210 lines
8.4 KiB
ReStructuredText
210 lines
8.4 KiB
ReStructuredText
.. highlightlang:: c
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.. _memory:
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*****************
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Memory Management
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*****************
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.. sectionauthor:: Vladimir Marangozov <Vladimir.Marangozov@inrialpes.fr>
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.. _memoryoverview:
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Overview
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========
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Memory management in Python involves a private heap containing all Python
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objects and data structures. The management of this private heap is ensured
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internally by the *Python memory manager*. The Python memory manager has
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different components which deal with various dynamic storage management aspects,
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like sharing, segmentation, preallocation or caching.
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At the lowest level, a raw memory allocator ensures that there is enough room in
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the private heap for storing all Python-related data by interacting with the
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memory manager of the operating system. On top of the raw memory allocator,
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several object-specific allocators operate on the same heap and implement
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distinct memory management policies adapted to the peculiarities of every object
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type. For example, integer objects are managed differently within the heap than
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strings, tuples or dictionaries because integers imply different storage
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requirements and speed/space tradeoffs. The Python memory manager thus delegates
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some of the work to the object-specific allocators, but ensures that the latter
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operate within the bounds of the private heap.
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It is important to understand that the management of the Python heap is
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performed by the interpreter itself and that the user has no control over it,
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even if she regularly manipulates object pointers to memory blocks inside that
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heap. The allocation of heap space for Python objects and other internal
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buffers is performed on demand by the Python memory manager through the Python/C
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API functions listed in this document.
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.. index::
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single: malloc()
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single: calloc()
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single: realloc()
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single: free()
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To avoid memory corruption, extension writers should never try to operate on
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Python objects with the functions exported by the C library: :cfunc:`malloc`,
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:cfunc:`calloc`, :cfunc:`realloc` and :cfunc:`free`. This will result in mixed
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calls between the C allocator and the Python memory manager with fatal
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consequences, because they implement different algorithms and operate on
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different heaps. However, one may safely allocate and release memory blocks
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with the C library allocator for individual purposes, as shown in the following
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example::
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PyObject *res;
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char *buf = (char *) malloc(BUFSIZ); /* for I/O */
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if (buf == NULL)
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return PyErr_NoMemory();
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...Do some I/O operation involving buf...
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res = PyString_FromString(buf);
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free(buf); /* malloc'ed */
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return res;
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In this example, the memory request for the I/O buffer is handled by the C
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library allocator. The Python memory manager is involved only in the allocation
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of the string object returned as a result.
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In most situations, however, it is recommended to allocate memory from the
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Python heap specifically because the latter is under control of the Python
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memory manager. For example, this is required when the interpreter is extended
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with new object types written in C. Another reason for using the Python heap is
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the desire to *inform* the Python memory manager about the memory needs of the
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extension module. Even when the requested memory is used exclusively for
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internal, highly-specific purposes, delegating all memory requests to the Python
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memory manager causes the interpreter to have a more accurate image of its
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memory footprint as a whole. Consequently, under certain circumstances, the
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Python memory manager may or may not trigger appropriate actions, like garbage
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collection, memory compaction or other preventive procedures. Note that by using
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the C library allocator as shown in the previous example, the allocated memory
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for the I/O buffer escapes completely the Python memory manager.
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.. _memoryinterface:
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Memory Interface
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================
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The following function sets, modeled after the ANSI C standard, but specifying
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behavior when requesting zero bytes, are available for allocating and releasing
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memory from the Python heap:
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.. cfunction:: void* PyMem_Malloc(size_t n)
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Allocates *n* bytes and returns a pointer of type :ctype:`void\*` to the
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allocated memory, or *NULL* if the request fails. Requesting zero bytes returns
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a distinct non-*NULL* pointer if possible, as if :cfunc:`PyMem_Malloc(1)` had
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been called instead. The memory will not have been initialized in any way.
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.. cfunction:: void* PyMem_Realloc(void *p, size_t n)
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Resizes the memory block pointed to by *p* to *n* bytes. The contents will be
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unchanged to the minimum of the old and the new sizes. If *p* is *NULL*, the
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call is equivalent to :cfunc:`PyMem_Malloc(n)`; else if *n* is equal to zero,
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the memory block is resized but is not freed, and the returned pointer is
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non-*NULL*. Unless *p* is *NULL*, it must have been returned by a previous call
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to :cfunc:`PyMem_Malloc` or :cfunc:`PyMem_Realloc`. If the request fails,
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:cfunc:`PyMem_Realloc` returns *NULL* and *p* remains a valid pointer to the
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previous memory area.
