One frequently wants to repeat the same test with different data sets. When using the functionalities of unittest this requires us to automatically generate test cases with the corresponding methods injected:

To this end, we first construct a test case with one or several methods that will be used, when we later set up test methods. Let's consider the bisection method again and let's check if the values it returns are really zeros of the given function.

We first build the test case and the method which we will use for the tests as follows:

class Tests(unittest.TestCase):
    def checkifzero(self,fcn_with_zero,interval):
        result = bisect(fcn_with_zero,*interval,tol=1.e-8)
        function_value=fcn_with_zero(result)
        expected=0.
        self.assertAlmostEqual(function_value, expected)

Then we dynamically create test functions as attributes of this class:

test_data=[
           {'name':'identity', 'function':lambda x: x,
                                     'interval' : [-1.2, 1.]},
           {'name':'parabola', 'function':lambda x: x**2-1,
                                        'interval' :[0, 10.]},
           {'name':'cubic', 'function':lambda x: x**3-2*x**2,
                                       'interval':[0.1, 5.]},
               ] 
def make_test_function(dic):
        return lambda self :
                   self.checkifzero(dic['function'],dic['interval'])
for data in test_data:
    setattr(Tests, "test_{name}".format(name=data['name']),
                                           make_test_function(data))
if __name__=='__main__':
  unittest.main()

In this example, the data is provided as a list of dictionaries. The make_test_function function dynamically generates a test function, which uses a particular data dictionary to perform the test with the previously defined method checkifzero. Finally, the command setattr is used to make these test functions methods of the class Tests.