Why Python is Used in DevOps????
Python is a popular programming language used in DevOps for various reasons:
## Easy to Learn and Use
Python has a simple and clean syntax which makes it easy to learn and use. This helps DevOps engineers quickly write scripts for automation tasks.
## Large Standard Library
Python comes with a large standard library that includes modules for tasks like:
- System administration - `os`, `subprocess`
- Networking - `socket`
- Database access - `sqlite3`, `mysqlclient`
- Regular expressions - `re`
- Multi-threading - `threading`
These modules allow Python scripts to interact with the operating system, databases, networks and more.
## Platform Independent
Python scripts work on all major platforms like Linux, Windows and macOS. This allows the same script to be used across development, testing and production environments.
## Supports Multiple Programming Paradigms
Python supports object-oriented, procedural and functional programming styles. This makes it flexible and suitable for a wide range of tasks.
## Integrates with DevOps Tools
Many DevOps tools either have Python APIs or are written in Python, which allows Python scripts to integrate and extend the functionality of these tools. For example:
- Ansible - All Ansible modules are written in Python
- SaltStack - Uses Python for Salt formulas
- Fabric - Is written in Python
- Jenkins - Has a Python API
## Easy Automation
Python's simplicity and extensive standard library make it very suitable for automating repetitive system administration and DevOps tasks.
## Supports Cloud APIs
Python has libraries that interface with cloud platforms like AWS, GCP, Azure, etc. This allows automating cloud infrastructure provisioning and management using Python scripts.
So in summary, Python's simplicity, extensive library support, platform independence, tool integrations and suitability for automation tasks make it a very useful programming language for DevOps engineers.
Shell scripting vs Python
Shell scripting and Python are both useful tools for automating tasks and gluing together different programs. Here are some of the main differences:
Simplicity: Shell scripts tend to be simpler and more concise, especially for quick one-off tasks. Python requires more boilerplate and syntax.
Readability: Python scripts are generally considered more readable, especially for more complex tasks. Shell scripts can become unmaintainable quickly.
Portability: Shell scripts are portable across *nix systems since bash is ubiquitous. Python depends on the Python version available.
Speed: Shell scripts execute faster since they are interpreting built-in shell commands. Python involves launching the Python interpreter.
Data handling: Python has a more robust set of tools for handling data, like lists, dictionaries, classes, etc. Shell scripts rely on text-processing commands.
Error handling: Python has exception handling which makes error checking easier. Shell scripts require more conditional checks.
Reusability: Python modules and functions promote code reusability. Shell scripts are usually not reused across projects.
Syntax: Shell syntax is simple but limited. Python has a more powerful yet cleaner syntax.
In summary, for quick one-off tasks or gluing together commands, shell scripting is a good choice due to its simplicity, speed, and portability. For more complex tasks involving data manipulation, error handling, and code reuse, Python is a better option due to its robust language features.
Both have their place - you'll likely find yourself using both regularly. Shell scripts are good for quick automation, while Python is better suited for larger projects and applications. The best approach is to learn both and use the right tools for the job.
How to use Codespaces for Python??
Open any repository inside your GitHub account and click on the code
here, you will see an option for Codespaces and click on "create codespace on main"
GitHub will give you a new instance and this instance is similar to the AWS or Azure instance but it will not provide you any information about this instance.
Now, in your terminal if you write
python --version
you will see that Python is already installed.
Now, simply on the "Explorer" side, you will have an option for creating a new file similar to VS code and there you write Python code.
That's a wrap......................