In my Django project, I have a use case where I have some complex Python functions which are computationally expensive: they involve numerous calculations based on a recurrence relation. They are already well optimized but still take a few seconds to run in some cases.

在我的Django项目中，我有一个用例，其中我有一些复杂的Python函数，它们的计算代价很高：它们涉及基于递归关系的大量计算。它们已经得到了很好的优化，但在某些情况下仍需要几秒钟才能运行。

In this context, I'm thinking about using Celery tasks to carry out the calculations and to update aggregated data in dedicated tables of my PostgreSQL database. However, I have a feeling it's not going to be easy to ensure the integrity of the data and to avoid unnecessary calculations. Race conditions and unreliable error handling / retry mechanisms are some of the pitfalls I have in mind.

在这种情况下，我正在考虑使用芹菜任务来执行计算并更新我的PostgreSQL数据库的专用表中的聚合数据。然而，我有一种感觉，要确保数据的完整性并避免不必要的计算并不容易。竞争条件和不可靠的错误处理/重试机制是我考虑的一些陷阱。

What are the best practices in this case? What do I need to pay particular attention to?

这种情况下的最佳实践是什么？我需要特别注意什么？

Are you aware of open source Django projects doing something similar?

您是否知道开源Django项目也在做类似的事情？

I'm using Django 4.2, PostgreSQL 15, Redis 7.2 (as a cache), Celery 5.3, RabbitMQ 3.12 (as a broker).

我使用Django 4.2、PostgreSQL 15、Redis 7.2(作为缓存)、Celery 5.3、RabbitMQ 3.12(作为代理)。