allow customizing the expected array type (#38)

* convert the `array_type` property to a static method

This will allow choosing the return type depending on the operation.

* call `array_type` with `op`

* change the numpy tests, as well

Author: keewis

xarray_array_testing/base.py

@@ -12,9 +12,8 @@ class DuckArrayTestMixin(ABC):
     def xp() -> ModuleType:
         pass
 
-    @property
-    @abc.abstractmethod
-    def array_type(self) -> type[duckarray]:
+    @staticmethod
+    def array_type(op: str) -> type[duckarray]:
         pass
 
     @staticmethod

xarray_array_testing/creation.py

@@ -10,4 +10,4 @@ class CreationTests(DuckArrayTestMixin):
     def test_create_variable(self, data):
         variable = data.draw(xrst.variables(array_strategy_fn=self.array_strategy_fn))
 
-        assert isinstance(variable.data, self.array_type)
+        assert isinstance(variable.data, self.array_type("__init__"))

xarray_array_testing/indexing.py

@@ -95,7 +95,9 @@ def test_variable_isel_orthogonal(self, data):
             raw_indexers = {dim: idx.get(dim, slice(None)) for dim in variable.dims}
             expected = variable.data[*raw_indexers.values()]
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(
+            actual, self.array_type("orthogonal_indexing")
+        ), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)
 
     @given(st.data())
@@ -109,5 +111,7 @@ def test_variable_isel_vectorized(self, data):
             raw_indexers = {dim: idx.get(dim, slice(None)) for dim in variable.dims}
             expected = variable.data[*raw_indexers.values()]
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(
+            actual, self.array_type("vectorized_indexing")
+        ), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)

xarray_array_testing/reduction.py

@@ -25,7 +25,7 @@ def test_variable_numerical_reduce(self, op, data):
             # compute using xp.<OP>(array)
             expected = getattr(self.xp, op)(variable.data)
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(actual, self.array_type(op)), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)
 
     @pytest.mark.parametrize("op", ["all", "any"])
@@ -39,7 +39,7 @@ def test_variable_boolean_reduce(self, op, data):
             # compute using xp.<OP>(array)
             expected = getattr(self.xp, op)(variable.data)
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(actual, self.array_type(op)), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)
 
     @pytest.mark.parametrize("op", ["max", "min"])
@@ -53,7 +53,7 @@ def test_variable_order_reduce(self, op, data):
             # compute using xp.<OP>(array)
             expected = getattr(self.xp, op)(variable.data)
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(actual, self.array_type(op)), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)
 
     @pytest.mark.parametrize("op", ["argmax", "argmin"])
@@ -96,5 +96,5 @@ def test_variable_cumulative_reduce(self, op, data):
             for axis in range(variable.ndim):
                 expected = getattr(self.xp, array_api_names[op])(expected, axis=axis)
 
-        assert isinstance(actual, self.array_type), f"wrong type: {type(actual)}"
+        assert isinstance(actual, self.array_type(op)), f"wrong type: {type(actual)}"
         self.assert_equal(actual, expected)

xarray_array_testing/tests/test_numpy.py

@@ -18,8 +18,8 @@ class NumpyTestMixin(DuckArrayTestMixin):
     def xp(self) -> ModuleType:
         return np
 
-    @property
-    def array_type(self) -> type[np.ndarray]:
+    @staticmethod
+    def array_type(op: str) -> type[np.ndarray]:
         return np.ndarray
 
     @staticmethod