loky/cloudpickle_wrapper.py
def wrap_non_picklable_objects(obj, keep_wrapper=True):
    """Wrapper for non-picklable object to use cloudpickle to serialize them.

    Note that this wrapper tends to slow down the serialization process as it
    is done with cloudpickle which is typically slower compared to pickle. The
    proper way to solve serialization issues is to avoid defining functions and
    objects in the main scripts and to implement __reduce__ functions for
    complex classes.
    """
    if not cloudpickle:
        raise ImportError("could not import cloudpickle. Please install "
                          "cloudpickle to allow extended serialization. "
                          "(`pip install cloudpickle`).")

    # If obj is a  class, create a CloudpickledClassWrapper which instantiates
    # the object internally and wrap it directly in a CloudpickledObjectWrapper
    if inspect.isclass(obj):
        class CloudpickledClassWrapper(CloudpickledObjectWrapper):
            def __init__(self, *args, **kwargs):
                self._obj = obj(*args, **kwargs)
                self._keep_wrapper = keep_wrapper

        CloudpickledClassWrapper.__name__ = obj.__name__
        return CloudpickledClassWrapper

    # If obj is an instance of a class, just wrap it in a regular
    # CloudpickledObjectWrapper
    return _wrap_non_picklable_objects(obj, keep_wrapper=keep_wrapper)
def wrap_non_picklable_objects(obj, keep_wrapper=True):
    if not cloudpickle:
        raise ImportError("could not import cloudpickle. Please install "
                          "cloudpickle to allow extended serialization. "
                          "(`pip install cloudpickle`).")

    # If obj is a  class, create a CloudpickledClassWrapper which instantiates
    # the object internally and wrap it directly in a CloudpickledObjectWrapper
    if inspect.isclass(obj):
        class CloudpickledClassWrapper(CloudpickledObjectWrapper):
            def __init__(self, *args, **kwargs):
                self._obj = obj(*args, **kwargs)
                self._keep_wrapper = keep_wrapper

        CloudpickledClassWrapper.__name__ = obj.__name__
        return CloudpickledClassWrapper

    # If obj is an instance of a class, just wrap it in a regular
    # CloudpickledObjectWrapper
    return _wrap_non_picklable_objects(obj, keep_wrapper=keep_wrapper)
def wrap_non_picklable_objects ( obj , keep_wrapper = True ) : if not cloudpickle : raise ImportError ( "could not import cloudpickle. Please install " "cloudpickle to allow extended serialization. " "(`pip install cloudpickle`)." ) # If obj is a  class, create a CloudpickledClassWrapper which instantiates # the object internally and wrap it directly in a CloudpickledObjectWrapper if inspect . isclass ( obj ) : class CloudpickledClassWrapper ( CloudpickledObjectWrapper ) : def __init__ ( self , * args , * * kwargs ) : self . _obj = obj ( * args , * * kwargs ) self . _keep_wrapper = keep_wrapper CloudpickledClassWrapper . __name__ = obj . __name__ return CloudpickledClassWrapper # If obj is an instance of a class, just wrap it in a regular # CloudpickledObjectWrapper return _wrap_non_picklable_objects ( obj , keep_wrapper = keep_wrapper )
Wrapper for non-picklable object to use cloudpickle to serialize them.

    Note that this wrapper tends to slow down the serialization process as it
    is done with cloudpickle which is typically slower compared to pickle. The
    proper way to solve serialization issues is to avoid defining functions and
    objects in the main scripts and to implement __reduce__ functions for
    complex classes.
Wrapper for non - picklable object to use cloudpickle to serialize them .