> > 1) What strategy for caching I should consider while using SQLAlchemy? > Currently, the only option I see is to have a duplicated declaration of > entities in a form of simple classes and use it when I don't need > modification. Needles to say, it's a lot of code duplication.
I cache SqlAlchemy objects into Redis by turning them into normal dicts first (iterating over the columns), and saving the dicts into Redis via msgpack and `dogpile.cache`. Dogpile is great, because you can use it as a read-through cache -- a cache miss will load the info from SqlAlchemy direct. The dicts are then loaded from Redis, and injected into a generic class that overrides __get__ to offer a a 'dotted attribute' style syntax. After a while, we extended that caching layer to load related cached objects from Redis; the columns and relations to be used in the cache are managed in our SqlAlchemy class declarations too. 99% of our application uses the read-through Redis cache. Only write and permission/auth-based operations will use SqlAlchemy objects. -- SQLAlchemy - The Python SQL Toolkit and Object Relational Mapper http://www.sqlalchemy.org/ To post example code, please provide an MCVE: Minimal, Complete, and Verifiable Example. See http://stackoverflow.com/help/mcve for a full description. --- You received this message because you are subscribed to the Google Groups "sqlalchemy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sqlalchemy+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/sqlalchemy/81db3849-d6da-48e6-b941-5b96811f78b8%40googlegroups.com.
