Discover gists

(It's not a file, do this before using)

Have D3.js v4 implement in your project first.
npm install --save d3-sankey

npm install --save @types/d3-sankey

Backend as a Service

Supabase - ~52K stars

Designed explicitly as an open source firebase alternative
Typescript based
Docker support

Appwrite - ~32K stars

Written in JavaScript and PHP
Docker based
Realtime support across all services

Conventional Commit Messages

See how a minor change to your commit message style can make a difference.

Tip

Have a look at git-conventional-commits , a CLI util to ensure these conventions and generate verion and changelogs

Commit Message Formats

Default

Moved to git repository: https://github.com/denji/nginx-tuning

NGINX Tuning For Best Performance

For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.

Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.

You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.

Paprika doesn't have their API documented, so this is me reverse-engineering it from an Android device

Live Demo

https://knowing-grain.glitch.me/

Code: https://glitch.com/edit/#!/knowing-grain

Sync

Gilbert–Johnson–Keerthi (GJK) 3D distance algorithm

The Gilbert–Johnson–Keerthi (GJK) distance algorithm is a method of determining the minimum distance between two convex sets. The algorithm's stability, speed which operates in near-constant time, and small storage footprint make it popular for realtime collision detection.

Unlike many other distance algorithms, it has no requirments on geometry data to be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplices to the correct answer using the Minkowski sum (CSO) of two convex shapes.

	# Copyright (c) Meta Platforms, Inc. All Rights Reserved

	import math
	import os
	import signal
	import sys
	import traceback
	from pathlib import Path
	from random import randint
	import datetime

	# Copyright (c) Meta Platforms, Inc. All Rights Reserved

	import math

	import numpy as np
	import scipy
	import torch.multiprocessing
	from pathlib import Path
	import torch
	import hydra

	<?php
	/**
	* Add rest api endpoint for category listing
	*/

	/**
	* Class Category_List_Rest
	*/
	class Category_List_Rest extends WP_REST_Controller {
	/**

	#!/usr/bin/env bash

	# Abort sign off on any error
	set -e

	# Start the benchmark timer
	SECONDS=0

	# Repository introspection
	OWNER=$(gh repo view --json owner --jq .owner.login)