We’re excited to introduce the Pyper package for concurrent / parallel data processing in Python.
Source code can be found on <a href="https://github.com/pyper-dev/pyper" target="_blank" rel="noopener nofollow">github</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.

Data Engineering

Pyper is a new Python package designed for concurrent and parallel data processing. It features an intuitive API, supports a functional programming paradigm, ensures safety by handling memory and thread-level errors, and is highly efficient with lazy execution. It is a pure Python package with zero dependencies.

Pyper: Concurrent Python Made Simple