> As noted above, it not reasonable for a C-API that isn't used internally because there is no reasonable way to measure the effect without writing a C extension.

Come on, there is a lot of C functions in Python using the C PyList_xxx() API. It's easy to write a benchmark on it in pure Python. Example.


Without the patch (best of 10 runs):

$ for i in $(seq 1 10); do ./python -m timeit -s 's="a " * 10**5' 's.split()'; done
1000 loops, best of 3: 1.40 msec per loop

With the patch (best of 10 runs):

$ for i in $(seq 1 10); do ./python -m timeit -s 's="a " * 10**5' 's.split()'; done
1000 loops, best of 3: 1.49 msec per loop

It looks like list_check_fastpath2.diff makes PyList_Append() *slower* (6%) in practice. I expected it to be *faster*.


Please try to reproduce my microbenchmark, timeit is not really reliable, and I hate microbenchmarks, it's easy to make mistakes :-/

Note: It looks like s.split() creates a list of 'a' strings where all 'a' strings are the same singleton. So I don't think that creating substrings has an important cost.


> If you're going to be in the optimization business, I really wish you would read some of the basics in the field so that each and every technique doesn't have to be re-proved to you each time it used.

It's easy to convince me: show me a benchmark where your patch makes the code faster :-) I don't think that there is a strict rule for a miniumum speedup in CPython. I'm open for discussion :-)