Addressed inaccuracies in performance docs
* Move the discussion of CachedStaticFilesStorage to the section about HTTP. It's really about client-side caching. It doesn't fit with the caching utilities from django.utils.functional. * Tone down the warning against Pypy as per Alex' feedback. It's a valid choice for advanced users who are comfortable using a non-standard stack. * Generally reworded the 'Using different versions of available software' section. * Some other minor adjustments to the document.
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@ -150,8 +150,8 @@ so there can be huge benefit in saving the value to a quickly accessible cache,
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ready for the next time it's required.
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It's a sufficiently significant and powerful technique that Django includes a
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comprehensive caching framework, as well as numerous other opportunities to
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make use of caching.
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comprehensive caching framework, as well as other smaller pieces of caching
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functionality.
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:doc:`The caching framework </topics/cache>`
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--------------------------------------------
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@ -168,14 +168,8 @@ Implementing caching should not be regarded as an alternative to improving code
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that's performing poorly because it has been written badly. It's one of the
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final steps towards producing well-performing code, not a shortcut.
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Other opportunities for caching
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-------------------------------
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Beyond the caching framework, Django offers other smaller pieces of caching
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functionality.
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:class:`~django.utils.functional.cached_property`
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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-------------------------------------------------
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It's common to have to call a class instances's method more than once. If
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that function is expensive, then doing so can be wasteful.
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@ -186,14 +180,8 @@ the saved value rather than re-computing it. Note that this only works on
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methods that take ``self`` as their only argument and that it changes the
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method to a property.
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:class:`~django.contrib.staticfiles.storage.CachedStaticFilesStorage`
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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:class:`~django.contrib.staticfiles.storage.CachedStaticFilesStorage` appends a
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content-dependent tag to the filenames of :doc:`static files
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</ref/contrib/staticfiles>` to make it safe for browsers to cache them
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long-term without missing future changes - when a file changes, so will the
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tag, so browsers will reload the asset automatically.
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Certain Django components also have their own caching functionality; these are
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discussed below in the sections related to those components.
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Understanding laziness
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======================
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@ -284,11 +272,31 @@ time. Note that GZipMiddleware is currently considered a security risk, and is
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vulnerable to attacks that nullify the protection provided by TLS/SSL. See the
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warning in :class:`~django.middleware.gzip.GZipMiddleware` for more information.
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Third-party HTTP tools
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----------------------
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Static files
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------------
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There are numerous third-party Django tools and packages available, notably
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ones that are able to "minify" and compress HTML, CSS and JavaScript.
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Static files, which by defintion are not dynamic, make an excellent target for
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optimization gains.
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:class:`~django.contrib.staticfiles.storage.CachedStaticFilesStorage`
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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By taking advantage of web browsers' caching abilities, you can
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eliminate network hits entirely for a given file after the initial download.
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:class:`~django.contrib.staticfiles.storage.CachedStaticFilesStorage` appends a
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content-dependent tag to the filenames of :doc:`static files
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</ref/contrib/staticfiles>` to make it safe for browsers to cache them
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long-term without missing future changes - when a file changes, so will the
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tag, so browsers will reload the asset automatically.
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"Minification"
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^^^^^^^^^^^^^^
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Several third-party Django tools and packages provide the ability to "minify"
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HTML, CSS, and JavaScript. They remove uneccessary whitespace, newlines, and
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comments, and shorten variable names, and thus reduce the size of the documents
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that your site publishes.
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Template performance
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====================
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@ -313,13 +321,19 @@ Using different versions of available software
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It can sometimes be worth checking whether different and better-performing
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versions of the software that you're using are available.
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This may be helpful, but is unlikely to solve a serious performance problem.
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You won't usually gain performance advantages that are better than marginal.
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These techniques are targeted at more advanced users who want to push the
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boundaries of performance of an already well-optimized Django site.
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However, they are not magic solutions to performance problems, and they're
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unlikely to bring better than marginal gains to sites that don't already do the
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more basic things the right way.
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.. note::
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It's worth repeating: **reaching for alternatives to software you're
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already using is very rarely the answer to performance problems**.
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already using is never the first answer to performance problems**. When
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you reach this level of optimization, you need a formal benchmarking
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solution.
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Newer is often - but not always - better
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----------------------------------------
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@ -369,16 +383,36 @@ templating language.
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Alternative software implementations
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------------------------------------
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It *may* be worth checking whether Python software you're using has been
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It may be worth checking whether Python software you're using has been
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provided in a different implementation that can execute the same code faster.
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However, most Django performance problems in well-written code are typically
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not to be found at the Python execution level, but rather in inefficient
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database querying, caching, and templates (and if you're relying on
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poorly-written Python code, your performance problems are very unlikely to be
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solved by having it execute faster).
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However: most performance problems in well-written Django sites aren't at the
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Python execution level, but rather in inefficient database querying, caching,
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and templates. If you're relying on poorly-written Python code, your
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performance problems are unlikely to be solved by having it execute faster.
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Avoid using C implementations of Python libraries or non-standard Python
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implementations like `PyPy <http://pypy.org/>`_ in search of performance gains,
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unless you are sure they are appropriate for your application. Any gains are
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likely to be small, and compatibility issues are common.
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Using an alternative implementation may introduce compatibility, deployment,
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portability, or maintenance issues. It goes without saying that before adopting
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a non-standard implementation you should ensure it provides sufficient
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performance gains for your application to outweigh the potential risks.
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With these caveats in mind, you should be aware of:
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`PyPy <http://pypy.org/>`_
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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`PyPy <http://pypy.org/>`_ is an implementation of Python in Python itself (the
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'standard' Python implementation is in C). PyPy can offer substantial
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performance gains, typically for heavyweight applications.
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A key aim of the PyPy project is `compatibility
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<http:://pypy.org/compat.html>`_ with existing Python APIs and libraries.
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Django is compatible, but you will need to check the compatibility of other
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libraries you rely on.
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C implementations of Python libraries
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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Some Python libraries are also implemented in C, and can be much faster. They
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aim to offer the same APIs. Note that compatibility issues and behaviour
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differences are not unknown (and not always immediately evident).
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