Python Party Launch

If you’ve skimmed network engineer job postings lately, you’ve noticed the pattern: automation experience required. Not “nice to have.” Required. Employers expect fluency with APIs, version control, repeatable workflows, and the ability to turn tribal CLI knowledge into code that anyone on the team can run safely.

That’s why we’re launching a new Python Study Session series on The Art of Network Engineering. We’re learning Python from the ground up, and bringing you along for the ride.

We Already Trust Automation Everywhere Else

Look at the parts of your life that quietly “just work” now:

• Bill pay & banking: autopay, fraud alerts, round-ups; no more calendar reminders or late fees.
• Groceries & deliveries: scheduled orders and curbside pickup; less time in lines, fewer mistakes.
• Home & car: thermostats that learn patterns, EVs that precondition batteries, apps that auto-update firmware.
• Calendars & travel: smart scheduling, flight rebooking, status notifications; issues handled before you even notice.
• Cameras & files: auto-backup, deduplication, search; no more “USB stick roulette.”

Automation moved us from manual busywork to systems that are faster, safer, and more predictable. The lesson is obvious: when repetitive tasks are automated, humans spend time on judgment, design, and improvement.

Now Apply That Mindset to Networks

Networks are perfect candidates for the same shift:

• From one-off CLI to repeatable workflows. Use templates and variables to generate consistent configs; no drift, fewer typos.
• From manual change windows to tested pipelines. Validate intent with pre-checks, dry runs, and automated rollbacks before touching prod.
• From “eyes on glass” to event-driven ops. Stream telemetry, detect anomalies, and trigger safe, idempotent responses automatically.
• From tribal knowledge to shared code. Put patterns in Git, review them with peers, and make improvements discoverable and auditable.
• From vendor silo to API-first. Talk to controllers and devices through consistent SDKs instead of remembering per-box syntaxes

Why Python Is the Easiest On-Ramp for Non-Coders

If you don’t identify as a “developer,” Python is the friendliest place to start:

• Readable syntax: it looks like English. You’ll spend brain cycles on network logic, not curly braces.
• Massive ecosystem: libraries like Netmiko, NAPALM, Paramiko, Requests, Jinja2, Pandas, and pytest solve real network problems out of the box.
• Cross-vendor reach: most modern platforms expose APIs/SDKs that have Python examples first.
• Career leverage: Python fluency maps directly to CI/CD, source control, testing, and infra-as-code skills showing up in net eng job postings.

What We’ll Do in the Series (and Why It Matters)

We’re working through Python Crash Course (3rd Ed.). Episode one gets the basics in place:

• Install Python, open the interpreter, and run print(“Hello, Python World”).
• Set up VS Code with syntax highlighting and extensions (instant feedback beats guessing).
• Learn core concepts; variables first, then build toward lists, dictionaries, loops, and functions with confidence.
• Embrace error messages (tracebacks) as our teachers, not punishments.

In future episodes, we’ll connect fundamentals to network-specific wins:

• Generate configs from Jinja2 templates and variables (repeatable, human-readable).
• Use Netmiko/NAPALM to push changes safely, with pre-/post-checks.
• Pull telemetry and API data into simple reports (Pandas) for real visibility.
• Add tests (pytest) so changes prove themselves before they touch prod.
• Wrap it in a Git workflow so your team collaborates, reviews, and rolls back with confidence.

If You’re New to Automation, Start Here

You don’t need to become a software engineer. You need small, consistent reps that map to daily network tasks:

1. One command → a function. Take a common CLI step and express it in Python.
2. One device → a loop. Run the same safe step across a list of devices.
3. Static text → a template. Turn a config snippet into a Jinja2 template with variables.
4. Manual verify → assertions. Automate pre-checks and post-checks so success is provable.
5. Your laptop → a repo. Commit, review, improve. Your future self (and teammates) will thank you.

Join the Journey

• Listen: https://www.buzzsprout.com/2127872/episodes/17841434
• Watch: https://youtu.be/BHNUk8ubZkc
• Participate: Bring your questions, your sticking points, and your “there’s-got-to-be-a-better-way” moments. We’ll solve them together. Subscribe to our YouTube channel and click the notification icon to get notified of our free Python Party Livestreams: https://www.youtube.com/@artofneteng

Automation has already improved the rest of our lives. It’s time our networks catch up. Python is the easiest first step.
Let’s take it together.