(AKA “Installating minicom on a Mac”)
If you’ve read the official documentation for the Pico Python SDK, you’ll have seen that in order to connect your Mac to the python REPL running on the Pico you need a serial interface program. The docs suggest the aptly named “Serial” which looks great, but is not cheap.
Being a frugal hacker, you might prefer to use an open source tool instead.
Well, help is at hand!
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The plumber package is great for creating APIs in R, but it has a coupe of lesser known tricks up it’s sleeve and I wanted to talk about one of those today.
In the modern web-based world, you sometimes just need a simple web server to serve HTML pages or other content across the network.
Fortunately, plumber can help. The goal here is to take a directory of content, such as HTML, CSS and javascript and create a web server that will serve that directory of content to users on the same network.
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Big (but mostly invisible) changes to awesome-blogdown.com which now uses GitHub Actions!
A couple of years ago I wrote about how awesome-blogdown.com works. Since then, it’s been ticking along nicely with very little intervention from me, which is exactly what I was aiming for.
Life goes on though, and over time things change. In particular for this story, the changes relate to all the automation tools I was using behind the scenes.
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I originally posted this to twitter, but figured a more permanent home might be useful.
A quick post on managing remote teams for anyone new to it amid the fast-evolving Coronavirus/Covid-19 situation:
Be intentional. You can’t rely on ad-hoc office chitchat to stay on top things. Have regular check-ins and catch-ups with your team.
Cameras on. It feels really weird at first, but being able to see people helps to maintain social bonds and provides useful clues for when people are about to speak and so on.
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I’ve been asked a few times recently about the prompt I have in my terminal.
It looks like this…
The people who’ve asked me about it have wondered what it shows, how it was done and how they can do it for themselves, so I thought I’d write it up for anyone that might be interested.
What does it show? Each of these things automatically updates (as required) each time you run a command in the terminal.
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I don’t generally write much code where R’s performance is a bottleneck, it’s just not what I do. The way I use R is different to many other people and as such I’ve never had to spend much time thinking about the performance of the language.
A few days ago, while reading an article in Quanta, I became interested in the Collatz Conjecture and I wrote up a little function to test how the conjecture plays out.
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Imagine you want to use data to really understand something about your product, users, market or the world. Along comes the infinitely re-programmable sales droid, promising that their tool or service will solve all your problems.
Whatever that silver bullet solution is probably uses a unique combination of cloud computing and cutting edge artificial intelligence algorithms in a neural network designed to stop you from losing ground against the competition.
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A new version of the R source was released today and so, as is customary, I download and install it on my personal Linux servers. My main server runs Ubuntu and the other run CentOS.
To download, build and install R I use the below script. It relies on you having ‘sudo’ enabled for your account as well as already having the build dependencies installed (see this post from RStudio for more info).
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In my last post, “Lifting the lid on CRAN”, we took a look at how R and CRAN interact to enable R users to install packages. In this post we’re going to dig a little deeper by building our own CRAN-like repo that we can install packages from.
Enterprise R package management Before we get started, I just want to stress that what we’ll learn about here is no substitute for using a product like RStudio Package Manager.
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CRAN is one of the many things that makes R such a great language. For those that don’t know, it’s where R users get the vast majority of the add-on packages that they use with the core language. CRAN also hosts downloads of the language itself, source code, tools and so on, but it’s most well known among users as the place where all the packages come from.
The “CRAN team” are responsible for the ongoing maintenance of CRAN, handle new and updated package submissions and generally ensure everything is running smoothly.
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