saving cProfile results to readable external file

Updated. You can get output of profiler using io.StringIO() and save it into file.Here is an example:

import cProfileimport pstatsimport iodef my_func():    result = []    for i in range(10000):        result.append(i)    return resultpr = cProfile.Profile()pr.enable()my_result = my_func()pr.disable()s = io.StringIO()ps = pstats.Stats(pr, stream=s).sort_stats('tottime')ps.print_stats()with open('test.txt', 'w+') as f:    f.write(s.getvalue())

Run our script and open test.txt. You will see readable result:

   10002 function calls in 0.003 seconds   Ordered by: internal time   ncalls  tottime  percall  cumtime  percall filename:lineno(function)        1    0.002    0.002    0.003    0.003 /path_to_script.py:26(my_func)    10000    0.001    0.000    0.001    0.000 {method 'append' of 'list' objects}        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}

Also I can recommend to use dump_stats + pstats.Stats. Here is an example how to use it. Structure of files:

# test_ex.py - just a small web appimport cProfileimport jsonfrom functools import wrapsfrom flask import Flaskfrom example.mod1 import func1from example.mod2 import func2app = Flask(__name__)# profiling decoratordef profiling():    def _profiling(f):        @wraps(f)        def __profiling(*rgs, **kwargs):            pr = cProfile.Profile()            pr.enable()            result = f(*rgs, **kwargs)            pr.disable()            # save stats into file            pr.dump_stats('profile_dump')            return result        return __profiling    return _profiling# demonstration route with profiler@app.route('/test')@profiling()def test():    counter = func1()    dict_data = func2()    result = dict()    for key, val in dict_data.items():        result[key] = val + counter    return json.dumps(result)if __name__ == '__main__':    app.run(debug=True, port=8083)

example package - let's imagine that this is some kind of application logic.

# example.mod1def func1():    counter = 0    for i in range(100000):        counter += i    return counter# example.mod2def func2():    res = dict()    for i in range(300000):        res['key_' + str(i)] = i    return res

Now let's run server(python3 test_ex.py) and open http://localhost:8083/test. After a few seconds you will see long json. After that you will see profile_dump file in project folder. Now run python live interpreter in project folder and print our dump using pstats:

import pstatsp = pstats.Stats('profile_dump')# skip strip_dirs() if you want to see full path'sp.strip_dirs().print_stats()

Also you can easy sorting results:

p.strip_dirs().sort_stats('tottime').print_stats()p.strip_dirs().sort_stats('cumulative').print_stats()p.strip_dirs().sort_stats().print_stats('mod1')

Hope this helps.

You don't really need StringIO, as a file qualifies as a stream.

import pstatswith open("profilingStatsAsText.txt", "w") as f:    ps = pstats.Stats("profilingResults.cprof", stream=f)    ps.sort_stats('cumulative')    ps.print_stats()

Expanding upon the previous answer, you can dump everything out to a .csv file to sort and play around with in your favorite spreadsheet application.

import pstats,StringIO# print stats to a stringresult=StringIO.StringIO()pstats.Stats(filename,stream=result).print_stats()result=result.getvalue()# chop the string into a csv-like bufferresult='ncalls'+result.split('ncalls')[-1]result='\n'.join([','.join(line.rstrip().split(None,6)) for line in result.split('\n')])# save it to diskf=open(filename.rsplit('.')[0]+'.csv','w')f.write(result)f.close()