Files
clawhdf5/crates/clawhdf5-format
osobhandClaude Opus 5.5 d54a0f4737 feat(format): read the other attributes when one cannot be read
attrs() read every attribute of an object through extract_attributes_full,
so one attribute it could not read (a corrupt or unsupported attribute
message, or a heap object it could not locate) failed all of them — the
same shape as the huge-object bug, where one 8 KiB attribute hid every
attribute on a NetCDF file's root group.

- clawhdf5-format: new attribute::extract_attributes_tolerant returns the
  attributes it could read plus one error per attribute it could not.
  Errors in the attribute index itself (Attribute Info message, dense
  heap header, B-tree) still fail, since then it is unknown which
  attributes exist. extract_attributes_full is unchanged (strict); both
  share one implementation.
- clawhdf5: attrs() on Group/Dataset, MmapGroup/MmapDataset and
  LazyGroup/LazyDataset leaves an unreadable attribute out (documented),
  and the new attrs_with_errors() returns the map with the per-attribute
  errors. A value is either returned complete or not at all.

Regression test: one_unreadable_attribute_does_not_hide_the_others (h5py
writes 11 dense attributes; one message's version byte is corrupted;
before: attrs() failed with InvalidAttributeVersion(127), after: the 10
others come back with their values and one error is reported).

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-25 22:03:09 -05:00
..

clawhdf5-format

crates.io docs.rs

Pure-Rust HDF5 binary format parsing and writing — no C dependencies.

Features

  • Zero-copy superblock, object header, and B-tree parsing
  • Chunked dataset read/write with filter pipelines
  • no_std support (disable std feature)
  • Optional parallel reads via Rayon
  • SHA-256 provenance tracking

Usage

use clawhdf5_format::Superblock;

let data = std::fs::read("data.h5").unwrap();
let sb = Superblock::from_bytes(&data).unwrap();
println!("HDF5 version {}.{}", sb.version_major(), sb.version_minor());

License

MIT