# Calls to `type()`

## Single-argument form

A single-argument call to `type()` returns an object that has the argument's meta-type. (This is
tested more extensively in `crates/ty_python_semantic/resources/mdtest/attributes.md`, alongside the
tests for the `__class__` attribute.)

```py
reveal_type(type(1))  # revealed: <class 'int'>
```

## Three-argument form (dynamic class creation)

A three-argument call to `type()` creates a new class. We synthesize a class type using the name
from the first argument:

```py
class Base: ...
class Mixin: ...

# We synthesize a class type using the name argument
reveal_type(type("Foo", (), {}))  # revealed: <class 'Foo'>

# With a single base class
reveal_type(type("Foo", (Base,), {"attr": 1}))  # revealed: <class 'Foo'>

# With multiple base classes
reveal_type(type("Foo", (Base, Mixin), {}))  # revealed: <class 'Foo'>

# The inferred type is assignable to type[Base] since Foo inherits from Base
tests: list[type[Base]] = []
testCaseClass = type("Foo", (Base,), {})
tests.append(testCaseClass)  # No error - type[Foo] is assignable to type[Base]
```

The name can also be provided indirectly via a variable with a string literal type:

```py
name = "IndirectClass"
IndirectClass = type(name, (), {})
reveal_type(IndirectClass)  # revealed: <class 'IndirectClass'>

# Works with base classes too
class Base: ...

base_name = "DerivedClass"
DerivedClass = type(base_name, (Base,), {})
reveal_type(DerivedClass)  # revealed: <class 'DerivedClass'>
```

## Distinct class types

Each `type()` call produces a distinct class type, even if they have the same name and bases:

```py
from ty_extensions import static_assert, is_equivalent_to

class Base: ...

Foo1 = type("Foo", (Base,), {})
Foo2 = type("Foo", (Base,), {})

# Even though they have the same name and bases, they are distinct types
static_assert(not is_equivalent_to(Foo1, Foo2))

# Each instance is typed with its respective class
foo1 = Foo1()
foo2 = Foo2()

def takes_foo1(x: Foo1) -> None: ...
def takes_foo2(x: Foo2) -> None: ...

takes_foo1(foo1)  # OK
takes_foo2(foo2)  # OK

# error: [invalid-argument-type] "Argument to function `takes_foo1` is incorrect: Expected `mdtest_snippet.Foo @ src/mdtest_snippet.py:5:8`, found `mdtest_snippet.Foo @ src/mdtest_snippet.py:6:8`"
takes_foo1(foo2)
# error: [invalid-argument-type] "Argument to function `takes_foo2` is incorrect: Expected `mdtest_snippet.Foo @ src/mdtest_snippet.py:6:8`, found `mdtest_snippet.Foo @ src/mdtest_snippet.py:5:8`"
takes_foo2(foo1)
```

## Instances and attribute access

Instances of dynamic classes are typed with the synthesized class name. Attributes from all base
classes are accessible:

```py
class Base:
    base_attr: int = 1

    def base_method(self) -> str:
        return "hello"

class Mixin:
    mixin_attr: str = "mixin"

Foo = type("Foo", (Base,), {})
foo = Foo()

# Instance is typed with the synthesized class name
reveal_type(foo)  # revealed: Foo

# Inherited attributes are accessible
reveal_type(foo.base_attr)  # revealed: int
reveal_type(foo.base_method())  # revealed: str

# Multiple inheritance: attributes from all bases are accessible
Bar = type("Bar", (Base, Mixin), {})
bar = Bar()
reveal_type(bar.base_attr)  # revealed: int
reveal_type(bar.mixin_attr)  # revealed: str
```

Attributes from the namespace dict (third argument) are tracked:

```py
class Base: ...

Foo = type("Foo", (Base,), {"custom_attr": 42})

# Class attribute access
reveal_type(Foo.custom_attr)  # revealed: Literal[42]

# Instance attribute access
foo = Foo()
reveal_type(foo.custom_attr)  # revealed: Literal[42]
```

When the namespace dict is not a literal (e.g., passed as a parameter), attribute access returns
`Unknown` since we can't know what attributes might be defined:

```py
from typing import Any

class DynamicBase: ...

def f(attributes: dict[str, Any]):
    X = type("X", (DynamicBase,), attributes)

    reveal_type(X)  # revealed: <class 'X'>

    # Attribute access returns Unknown since the namespace is dynamic
    reveal_type(X.foo)  # revealed: Unknown

    x = X()
    reveal_type(x.bar)  # revealed: Unknown
```

