From f8de32290191fdc087c60b1781762ba604855747 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 10:41:37 -0400 Subject: [PATCH 01/37] modify function formals --- R/action_levels.R | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index 47aa940a9..f299cef45 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -301,10 +301,14 @@ NULL #' @rdname action_levels #' @export action_levels <- function( + warn = NULL, + error = NULL, + critical = NULL, + fns = NULL, + ..., warn_at = NULL, stop_at = NULL, - notify_at = NULL, - fns = NULL + notify_at = NULL ) { fns <- normalize_fns_list(fns = fns) From aeae7ab8b643ed10fe37bb469ae8e2a9af8c40d9 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 10:59:17 -0400 Subject: [PATCH 02/37] soft deprecation safeguards --- R/action_levels.R | 37 ++++++++++++++++++++++++++++++------- 1 file changed, 30 insertions(+), 7 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index f299cef45..4a93f25b4 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -104,6 +104,8 @@ #' `list(warn = ~ warning("Too many failures."))`. A series of expressions for #' each named state can be used by enclosing the set of statements with `{ }`. #' +#' @inheritParams rlang::args_dots_empty +#' #' @return An `action_levels` object. #' #' @section Defining threshold values: @@ -311,11 +313,32 @@ action_levels <- function( notify_at = NULL ) { + # Gradual argument name deprecation + ## Deprecation message + if (!missing(warn_at) || !missing(stop_at) || !missing(notify_at)) { + cli::cli_warn( + c("!" = "`warn_at`, `stop_at`, and `notify_at` are deprecated.", + " " = "Action levels are now `warn`, `error`, and `critical`."), + class = "deprecatedWarning", + .frequency = "regularly", + .frequency_id = "pointblank-action-levels-args-deprecation" + ) + } + ## Guard partial matching and redundant args + rlang::check_dots_empty() + rlang::check_exclusive(warn, warn_at, .require = FALSE) + rlang::check_exclusive(error, stop_at, .require = FALSE) + rlang::check_exclusive(critical, notify_at, .require = FALSE) + ## Resolve names + warn <- warn %||% warn_at + error <- error %||% stop_at + critical <- critical %||% notify_at + fns <- normalize_fns_list(fns = fns) - warn_list <- normalize_fraction_count(warn_at) - stop_list <- normalize_fraction_count(stop_at) - notify_list <- normalize_fraction_count(notify_at) + warn_list <- normalize_fraction_count(warn) + stop_list <- normalize_fraction_count(error) + notify_list <- normalize_fraction_count(critical) action_levels <- list( @@ -337,14 +360,14 @@ action_levels <- function( #' @rdname action_levels #' @export -warn_on_fail <- function(warn_at = 1) { - action_levels(warn_at = warn_at, fns = list(warn = ~stock_warning(x = x))) +warn_on_fail <- function(warn = 1) { + action_levels(warn = warn, fns = list(warn = ~stock_warning(x = x))) } #' @rdname action_levels #' @export -stop_on_fail <- function(stop_at = 1) { - action_levels(stop_at = stop_at, fns = list(stop = ~stock_stoppage(x = x))) +stop_on_fail <- function(error = 1) { + action_levels(error = error, fns = list(stop = ~stock_stoppage(x = x))) } normalize_fns_list <- function(fns) { From 718e0169d477791bfd9d8dd9c92617aa650e4b3c Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:08:29 -0400 Subject: [PATCH 03/37] use lifecycle badges; add lifecycle to suggests as requirement for vignette building --- DESCRIPTION | 3 ++- R/action_levels.R | 10 ++++++--- man/figures/lifecycle-deprecated.svg | 21 +++++++++++++++++++ man/figures/lifecycle-experimental.svg | 21 +++++++++++++++++++ man/figures/lifecycle-stable.svg | 29 ++++++++++++++++++++++++++ man/figures/lifecycle-superseded.svg | 21 +++++++++++++++++++ 6 files changed, 101 insertions(+), 4 deletions(-) create mode 100644 man/figures/lifecycle-deprecated.svg create mode 100644 man/figures/lifecycle-experimental.svg create mode 100644 man/figures/lifecycle-stable.svg create mode 100644 man/figures/lifecycle-superseded.svg diff --git a/DESCRIPTION b/DESCRIPTION index 5505108d4..71a258774 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -66,7 +66,8 @@ Suggests: rmarkdown, sparklyr, dittodb, - odbc + odbc, + lifecycle Roxygen: list(markdown = TRUE) Config/testthat/edition: 3 Config/testthat/parallel: true diff --git a/R/action_levels.R b/R/action_levels.R index 4a93f25b4..dec6aeb44 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -72,21 +72,21 @@ #' on the entire interrogation, allowing for finer control on side effects and #' reducing potential for duplicating any side effects. #' -#' @param warn_at *Threshold value for the 'warn' failure state* +#' @param warn *Threshold value for the 'warn' failure state* #' #' `scalar(val>=0)` // *default:* `NULL` (`optional`) #' #' Either the threshold number or the threshold fraction of *failing* test #' units that result in entering the `warn` failure state. #' -#' @param stop_at *Threshold value for the 'stop' failure state* +#' @param error *Threshold value for the 'stop' failure state* #' #' `scalar(val>=0)` // *default:* `NULL` (`optional`) #' #' Either the threshold number or the threshold fraction of *failing* test #' units that result in entering the `stop` failure state. #' -#' @param notify_at *Threshold value for the 'notify' failure state* +#' @param critical *Threshold value for the 'notify' failure state* #' #' `scalar(val>=0)` // *default:* `NULL` (`optional`) #' @@ -106,6 +106,10 @@ #' #' @inheritParams rlang::args_dots_empty #' +#' @param warn_at `r lifecycle::badge("deprecated")` +#' @param stop_at `r lifecycle::badge("deprecated")` +#' @param notify_at `r lifecycle::badge("deprecated")` +#' #' @return An `action_levels` object. #' #' @section Defining threshold values: diff --git a/man/figures/lifecycle-deprecated.svg b/man/figures/lifecycle-deprecated.svg new file mode 100644 index 000000000..b61c57c3f --- /dev/null +++ b/man/figures/lifecycle-deprecated.svg @@ -0,0 +1,21 @@ + + lifecycle: deprecated + + + + + + + + + + + + + + + lifecycle + + deprecated + + diff --git a/man/figures/lifecycle-experimental.svg b/man/figures/lifecycle-experimental.svg new file mode 100644 index 000000000..5d88fc2c6 --- /dev/null +++ b/man/figures/lifecycle-experimental.svg @@ -0,0 +1,21 @@ + + lifecycle: experimental + + + + + + + + + + + + + + + lifecycle + + experimental + + diff --git a/man/figures/lifecycle-stable.svg b/man/figures/lifecycle-stable.svg new file mode 100644 index 000000000..9bf21e76b --- /dev/null +++ b/man/figures/lifecycle-stable.svg @@ -0,0 +1,29 @@ + + lifecycle: stable + + + + + + + + + + + + + + + + lifecycle + + + + stable + + + diff --git a/man/figures/lifecycle-superseded.svg b/man/figures/lifecycle-superseded.svg new file mode 100644 index 000000000..db8d757f7 --- /dev/null +++ b/man/figures/lifecycle-superseded.svg @@ -0,0 +1,21 @@ + + lifecycle: superseded + + + + + + + + + + + + + + + lifecycle + + superseded + + From 285ee9554727849b696d4a1a28d5604b5e499fc9 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:09:24 -0400 Subject: [PATCH 04/37] use_tidy_description() --- DESCRIPTION | 63 ++++++++++++++++++++++++++++------------------------- 1 file changed, 33 insertions(+), 30 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 71a258774..6d0b253df 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,31 +1,29 @@ Type: Package Package: pointblank +Title: Data Validation and Organization of Metadata for Local and Remote + Tables Version: 0.12.2.9000 -Title: Data Validation and Organization of Metadata for Local and Remote Tables -Description: Validate data in data frames, 'tibble' objects, 'Spark' - 'DataFrames', and database tables. Validation pipelines can be made using - easily-readable, consecutive validation steps. Upon execution of the - validation plan, several reporting options are available. User-defined - thresholds for failure rates allow for the determination of appropriate - reporting actions. Many other workflows are available including an - information management workflow, where the aim is to record, collect, and - generate useful information on data tables. Authors@R: c( - person("Richard", "Iannone", , "rich@posit.co", c("aut", "cre"), + person("Richard", "Iannone", , "rich@posit.co", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3925-190X")), - person("Mauricio", "Vargas", , "mavargas11@uc.cl", c("aut"), + person("Mauricio", "Vargas", , "mavargas11@uc.cl", role = "aut", comment = c(ORCID = "0000-0003-1017-7574")), - person("June", "Choe", , "jchoe001@gmail.com", c("aut"), + person("June", "Choe", , "jchoe001@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-0701-921X")), - person("Olivier", "Roy", role = c("ctb")) - ) + person("Olivier", "Roy", role = "ctb") + ) +Description: Validate data in data frames, 'tibble' objects, 'Spark' + 'DataFrames', and database tables. Validation pipelines can be made + using easily-readable, consecutive validation steps. Upon execution of + the validation plan, several reporting options are available. + User-defined thresholds for failure rates allow for the determination + of appropriate reporting actions. Many other workflows are available + including an information management workflow, where the aim is to + record, collect, and generate useful information on data tables. License: MIT + file LICENSE -URL: https://rstudio.github.io/pointblank/, https://github.com/rstudio/pointblank +URL: https://rstudio.github.io/pointblank/, + https://github.com/rstudio/pointblank BugReports: https://github.com/rstudio/pointblank/issues -Encoding: UTF-8 -LazyData: true -ByteCompile: true -RoxygenNote: 7.3.2 Depends: R (>= 3.5.0) Imports: @@ -33,16 +31,16 @@ Imports: blastula (>= 0.3.3), cli (>= 3.6.0), DBI (>= 1.1.0), + dbplyr (>= 2.3.0), digest (>= 0.6.27), dplyr (>= 1.1.0), - dbplyr (>= 2.3.0), fs (>= 1.6.0), glue (>= 1.6.2), gt (>= 0.9.0), htmltools (>= 0.5.4), knitr (>= 1.42), - rlang (>= 1.0.3), magrittr, + rlang (>= 1.0.3), scales (>= 1.2.1), testthat (>= 3.2.0), tibble (>= 3.1.8), @@ -53,22 +51,27 @@ Suggests: arrow, bigrquery, data.table, + dittodb, duckdb, ggforce, ggplot2 (>= 3.5.0), jsonlite, + lifecycle, log4r, lubridate, - RSQLite, - RMySQL, - RPostgres, + odbc, readr, rmarkdown, - sparklyr, - dittodb, - odbc, - lifecycle -Roxygen: list(markdown = TRUE) + RMySQL, + RPostgres, + RSQLite, + sparklyr +ByteCompile: true Config/testthat/edition: 3 Config/testthat/parallel: true -Config/testthat/start-first: expectation_fns, scan_data,tidyselect_fails_safely_batch,test_fns +Config/testthat/start-first: expectation_fns, + scan_data,tidyselect_fails_safely_batch,test_fns +Encoding: UTF-8 +LazyData: true +Roxygen: list(markdown = TRUE) +RoxygenNote: 7.3.2 From 64eaa163974375fd3103e991a04216c66d1c121f Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:13:00 -0400 Subject: [PATCH 05/37] document() --- man/action_levels.Rd | 53 +++++++++++++++++++++++++++++--------------- 1 file changed, 35 insertions(+), 18 deletions(-) diff --git a/man/action_levels.Rd b/man/action_levels.Rd index 09e87e188..b1477ea1d 100644 --- a/man/action_levels.Rd +++ b/man/action_levels.Rd @@ -6,28 +6,37 @@ \alias{stop_on_fail} \title{Set action levels: failure thresholds and functions to invoke} \usage{ -action_levels(warn_at = NULL, stop_at = NULL, notify_at = NULL, fns = NULL) - -warn_on_fail(warn_at = 1) - -stop_on_fail(stop_at = 1) +action_levels( + warn = NULL, + error = NULL, + critical = NULL, + fns = NULL, + ..., + warn_at = NULL, + stop_at = NULL, + notify_at = NULL +) + +warn_on_fail(warn = 1) + +stop_on_fail(error = 1) } \arguments{ -\item{warn_at}{\emph{Threshold value for the 'warn' failure state} +\item{warn}{\emph{Threshold value for the 'warn' failure state} \code{scalar(val>=0)} // \emph{default:} \code{NULL} (\code{optional}) Either the threshold number or the threshold fraction of \emph{failing} test units that result in entering the \code{warn} failure state.} -\item{stop_at}{\emph{Threshold value for the 'stop' failure state} +\item{error}{\emph{Threshold value for the 'stop' failure state} \code{scalar(val>=0)} // \emph{default:} \code{NULL} (\code{optional}) Either the threshold number or the threshold fraction of \emph{failing} test units that result in entering the \code{stop} failure state.} -\item{notify_at}{\emph{Threshold value for the 'notify' failure state} +\item{critical}{\emph{Threshold value for the 'notify' failure state} \code{scalar(val>=0)} // \emph{default:} \code{NULL} (\code{optional}) @@ -44,6 +53,14 @@ the set of \code{warn}, \code{stop}, and \code{notify}. The functions correspond failure states are provided as formulas (e.g., \code{list(warn = ~ warning("Too many failures."))}. A series of expressions for each named state can be used by enclosing the set of statements with \code{{ }}.} + +\item{...}{These dots are for future extensions and must be empty.} + +\item{warn_at}{\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}} + +\item{stop_at}{\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}} + +\item{notify_at}{\ifelse{html}{\href{https://lifecycle.r-lib.org/articles/stages.html#deprecated}{\figure{lifecycle-deprecated.svg}{options: alt='[Deprecated]'}}}{\strong{[Deprecated]}}} } \value{ An \code{action_levels} object. @@ -142,7 +159,7 @@ For these examples, we will use the included \code{small_table} dataset. Create an \code{action_levels} object with fractional values for the \code{warn}, \code{stop}, and \code{notify} states. -\if{html}{\out{
}}\preformatted{al <- +\if{html}{\out{
}}\preformatted{al <- action_levels( warn_at = 0.2, stop_at = 0.8, @@ -227,21 +244,21 @@ data). }\if{html}{\out{
}} \preformatted{## # A tibble: 13 × 8 -## date_time date a b c d e +## date_time date a b c d e ## -## 1 2016-01-04 11:00:00 2016-01-04 2 1-bcd-… 3 3423. TRUE -## 2 2016-01-04 00:32:00 2016-01-04 3 5-egh-… 8 10000. TRUE -## 3 2016-01-05 13:32:00 2016-01-05 6 8-kdg-… 3 2343. TRUE +## 1 2016-01-04 11:00:00 2016-01-04 2 1-bcd-… 3 3423. TRUE +## 2 2016-01-04 00:32:00 2016-01-04 3 5-egh-… 8 10000. TRUE +## 3 2016-01-05 13:32:00 2016-01-05 6 8-kdg-… 3 2343. TRUE ## 4 2016-01-06 17:23:00 2016-01-06 2 5-jdo-… NA 3892. FALSE -## 5 2016-01-09 12:36:00 2016-01-09 8 3-ldm-… 7 284. TRUE -## 6 2016-01-11 06:15:00 2016-01-11 4 2-dhe-… 4 3291. TRUE -## 7 2016-01-15 18:46:00 2016-01-15 7 1-knw-… 3 843. TRUE +## 5 2016-01-09 12:36:00 2016-01-09 8 3-ldm-… 7 284. TRUE +## 6 2016-01-11 06:15:00 2016-01-11 4 2-dhe-… 4 3291. TRUE +## 7 2016-01-15 18:46:00 2016-01-15 7 1-knw-… 3 843. TRUE ## 8 2016-01-17 11:27:00 2016-01-17 4 5-boe-… 2 1036. FALSE ## 9 2016-01-20 04:30:00 2016-01-20 3 5-bce-… 9 838. FALSE ## 10 2016-01-20 04:30:00 2016-01-20 3 5-bce-… 9 838. FALSE -## 11 2016-01-26 20:07:00 2016-01-26 4 2-dmx-… 7 834. TRUE +## 11 2016-01-26 20:07:00 2016-01-26 4 2-dmx-… 7 834. TRUE ## 12 2016-01-28 02:51:00 2016-01-28 2 7-dmx-… 8 108. FALSE -## 13 2016-01-30 11:23:00 2016-01-30 1 3-dka-… NA 2230. TRUE +## 13 2016-01-30 11:23:00 2016-01-30 1 3-dka-… NA 2230. TRUE ## # … with 1 more variable: f ## Warning message: ## Exceedance of failed test units where values in `a` should have been > From c668faeb571c40b332d11d7a18a20ba156448cf8 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:18:30 -0400 Subject: [PATCH 06/37] factor out deprecation warning and add safeguards to _on_fail() shotcuts --- R/action_levels.R | 34 +++++++++++++++++++++++++--------- 1 file changed, 25 insertions(+), 9 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index dec6aeb44..cf3f39222 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -320,13 +320,7 @@ action_levels <- function( # Gradual argument name deprecation ## Deprecation message if (!missing(warn_at) || !missing(stop_at) || !missing(notify_at)) { - cli::cli_warn( - c("!" = "`warn_at`, `stop_at`, and `notify_at` are deprecated.", - " " = "Action levels are now `warn`, `error`, and `critical`."), - class = "deprecatedWarning", - .frequency = "regularly", - .frequency_id = "pointblank-action-levels-args-deprecation" - ) + warn_deprecated_action_levels() } ## Guard partial matching and redundant args rlang::check_dots_empty() @@ -364,13 +358,25 @@ action_levels <- function( #' @rdname action_levels #' @export -warn_on_fail <- function(warn = 1) { +warn_on_fail <- function(warn = 1, warn_at = NULL) { + rlang::check_exclusive(warn, warn_at, .require = FALSE) + if (!missing(warn_at)) { + warn_deprecated_action_levels() + } + warn <- warn_at %||% warn + action_levels(warn = warn, fns = list(warn = ~stock_warning(x = x))) } #' @rdname action_levels #' @export -stop_on_fail <- function(error = 1) { +stop_on_fail <- function(error = 1, stop_at = NULL) { + rlang::check_exclusive(error, stop_at, .require = FALSE) + if (!missing(stop_at)) { + warn_deprecated_action_levels() + } + error <- stop_at %||% error + action_levels(error = error, fns = list(stop = ~stock_stoppage(x = x))) } @@ -538,3 +544,13 @@ stock_warning <- function(x) { warning(failure_message, call. = FALSE) } + +warn_deprecated_action_levels <- function() { + cli::cli_warn( + c("!" = "`warn_at`, `stop_at`, and `notify_at` are deprecated.", + " " = "Action levels are now `warn`, `error`, and `critical`."), + class = "deprecatedWarning", + .frequency = "regularly", + .frequency_id = "pointblank-action-levels-args-deprecation" + ) +} From 57902959f657509a7a0007650dc5190f9216dfff Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:22:24 -0400 Subject: [PATCH 07/37] deprecate stop_on_fail() for error_on_fail() --- R/action_levels.R | 18 +++++++++++------- 1 file changed, 11 insertions(+), 7 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index cf3f39222..2157e35df 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -370,16 +370,20 @@ warn_on_fail <- function(warn = 1, warn_at = NULL) { #' @rdname action_levels #' @export -stop_on_fail <- function(error = 1, stop_at = NULL) { - rlang::check_exclusive(error, stop_at, .require = FALSE) - if (!missing(stop_at)) { - warn_deprecated_action_levels() - } - error <- stop_at %||% error - +error_on_fail <- function(error = 1) { action_levels(error = error, fns = list(stop = ~stock_stoppage(x = x))) } +#' @rdname action_levels +#' @export +stop_on_fail <- function(stop_at = 1) { + cli::cli_warn(c( + "!" = "`stop_on_fail(stop_at)` is deprecated.", + " " = "Please use `error_on_fail(error)` instead." + )) + error_on_fail(error = stop_at) +} + normalize_fns_list <- function(fns) { if (is.null(fns) || (is.list(fns) && length(fns) == 0)) { From 74970d63fc21dfd4118c1cd382bed1fb67e7e0b4 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:24:31 -0400 Subject: [PATCH 08/37] document() --- NAMESPACE | 1 + man/action_levels.Rd | 7 +++++-- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 24736fbf4..e39af4d0f 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -61,6 +61,7 @@ export(deactivate_steps) export(draft_validation) export(email_blast) export(email_create) +export(error_on_fail) export(expect_col_count_match) export(expect_col_exists) export(expect_col_is_character) diff --git a/man/action_levels.Rd b/man/action_levels.Rd index b1477ea1d..2b186acb1 100644 --- a/man/action_levels.Rd +++ b/man/action_levels.Rd @@ -3,6 +3,7 @@ \name{action_levels} \alias{action_levels} \alias{warn_on_fail} +\alias{error_on_fail} \alias{stop_on_fail} \title{Set action levels: failure thresholds and functions to invoke} \usage{ @@ -17,9 +18,11 @@ action_levels( notify_at = NULL ) -warn_on_fail(warn = 1) +warn_on_fail(warn = 1, warn_at = NULL) -stop_on_fail(error = 1) +error_on_fail(error = 1) + +stop_on_fail(stop_at = 1) } \arguments{ \item{warn}{\emph{Threshold value for the 'warn' failure state} From 1452f34d3f1b75588a0511b60cd52fca2ab54db8 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 11:45:06 -0400 Subject: [PATCH 09/37] clean up documentation --- R/action_levels.R | 57 ++++++++++++++++++++++---------------------- man/action_levels.Rd | 57 ++++++++++++++++++++++---------------------- 2 files changed, 58 insertions(+), 56 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index 2157e35df..e245143a0 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -26,8 +26,8 @@ #' The `action_levels()` function works with the `actions` argument that is #' present in the [create_agent()] function and in every validation step #' function (which also has an `actions` argument). With it, we can provide -#' threshold *failure* values for any combination of `warn`, `stop`, or `notify` -#' failure states. +#' threshold *failure* values for any combination of `warn`, `error`, or +#' `critical` failure states. #' #' We can react to any entering of a state by supplying corresponding functions #' to the `fns` argument. They will undergo evaluation at the time when the @@ -41,32 +41,33 @@ #' warnings, throwing errors) in the case of validation functions operating #' directly on data (e.g., `mtcars %>% col_vals_lt("mpg", 35)`). There are two #' helper functions that are convenient when using validation functions directly -#' on data (the `agent`-less workflow): `warn_on_fail()` and `stop_on_fail()`. +#' on data (the `agent`-less workflow): `warn_on_fail()` and `error_on_fail()`. #' These helpers either warn or stop (default failure threshold for each is set #' to `1`), and, they do so with informative warning or error messages. The -#' `stop_on_fail()` helper is applied by default when using validation functions -#' directly on data (more information on this is provided in *Details*). +#' `error_on_fail()` helper is applied by default when using validation +#' functions directly on data (more information on this is provided in +#' *Details*). #' #' @details #' #' The output of the `action_levels()` call in `actions` will be interpreted #' slightly differently if using an *agent* or using validation functions #' directly on a data table. For convenience, when working directly on data, any -#' values supplied to `warn_at` or `stop_at` will be automatically given a stock +#' values supplied to `warn` or `error` will be automatically given a stock #' `warning()` or `stop()` function. For example using #' `small_table %>% col_is_integer("date")` will provide a detailed stop message #' by default, indicating the reason for the failure. If you were to supply the -#' `fns` for `stop` or `warn` manually then the stock functions would be +#' `fns` for `warn` or `error` manually then the stock functions would be #' overridden. Furthermore, if `actions` is NULL in this workflow (the default), -#' **pointblank** will use a `stop_at` value of `1` (providing a detailed, +#' **pointblank** will use a `error` value of `1` (providing a detailed, #' context-specific error message if there are any *failing* units). We can #' absolutely suppress this automatic stopping behavior at each validation #' step by setting `active = FALSE`. In this interactive data case, there is no -#' stock function given for `notify_at`. The `notify` failure state is less +#' stock function given for `critical`. The `critical` failure state is less #' commonly used in this workflow as it is in the *agent*-based one. #' #' When using an *agent*, we often opt to not use any functions in `fns` as the -#' `warn`, `stop`, and `notify` failure states will be reported on when using +#' `warn`, `error`, and `critical` failure states will be reported on when using #' `create_agent_report()` (and, usually that's sufficient). Instead, using the #' `end_fns` argument is a better choice since that scheme provides useful data #' on the entire interrogation, allowing for finer control on side effects and @@ -84,14 +85,14 @@ #' `scalar(val>=0)` // *default:* `NULL` (`optional`) #' #' Either the threshold number or the threshold fraction of *failing* test -#' units that result in entering the `stop` failure state. +#' units that result in entering the `error` failure state. #' #' @param critical *Threshold value for the 'notify' failure state* #' #' `scalar(val>=0)` // *default:* `NULL` (`optional`) #' #' Either the threshold number or the threshold fraction of *failing* test -#' units that result in entering the `notify` failure state. +#' units that result in entering the `critical` failure state. #' #' @param fns *Functions to execute when entering failure states* #' @@ -99,7 +100,7 @@ #' #' A named list of functions that is to be paired with the appropriate failure #' states. The syntax for this list involves using failure state names from -#' the set of `warn`, `stop`, and `notify`. The functions corresponding to the +#' the set of `warn`, `error`, and `critical`. The functions corresponding to the #' failure states are provided as formulas (e.g., #' `list(warn = ~ warning("Too many failures."))`. A series of expressions for #' each named state can be used by enclosing the set of statements with `{ }`. @@ -114,12 +115,12 @@ #' #' @section Defining threshold values: #' -#' Any threshold values supplied for the `warn_at`, `stop_at`, or `notify_at` -#' arguments correspond to the `warn`, `stop`, and `notify` failure states, -#' respectively. A threshold value can either relates to an absolute number of -#' test units or a fraction-of-total test units that are *failing*. Exceeding -#' the threshold means entering one or more of the `warn`, `stop`, or `notify` -#' failure states. +#' Any threshold values supplied for the `warn`, `error`, or `critical` +#' arguments correspond to the failure states of the same name. +#' A threshold value can either relates to an absolute number of +#' test units or a fraction-of-total test units that are *failing*. +#' Exceeding the threshold means entering one or more of the `warn`, `error`, +#' or `critical` failure states. #' #' If a threshold value is a decimal value between `0` and `1` then it's a #' proportional failure threshold (e.g., `0.15` indicates that if 15 percent of @@ -137,14 +138,14 @@ #' ``` #' #' Create an `action_levels` object with fractional values for the `warn`, -#' `stop`, and `notify` states. +#' `error`, and `critical` states. #' #' ```r #' al <- #' action_levels( -#' warn_at = 0.2, -#' stop_at = 0.8, -#' notify_at = 0.5 +#' warn = 0.2, +#' error = 0.8, +#' critical = 0.5 #' ) #' ``` #' @@ -195,7 +196,7 @@ #' ) %>% #' col_vals_gt( #' columns = a, value = 2, -#' actions = warn_on_fail(warn_at = 0.5) +#' actions = warn_on_fail(warn = 0.5) #' ) %>% #' col_vals_lt( #' columns = d, value = 20000 @@ -227,7 +228,7 @@ #' small_table %>% #' col_vals_gt( #' columns = a, value = 2, -#' actions = warn_on_fail(warn_at = 2) +#' actions = warn_on_fail(warn = 2) #' ) #' ``` #' @@ -258,7 +259,7 @@ #' #' #' With the same pipeline, not supplying anything for `actions` (it's `NULL` by -#' default) will have the same effect as using `stop_on_fail(stop_at = 1)`. +#' default) will have the same effect as using `error_on_fail(error = 1)`. #' #' ```r #' small_table %>% @@ -280,7 +281,7 @@ #' small_table %>% #' col_vals_gt( #' columns = a, value = 2, -#' actions = stop_on_fail(stop_at = 1) +#' actions = error_on_fail(error = 1) #' ) #' ``` #' @@ -293,7 +294,7 @@ #' ``` #' #' -#' This is because the `stop_on_fail()` call is auto-injected in the default +#' This is because the `error_on_fail()` call is auto-injected in the default #' case (when operating on data) for your convenience. Behind the scenes a #' 'secret agent' uses 'covert actions': all so you can type less. #' diff --git a/man/action_levels.Rd b/man/action_levels.Rd index 2b186acb1..ce4840dea 100644 --- a/man/action_levels.Rd +++ b/man/action_levels.Rd @@ -37,14 +37,14 @@ units that result in entering the \code{warn} failure state.} \code{scalar(val>=0)} // \emph{default:} \code{NULL} (\code{optional}) Either the threshold number or the threshold fraction of \emph{failing} test -units that result in entering the \code{stop} failure state.} +units that result in entering the \code{error} failure state.} \item{critical}{\emph{Threshold value for the 'notify' failure state} \code{scalar(val>=0)} // \emph{default:} \code{NULL} (\code{optional}) Either the threshold number or the threshold fraction of \emph{failing} test -units that result in entering the \code{notify} failure state.} +units that result in entering the \code{critical} failure state.} \item{fns}{\emph{Functions to execute when entering failure states} @@ -52,7 +52,7 @@ units that result in entering the \code{notify} failure state.} A named list of functions that is to be paired with the appropriate failure states. The syntax for this list involves using failure state names from -the set of \code{warn}, \code{stop}, and \code{notify}. The functions corresponding to the +the set of \code{warn}, \code{error}, and \code{critical}. The functions corresponding to the failure states are provided as formulas (e.g., \code{list(warn = ~ warning("Too many failures."))}. A series of expressions for each named state can be used by enclosing the set of statements with \code{{ }}.} @@ -72,8 +72,8 @@ An \code{action_levels} object. The \code{action_levels()} function works with the \code{actions} argument that is present in the \code{\link[=create_agent]{create_agent()}} function and in every validation step function (which also has an \code{actions} argument). With it, we can provide -threshold \emph{failure} values for any combination of \code{warn}, \code{stop}, or \code{notify} -failure states. +threshold \emph{failure} values for any combination of \code{warn}, \code{error}, or +\code{critical} failure states. We can react to any entering of a state by supplying corresponding functions to the \code{fns} argument. They will undergo evaluation at the time when the @@ -87,31 +87,32 @@ of \code{action_levels()} is required to have any useful side effects (i.e., warnings, throwing errors) in the case of validation functions operating directly on data (e.g., \code{mtcars \%>\% col_vals_lt("mpg", 35)}). There are two helper functions that are convenient when using validation functions directly -on data (the \code{agent}-less workflow): \code{warn_on_fail()} and \code{stop_on_fail()}. +on data (the \code{agent}-less workflow): \code{warn_on_fail()} and \code{error_on_fail()}. These helpers either warn or stop (default failure threshold for each is set to \code{1}), and, they do so with informative warning or error messages. The -\code{stop_on_fail()} helper is applied by default when using validation functions -directly on data (more information on this is provided in \emph{Details}). +\code{error_on_fail()} helper is applied by default when using validation +functions directly on data (more information on this is provided in +\emph{Details}). } \details{ The output of the \code{action_levels()} call in \code{actions} will be interpreted slightly differently if using an \emph{agent} or using validation functions directly on a data table. For convenience, when working directly on data, any -values supplied to \code{warn_at} or \code{stop_at} will be automatically given a stock +values supplied to \code{warn} or \code{error} will be automatically given a stock \code{warning()} or \code{stop()} function. For example using \code{small_table \%>\% col_is_integer("date")} will provide a detailed stop message by default, indicating the reason for the failure. If you were to supply the -\code{fns} for \code{stop} or \code{warn} manually then the stock functions would be +\code{fns} for \code{warn} or \code{error} manually then the stock functions would be overridden. Furthermore, if \code{actions} is NULL in this workflow (the default), -\strong{pointblank} will use a \code{stop_at} value of \code{1} (providing a detailed, +\strong{pointblank} will use a \code{error} value of \code{1} (providing a detailed, context-specific error message if there are any \emph{failing} units). We can absolutely suppress this automatic stopping behavior at each validation step by setting \code{active = FALSE}. In this interactive data case, there is no -stock function given for \code{notify_at}. The \code{notify} failure state is less +stock function given for \code{critical}. The \code{critical} failure state is less commonly used in this workflow as it is in the \emph{agent}-based one. When using an \emph{agent}, we often opt to not use any functions in \code{fns} as the -\code{warn}, \code{stop}, and \code{notify} failure states will be reported on when using +\code{warn}, \code{error}, and \code{critical} failure states will be reported on when using \code{create_agent_report()} (and, usually that's sufficient). Instead, using the \code{end_fns} argument is a better choice since that scheme provides useful data on the entire interrogation, allowing for finer control on side effects and @@ -120,12 +121,12 @@ reducing potential for duplicating any side effects. \section{Defining threshold values}{ -Any threshold values supplied for the \code{warn_at}, \code{stop_at}, or \code{notify_at} -arguments correspond to the \code{warn}, \code{stop}, and \code{notify} failure states, -respectively. A threshold value can either relates to an absolute number of -test units or a fraction-of-total test units that are \emph{failing}. Exceeding -the threshold means entering one or more of the \code{warn}, \code{stop}, or \code{notify} -failure states. +Any threshold values supplied for the \code{warn}, \code{error}, or \code{critical} +arguments correspond to the failure states of the same name. +A threshold value can either relates to an absolute number of +test units or a fraction-of-total test units that are \emph{failing}. +Exceeding the threshold means entering one or more of the \code{warn}, \code{error}, +or \code{critical} failure states. If a threshold value is a decimal value between \code{0} and \code{1} then it's a proportional failure threshold (e.g., \code{0.15} indicates that if 15 percent of @@ -160,13 +161,13 @@ For these examples, we will use the included \code{small_table} dataset. }\if{html}{\out{
}} Create an \code{action_levels} object with fractional values for the \code{warn}, -\code{stop}, and \code{notify} states. +\code{error}, and \code{critical} states. \if{html}{\out{
}}\preformatted{al <- action_levels( - warn_at = 0.2, - stop_at = 0.8, - notify_at = 0.5 + warn = 0.2, + error = 0.8, + critical = 0.5 ) }\if{html}{\out{
}} @@ -213,7 +214,7 @@ another such object to the validation step instead (this time using the ) \%>\% col_vals_gt( columns = a, value = 2, - actions = warn_on_fail(warn_at = 0.5) + actions = warn_on_fail(warn = 0.5) ) \%>\% col_vals_lt( columns = d, value = 20000 @@ -242,7 +243,7 @@ data). \if{html}{\out{
}}\preformatted{small_table \%>\% col_vals_gt( columns = a, value = 2, - actions = warn_on_fail(warn_at = 2) + actions = warn_on_fail(warn = 2) ) }\if{html}{\out{
}} @@ -273,7 +274,7 @@ data). With the same pipeline, not supplying anything for \code{actions} (it's \code{NULL} by -default) will have the same effect as using \code{stop_on_fail(stop_at = 1)}. +default) will have the same effect as using \code{error_on_fail(error = 1)}. \if{html}{\out{
}}\preformatted{small_table \%>\% col_vals_gt(columns = a, value = 2) @@ -291,7 +292,7 @@ Here's the equivalent set of statements: \if{html}{\out{
}}\preformatted{small_table \%>\% col_vals_gt( columns = a, value = 2, - actions = stop_on_fail(stop_at = 1) + actions = error_on_fail(error = 1) ) }\if{html}{\out{
}} @@ -302,7 +303,7 @@ Here's the equivalent set of statements: ## * failure level (4) >= failure threshold (1) }\if{html}{\out{
}} -This is because the \code{stop_on_fail()} call is auto-injected in the default +This is because the \code{error_on_fail()} call is auto-injected in the default case (when operating on data) for your convenience. Behind the scenes a 'secret agent' uses 'covert actions': all so you can type less. } From 38ba2984d84e839f89c30e3792224a1ff4a3ceac Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 12:01:03 -0400 Subject: [PATCH 10/37] more internal renaming --- R/action_levels.R | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index e245143a0..117652e37 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -100,8 +100,8 @@ #' #' A named list of functions that is to be paired with the appropriate failure #' states. The syntax for this list involves using failure state names from -#' the set of `warn`, `error`, and `critical`. The functions corresponding to the -#' failure states are provided as formulas (e.g., +#' the set of `warn`, `error`, and `critical`. The functions corresponding to +#' the failure states are provided as formulas (e.g., #' `list(warn = ~ warning("Too many failures."))`. A series of expressions for #' each named state can be used by enclosing the set of statements with `{ }`. #' @@ -336,17 +336,17 @@ action_levels <- function( fns <- normalize_fns_list(fns = fns) warn_list <- normalize_fraction_count(warn) - stop_list <- normalize_fraction_count(error) - notify_list <- normalize_fraction_count(critical) + error_list <- normalize_fraction_count(error) + critical_list <- normalize_fraction_count(critical) action_levels <- list( warn_fraction = warn_list$fraction, warn_count = warn_list$count, - stop_fraction = stop_list$fraction, - stop_count = stop_list$count, - notify_fraction = notify_list$fraction, - notify_count = notify_list$count, + stop_fraction = error_list$fraction, + stop_count = error_list$count, + notify_fraction = critical_list$fraction, + notify_count = critical_list$count, fns = fns ) From fbf6d68febc990916fe323aaa18f8b7b925994a9 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 12:27:42 -0400 Subject: [PATCH 11/37] broad strokes rename levels in tests --- tests/testthat/postgres.R | 2 +- tests/testthat/test-action_levels.R | 30 ++++++------ tests/testthat/test-brief.R | 10 ++-- tests/testthat/test-get_agent_report.R | 2 +- tests/testthat/test-interrogate_simple.R | 4 +- tests/testthat/test-interrogate_with_agent.R | 46 +++++++++---------- .../testthat/test-interrogate_with_agent_db.R | 40 ++++++++-------- tests/testthat/test-schema.R | 2 +- tests/testthat/test-write_testthat_file.R | 2 +- tests/testthat/test-x_list.R | 2 +- tests/testthat/test-yaml.R | 38 +++++++-------- 11 files changed, 89 insertions(+), 89 deletions(-) diff --git a/tests/testthat/postgres.R b/tests/testthat/postgres.R index b201d3526..f83724430 100644 --- a/tests/testthat/postgres.R +++ b/tests/testthat/postgres.R @@ -18,7 +18,7 @@ test_that("pointblank agent works with dittodb-mocked Postgres database connecti # 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) + al <- action_levels(warn = 0.02, error = 0.05, critical = 0.10) # Validate the `assembly` table in the `aedes_aegypti_core_55_1d` DB # the expect_warning is used to suppres the message diff --git a/tests/testthat/test-action_levels.R b/tests/testthat/test-action_levels.R index 865a71d82..0c9dc63e4 100644 --- a/tests/testthat/test-action_levels.R +++ b/tests/testthat/test-action_levels.R @@ -27,7 +27,7 @@ test_that("The `action_levels()` helper function works as expected", { expect_length(al[[7]], 3) # Create an `action_levels()` list with fractional values - al <- action_levels(warn_at = 0.2, stop_at = 0.8, notify_at = 0.345) + al <- action_levels(warn = 0.2, error = 0.8, critical = 0.345) expect_s3_class(al, "action_levels") expect_length(al, 7) @@ -54,7 +54,7 @@ test_that("The `action_levels()` helper function works as expected", { expect_null(al[[7]][[3]]) # Create an `action_levels()` list with count values - al <- action_levels(warn_at = 20, stop_at = 80, notify_at = 34.6) + al <- action_levels(warn = 20, error = 80, critical = 34.6) al %>% expect_s3_class("action_levels") al %>% @@ -79,17 +79,17 @@ test_that("The `action_levels()` helper function works as expected", { al[[7]] %>% length() %>% expect_equal(3) # Expect an error if non-numeric values provided - expect_error(action_levels(warn_at = "20")) + expect_error(action_levels(warn = "20")) # Expect an error if any value less than or # equal to zero is provided - expect_error(action_levels(warn_at = 0)) - expect_error(action_levels(warn_at = -1.5)) + expect_error(action_levels(warn = 0)) + expect_error(action_levels(warn = -1.5)) # Add functions to the `fns` arg al <- action_levels( - warn_at = 3, + warn = 3, fns = list(warn = ~ my_great_function(vl = .vars_list)) ) @@ -119,13 +119,13 @@ test_that("The `action_levels()` helper function works as expected", { # Expect an error if not all components # of the `fns` list are formulas - expect_error(action_levels(warn_at = 3, fns = list(warn = "text"))) + expect_error(action_levels(warn = 3, fns = list(warn = "text"))) # Expect an error if not all components # of the `fns` list are named expect_error( action_levels( - warn_at = 3, + warn = 3, fns = list( warn = ~ my_great_function(vl = .vars_list), ~ another_function() @@ -138,7 +138,7 @@ test_that("The `action_levels()` helper function works as expected", { # or `notify` expect_error( action_levels( - warn_at = 3, + warn = 3, fns = list( warn = ~ my_great_function(vl = .vars_list), notable = ~ another_function() @@ -153,12 +153,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(warn_at = 3, fns = list(warn = ~"warning") + actions = action_levels(warn = 3, fns = list(warn = ~"warning") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(warn_at = 0.1, fns = list(warn = ~"warning") + actions = action_levels(warn = 0.1, fns = list(warn = ~"warning") ) ) %>% interrogate() @@ -170,12 +170,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(notify_at = 3, fns = list(notify = ~"notify") + actions = action_levels(critical = 3, fns = list(notify = ~"notify") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(notify_at = 0.1, fns = list(notify = ~"notify") + actions = action_levels(critical = 0.1, fns = list(notify = ~"notify") ) ) %>% interrogate() @@ -187,12 +187,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(stop_at = 3, fns = list(stop = ~"stop") + actions = action_levels(error = 3, fns = list(stop = ~"stop") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(stop_at = 0.1, fns = list(stop = ~"stop") + actions = action_levels(error = 0.1, fns = list(stop = ~"stop") ) ) %>% interrogate() diff --git a/tests/testthat/test-brief.R b/tests/testthat/test-brief.R index f422b9bcf..8e678a2e0 100644 --- a/tests/testthat/test-brief.R +++ b/tests/testthat/test-brief.R @@ -152,7 +152,7 @@ test_that("Briefs batch tests: special validations", { ~ test_col_vals_gt(., columns = c, value = vars(a)), ~ col_vals_not_null(., columns = b), preconditions = ~ . %>% dplyr::filter(a < 10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2), + actions = action_levels(warn = 0.1, error = 0.2), label = "The `serially()` step.", active = FALSE, brief = "custom brief" @@ -168,7 +168,7 @@ test_that("Briefs batch tests: special validations", { specially( fn = function(x) { ... }, preconditions = ~ . %>% dplyr::filter(a < 10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2), + actions = action_levels(warn = 0.1, error = 0.2), label = "The `specially()` step.", active = FALSE, brief = "custom brief" @@ -187,7 +187,7 @@ test_that("Briefs batch tests: special validations", { ~ col_vals_not_null(., columns = b), preconditions = ~ . %>% dplyr::filter(a < 10), # segments = b ~ c("group_1", "group_2"), - actions = action_levels(warn_at = 0.1, stop_at = 0.2), + actions = action_levels(warn = 0.1, error = 0.2), label = "The `conjointly()` step.", active = FALSE, brief = "custom brief" @@ -205,7 +205,7 @@ test_that("Briefs batch tests: special validations", { ~ col_vals_not_null(., columns = b), preconditions = ~ . %>% dplyr::filter(a < 10), segments = b ~ c("group_1", "group_2"), - actions = action_levels(warn_at = 0.1, stop_at = 0.2), + actions = action_levels(warn = 0.1, error = 0.2), label = "The `conjointly()` step.", active = FALSE, brief = "custom brief constant" @@ -216,7 +216,7 @@ test_that("Briefs batch tests: special validations", { ~ col_vals_not_null(., columns = b), preconditions = ~ . %>% dplyr::filter(a < 10), segments = b ~ c("group_1", "group_2"), - actions = action_levels(warn_at = 0.1, stop_at = 0.2), + actions = action_levels(warn = 0.1, error = 0.2), label = "The `conjointly()` step.", active = FALSE, brief = c("custom brief multi1", "custom brief multi2") diff --git a/tests/testthat/test-get_agent_report.R b/tests/testthat/test-get_agent_report.R index 85b468102..4253fb484 100644 --- a/tests/testthat/test-get_agent_report.R +++ b/tests/testthat/test-get_agent_report.R @@ -322,7 +322,7 @@ test_that("report shows informative error tooltips", { test_that("rows of report can be shuffled or dropped", { agent <- iris %>% - create_agent(actions = action_levels(warn_at = 1)) %>% + create_agent(actions = action_levels(warn = 1)) %>% col_exists("Petal.Length", active = has_columns(iris, Petal.Length)) %>% col_exists("skip", diff --git a/tests/testthat/test-interrogate_simple.R b/tests/testthat/test-interrogate_simple.R index f6a32053d..a6a184923 100644 --- a/tests/testthat/test-interrogate_simple.R +++ b/tests/testthat/test-interrogate_simple.R @@ -2038,7 +2038,7 @@ test_that("The inclusivity options work well for the range-based validations", { col_vals_between( columns = vars(a), left = 1, right = 10, inclusive = c(FALSE, FALSE), - actions = action_levels(warn_at = 3) + actions = action_levels(warn = 3) ) ) expect_warning( @@ -2046,7 +2046,7 @@ test_that("The inclusivity options work well for the range-based validations", { col_vals_between( columns = vars(a), left = 1, right = 10, inclusive = c(FALSE, FALSE), - actions = action_levels(warn_at = 2) + actions = action_levels(warn = 2) ) ) diff --git a/tests/testthat/test-interrogate_with_agent.R b/tests/testthat/test-interrogate_with_agent.R index fb377461c..93c448adc 100644 --- a/tests/testthat/test-interrogate_with_agent.R +++ b/tests/testthat/test-interrogate_with_agent.R @@ -1495,7 +1495,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 1.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1507,7 +1507,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 1.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1522,7 +1522,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 2.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1534,7 +1534,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 2.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1549,7 +1549,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 0.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1561,7 +1561,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 0.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1576,7 +1576,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 1.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1588,7 +1588,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 1.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1603,7 +1603,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 3.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1615,7 +1615,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 3.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1630,7 +1630,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 2.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1642,7 +1642,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), value = 2.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1657,7 +1657,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), left = 0, right = 3.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1669,7 +1669,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), left = 0, right = 3.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1684,7 +1684,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), left = 3.0, right = 4.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1696,7 +1696,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), left = 3.0, right = 4.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1711,7 +1711,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), regex = "[0-9]-[a-z]{3}-[0-9]{3}", na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1723,7 +1723,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(a), regex = "[0-9]-[a-z]{3}-[0-9]{3}", na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1756,7 +1756,7 @@ test_that("The validations with sets can include NA values", { col_vals_in_set( columns = vars(a), set = c("one", "two", "three", "four", "five"), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1767,7 +1767,7 @@ test_that("The validations with sets can include NA values", { col_vals_in_set( columns = vars(a), set = c("one", "two", "three", "four", "five", NA), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1780,7 +1780,7 @@ test_that("The validations with sets can include NA values", { col_vals_not_in_set( columns = vars(a), set = c("four", "five", "six", NA), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1791,7 +1791,7 @@ test_that("The validations with sets can include NA values", { col_vals_not_in_set( columns = vars(a), set = c("four", "five", "six"), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1925,7 +1925,7 @@ test_that("Select validation steps can be `active` or not", { # Perform validation directly on data with `active = TRUE` # for all of the validation steps; set action levels to # warn when there is a single unit failing in each step - al <- action_levels(warn_at = 1) + al <- action_levels(warn = 1) expect_snapshot( obj <- small_table %>% diff --git a/tests/testthat/test-interrogate_with_agent_db.R b/tests/testthat/test-interrogate_with_agent_db.R index a128dee06..f6daf2671 100644 --- a/tests/testthat/test-interrogate_with_agent_db.R +++ b/tests/testthat/test-interrogate_with_agent_db.R @@ -843,7 +843,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -856,7 +856,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -872,7 +872,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 2.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -885,7 +885,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 2.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -901,7 +901,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 0.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -914,7 +914,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 0.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -930,7 +930,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -943,7 +943,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -959,7 +959,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 3.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -972,7 +972,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 3.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -988,7 +988,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1001,7 +1001,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), value = 1.