Merge pull request #2079 from Hoblovski/fix/star-unpack

Fix unhandled '*' operator in infer_node

conftest.py

@@ -156,6 +156,14 @@ def jedi_path():
     return os.path.dirname(__file__)
 
 
+@pytest.fixture()
+def skip_pre_python311(environment):
+    if environment.version_info < (3, 11):
+        # This if is just needed to avoid that tests ever skip way more than
+        # they should for all Python versions.
+        pytest.skip()
+
+
 @pytest.fixture()
 def skip_pre_python38(environment):
     if environment.version_info < (3, 8):

jedi/inference/syntax_tree.py

@@ -251,6 +251,8 @@ def _infer_node(context, element):
         return NO_VALUES
     elif typ == 'namedexpr_test':
         return context.infer_node(element.children[2])
+    elif typ == 'star_expr':
+        return NO_VALUES
     else:
         return infer_or_test(context, element)
 

jedi/inference/value/klass.py

@@ -36,6 +36,10 @@ py__doc__()                            Returns the docstring for a value.
 ====================================== ========================================
 
 """
+from __future__ import annotations
+
+from typing import List, Optional, Tuple
+
 from jedi import debug
 from jedi.parser_utils import get_cached_parent_scope, expr_is_dotted, \
     function_is_property
@@ -47,11 +51,15 @@ from jedi.inference.filters import ParserTreeFilter
 from jedi.inference.names import TreeNameDefinition, ValueName
 from jedi.inference.arguments import unpack_arglist, ValuesArguments
 from jedi.inference.base_value import ValueSet, iterator_to_value_set, \
-    NO_VALUES
+    NO_VALUES, ValueWrapper
 from jedi.inference.context import ClassContext
-from jedi.inference.value.function import FunctionAndClassBase
+from jedi.inference.value.function import FunctionAndClassBase, FunctionMixin
+from jedi.inference.value.decorator import Decoratee
 from jedi.inference.gradual.generics import LazyGenericManager, TupleGenericManager
 from jedi.plugins import plugin_manager
+from inspect import Parameter
+from jedi.inference.names import BaseTreeParamName
+from jedi.inference.signature import AbstractSignature
 
 
 class ClassName(TreeNameDefinition):
@@ -129,6 +137,65 @@ class ClassFilter(ParserTreeFilter):
         return [name for name in names if self._access_possible(name)]
 
 
+def init_param_value(arg_nodes) -> Optional[bool]:
+    """
+    Returns:
+
+    - ``True`` if ``@dataclass(init=True)``
+    - ``False`` if ``@dataclass(init=False)``
+    - ``None`` if not specified ``@dataclass()``
+    """
+    for arg_node in arg_nodes:
+        if (
+            arg_node.type == "argument"
+            and arg_node.children[0].value == "init"
+        ):
+            if arg_node.children[2].value == "False":
+                return False
+            elif arg_node.children[2].value == "True":
+                return True
+
+    return None
+
+
+def get_dataclass_param_names(cls) -> List[DataclassParamName]:
+    """
+    ``cls`` is a :class:`ClassMixin`. The type is only documented as mypy would
+    complain that some fields are missing.
+
+    .. code:: python
+
+        @dataclass
+        class A:
+            a: int
+            b: str = "toto"
+
+    For the previous example, the param names would be ``a`` and ``b``.
+    """
+    param_names = []
+    filter_ = cls.as_context().get_global_filter()
+    for name in sorted(filter_.values(), key=lambda name: name.start_pos):
+        d = name.tree_name.get_definition()
+        annassign = d.children[1]
+        if d.type == 'expr_stmt' and annassign.type == 'annassign':
+            node = annassign.children[1]
+            if node.type == "atom_expr" and node.children[0].value == "ClassVar":
+                continue
+
+            if len(annassign.children) < 4:
+                default = None
+            else:
+                default = annassign.children[3]
+
+            param_names.append(DataclassParamName(
+                parent_context=cls.parent_context,
+                tree_name=name.tree_name,
+                annotation_node=annassign.children[1],
+                default_node=default,
+            ))
+    return param_names
+
+
 class ClassMixin:
     def is_class(self):
         return True
@@ -221,6 +288,73 @@ class ClassMixin:
                     assert x is not None
                     yield x
 
