Sophia Wisdom added the comment:
While not calling executor.shutdown() may leave some resources still used, it
should be small and fixed. Regularly calling executor.shutdown() and then
instantiating a new ThreadPoolExecutor in order to run an asyncio program does
not seem like a good API to
Sophia Wisdom added the comment:
It looks like it's not specific to the ThreadPoolExecutor.
```
import asyncio
import concurrent
def leaker_func():
list(range(int(1000)))
# removed 1/0 because this causes issues with the ProcessPoolExecutor
async def function():
New submission from Sophia Wisdom :
The below example leaks ~20 megabytes of memory. The amount leaked is related
to both the number of items in the list and the number of times
`run_in_executor` is called.
```
import asyncio
def leaker():
x = list(range(int(1000)))
1/0
async def
