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Type: Package
Title: 'Shiny' App Usage Telemetry
Version: 0.3.2
Description: Enables instrumentation of 'Shiny' apps for tracking user session events such as input changes, browser type, and session duration. These events can be sent to any of the available storage backends and analyzed using the included 'Shiny' app to gain insights about app usage and adoption.
License: LGPL-3
URL: https://appsilon.github.io/shiny.telemetry/, https://github.com/Appsilon/shiny.telemetry
BugReports: https://github.com/Appsilon/shiny.telemetry/issues
Imports: checkmate, digest, dplyr (≥ 1.1.0), glue, htmltools, httr2, jsonlite, lifecycle, logger, lubridate, odbc, purrr, R6, rlang, RSQLite, shiny, stringr, tidyr
Suggests: box, config, DT, knitr, mongolite, plotly, plumber, RColorBrewer, RMariaDB, rmarkdown, RPostgres, RPostgreSQL, scales, semantic.dashboard (≥ 0.1.1), shiny.semantic (≥ 0.2.0), shinyjs, testthat (≥ 3.1.7), timevis, withr
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-08-26 11:47:21 UTC; averissimo
Author: André Veríssimo [aut, cre], Kamil Żyła [aut], Krystian Igras [aut], Recle Vibal [aut], Arun Kodati [aut], Wahaduzzaman Khan [aut], Appsilon Sp. z o.o. [cph]
Maintainer: André Veríssimo <opensource+andre@appsilon.com>
Repository: CRAN
Date/Publication: 2025-08-26 14:20:06 UTC

Data Storage abstract class to handle all the read/write operations

Description

Abstract R6 Class that encapsulates all the operations needed by Shiny.telemetry to read and write. This removes the complexity from the functions and uses a unified API.

Active bindings

event_bucket

string that identifies the bucket to store user related and action data

Methods

Public methods

Method new()

initialize data storage object common with all providers

Usage
DataStorage$new()

Method insert()

Insert new data

Usage
DataStorage$insert(app_name, type, session = NULL, details = NULL, time = NULL)
Arguments
app_name

string with name of dashboard (the version can be also included in this string)

type

string that identifies the event type to store

session

(optional) string that identifies a session where the event was logged

details

atomic element of list with data to save in storage

time

date time value indicates the moment the record was generated in UTC. By default it should be NULL and determined automatically, but in cases where it should be defined, use Sys.time() or lubridate::now(tzone = "UTC") to generate it.

Returns

Nothing. This method is called for side effects.

Method read_event_data()

read all user data from SQLite.

Usage
DataStorage$read_event_data(date_from = NULL, date_to = NULL, app_name = NULL)
Arguments
date_from

(optional) date representing the starting day of results.

date_to

(optional) date representing the last day of results.

app_name

(optional) string identifying the Dashboard-specific event data

Method close()

Close the connection if necessary

Usage
DataStorage$close()

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorage$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Data storage class for JSON Log File

Description

Implementation of the DataStorage R6 class to a JSON log file backend using a unified API for read/write operations

Super class

shiny.telemetry::DataStorage -> DataStorageLogFile

Active bindings

event_bucket

string that identifies the file path to store user related and action data

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStorageLogFile$new(log_file_path)
Arguments
log_file_path

string with path to JSON log file user actions

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageLogFile$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

log_file_path <- tempfile(fileext = ".txt")
data_storage <- DataStorageLogFile$new(log_file_path = log_file_path)

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)

file.remove(log_file_path)

Data storage class with MS SQL Server provider

Description

Implementation of the DataStorage R6 class to MS SQL Server backend using a unified API for read/write operations. This provider requires a configured and named ODBC driver to be set up on your system, for example, "ODBC Driver 17 for SQL Server" or "ODBC Driver 18 for SQL Server".

Note that MS SQL Server support requires a subtly different database schema: the time field is stored as a DATETIME rather than a TIMESTAMP.

Super classes

shiny.telemetry::DataStorage -> shiny.telemetry::DataStorageSQLFamily -> DataStorageMSSQLServer

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStorageMSSQLServer$new(
  username = NULL,
  password = NULL,
  hostname = "127.0.0.1",
  port = 1433,
  dbname = "shiny_telemetry",
  driver = "ODBC Driver 17 for SQL Server",
  trust_server_certificate = "NO"
)
Arguments
username

string with a MS SQL Server username.

password

string with the password for the username.

hostname

string with hostname of the MS SQL Server instance.

port

numeric value with the port number of MS SQL Server instance.

dbname

string with the name of the database in the MS SQL Server instance.

driver

string with the name of the ODBC driver class for MS SQL, for example "ODBC Driver 17 for SQL Server".

trust_server_certificate

string with "NO" or "YES", setting whether or not to trust the server's certificate implicitly.

