[ci] re-enable all {lintr} linters (#233)

.ci/lint_r_code.R

@@ -29,17 +29,15 @@ interactive_text <- paste0(
 )
 
 LINTERS_TO_USE <- list(
-    # "absolute_path"          = lintr::absolute_path_linter()
-    "assignment"           = lintr::assignment_linter()
-    # , "closed_curly"         = lintr::closed_curly_linter()
+    "absolute_path"          = lintr::absolute_path_linter()
+    , "assignment"           = lintr::assignment_linter()
+    , "braces"               = lintr::brace_linter()
     , "commas"               = lintr::commas_linter()
     , "equals_na"            = lintr::equals_na_linter()
     , "function_left"        = lintr::function_left_parentheses_linter()
     , "infix_spaces"         = lintr::infix_spaces_linter()
-    , "no_tabs"              = lintr::no_tab_linter()
-    # , "non_portable_path"    = lintr::nonportable_path_linter()
-    # , "open_curly"           = lintr::open_curly_linter()
-    , "semicolon"            = lintr::semicolon_terminator_linter()
+    , "non_portable_path"    = lintr::nonportable_path_linter()
+    , "semicolon"            = lintr::semicolon_linter()
     , "seq"                  = lintr::seq_linter()
     , "spaces_inside"        = lintr::spaces_inside_linter()
     , "spaces_left_parens"   = lintr::spaces_left_parentheses_linter()
@@ -72,7 +70,8 @@ LINTERS_TO_USE <- list(
             , "??" = interactive_text
         )
     )
-    , "unneeded_concatenation" = lintr::unneeded_concatenation_linter()
+    , "unnecessary_concatenation" = lintr::unnecessary_concatenation_linter()
+    , "whitespace"                = lintr::whitespace_linter()
 )
 
 cat(sprintf("Found %i R files to lint\n", length(FILES_TO_LINT)))

.ci/setup.sh

@@ -16,6 +16,7 @@ sudo apt-get install \
     texlive-latex-recommended \
     texlive-fonts-recommended \
     texlive-fonts-extra \
+    tidy \
     qpdf
 
 Rscript -e "install.packages(c('assertthat', 'covr', 'data.table', 'futile.logger', 'httr', 'jsonlite', 'knitr', 'lintr', 'purrr', 'rmarkdown', 'stringr', 'testthat', 'uuid'), repos = 'https://cran.r-project.org', Ncpus = parallel::detectCores())"

.github/workflows/ci.yml

@@ -8,6 +8,15 @@ on:
     branches:
       - main
 
+# automatically cancel in-progress builds if another commit is pushed
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+env:
+  # parallelize compilation (extra important for Linux, where CRAN doesn't supply pre-compiled binaries)
+  MAKEFLAGS: "-j4"
+
 jobs:
   test:
     name: test (ES ${{ matrix.es_version }})

r-pkg/R/chomp_aggs.R

@@ -48,15 +48,15 @@ chomp_aggs <- function(aggs_json = NULL) {
     )
 
     # Gross special-case handler for one-level extended_stats aggregation
-    if (.IsExtendedStatsAgg(jsonList[["aggregations"]][[aggNames]])){
+    if (.IsExtendedStatsAgg(jsonList[["aggregations"]][[aggNames]])) {
         log_info("es_search is assuming that this result is a one-level 'extended_stats' result.")
         jsonList[["aggregations"]][[1]][["std_deviation_bounds.upper"]] <- jsonList[["aggregations"]][[1]][["std_deviation_bounds"]][["upper"]]
         jsonList[["aggregations"]][[1]][["std_deviation_bounds.lower"]] <- jsonList[["aggregations"]][[1]][["std_deviation_bounds"]][["lower"]]
         jsonList[["aggregations"]][[1]][["std_deviation_bounds"]] <- NULL
     }
 
     # Gross special-case handler for one-level percentiles aggregation
-    if (.IsPercentilesAgg(jsonList[["aggregations"]][[aggNames]])){
+    if (.IsPercentilesAgg(jsonList[["aggregations"]][[aggNames]])) {
         log_info("es_search is assuming that this result is a one-level 'percentiles' result.")
 
         # Replace names like `25.0` with something that will be easier for users to understand
@@ -66,7 +66,7 @@ chomp_aggs <- function(aggs_json = NULL) {
         jsonList[["aggregations"]][[aggNames]] <- percValues
     }
 
-    if (.IsSigTermsAgg(jsonList[["aggregations"]][[aggNames]])){
+    if (.IsSigTermsAgg(jsonList[["aggregations"]][[aggNames]])) {
         log_info("es_search is assuming that this result is a one-level 'significant terms' result.")
 
