# 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.

W większości przypadków, jednakże, zalecane jest umieszczanie w pamięci ze sterty Pythona szczególnie ponieważ ta ostatnia jest pod kontrolą zarządcy pamięci języka Pytonowskiego. Na przykład, jest to wymagane gdy program interpretujący polecenia Pythona jest rozszerzany nowymi typami obiektów napisanych w języku C. Inną przyczyną użycia sterty Pythona jest chęć poinformowania zarządcy pamięci Pythona o potrzebach pamięciowych modułu rozszerzającego. Nawet gdy żądana pamięć jest używana wyłącznie dla wewnętrznych wysoko-wyspecjalizowanych potrzeb, oddelegowanie wszystkich zapytań o pamięć do zarządcy pamięci Pythona spowoduje że program interpretujący polecenia Pythona będzie miał bardziej trafny obraz podstawowego rozmiaru potrzeb pamięciowych jako całości. Konsekwentnie, w pewnych warunkach zarządca pamięci Pythona może lub może nie uruchomić właściwych działań, jak zbiórki śmieci, porządkowania pamięci lub innych zapobiegawczych działań. Zauważ, że używając programu bibliotecznego lokującego pamięć z języka C jak pokazano w poprzednim przykładzie zarezerwowana pamięć dla obszaru wymiany wejścia/wyjścia całkowicie umyka uwadze zarządcy pamięci Pythona.

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.

## Raw Memory Interface

The following function sets are wrappers to the system allocator. These functions are thread-safe, the GIL does not need to be held.

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.

Nowe w wersji 3.4.

void* `PyMem_RawMalloc`(size_t n)

  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)

  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.

  Nowe w wersji 3.5.

void* `PyMem_RawRealloc`(void *p, size_t n)

  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)

  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.

The default memory allocator uses the pymalloc memory allocator.

Ostrzeżenie

The GIL must be held when using these functions.

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

void* `PyMem_Malloc`(size_t n)

  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)

  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.

  Nowe w wersji 3.5.

void* `PyMem_Realloc`(void *p, size_t n)

  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)

  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.

TYPE* `PyMem_New`(TYPE, size_t 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.

TYPE* `PyMem_Resize`(void *p, TYPE, size_t 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()`.

Dodać należy, że następujący zbiór makropoleceń dostarczony jest aby odwoływać się do programu przydzielającego pamięć w języku pytonowskim bezpośrednio, bez udziału zadań sprzęgu C wymienionych powyżej. Jednakże, zauważ, że ich użycie nie zachowuje wzajemnej zgodności binarnej pomiędzy wersjami Pythona i z tego też powodu ich użycie jest niewskazane w modułach rozszerzających.

- `PyMem_MALLOC(size)`

- `PyMem_NEW(type, size)`

- `PyMem_REALLOC(ptr, size)`

- `PyMem_RESIZE(ptr, type, size)`

- `PyMem_FREE(ptr)`

- `PyMem_DEL(ptr)`

## 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.

The default object allocator uses the pymalloc memory allocator.

Ostrzeżenie

The GIL must be held when using these functions.

void* `PyObject_Malloc`(size_t n)

  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)

  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.

  Nowe w wersji 3.5.

void* `PyObject_Realloc`(void *p, size_t n)

  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)

  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.

## Default Memory Allocators

Default memory allocators:

Configuration | 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

Legend:

- 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

- „+ debug”: with debug hooks installed by `PyMem_SetupDebugHooks()`

## Customize Memory Allocators

Nowe w wersji 3.4.

`PyMemAllocatorEx`

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

  Field | 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.

`PyMemAllocatorDomain`

  Enum used to identify an allocator domain. Domains:

  `PYMEM_DOMAIN_RAW`

    Functions:

    - `PyMem_RawMalloc()`

    - `PyMem_RawRealloc()`

    - `PyMem_RawCalloc()`

    - `PyMem_RawFree()`

  `PYMEM_DOMAIN_MEM`

    Functions:

    - `PyMem_Malloc()`,

    - `PyMem_Realloc()`

    - `PyMem_Calloc()`

    - `PyMem_Free()`

  `PYMEM_DOMAIN_OBJ`

    Functions:

    - `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: the GIL is not held when the allocator is called.

  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.

void `PyMem_SetupDebugHooks`(void)

  Setup hooks to detect bugs in the Python memory allocator functions.

  Newly allocated memory is filled with the byte `0xCD` (`CLEANBYTE`), freed memory is filled with the byte `0xDD` (`DEADBYTE`). Memory blocks are surrounded by „forbidden bytes” (`FORBIDDENBYTE`: byte `0xFD`).

  Runtime checks:

  - Detect API violations, ex: `PyObject_Free()` called on a buffer 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 the GIL is held 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.

  These hooks are installed by default if Python is compiled in debug mode. The `PYTHONMALLOC` environment variable can be used to install debug hooks on a Python compiled in release mode.

  Zmienione w wersji 3.6: This 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 the GIL is held when functions of `PYMEM_DOMAIN_OBJ` and `PYMEM_DOMAIN_MEM` domains are called.

  Zmienione w wersji 3.8: Byte patterns `0xCB` (`CLEANBYTE`), `0xDB` (`DEADBYTE`) and `0xFB` (`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 256 KiB. 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.

### Customize pymalloc Arena Allocator

Nowe w wersji 3.4.

`PyObjectArenaAllocator`

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

  Field | 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.

## tracemalloc C API

Nowe 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_Del(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_Del()  */

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_Del()`.

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