Python Library Reference

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10.5 Reference Manual

The primary entry point for the profiler is the global function profile.run(). It is typically used to create any profile information. The reports are formatted and printed using methods of the class pstats.Stats. The following is a description of all of these standard entry points and functions. For a more in-depth view of some of the code, consider reading the later section on Profiler Extensions, which includes discussion of how to derive ``better'' profilers from the classes presented, or reading the source code for these modules.

run (string[, filename[, ...]])

This function takes a single argument that has can be passed to the exec statement, and an optional file name. In all cases this routine attempts to exec its first argument, and gather profiling statistics from the execution. If no file name is present, then this function automatically prints a simple profiling report, sorted by the standard name string (file/line/function-name) that is presented in each line. The following is a typical output from such a call:

      main()
      2706 function calls (2004 primitive calls) in 4.504 CPU seconds

Ordered by: standard name

ncalls  tottime  percall  cumtime  percall filename:lineno(function)
     2    0.006    0.003    0.953    0.477 pobject.py:75(save_objects)
  43/3    0.533    0.012    0.749    0.250 pobject.py:99(evaluate)
 ...

The first line indicates that this profile was generated by the call:
profile.run('main()'), and hence the exec'ed string is 'main()'. The second line indicates that 2706 calls were monitored. Of those calls, 2004 were primitive. We define primitive to mean that the call was not induced via recursion. The next line: Ordered by: standard name, indicates that the text string in the far right column was used to sort the output. The column headings include:

ncalls

for the number of calls,

tottime

for the total time spent in the given function (and excluding time made in calls to sub-functions),

percall

is the quotient of tottime divided by ncalls

cumtime

is the total time spent in this and all subfunctions (i.e., from invocation till exit). This figure is accurate even for recursive functions.

percall

is the quotient of cumtime divided by primitive calls

filename:lineno(function)

provides the respective data of each function

When there are two numbers in the first column (e.g.: "43/3"), then the latter is the number of primitive calls, and the former is the actual number of calls. Note that when the function does not recurse, these two values are the same, and only the single figure is printed.

Analysis of the profiler data is done using this class from the pstats module:

Stats (filename[, ...])

This class constructor creates an instance of a ``statistics object'' from a filename (or set of filenames). Stats objects are manipulated by methods, in order to print useful reports.

The file selected by the above constructor must have been created by the corresponding version of profile. To be specific, there is no file compatibility guaranteed with future versions of this profiler, and there is no compatibility with files produced by other profilers (e.g., the old system profiler).

If several files are provided, all the statistics for identical functions will be coalesced, so that an overall view of several processes can be considered in a single report. If additional files need to be combined with data in an existing Stats object, the add() method can be used.

• 10.5.1 The Stats Class

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Python Library Reference

Previous: 10.4 What Is Deterministic Up: 10. The Python Profiler Next: 10.5.1 The Stats Class