数据与测试数据
"""
import pandas as pd
import csv
import os
#将文件中的数据按照userId进行排序，如果userId相同则按照timestamp进行排序
origin_f = open('data/ratings.csv','rt',encoding='utf-8',errors="ignore")
new_f= open('data/ratings_sort.csv','wt',encoding='utf-8',errors="ignore",newline="")
reader=cs... | wyhluckydog/ML-For-Recommendation | fm/divideData.py | divideData.py | py | 3,811 | python | en | code | 1 | github-code | 1 |
933868552 | from collections import deque
import sys
input = sys.stdin.readline
n, m = map(int, input().split())
graph = [[]*(n+1) for _ in range(n+1)]
visited = [False] * (n+1)
for _ in range(m):
a, b = map(int, input().split())
graph[a].append(b)
graph[b].append(a)
cnt = 0
def bfs(v):
queue = deque([v])
vis... | jjs0211/problem-solving-with-study | Baekjoon/Class03/11724_연결요소의개수.py | 11724_연결요소의개수.py | py | 1,228 | python | en | code | 0 | github-code | 1 |
31136763706 | # -*- coding: utf-8 -*-
"""
This model takes the winemag data & filters on the north_america and europe continents.
After cleaning and prepping the date,
we run two bayesian hierarchical models (one for each continent) on the data using variational inference & pymc3
"""
import pandas as pd
import numpy as np
import py... | wkdaniel3/Bayesian-Analysis-for-Wine | points_regression_hierarchical.py | points_regression_hierarchical.py | py | 8,895 | python | en | code | 0 | github-code | 1 |
31602843689 | from matplotlib import pyplot as plt
from PIL import Image
img = Image.open("original.jpg")
img2 = Image.open("broken1.png").convert(img.mode)
img2 = img2.resize(img.size)
img3 = Image.blend(img,img2,0.35)
plt.figure(num='BROKEN LENS Failure')
plt.subplot(121),plt.imshow(img),plt.title('Original')
plt.xticks([]),... | XYZ121212/issre2020 | superimposition.py | superimposition.py | py | 437 | python | en | code | 0 | github-code | 1 |
10111024127 | # coding=utf-8
__author__ = '01053185'
"""
该代码实现功能：
1.测试集 与 学习集合的划分
2.测试集的输入文件构造
3.构造学习集的输入文件
"""
import os
import random
class StepOne():
def __init__(self):
self.data_dir_in = 'E:\\gitshell\\tianchi2' # 输入文件夹
self.data_dir_out = 'E:\\gitshell\\tianchi3' # 输出文件夹
# 搭配关系重新表示
def my_ShangP... | axuanwu/bayes3 | set_partition.py | set_partition.py | py | 4,154 | python | en | code | 0 | github-code | 1 |
3181829099 | #!/usr/bin/env python3
"""
cron: 0 40 22 * * *
new Env('明日天气');
"""
import sys
import requests
import json
import time
from bs4 import BeautifulSoup
import os, re
# 获取WxPusher appToken WxPusher_appToken
if "WxPusher_appToken" in os.environ:
if len(os.environ["WxPusher_appToken"]) > 1:
WxPusher_appToken = ... | BSSAMA/weather | tomorrow_weather.py | tomorrow_weather.py | py | 5,931 | python | en | code | 0 | github-code | 1 |
35990787928 | """
Get Options Action for App ID
"""
from urllib.parse import urlencode
from api.api_samples.python_client.ext import requests
from common.methods import set_progress
from itsm.servicenow.models import ServiceNowITSM
import json
def get_options_list(field, **kwargs):
options = [('', '--- Select an App ID ---')]... | mbomb67/cloudbolt_samples | params/create_tags.py | create_tags.py | py | 2,362 | python | en | code | 2 | github-code | 1 |
25577714533 | # Copyright (C) 2020 Claudio Marques - All Rights Reserved
from enum import Enum
class Lists(Enum):
VOWEL = 'aeiou'
CONSOANT = "bcdfghjklmnpqrstvwxyz"
NUMERIC = "0123456789"
SPECIALCHAR = "!\"#|\\$%&/()=?«»´`*+ºª^~;,-_@£€{[]}'"
class DatesEnum(Enum):
SemDados = 0
UmMes = 1
... | claudioti/dataset-creator | lib/enumerations.py | enumerations.py | py | 532 | python | en | code | 3 | github-code | 1 |
29165679484 | from django.shortcuts import render
# Create your views here.
from django.http import HttpResponse
from wmh_server.models import LocationData as lc
from django.views.decorators.csrf import csrf_exempt
import json
import datetime as dt
from django.conf import settings
def index(request):
res = "Base Path:{}. This ... | PavloZub/WalkMeHome_SRV | wmh_server/views.py | views.py | py | 2,572 | python | en | code | 0 | github-code | 1 |
20491564834 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pywt
from sklearn.cluster import KMeans
from sklearn.cluster import AgglomerativeClustering
import random
from scipy.spatial import distance
import math
from typing import Union
DataSources = Union[str,pd.Series,np.ndarray]
class TemplateEr... | ZoyaV/ikmeans | ikmeans/dwt_templates.py | dwt_templates.py | py | 5,004 | python | en | code | 1 | github-code | 1 |
41919082633 | # Sytulacja rzutu dwoma kośćmi.
