Question

Describe how to implement a capacity-limited queue, which uses the functions of a capacity-limited deque to perform the functions of the queue ADT in ways that do not throw exceptions when we attempt to perform a enqueue on a full queue or a dequeue on an empty queue.

Short answer

Implement a capacity-limited queue using a deque with checks in enqueue and dequeue to handle capacity limits without throwing exceptions.

Step-by-step solution

Understand the Problem

A queue ADT (Abstract Data Type) is a linear data structure that follows the FIFO (First In First Out) principle. A deque (double-ended queue) allows insertion and deletion at both ends. We need to implement a queue using deque functions that can handle capacity limits without throwing exceptions.

Define the Class

Define a class for your capacity-limited queue. Include attributes for maximum capacity and a deque to store the queue elements.

Initialize the Constructor

In the constructor method (__init__), initialize the maximum capacity and deque.

Implement Enqueue Function

Define the enqueue method. Check if the deque's size is less than the maximum capacity: if it is, insert the element at the rear; if it isn't, remove the front element and then insert the new element at the rear.

Implement Dequeue Function

Define the dequeue method. Check if the deque is empty: if it is, return None; if it isn't, remove and return the front element of the deque.

Implement Size Check

Define a size method that returns the current number of elements in the deque to keep track of the queue's size.

Implement Is_Empty Check

Define an is_empty method that checks if the deque is empty and returns a boolean value.

Implement Is_Full Check

Define an is_full method that checks if the deque size is equal to the maximum capacity and returns a boolean value.

Key concepts

queue ADT

A Queue Abstract Data Type (ADT) is a fundamental data structure in computer science. It follows the First In, First Out (FIFO) principle, meaning the first element added is the first one to be removed. Queues are particularly useful for scenarios like task scheduling, breadth-first search in graphs, and managing data streams.
Core operations of a queue include:

• Enqueue: Adding an element to the rear (end) of the queue.
• Dequeue: Removing an element from the front of the queue.
• Peek/Front: Viewing the front element without removing it.
• Is_Empty: Checking if the queue has no elements.
• Size: Getting the number of elements in the queue.

In our specific problem, we need to implement a capacity-limited queue. This means it has a predefined maximum size, and it should avoid throwing exceptions when executing an enqueue operation on a full queue or a dequeue operation on an empty queue.
To achieve this, we utilize the deque (double-ended queue) data structure, enabling more flexibility in managing the queue's capacity without errors.

deque data structure

A Deque, or Double-Ended Queue, is an extension of the queue ADT. Unlike a standard queue, a deque allows insertion and deletion of elements at both ends (front and rear). This makes it a versatile data structure used in various complex algorithm implementations.
Key operations of a deque include:

• Add Front: Insert an element at the front of the deque.
• Add Rear: Insert an element at the rear of the deque.
• Remove Front: Remove an element from the front of the deque.
• Remove Rear: Remove an element from the rear of the deque.
• Peek Front: View the front element without removing it.
• Peek Rear: View the rear element without removing it.
• Is_Empty: Check if the deque has no elements.
• Size: Get the number of elements in the deque.

In our implementation, we'll leverage the features of a deque to create a capacity-limited queue with seamless enqueue-dequeue operations, handling capacity constraints without causing runtime errors.
We define methods for checking if the deque is full (is_full) and handle the enqueue operation by removing the front element when necessary before adding a new element at the rear.

capacity management

Capacity management is crucial when implementing data structures that need to handle a fixed maximum number of elements. For our capacity-limited queue, capacity management ensures that we don't exceed the allowed maximum size and handle operations gracefully, avoiding exceptions.
Key components of capacity management include:

• Initialization: Setting up a maximum capacity during the construction of the queue class.
• Enqueue Handling: Before adding a new element, checking if the current size is less than the maximum capacity. If the queue is full, we remove the front element to create space, thus maintaining the capacity without exception.
• Dequeue Handling: Checking if the queue is empty before removing an element to return None instead of causing an error.
• Size Tracking: Keeping track of the current number of elements in the queue to assist in checking full or empty states.

In our solution, methods like is_full and is_empty help manage the capacity effectively. This makes the queue operations smooth and reliable, even when the queue reaches its capacity limit or becomes empty.