* Eliminate all remaining uses of Py_SIZE and Py_SET_SIZE on PyLongObject, adding asserts.
* Change layout of size/sign bits in longobject to support future addition of immortal ints and tagged medium ints.
* Add functions to hide some internals of long object, and for setting sign and digit count.
* Replace uses of IS_MEDIUM_VALUE macro with _PyLong_IsCompact().
When executing the BUILD_LIST opcode, steal the references from the stack,
in a manner similar to the BUILD_TUPLE opcode. Implement this by offloading
the logic to a new private API, _PyList_FromArraySteal(), that works similarly
to _PyTuple_FromArraySteal().
This way, instead of performing multiple stack pointer adjustments while the
list is being initialized, the stack is adjusted only once and a fast memory
copy operation is performed in one fell swoop.
builtins and extension module functions and methods that expect boolean values for parameters now accept any Python object rather than just a bool or int type. This is more consistent with how native Python code itself behaves.
The implementation of __sizeof__() methods using _PyObject_SIZE() now
use an unsigned type (size_t) to compute the size, rather than a signed
type (Py_ssize_t).
Cast explicitly signed (Py_ssize_t) values to unsigned type
(Py_ssize_t).
Fix multiplying a list by an integer (list *= int): detect the
integer overflow when the new allocated length is close to the
maximum size. Issue reported by Jordan Limor.
list_resize() now checks for integer overflow before multiplying the
new allocated length by the list item size (sizeof(PyObject*)).
* Add _Py_memory_repeat function to pycore_list
* Add _Py_RefcntAdd function to pycore_object
* Use the new functions in tuplerepeat, list_repeat, and list_inplace_repeat
We're no longer using _Py_IDENTIFIER() (or _Py_static_string()) in any core CPython code. It is still used in a number of non-builtin stdlib modules.
The replacement is: PyUnicodeObject (not pointer) fields under _PyRuntimeState, statically initialized as part of _PyRuntime. A new _Py_GET_GLOBAL_IDENTIFIER() macro facilitates lookup of the fields (along with _Py_GET_GLOBAL_STRING() for non-identifier strings).
https://bugs.python.org/issue46541#msg411799 explains the rationale for this change.
The core of the change is in:
* (new) Include/internal/pycore_global_strings.h - the declarations for the global strings, along with the macros
* Include/internal/pycore_runtime_init.h - added the static initializers for the global strings
* Include/internal/pycore_global_objects.h - where the struct in pycore_global_strings.h is hooked into _PyRuntimeState
* Tools/scripts/generate_global_objects.py - added generation of the global string declarations and static initializers
I've also added a --check flag to generate_global_objects.py (along with make check-global-objects) to check for unused global strings. That check is added to the PR CI config.
The remainder of this change updates the core code to use _Py_GET_GLOBAL_IDENTIFIER() instead of _Py_IDENTIFIER() and the related _Py*Id functions (likewise for _Py_GET_GLOBAL_STRING() instead of _Py_static_string()). This includes adding a few functions where there wasn't already an alternative to _Py*Id(), replacing the _Py_Identifier * parameter with PyObject *.
The following are not changed (yet):
* stop using _Py_IDENTIFIER() in the stdlib modules
* (maybe) get rid of _Py_IDENTIFIER(), etc. entirely -- this may not be doable as at least one package on PyPI using this (private) API
* (maybe) intern the strings during runtime init
https://bugs.python.org/issue46541
When multiplying lists and tuples by `n`, increment each element's refcount, by `n`, just once.
Saves `n-1` increments per element, and allows for a leaner & faster copying loop.
Code by sweeneyde (Dennis Sweeney).
This change is strictly renames and moving code around. It helps in the following ways:
* ensures type-related init functions focus strictly on one of the three aspects (state, objects, types)
* passes in PyInterpreterState * to all those functions, simplifying work on moving types/objects/state to the interpreter
* consistent naming conventions help make what's going on more clear
* keeping API related to a type in the corresponding header file makes it more obvious where to look for it
https://bugs.python.org/issue46008
Keep track of whether unsafe_tuple_compare() calls are resolved by the very
first tuple elements, and adjust strategy accordingly. This can significantly
cut the number of calls made to the full-blown PyObject_RichCompareBool(),
and especially when duplicates are rare.