from die import Die
from plotly.graph_objs import Bar, Layout
from plotly import offline
die_1 = Die()
die_2 = Die(10)
results = [die_1.roll()+die_2.roll() for roll_num in range(50_000)]
max_result = die_1.num_sides + die_2.num_sides
frequencies = [results.count(value) for value in r... | Jvlia17/Data-Visualization | dice_visual.py | dice_visual.py | py | 830 | python | pl | code | 0 | github-code | 1 |
35718199463 | # -*- coding: utf-8 -*-
"""
Course: CS 4365/5354 [Computer Vision]
Author: Jose Perez [ID: 80473954]
Assignment: Lab 1
Instructor: Olac Fuentes
Last Modification: September 2, 2016 by Jose Perez
"""
from timeit import default_timer as timer
from PIL import Image
from numpy import *
# Page 42-43, exercise 5
# Gradient ... | DeveloperJose/Python-CS4363-Computer-Vision | Lab1/problem1_exercise5.py | problem1_exercise5.py | py | 1,877 | python | en | code | 0 | github-code | 1 |
15803733936 | import time
import csv
import osm_bot_abstraction_layer.osm_bot_abstraction_layer as osm_bot_abstraction_layer
import osmapi
def is_imprecise_ukrainian_name(name_uk, name):
if name_uk in ["шкільний комплекс", "професійна школа"]:
return True
if name_uk == "Загальноосвітній ліцей" and name.lower() != "... | matkoniecz/ua-names | ua.py | ua.py | py | 14,623 | python | en | code | 0 | github-code | 1 |
11397164333 | from bs4 import BeautifulSoup
import requests
from rus import send_mail
from soc import messages_to_string
def parse_hearpwn_page(page):
page = requests.get(page)
soup = BeautifulSoup(page.text, 'html.parser')
messages = soup.find_all('div', itemprop='text')
return messages
def parse_sa... | komap2017/soc | hearthpwn.py | hearthpwn.py | py | 848 | python | en | code | 0 | github-code | 1 |
20667568841 | # 케이스를 2가지 밖에 생각 못함 ,이번꺼 안먹은 경우// 이번꺼 먹고 + dp[i-2]
# + 추가로 이번꺼 저번꺼 먹은 경우도 생각 해줬어야함 lst[i-2],lst[i-1],dp[i-3]
# lst랑 dp랑 인덱스 안맞기때문에 헷갈리는거 조심, 가짓수를 더 생각해보자!!!
import sys
input=sys.stdin.readline
n=int(input())
lst=[]
dp=[0]*(n+1)
for _ in range(n):
lst.append(int(input()))
dp[1]=lst[0]
if n>1:
dp[2]=lst[0]+ls... | jeongkwangkyun/algorithm | dp/2156.py | 2156.py | py | 788 | python | ko | code | 0 | github-code | 1 |
8496698639 | import json
import os
import socket
import sys
import threading
import time
class Server:
__instance = None
@staticmethod
def getInstance(callback=None):
if Server.__instance == None:
Server(callback)
return Server.__instance
def __init__(self, callback):... | jaanonim/ISM | server/server.py | server.py | py | 6,736 | python | en | code | 0 | github-code | 1 |
43279921183 | import ply.yacc as yacc
from mathpy.grammar.paranthesis.lexer import tokens
precedence = (
('nonassoc', 'NUMBER'),
('nonassoc', 'SINE', 'COSINE', 'SECANT', 'COSECANT', 'TANGENT', 'COTANGENT', 'LOG', 'EXP', 'ARCSINE', 'ARCCOSINE', 'ARCTANGENT', 'SINEH', 'COSINEH', 'TANGENTH', 'ARCSINEH', 'ARCCOSINEH', 'ARCTANGE... | pritansh/mathpy | mathpy/grammar/paranthesis/parser.py | parser.py | py | 2,810 | python | en | code | 0 | github-code | 1 |
70673992353 | #!/usr/bin/env python
import os
import shutil
import argparse
import subprocess
import random
import pandas as pd
import numpy as np
import pickle as pkl
import scipy as sp
import networkx as nx
import scipy.stats as stats
import scipy.sparse as sparse
from torch import nn
from torch import optim
from torch.nn import ... | KennthShang/PhaBOX | PhaMer_single.py | PhaMer_single.py | py | 7,806 | python | en | code | 16 | github-code | 1 |
17955145003 | from __future__ import unicode_literals
from sklearn.metrics import confusion_matrix
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from hazm import *
import fasttext
import string
import emoji
import hazm
import json
import os
import re
#
normalizer = Normalizer()
def remove_extra_chars(text):... | MinaHajirezaei/Text-classification-with-fasttext | fasttext_classification.py | fasttext_classification.py | py | 8,412 | python | en | code | 1 | github-code | 1 |
34519629611 | #!/usr/bin/env python3
from Crypto.Util import number
from binascii import hexlify, unhexlify
from gmpy2 import next_prime, powmod, gcdext, gcd
from itertools import count
from random import randint
class MPRSA(object):
def __init__(self):
self.public_key = None
self.secret_key = None
def key... | p4-team/ctf | 2017-07-15-ctfzone/mprsa/mprsa.py | mprsa.py | py | 1,901 | python | en | code | 1,716 | github-code | 1 |
27827135577 | import pytest
from thefuck.types import Command
from thefuck_contrib_scoop.rules.scoop_unknown_command import get_new_command, match
from thefuck_contrib_scoop.scoop import get_aliases, get_commands
@pytest.mark.parametrize(
"script, output",
[
(
"scoop bucke add versions",
"s... | beerpiss/thefuck-contrib-scoop | tests/rules/test_scoop_unknown_command.py | test_scoop_unknown_command.py | py | 1,453 | python | en | code | 0 | github-code | 1 |
8708358698 | from random import randrange
def main():
limit = -1
while limit < 1:
try:
limit = int(input("What is the level of this game? "))
except ValueError:
print ("Please input a positive integer!")
guess = ''
num = randrange(limit)
while guess != limit:
... | Motunrayo321/Programming-review | Week 4/Pset 4/4. Guessing Game/game.py | game.py | py | 693 | python | en | code | 0 | github-code | 1 |
6104384803 | # Import the dependencies.
