Fix deprecation warnings + code cleanup

DESCRIPTION

@@ -33,7 +33,7 @@ Imports:
     cli (>= 3.6.0),
     DBI (>= 1.1.0),
     digest (>= 0.6.27),
-    dplyr (>= 1.0.10),
+    dplyr (>= 1.1.0),
     dbplyr (>= 2.3.0),
     fs (>= 1.6.0),
     glue (>= 1.6.2),
@@ -54,7 +54,7 @@ Suggests:
     data.table,
     duckdb,
     ggforce,
-    ggplot2,
+    ggplot2 (>= 3.5.0),
     jsonlite,
     log4r,
     lubridate,

R/get_agent_report.R

@@ -1612,7 +1612,7 @@ get_agent_report <- function(
       n_pass, f_pass, n_fail, f_fail, W, S, N, extract,
       W_val, S_val, N_val, eval, active
     ) %>%
-    gt::gt(id = "pb_agent") %>%
+    gt::gt(id = "pb_agent", locale = locale) %>%
     gt::tab_header(
       title = title_text,
       subtitle = gt::md(combined_subtitle)
@@ -1666,15 +1666,13 @@ get_agent_report <- function(
       align = "right",
       columns = "i"
     ) %>%
-    gt::fmt_number(
+    gt::fmt_integer(
       columns = c("units", "n_pass", "n_fail", "f_pass", "f_fail"),
-      decimals = 0, drop_trailing_zeros = TRUE, suffixing = TRUE,
-      locale = locale
+      suffixing = TRUE
     ) %>%
     gt::fmt_number(
       columns = c("f_pass", "f_fail"),
-      decimals = 2,
-      locale = locale
+      decimals = 2
     ) %>%
     gt::fmt_markdown(
       columns = c(

R/get_informant_report.R

@@ -359,7 +359,7 @@ get_informant_report <- function(
             gsub("(\\(|\\)|\\[|\\]|\\||\\.|\\^|\\?|\\+|\\$|\\*)", "\\\\\\1", .)
 
           row_idx <-
-            which(grepl(paste0("^<code.*?>", column_escaped, "<.*?"), tbl$item))
+            grep(paste0("^<code.*?>", column_escaped, "<.*?"), tbl$item)
 
           if (length(miniheader_vec) > 0) {
             tbl$item[[row_idx]] <-

R/incorporate.R

@@ -283,10 +283,10 @@ incorporate <- function(informant) {
       # of the `lang` value (from `NULL` to the informant `lang`)
 
       select_call_idx <-
-        which(grepl("select", snippet_f_rhs_str))
+        grep("select", snippet_f_rhs_str)
 
       pb_str_catalog_call_idx <-
-        which(grepl("pb_str_catalog", snippet_f_rhs_str))
+        grep("pb_str_catalog", snippet_f_rhs_str)
 
       snippet_f_rhs_str[pb_str_catalog_call_idx] <-
         gsub(

R/interrogate.R

@@ -339,8 +339,8 @@ interrogate <- function(
 
       if (any_1_unit && any_n_unit) {
 
-        col_is_idx <- which(grepl("col_is|col_exists", validation_fns))
-        col_vals_idx <- which(grepl("col_vals", validation_fns))
+        col_is_idx <- grep("col_is|col_exists", validation_fns)
+        col_vals_idx <- grep("col_vals", validation_fns)
 
         validation_formulas <-
           c(
@@ -427,10 +427,7 @@ interrogate <- function(
         tbl_checked %>%
           dplyr::mutate(pb_is_good_ = !!rlang::parse_expr(columns_str_add)) %>%
           dplyr::select(-dplyr::all_of(columns_str_vec)) %>%
-          dplyr::mutate(pb_is_good_ = dplyr::case_when(
-            pb_is_good_ == validation_n ~ TRUE,
-            TRUE ~ FALSE
-          ))
+          dplyr::mutate(pb_is_good_ = pb_is_good_ == validation_n)
       }
 
