# lets look at the idea of another data structure# a Stack like a stack of plates or books# LIFO (last in first out)
Stack
Implementation of an interpreter for a small language that does multiplication/addition/etc.
Design a MinStack data structure that supports a min() operation that returns the minimum value in the stack in O(1) time.
Write an algorithm to determine if all of the delimiters in an expression are matched and closed.
E.g. {ac[bb]}, [dklf(df(kl))d]{} and {[[[]]]} are matched. But {3234[fd and {df][d} are not.
Sort a stack in ascending order using an additional stack.
Stacks in Python
are a sequential data structure that act as the Last-in, First-out (LIFO) version of queues. The last element inserted in a stack is considered at the top of the stack and is the only accessible element. To access a middle element, you must first remove enough elements to make the desired element the top of the stack.
Many developers imagine stacks as a stack of dinner plates; you can add or remove plates to the top of the stack but must move the whole stack to place one at the bottom.
Adding elements is known as a push, and removing elements is known as a pop. You can implement stacks in Python using the built-in list structure. With list implementation, push operations use the append() method, and pop operations use pop().
Advantages:
Offers LIFO data management that’s impossible with arrays
Automatic scaling and object cleanup
Simple and reliable data storage system
Disadvantages:
Stack memory is limited
Too many objects on the stack leads to a stack overflow error
Applications:
Used for making highly reactive systems
Memory management systems use stacks to handle the most recent requests first
Helpful for questions like parenthesis matching
Common stacks interview questions in Python
Implement a queue using stacks
Evaluate a Postfix expression with a stack
Next greatest element using a stack
Stack in Python
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions.
A stack is a linear data structure that stores items in a Last-In/First-Out (LIFO) or First-In/Last-Out (FILO) manner. In stack, a new element is added at one end and an element is removed from that end only. The insert and delete operations are often called push and pop.
The functions associated with stack are:
empty() – Returns whether the stack is empty – Time Complexity: O(1)
size() – Returns the size of the stack – Time Complexity: O(1)
top() – Returns a reference to the topmost element of the stack – Time Complexity: O(1)
Implementation
There are various ways from which a stack can be implemented in Python. This article covers the implementation of a stack using data structures and modules from the Python library.
Stack in Python can be implemented using the following ways:
list
Collections.deque
queue.LifoQueue
Implementation using list:
Python’s built-in data structure list can be used as a stack. Instead of push(), append() is used to add elements to the top of the stack while pop() removes the element in LIFO order.
Unfortunately, the list has a few shortcomings. The biggest issue is that it can run into speed issues as it grows. The items in the list are stored next to each other in memory, if the stack grows bigger than the block of memory that currently holds it, then Python needs to do some memory allocations. This can lead to some append() calls taking much longer than other ones.
Python3
Output:
Initial stack ['a', 'b', 'c']
Elements popped from stack: c b a
Stack after elements are popped: []
Traceback (most recent call last): File "/home/2426bc32be6a59881fde0eec91247623.py", line 25, in print(stack.pop())
IndexError: pop from empty list
Implementation using collections.deque:
Python stack can be implemented using the deque class from the collections module. Deque is preferred over the list in the cases where we need quicker append and pop operations from both the ends of the container, as deque provides an O(1) time complexity for append and pop operations as compared to list which provides O(n) time complexity.
The same methods on deque as seen in the list are used, append() and pop().
Python3
Output:
Initial stack: deque(['a', 'b', 'c'])
Elements popped from stack: c b a
Stack after elements are popped: deque([])
Traceback (most recent call last): File "/home/97171a8f6fead6988ea96f86e4b01c32.py", line 29, in print(stack.pop())
IndexError: pop from an empty deque
Implementation using queue module
Queue module also has a LIFO Queue, which is basically a Stack. Data is inserted into Queue using the put() function and get() takes data out from the Queue.
There are various functions available in this module:
maxsize – Number of items allowed in the queue.
empty() – Return True if the queue is empty, False otherwise.
full() – Return True if there are maxsize items in the queue. If the queue was initialized with maxsize=0 (the default), then full() never returns True.
Python3
Output:
0 Full: True Size: 3
Elements popped from the stack c b a
Empty: True
Implementation using singly linked list:
The linked list has two methods addHead(item) and removeHead() that run in constant time. These two methods are suitable to implement a stack.
getSize()– Get the number of items in the stack.
isEmpty() – Return True if the stack is empty, False otherwise.
peek() – Return the top item in the stack. If the stack is empty, raise an exception.
Below is the implementation of the above approach:
# lets look at the idea of another data structure
# a Stack like a stack of plates or books
# LIFO (last in first out)
# we can push items on to the stack
# we can pop items off a stack
# and we can peek at the item at the top of the stack
# think of how you could utilise a linked list to form a stack
"""
A stack is a data structure whose primary purpose is to store and
return elements in Last In First Out order.
1. Implement the Stack class using an array as the underlying storage structure.
Make sure the Stack tests pass.
2. Re-implement the Stack class, this time using the linked list implementation
as the underlying storage structure.
Make sure the Stack tests pass.
3. What is the difference between using an array vs. a linked list when
implementing a Stack?
"""
# Implement a Stack using an array for the underlying storage
class StackA:
def __init__(self):
self.storage = []
def __len__(self):
return len(self.storage)
def push(self, value):
self.storage.append(value)
def pop(self):
if len(self.storage) == 0:
return None
return self.storage.pop()
def peek(self):
return self.storage[-1]
from linked_list import LinkedList
# Stack implementation using a Linked List
class StackL:
def __init__(self):
self.size = 0
self.storage = LinkedList()
def __len__(self):
return self.size
def push(self, value):
self.storage.add_to_head(value)
self.size += 1
def pop(self):
if self.size == 0:
return None
self.size -= 1
return self.storage.remove_head()
def peek(self):
return self.storage.head.get_value()
# LIFO: last in first out
# create the abstract data type
class Stack:
def __init__(self):
# initialize it to a one dimensional array or linked list
self.stack = []
"""
Stack methods (push, pop, peek, is_empty, stack_size)
"""
# function for adding item into the stack O(1)
def push(self, data):
self.stack.append(data)
# function for removing last item inserted O(1)
def pop(self):
# first check to make sure its not an empty stack
if self.stack_size() < 1:
return -1
# get the last item in the stack
data = self.stack[-1]
# remove it
del self.stack[-1]
# return the data
return data
# function to return the last item in the stack without removing it O(1)
def peek(self):
return self.stack[-1]
# function to check if the stack is empty O(1)
def is_empty(self):
return self.stack == []
# function to return the size of the stack O(1)
def stack_size(self):
return len(self.stack)
"""
Using the methods
"""
stack = Stack()
stack.push(1)
stack.push(2)
stack.push(3)
print(f'Size: {stack.stack_size()}')
print(f'Popped item: {stack.pop()}')
print(f'Size: {stack.stack_size()}')
print(f'Peeked item: {stack.peek()}')
print(f'Size: {stack.stack_size()}')
Create a min() function using a stack
push(a) – Inserts the element ‘a’ at the top of the stack – Time Complexity: O(1)
pop() – Deletes the topmost element of the stack – Time Complexity: O(1)
get() – Remove and return an item from the queue. If the queue is empty, wait until an item is available.
get_nowait() – Return an item if one is immediately available, else raise QueueEmpty.
put(item) – Put an item into the queue. If the queue is full, wait until a free slot is available before adding the item.
put_nowait(item) – Put an item into the queue without blocking.
qsize() – Return the number of items in the queue. If no free slot is immediately available, raise QueueFull.
Python3
push(value) – Push a value into the head of the stack.
pop() – Remove and return a value in the head of the stack. If the stack is empty, raise an exception.
# we can push items on to the stack
# we can pop items off a stack
# and we can peek at the item at the top of the stack
# think of how you could utilise a linked list to form a stack
"""
A stack is a data structure whose primary purpose is to store and
return elements in Last In First Out order.
1. Implement the Stack class using an array as the underlying storage structure.
Make sure the Stack tests pass.
2. Re-implement the Stack class, this time using the linked list implementation
as the underlying storage structure.
Make sure the Stack tests pass.
3. What is the difference between using an array vs. a linked list when
implementing a Stack?
"""
# Implement a Stack using an array for the underlying storage
stack = []
# append() function to push
# element in the stack
stack.append('a')
stack.append('b')
stack.append('c')
print('Initial stack')
print(stack)
# pop() function to pop
# element from stack in
# LIFO order
print('\nElements popped from stack:')
print(stack.pop())
print(stack.pop())
print(stack.pop())
print('\nStack after elements are popped:')
print(stack)
//creates a stack
let stack = function(){
//two variables of the stack
this.count = 0; //keeps track of the count of the stack
this.storage = {}; //empty object
//adding the value on to the end of the stack
this.push = function(value){
this.storage[this.count] = value;
this.count++;
}
//removes and returns the value at the end of the stack
this.pop = function(){
if(this.count === 0){
return undefined;
}
this.count--;
const result = this.storage[this.count];
//removes the top element and returns it
delete this.storage[this.count];
return result;
}
//to know the size of the stack
this.size = function(){
return this.count;
}
//peek() - returns the value top of the stack i.e which is at the end of the stack
this.peek = function(){
return this.storage[this.count-1];
}
}
let myStack = new stack();
myStack.push(1);
myStack.push(2);
console.log(myStack.peek());
console.log(myStack.pop());
console.log(myStack.peek());
# Python program to
# demonstrate stack implementation
# using list
stack = []
# append() function to push
# element in the stack
stack.append('a')
stack.append('b')
stack.append('c')
print('Initial stack')
print(stack)
# pop() function to pop
# element from stack in
# LIFO order
print('\nElements popped from stack:')
print(stack.pop())
print(stack.pop())
print(stack.pop())
print('\nStack after elements are popped:')
print(stack)
# uncommenting print(stack.pop())
# will cause an IndexError
# as the stack is now empty
# Python program to
# demonstrate stack implementation
# using collections.deque
from Collections import deque
stack = deque()
# append() function to push
# element in the stack
stack.append('a')
stack.append('b')
stack.append('c')
print('Initial stack:')
print(stack)
# pop() function to pop
# element from stack in
# LIFO order
print('\nElements popped from stack:')
print(stack.pop())
print(stack.pop())
print(stack.pop())
print('\nStack after elements are popped:')
print(stack)
# uncommenting print(stack.pop())
# will cause an IndexError
# as the stack is now empty
# Python program to
# demonstrate stack implementation
# using queue module
from queue import LifoQueue
# Initializing a stack
stack = LifoQueue(maxsize = 3)
# qsize() show the number of elements
# in the stack
print(stack.qsize())
# put() function to push
# element in the stack
stack.put('a')
stack.put('b')
stack.put('c')
print("Full: ", stack.full())
print("Size: ", stack.qsize())
# get() function to pop
# element from stack in
# LIFO order
print('\nElements popped from the stack')
print(stack.get())
print(stack.get())
print(stack.get())
print("\nEmpty: ", stack.empty())
# Python program to demonstrate
# stack implementation using a linked list.
# node class
class Node:
def __init__(self, value):
self.value = value
self.next = None
class Stack:
# Initializing a stack.
# Use a dummy node, which is
# easier for handling edge cases.
def __init__(self):
self.head = Node("head")
self.size = 0
# String representation of the stack
def __str__(self):
cur = self.head.next
out = ""
while cur:
out += str(cur.value) + "->"
cur = cur.next
return out[:-3]
# Get the current size of the stack
def getSize(self):
return self.size
# Check if the stack is empty
def isEmpty(self):
return self.size == 0
# Get the top item of the stack
def peek(self):
# Sanitary check to see if we
# are peeking an empty stack.
if self.isEmpty():
raise Exception("Peeking from an empty stack")
return self.head.next.value
# Push a value into the stack.
def push(self, value):
node = Node(value)
node.next = self.head.next
self.head.next = node
self.size += 1
# Remove a value from the stack and return.
def pop(self):
if self.isEmpty():
raise Exception("Popping from an empty stack")
remove = self.head.next
self.head.next = self.head.next.next
self.size -= 1
return remove.value
# Driver Code
if __name__ == "__main__":
stack = Stack()
for i in range(1, 11):
stack.push(i)
print(f"Stack: {stack}")
for _ in range(1, 6):
remove = stack.pop()
print(f"Pop: {remove}")
print(f"Stack: {stack}")
# Python program to
# demonstrate stack implementation
# using list
stack = []
# append() function to push
# element in the stack
stack.append('a')
stack.append('b')
stack.append('c')
print('Initial stack')
print(stack)
# pop() function to pop
# element from stack in
# LIFO order
print('\nElements popped from stack:')
print(stack.pop())
print(stack.pop())
print(stack.pop())
print('\nStack after elements are popped:')
print(stack)
# uncommenting print(stack.pop())
# will cause an IndexError
# as the stack is now empty
Unlike an array structure, which allows random access at all the positions, a stack limits the inserting and removing operation to only one side of the data sequence. A stack follows the last in, first out (LIFO) principle.
In Python, stack can be implemented using a list. To follow the LIFO principle, inserting and removing operations both occur at the tail of the list.Python implementation of a stack
Stack: Introduction
push in a stack is putting an item on top of the stack.
pop in a stack is taking out the top item in the stack.
Uses of Stacks
Stacks are used extensively in a lot of places.
Compilers and Parsers – Expression evaluation is done by stacks by postfix or prefix using stacks in compilers.
Activation Records – An activation record is data that keeps track of the procedure activities during the runtime of a program.
When the function is called, an activation record is created for it and keeps track of parameters and information like local variables, return address, static and dynamic links, and the return value.
This activation record is the fundamental part of programming languages and is implemented using a stack.
Web Browsers – Web Browsers use a stack to keep track of URLs that you have visited previously. When you visit a new page, it is added to the stack and when you hit the back button, the stack is popped and the previous URL is accessed.
Implementing Stacks
Stack Methods
There are various functions that are associated with a stack. They are,
stack.isEmpty()
The stack.isEmpty() method returns True if the stack is empty. Else, returns False
Time Complexity - O(1)
stack.length()
The stack.length() method returns the length of the stack.
Time Complexity - O(1)
stack.top()
The stack.top() method returns a pointer/reference to the top element in the stack.
Time Complexity - O(1)
stack.push(x)
The stack.push() method inserts the element, x to the top of the stack.
Time Complexity - O(1)
stack.pop()
The stack.pop() method removes the top element of the stack and returns it.
Time Complexity - O(1)
Stack Implementations
In Python, we can implement the stack by various methods. We are going to dive into two of the methods - the common method and the efficient method.
Stack using a List
We use the list methods append and pop to implement a Stack.
Stack using collection.Deque
Python collections are container classes that are used for data collection storage. They are highly optimized, are really fast, and have lots of methods built-in.
Deque is one such python collection that is used for inserting and removing items. We can use it to create a faster implementation of a stack.
Practice Stacks
Once you are done with understanding the stack and the basic implementation, practice the following problems and problem-sets in order to get a strong grasp on stacks.
Infix to Postfix -
Next Greater Element -
Postfix to Prefix -
Conclusion
We have learned the implementation, importance, and application of stacks. This is one of the most important data structures to know and it is extensively asked in the computer science industry. It is important to have strong knowledge on this topic as it would give you an edge.
push in a stack is putting an item on top of the stack.
pop in a stack is taking out the top item in the stack.
Uses of Stacks
Stacks are used extensively in a lot of places.
Compilers and Parsers – Expression evaluation is done by stacks by postfix or prefix using stacks in compilers.
Activation Records – An activation record is data that keeps track of the procedure activities during the runtime of a program.
When the function is called, an activation record is created for it and keeps track of parameters and information like local variables, return address, static and dynamic links, and the return value.
This activation record is the fundamental part of programming languages and is implemented using a stack.
Web Browsers – Web Browsers use a stack to keep track of URLs that you have visited previously. When you visit a new page, it is added to the stack and when you hit the back button, the stack is popped and the previous URL is accessed.
Implementing Stacks
Stack Methods
There are various functions that are associated with a stack. They are,
stack.isEmpty()
The stack.isEmpty() method returns True if the stack is empty. Else, returns False
Time Complexity - O(1)
stack.length()
The stack.length() method returns the length of the stack.
Time Complexity - O(1)
stack.top()
The stack.top() method returns a pointer/reference to the top element in the stack.
Time Complexity - O(1)
stack.push(x)
The stack.push() method inserts the element, x to the top of the stack.
Time Complexity - O(1)
stack.pop()
The stack.pop() method removes the top element of the stack and returns it.
Time Complexity - O(1)
Stack Implementations
In Python, we can implement the stack by various methods. We are going to dive into two of the methods - the common method and the efficient method.
Stack using a List
We use the list methods append and pop to implement a Stack.
Stack using collection.Deque
Python collections are container classes that are used for data collection storage. They are highly optimized, are really fast, and have lots of methods built-in.
Deque is one such python collection that is used for inserting and removing items. We can use it to create a faster implementation of a stack.
Practice Stacks
Once you are done with understanding the stack and the basic implementation, practice the following problems and problem-sets in order to get a strong grasp on stacks.
Infix to Postfix -
Next Greater Element -
Postfix to Prefix -
Conclusion
We have learned the implementation, importance, and application of stacks. This is one of the most important data structures to know and it is extensively asked in the computer science industry. It is important to have strong knowledge on this topic as it would give you an edge.
To implement other Data Structures – Stacks are used to implement searches in Graphs and Trees, which are other complex data structures.
Reverse a String using Stack -
Mini Parser -
Simplify Path -
More Stack Problems -
Stack Problem Set -
A great analogy we can use is stacking a pile of books. We always keep a new book on top and remove the topmost book. Stacks are similar to queues in that they are linear collections of items, but they differ in the order in which they are accessed. Stacks are used in a variety of areas from Operating System Software, in Compilers and Language Parsing, and to implement other complex Data Structures like Trees and Graphs.
To implement other Data Structures – Stacks are used to implement searches in Graphs and Trees, which are other complex data structures.
Reverse a String using Stack -
Mini Parser -
Simplify Path -
More Stack Problems -
Stack Problem Set -
A great analogy we can use is stacking a pile of books. We always keep a new book on top and remove the topmost book. Stacks are similar to queues in that they are linear collections of items, but they differ in the order in which they are accessed. Stacks are used in a variety of areas from Operating System Software, in Compilers and Language Parsing, and to implement other complex Data Structures like Trees and Graphs.
