Metrics

The Scheduler and Job classes provide access to various metrics that can be of interest for the using program.

Starting with a Scheduler and two Jobs:

>>> import datetime as dt
>>> import time

>>> from scheduler import Scheduler

>>> def foo():
...     print("foo")
...

>>> schedule = Scheduler()
>>> job = schedule.once(dt.timedelta(minutes=10), foo)
>>> print(schedule)  
max_exec=inf, tzinfo=None, priority_function=linear_priority_function, #jobs=1

type     function / alias due at                 due in      attempts weight
-------- ---------------- ------------------- --------- ------------- ------
ONCE     foo()            2021-06-21 04:53:34   0:09:59           0/1      1

Scheduler provides access to the set of Jobs stored with the jobs We can access the Jobs of the scheduler via the jobs property.

>>> schedule.jobs == {job}
True

For the Job with the following string representation

>>> print(job)  
ONCE, foo(), at=2020-07-16 23:56:12, tz=None, in=0:09:59, #0/1, w=1.000

The scheduled datetime and timedelta informations can directly be accessed and might look like similar to what is listed below:

>>> print(f"{job.datetime = !s}\n{job.timedelta() = !s}")  
job.datetime = 2021-06-21 04:53:34.879346
job.timedelta() = 0:09:59.999948

These metrics can change during the Jobs lifetime. We can exemplify this for the attempts attribute:

>>> job = schedule.cyclic(dt.timedelta(seconds=0.1), foo, max_attempts=2)
>>> print(job)  
CYCLIC, foo(), at=2021-06-21 04:53:34, tz=None, in=0:00:00, #0/2, w=1.000

>>> print(job.attempts, job.max_attempts)
0 2

>>> time.sleep(0.1)
>>> exec_count = schedule.exec_jobs()
foo

>>> print(job.attempts, job.max_attempts)
1 2

>>> time.sleep(0.1)
>>> exec_count = schedule.exec_jobs()
foo

>>> print(job.attempts, job.max_attempts)
2 2