Mixing
Error publishing shiny app: app.R did not return a shiny.appobj object
0
I'm creating an app with a simple ML model, the work flow is as follow:
1) Read a file.
2) Create a model
3) Plot the prediction and variable importance
Localy, the app is working fine:
But when I try to publish the app, I get following error:
Error in value[[3L]](cond) : app.R did not return a shiny.appobj object.
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Ejecución interrumpida
The error is not telling to me, this is the complete code:
library(shiny)
library(readxl)
library(tidyverse)
library(xgboost)
library(caret)
library(iml)
#### UI
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
tags$hr(),
checkboxInput("header", "Header", TRUE)
),
mainPanel(
plotOutput("plot2", click = "plot_brush"),
plotOutput("plot1", click = "plot_brush")
)
)
)
server <- function(input, output) {
# create mydata as a reactiveVal so that it can be edited everywhere
mydata = reactiveVal()
model <- reactiveValues()
# reactive block is changed with an observe that allows mydata to be updated
# on change of data
observe({
req(input$file1, input$header, file.exists(input$file1$datapath))
data = read.csv(input$file1$datapath, header = input$header)
mydata(data)
})
output$contents <- renderTable({
req(mydata())
#mydata()
})
### test
xgb_trcontrol = trainControl(
method = "cv",
number = 5,
allowParallel = TRUE,
verboseIter = FALSE,
returnData = FALSE
)
xgbGrid <- expand.grid(nrounds = c(10,14), # this is n_estimators in the python code above
max_depth = c(10, 15, 20, 25),
colsample_bytree = seq(0.5, 0.9, length.out = 5),
## The values below are default values in the sklearn-api.
eta = 0.1,
gamma=0,
min_child_weight = 1,
subsample = 1
)
observe({
if ('data.frame' %in% class(mydata()) & !'predicted' %in% names(mydata())){
set.seed(0)
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predicted = predict(xgb_model, select(mydata(),"LotArea","YrSold"))
data = mydata()
data["predicted"] = predicted
mydata(data)
}
#xgb_model
})
output$plot1 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
ggplot(mydata(), aes(x=predicted, y=SalePrice)) + geom_point()
}
})
output$plot2 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predictor = Predictor$new(xgb_model, data = select(mydata(),"LotArea","YrSold"), y = mydata()["SalePrice"])
shapley = Shapley$new(predictor, x.interest = select(mydata(),"LotArea","YrSold")[1,])
shapley$plot()
}
})
}
shinyApp(ui, server)
And a sample of the input data:
https://drive.google.com/file/d/1R8GA0fW0pOgG8Cpykc8mAThvKOCRCVl0/view?usp=sharing
r shiny
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
add a comment |
0
I'm creating an app with a simple ML model, the work flow is as follow:
1) Read a file.
2) Create a model
3) Plot the prediction and variable importance
Localy, the app is working fine:
But when I try to publish the app, I get following error:
Error in value[[3L]](cond) : app.R did not return a shiny.appobj object.
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Ejecución interrumpida
The error is not telling to me, this is the complete code:
library(shiny)
library(readxl)
library(tidyverse)
library(xgboost)
library(caret)
library(iml)
#### UI
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
tags$hr(),
checkboxInput("header", "Header", TRUE)
),
mainPanel(
plotOutput("plot2", click = "plot_brush"),
plotOutput("plot1", click = "plot_brush")
)
)
)
server <- function(input, output) {
# create mydata as a reactiveVal so that it can be edited everywhere
mydata = reactiveVal()
model <- reactiveValues()
# reactive block is changed with an observe that allows mydata to be updated
# on change of data
observe({
req(input$file1, input$header, file.exists(input$file1$datapath))
data = read.csv(input$file1$datapath, header = input$header)
mydata(data)
})
output$contents <- renderTable({
req(mydata())
#mydata()
})
### test
xgb_trcontrol = trainControl(
method = "cv",
number = 5,
allowParallel = TRUE,
verboseIter = FALSE,
returnData = FALSE
)
xgbGrid <- expand.grid(nrounds = c(10,14), # this is n_estimators in the python code above
max_depth = c(10, 15, 20, 25),
colsample_bytree = seq(0.5, 0.9, length.out = 5),
## The values below are default values in the sklearn-api.
eta = 0.1,
gamma=0,
min_child_weight = 1,
subsample = 1
)
observe({
if ('data.frame' %in% class(mydata()) & !'predicted' %in% names(mydata())){
set.seed(0)
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predicted = predict(xgb_model, select(mydata(),"LotArea","YrSold"))
data = mydata()
data["predicted"] = predicted
mydata(data)
}
#xgb_model
})
output$plot1 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
ggplot(mydata(), aes(x=predicted, y=SalePrice)) + geom_point()
}
})
output$plot2 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predictor = Predictor$new(xgb_model, data = select(mydata(),"LotArea","YrSold"), y = mydata()["SalePrice"])
shapley = Shapley$new(predictor, x.interest = select(mydata(),"LotArea","YrSold")[1,])
shapley$plot()
}
})
}
shinyApp(ui, server)
And a sample of the input data:
https://drive.google.com/file/d/1R8GA0fW0pOgG8Cpykc8mAThvKOCRCVl0/view?usp=sharing
r shiny
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
Have you tried splitting the app into two filesuiandserverprior to publishing?
