• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1.. highlightlang:: c
2
3
4.. _memory:
5
6*****************
7Memory Management
8*****************
9
10.. sectionauthor:: Vladimir Marangozov <Vladimir.Marangozov@inrialpes.fr>
11
12
13
14.. _memoryoverview:
15
16Overview
17========
18
19Memory management in Python involves a private heap containing all Python
20objects and data structures. The management of this private heap is ensured
21internally by the *Python memory manager*.  The Python memory manager has
22different components which deal with various dynamic storage management aspects,
23like sharing, segmentation, preallocation or caching.
24
25At the lowest level, a raw memory allocator ensures that there is enough room in
26the private heap for storing all Python-related data by interacting with the
27memory manager of the operating system. On top of the raw memory allocator,
28several object-specific allocators operate on the same heap and implement
29distinct memory management policies adapted to the peculiarities of every object
30type. For example, integer objects are managed differently within the heap than
31strings, tuples or dictionaries because integers imply different storage
32requirements and speed/space tradeoffs. The Python memory manager thus delegates
33some of the work to the object-specific allocators, but ensures that the latter
34operate within the bounds of the private heap.
35
36It is important to understand that the management of the Python heap is
37performed by the interpreter itself and that the user has no control over it,
38even if she regularly manipulates object pointers to memory blocks inside that
39heap.  The allocation of heap space for Python objects and other internal
40buffers is performed on demand by the Python memory manager through the Python/C
41API functions listed in this document.
42
43.. index::
44   single: malloc()
45   single: calloc()
46   single: realloc()
47   single: free()
48
49To avoid memory corruption, extension writers should never try to operate on
50Python objects with the functions exported by the C library: :c:func:`malloc`,
51:c:func:`calloc`, :c:func:`realloc` and :c:func:`free`.  This will result in  mixed
52calls between the C allocator and the Python memory manager with fatal
53consequences, because they implement different algorithms and operate on
54different heaps.  However, one may safely allocate and release memory blocks
55with the C library allocator for individual purposes, as shown in the following
56example::
57
58   PyObject *res;
59   char *buf = (char *) malloc(BUFSIZ); /* for I/O */
60
61   if (buf == NULL)
62       return PyErr_NoMemory();
63   ...Do some I/O operation involving buf...
64   res = PyString_FromString(buf);
65   free(buf); /* malloc'ed */
66   return res;
67
68In this example, the memory request for the I/O buffer is handled by the C
69library allocator. The Python memory manager is involved only in the allocation
70of the string object returned as a result.
71
72In most situations, however, it is recommended to allocate memory from the
73Python heap specifically because the latter is under control of the Python
74memory manager. For example, this is required when the interpreter is extended
75with new object types written in C. Another reason for using the Python heap is
76the desire to *inform* the Python memory manager about the memory needs of the
77extension module. Even when the requested memory is used exclusively for
78internal, highly-specific purposes, delegating all memory requests to the Python
79memory manager causes the interpreter to have a more accurate image of its
80memory footprint as a whole. Consequently, under certain circumstances, the
81Python memory manager may or may not trigger appropriate actions, like garbage
82collection, memory compaction or other preventive procedures. Note that by using
83the C library allocator as shown in the previous example, the allocated memory
84for the I/O buffer escapes completely the Python memory manager.
85
86
87.. _memoryinterface:
88
89Memory Interface
90================
91
92The following function sets, modeled after the ANSI C standard, but specifying
93behavior when requesting zero bytes, are available for allocating and releasing
94memory from the Python heap:
95
96
97.. c:function:: void* PyMem_Malloc(size_t n)
98
99   Allocates *n* bytes and returns a pointer of type :c:type:`void\*` to the
100   allocated memory, or *NULL* if the request fails. Requesting zero bytes returns
101   a distinct non-*NULL* pointer if possible, as if ``PyMem_Malloc(1)`` had
102   been called instead. The memory will not have been initialized in any way.
103
104
105.. c:function:: void* PyMem_Realloc(void *p, size_t n)
106
107   Resizes the memory block pointed to by *p* to *n* bytes. The contents will be
108   unchanged to the minimum of the old and the new sizes. If *p* is *NULL*, the
109   call is equivalent to ``PyMem_Malloc(n)``; else if *n* is equal to zero,
110   the memory block is resized but is not freed, and the returned pointer is
111   non-*NULL*.  Unless *p* is *NULL*, it must have been returned by a previous call
112   to :c:func:`PyMem_Malloc` or :c:func:`PyMem_Realloc`. If the request fails,
113   :c:func:`PyMem_Realloc` returns *NULL* and *p* remains a valid pointer to the
114   previous memory area.
