使用 R Shiny 中的 actionButton 附加行更新新的 table
Update new table with rows appended using actionButton in R Shiny
我在 Aurora 中有一个预报 table，我可以使用反应式读取和过滤加载。我正在使用操作按钮 'write_to_forecast_table' 将新行写入 table，但我无法同时在主 table 中加载新添加的行。
tabPanel("Plant-Screen",
fluidRow(id='forecast_section',
column(width = 3, class='div-box-shadow',
tags$div(selectInput("fb_plant_input", label = 'Select Plant: ', choices= c(" All"), selected = NULL, multiple = FALSE, width = "100%"),
selectInput("fb_material_input", label = 'Commodity', choices = c(" All"), multiple=FALSE, width="100%"),
selectInput("fb_for_month_year", label = 'Procured for Month_Year', choices = c(" All"), multiple=FALSE, width="100%"),
br(),
tags$div(shinyWidgets::actionBttn(inputId = 'view_existing_forecasts', label='View Volume Forecast')),
tags$div(shinyWidgets::actionBttn(inputId = 'create_new_forecast', label='Create New Forecast')
),
bsModal(id="modal_demand_view",
title = "Create Volume Demand Forecast",
trigger = "create_new_forecast",
size="medium",
fluidRow(id = 'new_demand_form',
column(width = 12,
tags$div(style="display:contents;",
selectizeInput("selected_plant",
label = 'Plant',
options = list(placeholder = 'Select Plant'),
choices= unique(fb_plant_table$plant_name),
multiple=FALSE,
width="100%"),
br(),
selectizeInput("selected_material",
label = 'Commodity',
options = list(placeholder = 'Select Commodity'),
choices = unique(fb_material_table$commodity),
multiple=FALSE,
width="100%"),
br(),
airDatepickerInput("selected_month_year",
label = "Enter for Month-Year :",
value = lubridate::ymd(today()),
minDate = lubridate::ymd(today()) %m+% months(1),
maxDate = lubridate::ymd(today()) %m+% months(12),
view = "months",
minView = "months",
dateFormat = "yyyy-mm",
width = "50%",
autoClose = TRUE
),
br(),
numericInput("volume_requested",
label = "Enter Additional Volume",
value = 0,
width = "50%"),
br(),
selectizeInput("volume_unit", label = "Unit of Volume",
choices = c("pounds"),
multiple = FALSE,
width = "50%"),
br(),
selectInput("selected_supplier", label = "Supplier",
choices = "",
multiple = FALSE,
width = "50%")
)
)
),
br(),
tags$hr(),
tags$div(shinyWidgets::actionBttn(inputId = 'write_to_forecast_table',
label='New Volume Demand Created',
color="success",
style="material-flat")
)
)
)
),
column(width = 9, class='div-box-shadow',
tags$div(tags$h4 ('Volume Forecast Tabular View',
style="font-weight:bold;color: #ffd207;text-align: center;"
),
br(),
dataTableOutput("vol_forecast_meta_data") %>% shinycssloaders::withSpinner(color="#78620e")
)
服务器端：
#reading table from Aurora:
c <- dcon_iam()
vol_forecast_aurora <- DBI::dbGetQuery(c, 'select * from database_name.vol_forecast_aurora')
vol_forecast_aurora <- vol_forecast_aurora %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
#Viewing forecast based on inputs selected from Select Input:
observeEvent(input$view_existing_forecasts, {
view_fc_reactive <- reactive({
vol_forecast_aurora %>%
filter(plant_name == input$fb_plant_input) %>%
filter(commodity == input$fb_material_input) %>%
filter(for_month_year == input$fb_for_month_year)
})
output$vol_forecast_meta_data <- DT::renderDataTable(view_fc_reactive(),
options = list(paging = FALSE, searching = FALSE),
rownames = FALSE)
})
#update table based on the new row added using Modal:
observeEvent(input$write_to_forecast_table, {
forecast_temp <- z$vol_forecast_aurora
forecast_temp$entered_by=input$user_id
forecast_temp$entered_on=lubridate::ymd(today())
forecast_temp$plant_name=input$selected_plant
forecast_temp$commodity=input$selected_material
forecast_temp$for_month_year=input$selected_month_year
forecast_temp$additional_volume=input$volume_requested
forecast_temp$unit_of_vol=input$volume_unit
forecast_temp$supplier=input$selected_supplier
forecast_temp = forecast_temp[, c('entered_by', 'entered_on', 'plant_name', 'commodity', 'for_month_year', 'additional_volume', 'unit_of_vol', 'supplier')]
c = dcon_iam()
write_to_caspian_aurora(c,
value= z$forecast_temp,
name="vol_forecast_aurora",
append = TRUE,
overwrite=FALSE,
row.names=FALSE
)
#removeModal('modal_demand_view')
showNotification({"Demand Forecast Submitted"})
DBI::dbDisconnect(c)
#reloading the data to the app:
c <- dcon_iam()
vol_forecast_aurora <- DBI::dbGetQuery(c, 'select * from spendanalytics_ico.vol_forecast_aurora')
vol_forecast_aurora <- vol_forecast_aurora %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
})
我需要帮助对服务器的最后一部分进行排序：observeEvent(input$write_to_forecast_table, {})
你的问题是基础数据 vol_forecast_aurora 只在应用程序加载时获取一次（并且它不是反应性的，因此 observeEvent(input$write_to_forecast_table 中的最后几行只创建一个本地对象在观察者内）。因此，当您在应用程序中更新数据库时，您看不到更改。我建议您将 vol_forecast_aurora 存储在 reactiveValues 对象中，以便您可以轻松更新它。
未经测试的代码：
#reading table from Aurora:
c <- dcon_iam()
data <- reactiveValues(vol_forecast_aurora = DBI::dbGetQuery(c, 'select * from database_name.vol_forecast_aurora') %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume)))
DBI::dbDisconnect(c)
#Viewing forecast based on inputs selected from Select Input:
observeEvent(input$view_existing_forecasts, {
view_fc_reactive <- reactive({
data$vol_forecast_aurora %>%
filter(plant_name == input$fb_plant_input) %>%
filter(commodity == input$fb_material_input) %>%
filter(for_month_year == input$fb_for_month_year)
})
output$vol_forecast_meta_data <- DT::renderDataTable(view_fc_reactive(),
options = list(paging = FALSE, searching = FALSE),
rownames = FALSE)
})
#update table based on the new row added using Modal:
observeEvent(input$write_to_forecast_table, {
forecast_temp <- z$vol_forecast_aurora
forecast_temp$entered_by=input$user_id
forecast_temp$entered_on=lubridate::ymd(today())
forecast_temp$plant_name=input$selected_plant
forecast_temp$commodity=input$selected_material
forecast_temp$for_month_year=input$selected_month_year
forecast_temp$additional_volume=input$volume_requested
forecast_temp$unit_of_vol=input$volume_unit
forecast_temp$supplier=input$selected_supplier
forecast_temp = forecast_temp[, c('entered_by', 'entered_on', 'plant_name', 'commodity', 'for_month_year', 'additional_volume', 'unit_of_vol', 'supplier')]
c = dcon_iam()
write_to_caspian_aurora(c,
value= z$forecast_temp,
name="vol_forecast_aurora",
append = TRUE,
overwrite=FALSE,
row.names=FALSE
)
#removeModal('modal_demand_view')
showNotification({"Demand Forecast Submitted"})
DBI::dbDisconnect(c)
#reloading the data to the app:
c <- dcon_iam()
vol_forecast_aurora_local <- DBI::dbGetQuery(c, 'select * from spendanalytics_ico.vol_forecast_aurora')
data$vol_forecast_aurora <- vol_forecast_aurora_local %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
