Devop Skills

Python for DevOps: Python Scripting Tutorial for Beginners

In this article, I will discuss Python Scripting Tutorial for Beginners. So let’s get started.

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What is Python?

Python is a high-level programming language widely used for general-purpose programming, web development, scientific computing, data analysis, and automation. It is known for its readability and simplicity, making it an ideal choice for beginners.

Python has a large and active community that contributes to its extensive library of modules and frameworks. With its vast ecosystem and cross-platform compatibility, Python has become a popular choice for DevOps professionals.

What is DevOps?

DevOps is a set of practices that combines software development (Dev) and IT operations (Ops) to streamline the software delivery process.

It aims to improve collaboration and communication between development and operations teams, automate the software development lifecycle, and ensure faster and more reliable software releases. DevOps emphasizes automationcontinuous integration, and continuous deployment to enable teams to deliver software more efficiently and effectively.

Why Python for DevOps?

Python is a versatile and powerful programming language that is widely used in the field of DevOps. Its simplicity, readability, and extensive library support make it an ideal choice for automating various tasks in the DevOps workflow.

Python’s rich ecosystem of libraries and frameworks, such as AnsibleDocker, and Jenkins, provides developers with the tools they need to automate infrastructure provisioning, configuration management, and continuous integration and deployment. Additionally, Python’s cross-platform compatibility allows DevOps teams to write code once and run it on multiple operating systems, making it highly efficient and time-saving.

With its easy-to-learn syntax and broad community support, Python has become the go-to language for DevOps professionals looking to streamline their processes and improve efficiency.

Setting Up the Environment

Installing Python & Setup

Firstly, you have to install Python on your PC. You can download the latest version of Python from the official website (

Once installed, you can check for it by using a terminal or entering the following command:-


python --version

Writing Your First Python Script

Let’s begin your exploration of Python programming with a simple “Hello, DevOps!” script. ‘’ is a new file that should be created and opened in your favorite text editor. Add the following code after that:


print("Hello, DevOps!")

Save the file and navigate to its directory in your terminal. Execute the script by running:



You should see the output: “Hello, DevOps!” Congratulations, you’ve written and executed your first Python script!

Variables and Data Types

Python supports integers, floats, texts, and more data types. For scripting to be successful, it is essential to understand data types. Here is a summary:

  • Whole numbers without a decimal point are called integers.
  • Floats are decimalized numbers.
  • Character groups that are separated by single or double quotes are called strings.


age = 25           # Integer variable
pi = 3.14159       # Float variable
name = "Alice"     # String variable

Conditional Statements

Your scripts may make judgments based on specific situations thanks to conditional statements. The three keywords, if, Elif, and else, are necessary for developing this kind of reasoning.

python:-Explaintemperature = 28 if temperature > 30: print("It's hot outside!") elif temperature > 20: print("It's warm.") else: print("It's cool.")

Loops for Automation

The use of loops in automating routine chores is essential. While the “while” loop appears as long as a specific condition is fulfilled, the “for” loop enables you to iterate through a sequence.

python:-Explaintemperature = 28 if temperature > 30: print("It's hot outside!") elif temperature > 20: print("It's warm.") else: print("It's cool.")

Functions for Reusability

You may reuse portions of code called functions across your scripts. They improve the maintainability and structure of the code. 📄

python:-Explaindef greet(name): print("Hello,", name) greet("Alice") # Output: Hello, Alice greet("Bob") # Output: Hello, Bob

To get started with Python development, you first need to install Python on your system. Python is a versatile and powerful programming language that is widely used in the DevOps field.

It offers a wide range of libraries and frameworks that make it easier to automate tasks and manage infrastructure. To install Python, you can visit the official Python website and download the latest version for your operating system.

Once installed, you can use the pip package manager to install additional Python packages and libraries required for your DevOps projects.

