Class Parallel

sklearn/utils/parallel.py:41–91

Tweak of :class:`joblib.Parallel` that propagates the scikit-learn configuration. This subclass of :class:`joblib.Parallel` ensures that the active configuration (thread-local) of scikit-learn is propagated to the parallel workers for the duration of the execution of the parallel tasks.

class Parallel(joblib.Parallel):
    """Tweak of :class:`joblib.Parallel` that propagates the scikit-learn configuration.

    This subclass of :class:`joblib.Parallel` ensures that the active configuration
    (thread-local) of scikit-learn is propagated to the parallel workers for the
    duration of the execution of the parallel tasks.

    The API does not change and you can refer to :class:`joblib.Parallel`
    documentation for more details.

    .. versionadded:: 1.3
    """

    def __call__(self, iterable):
        """Dispatch the tasks and return the results.

        Parameters
        ----------
        iterable : iterable
            Iterable containing tuples of (delayed_function, args, kwargs) that should
            be consumed.

        Returns
        -------
        results : list
            List of results of the tasks.
        """
        # Capture the thread-local scikit-learn configuration at the time
        # Parallel.__call__ is issued since the tasks can be dispatched
        # in a different thread depending on the backend and on the value of
        # pre_dispatch and n_jobs.
        config = get_config()
        # In free-threading Python >= 3.14, warnings filters are managed through a
        # ContextVar and warnings.filters is not modified inside a
        # warnings.catch_warnings context. You need to use warnings._get_filters().
        # For more details, see
        # https://docs.python.org/3.14/whatsnew/3.14.html#concurrent-safe-warnings-control
        filters_func = getattr(warnings, "_get_filters", None)
        warning_filters = (
            filters_func() if filters_func is not None else warnings.filters
        )

        iterable_with_config_and_warning_filters = (
            (
                _with_config_and_warning_filters(delayed_func, config, warning_filters),
                args,
                kwargs,
            )
            for delayed_func, args, kwargs in iterable
        )
        return super().__call__(iterable_with_config_and_warning_filters)


# remove when https://github.com/joblib/joblib/issues/1071 is fixed