A demonstration script that uses pointblank, logging, email notification, and a gt table report

pointblank_demo.R

library(pointblank)
library(log4r)
library(blastula)

# Create a connection to the game analytics data
# This is the `intendo` database
con <-
  DBI::dbConnect(
    drv = RMariaDB::MariaDB(),
    dbname = Sys.getenv("DBNAME"),
    username = Sys.getenv("USERNAME"),
    password = Sys.getenv("PASSWORD"),
    host = Sys.getenv("HOST"),
    port = Sys.getenv("PORT")
  )

# Create a log4r `logger` object
logger <- logger("WARN", appenders = file_appender("log_file"))

# Create custom logging functions with `log4r` to react to any
# `warn` or `stop` states. The `.vars_list` list is available
# in the context where the function will be evaluated
log4r_warn <- function(vl) {
  log4r::warn(logger, glue::glue(
    "Step {vl$i} exceeded the `warn` threshold (f_failed = {vl$f_failed}) ['{vl$name}']"
  ))
}
log4r_stop <- function(vl) {
  log4r::warn(logger, glue::glue(
    "Step {vl$i} exceeded the `stop` threshold (f_failed = {vl$f_failed}) ['{vl$name}']"
  ))
}

# Create an email notifier using `blastula`
email_blast <- function(vl) {
  compose_email(
    body = glue::glue(
      "Validation step {vl$i} indicates some serious problems \\
      (f_failed = {vl$f_failed}) ['{vl$name}']. Problem rows extracted."
    )
  ) %>%
    smtp_send(
      to = "[email protected]",
      from = "[email protected]",
      subject = "Validation of the table has failed.",
      credentials = creds_key(id = "gmail")
    )
}

# Set failure thresholds and functions that are
# actioned from exceeding certain error levels
al <- 
  action_levels(
    warn_at = 0.02, stop_at = 0.05, notify_at = 0.10,
    fns = list(
      warn = ~ log4r_warn(.vars_list),
      stop = ~ log4r_stop(.vars_list),
      notify = ~ email_blast(.vars_list)
    )
  )

# Validate the Intendo `users` table
agent <- 
  tbl(con, "users") %>%
  create_agent(name = "Intendo: 'users' table") %>%
  rows_distinct(columns = vars(user_id)) %>%
  col_vals_between(
    vars(first_login), left = "2015-01-01", right = "2015-12-30",
    actions = al
  ) %>%
  col_vals_null(
    vars(ad_revenue),
    preconditions = ~ tbl %>% filter(is.na(ad_count)),
    actions = al
  ) %>%
  col_vals_equal(
    vars(customer), value = 1,
    preconditions = ~ tbl %>% filter(!is.na(iap_count)),
    actions = al
  ) %>%
  col_vals_in_set(
    vars(country), set = c(
      "China", "Egypt", "France", "Germany", "Hong Kong", "India",
      "Japan", "Mexico", "Norway", "Philippines", "Portugal",
      "Russia", "South Africa", "South Korea", "Spain", "Sweden",
      "Switzerland", "United Kingdom", "United States"),
    actions = al
  ) %>%
  col_vals_in_set(
    vars(platform), set = c("apple", "android"),
    actions = al
  ) %>%
  col_vals_in_set(
    vars(acquired), set = c("apple", "facebook", "organic"),
    actions = al
  ) %>%
  interrogate()

# This is the part where gt comes in
agent %>% get_agent_report()

# Read from the generated `log_file`
readLines("log_file")