In today’s fast-paced world of application development organizations need to deliver high-quality applications in less time. To achieve high quality and seamless functionality developers put the application through various testing phases, before releasing them to end users, which takes a lot of time. But, for the application to reach the market early, the testing cycles need to be shortened, and therefore it becomes necessary for developers to adopt automation testing.
Automation testing helps to shorten the testing cycle by reducing overall regression time and delivering quality applications faster to the market. Automation testing is a testing process that utilizes automated testing tools, frameworks, and scripts for testing the application. In this testing technique, developers create automated reusable test scripts using various programming languages to test the application functionality, and Python is one of them.
Python is one of the most widely used programming languages among developers and testers worldwide. As compared to other programming languages Python is easy to learn, and use. It includes all the tools and modules needed to facilitate automated testing. Its user-friendly nature makes it a preferred language among developers to write test cases in Python.
The increasing usage and growing popularity have led to a high demand for advanced Python-based test automation frameworks in the field of application development. These frameworks enable developers to identify and address defects more effectively, resulting in higher application quality.
In this article, we will discuss the top Python testing frameworks that are most appropriate for quick and comprehensive automation of test cases written in Python.
What is a Python testing framework?
A framework is a set of instructions or standards used for developing and designing test cases. Python testing framework is a dynamic framework with a set of tools, and libraries designed to easily write, execute, and manage tests for Python code. It is well known for its simplicity in web development and test automation.
There are several frameworks and libraries in Python like selenium python. It supports automated testing by providing developers with a structured environment to create automated tests and verify the functionality and correctness of their applications.
Advantages of using Python testing frameworks
Python is becoming more popular and so are the testing frameworks built on Python. Python testing frameworks offer various features, including assertion libraries, test discovery mechanisms, fixtures to set up test environments, and reporting functionalities for ensuring the quality, reliability, functionality, and performance of Python-based applications.
It is done by automating the testing process; enabling developers to prevent bugs early in the development cycle and enhance overall code quality. Besides, they also enable teams to facilitate the creation of repeatable and maintainable test suites.
Some of the other advantages of using Python testing frameworks are.
- Enables easy debugging.
- Provide extensive library support.
- Quicker feedback.
- High productivity, saving a lot of time
- Team collaboration.
- Reduce cost.
- Allows performing multiple tests.
- Provide better insights.
Why use the Python testing framework?
Choosing the right Python testing framework has a significant impact on the quality and success of the application because these frameworks lay the foundation for a reliable, flawless, and enduring application. These frameworks provide a set of tools to streamline the testing process, allowing to automate tests, and ensuring Python code functions correctly across various scenarios.
Here are some of the reasons for choosing the Python testing framework
To enhance code quality
Python testing frameworks allow developers to refine and enhance the code by verifying that the code functions correctly and meets the specified requirements. This precision and attention to detail lead to a refined, polished final application.
To automate the testing process
Python testing frameworks allow to automate the test execution process, making it easier and faster to run tests and identify issues in the code base. It guarantees that the application functions correctly and meets defined standards.
To detect bugs early
By writing tests before or alongside code implementation, developers can catch bugs and prevent issues early in the development cycle, reducing the overall cost and effort of fixing them later and enhancing code quality.
To facilitate regression testing
Python testing frameworks enable regression testing, where previously working features are tested again after changes or updates are made to ensure that no new bugs have been introduced, and previously tested features are working properly.
Best Python testing frameworks for 2024
Below we will provide a list of Python testing frameworks. We will go through the details of each framework and understand its benefits and limitations so that it becomes easier to decide when to use which of them.
Behave framework
Behave is an open-source, and one of the most widely used Python testing frameworks used for behavior-driven development (BDD). Anyone with basic knowledge of Python can use Behave because it allows writing all test scripts in a simple human-readable language and then attached to the code during execution. This makes it easier for technical and non-technical team members to understand the testing process.
Behave, allows developers to efficiently automate testing and ensure that their Python applications meet the desired behavioral requirements. Additionally, it’s a valuable tool for enhancing the quality and reliability of applications.
Benefits of Behave
- Provide building blocks for executing a large variety of test cases.
- Facilitates effective coordination among development teams, testers, and developers to work on diverse modules with similar features.
- Offers various customization options, to make it adaptable to various testing needs.
- Allows developers to create robust and error-free Python applications, thus streamlining the testing process.
- Encourages writing tests in simple language that is easily readable and understandable to humans.
Limitations of Behave
- Sometimes it can be slower to write tests compared to other frameworks.
- Developers need to have a good understanding of Gherkin syntax.
- Works well only for black-box testing.
- Not ideal for a unit or integration testing.
Lettuce framework
Lettuce is an effective Python testing framework that facilitates automating behavior-driven development. It enables developers to write more than one scenario of an application and describes its characteristics in plain English sentences. Its functioning is based on Ruby’s Cucumber and Python.
Benefits of Lettuce
- Allows writing high-level tests in a human-readable format using plain English.
- Provide support for integration with various testing tools.
Limitations of Lettuce
- Requires setup overhead compared to built-in Python frameworks.
- Requires a high system of communication between QAs, developers, and stakeholders to be able to be functional as a Python testing framework.
- Due to its natural language processing, it can be slower at times.
Robot Framework
It is one of the most popular and open-source Python automation testing frameworks. It is entirely well suited for acceptance testing, test-driven development, and robotic process automation. Robot framework uses Keyword style to write test cases. Because of its simplicity and flexibility, it is popular among testers and developers.
