abs-sleep: Absolutely Timed Sleeps in Python
The abs-sleep
package for Python 3 provides a thin wrapper around the ctypes
module for calling clock_nanosleep
on Linux with the TIMER_ABSTIME
flag set. This allows for precisely timed sleeps that are not affected by timer drift (e.g., due to preemptions).
The two primary provided functions are:
abs_sleep(wakeup_time, clock=time.CLOCK_MONOTONIC)
Sleep until the absolute time wakeup_time
(specified in seconds) is reached w.r.t. the specified clock (time.CLOCK_MONOTONIC
by default).abs_nanosleep(wakeup_time_ns, clock=time.CLOCK_MONOTONIC)
Sleep until the absolute time wakeup_time
(specified in integral nanoseconds) is reached w.r.t. the specified clock (time.CLOCK_MONOTONIC
by default).
They are intended to be used together with time.monotonic()
and time.monotonic_ns()
, respectively.
On POSIX platforms other than Linux, the library resorts to an inaccurate approximation.
Tested on Linux and macOS.
Example: Absolutely Timed Sleeps
from abs_sleep import abs_sleep, abs_nanosleep
import time
t = time.monotonic()
print('One sec...', end='', flush=True)
abs_sleep(t + 1)
print('done.')
t = time.monotonic_ns()
print('Five secs...', end='', flush=True)
abs_nanosleep(t + 5000000000)
print('done.')
Periodic Activations Iterators
Additionally, there are two convenience iterators that help with implementing periodic activations (w.r.t. time.CLOCK_MONOTONIC
):
periodic(period_secs)
periodic_ns(period_nsecs)
These two iterators take a number of optional keyword arguments.
periodic argument | periodic_ns argument | effect | default |
---|
offset_secs | offset_nsecs | offset of the first activation | 0 |
start_time_secs | start_time_nsecs | time of the first activation | current time + period |
align_secs | align_nsecs | round up the start time to a multiple of the given alignment granularity | no alignment |
release_jitter | release_jitter | callback function to determine release jitter (see below) | no jitter |
sporadic_delay | sporadic_delay | callback function to determine sporadic inter-arrival delay (see below) | no delay |
The release_jitter
argument accepts a function iterator_state -> release jitter value
that, given the current iterator state object, produces a release jitter value for the next release (e.g., lambda _it: 123
). The time scale must match that of the iterator (i.e., seconds in case of periodic
and integral nanoseconds in case of periodic_ns
).
The sporadic_delay
argument accepts a function iterator_state -> sporadic delay value
that, given the current iterator state object, produces a sporadic inter-arrival delay value for the next release (e.g., lambda _it: 123
). The time scale must match that of the iterator (i.e., seconds in case of periodic
and integral nanoseconds in case of periodic_ns
).
The difference between release jitter and sporadic inter-arrival delays is that release jitter affects only the next activation, whereas sporadic inter-arrival delay is cumulative (i.e., a delay > 0 implicitly delays all future activations, too).
The first three arguments (offset, start time, alignment) are useful for implementing periodic real-time tasks. The latter two arguments (release jitter and sporadic delay) are useful for simulating periodic and sporadic real-time task behavior.
Example: Periodic Activations
from abs_sleep import periodic, periodic_ns
import time
for i, t in enumerate(periodic(0.2)):
print(t)
if i >= 4:
break
for i, t in enumerate(periodic(0.5, align_secs=1)):
print(t)
if i >= 4:
break
for i, t in enumerate(periodic_ns(500000000, align_nsecs=1000000000)):
print(t)
if i >= 4:
break
for i, t in enumerate(periodic(0.2, align_secs=2, release_jitter=lambda _it: 0.123)):
print(t, time.monotonic())
if i >= 4:
break
for i, t in enumerate(periodic_ns(100000000, align_nsecs=2000000000, sporadic_delay=lambda it: 1000)):
print(t, time.monotonic_ns())
if i >= 4:
break