@Marvin when to use subflows and when to use tasks ?

In Prefect 3.x, the choice between using subflows and tasks depends on the level of abstraction and organization you need in your workflow: 1. Tasks: - Tasks are the building blocks of Prefect workflows. They represent a single logical step in your workflow. Prefect encourages "small tasks" to improve fault isolation and retry capabilities. If any line of code in a task fails, the entire task fails and must be retried from the beginning. Therefore, splitting your code into multiple dependent tasks can enhance reliability and make debugging easier. - Tasks are created by decorating standard Python functions with the

@task

decorator. They are executed in the main thread by default, which facilitates native Python debugging and profiling. - More on writing tasks: Prefect Tasks 2. Subflows: - Subflows are essentially flows nested within other flows. They are useful when you want to encapsulate a sequence of tasks that logically belong together and might be reused in different workflows. Subflows can help in organizing complex workflows by breaking them down into more manageable parts. - They allow for better modularity and reusability of code, as a subflow can be treated as a single unit within a larger flow. In summary, use tasks for individual steps in your workflow and subflows to encapsulate and organize a sequence of tasks that form a coherent sub-process. This approach will help you maintain a clear and modular workflow structure. For more details on Prefect's API, you can explore the top-level API here. If you have further questions or need more specific guidance, feel free to ask!

@Marvin why are Task Inputs of a task run empty ?

The issue of task inputs being empty in a task run can arise due to several reasons: 1. Parameter Resolution: The task inputs might not be properly resolved if there are issues in parameter mapping or if the parameters are not correctly passed to the task. Prefect resolves parameters by checking their types and ensuring they are expanded before execution. If parameters are not correctly mapped or passed, they may not appear as expected in the task inputs. 2. Dynamic Inputs: If the inputs are supposed to be dynamic and depend on other tasks or flow context, there might be a problem in how these dependencies are defined or resolved. Prefect uses functions like

collect_task_run_inputs_sync

to gather inputs, and any misconfiguration in dependencies might lead to empty inputs. 3. Task Context: The task might be lacking the necessary context or state information, such as

flow_run_id

or

task_run_id

. If the context is not correctly set up, the task might not be able to access its inputs. 4. Code Issues: There might be a bug or logical error in the code that handles task inputs. For instance, if the code responsible for joining extra task inputs is not functioning correctly, it might lead to empty task inputs. To troubleshoot this issue, ensure that: - Parameters are correctly defined and passed to the task. - Dependencies and dynamic inputs are correctly configured. - The task context is properly set up with necessary IDs and state information. If the problem persists, reviewing the specific task code or consulting Prefect's GitHub issues might provide more insights. Here are the relevant links for further investigation: - Prefect Tasks Code - Prefect Task Runners Code If you need more specific guidance, feel free to provide additional details or context!