Merge pull request #39 from p2p-ld/bugfix-union-dtypes

Fix JSON Schema generation for union dtypes

.github/workflows/tests.yml

@@ -15,20 +15,28 @@ jobs:
       matrix:
         platform: ["ubuntu-latest", "macos-latest", "windows-latest"]
         numpy-version: ["<2.0.0", ">=2.0.0"]
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
         exclude:
           - numpy-version: "<2.0.0"
             python-version: "3.10"
           - numpy-version: "<2.0.0"
             python-version: "3.11"
+            # let's call python 3.12 the last version we're going to support with numpy <2
+            # they don't provide wheels for <2 in 3.13 and beyond.
+          - numpy-version: "<2.0.0"
+            python-version: "3.13"
           - platform: "macos-latest"
             python-version: "3.10"
           - platform: "macos-latest"
             python-version: "3.11"
+          - platform: "macos-latest"
+            python-version: "3.12"
           - platform: "windows-latest"
             python-version: "3.10"
           - platform: "windows-latest"
             python-version: "3.11"
+          - platform: "windows-latest"
+            python-version: "3.12"
 
     runs-on: ${{ matrix.platform }}
 

docs/changelog.md

@@ -1,5 +1,21 @@
 # Changelog
 
+## Upcoming
+
+**Bugfix**
+- [#38](https://github.com/p2p-ld/numpydantic/issues/38), [#39](https://github.com/p2p-ld/numpydantic/pull/39) -
+  - JSON Schema generation failed when the `dtype` was embedded from dtypes that lack a `__name__` attribute.
+    An additional check was added for presence of `__name__` when embedding.
+  - `NDArray` types were incorrectly cached s.t. pipe-union dtypes were considered equivalent to `Union[]`
+    dtypes. An additional tuple with the type of the args was added to the cache key to disambiguate them.
+
+**Testing**
+- [#39](https://github.com/p2p-ld/numpydantic/pull/39) - Test that all combinations of shapes, dtypes, and interfaces
+  can generate JSON schema.
+- [#39](https://github.com/p2p-ld/numpydantic/pull/39) - Add python 3.13 to the testing matrix.
+- [#39](https://github.com/p2p-ld/numpydantic/pull/39) - Add an additional `marks` field to ValidationCase
+  for finer-grained control over running tests.
+
 ## 1.*
 
 ### 1.6.*

pdm.lock

@@ -5,7 +5,7 @@
 groups = ["default", "arrays", "dask", "dev", "docs", "hdf5", "tests", "video", "zarr"]
 strategy = ["cross_platform", "inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:cc2b0fb32896c6df0ad747ddb5dee89af22f5c4c4643ee7a52db47fef30da936"
+content_hash = "sha256:89ac87e811ecc42bf5117e9c9e4aa6a69011cb7c5c1a630fbfb2643b0045c526"
 
 [[metadata.targets]]
 requires_python = "~=3.9"

pyproject.toml

@@ -129,6 +129,8 @@ markers = [
     "numpy: numpy interface",
     "video: video interface",
     "zarr: zarr interface",
+    "union: union dtypes",
+    "pipe_union: union dtypes specified with a pipe",
 ]
 
 [tool.black]

src/numpydantic/ndarray.py

@@ -204,9 +204,15 @@ class NDArray(NPTypingType, metaclass=NDArrayMeta):
         json_schema = handler(schema["metadata"])
         json_schema = handler.resolve_ref_schema(json_schema)
 
-        if not isinstance(dtype, tuple) and dtype.__module__ not in (
+        if (
+            not isinstance(dtype, tuple)
+            and dtype.__module__
+            not in (
                 "builtins",
                 "typing",
+                "types",
+            )
+            and hasattr(dtype, "__name__")
         ):
             json_schema["dtype"] = ".".join([dtype.__module__, dtype.__name__])
 

