Reticulate not accessing data when using within Shiny-CodePudding

i'm trying to execute some python class object (using reticulate) which works fine when i'm using it outside of Shiny, but when i run my script within Shiny I get the following error message 'Warning: Error in py_run_string_impl: RuntimeError: Evaluation error: object 'pydata2' not found.' ('pydata2' is a dataframe that is actually created ok, I can print it etc so I don't understand why it says it's missing..). My code is a bit long but i've made a mention where it works until (#all fine until here!). I suspect that the problem is that the command r.pydata2 does not seem to work within Shiny (it does work outside of Shiny so it's strange) ?

Thank you in advance if someone can help!

library(dplyr)
library(shinyWidgets)
library(shinythemes)
library(DT)

fpath <- '/dbfs/dbfs/ShinyApp'

# Define UI
ui <- fluidPage(
  theme = shinytheme("spacelab"),
  navbarPage(
    "APP Platform",
    tabPanel(
      "Select File",
      sidebarPanel(
        selectInput("selectfile", "Select File", choice = list.files(fpath, pattern = ".csv")),
        mainPanel("Main Panel", dataTableOutput("ftxtout"), style = "font-size:50%") # mainPanel
      ), # sidebarPanel
    ), # tabPanel
    tabPanel(
      "Subset Data",
      sidebarPanel(
        dropdown(
          size   = "xs",
          label  = "Please Select Columns to Display",
          icon   = icon("sliders"),
          status = "primary",
          pickerInput(
            inputId  = "columns",
            #       label = "Select Columns",
            choices  = NULL,
            multiple = TRUE
          ) # pickerInput
        ), # dropdown
        selectInput("v_attribute1", "First Attribute to Filter Data", choices = NULL),
        selectInput("v_attribute2", "Second Attribute to Filter Data", choices = NULL),
        selectInput("v_filter1", "First Filter", choices = NULL),
        selectInput("v_filter2", "Second Filter", choices = NULL),
        textInput("save_file", "Save to file:", value = ""),
        actionButton("doSave", "Save Selected Data"),
        actionButton("doBert", "Run Bert Model")
      ), # sidebarPanel
      mainPanel(
        tags$br(),
        tags$br(),
        h4("Data Selection"),
        dataTableOutput("txtout"),
        style = "font-size:70%"
      ), # mainPanel
      mainPanel(
        tags$br(),
        tags$br(),
        h4("Topic Words"),
        dataTableOutput("topicwrds"),
        style = "font-size:70%"
      ) # mainPanel
      
      
    ), # Navbar 1, tabPanel
    tabPanel("Create Label", "This panel is intentionally left blank")
  ) # navbarPage
) # fluidPage


# Define server function
server <- function(input, output, session) {
  # DECLARE REACTIVEVALUES FUNCTION HERE
  rResult <- reactiveValues(df_sub = NULL , r_top_words2 = NULL, r_output=NULL)
  
  output$fileselected <- renderText({
    paste0("You have selected: ", input$selectfile)
  })

  info <- eventReactive(input$selectfile, {
    fullpath <- file.path(fpath, input$selectfile)
    read.csv(fullpath, header = TRUE, sep = ",")
  })

  observeEvent(info(), {
    df <- info()
    vars <- names(df)
    # Update select input immediately after clicking on the action button.
    updatePickerInput(session, "columns", "Select Columns", choices = vars, selected = vars[1:2])
  })

  observeEvent(input$columns, {
    vars <- input$columns
    updateSelectInput(session, "v_attribute1", "First Attribute to Filter Data", choices = vars)
    updateSelectInput(session, "v_attribute2", "Second Attribute to Filter Data", choices = vars, selected = vars[2])
  })

  observeEvent(input$v_attribute1, {
    choicesvar1 <- unique(info()[[input$v_attribute1]])
    req(choicesvar1)
    updateSelectInput(session, "v_filter1", "First Filter", choices = choicesvar1)
  })

  observeEvent(input$v_attribute2, {
    choicesvar2 <- unique(info()[[input$v_attribute2]])
    req(choicesvar2)
    updateSelectInput(session, "v_filter2", "Second Filter", choices = choicesvar2)
  })

  output$ftxtout <- renderDataTable(
    {
      head(info())
    },
    options = list(pageLength = 5)
  )

  output$txtout <- renderDataTable(
    {
      f <- info() %>% subset(select = input$columns)
      f$var1 <- f[[input$v_attribute1]]
      f$var2 <- f[[input$v_attribute2]]
      ff <- f %>% dplyr::filter(var1 == input$v_filter1 & var2 == input$v_filter2)
      fff <- ff %>% subset(select = -c(var1, var2))
      head(fff)
    },
    options = list(pageLength = 5)
  ) # renderDataTable

  # Saving data
  observeEvent(input$doSave, {
    req(
      input$columns, input$v_attribute1,
      input$v_attribute2, input$v_filter1,
      input$v_filter2, input$save_file
    )
    df <- info() %>% select(all_of(input$columns))
    df_filtered <- df %>%
      dplyr::filter(
        .data[[input$v_attribute1]] == input$v_filter1 &
          .data[[input$v_attribute2]] == input$v_filter2
      )
    fullfpath <- paste0(file.path(fpath, input$save_file), ".csv", sep = "")
    write.csv(df_filtered, fullfpath, row.names = TRUE)
    showNotification(paste("Data Has been saved"), duration = NULL)
    rResult$df_sub <-df_filtered #passed to other object below
  })
  
  observeEvent(input$doBert, {
  pydata2=rResult$df_sub
  showNotification(paste("pydata2 loaded"), duration = NULL) #all fine until here!
py_run_string("
pydata=r.pydata2
pipeline=RunBert(pydata[\"transcript\"],pydata[\"conversation_id\"],36)
pipeline.get_ready_docs()
pipeline.create_model()
top_words=pipeline.get_top_words()
output = pipeline.get_output()
                 ")
# rResult$r_output <-py$output
# rResult$r_top_words2 <-py$top_words
showNotification(paste("Topic have been run"), duration = NULL)
# output$topicwrds <- renderDataTable({rResult$r_top_words2},options = list(pageLength = 5))
  })
} # server

# Create Shiny object
shinyApp(ui = ui, server = server)

CodePudding user response：

The problem is that pydata2 is scoped only locally. python can only access global variables through r..

Thus, you have to define pydata2 on global scope. Yet a better way would be to define a python function which accepts your data as an argument and returns whatever is needed. Then you do not have to pollute your global environment with a copy of pydata2.

This sample code illustrates the problem behind and shows

how to use assign to circumvent it
how to use a function to avoid spamming the .GlobalEnv

library(shiny)
library(reticulate)

globally <- "I am defined globally"

ui <- fluidPage(
  fluidRow(
    actionButton("run", "Run!")
  ))

server <- function(input, output, session) {
  observeEvent(input$run, {
    locally <- "I am defined locally"
    assign("local_globally", "I am defined locally but in global scope", envir = .GlobalEnv)
    script1 <- paste("try:",
      "   print(r.globally)",
      "   print(r.local_globally)",
      "   print(r.locally)",
      "except Exception as inst:",
      "   print(inst)", sep = "\n")
    script2 <- paste("def fun(x):",
                     "   return(x)", sep = "\n")
    py_run_string(script1)
    py_run_string(script2)
    print(py$fun(locally))
  })
}

shinyApp(ui, server)

The output on the cosole after pressing the actionButton is:

I am defined globally

I am defined locally but in global scope

Evaluation error: object 'locally' not found.

[1] "I am defined locally"