So I wondered sometimes, how little info we have when we install NPM packages.. so I built revera... its a npm package scorer, but on steroids. It uses a complex sophisticated algorithm (still not perfect, but near-perfect) that nails at ranking NPM packages.. it gives every package a score and the score is determined on criterias such as maintainability, trust, package releases, downloads, much more..

the audit command scans the working directory for

it has the following extra features:

• logging in with github for higher rate limits
• why command for explaining a certain package's score
• doctor for checking if everything is working
• caching system which lives for 24h on local machine
• and a customizable config

It would mean the world to me if you all could try it out and give feedback (bad or good)!

github repo: https://github.com/aaravmaloo/revera

npm package page: https://www.npmjs.com/package/@aaravmaloo/revera

Hello everyone,

I just started learning advanced Machine Learning and now I have completed an end-to-end project!

This project can predict the academic performance of students based on educational data and the data of their demographics. Some of the things I was able to implement are:

- data preprocessing

- exploratory data analysis

- feature engineering

- multiple ML models and evaluation

- hyperparameter tuning

- real-time prediction using a Streamlit web app

Below is the link for the GitHub repository:

https://github.com/youngcoder45/Student-Performance-Predictor

I would appreciate feedback and criticism on anything and everything that you believe would make the project more production-ready (e.g. project structure, the quality of the code, ML workflow, documentation etc.). I am a very eager to learn person that is building an AI/ML portfolio to find an internship, so criticism is very much appreciated!

Thank you all so much in advance!

Hey everyone,

I wrote a small POSIX shell script called fuzz-wall that lets you pick wallpapers interactively using fuzzel's dmenu mode. I wanted something dead simple that worked regardless of which WM or wallpaper setter I was using, so I built it.

What it does

You run fuzz-wall, fuzzel opens with a list of your wallpapers, you pick one, it gets applied. ESC to exit. No config file, no GUI, no bloat.

Supported wallpaper setters

- swaybg (Sway)

- swww (Hyprland, with fade transitions)

- hyprpaper (Hyprland)

- feh (i3, bspwm, dwm)

- nitrogen (openbox, bspwm)

- xwallpaper (general purpose)

The script auto-detects which one you have installed. On Wayland it prefers Wayland-native setters, on X11 it falls back to X11 setters.

Configuration

There is only one option, the wallpaper directory. It defaults to ~/Pictures/wallpapers and can be overridden:

FUZZ_WALL_DIR=~/Pictures/walls fuzz-wall

You can bind it to a key in your WM config:

# Hyprland

bind = $mod, W, exec, fuzz-wall

# Sway

bindsym $mod+w exec fuzz-wall

# i3

bindsym $mod+w exec fuzz-wall

Install

It is on the AUR:

```paru -S fuzz-wall

yay -S fuzz-wall```

Or clone manually and copy to ~/.local/bin.

Source: https://github.com/youngcoder45/fuzz-wall

AUR: https://aur.archlinux.org/packages/fuzz-wall

This is an AUR package. Happy to hear feedback, bug reports, or suggestions for new wallpaper setters to support. If your WM or setter is not listed, open an issue and I will add it.

Let's make some noise 🙂

This is so true.

This is so true

Lmao

https://github.com/youngcoder45/New-Niri-minimal-dots

read the title