pain point: serialization

converting data in one format to another format

especially painful when complex

other languages have good ideas

marshmallow - a Python library

marshmallow

A lightweight library for converting complex objects to and from simple Python datatypes.

similar art in R

• assertr (assertions for analysis pipeline)

• validate (very similar to assertr AFAICT)

• errorlocate (find errors in datasets)




• any others?

why?/use cases

• data validation: lots of potential users

• remote data sources can change: schemas help validate and catch changes

• use in scripts (most researchers): help raise issues with scripts as time goes on and data inputs change

• using R with plumbr or similar: convert data to serve to API or consume from API request bodies

To do

• Nested data works - but needs more testing

• Add more 'field' types: url, email, (domain specific types)

• Add support for user-defined fields

• Probably add an easier to use interface, less R6'y

When should I not make a pkg?

• the pkg doesn't solve actual use cases

• there's significant overlap with existing solutions

• and maintainers are responsive

• there's higher priority/lowering hanging fruit

Use cases

For staypuft, likely many users

Everyone deals with objects in R

& I'm not against sillyness

elephant in the room ...

aren't you just re-making S4?

higher priority/lower hanging fruit

• I've got many other packages

• Many of which have many users

• What if new package has a huge impact though?

• How would I know?

So...

staypuft future is unclear

if you're interested:

 ropensci/staypuft

 scotttalks.info/staypuft