What Is Stack Abstract Data Type in Python?


Angela Bailey

What Is Stack Abstract Data Type in Python?

A stack is an abstract data type (ADT) that follows the Last-In-First-Out (LIFO) principle. In simple terms, it means that the last element added to the stack will be the first one to be removed. Imagine a stack of plates – you can only add or remove plates from the top of the stack.

Stack Operations

A stack supports two main operations:

  • Push: Adds an element to the top of the stack.
  • Pop: Removes and returns the topmost element from the stack.

Additionally, we have two other auxiliary operations:

  • Peek: Returns the value of the topmost element without removing it from the stack.
  • isEmpty: Checks if the stack is empty or not.

Implementing a Stack in Python

In Python, we can implement a stack using lists or collections.deque. Let’s look at an example using lists:

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class Stack:
    def __init__(self):
        self.stack = []

    def push(self, item):

    def pop(self):
        if not self.is_empty():
            return self.pop()
            return None

    def peek(self):
        if not self.stack[-1]
            return None

    def is_empty(self):
        return len(self.stack) == 0

Stack Applications

Stacks have various applications in computer science. Here are a few common use cases:

  • Expression evaluation: Stacks are used to evaluate expressions, such as infix, prefix, and postfix.
  • Function call stack: Stacks are used to manage function calls and their local variables.
  • Undo/Redo operations: Stacks can be used to implement undo and redo functionality in applications.
  • Backtracking algorithms: Stacks are often used in backtracking algorithms like maze solving, N-Queens problem, etc.


A stack is a fundamental data structure that is widely used in programming. It follows the LIFO principle and supports push, pop, peek, and isEmpty operations.

Understanding stacks and their applications can greatly enhance your problem-solving skills. So go ahead and start using stacks to make your code more efficient!

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