| .. highlightlang:: c |
| |
| |
| .. _defining-new-types: |
| |
| ****************** |
| Defining New Types |
| ****************** |
| |
| .. sectionauthor:: Michael Hudson <mwh@python.net> |
| .. sectionauthor:: Dave Kuhlman <dkuhlman@rexx.com> |
| .. sectionauthor:: Jim Fulton <jim@zope.com> |
| |
| |
| As mentioned in the last chapter, Python allows the writer of an extension |
| module to define new types that can be manipulated from Python code, much like |
| strings and lists in core Python. |
| |
| This is not hard; the code for all extension types follows a pattern, but there |
| are some details that you need to understand before you can get started. |
| |
| |
| .. _dnt-basics: |
| |
| The Basics |
| ========== |
| |
| The Python runtime sees all Python objects as variables of type |
| :ctype:`PyObject\*`. A :ctype:`PyObject` is not a very magnificent object - it |
| just contains the refcount and a pointer to the object's "type object". This is |
| where the action is; the type object determines which (C) functions get called |
| when, for instance, an attribute gets looked up on an object or it is multiplied |
| by another object. These C functions are called "type methods" to distinguish |
| them from things like ``[].append`` (which we call "object methods"). |
| |
| So, if you want to define a new object type, you need to create a new type |
| object. |
| |
| This sort of thing can only be explained by example, so here's a minimal, but |
| complete, module that defines a new type: |
| |
| .. literalinclude:: ../includes/noddy.c |
| |
| |
| Now that's quite a bit to take in at once, but hopefully bits will seem familiar |
| from the last chapter. |
| |
| The first bit that will be new is:: |
| |
| typedef struct { |
| PyObject_HEAD |
| } noddy_NoddyObject; |
| |
| This is what a Noddy object will contain---in this case, nothing more than every |
| Python object contains, namely a refcount and a pointer to a type object. These |
| are the fields the ``PyObject_HEAD`` macro brings in. The reason for the macro |
| is to standardize the layout and to enable special debugging fields in debug |
| builds. Note that there is no semicolon after the ``PyObject_HEAD`` macro; one |
| is included in the macro definition. Be wary of adding one by accident; it's |
| easy to do from habit, and your compiler might not complain, but someone else's |
| probably will! (On Windows, MSVC is known to call this an error and refuse to |
| compile the code.) |
| |
| For contrast, let's take a look at the corresponding definition for standard |
| Python floats:: |
| |
| typedef struct { |
| PyObject_HEAD |
| double ob_fval; |
| } PyFloatObject; |
| |
| Moving on, we come to the crunch --- the type object. :: |
| |
| static PyTypeObject noddy_NoddyType = { |
| PyVarObject_HEAD_INIT(NULL, 0) |
| "noddy.Noddy", /* tp_name */ |
| sizeof(noddy_NoddyObject), /* tp_basicsize */ |
| 0, /* tp_itemsize */ |
| 0, /* tp_dealloc */ |
| 0, /* tp_print */ |
| 0, /* tp_getattr */ |
| 0, /* tp_setattr */ |
| 0, /* tp_reserved */ |
| 0, /* tp_repr */ |
| 0, /* tp_as_number */ |
| 0, /* tp_as_sequence */ |
| 0, /* tp_as_mapping */ |
| 0, /* tp_hash */ |
| 0, /* tp_call */ |
| 0, /* tp_str */ |
| 0, /* tp_getattro */ |
| 0, /* tp_setattro */ |
| 0, /* tp_as_buffer */ |
| Py_TPFLAGS_DEFAULT, /* tp_flags */ |
| "Noddy objects", /* tp_doc */ |
| }; |
| |
| Now if you go and look up the definition of :ctype:`PyTypeObject` in |
| :file:`object.h` you'll see that it has many more fields that the definition |
| above. The remaining fields will be filled with zeros by the C compiler, and |
| it's common practice to not specify them explicitly unless you need them. |
| |
| This is so important that we're going to pick the top of it apart still |
| further:: |
| |
| PyVarObject_HEAD_INIT(NULL, 0) |
| |
| This line is a bit of a wart; what we'd like to write is:: |
| |
| PyVarObject_HEAD_INIT(&PyType_Type, 0) |
| |
| as the type of a type object is "type", but this isn't strictly conforming C and |
| some compilers complain. Fortunately, this member will be filled in for us by |
| :cfunc:`PyType_Ready`. :: |
| |
| "noddy.Noddy", /* tp_name */ |
| |
| The name of our type. This will appear in the default textual representation of |
| our objects and in some error messages, for example:: |
| |
| >>> "" + noddy.new_noddy() |
| Traceback (most recent call last): |
| File "<stdin>", line 1, in ? |
| TypeError: cannot add type "noddy.Noddy" to string |
| |
| Note that the name is a dotted name that includes both the module name and the |
| name of the type within the module. The module in this case is :mod:`noddy` and |
| the type is :class:`Noddy`, so we set the type name to :class:`noddy.Noddy`. :: |
| |
| sizeof(noddy_NoddyObject), /* tp_basicsize */ |
| |
| This is so that Python knows how much memory to allocate when you call |
| :cfunc:`PyObject_New`. |
| |
| .. note:: |
| |
| If you want your type to be subclassable from Python, and your type has the same |
| :attr:`tp_basicsize` as its base type, you may have problems with multiple |
| inheritance. A Python subclass of your type will have to list your type first |
| in its :attr:`__bases__`, or else it will not be able to call your type's |
| :meth:`__new__` method without getting an error. You can avoid this problem by |
| ensuring that your type has a larger value for :attr:`tp_basicsize` than its |
| base type does. Most of the time, this will be true anyway, because either your |
| base type will be :class:`object`, or else you will be adding data members to |
| your base type, and therefore increasing its size. |
| |
| :: |
| |
| 0, /* tp_itemsize */ |
| |
| This has to do with variable length objects like lists and strings. Ignore this |
| for now. |
| |
| Skipping a number of type methods that we don't provide, we set the class flags |
| to :const:`Py_TPFLAGS_DEFAULT`. :: |
| |
| Py_TPFLAGS_DEFAULT, /* tp_flags */ |
| |
| All types should include this constant in their flags. It enables all of the |
| members defined by the current version of Python. |
| |
| We provide a doc string for the type in :attr:`tp_doc`. :: |
| |
| "Noddy objects", /* tp_doc */ |
| |
| Now we get into the type methods, the things that make your objects different |
| from the others. We aren't going to implement any of these in this version of |
| the module. We'll expand this example later to have more interesting behavior. |
| |
| For now, all we want to be able to do is to create new :class:`Noddy` objects. |
| To enable object creation, we have to provide a :attr:`tp_new` implementation. |
| In this case, we can just use the default implementation provided by the API |
| function :cfunc:`PyType_GenericNew`. We'd like to just assign this to the |
| :attr:`tp_new` slot, but we can't, for portability sake, On some platforms or |
| compilers, we can't statically initialize a structure member with a function |
| defined in another C module, so, instead, we'll assign the :attr:`tp_new` slot |
| in the module initialization function just before calling |
| :cfunc:`PyType_Ready`:: |
| |
| noddy_NoddyType.tp_new = PyType_GenericNew; |
| if (PyType_Ready(&noddy_NoddyType) < 0) |
| return; |
| |
| All the other type methods are *NULL*, so we'll go over them later --- that's |
| for a later section! |
| |
| Everything else in the file should be familiar, except for some code in |
| :cfunc:`PyInit_noddy`:: |
| |
| if (PyType_Ready(&noddy_NoddyType) < 0) |
| return; |
| |
| This initializes the :class:`Noddy` type, filing in a number of members, |
| including :attr:`ob_type` that we initially set to *NULL*. :: |
| |
| PyModule_AddObject(m, "Noddy", (PyObject *)&noddy_NoddyType); |
| |
| This adds the type to the module dictionary. This allows us to create |
| :class:`Noddy` instances by calling the :class:`Noddy` class:: |
| |
| >>> import noddy |
| >>> mynoddy = noddy.Noddy() |
| |
| That's it! All that remains is to build it; put the above code in a file called |
| :file:`noddy.c` and :: |
| |
| from distutils.core import setup, Extension |
| setup(name="noddy", version="1.0", |
| ext_modules=[Extension("noddy", ["noddy.c"])]) |
| |
| in a file called :file:`setup.py`; then typing :: |
| |
| $ python setup.py build |
| |
| at a shell should produce a file :file:`noddy.so` in a subdirectory; move to |
| that directory and fire up Python --- you should be able to ``import noddy`` and |
| play around with Noddy objects. |
| |
| That wasn't so hard, was it? |
| |
| Of course, the current Noddy type is pretty uninteresting. It has no data and |
| doesn't do anything. It can't even be subclassed. |
| |
| |
| Adding data and methods to the Basic example |
| -------------------------------------------- |
| |
| Let's expend the basic example to add some data and methods. Let's also make |
| the type usable as a base class. We'll create a new module, :mod:`noddy2` that |
| adds these capabilities: |
| |
| .. literalinclude:: ../includes/noddy2.c |
| |
| |
| This version of the module has a number of changes. |
| |
| We've added an extra include:: |
| |
| #include <structmember.h> |
| |
| This include provides declarations that we use to handle attributes, as |
| described a bit later. |
| |
| The name of the :class:`Noddy` object structure has been shortened to |
| :class:`Noddy`. The type object name has been shortened to :class:`NoddyType`. |
| |
| The :class:`Noddy` type now has three data attributes, *first*, *last*, and |
| *number*. The *first* and *last* variables are Python strings containing first |
| and last names. The *number* attribute is an integer. |
| |
| The object structure is updated accordingly:: |
| |
| typedef struct { |
| PyObject_HEAD |
| PyObject *first; |
| PyObject *last; |
| int number; |
| } Noddy; |
| |
| Because we now have data to manage, we have to be more careful about object |
| allocation and deallocation. At a minimum, we need a deallocation method:: |
| |
| static void |
| Noddy_dealloc(Noddy* self) |
| { |
| Py_XDECREF(self->first); |
| Py_XDECREF(self->last); |
| Py_TYPE(self)->tp_free((PyObject*)self); |
| } |
| |
| which is assigned to the :attr:`tp_dealloc` member:: |
| |
| (destructor)Noddy_dealloc, /*tp_dealloc*/ |
| |
| This method decrements the reference counts of the two Python attributes. We use |
| :cfunc:`Py_XDECREF` here because the :attr:`first` and :attr:`last` members |
| could be *NULL*. It then calls the :attr:`tp_free` member of the object's type |
| to free the object's memory. Note that the object's type might not be |
| :class:`NoddyType`, because the object may be an instance of a subclass. |
| |
| We want to make sure that the first and last names are initialized to empty |
| strings, so we provide a new method:: |
| |
| static PyObject * |
| Noddy_new(PyTypeObject *type, PyObject *args, PyObject *kwds) |
| { |
| Noddy *self; |
| |
| self = (Noddy *)type->tp_alloc(type, 0); |
| if (self != NULL) { |
| self->first = PyString_FromString(""); |
| if (self->first == NULL) |
| { |
| Py_DECREF(self); |
| return NULL; |
| } |
| |
| self->last = PyString_FromString(""); |
| if (self->last == NULL) |
| { |
| Py_DECREF(self); |
| return NULL; |
| } |
| |
| self->number = 0; |
| } |
| |
| return (PyObject *)self; |
| } |
| |
| and install it in the :attr:`tp_new` member:: |
| |
| Noddy_new, /* tp_new */ |
| |
| The new member is responsible for creating (as opposed to initializing) objects |
| of the type. It is exposed in Python as the :meth:`__new__` method. See the |
| paper titled "Unifying types and classes in Python" for a detailed discussion of |
| the :meth:`__new__` method. One reason to implement a new method is to assure |
| the initial values of instance variables. In this case, we use the new method |
| to make sure that the initial values of the members :attr:`first` and |
| :attr:`last` are not *NULL*. If we didn't care whether the initial values were |
| *NULL*, we could have used :cfunc:`PyType_GenericNew` as our new method, as we |
| did before. :cfunc:`PyType_GenericNew` initializes all of the instance variable |
| members to *NULL*. |
| |
| The new method is a static method that is passed the type being instantiated and |
| any arguments passed when the type was called, and that returns the new object |
| created. New methods always accept positional and keyword arguments, but they |
| often ignore the arguments, leaving the argument handling to initializer |
| methods. Note that if the type supports subclassing, the type passed may not be |
| the type being defined. The new method calls the tp_alloc slot to allocate |
| memory. We don't fill the :attr:`tp_alloc` slot ourselves. Rather |
| :cfunc:`PyType_Ready` fills it for us by inheriting it from our base class, |
| which is :class:`object` by default. Most types use the default allocation. |
| |
| .. note:: |
| |
| If you are creating a co-operative :attr:`tp_new` (one that calls a base type's |
| :attr:`tp_new` or :meth:`__new__`), you must *not* try to determine what method |
| to call using method resolution order at runtime. Always statically determine |
| what type you are going to call, and call its :attr:`tp_new` directly, or via |
| ``type->tp_base->tp_new``. If you do not do this, Python subclasses of your |
| type that also inherit from other Python-defined classes may not work correctly. |
| (Specifically, you may not be able to create instances of such subclasses |
| without getting a :exc:`TypeError`.) |
| |
| We provide an initialization function:: |
| |
| static int |
| Noddy_init(Noddy *self, PyObject *args, PyObject *kwds) |
| { |
| PyObject *first=NULL, *last=NULL, *tmp; |
| |
| static char *kwlist[] = {"first", "last", "number", NULL}; |
| |
| if (! PyArg_ParseTupleAndKeywords(args, kwds, "|OOi", kwlist, |
| &first, &last, |
| &self->number)) |
| return -1; |
| |
| if (first) { |
| tmp = self->first; |
| Py_INCREF(first); |
| self->first = first; |
| Py_XDECREF(tmp); |
| } |
| |
| if (last) { |
| tmp = self->last; |
| Py_INCREF(last); |
| self->last = last; |
| Py_XDECREF(tmp); |
| } |
| |
| return 0; |
| } |
| |
| by filling the :attr:`tp_init` slot. :: |
| |
| (initproc)Noddy_init, /* tp_init */ |
| |
| The :attr:`tp_init` slot is exposed in Python as the :meth:`__init__` method. It |
| is used to initialize an object after it's created. Unlike the new method, we |
| can't guarantee that the initializer is called. The initializer isn't called |
| when unpickling objects and it can be overridden. Our initializer accepts |
| arguments to provide initial values for our instance. Initializers always accept |
