Add support for strings in hdf5

src/numpydantic/interface/hdf5.py

@@ -1,5 +1,27 @@
 """
 Interfaces for HDF5 Datasets
+
+.. note::
+
+    HDF5 arrays are accessed through a proxy class :class:`.H5Proxy` .
+    Getting/setting values should work as normal, **except** that setting
+    values on nested views is impossible - 
+    
+    Specifically this doesn't work:
+    
+    .. code-block:: python
+    
+        my_model.array[0][0] = 1
+    
+    But this does work:
+    
+    .. code-block:: python
+    
+        my_model.array[0,0] = 1
+        
+    To have direct access to the hdf5 dataset, use the
+    :meth:`.H5Proxy.open` method.
+    
 """
 
 import sys
@@ -10,7 +32,7 @@ import numpy as np
 from pydantic import SerializationInfo
 
 from numpydantic.interface.interface import Interface
-from numpydantic.types import NDArrayType
+from numpydantic.types import DtypeType, NDArrayType
 
 try:
     import h5py
@@ -102,7 +124,14 @@ class H5Proxy:
         with h5py.File(self.file, "r") as h5f:
             obj = h5f.get(self.path)
             if self.field is not None:
+                if h5py.h5t.check_string_dtype(obj.dtype[self.field]):
+                    obj = obj.fields(self.field).asstr()
+                else:
                     obj = obj.fields(self.field)
+            else:
+                if h5py.h5t.check_string_dtype(obj.dtype):
+                    obj = obj.asstr()
+
             return obj[item]
 
     def __setitem__(
@@ -222,6 +251,22 @@ class H5Interface(Interface):
 
         return array
 
+    def get_dtype(self, array: NDArrayType) -> DtypeType:
+        """
+        Get the dtype from the input array
+
+        Subclasses to correctly handle
+        """
+        if hasattr(array.dtype, "type") and array.dtype.type is np.object_:
+            if h5py.h5t.check_string_dtype(array.dtype):
+                return str
+            else:
+                return self.get_object_dtype(array)
+        elif h5py.h5t.check_string_dtype(array.dtype):
+            return str
+        else:
+            return array.dtype
+
     @classmethod
     def to_json(cls, array: H5Proxy, info: Optional[SerializationInfo] = None) -> dict:
         """

src/numpydantic/interface/interface.py

@@ -126,7 +126,10 @@ class Interface(ABC, Generic[T]):
         if isinstance(self.dtype, tuple):
             valid = dtype in self.dtype
         elif self.dtype is np.str_:
-            valid = getattr(dtype, "type", None) is np.str_ or dtype is np.str_
+            valid = getattr(dtype, "type", None) in (np.str_, str) or dtype in (
+                np.str_,
+                str,
+            )
         else:
             # try to match as any subclass, if self.dtype is a class
             try:

tests/fixtures.py

@@ -127,6 +127,11 @@ def hdf5_array(
             _ = hdf5_file.create_dataset(array_path, data=data)
             return H5ArrayPath(Path(hdf5_file.filename), array_path)
         else:
+
+            if dtype is str:
+                dt = np.dtype([("data", np.dtype("S10")), ("extra", "i8")])
+                data = np.array([("hey", 0)] * np.prod(shape), dtype=dt).reshape(shape)
+            else:
                 dt = np.dtype([("data", dtype), ("extra", "i8")])
                 data = np.zeros(shape, dtype=dt)
             _ = hdf5_file.create_dataset(array_path, data=data)

tests/test_interface/test_hdf5.py

@@ -78,8 +78,6 @@ def test_hdf5_shape(shape_cases, hdf5_array, compound):
 
 @pytest.mark.parametrize("compound", [True, False])
 def test_hdf5_dtype(dtype_cases, hdf5_array, compound):
-    if dtype_cases.dtype is str:
-        pytest.skip("hdf5 cant do string arrays")
     _test_hdf5_case(dtype_cases, hdf5_array, compound)
 
 
@@ -157,3 +155,18 @@ def test_compound_dtype(tmp_path):
     assert all(instance.array[1, :] == 0)
     instance.array[1] = 2
     assert all(instance.array[1] == 2)
+
+
+def test_strings(hdf5_array):
+    """
+    HDF5 proxy can get and set strings just like any other dtype
+    """
+    array = hdf5_array((10, 10), str)
+
+    class MyModel(BaseModel):
+        array: NDArray[Shape["10, 10"], str]
+
+    instance = MyModel(array=array)
+    instance.array[0, 0] = "hey"
+    assert instance.array[0, 0] == "hey"
+    assert isinstance(instance.array[0, 1], str)