Currently we only instantiate them with the old CFG library, but in the
future we'll want to do this with the new library as well.
Co-authored-by: yoff <yoff@github.com>
This one is potentially a bit iffy -- it checks for a very powerful
propetry (that implies many of the other queries), but as the test
results show, it can produce false positives when there is in fact no
problem. We may want to get rid of it entirely, if it becomes too noisy.
This looks for nodes annotated with `t.never` in the test that are
reachable in the CFG. This should not happen (it messes with various
queries, e.g. the "mixed returns" query), but the test shows that in a
few particular cases (involving the `match` statement where all cases
contain `return`s), we _do_ have reachable nodes that shouldn't be.
This one demonstrates a bug in the current CFG. In a dictionary
comprehension `{k: v for k, v in d.items()}`, we evaluate the value
before the key, which is incorrect. (A fix for this bug has been
implemented in a separate PR.)
These use the annotated, self-verifying test files to check various
consistency requirements.
Some of these may be expressing the same thing in different ways, but
it's fairly cheap to keep them around, so I have not attempted to
produce a minimal set of queries for this.
These tests consist of various Python constructions (hopefully a
somewhat comprehensive set) with specific timestamp annotations
scattered throughout. When the tests are run using the Python 3
interpreter, these annotations are checked and compared to the "current
timestamp" to see that they are in agreement. This is what makes the
tests "self-validating".
There are a few different kinds of annotations: the basic `t[4]` style
(meaning this is executed at timestamp 4), the `t.dead[4]` variant
(meaning this _would_ happen at timestamp 4, but it is in a dead
branch), and `t.never` (meaning this is never executed at all).
In addition to this, there is a query, MissingAnnotations, which checks
whether we have applied these annotations maximally. Many expression
nodes are not actually annotatable, so there is a sizeable list of
excluded nodes for that query.
We won't be able to run these tests until Python 3.15 is actually out
(and our CI is using it), so it seemed easiest to just put them in their
own test directory.
First, we extend the various location overriding hacks to also accept
list and dict splats in various places. Having done this, we then have
to tackle how to actually desugar these new comprehension forms (as this
is what we currently do for the old forms).
As a reminder, a list comprehension like `[x for x in y]` currently gets
desugared into a small local function, something like
```python
def listcomp(a):
for x in a:
yield x
listcomp(y)
```
For `[*x for x in y]`, the behaviour we want is that we unpack `x`
before yielding its elements in turn. This is essentially what we would
get if we were to use `yield from x` instead of `yield x` in the above
desugaring, so that's what we do. This also works for set
comprehensions.
For dict comprehensions, it's slightly more complicated. Here, the
generator function instead yields a stream of `(key, value)` tuples.
(And apparently the old parser got this wrong and emitted `(value, key)`
pairs instead, which we faithfully recreated in the new parser as well.
We fix that bug in both parsers while we're at it). So, a bare `yield
from` is not enough, we also need a `.items()` call to get the
double-starred expression to emit its items as a stream of tuples (that
we then `yield from`.
To make this (hopefully) less verbose in the implementation, we defer
the decision of whether to use `yield` or `yield from` by introducing a
`yield_kind` scoped variable that determines the type of the actual AST
node. And of course for dict comprehensions with unpacking we need to
synthesise the extra machinery mentioned above.
On the plus side, this means we don't have to mess with control-flow, as
the existing machinery should be able to handle the desugared syntax
just fine.
Adds a new `isLazy` predicate to the relevant classes, and adds the
relevant dbscheme (and up/downgrade) changes. On upgrades we do nothing,
and on downgrades we remove the `is_lazy` bits.
As defined in PEP-810. We implement this in much the same way as how we
handle `async` annotations currently. The relevant nodes get an
`is_lazy` field that defaults to being false.
This allows us to build and test the extractor (for actual QL extraction
-- not just the extractor unit tests) entirely from within the
`github/codeql` repo, just as we do with Ruby. All that's needed is a
`--search-path` argument that points to the repo root.
