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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30823116350 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.shortcuts import render, redirect, get_object_or_404
# from django.views.decorators.http import require_POST
from shop.models import Product
from .models import Cart, CartItem
# from .forms import CartAddProductForm
from django.contrib.auth.de... | studiosemicolon/onlineshop | cart/views.py | views.py | py | 2,091 | python | en | code | 23 | github-code | 6 |
13119405899 | from django.conf.urls import url, include
from . import views
from .models import *
from rest_framework import routers, permissions, serializers, viewsets
from oauth2_provider.ext.rest_framework import TokenHasReadWriteScope, TokenHasScope
class UserProfileSerializer(serializers.HyperlinkedModelSerializer):
class... | dammahom/matchpredict | gameapi/urls.py | urls.py | py | 1,075 | python | en | code | 0 | github-code | 6 |
37325658730 | '''
5. Write a Pandas program to convert a dictionary to a Pandas series.
'''
dict1 = {"First Name" : ["Kevin","Lebron","Kobe","Michael"],
"Last Name" : ["Durant","James","Bryant","Jordan"],
"Team" : ["Brooklyn Nets","Los Angeles Lakers","Los Angeles Lakers","Chicago Bulls"]
}
import pandas a... | ErenBtrk/Python-Fundamentals | Pandas/PandasDataSeries/Exercise5.py | Exercise5.py | py | 371 | python | en | code | 0 | github-code | 6 |
5308409788 | ## adsbib.py
## A tool for collecting BibTeX records from NASA ADS.
##
## Call with reference to a plaintext list of bibcodes,
## separated by newlines. Output will be to the same
## filename, appended with .bib
## >> python3 ads-bib.py bibcodes
##
## Note : To strip an existing BibTeX file down to bibcodes with vi... | lowderchris/ads-bib | ads-bib.py | ads-bib.py | py | 959 | python | en | code | 0 | github-code | 6 |
14255729146 | from _MOM import MOM
from _TFL import TFL
import _TFL._Meta.Object
import _TFL._Meta.Once_Property
from _TFL.predicate import first, paired
from _TFL.Decorator import getattr_safe
from _TFL.I18N import _, _T, _Tn
import itertools
import logging
class Entity (TFL.Meta.Object) :
... | xiaochang91/tapyr | _MOM/E_Type_Manager.py | E_Type_Manager.py | py | 20,532 | python | en | code | 0 | github-code | 6 |
17043247074 | # https://atcoder.jp/contests/dp/tasks/dp_a
N = int(input())
h = list(map(int, input().split()))
cost = [0] * N
for i in range(1, N):
if i == 1:
cost[i] = abs(h[i] - h[i - 1]) + cost[i - 1]
else:
cost[i] = min(
abs(h[i] - h[i - 1]) + cost[i - 1], abs(h[i] - h[i - 2]) + cost[i - 2]
... | atsushi-matsui/atcoder | best_choise/dp/dp_a.py | dp_a.py | py | 349 | python | en | code | 0 | github-code | 6 |
32583976944 | import json
import logging
import os
import threading
from time import sleep
from tqdm import tqdm
from logger import get_logger
machines = [
'4GB-rpi-4B-alpha',
'4GB-rpi-4B-beta',
'2GB-rpi-4B-beta',
'2GB-rpi-4B-alpha',
'cloud1',
'cloud2',
'desktop-remote'
]
ips = {
'4GB-rpi-4B-alpha'... | Cloudslab/FogBus2 | containers/experiment.py | experiment.py | py | 11,903 | python | en | code | 17 | github-code | 6 |
6814540794 | from django.urls import path
from . import views
################################################################################
# Registering the app namespace...
# this will allow you to create dynamic Django hyperlinks in html files
# when using the django tag: {% url atomic:tracker ... %} for example.
app_name = ... | chinchay/habit-tracker | backend/atomic/urls.py | urls.py | py | 669 | python | en | code | 0 | github-code | 6 |
71484222588 | class UnionFindTree:
"""Disjoint-Set Data Structure
Union-Find Tree
complexity:
init: O(n)
find, unite, same: O(alpha(n))
used in SRM505 div.2 900, ATC001 A, DSL1A(AOJ)
"""
def __init__(self, n):
self.par = list(range(n)) # parent
self.rank = [0] * n... | knuu/competitive-programming | atcoder/abc/abc131_f.py | abc131_f.py | py | 1,339 | python | en | code | 1 | github-code | 6 |
45561392364 | import csv
CSV_PATH =""
reader = csv.reader(opne(CSV_PATH, 'rt', encoding='cp494'), delimiter="|")
columns = next(reader)
for idx, row in enumerate(reader):
row = dict(zip(columns, row))
print(data['우편번호'])
if idx > 100:
break
#만약 db에 있는 데이터를 가져 오는 경우라면
'''
유니코드로 사용하다가 데이터를 가장 마지막에 밖으로 내보내... | rheehyerin/programming_hw | read_file.py | read_file.py | py | 670 | python | ko | code | 0 | github-code | 6 |
646604887 | import copy
import logging
import os
from gunpowder.caffe.net_io_wrapper import NetIoWrapper
from gunpowder.ext import caffe
from gunpowder.nodes.generic_predict import GenericPredict
from gunpowder.volume import VolumeType, Volume
logger = logging.getLogger(__name__)
class StupidPredict(object):
'''Augments a ... | constantinpape/gunpowder-experiments | experiments/inference/stupid_predict.py | stupid_predict.py | py | 2,500 | python | en | code | 0 | github-code | 6 |
19373198646 | import time
from selenium import webdriver
from selenium.webdriver.common.by import By
url = 'http://parsinger.ru/selenium/1/1.html'
text = ['Name', 'Surname', 'Sursurname', 'Age', 'City', 'EMAIL']
with webdriver.Chrome() as browser:
browser.get(url)
inputs = browser.find_elements(By.CLASS_NAME, 'form')
... | spac3orange/Web-parsing-study | Selenium/search_elements/tasks/task1_5sek.py | task1_5sek.py | py | 496 | python | en | code | 1 | github-code | 6 |
39209939169 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import math
from scipy.interpolate import griddata
import copy
# import tecplot as tp
# with open('Rectangle_EXP.dat') as Rectangle_EXP:
# all_data =
# D rectangle = 100
def load_data(fname):
# To load tecplot dat to datafram... | hmharley/FlowData_processing_py | source/Plot.py | Plot.py | py | 7,313 | python | en | code | 0 | github-code | 6 |
71454711549 | import os
import sys
if len(sys.argv) == 1:
f1 = open("newdummy.txt", 'w+')
f1.write("This is new file text. This will be re-read once again.")
