Using HTTP Requests in Locust: Basic and Advanced Guide

Locust is a load testing tool that provides built‑in support for HTTP requests via the HttpUser class, allowing you to simulate many concurrent users.

Basic steps

1. Install Locust with pip install locust .

2. Write a Locust script (locustfile.py). The example defines a WebsiteUser class inheriting from HttpUser with three tasks: index_page (GET “/”), get_posts (GET “/posts”), and create_post (POST “/posts” with JSON data).

from locust import HttpUser, task, between

class WebsiteUser(HttpUser):
    wait_time = between(1, 5)  # wait 1‑5 seconds between tasks

    @task
    def index_page(self):
        """Visit home page"""
        self.client.get("/")

    @task
    def get_posts(self):
        """Get list of posts"""
        self.client.get("/posts")

    @task
    def create_post(self):
        """Create a new post"""
        post_data = {
            "title": "foo",
            "body": "bar",
            "userId": 1,
        }
        headers = {'Content-Type': 'application/json'}
        self.client.post("/posts", json=post_data, headers=headers)

3. Start Locust with locust -f locustfile.py and open the web UI at http://localhost:8089.

4. In the web UI, set the number of users to simulate and the hatch rate, then click “Start swarming”.

Advanced usage

Beyond basic GET and POST, Locust supports other HTTP methods (PUT, DELETE, etc.) and additional client features.

Use custom headers: self.client.get("/path", headers={"Authorization": "Bearer your_token"}) .

Use cookies: self.client.get("/path", cookies={"session_id": "your_session_id"}) or set global cookies in on_start method.

Handling responses

Capture responses with catch_response=True and mark success or failure based on status code:

with self.client.get("/path", catch_response=True) as response:
    if response.status_code == 200:
        response.success()
    else:
        response.failure(f"Failed with status code: {response.status_code}")

This guide provides both basic and advanced techniques for using HTTP requests in Locust to build effective performance testing scripts.