.. role:: python(code)
:language: python
======
timing
======
Simplify logging of timings of selected parts of an application.
.. image:: https://img.shields.io/pypi/v/timing.svg
:target: https://pypi.org/project/timing
:alt: package version from PyPI
.. image:: https://github.com/mbdevpl/timing/actions/workflows/python.yml/badge.svg?branch=main
:target: https://github.com/mbdevpl/timing/actions
:alt: build status from GitHub
.. image:: https://codecov.io/gh/mbdevpl/timing/branch/main/graph/badge.svg
:target: https://codecov.io/gh/mbdevpl/timing
:alt: test coverage from Codecov
.. image:: https://api.codacy.com/project/badge/Grade/5dba9ea9f47e4e86aeed6eddfce42640
:target: https://app.codacy.com/gh/mbdevpl/timing
:alt: grade from Codacy
.. image:: https://img.shields.io/github/license/mbdevpl/timing.svg
:target: https://github.com/mbdevpl/timing/blob/v0.5.1/NOTICE
:alt: license
.. contents::
:backlinks: none
How to use
==========
Recommended initialization is as follows.
.. code:: python
import timing
_TIME = timing.get_timing_group(__name__) # type: timing.TimingGroup
This follows the conventions of :python:`logging` module.
.. code:: python
import logging
_LOG = logging.getLogger(__name__)
Any name can be used instead of :python:`__name__`.
However, if names of format :python:`module.sub.sub_sub` are used, this will create a timing
hierarchy where each timing data is stored in its proper location and can be queried easier.
The resulting :python:`_TIME` object is used to create individual timers,
and will handle storing results in cache, which later can be used to obtain timing statistics.
You can obtain the timer object directly via :python:`start(name)` method.
You'll need to manually call :python:`stop()` in this case.
.. code:: python
timer = _TIME.start('spam') # type: timing.Timing
spam()
more_spam()
timer.stop()
You can also obtain the timer object indirectly via :python:`measure(name)` context manager.
The context manager will take care of calling :python:`stop()` at the end.
.. code:: python
with _TIME.measure('ham') as timer: # type: timing.Timing
ham()
more_ham()
And if you want to time many repetitions of the same action (e.g. for statistical significance)
you can use :python:`measure_many(name[, samples][, threshold])` generator.
You can decide how many times you want to measure via :python:`samples` parameter
and how many seconds at most you want to spend on measurements via :python:`threshold` parameter
.. code:: python
for timer in _TIME.measure_many('eggs', samples=1000): # type: timing.Timing
eggs()
more_eggs()
for timer in _TIME.measure_many('bacon', threshold=0.5): # type: timing.Timing
bacon()
more_bacon()
for timer in _TIME.measure_many('tomatoes', samples=500, threshold=0.5): # type: timing.Timing
tomatoes()
more_tomatoes()
Also, you can use :python:`measure` and :python:`measure(name)` as decorator.
In this scenario you cannot access the timings directly, but the results will be stored
in the timing group object, as well as in the global cache unless you configure the timing
to not use the cache.
.. code:: python
import timing
_TIME = timing.get_timing_group(__name__)
@_TIME.measure
def recipe():
ham()
eggs()
bacon()
@_TIME.measure('the_best_recipe')
def bad_recipe():
spam()
spam()
spam()
Then, after calling each function the results can be accessed through :python:`summary` property.
.. code:: python
recipe()
bad_recipe()
bad_recipe()
assert _TIME.summary['recipe']['samples'] == 1
assert _TIME.summary['the_best_recipe']['samples'] == 2
The :python:`summary` property is dynamically computed on first access. Subsequent accesses
will not recompute the values, so if you need to access the updated results,
call the :python:`summarize()` method.
.. code:: python
recipe()
assert _TIME.summary['recipe']['samples'] == 1
bad_recipe()
bad_recipe()
assert _TIME.summary['the_best_recipe']['samples'] == 2 # will fail
_TIME.summarize()
assert _TIME.summary['the_best_recipe']['samples'] == 2 # ok
Further API and documentation are in development.
See these examples in action in `<examples.ipynb>`_ notebook.
Requirements
============
Python version 3.11 or later.
Python libraries as specified in `requirements.txt <https://github.com/mbdevpl/timing/blob/v0.5.1/requirements.txt>`_.
Building and running tests additionally requires packages listed in `<test_requirements.txt>`_.
Tested on Linux, macOS and Windows.
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