test-load

Automate Locust-based performance testing of Python applications in CI pipelines.

1|Updated Dec 22, 2025
One-click install
npx skills add https://github.com/CybLow/pypaginate --skill test-load
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: test-load
Source: https://github.com/CybLow/pypaginate/tree/main/.opencode/skills/test-load
Command: npx skills add https://github.com/CybLow/pypaginate --skill test-load

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Load and performance testing of Python applications can be time-consuming and brittle without a repeatable framework. This Skill provides an end-to-end Locust-based workflow to simulate realistic user load, collect performance metrics, and validate SLAs across local, staging, and distributed environments. It supports CI integration, automated performance assertions, and scalable test orchestration.

Core Features & Use Cases

  • Locust-based load testing for Python apps
  • Automated performance assertions and SLA verification
  • Distributed testing with CI integration
  • Guidance for end-to-end performance workflows in real-world environments

Quick Start

Run a Locust load test against your API to observe latency, throughput, and reliability in CI.

Frequently Asked Questions about test-load

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate Locust load testing in a CI pipeline?

Automate Locust load testing in your CI pipeline by orchestrating distributed test runs against staging environments, collecting throughput and latency metrics, and enforcing automated performance assertions to verify SLAs.

What is distributed load testing and when do I need it for Python apps?

Distributed load testing simulates high user traffic across multiple machines to stress-test Python apps. You need it when a single machine cannot generate enough concurrent requests to validate SLA thresholds under realistic peak load.

How do I verify SLA thresholds with automated performance assertions?

Verify SLA thresholds by running Locust load tests to collect latency and reliability metrics, then applying automated performance assertions that fail the test run if response times or error rates exceed your defined SLA limits.

Does Locust work for containerized load testing environments?

Yes, Locust supports containerized load testing environments. You can orchestrate distributed Locust workers in containers to generate scalable load, collect performance metrics, and validate SLAs across your staging infrastructure.

What's the best way to run end-to-end performance testing for Python APIs?

The best way to run end-to-end performance testing for Python APIs is using a Locust-based workflow that simulates realistic user load, collects metrics, and validates SLAs through automated assertions integrated directly into your CI pipeline.

Why do I need load testing not working without distributed Locust workers?

Load testing fails to reach target concurrency without distributed Locust workers because a single machine hits CPU and network limits. Distributed testing scales load generation across multiple nodes to accurately simulate realistic traffic.