When a namespace dictionary is partially dynamic (e.g., a dict literal with spread or non-literal
keys), static attributes have precise types while unknown attributes return `Unknown`:

```py
from typing import Any

def f(extra_attrs: dict[str, Any], y: str):
    X = type("X", (), {"a": 42, **extra_attrs})

    # Static attributes in the namespace dictionary have precise types,
    # but the dictionary was not entirely static, so other attributes
    # are still available and resolve to `Unknown`:
    reveal_type(X().a)  # revealed: Literal[42]
    reveal_type(X().whatever)  # revealed: Unknown

    Y = type("Y", (), {"a": 56, y: 72})
    reveal_type(Y().a)  # revealed: Literal[56]
    reveal_type(Y().whatever)  # revealed: Unknown
```

When a `TypedDict` is passed as the namespace argument, we synthesize a class type with the known
keys from the `TypedDict` as attributes. Since `TypedDict` instances are "open" (they can have
arbitrary additional string keys), unknown attributes return `Unknown`:

```py
from typing import TypedDict

class Namespace(TypedDict):
    z: int

def g(attributes: Namespace):
    Y = type("Y", (), attributes)

    reveal_type(Y)  # revealed: <class 'Y'>

    # Known keys from the TypedDict are tracked as attributes
    reveal_type(Y.z)  # revealed: int

    y = Y()
    reveal_type(y.z)  # revealed: int

    # Unknown attributes return Unknown since TypedDicts are open
    reveal_type(Y.unknown)  # revealed: Unknown
    reveal_type(y.unknown)  # revealed: Unknown
```

## Closed TypedDicts (PEP-728)

TODO: We don't support the PEP-728 `closed=True` keyword argument to `TypedDict` yet. When we do, a
closed TypedDict namespace should NOT be marked as dynamic, and accessing unknown attributes should
emit an error instead of returning `Unknown`.

```py
from typing import TypedDict

class ClosedNamespace(TypedDict, closed=True):
    x: int
    y: str

def h(ns: ClosedNamespace):
    X = type("X", (), ns)

    reveal_type(X)  # revealed: <class 'X'>

    # Known keys from the TypedDict are tracked as attributes
    reveal_type(X.x)  # revealed: int
    reveal_type(X.y)  # revealed: str

    x = X()
    reveal_type(x.x)  # revealed: int
    reveal_type(x.y)  # revealed: str

    # TODO: Once we support `closed=True`, these should emit errors instead of returning Unknown
    reveal_type(X.unknown)  # revealed: Unknown
    reveal_type(x.unknown)  # revealed: Unknown
```

## Inheritance from dynamic classes

Regular classes can inherit from dynamic classes:

```py
class Base:
    base_attr: int = 1

DynamicClass = type("DynamicClass", (Base,), {})

class Child(DynamicClass):
    child_attr: str = "child"

child = Child()

# Attributes from the dynamic class's base are accessible
reveal_type(child.base_attr)  # revealed: int

# The child class's own attributes are accessible
reveal_type(child.child_attr)  # revealed: str

# Child instances are subtypes of DynamicClass instances
def takes_dynamic(x: DynamicClass) -> None: ...

takes_dynamic(child)  # No error - Child is a subtype of DynamicClass

# isinstance narrows to the dynamic class instance type
def check_isinstance(x: object) -> None:
    if isinstance(x, DynamicClass):
        reveal_type(x)  # revealed: DynamicClass

# Dynamic class inheriting from int narrows correctly with isinstance
IntSubclass = type("IntSubclass", (int,), {})

def check_int_subclass(x: IntSubclass | str) -> None:
    if isinstance(x, int):
        # IntSubclass inherits from int, so it's included in the narrowed type
        reveal_type(x)  # revealed: IntSubclass
    else:
        reveal_type(x)  # revealed: str
```

## Disjointness

Dynamic classes are not considered disjoint from unrelated types (since a subclass could inherit
from both):

```py
class Base: ...

Foo = type("Foo", (Base,), {})

def check_disjointness(x: Foo | int) -> None:
    if isinstance(x, int):
        reveal_type(x)  # revealed: int
    else:
        # Foo and int are not considered disjoint because `class C(Foo, int)` could exist.
        reveal_type(x)  # revealed: Foo & ~int
```

Disjointness also works for `type[]` of dynamic classes:

```py
from ty_extensions import is_disjoint_from, static_assert

# Dynamic classes with disjoint bases have disjoint type[] types.
IntClass = type("IntClass", (int,), {})
StrClass = type("StrClass", (str,), {})

static_assert(is_disjoint_from(type[IntClass], type[StrClass]))
static_assert(is_disjoint_from(type[StrClass], type[IntClass]))

# Dynamic classes that share a common base are not disjoint.
class Base: ...

Foo = type("Foo", (Base,), {})
Bar = type("Bar", (Base,), {})

static_assert(not is_disjoint_from(type[Foo], type[Bar]))
```

