Hi all,
after I updated the pyrex code to use cython, a bit of confusion led
me to using .pxi includes instead of .pxd files and cimport. That
turned out to be mistaken, as later clarified by the Cython team:
http://codespeak.net/pipermail/cython-dev/2008-April/000628.html
Would anyone object to my fixing the code to the new convention? The
changes are minimal, the .pxi files can just be renamed and then a few
trivial modifications are done. But I figured since this gets shipped
as canonical example code, vetting from the core developers is a good
idea.
In particular, I used:
# Import the pieces of the Python C API we need to use (from c_python.pxd):
cimport c_python as py
# Import the NumPy C API (from c_numpy.pxd)
cimport c_numpy as cnp
# Import the NumPy module for access to its usual Python API
import numpy as np
I don't know if those are the conventions people want to use. I went
with 'cnp' for symmetry, and plain 'py' for simplicity.
The patch is otherwise an inconsequential adding of those prefixes,
since the old include mechanism was equivalent to an 'import *' while
this gives us a namespace. I've attached the diff for the numpyx file
here for review (the actual diff is lager because of the renames, but
there's no code changes there).
Stefan, core team?
Cheers,
f
Index: numpyx.pyx
===================================================================
--- numpyx.pyx (revision 5297)
+++ numpyx.pyx (working copy)
@@ -3,20 +3,22 @@
"""
# Includes from the python headers
-include "Python.pxi"
+#include "Python.pxi"
+cimport c_python as py
+
# Include the Numpy C API for use via Cython extension code
-include "numpy.pxi"
+#include "numpy.pxi"
+cimport c_numpy as cnp
################################################
# Initialize numpy - this MUST be done before any other code is executed.
-import_array()
+cnp.import_array()
# Import the Numpy module for access to its usual Python API
import numpy as np
-
# A 'def' function is visible in the Python-imported module
-def print_array_info(ndarray arr):
+def print_array_info(cnp.ndarray arr):
"""Simple information printer about an array.
Code meant to illustrate Cython/NumPy integration only."""
@@ -24,19 +26,19 @@
cdef int i
print '-='*10
- # Note: the double cast here (void * first, then Py_intptr_t) is needed in
- # Cython but not in Pyrex, since the casting behavior of cython is slightly
- # different (and generally safer) than that of Pyrex. In this case, we
- # just want the memory address of the actual Array object, so we cast it to
- # void before doing the Py_intptr_t cast:
+ # Note: the double cast here (void * first, then py.Py_intptr_t) is needed
+ # in Cython but not in Pyrex, since the casting behavior of cython is
+ # slightly different (and generally safer) than that of Pyrex. In this
+ # case, we just want the memory address of the actual Array object, so we
+ # cast it to void before doing the py.Py_intptr_t cast:
print 'Printing array info for ndarray at 0x%0lx'% \
- (<Py_intptr_t><void *>arr,)
+ (<py.Py_intptr_t><void *>arr,)
print 'number of dimensions:',arr.nd
- print 'address of strides: 0x%0lx'%(<Py_intptr_t>arr.strides,)
+ print 'address of strides: 0x%0lx'%(<py.Py_intptr_t>arr.strides,)
print 'strides:'
for i from 0<=i<arr.nd:
# print each stride
- print ' stride %d:'%i,<Py_intptr_t>arr.strides[i]
+ print ' stride %d:'%i,<py.Py_intptr_t>arr.strides[i]
print 'memory dump:'
print_elements( arr.data, arr.strides, arr.dimensions,
arr.nd, sizeof(double), arr.dtype )
@@ -46,12 +48,12 @@
# A 'cdef' function is NOT visible to the python side, but it is accessible to
# the rest of this Cython module
cdef print_elements(char *data,
- Py_intptr_t* strides,
- Py_intptr_t* dimensions,
+ py.Py_intptr_t* strides,
+ py.Py_intptr_t* dimensions,
int nd,
int elsize,
object dtype):
- cdef Py_intptr_t i,j
+ cdef py.Py_intptr_t i,j
cdef void* elptr
if dtype not in [np.dtype(np.object_),
@@ -78,7 +80,7 @@
print_elements(data, strides+1, dimensions+1, nd-1, elsize, dtype)
data = data + strides[0]
-def test_methods(ndarray arr):
+def test_methods(cnp.ndarray arr):
"""Test a few attribute accesses for an array.
This illustrates how the pyrex-visible object is in practice a strange
_______________________________________________
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