f1.seek(0)
print("We wrote the following:")
print(f1.read())
f1.close()
else:
print("Too many or too few arguments.")
| axmenon/python-training | linux_rw.py | linux_rw.py | py | 315 | python | en | code | 0 | github-code | 6 |
28774253567 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: Leonardo La Rocca
"""
import melopero_RV_3028 as mp
import datetime
import gpiozero as gpio
from signal import pause
def main():
# First initialize and create the rtc device
rtc = mp.RV_3028()
# Set the device to use the 24hour format (default) ... | melopero/Melopero_RV-3028 | examples/alarm_interrupt_example.py | alarm_interrupt_example.py | py | 1,795 | python | en | code | 2 | github-code | 6 |
2124151948 | import asyncio
import inspect
import sys
import json
import socket
from contextlib import redirect_stdout, suppress
from traceback import format_exc
from typing import Dict, Callable
from copy import copy
from gornilo.models.api_constants import *
from gornilo.models.action_names import INFO, CHECK, PUT, GET, TEST
fr... | HackerDom/Gornilo | gornilo/actions.py | actions.py | py | 10,242 | python | en | code | 0 | github-code | 6 |
36242169771 | """
RUNBASE-IMP
HTML scraping bot for monitoring Adidas Runners events
Author: Francesco Ramoni
francesco[dot]ramoni@email.it
https://github.com/framoni/
"""
import json
from lxml import html
from selenium import webdriver
import time
from twilio.rest import Client
#-------------------------------... | framoni/runbase-imp | main.py | main.py | py | 3,011 | python | en | code | 0 | github-code | 6 |
29456733472 | from __future__ import print_function
import sys
from atrope import exception
from atrope.cmd import image_list
from atrope.cmd import version
from oslo_config import cfg
from oslo_log import log
CONF = cfg.CONF
def add_command_parsers(subparsers):
image_list.CommandImageListIndex(subparsers)
image_list.C... | alvarolopez/atrope | atrope/cmd/commands.py | commands.py | py | 1,235 | python | en | code | 2 | github-code | 6 |
73652308669 | # 给你一个 只包含正整数 的 非空 数组 nums 。请你判断是否可以将这个数组分割成两个子集，使得两个子集的元素和相等。
class Solution(object):
def canPartition(self, nums):
"""
:type nums: List[int]
:rtype: bool
"""
sumnums = 0
for i in nums:
sumnums += i
if sumnums % 2 != 0:
return False
... | xxxxlc/leetcode | Dynamicprogramming/canPartition.py | canPartition.py | py | 980 | python | en | code | 0 | github-code | 6 |
42929655074 | from collections import defaultdict
class Solution:
def accountsMerge(self, accounts):
email_accounts_map = defaultdict(list)
visited_accounts = [False]*len(accounts)
result = []
for i, account in enumerate(accounts):
for j in range(1, len(account)):
ema... | shwetakumari14/Leetcode-Solutions | Miscellaneous/Python/721. Accounts Merge.py | 721. Accounts Merge.py | py | 1,279 | python | en | code | 0 | github-code | 6 |
1796292061 | from hashlib import md5
from typing import Union
def hash_encode(data: Union[str, bytes],
return_bytes: bool = False) -> Union[str, bytes]:
if isinstance(data, str):
data = data.encode()
output = md5(data)
return output.digest() if return_bytes else output.hexdigest()
| FZQ0003/Qi-Bot | utils/hash.py | hash.py | py | 307 | python | en | code | 1 | github-code | 6 |
37373995341 | #!/usr/bin/env python
"""
ONS Address Index - Land Registry Data
======================================
A simple script to process land registry sales data.
The original data were downloaded on the 10th of November from:
https://data.gov.uk/dataset/land-registry-monthly-price-paid-data
Because the AddressBased used b... | ONSdigital/address-index-data | DataScience/Analytics/data/landRegistryData.py | landRegistryData.py | py | 4,514 | python | en | code | 18 | github-code | 6 |
41978220901 | from task_3 import Bucket, Unbucketed, JoinBuckets
from pyspark.sql import SparkSession
from pyspark.sql.types import StructType, StructField, StringType, DateType, IntegerType
from datetime import datetime
import pytest
spark = SparkSession.builder.appName("Clients").getOrCreate()
# schema for trx_table
... | rkrvchnk/pyspark_tasks | tests/test_task_3.py | test_task_3.py | py | 2,853 | python | en | code | 0 | github-code | 6 |
3690450175 | class NumericSolverModelResults:
def __init__(self, model_name, model, X, P, S, V, t, dt, non_dim_scaler):
"""
model_name é algo como "euler" ou "runge_kutta"
O resto são os parâmetros de solução numérica
"""
self.model_name = model_name
self.model = model
sel... | takenoto/pinn_la_casei_2023 | domain/numeric_solver/numeric_solver_model_results.py | numeric_solver_model_results.py | py | 476 | python | pt | code | 0 | github-code | 6 |
11005307998 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import math
import seaborn as sns
from numpy.random import rand
from sklearn import preprocessing
from sklearn import metrics, svm
from sklearn.metrics import plot_confusion_matrix, precision_score
from collections import Counter
from sklearn.linea... | xixihaha1995/cosc5555 | proposal/simpleLogistic.py | simpleLogistic.py | py | 7,185 | python | en | code | 0 | github-code | 6 |
5430866729 | from airflow import DAG
from datetime import datetime, timedelta
from airflow.operators.python import PythonOperator
default_args = {
'owner': 'airflow',
'start_date': datetime(2023, 7, 16),
'retries': 1,
}
def print_hello():
return "Hello World from Airflow!"
dag = DAG(
dag_id="hello_airflow",... | tejas7777/RobinHood | dags/test.py | test.py | py | 594 | python | en | code | 0 | github-code | 6 |
1549161757 | import numpy as np
import pickle
import os
import random
from compute_pairwise_dataset import compute_pairwise_dataset
import torch
from utils import get_torch_device
def save_dataset(qids, X, y, folder):
"""
Save the dataset in the provided folder.
