
## Summary * Attributes/method are now properly looked up on metaclasses, when called on class objects * We properly distinguish between data descriptors and non-data descriptors (but we do not yet support them in store-context, i.e. `obj.data_descr = …`) * The descriptor protocol is now implemented in a single unified place for instances, classes and dunder-calls. Unions and possibly-unbound symbols are supported in all possible stages of the process by creating union types as results. * In general, the handling of "possibly-unbound" symbols has been improved in a lot of places: meta-class attributes, attributes, descriptors with possibly-unbound `__get__` methods, instance attributes, … * We keep track of type qualifiers in a lot more places. I anticipate that this will be useful if we import e.g. `Final` symbols from other modules (see relevant change to typing spec: https://github.com/python/typing/pull/1937). * Detection and special-casing of the `typing.Protocol` special form in order to avoid lots of changes in the test suite due to new `@Todo` types when looking up attributes on builtin types which have `Protocol` in their MRO. We previously looked up attributes in a wrong way, which is why this didn't come up before. closes #16367 closes #15966 ## Context The way attribute lookup in `Type::member` worked before was simply wrong (mostly my own fault). The whole instance-attribute lookup should probably never have been integrated into `Type::member`. And the `Type::static_member` function that I introduced in my last descriptor PR was the wrong abstraction. It's kind of fascinating how far this approach took us, but I am pretty confident that the new approach proposed here is what we need to model this correctly. There are three key pieces that are required to implement attribute lookups: - **`Type::class_member`**/**`Type::find_in_mro`**: The `Type::find_in_mro` method that can look up attributes on class bodies (and corresponding bases). This is a partial function on types, as it can not be called on instance types like`Type::Instance(…)` or `Type::IntLiteral(…)`. For this reason, we usually call it through `Type::class_member`, which is essentially just `type.to_meta_type().find_in_mro(…)` plus union/intersection handling. - **`Type::instance_member`**: This new function is basically the type-level equivalent to `obj.__dict__[name]` when called on `Type::Instance(…)`. We use this to discover instance attributes such as those that we see as declarations on class bodies or as (annotated) assignments to `self.attr` in methods of a class. - The implementation of the descriptor protocol. It works slightly different for instances and for class objects, but it can be described by the general framework: - Call `type.class_member("attribute")` to look up "attribute" in the MRO of the meta type of `type`. Call the resulting `Symbol` `meta_attr` (even if it's unbound). - Use `meta_attr.class_member("__get__")` to look up `__get__` on the *meta type* of `meta_attr`. Call it with `__get__(meta_attr, self, self.to_meta_type())`. If this fails (either the lookup or the call), just proceed with `meta_attr`. Otherwise, replace `meta_attr` in the following with the return type of `__get__`. In this step, we also probe if a `__set__` or `__delete__` method exists and store it in `meta_attr_kind` (can be either "data descriptor" or "normal attribute or non-data descriptor"). - Compute a `fallback` type. - For instances, we use `self.instance_member("attribute")` - For class objects, we use `class_attr = self.find_in_mro("attribute")`, and then try to invoke the descriptor protocol on `class_attr`, i.e. we look up `__get__` on the meta type of `class_attr` and call it with `__get__(class_attr, None, self)`. This additional invocation of the descriptor protocol on the fallback type is one major asymmetry in the otherwise universal descriptor protocol implementation. - Finally, we look at `meta_attr`, `meta_attr_kind` and `fallback`, and handle various cases of (possible) unboundness of these symbols. - If `meta_attr` is bound and a data descriptor, just return `meta_attr` - If `meta_attr` is not a data descriptor, and `fallback` is bound, just return `fallback` - If `meta_attr` is not a data descriptor, and `fallback` is unbound, return `meta_attr` - Return unions of these three possibilities for partially-bound symbols. This allows us to handle class objects and instances within the same framework. There is a minor additional detail where for instances, we do not allow the fallback type (the instance attribute) to completely shadow the non-data descriptor. We do this because we (currently) don't want to pretend that we can statically infer that an instance attribute is always set. Dunder method calls can also be embedded into this framework. The only thing that changes is that *there is no fallback type*. If a dunder method is called on an instance, we do not fall back to instance variables. If a dunder method is called on a class object, we only look it up on the meta class, never on the class itself. ## Test Plan New Markdown tests.
3.9 KiB
Generic classes
PEP 695 syntax
TODO: Add a red_knot_extension
function that asserts whether a function or class is generic.
This is a generic class defined using PEP 695 syntax:
class C[T]: ...
A class that inherits from a generic class, and fills its type parameters with typevars, is generic:
# TODO: no error
# error: [non-subscriptable]
class D[U](C[U]): ...
A class that inherits from a generic class, but fills its type parameters with concrete types, is not generic:
# TODO: no error
# error: [non-subscriptable]
class E(C[int]): ...
A class that inherits from a generic class, and doesn't fill its type parameters at all, implicitly
uses the default value for the typevar. In this case, that default type is Unknown
, so F
inherits from C[Unknown]
and is not itself generic.
class F(C): ...
Legacy syntax
This is a generic class defined using the legacy syntax:
from typing import Generic, TypeVar
T = TypeVar("T")
# TODO: no error
# error: [invalid-base]
class C(Generic[T]): ...
A class that inherits from a generic class, and fills its type parameters with typevars, is generic.
class D(C[T]): ...
(Examples E
and F
from above do not have analogues in the legacy syntax.)
Inferring generic class parameters
The type parameter can be specified explicitly:
class C[T]:
x: T
# TODO: no error
# TODO: revealed: C[int]
# error: [non-subscriptable]
reveal_type(C[int]()) # revealed: C
We can infer the type parameter from a type context:
c: C[int] = C()
# TODO: revealed: C[int]
reveal_type(c) # revealed: C
The typevars of a fully specialized generic class should no longer be visible:
# TODO: revealed: int
reveal_type(c.x) # revealed: T
If the type parameter is not specified explicitly, and there are no constraints that let us infer a specific type, we infer the typevar's default type:
class D[T = int]: ...
# TODO: revealed: D[int]
reveal_type(D()) # revealed: D
If a typevar does not provide a default, we use Unknown
:
# TODO: revealed: C[Unknown]
reveal_type(C()) # revealed: C
If the type of a constructor parameter is a class typevar, we can use that to infer the type parameter:
class E[T]:
def __init__(self, x: T) -> None: ...
# TODO: revealed: E[int] or E[Literal[1]]
reveal_type(E(1)) # revealed: E
The types inferred from a type context and from a constructor parameter must be consistent with each other:
# TODO: error
wrong_innards: E[int] = E("five")
Generic subclass
When a generic subclass fills its superclass's type parameter with one of its own, the actual types propagate through:
class Base[T]:
x: T | None = None
# TODO: no error
# error: [non-subscriptable]
class Sub[U](Base[U]): ...
# TODO: no error
# TODO: revealed: int | None
# error: [non-subscriptable]
reveal_type(Base[int].x) # revealed: T | None
# TODO: revealed: int | None
# error: [non-subscriptable]
reveal_type(Sub[int].x) # revealed: T | None
Cyclic class definition
A class can use itself as the type parameter of one of its superclasses. (This is also known as the curiously recurring template pattern or F-bounded quantification.)
Here, Sub
is not a generic class, since it fills its superclass's type parameter (with itself).
stub.pyi
:
class Base[T]: ...
# TODO: no error
# error: [non-subscriptable]
class Sub(Base[Sub]): ...
reveal_type(Sub) # revealed: Literal[Sub]
string_annotation.py
:
class Base[T]: ...
# TODO: no error
# error: [non-subscriptable]
class Sub(Base["Sub"]): ...
reveal_type(Sub) # revealed: Literal[Sub]
bare_annotation.py
:
class Base[T]: ...
# TODO: error: [unresolved-reference]
class Sub(Base[Sub]): ...