Data science and data engineering with R and Shiny in the cloud

Posts

Automating building and ckecking of renv environments using GitHub Actions

A quick how-to on building renv environments with GitHub Actions.

Happy New Year

Just a ggplot2 decorated tree.

r2lambda update to support multi-file projects and renv projects

A demo of two newly added features in the {r2lambda} R package. How to deploy R projects with multiple files, and how to use the {renv} lockfile to manage dependencies in the AWS Lambda docker image

Noting the differences in deploying R vs Python apps on Posit Connect

Clarifying confusion regarding using GitHub Actions to deploy R and Python Shiny apps

Using uv to manage the environment for a Python Shiny app and setting up a GitHub action to publish it to Posit Connect

A step-by-step guide to work with a Python Shiny app with the help of uv and a GitHub Actions workflow to have it published from GitHub to Posit Connect.

Shiny ducks: connecting to MotherDuck from Shiny

Few notes about getting up and running with Shiny and Mother duck

Few notes on getting R package data from the local library

The missing conventions in the descriptions of packages

Joining the flock from R: working with data on MotherDuck

Using R to connect to MotherDuck, the cloud data warehouse powered by DuckDB.

How to set up development and production environments using AWS Copilot: Example using a `plumber` API.

In this post I dive deep into setting up a dev/stage/prod environment setup for a {plumber} API on AWS AppRunner

A simple workflow for async {shiny} with {mirai}

A module-based approach to simplify async calls in {shiny} apps using {mirai}

A simple workflow for async {shiny} with {callr}

An approach to simplify and standardize async calls in {shiny} apps using {callr}

100 days of Python and R

Random things from 100 days of code challenge.

Deploying Plumber API to AWS Elastic Container Service

Notes on deploying Plumber API to AWS ECS.

How to deploy Shiny application to Digital Ocean using GitHub Actions

A walkthrough on setting up GitHub Actions for automatic deployment of Shiny application to DigitalOcean server running ShinyProxy

How to use buttons in a Reactable widget for navigation in a Shiny application

A few helpful design patterns for navigation in {shiny} applications using buttons in a {reactable} widget

How to use Bootstrap 5 popovers in Shiny applications

A few tips on using bootstrap 5 popovers in Shiny

Data wrangling tricks from the R4DS slack

R4DS slack tips and tricks.

How to use custom icons in Rmd reports and Shiny applications

A workflow on how to create visually pleasing and effective static HTML visualizations of small-scale and heterogenous tabular data

How to set up an R-based AWS Lambda to write to AWS S3 on a schedule

An introduction to working with AWS S3 from R and a step-by-step workflow to set an AWS Lambda functon to save datasets to an S3 bucket on a weekly schedule

Set an R-based AWS Lambda function to run on a schedule

A step-by-step tutorial on how to deploy an R-based AWS Lambda function, how to set it to run on a recurring schedule, how to validate that the execution happens on schedule, and how to clean up. All from the R console.

An R AWS Lambda function to download Tidytuesday datasets

A detailed walk through the steps to prepare a custom R script for deployment as AWS Lambda with the r2lambda package. How to prepare an R script? What are the roles of several key arguments? How to request longer timeout or more memory for a Lambda function? How to parse the response payload returned by the Lambda function?

Test an R-based AWS lambda function locally before deploying to the cloud

Learn how to test an R-based AWS Lambda function locally before deploying it to the cloud using the r2lambda package. This post covers the steps to build, test, and deploy your Lambda function, ensuring it works correctly before using AWS resources.

Using {stevedore} to manage docker-based variant-calling pipelines from R

Docker and stevedore for overcoming usual obstacles in complicated pipelines.

Deploy an R script as an AWS Lambda function without leaving the R console

This post introduces the {r2lambda} package, which simplifies the process of deploying R scripts as AWS Lambda functions. It automates the steps of creating a Docker image, pushing it to AWS ECR, and creating the Lambda function, all from within the R console. The post provides a detailed guide on how to use the package, including writing the R script, deploying the Lambda function, and testing it. Additionally, it covers the necessary system and R dependencies, AWS configuration, and installation steps. The post concludes with a demo run and a discussion of future improvements for the package.

Rstudio in the cloud for those of us with old laptops part 2: automating with terraform

In this post, we automate the process of setting up an RStudio server on AWS EC2 using Terraform. This guide covers the prerequisites, writing the Terraform configuration, and extending it to install R and RStudio server on the instance.

Rstudio in the cloud for those of us with old laptops

A guide on setting up Rstudio server on an AWS EC2 instance for users with older laptops, including steps for installation, configuration, and secure access.

Getting Google Analytics data in R the long way

An overview of how to work with dbt and Big Query to analyze Google Analytics data

Python dashboards after Shiny for Python

Exploring other dashboarding option in Python

Packaging a Python Shiny app

A step-by-step guide on how to package a Python Shiny app, including directory structure, necessary files, and commands to build and run the package.

Using Wikidata to draw networks of Politically Exposed Persons #2

Building a PyShiny app for displaing data from Wikidata

Using Wikidata to draw networks of Politically Exposed Persons #1

Introduction on getting data from Wikidata using python

How to invoke an AWS Lambda function with R and paws

This post provides a step-by-step guide on how to invoke an AWS Lambda function using R and the {paws} package. It covers setting up AWS credentials, starting a Lambda service, listing available functions, and invoking a specific Lambda function with a payload. The post also includes examples and a custom function to streamline the process.

A {shiny} app to wrap BlasterJS and visualize NCBI BLAST results locally

I recently learned about a really slick JavaScript component for interactive visualization of NCBI’s blast output. BlasterJS (Website, Paper) makes it possible to visualize b…

Using R and {paws} to populate DynamoDB tables #2

How to start on using R with paws to work with AWS DynamoDB, part 2.

Building a multi-session {shiny} application with {brochure}

In this post, I share my experience building a multi-session Shiny application using the {brochure} package. I discuss the advantages of using {brochure} for creating independent Shiny sessions for different pages, the integration with {golem}, and the steps to deploy the application on shinyapps.io. Additionally, I provide a solution for handling URL redirects in different environments.

Using R and {paws} to populate DynamoDB tables

How to start on using R with paws to work with AWS DynamoDB.

Using {shiny.i18n} with {golem} for server-side translation

using-shiny-i18n-with-golem-for-server-side-translation

OpenBudget: A Shiny app for transparent finances in local government in North Macedonia

OpenBudget: A Shiny app for transparent finances in local government in North Macedonia

WindsoraiR package for accessing Windsor.ai API from R

Few notes on the package I wrote for Windsor.ai.

A guide for reproducible data analysis in Macedonian

An overview of the document we produced for the reproducible data analysis workshop.

Few things I learned while writing an R package

On writing my first R package and publishing to CRAN.

Asynchronous background execution in Shiny using callr

This post explores how to handle asynchronous background execution in Shiny applications using the callr package. We discuss the limitations of the current promises implementation in Shiny and demonstrate how to use callr::r_bg to run long computations in the background, allowing users to continue interacting with the app. The post includes example code and a link to a live demo app.

Six months of #rstats workshops in Skopje, and more

Few notes on running R and Python workshops in Skopje.

Using GitHub actions with R: Some notes from our #TidyTuesday setup

Notes on using GitHub Actions with R for our #TidyTuesday setup, including automation of gh-pages publishing and handling dependencies.

Basic visual manupulation of phylogenies in R

Some notes from StackOverflow.