Development

Download free Shiny dashboard templates from Appsilon. Select a ready-to-go template and customize it to add your unique style.

A writeup about the process taken to create a plugin for note app Obsidian.md.

Storing and managing secrets like API keys and other credentials can be challenging. Here are some of the best practices to help keep secrets and credentials safe.

A Python refresher section for all our courses. Contribute to tecladocode/python-refresher development by creating an account on GitHub.

A beginner Python programming course to help you get started!

Typical data-driven web apps need a Database (DB) connection to render almost every page or to serve every API call. For scalability reasons, Web Server and Database servers are hosted on different Machines.

the community's sql powershell module

TLDR; this article covers how to build a package for the PowerShell gallery. This is a great way to share your scripts and modules with others. You want to help the community, right? Of course, you do Here's the steps we are about to take: Author script. First you need to create a script. In this ...

Fast forward merge can be performed when there is a direct linear path from the source branch to the target branch. In fast-forward merge, git simply moves the ...

In certain situations, Git does a fast forward when you merge a branch that is ahead of the branch you have checked out. Learn more here.

Tools for building and working with docker containers in R - GitHub - thebioengineer/dockyard: Tools for building and working with docker containers in R

Determine system requirements from R packages using the RStudio Package Manager. This is a weekend project, not a real package, so please think twice before using it for anything serious. - getsys...

Locking down R package dependencies and versions is a solved problem, thanks to the easy-to-use renv package. System dependencies — those Linux packages that need to be installed to make certain R packages work — are a bit harder to manage. Option 1: Hard-coding The easiest option is to hard-code the system dependencies. I did this recently when I was creating a Dockerfile for a very simple Plumber API: RUN apt-get update -qq && apt-get -y --no-install-recommends install \ make \ libsodium-dev \ libicu-dev \ libcurl4-openssl-dev \ libssl-dev My Dockerfile used only three R packages and so its system dependencies were not complicated.

I went down a strange path recently, trying to compile binaries of R packages for Linux. I’m not sure why — this area is pretty much covered by the RStudio Package Manager. I’ll leave my Dockerfiles here in case they’re of any use to a future wayward R programmer. The intention here is to build a Docker image that can build an R binary with the below command. I’m trying to build x86 binaries on my ARM Macbook, so I’m specifying the platform during both build and run.

AWS has announced support for container images for their serverless computing platform Lambda. AWS doesn’t provide an R runtime for Lambda, and this was the excuse I needed to finally try to make one. An R runtime means that I can take advantage of AWS Lambda to put my R functions in the cloud. I don’t have to worry about provisioning servers or spinning up containers — the function itself is the star.

An attempt to get an R runtime and function working on AWS Lambda using a container. - r-on-lambda/Dockerfile at main · mdneuzerling/r-on-lambda

A collection of awesome rShiny packages, tools, addons and examples

CLIs are a fantastic way to build products. Unlike web applications, they take a small fraction of the time to build and are much more…

lambdr

A (somewhat) currated list of resources for R Shiny - GitHub - dpastoor/awesome-shiny: A (somewhat) currated list of resources for R Shiny