gh-136681: optimize builtin calls if kwargs allowed #137202
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This is a first part, that should address python#136681. With this patch there should be no overhead for function calls if it's signature allows keyword arguments. Below are micro-benchmarks for math.fmin(), when only positional arguments are allowed (as in the main) vs positional-or-keyword. The missing part is specialization for 1-arg functions, like cmath.sin(): python#136681 (comment) In the main: | Benchmark | posonly-patch | posorkw-patch | |----------------------------|:-------------:|:---------------------:| | fmin(1.0, 2.0) | 169 ns | 170 ns: 1.01x slower | | fmin(1.0, 2.0) x 2 times | 913 ns | 890 ns: 1.03x faster | | fmin(1.0, 2.0) x 100 times | 14.7 us | 14.8 us: 1.01x slower | | Geometric mean | (ref) | 1.00x faster | Benchmark hidden because not significant (1): fmin(1.0, 2.0) x 10 times With the patch: | Benchmark | posonly-ref | posorkw-ref | |----------------------------|:-----------:|:---------------------:| | fmin(1.0, 2.0) | 177 ns | 199 ns: 1.12x slower | | fmin(1.0, 2.0) x 2 times | 937 ns | 980 ns: 1.05x slower | | fmin(1.0, 2.0) x 10 times | 2.08 us | 2.25 us: 1.08x slower | | fmin(1.0, 2.0) x 100 times | 14.8 us | 16.5 us: 1.12x slower | | Geometric mean | (ref) | 1.09x slower | Benchmark code: ```py import pyperf from math import fmin def f(n): for _ in range(n): fmin(1.0, 2.0) runner = pyperf.Runner() runner.bench_func('fmin(1.0, 2.0)', fmin, 1.0, 2.0) for n in [2, 10, 100]: s = f'fmin(1.0, 2.0) x {n:3} times' runner.bench_func(s, f, n) ```
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This is a first part, that should address #136681. With this patch there should be no overhead for function calls if it's signature allows keyword arguments.
Below are micro-benchmarks for math.fmin(), when only positional arguments are allowed (as in the main) vs positional-or-keyword.
The missing part is specialization for 1-arg functions, like cmath.sin(): #136681 (comment)
In the main:
Benchmark hidden because not significant (1): fmin(1.0, 2.0) x 10 times
With the patch:
Benchmark code: