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description= In this tutorial, I will introduce the core concepts of TDD, and will provide examples in Python, using the nosetests unit-testing package. I will additionally offer some alternative packages.;
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er yii coding fundamentals coding fundamentals view all coding fundamentals oop functional programming databases sql security testing workflow design patterns rest api machine learning authentication version control git performance xml ajax regular expressions tools terminal and cli python python view all python django ruby ruby view all ruby ruby on rails game development cloud hosting cloud hosting view all cloud hosting aws web servers hosting scaling music tuts youtube envato get unlimited creative assets go to envato tuts youtube design business photo video web design code wordpress start learning plugin development theme development all wordpress mobile development start learning ios development ios templates android development android templates react native development react native templates ionic development ionic templates corona firebase kotlin all mobile development javascript start learning react vue js node jquery angular web apis all javascript php start learning laravel php scripts codeigniter yii all php coding fundamentals start learning oop functional programming databases sql security testing workflow design patterns rest api machine learning authentication version control git performance xml ajax regular expressions tools terminal and cli all coding fundamentals python start learning django all python ruby start learning ruby on rails all ruby game development cloud hosting start learning aws web servers hosting scaling all cloud hosting music get unlimited creative assets home code coding fundamentals testing how to begin with test driven development in python scroll to top david sale feb 28 2023 18 min read copied to clipboard coding fundamentals testing python test driven development tdd is a concept that s had a lot of attention in recent years it is a practice of baking your tests right into your everyday coding rather than leaving them as an afterthought in this post i will introduce the core concepts of tdd the whole process is very simple to get to grips with and it shouldn t take too long before you wonder how you were able to get anything done before there are huge gains to be made from tdd namely the quality of your code improving but also clarity and focus on what it is that you are trying to achieve and the way in which you will achieve it tdd also works seamlessly with agile development and can best be utilized when pair programming as you will see later on in this tutorial i will introduce the core concepts of tdd and will provide examples in python using the nosetests unit testing package i will additionally offer some alternative packages that are also available within python what is test driven development tdd in its most basic terms is the process of implementing code by writing your tests first seeing them fail and then writing the code to make the tests pass you can then build upon this developed code by appropriately altering your test to expect the outcome of additional functionality before writing the code to make it pass again you can see that tdd is very much a cycle with your code going through as many iterations of tests writing and development as necessary until the feature is finished implementing these tests before you write the code brings out a natural tendency to think about your problem first while you start to construct your test you have to think about the way you design your code what will this method return what if we get an exception here and so on developing in this way means you consider the different routes through the code and cover these with tests as needed this approach allows you to escape the trap that many developers fall into myself included diving into a problem and writing code exclusively for the first solution you need to handle the process can be defined as write a failing unit test make the unit test pass refactor repeat this process for every feature as necessary agile development with test driven development tdd is a perfect match for the ideals and principles of agile development with a focus on delivering incremental updates to a product with true quality as opposed to quantity the confidence in your individual units of code that unit testing provides means that you meet this requirement to deliver quality while eradicating issues in your production environments tdd comes into its own when pair programming however the ability to mix up your development workflow when working as a pair as you see fit is nice for example one person can write the unit test see it pass and then allow the other developer to write the code to make the test pass the roles can either be switched each time each half day or every day as you see fit this means both parties in the pair are engaged focused on what they are doing and checking each other s work at every stage this translates to a win in every sense with this approach i think you d agree tdd also forms an integral part of the behaviour driven development process which is again writing tests up front but in the form of acceptance tests these ensure a feature behaves in the way you expect from end to end syntax for unit testing the main methods that we make use of in unit testing for python are assert base assert allowing you to write your own assertions assertequal a b check a and b are equal assertnotequal a b check a and b are not equal assertin a b check that a is in the item b assertnotin a b check that a is not in the item b assertfalse a check that the value of a is false asserttrue a check that the value of a is true assertisinstance a type check that a is of type type assertraises error a args check that when a is called with args it raises error there are certainly more methods available to us which you can view see the python unit test docs but in my experience the ones listed above are among the most frequently used we will make use of these within our examples below installing and using python s nose before starting the exercises below you will need to install the nosetest test runner package installation of the nosetest runner is straightforward following the standard pip install pattern it s also usually a good idea to work on your projects using virtualenv s which keeps all the packages you use for various projects separate if you are unfamiliar with pip or virtualenv s you can find documentation on them here virtualenv pip the pip install is as easy as running this line 1 pip install nose once installed you can execute a single test file 1 nosetests example_unit_test py or execute a suite of tests in a folder 1 nosetests path to tests the only standard you need to follow is to begin each test s method with test_ to ensure that the nosetest runner can find your tests options some useful command line options that you may wish to keep in mind include v gives more verbose output including the names of the tests being executed s or nocapture allows output of print statements which are normally captured and hidden while executing tests useful for debugging nologcapture allows output of logging information rednose an optional plugin which can be downloaded here but provides colored output for the tests tags tags allows you to place a tag above a specific test to only execute those rather than the entire test suite example problem and test driven approach we are going to take a look at a really simple example to introduce both unit testing in python and the concept of tdd we will write a very simple calculator class with add subtract and other simple methods as you would expect following a tdd approach let s say that we have a requirement for an add function which will determine the sum of two numbers and return the output let s write a failing test for this in an empty project create two python packages app and test to make them python packages and thus support importing of the files in the tests later on create an empty file called __init__ py in each directory this is python s standard structure for projects and must be followed to allow items to be imported across the directory structure for a better understanding of this structure you can refer to the python packages documentation create a file named test_calculator py in the test directory with the following contents 1 import unittest 2 3 class tddinpythonexample unittest testcase 4 def test_calculator_add_method_returns_correct_result self 5 calc calculator 6 result calc add 2 2 7 self assertequal 4 result writing the test is fairly simple first we import the standard unittest module from the python standard library next we need a class to contain the different test cases finally a method is required for the test itself with the only requirement being that it is named with test_ at the beginning so that it may be picked up and executed by the nosetest runner which we will cover shortly with the structure in place we can then write the test code we initialize our calculator so that we can execute the methods on it following this we can then call the add method which we wish to test and store its value in the variable result once this is complete we can then make use of unittest s assertequal method to ensure that our calculator s add method behaves as expected now you will use the nosetest runner to execute the test you could execute the test using the standard unittest runner if you wish by adding the following block of code to the end of your test file 1 if __name__ __main__ 2 unittest main this will allow you to run the test using the standard way of executing python files python test_calculator py however for this tutorial you will use the nosetests runner which has some nice features such as executing nose tests against a directory and running all tests 1 nosetests test_calculator py 2 e 3 4 error test_calculator_add_method_returns_correct_result test test_calculator tddinpythonexample 5 6 traceback most recent call last 7 file users user pycharmprojects tdd_in_python test test_calculator py line 6 in test_calculator_add_method_returns_correct_result 8 calc calculator 9 nameerror global name calculator is not defined 10 11 ran 1 test in 0 001s 12 failed errors 1 from the output nosetest has given us we can see that the problem relates to us not importing calculator that s because we haven t created it yet so let s go and define our calculator in a file named calculator py under the app directory and import it app calculator py 1 class calculator object 2 def add self x y 3 pass test_calculator py 1 import unittest 2 from app calculator import calculator 3 4 class tddinpythonexample unittest testcase 5 def test_calculator_add_method_returns_correct_result self 6 calc calculator 7 result calc add 2 2 8 self assertequal 4 result 9 10 if __name__ __main__ 11 unittest main now that we have calculator defined let s see what nosetest indicates to us now 1 nosetests test_calculator py 2 f 3 4 fail test_calculator_add_method_returns_correct_result test test_calculator tddinpythonexample 5 6 traceback most recent call last 7 file users user pycharmprojects tdd_in_python test test_calculator py line 9 in test_calculator_add_method_returns_correct_result 8 self assertequal 4 result 9 assertionerror 4 none 10 11 ran 1 test in 0 001s 12 failed failures 1 so obviously our add method is returning the wrong value as it doesn t do anything at the moment handily nosetest gives us the offending line in the test and we can then confirm what we need to change let s fix the method and see if our test passes now calculator py 1 class calculator object 2 def add self x y 3 return x y output 1 nosetests test_calculator py 2 3 4 ran 1 test in 0 000s 5 ok success we have defined our add method and it works as expected however there is more work to do around this method to ensure that we have tested it properly we have fallen into the trap of just testing the case we are interested in at the moment what would happen if someone were to add anything other than numbers python will actually allow for the addition of strings and other types but in our case for our calculator it makes sense to only allow adding of numbers let s add another failing test for this case making use of the assertraises method to test if an exception is raised here test_calculator py 1 import unittest 2 from app calculator import calculator 3 4 class tddinpythonexample unittest testcase 5 def setup self 6 self calc calculator 7 def test_calculator_add_method_returns_correct_result self 8 result self calc add 2 2 9 self assertequal 4 result 10 def test_calculator_returns_error_message_if_both_args_not_numbers self 11 self assertraises valueerror self calc add two three 12 13 if __name__ __main__ 14 unittest main you can see above that we added the test and are now checking for a valueerror to be raised if we pass in strings we could also add more checks for other types but for now we ll keep things simple you may also notice that we ve made use of the setup method this allows us to put things in place before each test case so as we need our calculator object to be available in both test cases it makes sense to initialize this in the setup method let s see what nosetest indicates to us now 1 nosetests test_calculator py 2 f 3 4 fail test_calculator_returns_error_message_if_both_args_not_numbers test test_calculator tddinpythonexample 5 6 traceback most recent call last 7 file users user pycharmprojects tdd_in_python test test_calculator py line 15 in test_calculator_returns_error_message_if_both_args_not_numbers 8 self assertraises valueerror self calc add two three 9 assertionerror valueerror not raised 10 11 ran 2 tests in 0 001s 12 failed failures 1 clearly nosetests indicates to us that we are not raising the valueerror when we expect to be now that we have a new failing test we can code the solution to make it pass 1 class calculator object 2 def add self x y 3 number_types int float complex 4 if isinstance x number_types and isinstance y number_types 5 return x y 6 else 7 raise valueerror from the code above you can see that we ve made a small addition to check the types of the values and whether they match what we want one approach to this problem could mean that you follow duck typing and simply attempt to use it as a number and try except the errors that would be raised in other cases the above is a bit of an edge case and means we must check before moving forward as mentioned earlier strings can be concatenated with the plus symbol so we only want to allow numbers using the isinstance method allows us to ensure that the provided values can only be numbers to complete the testing there are a couple of different cases that we can add as there are two variables it means that both could potentially not be numbers add the test case to cover all the scenarios 1 import unittest 2 from app calculator import calculator 3 4 class tddinpythonexample unittest testcase 5 def setup self 6 self calc calculator 7 def test_calculator_add_method_returns_correct_result self 8 result self calc add 2...
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