Hi,

I'm still working on analyzing past optimizations to guide future optimizations. I succeeded to identify multiple significant optimizations over the last 3 years. At least for me, some were unexpected like "Use the test suite for profile data" which made pidigts 1.16x faster.

Here is a report of my work of last weeks.

I succeeded to compute benchmarks on CPython master on the period April, 2014-April,2017: we now have have a timeline over 3 years of CPython performance!

https://speed.python.org/timeline/

I started to take notes on significant performance changes (speedup and slowdown) of this timeline:

http://pyperformance.readthedocs.io/cpython_results_2017.html

To identify the change which introduced a significant performance change, I wrote a Python script running a Git bisection: compile CPython, run benchmark, repeat.

https://github.com/haypo/misc/blob/master/misc/bisect_cpython_perf.py

It uses a configuration file which looks like:

[config] work_dir = ~/prog/bench_python/bisect-pickle src_dir = ~/prog/bench_python/master

old_commit = 133138a284be1985ebd9ec9014f1306b9a42 new_commit = 10427f44852b6e872034061421a8890902b8f benchmark = ~/prog/bench_python/performance/performance/benchmarks/bm_pickle.py pickle

benchmark_opts = --inherit-environ=PYTHONPATH -p5 -v configure_args =

I succeeded to identify many significant optimizations (TODO: validate them on the speed-python server), examples:

• PyMem_Malloc() now uses the fast pymalloc allocator
• Add a C implementation of collections.OrderedDict
• Use the test suite for profile data
• Speedup method calls 1.2x
• Added C implementation of functools.lru_cache()
• Optimized ElementTree.iterparse(); it is now 2x faster

perf, performance, server configuration, etc. evolve quicker than expected, so I created a Git project to keep a copy of JSON files:

https://github.com/haypo/performance_results

I already lost data of my first miletone (november-december 2016), but you have data from the second (december 2016-february 2017) and third (march 2016-today) milestones.

I'm now discussing with PyPy to see how performance could be used to measure PyPy performance.

Victor