# Zarządzanie Pamięcią

## Skorowidz

Zarządzanie pamięcią w Pythonie zakłada prywatną stertę zawierającą wszystkie obiekty i struktury danych Pythona. Zarządzanie tą prywatną stertą jest zapewniane wewnętrznie przez zarządcę pamięci Pythona. Zarządca pamięci Pythona ma różne komponenty które radzą sobie z różnymi aspektami dynamicznego przechowywania, jak współdzielenie, segmentacja, alokacja wstępna i kieszeniowanie.

Na najniższym poziomie, przedmiot przydzielający pamięć „na-surowo” zapewnia że będzie dość pamięci na prywatnej stercie dla przechowania wszystkich związanych-z-językiem-pytonowskim danych przez współdziałanie z zarządcą pamięci systemu operacyjnego. Ponad zarządcą surowej pamięci, kilka szczególnych dla danych typów przedmiotów zarządców operuje na tej samej stercie i wypełnia szczególne zasady zarządzania pamięcią dostosowane do szczególnych własności każdego rodzaju przedmiotu. Dla przykładu przedmioty liczb całkowitych są zarządzane inaczej wewnątrz sterty niż ciągi znaków, krotki czy słowniki gdyż liczby całkowite zakładają inne wymagania przechowywania i wady i zalety prędkości/zajętej przestrzeni. Zarządca pamięcią Pythona zatem odprawia pewną ilość nakładów pracy dla szczególnych dla przedmiotów różnych typów zarządców, ale zapewnia że te drugie będą operować wewnątrz ograniczeń prywatnej sterty.

It is important to understand that the management of the Python heap is performed by the interpreter itself and that the user has no control over it, even if they regularly manipulate object pointers to memory blocks inside that heap. The allocation of heap space for Python objects and other internal buffers is performed on demand by the Python memory manager through the Python/C API functions listed in this document.

To avoid memory corruption, extension writers should never try to operate on Python objects with the functions exported by the C library: `malloc()`, `calloc()`, `realloc()` and `free()`. This will result in mixed calls between the C allocator and the Python memory manager with fatal consequences, because they implement different algorithms and operate on different heaps. However, one may safely allocate and release memory blocks with the C library allocator for individual purposes, as shown in the following example:

    PyObject *res;
    char *buf = (char *) malloc(BUFSIZ); /* for I/O */

    if (buf == NULL)
        return PyErr_NoMemory();
    ...Do some I/O operation involving buf...
    res = PyBytes_FromString(buf);
    free(buf); /* malloc'ed */
    return res;

In this example, the memory request for the I/O buffer is handled by the C library allocator. The Python memory manager is involved only in the allocation of the bytes object returned as a result.

In most situations, however, it is recommended to allocate memory from the Python heap specifically because the latter is under control of the Python memory manager. For example, this is required when the interpreter is extended with new object types written in C. Another reason for using the Python heap is the desire to inform the Python memory manager about the memory needs of the extension module. Even when the requested memory is used exclusively for internal, highly specific purposes, delegating all memory requests to the Python memory manager causes the interpreter to have a more accurate image of its memory footprint as a whole. Consequently, under certain circumstances, the Python memory manager may or may not trigger appropriate actions, like garbage collection, memory compaction or other preventive procedures. Note that by using the C library allocator as shown in the previous example, the allocated memory for the I/O buffer escapes completely the Python memory manager.

Zobacz także

The `PYTHONMALLOC` environment variable can be used to configure the memory allocators used by Python.

The `PYTHONMALLOCSTATS` environment variable can be used to print statistics of the pymalloc memory allocator every time a new pymalloc object arena is created, and on shutdown.

## Allocator Domains

All allocating functions belong to one of three different „domains” (see also `PyMemAllocatorDomain`). These domains represent different allocation strategies and are optimized for different purposes. The specific details on how every domain allocates memory or what internal functions each domain calls is considered an implementation detail, but for debugging purposes a simplified table can be found at Default Memory Allocators. The APIs used to allocate and free a block of memory must be from the same domain. For example, `PyMem_Free()` must be used to free memory allocated using `PyMem_Malloc()`.

The three allocation domains are:

- Raw domain: intended for allocating memory for general-purpose memory buffers where the allocation must go to the system allocator or where the allocator can operate without an attached thread state. The memory is requested directly from the system. See Raw Memory Interface.

- „Mem” domain: intended for allocating memory for Python buffers and general-purpose memory buffers where the allocation must be performed with an attached thread state. The memory is taken from the Python private heap. See Memory Interface.

- Object domain: intended for allocating memory for Python objects. The memory is taken from the Python private heap. See Object allocators.

Informacja

The free-threaded build requires that only Python objects are allocated using the „object” domain and that all Python objects are allocated using that domain. This differs from the prior Python versions, where this was only a best practice and not a hard requirement.

For example, buffers (non-Python objects) should be allocated using `PyMem_Malloc()`, `PyMem_RawMalloc()`, or `malloc()`, but not `PyObject_Malloc()`.

See Memory Allocation APIs.

## Raw Memory Interface

The following function sets are wrappers to the system allocator. These functions are thread-safe, so a thread state does not need to be attached.

The default raw memory allocator uses the following functions: `malloc()`, `calloc()`, `realloc()` and `free()`; call `malloc(1)` (or `calloc(1, 1)`) when requesting zero bytes.

Dodane w wersji 3.4.

void *PyMem_RawMalloc(size_t n)
  Część stabilnego ABI od wersji 3.13.

  Allocates n bytes and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails.

  Requesting zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyMem_RawMalloc(1)` had been called instead. The memory will not have been initialized in any way.

void *PyMem_RawCalloc(size_t nelem, size_t elsize)
  Część stabilnego ABI od wersji 3.13.

  Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails. The memory is initialized to zeros.

  Requesting zero elements or elements of size zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyMem_RawCalloc(1, 1)` had been called instead.

  Dodane w wersji 3.5.

void *PyMem_RawRealloc(void *p, size_t n)
  Część stabilnego ABI od wersji 3.13.

  Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

  If p is `NULL`, the call is equivalent to `PyMem_RawMalloc(n)`; else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-`NULL`.

  Unless p is `NULL`, it must have been returned by a previous call to `PyMem_RawMalloc()`, `PyMem_RawRealloc()` or `PyMem_RawCalloc()`.

  If the request fails, `PyMem_RawRealloc()` returns `NULL` and p remains a valid pointer to the previous memory area.

void PyMem_RawFree(void *p)
  Część stabilnego ABI od wersji 3.13.

  Frees the memory block pointed to by p, which must have been returned by a previous call to `PyMem_RawMalloc()`, `PyMem_RawRealloc()` or `PyMem_RawCalloc()`. Otherwise, or if `PyMem_RawFree(p)` has been called before, undefined behavior occurs.

  If p is `NULL`, no operation is performed.

## Sprzęg Pamięci

The following function sets, modeled after the ANSI C standard, but specifying behavior when requesting zero bytes, are available for allocating and releasing memory from the Python heap.

In the GIL-enabled build (default build) the default memory allocator uses the pymalloc memory allocator, whereas in the free-threaded build, the default is the mimalloc memory allocator instead.

Ostrzeżenie

There must be an attached thread state when using these functions.

Zmienione w wersji 3.6: The default allocator is now pymalloc instead of system `malloc()`.

Zmienione w wersji 3.13: In the free-threaded build, the default allocator is now mimalloc.

void *PyMem_Malloc(size_t n)
  Część stabilnego ABI.

  Allocates n bytes and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails.

  Requesting zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyMem_Malloc(1)` had been called instead. The memory will not have been initialized in any way.

void *PyMem_Calloc(size_t nelem, size_t elsize)
  Część stabilnego ABI od wersji 3.7.

  Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails. The memory is initialized to zeros.

  Requesting zero elements or elements of size zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyMem_Calloc(1, 1)` had been called instead.

  Dodane w wersji 3.5.

void *PyMem_Realloc(void *p, size_t n)
  Część stabilnego ABI.

  Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

  If p is `NULL`, the call is equivalent to `PyMem_Malloc(n)`; else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-`NULL`.

