Nested array reprs

[hameerabbasi]

I thought about this, and calculating the repr is indeed a hard problem, but it becomes easy if we exclude distributed/chunked arrays.

What I propose is:

• every meta array have a __array_meta__(): duck_array which returns the inner array (as one can see for distributed arrays, this could require materialising the array).
• In addition, there should be an __array_attrs__(html: bool): Dict[str, Union[int, bool, float, np.generic, str]] which should be on ALL arrays that want to be included into meta-arrays. This method returns a dict containing the elements it would like displayed. One can then use an implementation like the following:

def __repr__(self):
    attrs = {}
    type_names = []
    current_arr = self
    while current_arr is not None:
        # This formulation guards against duplicate attrs
        attrs = dict(**attrs, **current_arr.__array_attrs__(false))
        class_names.append(type(current_arr).__name__)
        current_arr = getattr(current_array, "__array_meta__", lambda: None)()
    return "<{super_type_name}: {attrs_repr}>".format(
        super_type_name=".".join(type_names),
        attrs_repr=", ".join(f"{k}: {v!r}" for k, v in attrs.items())
    )

[hameerabbasi]

For a chunked representation, one could also have a third slot, __attr_aggregate__(attr_name): Callable[[Iterable[Union[int, bool, float, np.generic, str]]], Union[int, bool, float, np.generic, str]] which could aggregate the given attribute. This way, Dask (or other distributed/chunked array libraries) could easily aggregate the attrs.