Home Guide Top 3 Python Testing Frameworks

Top 3 Python Testing Frameworks

By Shreya Bose, Technical Content Writer at BrowserStack -

As per TechRepublic, Python is one of the most used programming languages in the world. Thus, effective, easy-to-use Python testing frameworks are in high demand. This article lists three frameworks that are most suitable for quick and comprehensive automation of test cases written in Python. Let’s begin.

#1 Behave

Behave is one of the most widely used Python test frameworks, known for being especially useful when it comes to behavior-driven development (BDD). BDD is a recent innovation in Agile software development methodology which strives for constant and close collaboration among developers, business participants, and quality analysts. Behave facilitates this with no complications.

This framework is quite similar to Cucumber and SpecFlow. All test scripts are written in a simple, easily understandable language and then attached to the code during execution. Code behavior is determined by relevant specs. Behave allows once-defined steps to be reused by other use case scenarios.

Prerequisites

Behave can be used by anyone who possessed basic knowledge of Python. Before installing Behave, do the following:

  • Install any version of Python over 2.7.14
  • Install a Python package manager or pip
  • Install Pycharm or a similar IDE.

Pros

  • In Behave, system behavior is defined by semi-formal language and involves the use of a domain vocabulary that ensures behavior remains constant in the organization.
  • Facilitates effective coordination of development teams work on diverse modules with some similar features.
  • There are building blocks available for the execution of a large variety of test cases.
  • Behave contains better product specs since thinking and reasoning are featured in details.
  • All specs are in a similar format, offering managers better clarity on the output of developers and QAs.

Cons

  • Works optimally only for black box testing.
  • Not the best fit for unit or integration testing, as the verbosity inherent in these tests, can lead to complications in test scenarios.

BrowserStack provides integration with Behave to facilitate simpler test automation using Python & Selenium. To know more, view the documentation for running Selenium tests using Behave with Browserstack.

#2 Lettuce

Lettuce is also extremely effective when it comes to automating behavior-driven test structures. Its functioning is based on Cucumber and Python. Primarily, Lettuce is good for making the common tasks of a BDD structure easier to accomplish.

Prerequisites

Before installing Lettuce, do the following:

  • Install Python 2.7.14 or above
  • Install Pycharm or an equally capable IDE
  • Install the Python package manager

Pros

  • Enables developers to program more than one scenario and describe its characteristics in a simple, natural language
  • Enables, much like Behave, productive coordination due to specs being defined in a similar format
  • Is especially handy when it comes to running behavior-driven test cases

Cons

  • Lettuce requires a highly refined system of communication between QAs, developers, and stakeholders in order to be truly functional as a Python testing framework. There is no room for ambiguity here.

As is the case with Behave, BrowserStack provides integration with Lettuce to facilitate simpler test automation using Python. View the relevant documentation here to learn more about automated testing with Lettuce and Python.

#3 Robot Framework

This framework is largely suitable for acceptance testing. While it has been developed with Python, it is also capable of running on IronPython (.net based) as well as Jython (Java-based). The Robot Framework is compatible with Windows, MacOS or Linux.

Prerequisites

Before installing Robot Framework, do the following:

  • Install Python 2.7.14 or above
  • Install the Python package manager (pip)
  • Download a development framework such as the Pycharm Community Edition

Pros

  • Makes automation simpler by helping testers easily create readable test cases
  • Enables easy usage of test data syntax
  • Is equipped with a vast ecosystem that consists of generic tools and test libraries, each of which can be individually used in separate projects
  • Thanks to its many APIs, it is highly-extensible
  • Helps users run parallel tests via a Selenium grid. Note that this feature is not built-in.

Cons

  • While it is largely convenient to use, some complications may arise when creating customized HTML reports. However, it does allow for the presentation of xUnit formatted short reports
  • Involves some inadequacies in case of parallel testing

Choosing the right Python testing framework undoubtedly takes a bit of research and judgment. Attention must be paid to script quality, simplicity of test case definition and techniques used to run modules. The frameworks described above rank highly on these factors, and are widely used by developers because of their many advantages. Nonetheless, it is advisable to try testing on each framework, and gauge results for oneself so that the automation testing process is not hindered in any way.

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