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageMSSQLServer$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 
data_storage <- DataStorageMSSQLServer$new(
  user = "sa",
  password = "my-Secr3t_Password",
  hostname = "localhost",
  port = 1433,
  dbname = "shiny_telemetry",
  driver = "ODBC Driver 18 for SQL Server",
  trust_server_certificate = "YES"
)

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id1"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)
data_storage$close()

## End(Not run)

Data storage class with MariaDB / MySQL provider

Description

Implementation of the DataStorage R6 class to MariaDB backend using a unified API for read/write operations

Super classes

shiny.telemetry::DataStorage -> shiny.telemetry::DataStorageSQLFamily -> DataStorageMariaDB

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStorageMariaDB$new(
  username = NULL,
  password = NULL,
  hostname = "127.0.0.1",
  port = 3306,
  dbname = "shiny_telemetry"
)
Arguments
username

string with a MariaDB username.

password

string with the password for the username.

hostname

string with hostname of MariaDB instance.

port

numeric value with the port number of MariaDB instance.

dbname

string with the name of the database in the MariaDB instance.

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageMariaDB$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 
data_storage <- DataStorageMariaDB$new(user = "mariadb", password = "mysecretpassword")

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id1"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)
data_storage$close()

## End(Not run)

Data storage class with MongoDB provider

Description

Implementation of the DataStorage R6 class to MongoDB backend using a unified API for read/write operations

Super class

shiny.telemetry::DataStorage -> DataStorageMongoDB

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStorageMongoDB$new(
  hostname = "localhost",
  port = 27017,
  username = NULL,
  password = NULL,
  authdb = NULL,
  dbname = "shiny_telemetry",
  options = NULL,
  ssl_options = mongolite::ssl_options()
)
Arguments
hostname

the hostname or IP address of the MongoDB server.

port

the port number of the MongoDB server (default is 27017).

username

the username for authentication (optional).

password

the password for authentication (optional).

authdb

the default authentication database (optional).

dbname

name of database (default is "shiny_telemetry").

options

Additional connection options in a named list format (e.g., list(ssl = "true", replicaSet = "myreplicaset")) (optional).

ssl_options

additional connection options such as SSL keys/certs (default is mongolite::ssl_options()).

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageMongoDB$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 
data_storage <- DataStorageMongoDB$new(
  host = "localhost",
  db = "test",
  ssl_options = mongolite::ssl_options()
)
data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id1"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)
data_storage$close()

## End(Not run)

Data storage class with SQLite provider

Description

Implementation of the DataStorage R6 class to SQLite backend using a unified API for read/write operations

Super class

shiny.telemetry::DataStorage -> DataStoragePlumber

Active bindings

event_read_endpoint

string field that returns read action endpoint

event_insert_endpoint

string field that returns insert action endpoint

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStoragePlumber$new(
  hostname = "127.0.0.1",
  port = 80,
  protocol = "http",
  path = NULL,
  secret = NULL,
  authorization = NULL
)
Arguments
hostname

string with hostname of plumber instance,

port

numeric value with port number of plumber instance.

protocol

string with protocol of the connection of the plumber instance.

path

string with sub-path of plumber deployment.

secret

string with secret to sign communication with plumber (can be NULL for disabling communication signing).

authorization

string to use in HTTP headers for authorization (for example: to authenticate to a plumber deployment behind a connect server).

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStoragePlumber$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 
# Make sure the PLUMBER_SECRET environment variable is valid before
# running these examples (NULL or a valid secret)

data_storage <- DataStoragePlumber$new(
  hostname = "connect.appsilon.com",
  path = "shiny_telemetry_plumber",
  port = 443,
  protocol = "https",
  authorization = Sys.getenv("CONNECT_AUTHORIZATION_KEY"),
  secret = Sys.getenv("PLUMBER_SECRET")
)

data_storage <- DataStoragePlumber$new(
  hostname = "127.0.0.1",
  path = NULL,
  port = 8087,
  protocol = "http",
  secret = Sys.getenv("PLUMBER_SECRET")
)

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)

## End(Not run)

Data storage class with PostgreSQL provider

Description

Implementation of the DataStorage R6 class to PostgreSQL backend using a unified API for read/write operations

Super classes

shiny.telemetry::DataStorage -> shiny.telemetry::DataStorageSQLFamily -> DataStoragePostgreSQL

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStoragePostgreSQL$new(
  username = NULL,
  password = NULL,
  hostname = "127.0.0.1",
  port = 5432,
  dbname = "shiny_telemetry",
  driver = "RPostgreSQL"
)
Arguments
username

string with a PostgreSQL username.

password

string with the password for the username.

hostname

string with hostname of PostgreSQL instance.

port

numeric value with the port number of PostgreSQL instance.

dbname

string with the name of the database in the PostgreSQL instance.

driver

string, to select PostgreSQL driver among c("RPostgreSQL", "RPostgres").

