fix: conditionally define generic NumPy NDArray alias

modules/python/src2/typing_stubs_generation/generation.py

@@ -15,7 +15,8 @@ from .nodes import (ASTNode, ASTNodeType, NamespaceNode, ClassNode, FunctionNode
                     EnumerationNode, ConstantNode)
 
 from .nodes.type_node import (TypeNode, AliasTypeNode, AliasRefTypeNode,
-                              AggregatedTypeNode, ASTNodeTypeNode)
+                              AggregatedTypeNode, ASTNodeTypeNode,
+                              ConditionalAliasTypeNode, PrimitiveTypeNode)
 
 
 def generate_typing_stubs(root: NamespaceNode, output_path: Path):
@@ -682,28 +683,37 @@ def _generate_typing_module(root: NamespaceNode, output_path: Path) -> None:
             f"Provided type node '{type_node.ctype_name}' is not an aggregated type"
 
         for item in filter(lambda i: isinstance(i, AliasRefTypeNode), type_node):
-            register_alias(PREDEFINED_TYPES[item.ctype_name])  # type: ignore
+            type_node = PREDEFINED_TYPES[item.ctype_name]
+            if isinstance(type_node, AliasTypeNode):
+                register_alias(type_node)
+            elif isinstance(type_node, ConditionalAliasTypeNode):
+                conditional_type_nodes[type_node.ctype_name] = type_node
 
-    def create_alias_for_enum_node(enum_node: ASTNode) -> AliasTypeNode:
-        """Create int alias corresponding to the given enum node.
+    def create_alias_for_enum_node(enum_node_alias: AliasTypeNode) -> ConditionalAliasTypeNode:
+        """Create conditional int alias corresponding to the given enum node.
 
         Args:
-            enum_node (ASTNodeTypeNode): Enumeration node to create int alias for.
+            enum_node (AliasTypeNode): Enumeration node to create conditional
+                int alias for.
 
         Returns:
-            AliasTypeNode: int alias node with same export name as enum.
+            ConditionalAliasTypeNode: conditional int alias node with same
+                export name as enum.
         """
+        enum_node = enum_node_alias.ast_node
         assert enum_node.node_type == ASTNodeType.Enumeration, \
             f"{enum_node} has wrong node type. Expected type: Enumeration."
 
         enum_export_name, enum_module_name = get_enum_module_and_export_name(
             enum_node
         )
-        enum_full_export_name = f"{enum_module_name}.{enum_export_name}"
-        alias_node = AliasTypeNode.int_(enum_full_export_name,
-                                        enum_export_name)
-        type_checking_time_definitions.add(alias_node)
-        return alias_node
+        return ConditionalAliasTypeNode(
+            enum_export_name,
+            "typing.TYPE_CHECKING",
+            positive_branch_type=enum_node_alias,
+            negative_branch_type=PrimitiveTypeNode.int_(enum_export_name),
+            condition_required_imports=("import typing", )
+        )
 
     def register_alias(alias_node: AliasTypeNode) -> None:
         typename = alias_node.typename
@@ -726,11 +736,15 @@ def _generate_typing_module(root: NamespaceNode, output_path: Path) -> None:
                     continue
                 if item.ast_node.node_type != ASTNodeType.Enumeration:
                     continue
-                alias_node.value.items[i] = create_alias_for_enum_node(item.ast_node)
+                enum_node = create_alias_for_enum_node(item)
+                alias_node.value.items[i] = enum_node
+                conditional_type_nodes[enum_node.ctype_name] = enum_node
 
         if isinstance(alias_node.value, ASTNodeTypeNode) \
                 and alias_node.value.ast_node == ASTNodeType.Enumeration:
-            alias_node.value = create_alias_for_enum_node(alias_node.ast_node)
+            enum_node = create_alias_for_enum_node(alias_node.ast_node)
+            conditional_type_nodes[enum_node.ctype_name] = enum_node
+            return
 
