Commit Graph
10 Commits
Author SHA1 Message Date
osobhandClaude Opus 5.5 05b0192a60 fix(py): a 0-d integer array indexes like an int
ds[np.array(1)] went down the index-list path, where tolist() returns a
scalar and extracting a list of indices raised a confusing TypeError.
h5py treats it as an integer index; so do we now. The h5py comparison
keys include 0-d arrays (signed and unsigned) on each axis; they failed
before.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 09:02:28 -05:00
osobhandClaude Opus 5.5 f0ecae38b6 perf(py): datasets and groups keep their address; groups their links
Every ds[...] and g[k] resolved the path from the root again, two or
three times per open, and resolving a name in a large group scans its
links: visiting a group was O(n^2). 4000 scalar datasets in one group
took 39 s (v1 group) and 131 s (dense) to list, read and re-read; now
0.3 s each. A Dataset keeps its object address, a Group (and the file's
root) its address and, after the first lookup, its link table.

New facade API File::dataset_at(address), tested in integration_tests.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 09:01:54 -05:00
osobhandClaude Opus 5.5 b43bd2e67f perf(py): read an index list one group of chunks at a time
Each run of consecutive indices was its own uncached hyperslab read, so
a list over a compressed chunked dataset decoded the same chunk once per
run (d[range(0, 200000, 40)] over 20 gzip chunks: 8 s, h5py 0.014 s).
Plan::reads now groups the indices — a group ends only where a whole
chunk holds no selected index, or, unchunked, at a gap over 64 KiB — and
the selected rows are gathered from each group's block in Rust. Now
3.8 ms (h5py 4.1 ms, release, tank). The new test (1-D, 2-D and
contiguous, compared with h5py, 2 s bound) took 5.8 s before.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 08:57:16 -05:00
osobhandClaude Opus 5.5 8c51b05b9c fix(py): index lists of padded compounds no longer return uninitialised padding
np.concatenate copies structured dtypes field by field into np.empty, so
the padding of ds[[0, 3, 6]] held process memory. The runs' bytes are
joined in Rust, whole elements at a time, before anything becomes numpy:
the padding is the file's bytes (h5py's) and the result is still a view
of the Rust buffer. The h5py comparisons now compare every byte of
structured values; the new test failed on the padding before.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 08:54:04 -05:00
osobhandClaude Opus 5.5 24412a0e59 fix(py): a panic in the library raises clawhdf5.InternalError, not PanicException
PanicException derives from BaseException, so `except Exception` let a
library bug through. Every call from the bindings into the library now
runs under catch_unwind and a panic becomes InternalError (RuntimeError)
naming the object. Tests: a hidden hook panics inside the guard; and the
v4 chunk indexes are compared with h5py from Python — with the library
fix reverted, ds[0:30] of the implicit-index dataset now raises
InternalError instead of aborting the test run.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 08:52:55 -05:00
osobhandClaude Opus 5.5 2d4b211523 feat(py): h5py-style reads of only the selected elements, GIL released
ds[key] read the whole dataset and sliced it in numpy, and knew six
dtypes. Keys (ints, positive-step slices, Ellipsis, one increasing index
list, compound field names) now map onto hyperslab selections, and the
facade's read_selection bytes become the numpy buffer without a copy
(PyArray::from_vec viewed as the dtype). dtype mapping follows h5py for
all integer/IEEE float widths and byte orders, bool, enum, complex, fixed
and variable-length strings, vlen sequences, opaque, array types and
(nested, padded) compounds; anything it cannot describe exactly is a
TypeError. Attributes return what h5py returns; groups and files gain
the rest of the h5py mapping interface. Reads run under py.detach.

tests/test_read_vs_h5py.py compares >500 reads with h5py 3.16 on an
h5py-written file, checks errors match, that a damaged chunk outside the
selection is never touched, and 8 threads reading at once.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 08:19:48 -05:00
osobhandClaude Opus 5.5 006bf3b131 fix(py): one name, clawhdf5, for the Python distribution and module
pyproject.toml named the distribution rustyhdf5 while the extension
module is clawhdf5, and the package's tests imported rustyhdf5, so
pytest failed at collection. Distribution, module-name and tests now
agree; the module gains __version__. maturin develop + pytest: 28 pass.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
2026-09-26 08:09:54 -05:00
osobhandClaude Fable 5.1 97ab658c11 feat: attrs() reports every attribute; unsigned arrays stay unsigned
attrs() silently omitted any attribute whose datatype had no AttrValue variant
— including every Python bool, which h5py stores as an enum — plus complex,
compound and reference attributes, and cast unsigned 64-bit arrays to
I64Array so values above i64::MAX came back negative.

- numpy/h5py-style booleans (an enum of exactly FALSE=0 / TRUE=1 over an
  integer base) decode as I64 / I64Array of 0/1.
- AttrValue::U64Array keeps unsigned arrays unsigned. Behaviour change: an
  unsigned array attribute no longer arrives as I64Array; the netCDF-4 CF
  helpers (_FillValue, valid_range) and the Python bindings handle it.
- AttrValue::Raw { datatype, shape, data } carries any other attribute
  verbatim (also used when a value fails to decode as its declared type), so
  the attribute list is always complete. Decodable with data_read against the
  datatype; Python receives {"dtype", "shape", "data"}.
- Both new variants are writable, so attributes round-trip between files.
  h5py interop tests cover reading 13 attribute kinds and h5py reading back a
  compound and a u64 attribute written by clawhdf5.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
2026-09-19 07:05:34 -07:00
osobhandClaude Opus 4.8 8f9dbd812c feat: integrate HNSW into agent search, fix Python 3.14 build
Resolves two gaps found in a project-state review:

1. Python build was broken: PyO3/numpy 0.23 caps at Python 3.13 but the
   environment has 3.14. Bumped to 0.28 and updated the two breaking APIs
   (PyObject -> Py<PyAny>, allow_threads -> detach). The extension module now
   imports and round-trips under Python 3.14, unblocking cargo build --workspace.

2. The "HNSW vector search over agent memories" headline was unwired:
   clawhdf5-ann had zero dependents and the agent used a linear cosine+BM25 scan.
   - clawhdf5-ann is now a live index: insert, mark_deleted (soft delete with a
     deleted bitset, traversed but never returned), compact, and a format
     version tag (v2) with backward-compatible load of v1 files.
   - clawhdf5-agent wires HNSW behind the `hnsw` feature (ON by default). The
     index mirrors the cache (node id == cache index) and self-heals: it rebuilds
     whenever hnsw_synced_len drifts from cache.len(), so unhooked pushes can't
     desync it. Non-indexable stores (no/zero-dim/mixed embeddings) and queries
     whose dim doesn't match fall back to the exact linear scan.
   - hybrid.rs gains merge_vector_keyword, shared by the linear and HNSW paths.
   - tests/hnsw_integration.rs validates recall vs a brute-force oracle plus
     insert/delete/batch behaviour.

Disable HNSW for exact search with `--no-default-features --features float16`.

Co-Authored-By: Claude Opus 4.8 (1M context) <[email protected]>
2026-06-03 07:10:48 +00:00
redclawsystems 3f222f6956 Merge pull request 'docs(clawhdf5): document DType variants, fix unresolved doc links' (#17) from sdlc-docs/clawhdf5-types-20260514-165210 into main 2026-05-14 23:54:48 +00:00