@Marvin / anybody who may know, I am receiving the following warning for a task in my flow. The inputs for for this task are fairly large datasets (~500k rows). Is the long duration for parameter introspection just caused by the size of the datasets that are input to the task? It's also not really necessary for me to use the @-task decorator for this flow. Would getting rid of the decorator result in Prefect not running the long-duration task introspection?

Task parameter introspection took 154.742 seconds , exceeding `PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD` of 10.0. Try wrapping large task parameters with `prefect.utilities.annotations.quote` for increased performance, e.g. `my_task(quote(param))`. To disable this message set `PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD=0`.

The search did not yield specific documentation about your issue with

Task parameter introspection

and the

PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD

, nor did it provide information about using

quote

with task parameters or how getting rid of the

@task

decorator might affect performance. However, a general code example for defining and using tasks in Prefect has been provided, which can be found here. While the search results are not directly applicable to your question, they still give us a path to consider: 1. The warning suggests that Prefect is taking a long time introspecting the parameters of your task which can be affected by the size and complexity of the parameters passed. 2. It's recommended to wrap large task parameters with the

prefect.utilities.annotations.quote

function which could potentially reduce the introspection time. 3. Disabling the warning can be done by setting

PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD=0

. I'll follow up with another search specifically about the use of

prefect.utilities.annotations.quote

and turning off the introspection warning by setting the threshold to 0 to give you the most relevant guidance. Please hold on for a moment. It appears that the search did not return relevant results directly addressing the specific questions about wrapping large task parameters with

prefect.utilities.annotations.quote

and the

PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD

setting. However, based on the information obtained in the warning message you received, here are some steps you can consider: 1. Wrap Large Parameters: When you pass large datasets to your task, Prefect tries to introspect these parameters which can take significant time. Use

prefect.utilities.annotations.quote

to wrap these parameters. This function might not be in the current documentation search; however, since it's mentioned in the warning, it likely exists in the Prefect library. You will have to experiment with it on your codebase. 2. Disabling the Warning: If you want to disable the introspection warning, you can set

PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD=0

in your environment variables. This will suppress the warning, but it won't improve the performance of the parameter introspection. 3. Removing

@task

Decorator: The removal of the

@task

decorator will not run the function as a Prefect task, and thus, task introspection should not occur. However, remember that you will lose all the benefits of a Prefect task, such as retrying, caching, and logging. Without specific documentation links that I can provide, I recommend experimenting with these steps, especially using quoting for large parameters. If further assistance from the documentation is required, visiting the official Prefect documentation might provide additional guidance.

@Marvin can you explain the purpose of PREFECT_TASK_INTROSPECTION

The search did not provide a direct explanation of the purpose of

PREFECT_TASK_INTROSPECTION

or why Prefect introspects task parameters. Based on common workflow platform features and my understanding of Prefect, I can infer the following: Task introspection is likely a feature in Prefect used to examine and verify task parameters before execution, which could include type validation and other checks to ensure that a task will run as expected with the given inputs. This kind of introspection can help prevent runtime errors by catching configuration issues early. Since Prefect aims for strong typing and validation of parameters (as suggested by the usage of Pydantic for parameter validation mentioned in one of the excerpts), task introspection might be an extension of this validation process providing robustness to the flow execution lifecycle. Unfortunately, without specific documentation excerpts, this is a high-level guess. Would you like to perform another search or visit the official Prefect documentation to explore more about task introspection or PREFECT_TASK_INTROSPECTION settings specifically?