Add a separate benchmark that measures the effect of
`_PyObject_LookupSpecial()` on scaling.
In the process of cleaning up the scaling benchmarks for inclusion, I
unintentionally changed the "cmodule_function" benchmark to pass an
`int` to `math.floor()` instead of a `float`, which causes it to use the
`_PyObject_LookupSpecial()` code path. `_PyObject_LookupSpecial()` has
its own scaling issues that we want to measure separately from calling a
function on a C module.
@register_benchmark
def cmodule_function():
- for i in range(1000 * WORK_SCALE):
- math.floor(i * i)
+ N = 1000 * WORK_SCALE
+ for i in range(N):
+ math.cos(i / N)
+
+@register_benchmark
+def object_lookup_special():
+ # round() uses `_PyObject_LookupSpecial()` internally.
+ N = 1000 * WORK_SCALE
+ for i in range(N):
+ round(i / N)
@register_benchmark
def mult_constant():
color = "\x1b[33m" # yellow
reset_color = "\x1b[0m"
- print(f"{color}{func.__name__:<18} {round(factor, 1):>4}x {direction}{reset_color}")
+ print(f"{color}{func.__name__:<25} {round(factor, 1):>4}x {direction}{reset_color}")
def determine_num_threads_and_affinity():
if sys.platform != "linux":