import numpy as np
import pandas as pd
import datetime as dt
import sqlalchemy
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import Session
from sqlalchemy import create_engine, func
from flask import Flask, jsonify
#################################################
# Da... | Wheezyotter/sqlalchemy-challenge | SurfsUp/app.py | app.py | py | 7,631 | python | en | code | 0 | github-code | 1 |
8139262298 | class Solution:
def letterCombinations(self, digits: str) -> list:
if not digits: return []
nums = {'1':('','',''),
'2':('a','b','c'),
'3':('d','e','f'),
'4':('g','h','i'),
'5':('j','k','l'),
'6':('m','n','o'),
... | MinecraftDawn/LeetCode | Medium/17. Letter Combinations of a Phone Number.py | 17. Letter Combinations of a Phone Number.py | py | 666 | python | en | code | 1 | github-code | 1 |
34468401334 | # Code source: Jaques Grobler
# License: BSD 3 clause
# Code from https://scikit-learn.org/stable/auto_examples/linear_model/plot_ols.html
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets, linear_model
from sklearn.metrics import mean_squared_error, r2_score
from joblib import dump, load... | Wallis16/Docker_Machine_Learning | App/Training/train.py | train.py | py | 1,870 | python | en | code | 0 | github-code | 1 |
32486175131 | def game(r, c, s):
grid[r][c] = s
for i in range(8):
stack = []
for l in range(1, N):
nr = r + delta[i][0] * l
nc = c + delta[i][1] * l
if 0 <= nr < N and 0 <= nc < N and not grid[nr][nc]:
break
if 0 <= nr < N and 0 <= nc < N and gr... | CrimsonTheLegoBuilder/MyBaekjoonSolve | hw/sw4615.py | sw4615.py | py | 1,181 | python | en | code | 0 | github-code | 1 |
37257135092 | # Exercise 2: Write a program to look for lines of the form:
#
# New Revision: 39772
#
# Extract the number from each of the lines using a regular expression and the
# findall() method. Compute the average of the numbers and print out the average
# as an integer.
#
# Enter file:mbox.txt
# 38549
#
# Enter file:m... | caseywschmid/python_for_everybody | exercise_11-02.py | exercise_11-02.py | py | 1,129 | python | en | code | 0 | github-code | 1 |
15628978181 | import math
from statistics import mean,stdev,mode
import os
import pandas as pd
library = pd.read_csv('Z:/Helium_Tan/PTMDIAProject_SpectralLibraries/Pro_12fxnOnly/PTMDIAProject_TimsTOFPro_12fxnOnly.tsv', delimiter= '\t',low_memory = False)
# print(len(library))
phospho_library = library[library['IntLabeledPeptide'].... | tvashist/PTMDIA | Library_DIA_Overlap.py | Library_DIA_Overlap.py | py | 1,423 | python | en | code | 0 | github-code | 1 |
14777550147 | import functools
import turtle
import hangman
import words
def write_word(word):
writer = turtle.Turtle()
writer.penup()
writer.goto(100, 200)
writer.write(word, font=('Arial', 16, 'bold'))
writer.hideturtle()
# Иницилизация
original_word = words.get_random_word()
word = '_' * len(original_word... | simo1209/tues_homework | 24/game.py | game.py | py | 954 | python | en | code | 5 | github-code | 1 |
839842385 | # def solution(gems):
# size = len(set(gems))
# dic = {gems[0]:1}
# temp = [0, len(gems) - 1]
# start, end = 0, 0
#
# while(start < len(gems) and end < len(gems)):
# if len(dic) == size:
# if end - start < temp[1] - temp[0]:
# temp = [start, end]
# if ... | smileostrich/algorithm-practice | problemSolving/company/kakao/2020/2020_suumer_intern/p3.py | p3.py | py | 1,218 | python | en | code | 0 | github-code | 1 |
27203130897 | from ast import Interactive
from typing import Collection
import pygame
import logging
from settings import *
from player import Player
from overlay import Overlay
from sprites import GenericSprites, WaterSprites, TreeSprites, WildFlowerSprites, InteractionSprites, ParticleEffects
from pytmx.util_pygame import load_pyg... | lordhelmut/pygame-town | src/level.py | level.py | py | 10,702 | python | en | code | 0 | github-code | 1 |
6384058720 | # (C) 2021 Victor Suarez Rovere <suarezvictor@gmail.com>
#NOTES:
"""
#test command:
$
$ clang -E -I. ../tr_pipelinec.cpp > tr_pipelinec.E.cpp && python3 cflexc.py tr_pipelinec.E.cpp > tr_pipelinec.gen.cpp && clang -c tr_pipelinec.gen.cpp -o tr_pipelinec.gen.o && clang++ -O3 -I.. -fopenmp=libiomp5 -ffast-math `sdl2-co... | suarezvictor/CflexHDL | cflexparser/cflexc.py | cflexc.py | py | 4,746 | python | en | code | 153 | github-code | 1 |
35282075051 | """
It is a file that crops the mp3 and srt file by the durations
which is getting from the srt file.
"""
import os
from ..helper.helper import run_bash, parse_time
class CropMp3Srt:
"""
Gets the mp3 and srt files to crop
"""
def __init__(self, filepath):
self._path = filepath
def crop(s... | IoT-Ignite/ArdicSrtCollector | ardicsrtcollector/crop_mp3_srt/crop_mp3_srt.py | crop_mp3_srt.py | py | 3,773 | python | en | code | 1 | github-code | 1 |
4340565342 | import logging
import re
from datetime import datetime, timezone
from zipfile import ZipFile
import pandas
from jal.widgets.helpers import g_tr
from jal.db.update import JalDB
from jal.constants import Setup, DividendSubtype, PredefinedCategory, PredefinedAsset
# -----------------------------------------------------... | iliakan/jal | jal/data_import/statement_uralsib.py | statement_uralsib.py | py | 13,042 | python | en | code | null | github-code | 1 |
72632121635 | # Capture multiple Faces from multiple users to be stored on a DataBase (dataset directory)
# ==> Faces will be stored on a directory: dataset/ (if does not exist, pls create one)
# ==> Each face will have a unique numeric integer ID as 1, 2, 3, etc
import cv2
from scripts.database_connection import Connection
... | FoOkySNick/faceRecognition | FaceRecognition/scripts/frontal_face_dataset_with_database.py | frontal_face_dataset_with_database.py | py | 3,813 | python | en | code | 0 | github-code | 1 |
29847344408 | from app import app
from boto.s3.connection import S3Connection
from boto.s3.key import Key
import json
class IneffableStorage(object):
def __init__(self):
""" Initialize the class """
self.connection = None
self.bucket = None
def setup_connection(self):
""" Setup the connect... | taeram/ineffable | app/controllers/helpers/storage.py | storage.py | py | 1,142 | python | en | code | 8 | github-code | 1 |
33274035782 | # -- coding: utf-8 --
import tensorflow as tf
import pandas as pd
import numpy as np
import pymysql
import sys
sys.path.append(sys.path.append('../')) # 导入上一级目录中的包
from settings import *
# 查询课程信息
# 课程信息查询,例：离散数学及其应用
# 课程编号，课程名称，公司企业名称，课程编码，课程类别，学分，是否考试，上传时间，标签
def courInfo(courseName):
db = pymysql.connect("10.1... | BoolWang/FuXueCase | fuxuecase/case4/case4.py | case4.py | py | 6,928 | python | en | code | 0 | github-code | 1 |
74705291873 | import numpy as np
m1 = (
(1, -1),
(1, 2)
)
matrix = np.array(
m1
)
print(matrix)
output = np.array(
(0, 8)
)
solve = np.linalg.solve(matrix, output) # 线性方程组求解 .
