clock_test.py

import time


titles = ("Clock", "Implementation", "Monotonic", "Adjustable", "Resolution")
print("".join(str(x).ljust(30) for x in titles))
print("".join(("-" * len(x)).ljust(30) for x in titles))
for clock in ("time",
              "clock",
              "monotonic",
              "perf_counter",
              "process_time"):
    info = time.get_clock_info(clock)
    infos = [clock, info.implementation, info.monotonic, info.adjustable, info.resolution]
    print("".join(str(x).ljust(30) for x in infos))

clock_test_empirical.py

import math
import time

import expyriment as xpy


LOOPS = 10 ** 6

clocks = {"clock": time.clock,
          "time": time.time,
          "time_ns": time.time_ns,
          "monotonic": time.monotonic,
          "monotonic_ns": time.monotonic_ns,
          "perf_counter": time.perf_counter,
          "perf_counter_ns": time.perf_counter_ns,
          "process_time": time.process_time,
          "process_time_ns": time.process_time_ns,
          "expyriment": xpy.misc.Clock().monotonic_time}

for clock in clocks:
    min_dt = [abs(clocks[clock]() - clocks[clock]())
              for _ in range(LOOPS)]
    min_dt = min(filter(bool, min_dt))

    if clock.endswith("ns"):
        print("min " + clock + " delta: %s ns" % min_dt)
    else:
        print("min " + clock + " delta: %s ns" % math.ceil(min_dt * 1e9))

Why is expyriment so slow (at least under Linux)?

min clock delta: 1000 ns
min time delta: 239 ns
min time_ns delta: 60 ns
min monotonic delta: 50 ns
min monotonic_ns delta: 69 ns
min perf_counter delta: 59 ns
min perf_counter_ns delta: 70 ns
min process_time delta: 219 ns
min process_time_ns delta: 229 ns
min expyriment delta: 1780 ns