Dtype / checking standardization

In the current specification, there are not standardized data type objects, or a specification as to what a data type object needs to implement: https://data-apis.org/array-api/latest/API_specification/data_types.html

Additionally, there’s no APIs in the specification for checking dtypes, i.e. something like np.issubdtype that is somewhat commonly used in code that would look something like:

def dispatch_based_on_dtype(array):
    if np.issubdtype(array.dtype, np.integer):
        return ...
    elif np.issubdtype(array.dtype, np.floating):
        return ...
    else:
        return ...

cc @jakirkham as I believe this pattern is used quite a bit in Dask which would presumably want to be able to target arbitrary array objects under the hood

[jakirkham]

FWIW numbers objects are ABC’s so we can just call register on each subclass to add float32 and float64 if subclassing is not an option

[rgommers]

All the discussion is happening in gh-425 and this is basically a duplicate issue, so I’ll close this again. And we’ll try to finalize gh-425 very soon.