Skip to main content

Posts

Showing posts with the label Python Fundamentals

#9/10 | Spring Boot + Docker Compose: 7 Bugs That Broke My First Boot

Part 9 of 10 of Building Instagram's Authentication Backend . If you're just joining, the repo is here and you can catch the earlier parts on the YouTube playlist . Eight parts of code, zero runs By the end of part 8, every layer of this backend existed: DTOs, exceptions, entities, repositories, five services, a security filter chain and a controller. And I had never started the application. Not once. Everything so far was code I'd reasoned through and believed would work. This part is where that belief gets tested. We containerize the app, put Postgres, Redis and a fake mail server next to it, and bring all four up with one command. It did not work the first time, so this post is the real debugging session, with each bug, its symptom and its fix. If you're containerizing your own Spring Boot app, there's a good chance you'll hit at least one of these. In this post: A multi-stage Dockerfile for Spring Boot, line by line A docker-compose.yml ...

Python Development Crash Guide 2026 — Part 6 (Job-Ready Blueprint: Projects, Roadmap, Resume & Interview Preparation)

Python Development Crash Guide 2026 — Part 6: Job-Ready Blueprint: Projects, Resume & Interview Prep Learning Python is the easy part. Getting hired with Python — that's where most people get stuck. Not because they lack knowledge, but because they can't prove what they know. This final part is about turning everything from Parts 1–5 into something a recruiter, hiring manager, or interviewer can evaluate. I've been on both sides of this. I've prepared for interviews, built portfolio projects, and landed roles. I also run mock interview sessions on Topmate where I see exactly what works and what doesn't when candidates present their Python experience. This post is built on that. What "Job-Ready" Actually Means I want to be blunt about this because most guides aren't. Being job-ready doesn't mean you know every Python feature. It doesn't mean you've completed 15 Udemy courses or have 200 LeetCode solutions. I've interview...

Python Development Crash Guide 2026 — Part 5 (Python in Real-World Engineering: Automation, Backend APIs, Data Science & AI)

Python Development Crash Guide 2026 — Part 5: Python in Real-World Engineering This is where Python stops being a language you learn and becomes a tool you use to solve real problems. Parts 1–4 gave you the fundamentals. Part 5 is about how those fundamentals translate into actual engineering work — the kind that companies pay for. I work primarily with Java and Spring Boot in production, but I reach for Python constantly — for automation scripts, data processing, quick API prototypes, and infrastructure tooling. This dual perspective gives me a clear view of where Python genuinely excels and where you might be better off with something else. Automation — Where Python Delivers Value Fastest If you're looking for the quickest path from "I know Python" to "I'm useful at work," automation is it. I've written Python scripts that replaced hours of manual work — and you don't need to be a senior developer to do this. A 40-line script that saves...

Python Development Crash Guide 2026 — Part 4 (Modules, Packages, Virtual Environments & Professional Project Structure)

🐍 Python Development Crash Guide 2026 — Part 4: Modules, Packages, Virtual Environments & Professional Project Structure This is the part where Python stops being “just code” and becomes real software engineering . Many developers know Python syntax but still: Break their environments Ship unmaintainable code Struggle with imports Fail deployments Get rejected in interviews Part-4 fixes that permanently. 📌 What This Part Covers In this post, you will learn: How Python modules and packages actually work How Python resolves imports internally Absolute vs relative imports (and when to use which) Virtual environments and dependency isolation Dependency management best practices (pip, requirements.txt) Modern tools (Poetry, pipx) Industry-standard Python project structures Configuration management using environment variables Packaging Python applications correctly This knowledge is mandatory for: Backend development Automation projects Data science pipelines Deployments Team collabor...

Python Development Crash Guide 2026 — Part 3: Advanced Python: OOP, Decorators, Generators & Memory Model

🐍 Python Crash Guide 2026 — Part 3: Advanced Python: OOP, Decorators, Generators & Memory Model This is the part where Python stops feeling “easy” and starts feeling powerful . Most people can write Python scripts. Very few understand how Python really works under the hood . This post focuses on the concepts that: Differentiate amateurs from professionals Are heavily used in real-world frameworks Appear frequently in interviews Matter in backend systems, automation tools, and libraries 📌 What This Part Covers In this post, you will learn: Advanced Object-Oriented Programming in Python Inheritance patterns, MRO, composition vs inheritance Dataclasses and modern class design Decorators (how they actually work) Closures and function factories Iterators and generators (lazy execution) Python’s memory model and garbage collection Mutability, references, and copy semantics This knowledge is non-negotiable for: Backend development (FastAPI, Django) Writing reusable libraries Debugging ...

Python Development Crash Guide 2026 — Part 2: Core Python: Syntax, Control Flow, Functions & Data Structures

Python Development Crash Guide 2026 — Part 2: Core Python: Syntax, Control Flow, Functions & Data Structures If Part 1 was about understanding what Python is, Part 2 is where you start thinking in Python. This is the part that separates people who've watched Python tutorials from people who can actually write Python code on their own. I use everything in this post daily — whether I'm writing automation scripts, building FastAPI endpoints, or teaching Python in my YouTube tutorials . Control flow, functions, and data structures aren't "beginner topics" you outgrow — they're the foundation you build everything else on. Boolean Logic and Decision Making Before you write a single if statement, you need to understand how Python evaluates truth. This trips up even experienced developers from other languages. Python doesn't just check for True or False — it checks for truthiness . These values are all considered false: False , None , 0 , ...