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 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)returnPyErr_NoMemory();...DosomeI/Ooperationinvolvingbuf...res=PyBytes_FromString(buf);free(buf);/* malloc'ed */returnres;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.
See also
The
environment variable can be used to configure the memory allocators used by Python.
The
environment variable can be used to print statistics of the
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
). 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
. 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
for allocating Python objects or the memory returned by
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
. 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
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,
must be used to free memory allocated using
.
Raw Memory Interface
The following function sets are wrappers to the system allocator. These functions are thread-safe, the
does not need to be held.
The
uses the following functions: malloc(), calloc(), realloc() and free(); call malloc(1) (or calloc(1,1)) when requesting zero bytes.
New in version 3.4.
void*PyMem_RawMalloc(size_tn)
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_tnelem, size_telsize)
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.
New in version 3.5.
void*PyMem_RawRealloc(void*p, size_tn)
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
,
or
.
If the request fails,
returns NULL and p remains a valid pointer to the previous memory area.
voidPyMem_RawFree(void*p)
Frees the memory block pointed to by p, which must have been returned by a previous call to
,
or
. Otherwise, or if PyMem_RawFree(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
uses the
.
Warning
The
must be held when using these functions.
Changed in version 3.6: The default allocator is now pymalloc instead of system malloc().
void*PyMem_Malloc(size_tn)
Part of the
.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_tnelem, size_telsize)
Part of the
since version 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.
New in version 3.5.
void*PyMem_Realloc(void*p, size_tn)
Part of the
.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
,
or
.
If the request fails,
returns NULL and p remains a valid pointer to the previous memory area.
voidPyMem_Free(void*p)
Part of the
.Frees the memory block pointed to by p, which must have been returned by a previous call to
,
or
. Otherwise, or if PyMem_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.
PyMem_New(TYPE, n)
Same as
, 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
, 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.
voidPyMem_Del(void*p)
Same as
.
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)
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.
Note
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
section.
The
uses the
.
Warning
The
must be held when using these functions.
void*PyObject_Malloc(size_tn)
Part of the
.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_tnelem, size_telsize)
Part of the
since version 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.
New in version 3.5.
void*PyObject_Realloc(void*p, size_tn)
Part of the
.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
,
or
.
If the request fails,
returns NULL and p remains a valid pointer to the previous memory area.
voidPyObject_Free(void*p)
Part of the
.Frees the memory block pointed to by p, which must have been returned by a previous call to
,
or
. 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
Name
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
environment variable.
malloc: system allocators from the standard C library, C functions: malloc(), calloc(), realloc() and free().
pymalloc:
.
“+ debug”: with
debug hooks on the Python memory allocators
.
“Debug build”:
.
Customize Memory Allocators
New in version 3.4.
typePyMemAllocatorEx
Structure used to describe a memory block allocator. The structure has the following fields:
Field
Meaning
void*ctx
user context passed as first argument
void*malloc(void*ctx,size_tsize)
allocate a memory block
void*calloc(void*ctx,size_tnelem,size_telsize)
allocate a memory block initialized with zeros
void*realloc(void*ctx,void*ptr,size_tnew_size)
allocate or resize a memory block
voidfree(void*ctx,void*ptr)
free a memory block
Changed in version 3.5: The PyMemAllocator structure was renamed to
and a new calloc field was added.
typePyMemAllocatorDomain
Enum used to identify an allocator domain. Domains:
PYMEM_DOMAIN_RAW
Functions:
PYMEM_DOMAIN_MEM
Functions:
,
PYMEM_DOMAIN_OBJ
Functions:
voidPyMem_GetAllocator(
domain,
*allocator)
Get the memory block allocator of the specified domain.
voidPyMem_SetAllocator(
domain,
*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
domain, the allocator must be thread-safe: the
is not held when the allocator is called.
If the new allocator is not a hook (does not call the previous allocator), the
function must be called to reinstall the debug hooks on top on the new allocator.
See also
and
Preinitialize Python with PyPreConfig
.
Warning
does have the following contract:
It can be called after
and before
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
has been called) the allocator must wrap the existing allocator. Substituting the current allocator for some other arbitrary one is not supported.
voidPyMem_SetupDebugHooks(void)
Setup
debug hooks in the Python memory allocators
to detect memory errors.
Debug hooks on the Python memory allocators
When
, the
function is called at the
to setup debug hooks on Python memory allocators to detect memory errors.
The
environment variable can be used to install debug hooks on a Python compiled in release mode (ex: PYTHONMALLOC=debug).
The
function can be used to set debug hooks after calling
.
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
is called on a memory block allocated by
.
Detect write before the start of the buffer (buffer underflow).
Detect write after the end of the buffer (buffer overflow).
Check that the
is held when allocator functions of
(ex:
) and
(ex:
) domains are called.
On error, the debug hooks use the
module to get the traceback where a memory block was allocated. The traceback is only displayed if
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
.
'm' for
.
'o' for
.
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).
Changed in version 3.6: The
function now also works on Python compiled in release mode. On error, the debug hooks now use
to get the traceback where a memory block was allocated. The debug hooks now also check if the GIL is held when functions of
and
domains are called.
Changed in version 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
and
for allocations larger than 512 bytes.
pymalloc is the
of the
(ex:
) and
(ex:
) 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
option. It can also be disabled at runtime using the
environment variable (ex: PYTHONMALLOC=malloc).
Customize pymalloc Arena Allocator
New in version 3.4.
typePyObjectArenaAllocator
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_tsize)
allocate an arena of size bytes
voidfree(void*ctx,void*ptr,size_tsize)
free an arena
voidPyObject_GetArenaAllocator(
*allocator)
Get the arena allocator.
voidPyObject_SetArenaAllocator(
*allocator)
Set the arena allocator.
tracemalloc C API
New in version 3.7.
intPyTraceMalloc_Track(unsignedintdomain, uintptr_tptr, size_tsize)
Track an allocated memory block in the
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.
intPyTraceMalloc_Untrack(unsignedintdomain, uintptr_tptr)
Untrack an allocated memory block in the
module. Do nothing if the block was not tracked.
Return -2 if tracemalloc is disabled, otherwise return 0.
Examples
Here is the example from section
, 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)returnPyErr_NoMemory();/* ...Do some I/O operation involving buf... */res=PyBytes_FromString(buf);PyMem_Free(buf);/* allocated with PyMem_Malloc */returnres;The same code using the type-oriented function set:
PyObject*res;char*buf=PyMem_New(char,BUFSIZ);/* for I/O */if(buf==NULL)returnPyErr_NoMemory();/* ...Do some I/O operation involving buf... */res=PyBytes_FromString(buf);PyMem_Del(buf);/* allocated with PyMem_New */returnres;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
,
and
.
These will be explained in the next chapter on defining and implementing new object types in C.