Performance bottlenecks can make or break your app, but load testing often gets pushed aside during development. In the open-source world, why aren't we treating performance testing as a shared responsibility? This talk shows how developers, testers, and infrastructure engineers can collaborate to build scalable Python applications.

We'll use a Django case study and Apache JMeter to demonstrate effective stress-testing techniques and common pitfalls to avoid. We'll also explore open-source tools like Locust and k6, and discuss how the community can contribute by sharing test plans, scripts, and best practices. Think of it as open-sourcing your load testing strategy.

Beyond the technical aspects, this session emphasizes collective knowledge. Imagine a world where shared test suites and benchmarking efforts become the norm—where Python apps benefit from community-driven testing.

标题：携手扩展：社区驱动的 Python 应用负载测试

议题介绍：性能瓶颈可能成就或毁掉您的应用，但负载测试在开发过程中常常被搁置一旁。在开源世界中，为什么我们没有将性能测试视为一项共同的责任？本次演讲将展示开发人员、测试人员和基础架构工程师如何协作构建可扩展的 Python 应用。

我们将使用 Django 案例研究和 Apache JMeter 来演示有效的压力测试技术以及需要避免的常见陷阱。我们还将探索 Locust 和 k6 等开源工具，并讨论社区如何通过共享测试计划、脚本和最佳实践来做出贡献。您可以将其视为对您的负载测试策略进行开源。

除了技术层面之外，本次演讲还强调集体智慧。想象一下，一个共享测试套件和基准测试工作成为常态的世界——Python 应用将从社区驱动的测试中受益。