Function reference • teal

Core `teal` functions

Main functions needed to build a teal app

init(): Create the server and UI function for the shiny app

teal_data_module() eval_code(<teal_data_module>,<character>) within(<teal_data_module>): Data module for teal applications

module() modules() format(<teal_module>) print(<teal_module>) format(<teal_modules>) print(<teal_modules>): Create teal_module and teal_modules objects.

ui_teal_with_splash() srv_teal_with_splash(): Add splash screen to teal application.

teal_slices() as.teal_slices() c(<teal_slices>): Filter settings for teal applications

Helper Functions

Helper functions for teal

build_app_title(): Build app title with favicon

Example module

A simple teal module

example_module(): An example teal module

Creating reports

reporter_previewer_module(): Create a teal module for previewing a report

TealReportCard: TealReportCard

report_card_template(): Template function for TealReportCard creation and customization

landing_popup_module(): Landing popup module

Functions for module developers

as_tdata(): Downgrade teal_data objects in modules for compatibility

new_tdata(): Create a tdata object

get_code_tdata(): Wrapper for get_code.tdata

get_metadata(): Function to get metadata from a tdata object

tdata2env(): Function to convert a tdata object to an environment

teal_data_module() eval_code(<teal_data_module>,<character>) within(<teal_data_module>): Data module for teal applications

show_rcode_modal(): Show R code modal

join_keys(<tdata>): Extract join_keys from tdata

Validation functions

validate_has_data(): Validate that dataset has a minimum number of observations

validate_has_elements(): Validates that vector has length greater than 0

validate_has_variable(): Validates that dataset contains specific variable

validate_in(): Validates that vector includes all expected values

validate_inputs(): Send input validation messages to output.

validate_n_levels(): Validate that variables has expected number of levels

validate_no_intersection(): Validates no intersection between two vectors

validate_one_row_per_id(): Validate that dataset has unique rows for key variables