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Extension Types

## Contents

- Introduction
- Attributes
- Extension types and None
- Special methods
- Properties (NEW in 0.9)
- Subclassing
- C Methods (NEW in 0.9)
  Forward-declaring extension types
- Making extension types weak-referenceable (NEW in 0.9.4)
- Public and external extension types

- External extension types
- Implicit importing
- Type names vs. constructor names
- Public extension types
- Name specification clause

## Introduction

As well as creating normal user-defined classes with the Python class statement, Cython also lets you create new built-in Python types, known as extension types. You define an extension type using the cdef class statement. Here's an example:

> `cdef class Shrubbery:`

> `cdef int width, height`

> `def __init__(self, w, h):`
> `self.width = w`
> `self.height = h`

> `def describe(self):`
> `print "This shrubbery is", self.width, \`
> `"by", self.height, "cubits."`

As you can see, a Cython extension type definition looks a lot like a Python class definition. Within it, you use the def statement to define methods that can be called from Python code. You can even define many of the special methods such as `__init__` as you would in Python.

The main difference is that you can use the cdef statement to define attributes. The attributes may be Python objects (either generic or of a particular extension type), or they may be of any C data type. So you can use extension types to wrap arbitrary C data structures and provide a Python-like interface to them.

## Attributes

Attributes of an extension type are stored directly in the object's C struct. The set of attributes is fixed at compile time; you can't add attributes to an extension type instance at run time simply by assigning to them, as you could with a Python class instance. (You can subclass the extension type in Python and add attributes to instances of the subclass, however.)

There are two ways that attributes of an extension type can be accessed: by Python attribute lookup, or by direct access to the C struct from Cython code. Python code is only able to access attributes of an extension type by the first method, but Cython code can use either method.

By default, extension type attributes are only accessible by direct access, not Python access, which means that they are not accessible from Python code. To make them accessible from Python code, you need to declare them as `public` or `readonly`. For example,

> `cdef class Shrubbery:`
> `cdef public int width, height`
> `cdef readonly float depth`

makes the `width` and `height` attributes readable and writable from Python code, and the `depth` attribute readable but not writable.

Note that you can only expose simple C types, such as ints, floats and strings, for Python access. You can also expose Python-valued attributes, although read-write exposure is only possible for generic Python attributes (of type `object`). If the attribute is declared to be of an extension type, it must be exposed `readonly`.

Note also that the `public` and `readonly` options apply only to Python access, not direct access. All the attributes of an extension type are always readable and writable by direct access.

Howerver, for direct access to be possible, the Cython compiler must know that you have an instance of that type, and not just a generic Python object. It knows this already in the case of the "self" parameter of the methods of that type, but in other cases you will have to tell it by means of a declaration. For example,

> `cdef widen_shrubbery(Shrubbery sh, extra_width):`
> `sh.width = sh.width + extra_width`

If you attempt to access an extension type attribute through a generic object reference, Cython will use a Python attribute lookup. If the attribute is exposed for Python access (using `public` or `readonly`) then this will work, but it will be much slower than direct access.

## Extension types and None

When you declare a parameter or C variable as being of an extension type, Cython will allow it to take on the value None as well as values of its declared type. This is analogous to the way a C pointer can take on the value NULL, and you need to exercise the same caution because of it. There is no problem as long as you are performing Python operations on it, because full dynamic type checking will be applied. However, when you access C attributes of an extension type (as in the `widen_shrubbery` function above), it's up to you to make sure the reference you're using is not None -- in the interests of efficiency, Cython does not check this.

You need to be particularly careful when exposing Python functions which take extension types as arguments. If we wanted to make `widen_shrubbery` a Python function, for example, if we simply wrote

> `def widen_shrubbery(Shrubbery sh, extra_width): # This is`
> `sh.width = sh.width + extra_width # dangerous!`

then users of our module could crash it by passing None for the `sh` parameter.

One way to fix this would be

> `def widen_shrubbery(Shrubbery sh, extra_width):`
> `if sh is None:`
> `raise TypeError`
> `sh.width = sh.width + extra_width`

but since this is anticipated to be such a frequent requirement, Cython provides a more convenient way. Parameters of a Python function declared as an extension type can have a `not None` clause:

> `def widen_shrubbery(Shrubbery sh not None, extra_width):`
> `sh.width = sh.width + extra_width`

Now the function will automatically check that `sh` is not None along with checking that it has the right type.

