1991-02-19 12:39:46 +00:00
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/***********************************************************
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2000-06-30 23:50:40 +00:00
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Copyright (c) 2000, BeOpen.com.
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Copyright (c) 1995-2000, Corporation for National Research Initiatives.
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Copyright (c) 1990-1995, Stichting Mathematisch Centrum.
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All rights reserved.
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See the file "Misc/COPYRIGHT" for information on usage and
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redistribution of this file, and for a DISCLAIMER OF ALL WARRANTIES.
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1991-02-19 12:39:46 +00:00
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******************************************************************/
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2000-07-09 00:55:06 +00:00
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#ifndef Py_OBJIMPL_H
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#define Py_OBJIMPL_H
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2000-07-31 22:19:30 +00:00
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#include "pymem.h"
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2000-07-09 00:55:06 +00:00
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#ifdef __cplusplus
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extern "C" {
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#endif
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1990-10-14 12:07:46 +00:00
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/*
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2000-05-03 23:44:39 +00:00
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Functions and macros for modules that implement new object types.
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1990-10-14 12:07:46 +00:00
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You must first include "object.h".
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2000-05-03 23:44:39 +00:00
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- PyObject_New(type, typeobj) allocates memory for a new object of
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the given type; here 'type' must be the C structure type used to
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represent the object and 'typeobj' the address of the corresponding
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type object. Reference count and type pointer are filled in; the
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rest of the bytes of the object are *undefined*! The resulting
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expression type is 'type *'. The size of the object is actually
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determined by the tp_basicsize field of the type object.
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- PyObject_NewVar(type, typeobj, n) is similar but allocates a
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variable-size object with n extra items. The size is computed as
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tp_basicsize plus n * tp_itemsize. This fills in the ob_size field
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as well.
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- PyObject_Del(op) releases the memory allocated for an object.
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- PyObject_Init(op, typeobj) and PyObject_InitVar(op, typeobj, n) are
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similar to PyObject_{New, NewVar} except that they don't allocate
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the memory needed for an object. Instead of the 'type' parameter,
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they accept the pointer of a new object (allocated by an arbitrary
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allocator) and initialize its object header fields.
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Note that objects created with PyObject_{New, NewVar} are allocated
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within the Python heap by an object allocator, the latter being
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implemented (by default) on top of the Python raw memory
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allocator. This ensures that Python keeps control on the user's
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objects regarding their memory management; for instance, they may be
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subject to automatic garbage collection.
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In case a specific form of memory management is needed, implying that
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the objects would not reside in the Python heap (for example standard
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malloc heap(s) are mandatory, use of shared memory, C++ local storage
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or operator new), you must first allocate the object with your custom
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allocator, then pass its pointer to PyObject_{Init, InitVar} for
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filling in its Python-specific fields: reference count, type pointer,
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possibly others. You should be aware that Python has very limited
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control over these objects because they don't cooperate with the
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Python memory manager. Such objects may not be eligible for automatic
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garbage collection and you have to make sure that they are released
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accordingly whenever their destructor gets called (cf. the specific
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form of memory management you're using).
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Unless you have specific memory management requirements, it is
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recommended to use PyObject_{New, NewVar, Del}. */
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/*
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* Core object memory allocator
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* ============================
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*/
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1990-10-14 12:07:46 +00:00
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2000-07-10 04:30:56 +00:00
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/* The purpose of the object allocator is to make the distinction
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2000-05-03 23:44:39 +00:00
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between "object memory" and the rest within the Python heap.
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Object memory is the one allocated by PyObject_{New, NewVar}, i.e.
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the one that holds the object's representation defined by its C
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type structure, *excluding* any object-specific memory buffers that
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might be referenced by the structure (for type structures that have
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pointer fields). By default, the object memory allocator is
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implemented on top of the raw memory allocator.