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStoragePostgreSQL$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

## Not run: 
data_storage <- DataStoragePostgreSQL$new(user = "postgres", password = "mysecretpassword")

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id1"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)
data_storage$close()

## End(Not run)

Data storage abstract class for SQL providers

Description

Abstract subclass of the DataStorage R6 class for the SQL family of providers

Super class

shiny.telemetry::DataStorage -> DataStorageSQLFamily

Methods

Public methods

Inherited methods

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageSQLFamily$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Data storage class with SQLite provider

Description

Implementation of the DataStorage R6 class to SQLite backend using a unified API for read/write operations

Super classes

shiny.telemetry::DataStorage -> shiny.telemetry::DataStorageSQLFamily -> DataStorageSQLite

Methods

Public methods

Inherited methods

Method new()

Initialize the data storage class

Usage
DataStorageSQLite$new(db_path = "user_stats.sqlite")
Arguments
db_path

string with path to SQLite file.

Method clone()

The objects of this class are cloneable with this method.

Usage
DataStorageSQLite$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

db_path <- tempfile(fileext = ".sqlite")
data_storage <- DataStorageSQLite$new(db_path = db_path)

data_storage$insert("example", "test_event", "session1")
data_storage$insert("example", "input", "s1", list(id = "id1"))
data_storage$insert("example", "input", "s1", list(id = "id2", value = 32))

data_storage$insert(
  "example", "test_event_3_days_ago", "session1",
  time = lubridate::as_datetime(lubridate::today() - 3)
)

data_storage$read_event_data()
data_storage$read_event_data(Sys.Date() - 1, Sys.Date() + 1)

file.remove(db_path)

Telemetry class to manage analytics gathering at a global level

Description

An instance of this class will define metadata and data storage provider for gathering telemetry analytics of a Shiny dashboard.

The name and version parameters will describe the dashboard name and version to track using analytics, allowing to store the analytics data from multiple dashboards in the same data storage provider. As well as discriminate different versions of the dashboard.

The default data storage provider uses a local SQLite database, but this can be customizable when instantiating the class, by using another one of the supported providers (see DataStorage).

Debugging

Events are logged at the DEBUG level using the logger package. To see the logs, you can set: 

logger::log_threshold("DEBUG", namespace = "shiny.telemetry")

Active bindings

data_storage

instance of a class that inherits from DataStorage. See the documentation on that class for more information.

app_name

string with name of dashboard

Methods

Public methods

Method new()

Constructor that initializes Telemetry instance with parameters.

Usage
Telemetry$new(
  app_name = "(dashboard)",
  data_storage = DataStorageSQLite$new(db_path = file.path("telemetry.sqlite"))
)
Arguments
app_name

(optional) string that identifies the name of the dashboard. By default it will store data with (dashboard).

data_storage

(optional) DataStorage instance where telemetry data is being stored. It can take any of data storage providers by this package, By default it will store in a SQLite local database in the current working directory with filename telemetry.sqlite

version

(optional) string that identifies the version of the dashboard. By default it will use v0.0.0.

Method start_session()

Setup basic telemetry

Usage
Telemetry$start_session(
  track_inputs = TRUE,
  track_values = FALSE,
  login = TRUE,
  logout = TRUE,
  browser_version = TRUE,
  navigation_input_id = NULL,
  session = shiny::getDefaultReactiveDomain(),
  username = NULL,
  track_anonymous_user = TRUE,
  track_errors = TRUE
)
Arguments
track_inputs

flag that indicates if the basic telemetry should track the inputs that change value. TRUE by default

track_values

flag that indicates if the basic telemetry should track the values of the inputs that are changing. FALSE by default. This parameter is ignored if track_inputs is FALSE

login

flag that indicates if the basic telemetry should track when a session starts. TRUE by default.

logout

flag that indicates if the basic telemetry should track when the session ends. TRUE by default.

