Easy logging of users activity and session events of your Shiny App
The shiny.telemetry
R package tracks events occurring on a user session,
such as input changes and session duration, and stores them in a local or remote database.
It provides developers with the tools to help understand how users interact with Shiny dashboards and answer questions such as: which tabs/pages are more often visited, which inputs users are changing, what is the average length of a session, etc.
The shiny.telemetry
package can be installed from GitHub by using the remotes package:
remotes::install_github("Appsilon/shiny.telemetry", dependencies = TRUE)
With dependencies = TRUE
the suggested packages (required to run some examples)
will be installed in addition to mandatory dependencies.
shiny.telemetry
allows for a minimal setup with only 3 commands
that can track some information about the session:
- When session starts and ends
- The browser version used by the client
- Changes in the inputs (doesn't track values by default)
The code below runs a minimal example of a Shiny application that uses shiny.telemetry
.
The package will keep track of the session information and all changes to the numericInput
.
Note: When using the dashboard nothing is happening from the user's perspective as all operation run in the background (either in the server or in Javascript).
library(shiny)
library(shiny.telemetry)
telemetry <- Telemetry$new() # 1. Initialize telemetry with default options
shinyApp(
ui = fluidPage(
use_telemetry(), # 2. Add necessary Javascript to Shiny
numericInput("n", "n", 1),
plotOutput('plot')
),
server = function(input, output) {
telemetry$start_session() # 3. Minimal setup to track events
output$plot <- renderPlot({ hist(runif(input$n)) })
}
)
When inspecting the code above, we can breakdown the 3 lines of code by:
- Global
Telemetry
object that is used across the different sessions - Add necessary Javascript to the UI by calling
use_telemetry()
. It is used to track browser version. - Initialize the session-specific tracking
by calling method
start_session()
of theTelemetry
object.
The developers and administrators of the dashboard can access the data that is gathered by shiny.telemetry
via a Telemetry object or directly from DataStorage
via the appropriate provider.
# After running the instrumented app
shiny.telemetry::Telemetry$new()$data_storage$read_events("2020-01-01", "2050-01-01")
# Default provider and path for Telemetry$new()
shiny.telemetry::DataStorageSQLite$new(db_path = "telemetry.sqlite")$read_events("2020-01-01", "2050-01-01")
The package includes an analytics dashboard to view the data.
It is located at inst/examples/app/analytics
and it should be modified
so that it references the correct DataStorage
provider and configuration.
There are 3 different types of data providers that can range from local filesystem storage to a remote Plumber REST API instance.
- Local file:
- SQLite using
DataStorageSQLite
class - Logfile using
DataStorageLogFile
class
- SQLite using
- Remote SQL database:
- MariaDB using
DataStorageMariaDB
class - PostgreSQL using
DataStoragePostgreSQL
class
- MariaDB using
- Plumber REST API using
DataStoragePlumber
class- In turn, the Plumber data provider will use one of the other classes above as the method of data storage.
The setup for plumber requires a valid Plumber instance running on the network and the communication can be protected. See Plumber deployment documentation for more information.
The package uses the logger
package internally with the shiny.telemetry
namespace.
To debug the shiny.telemetry
calls in the dashboard,
change the threshold of this namespace to DEBUG
:
logger::log_threshold("DEBUG", namespace = "shiny.telemetry")
note: This command can be run before the Shiny call or by adding it to the .Rprofile
.
Appsilon is a Posit (formerly RStudio) Full Service Certified Partner.
Learn more at appsilon.com.
Get in touch [email protected]
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