Fundamentals

============

Test Driven Development, abbreviated as TDD is a method of software

development which banks on the idea of writing test cases that fail for the

code that doesn't even exist yet. The actual code is written later to pass

the test and then refactored.

First "Test"

============

Writing a test is simple. Writing a failing test? It is much more simple.

Let us consider a very simple program which returns the Greatest Common

Divisor (GCD) of two numbers. Since the test cases for the code is written

prior to the code itself, it is necessary to have a clear idea of the code

units that our program will contain. Let us attempt to clearly define the

code units in our case of a GCD program. Let our program contain one and

only one function called gcd() which takes in two arguments as parameters.

These arguments are the numbers for which GCD must be computed. The gcd()

function returns a single value which is the GCD of the two arguments

passed. So if we want to find out GCD of 44, 23, I will call my code unit

as c = gcd(44, 23) where c will contain the GCD of those two numbers.

Now we have defined our code units, how will we write tests? Before writing

the test, a very fundamental question arises in our minds. How do tests

look like? So let us answer this question first. Tests are nothing but a

series of assertions which are either True or False depending on the

expected behaviour of the code. We tell our tests whether our code unit

asserts True or asserts False based on the expected behaviour of the code

units. If we happen to run the tests now we are sure to get errors. Oh! But

why? We don't even have the function gcd to call. The test code doesn't

even compile! So what should we do now? So the idea is to first write the

stubs for the code units before we start writing tests. This is necessary

for two reasons. Firstly, by writing the stubs for the code units we will

be able to correctly decide and fix on to the code units that we have

planned to include in our program. We have a clear cut idea as to how our

program is structured, how the tests must be written among other

things. Secondly, the tests must at least compile and then fail! If the

tests don't even compile, that doesn't mean the tests failed. It means

it was a failure on the programmer's part. Let us define our stub::

  def gcd(a, b):

      pass

This stub does nothing other than defining a new function called gcd

which takes two parameters a and b for which the GCD must be

calculated. The body of the function just contains Python's **pass**

statement which means it does nothing, i.e. empty. We have our stub

ready. One important thing we need to keep in mind when we adopt TDD

methodology is that we need to have a clear set of results defined for

our code units. To put it more clearly, for every given set of inputs

as test case we must have, before hand, the exact outputs that are

expected for those input test cases. If we don't have that we have

failed in the first step of the TDD methodology itself. We must never

run looking for outputs for our test cases after we have the code

ready or even while writing tests. The expected outputs/behaviour must

be in our hands before we start writing tests. Therefore let us define

our test cases and the expected output for those inputs. Let one of

our test cases be 48 and 64 as *a* and *b* respectively. For this test

case we know that the GCD is 16. So that is the expected output. Let

our second test case be 44 and 19 as *a* and *b* respectively. We know

that their GCD is 1 by simple paper and pen calculation.

Now we know what a test is? What are the ingredients required to write

tests? So what else should we wait for? Let us write our first test!::

  tc1 = gcd(48, 64)

  if tc1 != 16:

      print "Test failed for the case a=48 and b=64. Expected 16. Obtained %d instead." % tc1

      exit(1)

  tc2 = gcd(44, 19)

  if tc2 != 1:

      print "Test failed for the case a=44 and b=19. Expected 1. Obtained %d instead." % tc2

      exit(1)

  print "All tests passed!"

Let us put all these in a file and call this file **gcd.py**::

  def gcd(a, b):

      pass

  if __name__ == '__main__':

      tc1 = gcd(48, 64)

      if tc1 != 16:

          print "Test failed for the case a=48 and b=64. Expected 16. Obtained %d instead." % tc1

          exit(1)

      tc2 = gcd(44, 19)

      if tc2 != 1:

          print "Test failed for the case a=44 and b=19. Expected 1. Obtained %d instead." % tc2

          exit(1)

      print "All tests passed!"