})
我在 Aurora 中有一个预报 table，我可以使用反应式读取和过滤加载。我正在使用操作按钮 'write_to_forecast_table' 将新行写入 table，但我无法同时在主 table 中加载新添加的行。
tabPanel("Plant-Screen",
fluidRow(id='forecast_section',
column(width = 3, class='div-box-shadow',
tags$div(selectInput("fb_plant_input", label = 'Select Plant: ', choices= c(" All"), selected = NULL, multiple = FALSE, width = "100%"),
selectInput("fb_material_input", label = 'Commodity', choices = c(" All"), multiple=FALSE, width="100%"),
selectInput("fb_for_month_year", label = 'Procured for Month_Year', choices = c(" All"), multiple=FALSE, width="100%"),
br(),
tags$div(shinyWidgets::actionBttn(inputId = 'view_existing_forecasts', label='View Volume Forecast')),
tags$div(shinyWidgets::actionBttn(inputId = 'create_new_forecast', label='Create New Forecast')
),
bsModal(id="modal_demand_view",
title = "Create Volume Demand Forecast",
trigger = "create_new_forecast",
size="medium",
fluidRow(id = 'new_demand_form',
column(width = 12,
tags$div(style="display:contents;",
selectizeInput("selected_plant",
label = 'Plant',
options = list(placeholder = 'Select Plant'),
choices= unique(fb_plant_table$plant_name),
multiple=FALSE,
width="100%"),
br(),
selectizeInput("selected_material",
label = 'Commodity',
options = list(placeholder = 'Select Commodity'),
choices = unique(fb_material_table$commodity),
multiple=FALSE,
width="100%"),
br(),
airDatepickerInput("selected_month_year",
label = "Enter for Month-Year :",
value = lubridate::ymd(today()),
minDate = lubridate::ymd(today()) %m+% months(1),
maxDate = lubridate::ymd(today()) %m+% months(12),
view = "months",
minView = "months",
dateFormat = "yyyy-mm",
width = "50%",
autoClose = TRUE
),
br(),
numericInput("volume_requested",
label = "Enter Additional Volume",
value = 0,
width = "50%"),
br(),
selectizeInput("volume_unit", label = "Unit of Volume",
choices = c("pounds"),
multiple = FALSE,
width = "50%"),
br(),
selectInput("selected_supplier", label = "Supplier",
choices = "",
multiple = FALSE,
width = "50%")
)
)
),
br(),
tags$hr(),
tags$div(shinyWidgets::actionBttn(inputId = 'write_to_forecast_table',
label='New Volume Demand Created',
color="success",
style="material-flat")
)
)
)
),
column(width = 9, class='div-box-shadow',
tags$div(tags$h4 ('Volume Forecast Tabular View',
style="font-weight:bold;color: #ffd207;text-align: center;"
),
br(),
dataTableOutput("vol_forecast_meta_data") %>% shinycssloaders::withSpinner(color="#78620e")
)
服务器端：
#reading table from Aurora:
c <- dcon_iam()
vol_forecast_aurora <- DBI::dbGetQuery(c, 'select * from database_name.vol_forecast_aurora')
vol_forecast_aurora <- vol_forecast_aurora %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
#Viewing forecast based on inputs selected from Select Input:
observeEvent(input$view_existing_forecasts, {
view_fc_reactive <- reactive({
vol_forecast_aurora %>%
filter(plant_name == input$fb_plant_input) %>%
filter(commodity == input$fb_material_input) %>%
filter(for_month_year == input$fb_for_month_year)
})
output$vol_forecast_meta_data <- DT::renderDataTable(view_fc_reactive(),
options = list(paging = FALSE, searching = FALSE),
rownames = FALSE)
})
#update table based on the new row added using Modal:
observeEvent(input$write_to_forecast_table, {
forecast_temp <- z$vol_forecast_aurora