       # Perform rowwise validations for the column
@@ -1158,7 +1155,7 @@ tbl_val_comparison <- function(
     table %>%
       dplyr::mutate(pb_is_good_ = dplyr::case_when(
         !!expression ~ 1,
-        TRUE ~ 0
+        .default = 0
       ))
 
   } else {
@@ -1167,7 +1164,7 @@ tbl_val_comparison <- function(
       dplyr::mutate(pb_is_good_ = !!expression) %>%
       dplyr::mutate(pb_is_good_ = dplyr::case_when(
         is.na(pb_is_good_) ~ na_pass,
-        TRUE ~ pb_is_good_
+        .default = pb_is_good_
       ))
   }
 }
@@ -1363,7 +1360,7 @@ tbl_vals_between <- function(
   table %>%
     dplyr::mutate(pb_is_good_ = dplyr::case_when(
       is.na({{ column }}) ~ na_pass_bool,
-      TRUE ~ pb_is_good_
+      .default = pb_is_good_
     ))
 }
 
@@ -2031,7 +2028,7 @@ interrogate_within_spec <- function(
           check_vin_db(table, column = {{ column }}) %>%
           dplyr::mutate(pb_is_good_ = dplyr::case_when(
             is.na(pb_is_good_) ~ na_pass,
-            TRUE ~ pb_is_good_
+            .default = pb_is_good_
           ))
       }
 

R/remove_deactivate.R

@@ -269,7 +269,7 @@ remove_steps <- function(
 
   # Renumber steps
   agent$validation_set$i <-
-    as.integer(seq(from = 1, to = nrow(agent$validation_set), by = 1))
+    seq.int(from = 1L, to = nrow(agent$validation_set), by = 1L)
 
   # Remove any data extracts
   agent$extracts <- NULL

R/scan_data.R

@@ -1421,9 +1421,11 @@ get_corr_plot <- function(
 
   corr_df <-
     as.data.frame(as.table(mat)) %>%
-    dplyr::mutate(Freq = ifelse(Var1 == Var2, NA_real_, Freq)) %>%
-    dplyr::mutate(Var1 = factor(Var1, levels = names(labels_vec))) %>%
-    dplyr::mutate(Var2 = factor(Var2, levels = rev(names(labels_vec))))
+    dplyr::mutate(
+      Freq = ifelse(Var1 == Var2, NA_real_, Freq),
+      Var1 = factor(Var1, levels = names(labels_vec)),
+      Var2 = factor(Var2, levels = rev(names(labels_vec)))
+    )
 
   plot_missing <-
     corr_df %>%
@@ -1444,7 +1446,8 @@ get_corr_plot <- function(
       panel.grid = ggplot2::element_blank(),
       legend.direction = "horizontal",
       legend.title = ggplot2::element_blank(),
-      legend.position = c(0.5, 1.03),
+      legend.position = "inside",
+      legend.position.inside = c(0.5, 1.03),
       plot.margin = ggplot2::unit(c(1, 0.5, 0, 0), "cm"),
       legend.key.width = ggplot2::unit(2.0, "cm"),
       legend.key.height = ggplot2::unit(3.0, "mm")

R/steps_and_briefs.R

@@ -159,6 +159,7 @@ hash_validation_step <- function(assertion_type,
     seg_val = as.character(seg_val %||% NA_character_)
   )
 
+  # Maybe consider replacing with rlang::hash?
   step_hash <- digest::sha1(step_chr)
 
   paste(step_hash, hash_version, sep = "-")

R/utils-profiling.R

@@ -339,7 +339,7 @@ get_table_column_histogram <- function(data_column, lang, locale) {
       ggplot2::geom_col(fill = "steelblue", width = 0.5) +
       ggplot2::geom_hline(yintercept = 0, color = "#B2B2B2") +
       ggplot2::labs(x = x_label, y = y_label) +
-      ggplot2::scale_y_continuous(labels = scales::comma_format()) +
+      ggplot2::scale_y_continuous(labels = scales::label_comma()) +
       ggplot2::theme_minimal()
   )
 }
@@ -423,8 +423,10 @@ get_tbl_dbi_missing_tbl <- function(data) {
 
   frequency_list %>%
     dplyr::bind_rows() %>%
-    dplyr::mutate(value = ifelse(value == 0, NA_real_, value)) %>%
-    dplyr::mutate(col_name = factor(col_name, levels = colnames(data)))
+    dplyr::mutate(
+      value = ifelse(value == 0, NA_real_, value),
+      col_name = factor(col_name, levels = colnames(data))
+    )
 }
 
