diff --git a/src/numpydantic/maps.py b/src/numpydantic/maps.py index 7de60c0..4db4b2d 100644 --- a/src/numpydantic/maps.py +++ b/src/numpydantic/maps.py @@ -58,5 +58,11 @@ flat_to_nptyping = { } """Map from NWB-style flat dtypes to nptyping types""" -python_to_nptyping = {float: dt.Float, str: dt.String, int: dt.Int, bool: dt.Bool} +python_to_nptyping = { + float: dt.Float, + str: dt.String, + int: dt.Int, + bool: dt.Bool, + complex: dt.Complex, +} """Map from python types to nptyping types""" diff --git a/src/numpydantic/schema.py b/src/numpydantic/schema.py index b7733c6..5b22826 100644 --- a/src/numpydantic/schema.py +++ b/src/numpydantic/schema.py @@ -41,7 +41,6 @@ def _numeric_dtype(dtype: DtypeType, _handler: _handler_type) -> CoreSchema: def _lol_dtype(dtype: DtypeType, _handler: _handler_type) -> CoreSchema: """Get the innermost dtype schema to use in the generated pydantic schema""" - if isinstance(dtype, nptyping.structure.StructureMeta): # pragma: no cover raise NotImplementedError("Structured dtypes are currently unsupported") @@ -63,7 +62,10 @@ def _lol_dtype(dtype: DtypeType, _handler: _handler_type) -> CoreSchema: else: try: python_type = np_to_python[dtype] - except KeyError as e: + except KeyError as e: # pragma: no cover + # this should pretty much only happen in downstream/3rd-party interfaces + # that use interface-specific types. those need to provide mappings back + # to base python types (making this more streamlined is TODO) if dtype in np_to_python.values(): # it's already a python type python_type = dtype diff --git a/tests/test_ndarray.py b/tests/test_ndarray.py index 88fe55b..f39dc8d 100644 --- a/tests/test_ndarray.py +++ b/tests/test_ndarray.py @@ -169,6 +169,7 @@ def test_json_schema_dtype_single(dtype, array_model): (int, "integer"), (float, "number"), (bool, "boolean"), + (complex, "any"), ], ) def test_json_schema_dtype_builtin(dtype, expected, array_model): @@ -179,7 +180,10 @@ def test_json_schema_dtype_builtin(dtype, expected, array_model): model = array_model(dtype=dtype) schema = model.model_json_schema() inner_type = schema["properties"]["array"]["items"]["items"] - assert inner_type["type"] == expected + if expected == "any": + assert inner_type == {} + else: + assert inner_type["type"] == expected @pytest.mark.skip("Not implemented yet")