Erik Erlandson

Maybe it's deliberate. I just thought it was a little unintuitive that you can import from `all` or `int`, but `double` and `float` cannot be imported individually.

I'd like to see this

This blog post makes a better argument for value of continuation monads than I would have made: http://www.haskellforall.com/2012/12/the-continuation-monad.html 

@johnynek that looks very cool! To the extent that I understand the use cases I've seen (which isn't as much as I'd like), I don't think they would manifest deep...

I've been trying to do `interp.load.cp` in the latest `almond` (0.1.7) and nothing works

I put this here: https://github.com/jupyter-scala/jupyter-scala/issues/173, which seems more appropriate.

cc @tmckayus

With respect to Spark, you can define custom partitioners, like I did here: https://github.com/roofmonkey/cambio/blob/eje/common/src/main/scala/com/redhat/et/cambio/common/trees.scala#L1469 I'm not sure if there is any added abstraction you can layer on top of `Partitioner`...

Potential efficiency benefits aside, manipulating keys is an easier way to think about the problem, and it is totally general, since there is no restriction on key data types except...

Well, maybe the `cut` example is informative for that. You can set up a key space, and instantiate a partitioner that maps each key to its own partition.