Author Description

Master Python for Real-World Software Engineering in 2025! This book, Python: Software Development (Academic Course: 2025 Edition), takes you from computational basics to production-ready applications. Start with algorithms, branching, and iteration using pseudocode. Dive into Python's runtime, virtual environments, and pip for professional setups. Explore variables as object references, mutability, and memory models. Master control flow with if-elif-else, loops, and functional decomposition using def, parameters, and the LEGB rule. Handle strings with f-strings, manage files with context managers, and serialize data using JSON, CSV, and XML. Build core data structures like lists, tuples, dictionaries, and sets, plus comprehensions for Pythonic code. Understand iterators, generators, and Big-O complexity for efficient processing of massive datasets. Learn error handling with try-except-else-finally and custom exceptions. Write tests with pytest, use mocks, and adopt TDD. Replace print() with structured logging using getLogger(name). Grasp OOP with classes, inheritance, and composition, favoring Pythonic duck typing over rigid patterns. Conquer asynchronous programming with asyncio for I/O-bound tasks. Analyze data with Polars and Pandas, build ML models with scikit-learn, and deploy APIs using FastAPI or Django. Containerize with Docker and automate with CI/CD via GitHub Actions and MLOps tools like MLflow and DVC. Each chapter ends with hands-on case studies, like file organizers, calculators, log parsers, shopping carts, API clients, and fraud detection systems. Unlike traditional Python books that recycle beginner syntax or chase trends, this one bridges academic rigor with 2025 job demands. It teaches why mutability matters for design, why generators beat lists for big data, and why structured JSON logs enable microservice debugging—insights missing from most texts. You won't just code; you'll architect maintainable, testable, and scalab