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  • Question: Guaranteed zero-copy round-trip from numpy? · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
508785516 https://github.com/pydata/xarray/issues/3077#issuecomment-508785516 https://api.github.com/repos/pydata/xarray/issues/3077 MDEyOklzc3VlQ29tbWVudDUwODc4NTUxNg== amueller 449558 2019-07-05T14:58:12Z 2019-07-05T14:58:12Z NONE

Thank you @shoyer, that's very useful input. It seems that xarray would fulfill our requirements and so at least is a reasonable candidate for us.

 
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   Question: Guaranteed zero-copy round-trip from numpy? 463841931
508574137 https://github.com/pydata/xarray/issues/3077#issuecomment-508574137 https://api.github.com/repos/pydata/xarray/issues/3077 MDEyOklzc3VlQ29tbWVudDUwODU3NDEzNw== shoyer 1217238 2019-07-04T20:48:40Z 2019-07-04T20:48:40Z MEMBER

Xarray currently only converts NumPy arrays with very particular dtypes: - object arrays will sometimes get converted to more specific dtypes (using pandas's rules) - datetime64 and timedelta64 arrays get converted into ns precision

I imagine we might add special cases like this in the future for esoteric dtypes, but numeric arrays will always be guaranteed to use views, both when creating a DataArray and casting it into a NumPy array.

(Pandas not being able to guarantee this was one of my motivations for writing xarray in the first place...)

 
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   Question: Guaranteed zero-copy round-trip from numpy? 463841931

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