If you work with Flask and have an under heavy load API, you can setup a cache for your endpoints. One of the tools is Flask- Cache that can work with different cache backends like Memcached, Redis, Simple, etc.

To install it:

pip install Flask-Cache

To setup up:

from flask import Flask
 from flask.ext.cache import Cache

 app = Flask(__name__)
 # Check Configuring Flask-Cache section for more details
 cache_config = {
     "CACHE_TYPE": "redis",
     "CACHE_REDIS_HOST": "127.0.0.1",
     "CACHE_REDIS_PORT": 6379,
     "CACHE_REDIS_DB": 3
 }
 cache = Cache(app,config=cache_config})

Another redis implementation:

#: the_app/custom.py
 class RedisCache(BaseCache):
     def __init__(self, servers, default_timeout=500):
         pass

 def redis(app, config, args, kwargs):
    args.append(app.config['REDIS_SERVERS'])
    return RedisCache(*args, **kwargs)

Now to use the cache on a method use its decorator:

@cache.memoize(timeout=50)
 def big_foo(a, b):
     return a + b + random.randrange(0, 1000)

#python #flask #cache #redis #memcached

Those who are looking for scaling their cache server horizontally (redis/memcached) can use twemproxy. It is created by twitter:

https://github.com/twitter/twemproxy

#cache #redis #memcached #twemproxy

If you are building a docker image using docker build and you want to force building the package use --no-cache:

docker build --no-cache

#docker #build #no_cache #cache #force