# shinyreprex 

<img src="man/figures/logo.png" width="120" height="120" align="right" alt=""/>

<!-- badges: start -->
[![R-CMD-check](https://github.com/AscentSoftware/shinyreprex/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/AscentSoftware/shinyreprex/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The aim of **shinyreprex** is to be able to recreate any reactive or output that is available in 
a Shiny application outside of said application.

In static documents, like Quarto, it is easy to include the code chunk by including code folding. 
Due to the interactiveness of Shiny, this isn't as easy to include out of the box. Reactive depend on
inputs set by the user, and need to be replaced in the reactive expressions to be able to run in an
environment outside of Shiny.

## Installation

To get the latest version of shinyreprex, install from GitHub:

```r
require(remotes)
remotes::install_github("AscentSoftware/shinyreprex")
```

## Usage

The following examples takes a couple of inputs, and uses one of them in one reactive, and the 
other in another reactive. The second reactive is a table output, which can be passed to 
`reprex_reactive` to re-create the code that generates the table seen in the UI.

```r
library(shiny)
library(shinyreprex)

ui <- fluidPage(
  h1("Reproducible Code Example"),
  inputPanel(
    sliderInput(
      "min_width",
      "Minimum Petal Width",
      min(iris$Petal.Width),
      max(iris$Petal.Width),
      min(iris$Petal.Width),
      step = 0.1
    ),
    selectInput(
      "summary_fn",
      "Summary Function",
      c("Mean" = "mean", "Median" = "median", "SD" = "sd"),
      selected = "mean"
    ),
    actionButton("update", "Update")
  ),
  fluidRow(
    column(
      width = 5,
      h2("Table"),
      tableOutput("table")
    ),
    column(
      width = 7,
      h2("Code"),
      verbatimTextOutput("code")
    )
  )
)

server <- function(input, output, session) {
  iris_filt <- reactive({
    iris[with(iris, Petal.Width > input$min_width), ]
  }) |>
    bindEvent(input$update)

  summary_tbl <- reactive({
    aggregate(
      Sepal.Width ~ Species,
      data = iris_filt(),
      FUN = get(input$summary_fn)
    )
  }) |>
    bindEvent(input$update)

  output$table <- renderTable(summary_tbl())
  output$code <- renderText(reprex_reactive(summary_tbl))
}

shinyApp(ui, server)
```
