Fix ThreadPoolTaskRunner concurrency by copying max_workers on duplication

[desertaxle]

Fixes issue with ThreadPoolTaskRunner concurrency by copying max_workers on task runner duplication. Now the max_workers setting is respected, and users can increase the amount of concurrent execution if desired.

Example

Execute 100 tasks concurrently (this would execute in batches previously):

from prefect import task, flow
from prefect.task_runners import ThreadPoolTaskRunner


@task
def sleepy_task(i):
    import time

    print(f"Sleepy task {i}")
    time.sleep(10)
    return i


@flow(task_runner=ThreadPoolTaskRunner(max_workers=100))
def test_flow():
    return sleepy_task.map(range(100))


if __name__ == "__main__":
    test_flow()

Checklist

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