Brainstorm decorators useful for PySpark programmers

[MrPowers]

Python decorators and nice and allow for some beautiful code.

PySpark programmers ofter write DataFrame transformations that change the schema of a DataFrame as follows:

• adding columns
• removing columns
• other changes to schema

This pull request proposes adding some decorators to the quinn public interface. Decorators could provide PySpark programmers with a really nice programming experience.

What would be the ideal decorator end state for PySpark programmers? Or are decorators limited for common PySpark programming patterns?

[jeffbrennan]

I like the idea of using decorators to run validations on a returned DataFrame. It allows programmers to clearly define expected output properties without having to modify their existing functions. Transformations like adding/removing columns or changing the schema tend to be part of the function logic and I don't think decorators make as much sense for that use case. Decorators could allow PySpark programmers to abstract validations away from core transformation logic.