As a backend developer, I've been working with Python for about 1 to 1.5 years, and I'm fairly proficient with frameworks like Flask and FastAPI. But what happens when you hear whispers of a language that promises blazing speed and robust structure? I decided to find out by rewriting my entire anime recommendation system in Go. And boy, what a ride it's been!

🔁 The Project: My Anime Recommendation System

The guinea pig for this experiment was my content-based anime recommendation system. In its original Python incarnation, it was powered by:

FastAPI for the API
MongoDB as the database
Gemini API for generating those all-important vector embeddings for similarity matching

For the Go version, I aimed for a similar setup but with a fresh Go flavor:

Chi router for handling requests (a new discovery for me!)
Still MongoDB for data persistence
I've tackled 7 out of the 10 endpoints so far, which feels like solid progress.
I also made sure to keep things modular, separating handlers, services, and routes.

Even though it's not fully ported yet, I'm genuinely thrilled with what I've learned and how my understanding of backend development has deepened.

⚙️ My Workflow: Python vs. Go – A Head-to-Head

Stepping into Go from Python felt both familiar and surprisingly different.

✅ What Felt Familiar

Schema Definitions: Whether it was Pydantic models in FastAPI or structs in Go, defining data schemas for requests and responses felt like home.
Modular Structure: The clean, modular project layout I adopted in Python translated beautifully into Go. It's a pattern that just works, regardless of the language.

⚠️ The Eye-Opening Differences

Aspect	Python (FastAPI)	Go
Async Support	First-class with `async def`	Done via goroutines, but I haven't explored them in this project yet.
Error Handling	`try/except` blocks; stack traces can sometimes feel like a cryptic puzzle.	Explicit `value, err` returns; the compiler points out issues with crystal clarity.
Request Timeout	Manual configuration needed.	Built-in `context.Context` handles timeouts and cancellation elegantly.
Project Setup	Requires `virtualenv`, meticulous dependency management.	Just a `main.go` and `go mod` – simple and ready to run.
Deployment	Needs Python runtime, dependencies, environment setup.	A single, static binary. Extremely lightweight and easy to deploy.

One difference that truly stood out was Go's error messages. Seriously, the Go compiler is like a helpful, super-smart friend who tells you exactly where you messed up. This alone saved me hours of head-scratching compared to deciphering ambiguous Python stack traces!

🔥 What Made Me Fall in Love with Go

Predictable Logic & Static Typing: Go's static typing meant fewer surprises. Unlike Python where I sometimes forgot type hints and only found issues at runtime, Go forced me to define types or structs upfront. This made my code feel more robust and predictable from the start.
Fantastic Tooling & LSP: gopls and LSP were game-changers. Because everything was strictly typed and structured, the LSP always knew what I was expecting to write, offering incredibly accurate code suggestions and type hints that made development smooth and efficient.
Blazing Fast: The build times and execution speed are genuinely impressive. No more waiting around!
Clean Code from the Get-Go: Go's opinionated nature really encourages good, modular, and readable code from the very beginning.
Deployment Dream: Oh, the joy of a single static binary! No virtualenv woes, no dependency hell. Just copy, paste, and run. It's truly a breath of fresh air.

😓 Where I Stumbled (Because It Wasn't All Sunshine and Rainbows)

if err != nil Repetition: This pattern, while explicit, can feel a bit noisy at times. I'm still getting used to its ubiquity.
Fewer Plug-and-Play Libraries: Compared to Python's vast ecosystem, Go's library landscape felt a bit leaner. Sometimes I had to build things myself or dig a bit deeper.
Learning Idiomatic Go: Understanding pointers, slices, and designing interfaces the "Go way" took some dedicated effort. It's a different mindset.

But honestly, with every file I wrote, I could feel my comfort and confidence growing. It's like learning to ride a bike – wobbly at first, then suddenly you're cruising.

💭 Final Thoughts: Should You Give Go a Shot?

If you're a seasoned Pythonista looking to:

Level up your backend skills
Write seriously performant APIs
Gain a deeper understanding of how systems programming works

Then absolutely, Go is a fantastic "second language" to pick up. It's strict, it's minimal, and it's incredibly honest – and that, I've come to realize, is a truly good thing.

🚀 What's Next for My Go Adventure?

My journey is far from over! My next steps include:

Finishing up those remaining endpoints.
Diving into the world of concurrency with goroutines – I hear it's magical!
Adding comprehensive tests and middleware.
Finally, deploying the Go version and seeing how its performance stacks up against the Python one.

You can explore the full project on GitHub here: Git Repo

📌 TL;DR

Rewriting my Python project in Go wasn't just about learning a new language; it fundamentally shifted my perspective on backend development. From Go's stricter typing to its ridiculously simple deployments, I'm pretty sure it's earned a permanent spot in my developer toolkit.

Have you tried switching languages for a project? What were your biggest takeaways?

🐍 From Pythonista to Gopher: My Adventure Rewriting a Backend Project