Hùng ndgnuh

These instructions create a conda-shell type of environment for running Julia 1.1. (Derivation originally from https://gist.github.com/tbenst/c8247a1abcf318d231c396dcdd1f5304).

Note: Some Julia packages may fail to install due to missing binary dependencies. The built-in package manager of Julia will normally install these for you but will fail in case of NixOS. You need to "simply" figure out what is missing and add them to the .nix-file.

Write the following expression to a file, e.g., julia-shell.nix:

{ pkgs ? import <nixpkgs> {}}:

let
jupyterPort = pkgs.config.jupyterPort;

Add new Youtube-dl copy to DMCA repo

Fork https://github.com/github/dmca
Download latest youtube-dl source code from https://yt-dl.org/latest
Extract
```
tar -xvf youtube-dl-2020.09.20.tar.gz
```
Push code to your fork as the GitHub CEO

	Config Files Repo : https://github.com/Bearbobs/glorious-awesome-debian

	Setps to setup on debain based system as the original author is on arch and It's quite diffrent procedure as compared.

	## Awesome and Rofi are quite old in debain repo, Building from Git is required.

	Steps to do the same.
	## Rofi->
	git clone --recursive https://github.com/DaveDavenport/rofi
	cd rofi

	# Tested on Ubuntu 16.04 and X11, 2019

	# 1. Download NVIDIA driver as a .run file

	# 2. Stop X-Server
	sudo service lightdm stop

	# 3. Blacklist Nouveau driver
	sudo nano /etc/modprobe.d/blacklist-nouveau.conf

	# Demonstration: https://www.youtube.com/watch?v=5AvHrIK-Kjc&feature=youtu.be
	# rand_cmap from https://stackoverflow.com/questions/14720331/how-to-generate-random-colors-in-matplotlib

	import matplotlib.pyplot as plt
	import torch
	import torch.nn.functional as F
	from visualizations import rand_cmap

	W = H = 64
	img = torch.randn(W, H).to(device)

	# Global packages to be installed in home directory
	# Desktop apps
	gdown
	https://github.com/thenaterhood/gscreenshot/archive/refs/tags/v3.4.1.tar.gz

	# Installed out of convenience
	fastapi
	uvicorn
	pydantic>=2
	lenses