Billy Ma billyma128

WebM to MP4 using FFmpeg

This FFmpeg command converts a .webm video file to a standard .mp4 file using the libx264 codec for video, aac codec for audio, and a CRF value of 22. The preset is set to 'slow' for higher quality encoding, and the audio bitrate is set to 128 kbps.

If the input and output filenames don't contain spaces, quotation marks or other special characters:

ffmpeg -i input.webm -c:v libx264 -preset slow -crf 22 -c:a aac -b:a 128k output.mp4

Current (2023-03-01) OpenAI Whisper API expects a file uploaded as part of multipart/form-data in POST request. I initially struggled to use this API inside Node.js with an audio file stored inside an AWS s3 bucket, so I decided to share this snippet:

The API usage example from the OpenAI docs:

curl --request POST \
  --url https://api.openai.com/v1/audio/transcriptions \
  --header 'Authorization: Bearer TOKEN' \
 --header 'Content-Type: multipart/form-data' \

For some reason, it is surprisingly hard to create a bootable Windows USB using macOS. These are my steps for doing so, which have worked for me in macOS Monterey (12.6.1) for Windows 10 and 11. After following these steps, you should have a bootable Windows USB drive.

1. Download a Windows disc image (i.e. ISO file)

You can download Windows 10 or Windows 11 directly from Microsoft.

2. Identify your USB drive

After plugging the drive to your machine, identify the name of the USB device using diskutil list, which should return an output like the one below. In my case, the correct disk name is disk2.

Example of Domain-Driven Design in Rails

Object

Name	Layer	Type	Description
app/models/visitor_pass.rb	Domain	Aggregate	Pass-related domain
app/services/tracker_service.rb	Domain	Domain Service	Logic between `door` and `visitor` interaction
app/controllers/passes_controller.rb	Application	Use Case	The user flow of "pass" a door

Kubernetes

Install

Prerequisites

Bash v5+ checkout Upgrading Bash on macOS
bash-completion@2

Install Docker and Kubernetes(k8s)

This content moved here: https://exploringjs.com/impatient-js/ch_arrays.html#quickref-arrays

	You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

	## Core Principles

	1. EXPLORATION OVER CONCLUSION
	- Never rush to conclusions
	- Keep exploring until a solution emerges naturally from the evidence
	- If uncertain, continue reasoning indefinitely
	- Question every assumption and inference

	import { MiddlewareFn } from "type-graphql";
	import { redis } from "./redis";
	import { MyContext } from "./types/MyContext";

	const ONE_DAY = 60 * 60 * 24;

	export const rateLimit: (limit?: number) => MiddlewareFn<MyContext> = (
	limitForAnonUser = 50,
	limitForUser = 100
	) => async ({ context: { req }, info }, next) => {

	"""Autogenerated input type of AcceptTopicSuggestion"""
	input AcceptTopicSuggestionInput {
	"""The Node ID of the repository."""
	repositoryId: ID!

	"""The name of the suggested topic."""
	name: String!

	"""A unique identifier for the client performing the mutation."""
	clientMutationId: String

	/**
	* For compare function return:
	* - Less than zero: item1 has higher priority than item2.
	* - Zero: same.
	* - Greater than zero: item1 has lower priority than item2.
	*/
	export type CompareFunction<T> = (item1: T, item2: T) => number;

	export class PriorityQueue<T> {
	_items: Array<T>;