3 """Tool for measuring execution time of small code snippets.
5 This module avoids a number of common traps for measuring execution
6 times. See also Tim Peters' introduction to the Algorithms chapter in
7 the Python Cookbook, published by O'Reilly.
9 Library usage: see the Timer class.
12 python timeit.py [-n N] [-r N] [-s S] [-t] [-c] [-h] [statement]
15 -n/--number N: how many times to execute 'statement' (default: see below)
16 -r/--repeat N: how many times to repeat the timer (default 3)
17 -s/--setup S: statement to be executed once initially (default 'pass')
18 -t/--time: use time.time() (default on Unix)
19 -c/--clock: use time.clock() (default on Windows)
20 -v/--verbose: print raw timing results; repeat for more digits precision
21 -h/--help: print this usage message and exit
22 statement: statement to be timed (default 'pass')
24 A multi-line statement may be given by specifying each line as a
25 separate argument; indented lines are possible by enclosing an
26 argument in quotes and using leading spaces. Multiple -s options are
29 If -n is not given, a suitable number of loops is calculated by trying
30 successive powers of 10 until the total time is at least 0.2 seconds.
32 The difference in default timer function is because on Windows,
33 clock() has microsecond granularity but time()'s granularity is 1/60th
34 of a second; on Unix, clock() has 1/100th of a second granularity and
35 time() is much more precise. On either platform, the default timer
36 functions measure wall clock time, not the CPU time. This means that
37 other processes running on the same computer may interfere with the
38 timing. The best thing to do when accurate timing is necessary is to
39 repeat the timing a few times and use the best time. The -r option is
40 good for this; the default of 3 repetitions is probably enough in most
41 cases. On Unix, you can use clock() to measure CPU time.
43 Note: there is a certain baseline overhead associated with executing a
44 pass statement. The code here doesn't try to hide it, but you should
45 be aware of it. The baseline overhead can be measured by invoking the
46 program without arguments.
48 The baseline overhead differs between Python versions! Also, to
49 fairly compare older Python versions to Python 2.3, you may want to
50 use python -O for the older versions to avoid timing SET_LINENO
60 # Must be an older Python version (see timeit() below)
65 dummy_src_name
= "<timeit-src>"
66 default_number
= 1000000
69 if sys
.platform
== "win32":
70 # On Windows, the best timer is time.clock()
71 default_timer
= time
.clock
73 # On most other platforms the best timer is time.time()
74 default_timer
= time
.time
76 # Don't change the indentation of the template; the reindent() calls
77 # in Timer.__init__() depend on setup being indented 4 spaces and stmt
78 # being indented 8 spaces.
80 def inner(_it, _timer):
89 def reindent(src
, indent
):
90 """Helper to reindent a multi-line statement."""
91 return src
.replace("\n", "\n" + " "*indent
)
94 """Class for timing execution speed of small code snippets.
96 The constructor takes a statement to be timed, an additional
97 statement used for setup, and a timer function. Both statements
98 default to 'pass'; the timer function is platform-dependent (see
101 To measure the execution time of the first statement, use the
102 timeit() method. The repeat() method is a convenience to call
103 timeit() multiple times and return a list of results.
105 The statements may contain newlines, as long as they don't contain
106 multi-line string literals.
109 def __init__(self
, stmt
="pass", setup
="pass", timer
=default_timer
):
110 """Constructor. See class doc string."""
112 stmt
= reindent(stmt
, 8)
113 setup
= reindent(setup
, 4)
114 src
= template
% {'stmt': stmt
, 'setup': setup
}
115 self
.src
= src
# Save for traceback display
116 code
= compile(src
, dummy_src_name
, "exec")
118 exec code
in globals(), ns
119 self
.inner
= ns
["inner"]
121 def print_exc(self
, file=None):
122 """Helper to print a traceback from the timed code.
126 t = Timer(...) # outside the try/except
128 t.timeit(...) # or t.repeat(...)
