## Summary
This changeset migrates all existing `is_assignable_to` tests to a
Markdown-based test. It also increases our test coverage in a hopefully
meaningful way (not claiming to be complete in any sense). But at least
I found and fixed one bug while doing so.
## Test Plan
Ran property tests to make sure the new test succeeds after fixing it.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Adds a type-check-time Python API that allows us to create and
manipulate types and to test various of their properties. For example,
this can be used to write a Markdown test to make sure that `A & B` is a
subtype of `A` and `B`, but not of an unrelated class `C` (something
that requires quite a bit more code to do in Rust):
```py
from knot_extensions import Intersection, is_subtype_of, static_assert
class A: ...
class B: ...
type AB = Intersection[A, B]
static_assert(is_subtype_of(AB, A))
static_assert(is_subtype_of(AB, B))
class C: ...
static_assert(not is_subtype_of(AB, C))
```
I think this functionality is also helpful for interactive debugging
sessions, in order to query various properties of Red Knot's type
system. Which is something that otherwise requires a custom Rust unit
test, some boilerplate code and constant re-compilation.
## Test Plan
- New Markdown tests
- Tested the modified typeshed_sync workflow locally
## Summary
`Type[Any]` should be assignable to `object`. All types should be
assignable to `object`.
We specifically didn't understand the former; this PR adds a test for
it, and a case to ensure that `Type[Any]` is assignable to anything that
`type` is assignable to (which includes `object`).
This PR also adds a property test that all types are assignable to
object. In order to make it pass, I added a special case to check early
if we are assigning to `object` and just return `true`. In principle,
once we get all the more general cases correct, this special case might
be removable. But having the special case for now allows the property
test to pass.
And we add a property test that all types are subtypes of object. This
failed for the case of an intersection with no positive elements (that
is, a negation type). This really does need to be a special case for
`object`, because there is no other type we can know that a negation
type is a subtype of.
## Test Plan
Added unit test and property test.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
We now support class patterns in a match statement, adding a narrowing
constraint that within the body of that match arm, we can assume that
the subject is an instance of that class.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
This implements checking of calls.
I ended up following Micha's original suggestion from back when the
signature representation was first introduced, and flattening it to a
single array of parameters. This turned out to be easier to manage,
because we can represent parameters using indices into that array, and
represent the bound argument types as an array of the same length.
Starred and double-starred arguments are still TODO; these won't be very
useful until we have generics.
The handling of diagnostics is just hacked into `return_ty_result`,
which was already inconsistent about whether it emitted diagnostics or
not; now it's even more inconsistent. This needs to be addressed, but
could be a follow-up.
The new benchmark errors here surface the need for intersection support
in `is_assignable_to`.
Fixes#14161.
## Test Plan
Added mdtests.
## Summary
When debugging, I frequently want to know which symbols are being looked
up. `symbol_by_id` adds tracing information, but it only shows the
`ScopedSymbolId`. Since `symbol_by_id` is only called from `symbol`, it
seems reasonable to move the tracing call one level up from
`symbol_by_id` to `symbol`, where we can also show the name of the
symbol.
**Before**:
```
6 └─┐red_knot_python_semantic::types::infer::infer_expression_types{expression=Id(60de), file=/home/shark/tomllib_modified/_parser.py}
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(33)}
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(123)}
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(54)}
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(122)}
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(165)}
6 ┌─┘
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(32)}
6 ┌─┘
6 └─┐red_knot_python_semantic::types::symbol_by_id{symbol=ScopedSymbolId(232)}
6 ┌─┘
6 ┌─┘
6 ┌─┘
6┌─┘
```
**After**:
```
5 └─┐red_knot_python_semantic::types::infer::infer_expression_types{expression=Id(60de), file=/home/shark/tomllib_modified/_parser.py}
5 └─┐red_knot_python_semantic::types::symbol{name="dict"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="dict"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="list"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="list"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="isinstance"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="isinstance"}
5 ┌─┘
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="ValueError"}
5 ┌─┘
5 └─┐red_knot_python_semantic::types::symbol{name="ValueError"}
5 ┌─┘
5 ┌─┘
5 ┌─┘
5┌─┘
```
## Test Plan
```
cargo run --bin red_knot -- --current-directory path/to/tomllib -vvv
```
## Summary
While looking at #14899, I looked at seeing if I could get shrinking on
the examples. It turned out to be straightforward, with a couple of
caveats.
I'm calling `clone` a lot during shrinking. Since by the shrink step
we're already looking at a test failure this feels fine? Unless I
misunderstood `quickcheck`'s core loop
When shrinking `Intersection`s, in order to just rely on `quickcheck`'s
`Vec` shrinking without thinking about it too much, the shrinking
strategy is:
- try to shrink the negative side (keeping the positive side the same)
- try to shrink the positive side (keeping the negative side the same)
This means that you can't shrink from `(A & B & ~C & ~D)` directly to
`(A & ~C)`! You would first need an intermediate failure at `(A & B &
~C)` or `(A & ~C & ~D)`. This feels good enough. Shrinking the negative
side first also has the benefit of trying to strip down negative
elements in these intersections.
## Test Plan
`cargo test -p red_knot_python_semantic -- --ignored
types::property_tests::stable` still fails as it current does on `main`,
but now the errors seem more minimal.
Just like in #15045 for unary expressions: In binary expressions, we
were only looking for dunder expressions for `Type::Instance` types. We
had some special cases for coercing the various `Literal` types into
their corresponding `Instance` types before doing the lookup. But we can
side-step all of that by using the existing `Type::to_meta_type` and
`Type::to_instance` methods.
Resolves#14840
## Summary
Usage of ellipsis literal as default argument is allowed in stub files.
## Test Plan
Added mdtest for both python files and stub files.
---------
Co-authored-by: Carl Meyer <carl@oddbird.net>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
The test expression in an `elif` clause is evaluated whether or not we
take the branch. Our control flow model for if/elif chains failed to
reflect this, causing wrong inference in cases where an assignment
expression occurs inside an `elif` test expression. Our "no branch taken
yet" snapshot (which is the starting state for every new elif branch)
can't simply be the pre-if state, it must be updated after visiting each
test expression.
Once we do this, it also means we no longer need to track a vector of
narrowing constraints to reapply for each new branch, since our "branch
not taken" state (which is the initial state for each branch) is
continuously updated to include the negative narrowing constraints of
all previous branches.
Fixes#15033.
## Test Plan
Added mdtests.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
We understand `sys.version_info` branches now! As such, I _believe_ this
branch is no longer required; all tests pass without it. I also ran
`QUICKCHECK_TESTS=100000 cargo test -p red_knot_python_semantic --
--ignored types::property_tests::stable`, and no tests failed except for
the known issue with `Type::is_assignable_to()`
(https://github.com/astral-sh/ruff/issues/14899)
## Test Plan
See above
## Summary
Remove `Type::tuple` in favor of `TupleType::from_elements`, avoid a few
intermediate `Vec`tors. Resolves an old [review
comment](https://github.com/astral-sh/ruff/pull/14744#discussion_r1867493706).
## Test Plan
New regression test for something I ran into while implementing this.
## Summary
Part of #13773
This PR adds diagnostics when there is a length mismatch during
unpacking between the number of target expressions and the number of
types for the unpack value expression.
There are 3 cases of diagnostics here where the first two occurs when
there isn't a starred expression and the last one occurs when there's a
starred expression:
1. Number of target expressions is **less** than the number of types
that needs to be unpacked
2. Number of target expressions is **greater** then the number of types
that needs to be unpacked
3. When there's a starred expression as one of the target expression and
the number of target expressions is greater than the number of types
Examples for all each of the above cases:
```py
# red-knot: Too many values to unpack (expected 2, got 3) [lint:invalid-assignment]
a, b = (1, 2, 3)
# red-knot: Not enough values to unpack (expected 2, got 1) [lint:invalid-assignment]
a, b = (1,)
# red-knot: Not enough values to unpack (expected 3 or more, got 2) [lint:invalid-assignment]
a, *b, c, d = (1, 2)
```
The (3) case is a bit special because it uses a distinct wording
"expected n or more" instead of "expected n" because of the starred
expression.
### Location
The diagnostic location is the target expression that's being unpacked.
For nested targets, the location will be the nested expression. For
example:
```py
(a, (b, c), d) = (1, (2, 3, 4), 5)
# ^^^^^^
# red-knot: Too many values to unpack (expected 2, got 3) [lint:invalid-assignment]
```
For future improvements, it would be useful to show the context for why
this unpacking failed. For example, for why the expected number of
targets is `n`, we can highlight the relevant elements for the value
expression.
In the **ecosystem**, **Pyright** uses the target expressions for
location while **mypy** uses the value expression for the location. For
example:
```py
if 1:
# mypy: Too many values to unpack (2 expected, 3 provided) [misc]
# vvvvvvvvv
a, b = (1, 2, 3)
# ^^^^
# Pyright: Expression with type "tuple[Literal[1], Literal[2], Literal[3]]" cannot be assigned to target tuple
# Type "tuple[Literal[1], Literal[2], Literal[3]]" is incompatible with target tuple
# Tuple size mismatch; expected 2 but received 3 [reportAssignmentType]
# red-knot: Too many values to unpack (expected 2, got 3) [lint:invalid-assignment]
```
## Test Plan
Update existing test cases TODO with the error directives.
## Summary
Ref:
3533d7f5b4 (r150651102)
This PR removes the `Ranged` implementation on `DefinitionKind` and
instead uses a method called `target_range` to avoid any confusion about
what range this is for i.e., it's not the range of the node that
represents the definition.
## Summary
Related to #13773
This PR adds support for unpacking `for` statement targets.
This involves updating the `value` field in the `Unpack` target to use
an enum which specifies the "where did the value expression came from?".
This is because for an iterable expression, we need to unpack the
iterator type while for assignment statement we need to unpack the value
type itself. And, this needs to be done in the unpack query.
### Question
One of the ways unpacking works in `for` statement is by looking at the
union of the types because if the iterable expression is a tuple then
the iterator type will be union of all the types in the tuple. This
means that the test cases that will test the unpacking in `for`
statement will also implicitly test the unpacking union logic. I was
wondering if it makes sense to merge these cases and only add the ones
that are specific to the union unpacking or for statement unpacking
logic.
## Test Plan
Add test cases involving iterating over a tuple type. I've intentionally
left out certain cases for now and I'm curious to know any thoughts on
the above query.
## Summary
This changeset adds support for precise type-inference and
boundness-handling of definitions inside control-flow branches with
statically-known conditions, i.e. test-expressions whose truthiness we
can unambiguously infer as *always false* or *always true*.
This branch also includes:
- `sys.platform` support
- statically-known branches handling for Boolean expressions and while
loops
- new `target-version` requirements in some Markdown tests which were
now required due to the understanding of `sys.version_info` branches.
closes#12700closes#15034
## Performance
### `tomllib`, -7%, needs to resolve one additional module (sys)
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./red_knot_main --project /home/shark/tomllib` | 22.2 ± 1.3 | 19.1 |
25.6 | 1.00 |
| `./red_knot_feature --project /home/shark/tomllib` | 23.8 ± 1.6 | 20.8
| 28.6 | 1.07 ± 0.09 |
### `black`, -6%
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./red_knot_main --project /home/shark/black` | 129.3 ± 5.1 | 119.0 |
137.8 | 1.00 |
| `./red_knot_feature --project /home/shark/black` | 136.5 ± 6.8 | 123.8
| 147.5 | 1.06 ± 0.07 |
## Test Plan
- New Markdown tests for the main feature in
`statically-known-branches.md`
- New Markdown tests for `sys.platform`
- Adapted tests for `EllipsisType`, `Never`, etc
## Summary
Refer:
https://github.com/astral-sh/ruff/issues/13773#issuecomment-2548020368
This PR adds support for unpacking union types.
Unpacking a union type requires us to first distribute the types for all
the targets that are involved in an unpacking. For example, if there are
two targets and a union type that needs to be unpacked, each target will
get a type from each element in the union type.
For example, if the type is `tuple[int, int] | tuple[int, str]` and the
target has two elements `(a, b)`, then
* The type of `a` will be a union of `int` and `int` which are at index
0 in the first and second tuple respectively which resolves to an `int`.
* Similarly, the type of `b` will be a union of `int` and `str` which
are at index 1 in the first and second tuple respectively which will be
`int | str`.
### Refactors
There are couple of refactors that are added in this PR:
* Add a `debug_assertion` to validate that the unpack target is a list
or a tuple
* Add a separate method to handle starred expression
## Test Plan
Update `unpacking.md` with additional test cases that uses union types.
This is done using parameter type hints style.
## Summary
This PR adds initial support for `type: ignore`. It doesn't do anything
fancy yet like:
* Detecting invalid type ignore comments
* Detecting type ignore comments that are part of another suppression
comment: `# fmt: skip # type: ignore`
* Suppressing specific lints `type: ignore [code]`
* Detecting unsused type ignore comments
* ...
The goal is to add this functionality in separate PRs.
## Test Plan
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
We have a handy `to_meta_type` that does the right thing for class
instances, and also works for all of the other types that are “instances
of” something. Unless I'm missing something, this should let us get rid
of the catch-all clause in one fell swoop.
cf #14548
## Summary
I'm currently on the fence about landing the #14760 PR because it's
unclear how we'd support tracking used and unused suppression comments
in a performant way:
* Salsa adds an "untracked" dependency to every query reading
accumulated values. This has the effect that the query re-runs on every
revision. For example, a possible future query
`unused_suppression_comments(db, file)` would re-run on every
incremental change and for every file. I don't expect the operation
itself to be expensive, but it all adds up in a project with 100k+ files
* Salsa collects the accumulated values by traversing the entire query
dependency graph. It can skip over sub-graphs if it is known that they
contain no accumulated values. This makes accumulators a great tool for
when they are rare; diagnostics are a good example. Unfortunately,
suppressions are more common, and they often appear in many different
files, making the "skip over subgraphs" optimization less effective.
Because of that, I want to wait to adopt salsa accumulators for type
check diagnostics (we could start using them for other diagnostics)
until we have very specific reasons that justify regressing incremental
check performance.
This PR does a "small" refactor that brings us closer to what I have in
#14760 but without using accumulators. To emit a diagnostic, a method
needs:
* Access to the db
* Access to the currently checked file
This PR introduces a new `InferContext` that holds on to the db, the
current file, and the reported diagnostics. It replaces the
`TypeCheckDiagnosticsBuilder`. We pass the `InferContext` instead of the
`db` to methods that *might* emit diagnostics. This simplifies some of
the `Outcome` methods, which can now be called with a context instead of
a `db` and the diagnostics builder. Having the `db` and the file on a
single type like this would also be useful when using accumulators.
This PR doesn't solve the issue that the `Outcome` types feel somewhat
complicated nor that it can be annoying when you need to report a
`Diagnostic,` but you don't have access to an `InferContext` (or the
file). However, I also believe that accumulators won't solve these
problems because:
* Even with accumulators, it's necessary to have a reference to the file
that's being checked. The struggle would be to get a reference to that
file rather than getting a reference to `InferContext`.
* Users of the `HasTy` trait (e.g., a linter) don't want to bother
getting the `File` when calling `Type::return_ty` because they aren't
interested in the created diagnostics. They just want to know what
calling the current expression would return (and if it even is a
callable). This is what the different methods of `Outcome` enable today.
I can ask for the return type without needing extra data that's only
relevant for emitting a diagnostic.
A shortcoming of this approach is that it is now a bit confusing when to
pass `db` and when an `InferContext`. An option is that we'd make the
`file` on `InferContext` optional (it won't collect any diagnostics if
`None`) and change all methods on `Type` to take `InferContext` as the
first argument instead of a `db`. I'm interested in your opinion on
this.
Accumulators are definitely harder to use incorrectly because they
remove the need to merge the diagnostics explicitly and there's no risk
that we accidentally merge the diagnostics twice, resulting in
duplicated diagnostics. I still value performance more over making our
life slightly easier.
This tweaks the new semantics from #15026 a bit when a symbol could be
interpreted both as an attribute and a submodule of a package. For
`from...import`, we should actually prioritize the attribute, because of
how the statement itself is implemented [1].