print(solve)
X = np.arange(-5, 5, 0.25)
a1 = np.arange(0, 10, 0.5)
print(a1)
| carl10086/dm-learning | dm-algebra/it/numpy_test.py | numpy_test.py | py | 274 | python | en | code | 0 | github-code | 1 |
24997965734 | from __future__ import absolute_import
import random
from src.event import SignalEvent
class TestRandomStrategy(object):
def __init__(self, instrument, units, events):
self.instrument = instrument
self.units = units
self.events = events
self.ticks = 0
self.invested = False... | LongntLe/Tradingsystem | src/strategy/randomstrategy.py | randomstrategy.py | py | 846 | python | en | code | 2 | github-code | 1 |
12747428660 | from keras.utils import to_categorical
import numpy as np
import pandas as pd
import time
TRAIN_SIZE = 30000
TEST_SIZE = 2
def label_generator(num_of_labels, size):
"""
Create a two coloum label set
:param size1:
:param size2:
:return:
"""
lab = np.zeros((size, num_of_labels), dtype=np.float)
length_per_label... | odedyec/biological_dnn | dataset_generator.py | dataset_generator.py | py | 7,460 | python | en | code | 0 | github-code | 1 |
5987291793 | inp = int(input())
fat = 1
soma = 0
for k in range(inp + 1):
for i in range( 1, k + 1 ):
fat = fat * i
soma = soma + fat
fat = 1
print (soma) | totoi690/trabalhosuni | SCC0600/exercíciosPy/ex13.py | ex13.py | py | 153 | python | en | code | 0 | github-code | 1 |
18709052300 | # Program for array rotation
# Write a function rotate(ar[], d, n) that rotates arr[] of size n by d elements.
# Input : [1, 2, 3, 4, 5, 6, 7]
# Output : 3 4 5 6 7 1 2
print("==========Calling functions============")
def leftRotate(arr,d,n):
for i in range(d):
leftRotateByOne(arr,n)
def leftRotateByOne(... | dilipksahu/Python-Programming-Example | Array programs/sumOfElement.py | sumOfElement.py | py | 1,027 | python | en | code | 0 | github-code | 1 |
32600971056 | #!/usr/bin/python3
from typing import List
import json
from bplib.butil import TreeNode, arr2TreeNode, btreeconnect, aprint
class Solution:
def canAttendMeetings(self, intervals: List[List[int]]) -> bool:
intervals = sorted(intervals)
current_start = -1
current_end = -1
for [start... | negibokken/sandbox | leetcode/252_meeting_rooms/main.py | main.py | py | 536 | python | en | code | 0 | github-code | 1 |
3897944753 | area_side = int(input())
tile_width = float(input())
tile_height = float(input())
bench_width = int(input())
bench_length = int(input())
area_to_cover = area_side*area_side - bench_length*bench_width
tile_area = tile_height*tile_width
tiles_needed = area_to_cover/tile_area
time = tiles_needed*0.2
print(round(tiles_nee... | LuGeorgiev/PythonSelfLearning | NakovBook/SimpleCalculations/ChangeTiles.py | ChangeTiles.py | py | 350 | python | en | code | 0 | github-code | 1 |
31976121540 | india = ["mumbai", "banglore", "chennai", "delhi"]
pakistan = ["lahore","karachi","islamabad"]
bangladesh = ["dhaka", "khulna", "rangpur"]
city_name = input("Enter a city name: ")
city_name = str(city_name)
if city_name in india:
print("This city is in India!")
elif city_name in pakistan:
print("This city is ... | Arkem001209/Python_Testing | exercise_8_1.py | exercise_8_1.py | py | 473 | python | en | code | 0 | github-code | 1 |
27016684208 | from Supersymmetry_nonBPS_3pt import*
from Supersymmetry_nonBPS_3pt_fourier import*
def etaP_Mul(amplitude, multiplier=sqrt(2)):
result = 0
a = multiplier
for susy in amplitude.arr:
temp = susy.copy()
if '01' in susy.etalist:
temp *= a
if '02' in susy.etalist:
... | DanielChen86/Supersymmetry | FourierTransformation.py | FourierTransformation.py | py | 2,147 | python | en | code | 0 | github-code | 1 |
25316109249 | from config import data_db_schema,data_ocr
from repositories import DataRepo
from utilities import LANG_CODES
import logging
from logging.config import dictConfig
log = logging.getLogger('file')
repo = DataRepo()
class OcrModel:
def __init__(self):
self.db = data_db_schema
self.col = da... | ishudahiya2001/ULCA-IN-ulca-Public | backend/metric/ulca-utility-service/src/models/ocr.py | ocr.py | py | 3,702 | python | en | code | 0 | github-code | 1 |
19658143575 | from pyBrainNetSim.generators.network import SensorMoverProperties
from pyBrainNetSim.models.individuals import SensorMover
class SensorMoverEvolutionarySolver(object):
"""
An Evolutionary solver to find the best 'SensorMover' for the environment. This simulates I individuals at time 0.
