Dpbm

Shebangs are very common for bash scripts, but they are most part of the time take for granted, and their underlying mechanisms ignored.

In this post and the video I reference, I describe how does that work and also implement some tests to understand it further.

A million thanks!

As a non-English speaker, sometimes I can't see some errors in my text. It'll be very useful for me, thank you so much!

Thanks for your suggestion. I'll do that for sure.

The english version is here

https://github.com/Dpbm/n-rainhas/blob/main/readme-en.md

I did my best to write it, but if you find any mistakes in my text, feel free to open an issue/PR.

Thank you, I'm glad to see you're interested in my content.

Sure man, I'll do my best to make it more accessible for non-brazilian people. Actually, I'm not fluent in English, so doing that will be a nice way to put in practice my knowledge, as well.

The website I shared is very young yet, it has been about a week since I first deployed it. But I'm working to make it available in other languages.

Although the english version is not available on my website yet, I could translate it on my Github repo. The content is pretty much the same, and it would be easier for me now.

https://github.com/Dpbm/n-rainhas

In just a moment I'll push the English version there. Hope it'll help you

Recently, I had a class about hill climbing and local optima in college. The subject was kinda magic for me, and it became even better when a challenge was given to us.

During our class, we approached the N-Queens problem using this algorithm, and latter our task was to improve this implementation to escape the local optima.

As I was super excited, I spent my entire weekend implementing my solution and documenting it.

This is a project I've been working on and I want to share it with you. This one is a whole infrastructure to handle quantum jobs on a server you're able control (even on a raspberry pi).

To use it, just run the docker compose on your server machine and then use the python client library (https://github.com/Dpbm/qserver-connect) to add plugins and submit/retrieve jobs.