forecast_temp$entered_by=input$user_id
forecast_temp$entered_on=lubridate::ymd(today())
forecast_temp$plant_name=input$selected_plant
forecast_temp$commodity=input$selected_material
forecast_temp$for_month_year=input$selected_month_year
forecast_temp$additional_volume=input$volume_requested
forecast_temp$unit_of_vol=input$volume_unit
forecast_temp$supplier=input$selected_supplier
forecast_temp = forecast_temp[, c('entered_by', 'entered_on', 'plant_name', 'commodity', 'for_month_year', 'additional_volume', 'unit_of_vol', 'supplier')]
c = dcon_iam()
write_to_caspian_aurora(c,
value= z$forecast_temp,
name="vol_forecast_aurora",
append = TRUE,
overwrite=FALSE,
row.names=FALSE
)
#removeModal('modal_demand_view')
showNotification({"Demand Forecast Submitted"})
DBI::dbDisconnect(c)
#reloading the data to the app:
c <- dcon_iam()
vol_forecast_aurora <- DBI::dbGetQuery(c, 'select * from spendanalytics_ico.vol_forecast_aurora')
vol_forecast_aurora <- vol_forecast_aurora %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
})
我需要帮助对服务器的最后一部分进行排序：observeEvent(input$write_to_forecast_table, {})
你的问题是基础数据 vol_forecast_aurora 只在应用程序加载时获取一次（并且它不是反应性的，因此 observeEvent(input$write_to_forecast_table 中的最后几行只创建一个本地对象在观察者内）。因此，当您在应用程序中更新数据库时，您看不到更改。我建议您将 vol_forecast_aurora 存储在 reactiveValues 对象中，以便您可以轻松更新它。
未经测试的代码：
#reading table from Aurora:
c <- dcon_iam()
data <- reactiveValues(vol_forecast_aurora = DBI::dbGetQuery(c, 'select * from database_name.vol_forecast_aurora') %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume)))
DBI::dbDisconnect(c)
#Viewing forecast based on inputs selected from Select Input:
observeEvent(input$view_existing_forecasts, {
view_fc_reactive <- reactive({
data$vol_forecast_aurora %>%
filter(plant_name == input$fb_plant_input) %>%
filter(commodity == input$fb_material_input) %>%
filter(for_month_year == input$fb_for_month_year)
})
output$vol_forecast_meta_data <- DT::renderDataTable(view_fc_reactive(),
options = list(paging = FALSE, searching = FALSE),
rownames = FALSE)
})
#update table based on the new row added using Modal:
observeEvent(input$write_to_forecast_table, {
forecast_temp <- z$vol_forecast_aurora
forecast_temp$entered_by=input$user_id
forecast_temp$entered_on=lubridate::ymd(today())
forecast_temp$plant_name=input$selected_plant
forecast_temp$commodity=input$selected_material
forecast_temp$for_month_year=input$selected_month_year
forecast_temp$additional_volume=input$volume_requested
forecast_temp$unit_of_vol=input$volume_unit
forecast_temp$supplier=input$selected_supplier
forecast_temp = forecast_temp[, c('entered_by', 'entered_on', 'plant_name', 'commodity', 'for_month_year', 'additional_volume', 'unit_of_vol', 'supplier')]
c = dcon_iam()
write_to_caspian_aurora(c,
value= z$forecast_temp,
name="vol_forecast_aurora",
append = TRUE,
overwrite=FALSE,
row.names=FALSE
)
#removeModal('modal_demand_view')
showNotification({"Demand Forecast Submitted"})
DBI::dbDisconnect(c)
#reloading the data to the app:
c <- dcon_iam()
vol_forecast_aurora_local <- DBI::dbGetQuery(c, 'select * from spendanalytics_ico.vol_forecast_aurora')
data$vol_forecast_aurora <- vol_forecast_aurora_local %>% group_by(plant_name, commodity, for_month_year) %>% mutate(cum_sum = cumsum(additional_volume))
DBI::dbDisconnect(c)
})