Soham
09/12/2024, 12:47 AMMarvin
09/12/2024, 12:47 AMSoham
09/12/2024, 12:47 AMSoham
09/12/2024, 12:48 AMMarvin
09/12/2024, 12:48 AMflow.to_deployment
alone actually does create the deployment object without registering it with the API. If you don't call serve(...)
, the deployment won't be actively scheduled.
Here's an example:
python
import time
from prefect import flow, serve
@flow
def slow_flow(sleep: int = 60):
"Sleepy flow - sleeps the provided amount of time (in seconds)."
time.sleep(sleep)
@flow
def fast_flow():
"Fastest flow this side of the Mississippi."
return
if __name__ == "__main__":
slow_deploy = slow_flow.to_deployment(name="sleeper", interval=45)
fast_deploy = fast_flow.to_deployment(name="fast")
# Serve is not called here, so deployments are created but not scheduled
# serve(slow_deploy, fast_deploy)
By omitting the serve(...)
call, you basically create deployments without serving them. For more detailed information, you can check the source documentation.Soham
09/12/2024, 12:53 AMMarvin
09/12/2024, 12:53 AMto_deployment()
method and the Prefect CLI.
1. Use to_deployment()
Method:
Create the deployment object using the to_deployment()
method.
2. Register with the API Manually:
Instead of serving it, use the Prefect CLI to register the deployment with the Prefect API.
Here's a sample approach:
1. Define your flow and create the deployment object:
python
from prefect import flow
@flow
def my_flow():
print("Hello from my flow!")
deployment = my_flow.to_deployment(name="my-deployment")
2. Manually register the deployment using the Prefect CLI:
After creating the deployment object, you can use the Prefect CLI to register it with the Prefect API. Save the deployment as a YAML file and then register it.
bash
prefect deployment build -n my-deployment -p my_flow:deployment
prefect deployment apply my_flow-my-deployment.yaml
This way, you register the deployment with the Prefect API but do not start a long-running serve
process.
You can always refer to the official Prefect documentation for more details on running flows in local processes and deploying them.
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