Queue Data Structure
Queue Implementation

We can create a Queue class as a wrapper and use the Python list to store the queue data. This class will have the implementation of the enqueue , dequeue , size , front , back , and is_empty methods.

The first step is to create a class definition and how we are gone store our items.

class Queue:

def __init__(self):

self.items = []

This is basically what we need for now. Just a class and its constructor. When the instance is created, it will have the items list to store the queue items.

For the enqueue method, we just need to use the list append method to add new items. The new items will be placed in the last index of this items list. So the front item from the queue will always be the first item.

def enqueue(self, item):

self.items.append(item)

It receives the new item and appends it to the list.

The size method only counts the number of queue items by using the len function.

def size(self):

return len(self.items)

The idea of the is_empty method is to verify if the list has or not items in it. If it has, returns False . Otherwise, True . To count the number of items in the queue, we can simply use the size method already implemented.

def is_empty(self):

return self.size() == 0

The pop method from the list data structure can also be used to dequeue the item from the queue. It dequeues the first element as it is expected for the queue. The first added item.

def dequeue(self):

return self.items.pop(0)

But we need to handle the queue emptiness. For an empty list, the pop method raises an exception IndexError: poop from empty list . So we can create an exception class to handle this issue.

class Emptiness(Exception):

pass

And uses it when the list is empty:

def dequeue(self):

if self.is_empty():

raise Emptiness('The Queue is empty') return self.items.pop(0)

If it is empty, we raise this exception. Otherwise, we can dequeue the front item from the queue.

We use this same emptiness strategy for the front method:

def front(self):

if self.is_empty():

raise Emptiness('The Queue is empty') return self.items[0]

If it has at least one item, we get the front, the first added item in the queue.

Also the same emptiness strategy for the back method:

def back(self):

if self.is_empty():

raise Emptiness('The Queue is empty') return self.items[-1]

If it has at least one item, we get the back item, the last added item in the queue.

Queue usage

I created some helper functions to help test the queue usage.

def test_enqueue(queue, item):

queue.enqueue(item)

print(queue.items)

def test_dequeue(queue):

queue.dequeue()

print(queue.items)

def test_emptiness(queue):

is_empty = queue.is_empty()

print(is_empty)

def test_size(queue):

size = queue.size()

print(size)

def test_front(queue):

front = queue.front()

print(front)

def test_back(queue):

back = queue.back()

print(back)

They basically call a queue method and print the expected result from the method call.

The usage will be something like:

queue = Queue() test_emptiness(queue) # True

test_size(queue) # 0 test_enqueue(queue, 1) # [1]

test_enqueue(queue, 2) # [1, 2]

test_enqueue(queue, 3) # [1, 2, 3]

test_enqueue(queue, 4) # [1, 2, 3, 4]

test_enqueue(queue, 5) # [1, 2, 3, 4, 5] test_emptiness(queue) # False

test_size(queue) # 5

test_front(queue) # 1

test_back(queue) # 5 test_dequeue(queue) # [2, 3, 4, 5]

test_dequeue(queue) # [3, 4, 5]

test_dequeue(queue) # [4, 5]

test_dequeue(queue) # [5] test_emptiness(queue) # False

test_size(queue) # 1

test_front(queue) # 5

test_back(queue) # 5 test_dequeue(queue) # [] test_emptiness(queue) # True

test_size(queue) # 0

We first instantiate a new queue from the Queue class.
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['Python', 'Algorithms', 'Software Development', 'Software Engineering', 'Programming']