README.md
In edgararuiz/shinyevents: Log Shiny app events
shinyevents
shinyevents provides a flexible and easy to use framework to record
activity occurring withing a Shiny app. The logged information can be
accumulated and later be used to help improve the app’s performance and
user’s experience.
Installation
The development version of shinyevents is available on
GitHub:
# install.packages("remotes")
remotes::install_github("edgararuiz/shinyevents")
Usage
shinyevents attempts to provide a simple way to track different Shiny
events by using two functions. The first function is one of four which
initialize the tracking:
shiny_events_to_log() - Saves the event data into a .log fileshiny_events_to_csv() - Saves the event data into a .csv fileshiny_events_to_dbi() - Saves the event data into a database, via
the DBI packageshiny_events_to_logger() - Sends the event as an entry to the
logger package
Once the target for the event tracking is chosen, shinyevents is
initialized by assigning the function’s result to a variable:
library(shinyevents)
tracker <- shiny_events_to_log()
Once initialized, the second function to use, is one created inside the
assigned variable. The function is called: event(). Since selected
variable’s name was tracker, to access it we use tracker$event(). To
it we can pass two values, as arguments, those values are free-form
text, so the developer of the app can decide what to record:
tracker$event("example", "readme")
By default, the log file name is shiny-events.log. At this point, it
can be accessed in one of many ways. In this case we’ll just use
readLines().
readLines("shiny-events.log")
#> [1] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 example readme"
A Globally Unique Identifier, or GUID, is created by
shiny_events_to_log(). Every event entry for that session will contain
the same GUID. This allows us to know what activity was part of which
app’s user session.
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
readLines("shiny-events.log")
#> [1] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 example readme"
#> [2] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 start_app "
#> [3] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 slider 3"
#> [4] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 stop_app "
In a Shiny app
Here is the code for a sample app that tracks several different events:
- App’s session begins
- Slider is changed, and its current value
- Beginning of the plot’s output processing
- Completion of the plot’s output processing
- App’s session closes
Feel free to copy and run this code in your R session. There are several
comments inside the code to further clarify the purpose of the tracking
related activity.
library(shiny)
library(shinyevents)
ui <- fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(sliderInput("bins", "Bins:", 1, 50, 30)),
mainPanel(plotOutput("distPlot"))
))
server <- function(input, output, session) {
tracker <- shiny_events_to_log() # <- Initializes as log file
tracker$event("app_initiated") # <- Tracks start of app session
observeEvent( # <- Track input using shiny::observeEvent()
input$bins,
tracker$event("bin_slider", input$bins), # <- Pass the input's value to the event
ignoreInit = TRUE) # <- ignoreInit avoids logging the input's initial value
session$onSessionEnded( # <- Track when the app closes using session$onSessionEnded
function() tracker$event("close_app")) # <- Combine with a simple event entry
output$distPlot <- renderPlot({
tracker$event("plot_started", input$bins) # <- Tracks code start
x <- faithful[, 2]
bins <- seq(min(x), max(x), length.out = input$bins + 1)
hist(x, breaks = bins, col = 'darkgray', border = 'white')
tracker$event("plot_rendered", input$bins) # <- Tracks code completion
})
}
shinyApp(ui, server)
After playing a bit with the slider, the app can be closed. This
activity was recorded in a new file, called shiny-events.log. If you
tried the app code above, use the readLines() code below to see the
resulting
entries.
readLines("shiny-events.log")
## [1] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 app_initiated "
## [2] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 30"
## [3] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 30"
## [4] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 bin_slider 19"
## [5] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 19"
## [6] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 19"
## [7] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 41"
## [8] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 41"
## [9] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 bin_slider 41"
## [10] "2019-09-03 16:22:24 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 close_app "
Further info
Some additional information is exposed by the variable assigned to the
Shiny event function. These are made available to allow developers to
use them in other functions, or to create a custom target for the event
tracking. Two of these are:
- The app’s name
- The session’s GUID
tracker$app
#> [1] "shinyevents"
tracker$guid
#> [1] "1da09552-1ebf-4581-a00a-e144a2891680"
The entry() function returns a list object. The list contains the
session information, and the date/time of the entry. This is the base
function that the shiny_events_to_log(), shiny_events_to_csv() and
shiny_events_to_dbi() use.
