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
parent f0ecae38b6
commit 05b0192a60
3 changed files with 15 additions and 1 deletions
@@ -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)?));