Use a `_PyStackRef` and defer the reference to `f_executable` when
possible. This avoids some reference count contention in the common case
of executing the same code object from multiple threads concurrently in
the free-threaded build.
In gh-121602, I applied a fix to a builtin types initialization bug.
That fix made sense in the context of some broader future changes,
but introduced a little bit of extra complexity. That fix has turned
out to be incomplete for some of the builtin types we haven't
been testing. I found that out while improving the tests.
A while back, @markshannon suggested a simpler fix that doesn't
have that problem, which I've already applied to 3.12 and 3.13.
I'm switching to that here. Given the potential long-term
benefits of the more complex (but still incomplete) approach,
I'll circle back to it in the future, particularly after I've improved
the tests so no corner cases slip through the cracks.
(This is effectively a "forward-port" of 716c677 from 3.13.)
Add PyConfig_Get(), PyConfig_GetInt(), PyConfig_Set() and
PyConfig_Names() functions to get and set the current runtime Python
configuration.
Add visibility and "sys spec" to config and preconfig specifications.
_PyConfig_AsDict() now converts PyConfig.xoptions as a dictionary.
Co-authored-by: Bénédikt Tran <10796600+picnixz@users.noreply.github.com>
Switch more _Py_IsImmortal(...) assertions to _Py_IsImmortalLoose(...)
The remaining calls to _Py_IsImmortal are in free-threaded-only code,
initialization of core objects, tests, and guards that fall back to
code that works with mortal objects.
The `zip_next` function uses a common optimization technique for methods
that generate tuples. The iterator maintains an internal reference to
the returned tuple. When the method is called again, it checks if the
internal tuple's reference count is 1. If so, the tuple can be reused.
However, this approach is not safe under the free-threading build:
after checking the reference count, another thread may perform the same
check and also reuse the tuple. This can result in a double decref on
the items of the replaced tuple and a double incref (memory leak) on
the items of the tuple being set.
This adds a function, `_PyObject_IsUniquelyReferenced` that
encapsulates the stricter logic necessary for the free-threaded build:
the internal tuple must be owned by the current thread, have a local
refcount of one, and a shared refcount of zero.
`Py_DECREF` and `PyStackRef_CLOSE` are now implemented as macros in the
free-threaded build in ceval.c. There are two motivations;
* MSVC has problems inlining functions in ceval.c in the PGO build.
* We will want to mark escaping calls in order to spill the stack
pointer in ceval.c and we will want to do this around `_Py_Dealloc`
(or `_Py_MergeZeroLocalRefcount` or `_Py_DecRefShared`), not around
the entire `Py_DECREF` or `PyStackRef_CLOSE` call.
The free-threaded GC now visits interpreter stacks to keep objects
that use deferred reference counting alive.
Interpreter frames are zero initialized in the free-threaded GC so
that the GC doesn't see garbage data. This is a temporary measure
until stack spilling around escaping calls is implemented.
Co-authored-by: Ken Jin <kenjin@python.org>
As of 529a160 (gh-118204), building with HAVE_DYNAMIC_LOADING stopped working. This is a minimal fix just to get builds working again. There are actually a number of long-standing deficiencies with HAVE_DYNAMIC_LOADING builds that need to be resolved separately.
There were a still a number of gaps in the tests, including not looking
at all the builtin types and not checking wrappers in subinterpreters
that weren't in the main interpreter. This fixes all that.
I considered incorporating the names of the PyTypeObject fields
(a la gh-122866), but figured doing so doesn't add much value.
This replaces `_PyList_FromArraySteal` with `_PyList_FromStackRefSteal`.
It's functionally equivalent, but takes a `_PyStackRef` array instead of
an array of `PyObject` pointers.
Co-authored-by: Ken Jin <kenjin@python.org>
The free-threaded build partially stores heap type reference counts in
distributed manner in per-thread arrays. This avoids reference count
contention when creating or destroying instances.
Co-authored-by: Ken Jin <kenjin@python.org>
Victor Stinner
Irit Katriel
Ken Jin
Sam Gross
Eric Snow
Petr Viktorin
Matt Wozniski
Serhiy Storchaka
Pieter Eendebak
Mark Shannon
Pablo Galindo Salgado
Michael Droettboom
Brandt Bucher
Lysandros Nikolaou
Jelle Zijlstra