sklearn base

model.py

try:
    from typing import Annotated
except ImportError:
    # Backported Annotated, available through https://pypi.org/project/typing-extensions/.
    from typing_extensions import Annotated

class Model(Base):
    # This docstring is automatically extended with types and defaults.
    # Maybe one of the following existing projects could be reused for this:
    # https://github.com/agronholm/sphinx-autodoc-typehints
    # https://www.sphinx-doc.org/en/2.0/usage/extensions/autodoc.html#generating-documents-from-type-annotations
    # A similar approach could be used to extract default values out as well.
    """This is a cool model.
    
    Parameters
    ----------
    penalty:
        This is a something cool.
            - This is a list
            - Another list
    n_jobs:
        This is parallel.
        
    Attributes
    ----------
    n_features_:
        The number of features when ``fit`` is performed.
    estimators_:
        The collection of fitted sub-estimators.
    """

    # So this allows mypy and IDEs to know which properties are available on the object.
    n_features_: int
    estimators_: List[sklearn.tree.DecisionTreeClassifier]

    # If there has to be any special handling of default values for backwards compatibility reasons,
    # or some other special processing where it is imporant to know if parameter was passed in or not,
    # then we should use a decorator to help with that, but keep the original constructor signature.
    def __init__(self, *,
        penalty: Annotated[str, Enum("l2", "l1", "elasticnet", "none")] = "l2",
        n_jobs: Annotated[Union[int, str], Interval(int, lower=1) + Enum(-1, None), Tags('resource')] = None,
    ):
        self.penalty = penalty
        self.n_jobs = n_jobs