Refs https://github.com/astral-sh/ty/issues/544
## Summary
Takes a more incremental approach to PEP 613 type alias support (vs
https://github.com/astral-sh/ruff/pull/20107). Instead of eagerly
inferring the RHS of a PEP 613 type alias as a type expression, infer it
as a value expression, just like we do for implicit type aliases, taking
advantage of the same support for e.g. unions and other type special
forms.
The main reason I'm following this path instead of the one in
https://github.com/astral-sh/ruff/pull/20107 is that we've realized that
people do sometimes use PEP 613 type aliases as values, not just as
types (because they are just a normal runtime assignment, unlike PEP 695
type aliases which create an opaque `TypeAliasType`).
This PR doesn't yet provide full support for recursive type aliases
(they don't panic, but they just fall back to `Unknown` at the recursion
point). This is future work.
## Test Plan
Added mdtests.
Many new ecosystem diagnostics, mostly because we
understand new types in lots of places.
Conformance suite changes are correct.
Performance regression is due to understanding lots of new
types; nothing we do in this PR is inherently expensive.
Summary
--
Closes#19467 and also removes the warning about using Python 3.14
without
preview enabled.
I also bumped `PythonVersion::default` to 3.9 because it reaches EOL
this month,
but we could also defer that for now if we wanted.
The first three commits are related to the `latest` bump to 3.14; the
fourth commit
bumps the default to 3.10.
Note that this PR also bumps the default Python version for ty to 3.10
because
there was a test asserting that it stays in sync with
`ast::PythonVersion`.
Test Plan
--
Existing tests
I spot-checked the ecosystem report, and I believe these are all
expected. Inbits doesn't specify a target Python version, so I guess
we're applying the default. UP007, UP035, and UP045 all use the new
default value to emit new diagnostics.
We already had support for homogeneous tuples (`tuple[int, ...]`). This
PR extends this to also support mixed tuples (`tuple[str, str,
*tuple[int, ...], str str]`).
A mixed tuple consists of a fixed-length (possibly empty) prefix and
suffix, and a variable-length portion in the middle. Every element of
the variable-length portion must be of the same type. A homogeneous
tuple is then just a mixed tuple with an empty prefix and suffix.
The new data representation uses different Rust types for a fixed-length
(aka heterogeneous) tuple. Another option would have been to use the
`VariableLengthTuple` representation for all tuples, and to wrap the
"variable + suffix" portion in an `Option`. I don't think that would
simplify the method implementations much, though, since we would still
have a 2×2 case analysis for most of them.
One wrinkle is that the definition of the `tuple` class in the typeshed
has a single typevar, and canonically represents a homogeneous tuple.
When getting the class of a tuple instance, that means that we have to
summarize our detailed mixed tuple type information into its
"homogeneous supertype". (We were already doing this for heterogeneous
types.)
A similar thing happens when concatenating two mixed tuples: the
variable-length portion and suffix of the LHS, and the prefix and
variable-length portion of the RHS, all get unioned into the
variable-length portion of the result. The LHS prefix and RHS suffix
carry through unchanged.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
This PR adds initial support for listing all attributes of
an object. It is exposed through a new `all_members`
routine in `ty_extensions`, which is in turn used to test
the functionality.
The purpose of listing all members is for code
completion. That is, given a `object.<CURSOR>`, we
would like to list all available attributes on
`object`.
Division works differently in Python than in Rust. If the result is
negative and there is a remainder, the division rounds down (instead of
towards zero). The remainder needs to be adjusted to compensate so that
`(lhs // rhs) * rhs + (lhs % rhs) == lhs`.
Fixesastral-sh/ty#481.
This updates our function specialization inference to infer type
mappings from parameters that are generic aliases, e.g.:
```py
def f[T](x: list[T]) -> T: ...
reveal_type(f(["a", "b"])) # revealed: str
```
Though note that we're still inferring the type of list literals as
`list[Unknown]`, so for now we actually need something like the
following in our tests:
```py
def _(x: list[str]):
reveal_type(f(x)) # revealed: str
```
Alex Waygood
Carl Meyer
David Peter
github-actions[bot]
Brent Westbrook
Douglas Creager
Alperen Keleş
Andrew Gallant
Brandt Bucher
Charlie Marsh
Micha Reiser