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<div class="section" id="s-performance-and-optimization">
<span id="performance-and-optimization"></span><h1>Performance and optimization<a class="headerlink" href="#performance-and-optimization" title="Permalink to this headline">¶</a></h1>
<p>This document provides an overview of techniques and tools that can help get
your Django code running more efficiently - faster, and using fewer system
resources.</p>
<div class="section" id="s-introduction">
<span id="introduction"></span><h2>Introduction<a class="headerlink" href="#introduction" title="Permalink to this headline">¶</a></h2>
<p>Generally one’s first concern is to write code that <em>works</em>, whose logic
functions as required to produce the expected output. Sometimes, however, this
will not be enough to make the code work as <em>efficiently</em> as one would like.</p>
<p>In this case, what’s needed is something - and in practice, often a collection
of things - to improve the code’s performance without, or only minimally,
affecting its behavior.</p>
</div>
<div class="section" id="s-general-approaches">
<span id="general-approaches"></span><h2>General approaches<a class="headerlink" href="#general-approaches" title="Permalink to this headline">¶</a></h2>
<div class="section" id="s-what-are-you-optimizing-for">
<span id="what-are-you-optimizing-for"></span><h3>What are you optimizing <em>for</em>?<a class="headerlink" href="#what-are-you-optimizing-for" title="Permalink to this headline">¶</a></h3>
<p>It’s important to have a clear idea what you mean by ‘performance’. There is
not just one metric of it.</p>
<p>Improved speed might be the most obvious aim for a program, but sometimes other
performance improvements might be sought, such as lower memory consumption or
fewer demands on the database or network.</p>
<p>Improvements in one area will often bring about improved performance in
another, but not always; sometimes one can even be at the expense of another.
For example, an improvement in a program’s speed might cause it to use more
memory. Even worse, it can be self-defeating - if the speed improvement is so
memory-hungry that the system starts to run out of memory, you’ll have done
more harm than good.</p>
<p>There are other trade-offs to bear in mind. Your own time is a valuable
resource, more precious than CPU time. Some improvements might be too difficult
to be worth implementing, or might affect the portability or maintainability of
the code. Not all performance improvements are worth the effort.</p>
<p>So, you need to know what performance improvements you are aiming for, and you
also need to know that you have a good reason for aiming in that direction -
and for that you need:</p>
</div>
<div class="section" id="s-performance-benchmarking">
<span id="performance-benchmarking"></span><h3>Performance benchmarking<a class="headerlink" href="#performance-benchmarking" title="Permalink to this headline">¶</a></h3>
<p>It’s no good just guessing or assuming where the inefficiencies lie in your
code.</p>
<div class="section" id="s-django-tools">
<span id="django-tools"></span><h4>Django tools<a class="headerlink" href="#django-tools" title="Permalink to this headline">¶</a></h4>
<p><a class="reference external" href="https://github.com/django-debug-toolbar/django-debug-toolbar/">django-debug-toolbar</a> is a very
handy tool that provides insights into what your code is doing and how much
time it spends doing it. In particular it can show you all the SQL queries your
page is generating, and how long each one has taken.</p>
<p>Third-party panels are also available for the toolbar, that can (for example)
report on cache performance and template rendering times.</p>
</div>
<div class="section" id="s-third-party-services">
<span id="third-party-services"></span><h4>Third-party services<a class="headerlink" href="#third-party-services" title="Permalink to this headline">¶</a></h4>
<p>There are a number of free services that will analyze and report on the
performance of your site’s pages from the perspective of a remote HTTP client,
in effect simulating the experience of an actual user.</p>
<p>These can’t report on the internals of your code, but can provide a useful
insight into your site’s overall performance, including aspects that can’t be
adequately measured from within Django environment. Examples include:</p>
<ul class="simple">
<li><a class="reference external" href="http://yslow.org/">Yahoo’s Yslow</a></li>
<li><a class="reference external" href="https://developers.google.com/speed/pagespeed/">Google PageSpeed</a></li>
</ul>
<p>There are also several paid-for services that perform a similar analysis,
including some that are Django-aware and can integrate with your codebase to
profile its performance far more comprehensively.</p>
</div>
</div>
<div class="section" id="s-get-things-right-from-the-start">
<span id="get-things-right-from-the-start"></span><h3>Get things right from the start<a class="headerlink" href="#get-things-right-from-the-start" title="Permalink to this headline">¶</a></h3>
<p>Some work in optimization involves tackling performance shortcomings, but some
of the work can simply be built in to what you’d do anyway, as part of the good
practices you should adopt even before you start thinking about improving
performance.</p>
<p>In this respect Python is an excellent language to work with, because solutions
that look elegant and feel right usually are the best performing ones. As with
most skills, learning what “looks right” takes practice, but one of the most
useful guidelines is:</p>
<div class="section" id="s-work-at-the-appropriate-level">
<span id="work-at-the-appropriate-level"></span><h4>Work at the appropriate level<a class="headerlink" href="#work-at-the-appropriate-level" title="Permalink to this headline">¶</a></h4>
<p>Django offers many different ways of approaching things, but just because it’s
possible to do something in a certain way doesn’t mean that it’s the most
appropriate way to do it. For example, you might find that you could calculate
the same thing - the number of items in a collection, perhaps - in a
<code class="docutils literal"><span class="pre">QuerySet</span></code>, in Python, or in a template.</p>
<p>However, it will almost always be faster to do this work at lower rather than
higher levels. At higher levels the system has to deal with objects through
multiple levels of abstraction and layers of machinery.</p>
<p>That is, the database can typically do things faster than Python can, which can
do them faster than the template language can:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1"># QuerySet operation on the database</span>
<span class="c1"># fast, because that's what databases are good at</span>
<span class="n">my_bicycles</span><span class="o">.</span><span class="n">count</span><span class="p">()</span>
<span class="c1"># counting Python objects</span>
<span class="c1"># slower, because it requires a database query anyway, and processing</span>
<span class="c1"># of the Python objects</span>
<span class="nb">len</span><span class="p">(</span><span class="n">my_bicycles</span><span class="p">)</span>
<span class="c1"># Django template filter</span>
<span class="c1"># slower still, because it will have to count them in Python anyway,</span>
<span class="c1"># and because of template language overheads</span>
<span class="p">{{</span> <span class="n">my_bicycles</span><span class="o">|</span><span class="n">length</span> <span class="p">}}</span>
</pre></div>
</div>
<p>Generally speaking, the most appropriate level for the job is the lowest-level
one that it is comfortable to code for.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p>The example above is merely illustrative.</p>
<p>Firstly, in a real-life case you need to consider what is happening before
and after your count to work out what’s an optimal way of doing it <em>in that
particular context</em>. The database optimization documents describes <a class="reference internal" href="db/optimization.html#overuse-of-count-and-exists"><span class="std std-ref">a
case where counting in the template would be better</span></a>.</p>
<p class="last">Secondly, there are other options to consider: in a real-life case, <code class="docutils literal"><span class="pre">{{</span>
<span class="pre">my_bicycles.count</span> <span class="pre">}}</span></code>, which invokes the <code class="docutils literal"><span class="pre">QuerySet</span></code> <code class="docutils literal"><span class="pre">count()</span></code> method
directly from the template, might be the most appropriate choice.</p>
</div>
</div>
</div>
</div>
<div class="section" id="s-caching">
<span id="caching"></span><h2>Caching<a class="headerlink" href="#caching" title="Permalink to this headline">¶</a></h2>
<p>Often it is expensive (that is, resource-hungry and slow) to compute a value,
so there can be huge benefit in saving the value to a quickly accessible cache,
ready for the next time it’s required.</p>
<p>It’s a sufficiently significant and powerful technique that Django includes a
comprehensive caching framework, as well as other smaller pieces of caching
functionality.</p>
<div class="section" id="s-the-caching-framework">
<span id="the-caching-framework"></span><h3><a class="reference internal" href="cache.html"><span class="doc">The caching framework</span></a><a class="headerlink" href="#the-caching-framework" title="Permalink to this headline">¶</a></h3>
<p>Django’s <a class="reference internal" href="cache.html"><span class="doc">caching framework</span></a> offers very significant
opportunities for performance gains, by saving dynamic content so that it
doesn’t need to be calculated for each request.</p>
<p>For convenience, Django offers different levels of cache granularity: you can