## Using dynamic classes with `super()`

Dynamic classes can be used as the pivot class in `super()` calls:

```py
class Base:
    def method(self) -> int:
        return 42

DynamicChild = type("DynamicChild", (Base,), {})

# Using dynamic class as pivot with dynamic class instance owner
fc = DynamicChild()
reveal_type(super(DynamicChild, fc))  # revealed: <super: <class 'DynamicChild'>, DynamicChild>
reveal_type(super(DynamicChild, fc).method())  # revealed: int

# Regular class inheriting from dynamic class
class RegularChild(DynamicChild):
    pass

rc = RegularChild()
reveal_type(super(RegularChild, rc))  # revealed: <super: <class 'RegularChild'>, RegularChild>
reveal_type(super(RegularChild, rc).method())  # revealed: int

# Using dynamic class as pivot with regular class instance owner
reveal_type(super(DynamicChild, rc))  # revealed: <super: <class 'DynamicChild'>, RegularChild>
reveal_type(super(DynamicChild, rc).method())  # revealed: int
```

## Dynamic class inheritance chains

Dynamic classes can inherit from other dynamic classes:

```py
class Base:
    base_attr: int = 1

# Create a dynamic class that inherits from a regular class.
Parent = type("Parent", (Base,), {})
reveal_type(Parent)  # revealed: <class 'Parent'>

# Create a dynamic class that inherits from another dynamic class.
ChildCls = type("ChildCls", (Parent,), {})
reveal_type(ChildCls)  # revealed: <class 'ChildCls'>

# Child instances have access to attributes from the entire inheritance chain.
child = ChildCls()
reveal_type(child)  # revealed: ChildCls
reveal_type(child.base_attr)  # revealed: int

# Child instances are subtypes of `Parent` instances.
def takes_parent(x: Parent) -> None: ...

takes_parent(child)  # No error - `ChildCls` is a subtype of `Parent`
```

## Dataclass transform inheritance

Dynamic classes that inherit from a `@dataclass_transform()` decorated base class are recognized as
dataclass-like and have the synthesized `__dataclass_fields__` attribute:

```py
from dataclasses import Field
from typing_extensions import dataclass_transform

@dataclass_transform()
class DataclassBase:
    """Base class decorated with @dataclass_transform()."""

    pass

# A dynamic class inheriting from a dataclass_transform base
DynamicModel = type("DynamicModel", (DataclassBase,), {})

# The dynamic class has __dataclass_fields__ synthesized
reveal_type(DynamicModel.__dataclass_fields__)  # revealed: dict[str, Field[Any]]
```

## Applying `@dataclass` decorator directly

Applying the `@dataclass` decorator directly to a dynamic class is supported:

```py
from dataclasses import dataclass

Foo = type("Foo", (), {})
Foo = dataclass(Foo)

reveal_type(Foo.__dataclass_fields__)  # revealed: dict[str, Field[Any]]
```

## Generic base classes

Dynamic classes with generic base classes:

```py
from typing import Generic, TypeVar

T = TypeVar("T")

class Container(Generic[T]):
    value: T

# Dynamic class inheriting from a generic class specialization
IntContainer = type("IntContainer", (Container[int],), {})
reveal_type(IntContainer)  # revealed: <class 'IntContainer'>

container = IntContainer()
reveal_type(container)  # revealed: IntContainer
reveal_type(container.value)  # revealed: int
```

## `type()` and `__class__` on dynamic instances

`type(instance)` returns the class of the dynamic instance:

```py
class Base: ...

Foo = type("Foo", (Base,), {})
foo = Foo()

# type() on an instance returns the class
reveal_type(type(foo))  # revealed: type[Foo]
```

`__class__` attribute access on dynamic instances:

```py
class Base: ...

Foo = type("Foo", (Base,), {})
foo = Foo()

# __class__ returns the class type
reveal_type(foo.__class__)  # revealed: type[Foo]
```

`__class__` on the dynamic class itself returns the metaclass (consistent with static classes):

```py
class StaticClass: ...

DynamicClass = type("DynamicClass", (), {})

# Both static and dynamic classes have `type` as their metaclass
reveal_type(StaticClass.__class__)  # revealed: <class 'type'>
reveal_type(DynamicClass.__class__)  # revealed: <class 'type'>
```

## Subtype relationships

Dynamic instances are subtypes of `object`:

```py
class Base: ...

Foo = type("Foo", (Base,), {})
foo = Foo()

# All dynamic instances are subtypes of object
def takes_object(x: object) -> None: ...

takes_object(foo)  # No error - Foo is a subtype of object

# Even dynamic classes with no explicit bases are subtypes of object
EmptyBases = type("EmptyBases", (), {})
empty = EmptyBases()
takes_object(empty)  # No error
```

