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Please note that the code described here is slightly out of date, since today cython is the actively maintained version of Pyrex, and numpy now ships with Cython examples.

Rather than maintaining both the wiki and the source dir, we'll continue to update the sources, kept here.

Old Pyrex page

Pyrex is a language for writing C extensions to Python. Its syntax is very similar to writing Python. A .pyx file is compiled to a .c file, which is then compiled like a standard C extension module for Python. Many people find writing extension modules with Pyrex preferable to writing them in C or using other tools, such as SWIG.

This page is a starting point for accessing numpy arrays natively with Pyrex. Please note that with current versions of NumPy (SVN), the directory numpy/doc/pyrex contains a complete working example with the code in this page, including also a proper setup.py file so you can install it with the standard Python mechanisms. This should help you get up and running quickly.

Here's a file I call "c_python.pxd":

cdef extern from "Python.h":
    ctypedef int Py_intptr_t

and here's "c_numpy.pxd":

cimport c_python

cdef extern from "numpy/arrayobject.h":
    ctypedef class numpy.ndarray [object PyArrayObject]:
        cdef char *data
        cdef int nd
        cdef c_python.Py_intptr_t *dimensions
        cdef c_python.Py_intptr_t *strides
        cdef object base
        # descr not implemented yet here...
        cdef int flags
        cdef int itemsize
        cdef object weakreflist

    cdef void import_array()

Here's an example program, name this something like "test.pyx" suffix.

cimport c_numpy
cimport c_python
import numpy

c_numpy.import_array()

def print_array_info(c_numpy.ndarray arr):
    cdef int i

    print '-='*10
    print 'printing array info for ndarray at 0x%0lx'%(<c_python.Py_intptr_t>arr,)
    print 'print number of dimensions:',arr.nd
    print 'address of strides: 0x%0lx'%(<c_python.Py_intptr_t>arr.strides,)
    print 'strides:'
    for i from 0<=i<arr.nd:
        # print each stride
        print '  stride %d:'%i,<c_python.Py_intptr_t>arr.strides[i]
    print 'memory dump:'
    print_elements( arr.data, arr.strides, arr.dimensions, arr.nd, sizeof(double), arr.dtype )
    print '-='*10
    print

cdef print_elements(char *data,
                    c_python.Py_intptr_t* strides,
                    c_python.Py_intptr_t* dimensions,
                    int nd,
                    int elsize,
                    object dtype):
    cdef c_python.Py_intptr_t i,j
    cdef void* elptr

    if dtype not in [numpy.dtype(numpy.object_),
                     numpy.dtype(numpy.float64)]:
        print '   print_elements() not (yet) implemented for dtype %s'%dtype.name
        return

    if nd ==0:
        if dtype==numpy.dtype(numpy.object_):
            elptr = (<void**>data)[0] #[0] dereferences pointer in Pyrex
            print '  ',<object>elptr
        elif dtype==numpy.dtype(numpy.float64):
            print '  ',(<double*>data)[0]
    elif nd == 1:
        for i from 0<=i<dimensions[0]:
            if dtype==numpy.dtype(numpy.object_):
                elptr = (<void**>data)[0]
                print '  ',<object>elptr
            elif dtype==numpy.dtype(numpy.float64):
                print '  ',(<double*>data)[0]
            data = data + strides[0]
    else:
        for i from 0<=i<dimensions[0]:
            print_elements(data, strides+1, dimensions+1, nd-1, elsize, dtype)
            data = data + strides[0]

def test():
    """this function is pure Python"""
    arr1 = numpy.array(-1e-30,dtype=numpy.Float64)
    arr2 = numpy.array([1.0,2.0,3.0],dtype=numpy.Float64)

    arr3 = numpy.arange(9,dtype=numpy.Float64)
    arr3.shape = 3,3

    four = 4
    arr4 = numpy.array(['one','two',3,four],dtype=numpy.object_)

    arr5 = numpy.array([1,2,3]) # int types not (yet) supported by print_elements

    for arr in [arr1,arr2,arr3,arr4,arr5]:
        print_array_info(arr)

Now, if you compile and install the above test.pyx, the output of python -c "import pyrex_and_numpy.test as t; t.test()" should be something like the following:

-=-=-=-=-=-=-=-=-=-=
printing array info for ndarray at 0x8184508
print number of dimensions: 0
address of strides: 0xb764f7ec
strides:
memory dump:
   -1e-30
-=-=-=-=-=-=-=-=-=-=

-=-=-=-=-=-=-=-=-=-=
printing array info for ndarray at 0x8190060
print number of dimensions: 1
address of strides: 0x818453c
strides:
  stride 0: 8
memory dump:
   1.0
   2.0
   3.0
-=-=-=-=-=-=-=-=-=-=

-=-=-=-=-=-=-=-=-=-=
printing array info for ndarray at 0x82698a0
print number of dimensions: 2
address of strides: 0x8190098
strides:
  stride 0: 24
  stride 1: 8
memory dump:
   0.0
   1.0
   2.0
   3.0
   4.0
   5.0
   6.0
   7.0
   8.0
-=-=-=-=-=-=-=-=-=-=

-=-=-=-=-=-=-=-=-=-=
printing array info for ndarray at 0x821d6e0
print number of dimensions: 1
address of strides: 0x818ed74
strides:
  stride 0: 4
memory dump:
   one
   two
   3
   4
-=-=-=-=-=-=-=-=-=-=

-=-=-=-=-=-=-=-=-=-=
printing array info for ndarray at 0x821d728
print number of dimensions: 1
address of strides: 0x821d75c
strides:
  stride 0: 4
memory dump:
   print_elements() not (yet) implemented for dtype int32
-=-=-=-=-=-=-=-=-=-=

The pytables project makes extensive use of Pyrex and numarray. See the pytables source code for more ideas.

See Also


CategoryCookbook

Cookbook/Pyrex and NumPy (last edited 2008-04-09 02:01:01 by FernandoPerez)