browser_version

flag that indicates that the browser version should be tracked.TRUE by default.

navigation_input_id

string or vector of strings that represent input ids and which value should be tracked as navigation events. i.e. a change in the value represent a navigation to a page or tab. By default, no navigation is tracked.

session

ShinySession object or NULL to identify the current Shiny session.

username

Character with username. If set, it will overwrite username from session object.

track_anonymous_user

flag that indicates to track anonymous user. A cookie is used to track same user without login over multiple sessions, This is only activated if none of the automatic methods produce a username and when a username is not explicitly defined.TRUE by default.

track_errors

flag that indicates if the basic telemetry should track the errors. TRUE by default. if using shiny version < ⁠1.8.1⁠, it can auto log errors only in UI output functions. By using latest versions of shiny, it can auto log all types of errors.

Returns

Nothing. This method is called for side effects.

Method log_navigation()

Log an input change as a navigation event

Usage
Telemetry$log_navigation(input_id, session = shiny::getDefaultReactiveDomain())
Arguments
input_id

string that identifies the generic input in the Shiny application so that the function can track and log changes to it.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_navigation_manual()

Log a navigation event manually by indicating the id (as input id)

Usage
Telemetry$log_navigation_manual(
  navigation_id,
  value,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
navigation_id

string that identifies navigation event.

value

string that indicates a value for the navigation

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_login()

Log when session starts

Usage
Telemetry$log_login(
  username = NULL,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
username

string with username from current session

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_logout()

Log when session ends

Usage
Telemetry$log_logout(
  username = NULL,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
username

string with username from current session

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_click()

Log an action click

Usage
Telemetry$log_click(id, session = shiny::getDefaultReactiveDomain())
Arguments
id

string that identifies a manual click to the dashboard.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_browser_version()

Log the browser version

Usage
Telemetry$log_browser_version(session = shiny::getDefaultReactiveDomain())
Arguments
session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_button()

Track a button and track changes to this input (without storing the values)

Usage
Telemetry$log_button(
  input_id,
  track_value = FALSE,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
input_id

string that identifies the button in the Shiny application so that the function can track and log changes to it.

track_value

flag that indicates if the basic telemetry should track the value of the input that are changing. FALSE by default.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_all_inputs()

Automatic tracking of all input changes in the App. Depending on the parameters, it may only track a subset of inputs by excluding patterns or by including specific vector of input_ids.

Usage
Telemetry$log_all_inputs(
  track_values = FALSE,
  excluded_inputs = c("browser_version"),
  excluded_inputs_regex = NULL,
  include_input_ids = NULL,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
track_values

flag that indicates if the basic telemetry should track the values of the inputs that are changing. FALSE by default. This parameter is ignored if track_inputs is FALSE.

excluded_inputs

vector of input_ids that should not be tracked. By default it doesn't track browser version, which is added by this package.

excluded_inputs_regex

vector of input_ids that should not be tracked. All Special characters will be escaped.

include_input_ids

vector of input_ids that will be tracked. This input_ids should be an exact match and will be given priority over exclude list.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_input()

Track changes of a specific input id.

Usage
Telemetry$log_input(
  input_id,
  track_value = FALSE,
  matching_values = NULL,
  input_type = "text",
  session = shiny::getDefaultReactiveDomain()
)
Arguments
input_id

string (or vector of strings) that identifies the generic input in the Shiny application so that the function can track and log changes to it.

When the input_id is a vector of strings, the function will behave just as calling log_input one by one with the same arguments.

track_value

flag that indicates if the basic telemetry should track the value of the input that are changing. FALSE by default.

matching_values

An object specified possible values to register.

input_type

"text" to registered bare input value, "json" to parse value from JSON format.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for its side effects.

Method log_input_manual()

Log a manual input value.

This can be called in telemetry and is also used as a layer between log_input family of functions and actual log event. It creates the correct payload to log the event internally.

Usage
Telemetry$log_input_manual(
  input_id,
  value = NULL,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
input_id

string that identifies the generic input in the Shiny application so that the function can track and log changes to it.

value

(optional) scalar value or list with the value to register.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_custom_event()

Log a manual event

Usage
Telemetry$log_custom_event(
  event_type,
  details = NULL,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
event_type

string that identifies the event type

details

(optional) scalar value or list with the value to register.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_error()

Log a manual error event

Usage
Telemetry$log_error(
  output_id,
  message,
  session = shiny::getDefaultReactiveDomain()
)
Arguments
output_id

string that refers to the output element where the error occurred.

message

string that describes the error.

session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method log_errors()

Track errors as they occur in observe and reactive

Usage
Telemetry$log_errors(session = shiny::getDefaultReactiveDomain())
Arguments
session

ShinySession object or NULL to identify the current Shiny session.

