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<@ULVA73B9P> In Prefect3.x, why is my flow not fai...
# ask-marvin
k
@Marvin In Prefect3.x, why is my flow not failing when the following error is thrown in a task:
Copy code
Finished in state NotReady("Upstream task run '6be2bc12-91d8-47a7-8659-684c163cdd32' did not reach a 'COMPLETED' state.", type=PENDING)
Please wait for all submitted tasks to complete before exiting your flow by calling `.wait()` on the `PrefectFuture` returned from your `.submit()` calls.

Example:

from prefect import flow, task

@task
def say_hello(name):
    print(f"Hello, {name}!")

@flow
def example_flow():
    future = say_hello.submit(name="Marvin")
    future.wait()

example_flow()
m
In Prefect 3.x, the behavior you observed, where a flow does not fail even though an upstream task is not completed, can be attributed to how Prefect handles flow state determination and the execution of tasks. ### Key Points from the Prefect Documentation: 1. State Determination: - Prefect determines the final state of a flow or task based on various terminal states like 
COMPLETED
, 
FAILED
, or 
CRASHED
. A task can return any Python object without failing unless it explicitly returns a 
Failed
state. See this section for more details. 2. Flow Completion: - In Prefect 3.x, flows may complete successfully even if they contain failed tasks unless the failure affects the flow's return value or raises an uncaught exception. This is because task failures within a flow do not automatically cause the entire flow to fail unless explicitly handled. Read more here. 3. Exception Handling: - By default, task exceptions are suppressed (besides logging), unless you explicitly handle them with 
raise_on_failure=False
. This means that unless these exceptions are allowed to propagate, they won't affect the flow run state. 4. Using 
PrefectFuture.wait()
: - Make sure to use 
.wait()
on your 
PrefectFuture
objects to synchronize task execution and correctly determine their final states before exiting the flow. ### Recommendations: To ensure your flow fails when critical tasks fail, consider these suggestions: - Allow task exceptions to propagate by avoiding 
raise_on_failure=False
. - Utilize 
return_state=True
or 
wait()
to explicitly check task states and conditionally handle exceptions or return a failed state. - Use 
try/except
blocks within the flow or tasks to manage potential failures and return appropriate states. These strategies align with Prefect's execution model and should help in scenarios where you expect the flow to fail due to task exceptions. You can find more details in the Prefect 3.x documentation on writing flows and managing states.
k
@Marvin Give me an example of raise_on_failure in code
m
In Prefect 3.x, you can use the 
raise_on_failure
option to control how exceptions are handled in your tasks and flows. Here's a simple example to demonstrate how to work with `raise_on_failure`:
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python
from prefect import task, flow

@task
def risky_task():
    # Simulating a task that raises an exception
    raise ValueError("This is a risky task!")

@flow
def handle_task_failure():
    try:
        # Run the task and set raise_on_failure=True
        risky_task(raise_on_failure=True)
    except Exception as e:
        # Handle the exception in case the task fails
        print(f"Task failed with exception: {e}")

# Execute the flow
handle_task_failure()
### Explanation: - Task Definition: The 
risky_task
function simulates a task that raises an exception. - Flow Execution: The 
handle_task_failure
flow calls the task with 
raise_on_failure=True
, which means any exception that occurs will propagate and must be handled explicitly. - Exception Handling: Surrounding the task invocation with a try-except block allows you to manage the exception and take appropriate actions, such as logging the error or performing cleanup tasks. This approach ensures that task failures do not quietly pass by, allowing you to handle critical errors as needed. You can find more information about handling task failures and using 
raise_on_failure
in the Prefect 3.x documentation at this link.
k
@Marvin Show me an example where you set raise_on_failure but also pass other parameters to the task function
m
Here's an example where you set 
raise_on_failure
and also pass other parameters to the task function:
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python
from prefect import task, flow

@task
def greet_person(name: str, age: int):
    # A simple task that raises an exception if age is unrealistic
    if age < 0:
        raise ValueError("Age cannot be negative!")
    print(f"Hello, {name}! You are {age} years old.")

@flow
def greeting_flow():
    try:
        # Call the task with parameters and set raise_on_failure=True
        greet_person.with_options(raise_on_failure=True).submit(name="Alice", age=25)
        greet_person.with_options(raise_on_failure=True).submit(name="Bob", age=-3)  # This will raise an exception
    except Exception as e:
        print(f"Task failed with exception: {e}")

# Execute the flow
greeting_flow()
### Explanation: - Task Definition: The 
greet_person
task takes parameters 
name
and 
age
and raises an exception if the age is less than zero. - Flow Execution: The 
greeting_flow
calls the task with different sets of parameters. It uses 
.with_options(raise_on_failure=True)
to ensure any exceptions are raised. - Error Handling: The flow captures exceptions using a try-except block to manage task failures. This example illustrates how you can set 
raise_on_failure
while still passing regular parameters to your tasks, ensuring better control over task execution and error management.
k
@Marvin Invoking like this: steam_app_ids = fetch_games_without_details.with_options(raise_on_failure=True).submit(conn) Raises the error of this:
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TypeError: Task.with_options() got an unexpected keyword argument 'raise_on_failure'
m
The error you're encountering indicates that 
raise_on_failure
is not a valid argument for the 
.with_options()
method. Instead, 
raise_on_failure
can be used directly with the 
.result()
method or within task execution. Here's how you can correctly use `raise_on_failure`:
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python
from prefect import task, flow

@task
def fetch_games_without_details(conn):
    # Simulated logic which could raise an exception
    if not conn:
        raise ValueError("Invalid database connection!")
    # Assuming some operation that returns game IDs
    return [1, 2, 3]

@flow
def retrieve_game_details_flow():
    try:
        # Submit the task and get the result with raise_on_failure=True
        future = fetch_games_without_details.submit(conn=None)  # Simulating an invalid connection
        result = future.result(raise_on_failure=True)
        print(f"Fetched game IDs: {result}")
    except Exception as e:
        print(f"Task failed with exception: {e}")

# Execute the flow
retrieve_game_details_flow()
### Explanation: - Task Definition: The 
fetch_games_without_details
task simulates fetching game IDs, but raises an exception if the connection is invalid. - Flow Execution: - Use 
.submit()
to run the task. This will return a 
PrefectFuture
. - Use 
.result(raise_on_failure=True)
on the returned 
PrefectFuture
to ensure that any exceptions raised during the task execution are propagated and must be handled. - Error Handling: The try-except block captures exceptions, allowing you to handle task failures appropriately. In summary, 
raise_on_failure
is not part of 
.with_options()
but is instead used with 
.result()
to control task execution behavior.
k
@Marvin That's really un-intuitive. Are you sure this is how it's meant to be used?
🙌 1
m
Yes, using 
raise_on_failure
with the 
.result()
method is indeed the intended way to handle task exceptions in Prefect 3.x. This approach provides flexibility in controlling how exceptions are propagated during task execution within a flow. Here's a more detailed explanation based on the documentation: ### Usage of 
raise_on_failure
in Prefect 3.x 1. PrefectFuture: - When you submit a task using 
.submit()
, it returns a 
PrefectFuture
object. This object allows you to manage task execution asynchronously and retrieve results once the task is completed. 2. Accessing Results: - To access the result of a task, use the 
.result()
method on the 
PrefectFuture
. By default, if the task raises an exception, calling 
.result()
will raise that exception. 3. raise_on_failure Parameter: - You can adjust this behavior using the 
raise_on_failure
parameter in the 
.result()
method. Setting 
raise_on_failure=False
allows the flow to continue even if the task fails, enabling you to handle exceptions as needed within your flow rather than stopping execution. Here is a basic example from the documentation that illustrates this pattern:
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python
from prefect import flow, task

@task
def may_fail_task():
    raise ValueError("This is a failure!")

@flow
def example_flow():
    # Submit the task and retrieve the future
    future = may_fail_task.submit()
    
    try:
        # Access the result and propagate failure if any
        result = future.result(raise_on_failure=True)
    except Exception as e:
        print(f"Task run failed with exception: {e}")

example_flow()
### Summary This way of handling task results gives you more control, especially in cases where you want the flow to continue or take specific actions upon encountering errors. You can find more details in the Prefect 3.x documentation on the task runners page.
k
@Marvin Why aren't you using the .wait() function after submit?
m
The 
.wait()
function is used to block the execution of the flow until all submitted tasks are completed. This can be particularly useful when you want to ensure that all asynchronous operations finish before proceeding to the next step in your flow. In the example I provided, the use of 
.result()
inherently waits for the task to complete before retrieving the result, so additional use of 
.wait()
is not strictly necessary if you're immediately calling 
.result()
. However, there are scenarios where explicitly using 
.wait()
can be beneficial: 1. Batch Submission: When submitting multiple tasks, you might use 
.wait()
to pause execution until all tasks have completed before moving on, ensuring that all results are available. 2. Explicit Synchronization: Even if you don't need the immediate result, you might want to ensure task completion at a certain point in the flow for other logic reasons. Here's how you might include 
.wait()
in the example:
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python
from prefect import flow, task

@task
def may_fail_task():
    raise ValueError("This is a failure!")

