Add decorators for functions

[kunaljubce]

Proposed changes

Took another stab at #140, as an extension to #144.

Types of changes

What types of changes does your code introduce to quinn?
Put an x in the boxes that apply

• Bugfix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• Documentation Update (if none of the other choices apply)

[SemyonSinchenko]

Is it a breaking change, isn't it? If so, I would suggest pushing it into 1.0, not main. In the same moment, we need to mark these functions as deprecated in the main and make a new release. @MrPowers what do you think?

[kunaljubce]

Is it a breaking change, isn't it? If so, I would suggest pushing it into 1.0, not main. In the same moment, we need to mark these functions as deprecated in the main and make a new release. @MrPowers what do you think?

Could be a potential breaking change, yes. Would like to discuss more on this. Let me move this 1.0.

[kunaljubce]

I don't see a branch for 1.0. Did we create it? I remember seeing a label for 1.0, though.

[kunaljubce]

@SemyonSinchenko Also we are not exactly deprecating this functionality but evolving it to serve a better purpose, if I may say so 😆 Would a DeprecationWarning be apt for this?

I would think a better way would be to publish this change under a change log or something.

[kunaljubce]

Implementation details for validate_schema

So basically we are implementing a decorator factory here so that our function can be used both as a decorator as well as a callable function. In this implementation:

• The validate_schema function acts as both a decorator factory and a decorator. It takes required_schema, ignore_nullable, and an optional _df argument.
• If _df is None, it means the function is being used as a decorator factory, and it returns the decorator decorator.
• If _df is not None, it means the function is being called directly with a DataFrame, and it applies the decorator to _df immediately.

When validate_schema is called directly with a DataFrame, the validation logic gets executed by wrapping the DataFrame in a lambda function and immediately calling the decorator.

[SemyonSinchenko]

Hmm, maybe it would be better to leave a current function as is and create a new one? I don't know. @MrPowers @jeffbrennan, what do you think, guys?

[jeffbrennan]

I like the idea of having one function that uses the decorator if no dataframe is provided - we would need to keep the arguments consistent with the current validate_schema implementation though

[kunaljubce]

I like the idea of having one function that uses the decorator if no dataframe is provided - we would need to keep the arguments consistent with the current validate_schema implementation though

@jeffbrennan The only difference in the arguments is the absence of _df since this will be fetched from the base function on which the decorator is applied. The other two arguments required_schema and ignore_nullable are consistent across both scenarios. Is this what you are talking about or did I miss your point?

[kunaljubce]

Hmm, maybe it would be better to leave a current function as is and create a new one? I don't know. @MrPowers @jeffbrennan, what do you think, guys?

@SemyonSinchenko This was the case with #141. I agree with the discussion in there that two different functions achieving a similar objective, one being used as a callable and one being used as a decorator can be confusing to users. That, in fact, was my inspiration to take a fresh attempt at this problem.