machinable🛠️
Unified representation
Run code and inspect results using the same abstraction. Check out the example below ⏬
machinable
research code
A modular system to manage research code so you can move quickly while enabling reuse and collaboration.
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⚡️
Designed for rapid iteration
Spend more time experimenting while relying on machinable to keep things organized.
💡
Hackable and interactive
Tweak, extend, override while leveraging first-class support for Jupyter as well as the CLI.
💻
Some research code
Running code ...
python regression.py --rate=0.1 --logs=1 --name=run-01
... and loading the corresponding results ...
python plot_regression_result.py --component=run-01
... are distinct and often redundant.
This means you have to manually keep track by remembering what the component with rate=0.1 was called.
machinable research code
Running code ...
machinable regression rate=0.1 logs_=True --launch
... and loading the corresponding results ...
machinable regression rate=0.1 logs_=True --launch --plot
... are distinct but use the same abstraction.
This means no need to worry about names as machinable automatically keeps track if you ran rate=0.1 before.