Day 15 : Python Libraries for DevOps

Day 15 : Python Libraries for DevOps

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4 min read

Introduction

Python is a popular programming language for DevOps because it is versatile, easy to learn, and has a large ecosystem of libraries and tools.
Python libraries are collections of pre-written code that can be used to perform specific tasks in Python. They are typically installed using a package manager, such as pip.

Python libraries are a valuable resource for Python developers, as they allow them to avoid having to write code from scratch for common tasks. This can save a lot of time and effort, and it can also help to improve the quality and consistency of code. Python libraries can be used to automate a wide range of DevOps tasks, such as configuration management, infrastructure provisioning, and continuous integration and delivery (CI/CD).

Libraries used by DevOps Engineer in day-to-day tasks

As a DevOps engineer, there are several libraries in Python that are essential for daily tasks. Here are some of the most commonly used libraries:

  1. Os and Sys Libraries: The os and sys libraries provide a way to interact with the operating system and access various system-related information. These libraries are used extensively in scripting and automation tasks, such as reading or modifying environment variables, working with directories and files, and executing system commands.

  2. Json and YAML Libraries: JSON (JavaScript Object Notation) and YAML (YAML Ain't Markup Language) are popular data serialization formats used in DevOps for storing and sharing data between different systems. Python provides built-in support for JSON through the json module, while YAML can be parsed using libraries like ruamel.yaml or PyYAML.

  3. requests Library: The requests library is a powerful tool for making HTTP requests in Python. It simplifies the process of sending HTTP requests and parsing responses, making it easier to interact with web services and APIs. This library is widely used in DevOps for tasks like deploying applications, fetching configuration files, and monitoring API endpoints.

  4. Paramiko Library: Paramiko is a Python library that provides secure remote access to servers using SSH (Secure Shell). It allows DevOps engineers to connect to remote machines, execute commands, transfer files, and manage server configurations. Paramiko is an essential library when working with cloud providers, virtual private networks, or other remote environments.

  5. Fabric Library: Fabric is another popular Python library for task automation and deployment. It provides a simple and elegant way to execute shell commands on remote hosts, allowing DevOps engineers to perform tasks like software installation, file editing, and user management quickly and efficiently.

  6. Ansible Library: Ansible is an open-source automation tool that helps streamline DevOps processes. The Ansible library in Python enables developers to define infrastructure, deploy applications, and manage configurations easily. With Ansible, DevOps engineers can create playbooks that automate repetitive tasks, reducing errors and increasing efficiency.

  7. Docker Library: Docker is a containerization platform that revolutionized the way applications are deployed and managed. The Docker library in Python allows DevOps engineers to work with containers programmatically, creating, managing, and orchestrating them. Developers can use this library to build custom Docker images, run containers, and manage Docker volumes and networks.

  8. Pyyaml Library: Pyyaml is a YAML parser library that provides a convenient way to read and write YAML documents in Python. It offers flexible options for loading and dumping YAML data, making it easy to work with YAML configurations in DevOps workflows.

  9. Jmespath Library: JMESPath (JSON Matching Expressions Syntax for Paths) is a query language for JSON data. The jmespath library in Python enables DevOps engineers to search and manipulate JSON data using simple and complex queries. This library is useful when working with large JSON datasets, such as those generated by Cloud providers or Configuration Management tools.

  10. Awscli Library: AWS CLI (Command Line Interface) is a set of tools that allow developers to interact with Amazon Web Services (AWS) resources from the command line. The awscli library in Python provides a unified way to manage AWS services, including EC2 instances, S3 buckets, and IAM users. This library is essential for DevOps engineers working with AWS infrastructure.

These libraries are just a few examples of the many tools available to DevOps engineers working with Python. By mastering these libraries, developers can automate tasks more effectively, improve productivity, and enhance overall workflow efficiency.

Parsing files

The ability to parse files in various formats, including plain text (.txt), JSON, and YAML, is essential for automating tasks, troubleshooting issues, and monitoring and securing systems.
By possessing file parsing skills, DevOps Engineers can efficiently manage and configure systems, extract meaningful insights from logs and reports, and automate routine tasks. This ultimately leads to improved system performance, increased productivity, and better decision-making based on accurate data analysis.


Tasks

  1. Create a Dictionary in Python and write it to a json File.

  1. Read a json file services.json kept in this folder and print the service names of every cloud service provider.
output

aws : ec2
azure : VM
gcp : compute engine

  1. Read YAML file using python, file services.yaml and read the contents to convert yaml to json


Thankyou for reading until here.Happy Coding! See you in the next one.