@Marvin I want to define one task that can check on the state of previous tasks and can skip any downstream tasks based on some condition. I want to do this in a task and not with an if statement in my flow. How can I write such a task?

To write a task that checks on the state of previous tasks and skips downstream tasks based on some condition, you can use custom logic within your task in Prefect 2.x. There are a couple of methods that can help achieve this behavior: 1. Task-level State Handling: In Prefect 2.x, you have the ability to build custom logic that reacts to task-run states within your flow function without needing separate

state_handlers

. You can inspect the state of previous tasks and conditionally execute or skip the current task based on the outcomes of those tasks. The documentation provides further explanation and code examples on how to take action on a state change of a task run. 2. Raising Custom Exceptions: Instead of sending signals like in Prefect 1.x, in Prefect 2.x, you can raise an arbitrary exception in your task or flow and return a custom state based on your logic. This means you can use exceptions to control the flow of your tasks, stopping the task run or skipping downstream tasks as needed. Here's a simple example of how you might write a task to check the state of previous tasks and make a decision:

python
from prefect import flow, task
from prefect.engine import State

@task
def check_previous_states(*args):
    # args consist of the outputs from previous tasks
    for arg in args:
        if isinstance(arg, State) and arg.is_failed():
            # Here we check if any previous task has failed
            # You can extend this logic for other task states or conditions
            raise Exception("A previous task has failed, skipping downstream tasks.")
    return "All previous tasks succeeded, continuing execution."

@flow
def my_flow():
    # Define the tasks and their dependencies here
    result1 = task1()
    result2 = task2()

    # Here we have the checking task that will inspect previous task results
    check_result = check_previous_states(result1, result2)

    # If check_previous_states does not raise an exception, the flow proceeds
    # Otherwise, downstream tasks can be skipped based on the custom exception handling
    downstream_result = downstream_task(check_result)

# Flow and tasks definitions for task1, task2, and downstream_task would be here

In the above example,

check_previous_states

is a task that receives the outputs from previous tasks (

result1

,

result2

). It checks their state, and if any has failed, it raises an exception to indicate that downstream tasks should be skipped. This is just a simplified example to illustrate the concept; in a real-world scenario, you would customize this to handle your specific conditions and logic for skipping tasks. Remember, conditional constructs such as

case

are no longer required in Prefect 2.x, and you can use Python's native if/else conditionals as part of your flow control logic.

havent read all this :) but the import for State should be from prefect.states import State, not from engine

@Marvin Let's say I have the following code:

@task
def do_some_work():
    # Do something with side effects

@task
def check_on_results():
    # Compute something about the side effects, and decide whether downstream tasks should continue to run

@task
def do_some_other_work(check_result):
    # Do something else expensive that we don't want to do unnecessarily

@flow
def my_flow():
    a = do_some_work.submit()
    b = check_on_results.submit(wait_for=[a])
    c = do_some_other_work.submit(b)

What I want to happen is that B be able to return some state or raise some exception such that C can know not to run (perhaps, marking C as cancelled) without crashing the flow AND without requiring an if-statement in the flow run (I don't want to block the flow function's execution)

In Prefect 2.x, you can manage the flow of tasks, including canceling downstream tasks based on the outcome of a previous task without stopping the whole flow. There are a couple of techniques you can use to achieve this: 1. Canceling a Task Run: Prefect 2.x provides the capability to cancel a task run programmatically by setting a task state to

Cancelled

. You can have your

check_on_results

task return a special value or raise a custom exception that is then handled by

do_some_other_work

to determine not to execute its logic. 2. Control Dependencies: You can manipulate the flow's dependencies so that

do_some_other_work

only runs if

check_on_results

is successful. This way, if

check_on_results

sets its state to

Cancelled

or

Failed

, the downstream task won't run. Here is an example of how you might modify your existing flow to achieve this:

python
from prefect import task, flow
from prefect.tasks import task_input_hash
from prefect.engine import get_run_logger

