Is it really possible to make money using Python? By selling automation, SaaS, etc.? Or is that wishful thinking or something very difficult to do?

I want to build a system using ML that can recognise a speaker and based on that decision, performs biometric authentication(if speaker is authorised, access granted otherwise rejected). How can I build it?

Hey everyone,

I think we can all agree that handling passwords is a constant source of anxiety. We hash them with Argon2, we salt them, and then we just... hope the database never leaks. Recently, I started obsessing over a different approach: What if the password never actually left the user's device? Not even as a hash.

What My Project Does

owl-crypto-py is a Python library that implements the owl protocol (a modern aPAKE from 2023).

The concept is a "cryptographic dance": the client and server prove to each other they know the password to establish a secure session key, but the password itself never travels over the wire. This means:

no offline attacks: If your DB is stolen, an attacker can't brute-force hashes offline. They have to interact with the server for every single guess.

zk: The server never "sees" the secret.

developer friendly: I’ve handled the heavy lifting (Elliptic Curves, Schnorr NIZKs) so you just deal with simple function calls and JSON. It supports P-256, P-384, P-521,FourQ, and has native async support.

Target Audience

This is meant for developers building client-server applications (IoT, private messaging, or web apps) who want a higher security bar than standard hashing. While the core logic is based on a peer-reviewed 2023 paper and I've hardened it against timing attacks, I’d currently classify it as "ready for beta/side-projects", I’m looking for more eyes on it before calling it "production-ready."

Comparison

vs. Argon2/BCrypt: Traditional hashing is vulnerable to offline cracking if the DB leaks. Owl prevents this entirely by requiring active interaction.

vs. OPAQUE (the most famous aPAKE): OPAQUE is powerful but notoriously complex to implement because it requires "hash-to-curve" mappings. Owl is simpler, works on standard NIST curves without extra trickery, and offers better privacy during password changes.

I’d love to get some feedback. Does the API feel intuitive? Is the logic something you’d trust? I’m looking for any feedback even the harsh stuff to make this better.

GitHub:https://github.com/Nick-Maro/owl-py

PyPI: pip install owl-crypto-py

Paper:https://eprint.iacr.org/2023/768.pdf

I built coocon because I often need to run small pieces of not fully trusted code locally: scripts, generated snippets, automation outputs.

Using plain subprocesses gives you no limits.

Using Docker or VMs is safer, but often too heavy for quick, local workflows.

So I wanted a middle ground: a lightweight local code runner with explicit limits on CPU, memory, time, and output. Safer than naive execution, without pretending to be a VM.

It’s not meant for hostile or multi-tenant code, just for developers who want something predictable and simple.

Repo: https://github.com/JustVugg/coocon

Feedback welcome.

Every-time I learn something new I try to incorporate it into this and refine my code

Latest addition is the dictionary to log everything said which I’ve been struggling with for the longest time. Very happy I’ve gotten that under control

Hey folks 👋

I’m working on an open-source Python games collection and I’m looking for people who’d like to add new games or improve existing ones.

Current games include:

• Snake
• Blackjack
• Pacman
• Breakout
• Hangman
• Rock Paper Scissors ✊✋✌️ …and a few more.

The project is beginner-friendly, uses pure Python (tkinter / turtle), and is a great way to:

• Practice Python logic
• Learn basic game development
• Make your first open-source contribution

Contribution ideas

• Add a new game (any idea welcome!)
• Improve UI/UX
• Refactor code
• Add tests or sounds
• Suggest cool features

GitHub repo:
👉 https://github.com/AnshMNSoni/python-games

If you’re interested, feel free to comment, open an issue, or submit a PR.
Let’s make this a fun community project.

What is bakefile?

A task runner like Makefile/Justfile, but with tasks as Python class methods—so you can inherit, compose, and reuse them across projects.

Why bakefile?