  Unless p is `NULL`, it must have been returned by a previous call to `PyMem_Malloc()`, `PyMem_Realloc()` or `PyMem_Calloc()`.

  If the request fails, `PyMem_Realloc()` returns `NULL` and p remains a valid pointer to the previous memory area.

void PyMem_Free(void *p)
  Część stabilnego ABI.

  Frees the memory block pointed to by p, which must have been returned by a previous call to `PyMem_Malloc()`, `PyMem_Realloc()` or `PyMem_Calloc()`. Otherwise, or if `PyMem_Free(p)` has been called before, undefined behavior occurs.

  If p is `NULL`, no operation is performed.

Następujące makropolecenia zorientowane-według-typu dostarczone są dla wygody. Zauważ że TYP odnosi się do dowolnego typu C.

PyMem_New(TYPE, n)

  Same as `PyMem_Malloc()`, but allocates `(n * sizeof(TYPE))` bytes of memory. Returns a pointer cast to `TYPE*`. The memory will not have been initialized in any way.

PyMem_Resize(p, TYPE, n)

  Same as `PyMem_Realloc()`, but the memory block is resized to `(n * sizeof(TYPE))` bytes. Returns a pointer cast to `TYPE*`. On return, p will be a pointer to the new memory area, or `NULL` in the event of failure.

  This is a C preprocessor macro; p is always reassigned. Save the original value of p to avoid losing memory when handling errors.

void PyMem_Del(void *p)

  Same as `PyMem_Free()`.

### Deprecated aliases

These are soft deprecated aliases to existing functions and macros. They exist solely for backwards compatibility.

Deprecated alias | Corresponding function or macro
--- | ---
PyMem_MALLOC(size) | `PyMem_Malloc()`
PyMem_NEW(type, size) | `PyMem_New`
PyMem_REALLOC(ptr, size) | `PyMem_Realloc()`
PyMem_RESIZE(ptr, type, size) | `PyMem_Resize`
PyMem_FREE(ptr) | `PyMem_Free()`
PyMem_DEL(ptr) | `PyMem_Free()`

Zmienione w wersji 3.4: The macros are now aliases of the corresponding functions and macros. Previously, their behavior was the same, but their use did not necessarily preserve binary compatibility across Python versions.

Niezalecane od wersji 2.0.

## Object allocators

The following function sets, modeled after the ANSI C standard, but specifying behavior when requesting zero bytes, are available for allocating and releasing memory from the Python heap.

Informacja

There is no guarantee that the memory returned by these allocators can be successfully cast to a Python object when intercepting the allocating functions in this domain by the methods described in the Customize Memory Allocators section.

The default object allocator uses the pymalloc memory allocator. In the free-threaded build, the default is the mimalloc memory allocator instead.

Ostrzeżenie

There must be an attached thread state when using these functions.

void *PyObject_Malloc(size_t n)
  Część stabilnego ABI.

  Allocates n bytes and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails.

  Requesting zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyObject_Malloc(1)` had been called instead. The memory will not have been initialized in any way.

void *PyObject_Calloc(size_t nelem, size_t elsize)
  Część stabilnego ABI od wersji 3.7.

  Allocates nelem elements each whose size in bytes is elsize and returns a pointer of type void* to the allocated memory, or `NULL` if the request fails. The memory is initialized to zeros.

  Requesting zero elements or elements of size zero bytes returns a distinct non-`NULL` pointer if possible, as if `PyObject_Calloc(1, 1)` had been called instead.

  Dodane w wersji 3.5.

void *PyObject_Realloc(void *p, size_t n)
  Część stabilnego ABI.

  Resizes the memory block pointed to by p to n bytes. The contents will be unchanged to the minimum of the old and the new sizes.

  If p is `NULL`, the call is equivalent to `PyObject_Malloc(n)`; else if n is equal to zero, the memory block is resized but is not freed, and the returned pointer is non-`NULL`.

  Unless p is `NULL`, it must have been returned by a previous call to `PyObject_Malloc()`, `PyObject_Realloc()` or `PyObject_Calloc()`.

