Automation Framework: Top Python Frameworks for Automation Testing Explained
Python is considered to be one of the most popular programming languages globally. It is a user-friendly language. It is relatively easy to write test cases in python. For this purpose, there is a huge demand for easy-to-use and effective python testing frameworks. These testing frameworks provide a reliable and productive platform for carrying out python related works rewardingly.
In this article, you will get to know some of the best python frameworks for automation testing.
What is a Python testing framework?
It is a dynamic framework based on Python. It is known for its effective use in both test automation and web development activities. Eventually, these transitions also lead to the need for testing tools. There are several libraries and frameworks in python that support automated testing.
The following are the top python frameworks for automation testing:
1. Robot: This framework is well-suited for acceptance testing. It is capable of running on both Jython (Java-based) and IronPython (.net-based). The framework is compatible with Linux, macOS and Windows. It is based on keyword-driven testing and helps testers easily create readable test cases by making the automation process simpler. The test data syntax can be easily used. It also has an easy-to-understand report data.
2. Behave: This framework supports Behavior-Driven Development (BDD). A simple language is used to write all the test cases and then the code is attached during execution. The code behavior is ascertained by pertinent specifications. The steps that are defined once can be reused by other use case scenarios. A semi-formal language is used to define the system behavior and the use of a domain vocabulary is involved to ensure constant behavior in the organization.
3. PyTest: It is one of the most popular python testing frameworks. It is an open-source framework that supports API tests, functional testing and unit testing. It provides a simple and compact test suite. It comes with many plugins and is highly extensible. If possible, the team can add the PyTest HTML plugin to the project, so that HTML reports can be printed with a single command-line option. All parameter combinations are covered without the need to rewrite test cases.
4. PyUnit (Unittest): This framework comes with a python package by default. Additional modules need not be installed as it is a significant part of the standard python library. It provides clean, simple and quick test execution. The test reports can be generated quickly, which includes Unittest SML and XML reports. File path can be used to specify the test module. If the test files are stored as packages and modules, then the tests can be quickly and easily detected by Unittest.
5. Lettuce: This framework facilitates Behavior Driven Development (BDD) testing. The functionality of Lettuce is based on Python and Cucumber. It is easier to accomplish the basic tasks of a BDD structure. More than one scenario can be programmed by developers and the characteristics can be described in a natural, simple language. There is proper coordination between QA and development teams as the specifications are defined in a similar format. Behavior-driven test cases can be easily run using this framework.
6. Testify: This framework is used for system and integration testing. Nose and Unitttest frameworks can be easily replaced by Testify. It has a lucid, simple syntax and can be easily understood. Extensive plugins are offered for additional functionality. It provides class-level setup and TearDown fixture methods and enhanced test discovery that can be executed once for the whole set of test methods.
Conclusion:
If you are looking forward to implementing python testing for your specific project, then do get connected with a premium test automation services company that will provide you with comprehensive testing solutions that can justify your project specific requirements.
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