Python Unit Test Automation

Listing 4-4.  test_module03.py
from mypackage.mymathlib import *
math_obj = 0
def setUpModule():
    """called once, before anything else in this module"""
    print("In setUpModule()...")
    global math_obj
    math_obj = mymathlib()
def tearDownModule():
    """called once, after everything else in this module"""
    print("In tearDownModule()...")
    global math_obj
    del math_obj
class TestClass02:
    @classmethod
    def setUpClass(cls):

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        """called once, before any test in the class"""
        print("In setUpClass()...")
    def setUp(self):
        """called before every test method"""
        print("\nIn setUp()...")
    def test_case01(self):
        print("In test_case01()")
        assert math_obj.add(2, 5) == 7
    def test_case02(self):
        print("In test_case02()")
    def tearDown(self):
        """called after every test method"""
        print("In tearDown()...")
    @classmethod
    def tearDownClass(cls):
        """called once, after all tests, if setUpClass() successful"""
        print ("\nIn tearDownClass()...")
If you run the code in Listing 
4-4
 with the following command:
nosetests test_module03.py -v
The output will be as follows:
test.test_module03.TestClass02.test_case01 ... ok
test.test_module03.TestClass02.test_case02 ... ok
----------------------------------------------------------------------
Ran 2 tests in 0.010s
OK
In order to get more details of test execution, you need to add the -s option to the 
command line, which allows any stdout output to be printed in the command line 
immediately.
Run the following command:
nosetests test_module03.py -vs

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The output is as follows:
In setUpModule()...
Creating object : mymathlib
In setUpClass()...
test.test_module03.TestClass02.test_case01 ...
In setUp()...
In test_case01()
In tearDown()...
ok
test.test_module03.TestClass02.test_case02 ...
In setUp()...
In test_case02()
In tearDown()...
ok
In tearDownClass()...
In tearDownModule()...
Destroying object : mymathlib
----------------------------------------------------------------------
Ran 2 tests in 0.011s
OK
From now onward, we will add the -s option to the nosetests command while 
executing the tests.
Fixtures for Functions
Before you get started with the fixtures for functions, you must understand the difference 
between a function and a method in Python. A function is a named piece of code that 
performs an operation and a method is a function with an extra parameter that’s the 
object on which it runs. A function is not associated with a class. A method is always 
associated with a class.
Check the code in Listing 
4-5
 as an example.