added skip on cran

tests/testthat/test-demo-crowding.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_crowding(area = "wa",
                           areatype = "hsa", 
                           crowding = "household with >1 person per room",
@@ -14,6 +15,7 @@ test_that("Output data type is correct", {
 
 #Ensures that variables are present and working on SCP
 test_that("demo-crowding returns non-empty data frame", {
+  skip_on_cran()
   crowding1 <- demo_crowding(area = "wa",
                              areatype = "hsa", 
                              crowding = "household with >1 person per room",
@@ -23,6 +25,7 @@ test_that("demo-crowding returns non-empty data frame", {
 
 #demo-crowding must have 5 columns
 test_that("demo-crowding has correct number of columns", {
+  skip_on_cran()
   df <- demo_crowding(area = "wa",
                       areatype = "hsa", 
                       crowding = "household with >1 person per room",

tests/testthat/test-demo-education.R

@@ -4,13 +4,15 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_education("wa", "county", "at least high school", "males")
 
   expect_true(inherits(output, "data.frame"))
 })
 
 #Ensures that variables are present and working on SCP
 test_that("demo-education returns non-empty data frame", {
+  skip_on_cran()
   education1 <- demo_education("wa", "county", "at least high school", "males")
   expect_true(is.data.frame(education1))
 
@@ -24,6 +26,7 @@ test_that("demo-education returns non-empty data frame", {
 
 #demo-education must have 5 columns
 test_that("demo-education has correct number of columns", {
+  skip_on_cran()
   df <- demo_education("wa", "county", "at least high school", "both sexes")
   expected_columns <- 5
   expect_equal(ncol(df), expected_columns)
@@ -33,6 +36,7 @@ test_that("demo-education has correct number of columns", {
 
 #write one for error handling in education - mention in the message how values could have chnaged in SCP
 test_that("demo-education handles invalid education parameters", {
+  skip_on_cran()
   expect_error(
     demo_education("wa", "county", "less than 9th grade", "males"),
     "For Less than 9th Grade, Race and Sex must be NULL"

tests/testthat/test-demo-food-access.R

@@ -4,6 +4,7 @@
 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_food("wa", "county", "food insecurity", "black")
 
   expect_equal(class(output), "data.frame",
@@ -15,6 +16,7 @@ test_that("Output data type is correct", {
 
 #Ensures that variables are present and working on SCP
 test_that("demo-food returns non-empty data frame", {
+  skip_on_cran()
   food_test_1 <- demo_food("wa", "county", "food insecurity", "all races (includes hispanic)")
   expect_true(!is.null(food_test_1))
   expect_true(is.data.frame(food_test_1))
@@ -31,6 +33,7 @@ test_that("demo-food returns non-empty data frame", {
 # sometimes functions will output different nuber of columns depending on variables...
 # demo-food must have 5 columns
 test_that("demo-food has correct number of columns", {
+  skip_on_cran()
   df <- demo_food("wa", "county", "food insecurity", "black")
   df2 <- demo_food("wa", "county", "limited access to healthy food")
   expected_columns <- 3
@@ -41,6 +44,7 @@ test_that("demo-food has correct number of columns", {
 
 #test error handling
 test_that("demo-food handles invalid education parameters", {
+  skip_on_cran()
   expect_error(
     demo_food("wa", "county", "limited access to healthy food", "all races (includes hispanic)"),
     "For limited access to healthy food, Race must be NULL"
@@ -54,24 +58,4 @@ test_that("demo-food handles invalid education parameters", {
 #parameter
 test_that("demo-food has correct parameters", {
   expect_error(demo_food())
-  expect_error(demo_food("wa", "county", "all races (includes hispanic)", "food insecurity"))
 })
-
-
-
-
-
-
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-

tests/testthat/test-demo-income.R

@@ -4,13 +4,15 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_income("wa", "county", "median family income", "all races (includes hispanic)")
 
   expect_true(inherits(output, "data.frame"))
 })
 
 #Ensures that variables are present and working on SCP
 test_that("demo-income returns non-empty data frame", {
+  skip_on_cran()
   income1 <- demo_income("wa", "county", "median family income", "all races (includes hispanic)")
   expect_true(is.data.frame(income1))
 
@@ -20,6 +22,7 @@ test_that("demo-income returns non-empty data frame", {
 
 #demo-income must have 5 columns
 test_that("demo-income has correct number of columns", {
+  skip_on_cran()
   df <- demo_income("usa", "state", "median household income", "all races (includes hispanic)")
   expected_columns <- 4
   expect_equal(ncol(df), expected_columns)

tests/testthat/test-demo-insurance.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_insurance("usa", "state", "% Insured in demographic group, all income levels", 
                            "both sexes", "under 19 years", "all races (includes hispanic)")
 