         # Strip module prefix from aliased types
         aliases[typename] = alias_node.value.full_typename.replace(
@@ -744,7 +758,7 @@ def _generate_typing_module(root: NamespaceNode, output_path: Path) -> None:
 
     required_imports: Set[str] = set()
     aliases: Dict[str, str] = {}
-    type_checking_time_definitions: Set[AliasTypeNode] = set()
+    conditional_type_nodes: Dict[str, ConditionalAliasTypeNode] = {}
 
     # Resolve each node and register aliases
     TypeNode.compatible_to_runtime_usage = True
@@ -752,6 +766,12 @@ def _generate_typing_module(root: NamespaceNode, output_path: Path) -> None:
         node.resolve(root)
         if isinstance(node, AliasTypeNode):
             register_alias(node)
+        elif isinstance(node, ConditionalAliasTypeNode):
+            conditional_type_nodes[node.ctype_name] = node
+
+    for node in conditional_type_nodes.values():
+        for required_import in node.required_definition_imports:
+            required_imports.add(required_import)
 
     output_stream = StringIO()
     output_stream.write("__all__ = [\n")
@@ -762,12 +782,10 @@ def _generate_typing_module(root: NamespaceNode, output_path: Path) -> None:
     _write_required_imports(required_imports, output_stream)
 
     # Add type checking time definitions as generated __init__.py content
-    for alias in type_checking_time_definitions:
-        output_stream.write("if typing.TYPE_CHECKING:\n    ")
-        output_stream.write(f"{alias.typename} = {alias.ctype_name}\nelse:\n")
-        output_stream.write(f"    {alias.typename} = {alias.value.ctype_name}\n")
-    if type_checking_time_definitions:
-        output_stream.write("\n\n")
+    for _, type_node in conditional_type_nodes.items():
+        output_stream.write(f"if {type_node.condition}:\n    ")
+        output_stream.write(f"{type_node.typename} = {type_node.positive_branch_type.full_typename}\nelse:\n")
+        output_stream.write(f"    {type_node.typename} = {type_node.negative_branch_type.full_typename}\n\n\n")
 
     for alias_name, alias_type in aliases.items():
         output_stream.write(f"{alias_name} = {alias_type}\n")

modules/python/src2/typing_stubs_generation/nodes/type_node.py

@@ -307,14 +307,31 @@ class AliasTypeNode(TypeNode):
         return cls(ctype_name, PrimitiveTypeNode.float_(), export_name, doc)
 
     @classmethod
-    def array_(cls, ctype_name: str, shape: Optional[Tuple[int, ...]],
-               dtype: Optional[str] = None, export_name: Optional[str] = None,
-               doc: Optional[str] = None):
+    def array_ref_(cls, ctype_name: str, array_ref_name: str,
+                   shape: Optional[Tuple[int, ...]],
+                   dtype: Optional[str] = None,
+                   export_name: Optional[str] = None,
+                   doc: Optional[str] = None):
+        """Create alias to array reference alias `array_ref_name`.
+
+        This is required to preserve backward compatibility with Python < 3.9
+        and NumPy 1.20, when NumPy module introduces generics support.
+
+        Args:
+            ctype_name (str): Name of the alias.
+            array_ref_name (str): Name of the conditional array alias.
+            shape (Optional[Tuple[int, ...]]): Array shape.
+            dtype (Optional[str], optional): Array type.  Defaults to None.
+            export_name (Optional[str], optional): Alias export name.
+                Defaults to None.
+            doc (Optional[str], optional): Documentation string for alias.
+                Defaults to None.
+        """
         if doc is None:
-            doc = "Shape: " + str(shape)
+            doc = f"NDArray(shape={shape}, dtype={dtype})"
         else:
-            doc += ". Shape: " + str(shape)
-        return cls(ctype_name, NDArrayTypeNode(ctype_name, shape, dtype),
+            doc += f". NDArray(shape={shape}, dtype={dtype})"
+        return cls(ctype_name, AliasRefTypeNode(array_ref_name),
                    export_name, doc)
 
     @classmethod
@@ -376,24 +393,112 @@ class AliasTypeNode(TypeNode):
                    export_name, doc)
 
