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Bumped reqs in docs for content extraction bits.
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README.rst

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@@ -3,7 +3,7 @@ Haystack
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========
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:author: Daniel Lindsley
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:date: 2011/05/02
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:date: 2011/09/18
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Haystack provides modular search for Django. It features a unified, familiar
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API that allows you to plug in different search backends (such as Solr_,

docs/installing_search_engines.rst

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@@ -20,12 +20,12 @@ Haystack requires Solr 1.3+. Installation is relatively simple::
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java -jar start.jar
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You'll need to revise your schema. You can generate this from your application
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(once Haystack is installed and setup) by running
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(once Haystack is installed and setup) by running
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``./manage.py build_solr_schema``. Take the output from that command and place
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it in ``apache-solr-1.4.1/example/solr/conf/schema.xml``. Then restart Solr.
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You'll also need a Solr binding, ``pysolr``. The official ``pysolr`` package,
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distributed via PyPI, is the best version to use (2.0.13+). Place ``pysolr.py``
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distributed via PyPI, is the best version to use (2.1.0+). Place ``pysolr.py``
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somewhere on your ``PYTHONPATH``.
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.. note::
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text = indexes.CharField(document=True, use_template=True)
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# ... normal fields then...
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suggestions = indexes.CharField()
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def prepare(self, obj):
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prepared_data = super(NoteIndex, self).prepare(object)
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prepared_data['suggestions'] = prepared_data['text']
@@ -128,15 +128,15 @@ package for it). Installation looks like::
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curl -O http://oligarchy.co.uk/xapian/1.0.11/xapian-core-1.0.11.tar.gz
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curl -O http://oligarchy.co.uk/xapian/1.0.11/xapian-bindings-1.0.11.tar.gz
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tar xvzf xapian-core-1.0.11.tar.gz
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tar xvzf xapian-bindings-1.0.11.tar.gz
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cd xapian-core-1.0.11
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./configure
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make
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sudo make install
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cd ..
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cd xapian-bindings-1.0.11
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./configure
@@ -149,4 +149,4 @@ proper due to licensing. To use it, you need both Haystack itself as well as
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http://github.com/notanumber/xapian-haystack/tree/master. Installation
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instructions can be found on that page as well. The backend, written
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by David Sauve (notanumber), fully implements the `SearchQuerySet` API and is
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an excellent alternative to Solr.
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an excellent alternative to Solr.

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