Klashe
11/02/2024, 6:47 AMMarvin
11/02/2024, 6:47 AMKlashe
11/02/2024, 6:47 AMMarvin
11/02/2024, 6:47 AMCOMPLETED
, the flow will reflect this failure.
Here's a simple example to illustrate this:
python
from prefect import task, flow
@task
def always_fails_task():
raise ValueError("I am a failing task")
@task
def always_succeeds_task():
return "I am a successful task"
@flow
def main_flow():
x = always_fails_task()
y = always_succeeds_task()
# You can also handle the return results if needed
return x, y
# Running main_flow() will result in a failure because always_fails_task() raises an exception
In the example above, running main_flow()
will result in a failure due to the always_fails_task
task raising an exception, which will cause the entire flow to fail. For more details, you can refer to the official Prefect documentation here.Klashe
11/02/2024, 6:52 AMMarvin
11/02/2024, 6:52 AM.submit()
method with tasks, the flow will not automatically fail if a task fails, depending on how you handle task results. Specifically, you can control whether a task's failure affects the flow by how you manage the task's future object.
In the example below, if you choose to ignore the failure by setting raise_on_failure=False
, the flow can complete successfully even if a task fails:
python
from prefect import flow, task
@task
def always_fails_task():
raise ValueError("I fail successfully")
@task
def always_succeeds_task():
return "I am a successful task"
@flow
def example_flow():
# Using submit() with raise_on_failure=False allows subsequent tasks to run even if this task fails
x = always_fails_task.submit().result(raise_on_failure=False)
y = always_succeeds_task.submit(wait_for=[x])
return y
example_flow()
In this setup, because the result of always_fails_task
is captured with raise_on_failure=False
, the flow does not fail despite the task failure, and it may continue to execute other tasks. The flow's completion will depend on the state of returned futures or other tasks.
If you want the flow to fail when a task fails, you should set raise_on_failure=True
or simply let the failure propagate without handling it explicitly.
More details can be found in the Prefect 3.x documentation.Klashe
11/02/2024, 6:52 AMMarvin
11/02/2024, 6:53 AMsubmit()
method in Prefect is used to asynchronously schedule tasks for execution. This method provides several utilities:
1. Concurrency and Task Scheduling: When you submit a task using .submit()
, it allows Prefect to manage the execution of the task asynchronously, utilizing the task runner's capabilities to handle tasks concurrently, typically with a thread or process pool.
2. PrefectFuture Object: Submitting a task returns a PrefectFuture
object, which represents the asynchronous computation of the task. This object provides access to the task's state and result, allowing you to manage and track its execution.
3. Dependency Management: You can specify task dependencies directly when submitting, by using the wait_for
argument. This allows you to orchestrate complex workflows where tasks execute in a certain order based on the completion of dependent tasks.
4. Accessing Results: With the PrefectFuture
, you can access the result of a task asynchronously. You have the option to block and wait for the task's result when needed, or continue execution and use the result later.
5. Error Handling and Graceful Degradation: Using .submit()
, you can more flexibly handle task failures by deciding whether the flow should continue or halt based on task outcomes, as seen by setting error handling options like raise_on_failure
.
Here's a simple conceptual example of using .submit()
in a flow:
python
from prefect import flow, task
@task
def task_a():
return "Data from task A"
@task
def task_b(dep):
return f"Task B processing {dep}"
@flow
def my_flow():
# Submit task_a and get its future
future_a = task_a.submit()
# Pass the result of future_a to task_b once task_a is complete
future_b = task_b.submit(dep=future_a)
# Optionally wait and get the final result
result_b = future_b.result()
print(result_b)
my_flow()
In the example above, task_b
waits for task_a
to complete by using the future returned from task_a.submit()
. This setup allows you to build more responsive and efficient workflows by leveraging concurrency.
For more detailed information and examples, you can refer to the Prefect 3.x documentation on task runners.Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.
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