<@ULVA73B9P> I'd like to deploy a flow using from_source, from another flow that must be async. Here...

Javier SG

10/31/2024, 12:24 PM

@Marvin I'd like to deploy a flow using from_source, from another flow that must be async. Here it is an example:

Copy code

from prefect import flow
import asyncio

@flow
async def f():
    flow.from_source(
        source=GitRepository(
        # ...
        ),
        entrypoint="...",
    ).deploy( 
        name="my-deployment",
        work_pool_name=...,
        image=...,
        build=False,
    )

if __name__ == "__main__":
    asyncio.run(f())

I get this error:

AttributeError: 'coroutine' object has no attribute 'deploy'

Do you have any suggested approaches? I am using Prefect v3.0

Marvin

10/31/2024, 12:25 PM

The error

AttributeError: 'coroutine' object has no attribute 'deploy'

suggests that when you're calling

deploy

, it's being called on a coroutine object, rather than a flow deployment object in Prefect. In Prefect 3.x, the

deploy

method should be invoked on a deployment object, not directly within an async function like this. From the documentation I found, it seems a common pattern to create deployments from flows is to use the

to_deployment

deploy

functions outside of an async context. Here's an alternative approach that might help resolve your issue: 1. Create the deployment outside the async function - Since deployment can be managed independently, consider creating your deployment when the app starts or within a separate script that doesn't require async execution. 2. Use Prefect's
deploy
function - The

deploy

function is typically used to create and manage multiple deployments, and can be more suitable in environments where asynchronous logic is required. Here's an example of how you might refactor your flow:

Copy code

python
from prefect import flow, deploy
import asyncio

@flow
def my_flow():
    return

async def deploy_flow():
    deployment = my_flow.to_deployment(
        name="my-deployment",
        work_pool_name="your-work-pool",
        image="your-image",
        build=False,
    )
    await asyncio.to_thread(deployment.deploy)

if __name__ == "__main__":
    asyncio.run(deploy_flow())

Ensure that the work pool name and image name are correctly specified for your use case. Also, note that

asyncio.to_thread

is used here to call potentially blocking code within an async function without blocking the event loop. For more information, you can visit the Prefect 3.x documentation on flow deployment patterns. If this doesn't resolve your error, consider checking the flow creation and deployment patterns section of the Prefect 3.x documentation for further guidance.

Javier SG

10/31/2024, 12:30 PM

@Marvin Can you suggest a similar answer, but using from_source?

Marvin

10/31/2024, 12:35 PM

In Prefect 3.x, you cannot directly deploy a flow using

from_source

within an asynchronous function, primarily because the

deploy

method is not designed to work with async coroutines directly. However, you can work around this by managing deployment in a non-async context. While the documentation directly doesn't provide

from_source

with async execution, here's a structured approach based on what Prefect 3.x supports and a traditional pattern for deployment: 1. Define your flow using
from_source
outside the async context. 2. Initiate the deployment process, ensuring it is outside of any coroutine. Here's an adapted example using `from_source`:

Copy code

python
from prefect import flow
from prefect.deployments import DeploymentSpec
from prefect.filesystems import GitHub

# Define a flow
@flow
def my_flow():
    return

# Deployment spec using from_source
def create_deployment():
    repo = GitHub(repository="your-repo/your-repo-name")
    
    deployment = DeploymentSpec(
        flow_location="path_to_flow_script.py",
        name="my-deployment",
        storage=repo,
        infrastructure = "your-infrastructure",
        entrypoint="your_entry_point.py:flow_name"  # Entry point to your flow
    )
    deployment.deploy()  # Deploy the flow

    return deployment

async def async_work():
    # Do your async task here
    pass

if __name__ == "__main__":
    create_deployment()  # Ensure deployment is initiated outside async context
    asyncio.run(async_work())

### Key Points: - Separation of Concerns: Keep deployment setup and async work separate to avoid coroutine-related errors. - Infrastructure Specification: Make sure your infrastructure (e.g., work pool) aligns with what's needed for your project setup. More detailed information can be found on managing deployments with

from_source

in the Prefect 3.x infrastructure documentation. This approach should help you structure your code to remain within the preferred use patterns of Prefect 3.x. If specific adjustments are needed to fit your architecture, consider consulting with the official Prefect support or their community forums for more tailored advice.

7 Views

Open in Slack

Previous Next

Prefect Community

Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.