When inheriting a heap subclass from a vectorcall class that sets
`.tp_call=PyVectorcall_Call` (as recommended in PEP 590), the subclass does
not inherit `_Py_TPFLAGS_HAVE_VECTORCALL`, and thus `PyVectorcall_Call` does
not work for it.
This attempts to solve the issue by:
* always inheriting `tp_vectorcall_offset` unless `tp_call` is overridden
in the subclass
* inheriting _Py_TPFLAGS_HAVE_VECTORCALL for static types, unless `tp_call`
is overridden
* making `PyVectorcall_Call` ignore `_Py_TPFLAGS_HAVE_VECTORCALL`
This means it'll be ever more important to only call `PyVectorcall_Call`
on classes that support vectorcall. In `PyVectorcall_Call`'s intended role
as `tp_call` filler, that's not a problem.
This adds a vector of "search fingers" so that usable_arenas can be kept in sorted order (by number of free pools) via constant-time operations instead of linear search.
This should reduce worst-case time for reclaiming a great many objects from O(A**2) to O(A), where A is the number of arenas. See bpo-37029.
It is now allowed to add new fields at the end of the PyTypeObject struct without having to allocate a dedicated compatibility flag in tp_flags.
This will reduce the risk of running out of bits in the 32-bit tp_flags value.
* bpo-22385: Support output separators in hex methods.
Also in binascii.hexlify aka b2a_hex.
The underlying implementation behind all hex generation in CPython uses the
same pystrhex.c implementation. This adds support to bytes, bytearray,
and memoryview objects.
The binascii module functions exist rather than being slated for deprecation
because they return bytes rather than requiring an intermediate step through a
str object.
This change was inspired by MicroPython which supports sep in its binascii
implementation (and does not yet support the .hex methods).
https://bugs.python.org/issue22385
* No type cache for types with specialized mro, invalidation is hard.
* FIX: Don't disable method cache custom types that do not implement mro().
* fixing implem.
* Avoid storing error flags, also decref.
* news entry
* Clear as soon as we're getting an error.
* FIX: Reference leak.
Update PyObject_CallMethodObjArgs and _PyObject_CallMethodIdObjArgs
to use _PyObject_GetMethod to avoid creating a bound method object
in many cases.
On a microbenchmark of PyObject_CallMethodObjArgs calling a method on
an interpreted Python class, this optimization resulted in a 1.7x
speedup.
…nctions with asserts
The actual overflow can never happen because of the following:
* The size of a list can't be greater than PY_SSIZE_T_MAX / sizeof(PyObject*).
* The size of a pointer on all supported plaftorms is at least 4 bytes.
* ofs is positive and less than the list size at the beginning of each iteration.
https://bugs.python.org/issue35091
* Add _PyInitError functions:
* _PyInitError_Ok()
* _PyInitError_Error()
* _PyInitError_NoMemory()
* _PyInitError_Exit()
* _PyInitError_IsError()
* _PyInitError_IsExit()
* _PyInitError_Failed()
* frozenmain.c and _testembed.c now use functions rather than macros.
* Move _Py_INIT_xxx() macros to the internal API.
* Move _PyWstrList_INIT macro to the internal API.
* Add PyMemAllocatorName enum
* _PyPreConfig.allocator type becomes PyMemAllocatorName, instead of
char*
* Remove _PyPreConfig_Clear()
* Add _PyMem_GetAllocatorName()
* Rename _PyMem_GetAllocatorsName() to
_PyMem_GetCurrentAllocatorName()
* Remove _PyPreConfig_SetAllocator(): just call
_PyMem_SetupAllocators() directly, we don't have do reallocate the
configuration with the new allocator anymore!
* _PyPreConfig_Write() parameter becomes const, as it should be in
the first place!
The final addition (cur += step) may overflow, so use size_t for "cur".
"cur" is always positive (even for negative steps), so it is safe to use
size_t here.
Co-Authored-By: Martin Panter <vadmium+py@gmail.com>
Add new trashcan macros to deal with a double deallocation that could occur when the `tp_dealloc` of a subclass calls the `tp_dealloc` of a base class and that base class uses the trashcan mechanism.
Patch by Jeroen Demeyer.