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Django Kindle
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This is a simple app to help a newspaper website feed daily print-edition
stories to Amazon for a Kindle edition. This is the app we use in production
at Spokesman.com, with minor changes to obfuscate security-related things.

You probably won't be able to just drop this in place and go, unless you were
crazy enough to match the Story and Section structure that we use in the CMS
underneath Spokesman.com. But again, it's a really simple app -- it should be
easy to tweak the views and templates to match your CMS.


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A Little Intro
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Amazon wants Kindle editions to match the format of your print newspaper as
closely as possible. They want a Front Page section, a News section, a Sports
section, and so on, containing every story you published in print, and ONLY
those stories. No breaking news posted online, etc.

To do this, you'll need a way to:

* Provide a list of sections, mapping to your print edition's sections,
  that contained stories on a given pubdate.

* Provide a list of that day's stories within each of those sections.

* Provide article detail pages suitable for ingestion by Amazon's
  automated process. These should include references to image files
  associated with the story.

This app should provide a good head start; with a little customization you'll
have a perfectly Kindle-friendly story feed.


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Views
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These are named to match Amazon's terminology, for ease of communication.
Model and field names are obviously specific to our platform. Our CMS is
called Cannonball; I've left in those references to (hopefully) make it
obvious where changes will be required.

More explanation is provided with each view in views.py. Here's an overview:

* kindle_section_manifest: Fetches all sections that contain stories published
  in the print edition for a given pubdate. If no pubdate is provided via URL,
  the default is today's date.

* kindle_article_manifest: Fetches all stories within a section of the print
  edition, published on a given pubdate.
  
* kindle_article_detail: Returns an individual print-edition story for
  ingestion by Amazon.


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Templates
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These templates are also named to match Amazon's terminology, for ease of
communication. Again, field references and relationships match our models,
so you'll need to change where appropriate.

The formatting, however, exactly matches Amazon's preferred method of delivery.
After this app went into production at The Spokesman-Review, the Kindle team
asked to use our feed as an example for other papers working through the
integration process. We've never had a bit of trouble with the mechanics.

If you stick with this app's URL setup and template structure, you should
end up with a pretty bulletproof Kindle feed.

* kindle_section_manifest.xml: (RSS 2.0 format) Lists all sections that
  contain stories published in the print edition for a given pubdate. Amazon
  also wants the Kindle edition to provide a "Front Page" section; a link
  to the corresponding article_manifest is hard-coded into this template.

* kindle_article_manifest.xml: (RSS 2.0 format) Lists all stories within
  a section of the print edition, published on a given pubdate.

* kindle_article_file.xml: (NITF format) Displays an individual print-edition
  story for ingestion by Amazon. This template also contains references to
  images associated with the story.


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Notes
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* The urls.py in this app makes it possible to fetch a section_manifest
  for any date in your database. In practice, Amazon should only ever
  need stories from the *current* date, but this is built in, just in case.
  If you don't want to expose your entire archive, you can modify this, or 
  just use the allowed_timeframe variable in views.py.
  
* For security reasons, you may want to limit access to this XML feed. The
  utils in this app offer an IP-based method; to enable this you'll need
  a list of IP addresses from Amazon. Add them to APPROVED_IPS in
  utils.ip_whitelist, then add an ip_in_whitelist check to each view.
  
* Amazon fetches stories for the Kindle edition early each morning, so
  naturally you'll need some sort of overnight system to get print-edition
  stories into your web CMS.
  
* If something fails, you can alert Amazon to delay the ingestion of your
  story feed. We use a cron job to count the number of stories for the day,
  and fire off an email to Amazon (and our web team) if something looks wrong.