tracker$entry()
#> $guid
#> [1] "1da09552-1ebf-4581-a00a-e144a2891680"
#>
#> $app
#> [1] "shinyevents"
#>
#> $datetime
#> [1] "2019-09-03 16:24:21 CDT"
#>
#> $activity
#> [1] ""
#>
#> $value
#> [1] ""
Custom event
It is possible to customize the output or add a new target file (beyond
CSV, log or Database). To do that, override the event() function after
assigning it to a variable. For example, if a pipe delimited file is
required for tracking the Shiny events, we could use the following:
tracker <- shiny_events()
tracker$event <- function(activity = "", value = "") {
entry <- tracker$entry(activity = activity, value = value)
cat(
paste(entry$guid, entry$datetime, entry$app, entry$activity, entry$value, "\n", sep = "|"),
file = "shinyevents-pipe.txt",
append = TRUE
)
}
tracker$event("example", "readme")
readLines("shinyevents-pipe.txt")
#> [1] "f929c79d-1e7d-4649-a8c3-c8fbf7794d91|2019-09-03 16:24:21 CDT|shinyevents|example|readme|"
CSV example
Initialize a new CSV log with shiny_events_to_csv().
tracker <- shiny_events_to_csv()
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
To avoid file locks, shiny_events_to_csv() uses the cat() function
inside its code. It also means that the table will not have headers, so
they have to be defined at read time:
read.csv(
"shiny-events.csv",
stringsAsFactors = FALSE,
header = FALSE,
col.names = c("guid", "app", "activity", "value", "datetime")
)
#> guid app activity value
#> 1 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents start_app NA
#> 2 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents slider 3
#> 3 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents stop_app NA
#> datetime
#> 1 2019-09-03 16:24:21 CDT
#> 2 2019-09-03 16:24:21 CDT
#> 3 2019-09-03 16:24:21 CDT
Database example
shiny_events_to_dbi uses the DBI package to record events. Here are
a few highlights of how it works:
- Uses the
dbWriteTable() function, this allows it to work on most
databases DBI is able to interact with
- The
append = TRUE argument is used. This allows the table to be
created if it doesn’t exists yet, and only to add new records to the
table, instead of overriding its content.
- It creates, or expects, a table with the following names:
guid,
app, datetime, activity, value.
library(DBI)
library(RSQLite)
con <- dbConnect(SQLite(), "example.db")
tracker <- shiny_events_to_dbi(table = "shinyevents", connection = con)
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
dbGetQuery(con, "SELECT * FROM shinyevents")
#> guid app datetime
#> 1 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> 2 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> 3 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> activity value
#> 1 start_app
#> 2 slider 3
#> 3 stop_app
dbDisconnect(con)
Example using logger
To combine with the logger package, simply use
shiny_events_to_logger(). The log_appender() function should be
initialized before running the first event() function.
library(logger)
t <- tempfile()
log_appender(appender_file(t))
tracker <- shiny_events_to_logger()
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("data_frame", "0", "warn")
tracker$event("stop_app")
readLines(t)
#> [1] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents start_app "
#> [2] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents slider 3"
#> [3] "WARN [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents data_frame 0"
#> [4] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents stop_app "
Sample apps
The package includes several app examples. The example pictured below,
uses shiny_events_to_dbi() to record the events in a database, in this
case SQLite. It records when there are changes in each of the inputs, as
well as when the plot;s code starts and ends. There are entries for when
the app starts and is closed.
Run the following code in your R session to access the app:
shiny::runApp(
system.file(
"samples", "shinydashboard-db",
package = "shinyevents"
),
display.mode = "normal"
)
Additional samples
-
Simple example - An example using the “Old Faithful Geyser” app,
shows the easiest way to include shinyevents in an app.
r
shiny::runApp(
system.file(
"samples", "simple",
package = "shinyevents"
),
display.mode = "normal"
)
-
shinydashboard - An example that looks the same as the
shinydashboard example above, but it uses a CSV file to record the
events instead of a database.
r
shiny::runApp(
system.file(
"samples", "shinydashboard",
package = "shinyevents"
),
display.mode = "normal"
)
edgararuiz/shinyevents documentation built on Nov. 4, 2019, 11:33 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
shinyevents
shinyevents provides a flexible and easy to use framework to record
activity occurring withing a Shiny app. The logged information can be
accumulated and later be used to help improve the app’s performance and
user’s experience.
