Introduction to Memory Cache

Memory caching is a crucial technique in application development that helps improve performance by storing frequently accessed data in memory. This reduces the need to query slower data storage layers repeatedly, thus speeding up data retrieval. This blog post covers various APIs provided for memory caching along with code snippets and a comprehensive application example.

Basic Memory Cache Operations

Setting a Cache Value

Store a value in the cache with the following function.

  
  def set_cache(key, value):
      cache[key] = value
  

Getting a Cache Value

Retrieve a value from the cache:

  
  def get_cache(key):
      return cache.get(key)
  

Deleting a Cache Value

Remove a value from the cache:

  
  def delete_cache(key):
      if key in cache:
          del cache[key]
  

Checking if Cache Contains a Key

Check for the presence of a key in the cache:

  
  def contains_cache(key):
      return key in cache
  

Advanced Memory Cache Operations

Using Expiration Time

Implement an expiration mechanism:

  
  import time

  def set_cache_with_expiry(key, value, ttl):
      cache[key] = (value, time.time() + ttl)

  def get_cache_with_expiry(key):
      value, expiry = cache.get(key, (None, 0))
      if time.time() < expiry:
          return value
      else:
          cache.pop(key, None)
          return None
  

LRU (Least Recently Used) Cache

Implement LRU caching:

  
  from collections import OrderedDict

  class LRUCache:
      def __init__(self, capacity):
          self.cache = OrderedDict()
          self.capacity = capacity

      def get(self, key):
          if key not in self.cache:
              return -1
          else:
              self.cache.move_to_end(key)
              return self.cache[key]

      def put(self, key, value):
          if key in self.cache:
              self.cache.move_to_end(key)
          self.cache[key] = value
          if len(self.cache) > self.capacity:
              self.cache.popitem(last=False)
  

Application Example Using Memory Cache

Below is an example application that employs memory caching techniques mentioned above.

  
  class Application:
      def __init__(self):
          self.cache = LRUCache(5)
      
      def calculate_expensive_operation(self, num):
          if self.cache.get(num) == -1:
              result = num * num  # Placeholder for expensive calculation
              self.cache.put(num, result)
          return self.cache.get(num)
      
  app = Application()
  for i in range(10):
      print(f"Square of {i}: {app.calculate_expensive_operation(i)}")
  

By leveraging these memory caching techniques, applications can achieve significant performance improvements and ensure faster data retrieval.

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