On Mon, Apr 05, 2010 at 05:43:41PM -0500, Travis Oliphant wrote:
I should have some time over the next couple of weeks, and I am very interested in refactoring the NumPy code to separate out the Python interface layer from the "library" layer as much as possible. I had some discussions with people at PyCon about making it easier for Jython, IronPython, and perhaps even other high-level languages to utilize NumPy.
Is there a willingness to consider as part of this reorganization creating a clear boundary between the NumPy library code and the Python-specific interface to it? What other re-organization thoughts are you having David?
I have been following discussion too well, so please pardon me if my answer is off topic or irrelevant... At work, we want to code in a mixture of Python and C, optimizing only the bottlenecks of the computation in C. When we want to use numerical facilities in C, we would like to benefit from the fact that numpy already went through the hard work of getting basic vectorized math compiled and running on the user's computer. Indeed, one of the issues that we have been facing lately is that deploying a Python application with some C can increase a lot the difficulty of building and installing due to the required C libraries. The reason I bring this up, is that your refactor could make it easier for C or Cython coders to use the numpy internal to do their own dirty work. If the corresponding functions are exposed in the numpy headers, it would be fairly easy to include them in a numpy.distutils-driven build, via a call to 'numpy.get_include()'. My 2 cents, Gaël