Cythonize is special?

Hello. How exactly is:

from distutils.core import setup
from Cython.Build import cythonize
setup(
    name = "My hello app",
    ext_modules = cythonize('hello.pyx'), # accepts a glob pattern
)

different from:

from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext
setup (
	ext_modules = [ Extension ( "hello", [ "hello.pyx" ] ) ],
	cmdclass    = { "build_ext" : build_ext }
)

Is it just that the former is somewhat shorter, especially seeing as
the docstring for cythonize says: ""Compile a set of source modules
into C/C++ files and return a list of distutils Extension objects for
them.""

Or is there any other essential difference that makes using Cythonize
preferable to manually specifying the Extension params?

Thanks.

--

-- 

Win7 Python 2.7 Cython helloworld example compile error ! help ,please

Cython c compiler setting

First Cython ModuleI

Type error

for loop with variable step not optimized

Spiro Python interface using Cython

Spiro is an algorithm for producing smooth splines given a set of
on-curve control points. I am working on polishing the library. I
wrote a Python interface using Cython (thanks to all those who develop
it!).

The Spiro library uses callbacks, hence my recent in doing that in
Cython. I am happy to say I have been successful. The attached code
demonstrates it to whoever can spend the time to read it. The code is
under the GPLv3+. (Note: you don't need to worry about the internals
of spiro.c -- just look at spiro.h and bezctx.h to understand the
library being wrapped.)

I have one question: Clang generates the warning:

spiro_cy.c:653:1: warning: declaration does not declare anything
[-Wmissing-declarations]
spiro_cp;
^~~~~~~~
1 warning generated.

Why is this and what should I do to fix it? Thanks.

-- 
Shriramana Sharma ஶ்ரீரமணஶர்மா श्रीरमणशर्मा

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OSX 10.8: setuptools generates gcc command that wants to use to use .c instead of .cpp

Sorting algorithm

cython's property and nondata descriptors

Two questions about cython's "property:" directive.

1] In python, a nondata descriptor is a descriptor that doesn't have
its '__set__' slot filled. Such descriptors can be overridden by
entries in the instance '__dict__'. One might expect that specifying a
cython "property" without giving a "__set__" method would lead to such
an entry, but it doesn't: It leads to a datadescriptor that cannot be
overridden by instance attributes:

%cython
cdef class T(object):
    property B:
        def __get__(self):
            return 1

>>> class S(T): pass
>>> s=S()
>>> s.B=10
AttributeError: attribute 'B' of 'T' objects is not writable

This mirrors the  <at> property decorator in python but it makes it hard to
specify nondata descriptors. Are there thoughts about how to make it
more convenient to declare nondata descriptors

2] Using the  <at> property decorator in a cdef class works, but leads to
less efficient code:

%cython
cdef class T(object):
    property B:
        def __get__(self):
            return 1
     <at> property
    def C(self):
        return 1

>>> t=T()
>>> timeit("t.B")
625 loops, best of 3: 78.6 ns per loop
>>> timeit("t.C")
625 loops, best of 3: 275 ns per loop

would it be desirable to automatically transcribe " <at> property" to
"property .."? Perhaps not, since the semantics of the two are
different and both are valid, but I expect it's a common pitfall for
people who try to translate python to cython code.

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static typing of mpf type variables in cython