"""
if not os.path.exists(folder):
os.mkdir(... | catalinlup/learning-to-rank | src/data_loaders.py | data_loaders.py | py | 4,938 | python | en | code | 0 | github-code | 6 |
43694416643 | from django import template
from django.contrib.contenttypes.models import ContentType
from notification_channels.models import Notification
register = template.Library()
""" Notification tags """
@register.simple_tag(name='get_all_notifs')
def get_all_notifs(user):
return user.notifications.all().order_by("-... | Velle-log/FusionIIIT | FusionIIIT/notification_channels/templatetags/notif_tags.py | notif_tags.py | py | 3,084 | python | en | code | 13 | github-code | 6 |
24812924597 | from selenium import webdriver
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.by import By
from selenium.webdriver.common.action_chains import ActionChains
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from ... | IldarKhuzin/selenium_7 | lenta.py | lenta.py | py | 1,400 | python | en | code | 0 | github-code | 6 |
36275046877 | import pygame
SCROLLBAR_THICKNESS = 20
BUTTON_SCROLL_WHEEL_UP = 4
BUTTON_SCROLL_WHEEL_DOWN = 5
SCROLL_SPEED = 20
VSPACE = 20
class ScrolledPanel(pygame.Surface):
def __init__(self, display, x, y, width, height, vspace=VSPACE, background_color=(255, 255, 255)):
pygame.Surface.__init__(self, (width, height))
... | Timtam/cards-against-humanity | client/scrolled_panel.py | scrolled_panel.py | py | 6,728 | python | en | code | 4 | github-code | 6 |
18536127088 | import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
input_file_aclevel = '/exports/humgen/idenhond/data/basenji_preprocess/human_atac_targets_Ac-level_cluster.csv'
df_aclevel = pd.read_csv(input_file_aclevel, sep = '\t').rename(columns = {'Unnamed: 0' : 'Index per level'})
df_aclevel_test = pd.re... | icdh99/LUMC_internship_enformer_continual | enformer/correlation/plots_paper/correlation_atac.py | correlation_atac.py | py | 9,010 | python | en | code | 0 | github-code | 6 |
30410039881 | from Node import *
from bitarray import bitarray
import os
def alphabet_frequency(nom_fichier) -> dict:
"""Renvoies un dictionnaire comportant les caractères du texte dans l'ordre de fréquence croissante puis si deux caractères ont le même nombre d'apparition, par leur ordre dans l'alphabet ASCII
Args:
... | ArthurOnWeb/Codage-de-Huffman-PROJ631- | Main.py | Main.py | py | 5,011 | python | fr | code | 0 | github-code | 6 |
8451903556 | from pyrogram import Client, idle, enums
import json
from userbot import app, Db
from config import *
from userbot import UPSTREAM_REPO
import sys
import requests
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from random import choice
import base64
async def keep_alive():
url = "https://ap... | LavanderProjects/XUserBot | userbot/__main__.py | __main__.py | py | 2,355 | python | en | code | 4 | github-code | 6 |
15548163858 | import argparse
import itertools
import json
import logging
import sys
from pathlib import Path
from server.src.pdf_tools_core import Document, set_log_level
log = logging.getLogger()
log_handler = logging.StreamHandler()
log.addHandler(log_handler)
log_handler.setFormatter(logging.Formatter('%(levelname)s: %(messag... | lukasstorck/py-pdf-tools | pdf_tools_cli.py | pdf_tools_cli.py | py | 4,787 | python | en | code | 0 | github-code | 6 |
22493469406 | import logging
from pathlib import Path
from yapsy.PluginManager import PluginManager
def get_module_logger():
return logging.getLogger(__name__)
THIS_PATH = Path(__file__).parent
modules_plugin_manager = PluginManager()
modules_plugin_manager.setPluginPlaces([str(THIS_PATH)])
modules_plugin_manager.collectP... | cryptologyrooms/raat | raat/modules/__init__.py | __init__.py | py | 1,189 | python | en | code | null | github-code | 6 |
655699777 | import os
import numpy as np
import torch_em
from . import util
CREMI_URLS = {
"original": {
"A": "https://cremi.org/static/data/sample_A_20160501.hdf",
"B": "https://cremi.org/static/data/sample_B_20160501.hdf",
"C": "https://cremi.org/static/data/sample_C_20160501.hdf",
},
"reali... | constantinpape/torch-em | torch_em/data/datasets/cremi.py | cremi.py | py | 4,761 | python | en | code | 42 | github-code | 6 |
19007770169 | import traceback,json,pdb
from datetime import date,timedelta,datetime
import pandas as pd
from flask import jsonify
from backEnd.database.db_connection import set_connection
from answergen import create_single_column_response,create_multi_column_response,get_highlight_response
from frontendAPI import city_region_mappi... | divakar-yadav/Backend-APIs | frontendAPI/executor.py | executor.py | py | 11,994 | python | en | code | 0 | github-code | 6 |
42589875789 | def medias(records):
soma = 0
num = 0
for a in records[2]:
soma += a
num += 1
medias = soma/num
return medias
def sort_grades(records):
names = sorted(records)
by_order_records = tuple(sorted(names, key=medias, reverse = True))
return by_order_records | JoaoCarlosPires/feup-fpro | grades.py | grades.py | py | 307 | python | en | code | 0 | github-code | 6 |
1772299948 | from __init__ import CURSOR, CONN
import string
class Group:
CONTINENT = {
"Bettle": ["Burg", "Hommoch", "Lei"],
"Jidoth": ["Lord's Port", "Oth", "Tirena", "Videlsen"],
"Mollen": ["Aldon", "Exigot", "Len City", "Pelta", "The Villages Of Southern Aldon", "Vanna's Perch"],
"Rise": ["... | regisaslewis/adventurers-unite | group.py | group.py | py | 6,305 | python | en | code | 1 | github-code | 6 |
22319846051 | import argparse
import os
from . import _argparse
__version__ = '0.0.1'
_BUFSIZ = 4096 * 16
STDIN_FILENO = 0
STDOUT_FILENO = 1
STDERR_FILENO = 2
def do_cat(ifd, ofd, *, unbuffered):
# Currently, always act as if `unbuffered` is True.
while True:
buf = os.read(ifd, _BUFSIZ)
if not buf:
... | o11c/python-coreutils | coreutils/cat.py | cat.py | py | 2,738 | python | en | code | 0 | github-code | 6 |
21738867922 | import time
start_time = time.time()
f = open("names_1.txt", "r")
names_1 = f.read().split("\n") # List containing 10000 names
f.close()
f = open("names_2.txt", "r")
names_2 = f.read().split("\n") # List containing 10000 names
f.close()
duplicates = [] # Return the list of duplicates in this data structure
# Re... | MarkHalls/Sprint-Challenge--Data-Structures-Python | names/names.py | names.py | py | 2,616 | python | en | code | 0 | github-code | 6 |
73825796027 | """
分类算法应用案例-汽车金融预测用户是否会贷款买车
"""
from sklearn import tree
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.neighbors import KNeighborsClassifier
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, auc
i... | ghostlyFeng/ML | Cluster/car.py | car.py | py | 4,212 | python | en | code | 0 | github-code | 6 |
23010318012 | __all__ = (
"__version__",
"AssumedDiagonalGraphTraversal",
"Edge",
"Flow",
"get_path_from_matrix",
"guess_production_exchanges",
"NewNodeEachVisitGraphTraversal",
"Node",
"path_as_brightway_objects",
"to_normalized_adjacency_matrix",
)
from .graph_traversal_utils import get_pat... | brightway-lca/bw_graph_tools | bw_graph_tools/__init__.py | __init__.py | py | 652 | python | en | code | 1 | github-code | 6 |
7894457497 | from flask import Flask, render_template, request
import os
import json
from nova_code import start_vm
from swift_code import upload_to_container, check_file_exists
container_upload = 'uploads'
container_download = 'rendered'
environ = json.load(open(os.environ['CRED_FILE']))['CONFIG']['CONFIG_VARS']
app = Flask(__na... | stepanvanecek/cah-blender | main.py | main.py | py | 1,784 | python | en | code | 1 | github-code | 6 |
73815172026 | import selenium.webdriver
from bonobo_selenium._version import __version__
USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_3) AppleWebKit/601.4.4 (KHTML, like Gecko) Version/9.0.3 Safari/601.4.4'
def create_profile(use_tor=False):
_profile = selenium.webdriver.FirefoxProfile()
_profile.set_prefer... | python-bonobo/bonobo-selenium | bonobo_selenium/__init__.py | __init__.py | py | 1,078 | python | en | code | 4 | github-code | 6 |
36609185341 | #!/usr/bin/env python
import re
def revert(text):
result = []
for word, space in re.findall(r'([^\s]*)(\s*)', text):
result += [i for i in reversed(word)]
result.append(space)
return ''.join(result) | raimu/code-kata | python/BackwardsTalk/backward_talk.py | backward_talk.py | py | 228 | python | en | code | 0 | github-code | 6 |
31315499323 | ###########
# This script builds the database for the web visualization
# It can take a long time to run, so it is recommended to run it in the background
# Here we we are going to take a folder of ABF or NWB files, and extract some features
# we will choose to use a custom backend or ipfx to extract the features
# fro... | smestern/pyAPisolation | pyAPisolation/web_viz/build_database.py | build_database.py | py | 22,652 | python | en | code | 1 | github-code | 6 |
75114038906 | from timeit import default_timer as timer
import re
start = timer()
file = open('input.txt')
# exponential growth, every 7 days, after 0
# unsynchronized
# +2 day before first cycle
class LanternFish:
def __init__(self, initial_clock, spawn_clock, cycle):
self.clock = initial_clock
self.spawn = spawn_clock
se... | kmckenna525/advent-of-code | 2021/day06/part1.py | part1.py | py | 1,034 | python | en | code | 2 | github-code | 6 |
10933573696 | from copy import deepcopy
from ansible_collections.ansible.netcommon.plugins.module_utils.network.common import (
utils,
)
from ansible_collections.alliedtelesis.awplus.plugins.module_utils.network.awplus.argspec.banner.banner import BannerArgs
class BannerFacts(object):
""" The awplus banner fact class
... | alliedtelesis/ansible_awplus | plugins/module_utils/network/awplus/facts/banner/banner.py | banner.py | py | 2,915 | python | en | code | 7 | github-code | 6 |
27260781556 | #Script for the first experiment of the multi-channel DART paper
#In this experiment, the performance of MC-DART is investigated for different number of channels and materials in the phantom,
# all averaged over 100 runs.
#Author,
# Mathé Zeegers,
# Centrum Wiskunde & Informatica, Amsterdam (m.t.zeegers@cwi.n... | mzeegers/MC-DART | scripts/MCDARTExp1.py | MCDARTExp1.py | py | 8,833 | python | en | code | 0 | github-code | 6 |
75140441147 | import numpy as np
class GradientDescent():
def __init__(self, X, y, w, loss, batch_size = None, reg_lambda = 0, update_X = False, seed = None):
'''input:
X: (n, m)
y: (n, 1)
loss: instace of class with at least two methods: "compute_loss" and "derivative"
'''
np.ran... | Enrico4444/AlgosFromScratch | utils/gradient_descent.py | gradient_descent.py | py | 2,442 | python | en | code | 0 | github-code | 6 |
30060227014 | #! /usr/bin/env python3
'''
invocation: ram_gen.py -width 10 -depth 20 [-name myram] [-help] [-mon] [-addr Addr] [-din Din] [-dout Dout] [-wr wr | ~wr] [-cs cs | ~cs] [-clk Clk]
kmon will add $display lines to verilog to help keep track of writes/reads.
