JeanKossaifi/zencfg

A Zen approach to configuring your Python project

42
/ 100
Emerging

ZenCFG helps machine learning engineers and researchers manage complex experiment settings by defining them directly in Python code. You provide nested Python classes that describe your model architectures, optimizers, and other experiment parameters. The tool then generates a full configuration, allowing you to easily override any setting using simple command-line arguments. This ensures that your experiments are consistently configured.

Use this if you are a machine learning practitioner managing training runs and need a straightforward way to define, compose, and override experiment parameters from the command line without editing config files.

Not ideal if you need to manage configurations for projects that are not primarily written in Python or require a non-code-based configuration approach.

deep-learning-experiments ml-workflow experiment-configuration model-training research-workflow
No Package No Dependents
Maintenance 10 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 10 / 25

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Stars

15

Forks

2

Language

Python

License

MIT

Last pushed

Feb 27, 2026

Commits (30d)

0

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