The Basics of Test Driven Web Development with Python

Software development is a challenging task whose validity is proved only by the totally functional digital product that operates in accordance with expectations. In the days of yore, programmers of any specialization (be it web developers or back-end engineers) had to wait till the code writing was completed to check whether the solution they created was a viable one. Why? Because they took for granted the premise forwarded by Glenford Myers in his Software Reliability in 1976 that a developer should never test the code they wrote. 

The evolution of approaches in the IT realm has brought about a U-turn in many conventional practices ushering in new technologies that prescribe a different avenue of handling the coding/testing algorithm. The roots of this changeover go back to the 2003 book by Kent Beck when the entire high-tech world learned the term “test driven development” (TDD for short), which is recommended to follow by most high-profile software consultants today.

Test Driven Development Explained

This approach runs counter to what generations of programmers have been accustomed to for ages: the first-build-then-test scheme or the so-called architecture driven design. Instead, TDD web development departs from the tenet voiced in the 1998 article on Extreme Programming: write the test first. So, building any software piece, developers kick off by creating a small test that would check the operability of a feature based on the understanding of it that developers have prior to the actual building of it. 

The aim of this technique is to fine-tune or even overhaul the code only in case the test miscarries (which, in fact, rules out any occurrences of test script duplication). The code obtained in such a way proves to be an optimized one that is both reliable and resilient in the long term. What practical boons does this method promise to developers?

Perks of Test Driven Development

As a seasoned company practicing TDD for projects in various fields – from fintech to healthcare – Ideamotive realizes numerous benefits it brings both to the development process and the finished product:

• Deep understanding of customer requirements. In case any detail or feature isn’t clear, it becomes evident early in the development cycle. So the crew of experts has a chance to eliminate obscurity before they are well into code-writing.
• Considerable code optimization. You write only the code that will be actually used in the product without wasting time (and time is money – remember?) for the conventional trial-and-error method.
• Promotion of modular design. Since each feature is dealt with piecemeal, TDD is a perfect fit for developing microservices solutions whose architecture relies on the unity of loosely-coupled components. 
• Huge test coverage. Writing tests for every feature spells embracing all functionalities of a software piece without the slightest possibility to overlook any. 
• Foolproof code maintenance. Separate codes and standalone interfaces prevent developers from getting confused among the loose ends of codes belonging to different elements. Besides, you can alter one feature without wreaking havoc on another.
• Easier debugging. No more wasting days trying to identify where the bug lives. Each small test will show its lurking-place within seconds. 

Moreover, there is no chance of copying errors into the new code piece since with every feature is always a brand new start.

• Longer shelf life. If a project is suspended for quite a time, it is often difficult to remember its details when you resume it a couple of months later. With the test suite at your disposal, you can proceed with or improve the product without the risk of ruining it after a long pause.
• Test code usability. When you write a test code, you write a sample of the programming code, in fact. Since the test code displays what the code does and how you should use the interface, you save a lot of time killing two birds with one stone – doing testing and code writing simultaneously.

One of the most valuable merits of test driven development is that it suits Agile practices to a tee.

How does TDD Dovetail into Agile Development?

Not long ago, the whole IT world employed the good old Waterfall methodology. It consists in moving sequentially from one meticulously planned stage of development to the next with a precise duration of phases and a rigid list of tasks to be fulfilled during each. It may seem to be a perfect way of creating software products until one observes the extreme volatility of the industry and customers’ preferences.

Very often, clients address full-stack developers having no clear-cut vision of the product they want to commission. Or they come up with the idea of new functionality when the project is well underway. Or, a new technology crops up (like, say, machine learning or artificial intelligence), and the customer wants to see it implemented in their app. But with Waterfall, changes of any scope can’t be implemented at later development stages. Agile methodology appeared as a reaction to the inadequacy of the old approaches in the conditions of the exceedingly dynamic IT environment. 

This disruptive methodology has flexibility as its major asset. In Agile, the development process handled by a cross-functional team embraces several iterations (sprints) where each one aims to deliver a fully functional product. Such an approach guarantees utmost flexibility, capability to onboard changes, and prompt reaction to customers’ feedback. 

In terms of Agile methodology, test driven development is a perfect fit since it is also susceptible to changes, permits returning to any feature even if the development team has passed on to another one, and allows to take into account the customer’s remarks and suggestions as to the feature roster or technologies utilized. Moreover, the project TDD crew is truly a cross-functional one, requiring robust communication and close cooperation between its development and QA subgroups. 

Despite the unquestionable advantages, test driven development should be approached with care.

TDD Pitfalls to Avoid

What are the bottlenecks developers may face while adopting the test driven development scheme?

