<@ULVA73B9P> I have a task who’s cache_key_fn is r...
# ask-marvin
b
@Marvin I have a task who’s cache_key_fn is returning a constant string.
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@task(
    name="Get Menu URLs Task",
    on_completion=[record_menu_urls_results],
    timeout_seconds=600,
    tags=["menu"],
    cache_key_fn=menu_cache_key_fn,
    result_serializer="json",
    cache_expiration=timedelta(days=30),
    persist_result=True,
    result_storage_key=f"{get_task_cache_key()}/menu_urls.json",
)
async def get_menu_urls_task(menu_data: MenuData) -> list[dict]:
    """Get menu urls for the venue.

    Args:
    ----
        menu_data (MenuData): The menu data

    """
    return menu_data
However, when i rerun this task in a following flow, it is continuing the rerun the task (not return the cached data). The result is getting persisted into S3 correctly. Why is the caching not working. Im using prefect 3
m
Based on the information from Prefect documentation and code examples, your task caching should typically work if the
cache_key_fn
returns a constant key. However, since the task is not returning cached data, there are a few things you should check: 1. Cache Key: Ensure the cache key returned by
menu_cache_key_fn
is consistent. 2. Caching Setup: Ensure the environment correctly supports caching and that configurations like
cache_expiration
and
persist_result
are correctly set. 3. Flow Execution: Ensure the flow and task runs are correctly traced and connected. Here are some steps and considerations to help troubleshoot further: - Verify that the
menu_cache_key_fn
is truly generating a constant key and it aligns with the setup in Prefect expectations. - Ensure that your task decorator settings are correctly applied. For reference, here's a simple example from the documentation on how to use `cache_key_fn`:
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python
from prefect import task, flow

def static_cache_key(context, parameters):
    return "static_cache_key"

@task(cache_key_fn=static_cache_key, cache_expiration=timedelta(days=1))
def cached_task():
    return 42

@flow
def test_caching():
    cached_task()
    cached_task()
    cached_task()

if __name__ == "__main__":
    test_caching()
This example ensures that your flow is correctly identifying and using the cache key. You can find more about Prefect tasks and caching in their documentation. If you ensure that everything matches and it still doesn't work, consider contacting Prefect support or looking through open issues related to caching for possible bugs or updates.