Each individual mo... | hurtb777/pyBrainNetSim | pyBrainNetSim/solvers/solver.py | solver.py | py | 2,108 | python | en | code | 0 | github-code | 1 |
34576891554 | __author__ = "Michael Chambers"
__copyright__ = "Copyright 2019, Michael Chambers"
__email__ = "greenkidneybean@gmail.com"
__license__ = "MIT"
from snakemake.shell import shell
log = snakemake.log_fmt_shell(stdout=False, stderr=True)
shell(
"samtools faidx {snakemake.params} {snakemake.input[0]} > {snakemake.ou... | leonqli/snakemake-wrappers | bio/samtools/faidx/wrapper.py | wrapper.py | py | 338 | python | en | code | null | github-code | 1 |
43564951062 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
def trim_fields(apps, schema_editor):
trim_extra_account(apps, schema_editor, "facebook")
trim_extra_account(apps, schema_editor, "github")
trim_extra_account(apps, schema_editor, "twitter")
def trim_... | colab/colab | colab/accounts/migrations/0004_auto_20150311_1818.py | 0004_auto_20150311_1818.py | py | 1,511 | python | en | code | 23 | github-code | 1 |
13761313878 | import math
def secante(x, y):
#x = Xn
#y = Xn-1
for i in range(6):
aux = x
x = (y*f(x) - x*f(y))/(f(x) - f(y))
y = aux
return x
def f(x):
return x**2 + 25600/(((240/math.sqrt(900 - x**2)*x)/30) - x)**2 - 20**2
print("Valor de L aproximadamente: " + str(secante(5, 4)))
| martinsspn/Calculo-numerico | tarefa2/questão4/secanteQ4.py | secanteQ4.py | py | 317 | python | pt | code | 1 | github-code | 1 |
26165070556 | class Headline:
'''
Headlines class to define Headlines Objects
'''
def __init__(self,id,title,description,urlToImage,publishedAt,author,content,url):
self.id =id
self.title = title
self.description = description
self.urlToImage = urlToImage
self.publishedAt ... | Muia23/NewsHub | app/models.py | models.py | py | 637 | python | en | code | 0 | github-code | 1 |
32204725988 | from random import randint
import random
age = input('how old are you? ')
age = int(age)
# if condition:
# "code that runs if condition if true" - typically 4 spaces of indentation
if age >= 21:
print('Come on in!')
print('*******')
print('AFTER THE IF STATEMENT')
# this gets printed regardless of True or ... | JLoh17/One-Week-Python | 10_Conditionals-Basics.py | 10_Conditionals-Basics.py | py | 1,391 | python | en | code | 0 | github-code | 1 |
23584376110 | # vim: set expandtab:
import typing
import subprocess
import os
import pwd
import sys
import docker
import re
import socket
import psutil
import io
import pickle
import math
import threading
import time
import shutil
import uuid
from .imageTransient import TransientImageSlurmBackend, list_instances, get_gce_client
fr... | getzlab/canine | canine/backends/dockerTransient.py | dockerTransient.py | py | 24,264 | python | en | code | 6 | github-code | 1 |
21065266517 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from absl import flags
import tensorflow as tf
import dataloader
import retinanet_model
from tensorflow.contrib.tpu.python.tpu import tpu_config
from tensorflow.contrib.tpu.python.tpu import tpu_est... | ProjectSidewalk/sidewalk-cv-assets19 | old/tf_resnet_tutorial/tpu/models/official/retinanet/retinanet_main.py | retinanet_main.py | py | 8,690 | python | en | code | 4 | github-code | 1 |
40355111174 | from sqlitedatabase import add_entry,get_entries,create_connection,create_table
menu = """ Welcome to the programming diary!
Please select one of the following options:
1) Add new entry for today.
2) View entries.
3) Exit.
Your selection:
"""
welcome = "**Welcome to the programing diary!**"
# entries = [
# {"c... | manishg2015/python_workpsace | python-postrgress/main.py | main.py | py | 1,625 | python | en | code | 0 | github-code | 1 |
4573261188 | # n = int(input())
# times = []
#
# for _ in range(n):
# start, end = map(int, input().split())
# times.append([start, end])
#
# times = sorted(times, key=lambda x: x[0])
# times = sorted(times, key=lambda x: x[1])
#
# finish_time = 0
# count = 0
#
# for start, end in times:
# if start >= finish_time:
# ... | 21CatchStudy/wonhee_repo | greedy/1931 회의실.py | 1931 회의실.py | py | 745 | python | en | code | 0 | github-code | 1 |
4568639765 | from datetime import datetime
import scrapy
from scrapy.http import Request
from maksavit_scrapy.items import ScrapyMaksavitItem
from maksavit_scrapy.settings import (CATEGORIES, DOMAIN, LOCATION, MAIN_URL,
PROXY)
class MaksavitSpider(scrapy.Spider):
name = 'maksavit'
p... | danlaryushin/parser_scrapy | maksavit_scrapy/spiders/maksavit.py | maksavit.py | py | 5,849 | python | en | code | 0 | github-code | 1 |
11745868944 | import math
from tkinter import *
size = 600
radius1 = size / 2.9
#radius orbiti
radius2 = size / 100
#radius vrashaushegosya kruga
def coords(angle):
x = math.cos(angle) * radius1
y = math.sin(angle) * radius1
return x - radius2 + size / 2, y - radius2 + size / 2, x + radius2 + size / 2, y + radi... | GeoYak/Praktikum_tkinter | Yakushchev_ZBPI212/Знакомство с tkinter.py | Знакомство с tkinter.py | py | 787 | python | en | code | 0 | github-code | 1 |
