Circular Buffer (Circular Queue)

Write a Python program to implement a Circular Buffer (also known as a Circular Queue). A circular buffer is a fixed-size buffer that works as if the memory is contiguous and circular in nature, allowing for efficient memory usage.

Algorithm for MyCircularBuffer class

1. Initialize a fixed-size array and front/rear pointers.
2. For enqueue operations, update the rear pointer and add elements.
3. For dequeue operations, update the front pointer and remove elements.
4. Implement methods to check if the buffer is empty or full.
5. Use modulo arithmetic to handle wraparound of indices.

Example 1

Input: ["MyCircularBuffer", "enqueue", "enqueue", "enqueue", "enqueue", "Rear", "isFull", "dequeue", "enqueue", "Rear"]
[[3], [1], [2], [3], [4], [], [], [], [4], []]
Output: [null, true, true, true, false, 3, true, true, true, 4]
Explanation: 

MyCircularBuffer myCircularBuffer = new MyCircularBuffer(3);
myCircularBuffer.enqueue(1); // return True
myCircularBuffer.enqueue(2); // return True
myCircularBuffer.enqueue(3); // return True
myCircularBuffer.enqueue(4); // return False, the buffer is full
myCircularBuffer.Rear();     // return 3
myCircularBuffer.isFull();   // return True
myCircularBuffer.dequeue();  // return True
myCircularBuffer.enqueue(4); // return True
myCircularBuffer.Rear();     // return 4

Example 2

Input: ["MyCircularBuffer", "enqueue", "dequeue", "Front", "Rear", "isEmpty", "isFull"]
[[5], [10], [], [], [], [], []]
Output: [null, true, true, -1, -1, true, false]
Explanation: 

MyCircularBuffer myCircularBuffer = new MyCircularBuffer(5);
myCircularBuffer.enqueue(10); // return True
myCircularBuffer.dequeue();   // return True
myCircularBuffer.Front();     // return -1, buffer is empty
myCircularBuffer.Rear();      // return -1, buffer is empty
myCircularBuffer.isEmpty();   // return True
myCircularBuffer.isFull();    // return False

Constraints

1 ≤ capacity ≤ 1000
0 ≤ value ≤ 10^4
At most 3000 calls will be made to enqueue, dequeue, Front, Rear, isEmpty, and isFull.
Time Complexity: O(1) for all operations
Space Complexity: O(n) where n is the capacity