@Marvin I have a flow that executes a number of tasks. If a task fails I would like to stop executing the flow and any remaining tasks. What is the best way to achieve this in Prefect 2.x?

In Prefect 2.x, you can stop the execution of a flow if a task fails by using the

wait_for

parameter in task submissions. This parameter allows you to specify dependencies between tasks, ensuring that subsequent tasks only run if their dependencies succeed. Here's a conceptual example:

python
from prefect import flow, task

@task
def task_a():
    # Some logic that might fail
    pass

@task
def task_b():
    # Some logic
    pass

@flow
def example_flow():
    result_a = task_a.submit()
    # task_b will only run if task_a is successful
    result_b = task_b.submit(wait_for=[result_a])

if __name__ == "__main__":
    example_flow()

In this setup,

task_b

will only execute if

task_a

completes successfully. If

task_a

fails, the flow will stop executing further tasks that depend on it. This is a simple way to implement a "fail-fast" approach in your flow execution. For more details, you can refer to the Prefect 2.x documentation: Prefect 2.x Flows.

@Marvin If there is an exception raised in a task and caught I return

Failed(message)

. The next task doesn't seem to honour this even with

wait_for=task_state

being used. Any ideas why the next task still executes?

In Prefect 2.x, if you're returning a

Failed

state from a task and using the

wait_for

parameter, the subsequent task should indeed respect this state and not execute. Here are a few things to consider: 1. State Propagation: Ensure that the

Failed

state is being correctly propagated. The

wait_for

parameter should be given the result of the task that returns the

Failed

state. Double-check that the task's result is indeed a

Failed

state. 2. State Handling: Prefect has specific orchestration rules for state transitions. If a task transitions to a

Failed

state, subsequent tasks waiting on it should not proceed. Ensure that the state returned by your task is properly being set to

Failed

. 3. Review Common Gotchas: Prefect's state management can sometimes be tricky. Review the Prefect 2.x documentation on state types and transitions to ensure you're following the correct patterns for state handling. If these steps don't resolve the issue, it might be worth checking if there are any custom state handlers or configurations in your flow that could affect state transitions. For more details on state transitions and handling in Prefect, refer to the Prefect 2.x States Documentation.

@Marvin I have printed out the state and it has been set to

Failed(message)

. I noticed that the example used

wait_for=[result_a]

in

[ .. ]

brackets, does that make a difference?

Yes, using brackets in

wait_for=[result_a]

is important. The

wait_for

parameter expects a list of task futures, even if it's just a single task. This ensures that Prefect correctly interprets the dependencies and waits for all specified tasks to complete successfully before proceeding. Here's the correct way to use `wait_for`:

python
from prefect import flow, task, Failed

@task
def task_a():
    try:
        # Some logic that might fail
        raise Exception("An error occurred")
    except Exception as e:
        return Failed(str(e))

@task
def task_b():
    # Some logic
    pass

@flow
def example_flow():
    result_a = task_a.submit()
    # Use brackets to ensure it's a list
    result_b = task_b.submit(wait_for=[result_a])

if __name__ == "__main__":
    example_flow()

Ensure you use brackets to wrap the

result_a

in a list when passing it to

wait_for

. This should help Prefect correctly manage task dependencies and halt execution if a preceding task fails.

@Marvin how can I stop the next task from starting if result_a is False i.e. the previous task didn't finish successfully?

To ensure that the next task does not start if

result_a

is

False

, you can use conditional logic within your flow to check the result of

result_a

before submitting the next task. Here's how you can do it:

python
from prefect import flow, task, Failed

@task
def task_a():
    # Some logic that might fail
    success = False  # Simulate a failure
    if not success:
        return Failed("Task A failed")
    return success

@task
def task_b():
    # Some logic
    print("Task B executed")

@flow
def example_flow():
    result_a = task_a.submit().result()  # Get the result of task_a
    if not isinstance(result_a, Failed):  # Check if result_a is not a Failed state
        task_b.submit()  # Only submit task_b if task_a succeeded

if __name__ == "__main__":
    example_flow()

In this setup: -

task_a

returns a

Failed

state if it doesn't succeed. - In the flow,

result_a

is checked to ensure it's not a

Failed

state before proceeding to

task_b

. - This pattern allows you to conditionally execute tasks based on the success of previous tasks.

@Marvin can I return a state from a task method? For example Completed (if successful) or Failed (if unsuccessful)

Yes, in Prefect 2.x, you can return a state from a task method, such as

Completed

or

Failed

. Here's how you can do it:

python
from prefect import task
from prefect.states import Completed, Failed

@task
def my_task():
    try:
        # Task logic that might succeed
        result = "Task succeeded!"
        return Completed(result=result)
    except Exception as e:
        # Return a Failed state if an exception occurs
        return Failed(message=str(e))

In this example, the task returns a

Completed

state if it succeeds, with the result attached. If an exception occurs, it returns a

Failed

state with a message describing the failure. Returning explicit states like this allows you to control the flow's behavior based on the task's success or failure. For more information, you can refer to the Prefect 2.x States Documentation.

@Marvin accessing the State result returned for testing I am able to access the message and the type, is there a way to access the result?

To access the result of a

State

in Prefect 2.x, you can use the

State.result()

method. This method retrieves the result of a task that has completed successfully. Here's how you can do it:

python
from prefect import flow, task, Completed

@task
def my_task():
    # Return a successful result
    return Completed(result="Task succeeded!")

@flow
def example_flow():
    state = my_task(return_state=True)  # Get the state of the task
    result = state.result()  # Access the result from the state
    print(result)  # Output the result

if __name__ == "__main__":
    example_flow()

In this example,

state.result()

is used to access the result stored in the

Completed

state. If you're working in an asynchronous context, you might need to use

await state.result(fetch=True)

to fetch the result. For more detailed information, you can refer to the Prefect documentation on retrieving results from states.

Hi @Marvin can you please explain the difference between a Proactive and a Reactive Trigger and give me a use case for both?

In Prefect, triggers are mechanisms to automate responses based on certain conditions. Here's a brief explanation of Proactive and Reactive Triggers: 1. Proactive Triggers: - Definition: These triggers activate when a specified event does not occur within a defined time window. They are designed to respond to the absence of expected events. - Use Case: Consider a scenario where you expect a flow run to complete within a minute after it starts. A proactive trigger can be set up to notify you if a

prefect.flow-run.Completed

event is not detected within 60 seconds after a

prefect.flow-run.Running

event is observed. - Example: Monitoring if a critical data processing flow completes on time, and alerting if it doesn't. 2. Reactive Triggers: - Definition: These triggers activate when a certain event or set of events occurs. They count events towards a threshold and execute actions once the threshold is met. - Use Case: Suppose you want to trigger an action every time a flow run fails. A reactive trigger can be set to respond to

prefect.flow-run.Failed

events. - Example: Automatically restarting a flow if it fails a certain number of times. For more in-depth information, you can refer to the Prefect documentation on custom triggers.