-din -dout -addr -cs -wr -clk : all these enable re... | greenblat/vlsistuff | pybin3/ram_gen.py | ram_gen.py | py | 6,540 | python | en | code | 41 | github-code | 6 |
1173013676 | from hand import Hand
from deck import Deck
class Play:
def play(self):
wins = 0
losses = 0
games_played = 0
cont = True
print("\n---------------------------------------------------------------------------------\n")
print("\n ... | IamFyrus/Blackjack | Blackjack/play.py | play.py | py | 4,509 | python | en | code | 0 | github-code | 6 |
33917530992 | from dateutil.parser import parse as parse_date
from flask import current_app
from inspire_dojson import record2marcxml
from inspire_utils.record import get_value
from lxml import etree
def dumps_etree(pid, record, **kwargs):
"""Dump MARC21 compatible record.
:param pid: The :class:`invenio_pidstore.models.Pe... | SCOAP3/scoap3-next | scoap3/modules/records/oai_serializer.py | oai_serializer.py | py | 1,264 | python | en | code | 2 | github-code | 6 |
33036426825 | """Config flow for UniFi."""
import socket
import voluptuous as vol
from homeassistant import config_entries
from homeassistant.const import (
CONF_HOST,
CONF_PASSWORD,
CONF_PORT,
CONF_USERNAME,
CONF_VERIFY_SSL,
)
from homeassistant.core import callback
import homeassistant.helpers.config_validati... | 84KaliPleXon3/home-assistant-core | homeassistant/components/unifi/config_flow.py | config_flow.py | py | 11,066 | python | en | code | 1 | github-code | 6 |
3439919651 | from sortedcontainers import SortedDict
class Node:
def __init__(self, val=None):
self.val = val
self.next = None
self.last = None
class MaxStack:
def __init__(self):
self.dic = SortedDict()
self.root = Node()
self.root.last, self.root.next = self.root... | cuiy0006/Algorithms | leetcode/716. Max Stack.py | 716. Max Stack.py | py | 1,463 | python | en | code | 0 | github-code | 6 |
74492711866 | num1 = int(input("Number 1: "))
num2 = int(input("Number 2: "))
factors1, factors2 = [], []
def factoriser(arr, num):
for i in range(num):
if num%(i+1) == 0 and i+1 != num:
arr.append(i+1)
factoriser(factors1, num1)
factoriser(factors2, num2)
if (sum(factors1) == num2) and (sum(factors2) == num1) and num... | Pararcana/British-Informatics-Olympiad-Python | 1996/Q1 - Amicable Numbers [E] .py | Q1 - Amicable Numbers [E] .py | py | 555 | python | en | code | 1 | github-code | 6 |
13041202153 | import falcon
import json
import logging
logger = logging.getLogger(__name__)
class Correlation:
def __init__(self, store):
self.__store = store
def on_get(self, req, resp):
params = req.params
logger.info('request: {}'.format(params))
if 'series1' not in params or 'series2'... | Qinode/final-visual-api | src/resources/data/corr.py | corr.py | py | 576 | python | en | code | 0 | github-code | 6 |
73076321467 | from __future__ import annotations
import os
from typing import Callable, TYPE_CHECKING
if TYPE_CHECKING:
from bot.translator import Translator
app_name = "TTMediaBot"
app_version = "2.3.1"
client_name = app_name + "-V" + app_version
about_text: Callable[[Translator], str] = lambda translator: translator.translat... | gumerov-amir/TTMediaBot | bot/app_vars.py | app_vars.py | py | 715 | python | en | code | 52 | github-code | 6 |
43959470416 | import datetime
import os
import random
import sys
from itertools import islice
from typing import List, Generator, Iterator
folder = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'ch03-mem-and-variables'))
sys.path.insert(0, folder)
import size_util
random.seed(42)
def main():
# Took 83 MB in n... | talkpython/python-memory-management-course | code/ch07-mem-and-functions/app_one_at_a_time.py | app_one_at_a_time.py | py | 1,496 | python | en | code | 39 | github-code | 6 |
71442915067 | import sys
import os
import logging
from datetime import datetime
from logging.handlers import TimedRotatingFileHandler
from logging import StreamHandler
from panda3d.core import (
loadPrcFile,
Filename,
ConfigVariableBool,
)
def setup_log(editor_name, log_to_console=False, log_level=logging.DEBUG):
... | fireclawthefox/FRAME | panda3d_frame/editorLogHandler.py | editorLogHandler.py | py | 2,086 | python | en | code | 12 | github-code | 6 |
70488681147 | # accepted on coderun
import random
import sys
import time
length: int # = 98
arr: list[int] # = [1, 1, 1, 2, 3, 3, 4, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 7]
s_tree_l: int # = 4 * length
max_tree: list[tuple[int, int]] # = [(0, 0) for _ in range(s_tree_l)]
postponed_update: list[tuple[int, int]]
p: int
def process_que... | LocusLontrime/Python | Yandex_fast_recruit_days/Hard/chunks_moving.py | chunks_moving.py | py | 4,264 | python | en | code | 1 | github-code | 6 |
70788138747 | import sys
import numpy as np
import util
from regression.linreg import NormalEquationLinearRegressor, GradientDescentLinearRegressor
from preprocess import reader, scaling
from validation import CrossValidator
def main():
if len(sys.argv) < 2:
print("Usage:\n\t{} [housing-data]".format(sys.argv[0]))
... | get9/ml-test | houselinreg.py | houselinreg.py | py | 1,227 | python | en | code | 1 | github-code | 6 |
72729149627 | import cv2
