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Author here. Philosophically, Syberia can be thought of as an extension of caret with hopefully clearer abstractions in large projects. In particular, all of th

Author here. Philosophically, Syberia can be thought of as an extension of caret with hopefully clearer abstractions in large projects. In particular, all of the packages supported by caret can and will eventually be parametrized into the modeling engine. This is the 0.6 release in which we make the scaffold available. Over time, we will fill in the pieces that are currently provided by other tools like caret or Bernd Bischl's mlr.

scottlocklin 9y ago
You know, the real problem with R for production work is dealing with munged package dependencies. Writing a makefile with hand curated package deps is something I really wish I never had to do again.
- claytonjy 9y ago
  Looks like robertk wrote `lockbox` specifically to solve this. Dependency management still sucks in R. Too many options, each a little different: Packrat, checkpoint, now lockbox. I have friends using Docker specifically to encapsulate their R package dependencies, too.
  - kirillseva 9y ago
    disclosure: I work with robertk at Avant, where we've developed syberia and lockbox specifically to have reproducible model builds and to turn R model objects into API servers in a deterministic way. Lockbox is closely modelled after ruby's bundler, and syberia is like rails for data science. I've you've ever written a ruby-on-rails or a django app you'll feel like at home using lockbox. I encourage you to give it a try, and let us know in github issues if you are having any trouble using it
    - claytonjy 9y ago
      I'd love to hear more about how it compares to other workflows. Is it worth the learning curve? There's a lot going on here, and a lot of overlap with more popular and widely used tools in the R world. My small team is R-first and a big fan of the tidyverse, and we're exploring using Docker in tandem with tools like plumber (R package for building simple API's around R code) and pachyderm (language-independent, containerized data pipelining with straightforward cloud integration) for different projects. Does Syberia fit in nicely with these tools, or aim to replace them with its own set of conventions and philosophies?

scottlocklin 9y ago

You know, the real problem with R for production work is dealing with munged package dependencies. Writing a makefile with hand curated package deps is something I really wish I never had to do again.

claytonjy 9y ago
Looks like robertk wrote `lockbox` specifically to solve this. Dependency management still sucks in R. Too many options, each a little different: Packrat, checkpoint, now lockbox. I have friends using Docker specifically to encapsulate their R package dependencies, too.
- kirillseva 9y ago
  disclosure: I work with robertk at Avant, where we've developed syberia and lockbox specifically to have reproducible model builds and to turn R model objects into API servers in a deterministic way. Lockbox is closely modelled after ruby's bundler, and syberia is like rails for data science. I've you've ever written a ruby-on-rails or a django app you'll feel like at home using lockbox. I encourage you to give it a try, and let us know in github issues if you are having any trouble using it
  - claytonjy 9y ago
    I'd love to hear more about how it compares to other workflows. Is it worth the learning curve? There's a lot going on here, and a lot of overlap with more popular and widely used tools in the R world. My small team is R-first and a big fan of the tidyverse, and we're exploring using Docker in tandem with tools like plumber (R package for building simple API's around R code) and pachyderm (language-independent, containerized data pipelining with straightforward cloud integration) for different projects. Does Syberia fit in nicely with these tools, or aim to replace them with its own set of conventions and philosophies?