While it is developed with Python, it can be extensible with other languages, like it is capable of running Java and .Net. Provide compatibility with Windows, Mac OS, and Linux to perform cross-platform automation testing for desktop applications, mobile applications, web applications, etc.
It uses tabular data syntax for test case definition, keyword-driven testing to make tests highly readable, extensive libraries and toolsets that can be individually used in different projects, and parallel testing. All these strong features make Robot popular among testers and developers.
Benefits of Robot Framework
- It uses a keyword-driven approach, making automation easier by allowing testers to create easy-to-read and easy-to-maintain test cases
- Supports major operating systems like macOS, Windows, and Linux, and different application types such as web and mobile apps.
- It is highly extensible and easy to integrate with third-party tools because of its rich ecosystem and various APIs.
- Active user community support.
Limitations of Robot Framework
- Requires a longer learning curve for beginners of its specific syntax and keywords.
- There is no inbuilt parallel testing support, and can only be achieved with Selenium Grid.
- Report customization is difficult.
Pytest Framework
Pytest is another widely used open-source Python testing framework that supports unit, functional, and API testing.
It is most liked among developers because of its ease of use and flexibility, enabling developers to simplify the test creation and execution process by writing efficient, maintainable, and readable test cases.
Benefits of Pytest
- Provides a compact and simple test suite.
- Provide powerful assertion introspection and modular fixtures, to streamline test setup and teardown.
- Offers highly extensible rich plug-ins and different fixtures.
- Allows running tests in parallel.
- Active large community support.
- Covers all testing parameter combinations without rewriting test cases.
- Limitations of Pytest.
- Pytest is only compatible with Python, which means test cases written in this framework, cannot be used with other testing frameworks.
TestProject Framework
TestProject is an open-source Python automation framework that simplifies automation testing and offers support for both hybrid cloud and completely offline modes. It is built upon the foundation of Selenium and Appium and supports Pytest and Unittest frameworks.
It is cross-platform compatible which simplifies the process of handling and setting up drivers for various platforms and browsers required to conduct testing for Web, Android, and iOS applications. TestProject is packed with all necessary dependencies into a single executable agent file; installing it will provide developers the ability to access all browsers and devices on their computers. This enables immediate test recording, creation, and execution.
Benefits of TestProject
- Provide flexibility in reporting options by offering cloud-based and local HTML/PDF format automated reports.
- Always get updated with the latest Selenium and Appium driver versions.
- Provides a single SDK to conduct Android, iOS, web, and general testing.
- Cross-platform compatible and easy to set up.
Limitations of TestProject
- Compared to other more complex test automation frameworks, it lacks advanced customization options.
- Does not support parallel testing, hence only one test can be run at a time.
PyUnit Framework
PyUnit, also known as Unittest, is a Python standard library that provides a solid foundation for writing and running test cases in Python. It is a JUnit-inspired unit testing framework that comes with a built-in Python package for Python developers.
Benefits of PyUnit
- Since PyUnit is part of the standard Python library, it doesn’t require the installation of additional modules.
- It provides simple and quick test case execution, has fewer bugs, and is easy to modify.
- Helps detect bugs early in the development cycle, and write better programs
- Provide compatibility with other Python testing frameworks.
- Quick test reports generation.
Limitations of PyUnit
- Limited assertions.
- Minimal built-in test generation.
- No parallel testing support.
- Difficult to learn.
- Limited non-Python support.
- Restricted CI integration.
- Requires boilerplate code.
Doctest
Doctest is a module included in the standard library of Python. It is used for white-box unit testing, making it easy to generate tests based on the output of the standard Python interpreter shell.
One limitation of this framework is that it is not suitable for complex test scenarios.
Testify
The testing framework Unittest served as an inspiration for Testify, a well-known Python testing framework that is designed to be used for integration and system testing. It is simple and easy to use and offers extensive plugins for additional functionality for testing Python code.
One limitation of this framework is that it has limited documentation and community support.
Utilize LambdaTest to run Python automated test script
Test automation plays an essential role in the application testing process. It uses automated scripts and tools to execute test cases, allowing developers to save time and reduce errors in the testing process, ensuring application reliability, preventing bugs, and enhancing overall code quality.
There are various scripting languages available to facilitate automated test script creation; each scripting language provides a unique set of features, capabilities, and ways of writing test scripts. Python is one of the versatile and powerful languages that come with various tools and frameworks to support automated testing of applications.
However to fully utilize the real power of Python, and its various frameworks it is better to utilize it with an automation testing platform like LambdaTest because this platform provides integration with all the Python testing frameworks to facilitate easy test automation using Python.
LambdaTest is an AI-powered test orchestration and execution platform that allows running manual and automated tests at scale. Using the LambdaTest platform developers can also perform both real-time and automation testing of native, hybrid, web, and mobile applications on both iOS and Android platforms by getting access to the real device cloud. This capability allows validating applications with real-world user experiences across various devices, screen sizes, and operating systems.
Other than Python, LambdaTest provides support for other widely used scripting languages like Java, JavaScript, PHP, Ruby, or C#, so that developers can write test scripts in any of the languages they are most comfortable with. It also offers in-built debugging and reporting capabilities to log failure, performance metrics, and user experience insights for a comprehensive view of application behavior to enhance application performance.
Conclusion
In conclusion, it can be said that to address the evolving needs of modern application development, advanced Python testing frameworks offer features that help to enhance application quality, efficiency, scalability, and collaboration. Above we have discussed the best Python testing frameworks with their benefits and limitations. Choosing the right Python testing framework depends on the test requirement.