Dev Ops Development Python

Python timeit module

Programming is not just about accomplishing a task and getting an output we intended to get. It is also about how fast a program runs and execute so that the desired output is achieved. With most of the programming languages, it is not easy to compare how fast out program has run and it is never easy to time a particular piece of code to understand which part of our code is taking the most time to execute. This is the issue which is solved by the Python timeit module.

Python timeit module

Python timeit module allows us to time the execution time of a piece of code without taking into account the background processes which are run to make a code executable. If you need slightly accurate measurements of how your code is performing timeit is the module to go for.

timeit simple example

We will start by using the timeit module directly from the command prompt. timeit module can be used directly from the CLI where we can input a simple loop statement and time it using the shown command:

$ python --version
$ python -m timeit '"&".join(str(n) for n in range(1000))'
$ python -m timeit '"&".join([str(n) for n in range(1000)])'
$ python -m timeit '"&".join(map(str, range(1000)))'

Here is what we get back with this command:

Time of execution from CLI using timeit

Time of execution from CLI using timeit

In one of the later sections, we will learn how we can manage the number of loops performed to find the optimal number for the execution of a given expression.

Timing a piece of code

If you have a basic python script which you want to measure time for, timeit module is the way to go:

import timeit

# setup code is executed just once
setup_code = "from math import sqrt"

# main code snippet for performance check
code_to_measure = '''
def example():
mylist = []
for x in range(100):
mylist.append(sqrt(x))
'
''

# timeit statement
print(timeit.timeit(setup = setup_code,
stmt = code_to_measure,
number = 10000))

Let’s see the output for this command:

Timing a loop

Timing a loop

In this code, we also saw how we can control the number of repetitios the timeit module will perform to find the best time of execution for the program.

Measure time for multi-line code from CLI

We can also measure time for code which spans through multiple lines in the Python CLI. Let’s look at a sample program to see this:

$ python -m timeit -s \
> "linuxhint = {}" \
> "for n in range(1000):" \
> " linuxhint[str(n)] = n"

Here is what we get back with this command:

Timing multi-line code on CLI

Timing multi-line code on CLI

Generally comparing two blocks of code

If you don’t want to get into a hassle of using CLI and just want to compare two Python programs so that you know which one runs faster, there is a pretty simple way of achieveing this:

import timeit

start = timeit.default_timer()
funcOne()
print(timeit.default_timer() - start)

start = timeit.default_timer()
funcTwo()
print(timeit.default_timer() - start)

By using the default_timer() function, we start the times again and again to find a difference for the same when it was last started. This can only be used when you have good modular style of writing code so that each pieve of code can be measured separately.

Conclusion

In this lesson, we studied how we can time our code in Python and see their time complexity and efficiency and work over it if the code is too slow.

About the author

Shubham Aggarwal

Shubham Aggarwal

I’m a Java EE Engineer with about 4 years of experience in building quality products. I have excellent problem-solving skills in Spring Boot, Hibernate ORM, AWS, Git, Python and I am an emerging Data Scientist.