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moving the location of learning checklist for task queues
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‎feeds/all.atom.xml‎

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<?xml version="1.0" encoding="utf-8"?>
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<feed xmlns="http://www.w3.org/2005/Atom"><title>Matt Makai</title><link href="http://www.fullstackpython.com/" rel="alternate"></link><link href="http://www.fullstackpython.com/feeds/all.atom.xml" rel="self"></link><id>http://www.fullstackpython.com/</id><updated>2014-05-10T14:50:02Z</updated></feed>
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<feed xmlns="http://www.w3.org/2005/Atom"><title>Matt Makai</title><link href="http://www.fullstackpython.com/" rel="alternate"></link><link href="http://www.fullstackpython.com/feeds/all.atom.xml" rel="self"></link><id>http://www.fullstackpython.com/</id><updated>2014-05-10T18:08:45Z</updated></feed>

‎source/content/pages/07-performance/0705-task-queues.markdown‎

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* scheduling periodic jobs such as batch processes
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## Task queues learning checklist
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<i class="fa fa-check-square-o"></i>
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Pick a slow function in your project that is called during an HTTP request.
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<i class="fa fa-check-square-o"></i>
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Determine if you can precompute the results on a fixed interval instead of
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during the HTTP request. If so, create a separate function you can call
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from elsewhere then store the precomputed value in the database.
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<i class="fa fa-check-square-o"></i>
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Read the Celery documentation and the links in the resources section below
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to understand how the project works.
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<i class="fa fa-check-square-o"></i>
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Install a message broker such as RabbitMQ or Redis and then add Celery to your
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project. Configure Celery to work with the installed message broker.
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<i class="fa fa-check-square-o"></i>
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Use Celery to invoke the function from step one on a regular basis.
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<i class="fa fa-check-square-o"></i>
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Have the HTTP request function use the precomputed value instead of the
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slow running code it originally relied upon.
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## Task queue projects
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The defacto standard Python task queue is Celery. The other task queue
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projects that arise tend to come from the perspective that Celery is overly
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RabbitMQ installed and configured. This service is an option if you are
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using RabbitMQ and do not want to maintain RabbitMQ installations on your
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own servers.
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## Task queues learning checklist
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<i class="fa fa-check-square-o"></i>
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Pick a slow function in your project that is called during an HTTP request.
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<i class="fa fa-check-square-o"></i>
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Determine if you can precompute the results on a fixed interval instead of
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during the HTTP request. If so, create a separate function you can call
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from elsewhere then store the precomputed value in the database.
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<i class="fa fa-check-square-o"></i>
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Read the Celery documentation and the links in the resources section below
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to understand how the project works.
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<i class="fa fa-check-square-o"></i>
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Install a message broker such as RabbitMQ or Redis and then add Celery to your
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project. Configure Celery to work with the installed message broker.
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<i class="fa fa-check-square-o"></i>
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Use Celery to invoke the function from step one on a regular basis.
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<i class="fa fa-check-square-o"></i>
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Have the HTTP request function use the precomputed value instead of the
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slow running code it originally relied upon.
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## Task queue resources
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* [Distributing work without Celery](http://justcramer.com/2012/05/04/distributing-work-without-celery/)

‎task-queues.html‎

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<p>scheduling periodic jobs such as batch processes</p>
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</li>
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</ul>
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<h2>Task queues learning checklist</h2>
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<p><i class="fa fa-check-square-o"></i>
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Pick a slow function in your project that is called during an HTTP request.</p>
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<p><i class="fa fa-check-square-o"></i>
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Determine if you can precompute the results on a fixed interval instead of
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during the HTTP request. If so, create a separate function you can call
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from elsewhere then store the precomputed value in the database.</p>
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<p><i class="fa fa-check-square-o"></i>
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Read the Celery documentation and the links in the resources section below
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to understand how the project works.</p>
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<p><i class="fa fa-check-square-o"></i>
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Install a message broker such as RabbitMQ or Redis and then add Celery to your
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project. Configure Celery to work with the installed message broker.</p>
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<p><i class="fa fa-check-square-o"></i>
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Use Celery to invoke the function from step one on a regular basis.</p>
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<p><i class="fa fa-check-square-o"></i>
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Have the HTTP request function use the precomputed value instead of the
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slow running code it originally relied upon.</p>
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<h2>Task queue projects</h2>
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<p>The defacto standard Python task queue is Celery. The other task queue
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projects that arise tend to come from the perspective that Celery is overly
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own servers.</p>
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</li>
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</ul>
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<h2>Task queues learning checklist</h2>
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<p><i class="fa fa-check-square-o"></i>
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Pick a slow function in your project that is called during an HTTP request.</p>
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<p><i class="fa fa-check-square-o"></i>
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Determine if you can precompute the results on a fixed interval instead of
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during the HTTP request. If so, create a separate function you can call
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from elsewhere then store the precomputed value in the database.</p>
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<p><i class="fa fa-check-square-o"></i>
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Read the Celery documentation and the links in the resources section below
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to understand how the project works.</p>
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<p><i class="fa fa-check-square-o"></i>
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Install a message broker such as RabbitMQ or Redis and then add Celery to your
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project. Configure Celery to work with the installed message broker.</p>
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<p><i class="fa fa-check-square-o"></i>
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Use Celery to invoke the function from step one on a regular basis.</p>
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<p><i class="fa fa-check-square-o"></i>
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Have the HTTP request function use the precomputed value instead of the
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slow running code it originally relied upon.</p>
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<h2>Task queue resources</h2>
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<ul>
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<li>

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