Reference¶
Defines tools for simplifying the use of asynchronous Python.
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class
fsc.async_tools.PeriodicTask(task_func, *, loop=None, delay=1.0, run_on_exit=True)[source]¶ Asynchronous context manager that periodically runs a given function.
Parameters: - loop (EventLoop) – The event loop on which the tasks are executed. Uses
asyncio.get_event_loop()if no event loop is specified. - task_func (Callable) – The function which is executed. It cannot take any arguments, and must not be a coroutine.
- delay (float) – The minimum time between running two calls to the function.
- run_on_exit (bool) – Determines if the function should be run again when exiting the context manager.
- loop (EventLoop) – The event loop on which the tasks are executed. Uses
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fsc.async_tools.wrap_to_coroutine(func)[source]¶ Wraps a function or coroutine into a coroutine.
Parameters: func (Callable) – The function or coroutine that should be wrapped.
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class
fsc.async_tools.BatchSubmitter(func, *, loop=None, timeout=0.1, sleep_time=0.0, wait_batch_size=None, max_batch_size=1000)[source]¶ Function wrapper that collects calls to a function of one parameter, and submits it in batches to a function which can take a list of parameters.
Parameters: - func (Callable) – Function or coroutine which is “listable”, i.e. given a list of input parameters it will return a list of results.
- loop (EventLoop) – The event loop on which the batch submitter runs. Uses
asyncio.get_event_loop()by default. - timeout (float) – Maximum time after which the batch submitter will submit all current tasks, even if the minimum batch size is not reached.
- sleep_time (float) – Time the batch submitter will sleep between checking if the minimum batch size has been reached.
- wait_batch_size (int) – Minimum batch size that will be submitted before the timeout has been
reached. Is set to the same value as
max_batch_sizeunless specified explicitly. - max_batch_size (int) – The maximum size of a batch that will be submitted.