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# ChileDataAPI - Access Chilean Data via APIs and Curated Datasets
# Version 0.2.0
# Copyright (C) 2025 Renzo Caceres Rossi
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
# get_chile_literacy_rate
library(testthat)
test_that("get_chile_literacy_rate() returns a tibble with correct structure and types", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_s3_class(result, "tbl_df")
expect_named(result, c("indicator", "country", "year", "value"))
expect_equal(ncol(result), 4)
expect_type(result$indicator, "character")
expect_type(result$country, "character")
expect_type(result$year, "integer")
expect_type(result$value, "double")
})
test_that("get_chile_literacy_rate() returns data only for Chile", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_true(all(result$country == "Chile"))
})
test_that("get_chile_literacy_rate() returns correct indicator label", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_true(all(result$indicator == "Literacy rate, adult total (% of people ages 15 and above)"))
})
test_that("get_chile_literacy_rate() returns data for years 2010 to 2022", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_true(all(result$year %in% 2010:2022))
expect_equal(sort(unique(result$year)), 2010:2022)
})
test_that("get_chile_literacy_rate() returns exactly 13 rows (one per year 2010-2022)", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_equal(nrow(result), 13)
})
test_that("get_chile_literacy_rate() year column has no missing values", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_false(any(is.na(result$year)))
})
test_that("get_chile_literacy_rate() value column is numeric and may contain NA values", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_true(is.numeric(result$value))
# NA values are valid and expected from the API
})
test_that("get_chile_literacy_rate() years are sorted in descending order", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_equal(result$year, sort(result$year, decreasing = TRUE))
})
test_that("get_chile_literacy_rate() indicator and country columns have consistent values", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_equal(length(unique(result$indicator)), 1)
expect_equal(length(unique(result$country)), 1)
})
test_that("get_chile_literacy_rate() non-NA values are reasonable percentages", {
skip_on_cran()
result <- get_chile_literacy_rate()
non_na_values <- result$value[!is.na(result$value)]
if (length(non_na_values) > 0) {
expect_true(all(non_na_values >= 0))
expect_true(all(non_na_values <= 100)) # Percentages should be 0-100
expect_true(all(non_na_values >= 80)) # Chile should have high literacy rate
}
})
test_that("get_chile_literacy_rate() returns consistent structure", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_false(is.null(result))
expect_s3_class(result, "data.frame")
expect_equal(length(names(result)), 4)
})
test_that("get_chile_literacy_rate() non-NA values are within expected range for Chile", {
skip_on_cran()
result <- get_chile_literacy_rate()
non_na_values <- result$value[!is.na(result$value)]
if (length(non_na_values) > 0) {
# Chile should have very high literacy rates (developed country)
expect_true(all(non_na_values >= 95)) # Lower bound for developed countries
expect_true(all(non_na_values <= 100)) # Upper bound (100%)
}
})
test_that("get_chile_literacy_rate() contains no empty strings in text columns", {
skip_on_cran()
result <- get_chile_literacy_rate()
expect_true(all(nchar(result$indicator) > 0))
expect_true(all(nchar(result$country) > 0))
})
test_that("get_chile_literacy_rate() handles NA values correctly", {
skip_on_cran()
result <- get_chile_literacy_rate()
# NA values are valid from the API and should be preserved
expect_true(is.logical(is.na(result$value)))
# Check that we have some data (not all NA)
expect_true(sum(!is.na(result$value)) > 0)
})
test_that("get_chile_literacy_rate() non-NA values show reasonable stability", {
skip_on_cran()
result <- get_chile_literacy_rate()
non_na_values <- result$value[!is.na(result$value)]
if (length(non_na_values) > 1) {
# Literacy rates should be relatively stable for developed countries
range_difference <- max(non_na_values) - min(non_na_values)
expect_true(range_difference <= 5) # Should not vary by more than 5 percentage points
}
})
test_that("get_chile_literacy_rate() all finite values are realistic literacy percentages", {
skip_on_cran()
result <- get_chile_literacy_rate()
finite_values <- result$value[is.finite(result$value)]
if (length(finite_values) > 0) {
expect_true(all(finite_values >= 90)) # Very high literacy expected for Chile
expect_true(all(finite_values <= 100)) # Cannot exceed 100%
expect_true(all(finite_values > 0)) # Must be positive
}
})
test_that("get_chile_literacy_rate() reflects developed country literacy standards", {
skip_on_cran()
result <- get_chile_literacy_rate()
non_na_values <- result$value[!is.na(result$value)]
if (length(non_na_values) > 0) {
# All available values should reflect very high literacy
expect_true(all(non_na_values >= 96)) # Based on Chile's development level
expect_true(all(non_na_values <= 98)) # Reasonable upper bound considering measurement
}
})
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