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.. cfunction:: void PyMem_Free(void *p)
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Frees the memory block pointed to by *p*, which must have been returned by a
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previous call to :cfunc:`PyMem_Malloc` or :cfunc:`PyMem_Realloc`. Otherwise, or
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if :cfunc:`PyMem_Free(p)` has been called before, undefined behavior occurs. If
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*p* is *NULL*, no operation is performed.
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The following type-oriented macros are provided for convenience. Note that
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*TYPE* refers to any C type.
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.. cfunction:: TYPE* PyMem_New(TYPE, size_t n)
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Same as :cfunc:`PyMem_Malloc`, but allocates ``(n * sizeof(TYPE))`` bytes of
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memory. Returns a pointer cast to :ctype:`TYPE\*`. The memory will not have
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been initialized in any way.
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.. cfunction:: TYPE* PyMem_Resize(void *p, TYPE, size_t n)
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Same as :cfunc:`PyMem_Realloc`, but the memory block is resized to ``(n *
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sizeof(TYPE))`` bytes. Returns a pointer cast to :ctype:`TYPE\*`. On return,
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*p* will be a pointer to the new memory area, or *NULL* in the event of
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failure. This is a C preprocessor macro; p is always reassigned. Save
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the original value of p to avoid losing memory when handling errors.
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.. cfunction:: void PyMem_Del(void *p)
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Same as :cfunc:`PyMem_Free`.
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In addition, the following macro sets are provided for calling the Python memory
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allocator directly, without involving the C API functions listed above. However,
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note that their use does not preserve binary compatibility across Python
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versions and is therefore deprecated in extension modules.
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:cfunc:`PyMem_MALLOC`, :cfunc:`PyMem_REALLOC`, :cfunc:`PyMem_FREE`.
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:cfunc:`PyMem_NEW`, :cfunc:`PyMem_RESIZE`, :cfunc:`PyMem_DEL`.
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.. _memoryexamples:
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Examples
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========
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Here is the example from section :ref:`memoryoverview`, rewritten so that the
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I/O buffer is allocated from the Python heap by using the first function set::
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PyObject *res;
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char *buf = (char *) PyMem_Malloc(BUFSIZ); /* for I/O */
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if (buf == NULL)
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return PyErr_NoMemory();
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/* ...Do some I/O operation involving buf... */
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res = PyString_FromString(buf);
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PyMem_Free(buf); /* allocated with PyMem_Malloc */
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return res;
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The same code using the type-oriented function set::
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PyObject *res;
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char *buf = PyMem_New(char, BUFSIZ); /* for I/O */
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if (buf == NULL)
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return PyErr_NoMemory();
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/* ...Do some I/O operation involving buf... */
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res = PyString_FromString(buf);
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PyMem_Del(buf); /* allocated with PyMem_New */
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return res;
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Note that in the two examples above, the buffer is always manipulated via
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functions belonging to the same set. Indeed, it is required to use the same
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memory API family for a given memory block, so that the risk of mixing different
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allocators is reduced to a minimum. The following code sequence contains two
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errors, one of which is labeled as *fatal* because it mixes two different
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allocators operating on different heaps. ::
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char *buf1 = PyMem_New(char, BUFSIZ);
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char *buf2 = (char *) malloc(BUFSIZ);
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char *buf3 = (char *) PyMem_Malloc(BUFSIZ);
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...
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PyMem_Del(buf3); /* Wrong -- should be PyMem_Free() */
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free(buf2); /* Right -- allocated via malloc() */
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free(buf1); /* Fatal -- should be PyMem_Del() */
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In addition to the functions aimed at handling raw memory blocks from the Python
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heap, objects in Python are allocated and released with :cfunc:`PyObject_New`,
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:cfunc:`PyObject_NewVar` and :cfunc:`PyObject_Del`.
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These will be explained in the next chapter on defining and implementing new
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object types in C.
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