Installation
The development version of shinyevents is available on
GitHub:
# install.packages("remotes")
remotes::install_github("edgararuiz/shinyevents")
Usage
shinyevents attempts to provide a simple way to track different Shiny
events by using two functions. The first function is one of four which
initialize the tracking:
shiny_events_to_log()- Saves the event data into a.logfileshiny_events_to_csv()- Saves the event data into a.csvfileshiny_events_to_dbi()- Saves the event data into a database, via theDBIpackageshiny_events_to_logger()- Sends the event as an entry to theloggerpackage
Once the target for the event tracking is chosen, shinyevents is
initialized by assigning the function’s result to a variable:
library(shinyevents)
tracker <- shiny_events_to_log()
Once initialized, the second function to use, is one created inside the
assigned variable. The function is called: event(). Since selected
variable’s name was tracker, to access it we use tracker$event(). To
it we can pass two values, as arguments, those values are free-form
text, so the developer of the app can decide what to record:
tracker$event("example", "readme")
By default, the log file name is shiny-events.log. At this point, it
can be accessed in one of many ways. In this case we’ll just use
readLines().
readLines("shiny-events.log")
#> [1] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 example readme"
A Globally Unique Identifier, or GUID, is created by
shiny_events_to_log(). Every event entry for that session will contain
the same GUID. This allows us to know what activity was part of which
app’s user session.
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
readLines("shiny-events.log")
#> [1] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 example readme"
#> [2] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 start_app "
#> [3] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 slider 3"
#> [4] "2019-09-03 16:24:21 CDT INFO shinyevents 1da09552-1ebf-4581-a00a-e144a2891680 stop_app "
In a Shiny app
Here is the code for a sample app that tracks several different events:
- App’s session begins
- Slider is changed, and its current value
- Beginning of the plot’s output processing
- Completion of the plot’s output processing
- App’s session closes
Feel free to copy and run this code in your R session. There are several comments inside the code to further clarify the purpose of the tracking related activity.
library(shiny)
library(shinyevents)
ui <- fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(sliderInput("bins", "Bins:", 1, 50, 30)),
mainPanel(plotOutput("distPlot"))
))
server <- function(input, output, session) {
tracker <- shiny_events_to_log() # <- Initializes as log file
tracker$event("app_initiated") # <- Tracks start of app session
observeEvent( # <- Track input using shiny::observeEvent()
input$bins,
tracker$event("bin_slider", input$bins), # <- Pass the input's value to the event
ignoreInit = TRUE) # <- ignoreInit avoids logging the input's initial value
session$onSessionEnded( # <- Track when the app closes using session$onSessionEnded
function() tracker$event("close_app")) # <- Combine with a simple event entry
output$distPlot <- renderPlot({
tracker$event("plot_started", input$bins) # <- Tracks code start
x <- faithful[, 2]
bins <- seq(min(x), max(x), length.out = input$bins + 1)
hist(x, breaks = bins, col = 'darkgray', border = 'white')
tracker$event("plot_rendered", input$bins) # <- Tracks code completion
})
}
shinyApp(ui, server)
After playing a bit with the slider, the app can be closed. This
activity was recorded in a new file, called shiny-events.log. If you
tried the app code above, use the readLines() code below to see the
resulting
entries.
readLines("shiny-events.log")
## [1] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 app_initiated "
## [2] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 30"
## [3] "2019-09-03 16:22:17 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 30"
## [4] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 bin_slider 19"
## [5] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 19"
## [6] "2019-09-03 16:22:20 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 19"
## [7] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_started 41"
## [8] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 plot_rendered 41"
## [9] "2019-09-03 16:22:22 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 bin_slider 41"
## [10] "2019-09-03 16:22:24 CDT INFO shinyevents ff55ea39-7d8a-4e5f-9f33-18ee804b2218 close_app "
Further info
Some additional information is exposed by the variable assigned to the Shiny event function. These are made available to allow developers to use them in other functions, or to create a custom target for the event tracking. Two of these are:
- The app’s name
- The session’s GUID
tracker$app
#> [1] "shinyevents"
tracker$guid
#> [1] "1da09552-1ebf-4581-a00a-e144a2891680"
The entry() function returns a list object. The list contains the
session information, and the date/time of the entry. This is the base
function that the shiny_events_to_log(), shiny_events_to_csv() and
shiny_events_to_dbi() use.