| positional and keyword arguments. |
| |
| Initializers can be called multiple times. Anyone can call the :meth:`__init__` |
| method on our objects. For this reason, we have to be extra careful when |
| assigning the new values. We might be tempted, for example to assign the |
| :attr:`first` member like this:: |
| |
| if (first) { |
| Py_XDECREF(self->first); |
| Py_INCREF(first); |
| self->first = first; |
| } |
| |
| But this would be risky. Our type doesn't restrict the type of the |
| :attr:`first` member, so it could be any kind of object. It could have a |
| destructor that causes code to be executed that tries to access the |
| :attr:`first` member. To be paranoid and protect ourselves against this |
| possibility, we almost always reassign members before decrementing their |
| reference counts. When don't we have to do this? |
| |
| * when we absolutely know that the reference count is greater than 1 |
| |
| * when we know that deallocation of the object [#]_ will not cause any calls |
| back into our type's code |
| |
| * when decrementing a reference count in a :attr:`tp_dealloc` handler when |
| garbage-collections is not supported [#]_ |
| |
| We want to expose our instance variables as attributes. There are a |
| number of ways to do that. The simplest way is to define member definitions:: |
| |
| static PyMemberDef Noddy_members[] = { |
| {"first", T_OBJECT_EX, offsetof(Noddy, first), 0, |
| "first name"}, |
| {"last", T_OBJECT_EX, offsetof(Noddy, last), 0, |
| "last name"}, |
| {"number", T_INT, offsetof(Noddy, number), 0, |
| "noddy number"}, |
| {NULL} /* Sentinel */ |
| }; |
| |
| and put the definitions in the :attr:`tp_members` slot:: |
| |
| Noddy_members, /* tp_members */ |
| |
| Each member definition has a member name, type, offset, access flags and |
| documentation string. See the :ref:`Generic-Attribute-Management` section below for |
| details. |
| |
| A disadvantage of this approach is that it doesn't provide a way to restrict the |
| types of objects that can be assigned to the Python attributes. We expect the |
| first and last names to be strings, but any Python objects can be assigned. |
| Further, the attributes can be deleted, setting the C pointers to *NULL*. Even |
| though we can make sure the members are initialized to non-*NULL* values, the |
| members can be set to *NULL* if the attributes are deleted. |
| |
| We define a single method, :meth:`name`, that outputs the objects name as the |
| concatenation of the first and last names. :: |
| |
| static PyObject * |
| Noddy_name(Noddy* self) |
| { |
| static PyObject *format = NULL; |
| PyObject *args, *result; |
| |
| if (format == NULL) { |
| format = PyString_FromString("%s %s"); |
| if (format == NULL) |
| return NULL; |
| } |
| |
| if (self->first == NULL) { |
| PyErr_SetString(PyExc_AttributeError, "first"); |
| return NULL; |
| } |
| |
| if (self->last == NULL) { |
| PyErr_SetString(PyExc_AttributeError, "last"); |
| return NULL; |
| } |
| |
| args = Py_BuildValue("OO", self->first, self->last); |
| if (args == NULL) |
| return NULL; |
| |
| result = PyString_Format(format, args); |
| Py_DECREF(args); |
| |
| return result; |
| } |
| |
| The method is implemented as a C function that takes a :class:`Noddy` (or |
| :class:`Noddy` subclass) instance as the first argument. Methods always take an |
| instance as the first argument. Methods often take positional and keyword |
| arguments as well, but in this cased we don't take any and don't need to accept |
| a positional argument tuple or keyword argument dictionary. This method is |
| equivalent to the Python method:: |
| |
| def name(self): |
| return "%s %s" % (self.first, self.last) |
| |
| Note that we have to check for the possibility that our :attr:`first` and |
| :attr:`last` members are *NULL*. This is because they can be deleted, in which |
| case they are set to *NULL*. It would be better to prevent deletion of these |
| attributes and to restrict the attribute values to be strings. We'll see how to |
| do that in the next section. |
| |
| Now that we've defined the method, we need to create an array of method |
| definitions:: |
| |
| static PyMethodDef Noddy_methods[] = { |
| {"name", (PyCFunction)Noddy_name, METH_NOARGS, |
| "Return the name, combining the first and last name" |
| }, |
| {NULL} /* Sentinel */ |
| }; |
| |
| and assign them to the :attr:`tp_methods` slot:: |
| |
| Noddy_methods, /* tp_methods */ |
| |
| Note that we used the :const:`METH_NOARGS` flag to indicate that the method is |
| passed no arguments. |
| |
| Finally, we'll make our type usable as a base class. We've written our methods |
| carefully so far so that they don't make any assumptions about the type of the |
| object being created or used, so all we need to do is to add the |
| :const:`Py_TPFLAGS_BASETYPE` to our class flag definition:: |
| |
| Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE, /*tp_flags*/ |
| |
| We rename :cfunc:`PyInit_noddy` to :cfunc:`PyInit_noddy2` and update the module |
| name in the :ctype:`PyModuleDef` struct. |
| |
| Finally, we update our :file:`setup.py` file to build the new module:: |
| |
| from distutils.core import setup, Extension |
| setup(name="noddy", version="1.0", |
| ext_modules=[ |
| Extension("noddy", ["noddy.c"]), |
| Extension("noddy2", ["noddy2.c"]), |
| ]) |
| |
| |
| Providing finer control over data attributes |
| -------------------------------------------- |
| |
| In this section, we'll provide finer control over how the :attr:`first` and |
| :attr:`last` attributes are set in the :class:`Noddy` example. In the previous |
| version of our module, the instance variables :attr:`first` and :attr:`last` |
| could be set to non-string values or even deleted. We want to make sure that |
| these attributes always contain strings. |
| |
| .. literalinclude:: ../includes/noddy3.c |
| |
| |
| To provide greater control, over the :attr:`first` and :attr:`last` attributes, |
| we'll use custom getter and setter functions. Here are the functions for |
| getting and setting the :attr:`first` attribute:: |
| |
| Noddy_getfirst(Noddy *self, void *closure) |
| { |
| Py_INCREF(self->first); |
| return self->first; |
| } |
| |
| static int |
| Noddy_setfirst(Noddy *self, PyObject *value, void *closure) |
| { |
| if (value == NULL) { |
| PyErr_SetString(PyExc_TypeError, "Cannot delete the first attribute"); |
| return -1; |
| } |
| |
| if (! PyString_Check(value)) { |
| PyErr_SetString(PyExc_TypeError, |
| "The first attribute value must be a string"); |
| return -1; |
| } |
| |
| Py_DECREF(self->first); |
| Py_INCREF(value); |
| self->first = value; |
| |
| return 0; |
| } |
| |
| The getter function is passed a :class:`Noddy` object and a "closure", which is |
| void pointer. In this case, the closure is ignored. (The closure supports an |
| advanced usage in which definition data is passed to the getter and setter. This |
| could, for example, be used to allow a single set of getter and setter functions |
| that decide the attribute to get or set based on data in the closure.) |
| |
| The setter function is passed the :class:`Noddy` object, the new value, and the |
| closure. The new value may be *NULL*, in which case the attribute is being |
| deleted. In our setter, we raise an error if the attribute is deleted or if the |
| attribute value is not a string. |
| |
| We create an array of :ctype:`PyGetSetDef` structures:: |
| |
| static PyGetSetDef Noddy_getseters[] = { |
| {"first", |
| (getter)Noddy_getfirst, (setter)Noddy_setfirst, |
| "first name", |
| NULL}, |
| {"last", |
| (getter)Noddy_getlast, (setter)Noddy_setlast, |
| "last name", |
| NULL}, |
| {NULL} /* Sentinel */ |
| }; |
| |
| and register it in the :attr:`tp_getset` slot:: |
| |
| Noddy_getseters, /* tp_getset */ |
| |
| to register our attribute getters and setters. |
| |
| The last item in a :ctype:`PyGetSetDef` structure is the closure mentioned |
| above. In this case, we aren't using the closure, so we just pass *NULL*. |
| |
| We also remove the member definitions for these attributes:: |
| |
| static PyMemberDef Noddy_members[] = { |
| {"number", T_INT, offsetof(Noddy, number), 0, |
| "noddy number"}, |
| {NULL} /* Sentinel */ |
| }; |
| |
| We also need to update the :attr:`tp_init` handler to only allow strings [#]_ to |
| be passed:: |
| |
| static int |
| Noddy_init(Noddy *self, PyObject *args, PyObject *kwds) |
| { |
| PyObject *first=NULL, *last=NULL, *tmp; |
| |
| static char *kwlist[] = {"first", "last", "number", NULL}; |
| |
| if (! PyArg_ParseTupleAndKeywords(args, kwds, "|SSi", kwlist, |
| &first, &last, |
| &self->number)) |
| return -1; |
| |
| if (first) { |
| tmp = self->first; |
| Py_INCREF(first); |
| self->first = first; |
| Py_DECREF(tmp); |
| } |
| |
| if (last) { |
| tmp = self->last; |
| Py_INCREF(last); |
| self->last = last; |
| Py_DECREF(tmp); |
| } |
| |
| return 0; |
| } |
| |
| With these changes, we can assure that the :attr:`first` and :attr:`last` |
| members are never *NULL* so we can remove checks for *NULL* values in almost all |
| cases. This means that most of the :cfunc:`Py_XDECREF` calls can be converted to |
| :cfunc:`Py_DECREF` calls. The only place we can't change these calls is in the |
| deallocator, where there is the possibility that the initialization of these |
| members failed in the constructor. |
| |
| We also rename the module initialization function and module name in the |
| initialization function, as we did before, and we add an extra definition to the |
| :file:`setup.py` file. |
| |
| |
| Supporting cyclic garbage collection |
| ------------------------------------ |
| |
| Python has a cyclic-garbage collector that can identify unneeded objects even |
| when their reference counts are not zero. This can happen when objects are |
| involved in cycles. For example, consider:: |
| |
| >>> l = [] |
| >>> l.append(l) |
| >>> del l |
| |
| In this example, we create a list that contains itself. When we delete it, it |
| still has a reference from itself. Its reference count doesn't drop to zero. |
| Fortunately, Python's cyclic-garbage collector will eventually figure out that |
| the list is garbage and free it. |
| |
| In the second version of the :class:`Noddy` example, we allowed any kind of |
| object to be stored in the :attr:`first` or :attr:`last` attributes. [#]_ This |
| means that :class:`Noddy` objects can participate in cycles:: |
| |
| >>> import noddy2 |
| >>> n = noddy2.Noddy() |
| >>> l = [n] |
| >>> n.first = l |
| |
| This is pretty silly, but it gives us an excuse to add support for the |
| cyclic-garbage collector to the :class:`Noddy` example. To support cyclic |
| garbage collection, types need to fill two slots and set a class flag that |
| enables these slots: |
| |
| .. literalinclude:: ../includes/noddy4.c |
| |
| |
| The traversal method provides access to subobjects that could participate in |
| cycles:: |
| |
| static int |
| Noddy_traverse(Noddy *self, visitproc visit, void *arg) |
| { |
| int vret; |
| |
| if (self->first) { |
| vret = visit(self->first, arg); |
| if (vret != 0) |
| return vret; |
| } |
| if (self->last) { |
| vret = visit(self->last, arg); |
| if (vret != 0) |
| return vret; |
| } |
| |
| return 0; |
| } |
| |
| For each subobject that can participate in cycles, we need to call the |
| :cfunc:`visit` function, which is passed to the traversal method. The |
| :cfunc:`visit` function takes as arguments the subobject and the extra argument |
| *arg* passed to the traversal method. It returns an integer value that must be |
| returned if it is non-zero. |
| |
| Python provides a :cfunc:`Py_VISIT` macro that automates calling visit |
| functions. With :cfunc:`Py_VISIT`, :cfunc:`Noddy_traverse` can be simplified:: |
| |
| static int |
| Noddy_traverse(Noddy *self, visitproc visit, void *arg) |
| { |
| Py_VISIT(self->first); |
| Py_VISIT(self->last); |
| return 0; |
| } |
| |
| .. note:: |
| |
| Note that the :attr:`tp_traverse` implementation must name its arguments exactly |
| *visit* and *arg* in order to use :cfunc:`Py_VISIT`. This is to encourage |
| uniformity across these boring implementations. |
| |
| We also need to provide a method for clearing any subobjects that can |
| participate in cycles. We implement the method and reimplement the deallocator |
| to use it:: |
| |
| static int |
| Noddy_clear(Noddy *self) |
| { |
| PyObject *tmp; |
| |
| tmp = self->first; |
| self->first = NULL; |
| Py_XDECREF(tmp); |
| |
| tmp = self->last; |
| self->last = NULL; |
| Py_XDECREF(tmp); |
| |
| return 0; |
| } |
| |
| static void |
| Noddy_dealloc(Noddy* self) |
| { |
| Noddy_clear(self); |
| Py_TYPE(self)->tp_free((PyObject*)self); |
| } |
| |
| Notice the use of a temporary variable in :cfunc:`Noddy_clear`. We use the |
| temporary variable so that we can set each member to *NULL* before decrementing |
| its reference count. We do this because, as was discussed earlier, if the |
| reference count drops to zero, we might cause code to run that calls back into |
| the object. In addition, because we now support garbage collection, we also |
| have to worry about code being run that triggers garbage collection. If garbage |
| collection is run, our :attr:`tp_traverse` handler could get called. We can't |
| take a chance of having :cfunc:`Noddy_traverse` called when a member's reference |
| count has dropped to zero and its value hasn't been set to *NULL*. |
| |
| Python provides a :cfunc:`Py_CLEAR` that automates the careful decrementing of |
| reference counts. With :cfunc:`Py_CLEAR`, the :cfunc:`Noddy_clear` function can |
| be simplified:: |
| |
| static int |
| Noddy_clear(Noddy *self) |
| { |
| Py_CLEAR(self->first); |
| Py_CLEAR(self->last); |
| return 0; |
| } |
| |
| Finally, we add the :const:`Py_TPFLAGS_HAVE_GC` flag to the class flags:: |
| |
| Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HAVE_GC, /* tp_flags */ |
| |
| That's pretty much it. If we had written custom :attr:`tp_alloc` or |
| :attr:`tp_free` slots, we'd need to modify them for cyclic-garbage collection. |
| Most extensions will use the versions automatically provided. |
| |
| |
| Subclassing other types |
| ----------------------- |
| |
| It is possible to create new extension types that are derived from existing |
| types. It is easiest to inherit from the built in types, since an extension can |
| easily use the :class:`PyTypeObject` it needs. It can be difficult to share |
| these :class:`PyTypeObject` structures between extension modules. |
| |
| In this example we will create a :class:`Shoddy` type that inherits from the |
