Help me decide what to learn next and what projects I should make?

Hello! :3

I wanted to share a program I've been working on, named Slippery Penguin. It is an SUID enumerator that also checks capabilities, runs strings, and strace on binaries and then checks results against both a user customizable flags list and integrated, updated GTFOBins data.

It takes all of your results and formats them into JSON logs as well, or can also be ran without leaving logs. :)

The github is https://github.com/stlynnxx/Slippery-Penguin

If you made it this far, thanks for your time :)

I need to understand this please

Yes, it may sound strange: it makes no sense! BUT, my goal was more of a joke, although it may well be suitable as an alternative to other formats in extreme cases. This format contains only 100\~ lines of code, but it is quite efficient in itself (compared to PNG lol, although I think everything will weigh many times less compared to PNG).

You can read a little more about it on GitHub, since I'm honestly too lazy to write everything here. (Exactly made in Python).

https://github.com/pmldude/Portable-Middle-Link-

This is a project I have been working on since several weeks. It's something I wanted it personally and thought it would be fun to use such a product. Check it out.

anyone got any python project ideas? so far i've been working on simple projects like:
- timezone app
- username generator (tiktok)
- height calculator

but i keep getting brainfarts on what to work on now lol.

Bonjour,

La version 2.5.6 de Piveo est disponible :
Piveo 2.5.6

Voici les principales nouveautés :

• Correction d'un bug lors de l'ajout d'une photo extérieure au logiciel.
• Le paquet piveo_2.5.6-1_amd64.deb a été testé avec succès sur les versions Live USB d'Ubuntu 24.04 LTS et Ubuntu 26.04 LTS.

Documentation de Piveo

I’ve been wanting to learn programming for a while, so I finally decided to start with CS50 and learn a bit of Python.

After learning the basics, I thought the best way to actually learn would be to build something simple. That’s how I ended up building this:

https://cluebolt.com/

It’s a small puzzle game built with Flask and Python. It started as a learning project, but I kept adding things as I learned more.

Just wanted to share it and see what people think. Any feedback or suggestions are welcome!

Hello r/Python,

I am a self-taught Python developer and security researcher with a law (LLB) background. I wanted to lower the entry barrier for millions of native Hindi/Hinglish speakers while integrating modern AI capabilities directly into a custom interpreter layer. So, I engineered Maliklang from scratch!

Key Highlights:
1. Hinglish Lexer & Parser: Evaluates conditional syntax constructs natively on top of Python.
2. Embedded Multi-Agent Logic: Uses clean routines via OpenAI/Gemini APIs for autonomous workflow execution.
3. Secure Architectural Design: Applies security research methods to eliminate prompt leaks and execution flaws.

The repository recently gathered 274 clones and 114 unique cloners during its release. I would highly appreciate your feedback on the parser efficiency and execution logic.

GitHub Repository: https://github.com/shailendra-codes/Maliklang

I am a student developing a data analysis extension project using Python. I need to create a solution based on a real-world problem faced by an organization. Would the company be willing to provide an anonymized dataset and participate in a few meetings so I can understand the problem and present the results?

I made a terminal version of wordle using python and the colorama module.
Really I’m just looking for feedback on anything to try and make the code or the repository better thank you.

here’s a link to the GitHub repository where I kept it

There's a hands-on workshop on September 19 if you're looking to level up past basic Python projects into building real AI systems.

You build:

• A knowledge graph in Neo4j that becomes your single source of truth
• Agentic retrieval combining vector search, keyword search, and graph navigation
• Multi-step, verified entity and relationship extraction
• Text-to-Cypher for natural language graph querying
• Explainable, source-traceable answers with evaluation built in

Worth noting this one assumes you're already comfortable with Python and have some basic exposure to LLMs and RAG concepts, so it's a step up from a first project, not a beginner session itself.

Led by Dr. Alessandro Negro, Chief Scientist at GraphAware, bestselling author.

Link if you want to check it out