tracker$entry()
#> $guid
#> [1] "1da09552-1ebf-4581-a00a-e144a2891680"
#>
#> $app
#> [1] "shinyevents"
#>
#> $datetime
#> [1] "2019-09-03 16:24:21 CDT"
#>
#> $activity
#> [1] ""
#>
#> $value
#> [1] ""
Custom event
It is possible to customize the output or add a new target file (beyond
CSV, log or Database). To do that, override the event() function after
assigning it to a variable. For example, if a pipe delimited file is
required for tracking the Shiny events, we could use the following:
tracker <- shiny_events()
tracker$event <- function(activity = "", value = "") {
entry <- tracker$entry(activity = activity, value = value)
cat(
paste(entry$guid, entry$datetime, entry$app, entry$activity, entry$value, "\n", sep = "|"),
file = "shinyevents-pipe.txt",
append = TRUE
)
}
tracker$event("example", "readme")
readLines("shinyevents-pipe.txt")
#> [1] "f929c79d-1e7d-4649-a8c3-c8fbf7794d91|2019-09-03 16:24:21 CDT|shinyevents|example|readme|"
CSV example
Initialize a new CSV log with shiny_events_to_csv().
tracker <- shiny_events_to_csv()
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
To avoid file locks, shiny_events_to_csv() uses the cat() function
inside its code. It also means that the table will not have headers, so
they have to be defined at read time:
read.csv(
"shiny-events.csv",
stringsAsFactors = FALSE,
header = FALSE,
col.names = c("guid", "app", "activity", "value", "datetime")
)
#> guid app activity value
#> 1 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents start_app NA
#> 2 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents slider 3
#> 3 a90c5b13-cdfa-442c-aa51-0c5e8f65fe56 shinyevents stop_app NA
#> datetime
#> 1 2019-09-03 16:24:21 CDT
#> 2 2019-09-03 16:24:21 CDT
#> 3 2019-09-03 16:24:21 CDT
Database example
shiny_events_to_dbi uses the DBI package to record events. Here are
a few highlights of how it works:
- Uses the
dbWriteTable()function, this allows it to work on most databasesDBIis able to interact with - The
append = TRUEargument is used. This allows the table to be created if it doesn’t exists yet, and only to add new records to the table, instead of overriding its content. - It creates, or expects, a table with the following names:
guid,app,datetime,activity,value.
library(DBI)
library(RSQLite)
con <- dbConnect(SQLite(), "example.db")
tracker <- shiny_events_to_dbi(table = "shinyevents", connection = con)
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("stop_app")
dbGetQuery(con, "SELECT * FROM shinyevents")
#> guid app datetime
#> 1 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> 2 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> 3 b62911a6-4ef2-4220-8a7e-e0b9eda70aca shinyevents 2019-09-03 16:24:23 CDT
#> activity value
#> 1 start_app
#> 2 slider 3
#> 3 stop_app
dbDisconnect(con)
Example using logger
To combine with the logger package, simply use
shiny_events_to_logger(). The log_appender() function should be
initialized before running the first event() function.
library(logger)
t <- tempfile()
log_appender(appender_file(t))
tracker <- shiny_events_to_logger()
tracker$event("start_app")
tracker$event("slider", "3")
tracker$event("data_frame", "0", "warn")
tracker$event("stop_app")
readLines(t)
#> [1] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents start_app "
#> [2] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents slider 3"
#> [3] "WARN [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents data_frame 0"
#> [4] "INFO [2019-09-03 16:24:23] 3e590609-5e2d-42df-8085-6bf2c3742f85 shinyevents stop_app "
Sample apps
The package includes several app examples. The example pictured below,
uses shiny_events_to_dbi() to record the events in a database, in this
case SQLite. It records when there are changes in each of the inputs, as
well as when the plot;s code starts and ends. There are entries for when
the app starts and is closed.
Run the following code in your R session to access the app:
shiny::runApp(
system.file(
"samples", "shinydashboard-db",
package = "shinyevents"
),
display.mode = "normal"
)
Additional samples
-
Simple example - An example using the “Old Faithful Geyser” app, shows the easiest way to include
shinyeventsin an app.r shiny::runApp( system.file( "samples", "simple", package = "shinyevents" ), display.mode = "normal" ) -
shinydashboard - An example that looks the same as the
shinydashboardexample above, but it uses a CSV file to record the events instead of a database.r shiny::runApp( system.file( "samples", "shinydashboard", package = "shinyevents" ), display.mode = "normal" )
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.