Returns

Nothing. This method is called for side effects.

Method clone()

The objects of this class are cloneable with this method.

Usage
Telemetry$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

DataStorage which this function wraps.

Examples

log_file_path <- tempfile(fileext = ".txt")
telemetry <- Telemetry$new(
  data_storage = DataStorageLogFile$new(log_file_path = log_file_path)
) # 1. Initialize telemetry with default options

#
# Use in a shiny application

if (interactive()) {
  library(shiny)

  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)) })
    }
  )
}

#
# Manual logging of Telemetry that can be used inside Shiny Application
# to further customize the events to be tracked.

session <- shiny::MockShinySession$new() # Create dummy session (only for example purposes)
class(session) <- c(class(session), "ShinySession")

telemetry$log_click("a_button", session = session)

telemetry$log_error("global", message = "An error has occured")

telemetry$log_custom_event("a_button", list(value = 2023), session = session)
telemetry$log_custom_event("a_button", list(custom_field = 23), session = session)

# Manual call login with custom username
telemetry$log_login("ben", session = session)

# Read all data
telemetry$data_storage$read_event_data()

file.remove(log_file_path)

#
# Using SQLite

db_path <- tempfile(fileext = ".sqlite")
telemetry_sqlite <- Telemetry$new(
  data_storage = DataStorageSQLite$new(db_path = db_path)
)

telemetry_sqlite$log_custom_event("a_button", list(value = 2023), session = session)
telemetry_sqlite$log_custom_event("a_button", list(custom_field = 23), session = session)

# Read all data from time range
telemetry_sqlite$data_storage$read_event_data("2020-01-01", "2055-01-01")

file.remove(db_path)

Run example telemetry analytics dashboard

Description

Run example telemetry analytics dashboard

Usage

analytics_app(data_storage)

Arguments

data_storage

data_storage instance that will handle all backend read and writes.

Value

An object that represents the analytics app. Printing the object or passing it to shiny::runApp() will run it.

Builds id from a secret that can be used in open communication

Description

This is used in shiny.telemetry, but also externally with the Plumber endpoint.

Usage

build_id_from_secret(secret)

Arguments

secret

string that contains information that should not be publicly available

Value

A string with an hash of the secret.

Examples

build_id_from_secret("some_random_secret_generated_with_uuid::UUIDgenerate")

Builds hash for a call

Description

Function that takes creates a signature for the values using a secret.

Usage

build_token(values, secret = NULL)

Arguments

values

R object that is going to be signed

secret

string that contains the shared secret to sign the communication. It can be NULL on both telemetry and in plumber API to disable this communication feature

Details

This is used in shiny.telemetry, but also externally with the Plumber endpoint.

Value

A string that contains an hash to uniquely identify the parameters.

Examples

build_token(values = list(list(1, 2, 3), 2, 2, 3, "bb"))
build_token(values = list(list(1, 2, 3), 1, 2, 3, "bb"))
build_token(values = list(list(1, 2, 3), 1, 2, 3, "bb"), secret = "abc")
build_token(values = list(list(1, 2, 3), 1, 2, 3, "bb"), secret = "abd")

Common date_from to recognize as NULL

Description

Common date_from to recognize as NULL

Usage

date_from_null

Format

An object of class character of length 1.

Common date_to to recognize as NULL

Description

Common date_to to recognize as NULL

Usage

date_to_null

Format

An object of class character of length 1.

Merge a list of regular expressions into a single one

Description

Merge a list of regular expressions into a single one

Usage

merge_excluded_regex(regex_l, trim_whitespace = TRUE)

Arguments

regex_l

list of regular expressions to be merged.

trim_whitespace

boolean indicating if whitespace should be trim from the start and end of the regex list.

Value

Single regular expression string.

prepare_admin_panel_components

Description

prepare_admin_panel_components

Usage

prepare_admin_panel_components(input, output, session, data_storage)

Arguments

input

input object inherited from server function.

output

output object inherited from server function.

session

session object inherited from server function.

data_storage

data_storage instance that will handle all backend read and writes.

Function that adds telemetry HTML elements to UI

Description

Function that adds telemetry HTML elements to UI

Usage

use_telemetry(id = "")

Arguments

id

(optional) string with id representing the namespace

Value

A shiny.tag object to be included in the UI of a Shiny app.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.