+    def _has_dataclass_transform_metaclasses(self) -> Tuple[bool, Optional[bool]]:
+        for meta in self.get_metaclasses():  # type: ignore[attr-defined]
+            if (
+                isinstance(meta, Decoratee)
+                # Internal leakage :|
+                and isinstance(meta._wrapped_value, DataclassTransformer)
+            ):
+                return True, meta._wrapped_value.init_mode_from_new()
+
+        return False, None
+
+    def _get_dataclass_transform_signatures(self) -> List[DataclassSignature]:
+        """
+        Returns: A non-empty list if the class has dataclass semantics else an
+        empty list.
+
+        The dataclass-like semantics will be assumed for any class that directly
+        or indirectly derives from the decorated class or uses the decorated
+        class as a metaclass.
+        """
+        param_names = []
+        is_dataclass_transform = False
+        default_init_mode: Optional[bool] = None
+        for cls in reversed(list(self.py__mro__())):
+            if not is_dataclass_transform:
+
+                # If dataclass_transform is applied to a class, dataclass-like semantics
+                # will be assumed for any class that directly or indirectly derives from
+                # the decorated class or uses the decorated class as a metaclass.
+                if (
+                    isinstance(cls, DataclassTransformer)
+                    and cls.init_mode_from_init_subclass
+                ):
+                    is_dataclass_transform = True
+                    default_init_mode = cls.init_mode_from_init_subclass
+
+                elif (
+                    # Some object like CompiledValues would not be compatible
+                    isinstance(cls, ClassMixin)
+                ):
+                    is_dataclass_transform, default_init_mode = (
+                        cls._has_dataclass_transform_metaclasses()
+                    )
+
+                # Attributes on the decorated class and its base classes are not
+                # considered to be fields.
+                if is_dataclass_transform:
+                    continue
+
+            # All inherited classes behave like dataclass semantics
+            if (
+                is_dataclass_transform
+                and isinstance(cls, ClassValue)
+                and (
+                    cls.init_param_mode()
+                    or (cls.init_param_mode() is None and default_init_mode)
+                )
+            ):
+                param_names.extend(
+                    get_dataclass_param_names(cls)
+                )
+
+        if is_dataclass_transform:
+            return [DataclassSignature(cls, param_names)]
+        else:
+            return []
+
     def get_signatures(self):
         # Since calling staticmethod without a function is illegal, the Jedi
         # plugin doesn't return anything. Therefore call directly and get what
@@ -232,7 +366,12 @@ class ClassMixin:
                 return sigs
         args = ValuesArguments([])
         init_funcs = self.py__call__(args).py__getattribute__('__init__')
-        return [sig.bind(self) for sig in init_funcs.get_signatures()]
+
+        dataclass_sigs = self._get_dataclass_transform_signatures()
+        if dataclass_sigs:
+            return dataclass_sigs
+        else:
+            return [sig.bind(self) for sig in init_funcs.get_signatures()]
 
     def _as_context(self):
         return ClassContext(self)
@@ -319,6 +458,158 @@ class ClassMixin:
         return ValueSet({self})
 
