Types from data Making structured data first-class citizens in F#
Tomas Petricek, Gustavo Guerra, Don Syme
In proceedings of PLDI 2016
Most modern applications interact with external services and access data in structured formats such as XML, JSON and CSV. Static type systems do not understand such formats, often making data access more cumbersome. Should we give up and leave the messy world of external data to dynamic typing and runtime checks? Of course, not!
We present F# Data, a library that integrates external structured data into F#. As most real-world data does not come with an explicit schema, we develop a shape inference algorithm that infers a shape from representative sample documents. We then integrate the inferred shape into the F# type system using type providers. We formalize the process and prove a relative type soundness theorem.
Our library significantly reduces the amount of data access code and it provides additional safety guarantees when contrasted with the widely used weakly typed techniques.
Paper and more information
- Download the paper (PDF)
- Supplementary screencast shows the library in action
- For more info, see F# Data homepage
- Poster about F# Data (PDF) from Student Research Competition
Watch the talk
As far as I'm aware, the PLDI 2016 talk has not been recorded, but I did a brief practical demonstration of the F# Data library, similar to one that I did in a number of industry talks. One good talk to watch has been recorded by Microsoft's Channel 9 team:
If you want to cite the paper, you can use the following BibTeX information, or get full details from the paper paper page on ACM
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Published: Sunday, 1 May 2016, 12:00 AM
Author: Tomas Petricek
Typos: Send me pull request!