Testing

Programming is not just about writing code. It is important to verify that the code does what it should (and about fixing it if needed). The process of verification that the program works as expected is called testing.

You have probably tested your programs by trying to execute them, entered some input data and looked if the results are correct. It is harder to do it for bigger programs. Bigger programs have more possibilities what to do and it is harder to verify that all possibilities do what they should.

That is why developers write code that verifies their program instead of testing their programs manually.

Automated tests are functions that check that the program works correctly. You can execute the tests anytime and verify that the code works. The main benefit is that you can change the code in the future and let the tests verify that the change does not break existing functionalitye.

Installing the pytest library

Up to now, we have used only the modules that come installed with Python, for example, modules such as math or turtle. There are many more libraries that are not included in Python but you can install them to your Python environment and use them.

The library for testing in Python is called unittest. It is quite difficult to use this library so we will use a better one. We will install the library pytest which is easy to use and very popular.

You install libraries into your active virtual environment. We have learned how to create and activate a virtual environment in the lesson about Python installation. Make sure that you have activated a virtual environment.

Submit the following command. (It is a command-line command, just as cd or mkdir; do not enter it into the Python console.)

(venv)$ python -m pip install pytest

Writing tests

We will show testing thtough a very simple example. There is a function add that can add two numbers. There is another function that tests if the add function returns correct results for specific numbers.

Make a copy of the code into a file named test_addition.py in a new empty directory.

The naming of files and test functions is important for pytest (with default settings). It is important for names of files containing tests and test functions to start with test_.

def add(a, b):
    return a + b

def test_add():
    assert add(1, 2) == 3

What does the test function do?

The assert statement evaluates the expression that follows it. If the result is not true then it raises an exception and it makes the test fail. You can imagine that assert a == b does following:

if a != b:
    raise AssertionError('Test failed!')

Running tests

You execute tests with the command python -m pytest -v, followed by the name of the file containing the tests. By using this command you are telling: Python: Execute the module named pytest, in verbose mode, for the given file.

$ python -m pytest -v test_addition.py
============= test session starts =============
platform darwin -- Python 3.6.5, pytest-3.9.1, py-1.7.0, pluggy-0.8.0 -- 
rootdir: learn, inifile: 
collecting ... collected 1 items

test_addition.py::test_add PASSED

============= 1 passed in 0.01 seconds =============

This command scans the given file and calls all functions that start with test_. It checks that they do not raise any exceptions, for example, an exception raised by assert. If an exception occurs, pytest shows a red message with additional details that can help you find the bug and fix it.

Try to change the add function (or its test) and see what happens if a test fails.

Test modules

You do not usually write tests in the same file with the regular code. Typically, you write tests in another file. This way, your code is easier to read, and it makes it possible to distribute only the code, without the tests, to someone who is interested only in executing the program.

Split the test_addition.py file: Move the add function to a new module addition.py. In the test_addition.py file, keep only the test. To the test_addition.py file, add from addition import add to the top so the test can call the tested function.

The test should pass again.

Executable modules

Automated tests have to run "unattended". They are usually executed automatically and the failures are reported automatically (e.g. by email) and the code that passes all tests can be automatically released (installed to a system where it runs or is made available to customers).

What does this mean to us? The input function will not work in tests. There is no-one who can reply.

This can make your work harder sometimes. Let's look at a more complex project: 1D (one-dimensional) tic-tac-toe.

The structure of your 1D tic-tac-toe code could look like this:

import random  # (and possibly other import statements that are needed)

def move(board, space_number, mark):
    """Returns the board with the specified mark placed in the specified position"""
    ...

def player_move(board):
    """Asks the player what move should be done and returns the board
    with the move played.
    """
    ...
    input('What is your move? ')
    ...

def tic_tac_toe_1d():
    """Starts the game

    It creates an empty board and runs player_move and computer_move alternately
    until the game is finished.
    """
    while ...:
        ...
        player_move(...)
        ...

# Start the game:
tic_tac_toe_1d()

If you import this module, Python executes all commands in it from top to bottom.

The first command, import, makes some functions and variables available. Imports do not usually have any side-effects.

The definitions of functions (def statements and everything in them) just define the functions (but they do not execute the functions).

Calling the tic_tac_toe_1d function starts the game. The tic_tac_toe_1d calls the player_move() function which calls input().

If you import this module from tests, the input fails and the module is not imported.

The calling of tic_tac_toe_1d is a side-effect and we need to remove it. Yeah but you cannot start the game without it! What about it?

You can create a new module. Name it game.py and put just this call into it:

import tic_tac_toe

tic_tac_toe.tic_tac_toe_1d()

You cannot test this module because it calls input indirectly. But you can execute it if you want to play. Since you do not have tests for this module, it should be very simple: one import and one statement.

You can import the original module from tests or other modules.

A test for the original module could look like this:

import tic_tac_toe

def test_move_to_empty_space():
    board = tic_tac_toe.computer_move('--------------------')
    assert len(board) == 20
    assert board.count('x') == 1
    assert board.count('-') == 19

Positive and negative tests

The tests that verify that the program works correctly under correct conditions are called positive tests. But you can test what your program does under unexpected conditions.

The tests that check the behavior in case of "invalid" input are called negative tests. They can check for a specific negative result (for example that a call like is_number_even(7) returns False), or that a "reasonable" exception is raised.

For example, the computer_move function should raise an error (for example ValueError) when the board is full.

Use the with statement and the raises function to test that your code raises the expected exception. The raises function is imported from the pytest module. We will explain the with statement later. You just need to know that it checks that the block of code below raises the specified exception:

import pytest

import tic_tac_toe

def test_move_failure():
    with pytest.raises(ValueError):
        tic_tac_toe.computer_move('oxoxoxoxoxoxoxoxoxox')