Co-authored-by: Łukasz Langa <lukasz@langa.pl>
Freelists for object structs can now be disabled. A new ``configure``
option ``--without-freelists`` can be used to disable all freelists
except empty tuple singleton. Internal Py*_MAXFREELIST macros can now
be defined as 0 without causing compiler warnings and segfaults.
Signed-off-by: Christian Heimes <christian@python.org>
For list.sort(), replace our ad hoc merge ordering strategy with the principled, elegant,
and provably near-optimal one from Munro and Wild's "powersort".
* Add Py_TPFLAGS_SEQUENCE and Py_TPFLAGS_MAPPING, add to all relevant standard builtin classes.
* Set relevant flags on collections.abc.Sequence and Mapping.
* Use flags in MATCH_SEQUENCE and MATCH_MAPPING opcodes.
* Inherit Py_TPFLAGS_SEQUENCE and Py_TPFLAGS_MAPPING.
* Add NEWS
* Remove interpreter-state map_abc and seq_abc fields.
Pass the current interpreter (interp) rather than the current Python
thread state (tstate) to internal functions which only use the
interpreter.
Modified functions:
* _PyXXX_Fini() and _PyXXX_ClearFreeList() functions
* _PyEval_SignalAsyncExc(), make_pending_calls()
* _PySys_GetObject(), sys_set_object(), sys_set_object_id(), sys_set_object_str()
* should_audit(), set_flags_from_config(), make_flags()
* _PyAtExit_Call()
* init_stdio_encoding()
* etc.
No longer use deprecated aliases to functions:
* Replace PyMem_MALLOC() with PyMem_Malloc()
* Replace PyMem_REALLOC() with PyMem_Realloc()
* Replace PyMem_FREE() with PyMem_Free()
* Replace PyMem_Del() with PyMem_Free()
* Replace PyMem_DEL() with PyMem_Free()
Modify also the PyMem_DEL() macro to use directly PyMem_Free().
In debug mode, ensure that free lists are no longer used after being
finalized. Set numfree to -1 in finalization functions
(eg. _PyList_Fini()), and then check that numfree is not equal to -1
before using a free list (e.g list_dealloc()).
Each interpreter now has its own list free list:
* Move list numfree and free_list into PyInterpreterState.
* Add _Py_list_state structure.
* Add tstate parameter to _PyList_ClearFreeList()
and _PyList_Fini().
* Remove "#ifdef EXPERIMENTAL_ISOLATED_SUBINTERPRETERS".
* _PyGC_Fini() clears gcstate->garbage list which can be stored in
the list free list. Call _PyGC_Fini() before _PyList_Fini() to
prevent leaking this list.
When Python is built with experimental isolated interpreters, disable
the list free list.
Temporary workaround until this cache is made per-interpreter.
Remove the following function from the C API:
* PyAsyncGen_ClearFreeLists()
* PyContext_ClearFreeList()
* PyDict_ClearFreeList()
* PyFloat_ClearFreeList()
* PyFrame_ClearFreeList()
* PyList_ClearFreeList()
* PySet_ClearFreeList()
* PyTuple_ClearFreeList()
Make these functions private, move them to the internal C API and
change their return type to void.
Call explicitly PyGC_Collect() to free all free lists.
Note: PySet_ClearFreeList() did nothing.
Add _PyIndex_Check() function to the internal C API: fast inlined
verson of PyIndex_Check().
Add Include/internal/pycore_abstract.h header file.
Replace PyIndex_Check() with _PyIndex_Check() in C files of Objects
and Python subdirectories.
This implements things like `list[int]`,
which returns an object of type `types.GenericAlias`.
This object mostly acts as a proxy for `list`,
but has attributes `__origin__` and `__args__`
that allow recovering the parts (with values `list` and `(int,)`.
There is also an approximate notion of type variables;
e.g. `list[T]` has a `__parameters__` attribute equal to `(T,)`.
Type variables are objects of type `typing.TypeVar`.
Speed up calls to list() by using the PEP 590 vectorcall
calling convention. Patch by Mark Shannon.
Co-authored-by: Mark Shannon <mark@hotpy.org>
Co-authored-by: Dong-hee Na <donghee.na92@gmail.com>