         # We can grab that nested data.frame and break out right now
@@ -76,7 +76,7 @@ chomp_aggs <- function(aggs_json = NULL) {
     }
 
     # check for an empty result
-    if (identical(jsonList[["aggregations"]][[aggNames]][["buckets"]], list())){
+    if (identical(jsonList[["aggregations"]][[aggNames]][["buckets"]], list())) {
         log_info("this aggregation result was empty. Returning NULL")
         return(invisible(NULL))
     }
@@ -96,7 +96,7 @@ chomp_aggs <- function(aggs_json = NULL) {
         } else {
 
             # Other bucketed aggregations (not date_histogram) will have "key"
-            if ("key" %in% names(outDT)){
+            if ("key" %in% names(outDT)) {
                 data.table::setnames(outDT, "key", aggNames[length(aggNames)])
             } else {
                 # If we get down here, we know it's not a bucketed aggregation
@@ -115,7 +115,7 @@ chomp_aggs <- function(aggs_json = NULL) {
 
             # Remove unwanted columns
             badCols <- grep("doc_count", names(outDT))
-            if (length(badCols) > 0){
+            if (length(badCols) > 0) {
                 outDT <- outDT[, !badCols, with = FALSE]
             }
 
@@ -135,7 +135,7 @@ chomp_aggs <- function(aggs_json = NULL) {
     # Re-set the column order to mirror the way the user specified their aggs query
     # NOTE: If there's no "doc_count" in the names, we know that this was not a bucketed
     # / nested query and reordering is unnecessary
-    if ("doc_count" %in% names(outDT)){
+    if ("doc_count" %in% names(outDT)) {
         data.table::setcolorder(
             outDT,
             c(aggNames, base::setdiff(names(outDT), c(aggNames, "doc_count")), "doc_count")
@@ -160,7 +160,7 @@ chomp_aggs <- function(aggs_json = NULL) {
 #               "extended_stats" aggregation. data.table doesn't handle those
 #               in a way that's consistent with the way this package handles all other aggregations
 # [param] aggsList R list-object representation of an "aggs" result from Elasticsearch
-.IsExtendedStatsAgg <- function(aggsList){
+.IsExtendedStatsAgg <- function(aggsList) {
     statsNames <- c("count", "min", "max", "avg", "sum", "sum_of_squares"
                     , "variance", "std_deviation", "std_deviation_bounds")
 
@@ -172,16 +172,24 @@ chomp_aggs <- function(aggs_json = NULL) {
 #               "Percentiles" aggregation. data.table doesn't handle those
 #               in a way that's consistent with the way this package handles all other aggregations
 # [param] aggsList R list-object representation of an "aggs" result from Elasticsearch
-.IsPercentilesAgg <- function(aggsList){
+.IsPercentilesAgg <- function(aggsList) {
 
     # check 1 - has a single element called "values"
-    if (! identical("values", names(aggsList))){
+    if (! identical("values", names(aggsList))) {
         return(FALSE)
     }
 
     # check 2 - all names of "values" are convertible to numbers
-    numNames <- as.numeric(names(aggsList[["values"]]))
-    if (all(vapply(numNames, function(val){!is.na(val)}, FUN.VALUE = TRUE))){
+    all_convertible <- all(
+        vapply(
+            X = as.numeric(names(aggsList[["values"]]))
+            , FUN = function(val) {
+                return(!is.na(val))
+            }
+            , FUN.VALUE = TRUE
+        )
+    )
+    if (all_convertible) {
         return(TRUE)
     } else {
         return(FALSE)
@@ -194,20 +202,20 @@ chomp_aggs <- function(aggs_json = NULL) {
 #               "significant terms" aggregation. data.table doesn't handle those
 #               in a way that's consistent with the way this package handles all other aggregations
 # [param] aggsList R list-object representation of an "aggs" result from Elasticsearch
-.IsSigTermsAgg <- function(aggsList){
+.IsSigTermsAgg <- function(aggsList) {
 
     # check 1 - has exactly two keys - "doc_count", "buckets"
-    if (! identical(sort(names(aggsList)), c('buckets', 'doc_count'))){
+    if (! identical(sort(names(aggsList)), c('buckets', 'doc_count'))) {
         return(FALSE)
     }
 
     # check 2 - "buckets" is a data.frame
-    if (!is.data.frame(aggsList[['buckets']])){
+    if (!is.data.frame(aggsList[['buckets']])) {
         return(FALSE)
     }
 
     # check 3 - "buckets" has at least the columns "key", "doc_count", and "bg_count"
-    if (!all(c('key', 'doc_count', 'bg_count') %in% names(aggsList[['buckets']]))){
+    if (!all(c('key', 'doc_count', 'bg_count') %in% names(aggsList[['buckets']]))) {
         return(FALSE)
     }