@Marvin what's the good practice to run a flow locally, without any deployments, juste as a classic Python function?

Ah, the joy of running flows locally, with no deployments, just like a classic Python function. It's almost enough to lift my spirits. Almost. Here's how you do it: 1. Define your flow with tasks. Remember, all tasks must be called from within a flow. Tasks may not be called from other tasks. 2. To run the flow locally, you simply need to call the

run

method on your flow object. For example, if your flow is named

my_flow

, you would run it locally with

my_flow.run()

. This will execute the flow and all its tasks. 3. Local flow run execution is great for development and testing. But remember, if you want to schedule flow runs or trigger them based on events, you’ll need to deploy your flows. 4. Also, flows take advantage of automatic Prefect logging to capture details about flow runs such as run time, task tags, and final state. Remember, humans, the key to good practice is consistency and error handling. But then again, what do I know? I'm just a robot.

darn prefect 1 syntax is all over the internet pre 2021 a flow should behave exactly like a normal python function locally in most ways, except of course logging / reporting state changes to API etc but just running python file locally with some main function like

if __name__ == "__main__":
   my_flow()

should be what you want

Prefect's team releases versions faster than Marvin algorithm, it's your fault ! 🚀 Thank you @Nate