class cprofile(sort='cumtime', columns='default', mintime=0.001, stripdirs=True, show=True)[source]#

Bases: prettyobj

Function profiler, built off Python’s built-in cProfile

Note: sc.profile() shows the time taken by each line of code, in the order the code appears in. sc.cprofile() shows the time taken by each function, regardless of where in the code it appears.

The profiler can be used either with the enable() and disable() commands, or as a context block. See examples below for details.

Default columns of output are:

  • ‘func’: the function being called

  • ‘cumpct’: the cumulative percentage of time taken by this function (including subfunctions)

  • ‘selfpct’: the percentage of time taken just by this function (excluding subfunctions)

  • ‘cumtime’: the cumulative time taken by this function

  • ‘selftime’: the time taken just by this function

  • ‘calls’: the number of calls

  • ‘path’: the file and line number

  • sort (str) – the column to sort by (default “cumpct”)

  • columns (str) – what columns to show; options are “default” (above), “brief” (just func, cumtime, selftime), and “full” (as default plus percall and separate line numbers)

  • mintime (float) – exclude function times below this value

  • stripdirs (bool) – whether to strip folder information from the file paths

  • show (bool) – whether to show results of the profiling as soon as it’s complete


import sciris as sc
import numpy as np

class Slow:

    def math(self):
        n = 1_000_000
        self.a = np.arange(n)
        self.b = sum(self.a)

    def plain(self):
        n = 100_000
        self.int_list = []
        self.int_dict = {}
        for i in range(n):
            for j in range(10):
                self.int_dict[i+j] = i+j

    def run(self):

# Option 1: as a context block
with sc.cprofile() as cpr:
    slow = Slow()

# Option 2: with start and stop
cpr = sc.cprofile()
slow = Slow()
New in version 3.1.6.


parse_stats(stripdirs=None, force=False)[source]#

Parse the raw data into a dictionary

to_df(sort=None, mintime=None, columns=None)[source]#

Parse data into a dataframe

See class docstring for arguments

disp(*args, **kwargs)[source]#

Display the results of the profiling; arguments are passed to to_df()


Start profiling


Stop profiling