tablecache 2.1.0

Dead simple cache for unwieldily joined relations.

tablecache

Dead simple cache for unwieldily joined relations.

Copyright and license

Copyright 2023 Marc Lehmann

This file is part of tablecache.

tablecache is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

tablecache is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with tablecache. If not, see https://www.gnu.org/licenses/.

Purpose

tablecache is a small library that caches tables in a slow database (or, more likely, big joins of many tables) in a faster storage.

Suppose you have a relational database that's nice and normalized (many tables), but you also need fast access to data resulting from joining a lot of these tables to display somewhere.

tablecache can take your big query, and put the denormalized results in faster storage. When data is updated in the DB, the corresponding key in cache can be invalidated to be refreshed on the next request.

Usage

The main components when using the library are a DB table abstraction (PostgresTable), a storage table abstraction (RedisTable), and a CachedTable tying the 2 ends together.

The storage needs to encode and decode the data (to/from bytes). This is done via codecs. Some basic ones are provided (tablecache.*Codec).

Check out examples/users_cities.py for a quick start, which should be pretty self-explanatory.

Limitations

Currently, only Postgres is supported as DB, and only Redis as the fast storage.

The library assumes that the query to be cached has a (single) column acting as primary key, i.e. one which uniquely identifies a row in the result set of the query.

At the moment, the Redis storage supports only one table, which takes up the entire keyspace of the connected Redis instance.