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1017,7 +1017,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), left = 0, right = 3.0, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1030,7 +1030,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), left = 0, right = 3.0, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1046,7 +1046,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), left = 3.0, right = 4.5, na_pass = FALSE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1059,7 +1059,7 @@ test_that("Interrogating with an agent incorporates the `na_pass` option", { columns = vars(g), left = 3.0, right = 4.5, na_pass = TRUE, - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1084,7 +1084,7 @@ test_that("The validations with sets can include NA values", { col_vals_in_set( columns = vars(g), set = c("one", "two", "three", "four", "five"), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1095,7 +1095,7 @@ test_that("The validations with sets can include NA values", { col_vals_in_set( columns = vars(g), set = c("one", "two", "three", "four", "five", NA), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1108,7 +1108,7 @@ test_that("The validations with sets can include NA values", { col_vals_not_in_set( columns = vars(g), set = c("four", "five", "six", NA), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% @@ -1119,7 +1119,7 @@ test_that("The validations with sets can include NA values", { col_vals_not_in_set( columns = vars(g), set = c("four", "five", "six"), - actions = action_levels(warn_at = 1) + actions = action_levels(warn = 1) ) %>% interrogate() %>% all_passed() %>% diff --git a/tests/testthat/test-schema.R b/tests/testthat/test-schema.R index 32c2a96c5..05316e82f 100644 --- a/tests/testthat/test-schema.R +++ b/tests/testthat/test-schema.R @@ -1,4 +1,4 @@ -al <- action_levels(stop_at = 1) +al <- action_levels(error = 1) test_that("The `cols_schema_match()` function works with an agent", { diff --git a/tests/testthat/test-write_testthat_file.R b/tests/testthat/test-write_testthat_file.R index f65b854b8..d7c37f000 100644 --- a/tests/testthat/test-write_testthat_file.R +++ b/tests/testthat/test-write_testthat_file.R @@ -2,7 +2,7 @@ agent <- create_agent( tbl = ~ small_table, - actions = action_levels(stop_at = 0.1) + actions = action_levels(error = 0.1) ) %>% col_vals_gt( vars(date_time), vars(date), diff --git a/tests/testthat/test-x_list.R b/tests/testthat/test-x_list.R index a56101163..3a75456dc 100644 --- a/tests/testthat/test-x_list.R +++ b/tests/testthat/test-x_list.R @@ -1,4 +1,4 @@ -al <- action_levels(warn_at = 0.1, stop_at = 0.2) +al <- action_levels(warn = 0.1, error = 0.2) agent <- create_agent(tbl = small_table, actions = al) %>% diff --git a/tests/testthat/test-yaml.R b/tests/testthat/test-yaml.R index 89bb36de5..ae9957c31 100644 --- a/tests/testthat/test-yaml.R +++ b/tests/testthat/test-yaml.R @@ -17,7 +17,7 @@ get_oneline_expr_str <- function(agent, expanded = FALSE) { test_that("YAML writing and reading works as expected", { - al <- action_levels(warn_at = 0.1, stop_at = 0.2) + al <- action_levels(warn = 0.1, error = 0.2) agent <- create_agent(tbl = ~ small_table, actions = al) %>% @@ -273,10 +273,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_lt( vars(a, c), 1, - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_lt(vars(a, c), 1, label = "my_label")), @@ -342,10 +342,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_between( vars(c), left = vars(a), right = vars(d), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_between(vars(c), left = -5, right = 15, label = "my_label")), @@ -403,10 +403,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_not_between( vars(c), left = vars(a), right = vars(d), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_between(vars(a), left = -5, right = 15, label = "my_label")), @@ -448,10 +448,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_in_set( vars(c), set = c(1:10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -493,10 +493,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_not_in_set( vars(c), set = c(1:10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -538,10 +538,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_make_set( vars(c), set = c(1:10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -583,10 +583,10 @@ test_that("Individual validation steps make the YAML round-trip successfully", { agent %>% col_vals_make_subset( vars(c), set = c(1:10), - actions = action_levels(warn_at = 0.1, stop_at = 0.2) + actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_subset(vars(f), set = c("low", "high"), label = "my_label")), @@ -829,9 +829,9 @@ test_that("Individual validation steps make the YAML round-trip successfully", { ) expect_equal( get_oneline_expr_str( - agent %>% col_is_character(vars(b, f), actions = action_levels(warn_at = 0.1, stop_at = 0.2)) + agent %>% col_is_character(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_is_character(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_is_character(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_is_character(vars(b), label = "my_label")), @@ -852,9 +852,9 @@ test_that("Individual validation steps make the YAML round-trip successfully", { ) expect_equal( get_oneline_expr_str( - agent %>% col_exists(vars(b, f), actions = action_levels(warn_at = 0.1, stop_at = 0.2)) + agent %>% col_exists(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_exists(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_exists(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_exists(vars(b), label = "my_label")), From 7733fd3ee663d0781c4ebeb07c2f58d6d6dcf69f Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 12:29:13 -0400 Subject: [PATCH 12/37] revert name changes in yaml tests for now --- tests/testthat/test-yaml.R | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/tests/testthat/test-yaml.R b/tests/testthat/test-yaml.R index ae9957c31..da002dcdc 100644 --- a/tests/testthat/test-yaml.R +++ b/tests/testthat/test-yaml.R @@ -276,7 +276,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_lt(vars(a, c), 1, label = "my_label")), @@ -345,7 +345,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_between(vars(c), left = -5, right = 15, label = "my_label")), @@ -406,7 +406,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_between(vars(a), left = -5, right = 15, label = "my_label")), @@ -451,7 +451,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -496,7 +496,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -541,7 +541,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -586,7 +586,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" + "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_subset(vars(f), set = c("low", "high"), label = "my_label")), @@ -831,7 +831,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { get_oneline_expr_str( agent %>% col_is_character(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_is_character(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" + "col_is_character(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_is_character(vars(b), label = "my_label")), @@ -854,7 +854,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { get_oneline_expr_str( agent %>% col_exists(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_exists(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" + "col_exists(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_exists(vars(b), label = "my_label")), From 6a241d474e9b164ba833ef3e4c01927701aa3f3a Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 12:29:42 -0400 Subject: [PATCH 13/37] more internal renaming --- R/action_levels.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/action_levels.R b/R/action_levels.R index 117652e37..e021ce840 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -469,7 +469,7 @@ prime_actions <- function(actions) { } else { actions <- action_levels( - stop_at = 1, + error = 1, fns = list(stop = ~stock_stoppage(x = x)) ) } From 98b5342b4cf56fdfa24730e046db3e1df1b4ae76 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 13:17:01 -0400 Subject: [PATCH 14/37] use new names in test_/expect_ --- R/col_count_match.R | 4 ++-- R/col_exists.R | 4 ++-- R/col_is_character.R | 4 ++-- R/col_is_date.R | 4 ++-- R/col_is_factor.R | 4 ++-- R/col_is_integer.R | 4 ++-- R/col_is_logical.R | 4 ++-- R/col_is_numeric.R | 4 ++-- R/col_is_posix.R | 4 ++-- R/col_schema_match.R | 4 ++-- R/col_vals_between.R | 4 ++-- R/col_vals_decreasing.R | 4 ++-- R/col_vals_equal.R | 4 ++-- R/col_vals_expr.R | 4 ++-- R/col_vals_gt.R | 4 ++-- R/col_vals_gte.R | 4 ++-- R/col_vals_in_set.R | 4 ++-- R/col_vals_increasing.R | 4 ++-- R/col_vals_lt.R | 4 ++-- R/col_vals_lte.R | 4 ++-- R/col_vals_make_set.R | 4 ++-- R/col_vals_make_subset.R | 4 ++-- R/col_vals_not_between.R | 4 ++-- R/col_vals_not_equal.R | 4 ++-- R/col_vals_not_in_set.R | 4 ++-- R/col_vals_not_null.R | 4 ++-- R/col_vals_null.R | 4 ++-- R/col_vals_regex.R | 4 ++-- R/col_vals_within_spec.R | 4 ++-- R/conjointly.R | 4 ++-- R/row_count_match.R | 4 ++-- R/rows_complete.R | 4 ++-- R/rows_distinct.R | 4 ++-- R/serially.R | 4 ++-- R/specially.R | 4 ++-- R/tbl_match.R | 4 ++-- 36 files changed, 72 insertions(+), 72 deletions(-) diff --git a/R/col_count_match.R b/R/col_count_match.R index 33e5b379b..078a50cce 100644 --- a/R/col_count_match.R +++ b/R/col_count_match.R @@ -353,7 +353,7 @@ expect_col_count_match <- function( col_count_match( count = {{ count }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -406,7 +406,7 @@ test_col_count_match <- function( col_count_match( count = {{ count }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_exists.R b/R/col_exists.R index 986c9e0e3..024dc2a10 100644 --- a/R/col_exists.R +++ b/R/col_exists.R @@ -334,7 +334,7 @@ expect_col_exists <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_exists( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -404,7 +404,7 @@ test_col_exists <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_exists( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_character.R b/R/col_is_character.R index 6d34e92a8..c8105d677 100644 --- a/R/col_is_character.R +++ b/R/col_is_character.R @@ -325,7 +325,7 @@ expect_col_is_character <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_character( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -396,7 +396,7 @@ test_col_is_character <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_character( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_date.R b/R/col_is_date.R index 351e70da6..4c4b0b1bc 100644 --- a/R/col_is_date.R +++ b/R/col_is_date.R @@ -317,7 +317,7 @@ expect_col_is_date <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_date( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -390,7 +390,7 @@ test_col_is_date <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_date( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_factor.R b/R/col_is_factor.R index 0e8a3350c..b20010b38 100644 --- a/R/col_is_factor.R +++ b/R/col_is_factor.R @@ -323,7 +323,7 @@ expect_col_is_factor <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_factor( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -396,7 +396,7 @@ test_col_is_factor <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_factor( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_integer.R b/R/col_is_integer.R index 0796f8900..8aec61d58 100644 --- a/R/col_is_integer.R +++ b/R/col_is_integer.R @@ -321,7 +321,7 @@ expect_col_is_integer <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_integer( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -394,7 +394,7 @@ test_col_is_integer <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_integer( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_logical.R b/R/col_is_logical.R index c6832e161..b6a852fe0 100644 --- a/R/col_is_logical.R +++ b/R/col_is_logical.R @@ -318,7 +318,7 @@ expect_col_is_logical <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_logical( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -391,7 +391,7 @@ test_col_is_logical <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_logical( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_numeric.R b/R/col_is_numeric.R index 459b4ee1e..80b4e4d09 100644 --- a/R/col_is_numeric.R +++ b/R/col_is_numeric.R @@ -318,7 +318,7 @@ expect_col_is_numeric <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_numeric( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -391,7 +391,7 @@ test_col_is_numeric <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_numeric( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_is_posix.R b/R/col_is_posix.R index 229d8c873..b13f186dc 100644 --- a/R/col_is_posix.R +++ b/R/col_is_posix.R @@ -318,7 +318,7 @@ expect_col_is_posix <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_posix( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -391,7 +391,7 @@ test_col_is_posix <- function( create_agent(tbl = object, label = "::QUIET::") %>% col_is_posix( columns = {{ columns }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_schema_match.R b/R/col_schema_match.R index 1408e78f4..6c90afa25 100644 --- a/R/col_schema_match.R +++ b/R/col_schema_match.R @@ -410,7 +410,7 @@ expect_col_schema_match <- function( complete = complete, in_order = in_order, is_exact = is_exact, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -467,7 +467,7 @@ test_col_schema_match <- function( complete = complete, in_order = in_order, is_exact = is_exact, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_between.R b/R/col_vals_between.R index d0715a8f7..621afe7d4 100644 --- a/R/col_vals_between.R +++ b/R/col_vals_between.R @@ -509,7 +509,7 @@ expect_col_vals_between <- function( inclusive = inclusive, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -599,7 +599,7 @@ test_col_vals_between <- function( inclusive = inclusive, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_decreasing.R b/R/col_vals_decreasing.R index d8545fd97..f632de3ad 100644 --- a/R/col_vals_decreasing.R +++ b/R/col_vals_decreasing.R @@ -487,7 +487,7 @@ expect_col_vals_decreasing <- function( increasing_tol = increasing_tol, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -567,7 +567,7 @@ test_col_vals_decreasing <- function( increasing_tol = increasing_tol, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_equal.R b/R/col_vals_equal.R index fa81a154b..a704a3544 100644 --- a/R/col_vals_equal.R +++ b/R/col_vals_equal.R @@ -437,7 +437,7 @@ expect_col_vals_equal <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -518,7 +518,7 @@ test_col_vals_equal <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_expr.R b/R/col_vals_expr.R index ab8f930fb..7ef6a5591 100644 --- a/R/col_vals_expr.R +++ b/R/col_vals_expr.R @@ -432,7 +432,7 @@ expect_col_vals_expr <- function( col_vals_expr( expr = {{ expr }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -485,7 +485,7 @@ test_col_vals_expr <- function( col_vals_expr( expr = {{ expr }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_gt.R b/R/col_vals_gt.R index 07b64c80e..903ecadf3 100644 --- a/R/col_vals_gt.R +++ b/R/col_vals_gt.R @@ -559,7 +559,7 @@ expect_col_vals_gt <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -640,7 +640,7 @@ test_col_vals_gt <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_gte.R b/R/col_vals_gte.R index 2588a08b2..1c944ce22 100644 --- a/R/col_vals_gte.R +++ b/R/col_vals_gte.R @@ -436,7 +436,7 @@ expect_col_vals_gte <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -517,7 +517,7 @@ test_col_vals_gte <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_in_set.R b/R/col_vals_in_set.R index 37cbdde20..333c431fb 100644 --- a/R/col_vals_in_set.R +++ b/R/col_vals_in_set.R @@ -427,7 +427,7 @@ expect_col_vals_in_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -505,7 +505,7 @@ test_col_vals_in_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_increasing.R b/R/col_vals_increasing.R index 1b55db9c8..3c8805c2c 100644 --- a/R/col_vals_increasing.R +++ b/R/col_vals_increasing.R @@ -475,7 +475,7 @@ expect_col_vals_increasing <- function( decreasing_tol = decreasing_tol, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -561,7 +561,7 @@ test_col_vals_increasing <- function( decreasing_tol = decreasing_tol, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_lt.R b/R/col_vals_lt.R index 179c64ef6..95d5f4b35 100644 --- a/R/col_vals_lt.R +++ b/R/col_vals_lt.R @@ -438,7 +438,7 @@ expect_col_vals_lt <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -519,7 +519,7 @@ test_col_vals_lt <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_lte.R b/R/col_vals_lte.R index 7d21a5a65..a96a3a07c 100644 --- a/R/col_vals_lte.R +++ b/R/col_vals_lte.R @@ -439,7 +439,7 @@ expect_col_vals_lte <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -520,7 +520,7 @@ test_col_vals_lte <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_make_set.R b/R/col_vals_make_set.R index caab56fd2..e25f982d7 100644 --- a/R/col_vals_make_set.R +++ b/R/col_vals_make_set.R @@ -429,7 +429,7 @@ expect_col_vals_make_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -507,7 +507,7 @@ test_col_vals_make_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_make_subset.R b/R/col_vals_make_subset.R index 23106f1cf..09c0f0426 100644 --- a/R/col_vals_make_subset.R +++ b/R/col_vals_make_subset.R @@ -425,7 +425,7 @@ expect_col_vals_make_subset <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -503,7 +503,7 @@ test_col_vals_make_subset <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_not_between.R b/R/col_vals_not_between.R index d23982593..fa80f8d8b 100644 --- a/R/col_vals_not_between.R +++ b/R/col_vals_not_between.R @@ -512,7 +512,7 @@ expect_col_vals_not_between <- function( inclusive = inclusive, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -602,7 +602,7 @@ test_col_vals_not_between <- function( inclusive = inclusive, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_not_equal.R b/R/col_vals_not_equal.R index 052fe586f..ab332f29e 100644 --- a/R/col_vals_not_equal.R +++ b/R/col_vals_not_equal.R @@ -436,7 +436,7 @@ expect_col_vals_not_equal <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -517,7 +517,7 @@ test_col_vals_not_equal <- function( value = {{ value }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_not_in_set.R b/R/col_vals_not_in_set.R index 3f8fc1348..0321d2f13 100644 --- a/R/col_vals_not_in_set.R +++ b/R/col_vals_not_in_set.R @@ -422,7 +422,7 @@ expect_col_vals_not_in_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -500,7 +500,7 @@ test_col_vals_not_in_set <- function( columns = {{ columns }}, set = {{ set }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_not_null.R b/R/col_vals_not_null.R index 44129a0b4..e6439edda 100644 --- a/R/col_vals_not_null.R +++ b/R/col_vals_not_null.R @@ -409,7 +409,7 @@ expect_col_vals_not_null <- function( col_vals_not_null( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -483,7 +483,7 @@ test_col_vals_not_null <- function( col_vals_not_null( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_null.R b/R/col_vals_null.R index ee1814340..63d1b826d 100644 --- a/R/col_vals_null.R +++ b/R/col_vals_null.R @@ -408,7 +408,7 @@ expect_col_vals_null <- function( col_vals_null( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -482,7 +482,7 @@ test_col_vals_null <- function( col_vals_null( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_regex.R b/R/col_vals_regex.R index f961a16f7..e394dba57 100644 --- a/R/col_vals_regex.R +++ b/R/col_vals_regex.R @@ -430,7 +430,7 @@ expect_col_vals_regex <- function( regex = {{ regex }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -510,7 +510,7 @@ test_col_vals_regex <- function( regex = {{ regex }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/col_vals_within_spec.R b/R/col_vals_within_spec.R index 1557481f4..c8287434e 100644 --- a/R/col_vals_within_spec.R +++ b/R/col_vals_within_spec.R @@ -495,7 +495,7 @@ expect_col_vals_within_spec <- function( spec = {{ spec }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -575,7 +575,7 @@ test_col_vals_within_spec <- function( spec = {{ spec }}, na_pass = na_pass, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/conjointly.R b/R/conjointly.R index 5f203832c..844a35ec5 100644 --- a/R/conjointly.R +++ b/R/conjointly.R @@ -468,7 +468,7 @@ expect_conjointly <- function( conjointly( .list = .list, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -519,7 +519,7 @@ test_conjointly <- function( conjointly( .list = .list, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/row_count_match.R b/R/row_count_match.R index c382688d4..26e64c360 100644 --- a/R/row_count_match.R +++ b/R/row_count_match.R @@ -444,7 +444,7 @@ expect_row_count_match <- function( row_count_match( count = {{ count }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -514,7 +514,7 @@ test_row_count_match <- function( row_count_match( count = {{ count }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/rows_complete.R b/R/rows_complete.R index 9dce015df..4b12a7ab5 100644 --- a/R/rows_complete.R +++ b/R/rows_complete.R @@ -398,7 +398,7 @@ expect_rows_complete <- function( rows_complete( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -451,7 +451,7 @@ test_rows_complete <- function( rows_complete( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/rows_distinct.R b/R/rows_distinct.R index c7096f5ee..fb9c2a074 100644 --- a/R/rows_distinct.R +++ b/R/rows_distinct.R @@ -399,7 +399,7 @@ expect_rows_distinct <- function( rows_distinct( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -452,7 +452,7 @@ test_rows_distinct <- function( rows_distinct( columns = {{ columns }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/serially.R b/R/serially.R index bda525014..5bec3e072 100644 --- a/R/serially.R +++ b/R/serially.R @@ -708,7 +708,7 @@ expect_serially <- function( serially( .list = .list, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -759,7 +759,7 @@ test_serially <- function( serially( .list = .list, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/specially.R b/R/specially.R index 548f7f161..e37b852fa 100644 --- a/R/specially.R +++ b/R/specially.R @@ -422,7 +422,7 @@ expect_specially <- function( specially( fn = fn, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -470,7 +470,7 @@ test_specially <- function( specially( fn = fn, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set diff --git a/R/tbl_match.R b/R/tbl_match.R index a270c5dba..3f5679c33 100644 --- a/R/tbl_match.R +++ b/R/tbl_match.R @@ -398,7 +398,7 @@ expect_tbl_match <- function( tbl_match( tbl_compare = {{ tbl_compare }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set @@ -451,7 +451,7 @@ test_tbl_match <- function( tbl_match( tbl_compare = {{ tbl_compare }}, preconditions = {{ preconditions }}, - actions = action_levels(notify_at = threshold) + actions = action_levels(critical = threshold) ) %>% interrogate() %>% .$validation_set From 4a45001431465ecdceaddec462ffd26e2f5950a5 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 13:25:51 -0400 Subject: [PATCH 15/37] double agents use renamed levels --- R/interrogate.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/interrogate.R b/R/interrogate.R index 0ff376ee1..619063f39 100644 --- a/R/interrogate.R +++ b/R/interrogate.R @@ -526,7 +526,7 @@ interrogate <- function( tidy_gsub( "threshold\\s+?=\\s+?[0-9\\.]+?", paste0( - "actions = action_levels(stop_at = ", + "actions = action_levels(error = ", threshold_value, ")" ) ) @@ -550,7 +550,7 @@ interrogate <- function( tidy_gsub( "\\)$", paste0( - ", actions = action_levels(stop_at = ", + ", actions = action_levels(error = ", threshold_value, "))" ) ) From 06d943ff9480d70d6d665cfd6050e870be8c9d17 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 14:35:31 -0400 Subject: [PATCH 16/37] standardize fns to action_fns object internally --- R/action_levels.R | 59 +++++++++++++++++++++++++---------------------- 1 file changed, 32 insertions(+), 27 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index e021ce840..55b948219 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -333,7 +333,9 @@ action_levels <- function( error <- error %||% stop_at critical <- critical %||% notify_at - fns <- normalize_fns_list(fns = fns) + if (!inherits(fns, "action_fns")) { + fns <- normalize_fns_list(fns = fns) + } warn_list <- normalize_fraction_count(warn) error_list <- normalize_fraction_count(error) @@ -385,41 +387,44 @@ stop_on_fail <- function(stop_at = 1) { error_on_fail(error = stop_at) } -normalize_fns_list <- function(fns) { - - if (is.null(fns) || (is.list(fns) && length(fns) == 0)) { - return(list(warn = NULL, stop = NULL, notify = NULL)) +action_fns <- function(warn = NULL, error = NULL, critical = NULL) { + fns <- structure( + list(warn = warn, error = error, critical = critical, + stop = error, notify = critical), # temp compatibility with rest of internals + class = "action_fns" + ) + if (!all(vapply(fns, function(x) is.null(x) || is_formula(x), logical(1)))) { + cli::cli_abort("Action functions must be supplied as formulas.") } + fns +} - are_formulas <- - fns %>% - vapply( - FUN.VALUE = logical(1), USE.NAMES = FALSE, - FUN = function(x) rlang::is_formula(x) - ) - - if (!all(are_formulas)) { +normalize_fns_list <- function(fns) { - stop( - "All components of the `fns` list must be formulas.", - call. = FALSE - ) + if (is.null(fns)) { + return(action_fns()) } - if ("" %in% names(fns)) { + nms <- c("warn", "error", "critical", + "stop", "notify") - stop("The `fns` list must be fully named.", call. = FALSE) - } + stopifnot( + "`fns` must be a `action_fns()` object" = is.list(fns), + "The `fns` list must be fully named." = !("" %in% rlang::names2(fns)), + "`fns` must contain valid action levels" = all(names(fns) %in% nms) + ) - if (!all(names(fns) %in% c("warn", "stop", "notify"))) { + cli::cli_warn(c( + "!" = "Passing a list to `fns` is deprecated.", + " " = "Please use `action_fns()` instead." + )) - stop( - "All names in the `fns` list must be one of `warn`, `stop`, or `notify`.", - call. = FALSE - ) - } + warn <- fns$warn %||% fns$warn_at + error <- fns$error %||% fns$error_at + critical <- fns$critical %||% fns$notify_at + + action_fns(warn, error, critical) - fns } normalize_fraction_count <- function(x) { From 6f2d46c071d5a36bf111e36917648256c4f96da3 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 14:35:45 -0400 Subject: [PATCH 17/37] update tests to expect action_fns structure --- tests/testthat/test-action_levels.R | 15 +++++++-------- 1 file changed, 7 insertions(+), 8 deletions(-) diff --git a/tests/testthat/test-action_levels.R b/tests/testthat/test-action_levels.R index 0c9dc63e4..35f40b082 100644 --- a/tests/testthat/test-action_levels.R +++ b/tests/testthat/test-action_levels.R @@ -19,12 +19,12 @@ test_that("The `action_levels()` helper function works as expected", { expect_null(al[[4]]) expect_null(al[[5]]) expect_null(al[[6]]) - expect_named(al[[7]], c("warn", "stop", "notify")) + expect_true(all(c("warn", "stop", "notify") %in% names(al[[7]]))) expect_type(al[[7]], "list") expect_null(al[[7]][[1]]) expect_null(al[[7]][[2]]) expect_null(al[[7]][[3]]) - expect_length(al[[7]], 3) + expect_length(al[[7]], 5) # Create an `action_levels()` list with fractional values al <- action_levels(warn = 0.2, error = 0.8, critical = 0.345) @@ -46,8 +46,8 @@ test_that("The `action_levels()` helper function works as expected", { expect_equal(al$notify_fraction, 0.345) expect_null(al$notify_count) - expect_length(al[[7]], 3) - expect_named(al[[7]], c("warn", "stop", "notify")) + expect_length(al[[7]], 5) + expect_true(all(c("warn", "stop", "notify") %in% names(al[[7]]))) expect_type(al[[7]], "list") expect_null(al[[7]][[1]]) expect_null(al[[7]][[2]]) @@ -63,7 +63,7 @@ test_that("The `action_levels()` helper function works as expected", { "warn_fraction", "warn_count", "stop_fraction", "stop_count", "notify_fraction", "notify_count", "fns") ) - al[[7]] %>% expect_named(c("warn", "stop", "notify")) + expect_true(all(c("warn", "stop", "notify") %in% names(al[[7]]))) al$warn_fraction %>% expect_null() al$warn_count %>% expect_equal(20) @@ -76,7 +76,7 @@ test_that("The `action_levels()` helper function works as expected", { al[[7]][[2]] %>% expect_null() al[[7]][[3]] %>% expect_null() al %>% length() %>% expect_equal(7) - al[[7]] %>% length() %>% expect_equal(3) + expect_length(al[[7]], 5) # Expect an error if non-numeric values provided expect_error(action_levels(warn = "20")) @@ -101,7 +101,7 @@ test_that("The `action_levels()` helper function works as expected", { "warn_fraction", "warn_count", "stop_fraction", "stop_count", "notify_fraction", "notify_count", "fns") ) - al[[7]] %>% expect_named("warn") + expect_true(all(c("warn", "stop", "notify") %in% names(al[[7]]))) al[[7]][[1]] %>% expect_s3_class("formula") al[[7]][[1]] %>% as.character() %>% @@ -115,7 +115,6 @@ test_that("The `action_levels()` helper function works as expected", { al$notify_count %>% expect_null() al[[7]] %>% expect_type("list") al %>% expect_length(7) - al[[7]] %>% expect_length(1) # Expect an error if not all components # of the `fns` list are formulas From 7ecfa0157f84158f40d6ec701daa48ba6114d0a4 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 14:37:26 -0400 Subject: [PATCH 18/37] use action_fns in action_levels tests --- tests/testthat/test-action_levels.R | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/tests/testthat/test-action_levels.R b/tests/testthat/test-action_levels.R index 35f40b082..97a802fea 100644 --- a/tests/testthat/test-action_levels.R +++ b/tests/testthat/test-action_levels.R @@ -90,7 +90,7 @@ test_that("The `action_levels()` helper function works as expected", { al <- action_levels( warn = 3, - fns = list(warn = ~ my_great_function(vl = .vars_list)) + fns = action_fns(warn = ~ my_great_function(vl = .vars_list)) ) al %>% expect_s3_class("action_levels") @@ -118,7 +118,7 @@ test_that("The `action_levels()` helper function works as expected", { # Expect an error if not all components # of the `fns` list are formulas - expect_error(action_levels(warn = 3, fns = list(warn = "text"))) + expect_error(action_levels(warn = 3, fns = action_fns(warn = "text"))) # Expect an error if not all components # of the `fns` list are named @@ -138,7 +138,7 @@ test_that("The `action_levels()` helper function works as expected", { expect_error( action_levels( warn = 3, - fns = list( + fns = action_fns( warn = ~ my_great_function(vl = .vars_list), notable = ~ another_function() ) @@ -152,12 +152,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(warn = 3, fns = list(warn = ~"warning") + actions = action_levels(warn = 3, fns = action_fns(warn = ~"warning") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(warn = 0.1, fns = list(warn = ~"warning") + actions = action_levels(warn = 0.1, fns = action_fns(warn = ~"warning") ) ) %>% interrogate() @@ -169,12 +169,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(critical = 3, fns = list(notify = ~"notify") + actions = action_levels(critical = 3, fns = action_fns(critical = ~"critical") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(critical = 0.1, fns = list(notify = ~"notify") + actions = action_levels(critical = 0.1, fns = action_fns(critical = ~"critical") ) ) %>% interrogate() @@ -186,12 +186,12 @@ test_that("The appropriate actions occur when using `action_levels()`", { create_agent(tbl = small_table, label = "small_table_tests") %>% col_vals_gt( vars(d), 1000, - actions = action_levels(error = 3, fns = list(stop = ~"stop") + actions = action_levels(error = 3, fns = action_fns(error = ~"error") ) ) %>% col_vals_in_set( vars(f), c("low", "high"), - actions = action_levels(error = 0.1, fns = list(stop = ~"stop") + actions = action_levels(error = 0.1, fns = action_fns(error = ~"error") ) ) %>% interrogate() From 1a92a42bcff43e4b59b7579cb0e74b1bde7b6d00 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:00:36 -0400 Subject: [PATCH 19/37] use new action names in draft_validation --- R/draft_validation.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/draft_validation.R b/R/draft_validation.R index 4a9d5f7ac..37e84cf2d 100644 --- a/R/draft_validation.R +++ b/R/draft_validation.R @@ -348,7 +348,7 @@ draft_validation <- function( tbl = tbl, tbl_name = tbl_name, label = "Validation plan generated by `draft_validation()`.", - actions = action_levels(warn_at = 0.05, stop_at = 0.10), + actions = action_levels(warn = 0.05, error = 0.10), lang = lang ) From be64f218396c4680a44d4a14a80a96ae31085622 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:01:13 -0400 Subject: [PATCH 20/37] more use of action_fns --- R/action_levels.R | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index 55b948219..66da22edb 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -465,17 +465,17 @@ normalize_fraction_count <- function(x) { prime_actions <- function(actions) { if (!is.null(actions)) { - if (is.null(actions$fns$warn)) { - actions$fns$warn <- ~stock_warning(x = x) - } - if (is.null(actions$fns$stop)) { - actions$fns$stop <- ~stock_stoppage(x = x) - } + actions$fns <- + action_fns( + warn = actions$fns$warn %||% ~stock_warning(x = x), + error = actions$fns$stop %||% ~stock_stoppage(x = x), + critical = actions$fns$critical + ) } else { actions <- action_levels( error = 1, - fns = list(stop = ~stock_stoppage(x = x)) + fns = action_fns(error = ~stock_stoppage(x = x)) ) } From b196b8c11e31f3e9c88de5969738d35b615e8666 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:12:57 -0400 Subject: [PATCH 21/37] clean up duplicate code --- R/yaml_write.R | 2 -- 1 file changed, 2 deletions(-) diff --git a/R/yaml_write.R b/R/yaml_write.R index a1167be57..b16fa4027 100644 --- a/R/yaml_write.R +++ b/R/yaml_write.R @@ -752,8 +752,6 @@ to_list_action_levels <- function(actions) { agent_actions[sapply(agent_actions, is.null)] <- NULL agent_actions$fns[sapply(agent_actions$fns, is.null)] <- NULL - if (length(agent_actions$fns) == 0) agent_actions$fns <- NULL - if (length(agent_actions$fns) == 0) { agent_actions$fns <- NULL } else { From 7ae0ef270999a234266075c0a8f317e6569c1fd6 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:19:57 -0400 Subject: [PATCH 22/37] use error_on_fail() --- tests/testthat/test-interrogate_simple.R | 86 ++++++++++++------------ 1 file changed, 43 insertions(+), 43 deletions(-) diff --git a/tests/testthat/test-interrogate_simple.R b/tests/testthat/test-interrogate_simple.R index a6a184923..5f93c2d82 100644 --- a/tests/testthat/test-interrogate_simple.R +++ b/tests/testthat/test-interrogate_simple.R @@ -89,7 +89,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_lt( columns = vars(a), value = 7, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -136,7 +136,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_lte( columns = vars(a), value = 7, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -184,7 +184,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_equal( columns = vars(d), value = 283.94, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -233,7 +233,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_not_equal( columns = vars(d), value = 283.94, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -280,7 +280,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_gte( columns = vars(a), value = 3, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -327,7 +327,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_gt( columns = vars(a), value = 2, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -374,7 +374,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_between( columns = vars(d), left = 0, right = 1000, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -421,7 +421,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_not_between( columns = vars(d), left = 9000, right = 11000, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -467,7 +467,7 @@ test_that("Interrogating simply returns the expected results", { columns = vars(d), left = 0, right = 3000, preconditions = ~ . %>% dplyr::filter(date > "2016-01-20"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -514,7 +514,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_in_set( columns = vars(f), set = c("low", "mid", "higher"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -561,7 +561,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_not_in_set( columns = vars(f), set = c("lower", "mid", "higher"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -608,7 +608,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_in_set( columns = vars(f), set = c("low", "mid", "higher", "highest"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -622,7 +622,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_in_set( columns = vars(f), set = c("low", "mid"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -682,7 +682,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_make_subset( columns = vars(f), set = c("lower", "mid", "higher", "highest"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -696,7 +696,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_make_subset( columns = vars(f), set = c("low", "mid", "highly"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -740,7 +740,7 @@ test_that("Interrogating simply returns the expected results", { increasing_tbl %>% col_vals_increasing( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -784,7 +784,7 @@ test_that("Interrogating simply returns the expected results", { decreasing_tbl %>% col_vals_decreasing( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -831,7 +831,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_null( columns = vars(c), preconditions = ~ . %>% dplyr::filter(date != "2016-01-06"), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -875,7 +875,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_vals_not_null( columns = vars(c), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -922,7 +922,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_regex( columns = vars(b), regex = "[0-7]-[a-z]*?-[0-9]*?", - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -978,7 +978,7 @@ test_that("Interrogating simply returns the expected results", { col_vals_within_spec( columns = vars(isbn_numbers), spec = "isbn", - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1022,7 +1022,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_vals_expr( expr = ~ a %% 2 == 0, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1052,7 +1052,7 @@ test_that("Interrogating simply returns the expected results", { # Perform a simple validation step that results in stopping expect_error( - tbl_result <- tbl %>% rows_distinct(actions = stop_on_fail()) + tbl_result <- tbl %>% rows_distinct(actions = error_on_fail()) ) # Expect that `tbl_result` is never created @@ -1081,7 +1081,7 @@ test_that("Interrogating simply returns the expected results", { # Perform a simple validation step that results in stopping expect_error( - tbl_result <- tbl_complete_no %>% rows_complete(actions = stop_on_fail()) + tbl_result <- tbl_complete_no %>% rows_complete(actions = error_on_fail()) ) # Expect that `tbl_result` is never created @@ -1119,7 +1119,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_character( columns = vars(a), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1165,7 +1165,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_numeric( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1209,7 +1209,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_integer( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1253,7 +1253,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_posix( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1297,7 +1297,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_date( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1335,7 +1335,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_logical( columns = vars(b), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1374,7 +1374,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_is_factor( columns = vars(a), - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1403,16 +1403,16 @@ test_that("Interrogating simply returns the expected results", { # Using the `col_exists()` function to perform # a simple validation step results in an error expect_error( - tbl %>% col_exists(columns = vars(h), actions = stop_on_fail()) + tbl %>% col_exists(columns = vars(h), actions = error_on_fail()) ) expect_error( - tbl %>% col_exists(columns = "h", actions = stop_on_fail()) + tbl %>% col_exists(columns = "h", actions = error_on_fail()) ) expect_error( - tbl %>% col_exists(columns = vars(a, h), actions = stop_on_fail()) + tbl %>% col_exists(columns = vars(a, h), actions = error_on_fail()) ) expect_error( - tbl %>% col_exists(columns = c("a", "h"), actions = stop_on_fail()) + tbl %>% col_exists(columns = c("a", "h"), actions = error_on_fail()) ) # Expect no warning or error if all column names are correct @@ -1420,7 +1420,7 @@ test_that("Interrogating simply returns the expected results", { tbl %>% col_exists(columns = colnames(tbl), actions = warn_on_fail()) ) expect_no_error( - tbl %>% col_exists(columns = colnames(tbl), actions = stop_on_fail()) + tbl %>% col_exists(columns = colnames(tbl), actions = error_on_fail()) ) # @@ -1466,7 +1466,7 @@ test_that("Interrogating simply returns the expected results", { tbl_result <- tbl %>% col_schema_match( schema = schema_incorrect, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1521,7 +1521,7 @@ test_that("Interrogating simply returns the expected results", { tbl_complete_yes %>% row_count_match( count = pointblank::small_table, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1569,7 +1569,7 @@ test_that("Interrogating simply returns the expected results", { tbl_complete_yes %>% row_count_match( count = 15, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1624,7 +1624,7 @@ test_that("Interrogating simply returns the expected results", { tbl_complete_yes %>% col_count_match( count = pointblank::small_table, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1672,7 +1672,7 @@ test_that("Interrogating simply returns the expected results", { tbl_complete_yes %>% col_count_match( count = 15, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1725,7 +1725,7 @@ test_that("Interrogating simply returns the expected results", { tbl_complete_yes %>% tbl_match( tbl_compare = pointblank::small_table, - actions = stop_on_fail() + actions = error_on_fail() ) ) @@ -1784,7 +1784,7 @@ test_that("Interrogating simply returns the expected results", { conjointly( ~ col_vals_gt(., columns = vars(d), value = 200), ~ col_vals_lt(., columns = vars(c), value = 10), - actions = stop_on_fail() + actions = error_on_fail() ) ) From e8407f684017e48532b6feda3cb612f8b583b1fa Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:22:52 -0400 Subject: [PATCH 23/37] more usage of action_fns() --- R/action_levels.R | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index 66da22edb..fccdef750 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -368,21 +368,27 @@ warn_on_fail <- function(warn = 1, warn_at = NULL) { } warn <- warn_at %||% warn - action_levels(warn = warn, fns = list(warn = ~stock_warning(x = x))) + action_levels( + warn = warn, + fns = action_fns(warn = ~stock_warning(x = x)) + ) } #' @rdname action_levels #' @export error_on_fail <- function(error = 1) { - action_levels(error = error, fns = list(stop = ~stock_stoppage(x = x))) + action_levels( + error = error, + fns = action_fns(error = ~stock_stoppage(x = x)) + ) } #' @rdname action_levels #' @export stop_on_fail <- function(stop_at = 1) { cli::cli_warn(c( - "!" = "`stop_on_fail(stop_at)` is deprecated.", - " " = "Please use `error_on_fail(error)` instead." + "!" = "`stop_on_fail()` is deprecated.", + " " = "Please use `error_on_fail()` instead." )) error_on_fail(error = stop_at) } From 088838487213d2a53c298c31497086345edd3fe7 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:39:33 -0400 Subject: [PATCH 24/37] simplify fraction count calculation --- R/action_levels.R | 40 +++++++++++++++------------------------- 1 file changed, 15 insertions(+), 25 deletions(-) diff --git a/R/action_levels.R b/R/action_levels.R index fccdef750..773b5e417 100644 --- a/R/action_levels.R +++ b/R/action_levels.R @@ -396,7 +396,8 @@ stop_on_fail <- function(stop_at = 1) { action_fns <- function(warn = NULL, error = NULL, critical = NULL) { fns <- structure( list(warn = warn, error = error, critical = critical, - stop = error, notify = critical), # temp compatibility with rest of internals + # temp compatibility with rest of internals + stop = error, notify = critical), class = "action_fns" ) if (!all(vapply(fns, function(x) is.null(x) || is_formula(x), logical(1)))) { @@ -435,37 +436,26 @@ normalize_fns_list <- function(fns) { normalize_fraction_count <- function(x) { - if (!is.null(x) && !any(c(inherits(x, "numeric"), inherits(x, "integer")))) { + fraction_count <- list(fraction = NULL, count = NULL) - stop( - "All values provided to `action_levels()` must be either ", - "`numeric` or `integer` types.", - call. = FALSE - ) + if (is.null(x)) { + return(fraction_count) } - if (!is.null(x) && x <= 0) { - - stop( - "All values provided to `action_levels()` must be `>=0`.", - call. = FALSE - ) - } + stopifnot( + "Action level thresholds must be a single number." = + length(x) == 1 || is.numeric(x), + "Action level threshold values must be positive." = x > 0 + ) - if (!is.null(x)) { - if (x < 1) { - fraction <- x - count <- NULL - } else if (x >= 1) { - count <- floor(x) %>% as.numeric() - fraction <- NULL - } + if (x < 1) { + fraction_count$fraction <- x } else { - fraction <- NULL - count <- NULL + fraction_count$count <- floor(x) } - list(fraction = fraction, count = count) + fraction_count + } prime_actions <- function(actions) { From 6e055a0856fad3295c8b8a0c8e2e47ff016e86ee Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:56:45 -0400 Subject: [PATCH 25/37] rename agent report table --- R/get_agent_report.R | 62 ++++++++++++++++++++++---------------------- 1 file changed, 31 insertions(+), 31 deletions(-) diff --git a/R/get_agent_report.R b/R/get_agent_report.R index 10621aa99..639a45333 100644 --- a/R/get_agent_report.R +++ b/R/get_agent_report.R @@ -409,8 +409,8 @@ get_agent_report <- function( n_pass = validation_set$n_passed, f_pass = validation_set$f_passed, W = validation_set$warn, - S = validation_set$stop, - N = validation_set$notify, + E = validation_set$stop, + C = validation_set$notify, extract = extract_count ) @@ -418,10 +418,10 @@ get_agent_report <- function( report_tbl %>% dplyr::mutate( eval_pts = ifelse(eval != "OK", 10, 0), - N_pts = ifelse(!is.na(N) & N, 3, 0), - S_pts = ifelse(!is.na(S) & S, 2, 0), + C_pts = ifelse(!is.na(C) & C, 3, 0), + E_pts = ifelse(!is.na(E) & E, 2, 0), W_pts = ifelse(!is.na(W) & W, 1, 0), - total_pts = eval_pts + N_pts + S_pts + W_pts + total_pts = eval_pts + C_pts + E_pts + W_pts ) if (arrange_by == "severity") { @@ -1538,7 +1538,7 @@ get_agent_report <- function( } ) - s_upd <- + e_upd <- validation_set$stop %>% vapply( FUN.VALUE = character(1), @@ -1555,7 +1555,7 @@ get_agent_report <- function( } ) - n_upd <- + c_upd <- validation_set$notify %>% vapply( FUN.VALUE = character(1), @@ -1600,17 +1600,17 @@ get_agent_report <- function( f_pass = f_pass_val, f_fail = f_fail_val, W_val = W, - S_val = S, - N_val = N, + E_val = E, + C_val = C, W = w_upd, - S = s_upd, - N = n_upd, + E = e_upd, + C = c_upd, extract = extract_upd ) %>% dplyr::select( status_color, i, type, columns, values, precon, eval_sym, units, - n_pass, f_pass, n_fail, f_fail, W, S, N, extract, - W_val, S_val, N_val, eval, active + n_pass, f_pass, n_fail, f_fail, W, E, C, extract, + W_val, E_val, C_val, eval, active ) %>% gt::gt(id = "pb_agent", locale = locale) %>% gt::tab_header( @@ -1656,7 +1656,7 @@ get_agent_report <- function( ) %>% gt::cols_align( align = "center", - columns = c("precon", "eval_sym", "W", "S", "N", "extract") + columns = c("precon", "eval_sym", "W", "E", "C", "extract") ) %>% gt::cols_align( align = "center", @@ -1677,12 +1677,12 @@ get_agent_report <- function( gt::fmt_markdown( columns = c( "type", "columns", "values", "precon", - "eval_sym", "W", "S", "N", "extract" + "eval_sym", "W", "E", "C", "extract" ) ) %>% gt::sub_missing(columns = c("columns", "values", "units", "extract")) %>% gt::sub_missing(columns = "status_color", missing_text = "") %>% - gt::cols_hide(columns = c("W_val", "S_val", "N_val", "active", "eval")) %>% + gt::cols_hide(columns = c("W_val", "E_val", "C_val", "active", "eval")) %>% gt::text_transform( locations = gt::cells_body(columns = "units"), fn = function(x) { @@ -1741,7 +1741,7 @@ get_agent_report <- function( style = gt::cell_fill(color = "#CF142B"), locations = gt::cells_body( columns = "status_color", - rows = S_val + rows = E_val ) ) %>% gt::tab_style( @@ -1764,11 +1764,11 @@ get_agent_report <- function( gt::cell_borders(sides = "right", color = "#D3D3D3"), gt::cell_fill(color = "#FCFCFC") ), - locations = gt::cells_body(columns = c("eval_sym", "N")) + locations = gt::cells_body(columns = c("eval_sym", "C")) ) %>% gt::tab_style( style = gt::cell_fill(color = "#FCFCFC"), - locations = gt::cells_body(columns = "S") + locations = gt::cells_body(columns = "E") ) %>% gt::tab_style( style = gt::cell_borders( @@ -1812,7 +1812,7 @@ get_agent_report <- function( locations = gt::cells_body( columns = c( "precon", "eval_sym", "units", "f_pass", "f_fail", - "n_pass", "n_fail", "W", "S", "N", "extract" + "n_pass", "n_fail", "W", "E", "C", "extract" ) ), fn = function(x) { @@ -1831,7 +1831,7 @@ get_agent_report <- function( locations = gt::cells_body( columns = c( "precon", "eval_sym", "units", "f_pass", "f_fail", - "n_pass", "n_fail", "W", "S", "N", "extract" + "n_pass", "n_fail", "W", "E", "C", "extract" ) ) ) %>% @@ -1873,8 +1873,8 @@ get_agent_report <- function( "n_pass" ~ gt::px(50), "n_fail" ~ gt::px(50), "W" ~ gt::px(30), - "S" ~ gt::px(30), - "N" ~ gt::px(30), + "E" ~ gt::px(30), + "C" ~ gt::px(30), gt::everything() ~ gt::px(20) ) %>% gt::tab_style( @@ -1931,8 +1931,8 @@ get_agent_report <- function( "precon" ~ gt::px(50), "eval_sym" ~ gt::px(50), "W" ~ gt::px(30), - "S" ~ gt::px(30), - "N" ~ gt::px(30), + "E" ~ gt::px(30), + "C" ~ gt::px(30), "extract" ~ gt::px(65), gt::everything() ~ gt::px(50) ) %>% @@ -2263,14 +2263,14 @@ make_action_levels_html <- function( pb_fmt_number(actions$warn_count, decimals = 0, locale = locale) ) %||% "—" - stop <- + error <- c( pb_fmt_number(actions$stop_fraction, decimals = 2, locale = locale), pb_fmt_number(actions$stop_count, decimals = 0, locale = locale) ) %||% "—" - notify <- + critical <- c( pb_fmt_number(actions$notify_fraction, decimals = 2, locale = locale), pb_fmt_number(actions$notify_count, decimals = 0, locale = locale) @@ -2308,7 +2308,7 @@ make_action_levels_html <- function( ) ), htmltools::tags$span( - "STOP", + "ERROR", style = htmltools::css( `background-color` = "#D0182F", color = "white", @@ -2323,7 +2323,7 @@ make_action_levels_html <- function( ) ), htmltools::tags$span( - htmltools::HTML(stop), + htmltools::HTML(error), style = htmltools::css( `background-color` = "none", color = "#333333", @@ -2337,7 +2337,7 @@ make_action_levels_html <- function( ) ), htmltools::tags$span( - "NOTIFY", + "CRITICAL", style = htmltools::css( `background-color` = "#499FFE", color = "white", @@ -2352,7 +2352,7 @@ make_action_levels_html <- function( ) ), htmltools::tags$span( - htmltools::HTML(notify), + htmltools::HTML(critical), style = htmltools::css( `background-color` = "none", color = "#333333", From 650f7bf1e2bc6ec4957fdc4754c64f2438eff31a Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:57:08 -0400 Subject: [PATCH 26/37] update tests on agent report table column names --- tests/testthat/test-get_agent_report.