Python is often praised for its simplicity, but that same simplicity can cause teams to overlook powerful features already built into the language. In real-world projects, this leads to reinventing solutions, writing excessive boilerplate, unclear APIs, and accumulating technical debt—often without realizing better tools already exist.

In this talk, we’ll explore commonly skipped Python features and show why they matter in production systems. These are not obscure tricks or niche hacks, but practical, standard-library and language features that many developers know of but rarely use.

Through real project–inspired examples, we’ll look at:

Python features developers tend to avoid or forget

The reasons they’re skipped (habit, fear of complexity, lack of examples)

How these features solve real problems around maintainability, readability, correctness, and performance

When not to use them, to avoid overengineering

Topics may include (time permitting):

Typing tools like Protocol, TypedDict, and TypeGuard

dataclasses, enums, and better data modeling

contextlib and advanced context managers

Underused built-ins and stdlib utilities (functools, itertools)

Modern Python improvements (3.10–3.12) that simplify real code

Debugging and introspection tools developers forget exist

The focus is on before/after refactors, practical guidelines, and mental models attendees can immediately apply in their own codebases.

This talk helps developers write clearer, safer, and more maintainable Python—without adding new dependencies.