this post was submitted on 27 Jun 2023
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For what it is worth, my take on the article. A really over whelming list. Nice read through but for those that are interested, the most useful components that were discussed were probably:
Since I talked about C code. There are three ways to integrate C code into python: ctypes, CFFI, and using the standard C extension method. I found ctypes to be about 107X, CFFI 108X, and the standard method about 112X for my code on my hardware with code which was using autoparallel and autovectorize, fastmath, and maybe other settings. My point, the speeds of these are about the same though the standard method is just a little faster. So you can really pretty much do whichever is easier.
Anyway my thoughts. Hope they make some sense.
Thanks. That's a big article, and some extra commentary and streamlining there is welcome!
Thanks. I love Python and have used since about 1998. The two areas where I have always found a little lacking is a) creating and app that you can actually give some one, b) computational speed when needed. So I am always interested in those two areas. A year or so ago I looked at a lot of the tools that that the article described, but there are one or two that were mentioned that are new to me. I think I will have to try when I get some time.