Fix: Fixed incorrect methodology of getting Config from model instanc…

…e, self.Config -> self.__config__

Test: Improved coverage for NumpyModel
Chore: Version bump, PATCH

.gitignore

@@ -1,3 +1,7 @@
+# Project
+
+delete_me_test_dump*/
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

pydantic_numpy/model.py

@@ -25,8 +25,8 @@ def model_directory_path(cls, pre_model_path: Path) -> DirectoryPath:
         return pre_model_path.parent / f"{pre_model_path.stem}-{cls.__name__}{cls._directory_suffix}"
 
     def dump(self, dump_directory_path: Path, compress: bool = True, pickle: bool = False) -> None:
-        assert not (
-            self.Config.arbitrary_types_allowed and not pickle
+        assert not self.__config__.arbitrary_types_allowed or (
+            self.__config__.arbitrary_types_allowed and pickle
         ), "Arbitrary types are only supported in pickle mode"
 
         dump_directory_path = self.model_directory_path(dump_directory_path)

pydantic_numpy/ndarray.py

@@ -1,5 +1,3 @@
-from __future__ import annotations
-
 from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Generic, Mapping, Optional, TypeVar
@@ -27,7 +25,7 @@ def check_absolute(cls, value: Path) -> Path:
 
 class BaseNDArrayType(Generic[T, ScalarType], np.ndarray[T, np.dtype[ScalarType]], ABC):
     @classmethod
-    def __get_validators__(cls) -> CallableGenerator:
+    def __get_validators__(cls) -> "CallableGenerator":
         yield cls.validate
 
     @classmethod

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "pydantic_numpy"
-version = "2.0.1"
+version = "2.0.2"
 description = "Seamlessly integrate numpy arrays into pydantic models"
 authors = ["Can H. Tartanoglu <[email protected]>", "Christoph Heindl"]
 license = "MIT"

tests/test_model.py

@@ -1,50 +1,84 @@
 import shutil
 from pathlib import Path
+from typing import Union
 
 import numpy as np
 import pytest
 
-from pydantic_numpy import NDArray
+from pydantic_numpy import NDArray, NDArrayBool
 from pydantic_numpy.model import NumpyModel
 
-TEST_DUMP_PATH: Path = Path("./test_dump").resolve()
+TEST_DUMP_PATH: Path = Path("../delete_me_test_dump").resolve()
 
 
-class TestNumpyModel(NumpyModel):
+class NumpyModelForTest(NumpyModel):
     array: NDArray
     non_array: int
 
 
+class TestWithArbitraryForTest(NumpyModelForTest):
+    my_arbitrary_slice: slice
+
+    class Config:
+        arbitrary_types_allowed = True
+
+
+numpy_bool_array: NDArrayBool = np.array([True, True, True, True, True], dtype=bool)
+
+
+def _numpy_model():
+    return NumpyModelForTest(array=numpy_bool_array, non_array=5)
+
+
 @pytest.fixture
-def test_numpy_model():
-    return TestNumpyModel(array=np.array([True, False, True, True, True], dtype=bool), non_array=5)
+def numpy_model():
+    return _numpy_model()
+
 
+@pytest.fixture(params=[
+    _numpy_model(),
+    TestWithArbitraryForTest(array=numpy_bool_array, non_array=5, my_arbitrary_slice=slice(0, 10))
+])
+def numpy_model_with_arbitrary(request):
+    return request.param
 
-def test_io_yaml(test_numpy_model):
+
+def test_io_yaml(numpy_model):
     try:
-        test_numpy_model.dump(TEST_DUMP_PATH)
-        test_numpy_model.load(TEST_DUMP_PATH)
+        numpy_model.dump(TEST_DUMP_PATH)
+        _test_loaded_numpy_model(numpy_model.load(TEST_DUMP_PATH))
     finally:
         _delete_leftovers()
 
 
-def test_io_compressed_pickle(test_numpy_model):
+def test_io_compressed_pickle(numpy_model_with_arbitrary):
     try:
-        test_numpy_model.dump(TEST_DUMP_PATH, pickle=True)
-        test_numpy_model.load(TEST_DUMP_PATH)
+        numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, pickle=True)
+        _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH))
+
     finally:
         _delete_leftovers()
 
 
-def test_io_pickle(test_numpy_model):
+def test_io_pickle(numpy_model_with_arbitrary):
     try:
-        test_numpy_model.dump(TEST_DUMP_PATH, pickle=True, compress=False)
-        test_numpy_model.load(TEST_DUMP_PATH)
+        numpy_model_with_arbitrary.dump(TEST_DUMP_PATH, pickle=True, compress=False)
+        _test_loaded_numpy_model(numpy_model_with_arbitrary.load(TEST_DUMP_PATH))
     finally:
         _delete_leftovers()
 
 
+def _test_loaded_numpy_model(model: Union[NumpyModelForTest, TestWithArbitraryForTest]):
+    assert np.all(model.array) and len(model.array) == 5
+    if isinstance(model, TestWithArbitraryForTest):
+        assert isinstance(model.my_arbitrary_slice, slice)
+
+
 def _delete_leftovers():
-    dump_path = TestNumpyModel.model_directory_path(TEST_DUMP_PATH)
+    dump_path = NumpyModelForTest.model_directory_path(TEST_DUMP_PATH)
+    if dump_path.exists():
+        shutil.rmtree(dump_path)
+
+    dump_path = TestWithArbitraryForTest.model_directory_path(TEST_DUMP_PATH)
     if dump_path.exists():
         shutil.rmtree(dump_path)