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IUNIT TESTING PYTHON HOW TO
IUNIT TESTING PYTHON SOFTWARE

In the case of Fedora or Red Hat Enterprise Linux, it is the RPM database. The usual way to look at that metadata is through your package manager.

IUNIT TESTING PYTHON SOFTWARE

python -m unittest test_advanced_fish_tank.When installing software on a Linux system, your package manager keeps track of what's installed, what it's dependent upon, what it provides, and much more.

The test_fish_tank_writes_file method verifies that the default contents of "shark, tuna" are written to the fish_tank.txt file.įrom the same directory as test_advanced_fish_tank.py let’s run: This way, each test starts with a clean slate.

The tearDown method calls the empty_tank method on self.fish_tank: this ensures that the fish_tank.txt file is removed after each test method runs. The setUp method creates an AdvancedFishTank instance and assigns it to self.fish_tank. The TestAdvancedFishTank TestCase subclass defines both a setUp and tearDown method. AdvancedFishTank also exposes an empty_tank method that removes the fish_tank.txt file. AdvancedFishTank creates a file named fish_tank.txt and writes the string "shark, tuna" to it. Test_advanced_fish_tank.py defines a class named AdvancedFishTank. empty_tank ( ) def test_fish_tank_writes_file (self ) : with open (self. fish_tank = AdvancedFishTank ( ) def tearDown (self ) :

fish_tank_file_name ) class TestAdvancedFishTank (unittest. write (default_contents ) def empty_tank (self ) : fish_tank_file_name = "fish_tank.txt"ĭefault_contents = "shark, tuna" with open (self. If we run the previous command, we will receive the following output:Ĭlass AdvancedFishTank : def _init_ (self ) : test_fish_tank_can_be_filled verifies that has_water is set to True after calling fill_with_water().įrom the same directory as test_fish_tank.py, we can run: test_fish_tank_empty_by_default verifies that has_water starts off as False. Since setUp is run before every individual test method, a new FishTank instance is instantiated for both test_fish_tank_empty_by_default and test_fish_tank_can_be_filled. The TestCase subclass TestFishTank defines a method named setUp that instantiates a new FishTank instance and assigns that instance to self.fish_tank. FishTank.has_water is initially set to False, but can be set to True by calling FishTank.fill_with_water(). Test_fish_tank.py defines a class named FishTank. has_water ) def test_fish_tank_can_be_filled (self ) : fish_tank = FishTank ( ) def test_fish_tank_empty_by_default (self ) : has_water = True class TestFishTank (unittest. has_water = False def fill_with_water (self ) : When we run this command, we receive output like the following:

python -m unittest test_add_fish_to_aquarium.py.

When we call str() on that ValueError to retrieve its message, it returns the correct exception message we expected.įrom the same directory as test_add_fish_to_aquarium.py, let’s run our test: The exception attribute on exception_context contains the underlying ValueError that add_fish_to_aquarium raised. The self.assertRaises context manager is bound to a variable named exception_context. The first argument to self.assertRaises is the Exception class that we expect to be raised-in this case, ValueError. Test_add_fish_to_aquarium_exception uses the with self.assertRaises(.) context manager provided by TestCase to check that add_fish_to_aquarium rejects the inputted list as too long. The new test method test_add_fish_to_aquarium_exception also invokes the add_fish_to_aquarium function, but it does so with a 25 element long list containing the string "shark" repeated 25 times. exception ), "A maximum of 10 fish can be added to the aquarium" ) assertRaises (ValueError ) as exception_context :Īdd_fish_to_aquarium (fish_list =too_many_fish ) assertEqual (actual, expected ) def test_add_fish_to_aquarium_exception (self ) : Test_add_fish_to_aquarium.py import unittestĭef add_fish_to_aquarium (fish_list ) : if len (fish_list ) > 10 : raise ValueError ( "A maximum of 10 fish can be added to the aquarium" ) return TestCase provides the general scaffolding for testing our functions. One of the most important classes provided by the unittest module is named TestCase.

IUNIT TESTING PYTHON HOW TO

You can review the How To Define Functions in Python 3 tutorial, which is part of the How To Code in Python 3 series.

An understanding of functions in Python.To get the most out of this tutorial, you’ll need: In this tutorial, you will use Python’s unittest module to write a test for a function. Teams adhering to test-driven development may find unittest useful to ensure all authored code has a corresponding set of tests. Tests written using the unittest module can help you find bugs in your programs, and prevent regressions from occurring as you change your code over time. The Python standard library includes the unittest module to help you write and run tests for your Python code. The author selected the COVID-19 Relief Fund to receive a donation as part of the Write for DOnations program.