< Marvin> when I run this code my fifth task wont start sinc Prefect Community #ask-marvin

It seems like your "fifth_task" is stuck in a "pending" state because its upstream task hasn't completed. In Prefect, tasks are often dependent on the completion of upstream tasks, and a task will not start until all its dependencies have reached a "completed" state. Here are a few things you can check or try: 1. Task Dependencies: Ensure that the upstream tasks are correctly defined and are capable of reaching a "completed" state. If they are not completing due to errors or logic issues, the downstream tasks will remain pending. 2. State Management: The task state management system in Prefect can sometimes be tricky. If a task remains in a "pending" state, it might be due to a failure in the upstream task or an incorrect state transition. Ensure that your upstream tasks are not failing silently. 3. Force State Transition: In some cases, you might want to force a state transition. This can be done programmatically by setting the state forcefully if you are sure that the task should proceed. For more detailed information, you can refer to the following links: - Task Engine - Tasks If your issue persists, you might want to review the task logic or consult Prefect's documentation on state management for more insights.

Koen

02/11/2025, 1:54 PM

@Marvin when I run this code my "fifth_task" wont start since the upstream task did not reach a "completed" state, type =pending

Copy code

from prefect import flow, get_run_logger, task
from prefect.states import Failed, Completed


#Custom Exception class that allows to return data
class TaskFailureException(Exception):
    def __init__(self, message, data):
        super().__init__(message)
        self.data = data


@task(task_run_name="task_that_raises: {x}")
def task_that_raises(x):    
    if x < 3:
        # Raise a custom exception with the data you want to preserve
        raise TaskFailureException(f"Value is too low: {x}", data=x)
    # Return data normally for a Completed state
    return x

@task()
def another_task(data):
    return (f"got here and showing data from previous task: {data}")


@flow()
def demo_passing_data():
    global run_logger
    run_logger = get_run_logger()
     
    fourth_task = task_that_raises(x=1, return_state=True)
    print("hey i'm here")
    if fourth_task.is_failed():       
        print("now I'm here")
        print(f"{fourth_task.data}")
        print(f"{fourth_task.data.result.data}")
    
    fifth_task = another_task(data=10, wait_for=[fourth_task])
    print(fifth_task)
    return Completed()

if __name__ == "__main__":
    demo_passing_data()

Marvin

02/11/2025, 1:54 PM

The issue with your "fifth_task" not starting likely stems from the

wait_for

parameter and the state management of the

fourth_task

. Here's a breakdown of what's happening: 1. Task State Management: In Prefect, tasks have states such as Pending, Running, Completed, Failed, etc. If a task fails, its state is set to Failed, and any downstream tasks that depend on it using

wait_for

will not run unless the upstream task completes successfully. 2. Custom Exception Handling: In your

task_that_raises

, you're raising a

TaskFailureException

when

x < 3

, which sets the task's state to Failed. This prevents

another_task

from starting because it is waiting for

fourth_task

to complete successfully. 3. Using
wait_for
: The

wait_for

parameter is used to specify that a task should wait for other tasks to complete before starting. If any of those tasks fail, the task with

wait_for

will not start. To resolve this, you can modify your flow to handle failed states in a way that allows downstream tasks to proceed. Here's a suggestion: - Use a try-except block to catch the custom exception and handle it appropriately, possibly setting a default value or using a fallback task. Here's a conceptual example:

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

class TaskFailureException(Exception):
    def __init__(self, message, data):
        super().__init__(message)
        self.data = data

@task(task_run_name="task_that_raises: {x}")
def task_that_raises(x):    
    if x < 3:
        raise TaskFailureException(f"Value is too low: {x}", data=x)
    return x

@task()
def another_task(data):
    return f"got here and showing data from previous task: {data}"

@flow()
def demo_passing_data():
    global run_logger
    run_logger = get_run_logger()
     
    try:
        fourth_task = task_that_raises(x=1)
    except TaskFailureException as e:
        run_logger.warning(f"Task failed with data: {e.data}")
        # Optionally set a default or handle the failure
        fourth_task_result = e.data
    else:
        fourth_task_result = fourth_task

    fifth_task = another_task(data=fourth_task_result)
    print(fifth_task)
    return Completed()

if __name__ == "__main__":
    demo_passing_data()

This way, you handle the failure case and allow

another_task

to proceed with a fallback or default value. For more on task dependencies and state management, you might find these resources helpful: - Task Engine - Tasks

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