Memory Management¶
Overview¶
Memory management in Python involves a private heap containing all Python objects and data structures. The management of this private heap is ensured internally by the Python memory manager. The Python memory manager has different components which deal with various dynamic storage management aspects, like sharing, segmentation, preallocation or caching.
At the lowest level, a raw memory allocator ensures that there is enough room in the private heap for storing all Python-related data by interacting with the memory manager of the operating system. On top of the raw memory allocator, several object-specific allocators operate on the same heap and implement distinct memory management policies adapted to the peculiarities of every object type. For example, integer objects are managed differently within the heap than strings, tuples or dictionaries because integers imply different storage requirements and speed/space tradeoffs. The Python memory manager thus delegates some of the work to the object-specific allocators, but ensures that the latter operate within the bounds of the private heap.
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 she regularly manipulates 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 string 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.
Ver también
The PYTHONMALLOCSTATS
environment variable can be used to print
memory allocation statistics every time a new 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 block allocator uses the following functions:
malloc()
, calloc()
, realloc()
and free()
; call
malloc(1)
(or calloc(1, 1)
) when requesting zero bytes.
Nuevo en la versión 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.Nuevo en la versión 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()
orPyMem_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()
orPyMem_RawCalloc()
. Otherwise, or ifPyMem_Free(p)
has been called before, undefined behavior occurs.If p is NULL, no operation is performed.
Memory Interface¶
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 block allocator uses the following functions:
malloc()
, calloc()
, realloc()
and free()
; call
malloc(1)
(or calloc(1, 1)
) when requesting zero bytes.
Advertencia
The GIL must be held when using these functions.
-
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.Nuevo en la versión 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()
orPyMem_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()
orPyMem_Calloc()
. Otherwise, or ifPyMem_Free(p)
has been called before, undefined behavior occurs.If p is NULL, no operation is performed.
The following type-oriented macros are provided for convenience. Note that TYPE refers to any C type.
-
TYPE*
PyMem_New
(TYPE, size_t 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.
-
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 toTYPE*
. 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()
.
In addition, the following macro sets are provided for calling the Python memory allocator directly, without involving the C API functions listed above. However, note that their use does not preserve binary compatibility across Python versions and is therefore deprecated in extension modules.
PyMem_MALLOC(size)
PyMem_NEW(type, size)
PyMem_REALLOC(ptr, size)
PyMem_RESIZE(ptr, type, size)
PyMem_FREE(ptr)
PyMem_DEL(ptr)
Customize Memory Allocators¶
Nuevo en la versión 3.4.
-
PyMemAllocatorEx
¶ Structure used to describe a memory block allocator. The structure has four fields:
Field Meaning 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 Distinto en la versión 3.5: The
PyMemAllocator
structure was renamed toPyMemAllocatorEx
and a newcalloc
field was added.
-
PyMemAllocatorDomain
¶ Enum used to identify an allocator domain. Domains:
PYMEM_DOMAIN_RAW
: functionsPyMem_RawMalloc()
,PyMem_RawRealloc()
,PyMem_RawCalloc()
andPyMem_RawFree()
PYMEM_DOMAIN_MEM
: functionsPyMem_Malloc()
,PyMem_Realloc()
,PyMem_Calloc()
andPyMem_Free()
PYMEM_DOMAIN_OBJ
: functionsPyObject_Malloc()
,PyObject_Realloc()
,PyObject_Calloc()
andPyObject_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 following Python memory allocator functions:
PyMem_RawMalloc()
,PyMem_RawRealloc()
,PyMem_RawCalloc()
,PyMem_RawFree()
PyMem_Malloc()
,PyMem_Realloc()
,PyMem_Calloc()
,PyMem_Free()
PyObject_Malloc()
,PyObject_Realloc()
,PyObject_Calloc()
,PyObject_Free()
Newly allocated memory is filled with the byte
0xCB
, freed memory is filled with the byte0xDB
. Additional checks:- detect API violations, ex:
PyObject_Free()
called on a buffer allocated byPyMem_Malloc()
- detect write before the start of the buffer (buffer underflow)
- detect write after the end of the buffer (buffer overflow)
The function does nothing if Python is not compiled is debug mode.
Customize PyObject Arena Allocator¶
Python has a pymalloc allocator for allocations smaller than 512 bytes. This
allocator is optimized for small objects with a short lifetime. It uses memory
mappings called «arenas» with a fixed size of 256 KB. It falls back to
PyMem_RawMalloc()
and PyMem_RawRealloc()
for allocations larger
than 512 bytes. pymalloc is the default allocator used by
PyObject_Malloc()
.
The default arena allocator uses the following functions:
VirtualAlloc()
andVirtualFree()
on Windows,mmap()
andmunmap()
if available,malloc()
andfree()
otherwise.
Nuevo en la versión 3.4.
-
PyObjectArenaAllocator
¶ Structure used to describe an arena allocator. The structure has three fields:
Field Meaning 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, size_t size, void *ptr)
free an arena
-
PyObject_GetArenaAllocator
(PyObjectArenaAllocator *allocator)¶ Get the arena allocator.
-
PyObject_SetArenaAllocator
(PyObjectArenaAllocator *allocator)¶ Set the arena allocator.
Examples¶
Here is the example from section Overview, rewritten so that the I/O buffer is allocated from the Python heap by using the first function set:
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;
The same code using the type-oriented function set:
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;
Note that in the two examples above, the buffer is always manipulated via functions belonging to the same set. Indeed, it is required to use the same memory API family for a given memory block, so that the risk of mixing different allocators is reduced to a minimum. The following code sequence contains two errors, one of which is labeled as fatal because it mixes two different allocators operating on different heaps.
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()
.
These will be explained in the next chapter on defining and implementing new object types in C.