What are *args and **kwargs actually for, and where do...

*args gathers any number of positional arguments into a tuple, and **kwargs gathers any number of keyword arguments into a dictionary. The point of both is flexibility: the function doesn’t have to know in advance exactly what it will receive.

In practice, the single most common use in ML code is config-driven model creation — hyperparameters live in a YAML file, get loaded into a Python dict, and get unpacked straight into a model constructor with XGBClassifier(**config), instead of hardcoding every parameter name by hand. The same pattern powers model-factory functions that build different estimator types from one function, and it’s what makes decorators — a timing wrapper, a retry-with-backoff wrapper around an API call — work on any function regardless of its signature, since the wrapper just forwards *args, **kwargs through to whatever it’s wrapping.