> 1. check if the imported module has an attribute by that name
> 2. if not, attempt to import a submodule with that name and then check
the imported module again for that attribute
[1] https://docs.python.org/3/reference/simple_stmts.html#the-import-statement
## Summary
Fixes#14550.
Add `AlwaysTruthy` and `AlwaysFalsy` types, representing the set of objects whose `__bool__` method can only ever return `True` or `False`, respectively, and narrow `if x` and `if not x` accordingly.
## Test Plan
- New Markdown test for truthiness narrowing `narrow/truthiness.md`
- unit tests in `types.rs` and `builders.rs` (`cargo test --package
red_knot_python_semantic --lib -- types`)
## Summary
Fixes https://github.com/astral-sh/ruff/issues/15027
The `MemoryFileSystem::write_file` API automatically creates
non-existing ancestor directoryes
but we failed to update the status of the now created ancestor
directories in the `Files` data structure.
## Test Plan
Tested that the case in https://github.com/astral-sh/ruff/issues/15027
now passes regardless of whether the *Simple* case is commented out or
not
## Summary
This PR updates the logic when raising conflicting declarations
diagnostic to avoid the undeclared path if present.
The conflicting declaration diagnostics is added when there are two or
more declarations in the control flow path of a definition whose type
isn't equivalent to each other. This can be seen in the following
example:
```py
if flag:
x: int
x = 1 # conflicting-declarations: Unknown, int
```
After this PR, we'd avoid considering "Unknown" as part of the
conflicting declarations. This means we'd still flag it for the
following case:
```py
if flag:
x: int
else:
x: str
x = 1 # conflicting-declarations: int, str
```
A solution that's local to the exception control flow was also explored
which required updating the logic for merging the flow snapshot to avoid
considering declarations using a flag. This is preserved here:
https://github.com/astral-sh/ruff/compare/dhruv/control-flow-no-declarations?expand=1.
The main motivation to avoid that is we don't really understand what the
user experience is w.r.t. the Unknown type and the
conflicting-declaration diagnostics. This makes us unsure on what the
right semantics are as to whether that diagnostics should be raised or
not and when to raise them. For now, we've decided to move forward with
this PR and could decide to adopt another solution or remove the
conflicting-declaration diagnostics in the future.
Closes: #13966
## Test Plan
Update the existing mdtest case. Add an additional case specific to
exception control flow to verify that the diagnostic is not being raised
now.
When importing a nested module, we were correctly creating a binding for
the top-most parent, but we were binding that to the nested module, not
to that parent module. Moreover, we weren't treating those submodules as
members of their containing parents. This PR addresses both issues, so
that nested imports work as expected.
As discussed in ~Slack~ whatever chat app I find myself in these days
😄, this requires keeping track of which modules have been imported
within the current file, so that when we resolve member access on a
module reference, we can see if that member has been imported as a
submodule. If so, we return the submodule reference immediately, instead
of checking whether the parent module's definition defines the symbol.
This is currently done in a flow insensitive manner. The `SemanticIndex`
now tracks all of the modules that are imported (via `import`, not via
`from...import`). The member access logic mentioned above currently only
considers module imports in the file containing the attribute
expression.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
A class is an instance of its metaclass, so `ClassLiteral("ABC")` is not
disjoint from `Instance("ABCMeta")`. However, we erroneously consider
the two types disjoint on the `main` branch. This PR fixes that.
This bug was uncovered by adding some more core types to the property
tests that provide coverage for classes that have custom metaclasses.
The additions to the property tests are included in this PR.
## Test Plan
New unit tests and property tests added. Tested with:
- `cargo test -p red_knot_python_semantic`
- `QUICKCHECK_TESTS=100000 cargo test -p red_knot_python_semantic --
--ignored types::property_tests::stable`
The assignability property test fails on this branch, but that's a known
issue that exists on `main`, due to
https://github.com/astral-sh/ruff/issues/14899.
## Summary
Teach red-knot that `type[...]` is always disjoint from `None` and from
`LiteralString`. Fixes#14925.
This should properly be generalized to "all instances of final types
which are not subclasses of `type`", but until we support finality,
hardcoding `None` (which is known to be final) allows us to fix the
subtype transitivity property test.
## Test Plan
Existing tests pass, added new unit tests for `is_disjoint_from` and
`is_subtype_of`.
`QUICKCHECK_TESTS=100000 cargo test -p red_knot_python_semantic --
--ignored types::property_tests::stable` fails only the "assignability
is reflexive" test, which is known to fail on `main` (#14899).
The same command, with `property_tests.rs` edited to prevent generating
intersection tests (the cause of #14899), passes all quickcheck tests.
## Summary
Resolves#14922.
## Test Plan
Markdown tests.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This is not strictly required yet, but makes these tests future-proof.
They need a `python-version` requirement as they rely on language
features that are not available in 3.9.
## Summary
Add support for `typing.TYPE_CHECKING` and
`typing_extensions.TYPE_CHECKING`.
relates to: https://github.com/astral-sh/ruff/issues/14170
## Test Plan
New Markdown-based tests
## Summary
This PR extends the mdtest configuration with a `log` setting that can
be any of:
* `true`: Enables tracing
* `false`: Disables tracing (default)
* String: An ENV_FILTER similar to `RED_KNOT_LOG`
```toml
log = true
```
Closes https://github.com/astral-sh/ruff/issues/13865
## Test Plan
I changed a test and tried `log=true`, `log=false`, and `log=INFO`
## Summary
This PR renames the `--custom-typeshed-dir`, `target-version`, and
`--current-directory` cli options to `--typeshed`,
`--python-version`, and `--project` as discussed in the CLI proposal
document.
I added aliases for `--target-version` (for Ruff compat) and
`--custom-typeshed-dir` (for Alex)
## Test Plan
Long help
```
An extremely fast Python type checker.
Usage: red_knot [OPTIONS] [COMMAND]
Commands:
server Start the language server
help Print this message or the help of the given subcommand(s)
Options:
--project <PROJECT>
Run the command within the given project directory.
All `pyproject.toml` files will be discovered by walking up the directory tree from the project root, as will the project's virtual environment (`.venv`).
Other command-line arguments (such as relative paths) will be resolved relative to the current working directory."#,
--venv-path <PATH>
Path to the virtual environment the project uses.
If provided, red-knot will use the `site-packages` directory of this virtual environment to resolve type information for the project's third-party dependencies.
--typeshed-path <PATH>
Custom directory to use for stdlib typeshed stubs
--extra-search-path <PATH>
Additional path to use as a module-resolution source (can be passed multiple times)
--python-version <VERSION>
Python version to assume when resolving types
[possible values: 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13]
-v, --verbose...
Use verbose output (or `-vv` and `-vvv` for more verbose output)
-W, --watch
Run in watch mode by re-running whenever files change
-h, --help
Print help (see a summary with '-h')
-V, --version
Print version
```
Short help
```
An extremely fast Python type checker.
Usage: red_knot [OPTIONS] [COMMAND]
Commands:
server Start the language server
help Print this message or the help of the given subcommand(s)
Options:
--project <PROJECT> Run the command within the given project directory
--venv-path <PATH> Path to the virtual environment the project uses
--typeshed-path <PATH> Custom directory to use for stdlib typeshed stubs
--extra-search-path <PATH> Additional path to use as a module-resolution source (can be passed multiple times)
--python-version <VERSION> Python version to assume when resolving types [possible values: 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13]
-v, --verbose... Use verbose output (or `-vv` and `-vvv` for more verbose output)
-W, --watch Run in watch mode by re-running whenever files change
-h, --help Print help (see more with '--help')
-V, --version Print version
```
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Regression test(s) for something that broken while implementing #14759.
We have similar tests for other control flow elements, but feel free to
let me know if this seems superfluous.
## Test Plan
New mdtests
## Summary
Using `typing.LiteralString` breaks as soon as we understand
`sys.version_info` branches, as it's only available in 3.11 and later.
## Test Plan
Made sure it didn't fail on my #14759 branch anymore.
We support using `typing.Type[]` as a base class (and we have tests for
it), but not yet `builtins.type[]`. At some point we should fix that,
but I don't think it';s worth spending much time on now (and it might be
easier once we've implemented generics?). This PR just adds a failing
test with a TODO.
## Summary
This is the third and last PR in this stack that adds support for
toggling lints at a per-rule level.
This PR introduces a new `LintRegistry`, a central index of known lints.
The registry is required because we want to support lint rules from many
different crates but need a way to look them up by name, e.g., when
resolving a lint from a name in the configuration or analyzing a
suppression comment.
Adding a lint now requires two steps:
1. Declare the lint with `declare_lint`
2. Register the lint in the registry inside the `register_lints`
function.
I considered some more involved macros to avoid changes in two places.
Still, I ultimately decided against it because a) it's just two places
and b) I'd expect that registering a type checker lint will differ from
registering a lint that runs as a rule in the linter. I worry that any
more opinionated design could limit our options when working on the
linter, so I kept it simple.
The second part of this PR is the `RuleSelection`. It stores which lints
are enabled and what severity they should use for created diagnostics.
For now, the `RuleSelection` always gets initialized with all known
lints and it uses their default level.
## Linter crates
Each crate that defines lints should export a `register_lints` function
that accepts a `&mut LintRegistryBuilder` to register all its known
lints in the registry. This should make registering all known lints in a
top-level crate easy: Just call `register_lints` of every crate that
defines lint rules.
I considered defining a `LintCollection` trait and even some fancy
macros to accomplish the same but decided to go for this very simplistic
approach for now. We can add more abstraction once needed.
## Lint rules
This is a bit hand-wavy. I don't have a good sense for how our linter
infrastructure will look like, but I expect we'll need a way to register
the rules that should run as part of the red knot linter. One way is to
keep doing what Ruff does by having one massive `checker` and each lint
rule adds a call to itself in the relevant AST visitor methods. An
alternative is that we have a `LintRule` trait that provides common
hooks and implementations will be called at the "right time". Such a
design would need a way to register all known lint implementations,
possibly with the lint. This is where we'd probably want a dedicated
`register_rule` method. A third option is that lint rules are handled
separately from the `LintRegistry` and are specific to the linter crate.
The current design should be flexible enough to support the three
options.
## Documentation generation
The documentation for all known lints can be generated by creating a
factory, registering all lints by calling the `register_lints` methods,
and then querying the registry for the metadata.
## Deserialization and Schema generation
I haven't fully decided what the best approach is when it comes to
deserializing lint rule names:
* Reject invalid names in the deserializer. This gives us error messages
with line and column numbers (by serde)
* Don't validate lint rule names during deserialization; defer the
validation until the configuration is resolved. This gives us more
control over handling the error, e.g. emit a warning diagnostic instead
of aborting when a rule isn't known.
One technical challenge for both deserialization and schema generation
is that the `Deserialize` and `JSONSchema` traits do not allow passing
the `LintRegistry`, which is required to look up the lints by name. I
suggest that we either rely on the salsa db being set for the current
thread (`salsa::Attach`) or build our own thread-local storage for the
`LintRegistry`. It's the caller's responsibility to make the lint
registry available before calling `Deserialize` or `JSONSchema`.
## CLI support
I prefer deferring adding support for enabling and disabling lints from
the CLI for now because I think it will be easier
to add once I've figured out how to handle configurations.
## Bitset optimization
Ruff tracks the enabled rules using a cheap copyable `Bitset` instead of
a hash map. This helped improve performance by a few percent (see
https://github.com/astral-sh/ruff/pull/3606). However, this approach is
no longer possible because lints have no "cheap" way to compute their
index inside the registry (other than using a hash map).
We could consider doing something similar to Salsa where each
`LintMetadata` stores a `LazyLintIndex`.
```
pub struct LazyLintIndex {
cached: OnceLock<(Nonce, LintIndex)>
}
impl LazyLintIndex {
pub fn get(registry: &LintRegistry, lint: &'static LintMetadata) {
let (nonce, index) = self.cached.get_or_init(|| registry.lint_index(lint));
if registry.nonce() == nonce {
index
} else {
registry.lint_index(lint)
}
}
```
Each registry keeps a map from `LintId` to `LintIndex` where `LintIndex`
is in the range of `0...registry.len()`. The `LazyLintIndex` is based on
the assumption that every program has exactly **one** registry. This
assumption allows to cache the `LintIndex` directly on the
`LintMetadata`. The implementation falls back to the "slow" path if
there is more than one registry at runtime.
I was very close to implementing this optimization because it's kind of
fun to implement. I ultimately decided against it because it adds
complexity and I don't think it's worth doing in Red Knot today:
* Red Knot only queries the rule selection when deciding whether or not
to emit a diagnostic. It is rarely used to detect if a certain code
block should run. This is different from Ruff where the rule selection
is queried many times for every single AST node to determine which rules
*should* run.
* I'm not sure if a 2-3% performance improvement is worth the complexity
I suggest revisiting this decision when working on the linter where a
fast path for deciding if a rule is enabled might be more important (but
that depends on how lint rules are implemented)
## Test Plan
I removed a lint from the default rule registry, and the MD tests
started failing because the diagnostics were no longer emitted.
This adds support for `type[Any]`, which represents an unknown type (not
an instance of an unknown type), and `type`, which we are choosing to
interpret as `type[object]`.
Closes#14546
## Summary
This is already several hundred lines of code, and it will get more
complex with call-signature checking.
## Test Plan
This is a pure code move; the moved code wasn't changed, just imports.
Existing tests pass.
## Summary
Add a `is_fully_static` premise to the equivalence on subtyping property tests.
## Test Plan
```
cargo test -p red_knot_python_semantic -- --ignored types::property_tests::stable
```
## Summary
This is the second PR out of three that adds support for
enabling/disabling lint rules in Red Knot. You may want to take a look
at the [first PR](https://github.com/astral-sh/ruff/pull/14869) in this
stack to familiarize yourself with the used terminology.
This PR adds a new syntax to define a lint:
```rust
declare_lint! {
/// ## What it does
/// Checks for references to names that are not defined.
///
/// ## Why is this bad?
/// Using an undefined variable will raise a `NameError` at runtime.
///
/// ## Example
///
/// ```python
/// print(x) # NameError: name 'x' is not defined
/// ```
pub(crate) static UNRESOLVED_REFERENCE = {
summary: "detects references to names that are not defined",
status: LintStatus::preview("1.0.0"),
default_level: Level::Warn,
}
}
```
A lint has a name and metadata about its status (preview, stable,
removed, deprecated), the default diagnostic level (unless the
configuration changes), and documentation. I use a macro here to derive
the kebab-case name and extract the documentation automatically.
This PR doesn't yet add any mechanism to discover all known lints. This
will be added in the next and last PR in this stack.
## Documentation
I documented some rules but then decided that it's probably not my best
use of time if I document all of them now (it also means that I play
catch-up with all of you forever). That's why I left some rules
undocumented (marked with TODO)
## Where is the best place to define all lints?
I'm not sure. I think what I have in this PR is fine but I also don't
love it because most lints are in a single place but not all of them. If
you have ideas, let me know.
## Why is the message not part of the lint, unlike Ruff's `Violation`
I understand that the main motivation for defining `message` on
`Violation` in Ruff is to remove the need to repeat the same message
over and over again. I'm not sure if this is an actual problem. Most
rules only emit a diagnostic in a single place and they commonly use
different messages if they emit diagnostics in different code paths,
requiring extra fields on the `Violation` struct.
That's why I'm not convinced that there's an actual need for it and
there are alternatives that can reduce the repetition when creating a
diagnostic:
* Create a helper function. We already do this in red knot with the
`add_xy` methods
* Create a custom `Diagnostic` implementation that tailors the entire
diagnostic and pre-codes e.g. the message
Avoiding an extra field on the `Violation` also removes the need to
allocate intermediate strings as it is commonly the place in Ruff.
Instead, Red Knot can use a borrowed string with `format_args`
## Test Plan
`cargo test`
## Summary
This PR introduces a structured `DiagnosticId` instead of using a plain
`&'static str`. It is the first of three in a stack that implements a
basic rules infrastructure for Red Knot.
`DiagnosticId` is an enum over all known diagnostic codes. A closed enum
reduces the risk of accidentally introducing two identical diagnostic
codes. It also opens the possibility of generating reference
documentation from the enum in the future (not part of this PR).
