pyvers is a lightweight Python library that lets you write version-specific implementations of functions to handle breaking changes in dependencies or switch between different backends (e.g., CPU/GPU, numpy/jax/torch) without cluttering your code with conditionals.Example use case: NumPy 2.0 changed bool8 to bool_. With pyvers, you can handle both versions elegantly:```python@implement_for("numpy", from_version=None, to_version="2.0.0")def create_mask(arr): np = get_backend("numpy") return np.array([x > 0 for x in arr], dtype=np.bool8)@implement_for("numpy", from_version="2.0.0")def create_mask(arr): np = get_backend("numpy") return np.array([x > 0 for x in arr], dtype=np.bool_)```The README.md gives you a more complete example, including using Jax as a backend.Other real-world examples:- Switching between SciPy (CPU) and CuPy (GPU) sparse matrix operations- Using various libraries for linalg depending on resources: torch, numpy, jax- Handling gym → gymnasium breaking changes in RL librariesThe library is battle-tested: we've been using it in production in several robotic projects to handle BC-breaking changes in our dependencies for the past four years.GitHub: https://github.com/vmoens/pyversPyPI: `pip install pyvers`Comments URL: https://news.ycombinator.com/item?id=44220340Points: 1# Comments: 0