Tri
07/17/2025, 4:10 AMMarvin
07/17/2025, 4:10 AMMarvin
07/17/2025, 4:11 AMallow_failure
feature from Prefect 2.x has been replaced with different patterns in Prefect 3.x. Here are the main ways to handle task failures while allowing subsequent tasks to continue:
1. Using try/except blocks (Recommended approach):
python
from prefect import flow, task
@task
def task_that_might_fail():
raise ValueError("Something went wrong!")
@task
def subsequent_task():
return "I still run!"
@flow
def my_flow():
try:
task_that_might_fail()
except Exception as e:
print(f"Task failed but we're continuing: {e}")
# This will still run
result = subsequent_task()
return result
2. Using return_state=True to check task states:
python
from prefect import flow, task
@task
def task_that_might_fail():
raise ValueError("Something went wrong!")
@task
def subsequent_task():
return "I still run!"
@flow
def my_flow():
# return_state=True returns a State object instead of raising an exception
state = task_that_might_fail(return_state=True)
if state.is_failed():
print(f"Task failed: {state.result()}")
# This will still run
result = subsequent_task()
return result
Key points to understand:
- In Prefect 3.x, flows can complete successfully even if they contain failed tasks (unless exceptions are explicitly propagated)
- The recommended pattern is to use explicit error handling with try/except blocks
- For more complex scenarios, you can use return_state=True
to inspect task states and make decisions based on them
- You can also implement custom retry logic or failure hooks if needed
This new approach in Prefect 3.x gives you more explicit control over how task failures are handled, allowing you to implement more sophisticated error handling patterns.
Remember that if you need to handle failures in mapped tasks or more complex scenarios, you'll want to implement appropriate error handling patterns for those specific cases.