| built-in :class:`list` type. The new type will be completely compatible with |
| regular lists, but will have an additional :meth:`increment` method that |
| increases an internal counter. :: |
| |
| >>> import shoddy |
| >>> s = shoddy.Shoddy(range(3)) |
| >>> s.extend(s) |
| >>> print(len(s)) |
| 6 |
| >>> print(s.increment()) |
| 1 |
| >>> print(s.increment()) |
| 2 |
| |
| .. literalinclude:: ../includes/shoddy.c |
| |
| |
| As you can see, the source code closely resembles the :class:`Noddy` examples in |
| previous sections. We will break down the main differences between them. :: |
| |
| typedef struct { |
| PyListObject list; |
| int state; |
| } Shoddy; |
| |
| The primary difference for derived type objects is that the base type's object |
| structure must be the first value. The base type will already include the |
| :cfunc:`PyObject_HEAD` at the beginning of its structure. |
| |
| When a Python object is a :class:`Shoddy` instance, its *PyObject\** pointer can |
| be safely cast to both *PyListObject\** and *Shoddy\**. :: |
| |
| static int |
| Shoddy_init(Shoddy *self, PyObject *args, PyObject *kwds) |
| { |
| if (PyList_Type.tp_init((PyObject *)self, args, kwds) < 0) |
| return -1; |
| self->state = 0; |
| return 0; |
| } |
| |
| In the :attr:`__init__` method for our type, we can see how to call through to |
| the :attr:`__init__` method of the base type. |
| |
| This pattern is important when writing a type with custom :attr:`new` and |
| :attr:`dealloc` methods. The :attr:`new` method should not actually create the |
| memory for the object with :attr:`tp_alloc`, that will be handled by the base |
| class when calling its :attr:`tp_new`. |
| |
| When filling out the :cfunc:`PyTypeObject` for the :class:`Shoddy` type, you see |
| a slot for :cfunc:`tp_base`. Due to cross platform compiler issues, you can't |
| fill that field directly with the :cfunc:`PyList_Type`; it can be done later in |
| the module's :cfunc:`init` function. :: |
| |
| PyMODINIT_FUNC |
| PyInit_shoddy(void) |
| { |
| PyObject *m; |
| |
| ShoddyType.tp_base = &PyList_Type; |
| if (PyType_Ready(&ShoddyType) < 0) |
| return NULL; |
| |
| m = PyModule_Create(&shoddymodule); |
| if (m == NULL) |
| return NULL; |
| |
| Py_INCREF(&ShoddyType); |
| PyModule_AddObject(m, "Shoddy", (PyObject *) &ShoddyType); |
| return m; |
| } |
| |
| Before calling :cfunc:`PyType_Ready`, the type structure must have the |
| :attr:`tp_base` slot filled in. When we are deriving a new type, it is not |
| necessary to fill out the :attr:`tp_alloc` slot with :cfunc:`PyType_GenericNew` |
| -- the allocate function from the base type will be inherited. |
| |
| After that, calling :cfunc:`PyType_Ready` and adding the type object to the |
| module is the same as with the basic :class:`Noddy` examples. |
| |
| |
| .. _dnt-type-methods: |
| |
| Type Methods |
| ============ |
| |
| This section aims to give a quick fly-by on the various type methods you can |
| implement and what they do. |
| |
| Here is the definition of :ctype:`PyTypeObject`, with some fields only used in |
| debug builds omitted: |
| |
| .. literalinclude:: ../includes/typestruct.h |
| |
| |
| Now that's a *lot* of methods. Don't worry too much though - if you have a type |
| you want to define, the chances are very good that you will only implement a |
| handful of these. |
| |
| As you probably expect by now, we're going to go over this and give more |
| information about the various handlers. We won't go in the order they are |
| defined in the structure, because there is a lot of historical baggage that |
| impacts the ordering of the fields; be sure your type initialization keeps the |
| fields in the right order! It's often easiest to find an example that includes |
| all the fields you need (even if they're initialized to ``0``) and then change |
| the values to suit your new type. :: |
| |
| char *tp_name; /* For printing */ |
| |
| The name of the type - as mentioned in the last section, this will appear in |
| various places, almost entirely for diagnostic purposes. Try to choose something |
| that will be helpful in such a situation! :: |
| |
| int tp_basicsize, tp_itemsize; /* For allocation */ |
| |
| These fields tell the runtime how much memory to allocate when new objects of |
| this type are created. Python has some built-in support for variable length |
| structures (think: strings, lists) which is where the :attr:`tp_itemsize` field |
| comes in. This will be dealt with later. :: |
| |
| char *tp_doc; |
| |
| Here you can put a string (or its address) that you want returned when the |
| Python script references ``obj.__doc__`` to retrieve the doc string. |
| |
| Now we come to the basic type methods---the ones most extension types will |
| implement. |
| |
| |
| Finalization and De-allocation |
| ------------------------------ |
| |
| .. index:: |
| single: object; deallocation |
| single: deallocation, object |
| single: object; finalization |
| single: finalization, of objects |
| |
| :: |
| |
| destructor tp_dealloc; |
| |
| This function is called when the reference count of the instance of your type is |
| reduced to zero and the Python interpreter wants to reclaim it. If your type |
| has memory to free or other clean-up to perform, put it here. The object itself |
| needs to be freed here as well. Here is an example of this function:: |
| |
| static void |
| newdatatype_dealloc(newdatatypeobject * obj) |
| { |
| free(obj->obj_UnderlyingDatatypePtr); |
| Py_TYPE(obj)->tp_free(obj); |
| } |
| |
| .. index:: |
| single: PyErr_Fetch() |
| single: PyErr_Restore() |
| |
| One important requirement of the deallocator function is that it leaves any |
| pending exceptions alone. This is important since deallocators are frequently |
| called as the interpreter unwinds the Python stack; when the stack is unwound |
| due to an exception (rather than normal returns), nothing is done to protect the |
| deallocators from seeing that an exception has already been set. Any actions |
| which a deallocator performs which may cause additional Python code to be |
| executed may detect that an exception has been set. This can lead to misleading |
| errors from the interpreter. The proper way to protect against this is to save |
| a pending exception before performing the unsafe action, and restoring it when |
| done. This can be done using the :cfunc:`PyErr_Fetch` and |
| :cfunc:`PyErr_Restore` functions:: |
| |
| static void |
| my_dealloc(PyObject *obj) |
| { |
| MyObject *self = (MyObject *) obj; |
| PyObject *cbresult; |
| |
| if (self->my_callback != NULL) { |
| PyObject *err_type, *err_value, *err_traceback; |
| int have_error = PyErr_Occurred() ? 1 : 0; |
| |
| if (have_error) |
| PyErr_Fetch(&err_type, &err_value, &err_traceback); |
| |
| cbresult = PyObject_CallObject(self->my_callback, NULL); |
| if (cbresult == NULL) |
| PyErr_WriteUnraisable(self->my_callback); |
| else |
| Py_DECREF(cbresult); |
| |
| if (have_error) |
| PyErr_Restore(err_type, err_value, err_traceback); |
| |
| Py_DECREF(self->my_callback); |
| } |
| Py_TYPE(obj)->tp_free((PyObject*)self); |
| } |
| |
| |
| Object Presentation |
| ------------------- |
| |
| .. index:: |
| builtin: repr |
| builtin: str |
| |
