Using C++ in Cython¶
Overview¶
Cython v0.13 introduces native support for most of the C++ language. This means that the previous tricks that were used to wrap C++ classes (as described in http://wiki.cython.org/WrappingCPlusPlus_ForCython012AndLower) are no longer needed.
Wrapping C++ classes with Cython is now much more straightforward. This document describe in details the new way of wrapping C++ code.
What’s new in Cython v0.13 about C++¶
For users of previous Cython versions, here is a brief overview of the main new features of Cython v0.13 regarding C++ support:
- C++ objects can now be dynamically allocated with new and del keywords.
- C++ objects can now be stack-allocated.
- C++ classes can be declared with the new keyword cppclass.
- Templated classes are supported.
- Overloaded functions are supported.
- Overloading of C++ operators (such as operator+, operator[],...) is supported.
Procedure Overview¶
The general procedure for wrapping a C++ file can now be described as follow:
- Specify C++ language in setup.py script
- Create cdef extern from blocks with the optional namespace (if exists) and the namespace name as string
- Declare classes as cdef cppclass blocks
- Declare public attributes (variables, methods and constructors)
A simple Tutorial¶
An example C++ API¶
Here is a tiny C++ API which we will use as an example throughout this document. Let’s assume it will be in a header file called Rectangle.h:
namespace shapes {
class Rectangle {
public:
int x0, y0, x1, y1;
Rectangle(int x0, int y0, int x1, int y1);
~Rectangle();
int getLength();
int getHeight();
int getArea();
void move(int dx, int dy);
};
}
and the implementation in the file called Rectangle.cpp:
#include "Rectangle.h"
using namespace shapes;
Rectangle::Rectangle(int X0, int Y0, int X1, int Y1)
{
x0 = X0;
y0 = Y0;
x1 = X1;
y1 = Y1;
}
Rectangle::~Rectangle()
{
}
int Rectangle::getLength()
{
return (x1 - x0);
}
int Rectangle::getHeight()
{
return (y1 - y0);
}
int Rectangle::getArea()
{
return (x1 - x0) * (y1 - y0);
}
void Rectangle::move(int dx, int dy)
{
x0 += dx;
y0 += dy;
x1 += dx;
y1 += dy;
}
This is pretty dumb, but should suffice to demonstrate the steps involved.
Specify C++ language in setup.py¶
In Cython setup.py scripts, one normally instantiates an Extension object. To make Cython generate and compile a C++ source, you just need to add the keyword language="c++" to your Extension construction statement, as in:
from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
setup(ext_modules=[Extension(
"rectangle", # name of extension
["rectangle.pyx", "Rectangle.cpp"], # our Cython source
language="c++")], # causes Cython to create C++ source
cmdclass={'build_ext': build_ext})
Cython will generate and compile the rectangle.cpp file (from the rectangle.pyx), then it will compile Rectangle.cpp (implementation of the Rectangle class) and link both objects files together into rectangle.so, which you can then import in Python using import rectangle (if you forget to link the Rectangle.o, you will get missing symbols while importing the library in Python).
Alternatively, one can also use the cython command-line utility to generate a C++ .cpp file, and then compile it into a python extension. C++ mode for the cython command is turned on with the --cplus option.
Declaring a C++ class interface¶
The procedure for wrapping a C++ class is quite similar to that for wrapping normal C structs, with a couple of additions. Let’s start here by creating the basic cdef extern from block:
cdef extern from "Rectangle.h" namespace "shapes":
This will make the C++ class def for Rectangle available. Note the namespace declaration.
Declare class with cdef cppclass¶
Now, let’s add the Rectangle class to this extern from block - just copy the class name from Rectangle.h and adjust for Cython syntax, so now it becomes:
cdef extern from "Rectangle.h" namespace "shapes":
cdef cppclass Rectangle:
Add public attributes¶
We now need to declare the attributes for use on Cython:
cdef extern from "Rectangle.h" namespace "shapes":
cdef cppclass Rectangle:
Rectangle(int, int, int, int)
int x0, y0, x1, y1
int getLength()
int getHeight()
int getArea()
void move(int, int)
Declare a var with the wrapped C++ class¶
Now, we use cdef to declare a var of the class with the C++ new statement:
cdef Rectangle *rec = new Rectangle(1, 2, 3, 4)
cdef int recLength = rec.getLength()
...
del rec #delete heap allocated object
It’s also possible to declare a stack allocated object, but it’s necessary to have a “default” constructor:
cdef extern from "Foo.h":
cdef cppclass Foo:
Foo()
cdef Foo foo
Note that, like C++, if the class has only one constructor and it is a default one, it’s not necessary to declare it.
Create Cython wrapper class¶
At this point, we have exposed into our pyx file’s namespace the interface of the C++ Rectangle type. Now, we need to make this accessible from external Python code (which is our whole point).
Common programming practice is to create a Cython extension type which holds a C++ instance pointer as an attribute thisptr, and create a bunch of forwarding methods. So we can implement the Python extension type as:
cdef class PyRectangle:
cdef Rectangle *thisptr # hold a C++ instance which we're wrapping
def __cinit__(self, int x0, int y0, int x1, int y1):
self.thisptr = new Rectangle(x0, y0, x1, y1)
def __dealloc__(self):
del self.thisptr
def getLength(self):
return self.thisptr.getLength()
def getHeight(self):
return self.thisptr.getHeight()
def getArea(self):
return self.thisptr.getArea()
def move(self, dx, dy):
self.thisptr.move(dx, dy)
And there we have it. From a Python perspective, this extension type will look and feel just like a natively defined Rectangle class. If you want to give attribute access, you could just implement some properties:
property x0:
def __get__(self): return self.thisptr.x0
def __set__(self, x0): self.thisptr.x0 = x0
...
Advanced C++ features¶
We describe here all the C++ features that were not discussed in the above tutorial.
Overloading¶
Overloading is very simple. Just declare the method with different parameters and use any of them:
cdef extern from "Foo.h":
cdef cppclass Foo:
Foo(int)
Foo(bool)
Foo(int, bool)
Foo(int, int)
Overloading operators¶
Cython uses C++ for overloading operators:
cdef extern from "foo.h":
cdef cppclass Foo:
Foo()
Foo* operator+(Foo*)
Foo* operator-(Foo)
int operator*(Foo*)
int operator/(int)
cdef Foo* foo = new Foo()
cdef int x
cdef Foo* foo2 = foo[0] + foo
foo2 = foo[0] - foo[0]
x = foo[0] * foo2
x = foo[0] / 1
cdef Foo f
foo = f + &f
foo2 = f - f
del foo, foo2
Nested class declarations¶
C++ allows nested class declaration. Class declarations can also be nested in Cython:
cdef extern from "<vector>" namespace "std":
cdef cppclass vector[T]:
cppclass iterator:
T operator*()
iterator operator++()
bint operator==(iterator)
bint operator!=(iterator)
vector()
void push_back(T&)
T& operator[](int)
T& at(int)
iterator begin()
iterator end()
cdef vector[int].iterator iter #iter is declared as being of type vector<int>::iterator
Note that the nested class is declared with a cppclass but without a cdef.
C++ operators not compatible with Python syntax¶
Cython try to keep a syntax as close as possible to standard Python. Because of this, certain C++ operators, like the preincrement ++foo or the dereferencing operator *foo cannot be used with the same syntax as C++. Cython provides functions replacing these operators in a special module cython.operator. The functions provided are:
- cython.operator.dereference for dereferencing. dereference(foo) will produce the C++ code *foo
- cython.operator.preincrement for pre-incrementation. preincrement(foo) will produce the C++ code ++foo
- ...