cache the output of specific views, or only the pieces that are difficult to
produce, or even an entire site.</p>
<p>Implementing caching should not be regarded as an alternative to improving code
that’s performing poorly because it has been written badly. It’s one of the
final steps towards producing well-performing code, not a shortcut.</p>
</div>
<div class="section" id="s-cached-property">
<span id="cached-property"></span><h3><a class="reference internal" href="../ref/utils.html#django.utils.functional.cached_property" title="django.utils.functional.cached_property"><code class="xref py py-class docutils literal"><span class="pre">cached_property</span></code></a><a class="headerlink" href="#cached-property" title="Permalink to this headline">¶</a></h3>
<p>It’s common to have to call a class instances’s method more than once. If
that function is expensive, then doing so can be wasteful.</p>
<p>Using the <a class="reference internal" href="../ref/utils.html#django.utils.functional.cached_property" title="django.utils.functional.cached_property"><code class="xref py py-class docutils literal"><span class="pre">cached_property</span></code></a> decorator saves the
value returned by a property; the next time the function is called on that
instance, it will return the saved value rather than re-computing it. Note that
this only works on methods that take <code class="docutils literal"><span class="pre">self</span></code> as their only argument and that
it changes the method to a property.</p>
<p>Certain Django components also have their own caching functionality; these are
discussed below in the sections related to those components.</p>
</div>
</div>
<div class="section" id="s-understanding-laziness">
<span id="understanding-laziness"></span><h2>Understanding laziness<a class="headerlink" href="#understanding-laziness" title="Permalink to this headline">¶</a></h2>
<p><em>Laziness</em> is a strategy complementary to caching. Caching avoids
recomputation by saving results; laziness delays computation until it’s
actually required.</p>
<p>Laziness allows us to refer to things before they are instantiated, or even
before it’s possible to instantiate them. This has numerous uses.</p>
<p>For example, <a class="reference internal" href="i18n/translation.html#lazy-translations"><span class="std std-ref">lazy translation</span></a> can be used before the
target language is even known, because it doesn’t take place until the
translated string is actually required, such as in a rendered template.</p>
<p>Laziness is also a way to save effort by trying to avoid work in the first
place. That is, one aspect of laziness is not doing anything until it has to be
done, because it may not turn out to be necessary after all. Laziness can
therefore have performance implications, and the more expensive the work
concerned, the more there is to gain through laziness.</p>
<p>Python provides a number of tools for lazy evaluation, particularly through the
<span class="xref std std-term">generator</span> and <span class="xref std std-term">generator expression</span> constructs. It’s worth
reading up on laziness in Python to discover opportunities for making use of
lazy patterns in your code.</p>
<div class="section" id="s-laziness-in-django">
<span id="laziness-in-django"></span><h3>Laziness in Django<a class="headerlink" href="#laziness-in-django" title="Permalink to this headline">¶</a></h3>
<p>Django is itself quite lazy. A good example of this can be found in the
evaluation of <code class="docutils literal"><span class="pre">QuerySets</span></code>. <a class="reference internal" href="db/queries.html#querysets-are-lazy"><span class="std std-ref">QuerySets are lazy</span></a>.
Thus a <code class="docutils literal"><span class="pre">QuerySet</span></code> can be created, passed around and combined with other
<code class="docutils literal"><span class="pre">QuerySets</span></code>, without actually incurring any trips to the database to fetch
the items it describes. What gets passed around is the <code class="docutils literal"><span class="pre">QuerySet</span></code> object, not
the collection of items that - eventually - will be required from the database.</p>
<p>On the other hand, <a class="reference internal" href="../ref/models/querysets.html#when-querysets-are-evaluated"><span class="std std-ref">certain operations will force the evaluation of a
QuerySet</span></a>. Avoiding the premature evaluation of
a <code class="docutils literal"><span class="pre">QuerySet</span></code> can save making an expensive and unnecessary trip to the
database.</p>
<p>Django also offers an <a class="reference internal" href="../ref/utils.html#django.utils.functional.allow_lazy" title="django.utils.functional.allow_lazy"><code class="xref py py-meth docutils literal"><span class="pre">allow_lazy()</span></code></a> decorator.
This allows a function that has been called with a lazy argument to behave
lazily itself, only being evaluated when it needs to be. Thus the lazy argument
- which could be an expensive one - will not be called upon for evaluation
until it’s strictly required.</p>
</div>
</div>
<div class="section" id="s-databases">
<span id="databases"></span><h2>Databases<a class="headerlink" href="#databases" title="Permalink to this headline">¶</a></h2>
<div class="section" id="s-database-optimization">
<span id="database-optimization"></span><h3><a class="reference internal" href="db/optimization.html"><span class="doc">Database optimization</span></a><a class="headerlink" href="#database-optimization" title="Permalink to this headline">¶</a></h3>
<p>Django’s database layer provides various ways to help developers get the best
performance from their databases. The <a class="reference internal" href="db/optimization.html"><span class="doc">database optimization documentation</span></a> gathers together links to the relevant
documentation and adds various tips that outline the steps to take when
attempting to optimize your database usage.</p>
</div>
<div class="section" id="s-other-database-related-tips">
<span id="other-database-related-tips"></span><h3>Other database-related tips<a class="headerlink" href="#other-database-related-tips" title="Permalink to this headline">¶</a></h3>
<p>Enabling <a class="reference internal" href="../ref/databases.html#persistent-database-connections"><span class="std std-ref">Persistent connections</span></a> can speed up connections to the
database accounts for a significant part of the request processing time.</p>
<p>This helps a lot on virtualized hosts with limited network performance, for example.</p>
</div>
</div>
<div class="section" id="s-http-performance">
<span id="http-performance"></span><h2>HTTP performance<a class="headerlink" href="#http-performance" title="Permalink to this headline">¶</a></h2>
<div class="section" id="s-middleware">
<span id="middleware"></span><h3>Middleware<a class="headerlink" href="#middleware" title="Permalink to this headline">¶</a></h3>
<p>Django comes with a few helpful pieces of <a class="reference internal" href="../ref/middleware.html"><span class="doc">middleware</span></a>
that can help optimize your site’s performance. They include:</p>
<div class="section" id="s-conditionalgetmiddleware">
<span id="conditionalgetmiddleware"></span><h4><a class="reference internal" href="../ref/middleware.html#django.middleware.http.ConditionalGetMiddleware" title="django.middleware.http.ConditionalGetMiddleware"><code class="xref py py-class docutils literal"><span class="pre">ConditionalGetMiddleware</span></code></a><a class="headerlink" href="#conditionalgetmiddleware" title="Permalink to this headline">¶</a></h4>
<p>Adds support for modern browsers to conditionally GET responses based on the
<code class="docutils literal"><span class="pre">ETag</span></code> and <code class="docutils literal"><span class="pre">Last-Modified</span></code> headers.</p>
</div>
<div class="section" id="s-gzipmiddleware">
<span id="gzipmiddleware"></span><h4><a class="reference internal" href="../ref/middleware.html#django.middleware.gzip.GZipMiddleware" title="django.middleware.gzip.GZipMiddleware"><code class="xref py py-class docutils literal"><span class="pre">GZipMiddleware</span></code></a><a class="headerlink" href="#gzipmiddleware" title="Permalink to this headline">¶</a></h4>
<p>Compresses responses for all modern browsers, saving bandwidth and transfer
time. Note that GZipMiddleware is currently considered a security risk, and is
vulnerable to attacks that nullify the protection provided by TLS/SSL. See the
warning in <a class="reference internal" href="../ref/middleware.html#django.middleware.gzip.GZipMiddleware" title="django.middleware.gzip.GZipMiddleware"><code class="xref py py-class docutils literal"><span class="pre">GZipMiddleware</span></code></a> for more information.</p>
</div>
</div>
<div class="section" id="s-sessions">
<span id="sessions"></span><h3>Sessions<a class="headerlink" href="#sessions" title="Permalink to this headline">¶</a></h3>
<div class="section" id="s-using-cached-sessions">
<span id="using-cached-sessions"></span><h4>Using cached sessions<a class="headerlink" href="#using-cached-sessions" title="Permalink to this headline">¶</a></h4>
<p><a class="reference internal" href="http/sessions.html#cached-sessions-backend"><span class="std std-ref">Using cached sessions</span></a> may be a way to increase