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1990-10-14 12:07:46 +00:00
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2000-05-03 23:44:39 +00:00
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The PyCore_* macros can be defined to make the interpreter use a
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custom object memory allocator. They are reserved for internal
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memory management purposes exclusively. Both the core and extension
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modules should use the PyObject_* API. */
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#ifndef PyCore_OBJECT_MALLOC_FUNC
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#undef PyCore_OBJECT_REALLOC_FUNC
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#undef PyCore_OBJECT_FREE_FUNC
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#define PyCore_OBJECT_MALLOC_FUNC PyCore_MALLOC_FUNC
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#define PyCore_OBJECT_REALLOC_FUNC PyCore_REALLOC_FUNC
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#define PyCore_OBJECT_FREE_FUNC PyCore_FREE_FUNC
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#endif
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#ifndef PyCore_OBJECT_MALLOC_PROTO
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#undef PyCore_OBJECT_REALLOC_PROTO
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#undef PyCore_OBJECT_FREE_PROTO
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#define PyCore_OBJECT_MALLOC_PROTO PyCore_MALLOC_PROTO
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#define PyCore_OBJECT_REALLOC_PROTO PyCore_REALLOC_PROTO
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#define PyCore_OBJECT_FREE_PROTO PyCore_FREE_PROTO
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#endif
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#ifdef NEED_TO_DECLARE_OBJECT_MALLOC_AND_FRIEND
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2000-07-25 12:56:38 +00:00
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extern void *PyCore_OBJECT_MALLOC_FUNC PyCore_OBJECT_MALLOC_PROTO;
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extern void *PyCore_OBJECT_REALLOC_FUNC PyCore_OBJECT_REALLOC_PROTO;
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2000-05-03 23:44:39 +00:00
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extern void PyCore_OBJECT_FREE_FUNC PyCore_OBJECT_FREE_PROTO;
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#endif
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#ifndef PyCore_OBJECT_MALLOC
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#undef PyCore_OBJECT_REALLOC
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#undef PyCore_OBJECT_FREE
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#define PyCore_OBJECT_MALLOC(n) PyCore_OBJECT_MALLOC_FUNC(n)
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#define PyCore_OBJECT_REALLOC(p, n) PyCore_OBJECT_REALLOC_FUNC((p), (n))
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#define PyCore_OBJECT_FREE(p) PyCore_OBJECT_FREE_FUNC(p)
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#endif
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/*
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* Raw object memory interface
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* ===========================
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*/
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/* The use of this API should be avoided, unless a builtin object
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constructor inlines PyObject_{New, NewVar}, either because the
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latter functions cannot allocate the exact amount of needed memory,
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either for speed. This situation is exceptional, but occurs for
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some object constructors (PyBuffer_New, PyList_New...). Inlining
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PyObject_{New, NewVar} for objects that are supposed to belong to
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the Python heap is discouraged. If you really have to, make sure
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the object is initialized with PyObject_{Init, InitVar}. Do *not*
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inline PyObject_{Init, InitVar} for user-extension types or you
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might seriously interfere with Python's memory management. */
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/* Functions */
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/* Wrappers around PyCore_OBJECT_MALLOC and friends; useful if you
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need to be sure that you are using the same object memory allocator
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as Python. These wrappers *do not* make sure that allocating 0
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bytes returns a non-NULL pointer. Returned pointers must be checked
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for NULL explicitly; no action is performed on failure. */
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2000-07-25 12:56:38 +00:00
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extern DL_IMPORT(void *) PyObject_Malloc(size_t);
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extern DL_IMPORT(void *) PyObject_Realloc(void *, size_t);
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extern DL_IMPORT(void) PyObject_Free(void *);
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2000-05-03 23:44:39 +00:00
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/* Macros */
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#define PyObject_MALLOC(n) PyCore_OBJECT_MALLOC(n)
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2000-07-25 12:56:38 +00:00
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#define PyObject_REALLOC(op, n) PyCore_OBJECT_REALLOC((void *)(op), (n))
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#define PyObject_FREE(op) PyCore_OBJECT_FREE((void *)(op))
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2000-05-03 23:44:39 +00:00
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/*
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* Generic object allocator interface
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* ==================================
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*/
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/* Functions */
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2000-07-09 00:55:06 +00:00
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extern DL_IMPORT(PyObject *) PyObject_Init(PyObject *, PyTypeObject *);
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extern DL_IMPORT(PyVarObject *) PyObject_InitVar(PyVarObject *,
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PyTypeObject *, int);
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extern DL_IMPORT(PyObject *) _PyObject_New(PyTypeObject *);
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extern DL_IMPORT(PyVarObject *) _PyObject_NewVar(PyTypeObject *, int);
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extern DL_IMPORT(void) _PyObject_Del(PyObject *);
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2000-05-03 23:44:39 +00:00
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#define PyObject_New(type, typeobj) \
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( (type *) _PyObject_New(typeobj) )
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#define PyObject_NewVar(type, typeobj, n) \
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( (type *) _PyObject_NewVar((typeobj), (n)) )
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#define PyObject_Del(op) _PyObject_Del((PyObject *)(op))
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/* Macros trading binary compatibility for speed. See also mymalloc.h.
