干货：教你如何在JMeter中调用Python代码N种方法！

Summary of JMeter Integration with Python for Performance Testing

JMeter has become the go-to tool for performance testing professionals, facilitating user behavior simulation, response time measurement, and system performance evaluation. With the increasing complexity of interfaces that involve verification, signing, and encryption, there is a need for greater flexibility, such as the incorporation of Python for specific operations or complex logic handling, especially for those proficient in Python rather than Java.

There are several methods to integrate Python within JMeter, with some recommendations provided below.

Method 1: Using beanshell + Runtime.getRuntime().exec()

The Runtime.getRuntime().exec() method allows the execution of external commands within a Java application, enabling the use of command-line tools or executables. It returns a Process object for managing the external process, but caution is advised to prevent potential security vulnerabilities. The article provides an example of how to execute a Python script to fetch a token from an API using this method. Alternatively, the OS Process Sampler in JMeter can also execute system commands, including Python scripts.

Method 2: Using JSR223 Sampler + jython

Another approach is to leverage the JSR223 Sampler with Jython to execute Python scripts. The process involves downloading the Jython standalone JAR, placing it in the JMeter's lib directory, and restarting JMeter. After adding a JSR223 Sampler to the thread group, users can write Python scripts according to their performance testing needs. An example is provided where a script encrypts login details.

Method 3: Using the pymeter library

The pymeter library enables performance testing in Python with an experience similar to that of JMeter's GUI. After installing pymeter using pip, users can create performance tests as illustrated in the example provided, which showcases the use of a TestCase class, various samplers, postprocessors, timers, and an HTML reporter. The execution generates an output directory with an HTML report and a .jtl results file.

The article concludes by encouraging readers to follow for more useful tips, like the article, and share it with their network. It also suggests additional reading materials on full-stack testing skills, testing development tools, and test data generation tools.

想要了解更多内容？

查看原文：干货：教你如何在JMeter中调用Python代码N种方法！

文章来源：

测试开发技术

扫码关注公众号