Chapter 16: Automate Repetition - Python Loops for Network Engineers

1. Why Loops Matter in Network Automation

When we talk about network automation, we’re really talking about systems that reduce human effort through structured, repeatable logic. Whether it’s pushing configurations to dozens of routers, validating interface statuses across thousands of ports, or analyzing logs from a distributed fleet of switches, one concept sits at the heart of these operations: loops.

Loops are one of the most fundamental control structures in programming. They allow you to instruct Python to repeat a block of code, either a specific number of times or until a condition is met. This idea may sound simple, but its power is profound.

In manual operations, a network engineer might SSH into 10 routers and run the same command on each. In automation, we use a loop to iterate through a list of those routers and run the same logic in code, consistently, rapidly, and reliably.

Let’s explore some practical motivations:

Repetition Is Inevitable in Network Engineering

Here are some tasks that naturally involve repetition and therefore benefit from loops:

Without loops, you'd have to write redundant, repetitive code, not only inefficient, but also error-prone and hard to maintain.

Why Not Just Copy-Paste Commands?

Copy-pasting commands might feel like a shortcut when dealing with 3 or 5 devices. But at scale, say, 2000 devices, it's unsustainable.

More importantly:

• Copy-paste lacks logic: No conditions, no branching, no real decision-making

• Harder to audit: You can't trace what happened, when, and why

• Not reusable: Every situation requires rewriting or adapting the steps manually

Loops introduce logic, structure, and flexibility into your workflow, which is essential for declarative, intent-based automation.

Loops as Foundations for Declarative Networking

In more advanced paradigms (like GitOps, Nornir workflows, or Ansible playbooks), you're working with models, devices, intents, states, often stored in dictionaries or YAML files. Loops help you traverse those data models, apply logic, and validate outcomes.

For example:

for device in device_list:
    if device["vendor"] == "juniper":
        push_junos_config(device)
    else:
        push_ios_config(device)

This kind of code reads naturally and aligns perfectly with declarative control over your network infrastructure.

But When Should You Use a for Loop vs a while Loop?

We’ll cover this in detail later, but as a rule of thumb:

Think of it as "iterate over known things" vs "wait for something to happen."

As a network engineer learning Python, understanding loops means adopting a mindset of repeatable, scalable logic. Loops let you think once, automate forever.

Let's dive in.

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