Function process_routing

sklearn/utils/_metadata_requests.py:1762–1861

Validate and route metadata. This function is used inside a :term:`router`'s method, e.g. :term:`fit`, to validate the metadata and handle the routing. Assuming this signature of a router's fit method: ``fit(self, X, y, sample_weight=None, **fit_params)``, a call to this functi

(_obj, _method, /, **kwargs)

# prefix to reduce the chances of name collisions with the passed metadata, and
# since they're positional only, users will never type those underscores.
def process_routing(_obj, _method, /, **kwargs):
    """Validate and route metadata.

    This function is used inside a :term:`router`'s method, e.g. :term:`fit`,
    to validate the metadata and handle the routing.

    Assuming this signature of a router's fit method:
    ``fit(self, X, y, sample_weight=None, **fit_params)``,
    a call to this function would be:
    ``process_routing(self, "fit", sample_weight=sample_weight, **fit_params)``.

    Internally, the function uses the router's `MetadataRouter` object (as
    returned by a call to its `get_metadata_routing` method) to validate
    per method that the routed metadata had been requested by the underlying
    estimator, and extracts a mapping of the given metadata to the requested
    metadata based on the routing information defined by the `MetadataRouter`.

    Note that if routing is not enabled and ``kwargs`` is empty, then it
    returns an empty routing where ``process_routing(...).ANYTHING.ANY_METHOD``
    is always an empty dictionary.

    The output of this function is a :class:`~sklearn.utils.Bunch` that has a key for
    each consuming object and those hold keys for their consuming methods, which then
    contain keys for the metadata which should be routed to them.

    Read more on developing custom estimators that can route metadata in the
    :ref:`Metadata Routing Developing Guide
    <sphx_glr_auto_examples_miscellaneous_plot_metadata_routing.py>`.

    .. versionadded:: 1.3

    Parameters
    ----------
    _obj : object
        An object implementing ``get_metadata_routing``. Typically a
        :term:`meta-estimator`.

    _method : str
        The name of the router&#x27;s method in which this function is called.

    **kwargs : dict
        Metadata to be routed.

    Returns
    -------
    routed_params : Bunch
        A :class:`~sklearn.utils.Bunch` of the form ``{"object_name":
        {"method_name": {metadata: value}}}`` which can be used to pass the
        required metadata to corresponding methods or corresponding child objects.
        The object names are those defined in `obj.get_metadata_routing()`.

    Examples
    --------
    >>> import numpy as np
    >>> from sklearn import set_config
    >>> from sklearn.utils.metadata_routing import process_routing
    >>> from sklearn.linear_model import Ridge
    >>> from sklearn.feature_selection import SelectFromModel