---
name: pruebas-de-carga-locust
description: Experto en Locust para crear pruebas de carga distribuidas con Python, definiendo comportamiento de usuarios, formas de carga personalizadas e integración en pipelines CI. Ideal para validar el rendimiento de APIs y servicios web bajo tráfico real.
license: Apache-2.0
metadata:
  id: 10562161
  slug: pruebas-de-carga-locust
  titulo: "Pruebas de Carga con Locust"
  servicio: Web
  categoria_recurso: Web-Desarrollo
  tipo: referencia
  nivel: avanzado
  idioma: es
  idioma_original: en
  acceso: gratis
  precio_eur: 0
  plataformas: [Python, Locust, GitHub Actions, Linux, macOS]
  dependencias: [locust, python3]
  licencia: { spdx: Apache-2.0, redistribuible: true, uso_comercial: true }
  fuente:
    repo: TerminalSkills/skills
    url: https://github.com/TerminalSkills/skills/tree/main/skills/locust
    commit: 77fa015
    autor: TerminalSkills
    nombre_original: locust
    duplicados_en: []
  seguridad: { veredicto: seguro, riesgo: bajo, escaneado: "2026-06-14", motor: "grep-estatico+auditor-llm" }
  ficha:
    que_hace: "Genera locustfiles Python para simular usuarios concurrentes y medir el rendimiento de APIs bajo carga distribuida."
    como_lo_hace: "Define clases HttpUser con tareas ponderadas, formas de carga personalizadas y hooks de eventos, ejecutando pruebas en modo web UI o headless CI."
  content_hash: "10562161435a63017863c38a493b8aa10585457914f047a5656f00fe3a4905a5"
  version: 1.0.0
---

# Locust

## 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
```