The enum isn't *fully closed* because it uses a `&'static str` for lint
names. This is because we want the flexibility to define lints in
different crates, and all names are only known in `red_knot_linter` or
above. Still, lower-level crates must already reference the lint names
to emit diagnostics. We could define all lint-names in `DiagnosticId`
but I decided against it because:
* We probably want to share the `DiagnosticId` type between Ruff and Red
Knot to avoid extra complexity in the diagnostic crate, and both tools
use different lint names.
* Lints require a lot of extra metadata beyond just the name. That's why
I think defining them close to their implementation is important.
In the long term, we may also want to support plugins, which would make
it impossible to know all lint names at compile time. The next PR in the
stack introduces extra syntax for defining lints.
A closed enum does have a few disadvantages:
* rustc can't help us detect unused diagnostic codes because the enum is
public
* Adding a new diagnostic in the workspace crate now requires changes to
at least two crates: It requires changing the workspace crate to add the
diagnostic and the `ruff_db` crate to define the diagnostic ID. I
consider this an acceptable trade. We may want to move `DiagnosticId` to
its own crate or into a shared `red_knot_diagnostic` crate.
## Preventing duplicate diagnostic identifiers
One goal of this PR is to make it harder to introduce ambiguous
diagnostic IDs, which is achieved by defining a closed enum. However,
the enum isn't fully "closed" because it doesn't explicitly list the IDs
for all lint rules. That leaves the possibility that a lint rule and a
diagnostic ID share the same name.
I made the names unambiguous in this PR by separating them into
different namespaces by using `lint/<rule>` for lint rule codes. I don't
mind the `lint` prefix in a *Ruff next* context, but it is a bit weird
for a standalone type checker. I'd like to not overfocus on this for now
because I see a few different options:
* We remove the `lint` prefix and add a unit test in a top-level crate
that iterates over all known lint rules and diagnostic IDs to ensure the
names are non-overlapping.
* We only render `[lint]` as the error code and add a note to the
diagnostic mentioning the lint rule. This is similar to clippy and has
the advantage that the header line remains short
(`lint/some-long-rule-name` is very long ;))
* Any other form of adjusting the diagnostic rendering to make the
distinction clear
I think we can defer this decision for now because the `DiagnosticId`
contains all the relevant information to change the rendering
accordingly.
## Why `Lint` and not `LintRule`
I see three kinds of diagnostics in Red Knot:
* Non-suppressable: Reveal type, IO errors, configuration errors, etc.
(any `DiagnosticId`)
* Lints: code-related diagnostics that are suppressable.
* Lint rules: The same as lints, but they can be enabled or disabled in
the configuration. The majority of lints in Red Knot and the Ruff
linter.
Our current implementation doesn't distinguish between lints and Lint
rules because we aren't aware of a suppressible code-related lint that
can't be configured in the configuration. The only lint that comes to my
mind is maybe `division-by-zero` if we're 99.99% sure that it is always
right. However, I want to keep the door open to making this distinction
in the future if it proves useful.
Another reason why I chose lint over lint rule (or just rule) is that I
want to leave room for a future lint rule and lint phase concept:
* lint is the *what*: a specific code smell, pattern, or violation
* the lint rule is the *how*: I could see a future `LintRule` trait in
`red_knot_python_linter` that provides the necessary hooks to run as
part of the linter. A lint rule produces diagnostics for exactly one
lint. A lint rule differs from all lints in `red_knot_python_semantic`
because they don't run as "rules" in the Ruff sense. Instead, they're a
side-product of type inference.
* the lint phase is a different form of *how*: A lint phase can produce
many different lints in a single pass. This is a somewhat common pattern
in Ruff where running one analysis collects the necessary information
for finding many different lints
* diagnostic is the *presentation*: Unlike a lint, the diagnostic isn't
the what, but how a specific lint gets presented. I expect that many
lints can use one generic `LintDiagnostic`, but a few lints might need
more flexibility and implement their custom diagnostic rendering (at
least custom `Diagnostic` implementation).
## Test Plan
`cargo test`
## Summary
Per suggestion in
https://github.com/astral-sh/ruff/pull/14802#discussion_r1875455417
This is a bit less error-prone and allows us to handle both expressions
in the current scope or a different scope. Also, there's currently no
need for this method outside of `TypeInferenceBuilder`, so no reason to
expose it in `types.rs`.
## Test Plan
Pure refactor, no functional change; existing tests pass.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
This adds support for `type[a.X]`, where the `type` special form is
applied to a qualified name that resolves to a class literal. This works
for both nested classes and classes imported from another module.
Closes#14545
## Summary
Inferred and declared types for function parameters, in the function
body scope.
Fixes#13693.
## Test Plan
Added mdtests.
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
`typing.Never` and `typing.LiteralString` are only conditionally
exported from `typing` for Python versions 3.11 and later. We run the
Markdown tests with the default Python version of 3.9, so here we change
the import to `typing_extensions` instead, and add a new test to make
sure we'll continue to understand the `typing`-version of these symbols
for newer versions.
This didn't cause problems so far, as we don't understand
`sys.version_info` branches yet.
## Test Plan
New Markdown tests to make sure this will continue to work in the
future.
## Summary
This adds support for specifying the target Python version from a
Markdown test. It is a somewhat limited ad-hoc solution, but designed to
be future-compatible. TOML blocks can be added to arbitrary sections in
the Markdown block. They have the following format:
````markdown
```toml
[tool.knot.environment]
target-version = "3.13"
```
````
So far, there is nothing else that can be configured, but it should be
straightforward to extend this to things like a custom typeshed path.
This is in preparation for the statically-known branches feature where
we are going to have to specify the target version for lots of tests.
## Test Plan
- New Markdown test that fails without the explicitly specified
`target-version`.
- Manually tested various error paths when specifying a wrong
`target-version` field.
- Made sure that running tests is as fast as before.
## Summary
This is related to #13778, more specifically
https://github.com/astral-sh/ruff/issues/13778#issuecomment-2513556004.
This PR adds various test cases where a keyword is being where an
identifier is expected. The tests are to make sure that red knot doesn't
panic, raises the syntax error and the identifier is added to the symbol
table. The final part allows editor related features like renaming the
symbol.
## Summary
`typing_extensions` has a `>=3.13` re-export for the `typing.NoDefault`
singleton, but not for `typing._NoDefaultType`. This causes problems as
soon as we understand `sys.version_info` branches, so we explicity
switch to `typing._NoDefaultType` for Python 3.13 and later.
This is a part of #14759 that I thought might make sense to break out
and merge in isolation.
## Test Plan
New test that will become more meaningful with #12700
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
- Instead of seven (more or less similar) `setup_db` functions, use just
one in a single central place.
- For every test that needs customization beyond that, offer a
`TestDbBuilder` that can control the Python target version, custom
typeshed, and pre-existing files.
The main motivation for this is that we're soon going to need
customization of the Python version, and I didn't feel like adding this
to each of the existing `setup_db` functions.
## Summary
This changeset contains various improvements concerning non-fully-static
types and their relationships:
- Make sure that non-fully-static types do not participate in
equivalence or subtyping.
- Clarify what `Type::is_equivalent_to` actually implements.
- Introduce `Type::is_fully_static`
- New tests making sure that multiple `Any`/`Unknown`s inside unions and
intersections are collapsed.
closes#14524
## Test Plan
- Added new unit tests for union and intersection builder
- Added new unit tests for `Type::is_equivalent_to`
- Added new unit tests for `Type::is_subtype_of`
- Added new property test making sure that non-fully-static types do not
participate in subtyping
We already had a representation for the Any type, which we would use
e.g. for expressions without type annotations. We now recognize
`typing.Any` as a way to refer to this type explicitly. Like other
special forms, this is tracked correctly through aliasing, and isn't
confused with local definitions that happen to have the same name.
Closes#14544
## Summary
Minor change that uses two plain classes `A` and `B` instead of
`typing.Sized` and `typing.Hashable`.
The motivation is twofold: I remember that I was confused when I first
saw this test. Was there anything specific to `Sized` and `Hashable`
that was relevant here? (there is, these classes are not overlapping;
and you can build a proper intersection from them; but that's true for
almost all non-builtin classes).
I now ran into another problem while working on #14758: `Sized` and
`Hashable` are protocols that we don't fully understand yet. This
causing some trouble when trying to infer whether these are fully-static
types or not.
## Summary
This PR adds a new `property_tests` module with quickcheck-based tests
that verify certain properties of types. The following properties are
currently checked:
* `is_equivalent_to`:
* is reflexive: `T` is equivalent to itself
* `is_subtype_of`:
* is reflexive: `T` is a subtype of `T`
* is antisymmetric: if `S <: T` and `T <: S`, then `S` is equivalent to
`T`
* is transitive: `S <: T` & `T <: U` => `S <: U`
* `is_disjoint_from`:
* is irreflexive: `T` is not disjoint from `T`
* is symmetric: `S` disjoint from `T` => `T` disjoint from `S`
* `is_assignable_to`:
* is reflexive
* `negate`:
* is an involution: `T.negate().negate()` is equivalent to `T`
There are also some tests that validate higher-level properties like:
* `S <: T` implies that `S` is not disjoint from `T`
* `S <: T` implies that `S` is assignable to `T`
* A singleton type must also be single-valued
These tests found a few bugs so far:
- #14177
- #14195
- #14196
- #14210
- #14731
Some additional notes:
- Quickcheck-based property tests are non-deterministic and finding
counter-examples might take an arbitrary long time. This makes them bad
candidates for running in CI (for every PR). We can think of running
them in a cron-job way from time to time, similar to fuzzing. But for
now, it's only possible to run them locally (see instructions in source
code).
- Some tests currently find false positive "counterexamples" because our
understanding of equivalence of types is not yet complete. We do not
understand that `int | str` is the same as `str | int`, for example.
These tests are in a separate `property_tests::flaky` module.
- Properties can not be formulated in every way possible, due to the
fact that `is_disjoint_from` and `is_subtype_of` can produce false
negative answers.
- The current shrinking implementation is very naive, which leads to
counterexamples that are very long (`str & Any & ~tuple[Any] &
~tuple[Unknown] & ~Literal[""] & ~Literal["a"] | str & int & ~tuple[Any]
& ~tuple[Unknown]`), requiring the developer to simplify manually. It
has not been a major issue so far, but there is a comment in the code
how this can be improved.
- The tests are currently implemented using a macro. This is a single
commit on top which can easily be reverted, if we prefer the plain code
instead. With the macro:
```rs
// `S <: T` implies that `S` can be assigned to `T`.
type_property_test!(
subtype_of_implies_assignable_to, db,
forall types s, t. s.is_subtype_of(db, t) => s.is_assignable_to(db, t)
);
```
without the macro:
```rs
/// `S <: T` implies that `S` can be assigned to `T`.
#[quickcheck]
fn subtype_of_implies_assignable_to(s: Ty, t: Ty) -> bool {
let db = get_cached_db();
let s = s.into_type(&db);
let t = t.into_type(&db);
!s.is_subtype_of(&*db, t) || s.is_assignable_to(&*db, t)
}
```
## Test Plan
```bash
while cargo test --release -p red_knot_python_semantic --features property_tests types::property_tests; do :; done
```
## Summary
`KnownInstance::instance_fallback` may return instances of supertypes.
For example, it returns an instance of `_SpecialForm` for `Literal`.
This means it can't be used on the right-hand side of `is_subtype_of`
relationships, because it might lead to false positives.
I can lead to false negatives on the left hand side of `is_subtype_of`,
but this is at least a known limitation. False negatives are fine for
most applications, but false positives can lead to wrong results in
intersection-simplification, for example.
closes#14731
## Test Plan
Added regression test
## Summary
Simplify tuples containing `Never` to `Never`:
```py
from typing import Never
def never() -> Never: ...
reveal_type((1, never(), "foo")) # revealed: Never
```
I should note that mypy and pyright do *not* perform this
simplification. I don't know why.
There is [only one
place](5137fcc9c8/crates/red_knot_python_semantic/src/types/infer.rs (L1477-L1484))
where we use `TupleType::new` directly (instead of `Type::tuple`, which
changes behavior here). This appears when creating `TypeVar`
constraints, and it looks to me like it should stay this way, because
we're using `TupleType` to store a list of constraints there, instead of
an actual type. We also store `tuple[constraint1, constraint2, …]` as
the type for the `constraint1, constraint2, …` tuple expression. This
would mean that we infer a type of `tuple[str, Never]` for the following
type variable constraints, without simplifying it to `Never`. This seems
like a weird edge case that's maybe not worth looking further into?!
```py
from typing import Never
# vvvvvvvvvv
def f[T: (str, Never)](x: T):
pass
```
## Test Plan
- Added a new unit test. Did not add additional Markdown tests as that
seems superfluous.
- Tested the example above using red knot, mypy, pyright.
- Verified that this allows us to remove `contains_never` from the
property tests
(https://github.com/astral-sh/ruff/pull/14178#discussion_r1866473192)
Resolves https://github.com/astral-sh/ruff/issues/14547 by delegating
narrowing to `E` for `bool(E)` where `E` is some expression.
This change does not include other builtin class constructors which
should also work in this position, like `int(..)` or `float(..)`, as the
original issue does not mention these. It should be easy enough to add
checks for these as well if we want to.
I don't see a lot of markdown tests for malformed input, maybe there's a
better place for the no args and too many args cases to go?
I did see after the fact that it looks like this task was intended for a
new hire.. my apologies. I got here from
https://github.com/astral-sh/ruff/issues/13694, which is marked
help-wanted.
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
Closes: https://github.com/astral-sh/ruff/issues/14593
The final type of a variable after if-statement without explicit else
branch should be similar to having an explicit else branch.
## Test Plan
Originally failed test cases from the bug are added.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
`bool()` is equal to `False`, and we infer `Literal[False]` for it. Which
means that the test here will fail as soon as we treat the body of
this `if` as unreachable.
## Summary
Fix panics related to expressions without inferred types in invalid
syntax examples like:
```py
x: f"Literal[{1 + 2}]" = 3
```
where the `1 + 2` expression (and its sub-expressions) inside the
annotation did not have an inferred type.
## Test Plan
Added new corpus test.
## Summary
This is about the easiest patch that I can think of. It has a drawback
in that there is no real guarantee this won't happen again. I think this
might be acceptable, given that all of this is a temporary thing.
And we also add a new CI job to prevent regressions like this in the
future.
For the record though, I'm listing alternative approaches I thought of:
- We could get rid of the debug/release distinction and just add `@Todo`
type metadata everywhere. This has possible affects on runtime. The main
reason I didn't follow through with this is that the size of `Type`
increases. We would either have to adapt the `assert_eq_size!` test or
get rid of it. Even if we add messages everywhere and get rid of the
file-and-line-variant in the enum, it's not enough to get back to the
current release-mode size of `Type`.
- We could generally discard `@Todo` meta information when using it in
tests. I think this would be a huge drawback. I like that we can have
the actual messages in the mdtest. And make sure we get the expected
`@Todo` type, not just any `@Todo`. It's also helpful when debugging
tests.
closes#14594
## Test Plan
```rs
cargo nextest run --release
```
Fix#14558
## Summary
- Add `typing.NoReturn` and `typing.Never` to known instances and infer
them as `Type::Never`
- Add `is_assignable_to` cases for `Type::Never`
I skipped emitting diagnostic for when a function is annotated as
`NoReturn` but it actually returns.
## Test Plan
Added tests from
https://github.com/python/typing/blob/main/conformance/tests/specialtypes_never.py
except from generics and checking if the return value of the function
and the annotations match.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Closes#14588
```py
x: Literal[42, "hello"] = 42 if bool_instance() else "hello"
reveal_type(x) # revealed: Literal[42] | Literal["hello"]
_ = ... if isinstance(x, str) else ...
# The `isinstance` test incorrectly narrows the type of `x`.
# As a result, `x` is revealed as Literal["hello"], but it should remain Literal[42, "hello"].
reveal_type(x) # revealed: Literal["hello"]
```
## Test Plan
mdtest included!
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
This fix addresses panics related to invalid syntax like the following
where a `break` statement is used in a nested definition inside a
loop:
```py
while True:
def b():
x: int
break
```
closes#14342
## Test Plan
* New corpus regression tests.
* New unit test to make sure we handle nested while loops correctly.
