import heapq
import itertools

# A unique sequence count for tie-breaking, ensuring consistent ordering for same-priority items
# and that items added earlier with same priority are retrieved earlier.
count = itertools.count()

# Our priority queue
pq = []

# Function to add a task
def add_task(priority, task):
    'Add a new task or update the priority of an existing task'
    entry = [priority, next(count), task] # priority, entry_id, task
    heapq.heappush(pq, entry)

# Function to get the next task
def get_next_task():
    'Remove and return the lowest priority task'
    if pq:
        priority, id, task = heapq.heappop(pq)
        return task
    return None

# Example Usage
add_task(5, 'Low priority background job')
add_task(1, 'High priority user request')
add_task(3, 'Medium priority cache update')
add_task(1, 'Another high priority user request') # Same priority, different entry_id

print(f"Next task: {get_next_task()}") # Should be 'High priority user request'
print(f"Next task: {get_next_task()}") # Should be 'Another high priority user request'
print(f"Next task: {get_next_task()}") # Should be 'Medium priority cache update'
print(f"Next task: {get_next_task()}") # Should be 'Low priority background job'
print(f"Next task: {get_next_task()}") # Should be None (queue is empty)