Files
clawhdf5/crates/clawhdf5-py/src/file.rs
T
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

343 lines
11 KiB
Rust

//! PyFile — the main entry point for opening and creating HDF5 files.
use std::path::PathBuf;
use std::sync::{Arc, Mutex};
use pyo3::prelude::*;
use crate::attrs::PyAttrs;
use crate::dataset::PyDataset;
use crate::group::{PyGroup, WriteGroupState, finalize_write_group};
use crate::{DatasetSpec, OwnedAttrValue, apply_dataset_spec, extract_numpy_data, to_py_err};
/// Internal state for write mode.
struct WriteState {
path: PathBuf,
root_datasets: Vec<DatasetSpec>,
root_attrs: Arc<Mutex<Vec<(String, OwnedAttrValue)>>>,
groups: Vec<Arc<Mutex<WriteGroupState>>>,
}
/// An open HDF5 file.
///
/// Mirrors the h5py.File interface:
///
/// ```python
/// # Reading
/// f = clawhdf5.File('data.h5', 'r')
/// ds = f['dataset']
/// f.close()
///
/// # Writing
/// with clawhdf5.File('out.h5', 'w') as f:
/// f.create_dataset('data', data=numpy_array)
/// ```
#[pyclass(name = "File")]
pub struct PyFile {
inner: Option<FileInner>,
}
enum FileInner {
Read(Arc<clawhdf5_rs::File>),
Write(WriteState),
}
#[pymethods]
impl PyFile {
/// Open or create an HDF5 file.
///
/// Parameters:
/// path: file path
/// mode: 'r' for read (default), 'w' for write
#[new]
#[pyo3(signature = (path, mode="r"))]
fn new(path: &str, mode: &str) -> PyResult<Self> {
match mode {
"r" => {
let file = clawhdf5_rs::File::open(path).map_err(to_py_err)?;
Ok(Self {
inner: Some(FileInner::Read(Arc::new(file))),
})
}
"w" => Ok(Self {
inner: Some(FileInner::Write(WriteState {
path: PathBuf::from(path),
root_datasets: Vec::new(),
root_attrs: Arc::new(Mutex::new(Vec::new())),
groups: Vec::new(),
})),
}),
other => Err(PyErr::new::<pyo3::exceptions::PyValueError, _>(format!(
"unsupported mode '{other}'; expected 'r' or 'w'"
))),
}
}
/// Close the file. In write mode, this finalizes and writes the file.
fn close(&mut self) -> PyResult<()> {
let inner = self.inner.take().ok_or_else(|| {
PyErr::new::<pyo3::exceptions::PyIOError, _>("file is already closed")
})?;
match inner {
FileInner::Read(_) => Ok(()),
FileInner::Write(state) => finalize_write(state),
}
}
/// Context manager entry — returns self.
fn __enter__(slf: Py<Self>) -> Py<Self> {
slf
}
/// Context manager exit — closes the file.
#[pyo3(signature = (_exc_type=None, _exc_val=None, _exc_tb=None))]
fn __exit__(
&mut self,
_exc_type: Option<&Bound<'_, PyAny>>,
_exc_val: Option<&Bound<'_, PyAny>>,
_exc_tb: Option<&Bound<'_, PyAny>>,
) -> PyResult<bool> {
self.close()?;
Ok(false) // don't suppress exceptions
}
/// Get a child object (dataset or group) by path.
fn __getitem__(&self, py: Python<'_>, key: &str) -> PyResult<Py<PyAny>> {
let file = self.read_file()?;
// Try dataset first
match file.dataset(key) {
Ok(_) => {
let ds = PyDataset::new(Arc::clone(file), key.to_string())?;
Ok(ds.into_pyobject(py)?.into_any().unbind())
}
Err(clawhdf5_rs::Error::NotADataset(_)) => {
let grp = PyGroup::from_read(Arc::clone(file), key.to_string());
Ok(grp.into_pyobject(py)?.into_any().unbind())
}
Err(_) => {
// Could be a group (no DataLayout message, no error)
match file.group(key) {
Ok(_) => {
let grp = PyGroup::from_read(Arc::clone(file), key.to_string());
Ok(grp.into_pyobject(py)?.into_any().unbind())
}
Err(e) => Err(PyErr::new::<pyo3::exceptions::PyKeyError, _>(format!(
"{key}: {e}"
))),
}
}
}
}
/// List the names of all children in the root group.
fn keys(&self, py: Python<'_>) -> PyResult<Py<PyAny>> {
let file = self.read_file()?;
let root = file.root();
let mut names = root.datasets().map_err(to_py_err)?;
let groups = root.groups().map_err(to_py_err)?;
names.extend(groups);
names.sort();
let list = pyo3::types::PyList::new(py, &names)?;
Ok(list.into_any().unbind())
}
/// Create a dataset in the root group (write mode only).
///
/// Parameters:
/// name: dataset name
/// data: numpy array
/// chunks: optional chunk dimensions (tuple or list)
/// compression: optional, only 'gzip' supported
/// compression_opts: gzip compression level (1-9)
#[pyo3(signature = (name, *, data, chunks=None, compression=None, compression_opts=None))]
fn create_dataset(
&mut self,
py: Python<'_>,
name: &str,
data: &Bound<'_, PyAny>,
chunks: Option<Vec<u64>>,
compression: Option<&str>,
compression_opts: Option<u32>,
) -> PyResult<()> {
let state = self.write_state_mut()?;
let (dataset_data, shape) = extract_numpy_data(py, data)?;
let deflate_level = parse_compression(compression, compression_opts)?;
let spec = DatasetSpec {
name: name.to_string(),
data: dataset_data,
shape,
chunks,
deflate_level,
attrs: vec![],
};
state.root_datasets.push(spec);
Ok(())
}
/// Create a group (write mode only). Returns a `Group` handle.
fn create_group(&mut self, py: Python<'_>, name: &str) -> PyResult<Py<PyAny>> {
let state = self.write_state_mut()?;
let group_state = Arc::new(Mutex::new(WriteGroupState {
name: name.to_string(),
datasets: vec![],
attrs: Arc::new(Mutex::new(vec![])),
}));
state.groups.push(Arc::clone(&group_state));
let grp = PyGroup::from_write(group_state);
Ok(grp.into_pyobject(py)?.into_any().unbind())
}
/// Attribute access. In read mode, returns attributes of the root group.
