Current File : //lib64/python3.8/__pycache__/timeit.cpython-38.pyc
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eedfdd�Zddd�dd�Zedkr�e�e� � dS )a9 Tool for measuring execution time of small code snippets.
This module 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.
Library usage: see the Timer class.
Command line usage:
python timeit.py [-n N] [-r N] [-s S] [-p] [-h] [--] [statement]
Options:
-n/--number N: how many times to execute 'statement' (default: see below)
-r/--repeat N: how many times to repeat the timer (default 5)
-s/--setup S: statement to be executed once initially (default 'pass').
Execution time of this setup statement is NOT timed.
-p/--process: use time.process_time() (default is time.perf_counter())
-v/--verbose: print raw timing results; repeat for more digits precision
-u/--unit: set the output time unit (nsec, usec, msec, or sec)
-h/--help: print this usage message and exit
--: separate options from statement, use when statement starts with -
statement: statement to be timed (default 'pass')
A multi-line statement may be given by specifying each line as a
separate argument; indented lines are possible by enclosing an
argument in quotes and using leading spaces. Multiple -s options are
treated similarly.
If -n is not given, a suitable number of loops is calculated by trying
increasing numbers from the sequence 1, 2, 5, 10, 20, 50, ... until the
total time is at least 0.2 seconds.
Note: there is a certain baseline overhead associated with executing a
pass statement. It differs between versions. 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.
Classes:
Timer
Functions:
timeit(string, string) -> float
repeat(string, string) -> list
default_timer() -> float
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def inner(_it, _timer{init}):
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for _i in _it:
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return _t1 - _t0
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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
module doc string). If 'globals' is specified, the code will be
executed within that namespace (as opposed to inside timeit's
namespace).
To measure the execution time of the first statement, use the
timeit() method. The repeat() method is a convenience to call
timeit() multiple times and return a list of results.
The statements may contain newlines, as long as they don't contain
multi-line string literals.
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repeatedly, returning a list of results. The first argument
specifies how many times to call timeit(), defaulting to 5;
the second argument specifies the timer argument, defaulting
to one million.
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 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.
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The optional 'args' argument specifies the command line to be parsed,
defaulting to sys.argv[1:].
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may be None to indicate success.
When an exception happens during timing, a traceback is printed to
stderr and the return value is 1. Exceptions at other times
(including the template compilation) are not caught.
'_wrap_timer' is an internal interface used for unit testing. If it
is not None, it must be a callable that accepts a timer function
and returns another timer function (used for unit testing).
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