Hello and happy new year!
We’re excited to introduce the Pyper package for concurrency &amp; parallelism in Python. Pyper is a flexible framework for concurrent / parallel data processing, following the functional paradigm.
See the source code <a href="https://github.com/pyper-dev/pyper" target="_blank" rel="noopener nofollow">here</a>
Key features:
💡Intuitive API: Easy to learn, easy to think about. Implements clean abstractions to seamlessly unify threaded, multiprocessed, and asynchronous work.
🚀 Functional Paradigm: Python functions are the building blocks of data pipelines. Let’s you write clean, reusable code naturally.
🛡️ Safety: Hides the heavy lifting of underlying task execution and resource clean-up. No more worrying about race conditions, memory leaks, or thread-level error handling.
⚡ Efficiency: Designed from the ground up for lazy execution, using queues, workers, and generators.
✨ Pure Python: Lightweight, with zero sub-dependencies.
We’d love to hear any feedback on this project!

Python Developers is a dedicated community for Python developers of all levels. From beginners to experts. Whether you’re diving into web development or data science this is the place to connect, learn, and grow. 

Python Developers

Pyper is a new and flexible framework for concurrency and parallelism in Python, emphasizing the functional programming paradigm. It offers an intuitive API, prioritizes safety, and is designed for efficiency, all while being a lightweight and pure Python package with no dependencies.

Pyper: Concurrent Python Made Simple

For the newbies, could you please show an example that compares two scripts ? : both achieve the same goal, one with your package, the other without.