#38: Faster Feedback Systems

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Engineers build systems. Good engineers always stress and focus efficiency of these systems.

Two recent examples of engineering thinking follow. One was in a video / podcast interview with Martin Thompson (who is a noted high-performance code expert) I came across recently. The overall focus of the hour-long interview is on ‘managing software complexity’. Around minute twenty-two, the conversation turns to feedback loops and systems, and a strong preference for simple and fast systems for more immediate feedback. An important topic indeed.

The second example connects to this and permeates many tweets and other writings by Erik Bernhardsson. He had an earlier 2017 post on ‘Optimizing for iteration speed’, as well as a 17 May 2022 tweet on minimizing feedback loop size, another 28 Mar 2022 tweet reply on shorter feedback loops, then a 14 Feb 2022 post on problems with slow feedback loops, as well as a 13 Jan 2022 post on a priority for tighter feedback loops, and lastly a 23 Jul 2021 post on fast feedback cycles. You get the idea: Erik really digs faster feedback loops. Nobody likes to wait: immediatecy wins each time.

A few years ago, I had touched on this topic with two posts on how to make (R) package compilation (and hence installation) faster. One idea (which I still use whenever I must compile) was in post #11 on caching compilation. Another idea was in post #13: make it faster by not doing it, in this case via binary installation which skip the need for compilation (and which is what I aim for with, say, CI dependencies). Several subsequent posts can be found by scrolling down the r^4 blog section: we stressed the use of the amazing Rutter PPA ‘c2d4u’ for CRAN binaries (often via Rocker containers, the (post #28) promise of RSPM, and the (post #29) awesomeness of bspm. And then in the more recent post #34 from last December we got back to a topic which ties all these things together: Dependencies. We quoted Mies van der Rohe: Less is more. Especially when it comes to dependencies as these elongate the feedback loop and thereby delay feedback.

Our most recent post #37 on r2u connects these dots. Access to a complete set of CRAN binaries with full-dependency resolution accelerates use and installation. This of course also covers testing and continuous integration. Why wait minutes to recompile the same packages over and over when you can install the full Tidyverse in 18 seconds or the brms package and all it needs in 13 seconds as shown in the two gifs also on the r2u documentation site.

You can even power up the example setup of the second gif via this gitpod link giving you a full Ubuntu 22.04 session in your browser to try this: so go forth and install something from CRAN with ease! The benefit of a system such our r2u CRAN binaries is clear: faster feedback loops. This holds whether you work with few or many dependencies, tiny or tidy. Faster matters, and feedback can be had sooner.

And with the title of this post we now get a rallying cry to advocate for faster feedback systems: “FFS”.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. Please report excessive re-aggregation in third-party for-profit settings.

To leave a comment for the author, please follow the link and comment on their blog: Thinking inside the box .

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