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)
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.
也參考
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.
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.
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 the GIL. 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 the GIL held. 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.
備註
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()
.
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.
在 3.4 版被加入.
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.
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.
在 3.5 版被加入.
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.
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.
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.
警告
The GIL must be held when using these functions.
在 3.6 版的變更: The default allocator is now pymalloc instead of system malloc()
.
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.
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.
在 3.5 版被加入.
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.
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.
The following type-oriented macros are provided for convenience. Note that TYPE refers to any C type.
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.
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.
和 PyMem_Free()
相同。
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)
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.
備註
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.
警告
The GIL must be held when using these functions.
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.
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.
在 3.5 版被加入.
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.
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:
配置 |
名稱 |
PyMem_RawMalloc |
PyMem_Malloc |
PyObject_Malloc |
---|---|---|---|---|
Release build |
|
|
|
|
Debug build |
|
|
|
|
Release build, without pymalloc |
|
|
|
|
Debug build, without pymalloc |
|
|
|
|
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.
mimalloc
: mimalloc memory allocator. The pymalloc
allocator will be used if mimalloc support isn't available.
"+ debug": with debug hooks on the Python memory allocators.
"Debug build": Python build in debug mode.
在 3.4 版被加入.
Structure used to describe a memory block allocator. The structure has the following fields:
欄位 |
意義 |
---|---|
|
user context passed as first argument |
|
allocate a memory block |
|
allocate a memory block initialized with zeros |
|
allocate or resize a memory block |
|
free a memory block |
在 3.5 版的變更: The PyMemAllocator
structure was renamed to
PyMemAllocatorEx
and a new calloc
field was added.
Enum used to identify an allocator domain. Domains:
函式:
函式:
函式:
Get the memory block allocator of the specified domain.
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.
警告
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 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.
在 3.12 版的變更: All allocators must be thread-safe.
Setup debug hooks in the Python memory allocators to detect memory errors.
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 檢查:
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 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.
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).
在 3.6 版的變更: 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.
在 3.8 版的變更: 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()
.
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()
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
).
在 3.4 版被加入.
Structure used to describe an arena allocator. The structure has three fields:
欄位 |
意義 |
---|---|
|
user context passed as first argument |
|
allocate an arena of size bytes |
|
free an arena |
Get the arena allocator.
Set the arena allocator.
在 3.13 版被加入.
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."
在 3.7 版被加入.
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.
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
.
Here is the example from section 總覽, 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.