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.

Link Against the GSL Libraries When we compile code with GSL, we need to tell the linker to include the GSL libraries. For ex...

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

the c++ casting operators the four c++ casting operators are static_cast dynamic_cast reinterpret_cast const_cast use stati...

move constructor and move assignment operator Take a look at the addition operator + as implemented in demolist12_4. Notice t...

binary operators operators that function on two operands are called binary operators. syntax : 1return_type operator_type (pa...

on a board level, operators in c++ can be classified into two type: unary operators and binary operators. unary operators ope...