@task
def do_some_work():
    # Do something with side effects
    return {"some": "result"}

@task
def check_on_results():
    # Compute something about the side effects, and decide whether downstream tasks should continue to run
    # If the task should not continue, return a special value or raise an exception. For example:
    should_continue = False  # This is where you put your actual logic
    if not should_continue:
        raise Exception("Downstream tasks should not continue.")
    return should_continue

@task
def do_some_other_work(check_result):
    if check_result is False:
        get_run_logger().info("Canceling the task based on the check result.")
        # Use Prefect API or mechanism to mark this task as cancelled
        
    # If the task has not been cancelled, proceed with the expensive operation
    # Do something else expensive that we don't want to do unnecessarily

@flow
def my_flow():
    a = do_some_work.submit()
    b = check_on_results.submit(wait_for=[a])

    # The downstream task checks the result from `check_on_results` task
    # If an exception is caught, it will skip the execution of "expensive" work
    b_result = b.result()  # Wait for task `b` to complete and get its result
    c = do_some_other_work.submit(b_result, wait_for=[b])

# Execute the flow
my_flow()

In the

do_some_other_work

task, you could include logic to check the result of the

check_on_results

task. If the result indicates that it should not continue, it can either skip its execution internally and end with a

Cancelled

state or raise an exception that you catch elsewhere in the flow. With this approach, you need to make sure that the "cancellation" is handled gracefully so that it does not crash the whole flow, and that

do_some_other_work

is aware of the need to check the result of

check_on_results

. Please note that as of the information provided, there isn't a built-in mechanism in the flow definition itself to automatically cancel a downstream task based on the state of an upstream task without an explicit check or an if-statement. The key is to add logic within your tasks that makes this determination. The details may vary depending on the specific mechanics of how task results and exceptions are handled in the version of Prefect you're using.

@Marvin Can you provide an example of how to "Use Prefect API or mechanism to mark this task as cancelled"?

To programmatically mark a task as canceled in Prefect 2.x, you can set the task's state to 'Cancelled' using the Prefect API or client. Although the available documentation and release notes snippets do not provide a direct example of canceling an individual task run, they do explain how to cancel a flow run using the CLI, UI, REST API, or Python client. For flow runs, cancellation is requested via the command

prefect flow-run cancel <flow-run-id>

, and the flow run is moved to a "Cancelling" state. While the documentation snippet does not detail individual task cancellation, the underlying approach would be similar. As an example, you might use the Prefect client within your task to update its state. Here's a conceptual example of how you might approach this within a Python task function:

python
from prefect import task, flow
from prefect.client import get_client
from prefect.engine import get_run_logger

@task
def do_some_other_work(task_run_id):
    logger = get_run_logger()
    with get_client() as client:
        try:
            # If the task should be canceled, update task run state to 'Cancelled'
            
            # Here, assume `should_cancel` is determined by some condition
            should_cancel = True  # Replace with actual condition

            if should_cancel:
                client.set_task_run_state(task_run_id=task_run_id, state="Cancelled")
                <http://logger.info|logger.info>(f"Task {task_run_id} was canceled.")
                return

            # Perform the actual task work if not canceled.
            <http://logger.info|logger.info>("Doing some work...")
            # ... do the expensive work ...

        except Exception as exc:
            logger.error(f"An error occurred: {exc}")
            # Optionally, handle the exception by setting an appropriate task state.

Please note,

client.set_task_run_state

is used conceptually here, and you will need to ensure that you use the correct method from the Prefect client to update the task state. This example uses a placeholder

should_cancel

condition to demonstrate where your logic would determine whether to cancel the task. The actual Prefect client's method to use for setting the task run state might vary, and you should refer to the latest Prefect client API documentation or source code for the exact method and usage. In Prefect 2.x, tasks are typically designed to handle their own state transitions, and there might not be direct support for individual task cancellation analogous to flow cancellation. If you need further clarification or details, consulting the latest Prefect documentation or source code for state management would be advisable.