Publications by Posts on Tychobra
Meet T3 – Tychobra Time Tracker
Raison d’être At Tychobra, like many consulting businesses, we have multiple projects for multiple clients being worked on by multiple developers. To keep everything tracked to double precision, and because we love the taste of dog food, we built our own time tracking system using Shiny and our R package for authentication, Polished. How it w...
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Shiny CRUD
NOTE: This post assumes knowledge of R and Shiny and some familiarity with databases. If you are new to R and Shiny, there are great learning resources at https://shiny.rstudio.com/. If you are comfortable with R and Shiny, but the idea of persistent data storage is new to you, then first read Dean Attali’s excellent post on persistent data sto...
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shinyFeedback 0.2.0 CRAN Release
I am excited to announce that shinyFeedback 0.2.0 is on its way to CRAN (it may take a day or 2 for it to be available on your CRAN mirror). shinyFeedback is an R package that allows you to easily display user feedback in Shiny apps. shinyFeedback’s primary user feedbacks are displayed alongside Shiny inputs like this: shinyFeedback 0.2.0 unde...
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Auditable Database Storage… What’s Different?
This is a followup post to the Shiny CRUD blog post. The Shiny CRUD blog post covers how to build a Shiny app that is capable of Creating, Reading, Updating, and Deleting records from a database. This post describes an auditable alternative to CRUD. Auditable data storage requires that you never lose any information; the historical state of the d...
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Using XGBoost with Tidymodels
Background XGBoost is a machine learning library originally written in C++ and ported to R in the xgboost R package. Over the last several years, XGBoost’s effectiveness in Kaggle competitions catapulted it in popularity. At Tychobra, XGBoost is our go-to machine learning library. François Chollet and JJ Allaire summarize the value of XGBoost ...
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My Favorite dplyr 1.0.0 Features
As you are likely aware by now, the dplyr 1.0.0 release is right around the corner. I am very excited about this huge milestone for dplyr. In this post, we’ll go over my favorite new features coming in the 1.0.0 release. # Install development version of dplyr remotes::install_github( "tidyverse/dplyr", ref = "23c166fa7cc247f0ee1a4ee5ac31cd...
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Introducing Polished.tech
Polished.tech is our new software service that makes it easier than ever to add modern authentication to your Shiny apps. Implementing authentication from scratch is inefficient and increases the probability of security vulnerabilities. Hand rolling custom logic to encrypt credentials, reset passwords, verify email addresses, etc. is a tedious, ...
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Experiences Building a Production Shiny App for Mobile
A few months back we had the pleasure of working with Axion Biosystems to develop a mobile first shiny application. The app is called “Maestro Z”, and Axion ended up making a couple commercial advertisements for it (one magazine ad and a video). We are very happy with how the app turned out, and we were thrilled to see a Shiny app we built fe...
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A Dashboard of Shiny Apps
We build a lot of Shiny apps. Once we have more than a couple related Shiny apps, it often makes sense to create a dashboard for our Shiny apps. A dashboard of Shiny apps allows users to easily visualize available apps and navigate between apps. This post covers a simple example of one of these dashboards of Shiny apps. The Shiny apps dashboard l...
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New Polished Feature – Email Templates
Polished is an R package that adds authentication and user administration to your Shiny apps. We are constantly working to make polished easier to set up and more useful (once set up). Most recently, we reworked the user invite flow to send email invites when inviting new users to your Shiny app. As a user of polished, you can send an email invi...
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