This is a really quick one, as we use this trick a lot when working remotely, but we always have to scrabble around to find the info!
We use the open source OpenVPN for our office VPN. In general it’s great, however when working away from the office, it’s configured such that any request for a resource first checks outside of the firewall to see if it can access it. If it can, it does, no VPN involved.
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This post originally appeared on the Mango blog, here - http://www.mango-solutions.com/wp/2017/02/production-r-at-ons/
I’ve recently been working at the Office for National Statistics, under the very broad umbrella of a SAS to R transition project.
As you might imagine, ONS, as the UK’s largest producer of official statistics, has a huge number of internal statistical applications, so it’s not possible to “simply” switch from SAS to R. Working with various product owners and maintainers, a small team from Mango were able to perform a deep dive into a few of their existing applications which rely on SAS for statistical processing, and identify some likely candidates for proof of concept transitions.
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If you were in an environment where you have R running on server on a secure LAN with no internet access, you’ll be familiar with the situation outlined in the image above. R is running in an environmnet where there is no internet access, and you’re therefore unable to install anything from CRAN. This is common in many large organisations where the security of the systems is more important than end user convenience.
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ODSC London, October 2016 For some reason the audio is really bad for the first couple of minutes, and the projector kept glitching when I tried to run the demos, but apart from that, it was great!
The issues with the projector actually only lasted a couple of minutes (before I dropped all the demos) but it felt like ages! If you’ve ever given a talk that didn’t go according to plan you’ll probably know how that feels.
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I completely forgot that I made this silly video last year.
It’s terrible quality, but it basically shows me using a Shiny gadget that I wrote to control a light in my house, all from the comfort of the RStudio IDE.
Obvioulsy that’s not really what Shiny gadgets were intended for, but it’s always fun to to do odd things with cool technologies!
The gadget itself is written to take advantage of the super simple API’s that I wrote for my Energenie Remote Control Project.
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Plumber Launcher Script I use Jeff Allen’s Plumber a lot. If you haven’t seen it and want to start writing APIs in R, I’d strongly encourage you to check it out.
Jeff’s documentation tells you how to start the API that you’ve written, with the following code:
> library(plumber) > r <- plumb("myfile.R") # Where 'myfile.R' is the path to your plumber file > r$run(port=8000) This is fine if you’re working directly in RStudio and want to start your API endpoints running, but what about in a production environment?
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EARL Boston, November 2016 I was really pleased to be asked to speak at EARL Boston again this year. On this occasion I was asked to talk about using R in production and whether it’s really possible/advisable or not.
For those of us within the R Community, it almost seems like a silly question but, based on my experiences working with those outside the community, it can be a very real fear.
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