How to Load Test a Local API with Locust in Python

Defines a Locust load test that simulates traffic to local endpoints, enabling manual load testing against a development server.

Medium Python 3.9+ Aug 9, 2026 Testing & modern typing 16 views 0 copies

locust load-testing performance-testing testing
Requires third-party packages — install first
pip install locust

Python code

18 lines
Python 3.9+ 
from locust import HttpUser, task, between


class WebsiteUser(HttpUser):
    wait_time = between(1, 3)

    @task
    def home_page(self):
        self.client.get("/")

    @task(3)
    def about_page(self):
        self.client.get("/about")


if __name__ == "__main__":
    print("Run with: locust -f this_file.py --host=http://localhost:8000")
    print("Open http://localhost:8080 to start load testing.")

Output

stdout 
Run with: locust -f this_file.py --host=http://localhost:8000
Open http://localhost:8080 to start load testing.

How it works

The HttpUser class defines a simulated user that hits your local server. The @task decorator marks methods that are executed during the test; the optional weight (like @task(3) for about_page) means that endpoint is hit three times as often as the default weight 1. Setting wait_time = between(1, 3) adds realistic user think time between requests. When you run locust -f this_file.py --host=http://localhost:8000, Locust serves a web UI at localhost:8080 where you can set the number of users and spawn rate, then start the test.

Common mistakes

  • Forgetting to include a valid `--host` pointing to your running local server
  • Defining tasks without the `@task` decorator so Locust ignores them
  • Using a wait_time of 0, which floods the server and gives unrealistic results

Variations

  1. Run the test headless with `--headless -u 10 -r 2` for a CLI-only load test
  2. Use `SequentialTaskSet` to enforce an order of operations, like login then view a page

Real-world use cases

  • Checking that a locally running FastAPI or Flask dev server handles expected traffic before deploy.
  • Simulating spike traffic in a CI pipeline to catch performance regressions early.
  • Load testing a staging API to verify scaling capacity before a product launch.

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Run locally

This sample needs third-party packages, so it cannot run in the browser IDE. Copy the code above, install the packages shown at the top, then run it in your own Python environment.

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