Files
clawhdf5/crates/clawhdf5
osobhandClaude Opus 5.5 ca81c3ebfa format, wasm: Storage::hint, fetched by the lazy reader with a pass's misses
A parser often learns where the next structures are (a node's children,
a structure's body once its prefix gives its length) before it reads
them one at a time. Over openUrl's restartable reader a structure only
reached after a miss costs a pass, and a round trip, of its own.

- clawhdf5-format: `Storage::hint(offset, len)`, "about to be read by
  this operation". Default: nothing (every backend that reads when
  asked); `&T`, `Box`, `Arc` and the facade's `FileData` forward it
  (shifted past a user block, clamped to the file).
- clawhdf5-wasm `LazyStorage` records hinted blocks it lacks. A pass
  that misses nothing ignores them (a hint never adds a round trip); a
  pass that misses also asks for them, in file order, while the pass
  stays within what is left of the operation's `maxFetch` budget (a
  hint never makes a call fail). At most 1 MiB (or a block) per hint
  and 65536 blocks per pass are recorded, whatever a file makes a
  parser hint. `Operation::attempt` follows hints; the plain
  `LazyStorage::attempt` does not. `run_blocking` and the browser's
  driver use the former. `LazyStats::hinted_blocks` counts them.

No parser hints yet: results, passes and requests are unchanged.
Tests: hinted blocks come with a miss and never alone (cached ones
skipped, a plain attempt ignores them), and stay within the fetch
budget, a hint past the end or longer than the file harmless.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-27 22:41:09 -05:00
..

clawhdf5

crates.io docs.rs

Pure-Rust HDF5 reader/writer — no C dependencies.

Features

  • Read and write HDF5 files entirely in Rust
  • Memory-mapped I/O for large files (mmap feature, enabled by default)
  • Parallel chunk reads via Rayon (parallel feature)
  • Lazy dataset access for minimal memory usage
  • h5py-compatible file output

Usage

use clawhdf5::File;

let file = File::open("data.h5").unwrap();
let dataset = file.dataset("/group/data").unwrap();
let values: Vec<f64> = dataset.read_1d().unwrap();

License

MIT