How do you optimize keyword performance and reduce execution time?

2 Create reusable and maintainable keywords

Another way to optimize your keywords is to create reusable and maintainable keywords that can be used across different test cases and suites. Reusable keywords are keywords that perform common or generic tasks, such as logging in, filling a form, or clicking a button. Maintainable keywords are keywords that are easy to read, understand, and modify, and that follow consistent naming and formatting conventions. By creating reusable and maintainable keywords, you can reduce code duplication, improve readability, and simplify maintenance.

3 Use variables and arguments wisely

Variables and arguments are essential for making your keywords dynamic and flexible, but they can also affect your keyword performance and execution time. Since variables and arguments are evaluated at runtime, they can introduce overhead and complexity. To optimize your keywords, you should use variables and arguments wisely. This includes using scalar variables for single values, list variables for collections, and dictionary variables for mappings; global variables for constants, suite variables for suite-level settings, test variables for test-level data, and local variables for keyword-level scopes; default values for arguments when possible; and the Set Variable If keyword to assign conditional values to variables instead of using the Evaluate keyword to execute Python expressions.

4 Run keywords in parallel

Running keywords in parallel can drastically reduce your execution time, especially if you have many independent or concurrent keywords. Robot Framework supports parallel execution with the Pabot library, a wrapper for the Robot Framework command line interface. Pabot enables you to run multiple test suites or test cases in parallel and also offers additional features like distributing the test load among different processes or machines, merging output and report files, sharing variables and resources across parallel sessions, and controlling the level of parallelism and concurrency. To use Pabot, you must first install it with pip and then run it with the pabot command instead of the robot command. Additionally, you can use options and arguments like --processes, --resourcefile, or --suitesfrom to customize your parallel execution.

5 Monitor and analyze keyword performance

To optimize your keyword performance and reduce execution time, it's important to monitor and analyze your keyword performance. Robot Framework offers several options to measure and improve your keyword performance, such as the --loglevel option to control the amount of information logged during the execution, the --consolecolors option to highlight the status and duration of keywords, the --consolemarkers option to indicate the progress and outcome of keywords, the --timestampoutputs option to add timestamps to output and report files, and the --profile option to generate a profile file with detailed information about keyword execution time. By utilizing these tools and metrics, you can pinpoint bottlenecks and issues that affect your keyword performance and execution time, allowing you to apply the necessary changes and optimizations.