confection is a lightweight library that offers a configuration system letting
you conveniently describe arbitrary trees of objects.
Configuration is a huge challenge for machine-learning code because you may want
to expose almost any detail of any function as a hyperparameter. The setting you
want to expose might be arbitrarily far down in your call stack, so it might
need to pass all the way through the CLI or REST API, through any number of
intermediate functions, affecting the interface of everything along the way. And
then once those settings are added, they become hard to remove later. Default
values also become hard to change without breaking backwards compatibility.
To solve this problem, confection offers a config system that lets you easily
describe arbitrary trees of objects. The objects can be created via function
calls you register using a simple decorator syntax. You can even version the
functions you create, allowing you to make improvements without breaking
backwards compatibility. The most similar config system we're aware of is Gin,
which uses a similar syntax, and also allows you to link the configuration
system to functions in your code using a decorator. confection's config system
is simpler and emphasizes a different workflow via a subset of Gin's
functionality.
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