[R-package] [docs] fix calculation of R test coverage (fixes #4919) (#4922)

* [R-package] [docs] fix calculation of R test coverage (fixes #4919)

* use quotes

* use in_covr() instead of env variable

* Update R-package/README.md
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

* check that covr exists

* add covr to suggests

* use R_COVR environment variable

* Update R-package/tests/testthat/test_lgb.unloader.R
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>
Co-authored-by: Nikita Titov <nekit94-08@mail.ru>

R-package/README.md

@@ -265,11 +265,13 @@ The example below shows how to generate code coverage for the R package on a mac
 
 ```shell
 # Install
-sh build-cran-package.sh
+sh build-cran-package.sh \
+    --no-build-vignettes
 
 # Get coverage
 Rscript -e " \
-    coverage  <- covr::package_coverage('./lightgbm_r', type = 'tests', quiet = FALSE);
+    library(covr);
+    coverage <- covr::package_coverage('./lightgbm_r', type = 'tests', quiet = FALSE);
     print(coverage);
     covr::report(coverage, file = file.path(getwd(), 'coverage.html'), browse = TRUE);
     "

R-package/tests/testthat/test_lgb.unloader.R

@@ -2,7 +2,13 @@ VERBOSITY <- as.integer(
     Sys.getenv("LIGHTGBM_TEST_VERBOSITY", "-1")
 )
 
+CALCULATING_TEST_COVERAGE <- Sys.getenv("R_COVR", unset = "unset") != "unset"
+
 test_that("lgb.unloader works as expected", {
+    testthat::skip_if(
+        condition = CALCULATING_TEST_COVERAGE
+        , message = "lgb.unloader() tests are skipped when calculating test coverage"
+    )
     data(agaricus.train, package = "lightgbm")
     train <- agaricus.train
     dtrain <- lgb.Dataset(train$data, label = train$label)
@@ -24,6 +30,10 @@ test_that("lgb.unloader works as expected", {
 })
 
 test_that("lgb.unloader finds all boosters and removes them", {
+    testthat::skip_if(
+        condition = CALCULATING_TEST_COVERAGE
+        , message = "lgb.unloader() tests are skipped when calculating test coverage"
+    )
     data(agaricus.train, package = "lightgbm")
     train <- agaricus.train
     dtrain <- lgb.Dataset(train$data, label = train$label)