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Installing DevOps Tools

After installing Python, the next step in setting up the development environment for Python DevOps is to install the necessary DevOps tools. These tools are essential for automating various tasks in the DevOps workflow. Some popular DevOps tools that can be installed include:

  • Docker: A containerization platform that allows for easy deployment and management of applications.
  • Ansible: An open-source automation tool that helps in configuration management and application deployment.
  • Jenkins: A widespread continuous integration and continuous deployment (CI/CD) tool.

By installing these tools, developers can leverage the power of Python to automate infrastructure, manage configurations, and streamline the CI/CD process.

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Configuring the Development Environment

After installing Python and the necessary DevOps tools, the next step is configuring the development environment. This involves setting up environment variables path variables, and configuring version control systems.

Additionally, it is essential to install and configure code editors and IDEs that support Python development. A popular choice for Python development is Visual Studio Code, which offers a wide range of extensions and integrations for DevOps workflows.

Once the development environment is configured correctly, developers can start writing and testing Python scripts for various DevOps tasks.

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Automating Infrastructure

Infrastructure as Code

Infrastructure as Code is a methodology that allows developers and operations teams to manage and provision infrastructure resources using code.

This approach brings several benefits, such as improved reproducibilityscalability, and version control. By treating infrastructure as code, organizations can automate the provisioning and configuration of servers, networks, and other resources, reducing the risk of manual errors and enabling efficient collaboration between teams.

With Python, developers can leverage various libraries and frameworks to write declarative and programmatic infrastructure code, making it easier to manage complex infrastructure setups and configurations.

Using Python for Infrastructure Automation

Python is a powerful and versatile programming language that is widely used in the field of DevOps for automating infrastructure tasks. With its simple syntax and extensive libraries, Python provides developers with a wide range of tools and frameworks to automate various aspects of infrastructure management.

Python can provision and configure servers, deploy applications, and manage network infrastructure. It also integrates well with popular DevOps tools such as Ansible and Docker, allowing for seamless automation of infrastructure tasks.

By leveraging the power of Python, DevOps teams can streamline their operations, improve efficiency, and reduce manual errors in infrastructure management.

Managing Configuration with Ansible

Ansible is an open-source configuration management and automation tool. It allows you to define and manage your infrastructure as code, making it easier to automate the configuration of your servers and network devices.

With Ansible, you can define the desired state of your infrastructure using playbooks and roles and then apply those configurations across multiple hosts. Ansible also provides a simple and powerful way to manage inventory, allowing you to group and target specific hosts quickly.

Additionally, Ansible integrates well with other DevOps tools, making it a popular choice for managing configuration in a DevOps environment.

Continuous Integration and Deployment

Introduction to CI/CD

Continuous Integration/Continuous Deployment (CI/CD) is a software development practice that enables developers to automate the process of integrating code changes, building and testing applications, and deploying them to production environments.

With Python, developers can easily create and manage CI/CD pipelines, allowing faster and more efficient software delivery. In this section, we will explore the fundamental concepts of CI/CD and how Python can be used to build robust and scalable pipelines.

We will also investigate deploying applications using Docker, a popular containerization platform.

Building CI/CD Pipelines with Python

Building CI/CD pipelines is a crucial aspect of DevOps. Python provides a wide range of libraries and frameworks that can be used to automate the process.

With tools like Jenkins and GitLab, developers can easily integrate Python scripts into their pipelines to automate tasks such as code compilation, testing, and deployment.

By leveraging Python’s simplicity and flexibility, teams can achieve faster and more reliable software delivery, ensuring continuous integration and deployment of their applications.

Deploying Applications with Docker

Deploying applications with Docker is a crucial step in the DevOps process. Docker allows developers to package their applications into containers, which can be deployed consistently across different environments.

This ensures the application runs the same way in development, testing, and production. With Docker, it becomes easier to manage dependencies, isolate applications, and scale them as needed.

Docker also integrates well with DevOps tools, such as Ansible, for configuration management and CI/CD pipelines built with Python. By leveraging Docker, teams can streamline the deployment process, reduce deployment errors, and achieve faster time-to-market for their applications.

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