import pdb import pytest from typing import Any from pydantic import BaseModel, ValidationError import numpy as np from numpydantic import NDArray, Shape @pytest.mark.parametrize( "shape,valid", [ ((2, 6), True), ((2, 7), True), ((3, 6), True), ((3, 7), True), ((4, 6), True), ((4, 7), True), ((1, 6), False), ((5, 6), False), ((2, 5), False), ((2, 8), False), ], ) def test_shape_range(shape, valid): """Specify a dimension with a range of possible sizes""" class MyModel(BaseModel): array: NDArray[Shape["2-4, 6-7"], Any] if valid: _ = MyModel(array=np.zeros(shape, dtype=np.uint8)) else: with pytest.raises(ValidationError): _ = MyModel(array=np.zeros(shape, dtype=np.uint8)) @pytest.mark.parametrize( "shape,valid", [ ((2, 5), True), ((10, 5), True), ((2, 2), True), ((1, 5), False), ((2, 6), False), ], ) def test_shape_wildcard(shape, valid): """Specify an open-ended minimum or maximum size for a given dimension""" class MyModel(BaseModel): array: NDArray[Shape["2-*, *-5"], Any] if valid: _ = MyModel(array=np.zeros(shape, dtype=np.uint8)) else: with pytest.raises(ValidationError): _ = MyModel(array=np.zeros(shape, dtype=np.uint8)) def test_range_shape_schema(): """ Range shapes should correctly generate JSON Schema """ class MyModel(BaseModel): array_range: NDArray[Shape["2-4"], Any] array_range_min: NDArray[Shape["2-*"], Any] array_range_max: NDArray[Shape["*-4"], Any] schema = MyModel.model_json_schema() assert schema["properties"]["array_range"]["minItems"] == 2 assert schema["properties"]["array_range"]["maxItems"] == 4 assert schema["properties"]["array_range_min"]["minItems"] == 2 assert "maxItems" not in schema["properties"]["array_range_min"] assert schema["properties"]["array_range_max"]["maxItems"] == 4 assert "minItems" not in schema["properties"]["array_range_max"]