Xarray io tests #66
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Xarray io tests #66
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To keep the load small, we need to write files via generators, not simply via one big string. Using file.writelines() is buffered, and the dask array is buffered.
wpbonelli
reviewed
Mar 3, 2025
| promise.compute() | ||
| # we have to open the file again, | ||
| # because xarray_extras only allows paths and no file handlers. | ||
| with open(file_path, "a") as f: |
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one option would be to just use pandas to_csv for internal arrays, and accept the performance hit, and advise that for fast IO people should use external arrays. pandas accepts a file handle not only a path. is dask lazy io the reason extras does not? I wonder if extras could support file handle for the numpy-backed array case, then we can still get a speedup.
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Based on discussion #49 , we are looking into ways to efficiently write lazy data arrays to disk in ascii format. Our main contestant would be
xarray-extras. A package that can handle large data arrays and writes them with a 10x speed increase compared to simple numpy data writing.