Prefect caching through a file target

ghz 2days ago ⋅ 2 views

After reading the documentation on Output Caching based on a file target , I figured this workflow should be an example of output caching:

from time import sleep
from prefect import Flow, task
from prefect.engine.results import LocalResult


@task(target="func_task_target.txt", checkpoint=True, 
      result=LocalResult(dir="~/.prefect"))
def func_task():
    sleep(5)
    return 99

with Flow("Test-cache") as flow:
    func_task()

if __name__ == '__main__':
    flow.run()

I would expect func_task to run one time, get cached, and then use the cached value next time I run the flow. However, it seems that func_task runs each time.

Where am I going wrong? Or have I misunderstood the documentation?

Answer

Your code example is very close to the correct approach, but there are a few things to address regarding how output caching works in Prefect.

Key Points About Output Caching:

  • Output caching works by persisting the result of a task based on its target (which is typically a file or other external system) and checking if the result already exists before re-running the task.
  • The task will be re-executed only if the result does not exist (or the result is invalidated) in the specified target.
  • You need to make sure that the target for caching is properly handled and that the output location is correctly specified.

Problems with Your Code:

  1. Target Path: The target="func_task_target.txt" is being used, but Prefect expects this to be a file path (it can be relative or absolute). However, in your case, the file will likely be created in the current working directory. Using ~/.prefect in the result=LocalResult(dir="~/.prefect") might cause confusion because ~ should be expanded to the home directory. It may not resolve automatically when used with LocalResult.

  2. Cache Key: Prefect uses the task arguments and the target path to generate a cache key. If the arguments to the task are always the same (in this case, none), caching should work, but it is important to ensure that there are no dynamic changes that would invalidate the cache.

Corrected Code:

from time import sleep
from prefect import Flow, task
from prefect.engine.results import LocalResult
import os

# Expanding the "~" to the home directory
result_dir = os.path.expanduser("~/.prefect")

@task(target="func_task_target.txt", checkpoint=True, result=LocalResult(dir=result_dir))
def func_task():
    sleep(5)
    return 99

with Flow("Test-cache") as flow:
    func_task()

if __name__ == '__main__':
    flow.run()

Changes and Explanation:

  1. Path Expansion: I used os.path.expanduser("~/.prefect") to ensure the ~ gets expanded correctly to your home directory. This is important because ~ won't be expanded automatically when specified in Prefect's LocalResult.

  2. Target File: The target file func_task_target.txt is correctly set, and Prefect will store the result in this file. When you run the flow again, Prefect should check if the cached result exists and use it if available.

Testing Caching:

  • The first time you run the flow, func_task will execute, take 5 seconds, and save the result in func_task_target.txt.
  • On subsequent runs, Prefect will read the result from func_task_target.txt and won't re-execute func_task unless the target is deleted or modified, or the arguments change.

Additional Notes:

  • If you still see that the task runs every time, ensure that the func_task_target.txt file is properly being saved and located at the expected directory.
  • You can check if the file is being written by inspecting ~/.prefect to see if the cached result is there after the first run.
#py