The yaml_agent_show_exprs() function follows the specifications of a pointblank YAML file to generate and show the pointblank expressions for generating the described validation plan. The expressions are shown in the console, providing an opportunity to copy the statements and extend as needed. A pointblank YAML file can itself be generated by using the yaml_write() function with a pre-existing agent, or, it can be carefully written by hand.

yaml_agent_show_exprs(filename, path = NULL)



The name of the YAML file that contains fields related to an agent.


An optional path to the YAML file (combined with filename).

Function ID


See also


if (interactive()) { # Let's create a validation plan for the # data quality analysis of the `small_table` # dataset; we need an agent and its # table-prep formula enables retrieval # of the target table agent <- create_agent( read_fn = ~small_table, label = "A simple example with the `small_table`.", actions = action_levels( warn_at = 0.10, stop_at = 0.25, notify_at = 0.35 ) ) %>% col_exists(vars(date, date_time)) %>% col_vals_regex( vars(b), regex = "[0-9]-[a-z]{3}-[0-9]{3}" ) %>% rows_distinct() %>% col_vals_gt(vars(d), value = 100) %>% col_vals_lte(vars(c), value = 5) # The agent can be written to a pointblank # YAML file with `yaml_write()` yaml_write( agent = agent, filename = "agent-small_table.yml" ) # The 'agent-small_table.yml' file is # available in the package through # `system.file()` yml_file <- system.file( "yaml", "agent-small_table.yml", package = "pointblank" ) # At a later time, the YAML file can # be read into a new agent with the # `yaml_read_agent()` function agent <- yaml_read_agent(filename = yml_file) class(agent) # To get a sense of which expressions are # being used to generate the new agent, we # can use `yaml_agent_show_exprs()` yaml_agent_show_exprs(filename = yml_file) }