Python: Peeling the layers of the onion (First post)
Hi, DEV community!
I’ve been staring at Python code for a while now, and the more I look, the more I realize how much is hidden just beneath the surface. You know that feeling when you think you’ve mastered a library or a built-in feature, and then you accidentally stumble upon a dunder method or a memory management quirk that changes everything? That’s where I am right now.
I’ve decided to start documenting my journey of dissecting Python internals. Not because I’m a core dev (yet), but because I’m obsessed with how things actually work under the hood.
What I’m currently digging into:
The Explicit and the Implicit: Python is famous for being readable, but sometimes its "magic" is a double-edged sword. I’m currently trying to draw the line between "clean code" and "too much abstraction."
Architectural Flaws: I like to take apart popular tools and see why they were built the way they were. Some parts are brilliant; others look like they were held together by duct tape and prayers.
The "Why" behind the "How": It’s easy to follow a tutorial. It’s much harder to explain why a certain implementation throttles your performance or why a specific design pattern feels "un-pythonic."
My goal here
I’m not here to drop "Top 10 Tips" or clickbait tutorials. I want to write deep, long-form teardowns (expect some 1.5k+ word deep dives soon) where we can actually look at the source code and figure out the logic together.
Some things I’ve already figured out, and some... well, I’m still scratching my head over. But I think there’s a lot of value in sharing the process of "figuring it out" rather than just the final result.
If you’re into technical audits, architectural deep dives, or just curious about why Python behaves the way it does — let’s connect.
I’d love to hear what part of Python (or its ecosystem) always felt like a "black box" to you. Maybe we can break it down together in my next post.
Stay tuned, more "under the hood" stuff is coming.
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