Similarly to shiny, shiny.semantic works well with other popular R packages.
Let’s see how to create a simple application with plotly.
library(shiny)
library(shiny.semantic)
library(plotly)
ui <- semanticPage(
  segment(
    class = "basic",
    a(class="ui green ribbon label", "Plotly demo"),
    plotlyOutput("plot")
  )
)
server <- function(input, output, session) {
  output$plot <- renderPlotly({
    plot_ly(economics, x = ~date, color = I("black")) %>%
      add_lines(y = ~uempmed) %>%
      add_lines(y = ~psavert, color = I("red"))
  })
}
shinyApp(ui = ui, server = server)
And now let’s have a look at similar example, but with leaflet.
library(shiny)
library(shiny.semantic)
library(leaflet)
ui <- semanticPage(
  segment(
    class = "basic",
    a(class="ui blue ribbon label", "Leaflet demo"),
    leafletOutput("map")
  )
)
server <- function(input, output, session) {
  output$map <- renderLeaflet({
    m <- leaflet() %>% addTiles()
    m <- m %>% setView(21.00, 52.21, zoom = 12)
    m
  })
}
shinyApp(ui = ui, server = server)
To add some neat Fomantic styling to your DT table you need to use
semantic_DT wrapper.
 library(shiny)
 library(shiny.semantic)
 ui <- semanticPage(
   h2("Pretty tables in Shiny Semantic"),
   semantic_DTOutput("table")
 )
 server <- function(input, output, session) {
   output$table <- DT::renderDataTable(
     semantic_DT(mtcars)
   )
 }
 shinyApp(ui, server)