4062704487 | # Square root digital expansion
# Problem 80
# It is well known that if the square root of a natural number is not an integer, then it is irrational.
# The decimal expansion of such square roots is infinite without any repeating pattern at all.
# The square root of two is 1.41421356237309504880..., and the digital s... | IgorKon/ProjectEuler | 080.py | 080.py | py | 941 | python | en | code | 0 | github-code | 1 |
32990811232 | from scrapy.contrib.spiders import CrawlSpider, Rule
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector
from cssspy.utils import domains_from_urls, absolute_urls
from cssspy.cssscrapy.items import CssFilesItem
from scrapy.contrib.linkextractors.htmlparser import HtmlParserLinkExtractor
... | Scorpil/cssspy | cssspy/cssscrapy/spiders/cssspider.py | cssspider.py | py | 1,492 | python | en | code | 0 | github-code | 1 |
1707012386 | from typing import Dict, List
import asana
from giges.models.team import Team
from giges.slack import SlackClient
from giges.tasks.app import app
from giges.util import validate_uuid
def _add_ds_class_item(custom_field: Dict[str, str]) -> str:
"""
Returns the slack representation for a Data Science item.
... | tesselo/giges | giges/tasks/asana.py | asana.py | py | 4,761 | python | en | code | 0 | github-code | 1 |
22525543773 | import json
import os
import numpy as np
import sys
import copy
import random
import jsonlines
import time
import scipy.stats
task = sys.argv[1]
model = sys.argv[2]
model = f"en_dense_lm_{model}"
# !!! replace by your $base_dir/ana_rlt here
base_dir = "$base_dir/ana_rlt"
ana_rlt_dir = f"{base_dir}/{model}"
debug_sca... | microsoft/LMOps | understand_icl/icl_ft/compute_training_example_attn.py | compute_training_example_attn.py | py | 8,440 | python | en | code | 2,623 | github-code | 1 |
21499865608 | #!/usr/bin/env python
import sys
from setuptools import find_packages, setup
setup_requires = []
# I only release from OS X so markdown/pypandoc isn't needed in Windows
if not sys.platform.startswith('win'):
setup_requires.extend([
'setuptools-markdown',
])
setup(
name='serplint',
author='B... | beaugunderson/serplint | setup.py | setup.py | py | 1,362 | python | en | code | 5 | github-code | 1 |
2427076789 | import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
class TrainTestSplitter:
def __init__(self, subjects, labels):
"""
Initializes the TrainTestSplitter class.
Parameters:
- subjects (list): List of subjects.
- labels (list): List of... | dheerajpr97/Explainable-AI-Non-EEG | src/utils/cross_val.py | cross_val.py | py | 5,499 | python | en | code | 0 | github-code | 1 |
9395637463 | def solution(people, limit):
people = sorted(people, reverse=True)
start = 0
end = len(people) - 1
counter = 0
while start <= end:
weight_heavy = people[start]
weight_light = people[end]
if weight_heavy + weight_light <= limit:
end -= 1
start += 1
... | dhsong95/-PRACTICE-Programmers-Algorithm | level 2/구명보트.py | 구명보트.py | py | 473 | python | en | code | 0 | github-code | 1 |
40738971562 | import h2o
import numpy as np
# Start H2O on your local machine
h2o.init ( ip='localhost', port=54321, nthreads=-1, max_mem_size='25g' )
# Import the train_numeric
train_numeric = h2o.import_file ( path="/Users/avinashbarnwal/Desktop/Kaggle/Bosch/train_numeric.csv" )
# train_categorical = h2o.import_file(path = "/User... | avinashbarnwal/Bosch-Kaggle | .idea/Code.py | Code.py | py | 2,944 | python | en | code | 0 | github-code | 1 |
40363495908 | __author__ = 'M_Nour'
import numpy as np
from scipy import stats
from sklearn.semi_supervised import label_propagation
from sklearn.metrics import classification_report, confusion_matrix,accuracy_score, f1_score, recall_score
import dataset
from collections import Counter
import matplotlib.pyplot as plt
from ... | marjan-nourollahi/PALS | stream_PAL.py | stream_PAL.py | py | 11,813 | python | en | code | 0 | github-code | 1 |
17567214725 | import torch
import torch.nn as nn
import numpy as np
import pickle
from utils.utils import NeighborSampler
class MTL(nn.Module):
def __init__(self, base_encoder_k, encoder, view_learner, edge_rnn, sample_time_encoder, len_full_edge,
train_e_idx_l, train_node_set, train_ts_l, e_feat, device, dim... | ViktorAxelsen/TGSL | GraphMixer+TGSL/MTL.py | MTL.py | py | 13,488 | python | en | code | 9 | github-code | 1 |
12533465974 | #!/usr/bin/env python3
"""
Sales As Code: randomly selects a sales-y buzzword from a google sheet.
"""
import argparse
import logging
import os
import random
import sys
import gspread
from cachetools import TTLCache
from dotenv import load_dotenv
from oauth2client.service_account import ServiceAccountCredentials
lo... | bblinder/home-brews | SalesAsCode.py | SalesAsCode.py | py | 3,610 | python | en | code | 0 | github-code | 1 |
15143070119 | #!/usr/bin/env python
# coding: utf-8
# # COURSE: Master statistics and machine learning: Intuition, Math, code
# ##### COURSE URL: udemy.com/course/statsml_x/?couponCode=202006
# ## SECTION: The t-test family
# ### VIDEO: Permutation testing
# #### TEACHER: Mike X Cohen, sincxpress.com
# In[ ]:
# import libraries... | mikexcohen/Statistics_course | Python/ttest/stats_ttest_permutation.py | stats_ttest_permutation.py | py | 2,373 | python | en | code | 18 | github-code | 1 |
36108195573 | import rclpy
from rclpy.node import Node
class Talk(Node):
def __init__(self,name):
super().__init__(name)
self.get_logger().info("Hello, I'm %s" % name)
def main(args=None):
rclpy.init(args=args)
node = Talk("Tom")
rclpy.spin(node)
rclpy.shutdown() | benjaminhuanghuang/ros-study | _projects/py_ws/src/py_study/py_study/ooptalk.py | ooptalk.py | py | 292 | python | en | code | 0 | github-code | 1 |
