What are the best practices for using Redis caching in Flask applications?

What are the best practices for using Redis caching in Flask applications?

When using Redis caching in Flask, consider these best practices: 1. Use a dedicated Redis client like redis-py. 2. Cache only the data that is expensive to compute. 3. Set appropriate expiration times for cached data. 4. Use cache keys wisely to avoid collisions. 5. Monitor cache performance and hit rates.

How do I set up Redis with Flask?

To set up Redis with Flask, first install the redis-py library using pip. Then, configure your Flask app to connect to your Redis server by initializing a Redis client and using it to cache your data.

What types of data should I cache?

You should cache data that is frequently accessed and computationally expensive to retrieve, such as database query results, API responses, or rendered templates.

Can you give an example of caching a database query?

Sure! You can use the Redis client to cache the result of a database query like this:

result = redis_client.get('my_query_key')
if result is None:
    result = db.session.query(MyModel).filter_by(condition).all()
    redis_client.set('my_query_key', result, ex=3600)  # Cache for 1 hour