Add tests for ArrayValue __array__ copy semantics (#710)

* Add numpy-backed ArrayValue tests

* Guard ArrayValue numpy tests on devdeps

* Use Setup module for ArrayValue numpy tests

Author: cjdoris

CondaPkg.toml

@@ -14,5 +14,6 @@ version = ">=3.10,<4"
 
 [dev.deps]
 matplotlib = ""
+numpy = ""
 pyside6 = ""
 python = "<3.14"

src/JlWrap/array.jl

@@ -355,22 +355,20 @@ class ArrayValue(AnyValue):
     @property
     def __array_interface__(self):
         return self._jl_callmethod($(pyjl_methodnum(pyjlarray_array_interface)))
-    def __array__(self, dtype=None):
+    def __array__(self, dtype=None, copy=None):
+        import numpy
         # convert to an array-like object
         arr = self
         if not (hasattr(arr, "__array_interface__") or hasattr(arr, "__array_struct__")):
+            if copy is False:
+                raise ValueError("copy=False is not supported when collecting ArrayValue data")
             # the first attempt collects into an Array
             arr = self._jl_callmethod($(pyjl_methodnum(pyjlarray_array__array)))
             if not (hasattr(arr, "__array_interface__") or hasattr(arr, "__array_struct__")):
                 # the second attempt collects into a PyObjectArray
                 arr = self._jl_callmethod($(pyjl_methodnum(pyjlarray_array__pyobjectarray)))
         # convert to a numpy array if numpy is available
-        try:
-            import numpy
-            arr = numpy.array(arr, dtype=dtype)
-        except ImportError:
-            pass
-        return arr
+        return numpy.array(arr, dtype=dtype, copy=copy)
     def to_numpy(self, dtype=None, copy=True, order="K"):
         import numpy
         return numpy.array(self, dtype=dtype, copy=copy, order=order)

test/JlWrap.jl

@@ -215,7 +215,7 @@
     end
 end
 
-@testitem "array" begin
+@testitem "array" setup=[Setup] begin
     @testset "type" begin
         @test pyis(pytype(pyjl(fill(nothing))), PythonCall.pyjlarraytype)
         @test pyis(pytype(pyjl([1 2; 3 4])), PythonCall.pyjlarraytype)
@@ -313,6 +313,42 @@ end
         @test pyjlvalue(x) == [0 2; 3 4]
         @test pyjlvalue(y) == [1 2; 3 4]
     end
+    @testset "__array__" begin
+        if Setup.devdeps
+            np = pyimport("numpy")
+
+            numeric = pyjl(Float64[1, 2, 3])
+            numeric_array = numeric.__array__()
+            @test pyisinstance(numeric_array, np.ndarray)
+            @test pyconvert(Vector{Float64}, numeric_array) == [1.0, 2.0, 3.0]
+
+            numeric_no_copy = numeric.__array__(copy=false)
+            numeric_data = pyjlvalue(numeric)
+            numeric_data[1] = 42.0
+            @test pyconvert(Vector{Float64}, numeric_no_copy) == [42.0, 2.0, 3.0]
+
+            string_array = pyjl(["a", "b"])
+            string_result = string_array.__array__()
+            @test pyisinstance(string_result, np.ndarray)
+            @test pyconvert(Vector{String}, pybuiltins.list(string_result)) == ["a", "b"]
+
+            err = try
+                string_array.__array__(copy=false)
+                nothing
+            catch err
+                err
+            end
+            @test err !== nothing
+            @test err isa PythonCall.PyException
+            @test pyis(err._t, pybuiltins.ValueError)
+            @test occursin(
+                "copy=False is not supported when collecting ArrayValue data",
+                sprint(showerror, err),
+            )
+        else
+            @test_skip Setup.devdeps
+        end
+    end
     @testset "array_interface" begin
         x = pyjl(Float32[1 2 3; 4 5 6]).__array_interface__
         @test pyisinstance(x, pybuiltins.dict)