## Attributes from `builtins.type`

Attributes defined on `builtins.type` are accessible on dynamic classes:

```py
T = type("T", (), {})

# Inherited from `builtins.type`:
reveal_type(T.__dictoffset__)  # revealed: int
reveal_type(T.__name__)  # revealed: str
reveal_type(T.__bases__)  # revealed: tuple[type, ...]
reveal_type(T.__mro__)  # revealed: tuple[type, ...]
```

## Invalid calls

Other numbers of arguments are invalid:

```py
# error: [no-matching-overload] "No overload of class `type` matches arguments"
reveal_type(type("Foo", ()))  # revealed: type[Unknown]

# TODO: the keyword arguments for `Foo`/`Bar`/`Baz` here are invalid
# (none of them have base classes with `__init_subclass__` methods).
#
# The intent to create a new class is however clear,
# so we still infer these as class-literal types.
reveal_type(type("Foo", (), {}, weird_other_arg=42))  # revealed: <class 'Foo'>
reveal_type(type("Bar", (int,), {}, weird_other_arg=42))  # revealed: <class 'Bar'>

# You can't pass `metaclass=` to the `type()` constructor, but the intent is clear,
# so we infer `<class 'Baz'>` here rather than `type[Unknown]`
# error: [no-matching-overload] "No overload of class `type` matches arguments"
reveal_type(type("Baz", (), {}, metaclass=type))  # revealed: <class 'Baz'>
```

The following calls are also invalid, due to incorrect argument types:

```py
class Base: ...

# error: [invalid-argument-type] "Invalid argument to parameter 1 (`name`) of `type()`: Expected `str`, found `Literal[b"Foo"]`"
type(b"Foo", (), {})

# error: [invalid-argument-type] "Invalid argument to parameter 2 (`bases`) of `type()`: Expected `tuple[type, ...]`, found `<class 'Base'>`"
type("Foo", Base, {})

# error: 14 [invalid-base] "Invalid class base with type `Literal[1]`"
# error: 17 [invalid-base] "Invalid class base with type `Literal[2]`"
type("Foo", (1, 2), {})

# error: [invalid-argument-type] "Invalid argument to parameter 3 (`namespace`) of `type()`: Expected `dict[str, Any]`, found `dict[Unknown | bytes, Unknown | int]`"
type("Foo", (Base,), {b"attr": 1})
```

## `type[...]` as base class

`type[...]` (SubclassOf) types cannot be used as base classes. When a `type[...]` is used in the
bases tuple, we emit a diagnostic and insert `Unknown` into the MRO. This gives exactly one
diagnostic about the unsupported base, rather than cascading errors:

```py
from ty_extensions import reveal_mro

class Base:
    base_attr: int = 1

def f(x: type[Base]):
    # error: [unsupported-dynamic-base] "Unsupported class base"
    Child = type("Child", (x,), {})

    # The class is still created with `Unknown` in MRO, allowing attribute access
    reveal_type(Child)  # revealed: <class 'Child'>
    reveal_mro(Child)  # revealed: (<class 'Child'>, Unknown, <class 'object'>)
    child = Child()
    reveal_type(child)  # revealed: Child

    # Attributes from `Unknown` are accessible without further errors
    reveal_type(child.base_attr)  # revealed: Unknown
```

## MRO errors

MRO errors are detected and reported:

```py
class A: ...

# Duplicate bases are detected
# error: [duplicate-base] "Duplicate base class <class 'A'> in class `Dup`"
Dup = type("Dup", (A, A), {})
```

Unknown bases (from unresolved imports) don't trigger duplicate-base diagnostics, since we can't
know if they represent the same type:

```py
from unresolved_module import Bar, Baz  # error: [unresolved-import]

# No duplicate-base error here - Bar and Baz are Unknown, and we can't
# know if they're the same type.
X = type("X", (Bar, Baz), {})
```

```py
class A: ...
class B(A): ...
class C(A): ...

# This creates an inconsistent MRO because D would need B before C (from first base)
# but also C before B (from second base inheritance through A)
class X(B, C): ...
class Y(C, B): ...

# error: [inconsistent-mro] "Cannot create a consistent method resolution order (MRO) for class `Conflict` with bases `[<class 'X'>, <class 'Y'>]`"
Conflict = type("Conflict", (X, Y), {})
```

## Cyclic base class MRO

A dynamic class inheriting from a static class with a cyclic MRO also produces an error:

```pyi
class Cyclic(Cyclic): ...  # error: [cyclic-class-definition]

# error: [cyclic-class-definition]
CyclicChild = type("CyclicChild", (Cyclic,), {})
```

