Add skip_on_cran to all unit tests in effort to appease CRAN gods

tests/test-all.R

@@ -1,3 +1,3 @@
 library(testthat)
-skip_on_cran()
+
 test_check("phonics")

tests/testthat/test-caverphone.R

@@ -1,17 +1,25 @@
 context("caverphone")
 
 ##  Test the Caverphone algorithm
-test <- read.csv("caverphone.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(caverphone(test$word[i]) == test$value[i])
-test$test <- caverphone(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("Caverphone works", {
+    skip_on_cran()
+
+    test <- read.csv("caverphone.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(caverphone(test$word[i]) == test$value[i])
+    test$test <- caverphone(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})
 
 ##  Test the Caverphone 2 algorithm
-test <- read.csv("caverphone-modified.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(caverphone(test$word[i], modified = TRUE) == test$value[i])
-test$test <- caverphone(test$word, modified = TRUE)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("Caverphone works", {
+    skip_on_cran()
+
+    test <- read.csv("caverphone-modified.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(caverphone(test$word[i], modified = TRUE) == test$value[i])
+    test$test <- caverphone(test$word, modified = TRUE)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-cologne.R

@@ -1,9 +1,13 @@
 context("cologne")
 
 ##  Test the Cologne algorithm
-test <- read.csv("cologne.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
+test_that("Cologne works", {
+    skip_on_cran()
+
+    test <- read.csv("cologne.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
     expect_true(cologne(test$word[i]) == test$value[i])
-test$test <- cologne(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+    test$test <- cologne(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-lein.R

@@ -1,9 +1,13 @@
 context("lein")
 
 ##  Test the lein algorithm
-test <- read.csv("lein.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(lein(test$word[i]) == test$value[i])
-test$test <- lein(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("Lein works", {
+    skip_on_cran()
+
+    test <- read.csv("lein.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(lein(test$word[i]) == test$value[i])
+    test$test <- lein(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-metaphone.R

@@ -1,13 +1,17 @@
 context("metaphone")
 
 test_that("The metaphone algorithm implementation accurately maps strings to metaphones", {
-  test_data <- read.csv("metaphone.csv", comment.char = "#", stringsAsFactors = FALSE)
-  expect_true(all(metaphone(test_data$word) == test_data$value))
-  test_data$test_metaphones <- metaphone(test_data$word)
-  expect_true(all(test_data$test_metaphones == test_data$value))
+    skip_on_cran()
+
+    test_data <- read.csv("metaphone.csv", comment.char = "#", stringsAsFactors = FALSE)
+    expect_true(all(metaphone(test_data$word) == test_data$value))
+    test_data$test_metaphones <- metaphone(test_data$word)
+    expect_true(all(test_data$test_metaphones == test_data$value))
 })
 
 test_that("The metaphone algorithm implementation can handle NAs", {
-  test_data <- metaphone(NA_character_)
-  expect_true(is.na(test_data))
+    skip_on_cran()
+
+    test_data <- metaphone(NA_character_)
+    expect_true(is.na(test_data))
 })

tests/testthat/test-mra.R

@@ -4,17 +4,25 @@ context("mra")
 ##  to test both the encoder and the comparison.
 
 ##  Test the MRA encoding algorithm
-test <- read.csv("mra-encode.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(mra_encode(test$word[i]) == test$value[i])
-test$test <- mra_encode(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("MRA encoder works", {
+    skip_on_cran()
+
+    test <- read.csv("mra-encode.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(mra_encode(test$word[i]) == test$value[i])
+    test$test <- mra_encode(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})
 
 ##  Test the MRA compare algorithm
-test <- read.csv("mra-compare.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(mra_compare(mra_encode(test$word1[i]), mra_encode(test$word2[i])) == test$value[i])
-test$test <- mra_compare(mra_encode(test$word1), mra_encode(test$word2))
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("MRA comparison works", {
+    skip_on_cran()
+
+    test <- read.csv("mra-compare.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(mra_compare(mra_encode(test$word1[i]), mra_encode(test$word2[i])) == test$value[i])
+    test$test <- mra_compare(mra_encode(test$word1), mra_encode(test$word2))
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-nysiis.R

@@ -1,17 +1,25 @@
 context("nysiis")
 
 ##  Test the NYSIIS algorithm
-test <- read.csv("nysiis.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(nysiis(test$word[i]) == test$value[i])
-test$test <- nysiis(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("NYSIIS works", {
+    skip_on_cran()
+
+    test <- read.csv("nysiis.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(nysiis(test$word[i]) == test$value[i])
+    test$test <- nysiis(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})
 