src/numpydantic/testing/cases.py

@@ -143,27 +143,35 @@ DTYPE_CASES = [
         dtype=np.uint32,
         passes=True,
         id="union-type-uint32",
+        marks={"union"},
     ),
     ValidationCase(
         annotation_dtype=UNION_TYPE,
         dtype=np.float32,
         passes=True,
         id="union-type-float32",
+        marks={"union"},
     ),
     ValidationCase(
         annotation_dtype=UNION_TYPE,
         dtype=np.uint64,
         passes=False,
         id="union-type-uint64",
+        marks={"union"},
     ),
     ValidationCase(
         annotation_dtype=UNION_TYPE,
         dtype=np.float64,
         passes=False,
         id="union-type-float64",
+        marks={"union"},
     ),
     ValidationCase(
-        annotation_dtype=UNION_TYPE, dtype=str, passes=False, id="union-type-str"
+        annotation_dtype=UNION_TYPE,
+        dtype=str,
+        passes=False,
+        id="union-type-str",
+        marks={"union"},
     ),
 ]
 """
@@ -181,30 +189,35 @@ if YES_PIPE:
                 dtype=np.uint32,
                 passes=True,
                 id="union-pipe-uint32",
+                marks={"union", "pipe_union"},
             ),
             ValidationCase(
                 annotation_dtype=UNION_PIPE,
                 dtype=np.float32,
                 passes=True,
                 id="union-pipe-float32",
+                marks={"union", "pipe_union"},
             ),
             ValidationCase(
                 annotation_dtype=UNION_PIPE,
                 dtype=np.uint64,
                 passes=False,
                 id="union-pipe-uint64",
+                marks={"union", "pipe_union"},
             ),
             ValidationCase(
                 annotation_dtype=UNION_PIPE,
                 dtype=np.float64,
                 passes=False,
                 id="union-pipe-float64",
+                marks={"union", "pipe_union"},
             ),
             ValidationCase(
                 annotation_dtype=UNION_PIPE,
                 dtype=str,
                 passes=False,
                 id="union-pipe-str",
+                marks={"union", "pipe_union"},
             ),
         ]
     )

src/numpydantic/testing/helpers.py

@@ -4,16 +4,19 @@ from functools import reduce
 from itertools import product
 from operator import ior
 from pathlib import Path
-from typing import Generator, List, Literal, Optional, Tuple, Type, Union
+from typing import TYPE_CHECKING, Generator, List, Literal, Optional, Tuple, Type, Union
 
 import numpy as np
-from pydantic import BaseModel, ConfigDict, ValidationError, computed_field
+from pydantic import BaseModel, ConfigDict, Field, ValidationError, computed_field
 
 from numpydantic import NDArray, Shape
 from numpydantic.dtype import Float
 from numpydantic.interface import Interface
 from numpydantic.types import DtypeType, NDArrayType
 
+if TYPE_CHECKING:
+    from _pytest.mark.structures import MarkDecorator
+
 
 class InterfaceCase(ABC):
     """
@@ -139,6 +142,8 @@ class ValidationCase(BaseModel):
     """The interface test case to generate and validate the array with"""
     path: Optional[Path] = None
     """The path to generate arrays into, if any."""
+    marks: set[str] = Field(default_factory=set)
+    """pytest marks to set for this test case"""
 
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
@@ -179,6 +184,19 @@ class ValidationCase(BaseModel):
 
         return Model
 
+    @property
+    def pytest_marks(self) -> list["MarkDecorator"]:
+        """
+        Instantiated pytest marks from :attr:`.ValidationCase.marks`
+        plus the interface name.
+        """
+        import pytest
+
+        marks = self.marks.copy()
+        if self.interface is not None:
+            marks.add(self.interface.interface.name)
+        return [getattr(pytest.mark, m) for m in marks]
+
     def validate_case(self, path: Optional[Path] = None) -> bool:
         """
         Whether the generated array correctly validated against the annotation,
@@ -246,7 +264,10 @@ def merge_cases(*args: ValidationCase) -> ValidationCase:
         return args[0]
 
     dumped = [
-        m.model_dump(exclude_unset=True, exclude={"model", "annotation"}) for m in args
+        m.model_dump(
+            exclude_unset=True, exclude={"model", "annotation", "pytest_marks"}
+        )
+        for m in args
     ]
 
     # self_dump = self.model_dump(exclude_unset=True)
@@ -263,6 +284,7 @@ def merge_cases(*args: ValidationCase) -> ValidationCase:
     merged = reduce(ior, dumped, {})
     merged["passes"] = passes
     merged["id"] = ids
+    merged["marks"] = set().union(*[v.get("marks", set()) for v in dumped])
     return ValidationCase.model_construct(**merged)
 
