Conveniently measures the time of your loops, contexts and functions.
Simply:
pip install horology
Works with python versions 3.6, 3.7, 3.8 and 3.9. Tested on Linux, Windows and MacOS.
The following 3 tools will let you measure practically any part of your Python code.
from horology import Timed
animals = ['cat', 'dog', 'crocodile']
for x in Timed(animals):
feed(x)Result:
iteration 1: 12.0 s
iteration 2: 8.00 s
iteration 3: 100 s
total 3 iterations in 120 s
min/median/max: 8.00/12.0/100 s
average (std): 40.0 (52.0) s
You can specify where (if at all) you want each iteration and summary to be printed, eg.:
for x in Timed(animals, unit='ms',
iteration_print_fn=logger.debug,
summary_print_fn=logger.info):
feed(x)from horology import timed
@timed
def foo():
...Result:
>>> foo()
foo: 7.12 ms
Personalize time unit and name
@timed(unit='s', name='Processing took ')
def bar():
...Result:
>>> bar()
Processing took 0.185 s
Just wrap your code using a with statement
from horology import Timing
with Timing(name='Important calculations: '):
...Result:
Important calculations: 12.4 s
You can suppress default printing and directly use measured time (also within context)
with Timing(print_fn=None) as t:
...
make_use_of(t.interval)Time units are by default automatically adjusted, for example you will see
foo: 7.12 ms rather than foo: 0.007 s. If you don't like it, you can
override this by setting the unit argument with one of these names:
['ns', 'us', 'ms', 's', 'min', 'h', 'd'].
Contributions are welcomed, see contribution guide.
Horology internally measures time with perf_counter which provides the highest available resolution,
see docs.