Note, however that the `not None` clause can only be used in Python functions (defined with `def`) and not C functions (defined with `cdef`). If you need to check whether a parameter to a C function is None, you will need to do it yourself.

Some more things to note:

- The self parameter of a method of an extension type is guaranteed never to be None.

- When comparing a value with None, keep in mind that, if `x` is a Python object, `x is None` and `x is not None` are very efficient because they translate directly to C pointer comparisons, whereas `x == None` and `x != None`, or simply using `x` as a boolean value (as in `if x: ...`) will invoke Python operations and therefore be much slower.

## Special methods

Although the principles are similar, there are substantial differences between many of the __xxx__ special methods of extension types and their Python counterparts. There is a separate page devoted to this subject, and you should read it carefully before attempting to use any special methods in your extension types.

## Properties

There is a special syntax for defining properties in an extension class:

> `cdef class Spam:`

> `property cheese:`

> `"A doc string can go here."`

> `def __get__(self):`
> `# This is called when the property is read.`
> `...`

> `def __set__(self, value):`
> `# This is called when the property is written.`
> `...`

> `def __del__(self):`
> `# This is called when the property is deleted.`

The `__get__`, `__set__` and `__del__` methods are all optional; if they are omitted, an exception will be raised when the corresponding operation is attempted.

Here's a complete example. It defines a property which adds to a list each time it is written to, returns the list when it is read, and empties the list when it is deleted.

`cheesy.pyx` | Test input
`cdef class CheeseShop:` `cdef object cheeses` `def __new__(self):` `self.cheeses = []` `property cheese:` `def __get__(self):` `return "We don't have: %s" % self.cheeses` `def __set__(self, value):` `self.cheeses.append(value)` `def __del__(self):` `del self.cheeses[:]` | `from cheesy import CheeseShop` `shop = CheeseShop()` `print shop.cheese` `shop.cheese = "camembert"` `print shop.cheese` `shop.cheese = "cheddar"` `print shop.cheese` `del shop.cheese` `print shop.cheese`
Test output
`We don't have: []` `We don't have: ['camembert']` `We don't have: ['camembert', 'cheddar']` `We don't have: []`

## Subclassing

An extension type may inherit from a built-in type or another extension type:

> `cdef class Parrot:`
> `...```

> `cdef class Norwegian(Parrot):`
> `...`

A complete definition of the base type must be available to Cython, so if the base type is a built-in type, it must have been previously declared as an extern extension type. If the base type is defined in another Cython module, it must either be declared as an extern extension type or imported using the cimport statement.

An extension type can only have one base class (no multiple inheritance).

Cython extension types can also be subclassed in Python. A Python class can inherit from multiple extension types provided that the usual Python rules for multiple inheritance are followed (i.e. the C layouts of all the base classes must be compatible).

## C methods

Extension types can have C methods as well as Python methods. Like C functions, C methods are declared using `cdef` instead of `def`. C methods are "virtual", and may be overridden in derived extension types.

`pets.pyx` | Output
`cdef class Parrot: cdef void describe(self): print "This parrot is resting." cdef class Norwegian(Parrot): cdef void describe(self): Parrot.describe(self) print "Lovely plumage!" cdef Parrot p1, p2 p1 = Parrot() p2 = Norwegian() print "p1:" p1.describe() print "p2:" p2.describe()` | `p1: This parrot is resting. p2:` `This parrot is resting.` `Lovely plumage!`

The above example also illustrates that a C method can call an inherited C method using the usual Python technique, i.e.

> `Parrot.describe(self)`

## Forward-declaring extension types

Extension types can be forward-declared, like struct and union types. This will be necessary if you have two extension types that need to refer to each other, e.g.

> `cdef class Shrubbery # forward declaration`

> `cdef class Shrubber:`
> `cdef Shrubbery work_in_progress`

> `cdef class Shrubbery:`
> `cdef Shrubber creator`

If you are forward-declaring an exension type that has a base class, you must specify the base class in both the forward declaration and its subsequent definition, for example,

> `cdef class A(B)
> ...
> cdef class A(B):
> # attributes and methods`

## Making extension types weak-referenceable

By default, extension types do not support having weak references made to them. You can enable weak referencing by declaring a C attribute of type object called __weakref__. For example,
cdef class ExplodingAnimal:
"""This animal will self-destruct when it is
no longer strongly referenced."""
cdef object __weakref__

## Public and external extension types

Extension types can be declared extern or public. An extern extension type declaration makes an extension type defined in external C code available to a Cython module. A public extension type declaration makes an extension type defined in a Cython module available to external C code.