@@ -26,23 +27,24 @@ insurance_options <- c("% Insured in demographic group, all income levels",
 
 for (option in insurance_options) {
   test_that("demo-insurance returns non-empty data frame", {
+    skip_on_cran()
     expect_true(is.data.frame(demo_insurance("usa", "state", option, "both sexes", 
                                              "under 19 years", "all races (includes hispanic)")))
   })
 }
 
 #demo-insurance must have 5 columns
 test_that("demo-insurance has correct number of columns", {
+  skip_on_cran()
   df <- demo_insurance("wa", "hsa", "% Insured in demographic group, all income levels", 
                        "males", "18 to 64 years")
   expected_columns <- 5
   expect_equal(ncol(df), expected_columns)
 })
 
 #test error handling
-
-#write one for error handling in insurance - mention in the message how values could have chnaged in SCP
 test_that("demo-insurance handles invalid insurance parameters", {
+  skip_on_cran()
   expect_error(
     demo_insurance("wa", "county", "% Insured in demographic group, all income levels", 
                    "males", "18 to 64 years", "all races (includes hispanic)")

tests/testthat/test-demo-mobility.R

@@ -4,13 +4,12 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_mobility("wa", "county", "moved, different county, same state (in past year)")
 
   expect_true(inherits(output, "data.frame"))
 })
 
-
-
 mobility_options <- c("i haven't moved (in past year)", 
                       "moved from outside us (in past year)", 
                       "moved, different state (in past year)", 
@@ -20,12 +19,14 @@ mobility_options <- c("i haven't moved (in past year)",
 
 for (option in mobility_options) {
   test_that("demo-mobility returns non-empty data frame", {
+    skip_on_cran()
     expect_true(is.data.frame(demo_mobility("wa", "county", option)))
   })
 }
 
 #demo-mobility must have 5 columns
 test_that("demo-mobility has correct number of columns", {
+  skip_on_cran()
   df <- demo_mobility("wa", "county", "moved, different county, same state (in past year)")
   expected_columns <- 5
   expect_equal(ncol(df), expected_columns)

tests/testthat/test-demo-non-english-language.R

@@ -4,19 +4,22 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_language("wa", "county", "language isolation")
 
   expect_true(inherits(output, "data.frame"))
 })
 
 #Ensures that variables are present and working on SCP
 test_that("demo-language returns non-empty data frame", {
+  skip_on_cran()
   language1 <- demo_language("wa", "county", "language isolation")
   expect_true(is.data.frame(language1))
 })
 
 #demo-language must have 5 columns
 test_that("demo-language has correct number of columns", {
+  skip_on_cran()
   df <- demo_language("wa", "county", "language isolation")
   expected_columns <- 5
   expect_equal(ncol(df), expected_columns)

tests/testthat/test-demo-population.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_population("WA", "county", "asian/pacific islander", sex="females")
 
   expect_true(inherits(output, "data.frame"))
@@ -24,6 +25,7 @@ population_options <- list(
 
 for (option_name in names(population_options)) {
   test_that("demo-population returns non-empty data frame", {
+    skip_on_cran()
     option <- population_options[[option_name]]
     expect_true(is.data.frame(option))
   })
@@ -34,19 +36,22 @@ race_options <- c("american indian/alaska native", "asian/pacific islander",
 
 for (option in race_options) {
   test_that("demo-population returns non-empty data frame", {
+    skip_on_cran()
     expect_true(is.data.frame(demo_population("wa", "county", option, sex="both sexes")))
   })
 }
 
 #demo-population must have 5 columns
 test_that("demo-population has correct number of columns", {
+  skip_on_cran()
   df <- demo_population("WA", "county", "asian/pacific islander", sex="females")
   expected_columns <- 5
   expect_equal(ncol(df), expected_columns)
 })
 
 #test error handling
 test_that("demo-population handles invalid population parameters", {
+  skip_on_cran()
   expect_error(
     demo_population("wa", "county", "ages 40 and over", race="all races includes hispanic"),
     "ages 40 and over and ages 50 and over, Race and Sex must be NULL"

tests/testthat/test-demo-poverty.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_poverty("wa", "county", "persistent poverty")
 
   expect_true(inherits(output, "data.frame"))
@@ -19,13 +20,15 @@ poverty_options <- list(
 
 for (option_name in names(poverty_options)) {
   test_that("demo-poverty returns non-empty data frame", {
+    skip_on_cran()
     option <- poverty_options[[option_name]]
     expect_true(is.data.frame(option))
   })
 }
 
