cpython / Doc / library / timeit.rst

:mod:`timeit` --- Measure execution time of small code snippets

Source code: :source:`Lib/`

This module provides a simple way to time small bits of Python code. It has both a :ref:`command-line-interface` as well as a :ref:`callable <python-interface>` one. It avoids a number of common traps for measuring execution times. See also Tim Peters' introduction to the "Algorithms" chapter in the Python Cookbook, published by O'Reilly.

Basic Examples

The following example shows how the :ref:`command-line-interface` can be used to compare three different expressions:

$ python -m timeit '"-".join(str(n) for n in range(100))'
10000 loops, best of 3: 40.3 usec per loop
$ python -m timeit '"-".join([str(n) for n in range(100)])'
10000 loops, best of 3: 33.4 usec per loop
$ python -m timeit '"-".join(map(str, range(100)))'
10000 loops, best of 3: 25.2 usec per loop

This can be achieved from the :ref:`python-interface` with:

>>> import timeit
>>> timeit.timeit('"-".join(str(n) for n in range(100))', number=10000)
>>> timeit.timeit('"-".join([str(n) for n in range(100)])', number=10000)
>>> timeit.timeit('"-".join(map(str, range(100)))', number=10000)

Note however that :mod:`timeit` will automatically determine the number of repetitions only when the command-line interface is used. In the :ref:`timeit-examples` section you can find more advanced examples.

Python Interface

The module defines three convenience functions and a public class:

Class for timing execution speed of small code snippets.

The constructor takes a statement to be timed, an additional statement used for setup, and a timer function. Both statements default to 'pass'; the timer function is platform-dependent (see the module doc string). stmt and setup may also contain multiple statements separated by ; or newlines, as long as they don't contain multi-line string literals.

To measure the execution time of the first statement, use the :meth:`.timeit` method. The :meth:`.repeat` method is a convenience to call :meth:`.timeit` multiple times and return a list of results.

The stmt and setup parameters can also take objects that are callable without arguments. This will embed calls to them in a timer function that will then be executed by :meth:`.timeit`. Note that the timing overhead is a little larger in this case because of the extra function calls.

Command-Line Interface

When called as a program from the command line, the following form is used:

python -m timeit [-n N] [-r N] [-s S] [-t] [-c] [-h] [statement ...]

Where the following options are understood:

A multi-line statement may be given by specifying each line as a separate statement argument; indented lines are possible by enclosing an argument in quotes and using leading spaces. Multiple :option:`-s` options are treated similarly.

If :option:`-n` is not given, a suitable number of loops is calculated by trying successive powers of 10 until the total time is at least 0.2 seconds.

:func:`default_timer` measurements can be affected by other programs running on the same machine, so the best thing to do when accurate timing is necessary is to repeat the timing a few times and use the best time. The :option:`-r` option is good for this; the default of 3 repetitions is probably enough in most cases. You can use :func:`time.process_time` to measure CPU time.


There is a certain baseline overhead associated with executing a pass statement. The code here doesn't try to hide it, but you should be aware of it. The baseline overhead can be measured by invoking the program without arguments, and it might differ between Python versions.


It is possible to provide a setup statement that is executed only once at the beginning:

$ python -m timeit -s 'text = "sample string"; char = "g"'  'char in text'
10000000 loops, best of 3: 0.0877 usec per loop
$ python -m timeit -s 'text = "sample string"; char = "g"'  'text.find(char)'
1000000 loops, best of 3: 0.342 usec per loop
>>> import timeit
>>> timeit.timeit('char in text', setup='text = "sample string"; char = "g"')
>>> timeit.timeit('text.find(char)', setup='text = "sample string"; char = "g"')

The same can be done using the :class:`Timer` class and its methods:

>>> import timeit
>>> t = timeit.Timer('char in text', setup='text = "sample string"; char = "g"')
>>> t.timeit()
>>> t.repeat()
[0.40193588800002544, 0.3960157959998014, 0.39594301399984033]

The following examples show how to time expressions that contain multiple lines. Here we compare the cost of using :func:`hasattr` vs. :keyword:`try`/:keyword:`except` to test for missing and present object attributes:

$ python -m timeit 'try:' '  str.__bool__' 'except AttributeError:' '  pass'
100000 loops, best of 3: 15.7 usec per loop
$ python -m timeit 'if hasattr(str, "__bool__"): pass'
100000 loops, best of 3: 4.26 usec per loop

$ python -m timeit 'try:' '  int.__bool__' 'except AttributeError:' '  pass'
1000000 loops, best of 3: 1.43 usec per loop
$ python -m timeit 'if hasattr(int, "__bool__"): pass'
100000 loops, best of 3: 2.23 usec per loop
>>> import timeit
>>> # attribute is missing
>>> s = """\
... try:
...     str.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
>>> s = "if hasattr(str, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)
>>> # attribute is present
>>> s = """\
... try:
...     int.__bool__
... except AttributeError:
...     pass
... """
>>> timeit.timeit(stmt=s, number=100000)
>>> s = "if hasattr(int, '__bool__'): pass"
>>> timeit.timeit(stmt=s, number=100000)

To give the :mod:`timeit` module access to functions you define, you can pass a setup parameter which contains an import statement:

def test():
    """Stupid test function"""
    L = [i for i in range(100)]

if __name__ == '__main__':
    import timeit
    print(timeit.timeit("test()", setup="from __main__ import test"))
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