This test is passing on `main`, but can easily fail if the
`is_inside_loop` state isn't properly saved/restored.
## Summary
Add support for (non-generic) type aliases. The main motivation behind
this was to get rid of panics involving expressions in (generic) type
aliases. But it turned out the best way to fix it was to implement
(partial) support for type aliases.
```py
type IntOrStr = int | str
reveal_type(IntOrStr) # revealed: typing.TypeAliasType
reveal_type(IntOrStr.__name__) # revealed: Literal["IntOrStr"]
x: IntOrStr = 1
reveal_type(x) # revealed: Literal[1]
def f() -> None:
reveal_type(x) # revealed: int | str
```
## Test Plan
- Updated corpus test allow list to reflect that we don't panic anymore.
- Added Markdown-based test for type aliases (`type_alias.md`)
## Summary
Fixes a panic related to sub-expressions of `typing.Union` where we fail
to store a type for the `int, str` tuple-expression in code like this:
```
x: Union[int, str] = 1
```
relates to [my
comment](https://github.com/astral-sh/ruff/pull/14499#discussion_r1851794467)
on #14499.
## Test Plan
New corpus test
## Summary
Adds meta information to `Type::Todo`, allowing developers to easily
trace back the origin of a particular `@Todo` type they encounter.
Instead of `Type::Todo`, we now write either `type_todo!()` which
creates a `@Todo[path/to/source.rs:123]` type with file and line
information, or using `type_todo!("PEP 604 unions not supported")`,
which creates a variant with a custom message.
`Type::Todo` now contains a `TodoType` field. In release mode, this is
just a zero-sized struct, in order not to create any overhead. In debug
mode, this is an `enum` that contains the meta information.
`Type` implements `Copy`, which means that `TodoType` also needs to be
copyable. This limits the design space. We could intern `TodoType`, but
I discarded this option, as it would require us to have access to the
salsa DB everywhere we want to use `Type::Todo`. And it would have made
the macro invocations less ergonomic (requiring us to pass `db`).
So for now, the meta information is simply a `&'static str` / `u32` for
the file/line variant, or a `&'static str` for the custom message.
Anything involving a chain/backtrace of several `@Todo`s or similar is
therefore currently not implemented. Also because we currently don't see
any direct use cases for this, and because all of this will eventually
go away.
Note that the size of `Type` increases from 16 to 24 bytes, but only in
debug mode.
## Test Plan
- Observed the changes in Markdown tests.
- Added custom messages for all `Type::Todo`s that were revealed in the
tests
- Ran red knot in release and debug mode on the following Python file:
```py
def f(x: int) -> int:
reveal_type(x)
```
Prints `@Todo` in release mode and `@Todo(function parameter type)` in
debug mode.
Fix#14498
## Summary
This PR adds `typing.Union` support
## Test Plan
I created new tests in mdtest.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
closes#14279
### Limitations of the Current Implementation
#### Incorrect Error Propagation
In the current implementation of lexicographic comparisons, if the
result of an Eq operation is Ambiguous, the comparison stops
immediately, returning a bool instance. While this may yield correct
inferences, it fails to capture unsupported-operation errors that might
occur in subsequent comparisons.
```py
class A: ...
(int_instance(), A()) < (int_instance(), A()) # should error
```
#### Weak Inference in Specific Cases
> Example: `(int_instance(), "foo") == (int_instance(), "bar")`
> Current result: `bool`
> Expected result: `Literal[False]`
`Eq` and `NotEq` have unique behavior in lexicographic comparisons
compared to other operators. Specifically:
- For `Eq`, if any non-equal pair exists within the tuples being
compared, we can immediately conclude that the tuples are not equal.
- For `NotEq`, if any equal pair exists, we can conclude that the tuples
are unequal.
```py
a = (str_instance(), int_instance(), "foo")
reveal_type(a == a) # revealed: bool
reveal_type(a != a) # revealed: bool
b = (str_instance(), int_instance(), "bar")
reveal_type(a == b) # revealed: bool # should be Literal[False]
reveal_type(a != b) # revealed: bool # should be Literal[True]
```
#### Incorrect Support for Non-Boolean Rich Comparisons
In CPython, aside from `==` and `!=`, tuple comparisons return a
non-boolean result as-is. Tuples do not convert the value into `bool`.
Note: If all pairwise `==` comparisons between elements in the tuples
return Truthy, the comparison then considers the tuples' lengths.
Regardless of the return type of the dunder methods, the final result
can still be a boolean.
```py
from __future__ import annotations
class A:
def __eq__(self, o: object) -> str:
return "hello"
def __ne__(self, o: object) -> bytes:
return b"world"
def __lt__(self, o: A) -> float:
return 3.14
a = (A(), A())
reveal_type(a == a) # revealed: bool
reveal_type(a != a) # revealed: bool
reveal_type(a < a) # revealed: bool # should be: `float | Literal[False]`
```
### Key Changes
One of the major changes is that comparisons no longer end with a `bool`
result when a pairwise `Eq` result is `Ambiguous`. Instead, the function
attempts to infer all possible cases and unions the results. This
improvement allows for more robust type inference and better error
detection.
Additionally, as the function is now optimized for tuple comparisons,
the name has been changed from the more general
`infer_lexicographic_comparison` to `infer_tuple_rich_comparison`.
## Test Plan
mdtest included
## Summary
Previously, we panicked on expressions like `f"{v:{f'0.2f'}}"` because
we did not infer types for expressions nested inside format spec
elements.
## Test Plan
```
cargo nextest run -p red_knot_workspace -- --ignored linter_af linter_gz
```
## Summary
Add type narrowing for `type(x) is C` conditions (and `else` clauses of
`type(x) is not C` conditionals):
```py
if type(x) is A:
reveal_type(x) # revealed: A
else:
reveal_type(x) # revealed: A | B
```
closes: #14431, part of: #13694
## Test Plan
New Markdown-based tests.
## Summary
This patches up various missing paths where sub-expressions of type
annotations previously had no type attached. Examples include:
```py
tuple[int, str]
# ~~~~~~~~
type[MyClass]
# ~~~~~~~
Literal["foo"]
# ~~~~~
Literal["foo", Literal[1, 2]]
# ~~~~~~~~~~~~~
Literal[1, "a", random.illegal(sub[expr + ession])]
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
## Test Plan
```
cargo nextest run -p red_knot_workspace -- --ignored linter_af linter_gz
```
## Summary
This PR adds support for parsing and inferring types within string
annotations.
### Implementation (attempt 1)
This is preserved in
6217f48924.
The implementation here would separate the inference of string
annotations in the deferred query. This requires the following:
* Two ways of evaluating the deferred definitions - lazily and eagerly.
* An eager evaluation occurs right outside the definition query which in
this case would be in `binding_ty` and `declaration_ty`.
* A lazy evaluation occurs on demand like using the
`definition_expression_ty` to determine the function return type and
class bases.
* The above point means that when trying to get the binding type for a
variable in an annotated assignment, the definition query won't include
the type. So, it'll require going through the deferred query to get the
type.
This has the following limitations:
* Nested string annotations, although not necessarily a useful feature,
is difficult to implement unless we convert the implementation in an
infinite loop
* Partial string annotations require complex layout because inferring
the types for stringified and non-stringified parts of the annotation
are done in separate queries. This means we need to maintain additional
information
### Implementation (attempt 2)
This is the final diff in this PR.
The implementation here does the complete inference of string annotation
in the same definition query by maintaining certain state while trying
to infer different parts of an expression and take decisions
accordingly. These are:
* Allow names that are part of a string annotation to not exists in the
symbol table. For example, in `x: "Foo"`, if the "Foo" symbol is not
defined then it won't exists in the symbol table even though it's being
used. This is an invariant which is being allowed only for symbols in a
string annotation.
* Similarly, lookup name is updated to do the same and if the symbol
doesn't exists, then it's not bounded.
* Store the final type of a string annotation on the string expression
itself and not for any of the sub-expressions that are created after
parsing. This is because those sub-expressions won't exists in the
semantic index.
Design document:
https://www.notion.so/astral-sh/String-Annotations-12148797e1ca801197a9f146641e5b71?pvs=4Closes: #13796
## Test Plan
* Add various test cases in our markdown framework
* Run `red_knot` on LibCST (contains a lot of string annotations,
specifically
https://github.com/Instagram/LibCST/blob/main/libcst/matchers/_matcher_base.py),
FastAPI (good amount of annotated code including `typing.Literal`) and
compare against the `main` branch output
## Summary
Add a typed representation of function signatures (parameters and return
type) and infer it correctly from a function.
Convert existing usage of function return types to use the signature
representation.
This does not yet add inferred types for parameters within function body
scopes based on the annotations, but it should be easy to add as a next
step.
Part of #14161 and #13693.
## Test Plan
Added tests.
## Summary
This fixes several panics related to invalid assignment targets. All of
these led to some a crash, previously:
```py
(x.y := 1) # only name-expressions are valid targets of named expressions
([x, y] := [1, 2]) # same
(x, y): tuple[int, int] = (2, 3) # tuples are not valid targets for annotated assignments
(x, y) += 2 # tuples are not valid targets for augmented assignments
```
closes#14321closes#14322
## Test Plan
I symlinked four files from `crates/ruff_python_parser/resources` into
the red knot corpus, as they seemed like ideal test files for this exact
scenario. I think eventually, it might be a good idea to simply include *all*
invalid-syntax examples from the parser tests into red knots corpus (I believe
we're actually not too far from that goal). Or expand the scope of the corpus
test to this directory. Then we can get rid of these symlinks again.
## Summary
This avoids a panic inside `TypeInferenceBuilder::infer_type_parameters`
when encountering generic type aliases:
```py
type ListOrSet[T] = list[T] | set[T]
```
To fix this properly, we would have to treat type aliases as being their own
annotation scope [1]. The left hand side is a definition for the type parameter
`T` which is being used in the special annotation scope on the right hand side.
Similar to how it works for generic functions and classes.
[1] https://docs.python.org/3/reference/compound_stmts.html#generic-type-aliasescloses#14307
## Test Plan
Added new example to the corpus.
When we look up the types of class bases or keywords (`metaclass`), we
currently do this little dance: if there are type params, then look up
the type using `SemanticModel` in the type-params scope, if not, look up
the type directly in the definition's own scope, with support for
deferred types.
With inference of function parameter types, I'm now adding another case
of this same dance, so I'm motivated to make it a bit more ergonomic.
Add support to `definition_expression_ty` to handle any sub-expression
of a definition, whether it is in the definition's own scope or in a
type-params sub-scope.
Related to both #13693 and #14161.
## Summary
Use the memory address to uniquely identify AST nodes, instead of
relying on source range and kind. The latter fails for ASTs resulting
from invalid syntax examples. See #14313 for details.
Also results in a 1-2% speedup
(https://codspeed.io/astral-sh/ruff/runs/67349cf55f36b36baa211360)
closes#14313
## Review
Here are the places where we use `NodeKey` directly or indirectly (via
`ExpressionNodeKey` or `DefinitionNodeKey`):
```rs
// semantic_index.rs
pub(crate) struct SemanticIndex<'db> {
// [...]
/// Map expressions to their corresponding scope.
scopes_by_expression: FxHashMap<ExpressionNodeKey, FileScopeId>,
/// Map from a node creating a definition to its definition.
definitions_by_node: FxHashMap<DefinitionNodeKey, Definition<'db>>,
/// Map from a standalone expression to its [`Expression`] ingredient.
expressions_by_node: FxHashMap<ExpressionNodeKey, Expression<'db>>,
// [...]
}
// semantic_index/builder.rs
pub(super) struct SemanticIndexBuilder<'db> {
// [...]
scopes_by_expression: FxHashMap<ExpressionNodeKey, FileScopeId>,
definitions_by_node: FxHashMap<ExpressionNodeKey, Definition<'db>>,
expressions_by_node: FxHashMap<ExpressionNodeKey, Expression<'db>>,
}
// semantic_index/ast_ids.rs
pub(crate) struct AstIds {
/// Maps expressions to their expression id.
expressions_map: FxHashMap<ExpressionNodeKey, ScopedExpressionId>,
/// Maps expressions which "use" a symbol (that is, [`ast::ExprName`]) to a use id.
uses_map: FxHashMap<ExpressionNodeKey, ScopedUseId>,
}
pub(super) struct AstIdsBuilder {
expressions_map: FxHashMap<ExpressionNodeKey, ScopedExpressionId>,
uses_map: FxHashMap<ExpressionNodeKey, ScopedUseId>,
}
```
## Test Plan
Added two failing examples to the corpus.
## Summary
Fixes a failing debug assertion that triggers for the following code:
```py
match some_int:
case x:=2:
pass
```
closes#14305
## Test Plan
Added problematic code example to corpus.
## Summary
- Emit diagnostics when looking up (possibly) unbound attributes
- More explicit test assertions for unbound symbols
- Review remaining call sites of `Symbol::ignore_possibly_unbound`. Most
of them are something like `builtins_symbol(self.db,
"Ellipsis").ignore_possibly_unbound().unwrap_or(Type::Unknown)` which
look okay to me, unless we want to emit additional diagnostics. There is
one additional case in enum literal handling, which has a TODO comment
anyway.
part of #14022
## Test Plan
New MD tests for (possibly) unbound attributes.
## Summary
This adds a new diagnostic when possibly unbound symbols are imported.
The `TODO` comment had a question mark, do I'm not sure if this is
really something that we want.
This does not touch the un*declared* case, yet.
relates to: #14022
## Test Plan
Updated already existing tests with new diagnostics
## Summary
Apart from one small functional change, this is mostly a refactoring of
the `Symbol` API:
- Rename `as_type` to the more explicit `ignore_possibly_unbound`, no
functional change
- Remove `unwrap_or_unknown` in favor of the more explicit
`.ignore_possibly_unbound().unwrap_or(Type::Unknown)`, no functional
change
- Consistently call it "possibly unbound" (not "may be unbound")
- Rename `replace_unbound_with` to `or_fall_back_to` and properly handle
boundness of the fall back. This is the only functional change (did not
have any impact on existing tests).
relates to: #14022
## Test Plan
New unit tests for `Symbol::or_fall_back_to`
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Create definitions and infer types for PEP 695 type variables.
This just gives us the type of the type variable itself (the type of `T`
as a runtime object in the body of `def f[T](): ...`), with special
handling for its attributes `__name__`, `__bound__`, `__constraints__`,
and `__default__`. Mostly the support for these attributes exists
because it is easy to implement and allows testing that we are
internally representing the typevar correctly.
This PR doesn't yet have support for interpreting a typevar as a type
annotation, which is of course the primary use of a typevar. But the
information we store in the typevar's type in this PR gives us
everything we need to handle it correctly in a future PR when the
typevar appears in an annotation.
## Test Plan
Added mdtest.
## Summary
`Ty::BuiltinClassLiteral(…)` is a sub~~class~~type of
`Ty::BuiltinInstance("type")`, so it can't be disjoint from it.
## Test Plan
New `is_not_disjoint_from` test case
## Summary
Fix `Type::is_assignable_to` for union types on the left hand side (of
`.is_assignable_to`; or the right hand side of the `… = …` assignment):
`Literal[1, 2]` should be assignable to `int`.
## Test Plan
New unit tests that were previously failing.
## Summary
Minor fix to `Type::is_subtype_of` to make sure that Boolean literals
are subtypes of `int`, to match runtime semantics.
Found this while doing some property-testing experiments [1].
[1] https://github.com/astral-sh/ruff/pull/14178
## Test Plan
New unit test.
## Summary
Fixes#14114. I don't think I can really describe the problems with our
current architecture (and therefore the motivations for this PR) any
better than @carljm did in that issue, so I'll just copy it out here!
---
We currently represent "known instances" (e.g. special forms like
`typing.Literal`, which are an instance of `typing._SpecialForm`, but
need to be handled differently from other instances of
`typing._SpecialForm`) as an `InstanceType` with a `known` field that is
`Some(...)`.
This makes it easy to handle a known instance as if it were a regular
instance type (by ignoring the `known` field), and in some cases (e.g.
`Type::member`) that is correct and convenient. But in other cases (e.g.
`Type::is_equivalent_to`) it is not correct, and we currently have a bug
that we would consider the known-instance type of `typing.Literal` as
equivalent to the general instance type for `typing._SpecialForm`, and
we would fail to consider it a singleton type or a single-valued type
(even though it is both.)
An instance type with `known.is_some()` is semantically quite different
from an instance type with `known.is_none()`. The former is a singleton
type that represents exactly one runtime object; the latter is an open
type that represents many runtime objects, including instances of
unknown subclasses. It is too error-prone to represent these
very-different types as a single `Type` variant. We should instead
introduce a dedicated `Type::KnownInstance` variant and force ourselves
to handle these explicitly in all `Type` variant matches.
## Possible followups
There is still a little bit of awkwardness in our current design in some
places, in that we first infer the symbol `typing.Literal` as a
`_SpecialForm` instance, and then later convert that instance-type into
a known-instance-type. We could also use this `KnownInstanceType` enum
to account for other special runtime symbols such as `builtins.Ellipsis`
or `builtins.NotImplemented`.
I think these might be worth pursuing, but I didn't do them here as they
didn't seem essential right now, and I wanted to keep the diff
relatively minimal.
## Test Plan
`cargo test -p red_knot_python_semantic`. New unit tests added for
`Type::is_subtype_of`.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This adds type inference for comparison expressions involving
intersection types.
For example:
```py
x = get_random_int()
if x != 42:
reveal_type(x == 42) # revealed: Literal[False]
reveal_type(x == 43) # bool
```
closes#13854
## Test Plan
New Markdown-based tests.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
- Get rid of `Symbol::unwrap_or` (unclear semantics, not needed anymore)
- Introduce `Type::call_dunder`
- Emit new diagnostic for possibly-unbound `__iter__` methods
- Better diagnostics for callables with possibly-unbound /
possibly-non-callable `__call__` methods
part of: #14022closes#14016
## Test Plan
- Updated test for iterables with possibly-unbound `__iter__` methods.
- New tests for callables
## Summary
- Adds basic support for `type[C]` as a red knot `Type`. Some things
might not be supported yet, like `type[Any]`.
- Adds type narrowing for `issubclass` checks.
closes#14117
## Test Plan
New Markdown-based tests
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
I mirrored some of the idioms that @AlexWaygood used in the MRO work.
Closes https://github.com/astral-sh/ruff/issues/14096.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Related to
https://github.com/astral-sh/ruff/pull/13979#discussion_r1828305790,
this PR removes the `current_unpack` state field from
`SemanticIndexBuilder` and passes the `Unpack` ingredient via the
`CurrentAssignment` -> `DefinitionNodeRef` conversion to finally store
it on `DefintionNodeKind`.
This involves updating the lifetime of `AnyParameterRef` (parameter to
`declare_parameter`) to use the `'db` lifetime. Currently, all AST nodes
stored on various enums are marked with `'a` lifetime but they're always
utilized using the `'db` lifetime.
This also removes the dedicated `'a` lifetime parameter on
`add_definition` which is currently being used in `DefinitionNodeRef`.
As mentioned, all AST nodes live through the `'db` lifetime so we can
remove the `'a` lifetime parameter from that method and use the `'db`
lifetime instead.
## Summary
- Store the expression type for annotations that are starred expressions
(see [discussion
here](https://github.com/astral-sh/ruff/pull/14091#discussion_r1828332857))
- Use `self.store_expression_type(…)` consistently throughout, as it
makes sure that no double-insertion errors occur.
closes#14115
## Test Plan
Added an invalid-syntax example to the corpus which leads to a panic on
`main`. Also added a Markdown test with a valid-syntax example that
would lead to a panic once we implement function parameter inference.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Adds more precise type inference for `… is …` and `… is not …` identity
checks in some limited cases where we statically know the answer to be
either `Literal[True]` or `Literal[False]`.
I found this helpful while working on type inference for comparisons
involving intersection types, but I'm not sure if this is at all useful
for real world code (where the answer is most probably *not* statically
known). Note that we already have *type narrowing* for identity tests.
So while we are already able to generate constraints for things like `if
x is None`, we can now — in some limited cases — make an even stronger
conclusion and infer that the test expression itself is `Literal[False]`
(branch never taken) or `Literal[True]` (branch always taken).
## Test Plan
New Markdown tests
Handling `Literal` type in annotations.
Resolves: #13672
## Implementation
Since Literals are not a fully defined type in typeshed. I used a trick
to figure out when a special form is a literal.
When we are inferring assignment types I am checking if the type of that
assignment was resolved to typing.SpecialForm and the name of the target
is `Literal` if that is the case then I am re creating a new instance
type and set the known instance field to `KnownInstance:Literal`.
**Why not defining a new type?**
From this [issue](https://github.com/python/typeshed/issues/6219) I
learned that we want to resolve members to SpecialMethod class. So if we
create a new instance here we can rely on the member resolving in that
already exists.
## Tests
https://typing.readthedocs.io/en/latest/spec/literal.html#equivalence-of-two-literals
Since the type of the value inside Literal is evaluated as a
Literal(LiteralString, LiteralInt, ...) then the equality is only true
when types and value are equal.
https://typing.readthedocs.io/en/latest/spec/literal.html#legal-and-illegal-parameterizations
The illegal parameterizations are mostly implemented I'm currently
checking the slice expression and the slice type to make sure it's
valid.
https://typing.readthedocs.io/en/latest/spec/literal.html#shortening-unions-of-literals
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
This PR enables red-knot to support type narrowing based on `and` and
`or` conditionals, including nested combinations and their negation (for
`elif` / `else` blocks and for `not` operator). Part of #13694.
In order to address this properly (hopefully 😅), I had to run
`NarrowingConstraintsBuilder` functions recursively. In the first commit
I introduced a minor refactor - instead of mutating `self.constraints`,
the new constraints are now returned as function return values. I also
modified the constraints map to be optional, preventing unnecessary
hashmap allocations.
Thanks @carljm for your support on this :)
The second commit contains the logic and tests for handling boolean ops,
with improvements to intersections handling in `is_subtype_of` .
As I'm still new to Rust and the internals of type checkers, I’d be more
than happy to hear any insights or suggestions.
Thank you!
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Encountered this while running red-knot benchmarks on the `black`
codebase.
Fixes two of the issues in #13478.
## Test Plan
Added a regression test.
## Summary
Removes `Type::None` in favor of `KnownClass::NoneType.to_instance(…)`.
closes#13670
## Performance
There is a -4% performance regression on our red-knot benchmark. This is due to the fact that we now have to import `_typeshed` as a module, and infer types.
## Test Plan
Existing tests pass.
## Summary
This PR adds a new salsa query and an ingredient to resolve all the
variables involved in an unpacking assignment like `(a, b) = (1, 2)` at
once. Previously, we'd recursively try to match the correct type for
each definition individually which will result in creating duplicate
diagnostics.
This PR still doesn't solve the duplicate diagnostics issue because that
requires a different solution like using salsa accumulator or
de-duplicating the diagnostics manually.
Related: #13773
## Test Plan
Make sure that all unpack assignment test cases pass, there are no
panics in the corpus tests.
## Todo
- [x] Look at the performance regression
## Summary
Removing more TODOs from the augmented assignment test suite. Now, if
the _target_ is a union, we correctly infer the union of results:
```python
if flag:
f = Foo()
else:
f = 42.0
f += 12
```
## Summary
One of the follow-ups from augmented assignment inference, now that
`Type::Unbound` has been removed.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
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## Summary
- Remove `Type::Unbound`
- Handle (potential) unboundness as a concept orthogonal to the type
system (see new `Symbol` type)
- Improve existing and add new diagnostics related to (potential)
unboundness
closes#13671
## Test Plan
- Update existing markdown-based tests
- Add new tests for added/modified functionality
## Summary
This PR fixes a panic which can occur in an unpack assignment when:
* (number of target expressions) - (number of tuple types) > 2
* There's a starred expression
The reason being that the `insert` panics because the index is greater
than the length.
This is an error case and so practically it should occur very rarely.
The solution is to resize the types vector to match the number of
expressions and then insert the starred expression type.
## Test Plan
Add a new test case.
## Summary
This PR creates a new `TypeCheckDiagnosticsBuilder` for the
`TypeCheckDiagnostics` struct. The main motivation behind this is to
separate the helpers required to build the diagnostics from the type
inference builder itself. This allows us to use such helpers outside of
the inference builder like for example in the unpacking logic in
https://github.com/astral-sh/ruff/pull/13979.
## Test Plan
`cargo insta test`
## Summary
These cases aren't handled correctly yet -- some of them are waiting on
refactors to `Unbound` before fixing. Part of #12699.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
I noticed that augmented assignments on floats were yielding "not
supported" diagnostics. If the dunder isn't bound at all, we should use
binary operator semantics, rather than treating it as not-callable.
## Summary
Minor follow-up to #13917 — thanks @AlexWaygood for the post-merge
review.
- Add
SliceLiteralType::as_tuple
- Use .expect() instead of SAFETY
comment
- Match on ::try_from
result
- Add TODO comment regarding raising a diagnostic for `"foo"["bar":"baz"]`
## Summary
This PR adds support for heterogenous `tuple` annotations to red-knot.
It does the following:
- Extends `infer_type_expression` so that it understands tuple
annotations
- Changes `infer_type_expression` so that `ExprStarred` nodes in type
annotations are inferred as `Todo` rather than `Unknown` (they're valid
in PEP-646 tuple annotations)
- Extends `Type::is_subtype_of` to understand when one heterogenous
tuple type can be understood to be a subtype of another (without this
change, the PR would have introduced new false-positive errors to some
existing mdtests).
## Summary
- Add a new `Type::SliceLiteral` variant
- Infer `SliceLiteral` types for slice expressions, such as
`<int-literal>:<int-literal>:<int-literal>`.
- Infer "sliced" literal types for subscript expressions using slices,
such as `<string-literal>[<slice-literal>]`.
- Infer types for expressions involving slices of tuples:
`<tuple>[<slice-literal>]`.
closes#13853
## Test Plan
- Unit tests for indexing/slicing utility functions
- Markdown-based tests for
- Subscript expressions `tuple[slice]`
- Subscript expressions `string_literal[slice]`
- Subscript expressions `bytes_literal[slice]`
## Summary
This does two things:
- distribute negated intersections when building up intersections (i.e.
going from `A & ~(B & C)` to `(A & ~B) | (A & ~C)`) (fixing #13931)
## Test Plan
`cargo test`
## Summary
This PR adds type narrowing in `and` and `or` expressions, for example:
```py
class A: ...
x: A | None = A() if bool_instance() else None
isinstance(x, A) or reveal_type(x) # revealed: None
```
## Test Plan
New mdtests 😍
## Summary
After #13918 has landed, narrowing constraint negation became easy, so
adding support for `not` operator.
## Test Plan
Added a new mdtest file for `not` expression.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
As python uses short-circuiting boolean operations in runtime, we should
mimic that logic in redknot as well.
For example, we should detect that in the following code `x` might be
undefined inside the block:
```py
if flag or (x := 1):
print(x)
```
## Test Plan
Added mdtest suit for boolean expressions.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Add support for type narrowing in elif and else scopes as part of
#13694.
## Test Plan
- mdtest
- builder unit test for union negation.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Add type narrowing for `isinstance(object, classinfo)` [1] checks:
```py
x = 1 if flag else "a"
if isinstance(x, int):
reveal_type(x) # revealed: Literal[1]
```
closes#13893
[1] https://docs.python.org/3/library/functions.html#isinstance
## Test Plan
New Markdown-based tests in `narrow/isinstance.md`.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
A minor quality-of-life improvement: add
[`#[track_caller]`](https://doc.rust-lang.org/reference/attributes/codegen.html#the-track_caller-attribute)
attribute to `Type::expect_xyz()` methods and some `TypeInference` methods such that the panic-location
is reported one level higher up in the stack trace.
before: reports location inside the `Type::expect_class_literal()`
method. Not very useful.
```
thread 'types::infer::tests::deferred_annotation_builtin' panicked at crates/red_knot_python_semantic/src/types.rs:304:14:
Expected a Type::ClassLiteral variant
```
after: reports location at the `Type::expect_class_literal()` call site,
where the error was made.
```
thread 'types::infer::tests::deferred_annotation_builtin' panicked at crates/red_knot_python_semantic/src/types/infer.rs:4302:14:
Expected a Type::ClassLiteral variant
```
## Test Plan
Called `expect_class_literal()` on something that's not a
`Type::ClassLiteral` and saw that the error was reported at the call
site.
## Summary
* Rename `Type::Class` => `Type::ClassLiteral`
* Rename `Type::Function` => `Type::FunctionLiteral`
* Do not rename `Type::Module`
* Remove `*Literal` suffixes in `display::LiteralTypeKind` variants, as
per clippy suggestion
* Get rid of `Type::is_class()` in favor of `is_subtype_of(…, 'type')`;
modifiy `is_subtype_of` to support this.
* Add new `Type::is_xyz()` methods and use them instead of matching on
`Type` variants.
closes#13863
## Test Plan
New `is_subtype_of_class_literals` unit test.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
- Properly treat the empty intersection as being of type `object`.
- Consequently, change the simplification method to explicitly add
`Never` to the positive side of the intersection when collapsing a type
such as `int & str` to `Never`, as opposed to just clearing both the
positive and the negative side.
- Minor code improvement in `bindings_ty`: use `peekable()` to check
whether the iterator over constraints is empty, instead of handling
first and subsequent elements separately.
fixes#13870
## Test Plan
- New unit tests for `IntersectionBuilder` to make sure the empty
intersection represents `object`.
- Markdown-based regression test for the original issue in #13870
Add the following subtype relations:
- `BooleanLiteral <: object`
- `IntLiteral <: object`
- `StringLiteral <: object`
- `LiteralString <: object`
- `BytesLiteral <: object`
Added a test case for `bool <: int`.
## Test Plan
New unit tests.
Add type narrowing for `!=` expression as stated in
#13694.
### Test Plan
Add tests in new md format.
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
A small fix for comparisons of multiple comparators.
Instead of comparing each comparator to the leftmost item, we should
compare it to the closest item on the left.
While implementing this, I noticed that we don’t yet narrow Yoda
comparisons (e.g., `True is x`), so I didn’t change that behavior in
this PR.
## Test Plan
Added some mdtests 🎉
## Summary
Just a drive-by change that occurred to me while I was looking at
`Type::is_subtype_of`: the existing pattern for unions on the *right
hand side*:
```rs
(ty, Type::Union(union)) => union
.elements(db)
.iter()
.any(|&elem_ty| ty.is_subtype_of(db, elem_ty)),
```
is not (generally) correct if the *left hand side* is a union.
## Test Plan
Added new test cases for `is_subtype_of` and `!is_subtype_of`
## Summary
- Consistent naming: `BoolLiteral` => `BooleanLiteral` (it's mainly the
`Ty::BoolLiteral` variant that was renamed)
I tripped over this a few times now, so I thought I'll smooth it out.
- Add a new test case for `Literal[True] <: bool`, as suggested here:
https://github.com/astral-sh/ruff/pull/13781#discussion_r1804922827
Remove unnecessary uses of `.as_ref()`, `.iter()`, `&**` and similar, mostly in situations when iterating over variables. Many of these changes are only possible following #13826, when we bumped our MSRV to 1.80: several useful implementations on `&Box<[T]>` were only stabilised in Rust 1.80. Some of these changes we could have done earlier, however.
Implemented some points from
https://github.com/astral-sh/ruff/issues/12701
- Handle Unknown and Any in Unary operation
- Handle Boolean in binary operations
- Handle instances in unary operation
- Consider division by False to be division by zero
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
- Refactored comparison type inference functions in `infer.rs`: Changed
the return type from `Option` to `Result` to lay the groundwork for
providing more detailed diagnostics.
- Updated diagnostic messages.
This is a small step toward improving diagnostics in the future.
Please refer to #13787
## Test Plan
mdtest included!
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This fixes an edge case that @carljm and I missed when implementing
https://github.com/astral-sh/ruff/pull/13800. Namely, if the left-hand
operand is the _exact same type_ as the right-hand operand, the
reflected dunder on the right-hand operand is never tried:
```pycon
>>> class Foo:
... def __radd__(self, other):
... return 42
...