| In Python, there are two ways to generate a textual representation of an object: |
| the :func:`repr` function, and the :func:`str` function. (The :func:`print` |
| function just calls :func:`str`.) These handlers are both optional. |
| |
| :: |
| |
| reprfunc tp_repr; |
| reprfunc tp_str; |
| |
| The :attr:`tp_repr` handler should return a string object containing a |
| representation of the instance for which it is called. Here is a simple |
| example:: |
| |
| static PyObject * |
| newdatatype_repr(newdatatypeobject * obj) |
| { |
| return PyString_FromFormat("Repr-ified_newdatatype{{size:\%d}}", |
| obj->obj_UnderlyingDatatypePtr->size); |
| } |
| |
| If no :attr:`tp_repr` handler is specified, the interpreter will supply a |
| representation that uses the type's :attr:`tp_name` and a uniquely-identifying |
| value for the object. |
| |
| The :attr:`tp_str` handler is to :func:`str` what the :attr:`tp_repr` handler |
| described above is to :func:`repr`; that is, it is called when Python code calls |
| :func:`str` on an instance of your object. Its implementation is very similar |
| to the :attr:`tp_repr` function, but the resulting string is intended for human |
| consumption. If :attr:`tp_str` is not specified, the :attr:`tp_repr` handler is |
| used instead. |
| |
| Here is a simple example:: |
| |
| static PyObject * |
| newdatatype_str(newdatatypeobject * obj) |
| { |
| return PyString_FromFormat("Stringified_newdatatype{{size:\%d}}", |
| obj->obj_UnderlyingDatatypePtr->size); |
| } |
| |
| |
| |
| Attribute Management |
| -------------------- |
| |
| For every object which can support attributes, the corresponding type must |
| provide the functions that control how the attributes are resolved. There needs |
| to be a function which can retrieve attributes (if any are defined), and another |
| to set attributes (if setting attributes is allowed). Removing an attribute is |
| a special case, for which the new value passed to the handler is *NULL*. |
| |
| Python supports two pairs of attribute handlers; a type that supports attributes |
| only needs to implement the functions for one pair. The difference is that one |
| pair takes the name of the attribute as a :ctype:`char\*`, while the other |
| accepts a :ctype:`PyObject\*`. Each type can use whichever pair makes more |
| sense for the implementation's convenience. :: |
| |
| getattrfunc tp_getattr; /* char * version */ |
| setattrfunc tp_setattr; |
| /* ... */ |
| getattrofunc tp_getattro; /* PyObject * version */ |
| setattrofunc tp_setattro; |
| |
| If accessing attributes of an object is always a simple operation (this will be |
| explained shortly), there are generic implementations which can be used to |
| provide the :ctype:`PyObject\*` version of the attribute management functions. |
| The actual need for type-specific attribute handlers almost completely |
| disappeared starting with Python 2.2, though there are many examples which have |
| not been updated to use some of the new generic mechanism that is available. |
| |
| |
| .. _generic-attribute-management: |
| |
| Generic Attribute Management |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| Most extension types only use *simple* attributes. So, what makes the |
| attributes simple? There are only a couple of conditions that must be met: |
| |
| #. The name of the attributes must be known when :cfunc:`PyType_Ready` is |
| called. |
| |
| #. No special processing is needed to record that an attribute was looked up or |
| set, nor do actions need to be taken based on the value. |
| |
| Note that this list does not place any restrictions on the values of the |
| attributes, when the values are computed, or how relevant data is stored. |
| |
| When :cfunc:`PyType_Ready` is called, it uses three tables referenced by the |
| type object to create :term:`descriptor`\s which are placed in the dictionary of the |
| type object. Each descriptor controls access to one attribute of the instance |
| object. Each of the tables is optional; if all three are *NULL*, instances of |
| the type will only have attributes that are inherited from their base type, and |
| should leave the :attr:`tp_getattro` and :attr:`tp_setattro` fields *NULL* as |
| well, allowing the base type to handle attributes. |
| |
| The tables are declared as three fields of the type object:: |
| |
| struct PyMethodDef *tp_methods; |
| struct PyMemberDef *tp_members; |
| struct PyGetSetDef *tp_getset; |
| |
| If :attr:`tp_methods` is not *NULL*, it must refer to an array of |
| :ctype:`PyMethodDef` structures. Each entry in the table is an instance of this |
| structure:: |
| |
| typedef struct PyMethodDef { |
| char *ml_name; /* method name */ |
| PyCFunction ml_meth; /* implementation function */ |
| int ml_flags; /* flags */ |
| char *ml_doc; /* docstring */ |
| } PyMethodDef; |
| |
| One entry should be defined for each method provided by the type; no entries are |
| needed for methods inherited from a base type. One additional entry is needed |
| at the end; it is a sentinel that marks the end of the array. The |
| :attr:`ml_name` field of the sentinel must be *NULL*. |
| |
| XXX Need to refer to some unified discussion of the structure fields, shared |
| with the next section. |
| |
| The second table is used to define attributes which map directly to data stored |
| in the instance. A variety of primitive C types are supported, and access may |
| be read-only or read-write. The structures in the table are defined as:: |
| |
| typedef struct PyMemberDef { |
| char *name; |
| int type; |
| int offset; |
| int flags; |
| char *doc; |
| } PyMemberDef; |
| |
| For each entry in the table, a :term:`descriptor` will be constructed and added to the |
| type which will be able to extract a value from the instance structure. The |
| :attr:`type` field should contain one of the type codes defined in the |
| :file:`structmember.h` header; the value will be used to determine how to |
| convert Python values to and from C values. The :attr:`flags` field is used to |
| store flags which control how the attribute can be accessed. |
| |
| XXX Need to move some of this to a shared section! |
| |
| The following flag constants are defined in :file:`structmember.h`; they may be |
| combined using bitwise-OR. |
| |
| +---------------------------+----------------------------------------------+ |
| | Constant | Meaning | |
| +===========================+==============================================+ |
| | :const:`READONLY` | Never writable. | |
| +---------------------------+----------------------------------------------+ |
| | :const:`READ_RESTRICTED` | Not readable in restricted mode. | |
| +---------------------------+----------------------------------------------+ |
| | :const:`WRITE_RESTRICTED` | Not writable in restricted mode. | |
| +---------------------------+----------------------------------------------+ |
| | :const:`RESTRICTED` | Not readable or writable in restricted mode. | |
| +---------------------------+----------------------------------------------+ |
| |
| .. index:: |
| single: READONLY |
| single: READ_RESTRICTED |
| single: WRITE_RESTRICTED |
| single: RESTRICTED |
| |
| An interesting advantage of using the :attr:`tp_members` table to build |
