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Time the performance by timeit and cell magic

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Goal

This post aims to introduce how to measure the running time of your code or function by using timeit module and cell magic command %%time and %%timeit.

Reference *Time a Python Function

Libraries

In [1]:
import pandas as pd
import timeit

Measure a literal code

In [2]:
timeit.timeit('2**10')
Out[2]:
0.01853936500265263

Measure the execution time for a function

In [4]:
def execute_abc(x=10):
    return 2 ** 10
In [7]:
timeit.timeit(execute_abc)
Out[7]:
0.0984989230055362

Measure the time by using Cell Magic in Jupyter Notebook

In [3]:
%%time
2**10

CPU times: user 4 µs, sys: 1e+03 ns, total: 5 µs
Wall time: 11 µs
Out[3]:
1024
In [9]:
%timeit 2**10

17.9 ns ± 0.597 ns per loop (mean ± std. dev. of 7 runs, 100000000 loops each)