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+:mod:`timeit` --- Measure execution time of small code snippets
+===============================================================
+
+.. module:: timeit
+ :synopsis: Measure the execution time of small code snippets.
+
+
+.. versionadded:: 2.3
+
+.. index::
+ single: Benchmarking
+ single: Performance
+
+This module provides a simple way to time small bits of Python code. It has both
+command line as well as callable interfaces. 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.
+
+The module defines the following public class:
+
+
+.. class:: Timer([stmt='pass' [, setup='pass' [, timer=<timer function>]]])
+
+ 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). The statements may
+ contain 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.
+
+ .. versionchanged:: 2.6
+ The *stmt* and *setup* parameters can now 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.
+
+
+.. method:: Timer.print_exc([file=None])
+
+ Helper to print a traceback from the timed code.
+
+ Typical use::
+
+ t = Timer(...) # outside the try/except
+ try:
+ t.timeit(...) # or t.repeat(...)
+ except:
+ t.print_exc()
+
+ The advantage over the standard traceback is that source lines in the compiled
+ template will be displayed. The optional *file* argument directs where the
+ traceback is sent; it defaults to ``sys.stderr``.
+
+
+.. method:: Timer.repeat([repeat=3 [, number=1000000]])
+
+ Call :meth:`timeit` a few times.
+
+ This is a convenience function that calls the :meth:`timeit` repeatedly,
+ returning a list of results. The first argument specifies how many times to
+ call :meth:`timeit`. The second argument specifies the *number* argument for
+ :func:`timeit`.
+
+ .. note::
+
+ It's tempting to calculate mean and standard deviation from the result vector
+ and report these. However, this is not very useful. In a typical case, the
+ lowest value gives a lower bound for how fast your machine can run the given
+ code snippet; higher values in the result vector are typically not caused by
+ variability in Python's speed, but by other processes interfering with your
+ timing accuracy. So the :func:`min` of the result is probably the only number
+ you should be interested in. After that, you should look at the entire vector
+ and apply common sense rather than statistics.
+
+
+.. method:: Timer.timeit([number=1000000])
+
+ Time *number* executions of the main statement. This executes the setup
+ statement once, and then returns the time it takes to execute the main statement
+ a number of times, measured in seconds as a float. The argument is the number
+ of times through the loop, defaulting to one million. The main statement, the
+ setup statement and the timer function to be used are passed to the constructor.
+
+ .. note::
+
+ By default, :meth:`timeit` temporarily turns off garbage collection during the
+ timing. The advantage of this approach is that it makes independent timings
+ more comparable. This disadvantage is that GC may be an important component of
+ the performance of the function being measured. If so, GC can be re-enabled as
+ the first statement in the *setup* string. For example::
+
+ timeit.Timer('for i in range(10): oct(i)', 'gc.enable()').timeit()
+
+Starting with version 2.6, the module also defines two convenience functions:
+
+
+.. function:: repeat(stmt[, setup[, timer[, repeat=3 [, number=1000000]]]])
+
+ Create a :class:`Timer` instance with the given statement, setup code and timer
+ function and run its :meth:`repeat` method with the given repeat count and
+ *number* executions.
+
+ .. versionadded:: 2.6
+
+
+.. function:: timeit(stmt[, setup[, timer[, number=1000000]]])
+
+ Create a :class:`Timer` instance with the given statement, setup code and timer
+ function and run its :meth:`timeit` method with *number* executions.
+
+ .. versionadded:: 2.6
+
+
+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:
+
+-n N/:option:`--number=N`
+ how many times to execute 'statement'
+
+-r N/:option:`--repeat=N`
+ how many times to repeat the timer (default 3)
+
+-s S/:option:`--setup=S`
+ statement to be executed once initially (default ``'pass'``)
+
+-t/:option:`--time`
+ use :func:`time.time` (default on all platforms but Windows)
+
+-c/:option:`--clock`
+ use :func:`time.clock` (default on Windows)
+
+-v/:option:`--verbose`
+ print raw timing results; repeat for more digits precision
+
+-h/:option:`--help`
+ print a short usage message and exit
+
+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.
+
+The default timer function is platform dependent. On Windows,
+:func:`time.clock` has microsecond granularity but :func:`time.time`'s
+granularity is 1/60th of a second; on Unix, :func:`time.clock` has 1/100th of a
+second granularity and :func:`time.time` is much more precise. On either
+platform, the default timer functions measure wall clock time, not the CPU time.
+This means that other processes running on the same computer may interfere with
+the timing. 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. On
+Unix, you can use :func:`time.clock` to measure CPU time.
+
+.. note::
+
+ 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.
+
+The baseline overhead differs between Python versions! Also, to fairly compare
+older Python versions to Python 2.3, you may want to use Python's :option:`-O`
+option for the older versions to avoid timing ``SET_LINENO`` instructions.
+
+
+Examples
+--------
+
+Here are two example sessions (one using the command line, one using the module
+interface) that compare the cost of using :func:`hasattr` vs.
+:keyword:`try`/:keyword:`except` to test for missing and present object
+attributes. ::
+
+ % timeit.py 'try:' ' str.__bool__' 'except AttributeError:' ' pass'
+ 100000 loops, best of 3: 15.7 usec per loop
+ % timeit.py 'if hasattr(str, "__bool__"): pass'
+ 100000 loops, best of 3: 4.26 usec per loop
+ % timeit.py 'try:' ' int.__bool__' 'except AttributeError:' ' pass'
+ 1000000 loops, best of 3: 1.43 usec per loop
+ % timeit.py 'if hasattr(int, "__bool__"): pass'
+ 100000 loops, best of 3: 2.23 usec per loop
+
+::
+
+ >>> import timeit
+ >>> s = """\
+ ... try:
+ ... str.__bool__
+ ... except AttributeError:
+ ... pass
+ ... """
+ >>> t = timeit.Timer(stmt=s)
+ >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)
+ 17.09 usec/pass
+ >>> s = """\
+ ... if hasattr(str, '__bool__'): pass
+ ... """
+ >>> t = timeit.Timer(stmt=s)
+ >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)
+ 4.85 usec/pass
+ >>> s = """\
+ ... try:
+ ... int.__bool__
+ ... except AttributeError:
+ ... pass
+ ... """
+ >>> t = timeit.Timer(stmt=s)
+ >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)
+ 1.97 usec/pass
+ >>> s = """\
+ ... if hasattr(int, '__bool__'): pass
+ ... """
+ >>> t = timeit.Timer(stmt=s)
+ >>> print "%.2f usec/pass" % (1000000 * t.timeit(number=100000)/100000)
+ 3.15 usec/pass
+
+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 = []
+ for i in range(100):
+ L.append(i)
+
+ if __name__=='__main__':
+ from timeit import Timer
+ t = Timer("test()", "from __main__ import test")
+ print t.timeit()
+