potiuk edited a comment on issue #14396:
URL: https://github.com/apache/airflow/issues/14396#issuecomment-785350406
> While switching to dataclasses would be harder than TypedDicts it does not
have to be a breaking change. You can convert dictionaries to dataclasses and
vice versa pretty seamlessly. Although, implementing Dataclasses would
certainly be more work to get right in the initial pr.
Let me explain why this would be a breaking change. if you have an operator
that already uses context. Example from task decorator case (but this is the
same for any custom operator):
```
from airflow.operators.python import task, get_current_context
@task
def my_task():
context = get_current_context()
ti = context["ti"]
```
Surely you can map from Dataclass to Dict in "get_current_context()" method
(otherwise you'd have to also correct the `context["ti"]` into `context.ti`.
Thus it would be a breaking change.
But if you do that (i.e map dataclass to dict), then you loose the type
hinting. This is precisely the place where typehinting is needed (in the user
code). And I think Typed Dict (if used everywhere including return value from
get_current_context() gives you what you need from the user point of view and
there is no need to implement the `> Dataclass` step - as you have everything
you need by implementing TypeDict.
Or maybe I am missing something?
> Personally I'm of the opinion that working with the dataclass api is
superior to working with the dictionary api due to the reasons outlined above
but thats just like my opinion man.
In a number of cases yes. But in others flexibility of the dict and fact
that you can add any value there, trumps.
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