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  1. Stackups
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  3. Testing Frameworks
  4. Testing Frameworks
  5. TestComplete vs pytest

TestComplete vs pytest

OverviewComparisonAlternatives

Overview

TestComplete
TestComplete
Stacks39
Followers60
Votes0
pytest
pytest
Stacks4.0K
Followers306
Votes0
GitHub Stars13.2K
Forks2.9K

TestComplete vs pytest: What are the differences?

Introduction

TestComplete and pytest are both popular tools used for software testing, but they have some key differences that set them apart. In this article, we will explore these differences in detail.

  1. Automation Testing Framework: TestComplete is a comprehensive commercial testing tool that provides a wide range of testing capabilities, including record and playback, script-based testing, and data-driven testing. On the other hand, pytest is an open-source testing framework for Python that focuses on simplicity and scalability. It allows test cases to be written as regular functions and provides powerful features for test discovery and test execution.

  2. Test Configuration and Execution: TestComplete allows tests to be configured and executed through its own integrated IDE. It provides a graphical user interface to create and manage test projects, test items, and test cases. pytest, on the other hand, can be executed directly from the command line. Test cases are written as plain Python functions and can be organized using standard Python packages and modules.

  3. Test Development Approach: TestComplete follows a keyword-driven testing approach, where test scripts are created by assembling reusable keywords. These keywords represent actions, objects, and verification points in the application under test. pytest, on the other hand, follows a more traditional test-driven development (TDD) approach, where test cases are written as separate functions and can take advantage of Python's rich set of libraries and assertions.

  4. Test Reporting and Integration: TestComplete provides built-in reporting capabilities that enable detailed test reports to be generated automatically. It also offers integration with popular issue tracking systems and test management tools. pytest, on the other hand, offers flexible reporting options through plugins. Test results can be displayed in various formats, and pytest integrates well with continuous integration (CI) systems like Jenkins and Travis CI.

  5. Test Parameterization: TestComplete allows test parameters to be defined and managed within the tool itself. These parameters can be used to drive test data and test configurations. pytest, on the other hand, provides a powerful parameterization feature that allows test cases to be executed with different sets of input values. Test cases can be parameterized using decorators or by defining fixtures that provide test data and resources.

  6. Community and Support: TestComplete is a commercial tool developed and supported by SmartBear Software. It provides comprehensive documentation, tutorials, and technical support. pytest, on the other hand, is an open-source project with a large and active community. It has extensive online resources, including documentation, user forums, and plugins developed by the community.

In Summary, TestComplete is a commercial automation testing tool with a keyword-driven approach, while pytest is an open-source testing framework for Python with a focus on simplicity and scalability. TestComplete provides an integrated IDE and comprehensive features for test management and execution, while pytest offers a flexible and powerful test development approach using plain Python functions. Both tools have different reporting options and support different parameterization techniques.

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Detailed Comparison

TestComplete
TestComplete
pytest
pytest

It is an automated UI testing tool that makes it fast and easy to create, maintain, and execute functional tests across desktop, web, and mobile applications. With TestComplete, you can increase test coverage and ensure you ship high-quality, battle-tested software

A framework makes it easy to write small tests, yet scales to support complex functional testing for applications and libraries. It is a mature full-featured Python testing tool.

Building Automated UI Tests; Object Recognition Engine now with Artificial Intelligence; HTML5 Test Automation; Data-Driven Testing; Automated Test Reporting & Analysis
Auto-discovery; Modular fixtures
Statistics
GitHub Stars
-
GitHub Stars
13.2K
GitHub Forks
-
GitHub Forks
2.9K
Stacks
39
Stacks
4.0K
Followers
60
Followers
306
Votes
0
Votes
0
Integrations
Jenkins
Jenkins
Git
Git
Visual Studio
Visual Studio
Jira
Jira
Bugzilla
Bugzilla
PyCharm
PyCharm

What are some alternatives to TestComplete, pytest?

BrowserStack

BrowserStack

BrowserStack is the leading test platform built for developers & QAs to expand test coverage, scale & optimize testing with cross-browser, real device cloud, accessibility, visual testing, test management, and test observability.

Selenium

Selenium

Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that. Boring web-based administration tasks can (and should!) also be automated as well.

Sauce Labs

Sauce Labs

Cloud-based automated testing platform enables developers and QEs to perform functional, JavaScript unit, and manual tests with Selenium or Appium on web and mobile apps. Videos and screenshots for easy debugging. Secure and CI-ready.

LambdaTest

LambdaTest

LambdaTest platform provides secure, scalable and insightful test orchestration for website, and mobile app testing. Customers at different points in their DevOps lifecycle can leverage Automation and/or Manual testing on LambdaTest.

Karma

Karma

Karma is not a testing framework, nor an assertion library. Karma just launches a HTTP server, and generates the test runner HTML file you probably already know from your favourite testing framework. So for testing purposes you can use pretty much anything you like.

Robot Framework

Robot Framework

It is a generic test automation framework for acceptance testing and acceptance test-driven development. It has easy-to-use tabular test data syntax and it utilizes the keyword-driven testing approach. Its testing capabilities can be extended by test libraries implemented either with Python or Java, and users can create new higher-level keywords from existing ones using the same syntax that is used for creating test cases.

Karate DSL

Karate DSL

Combines API test-automation, mocks and performance-testing into a single, unified framework. The BDD syntax popularized by Cucumber is language-neutral, and easy for even non-programmers. Besides powerful JSON & XML assertions, you can run tests in parallel for speed - which is critical for HTTP API testing.

Playwright

Playwright

It is a Node library to automate the Chromium, WebKit and Firefox browsers with a single API. It enables cross-browser web automation that is ever-green, capable, reliable and fast.

Rainforest QA

Rainforest QA

Rainforest gives you the reliability of a QA team and the speed of automation, without the hassle of managing a team or the pain of writing automated tests.

WebdriverIO

WebdriverIO

WebdriverIO lets you control a browser or a mobile application with just a few lines of code. Your test code will look simple, concise and easy to read.

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