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import heapq

# Create a minheap
minheap = []
heapq.heapify(minheap) 
# In Python, there is no maxheap. If maxheap is required, 
# try to multiply each element with -1 and then heapify it.
# In the operations, the value should be converted back.

# Add elements
heapq.heappush(minheap, 10)
heapq.heappush(minheap, 8)
heapq.heappush(minheap, 9)
heapq.heappush(minheap, 2)
heapq.heappush(minheap, 1)
heapq.heappush(minheap, 11) # [1,2,9,10,8,11]

# Peek
print(minheap[0])

# Delete
heapq.heappop(minheap)

# Size
len(minheap)

# Iteration
while len(minheap) != 0:
    print(heapq.heappop(minheap))
    

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// Create
PriorityQueue<Integer> minheap = new PriorityQueue<>();
PriorityQueue<Integer> maxheap = new PriorityQueue<>(Collections.reverseOrder());

// Add
minheap.add(2);
maxheap.add(3);

// Peek
int mi = minheap.peek();
int ma = maxheap.peek();  

// Remove the top element
int mi = minheap.poll();
int ma = maxheap.poll(); 

// Get the size of the heap
int lenMin = minheap.size();
int lenMax = maxheap.size();

// Iteration
while (!minheap.isEmpty()) {
    System.out.println(minheap.poll());
}