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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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eturns_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 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 def test_calculator_returns_error_message_if_x_arg_not_number self 13 self assertraises valueerror self calc add two 3 14 def test_calculator_returns_error_message_if_y_arg_not_number self 15 self assertraises valueerror self calc add 2 three 16 17 18 if __name__ __main__ 19 unittest main when we run all these tests now we can confirm that the method meets our requirements 1 nosetests test_calculator py 2 3 4 ran 4 tests in 0 001 s 5 ok other unit test packages py test this is a similar test runner to nosetest which makes use of the same conventions meaning that you can execute your tests in either of the two a nice feature of pytest is that it captures your output from the test at the bottom in a separate area meaning you can quickly see anything printed to the command line see below i ve found pytest to be useful when executing single tests as opposed to a suite of tests to install the pytest runner follow the same pip install procedure that you followed to install nosetest simply execute pip install pytest and it will grab the latest version and install it on your machine pytest allows you to run your tests by simply issuing the command pytest in the top level project folder 1 pytest 2 test session starts 3 platform linux python 3 9 12 pytest 7 2 1 pluggy 1 0 0 4 rootdir home vaati desktop tdd test 5 collected 4 items 6 7 test_calculator py 100 8 9 4 passed in 0 01s an example of pytest s output when printing from within your tests or code is shown below this can be useful for quickly debugging your tests and seeing some of the data it is manipulating note you will only be shown output from your code on errors or failures in your tests otherwise pytest suppresses any output 1 pytest 2 test session starts 3 platform linux python 3 9 12 pytest 7 2 1 pluggy 1 0 0 4 rootdir home vaati desktop tdd test 5 collected 4 items 6 7 test_calculator py f 100 8 9 failures 10 _____________________________ tddinpythonexample test_calculator_add_method_returns_correct_result _____________________________ 11 12 self test test_calculator tddinpythonexample testmethod test_calculator_add_method_returns_correct_result 13 14 def test_calculator_add_method_returns_correct_result self 15 result self calc add 2 2 16 self assertequal 4 result 17 e assertionerror 4 0 18 19 test_calculator py 9 assertionerror 20 captured stdout call 21 x is 2 22 y is 2 23 result is 0 24 short test summary info 25 failed test_calculator py tddinpythonexample test_calculator_add_method_returns_correct_result assertionerror 4 0 26 1 failed 3 passed in 0 02s unittest python s built in unittest package that we have used to create our tests can actually be executed itself and gives nice output this is useful if you don t wish to install any external packages and keep everything pure to the standard library to use this simply add the following block to the end of your test file 1 if __name__ __main__ 2 unittest main execute the test using python calculator_tests py here is the output that you can expect 1 python test test_calculator py 2 3 4 ran 4 tests in 0 004s 5 ok debug code with pdb often when following tdd you will encounter issues with your code and your tests will fail there will be occasions where when your tests do fail it isn t immediately obvious why that is happening in such instances it will be necessary to apply some debugging techniques to your code to understand exactly how the code is manipulating the data and not getting the exact response or outcome that you expect fortunately when you find yourself in such a position there are a couple of approaches you can take to understand what the code is doing and rectify the issue to get your tests passing the simplest method and one many beginners use when first writing python code is to add print statements at certain points in your code and see what they output when running tests debug with print statements if you deliberately alter our calculator code so that it fails you can get an idea of how debugging your code will work change the code in the add method of app calculator py to subtract the two values 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 when you run the tests now the test which checks that your add method correctly returns four when adding two plus two fails as it now returns 0 to check how it is reaching this conclusion you could add some print statements to check that it is receiving the two values correctly and then check the output this would then lead you to conclude the logic on the addition of the two numbers is incorrect add the following print statements to the code in app calculator py 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 print x is format x 6 print y is format y 7 result x y 8 print result is format result 9 return result 10 else 11 raise valueerror now when you execute nosetest against the tests it nicely shows you the captured output for the failing test giving you a chance to understand the problem and fix the code to use addition rather than subtraction 1 nosetests test 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 11 in test_calculator_add_method_returns_correct_result 8 self assertequal 4 result 9 assertionerror 4 0 10 begin captured stdout 11 x is 2 12 y is 2 13 result is 0 14 end captured stdout 15 16 ran 4 tests in 0 002s 17 failed failures 1 advanced debug with pdb as you start to write more advanced code print statements alone will not be enough or start to become tiresome to write all over the place and have to be cleaned up later as the process of needing to debug has become commonplace when writing code tools have evolved to make debugging python code easier and more interactive one of the most commonly used tools is pdb or python debugger the tool is included in the standard library and simply requires adding one line where you would like to stop the program execution and enter into pdb typically known as the breakpoint using our failing code in the add method try adding the following line before the two values are subtracted 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 import pdb pdb set_trace 6 return x y 7 else 8 raise valueerror if using nosetest to execute the test be sure to execute using the s flag which tells nosetest not to capture standard output otherwise your test will just hang and not give you the pdb prompt using the standard unittest runner and pytest does not require such a step with the pdb code snippet in place when you execute the test now the execution of the code will break at the point at which you placed the pdb line allowing you to interact with the code and variables that are currently loaded at the point of execution when the execution first stops and you are given the pdb prompt try typing list to see where you are in the code and what line you are currently at 1 nosetests s 2 users user pycharmprojects tdd_in_python app calculator py 7 add 3 return x y 4 pdb list 5 2 def add self x y 6 3 number_types int float complex 7 4 8 5 if isinstance x number_types and isinstance y number_types 9 6 import pdb pdb set_trace 10 7 return x y 11 8 else 12 9 raise valueerror 13 eof 14 pdb you can interact with your code as if you were within a python prompt so try evaluating what is in the x and y variables at this point 1 pdb x 2 2 3 pdb y 4 2 you can continue to play around with the code as you require to figure out what is wrong you can type help at any point to get a list of commands but here s the core set you will likely need n step forward to the next line of execution list show five lines either side of where you are currently executing to see the code involved with the current execution point args list the variables involved in the current execution point continue run the code through to completion jump line number run the code until the specified line number quit exit stop pdb conclusion test driven development is a process that can be both fun to practice and hugely beneficial to the quality of your production code its flexibility in its application to anything from large projects with many team members right down to a small solo project means that it s a fantastic methodology to advocate to your team whether pair programming or developing by yourself the process of making a failing test pass is hugely satisfying if you ve ever argued that tests weren t necessary hopefully this article has swayed your approach for future projects make tdd a part of your daily workflow today coding fundamentals testing python by david sale like your all in one creative asset toolkit start now unlimited downloads from 16 50 month get access to over one million creative assets on envato over 9 million digital assets everything you need for your next creative project create beautiful logos designs mockups in seconds design like a professional without photoshop join the community share ideas host meetups lead discussions collaborate discover about envato our pricing plans stock video video templates royalty free music stock photos fonts popular searches license user terms license terms terms conditions privacy policy acceptable use policy fair use policy cookies cookie settings do not sell or share my personal information resources discover tuts video music design marketing web design explore blog help help center become an affiliate about us who we are our products 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