OOP in Practice: Real-World OOP Problems With Code

Free series · Python · TypeScript · Java · PHP

OOP in Practice is a series of short, worked problems that teach object-oriented programming the way you use it at work and in interviews: start with a real-world problem, find the objects, write the naive version, see why it breaks, then design and run a clean solution.

Each episode is a single problem, not a long article. You get a problem card with requirements, a class/responsibility table, an ASCII class diagram, the full solution, the real output from running it, the trade-offs, the follow-up questions an interviewer is likely to ask, and two or three exercises to extend it yourself.

How each episode works

  1. The problem — a concrete scenario with requirements and constraints.
  2. Find the objects — which classes exist and what each one is responsible for.
  3. The naive approach — the version most people write first, and exactly how it fails.
  4. The design — the principle or pattern that fixes it, with a class diagram.
  5. The code and its real output — every solution is executed before publishing; the output you see is from that run, with the runtime version.
  6. Interview follow-ups and practice — how to extend, scale, test or make it thread-safe.

How to use it for interview prep

  • Read the problem card, then stop. Try the design on paper for 10–15 minutes before you scroll.
  • Compare your classes with the responsibility table. Most interview feedback is about responsibilities, not syntax.
  • Answer the follow-up questions out loud. Then do one practice exercise in your own language.
  • Work in order if you are new to OOP: foundations and SOLID come first, then design patterns, then full low-level design problems. Episodes link back to the ideas they build on.

Code is written in Python, TypeScript, Java or PHP, usually with a second language version underneath. The design matters more than the language, so pick whichever you will use in your interview.

All episodes

1 episode published so far.

OOP Foundations

  1. Encapsulation in Python: A Wallet That Can't Go Negative Beginner Python