Python variables do not store raw values directly but instead hold references to objects on the heap. This note builds a practical mental model for how references work, how they compare to C++ pointers, and how this affects assignment, mutation, function parameters, copying, and common pitfalls. We include small typed examples and a focused discussion of shallow copies such as a.copy() vs m1.copy() in both flat and nested list cases.

A decorator is just a callable that takes a function and returns a new one, often a wrapper, letting us extend behavior while keeping functions clean and following the Open–Closed Principle.

Several examples are presented to clarify the definition and application of type annotations in Python.

Given an array of integers nums and an integer target, return indices of the two numbers such that they add up to target.

Lambda function Lambda functions in Python are small, anonymous functions defined with the lambda keyword rather than with th...