Robot Framework's architecture is designed for extensibility and flexibility. Here's a high-level overview:
Test Data: This is where you define your test cases, keywords, and other test-related information. It's typically written in plain text files using a tabular format, but other formats like HTML, TSV, reStructuredText, and JSON are also supported. The test data is the input to the Robot Framework engine.
Robot Framework Engine: This is the core of Robot Framework. It's responsible for parsing the test data, executing the tests, and generating reports. The engine doesn't actually perform the actions in your tests (like clicking buttons or making API calls); it delegates that to libraries.
Libraries: Libraries are collections of keywords that provide the actual functionality for your tests. They are the "action" part of your tests. There are two main types:
BuiltIn, Collections, OperatingSystem, String)SeleniumLibrary: For web UI testing.RequestsLibrary: For API testing.DatabaseLibrary: For database testing.Resource Files: Resource files are like mini-libraries. They contain reusable variables, keywords, and settings that can be imported into your test suites. This helps you organize your test data and avoid duplication.
Listeners: Listeners are components that can be used to monitor and interact with the test execution process. They can be used for logging, reporting, or integrating with other tools. They are essentially callbacks that are triggered at various points during the test run.
Runners: Robot Framework can be executed in several ways. The most common is using the robot command-line tool. RIDE (Robot Integrated Development Environment) provides a graphical interface for running tests. You can also embed the Robot Framework engine within your Python code to execute tests programmatically.
Reports and Logs: After the test execution is complete, Robot Framework generates HTML reports and logs. These provide detailed information about the test results, including which tests passed or failed, the steps that were executed, and any errors that occurred.
Workflow:
Key Architectural Principles: