Hi everyone, I have a question about running

async

tasks.

from prefect import task, Flow

@task
async def extract():
    return [1,2,3]

@task
async def transform(some_list):
    transformed = [x + 1 for x in some_list]
    return transformed

@task
async def load(transformed):
    print('load somewhere')
    
with Flow('async testing') as flow:
    extract_nums = extract()
    transformed = transform(extract_nums)
    load(transformed)

flow.run()

This creates a flow and all, but how do I actually run this flow asynchronously? Posted in #random

Hi @Adisun Wheelock! Async tasks can be run using the

DaskExecutor

. You can read a bit more about that here: https://docs.prefect.io/core/concepts/engine.html#executors

Thanks for the quick response! I just followed that tutorial, and it modifies my code slightly:

from prefect.engine.executors import LocalDaskExecutor
from prefect import task, Flow

@task
async def extract():
    return [1,2,3]

@task
async def transform(some_list):
    transformed = [x + 1 for x in some_list]
    return transformed

@task
async def load(transformed):
    print('load somewhere')
    
with Flow('async testing') as flow:
    extract_nums = extract()
    transformed = transform(extract_nums)
    load(transformed)

executor = LocalDaskExecutor(address="<tcp://10.0.0.166:8786>")
flow.run(executor=executor)

Is there a more in depth tutorial using the

LocalDaskExecutor

with python coroutines?

Great! We have an advanced tutorial on Dask deployment here: https://docs.prefect.io/core/advanced_tutorials/dask-cluster.html#the-dask-executor - it doesn't mention any coroutines in particular as far as I remember but it should get you started with Local Dask

Yeah I saw that one, was hoping for an example of building a DAG with async tasks using

LocalDaskExecutor

😕

Ah sorry, I misunderstood what you were looking for there. Can you help me understand your use case? In a linear DAG like your earlier example, the tasks need to be run sequentially whether they're asynchronous or not.

Linear is fine, i'm mostly just looking for if prefect supports pythons

async

syntax.

Thanks @Adisun Wheelock - Prefect doesn't directly support

async

functions (and neither does Dask). We could potentially create a new Executor to run things in a single event loop but that doesn't exist atm.

okay thanks! I think my

AsyncTask

wrapper will suffice for the time being.

Great! If you're feeling like it's not quite doing what you'd hoped, let us know!

Interesting problem. Is there an overhead of creating one event loop per task vs one event loop per executor? I see the use cases for async flows when the tasks perform exclusively IO operations (i.e.: downloading files, calling external services). But it can also be common to need to mix sync and async tasks (i.e.: doing some processing in one task and IO operations in a parallel one).

@Adisun Wheelock any chance you could share your

AsyncTask

? Even if it might be as simple as

get_event_loop(); ...run_until_complete()

. There are a few ways one could cut that problem and every variant helps.

yeah it's basically just that. Here it is:

import asyncio
from prefect import Task
class AsyncTask(Task):
    def __init__(self, fn, name: str = None, **kwargs):
        if not callable(fn):
            raise TypeError("fn must be callable.")

        # set the name from the fn
        if name is None:
            name = getattr(fn, "__name__", type(self).__name__)

        prefect.core.task._validate_run_signature(fn)  # type: ignore
        self.fn = fn
        self.result = None
        super().__init__(name=name, **kwargs)

    def run(self, **kwargs):
        task_event_loop = asyncio.get_event_loop()
        self.result = task_event_loop.run_until_complete(self.fn(**kwargs))
        return self.result

got ya, thx!

I didn't in the tests I ran. But they were very minimal. A better solution would be to omit

self.results

entirely and just

return task_event_loop.run_until_complete(self.fn(**kwargs))