Modifies the behavior of the interpreter on crash under Emscripten:
1. No Python traceback shown on segfault/trap
2. The JavaScript source line is shown
The JavaScript source line is super long and completely unenlightening,
whereas the Python traceback is very helpful.
Add free-threaded versions of existing specialization for FOR_ITER (list, tuples, fast range iterators and generators), without significantly affecting their thread-safety. (Iterating over shared lists/tuples/ranges should be fine like before. Reusing iterators between threads is not fine, like before. Sharing generators between threads is a recipe for significant crashes, like before.)
The PyThreadState field gains a reference count field to avoid
issues with PyThreadState being a dangling pointer to freed memory.
The refcount starts with a value of two: one reference is owned by the
interpreter's linked list of thread states and one reference is owned by
the OS thread. The reference count is decremented when the thread state
is removed from the interpreter's linked list and before the OS thread
calls `PyThread_hang_thread()`. The thread that decrements it to zero
frees the `PyThreadState` memory.
The `holds_gil` field is moved out of the `_status` bit field, to avoid
a data race where on thread calls `PyThreadState_Clear()`, modifying the
`_status` bit field while the OS thread reads `holds_gil` when
attempting to acquire the GIL.
The `PyThreadState.state` field now has `_Py_THREAD_SHUTTING_DOWN` as a
possible value. This corresponds to the `_PyThreadState_MustExit()`
check. This avoids race conditions in the free threading build when
checking `_PyThreadState_MustExit()`.
* Fix use after free in list objects
Set the items pointer in the list object to NULL after the items array
is freed during list deallocation. Otherwise, we can end up with a list
object added to the free list that contains a pointer to an already-freed
items array.
* Mark `_PyList_FromStackRefStealOnSuccess` as escaping
I think technically it's not escaping, because the only object that
can be decrefed if allocation fails is an exact list, which cannot
execute arbitrary code when it is destroyed. However, this seems less
intrusive than trying to special cases objects in the assert in `_Py_Dealloc`
that checks for non-null stackpointers and shouldn't matter for performance.
Avoid a data race in free-threaded builds due to mutating global arrays at
runtime. Instead, compute the constants with an external Python script and
then define them as static global constant arrays. These constants are
used by `long_from_non_binary_base()`.
* Combine _GUARD_GLOBALS_VERSION_PUSH_KEYS and _LOAD_GLOBAL_MODULE_FROM_KEYS into _LOAD_GLOBAL_MODULE
* Combine _GUARD_BUILTINS_VERSION_PUSH_KEYS and _LOAD_GLOBAL_BUILTINS_FROM_KEYS into _LOAD_GLOBAL_BUILTINS
* Combine _CHECK_ATTR_MODULE_PUSH_KEYS and _LOAD_ATTR_MODULE_FROM_KEYS into _LOAD_ATTR_MODULE
* Remove stack transient in LOAD_ATTR_WITH_HINT
The race condition with `free_threadstate` and daemon threads exists in
both the free threading and default builds. We were missing a
suppression in the default build.
* Implement C recursion protection with limit pointers for Linux, MacOS and Windows
* Remove calls to PyOS_CheckStack
* Add stack protection to parser
* Make tests more robust to low stacks
* Improve error messages for stack overflow
Revert "GH-91079: Implement C stack limits using addresses, not counters. (GH-130007)" for now
Unfortunatlely, the change broke some buildbots.
This reverts commit 2498c22fa0.
CPython current temporarily changes `PYMEM_DOMAIN_RAW` to the default
allocator during initialization and shutdown. The motivation is to
ensure that core runtime structures are allocated and freed using the
same allocator. However, modifying the current allocator changes global
state and is not thread-safe even with the GIL. Other threads may be
allocating or freeing objects use PYMEM_DOMAIN_RAW; they are not
required to hold the GIL to call PyMem_RawMalloc/PyMem_RawFree.
This adds new internal-only functions like `_PyMem_DefaultRawMalloc`
that aren't affected by calls to `PyMem_SetAllocator()`, so they're
appropriate for Python runtime initialization and finalization. Use
these calls in places where we previously swapped to the default raw
allocator.
* Implement C recursion protection with limit pointers
* Remove calls to PyOS_CheckStack
* Add stack protection to parser
* Make tests more robust to low stacks
* Improve error messages for stack overflow
Make tuple iteration more thread-safe, and actually test concurrent iteration of tuple, range and list. (This is prep work for enabling specialization of FOR_ITER in free-threaded builds.) The basic premise is:
Iterating over a shared iterable (list, tuple or range) should be safe, not involve data races, and behave like iteration normally does.
Using a shared iterator should not crash or involve data races, and should only produce items regular iteration would produce. It is not guaranteed to produce all items, or produce each item only once. (This is not the case for range iteration even after this PR.)
Providing stronger guarantees is possible for some of these iterators, but it's not always straight-forward and can significantly hamper the common case. Since iterators in general aren't shared between threads, and it's simply impossible to concurrently use many iterators (like generators), better to make sharing iterators without explicit synchronization clearly wrong.
Specific issues fixed in order to make the tests pass:
- List iteration could occasionally fail an assertion when a shared list was shrunk and an item past the new end was retrieved concurrently. There's still some unsafety when deleting/inserting multiple items through for example slice assignment, which uses memmove/memcpy.
- Tuple iteration could occasionally crash when the iterator's reference to the tuple was cleared on exhaustion. Like with list iteration, in free-threaded builds we can't safely and efficiently clear the iterator's reference to the iterable (doing it safely would mean extra, slow refcount operations), so just keep the iterable reference around.
Use an atomic operation when setting
`_PyRuntime.signals.unhandled_keyboard_interrupt`. We now only clear the
variable at the start of `_PyRun_Main`, which is the same function where
we check it.
This avoids race conditions where previously another thread might call
`run_eval_code_obj()` and erroneously clear the unhandled keyboard
interrupt.
Fix a few thread-safety bugs to enable test_opcache when run with TSAN:
* Use relaxed atomics when clearing `ht->_spec_cache.getitem`
(gh-115999)
* Add temporary suppression for type slot modifications (gh-127266)
* Use atomic load when reading `*dictptr`
