@Marvin how can I create a flow run for a deployment directly form python in prefect 2.0?

To create a flow run for a deployment directly from Python in Prefect 2.0, you can use the

run_deployment

function available in the

prefect.deployments

module. Here's an example code snippet demonstrating how to use this function:

python
from prefect.deployments import run_deployment

def main():
    run_deployment(name="my_flow_name/my_deployment_id")

if __name__ == "__main__":
    main()

Replace

"my_flow_name/my_deployment_id"

with the name or ID of your deployment. This will trigger a run of the deployment when the Python code is executed. You can find more information about this in the Prefect documentation on Running a Deployed Flow from Within Python Code.

@Marvin and what If i want to specify parameters into the run deployments?

To specify parameters when running a deployment in Prefect 2.0, you can pass them as a dictionary to the

run_deployment

function. Here's an example of how you might specify parameters:

python
from prefect.deployments import run_deployment

def main():
    parameters = {'param1': 'value1', 'param2': 'value2'}
    run_deployment(name="my_flow_name/my_deployment_id", parameters=parameters)

if __name__ == "__main__":
    main()

In the code snippet above,

parameters

is a dictionary containing the parameter keys and values that you want to pass to the deployment run. You would replace

'param1'

and

'param2'

with the actual names of your deployment's parameters and

'value1'

and

'value2'

with the corresponding values you wish to set for the run. Unfortunately, the searches did not return relevant excerpts for this specific use case in the documentation, but the example provided should help in constructing the necessary function call to

run_deployment

with parameters in Prefect 2.0. If you need to review the parameters schema, refer to the Prefect documentation for details on defining them in your deployment manifest.

for i in max_num: envoy_name = f"{i}" params = { ... } run_deployment( name = envoy_deployment, as_subflow=False, parameters = params, timeout = 0 ) From the GUI I can see that only a flow run is created and not max_num!

It seems like you are attempting to create multiple flow runs within a loop, but are observing only one flow run being created. The code snippet you provided has an incomplete context, but from what you've shared, it looks like you're trying to dynamically generate a deployment name (

envoy_name

) and parameters for each iteration of the loop to create separate flow runs. Here's a slightly revised version of the loop you might be using:

python
from prefect.deployments import run_deployment

envoy_deployment = "your_deployment_name"  # Make sure this is the name of your actual deployment

for i in max_num:
    envoy_name = f"{i}"
    params = {
        # ... your parameters here
    }

    run_deployment(
        name=envoy_deployment,
        as_subflow=False,
        parameters=params,
        timeout=0
    )

Please ensure that: 1.

max_num

is a correctly defined list or range of numbers that you want to iterate over. 2. The

envoy_name

variable is actually being used somewhere within the loop where needed. 3. The

envoy_deployment

variable actually contains the correct name or reference to your deployment. 4. Each call to

run_deployment

has parameters (inside

params

dictionary) that are appropriate for the deployment you are running. If problems persist, it could be an issue related to the concurrent creation of flow runs, or a limitation of the backend system that's not able to process all the requests in a tight loop succession. You might consider inserting a small delay between iterations or use asynchronous execution to manage the run creations more effectively. Note: The usage of

timeout=0

is a bit unusual as this implies no timeout. Unless this is specifically what you want, you might consider removing it or setting an appropriate timeout value. Additionally, if you are still facing issues, you might want to verify that your code is running as expected by adding debug logs and ensuring that

max_num

represents the correct iterable you intend to loop over. If the issue still isn't resolved, you could check the Prefect community Slack channel or GitHub issues for similar problems or consider contacting Prefect support for detailed help.