| descriptors that are used at runtime is that any attribute defined this way can |
| have an associated doc string simply by providing the text in the table. An |
| application can use the introspection API to retrieve the descriptor from the |
| class object, and get the doc string using its :attr:`__doc__` attribute. |
| |
| As with the :attr:`tp_methods` table, a sentinel entry with a :attr:`name` value |
| of *NULL* is required. |
| |
| .. XXX Descriptors need to be explained in more detail somewhere, but not here. |
| |
| Descriptor objects have two handler functions which correspond to the |
| \member{tp_getattro} and \member{tp_setattro} handlers. The |
| \method{__get__()} handler is a function which is passed the descriptor, |
| instance, and type objects, and returns the value of the attribute, or it |
| returns \NULL{} and sets an exception. The \method{__set__()} handler is |
| passed the descriptor, instance, type, and new value; |
| |
| |
| Type-specific Attribute Management |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
| |
| For simplicity, only the :ctype:`char\*` version will be demonstrated here; the |
| type of the name parameter is the only difference between the :ctype:`char\*` |
| and :ctype:`PyObject\*` flavors of the interface. This example effectively does |
| the same thing as the generic example above, but does not use the generic |
| support added in Python 2.2. It explains how the handler functions are |
| called, so that if you do need to extend their functionality, you'll understand |
| what needs to be done. |
| |
| The :attr:`tp_getattr` handler is called when the object requires an attribute |
| look-up. It is called in the same situations where the :meth:`__getattr__` |
| method of a class would be called. |
| |
| Here is an example:: |
| |
| static PyObject * |
| newdatatype_getattr(newdatatypeobject *obj, char *name) |
| { |
| if (strcmp(name, "data") == 0) |
| { |
| return PyInt_FromLong(obj->data); |
| } |
| |
| PyErr_Format(PyExc_AttributeError, |
| "'%.50s' object has no attribute '%.400s'", |
| tp->tp_name, name); |
| return NULL; |
| } |
| |
| The :attr:`tp_setattr` handler is called when the :meth:`__setattr__` or |
| :meth:`__delattr__` method of a class instance would be called. When an |
| attribute should be deleted, the third parameter will be *NULL*. Here is an |
| example that simply raises an exception; if this were really all you wanted, the |
| :attr:`tp_setattr` handler should be set to *NULL*. :: |
| |
| static int |
| newdatatype_setattr(newdatatypeobject *obj, char *name, PyObject *v) |
| { |
| (void)PyErr_Format(PyExc_RuntimeError, "Read-only attribute: \%s", name); |
| return -1; |
| } |
| |
| Object Comparison |
| ----------------- |
| |
| :: |
| |
| richcmpfunc tp_richcompare; |
| |
| The :attr:`tp_richcompare` handler is called when comparisons are needed. It is |
| analogous to the :ref:`rich comparison methods <richcmpfuncs>`, like |
| :meth:`__lt__`, and also called by :cfunc:`PyObject_RichCompare` and |
| :cfunc:`PyObject_RichCompareBool`. |
| |
| This function is called with two Python objects and the operator as arguments, |
| where the operator is one of ``Py_EQ``, ``Py_NE``, ``Py_LE``, ``Py_GT``, |
| ``Py_LT`` or ``Py_GT``. It should compare the two objects with respect to the |
| specified operator and return ``Py_True`` or ``Py_False`` if the comparison is |
| successfull, ``Py_NotImplemented`` to indicate that comparison is not |
| implemented and the other object's comparison method should be tried, or *NULL* |
| if an exception was set. |
| |
| Here is a sample implementation, for a datatype that is considered equal if the |
| size of an internal pointer is equal:: |
| |
| static int |
| newdatatype_richcmp(PyObject *obj1, PyObject *obj2, int op) |
| { |
| PyObject *result; |
| int c, size1, size2; |
| |
| /* code to make sure that both arguments are of type |
| newdatatype omitted */ |
| |
| size1 = obj1->obj_UnderlyingDatatypePtr->size; |
| size2 = obj2->obj_UnderlyingDatatypePtr->size; |
| |
| switch (op) { |
| case Py_LT: c = size1 < size2; break; |
| case Py_LE: c = size1 <= size2; break; |
| case Py_EQ: c = size1 == size2; break; |
| case Py_NE: c = size1 != size2; break; |
| case Py_GT: c = size1 > size2; break; |
| case Py_GE: c = size1 >= size2; break; |
| } |
| result = c ? Py_True : Py_False; |
| Py_INCREF(result); |
| return result; |
| } |
| |
| |
| Abstract Protocol Support |
| ------------------------- |
| |
| Python supports a variety of *abstract* 'protocols;' the specific interfaces |
| provided to use these interfaces are documented in :ref:`abstract`. |
| |
| |
| A number of these abstract interfaces were defined early in the development of |
| the Python implementation. In particular, the number, mapping, and sequence |
| protocols have been part of Python since the beginning. Other protocols have |
| been added over time. For protocols which depend on several handler routines |
| from the type implementation, the older protocols have been defined as optional |
| blocks of handlers referenced by the type object. For newer protocols there are |
| additional slots in the main type object, with a flag bit being set to indicate |
| that the slots are present and should be checked by the interpreter. (The flag |
| bit does not indicate that the slot values are non-*NULL*. The flag may be set |
| to indicate the presence of a slot, but a slot may still be unfilled.) :: |
| |
| PyNumberMethods tp_as_number; |
| PySequenceMethods tp_as_sequence; |
| PyMappingMethods tp_as_mapping; |
| |
| If you wish your object to be able to act like a number, a sequence, or a |
| mapping object, then you place the address of a structure that implements the C |
| type :ctype:`PyNumberMethods`, :ctype:`PySequenceMethods`, or |
| :ctype:`PyMappingMethods`, respectively. It is up to you to fill in this |
| structure with appropriate values. You can find examples of the use of each of |
| these in the :file:`Objects` directory of the Python source distribution. :: |
| |
| hashfunc tp_hash; |
| |
| This function, if you choose to provide it, should return a hash number for an |
| instance of your data type. Here is a moderately pointless example:: |
| |
| static long |
| newdatatype_hash(newdatatypeobject *obj) |
| { |
| long result; |
| result = obj->obj_UnderlyingDatatypePtr->size; |
| result = result * 3; |
| return result; |
| } |
| |
| :: |
| |
| ternaryfunc tp_call; |
| |
| This function is called when an instance of your data type is "called", for |
| example, if ``obj1`` is an instance of your data type and the Python script |
| contains ``obj1('hello')``, the :attr:`tp_call` handler is invoked. |
| |
| This function takes three arguments: |
| |
| #. *arg1* is the instance of the data type which is the subject of the call. If |
| the call is ``obj1('hello')``, then *arg1* is ``obj1``. |
| |
| #. *arg2* is a tuple containing the arguments to the call. You can use |
| :cfunc:`PyArg_ParseTuple` to extract the arguments. |
| |
| #. *arg3* is a dictionary of keyword arguments that were passed. If this is |
| non-*NULL* and you support keyword arguments, use |
| :cfunc:`PyArg_ParseTupleAndKeywords` to extract the arguments. If you do not |
| want to support keyword arguments and this is non-*NULL*, raise a |