from skimage.metrics import structural_similarity as ssim
import numpy as np
from PIL import Image, ImageChops
import matplotlib.pyplot as plt
################################################################
########### USING PIXEL COMPARISON #########################
############## IMPORTANT TO REA... | joaofgois/saut_ogm | scripts/MapComparisonMetric.py | MapComparisonMetric.py | py | 4,169 | python | en | code | 0 | github-code | 6 |
13126975486 | #다익스트라 알고리즘 연습
#프로그래머스 합승 택시 요금
import sys
import heapq
# 다익스트라 알고리즘
def dijkstra(s, e):
global graph, length
# 방문한 노드를 최대값으로 세팅
visit = [sys.maxsize]*(length+1)
# start node는 0으로 바꾸어주고
visit[s] = 0
# 우선순위힙큐에 [cost, node]로 넣어준다
pq = [[0, s]]
heapq.heapify(pq)
... | 39world/Today-Algorithm-Study- | old_test/al_th_02.py | al_th_02.py | py | 1,747 | python | ko | code | 0 | github-code | 6 |
6690596464 | from json import load
with open('config.json', 'r') as file:
params = load(file)
BOT_TOKEN = params['BOT_TOKEN']
PARAMS = params['PARAMS']
SEARCH_URL = params['SEARCH_URL']
HOST = params['HOST']
PORT = params['PORT']
DB_NAME = params['DB_NAME']
| YusupovAI/TelegramBot | config.py | config.py | py | 274 | python | en | code | 0 | github-code | 6 |
22021057101 | from fractions import Fraction
from typing import Generic, TypeVar
import funcy
# generic `NamedTuple`s were only introduced in Python 3.11 - until then we need to
# import from `typing_extensions`
from typing_extensions import NamedTuple
from boiling_learning.io.dataclasses import dataclass
_T = TypeVar('_T')
cl... | ruancomelli/boiling-learning | boiling_learning/datasets/splits.py | splits.py | py | 1,911 | python | en | code | 7 | github-code | 6 |
39254020126 | import os
import rasterio
import geopandas as gpd
import shapely
from shapely.geometry import box
from tqdm import tqdm
def parse_txt(txt_dir):
"""
Read txt file.
bbox format - xmin, ymin, xmax, ymax (unnormalized).
Params:
txt_dir (str): path to text file containing bboxes.
... | unicef/Mongolia-school-mapping-AI-models | codes/geo_utils.py | geo_utils.py | py | 6,240 | python | en | code | 2 | github-code | 6 |
35253535585 | """
A list of utility functions for creating test and training datasets from labelled hyperspectral data. Note that we avoid implementing
specific supervised classification algorithms, as scikit-learn already does an excellent job of this. Hence, the following
functions are simply designed to easily extract features an... | hifexplo/hylite | hylite/analyse/supervised.py | supervised.py | py | 4,132 | python | en | code | 24 | github-code | 6 |
13703423658 | # pyedit
# create at 2015/6/14
# autor: qianqians
from tools import argv_instance
from pyelement import pyelement
class pyedit(pyelement):
# edit input type
text = "text"
password = "password"
textarea = "textarea"
#event
oninput = "oninput"
onkeydown = "onkeydown"
def __init__(self, cname, type, layout, pra... | theDarkForce/plask | plask/pyedit.py | pyedit.py | py | 2,205 | python | en | code | 2 | github-code | 6 |
74977717307 | import csv
import os
from datetime import datetime
import logging
import re
from dipper.sources.PostgreSQLSource import PostgreSQLSource
from dipper.models.assoc.Association import Assoc
from dipper.models.assoc.G2PAssoc import G2PAssoc
from dipper.models.Genotype import Genotype
from dipper.models.Reference import Ref... | monarch-initiative/dipper | dipper/sources/MGI.py | MGI.py | py | 99,120 | python | en | code | 53 | github-code | 6 |
30086443751 | import os
import pickle
import numpy as np
from .util import draw_roc
from .statistic import get_EER_states, get_HTER_at_thr
from sklearn.metrics import roc_auc_score
def eval_acer(results, is_print=False):
"""
:param results: np.array shape of (N, 2) [pred, label]
:param is_print: print eval score
:r... | VIS-VAR/LGSC-for-FAS | utils/eval.py | eval.py | py | 4,112 | python | en | code | 223 | github-code | 6 |
24556414335 | import json
from flask import Flask, jsonify, request
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func
from flask_bcrypt import Bcrypt
from flask_redis import FlaskRedis
app = Flask(__name__)
app.config['SECRET_KEY'] = 'ghjrhhrohirorthrtohi'
app.config['SQLALCHEMY_DATABASE_URI'] = "mysql://root:root... | Ankita2802/Quiz_backend | routes.py | routes.py | py | 9,890 | python | en | code | 0 | github-code | 6 |
22688604701 | from django.shortcuts import render, redirect, get_object_or_404
from django.contrib.auth.decorators import login_required
from .models import Product
from apps.customers.models import Customer
from django.views.decorators.http import require_POST
from .cart import Cart
from .forms import CartAddProductForm
@login_re... | ordemdigitale/django-crm-v2 | apps/shop/views.py | views.py | py | 2,148 | python | en | code | 1 | github-code | 6 |
32509272843 | import numpy as np
import matplotlib.pyplot as plt
from math import sqrt
import scipy.stats as sc
def myRho(T,n):
COV=0;
pq =0 ;
SY=0;
SX=0;
EX=sum(T[0][0:])/float(len(T[0][0:])) #La experence de x
EY=sum(T[1][0:])/float(len(T[1][0:])) #La experence de y
for i in range(n):
COV = COV ... | Varelafv/TD6.py | exo3.py | exo3.py | py | 1,511 | python | en | code | 0 | github-code | 6 |
