metashiny is an R package that provides a point-and-click interface to quickly design, prototype, and deploy essential Shiny applications without having to write one single line of R code. The core idea behind metashiny is to parametrize Shiny modules, which are reusable units of Shiny logic with their own namespace. Instead of modifying a module to fit various analytical needs, metashiny strives to build a module template that encompasses a wide range of popular Shiny logic, then uses a "meta"-Shiny interface to collect user requirements and customize the Shiny modules using these inputs as parameters. The customized Shiny modules are embedded in the "meta"-Shiny for preview, may be downloaded in a self-contained, functioning Shiny directory and may be deployed to a Shiny Server with minimal configuration. metashiny may be very useful in the initial design phase of Shiny products. Finally, an important feature for non-R users is it eliminates the need of learning Shiny code and the R environment, thus enables analytical colleagues from all backgrounds to explore the fantastic power of Shiny.
Bo Wang
Novartis
metashiny: build Shiny apps with a Shiny app
metashiny is an R package that provides a point-and-click interface to quickly design, prototype, and deploy essential Shiny applications without having to write one single line of R code. The core idea behind metashiny is to parametrize Shiny modules, which are reusable units of Shiny logic with their own namespace. Instead of modifying a module to fit various analytical needs, metashiny strives to build a module template that encompasses a wide range of popular Shiny logic, then uses a "meta"-Shiny interface to collect user requirements and customize the Shiny modules using these inputs as parameters. The customized Shiny modules are embedded in the "meta"-Shiny for preview, may be downloaded in a self-contained, functioning Shiny directory and may be deployed to a Shiny Server with minimal configuration. metashiny may be very useful in the initial design phase of Shiny products. Finally, an important feature for non-R users is it eliminates the need of learning Shiny code and the R environment, thus enables analytical colleagues from all backgrounds to explore the fantastic power of Shiny.