interactive-python-series

Python’s standard library is vast, providing ready-made tools for math, random numbers, and system interactions. Learn how to import and utilize modules like math, datetime, and os to avoid reinventing the wheel.

Why write code from scratch when you can extend functionality that already exists? We’ll explore inheritance to create specialized child classes that retain the features of their parent classes.

Not all methods act on individual objects; some belong to the class as a whole. Distinguish between instance methods that modify specific data and class methods that manage shared state.

Every object needs a setup phase when it is first created to establish its initial state. We will explain the __init__ method and the role of self in defining object attributes.

Object-Oriented Programming (OOP) helps organize code by modeling real-world entities. We’ll break down the concept of Classes as blueprints and Objects as the specific houses built from those blueprints.

Modern applications exchange data using JSON, and Python’s built-in library handles this format seamlessly. Learn to serialize Python objects into JSON strings and deserialize them back for easy data storage and transfer.

Leaving files open can lead to memory leaks and corruption, but context managers automate the cleanup process. We’ll show why with open(...) is the gold standard for safe and professional file handling.

Data persistence requires saving information to the disk so it survives after the program closes. We will cover how to read from and write to text files to create logs or save user progress.

Errors are inevitable, but crashing your program doesn't have to be. Learn how to use try, except, and finally blocks to handle unexpected issues gracefully without stopping execution.

Python comes batteries-included with powerful helpers that save you from writing standard logic from scratch. We’ll explore zip(), enumerate(), map(), and filter() to level up your coding efficiency.