A hearty welcome to our learners! Building on the foundation of our previous lesson on the importance of data structures, today we're venturing into the depths of a fundamental data structure in software engineering: the "Stack". Drawing parallels from the real world, a Stack operates just like a stack of plates. The last plate you put (push) on the stack will be the first one you take (pop) off. It's this simple principle that makes Stacks so powerful and widely used.
In this lesson, our learning objectives are to conceptualize Stacks, understand how to implement them, analyze their time and space complexity, and learn how to manipulate Stacks to solve algorithmic problems.
As today's lesson concludes, you will have gained the ability to implement a Stack in Python, understand its basic operations, and possess a robust knowledge of its applications in real-world scenarios.
Take a moment to visualize a real-life stack of plates. The logic behind Stacks in the realm of computer science mirrors this real-world stack closely. A Stack follows the principle of "Last In, First Out" (LIFO), meaning the most recent item you place on the Stack will be the first one to be removed. All elements in a Stack are added and removed from the top.
As a real-world comparison, consider the Stack to be a stack of books. You can only add (push) a book to the top of the stack, and similarly, to remove (pop) a book, you must do so from the top of the stack. Suppose you need to access a specific book in the middle of the stack. In that case, you must remove (pop) all the books placed above it first.
In computer science, a Stack is a dynamic data structure. It has the ability to grow and shrink as we add and remove elements, respectively. Stacks find use in various areas of software engineering, such as tracking the execution of computer programs, memory management, parsing expressions, and much more.
We can utilize Python's built-in datatype to implement a Stack. To build a Stack, we need to define the following three basic operations:
