Skip to main content

A timer context manager measuring the clock wall time of the code block it contains.

Project description

contexttimer provides you with a couple of utilities to quickly measure the execution time of a code block or a function.

Timer as a context manager

contexttimer.Timer is a context manager measuring the execution time of the code block it contains. The elapsed time is accessible through the elapsed property.

>>> with Timer() as t:
...     # some code here
>>> print t.elapsed
# a value in seconds

The contexttimer.Timer context manager

contexttimer.Timer is a context manager with 2 parameters and a public property:

  • default_timer: a platform specific timer function (time.time for Unix platforms and time.clock for Windows platforms). You can instanciate a Timer object with your own timer, by passing it to the constructor.

  • factor: a multiplying factor applied to the elapsed property. For example, a factor or 1000 will lead to elapsed being expressed in milliseconds instead of seconds. Default value of 1.

  • elapsed: (read only property) the wall clock timing of the execution of the code block, in seconds. By default, expressed in seconds.


>>> from contexttimer import Timer
>>> with Timer(factor=1000) as t:
...     for i in xrange(10000000):
...         pass
>>> print(t.elapsed)
73.6618041992 # in miliseconds

Note that elapsed is calculated on demand, so it is possible to time sub-parts of your code block:

>>> with Timer(factor=1000) as t:
...     # do some things
...     print t.elapsed
...     # do other tings
...     print t.elapsed
10.122  # in ms

The contexttimer.timer function decorator

You can use the @timer function decorator to measure the time execution of an entire function. When the function returns its value, its execution time will be printed to the stdout (default), or to the argument logger.


>>> @timer
... def sleep_for_2s():
...     time.sleep(2)
>>> sleep_for_2s()
function sleep_for_2s execution time: 2.002
>>> logging.basicConfig()
>>> @timer(logger=logging.getLogger())
... def sleep_for_2s():
...     time.sleep(2)
>>> sleep_for_2s()
DEBUG:root:function blah execution time: 2.002

As it makes use of the Timer context manager inside, all arguments passed to the @timer decorator will be used a Timer init arguments.


>>> @timer(factor=1000)
... def sleepawhile(n):
...     time.sleep(n)
>>> sleepawhile(2)
function sleepawhile execution time: 2000.089

The contexttimer.timeout.timeout decorator

You can use the @timeout function decorator to stop a function/method call and call a handler if the call exceeds a fixed amount of time.


>>> def timeout_handler(limit, f, *args, **kwargs):
...     print "{func} call timed out after {lim}s.".format(
...         func=f.__name__, lim=limit)
>>> @timeout(limit=5, handler=timeout_handler)
... def work(foo, bar, baz="spam")
...     time.sleep(10)
>>> work("foo", "bar", "baz")
# time passes...
work call timed out after 5s.


Thanks to halloi, wolanko and Jon Blackburn for their helpful insights and contributions.


contexttimer is released under the GPLv3 license.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

contexttimer-0.3.3.tar.gz (4.9 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page