bpo-47009: Streamline list.append for the common case

[sweeneyde]

https://bugs.python.org/issue47009

[sweeneyde]

Benchmarks are good:

frompyperfimportRunner, perf_counterdefbench_listcomp(loops, length):
src=list(map(float, range(length)))
t0=perf_counter()
foriinrange(loops):
[xforxinsrc]
returnperf_counter() -t0defbench_append(loops, length):
src=list(map(float, range(length)))
t0=perf_counter()
foriinrange(loops):
arr= []
forxinsrc:
arr.append(x)
returnperf_counter() -t0runner=Runner()
fornin [100, 1_000, 10_000, 100_000]:
runner.bench_time_func(f"listcomp {n}", bench_listcomp, n)
runner.bench_time_func(f"append {n}", bench_append, n)

Results from GCC on WSL with --enable-optimizations --with-lto

Faster (8):
- listcomp 10000: 118 us +- 2 us -> 92.6 us +- 1.5 us: 1.28x faster
- listcomp 100000: 1.16 ms +- 0.02 ms -> 916 us +- 26 us: 1.27x faster
- listcomp 1000: 12.3 us +- 0.2 us -> 9.89 us +- 0.41 us: 1.25x faster
- listcomp 100: 1.59 us +- 0.03 us -> 1.32 us +- 0.05 us: 1.21x faster
- append 100000: 1.69 ms +- 0.05 ms -> 1.45 ms +- 0.04 ms: 1.17x faster
- append 10000: 168 us +- 4 us -> 145 us +- 3 us: 1.16x faster
- append 1000: 17.4 us +- 0.3 us -> 15.2 us +- 0.6 us: 1.14x faster
- append 100: 2.03 us +- 0.06 us -> 1.81 us +- 0.08 us: 1.12x faster
Geometric mean: 1.20x faster

[markshannon]

I think this would be simpler, and just as fast, by renaming app1 to _PyList_AppendTakeRef (with appropriate refcount adjustments).
No need for the inline functions.

[markshannon]

No need for an inline function.
Let the LTO pass decide if it wants to inline it.

[markshannon]

Do we need the extra function?
Converting app1 to _PyList_AppendTakeRef would seem to be enough.

[sweeneyde]

I tried something like that and the results are on the bpo issue, but it seems there is a significant benefit to having the separate as-small-as-possible function that always gets inlined as opposed to a slightly longer version that we let the compiler figure out.

[markshannon]

Presumably the compiler isn't inlining the function because it isn't hot enough.
PRECALL_NO_KW_LIST_APPEND and LIST_APPEND are only 0.3% of all instructions executed, so maybe it is best not to inline.

Do you have benchmark numbers for the standard suite?

[sweeneyde]

https://gist.github.com/sweeneyde/6cbbe1c9d216d117370a809c704b6cfc

Geometric mean: 1.00x faster

[sweeneyde]

Also, IMO there is a relative lack of list comprehensions in the pyperformance suite.

[sweeneyde]

@markshannon Since pyperformance results were negligible and this has a significant speedup on operations that live in hot loops (albeit not in pyperformance), is it okay if I merge this?

[markshannon]

Sorry, this dropped off my radar.