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)