## `inconsistent-mro` errors with autofixes

A common cause of "inconsistent MRO" errors is where a class inherits from `Generic[]`, but
`Generic[]` is not the last base class. We provide an autofix for this common error:

<!-- snapshot-diagnostics -->

```py
from typing import Generic, TypeVar

K = TypeVar("K")
V = TypeVar("V")

class Foo1(Generic[K, V], dict): ...  # error: [inconsistent-mro]

# fmt: off

class Foo2(  # error: [inconsistent-mro]
    # comment1
    Generic[K, V],  # comment2
    # comment3
    dict  # comment4
    # comment5
): ...

class Foo3(Generic[K, V], dict, metaclass=type): ...  # error: [inconsistent-mro]

class Foo4(  # error: [inconsistent-mro]
    # comment1
    Generic[K, V],  # comment2
    # comment3
    dict,  # comment4
    # comment5
    metaclass=type  # comment6
    # comment7
): ...

# fmt: on
```

## MRO error highlighting (snapshot)

<!-- snapshot-diagnostics -->

This snapshot test documents the diagnostic highlighting range for dynamic class literals.
Currently, the entire `type()` call expression is highlighted:

```py
class A: ...

Dup = type("Dup", (A, A), {})  # error: [duplicate-base]
```

## Metaclass conflicts

Metaclass conflicts are detected and reported:

```py
class Meta1(type): ...
class Meta2(type): ...
class A(metaclass=Meta1): ...
class B(metaclass=Meta2): ...

# error: [conflicting-metaclass] "The metaclass of a derived class (`Bad`) must be a subclass of the metaclasses of all its bases, but `Meta1` (metaclass of base class `<class 'A'>`) and `Meta2` (metaclass of base class `<class 'B'>`) have no subclass relationship"
Bad = type("Bad", (A, B), {})
```

## `__slots__` in namespace dictionary

Dynamic classes can define `__slots__` in the namespace dictionary. Non-empty `__slots__` makes the
class a "disjoint base", which prevents it from being used alongside other disjoint bases in a class
hierarchy:

```py
# Dynamic class with non-empty __slots__
Slotted = type("Slotted", (), {"__slots__": ("x", "y")})
slotted = Slotted()
reveal_type(slotted)  # revealed: Slotted

# Classes with empty __slots__ are not disjoint bases
EmptySlots = type("EmptySlots", (), {"__slots__": ()})

# Classes with no __slots__ are not disjoint bases
NoSlots = type("NoSlots", (), {})

# String __slots__ are treated as a single slot (non-empty)
StringSlots = type("StringSlots", (), {"__slots__": "x"})
```

Dynamic classes with non-empty `__slots__` cannot coexist with other disjoint bases:

```py
class RegularSlotted:
    __slots__ = ("a",)

DynSlotted = type("DynSlotted", (), {"__slots__": ("b",)})

# error: [instance-layout-conflict]
class Conflict(
    RegularSlotted,
    DynSlotted,
): ...
```

Two dynamic classes with non-empty `__slots__` also conflict:

```py
A = type("A", (), {"__slots__": ("x",)})
B = type("B", (), {"__slots__": ("y",)})

# error: [instance-layout-conflict]
class Conflict(
    A,
    B,
): ...
```

`instance-layout-conflict` errors are also emitted for classes that inherit from dynamic classes
with disjoint bases:

```py
from typing import Any

class DisjointBase1:
    __slots__ = ("a",)

class DisjointBase2:
    __slots__ = ("b",)

def f(ns: dict[str, Any]):
    cls1 = type("cls1", (DisjointBase1,), ns)
    cls2 = type("cls2", (DisjointBase2,), ns)

    # error: [instance-layout-conflict]
    cls3 = type("cls3", (cls1, cls2), {})

    # error: [instance-layout-conflict]
    class Cls4(cls1, cls2): ...
```

When the namespace dictionary is dynamic (not a literal), we can't determine if `__slots__` is
defined, so no diagnostic is emitted:

```py
from typing import Any

class SlottedBase:
    __slots__ = ("a",)

def f(ns: dict[str, Any]):
    # The namespace might or might not contain __slots__, so no error is emitted
    Dynamic = type("Dynamic", (), ns)

    # No error: we can't prove there's a conflict since ns might not have __slots__
    class MaybeConflict(SlottedBase, Dynamic): ...
```

## `instance-layout-conflict` diagnostic snapshots

<!-- snapshot-diagnostics -->

When the bases are a tuple literal, the diagnostic includes annotations for each conflicting base:

```py
class A:
    __slots__ = ("x",)

class B:
    __slots__ = ("y",)

# error: [instance-layout-conflict]
X = type("X", (A, B), {})
```

When the bases are not a tuple literal (e.g., a variable), the diagnostic is emitted without
per-base annotations:

```py
class C:
    __slots__ = ("x",)

class D:
    __slots__ = ("y",)

bases: tuple[type[C], type[D]] = (C, D)
# error: [instance-layout-conflict]
Y = type("Y", bases, {})
```

## Cyclic functional class definitions

### Self-referential

Self-referential class definitions using `type()` are detected. The name being defined is referenced
in the bases tuple before it's available:

```pyi
# error: [unresolved-reference] "Name `X` used when not defined"
X = type("X", (X,), {})
```

### No string literal bases

String literals directly in the bases tuple are not valid class bases:

```py
# error: [invalid-base] "Invalid class base with type `Literal["X"]`"
X = type("X", ("X",), {})
```

### Forward references via string annotations

However, forward references via string annotations are supported, similar to regular class
definitions. This works with `NamedTuple` where field annotations can be forward references:

```py
from typing import NamedTuple

# Forward reference in NamedTuple field annotation
X = type("X", (NamedTuple("NT", [("field", "X | int")]),), {})
reveal_type(X)  # revealed: <class 'X'>
```

### Static class inheriting from dynamic class with forward ref

Forward references also work when a static class inherits from a dynamic class that references it:

```py
from typing import NamedTuple

# Static class inheriting from dynamic class with forward ref back to static class
class Y(type("X", (NamedTuple("NT", [("field", "Y | int")]),), {})): ...

reveal_type(Y)  # revealed: <class 'Y'>
```

Forward references via subscript annotations on generic bases are supported:

```py
# Forward reference to X via subscript annotation in tuple base
# (This fails at runtime, but we should handle it without panicking)
X = type("X", (tuple["X | None"],), {})
reveal_type(X)  # revealed: <class 'X'>
```

## Dynamic class names (non-literal strings)

When the class name is not a string literal, we still create a class literal type but with a
placeholder name `<unknown>`:

```py
def make_class(name: str):
    # When the name is a dynamic string, we use a placeholder name
    cls = type(name, (), {})
    reveal_type(cls)  # revealed: <class '<unknown>'>
    return cls

def make_classes(name1: str, name2: str):
    cls1 = type(name1, (), {})
    cls2 = type(name2, (), {})

    def inner(x: cls1): ...

    # error: [invalid-argument-type] "Argument to function `inner` is incorrect: Expected `mdtest_snippet.<locals of function 'make_classes'>.<unknown> @ src/mdtest_snippet.py:8:12`, found `mdtest_snippet.<locals of function 'make_classes'>.<unknown> @ src/mdtest_snippet.py:9:12`"
    inner(cls2())
```

When the name comes from a union of string literals, we also use a placeholder name:

```py
import random

name = "Foo" if random.random() > 0.5 else "Bar"
reveal_type(name)  # revealed: Literal["Foo", "Bar"]

# We cannot determine which name will be used at runtime
cls = type(name, (), {})
reveal_type(cls)  # revealed: <class '<unknown>'>
```

## Dynamic bases (variable tuple)

When the bases tuple is a function parameter with a non-literal tuple type, we still create a class
literal type but with `Unknown` in the MRO. This means instances are treated highly dynamically -
any attribute access returns `Unknown`:

```py
from ty_extensions import reveal_mro

class Base1: ...
class Base2: ...

def make_class(bases: tuple[type, ...]):
    # Class literal is created with Unknown base in MRO
    cls = type("Cls", bases, {})
    reveal_type(cls)  # revealed: <class 'Cls'>
    reveal_mro(cls)  # revealed: (<class 'Cls'>, Unknown, <class 'object'>)

    # Instances have dynamic attribute access due to Unknown base
    instance = cls()
    reveal_type(instance)  # revealed: Cls
    reveal_type(instance.any_attr)  # revealed: Unknown
    reveal_type(instance.any_method())  # revealed: Unknown

    return cls
```

When `bases` is a module-level variable holding a tuple of class literals, we can extract the base
classes:

```py
class Base:
    attr: int = 1

bases = (Base,)
Cls = type("Cls", bases, {})
reveal_type(Cls)  # revealed: <class 'Cls'>

instance = Cls()
reveal_type(instance.attr)  # revealed: int
```

## Variadic arguments

Unpacking arguments with `*args` or `**kwargs`:

```py
from ty_extensions import reveal_mro

class Base: ...

# Unpacking a tuple for bases
bases_tuple = (Base,)
Cls1 = type("Cls1", (*bases_tuple,), {})
reveal_type(Cls1)  # revealed: <class 'Cls1'>
reveal_mro(Cls1)  # revealed: (<class 'Cls1'>, <class 'Base'>, <class 'object'>)

# Unpacking a dict for the namespace - the dict contents are not tracked anyway
namespace = {"attr": 1}
Cls2 = type("Cls2", (Base,), {**namespace})
reveal_type(Cls2)  # revealed: <class 'Cls2'>
```

When `*args` or `**kwargs` fill an unknown number of parameters, we cannot determine which overload
of `type()` is being called:

```py
def f(*args, **kwargs):
    # Completely dynamic: could be 1-arg or 3-arg form
    A = type(*args, **kwargs)
    reveal_type(A)  # revealed: type[Unknown]

    # Has a string first arg, but unknown additional args from *args
    B = type("B", *args, **kwargs)
    reveal_type(B)  # revealed: type[Unknown]

    # Has string and tuple, but unknown additional args
    C = type("C", (), *args, **kwargs)
    reveal_type(C)  # revealed: type[Unknown]

    # All three positional args provided, only **kwargs unknown
    D = type("D", (), {}, **kwargs)
    reveal_type(D)  # revealed: <class 'D'>

    # Three starred expressions - we can't know how they expand
    a = ("E",)
    b = ((),)
    c = ({},)
    E = type(*a, *b, *c)
    reveal_type(E)  # revealed: type[Unknown]
```

## Explicit type annotations

When an explicit type annotation is provided, the inferred type is checked against it:

```py
# The annotation `type` is compatible with the inferred class literal type
T: type = type("T", (), {})
reveal_type(T)  # revealed: <class 'T'>

# The annotation `type[Base]` is compatible with the inferred type
class Base: ...

Derived: type[Base] = type("Derived", (Base,), {})
reveal_type(Derived)  # revealed: <class 'Derived'>

# Incompatible annotation produces an error
class Unrelated: ...

# error: [invalid-assignment]
Bad: type[Unrelated] = type("Bad", (Base,), {})
```

## Special base classes

Some special base classes work with dynamic class creation, but special semantics may not be fully
synthesized.

### Invalid special bases

Dynamic classes cannot directly inherit from `Generic`, `Protocol`, or `TypedDict`. These special
forms require class syntax for their semantics to be properly applied:

```py
from typing import Generic, NamedTuple, Protocol, TypeVar
from typing_extensions import TypedDict

T = TypeVar("T")

# error: [invalid-base] "Invalid base for class created via `type()`"
GenericClass = type("GenericClass", (Generic[T],), {})

# error: [unsupported-dynamic-base] "Unsupported base for class created via `type()`"
ProtocolClass = type("ProtocolClass", (Protocol,), {})

# error: [invalid-base] "Invalid base for class created via `type()`"
TypedDictClass = type("TypedDictClass", (TypedDict,), {})

# error: [invalid-base] "Invalid class base with type `<special-form 'typing.NamedTuple'>`"
NamedTupleClass = type("NamedTupleClass", (NamedTuple,), {"x": int})
```

`NamedTuple` is also not allowed as a base for dynamic classes, since creating a NamedTuple requires
class syntax for the field declarations to be properly processed:

```py
from typing import NamedTuple

# error: [invalid-base] "Invalid class base with type `<special-form 'typing.NamedTuple'>`"
NT = type("NT", (NamedTuple,), {})
```

### Protocol bases

Inheriting from a class that is itself a protocol is valid:

```py
from typing import Protocol
from ty_extensions import reveal_mro

class MyProtocol(Protocol):
    def method(self) -> int: ...

ProtoImpl = type("ProtoImpl", (MyProtocol,), {"method": lambda self: 42})
reveal_type(ProtoImpl)  # revealed: <class 'ProtoImpl'>
reveal_mro(ProtoImpl)  # revealed: (<class 'ProtoImpl'>, <class 'MyProtocol'>, typing.Protocol, typing.Generic, <class 'object'>)

instance = ProtoImpl()
reveal_type(instance)  # revealed: ProtoImpl
```

### TypedDict bases

Inheriting from a class that is itself a TypedDict is valid:

```py
from typing_extensions import TypedDict
from ty_extensions import reveal_mro

class MyDict(TypedDict):
    name: str
    age: int

DictSubclass = type("DictSubclass", (MyDict,), {})
reveal_type(DictSubclass)  # revealed: <class 'DictSubclass'>
reveal_mro(DictSubclass)  # revealed: (<class 'DictSubclass'>, <class 'MyDict'>, typing.TypedDict, <class 'object'>)
```

### NamedTuple bases

```py
# NamedTuple bases work but the dynamic subclass isn't recognized as a NamedTuple
from typing import NamedTuple
from ty_extensions import reveal_mro

class Point(NamedTuple):
    x: int
    y: int

Point3D = type("Point3D", (Point,), {})
reveal_type(Point3D)  # revealed: <class 'Point3D'>
# fmt: off
reveal_mro(Point3D)  # revealed: (<class 'Point3D'>, <class 'Point'>, <class 'tuple[int, int]'>, <class 'Sequence[int]'>, <class 'Reversible[int]'>, <class 'Collection[int]'>, <class 'Iterable[int]'>, <class 'Container[Any]'>, typing.Protocol, typing.Generic, <class 'object'>)
# fmt: on
```

### Enum bases

Creating a class via `type()` that inherits from any Enum class fails at runtime because `EnumMeta`
expects special attributes in the class dict that `type()` doesn't provide:

```py
from enum import Enum

class Color(Enum):
    RED = 1
    GREEN = 2

# Enums with members are final and cannot be subclassed
# error: [subclass-of-final-class]
ExtendedColor = type("ExtendedColor", (Color,), {})

class EmptyEnum(Enum):
    pass

# Empty enums fail because EnumMeta requires special dict handling
# error: [invalid-base] "Invalid base for class created via `type()`"
InvalidExtension = type("InvalidExtension", (EmptyEnum,), {})
```

## `__init_subclass__` keyword arguments

When a base class defines `__init_subclass__` with required arguments, those should be passed to
`type()`. This is not yet supported:

```py
class Base:
    def __init_subclass__(cls, required_arg: str, **kwargs):
        super().__init_subclass__(**kwargs)
        cls.config = required_arg

# Regular class definition - this works and passes the argument
class Child(Base, required_arg="value"):
    pass

# The dynamically assigned attribute has Unknown in its type
reveal_type(Child.config)  # revealed: Unknown | str

DynamicChild = type("DynamicChild", (Base,), {}, required_arg="value")
```

## Empty bases tuple

When the bases tuple is empty, the class implicitly inherits from `object`:

```py
from ty_extensions import reveal_mro

EmptyBases = type("EmptyBases", (), {})
reveal_type(EmptyBases)  # revealed: <class 'EmptyBases'>
reveal_mro(EmptyBases)  # revealed: (<class 'EmptyBases'>, <class 'object'>)

instance = EmptyBases()
reveal_type(instance)  # revealed: EmptyBases

# object methods are available
reveal_type(instance.__hash__())  # revealed: int
reveal_type(instance.__str__())  # revealed: str
```

## Custom metaclass via bases

When a base class has a custom metaclass, the dynamic class inherits that metaclass:

```py
class MyMeta(type):
    custom_attr: str = "meta"

class Base(metaclass=MyMeta): ...

# Dynamic class inherits the metaclass from Base
Dynamic = type("Dynamic", (Base,), {})
reveal_type(Dynamic)  # revealed: <class 'Dynamic'>

# Metaclass attributes are accessible on the class
reveal_type(Dynamic.custom_attr)  # revealed: str
```

## `final()` on dynamic classes

Using `final()` as a function (not a decorator) on dynamic classes will not be understood by type
checkers. The class is passed through unchanged, and subclassing will not be prevented:

```py
from typing import final

# error: [ineffective-final]
FinalClass = final(type("FinalClass", (), {}))
reveal_type(FinalClass)  # revealed: <class 'FinalClass'>

# Subclassing is allowed because type checkers don't understand `final()` called as a function
class Child(FinalClass): ...

# Same with base classes
class Base: ...

# error: [ineffective-final]
FinalDerived = final(type("FinalDerived", (Base,), {}))

class Child2(FinalDerived): ...
```

## Calling `type` via unannotated parameter

When `type` is captured as an unannotated parameter default (a common Python optimization pattern),
the parameter type is inferred as `Unknown | type[type]`. This union bypasses the early-return guard
for `type()` calls, but should not panic.

```py
def _check_type_strict(obj, t, type=type, tuple=tuple):
    if type(t) is tuple:
        return type(obj) in t
    else:
        return type(obj) is t
```

## Three-argument `type()` in a union

When `type` is one member of a union, three-argument `type()` calls go through normal call binding
instead of the early-return path, so dynamic class creation is missed.

```py
def f(flag: bool):
    if flag:
        x = type
    else:
        x = int

    # TODO: should be `type[MyClass] | int`, but the `type` arm misses dynamic class creation
    # because the early-return guard only matches `ClassLiteral`, not union members.
    MyClass = x("MyClass", (), {})  # error: [no-matching-overload]
    reveal_type(MyClass)  # revealed: type | Unknown
```