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/tests/testthat/test-get_agent_report.R b/tests/testthat/test-get_agent_report.R index 4253fb484..aa64e3ced 100644 --- a/tests/testthat/test-get_agent_report.R +++ b/tests/testthat/test-get_agent_report.R @@ -14,7 +14,7 @@ test_that("Getting an agent report is possible", { expect_equal( colnames(report), c("i", "type", "columns", "values", "precon", "active", "eval", - "units", "n_pass", "f_pass", "W", "S", "N", "extract") + "units", "n_pass", "f_pass", "W", "E", "C", "extract") ) # Expect a single row in this report @@ -29,8 +29,8 @@ test_that("Getting an agent report is possible", { expect_type(report$n_pass, "double") expect_type(report$f_pass, "double") expect_type(report$W, "logical") - expect_type(report$S, "logical") - expect_type(report$N, "logical") + expect_type(report$E, "logical") + expect_type(report$C, "logical") expect_type(report$extract, "integer") # Use `col_is_character()` function to create @@ -49,8 +49,8 @@ test_that("Getting an agent report is possible", { expect_equal(agent_report_empty$n_pass, NA_integer_) expect_equal(agent_report_empty$f_pass, NA_real_) expect_equal(agent_report_empty$W, NA) - expect_equal(agent_report_empty$S, NA) - expect_equal(agent_report_empty$N, NA) + expect_equal(agent_report_empty$E, NA) + expect_equal(agent_report_empty$C, NA) expect_equal(agent_report_empty$extract, NA) }) From b667ba5c9dd0a6d42fb5400ccb42f672bc32d25c Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 15:59:54 -0400 Subject: [PATCH 27/37] rename action levels in vignette --- vignettes/pointblank.Rmd | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/vignettes/pointblank.Rmd b/vignettes/pointblank.Rmd index 416b6d120..74ec58eb8 100644 --- a/vignettes/pointblank.Rmd +++ b/vignettes/pointblank.Rmd @@ -121,10 +121,10 @@ Some validation methods like `col_exists()` or `row_count_match()` have only a s ## Using Action Levels -Knowing about the numbers of test units across validation methods matters because you have the option to set action levels (that can signal 'warn_at', 'stop_at', and 'notify_at' flags) based on either the relative proportion or absolute number of failing test units. +Knowing about the numbers of test units across validation methods matters because you have the option to set action levels (that can signal 'warn', 'error', and 'critical' flags) based on either the relative proportion or absolute number of failing test units. ```{r} -al <- action_levels(warn_at = 2, stop_at = 4) +al <- action_levels(warn = 2, error = 4) small_table %>% col_vals_lt(a, value = 7, actions = al) @@ -146,10 +146,10 @@ If you look at the validation report table, we can see: - The `FAIL` column shows that 2 tests units have failed. - the `W` column (short for 'warning') shows a filled yellow circle indicating those failing test units reached that threshold value. -- the `S` column (short for 'stop') shows an open red circle indicating that the number of +- the `E` column (short for 'error') shows an open red circle indicating that the number of failing test units is below that threshold. -The one final action level, `N` (for 'notify'), wasn't set so it appears on the validation table as a long dash. +The one final action level, `C` (for 'critical'), wasn't set so it appears on the validation table as a long dash. Setting thresholds is important since you might want some sort of signal for the discovery of errors in your data. How you set the particular threshold levels is highly dependent on your tolerance for data failures. From 33db60d8133ba0aeaabd574759bbe3f64812c56f Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:08:08 -0400 Subject: [PATCH 28/37] rename action levels in x_list --- R/get_agent_x_list.R | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/R/get_agent_x_list.R b/R/get_agent_x_list.R index 927821d2d..19c346a2e 100644 --- a/R/get_agent_x_list.R +++ b/R/get_agent_x_list.R @@ -68,8 +68,8 @@ #' `n_passed` / `n` (`num [1]`) #' \item `f_failed`: the fraction of failing test units for the validation step, #' `n_failed` / `n` (`num [1]`) -#' \item `warn`, `stop`, `notify`: a logical value indicating whether the level -#' of failing test units caused the corresponding conditions to be entered +#' \item `warn`, `error`, `critical`: a logical value indicating whether the +#' level of failing test units caused the corresponding conditions to be entered #' (`lgl [1]`) #' \item `lang`: the two-letter language code that indicates which #' language should be used for all briefs, the agent report, and the reporting @@ -80,8 +80,8 @@ #' then certain length-one components in the **x-list** will be expanded to the #' total number of validation steps (these are: `i`, `type`, `columns`, #' `values`, `briefs`, `eval_error`, `eval_warning`, `capture_stack`, `n`, -#' `n_passed`, `n_failed`, `f_passed`, `f_failed`, `warn`, `stop`, and -#' `notify`). The **x-list** will also have additional components when `i` is +#' `n_passed`, `n_failed`, `f_passed`, `f_failed`, `warn`, `error`, and +#' `critical`). The **x-list** will also have additional components when `i` is #' `NULL`, which are: #' \itemize{ #' \item `report_object`: a **gt** table object, which is also presented as the @@ -125,14 +125,14 @@ #' ``` #' #' Create an `action_levels()` list with fractional values for the `warn`, -#' `stop`, and `notify` states. +#' `error`, and `critical` states. #' #' ```r #' al <- #' action_levels( -#' warn_at = 0.2, -#' stop_at = 0.8, -#' notify_at = 0.345 +#' warn = 0.2, +#' error = 0.8, +#' critical = 0.345 #' ) #' ``` #' @@ -175,8 +175,8 @@ get_agent_x_list <- function( if (!is.null(i)) { .warn <- agent$validation_set[[i, "warn"]] - .notify <- agent$validation_set[[i, "notify"]] - .stop <- agent$validation_set[[i, "stop"]] + .error <- agent$validation_set[[i, "stop"]] + .critical <- agent$validation_set[[i, "notify"]] .agent_label <- agent$label .time_start <- agent$time_start @@ -232,8 +232,8 @@ get_agent_x_list <- function( f_passed = .f_passed, f_failed = .f_failed, warn = .warn, - stop = .stop, - notify = .notify, + error = .error, + critical = .critical, lang = .lang ) @@ -243,8 +243,8 @@ get_agent_x_list <- function( if (is.null(i)) { .warn <- agent$validation_set$warn - .notify <- agent$validation_set$notify - .stop <- agent$validation_set$stop + .error <- agent$validation_set$stop + .critical <- agent$validation_set$notify .agent_label <- agent$label .time_start <- agent$time_start @@ -343,8 +343,8 @@ get_agent_x_list <- function( f_passed = .f_passed, f_failed = .f_failed, warn = .warn, - stop = .stop, - notify = .notify, + error = .error, + critical = .critical, lang = .lang, validation_set = .validation_set, report_object = .report_object, From 91d4bf7528a38eafd7aa4eb483794111a5e84fa4 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:08:47 -0400 Subject: [PATCH 29/37] rename action levels in x_list display --- R/print.R | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/R/print.R b/R/print.R index a80c82c9e..65e510e4c 100644 --- a/R/print.R +++ b/R/print.R @@ -270,7 +270,7 @@ print.x_list_i <- function(x, ...) { "({.green num [{length_rows}]})" ) cli::cli_text( - "{.cyan $warn $stop $notify} ({.yellow lgl [{length_rows}]})" + "{.cyan $warn $error $critical} ({.yellow lgl [{length_rows}]})" ) cli::cli_text( "{.cyan $lang} ({.red chr [1]})" @@ -321,7 +321,7 @@ knit_print.x_list_i <- function(x, ...) { "$capture_stack (list [{length(x$capture_stack)}])\n", "$n $n_passed $n_failed $f_passed $f_failed ", "(num [{length_rows}])\n", - "$warn $stop $notify (lgl [{length_rows}])\n", + "$warn $error $critical (lgl [{length_rows}])\n", "$lang (chr [1])\n", "{bottom_rule}\n" ) @@ -395,7 +395,7 @@ print.x_list_n <- function(x, ...) { "({.green num [{length_rows}]})" ) cli::cli_text( - "{.cyan $warn $stop $notify} ({.yellow lgl [{length_rows}]})" + "{.cyan $warn $error $critical} ({.yellow lgl [{length_rows}]})" ) cli::cli_text( "{.cyan $validation_set} ", @@ -461,7 +461,7 @@ knit_print.x_list_n <- function(x, ...) { "$capture_stack (list [{length(x$capture_stack)}])\n", "$n $n_passed $n_failed $f_passed $f_failed ", "(num [{length_rows}])\n", - "$warn $stop $notify (lgl [{length_rows}])\n", + "$warn $error $critical (lgl [{length_rows}])\n", "$validation_set (tbl_df [{validation_set_rows}, ", "{validation_set_cols}])\n", "$lang (chr [1])\n", From 7054830160ccc65edb8830e0ea26b627016ae6e5 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:10:31 -0400 Subject: [PATCH 30/37] update tests for x_list --- tests/testthat/test-x_list.R | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/tests/testthat/test-x_list.R b/tests/testthat/test-x_list.R index 3a75456dc..3d3bed6da 100644 --- a/tests/testthat/test-x_list.R +++ b/tests/testthat/test-x_list.R @@ -84,10 +84,10 @@ test_that("An x-list for a step is structurally correct", { expect_equal(x_list_before$f_failed, NA_real_) expect_type(x_list_before$warn, "logical") expect_equal(x_list_before$warn, NA) - expect_type(x_list_before$stop, "logical") - expect_equal(x_list_before$stop, NA) - expect_type(x_list_before$notify, "logical") - expect_equal(x_list_before$notify, NA) + expect_type(x_list_before$error, "logical") + expect_equal(x_list_before$error, NA) + expect_type(x_list_before$critical, "logical") + expect_equal(x_list_before$critical, NA) expect_type(x_list_before$lang, "character") expect_equal(x_list_before$lang, "en") @@ -170,10 +170,10 @@ test_that("An x-list for a step is structurally correct", { expect_equal(x_list_after$f_failed, 0.76923) expect_type(x_list_after$warn, "logical") expect_equal(x_list_after$warn, TRUE) - expect_type(x_list_after$stop, "logical") - expect_equal(x_list_after$stop, TRUE) - expect_type(x_list_after$notify, "logical") - expect_equal(x_list_after$notify, NA) + expect_type(x_list_after$error, "logical") + expect_equal(x_list_after$error, TRUE) + expect_type(x_list_after$critical, "logical") + expect_equal(x_list_after$critical, NA) expect_type(x_list_after$lang, "character") expect_equal(x_list_after$lang, "en") }) @@ -270,10 +270,10 @@ test_that("A complete x-list is structurally correct", { expect_equal(x_list_before$f_failed, rep(NA_real_, 3)) expect_type(x_list_before$warn, "logical") expect_equal(x_list_before$warn, rep(NA, 3)) - expect_type(x_list_before$stop, "logical") - expect_equal(x_list_before$stop, rep(NA, 3)) - expect_type(x_list_before$notify, "logical") - expect_equal(x_list_before$notify, rep(NA, 3)) + expect_type(x_list_before$error, "logical") + expect_equal(x_list_before$error, rep(NA, 3)) + expect_type(x_list_before$critical, "logical") + expect_equal(x_list_before$critical, rep(NA, 3)) expect_s3_class(x_list_before$validation_set, c("tbl_df", "tbl", "data.frame")) expect_equal(nrow(x_list_before$validation_set), 3) expect_equal(ncol(x_list_before$validation_set), 35) @@ -374,10 +374,10 @@ test_that("A complete x-list is structurally correct", { expect_equal(x_list_after$f_failed, c(0.76923, 0.23077, 0)) expect_type(x_list_after$warn, "logical") expect_equal(x_list_after$warn, c(TRUE, TRUE, FALSE)) - expect_type(x_list_after$stop, "logical") - expect_equal(x_list_after$stop, c(TRUE, TRUE, FALSE)) - expect_type(x_list_after$notify, "logical") - expect_equal(x_list_after$notify, rep(NA, 3)) + expect_type(x_list_after$error, "logical") + expect_equal(x_list_after$error, c(TRUE, TRUE, FALSE)) + expect_type(x_list_after$critical, "logical") + expect_equal(x_list_after$critical, rep(NA, 3)) expect_s3_class(x_list_after$validation_set, c("tbl_df", "tbl", "data.frame"), exact = TRUE) expect_equal(nrow(x_list_after$validation_set), 3) expect_equal(ncol(x_list_after$validation_set), 35) From 49a00c9acbcf3a18de1536bbb6a34eba179fed8a Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:17:02 -0400 Subject: [PATCH 31/37] update tests that read WEC off agent report --- .../generated_testthat_files/test.yaml | 71 +++++++++++++++++++ tests/testthat/test-action_levels.R | 4 +- .../testthat/yaml_files/agent-small_table.yml | 26 +++++++ .../yaml_files/informant-small_table.yml | 36 ++++++++++ tests/testthat/yaml_files/tbl_store.yml | 3 + 5 files changed, 138 insertions(+), 2 deletions(-) create mode 100644 tests/testthat/generated_testthat_files/test.yaml create mode 100644 tests/testthat/yaml_files/agent-small_table.yml create mode 100644 tests/testthat/yaml_files/informant-small_table.yml create mode 100644 tests/testthat/yaml_files/tbl_store.yml diff --git a/tests/testthat/generated_testthat_files/test.yaml b/tests/testthat/generated_testthat_files/test.yaml new file mode 100644 index 000000000..552d55c74 --- /dev/null +++ b/tests/testthat/generated_testthat_files/test.yaml @@ -0,0 +1,71 @@ +type: agent +tbl: ~small_table +tbl_name: ~small_table +label: '[2025-03-25|16:16:29]' +lang: en +locale: en +actions: + warn_fraction: 0.1 + stop_fraction: 0.2 +steps: +- col_vals_in_set: + columns: vars(f) + set: + - low + - mid + - high +- col_vals_between: + columns: c("a") + left: 2.0 + right: 8.0 +- col_vals_lt: + columns: vars(a) + value: vars(d) + na_pass: true + preconditions: ~. %>% dplyr::filter(a > 3) +- col_vals_gt: + columns: vars(d) + value: 100.0 +- col_vals_equal: + columns: vars(d) + value: vars(d) + na_pass: true +- col_vals_null: + columns: vars(c) +- col_vals_not_null: + columns: matches("^.$") +- col_vals_regex: + columns: c("b") + regex: '[0-9]-[a-z]{3}-[0-9]{3}' +- col_is_character: + columns: vars(b) +- col_exists: + columns: vars(a, b) +- col_vals_expr: + expr: ~a%%1 == 0 +- rows_distinct: + columns: vars(a, b, c) +- rows_distinct: + columns: everything() +- col_schema_match: + schema: + date_time: + - POSIXct + - POSIXt + date: Date + a: integer + b: character + c: numeric + d: numeric + e: logical + f: character +- conjointly: + fns: + - ~col_vals_lt(., vars(a), 8) + - ~col_vals_gt(., vars(c), vars(a)) + - ~col_vals_not_null(., vars(b)) +- col_vals_between: + columns: vars(c) + left: 2.03 + right: vars(d) + na_pass: true diff --git a/tests/testthat/test-action_levels.R b/tests/testthat/test-action_levels.R index 97a802fea..deb78f638 100644 --- a/tests/testthat/test-action_levels.R +++ b/tests/testthat/test-action_levels.R @@ -180,7 +180,7 @@ test_that("The appropriate actions occur when using `action_levels()`", { interrogate() agent_report <- get_agent_report(agent, display_table = FALSE) - agent_report$N %>% expect_equal(rep(TRUE, 2)) + agent_report$C %>% expect_equal(rep(TRUE, 2)) agent <- create_agent(tbl = small_table, label = "small_table_tests") %>% @@ -197,5 +197,5 @@ test_that("The appropriate actions occur when using `action_levels()`", { interrogate() agent_report <- get_agent_report(agent, display_table = FALSE) - agent_report$S %>% expect_equal(rep(TRUE, 2)) + agent_report$E %>% expect_equal(rep(TRUE, 2)) }) diff --git a/tests/testthat/yaml_files/agent-small_table.yml b/tests/testthat/yaml_files/agent-small_table.yml new file mode 100644 index 000000000..78dc055f5 --- /dev/null +++ b/tests/testthat/yaml_files/agent-small_table.yml @@ -0,0 +1,26 @@ +type: agent +tbl: ~ tbl_source("small_table", "tbl_store.yml") +tbl_name: small_table +label: A simple example with the `small_table`. +lang: en +locale: en +actions: + warn_fraction: 0.1 + stop_fraction: 0.25 + notify_fraction: 0.35 +steps: +- col_exists: + columns: vars(date) +- col_exists: + columns: vars(date_time) +- col_vals_regex: + columns: vars(b) + regex: '[0-9]-[a-z]{3}-[0-9]{3}' +- rows_distinct: + columns: ~ +- col_vals_gt: + columns: vars(d) + value: 100.0 +- col_vals_lte: + columns: vars(c) + value: 5.0 diff --git a/tests/testthat/yaml_files/informant-small_table.yml b/tests/testthat/yaml_files/informant-small_table.yml new file mode 100644 index 000000000..0dd699817 --- /dev/null +++ b/tests/testthat/yaml_files/informant-small_table.yml @@ -0,0 +1,36 @@ +type: informant +tbl: ~ tbl_source("small_table", "tbl_store.yml") +tbl_name: small_table +info_label: A simple example with the `small_table`. +lang: en +locale: en +table: + name: small_table + _columns: 8 + _rows: 13 + _type: tbl_df +columns: + date_time: + _type: POSIXct, POSIXt + info: Date-time values. + date: + _type: Date + info: Date values (the date part of `date_time`). + a: + _type: integer + info: Small integer values (no missing values). + b: + _type: character + info: Strings with a common pattern. + c: + _type: numeric + info: Small numeric values (contains missing values). + d: + _type: numeric + info: Large numeric values (much greater than `c`). + e: + _type: logical + info: TRUE and FALSE values. + f: + _type: character + info: Strings of the set `"low"`, `"mid"`, and `"high"`. diff --git a/tests/testthat/yaml_files/tbl_store.yml b/tests/testthat/yaml_files/tbl_store.yml new file mode 100644 index 000000000..cf0a6d2e8 --- /dev/null +++ b/tests/testthat/yaml_files/tbl_store.yml @@ -0,0 +1,3 @@ +type: tbl_store +tbls: + small_table: ~ pointblank::small_table From 54a021884b12aa6f397f1734de2f132bd63cc78e Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:28:06 -0400 Subject: [PATCH 32/37] reconstruct action levels from yaml using new names --- R/yaml_read_agent.R | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/R/yaml_read_agent.R b/R/yaml_read_agent.R index 3ae51dc72..c8fbe7359 100644 --- a/R/yaml_read_agent.R +++ b/R/yaml_read_agent.R @@ -478,17 +478,17 @@ make_action_levels_str <- function(al) { if (!is.null(al$warn_fraction) || !is.null(al$warn_count)) { top_args <- - c(top_args, paste0("warn_at = ", c(al$warn_fraction, al$warn_count))) + c(top_args, paste0("warn = ", c(al$warn_fraction, al$warn_count))) } if (!is.null(al$stop_fraction) || !is.null(al$stop_count)) { top_args <- - c(top_args, paste0("stop_at = ", c(al$stop_fraction, al$stop_count))) + c(top_args, paste0("error = ", c(al$stop_fraction, al$stop_count))) } if (!is.null(al$notify_fraction) || !is.null(al$notify_count)) { top_args <- c( top_args, - paste0("notify_at = ", c(al$notify_fraction, al$notify_count)) + paste0("critical = ", c(al$notify_fraction, al$notify_count)) ) } @@ -498,15 +498,15 @@ make_action_levels_str <- function(al) { fns_args <- c(fns_args, paste0("warn = ", al$fns$warn)) } if (!is.null(al$fns$stop)) { - fns_args <- c(fns_args, paste0("stop = ", al$fns$stop)) + fns_args <- c(fns_args, paste0("error = ", al$fns$stop)) } if (!is.null(al$fns$notify)) { - fns_args <- c(fns_args, paste0("notify = ", al$fns$notify)) + fns_args <- c(fns_args, paste0("critical = ", al$fns$notify)) } if (length(fns_args) > 0) { fns_args <- - paste0(" fns = list(\n", paste0(" ", fns_args), "\n )") + paste0(" fns = action_fns(\n", paste0(" ", fns_args), "\n )") } paste0( From fd17ef413381c0d6c360ca2d60b87f47c9c7d06e Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:28:43 -0400 Subject: [PATCH 33/37] update yaml reading tests --- tests/testthat/test-yaml.R | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/tests/testthat/test-yaml.R b/tests/testthat/test-yaml.R index da002dcdc..ae9957c31 100644 --- a/tests/testthat/test-yaml.R +++ b/tests/testthat/test-yaml.R @@ -276,7 +276,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_lt(columns = vars(a, c),value = 1,actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_lt(vars(a, c), 1, label = "my_label")), @@ -345,7 +345,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_between(vars(c), left = -5, right = 15, label = "my_label")), @@ -406,7 +406,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_not_between(columns = vars(c),left = vars(a),right = vars(d),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_between(vars(a), left = -5, right = 15, label = "my_label")), @@ -451,7 +451,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -496,7 +496,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_not_in_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_not_in_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -541,7 +541,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_make_set(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_set(vars(f), set = c("low", "high"), label = "my_label")), @@ -586,7 +586,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { actions = action_levels(warn = 0.1, error = 0.2) ) ), - "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_vals_make_subset(columns = vars(c),set = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_vals_make_subset(vars(f), set = c("low", "high"), label = "my_label")), @@ -831,7 +831,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { get_oneline_expr_str( agent %>% col_is_character(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_is_character(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_is_character(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_is_character(vars(b), label = "my_label")), @@ -854,7 +854,7 @@ test_that("Individual validation steps make the YAML round-trip successfully", { get_oneline_expr_str( agent %>% col_exists(vars(b, f), actions = action_levels(warn = 0.1, error = 0.2)) ), - "col_exists(columns = vars(b, f),actions = action_levels(warn_at = 0.1,stop_at = 0.2))" + "col_exists(columns = vars(b, f),actions = action_levels(warn = 0.1,error = 0.2))" ) expect_equal( get_oneline_expr_str(agent %>% col_exists(vars(b), label = "my_label")), From f9fc4e29b355965d8c50a8dd0794138ac1fecf06 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:40:48 -0400 Subject: [PATCH 34/37] un-commit test artifacts --- .../generated_testthat_files/test.yaml | 71 ------------------- .../testthat/yaml_files/agent-small_table.yml | 26 ------- .../yaml_files/informant-small_table.yml | 36 ---------- tests/testthat/yaml_files/tbl_store.yml | 3 - 4 files changed, 136 deletions(-) delete mode 100644 tests/testthat/generated_testthat_files/test.yaml delete mode 100644 tests/testthat/yaml_files/agent-small_table.yml delete mode 100644 tests/testthat/yaml_files/informant-small_table.yml delete mode 100644 tests/testthat/yaml_files/tbl_store.yml diff --git a/tests/testthat/generated_testthat_files/test.yaml b/tests/testthat/generated_testthat_files/test.yaml deleted file mode 100644 index 552d55c74..000000000 --- a/tests/testthat/generated_testthat_files/test.yaml +++ /dev/null @@ -1,71 +0,0 @@ -type: agent -tbl: ~small_table -tbl_name: ~small_table -label: '[2025-03-25|16:16:29]' -lang: en -locale: en -actions: - warn_fraction: 0.1 - stop_fraction: 0.2 -steps: -- col_vals_in_set: - columns: vars(f) - set: - - low - - mid - - high -- col_vals_between: - columns: c("a") - left: 2.0 - right: 8.0 -- col_vals_lt: - columns: vars(a) - value: vars(d) - na_pass: true - preconditions: ~. %>% dplyr::filter(a > 3) -- col_vals_gt: - columns: vars(d) - value: 100.0 -- col_vals_equal: - columns: vars(d) - value: vars(d) - na_pass: true -- col_vals_null: - columns: vars(c) -- col_vals_not_null: - columns: matches("^.$") -- col_vals_regex: - columns: c("b") - regex: '[0-9]-[a-z]{3}-[0-9]{3}' -- col_is_character: - columns: vars(b) -- col_exists: - columns: vars(a, b) -- col_vals_expr: - expr: ~a%%1 == 0 -- rows_distinct: - columns: vars(a, b, c) -- rows_distinct: - columns: everything() -- col_schema_match: - schema: - date_time: - - POSIXct - - POSIXt - date: Date - a: integer - b: character - c: numeric - d: numeric - e: logical - f: character -- conjointly: - fns: - - ~col_vals_lt(., vars(a), 8) - - ~col_vals_gt(., vars(c), vars(a)) - - ~col_vals_not_null(., vars(b)) -- col_vals_between: - columns: vars(c) - left: 2.03 - right: vars(d) - na_pass: true diff --git a/tests/testthat/yaml_files/agent-small_table.yml b/tests/testthat/yaml_files/agent-small_table.yml deleted file mode 100644 index 78dc055f5..000000000 --- a/tests/testthat/yaml_files/agent-small_table.yml +++ /dev/null @@ -1,26 +0,0 @@ -type: agent -tbl: ~ tbl_source("small_table", "tbl_store.yml") -tbl_name: small_table -label: A simple example with the `small_table`. -lang: en -locale: en -actions: - warn_fraction: 0.1 - stop_fraction: 0.25 - notify_fraction: 0.35 -steps: -- col_exists: - columns: vars(date) -- col_exists: - columns: vars(date_time) -- col_vals_regex: - columns: vars(b) - regex: '[0-9]-[a-z]{3}-[0-9]{3}' -- rows_distinct: - columns: ~ -- col_vals_gt: - columns: vars(d) - value: 100.0 -- col_vals_lte: - columns: vars(c) - value: 5.0 diff --git a/tests/testthat/yaml_files/informant-small_table.yml b/tests/testthat/yaml_files/informant-small_table.yml deleted file mode 100644 index 0dd699817..000000000 --- a/tests/testthat/yaml_files/informant-small_table.yml +++ /dev/null @@ -1,36 +0,0 @@ -type: informant -tbl: ~ tbl_source("small_table", "tbl_store.yml") -tbl_name: small_table -info_label: A simple example with the `small_table`. -lang: en -locale: en -table: - name: small_table - _columns: 8 - _rows: 13 - _type: tbl_df -columns: - date_time: - _type: POSIXct, POSIXt - info: Date-time values. - date: - _type: Date - info: Date values (the date part of `date_time`). - a: - _type: integer - info: Small integer values (no missing values). - b: - _type: character - info: Strings with a common pattern. - c: - _type: numeric - info: Small numeric values (contains missing values). - d: - _type: numeric - info: Large numeric values (much greater than `c`). - e: - _type: logical - info: TRUE and FALSE values. - f: - _type: character - info: Strings of the set `"low"`, `"mid"`, and `"high"`. diff --git a/tests/testthat/yaml_files/tbl_store.yml b/tests/testthat/yaml_files/tbl_store.yml deleted file mode 100644 index cf0a6d2e8..000000000 --- a/tests/testthat/yaml_files/tbl_store.yml +++ /dev/null @@ -1,3 +0,0 @@ -type: tbl_store -tbls: - small_table: ~ pointblank::small_table From a1dae506c7fc013372a24d272a2ae9f60c7f56b8 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 16:57:30 -0400 Subject: [PATCH 35/37] update draft validation snaps --- tests/testthat/_snaps/draft_validation.md | 118 +++++++++++----------- 1 file changed, 59 insertions(+), 59 deletions(-) diff --git a/tests/testthat/_snaps/draft_validation.md b/tests/testthat/_snaps/draft_validation.md index a80d2f82a..8467daa39 100644 --- a/tests/testthat/_snaps/draft_validation.md +++ b/tests/testthat/_snaps/draft_validation.md @@ -3,411 +3,411 @@ Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `latitude` is of type: numeric\n col_is_numeric(\n columns = c(\"latitude\")\n ) %>%\n # Expect that values in `latitude` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"latitude\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `month` is of type: factor\n col_is_factor(\n columns = c(\"month\")\n ) %>%\n # Expect that column `tst` is of type: character\n col_is_character(\n columns = c(\"tst\")\n ) %>%\n # Expect that column `sza` is of type: numeric\n col_is_numeric(\n columns = c(\"sza\")\n ) %>%\n # Expect that values in `sza` should be between `1.9` and `89.7`\n col_vals_between(\n columns = c(\"sza\"),\n left = 1.9,\n right = 89.7,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `latitude, month, tst, sza`\n rows_distinct(\n columns = c(\"latitude\", \"month\", \"tst\", \"sza\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n latitude = \"numeric\",\n month = \"factor\",\n tst = \"character\",\n sza = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `latitude` is of type: numeric\n col_is_numeric(\n columns = c(\"latitude\")\n ) %>%\n # Expect that values in `latitude` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"latitude\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `month` is of type: factor\n col_is_factor(\n columns = c(\"month\")\n ) %>%\n # Expect that column `tst` is of type: character\n col_is_character(\n columns = c(\"tst\")\n ) %>%\n # Expect that column `sza` is of type: numeric\n col_is_numeric(\n columns = c(\"sza\")\n ) %>%\n # Expect that values in `sza` should be between `1.9` and `89.7`\n col_vals_between(\n columns = c(\"sza\"),\n left = 1.9,\n right = 89.7,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `latitude, month, tst, sza`\n rows_distinct(\n columns = c(\"latitude\", \"month\", \"tst\", \"sza\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n latitude = \"numeric\",\n month = \"factor\",\n tst = \"character\",\n sza = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mfr` is of type: character\n col_is_character(\n columns = c(\"mfr\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `year` is of type: numeric\n col_is_numeric(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2014` and `2017`\n col_vals_between(\n columns = c(\"year\"),\n left = 2014,\n right = 2017\n ) %>%\n # Expect that column `trim` is of type: character\n col_is_character(\n columns = c(\"trim\")\n ) %>%\n # Expect that column `bdy_style` is of type: character\n col_is_character(\n columns = c(\"bdy_style\")\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `259` and `949`\n col_vals_between(\n columns = c(\"hp\"),\n left = 259,\n right = 949\n ) %>%\n # Expect that column `hp_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"hp_rpm\")\n ) %>%\n # Expect that values in `hp_rpm` should be between `5000` and `9000`\n col_vals_between(\n columns = c(\"hp_rpm\"),\n left = 5000,\n right = 9000\n ) %>%\n # Expect that column `trq` is of type: numeric\n col_is_numeric(\n columns = c(\"trq\")\n ) %>%\n # Expect that values in `trq` should be between `243` and `664`\n col_vals_between(\n columns = c(\"trq\"),\n left = 243,\n right = 664\n ) %>%\n # Expect that column `trq_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"trq_rpm\")\n ) %>%\n # Expect that values in `trq_rpm` should be between `1400` and `6750`\n col_vals_between(\n columns = c(\"trq_rpm\"),\n left = 1400,\n right = 6750,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_c` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_c\")\n ) %>%\n # Expect that values in `mpg_c` should be between `11` and `28`\n col_vals_between(\n columns = c(\"mpg_c\"),\n left = 11,\n right = 28,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_h` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_h\")\n ) %>%\n # Expect that values in `mpg_h` should be between `16` and `30`\n col_vals_between(\n columns = c(\"mpg_h\"),\n left = 16,\n right = 30,\n na_pass = TRUE\n ) %>%\n # Expect that column `drivetrain` is of type: character\n col_is_character(\n columns = c(\"drivetrain\")\n ) %>%\n # Expect that column `trsmn` is of type: character\n col_is_character(\n columns = c(\"trsmn\")\n ) %>%\n # Expect that column `ctry_origin` is of type: character\n col_is_character(\n columns = c(\"ctry_origin\")\n ) %>%\n # Expect that values in `ctry_origin` should be in the set of `United States`, `Italy`, `Japan` (and 2 more)\n col_vals_in_set(\n columns = c(\"ctry_origin\"),\n set = c(\"United States\", \"Italy\", \"Japan\", \"United Kingdom\", \"Germany\")\n ) %>%\n # Expect that column `msrp` is of type: numeric\n col_is_numeric(\n columns = c(\"msrp\")\n ) %>%\n # Expect that values in `msrp` should be between `53900` and `1416362`\n col_vals_between(\n columns = c(\"msrp\"),\n left = 53900,\n right = 1416362\n ) %>%\n # Expect entirely distinct rows across `mfr, model, year, trim, bdy_style, hp, hp_rpm, trq, trq_rpm, mpg_c, mpg_h, drivetrain, trsmn, ctry_origin, msrp`\n rows_distinct(\n columns = c(\"mfr\", \"model\", \"year\", \"trim\", \"bdy_style\", \"hp\", \"hp_rpm\", \"trq\", \"trq_rpm\", \"mpg_c\", \"mpg_h\", \"drivetrain\", \"trsmn\", \"ctry_origin\", \"msrp\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mfr = \"character\",\n model = \"character\",\n year = \"numeric\",\n trim = \"character\",\n bdy_style = \"character\",\n hp = \"numeric\",\n hp_rpm = \"numeric\",\n trq = \"numeric\",\n trq_rpm = \"numeric\",\n mpg_c = \"numeric\",\n mpg_h = \"numeric\",\n drivetrain = \"character\",\n trsmn = \"character\",\n ctry_origin = \"character\",\n msrp = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mfr` is of type: character\n col_is_character(\n columns = c(\"mfr\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `year` is of type: numeric\n col_is_numeric(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2014` and `2017`\n col_vals_between(\n columns = c(\"year\"),\n left = 2014,\n right = 2017\n ) %>%\n # Expect that column `trim` is of type: character\n col_is_character(\n columns = c(\"trim\")\n ) %>%\n # Expect that column `bdy_style` is of type: character\n col_is_character(\n columns = c(\"bdy_style\")\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `259` and `949`\n col_vals_between(\n columns = c(\"hp\"),\n left = 259,\n right = 949\n ) %>%\n # Expect that column `hp_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"hp_rpm\")\n ) %>%\n # Expect that values in `hp_rpm` should be between `5000` and `9000`\n col_vals_between(\n columns = c(\"hp_rpm\"),\n left = 5000,\n right = 9000\n ) %>%\n # Expect that column `trq` is of type: numeric\n col_is_numeric(\n columns = c(\"trq\")\n ) %>%\n # Expect that values in `trq` should be between `243` and `664`\n col_vals_between(\n columns = c(\"trq\"),\n left = 243,\n right = 664\n ) %>%\n # Expect that column `trq_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"trq_rpm\")\n ) %>%\n # Expect that values in `trq_rpm` should be between `1400` and `6750`\n col_vals_between(\n columns = c(\"trq_rpm\"),\n left = 1400,\n right = 6750,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_c` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_c\")\n ) %>%\n # Expect that values in `mpg_c` should be between `11` and `28`\n col_vals_between(\n columns = c(\"mpg_c\"),\n left = 11,\n right = 28,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_h` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_h\")\n ) %>%\n # Expect that values in `mpg_h` should be between `16` and `30`\n col_vals_between(\n columns = c(\"mpg_h\"),\n left = 16,\n right = 30,\n na_pass = TRUE\n ) %>%\n # Expect that column `drivetrain` is of type: character\n col_is_character(\n columns = c(\"drivetrain\")\n ) %>%\n # Expect that column `trsmn` is of type: character\n col_is_character(\n columns = c(\"trsmn\")\n ) %>%\n # Expect that column `ctry_origin` is of type: character\n col_is_character(\n columns = c(\"ctry_origin\")\n ) %>%\n # Expect that values in `ctry_origin` should be in the set of `United States`, `Italy`, `Japan` (and 2 more)\n col_vals_in_set(\n columns = c(\"ctry_origin\"),\n set = c(\"United States\", \"Italy\", \"Japan\", \"United Kingdom\", \"Germany\")\n ) %>%\n # Expect that column `msrp` is of type: numeric\n col_is_numeric(\n columns = c(\"msrp\")\n ) %>%\n # Expect that values in `msrp` should be between `53900` and `1416362`\n col_vals_between(\n columns = c(\"msrp\"),\n left = 53900,\n right = 1416362\n ) %>%\n # Expect entirely distinct rows across `mfr, model, year, trim, bdy_style, hp, hp_rpm, trq, trq_rpm, mpg_c, mpg_h, drivetrain, trsmn, ctry_origin, msrp`\n rows_distinct(\n columns = c(\"mfr\", \"model\", \"year\", \"trim\", \"bdy_style\", \"hp\", \"hp_rpm\", \"trq\", \"trq_rpm\", \"mpg_c\", \"mpg_h\", \"drivetrain\", \"trsmn\", \"ctry_origin\", \"msrp\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mfr = \"character\",\n model = \"character\",\n year = \"numeric\",\n trim = \"character\",\n bdy_style = \"character\",\n hp = \"numeric\",\n hp_rpm = \"numeric\",\n trq = \"numeric\",\n trq_rpm = \"numeric\",\n mpg_c = \"numeric\",\n mpg_h = \"numeric\",\n drivetrain = \"character\",\n trsmn = \"character\",\n ctry_origin = \"character\",\n msrp = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `open` is of type: numeric\n col_is_numeric(\n columns = c(\"open\")\n ) %>%\n # Expect that values in `open` should be between `16.66` and `2130.3601`\n col_vals_between(\n columns = c(\"open\"),\n left = 16.66,\n right = 2130.3601\n ) %>%\n # Expect that column `high` is of type: numeric\n col_is_numeric(\n columns = c(\"high\")\n ) %>%\n # Expect that values in `high` should be between `16.66` and `2134.72`\n col_vals_between(\n columns = c(\"high\"),\n left = 16.66,\n right = 2134.72\n ) %>%\n # Expect that column `low` is of type: numeric\n col_is_numeric(\n columns = c(\"low\")\n ) %>%\n # Expect that values in `low` should be between `16.66` and `2126.0601`\n col_vals_between(\n columns = c(\"low\"),\n left = 16.66,\n right = 2126.0601\n ) %>%\n # Expect that column `close` is of type: numeric\n col_is_numeric(\n columns = c(\"close\")\n ) %>%\n # Expect that values in `close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `680000` and `11456230400`\n col_vals_between(\n columns = c(\"volume\"),\n left = 680000,\n right = 11456230000\n ) %>%\n # Expect that column `adj_close` is of type: numeric\n col_is_numeric(\n columns = c(\"adj_close\")\n ) %>%\n # Expect that values in `adj_close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"adj_close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect entirely distinct rows across `date, open, high, low, close, volume, adj_close`\n rows_distinct(\n columns = c(\"date\", \"open\", \"high\", \"low\", \"close\", \"volume\", \"adj_close\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n open = \"numeric\",\n high = \"numeric\",\n low = \"numeric\",\n close = \"numeric\",\n volume = \"numeric\",\n adj_close = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `open` is of type: numeric\n col_is_numeric(\n columns = c(\"open\")\n ) %>%\n # Expect that values in `open` should be between `16.66` and `2130.3601`\n col_vals_between(\n columns = c(\"open\"),\n left = 16.66,\n right = 2130.3601\n ) %>%\n # Expect that column `high` is of type: numeric\n col_is_numeric(\n columns = c(\"high\")\n ) %>%\n # Expect that values in `high` should be between `16.66` and `2134.72`\n col_vals_between(\n columns = c(\"high\"),\n left = 16.66,\n right = 2134.72\n ) %>%\n # Expect that column `low` is of type: numeric\n col_is_numeric(\n columns = c(\"low\")\n ) %>%\n # Expect that values in `low` should be between `16.66` and `2126.0601`\n col_vals_between(\n columns = c(\"low\"),\n left = 16.66,\n right = 2126.0601\n ) %>%\n # Expect that column `close` is of type: numeric\n col_is_numeric(\n columns = c(\"close\")\n ) %>%\n # Expect that values in `close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `680000` and `11456230400`\n col_vals_between(\n columns = c(\"volume\"),\n left = 680000,\n right = 11456230000\n ) %>%\n # Expect that column `adj_close` is of type: numeric\n col_is_numeric(\n columns = c(\"adj_close\")\n ) %>%\n # Expect that values in `adj_close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"adj_close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect entirely distinct rows across `date, open, high, low, close, volume, adj_close`\n rows_distinct(\n columns = c(\"date\", \"open\", \"high\", \"low\", \"close\", \"volume\", \"adj_close\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n open = \"numeric\",\n high = \"numeric\",\n low = \"numeric\",\n close = \"numeric\",\n volume = \"numeric\",\n adj_close = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `id` is of type: character\n col_is_character(\n columns = c(\"id\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `size` is of type: character\n col_is_character(\n columns = c(\"size\")\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `price` is of type: numeric\n col_is_numeric(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `9.75` and `35.95`\n col_vals_between(\n columns = c(\"price\"),\n left = 9.75,\n right = 35.95\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n id = \"character\",\n date = \"character\",\n time = \"character\",\n name = \"character\",\n size = \"character\",\n type = \"character\",\n price = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `id` is of type: character\n col_is_character(\n columns = c(\"id\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `size` is of type: character\n col_is_character(\n columns = c(\"size\")\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `price` is of type: numeric\n col_is_numeric(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `9.75` and `35.95`\n col_vals_between(\n columns = c(\"price\"),\n left = 9.75,\n right = 35.95\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n id = \"character\",\n date = \"character\",\n time = \"character\",\n name = \"character\",\n size = \"character\",\n type = \"character\",\n price = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `num` is of type: numeric\n col_is_numeric(\n columns = c(\"num\")\n ) %>%\n # Expect that values in `num` should be between `0.1111` and `8880000`\n col_vals_between(\n columns = c(\"num\"),\n left = 0.1111,\n right = 8880000,\n na_pass = TRUE\n ) %>%\n # Expect that column `char` is of type: character\n col_is_character(\n columns = c(\"char\")\n ) %>%\n # Expect that column `fctr` is of type: factor\n col_is_factor(\n columns = c(\"fctr\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `datetime` is of type: character\n col_is_character(\n columns = c(\"datetime\")\n ) %>%\n # Expect that column `currency` is of type: numeric\n col_is_numeric(\n columns = c(\"currency\")\n ) %>%\n # Expect that values in `currency` should be between `0.44` and `65100`\n col_vals_between(\n columns = c(\"currency\"),\n left = 0.44,\n right = 65100,\n na_pass = TRUE\n ) %>%\n # Expect that column `row` is of type: character\n col_is_character(\n columns = c(\"row\")\n ) %>%\n # Expect that column `group` is of type: character\n col_is_character(\n columns = c(\"group\")\n ) %>%\n # Expect entirely distinct rows across `num, char, fctr, date, time, datetime, currency, row, group`\n rows_distinct(\n columns = c(\"num\", \"char\", \"fctr\", \"date\", \"time\", \"datetime\", \"currency\", \"row\", \"group\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n num = \"numeric\",\n char = \"character\",\n fctr = \"factor\",\n date = \"character\",\n time = \"character\",\n datetime = \"character\",\n currency = \"numeric\",\n row = \"character\",\n group = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `num` is of type: numeric\n col_is_numeric(\n columns = c(\"num\")\n ) %>%\n # Expect that values in `num` should be between `0.1111` and `8880000`\n col_vals_between(\n columns = c(\"num\"),\n left = 0.1111,\n right = 8880000,\n na_pass = TRUE\n ) %>%\n # Expect that column `char` is of type: character\n col_is_character(\n columns = c(\"char\")\n ) %>%\n # Expect that column `fctr` is of type: factor\n col_is_factor(\n columns = c(\"fctr\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `datetime` is of type: character\n col_is_character(\n columns = c(\"datetime\")\n ) %>%\n # Expect that column `currency` is of type: numeric\n col_is_numeric(\n columns = c(\"currency\")\n ) %>%\n # Expect that values in `currency` should be between `0.44` and `65100`\n col_vals_between(\n columns = c(\"currency\"),\n left = 0.44,\n right = 65100,\n na_pass = TRUE\n ) %>%\n # Expect that column `row` is of type: character\n col_is_character(\n columns = c(\"row\")\n ) %>%\n # Expect that column `group` is of type: character\n col_is_character(\n columns = c(\"group\")\n ) %>%\n # Expect entirely distinct rows across `num, char, fctr, date, time, datetime, currency, row, group`\n rows_distinct(\n columns = c(\"num\", \"char\", \"fctr\", \"date\", \"time\", \"datetime\", \"currency\", \"row\", \"group\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n num = \"numeric\",\n char = \"character\",\n fctr = \"factor\",\n date = \"character\",\n time = \"character\",\n datetime = \"character\",\n currency = \"numeric\",\n row = \"character\",\n group = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `carat` is of type: numeric\n col_is_numeric(\n columns = c(\"carat\")\n ) %>%\n # Expect that values in `carat` should be between `0.2` and `5.01`\n col_vals_between(\n columns = c(\"carat\"),\n left = 0.2,\n right = 5.01\n ) %>%\n # Expect that column `cut` is of type: factor\n col_is_factor(\n columns = c(\"cut\")\n ) %>%\n # Expect that column `color` is of type: factor\n col_is_factor(\n columns = c(\"color\")\n ) %>%\n # Expect that column `clarity` is of type: factor\n col_is_factor(\n columns = c(\"clarity\")\n ) %>%\n # Expect that column `depth` is of type: numeric\n col_is_numeric(\n columns = c(\"depth\")\n ) %>%\n # Expect that values in `depth` should be between `43` and `79`\n col_vals_between(\n columns = c(\"depth\"),\n left = 43,\n right = 79\n ) %>%\n # Expect that column `table` is of type: numeric\n col_is_numeric(\n columns = c(\"table\")\n ) %>%\n # Expect that values in `table` should be between `43` and `95`\n col_vals_between(\n columns = c(\"table\"),\n left = 43,\n right = 95\n ) %>%\n # Expect that column `price` is of type: integer\n col_is_integer(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `326` and `18823`\n col_vals_between(\n columns = c(\"price\"),\n left = 326,\n right = 18823\n ) %>%\n # Expect that column `x` is of type: numeric\n col_is_numeric(\n columns = c(\"x\")\n ) %>%\n # Expect that values in `x` should be between `0` and `10.74`\n col_vals_between(\n columns = c(\"x\"),\n left = 0,\n right = 10.74\n ) %>%\n # Expect that column `y` is of type: numeric\n col_is_numeric(\n columns = c(\"y\")\n ) %>%\n # Expect that values in `y` should be between `0` and `58.9`\n col_vals_between(\n columns = c(\"y\"),\n left = 0,\n right = 58.9\n ) %>%\n # Expect that column `z` is of type: numeric\n col_is_numeric(\n columns = c(\"z\")\n ) %>%\n # Expect that values in `z` should be between `0` and `31.8`\n col_vals_between(\n columns = c(\"z\"),\n left = 0,\n right = 31.8\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n carat = \"numeric\",\n cut = c(\"ordered\", \"factor\"),\n color = c(\"ordered\", \"factor\"),\n clarity = c(\"ordered\", \"factor\"),\n depth = \"numeric\",\n table = \"numeric\",\n price = \"integer\",\n x = \"numeric\",\n y = \"numeric\",\n z = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `carat` is of type: numeric\n col_is_numeric(\n columns = c(\"carat\")\n ) %>%\n # Expect that values in `carat` should be between `0.2` and `5.01`\n col_vals_between(\n columns = c(\"carat\"),\n left = 0.2,\n right = 5.01\n ) %>%\n # Expect that column `cut` is of type: factor\n col_is_factor(\n columns = c(\"cut\")\n ) %>%\n # Expect that column `color` is of type: factor\n col_is_factor(\n columns = c(\"color\")\n ) %>%\n # Expect that column `clarity` is of type: factor\n col_is_factor(\n columns = c(\"clarity\")\n ) %>%\n # Expect that column `depth` is of type: numeric\n col_is_numeric(\n columns = c(\"depth\")\n ) %>%\n # Expect that values in `depth` should be between `43` and `79`\n col_vals_between(\n columns = c(\"depth\"),\n left = 43,\n right = 79\n ) %>%\n # Expect that column `table` is of type: numeric\n col_is_numeric(\n columns = c(\"table\")\n ) %>%\n # Expect that values in `table` should be between `43` and `95`\n col_vals_between(\n columns = c(\"table\"),\n left = 43,\n right = 95\n ) %>%\n # Expect that column `price` is of type: integer\n col_is_integer(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `326` and `18823`\n col_vals_between(\n columns = c(\"price\"),\n left = 326,\n right = 18823\n ) %>%\n # Expect that column `x` is of type: numeric\n col_is_numeric(\n columns = c(\"x\")\n ) %>%\n # Expect that values in `x` should be between `0` and `10.74`\n col_vals_between(\n columns = c(\"x\"),\n left = 0,\n right = 10.74\n ) %>%\n # Expect that column `y` is of type: numeric\n col_is_numeric(\n columns = c(\"y\")\n ) %>%\n # Expect that values in `y` should be between `0` and `58.9`\n col_vals_between(\n columns = c(\"y\"),\n left = 0,\n right = 58.9\n ) %>%\n # Expect that column `z` is of type: numeric\n col_is_numeric(\n columns = c(\"z\")\n ) %>%\n # Expect that values in `z` should be between `0` and `31.8`\n col_vals_between(\n columns = c(\"z\"),\n left = 0,\n right = 31.8\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n carat = \"numeric\",\n cut = c(\"ordered\", \"factor\"),\n color = c(\"ordered\", \"factor\"),\n clarity = c(\"ordered\", \"factor\"),\n depth = \"numeric\",\n table = \"numeric\",\n price = \"integer\",\n x = \"numeric\",\n y = \"numeric\",\n z = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `variable` is of type: character\n col_is_character(\n columns = c(\"variable\")\n ) %>%\n # Expect that column `value` is of type: numeric\n col_is_numeric(\n columns = c(\"value\")\n ) %>%\n # Expect that values in `value` should be between `2.2` and `320402.295`\n col_vals_between(\n columns = c(\"value\"),\n left = 2.2,\n right = 320402.295\n ) %>%\n # Expect that column `value01` is of type: numeric\n col_is_numeric(\n columns = c(\"value01\")\n ) %>%\n # Expect that values in `value01` should be between `0` and `1`\n col_vals_between(\n columns = c(\"value01\"),\n left = 0,\n right = 1\n ) %>%\n # Expect entirely distinct rows across `date, variable, value, value01`\n rows_distinct(\n columns = c(\"date\", \"variable\", \"value\", \"value01\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n variable = \"character\",\n value = \"numeric\",\n value01 = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `variable` is of type: character\n col_is_character(\n columns = c(\"variable\")\n ) %>%\n # Expect that column `value` is of type: numeric\n col_is_numeric(\n columns = c(\"value\")\n ) %>%\n # Expect that values in `value` should be between `2.2` and `320402.295`\n col_vals_between(\n columns = c(\"value\"),\n left = 2.2,\n right = 320402.295\n ) %>%\n # Expect that column `value01` is of type: numeric\n col_is_numeric(\n columns = c(\"value01\")\n ) %>%\n # Expect that values in `value01` should be between `0` and `1`\n col_vals_between(\n columns = c(\"value01\"),\n left = 0,\n right = 1\n ) %>%\n # Expect entirely distinct rows across `date, variable, value, value01`\n rows_distinct(\n columns = c(\"date\", \"variable\", \"value\", \"value01\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n variable = \"character\",\n value = \"numeric\",\n value01 = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `eruptions` is of type: numeric\n col_is_numeric(\n columns = c(\"eruptions\")\n ) %>%\n # Expect that values in `eruptions` should be between `1.6` and `5.1`\n col_vals_between(\n columns = c(\"eruptions\"),\n left = 1.6,\n right = 5.1\n ) %>%\n # Expect that column `waiting` is of type: numeric\n col_is_numeric(\n columns = c(\"waiting\")\n ) %>%\n # Expect that values in `waiting` should be between `43` and `96`\n