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Note that these macros expect non-NULL object pointers.*/
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#define PyObject_INIT(op, typeobj) \
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( (op)->ob_type = (typeobj), _Py_NewReference((PyObject *)(op)), (op) )
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#define PyObject_INIT_VAR(op, typeobj, size) \
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( (op)->ob_size = (size), PyObject_INIT((op), (typeobj)) )
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#define _PyObject_SIZE(typeobj) ( (typeobj)->tp_basicsize )
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#define _PyObject_VAR_SIZE(typeobj, n) \
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( (typeobj)->tp_basicsize + (n) * (typeobj)->tp_itemsize )
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#define PyObject_NEW(type, typeobj) \
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( (type *) PyObject_Init( \
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(PyObject *) PyObject_MALLOC( _PyObject_SIZE(typeobj) ), (typeobj)) )
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#define PyObject_NEW_VAR(type, typeobj, n) \
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( (type *) PyObject_InitVar( \
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(PyVarObject *) PyObject_MALLOC( _PyObject_VAR_SIZE((typeobj),(n)) ),\
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(typeobj), (n)) )
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2000-07-01 01:00:38 +00:00
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#define PyObject_DEL(op) PyObject_FREE(op)
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2000-05-03 23:44:39 +00:00
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/* This example code implements an object constructor with a custom
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allocator, where PyObject_New is inlined, and shows the important
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distinction between two steps (at least):
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1) the actual allocation of the object storage;
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2) the initialization of the Python specific fields
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in this storage with PyObject_{Init, InitVar}.
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PyObject *
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YourObject_New(...)
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{
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PyObject *op;
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1990-10-14 12:07:46 +00:00
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2000-05-03 23:44:39 +00:00
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op = (PyObject *) Your_Allocator(_PyObject_SIZE(YourTypeStruct));
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if (op == NULL)
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return PyErr_NoMemory();
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1993-07-28 09:05:47 +00:00
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2000-05-03 23:44:39 +00:00
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op = PyObject_Init(op, &YourTypeStruct);
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if (op == NULL)
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return NULL;
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1996-07-21 02:23:54 +00:00
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2000-05-03 23:44:39 +00:00
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op->ob_field = value;
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...
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return op;
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}
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1996-07-21 02:23:54 +00:00
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2000-05-03 23:44:39 +00:00
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Note that in C++, the use of the new operator usually implies that
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the 1st step is performed automatically for you, so in a C++ class
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constructor you would start directly with PyObject_Init/InitVar. */
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1996-07-21 02:23:54 +00:00
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2000-06-30 05:02:53 +00:00
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/*
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* Garbage Collection Support
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* ==========================
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*/
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2000-06-23 19:37:02 +00:00
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2000-06-30 05:02:53 +00:00
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/* To make a new object participate in garbage collection use
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PyObject_{New, VarNew, Del} to manage the memory. Set the type flag
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Py_TPFLAGS_GC and define the type method tp_recurse. You should also
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add the method tp_clear if your object is mutable. Include
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2000-07-01 01:00:38 +00:00
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PyGC_HEAD_SIZE in the calculation of tp_basicsize. Call
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2000-06-30 05:02:53 +00:00
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PyObject_GC_Init after the pointers followed by tp_recurse become
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valid (usually just before returning the object from the allocation
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method. Call PyObject_GC_Fini before those pointers become invalid
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(usually at the top of the deallocation method). */
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2000-06-23 19:37:02 +00:00
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#ifndef WITH_CYCLE_GC
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2000-06-30 05:02:53 +00:00
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#define PyGC_HEAD_SIZE 0
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#define PyObject_GC_Init(op)
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#define PyObject_GC_Fini(op)
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#define PyObject_AS_GC(op) (op)
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#define PyObject_FROM_GC(op) (op)
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#else
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/* Add the object into the container set */
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2000-07-09 00:55:06 +00:00
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extern DL_IMPORT(void) _PyGC_Insert(PyObject *);
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2000-06-30 05:02:53 +00:00
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/* Remove the object from the container set */
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2000-07-09 00:55:06 +00:00
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extern DL_IMPORT(void) _PyGC_Remove(PyObject *);
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2000-06-30 05:02:53 +00:00
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#define PyObject_GC_Init(op) _PyGC_Insert((PyObject *)op)
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#define PyObject_GC_Fini(op) _PyGC_Remove((PyObject *)op)
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/* Structure *prefixed* to container objects participating in GC */
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typedef struct _gc_head {
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struct _gc_head *gc_next;
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struct _gc_head *gc_prev;
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int gc_refs;
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} PyGC_Head;
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#define PyGC_HEAD_SIZE sizeof(PyGC_Head)
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/* Test if a type has a GC head */
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#define PyType_IS_GC(t) PyType_HasFeature((t), Py_TPFLAGS_GC)
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/* Test if an object has a GC head */
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#define PyObject_IS_GC(o) PyType_IS_GC((o)->ob_type)
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/* Get an object's GC head */
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#define PyObject_AS_GC(o) ((PyGC_Head *)(o)-1)
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/* Get the object given the PyGC_Head */
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#define PyObject_FROM_GC(g) ((PyObject *)(((PyGC_Head *)g)+1))
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#endif /* WITH_CYCLE_GC */
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2000-06-23 19:37:02 +00:00
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1993-07-28 09:05:47 +00:00
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#ifdef __cplusplus
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}
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#endif
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#endif /* !Py_OBJIMPL_H */
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