These functions need to be cimported. Of course, one can use a from ... cimport ... as to have shorter and more readable functions. For example: from cython.operator cimport dereference as deref.
Templates¶
Cython uses a bracket syntax for templating. A simple example for wrapping C++ vector:
from cython.operator cimport dereference as deref, preincrement as inc #dereference and increment operators
cdef extern from "<vector>" namespace "std":
cdef cppclass vector[T]:
cppclass iterator:
T operator*()
iterator operator++()
bint operator==(iterator)
bint operator!=(iterator)
vector()
void push_back(T&)
T& operator[](int)
T& at(int)
iterator begin()
iterator end()
cdef vector[int] *v = new vector[int]()
cdef int i
for i in range(10):
v.push_back(i)
cdef vector[int].iterator it = v.begin()
while it != v.end():
print deref(it)
inc(it)
del v
Multiple template parameters can be defined as a list, such as [T, U, V] or [int, bool, char].
Standard library¶
Most of the containers of the C++ Standard Library have been declared in pxd files located in /Cython/Includes/libcpp. These containers are: deque, list, map, pair, queue, set, stack, vector.
For example:
from libcpp.vector cimport vector
cdef vector[int] vect
cdef int i
for i in range(10):
vect.push_back(i)
for i in range(10):
print vect[i]
The pxd files in /Cython/Includes/libcpp also work as good examples on how to declare C++ classes.
Exceptions¶
Cython cannot throw C++ exceptions, or catch them with a try-except statement, but it is possible to declare a function as potentially raising an C++ exception and converting it into a Python exception. For example,
cdef extern from "some_file.h":
cdef int foo() except +
This will translate try and the C++ error into an appropriate Python exception. The translation is performed according to the following table (the std:: prefix is omitted from the C++ identifiers):
| C++ | Python |
|---|---|
| bad_alloc | MemoryError |
| bad_cast | TypeError |
| domain_error | ValueError |
| invalid_argument | ValueError |
| ios_base::failure | IOError |
| out_of_range | IndexError |
| overflow_error | OverflowError |
| range_error | ArithmeticError |
| underflow_error | ArithmeticError |
| (all others) | RuntimeError |
The what() message, if any, is preserved. Note that a C++ ios_base_failure can denote EOF, but does not carry enough information for Cython to discern that, so watch out with exception masks on IO streams.
cdef int bar() except +MemoryError
This will catch any C++ error and raise a Python MemoryError in its place. (Any Python exception is valid here.)
cdef int raise_py_error()
cdef int something_dangerous() except +raise_py_error
If something_dangerous raises a C++ exception then raise_py_error will be called, which allows one to do custom C++ to Python error “translations.” If raise_py_error does not actually raise an exception a RuntimeError will be raised.
Caveats and Limitations¶
Access to C-only functions¶
Whenever generating C++ code, Cython generates declarations of and calls to functions assuming these functions are C++ (ie, not declared as extern “C” {...} . This is ok if the C functions have C++ entry points, but if they’re C only, you will hit a roadblock. If you have a C++ Cython module needing to make calls to pure-C functions, you will need to write a small C++ shim module which:
- includes the needed C headers in an extern “C” block
- contains minimal forwarding functions in C++, each of which calls the respective pure-C function
Inherited C++ methods¶
If you have a class Foo with a child class Bar, and Foo has a method fred(), then you’ll have to cast to access this method from Bar objects. For example:
cdef class MyClass:
Bar *b
...
def myfunc(self):
...
b.fred() # wrong, won't work
(<Foo *>(self.b)).fred() # should work, Cython now thinks it's a 'Foo'
It might take some experimenting by others (you?) to find the most elegant ways of handling this issue.
Declaring/Using References¶
Question: How do you declare and call a function that takes a reference as an argument?
C++ left-values¶
C++ allows functions returning a reference to be left-values. This is currently not supported in Cython. cython.operator.dereference(foo) is also not considered a left-value.
