test(refactor): Adapt to new schema

test(dependency): Remove hypothesis as a dependency from the testing suite

Justfile

@@ -7,7 +7,7 @@ test:
 format:
     poetry run black .
     poetry run isort .
-    poetry run ruff check . --fix
+    poetry run ruff check --fix --exit-zero .
     @echo "Formatting complete 🎉"
 
 mypy:
@@ -26,4 +26,6 @@ pyright_test:
     poetry run pyright tests/
 
 typegen:
-    poetry run python typegen/generate_typing.py
+    poetry run python typegen/generate_typing.py
+
+check: format pyright test

pydantic_numpy/helper/annotation.py

@@ -283,18 +283,18 @@ def _deserialize_numpy_array_from_data_dict(data_dict: NumpyArrayTypeData) -> np
 
 # IN_THE_FUTURE: Only works with 3.11 and above
 # @validate_call
-# def _dimension_type_from_depth(depth: PositiveInt) -> type[tuple[Any, ...]]:
-#     return tuple[*[Any] * depth]  # type: ignore
-
-
-_dimensions_to_shape_type: Final[dict[PositiveInt, type[tuple[Any, ...]]]] = {
-    1: tuple[Any],
-    2: tuple[Any, Any],
-    3: tuple[Any, Any, Any],
-    4: tuple[Any, Any, Any, Any],
-    5: tuple[Any, Any, Any, Any, Any],
-    6: tuple[Any, Any, Any, Any, Any, Any],
-    7: tuple[Any, Any, Any, Any, Any, Any, Any],
+# def _dimension_type_from_depth(depth: PositiveInt) -> type[tuple[int, ...]]:
+#     return tuple[*[int] * depth]  # type: ignore
+
+
+_dimensions_to_shape_type: Final[dict[PositiveInt, type[tuple[int, ...]]]] = {
+    1: tuple[int],  # type: ignore[dict-item]
+    2: tuple[int, int],  # type: ignore[dict-item]
+    3: tuple[int, int, int],  # type: ignore[dict-item]
+    4: tuple[int, int, int, int],  # type: ignore[dict-item]
+    5: tuple[int, int, int, int, int],  # type: ignore[dict-item]
+    6: tuple[int, int, int, int, int, int],  # type: ignore[dict-item]
+    7: tuple[int, int, int, int, int, int, int],  # type: ignore[dict-item]
 }
 
 

pyproject.toml

@@ -29,22 +29,19 @@ semver = "^3.0.1"
 [tool.poetry.group.dev.dependencies]
 pytest = "^7.4.0"
 parameterized = "^0.9.0"
-hypothesis = "^6.82.0"
 orjson = "*"
-setuptools = "^68.0.0"
 
 [tool.poetry.group.format.dependencies]
 black = "^23.7.0"
 isort = "^5.12.0"
-ruff = "^0.0.285"
+ruff = "*"
 
 [tool.poetry.group.typecheck.dependencies]
 mypy = "*"
 pyright = "^1.1.338"
 
 [tool.pytest.ini_options]
 filterwarnings = [
-    "ignore::hypothesis.errors.NonInteractiveExampleWarning",
     "ignore:invalid value encountered in multiply:RuntimeWarning",
 ]
 
@@ -57,10 +54,11 @@ profile = "black"
 
 [tool.ruff]
 line-length = 120
-ignore-init-module-imports = true
-ignore = ["F403", "F405"]
+lint.ignore-init-module-imports = true
+lint.ignore = ["F403", "F405"]
 
 [tool.pyright]
+include = ["pydantic_numpy/**", "tests/**"]
 reportUnsupportedDunderAll = false
 
 [build-system]

tests/helper/cache.py

@@ -1,36 +1,11 @@
-from functools import cache
-from typing import Optional
+from functools import lru_cache
 
-import numpy as np
-from hypothesis.extra.numpy import arrays
-from hypothesis.strategies import floats
 from pydantic import BaseModel
 
-from pydantic_numpy.helper.typing import SupportedDTypes
 
-
-@cache
-def cached_calculation(array_type_hint) -> type[BaseModel]:
+@lru_cache
+def get_numpy_type_model(array_type_hint) -> type[BaseModel]:
     class ModelForTesting(BaseModel):
         array_field: array_type_hint
 
     return ModelForTesting
-
-
-@cache
-def cached_hyp_array(numpy_dtype: SupportedDTypes, dimensions: Optional[int] = None, *, _axis_length: int = 1):
-    if np.issubdtype(numpy_dtype, np.floating):
-        if numpy_dtype == np.float16:
-            width = 16
-        elif numpy_dtype == np.float32:
-            width = 32
-        elif numpy_dtype in (np.longdouble, np.float64):
-            width = 64
-        else:
-            raise RuntimeError
-
-        element_strategy = floats(allow_infinity=False, allow_nan=False, width=width)
-    else:
-        element_strategy = None
-
-    return arrays(numpy_dtype, tuple(_axis_length for _ in range(dimensions or 1)), elements=element_strategy)