col_vals_between(\n columns = c(\"waiting\"),\n left = 43,\n right = 96\n ) %>%\n # Expect that column `density` is of type: numeric\n col_is_numeric(\n columns = c(\"density\")\n ) %>%\n # Expect that values in `density` should be between `1.25924972782687e-24` and `0.0369877986891108`\n col_vals_between(\n columns = c(\"density\"),\n left = 1.2592497e-24,\n right = 0.0369878\n ) %>%\n # Expect entirely distinct rows across `eruptions, waiting, density`\n rows_distinct(\n columns = c(\"eruptions\", \"waiting\", \"density\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n eruptions = \"numeric\",\n waiting = \"numeric\",\n density = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `eruptions` is of type: numeric\n col_is_numeric(\n columns = c(\"eruptions\")\n ) %>%\n # Expect that values in `eruptions` should be between `1.6` and `5.1`\n col_vals_between(\n columns = c(\"eruptions\"),\n left = 1.6,\n right = 5.1\n ) %>%\n # Expect that column `waiting` is of type: numeric\n col_is_numeric(\n columns = c(\"waiting\")\n ) %>%\n # Expect that values in `waiting` should be between `43` and `96`\n col_vals_between(\n columns = c(\"waiting\"),\n left = 43,\n right = 96\n ) %>%\n # Expect that column `density` is of type: numeric\n col_is_numeric(\n columns = c(\"density\")\n ) %>%\n # Expect that values in `density` should be between `1.25924972782687e-24` and `0.0369877986891108`\n col_vals_between(\n columns = c(\"density\"),\n left = 1.2592497e-24,\n right = 0.0369878\n ) %>%\n # Expect entirely distinct rows across `eruptions, waiting, density`\n rows_distinct(\n columns = c(\"eruptions\", \"waiting\", \"density\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n eruptions = \"numeric\",\n waiting = \"numeric\",\n density = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `L` is of type: numeric\n col_is_numeric(\n columns = c(\"L\")\n ) %>%\n # Expect that values in `L` should be between `0` and `9341.57022199546`\n col_vals_between(\n columns = c(\"L\"),\n left = 0,\n right = 9341.570222\n ) %>%\n # Expect that column `u` is of type: numeric\n col_is_numeric(\n columns = c(\"u\")\n ) %>%\n # Expect that values in `u` should be between `-7971.69318804991` and `18325.9445754841`\n col_vals_between(\n columns = c(\"u\"),\n left = -7971.693188,\n right = 18325.9445755\n ) %>%\n # Expect that column `v` is of type: numeric\n col_is_numeric(\n columns = c(\"v\")\n ) %>%\n # Expect that values in `v` should be between `-15649.9250273997` and `10194.4413048169`\n col_vals_between(\n columns = c(\"v\"),\n left = -15649.9250274,\n right = 10194.4413048\n ) %>%\n # Expect that column `col` is of type: character\n col_is_character(\n columns = c(\"col\")\n ) %>%\n # Expect entirely distinct rows across `L, u, v, col`\n rows_distinct(\n columns = c(\"L\", \"u\", \"v\", \"col\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n L = \"numeric\",\n u = \"numeric\",\n v = \"numeric\",\n col = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `L` is of type: numeric\n col_is_numeric(\n columns = c(\"L\")\n ) %>%\n # Expect that values in `L` should be between `0` and `9341.57022199546`\n col_vals_between(\n columns = c(\"L\"),\n left = 0,\n right = 9341.570222\n ) %>%\n # Expect that column `u` is of type: numeric\n col_is_numeric(\n columns = c(\"u\")\n ) %>%\n # Expect that values in `u` should be between `-7971.69318804991` and `18325.9445754841`\n col_vals_between(\n columns = c(\"u\"),\n left = -7971.693188,\n right = 18325.9445755\n ) %>%\n # Expect that column `v` is of type: numeric\n col_is_numeric(\n columns = c(\"v\")\n ) %>%\n # Expect that values in `v` should be between `-15649.9250273997` and `10194.4413048169`\n col_vals_between(\n columns = c(\"v\"),\n left = -15649.9250274,\n right = 10194.4413048\n ) %>%\n # Expect that column `col` is of type: character\n col_is_character(\n columns = c(\"col\")\n ) %>%\n # Expect entirely distinct rows across `L, u, v, col`\n rows_distinct(\n columns = c(\"L\", \"u\", \"v\", \"col\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n L = \"numeric\",\n u = \"numeric\",\n v = \"numeric\",\n col = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `PID` is of type: integer\n col_is_integer(\n columns = c(\"PID\")\n ) %>%\n # Expect that values in `PID` should be between `561` and `3052`\n col_vals_between(\n columns = c(\"PID\"),\n left = 561,\n right = 3052\n ) %>%\n # Expect that column `county` is of type: character\n col_is_character(\n columns = c(\"county\")\n ) %>%\n # Expect that column `state` is of type: character\n col_is_character(\n columns = c(\"state\")\n ) %>%\n # Expect that column `area` is of type: numeric\n col_is_numeric(\n columns = c(\"area\")\n ) %>%\n # Expect that values in `area` should be between `0.005` and `0.11`\n col_vals_between(\n columns = c(\"area\"),\n left = 0.005,\n right = 0.11\n ) %>%\n # Expect that column `poptotal` is of type: integer\n col_is_integer(\n columns = c(\"poptotal\")\n ) %>%\n # Expect that values in `poptotal` should be between `1701` and `5105067`\n col_vals_between(\n columns = c(\"poptotal\"),\n left = 1701,\n right = 5105067\n ) %>%\n # Expect that column `popdensity` is of type: numeric\n col_is_numeric(\n columns = c(\"popdensity\")\n ) %>%\n # Expect that values in `popdensity` should be between `85.05` and `88018.3966`\n col_vals_between(\n columns = c(\"popdensity\"),\n left = 85.05,\n right = 88018.3966\n ) %>%\n # Expect that column `popwhite` is of type: integer\n col_is_integer(\n columns = c(\"popwhite\")\n ) %>%\n # Expect that values in `popwhite` should be between `416` and `3204947`\n col_vals_between(\n columns = c(\"popwhite\"),\n left = 416,\n right = 3204947\n ) %>%\n # Expect that column `popblack` is of type: integer\n col_is_integer(\n columns = c(\"popblack\")\n ) %>%\n # Expect that values in `popblack` should be between `0` and `1317147`\n col_vals_between(\n columns = c(\"popblack\"),\n left = 0,\n right = 1317147\n ) %>%\n # Expect that column `popamerindian` is of type: integer\n col_is_integer(\n columns = c(\"popamerindian\")\n ) %>%\n # Expect that values in `popamerindian` should be between `4` and `10289`\n col_vals_between(\n columns = c(\"popamerindian\"),\n left = 4,\n right = 10289\n ) %>%\n # Expect that column `popasian` is of type: integer\n col_is_integer(\n columns = c(\"popasian\")\n ) %>%\n # Expect that values in `popasian` should be between `0` and `188565`\n col_vals_between(\n columns = c(\"popasian\"),\n left = 0,\n right = 188565\n ) %>%\n # Expect that column `popother` is of type: integer\n col_is_integer(\n columns = c(\"popother\")\n ) %>%\n # Expect that values in `popother` should be between `0` and `384119`\n col_vals_between(\n columns = c(\"popother\"),\n left = 0,\n right = 384119\n ) %>%\n # Expect that column `percwhite` is of type: numeric\n col_is_numeric(\n columns = c(\"percwhite\")\n ) %>%\n # Expect that values in `percwhite` should be between `10.6940874` and `99.8228207`\n col_vals_between(\n columns = c(\"percwhite\"),\n left = 10.6940874,\n right = 99.8228207\n ) %>%\n # Expect that column `percblack` is of type: numeric\n col_is_numeric(\n columns = c(\"percblack\")\n ) %>%\n # Expect that values in `percblack` should be between `0` and `40.2099838`\n col_vals_between(\n columns = c(\"percblack\"),\n left = 0,\n right = 40.2099838\n ) %>%\n # Expect that column `percamerindan` is of type: numeric\n col_is_numeric(\n columns = c(\"percamerindan\")\n ) %>%\n # Expect that values in `percamerindan` should be between `0.05623243` and `89.1773779`\n col_vals_between(\n columns = c(\"percamerindan\"),\n left = 0.0562324,\n right = 89.1773779\n ) %>%\n # Expect that column `percasian` is of type: numeric\n col_is_numeric(\n columns = c(\"percasian\")\n ) %>%\n # Expect that values in `percasian` should be between `0` and `5.07045209`\n col_vals_between(\n columns = c(\"percasian\"),\n left = 0,\n right = 5.0704521\n ) %>%\n # Expect that column `percother` is of type: numeric\n col_is_numeric(\n columns = c(\"percother\")\n ) %>%\n # Expect that values in `percother` should be between `0` and `7.52426951`\n col_vals_between(\n columns = c(\"percother\"),\n left = 0,\n right = 7.5242695\n ) %>%\n # Expect that column `popadults` is of type: integer\n col_is_integer(\n columns = c(\"popadults\")\n ) %>%\n # Expect that values in `popadults` should be between `1287` and `3291995`\n col_vals_between(\n columns = c(\"popadults\"),\n left = 1287,\n right = 3291995\n ) %>%\n # Expect that column `perchsd` is of type: numeric\n col_is_numeric(\n columns = c(\"perchsd\")\n ) %>%\n # Expect that values in `perchsd` should be between `46.912261` and `88.8986737`\n col_vals_between(\n columns = c(\"perchsd\"),\n left = 46.912261,\n right = 88.8986737\n ) %>%\n # Expect that column `percollege` is of type: numeric\n col_is_numeric(\n columns = c(\"percollege\")\n ) %>%\n # Expect that values in `percollege` should be between `7.33610822` and `48.0785102`\n col_vals_between(\n columns = c(\"percollege\"),\n left = 7.3361082,\n right = 48.0785102\n ) %>%\n # Expect that column `percprof` is of type: numeric\n col_is_numeric(\n columns = c(\"percprof\")\n ) %>%\n # Expect that values in `percprof` should be between `0.52029136` and `20.7913213`\n col_vals_between(\n columns = c(\"percprof\"),\n left = 0.5202914,\n right = 20.7913213\n ) %>%\n # Expect that column `poppovertyknown` is of type: integer\n col_is_integer(\n columns = c(\"poppovertyknown\")\n ) %>%\n # Expect that values in `poppovertyknown` should be between `1696` and `5023523`\n col_vals_between(\n columns = c(\"poppovertyknown\"),\n left = 1696,\n right = 5023523\n ) %>%\n # Expect that column `percpovertyknown` is of type: numeric\n col_is_numeric(\n columns = c(\"percpovertyknown\")\n ) %>%\n # Expect that values in `percpovertyknown` should be between `80.9024412` and `99.8603839`\n col_vals_between(\n columns = c(\"percpovertyknown\"),\n left = 80.9024412,\n right = 99.8603839\n ) %>%\n # Expect that column `percbelowpoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percbelowpoverty\")\n ) %>%\n # Expect that values in `percbelowpoverty` should be between `2.1801676` and `48.6910995`\n col_vals_between(\n columns = c(\"percbelowpoverty\"),\n left = 2.1801676,\n right = 48.6910995\n ) %>%\n # Expect that column `percchildbelowpovert` is of type: numeric\n col_is_numeric(\n columns = c(\"percchildbelowpovert\")\n ) %>%\n # Expect that values in `percchildbelowpovert` should be between `1.91895478` and `64.3084767`\n col_vals_between(\n columns = c(\"percchildbelowpovert\"),\n left = 1.9189548,\n right = 64.3084767\n ) %>%\n # Expect that column `percadultpoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percadultpoverty\")\n ) %>%\n # Expect that values in `percadultpoverty` should be between `1.9385043` and `43.3124644`\n col_vals_between(\n columns = c(\"percadultpoverty\"),\n left = 1.9385043,\n right = 43.3124644\n ) %>%\n # Expect that column `percelderlypoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percelderlypoverty\")\n ) %>%\n # Expect that values in `percelderlypoverty` should be between `3.54706685` and `31.1619718`\n col_vals_between(\n columns = c(\"percelderlypoverty\"),\n left = 3.5470669,\n right = 31.1619718\n ) %>%\n # Expect that column `inmetro` is of type: integer\n col_is_integer(\n columns = c(\"inmetro\")\n ) %>%\n # Expect that values in `inmetro` should be between `0` and `1`\n col_vals_between(\n columns = c(\"inmetro\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `category` is of type: character\n col_is_character(\n columns = c(\"category\")\n ) %>%\n # Expect entirely distinct rows across `PID, county, state, area, poptotal, popdensity, popwhite, popblack, popamerindian, popasian, popother, percwhite, percblack, percamerindan, percasian, percother, popadults, perchsd, percollege, percprof, poppovertyknown, percpovertyknown, percbelowpoverty, percchildbelowpovert, percadultpoverty, percelderlypoverty, inmetro, category`\n rows_distinct(\n columns = c(\"PID\", \"county\", \"state\", \"area\", \"poptotal\", \"popdensity\", \"popwhite\", \"popblack\", \"popamerindian\", \"popasian\", \"popother\", \"percwhite\", \"percblack\", \"percamerindan\", \"percasian\", \"percother\", \"popadults\", \"perchsd\", \"percollege\", \"percprof\", \"poppovertyknown\", \"percpovertyknown\", \"percbelowpoverty\", \"percchildbelowpovert\", \"percadultpoverty\", \"percelderlypoverty\", \"inmetro\", \"category\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n PID = \"integer\",\n county = \"character\",\n state = \"character\",\n area = \"numeric\",\n poptotal = \"integer\",\n popdensity = \"numeric\",\n popwhite = \"integer\",\n popblack = \"integer\",\n popamerindian = \"integer\",\n popasian = \"integer\",\n popother = \"integer\",\n percwhite = \"numeric\",\n percblack = \"numeric\",\n percamerindan = \"numeric\",\n percasian = \"numeric\",\n percother = \"numeric\",\n popadults = \"integer\",\n perchsd = \"numeric\",\n percollege = \"numeric\",\n percprof = \"numeric\",\n poppovertyknown = \"integer\",\n percpovertyknown = \"numeric\",\n percbelowpoverty = \"numeric\",\n percchildbelowpovert = \"numeric\",\n percadultpoverty = \"numeric\",\n percelderlypoverty = \"numeric\",\n inmetro = \"integer\",\n category = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `PID` is of type: integer\n col_is_integer(\n columns = c(\"PID\")\n ) %>%\n # Expect that values in `PID` should be between `561` and `3052`\n col_vals_between(\n columns = c(\"PID\"),\n left = 561,\n right = 3052\n ) %>%\n # Expect that column `county` is of type: character\n col_is_character(\n columns = c(\"county\")\n ) %>%\n # Expect that column `state` is of type: character\n col_is_character(\n columns = c(\"state\")\n ) %>%\n # Expect that column `area` is of type: numeric\n col_is_numeric(\n columns = c(\"area\")\n ) %>%\n # Expect that values in `area` should be between `0.005` and `0.11`\n col_vals_between(\n columns = c(\"area\"),\n left = 0.005,\n right = 0.11\n ) %>%\n # Expect that column `poptotal` is of type: integer\n col_is_integer(\n columns = c(\"poptotal\")\n ) %>%\n # Expect that values in `poptotal` should be between `1701` and `5105067`\n col_vals_between(\n columns = c(\"poptotal\"),\n left = 1701,\n right = 5105067\n ) %>%\n # Expect that column `popdensity` is of type: numeric\n col_is_numeric(\n columns = c(\"popdensity\")\n ) %>%\n # Expect that values in `popdensity` should be between `85.05` and `88018.3966`\n col_vals_between(\n columns = c(\"popdensity\"),\n left = 85.05,\n right = 88018.3966\n ) %>%\n # Expect that column `popwhite` is of type: integer\n col_is_integer(\n columns = c(\"popwhite\")\n ) %>%\n # Expect that values in `popwhite` should be between `416` and `3204947`\n col_vals_between(\n columns = c(\"popwhite\"),\n left = 416,\n right = 3204947\n ) %>%\n # Expect that column `popblack` is of type: integer\n col_is_integer(\n columns = c(\"popblack\")\n ) %>%\n # Expect that values in `popblack` should be between `0` and `1317147`\n col_vals_between(\n columns = c(\"popblack\"),\n left = 0,\n right = 1317147\n ) %>%\n # Expect that column `popamerindian` is of type: integer\n col_is_integer(\n columns = c(\"popamerindian\")\n ) %>%\n # Expect that values in `popamerindian` should be between `4` and `10289`\n col_vals_between(\n columns = c(\"popamerindian\"),\n left = 4,\n right = 10289\n ) %>%\n # Expect that column `popasian` is of type: integer\n col_is_integer(\n columns = c(\"popasian\")\n ) %>%\n # Expect that values in `popasian` should be between `0` and `188565`\n col_vals_between(\n columns = c(\"popasian\"),\n left = 0,\n right = 188565\n ) %>%\n # Expect that column `popother` is of type: integer\n col_is_integer(\n columns = c(\"popother\")\n ) %>%\n # Expect that values in `popother` should be between `0` and `384119`\n col_vals_between(\n columns = c(\"popother\"),\n left = 0,\n right = 384119\n ) %>%\n # Expect that column `percwhite` is of type: numeric\n col_is_numeric(\n columns = c(\"percwhite\")\n ) %>%\n # Expect that values in `percwhite` should be between `10.6940874` and `99.8228207`\n col_vals_between(\n columns = c(\"percwhite\"),\n left = 10.6940874,\n right = 99.8228207\n ) %>%\n # Expect that column `percblack` is of type: numeric\n col_is_numeric(\n columns = c(\"percblack\")\n ) %>%\n # Expect that values in `percblack` should be between `0` and `40.2099838`\n col_vals_between(\n columns = c(\"percblack\"),\n left = 0,\n right = 40.2099838\n ) %>%\n # Expect that column `percamerindan` is of type: numeric\n col_is_numeric(\n columns = c(\"percamerindan\")\n ) %>%\n # Expect that values in `percamerindan` should be between `0.05623243` and `89.1773779`\n col_vals_between(\n columns = c(\"percamerindan\"),\n left = 0.0562324,\n right = 89.1773779\n ) %>%\n # Expect that column `percasian` is of type: numeric\n col_is_numeric(\n columns = c(\"percasian\")\n ) %>%\n # Expect that values in `percasian` should be between `0` and `5.07045209`\n col_vals_between(\n columns = c(\"percasian\"),\n left = 0,\n right = 5.0704521\n ) %>%\n # Expect that column `percother` is of type: numeric\n col_is_numeric(\n columns = c(\"percother\")\n ) %>%\n # Expect that values in `percother` should be between `0` and `7.52426951`\n col_vals_between(\n columns = c(\"percother\"),\n left = 0,\n right = 7.5242695\n ) %>%\n # Expect that column `popadults` is of type: integer\n col_is_integer(\n columns = c(\"popadults\")\n ) %>%\n # Expect that values in `popadults` should be between `1287` and `3291995`\n col_vals_between(\n columns = c(\"popadults\"),\n left = 1287,\n right = 3291995\n ) %>%\n # Expect that column `perchsd` is of type: numeric\n col_is_numeric(\n columns = c(\"perchsd\")\n ) %>%\n # Expect that values in `perchsd` should be between `46.912261` and `88.8986737`\n col_vals_between(\n columns = c(\"perchsd\"),\n left = 46.912261,\n right = 88.8986737\n ) %>%\n # Expect that column `percollege` is of type: numeric\n col_is_numeric(\n columns = c(\"percollege\")\n ) %>%\n # Expect that values in `percollege` should be between `7.33610822` and `48.0785102`\n col_vals_between(\n columns = c(\"percollege\"),\n left = 7.3361082,\n right = 48.0785102\n ) %>%\n # Expect that column `percprof` is of type: numeric\n col_is_numeric(\n columns = c(\"percprof\")\n ) %>%\n # Expect that values in `percprof` should be between `0.52029136` and `20.7913213`\n col_vals_between(\n columns = c(\"percprof\"),\n left = 0.5202914,\n right = 20.7913213\n ) %>%\n # Expect that column `poppovertyknown` is of type: integer\n col_is_integer(\n columns = c(\"poppovertyknown\")\n ) %>%\n # Expect that values in `poppovertyknown` should be between `1696` and `5023523`\n col_vals_between(\n columns = c(\"poppovertyknown\"),\n left = 1696,\n right = 5023523\n ) %>%\n # Expect that column `percpovertyknown` is of type: numeric\n col_is_numeric(\n columns = c(\"percpovertyknown\")\n ) %>%\n # Expect that values in `percpovertyknown` should be between `80.9024412` and `99.8603839`\n col_vals_between(\n columns = c(\"percpovertyknown\"),\n left = 80.9024412,\n right = 99.8603839\n ) %>%\n # Expect that column `percbelowpoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percbelowpoverty\")\n ) %>%\n # Expect that values in `percbelowpoverty` should be between `2.1801676` and `48.6910995`\n col_vals_between(\n columns = c(\"percbelowpoverty\"),\n left = 2.1801676,\n right = 48.6910995\n ) %>%\n # Expect that column `percchildbelowpovert` is of type: numeric\n col_is_numeric(\n columns = c(\"percchildbelowpovert\")\n ) %>%\n # Expect that values in `percchildbelowpovert` should be between `1.91895478` and `64.3084767`\n col_vals_between(\n columns = c(\"percchildbelowpovert\"),\n left = 1.9189548,\n right = 64.3084767\n ) %>%\n # Expect that column `percadultpoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percadultpoverty\")\n ) %>%\n # Expect that values in `percadultpoverty` should be between `1.9385043` and `43.3124644`\n col_vals_between(\n columns = c(\"percadultpoverty\"),\n left = 1.9385043,\n right = 43.3124644\n ) %>%\n # Expect that column `percelderlypoverty` is of type: numeric\n col_is_numeric(\n columns = c(\"percelderlypoverty\")\n ) %>%\n # Expect that values in `percelderlypoverty` should be between `3.54706685` and `31.1619718`\n col_vals_between(\n columns = c(\"percelderlypoverty\"),\n left = 3.5470669,\n right = 31.1619718\n ) %>%\n # Expect that column `inmetro` is of type: integer\n col_is_integer(\n columns = c(\"inmetro\")\n ) %>%\n # Expect that values in `inmetro` should be between `0` and `1`\n col_vals_between(\n columns = c(\"inmetro\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `category` is of type: character\n col_is_character(\n columns = c(\"category\")\n ) %>%\n # Expect entirely distinct rows across `PID, county, state, area, poptotal, popdensity, popwhite, popblack, popamerindian, popasian, popother, percwhite, percblack, percamerindan, percasian, percother, popadults, perchsd, percollege, percprof, poppovertyknown, percpovertyknown, percbelowpoverty, percchildbelowpovert, percadultpoverty, percelderlypoverty, inmetro, category`\n rows_distinct(\n columns = c(\"PID\", \"county\", \"state\", \"area\", \"poptotal\", \"popdensity\", \"popwhite\", \"popblack\", \"popamerindian\", \"popasian\", \"popother\", \"percwhite\", \"percblack\", \"percamerindan\", \"percasian\", \"percother\", \"popadults\", \"perchsd\", \"percollege\", \"percprof\", \"poppovertyknown\", \"percpovertyknown\", \"percbelowpoverty\", \"percchildbelowpovert\", \"percadultpoverty\", \"percelderlypoverty\", \"inmetro\", \"category\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n PID = \"integer\",\n county = \"character\",\n state = \"character\",\n area = \"numeric\",\n poptotal = \"integer\",\n popdensity = \"numeric\",\n popwhite = \"integer\",\n popblack = \"integer\",\n popamerindian = \"integer\",\n popasian = \"integer\",\n popother = \"integer\",\n percwhite = \"numeric\",\n percblack = \"numeric\",\n percamerindan = \"numeric\",\n percasian = \"numeric\",\n percother = \"numeric\",\n popadults = \"integer\",\n perchsd = \"numeric\",\n percollege = \"numeric\",\n percprof = \"numeric\",\n poppovertyknown = \"integer\",\n percpovertyknown = \"numeric\",\n percbelowpoverty = \"numeric\",\n percchildbelowpovert = \"numeric\",\n percadultpoverty = \"numeric\",\n percelderlypoverty = \"numeric\",\n inmetro = \"integer\",\n category = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `manufacturer` is of type: character\n col_is_character(\n columns = c(\"manufacturer\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `displ` is of type: numeric\n col_is_numeric(\n columns = c(\"displ\")\n ) %>%\n # Expect that values in `displ` should be between `1.6` and `7`\n col_vals_between(\n columns = c(\"displ\"),\n left = 1.6,\n right = 7\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `1999` and `2008`\n col_vals_between(\n columns = c(\"year\"),\n left = 1999,\n right = 2008\n ) %>%\n # Expect that column `cyl` is of type: integer\n col_is_integer(\n columns = c(\"cyl\")\n ) %>%\n # Expect that values in `cyl` should be between `4` and `8`\n col_vals_between(\n columns = c(\"cyl\"),\n left = 4,\n right = 8\n ) %>%\n # Expect that column `trans` is of type: character\n col_is_character(\n columns = c(\"trans\")\n ) %>%\n # Expect that column `drv` is of type: character\n col_is_character(\n columns = c(\"drv\")\n ) %>%\n # Expect that column `cty` is of type: integer\n col_is_integer(\n columns = c(\"cty\")\n ) %>%\n # Expect that values in `cty` should be between `9` and `35`\n col_vals_between(\n columns = c(\"cty\"),\n left = 9,\n right = 35\n ) %>%\n # Expect that column `hwy` is of type: integer\n col_is_integer(\n columns = c(\"hwy\")\n ) %>%\n # Expect that values in `hwy` should be between `12` and `44`\n col_vals_between(\n columns = c(\"hwy\"),\n left = 12,\n right = 44\n ) %>%\n # Expect that column `fl` is of type: character\n col_is_character(\n columns = c(\"fl\")\n ) %>%\n # Expect that column `class` is of type: character\n col_is_character(\n columns = c(\"class\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n manufacturer = \"character\",\n model = \"character\",\n displ = \"numeric\",\n year = \"integer\",\n cyl = \"integer\",\n trans = \"character\",\n drv = \"character\",\n cty = \"integer\",\n hwy = \"integer\",\n fl = \"character\",\n class = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `manufacturer` is of type: character\n col_is_character(\n columns = c(\"manufacturer\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `displ` is of type: numeric\n col_is_numeric(\n columns = c(\"displ\")\n ) %>%\n # Expect that values in `displ` should be between `1.6` and `7`\n col_vals_between(\n columns = c(\"displ\"),\n left = 1.6,\n right = 7\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `1999` and `2008`\n col_vals_between(\n columns = c(\"year\"),\n left = 1999,\n right = 2008\n ) %>%\n # Expect that column `cyl` is of type: integer\n col_is_integer(\n columns = c(\"cyl\")\n ) %>%\n # Expect that values in `cyl` should be between `4` and `8`\n col_vals_between(\n columns = c(\"cyl\"),\n left = 4,\n right = 8\n ) %>%\n # Expect that column `trans` is of type: character\n col_is_character(\n columns = c(\"trans\")\n ) %>%\n # Expect that column `drv` is of type: character\n col_is_character(\n columns = c(\"drv\")\n ) %>%\n # Expect that column `cty` is of type: integer\n col_is_integer(\n columns = c(\"cty\")\n ) %>%\n # Expect that values in `cty` should be between `9` and `35`\n col_vals_between(\n columns = c(\"cty\"),\n left = 9,\n right = 35\n ) %>%\n # Expect that column `hwy` is of type: integer\n col_is_integer(\n columns = c(\"hwy\")\n ) %>%\n # Expect that values in `hwy` should be between `12` and `44`\n col_vals_between(\n columns = c(\"hwy\"),\n left = 12,\n right = 44\n ) %>%\n # Expect that column `fl` is of type: character\n col_is_character(\n columns = c(\"fl\")\n ) %>%\n # Expect that column `class` is of type: character\n col_is_character(\n columns = c(\"class\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n manufacturer = \"character\",\n model = \"character\",\n displ = \"numeric\",\n year = \"integer\",\n cyl = \"integer\",\n trans = \"character\",\n drv = \"character\",\n cty = \"integer\",\n hwy = \"integer\",\n fl = \"character\",\n class = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `genus` is of type: character\n col_is_character(\n columns = c(\"genus\")\n ) %>%\n # Expect that column `vore` is of type: character\n col_is_character(\n columns = c(\"vore\")\n ) %>%\n # Expect that column `order` is of type: character\n col_is_character(\n columns = c(\"order\")\n ) %>%\n # Expect that column `conservation` is of type: character\n col_is_character(\n columns = c(\"conservation\")\n ) %>%\n # Expect that column `sleep_total` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_total\")\n ) %>%\n # Expect that values in `sleep_total` should be between `1.9` and `19.9`\n col_vals_between(\n columns = c(\"sleep_total\"),\n left = 1.9,\n right = 19.9\n ) %>%\n # Expect that column `sleep_rem` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_rem\")\n ) %>%\n # Expect that values in `sleep_rem` should be between `0.1` and `6.6`\n col_vals_between(\n columns = c(\"sleep_rem\"),\n left = 0.1,\n right = 6.6,\n na_pass = TRUE\n ) %>%\n # Expect that column `sleep_cycle` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_cycle\")\n ) %>%\n # Expect that values in `sleep_cycle` should be between `0.116666667` and `1.5`\n col_vals_between(\n columns = c(\"sleep_cycle\"),\n left = 0.1166667,\n right = 1.5,\n na_pass = TRUE\n ) %>%\n # Expect that column `awake` is of type: numeric\n col_is_numeric(\n columns = c(\"awake\")\n ) %>%\n # Expect that values in `awake` should be between `4.1` and `22.1`\n col_vals_between(\n columns = c(\"awake\"),\n left = 4.1,\n right = 22.1\n ) %>%\n # Expect that column `brainwt` is of type: numeric\n col_is_numeric(\n columns = c(\"brainwt\")\n ) %>%\n # Expect that values in `brainwt` should be between `0.00014` and `5.712`\n col_vals_between(\n columns = c(\"brainwt\"),\n left = 0.00014,\n right = 5.712,\n na_pass = TRUE\n ) %>%\n # Expect that column `bodywt` is of type: numeric\n col_is_numeric(\n columns = c(\"bodywt\")\n ) %>%\n # Expect that values in `bodywt` should be between `0.005` and `6654`\n col_vals_between(\n columns = c(\"bodywt\"),\n left = 0.005,\n right = 6654\n ) %>%\n # Expect entirely distinct rows across `name, genus, vore, order, conservation, sleep_total, sleep_rem, sleep_cycle, awake, brainwt, bodywt`\n rows_distinct(\n columns = c(\"name\", \"genus\", \"vore\", \"order\", \"conservation\", \"sleep_total\", \"sleep_rem\", \"sleep_cycle\", \"awake\", \"brainwt\", \"bodywt\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n genus = \"character\",\n vore = \"character\",\n order = \"character\",\n conservation = \"character\",\n sleep_total = \"numeric\",\n sleep_rem = \"numeric\",\n sleep_cycle = \"numeric\",\n awake = \"numeric\",\n brainwt = \"numeric\",\n bodywt = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `genus` is of type: character\n col_is_character(\n columns = c(\"genus\")\n ) %>%\n # Expect that column `vore` is of type: character\n col_is_character(\n columns = c(\"vore\")\n ) %>%\n # Expect that column `order` is of type: character\n col_is_character(\n columns = c(\"order\")\n ) %>%\n # Expect that column `conservation` is of type: character\n col_is_character(\n columns = c(\"conservation\")\n ) %>%\n # Expect that column `sleep_total` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_total\")\n ) %>%\n # Expect that values in `sleep_total` should be between `1.9` and `19.9`\n col_vals_between(\n columns = c(\"sleep_total\"),\n left = 1.9,\n right = 19.9\n ) %>%\n # Expect that column `sleep_rem` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_rem\")\n ) %>%\n # Expect that values in `sleep_rem` should be between `0.1` and `6.6`\n col_vals_between(\n columns = c(\"sleep_rem\"),\n left = 0.1,\n right = 6.6,\n na_pass = TRUE\n ) %>%\n # Expect that column `sleep_cycle` is of type: numeric\n col_is_numeric(\n columns = c(\"sleep_cycle\")\n ) %>%\n # Expect that values in `sleep_cycle` should be between `0.116666667` and `1.5`\n col_vals_between(\n columns = c(\"sleep_cycle\"),\n left = 0.1166667,\n right = 1.5,\n na_pass = TRUE\n ) %>%\n # Expect that column `awake` is of type: numeric\n col_is_numeric(\n columns = c(\"awake\")\n ) %>%\n # Expect that values in `awake` should be between `4.1` and `22.1`\n col_vals_between(\n columns = c(\"awake\"),\n left = 4.1,\n right = 22.1\n ) %>%\n # Expect that column `brainwt` is of type: numeric\n col_is_numeric(\n columns = c(\"brainwt\")\n ) %>%\n # Expect that values in `brainwt` should be between `0.00014` and `5.712`\n col_vals_between(\n columns = c(\"brainwt\"),\n left = 0.00014,\n right = 5.712,\n na_pass = TRUE\n ) %>%\n # Expect that column `bodywt` is of type: numeric\n col_is_numeric(\n columns = c(\"bodywt\")\n ) %>%\n # Expect that values in `bodywt` should be between `0.005` and `6654`\n col_vals_between(\n columns = c(\"bodywt\"),\n left = 0.005,\n right = 6654\n ) %>%\n # Expect entirely distinct rows across `name, genus, vore, order, conservation, sleep_total, sleep_rem, sleep_cycle, awake, brainwt, bodywt`\n rows_distinct(\n columns = c(\"name\", \"genus\", \"vore\", \"order\", \"conservation\", \"sleep_total\", \"sleep_rem\", \"sleep_cycle\", \"awake\", \"brainwt\", \"bodywt\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n genus = \"character\",\n vore = \"character\",\n order = \"character\",\n conservation = \"character\",\n sleep_total = \"numeric\",\n sleep_rem = \"numeric\",\n sleep_cycle = \"numeric\",\n awake = \"numeric\",\n brainwt = \"numeric\",\n bodywt = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `party` is of type: character\n col_is_character(\n columns = c(\"party\")\n ) %>%\n # Expect entirely distinct rows across `name, start, end, party`\n rows_distinct(\n columns = c(\"name\", \"start\", \"end\", \"party\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n start = \"Date\",\n end = \"Date\",\n party = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `party` is of type: character\n col_is_character(\n columns = c(\"party\")\n ) %>%\n # Expect entirely distinct rows across `name, start, end, party`\n rows_distinct(\n columns = c(\"name\", \"start\", \"end\", \"party\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n start = \"Date\",\n end = \"Date\",\n party = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `lat` is of type: numeric\n col_is_numeric(\n columns = c(\"lat\")\n ) %>%\n # Expect that values in `lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `long` is of type: numeric\n col_is_numeric(\n columns = c(\"long\")\n ) %>%\n # Expect that values in `long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `delta_long` is of type: numeric\n col_is_numeric(\n columns = c(\"delta_long\")\n ) %>%\n # Expect that values in `delta_long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"delta_long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `delta_lat` is of type: numeric\n col_is_numeric(\n columns = c(\"delta_lat\")\n ) %>%\n # Expect that values in `delta_lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"delta_lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect entirely distinct rows across `lat, long, delta_long, delta_lat`\n rows_distinct(\n columns = c(\"lat\", \"long\", \"delta_long\", \"delta_lat\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n lat = \"numeric\",\n long = \"numeric\",\n delta_long = \"numeric\",\n delta_lat = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `lat` is of type: numeric\n col_is_numeric(\n columns = c(\"lat\")\n ) %>%\n # Expect that values in `lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `long` is of type: numeric\n col_is_numeric(\n columns = c(\"long\")\n ) %>%\n # Expect that values in `long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `delta_long` is of type: numeric\n col_is_numeric(\n columns = c(\"delta_long\")\n ) %>%\n # Expect that values in `delta_long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"delta_long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `delta_lat` is of type: numeric\n col_is_numeric(\n columns = c(\"delta_lat\")\n ) %>%\n # Expect that values in `delta_lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"delta_lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect entirely distinct rows across `lat, long, delta_long, delta_lat`\n rows_distinct(\n columns = c(\"lat\", \"long\", \"delta_long\", \"delta_lat\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n lat = \"numeric\",\n long = \"numeric\",\n delta_long = \"numeric\",\n delta_lat = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `city` is of type: character\n col_is_character(\n columns = c(\"city\")\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2000` and `2015`\n col_vals_between(\n columns = c(\"year\"),\n left = 2000,\n right = 2015\n ) %>%\n # Expect that column `month` is of type: integer\n col_is_integer(\n columns = c(\"month\")\n ) %>%\n # Expect that values in `month` should be between `1` and `12`\n col_vals_between(\n columns = c(\"month\"),\n left = 1,\n right = 12\n ) %>%\n # Expect that column `sales` is of type: numeric\n col_is_numeric(\n columns = c(\"sales\")\n ) %>%\n # Expect that values in `sales` should be between `6` and `8945`\n col_vals_between(\n columns = c(\"sales\"),\n left = 6,\n right = 8945,\n na_pass = TRUE\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `835000` and `2568156780`\n col_vals_between(\n columns = c(\"volume\"),\n left = 835000,\n right = 2568156800,\n na_pass = TRUE\n ) %>%\n # Expect that column `median` is of type: numeric\n col_is_numeric(\n columns = c(\"median\")\n ) %>%\n # Expect that values in `median` should be between `50000` and `304200`\n col_vals_between(\n columns = c(\"median\"),\n left = 50000,\n right = 304200,\n na_pass = TRUE\n ) %>%\n # Expect that column `listings` is of type: numeric\n col_is_numeric(\n columns = c(\"listings\")\n ) %>%\n # Expect that values in `listings` should be between `0` and `43107`\n col_vals_between(\n columns = c(\"listings\"),\n left = 0,\n right = 43107,\n na_pass = TRUE\n ) %>%\n # Expect that column `inventory` is of type: numeric\n col_is_numeric(\n columns = c(\"inventory\")\n ) %>%\n # Expect that values in `inventory` should be between `0` and `55.9`\n col_vals_between(\n columns = c(\"inventory\"),\n left = 0,\n right = 55.9,\n na_pass = TRUE\n ) %>%\n # Expect that column `date` is of type: numeric\n col_is_numeric(\n columns = c(\"date\")\n ) %>%\n # Expect that values in `date` should be between `2000` and `2015.5`\n col_vals_between(\n columns = c(\"date\"),\n left = 2000,\n right = 2015.5\n ) %>%\n # Expect entirely distinct rows across `city, year, month, sales, volume, median, listings, inventory, date`\n rows_distinct(\n columns = c(\"city\", \"year\", \"month\", \"sales\", \"volume\", \"median\", \"listings\", \"inventory\", \"date\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n city = \"character\",\n year = \"integer\",\n month = \"integer\",\n sales = \"numeric\",\n volume = \"numeric\",\n median = \"numeric\",\n listings = \"numeric\",\n inventory = \"numeric\",\n date = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `city` is of type: character\n col_is_character(\n columns = c(\"city\")\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2000` and `2015`\n col_vals_between(\n columns = c(\"year\"),\n left = 2000,\n right = 2015\n ) %>%\n # Expect that column `month` is of type: integer\n col_is_integer(\n columns = c(\"month\")\n ) %>%\n # Expect that values in `month` should be between `1` and `12`\n col_vals_between(\n columns = c(\"month\"),\n left = 1,\n right = 12\n ) %>%\n # Expect that column `sales` is of type: numeric\n col_is_numeric(\n columns = c(\"sales\")\n ) %>%\n # Expect that values in `sales` should be between `6` and `8945`\n col_vals_between(\n columns = c(\"sales\"),\n left = 6,\n right = 8945,\n na_pass = TRUE\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `835000` and `2568156780`\n col_vals_between(\n columns = c(\"volume\"),\n left = 835000,\n right = 2568156800,\n na_pass = TRUE\n ) %>%\n # Expect that column `median` is of type: numeric\n col_is_numeric(\n columns = c(\"median\")\n ) %>%\n # Expect that values in `median` should be between `50000` and `304200`\n col_vals_between(\n columns = c(\"median\"),\n left = 50000,\n right = 304200,\n na_pass = TRUE\n ) %>%\n # Expect that column `listings` is of type: numeric\n col_is_numeric(\n columns = c(\"listings\")\n ) %>%\n # Expect that values in `listings` should be between `0` and `43107`\n col_vals_between(\n columns = c(\"listings\"),\n left = 0,\n right = 43107,\n na_pass = TRUE\n ) %>%\n # Expect that column `inventory` is of type: numeric\n col_is_numeric(\n columns = c(\"inventory\")\n ) %>%\n # Expect that values in `inventory` should be between `0` and `55.9`\n col_vals_between(\n columns = c(\"inventory\"),\n left = 0,\n right = 55.9,\n na_pass = TRUE\n ) %>%\n # Expect that column `date` is of type: numeric\n col_is_numeric(\n columns = c(\"date\")\n ) %>%\n # Expect that values in `date` should be between `2000` and `2015.5`\n col_vals_between(\n columns = c(\"date\"),\n left = 2000,\n right = 2015.5\n ) %>%\n # Expect entirely distinct rows across `city, year, month, sales, volume, median, listings, inventory, date`\n rows_distinct(\n columns = c(\"city\", \"year\", \"month\", \"sales\", \"volume\", \"median\", \"listings\", \"inventory\", \"date\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n city = \"character\",\n year = \"integer\",\n month = \"integer\",\n sales = \"numeric\",\n volume = \"numeric\",\n median = \"numeric\",\n listings = \"numeric\",\n inventory = \"numeric\",\n date = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `plays` is of type: character\n col_is_character(\n columns = c(\"plays\")\n ) %>%\n # Expect entirely distinct rows across `name, plays`\n rows_distinct(\n columns = c(\"name\", \"plays\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n plays = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `plays` is of type: character\n col_is_character(\n columns = c(\"plays\")\n ) %>%\n # Expect entirely distinct rows across `name, plays`\n rows_distinct(\n columns = c(\"name\", \"plays\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n plays = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `band` is of type: character\n col_is_character(\n columns = c(\"band\")\n ) %>%\n # Expect entirely distinct rows across `name, band`\n rows_distinct(\n columns = c(\"name\", \"band\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n band = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `band` is of type: character\n col_is_character(\n columns = c(\"band\")\n ) %>%\n # Expect entirely distinct rows across `name, band`\n rows_distinct(\n columns = c(\"name\", \"band\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n band = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `height` is of type: integer\n col_is_integer(\n columns = c(\"height\")\n ) %>%\n # Expect that values in `height` should be between `66` and `264`\n col_vals_between(\n columns = c(\"height\"),\n left = 66,\n right = 264,\n na_pass = TRUE\n ) %>%\n # Expect that column `mass` is of type: numeric\n col_is_numeric(\n columns = c(\"mass\")\n ) %>%\n # Expect that values in `mass` should be between `15` and `1358`\n col_vals_between(\n columns = c(\"mass\"),\n left = 15,\n right = 1358,\n na_pass = TRUE\n ) %>%\n # Expect that column `hair_color` is of type: character\n col_is_character(\n columns = c(\"hair_color\")\n ) %>%\n # Expect that column `skin_color` is of type: character\n col_is_character(\n columns = c(\"skin_color\")\n ) %>%\n # Expect that column `eye_color` is of type: character\n col_is_character(\n columns = c(\"eye_color\")\n ) %>%\n # Expect that column `birth_year` is of type: numeric\n col_is_numeric(\n columns = c(\"birth_year\")\n ) %>%\n # Expect that values in `birth_year` should be between `8` and `896`\n col_vals_between(\n columns = c(\"birth_year\"),\n left = 8,\n right = 896,\n na_pass = TRUE\n ) %>%\n # Expect that column `sex` is of type: character\n col_is_character(\n columns = c(\"sex\")\n ) %>%\n # Expect that column `gender` is of type: character\n col_is_character(\n columns = c(\"gender\")\n ) %>%\n # Expect that column `homeworld` is of type: character\n col_is_character(\n columns = c(\"homeworld\")\n ) %>%\n # Expect that column `species` is of type: character\n col_is_character(\n columns = c(\"species\")\n ) %>%\n # Expect entirely distinct rows across `name, height, mass, hair_color, skin_color, eye_color, birth_year, sex, gender, homeworld, species, films, vehicles, starships`\n rows_distinct(\n columns = c(\"name\", \"height\", \"mass\", \"hair_color\", \"skin_color\", \"eye_color\", \"birth_year\", \"sex\", \"gender\", \"homeworld\", \"species\", \"films\", \"vehicles\", \"starships\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n height = \"integer\",\n mass = \"numeric\",\n hair_color = \"character\",\n skin_color = \"character\",\n eye_color = \"character\",\n birth_year = \"numeric\",\n sex = \"character\",\n gender = \"character\",\n homeworld = \"character\",\n species = \"character\",\n films = \"list\",\n vehicles = \"list\",\n starships = \"list\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `height` is of type: integer\n col_is_integer(\n columns = c(\"height\")\n ) %>%\n # Expect that values in `height` should be between `66` and `264`\n col_vals_between(\n columns = c(\"height\"),\n left = 66,\n right = 264,\n na_pass = TRUE\n ) %>%\n # Expect that column `mass` is of type: numeric\n col_is_numeric(\n columns = c(\"mass\")\n ) %>%\n # Expect that values in `mass` should be between `15` and `1358`\n col_vals_between(\n columns = c(\"mass\"),\n left = 15,\n right = 1358,\n na_pass = TRUE\n ) %>%\n # Expect that column `hair_color` is of type: character\n col_is_character(\n columns = c(\"hair_color\")\n ) %>%\n # Expect that column `skin_color` is of type: character\n col_is_character(\n columns = c(\"skin_color\")\n ) %>%\n # Expect that column `eye_color` is of type: character\n col_is_character(\n columns = c(\"eye_color\")\n ) %>%\n # Expect that column `birth_year` is of type: numeric\n col_is_numeric(\n columns = c(\"birth_year\")\n ) %>%\n # Expect that values in `birth_year` should be between `8` and `896`\n col_vals_between(\n columns = c(\"birth_year\"),\n left = 8,\n right = 896,\n na_pass = TRUE\n ) %>%\n # Expect that column `sex` is of type: character\n col_is_character(\n columns = c(\"sex\")\n ) %>%\n # Expect that column `gender` is of type: character\n col_is_character(\n columns = c(\"gender\")\n ) %>%\n # Expect that column `homeworld` is of type: character\n col_is_character(\n columns = c(\"homeworld\")\n ) %>%\n # Expect that column `species` is of type: character\n col_is_character(\n columns = c(\"species\")\n ) %>%\n # Expect entirely distinct rows across `name, height, mass, hair_color, skin_color, eye_color, birth_year, sex, gender, homeworld, species, films, vehicles, starships`\n rows_distinct(\n columns = c(\"name\", \"height\", \"mass\", \"hair_color\", \"skin_color\", \"eye_color\", \"birth_year\", \"sex\", \"gender\", \"homeworld\", \"species\", \"films\", \"vehicles\", \"starships\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n name = \"character\",\n height = \"integer\",\n mass = \"numeric\",\n hair_color = \"character\",\n skin_color = \"character\",\n eye_color = \"character\",\n birth_year = \"numeric\",\n sex = \"character\",\n gender = \"character\",\n homeworld = \"character\",\n species = \"character\",\n films = \"list\",\n vehicles = \"list\",\n starships = \"list\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `artist` is of type: character\n col_is_character(\n columns = c(\"artist\")\n ) %>%\n # Expect that column `track` is of type: character\n col_is_character(\n columns = c(\"track\")\n ) %>%\n # Expect that column `wk1` is of type: numeric\n col_is_numeric(\n columns = c(\"wk1\")\n ) %>%\n # Expect that values in `wk1` should be between `15` and `100`\n col_vals_between(\n columns = c(\"wk1\"),\n left = 15,\n right = 100\n ) %>%\n # Expect that column `wk2` is of type: numeric\n col_is_numeric(\n columns = c(\"wk2\")\n ) %>%\n # Expect that values in `wk2` should be between `8` and `100`\n col_vals_between(\n columns = c(\"wk2\"),\n left = 8,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk3` is of type: numeric\n col_is_numeric(\n columns = c(\"wk3\")\n ) %>%\n # Expect that values in `wk3` should be between `6` and `100`\n col_vals_between(\n columns = c(\"wk3\"),\n left = 6,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk4` is of type: numeric\n col_is_numeric(\n columns = c(\"wk4\")\n ) %>%\n # Expect that values in `wk4` should be between `5` and `100`\n col_vals_between(\n columns = c(\"wk4\"),\n left = 5,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk5` is of type: numeric\n col_is_numeric(\n columns = c(\"wk5\")\n ) %>%\n # Expect that values in `wk5` should be between `2` and `100`\n col_vals_between(\n columns = c(\"wk5\"),\n left = 2,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk6` is of type: numeric\n col_is_numeric(\n columns = c(\"wk6\")\n ) %>%\n # Expect that values in `wk6` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk6\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk7` is of type: numeric\n col_is_numeric(\n columns = c(\"wk7\")\n ) %>%\n # Expect that values in `wk7` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk7\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk8` is of type: numeric\n col_is_numeric(\n columns = c(\"wk8\")\n ) %>%\n # Expect that values in `wk8` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk8\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk9` is of type: numeric\n col_is_numeric(\n columns = c(\"wk9\")\n ) %>%\n # Expect that values in `wk9` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk9\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk10` is of type: numeric\n col_is_numeric(\n columns = c(\"wk10\")\n ) %>%\n # Expect that values in `wk10` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk10\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk11` is of type: numeric\n col_is_numeric(\n columns = c(\"wk11\")\n ) %>%\n # Expect that values in `wk11` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk11\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk12` is of type: numeric\n col_is_numeric(\n columns = c(\"wk12\")\n ) %>%\n # Expect that values in `wk12` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk12\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk13` is of type: numeric\n col_is_numeric(\n columns = c(\"wk13\")\n ) %>%\n # Expect that values in `wk13` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk13\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk14` is of type: numeric\n col_is_numeric(\n columns = c(\"wk14\")\n ) %>%\n # Expect that values in `wk14` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk14\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk15` is of type: numeric\n col_is_numeric(\n columns = c(\"wk15\")\n ) %>%\n # Expect that values in `wk15` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk15\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk16` is of type: numeric\n col_is_numeric(\n columns = c(\"wk16\")\n ) %>%\n # Expect that values in `wk16` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk16\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk17` is of type: numeric\n col_is_numeric(\n columns = c(\"wk17\")\n ) %>%\n # Expect that values in `wk17` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk17\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk18` is of type: numeric\n col_is_numeric(\n columns = c(\"wk18\")\n ) %>%\n # Expect that values in `wk18` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk18\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk19` is of type: numeric\n col_is_numeric(\n columns = c(\"wk19\")\n ) %>%\n # Expect that values in `wk19` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk19\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk20` is of type: numeric\n col_is_numeric(\n columns = c(\"wk20\")\n ) %>%\n # Expect that values in `wk20` should be between `2` and `100`\n col_vals_between(\n columns = c(\"wk20\"),\n left = 