 
+class DataclassParamName(BaseTreeParamName):
+    """
+    Represent a field declaration on a class with dataclass semantics.
+    """
+
+    def __init__(self, parent_context, tree_name, annotation_node, default_node):
+        super().__init__(parent_context, tree_name)
+        self.annotation_node = annotation_node
+        self.default_node = default_node
+
+    def get_kind(self):
+        return Parameter.POSITIONAL_OR_KEYWORD
+
+    def infer(self):
+        if self.annotation_node is None:
+            return NO_VALUES
+        else:
+            return self.parent_context.infer_node(self.annotation_node)
+
+
+class DataclassSignature(AbstractSignature):
+    """
+    It represents the ``__init__`` signature of a class with dataclass semantics.
+
+    .. code:: python
+
+    """
+    def __init__(self, value, param_names):
+        super().__init__(value)
+        self._param_names = param_names
+
+    def get_param_names(self, resolve_stars=False):
+        return self._param_names
+
+
+class DataclassDecorator(ValueWrapper, FunctionMixin):
+    """
+    A dataclass(-like) decorator with custom parameters.
+
+    .. code:: python
+
+        @dataclass(init=True) # this
+        class A: ...
+
+        @dataclass_transform
+        def create_model(*, init=False): pass
+
+        @create_model(init=False) # or this
+        class B: ...
+    """
+
+    def __init__(self, function, arguments, default_init: bool = True):
+        """
+        Args:
+            function: Decoratee | function
+            arguments: The parameters to the dataclass function decorator
+            default_init: Boolean to indicate the default init value
+        """
+        super().__init__(function)
+        argument_init = self._init_param_value(arguments)
+        self.init_param_mode = (
+            argument_init if argument_init is not None else default_init
+        )
+
+    def _init_param_value(self, arguments) -> Optional[bool]:
+        if not arguments.argument_node:
+            return None
+
+        arg_nodes = (
+            arguments.argument_node.children
+            if arguments.argument_node.type == "arglist"
+            else [arguments.argument_node]
+        )
+
+        return init_param_value(arg_nodes)
+
+
+class DataclassTransformer(ValueWrapper, ClassMixin):
+    """
+    A class decorated with the ``dataclass_transform`` decorator. dataclass-like
+    semantics will be assumed for any class that directly or indirectly derives
+    from the decorated class or uses the decorated class as a metaclass.
+    Attributes on the decorated class and its base classes are not considered to
+    be fields.
+    """
+    def __init__(self, wrapped_value):
+        super().__init__(wrapped_value)
+
+    def init_mode_from_new(self) -> bool:
+        """Default value if missing is ``True``"""
+        new_methods = self._wrapped_value.py__getattribute__("__new__")
+
+        if not new_methods:
+            return True
+
+        new_method = list(new_methods)[0]
+
+        for param in new_method.get_param_names():
+            if (
+                param.string_name == "init"
+                and param.default_node
+                and param.default_node.type == "keyword"
+            ):
+                if param.default_node.value == "False":
+                    return False
+                elif param.default_node.value == "True":
+                    return True
+
+        return True
+
+    @property
+    def init_mode_from_init_subclass(self) -> Optional[bool]:
+        # def __init_subclass__(cls) -> None: ... is hardcoded in the typeshed
+        # so the extra parameters can not be inferred.
+        return True
+
+
+class DataclassWrapper(ValueWrapper, ClassMixin):
+    """
+    A class with dataclass semantics from a decorator. The init parameters are
+    only from the current class and parent classes decorated where the ``init``
+    parameter was ``True``.
+
+    .. code:: python
+
+        @dataclass
+        class A: ... # this
+
+        @dataclass_transform
+        def create_model(): pass
+
+        @create_model()
+        class B: ... # or this
+    """
+
+    def __init__(
+        self, wrapped_value, should_generate_init: bool
+    ):
+        super().__init__(wrapped_value)
+        self.should_generate_init = should_generate_init
+
+    def get_signatures(self):
+        param_names = []
+        for cls in reversed(list(self.py__mro__())):
+            if (
+                isinstance(cls, DataclassWrapper)
+                and cls.should_generate_init
+            ):
+                param_names.extend(get_dataclass_param_names(cls))
+        return [DataclassSignature(cls, param_names)]
+
+
 class ClassValue(ClassMixin, FunctionAndClassBase, metaclass=CachedMetaClass):
     api_type = 'class'
 
@@ -385,6 +676,19 @@ class ClassValue(ClassMixin, FunctionAndClassBase, metaclass=CachedMetaClass):
                         return values
         return NO_VALUES
 
+    def init_param_mode(self) -> Optional[bool]:
+        """
+        It returns ``True`` if ``class X(init=False):`` else ``False``.
+        """
+        bases_arguments = self._get_bases_arguments()
+
+        if bases_arguments.argument_node.type != "arglist":
+            # If it is not inheriting from the base model and having
+            # extra parameters, then init behavior is not changed.
+            return None
+
+        return init_param_value(bases_arguments.argument_node.children)
+
     @plugin_manager.decorate()
     def get_metaclass_signatures(self, metaclasses):
         return []

jedi/plugins/stdlib.py

@@ -11,7 +11,6 @@ compiled module that returns the types for C-builtins.
 """
 import parso
 import os
-from inspect import Parameter
 
 from jedi import debug
 from jedi.inference.utils import safe_property
@@ -25,15 +24,20 @@ from jedi.inference.value.instance import \
 from jedi.inference.base_value import ContextualizedNode, \
     NO_VALUES, ValueSet, ValueWrapper, LazyValueWrapper
 from jedi.inference.value import ClassValue, ModuleValue
-from jedi.inference.value.klass import ClassMixin
+from jedi.inference.value.decorator import Decoratee
+from jedi.inference.value.klass import (
+    DataclassWrapper,
+    DataclassDecorator,
+    DataclassTransformer,
+)
 from jedi.inference.value.function import FunctionMixin
 from jedi.inference.value import iterable
 from jedi.inference.lazy_value import LazyTreeValue, LazyKnownValue, \
     LazyKnownValues
-from jedi.inference.names import ValueName, BaseTreeParamName
+from jedi.inference.names import ValueName
 from jedi.inference.filters import AttributeOverwrite, publish_method, \
     ParserTreeFilter, DictFilter
-from jedi.inference.signature import AbstractSignature, SignatureWrapper
+from jedi.inference.signature import SignatureWrapper
 
 
 # Copied from Python 3.6's stdlib.
@@ -591,63 +595,101 @@ def _random_choice(sequences):
 
 
 def _dataclass(value, arguments, callback):
+    """
+    Decorator entry points for dataclass.
+
+    1. dataclass decorator declaration with parameters
+    2. dataclass semantics on a class from a dataclass(-like) decorator
+    """
     for c in _follow_param(value.inference_state, arguments, 0):
         if c.is_class():
-            return ValueSet([DataclassWrapper(c)])
+            # Declare dataclass semantics on a class from a dataclass decorator
+            should_generate_init = (
+                # Customized decorator, init may be disabled
+                value.init_param_mode
+                if isinstance(value, DataclassDecorator)
+                # Bare dataclass decorator, always with init mode
+                else True
+            )
+            return ValueSet([DataclassWrapper(c, should_generate_init)])
         else:
-            return ValueSet([value])
+            # @dataclass(init=False)
+            # dataclass decorator customization
+            return ValueSet(
+                [
+                    DataclassDecorator(
+                        value,
+                        arguments=arguments,
+                        default_init=True,
+                    )
+                ]
+            )
+
     return NO_VALUES
 
 
-class DataclassWrapper(ValueWrapper, ClassMixin):
-    def get_signatures(self):
-        param_names = []
-        for cls in reversed(list(self.py__mro__())):
-            if isinstance(cls, DataclassWrapper):
-                filter_ = cls.as_context().get_global_filter()
-                # .values ordering is not guaranteed, at least not in
-                # Python < 3.6, when dicts where not ordered, which is an
-                # implementation detail anyway.
-                for name in sorted(filter_.values(), key=lambda name: name.start_pos):
-                    d = name.tree_name.get_definition()
-                    annassign = d.children[1]
-                    if d.type == 'expr_stmt' and annassign.type == 'annassign':
-                        if len(annassign.children) < 4:
-                            default = None
-                        else:
-                            default = annassign.children[3]
-                        param_names.append(DataclassParamName(
-                            parent_context=cls.parent_context,
-                            tree_name=name.tree_name,
-                            annotation_node=annassign.children[1],
-                            default_node=default,
-                        ))
-        return [DataclassSignature(cls, param_names)]
+def _dataclass_transform(value, arguments, callback):
+    """
+    Decorator entry points for dataclass_transform.
 
+    1. dataclass-like decorator instantiation from a dataclass_transform decorator
+    2. dataclass_transform decorator declaration with parameters
+    3. dataclass-like decorator declaration with parameters
+    4. dataclass-like semantics on a class from a dataclass-like decorator
+    """
+    for c in _follow_param(value.inference_state, arguments, 0):
+        if c.is_class():
+            is_dataclass_transform = (
+                value.name.string_name == "dataclass_transform"
+                # The decorator function from dataclass_transform acting as the
+                # dataclass decorator.
+                and not isinstance(value, Decoratee)
+                # The decorator function from dataclass_transform acting as the
+                # dataclass decorator with customized parameters
+                and not isinstance(value, DataclassDecorator)
+            )
 
-class DataclassSignature(AbstractSignature):
-    def __init__(self, value, param_names):
-        super().__init__(value)
-        self._param_names = param_names
-
-    def get_param_names(self, resolve_stars=False):
-        return self._param_names
-
-
-class DataclassParamName(BaseTreeParamName):
-    def __init__(self, parent_context, tree_name, annotation_node, default_node):
-        super().__init__(parent_context, tree_name)
-        self.annotation_node = annotation_node
-        self.default_node = default_node
-
-    def get_kind(self):
-        return Parameter.POSITIONAL_OR_KEYWORD
-
-    def infer(self):
-        if self.annotation_node is None:
-            return NO_VALUES
+            if is_dataclass_transform:
+                # Declare base class
+                return ValueSet([DataclassTransformer(c)])
+            else:
+                # Declare dataclass-like semantics on a class from a
+                # dataclass-like decorator
+                should_generate_init = value.init_param_mode
+                return ValueSet([DataclassWrapper(c, should_generate_init)])
+        elif c.is_function():
+            # dataclass-like decorator instantiation:
+            # @dataclass_transform
+            # def create_model()
+            return ValueSet(
+                [
+                    DataclassDecorator(
+                        value,
+                        arguments=arguments,
+                        default_init=True,
+                    )
+                ]
+            )
+        elif (
+            # @dataclass_transform
+            # def create_model(): pass
+            # @create_model(init=...)
+            isinstance(value, Decoratee)
+        ):
+            # dataclass (or like) decorator customization
+            return ValueSet(
+                [
+                    DataclassDecorator(
+                        value,
+                        arguments=arguments,
+                        default_init=value._wrapped_value.init_param_mode,
+                    )
+                ]
+            )
         else:
-            return self.parent_context.infer_node(self.annotation_node)
+            # dataclass_transform decorator with parameters; nothing impactful
+            return ValueSet([value])
+    return NO_VALUES
 
 
 class ItemGetterCallable(ValueWrapper):
@@ -798,22 +840,17 @@ _implemented = {
         # runtime_checkable doesn't really change anything and is just
         # adding logs for infering stuff, so we can safely ignore it.
         'runtime_checkable': lambda value, arguments, callback: NO_VALUES,
+        # Python 3.11+
+        'dataclass_transform': _dataclass_transform,
+    },
+    'typing_extensions': {
+        # Python <3.11
+        'dataclass_transform': _dataclass_transform,
     },
     'dataclasses': {
         # For now this works at least better than Jedi trying to understand it.
         'dataclass': _dataclass
     },
-    # attrs exposes declaration interface roughly compatible with dataclasses
-    # via attrs.define, attrs.frozen and attrs.mutable
-    # https://www.attrs.org/en/stable/names.html
-    'attr': {
-        'define': _dataclass,
-        'frozen': _dataclass,
-    },
-    'attrs': {
-        'define': _dataclass,
-        'frozen': _dataclass,
-    },
     'os.path': {
         'dirname': _create_string_input_function(os.path.dirname),
         'abspath': _create_string_input_function(os.path.abspath),

setup.py

@@ -47,6 +47,7 @@ setup(name='jedi',
               'colorama',
               'Django',
               'attrs',
+              'typing_extensions',
           ],
           'qa': [
               # latest version on 2025-06-16

test/completion/arrays.py

@@ -527,3 +527,11 @@ lc = [x for a, *x in [(1, '', 1.0)]]
 lc[0][0]
 #?
 lc[0][1]
+
+
+xy = (1,)
+x, y = *xy, None
+
+# whatever it is should not crash
+#?
+x

test/test_inference/test_signature.py

@@ -318,40 +318,511 @@ def test_wraps_signature(Script, code, signature):
 