 # nocov start
@@ -484,7 +486,7 @@ get_tbl_df_missing_tbl <- function(data) {
             rowid < cuts_[18] ~ 18L,
             rowid < cuts_[19] ~ 19L,
             rowid < cuts_[20] ~ 20L,
-            TRUE ~ 20L
+            .default = 20L
           ))
         data <- dplyr::select(data, -rowid)
         data <- dplyr::group_by(data, `::cut_group::`)
@@ -604,7 +606,8 @@ get_missing_value_plot <- function(data, frequency_tbl, missing_by_column_tbl) {
       panel.grid = ggplot2::element_blank(),
       legend.direction = "horizontal",
       legend.title = ggplot2::element_blank(),
-      legend.position = c(0.5, 1.0),
+      legend.position = "inside",
+      legend.position.inside = c(0.5, 1.0),
       plot.margin = ggplot2::unit(c(1, 0.5, 0, 0), "cm"),
       legend.key.width = ggplot2::unit(2.0, "cm"),
       legend.key.height = ggplot2::unit(3.0, "mm")

R/utils-specifications.R

@@ -276,88 +276,84 @@ check_vin_db <- function(table,
 
   table <-
     table %>%
-    dplyr::mutate(pb_vin_all_ = {{ column }}) %>%
-    dplyr::mutate(pb_vin_all_ = tolower(as.character((pb_vin_all_)))) %>%
-    dplyr::mutate(pb_vin_nch_ = ifelse(nchar(pb_vin_all_) == 17, TRUE, FALSE)) %>%
-    dplyr::mutate(pb_vin_001_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 1, 1), "8")) %>%
-    dplyr::mutate(pb_vin_002_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 2, 2), "8")) %>%
-    dplyr::mutate(pb_vin_003_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 3, 3), "8")) %>%
-    dplyr::mutate(pb_vin_004_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 4, 4), "8")) %>%
-    dplyr::mutate(pb_vin_005_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 5, 5), "8")) %>%
-    dplyr::mutate(pb_vin_006_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 6, 6), "8")) %>%
-    dplyr::mutate(pb_vin_007_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 7, 7), "8")) %>%
-    dplyr::mutate(pb_vin_008_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 8, 8), "8")) %>%
-    dplyr::mutate(pb_vin_009_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 9, 9), "8")) %>%
-    dplyr::mutate(pb_vin_010_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 10, 10), "8")) %>%
-    dplyr::mutate(pb_vin_011_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 11, 11), "8")) %>%
-    dplyr::mutate(pb_vin_012_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 12, 12), "8")) %>%
-    dplyr::mutate(pb_vin_013_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 13, 13), "8")) %>%
-    dplyr::mutate(pb_vin_014_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 14, 14), "8")) %>%
-    dplyr::mutate(pb_vin_015_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 15, 15), "8")) %>%
-    dplyr::mutate(pb_vin_016_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 16, 16), "8")) %>%
-    dplyr::mutate(pb_vin_017_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 17, 17), "8")) %>%
-    dplyr::mutate_at(
-      dplyr::vars(dplyr::matches("pb_vin_[0-9]{3}_")),
-      .funs = list(~ case_when(