  If the request fails, `PyObject_Realloc()` returns `NULL` and p remains a valid pointer to the previous memory area.

void PyObject_Free(void *p)
  Część stabilnego ABI.

  Frees the memory block pointed to by p, which must have been returned by a previous call to `PyObject_Malloc()`, `PyObject_Realloc()` or `PyObject_Calloc()`. Otherwise, or if `PyObject_Free(p)` has been called before, undefined behavior occurs.

  If p is `NULL`, no operation is performed.

  Do not call this directly to free an object’s memory; call the type’s `tp_free` slot instead.

  Do not use this for memory allocated by `PyObject_GC_New` or `PyObject_GC_NewVar`; use `PyObject_GC_Del()` instead.

  Zobacz także

  - `PyObject_GC_Del()` is the equivalent of this function for memory allocated by types that support garbage collection.

  - `PyObject_Malloc()`

  - `PyObject_Realloc()`

  - `PyObject_Calloc()`

  - `PyObject_New`

  - `PyObject_NewVar`

  - `PyType_GenericAlloc()`

  - `tp_free`

## Default Memory Allocators

Default memory allocators:

Konfiguracja | Nazwa | PyMem_RawMalloc | PyMem_Malloc | PyObject_Malloc
--- | --- | --- | --- | ---
Release build | `"pymalloc"` | `malloc` | `pymalloc` | `pymalloc`
Debug build | `"pymalloc_debug"` | `malloc` + debug | `pymalloc` + debug | `pymalloc` + debug
Release build, without pymalloc | `"malloc"` | `malloc` | `malloc` | `malloc`
Debug build, without pymalloc | `"malloc_debug"` | `malloc` + debug | `malloc` + debug | `malloc` + debug
Free-threaded build | `"mimalloc"` | `mimalloc` | `mimalloc` | `mimalloc`
Free-threaded debug build | `"mimalloc_debug"` | `mimalloc` + debug | `mimalloc` + debug | `mimalloc` + debug

Legenda:

- Name: value for `PYTHONMALLOC` environment variable.

- `malloc`: system allocators from the standard C library, C functions: `malloc()`, `calloc()`, `realloc()` and `free()`.

- `pymalloc`: pymalloc memory allocator.

- `mimalloc`: mimalloc memory allocator.

- „+ debug”: with debug hooks on the Python memory allocators.

- „Debug build”: Python build in debug mode.

## Customize Memory Allocators

Dodane w wersji 3.4.

type PyMemAllocatorEx

  Structure used to describe a memory block allocator. The structure has the following fields:

  Pole | Znaczenie
  --- | ---
  `void *ctx` | user context passed as first argument
  `void* malloc(void *ctx, size_t size)` | allocate a memory block
  `void* calloc(void *ctx, size_t nelem, size_t elsize)` | allocate a memory block initialized with zeros
  `void* realloc(void *ctx, void *ptr, size_t new_size)` | allocate or resize a memory block
  `void free(void *ctx, void *ptr)` | free a memory block

  Zmienione w wersji 3.5: The `PyMemAllocator` structure was renamed to `PyMemAllocatorEx` and a new `calloc` field was added.

type PyMemAllocatorDomain

  Enum used to identify an allocator domain. Domains:

  PYMEM_DOMAIN_RAW

    Funkcje:

    - `PyMem_RawMalloc()`

    - `PyMem_RawRealloc()`

    - `PyMem_RawCalloc()`

    - `PyMem_RawFree()`

  PYMEM_DOMAIN_MEM

    Funkcje:

    - `PyMem_Malloc()`,

    - `PyMem_Realloc()`

    - `PyMem_Calloc()`

    - `PyMem_Free()`

  PYMEM_DOMAIN_OBJ

    Funkcje:

    - `PyObject_Malloc()`

    - `PyObject_Realloc()`

    - `PyObject_Calloc()`

    - `PyObject_Free()`

void PyMem_GetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)

  Get the memory block allocator of the specified domain.

void PyMem_SetAllocator(PyMemAllocatorDomain domain, PyMemAllocatorEx *allocator)

  Set the memory block allocator of the specified domain.

  The new allocator must return a distinct non-`NULL` pointer when requesting zero bytes.

  For the `PYMEM_DOMAIN_RAW` domain, the allocator must be thread-safe: a thread state is not attached when the allocator is called.

  For the remaining domains, the allocator must also be thread-safe: the allocator may be called in different interpreters that do not share a GIL.

  If the new allocator is not a hook (does not call the previous allocator), the `PyMem_SetupDebugHooks()` function must be called to reinstall the debug hooks on top on the new allocator.

  See also `PyPreConfig.allocator` and Preinitialize Python with PyPreConfig.

  Ostrzeżenie

  `PyMem_SetAllocator()` does have the following contract:

  - It can be called after `Py_PreInitialize()` and before `Py_InitializeFromConfig()` to install a custom memory allocator. There are no restrictions over the installed allocator other than the ones imposed by the domain (for instance, the Raw Domain allows the allocator to be called without an attached thread state). See the section on allocator domains for more information.

  - If called after Python has finish initializing (after `Py_InitializeFromConfig()` has been called) the allocator must wrap the existing allocator. Substituting the current allocator for some other arbitrary one is not supported.

  Zmienione w wersji 3.12: All allocators must be thread-safe.

void PyMem_SetupDebugHooks(void)

  Setup debug hooks in the Python memory allocators to detect memory errors.

## Debug hooks on the Python memory allocators

When Python is built in debug mode, the `PyMem_SetupDebugHooks()` function is called at the Python preinitialization to setup debug hooks on Python memory allocators to detect memory errors.

The `PYTHONMALLOC` environment variable can be used to install debug hooks on a Python compiled in release mode (ex: `PYTHONMALLOC=debug`).

The `PyMem_SetupDebugHooks()` function can be used to set debug hooks after calling `PyMem_SetAllocator()`.

These debug hooks fill dynamically allocated memory blocks with special, recognizable bit patterns. Newly allocated memory is filled with the byte `0xCD` (`PYMEM_CLEANBYTE`), freed memory is filled with the byte `0xDD` (`PYMEM_DEADBYTE`). Memory blocks are surrounded by „forbidden bytes” filled with the byte `0xFD` (`PYMEM_FORBIDDENBYTE`). Strings of these bytes are unlikely to be valid addresses, floats, or ASCII strings.

Runtime checks:

- Detect API violations. For example, detect if `PyObject_Free()` is called on a memory block allocated by `PyMem_Malloc()`.

- Detect write before the start of the buffer (buffer underflow).

- Detect write after the end of the buffer (buffer overflow).

- Check that there is an attached thread state when allocator functions of `PYMEM_DOMAIN_OBJ` (ex: `PyObject_Malloc()`) and `PYMEM_DOMAIN_MEM` (ex: `PyMem_Malloc()`) domains are called.

On error, the debug hooks use the `tracemalloc` module to get the traceback where a memory block was allocated. The traceback is only displayed if `tracemalloc` is tracing Python memory allocations and the memory block was traced.

Let S = `sizeof(size_t)`. `2*S` bytes are added at each end of each block of N bytes requested. The memory layout is like so, where p represents the address returned by a malloc-like or realloc-like function (`p[i:j]` means the slice of bytes from `*(p+i)` inclusive up to `*(p+j)` exclusive; note that the treatment of negative indices differs from a Python slice):

`p[-2*S:-S]`

  Number of bytes originally asked for. This is a size_t, big-endian (easier to read in a memory dump).

`p[-S]`

  API identifier (ASCII character):

  - `'r'` for `PYMEM_DOMAIN_RAW`.

  - `'m'` for `PYMEM_DOMAIN_MEM`.

  - `'o'` for `PYMEM_DOMAIN_OBJ`.

`p[-S+1:0]`

  Copies of PYMEM_FORBIDDENBYTE. Used to catch under- writes and reads.

`p[0:N]`

  The requested memory, filled with copies of PYMEM_CLEANBYTE, used to catch reference to uninitialized memory. When a realloc-like function is called requesting a larger memory block, the new excess bytes are also filled with PYMEM_CLEANBYTE. When a free-like function is called, these are overwritten with PYMEM_DEADBYTE, to catch reference to freed memory. When a realloc- like function is called requesting a smaller memory block, the excess old bytes are also filled with PYMEM_DEADBYTE.

