PyMutex is a one byte lock with fast, inlineable lock and unlock functions for the common uncontended case. The design is based on WebKit's WTF::Lock.
PyMutex is built using the _PyParkingLot APIs, which provides a cross-platform futex-like API (based on WebKit's WTF::ParkingLot). This internal API will be used for building other synchronization primitives used to implement PEP 703, such as one-time initialization and events.
This also includes tests and a mini benchmark in Tools/lockbench/lockbench.py to compare with the existing PyThread_type_lock.
Uncontended acquisition + release:
* Linux (x86-64): PyMutex: 11 ns, PyThread_type_lock: 44 ns
* macOS (arm64): PyMutex: 13 ns, PyThread_type_lock: 18 ns
* Windows (x86-64): PyMutex: 13 ns, PyThread_type_lock: 38 ns
PR Overview:
The primary purpose of this PR is to implement PyMutex, but there are a number of support pieces (described below).
* PyMutex: A 1-byte lock that doesn't require memory allocation to initialize and is generally faster than the existing PyThread_type_lock. The API is internal only for now.
* _PyParking_Lot: A futex-like API based on the API of the same name in WebKit. Used to implement PyMutex.
* _PyRawMutex: A word sized lock used to implement _PyParking_Lot.
* PyEvent: A one time event. This was used a bunch in the "nogil" fork and is useful for testing the PyMutex implementation, so I've included it as part of the PR.
* pycore_llist.h: Defines common operations on doubly-linked list. Not strictly necessary (could do the list operations manually), but they come up frequently in the "nogil" fork. ( Similar to https://man.freebsd.org/cgi/man.cgi?queue)
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Co-authored-by: Eric Snow <ericsnowcurrently@gmail.com>
There is a WIP proposal to enable webassembly stack switching which have been
implemented in v8:
https://github.com/WebAssembly/js-promise-integration
It is not possible to switch stacks that contain JS frames so the Emscripten JS
trampolines that allow calling functions with the wrong number of arguments
don't work in this case. However, the js-promise-integration proposal requires
the [type reflection for Wasm/JS API](https://github.com/WebAssembly/js-types)
proposal, which allows us to actually count the number of arguments a function
expects.
For better compatibility with stack switching, this PR checks if type reflection
is available, and if so we use a switch block to decide the appropriate
signature. If type reflection is unavailable, we should use the current EMJS
trampoline.
We cache the function argument counts since when I didn't cache them performance
was negatively affected.
Co-authored-by: T. Wouters <thomas@python.org>
Co-authored-by: Brett Cannon <brett@python.org>
Fix _thread.start_new_thread() race condition. If a thread is created
during Python finalization, the newly spawned thread now exits
immediately instead of trying to access freed memory and lead to a
crash.
thread_run() calls PyEval_AcquireThread() which checks if the thread
must exit. The problem was that tstate was dereferenced earlier in
_PyThreadState_Bind() which leads to a crash most of the time.
Move _PyThreadState_CheckConsistency() from thread_run() to
_PyThreadState_Bind().
thread_run() of _threadmodule.c now calls
_PyThreadState_CheckConsistency() to check if tstate is a dangling
pointer when Python is built in debug mode.
Rename ceval_gil.c is_tstate_valid() to
_PyThreadState_CheckConsistency() to reuse it in _threadmodule.c.
Symbols of the C API should be prefixed by "Py_" to avoid conflict
with existing names in 3rd party C extensions on "#include <Python.h>".
test.pythoninfo now logs Py_C_RECURSION_LIMIT constant and other
_testcapi and _testinternalcapi constants.
pycore_create_interpreter() now returns a status, rather than
calling Py_FatalError().
* PyInterpreterState_New() now calls Py_ExitStatusException() instead
of calling Py_FatalError() directly.
* Replace Py_FatalError() with PyStatus in init_interpreter() and
_PyObject_InitState().
* _PyErr_SetFromPyStatus() now raises RuntimeError, instead of
ValueError. It can now call PyErr_NoMemory(), raise MemoryError,
if it detects _PyStatus_NO_MEMORY() error message.
Python built with "configure --with-trace-refs" (tracing references)
is now ABI compatible with Python release build and debug build.
Moreover, it now also supports the Limited API.
Change Py_TRACE_REFS build:
* Remove _PyObject_EXTRA_INIT macro.
* The PyObject structure no longer has two extra members (_ob_prev
and _ob_next).
* Use a hash table (_Py_hashtable_t) to trace references (all
objects): PyInterpreterState.object_state.refchain.
* Py_TRACE_REFS build is now ABI compatible with release build and
debug build.
* Limited C API extensions can now be built with Py_TRACE_REFS:
xxlimited, xxlimited_35, _testclinic_limited.
* No longer rename PyModule_Create2() and PyModule_FromDefAndSpec2()
functions to PyModule_Create2TraceRefs() and
PyModule_FromDefAndSpec2TraceRefs().
* _Py_PrintReferenceAddresses() is now called before
finalize_interp_delete() which deletes the refchain hash table.
