How do I set the location of the result upon writing? Below code doesn't work, does not generate the

df.parquet

file:

parquet_result = LocalResult(dir="./test_prefect", serializer = PandasSerializer("parquet")

@task
def test_task(df1, df2):
    parquet_result.write(df1, location = "df1.parquet", **context)
    parquet_result.write(df2, location = "df2.parquet", **context)

Currently I have to set the

location

attribute at the time of instantiating the

LocalResult

object. The code below works

parquet_result_partial = partial(LocalResult, dir="./test_prefect", serializer = PandasSerializer("parquet"))

@task
def test_task(df1, df2):
    parquet_result_partial(location = "df1.parquet").write(df1, **context)
    parquet_result_partial(location = "df1.parquet").write(df2, **context)

So it seems the

location

kwargs to

Result.write

does not do anything. Is this by design? Or am I missing something

Hey @An Hoang, This is by design because results are normally meant to be attached to the task definition like

@task(result=LocalResult(location="xxx.csv"))

, This would save the return of the task. With the specific code snippet above, I think it might be easier to use the Pandas interface directly with

<http://df.to|df.to>_parquet("xxx.parquet", index=False)

If you want to use the Result class though, I think you can do something like templating the result. In this case, you can map over

df1

and

df2

and just provide the

task_run_id

or

map_index

to create a new file path. You can also use the value, so maybe you can pull the name of the dataframe to create the filename. With this, you can do

test_task.map([df1,df2])

. You can also template the first

LocalResult

and then maybe fill it with the kwargs later like this . You can also use the

LocalResult

inside the task, but I guess you’re asking because there is a lot of boilerplate code when you use the same result in a lot of different tasks?