performance by eliminating the need to load session data from a slower storage
source like the database and instead storing frequently used session data in
memory.</p>
</div>
</div>
<div class="section" id="s-static-files">
<span id="static-files"></span><h3>Static files<a class="headerlink" href="#static-files" title="Permalink to this headline">¶</a></h3>
<p>Static files, which by definition are not dynamic, make an excellent target for
optimization gains.</p>
<div class="section" id="s-cachedstaticfilesstorage">
<span id="cachedstaticfilesstorage"></span><h4><a class="reference internal" href="../ref/contrib/staticfiles.html#django.contrib.staticfiles.storage.CachedStaticFilesStorage" title="django.contrib.staticfiles.storage.CachedStaticFilesStorage"><code class="xref py py-class docutils literal"><span class="pre">CachedStaticFilesStorage</span></code></a><a class="headerlink" href="#cachedstaticfilesstorage" title="Permalink to this headline">¶</a></h4>
<p>By taking advantage of web browsers’ caching abilities, you can
eliminate network hits entirely for a given file after the initial download.</p>
<p><a class="reference internal" href="../ref/contrib/staticfiles.html#django.contrib.staticfiles.storage.CachedStaticFilesStorage" title="django.contrib.staticfiles.storage.CachedStaticFilesStorage"><code class="xref py py-class docutils literal"><span class="pre">CachedStaticFilesStorage</span></code></a> appends a
content-dependent tag to the filenames of <a class="reference internal" href="../ref/contrib/staticfiles.html"><span class="doc">static files</span></a> to make it safe for browsers to cache them
long-term without missing future changes - when a file changes, so will the
tag, so browsers will reload the asset automatically.</p>
</div>
<div class="section" id="s-minification">
<span id="minification"></span><h4>“Minification”<a class="headerlink" href="#minification" title="Permalink to this headline">¶</a></h4>
<p>Several third-party Django tools and packages provide the ability to “minify”
HTML, CSS, and JavaScript. They remove unnecessary whitespace, newlines, and
comments, and shorten variable names, and thus reduce the size of the documents
that your site publishes.</p>
</div>
</div>
</div>
<div class="section" id="s-template-performance">
<span id="template-performance"></span><h2>Template performance<a class="headerlink" href="#template-performance" title="Permalink to this headline">¶</a></h2>
<p>Note that:</p>
<ul class="simple">
<li>using <code class="docutils literal"><span class="pre">{%</span> <span class="pre">block</span> <span class="pre">%}</span></code> is faster than using <code class="docutils literal"><span class="pre">{%</span> <span class="pre">include</span> <span class="pre">%}</span></code></li>
<li>heavily-fragmented templates, assembled from many small pieces, can affect
performance</li>
</ul>
<div class="section" id="s-the-cached-template-loader">
<span id="the-cached-template-loader"></span><h3>The cached template loader<a class="headerlink" href="#the-cached-template-loader" title="Permalink to this headline">¶</a></h3>
<p>Enabling the <a class="reference internal" href="../ref/templates/api.html#django.template.loaders.cached.Loader" title="django.template.loaders.cached.Loader"><code class="xref py py-class docutils literal"><span class="pre">cached</span> <span class="pre">template</span> <span class="pre">loader</span></code></a> often improves performance
drastically, as it avoids compiling each template every time it needs to be
rendered.</p>
</div>
</div>
<div class="section" id="s-using-different-versions-of-available-software">
<span id="using-different-versions-of-available-software"></span><h2>Using different versions of available software<a class="headerlink" href="#using-different-versions-of-available-software" title="Permalink to this headline">¶</a></h2>
<p>It can sometimes be worth checking whether different and better-performing
versions of the software that you’re using are available.</p>
<p>These techniques are targeted at more advanced users who want to push the
boundaries of performance of an already well-optimized Django site.</p>
<p>However, they are not magic solutions to performance problems, and they’re
unlikely to bring better than marginal gains to sites that don’t already do the