Note that we have introduced a new semantic which uses two new magic names

in Python *__name__* and *__main__*. This is a very common idiom used in

Python. Every Python code in a file can be run in two ways: Either as an

independent stand-alone script or as a Python module which can be imported

by other Python scripts or modules. When the idiom::

  if __name__ == '__main__':

is used, the code within this if block is executed first when we run the

Python file as a stand-alone script. In other words, when we run this

python file as a stand-alone script the control of the program first starts

from the code that is within this if block from which the control is

transferred to other parts of the program or to other modules from

here. This comes as an extremely handy feature especially when we want to

test our modules individually. Now let us run our code as a stand-alone

script.::

  madhu@madhu:~/Desktop$ python gcd.py

  Traceback (most recent call last):

    File "gcd.py", line 7, in <module> print "Test failed for the case a=48 and b=64. Expected 16. Obtained %d instead." % tc1

  TypeError: %d format: a number is required, not NoneType

Now we have our tests, the test cases and the code unit stub at

hand. We also have the failing test. So we know for sure that we have

cleared the first check point of TDD where the tests have failed. The

failing tests also give a green signal for us to go ahead to our next

check point i.e. to write the actual code in our code unit and make

the test pass. So let us write the code for the gcd function by

removing the **pass** control statement which had just created a gcd

function stub for us.

Most of us have learnt in high school math classes that the best and

the easiest known algorithm to compute the gcd of two numbers was

given to us 2300 years ago by a greek mathematician named Euclid. So

let us use the Euclid's algorithm to compute the gcd of two numbers a

and b::

  def gcd(a, b):

      if a == 0:

          return b

      while b != 0:

          if a > b:

              a = a - b

          else:

              b = b - a

      return a

**Note**: If you are unaware of Euclidean algorithm to compute the gcd

of two numbers please refer to it on wikipedia. It has a very detailed

explanation of the algorithm and its proof of validity among other

things.

Now let us run our script which already has the tests written in it

and see what happens::

  madhu@madhu:/media/python/sttp/tdd$ python gcd.py

  All tests passed!

Success! We managed to pass all the tests. But wasn't that code simple

enough? Indeed it was. If you take a closer look at the code you will

soon realize that the chain of subtraction operations can be replaced

by a modulo operation i.e. taking remainders of the division between

the two numbers since they are equivalent operations. Also modulo

operation is far better than chain of subtractions because you will

reduce much faster using modulo operation than the subtraction. For

example if let us take 25, 5 as a and b in our example. If we write

down the steps of the algorithm written above we have the following:

Step 1: a = 25 b = 5: Since both a and b are not 0 and b is greater

than a: b = 25 - 5 = 20

Step 2: Since b is still not 0 and b is greater than a: b = 20 - 5 =

15

Step 3: Since b is still not 0 and b is greater than a: b = 15 - 5 =

10

Step 4: Since b is still not 0 and b is greater than a: b = 10 - 5 = 5

Step 5: Since b is still not 0 and b is equal to a: b = 5 - 5 = 0

Step 6: Since b is 0 the gcd is a = 5 which is returned

If we adopt the modulo operation instead of subtraction and follow the

steps:

Step 1: a = 25 b = 5: Since both a and b are not 0 and b is greater

than a: b = 25 % 5 = 0

Step 2: Since b is 0 the gcd is a = 5 which is returned

Wow! That was overwhelmingly lesser number of steps! So now we are

convinced that if we replace the subtraction operation with the modulo

operation our code performs much better. But if we think carefully we

know that the modulo of a and b is less than b irrespective of how

large the value of a is, including the case where a is already less

than b. So we can eliminate that extra conditional **if** statement by

just swapping the result of the modulo operation to the position of b

and b to the position of a. This ensures that a is always greater than

b and if not the swapping combined with modulo operation takes care of

it. To exemplify it, if a = 5 and b = 25 then by swapping and

performing modulo we have a = b = 25 and b = a % b = 5 % 25 = 5 and

hence we proceed. So let us replace our original code with this new

improved code we have come up with simple observations::

  def gcd(a, b):

      while b != 0:

          a, b = b, a % b

      return a

Executing our script again we will see that all the tests pass. One

final improvement we can think of which is not necessary in terms of

efficiency but is certainly good to do keeping in mind the readability

is that we can use the concept of recursion for the same

algorithm. Without going into much detail this is how the code looks

if we use a recursive approach::

  def gcd(a, b):

      if b == 0:

          return a

      return gcd(b, a%b)

Much shorter and sweeter! And it passes all the tests!

