Memcache Examples

This page provides code examples in Python code for using Memcache. Memcache is a high-performance, distributed memory object caching system that provides fast access to cached data. To learn more about memcache, read the Memcache Overview .

The memcache Pattern

Memcache is typically used with the following pattern:

• The application receives a query from the user or the application.
• The application checks whether the data needed to satisfy that query is in memcache.
  • If the data is in memcache, the application uses that data.
  • If the data is not in memcache, the application queries the datastore and stores the results in memcache for future requests.

The pseudocode below represents a typical memcache request:

  def 
  
 get_data 
 (): 
 data 
 = 
 memcache 
 . 
 get 
 ( 
 'key' 
 ) 
 if 
 data 
 is 
 not 
 None 
 : 
 return 
 data 
 else 
 : 
 data 
 = 
 query_for_data 
 () 
 memcache 
 . 
 add 
 ( 
 'key' 
 , 
 data 
 , 
 60 
 ) 
 return 
 data 
 

ndb internally uses memcache to speed up queries. However, if you wish, you can also explicitly add memcache calls to gain more control about the speed-ups.

Caching data

The following example demonstrates several ways to set values in memcache using the Python API.

  # Add a value if it doesn't exist in the cache 
 # with a cache expiration of 1 hour. 
 memcache 
 . 
 add 
 ( 
 key 
 = 
 "weather_USA_98105" 
 , 
 value 
 = 
 "raining" 
 , 
 time 
 = 
 3600 
 ) 
 # Set several values, overwriting any existing values for these keys. 
 memcache 
 . 
 set_multi 
 ( 
 { 
 "USA_98115" 
 : 
 "cloudy" 
 , 
 "USA_94105" 
 : 
 "foggy" 
 , 
 "USA_94043" 
 : 
 "sunny" 
 }, 
 key_prefix 
 = 
 "weather_" 
 , 
 time 
 = 
 3600 
 ) 
 # Atomically increment an integer value. 
 memcache 
 . 
 set 
 ( 
 key 
 = 
 "counter" 
 , 
 value 
 = 
 0 
 ) 
 memcache 
 . 
 incr 
 ( 
 "counter" 
 ) 
 memcache 
 . 
 incr 
 ( 
 "counter" 
 ) 
 memcache 
 . 
 incr 
 ( 
 "counter" 
 ) 
 

To learn more about the add() , set_multi() , and set() methods, see the memcache Python API documentation .