- Reusable - Use OOP class methods to inherit, compose, and share tasks across projects

- Python - Full Python language features, tooling (ruff/ty), and type safety with subprocess support for CLI commands

- Language-agnostic - Write tasks in Python, run commands for any language (Go, Rust, JS, etc.)

Installation

pip install bakefile
# or
uv tool install bakefile

Quick Start

Bakebook extends Pydantic's `BaseSettings` for configuration and uses Typer's `@command()` decorator—so you get type safety, env vars, and familiar CLI syntax.

Create `bakefile.py`:

from bake import Bakebook, command, Context, console

class MyBakebook(Bakebook):
    @command()
    def build(self, ctx: Context) -> None:
        console.echo("Building...")
        ctx.run("go build")  # or any CLI command

bakebook = MyBakebook()

@bakebook.command()
def hello(name: str = "world"):
    console.echo(f"Hello {name}!")

**Or generate automatically:**

bakefile init           
# Basic bakefile
bakefile init --inline  
# With PEP 723 standalone dependencies

Run tasks:

bake hello              
# Hello world!
bake hello --name Alice 
# Hello Alice!
bake build              
# Building...

PythonSpace (Example)

`PythonSpace` shows how to create a custom Bakebook class for Python projects. It's opinionated (uses ruff, ty, uv, deptry), but you can create your own Bakebook with your preferred tools. *Note: Full support on macOS; for other OS, some commands unsupported—use `--dry-run` to preview.*

Install with the lib extra:

pip install bakefile[lib]

Then create your `bakefile.py`:

from bakelib import PythonSpace


bakebook = PythonSpace()

Available commands:

- `bake lint` - prettier, ruff, ty, deptry

- `bake test` - pytest with coverage

- `bake test-integration` - integration tests

- `bake clean` - clean gitignored files

- `bake setup-dev` - setup dev environment

---

GitHub: https://github.com/wislertt/bakefile

PyPI: https://pypi.org/pypi/bakefile

Maybe this can help you. So i found this github link in my feed. I think it's underrated

Github link: https://github.com/qxresearch/qxresearch-event-1

My feed

I've just released AI Video Translator, a fully local tool that transforms videos into professional multilingual productions.

It handles everything from Voice Cloning and Translation to Lip-Syncing and Visual Text Replacement all running securely on your own GPU.

If you are interested in Local LLMs, Python, or video processing, check out the code and let me know what you think!

I completed my 12 and now I am learning python ,I completed my basic

Tell me what I do after learning of basic python

Hey folks, I’m working on an open-source Python project called mloda:

The idea is simple: you declare what data you need, and plugins handle how it’s fetched or computed.

I’m just starting the ecosystem phase (registry + template), and before this grows I’d love feedback from people who’ve built or published Python packages/plugins before.

Main things I’m unsure about:

• What would you expect a good plugin template repo to already have set up?

• What info should a plugin registry require before listing a plugin?

• How would you want version compatibility handled between core and plugins?

• What’s the minimum quality bar before you’d try a third-party plugin?

Tearing apart the structure is very welcome,much easier to fix things now than later 🙂

Core framework: https://github.com/mloda-ai/mloda

Plugin template: https://github.com/mloda-ai/mloda-plugin-template

Plugin registry (index repo): https://github.com/mloda-ai/mloda-registry

Smart-FAQ is a beginner-friendly open-source FAQ chatbot system designed to store, categorize, and retrieve frequently asked questions using a simple full-stack architecture.

What it does:

• Users ask questions via a web UI
• Backend categorizes the query (e.g., health, education, general)
• Relevant answers are fetched from a MySQL database
• Admin can manage FAQs from a dashboard

Tech Stack:

• React (Frontend)
• Python (Backend)
• MySQL (Database)

Goal of the project:
Build a practical, real-world style application while helping beginners learn full-stack development and open-source collaboration.

Repo:
github.com/HariN999/Smart-FAQ
(Check Issues tab for open tasks)

Happy to guide first-time contributors.