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Twitter allows users to download parts of their data, see How to download your Twitter archive.

But what's not included in that data dump is the usernames/handles of the people that you follow or are following you. All you get is account IDs which is just an internal number and so a bit useless when it comes to archival.

Here's a way to get that data (you need to know how to run stuff in the terminal):

Go to your Twitter profile in a desktop browser (Firefox or Chrome)
Right click on page → Inspect → Network tab
Click on the Following link (e.g. https://twitter.com/{yourusername}/following)

Setup AudioRelay on Pipewire

Official guide for PulseAudio: https://docs.audiorelay.net/instructions/linux/use-your-phone-as-a-mic-for-a-linux-pc

Download AudioRelay

From: https://audiorelay.net/downloads/linux

Deb on debian or ubuntu, archive for others.

Exporting your 2FA tokens from Authy to transfer them into another 2FA application

IMPORTANT - Update regarding deprecation of Authy desktop apps

Past August 2024, Authy stopped supported the desktop version of their apps:
See Authy is shutting down its desktop app | The 2FA app Authy will only be available on Android and iOS starting in August for details.

And indeed, after a while, Authy changed something in their backend which now prevents the old desktop app from logging in. If you are already logged in, then you are in luck, and you can follow the instructions below to export your tokens.

If you are not logged in anymore, but can find a backup of the necessary files, then restore those files, and re-install Authy 2.2.3 following the instructions below, and it should work as expected.

This is a comparison of the different formatting styles including with clang-format.

Generated via:

styles=( LLVM Google Chromium Mozilla WebKit )
for style in $styles
do
  clang-format -style=$style ChLcpIterativeAPGD.h > ChLcpIterativeAPGD.$style.h

done

	#!/usr/local/bin/php
	<?php

	require_once("config.inc");
	require_once("interfaces.inc");
	require_once("util.inc");

	$subsystem = !empty($argv[1]) ? $argv[1] : '';
	$type = !empty($argv[2]) ? $argv[2] : '';

	Shader "WorldNormalFromDepthTexture"
	{
	Properties {
	[KeywordEnum(3 Tap, 4 Tap, Improved, Accurate)] _ReconstructionMethod ("Normal Reconstruction Method", Float) = 0
	}

	SubShader
	{
	Tags { "RenderType"="Transparent" "Queue"="Transparent" }
	LOD 100

	"""
	A minimal implementation of Monte Carlo tree search (MCTS) in Python 3
	Luke Harold Miles, July 2019, Public Domain Dedication
	See also https://en.wikipedia.org/wiki/Monte_Carlo_tree_search
	https://gist.github.com/qpwo/c538c6f73727e254fdc7fab81024f6e1
	"""
	from abc import ABC, abstractmethod
	from collections import defaultdict
	import math

	"""
	A minimal implementation of Monte Carlo tree search (MCTS) in Python 3
	Luke Harold Miles, July 2019, Public Domain Dedication
	See also https://en.wikipedia.org/wiki/Monte_Carlo_tree_search
	https://gist.github.com/qpwo/c538c6f73727e254fdc7fab81024f6e1
	"""
	from abc import ABC, abstractmethod
	from collections import defaultdict
	import math

	Latency Comparison Numbers (~2012)
	----------------------------------
	L1 cache reference 0.5 ns
	Branch mispredict 5 ns
	L2 cache reference 7 ns 14x L1 cache
	Mutex lock/unlock 25 ns
	Main memory reference 100 ns 20x L2 cache, 200x L1 cache
	Compress 1K bytes with Zippy 3,000 ns 3 us
	Send 1K bytes over 1 Gbps network 10,000 ns 10 us
	Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD