Writing R in VSCode: A Fresh Start - Kun Ren's Blog Posts

R
John Blischak's blog: R programming in the Windows Subsystem for Linux
A comprehensive guide to setup an R development environment for Ubuntu running
in the Windows Subsystem for Linux (WSL)
sol-eng/db-dashboard
Serverless R functions with Cloud Run
Using serverless containers to deploy scalable R functions.
Effectively Deploying and Scaling Shiny Apps with ShinyProxy, Traefik and Docker Swarm | databentobox
This post provides a guide to effectively and securely scale your ShinyProxy deployment of shiny apps in production with Docker Swarm and Traefik
R in Prod: rip, a command line R package installer | sellorm
Supplement to Shiny in Production
This document is full of supplemental resources and content from the Shiny in Production Workshop delievered at rstudio::conf 2019.
Field Guide to the R Ecosystem
This guide aims to introduce the reader to the main elements of the R ecosystem.
dreamRs/shinypop: Collection of notifications, confirm dialogs and alerts for 'Shiny' applications
Collection of notifications, confirm dialogs and alerts for 'Shiny' applications - dreamRs/shinypop
Structured Errors in Plumber APIs
If you’ve used the Plumber package to make R models
or other code accessible to others via an API, sooner or later you will need to
decide how to handle and report errors.
By default, Plumber will catch R-level errors (like calls to stop()) and
report them to users of your API as a JSON-encoded error message with HTTP
status code 500 – also known as Internal Server Error. This might look
something like the following from the command line:
$ curl -v localhost:8000/
> GET /status HTTP/1.1
> Host: localhost:8000
> User-Agent: curl/7.64.0
> Accept: */*
>
< HTTP/1.1 500 Internal Server Error
< Date: Sun, 24 Mar 2019 22:56:27 GMT
< Content-Type: application/json
< Date: Sun, 24 Mar 2019 10:56:27 PM GMT
< Connection: close
< Content-Length: 97
<
* Closing connection 0
{"error":["500 - Internal server error"],"message":["Error: Missing required 'id' parameter.\n"]}
There are two problems with this approach: first, it gives you almost zero
control over how errors are reported to real users, and second, it’s badly
behaved at the protocol level – HTTP status codes provide for much more
granular and semantically meaningful error reporting.
In my view, the key to overcoming these problems is treating errors as more than
simply a message and adding additional context when they are emitted. This is
sometimes called structured error handling, and although it has not been
used much historically in R, this may be changing.
As you’ll see, we can take advantage of R’s powerful condition system to
implement rich error handling and reporting for Plumber APIs with relative ease.
Functions Similar to VLOOKUP in Excel • lookup
Simple functions to lookup items in key-value pairs. See Mehta (2021) .
Plumber and the Slack API - RStudio :: Solutions
Using Plumber to create APIs for R programs
Learn how to use the open-source tool Plumber to create RESTful APIs for R programs.
REST API with R - Ger Inberg
Learn how to create a REST API in R using the plumber package.
Isochrone - OpenStreetMap Wiki
Where to place DB connections within plumber APIs? - R Admins / RStudio Connect - RStudio Community
Best practices for API packages
mischelper/misc.R at master · jimsforks/mischelper
Plumber + Shiny + Docker
How to dockerize a Shiny app that calls a Plumber API
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.
Automatically Searching Github Repos by Topic - Chemometrics & Spectroscopy using R
Organisation of a collaborative project for PROPRE publication - Rtask
The R task Force - R experts for all your needs
Using Kubernetes and the Future Package to Easily Parallelize R in the Cloud – R-Craft
This is a guest post by Chris Paciorek, Department of Statistics, University of California at Berkeley. In this post, I’ll demonstrate that you can easily use the future package in R on a cluster of machines running in the cloud, specifically ...
Impressions from New Zealand’s R Exchange | RStudio Blog
In March of 2021, Epi-Interactive hosted one of the first in-person R events in Wellington, New Zealand. Here are some takeaways from their experience.
Using Kubernetes and the Future Package to Easily Parallelize R in the Cloud
This is a guest post by Chris Paciorek, Department of Statistics, University of California at Berkeley. In this post, I’ll demonstrate that you can easily use the future package in R on a cluster of machines running in the cloud, specifically on a Kubernetes cluster. This allows you to easily doing parallel computing in R in the cloud. One advantage of doing this in the cloud is the ability to easily scale the number and type of (virtual) machines across which you run your parallel computation.
Plumber Logging · R Views
Routing & Input • plumber
plumber
plumber-logging/app.R at master · sol-eng/plumber-logging
An opinionated example for implementing logging in Plumber APIs - sol-eng/plumber-logging
sol-eng/plumber-logging: An opinionated example for implementing logging in Plumber APIs
An opinionated example for implementing logging in Plumber APIs - sol-eng/plumber-logging
Routing & Input • plumber
plumber