There are several popular Python automation testing tools that you can use for various testing purposes.

Here are some of the widely used ones:

1. Selenium: Selenium is a versatile and widely adopted framework for automating web browsers. It supports multiple programming languages, including Python, and provides a rich set of features for browser automation, testing, and web scraping.

2. Pytest: Pytest is a powerful testing framework that makes it easy to write and execute tests in Python. It offers concise and expressive syntax, powerful assertion features, test discovery, test parallelization, fixtures for test setup/teardown, and integration with other testing tools.

3. unittest: The unittest module is Python’s built-in testing framework, inspired by JUnit. It provides a set of classes and methods for organizing and running test cases. Unittest is feature-rich, supports test discovery, and allows you to create test suites, fixtures, and custom test runners.

4. Robot Framework: Robot Framework is a generic open-source automation framework that uses a tabular, keyword-driven syntax. It supports various test libraries and tools and offers easy-to-read test cases. Robot Framework has excellent support for both acceptance testing and acceptance test-driven development (ATDD).

5. Behave: Behave is a behavior-driven development (BDD) framework for Python that uses the Gherkin language for defining test scenarios. It allows you to write tests in a human-readable format and encourages collaboration between stakeholders. Behave integrates well with Selenium for web testing.

6. Cucumber: Cucumber is a popular BDD tool that supports multiple programming languages, including Python. With Cucumber, you can write test scenarios in a plain-text format using Gherkin syntax. It promotes collaboration and clarity between stakeholders and developers.

7. PyUnitReport: PyUnitReport is a Python library that generates HTML test reports from unittest or pytest test results. It provides detailed test reports with summaries, captured logs, screenshots, and other useful information.

8. Mock: The mock library allows you to create mock objects and specify their behaviors during testing. It is useful for isolating dependencies, simulating external services, and controlling the behavior of certain components in your tests.

These are just a few examples of Python automation testing tools. Depending on your specific requirements and the nature of your project, you can choose the tool that best fits your needs.