WARNING: There are substantial differences in the way many of the special methods work in extension types compared to Python classes. Before attempting to define any __xxx__ methods, read the section on Special Methods of Extension Types. |
cdef class Shrubbery:As you can see, a Pyrex 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.cdef int width, height
def __init__(self, w, h):
self.width = w
self.height = hdef describe(self):
print "This shrubbery is", self.width, \
"by", self.height, "cubits."
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.
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 Pyrex code. Python code is only able to access attributes of an extension type by the first method, but Pyrex 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:makes the width and height attributes readable and writable from Python code, and the depth attribute readable but not writable.
cdef public int width, height
cdef readonly float depth
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.
Before you can directly access the attributes of an extension type, the Pyrex 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 use a type declaration.
For example, in the following function,
cdef widen_shrubbery(sh, extra_width): # BAD
sh.width = sh.width + extra_width
because the sh parameter hasn't been given a type, the width attribute will be accessed by a Python attribute lookup. If the attribute has been declared public or readonly then this will work, but it will be very inefficient. If the attribute is private, it will not work at all -- the code will compile, but an attribute error will be raised at run time.
The solution is to declare sh as being of type Shrubbery, as follows:
cdef widen_shrubbery(Shrubbery sh, extra_width):Now the Pyrex compiler knows that sh has a C attribute called width and will generate code to access it directly and efficiently. The same consideration applies to local variables, for example,
sh.width = sh.width + extra_width
cdef Shrubbery another_shrubbery(Shrubbery sh1):
cdef Shrubbery sh2
sh2 = Shrubbery()
sh2.width = sh1.width
sh2.height = sh1.height
return sh2
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 isthen users of our module could crash it by passing None for the sh parameter.
sh.width = sh.width + extra_width # dangerous!
One way to fix this would be
def widen_shrubbery(Shrubbery sh, extra_width):but since this is anticipated to be such a frequent requirement, Pyrex provides a more convenient way. Parameters of a Python function declared as an extension type can have a not None clause:
if sh is None:
raise TypeError
sh.width = sh.width + extra_width
def widen_shrubbery(Shrubbery sh not None, extra_width):Now the function will automatically check that sh is not None along with checking that it has the right type.
sh.width = sh.width + extra_width
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:
cdef class Spam:The __get__, __set__ and __del__ methods are all optional; if they are omitted, an exception will be raised when the corresponding operation is attempted.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.
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 __cinit__(self): property cheese: def __get__(self): def __set__(self, value): def __del__(self): |
from cheesy import CheeseShop
shop = CheeseShop() shop.cheese = "camembert" shop.cheese = "cheddar" del shop.cheese |
Test output | |
We don't have: [] We don't have: ['camembert'] We don't have: ['camembert', 'cheddar'] We don't have: [] |
cdef class Parrot:
...cdef class Norwegian(Parrot):
...
A complete definition of the base type must be available to Pyrex, 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 Pyrex
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).
Pyrex 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).
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! |
Parrot.describe(self)
cdef class Shrubbery # forward declarationcdef class Shrubber:
cdef Shrubbery work_in_progresscdef class Shrubbery:
cdef Shrubber creator
cdef class Hovercraft [nogc]:However, if there is a base type with Python attributes that participates in GC, any subclasses of it will also participate in GC regardless of their nogc options.
"""This object will not participate in cyclic gc
even though it has a Python attribute."""
cdef object eels
NOTE: In Pyrex versions before 0.8, extern extension types were also used to reference extension types defined in another Pyrex module. While you can still do that, Pyrex 0.8 and later provides a better mechanism for this. See Sharing C Declarations Between Pyrex 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":Some important things to note are:struct Py_complex:
double real
double imagctypedef 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
Backwards Incompatibility Note: You will have to update any pre-0.8 Pyrex 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.Pyrex 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
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,
...
from My.Nested.Package import Spam as Yummy
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.
...
[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 Pyrex 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 Pyrex must be able to generate code that is compatible with external C code.