Can you have multiple plans using R package drake?

Question

I know it is not best practice to use the R package called drake within a notebook tool, but I'm doing it anyway as a workaround for the limitations to the collaboration infrastructure we have on my team at work. Since my code is broken up into chunks that are distributed throughout sections of the notebook, it would be useful to have multiple analysis plans, which I would execute in the appropriate section, and other plans may be written and executed in subsequent sections of the notebook. Is it possible to write multiple plans in drake?

Answer 1

Sorry I am late to this thread. I am the maintainer of the drake R package, and I usually expect to receive questions on the issue tracker. A drake-r-package StackOverflow tag would really help me keep up, but I do not have that privilege.

Anyway, interesting use case. I do see some workarounds:

1. Separate caches for separate plans. drake uses storr to cache its targets, and you could create different caches for different sections of your report. Essentially, your report would manage a bunch of separate drake projects. See this chapter in the manual for more on the caching system. Use the cache argument to make() to supply a manual or non-default storr cache.
2. Separate plans and a single cache. Here, you would need to ensure that each plan has a completely unique set of targets. If there is overlap, then some targets will always rebuild whenever your run the report.
3. A single cumulative plan. Essentially, when it comes time to build additional targets as you move through the report, you can add new rows to an existing plan. In fact, this is the recommended approach for large complex projects (related example here). For even more control, use the targets argument to make() to only build a select few targets and their out-of-date dependencies.

Answer 2

I’m not sure i understand the question? We often use drake in jupyter notebook, and do try to support that use case (via the python bindings).

By “plans”, do you mean mathematical programs? Or inverse kinematics calls? Both should be ok in a notebook framework. Or are you actually calling them in parallel?

Not sure how R fits into it?