2,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk21` is of type: numeric\n col_is_numeric(\n columns = c(\"wk21\")\n ) %>%\n # Expect that values in `wk21` should be between `3` and `97`\n col_vals_between(\n columns = c(\"wk21\"),\n left = 3,\n right = 97,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk22` is of type: numeric\n col_is_numeric(\n columns = c(\"wk22\")\n ) %>%\n # Expect that values in `wk22` should be between `3` and `100`\n col_vals_between(\n columns = c(\"wk22\"),\n left = 3,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk23` is of type: numeric\n col_is_numeric(\n columns = c(\"wk23\")\n ) %>%\n # Expect that values in `wk23` should be between `3` and `91`\n col_vals_between(\n columns = c(\"wk23\"),\n left = 3,\n right = 91,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk24` is of type: numeric\n col_is_numeric(\n columns = c(\"wk24\")\n ) %>%\n # Expect that values in `wk24` should be between `3` and `91`\n col_vals_between(\n columns = c(\"wk24\"),\n left = 3,\n right = 91,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk25` is of type: numeric\n col_is_numeric(\n columns = c(\"wk25\")\n ) %>%\n # Expect that values in `wk25` should be between `2` and `90`\n col_vals_between(\n columns = c(\"wk25\"),\n left = 2,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk26` is of type: numeric\n col_is_numeric(\n columns = c(\"wk26\")\n ) %>%\n # Expect that values in `wk26` should be between `1` and `89`\n col_vals_between(\n columns = c(\"wk26\"),\n left = 1,\n right = 89,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk27` is of type: numeric\n col_is_numeric(\n columns = c(\"wk27\")\n ) %>%\n # Expect that values in `wk27` should be between `1` and `86`\n col_vals_between(\n columns = c(\"wk27\"),\n left = 1,\n right = 86,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk28` is of type: numeric\n col_is_numeric(\n columns = c(\"wk28\")\n ) %>%\n # Expect that values in `wk28` should be between `2` and `58`\n col_vals_between(\n columns = c(\"wk28\"),\n left = 2,\n right = 58,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk29` is of type: numeric\n col_is_numeric(\n columns = c(\"wk29\")\n ) %>%\n # Expect that values in `wk29` should be between `2` and `49`\n col_vals_between(\n columns = c(\"wk29\"),\n left = 2,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk30` is of type: numeric\n col_is_numeric(\n columns = c(\"wk30\")\n ) %>%\n # Expect that values in `wk30` should be between `2` and `45`\n col_vals_between(\n columns = c(\"wk30\"),\n left = 2,\n right = 45,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk31` is of type: numeric\n col_is_numeric(\n columns = c(\"wk31\")\n ) %>%\n # Expect that values in `wk31` should be between `3` and `49`\n col_vals_between(\n columns = c(\"wk31\"),\n left = 3,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk32` is of type: numeric\n col_is_numeric(\n columns = c(\"wk32\")\n ) %>%\n # Expect that values in `wk32` should be between `3` and `47`\n col_vals_between(\n columns = c(\"wk32\"),\n left = 3,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk33` is of type: numeric\n col_is_numeric(\n columns = c(\"wk33\")\n ) %>%\n # Expect that values in `wk33` should be between `2` and `50`\n col_vals_between(\n columns = c(\"wk33\"),\n left = 2,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk34` is of type: numeric\n col_is_numeric(\n columns = c(\"wk34\")\n ) %>%\n # Expect that values in `wk34` should be between `3` and `49`\n col_vals_between(\n columns = c(\"wk34\"),\n left = 3,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk35` is of type: numeric\n col_is_numeric(\n columns = c(\"wk35\")\n ) %>%\n # Expect that values in `wk35` should be between `4` and `34`\n col_vals_between(\n columns = c(\"wk35\"),\n left = 4,\n right = 34,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk36` is of type: numeric\n col_is_numeric(\n columns = c(\"wk36\")\n ) %>%\n # Expect that values in `wk36` should be between `5` and `41`\n col_vals_between(\n columns = c(\"wk36\"),\n left = 5,\n right = 41,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk37` is of type: numeric\n col_is_numeric(\n columns = c(\"wk37\")\n ) %>%\n # Expect that values in `wk37` should be between `5` and `48`\n col_vals_between(\n columns = c(\"wk37\"),\n left = 5,\n right = 48,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk38` is of type: numeric\n col_is_numeric(\n columns = c(\"wk38\")\n ) %>%\n # Expect that values in `wk38` should be between `9` and `40`\n col_vals_between(\n columns = c(\"wk38\"),\n left = 9,\n right = 40,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk39` is of type: numeric\n col_is_numeric(\n columns = c(\"wk39\")\n ) %>%\n # Expect that values in `wk39` should be between `3` and `50`\n col_vals_between(\n columns = c(\"wk39\"),\n left = 3,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk40` is of type: numeric\n col_is_numeric(\n columns = c(\"wk40\")\n ) %>%\n # Expect that values in `wk40` should be between `1` and `47`\n col_vals_between(\n columns = c(\"wk40\"),\n left = 1,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk41` is of type: numeric\n col_is_numeric(\n columns = c(\"wk41\")\n ) %>%\n # Expect that values in `wk41` should be between `1` and `50`\n col_vals_between(\n columns = c(\"wk41\"),\n left = 1,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk42` is of type: numeric\n col_is_numeric(\n columns = c(\"wk42\")\n ) %>%\n # Expect that values in `wk42` should be between `2` and `22`\n col_vals_between(\n columns = c(\"wk42\"),\n left = 2,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk43` is of type: numeric\n col_is_numeric(\n columns = c(\"wk43\")\n ) %>%\n # Expect that values in `wk43` should be between `3` and `32`\n col_vals_between(\n columns = c(\"wk43\"),\n left = 3,\n right = 32,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk44` is of type: numeric\n col_is_numeric(\n columns = c(\"wk44\")\n ) %>%\n # Expect that values in `wk44` should be between `4` and `45`\n col_vals_between(\n columns = c(\"wk44\"),\n left = 4,\n right = 45,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk45` is of type: numeric\n col_is_numeric(\n columns = c(\"wk45\")\n ) %>%\n # Expect that values in `wk45` should be between `4` and `31`\n col_vals_between(\n columns = c(\"wk45\"),\n left = 4,\n right = 31,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk46` is of type: numeric\n col_is_numeric(\n columns = c(\"wk46\")\n ) %>%\n # Expect that values in `wk46` should be between `5` and `37`\n col_vals_between(\n columns = c(\"wk46\"),\n left = 5,\n right = 37,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk47` is of type: numeric\n col_is_numeric(\n columns = c(\"wk47\")\n ) %>%\n # Expect that values in `wk47` should be between `6` and `41`\n col_vals_between(\n columns = c(\"wk47\"),\n left = 6,\n right = 41,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk48` is of type: numeric\n col_is_numeric(\n columns = c(\"wk48\")\n ) %>%\n # Expect that values in `wk48` should be between `8` and `39`\n col_vals_between(\n columns = c(\"wk48\"),\n left = 8,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk49` is of type: numeric\n col_is_numeric(\n columns = c(\"wk49\")\n ) %>%\n # Expect that values in `wk49` should be between `9` and `42`\n col_vals_between(\n columns = c(\"wk49\"),\n left = 9,\n right = 42,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk50` is of type: numeric\n col_is_numeric(\n columns = c(\"wk50\")\n ) %>%\n # Expect that values in `wk50` should be between `10` and `49`\n col_vals_between(\n columns = c(\"wk50\"),\n left = 10,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk51` is of type: numeric\n col_is_numeric(\n columns = c(\"wk51\")\n ) %>%\n # Expect that values in `wk51` should be between `12` and `49`\n col_vals_between(\n columns = c(\"wk51\"),\n left = 12,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk52` is of type: numeric\n col_is_numeric(\n columns = c(\"wk52\")\n ) %>%\n # Expect that values in `wk52` should be between `15` and `48`\n col_vals_between(\n columns = c(\"wk52\"),\n left = 15,\n right = 48,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk53` is of type: numeric\n col_is_numeric(\n columns = c(\"wk53\")\n ) %>%\n # Expect that values in `wk53` should be between `17` and `49`\n col_vals_between(\n columns = c(\"wk53\"),\n left = 17,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk54` is of type: numeric\n col_is_numeric(\n columns = c(\"wk54\")\n ) %>%\n # Expect that values in `wk54` should be between `17` and `22`\n col_vals_between(\n columns = c(\"wk54\"),\n left = 17,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk55` is of type: numeric\n col_is_numeric(\n columns = c(\"wk55\")\n ) %>%\n # Expect that values in `wk55` should be between `21` and `22`\n col_vals_between(\n columns = c(\"wk55\"),\n left = 21,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk56` is of type: numeric\n col_is_numeric(\n columns = c(\"wk56\")\n ) %>%\n # Expect that values in `wk56` should be between `25` and `26`\n col_vals_between(\n columns = c(\"wk56\"),\n left = 25,\n right = 26,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk57` is of type: numeric\n col_is_numeric(\n columns = c(\"wk57\")\n ) %>%\n # Expect that values in `wk57` should be between `26` and `29`\n col_vals_between(\n columns = c(\"wk57\"),\n left = 26,\n right = 29,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk58` is of type: numeric\n col_is_numeric(\n columns = c(\"wk58\")\n ) %>%\n # Expect that values in `wk58` should be between `31` and `32`\n col_vals_between(\n columns = c(\"wk58\"),\n left = 31,\n right = 32,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk59` is of type: numeric\n col_is_numeric(\n columns = c(\"wk59\")\n ) %>%\n # Expect that values in `wk59` should be between `32` and `39`\n col_vals_between(\n columns = c(\"wk59\"),\n left = 32,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk60` is of type: numeric\n col_is_numeric(\n columns = c(\"wk60\")\n ) %>%\n # Expect that values in `wk60` should be between `37` and `39`\n col_vals_between(\n columns = c(\"wk60\"),\n left = 37,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk61` is of type: numeric\n col_is_numeric(\n columns = c(\"wk61\")\n ) %>%\n # Expect that values in `wk61` should be between `42` and `43`\n col_vals_between(\n columns = c(\"wk61\"),\n left = 42,\n right = 43,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk62` is of type: numeric\n col_is_numeric(\n columns = c(\"wk62\")\n ) %>%\n # Expect that values in `wk62` should be between `42` and `47`\n col_vals_between(\n columns = c(\"wk62\"),\n left = 42,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk63` is of type: numeric\n col_is_numeric(\n columns = c(\"wk63\")\n ) %>%\n # Expect that values in `wk63` should be between `45` and `50`\n col_vals_between(\n columns = c(\"wk63\"),\n left = 45,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk64` is of type: numeric\n col_is_numeric(\n columns = c(\"wk64\")\n ) %>%\n # Expect that values in `wk64` should be between `50` and `50`\n col_vals_between(\n columns = c(\"wk64\"),\n left = 50,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk65` is of type: numeric\n col_is_numeric(\n columns = c(\"wk65\")\n ) %>%\n # Expect that values in `wk65` should be between `49` and `49`\n col_vals_between(\n columns = c(\"wk65\"),\n left = 49,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk66` is of type: logical\n col_is_logical(\n columns = c(\"wk66\")\n ) %>%\n # Expect that column `wk67` is of type: logical\n col_is_logical(\n columns = c(\"wk67\")\n ) %>%\n # Expect that column `wk68` is of type: logical\n col_is_logical(\n columns = c(\"wk68\")\n ) %>%\n # Expect that column `wk69` is of type: logical\n col_is_logical(\n columns = c(\"wk69\")\n ) %>%\n # Expect that column `wk70` is of type: logical\n col_is_logical(\n columns = c(\"wk70\")\n ) %>%\n # Expect that column `wk71` is of type: logical\n col_is_logical(\n columns = c(\"wk71\")\n ) %>%\n # Expect that column `wk72` is of type: logical\n col_is_logical(\n columns = c(\"wk72\")\n ) %>%\n # Expect that column `wk73` is of type: logical\n col_is_logical(\n columns = c(\"wk73\")\n ) %>%\n # Expect that column `wk74` is of type: logical\n col_is_logical(\n columns = c(\"wk74\")\n ) %>%\n # Expect that column `wk75` is of type: logical\n col_is_logical(\n columns = c(\"wk75\")\n ) %>%\n # Expect that column `wk76` is of type: logical\n col_is_logical(\n columns = c(\"wk76\")\n ) %>%\n # Expect entirely distinct rows across `artist, track, date.entered, wk1, wk2, wk3, wk4, wk5, wk6, wk7, wk8, wk9, wk10, wk11, wk12, wk13, wk14, wk15, wk16, wk17, wk18, wk19, wk20, wk21, wk22, wk23, wk24, wk25, wk26, wk27, wk28, wk29, wk30, wk31, wk32, wk33, wk34, wk35, wk36, wk37, wk38, wk39, wk40, wk41, wk42, wk43, wk44, wk45, wk46, wk47, wk48, wk49, wk50, wk51, wk52, wk53, wk54, wk55, wk56, wk57, wk58, wk59, wk60, wk61, wk62, wk63, wk64, wk65, wk66, wk67, wk68, wk69, wk70, wk71, wk72, wk73, wk74, wk75, wk76`\n rows_distinct(\n columns = c(\"artist\", \"track\", \"date.entered\", \"wk1\", \"wk2\", \"wk3\", \"wk4\", \"wk5\", \"wk6\", \"wk7\", \"wk8\", \"wk9\", \"wk10\", \"wk11\", \"wk12\", \"wk13\", \"wk14\", \"wk15\", \"wk16\", \"wk17\", \"wk18\", \"wk19\", \"wk20\", \"wk21\", \"wk22\", \"wk23\", \"wk24\", \"wk25\", \"wk26\", \"wk27\", \"wk28\", \"wk29\", \"wk30\", \"wk31\", \"wk32\", \"wk33\", \"wk34\", \"wk35\", \"wk36\", \"wk37\", \"wk38\", \"wk39\", \"wk40\", \"wk41\", \"wk42\", \"wk43\", \"wk44\", \"wk45\", \"wk46\", \"wk47\", \"wk48\", \"wk49\", \"wk50\", \"wk51\", \"wk52\", \"wk53\", \"wk54\", \"wk55\", \"wk56\", \"wk57\", \"wk58\", \"wk59\", \"wk60\", \"wk61\", \"wk62\", \"wk63\", \"wk64\", \"wk65\", \"wk66\", \"wk67\", \"wk68\", \"wk69\", \"wk70\", \"wk71\", \"wk72\", \"wk73\", \"wk74\", \"wk75\", \"wk76\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n artist = \"character\",\n track = \"character\",\n date.entered = \"Date\",\n wk1 = \"numeric\",\n wk2 = \"numeric\",\n wk3 = \"numeric\",\n wk4 = \"numeric\",\n wk5 = \"numeric\",\n wk6 = \"numeric\",\n wk7 = \"numeric\",\n wk8 = \"numeric\",\n wk9 = \"numeric\",\n wk10 = \"numeric\",\n wk11 = \"numeric\",\n wk12 = \"numeric\",\n wk13 = \"numeric\",\n wk14 = \"numeric\",\n wk15 = \"numeric\",\n wk16 = \"numeric\",\n wk17 = \"numeric\",\n wk18 = \"numeric\",\n wk19 = \"numeric\",\n wk20 = \"numeric\",\n wk21 = \"numeric\",\n wk22 = \"numeric\",\n wk23 = \"numeric\",\n wk24 = \"numeric\",\n wk25 = \"numeric\",\n wk26 = \"numeric\",\n wk27 = \"numeric\",\n wk28 = \"numeric\",\n wk29 = \"numeric\",\n wk30 = \"numeric\",\n wk31 = \"numeric\",\n wk32 = \"numeric\",\n wk33 = \"numeric\",\n wk34 = \"numeric\",\n wk35 = \"numeric\",\n wk36 = \"numeric\",\n wk37 = \"numeric\",\n wk38 = \"numeric\",\n wk39 = \"numeric\",\n wk40 = \"numeric\",\n wk41 = \"numeric\",\n wk42 = \"numeric\",\n wk43 = \"numeric\",\n wk44 = \"numeric\",\n wk45 = \"numeric\",\n wk46 = \"numeric\",\n wk47 = \"numeric\",\n wk48 = \"numeric\",\n wk49 = \"numeric\",\n wk50 = \"numeric\",\n wk51 = \"numeric\",\n wk52 = \"numeric\",\n wk53 = \"numeric\",\n wk54 = \"numeric\",\n wk55 = \"numeric\",\n wk56 = \"numeric\",\n wk57 = \"numeric\",\n wk58 = \"numeric\",\n wk59 = \"numeric\",\n wk60 = \"numeric\",\n wk61 = \"numeric\",\n wk62 = \"numeric\",\n wk63 = \"numeric\",\n wk64 = \"numeric\",\n wk65 = \"numeric\",\n wk66 = \"logical\",\n wk67 = \"logical\",\n wk68 = \"logical\",\n wk69 = \"logical\",\n wk70 = \"logical\",\n wk71 = \"logical\",\n wk72 = \"logical\",\n wk73 = \"logical\",\n wk74 = \"logical\",\n wk75 = \"logical\",\n wk76 = \"logical\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `artist` is of type: character\n col_is_character(\n columns = c(\"artist\")\n ) %>%\n # Expect that column `track` is of type: character\n col_is_character(\n columns = c(\"track\")\n ) %>%\n # Expect that column `wk1` is of type: numeric\n col_is_numeric(\n columns = c(\"wk1\")\n ) %>%\n # Expect that values in `wk1` should be between `15` and `100`\n col_vals_between(\n columns = c(\"wk1\"),\n left = 15,\n right = 100\n ) %>%\n # Expect that column `wk2` is of type: numeric\n col_is_numeric(\n columns = c(\"wk2\")\n ) %>%\n # Expect that values in `wk2` should be between `8` and `100`\n col_vals_between(\n columns = c(\"wk2\"),\n left = 8,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk3` is of type: numeric\n col_is_numeric(\n columns = c(\"wk3\")\n ) %>%\n # Expect that values in `wk3` should be between `6` and `100`\n col_vals_between(\n columns = c(\"wk3\"),\n left = 6,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk4` is of type: numeric\n col_is_numeric(\n columns = c(\"wk4\")\n ) %>%\n # Expect that values in `wk4` should be between `5` and `100`\n col_vals_between(\n columns = c(\"wk4\"),\n left = 5,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk5` is of type: numeric\n col_is_numeric(\n columns = c(\"wk5\")\n ) %>%\n # Expect that values in `wk5` should be between `2` and `100`\n col_vals_between(\n columns = c(\"wk5\"),\n left = 2,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk6` is of type: numeric\n col_is_numeric(\n columns = c(\"wk6\")\n ) %>%\n # Expect that values in `wk6` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk6\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk7` is of type: numeric\n col_is_numeric(\n columns = c(\"wk7\")\n ) %>%\n # Expect that values in `wk7` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk7\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk8` is of type: numeric\n col_is_numeric(\n columns = c(\"wk8\")\n ) %>%\n # Expect that values in `wk8` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk8\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk9` is of type: numeric\n col_is_numeric(\n columns = c(\"wk9\")\n ) %>%\n # Expect that values in `wk9` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk9\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk10` is of type: numeric\n col_is_numeric(\n columns = c(\"wk10\")\n ) %>%\n # Expect that values in `wk10` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk10\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk11` is of type: numeric\n col_is_numeric(\n columns = c(\"wk11\")\n ) %>%\n # Expect that values in `wk11` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk11\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk12` is of type: numeric\n col_is_numeric(\n columns = c(\"wk12\")\n ) %>%\n # Expect that values in `wk12` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk12\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk13` is of type: numeric\n col_is_numeric(\n columns = c(\"wk13\")\n ) %>%\n # Expect that values in `wk13` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk13\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk14` is of type: numeric\n col_is_numeric(\n columns = c(\"wk14\")\n ) %>%\n # Expect that values in `wk14` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk14\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk15` is of type: numeric\n col_is_numeric(\n columns = c(\"wk15\")\n ) %>%\n # Expect that values in `wk15` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk15\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk16` is of type: numeric\n col_is_numeric(\n columns = c(\"wk16\")\n ) %>%\n # Expect that values in `wk16` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk16\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk17` is of type: numeric\n col_is_numeric(\n columns = c(\"wk17\")\n ) %>%\n # Expect that values in `wk17` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk17\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk18` is of type: numeric\n col_is_numeric(\n columns = c(\"wk18\")\n ) %>%\n # Expect that values in `wk18` should be between `1` and `100`\n col_vals_between(\n columns = c(\"wk18\"),\n left = 1,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk19` is of type: numeric\n col_is_numeric(\n columns = c(\"wk19\")\n ) %>%\n # Expect that values in `wk19` should be between `1` and `99`\n col_vals_between(\n columns = c(\"wk19\"),\n left = 1,\n right = 99,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk20` is of type: numeric\n col_is_numeric(\n columns = c(\"wk20\")\n ) %>%\n # Expect that values in `wk20` should be between `2` and `100`\n col_vals_between(\n columns = c(\"wk20\"),\n left = 2,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk21` is of type: numeric\n col_is_numeric(\n columns = c(\"wk21\")\n ) %>%\n # Expect that values in `wk21` should be between `3` and `97`\n col_vals_between(\n columns = c(\"wk21\"),\n left = 3,\n right = 97,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk22` is of type: numeric\n col_is_numeric(\n columns = c(\"wk22\")\n ) %>%\n # Expect that values in `wk22` should be between `3` and `100`\n col_vals_between(\n columns = c(\"wk22\"),\n left = 3,\n right = 100,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk23` is of type: numeric\n col_is_numeric(\n columns = c(\"wk23\")\n ) %>%\n # Expect that values in `wk23` should be between `3` and `91`\n col_vals_between(\n columns = c(\"wk23\"),\n left = 3,\n right = 91,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk24` is of type: numeric\n col_is_numeric(\n columns = c(\"wk24\")\n ) %>%\n # Expect that values in `wk24` should be between `3` and `91`\n col_vals_between(\n columns = c(\"wk24\"),\n left = 3,\n right = 91,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk25` is of type: numeric\n col_is_numeric(\n columns = c(\"wk25\")\n ) %>%\n # Expect that values in `wk25` should be between `2` and `90`\n col_vals_between(\n columns = c(\"wk25\"),\n left = 2,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk26` is of type: numeric\n col_is_numeric(\n columns = c(\"wk26\")\n ) %>%\n # Expect that values in `wk26` should be between `1` and `89`\n col_vals_between(\n columns = c(\"wk26\"),\n left = 1,\n right = 89,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk27` is of type: numeric\n col_is_numeric(\n columns = c(\"wk27\")\n ) %>%\n # Expect that values in `wk27` should be between `1` and `86`\n col_vals_between(\n columns = c(\"wk27\"),\n left = 1,\n right = 86,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk28` is of type: numeric\n col_is_numeric(\n columns = c(\"wk28\")\n ) %>%\n # Expect that values in `wk28` should be between `2` and `58`\n col_vals_between(\n columns = c(\"wk28\"),\n left = 2,\n right = 58,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk29` is of type: numeric\n col_is_numeric(\n columns = c(\"wk29\")\n ) %>%\n # Expect that values in `wk29` should be between `2` and `49`\n col_vals_between(\n columns = c(\"wk29\"),\n left = 2,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk30` is of type: numeric\n col_is_numeric(\n columns = c(\"wk30\")\n ) %>%\n # Expect that values in `wk30` should be between `2` and `45`\n col_vals_between(\n columns = c(\"wk30\"),\n left = 2,\n right = 45,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk31` is of type: numeric\n col_is_numeric(\n columns = c(\"wk31\")\n ) %>%\n # Expect that values in `wk31` should be between `3` and `49`\n col_vals_between(\n columns = c(\"wk31\"),\n left = 3,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk32` is of type: numeric\n col_is_numeric(\n columns = c(\"wk32\")\n ) %>%\n # Expect that values in `wk32` should be between `3` and `47`\n col_vals_between(\n columns = c(\"wk32\"),\n left = 3,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk33` is of type: numeric\n col_is_numeric(\n columns = c(\"wk33\")\n ) %>%\n # Expect that values in `wk33` should be between `2` and `50`\n col_vals_between(\n columns = c(\"wk33\"),\n left = 2,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk34` is of type: numeric\n col_is_numeric(\n columns = c(\"wk34\")\n ) %>%\n # Expect that values in `wk34` should be between `3` and `49`\n col_vals_between(\n columns = c(\"wk34\"),\n left = 3,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk35` is of type: numeric\n col_is_numeric(\n columns = c(\"wk35\")\n ) %>%\n # Expect that values in `wk35` should be between `4` and `34`\n col_vals_between(\n columns = c(\"wk35\"),\n left = 4,\n right = 34,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk36` is of type: numeric\n col_is_numeric(\n columns = c(\"wk36\")\n ) %>%\n # Expect that values in `wk36` should be between `5` and `41`\n col_vals_between(\n columns = c(\"wk36\"),\n left = 5,\n right = 41,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk37` is of type: numeric\n col_is_numeric(\n columns = c(\"wk37\")\n ) %>%\n # Expect that values in `wk37` should be between `5` and `48`\n col_vals_between(\n columns = c(\"wk37\"),\n left = 5,\n right = 48,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk38` is of type: numeric\n col_is_numeric(\n columns = c(\"wk38\")\n ) %>%\n # Expect that values in `wk38` should be between `9` and `40`\n col_vals_between(\n columns = c(\"wk38\"),\n left = 9,\n right = 40,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk39` is of type: numeric\n col_is_numeric(\n columns = c(\"wk39\")\n ) %>%\n # Expect that values in `wk39` should be between `3` and `50`\n col_vals_between(\n columns = c(\"wk39\"),\n left = 3,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk40` is of type: numeric\n col_is_numeric(\n columns = c(\"wk40\")\n ) %>%\n # Expect that values in `wk40` should be between `1` and `47`\n col_vals_between(\n columns = c(\"wk40\"),\n left = 1,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk41` is of type: numeric\n col_is_numeric(\n columns = c(\"wk41\")\n ) %>%\n # Expect that values in `wk41` should be between `1` and `50`\n col_vals_between(\n columns = c(\"wk41\"),\n left = 1,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk42` is of type: numeric\n col_is_numeric(\n columns = c(\"wk42\")\n ) %>%\n # Expect that values in `wk42` should be between `2` and `22`\n col_vals_between(\n columns = c(\"wk42\"),\n left = 2,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk43` is of type: numeric\n col_is_numeric(\n columns = c(\"wk43\")\n ) %>%\n # Expect that values in `wk43` should be between `3` and `32`\n col_vals_between(\n columns = c(\"wk43\"),\n left = 3,\n right = 32,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk44` is of type: numeric\n col_is_numeric(\n columns = c(\"wk44\")\n ) %>%\n # Expect that values in `wk44` should be between `4` and `45`\n col_vals_between(\n columns = c(\"wk44\"),\n left = 4,\n right = 45,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk45` is of type: numeric\n col_is_numeric(\n columns = c(\"wk45\")\n ) %>%\n # Expect that values in `wk45` should be between `4` and `31`\n col_vals_between(\n columns = c(\"wk45\"),\n left = 4,\n right = 31,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk46` is of type: numeric\n col_is_numeric(\n columns = c(\"wk46\")\n ) %>%\n # Expect that values in `wk46` should be between `5` and `37`\n col_vals_between(\n columns = c(\"wk46\"),\n left = 5,\n right = 37,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk47` is of type: numeric\n col_is_numeric(\n columns = c(\"wk47\")\n ) %>%\n # Expect that values in `wk47` should be between `6` and `41`\n col_vals_between(\n columns = c(\"wk47\"),\n left = 6,\n right = 41,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk48` is of type: numeric\n col_is_numeric(\n columns = c(\"wk48\")\n ) %>%\n # Expect that values in `wk48` should be between `8` and `39`\n col_vals_between(\n columns = c(\"wk48\"),\n left = 8,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk49` is of type: numeric\n col_is_numeric(\n columns = c(\"wk49\")\n ) %>%\n # Expect that values in `wk49` should be between `9` and `42`\n col_vals_between(\n columns = c(\"wk49\"),\n left = 9,\n right = 42,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk50` is of type: numeric\n col_is_numeric(\n columns = c(\"wk50\")\n ) %>%\n # Expect that values in `wk50` should be between `10` and `49`\n col_vals_between(\n columns = c(\"wk50\"),\n left = 10,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk51` is of type: numeric\n col_is_numeric(\n columns = c(\"wk51\")\n ) %>%\n # Expect that values in `wk51` should be between `12` and `49`\n col_vals_between(\n columns = c(\"wk51\"),\n left = 12,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk52` is of type: numeric\n col_is_numeric(\n columns = c(\"wk52\")\n ) %>%\n # Expect that values in `wk52` should be between `15` and `48`\n col_vals_between(\n columns = c(\"wk52\"),\n left = 15,\n right = 48,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk53` is of type: numeric\n col_is_numeric(\n columns = c(\"wk53\")\n ) %>%\n # Expect that values in `wk53` should be between `17` and `49`\n col_vals_between(\n columns = c(\"wk53\"),\n left = 17,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk54` is of type: numeric\n col_is_numeric(\n columns = c(\"wk54\")\n ) %>%\n # Expect that values in `wk54` should be between `17` and `22`\n col_vals_between(\n columns = c(\"wk54\"),\n left = 17,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk55` is of type: numeric\n col_is_numeric(\n columns = c(\"wk55\")\n ) %>%\n # Expect that values in `wk55` should be between `21` and `22`\n col_vals_between(\n columns = c(\"wk55\"),\n left = 21,\n right = 22,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk56` is of type: numeric\n col_is_numeric(\n columns = c(\"wk56\")\n ) %>%\n # Expect that values in `wk56` should be between `25` and `26`\n col_vals_between(\n columns = c(\"wk56\"),\n left = 25,\n right = 26,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk57` is of type: numeric\n col_is_numeric(\n columns = c(\"wk57\")\n ) %>%\n # Expect that values in `wk57` should be between `26` and `29`\n col_vals_between(\n columns = c(\"wk57\"),\n left = 26,\n right = 29,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk58` is of type: numeric\n col_is_numeric(\n columns = c(\"wk58\")\n ) %>%\n # Expect that values in `wk58` should be between `31` and `32`\n col_vals_between(\n columns = c(\"wk58\"),\n left = 31,\n right = 32,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk59` is of type: numeric\n col_is_numeric(\n columns = c(\"wk59\")\n ) %>%\n # Expect that values in `wk59` should be between `32` and `39`\n col_vals_between(\n columns = c(\"wk59\"),\n left = 32,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk60` is of type: numeric\n col_is_numeric(\n columns = c(\"wk60\")\n ) %>%\n # Expect that values in `wk60` should be between `37` and `39`\n col_vals_between(\n columns = c(\"wk60\"),\n left = 37,\n right = 39,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk61` is of type: numeric\n col_is_numeric(\n columns = c(\"wk61\")\n ) %>%\n # Expect that values in `wk61` should be between `42` and `43`\n col_vals_between(\n columns = c(\"wk61\"),\n left = 42,\n right = 43,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk62` is of type: numeric\n col_is_numeric(\n columns = c(\"wk62\")\n ) %>%\n # Expect that values in `wk62` should be between `42` and `47`\n col_vals_between(\n columns = c(\"wk62\"),\n left = 42,\n right = 47,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk63` is of type: numeric\n col_is_numeric(\n columns = c(\"wk63\")\n ) %>%\n # Expect that values in `wk63` should be between `45` and `50`\n col_vals_between(\n columns = c(\"wk63\"),\n left = 45,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk64` is of type: numeric\n col_is_numeric(\n columns = c(\"wk64\")\n ) %>%\n # Expect that values in `wk64` should be between `50` and `50`\n col_vals_between(\n columns = c(\"wk64\"),\n left = 50,\n right = 50,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk65` is of type: numeric\n col_is_numeric(\n columns = c(\"wk65\")\n ) %>%\n # Expect that values in `wk65` should be between `49` and `49`\n col_vals_between(\n columns = c(\"wk65\"),\n left = 49,\n right = 49,\n na_pass = TRUE\n ) %>%\n # Expect that column `wk66` is of type: logical\n col_is_logical(\n columns = c(\"wk66\")\n ) %>%\n # Expect that column `wk67` is of type: logical\n col_is_logical(\n columns = c(\"wk67\")\n ) %>%\n # Expect that column `wk68` is of type: logical\n col_is_logical(\n columns = c(\"wk68\")\n ) %>%\n # Expect that column `wk69` is of type: logical\n col_is_logical(\n columns = c(\"wk69\")\n ) %>%\n # Expect that column `wk70` is of type: logical\n col_is_logical(\n columns = c(\"wk70\")\n ) %>%\n # Expect that column `wk71` is of type: logical\n col_is_logical(\n columns = c(\"wk71\")\n ) %>%\n # Expect that column `wk72` is of type: logical\n col_is_logical(\n columns = c(\"wk72\")\n ) %>%\n # Expect that column `wk73` is of type: logical\n col_is_logical(\n columns = c(\"wk73\")\n ) %>%\n # Expect that column `wk74` is of type: logical\n col_is_logical(\n columns = c(\"wk74\")\n ) %>%\n # Expect that column `wk75` is of type: logical\n col_is_logical(\n columns = c(\"wk75\")\n ) %>%\n # Expect that column `wk76` is of type: logical\n col_is_logical(\n columns = c(\"wk76\")\n ) %>%\n # Expect entirely distinct rows across `artist, track, date.entered, wk1, wk2, wk3, wk4, wk5, wk6, wk7, wk8, wk9, wk10, wk11, wk12, wk13, wk14, wk15, wk16, wk17, wk18, wk19, wk20, wk21, wk22, wk23, wk24, wk25, wk26, wk27, wk28, wk29, wk30, wk31, wk32, wk33, wk34, wk35, wk36, wk37, wk38, wk39, wk40, wk41, wk42, wk43, wk44, wk45, wk46, wk47, wk48, wk49, wk50, wk51, wk52, wk53, wk54, wk55, wk56, wk57, wk58, wk59, wk60, wk61, wk62, wk63, wk64, wk65, wk66, wk67, wk68, wk69, wk70, wk71, wk72, wk73, wk74, wk75, wk76`\n rows_distinct(\n columns = c(\"artist\", \"track\", \"date.entered\", \"wk1\", \"wk2\", \"wk3\", \"wk4\", \"wk5\", \"wk6\", \"wk7\", \"wk8\", \"wk9\", \"wk10\", \"wk11\", \"wk12\", \"wk13\", \"wk14\", \"wk15\", \"wk16\", \"wk17\", \"wk18\", \"wk19\", \"wk20\", \"wk21\", \"wk22\", \"wk23\", \"wk24\", \"wk25\", \"wk26\", \"wk27\", \"wk28\", \"wk29\", \"wk30\", \"wk31\", \"wk32\", \"wk33\", \"wk34\", \"wk35\", \"wk36\", \"wk37\", \"wk38\", \"wk39\", \"wk40\", \"wk41\", \"wk42\", \"wk43\", \"wk44\", \"wk45\", \"wk46\", \"wk47\", \"wk48\", \"wk49\", \"wk50\", \"wk51\", \"wk52\", \"wk53\", \"wk54\", \"wk55\", \"wk56\", \"wk57\", \"wk58\", \"wk59\", \"wk60\", \"wk61\", \"wk62\", \"wk63\", \"wk64\", \"wk65\", \"wk66\", \"wk67\", \"wk68\", \"wk69\", \"wk70\", \"wk71\", \"wk72\", \"wk73\", \"wk74\", \"wk75\", \"wk76\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n artist = \"character\",\n track = \"character\",\n date.entered = \"Date\",\n wk1 = \"numeric\",\n wk2 = \"numeric\",\n wk3 = \"numeric\",\n wk4 = \"numeric\",\n wk5 = \"numeric\",\n wk6 = \"numeric\",\n wk7 = \"numeric\",\n wk8 = \"numeric\",\n wk9 = \"numeric\",\n wk10 = \"numeric\",\n wk11 = \"numeric\",\n wk12 = \"numeric\",\n wk13 = \"numeric\",\n wk14 = \"numeric\",\n wk15 = \"numeric\",\n wk16 = \"numeric\",\n wk17 = \"numeric\",\n wk18 = \"numeric\",\n wk19 = \"numeric\",\n wk20 = \"numeric\",\n wk21 = \"numeric\",\n wk22 = \"numeric\",\n wk23 = \"numeric\",\n wk24 = \"numeric\",\n wk25 = \"numeric\",\n wk26 = \"numeric\",\n wk27 = \"numeric\",\n wk28 = \"numeric\",\n wk29 = \"numeric\",\n wk30 = \"numeric\",\n wk31 = \"numeric\",\n wk32 = \"numeric\",\n wk33 = \"numeric\",\n wk34 = \"numeric\",\n wk35 = \"numeric\",\n wk36 = \"numeric\",\n wk37 = \"numeric\",\n wk38 = \"numeric\",\n wk39 = \"numeric\",\n wk40 = \"numeric\",\n wk41 = \"numeric\",\n wk42 = \"numeric\",\n wk43 = \"numeric\",\n wk44 = \"numeric\",\n wk45 = \"numeric\",\n wk46 = \"numeric\",\n wk47 = \"numeric\",\n wk48 = \"numeric\",\n wk49 = \"numeric\",\n wk50 = \"numeric\",\n wk51 = \"numeric\",\n wk52 = \"numeric\",\n wk53 = \"numeric\",\n wk54 = \"numeric\",\n wk55 = \"numeric\",\n wk56 = \"numeric\",\n wk57 = \"numeric\",\n wk58 = \"numeric\",\n wk59 = \"numeric\",\n wk60 = \"numeric\",\n wk61 = \"numeric\",\n wk62 = \"numeric\",\n wk63 = \"numeric\",\n wk64 = \"numeric\",\n wk65 = \"numeric\",\n wk66 = \"logical\",\n wk67 = \"logical\",\n wk68 = \"logical\",\n wk69 = \"logical\",\n wk70 = \"logical\",\n wk71 = \"logical\",\n wk72 = \"logical\",\n wk73 = \"logical\",\n wk74 = \"logical\",\n wk75 = \"logical\",\n wk76 = \"logical\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Year` is of type: numeric\n col_is_numeric(\n columns = c(\"Year\")\n ) %>%\n # Expect that values in `Year` should be between `2018` and `2018`\n col_vals_between(\n columns = c(\"Year\"),\n left = 2018,\n right = 2018\n ) %>%\n # Expect that column `Month` is of type: character\n col_is_character(\n columns = c(\"Month\")\n ) %>%\n # Expect that column `1 unit` is of type: numeric\n col_is_numeric(\n columns = c(\"1 unit\")\n ) %>%\n # Expect that values in `1 unit` should be between `797` and `939`\n col_vals_between(\n columns = c(\"1 unit\"),\n left = 797,\n right = 939\n ) %>%\n # Expect that column `2 to 4 units` is of type: logical\n col_is_logical(\n columns = c(\"2 to 4 units\")\n ) %>%\n # Expect that column `5 units or more` is of type: numeric\n col_is_numeric(\n columns = c(\"5 units or more\")\n ) %>%\n # Expect that values in `5 units or more` should be between `286` and `447`\n col_vals_between(\n columns = c(\"5 units or more\"),\n left = 286,\n right = 447\n ) %>%\n # Expect that column `Northeast` is of type: numeric\n col_is_numeric(\n columns = c(\"Northeast\")\n ) %>%\n # Expect that values in `Northeast` should be between `76` and `150`\n col_vals_between(\n columns = c(\"Northeast\"),\n left = 76,\n right = 150\n ) %>%\n # Expect that column `Midwest` is of type: numeric\n col_is_numeric(\n columns = c(\"Midwest\")\n ) %>%\n # Expect that values in `Midwest` should be between `154` and `205`\n col_vals_between(\n columns = c(\"Midwest\"),\n left = 154,\n right = 205\n ) %>%\n # Expect that column `South` is of type: numeric\n col_is_numeric(\n columns = c(\"South\")\n ) %>%\n # Expect that values in `South` should be between `560` and `673`\n col_vals_between(\n columns = c(\"South\"),\n left = 560,\n right = 673\n ) %>%\n # Expect that column `West` is of type: numeric\n col_is_numeric(\n columns = c(\"West\")\n ) %>%\n # Expect that values in `West` should be between `286` and `360`\n col_vals_between(\n columns = c(\"West\"),\n left = 286,\n right = 360\n ) %>%\n # Expect entirely distinct rows across `Year, Month, 1 unit, 2 to 4 units, 5 units or more, Northeast, Midwest, South, West`\n rows_distinct(\n columns = c(\"Year\", \"Month\", \"1 unit\", \"2 to 4 units\", \"5 units or more\", \"Northeast\", \"Midwest\", \"South\", \"West\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Year = \"numeric\",\n Month = \"character\",\n 1 unit = \"numeric\",\n 2 to 4 units = \"logical\",\n 5 units or more = \"numeric\",\n Northeast = \"numeric\",\n Midwest = \"numeric\",\n South = \"numeric\",\n West = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Year` is of type: numeric\n col_is_numeric(\n columns = c(\"Year\")\n ) %>%\n # Expect that values in `Year` should be between `2018` and `2018`\n col_vals_between(\n columns = c(\"Year\"),\n left = 2018,\n right = 2018\n ) %>%\n # Expect that column `Month` is of type: character\n col_is_character(\n columns = c(\"Month\")\n ) %>%\n # Expect that column `1 unit` is of type: numeric\n col_is_numeric(\n columns = c(\"1 unit\")\n ) %>%\n # Expect that values in `1 unit` should be between `797` and `939`\n col_vals_between(\n columns = c(\"1 unit\"),\n left = 797,\n right = 939\n ) %>%\n # Expect that column `2 to 4 units` is of type: logical\n col_is_logical(\n columns = c(\"2 to 4 units\")\n ) %>%\n # Expect that column `5 units or more` is of type: numeric\n col_is_numeric(\n columns = c(\"5 units or more\")\n ) %>%\n # Expect that values in `5 units or more` should be between `286` and `447`\n col_vals_between(\n columns = c(\"5 units or more\"),\n left = 286,\n right = 447\n ) %>%\n # Expect that column `Northeast` is of type: numeric\n col_is_numeric(\n columns = c(\"Northeast\")\n ) %>%\n # Expect that values in `Northeast` should be between `76` and `150`\n col_vals_between(\n columns = c(\"Northeast\"),\n left = 76,\n right = 150\n ) %>%\n # Expect that column `Midwest` is of type: numeric\n col_is_numeric(\n columns = c(\"Midwest\")\n ) %>%\n # Expect that values in `Midwest` should be between `154` and `205`\n col_vals_between(\n columns = c(\"Midwest\"),\n left = 154,\n right = 205\n ) %>%\n # Expect that column `South` is of type: numeric\n col_is_numeric(\n columns = c(\"South\")\n ) %>%\n # Expect that values in `South` should be between `560` and `673`\n col_vals_between(\n columns = c(\"South\"),\n left = 560,\n right = 673\n ) %>%\n # Expect that column `West` is of type: numeric\n col_is_numeric(\n columns = c(\"West\")\n ) %>%\n # Expect that values in `West` should be between `286` and `360`\n col_vals_between(\n columns = c(\"West\"),\n left = 286,\n right = 360\n ) %>%\n # Expect entirely distinct rows across `Year, Month, 1 unit, 2 to 4 units, 5 units or more, Northeast, Midwest, South, West`\n rows_distinct(\n columns = c(\"Year\", \"Month\", \"1 unit\", \"2 to 4 units\", \"5 units or more\", \"Northeast\", \"Midwest\", \"South\", \"West\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Year = \"numeric\",\n Month = \"character\",\n 1 unit = \"numeric\",\n 2 to 4 units = \"logical\",\n 5 units or more = \"numeric\",\n Northeast = \"numeric\",\n Midwest = \"numeric\",\n South = \"numeric\",\n West = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `fish` is of type: factor\n col_is_factor(\n columns = c(\"fish\")\n ) %>%\n # Expect that column `station` is of type: factor\n col_is_factor(\n columns = c(\"station\")\n ) %>%\n # Expect that column `seen` is of type: integer\n col_is_integer(\n columns = c(\"seen\")\n ) %>%\n # Expect that values in `seen` should be between `1` and `1`\n col_vals_between(\n columns = c(\"seen\"),\n left = 1,\n right = 1\n ) %>%\n # Expect entirely distinct rows across `fish, station, seen`\n rows_distinct(\n columns = c(\"fish\", \"station\", \"seen\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n fish = \"factor\",\n station = \"factor\",\n seen = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `fish` is of type: factor\n col_is_factor(\n columns = c(\"fish\")\n ) %>%\n # Expect that column `station` is of type: factor\n col_is_factor(\n columns = c(\"station\")\n ) %>%\n # Expect that column `seen` is of type: integer\n col_is_integer(\n columns = c(\"seen\")\n ) %>%\n # Expect that values in `seen` should be between `1` and `1`\n col_vals_between(\n columns = c(\"seen\"),\n left = 1,\n right = 1\n ) %>%\n # Expect entirely distinct rows across `fish, station, seen`\n rows_distinct(\n columns = c(\"fish\", \"station\", \"seen\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n fish = \"factor\",\n station = \"factor\",\n seen = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `religion` is of type: character\n col_is_character(\n columns = c(\"religion\")\n ) %>%\n # Expect that column `<$10k` is of type: numeric\n col_is_numeric(\n columns = c(\"<$10k\")\n ) %>%\n # Expect that values in `<$10k` should be between `1` and `575`\n col_vals_between(\n columns = c(\"<$10k\"),\n left = 1,\n right = 575\n ) %>%\n # Expect that column `$10-20k` is of type: numeric\n col_is_numeric(\n columns = c(\"$10-20k\")\n ) %>%\n # Expect that values in `$10-20k` should be between `2` and `869`\n col_vals_between(\n columns = c(\"$10-20k\"),\n left = 2,\n right = 869\n ) %>%\n # Expect that column `$20-30k` is of type: numeric\n col_is_numeric(\n columns = c(\"$20-30k\")\n ) %>%\n # Expect that values in `$20-30k` should be between `3` and `1064`\n col_vals_between(\n columns = c(\"$20-30k\"),\n left = 3,\n right = 1064\n ) %>%\n # Expect that column `$30-40k` is of type: numeric\n col_is_numeric(\n columns = c(\"$30-40k\")\n ) %>%\n # Expect that values in `$30-40k` should be between `4` and `982`\n col_vals_between(\n columns = c(\"$30-40k\"),\n left = 4,\n right = 982\n ) %>%\n # Expect that column `$40-50k` is of type: numeric\n col_is_numeric(\n columns = c(\"$40-50k\")\n ) %>%\n # Expect that values in `$40-50k` should be between `2` and `881`\n col_vals_between(\n columns = c(\"$40-50k\"),\n left = 2,\n right = 881\n ) %>%\n # Expect that column `$50-75k` is of type: numeric\n col_is_numeric(\n columns = c(\"$50-75k\")\n ) %>%\n # Expect that values in `$50-75k` should be between `7` and `1486`\n col_vals_between(\n columns = c(\"$50-75k\"),\n left = 7,\n right = 1486\n ) %>%\n # Expect that column `$75-100k` is of type: numeric\n col_is_numeric(\n columns = c(\"$75-100k\")\n ) %>%\n # Expect that values in `$75-100k` should be between `3` and `949`\n col_vals_between(\n columns = c(\"$75-100k\"),\n left = 3,\n right = 949\n ) %>%\n # Expect that column `$100-150k` is of type: numeric\n col_is_numeric(\n columns = c(\"$100-150k\")\n ) %>%\n # Expect that values in `$100-150k` should be between `4` and `792`\n col_vals_between(\n columns = c(\"$100-150k\"),\n left = 4,\n right = 792\n ) %>%\n # Expect that column `>150k` is of type: numeric\n col_is_numeric(\n columns = c(\">150k\")\n ) %>%\n # Expect that values in `>150k` should be between `4` and `634`\n col_vals_between(\n columns = c(\">150k\"),\n left = 4,\n right = 634\n ) %>%\n # Expect that column `Don't know/refused` is of type: numeric\n col_is_numeric(\n columns = c(\"Don't know/refused\")\n ) %>%\n # Expect that values in `Don't know/refused` should be between `8` and `1529`\n col_vals_between(\n columns = c(\"Don't know/refused\"),\n left = 8,\n right = 1529\n ) %>%\n # Expect entirely distinct rows across `religion, <$10k, $10-20k, $20-30k, $30-40k, $40-50k, $50-75k, $75-100k, $100-150k, >150k, Don't know/refused`\n rows_distinct(\n columns = c(\"religion\", \"<$10k\", \"$10-20k\", \"$20-30k\", \"$30-40k\", \"$40-50k\", \"$50-75k\", \"$75-100k\", \"$100-150k\", \">150k\", \"Don't know/refused\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n religion = \"character\",\n <$10k = \"numeric\",\n $10-20k = \"numeric\",\n $20-30k = \"numeric\",\n $30-40k = \"numeric\",\n $40-50k = \"numeric\",\n $50-75k = \"numeric\",\n $75-100k = \"numeric\",\n $100-150k = \"numeric\",\n >150k = \"numeric\",\n Don't know/refused = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `religion` is of type: character\n col_is_character(\n columns = c(\"religion\")\n ) %>%\n # Expect that column `<$10k` is of type: numeric\n col_is_numeric(\n columns = c(\"<$10k\")\n ) %>%\n # Expect that values in `<$10k` should be between `1` and `575`\n col_vals_between(\n columns = c(\"<$10k\"),\n left = 1,\n right = 575\n ) %>%\n # Expect that column `$10-20k` is of type: numeric\n col_is_numeric(\n columns = c(\"$10-20k\")\n ) %>%\n # Expect that values in `$10-20k` should be between `2` and `869`\n col_vals_between(\n columns = c(\"$10-20k\"),\n left = 2,\n right = 869\n ) %>%\n # Expect that column `$20-30k` is of type: numeric\n col_is_numeric(\n columns = c(\"$20-30k\")\n ) %>%\n # Expect that values in `$20-30k` should be between `3` and `1064`\n col_vals_between(\n columns = c(\"$20-30k\"),\n left = 3,\n right = 1064\n ) %>%\n # Expect that column `$30-40k` is of type: numeric\n col_is_numeric(\n columns = c(\"$30-40k\")\n ) %>%\n # Expect that values in `$30-40k` should be between `4` and `982`\n col_vals_between(\n columns = c(\"$30-40k\"),\n left = 4,\n right = 982\n ) %>%\n # Expect that column `$40-50k` is of type: numeric\n col_is_numeric(\n columns = c(\"$40-50k\")\n ) %>%\n # Expect that values in `$40-50k` should be between `2` and `881`\n col_vals_between(\n columns = c(\"$40-50k\"),\n left = 2,\n right = 881\n ) %>%\n # Expect that column `$50-75k` is of type: numeric\n col_is_numeric(\n columns = c(\"$50-75k\")\n ) %>%\n # Expect that values in `$50-75k` should be between `7` and `1486`\n col_vals_between(\n columns = c(\"$50-75k\"),\n left = 7,\n right = 1486\n ) %>%\n # Expect that column `$75-100k` is of type: numeric\n col_is_numeric(\n columns = c(\"$75-100k\")\n ) %>%\n # Expect that values in `$75-100k` should be between `3` and `949`\n col_vals_between(\n columns = c(\"$75-100k\"),\n left = 3,\n right = 949\n ) %>%\n # Expect that column `$100-150k` is of type: numeric\n col_is_numeric(\n columns = c(\"$100-150k\")\n ) %>%\n # Expect that values in `$100-150k` should be between `4` and `792`\n col_vals_between(\n columns = c(\"$100-150k\"),\n left = 4,\n right = 792\n ) %>%\n # Expect that column `>150k` is of type: numeric\n col_is_numeric(\n columns = c(\">150k\")\n ) %>%\n # Expect that values in `>150k` should be between `4` and `634`\n col_vals_between(\n columns = c(\">150k\"),\n left = 4,\n right = 634\n ) %>%\n # Expect that column `Don't know/refused` is of type: numeric\n col_is_numeric(\n columns = c(\"Don't know/refused\")\n ) %>%\n # Expect that values in `Don't know/refused` should be between `8` and `1529`\n col_vals_between(\n columns = c(\"Don't know/refused\"),\n left = 8,\n right = 1529\n ) %>%\n # Expect entirely distinct rows across `religion, <$10k, $10-20k, $20-30k, $30-40k, $40-50k, $50-75k, $75-100k, $100-150k, >150k, Don't know/refused`\n rows_distinct(\n columns = c(\"religion\", \"<$10k\", \"$10-20k\", \"$20-30k\", \"$30-40k\", \"$40-50k\", \"$50-75k\", \"$75-100k\", \"$100-150k\", \">150k\", \"Don't know/refused\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n religion = \"character\",\n <$10k = \"numeric\",\n $10-20k = \"numeric\",\n $20-30k = \"numeric\",\n $30-40k = \"numeric\",\n $40-50k = \"numeric\",\n $50-75k = \"numeric\",\n $75-100k = \"numeric\",\n $100-150k = \"numeric\",\n >150k = \"numeric\",\n Don't know/refused = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `subject` is of type: character\n col_is_character(\n columns = c(\"subject\")\n ) %>%\n # Expect that column `time` is of type: numeric\n col_is_numeric(\n columns = c(\"time\")\n ) %>%\n # Expect that values in `time` should be between `1` and `1`\n col_vals_between(\n columns = c(\"time\"),\n left = 1,\n right = 1\n ) %>%\n # Expect that column `age` is of type: numeric\n col_is_numeric(\n columns = c(\"age\")\n ) %>%\n # Expect that values in `age` should be between `33` and `33`\n col_vals_between(\n columns = c(\"age\"),\n left = 33,\n right = 33,\n na_pass = TRUE\n ) %>%\n # Expect that column `weight` is of type: numeric\n col_is_numeric(\n columns = c(\"weight\")\n ) %>%\n # Expect that values in `weight` should be between `90` and `90`\n col_vals_between(\n columns = c(\"weight\"),\n left = 90,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column `height` is of type: numeric\n col_is_numeric(\n columns = c(\"height\")\n ) %>%\n # Expect that values in `height` should be between `1.54` and `1.87`\n col_vals_between(\n