## page was renamed from Cookbook/Pyrex And NumPy
Please note that the code described here is slightly out of date, since today [http://cython.org cython] is the actively maintained version of Pyrex, and numpy now ships with Cython examples.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 [http://projects.scipy.org/scipy/numpy/browser/trunk/numpy/doc/cython here].

== Old Pyrex page ==

[http://nz.cosc.canterbury.ac.nz/~greg/python/Pyrex/ 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":
{{{#!python numbers=disable
cdef extern from "Python.h":
    ctypedef int Py_intptr_t
}}}

and here's "c_numpy.pxd":
{{{#!python numbers=disable
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.

{{{#!python numbers=disable
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 [http://pytables.sourceforge.net/ pytables project] makes extensive use of Pyrex and numarray. See the pytables source code for more ideas.

= See Also =
 ["Cookbook/ArrayStruct_and_Pyrex"]

----
CategoryCookbook