 

src/numpydantic/vendor/nptyping/base_meta_classes.py

@@ -120,7 +120,7 @@ class SubscriptableMeta(ABCMeta):
     new type is returned for every unique set of arguments.
     """
 
-    _all_types: Dict[Tuple[type, Tuple[Any, ...]], type] = {}
+    _all_types: Dict[Tuple[type, Tuple[Any, ...], tuple[type, ...]], type] = {}
     _parameterized: bool = False
 
     @abstractmethod
@@ -160,7 +160,7 @@ class SubscriptableMeta(ABCMeta):
     def _create_type(
         cls, args: Tuple[Any, ...], additional_values: Dict[str, Any]
     ) -> type:
-        key = (cls, args)
+        key = (cls, args, tuple(type(a) for a in args))
         if key not in cls._all_types:
             cls._all_types[key] = type(
                 cls.__name__,

tests/conftest.py

@@ -14,7 +14,8 @@ def pytest_addoption(parser):
 
 
 @pytest.fixture(
-    scope="function", params=[pytest.param(c, id=c.id) for c in SHAPE_CASES]
+    scope="function",
+    params=[pytest.param(c, id=c.id, marks=c.pytest_marks) for c in SHAPE_CASES],
 )
 def shape_cases(request, tmp_output_dir_func) -> ValidationCase:
     case: ValidationCase = request.param.model_copy()
@@ -23,7 +24,8 @@ def shape_cases(request, tmp_output_dir_func) -> ValidationCase:
 
 
 @pytest.fixture(
-    scope="function", params=[pytest.param(c, id=c.id) for c in DTYPE_CASES]
+    scope="function",
+    params=[pytest.param(c, id=c.id, marks=c.pytest_marks) for c in DTYPE_CASES],
 )
 def dtype_cases(request, tmp_output_dir_func) -> ValidationCase:
     case: ValidationCase = request.param.model_copy()

tests/test_interface/conftest.py

@@ -61,10 +61,7 @@ def interface_cases(request) -> InterfaceCase:
 
 
 @pytest.fixture(
-    params=(
-        pytest.param(p, id=p.id, marks=getattr(pytest.mark, p.interface.interface.name))
-        for p in ALL_CASES
-    )
+    params=(pytest.param(p, id=p.id, marks=p.pytest_marks) for p in ALL_CASES)
 )
 def all_cases(interface_cases, request) -> ValidationCase:
     """
@@ -83,10 +80,7 @@ def all_cases(interface_cases, request) -> ValidationCase:
 
 
 @pytest.fixture(
-    params=(
-        pytest.param(p, id=p.id, marks=getattr(pytest.mark, p.interface.interface.name))
-        for p in ALL_CASES_PASSING
-    )
+    params=(pytest.param(p, id=p.id, marks=p.pytest_marks) for p in ALL_CASES_PASSING)
 )
 def all_passing_cases(request) -> ValidationCase:
     """
@@ -132,7 +126,7 @@ def all_passing_cases_instance(all_passing_cases, tmp_output_dir_func):
 
 @pytest.fixture(
     params=(
-        pytest.param(p, id=p.id, marks=getattr(pytest.mark, p.interface.interface.name))
+        pytest.param(p, id=p.id, marks=p.pytest_marks)
         for p in DTYPE_AND_INTERFACE_CASES_PASSING
     )
 )

tests/test_interface/test_interfaces.py

@@ -61,6 +61,18 @@ def test_interface_revalidate(all_passing_cases_instance):
     _ = type(all_passing_cases_instance)(array=all_passing_cases_instance.array)
 
 
+@pytest.mark.json_schema
+def test_interface_jsonschema(all_passing_cases_instance):
+    """
+    All interfaces should be able to generate json schema
+    for all combinations of dtype and shape
+
+    Note that this does not test for json schema correctness -
+    see ndarray tests for that
+    """
+    _ = all_passing_cases_instance.model_json_schema()
+
+
 @pytest.mark.xfail
 def test_interface_rematch(interface_cases, tmp_output_dir_func):
     """