Python profiling using line_profiler - clever way

2020-05-23 06:37发布

问题:

I want to use the excellent line_profiler, but only some of the time. To make it work I add

@profile

before every function call, e.g.

@profile
def myFunc(args):
    blah
    return

and execute

kernprof.py -l -v mycode.py args

But I don't want to have to put the @profile decorators in by hand each time, because most of the time I want to execute the code without them, and I get an exception if I try to include them, e.g.

mycode.py args

Is there a happy medium where I can dynamically have the decorators removed based on some condition switch/argument, without having to do things manually and/or modify each function too much?

回答1:

Instead of removing the @profile decorator lines, provide your own pass-through no-op version.

You can add the following code to your project somewhere:

try:
    # Python 2
    import __builtin__ as builtins
except ImportError:
    # Python 3
    import builtins

try:
    builtins.profile
except AttributeError:
    # No line profiler, provide a pass-through version
    def profile(func): return func
    builtins.profile = profile

Import this before any code using the @profile decorator and you can use the code with or without the line profiler being active.

Because the dummy decorator is a pass-through function, execution performance is not impacted (only import performance is every so lightly affected).

If you don't like messing with built-ins, you can make this a separate module; say profile_support.py:

try:
    # Python 2
    import __builtin__ as builtins
except ImportError:
    # Python 3
    import builtins

try:
    profile = builtins.profile
except AttributeError:
    # No line profiler, provide a pass-through version
    def profile(func): return func

(no assignment to builtins.profile) and use from profile_support import profile in any module that uses the @profile decorator.



回答2:

You don't need to import __builtins__/builtins or LineProfiler at all, you can simply rely on a NameError when trying to lookup profile:

try:
    profile
except NameError:
    profile = lambda x: x

However this needs to be included in every file that uses profile, but it doesn't (permanently) alter the global state (builtins) of Python.



回答3:

A comment that grew to become a variant of @Martijin Pieters answer.

I prefer not to involve __builtin__ at all. W/o a comment, it would be practically impossible for someone else to guess that line_profiler is involved, w/o a priori knowing this.

Looking at kernprof line 199, it suffices to instantiate LineProfiler.

try:
    from line_profiler import LineProfiler
    profile = LineProfiler()
except ImportError:
    def profile(func):
        return func

Importing (explicit) is better than globally modifying builtins (implicit). If the profiling decorators are permanent, then their origin should be clear in the code itself.

In presence of line_profiler, the above approach will wrap the decorated functions with profilers on every run, irrespective of whether run by kernprof. This side-effect may be undesired.



回答4:

I am using the following modified version with Python 3.4

try:
    import builtins
    profile = builtins.__dict__['profile']
except KeyError:
    # No line profiler, provide a pass-through version
    def profile(func): return func