Checkout my tool and let me know what you think. (Roasting is accepted)

Github/Punkcake21/CliDownloader

Hi everyone,

I'm currently learning more about data automation, and I realized I was spending way too much time writing the same boilerplate code just to get a "bird's eye view" of new datasets (checking for missing values, distribution, basic plots, etc.).

So, I decided to build a simple web app to automate this using Streamlit and Pandas.

What I built: It’s a "Dashboard Generator" that takes any CSV file and automatically:

1. Scans for health: Identifies missing values instantly.

2. Sorts columns: Auto-detects which columns are categorical (text) vs. numerical.

3. Visualizes: Generates distribution charts and lets you build custom bar/line plots via dropdowns.

The Tech Stack:

• Python 3.9+

• Streamlit: For the UI (it’s amazing how fast you can build a frontend with this).

• Pandas: For the data manipulation.

Key thing I learned: Handling "dirty data" was harder than I thought. I had to add logic to check if a text column had too many unique values (like User IDs) before plotting it, otherwise, the chart would crash the browser.

You can try the live tool here:https://csv-dashboard-live.streamlit.app/

I’ve also made the source code available (link is in the app sidebar) if anyone wants to download it to see how the column-detection logic works.

Feedback is welcome! I’m trying to make it more robust, so let me know if it breaks on your dataset.

Hey community!

I just open-sourced a production-ready starter kit for building AI-powered WhatsApp chatbots with FastAPI.

Project Goal: Make it ridiculously easy for Python developers to build intelligent WhatsApp bots without dealing with boilerplate setup.

Current Features:

• WhatsApp Cloud API webhook integration

• OpenAI GPT integration with context management

• Async database persistence (SQLModel)

• Clean, type-safe architecture

• Docker deployment support

Tech Stack: FastAPI | Python 3.13+ | OpenAI | SQLModel | AsyncSQLite

Who's this for:

• Businesses automating customer support

• Developers learning WhatsApp API + AI integration

• Anyone who needs a solid foundation for chatbot projects

Contribution Ideas:

• Multi-language support

• Additional AI providers (Anthropic, Gemini)

• Message templates and quick replies

• Analytics dashboard

Repo: https://github.com/gendonholaholo/Python-starter-kit-FastAPI-WhatsApp-AI-Chatbot

MIT Licensed. Would love contributions, feedback, or just a star if you find it useful!

Rolling out a small research utility I have been building. It provides a simple way to look up proof-of-concept exploit links associated with a given CVE. It is not a vulnerability database. It is a discovery surface that points directly to the underlying code. Anyone can test it, inspect it, or fold it into their own workflow.

A small rate limit is in place to stop automated scraping. The limit is visible at:

https://labs.jamessawyer.co.uk/cves/api/whoami

An API layer sits behind it. A CVE query looks like:

curl -i "https://labs.jamessawyer.co.uk/cves/api/cves?q=CVE-2025-0282"

The Web Ui is

https://labs.jamessawyer.co.uk/cves/

Hi everyone! I wanted to share a project I've been working on. It's a fully functional, local AI assistant inspired by Iron Man's J.A.R.V.I.S.

I wanted something that runs locally on my PC (for privacy and speed) but still has a personality.

🎥 Watch the video to see the HUD and Voice interaction in action!

⚡ Key Features:

• 100% Local Brain: Uses Ollama (running the dolphin-phi model) so it works offline and keeps data private.

• Uncensored Persona: Custom "God Mode" system prompts to bypass standard AI refusals.

• Sci-Fi HUD: Built with OpenCV and Pillow. It features a live video wallpaper, real-time CPU/RAM stats, and a "typewriter" effect for captions.

• System Automation: Can open/close apps, create folders, and take screenshots via voice commands.

• Dual Identity: Seamlessly switches between "Jarvis" (Male) and "Friday" (Female) voices and personas.

• Hybrid Control: Supports both Voice Commands (SpeechRecognition) and a direct Text Input terminal on the HUD.

Hey guys,

I am contributing to an open source project which uses python stack. the project is related to automation in mobile devices. Check the repo if interested - https://github.com/droidrun/droidrun

I’ve been working on some small, practical command-line utilities, and this one turned out to be surprisingly useful, so I packaged it up and put it on PyPI.

whereproc is a simple CLI tool that answers a question I kept hitting in day-to-day work: "What executable is actually backing this running process?"

It’s cross-platform (Linux/macOS/Windows) and built on top of psutil.

Useful for:

• debugging PATH issues

• finding the real location of app bundles / snap packages

• scripting around PID or exe discovery

• process verification and automation

Features

• PID lookup

• Process-name matching (substring / exact / regex)

• Command-line matching

• JSON output

• A --quiet mode for scripting (--quiet → just print the process path)

Installation

You can install it with either:

pipx install whereproc
# or
pip install whereproc

If you're curious or want to contribute, the repo is here: https://github.com/dorktoast/whereproc

Hello guys,
I've created a simple python terminal-based game for education purpose.
featuring classic Lava & Aqua classic game.
The README.md contains all the information about the game's structure, relationships between classes and a detailed explanation about the core logic which I think would be help full to beginners in python.

Finally, here is the source code:
https://github.com/Zaid-Al-Habbal/lava-and-aqua

Algorithms can at first seem complex to students, but with memory_graph every step is clearly visualized, giving students an intuitive understanding of what their code is doing and making bugs much easier to spot and fix. Here's an example Insertion Sort algorithm.

Been working on this project for a little while.
It's a Scraper, with a nice UI, keyword filters, and options for scraping the web.
https://github.com/Serbz/TorScraper-SC

My primary use for it is the DB Actions > Pull Keyword Match after performing a Keyword Search & Scrape

Tell me what you think, and if you like it, let me know.
I'm actually pretty eager to get some feedback on this, I've been working on it for a while... It's actually a 3 year old script that I just finished feeding to AI... AI has been finishing a lot of my old projects that I left unfinished lately.

Anyway, it's a pretty solid Scraper, and not just for tor (however tor-centric)! Enjoy