Trees | Indices | Help |
|
---|
|
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 module doc string).
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.
|
|||
|
|||
|
|||
|
|||
|
|
Constructor. See class doc string. |
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. |
Time 'number' executions of the main statement. To be precise, this executes the setup statement once, and then returns the time it takes to execute the main statement a number of times, as a float measured in seconds. 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. |
Call timeit() a few times. This is a convenience function that calls the timeit() repeatedly, returning a list of results. The first argument specifies how many times to call timeit(), defaulting to 3; 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. |
Trees | Indices | Help |
|
---|
Generated by Epydoc 3.0.1 on Fri Jun 13 23:39:10 2008 | http://epydoc.sourceforge.net |