Blog Posts by Andrew B. Collier / @datawookie

In a previous post I documented a new feature in {emayili}, the ability to render Plain Markdown directly into the body of an email message.

We’ve been able to attach text and HTML content to messages with {emayili}. But something that I’ve really been wanting to do is render Markdown directly into an email.

In version 0.4.19 I’ve added the ability to directly render Plain Markdown into a message. That version is not on CRAN, so you’ll need to install from GitHub.

At Fathom Data we use Clockify to keep detailed records of the time that we spend working on our clients' projects. Up until fairly recently we manually generated timesheets at the end of each month that were sent through to the clients along with their invoices. Our experience has been that providing detailed timesheets helps foster trust and transparency. However, with a growing team and an expanding clientele, generating these timesheets has become progressively more laborious. Time to automate!

It’s often handy to have access to a HTTP proxy. I use this recipe from time to time to quickly fling together a proxy server which I can use to relay HTTP requests from a different origin.

A small new feature added to {emayili}: the ability to interpolate content into the email message body.

In a previous post I looked at how to set up Websockify behind an NGINX proxy. The ultimate goal was to accommodate multiple simultaneous users. Although the setup in that post worked, if the number of users is large then it becomes very resource hungry because there’s a Websockify instance running for each user.

A recent issue on the {emayili} GitHub repository prompted me to think a bit more about email address validation. When I started looking into this I was somewhat surprised to learn that it’s such a complicated problem. Who would have thought that something as apparently simple as an email address could be linked with such complexity?

I recently moved from suburban South Africa to rural England. I’m figuring out my new environment. Making some maps seemed to be a good way to get familiar with the surroundings.

In the process I wanted to figure out two things:

• how to get maps with a consistent aspect ratio at different latitudes; and
• how to overlay a partially transparent map layer.

To make things more interesting I’ll create maps of both my old and new locations.

This post describes the process of building a custom AMI (Amazon Machine Image) using the AWS CLI. The goal is to automate the entire process, making it completely repeatable.

In the previous post I introduced the {tomtom} package and showed how it can be used for geographic routing. Now we’re going to look at the traffic statistics returned by the TomTom API.