Object-Oriented Programming (OOP) is one of the most powerful paradigms in Python. It allows you to model real-world entities into code by creating objects that encapsulate both data (attributes) and behavior (methods). Python makes OOP intuitive and flexible, which is why it’s widely used in large-scale applications.

File & Directory Management, Automation, Copy/Move/Delete. Python’s built-in os and shutil modules make these tasks simple and powerful.

A list comprehension produces a list using a single expression, while a dict comprehension produces a dictionary with key-value pairs.

A decorator in Python is a function that allows us to modify or enhance the behavior of another function or class without changing its source code. It uses higher-order functions and closures. Decorators are widely used for logging, authentication, caching, and performance measurement.

A module is simply a Python file (.py) containing functions, variables, or classes that you can reuse in other files.

In real-world applications, errors will happen — a user might provide wrong input, a file might be missing, or an API might fail.

File handling allows your Python program to interact with files on your computer: reading data from files or writing data to them.

Data structures help you organize and store data efficiently so that operations like insertion, deletion, searching, and sorting become easier.

A function is a reusable block of code that performs a specific task. Instead of writing the same code multiple times, you can define a function once and call it anywhere in your code.

Control flow refers to the order in which your code is executed. By default, Python runs code line by line from top to bottom.

A string is a sequence of characters enclosed in single, double, or triple quotes.

Operators are symbols or keywords that perform operations on variables and values. Python supports a wide range of operator types.