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Scott Asher
10/26/2020, 3:47 AMSecond question - and I assume this is in the docs somewhere, but i just can’t find it. In terms of using the Imperative API, you guys say:
Prefect’s imperative API allows more fine-grained control. Its main advantage over the functional API is that it allows tasks to be set as upstream or downstream dependencies without passing their results. This allows you to create a strict ordering of tasks through state dependencies without also creating data dependencies.And then you give an example where you force a “PlusOne” task to run after a task that simply prints something. My question is - what if you WANT a data dependency? Can you do this through the imperative API? More code blocks to follow in thread so I don’t clutter up the main thread.
The example you give in the docs is:
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from prefect import Task, Flow
class RunMeFirst(Task):
def run(self):
print("I'm running first!")
class PlusOneTask(Task):
def run(self, x):
return x + 1
flow = Flow('My Imperative Flow')
plus_one = PlusOneTask()
flow.set_dependencies(
task=plus_one,
upstream_tasks=[RunMeFirst()],
keyword_tasks=dict(x=10)) Copy code
from prefect import Task, Flow
class RandomNumber(Task):
def run(self):
return random.randint(0, 100)
class PlusOneTask(Task):
def run(self, x):
return x + 1RandomNumberPlusOneTaskMaybe the answer is something like:
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flow = Flow('My Imperative Flow')
plus_one = PlusOneTask()
flow.set_dependencies(
task=plus_one,
keyword_tasks=dict(x=RandomNumber())z
Zanie
10/26/2020, 2:02 PM
That looks right to me! `
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keyword_tasks: Mapping[str, object]: The results of these tasks will be provided to this task under the specified keyword arguments.s
Scott Asher
10/26/2020, 3:18 PMGreat! I would suggest you add this as your example of the Imperative API in the Flows docs section. I think it makes things much clearer!
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