 
-class NDArrayTypeNode(TypeNode):
-    """Type node representing NumPy ndarray.
+class ConditionalAliasTypeNode(TypeNode):
+    """Type node representing an alias protected by condition checked in runtime.
+    Example:
+    ```python
+    if numpy.lib.NumpyVersion(numpy.__version__) > "1.20.0" and sys.version_info >= (3, 9)
+        NumPyArray = numpy.ndarray[typing.Any, numpy.dtype[numpy.generic]]
+    else:
+        NumPyArray = numpy.ndarray
+    ```
+    is defined as follows:
+    ```python
+
+    ConditionalAliasTypeNode(
+        "NumPyArray",
+        'numpy.lib.NumpyVersion(numpy.__version__) > "1.20.0" and sys.version_info >= (3, 9)',
+        NDArrayTypeNode("NumPyArray"),
+        NDArrayTypeNode("NumPyArray", use_numpy_generics=False),
+        condition_required_imports=("import numpy", "import sys")
+    )
+    ```
     """
-    def __init__(self, ctype_name: str, shape: Optional[Tuple[int, ...]] = None,
-                 dtype: Optional[str] = None) -> None:
+    def __init__(self, ctype_name: str, condition: str,
+                 positive_branch_type: TypeNode,
+                 negative_branch_type: TypeNode,
+                 export_name: Optional[str] = None,
+                 condition_required_imports: Sequence[str] = ()) -> None:
         super().__init__(ctype_name)
-        self.shape = shape
-        self.dtype = dtype
+        self.condition = condition
+        self.positive_branch_type = positive_branch_type
+        self.positive_branch_type.ctype_name = self.ctype_name
+        self.negative_branch_type = negative_branch_type
+        self.negative_branch_type.ctype_name = self.ctype_name
+        self._export_name = export_name
+        self._condition_required_imports = condition_required_imports
 
     @property
     def typename(self) -> str:
-        return "numpy.ndarray[{shape}, numpy.dtype[{dtype}]]".format(
-            # NOTE: Shape is not fully supported yet
-            # shape=self.shape if self.shape is not None else "typing.Any",
-            shape="typing.Any",
-            dtype=self.dtype if self.dtype is not None else "numpy.generic"
+        if self._export_name is not None:
+            return self._export_name
+        return self.ctype_name
+
+    @property
+    def full_typename(self) -> str:
+        return "cv2.typing." + self.typename
+
+    @property
+    def required_definition_imports(self) -> Generator[str, None, None]:
+        yield from self.positive_branch_type.required_usage_imports
+        yield from self.negative_branch_type.required_usage_imports
+        yield from self._condition_required_imports
+
+    @property
+    def required_usage_imports(self) -> Generator[str, None, None]:
+        yield "import cv2.typing"
+
+    @property
+    def is_resolved(self) -> bool:
+        return self.positive_branch_type.is_resolved \
+                and self.negative_branch_type.is_resolved
+
+    def resolve(self, root: ASTNode):
+        try:
+            self.positive_branch_type.resolve(root)
+            self.negative_branch_type.resolve(root)
+        except TypeResolutionError as e:
+            raise TypeResolutionError(
+                'Failed to resolve alias "{}" exposed as "{}"'.format(
+                    self.ctype_name, self.typename
+                )
+            ) from e
+
+    @classmethod
+    def numpy_array_(cls, ctype_name: str, export_name: Optional[str] = None,
+                     shape: Optional[Tuple[int, ...]] = None,
+                     dtype: Optional[str] = None):
+        return cls(
+            ctype_name,
+            ('numpy.lib.NumpyVersion(numpy.__version__) > "1.20.0" '
+             'and sys.version_info >= (3, 9)'),
+            NDArrayTypeNode(ctype_name, shape, dtype),
+            NDArrayTypeNode(ctype_name, shape, dtype,
+                            use_numpy_generics=False),
+            condition_required_imports=("import numpy", "import sys")
         )
 