>>> Foo() + Foo()
Traceback (most recent call last):
File "<python-input-1>", line 1, in <module>
Foo() + Foo()
~~~~~~^~~~~~~
TypeError: unsupported operand type(s) for +: 'Foo' and 'Foo'
```
This edge case _is_ covered in Brett's blog at
https://snarky.ca/unravelling-binary-arithmetic-operations-in-python/,
but I missed it amongst all the other subtleties of this algorithm. The
motivations and history behind it were discussed in
https://mail.python.org/archives/list/python-dev@python.org/thread/7NZUCODEAPQFMRFXYRMGJXDSIS3WJYIV/
## Test Plan
I added an mdtest for this cornercase.
## Summary
- Add `Type::is_disjoint_from` as a way to test whether two types
overlap
- Add a first set of simplification rules for intersection types
- `S & T = S` for `S <: T`
- `S & ~T = Never` for `S <: T`
- `~S & ~T = ~T` for `S <: T`
- `A & ~B = A` for `A` disjoint from `B`
- `A & B = Never` for `A` disjoint from `B`
- `bool & ~Literal[bool] = Literal[!bool]`
resolves one item in #12694
## Open questions:
- Can we somehow leverage the (anti) symmetry between `positive` and
`negative` contributions? I could imagine that there would be a way if
we had `Type::Not(type)`/`Type::Negative(type)`, but with the
`positive`/`negative` architecture, I'm not sure. Note that there is a
certain duplication in the `add_positive`/`add_negative` functions (e.g.
`S & ~T = Never` is implemented twice), but other rules are actually not
perfectly symmetric: `S & T = S` vs `~S & ~T = ~T`.
- I'm not particularly proud of the way `add_positive`/`add_negative`
turned out. They are long imperative-style functions with some
mutability mixed in (`to_remove`). I'm happy to look into ways to
improve this code *if we decide to go with this approach* of
implementing a set of ad-hoc rules for simplification.
- ~~Is it useful to perform simplifications eagerly in
`add_positive`/`add_negative`? (@carljm)~~ This is what I did for now.
## Test Plan
- Unit tests for `Type::is_disjoint_from`
- Observe changes in Markdown-based tests
- Unit tests for `IntersectionBuilder::build()`
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Minor cleanup and consistent formatting of the Markdown-based tests.
- Removed lots of unnecessary `a`, `b`, `c`, … variables.
- Moved test assertions (`# revealed:` comments) closer to the tested
object.
- Always separate `# revealed` and `# error` comments from the code by
two spaces, according to the discussion
[here](https://github.com/astral-sh/ruff/pull/13746/files#r1799385758).
This trades readability for consistency in some cases.
- Fixed some headings
Summary
---------
PEP 695 Generics introduce a scope inside a class statement's arguments
and keywords.
```
class C[T](A[T]): # the T in A[T] is not from the global scope but from a type-param-specfic scope
...
```
When doing inference on the class bases, we currently have been doing
base class expression lookups in the global scope. Not an issue without
generics (since a scope is only created when generics are present).
This change instead makes sure to stop the global scope inference from
going into expressions within this sub-scope. Since there is a separate
scope, `check_file` and friends will trigger inference on these
expressions still.
Another change as a part of this is making sure that `ClassType` looks
up its bases in the right scope.
Test Plan
----------
`cargo test --package red_knot_python_semantic generics` will run the
markdown test that previously would panic due to scope lookup issues
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
Co-authored-by: Carl Meyer <carl@astral.sh>
This reverts https://github.com/astral-sh/ruff/pull/13799, and restores
the previous behavior, which I think was the most pragmatic and useful
version of the divide-by-zero error, if we will emit it at all.
In general, a type checker _does_ emit diagnostics when it can detect
something that will definitely be a problem for some inhabitants of a
type, but not others. For example, `x.foo` if `x` is typed as `object`
is a type error, even though some inhabitants of the type `object` will
have a `foo` attribute! The correct fix is to make your type annotations
more precise, so that `x` is assigned a type which definitely has the
`foo` attribute.
If we will emit it divide-by-zero errors, it should follow the same
logic. Dividing an inhabitant of the type `int` by zero may not emit an
error, if the inhabitant is an instance of a subclass of `builtins.int`
that overrides division. But it may emit an error (more likely it will).
If you don't want the diagnostic, you can clarify your type annotations
to require an instance of your safe subclass.
Because the Python type system doesn't have the ability to explicitly
reflect the fact that divide-by-zero is an error in type annotations
(e.g. for `int.__truediv__`), or conversely to declare a type as safe
from divide-by-zero, or include a "nonzero integer" type which it is
always safe to divide by, the analogy doesn't fully apply. You can't
explicitly mark your subclass of `int` as safe from divide-by-zero, we
just semi-arbitrarily choose to silence the diagnostic for subclasses,
to avoid false positives.
Also, if we fully followed the above logic, we'd have to error on every
`int / int` because the RHS `int` might be zero! But this would likely
cause too many false positives, because of the lack of a "nonzero
integer" type.
So this is just a pragmatic choice to emit the diagnostic when it is
very likely to be an error. It's unclear how useful this diagnostic is
in practice, but this version of it is at least very unlikely to cause
harm.
If the LHS is just `int` or `float` type, that type includes custom
subclasses which can arbitrarily override division behavior, so we
shouldn't emit a divide-by-zero error in those cases.
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Add type inference for comparisons involving union types. For example:
```py
one_or_two = 1 if flag else 2
reveal_type(one_or_two <= 2) # revealed: Literal[True]
reveal_type(one_or_two <= 1) # revealed: bool
reveal_type(one_or_two <= 0) # revealed: Literal[False]
```
closes#13779
## Test Plan
See `resources/mdtest/comparison/unions.md`
## Summary
Fixes the bug described in #13514 where an unbound public type defaulted
to the type or `Unknown`, whereas it should only be the type if unbound.
## Test Plan
Added a new test case
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR adds a debug assertion that asserts that `TypeInference::extend`
is only called on results that have the same scope.
This is critical because `expressions` uses `ScopedExpressionId` that
are local and merging expressions from different
scopes would lead to incorrect expression types.
We could consider storing `scope` only on `TypeInference` for debug
builds. Doing so has the advantage that the `TypeInference` type is
smaller of which we'll have many. However, a `ScopeId` is a `u32`... so
it shouldn't matter that much and it avoids storing the `scope` both on
`TypeInference` and `TypeInferenceBuilder`
## Test Plan
`cargo test`
## Summary
This PR implements comparisons for (tuple, tuple).
It will close#13688 and complete an item in #13618 once merged.
## Test Plan
Basic tests are included for (tuple, tuple) comparisons.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Just a small simplification to remove some unnecessary complexity here.
Rather than using separate branches for subscript expressions involving
boolean literals, we can simply convert them to integer literals and
reuse the logic in the `IntLiteral` branches.
## Test Plan
`cargo test -p red_knot_python_semantic`
## Summary
This PR adds support for unpacking tuple expression in an assignment
statement where the target expression can be a tuple or a list (the
allowed sequence targets).
The implementation introduces a new `infer_assignment_target` which can
then be used for other targets like the ones in for loops as well. This
delegates it to the `infer_definition`. The final implementation uses a
recursive function that visits the target expression in source order and
compares the variable node that corresponds to the definition. At the
same time, it keeps track of where it is on the assignment value type.
The logic also accounts for the number of elements on both sides such
that it matches even if there's a gap in between. For example, if
there's a starred expression like `(a, *b, c) = (1, 2, 3)`, then the
type of `a` will be `Literal[1]` and the type of `b` will be
`Literal[2]`.
There are a couple of follow-ups that can be done:
* Use this logic for other target positions like `for` loop
* Add diagnostics for mis-match length between LHS and RHS
## Test Plan
Add various test cases using the new markdown test framework.
Validate that existing test cases pass.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Porting infer tests to new markdown tests framework.
Link to the corresponding issue: #13696
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
- Fix a bug with `… is not …` type guards.
Previously, in an example like
```py
x = [1]
y = [1]
if x is not y:
reveal_type(x)
```
we would infer a type of `list[int] & ~list[int] == Never` for `x`
inside the conditional (instead of `list[int]`), since we built a
(negative) intersection with the type of the right hand side (`y`).
However, as this example shows, this assumption can only be made for
singleton types (types with a single inhabitant) such as `None`.
- Add support for `… is …` type guards.
closes#13715
## Test Plan
Moved existing `narrow_…` tests to Markdown-based tests and added new
ones (including a regression test for the bug described above). Note
that will create some conflicts with
https://github.com/astral-sh/ruff/pull/13719. I tried to establish the
correct organizational structure as proposed in
https://github.com/astral-sh/ruff/pull/13719#discussion_r1800188105
This adds documentation for the new test framework.
I also added documentation for the planned design of features we haven't
built yet (clearly marked as such), so that this doc can become the sole
source of truth for the test framework design (we don't need to refer
back to the original internal design document.)
Also fixes a few issues in the test framework implementation that were
discovered in writing up the docs.
---------
Co-authored-by: T-256 <132141463+T-256@users.noreply.github.com>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>
## Summary
Adds a markdown-based test framework for writing tests of type inference
and type checking. Fixes#11664.
Implements the basic required features. A markdown test file is a suite
of tests, each test can contain one or more Python files, with
optionally specified path/name. The test writes all files to an
in-memory file system, runs red-knot, and matches the resulting
diagnostics against `Type: ` and `Error: ` assertions embedded in the
Python source as comments.
We will want to add features like incremental tests, setting custom
configuration for tests, writing non-Python files, testing syntax
errors, capturing full diagnostic output, etc. There's also plenty of
room for improved UX (colored output?).
## Test Plan
Lots of tests!
Sample of the current output when a test fails:
```
Running tests/inference.rs (target/debug/deps/inference-7c96590aa84de2a4)
running 1 test
test inference::path_1_resources_inference_numbers_md ... FAILED
failures:
---- inference::path_1_resources_inference_numbers_md stdout ----
inference/numbers.md - Numbers - Floats
/src/test.py
line 2: unexpected error: [invalid-assignment] "Object of type `Literal["str"]` is not assignable to `int`"
thread 'inference::path_1_resources_inference_numbers_md' panicked at crates/red_knot_test/src/lib.rs:60:5:
Some tests failed.
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace
failures:
inference::path_1_resources_inference_numbers_md
test result: FAILED. 0 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out; finished in 0.19s
error: test failed, to rerun pass `-p red_knot_test --test inference`
```
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Fixed a TODO by adding another TODO. It's the red-knot way!
## Summary
`builtins.type` can be subscripted at runtime on Python 3.9+, even
though it has no `__class_getitem__` method and its metaclass (which
is... itself) has no `__getitem__` method. The special case is
[hardcoded directly into `PyObject_GetItem` in
CPython](744caa8ef4/Objects/abstract.c (L181-L184)).
We just have to replicate the special case in our semantic model.
This will fail at runtime on Python <3.9. However, there's a bunch of
outstanding questions (detailed in the TODO comment I added) regarding
how we deal with subscriptions of other generic types on lower Python
versions. Since we want to avoid too many false positives for now, I
haven't tried to address this; I've just made `type` subscriptable on
all Python versions.
## Test Plan
`cargo test -p red_knot_python_semantic --lib`
## Summary
Implements string literal comparisons and fallbacks to `str` instance
for `LiteralString`.
Completes an item in #13618
## Test Plan
- Adds a dedicated test with non exhaustive cases
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Implements the comparison operator for `[Type::IntLiteral]` and
`[Type::BooleanLiteral]` (as an artifact of special handling of `True` and
`False` in python).
Sets the framework to implement more comparison for types known at
static time (e.g. `BooleanLiteral`, `StringLiteral`), allowing us to only
implement cases of the triplet `<left> Type`, `<right> Type`, `CmpOp`.
Contributes to #12701 (without checking off an item yet).
## Test Plan
- Added a test for the comparison of literals that should include most
cases of note.
- Added a test for the comparison of int instances
Please note that the cases do not cover 100% of the branches as there
are many and the current testing strategy with variables make this
fairly confusing once we have too many in one test.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
...and remove periods from messages that don't span more than a single
sentence.
This is more consistent with how we present user-facing messages in uv
(which has a defined style guide).
## Summary
You can now call `return_ty_result` to operate on a `Result` directly
thereby using your own diagnostics, as in:
```rust
return dunder_getitem_method
.call(self.db, &[slice_ty])
.return_ty_result(self.db, value.as_ref().into(), self)
.unwrap_or_else(|err| {
self.add_diagnostic(
(&**value).into(),
"call-non-callable",
format_args!(
"Method `__getitem__` is not callable on object of type '{}'.",
value_ty.display(self.db),
),
);
err.return_ty()
});
```
Adds a diagnostic for division by the integer zero in `//`, `/`, and
`%`.
Doesn't handle `<int> / 0.0` because we don't track the values of float
literals.
This variant shows inference that is not yet implemented..
## Summary
PR #13500 reopened the idea of adding a new type variant to keep track
of not-implemented features in Red Knot.
It was based off of #12986 with a more generic approach of keeping track
of different kind of unknowns. Discussion in #13500 agreed that keeping
track of different `Unknown` is complicated for now, and this feature is
better achieved through a new variant of `Type`.
### Requirements
Requirements for this implementation can be summed up with some extracts
of comment from @carljm on the previous PR
> So at the moment we are leaning towards simplifying this PR to just
use a new top-level variant, which behaves like Any and Unknown but
represents inference that is not yet implemented in red-knot.
> I think the general rule should be that Todo should propagate only
when the presence of the input Todo caused the output to be unknown.
>
> To take a specific example, the inferred result of addition must be
Unknown if either operand is Unknown. That is, Unknown + X will always
be Unknown regardless of what X is. (Same for X + Unknown.) In this
case, I believe that Unknown + Todo (or Todo + Unknown) should result in
Unknown, not result in Todo. If we fix the upstream source of the Todo,
the result would still be Unknown, so it's not useful to propagate the
Todo in this case: it wrongly suggests that the output is unknown
because of a todo item.
## Test Plan
This PR does not introduce new tests, but it did required to edit some
tests with the display of `[Type::Todo]` (currently `@Todo`), which
suggests that those test are placeholders requirements for features we
don't support yet.
While working on https://github.com/astral-sh/ruff/pull/13576 I noticed
that it was really hard to tell which assertion failed in some of these
test cases. This could be expanded to elsewhere, but I've heard this
test suite format won't be around for long?
## Summary
Following #13449, this PR adds custom handling for the bool constructor,
so when the input type has statically known truthiness value, it will be
used as the return value of the bool function.
For example, in the following snippet x will now be resolved to
`Literal[True]` instead of `bool`.
```python
x = bool(1)
```
## Test Plan
Some cargo tests were added.
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## Summary
Implement inference for `f-string`, contributes to #12701.
### First Implementation
When looking at the way `mypy` handles things, I noticed the following:
- No variables (e.g. `f"hello"`) ⇒ `LiteralString`
- Any variable (e.g. `f"number {1}"`) ⇒ `str`
My first commit (1ba5d0f13fdf70ed8b2b1a41433b32fc9085add2) implements
exactly this logic, except that we deal with string literals just like
`infer_string_literal_expression` (if below `MAX_STRING_LITERAL_SIZE`,
show `Literal["exact string"]`)
### Second Implementation
My second commit (90326ce9af5549af7b4efae89cd074ddf68ada14) pushes
things a bit further to handle cases where the expression within the
`f-string` are all literal values (string representation known at static
time).
Here's an example of when this could happen in code:
```python
BASE_URL = "https://httpbin.org"
VERSION = "v1"
endpoint = f"{BASE_URL}/{VERSION}/post" # Literal["https://httpbin.org/v1/post"]
```
As this can be sightly more costly (additional allocations), I don't
know if we want this feature.
## Test Plan
- Added a test `fstring_expression` covering all cases I can think of
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR changes removes the typeshed stubs from the vendored file system
shipped with ruff
and instead ships an empty "typeshed".
Making the typeshed files optional required extracting the typshed files
into a new `ruff_vendored` crate. I do like this even if all our builds
always include typeshed because it means `red_knot_python_semantic`
contains less code that needs compiling.
This also allows us to use deflate because the compression algorithm
doesn't matter for an archive containing a single, empty file.
