Integration testing is the testing of multiple components in an application to ensure that they work as expected when integrated all together.
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Integration testing is performed after each component is separately tested (unit testing). After that, all the components are then unified into single applications and various actions are performed to check their execution as a whole application. The actions include,
Integration testing in python is often considered a relatively complicated type of testing as it requires more fixtures to be in place and needs to check all the components after every correction. It may also need to make changes in the database connection, a network socket, or a configuration file.
Projects made with python or any other programming language are not directly dependent on integration testing, Developers mostly rely on unit testing due to which developers and testers often do not build an advanced testing phase with the capability of finding issues during the integration. The discoveries of some major errors quite later in the development process created a demand for integration testing.
Following are some of the major features of integration testing:
Analysing or testing the working of integrated modules is obviously the first and primary purpose of integration testing. Integration testing ensures the connectivity between individual modules by examining the rendering values and logically implementing each of them.
Along with integration between different modules, Integration testing also ensures that the data is correctly accepted by a third-party API so that the response should be generated as per the requirement.
Before releasing the final build, it is very important to identify if there are any errors or red flags in the final build to prevent exception handling defects as much as possible. Integration testing can catch such errors if they were missed in the initial or developing stage before the release as they will be very expensive in terms of time and resources to fix them after the release.
These two testing approaches are often implemented together. Both types of testing are equally important and both of them must be implemented in your project. As the project code is developed, both unit and integration testing allow developers to identify any newly created errors in their code. Many of these errors are identified during unit testing but many are not discovered until components are integrated together, such errors are then discovered by integration testing.
Following are some basic differences between integration and unit testing:
Following are some challenges that are involved in Integration Test:
Integration testing involves testing two or more integrated systems in order to ensure that the system is working as expected after integration. In the case of a complex project, it can get very exhausting as not only do all the integration links need to be tested but a long series of tests considering all the different paths and permutations environment should be executed to ensure that the integrated system works properly.
Managing the Integration testing often gets complex because of dealing with external factors involved in it such as the databases, third-party tools, Platforms, different environments etc.
While integrating a new system with a legacy system, requires some significant changes and testing efforts in both new and old systems.
Integrating two different projects developed by a different group of developers is always a big challenge as it is very unpredictable to identify the impact of a system on the other system if any changes are done in any one of the systems.
The level of simplicity offered by python easily makes it one of the best programming languages for developing automated tests. A variety of automated testing frameworks are available for python that offers various tools for integrated testing to help the developers test their codes more efficiently.
Following are some of the most prominent automated testing frameworks for integrated testing of a python project:
Pytest is a simple testing framework for Python. It offers a very easy learning curve and is considered an ideal framework for unit and integration testing in python. Along with saving time with its headless parallel testing feature. Pytest also provides a cleaner and shorter way of writing tests in Python. Integration testing with Pytest also outputs a human-friendly result that traces the test steps and also identifies the errors in the code.
The support for command-line execution of test suites is also a favoured feature by python developers as it makes the test execution as simple as running the pytest command from the test folder terminal.
It also allows invoking Pytest with a simple file name like this:
Selenium is one of the most-used automation testing frameworks for python. It has very active community support and offers various other programming language support as well. It also accepts cloud grid capability for orchestrating test cases in parallel. Selenium also offers an array of dedicated selectors that let developers interact with the UI as a user.
Nose2 is another testing framework that is closely related to Pytest in terms of functionality. Similar to Pytest, it can be used as a test runner for test cases written in some other frameworks like Selenium or unittest. Nose2 supports Integration testing as well as unit testing allowing testers to test the UI of the project as well as check the code functions of each component.
Robot is a keyword-driven, open-source Python testing framework for integration testing. While other frameworks require writing code for test cases, Robot allows writing cases in simple and plain English. It makes automation testing as easy as possible and an ideal option for developers who are getting started with testing by writing more human-friendly test cases.
In this article, we have discussed integration testing in python. It is a crucial phase of testing that helps developers in detecting and remove any bugs after integrating all the modules into one whole program. We covered some of the prominent python integration testing frameworks. While some testing frameworks are primarily for integration testing, some offers support for multiple testing options including unit testing.
Also Read: Guide on How Xperti Helps You Find Python Jobs in the U.S.
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