This approach eliminates the originally reported race. It also gets rid of the deadlock reported in gh-96071, so we can remove the workaround added then.
* Mark almost all reachable objects before doing collection phase
* Add stats for objects marked
* Visit new frames before each increment
* Remove lazy dict tracking
* Update docs
* Clearer calculation of work to do.
* Document that slices can be marshalled
* Deduplicate and organize the list of supported types
in docs
* Organize the type code list in marshal.c, to make
it more obvious that this is a versioned format
* Back-fill some historical info
Co-authored-by: Michael Droettboom <mdboom@gmail.com>
The PyMutex implementation supports unlocking after fork because we
clear the list of waiters in parking_lot.c. This doesn't work as well
for _PyRecursiveMutex because on some systems, such as SerenityOS, the
thread id is not preserved across fork().
These changes makes it easier to backport the _interpreters, _interpqueues, and _interpchannels modules to Python 3.12.
This involves the following:
* add the _PyXI_GET_STATE() and _PyXI_GET_GLOBAL_STATE() macros
* add _PyXIData_lookup_context_t and _PyXIData_GetLookupContext()
* add _Py_xi_state_init() and _Py_xi_state_fini()
These changes makes it easier to backport the _interpreters, _interpqueues, and _interpchannels modules to Python 3.12.
This involves the following:
* rename several structs and typedefs
* add several typedefs
* stop using the PyThreadState.state field directly in parking_lot.c
Move creation of a tuple for var-positional parameter out of
_PyArg_UnpackKeywordsWithVararg().
Merge _PyArg_UnpackKeywordsWithVararg() with _PyArg_UnpackKeywords().
Add a new parameter in _PyArg_UnpackKeywords().
The "parameters" and "converters" attributes of ParseArgsCodeGen no
longer contain the var-positional parameter. It is now available as the
"varpos" attribute. Optimize code generation for var-positional
parameter and reuse the same generating code for functions with and without
keyword parameters.
Add special converters for var-positional parameter. "tuple" represents it as
a Python tuple and "array" represents it as a continuous array of PyObject*.
"object" is a temporary alias of "tuple".
The primary objective here is to allow some later changes to be cleaner. Mostly this involves renaming things and moving a few things around.
* CrossInterpreterData -> XIData
* crossinterpdatafunc -> xidatafunc
* split out pycore_crossinterp_data_registry.h
* add _PyXIData_lookup_t
Introduce helpers for (un)specializing instructions
Consolidate the code to specialize/unspecialize instructions into
two helper functions and use them in `_Py_Specialize_BinaryOp`.
The resulting code is more concise and keeps all of the logic at
the point where we decide to specialize/unspecialize an instruction.
- The specialization logic determines the appropriate specialization using only the operand's type, which is safe to read non-atomically (changing it requires stopping the world). We are guaranteed that the type will not change in between when it is checked and when we specialize the bytecode because the types involved are immutable (you cannot assign to `__class__` for exact instances of `dict`, `set`, or `frozenset`). The bytecode is mutated atomically using helpers.
- The specialized instructions rely on the operand type not changing in between the `DEOPT_IF` checks and the calls to the appropriate type-specific helpers (e.g. `_PySet_Contains`). This is a correctness requirement in the default builds and there are no changes to the opcodes in the free-threaded builds that would invalidate this.
Each thread specializes a thread-local copy of the bytecode, created on the first RESUME, in free-threaded builds. All copies of the bytecode for a code object are stored in the co_tlbc array on the code object. Threads reserve a globally unique index identifying its copy of the bytecode in all co_tlbc arrays at thread creation and release the index at thread destruction. The first entry in every co_tlbc array always points to the "main" copy of the bytecode that is stored at the end of the code object. This ensures that no bytecode is copied for programs that do not use threads.
Thread-local bytecode can be disabled at runtime by providing either -X tlbc=0 or PYTHON_TLBC=0. Disabling thread-local bytecode also disables specialization.
Concurrent modifications to the bytecode made by the specializing interpreter and instrumentation use atomics, with specialization taking care not to overwrite an instruction that was instrumented concurrently.
* Fix comprehensions comment to inlined by pep 709
* Update spacing
Co-authored-by: RUANG (James Roy) <longjinyii@outlook.com>
* Add reference to PEP 709
---------
Co-authored-by: Carol Willing <carolcode@willingconsulting.com>
Co-authored-by: RUANG (James Roy) <longjinyii@outlook.com>
Temporarily ignore warnings about JIT deactivation when perf support is active.
This will be reverted as soon as a way is found to determine at run time whether the interpreter was built with JIT. Currently, this is not possible on Windows.
Co-authored-by: Kirill Podoprigora <kirill.bast9@mail.ru>
Co-authored-by: Ken Jin <28750310+Fidget-Spinner@users.noreply.github.com>
Co-authored-by: Pablo Galindo <pablogsal@gmail.com>
Previously, if the `ast.AST._fields` attribute was deleted, attempts to create a new `as`t node would crash due to the assumption that `_fields` always had a non-NULL value. Now it has been fixed by adding an extra check to ensure that `_fields` does not have a NULL value (this can happen when you manually remove `_fields` attribute).
Brandt Bucher
Eric Snow
Mark Shannon
Pablo Galindo Salgado
Hugo van Kemenade
Petr Viktorin
Peter Bierma
Sergey B Kirpichev
Yuxuan Zhang
Sam Gross
Daehee Kim
Diego Russo
Ken Jin
Xuanteng Huang
Serhiy Storchaka
Valery Fedorenko
Bénédikt Tran
Aditya Borikar
Kirill Podoprigora
mpage
Donghee Na
Savannah Ostrowski
Nice Zombies
rimchoi
Brian Schubert
Tomas R.
sobolevn