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Top Python Testing Frameworks and Libraries

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Python is one of the most popular programming languages, with applications across various platforms, domains, industries, and use cases. From web development, data analysis, and visualization to machine learning, Artificial Intelligence as scrapping and automation, Python can be used for developing, designing, and deploying various innovative projects.

However, in any project’s SDLC, there is one more stage that is very crucial to ensure an app’s success, and that is testing. While testing should be implemented from the development stage in a project, you should also re-test the entire app before deployment. Luckily, Python provides a rich repository of testing tools, frameworks, and libraries to ensure your Python code is optimized, free from any possible vulnerabilities, and follows coding best practices.

How to select the right Python Testing Framework?

Still, trying to figure out how to select the best Python testing tool for your project? You can hire dedicated developers from a professional Python development company who can guide you with the right Python testing tool selection. Apart from that, here is a quick Python testing library selection checklist for you –

  1. Check if it supports the type of testing you need to conduct
  2. Check the learning curve and documentation availability
  3. Check how extensible and scalable it is
  4. Check for its reviews, installation details, and other specs

Top Python Testing Frameworks and Libraries to Use in 2023

Let’s look at some of the best Python testing frameworks, tools, and libraries that every Python developer should have a basic understanding of and experience using. Make sure tohire Python developers with expertise in Python testing tools like –

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1.   Robot Testing Framework

Ask any developer about their Python testing framework choice; at least 1 in 5 developers would say they use the Robots framework. It is a popular open-source Python testing framework that supports acceptance testing and acceptance test-driven development. Nokia engineers created it as a framework for testing their network solutions. It utilizes a keyword testing approach for creating test cases that are easy to read and understand.

Types of Supported Python Testing

  • Acceptance Testing
  •  Acceptance Test-Driven Development

Robot Testing Framework Pros

  • Easy to read and write Syntax
  • Built-in Libraries for different types of tests
  • Supports higher level of abstraction
  • Supports data-driven testing

Robot Testing Framework Cons

  • Steeper learning curve
  • Not suitable for small projects
  • Initial setup is complicated and time-consuming
  • Limited community support

2.   PyTest Testing Framework

PyTest is another open-source Python testing framework that every Python developer knows about. It simplifies writing test cases and focuses on testing databases, API, user interfaces, and more. PyTest is compatible with Python frameworks like Django, Flask, and others. It has dedicated features that help with Python GUI automation, such as – Hooks, Fixtures, and Makers.

Types of Supported Python Testing

  • Unit Testing
  • Functional Testing
  • Integration Testing
  • Test-Driven Development
  • General-Purpose Testing

PyTest Testing Framework Pros

  • Easy Learning Curve
  • Extensive Plugin Supports
  • Support for Parametrized Testing
  • Detailed Reporting and Logging
  • Rich Test Discovery
  • Highly Secure Architecture

PyTest Testing Framework Cons

  • Dependency on Additional Plugins
  • Difficult to integrate with other tools
  • Slower execution than other testing tools

3.   DocTest Testing Framework

DocTest is included in the standard Python library, which makes it easier to configure and set up test cases based on the output of the default Python interpreter shell. You can write test cases in embedded functions, docstrings, modules, and classes. The test cases can be used for documentation as well as executable code. This makes the documentation process easier and more efficient.

Types of Supported Python Testing

  • Unit Testing
  • Documentation Validation
  • Integration Testing
  • Acceptance Testing

DocTest Framework Pros

  • Easy to start and no installation required
  • Extensive code documentation
  • Easy Learning Curve
  • No further dependencies

DocTest Framework Cons

  • Static and hence can’t be parametrized
  • Not able to use functions of Test Fixtures, Test Runner, and Test Discovery
  • Requires using directives for controlling DocTest behavior

4.   Testify Testing Framework

Testify is another popular Python testing framework mainly used for automation testing. It offers an easy-to-use and expressive testing environment with a list of useful features for writing and executing tests, making it ideal for unit testing, integration testing, and functional testing scenarios.

Types of Supported Python Testing

  • Unit Testing
  • Functional Testing
  • Regression Testing
  • Integration Testing
  • Test-Driven Development
  • Continuous Integration Testing

Testify Framework Pros

  • Easy Learning Curve
  • Integrated Test Runner
  • Test Fixtures
  • Highly Extensible

Testify Framework Cons

  • Smaller community
  • Lesser built-in features
  • High Learning Curve for Advanced Features
  • Hard Set Conventions

5.   Nose 2 Testing Framework

Nose 2 is the successor to the popular Python testing framework – Nose. You can think of Nose 2 as a boosted PyUnitest alternative since it supports various plugins. It is ideal for developers familiar with Python standard library and unit testing and prefers it over other Python automation frameworks.

Types of Supported Python Testing

  • Unit Tasting
  • Functional Testing
  • Integration Testing
  • Coverage Reporting
  • Test Driven Development
  • General-Purpose Testing

Nose 2 Framework Pros

  • Easy Setup
  • Extensive Plugins
  • Test Discovery Support
  • Test Fixture Support
  • Parallel Testing Support

Nose 2 Framework Cons

  • Slower test execution
  • Less Popular
  • Lack of Support and Documentation

6.   Behave Testing Framework

Behave is one of the most preferred Python testing frameworks for behavior-driven development. It is similar to the Cucumber framework if you have had a chance to use it. The scripts are written in a simple language and then attached to the code at the execution stage. You can use the once-defined steps for other case scenarios as well.

Types of Supported Python Testing

  • Acceptance Testing
  • Functional Testing
  • System Testing
  • Integration Testing

Behave Framework Pros

  • Follows BDD – Behavioural Driven Development Approach
  • Easy to read and understand code
  • Proper test coverage with reporting
  • Modular and reusable step definitions

Behave Framework Cons

  • Steep Learning Curve for Non-Technical Members
  • Major Performance Bottlenecks
  • Overheads while setting up tests
  • Complex Maintenance of Step Definitions

7.   TestProject Testing Framework

TestProject is yet another efficient Python testing library that provides both local and cloud HTML Reports and the ability to set up automation tests. It supports other important Python testing frameworks like Unittest and PyTest and all their dependencies from a single executable agent file.

Types of Supported Python Testing

  • Functional Testing
  • Regression Testing
  • End-to-End Testing
  • Performance Testing
  • Cross-Browser Testing
  • Mobile Testing
  • API Testing

TestProject Framework Pros

  • Access to execution history through RESTful API
  • Single SDK for Android, web, iOS, and general testing
  • Extensive Community Support
  • Test Reporting Support
  • Proper Documentation

TestProject Framework Cons

  • No support for parallel testing
  • Restrictions on the team collaboration tools
  • Steeper Learning Curve
  • Limited Programming Language Support
  • High Platform Dependency
  • Tool Maturity

Final Words

These were the top Python frameworks and libraries that you could use for conducting different kinds of testing on your Python code and ensuring it is fully optimized for your project with lesser chances of running into bugs, crashes, and other complications. Make sure to hire dedicated developers who have proficiency in Python testing frameworks to make sure your project is as secure as possible.

Author Bio

Ronak Patel is a CEO and Founder of Aglowid IT Solutions, an ever-emerging Top Web and Mobile Development company with a motto of turning clients into successful businesses. He believes that Client’s success is company’s success and so that he always makes sure that Aglowid helps their client’s business to reach to its true potential with the help of his best team with the standard development process he set up for the company.

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