columns = c(\"height\"),\n left = 1.54,\n right = 1.87\n ) %>%\n # Expect entirely distinct rows across `subject, time, age, weight, height`\n rows_distinct(\n columns = c(\"subject\", \"time\", \"age\", \"weight\", \"height\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n subject = \"character\",\n time = \"numeric\",\n age = \"numeric\",\n weight = \"numeric\",\n height = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `subject` is of type: character\n col_is_character(\n columns = c(\"subject\")\n ) %>%\n # Expect that column `time` is of type: numeric\n col_is_numeric(\n columns = c(\"time\")\n ) %>%\n # Expect that values in `time` should be between `1` and `1`\n col_vals_between(\n columns = c(\"time\"),\n left = 1,\n right = 1\n ) %>%\n # Expect that column `age` is of type: numeric\n col_is_numeric(\n columns = c(\"age\")\n ) %>%\n # Expect that values in `age` should be between `33` and `33`\n col_vals_between(\n columns = c(\"age\"),\n left = 33,\n right = 33,\n na_pass = TRUE\n ) %>%\n # Expect that column `weight` is of type: numeric\n col_is_numeric(\n columns = c(\"weight\")\n ) %>%\n # Expect that values in `weight` should be between `90` and `90`\n col_vals_between(\n columns = c(\"weight\"),\n left = 90,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column `height` is of type: numeric\n col_is_numeric(\n columns = c(\"height\")\n ) %>%\n # Expect that values in `height` should be between `1.54` and `1.87`\n col_vals_between(\n columns = c(\"height\"),\n left = 1.54,\n right = 1.87\n ) %>%\n # Expect entirely distinct rows across `subject, time, age, weight, height`\n rows_distinct(\n columns = c(\"subject\", \"time\", \"age\", \"weight\", \"height\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n subject = \"character\",\n time = \"numeric\",\n age = \"numeric\",\n weight = \"numeric\",\n height = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `GEOID` is of type: character\n col_is_character(\n columns = c(\"GEOID\")\n ) %>%\n # Expect that column `NAME` is of type: character\n col_is_character(\n columns = c(\"NAME\")\n ) %>%\n # Expect that column `variable` is of type: character\n col_is_character(\n columns = c(\"variable\")\n ) %>%\n # Expect that column `estimate` is of type: numeric\n col_is_numeric(\n columns = c(\"estimate\")\n ) %>%\n # Expect that values in `estimate` should be between `464` and `43198`\n col_vals_between(\n columns = c(\"estimate\"),\n left = 464,\n right = 43198,\n na_pass = TRUE\n ) %>%\n # Expect that column `moe` is of type: numeric\n col_is_numeric(\n columns = c(\"moe\")\n ) %>%\n # Expect that values in `moe` should be between `2` and `681`\n col_vals_between(\n columns = c(\"moe\"),\n left = 2,\n right = 681,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `GEOID, NAME, variable, estimate, moe`\n rows_distinct(\n columns = c(\"GEOID\", \"NAME\", \"variable\", \"estimate\", \"moe\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n GEOID = \"character\",\n NAME = \"character\",\n variable = \"character\",\n estimate = \"numeric\",\n moe = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `GEOID` is of type: character\n col_is_character(\n columns = c(\"GEOID\")\n ) %>%\n # Expect that column `NAME` is of type: character\n col_is_character(\n columns = c(\"NAME\")\n ) %>%\n # Expect that column `variable` is of type: character\n col_is_character(\n columns = c(\"variable\")\n ) %>%\n # Expect that column `estimate` is of type: numeric\n col_is_numeric(\n columns = c(\"estimate\")\n ) %>%\n # Expect that values in `estimate` should be between `464` and `43198`\n col_vals_between(\n columns = c(\"estimate\"),\n left = 464,\n right = 43198,\n na_pass = TRUE\n ) %>%\n # Expect that column `moe` is of type: numeric\n col_is_numeric(\n columns = c(\"moe\")\n ) %>%\n # Expect that values in `moe` should be between `2` and `681`\n col_vals_between(\n columns = c(\"moe\"),\n left = 2,\n right = 681,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `GEOID, NAME, variable, estimate, moe`\n rows_distinct(\n columns = c(\"GEOID\", \"NAME\", \"variable\", \"estimate\", \"moe\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n GEOID = \"character\",\n NAME = \"character\",\n variable = \"character\",\n estimate = \"numeric\",\n moe = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `country` is of type: character\n col_is_character(\n columns = c(\"country\")\n ) %>%\n # Expect that column `indicator` is of type: character\n col_is_character(\n columns = c(\"indicator\")\n ) %>%\n # Expect that column `2000` is of type: numeric\n col_is_numeric(\n columns = c(\"2000\")\n ) %>%\n # Expect that values in `2000` should be between `-4.07538613162288` and `6144322697`\n col_vals_between(\n columns = c(\"2000\"),\n left = -4.0753861,\n right = 6144322700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2001` is of type: numeric\n col_is_numeric(\n columns = c(\"2001\")\n ) %>%\n # Expect that values in `2001` should be between `-3.8476707266781` and `6226339538`\n col_vals_between(\n columns = c(\"2001\"),\n left = -3.8476707,\n right = 6226339500,\n na_pass = TRUE\n ) %>%\n # Expect that column `2002` is of type: numeric\n col_is_numeric(\n columns = c(\"2002\")\n ) %>%\n # Expect that values in `2002` should be between `-3.5058941109977` and `6308092739`\n col_vals_between(\n columns = c(\"2002\"),\n left = -3.5058941,\n right = 6308092700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2003` is of type: numeric\n col_is_numeric(\n columns = c(\"2003\")\n ) %>%\n # Expect that values in `2003` should be between `-3.55055571718435` and `6389383352`\n col_vals_between(\n columns = c(\"2003\"),\n left = -3.5505557,\n right = 6389383400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2004` is of type: numeric\n col_is_numeric(\n columns = c(\"2004\")\n ) %>%\n # Expect that values in `2004` should be between `-3.72003227551706` and `6470821068`\n col_vals_between(\n columns = c(\"2004\"),\n left = -3.7200323,\n right = 6470821100,\n na_pass = TRUE\n ) %>%\n # Expect that column `2005` is of type: numeric\n col_is_numeric(\n columns = c(\"2005\")\n ) %>%\n # Expect that values in `2005` should be between `-4.07796901122163` and `6552571570`\n col_vals_between(\n columns = c(\"2005\"),\n left = -4.077969,\n right = 6552571600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2006` is of type: numeric\n col_is_numeric(\n columns = c(\"2006\")\n ) %>%\n # Expect that values in `2006` should be between `-4.39053378535746` and `6634935638`\n col_vals_between(\n columns = c(\"2006\"),\n left = -4.3905338,\n right = 6634935600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2007` is of type: numeric\n col_is_numeric(\n columns = c(\"2007\")\n ) %>%\n # Expect that values in `2007` should be between `-4.66353575517151` and `6717641730`\n col_vals_between(\n columns = c(\"2007\"),\n left = -4.6635358,\n right = 6717641700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2008` is of type: numeric\n col_is_numeric(\n columns = c(\"2008\")\n ) %>%\n # Expect that values in `2008` should be between `-4.90503090271691` and `6801408360`\n col_vals_between(\n columns = c(\"2008\"),\n left = -4.9050309,\n right = 6801408400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2009` is of type: numeric\n col_is_numeric(\n columns = c(\"2009\")\n ) %>%\n # Expect that values in `2009` should be between `-5.08445117030295` and `6885490816`\n col_vals_between(\n columns = c(\"2009\"),\n left = -5.0844512,\n right = 6885490800,\n na_pass = TRUE\n ) %>%\n # Expect that column `2010` is of type: numeric\n col_is_numeric(\n columns = c(\"2010\")\n ) %>%\n # Expect that values in `2010` should be between `-5.34393804525569` and `6969631901`\n col_vals_between(\n columns = c(\"2010\"),\n left = -5.343938,\n right = 6969631900,\n na_pass = TRUE\n ) %>%\n # Expect that column `2011` is of type: numeric\n col_is_numeric(\n columns = c(\"2011\")\n ) %>%\n # Expect that values in `2011` should be between `-4.79355371289299` and `7053533350`\n col_vals_between(\n columns = c(\"2011\"),\n left = -4.7935537,\n right = 7053533400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2012` is of type: numeric\n col_is_numeric(\n columns = c(\"2012\")\n ) %>%\n # Expect that values in `2012` should be between `-5.28007770057696` and `7140895722`\n col_vals_between(\n columns = c(\"2012\"),\n left = -5.2800777,\n right = 7140895700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2013` is of type: numeric\n col_is_numeric(\n columns = c(\"2013\")\n ) %>%\n # Expect that values in `2013` should be between `-6.96818698489862` and `7229184551`\n col_vals_between(\n columns = c(\"2013\"),\n left = -6.968187,\n right = 7229184600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2014` is of type: numeric\n col_is_numeric(\n columns = c(\"2014\")\n ) %>%\n # Expect that values in `2014` should be between `-8.83048301221807` and `7317508753`\n col_vals_between(\n columns = c(\"2014\"),\n left = -8.830483,\n right = 7317508800,\n na_pass = TRUE\n ) %>%\n # Expect that column `2015` is of type: numeric\n col_is_numeric(\n columns = c(\"2015\")\n ) %>%\n # Expect that values in `2015` should be between `-4.41574372125213` and `7404910892`\n col_vals_between(\n columns = c(\"2015\"),\n left = -4.4157437,\n right = 7404910900,\n na_pass = TRUE\n ) %>%\n # Expect that column `2016` is of type: numeric\n col_is_numeric(\n columns = c(\"2016\")\n ) %>%\n # Expect that values in `2016` should be between `-2.2172797902348` and `7491934113`\n col_vals_between(\n columns = c(\"2016\"),\n left = -2.2172798,\n right = 7491934100,\n na_pass = TRUE\n ) %>%\n # Expect that column `2017` is of type: numeric\n col_is_numeric(\n columns = c(\"2017\")\n ) %>%\n # Expect that values in `2017` should be between `-3.75548445756917` and `7578157615`\n col_vals_between(\n columns = c(\"2017\"),\n left = -3.7554845,\n right = 7578157600,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `country, indicator, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017`\n rows_distinct(\n columns = c(\"country\", \"indicator\", \"2000\", \"2001\", \"2002\", \"2003\", \"2004\", \"2005\", \"2006\", \"2007\", \"2008\", \"2009\", \"2010\", \"2011\", \"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n country = \"character\",\n indicator = \"character\",\n 2000 = \"numeric\",\n 2001 = \"numeric\",\n 2002 = \"numeric\",\n 2003 = \"numeric\",\n 2004 = \"numeric\",\n 2005 = \"numeric\",\n 2006 = \"numeric\",\n 2007 = \"numeric\",\n 2008 = \"numeric\",\n 2009 = \"numeric\",\n 2010 = \"numeric\",\n 2011 = \"numeric\",\n 2012 = \"numeric\",\n 2013 = \"numeric\",\n 2014 = \"numeric\",\n 2015 = \"numeric\",\n 2016 = \"numeric\",\n 2017 = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `country` is of type: character\n col_is_character(\n columns = c(\"country\")\n ) %>%\n # Expect that column `indicator` is of type: character\n col_is_character(\n columns = c(\"indicator\")\n ) %>%\n # Expect that column `2000` is of type: numeric\n col_is_numeric(\n columns = c(\"2000\")\n ) %>%\n # Expect that values in `2000` should be between `-4.07538613162288` and `6144322697`\n col_vals_between(\n columns = c(\"2000\"),\n left = -4.0753861,\n right = 6144322700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2001` is of type: numeric\n col_is_numeric(\n columns = c(\"2001\")\n ) %>%\n # Expect that values in `2001` should be between `-3.8476707266781` and `6226339538`\n col_vals_between(\n columns = c(\"2001\"),\n left = -3.8476707,\n right = 6226339500,\n na_pass = TRUE\n ) %>%\n # Expect that column `2002` is of type: numeric\n col_is_numeric(\n columns = c(\"2002\")\n ) %>%\n # Expect that values in `2002` should be between `-3.5058941109977` and `6308092739`\n col_vals_between(\n columns = c(\"2002\"),\n left = -3.5058941,\n right = 6308092700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2003` is of type: numeric\n col_is_numeric(\n columns = c(\"2003\")\n ) %>%\n # Expect that values in `2003` should be between `-3.55055571718435` and `6389383352`\n col_vals_between(\n columns = c(\"2003\"),\n left = -3.5505557,\n right = 6389383400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2004` is of type: numeric\n col_is_numeric(\n columns = c(\"2004\")\n ) %>%\n # Expect that values in `2004` should be between `-3.72003227551706` and `6470821068`\n col_vals_between(\n columns = c(\"2004\"),\n left = -3.7200323,\n right = 6470821100,\n na_pass = TRUE\n ) %>%\n # Expect that column `2005` is of type: numeric\n col_is_numeric(\n columns = c(\"2005\")\n ) %>%\n # Expect that values in `2005` should be between `-4.07796901122163` and `6552571570`\n col_vals_between(\n columns = c(\"2005\"),\n left = -4.077969,\n right = 6552571600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2006` is of type: numeric\n col_is_numeric(\n columns = c(\"2006\")\n ) %>%\n # Expect that values in `2006` should be between `-4.39053378535746` and `6634935638`\n col_vals_between(\n columns = c(\"2006\"),\n left = -4.3905338,\n right = 6634935600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2007` is of type: numeric\n col_is_numeric(\n columns = c(\"2007\")\n ) %>%\n # Expect that values in `2007` should be between `-4.66353575517151` and `6717641730`\n col_vals_between(\n columns = c(\"2007\"),\n left = -4.6635358,\n right = 6717641700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2008` is of type: numeric\n col_is_numeric(\n columns = c(\"2008\")\n ) %>%\n # Expect that values in `2008` should be between `-4.90503090271691` and `6801408360`\n col_vals_between(\n columns = c(\"2008\"),\n left = -4.9050309,\n right = 6801408400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2009` is of type: numeric\n col_is_numeric(\n columns = c(\"2009\")\n ) %>%\n # Expect that values in `2009` should be between `-5.08445117030295` and `6885490816`\n col_vals_between(\n columns = c(\"2009\"),\n left = -5.0844512,\n right = 6885490800,\n na_pass = TRUE\n ) %>%\n # Expect that column `2010` is of type: numeric\n col_is_numeric(\n columns = c(\"2010\")\n ) %>%\n # Expect that values in `2010` should be between `-5.34393804525569` and `6969631901`\n col_vals_between(\n columns = c(\"2010\"),\n left = -5.343938,\n right = 6969631900,\n na_pass = TRUE\n ) %>%\n # Expect that column `2011` is of type: numeric\n col_is_numeric(\n columns = c(\"2011\")\n ) %>%\n # Expect that values in `2011` should be between `-4.79355371289299` and `7053533350`\n col_vals_between(\n columns = c(\"2011\"),\n left = -4.7935537,\n right = 7053533400,\n na_pass = TRUE\n ) %>%\n # Expect that column `2012` is of type: numeric\n col_is_numeric(\n columns = c(\"2012\")\n ) %>%\n # Expect that values in `2012` should be between `-5.28007770057696` and `7140895722`\n col_vals_between(\n columns = c(\"2012\"),\n left = -5.2800777,\n right = 7140895700,\n na_pass = TRUE\n ) %>%\n # Expect that column `2013` is of type: numeric\n col_is_numeric(\n columns = c(\"2013\")\n ) %>%\n # Expect that values in `2013` should be between `-6.96818698489862` and `7229184551`\n col_vals_between(\n columns = c(\"2013\"),\n left = -6.968187,\n right = 7229184600,\n na_pass = TRUE\n ) %>%\n # Expect that column `2014` is of type: numeric\n col_is_numeric(\n columns = c(\"2014\")\n ) %>%\n # Expect that values in `2014` should be between `-8.83048301221807` and `7317508753`\n col_vals_between(\n columns = c(\"2014\"),\n left = -8.830483,\n right = 7317508800,\n na_pass = TRUE\n ) %>%\n # Expect that column `2015` is of type: numeric\n col_is_numeric(\n columns = c(\"2015\")\n ) %>%\n # Expect that values in `2015` should be between `-4.41574372125213` and `7404910892`\n col_vals_between(\n columns = c(\"2015\"),\n left = -4.4157437,\n right = 7404910900,\n na_pass = TRUE\n ) %>%\n # Expect that column `2016` is of type: numeric\n col_is_numeric(\n columns = c(\"2016\")\n ) %>%\n # Expect that values in `2016` should be between `-2.2172797902348` and `7491934113`\n col_vals_between(\n columns = c(\"2016\"),\n left = -2.2172798,\n right = 7491934100,\n na_pass = TRUE\n ) %>%\n # Expect that column `2017` is of type: numeric\n col_is_numeric(\n columns = c(\"2017\")\n ) %>%\n # Expect that values in `2017` should be between `-3.75548445756917` and `7578157615`\n col_vals_between(\n columns = c(\"2017\"),\n left = -3.7554845,\n right = 7578157600,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `country, indicator, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017`\n rows_distinct(\n columns = c(\"country\", \"indicator\", \"2000\", \"2001\", \"2002\", \"2003\", \"2004\", \"2005\", \"2006\", \"2007\", \"2008\", \"2009\", \"2010\", \"2011\", \"2012\", \"2013\", \"2014\", \"2015\", \"2016\", \"2017\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n country = \"character\",\n indicator = \"character\",\n 2000 = \"numeric\",\n 2001 = \"numeric\",\n 2002 = \"numeric\",\n 2003 = \"numeric\",\n 2004 = \"numeric\",\n 2005 = \"numeric\",\n 2006 = \"numeric\",\n 2007 = \"numeric\",\n 2008 = \"numeric\",\n 2009 = \"numeric\",\n 2010 = \"numeric\",\n 2011 = \"numeric\",\n 2012 = \"numeric\",\n 2013 = \"numeric\",\n 2014 = \"numeric\",\n 2015 = \"numeric\",\n 2016 = \"numeric\",\n 2017 = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `date` is of type: integer\n col_is_integer(\n columns = c(\"date\")\n ) %>%\n # Expect that values in `date` should be between `20081028` and `20090414`\n col_vals_between(\n columns = c(\"date\"),\n left = 20081028,\n right = 20090414\n ) %>%\n # Expect that column `opponent` is of type: character\n col_is_character(\n columns = c(\"opponent\")\n ) %>%\n # Expect that column `game_type` is of type: character\n col_is_character(\n columns = c(\"game_type\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `period` is of type: integer\n col_is_integer(\n columns = c(\"period\")\n ) %>%\n # Expect that values in `period` should be between `1` and `5`\n col_vals_between(\n columns = c(\"period\"),\n left = 1,\n right = 5\n ) %>%\n # Expect that column `etype` is of type: character\n col_is_character(\n columns = c(\"etype\")\n ) %>%\n # Expect that column `team` is of type: character\n col_is_character(\n columns = c(\"team\")\n ) %>%\n # Expect that column `player` is of type: character\n col_is_character(\n columns = c(\"player\")\n ) %>%\n # Expect that column `result` is of type: character\n col_is_character(\n columns = c(\"result\")\n ) %>%\n # Expect that column `points` is of type: integer\n col_is_integer(\n columns = c(\"points\")\n ) %>%\n # Expect that values in `points` should be between `0` and `3`\n col_vals_between(\n columns = c(\"points\"),\n left = 0,\n right = 3\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `x` is of type: integer\n col_is_integer(\n columns = c(\"x\")\n ) %>%\n # Expect that values in `x` should be between `0` and `51`\n col_vals_between(\n columns = c(\"x\"),\n left = 0,\n right = 51,\n na_pass = TRUE\n ) %>%\n # Expect that column `y` is of type: integer\n col_is_integer(\n columns = c(\"y\")\n ) %>%\n # Expect that values in `y` should be between `3` and `90`\n col_vals_between(\n columns = c(\"y\"),\n left = 3,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"integer\",\n opponent = \"character\",\n game_type = \"character\",\n time = \"character\",\n period = \"integer\",\n etype = \"character\",\n team = \"character\",\n player = \"character\",\n result = \"character\",\n points = \"integer\",\n type = \"character\",\n x = \"integer\",\n y = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `date` is of type: integer\n col_is_integer(\n columns = c(\"date\")\n ) %>%\n # Expect that values in `date` should be between `20081028` and `20090414`\n col_vals_between(\n columns = c(\"date\"),\n left = 20081028,\n right = 20090414\n ) %>%\n # Expect that column `opponent` is of type: character\n col_is_character(\n columns = c(\"opponent\")\n ) %>%\n # Expect that column `game_type` is of type: character\n col_is_character(\n columns = c(\"game_type\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `period` is of type: integer\n col_is_integer(\n columns = c(\"period\")\n ) %>%\n # Expect that values in `period` should be between `1` and `5`\n col_vals_between(\n columns = c(\"period\"),\n left = 1,\n right = 5\n ) %>%\n # Expect that column `etype` is of type: character\n col_is_character(\n columns = c(\"etype\")\n ) %>%\n # Expect that column `team` is of type: character\n col_is_character(\n columns = c(\"team\")\n ) %>%\n # Expect that column `player` is of type: character\n col_is_character(\n columns = c(\"player\")\n ) %>%\n # Expect that column `result` is of type: character\n col_is_character(\n columns = c(\"result\")\n ) %>%\n # Expect that column `points` is of type: integer\n col_is_integer(\n columns = c(\"points\")\n ) %>%\n # Expect that values in `points` should be between `0` and `3`\n col_vals_between(\n columns = c(\"points\"),\n left = 0,\n right = 3\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `x` is of type: integer\n col_is_integer(\n columns = c(\"x\")\n ) %>%\n # Expect that values in `x` should be between `0` and `51`\n col_vals_between(\n columns = c(\"x\"),\n left = 0,\n right = 51,\n na_pass = TRUE\n ) %>%\n # Expect that column `y` is of type: integer\n col_is_integer(\n columns = c(\"y\")\n ) %>%\n # Expect that values in `y` should be between `3` and `90`\n col_vals_between(\n columns = c(\"y\"),\n left = 3,\n right = 90,\n na_pass = TRUE\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"integer\",\n opponent = \"character\",\n game_type = \"character\",\n time = \"character\",\n period = \"integer\",\n etype = \"character\",\n team = \"character\",\n player = \"character\",\n result = \"character\",\n points = \"integer\",\n type = \"character\",\n x = \"integer\",\n y = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Ozone` is of type: integer\n col_is_integer(\n columns = c(\"Ozone\")\n ) %>%\n # Expect that values in `Ozone` should be between `1` and `168`\n col_vals_between(\n columns = c(\"Ozone\"),\n left = 1,\n right = 168,\n na_pass = TRUE\n ) %>%\n # Expect that column `Solar.R` is of type: integer\n col_is_integer(\n columns = c(\"Solar.R\")\n ) %>%\n # Expect that values in `Solar.R` should be between `7` and `334`\n col_vals_between(\n columns = c(\"Solar.R\"),\n left = 7,\n right = 334,\n na_pass = TRUE\n ) %>%\n # Expect that column `Wind` is of type: numeric\n col_is_numeric(\n columns = c(\"Wind\")\n ) %>%\n # Expect that values in `Wind` should be between `1.7` and `20.7`\n col_vals_between(\n columns = c(\"Wind\"),\n left = 1.7,\n right = 20.7\n ) %>%\n # Expect that column `Temp` is of type: integer\n col_is_integer(\n columns = c(\"Temp\")\n ) %>%\n # Expect that values in `Temp` should be between `56` and `97`\n col_vals_between(\n columns = c(\"Temp\"),\n left = 56,\n right = 97\n ) %>%\n # Expect that column `Month` is of type: integer\n col_is_integer(\n columns = c(\"Month\")\n ) %>%\n # Expect that values in `Month` should be between `5` and `9`\n col_vals_between(\n columns = c(\"Month\"),\n left = 5,\n right = 9\n ) %>%\n # Expect that column `Day` is of type: integer\n col_is_integer(\n columns = c(\"Day\")\n ) %>%\n # Expect that values in `Day` should be between `1` and `31`\n col_vals_between(\n columns = c(\"Day\"),\n left = 1,\n right = 31\n ) %>%\n # Expect entirely distinct rows across `Ozone, Solar.R, Wind, Temp, Month, Day`\n rows_distinct(\n columns = c(\"Ozone\", \"Solar.R\", \"Wind\", \"Temp\", \"Month\", \"Day\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Ozone = \"integer\",\n Solar.R = \"integer\",\n Wind = \"numeric\",\n Temp = \"integer\",\n Month = \"integer\",\n Day = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Ozone` is of type: integer\n col_is_integer(\n columns = c(\"Ozone\")\n ) %>%\n # Expect that values in `Ozone` should be between `1` and `168`\n col_vals_between(\n columns = c(\"Ozone\"),\n left = 1,\n right = 168,\n na_pass = TRUE\n ) %>%\n # Expect that column `Solar.R` is of type: integer\n col_is_integer(\n columns = c(\"Solar.R\")\n ) %>%\n # Expect that values in `Solar.R` should be between `7` and `334`\n col_vals_between(\n columns = c(\"Solar.R\"),\n left = 7,\n right = 334,\n na_pass = TRUE\n ) %>%\n # Expect that column `Wind` is of type: numeric\n col_is_numeric(\n columns = c(\"Wind\")\n ) %>%\n # Expect that values in `Wind` should be between `1.7` and `20.7`\n col_vals_between(\n columns = c(\"Wind\"),\n left = 1.7,\n right = 20.7\n ) %>%\n # Expect that column `Temp` is of type: integer\n col_is_integer(\n columns = c(\"Temp\")\n ) %>%\n # Expect that values in `Temp` should be between `56` and `97`\n col_vals_between(\n columns = c(\"Temp\"),\n left = 56,\n right = 97\n ) %>%\n # Expect that column `Month` is of type: integer\n col_is_integer(\n columns = c(\"Month\")\n ) %>%\n # Expect that values in `Month` should be between `5` and `9`\n col_vals_between(\n columns = c(\"Month\"),\n left = 5,\n right = 9\n ) %>%\n # Expect that column `Day` is of type: integer\n col_is_integer(\n columns = c(\"Day\")\n ) %>%\n # Expect that values in `Day` should be between `1` and `31`\n col_vals_between(\n columns = c(\"Day\"),\n left = 1,\n right = 31\n ) %>%\n # Expect entirely distinct rows across `Ozone, Solar.R, Wind, Temp, Month, Day`\n rows_distinct(\n columns = c(\"Ozone\", \"Solar.R\", \"Wind\", \"Temp\", \"Month\", \"Day\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Ozone = \"integer\",\n Solar.R = \"integer\",\n Wind = \"numeric\",\n Temp = \"integer\",\n Month = \"integer\",\n Day = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `weight` is of type: numeric\n col_is_numeric(\n columns = c(\"weight\")\n ) %>%\n # Expect that values in `weight` should be between `108` and `423`\n col_vals_between(\n columns = c(\"weight\"),\n left = 108,\n right = 423\n ) %>%\n # Expect that column `feed` is of type: factor\n col_is_factor(\n columns = c(\"feed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n weight = \"numeric\",\n feed = \"factor\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `weight` is of type: numeric\n col_is_numeric(\n columns = c(\"weight\")\n ) %>%\n # Expect that values in `weight` should be between `108` and `423`\n col_vals_between(\n columns = c(\"weight\"),\n left = 108,\n right = 423\n ) %>%\n # Expect that column `feed` is of type: factor\n col_is_factor(\n columns = c(\"feed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n weight = \"numeric\",\n feed = \"factor\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Sepal.Length` is of type: numeric\n col_is_numeric(\n columns = c(\"Sepal.Length\")\n ) %>%\n # Expect that values in `Sepal.Length` should be between `4.3` and `7.9`\n col_vals_between(\n columns = c(\"Sepal.Length\"),\n left = 4.3,\n right = 7.9\n ) %>%\n # Expect that column `Sepal.Width` is of type: numeric\n col_is_numeric(\n columns = c(\"Sepal.Width\")\n ) %>%\n # Expect that values in `Sepal.Width` should be between `2` and `4.4`\n col_vals_between(\n columns = c(\"Sepal.Width\"),\n left = 2,\n right = 4.4\n ) %>%\n # Expect that column `Petal.Length` is of type: numeric\n col_is_numeric(\n columns = c(\"Petal.Length\")\n ) %>%\n # Expect that values in `Petal.Length` should be between `1` and `6.9`\n col_vals_between(\n columns = c(\"Petal.Length\"),\n left = 1,\n right = 6.9\n ) %>%\n # Expect that column `Petal.Width` is of type: numeric\n col_is_numeric(\n columns = c(\"Petal.Width\")\n ) %>%\n # Expect that values in `Petal.Width` should be between `0.1` and `2.5`\n col_vals_between(\n columns = c(\"Petal.Width\"),\n left = 0.1,\n right = 2.5\n ) %>%\n # Expect that column `Species` is of type: factor\n col_is_factor(\n columns = c(\"Species\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Sepal.Length = \"numeric\",\n Sepal.Width = \"numeric\",\n Petal.Length = \"numeric\",\n Petal.Width = \"numeric\",\n Species = \"factor\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Sepal.Length` is of type: numeric\n col_is_numeric(\n columns = c(\"Sepal.Length\")\n ) %>%\n # Expect that values in `Sepal.Length` should be between `4.3` and `7.9`\n col_vals_between(\n columns = c(\"Sepal.Length\"),\n left = 4.3,\n right = 7.9\n ) %>%\n # Expect that column `Sepal.Width` is of type: numeric\n col_is_numeric(\n columns = c(\"Sepal.Width\")\n ) %>%\n # Expect that values in `Sepal.Width` should be between `2` and `4.4`\n col_vals_between(\n columns = c(\"Sepal.Width\"),\n left = 2,\n right = 4.4\n ) %>%\n # Expect that column `Petal.Length` is of type: numeric\n col_is_numeric(\n columns = c(\"Petal.Length\")\n ) %>%\n # Expect that values in `Petal.Length` should be between `1` and `6.9`\n col_vals_between(\n columns = c(\"Petal.Length\"),\n left = 1,\n right = 6.9\n ) %>%\n # Expect that column `Petal.Width` is of type: numeric\n col_is_numeric(\n columns = c(\"Petal.Width\")\n ) %>%\n # Expect that values in `Petal.Width` should be between `0.1` and `2.5`\n col_vals_between(\n columns = c(\"Petal.Width\"),\n left = 0.1,\n right = 2.5\n ) %>%\n # Expect that column `Species` is of type: factor\n col_is_factor(\n columns = c(\"Species\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Sepal.Length = \"numeric\",\n Sepal.Width = \"numeric\",\n Petal.Length = \"numeric\",\n Petal.Width = \"numeric\",\n Species = \"factor\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `sr` is of type: numeric\n col_is_numeric(\n columns = c(\"sr\")\n ) %>%\n # Expect that values in `sr` should be between `0.6` and `21.1`\n col_vals_between(\n columns = c(\"sr\"),\n left = 0.6,\n right = 21.1\n ) %>%\n # Expect that column `pop15` is of type: numeric\n col_is_numeric(\n columns = c(\"pop15\")\n ) %>%\n # Expect that values in `pop15` should be between `21.44` and `47.64`\n col_vals_between(\n columns = c(\"pop15\"),\n left = 21.44,\n right = 47.64\n ) %>%\n # Expect that column `pop75` is of type: numeric\n col_is_numeric(\n columns = c(\"pop75\")\n ) %>%\n # Expect that values in `pop75` should be between `0.56` and `4.7`\n col_vals_between(\n columns = c(\"pop75\"),\n left = 0.56,\n right = 4.7\n ) %>%\n # Expect that column `dpi` is of type: numeric\n col_is_numeric(\n columns = c(\"dpi\")\n ) %>%\n # Expect that values in `dpi` should be between `88.94` and `4001.89`\n col_vals_between(\n columns = c(\"dpi\"),\n left = 88.94,\n right = 4001.89\n ) %>%\n # Expect that column `ddpi` is of type: numeric\n col_is_numeric(\n columns = c(\"ddpi\")\n ) %>%\n # Expect that values in `ddpi` should be between `0.22` and `16.71`\n col_vals_between(\n columns = c(\"ddpi\"),\n left = 0.22,\n right = 16.71\n ) %>%\n # Expect entirely distinct rows across `sr, pop15, pop75, dpi, ddpi`\n rows_distinct(\n columns = c(\"sr\", \"pop15\", \"pop75\", \"dpi\", \"ddpi\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n sr = \"numeric\",\n pop15 = \"numeric\",\n pop75 = \"numeric\",\n dpi = \"numeric\",\n ddpi = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `sr` is of type: numeric\n col_is_numeric(\n columns = c(\"sr\")\n ) %>%\n # Expect that values in `sr` should be between `0.6` and `21.1`\n col_vals_between(\n columns = c(\"sr\"),\n left = 0.6,\n right = 21.1\n ) %>%\n # Expect that column `pop15` is of type: numeric\n col_is_numeric(\n columns = c(\"pop15\")\n ) %>%\n # Expect that values in `pop15` should be between `21.44` and `47.64`\n col_vals_between(\n columns = c(\"pop15\"),\n left = 21.44,\n right = 47.64\n ) %>%\n # Expect that column `pop75` is of type: numeric\n col_is_numeric(\n columns = c(\"pop75\")\n ) %>%\n # Expect that values in `pop75` should be between `0.56` and `4.7`\n col_vals_between(\n columns = c(\"pop75\"),\n left = 0.56,\n right = 4.7\n ) %>%\n # Expect that column `dpi` is of type: numeric\n col_is_numeric(\n columns = c(\"dpi\")\n ) %>%\n # Expect that values in `dpi` should be between `88.94` and `4001.89`\n col_vals_between(\n columns = c(\"dpi\"),\n left = 88.94,\n right = 4001.89\n ) %>%\n # Expect that column `ddpi` is of type: numeric\n col_is_numeric(\n columns = c(\"ddpi\")\n ) %>%\n # Expect that values in `ddpi` should be between `0.22` and `16.71`\n col_vals_between(\n columns = c(\"ddpi\"),\n left = 0.22,\n right = 16.71\n ) %>%\n # Expect entirely distinct rows across `sr, pop15, pop75, dpi, ddpi`\n rows_distinct(\n columns = c(\"sr\", \"pop15\", \"pop75\", \"dpi\", \"ddpi\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n sr = \"numeric\",\n pop15 = \"numeric\",\n pop75 = \"numeric\",\n dpi = \"numeric\",\n ddpi = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `GNP.deflator` is of type: numeric\n col_is_numeric(\n columns = c(\"GNP.deflator\")\n ) %>%\n # Expect that values in `GNP.deflator` should be between `83` and `116.9`\n col_vals_between(\n columns = c(\"GNP.deflator\"),\n left = 83,\n right = 116.9\n ) %>%\n # Expect that column `GNP` is of type: numeric\n col_is_numeric(\n columns = c(\"GNP\")\n ) %>%\n # Expect that values in `GNP` should be between `234.289` and `554.894`\n col_vals_between(\n columns = c(\"GNP\"),\n left = 234.289,\n right = 554.894\n ) %>%\n # Expect that column `Unemployed` is of type: numeric\n col_is_numeric(\n columns = c(\"Unemployed\")\n ) %>%\n # Expect that values in `Unemployed` should be between `187` and `480.6`\n col_vals_between(\n columns = c(\"Unemployed\"),\n left = 187,\n right = 480.6\n ) %>%\n # Expect that column `Armed.Forces` is of type: numeric\n col_is_numeric(\n columns = c(\"Armed.Forces\")\n ) %>%\n # Expect that values in `Armed.Forces` should be between `145.6` and `359.4`\n col_vals_between(\n columns = c(\"Armed.Forces\"),\n left = 145.6,\n right = 359.4\n ) %>%\n # Expect that column `Population` is of type: numeric\n col_is_numeric(\n columns = c(\"Population\")\n ) %>%\n # Expect that values in `Population` should be between `107.608` and `130.081`\n col_vals_between(\n columns = c(\"Population\"),\n left = 107.608,\n right = 130.081\n ) %>%\n # Expect that column `Year` is of type: integer\n col_is_integer(\n columns = c(\"Year\")\n ) %>%\n # Expect that values in `Year` should be between `1947` and `1962`\n col_vals_between(\n columns = c(\"Year\"),\n left = 1947,\n right = 1962\n ) %>%\n # Expect that column `Employed` is of type: numeric\n col_is_numeric(\n columns = c(\"Employed\")\n ) %>%\n # Expect that values in `Employed` should be between `60.171` and `70.551`\n col_vals_between(\n columns = c(\"Employed\"),\n left = 60.171,\n right = 70.551\n ) %>%\n # Expect entirely distinct rows across `GNP.deflator, GNP, Unemployed, Armed.Forces, Population, Year, Employed`\n rows_distinct(\n columns = c(\"GNP.deflator\", \"GNP\", \"Unemployed\", \"Armed.Forces\", \"Population\", \"Year\", \"Employed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n GNP.deflator = \"numeric\",\n GNP = \"numeric\",\n Unemployed = \"numeric\",\n Armed.Forces = \"numeric\",\n Population = \"numeric\",\n Year = \"integer\",\n Employed = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `GNP.deflator` is of type: numeric\n col_is_numeric(\n columns = c(\"GNP.deflator\")\n ) %>%\n # Expect that values in `GNP.deflator` should be between `83` and `116.9`\n col_vals_between(\n columns = c(\"GNP.deflator\"),\n left = 83,\n right = 116.9\n ) %>%\n # Expect that column `GNP` is of type: numeric\n col_is_numeric(\n columns = c(\"GNP\")\n ) %>%\n # Expect that values in `GNP` should be between `234.289` and `554.894`\n col_vals_between(\n columns = c(\"GNP\"),\n left = 234.289,\n right = 554.894\n ) %>%\n # Expect that column `Unemployed` is of type: numeric\n col_is_numeric(\n columns = c(\"Unemployed\")\n ) %>%\n # Expect that values in `Unemployed` should be between `187` and `480.6`\n col_vals_between(\n columns = c(\"Unemployed\"),\n left = 187,\n right = 480.6\n ) %>%\n # Expect that column `Armed.Forces` is of type: numeric\n col_is_numeric(\n columns = c(\"Armed.Forces\")\n ) %>%\n # Expect that values in `Armed.Forces` should be between `145.6` and `359.4`\n col_vals_between(\n columns = c(\"Armed.Forces\"),\n left = 145.6,\n right = 359.4\n ) %>%\n # Expect that column `Population` is of type: numeric\n col_is_numeric(\n columns = c(\"Population\")\n ) %>%\n # Expect that values in `Population` should be between `107.608` and `130.081`\n col_vals_between(\n columns = c(\"Population\"),\n left = 107.608,\n right = 130.081\n ) %>%\n # Expect that column `Year` is of type: integer\n col_is_integer(\n columns = c(\"Year\")\n ) %>%\n # Expect that values in `Year` should be between `1947` and `1962`\n col_vals_between(\n columns = c(\"Year\"),\n left = 1947,\n right = 1962\n ) %>%\n # Expect that column `Employed` is of type: numeric\n col_is_numeric(\n columns = c(\"Employed\")\n ) %>%\n # Expect that values in `Employed` should be between `60.171` and `70.551`\n col_vals_between(\n columns = c(\"Employed\"),\n left = 60.171,\n right = 70.551\n ) %>%\n # Expect entirely distinct rows across `GNP.deflator, GNP, Unemployed, Armed.Forces, Population, Year, Employed`\n rows_distinct(\n columns = c(\"GNP.deflator\", \"GNP\", \"Unemployed\", \"Armed.Forces\", \"Population\", \"Year\", \"Employed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n GNP.deflator = \"numeric\",\n GNP = \"numeric\",\n Unemployed = \"numeric\",\n Armed.Forces = \"numeric\",\n Population = \"numeric\",\n Year = \"integer\",\n Employed = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Expt` is of type: integer\n col_is_integer(\n columns = c(\"Expt\")\n ) %>%\n # Expect that values in `Expt` should be between `1` and `5`\n col_vals_between(\n columns = c(\"Expt\"),\n left = 1,\n right = 5\n ) %>%\n # Expect that column `Run` is of type: integer\n col_is_integer(\n columns = c(\"Run\")\n ) %>%\n # Expect that values in `Run` should be between `1` and `20`\n col_vals_between(\n columns = c(\"Run\"),\n left = 1,\n right = 20\n ) %>%\n # Expect that column `Speed` is of type: integer\n col_is_integer(\n columns = c(\"Speed\")\n ) %>%\n # Expect that values in `Speed` should be between `620` and `1070`\n col_vals_between(\n columns = c(\"Speed\"),\n left = 620,\n right = 1070\n ) %>%\n # Expect entirely distinct rows across `Expt, Run, Speed`\n rows_distinct(\n columns = c(\"Expt\", \"Run\", \"Speed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Expt = \"integer\",\n Run = \"integer\",\n Speed = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Expt` is of type: integer\n col_is_integer(\n columns = c(\"Expt\")\n ) %>%\n # Expect that values in `Expt` should be between `1` and `5`\n col_vals_between(\n columns = c(\"Expt\"),\n left = 1,\n right = 5\n ) %>%\n # Expect that column `Run` is of type: integer\n col_is_integer(\n columns = c(\"Run\")\n ) %>%\n # Expect that values in `Run` should be between `1` and `20`\n col_vals_between(\n columns = c(\"Run\"),\n left = 1,\n right = 20\n ) %>%\n # Expect that column `Speed` is of type: integer\n col_is_integer(\n columns = c(\"Speed\")\n ) %>%\n # Expect that values in `Speed` should be between `620` and `1070`\n col_vals_between(\n columns = c(\"Speed\"),\n left = 620,\n right = 1070\n ) %>%\n # Expect entirely distinct rows across `Expt, Run, Speed`\n rows_distinct(\n columns = c(\"Expt\", \"Run\", \"Speed\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Expt = \"integer\",\n Run = \"integer\",\n Speed = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mpg` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg\")\n ) %>%\n # Expect that values in `mpg` should be between `10.4` and `33.9`\n col_vals_between(\n columns = c(\"mpg\"),\n left = 10.4,\n right = 33.9\n ) %>%\n # Expect that column `cyl` is of type: numeric\n col_is_numeric(\n columns = c(\"cyl\")\n ) %>%\n # Expect that values in `cyl` should be between `4` and `8`\n col_vals_between(\n columns = c(\"cyl\"),\n left = 4,\n right = 8\n ) %>%\n # Expect that column `disp` is of type: numeric\n col_is_numeric(\n columns = c(\"disp\")\n ) %>%\n # Expect that values in `disp` should be between `71.1` and `472`\n col_vals_between(\n columns = c(\"disp\"),\n left = 71.1,\n right = 472\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `52` and `335`\n col_vals_between(\n columns = c(\"hp\"),\n left = 52,\n right = 335\n ) %>%\n # Expect that column `drat` is of type: numeric\n col_is_numeric(\n columns = c(\"drat\")\n ) %>%\n # Expect that values in `drat` should be between `2.76` and `4.93`\n col_vals_between(\n columns = c(\"drat\"),\n left = 2.76,\n right = 4.93\n ) %>%\n # Expect that column `wt` is of type: numeric\n col_is_numeric(\n columns = c(\"wt\")\n ) %>%\n # Expect that values in `wt` should be between `1.513` and `5.424`\n col_vals_between(\n columns = c(\"wt\"),\n left = 1.513,\n right = 5.424\n ) %>%\n # Expect that column `qsec` is of type: numeric\n col_is_numeric(\n columns = c(\"qsec\")\n ) %>%\n # Expect that values in `qsec` should be between `14.5` and `22.9`\n col_vals_between(\n columns = c(\"qsec\"),\n left = 14.5,\n right = 22.9\n ) %>%\n # Expect that column `vs` is of type: numeric\n col_is_numeric(\n columns = c(\"vs\")\n ) %>%\n # Expect that values in `vs` should be between `0` and `1`\n col_vals_between(\n columns = c(\"vs\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `am` is of type: numeric\n col_is_numeric(\n columns = c(\"am\")\n ) %>%\n # Expect that values in `am` should be between `0` and `1`\n col_vals_between(\n columns = c(\"am\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `gear` is of type: numeric\n col_is_numeric(\n columns = c(\"gear\")\n ) %>%\n # Expect that values in `gear` should be between `3` and `5`\n col_vals_between(\n columns = c(\"gear\"),\n left = 3,\n right = 5\n ) %>%\n # Expect that column `carb` is of type: numeric\n col_is_numeric(\n columns = c(\"carb\")\n ) %>%\n # Expect that values in `carb` should be between `1` and `8`\n col_vals_between(\n columns = c(\"carb\"),\n left = 1,\n right = 8\n ) %>%\n # Expect entirely distinct rows across `mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb`\n rows_distinct(\n columns = c(\"mpg\", \"cyl\", \"disp\", \"hp\", \"drat\", \"wt\", \"qsec\", \"vs\", \"am\", \"gear\", \"carb\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mpg = \"numeric\",\n cyl = \"numeric\",\n disp = \"numeric\",\n hp = \"numeric\",\n drat = \"numeric\",\n wt = \"numeric\",\n qsec = \"numeric\",\n vs = \"numeric\",\n am = \"numeric\",\n gear = \"numeric\",\n carb = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mpg` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg\")\n ) %>%\n # Expect that values in `mpg` should be between `10.4` and `33.9`\n col_vals_between(\n columns = c(\"mpg\"),\n left = 10.4,\n right = 33.9\n ) %>%\n # Expect that column `cyl` is of type: numeric\n col_is_numeric(\n columns = c(\"cyl\")\n ) %>%\n # Expect that values in `cyl` should be between `4` and `8`\n col_vals_between(\n columns = c(\"cyl\"),\n left = 4,\n right = 8\n ) %>%\n # Expect that column `disp` is of type: numeric\n col_is_numeric(\n columns = c(\"disp\")\n ) %>%\n # Expect that values in `disp` should be between `71.1` and `472`\n col_vals_between(\n columns = c(\"disp\"),\n left = 71.1,\n right = 472\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `52` and `335`\n col_vals_between(\n columns = c(\"hp\"),\n left = 52,\n right = 335\n ) %>%\n # Expect that column `drat` is of type: numeric\n col_is_numeric(\n columns = c(\"drat\")\n ) %>%\n # Expect that values in `drat` should be between `2.76` and `4.93`\n col_vals_between(\n columns = c(\"drat\"),\n left = 2.76,\n right = 4.93\n ) %>%\n # Expect that column `wt` is of type: numeric\n col_is_numeric(\n columns = c(\"wt\")\n ) %>%\n # Expect that values in `wt` should be between `1.513` and `5.424`\n col_vals_between(\n columns = c(\"wt\"),\n left = 1.513,\n right = 5.424\n ) %>%\n # Expect that column `qsec` is of type: numeric\n col_is_numeric(\n columns = c(\"qsec\")\n ) %>%\n # Expect that values in `qsec` should be between `14.5` and `22.9`\n col_vals_between(\n columns = c(\"qsec\"),\n left = 14.5,\n right = 22.9\n ) %>%\n # Expect that column `vs` is of type: numeric\n col_is_numeric(\n columns = c(\"vs\")\n ) %>%\n # Expect that values in `vs` should be between `0` and `1`\n col_vals_between(\n columns = c(\"vs\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `am` is of type: numeric\n col_is_numeric(\n columns = c(\"am\")\n ) %>%\n # Expect that values in `am` should be between `0` and `1`\n col_vals_between(\n columns = c(\"am\"),\n left = 0,\n right = 1\n ) %>%\n # Expect that column `gear` is of type: numeric\n col_is_numeric(\n columns = c(\"gear\")\n ) %>%\n # Expect that values in `gear` should be between `3` and `5`\n col_vals_between(\n columns = c(\"gear\"),\n left = 3,\n right = 5\n ) %>%\n # Expect that column `carb` is of type: numeric\n col_is_numeric(\n columns = c(\"carb\")\n ) %>%\n # Expect that values in `carb` should be between `1` and `8`\n col_vals_between(\n columns = c(\"carb\"),\n left = 1,\n right = 8\n ) %>%\n # Expect entirely distinct rows across `mpg, cyl, disp, hp, drat, wt, qsec, vs, am, gear, carb`\n rows_distinct(\n columns = c(\"mpg\", \"cyl\", \"disp\", \"hp\", \"drat\", \"wt\", \"qsec\", \"vs\", \"am\", \"gear\", \"carb\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mpg = \"numeric\",\n cyl = \"numeric\",\n disp = \"numeric\",\n hp = \"numeric\",\n drat = \"numeric\",\n wt = \"numeric\",\n qsec = \"numeric\",\n vs = \"numeric\",\n am = \"numeric\",\n gear = \"numeric\",\n carb = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Tree` is of type: factor\n col_is_factor(\n columns = c(\"Tree\")\n ) %>%\n # Expect that column `age` is of type: numeric\n col_is_numeric(\n columns = c(\"age\")\n ) %>%\n # Expect that values in `age` should be between `118` and `1582`\n col_vals_between(\n columns = c(\"age\"),\n left = 118,\n right = 1582\n ) %>%\n # Expect that column `circumference` is of type: numeric\n col_is_numeric(\n columns = c(\"circumference\")\n ) %>%\n # Expect that values in `circumference` should be between `30` and `214`\n col_vals_between(\n columns = c(\"circumference\"),\n left = 30,\n right = 214\n ) %>%\n # Expect entirely distinct rows across `Tree, age, circumference`\n rows_distinct(\n columns = c(\"Tree\", \"age\", \"circumference\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Tree = c(\"ordered\", \"factor\"),\n age = \"numeric\",\n circumference = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Tree` is of type: factor\n col_is_factor(\n columns = c(\"Tree\")\n ) %>%\n # Expect that column `age` is of type: numeric\n col_is_numeric(\n columns = c(\"age\")\n ) %>%\n # Expect that values in `age` should be between `118` and `1582`\n col_vals_between(\n columns = c(\"age\"),\n left = 118,\n right = 1582\n ) %>%\n # Expect that column `circumference` is of type: numeric\n col_is_numeric(\n columns = c(\"circumference\")\n ) %>%\n # Expect that values in `circumference` should be between `30` and `214`\n col_vals_between(\n columns = c(\"circumference\"),\n left = 30,\n right = 214\n ) %>%\n # Expect entirely distinct rows across `Tree, age, circumference`\n rows_distinct(\n columns = c(\"Tree\", \"age\", \"circumference\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Tree = c(\"ordered\", \"factor\"),\n age = \"numeric\",\n circumference = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `temperature` is of type: numeric\n col_is_numeric(\n columns = c(\"temperature\")\n ) %>%\n # Expect that values in `temperature` should be between `0` and `360`\n col_vals_between(\n columns = c(\"temperature\"),\n left = 0,\n right = 360\n ) %>%\n # Expect that column `pressure` is of type: numeric\n col_is_numeric(\n columns = c(\"pressure\")\n ) %>%\n # Expect that values in `pressure` should be between `2e-04` and `806`\n col_vals_between(\n columns = c(\"pressure\"),\n left = 2e-04,\n right = 806\n ) %>%\n # Expect entirely distinct rows across `temperature, pressure`\n rows_distinct(\n columns = c(\"temperature\", \"pressure\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n temperature = \"numeric\",\n pressure = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `temperature` is of type: numeric\n col_is_numeric(\n columns = c(\"temperature\")\n ) %>%\n # Expect that values in `temperature` should be between `0` and `360`\n col_vals_between(\n columns = c(\"temperature\"),\n left = 0,\n right = 360\n ) %>%\n # Expect that column `pressure` is of type: numeric\n col_is_numeric(\n columns = c(\"pressure\")\n ) %>%\n # Expect that values in `pressure` should be between `2e-04` and `806`\n col_vals_between(\n columns = c(\"pressure\"),\n left = 2e-04,\n right = 806\n ) %>%\n # Expect entirely distinct rows across `temperature, pressure`\n rows_distinct(\n columns = c(\"temperature\", \"pressure\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n temperature = \"numeric\",\n pressure = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `lat` is of type: numeric\n col_is_numeric(\n columns = c(\"lat\")\n ) %>%\n # Expect that values in `lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `long` is of type: numeric\n col_is_numeric(\n columns = c(\"long\")\n ) %>%\n # Expect that values in `long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `depth` is of type: integer\n col_is_integer(\n columns = c(\"depth\")\n ) %>%\n # Expect that values in `depth` should be between `40` and `680`\n col_vals_between(\n columns = c(\"depth\"),\n left = 40,\n right = 680\n ) %>%\n # Expect that column `mag` is of type: numeric\n col_is_numeric(\n columns = c(\"mag\")\n ) %>%\n # Expect that values in `mag` should be between `4` and `6.4`\n col_vals_between(\n columns = c(\"mag\"),\n left = 4,\n right = 6.4\n ) %>%\n # Expect that column `stations` is of type: integer\n col_is_integer(\n columns = c(\"stations\")\n ) %>%\n # Expect that values in `stations` should be between `10` and `132`\n col_vals_between(\n columns = c(\"stations\"),\n left = 10,\n right = 132\n ) %>%\n # Expect entirely distinct rows across `lat, long, depth, mag, stations`\n rows_distinct(\n columns = c(\"lat\", \"long\", \"depth\", \"mag\", \"stations\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n lat = \"numeric\",\n long = \"numeric\",\n depth = \"integer\",\n mag = \"numeric\",\n stations = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `lat` is of type: numeric\n col_is_numeric(\n columns = c(\"lat\")\n ) %>%\n # Expect that values in `lat` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"lat\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `long` is of type: numeric\n col_is_numeric(\n columns = c(\"long\")\n ) %>%\n # Expect that values in `long` should be between `-180` and `180`\n col_vals_between(\n columns = c(\"long\"),\n left = -180,\n right = 180\n ) %>%\n # Expect that column `depth` is of type: integer\n