This is a fork of Greg's gist, which allows use of character folding with haystack and whoosh. What I've done was to add allow EdgeNGram fields to be folded. This is useful if you're using autocomplete or just indexing text as EdgeNGram field to allow partial keywork search. Thanks, Greg. Have fun.

search_backends.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
This is a fork of Greg's gist, which allows use of character folding with haystack and whoosh. What
I've done was to add allow EdgeNGram fields to be folded. This is useful if you're using autocomplete
or just indexing text as EdgeNGram field to allow partial keywork search. Thanks, Greg. Have fun.

-+- original comments -+
https://gist.github.com/gregplaysguitar/1727204

Whoosh backend for haystack that implements character folding, as per http://packages.python.org/Whoosh/stemming.html#character-folding .

To use, put this file on your path and add it to your haystack settings, eg.

    HAYSTACK_CONNECTIONS = {
        'default': {
            'ENGINE': 'search_backends.FoldingWhooshEngine',
            'PATH': 'path-to-whoosh-index',
        },
    }

"""


from haystack.backends.whoosh_backend import WhooshEngine, WhooshSearchBackend, WHOOSH_ID, ID, DJANGO_CT, DJANGO_ID, Schema, IDLIST, TEXT, KEYWORD, NUMERIC, BOOLEAN, DATETIME, NGRAM, NGRAMWORDS, WhooshSearchQuery
from haystack.exceptions import SearchBackendError

from whoosh.analysis import CharsetFilter, StemmingAnalyzer
from whoosh.support.charset import accent_map


class FoldingWhooshSearchBackend(WhooshSearchBackend):

    def build_schema(self, fields):
        schema_fields = {
            ID: WHOOSH_ID(stored=True, unique=True),
            DJANGO_CT: WHOOSH_ID(stored=True),
            DJANGO_ID: WHOOSH_ID(stored=True),
            }
        # Grab the number of keys that are hard-coded into Haystack.
        # We'll use this to (possibly) fail slightly more gracefully later.
        initial_key_count = len(schema_fields)
        content_field_name = ''

        filter = CharsetFilter(accent_map)
        analyzer = StemmingAnalyzer() | filter

        for field_name, field_class in fields.items():
            if field_class.is_multivalued:
                if field_class.indexed is False:
                    schema_fields[field_class.index_fieldname] = IDLIST(stored=True, field_boost=field_class.boost)
                else:
                    schema_fields[field_class.index_fieldname] = KEYWORD(stored=True, commas=True, scorable=True, field_boost=field_class.boost)
            elif field_class.field_type in ['date', 'datetime']:
                schema_fields[field_class.index_fieldname] = DATETIME(stored=field_class.stored)
            elif field_class.field_type == 'integer':
                schema_fields[field_class.index_fieldname] = NUMERIC(stored=field_class.stored, type=int, field_boost=field_class.boost)
            elif field_class.field_type == 'float':
                schema_fields[field_class.index_fieldname] = NUMERIC(stored=field_class.stored, type=float, field_boost=field_class.boost)
            elif field_class.field_type == 'boolean':
                # Field boost isn't supported on BOOLEAN as of 1.8.2.
                schema_fields[field_class.index_fieldname] = BOOLEAN(stored=field_class.stored)
            elif field_class.field_type == 'ngram':
                schema_fields[field_class.index_fieldname] = NGRAM(minsize=3, analyzer=analyzer, maxsize=15, stored=field_class.stored, field_boost=field_class.boost)
            elif field_class.field_type == 'edge_ngram':
                schema_fields[field_class.index_fieldname] = NGRAMWORDS(minsize=2, maxsize=15, at='start', stored=field_class.stored, field_boost=field_class.boost)
                schema_fields[field_class.index_fieldname].analyzer |= filter
            else:
                schema_fields[field_class.index_fieldname] = TEXT(stored=True, analyzer=analyzer, field_boost=field_class.boost)

            if field_class.document is True:
                content_field_name = field_class.index_fieldname

        # Fail more gracefully than relying on the backend to die if no fields
        # are found.
        if len(schema_fields) <= initial_key_count:
            raise SearchBackendError("No fields were found in any search_indexes. Please correct this before attempting to search.")

        return (content_field_name, Schema(**schema_fields))


class FoldingWhooshEngine(WhooshEngine):
    backend = FoldingWhooshSearchBackend