132 The advantage over the standard traceback is that source lines
133 in the compiled template will be displayed.
135 The optional file argument directs where the traceback is
136 sent; it defaults to sys.stderr.
138 import linecache
, traceback
139 linecache
.cache
[dummy_src_name
] = (len(self
.src
),
141 self
.src
.split("\n"),
143 traceback
.print_exc(file=file)
145 def timeit(self
, number
=default_number
):
146 """Time 'number' executions of the main statement.
148 To be precise, this executes the setup statement once, and
149 then returns the time it takes to execute the main statement
150 a number of times, as a float measured in seconds. The
151 argument is the number of times through the loop, defaulting
152 to one million. The main statement, the setup statement and
153 the timer function to be used are passed to the constructor.
156 it
= itertools
.repeat(None, number
)
159 gcold
= gc
.isenabled()
161 timing
= self
.inner(it
, self
.timer
)
166 def repeat(self
, repeat
=default_repeat
, number
=default_number
):
167 """Call timeit() a few times.
169 This is a convenience function that calls the timeit()
170 repeatedly, returning a list of results. The first argument
171 specifies how many times to call timeit(), defaulting to 3;
172 the second argument specifies the timer argument, defaulting
175 Note: it's tempting to calculate mean and standard deviation
176 from the result vector and report these. However, this is not
177 very useful. In a typical case, the lowest value gives a
178 lower bound for how fast your machine can run the given code
179 snippet; higher values in the result vector are typically not
180 caused by variability in Python's speed, but by other
181 processes interfering with your timing accuracy. So the min()
182 of the result is probably the only number you should be
183 interested in. After that, you should look at the entire
184 vector and apply common sense rather than statistics.
187 for i
in range(repeat
):
188 t
= self
.timeit(number
)
193 """Main program, used when run as a script.
195 The optional argument specifies the command line to be parsed,
196 defaulting to sys.argv[1:].
198 The return value is an exit code to be passed to sys.exit(); it
199 may be None to indicate success.
201 When an exception happens during timing, a traceback is printed to
202 stderr and the return value is 1. Exceptions at other times
203 (including the template compilation) are not caught.
209 opts
, args
= getopt
.getopt(args
, "n:s:r:tcvh",
210 ["number=", "setup=", "repeat=",
211 "time", "clock", "verbose", "help"])
212 except getopt
.error
, err
:
214 print "use -h/--help for command line help"
216 timer
= default_timer
217 stmt
= "\n".join(args
) or "pass"
218 number
= 0 # auto-determine
220 repeat
= default_repeat
224 if o
in ("-n", "--number"):
226 if o
in ("-s", "--setup"):
228 if o
in ("-r", "--repeat"):
232 if o
in ("-t", "--time"):
234 if o
in ("-c", "--clock"):
236 if o
in ("-v", "--verbose"):
240 if o
in ("-h", "--help"):
243 setup
= "\n".join(setup
) or "pass"
244 # Include the current directory, so that local imports work (sys.path
245 # contains the directory of this script, rather than the current
248 sys
.path
.insert(0, os
.curdir
)
249 t
= Timer(stmt
, setup
, timer
)
251 # determine number so that 0.2 <= total time < 2.0
252 for i
in range(1, 10):
260 print "%d loops -> %.*g secs" % (number
, precision
, x
)
264 r
= t
.repeat(repeat
, number
)
270 print "raw times:", " ".join(["%.*g" % (precision
, x
) for x
in r
])
271 print "%d loops," % number
,
272 usec
= best
* 1e6
/ number
274 print "best of %d: %.*g usec per loop" % (repeat
, precision
, usec
)
278 print "best of %d: %.*g msec per loop" % (repeat
, precision
, msec
)
281 print "best of %d: %.*g sec per loop" % (repeat
, precision
, sec
)
284 if __name__
== "__main__":