Python has transformed from a normal programming language to a pivotal tool in IT. It is adopted in various fields, including web applications, application server programming, data science, DevOps, and even AI. It has evolved from an ordinary programming language to a powerful tool to assist in every part of IT. Let's look at it in this post.
What is Python?
Python is a general-purpose language first released in 1991 by Guido van Rossum. It supports OOPs concepts and is used in a wide range of use cases. Since it wasn’t created to solve a single problem, it has evolved to support a wide range of applications, including web development, devops, automation, AI, and data science.
Why is it popular?
Python is popular because of its code readability. Python works on 19 core principles, which are called the zen of Python. A few of them are,
- Beautiful is better than ugly.
- Explicit is better than implicit.
- Simple is better than complex.
- Complex is better than complicated.
- Readability counts.
It is easy to read and write the code and also supports dynamic typing, which means data types need not to be declared. It may be quite confusing for newbies. But in short, Python avoids some of the complexities we find in other programming languages (You need not to worry about a missing semicolon but watch out for the missed indentations :) )
Another powerful advantage of Python is its extensive libraries. Many problems can be solved using existing libraries, allowing developers to focus on higher-level tasks. The vast community support and community-driven libraries make it easier for people to use Python in various scenarios.
How can Python help in DevOps?
Python’s use cases vary from web development to AI. But we focused on the part where we use it in DevOps, particularly in scripting and automation.
One of its best use cases is that it can be used for automation extensively. There may be a question, if we already have shell scripting (Linux) and PowerShell (Windows), why there is a need for a new scripting language?
The answer is, that Python can be used as a machine-independent scripting language that will work in various OS. Large-scale corporate IT systems usually have multiple OS layers. Having different script languages to handle them will be a tedious task for a DevOps engineer. But having a single scripting language, which will work on various OS for automation, is a boon for DevOps people.
Important Modules in Python which can help us in DevOps
If you plan to use Python for DevOps activities, you have to familiarize yourself with some inbuilt libraries and modules that are readily available. This will reduce your workload and help you code Python efficiently and achieve the results faster.
os: For interacting with the operating system.
subprocess: For running subprocesses and handling their input/output.
sys: For system-related functions.
ansible: For IT automation.
saltStack: For managing scalable infrastructures.
paramiko: Supports SSHv2 protocol.
boto3: The AWS SDK for Python.
requests: For making HTTP requests.
fabric: For executing shell commands remotely.
docker SDK: For interacting with Docker within Python code.
I hope this information is useful to you. Please share your comments and feedback. If I missed anything, feel free to mention it, and I’ll update the post. Your input is valuable to me.
Super Srini
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