How can I dynamically trace and visualize memory allocation patterns of nested Python coroutines in real-time?

I'm trying to understand how memory is used in my async Python application. I have multiple coroutines running, and I want to see how much memory each one is using, especially when they are nested or calling each other.

I tried using tracemalloc and asyncio libraries, but I am not sure about correctness.

import asyncio
import tracemalloc

tracemalloc.start()

async def task1():
    print("Task 1 started")
    await asyncio.sleep(1)
    print("Task 1 memory:", tracemalloc.get_traced_memory())



async def task2():
    print("Task 2 started")
    await asyncio.sleep(1)
    print("Task 2 memory:", tracemalloc.get_traced_memory())

async def main():
    await asyncio.gather(task1(), task2())

asyncio.run(main())

This prints some memory numbers, but I don’t know if it is showing memory just for that coroutine or for the whole program. Also, I want to track memory usage over time, not just once at the end.

I need this detail because of strict guidelines about memory usage in my organization.

Is there a way to hook into coroutine lifecycle events or tag them somehow to track memory usage more accurately?