Hosting Patterns for Shiny Apps
There are four types of hosting patterns for Shiny apps: local, dockerized, Shiny Server, and Shiny Server inside Docker. Here is what you need to know if you want to self-host Shiny apps.
Articles by Peter Solymos
Running Shiny Server in Docker
The dockerized Shiny Server is a heavyweight hosting option that plays an important role in the Shiny hosting landscape.
Using systemd to Run Shiny Apps
Shiny is a fully capable web server that can directly be deployed and served to users with standard Linux tools like systemd.
Host Shiny Apps with Docker
A very basic setup to host your Shiny apps with Docker over HTTPS using your custom domain.
Best Practices for R with Docker
How following a few basic suggestions for writing Dockerfiles can hugely improve the developer experience and the quality of the final Docker images.
File Transfer Based Publishing for Shiny Apps
The open-source Shiny Server is an easy way to self-host Shiny apps on a low-cost virtual machine. Set up the server yourself or use an existing image and deploy apps in seconds.
Securing Shiny Server with Caddy
Caddy server makes it super easy to obtain TLS certificates for your custom domain and to serve Shiny apps securely over HTTPS on top of the open-source Shiny Server.
Dockerized Shiny Apps with Dependencies
The wealth of contributed R packages can supercharge Shiny app development. This also means that you have to manage these dependencies. Learn about dependency management when working with R and Docker.
Push Button Publishing for Shiny Apps
Deploying Shiny apps can be as easy as clicking a button. Deploy to the cloud using Shinyapps.io or to your own servers running RStudio Connect with a click of a button.
Dockerizing Shiny Applications
Docker provides isolation to applications. Images are immutable. Running multiple instances of the same image can serve many users at the same time. All these general advantages of containerized applications apply to Shiny apps too.
Run Shiny Apps Locally
You might be eager to deploy your Shiny app to a remote server. But the simplest way to run a Shiny app is to run it locally. You only need the shiny R package installed, and you can run the app in your browser.
The Best Resources for Learning Shiny App Development
The Hosting Data Apps website is dedicated to help you learn about your hosting options. As outlined in the opening post, data app development related content is kept to a minimum. In this post we list resources that provide accessible introduction to Shiny app development.
The Anatomy of a Shiny Application
Shiny lets you quickly build web applications using the R programming language. In this post I will walk you through how a Shiny application is structured. The goal is simply to have the most basic and dependency free app that we can deploy. Let's get going! [Read more...]
Introducing the bSims R package for simulating bird point counts
The bSims R package is
a highly scientific and utterly addictive bird point count
simulator. Highly scientific, because it implements a spatially explicit
mechanistic simulation that is based on statistical models widely used
in bird point count analysis (i.e. removal models, distance sampling),
and utterly addictive because the implementation ...
Fitting removal models with the detect R package
In a paper recently published in the Condor, titled Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity, we assessed different ways of controlling for point-count duration in bird counts using data from the Boreal Avian Modelling Project. As the title ... [Read more...]
Fitting removal models with the detect R package
In a paper recently published in the Condor, titled Evaluating time-removal models for estimating availability of boreal birds during point-count surveys: sample size requirements and model complexity, we assessed different ways of controlling for point-count duration in bird counts using data from the Boreal Avian Modelling Project. As the title ...
Shiny slider examples with the intrval R package
The intrval R package is lightweight (~11K), standalone (apart from importing from graphics, has exactly 0 non-base dependency), and it has a very narrow scope: it implements relational operators for intervals — very well aligned with the tiny manifesto. In this post we will explore the use of the package in two ... [Read more...]
Shiny slider examples with the intrval R package
The intrval R package is lightweight (~11K), standalone (apart from importing from graphics, has exactly 0 non-base dependency), and it has a very narrow scope: it implements relational operators for intervals — very well aligned with the tiny manifesto. In this post we will explore the use of the package in two ... [Read more...]
Phylogeny and species traits predict bird detectability
It all started with this paper in Methods in Ecol. Evol. where we looked at
detectability of many species. So we wanted to use life history
traits to validate our results. But we had to cut the manuscript,
and there was this leftover with some neat patterns, but without much ...
PVA: Publication Viability Analysis, round 3
A friend and colleague of mine, Péter Batáry
has circulated news from Nature
magazine about the EU freezing innovation funds to Bulgaria.
The article had a figure about publication trends for
Bulgaria, compared with Romania and Hungary.
As I have blogged about such trends in ecology before
(here ... [Read more...]
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