Stacks

A stack data structure is a so-called LIFO (Last In, First Out) data structure. It means that the last item inserted in the stack will be the first item removed. And, of course, it is very important that we can access only the last element in a data structure exclusively when dealing with the stack.

Stack implementation


              1234567891011121314151617181920212223242526272829303132333435363738
            
import numpy as np

class Stack:
    def __init__(self):
        self.stack = np.array([])  # Initialize an empty NumPy array

    def push(self, item):
        self.stack = np.append(self.stack, item)  # Append the item to the end of the array

    def pop(self):
        if self.is_empty():
            print("Stack is empty.")  # Handle empty stack case gracefully
            return None  # Return None if the stack is empty

        return_value = self.stack[-1]  # Store the value to return
        self.stack = np.delete(self.stack, -1)  # Remove the last item from the array
        return return_value  # Return the removed item

    def is_empty(self):
        return self.stack.size == 0  # Check if the stack is empty


# Example usage:
stack = Stack()

stack.push(1)
stack.push(2)
stack.push(3)

print("Stack:", stack.stack)

print("Pop:", stack.pop())
print("Stack after pop:", stack.stack)

# Attempt to pop from an empty stack
stack.pop()
stack.pop()
print("Pop from empty stack:", stack.pop())  # Should print 'Stack is empty.'

It is important to remember that a stack is an abstract data type. It means that it only defines behavior but not a concrete implementation. The stack abstract data type can be implemented either with the help of the array or linked list data structure.

Usually, in concrete implementations of the stack, two basic methods are used:

push() - inserts an item into a stack;
pop() - removes the last inserted item from a stack.

Basic operations time complexity

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 3. Розділ 1