Special Methods of Extenstion Types

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Special Methods of Extension Types

This page describes the special methods currently supported by Pyrex extension types. A complete list of all the special methods appears in the table at the bottom. Some of these methods behave differently from their Python counterparts or have no direct Python counterparts, and require special mention.

Note: Everything said on this page applies only to extension types, defined with the cdef class statement. It doesn't apply to classes defined with the Python class statement, where the normal Python rules apply.

## Declaration

Special methods of extension types must be declared with def, not cdef.

## Docstrings

Currently, docstrings are not fully supported in special methods of extension types. You can place a docstring in the source to serve as a comment, but it won't show up in the corresponding __doc__ attribute at run time. (This is a Python limitation -- there's nowhere in the PyTypeObject data structure to put such docstrings.)

## Initialisation methods: `__cinit__` and `__init__`

There are two methods concerned with initialising the object`.`

The `__cinit__` method is where you should perform basic C-level initialisation of the object, including allocation of any C data structures that your object will own. You need to be careful what you do in the __cinit__ method, because the object may not yet be a valid Python object when it is called. Therefore, you must not invoke any Python operations which might touch the object; in particular, do not try to call any of its methods.

By the time your `__cinit__` method is called, memory has been allocated for the object and any C attributes it has have been initialised to 0 or null. (Any Python attributes have also been initialised to `None`, but you probably shouldn't rely on that.) Your `__cinit__` method is guaranteed to be called exactly once.
If your extension type has a base type, the `__cinit__` method of the base type is automatically called before your `__cinit__` method is called; you cannot explicitly call the inherited `__cinit__` method. If you need to pass a modified argument list to the base type, you will have to do the relevant part of the initialisation in the `__init__` method instead (where the normal rules for calling inherited methods apply).

Any initialisation which cannot safely be done in the `__cinit__` method should be done in the `__init__` method. By the time `__init__` is called, the object is a fully valid Python object and all operations are safe. Under some circumstances it is possible for `__init__` to be called more than once or not to be called at all, so your other methods should be designed to be robust in such situations.

Any arguments passed to the constructor will be passed to both the `__cinit__` method and the `__init__` method. If you anticipate subclassing your extension type in Python, you may find it useful to give the `__cinit__` method * and ** arguments so that it can accept and ignore extra arguments. Otherwise, any Python subclass which has an `__init__` with a different signature will have to override `__new__` as well as `__init__`, which the writer of a Python class wouldn't expect to have to do.

## Finalization method: `__dealloc__```

The counterpart to the `__cinit__` method is the `__dealloc__` method, which should perform the inverse of the `__cinit__` method. Any C data structures that you allocated in your `__cinit__` method should be freed in your `__dealloc__` method.

You need to be careful what you do in a `__dealloc__` method. By the time your `__dealloc__` method is called, the object may already have been partially destroyed and may not be in a valid state as far as Python is concerned, so you should avoid invoking any Python operations which might touch the object. In particular, don't call any other methods of the object or do anything which might cause the object to be resurrected. It's best if you stick to just deallocating C data.

You don't need to worry about deallocating Python attributes of your object, because that will be done for you by Pyrex after your `__dealloc__` method returns.
Note: There is no `__del__` method for extension types.

## Arithmetic methods

Arithmetic operator methods, such as `__add__`, behave differently from their Python counterparts. There are no separate "reversed" versions of these methods (`__radd__`, etc.) Instead, if the first operand cannot perform the operation, the same method of the second operand is called, with the operands in the same order.

This means that you can't rely on the first parameter of these methods being "self", and you should test the types of both operands before deciding what to do. If you can't handle the combination of types you've been given, you should return `NotImplemented`.

This also applies to the in-place arithmetic method `__ipow__`. It doesn't apply to any of the other in-place methods (`__iadd__`, etc.) which always take self as the first argument.

## Rich comparisons

There are no separate methods for the individual rich comparison operations (`__eq__`, `__le__`, etc.) Instead there is a single method `__richcmp__` which takes an integer indicating which operation is to be performed, as follows:

< | 0 |  | == | 2 |  | > | 4
<= | 1 |  | != | 3 |  | >= | 5

## The __next__ method

Extension types wishing to implement the iterator interface should define a method called `__next__`, not `next`. The Python system will automatically supply a `next` method which calls your __next__. Do NOT explicitly give your type a `next` method, or bad things could happen.

