Terminal.skills
Skills/locust
>

locust

When the user wants to perform load testing using Python with Locust's distributed architecture and real-time web UI. Also use when the user mentions "locust," "Python load testing," "distributed load test," "locust web UI," or "locustfile." For JavaScript-based load testing, see k6 or artillery.

#load-testing#python#distributed#performance
terminal-skillsv1.0.0
Works with:claude-codeopenai-codexgemini-clicursor
Source

Usage

$
✓ Installed locust v1.0.0

Getting Started

  1. Install the skill using the command above
  2. Open your AI coding agent (Claude Code, Codex, Gemini CLI, or Cursor)
  3. Reference the skill in your prompt
  4. The AI will use the skill's capabilities automatically

Example Prompts

  • "Review the open pull requests and summarize what needs attention"
  • "Generate a changelog from the last 20 commits on the main branch"

Documentation

Overview

You are an expert in Locust, the Python-based load testing framework. You help users write locustfiles that define user behavior as Python code, configure distributed load generation across multiple machines, use the real-time web UI for monitoring, and integrate Locust into CI pipelines in headless mode. You understand Locust's event hooks, task weighting, and custom load shapes.

Instructions

Initial Assessment

Before writing a locustfile:

  1. Target — What service or API are you testing?
  2. User behavior — What does a typical user session look like?
  3. Scale — How many concurrent users? Distributed across machines?
  4. Mode — Interactive (web UI) or headless (CI)?

Basic Locustfile

python
# locustfile.py — Basic Locust load test for an e-commerce API.
# Simulates users browsing products and adding items to cart.
from locust import HttpUser, task, between

class WebsiteUser(HttpUser):
    wait_time = between(1, 3)
    host = "https://api.example.com"

    def on_start(self):
        """Called when a simulated user starts. Login once per user."""
        self.client.post("/login", json={
            "username": "testuser",
            "password": "testpass"
        })

    @task(3)
    def browse_products(self):
        self.client.get("/products")

    @task(2)
    def view_product(self):
        self.client.get("/products/1")

    @task(1)
    def add_to_cart(self):
        self.client.post("/cart", json={"product_id": 1, "quantity": 1})

Custom Load Shapes

python
# load_shape.py — Custom load shape that simulates daily traffic patterns.
# Ramps up in the morning, peaks at noon, drops in the evening.
from locust import HttpUser, task, between, LoadTestShape

class ApiUser(HttpUser):
    wait_time = between(1, 5)

    @task
    def get_data(self):
        self.client.get("/api/data")

class DailyTrafficShape(LoadTestShape):
    stages = [
        {"duration": 60, "users": 20, "spawn_rate": 5},
        {"duration": 120, "users": 100, "spawn_rate": 10},
        {"duration": 180, "users": 200, "spawn_rate": 20},
        {"duration": 120, "users": 100, "spawn_rate": 10},
        {"duration": 60, "users": 0, "spawn_rate": 20},
    ]

    def tick(self):
        run_time = self.get_run_time()
        elapsed = 0
        for stage in self.stages:
            elapsed += stage["duration"]
            if run_time < elapsed:
                return (stage["users"], stage["spawn_rate"])
        return None

Distributed Testing

bash
# distributed-run.sh — Run Locust in distributed mode across multiple machines.
# One master coordinates, workers generate the actual load.

# Install
pip install locust

# Start master (web UI on port 8089)
locust --master --host https://api.example.com

# Start workers (run on each worker machine)
locust --worker --master-host=192.168.1.100

# Headless distributed run
locust --master --headless -u 1000 -r 50 --run-time 5m \
  --expect-workers 4 --host https://api.example.com

Event Hooks

python
# events_example.py — Using Locust event hooks for custom reporting.
# Logs failures to a file and sends alerts on high error rates.
from locust import HttpUser, task, between, events
import logging

logger = logging.getLogger("locust_custom")

@events.request.add_listener
def on_request(request_type, name, response_time, response_length, exception, **kwargs):
    if exception:
        logger.error(f"FAILED: {request_type} {name} - {exception}")

@events.test_stop.add_listener
def on_test_stop(environment, **kwargs):
    stats = environment.runner.stats
    total = stats.total
    if total.fail_ratio > 0.05:
        logger.critical(f"ALERT: Error rate {total.fail_ratio:.1%} exceeds 5% threshold")

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

    @task
    def get_endpoint(self):
        self.client.get("/api/health")

Headless CI Mode

yaml
# .github/workflows/locust.yml — Run Locust headless in GitHub Actions.
# Exports CSV results as pipeline artifacts.
name: Load Test
on:
  push:
    branches: [main]
jobs:
  locust:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.12"
      - run: pip install locust
      - run: |
          locust --headless -u 50 -r 10 --run-time 2m \
            --host https://api.example.com \
            --csv results \
            -f tests/locustfile.py
      - uses: actions/upload-artifact@v4
        if: always()
        with:
          name: locust-results
          path: results_*.csv

Information

Version
1.0.0
Author
terminal-skills
Category
Development
License
Apache-2.0