Getting Memory Stats in Redis using Python (Detailed Guide w/ Code Examples)

Use Case(s)

Memory stats are crucial for monitoring and managing your Redis setup. They can provide insights into memory usage, fragmentation ratio, keyspace hits/misses, and other valuable indicators of performance or potential issues.

Code Examples

Example 1: Basic example to get memory stats.

import redis r = redis.Redis(host='localhost', port=6379, db=0) info ='memory') print(info)

In this example, we first import the redis module and then establish a connection to the Redis server. We use the info method with the 'memory' argument to get memory information.

Example 2: Getting specific memory stats.

import redis r = redis.Redis(host='localhost', port=6379, db=0) info ='memory') print('Used Memory:', info['used_memory'], 'bytes') print('Memory Fragmentation Ratio:', info['mem_fragmentation_ratio'])

This example is similar to the previous one, but we're extracting and printing specific memory statistics.

Best Practices

  • Regularly monitor your memory usage to identify potential memory leaks or inefficient data structures.
  • Clean up unused connections and keys to optimize memory use.

Common Mistakes

  • Ignoring memory stats can lead to bloating and eventually crashing of your Redis instance.
  • Not closing unused connections can leak memory over time.


Q: How can I reduce memory usage in Redis? A: You can use memory-efficient data types, enable key expiry, and configure Redis for LRU eviction when memory is full.

Q: How often should I check memory stats? A: This depends on your application's needs. However, it's generally good practice to monitor them regularly for any unusual trends or spikes.

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