## Test Plan
`cargo test`
I verified with ` cargo tree -f "{p} {f}" -p <package> ` that:
* red_knot_wasm: enables `deflate` compression
* red_knot: enables `zstd` compression
* `ruff`: uses stored
I'm not quiet sure how to build the binary that maturin builds but
comparing the release artifact size with `strip = true` shows a `1.5MB`
size reduction
---------
Co-authored-by: Charlie Marsh <charlie.r.marsh@gmail.com>
Avoid quadratic time in subsumed elements when adding a super-type of
existing union elements.
Reserve space in advance when adding multiple elements (from another
union) to a union.
Make union elements a `Box<[Type]>` instead of an `FxOrderSet`; the set
doesn't buy much since the rules of union uniqueness are defined in
terms of supertype/subtype, not in terms of simple type identity.
Move sealed-boolean handling out of a separate `UnionBuilder::simplify`
method and into `UnionBuilder::add`; now that `add` is iterating
existing elements anyway, this is more efficient.
Remove `UnionType::contains`, since it's now `O(n)` and we shouldn't
really need it, generally we care about subtype/supertype, not type
identity. (Right now it's used for `Type::Unbound`, which shouldn't even
be a type.)
Add support for `is_subtype_of` for the `object` type.
Addresses comments on https://github.com/astral-sh/ruff/pull/13401
This was mentioned in an earlier review, and seemed easy enough to just
do it. No need to repeat all the types twice when it gives no additional
information.
## Summary
This PR adds an experimental Ruff subcommand to generate dependency
graphs based on module resolution.
A few highlights:
- You can generate either dependency or dependent graphs via the
`--direction` command-line argument.
- Like Pants, we also provide an option to identify imports from string
literals (`--detect-string-imports`).
- Users can also provide additional dependency data via the
`include-dependencies` key under `[tool.ruff.import-map]`. This map uses
file paths as keys, and lists of strings as values. Those strings can be
file paths or globs.
The dependency resolution uses the red-knot module resolver which is
intended to be fully spec compliant, so it's also a chance to expose the
module resolver in a real-world setting.
The CLI is, e.g., `ruff graph build ../autobot`, which will output a
JSON map from file to files it depends on for the `autobot` project.
This fixes the last panic on checking pandas.
(Match statement became an `if let` because clippy decided it wanted
that once I added the additional line in the else case?)
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Support using `reveal_type` without importing it, as implied by the type
spec and supported by existing type checkers.
We use `typing_extensions.reveal_type` for the implicit built-in; this
way it exists on all Python versions. (It imports from `typing` on newer
Python versions.)
Emits an "undefined name" diagnostic whenever `reveal_type` is
referenced in this way (in addition to the revealed-type diagnostic when
it is called). This follows the mypy example (with `--enable-error-code
unimported-reveal`) and I think provides a good (and easily
understandable) balance for user experience. If you are using
`reveal_type` for quick temporary debugging, the additional
undefined-name diagnostic doesn't hinder that use case. If we make the
revealed-type diagnostic a non-failing one, the undefined-name
diagnostic can still be a failing diagnostic, helping prevent
accidentally leaving it in place. For any use cases where you want to
leave it in place, you can always import it to avoid the undefined-name
diagnostic.
In the future, we can easily provide configuration options to a) turn
off builtin-reveal_type altogether, and/or b) silence the undefined-name
diagnostic when using it, if we have users on either side (loving or
hating pseudo-builtin `reveal_type`) who are dissatisfied with this
compromise.
After looking at more cases (for example, the case in the added test in
this PR), I realized that our previous rule, "if a symbol has any
declarations, use only declarations for its public type" is not
adequate. Rather than using `Unknown` as fallback if the symbol is not
declared in some paths, we need to use the inferred type as fallback in
that case.
For the paths where the symbol _was_ declared, we know that any bindings
must be assignable to the declared type in that path, so this won't
change the overall declared type in those paths. But for paths where the
symbol wasn't declared, this will give us a better type in place of
`Unknown`.
Before `typing.reveal_type` existed, there was
`typing_extensions.reveal_type`. We should support both.
Also adds a test to verify that we can handle aliasing of `reveal_type`
to a different name.
Adds a bit of code to ensure that if we have a union of different
`reveal_type` functions (e.g. a union containing both
`typing_extensions.reveal_type` and `typing.reveal_type`) we still emit
the reveal-type diagnostic only once. This is probably unlikely in
practice, but it doesn't hurt to handle it smoothly. (It comes up now
because we don't support `version_info` checks yet, so
`typing_extensions.reveal_type` is actually that union.)
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
I noticed that this pattern sometimes occurs in typeshed:
```
if ...:
from foo import bar
else:
def bar(): ...
```
If we have the rule that symbols with declarations only use declarations
for the public type, then this ends up resolving as `Unknown |
Literal[bar]`, because we didn't consider the import to be a
declaration.
I think the most straightforward thing here is to also consider imports
as declarations. The same rationale applies as for function and class
definitions: if you shadow an import, you should have to explicitly
shadow with an annotation, rather than just doing it
implicitly/accidentally.
We may also ultimately need to re-evaluate the rule that public type
considers only declarations, if there are declarations.
Add support for the `typing.reveal_type` function, emitting a diagnostic
revealing the type of its single argument. This is a necessary piece for
the planned testing framework.
This puts the cart slightly in front of the horse, in that we don't yet
have proper support for validating call signatures / argument types. But
it's easy to do just enough to make `reveal_type` work.
This PR includes support for calling union types (this is necessary
because we don't yet support `sys.version_info` checks, so
`typing.reveal_type` itself is a union type), plus some nice
consolidated error messages for calls to unions where some elements are
not callable. This is mostly to demonstrate the flexibility in
diagnostics that we get from the `CallOutcome` enum.
Use declared types in inference and checking. This means several things:
* Imports prefer declarations over inference, when declarations are
available.
* When we encounter a binding, we check that the bound value's inferred
type is assignable to the live declarations of the bound symbol, if any.
* When we encounter a declaration, we check that the declared type is
assignable from the inferred type of the symbol from previous bindings,
if any.
* When we encounter a binding+declaration, we check that the inferred
type of the bound value is assignable to the declared type.
Add support for declared types to the semantic index. This involves a
lot of renaming to clarify the distinction between bindings and
declarations. The Definition (or more specifically, the DefinitionKind)
becomes responsible for determining which definitions are bindings,
which are declarations, and which are both, and the symbol table
building is refactored a bit so that the `IS_BOUND` (renamed from
`IS_DEFINED` for consistent terminology) flag is always set when a
binding is added, rather than being set separately (and requiring us to
ensure it is set properly).
The `SymbolState` is split into two parts, `SymbolBindings` and
`SymbolDeclarations`, because we need to store live bindings for every
declaration and live declarations for every binding; the split lets us
do this without storing more than we need.
The massive doc comment in `use_def.rs` is updated to reflect bindings
vs declarations.
The `UseDefMap` gains some new APIs which are allow-unused for now,
since this PR doesn't yet update type inference to take declarations
into account.
Add `::is_empty` and `::union` methods to the `BitSet` implementation.
Allowing unused for now, until these methods become used later with the
declared-types implementation.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
These are quite incomplete, but I needed to start stubbing them out in
order to build and test declared-types.
Allowing unused for now, until they are used later in the declared-types
PR.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
This PR adds a new `Type` variant called `TupleType` which is used for
heterogeneous elements.
### Display notes
* For an empty tuple, I'm using `tuple[()]` as described in the docs:
https://docs.python.org/3/library/typing.html#annotating-tuples
* For nested elements, it'll use the literal type instead of builtin
type unlike Pyright which does `tuple[Literal[1], tuple[int, int]]`
instead of `tuple[Literal[1], tuple[Literal[2], Literal[3]]]`. Also,
mypy would give `tuple[builtins.int, builtins.int]` instead of
`tuple[Literal[1], Literal[2]]`
## Test Plan
Update test case to account for the display change and add cases for
multiple elements and nested tuple elements.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR adds support for control flow for match statement.
It also adds the necessary infrastructure required for narrowing
constraints in case blocks and implements the logic for
`PatternMatchSingleton` which is either `None` / `True` / `False`. Even
after this the inferred type doesn't get simplified completely, there's
a TODO for that in the test code.
## Test Plan
Add test cases for control flow for (a) when there's a wildcard pattern
and (b) when there isn't. There's also a test case to verify the
narrowing logic.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
When a type of the form `Literal["..."]` would be constructed with too
large of a string, this PR converts it to `LiteralString` instead.
We also extend inference for binary operations to include the case where
one of the operands is `LiteralString`.
Closes#13224
Pull the tests from `types.rs` into `infer.rs`.
All of these are integration tests with the same basic form: create a
code sample, run type inference or check on it, and make some assertions
about types and/or diagnostics. These are the sort of tests we will want
to move into a test framework with a low-boilerplate custom textual
format. In the meantime, having them together (and more importantly,
their helper utilities together) means that it's easy to keep tests for
related language features together (iterable tests with other iterable
tests, callable tests with other callable tests), without an artificial
split based on tests which test diagnostics vs tests which test
inference. And it allows a single test to more easily test both
diagnostics and inference. (Ultimately in the test framework, they will
likely all test diagnostics, just in some cases the diagnostics will
come from `reveal_type()`.)
My plan for handling declared types is to introduce a `Declaration` in
addition to `Definition`. A `Declaration` is an annotation of a name
with a type; a `Definition` is an actual runtime assignment of a value
to a name. A few things (an annotated function parameter, an
annotated-assignment with an RHS) are both a `Definition` and a
`Declaration`.
This more cleanly separates type inference (only cares about
`Definition`) from declared types (only impacted by a `Declaration`),
and I think it will work out better than trying to squeeze everything
into `Definition`. One of the tests in this PR
(`annotation_only_assignment_transparent_to_local_inference`)
demonstrates one reason why. The statement `x: int` should have no
effect on local inference of the type of `x`; whatever the locally
inferred type of `x` was before `x: int` should still be the inferred
type after `x: int`. This is actually quite hard to do if `x: int` is
considered a `Definition`, because a core assumption of the use-def map
is that a `Definition` replaces the previous value. To achieve this
would require some hackery to effectively treat `x: int` sort of as if
it were `x: int = x`, but it's not really even equivalent to that, so
this approach gets quite ugly.
As a first step in this plan, this PR stops treating AnnAssign with no
RHS as a `Definition`, which fixes behavior in a couple added tests.
This actually makes things temporarily worse for the ellipsis-type test,
since it is defined in typeshed only using annotated assignments with no
RHS. This will be fixed properly by the upcoming addition of
declarations, which should also treat a declared type as sufficient to
import a name, at least from a stub.
Initially I had deferred annotation name lookups reuse the "public
symbol type", since that gives the correct "from end of scope" view of
reaching definitions that we want. But there is a key difference; public
symbol types are based only on definitions in the queried scope (or
"name in the given namespace" in runtime terms), they don't ever look up
a name in nonlocal/global/builtin scopes. Deferred annotation resolution
should do this lookup.
Add a test, and fix deferred name resolution to support
nonlocal/global/builtin names.
Fixes#13176
## Summary
Part of #13085, this PR updates the comprehension definition to handle
multiple targets.
## Test Plan
Update existing semantic index test case for comprehension with multiple
targets. Running corpus tests shouldn't panic.
Add support for non-local name lookups.
There's one TODO around annotated assignments without a RHS; these need
a fair amount of attention, which they'll get in an upcoming PR about
declared vs inferred types.
Fixes#11663
Test coverage for #13131 wasn't as good as I thought it was, because
although we infer a lot of types in stubs in typeshed, we don't check
typeshed, and therefore we don't do scope-level inference and pull all
types for a scope. So we didn't really have good test coverage for
scope-level inference in a stub. And because of this, I got the code for
supporting that wrong, meaning that if we did scope-level inference with
deferred types, we'd end up never populating the deferred types in the
scope's `TypeInference`, which causes panics like #13160.
Here I both add test coverage by running the corpus tests both as `.py`
and as `.pyi` (which reveals the panic), and I fix the code to support
deferred types in scope inference.
This also revealed a problem with deferred types in generic functions,
which effectively span two scopes. That problem will require a bit more
thought, and I don't want to block this PR on it, so for now I just
don't defer annotations on generic functions.
Fixes#13160.
## Summary
Follow-up to #13147, this PR implements the `AstNode` for `Identifier`.
This makes it easier to create the `NodeKey` in red knot because it uses
a generic method to construct the key from `AnyNodeRef` and is important
for definitions that are created only on identifiers instead of
`ExprName`.
## Test Plan
`cargo test` and `cargo clippy`
## Summary
This PR adds definition for match patterns.
## Test Plan
Update the existing test case for match statement symbols to verify that
the definitions are added as well.
The `UnionBuilder` builds `builtins.bool` when handed `Literal[True]`
and `Literal[False]`.
Caveat: If the builtins module is unfindable somehow, the builder falls
back to the union type of these two literals.
First task from #12694
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Adds basic support for inferring the type resulting from a call
expression. This only works for the *result* of call expressions; it
performs no inference on parameters. It also intentionally does nothing
with class instantiation, `__call__` implementors, or lambdas.
## Test Plan
Adds a test that it infers the right thing!
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
- Introduce methods for inferring annotation and type expressions.
- Correctly infer explicit return types from functions where they are
simple names that can be resolved in scope.
Contributes to #12701 by way of helping unlock call expressions (this
does not remotely finish that, as it stands, but it gets us moving that
direction).
## Test Plan
Added a test for function return types which use the name form of an
annotation expression, since this is aiming toward call expressions.
When we extend this to working for other annotation and type expression
positions, we should add explicit tests for those as well.
---------
Co-authored-by: Alex Waygood <alex.waygood@gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
Prototype deferred evaluation of type expressions by deferring
evaluation of class bases in a stub file. This allows self-referential
class definitions, as occur with the definition of `str` in typeshed
(which inherits `Sequence[str]`).
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Just what it says on the tin: adds basic `EllipsisType` inference for
any time `...` appears in the AST.
## Test Plan
Test that `x = ...` produces exactly what we would expect.
---------
Co-authored-by: Carl Meyer <carl@oddbird.net>
## Summary
The resulting type when multiplying a string literal by an integer
literal is one of two types:
- `StringLiteral`, in the case where it is a reasonably small resulting
string (arbitrarily bounded here to 4096 bytes, roughly a page on many
operating systems), including the fully expanded string.
- `LiteralString`, matching Pyright etc., for strings larger than that.
Additionally:
- Switch to using `Box<str>` instead of `String` for the internal value
of `StringLiteral`, saving some non-trivial byte overhead (and keeping
the total number of allocations the same).
- Be clearer and more accurate about which types we ought to defer to in
`StringLiteral` and `LiteralString` member lookup.
## Test Plan
Added a test case covering multiplication times integers: positive,
negative, zero, and in and out of bounds.
---------
Co-authored-by: Alex Waygood <alex.waygood@gmail.com>
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This fixes the outstanding TODO and make it easier to work with new
cases. (Tidy first, *then* implement, basically!)
## Test Plan
After making this change all the existing tests still pass. A classic
refactor win. 🎉
# Summary
Add support for the first unary operator: negating integer literals. The
resulting type is another integer literal, with the value being the
negated value of the literal. All other types continue to return
`Type::Unknown` for the present, but this is designed to make it easy to
extend easily with other combinations of operator and operand.
Contributes to #12701.
## Test Plan
Add tests with basic negation, including of very large integers and
double negation.
## Summary
Introduce a `StringLiteralType` with corresponding `Display` type and a
relatively basic test that the resulting representation is as expected.
Note: we currently always allocate for `StringLiteral` types. This may
end up being a perf issue later, at which point we may want to look at
other ways of representing `value` here, i.e. with some kind of smarter
string structure which can reuse types. That is most likely to show up
with e.g. concatenation.
Contributes to #12701.
## Test Plan
Added a test for individual strings with both single and double quotes
as well as concatenated strings with both forms.
This PR has the `SemanticIndexBuilder` visit function definition
annotations before adding the function symbol/name to the builder.
For example, the following snippet no longer causes a panic:
```python
def bool(x) -> bool:
Return True
```
Note: This fix changes the ordering of the global symbol table.
