| from django.contrib.auth.models import AnonymousUser | |
| from django.db import close_old_connections | |
| from django.conf import settings | |
| from channels.sessions import CookieMiddleware | |
| from channels.db import database_sync_to_async | |
| from rest_framework_simplejwt.authentication import JWTAuthentication | |
| import logging | |
| logger = logging.getLogger(__name__) |
| import torch as th | |
| """ | |
| Author: Josue N Rivera (github.com/wzjoriv) | |
| Date: 7/3/2021 | |
| Description: Snippet of various clustering implementations only using PyTorch | |
| Full project repository: https://github.com/wzjoriv/Lign (A graph deep learning framework that works alongside PyTorch) | |
| """ | |
| def random_sample(tensor, k): |
| HAI 1.2 | |
| OBTW | |
| CODED BY ./MEICOOKIES | |
| TLDR | |
| O HAI IM WEEB | |
| HOW IZ I SEX YR WAIFU AN YR CUM | |
| CUM, WTF? | |
| OMG "1" |
Many people state that kivy is slow. While this may be true it is mostly due to that python is slow to run on android devices.Thus it is in the programmer's hands to properly optimize their code so as to create a performant application.
Most of the lag on android devices runing kivy apps arise due to widget creation. Widget creation remains the slowest step in a kivy app. Here are some of the methods that I follow to optimize my apps and ensure I can hit 60fps even on old devices
| <script> | |
| import {trapFocus} from "./trapFocus"; | |
| </script> | |
| <div use:trapFocus> | |
| <button>Hi!</button> | |
| <button>Second button</button> | |
| </div> |
| import httpx | |
| from starlette.requests import Request | |
| from starlette.responses import StreamingResponse | |
| class Proxy: | |
| def __init__(self, hostname): | |
| self.hostname = hostname | |
| self.client = httpx.AsyncClient() |
| ## | |
| ## How to run multiple uvicorn server apps in the same process | |
| ## | |
| import asyncio | |
| from uvicorn import Server, Config | |
| class MyServer(Server): | |
| async def run(self, sockets=None): | |
| self.config.setup_event_loop() | |
| return await self.serve(sockets=sockets) |
ramips: add support for Asus RT-N11P / RT-N12+ / RT-N12E b1
This is a variant of the MT7620N-based Asus routers.
Specifications:
