@Marvin How do I specify upstream dependencies when using AsyncIO python tasks?

To specify upstream dependencies for AsyncIO tasks in Prefect, you can use the

wait_for

parameter explicitly. Prefect recognizes the upstream dependencies either automatically or manually. Here's a simple guide: 1. Automatic Dependencies: When a result from a task is used as the input for another task, Prefect automatically recognizes this dependency.

python
    from prefect import flow, task

    @flow
    async def async_flow():
        result = await upstream_task()
        await downstream_task(result)

    @task
    async def upstream_task():
        return "Hello, upstream!"

    @task
    async def downstream_task(data):
        print(data)

2. Manual Dependencies: You can manually specify the upstream dependencies using the

wait_for

parameter.

python
    from prefect import flow, task

    @flow
    async def async_flow():
        upstream_result = await upstream_task.submit()
        await downstream_task.submit(wait_for=[upstream_result])

    @task
    async def upstream_task():
        return "Hello again, upstream!"

    @task
    async def downstream_task():
        print("Hello again, downstream!")

For more detailed information, you can refer to the Prefect documentation on specifying upstream dependencies. If you encounter any issues while implementing this, here are some previously discussed GitHub issues that might be relevant: - Flow could not be retrieved from deployment with `s3fs==2023.3.0` - Timeout Error when mapping with the `DaskKubernetesEnvironment` Feel free to reach out if you have any other questions.