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  • 1. INTRODUCTION TO CYTHON John Saturday, December 21, 2013
  • 2. Overview • a superset of the Python language which give high-level, OO functional, and dynamic programming. • The source code translate to optimized C/C++ code and compiled as Python extension modules. • One word, Cython is Python with C data types.
  • 3. Installing Cython • Pythonxy already include Cython. • Use easy_install or pip install Cython from PYPI. $ python easy_install.py Cython $ pip install Cython
  • 4. First example: Building a Cython module “hello” hello.pyx def say_hello_to(name): print (“Hello %s!” % name) setup.py from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext ext_modules = [Extension("hello", ["hello.pyx"])] Run command line build the module $ python setup.py build_ext --inplace --compiler=mingw32 --inplace # How to run the function: >>> from hello import say_hello_to >>> say_hello_to(“John”) Hello John setup( name = 'Hello world app', cmdclass = {'build_ext': build_ext}, ext_modules = ext_modules )
  • 5. Static type declarations Cython can compile pure python code. To improve performance, use cdef add static type declarations # test1.pyx, 35% speedup def f(x): return x**2-x def integrate_f(a, b, N): s=0 dx = (b-a)/N for i in range(N): s += f(a+i*dx) return s*dx # 4 time speedup over python version def f(double x): return x**2-x def integrate_f(double a, double b, int N): cdef int i cdef double s, dx s=0 dx = (b-a)/N for i in range(N): s += f(a+i*dx) return s*dx
  • 6. Typing function #declare c-style function 150 times speedup cdef double f(double x) except ? -2: return x**2 - x >>> import hello >>> hasattr(hello,'f') False # if use cpdef instead of cdef, a Python wrapper is also created annotation tell you why your code take time $ cython.py -a hello.pyx a html (hello.html) is created, Click the yellow, you will get why the Python API is called here
  • 7. Calling C function A complete list of these cimport file see LibsitepackagesCythonIncludes from libc.math cimport sin cdef double f(double x): return sin(x*x) If Cython do not provide read-to-use declaration, access C code by cdef # instruct Cython generate C code that include math.h header file # C compiler will see it at compile time cdef extern from “math.h”: double sin(double) cdef double f(double x): return sin(x*x)
  • 8. Using C libraries Step 1: redefine .pxd head file Step 2: create a pyx define Queue class in Python # file: cqueue.pxd # copy most part of C head file here cdef extern from "libcalg/queue.h": ctypedef struct Queue: pass ctypedef void* QueueValue Queue* queue_new() void queue_free(Queue* queue) # file: queue.pyx cimport cqueue cdef class Queue: cdef cqueue.Queue *_c_queue def __cinit__(self): self._c_queue = cqueue.queue_new()
  • 9. Using C libraries - cont or step 3.2: include the lib in step 3.1: change the setup.py the option $ CFLAGS="change I/usr/local/otherdir/calg/include" ext_modules = [Extension("queue LDFLAGS="", ["queue.pyx"])] L/usr/local/otherdir/calg/lib" python setup.py build_ext -i to ext_modules = [ Extension("queu e", ["queue.pyx"], libraries=["calg"]) ] calg lib see Simon Howard, C Algorithms library, http://c-algorithms.sourceforge.net/
  • 10. Using C++ in Cython • Brief overview of C++ support in Cython(Cython v0.13) – C++ objects can now be dynamically allocated with new and del keywords. – C++ objects can 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.
  • 11. Review of this Slides 1. introduce the Cython 2. How to install Cython 3. An example show how to compile a Cython project 4. Optimize the pure Python code with Cython 5. Call C function in Python code 6. Use C library in Python code