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 here. There is no hard
requirement to use the memory returned by the allocation functions belonging to
a given domain for only the purposes hinted by that domain (although this is the
recommended practice). For example, one could use the memory returned by
PyMem_RawMalloc()
for allocating Python objects or the memory returned
by PyObject_Malloc()
for allocating memory for buffers.
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 the GIL. The memory is requested directly to the system.
„Mem” domain: intended for allocating memory for Python buffers and general-purpose memory buffers where the allocation must be performed with the GIL held. The memory is taken from the Python private heap.
Object domain: intended for allocating memory belonging to Python objects. The memory is taken from the Python private heap.
When freeing memory previously allocated by the allocating functions belonging to a
given domain,the matching specific deallocating functions must be used. For example,
PyMem_Free()
must be used to free memory allocated using PyMem_Malloc()
.
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.
Added in version 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 ifPyMem_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 ifPyMem_RawCalloc(1, 1)
had been called instead.Added in version 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 toPyMem_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 toPyMem_RawMalloc()
,PyMem_RawRealloc()
orPyMem_RawCalloc()
.If the request fails,
PyMem_RawRealloc()
returnsNULL
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()
orPyMem_RawCalloc()
. Otherwise, or ifPyMem_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)¶
- 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 ifPyMem_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 ifPyMem_Calloc(1, 1)
had been called instead.Added in version 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 toPyMem_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 toPyMem_Malloc()
,PyMem_Realloc()
orPyMem_Calloc()
.If the request fails,
PyMem_Realloc()
returnsNULL
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()
orPyMem_Calloc()
. Otherwise, or ifPyMem_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 toTYPE*
. 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 toTYPE*
. On return, p will be a pointer to the new memory area, orNULL
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.
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.
Ostrzeżenie
The GIL must be held 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 ifPyObject_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 ifPyObject_Calloc(1, 1)
had been called instead.Added in version 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 toPyObject_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 toPyObject_Malloc()
,PyObject_Realloc()
orPyObject_Calloc()
.If the request fails,
PyObject_Realloc()
returnsNULL
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()
orPyObject_Calloc()
. Otherwise, or ifPyObject_Free(p)
has been called before, undefined behavior occurs.If p is
NULL
, no operation is performed.
Default Memory Allocators¶
Default memory allocators:
Konfiguracja |
Nazwa |
PyMem_RawMalloc |
PyMem_Malloc |
PyObject_Malloc |
---|---|---|---|---|
Release build |
|
|
|
|
Debug build |
|
|
|
|
Release build, without pymalloc |
|
|
|
|
Debug build, without pymalloc |
|
|
|
|
Legenda:
Name: value for
PYTHONMALLOC
environment variable.malloc
: system allocators from the standard C library, C functions:malloc()
,calloc()
,realloc()
andfree()
.pymalloc
: pymalloc memory allocator.„+ debug”: with debug hooks on the Python memory allocators.
„Debug build”: Python build in debug mode.
Customize Memory Allocators¶
Added in version 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 toPyMemAllocatorEx
and a newcalloc
field was added.
-
type PyMemAllocatorDomain¶
Enum used to identify an allocator domain. Domains:
-
PYMEM_DOMAIN_RAW¶
Funkcje:
-
PYMEM_DOMAIN_MEM¶
Funkcje:
-
PYMEM_DOMAIN_OBJ¶
Funkcje:
-
PYMEM_DOMAIN_RAW¶
-
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.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 beforePy_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 the GIL held). 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 byPyMem_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()
) andPYMEM_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'
forPYMEM_DOMAIN_RAW
.'m'
forPYMEM_DOMAIN_MEM
.'o'
forPYMEM_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 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
(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. 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()
andVirtualFree()
on Windows,mmap()
andmunmap()
if available,malloc()
andfree()
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
).
Customize pymalloc Arena Allocator¶
Added in version 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.
tracemalloc C API¶
Added in version 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 return0
.
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.