20678009932 | from django.test import TestCase
from django.urls import reverse
from apps.articles.models import Tag
from apps.users.models import CustomUser
from .models import Tool
# Create your tests here.
test_tool = {
"name": "tool_name",
"slug": "tool_slug",
"description": "tool_description",
"img_link": "htt... | akundev/akundotdev | apps/tools/tests.py | tests.py | py | 4,039 | python | en | code | 0 | github-code | 6 |
39830056794 | import sys
from collections import deque
sys.setrecursionlimit(10**7)
n = int(sys.stdin.readline().rstrip())
k = int(sys.stdin.readline().rstrip())
graph = [[0] * n for _ in range(n)]
direction = deque()
moves = [[0, 1], [1, 0], [0, -1], [-1, 0]]
snake = deque()
for i in range(k):
x, y = map(int, sys.stdin.read... | omg7152/CodingTestPractice | Etc/Snake_3190.py | Snake_3190.py | py | 1,660 | python | ko | code | 0 | github-code | 6 |
70926690428 | """
youtube_downloader.py notes:
- May occasionally have errors. Just re-run.
- Caches to prevent duplicate downloading of videos.
"""
from pytube import YouTube
def download_youtube(video_url, videoname='0'):
if check_cache(video_url):
print(f"youtube_downloader.py: Video already exists.")
retur... | jetnew/carelytics | video_indexer/youtube_downloader.py | youtube_downloader.py | py | 1,291 | python | en | code | 3 | github-code | 6 |
40281678144 | colors = {
'gray' :( 0.56862745, 0.56862745, 0.56862745, 1),
'orange':( 0.96470588, 0.34509804, 0.05882352, 1),
'green' :( 0.50196078, 0.91372549, 0.09019607, 1),
'white' :( 0.8 , 0.8, 0.8, 1),
'yellow' :( 1.0, 0.792156862745098, 0.0941176470588235, 0.3... | NunoSilvaa/AI_project | model/tiles.py | tiles.py | py | 1,742 | python | en | code | 0 | github-code | 6 |
29214477520 | import pytest
from datetime import datetime
from ..forms import PostForm, CategoryForm, CommentForm
from accounts.models import Profile, User
from ..models import Post
@pytest.fixture
def create_test_user():
data = {"email": "test@test.com", "password": "a/1234567"}
return User.objects.create_user(**data, is... | smz6990/DRF-Blog | core/blog/tests/test_forms.py | test_forms.py | py | 3,203 | python | en | code | 2 | github-code | 6 |
36164982911 | from PyQt6 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(1500,200)
MainWindow.setStyleSheet("background-color: #282828")
self.centralwidget = QtWidgets.QWidget(MainWindow)... | Framon64/CryptoProgram | programWindow.py | programWindow.py | py | 11,677 | python | en | code | 0 | github-code | 6 |
35816996435 | """
chemreac.util.pyutil
--------------------
Utility functions used throughout chemreac.
"""
from __future__ import (absolute_import, division, print_function)
import sys
import numpy as np
import time
def monotonic(arr, positive=0, strict=False):
"""
Check monotonicity of a serie
Parameters
---... | chemreac/chemreac | chemreac/util/pyutil.py | pyutil.py | py | 4,068 | python | en | code | 14 | github-code | 6 |
15415931528 | import turtle
angles = [60, -120, 60, 0]
size_of_snowflake = 300
def get_input_depth():
massage = "Please provide the depth: "
value = input(massage)
while not value.isnumeric():
print("Input must ne positive integer!!!")
value = input(massage)
return int(value)
def setup... | singh-hemant/python-turtle-examples | koch_snowflake.py | koch_snowflake.py | py | 1,025 | python | en | code | 0 | github-code | 6 |
10114743152 | from __future__ import annotations
from typing import Tuple
import stage.tile_types as tile_types
from stage.game_map import GameMap
class Room:
"""Klass för att representera ett rektangulärt rum"""
def __init__(self, x: int, y: int, width: int, height: int) -> None:
self.x1 = x
self.y1 = y... | programmerare93/Dungeons_of_Kwargs | src/stage/rooms.py | rooms.py | py | 1,435 | python | sv | code | 4 | github-code | 6 |
17944469658 | import tensorflow as tf
from keras.layers.convolutional import Conv2D, MaxPooling2D
from keras.layers.core import Dense, Activation, Flatten
# import tensorflow as tf
# tf.python.control_flow_ops = tf # some hack to get tf running with Dropout
# 224x224
def alex_net_keras(x, num_classes=2, keep_prob=0.5):
x = C... | CharlesLoo/stockPrediction_CNN | alexnet_keras.py | alexnet_keras.py | py | 1,831 | python | en | code | 13 | github-code | 6 |
6727933661 | ###In this script I combined the raw features of colone and humanbonmarrow to run with Height GWAS summary statistics
#importing the imprtant maduals
import pandas as pd
import numpy as np
import os
from pathlib import Path
arr = os.listdir('combine')
out_dir = Path("combine")
for file in arr:
new_na... | molgenis/benchmark-gwas-prio | prioritization_methods/PoPS/Combine hbm_colon_rawfeatures.py | Combine hbm_colon_rawfeatures.py | py | 926 | python | en | code | 0 | github-code | 6 |
38813070065 | from glob import glob
from math import fabs
sum = 0
count = 0
abs = 0
for file in glob('data/*'):
for line in open(file):
(date, time, symbol, price, qty, eott) = line.strip().split(' ')
price = float(price)
qty = int(qty)
if date < '20170601' or date > '20180201': continue
... | KaedeTai/exercise1 | exercise1.py | exercise1.py | py | 493 | python | en | code | 0 | github-code | 6 |
73400038269 | #!/usr/bin/env python2
import sys
sys.path.insert(0, '/root/jhbuild')
import jhbuild.main
import jhbuild.moduleset
from jhbuild.versioncontrol.git import GitBranch
import __builtin__
import json
__builtin__.__dict__['SRCDIR'] = '/root/jhbuild'
__builtin__.__dict__['PKGDATADIR'] = None
__builtin__.__dict__['DATADIR'] ... | benwaffle/gnome-hound | gen-conf.py | gen-conf.py | py | 878 | python | en | code | 0 | github-code | 6 |
29913794129 | #
# VIK Example file for working with date information
#
import os
import calendar
from datetime import date, time, datetime
def main():
os.system('clear')
## DATE OBJECTS
# Get today's date from the simple today() method from the date class
# today = date.today()
# print("Today's date is", date.today())
... | VikramDMello/Python-Learning | src/Lynda.com Exercise Files/Ch3/dates_start.py | dates_start.py | py | 3,633 | python | en | code | 0 | github-code | 6 |
35976263312 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Oct 14 19:54:28 2018
@author: andychen
"""
a=int(input("a:"))
b=int(input("b:"))
if b!=0:
b,a=a%b,b
print(a)
| czh4/Python-Learning | exercise/exercise3-3.py | exercise3-3.py | py | 181 | python | en | code | 1 | github-code | 6 |
39717267724 | from enum import Enum
class VarTypes(Enum):
INT = "int"
FLOAT = "float"
BOOL = "bool"
STRING = "string"
VECTOR = "vector"
VOID = "void"
class Ops(Enum):
POW = "^"
NEG = "neg"
POS = "pos"
NOT_ = "not"
MAT_MULT = "@"
DOT = ".."
