By the end of this expansive lesson, we have greatly leveled up our basic key-value store. We found inspiration in Redis, a powerhouse in-memory data store, to implement features such as expiration times for keys and LRU caching, which are vital for optimizing memory usage and performance.

We explored deep into computer science concepts, gaining invaluable insights into how Redis, a software staple in various industries including AI and finance, operates under the hood. This surely expanded our dimension of knowledge and set a strong foundation for us to further delve into software development.

Remember, our improved key-value store is still a basic version when compared to Redis. Redis supports complex functionality like data replication, various data structures, Lua scripting, to name a few. Nonetheless, our expanded key-value store is a strong and confident stride into the world of building datastores from scratch, giving us a much comprehensive understanding of their working.

We encourage further exploration and experimentation with the key-value store, maybe adding enhancements or other features from Redis. The journey of learning and discovery continues, carrying forward our growth in the realm of software development and computer science.

xxxxxxxxxx

if __name__ == "__main__":

  # Final version of our Key-Value store

  store = KeyValueStore()

  store.set('AI', 'Artificial Intelligence')

  store.set('ML', 'Machine Learning')

  print(store.get('AI'))

  print(store.get('ML'))

  # Demonstrate LRU eviction

  for i in range(store.limit):

    store.set(f'key{i}', f'value{i}')

  print('Store state after LRU eviction', store.get_store())

​

  # Demonstrate expiration

  import time

  store.set('exp_key', 'exp_value', 5)

  time.sleep(5)

  print('Exp_key after expiration', store.get('exp_key'))