col_is_integer(\n columns = c(\"depth\")\n ) %>%\n # Expect that values in `depth` should be between `40` and `680`\n col_vals_between(\n columns = c(\"depth\"),\n left = 40,\n right = 680\n ) %>%\n # Expect that column `mag` is of type: numeric\n col_is_numeric(\n columns = c(\"mag\")\n ) %>%\n # Expect that values in `mag` should be between `4` and `6.4`\n col_vals_between(\n columns = c(\"mag\"),\n left = 4,\n right = 6.4\n ) %>%\n # Expect that column `stations` is of type: integer\n col_is_integer(\n columns = c(\"stations\")\n ) %>%\n # Expect that values in `stations` should be between `10` and `132`\n col_vals_between(\n columns = c(\"stations\"),\n left = 10,\n right = 132\n ) %>%\n # Expect entirely distinct rows across `lat, long, depth, mag, stations`\n rows_distinct(\n columns = c(\"lat\", \"long\", \"depth\", \"mag\", \"stations\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n lat = \"numeric\",\n long = \"numeric\",\n depth = \"integer\",\n mag = \"numeric\",\n stations = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `area` is of type: integer\n col_is_integer(\n columns = c(\"area\")\n ) %>%\n # Expect that values in `area` should be between `1016` and `12212`\n col_vals_between(\n columns = c(\"area\"),\n left = 1016,\n right = 12212\n ) %>%\n # Expect that column `peri` is of type: numeric\n col_is_numeric(\n columns = c(\"peri\")\n ) %>%\n # Expect that values in `peri` should be between `308.642` and `4864.22`\n col_vals_between(\n columns = c(\"peri\"),\n left = 308.642,\n right = 4864.22\n ) %>%\n # Expect that column `shape` is of type: numeric\n col_is_numeric(\n columns = c(\"shape\")\n ) %>%\n # Expect that values in `shape` should be between `0.0903296` and `0.464125`\n col_vals_between(\n columns = c(\"shape\"),\n left = 0.0903296,\n right = 0.464125\n ) %>%\n # Expect that column `perm` is of type: numeric\n col_is_numeric(\n columns = c(\"perm\")\n ) %>%\n # Expect that values in `perm` should be between `6.3` and `1300`\n col_vals_between(\n columns = c(\"perm\"),\n left = 6.3,\n right = 1300\n ) %>%\n # Expect entirely distinct rows across `area, peri, shape, perm`\n rows_distinct(\n columns = c(\"area\", \"peri\", \"shape\", \"perm\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n area = \"integer\",\n peri = \"numeric\",\n shape = \"numeric\",\n perm = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `area` is of type: integer\n col_is_integer(\n columns = c(\"area\")\n ) %>%\n # Expect that values in `area` should be between `1016` and `12212`\n col_vals_between(\n columns = c(\"area\"),\n left = 1016,\n right = 12212\n ) %>%\n # Expect that column `peri` is of type: numeric\n col_is_numeric(\n columns = c(\"peri\")\n ) %>%\n # Expect that values in `peri` should be between `308.642` and `4864.22`\n col_vals_between(\n columns = c(\"peri\"),\n left = 308.642,\n right = 4864.22\n ) %>%\n # Expect that column `shape` is of type: numeric\n col_is_numeric(\n columns = c(\"shape\")\n ) %>%\n # Expect that values in `shape` should be between `0.0903296` and `0.464125`\n col_vals_between(\n columns = c(\"shape\"),\n left = 0.0903296,\n right = 0.464125\n ) %>%\n # Expect that column `perm` is of type: numeric\n col_is_numeric(\n columns = c(\"perm\")\n ) %>%\n # Expect that values in `perm` should be between `6.3` and `1300`\n col_vals_between(\n columns = c(\"perm\"),\n left = 6.3,\n right = 1300\n ) %>%\n # Expect entirely distinct rows across `area, peri, shape, perm`\n rows_distinct(\n columns = c(\"area\", \"peri\", \"shape\", \"perm\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n area = \"integer\",\n peri = \"numeric\",\n shape = \"numeric\",\n perm = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Fertility` is of type: numeric\n col_is_numeric(\n columns = c(\"Fertility\")\n ) %>%\n # Expect that values in `Fertility` should be between `35` and `92.5`\n col_vals_between(\n columns = c(\"Fertility\"),\n left = 35,\n right = 92.5\n ) %>%\n # Expect that column `Agriculture` is of type: numeric\n col_is_numeric(\n columns = c(\"Agriculture\")\n ) %>%\n # Expect that values in `Agriculture` should be between `1.2` and `89.7`\n col_vals_between(\n columns = c(\"Agriculture\"),\n left = 1.2,\n right = 89.7\n ) %>%\n # Expect that column `Examination` is of type: integer\n col_is_integer(\n columns = c(\"Examination\")\n ) %>%\n # Expect that values in `Examination` should be between `3` and `37`\n col_vals_between(\n columns = c(\"Examination\"),\n left = 3,\n right = 37\n ) %>%\n # Expect that column `Education` is of type: integer\n col_is_integer(\n columns = c(\"Education\")\n ) %>%\n # Expect that values in `Education` should be between `1` and `53`\n col_vals_between(\n columns = c(\"Education\"),\n left = 1,\n right = 53\n ) %>%\n # Expect that column `Catholic` is of type: numeric\n col_is_numeric(\n columns = c(\"Catholic\")\n ) %>%\n # Expect that values in `Catholic` should be between `2.15` and `100`\n col_vals_between(\n columns = c(\"Catholic\"),\n left = 2.15,\n right = 100\n ) %>%\n # Expect that column `Infant.Mortality` is of type: numeric\n col_is_numeric(\n columns = c(\"Infant.Mortality\")\n ) %>%\n # Expect that values in `Infant.Mortality` should be between `10.8` and `26.6`\n col_vals_between(\n columns = c(\"Infant.Mortality\"),\n left = 10.8,\n right = 26.6\n ) %>%\n # Expect entirely distinct rows across `Fertility, Agriculture, Examination, Education, Catholic, Infant.Mortality`\n rows_distinct(\n columns = c(\"Fertility\", \"Agriculture\", \"Examination\", \"Education\", \"Catholic\", \"Infant.Mortality\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Fertility = \"numeric\",\n Agriculture = \"numeric\",\n Examination = \"integer\",\n Education = \"integer\",\n Catholic = \"numeric\",\n Infant.Mortality = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `Fertility` is of type: numeric\n col_is_numeric(\n columns = c(\"Fertility\")\n ) %>%\n # Expect that values in `Fertility` should be between `35` and `92.5`\n col_vals_between(\n columns = c(\"Fertility\"),\n left = 35,\n right = 92.5\n ) %>%\n # Expect that column `Agriculture` is of type: numeric\n col_is_numeric(\n columns = c(\"Agriculture\")\n ) %>%\n # Expect that values in `Agriculture` should be between `1.2` and `89.7`\n col_vals_between(\n columns = c(\"Agriculture\"),\n left = 1.2,\n right = 89.7\n ) %>%\n # Expect that column `Examination` is of type: integer\n col_is_integer(\n columns = c(\"Examination\")\n ) %>%\n # Expect that values in `Examination` should be between `3` and `37`\n col_vals_between(\n columns = c(\"Examination\"),\n left = 3,\n right = 37\n ) %>%\n # Expect that column `Education` is of type: integer\n col_is_integer(\n columns = c(\"Education\")\n ) %>%\n # Expect that values in `Education` should be between `1` and `53`\n col_vals_between(\n columns = c(\"Education\"),\n left = 1,\n right = 53\n ) %>%\n # Expect that column `Catholic` is of type: numeric\n col_is_numeric(\n columns = c(\"Catholic\")\n ) %>%\n # Expect that values in `Catholic` should be between `2.15` and `100`\n col_vals_between(\n columns = c(\"Catholic\"),\n left = 2.15,\n right = 100\n ) %>%\n # Expect that column `Infant.Mortality` is of type: numeric\n col_is_numeric(\n columns = c(\"Infant.Mortality\")\n ) %>%\n # Expect that values in `Infant.Mortality` should be between `10.8` and `26.6`\n col_vals_between(\n columns = c(\"Infant.Mortality\"),\n left = 10.8,\n right = 26.6\n ) %>%\n # Expect entirely distinct rows across `Fertility, Agriculture, Examination, Education, Catholic, Infant.Mortality`\n rows_distinct(\n columns = c(\"Fertility\", \"Agriculture\", \"Examination\", \"Education\", \"Catholic\", \"Infant.Mortality\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n Fertility = \"numeric\",\n Agriculture = \"numeric\",\n Examination = \"integer\",\n Education = \"integer\",\n Catholic = \"numeric\",\n Infant.Mortality = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `CONT` is of type: numeric\n col_is_numeric(\n columns = c(\"CONT\")\n ) %>%\n # Expect that values in `CONT` should be between `5.7` and `10.6`\n col_vals_between(\n columns = c(\"CONT\"),\n left = 5.7,\n right = 10.6\n ) %>%\n # Expect that column `INTG` is of type: numeric\n col_is_numeric(\n columns = c(\"INTG\")\n ) %>%\n # Expect that values in `INTG` should be between `5.9` and `9.2`\n col_vals_between(\n columns = c(\"INTG\"),\n left = 5.9,\n right = 9.2\n ) %>%\n # Expect that column `DMNR` is of type: numeric\n col_is_numeric(\n columns = c(\"DMNR\")\n ) %>%\n # Expect that values in `DMNR` should be between `4.3` and `9`\n col_vals_between(\n columns = c(\"DMNR\"),\n left = 4.3,\n right = 9\n ) %>%\n # Expect that column `DILG` is of type: numeric\n col_is_numeric(\n columns = c(\"DILG\")\n ) %>%\n # Expect that values in `DILG` should be between `5.1` and `9`\n col_vals_between(\n columns = c(\"DILG\"),\n left = 5.1,\n right = 9\n ) %>%\n # Expect that column `CFMG` is of type: numeric\n col_is_numeric(\n columns = c(\"CFMG\")\n ) %>%\n # Expect that values in `CFMG` should be between `5.4` and `8.7`\n col_vals_between(\n columns = c(\"CFMG\"),\n left = 5.4,\n right = 8.7\n ) %>%\n # Expect that column `DECI` is of type: numeric\n col_is_numeric(\n columns = c(\"DECI\")\n ) %>%\n # Expect that values in `DECI` should be between `5.7` and `8.8`\n col_vals_between(\n columns = c(\"DECI\"),\n left = 5.7,\n right = 8.8\n ) %>%\n # Expect that column `PREP` is of type: numeric\n col_is_numeric(\n columns = c(\"PREP\")\n ) %>%\n # Expect that values in `PREP` should be between `4.8` and `9.1`\n col_vals_between(\n columns = c(\"PREP\"),\n left = 4.8,\n right = 9.1\n ) %>%\n # Expect that column `FAMI` is of type: numeric\n col_is_numeric(\n columns = c(\"FAMI\")\n ) %>%\n # Expect that values in `FAMI` should be between `5.1` and `9.1`\n col_vals_between(\n columns = c(\"FAMI\"),\n left = 5.1,\n right = 9.1\n ) %>%\n # Expect that column `ORAL` is of type: numeric\n col_is_numeric(\n columns = c(\"ORAL\")\n ) %>%\n # Expect that values in `ORAL` should be between `4.7` and `8.9`\n col_vals_between(\n columns = c(\"ORAL\"),\n left = 4.7,\n right = 8.9\n ) %>%\n # Expect that column `WRIT` is of type: numeric\n col_is_numeric(\n columns = c(\"WRIT\")\n ) %>%\n # Expect that values in `WRIT` should be between `4.9` and `9`\n col_vals_between(\n columns = c(\"WRIT\"),\n left = 4.9,\n right = 9\n ) %>%\n # Expect that column `PHYS` is of type: numeric\n col_is_numeric(\n columns = c(\"PHYS\")\n ) %>%\n # Expect that values in `PHYS` should be between `4.7` and `9.1`\n col_vals_between(\n columns = c(\"PHYS\"),\n left = 4.7,\n right = 9.1\n ) %>%\n # Expect that column `RTEN` is of type: numeric\n col_is_numeric(\n columns = c(\"RTEN\")\n ) %>%\n # Expect that values in `RTEN` should be between `4.8` and `9.2`\n col_vals_between(\n columns = c(\"RTEN\"),\n left = 4.8,\n right = 9.2\n ) %>%\n # Expect entirely distinct rows across `CONT, INTG, DMNR, DILG, CFMG, DECI, PREP, FAMI, ORAL, WRIT, PHYS, RTEN`\n rows_distinct(\n columns = c(\"CONT\", \"INTG\", \"DMNR\", \"DILG\", \"CFMG\", \"DECI\", \"PREP\", \"FAMI\", \"ORAL\", \"WRIT\", \"PHYS\", \"RTEN\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n CONT = \"numeric\",\n INTG = \"numeric\",\n DMNR = \"numeric\",\n DILG = \"numeric\",\n CFMG = \"numeric\",\n DECI = \"numeric\",\n PREP = \"numeric\",\n FAMI = \"numeric\",\n ORAL = \"numeric\",\n WRIT = \"numeric\",\n PHYS = \"numeric\",\n RTEN = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `CONT` is of type: numeric\n col_is_numeric(\n columns = c(\"CONT\")\n ) %>%\n # Expect that values in `CONT` should be between `5.7` and `10.6`\n col_vals_between(\n columns = c(\"CONT\"),\n left = 5.7,\n right = 10.6\n ) %>%\n # Expect that column `INTG` is of type: numeric\n col_is_numeric(\n columns = c(\"INTG\")\n ) %>%\n # Expect that values in `INTG` should be between `5.9` and `9.2`\n col_vals_between(\n columns = c(\"INTG\"),\n left = 5.9,\n right = 9.2\n ) %>%\n # Expect that column `DMNR` is of type: numeric\n col_is_numeric(\n columns = c(\"DMNR\")\n ) %>%\n # Expect that values in `DMNR` should be between `4.3` and `9`\n col_vals_between(\n columns = c(\"DMNR\"),\n left = 4.3,\n right = 9\n ) %>%\n # Expect that column `DILG` is of type: numeric\n col_is_numeric(\n columns = c(\"DILG\")\n ) %>%\n # Expect that values in `DILG` should be between `5.1` and `9`\n col_vals_between(\n columns = c(\"DILG\"),\n left = 5.1,\n right = 9\n ) %>%\n # Expect that column `CFMG` is of type: numeric\n col_is_numeric(\n columns = c(\"CFMG\")\n ) %>%\n # Expect that values in `CFMG` should be between `5.4` and `8.7`\n col_vals_between(\n columns = c(\"CFMG\"),\n left = 5.4,\n right = 8.7\n ) %>%\n # Expect that column `DECI` is of type: numeric\n col_is_numeric(\n columns = c(\"DECI\")\n ) %>%\n # Expect that values in `DECI` should be between `5.7` and `8.8`\n col_vals_between(\n columns = c(\"DECI\"),\n left = 5.7,\n right = 8.8\n ) %>%\n # Expect that column `PREP` is of type: numeric\n col_is_numeric(\n columns = c(\"PREP\")\n ) %>%\n # Expect that values in `PREP` should be between `4.8` and `9.1`\n col_vals_between(\n columns = c(\"PREP\"),\n left = 4.8,\n right = 9.1\n ) %>%\n # Expect that column `FAMI` is of type: numeric\n col_is_numeric(\n columns = c(\"FAMI\")\n ) %>%\n # Expect that values in `FAMI` should be between `5.1` and `9.1`\n col_vals_between(\n columns = c(\"FAMI\"),\n left = 5.1,\n right = 9.1\n ) %>%\n # Expect that column `ORAL` is of type: numeric\n col_is_numeric(\n columns = c(\"ORAL\")\n ) %>%\n # Expect that values in `ORAL` should be between `4.7` and `8.9`\n col_vals_between(\n columns = c(\"ORAL\"),\n left = 4.7,\n right = 8.9\n ) %>%\n # Expect that column `WRIT` is of type: numeric\n col_is_numeric(\n columns = c(\"WRIT\")\n ) %>%\n # Expect that values in `WRIT` should be between `4.9` and `9`\n col_vals_between(\n columns = c(\"WRIT\"),\n left = 4.9,\n right = 9\n ) %>%\n # Expect that column `PHYS` is of type: numeric\n col_is_numeric(\n columns = c(\"PHYS\")\n ) %>%\n # Expect that values in `PHYS` should be between `4.7` and `9.1`\n col_vals_between(\n columns = c(\"PHYS\"),\n left = 4.7,\n right = 9.1\n ) %>%\n # Expect that column `RTEN` is of type: numeric\n col_is_numeric(\n columns = c(\"RTEN\")\n ) %>%\n # Expect that values in `RTEN` should be between `4.8` and `9.2`\n col_vals_between(\n columns = c(\"RTEN\"),\n left = 4.8,\n right = 9.2\n ) %>%\n # Expect entirely distinct rows across `CONT, INTG, DMNR, DILG, CFMG, DECI, PREP, FAMI, ORAL, WRIT, PHYS, RTEN`\n rows_distinct(\n columns = c(\"CONT\", \"INTG\", \"DMNR\", \"DILG\", \"CFMG\", \"DECI\", \"PREP\", \"FAMI\", \"ORAL\", \"WRIT\", \"PHYS\", \"RTEN\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n CONT = \"numeric\",\n INTG = \"numeric\",\n DMNR = \"numeric\",\n DILG = \"numeric\",\n CFMG = \"numeric\",\n DECI = \"numeric\",\n PREP = \"numeric\",\n FAMI = \"numeric\",\n ORAL = \"numeric\",\n WRIT = \"numeric\",\n PHYS = \"numeric\",\n RTEN = \"numeric\"\n )\n ) %>%\n interrogate()\n\nagent" # draft validations for data tables can be generated in different languages Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `a` is of type: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Expect that values in `a` should be between `1` and `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Expect that column `b` is of type: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Expect that column `c` is of type: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Expect that values in `c` should be between `2` and `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Expect that column `d` is of type: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Expect that values in `d` should be between `108.34` and `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Expect that column `e` is of type: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Expect that column `f` is of type: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `a` is of type: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Expect that values in `a` should be between `1` and `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Expect that column `b` is of type: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Expect that column `c` is of type: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Expect that values in `c` should be between `2` and `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Expect that column `d` is of type: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Expect that values in `d` should be between `108.34` and `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Expect that column `e` is of type: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Expect that column `f` is of type: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"fr\",\n locale = \"fr\"\n ) %>%\n # On s'attend à ce que la colonne `a` soit de type : integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # On s'attend à ce que les valeurs de `a` soient comprises entre `1` et `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # On s'attend à ce que la colonne `b` soit de type : character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # On s'attend à ce que la colonne `c` soit de type : numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # On s'attend à ce que les valeurs de `c` soient comprises entre `2` et `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # On s'attend à ce que la colonne `d` soit de type : numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # On s'attend à ce que les valeurs de `d` soient comprises entre `108.34` et `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # On s'attend à ce que la colonne `e` soit de type : logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # On s'attend à ce que la colonne `f` soit de type : character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # On s'attend à ce que les schémas de colonnes correspondent\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"fr\",\n locale = \"fr\"\n ) %>%\n # On s'attend à ce que la colonne `a` soit de type : integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # On s'attend à ce que les valeurs de `a` soient comprises entre `1` et `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # On s'attend à ce que la colonne `b` soit de type : character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # On s'attend à ce que la colonne `c` soit de type : numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # On s'attend à ce que les valeurs de `c` soient comprises entre `2` et `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # On s'attend à ce que la colonne `d` soit de type : numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # On s'attend à ce que les valeurs de `d` soient comprises entre `108.34` et `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # On s'attend à ce que la colonne `e` soit de type : logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # On s'attend à ce que la colonne `f` soit de type : character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # On s'attend à ce que les schémas de colonnes correspondent\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"de\",\n locale = \"de\"\n ) %>%\n # Erwarten Sie, dass die Spalte `a` vom Typ integer ist\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Erwarten Sie, dass die Werte in `a` zwischen `1` und `8` liegen sollten\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Erwarten Sie, dass die Spalte `b` vom Typ character ist\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Erwarten Sie, dass die Spalte `c` vom Typ numeric ist\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Erwarten Sie, dass die Werte in `c` zwischen `2` und `9` liegen sollten\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Erwarten Sie, dass die Spalte `d` vom Typ numeric ist\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Erwarten Sie, dass die Werte in `d` zwischen `108.34` und `9999.99` liegen sollten\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Erwarten Sie, dass die Spalte `e` vom Typ logical ist\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Erwarten Sie, dass die Spalte `f` vom Typ character ist\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Erwarten Sie, dass die Spaltenschemata übereinstimmen\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"de\",\n locale = \"de\"\n ) %>%\n # Erwarten Sie, dass die Spalte `a` vom Typ integer ist\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Erwarten Sie, dass die Werte in `a` zwischen `1` und `8` liegen sollten\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Erwarten Sie, dass die Spalte `b` vom Typ character ist\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Erwarten Sie, dass die Spalte `c` vom Typ numeric ist\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Erwarten Sie, dass die Werte in `c` zwischen `2` und `9` liegen sollten\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Erwarten Sie, dass die Spalte `d` vom Typ numeric ist\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Erwarten Sie, dass die Werte in `d` zwischen `108.34` und `9999.99` liegen sollten\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Erwarten Sie, dass die Spalte `e` vom Typ logical ist\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Erwarten Sie, dass die Spalte `f` vom Typ character ist\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Erwarten Sie, dass die Spaltenschemata übereinstimmen\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"it\",\n locale = \"it\"\n ) %>%\n # Aspettati che la colonna `a` sia di tipo: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Aspettati che i valori in `a` siano compresi tra `1` e `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Aspettati che la colonna `b` sia di tipo: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Aspettati che la colonna `c` sia di tipo: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Aspettati che i valori in `c` siano compresi tra `2` e `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Aspettati che la colonna `d` sia di tipo: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Aspettati che i valori in `d` siano compresi tra `108.34` e `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Aspettati che la colonna `e` sia di tipo: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Aspettati che la colonna `f` sia di tipo: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Aspettati che gli schemi di colonna corrispondano\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"it\",\n locale = \"it\"\n ) %>%\n # Aspettati che la colonna `a` sia di tipo: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Aspettati che i valori in `a` siano compresi tra `1` e `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Aspettati che la colonna `b` sia di tipo: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Aspettati che la colonna `c` sia di tipo: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Aspettati che i valori in `c` siano compresi tra `2` e `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Aspettati che la colonna `d` sia di tipo: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Aspettati che i valori in `d` siano compresi tra `108.34` e `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Aspettati che la colonna `e` sia di tipo: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Aspettati che la colonna `f` sia di tipo: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Aspettati che gli schemi di colonna corrispondano\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"es\",\n locale = \"es\"\n ) %>%\n # Se espera que la columna `a` sea del tipo \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Se espera que los valores en `a` estén entre `1` y `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Se espera que la columna `b` sea del tipo \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Se espera que la columna `c` sea del tipo \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Se espera que los valores en `c` estén entre `2` y `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Se espera que la columna `d` sea del tipo \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Se espera que los valores en `d` estén entre `108.34` y `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Se espera que la columna `e` sea del tipo \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Se espera que la columna `f` sea del tipo \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Se espera que los esquemas de columna coincidan\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"es\",\n locale = \"es\"\n ) %>%\n # Se espera que la columna `a` sea del tipo \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Se espera que los valores en `a` estén entre `1` y `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Se espera que la columna `b` sea del tipo \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Se espera que la columna `c` sea del tipo \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Se espera que los valores en `c` estén entre `2` y `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Se espera que la columna `d` sea del tipo \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Se espera que los valores en `d` estén entre `108.34` y `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Se espera que la columna `e` sea del tipo \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Se espera que la columna `f` sea del tipo \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Se espera que los esquemas de columna coincidan\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"pt\",\n locale = \"pt\"\n ) %>%\n # Espera-se que coluna `a` seja do tipo \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Espera-se que os valores em `a` devem estar entre `1` e `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Espera-se que coluna `b` seja do tipo \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Espera-se que coluna `c` seja do tipo \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Espera-se que os valores em `c` devem estar entre `2` e `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Espera-se que coluna `d` seja do tipo \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Espera-se que os valores em `d` devem estar entre `108.34` e `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Espera-se que coluna `e` seja do tipo \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Espera-se que coluna `f` seja do tipo \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Espera-se que os esquemas de coluna concordem\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"pt\",\n locale = \"pt\"\n ) %>%\n # Espera-se que coluna `a` seja do tipo \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Espera-se que os valores em `a` devem estar entre `1` e `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Espera-se que coluna `b` seja do tipo \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Espera-se que coluna `c` seja do tipo \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Espera-se que os valores em `c` devem estar entre `2` e `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Espera-se que coluna `d` seja do tipo \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Espera-se que os valores em `d` devem estar entre `108.34` e `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Espera-se que coluna `e` seja do tipo \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Espera-se que coluna `f` seja do tipo \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Espera-se que os esquemas de coluna concordem\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"tr\",\n locale = \"tr\"\n ) %>%\n # `a` sütununun şu türde olmasını bekleyin: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Beklenti, `a` 'deki değerlerin `1` ile `8` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # `b` sütununun şu türde olmasını bekleyin: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # `c` sütununun şu türde olmasını bekleyin: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Beklenti, `c` 'deki değerlerin `2` ile `9` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # `d` sütununun şu türde olmasını bekleyin: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Beklenti, `d` 'deki değerlerin `108.34` ile `9999.99` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # `e` sütununun şu türde olmasını bekleyin: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # `f` sütununun şu türde olmasını bekleyin: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Sütun şemalarının eşleşmesini bekleyin\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"tr\",\n locale = \"tr\"\n ) %>%\n # `a` sütununun şu türde olmasını bekleyin: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Beklenti, `a` 'deki değerlerin `1` ile `8` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # `b` sütununun şu türde olmasını bekleyin: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # `c` sütununun şu türde olmasını bekleyin: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Beklenti, `c` 'deki değerlerin `2` ile `9` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # `d` sütununun şu türde olmasını bekleyin: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Beklenti, `d` 'deki değerlerin `108.34` ile `9999.99` arasında olması gerektiğidir\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # `e` sütununun şu türde olmasını bekleyin: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # `f` sütununun şu türde olmasını bekleyin: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Sütun şemalarının eşleşmesini bekleyin\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"zh\",\n locale = \"zh\"\n ) %>%\n # 预期列 `a`为类型 \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # 预期在`a` 的值应当在 `1`和 `8`之间。 \n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # 预期列 `b`为类型 \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # 预期列 `c`为类型 \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # 预期在`c` 的值应当在 `2`和 `9`之间。 \n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # 预期列 `d`为类型 \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # 预期在`d` 的值应当在 `108.34`和 `9999.99`之间。 \n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # 预期列 `e`为类型 \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # 预期列 `f`为类型 \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # 预期列模式（column schemas）应当匹配。 \n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"zh\",\n locale = \"zh\"\n ) %>%\n # 预期列 `a`为类型 \n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # 预期在`a` 的值应当在 `1`和 `8`之间。 \n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # 预期列 `b`为类型 \n col_is_character(\n columns = c(\"b\")\n ) %>%\n # 预期列 `c`为类型 \n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # 预期在`c` 的值应当在 `2`和 `9`之间。 \n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # 预期列 `d`为类型 \n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # 预期在`d` 的值应当在 `108.34`和 `9999.99`之间。 \n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # 预期列 `e`为类型 \n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # 预期列 `f`为类型 \n col_is_character(\n columns = c(\"f\")\n ) %>%\n # 预期列模式（column schemas）应当匹配。 \n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"ru\",\n locale = \"ru\"\n ) %>%\n # Ожидайте, что столбец `a` имеет тип: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Ожидайте, что значения в `a` должны находиться между `1` и `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Ожидайте, что столбец `b` имеет тип: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Ожидайте, что столбец `c` имеет тип: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Ожидайте, что значения в `c` должны находиться между `2` и `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Ожидайте, что столбец `d` имеет тип: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Ожидайте, что значения в `d` должны находиться между `108.34` и `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Ожидайте, что столбец `e` имеет тип: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Ожидайте, что столбец `f` имеет тип: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Ожидайте, что схемы столбцов совпадают\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"ru\",\n locale = \"ru\"\n ) %>%\n # Ожидайте, что столбец `a` имеет тип: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Ожидайте, что значения в `a` должны находиться между `1` и `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Ожидайте, что столбец `b` имеет тип: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Ожидайте, что столбец `c` имеет тип: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Ожидайте, что значения в `c` должны находиться между `2` и `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Ожидайте, что столбец `d` имеет тип: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Ожидайте, что значения в `d` должны находиться между `108.34` и `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Ожидайте, что столбец `e` имеет тип: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Ожидайте, что столбец `f` имеет тип: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Ожидайте, что схемы столбцов совпадают\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"pl\",\n locale = \"pl\"\n ) %>%\n # Spodziewaj się, że kolumna `a` jest typu: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Spodziewaj się, że wartości w `a` powinny zawierac się między `1` a `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Spodziewaj się, że kolumna `b` jest typu: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Spodziewaj się, że kolumna `c` jest typu: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Spodziewaj się, że wartości w `c` powinny zawierac się między `2` a `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Spodziewaj się, że kolumna `d` jest typu: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Spodziewaj się, że wartości w `d` powinny zawierac się między `108.34` a `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Spodziewaj się, że kolumna `e` jest typu: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Spodziewaj się, że kolumna `f` jest typu: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Spodziewaj się, że schematy kolumn będa zgodne\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"pl\",\n locale = \"pl\"\n ) %>%\n # Spodziewaj się, że kolumna `a` jest typu: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Spodziewaj się, że wartości w `a` powinny zawierac się między `1` a `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Spodziewaj się, że kolumna `b` jest typu: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Spodziewaj się, że kolumna `c` jest typu: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Spodziewaj się, że wartości w `c` powinny zawierac się między `2` a `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Spodziewaj się, że kolumna `d` jest typu: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Spodziewaj się, że wartości w `d` powinny zawierac się między `108.34` a `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Spodziewaj się, że kolumna `e` jest typu: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Spodziewaj się, że kolumna `f` jest typu: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Spodziewaj się, że schematy kolumn będa zgodne\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"da\",\n locale = \"da\"\n ) %>%\n # Forvent at kolonne `a` er af typen: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Forvent at værdierne i `a` skal være imellem `1` og `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Forvent at kolonne `b` er af typen: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Forvent at kolonne `c` er af typen: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Forvent at værdierne i `c` skal være imellem `2` og `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Forvent at kolonne `d` er af typen: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Forvent at værdierne i `d` skal være imellem `108.34` og `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Forvent at kolonne `e` er af typen: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Forvent at kolonne `f` er af typen: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Forvent overensstemmelse med kolonne schema\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"da\",\n locale = \"da\"\n ) %>%\n # Forvent at kolonne `a` er af typen: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Forvent at værdierne i `a` skal være imellem `1` og `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Forvent at kolonne `b` er af typen: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Forvent at kolonne `c` er af typen: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Forvent at værdierne i `c` skal være imellem `2` og `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Forvent at kolonne `d` er af typen: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Forvent at værdierne i `d` skal være imellem `108.34` og `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Forvent at kolonne `e` er af typen: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Forvent at kolonne `f` er af typen: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Forvent overensstemmelse med kolonne schema\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"sv\",\n locale = \"sv\"\n ) %>%\n # Förvänta dig att kolumn `a` är av typen: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Förvänta dig att värdena i `a` ligger mellan `1` och `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Förvänta dig att kolumn `b` är av typen: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Förvänta dig att kolumn `c` är av typen: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Förvänta dig att värdena i `c` ligger mellan `2` och `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Förvänta dig att kolumn `d` är av typen: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Förvänta dig att värdena i `d` ligger mellan `108.34` och `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Förvänta dig att kolumn `e` är av typen: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Förvänta dig att kolumn `f` är av typen: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Förvänta överensstämmelse med kolumn schema\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"sv\",\n locale = \"sv\"\n ) %>%\n # Förvänta dig att kolumn `a` är av typen: integer\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Förvänta dig att värdena i `a` ligger mellan `1` och `8`\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Förvänta dig att kolumn `b` är av typen: character\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Förvänta dig att kolumn `c` är av typen: numeric\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Förvänta dig att värdena i `c` ligger mellan `2` och `9`\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Förvänta dig att kolumn `d` är av typen: numeric\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Förvänta dig att värdena i `d` ligger mellan `108.34` och `9999.99`\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Förvänta dig att kolumn `e` är av typen: logical\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Förvänta dig att kolumn `f` är av typen: character\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Förvänta överensstämmelse med kolumn schema\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"nl\",\n locale = \"nl\"\n ) %>%\n # Verwacht dat de kolom `a` van het type integer is\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Verwacht dat de waarden in `a` tussen `1` en `8` moeten liggen\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Verwacht dat de kolom `b` van het type character is\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Verwacht dat de kolom `c` van het type numeric is\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Verwacht dat de waarden in `c` tussen `2` en `9` moeten liggen\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Verwacht dat de kolom `d` van het type numeric is\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Verwacht dat de waarden in `d` tussen `108.34` en `9999.99` moeten liggen\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Verwacht dat de kolom `e` van het type logical is\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Verwacht dat de kolom `f` van het type character is\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Verwacht dat de kolomschema's overeenkomen\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\",\n lang = \"nl\",\n locale = \"nl\"\n ) %>%\n # Verwacht dat de kolom `a` van het type integer is\n col_is_integer(\n columns = c(\"a\")\n ) %>%\n # Verwacht dat de waarden in `a` tussen `1` en `8` moeten liggen\n col_vals_between(\n columns = c(\"a\"),\n left = 1,\n right = 8\n ) %>%\n # Verwacht dat de kolom `b` van het type character is\n col_is_character(\n columns = c(\"b\")\n ) %>%\n # Verwacht dat de kolom `c` van het type numeric is\n col_is_numeric(\n columns = c(\"c\")\n ) %>%\n # Verwacht dat de waarden in `c` tussen `2` en `9` moeten liggen\n col_vals_between(\n columns = c(\"c\"),\n left = 2,\n right = 9,\n na_pass = TRUE\n ) %>%\n # Verwacht dat de kolom `d` van het type numeric is\n col_is_numeric(\n columns = c(\"d\")\n ) %>%\n # Verwacht dat de waarden in `d` tussen `108.34` en `9999.99` moeten liggen\n col_vals_between(\n columns = c(\"d\"),\n left = 108.34,\n right = 9999.99\n ) %>%\n # Verwacht dat de kolom `e` van het type logical is\n col_is_logical(\n columns = c(\"e\")\n ) %>%\n # Verwacht dat de kolom `f` van het type character is\n col_is_character(\n columns = c(\"f\")\n ) %>%\n # Verwacht dat de kolomschema's overeenkomen\n col_schema_match(\n schema = col_schema(\n date_time = c(\"POSIXct\", \"POSIXt\"),\n date = \"Date\",\n a = \"integer\",\n b = \"character\",\n c = \"numeric\",\n d = \"numeric\",\n e = \"logical\",\n f = \"character\"\n )\n ) %>%\n interrogate()\n\nagent" # draft validations for data tables can be generated in .Rmd format Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `country_name` is of type: character\n col_is_character(\n columns = c(\"country_name\")\n ) %>%\n # Expect that values in `country_name` should be in the set of `Aruba`, `Afghanistan`, `Angola` (and 212 more)\n col_vals_in_set(\n columns = c(\"country_name\"),\n set = c(\"Aruba\", \"Afghanistan\", \"Angola\", \"Albania\", \"Andorra\", \"United Arab Emirates\", \"Argentina\", \"Armenia\", \"American Samoa\", \"Antigua & Barbuda\", \"Australia\", \"Austria\", \"Azerbaijan\", \"Burundi\", \"Belgium\", \"Benin\", \"Burkina Faso\", \"Bangladesh\", \"Bulgaria\", \"Bahrain\", \"Bahamas\", \"Bosnia & Herzegovina\", \"Belarus\", \"Belize\", \"Bermuda\", \"Bolivia\", \"Brazil\", \"Barbados\", \"Brunei\", \"Bhutan\", \"Botswana\", \"Central African Republic\", \"Canada\", \"Switzerland\", \"Chile\", \"China\", \"Cote d'Ivoire\", \"Cameroon\", \"Congo (DRC)\", \"Congo (Republic)\", \"Colombia\", \"Comoros\", \"Cape Verde\", \"Costa Rica\", \"Cuba\", \"Curacao\", \"Cayman Islands\", \"Cyprus\", \"Czech Republic\", \"Germany\", \"Djibouti\", \"Dominica\", \"Denmark\", \"Dominican Republic\", \"Algeria\", \"Ecuador\", \"Egypt\", \"Eritrea\", \"Spain\", \"Estonia\", \"Ethiopia\", \"Finland\", \"Fiji\", \"France\", \"Faroe Islands\", \"Micronesia\", \"Gabon\", \"United Kingdom\", \"Georgia\", \"Ghana\", \"Gibraltar\", \"Guinea\", \"Gambia\", \"Guinea-Bissau\", \"Equatorial Guinea\", \"Greece\", \"Grenada\", \"Greenland\", \"Guatemala\", \"Guam\", \"Guyana\", \"Hong Kong\", \"Honduras\", \"Croatia\", \"Haiti\", \"Hungary\", \"Indonesia\", \"Isle of Man\", \"India\", \"Ireland\", \"Iran\", \"Iraq\", \"Iceland\", \"Israel\", \"Italy\", \"Jamaica\", \"Jordan\", \"Japan\", \"Kazakhstan\", \"Kenya\", \"Kyrgyzstan\", \"Cambodia\", \"Kiribati\", \"St. Kitts & Nevis\", \"South Korea\", \"Kuwait\", \"Laos\", \"Lebanon\", \"Liberia\", \"Libya\", \"St. Lucia\", \"Liechtenstein\", \"Sri Lanka\", \"Lesotho\", \"Lithuania\", \"Luxembourg\", \"Latvia\", \"Macao\", \"St. Martin\", \"Morocco\", \"Monaco\", \"Moldova\", \"Madagascar\", \"Maldives\", \"Mexico\", \"Marshall Islands\", \"North Macedonia\", \"Mali\", \"Malta\", \"Myanmar\", \"Montenegro\", \"Mongolia\", \"Northern Mariana Islands\", \"Mozambique\", \"Mauritania\", \"Mauritius\", \"Malawi\", \"Malaysia\", \"Namibia\", \"New Caledonia\", \"Niger\", \"Nigeria\", \"Nicaragua\", \"Netherlands\", \"Norway\", \"Nepal\", \"Nauru\", \"New Zealand\", \"Oman\", \"Pakistan\", \"Panama\", \"Peru\", \"Philippines\", \"Palau\", \"Papua New Guinea\", \"Poland\", \"Puerto Rico\", \"North Korea\", \"Portugal\", \"Paraguay\", \"Palestine\", \"French Polynesia\", \"Qatar\", \"Romania\", \"Russia\", \"Rwanda\", \"Saudi Arabia\", \"Sudan\", \"Senegal\", \"Singapore\", \"Solomon Islands\", \"Sierra Leone\", \"El Salvador\", \"San Marino\", \"Somalia\", \"Serbia\", \"South Sudan\", \"Sao Tome & Principe\", \"Suriname\", \"Slovakia\", \"Slovenia\", \"Sweden\", \"Eswatini\", \"Sint Maarten\", \"Seychelles\", \"Syria\", \"Turks & Caicos Islands\", \"Chad\", \"Togo\", \"Thailand\", \"Tajikistan\", \"Turkmenistan\", \"East Timor\", \"Tonga\", \"Trinidad & Tobago\", \"Tunisia\", \"Turkey\", \"Tuvalu\", \"Tanzania\", \"Uganda\", \"Ukraine\", \"Uruguay\", \"United States\", \"Uzbekistan\", \"St. Vincent & Grenadines\", \"Venezuela\", \"British Virgin Islands\", \"U.S. Virgin Islands\", \"Vietnam\", \"Vanuatu\", \"Samoa\", \"Yemen\", \"South Africa\", \"Zambia\", \"Zimbabwe\")\n ) %>%\n # Expect that column `country_code_2` is of type: character\n col_is_character(\n columns = c(\"country_code_2\")\n ) %>%\n # Expect that values in `country_code_2` should be in the set of `AD`, `AE`, `AF` (and 246 more)\n col_vals_in_set(\n columns = c(\"country_code_2\"),\n set = c(\"AD\", \"AE\", \"AF\", \"AG\", \"AI\", \"AL\", \"AM\", \"AO\", \"AQ\", \"AR\", \"AS\", \"AT\", \"AU\", \"AW\", \"AX\", \"AZ\", \"BA\", \"BB\", \"BD\", \"BE\", \"BF\", \"BG\", \"BH\", \"BI\", \"BJ\", \"BL\", \"BM\", \"BN\", \"BO\", \"BQ\", \"BR\", \"BS\", \"BT\", \"BV\", \"BW\", \"BY\", \"BZ\", \"CA\", \"CC\", \"CD\", \"CF\", \"CG\", \"CH\", \"CI\", \"CK\", \"CL\", \"CM\", \"CN\", \"CO\", \"CR\", \"CU\", \"CV\", \"CW\", \"CX\", \"CY\", \"CZ\", \"DE\", \"DJ\", \"DK\", \"DM\", \"DO\", \"DZ\", \"EC\", \"EE\", \"EG\", \"EH\", \"ER\", \"ES\", \"ET\", \"FI\", \"FJ\", \"FK\", \"FM\", \"FO\", \"FR\", \"GA\", \"GB\", \"GD\", \"GE\", \"GF\", \"GG\", \"GH\", \"GI\", \"GL\", \"GM\", \"GN\", \"GP\", \"GQ\", \"GR\", \"GS\", \"GT\", \"GU\", \"GW\", \"GY\", \"HK\", \"HM\", \"HN\", \"HR\", \"HT\", \"HU\", \"ID\", \"IE\", \"IL\", \"IM\", \"IN\", \"IO\", \"IQ\", \"IR\", \"IS\", \"IT\", \"JE\", \"JM\", \"JO\", \"JP\", \"KE\", \"KG\", \"KH\", \"KI\", \"KM\", \"KN\", \"KP\", \"KR\", \"KW\", \"KY\", \"KZ\", \"LA\", \"LB\", \"LC\", \"LI\", \"LK\", \"LR\", \"LS\", \"LT\", \"LU\", \"LV\", \"LY\", \"MA\", \"MC\", \"MD\", \"ME\", \"MF\", \"MG\", \"MH\", \"MK\", \"ML\", \"MM\", \"MN\", \"MO\", \"MP\", \"MQ\", \"MR\", \"MS\", \"MT\", \"MU\", \"MV\", \"MW\", \"MX\", \"MY\", \"MZ\", \"NA\", \"NC\", \"NE\", \"NF\", \"NG\", \"NI\", \"NL\", \"NO\", \"NP\", \"NR\", \"NU\", \"NZ\", \"OM\", \"PA\", \"PE\", \"PF\", \"PG\", \"PH\", \"PK\", \"PL\", \"PM\", \"PN\", \"PR\", \"PS\", \"PT\", \"PW\", \"PY\", \"QA\", \"RE\", \"RO\", \"RS\", \"RU\", \"RW\", \"SA\", \"SB\", \"SC\", \"SD\", \"SE\", \"SG\", \"SH\", \"SI\", \"SJ\", \"SK\", \"SL\", \"SM\", \"SN\", \"SO\", \"SR\", \"SS\", \"ST\", \"SV\", \"SX\", \"SY\", \"SZ\", \"TC\", \"TD\", \"TF\", \"TG\", \"TH\", \"TJ\", \"TK\", \"TL\", \"TM\", \"TN\", \"TO\", \"TR\", \"TT\", \"TV\", \"TW\", \"TZ\", \"UA\", \"UG\", \"UM\", \"US\", \"UY\", \"UZ\", \"VA\", \"VC\", \"VE\", \"VG\", \"VI\", \"VN\", \"VU\", \"WF\", \"WS\", \"YE\", \"YT\", \"ZA\", \"ZM\", \"ZW\")\n ) %>%\n # Expect that column `country_code_3` is of type: character\n col_is_character(\n columns = c(\"country_code_3\")\n ) %>%\n # Expect that values in `country_code_3` should be in the set of `AND`, `ARE`, `AFG` (and 246 more)\n col_vals_in_set(\n columns = c(\"country_code_3\"),\n set = c(\"AND\", \"ARE\", \"AFG\", \"ATG\", \"AIA\", \"ALB\", \"ARM\", \"AGO\", \"ATA\", \"ARG\", \"ASM\", \"AUT\", \"AUS\", \"ABW\", \"ALA\", \"AZE\", \"BIH\", \"BRB\", \"BGD\", \"BEL\", \"BFA\", \"BGR\", \"BHR\", \"BDI\", \"BEN\", \"BLM\", \"BMU\", \"BRN\", \"BOL\", \"BES\", \"BRA\", \"BHS\", \"BTN\", \"BVT\", \"BWA\", \"BLR\", \"BLZ\", \"CAN\", \"CCK\", \"COD\", \"CAF\", \"COG\", \"CHE\", \"CIV\", \"COK\", \"CHL\", \"CMR\", \"CHN\", \"COL\", \"CRI\", \"CUB\", \"CPV\", \"CUW\", \"CXR\", \"CYP\", \"CZE\", \"DEU\", \"DJI\", \"DNK\", \"DMA\", \"DOM\", \"DZA\", \"ECU\", \"EST\", \"EGY\", \"ESH\", \"ERI\", \"ESP\", \"ETH\", \"FIN\", \"FJI\", \"FLK\", \"FSM\", \"FRO\", \"FRA\", \"GAB\", \"GBR\", \"GRD\", \"GEO\", \"GUF\", \"GGY\", \"GHA\", \"GIB\", \"GRL\", \"GMB\", \"GIN\", \"GLP\", \"GNQ\", \"GRC\", \"SGS\", \"GTM\", \"GUM\", \"GNB\", \"GUY\", \"HKG\", \"HMD\", \"HND\", \"HRV\", \"HTI\", \"HUN\", \"IDN\", \"IRL\", \"ISR\", \"IMN\", \"IND\", \"IOT\", \"IRQ\", \"IRN\", \"ISL\", \"ITA\", \"JEY\", \"JAM\", \"JOR\", \"JPN\", \"KEN\", \"KGZ\", \"KHM\", \"KIR\", \"COM\", \"KNA\", \"PRK\", \"KOR\", \"KWT\", \"CYM\", \"KAZ\", \"LAO\", \"LBN\", \"LCA\", \"LIE\", \"LKA\", \"LBR\", \"LSO\", \"LTU\", \"LUX\", \"LVA\", \"LBY\", \"MAR\", \"MCO\", \"MDA\", \"MNE\", \"MAF\", \"MDG\", \"MHL\", \"MKD\", \"MLI\", \"MMR\", \"MNG\", \"MAC\", \"MNP\", \"MTQ\", \"MRT\", \"MSR\", \"MLT\", \"MUS\", \"MDV\", \"MWI\", \"MEX\", \"MYS\", \"MOZ\", \"NAM\", \"NCL\", \"NER\", \"NFK\", \"NGA\", \"NIC\", \"NLD\", \"NOR\", \"NPL\", \"NRU\", \"NIU\", \"NZL\", \"OMN\", \"PAN\", \"PER\", \"PYF\", \"PNG\", \"PHL\", \"PAK\", \"POL\", \"SPM\", \"PCN\", \"PRI\", \"PSE\", \"PRT\", \"PLW\", \"PRY\", \"QAT\", \"REU\", \"ROU\", \"SRB\", \"RUS\", \"RWA\", \"SAU\", \"SLB\", \"SYC\", \"SDN\", \"SWE\", \"SGP\", \"SHN\", \"SVN\", \"SJM\", \"SVK\", \"SLE\", \"SMR\", \"SEN\", \"SOM\", \"SUR\", \"SSD\", \"STP\", \"SLV\", \"SXM\", \"SYR\", \"SWZ\", \"TCA\", \"TCD\", \"ATF\", \"TGO\", \"THA\", \"TJK\", \"TKL\", \"TLS\", \"TKM\", \"TUN\", \"TON\", \"TUR\", \"TTO\", \"TUV\", \"TWN\", \"TZA\", \"UKR\", \"UGA\", \"UMI\", \"USA\", \"URY\", \"UZB\", \"VAT\", \"VCT\", \"VEN\", \"VGB\", \"VIR\", \"VNM\", \"VUT\", \"WLF\", \"WSM\", \"YEM\", \"MYT\", \"ZAF\", \"ZMB\", \"ZWE\")\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `1960` and `2023`\n col_vals_between(\n columns = c(\"year\"),\n left = 1960,\n right = 2023\n ) %>%\n # Expect that column `population` is of type: integer\n col_is_integer(\n columns = c(\"population\")\n ) %>%\n # Expect that values in `population` should be between `2646` and `1428627663`\n