`p[N:N+S]`

  Copies of PYMEM_FORBIDDENBYTE. Used to catch over- writes and reads.

`p[N+S:N+2*S]`

  Only used if the `PYMEM_DEBUG_SERIALNO` macro is defined (not defined by default).

  A serial number, incremented by 1 on each call to a malloc-like or realloc-like function. Big-endian `size_t`. If „bad memory” is detected later, the serial number gives an excellent way to set a breakpoint on the next run, to capture the instant at which this block was passed out. The static function bumpserialno() in obmalloc.c is the only place the serial number is incremented, and exists so you can set such a breakpoint easily.

A realloc-like or free-like function first checks that the PYMEM_FORBIDDENBYTE bytes at each end are intact. If they’ve been altered, diagnostic output is written to stderr, and the program is aborted via Py_FatalError(). The other main failure mode is provoking a memory error when a program reads up one of the special bit patterns and tries to use it as an address. If you get in a debugger then and look at the object, you’re likely to see that it’s entirely filled with PYMEM_DEADBYTE (meaning freed memory is getting used) or PYMEM_CLEANBYTE (meaning uninitialized memory is getting used).

Zmienione w wersji 3.6: The `PyMem_SetupDebugHooks()` function now also works on Python compiled in release mode. On error, the debug hooks now use `tracemalloc` to get the traceback where a memory block was allocated. The debug hooks now also check if there is an attached thread state when functions of `PYMEM_DOMAIN_OBJ` and `PYMEM_DOMAIN_MEM` domains are called.

Zmienione w wersji 3.8: Byte patterns `0xCB` (`PYMEM_CLEANBYTE`), `0xDB` (`PYMEM_DEADBYTE`) and `0xFB` (`PYMEM_FORBIDDENBYTE`) have been replaced with `0xCD`, `0xDD` and `0xFD` to use the same values than Windows CRT debug `malloc()` and `free()`.

## The pymalloc allocator

Python has a pymalloc allocator optimized for small objects (smaller or equal to 512 bytes) with a short lifetime. It uses memory mappings called „arenas” with a fixed size of either 256 KiB on 32-bit platforms or 1 MiB on 64-bit platforms. When Python is configured with `--with-pymalloc-hugepages`, the arena size on 64-bit platforms is increased to 2 MiB to match the huge page size, and arena allocation will attempt to use huge pages (`MAP_HUGETLB` on Linux, `MEM_LARGE_PAGES` on Windows) with automatic fallback to regular pages. It falls back to `PyMem_RawMalloc()` and `PyMem_RawRealloc()` for allocations larger than 512 bytes.

pymalloc is the default allocator of the `PYMEM_DOMAIN_MEM` (ex: `PyMem_Malloc()`) and `PYMEM_DOMAIN_OBJ` (ex: `PyObject_Malloc()`) domains.

The arena allocator uses the following functions:

- `VirtualAlloc()` and `VirtualFree()` on Windows,

- `mmap()` and `munmap()` if available,

- `malloc()` and `free()` otherwise.

This allocator is disabled if Python is configured with the `--without-pymalloc` option. It can also be disabled at runtime using the `PYTHONMALLOC` environment variable (ex: `PYTHONMALLOC=malloc`).

Typically, it makes sense to disable the pymalloc allocator when building Python with AddressSanitizer (`--with-address-sanitizer`) which helps uncover low level bugs within the C code.

### Customize pymalloc Arena Allocator

Dodane w wersji 3.4.

type PyObjectArenaAllocator

  Structure used to describe an arena allocator. The structure has three fields:

  Pole | Znaczenie
  --- | ---
  `void *ctx` | user context passed as first argument
  `void* alloc(void *ctx, size_t size)` | allocate an arena of size bytes
  `void free(void *ctx, void *ptr, size_t size)` | free an arena

void PyObject_GetArenaAllocator(PyObjectArenaAllocator *allocator)

  Get the arena allocator.

void PyObject_SetArenaAllocator(PyObjectArenaAllocator *allocator)

  Set the arena allocator.