More realistic "Tests"

======================

Now we have successfully completed writing our first test, writing the

relevant code and ensured the tests passed. We also refactored our

code to perform better. With the knowledge of all these and some

concepts and semantics like __main__ magic names we learnt we have

come a long way with respect to writing tests. But our thirst is still

unquenched! We want to do more and more tests! Not just write better

code but also better tests! So let us keep building upon what we have

learnt so far.

Let us start writing tests for more realistic test cases. Generally

tests are predetermined as said above, if not the software design in

itself is flawed. The predetermined tests are stored along with the

test code in some persistent format like in a database, a text file, a

file of specific format like XML or in some other way. Let us continue

with our example of GCD function. We will keep all our test cases in a

text file, which is indeed persistent. Let us specify the format of

the test data in our file as follows.

  1. The file has multiple lines of test data.

  2. Each line in this file corresponds to a single test case.

  3. Each line consists of three comma separated coloumns:

     i. First two coloumns are the integers for which the GCD has to

        be computed

     ii. Third coloumn is the expected GCD to the preceding two

         numbers.

So how do we write our tests to use these test cases? Pretty simple, let

us review the machinery required first.

  1. File reading: We already have learnt this in the modules on

     Basic Python.

  2. Parsing the read data from the file: This just involves a using a

     **for** loop which iterates over the data line by line since we

     know that the file contains each test case as a sepate line which

     are equivalent to the file records and hence parse the data line

     by line as strings as we iterate over it and convert it to the

     required data type.

Since we already have all the machinery required, let us proceed writing

our test cases. We do not need not make any changes to the gcd

function so we will just write down the test here. Let us call our

data file gcd_testcases.dat::

  if __name__ == '__main__':

      for line in open('gcd_testcases.dat'):

          values = line.split(', ')

          a = int(values[0])

          b = int(values[1])

          g = int(values[2])

          tc = gcd(a, b)

          if tc != g:

              print "Test failed for the case a=%d and b=%d. Expected %d. Obtained %d instead." % (a, b, g, tc)

              exit(1)

      print "All tests passed!"

When we execute the gcd.py script again we will notice that all the

tests passed.

Running at the **nose**

=======================

Not too far ahead we go we will start running at the nose saying of

Python developers saying that this is not sufficient to write

complicated tests in an efficient manner and writing tests for the

programs are so important that Python should provide a tool for

managing large tests. To further explain, the idea of placing the

tests with in the Python scripts and to execute them when the script

is run as a stand-alone script works well as long as we have our code

in a single Python file or as long as the tests for each script can be

run separately. But in a more realistic software development scenario,

often this is not the case. The code is spread around multiple Python

scripts, each script also called as a Python module, and also across

several Python packages.

In such a scenario what we would like to do is to create a separate

directory for holding these test. The structure of this directory is

the exact replica of the Python package hierarchy of our software to

be tested. This structure is especially useful because of the fact

that we have a one to one correspondence to our code and to its test.

Hence it is easy for us to navigate through the tests as we maintain

the existing tests and to add new tests as the code evolves. We have a

collection of tests in the specified structure. Any collection of

tests is called as the test suite for the *software package*. Hence we

shall call this directory of tests as our test suite.

Fine we have all these, but how do we make our tests aware that they

are the tests for such and such a Python module or code and when

executed must test that corresponding code? To make the lives of

Python developers and testers easy Python provides a very handy tool

called as **nose**. The name should have been pretty evident from the

heading of this section! So in the rest of this module let us discuss

how to use **nose** to write, maintain and extend our tests as the

code evolves.