# import heapq
# import asyncio

# # Priority mapping for user types
# PRIORITY_MAP = {
#     "paid": 1,
#     "logged_in": 2,
#     "not_logged_in": 3,
# }

# # Task class to manage requests
# class Task:
#     def __init__(self, user, user_status, topic, category, tag):
#         self.user = user
#         self.priority = PRIORITY_MAP[user_status]
#         self.user_status = user_status
#         self.topic = topic
#         self.category = category
#         self.tag = tag

#     def __lt__(self, other):
#         return self.priority < other.priority

#     def __repr__(self):
#         return f"Task(user={self.user}, priority={self.priority}, tag={self.tag}, topic={self.topic})"

# # Queues for scraping and analysis
# scraping_queue = []
# analysis_queue = []

# # Dictionary to cache scraping results
# scraping_results = {}

# # Function to simulate scraping
# async def perform_scraping(task):
#     print(f"Scraping data for {task}...")
#     await asyncio.sleep(3)  # Simulate scraping delay
#     filename = f"{task.topic}_scraped_data.json"
#     scraping_results[task.topic] = filename  # Cache the result
#     print(f"Scraping complete for {task}. Saved as {filename}.")
#     return filename

# # Function to simulate analysis
# async def perform_analysis(task, filename):
#     print(f"Analyzing {task} with data from {filename}...")
#     await asyncio.sleep(5)  # Simulate analysis delay
#     print(f"Analysis complete for {task}.")

# # Background worker for scraping
# async def scraping_worker():
#     while True:
#         if scraping_queue:
#             task = heapq.heappop(scraping_queue)
#             if task.topic not in scraping_results:  # Perform scraping only if not already done
#                 filename = await perform_scraping(task)
#                 heapq.heappush(analysis_queue, (task, filename))
#             else:
#                 filename = scraping_results[task.topic]
#                 heapq.heappush(analysis_queue, (task, filename))
#         else:
#             await asyncio.sleep(1)

# # Background worker for analysis
# async def analysis_worker():
#     while True:
#         if analysis_queue:
#             task, filename = heapq.heappop(analysis_queue)
#             await perform_analysis(task, filename)
#         else:
#             await asyncio.sleep(1)

# # Function to add a task to the scraping queue
# async def add_task(user, user_status, topic, category, tags):
#     for tag in tags:
#         task = Task(user, user_status, topic, category, tag)
#         heapq.heappush(scraping_queue, task)
#         print(f"Task added to scraping queue: {task}")

# # Main function for testing
# async def initPriorityQueue():
#     # Start workers
#     asyncio.create_task(scraping_worker())
#     asyncio.create_task(analysis_worker())

#     # # Add tasks
#     # await add_task("User1", "not_logged_in", "AI in education", "tools", ["pain_point"])
#     # await asyncio.sleep(1)  # Simulate delay
#     # await add_task("User2", "paid", "E-commerce trends", "Amazon", ["competitor"])
#     # await asyncio.sleep(1)  # Simulate delay
#     # await add_task("User3", "logged_in", "Healthcare AI", "devices", ["pain_point", "competitor"])

#     # # Keep the program running
#     # while True:
#     #     await asyncio.sleep(1)