parsl.executors.ThreadPoolExecutor
- class parsl.executors.ThreadPoolExecutor(label: str = 'threads', max_threads: int | None = 2, thread_name_prefix: str = '', storage_access: List[Staging] | None = None, working_dir: str | None = None)[source]
A thread-based executor.
- Parameters:
- __init__(label: str = 'threads', max_threads: int | None = 2, thread_name_prefix: str = '', storage_access: List[Staging] | None = None, working_dir: str | None = None)[source]
Methods
__init__
([label, max_threads, ...])Resource monitoring sometimes deadlocks when using threads, so this function returns false to disable it.
shutdown
([block])Shutdown the ThreadPool.
start
()Start the executor.
submit
(func, resource_specification, *args, ...)Submits work to the thread pool.
Attributes
hub_address
Address to the Hub for monitoring.
hub_zmq_port
Port to the Hub for monitoring.
label
radio_mode
run_dir
Path to the run directory.
run_id
UUID for the enclosing DFK.
submit_monitoring_radio
Local radio for sending monitoring messages
- monitor_resources()[source]
Resource monitoring sometimes deadlocks when using threads, so this function returns false to disable it.
- shutdown(block=True)[source]
Shutdown the ThreadPool. The underlying concurrent.futures thread pool implementation will not terminate tasks that are being executed, because it does not provide a mechanism to do that. With block set to false, this will return immediately and it will appear as if the DFK is shut down, but the python process will not be able to exit until the thread pool has emptied out by task completions. In either case, this can be a very long wait.
- Kwargs:
block (Bool): To block for confirmations or not
- start()[source]
Start the executor.
Any spin-up operations (for example: starting thread pools) should be performed here.
- submit(func, resource_specification, *args, **kwargs)[source]
Submits work to the thread pool.
This method is simply pass through and behaves like a submit call as described here Python docs: