Chapter 8: How Network Engineers Use Python Data Types in Real Automation

Your First Practical Dive Into Python Data Types

Welcome to another edition of the Packets & Python series, where we begin bridging the gap between Python fundamentals and real-world network engineering workflows.

In this post, we’ll explore data types, a foundational topic that every network engineer needs to understand before diving into automation, telemetry parsing, or intent validation. Even if you’ve never written a single line of code, this lesson is crafted to ease you in from scratch.

We’ll walk through Python’s core data types using practical examples pulled straight from network automation scenarios: think BGP peer lists, interface counters, prefix mappings, or device telemetry. This isn’t abstract theory; it’s grounded in the kind of data you already work with.

If you're already experienced with Python, feel free to skim this for refreshers. But if you're starting your journey into automation, this is your launchpad.

And here’s your mission: don’t just read. Experiment. Copy and paste the examples into your Python environment or VS Code terminal. Run them. Break them. Modify them. Try replacing values with real data from your lab, testbed, or production snapshots.

Hands-on practice will rapidly build your comfort with how Python handles and classifies data, and that’s the very first step toward writing meaningful network automation.

Let’s get started.

Data Types

Data types categorize and classify data items, indicating the type of value that determines which operations can be applied to specific data.

Here are Python's standard built-in data types:

As a network engineer writing Python code, selecting the right data type is crucial for storing and handling operational data effectively.

Here’s a practical breakdown of Python’s core data types, illustrated with real-world networking examples:

Subscribe to our premium content to read the rest.