From 7355d3a0f574eefad24be5fddceb43db697c85e0 Mon Sep 17 00:00:00 2001 From: caniko Date: Wed, 29 Mar 2023 19:20:50 +0200 Subject: [PATCH] Feat: NumpyModel.load now has takes pre_load_modifier as argument Chore: Bump version, MINOR Test: Fixed tests for NumpyModel --- README.md | 4 +- poetry.lock | 182 ++++++++++++++++++++-------------------- pydantic_numpy/model.py | 38 +++++++-- pyproject.toml | 9 +- tests/test_model.py | 41 +++++---- 5 files changed, 151 insertions(+), 123 deletions(-) diff --git a/README.md b/README.md index 1c860a8..530002b 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ For more examples see [test_ndarray.py](./tests/test_ndarray.py) ```python import pydantic_numpy.dtype as pnd - from pydantic_numpy import NDArray, NDArrayFp32, NumpyModel, model_agnostic_load +from pydantic_numpy import NDArray, NDArrayFp32, NumpyModel class MyPydanticNumpyModel(NumpyModel): @@ -35,7 +35,7 @@ cfg.dump("path_to_dump_dir", "object_id") cfg.load("path_to_dump_dir", "object_id") ``` -`NumpyModel.load` requires the original mode, use `model_agnostic_load` when you have several models, and you want to load into a set of possible models. +`NumpyModel.load` requires the original mode, use `model_agnostic_load` when you have several models that may be the right model. ### Data type (dtype) support! diff --git a/poetry.lock b/poetry.lock index 9db311c..cbf3f66 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.4.0 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. 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cls._dump_numpy_savez_file_name) + other_path: FilePath if (other_path := object_directory_path / cls._dump_compressed_pickle_file_name).exists(): other_field_to_value = compress_pickle.load(other_path) elif (other_path := object_directory_path / cls._dump_pickle_file_name).exists(): @@ -74,7 +90,11 @@ def load(cls, output_directory: DirectoryPath, object_id: str) -> "NumpyModelVar else: other_field_to_value = {} - return cls(**npz_file, **other_field_to_value) + field_to_value = {**npz_file, **other_field_to_value} + if pre_load_modifier: + field_to_value = pre_load_modifier(field_to_value) + + return cls(**field_to_value) def _dump_numpy_split_dict(self) -> Tuple[Dict, Dict]: ndarray_field_to_array, other_field_to_value = {}, {} @@ -110,11 +130,15 @@ def _dump_non_array_yaml_name(cls) -> str: def model_agnostic_load( - output_directory: DirectoryPath, object_id: str, models: Iterable[NumpyModelCLS], not_found_error: bool = False -) -> NumpyModelVar | None: + output_directory: DirectoryPath, + object_id: str, + models: Iterable[NumpyModelCLS], + not_found_error: bool = False, + **load_kwargs, +) -> Union[NumpyModelVar, None]: for model in models: if model.model_directory_path(output_directory, object_id).exists(): - return model.load(output_directory, object_id) + return model.load(output_directory, object_id, **load_kwargs) if not_found_error: raise FileNotFoundError( f"Could not find NumpyModel with {object_id} in {output_directory}." diff --git a/pyproject.toml b/pyproject.toml index 56b5239..1692d4b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "pydantic_numpy" -version = "2.0.2" +version = "2.2.1" description = "Seamlessly integrate numpy arrays into pydantic models" authors = ["Can H. Tartanoglu ", "Christoph Heindl"] license = "MIT" @@ -8,6 +8,13 @@ license = "MIT" readme = "README.md" repository = "https://github.com/caniko/pydantic-numpy" +keywords = ["pydantic", "numpy", "typing"] +classifiers = [ + "Development Status :: 5 - Production/Stable", + "Topic :: Software Development :: Libraries :: Python Modules", + "Operating System :: OS Independent" +] + packages = [{include = "pydantic_numpy"}] [tool.poetry.dependencies] diff --git a/tests/test_model.py b/tests/test_model.py index 25c93c8..9cd0732 100644 --- a/tests/test_model.py +++ b/tests/test_model.py @@ -8,7 +8,7 @@ from pydantic_numpy import NDArray, NDArrayBool from pydantic_numpy.model import NumpyModel -TEST_DUMP_PATH: Path = Path("../delete_me_test_dump").resolve() +TEST_DUMP_PATH: Path = Path(__file__).absolute().parent / "delete_me_test_dump" TEST_MODEL_OBJECT_ID = "test" @@ -24,8 +24,6 @@ class Config: arbitrary_types_allowed = True -vanilla_numpy_model = NumpyModelForTest.model_directory_path(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID) -arbitrary_numpy_model = TestWithArbitraryForTest.model_directory_path(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID) numpy_bool_array: NDArrayBool = np.array([True, True, True, True, True], dtype=bool) @@ -48,40 +46,39 @@ def numpy_model_with_arbitrary(request): return request.param -def test_io_yaml(numpy_model): +def test_io_yaml(numpy_model: NumpyModel) -> None: try: - numpy_model.dump(TEST_DUMP_PATH) - _test_loaded_numpy_model(numpy_model.load(TEST_DUMP_PATH)) + TEST_DUMP_PATH.mkdir(exist_ok=True) + numpy_model.dump(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID) + _test_loaded_numpy_model(numpy_model.load(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID)) finally: - _delete_leftovers() + _delete_leftovers(numpy_model) -def test_io_compressed_pickle(numpy_model_with_arbitrary): +def test_io_compressed_pickle(numpy_model_with_arbitrary: NumpyModel) -> None: try: - numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, pickle=True) - _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH)) + TEST_DUMP_PATH.mkdir(exist_ok=True) + numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID, pickle=True) + _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID)) finally: - _delete_leftovers() + _delete_leftovers(numpy_model_with_arbitrary) -def test_io_pickle(numpy_model_with_arbitrary): +def test_io_pickle(numpy_model_with_arbitrary: NumpyModel) -> None: try: - numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, pickle=True, compress=False) - _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH)) + TEST_DUMP_PATH.mkdir(exist_ok=True) + numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID, pickle=True, compress=False) + _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID)) finally: - _delete_leftovers() + _delete_leftovers(numpy_model_with_arbitrary) -def _test_loaded_numpy_model(model: Union[NumpyModelForTest, TestWithArbitraryForTest]): +def _test_loaded_numpy_model(model: Union[NumpyModelForTest, TestWithArbitraryForTest]) -> None: assert np.all(model.array) and len(model.array) == 5 if isinstance(model, TestWithArbitraryForTest): assert isinstance(model.my_arbitrary_slice, slice) -def _delete_leftovers(): - if vanilla_numpy_model.exists(): - shutil.rmtree(vanilla_numpy_model) - - if arbitrary_numpy_model.exists(): - shutil.rmtree(arbitrary_numpy_model) +def _delete_leftovers(model: NumpyModel) -> None: + shutil.rmtree(model.model_directory_path(TEST_DUMP_PATH, TEST_MODEL_OBJECT_ID))