more basic things the right way.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">It’s worth repeating: <strong>reaching for alternatives to software you’re
already using is never the first answer to performance problems</strong>. When
you reach this level of optimization, you need a formal benchmarking
solution.</p>
</div>
<div class="section" id="s-newer-is-often-but-not-always-better">
<span id="newer-is-often-but-not-always-better"></span><h3>Newer is often - but not always - better<a class="headerlink" href="#newer-is-often-but-not-always-better" title="Permalink to this headline">¶</a></h3>
<p>It’s fairly rare for a new release of well-maintained software to be less
efficient, but the maintainers can’t anticipate every possible use-case - so
while being aware that newer versions are likely to perform better, don’t
simply assume that they always will.</p>
<p>This is true of Django itself. Successive releases have offered a number of
improvements across the system, but you should still check the real-world
performance of your application, because in some cases you may find that
changes mean it performs worse rather than better.</p>
<p>Newer versions of Python, and also of Python packages, will often perform
better too - but measure, rather than assume.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Unless you’ve encountered an unusual performance problem in a particular
version, you’ll generally find better features, reliability, and security
in a new release and that these benefits are far more significant than any
performance you might win or lose.</p>
</div>
</div>
<div class="section" id="s-alternatives-to-django-s-template-language">
<span id="alternatives-to-django-s-template-language"></span><h3>Alternatives to Django’s template language<a class="headerlink" href="#alternatives-to-django-s-template-language" title="Permalink to this headline">¶</a></h3>
<p>For nearly all cases, Django’s built-in template language is perfectly
adequate. However, if the bottlenecks in your Django project seem to lie in the
template system and you have exhausted other opportunities to remedy this, a
third-party alternative may be the answer.</p>
<p><a class="reference external" href="http://jinja.pocoo.org/docs/">Jinja2</a> can offer performance improvements,
particularly when it comes to speed.</p>
<p>Alternative template systems vary in the extent to which they share Django’s
templating language.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last"><em>If</em> you experience performance issues in templates, the first thing to do
is to understand exactly why. Using an alternative template system may
prove faster, but the same gains may also be available without going to
that trouble - for example, expensive processing and logic in your
templates could be done more efficiently in your views.</p>
</div>
</div>
<div class="section" id="s-alternative-software-implementations">
<span id="alternative-software-implementations"></span><h3>Alternative software implementations<a class="headerlink" href="#alternative-software-implementations" title="Permalink to this headline">¶</a></h3>
<p>It may be worth checking whether Python software you’re using has been
provided in a different implementation that can execute the same code faster.</p>
<p>However: most performance problems in well-written Django sites aren’t at the
Python execution level, but rather in inefficient database querying, caching,
and templates. If you’re relying on poorly-written Python code, your
performance problems are unlikely to be solved by having it execute faster.</p>
<p>Using an alternative implementation may introduce compatibility, deployment,
portability, or maintenance issues. It goes without saying that before adopting
a non-standard implementation you should ensure it provides sufficient
performance gains for your application to outweigh the potential risks.</p>
<p>With these caveats in mind, you should be aware of:</p>
<div class="section" id="s-id1">
<span id="id1"></span><h4><a class="reference external" href="http://pypy.org/">PyPy</a><a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h4>
<p><a class="reference external" href="http://pypy.org/">PyPy</a> is an implementation of Python in Python itself (the
‘standard’ Python implementation is in C). PyPy can offer substantial
performance gains, typically for heavyweight applications.</p>
<p>A key aim of the PyPy project is <a class="reference external" href="http://pypy.org/compat.html">compatibility</a> with existing Python APIs and libraries.