@flow
def example_flow():
    # Submit the task and retrieve the future
    future = may_fail_task.submit()
    
    # Wait for the task to complete, which is useful if you have multiple tasks
    future.wait()
    
    try:
        # Access the result and propagate failure if any
        result = future.result(raise_on_failure=True)
    except Exception as e:
        print(f"Task run failed with exception: {e}")

example_flow()
### Explanation for 
.wait()
Usage: - Execution Synchronization: Using 
.wait()
ensures the flow does not proceed until the task has reached a terminal state. This is redundant if calling 
.result()
immediately but can be useful for scenario-specific logic requirements or during more complex flow designs. - Managed Execution: When integrating multiple tasks or distributing execution across resources, 
.wait()
provides a straightforward mechanism for synchronizing task completion. Thus, whether you use 
.wait()
in your flow depends on your specific needs for task synchronization and result handling.
k
@Marvin I made all the changes you suggested and still my flow isn't failing when a task fails. What is going on?
m
In Prefect 3.x, despite making the correct changes, a flow might not fail when a task within it fails due to how Prefect handles task and flow states. Here's a summary of how to ensure your flow fails when a task fails: ### Key Considerations: 1. Tasks with Exceptions: - Prefect 3.x doesn't automatically fail the entire flow if a task fails unless the task's exception is explicitly handled. - By default, if a task encounters an exception, the flow might still complete unless the exception affects the returned state of the flow. 2. Explicit State Checking: - Use 
raise_on_failure=True
in the 
.result()
method to propagate task exceptions. - If using 
raise_on_failure=False
, explicitly check the state of the task and raise an exception manually if the task failed. 3. Flow Return: - Flows will generally mark as failed only if their final state determination includes failure states in the returned futures. ### Example Code Correction: Here’s a corrected example based on these principles:
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python
from prefect import flow, task
from prefect.states import Failed

@task
def risky_task(param):
    if param < 0:
        raise ValueError(f"Invalid parameter: {param}")

@flow
def main_flow():
    future = risky_task.submit(-1)  # This should fail
    try:
        # Use result() with raise_on_failure=True
        future.result(raise_on_failure=True)
    except Exception as e:
        print(f"Exception caught: {e}")
        return Failed(message="Critical task failed.")  # Ensure the flow fails

# Execute the flow
main_flow()
### Explanation: - Use of 
.result()
with 
raise_on_failure=True
 ensures that any task-level exceptions are not suppressed, allowing for proper exception handling within the flow. - Returning a 
Failed
state from your flow if a critical task fails ensures that the flow is marked as failed, which is necessary for scenarios where downstream logic is dependent on successful task execution. For a deeper dive, check the Prefect 3.x documentation on writing flows and managing state transitions to align with how Prefect manages execution states across tasks and flows.
k
@Marvin I exit a task with "return Failed(message="No API data returned.")" Will that not fail the flow as well?
m
Using 
return Failed(message="No API data returned.")
within a task is a good approach to indicate that a task has failed, but simply returning this state does not automatically propagate failure to the flow level. Here's how it works and what you might need to do: ### Understanding Task and Flow States: 1. Task State Handling: - Returning a 
Failed
state from a task correctly marks that task as failed. This is useful for signaling specific issues during task execution. 2. Flow Behavior: - In Prefect, the flow itself may continue running unless the failed state is specifically acted upon within the flow logic. - The flow run will not automatically fail unless the failure affects the flow’s execution path or is explicitly handled by the flow. ### Ensuring Flow Fails: To ensure that your flow also reflects this failure, follow these steps in the flow logic:
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python
from prefect import task, flow
from prefect.states import Failed

@task
def api_call_task():
    # Simulate an API call returning no data
    return Failed(message="No API data returned.")

@flow
def main_flow():
    task_state = api_call_task.submit().result(raise_on_failure=False)

    if isinstance(task_state, Failed):
        # Handle the task's failed state
        print("Task failed with message:", task_state.message)
        return Failed(message="Flow failed due to a critical task failure.")

# Execute the flow
main_flow()
### Explanation: - Task State Return: By returning a 
Failed
state, you clearly denote the task failure. - Result Handling in Flow: Using 
.result(raise_on_failure=False)
and checking if the result is a 
Failed
state allows you to take appropriate actions in the flow. - Flow Failure Indication: Explicitly return a 
Failed
state in the flow when a critical task fails, ensuring that the overall flow run is marked as failed. ### Conclusion: This approach allows you to manage failures explicitly and ensures that task failures are appropriately reflected in the flow's state. By handling failures at the flow level, you gain more control over flow execution outcomes according to your business logic requirements.
n
hi @Klashe! I haven't read this thread closely but tldr to fail the parent flow, you need to: • let an exception raise • explicitly return 
Failed
you can use 
raise_on_failure
but generally in similar cases I prefect 
return_state
so like
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from prefect import flow, task

@task
def t() -> int:
  return 42

@flow
def f():
  state = t(return_state=True)
  assert state.is_completed() # or check if its failed and do something
  assert state.result() == 42

f()
k
Thanks, @Nate, i will try your approach. Marvin took me on a bit of a ride and I want to get off. 🙂
n
sure thing, i think the only misinformation marvin was spreading here was that 
raise_on_failure
was a decorator kwarg, otherwise I think it was mostly correct, and based on these docs
j
You can use 
result
as Marvin was suggesting - it will 
wait
under the covers for the result to be available. Result + raise_on_failure should propogate an exception at the point in the flow where you called result. Here is where to find the docs on when a failed task causes flow failure https://docs-3.prefect.io/3.0/resources/upgrade-to-prefect-3#flow-final-states
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