 ##  Test the modified NYSIIS algorithm
-test <- read.csv("nysiis-modified.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(nysiis(test$word[i], modified = TRUE) == test$value[i])
-test$test <- nysiis(test$word, modified = TRUE)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("Modified NYSIIS works", {
+    skip_on_cran()
+
+    test <- read.csv("nysiis-modified.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(nysiis(test$word[i], modified = TRUE) == test$value[i])
+    test$test <- nysiis(test$word, modified = TRUE)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-onca.R

@@ -1,9 +1,13 @@
 context("onca")
 
 ##  Test the ONCA algorithm
-test <- read.csv("onca.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(onca(test$word[i]) == test$value[i])
-test$test <- onca(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("ONCA works", {
+    skip_on_cran()
+
+    test <- read.csv("onca.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(onca(test$word[i]) == test$value[i])
+    test$test <- onca(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-phonex.R

@@ -1,9 +1,13 @@
 context("phonex")
 
 ##  Test the Phonex algorithm
-test <- read.csv("phonex.csv", comment.char="#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(phonex(test$word[i]) == test$value[i])
-test$test <- phonex(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("Phonex works", {
+    skip_on_cran()
+
+    test <- read.csv("phonex.csv", comment.char="#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(phonex(test$word[i]) == test$value[i])
+    test$test <- phonex(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-rogerroot.R

@@ -1,9 +1,13 @@
 context("rogerroot")
 
 ##  Test the Roger Root name encoding
-test <- read.csv("rogerroot.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(rogerroot(test$word[i]) == test$value[i])
-test$test <- rogerroot(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("RogerRoot works", {
+    skip_on_cran()
+
+    test <- read.csv("rogerroot.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(rogerroot(test$word[i]) == test$value[i])
+    test$test <- rogerroot(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})

tests/testthat/test-soundex.R

@@ -1,25 +1,33 @@
 context("soundex")
 
 test_that("The soundex algorithm implementation accurately maps strings to soundexes", {
-  test_data <- read.csv("soundex.csv", comment.char = "#", stringsAsFactors = FALSE)
-  expect_true(all(soundex(test_data$word) == test_data$value))
-  test_data$test_soundexes <- soundex(test_data$word)
-  expect_true(all(test_data$test_soundexes == test_data$value))
+    skip_on_cran()
+
+    test_data <- read.csv("soundex.csv", comment.char = "#", stringsAsFactors = FALSE)
+    expect_true(all(soundex(test_data$word) == test_data$value))
+    test_data$test_soundexes <- soundex(test_data$word)
+    expect_true(all(test_data$test_soundexes == test_data$value))
 })
 
 test_that("The soundex algorithm implementation can handle NAs", {
-  test_data <- soundex(NA_character_)
-  expect_true(is.na(test_data))
+    skip_on_cran()
+
+    test_data <- soundex(NA_character_)
+    expect_true(is.na(test_data))
 })
 
 test_that("The refined soundex algorithm implementation accurately maps strings to soundexes", {
-  test_data <- read.csv("soundex-refined.csv", comment.char = "#", stringsAsFactors = FALSE)
-  expect_true(all(refinedSoundex(test_data$word) == test_data$value))
-  test_data$test_soundexes <- refinedSoundex(test_data$word)
-  expect_true(all(test_data$test_soundexes == test_data$value))
+    skip_on_cran()
+
+    test_data <- read.csv("soundex-refined.csv", comment.char = "#", stringsAsFactors = FALSE)
+    expect_true(all(refinedSoundex(test_data$word) == test_data$value))
+    test_data$test_soundexes <- refinedSoundex(test_data$word)
+    expect_true(all(test_data$test_soundexes == test_data$value))
 })
 
 test_that("The refined soundex algorithm implementation can handle NAs", {
-  test_data <- refinedSoundex(NA_character_)
-  expect_true(is.na(test_data))
+    skip_on_cran()
+
+    test_data <- refinedSoundex(NA_character_)
+    expect_true(is.na(test_data))
 })

tests/testthat/test-statcan.R

@@ -1,9 +1,13 @@
 context("statcan")
 
 ##  Test the statcan algorithm
-test <- read.csv("statcan.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
-for(i in 1:nrow(test))
-    expect_true(statcan(test$word[i]) == test$value[i])
-test$test <- statcan(test$word)
-for(i in 1:nrow(test))
-    expect_true(test$test[i] == test$value[i])
+test_that("StatCan works", {
+    skip_on_cran()
+
+    test <- read.csv("statcan.csv", comment.char = "#", stringsAsFactors = FALSE, colClasses = c("character", "character"), encoding = "UTF-8")
+    for(i in 1:nrow(test))
+        expect_true(statcan(test$word[i]) == test$value[i])
+    test$test <- statcan(test$word)
+    for(i in 1:nrow(test))
+        expect_true(test$test[i] == test$value[i])
+})