@Marvin Can Prefect auto detect and run flow deployment in python files?

Prefect 3.x does support deploying flows from Python files, but it doesn't automatically detect and run them. Instead, you need to explicitly define and deploy flows using Prefect's API. Here's a concise overview of how this works: 1. Define Your Flow: Write your flow in a Python file. For example:

python
   from prefect import flow

   @flow
   def my_flow():
       print("Hello, Prefect!")

2. Deploy Your Flow: Use

flow.deploy()

to specify how the flow should be deployed. This involves setting up deployment configurations, such as the work pool and Docker image details. Here's a basic example:

python
   from prefect import flow

   @flow
   def my_flow():
       print("Hello, Prefect!")

   if __name__ == "__main__":
       my_flow.deploy(name="my-flow-deployment", work_pool_name="default")

3. Run Your Script: Execute the script to deploy the flow. This will build a Docker image containing your flow code and create a deployment associated with the specified work pool. 4. Execution: You can then start a worker to execute scheduled runs, pulling the flow code from your Python file. For more information, you can refer to the Prefect documentation on deploying via Python. Additionally, Prefect's top-level API includes functions like

flow.deploy

and

flow.serve

that facilitate these operations. If you're interested in exploring more about the API, you can visit the Prefect API documentation.

@Marvin Where does prefect server store operational data?

Prefect Server stores its operational data in a database that tracks various states and configurations related to your flow runs. Here's a brief overview: - Default Database: Prefect uses a local SQLite database by default, which is suitable for lightweight, single-server deployments. This database is typically located at

~/.prefect/prefect.db

. - Data Tracked: The database stores data related to flow run and task run states, run history, logs, deployments, concurrency limits, storage blocks for flow and task results, variables, artifacts, and work pool status. - PostgreSQL Option: For more robust, external database needs, Prefect supports PostgreSQL. Setting up PostgreSQL requires additional configuration, such as using Docker, and the

pg_trgm

extension must be installed and enabled. For more detailed information, you can refer to the Prefect self-host documentation.