 
 @pytest.mark.parametrize(
-    'start, start_params', [
-        ['@dataclass\nclass X:', []],
-        ['@dataclass(eq=True)\nclass X:', []],
-        [dedent('''
+    "start, start_params, include_params",
+    [
+        ["@dataclass\nclass X:", [], True],
+        ["@dataclass(eq=True)\nclass X:", [], True],
+        [
+            dedent(
+                """
          class Y():
              y: int
          @dataclass
-         class X(Y):'''), []],
-        [dedent('''
+         class X(Y):"""
+            ),
+            [],
+            True,
+        ],
+        [
+            dedent(
+                """
          @dataclass
          class Y():
              y: int
              z = 5
          @dataclass
-         class X(Y):'''), ['y']],
-    ]
+         class X(Y):"""
+            ),
+            ["y"],
+            True,
+        ],
+        [
+            dedent(
+                """
+         @dataclass
+         class Y():
+             y: int
+         class Z(Y): # Not included
+             z = 5
+         @dataclass
+         class X(Z):"""
+            ),
+            ["y"],
+            True,
+        ],
+        # init=False
+        [
+            dedent(
+                """
+            @dataclass(init=False)
+            class X:"""
+            ),
+            [],
+            False,
+        ],
+        [
+            dedent(
+                """
+            @dataclass(eq=True, init=False)
+            class X:"""
+            ),
+            [],
+            False,
+        ],
+        # custom init
+        [
+            dedent(
+                """
+        @dataclass()
+        class X:
+            def __init__(self, toto: str):
+                pass
+            """
+            ),
+            ["toto"],
+            False,
+        ],
+    ],
+    ids=[
+        "direct_transformed",
+        "transformed_with_params",
+        "subclass_transformed",
+        "both_transformed",
+        "intermediate_not_transformed",
+        "init_false",
+        "init_false_multiple",
+        "custom_init",
+    ],
 )
-def test_dataclass_signature(Script, skip_pre_python37, start, start_params):
+def test_dataclass_signature(
+    Script, skip_pre_python37, start, start_params, include_params, environment
+):
+    if environment.version_info < (3, 8):
+        # Final is not yet supported
+        price_type = "float"
+        price_type_infer = "float"
+    else:
+        price_type = "Final[float]"
+        price_type_infer = "object"
+
+    code = dedent(
+        f"""
+            name: str
+            foo = 3
+            blob: ClassVar[str]
+            price: {price_type}
+            quantity: int = 0.0
+
+        X("""
+    )
+
+    code = (
+        "from dataclasses import dataclass\n"
+        + "from typing import ClassVar, Final\n"
+        + start
+        + code
+    )
+
+    sig, = Script(code).get_signatures()
+    expected_params = (
+        [*start_params, "name", "price", "quantity"]
+        if include_params
+        else [*start_params]
+    )
+    assert [p.name for p in sig.params] == expected_params
+
+    if include_params:
+        quantity, = sig.params[-1].infer()
+        assert quantity.name == 'int'
+        price, = sig.params[-2].infer()
+        assert price.name == price_type_infer
+
+
+dataclass_transform_cases = [
+    # Attributes on the decorated class and its base classes
+    # are not considered to be fields.
+    # 1/ Declare dataclass transformer
+    # Base Class
+    ['@dataclass_transform\nclass X:', [], False],
+    # Base Class with params
+    ['@dataclass_transform(eq_default=True)\nclass X:', [], False],
+    # Subclass
+    [dedent('''
+        class Y():
+            y: int
+        @dataclass_transform
+        class X(Y):'''), [], False],
+    # 2/ Declare dataclass transformed
+    # Class based
+    [dedent('''
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+        class X(Y):'''), [], True],
+    # Class based with params
+    [dedent('''
+        @dataclass_transform(eq_default=True)
+        class Y():
+            y: int
+            z = 5
+        class X(Y):'''), [], True],
+    # Decorator based
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        @create_model
+        class X:'''), [], True],
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        class Y:
+            y: int
+        @create_model
+        class X(Y):'''), [], True],
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        @create_model
+        class Y:
+            y: int
+        @create_model
+        class X(Y):'''), ["y"], True],
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        @create_model
+        class Y:
+            y: int
+        class Z(Y):
+            z: int
+        @create_model
+        class X(Z):'''), ["y"], True],
+    # Metaclass based
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase):'''), [], True],
+    # 3/ Init custom init
+    [dedent('''
+    @dataclass_transform()
+    class Y():
+        y: int
+        z = 5
+    class X(Y):
+        def __init__(self, toto: str):
+            pass
+        '''), ["toto"], False],
+    # 4/ init=false
+    # Class based
+    # WARNING: Unsupported
+    # [dedent('''
+    #     @dataclass_transform
+    #     class Y():
+    #         y: int
+    #         z = 5
+    #         def __init_subclass__(
+    #             cls,
+    #             *,
+    #             init: bool = False,
+    #         )
+    #     class X(Y):'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+            def __init_subclass__(
+                cls,
+                *,
+                init: bool = False,
+            )
+        class X(Y, init=True):'''), [], True],
+    [dedent('''
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+            def __init_subclass__(
+                cls,
+                *,
+                init: bool = False,
+            )
+        class X(Y, init=False):'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+        class X(Y, init=False):'''), [], False],
+    # Decorator based
+    [dedent('''
+        @dataclass_transform
+        def create_model(init=False):
+            pass
+        @create_model()
+        class X:'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        def create_model(init=False):
+            pass
+        @create_model(init=True)
+        class X:'''), [], True],
+    [dedent('''
+        @dataclass_transform
+        def create_model(init=False):
+            pass
+        @create_model(init=False)
+        class X:'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        @create_model(init=False)
+        class X:'''), [], False],
+    # Metaclass based
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+            def __new__(
+                cls,
+                name,
+                bases,
+                namespace,
+                *,
+                init: bool = False,
+            ):
+                ...
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase):'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+            def __new__(
+                cls,
+                name,
+                bases,
+                namespace,
+                *,
+                init: bool = False,
+            ):
+                ...
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase, init=True):'''), [], True],
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+            def __new__(
+                cls,
+                name,
+                bases,
+                namespace,
+                *,
+                init: bool = False,
+            ):
+                ...
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase, init=False):'''), [], False],
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase, init=False):'''), [], False],
+    # 4/ Other parameters
+    # Class based
+    [dedent('''
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+        class X(Y, eq=True):'''), [], True],
+    # Decorator based
+    [dedent('''
+        @dataclass_transform
+        def create_model():
+            pass
+        @create_model(eq=True)
+        class X:'''), [], True],
+    # Metaclass based
+    [dedent('''
+        @dataclass_transform
+        class ModelMeta():
+            y: int
+            z = 5
+        class ModelBase(metaclass=ModelMeta):
+            t: int
+            p = 5
+        class X(ModelBase, eq=True):'''), [], True],
+]
+
+ids = [
+    "direct_transformer",
+    "transformer_with_params",
+    "subclass_transformer",
+    "base_transformed",
+    "base_transformed_with_params",
+    "decorator_transformed_direct",
+    "decorator_transformed_subclass",
+    "decorator_transformed_both",
+    "decorator_transformed_intermediate_not",
+    "metaclass_transformed",
+    "custom_init",
+    # "base_transformed_init_false_dataclass_init_default",
+    "base_transformed_init_false_dataclass_init_true",
+    "base_transformed_init_false_dataclass_init_false",
+    "base_transformed_init_default_dataclass_init_false",
+    "decorator_transformed_init_false_dataclass_init_default",
+    "decorator_transformed_init_false_dataclass_init_true",
+    "decorator_transformed_init_false_dataclass_init_false",
+    "decorator_transformed_init_default_dataclass_init_false",
+    "metaclass_transformed_init_false_dataclass_init_default",
+    "metaclass_transformed_init_false_dataclass_init_true",
+    "metaclass_transformed_init_false_dataclass_init_false",
+    "metaclass_transformed_init_default_dataclass_init_false",
+    "base_transformed_other_parameters",
+    "decorator_transformed_other_parameters",
+    "metaclass_transformed_other_parameters",
+]
+
+
+@pytest.mark.parametrize(
+    'start, start_params, include_params', dataclass_transform_cases, ids=ids
+)
+def test_extensions_dataclass_transform_signature(
+    Script, skip_pre_python37, start, start_params, include_params, environment
+):
+    has_typing_ext = bool(Script('import typing_extensions').infer())
+    if not has_typing_ext:
+        raise pytest.skip("typing_extensions needed in target environment to run this test")
+
+    if environment.version_info < (3, 8):
+        # Final is not yet supported
+        price_type = "float"
+        price_type_infer = "float"
+    else:
+        price_type = "Final[float]"
+        price_type_infer = "object"
+
+    code = dedent(
+        f"""
+            name: str
+            foo = 3
+            blob: ClassVar[str]
+            price: {price_type}
+            quantity: int = 0.0
+
+        X("""
+    )
+
+    code = (
+        "from typing_extensions import dataclass_transform\n"
+        + "from typing import ClassVar, Final\n"
+        + start
+        + code
+    )
+
+    (sig,) = Script(code).get_signatures()
+    expected_params = (
+        [*start_params, "name", "price", "quantity"]
+        if include_params
+        else [*start_params]
+    )
+    assert [p.name for p in sig.params] == expected_params
+
+    if include_params:
+        quantity, = sig.params[-1].infer()
+        assert quantity.name == 'int'
+        price, = sig.params[-2].infer()
+        assert price.name == price_type_infer
+
+
+def test_dataclass_transform_complete(Script):
+    script = Script('''\
+        @dataclass_transform
+        class Y():
+            y: int
+            z = 5
+
+        class X(Y):
+            name: str
+            foo = 3
+
+        def f(x: X):
+            x.na''')
+    completion, = script.complete()
+    assert completion.description == 'name: str'
+
+
+@pytest.mark.parametrize(
+    "start, start_params, include_params", dataclass_transform_cases, ids=ids
+)
+def test_dataclass_transform_signature(
+    Script, skip_pre_python311, start, start_params, include_params
+):
     code = dedent('''
             name: str
             foo = 3
-            price: float
+            blob: ClassVar[str]
+            price: Final[float]
             quantity: int = 0.0
 