Django is compatible, but you will need to check the compatibility of other
libraries you rely on.</p>
</div>
<div class="section" id="s-c-implementations-of-python-libraries">
<span id="c-implementations-of-python-libraries"></span><h4>C implementations of Python libraries<a class="headerlink" href="#c-implementations-of-python-libraries" title="Permalink to this headline">¶</a></h4>
<p>Some Python libraries are also implemented in C, and can be much faster. They
aim to offer the same APIs. Note that compatibility issues and behavior
differences are not unknown (and not always immediately evident).</p>
</div>
</div>
</div>
</div>
</div>
</div>
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<h3><a href="../contents.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">Performance and optimization</a><ul>
<li><a class="reference internal" href="#introduction">Introduction</a></li>
<li><a class="reference internal" href="#general-approaches">General approaches</a><ul>
<li><a class="reference internal" href="#what-are-you-optimizing-for">What are you optimizing <em>for</em>?</a></li>
<li><a class="reference internal" href="#performance-benchmarking">Performance benchmarking</a><ul>
<li><a class="reference internal" href="#django-tools">Django tools</a></li>
<li><a class="reference internal" href="#third-party-services">Third-party services</a></li>
</ul>
</li>
<li><a class="reference internal" href="#get-things-right-from-the-start">Get things right from the start</a><ul>
<li><a class="reference internal" href="#work-at-the-appropriate-level">Work at the appropriate level</a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#caching">Caching</a><ul>
<li><a class="reference internal" href="#the-caching-framework"><code class="docutils literal"><span class="pre">The</span> <span class="pre">caching</span> <span class="pre">framework</span></code></a></li>
<li><a class="reference internal" href="#cached-property"><code class="docutils literal"><span class="pre">cached_property</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#understanding-laziness">Understanding laziness</a><ul>
<li><a class="reference internal" href="#laziness-in-django">Laziness in Django</a></li>
</ul>
</li>
<li><a class="reference internal" href="#databases">Databases</a><ul>
<li><a class="reference internal" href="#database-optimization"><code class="docutils literal"><span class="pre">Database</span> <span class="pre">optimization</span></code></a></li>
<li><a class="reference internal" href="#other-database-related-tips">Other database-related tips</a></li>
</ul>
</li>
<li><a class="reference internal" href="#http-performance">HTTP performance</a><ul>
<li><a class="reference internal" href="#middleware">Middleware</a><ul>
<li><a class="reference internal" href="#conditionalgetmiddleware"><code class="docutils literal"><span class="pre">ConditionalGetMiddleware</span></code></a></li>
<li><a class="reference internal" href="#gzipmiddleware"><code class="docutils literal"><span class="pre">GZipMiddleware</span></code></a></li>
</ul>
</li>
<li><a class="reference internal" href="#sessions">Sessions</a><ul>
<li><a class="reference internal" href="#using-cached-sessions">Using cached sessions</a></li>
</ul>
</li>
<li><a class="reference internal" href="#static-files">Static files</a><ul>
<li><a class="reference internal" href="#cachedstaticfilesstorage"><code class="docutils literal"><span class="pre">CachedStaticFilesStorage</span></code></a></li>
<li><a class="reference internal" href="#minification">“Minification”</a></li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#template-performance">Template performance</a><ul>
<li><a class="reference internal" href="#the-cached-template-loader">The cached template loader</a></li>
</ul>
</li>
<li><a class="reference internal" href="#using-different-versions-of-available-software">Using different versions of available software</a><ul>
<li><a class="reference internal" href="#newer-is-often-but-not-always-better">Newer is often - but not always - better</a></li>
<li><a class="reference internal" href="#alternatives-to-django-s-template-language">Alternatives to Django’s template language</a></li>
<li><a class="reference internal" href="#alternative-software-implementations">Alternative software implementations</a><ul>
<li><a class="reference internal" href="#id1">PyPy</a></li>
<li><a class="reference internal" href="#c-implementations-of-python-libraries">C implementations of Python libraries</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
</ul>
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<ul><li><a href="index.html">Using Django</a>
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<p class="topless">Feb 12, 2019</p>
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