Is Python good for cybersecurity?

Is Python good for cybersecurity?

Python is one of the most recommended programming languages today, especially in the field of cybersecurity. Many schools actually start off teaching python to students as their first programming language. The reason for this is because of the learning curve python has. The barrier to entry in minimal and students can start to pick up python right away.

Top 3 Reasons to Learn Python for Cybersecurity

1. Easy to learn the fundamentals

According to TIOBE index, Python is ranked (as of 2022) the most popular programming language. The top 5 are C, Java, Python, C++, and C#. From an entry level perspective, out of the top 5, learning Python is considered the easiest to learn for many. The reason for this is because Python can easily be read like a normal language. It’s been designed in such a way that the human eye can clearly understand what is going on in the code by scanning through it.

Python easy to learn.

This design of the python creators allowed it to take substantially less code to perform certain tasks compared to other programming languages. Below we will demonstrate how to say “Hello World” in three different languages and you will see how much easier it is to implement in python.

# This Python program prints Hello, World!
print("Hello, World! \n")
/* This C program prints Hello, World! */

int main(void)
    printf("Hello World \n");
    return 0;
// This C++ program prints Hello, World!
#include <iostream>

int main()
    std::cout << "Hello, World! \n";
    return 0;

1. Automating tasks

Another useful feature that makes python a great programming language is the ability to create scripts to automate specific tasks. It is easy to get started with Python automation, and its wide range of test frameworks can be used for unit testing, cross browser testing, and more.

Python automating tasks

Automation Frameworks

  • Jasmine – one more BDD framework. It is easily integrated into Django projects, allows parallel execution of server-side and client-side test cases, and makes tests more resilient to changes.
  • Robot – an open-source key-driven framework for acceptance testing that provides a rich collection of tools and libraries.
  • pytest – the best python testing framework for small projects. It supports compact test suites and offers quick bug fixing. It can run parallel tests and integrate with other test frameworks.
  • Behave – a widely-used behavior-driven framework. Written in semi-formal language, it is easy to read for QA team and non-technical specialists, opening opportunities for collaboration.
  • Python unittest (or PyUnit) is a framework from the standard Python library and a great solution to start with Python automation. It provides a basic set of tools that supports fixtures, test cases, test suites, and a test runner. Unittest is often used in test-driven development. To discover the full potential, you will also need nose2 with its system of plugins.

Very few programming languages offer such variety in automation test frameworks like Python, thereby making it the best scripting language for automation. For cybersecurity, Python is very commonly used for automation. There are many use cases where automation is needed to automate mundane tasks.

3. Prototyping

Prototyping in Python is rather easy and quick, resulting in the development of the minimal viable product in a very short period of time. Since Python is rather agile, you can easily refactor code for a rapid development from the first prototype to the final product. Python is also open-source, which is a huge advantage. It is well-designed, scalable, portable, robust and fast due to its nature. Its syntax is easy to pick up, and it has uncluttered and well-developed advanced language features. In many ways, it exceeds the features and capabilities of other commercially available comparable solutions.

Python Prototyping

Python’s open-source license also allows unrestricted modification, redistribution and use of the language and applications based on it. The full source is available, and there are no licensing costs involved, which is a huge cost saver. Support is freely available through online resources

Prototyping with Python Use Cases

  • Write a few lines of code and test them without compiling or worrying about Makefiles.
  • For an interpreted language (as opposed to compiled languages), Python is very flexible. Interpreted languages often seem to favor certain use cases, like Perl seems to perform very well when processing text.
  • Python programs tend to run at acceptable speeds.
  • Python is a high level programming language, which means you can write code without having to worry about low level details such as memory management.
  • Many modules exist for Python and are very well documented. If you want to see how well, say, MongoDB works instead of MySQL, you don’t have to write the database connector from scratch.
  • Python runs a many platforms.


Python is a very powerful programming language for many applications such as mobile, web development, scientific computing, statistics, automation, artificial intelligence, and much more. Python is the fastest-growing programming language. Python programmers all across the globe agree to its capabilities as a language with high-functionalities and world-class libraries.

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