• Writing too many tests in one go. It is next to impossible to maintain their quality and coherence when you create heaps of tests within a short time.
• Writing too large or too coarse-grained tests. The rule of thumb is to build small and wieldy tests that wouldn’t take forever to run.
• Writing too trivial tests. You shouldn’t omit assertions or any other details that would make your test a unique one. You also shouldn’t make tests that would address trivial code (like accessors).
• Neglecting to run tests frequently. The essence of the TDD approach is performing tests before each stage of code writing. If you don’t do that your endeavor is doomed to defeat.
• Divided preferences. The success of TDD can’t be complete if only some members of the team apply it. In such cases, the tasks performed by others will suffer from all the shortcomings architecture driven methods bring in their wake.
• Seemingly slow development. For novices in this methodology, it may appear that the development itself never starts since all they do is create and run tests. But, in fact, writing test codes is a part of actual code writing, so the whole process is proceeding faster than it may feel.
• Misinterpreting the TDD bug detection capacity. Being honed to identify bugs and inadequacies of code, tests can’t be total protection from them when careless developers introduce bugs themselves within the test code or during the implementation procedure.
• Taking into account code alterations. Whenever any changes are entered into the code, the tests should be modified accordingly to reflect the new conditions and requirements.

To successfully escape these pitfalls, developers should meticulously follow the prescribed in the test driven development procedure. 

Tackling TDD Hammer and Tongs

There is a universally recognized algorithm TDD teams must follow to get the expected result.

1. Write a Unit Test

Developers create a test that satisfies iff specifications related to some feature or unit of a software product. Such specifications can be obtained from use cases and user stories of the solution. That is, software engineers zoom in on requirements before writing the code. 

2. Run the Test

Strange as it may sound, the test must fail. Why? Because the program doesn’t have the feature it checks. If it fails, it is a telltale sign that you are moving the right way.

3. Write a Piece of Code the Test Would Validate

The quality of the code or its simplicity doesn’t matter (it will be polished at Stage 5 anyway). Its primary goal is to pass the test. Just remember not to add anything that doesn’t relate to the module or functionality you are building (and testing). 

4. Make Sure All Tests Pass

Now, all tests must confirm the code quality so as not to ruin the feature in question. If they don’t, move on to the next phase.

5. Refactor the Code

The code is modified until it passes tests. Such modification ensures code readability and maintainability. What are the possible modification steps?

• Transferring the code to the location that is most logical for it

• Re-organizing inheritance hierarchies

• Rendering names self-documenting

• Eliminating duplicate code

• Splitting methods into smaller units

6. Repeat the Cycle

The described sequence should be repeated for each feature and module until all of them are built and tested according to the TDD principles. 

When it comes to test driven development Python is the programming language that can be highly instrumental in such endeavors.

Test Driven Development: Python Use Rationalized

As a company whose specialists excel in building solutions in Python and ones that employ robust Python-powered frameworks (such as Django or Pytorch), we are sure that this high-level programming language is what the doctor ordered to be used in TDD projects. How come?

This language is not only a great tool for building software products of any scope via leveraging manageable and logical code for it. Its extensive library and easy-to-master data organization are also weighty arguments that make it suitable for data analysis tasks. 

Why do our experts believe that in test driven development Python is an optimal option? 

First of all, it is the coding routine in Python that developers follow. They start with reading into the code from the source file to see if there is any syntax error in it (which is a kind of testing before the development). If no inadequacies are spotted, the Python code is converted into byte code. Then, the byte code is conveyed to the Python Virtual Machine, which checks it for errors again. 

Second of all, it is the testing procedure and tools that ensure the foolproof creation of Python test cases that are subjected to automated testing. As a result, the debugging is easy and swift, providing high productivity and encouraging team collaboration. 

What are the frameworks for test driven development Python offers?

The Top 6 Python TDD Frameworks

As Python developers with dozens of delivered solutions under our belt, we recommend leveraging the following Python frameworks for test driven development. 

1. Robot

This open-source cross-platform automation testing framework is the most popular by all accounts since it can be employed for testing all kinds of apps powered by Windows, MacOs, and Linux. Although being a Python product, it can run .Net and Java as well, offering rich libraries and a voluminous toolset. The core of its testing process is keyword-driven, which allows for parallel testing of several features.

A tip from us: to install Robot, you should make use of Package Installer for Python (PiP). 

2. PyTest

This tool can be used for TDD of any kind, but it is specially honed for API and functional (database, UI, etc.) testing. By installing PiP, you can make use of the multiple plugins that go with PyTest and write test code of any complexity to be run in any subsets of tests.

3. Unittest

Being also called PyUnit, it is the earliest testing framework released by Python developers. It has been updated to Unittest2 version and streamlines test automation, making a special point of test collections, test independence, and setup code for tests. Moreover, in Unittest you can reuse test suits and test organization.

4. Nose2

Often referred to as a Unittest extension, this successor of Nose is used to perform unit and doc tests. Once you install a special plugin, you will be able to significantly streamline test and exception writing. Besides, it supports modules, classes, packages, and complex initializations to be defined once instead of being frequently repeated.

5. Testify

Designed as a replacement for Unittest and Nose, this framework sports more advanced features than those two. In addition to a large-size plugin roster and foolproof testing utilities, Testify offers automated unit, integration, and system kinds of tests as well as improvised test discovery.

6. DocTest

As a separate module of Python set, it is meant for regression and white-box unit testing via looking for interactive sessions to check their seamless functioning. To do it, DocTest utilizes native capabilities of Python (such as Python interactive shell, Python introspection, and docstrings).