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<!DOCTYPE html>
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<meta name="description" content="Caching reduces load on servers by pre-calculating the results of common operations. Learn more about caching on Full Stack Python.">
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<title>Caching - Full Stack Python</title>
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<h1>Caching</h1>
<p>Caching can reduce the load on servers by storing the results of common
operations and serving the precomputed answers to clients. </p>
<p>For example, instead of retrieving data from database tables that rarely
change, you can store the values in-memory. Retrieving values from an
in-memory location is far faster than retrieving them from a database (which
stores them on a persistent disk like a hard drive.) When the cached values
change the system can invalidate the cache and re-retrieve the updated values
for future requests.</p>
<p>A cache can be created for multiple layers of the stack. </p>
<h2>Caching backends</h2>
<ul>
<li>
<p><a href="http://memcached.org/">memcached</a> is a common in-memory caching system.</p>
</li>
<li>
<p><a href="http://redis.io/">Redis</a> is a key-value in-memory data store that can
easily be configured for caching with libraries such as
<a href="https://github.com/sebleier/django-redis-cache">django-redis-cache</a>.</p>
</li>
</ul>
<h2>Caching resources</h2>
<ul>
<li>
<p>"<a href="https://bjornjohansen.no/caching-varnish-or-nginx">Caching: Varnish or Nginx?</a>"
reviews some considerations such as SSL and SPDY support when choosing
reverse proxy Nginx or Varnish.</p>
</li>
<li>
<p><a href="http://bizcoder.com/caching-is-hard-draw-me-a-picture">Caching is Hard, Draw me a Picture</a>
has diagrams of how web request caching layers work. The post is relevant
reading even though the author is describing his Microsoft code as the
impetus for writing the content.</p>
</li>
<li>
<p>While caching is a useful technique in many situations, it's important
to also note that there are
<a href="https://msol.io/blog/tech/2015/09/05/youre-probably-wrong-about-caching/">downsides to caching</a>
that many developers fail to take into consideration.</p>
</li>
</ul>
<h2>Caching learning checklist</h2>
<ol>
<li>
<p>Analyze your web application for the slowest parts. It's likely there are
complex database queries that can be precomputed and stored in an in-memory
data store.</p>
</li>
<li>
<p>Leverage your existing in-memory data store already used for session data
to cache the results of those complex database queries. A
<a href="/task-queues.html">task queue</a> can often be used to precompute the results
on a regular basis and save them in the data store.</p>
</li>
<li>
<p>Incorporate a cache invalidation scheme so the precomputed results remain
accurate when served up to the user.</p>
</li>
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