115
116
117.. c:function:: void PyMem_Free(void *p)
118
119   Frees the memory block pointed to by *p*, which must have been returned by a
120   previous call to :c:func:`PyMem_Malloc` or :c:func:`PyMem_Realloc`.  Otherwise, or
121   if ``PyMem_Free(p)`` has been called before, undefined behavior occurs. If
122   *p* is *NULL*, no operation is performed.
123
124The following type-oriented macros are provided for convenience.  Note  that
125*TYPE* refers to any C type.
126
127
128.. c:function:: TYPE* PyMem_New(TYPE, size_t n)
129
130   Same as :c:func:`PyMem_Malloc`, but allocates ``(n * sizeof(TYPE))`` bytes of
131   memory.  Returns a pointer cast to :c:type:`TYPE\*`.  The memory will not have
132   been initialized in any way.
133
134
135.. c:function:: TYPE* PyMem_Resize(void *p, TYPE, size_t n)
136
137   Same as :c:func:`PyMem_Realloc`, but the memory block is resized to ``(n *
138   sizeof(TYPE))`` bytes.  Returns a pointer cast to :c:type:`TYPE\*`. On return,
139   *p* will be a pointer to the new memory area, or *NULL* in the event of
140   failure.  This is a C preprocessor macro; p is always reassigned.  Save
141   the original value of p to avoid losing memory when handling errors.
142
143
144.. c:function:: void PyMem_Del(void *p)
145
146   Same as :c:func:`PyMem_Free`.
147
148In addition, the following macro sets are provided for calling the Python memory
149allocator directly, without involving the C API functions listed above. However,
150note that their use does not preserve binary compatibility across Python
151versions and is therefore deprecated in extension modules.
152
153:c:func:`PyMem_MALLOC`, :c:func:`PyMem_REALLOC`, :c:func:`PyMem_FREE`.
154
155:c:func:`PyMem_NEW`, :c:func:`PyMem_RESIZE`, :c:func:`PyMem_DEL`.
156
157
158.. _memoryexamples:
159
160Examples
161========
162
163Here is the example from section :ref:`memoryoverview`, rewritten so that the
164I/O buffer is allocated from the Python heap by using the first function set::
165
166   PyObject *res;
167   char *buf = (char *) PyMem_Malloc(BUFSIZ); /* for I/O */
168
169   if (buf == NULL)
170       return PyErr_NoMemory();
171   /* ...Do some I/O operation involving buf... */
172   res = PyString_FromString(buf);
173   PyMem_Free(buf); /* allocated with PyMem_Malloc */
174   return res;
175
176The same code using the type-oriented function set::
177
178   PyObject *res;
179   char *buf = PyMem_New(char, BUFSIZ); /* for I/O */
180
181   if (buf == NULL)
182       return PyErr_NoMemory();
183   /* ...Do some I/O operation involving buf... */
184   res = PyString_FromString(buf);
185   PyMem_Del(buf); /* allocated with PyMem_New */
186   return res;
187
188Note that in the two examples above, the buffer is always manipulated via
189functions belonging to the same set. Indeed, it is required to use the same
190memory API family for a given memory block, so that the risk of mixing different
191allocators is reduced to a minimum. The following code sequence contains two
192errors, one of which is labeled as *fatal* because it mixes two different
193allocators operating on different heaps. ::
194
195   char *buf1 = PyMem_New(char, BUFSIZ);
196   char *buf2 = (char *) malloc(BUFSIZ);
197   char *buf3 = (char *) PyMem_Malloc(BUFSIZ);
198   ...
199   PyMem_Del(buf3);  /* Wrong -- should be PyMem_Free() */
200   free(buf2);       /* Right -- allocated via malloc() */
201   free(buf1);       /* Fatal -- should be PyMem_Del()  */
202
203In addition to the functions aimed at handling raw memory blocks from the Python
204heap, objects in Python are allocated and released with :c:func:`PyObject_New`,
205:c:func:`PyObject_NewVar` and :c:func:`PyObject_Del`.
206
207These will be explained in the next chapter on defining and implementing new
208object types in C.
209
210