+
+class NDArrayTypeNode(TypeNode):
+    """Type node representing NumPy ndarray.
+    """
+    def __init__(self, ctype_name: str,
+                 shape: Optional[Tuple[int, ...]] = None,
+                 dtype: Optional[str] = None,
+                 use_numpy_generics: bool = True) -> None:
+        super().__init__(ctype_name)
+        self.shape = shape
+        self.dtype = dtype
+        self._use_numpy_generics = use_numpy_generics
+
+    @property
+    def typename(self) -> str:
+        if self._use_numpy_generics:
+            # NOTE: Shape is not fully supported yet
+            dtype = self.dtype if self.dtype is not None else "numpy.generic"
+            return f"numpy.ndarray[typing.Any, numpy.dtype[{dtype}]]"
+        return "numpy.ndarray"
+
     @property
     def required_usage_imports(self) -> Generator[str, None, None]:
         yield "import numpy"

modules/python/src2/typing_stubs_generation/predefined_types.py

@@ -1,7 +1,7 @@
 from .nodes.type_node import (
     AliasTypeNode, AliasRefTypeNode, PrimitiveTypeNode,
     ASTNodeTypeNode, NDArrayTypeNode, NoneTypeNode, SequenceTypeNode,
-    TupleTypeNode, UnionTypeNode, AnyTypeNode
+    TupleTypeNode, UnionTypeNode, AnyTypeNode, ConditionalAliasTypeNode
 )
 
 # Set of predefined types used to cover cases when library doesn't
@@ -30,12 +30,15 @@ _PREDEFINED_TYPES = (
     PrimitiveTypeNode.str_("char"),
     PrimitiveTypeNode.str_("String"),
     PrimitiveTypeNode.str_("c_string"),
+    ConditionalAliasTypeNode.numpy_array_("NumPyArrayGeneric"),
+    ConditionalAliasTypeNode.numpy_array_("NumPyArrayFloat32", dtype="numpy.float32"),
+    ConditionalAliasTypeNode.numpy_array_("NumPyArrayFloat64", dtype="numpy.float64"),
     NoneTypeNode("void"),
     AliasTypeNode.int_("void*", "IntPointer", "Represents an arbitrary pointer"),
     AliasTypeNode.union_(
         "Mat",
         items=(ASTNodeTypeNode("Mat", module_name="cv2.mat_wrapper"),
-               NDArrayTypeNode("Mat")),
+               AliasRefTypeNode("NumPyArrayGeneric")),
         export_name="MatLike"
     ),
     AliasTypeNode.sequence_("MatShape", PrimitiveTypeNode.int_()),
@@ -137,10 +140,22 @@ _PREDEFINED_TYPES = (
                                 ASTNodeTypeNode("gapi.wip.draw.Mosaic"),
                                 ASTNodeTypeNode("gapi.wip.draw.Poly"))),
     SequenceTypeNode("Prims", AliasRefTypeNode("Prim")),
-    AliasTypeNode.array_("Matx33f", (3, 3), "numpy.float32"),
-    AliasTypeNode.array_("Matx33d", (3, 3), "numpy.float64"),
-    AliasTypeNode.array_("Matx44f", (4, 4), "numpy.float32"),
-    AliasTypeNode.array_("Matx44d", (4, 4), "numpy.float64"),
+    AliasTypeNode.array_ref_("Matx33f",
+                             array_ref_name="NumPyArrayFloat32",
+                             shape=(3, 3),
+                             dtype="numpy.float32"),
+    AliasTypeNode.array_ref_("Matx33d",
+                             array_ref_name="NumPyArrayFloat64",
+                             shape=(3, 3),
+                             dtype="numpy.float64"),
+    AliasTypeNode.array_ref_("Matx44f",
+                             array_ref_name="NumPyArrayFloat32",
+                             shape=(4, 4),
+                             dtype="numpy.float32"),
+    AliasTypeNode.array_ref_("Matx44d",
+                             array_ref_name="NumPyArrayFloat64",
+                             shape=(4, 4),
+                             dtype="numpy.float64"),
     NDArrayTypeNode("vector<uchar>", dtype="numpy.uint8"),
     NDArrayTypeNode("vector_uchar", dtype="numpy.uint8"),
     TupleTypeNode("GMat2", items=(ASTNodeTypeNode("GMat"),