– Philipp R
Jan 3 at 1:23
add a comment |
0
0
0
I'm creating an app with a simple ML model, the work flow is as follow:
1) Read a file.
2) Create a model
3) Plot the prediction and variable importance
Localy, the app is working fine:
But when I try to publish the app, I get following error:
Error in value[[3L]](cond) : app.R did not return a shiny.appobj object.
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Ejecución interrumpida
The error is not telling to me, this is the complete code:
library(shiny)
library(readxl)
library(tidyverse)
library(xgboost)
library(caret)
library(iml)
#### UI
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
tags$hr(),
checkboxInput("header", "Header", TRUE)
),
mainPanel(
plotOutput("plot2", click = "plot_brush"),
plotOutput("plot1", click = "plot_brush")
)
)
)
server <- function(input, output) {
# create mydata as a reactiveVal so that it can be edited everywhere
mydata = reactiveVal()
model <- reactiveValues()
# reactive block is changed with an observe that allows mydata to be updated
# on change of data
observe({
req(input$file1, input$header, file.exists(input$file1$datapath))
data = read.csv(input$file1$datapath, header = input$header)
mydata(data)
})
output$contents <- renderTable({
req(mydata())
#mydata()
})
### test
xgb_trcontrol = trainControl(
method = "cv",
number = 5,
allowParallel = TRUE,
verboseIter = FALSE,
returnData = FALSE
)
xgbGrid <- expand.grid(nrounds = c(10,14), # this is n_estimators in the python code above
max_depth = c(10, 15, 20, 25),
colsample_bytree = seq(0.5, 0.9, length.out = 5),
## The values below are default values in the sklearn-api.
eta = 0.1,
gamma=0,
min_child_weight = 1,
subsample = 1
)
observe({
if ('data.frame' %in% class(mydata()) & !'predicted' %in% names(mydata())){
set.seed(0)
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predicted = predict(xgb_model, select(mydata(),"LotArea","YrSold"))
data = mydata()
data["predicted"] = predicted
mydata(data)
}
#xgb_model
})
output$plot1 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
ggplot(mydata(), aes(x=predicted, y=SalePrice)) + geom_point()
}
})
output$plot2 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predictor = Predictor$new(xgb_model, data = select(mydata(),"LotArea","YrSold"), y = mydata()["SalePrice"])
shapley = Shapley$new(predictor, x.interest = select(mydata(),"LotArea","YrSold")[1,])
shapley$plot()
}
})
}
shinyApp(ui, server)
And a sample of the input data:
https://drive.google.com/file/d/1R8GA0fW0pOgG8Cpykc8mAThvKOCRCVl0/view?usp=sharing
r shiny
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
I'm creating an app with a simple ML model, the work flow is as follow:
1) Read a file.
2) Create a model
3) Plot the prediction and variable importance
Localy, the app is working fine:
But when I try to publish the app, I get following error:
Error in value[[3L]](cond) : app.R did not return a shiny.appobj object.
Calls: local ... tryCatch -> tryCatchList -> tryCatchOne -> <Anonymous>
Ejecución interrumpida
The error is not telling to me, this is the complete code:
library(shiny)
library(readxl)
library(tidyverse)
library(xgboost)
library(caret)
library(iml)
#### UI
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
fileInput("file1", "Choose CSV File",
accept = c(
"text/csv",
"text/comma-separated-values,text/plain",
".csv")
),
tags$hr(),
checkboxInput("header", "Header", TRUE)
),
mainPanel(
plotOutput("plot2", click = "plot_brush"),
plotOutput("plot1", click = "plot_brush")
)
)
)
server <- function(input, output) {
# create mydata as a reactiveVal so that it can be edited everywhere
mydata = reactiveVal()
model <- reactiveValues()
# reactive block is changed with an observe that allows mydata to be updated
# on change of data
observe({
req(input$file1, input$header, file.exists(input$file1$datapath))
data = read.csv(input$file1$datapath, header = input$header)
mydata(data)
})
output$contents <- renderTable({
req(mydata())
#mydata()
})
### test
xgb_trcontrol = trainControl(
method = "cv",
number = 5,
allowParallel = TRUE,
verboseIter = FALSE,
returnData = FALSE
)
xgbGrid <- expand.grid(nrounds = c(10,14), # this is n_estimators in the python code above