/// In write mode, returns a writable attrs handle.
#[getter]
fn attrs(&self) -> PyResult<PyAttrs> {
match self.inner.as_ref() {
Some(FileInner::Read(file)) => {
let map = file.root().attrs().map_err(to_py_err)?;
Ok(PyAttrs::from_read(map))
}
Some(FileInner::Write(state)) => Ok(PyAttrs::from_write(Arc::clone(&state.root_attrs))),
None => Err(PyErr::new::<pyo3::exceptions::PyIOError, _>(
"file is closed",
)),
}
}
fn __repr__(&self) -> String {
match &self.inner {
Some(FileInner::Read(f)) => {
format!("<HDF5 File (read, {} bytes)>", f.as_bytes().len())
}
Some(FileInner::Write(s)) => {
format!("<HDF5 File (write, \"{}\")>", s.path.display())
}
None => "<HDF5 File (closed)>".to_string(),
}
}
fn __contains__(&self, key: &str) -> PyResult<bool> {
let file = self.read_file()?;
Ok(file.dataset(key).is_ok() || file.group(key).is_ok())
}
}
impl PyFile {
fn read_file(&self) -> PyResult<&Arc<clawhdf5_rs::File>> {
match &self.inner {
Some(FileInner::Read(f)) => Ok(f),
Some(FileInner::Write(_)) => Err(PyErr::new::<pyo3::exceptions::PyIOError, _>(
"cannot read from a file opened for writing",
)),
None => Err(PyErr::new::<pyo3::exceptions::PyIOError, _>(
"file is closed",
)),
}
}
fn write_state_mut(&mut self) -> PyResult<&mut WriteState> {
match &mut self.inner {
Some(FileInner::Write(s)) => Ok(s),
Some(FileInner::Read(_)) => Err(PyErr::new::<pyo3::exceptions::PyIOError, _>(
"cannot write to a file opened for reading",
)),
None => Err(PyErr::new::<pyo3::exceptions::PyIOError, _>(
"file is closed",
)),
}
}
}
fn parse_compression(
compression: Option<&str>,
compression_opts: Option<u32>,
) -> PyResult<Option<u32>> {
match compression {
Some("gzip") => Ok(Some(compression_opts.unwrap_or(4))),
Some(other) => Err(PyErr::new::<pyo3::exceptions::PyValueError, _>(format!(
"unsupported compression: {other}; only 'gzip' is supported"
))),
None => Ok(None),
}
}
/// Build and write the HDF5 file from accumulated write state.
fn finalize_write(state: WriteState) -> PyResult<()> {
let mut builder = clawhdf5_rs::FileBuilder::new();
// Root attributes
let root_attrs = state.root_attrs.lock().unwrap_or_else(|e| e.into_inner());
for (name, val) in root_attrs.iter() {
builder.set_attr(name, val.clone().into());
}
drop(root_attrs);
// Root datasets
for spec in &state.root_datasets {
let db = builder.create_dataset(&spec.name);
apply_dataset_spec(db, spec);
}
// Groups
for group_arc in &state.groups {
let guard = group_arc.lock().unwrap();
finalize_write_group(&mut builder, &guard);
}
builder.write(&state.path).map_err(to_py_err)?;
Ok(())
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn parse_gzip_compression() {
assert_eq!(parse_compression(Some("gzip"), Some(6)).unwrap(), Some(6));
assert_eq!(parse_compression(Some("gzip"), None).unwrap(), Some(4));
assert_eq!(parse_compression(None, None).unwrap(), None);
assert!(parse_compression(Some("lz4"), None).is_err());
}
#[test]
fn finalize_roundtrip() {
let dir = std::env::temp_dir();
let path = dir.join("clawhdf5_py_test_finalize.h5");
let state = WriteState {
path: path.clone(),
root_datasets: vec![DatasetSpec {
name: "data".into(),
data: crate::DatasetData::F64(vec![1.0, 2.0, 3.0]),
shape: vec![3],
chunks: None,
deflate_level: None,
attrs: vec![("unit".into(), OwnedAttrValue::Str("m".into()))],
}],
root_attrs: Arc::new(Mutex::new(vec![("version".into(), OwnedAttrValue::I64(1))])),
groups: vec![Arc::new(Mutex::new(WriteGroupState {
name: "grp".into(),
datasets: vec![DatasetSpec {
name: "vals".into(),
data: crate::DatasetData::I32(vec![10, 20]),
shape: vec![2],
chunks: None,
deflate_level: None,
attrs: vec![],
}],
attrs: Arc::new(Mutex::new(vec![])),
}))],
};
finalize_write(state).unwrap();
let file = clawhdf5_rs::File::open(&path).unwrap();
let ds = file.dataset("data").unwrap();
assert_eq!(ds.read_f64().unwrap(), vec![1.0, 2.0, 3.0]);
let grp_ds = file.dataset("grp/vals").unwrap();
assert_eq!(grp_ds.read_i32().unwrap(), vec![10, 20]);
std::fs::remove_file(&path).ok();
}
}