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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
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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.