Cython. April 2008 Brian Blais

Size: px

Start display at page:

Download "Cython. April 2008 Brian Blais"

Dwain Randolf Wright
6 years ago
Views:

1 Cython O p t i m i z a t i o n i n P y t h o n April 2008 Brian Blais

2 Rule #1 of Optimization Premature optimization is the root of all evil - Donald Knuth

3 What is Cython/Pyrex? Python to C/Python-API Converter Extension modules to optimize code

4 Example.pyx import numpy def this(): print "hello world" a=5 b=numpy.abs(a)

5 Example.C static char pyx_k_2[] = "hello world"; pyx_v_a = Py_None; Py_INCREF(Py_None); pyx_v_b = Py_None; Py_INCREF(Py_None); /* print "hello world" */ if ( Pyx_PrintItem( pyx_k_2p) < 0) { pyx_filename = pyx_f[0]; pyx_lineno = 5; goto pyx_l1;} if ( Pyx_PrintNewline() < 0) { pyx_filename = pyx _f[0]; pyx_lineno = 5; goto pyx_l1;}

6 Example.C static PyObject * pyx_num_5; Py_INCREF( pyx_num_5); Py_DECREF( pyx_v_a); pyx_v_a = pyx_num_5;

7 Example.C pyx_1 = Pyx_GetName( pyx_m, pyx_n_numpy); if (unlikely(! pyx_1)) { pyx_filename = pyx_f [0]; pyx_lineno = 9; goto pyx_l1;} pyx_2 = PyObject_GetAttr( pyx_1, pyx_n_abs); if (unlikely(! pyx_2)) { pyx_filename = pyx_f[0]; pyx_lineno = 9; goto pyx_l1;} Py_DECREF( pyx_1); pyx_1 = 0; pyx_1 = PyTuple_New(1); if (unlikely(! pyx_1)) { pyx_filename = pyx_f[0]; pyx_lineno = 9; goto pyx_l1;} Py_INCREF( pyx_v_a); PyTuple_SET_ITEM( pyx_1, 0, pyx_v_a); pyx_3 = PyObject_Call( pyx_2, pyx_1, NULL); if (unlikely(! pyx_3)) { pyx_filename = pyx_f [0]; pyx_lineno = 9; goto pyx_l1;} Py_DECREF( pyx_2); pyx_2 = 0; Py_DECREF( pyx_1); pyx_1 = 0; Py_DECREF( pyx_v_b);

8 Cython vs Pyrex Cython is a recent branch off of Pyrex, related to the Sage project list comprehensions inplace operators boolean int type etc... Basically the same...will use Cython here

9 requirements/ Suggestions Python C compiler Cython - ipython, numpy, scipy, matplotlib

10 Windows Setup Run the MinGW Installer: extract to folder c:\mingw Copy the distutils.cfg to C:\Python25\Lib\distutils Right-click My Computer/Properties/Advanced/ Environment Variables add c:\python25;c:\mingw\bin to the path %SystemRoot%\system32;%SystemRoot%;%SystemRoot% \System32\Wbem;c:\mingw\bin;c:\python25

11 sum_python.py def my_sum(n): s=0 for k in range(n): s+=k return s

12 sum_python.py def my_sum(n): s=0 for k in range(n): s+=k return s In [2] :from sum_python import my_sum as python In [3]:python(100000) Out[3]: L In [4]:timeit python(100000) 100 loops, best of 3: 16.7 ms per loop

13 sum_cython1.pyx def my_sum(long long N): cdef long long k,s=0 for k in range(n): s+=k return s

14 sum_cython1.pyx In [1]:from cython_compile import * In [2]:compile('sum_cython1.pyx') running build_ext cythoning sum_cython1.pyx to sum_cython1.c building 'sum_cython1' extension creating build creating build/temp.macosx-10.3-fat-2.5 gcc -arch ppc -arch i o sum_cython1.so

15 sum_cython1.pyx def my_sum(long long N): cdef long long k,s=0 for k in range(n): s+=k return s In [3]:from sum_cython1 import my_sum as cython1 In [4]:cython1(100000) Out[4]: L In [5]:timeit cython1(100000) 100 loops, best of 3: 3.76 ms per loop

16 sum_python.py def my_sum(n): s=0 for k in range(n): s+=k return s In [2] :from sum_python import my_sum as python In [3]:python(100000) Out[3]: L In [4]:timeit python(100000) 100 loops, best of 3: 16.7 ms per loop

17 sum_cython2.pyx def my_sum(long long N): cdef long long k,s=0 for k from 0<=k<N: s+=k return s

18 sum_cython2.pyx def my_sum(long long N): cdef long long k,s=0 for k from 0<=k<N: s+=k return s In [12]:timeit python(100000) 100 loops, best of 3: 16.6 ms per loop In [13]:timeit cython1(100000) 100 loops, best of 3: 3.74 ms per loop In [14]:timeit cython2(100000) 1000 loops, best of 3: 314 µs per loop

19 dot.pyx cimport c_python cimport c_numpy c_numpy.import_array() # Numpy must be initialized def dotty(c_numpy.ndarray A1,c_numpy.ndarray A2): cdef int length=a1.dimensions[0] cdef int k cdef double s=0.0 cdef double *a1=<double *>A1.data cdef double *a2=<double *>A2.data for k from 0<=k<length: s+=a1[k]*a2[k] return s

20 dot.pyx In In In In [0]:from dot import * [1]:from numpy import * [2]:r=random.rand(10000) [3]:r2=list(r2) In [4]:timeit sum([a*b for a,b in zip(r2,r2)]) 100 loops, best of 3: 9.74 ms per loop In [5]:timeit dotty(r,r) loops, best of 3: 12.9 µs per loop In [6]:timeit dot(r,r) loops, best of 3: 14 µs per loop In [9]:timeit sum(r*r) loops, best of 3: 175 µs per loop

21 Gotchas! Forgetting a cdef Wrong type (float vs double) For-loop mistake Too much python

22 Appendix

23 Distutils.cfg [build] compiler=mingw32

24 Setup.py from distutils.core import setup from distutils.extension import Extension from Cython.Distutils import build_ext import numpy incdirs=[numpy.get_include()] setup( name = 'Demos', ext_modules=[ Extension("sum_cython2",["sum_cython2.pyx"], include_dirs = incdirs) ], cmdclass = {'build_ext': build_ext} )

Python is awesome. awesomeness C/gcc C++/gcc Java 6 Go/6g Haskell/GHC Scala Lisp SBCL C#/Mono OCaml Python

Python is awesome. awesomeness C/gcc C++/gcc Java 6 Go/6g Haskell/GHC Scala Lisp SBCL C#/Mono OCaml Python Python is awesome 30 28.07 awesomeness 22.5 15 7.5 0 2.95 3.35 2.16 2.22 2.67 1.55 2.01 1.07 1.19 C/gcc C++/gcc Java 6 Go/6g Haskell/GHC Scala Lisp SBCL C#/Mono OCaml Python A benchmark http://geetduggal.wordpress.com/2010/11/25/speed-up-your-python-unladen-vs-shedskin-vs-pypy-vs-c/