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Got another quick question : It seems that running a method in a ThreadPool makes it loose access to the current context and specifically the Prefect logger. Is there any easy workaround this ?

Here's a way to reproduce :
```from prefect import task, Flow
import prefect
import random

from multiprocessing.dummy import Pool as ThreadPool

@task
def random_number():
    return random.randint(0, 100)

def plus_one_f(x):
    prefect.context.get("logger").info(f"Plus One F : {x}")
    return x+1

@task
def plus_one(x):
    a = plus_one_f(x)
    with ThreadPool(8) as pool:
        results = pool.map(plus_one_f, [x])

with Flow('My Functional Flow') as flow:
    r = random_number()
    y = plus_one(x=r)

flow.run()```

Maybe you can use the LocalDaskExecutor instead which spins up a multiprocessing pool? Otherwise the only workaround I have seen is directly passing the prefect logger to that function

Thanks for the tip, i'll try this out ! Figured I could pass the logger as a parameter but it felt quite unclean :confused:

<@U02H6M1C5SQ> yeah unfortunately `prefect.context` needs to be threadsafe, so any threads you spawn yourself will need custom logic to pass the context.

As Kevin mentioned, Prefect's executors have logic to ensure context is passed around correctly to threads/processes