MULT = "*"
DIV = "/"
INT_DIV =... | Irvel/doflir | SemanticCube.py | SemanticCube.py | py | 6,726 | python | en | code | 0 | github-code | 6 |
25854008404 | #!/usr/bin/env python
# coding: utf-8
# In[38]:
#this code takes all the raw text files outputted from AWS textract
#and combines them into one long text file and re-separates them
#so there are not multiple apps in one document
#get the raw text file output for each pdf file and append the data to one huge text ... | avadodd/ocr_doc_scanning | split_docs.py | split_docs.py | py | 1,271 | python | en | code | 0 | github-code | 6 |
38775154404 | import random
import os
import cv2
import numpy as np
import pickle
from matplotlib import style
from AI_KNearestAlogrithm import Classifier
np.set_printoptions(threshold=np.inf, suppress=True)
style.use('fivethirtyeight')
class FacialClassifier:
def __init__(self):
self.frame_array = []
... | olusegvn/Defence-and-Privacy-mechanisms | AI_FacialRecognition.py | AI_FacialRecognition.py | py | 6,190 | python | en | code | 0 | github-code | 6 |
25352417620 | # coding: utf-8
__author__ = "humkyung <humkyung@atools.co.kr>"
# Imports
import os, sys
import vtk
from enum import IntEnum
class NetworksJsonImporter:
KEY = vtk.vtkInformationStringVectorKey.MakeKey('Attribute', 'vtkActor')
def __init__(self):
self._file_path = None
self._nodes = {}
... | humkyung/AViewer | NetworkxJson/NetworkxJsonImporter.py | NetworkxJsonImporter.py | py | 2,564 | python | en | code | 2 | github-code | 6 |
18803588453 | from django.urls import path, include
from watchlist_app.api import views
from rest_framework.routers import DefaultRouter
router = DefaultRouter()
router.register('stream', views.StreamPlatformVS,
basename='streamplatform')
urlpatterns = [
path('list/', views.WatchListAV.as_view(), name='Watch-l... | aliesmaeli79/watchmateAPI | watchlist_app/api/urls.py | urls.py | py | 1,206 | python | en | code | 1 | github-code | 6 |
24681181962 | import streamlit as st
from transformers import T5Tokenizer, T5ForConditionalGeneration
from transformers import pipeline
import torch
#model and tokenizer loading
checkpoint = "LaMini-Flan-T5-248M"
tokenizer = T5Tokenizer.from_pretrained(checkpoint)
base_model = T5ForConditionalGeneration.from_pretrained(checkpoint,... | Shoaib-Alauudin/Text-Summarization-Using-LLM | app.py | app.py | py | 1,650 | python | en | code | 0 | github-code | 6 |
38358782751 | # -*- coding: utf-8 -*-
"""
Created on Sun Oct 29 16:52:22 2017
@author: prver
"""
import pandas as pd
import seaborn as sns
#Import Jan 2017 Turnstile Data and Group By Station/Time
fields = ['Station', 'Time', 'Entries',
'Exits']
df = pd.read_csv('Jan2017.csv', header=0, skipinitialspace=True, ... | jxyu90/piggly-wiggly | TurnSample.py | TurnSample.py | py | 1,509 | python | en | code | 0 | github-code | 6 |
6486476570 | #!/usr/local/bin/python
# -*- coding: utf-8 -*-
from django.shortcuts import render_to_response
from django.template import RequestContext
from lavidaorganic.apps.talleres.models import Taller
from paypal.standard.forms import PayPalPaymentsForm
from django.shortcuts import get_object_or_404
import datetime
def taller... | Reston/lavidaorganic | lavidaorganic/lavidaorganic/apps/talleres/views.py | views.py | py | 1,372 | python | en | code | 0 | github-code | 6 |
37528229182 | import bs4 as bs
from urllib import request
def get_urls(file):
f = open(file,"r")
urls = []
for line in f.readlines():
urls.append(line)
return urls
def enter_urls(file,urls):
f = open(file,'w')
for url in urls:
f.write(url+'\n')
f.close()
def make_unique(... | stefanivus/Web-scraping | Web Cralwer.py | Web Cralwer.py | py | 1,017 | python | en | code | 0 | github-code | 6 |
23204188996 | import re
with open('input.txt') as infile:
claims = [claim.strip() for claim in infile.readlines()]
fabric = [[{'claimed_by': [], 'num_claims': 0} for x in range(1001)] for y in range(1001)]
claim_re = re.compile("#(\d+)\s@\s(\d+),(\d+):\s(\d+)x(\d+)")
claimants = list()
for claim in claims:
match = claim_re.... | jandersson/AdventOfCode2018 | 3/fabric_slicing.py | fabric_slicing.py | py | 1,209 | python | en | code | 0 | github-code | 6 |
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