Files
clawhdf5/crates/clawhdf5-py/README.md
T
osobhandClaude Opus 5.5 45d617c39e docs: say when a selection read decodes more than the selection
The READMEs said ds[...] reads only the selected elements, and the
facade's read_selection docs that only intersecting chunks are
decompressed. The bounding-box path runs only when the box covers at
most half the dataset; larger boxes (any strided slice across the
dataset), compact, virtual and unwritten datasets and chunked ones with
a non-default fill value decode the whole dataset. The READMEs, the
facade and format docs, the bindings' docstrings and known-issues now
say so, and how index lists are read.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 09:04:48 -05:00

3.1 KiB

clawhdf5-py

crates.io docs.rs

Python bindings for clawhdf5 — a pure-Rust HDF5 library. The package is clawhdf5 (import clawhdf5); it needs numpy and no libhdf5.

Install

Not on PyPI yet. Build it into a virtualenv with maturin:

pip install maturin numpy
cd crates/clawhdf5-py
maturin develop --release
python -c "import clawhdf5; print(clawhdf5.__version__)"

Reading

The read API follows h5py:

import numpy as np
import clawhdf5

with clawhdf5.File("data.h5", "r") as f:
    f.keys(), f["group"].items(), "group/data" in f
    ds = f["group/data"]           # or f["/group/data"], f["group"]["data"]
    ds.shape, ds.dtype, ds.attrs["units"]
    ds[10:20, ::2]                 # a small selection reads only its chunks
    ds[-1], ds[..., 0], ds[[1, 4, 7]]
    np.asarray(ds)
    f["table"]["id"]               # a compound field
  • Dataset.dtype is the numpy dtype h5py reports: integers and IEEE floats of every width in either byte order, bool, enums (with dtype.metadata['enum']), complex, S<n> fixed strings, object for variable-length strings (bytes values) and sequences (array values), V<n> opaque, array types, and compounds as structured dtypes. Other types raise TypeError.
  • Keys are h5py's: integers, slices with a positive step, ..., one increasing list of integers, compound field names. Each maps onto a hyperslab selection. None, negative steps and boolean masks are refused with h5py's errors.
  • What is read from the file: a selection whose bounding box covers at most half the dataset decodes only the chunks (or contiguous rows) the box overlaps. The library decodes the whole dataset for a larger box (including a strided slice such as ds[::100] across a chunked dataset), and for compact, virtual and unwritten datasets and chunked ones with a non-default fill value. An index list is read one group of neighbouring chunks at a time (a new group only past a chunk with no selected index), so each chunk is decoded once. ds[()], ds[...] and np.asarray(ds) use the file's chunk cache; other selections do not.
  • The bytes the library reads become the numpy array's buffer without a copy, and the read runs with the GIL released, so threads read in parallel. A bug in the library (a Rust panic) raises clawhdf5.InternalError, a RuntimeError.
  • Attributes return what h5py returns; clawhdf5.Empty stands for a null dataspace (h5py's Empty).

Writing

clawhdf5.File(path, "w") with create_dataset(name, data=array, chunks=..., compression="gzip"), create_group and attrs[...] = ... writes float64, float32, int64, int32 and uint8 arrays; the file is written on close().

Tests

pip install pytest h5py
pytest crates/clawhdf5-py/tests

tests/test_read_vs_h5py.py compares every read with h5py on a file h5py writes. scripts/ci-test.sh builds the wheel and runs these in CI.

License

MIT