Merge pull request #311 from epiforecasts/all-data-tests

Reduce test runtime

tests/testthat/functions/dummy_class.R

@@ -12,10 +12,14 @@ dummy_class <- function(class) {
   class$data$raw <- purrr::map(class$data$raw, ~ dplyr::slice_tail(., n = 250))
   class$data$raw <- purrr::map(class$data$raw, ~ .[, 1:min(20, ncol(.))])
   class$clean()
+  class$data$clean <- dplyr::slice_tail(class$data$clean, n = 250)
   class$process()
   replacePublicR6Method(class, "download", function() {
     return(invisible(NULL))
   })
+  replacePublicR6Method(class, "clean", function() {
+    return(invisible(NULL))
+  })
   class$verbose <- FALSE
   return(class)
 }

tests/testthat/test-regional-datasets.R

@@ -1,53 +1,55 @@
-# load testing function and tools.
-# set up custom tests using:
-# custom_tests/regional-dataset-specific.R
-source("custom_tests/test-regional-dataset.R")
+if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+  # load testing function and tools.
+  # set up custom tests using:
+  # custom_tests/regional-dataset-specific.R
+  source("custom_tests/test-regional-dataset.R")
 
-# should a single dataset be tested vs all datasets
-# set this when implementing a new dataset.
-# Can also be set using environment variables
-source_of_interest <- NULL
-if (!is.null(getOption("testSource"))) {
-  source_of_interest <- getOption("testSource")
-}
-# should downloads be tested (defaults to FALSE)
-# set this to true when implementing a new data set
-# can also be controlled using an environment variable
-download <- FALSE
-if (!is.null(getOption("testDownload"))) {
-  download <- getOption("testDownload")
-}
+  # should a single dataset be tested vs all datasets
+  # set this when implementing a new dataset.
+  # Can also be set using environment variables
+  source_of_interest <- NULL
+  if (!is.null(getOption("testSource"))) {
+    source_of_interest <- getOption("testSource")
+  }
+  # should downloads be tested (defaults to FALSE)
+  # set this to true when implementing a new data set
+  # can also be controlled using an environment variable
+  download <- FALSE
+  if (!is.null(getOption("testDownload"))) {
+    download <- getOption("testDownload")
+  }
 
-# get datasets for testing
-sources <- get_available_datasets() %>%
-  dplyr::filter(.data$type %in%
-    c("national", "regional")) %>%
-  dplyr::select(source = class, level_1_region, level_2_region) %>%
-  tidyr::pivot_longer(
-    cols = -source,
-    names_to = "level",
-    values_to = "regions"
-  ) %>%
-  dplyr::mutate(
-    level = stringr::str_split(level, "_"),
-    level = purrr::map_chr(level, ~ .[2])
-  ) %>%
-  tidyr::drop_na(regions)
+  # get datasets for testing
+  sources <- get_available_datasets() %>%
+    dplyr::filter(.data$type %in%
+      c("national", "regional")) %>%
+    dplyr::select(source = class, level_1_region, level_2_region) %>%
+    tidyr::pivot_longer(
+      cols = -source,
+      names_to = "level",
+      values_to = "regions"
+    ) %>%
+    dplyr::mutate(
+      level = stringr::str_split(level, "_"),
+      level = purrr::map_chr(level, ~ .[2])
+    ) %>%
+    tidyr::drop_na(regions)
 
-# filter out target datasets
-if (!is.null(source_of_interest)) {
-  sources <- sources %>%
-    dplyr::filter(source %in% source_of_interest)
-}
+  # filter out target datasets
+  if (!is.null(source_of_interest)) {
+    sources <- sources %>%
+      dplyr::filter(source %in% source_of_interest)
+  }
 
-# apply tests to each data source in turn
-sources %>%
-  dplyr::rowwise() %>%
-  dplyr::group_split() %>%
-  purrr::walk(
-    ~ test_regional_dataset(
-      source = .$source[[1]],
-      level = .$level[[1]],
-      download = download
+  # apply tests to each data source in turn
+  sources %>%
+    dplyr::rowwise() %>%
+    dplyr::group_split() %>%
+    purrr::walk(
+      ~ test_regional_dataset(
+        source = .$source[[1]],
+        level = .$level[[1]],
+        download = download
+      )
     )
-  )
+}