Closes#13069
## Summary
This PR adds symbols introduced by `for` loops to red-knot:
- `x` in `for x in range(10): pass`
- `x` and `y` in `for x, y in d.items(): pass`
- `a`, `b`, `c` and `d` in `for [((a,), b), (c, d)] in foo: pass`
## Test Plan
Several tests added, and the assertion in the benchmarks has been
updated.
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
This PR adds the `bytes` type to red-knot:
- Added the `bytes` type
- Added support for bytes literals
- Support for the `+` operator
Improves on #12701
Big TODO on supporting and normalizing r-prefixed bytestrings
(`rb"hello\n"`)
## Test Plan
Added a test for a bytes literals, concatenation, and corner values
The `SemanticIndexBuilder` was causing a cycle in a salsa query by
attempting to resolve the target before the value in a named expression
(e.g. `x := x+1`). This PR swaps the order, avoiding a panic.
Closes#13012.
## Summary
This PR adds symbols and definitions introduced by `with` statements.
The symbols and definitions are introduced for each with item. The type
inference is updated to call the definition region type inference
instead.
## Test Plan
Add test case to check for symbol table and definitions.
## Summary
This PR adds symbols introduced by `match` statements.
There are three patterns that introduces new symbols:
* `as` pattern
* Sequence pattern
* Mapping pattern
The recursive nature of the visitor makes sure that all symbols are
added.
## Test Plan
Add test case for all types of patterns that introduces a symbol.
## Summary
This PR adds definition for augmented assignment. This is similar to
annotated assignment in terms of implementation.
An augmented assignment should also record a use of the variable but
that's a TODO for now.
## Test Plan
Add test case to validate that a definition is added.
Extend the `UseDefMap` to also track which constraints (provided by e.g.
`if` tests) apply to each visible definition.
Uses a custom `BitSet` and `BitSetArray` to track which constraints
apply to which definitions, while keeping data inline as much as
possible.
## Summary
This PR adds support for adding symbols and definitions for function and
lambda parameters to the semantic index.
### Notes
* The default expression of a parameter is evaluated in the enclosing
scope (not the type parameter or function scope).
* The annotation expression of a parameter is evaluated in the type
parameter scope if they're present other in the enclosing scope.
* The symbols and definitions are added in the function parameter scope.
### Type Inference
There are two definitions `Parameter` and `ParameterWithDefault` and
their respective `*_definition` methods on the type inference builder.
These methods are preferred and are re-used when checking from a
different region.
## Test Plan
Add test case for validating that the parameters are defined in the
function / lambda scope.
### Benchmark update
Validated the difference in diagnostics for benchmark code between
`main` and this branch. All of them are either directly or indirectly
referencing one of the function parameters. The diff is in the PR description.
If a builtin is conditionally shadowed by a global, we didn't correctly
fall back to builtins for the not-defined-in-globals path (see added
test for an example.)
## Summary
This PR adds scope and definition for comprehension nodes. This includes
the following nodes:
* List comprehension
* Dictionary comprehension
* Set comprehension
* Generator expression
### Scope
Each expression here adds it's own scope with one caveat - the `iter`
expression of the first generator is part of the parent scope. For
example, in the following code snippet the `iter1` variable is evaluated
in the outer scope.
```py
[x for x in iter1]
```
> The iterable expression in the leftmost for clause is evaluated
directly in the enclosing scope and then passed as an argument to the
implicitly nested scope.
>
> Reference:
https://docs.python.org/3/reference/expressions.html#displays-for-lists-sets-and-dictionaries
There's another special case for assignment expressions:
> There is one special case: an assignment expression occurring in a
list, set or dict comprehension or in a generator expression (below
collectively referred to as “comprehensions”) binds the target in the
containing scope, honoring a nonlocal or global declaration for the
target in that scope, if one exists.
>
> Reference: https://peps.python.org/pep-0572/#scope-of-the-target
For example, in the following code snippet, the variables `a` and `b`
are available after the comprehension while `x` isn't:
```py
[a := 1 for x in range(2) if (b := 2)]
```
### Definition
Each comprehension node adds a single definition, the "target" variable
(`[_ for target in iter]`). This has been accounted for and a new
variant has been added to `DefinitionKind`.
### Type Inference
Currently, type inference is limited to a single scope. It doesn't
_enter_ in another scope to infer the types of the remaining expressions
of a node. To accommodate this, the type inference for a **scope**
requires new methods which _doesn't_ infer the type of the `iter`
expression of the leftmost outer generator (that's defined in the
enclosing scope).
The type inference for the scope region is split into two parts:
* `infer_generator_expression` (similarly for comprehensions) infers the
type of the `iter` expression of the leftmost outer generator
* `infer_generator_expression_scope` (similarly for comprehension)
infers the type of the remaining expressions except for the one
mentioned in the previous point
The type inference for the **definition** also needs to account for this
special case of leftmost generator. This is done by defining a `first`
boolean parameter which indicates whether this comprehension definition
occurs first in the enclosing expression.
## Test Plan
New test cases were added to validate multiple scenarios. Refer to the
documentation for each test case which explains what is being tested.
Make `cargo doc -p red_knot_python_semantic --document-private-items`
run warning-free. I'd still like to do this for all of ruff and start
enforcing it in CI (https://github.com/astral-sh/ruff/issues/12372) but
haven't gotten to it yet. But in the meantime I'm trying to maintain it
for at least `red_knot_python_semantic`, as it helps to ensure our doc
comments stay up to date.
A few of the comments I just removed or shortened, as their continued
relevance wasn't clear to me; please object in review if you think some
of them are important to keep!
Also remove a no-longer-needed `allow` attribute.
For type narrowing, we'll need intersections (since applying type
narrowing is just a type intersection.)
Add `IntersectionBuilder`, along with some tests for it and
`UnionBuilder` (renamed from `UnionTypeBuilder`).
We use smart builders to ensure that we always keep these types in
disjunctive normal form (DNF). That means that we never have deeply
nested trees of unions and intersections: unions flatten into unions,
intersections flatten into intersections, and intersections distribute
over unions, so the most complex tree we can ever have is a union of
intersections. We also never have a single-element union or a
single-positive-element intersection; these both just simplify to the
contained type.
Maintaining these invariants means that `UnionBuilder` doesn't
necessarily end up building a `Type::Union` (e.g. if you only add a
single type to the union, it'll just return that type instead), and
`IntersectionBuilder` doesn't necessarily build a `Type::Intersection`
(if you add a union to the intersection, we distribute the intersection
over that union, and `IntersectionBuilder` will end up returning a
`Type::Union` of intersections).
We also simplify intersections by ensuring that if a type and its
negation are both in an intersection, they simplify out. (In future this
should also respect subtyping, not just type identity, but we don't have
subtyping yet.) We do implement subtyping of `Never` as a special case
for now.
Most of this PR is unused for now until type narrowing lands; I'm just
breaking it out to reduce the review fatigue of a single massive PR.
## Summary
I'm not sure if this is useful but this is a hacky implementation to add
the filename and row / column numbers to the current Red Knot
diagnostics.
I hit this `todo!` trying to run type inference over some real modules.
Since it's a one-liner to implement it, I just did that rather than
changing to `Type::Unknown`.
Now that we have builtins available, resolve some simple cases to the
right builtin type.
We should also adjust the display for types to include their module
name; that's not done yet here.
Extend red-knot type inference to cover all syntax, so that inferring
types for a scope gives all expressions a type. This means we can run
the red-knot semantic lint on all Python code without panics. It also
means we can infer types for `builtins.pyi` without panics.
To keep things simple, this PR intentionally doesn't add any new type
inference capabilities: the expanded coverage is all achieved with
`Type::Unknown`. But this puts the skeleton in place for adding better
inference of all these language features.
I also had to add basic Salsa cycle recovery (with just `Type::Unknown`
for now), because some `builtins.pyi` definitions are cyclic.
To test this, I added a comprehensive corpus of test snippets sourced
from Cinder under [MIT
license](https://github.com/facebookincubator/cinder/blob/cinder/3.10/cinderx/LICENSE),
which matches Ruff's license. I also added to this corpus some
additional snippets for newer language features: all the
`27_func_generic_*` and `73_class_generic_*` files, as well as
`20_lambda_default_arg.py`, and added a test which runs semantic-lint
over all these files. (The test doesn't assert the test-corpus files are
lint-free; just that they are able to lint without a panic.)
Add support for while-loop control flow.
This doesn't yet include general support for terminals and reachability;
that is wider than just while loops and belongs in its own PR.
This also doesn't yet add support for cyclic definitions in loops; that
comes with enough of its own complexity in Salsa that I want to handle
it separately.
Add a lint rule to detect if a name is definitely or possibly undefined
at a given usage.
If I create the file `undef/main.py` with contents:
```python
x = int
def foo():
z
return x
if flag:
y = x
y
```
And then run `cargo run --bin red_knot -- --current-directory
../ruff-examples/undef`, I get the output:
```
Name 'z' used when not defined.
Name 'flag' used when not defined.
Name 'y' used when possibly not defined.
```
If I modify the file to add `y = 0` at the top, red-knot re-checks it
and I get the new output:
```
Name 'z' used when not defined.
Name 'flag' used when not defined.
```
Note that `int` is not flagged, since it's a builtin, and `return x` in
the function scope is not flagged, since it refers to the global `x`.
When poring over traces, the ones that just include a definition or
symbol or expression ID aren't very useful, because you don't know which
file it comes from. This adds that information to the trace.
I guess the downside here is that if calling `.file(db)` on a
scope/definition/expression would execute other traced code, it would be
marked as outside the span? I don't think that's a concern, because I
don't think a simple field access on a tracked struct should ever
execute our code. If I'm wrong and this is a problem, it seems like the
tracing crate has this feature where you can record a field as
`tracing::field::Empty` and then fill in its value later with
`span.record(...)`, but when I tried this it wasn't working for me, not
sure why.
I think there's a lot more we can do to make our tracing output more
useful for debugging (e.g. record an event whenever a
definition/symbol/expression/use id is created with the details of that
definition/symbol/expression/use), this is just dipping my toes in the
water.
Per comments in https://github.com/astral-sh/ruff/pull/12269, "module
global" is kind of long, and arguably redundant.
I tried just using "module" but there were too many cases where I felt
this was ambiguous. I like the way "global" works out better, though it
does require an understanding that in Python "global" generally means
"module global" not "globally global" (though in a sense module globals
are also globally global since modules are singletons).
Support falling back to a global name lookup if a name isn't defined in
the local scope, in the cases where that is correct according to Python
semantics.
In class scopes, a name lookup checks the local namespace first, and if
the name isn't found there, looks it up in globals.
In function scopes (and type parameter scopes, which are function-like),
if a name has any definitions in the local scope, it is a local, and
accessing it when none of those definitions have executed yet just
results in an `UnboundLocalError`, it does not fall back to a global. If
the name does not have any definitions in the local scope, then it is an
implicit global.
Public symbol type lookups never include such a fall back. For example,
if a name is not defined in a class scope, it is not available as a
member on that class, even if a name lookup within the class scope would
have fallen back to a global lookup.
This PR makes the `@override` lint rule work again.
Not yet included/supported in this PR:
* Support for free variables / closures: a free symbol in a nested
function-like scope referring to a symbol in an outer function-like
scope.
* Support for `global` and `nonlocal` statements, which force a symbol
to be treated as global or nonlocal even if it has definitions in the
local scope.
* Module-global lookups should fall back to builtins if the name isn't
found in the module scope.
I would like to expose nicer APIs for the various kinds of symbols
(explicit global, implicit global, free, etc), but this will also wait
for a later PR, when more kinds of symbols are supported.
Adds inference tests sufficient to give full test coverage of the
`UseDefMapBuilder::merge` method.
In the process I realized that we could implement visiting of if
statements in `SemanticBuilder` with fewer `snapshot`, `restore`, and
`merge` operations, so I restructured that visit a bit.
I also found one correctness bug in the `merge` method (it failed to
extend the given snapshot with "unbound" for any missing symbols,
meaning we would just lose the fact that the symbol could be unbound in
the merged-in path), and two efficiency bugs (if one of the ranges to
merge is empty, we can just use the other one, no need for copies, and
if the ranges are overlapping -- which can occur with nested branches --
we can still just merge them with no copies), and fixed all three.
Improve semantic index tests with better assertions than just `.len()`,
and re-add use-definition test that was commented out in the switch to
Salsa initially.
Implements definition-level type inference, with basic control flow
(only if statements and if expressions so far) in Salsa.
There are a couple key ideas here:
1) We can do type inference queries at any of three region
granularities: an entire scope, a single definition, or a single
expression. These are represented by the `InferenceRegion` enum, and the
entry points are the salsa queries `infer_scope_types`,
`infer_definition_types`, and `infer_expression_types`. Generally
per-scope will be used for scopes that we are directly checking and
per-definition will be used anytime we are looking up symbol types from
another module/scope. Per-expression should be uncommon: used only for
the RHS of an unpacking or multi-target assignment (to avoid
re-inferring the RHS once per symbol defined in the assignment) and for
test nodes in type narrowing (e.g. the `test` of an `If` node). All
three queries return a `TypeInference` with a map of types for all
definitions and expressions within their region. If you do e.g.
scope-level inference, when it hits a definition, or an
independently-inferable expression, it should use the relevant query
(which may already be cached) to get all types within the smaller
region. This avoids double-inferring smaller regions, even though larger
regions encompass smaller ones.
2) Instead of building a control-flow graph and lazily traversing it to
find definitions which reach a use of a name (which is O(n^2) in the
worst case), instead semantic indexing builds a use-def map, where every
use of a name knows which definitions can reach that use. We also no
longer track all definitions of a symbol in the symbol itself; instead
the use-def map also records which defs remain visible at the end of the
scope, and considers these the publicly-visible definitions of the
symbol (see below).
Major items left as TODOs in this PR, to be done in follow-up PRs:
1) Free/global references aren't supported yet (only lookup based on
definitions in current scope), which means the override-check example
doesn't currently work. This is the first thing I'll fix as follow-up to
this PR.
2) Control flow outside of if statements and expressions.
3) Type narrowing.
There are also some smaller relevant changes here:
1) Eliminate `Option` in the return type of member lookups; instead
always return `Type::Unbound` for a name we can't find. Also use
`Type::Unbound` for modules we can't resolve (not 100% sure about this
one yet.)
2) Eliminate the use of the terms "public" and "root" to refer to
module-global scope or symbols. Instead consistently use the term
"module-global". It's longer, but it's the clearest, and the most
consistent with typical Python terminology. In particular I don't like
"public" for this use because it has other implications around author
intent (is an underscore-prefixed module-global symbol "public"?). And
"root" is just not commonly used for this in Python.
3) Eliminate the `PublicSymbol` Salsa ingredient. Many non-module-global
symbols can also be seen from other scopes (e.g. by a free var in a
nested scope, or by class attribute access), and thus need to have a
"public type" (that is, the type not as seen from a particular use in
the control flow of the same scope, but the type as seen from some other
scope.) So all symbols need to have a "public type" (here I want to keep
the use of the term "public", unless someone has a better term to
suggest -- since it's "public type of a symbol" and not "public symbol"
the confusion with e.g. initial underscores is less of an issue.) At
least initially, I would like to try not having special handling for
module-global symbols vs other symbols.
4) Switch to using "definitions that reach end of scope" rather than
"all definitions" in determining the public type of a symbol. I'm
convinced that in general this is the right way to go. We may want to
refine this further in future for some free-variable cases, but it can
be changed purely by making changes to the building of the use-def map
(the `public_definitions` index in it), without affecting any other
code. One consequence of combining this with no control-flow support
(just last-definition-wins) is that some inference tests now give more
wrong-looking results; I left TODO comments on these tests to fix them
when control flow is added.
And some potential areas for consideration in the future:
1) Should `symbol_ty` be a Salsa query? This would require making all
symbols a Salsa ingredient, and tracking even more dependencies. But it
would save some repeated reconstruction of unions, for symbols with
multiple public definitions. For now I'm not making it a query, but open
to changing this in future with actual perf evidence that it's better.
Intern types using Salsa interning instead of in the `TypeInference`
result.
This eliminates the need for `TypingContext`, and also paves the way for
finer-grained type inference queries.
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