Andrew B. Collier / @datawookie

I’m building a model which requires historical weather data from a selection of locations in South Africa. In this post I demonstrate the process of acquiring the data and doing some simple processing.

I occasionally write scripts where I need to persist some information between runs. These scripts are often wrapped in a Docker image and deployed on Amazon ECS. This means that there is no persistent storage. I could use a database, but this would be overkill for the volume of data involved. This post describes a simple approach to storing these data on S3 using a pickle file.

Introducing the nascent R package {blimey} (repository). At this stage it contains only the following data:

• railways — latitude and longitude segments along railway lines (wide format);
• railways_pivot — latitude and longitude segments along railway lines (long format); and
• railway_stations — codes, names and locations of railway stations.

In this post I show how to connect to the Interactive Brokers API from MATLAB. The “obvious” way generates a SSL error. This is an alternative approach using the system curl command. It’s a bit of a hack but it does the job.

The Interactive Brokers Client Portal API Gateway provides access to a REAST API for IBKR accounts. It makes it possible to retrieve account information, manage portfolios, execute trades, and access market data via standard HTTP requests.

In a previous post I documented my local setup for accessing the Interactive Brokers API via their Gateway application. I’m now in a position where I need to deploy my code onto a VM. My local setup will no longer suffice.

A brief tutorial on setting up the Interactive Brokers Gateway on Linux.

In the previous post I ran through the process of setting up a Mailfence account for encrypting emails using asymmetric encryption. In this post I show how Mailfence can be used with the {emayili} package for sending encrypted email from R.

If you’re thinking about using encrypted email, then Mailfence appears to be a pretty good option for getting started in a relatively painless way.

In a previous post I described a recipe for setting up GitLab Runner using a Docker container. With that setup it was possible to register multiple runners on a single container. However, each runner needed to be registered manually. This setup makes complete sense if the container will be around for a while. But what if you’re spinning up a GitLab Runner container for only a short duration? In this case it might be preferable to have the container pre-configured (or at least easily configured) to provide a runner to a specific project or group. Setting that up is the goal of this post.

Materialised views are a great alternative to views if the underlying query takes a long time to run. However, the principle problem with materialised views is that their content gets stale… and if the database is active, then it gets out of date rather quickly. Sure you can manually refresh a materialised view, but who has the discipline or time to do that? Better to automate the process. Then you can safely forget about it, secure in the knowledge that the data in the materialised view will remain current.

I’ve just started collaborating on a new project, Votela, with Luke. We’re going to be using Firestore for stashing our data. I’ve never worked with Firestore before, so one of my first tasks was just figuring out how to get connected and how to shift some data to and from the database.

Drug pricing is complicated. In this post I take a look at reconciling ASP and WAC prices, focusing on normalising the WAC price per billing unit to achieve a price which is comparable to ASP. This post includes a number of case studies with the objective of laying out and testing a methodology for understanding and dealing with these data. There’s a fair amount of repetition, but I wanted to test the approach across a number of drugs.

A recent announcement from Google stated that from 30 May 2022 they will no longer support login via username and password (this is the “less secure” option). The change will have an impact for people using the {emayili} package to send email from R, but will also affect many others who use this form of authentication to access their emails via desktop email clients. In this short post I detail how to work around this by using an application password.

I use Continuous Integration (CI) extensively across almost all of my remote Git repositories. These are the typical jobs which it’s used for:

• running tests
• building documentation and
• acquiring data.

This post addresses the last item, acquiring data.

If you have database tables in which you are frequently adding or updating data, then it can be useful to have columns which indicates precisely when a specific record was created and updated.

I’ve been using the image registry on GitLab for quite a while now and loved the convenience of having my images living in the same place as my code. However, recently GitLab introduced a soft limit on transfers and that’s cramping my style. I’m moving a lot of my images onto Amazon Elastic Container Registry (ECR). In this post I look at how to get this set up.

At Fathom Data we tend to do quite a lot of web scraping. At the moment I’m working on a small project which requires assembling a large selection of RSS feeds. Aggregator sites (like Feedspot and Feedly) have extensive, carefully curated lists of RSS feeds. As we’ll see below, the underlying lists are not entirely trivial to access.

This is the recipe I use to upgrade R on a Linux box. It’s something that I do fairly frequently on fresh EC2 instances.

Services like Mailchimp and MailerLite make it easy to create stylish email campaigns. Their templating tools allow you to create elegant HTML messages which are personalised to the recipient.

Wouldn’t it be cool if you could do something similar when sending emails from R? Well, with the latest version of {emayili}, that’s now possible (although this feature is definitely in its infancy!).