diff --git a/docs/changelog.md b/docs/changelog.md
index 5dfe547..6959982 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -9,7 +9,8 @@ but it can be persuaded to store data in ASCII or virtualized utf-8 under somewh
 
 This PR uses h5py's string methods to expose string datasets (compound or not) 
 via the h5proxy with the `asstr()` view method. 
-This also allows us to set strings with normal python strings. 
+This also allows us to set strings with normal python strings,
+although hdf5 datasets can only be created with `bytes` or other non-unicode encodings.
 
 Since numpydantic isn't necessarily a tool for *creating* hdf5 files 
 (nobody should be doing that), but rather an interface to them, 
@@ -27,7 +28,7 @@ class MyModel(BaseModel):
   array: NDArray[Any, str]
 
 h5f = h5py.File('my_data.h5', 'w')
-data = np.random.random((10,10)).astype(str)
+data = np.random.random((10,10)).astype(bytes)
 _ = h5f.create_dataset('/dataset', data=data)
 
 instance = MyModel(array=('my_data.h5', '/dataset'))
diff --git a/tests/fixtures.py b/tests/fixtures.py
index cb5b59b..9d5bba6 100644
--- a/tests/fixtures.py
+++ b/tests/fixtures.py
@@ -122,8 +122,12 @@ def hdf5_array(
         compound: bool = False,
     ) -> H5ArrayPath:
         array_path = "/" + "_".join([str(s) for s in shape]) + "__" + dtype.__name__
+
         if not compound:
-            data = np.random.random(shape).astype(dtype)
+            if dtype is str:
+                data = np.random.random(shape).astype(bytes)
+            else:
+                data = np.random.random(shape).astype(dtype)
             _ = hdf5_file.create_dataset(array_path, data=data)
             return H5ArrayPath(Path(hdf5_file.filename), array_path)
         else: