## Summary
This PR adds a new `CallableTypeFromFunction` special form to allow
extracting the abstract signature of a function literal i.e., convert a
`Type::Function` into a `Type::Callable` (`CallableType::General`).
This is done to support testing the `is_gradual_equivalent_to` type
relation specifically the case we want to make sure that a function that
has parameters with no annotations and does not have a return type
annotation is gradual equivalent to `Callable[[Any, Any, ...], Any]`
where the number of parameters should match between the function literal
and callable type.
Refer
https://github.com/astral-sh/ruff/pull/16634#discussion_r1989976692
### Bikeshedding
The name `CallableTypeFromFunction` is a bit too verbose. A possibly
alternative from Carl is `CallableTypeOf` but that would be similar to
`TypeOf` albeit with a limitation that the former only accepts function
literal types and errors on other types.
Some other alternatives:
* `FunctionSignature`
* `SignatureOf` (similar issues as `TypeOf`?)
* ...
## Test Plan
Update `type_api.md` with a new section that tests this special form,
both invalid and valid forms.
## Summary
Add support for calling custom `__getattr__` methods in case an
attribute is not otherwise found. This allows us to get rid of many
ecosystem false positives where we previously emitted errors when
accessing attributes on `argparse.Namespace`.
closes#16614
## Test Plan
* New Markdown tests
* Observed expected ecosystem changes (the changes for `arrow` also look
fine, since the `Arrow` class has a custom [`__getattr__`
here](1d70d00919/arrow/arrow.py (L802-L815)))
Pulls in the latest Salsa main branch, which supports fixpoint
iteration, and uses it to handle all query cycles.
With this, we no longer need to skip any corpus files to avoid panics.
Latest perf results show a 6% incremental and 1% cold-check regression.
This is not a "no cycles" regression, as tomllib and typeshed do trigger
some definition cycles (previously handled by our old
`infer_definition_types` fallback to `Unknown`). We don't currently have
a benchmark we can use to measure the pure no-cycles regression, though
I expect there would still be some regression; the fixpoint iteration
feature in Salsa does add some overhead even for non-cyclic queries.
I think this regression is within the reasonable range for this feature.
We can do further optimization work later, but I don't think it's the
top priority right now. So going ahead and acknowledging the regression
on CodSpeed.
Mypy primer is happy, so this doesn't regress anything on our
currently-checked projects. I expect it probably unlocks adding a number
of new projects to our ecosystem check that previously would have
panicked.
Fixes#13792Fixes#14672
## Summary
Implements attribute access on intersection types, which didn't
previously work. For example:
```py
from typing import Any
class P: ...
class Q: ...
class A:
x: P = P()
class B:
x: Any = Q()
def _(obj: A):
if isinstance(obj, B):
reveal_type(obj.x) # revealed: P & Any
```
Refers to [this comment].
[this comment]:
https://github.com/astral-sh/ruff/pull/16416#discussion_r1985040363
## Test Plan
New Markdown tests
## Summary
Background - as a follow up to #16611 I noticed that there's a lot of
code duplicated between the `is_assignable_to` and `is_subtype_of`
functions and considered trying to merge them.
[A subtype and an assignable type are pretty much the
same](https://typing.python.org/en/latest/spec/concepts.html#the-assignable-to-or-consistent-subtyping-relation),
except that subtypes are by definition fully static, so I think we can
replace the whole of `is_subtype_of` with:
```
if !self.is_fully_static(db) || !target.is_fully_static(db) {
return false;
}
return self.is_assignable_to(target)
```
if we move all of the logic to is_assignable_to and delete duplicate
code. Then we can discuss if it even makes sense to have a separate
is_subtype_of function (I think the answer is yes since it's used by a
bunch of other places, but we may be able to basically rip out the
concept).
Anyways while playing with combining the functions I noticed is that the
handling of Intersections in `is_subtype_of` has a special case for two
intersections, which I didn't include in the last PR - rather I first
handled right hand intersections before left hand, which should properly
handle double intersections (hand-wavy explanation I can justify if
needed - (A & B & C) is assignable to (A & B) because the left is
assignable to both A and B, but none of A, B, or C is assignable to (A &
B)).
I took a look at what breaks if I remove the handling for double
intersections, and the reason it is needed is because is_disjoint does
not properly handle intersections with negative conditions (so instead
`is_subtype_of` basically implements the check correctly).
This PR adds support to is_disjoint for properly checking negative
branches, which also lets us simplify `is_subtype_of`, bringing it in
line with `is_assignable_to`
## Test Plan
Added a bunch of tests, most of which failed before this fix
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This is a pure restructuring of the `attributes.md` and
`descriptor_protocol.md` test suites. They have grown organically and I
didn't want to make major structural changes in my recent PR to keep the
diff clean.
## Summary
A follow up to address [this comment]:
> Similarly here, it might be a little more performant to have a single
`Type::instance()` branch with an inner match over `class.known()`
rather than having multiple branches with `if class.is_known()` guards
[this comment]:
https://github.com/astral-sh/ruff/pull/16416#discussion_r1985159037
## Summary
Properly handle binary operator inference for union types.
This fixes a bug I noticed while looking at ecosystem results. The MRE
version of it is this:
```py
def sub(x: float, y: float):
# Red Knot: Operator `-` is unsupported between objects of type `int | float` and `int | float`
return x - y
```
## Test Plan
- New Markdown tests.
- Expected diff in the ecosystem checks
## Summary
Part of #15382
This PR adds the check for whether a callable type is fully static or
not.
A callable type is fully static if all of the parameter types are fully
static _and_ the return type is fully static _and_ if it does not use
the gradual form (`...`) for its parameters.
## Test Plan
Update `is_fully_static.md` with callable types.
It seems that currently this test is grouped into either fully static or
not, I think it would be useful to split them up in groups like
callable, etc. I intentionally avoided that in this PR but I'll put up a
PR for an appropriate split.
Note: I've an explicit goal of updating the property tests with the new
callable types once all relations are implemented.
## Summary
This PR closes#16248.
If the return type of the function isn't assignable to the one
specified, an `invalid-return-type` error occurs.
I thought it would be better to report this as a different kind of error
than the `invalid-assignment` error, so I defined this as a new error.
## Test Plan
All type inconsistencies in the test cases have been replaced with
appropriate ones.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
This updates the `Signature` and `CallBinding` machinery to support
multiple overloads for a callable. This is currently only used for
`KnownFunction`s that we special-case in our type inference code. It
does **_not_** yet update the semantic index builder to handle
`@overload` decorators and construct a multi-signature `Overloads`
instance for real Python functions.
While I was here, I updated many of the `try_call` special cases to use
signatures (possibly overloaded ones now) and `bind_call` to check
parameter lists. We still need some of the mutator methods on
`OverloadBinding` for the special cases where we need to update return
types based on some Rust code.
## Summary
One of the motivations in https://github.com/astral-sh/ruff/pull/16428
for panicking when the `test` or `debug_assertions` features are enabled
and a lookup of a `KnownClass` fails is that we've had some latent bugs
in our code where certain variants have been silently falling back to
`Unknown` in every typeshed lookup without us realising. But that in
itself isn't a great motivation for panicking in
`KnownClass::to_instance()`, since we can fairly easily add some tests
that assert that we don't unexpectedly fallback to `Unknown` for any
`KnownClass` variant. This PR adds those tests.
## Test Plan
`cargo test -p red_knot_python_semantic`
## Summary
This mostly fixes#14899
My motivation was similar to the last comment by @sharkdp there. I ran
red_knot on a codebase and the most common error was patterns like this
failing:
```
def foo(x: str): ...
x: Any = ...
if isinstance(x, str):
foo(x) # Object of type `Any & str` cannot be assigned to parameter 1 (`x`) of function `foo`; expected type `str`
```
The desired behavior is pretty much to ignore Any/Unknown when resolving
intersection assignability - `Any & str` should be assignable to `str`,
and `str` should be assignable to `str & Any`
The fix is actually very similar to the existing code in
`is_subtype_of`, we need to correctly handle intersections on either
side, while being careful to handle dynamic types as desired.
This does not fix the second test case from that issue:
```
static_assert(is_assignable_to(Intersection[Unrelated, Any], Not[tuple[Unrelated, Any]]))
```
but that's misleading because the root cause there has nothing to do
with gradual types. I added a simpler test case that also fails:
```
static_assert(is_assignable_to(Unrelated, Not[tuple[Unrelated]]))
```
This is because we don't determine that Unrelated does not subclass from
tuple so we can't rule out this relation. If that logic is improved then
this fix should also handle the case of the intersection
## Test Plan
Added a bunch of is_assignable_to tests, most of which failed before
this fix.
## Summary
Part of https://github.com/astral-sh/ruff/issues/15382
This PR adds support for inferring the `lambda` expression and return
the `CallableType`.
Currently, this is only limited to inferring the parameters and a todo
type for the return type.
For posterity, I tried using the `file_expression_type` to infer the
return type of lambda but it would always lead to cycle. The main reason
is that in `infer_parameter_definition`, the default expression is being
inferred using `file_expression_type`, which is correct, but it then
Take the following source code as an example:
```py
lambda x=1: x
```
Here's how the code will flow:
* `infer_scope_types` for the global scope
* `infer_lambda_expression`
* `infer_expression` for the default value `1`
* `file_expression_type` for the return type using the body expression.
This is because the body creates it's own scope
* `infer_scope_types` (lambda body scope)
* `infer_name_load` for the symbol `x` whose visible binding is the
lambda parameter `x`
* `infer_parameter_definition` for parameter `x`
* `file_expression_type` for the default value `1`
* `infer_scope_types` for the global scope because of the default
expression
This will then reach to `infer_definition` for the parameter `x` again
which then creates the cycle.
## Test Plan
Add tests around `lambda` expression inference.
## Summary
Theoretically this should be slightly more performant, since the
`class.is_known()` calls each do a separate Salsa lookup, which we can
avoid if we do a single `match` on the value of `class.known()`. It also
ends up being two lines less code overall!
## Test Plan
`cargo test -p red_knot_python_semantic`
## Summary
Fixes#16566, fixes#16575
The semantics of `Type::class_member` changed in
https://github.com/astral-sh/ruff/pull/16416, but the property-test
infrastructure was not updated. That means that the property tests were
panicking on the second `expect_type` call here:
0361021863/crates/red_knot_python_semantic/src/types/property_tests.rs (L151-L158)
With the somewhat unhelpful message:
```
Expected a (possibly unbound) type, not an unbound symbol
```
Applying this patch, and then running `QUICKCHECK_TESTS=1000000 cargo
test --release -p red_knot_python_semantic -- --ignored
types::property_tests::stable::equivalent_to_is_reflexive` showed
clearly that it was no longer able to find _any_ methods on _any_
classes due to the change in semantics of `Type::class_member`:
```diff
--- a/crates/red_knot_python_semantic/src/types/property_tests.rs
+++ b/crates/red_knot_python_semantic/src/types/property_tests.rs
@@ -27,7 +27,7 @@
use std::sync::{Arc, Mutex, MutexGuard, OnceLock};
use crate::db::tests::{setup_db, TestDb};
-use crate::symbol::{builtins_symbol, known_module_symbol};
+use crate::symbol::{builtins_symbol, known_module_symbol, Symbol};
use crate::types::{
BoundMethodType, CallableType, IntersectionBuilder, KnownClass, KnownInstanceType,
SubclassOfType, TupleType, Type, UnionType,
@@ -150,10 +150,11 @@ impl Ty {
Ty::BuiltinsFunction(name) => builtins_symbol(db, name).symbol.expect_type(),
Ty::BuiltinsBoundMethod { class, method } => {
let builtins_class = builtins_symbol(db, class).symbol.expect_type();
- let function = builtins_class
- .class_member(db, method.into())
- .symbol
- .expect_type();
+ let Symbol::Type(function, ..) =
+ builtins_class.class_member(db, method.into()).symbol
+ else {
+ panic!("no method `{method}` on class `{class}`");
+ };
create_bound_method(db, function, builtins_class)
}
```
This PR updates the property-test infrastructure to use `Type::member`
rather than `Type::class_member`.
## Test Plan
- Ran `QUICKCHECK_TESTS=1000000 cargo test --release -p
red_knot_python_semantic -- --ignored types::property_tests::stable`
successfully
- Checked that there were no remaining uses of `Type::class_member` in
`property_tests.rs`
## Summary
Fixes a small nit of mine -- we are currently inconsistent in our
spelling between "metaclass" and "meta class", and between "meta type"
and "meta-type". This PR means that we consistently use "metaclass" and
"meta-type".
## Test Plan
`uvx pre-commit run -a`
## Summary
Part of https://github.com/astral-sh/ruff/issues/15382
This PR implements a general callable type that wraps around a
`Signature` and it uses that new type to represent `typing.Callable`.
It also implements `Display` support for `Callable`. The format is as:
```
([<arg name>][: <arg type>][ = <default type>], ...) -> <return type>
```
The `/` and `*` separators are added at the correct boundary for
positional-only and keyword-only parameters. Now, as `typing.Callable`
only has positional-only parameters, the rendered signature would be:
```py
Callable[[int, str], None]
# (int, str, /) -> None
```
The `/` separator represents that all the arguments are positional-only.
The relationship methods that check assignability, subtype relationship,
etc. are not yet implemented and will be done so as a follow-up.
## Test Plan
Add test cases for display support for `Signature` and various mdtest
for `typing.Callable`.
## Summary
Resolves#16365
Add support for unpacking `with` statement targets.
## Test Plan
Added some test cases, alike the ones added by #15058.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## 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#16367closes#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.
## Summary
This PR closes#15199.
The change I just made is to set all variables to type `Unknown` if
unpacking fails, but in some cases this may be excessive.
For example:
```py
a, b, c = "ab"
reveal_type(a) # Unknown, but it would be reasonable to think of it as LiteralString
reveal_type(c) # Unknown
```
```py
# Failed to unpack before the starred expression
(a, b, *c, d, e) = (1,)
reveal_type(a) # Unknown
reveal_type(b) # Unknown
...
# Failed to unpack after the starred expression
(a, b, *c, d, e) = (1, 2, 3)
reveal_type(a) # Unknown, but should it be Literal[1]?
reveal_type(b) # Unknown, but should it be Literal[2]?
reveal_type(c) # Todo
reveal_type(d) # Unknown
reveal_type(e) # Unknown
```
I will modify it if you think it would be better to make it a different
type than just `Unknown`.
## Test Plan
I have made appropriate modifications to the test cases affected by this
change, and also added some more test cases.
## Summary
- `Never` is callable
- `Never` is iterable
- Arbitrary attributes can be accessed on `Never`
Split out from #16416 that is going to be required.
## Test Plan
Tests for all properties above.
## Summary
This PR introduces a new mdtest option `system` that can either be
`in-memory` or `os`
where `in-memory` is the default.
The motivation for supporting `os` is so that we can write OS/system
specific tests
with mdtests. Specifically, I want to write mdtests for the module
resolver,
testing that module resolution is case sensitive.
## Test Plan
I tested that the case-sensitive module resolver test start failing when
setting `system = "os"`
## Summary
Python's module resolver is case sensitive.
This PR adds mdtests that assert that our module resolution is case
sensitive.
The tests currently all pass because our in memory file system is case
sensitive.
I'll add support for using the real file system to the mdtest framework
in a separate PR.
This PR also adds support for specifying extra search paths to the
mdtest framework.
## Test Plan
The tests fail when running them using the real file system.
To kick off the work of supporting generics, this adds many new
(currently failing) tests, showing the behavior we plan to support.
This is still missing a lot! Not included:
- typevar tuples
- param specs
- variance
- `Self`
But it's a good start! We can add more failing tests for those once we
tackle these.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
This is split out of https://github.com/astral-sh/ruff/pull/14029, to
reduce the size of that PR, and to validate that this "fallback type"
support in `TypeInference` doesn't come with a performance cost. It also
improves the reliability and debuggability of our current (temporary)
cycle handling.
In order to recover from a cycle, we have to be able to construct a
"default" `TypeInference` where all expressions and definitions have
some "default" type. In our current cycle handling, this "default" type
is just unknown or a todo type. With fixpoint iteration, the "default"
type will be `Type::Never`, which is the "bottom" type that fixpoint
iteration starts from.
Since it would be costly (both in space and time) to actually enumerate
all expressions and definitions in a scope, just to insert the same
default type for all of them, instead we add an optional "missing type"
fallback to `TypeInference`, which (if set) is the fallback type for any
expression or definition which doesn't have an explicit type set.
With this change, cycles can no longer result in the dreaded "Missing
key" errors looking up the type of some expression.
This trait should eventually go away, so we rename it (and supporting
types) to make room for a new concrete `Diagnostic` type.
This commit is just the rename. In the next commit, we'll move it to a
different module.
## Summary
This PR does a small refactor to avoid double
`symbol_table(...).symbol(...)` call to check for `__slots__` and
`TYPE_CHECKING`. It merges them into a single call.
I noticed this while looking at
https://github.com/astral-sh/ruff/pull/16468.
## Summary
This PR adds more features to #16468.
* Adds a new error rule `invalid-type-checking-constant`, which occurs
when we try to assign a value other than `False` to a user-defined
`TYPE_CHECKING` variable (it is possible to assign `...` in a stub
file).
* Allows annotated assignment to `TYPE_CHECKING`. Only types that
`False` can be assigned to are allowed. However, the type of
`TYPE_CHECKING` will be inferred to be `Literal[True]` regardless of
what the type is specified.
## Test plan
I ran the tests with `cargo test -p red_knot_python_semantic` and
confirmed that all tests passed.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR closes#15722.
The change is that if the variable `TYPE_CHECKING` is defined/imported,
the type of the variable is interpreted as `Literal[True]` regardless of
what the value is.
This is compatible with the behavior of other type checkers (e.g. mypy,
pyright).
## Test Plan
I ran the tests with `cargo test -p red_knot_python_semantic` and
confirmed that all tests passed.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Regardless of whether #16408 and #16311 pan out, this part is worth
pulling out as a separate PR.
Before, you had to define a new `IndexVec` index type for each type of
association list you wanted to create. Now there's a single index type
that's internal to the alist implementation, and you use `List<K, V>` to
store a handle to a particular list.
This also adds some property tests for the alist implementation.
We currently keep two separate pieces of state regarding the current
loop on `SemanticIndexBuilder`. One is an enum simply reflecting whether
we are currently inside a loop, and the other is the saved flow states
for `break` statements found in the current loop.
For adding loopy control flow, I'll need to add some additional loop
state (`continue` states, for example). Prepare for this by
consolidating our existing loop state into a single struct and
simplifying the API for pushing and popping a loop.
This is purely a refactor, so tests are not changed.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Minor follow-up to https://github.com/astral-sh/ruff/pull/16161
This `not_callable` flag wasn't functional, because it could never be
`false`. It was initialized to `true` and then only ever updated with
`|=`, which can never make it `false`.
Add a test that exercises the case where it _should_ be `false` (all of
the union elements are callable) but `bindings` is also empty (all union
elements have binding errors). Before this PR, the added test wrongly
emits a diagnostic that the union `Literal[f1] | Literal[f2]` is not
callable.
And add a test where a union call results in one binding error and one
not-callable error, where we currently give the wrong result (we show
only the binding error), with a TODO.
Also add TODO comments in a couple other tests where ideally we'd report
more than just one error out of a union call.
Also update the flag name to `all_errors_not_callable` to more clearly
indicate the semantics of the flag.
In https://github.com/astral-sh/ruff/pull/16306#discussion_r1966290700,
@carljm pointed out that #16306 introduced a terminology problem, with
too many things called a "constraint". This is a follow-up PR that
renames `Constraint` to `Predicate` to hopefully clear things up a bit.
So now we have that:
- a _predicate_ is a Python expression that might influence type
inference
- a _narrowing constraint_ is a list of predicates that constraint the
type of a binding that is visible at a use
- a _visibility constraint_ is a ternary formula of predicates that
define whether a binding is visible or a statement is reachable
This is a pure renaming, with no behavioral changes.
## Summary
Model dunder-calls correctly (and in one single place), by implementing
this behavior (using `__getitem__` as an example).
```py
def getitem_desugared(obj: object, key: object) -> object:
getitem_callable = find_in_mro(type(obj), "__getitem__")
if hasattr(getitem_callable, "__get__"):
getitem_callable = getitem_callable.__get__(obj, type(obj))
return getitem_callable(key)
```
See the new `calls/dunder.md` test suite for more information. The new
behavior also needs much fewer lines of code (the diff is positive due
to new tests).
## Test Plan
New tests; fix TODOs in existing tests.
This PR adds an implementation of [association
lists](https://en.wikipedia.org/wiki/Association_list), and uses them to
replace the previous `BitSet`/`SmallVec` representation for narrowing
constraints.
An association list is a linked list of key/value pairs. We additionally
guarantee that the elements of an association list are sorted (by their
keys), and that they do not contain any entries with duplicate keys.
Association lists have fallen out of favor in recent decades, since you
often need operations that are inefficient on them. In particular,
looking up a random element by index is O(n), just like a linked list;
and looking up an element by key is also O(n), since you must do a
linear scan of the list to find the matching element. Luckily we don't
need either of those operations for narrowing constraints!
The typical implementation also suffers from poor cache locality and
high memory allocation overhead, since individual list cells are
typically allocated separately from the heap. We solve that last problem
by storing the cells of an association list in an `IndexVec` arena.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Add a diagnostic if a pure instance variable is accessed on a class object. For example
```py
class C:
instance_only: str
def __init__(self):
self.instance_only = "a"
# error: Attribute `instance_only` can only be accessed on instances, not on the class object `Literal[C]` itself.
C.instance_only
```
---------
Co-authored-by: David Peter <mail@david-peter.de>
