I recently completed a deep-dive Python course by David Beazley — a name well known in the world of Pythonistas and systems programmers. What started as a refresher quickly became a revelation. This post is a personal reflection on the key ideas, moments of friction, and “aha!” insights that stuck with me throughout the course.
1. Python Is Simpler Than It Looks — and Trickier Than It Seems
Beazley has a rare gift: he teaches Python by stripping away abstractions rather than piling them on. Early exercises (like reimplementing add() or building a Frac class) reminded me that many “magic” features in Python are just protocol-driven behavior under the hood.
Rewriting basic operations like +, ==, and repr() from scratch made me appreciate how much power lies in Python’s dunder methods. It also made the built-in fractions.Fraction feel like less of a black box.
2. Introspection Isn’t Just Debugging — It’s a Language Feature
From the start, we used tools like type(), isinstance(), and operator.add not just to understand values, but to interrogate Python’s object model.
import operator
print(operator.add(2, 3)) # 5
print(operator.add("Hi ", "AI")) # 'Hi AI'This mindset — of exploring rather than assuming — helped me see Python as a dynamic, introspective system where types are discoverable and behavior is inspectable.
3. Writing a Class ≠ Understanding a Class
Sure, I had written classes in Python before. But writing a working arithmetic type from scratch — including simplification with gcd, comparisons, and error handling — is a different story.
What struck me was how Python lets you negotiate meaning between objects through operator overloading. You define what it means for two things to be equal, or for one to be less than another. It’s a kind of semantics by construction.