On 23 April 2018 at 05:00, Matthew Woodcraft email@example.com wrote:
To get comprehensible results, I think I really need to summarise the speed of a particular build+hardware combination as a single number, representing Python's performance for "general purpose code".
So does anyone have any recommendations on what the best figure to extract from pyperformance results would be?
There's no such number in the general case, since the way different aspects should be weighted differs significantly based on your use case (e.g. a long running server or GUI application may care very little about startup time, while it's critical for command line application responsiveness). That's why we have a benchmark suite, rather than just a single benchmark.
https://hackernoon.com/which-is-the-fastest-version-of-python-2ae7c61a6b2b is an example of going through and calling out specific benchmarks based on the kind of code they best represent.
So I don't think you're going to be able to get away from coming up with your own custom scheme that emphasises a particular usage profile. While the simplest approach is the one the linked article took (i.e. weight one benchmark at a time at 100%, ignore the others), searching for "combining multiple benchmark results into an aggregate score" returned https://pubsonline.informs.org/doi/pdf/10.1287/ited.2013.0124 as the first link for me, and based on skimming the abstract and introduction, I think it's likely to be quite relevant to your question.