The technical principles and use guidelines of the hot-redis library

Hot-Redis is a Python library for hot cache solutions.It uses the Redis database to achieve cache storage and update, which can effectively improve the reading performance and response speed of the system.This article will introduce the technical principles and use guidelines of the Hot-Redis class library in detail, and provide a complete programming code and related configuration description. 1. Technical principles Hot-Redis's hot cache solution is based on Redis's orderly setting (Sorted Set) and release/subscription mechanism.When the system needs to cache a data set, Hot-Redis first stores the data set in an orderly set, and the unique identifier of the data is used as a member of the orderly set, and the data thermal value is used as a score.The system will then subscribe to any update of the data set, such as data updates, delete or new operations.When a update operation occurs, the HOT-Redis will send the updated message to all subscribers by publishing/subscribing mechanism to update the cache in time. When using HOT-Redis on the client, you can use the following steps to achieve hotspot cache: 1. Install the Hot-Redis library Use the PIP command to install the latest version of the HOT-Redis library: pip install hot-redis 2. Initialize HOT-Redis object Import the HOT-Redis library in the Python code and initialize the HOT-Redis object: python from hot_redis import HotRedis redis = HotRedis(host='localhost', port=6379, db=0) 3. Cache data set Store the data set that needs to be cached to the orderly set, and set the corresponding heat value: python data = [{'id': 1, 'name': 'Alice'}, {'id': 2, 'name': 'Bob'}, ...] for item in data: redis.zadd('cache:key', item['id'], 0) 4. Subscribe to update operation Subs on the update operation of the data set in the code, such as: python def handle_update(message): print('Received update:', message) # refresh cache # Subscribe to update operation redis.subscribe('cache:update', handle_update) 5. Update data set When the data set needs to be updated, the update operation is triggered in the following way: python data = [{'id': 1, 'name': 'Alice'}, {'id': 2, 'name': 'Bob'}, ...] for item in data: redis.publish('cache:update', item) 2. Code interpretation and configuration description Some of the important descriptions in the above example code are as follows: -The "Cache: Key 'in Step 3 is the order name of the orderly collection of the storage data set, which can be set according to actual needs. -` `redis.zadd ('cache: key', item ['id'], 0)` `` `` `` `adds the members of the data set (Item ['ID']) toAnd set the corresponding heat value (0). -The "Cache: Update 'is a channel name for subscribing to update operation messages, which can be set according to actual needs. -` `redis.subscribe ('cache: update', handle_update)` `to subscribe to the update operation of the" Cache: Update 'channel, and perform the handle_update function to respond to the update message. -The `Redis.publish ('Cache: Update', Item)` is to publish data update messages through the 'Cache: Update' channel, thereby triggering the corresponding cache update operation. During the use of hot-redis, more configurations can be performed according to actual needs, such as setting the connection address (HOST), port number (Port) and database index (DB) of the Redis database.In addition, parameters of the cache expiration time and update frequency can be set to further optimize the cache strategy. Summarize: Hot-Redis, as a hot cache solution, uses the orderly collection and release/subscription mechanism of the Redis database to achieve efficient cache storage and update.By familiar with the technical principles and use guidelines of Hot-Redis, you can flexibly apply hotspots in the Python project to improve the performance and response speed of the system.