Allow easier array UDTs, such as "INT64[3, 3]"
#300
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eriknw
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It should be noted that record dtypes in numpy can be indexed. For example: >>> udt = gb.dtypes.lookup_dtype({"x": int, "y": float})
>>> udt
{'x': INT64, 'y': FP64}
>>> udt.np_type
dtype([('x', '<i8'), ('y', '<f8')])
>>> udt.np_type["x"]
dtype('int64')
>>> udt.np_type[0]
dtype('float64')Array dtypes cannot be indexed: >>> udt = gb.dtypes.lookup_dtype("INT64[3]")
>>> udt
INT64[3]
>>> udt.np_type
dtype(('<i8', (3,)))
>>> udt.np_type[0]
KeyError: "There are no fields in dtype ('<i8', (3,))."Might we want to index our dtypes someday, and, if so, does this change our mind about approving this PR? |
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This matches the "nicer" repr we have for array UDTs that we already have, so it should be natural to use.
I'm always a little skeptical when extending what numpy does, but I think this is so much easier and more readable.
Quick: can you create a valid numpy array dtype from memory?