# Test code goes here!
library(testthat)
# refer: http://r-pkgs.had.co.nz/tests.html
context(" ") # any info about this question
test_that("test sub question 1", {
expect_equal(nchar("a"), 1)
expect_true(var_name == correct_ans)
})
test_that("test sub question 2", {
expect_equal(length("a"), 1)
})A template for testing R code using testthat.
Fill in some description in the context( or just ignore it).
Test each sub questoins. For example you are asking student to calculate the (1)sum of 1 to 10, (2) sum of 11 to 20:
test_that("test sum of 1 to 10", {
expect_equal(sum_10, 55)
})
test_that("test sum of 11 to 20", {
expect_equal(sum_20, 165)
})However if their submissions are wrong, expect_equal the error message will expose the correct answer.
sum_10 = 40
test_that("test sum of 1 to 10", {
expect_equal(sum_10, 55)
})Error: Test failed: ‘test sum of 1 to 10’ *
sum_10not equal to 55. 1/1 mismatches [1] 40 - 55 == -15
Message not equal to 55 indicate that the right answer is 55. It is better to use expect_true to hide the answer:
sum_10 = 40
correct_sum_10 = 55
test_that("test sum of 1 to 10", {
expect_true(sum_10 == correct_sum_10)
})Error: Test failed: ‘test sum of 1 to 10’ * sum_10 == correct_sum_10 isn’t true.
| funs | desc |
|---|---|
| expect_ture | expression return true |
| expect_false | expression return false |
| expect_equal(obj, expected, tolerance = 1e-5) | modify tolerance to test float equal |
| expect_identical | exactly the same |
| expect_length | test length |
For more test functions, refer to http://r-pkgs.had.co.nz/tests.html.
# test x == c(1, 2,3)
x = 1:3
test_that('test x',{
expect_equal(x, c(1,2,3))
})
answer = c(1,2,4)
test_that('test x',{
expect_true(all(x == answer))
})df = head(iris)
# 1. class
expect_is(df, 'data.frame') # if use dplyr, test if it is
# 2. dimension
expect_equal(dim(df), c(6, 5))
# 3. colnames
answer = colnames(iris)
expect_equal(colnames(df), answer)
# 4. values
# It's hard to test all the values in a data.frame.
# one way is merge the data.frame with the coorrect and check
# whether the dimension remains the same
answer = head(iris)
expect_equal(dim(merge(df, answer)), dim(df))## test a scatter plot in ggplot2
library(ggplot2)
p_scatterplot = ggplot(cars, aes(x=speed, y=dist)) + geom_point()
# 1. class
expect_is(p_scatterplot, 'ggplot')
# 2. test mappings
expect_true(unlist(p_scatterplot)$mapping.x == 'speed')
expect_true(unlist(p_scatterplot)$mapping.y == 'dist')
# 3. test layer, whether it is a point layer
expect_is(layer_grob(p_scatterplot)[[1]], 'points')# test labels and title
p_title = p_scatterplot + xlab('Speed (mpg)') +
ylab('Stopping Distance (ft)') +
ggtitle("Scatterplot of Speed/Distance")
# 1. x label
expect_true(unlist(p_title)$labels.x == 'Speed (mpg)')
# 2. y label
expect_true(unlist(p_title)$labels.y == 'Stopping Distance (ft)')
# 3. title
expect_true(unlist(p_title)$labels.title == 'Scatterplot of Speed/Distance')# Test code goes here!
import unittest
import json
class MyTest(unittest.TestCase):
def setUp(self):
pass # before all test* method run
def tearDown(self):
pass # after all test* method done
# define testing functions here
def test_sub_question_1(self):
self.assertEqual(1, 1)
self.assertAlmostEqual(1, 1-1e-14)
def test_sub_question_2(self):
self.assertEqual(1, 1)
self.assertAlmostEqual(2, 9 / 4.5)
## dont touch the following code
if __name__ == '__main__':
suite = unittest.TestLoader().loadTestsFromTestCase(*[MyTest])
testResult = unittest.TextTestRunner(verbosity=2).run(suite)
total = testResult.testsRun
if total == 0:
res = {'score': 1, 'output': []}
else:
errors = [x[1] for x in testResult.errors]
failures = [x[1] for x in testResult.failures]
score = 1 - 1.0 * (len(errors) + len(failures)) / total
res = {'score': score, 'test_output': errors + failures}
print json.dumps(res)Define methods inside the MyTest class, each sub question should have a correseponding test method. For example:
class MyTest(unittest.TestCase):
# define testing functions here
def test_sum10(self):
self.assertEqual(sum_10, 55)
def test_10devide3(self):
# assertAlmostEqual used for float comparsion
test_x = 10 / 3
self.assertAlmostEqual(, 10 / 3.0)| funs | desc |
|---|---|
| self.assertAlmostEqual | test float numbers |
| self.assertTrue | expression return true |
| self.assertFalse | expression return false |
| self.assertIn | in |
| self.assertNotIn | not in |
| self.assertIsInstance | if it belongs to a class |
| expect_identical | exactly the same |
| expect_length | test length |