28052011409 | from comparison_sol import str_path
#from Global_alignment_MM_functions import seq_to_alignement
from matplotlib import colors
import argparse
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import os
# This is a script to visualize SCRaMbLEd chromosomes using an arrow plot.
# Created by ... | Mmark94/SCRaMbLE-SIM | arrowplot.py | arrowplot.py | py | 7,885 | python | en | code | 0 | github-code | 1 |
73066482913 | # -*- coding: utf-8 -*-
"""
Created on Wed Apr 29 16:40:47 2020
@author: Eric Bianchi
"""
import shutil
import os
import numpy as np
import tensorflow as tf
import cv2
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Try except statements
#+++++++++++++++++++++++++++++++++++++++++++++++... | beric7/COCO-Bridge-2021-plus | general_utils/classification_utils.py | classification_utils.py | py | 24,182 | python | en | code | 5 | github-code | 1 |
234718894 | import RPi.GPIO as GPIO
import time
import os
from numpy import interp
class ServoManager(object):
# self.current stores rot (degrees)
def __init__(self, pin):
# init GPIO
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BOARD)
GPIO.setup(pin, GPIO.OUT)
# default to center
self.pin = pin
self.currentAngle ... | jemgunay/bagel-turret | servo_manager.py | servo_manager.py | py | 907 | python | en | code | 0 | github-code | 1 |
8169473685 | import math
from torch import nn
import torch.nn.init as init
from .common import AdaptiveFM
from .dgr import DGR
import torch
import torch.nn.functional as F
def make_model(args, parent=False):
return ESPCN(args)
def get_valid_padding(kernel_size, dilation):
kernel_size = kernel_size + (kernel_size - 1) * (... | anonymousECCV2022/paper2031_ECCV2022_code | src/model/espcnori.py | espcnori.py | py | 3,794 | python | en | code | 1 | github-code | 1 |
20261507881 | from django.db.models import Manager
from .exceptions import TenantError
from .utils import state
FIELD_NAME = "shop"
class TenantManager(Manager):
def __init__(self):
self.state = state
super().__init__()
def get_queryset(self):
current_state = self.state.get_state()
queryse... | ragsub/smplshop2 | smplshop/users/tenant/managers.py | managers.py | py | 743 | python | en | code | 0 | github-code | 1 |
27582079263 | pref = input("Do you prefer Dogs or Cats? ")
def function(dogs, cats, pref):
print(f"You have {dogs} dogs")
print(f"You have {cats} cats.")
print(f"you prefer {pref}.\n")
function(10,15,pref)
function(10 - 5, 20 - 8,pref)
meow = 6
woof = 10
function(woof, meow,pref)
function(9,6,pref)
| chrisWalker11/Python | exercises/e19/function.py | function.py | py | 301 | python | en | code | 0 | github-code | 1 |
27438503281 | from __future__ import absolute_import
from __future__ import print_function
import os
import sys
import re
from builtins import str as text
import wx
# -----------------------------------------------------------------------------
# Global variables
# ----------------
#
__author__ = "Pierre Rouleau"
__version__ = "$... | thiagoralves/OpenPLC_Editor | editor/i18n/mki18n.py | mki18n.py | py | 17,501 | python | en | code | 307 | github-code | 1 |
6411650046 | import torch
import torchvision
from torch import nn
from torch.utils.tensorboard import SummaryWriter
from torchvision import transforms
from torch.utils.data import DataLoader
from torch.optim import Adam, SGD
from torch.optim.lr_scheduler import ChainedScheduler, LinearLR, MultiStepLR
import argparse
import os
impor... | rishabbala/Layerwise_model_training | extra_files/contrastive_training.py | contrastive_training.py | py | 13,603 | python | en | code | 0 | github-code | 1 |
17816136485 | from getmac import get_mac_address as gma
import sys
import os
import getopt
#varibles
mac = None
mac_vendor = ""
#argv
argv = sys.argv[1:]
opts, args = getopt.getopt(argv, "i:m:h", ["ip=", "mac=", "help"])
archivo = open("archivo.txt", "r")
def getmac(ipadress):
mac = gma(ip=ipadress)
... | robot-beep/tarea1-OUILookup | OUILookup.py | OUILookup.py | py | 730 | python | en | code | 0 | github-code | 1 |
12171445949 | #!/usr/bin/env python3
import rospy
from std_msgs.msg import String, Float32MultiArray, Bool
import time
class small_demo:
def __init__(self):
rospy.init_node('head_neck_screen_demo')
rospy.Subscriber("cmd_frm_tablet", String, self.demo_callback)
rospy.Subscriber('/battery_info', Float32Mu... | UsamaArshad16/demos | src/head_demo.py | head_demo.py | py | 3,580 | python | en | code | 0 | github-code | 1 |
24869313700 | from functools import wraps
import numpy as np
def handle_0D_1D_input(
patched_kwargs: [], patched_argpos: [], return_scalar=False
):
"""
A decorator that handles 0D, 1D inputs and transforms them to 2D.