         X(''')
 
-    code = 'from dataclasses import dataclass\n' + start + code
+    code = (
+        "from typing import dataclass_transform\n"
+        + "from typing import ClassVar, Final\n"
+        + start
+        + code
+    )
 
     sig, = Script(code).get_signatures()
-    assert [p.name for p in sig.params] == start_params + ['name', 'price', 'quantity']
-    quantity, = sig.params[-1].infer()
-    assert quantity.name == 'int'
-    price, = sig.params[-2].infer()
-    assert price.name == 'float'
+    expected_params = (
+        [*start_params, "name", "price", "quantity"]
+        if include_params
+        else [*start_params]
+    )
+    assert [p.name for p in sig.params] == expected_params
+
+    if include_params:
+        quantity, = sig.params[-1].infer()
+        assert quantity.name == 'int'
+        price, = sig.params[-2].infer()
+        assert price.name == 'object'
 
 
 @pytest.mark.parametrize(
@@ -371,7 +842,8 @@ def test_dataclass_signature(Script, skip_pre_python37, start, start_params):
              z = 5
          @define
          class X(Y):'''), ['y']],
-    ]
+    ],
+    ids=["define", "frozen", "define_customized", "define_subclass", "define_both"]
 )
 def test_attrs_signature(Script, skip_pre_python37, start, start_params):
     has_attrs = bool(Script('import attrs').infer())