soldni/springs
A set of utilities to turn Dataclasses into useful configuration managers.
This project helps machine learning engineers and researchers manage complex experiment settings efficiently. You define your experiment's parameters using Python data classes, which act as structured blueprints. Then, you can easily provide specific values or override defaults from the command line or YAML files, outputting a complete and validated configuration that's ready to run your ML models or data pipelines.
Used by 2 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning engineer or researcher looking to define, manage, and easily update configurations for your ML experiments using a structured and type-safe approach.
Not ideal if your configuration needs are very simple, or if you prefer entirely unstructured configuration files without the benefits of Python dataclasses and type checking.
Stars
11
Forks
1
Language
Python
License
MIT
Category
Last pushed
Mar 27, 2024
Commits (30d)
0
Dependencies
7
Reverse dependents
2
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