## The mimalloc allocator

Dodane w wersji 3.13.

Python supports the mimalloc allocator when the underlying platform support is available. mimalloc is a general purpose allocator with excellent performance characteristics, initially developed by Daan Leijen for the runtime systems of the Koka and Lean languages.

Unlike pymalloc, which is optimized for small objects (512 bytes or fewer), mimalloc handles allocations of any size.

In the free-threaded build, mimalloc is the default and required allocator for the `PYMEM_DOMAIN_MEM` and `PYMEM_DOMAIN_OBJ` domains. It cannot be disabled in free-threaded builds. The free-threaded build uses per-thread mimalloc heaps, which allows allocation and deallocation to proceed without locking in most cases.

In the default (non-free-threaded) build, mimalloc is available but not the default allocator. It can be selected at runtime using `PYTHONMALLOC``=mimalloc` (or `mimalloc_debug` to include debug hooks). It can be disabled at build time using the `--without-mimalloc` configure option, but this option cannot be combined with `--disable-gil`.

## tracemalloc C API

Dodane w wersji 3.7.

int PyTraceMalloc_Track(unsigned int domain, uintptr_t ptr, size_t size)

  Track an allocated memory block in the `tracemalloc` module.

  Return `0` on success, return `-1` on error (failed to allocate memory to store the trace). Return `-2` if tracemalloc is disabled.

  If memory block is already tracked, update the existing trace.

int PyTraceMalloc_Untrack(unsigned int domain, uintptr_t ptr)

  Untrack an allocated memory block in the `tracemalloc` module. Do nothing if the block was not tracked.

  Return `-2` if tracemalloc is disabled, otherwise return `0`.

## Przykłady

Tutaj jest przykład z sekcji „przeglądu pamięci” - z ang. - Skorowidz, przepisane, tak aby przestrzeń wejścia/wyjścia była przydzielona ze sterty Pythona używając pierwszego zestawu zadań:

    PyObject *res;
    char *buf = (char *) PyMem_Malloc(BUFSIZ); /* for I/O */

    if (buf == NULL)
        return PyErr_NoMemory();
    /* ...Do some I/O operation involving buf... */
    res = PyBytes_FromString(buf);
    PyMem_Free(buf); /* allocated with PyMem_Malloc */
    return res;

ten sam kod przy użyciu zorientowanych na typ zbiorów zadań:

    PyObject *res;
    char *buf = PyMem_New(char, BUFSIZ); /* for I/O */

    if (buf == NULL)
        return PyErr_NoMemory();
    /* ...Do some I/O operation involving buf... */
    res = PyBytes_FromString(buf);
    PyMem_Free(buf); /* allocated with PyMem_New */
    return res;

Zauważ, że w dwóch powyższych przykładach, przestrzeń wymiany jest zawsze zmieniana przez zadania należące do tego samego zbioru. Właściwie, jest wymagane użycie tej samej rodziny sprzęgów zarządzania pamięcią (z ang. - memory API) dla danego obszaru pamięci, tak, że ryzyko pomieszania różnych programów lokujących zmniejszone jest do minimum. Następująca sekwencja zawiera dwa błędy, jeden z których określony jest jako krytyczny ponieważ miesza dwa różne programy lokujące pamięć działające na różnych stertach.

    char *buf1 = PyMem_New(char, BUFSIZ);
    char *buf2 = (char *) malloc(BUFSIZ);
    char *buf3 = (char *) PyMem_Malloc(BUFSIZ);
    ...
    PyMem_Del(buf3);  /* Wrong -- should be PyMem_Free() */
    free(buf2);       /* Right -- allocated via malloc() */
    free(buf1);       /* Fatal -- should be PyMem_Free()  */

In addition to the functions aimed at handling raw memory blocks from the Python heap, objects in Python are allocated and released with `PyObject_New`, `PyObject_NewVar` and `PyObject_Free()`.

Te zostaną wyjaśnione w następnym rozdziale o określaniu i realizowaniu nowych typów obiektów w języku C.