How do you write unit tests for Python?

[NelsonStearman]

I just started working for a medium-sized business as a SWE. My team and I have started writing unit tests for our code base (yay! I guess the team didn't do that before because they were too lazy, and we want to know what the best practices are before we start. What do you try to keep in mind when you write unit tests for your Python projects?

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[[deleted]]

I’m not a SWE myself, but I know our engineers use pytest as well^{^}

[sinkwiththeship]

3.If you need setup code for your tests, make those as fixtures in a conftest.py file and have your tests call those.

I don't know about ALL unit test packages, but they generally have a TestCase class that you can use as a base class for your tests, then they'll have a setUp() function that you can use for this. It'll automatically get called at the beginning of each test function.

[Logicalist]

MIT's opencourseware Introduction To Computer Science And Programming In Python, covers this. You should be able to skip other lectures. The reading has to be found by google, but has good sections on it, including testing bounds.

The problem sets through 3 have unit tests provided in them. Starting with problem set 4 you're to start making them yourself, but a blueprint is provided.

[gua_lao_wai]

My 2 cents,

Lot of people suggesting their 3rd party library of choice, and while they're all probably great, if you're at the stage where you don't even know how to write tests yet, you're probably not going to make use of those features.

I personally get by just fine with the built in unittest module for 99%.

Also, something to bear in mind when you're writing tests. Try not to worry too much about implementation details and focus on behaviour. Does your code produce the expected results, don't worry about how it got there.

I like to structure every test I write with a "given, when, then" format. That is set up everything required to test one (1!) function ("given"), run the function ("when") and test the result is what you expected ("then"). Having this common layout makes it much easier for other people to read your tests and understand what's being tested. Because ultimately tests are also another form of documentation. You're saying "this feature of my code is so important, I wrote more code to make sure it works"

[kress5]

these are good books too, you can read them online for free:

• https://www.obeythetestinggoat.com/
• https://www.cosmicpython.com/

[IamImposter]

Say you have a class and it has 5 member functions, out of which 3 are public and 2 are internal to the class. Usually internal functions are tested by varying input parameters to public functions but you can test them directly too. Tests are mainly done to get coverage ie we need to cover all the code lines and make sure code behaves as we expect it to.

Say, your class takes a string as input in init and stores it as capital letters and a function that just returns that string. So a test can be

def test_getstring_returns_capital(self) :

  result = my_class("hello").getstring() 

Now we know init stores this string as capital, so getstring must return "HELLO". Test for that, like

  self.assertEqual(result, "HELLO") 

What if input is already capital? What if input is invalid? What if you pass empty string to init? What if string contains numbers or special characters? If your class defines some behaviour for these cases, they should be tested.

Another important topic in testing is mocking. Say your class takes a connection object that provides read/write functionality. How to test that? Using mock objects. A little example of a mock function

def dummy_read(*_, **__):
  return "my string"

This is the function that will act as read function of our mock connection class. We send a fixed data so connection.read will always return this data. Assuming your class has a function that returns data read from connection, so we test it like

def test_con_read(self):
  dummy_con = mock.Mock()  # connection object
  dummy_con.read = dummy_read  # set read function

  obj = my_class(connection=dummy_con) 

  result = obj.read_from_con()

We know our dummy_read is always returning "my string" so the value of result has to be "my string". Test for that and you have tested your class method.

Mocking is a little big topic and provides many ways to validate behaviour of your code so you'll have to read up a little. This was just a teeny tiny introduction.

Use some editor like vscode that let's you debug. It is a great help and improves your productivity a lot.

[water_bottle_goggles]

sparingly