* test_tracemalloc find_trace() now also filters by size to ignore
the memory allocated by _PyRefchain_Trace().
Test changes for Py_TRACE_REFS:
* Add test.support.Py_TRACE_REFS constant.
* Add test_sys.test_getobjects() to test sys.getobjects() function.
* test_exceptions skips test_recursion_normalizing_with_no_memory()
and test_memory_error_in_PyErr_PrintEx() if Python is built with
Py_TRACE_REFS.
* test_repl skips test_no_memory().
* test_capi skisp test_set_nomemory().
This fixes a crasher due to a race condition, triggered infrequently when two isolated (own GIL) subinterpreters simultaneously initialize their sys or builtins modules. The crash happened due the combination of the "detached" thread state we were using and the "last holder" logic we use for the GIL. It turns out it's tricky to use the same thread state for different threads. Who could have guessed?
We solve the problem by eliminating the one object we were still sharing between interpreters. We replace it with a low-level hashtable, using the "raw" allocator to avoid tying it to the main interpreter.
We also remove the accommodations for "detached" thread states, which were a dubious idea to start with.
The _xxsubinterpreters module should not rely on internal API. Some of the functions it uses were recently moved there however. Here we move them back (and expose them properly).
Rename private C API constants:
* Rename PY_MONITORING_UNGROUPED_EVENTS to _PY_MONITORING_UNGROUPED_EVENTS
* Rename PY_MONITORING_EVENTS to _PY_MONITORING_EVENTS
Remove private _PyThreadState and _PyInterpreterState C API
functions: move them to the internal C API (pycore_pystate.h and
pycore_interp.h). Don't export most of these functions anymore, but
still export functions used by tests.
Remove _PyThreadState_Prealloc() and _PyThreadState_Init() from the C
API, but keep it in the stable API.
* Replace PyWeakref_GET_OBJECT() with _PyWeakref_GET_REF().
* _sqlite/blob.c now holds a strong reference to the blob object
while calling close_blob().
* _xidregistry_find_type() now holds a strong reference to registered
while using it.
* Add table describing possible executable classes for out-of-process debuggers.
* Remove shim code object creation code as it is no longer needed.
* Make lltrace a bit more robust w.r.t. non-standard frames.
For a while now, pending calls only run in the main thread (in the main interpreter). This PR changes things to allow any thread run a pending call, unless the pending call was explicitly added for the main thread to run.
The risk of a race with this state is relatively low, but we play it safe anyway. We do avoid using the lock in performance-sensitive cases where the risk of a race is very, very low.
This avoids the problematic race in drop_gil() by skipping the FORCE_SWITCHING code there for finalizing threads.
(The idea for this approach came out of discussions with @markshannon.)
This is the culmination of PEP 684 (and of my 8-year long multi-core Python project)!
Each subinterpreter may now be created with its own GIL (via Py_NewInterpreterFromConfig()). If not so configured then the interpreter will share with the main interpreter--the status quo since subinterpreters were added decades ago. The main interpreter always has its own GIL and subinterpreters from Py_NewInterpreter() will always share with the main interpreter.
In preparation for a per-interpreter GIL, we add PyInterpreterState.ceval.gil, set it to the shared GIL for each interpreter, and use that rather than using _PyRuntime.ceval.gil directly. Note that _PyRuntime.ceval.gil is still the actual GIL.
This function no longer makes sense, since its runtime parameter is
no longer used. Use directly _PyThreadState_GET() and
_PyInterpreterState_GET() instead.
This is strictly about moving the "obmalloc" runtime state from
`_PyRuntimeState` to `PyInterpreterState`. Doing so improves isolation
between interpreters, specifically most of the memory (incl. objects)
allocated for each interpreter's use. This is important for a
per-interpreter GIL, but such isolation is valuable even without it.
FWIW, a per-interpreter obmalloc is the proverbial
canary-in-the-coalmine when it comes to the isolation of objects between
interpreters. Any object that leaks (unintentionally) to another
interpreter is highly likely to cause a crash (on debug builds at
least). That's a useful thing to know, relative to interpreter
isolation.
We replace _PyRuntime.tstate_current with a thread-local variable. As part of this change, we add a _Py_thread_local macro in pyport.h (only for the core runtime) to smooth out the compiler differences. The main motivation here is in support of a per-interpreter GIL, but this change also provides some performance improvement opportunities.
Note that we do not provide a fallback to the thread-local, either falling back to the old tstate_current or to thread-specific storage (PyThread_tss_*()). If that proves problematic then we can circle back. I consider it unlikely, but will run the buildbots to double-check.
Also note that this does not change any of the code related to the GILState API, where it uses a thread state stored in thread-specific storage. I suspect we can combine that with _Py_tss_tstate (from here). However, that can be addressed separately and is not urgent (nor critical).
(While this change was mostly done independently, I did take some inspiration from earlier (~2020) work by @markshannon (main...markshannon:threadstate_in_tls) and @vstinner (#23976).)
