[InMemoryDataset redesign] Read many slices at once with the HDF5 C API #378
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peytondmurray
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Oct 4, 2024
| @@ -11,6 +11,16 @@ py.install_sources( | |||
| subdir: 'versioned_hdf5', | |||
| ) | |||
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| # Adapted from https://numpy.org/doc/2.1/reference/random/examples/cython/meson.build.html | |||
| """Implements read_many_slices data transfer when fast transfer cannot be performed. | ||
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| This happens when: | ||
| 1. src is a h5py.Dataset but h5py.Dataset._fast_read_ok returns False. |
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I think you need a with phil lock here in the case where src is an h5py.Dataset.
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| def test_read_many_slices_not_fast_read_ok(h5file): | ||
| """src is a h5py dataset that doesn't support fast read""" |
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It might be good to outline somewhere in the docs when a dataset supports fast reading, since there is a significant difference in performance.
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This is an alternative to #370 after it's been found out that virtual datasets perform very poorly in libhdf5.
Add a function to quickly read potentially thousands of slices from HDF5 into a numpy array, or between numpy arrays. This new function remains dormant for now and will be used in a later PR by a variant of StagedChangesArray from #370.