 #demo-poverty must have 5 columns
 test_that("demo-poverty has correct number of columns", {
+  skip_on_cran()
   df1 <- demo_poverty("wa", "county", "persistent poverty")
   df2 <- demo_poverty("wa", "county", "families below poverty", "black")
   expected_columns1 <- 3
@@ -36,6 +39,7 @@ test_that("demo-poverty has correct number of columns", {
 
 #test error handling
 test_that("demo-poverty handles invalid poverty parameters", {
+  skip_on_cran()
   expect_error(
     demo_poverty("wa", "hsa", "persistent poverty"),
     "For persistent poverty, areatype must be county"

tests/testthat/test-demo-svi.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_svi("wa", "overall")
 
   expect_true(inherits(output, "data.frame"))
@@ -16,12 +17,14 @@ svi_options <- c("Overall", "socioeconomic status", "household characteristics",
 
 for (option in svi_options) {
   test_that("demo-svireturns non-empty data frame", {
+    skip_on_cran()
     expect_true(is.data.frame(demo_svi("wa", option)))
   })
 }
 
 #demo-svi must have 5 columns
 test_that("demo-svi has correct number of columns", {
+  skip_on_cran()
   df <- demo_svi("wa", "overall")
   expected_columns <- 3
   expect_equal(ncol(df), expected_columns)

tests/testthat/test-demo-workforce.R

@@ -4,6 +4,7 @@
 #' 
 #tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- demo_workforce("wa", "county", "unemployed",
                            "all races (includes hispanic)", "both sexes")
 
@@ -12,13 +13,15 @@ test_that("Output data type is correct", {
 
 #Ensures that variables are present and working on SCP
 test_that("demo-workforce returns non-empty data frame", {
+  skip_on_cran()
   workforce1 <- demo_workforce("wa", "county", "unemployed",
                                "all races (includes hispanic)", "both sexes")
   expect_true(is.data.frame(workforce1))
 })
 
 #demo-workforce must have 5 columns
 test_that("demo-workforce has correct number of columns", {
+  skip_on_cran()
   df <- demo_workforce("wa", "county", "unemployed",
                        "all races (includes hispanic)", "both sexes")
   expected_columns <- 5

tests/testthat/test-incidence-cancer.R

@@ -4,6 +4,7 @@
 #'
 # tests class and typeof output
 test_that("Output data type is correct", {
+  skip_on_cran()
   output <- incidence_cancer("wa", "county", "all cancer sites", "black (non-hispanic)", 
                              "both sexes", "ages 65+", "all stages", "latest 5 year average")
 
@@ -18,6 +19,7 @@ cancer_options <- c("all cancer sites","bladder", "brain & ons", "colon & rectum
 
 for (option in cancer_options) {
   test_that("incidence cancer returns non-empty data frame", {
+    skip_on_cran()
     result <- incidence_cancer("wa", "county", option, "all races (includes hispanic)", 
                                "both sexes", "all ages", "all stages", "latest 5 year average")
     expect_true(is.data.frame(result))
@@ -29,6 +31,7 @@ female_cancer_options <- c("breast (female)", "breast (female in situ)",
 
 for (option in female_cancer_options) {
   test_that("incidence female cancer returns non-empty data frame", {
+    skip_on_cran()
     result <- incidence_cancer("wa", "county", option, 
                                "all races (includes hispanic)", "females", 
                                "ages 50+", "all stages", "latest 5 year average")
@@ -48,13 +51,15 @@ childhood_male_cancer_options <- list(
 
 for (option_name in names(childhood_male_cancer_options)) {
   test_that("incidence cancer returns non-empty data frame", {
+    skip_on_cran()
     option <- childhood_male_cancer_options[[option_name]]
     expect_true(is.data.frame(option))
   })
 }
 
 #incidence_cancer must have 14 columns
 test_that("incidence_cancer has correct number of columns", {
+  skip_on_cran()
   df1 <- incidence_cancer("wa", "county", "all cancer sites", "black (non-hispanic)", 
                          "both sexes", "ages 65+", "all stages", "latest 5 year average")
   df2 <- incidence_cancer("usa", "state", "lung & bronchus", "all races (includes hispanic)", "males",