I like this idea. I've seen this called "extern" in other projects, but I don't have a strong feeling about the name. I think it's good idea for all of the reasons you mention.
Mike ________________________________________ From: Ian Thomas [[email protected]] Sent: Sunday, October 06, 2013 4:09 PM To: [email protected] Subject: [matplotlib-devel] Directories for C/C++ extensions Fellow developers, I am working on a PR to replace the use of matplotlib.delaunay with the Qhull library. Installation will be similar to the existing packages LibAgg and CXX in that if the system already has a sufficiently recent version of Qhull installed then matplotlib will use that, otherwise it will build the required library from the source code shipped with matplotlib. I have a thin C wrapper called qhull_wrap.c (following the coding guidelines) which I'll put in the top-level src directory along with most of the existing C/C++ extensions. But my question is where to put the qhull source code? Current practice has separate top-level directories called agg24 and CXX for the LibAgg and CXX packages respectively, so my initial thought was to follow this and create a new top-level directory called qhull to place the library code in. But I don't like this approach of creating a new top-level directory as (1) I think the top-level should remain as simple and uncluttered as possible, (2) it tends to overemphasize the importance of these third-party libraries as they are some of the first directories users see when unzipping the mpl tarball, and (3) it is not immediately obvious that the code in these directories is from third-party libraries rather than something we ourselves have written. Hence my preference is to create a new top-level directory called something like 'third-party' (or should that be 'third_party'?), and place all the third-party libraries in that; i.e. move the agg24 and CXX directories into third-party, and place the new qhull source code in third-party/qhull. What do others think of this idea? Ian Thomas ------------------------------------------------------------------------------ October Webinars: Code for Performance Free Intel webinars can help you accelerate application performance. Explore tips for MPI, OpenMP, advanced profiling, and more. Get the most from the latest Intel processors and coprocessors. See abstracts and register > http://pubads.g.doubleclick.net/gampad/clk?id=60134791&iu=/4140/ostg.clktrk _______________________________________________ Matplotlib-devel mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
