I use an @profile() decorator for almost all my profiling. If you want to
profile function foo you just decorate it and re-run the program.
With a with block you have to find the places where foo is called and put
with statements around the calls.
I think both approaches are equally valid and useful.
On 3 November 2016 at 07:30, Ben Hoyt <benh...@gmail.com> wrote:
> Hi folks,
>
> Every time I do some Python profiling (with cProfile) the API feels kinda
> baroque, and I have to write ~10 line helper functions to do what I want.
> For example, if I want the return value of running some function and the
> profiling output as a string (e.g., to send as part of a web response), I
> have to do something like this:
>
> import cProfile
> import io
> import pstats
>
> def profile(func, *args, **kwargs):
> profiler = cProfile.Profile()
> result = profiler.runcall(func, *args, **kwargs)
> stream = io.StringIO()
> stats = pstats.Stats(profiler, stream=stream)
> stats.sort_stats('cumulative')
> stats.print_stats(strip_dirs=True)
> return (result, stream.getvalue())
>
> Something like that might be a useful function in its own right, but I
> took a look at the current API, and also an open issue that addresses some
> of this (https://bugs.python.org/issue9285 last touched almost 4 years
> ago), and came up with the following:
>
> 1) Add a format_stats() function to Profile to give the profiling results
> as a string (kind of parallel to format_* vs print_* functions in the
> "traceback" module). Signature would format_stats(self, *restrictions,
> sort='stdname', strip_dirs=False).
>
> 2) Add __enter__ and __exit__ to Profile so you can use it in a "with"
> statement.
>
> 3) Add a top-level runcall() function to the cProfile (and profile)
> modules. This isn't particularly useful for me, but it'd make the module
> easier to use from the command line, and it's one of the API improvements
> over at issue 9285.
>
> Other things in issue 9285 that I don't think are a good idea: the
> separate runblock() context manager (there should be only one way to do it,
> and I think "with Profile()" is great), and the @profile decorator (I
> really don't see the use of this -- you don't always want to profile a
> function when calling it, only it certain contexts).
>
> My code implementing the above three things as a separate module
> (subclassing Profile) is copied below.
>
> I think the above additions are non-controversial improvements -- do you
> think I should make a patch to get this into the standard library? New
> issue or add it to 9285?
>
> Another feature that I wanted and would be useful for a lot of folks, I
> think, would be some way to fetch the results as proper Python objects,
> rather than as a file/string. Maybe a Profile.get_results() function that
> returns a ProfileResult namedtuple which has total time and number of calls
> etc, as well as a list of ProfileEntry namedtuples that have the data for
> each function. Thoughts on that (before any bike-shedding on the exact API)?
>
> Currently folks who need this data have to use undocumented parts of
> Profile like .stats and .fcn_list, for example the Pyramid debug toolbar
> extracts this data so it can render it in an HTML web page:
> https://github.com/Pylons/pyramid_debugtoolbar/blob/
> ed406d7f3c8581458c2e7bdf25e11e9ee8e3d489/pyramid_debugtoolbar/panels/
> performance.py#L93
>
> Thanks!
> Ben
>
> # BELOW is my profileutils.py module
>
> """Code profiling utilities.
>
> >>> def foo(n):
> ... return sum(sum(range(i)) for i in range(n))
>
> >>> with Profile() as profiler:
> ... result = foo(5)
> >>> print(profiler.format_stats(3, sort='nfl')) # doctest: +ELLIPSIS
> 15 function calls (10 primitive calls) in 0.000 seconds
> <BLANKLINE>
> Ordered by: name/file/line
> List reduced from 5 to 3 due to restriction <3>
> <BLANKLINE>
> ncalls tottime percall cumtime percall filename:lineno(function)
> 6/1 0.000 0.000 0.000 0.000 {built-in method
> builtins.sum}
> 6 0.000 0.000 0.000 0.000 <...>:2(<genexpr>)
> 1 0.000 0.000 0.000 0.000 {method 'disable' ...}
> <BLANKLINE>
> <BLANKLINE>
> <BLANKLINE>
> >>> result
> 10
>
> >>> result = runcall(foo, 10) # doctest: +ELLIPSIS
> 24 function calls (14 primitive calls) in 0.000 seconds
> <BLANKLINE>
> Ordered by: standard name
> <BLANKLINE>
> ncalls tottime percall cumtime percall filename:lineno(function)
> 1 0.000 0.000 0.000 0.000 <...>:1(foo)
> 11 0.000 0.000 0.000 0.000 <...>:2(<genexpr>)
> 11/1 0.000 0.000 0.000 0.000 {built-in method
> builtins.sum}
> 1 0.000 0.000 0.000 0.000 {method 'disable' ...}
> <BLANKLINE>
> <BLANKLINE>
> >>> result
> 120
> """
>
> import cProfile
> import io
> import pstats
>
>
> VALID_SORTS = [
> 'calls', 'cumtime', 'cumulative', 'file', 'filename',
> 'line', 'module', 'name', 'ncalls', 'nfl',
> 'pcalls', 'stdname', 'time', 'tottime',
> ]
>
>
> class Profile(cProfile.Profile):
> def format_stats(self, *restrictions, sort='stdname',
> strip_dirs=False):
> """Format stats report but return as string instead of printing to
> stdout. "restrictions" are as per Stats.print_stats(). Entries are
> sorted as per Stats.sort_stats(sort), and directories are stripped
> from filenames if strip_dirs is True.
> """
> sort_keys = (sort,) if isinstance(sort, (int, str)) else sort
> stream = io.StringIO()
> stats = pstats.Stats(self, stream=stream)
> stats.sort_stats(*sort_keys)
> if strip_dirs:
> stats.strip_dirs()
> stats.print_stats(*restrictions)
> return stream.getvalue()
>
> # Define __enter__ and __exit__ to enable "with statement" support
>
> def __enter__(self):
> self.enable()
> return self
>
> def __exit__(self, exc_type, exc_value, exc_traceback):
> self.disable()
>
>
> def runcall(func, *args, **kwargs):
> """Profile running func(*args, **kwargs) and print stats to stdout."""
> profiler = cProfile.Profile()
> result = profiler.runcall(func, *args, **kwargs)
> profiler.print_stats()
> return result
>
>
> if __name__ == '__main__':
> import doctest
> doctest.testmod()
>
>
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