Publications by The Jumping Rivers Blog
I’m an R user: Quarto or R Markdown?
Earlier this year, Posit (formerly RStudio) released Quarto. Quarto is an open-source scientific and technical publishing system that allows you to weave together narrative text and code to produce high-quality outputs including reports, presentations, websites, and more. One of the main features of Quarto is that it isn’t just built for R. It�...
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December Training Update
If you’re thinking of picking up a new skill in the new year, take a look at our upcoming public training courses! We have plenty of introductory courses coming up, both online and in-person, so you can hit the ground running after the holidays! Whether you want to start from scratch, or improve your skills, Jumping Rivers has a training cour...
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End-to-end testing with shinytest2: Part 1
This is the first of a series of three blog posts about using the {shinytest2} package to develop automated tests for shiny applications. In the posts we will cover the purpose of browser-driven end-to-end tests for a shiny developer, and tools (like {shinytest2}) that help implement them (this post); how to write and run a simple test using {s...
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Stylising your Python code: An introduction to linting and formatting
https://xkcd.com/1513Linting is a process for identifying bugs and stylistic errors in your code. The process is carried out by analysis tools called ‘linters’, which are widely available for every major programming language. Linters will flag issues and style violations in your code, sort of like a spell checker!In addition to linters, th...
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Training course update – Autumn 2022
Here at Jumping Rivers we like to keep our courses up to date so we can bring you training on the latests tools and technologies. To this end, we have recently added two new courses to our listing! Whether you want to start from scratch, or improve your skills, Jumping Rivers has a training course for you.Reporting with QuartoDo you create int...
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Customising figures in Matplotlib
Matplotlib is one of the longest standing and most comprehensive plotting libraries for Python. It is mostly used for creating static plots and its flexible customisation options make it a great choice for creating publication quality graphs.In this blog post we will look at formatting and colourmap customisation in Matplotlib, and how to set ...
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Hello Shiny Python
We would posit (see what we did there) that R-{shiny} has been a boon for data science practitioners using the R language over the last decade. We know that in our Python work, we have certainly been clamouring for something of the same ilk. And whilst there are other frameworks that we also like, streamlit and dash to name a couple, neither of t...
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Python API deployment with RStudio Connect: Flask
This is part one of our three part series Part 1: Python API deployment with RStudio Connect: Flask (this post) Part 2: Python API deployment with RStudio Connect: FastAPI (to be published) Part 3: Python API deployment with RStudio Connect: Streamlit (to be published) RStudio recently announced they are changing to Posit. Their publishing plat...
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API as a package: Logging
This is part two of our three part series Part 1: API as a package: Structure Part 2: API as a package: Logging (this post) Part 3: API as a package: Testing (to be released) Part 1 of this series laid out some ideas for how one might structure a {plumber} application as an R package, inspired by solutions such as {golem} and {leprechaun} for {...
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The Benefits of Learning Data Skills
It will come as no great surprise that here at Jumping Rivers, we are huge advocates for learning data skills. There are many benefits to learning at least some basic data skills, even if you don’t work explicitly with data. We all benefit from some form of data science every day, even if we don’t realise it – the weather forecast is based ...
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