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]>
This commit is contained in:
osobh
@@ -42,25 +42,27 @@ impl PyDataset {
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file: Arc<clawhdf5_rs::File>,
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path: String,
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) -> PyResult<Self> {
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let hdr = node::header(&file, &path)?;
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let null = node::is_null(&node::dataspace(&file, &hdr)?);
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let (shape, datatype) = {
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let ds = file.dataset(&path).map_err(to_py_err)?;
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let shape = if null {
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None
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} else {
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Some(ds.shape().map_err(to_py_err)?)
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crate::no_panic(|| {
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let hdr = node::header(&file, &path)?;
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let null = node::is_null(&node::dataspace(&file, &hdr)?);
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let (shape, datatype) = {
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let ds = file.dataset(&path).map_err(to_py_err)?;
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let shape = if null {
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None
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} else {
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Some(ds.shape().map_err(to_py_err)?)
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};
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(shape, ds.raw_datatype().map_err(to_py_err)?)
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};
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(shape, ds.raw_datatype().map_err(to_py_err)?)
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};
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let conv = Converter::new(py, &datatype, file.superblock().offset_size)
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.map_err(|e| e.value(py).to_string());
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Ok(Self {
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file,
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path,
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shape,
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datatype,
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conv,
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let conv = Converter::new(py, &datatype, file.superblock().offset_size)
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.map_err(|e| e.value(py).to_string());
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Ok(Self {
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file,
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path,
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shape,
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datatype,
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conv,
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})
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})
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}
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@@ -84,39 +86,43 @@ impl PyDataset {
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let path = self.path.as_str();
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let (vl, elem_size, unit) = (conv.is_vl(), conv.elem_size, conv.vl_unit);
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// Everything below touches only Rust data: release the GIL.
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let blocks: Vec<(Elements, Vec<usize>)> = py
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.detach(|| -> Result<_, ReadError> {
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let ds = file.dataset(path)?;
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let sb = file.superblock();
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let mut blocks = Vec::with_capacity(reads.len());
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for (sel, shape) in reads {
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let raw = ds.read_selection(&sel)?;
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let n: usize = shape.iter().product();
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let data = if vl {
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if raw.len() != n * elem_size {
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return Err(ReadError::Other(format!(
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"read {} bytes of variable-length references, expected {}",
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raw.len(),
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n * elem_size
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)));
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}
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Elements::Vl(
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resolve_vl(
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file.as_bytes(),
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&raw,
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n,
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sb.offset_size,
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sb.length_size,
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unit,
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)
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.map_err(ReadError::Other)?,
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let read = || -> Result<_, ReadError> {
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let ds = file.dataset(path)?;
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let sb = file.superblock();
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let mut blocks = Vec::with_capacity(reads.len());
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for (sel, shape) in reads {
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let raw = ds.read_selection(&sel)?;
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let n: usize = shape.iter().product();
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let data = if vl {
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if raw.len() != n * elem_size {
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return Err(ReadError::Other(format!(
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"read {} bytes of variable-length references, expected {}",
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raw.len(),
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n * elem_size
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)));
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}
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Elements::Vl(
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resolve_vl(
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file.as_bytes(),
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&raw,
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n,
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sb.offset_size,
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sb.length_size,
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unit,
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)
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} else {
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Elements::Bytes(raw)
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};
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blocks.push((data, shape));
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}
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Ok(blocks)
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.map_err(ReadError::Other)?,
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)
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} else {
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Elements::Bytes(raw)
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};
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blocks.push((data, shape));
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}
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Ok(blocks)
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};
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let blocks: Vec<(Elements, Vec<usize>)> = py
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.detach(|| {
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std::panic::catch_unwind(std::panic::AssertUnwindSafe(read))
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.unwrap_or_else(|p| Err(ReadError::Panic(crate::panic_text(&*p))))
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})
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.map_err(|e| e.into_py(&self.path))?;
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@@ -160,6 +166,7 @@ impl PyDataset {
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enum ReadError {
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Lib(clawhdf5_rs::Error),
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Other(String),
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Panic(String),
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}
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impl From<clawhdf5_rs::Error> for ReadError {
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@@ -173,6 +180,10 @@ impl ReadError {
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match self {
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ReadError::Lib(e) => to_py_err(e),
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ReadError::Other(msg) => PyValueError::new_err(format!("{}: {msg}", node::name(path))),
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ReadError::Panic(msg) => crate::InternalError::new_err(format!(
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"{}: clawhdf5 internal error (please report it): {msg}",
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node::name(path)
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)),
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}
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}
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}
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@@ -223,20 +234,22 @@ impl PyDataset {
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/// The maximum shape (`None` per unlimited dimension), like h5py.
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#[getter]
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fn maxshape<'py>(&self, py: Python<'py>) -> PyResult<Bound<'py, PyAny>> {
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let Some(shape) = &self.shape else {
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return Ok(py.None().into_bound(py));
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};
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let max = self
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.file
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.dataset(&self.path)
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.and_then(|ds| ds.max_dimensions())
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.map_err(to_py_err)?
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.unwrap_or_else(|| shape.clone());
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let items: Vec<Option<u64>> = max
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.into_iter()
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.map(|d| (d != u64::MAX).then_some(d))
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.collect();
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Ok(PyTuple::new(py, items)?.into_any())
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crate::no_panic(|| {
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let Some(shape) = &self.shape else {
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return Ok(py.None().into_bound(py));
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};
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let max = self
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.file
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.dataset(&self.path)
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.and_then(|ds| ds.max_dimensions())
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.map_err(to_py_err)?
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.unwrap_or_else(|| shape.clone());
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let items: Vec<Option<u64>> = max
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.into_iter()
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.map(|d| (d != u64::MAX).then_some(d))
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.collect();
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Ok(PyTuple::new(py, items)?.into_any())
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})
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}
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/// The dataset's numpy dtype, as h5py reports it.
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