-        . %in% c("a", "j") ~ "1",
-        . %in% c("b", "k", "s") ~ "2",
-        . %in% c("c", "l", "t") ~ "3",
-        . %in% c("d", "m", "u") ~ "4",
-        . %in% c("e", "n", "v") ~ "5",
-        . %in% c("f", "w") ~ "6",
-        . %in% c("g", "p", "x") ~ "7",
-        . %in% c("h", "y") ~ "8",
-        . %in% c("r", "z") ~ "9",
-        !(. %in% c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9")) ~ "100000",
-        TRUE ~ .
-      )
-      )) %>%
-    dplyr::mutate(pb_vin_chk_ = pb_vin_009_) %>%
-    dplyr::mutate_at(
-      dplyr::vars(dplyr::matches("pb_vin_[0-9]{3}_")),
-      .funs = as.integer
-    ) %>%
-    dplyr::mutate(pb_vin_001_w = pb_vin_001_ * 8L) %>%
-    dplyr::mutate(pb_vin_002_w = pb_vin_002_ * 7L) %>%
-    dplyr::mutate(pb_vin_003_w = pb_vin_003_ * 6L) %>%
-    dplyr::mutate(pb_vin_004_w = pb_vin_004_ * 5L) %>%
-    dplyr::mutate(pb_vin_005_w = pb_vin_005_ * 4L) %>%
-    dplyr::mutate(pb_vin_006_w = pb_vin_006_ * 3L) %>%
-    dplyr::mutate(pb_vin_007_w = pb_vin_007_ * 2L) %>%
-    dplyr::mutate(pb_vin_008_w = pb_vin_008_ * 10L) %>%
-    dplyr::mutate(pb_vin_009_w = pb_vin_009_ * 0L) %>%
-    dplyr::mutate(pb_vin_010_w = pb_vin_010_ * 9L) %>%
-    dplyr::mutate(pb_vin_011_w = pb_vin_011_ * 8L) %>%
-    dplyr::mutate(pb_vin_012_w = pb_vin_012_ * 7L) %>%
-    dplyr::mutate(pb_vin_013_w = pb_vin_013_ * 6L) %>%
-    dplyr::mutate(pb_vin_014_w = pb_vin_014_ * 5L) %>%
-    dplyr::mutate(pb_vin_015_w = pb_vin_015_ * 4L) %>%
-    dplyr::mutate(pb_vin_016_w = pb_vin_016_ * 3L) %>%
-    dplyr::mutate(pb_vin_017_w = pb_vin_017_ * 2L) %>%
     dplyr::mutate(
+      pb_vin_all_ = {{ column }},
+      pb_vin_all_ = tolower(as.character((pb_vin_all_))),
+      pb_vin_nch_ = nchar(pb_vin_all_) == 17,
+      pb_vin_001_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 1, 1), "8"),
+      pb_vin_002_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 2, 2), "8"),
+      pb_vin_003_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 3, 3), "8"),
+      pb_vin_004_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 4, 4), "8"),
+      pb_vin_005_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 5, 5), "8"),
+      pb_vin_006_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 6, 6), "8"),
+      pb_vin_007_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 7, 7), "8"),
+      pb_vin_008_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 8, 8), "8"),
+      pb_vin_009_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 9, 9), "8"),
+      pb_vin_010_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 10, 10), "8"),
+      pb_vin_011_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 11, 11), "8"),
+      pb_vin_012_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 12, 12), "8"),
+      pb_vin_013_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 13, 13), "8"),
+      pb_vin_014_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 14, 14), "8"),
+      pb_vin_015_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 15, 15), "8"),
+      pb_vin_016_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 16, 16), "8"),
+      pb_vin_017_ = ifelse(pb_vin_nch_, substr(pb_vin_all_, 17, 17), "8"),
+      dplyr::across(
+        .cols = dplyr::matches("pb_vin_[0-9]{3}_"),
+        function(x) {
+          dplyr::case_match(x,
+            c("a", "j") ~ "1",
+            c("b", "k", "s") ~ "2",
+            c("c", "l", "t") ~ "3",
+            c("d", "m", "u") ~ "4",
+            c("e", "n", "v") ~ "5",
+            c("f", "w") ~ "6",
+            c("g", "p", "x") ~ "7",
+            c("h", "y") ~ "8",
+            c("r", "z") ~ "9",
+            c("0", "1", "2", "3", "4", "5", "6", "7", "8", "9") ~ "100000",
+            .default = x
+          )
+      }),
+      pb_vin_chk_ = pb_vin_009_,
+      dplyr::across(dplyr::matches("pb_vin_[0-9]{3}_"), as.integer),
+      pb_vin_001_w = pb_vin_001_ * 8L,
+      pb_vin_002_w = pb_vin_002_ * 7L,
+      pb_vin_003_w = pb_vin_003_ * 6L,
+      pb_vin_004_w = pb_vin_004_ * 5L,
+      pb_vin_005_w = pb_vin_005_ * 4L,
+      pb_vin_006_w = pb_vin_006_ * 3L,
+      pb_vin_007_w = pb_vin_007_ * 2L,
+      pb_vin_008_w = pb_vin_008_ * 10L,
+      pb_vin_009_w = pb_vin_009_ * 0L,
+      pb_vin_010_w = pb_vin_010_ * 9L,
+      pb_vin_011_w = pb_vin_011_ * 8L,
+      pb_vin_012_w = pb_vin_012_ * 7L,
+      pb_vin_013_w = pb_vin_013_ * 6L,
+      pb_vin_014_w = pb_vin_014_ * 5L,
+      pb_vin_015_w = pb_vin_015_ * 4L,
+      pb_vin_016_w = pb_vin_016_ * 3L,
+      pb_vin_017_w = pb_vin_017_ * 2L,
       pb_vin_sum_uw =
         pb_vin_001_ + pb_vin_002_ + pb_vin_003_ + pb_vin_004_ +
         pb_vin_005_ + pb_vin_006_ + pb_vin_007_ + pb_vin_008_ +
         pb_vin_009_ + pb_vin_010_ + pb_vin_011_ + pb_vin_012_ +
         pb_vin_013_ + pb_vin_014_ + pb_vin_015_ + pb_vin_016_ +
-        pb_vin_017_
-    ) %>%
-    dplyr::mutate(
+        pb_vin_017_,
       pb_vin_sum_ =
         pb_vin_001_w + pb_vin_002_w + pb_vin_003_w + pb_vin_004_w +
         pb_vin_005_w + pb_vin_006_w + pb_vin_007_w + pb_vin_008_w +
         pb_vin_009_w + pb_vin_010_w + pb_vin_011_w + pb_vin_012_w +
         pb_vin_013_w + pb_vin_014_w + pb_vin_015_w + pb_vin_016_w +
-        pb_vin_017_w
-    ) %>%
-    dplyr::mutate(pb_vin_mod_ = as.character(pb_vin_sum_ %% 11L)) %>%
-    dplyr::mutate(pb_vin_mod_ = ifelse(pb_vin_mod_ == "10", "x", pb_vin_mod_)) %>%
-    dplyr::mutate(pb_is_good_ = pb_vin_mod_ == pb_vin_chk_) %>%
-    dplyr::mutate(pb_is_good_ = ifelse(!pb_vin_nch_, FALSE, pb_vin_nch_)) %>%
-    dplyr::mutate(pb_is_good_ = ifelse(pb_vin_sum_uw >= 100000, FALSE, pb_is_good_))
+        pb_vin_017_w,
+      pb_vin_mod_ = as.character(pb_vin_sum_ %% 11L),
+      pb_vin_mod_ = ifelse(pb_vin_mod_ == "10", "x", pb_vin_mod_),
+      pb_is_good_ = pb_vin_mod_ == pb_vin_chk_,
+      pb_is_good_ = ifelse(!pb_vin_nch_, FALSE, pb_vin_nch_),
+      pb_is_good_ = ifelse(pb_vin_sum_uw >= 100000, FALSE, pb_is_good_)
+    )
 
   table <-
-    table %>% dplyr::select(c(tbl_colnames, "pb_is_good_"))
+    table %>% dplyr::select(dplyr::all_of(c(tbl_colnames, "pb_is_good_")))
 
   table
 }