col_vals_between(\n columns = c(\"population\"),\n left = 2646,\n right = 1428627700,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `country_name, country_code_2, country_code_3, year, population`\n rows_distinct(\n columns = c(\"country_name\", \"country_code_2\", \"country_code_3\", \"year\", \"population\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n country_name = \"character\",\n country_code_2 = \"character\",\n country_code_3 = \"character\",\n year = \"integer\",\n population = \"integer\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `country_name` is of type: character\n col_is_character(\n columns = c(\"country_name\")\n ) %>%\n # Expect that values in `country_name` should be in the set of `Aruba`, `Afghanistan`, `Angola` (and 212 more)\n col_vals_in_set(\n columns = c(\"country_name\"),\n set = c(\"Aruba\", \"Afghanistan\", \"Angola\", \"Albania\", \"Andorra\", \"United Arab Emirates\", \"Argentina\", \"Armenia\", \"American Samoa\", \"Antigua & Barbuda\", \"Australia\", \"Austria\", \"Azerbaijan\", \"Burundi\", \"Belgium\", \"Benin\", \"Burkina Faso\", \"Bangladesh\", \"Bulgaria\", \"Bahrain\", \"Bahamas\", \"Bosnia & Herzegovina\", \"Belarus\", \"Belize\", \"Bermuda\", \"Bolivia\", \"Brazil\", \"Barbados\", \"Brunei\", \"Bhutan\", \"Botswana\", \"Central African Republic\", \"Canada\", \"Switzerland\", \"Chile\", \"China\", \"Cote d'Ivoire\", \"Cameroon\", \"Congo (DRC)\", \"Congo (Republic)\", \"Colombia\", \"Comoros\", \"Cape Verde\", \"Costa Rica\", \"Cuba\", \"Curacao\", \"Cayman Islands\", \"Cyprus\", \"Czech Republic\", \"Germany\", \"Djibouti\", \"Dominica\", \"Denmark\", \"Dominican Republic\", \"Algeria\", \"Ecuador\", \"Egypt\", \"Eritrea\", \"Spain\", \"Estonia\", \"Ethiopia\", \"Finland\", \"Fiji\", \"France\", \"Faroe Islands\", \"Micronesia\", \"Gabon\", \"United Kingdom\", \"Georgia\", \"Ghana\", \"Gibraltar\", \"Guinea\", \"Gambia\", \"Guinea-Bissau\", \"Equatorial Guinea\", \"Greece\", \"Grenada\", \"Greenland\", \"Guatemala\", \"Guam\", \"Guyana\", \"Hong Kong\", \"Honduras\", \"Croatia\", \"Haiti\", \"Hungary\", \"Indonesia\", \"Isle of Man\", \"India\", \"Ireland\", \"Iran\", \"Iraq\", \"Iceland\", \"Israel\", \"Italy\", \"Jamaica\", \"Jordan\", \"Japan\", \"Kazakhstan\", \"Kenya\", \"Kyrgyzstan\", \"Cambodia\", \"Kiribati\", \"St. Kitts & Nevis\", \"South Korea\", \"Kuwait\", \"Laos\", \"Lebanon\", \"Liberia\", \"Libya\", \"St. Lucia\", \"Liechtenstein\", \"Sri Lanka\", \"Lesotho\", \"Lithuania\", \"Luxembourg\", \"Latvia\", \"Macao\", \"St. Martin\", \"Morocco\", \"Monaco\", \"Moldova\", \"Madagascar\", \"Maldives\", \"Mexico\", \"Marshall Islands\", \"North Macedonia\", \"Mali\", \"Malta\", \"Myanmar\", \"Montenegro\", \"Mongolia\", \"Northern Mariana Islands\", \"Mozambique\", \"Mauritania\", \"Mauritius\", \"Malawi\", \"Malaysia\", \"Namibia\", \"New Caledonia\", \"Niger\", \"Nigeria\", \"Nicaragua\", \"Netherlands\", \"Norway\", \"Nepal\", \"Nauru\", \"New Zealand\", \"Oman\", \"Pakistan\", \"Panama\", \"Peru\", \"Philippines\", \"Palau\", \"Papua New Guinea\", \"Poland\", \"Puerto Rico\", \"North Korea\", \"Portugal\", \"Paraguay\", \"Palestine\", \"French Polynesia\", \"Qatar\", \"Romania\", \"Russia\", \"Rwanda\", \"Saudi Arabia\", \"Sudan\", \"Senegal\", \"Singapore\", \"Solomon Islands\", \"Sierra Leone\", \"El Salvador\", \"San Marino\", \"Somalia\", \"Serbia\", \"South Sudan\", \"Sao Tome & Principe\", \"Suriname\", \"Slovakia\", \"Slovenia\", \"Sweden\", \"Eswatini\", \"Sint Maarten\", \"Seychelles\", \"Syria\", \"Turks & Caicos Islands\", \"Chad\", \"Togo\", \"Thailand\", \"Tajikistan\", \"Turkmenistan\", \"East Timor\", \"Tonga\", \"Trinidad & Tobago\", \"Tunisia\", \"Turkey\", \"Tuvalu\", \"Tanzania\", \"Uganda\", \"Ukraine\", \"Uruguay\", \"United States\", \"Uzbekistan\", \"St. Vincent & Grenadines\", \"Venezuela\", \"British Virgin Islands\", \"U.S. Virgin Islands\", \"Vietnam\", \"Vanuatu\", \"Samoa\", \"Yemen\", \"South Africa\", \"Zambia\", \"Zimbabwe\")\n ) %>%\n # Expect that column `country_code_2` is of type: character\n col_is_character(\n columns = c(\"country_code_2\")\n ) %>%\n # Expect that values in `country_code_2` should be in the set of `AD`, `AE`, `AF` (and 246 more)\n col_vals_in_set(\n columns = c(\"country_code_2\"),\n set = c(\"AD\", \"AE\", \"AF\", \"AG\", \"AI\", \"AL\", \"AM\", \"AO\", \"AQ\", \"AR\", \"AS\", \"AT\", \"AU\", \"AW\", \"AX\", \"AZ\", \"BA\", \"BB\", \"BD\", \"BE\", \"BF\", \"BG\", \"BH\", \"BI\", \"BJ\", \"BL\", \"BM\", \"BN\", \"BO\", \"BQ\", \"BR\", \"BS\", \"BT\", \"BV\", \"BW\", \"BY\", \"BZ\", \"CA\", \"CC\", \"CD\", \"CF\", \"CG\", \"CH\", \"CI\", \"CK\", \"CL\", \"CM\", \"CN\", \"CO\", \"CR\", \"CU\", \"CV\", \"CW\", \"CX\", \"CY\", \"CZ\", \"DE\", \"DJ\", \"DK\", \"DM\", \"DO\", \"DZ\", \"EC\", \"EE\", \"EG\", \"EH\", \"ER\", \"ES\", \"ET\", \"FI\", \"FJ\", \"FK\", \"FM\", \"FO\", \"FR\", \"GA\", \"GB\", \"GD\", \"GE\", \"GF\", \"GG\", \"GH\", \"GI\", \"GL\", \"GM\", \"GN\", \"GP\", \"GQ\", \"GR\", \"GS\", \"GT\", \"GU\", \"GW\", \"GY\", \"HK\", \"HM\", \"HN\", \"HR\", \"HT\", \"HU\", \"ID\", \"IE\", \"IL\", \"IM\", \"IN\", \"IO\", \"IQ\", \"IR\", \"IS\", \"IT\", \"JE\", \"JM\", \"JO\", \"JP\", \"KE\", \"KG\", \"KH\", \"KI\", \"KM\", \"KN\", \"KP\", \"KR\", \"KW\", \"KY\", \"KZ\", \"LA\", \"LB\", \"LC\", \"LI\", \"LK\", \"LR\", \"LS\", \"LT\", \"LU\", \"LV\", \"LY\", \"MA\", \"MC\", \"MD\", \"ME\", \"MF\", \"MG\", \"MH\", \"MK\", \"ML\", \"MM\", \"MN\", \"MO\", \"MP\", \"MQ\", \"MR\", \"MS\", \"MT\", \"MU\", \"MV\", \"MW\", \"MX\", \"MY\", \"MZ\", \"NA\", \"NC\", \"NE\", \"NF\", \"NG\", \"NI\", \"NL\", \"NO\", \"NP\", \"NR\", \"NU\", \"NZ\", \"OM\", \"PA\", \"PE\", \"PF\", \"PG\", \"PH\", \"PK\", \"PL\", \"PM\", \"PN\", \"PR\", \"PS\", \"PT\", \"PW\", \"PY\", \"QA\", \"RE\", \"RO\", \"RS\", \"RU\", \"RW\", \"SA\", \"SB\", \"SC\", \"SD\", \"SE\", \"SG\", \"SH\", \"SI\", \"SJ\", \"SK\", \"SL\", \"SM\", \"SN\", \"SO\", \"SR\", \"SS\", \"ST\", \"SV\", \"SX\", \"SY\", \"SZ\", \"TC\", \"TD\", \"TF\", \"TG\", \"TH\", \"TJ\", \"TK\", \"TL\", \"TM\", \"TN\", \"TO\", \"TR\", \"TT\", \"TV\", \"TW\", \"TZ\", \"UA\", \"UG\", \"UM\", \"US\", \"UY\", \"UZ\", \"VA\", \"VC\", \"VE\", \"VG\", \"VI\", \"VN\", \"VU\", \"WF\", \"WS\", \"YE\", \"YT\", \"ZA\", \"ZM\", \"ZW\")\n ) %>%\n # Expect that column `country_code_3` is of type: character\n col_is_character(\n columns = c(\"country_code_3\")\n ) %>%\n # Expect that values in `country_code_3` should be in the set of `AND`, `ARE`, `AFG` (and 246 more)\n col_vals_in_set(\n columns = c(\"country_code_3\"),\n set = c(\"AND\", \"ARE\", \"AFG\", \"ATG\", \"AIA\", \"ALB\", \"ARM\", \"AGO\", \"ATA\", \"ARG\", \"ASM\", \"AUT\", \"AUS\", \"ABW\", \"ALA\", \"AZE\", \"BIH\", \"BRB\", \"BGD\", \"BEL\", \"BFA\", \"BGR\", \"BHR\", \"BDI\", \"BEN\", \"BLM\", \"BMU\", \"BRN\", \"BOL\", \"BES\", \"BRA\", \"BHS\", \"BTN\", \"BVT\", \"BWA\", \"BLR\", \"BLZ\", \"CAN\", \"CCK\", \"COD\", \"CAF\", \"COG\", \"CHE\", \"CIV\", \"COK\", \"CHL\", \"CMR\", \"CHN\", \"COL\", \"CRI\", \"CUB\", \"CPV\", \"CUW\", \"CXR\", \"CYP\", \"CZE\", \"DEU\", \"DJI\", \"DNK\", \"DMA\", \"DOM\", \"DZA\", \"ECU\", \"EST\", \"EGY\", \"ESH\", \"ERI\", \"ESP\", \"ETH\", \"FIN\", \"FJI\", \"FLK\", \"FSM\", \"FRO\", \"FRA\", \"GAB\", \"GBR\", \"GRD\", \"GEO\", \"GUF\", \"GGY\", \"GHA\", \"GIB\", \"GRL\", \"GMB\", \"GIN\", \"GLP\", \"GNQ\", \"GRC\", \"SGS\", \"GTM\", \"GUM\", \"GNB\", \"GUY\", \"HKG\", \"HMD\", \"HND\", \"HRV\", \"HTI\", \"HUN\", \"IDN\", \"IRL\", \"ISR\", \"IMN\", \"IND\", \"IOT\", \"IRQ\", \"IRN\", \"ISL\", \"ITA\", \"JEY\", \"JAM\", \"JOR\", \"JPN\", \"KEN\", \"KGZ\", \"KHM\", \"KIR\", \"COM\", \"KNA\", \"PRK\", \"KOR\", \"KWT\", \"CYM\", \"KAZ\", \"LAO\", \"LBN\", \"LCA\", \"LIE\", \"LKA\", \"LBR\", \"LSO\", \"LTU\", \"LUX\", \"LVA\", \"LBY\", \"MAR\", \"MCO\", \"MDA\", \"MNE\", \"MAF\", \"MDG\", \"MHL\", \"MKD\", \"MLI\", \"MMR\", \"MNG\", \"MAC\", \"MNP\", \"MTQ\", \"MRT\", \"MSR\", \"MLT\", \"MUS\", \"MDV\", \"MWI\", \"MEX\", \"MYS\", \"MOZ\", \"NAM\", \"NCL\", \"NER\", \"NFK\", \"NGA\", \"NIC\", \"NLD\", \"NOR\", \"NPL\", \"NRU\", \"NIU\", \"NZL\", \"OMN\", \"PAN\", \"PER\", \"PYF\", \"PNG\", \"PHL\", \"PAK\", \"POL\", \"SPM\", \"PCN\", \"PRI\", \"PSE\", \"PRT\", \"PLW\", \"PRY\", \"QAT\", \"REU\", \"ROU\", \"SRB\", \"RUS\", \"RWA\", \"SAU\", \"SLB\", \"SYC\", \"SDN\", \"SWE\", \"SGP\", \"SHN\", \"SVN\", \"SJM\", \"SVK\", \"SLE\", \"SMR\", \"SEN\", \"SOM\", \"SUR\", \"SSD\", \"STP\", \"SLV\", \"SXM\", \"SYR\", \"SWZ\", \"TCA\", \"TCD\", \"ATF\", \"TGO\", \"THA\", \"TJK\", \"TKL\", \"TLS\", \"TKM\", \"TUN\", \"TON\", \"TUR\", \"TTO\", \"TUV\", \"TWN\", \"TZA\", \"UKR\", \"UGA\", \"UMI\", \"USA\", \"URY\", \"UZB\", \"VAT\", \"VCT\", \"VEN\", \"VGB\", \"VIR\", \"VNM\", \"VUT\", \"WLF\", \"WSM\", \"YEM\", \"MYT\", \"ZAF\", \"ZMB\", \"ZWE\")\n ) %>%\n # Expect that column `year` is of type: integer\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `1960` and `2023`\n col_vals_between(\n columns = c(\"year\"),\n left = 1960,\n right = 2023\n ) %>%\n # Expect that column `population` is of type: integer\n col_is_integer(\n columns = c(\"population\")\n ) %>%\n # Expect that values in `population` should be between `2646` and `1428627663`\n col_vals_between(\n columns = c(\"population\"),\n left = 2646,\n right = 1428627700,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `country_name, country_code_2, country_code_3, year, population`\n rows_distinct(\n columns = c(\"country_name\", \"country_code_2\", \"country_code_3\", \"year\", \"population\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n country_name = \"character\",\n country_code_2 = \"character\",\n country_code_3 = \"character\",\n year = \"integer\",\n population = \"integer\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `latitude` is of type: numeric\n col_is_numeric(\n columns = c(\"latitude\")\n ) %>%\n # Expect that values in `latitude` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"latitude\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `month` is of type: factor\n col_is_factor(\n columns = c(\"month\")\n ) %>%\n # Expect that column `tst` is of type: character\n col_is_character(\n columns = c(\"tst\")\n ) %>%\n # Expect that column `sza` is of type: numeric\n col_is_numeric(\n columns = c(\"sza\")\n ) %>%\n # Expect that values in `sza` should be between `1.9` and `89.7`\n col_vals_between(\n columns = c(\"sza\"),\n left = 1.9,\n right = 89.7,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `latitude, month, tst, sza`\n rows_distinct(\n columns = c(\"latitude\", \"month\", \"tst\", \"sza\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n latitude = \"numeric\",\n month = \"factor\",\n tst = \"character\",\n sza = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `latitude` is of type: numeric\n col_is_numeric(\n columns = c(\"latitude\")\n ) %>%\n # Expect that values in `latitude` should be between `-90` and `90`\n col_vals_between(\n columns = c(\"latitude\"),\n left = -90,\n right = 90\n ) %>%\n # Expect that column `month` is of type: factor\n col_is_factor(\n columns = c(\"month\")\n ) %>%\n # Expect that column `tst` is of type: character\n col_is_character(\n columns = c(\"tst\")\n ) %>%\n # Expect that column `sza` is of type: numeric\n col_is_numeric(\n columns = c(\"sza\")\n ) %>%\n # Expect that values in `sza` should be between `1.9` and `89.7`\n col_vals_between(\n columns = c(\"sza\"),\n left = 1.9,\n right = 89.7,\n na_pass = TRUE\n ) %>%\n # Expect entirely distinct rows across `latitude, month, tst, sza`\n rows_distinct(\n columns = c(\"latitude\", \"month\", \"tst\", \"sza\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n latitude = \"numeric\",\n month = \"factor\",\n tst = \"character\",\n sza = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mfr` is of type: character\n col_is_character(\n columns = c(\"mfr\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `year` is of type: numeric\n col_is_numeric(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2014` and `2017`\n col_vals_between(\n columns = c(\"year\"),\n left = 2014,\n right = 2017\n ) %>%\n # Expect that column `trim` is of type: character\n col_is_character(\n columns = c(\"trim\")\n ) %>%\n # Expect that column `bdy_style` is of type: character\n col_is_character(\n columns = c(\"bdy_style\")\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `259` and `949`\n col_vals_between(\n columns = c(\"hp\"),\n left = 259,\n right = 949\n ) %>%\n # Expect that column `hp_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"hp_rpm\")\n ) %>%\n # Expect that values in `hp_rpm` should be between `5000` and `9000`\n col_vals_between(\n columns = c(\"hp_rpm\"),\n left = 5000,\n right = 9000\n ) %>%\n # Expect that column `trq` is of type: numeric\n col_is_numeric(\n columns = c(\"trq\")\n ) %>%\n # Expect that values in `trq` should be between `243` and `664`\n col_vals_between(\n columns = c(\"trq\"),\n left = 243,\n right = 664\n ) %>%\n # Expect that column `trq_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"trq_rpm\")\n ) %>%\n # Expect that values in `trq_rpm` should be between `1400` and `6750`\n col_vals_between(\n columns = c(\"trq_rpm\"),\n left = 1400,\n right = 6750,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_c` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_c\")\n ) %>%\n # Expect that values in `mpg_c` should be between `11` and `28`\n col_vals_between(\n columns = c(\"mpg_c\"),\n left = 11,\n right = 28,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_h` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_h\")\n ) %>%\n # Expect that values in `mpg_h` should be between `16` and `30`\n col_vals_between(\n columns = c(\"mpg_h\"),\n left = 16,\n right = 30,\n na_pass = TRUE\n ) %>%\n # Expect that column `drivetrain` is of type: character\n col_is_character(\n columns = c(\"drivetrain\")\n ) %>%\n # Expect that column `trsmn` is of type: character\n col_is_character(\n columns = c(\"trsmn\")\n ) %>%\n # Expect that column `ctry_origin` is of type: character\n col_is_character(\n columns = c(\"ctry_origin\")\n ) %>%\n # Expect that values in `ctry_origin` should be in the set of `United States`, `Italy`, `Japan` (and 2 more)\n col_vals_in_set(\n columns = c(\"ctry_origin\"),\n set = c(\"United States\", \"Italy\", \"Japan\", \"United Kingdom\", \"Germany\")\n ) %>%\n # Expect that column `msrp` is of type: numeric\n col_is_numeric(\n columns = c(\"msrp\")\n ) %>%\n # Expect that values in `msrp` should be between `53900` and `1416362`\n col_vals_between(\n columns = c(\"msrp\"),\n left = 53900,\n right = 1416362\n ) %>%\n # Expect entirely distinct rows across `mfr, model, year, trim, bdy_style, hp, hp_rpm, trq, trq_rpm, mpg_c, mpg_h, drivetrain, trsmn, ctry_origin, msrp`\n rows_distinct(\n columns = c(\"mfr\", \"model\", \"year\", \"trim\", \"bdy_style\", \"hp\", \"hp_rpm\", \"trq\", \"trq_rpm\", \"mpg_c\", \"mpg_h\", \"drivetrain\", \"trsmn\", \"ctry_origin\", \"msrp\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mfr = \"character\",\n model = \"character\",\n year = \"numeric\",\n trim = \"character\",\n bdy_style = \"character\",\n hp = \"numeric\",\n hp_rpm = \"numeric\",\n trq = \"numeric\",\n trq_rpm = \"numeric\",\n mpg_c = \"numeric\",\n mpg_h = \"numeric\",\n drivetrain = \"character\",\n trsmn = \"character\",\n ctry_origin = \"character\",\n msrp = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `mfr` is of type: character\n col_is_character(\n columns = c(\"mfr\")\n ) %>%\n # Expect that column `model` is of type: character\n col_is_character(\n columns = c(\"model\")\n ) %>%\n # Expect that column `year` is of type: numeric\n col_is_numeric(\n columns = c(\"year\")\n ) %>%\n # Expect that values in `year` should be between `2014` and `2017`\n col_vals_between(\n columns = c(\"year\"),\n left = 2014,\n right = 2017\n ) %>%\n # Expect that column `trim` is of type: character\n col_is_character(\n columns = c(\"trim\")\n ) %>%\n # Expect that column `bdy_style` is of type: character\n col_is_character(\n columns = c(\"bdy_style\")\n ) %>%\n # Expect that column `hp` is of type: numeric\n col_is_numeric(\n columns = c(\"hp\")\n ) %>%\n # Expect that values in `hp` should be between `259` and `949`\n col_vals_between(\n columns = c(\"hp\"),\n left = 259,\n right = 949\n ) %>%\n # Expect that column `hp_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"hp_rpm\")\n ) %>%\n # Expect that values in `hp_rpm` should be between `5000` and `9000`\n col_vals_between(\n columns = c(\"hp_rpm\"),\n left = 5000,\n right = 9000\n ) %>%\n # Expect that column `trq` is of type: numeric\n col_is_numeric(\n columns = c(\"trq\")\n ) %>%\n # Expect that values in `trq` should be between `243` and `664`\n col_vals_between(\n columns = c(\"trq\"),\n left = 243,\n right = 664\n ) %>%\n # Expect that column `trq_rpm` is of type: numeric\n col_is_numeric(\n columns = c(\"trq_rpm\")\n ) %>%\n # Expect that values in `trq_rpm` should be between `1400` and `6750`\n col_vals_between(\n columns = c(\"trq_rpm\"),\n left = 1400,\n right = 6750,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_c` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_c\")\n ) %>%\n # Expect that values in `mpg_c` should be between `11` and `28`\n col_vals_between(\n columns = c(\"mpg_c\"),\n left = 11,\n right = 28,\n na_pass = TRUE\n ) %>%\n # Expect that column `mpg_h` is of type: numeric\n col_is_numeric(\n columns = c(\"mpg_h\")\n ) %>%\n # Expect that values in `mpg_h` should be between `16` and `30`\n col_vals_between(\n columns = c(\"mpg_h\"),\n left = 16,\n right = 30,\n na_pass = TRUE\n ) %>%\n # Expect that column `drivetrain` is of type: character\n col_is_character(\n columns = c(\"drivetrain\")\n ) %>%\n # Expect that column `trsmn` is of type: character\n col_is_character(\n columns = c(\"trsmn\")\n ) %>%\n # Expect that column `ctry_origin` is of type: character\n col_is_character(\n columns = c(\"ctry_origin\")\n ) %>%\n # Expect that values in `ctry_origin` should be in the set of `United States`, `Italy`, `Japan` (and 2 more)\n col_vals_in_set(\n columns = c(\"ctry_origin\"),\n set = c(\"United States\", \"Italy\", \"Japan\", \"United Kingdom\", \"Germany\")\n ) %>%\n # Expect that column `msrp` is of type: numeric\n col_is_numeric(\n columns = c(\"msrp\")\n ) %>%\n # Expect that values in `msrp` should be between `53900` and `1416362`\n col_vals_between(\n columns = c(\"msrp\"),\n left = 53900,\n right = 1416362\n ) %>%\n # Expect entirely distinct rows across `mfr, model, year, trim, bdy_style, hp, hp_rpm, trq, trq_rpm, mpg_c, mpg_h, drivetrain, trsmn, ctry_origin, msrp`\n rows_distinct(\n columns = c(\"mfr\", \"model\", \"year\", \"trim\", \"bdy_style\", \"hp\", \"hp_rpm\", \"trq\", \"trq_rpm\", \"mpg_c\", \"mpg_h\", \"drivetrain\", \"trsmn\", \"ctry_origin\", \"msrp\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n mfr = \"character\",\n model = \"character\",\n year = \"numeric\",\n trim = \"character\",\n bdy_style = \"character\",\n hp = \"numeric\",\n hp_rpm = \"numeric\",\n trq = \"numeric\",\n trq_rpm = \"numeric\",\n mpg_c = \"numeric\",\n mpg_h = \"numeric\",\n drivetrain = \"character\",\n trsmn = \"character\",\n ctry_origin = \"character\",\n msrp = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `open` is of type: numeric\n col_is_numeric(\n columns = c(\"open\")\n ) %>%\n # Expect that values in `open` should be between `16.66` and `2130.3601`\n col_vals_between(\n columns = c(\"open\"),\n left = 16.66,\n right = 2130.3601\n ) %>%\n # Expect that column `high` is of type: numeric\n col_is_numeric(\n columns = c(\"high\")\n ) %>%\n # Expect that values in `high` should be between `16.66` and `2134.72`\n col_vals_between(\n columns = c(\"high\"),\n left = 16.66,\n right = 2134.72\n ) %>%\n # Expect that column `low` is of type: numeric\n col_is_numeric(\n columns = c(\"low\")\n ) %>%\n # Expect that values in `low` should be between `16.66` and `2126.0601`\n col_vals_between(\n columns = c(\"low\"),\n left = 16.66,\n right = 2126.0601\n ) %>%\n # Expect that column `close` is of type: numeric\n col_is_numeric(\n columns = c(\"close\")\n ) %>%\n # Expect that values in `close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `680000` and `11456230400`\n col_vals_between(\n columns = c(\"volume\"),\n left = 680000,\n right = 11456230000\n ) %>%\n # Expect that column `adj_close` is of type: numeric\n col_is_numeric(\n columns = c(\"adj_close\")\n ) %>%\n # Expect that values in `adj_close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"adj_close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect entirely distinct rows across `date, open, high, low, close, volume, adj_close`\n rows_distinct(\n columns = c(\"date\", \"open\", \"high\", \"low\", \"close\", \"volume\", \"adj_close\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n open = \"numeric\",\n high = \"numeric\",\n low = \"numeric\",\n close = \"numeric\",\n volume = \"numeric\",\n adj_close = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `open` is of type: numeric\n col_is_numeric(\n columns = c(\"open\")\n ) %>%\n # Expect that values in `open` should be between `16.66` and `2130.3601`\n col_vals_between(\n columns = c(\"open\"),\n left = 16.66,\n right = 2130.3601\n ) %>%\n # Expect that column `high` is of type: numeric\n col_is_numeric(\n columns = c(\"high\")\n ) %>%\n # Expect that values in `high` should be between `16.66` and `2134.72`\n col_vals_between(\n columns = c(\"high\"),\n left = 16.66,\n right = 2134.72\n ) %>%\n # Expect that column `low` is of type: numeric\n col_is_numeric(\n columns = c(\"low\")\n ) %>%\n # Expect that values in `low` should be between `16.66` and `2126.0601`\n col_vals_between(\n columns = c(\"low\"),\n left = 16.66,\n right = 2126.0601\n ) %>%\n # Expect that column `close` is of type: numeric\n col_is_numeric(\n columns = c(\"close\")\n ) %>%\n # Expect that values in `close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect that column `volume` is of type: numeric\n col_is_numeric(\n columns = c(\"volume\")\n ) %>%\n # Expect that values in `volume` should be between `680000` and `11456230400`\n col_vals_between(\n columns = c(\"volume\"),\n left = 680000,\n right = 11456230000\n ) %>%\n # Expect that column `adj_close` is of type: numeric\n col_is_numeric(\n columns = c(\"adj_close\")\n ) %>%\n # Expect that values in `adj_close` should be between `16.66` and `2130.8201`\n col_vals_between(\n columns = c(\"adj_close\"),\n left = 16.66,\n right = 2130.8201\n ) %>%\n # Expect entirely distinct rows across `date, open, high, low, close, volume, adj_close`\n rows_distinct(\n columns = c(\"date\", \"open\", \"high\", \"low\", \"close\", \"volume\", \"adj_close\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n date = \"Date\",\n open = \"numeric\",\n high = \"numeric\",\n low = \"numeric\",\n close = \"numeric\",\n volume = \"numeric\",\n adj_close = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `id` is of type: character\n col_is_character(\n columns = c(\"id\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `size` is of type: character\n col_is_character(\n columns = c(\"size\")\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `price` is of type: numeric\n col_is_numeric(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `9.75` and `35.95`\n col_vals_between(\n columns = c(\"price\"),\n left = 9.75,\n right = 35.95\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n id = \"character\",\n date = \"character\",\n time = \"character\",\n name = \"character\",\n size = \"character\",\n type = \"character\",\n price = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `id` is of type: character\n col_is_character(\n columns = c(\"id\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `name` is of type: character\n col_is_character(\n columns = c(\"name\")\n ) %>%\n # Expect that column `size` is of type: character\n col_is_character(\n columns = c(\"size\")\n ) %>%\n # Expect that column `type` is of type: character\n col_is_character(\n columns = c(\"type\")\n ) %>%\n # Expect that column `price` is of type: numeric\n col_is_numeric(\n columns = c(\"price\")\n ) %>%\n # Expect that values in `price` should be between `9.75` and `35.95`\n col_vals_between(\n columns = c(\"price\"),\n left = 9.75,\n right = 35.95\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n id = \"character\",\n date = \"character\",\n time = \"character\",\n name = \"character\",\n size = \"character\",\n type = \"character\",\n price = \"numeric\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" --- Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `num` is of type: numeric\n col_is_numeric(\n columns = c(\"num\")\n ) %>%\n # Expect that values in `num` should be between `0.1111` and `8880000`\n col_vals_between(\n columns = c(\"num\"),\n left = 0.1111,\n right = 8880000,\n na_pass = TRUE\n ) %>%\n # Expect that column `char` is of type: character\n col_is_character(\n columns = c(\"char\")\n ) %>%\n # Expect that column `fctr` is of type: factor\n col_is_factor(\n columns = c(\"fctr\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `datetime` is of type: character\n col_is_character(\n columns = c(\"datetime\")\n ) %>%\n # Expect that column `currency` is of type: numeric\n col_is_numeric(\n columns = c(\"currency\")\n ) %>%\n # Expect that values in `currency` should be between `0.44` and `65100`\n col_vals_between(\n columns = c(\"currency\"),\n left = 0.44,\n right = 65100,\n na_pass = TRUE\n ) %>%\n # Expect that column `row` is of type: character\n col_is_character(\n columns = c(\"row\")\n ) %>%\n # Expect that column `group` is of type: character\n col_is_character(\n columns = c(\"group\")\n ) %>%\n # Expect entirely distinct rows across `num, char, fctr, date, time, datetime, currency, row, group`\n rows_distinct(\n columns = c(\"num\", \"char\", \"fctr\", \"date\", \"time\", \"datetime\", \"currency\", \"row\", \"group\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n num = \"numeric\",\n char = \"character\",\n fctr = \"factor\",\n date = \"character\",\n time = \"character\",\n datetime = \"character\",\n currency = \"numeric\",\n row = \"character\",\n group = \"character\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" + [1] "---\ntitle: \"tbl\"\noutput: html_document\n---\n\n```{r setup, include=FALSE}\nknitr::opts_chunk$set(echo = TRUE)\nlibrary(pointblank)\n```\n\n\n```{r create_agent, echo=TRUE}\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n # Expect that column `num` is of type: numeric\n col_is_numeric(\n columns = c(\"num\")\n ) %>%\n # Expect that values in `num` should be between `0.1111` and `8880000`\n col_vals_between(\n columns = c(\"num\"),\n left = 0.1111,\n right = 8880000,\n na_pass = TRUE\n ) %>%\n # Expect that column `char` is of type: character\n col_is_character(\n columns = c(\"char\")\n ) %>%\n # Expect that column `fctr` is of type: factor\n col_is_factor(\n columns = c(\"fctr\")\n ) %>%\n # Expect that column `date` is of type: character\n col_is_character(\n columns = c(\"date\")\n ) %>%\n # Expect that column `time` is of type: character\n col_is_character(\n columns = c(\"time\")\n ) %>%\n # Expect that column `datetime` is of type: character\n col_is_character(\n columns = c(\"datetime\")\n ) %>%\n # Expect that column `currency` is of type: numeric\n col_is_numeric(\n columns = c(\"currency\")\n ) %>%\n # Expect that values in `currency` should be between `0.44` and `65100`\n col_vals_between(\n columns = c(\"currency\"),\n left = 0.44,\n right = 65100,\n na_pass = TRUE\n ) %>%\n # Expect that column `row` is of type: character\n col_is_character(\n columns = c(\"row\")\n ) %>%\n # Expect that column `group` is of type: character\n col_is_character(\n columns = c(\"group\")\n ) %>%\n # Expect entirely distinct rows across `num, char, fctr, date, time, datetime, currency, row, group`\n rows_distinct(\n columns = c(\"num\", \"char\", \"fctr\", \"date\", \"time\", \"datetime\", \"currency\", \"row\", \"group\")\n ) %>%\n # Expect that column schemas match\n col_schema_match(\n schema = col_schema(\n num = \"numeric\",\n char = \"character\",\n fctr = \"factor\",\n date = \"character\",\n time = \"character\",\n datetime = \"character\",\n currency = \"numeric\",\n row = \"character\",\n group = \"character\"\n )\n ) %>%\n interrogate()\n```\n\n\n```{r print_agent, echo=FALSE}\nagent\n```\n" # draft validations for data tables can be generated without comments Code readLines(con = path) %>% paste0(collapse = "\n") Output - [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn_at = 0.05,\n stop_at = 0.10\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n col_is_character(\n columns = c(\"country_name\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_name\"),\n set = c(\"Aruba\", \"Afghanistan\", \"Angola\", \"Albania\", \"Andorra\", \"United Arab Emirates\", \"Argentina\", \"Armenia\", \"American Samoa\", \"Antigua & Barbuda\", \"Australia\", \"Austria\", \"Azerbaijan\", \"Burundi\", \"Belgium\", \"Benin\", \"Burkina Faso\", \"Bangladesh\", \"Bulgaria\", \"Bahrain\", \"Bahamas\", \"Bosnia & Herzegovina\", \"Belarus\", \"Belize\", \"Bermuda\", \"Bolivia\", \"Brazil\", \"Barbados\", \"Brunei\", \"Bhutan\", \"Botswana\", \"Central African Republic\", \"Canada\", \"Switzerland\", \"Chile\", \"China\", \"Cote d'Ivoire\", \"Cameroon\", \"Congo (DRC)\", \"Congo (Republic)\", \"Colombia\", \"Comoros\", \"Cape Verde\", \"Costa Rica\", \"Cuba\", \"Curacao\", \"Cayman Islands\", \"Cyprus\", \"Czech Republic\", \"Germany\", \"Djibouti\", \"Dominica\", \"Denmark\", \"Dominican Republic\", \"Algeria\", \"Ecuador\", \"Egypt\", \"Eritrea\", \"Spain\", \"Estonia\", \"Ethiopia\", \"Finland\", \"Fiji\", \"France\", \"Faroe Islands\", \"Micronesia\", \"Gabon\", \"United Kingdom\", \"Georgia\", \"Ghana\", \"Gibraltar\", \"Guinea\", \"Gambia\", \"Guinea-Bissau\", \"Equatorial Guinea\", \"Greece\", \"Grenada\", \"Greenland\", \"Guatemala\", \"Guam\", \"Guyana\", \"Hong Kong\", \"Honduras\", \"Croatia\", \"Haiti\", \"Hungary\", \"Indonesia\", \"Isle of Man\", \"India\", \"Ireland\", \"Iran\", \"Iraq\", \"Iceland\", \"Israel\", \"Italy\", \"Jamaica\", \"Jordan\", \"Japan\", \"Kazakhstan\", \"Kenya\", \"Kyrgyzstan\", \"Cambodia\", \"Kiribati\", \"St. Kitts & Nevis\", \"South Korea\", \"Kuwait\", \"Laos\", \"Lebanon\", \"Liberia\", \"Libya\", \"St. Lucia\", \"Liechtenstein\", \"Sri Lanka\", \"Lesotho\", \"Lithuania\", \"Luxembourg\", \"Latvia\", \"Macao\", \"St. Martin\", \"Morocco\", \"Monaco\", \"Moldova\", \"Madagascar\", \"Maldives\", \"Mexico\", \"Marshall Islands\", \"North Macedonia\", \"Mali\", \"Malta\", \"Myanmar\", \"Montenegro\", \"Mongolia\", \"Northern Mariana Islands\", \"Mozambique\", \"Mauritania\", \"Mauritius\", \"Malawi\", \"Malaysia\", \"Namibia\", \"New Caledonia\", \"Niger\", \"Nigeria\", \"Nicaragua\", \"Netherlands\", \"Norway\", \"Nepal\", \"Nauru\", \"New Zealand\", \"Oman\", \"Pakistan\", \"Panama\", \"Peru\", \"Philippines\", \"Palau\", \"Papua New Guinea\", \"Poland\", \"Puerto Rico\", \"North Korea\", \"Portugal\", \"Paraguay\", \"Palestine\", \"French Polynesia\", \"Qatar\", \"Romania\", \"Russia\", \"Rwanda\", \"Saudi Arabia\", \"Sudan\", \"Senegal\", \"Singapore\", \"Solomon Islands\", \"Sierra Leone\", \"El Salvador\", \"San Marino\", \"Somalia\", \"Serbia\", \"South Sudan\", \"Sao Tome & Principe\", \"Suriname\", \"Slovakia\", \"Slovenia\", \"Sweden\", \"Eswatini\", \"Sint Maarten\", \"Seychelles\", \"Syria\", \"Turks & Caicos Islands\", \"Chad\", \"Togo\", \"Thailand\", \"Tajikistan\", \"Turkmenistan\", \"East Timor\", \"Tonga\", \"Trinidad & Tobago\", \"Tunisia\", \"Turkey\", \"Tuvalu\", \"Tanzania\", \"Uganda\", \"Ukraine\", \"Uruguay\", \"United States\", \"Uzbekistan\", \"St. Vincent & Grenadines\", \"Venezuela\", \"British Virgin Islands\", \"U.S. Virgin Islands\", \"Vietnam\", \"Vanuatu\", \"Samoa\", \"Yemen\", \"South Africa\", \"Zambia\", \"Zimbabwe\")\n ) %>%\n col_is_character(\n columns = c(\"country_code_2\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_code_2\"),\n set = c(\"AD\", \"AE\", \"AF\", \"AG\", \"AI\", \"AL\", \"AM\", \"AO\", \"AQ\", \"AR\", \"AS\", \"AT\", \"AU\", \"AW\", \"AX\", \"AZ\", \"BA\", \"BB\", \"BD\", \"BE\", \"BF\", \"BG\", \"BH\", \"BI\", \"BJ\", \"BL\", \"BM\", \"BN\", \"BO\", \"BQ\", \"BR\", \"BS\", \"BT\", \"BV\", \"BW\", \"BY\", \"BZ\", \"CA\", \"CC\", \"CD\", \"CF\", \"CG\", \"CH\", \"CI\", \"CK\", \"CL\", \"CM\", \"CN\", \"CO\", \"CR\", \"CU\", \"CV\", \"CW\", \"CX\", \"CY\", \"CZ\", \"DE\", \"DJ\", \"DK\", \"DM\", \"DO\", \"DZ\", \"EC\", \"EE\", \"EG\", \"EH\", \"ER\", \"ES\", \"ET\", \"FI\", \"FJ\", \"FK\", \"FM\", \"FO\", \"FR\", \"GA\", \"GB\", \"GD\", \"GE\", \"GF\", \"GG\", \"GH\", \"GI\", \"GL\", \"GM\", \"GN\", \"GP\", \"GQ\", \"GR\", \"GS\", \"GT\", \"GU\", \"GW\", \"GY\", \"HK\", \"HM\", \"HN\", \"HR\", \"HT\", \"HU\", \"ID\", \"IE\", \"IL\", \"IM\", \"IN\", \"IO\", \"IQ\", \"IR\", \"IS\", \"IT\", \"JE\", \"JM\", \"JO\", \"JP\", \"KE\", \"KG\", \"KH\", \"KI\", \"KM\", \"KN\", \"KP\", \"KR\", \"KW\", \"KY\", \"KZ\", \"LA\", \"LB\", \"LC\", \"LI\", \"LK\", \"LR\", \"LS\", \"LT\", \"LU\", \"LV\", \"LY\", \"MA\", \"MC\", \"MD\", \"ME\", \"MF\", \"MG\", \"MH\", \"MK\", \"ML\", \"MM\", \"MN\", \"MO\", \"MP\", \"MQ\", \"MR\", \"MS\", \"MT\", \"MU\", \"MV\", \"MW\", \"MX\", \"MY\", \"MZ\", \"NA\", \"NC\", \"NE\", \"NF\", \"NG\", \"NI\", \"NL\", \"NO\", \"NP\", \"NR\", \"NU\", \"NZ\", \"OM\", \"PA\", \"PE\", \"PF\", \"PG\", \"PH\", \"PK\", \"PL\", \"PM\", \"PN\", \"PR\", \"PS\", \"PT\", \"PW\", \"PY\", \"QA\", \"RE\", \"RO\", \"RS\", \"RU\", \"RW\", \"SA\", \"SB\", \"SC\", \"SD\", \"SE\", \"SG\", \"SH\", \"SI\", \"SJ\", \"SK\", \"SL\", \"SM\", \"SN\", \"SO\", \"SR\", \"SS\", \"ST\", \"SV\", \"SX\", \"SY\", \"SZ\", \"TC\", \"TD\", \"TF\", \"TG\", \"TH\", \"TJ\", \"TK\", \"TL\", \"TM\", \"TN\", \"TO\", \"TR\", \"TT\", \"TV\", \"TW\", \"TZ\", \"UA\", \"UG\", \"UM\", \"US\", \"UY\", \"UZ\", \"VA\", \"VC\", \"VE\", \"VG\", \"VI\", \"VN\", \"VU\", \"WF\", \"WS\", \"YE\", \"YT\", \"ZA\", \"ZM\", \"ZW\")\n ) %>%\n col_is_character(\n columns = c(\"country_code_3\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_code_3\"),\n set = c(\"AND\", \"ARE\", \"AFG\", \"ATG\", \"AIA\", \"ALB\", \"ARM\", \"AGO\", \"ATA\", \"ARG\", \"ASM\", \"AUT\", \"AUS\", \"ABW\", \"ALA\", \"AZE\", \"BIH\", \"BRB\", \"BGD\", \"BEL\", \"BFA\", \"BGR\", \"BHR\", \"BDI\", \"BEN\", \"BLM\", \"BMU\", \"BRN\", \"BOL\", \"BES\", \"BRA\", \"BHS\", \"BTN\", \"BVT\", \"BWA\", \"BLR\", \"BLZ\", \"CAN\", \"CCK\", \"COD\", \"CAF\", \"COG\", \"CHE\", \"CIV\", \"COK\", \"CHL\", \"CMR\", \"CHN\", \"COL\", \"CRI\", \"CUB\", \"CPV\", \"CUW\", \"CXR\", \"CYP\", \"CZE\", \"DEU\", \"DJI\", \"DNK\", \"DMA\", \"DOM\", \"DZA\", \"ECU\", \"EST\", \"EGY\", \"ESH\", \"ERI\", \"ESP\", \"ETH\", \"FIN\", \"FJI\", \"FLK\", \"FSM\", \"FRO\", \"FRA\", \"GAB\", \"GBR\", \"GRD\", \"GEO\", \"GUF\", \"GGY\", \"GHA\", \"GIB\", \"GRL\", \"GMB\", \"GIN\", \"GLP\", \"GNQ\", \"GRC\", \"SGS\", \"GTM\", \"GUM\", \"GNB\", \"GUY\", \"HKG\", \"HMD\", \"HND\", \"HRV\", \"HTI\", \"HUN\", \"IDN\", \"IRL\", \"ISR\", \"IMN\", \"IND\", \"IOT\", \"IRQ\", \"IRN\", \"ISL\", \"ITA\", \"JEY\", \"JAM\", \"JOR\", \"JPN\", \"KEN\", \"KGZ\", \"KHM\", \"KIR\", \"COM\", \"KNA\", \"PRK\", \"KOR\", \"KWT\", \"CYM\", \"KAZ\", \"LAO\", \"LBN\", \"LCA\", \"LIE\", \"LKA\", \"LBR\", \"LSO\", \"LTU\", \"LUX\", \"LVA\", \"LBY\", \"MAR\", \"MCO\", \"MDA\", \"MNE\", \"MAF\", \"MDG\", \"MHL\", \"MKD\", \"MLI\", \"MMR\", \"MNG\", \"MAC\", \"MNP\", \"MTQ\", \"MRT\", \"MSR\", \"MLT\", \"MUS\", \"MDV\", \"MWI\", \"MEX\", \"MYS\", \"MOZ\", \"NAM\", \"NCL\", \"NER\", \"NFK\", \"NGA\", \"NIC\", \"NLD\", \"NOR\", \"NPL\", \"NRU\", \"NIU\", \"NZL\", \"OMN\", \"PAN\", \"PER\", \"PYF\", \"PNG\", \"PHL\", \"PAK\", \"POL\", \"SPM\", \"PCN\", \"PRI\", \"PSE\", \"PRT\", \"PLW\", \"PRY\", \"QAT\", \"REU\", \"ROU\", \"SRB\", \"RUS\", \"RWA\", \"SAU\", \"SLB\", \"SYC\", \"SDN\", \"SWE\", \"SGP\", \"SHN\", \"SVN\", \"SJM\", \"SVK\", \"SLE\", \"SMR\", \"SEN\", \"SOM\", \"SUR\", \"SSD\", \"STP\", \"SLV\", \"SXM\", \"SYR\", \"SWZ\", \"TCA\", \"TCD\", \"ATF\", \"TGO\", \"THA\", \"TJK\", \"TKL\", \"TLS\", \"TKM\", \"TUN\", \"TON\", \"TUR\", \"TTO\", \"TUV\", \"TWN\", \"TZA\", \"UKR\", \"UGA\", \"UMI\", \"USA\", \"URY\", \"UZB\", \"VAT\", \"VCT\", \"VEN\", \"VGB\", \"VIR\", \"VNM\", \"VUT\", \"WLF\", \"WSM\", \"YEM\", \"MYT\", \"ZAF\", \"ZMB\", \"ZWE\")\n ) %>%\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n col_vals_between(\n columns = c(\"year\"),\n left = 1960,\n right = 2023\n ) %>%\n col_is_integer(\n columns = c(\"population\")\n ) %>%\n col_vals_between(\n columns = c(\"population\"),\n left = 2646,\n right = 1428627700,\n na_pass = TRUE\n ) %>%\n rows_distinct(\n columns = c(\"country_name\", \"country_code_2\", \"country_code_3\", \"year\", \"population\")\n ) %>%\n col_schema_match(\n schema = col_schema(\n country_name = \"character\",\n country_code_2 = \"character\",\n country_code_3 = \"character\",\n year = \"integer\",\n population = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" + [1] "library(pointblank)\n\nagent <-\n create_agent(\n tbl = ~ tbl,\n actions = action_levels(\n warn = 0.05,\n error = 0.1\n ),\n tbl_name = \"tbl\",\n label = \"Validation plan generated by `draft_validation()`.\"\n ) %>%\n col_is_character(\n columns = c(\"country_name\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_name\"),\n set = c(\"Aruba\", \"Afghanistan\", \"Angola\", \"Albania\", \"Andorra\", \"United Arab Emirates\", \"Argentina\", \"Armenia\", \"American Samoa\", \"Antigua & Barbuda\", \"Australia\", \"Austria\", \"Azerbaijan\", \"Burundi\", \"Belgium\", \"Benin\", \"Burkina Faso\", \"Bangladesh\", \"Bulgaria\", \"Bahrain\", \"Bahamas\", \"Bosnia & Herzegovina\", \"Belarus\", \"Belize\", \"Bermuda\", \"Bolivia\", \"Brazil\", \"Barbados\", \"Brunei\", \"Bhutan\", \"Botswana\", \"Central African Republic\", \"Canada\", \"Switzerland\", \"Chile\", \"China\", \"Cote d'Ivoire\", \"Cameroon\", \"Congo (DRC)\", \"Congo (Republic)\", \"Colombia\", \"Comoros\", \"Cape Verde\", \"Costa Rica\", \"Cuba\", \"Curacao\", \"Cayman Islands\", \"Cyprus\", \"Czech Republic\", \"Germany\", \"Djibouti\", \"Dominica\", \"Denmark\", \"Dominican Republic\", \"Algeria\", \"Ecuador\", \"Egypt\", \"Eritrea\", \"Spain\", \"Estonia\", \"Ethiopia\", \"Finland\", \"Fiji\", \"France\", \"Faroe Islands\", \"Micronesia\", \"Gabon\", \"United Kingdom\", \"Georgia\", \"Ghana\", \"Gibraltar\", \"Guinea\", \"Gambia\", \"Guinea-Bissau\", \"Equatorial Guinea\", \"Greece\", \"Grenada\", \"Greenland\", \"Guatemala\", \"Guam\", \"Guyana\", \"Hong Kong\", \"Honduras\", \"Croatia\", \"Haiti\", \"Hungary\", \"Indonesia\", \"Isle of Man\", \"India\", \"Ireland\", \"Iran\", \"Iraq\", \"Iceland\", \"Israel\", \"Italy\", \"Jamaica\", \"Jordan\", \"Japan\", \"Kazakhstan\", \"Kenya\", \"Kyrgyzstan\", \"Cambodia\", \"Kiribati\", \"St. Kitts & Nevis\", \"South Korea\", \"Kuwait\", \"Laos\", \"Lebanon\", \"Liberia\", \"Libya\", \"St. Lucia\", \"Liechtenstein\", \"Sri Lanka\", \"Lesotho\", \"Lithuania\", \"Luxembourg\", \"Latvia\", \"Macao\", \"St. Martin\", \"Morocco\", \"Monaco\", \"Moldova\", \"Madagascar\", \"Maldives\", \"Mexico\", \"Marshall Islands\", \"North Macedonia\", \"Mali\", \"Malta\", \"Myanmar\", \"Montenegro\", \"Mongolia\", \"Northern Mariana Islands\", \"Mozambique\", \"Mauritania\", \"Mauritius\", \"Malawi\", \"Malaysia\", \"Namibia\", \"New Caledonia\", \"Niger\", \"Nigeria\", \"Nicaragua\", \"Netherlands\", \"Norway\", \"Nepal\", \"Nauru\", \"New Zealand\", \"Oman\", \"Pakistan\", \"Panama\", \"Peru\", \"Philippines\", \"Palau\", \"Papua New Guinea\", \"Poland\", \"Puerto Rico\", \"North Korea\", \"Portugal\", \"Paraguay\", \"Palestine\", \"French Polynesia\", \"Qatar\", \"Romania\", \"Russia\", \"Rwanda\", \"Saudi Arabia\", \"Sudan\", \"Senegal\", \"Singapore\", \"Solomon Islands\", \"Sierra Leone\", \"El Salvador\", \"San Marino\", \"Somalia\", \"Serbia\", \"South Sudan\", \"Sao Tome & Principe\", \"Suriname\", \"Slovakia\", \"Slovenia\", \"Sweden\", \"Eswatini\", \"Sint Maarten\", \"Seychelles\", \"Syria\", \"Turks & Caicos Islands\", \"Chad\", \"Togo\", \"Thailand\", \"Tajikistan\", \"Turkmenistan\", \"East Timor\", \"Tonga\", \"Trinidad & Tobago\", \"Tunisia\", \"Turkey\", \"Tuvalu\", \"Tanzania\", \"Uganda\", \"Ukraine\", \"Uruguay\", \"United States\", \"Uzbekistan\", \"St. Vincent & Grenadines\", \"Venezuela\", \"British Virgin Islands\", \"U.S. Virgin Islands\", \"Vietnam\", \"Vanuatu\", \"Samoa\", \"Yemen\", \"South Africa\", \"Zambia\", \"Zimbabwe\")\n ) %>%\n col_is_character(\n columns = c(\"country_code_2\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_code_2\"),\n set = c(\"AD\", \"AE\", \"AF\", \"AG\", \"AI\", \"AL\", \"AM\", \"AO\", \"AQ\", \"AR\", \"AS\", \"AT\", \"AU\", \"AW\", \"AX\", \"AZ\", \"BA\", \"BB\", \"BD\", \"BE\", \"BF\", \"BG\", \"BH\", \"BI\", \"BJ\", \"BL\", \"BM\", \"BN\", \"BO\", \"BQ\", \"BR\", \"BS\", \"BT\", \"BV\", \"BW\", \"BY\", \"BZ\", \"CA\", \"CC\", \"CD\", \"CF\", \"CG\", \"CH\", \"CI\", \"CK\", \"CL\", \"CM\", \"CN\", \"CO\", \"CR\", \"CU\", \"CV\", \"CW\", \"CX\", \"CY\", \"CZ\", \"DE\", \"DJ\", \"DK\", \"DM\", \"DO\", \"DZ\", \"EC\", \"EE\", \"EG\", \"EH\", \"ER\", \"ES\", \"ET\", \"FI\", \"FJ\", \"FK\", \"FM\", \"FO\", \"FR\", \"GA\", \"GB\", \"GD\", \"GE\", \"GF\", \"GG\", \"GH\", \"GI\", \"GL\", \"GM\", \"GN\", \"GP\", \"GQ\", \"GR\", \"GS\", \"GT\", \"GU\", \"GW\", \"GY\", \"HK\", \"HM\", \"HN\", \"HR\", \"HT\", \"HU\", \"ID\", \"IE\", \"IL\", \"IM\", \"IN\", \"IO\", \"IQ\", \"IR\", \"IS\", \"IT\", \"JE\", \"JM\", \"JO\", \"JP\", \"KE\", \"KG\", \"KH\", \"KI\", \"KM\", \"KN\", \"KP\", \"KR\", \"KW\", \"KY\", \"KZ\", \"LA\", \"LB\", \"LC\", \"LI\", \"LK\", \"LR\", \"LS\", \"LT\", \"LU\", \"LV\", \"LY\", \"MA\", \"MC\", \"MD\", \"ME\", \"MF\", \"MG\", \"MH\", \"MK\", \"ML\", \"MM\", \"MN\", \"MO\", \"MP\", \"MQ\", \"MR\", \"MS\", \"MT\", \"MU\", \"MV\", \"MW\", \"MX\", \"MY\", \"MZ\", \"NA\", \"NC\", \"NE\", \"NF\", \"NG\", \"NI\", \"NL\", \"NO\", \"NP\", \"NR\", \"NU\", \"NZ\", \"OM\", \"PA\", \"PE\", \"PF\", \"PG\", \"PH\", \"PK\", \"PL\", \"PM\", \"PN\", \"PR\", \"PS\", \"PT\", \"PW\", \"PY\", \"QA\", \"RE\", \"RO\", \"RS\", \"RU\", \"RW\", \"SA\", \"SB\", \"SC\", \"SD\", \"SE\", \"SG\", \"SH\", \"SI\", \"SJ\", \"SK\", \"SL\", \"SM\", \"SN\", \"SO\", \"SR\", \"SS\", \"ST\", \"SV\", \"SX\", \"SY\", \"SZ\", \"TC\", \"TD\", \"TF\", \"TG\", \"TH\", \"TJ\", \"TK\", \"TL\", \"TM\", \"TN\", \"TO\", \"TR\", \"TT\", \"TV\", \"TW\", \"TZ\", \"UA\", \"UG\", \"UM\", \"US\", \"UY\", \"UZ\", \"VA\", \"VC\", \"VE\", \"VG\", \"VI\", \"VN\", \"VU\", \"WF\", \"WS\", \"YE\", \"YT\", \"ZA\", \"ZM\", \"ZW\")\n ) %>%\n col_is_character(\n columns = c(\"country_code_3\")\n ) %>%\n col_vals_in_set(\n columns = c(\"country_code_3\"),\n set = c(\"AND\", \"ARE\", \"AFG\", \"ATG\", \"AIA\", \"ALB\", \"ARM\", \"AGO\", \"ATA\", \"ARG\", \"ASM\", \"AUT\", \"AUS\", \"ABW\", \"ALA\", \"AZE\", \"BIH\", \"BRB\", \"BGD\", \"BEL\", \"BFA\", \"BGR\", \"BHR\", \"BDI\", \"BEN\", \"BLM\", \"BMU\", \"BRN\", \"BOL\", \"BES\", \"BRA\", \"BHS\", \"BTN\", \"BVT\", \"BWA\", \"BLR\", \"BLZ\", \"CAN\", \"CCK\", \"COD\", \"CAF\", \"COG\", \"CHE\", \"CIV\", \"COK\", \"CHL\", \"CMR\", \"CHN\", \"COL\", \"CRI\", \"CUB\", \"CPV\", \"CUW\", \"CXR\", \"CYP\", \"CZE\", \"DEU\", \"DJI\", \"DNK\", \"DMA\", \"DOM\", \"DZA\", \"ECU\", \"EST\", \"EGY\", \"ESH\", \"ERI\", \"ESP\", \"ETH\", \"FIN\", \"FJI\", \"FLK\", \"FSM\", \"FRO\", \"FRA\", \"GAB\", \"GBR\", \"GRD\", \"GEO\", \"GUF\", \"GGY\", \"GHA\", \"GIB\", \"GRL\", \"GMB\", \"GIN\", \"GLP\", \"GNQ\", \"GRC\", \"SGS\", \"GTM\", \"GUM\", \"GNB\", \"GUY\", \"HKG\", \"HMD\", \"HND\", \"HRV\", \"HTI\", \"HUN\", \"IDN\", \"IRL\", \"ISR\", \"IMN\", \"IND\", \"IOT\", \"IRQ\", \"IRN\", \"ISL\", \"ITA\", \"JEY\", \"JAM\", \"JOR\", \"JPN\", \"KEN\", \"KGZ\", \"KHM\", \"KIR\", \"COM\", \"KNA\", \"PRK\", \"KOR\", \"KWT\", \"CYM\", \"KAZ\", \"LAO\", \"LBN\", \"LCA\", \"LIE\", \"LKA\", \"LBR\", \"LSO\", \"LTU\", \"LUX\", \"LVA\", \"LBY\", \"MAR\", \"MCO\", \"MDA\", \"MNE\", \"MAF\", \"MDG\", \"MHL\", \"MKD\", \"MLI\", \"MMR\", \"MNG\", \"MAC\", \"MNP\", \"MTQ\", \"MRT\", \"MSR\", \"MLT\", \"MUS\", \"MDV\", \"MWI\", \"MEX\", \"MYS\", \"MOZ\", \"NAM\", \"NCL\", \"NER\", \"NFK\", \"NGA\", \"NIC\", \"NLD\", \"NOR\", \"NPL\", \"NRU\", \"NIU\", \"NZL\", \"OMN\", \"PAN\", \"PER\", \"PYF\", \"PNG\", \"PHL\", \"PAK\", \"POL\", \"SPM\", \"PCN\", \"PRI\", \"PSE\", \"PRT\", \"PLW\", \"PRY\", \"QAT\", \"REU\", \"ROU\", \"SRB\", \"RUS\", \"RWA\", \"SAU\", \"SLB\", \"SYC\", \"SDN\", \"SWE\", \"SGP\", \"SHN\", \"SVN\", \"SJM\", \"SVK\", \"SLE\", \"SMR\", \"SEN\", \"SOM\", \"SUR\", \"SSD\", \"STP\", \"SLV\", \"SXM\", \"SYR\", \"SWZ\", \"TCA\", \"TCD\", \"ATF\", \"TGO\", \"THA\", \"TJK\", \"TKL\", \"TLS\", \"TKM\", \"TUN\", \"TON\", \"TUR\", \"TTO\", \"TUV\", \"TWN\", \"TZA\", \"UKR\", \"UGA\", \"UMI\", \"USA\", \"URY\", \"UZB\", \"VAT\", \"VCT\", \"VEN\", \"VGB\", \"VIR\", \"VNM\", \"VUT\", \"WLF\", \"WSM\", \"YEM\", \"MYT\", \"ZAF\", \"ZMB\", \"ZWE\")\n ) %>%\n col_is_integer(\n columns = c(\"year\")\n ) %>%\n col_vals_between(\n columns = c(\"year\"),\n left = 1960,\n right = 2023\n ) %>%\n col_is_integer(\n columns = c(\"population\")\n ) %>%\n col_vals_between(\n columns = c(\"population\"),\n left = 2646,\n right = 1428627700,\n na_pass = TRUE\n ) %>%\n rows_distinct(\n columns = c(\"country_name\", \"country_code_2\", \"country_code_3\", \"year\", \"population\")\n ) %>%\n col_schema_match(\n schema = col_schema(\n country_name = \"character\",\n country_code_2 = \"character\",\n country_code_3 = \"character\",\n year = \"integer\",\n population = \"integer\"\n )\n ) %>%\n interrogate()\n\nagent" From 9ad557f93545fb694ce7cd000ec00e188c16f4ab Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 17:39:25 -0400 Subject: [PATCH 36/37] rename levels in action_levels() print method --- R/print.R | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/R/print.R b/R/print.R index 65e510e4c..75889ee8c 100644 --- a/R/print.R +++ b/R/print.R @@ -534,22 +534,22 @@ print.action_levels <- function(x, ...) { if (!is.null(x$stop_fraction)) { cli::cli_text( - "{.red STOP} failure threshold of {x$stop_fraction} of all test units." + "{.red ERROR} failure threshold of {x$stop_fraction} of all test units." ) } if (!is.null(x$stop_count)) { cli::cli_text( - "{.red STOP} failure threshold of ", + "{.red ERROR} failure threshold of ", "{pb_fmt_number(x$stop_count, decimals = 0)} test units." ) } if (has_stop_fns) { if (is.null(x$stop_fraction) && is.null(x$stop_count)) { cli::cli_alert_warning( - "{.red STOP} fns provided without a failure threshold." + "{.red ERROR} fns provided without a failure threshold." ) cli::cli_alert_info( - "Set the {.red STOP} threshold using the `stop_at` argument." + "Set the {.red ERROR} threshold using the `error` argument." ) cli::cli_text() } else { @@ -561,22 +561,22 @@ print.action_levels <- function(x, ...) { if (!is.null(x$notify_fraction)) { cli::cli_text( - "{.blue NOTIFY} failure threshold of {x$notify_fraction} of all test units." + "{.blue CRITICAL} failure threshold of {x$notify_fraction} of all test units." ) } if (!is.null(x$notify_count)) { cli::cli_text( - "{.blue NOTIFY} failure threshold of ", + "{.blue CRITICAL} failure threshold of ", "{pb_fmt_number(x$notify_count, decimals = 0)} test units." ) } if (has_notify_fns) { if (is.null(x$notify_fraction) && is.null(x$notify_count)) { cli::cli_alert_warning( - "{.blue NOTIFY} fns provided without a failure threshold." + "{.blue CRITICAL} fns provided without a failure threshold." ) cli::cli_alert_info( - "Set the {.blue NOTIFY} threshold using the `notify_at` argument." + "Set the {.blue CRITICAL} threshold using the `critical` argument." ) cli::cli_text() } else { @@ -651,7 +651,7 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "STOP failure threshold of ", + "ERROR failure threshold of ", x$stop_fraction, " of all test units." ) @@ -661,7 +661,7 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "STOP failure threshold of ", + "ERROR failure threshold of ", pb_fmt_number(x$stop_count, decimals = 0), "test units." ) @@ -672,8 +672,8 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "STOP fns provided without a failure threshold.\n", - "Set the STOP threshold using the `stop_at` argument.\n" + "ERROR fns provided without a failure threshold.\n", + "Set the ERROR threshold using the `error` argument.\n" ) ) } else { @@ -688,7 +688,7 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "NOTIFY failure threshold of ", + "CRITICAL failure threshold of ", x$notify_fraction, " of all test units." ) @@ -698,7 +698,7 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "NOTIFY failure threshold of ", + "CRITICAL failure threshold of ", pb_fmt_number(x$notify_count, decimals = 0), "test units." ) @@ -709,8 +709,8 @@ knit_print.action_levels <- function(x, ...) { action_levels_lines <- c(action_levels_lines, paste0( - "NOTIFY fns provided without a failure threshold.\n", - "Set the NOTIFY threshold using the `notify_at` argument.\n" + "CRITICAL fns provided without a failure threshold.\n", + "Set the CRITICAL threshold using the `critical` argument.\n" ) ) } else { From a074b49f10ff6f2032cb7c27b86aa6af29dc5100 Mon Sep 17 00:00:00 2001 From: yjunechoe Date: Tue, 25 Mar 2025 17:41:42 -0400 Subject: [PATCH 37/37] rename levels in interrogate() progress --- R/interrogate.R | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/R/interrogate.R b/R/interrogate.R index 619063f39..9a3b7eb48 100644 --- a/R/interrogate.R +++ b/R/interrogate.R @@ -895,7 +895,7 @@ create_post_step_cli_output_a <- function( if (validation_condition == "STOP") { cli::cli_alert_danger( c( - "Step {.field {i}}: {.red STOP} condition met.", + "Step {.field {i}}: {.red ERROR} condition met.", print_time(time_diff_s), step_label ) @@ -913,8 +913,8 @@ create_post_step_cli_output_a <- function( if (validation_condition == "STOP") { cli::cli_alert_danger( c( - "Step {.field {i}}: {.red STOP} and ", - "{.blue NOTIFY} conditions met.", + "Step {.field {i}}: {.red ERROR} and ", + "{.blue CRITICAL} conditions met.", print_time(time_diff_s), step_label ) @@ -923,7 +923,7 @@ create_post_step_cli_output_a <- function( cli::cli_alert_warning( c( "Step {.field {i}}: {.yellow WARNING} and ", - "{.blue NOTIFY} conditions met.", + "{.blue CRITICAL} conditions met.", print_time(time_diff_s), step_label ) @@ -932,7 +932,7 @@ create_post_step_cli_output_a <- function( } else if (validation_condition == "NONE" && notify_condition != "NONE") { cli::cli_alert_warning( c( - "Step {.field {i}}: {.blue NOTIFY} condition met.", + "Step {.field {i}}: {.blue CRITICAL} condition met.", print_time(time_diff_s), step_label )