* The majority of the monitoring code is in instrumentation.c
* The new instrumentation bytecodes are in bytecodes.c
* legacy_tracing.c adapts the new API to the old sys.setrace and sys.setprofile APIs
Sharing mutable (or non-immortal) objects between interpreters is generally not safe. We can work around that but not easily.
There are two restrictions that are critical for objects that break interpreter isolation.
The first is that the object's state be guarded by a global lock. For now the GIL meets this requirement, but a granular global lock is needed once we have a per-interpreter GIL.
The second restriction is that the object (and, for a container, its items) be deallocated/resized only when the interpreter in which it was allocated is the current one. This is because every interpreter has (or will have, see gh-101660) its own object allocator. Deallocating an object with a different allocator can cause crashes.
The dict for the cache of module defs is completely internal, which simplifies what we have to do to meet those requirements. To do so, we do the following:
* add a mechanism for re-using a temporary thread state tied to the main interpreter in an arbitrary thread
* add _PyRuntime.imports.extensions.main_tstate`
* add _PyThreadState_InitDetached() and _PyThreadState_ClearDetached() (pystate.c)
* add _PyThreadState_BindDetached() and _PyThreadState_UnbindDetached() (pystate.c)
* make sure the cache dict (_PyRuntime.imports.extensions.dict) and its items are all owned by the main interpreter)
* add a placeholder using for a granular global lock
Note that the cache is only used for legacy extension modules and not for multi-phase init modules.
https://github.com/python/cpython/issues/100227
This reverts commit 87be8d9.
This approach to keeping the interned strings safe is turning out to be too complex for my taste (due to obmalloc isolation). For now I'm going with the simpler solution, making the dict per-interpreter. We can revisit that later if we want a sharing solution.
This is effectively two changes. The first (the bulk of the change) is where we add _Py_AddToGlobalDict() (and _PyRuntime.cached_objects.main_tstate, etc.). The second (much smaller) change is where we update PyUnicode_InternInPlace() to use _Py_AddToGlobalDict() instead of calling PyDict_SetDefault() directly.
Basically, _Py_AddToGlobalDict() is a wrapper around PyDict_SetDefault() that should be used whenever we need to add a value to a runtime-global dict object (in the few cases where we are leaving the container global rather than moving it to PyInterpreterState, e.g. the interned strings dict). _Py_AddToGlobalDict() does all the necessary work to make sure the target global dict is shared safely between isolated interpreters. This is especially important as we move the obmalloc state to each interpreter (gh-101660), as well as, potentially, the GIL (PEP 684).
https://github.com/python/cpython/issues/100227
Moving it valuable with a per-interpreter GIL. However, it is also useful without one, since it allows us to identify refleaks within a single interpreter or where references are escaping an interpreter. This becomes more important as we move the obmalloc state to PyInterpreterState.
https://github.com/python/cpython/issues/102304
The essentially eliminates the global variable, with the associated benefits. This is also a precursor to isolating this bit of state to PyInterpreterState.
Folks that currently read _Py_RefTotal directly would have to start using _Py_GetGlobalRefTotal() instead.
https://github.com/python/cpython/issues/102304
It doesn't make sense to use multi-phase init for these modules. Using a per-interpreter "m_copy" (instead of PyModuleDef.m_base.m_copy) makes this work okay. (This came up while working on gh-101660.)
Note that we might instead end up disallowing re-load for sys/builtins since they are so special.
https://github.com/python/cpython/issues/102660
This change is almost entirely moving code around and hiding import state behind internal API. We introduce no changes to behavior, nor to non-internal API. (Since there was already going to be a lot of churn, I took this as an opportunity to re-organize import.c into topically-grouped sections of code.) The motivation is to simplify a number of upcoming changes.
Specific changes:
* move existing import-related code to import.c, wherever possible
* add internal API for interacting with import state (both global and per-interpreter)
* use only API outside of import.c (to limit churn there when changing the location, etc.)
* consolidate the import-related state of PyInterpreterState into a single struct field (this changes layout slightly)
* add macros for import state in import.c (to simplify changing the location)
* group code in import.c into sections
*remove _PyState_AddModule()
https://github.com/python/cpython/issues/101758
* Make sure that the current exception is always normalized.
* Remove redundant type and traceback fields for the current exception.
* Add new API functions: PyErr_GetRaisedException, PyErr_SetRaisedException
* Add new API functions: PyException_GetArgs, PyException_SetArgs
The GILState API (PEP 311) implementation from 2003 made the assumption that only one thread state would ever be used for any given OS thread, explicitly disregarding the case of subinterpreters. However, PyThreadState_Swap() still facilitated switching between subinterpreters, meaning the "current" thread state (holding the GIL), and the GILState thread state could end up out of sync, causing problems (including crashes).
This change addresses the issue by keeping the two in sync in PyThreadState_Swap(). I verified the fix against gh-99040.
Note that the other GILState-subinterpreter incompatibility (with autoInterpreterState) is not resolved here.
https://github.com/python/cpython/issues/59956
Eric Snow
Sam Gross
Hood Chatham
Victor Stinner
Mark Shannon
Irit Katriel
Kumar Aditya