@Marvin I have my flows served with the .serve() method my flow Is defined @flow () Def my_flow(input) Return outputmodel(input.x +input.y) My_flow.serve() How can I invoke the deployed flow and retrieve the resulting data?

To invoke a deployed flow with Prefect, you would typically run the deployment, which creates a flow run. This is done automatically for deployments with schedules. An agent then picks up the flow run from a work queue and uses an infrastructure to execute it. To retrieve a flow from remote storage, you can use the

flow.from_source

method. This method accepts a git repository URL and an entrypoint pointing to the flow to load from the repository. Here is an example:

from prefect import flow 
my_flow = flow.from_source( 
    source="<https://github.com/org/repo.git>", 
    entrypoint="flows.py:my_flow" 
) 
my_flow()

In this example, a flow entrypoint is the path to the file the flow is located in and the name of the flow function separated by a colon. Please note that this information is based on Prefect version 2.14.2 and may vary with different versions. For the most accurate information, please refer to the Prefect documentation.

if you want the result back from your flow, you can either just run it locally (no serve just call the flow like a function) or with your above example you could use run_deployment(“my-flow/my-deploy”) to get a flow_run back, where if you have persist_result=True, flow_run.state.result() will contain the return value @Marvin find docs on run_deployment

I'm sorry, but I couldn't find specific documentation on

run_deployment

. It seems like it might be a method or function specific to your codebase or a third-party library. However, in Prefect, you typically use the

run

method to execute a flow and retrieve its result. If you have set

persist_result=True

, you can retrieve the result of the flow run with

flow_run.state.result()

. Here is an example:

flow_run = my_flow.run(parameters=dict(input=dict(x=1, y=2)))
result = flow_run.state.result

In this example,

my_flow

is your flow object, and

run

is a method that executes the flow and returns a

FlowRun

object.

FlowRun.state.result

contains the result of the flow run if

persist_result

was set to

True

. Please refer to the Prefect documentation for more details: Running Flows and Results and Persisting State.

🧐 weird

Run_deployment was exactly what I had thought. Persist_result seems like the correct way to address my problem, but when I added it to the flow parameters, it said it was a reserved name. Then I couldn’t figure out how to pass it as an argument to run_deployment as well.

sorry, it’s going to be a flow decorator kwarg / setting, like @flow(persist_result=True)

This will likely solve all my problems! Thank you!

👍

I'm sorry, but I couldn't find specific documentation on

run_deployment

in the Prefect documentation. The closest match was a command

prefect deployment run 'get-repo-info/my-first-deployment'

which is used to run a deployment from the command line. It's possible that

run_deployment

is a method specific to your codebase or a third-party library. I would recommend checking the documentation or source code of the library you're using, or asking for help in the relevant community or support channel. If you're referring to running a deployment in Prefect, you would typically use the Prefect UI, Prefect CLI, or Prefect API to create and manage flow runs. For example, to run a deployment from the command line, you can use the

prefect deployment run

command. Here is an example from the Prefect documentation:

bash
prefect deployment run 'get-repo-info/my-first-deployment'

In this example,

get-repo-info/my-first-deployment

is the name of the deployment to run. This command creates a new flow run, which is then picked up by an agent and executed. For more information, please refer to the Prefect documentation.

@Marvin can I delete persisted results after certain period of time?

In Prefect, the result of a task is persisted to a storage location in your infrastructure and Prefect stores a reference to the result. The Prefect API does not store your results except in special cases. If you're using Prefect Cloud, flow runs are retained according to the Flow Run Retention Policy setting in your personal account or organization profile. This policy represents the number of days each flow run is available in the Prefect Cloud UI, and via the Prefect CLI and API. However, the deletion of the actual persisted results (the data stored in your infrastructure) would depend on the specifics of your storage system. You would need to configure your storage system to automatically delete or archive data after a certain period of time. For more information, please refer to the Prefect documentation.