Hi everyone! I’m looking for guidance on the following scenario. Currently playing around with Prefect Cloud. I have my execution environment for this exercise setup to be an EC2 instance and I’m using file based storage via Github. What’s the best practice for running the

.py

file locally to test that it works as intended before pushing to GH without changing any code? From my understanding you shouldn’t have

flow.run()

in your file when using Prefect cloud, but that’s how I started off running things locally Simple hello world script for reference

import prefect

from prefect import task, Flow
from prefect.environments.storage import GitHub


@task
def hello_task():
    logger = prefect.context.get("logger")
    <http://logger.info|logger.info>("Hello world!")


hello_flow = Flow("gh_storage_flow", tasks=[hello_task])

hello_flow.storage = GitHub(
    repo="{redacted}",
    path="{redacted}",
    secrets=["{redacted}"]
)

# Basically, I want the functionality of the below line so I can run this locally via Pycharm and then push to GH, merge to main branch, register, etc, and schedule via the UI to execute in our dedicated execution environment, but when you aren't running this as a script my understanding is that you need to remove the following line
hello_flow.run()

Hi Michael and welcome! You should able to achieve this by putting the

.run

block within the following check:

if __name__ == "__main__":
    hello_flow.run()

this way, the run command will only run when you call

python my_file.py

but will not run when the file is loaded for use with Cloud

That was insanely quick, Chris! I greatly appreciate your help and I was 100% overthinking this one 😅

No worries, glad I could help!