JMeter is a popular performance testing tool for testing the performance and load of web applications. It is usually used with a GUI, but the pymeter library is a powerful tool if you want to integrate JMeter in your automated tests or create and run test plans programmatically. This article will cover how to do JMeter testing in practice using Python and the pymeter library.
What is pymeter
pymeter is a Python library to programmatically create and run JMeter test plans. Using pymeter, you can easily configure test plans, add thread groups, set timers, add Samplers and listeners, and more. This makes it easy to automate performance tests and integrate performance tests in the continuous integration process.
Installing pymeter
To start using pymeter, you need to install it first.
It can be installed using pip:
pip install pymeter
Creating a JMeter Test Plan
Start by creating a simple JMeter test plan. Create a test plan that includes a thread group, an HTTP request Sampler, and an aggregated report Listener.
The following is sample code:
from import JMeter, TestPlan, ThreadGroup, Sampler, Listener
# Create JMeter objects
jmeter = JMeter()
# Create test plans
test_plan = TestPlan(name='My Test Plan', enabled=True)
(test_plan)
# Create thread groups
thread_group = ThreadGroup(name='Thread Group', num_threads=1, ramp_time=1, loops=1, enabled=True)
test_plan.append(thread_group)
# Create HTTP Request Sampler
http_sampler = Sampler(name='HTTP Request', enabled=True)
http_sampler.HTTPSamplerProxy(server_name='', path='/')
thread_group.append(http_sampler)
# Create aggregated reports Listener
aggregate_report = Listener(name='Aggregate Report', enabled=True)
thread_group.append(aggregate_report)
# Save test plan to file
('my_test.jmx')
The code above creates a simple JMeter test plan with a thread group, an HTTP request Sampler, and an aggregated report Listener; you can add more Samplers and Listener and configure their properties as needed.
Running a JMeter Test Plan
Having created a JMeter test plan, you can run it using pymeter. Here is the sample code:
from import Runner
# Create the Runner object
runner = Runner()
# Run test plans
result = ('my_test.jmx')
# Print results
print(result)
In the above code, a Runner object is created and the test plan created earlier is run using the run method. Once the run is complete, the test results can be obtained and processed.
Processing JMeter test results
pymeter makes it easy to work with JMeter test results.
Here is an example demonstrating how to get and print some test result data:
# Access to data from aggregated reports aggregate_report_data = result.get_aggregate_report_data() # Print the header line of the aggregated report print(aggregate_report_data[0]) # Print the first line of data print(aggregate_report_data[1])
In the code above, the data from the aggregated report is first fetched and then the header row and first row of data are printed. The test result data can be further processed as needed, such as saving it to a file or integrating it with other systems.
summarize
pymeter is a powerful Python library for creating and running JMeter test plans programmatically. It makes it easy to automate performance tests and can integrate performance tests in a continuous integration process. Hopefully, the hands-on guide in this article will help you get started with pymeter and improve your performance testing efficiency.
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