1: Python’s assert keyword#

This tutorial defines the assert keyword in Python and shows how it can be used to write test cases for a simple function.

Other lessons in this tutorial:#

This lesson covers:#

Assert keyword
Test for Pass
Test for Fail


The example plugin and all the tests discussed in this lesson are available in this GitHub repository.

Assert keyword#

The key to testing in Python is the assert keyword. We assert a Boolean expression is true and create an error message that appears when that expression is false.

assert <Boolean expression>, <error message>    

If it is true, code execution continues as though the assert statement doesn’t exist. If the Boolean expression is false, an AssertionError is thrown, an exception raised, and the error message displayed.

Here is a simple function, get_grade_from_mark. It takes a mark (score) from zero to 100. If the mark (score) is more than 50, the grade is Pass; if it’s less than 50, the grade is Fail.

def get_grade_from_mark(mark):
    if mark > 50: 
        return "Pass"
        return "Fail"

get_grade_from_mark can be tested by writing two test functions. The first one is for when the mark is > 50.

Test for the Pass case#

When the mark is > 50, call get_grade_from_mark and assert that the grade is what we expect (either Pass or Fail). When testing the passing case, test that the grade is Pass. If it’s not Pass, the best practice is to write a helpful error message like, "Expected {mark} to pass but result was {grade}."

def test_get_grade_pass(mark):
    grade = get_grade_from_mark(mark):
    assert grade == "Pass", f"Expected {mark} to pass, but result was{grade}"

Test for the Fail case#

Test the same thing for Fail to test all options. Everything is almost the same, so copy and paste and change a few words to create the second test.

def test_get_grade_fail(mark):
    grade = get_grade_from_mark(mark):
    assert grade == "Fail", f"Expected {mark} to fail, but result was{grade}"

We can now write code to run both of the functions with expected values. For example, we expect 65 to pass and 43 to fail. After running both functions, if no exception has been raised we print “All passing.”

if __name__ == "__main__":
    print("All passing.")

We can place all this code in a Python file, e.g. example_test.py, and run it from the command line.

(napari-env) user@directory % python example_test.py
All passing.

We now update the test to see what a failure looks like:

if __name__ == "__main__":
    test_get_grade_fail(70)  # updated this to 70 to force failure
    print("All passing.")

If we assert that 70 fails, the AssertionError, “Expected something to fail, but the result was pass.” would be thrown, which is correct. It would look like this:

(napari-env) user@directory % python example_func.py  
Traceback (most recent call last):  
File “/Users/user/directory/example_test.py” line 20, in <module> test_get_grade_fail(70)  
File “/Users/user/directory/example_test.py” line 16, in <module> test_get_grade_fail  
Assert grade == “Fail”, f”Expected {mark} to fail, but result was {grade}”  
AssertionError: Expected 70 to fail, but result was Pass.   

Note that when the assertion fails, a traceback occurs.

This example is a simple way to demonstrate the use of the assert keyword, but it’s not particularly useful for testing a larger codebase. This test function has to be called explicitly to test different marks. There’s not much detail when the code is running. We just get “All passing.” and there’s no information about other tests when one of the tests fails.

Making testing more convenient is where testing frameworks, like pytest come in.