## Type Testing in Special Methods (New in 0.9.7)

When testing the types of operands to your special methods, the obvious way might appear to be to use the isinstance function. However, this is not completely safe, because it's possible for a class to override what gets returned by isinstance tests on its instances. This is not a great problem in Python code, but in Pyrex it could be disastrous, as we are relying on knowing the C layout of the objects we're dealing with.
Pyrex provides an alternative function, typecheck, which corresponds to PyObject_TypeCheck in the Python/C API. This is safe to use, as it always tests the actual C type of the object.
Similarly, there is an issubtype function, corresponding to PyType_IsSubType, as a safe alternative to issubclass.
As an example, here's how you might write an __add__ method for an extension type called MyNumber:
def __add__(x, y):
if typecheck(x, MyNumber):
# we are the left operand
if typecheck(y, MyNumber):
# add ourselves to another MyNumber and return result
if typecheck(y, int):
# add ourselves to an int and return result
elseif typecheck(y, MyNumber):
# we are the right operand
if typecheck(x, int):
# add an int to ourselves and return the result
# Get here if unknown combination
return NotImplemented

## Special Method Table

This table lists all of the special methods together with their parameter and return types. In the table below, a parameter name of self is used to indicate that the parameter has the type that the method belongs to. Other parameters with no type specified in the table are generic Python objects.

You don't have to declare your method as taking these parameter types. If you declare different types, conversions will be performed as necessary.

Name | Parameters | Return type | Description
General
`__cinit__` | self, ... |  | Basic initialisation (no direct Python equivalent)
`__init__` | self, ... |  | Further initialisation
`__dealloc__` | self |  | Basic deallocation (no direct Python equivalent)
`__cmp__` | x, y | int | 3-way comparison
`__richcmp__` | x, y, int op | object | Rich comparison (no direct Python equivalent)
`__str__` | self | object | str(self)
`__repr__` | self | object | repr(self)
`__hash__` | self | int | Hash function
`__call__` | self, ... | object | self(...)
`__iter__` | self | object | Return iterator for sequence
`__getattr__` | self, name | object | Get attribute
`__setattr__` | self, name, val |  | Set attribute
`__delattr__` | self, name |  | Delete attribute
Arithmetic operators
`__add__` | x, y | object | binary + operator
`__sub__` | x, y | object | binary - operator
`__mul__` | x, y | object | * operator
`__div__` | x, y | object | / operator for old-style division
`__floordiv__` | x, y | object | // operator
`__truediv__` | x, y | object | / operator for new-style division
`__mod__` | x, y | object | % operator
`__divmod__` | x, y | object | combined div and mod
`__pow__` | x, y, z | object | ** operator or pow(x, y, z)
`__neg__` | self | object | unary - operator
`__pos__` | self | object | unary + operator
`__abs__` | self | object | absolute value
`__nonzero__` | self | int | convert to boolean
`__invert__` | self | object | ~ operator
`__lshift__` | x, y | object | << operator
`__rshift__` | x, y | object | >> operator
`__and__` | x, y | object | & operator
`__or__` | x, y | object | | operator
`__xor__` | x, y | object | ^ operator
Numeric conversions
`__int__` | self | object | Convert to integer
`__long__` | self | object | Convert to long integer
`__float__` | self | object | Convert to float
`__oct__` | self | object | Convert to octal
`__hex__` | self | object | Convert to hexadecimal
__index__ (2.5+ only) | self | object | Convert to sequence index
In-place arithmetic operators
`__iadd__` | self, x | object | += operator
`__isub__` | self, x | object | -= operator
`__imul__` | self, x | object | *= operator
`__idiv__` | self, x | object | /= operator for old-style division
`__ifloordiv__` | self, x | object | //= operator
`__itruediv__` | self, x | object | /= operator for new-style division
`__imod__` | self, x | object | %= operator
`__ipow__` | x, y, z | object | **= operator
`__ilshift__` | self, x | object | <<= operator
`__irshift__` | self, x | object | >>= operator
`__iand__` | self, x | object | &= operator
`__ior__` | self, x | object | |= operator
`__ixor__` | self, x | object | ^= operator
Sequences and mappings
`__len__` | self | int | len(self)
`__getitem__` | self, x | object | self[x]
`__setitem__` | self, x, y |  | self[x] = y
`__delitem__` | self, x |  | del self[x]
`__getslice__` | self, Py_ssize_t i, Py_ssize_t j | object | self[i:j]
`__setslice__` | self, Py_ssize_t i, Py_ssize_t j, x |  | self[i:j] = x
`__delslice__` | self, Py_ssize_t i, Py_ssize_t j |  | del self[i:j]
`__contains__` | self, x | int | x in self
Iterators
`__next__` | self | object | Get next item (called `next` in Python)
Buffer interface (no Python equivalents - see note 1)
`__getreadbuffer__` | self, int i, void **p |  |
`__getwritebuffer__` | self, int i, void **p |  |
`__getsegcount__` | self, int *p |  |
`__getcharbuffer__` | self, int i, char **p |  |
Descriptor objects (see note 2)
`__get__` | self, instance, class | object | Get value of attribute
`__set__` | self, instance, value |  | Set value of attribute
__delete__ | self, instance |  | Delete attribute

Note 1: The buffer interface is intended for use by C code and is not directly accessible from Python. It is described in the Python/C API Reference Manual under sections 6.6 and 10.6.

Note 2: Descriptor objects are part of the support mechanism for new-style Python classes. See the discussion of descriptors in the Python documentation. See also PEP 252, "Making Types Look More Like Classes", and PEP 253, "Subtyping Built-In Types".