### External extension types

An extern extension type allows you to gain access to the internals of Python objects defined in the Python core or in a non-Cython extension module.

> NOTE: In Cython versions before 0.8, extern extension types were also used to reference extension types defined in another Cython module. While you can still do that, Cython 0.8 and later provides a better mechanism for this. See Sharing C Declarations Between Cython Modules.

Here is an example which will let you get at the C-level members of the built-in complex object.

> `cdef extern from "complexobject.h":`

> `struct Py_complex:`
> `double real`
> `double imag`

> `ctypedef class __builtin__.complex [object PyComplexObject]:`
> `cdef Py_complex cval`

> `# A function which uses the above type`
> `def spam(complex c):`
> `print "Real:", c.cval.real`
> `print "Imag:", c.cval.imag`

Some important things to note are:

1. In this example, ctypedef class has been used. This is because, in the Python header files, the `PyComplexObject` struct is declared with
   `ctypedef struct {`
   `...`
   `} PyComplexObject;
   `
2. As well as the name of the extension type, the module in which its type object can be found is also specified. See the implicit importing section below.
3. When declaring an external extension type, you don't declare any methods. Declaration of methods is not required in order to call them, because the calls are Python method calls. Also, as with structs and unions, if your extension class declaration is inside a cdef extern from block, you only need to declare those C members which you wish to access.

### Implicit importing

> Backwards Incompatibility Note: You will have to update any pre-0.8 Cython modules you have which use extern extension types. I apologise for this, but for complicated reasons it proved to be too difficult to continue supporting the old way of doing these while introducing the new features that I wanted.

Cython 0.8 and later requires you to include a module name in an extern extension class declaration, for example,

> `cdef extern class MyModule.Spam:`
> `...`

The type object will be implicitly imported from the specified module and bound to the corresponding name in this module. In other words, in this example an implicit

    from MyModule import Spam

statement will be executed at module load time.

The module name can be a dotted name to refer to a module inside a package hierarchy, for example,

> `cdef extern class My.Nested.Package.Spam:`
> `...`

You can also specify an alternative name under which to import the type using an as clause, for example,

`cdef extern class My.Nested.Package.Spam as Yummy:`
`...`

which corresponds to the implicit import statement

    from My.Nested.Package import Spam as Yummy

### Type names vs. constructor names

Inside a Cython module, the name of an extension type serves two distinct purposes. When used in an expression, it refers to a module-level global variable holding the type's constructor (i.e. its type-object). However, it can also be used as a C type name to declare variables, arguments and return values of that type.

When you declare

> `cdef extern class MyModule.Spam:`
> `...`

the name `Spam` serves both these roles. There may be other names by which you can refer to the constructor, but only `Spam` can be used as a type name. For example, if you were to explicity `import MyModule`, you could use`MyModule.Spam()` to create a Spam instance, but you wouldn't be able to use `MyModule.Spam` as a type name.

When an as clause is used, the name specified in the as clause also takes over both roles. So if you declare

> `cdef extern class MyModule.Spam as Yummy:`
> `...`

then `Yummy` becomes both the type name and a name for the constructor. Again, there are other ways that you could get hold of the constructor, but only `Yummy` is usable as a type name.

### Public extension types

An extension type can be declared public, in which case a .h file is generated containing declarations for its object struct and type object. By including the .h file in external C code that you write, that code can access the attributes of the extension type.

### Name specification clause

The part of the class declaration in square brackets is a special feature only available for extern or public extension types. The full form of this clause is

> `[object` object_struct_name`, type` type_object_name ]

where object_struct_name is the name to assume for the type's C struct, and type_object_name is the name to assume for the type's statically declared type object. (The object and type clauses can be written in either order.)

If the extension type declaration is inside a cdef extern from block, the object clause is required, because Cython must be able to generate code that is compatible with the declarations in the header file. Otherwise, for extern extension types, the object clause is optional.

For public extension types, the object and type clauses are both required, because Cython must be able to generate code that is compatible with external C code.

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