max_depth = c(10, 15, 20, 25),
colsample_bytree = seq(0.5, 0.9, length.out = 5),
## The values below are default values in the sklearn-api.
eta = 0.1,
gamma=0,
min_child_weight = 1,
subsample = 1
)
observe({
if ('data.frame' %in% class(mydata()) & !'predicted' %in% names(mydata())){
set.seed(0)
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predicted = predict(xgb_model, select(mydata(),"LotArea","YrSold"))
data = mydata()
data["predicted"] = predicted
mydata(data)
}
#xgb_model
})
output$plot1 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
ggplot(mydata(), aes(x=predicted, y=SalePrice)) + geom_point()
}
})
output$plot2 <- renderPlot({
data = mydata()
# this is here to prevent premature triggering of this ggplot.
# otherwise you'll get the "object not found" error
if('predicted' %in% names(data)){
xgb_model = train(
select(mydata(),"LotArea","YrSold"), as.vector(t(mydata()["SalePrice"])),
trControl = xgb_trcontrol,
tuneGrid = xgbGrid,
method = "xgbTree"
)
predictor = Predictor$new(xgb_model, data = select(mydata(),"LotArea","YrSold"), y = mydata()["SalePrice"])
shapley = Shapley$new(predictor, x.interest = select(mydata(),"LotArea","YrSold")[1,])
shapley$plot()
}
})
}
shinyApp(ui, server)
And a sample of the input data:
https://drive.google.com/file/d/1R8GA0fW0pOgG8Cpykc8mAThvKOCRCVl0/view?usp=sharing
r shiny
r shiny
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
asked Jan 3 at 0:47
Luis Ramon Ramirez RodriguezLuis Ramon Ramirez Rodriguez
1,51173364
1,51173364
Have you tried splitting the app into two filesuiandserverprior to publishing?
– Philipp R
Jan 3 at 1:23
add a comment |
Have you tried splitting the app into two filesuiandserverprior to publishing?
– Philipp R
Jan 3 at 1:23
Have you tried splitting the app into two files
ui and server prior to publishing?– Philipp R
Jan 3 at 1:23
Have you tried splitting the app into two files
ui and server prior to publishing?– Philipp R
Jan 3 at 1:23
add a comment |
1 Answer
1
active
oldest
votes
1
and it worked. Here the app on my shinyapp.io account. Only took a while to upload and to run.
Maybe you'll have to check the applications version. Here's the packages versions I have. I'm on R version 3.5.2 (2018-12-20) and RStudio 1.1.463.
answered Jan 3 at 2:03
alessioalessio
37417
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
add a comment |
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1 Answer
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1 Answer
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active
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active
oldest
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active
oldest
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1
and it worked. Here the app on my shinyapp.io account. Only took a while to upload and to run.
Maybe you'll have to check the applications version. Here's the packages versions I have. I'm on R version 3.5.2 (2018-12-20) and RStudio 1.1.463.
answered Jan 3 at 2:03
alessioalessio
37417
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
add a comment |
1
and it worked. Here the app on my shinyapp.io account. Only took a while to upload and to run.
Maybe you'll have to check the applications version. Here's the packages versions I have. I'm on R version 3.5.2 (2018-12-20) and RStudio 1.1.463.
answered Jan 3 at 2:03
alessioalessio
37417
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
add a comment |
1
1
1
and it worked. Here the app on my shinyapp.io account. Only took a while to upload and to run.
Maybe you'll have to check the applications version. Here's the packages versions I have. I'm on R version 3.5.2 (2018-12-20) and RStudio 1.1.463.
answered Jan 3 at 2:03
alessioalessio
37417
and it worked. Here the app on my shinyapp.io account. Only took a while to upload and to run.
Maybe you'll have to check the applications version. Here's the packages versions I have. I'm on R version 3.5.2 (2018-12-20) and RStudio 1.1.463.
answered Jan 3 at 2:03
alessioalessio
37417
answered Jan 3 at 2:03
alessioalessio
37417
answered Jan 3 at 2:03
alessioalessio
37417
answered Jan 3 at 2:03
alessioalessio
37417
37417
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
add a comment |
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
I updated the R version but still is not working. The issue seems to be related with the libraries (iml) and (caret)
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:12
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Does other shiny apps run correctly on your shinyapp.io account?
– alessio
Jan 4 at 18:16
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
Yes, testtvn.shinyapps.io/house I have tried few others as well. I created A new question with mode details here: stackoverflow.com/questions/54044245/…
– Luis Ramon Ramirez Rodriguez
Jan 4 at 18:26
add a comment |
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Have you tried splitting the app into two files
uiandserverprior to publishing?– Philipp R
Jan 3 at 1:23