| :exc:`TypeError` with a message saying that keyword arguments are not supported. |
| |
| Here is a desultory example of the implementation of the call function. :: |
| |
| /* Implement the call function. |
| * obj1 is the instance receiving the call. |
| * obj2 is a tuple containing the arguments to the call, in this |
| * case 3 strings. |
| */ |
| static PyObject * |
| newdatatype_call(newdatatypeobject *obj, PyObject *args, PyObject *other) |
| { |
| PyObject *result; |
| char *arg1; |
| char *arg2; |
| char *arg3; |
| |
| if (!PyArg_ParseTuple(args, "sss:call", &arg1, &arg2, &arg3)) { |
| return NULL; |
| } |
| result = PyString_FromFormat( |
| "Returning -- value: [\%d] arg1: [\%s] arg2: [\%s] arg3: [\%s]\n", |
| obj->obj_UnderlyingDatatypePtr->size, |
| arg1, arg2, arg3); |
| printf("\%s", PyString_AS_STRING(result)); |
| return result; |
| } |
| |
| XXX some fields need to be added here... :: |
| |
| /* Iterators */ |
| getiterfunc tp_iter; |
| iternextfunc tp_iternext; |
| |
| These functions provide support for the iterator protocol. Any object which |
| wishes to support iteration over its contents (which may be generated during |
| iteration) must implement the ``tp_iter`` handler. Objects which are returned |
| by a ``tp_iter`` handler must implement both the ``tp_iter`` and ``tp_iternext`` |
| handlers. Both handlers take exactly one parameter, the instance for which they |
| are being called, and return a new reference. In the case of an error, they |
| should set an exception and return *NULL*. |
| |
| For an object which represents an iterable collection, the ``tp_iter`` handler |
| must return an iterator object. The iterator object is responsible for |
| maintaining the state of the iteration. For collections which can support |
| multiple iterators which do not interfere with each other (as lists and tuples |
| do), a new iterator should be created and returned. Objects which can only be |
| iterated over once (usually due to side effects of iteration) should implement |
| this handler by returning a new reference to themselves, and should also |
| implement the ``tp_iternext`` handler. File objects are an example of such an |
| iterator. |
| |
| Iterator objects should implement both handlers. The ``tp_iter`` handler should |
| return a new reference to the iterator (this is the same as the ``tp_iter`` |
| handler for objects which can only be iterated over destructively). The |
| ``tp_iternext`` handler should return a new reference to the next object in the |
| iteration if there is one. If the iteration has reached the end, it may return |
| *NULL* without setting an exception or it may set :exc:`StopIteration`; avoiding |
| the exception can yield slightly better performance. If an actual error occurs, |
| it should set an exception and return *NULL*. |
| |
| |
| .. _weakref-support: |
| |
| Weak Reference Support |
| ---------------------- |
| |
| One of the goals of Python's weak-reference implementation is to allow any type |
| to participate in the weak reference mechanism without incurring the overhead on |
| those objects which do not benefit by weak referencing (such as numbers). |
| |
| For an object to be weakly referencable, the extension must include a |
| :ctype:`PyObject\*` field in the instance structure for the use of the weak |
| reference mechanism; it must be initialized to *NULL* by the object's |
| constructor. It must also set the :attr:`tp_weaklistoffset` field of the |
| corresponding type object to the offset of the field. For example, the instance |
| type is defined with the following structure:: |
| |
| typedef struct { |
| PyObject_HEAD |
| PyClassObject *in_class; /* The class object */ |
| PyObject *in_dict; /* A dictionary */ |
| PyObject *in_weakreflist; /* List of weak references */ |
| } PyInstanceObject; |
| |
| The statically-declared type object for instances is defined this way:: |
| |
| PyTypeObject PyInstance_Type = { |
| PyVarObject_HEAD_INIT(&PyType_Type, 0) |
| 0, |
| "module.instance", |
| |
| /* Lots of stuff omitted for brevity... */ |
| |
| Py_TPFLAGS_DEFAULT, /* tp_flags */ |
| 0, /* tp_doc */ |
| 0, /* tp_traverse */ |
| 0, /* tp_clear */ |
| 0, /* tp_richcompare */ |
| offsetof(PyInstanceObject, in_weakreflist), /* tp_weaklistoffset */ |
| }; |
| |
| The type constructor is responsible for initializing the weak reference list to |
| *NULL*:: |
| |
| static PyObject * |
| instance_new() { |
| /* Other initialization stuff omitted for brevity */ |
| |
| self->in_weakreflist = NULL; |
| |
| return (PyObject *) self; |
| } |
| |
| The only further addition is that the destructor needs to call the weak |
| reference manager to clear any weak references. This should be done before any |
| other parts of the destruction have occurred, but is only required if the weak |
| reference list is non-*NULL*:: |
| |
| static void |
| instance_dealloc(PyInstanceObject *inst) |
| { |
| /* Allocate temporaries if needed, but do not begin |
| destruction just yet. |
| */ |
| |
| if (inst->in_weakreflist != NULL) |
| PyObject_ClearWeakRefs((PyObject *) inst); |
| |
| /* Proceed with object destruction normally. */ |
| } |
| |
| |
| More Suggestions |
| ---------------- |
| |
| Remember that you can omit most of these functions, in which case you provide |
| ``0`` as a value. There are type definitions for each of the functions you must |
| provide. They are in :file:`object.h` in the Python include directory that |
| comes with the source distribution of Python. |
| |
| In order to learn how to implement any specific method for your new data type, |
| do the following: Download and unpack the Python source distribution. Go to |
| the :file:`Objects` directory, then search the C source files for ``tp_`` plus |
| the function you want (for example, ``tp_richcompare``). You will find examples |
| of the function you want to implement. |
| |
| When you need to verify that an object is an instance of the type you are |
| implementing, use the :cfunc:`PyObject_TypeCheck` function. A sample of its use |
| might be something like the following:: |
| |
| if (! PyObject_TypeCheck(some_object, &MyType)) { |
| PyErr_SetString(PyExc_TypeError, "arg #1 not a mything"); |
| return NULL; |
| } |
| |
| .. rubric:: Footnotes |
| |
| .. [#] This is true when we know that the object is a basic type, like a string or a |
| float. |
| |
| .. [#] We relied on this in the :attr:`tp_dealloc` handler in this example, because our |
| type doesn't support garbage collection. Even if a type supports garbage |
| collection, there are calls that can be made to "untrack" the object from |
| garbage collection, however, these calls are advanced and not covered here. |
| |
| .. [#] We now know that the first and last members are strings, so perhaps we could be |
| less careful about decrementing their reference counts, however, we accept |
| instances of string subclasses. Even though deallocating normal strings won't |
| call back into our objects, we can't guarantee that deallocating an instance of |
| a string subclass won't call back into our objects. |
| |
| .. [#] Even in the third version, we aren't guaranteed to avoid cycles. Instances of |
| string subclasses are allowed and string subclasses could allow cycles even if |
| normal strings don't. |
| |