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]>

crates/clawhdf5-py/src/select.rs

@@ -361,6 +361,14 @@ fn parse_axis(py: Python<'_>, a: &Bound<'_, PyAny>, n: u64) -> PyResult<Axis> {
     let is_array_like = a.is_instance(&np.getattr("ndarray")?)?
         || a.is_instance_of::<pyo3::types::PyList>()
         || a.is_instance_of::<PyTuple>();
+    // A 0-d integer array (`ds[np.array(1)]`) is an integer index, as in h5py.
+    if a.is_instance(&np.getattr("ndarray")?)? && a.getattr("ndim")?.extract::<usize>()? == 0 {
+        let kind: String = a.getattr("dtype")?.getattr("kind")?.extract()?;
+        if kind == "i" || kind == "u" {
+            let i: i128 = a.call_method0("item")?.extract()?;
+            return Ok(Axis::Index(normalize(i, n)?));
+        }
+    }
     if !is_bool && !is_array_like && a.hasattr("__index__")? {
         let i: i128 = a.call_method0("__index__")?.extract()?;
         return Ok(Axis::Index(normalize(i, n)?));

crates/clawhdf5-py/tests/test_read_vs_h5py.py

@@ -234,7 +234,8 @@ def assert_same(ours, theirs, what=""):
 def keys_for(shape):
     if shape == ():
         return [(), Ellipsis]
-    keys = [(), Ellipsis, 0, -1, slice(None), slice(None, None, 2), slice(1, None, 3), slice(0, 0), np.int64(0)]
+    keys = [(), Ellipsis, 0, -1, slice(None), slice(None, None, 2), slice(1, None, 3), slice(0, 0), np.int64(0),
+            np.array(0), np.array(-1, dtype="i1")]
     n0 = shape[0]
     if n0 == 0:
         return [(), Ellipsis, slice(None), slice(None, None, 2), slice(0, 0)]
@@ -252,6 +253,8 @@ def keys_for(shape):
             (slice(None), [0, n1 - 1] if n1 > 1 else [0]),
             (slice(None, None, 2), 1),
             (slice(0, 2), slice(3, 1)),
+            (np.array(1) if n0 > 1 else np.array(0), slice(None)),
+            (slice(None), np.array(n1 - 1, dtype="u2")),
         ]
     if len(shape) >= 3:
         keys += [(0, slice(None), -1), (slice(1, None, 2), 2, slice(None, None, 3)), (Ellipsis, 0, 0), (0, Ellipsis, 1)]