Comments on: Benchmarking Python decimal vs. float http://jboxer.com/2009/03/benchmarking-python-decimal-vs-float/ I change the directions of small pieces of metal for a living. Fri, 20 Aug 2010 19:29:20 -0700 hourly 1 http://wordpress.org/?v=3.0.1 By: Burton Haynes http://jboxer.com/2009/03/benchmarking-python-decimal-vs-float/comment-page-1/#comment-248 Burton Haynes Sat, 06 Mar 2010 23:30:47 +0000 http://jboxer.com/?p=140#comment-248 Cool Thanks for the article. I am starting development and this will help a lot. Cool Thanks for the article. I am starting development and this will help a lot.

]]> By: Ronny Pfannschmidt http://jboxer.com/2009/03/benchmarking-python-decimal-vs-float/comment-page-1/#comment-20 Ronny Pfannschmidt Tue, 17 Mar 2009 12:47:52 +0000 http://jboxer.com/?p=140#comment-20 sorry, your tests are invalid please kill the io parts and redo with the timeit module testing only the expressions and not the outout sorry, your tests are invalid

please kill the io parts and redo with the timeit module testing only the expressions and not the outout

]]> By: Marek Kubica http://jboxer.com/2009/03/benchmarking-python-decimal-vs-float/comment-page-1/#comment-19 Marek Kubica Tue, 17 Mar 2009 10:43:45 +0000 http://jboxer.com/?p=140#comment-19 You might want to check out the ``timeit`` module in the Python stdlib which is specifically designed to test the speeds of code snippets. It runs the code many times and as the code runs in one interpreter it doesn't need to include the cost of interpreter startups (memory allocations, library loading, disk seeks to get the files into memory, etc.) and exits (freeing memory) as ``time`` does. Plus, it uses the most accurate timer that Python can find of your platform which means that it runs on any system that Python runs on. You might want to check out the “timeit“ module in the Python stdlib which is specifically designed to test the speeds of code snippets. It runs the code many times and as the code runs in one interpreter it doesn’t need to include the cost of interpreter startups (memory allocations, library loading, disk seeks to get the files into memory, etc.) and exits (freeing memory) as “time“ does. Plus, it uses the most accurate timer that Python can find of your platform which means that it runs on any system that Python runs on.

]]>