Hi all, Say python’s builtin `int` type. It can be as large as memory allows.
np.ndarray on the other hand is optimized for vectorization via strides, memory structure and many things that I probably don’t know. Well the point is that it is convenient and efficient to use for many things in comparison to python’s built-in list of integers. So, I am thinking whether something in between exists? (And obviously something more clever than np.array(dtype=object)) Probably something similar to `StringDType`, but for integers and floats. (It’s just my guess. I don’t know anything about `StringDType`, but just guessing it must be better than np.array(dtype=object) in combination with np.vectorize) Regards, dgpb
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