Parameters
----------
kwarg : list of str
The names of the keyword arguments tha... | acerbilab/pyvbmc | pyvbmc/decorators/handle_0D_1D_input.py | handle_0D_1D_input.py | py | 2,169 | python | en | code | 99 | github-code | 1 |
34427844204 | import pandas as pd
import numpy as np
import datetime
import matplotlib
import matplotlib.pyplot as plt
from matplotlib import colors
import seaborn as sns
from sklearn.preprocessing import LabelEncoder, OneHotEncoder, OrdinalEncoder
from sklearn.preprocessing import StandardScaler
from sklearn.decomposition ... | charanharsha-git/VehicleInsuranceProject | fraud_detection.py | fraud_detection.py | py | 5,440 | python | en | code | 0 | github-code | 1 |
13255214663 | # count number of items brought in total
allGuests = {'Alice': {'apples': 5, 'pretzels': 12},
'Bob': {'ham sandwiches': 3, 'apples': 2},
'Carol': {'cups': 3, 'apple pies': 1}}
# create definition
def totalBrought(guests, product):
numBrought = 0
for k, v in guests.items():
n... | simink/py_automatetheboringstuff | code/5_totalBrought.py | 5_totalBrought.py | py | 541 | python | en | code | 1 | github-code | 1 |
17330037248 | import torch
import numpy as np
from scipy import interpolate
def load_pretrained(checkpoint_path, model, simmim):
if not simmim:
load_pretrained_swin(checkpoint_path, model)
else:
load_pretrained_simmim(checkpoint_path, model)
def load_pretrained_swin(checkpoint_path, model):
checkpoint ... | isadrtdinov/ens-for-transfer | models/swin/utils.py | utils.py | py | 6,790 | python | en | code | 0 | github-code | 1 |
17218746745 | import os
import click
import requests
from .utils import prepare_path, save_list_and_cache, write_to, get_result
from .help import BRANDING
prepare_path()
# @click.group()
@click.command()
@click.argument('ignore', required=False)
@click.version_option(message=BRANDING)
@click.option('-a', '--listall', help='Get al... | AzatAI/addignore | addignore/cli.py | cli.py | py | 1,397 | python | en | code | 0 | github-code | 1 |
15972604163 | #load matplotlib.pyplot as plt
import matplotlib.pyplot as plt
#load numpy as np
import numpy as np
#x range: [-pi, pi]
x = np.linspace(-np.pi, np.pi, 256, endpoint = True)
#y = sin(x)
y_sin = np.sin(x)
#y = cos(x)
y_cos = np.cos(x)
#Figure & subplot
fig = plt.figure(figsize = (12,8))
ax = fig.add_subplot(1,1,1)
#... | SONG-WONHO/start_Matplotlib | 07_review.py | 07_review.py | py | 976 | python | en | code | 0 | github-code | 1 |
8999801447 | from sklearn.compose import ColumnTransformer
from sklearn.pipeline import Pipeline
from data_processing.transformers.CommonSimilarity import CommonSimilarity
from data_processing.transformers.ToPandas import ToPandas
from recommend.transformers.CosSimilarity import CosSimilarity
from recommend.transformers.FetchSimil... | arctic-source/game_recommendation | recommend/pipeline.py | pipeline.py | py | 3,726 | python | en | code | 0 | github-code | 1 |
22718690979 | import cPickle as pickle
import scipy.io
import numpy as np
import theano.tensor as T
import theano
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
from utils import *
#this scrip is designed to produce prediction results from the pickled
#models generated by the utils and cnnlearning scripts... | corentintallec/mlproject2 | code/python/generate_results.py | generate_results.py | py | 2,841 | python | en | code | 0 | github-code | 1 |
19822983990 | from fastapi import FastAPI
from models import User, UserBet, VerifyRequest
app = FastAPI()
@app.post("/server_seed")
def get_hashed_server_seed(request: User):
resp = request.get_server_seed()
return resp
@app.post("/bet")
def bet(request: UserBet):
resp = request.process()
return resp
@app.pos... | PerryGraham/provably-fair-python | main.py | main.py | py | 414 | python | en | code | 0 | github-code | 1 |
15485119752 | from datetime import datetime, timedelta
import json
import threading
import logging
from enum import Enum
from const import CONST
from main import send_post
import pykka
import ledPWM
'''
on: time_h=19 photoresistor=50
time_h=18 photoresistor=20 -> nothing
time_h=20 photoresistor=60 -> nothing
time_h=21 photoresistor... | RyuzakiKK/esls | rpi/lamp.py | lamp.py | py | 11,090 | python | en | code | 0 | github-code | 1 |
72116408675 | import torch
import numpy as np
from torch.utils.data import DataLoader
import pandas as pd
from sklearn.model_selection import train_test_split
from keras.datasets import mnist
from torch.autograd import Variable
import matplotlib.pyplot as plt
import torch.nn as nn
import warnings
warnings.filterwarnings("i... | Berkan352/Machine-Learning | CNN.py | CNN.py | py | 3,659 | python | en | code | 0 | github-code | 1 |
42366561365 | class Solution:
def checkInclusion(self, s1: str, s2: str) -> bool:
if len(s2) < len(s1) : return False
left = 0
s1Counter = defaultdict(int)
s2Counter = defaultdict(int)
for i in range(len(s1)):
s1Counter[s1[i]] += 1
s2Counter[s2[i]]... | mykelbengineer/LeetCode | permutation-in-string/permutation-in-string.py | permutation-in-string.py | py | 782 | python | en | code | 1 | github-code | 1 |
32844015163 | from sklearn import preprocessing
import pickle
import joblib
import nltk
import pandas as pd
from flask import Flask,request
"""
string = "infection including flu pneumonia immunization diphtheria tetanus child teething \
infant inflammatory disease including rheumatoid arthritis ra crohn disease blood \
... | azharudh33n/MedConnect | ml/app_api.py | app_api.py | py | 1,991 | python | en | code | null | github-code | 1 |
22645813504 | #!/usr/bin/python3
'''Square Module
This module demonstrates how to work with classes.
The functionality included in this module is only for
demonstration purposes.
'''
class Square:
'''class Square
This is a simple class to demonstrate how to work with properties
setters, and getters. It also demonstrat... | Akochieng/alx-higher_level_programming | 0x06-python-classes/5-square.py | 5-square.py | py | 2,159 | python | en | code | 0 | github-code | 1 |
31241017265 | from PyQt5.QtWidgets import QWidget, QLabel, QPushButton
from PyQt5.QtWidgets import QVBoxLayout, QHBoxLayout, QGridLayout
from PyQt5.QtGui import QPixmap, QImage
import numpy as np
class Panel(QWidget):
def __PrivateMethod(self):
print("private method, value of")
return
def __init__(self)... | shane97luo/python_play | face_rec/ui/Panel.py | Panel.py | py | 2,168 | python | en | code | 0 | github-code | 1 |
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