xapian-haystack/xapian_backend.py

# Copyright (C) 2009 David Sauve, Trapeze

__author__ = 'David Sauve'
__version__ = (2, 0, 0, 'alpha')

import time
import datetime
import cPickle as pickle
import os
import re
import shutil
import sys
import warnings

from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from django.utils.encoding import smart_unicode, force_unicode

from haystack.backends import BaseSearchBackend, BaseSearchQuery, SearchNode, log_query
from haystack.exceptions import MissingDependency
from haystack.fields import DateField, DateTimeField, IntegerField, FloatField, BooleanField, MultiValueField
from haystack.models import SearchResult
from haystack.utils import get_identifier

try:
    import xapian
except ImportError:
    raise MissingDependency("The 'xapian' backend requires the installation of 'xapian'. Please refer to the documentation.")


DOCUMENT_ID_TERM_PREFIX = 'Q'
DOCUMENT_CUSTOM_TERM_PREFIX = 'X'
DOCUMENT_CT_TERM_PREFIX = DOCUMENT_CUSTOM_TERM_PREFIX + 'CONTENTTYPE'


class XHExpandDecider(xapian.ExpandDecider):
    def __call__(self, term):
        """
        Return True if the term should be used for expanding the search
        query, False otherwise.
        
        Currently, we only want to ignore terms beginning with `DOCUMENT_CT_TERM_PREFIX`
        """
        if term.startswith(DOCUMENT_CT_TERM_PREFIX):
            return False
        return True


class SearchBackend(BaseSearchBackend):
    """
    `SearchBackend` defines the Xapian search backend for use with the Haystack
    API for Django search.
    
    It uses the Xapian Python bindings to interface with Xapian, and as
    such is subject to this bug: <http://trac.xapian.org/ticket/364> when
    Django is running with mod_python or mod_wsgi under Apache.
    
    Until this issue has been fixed by Xapian, it is neccessary to set
    `WSGIApplicationGroup to %{GLOBAL}` when using mod_wsgi, or
    `PythonInterpreter main_interpreter` when using mod_python.
    
    In order to use this backend, `HAYSTACK_XAPIAN_PATH` must be set in
    your settings.  This should point to a location where you would your
    indexes to reside.
    """
    def __init__(self, site=None, language='english'):
        """
        Instantiates an instance of `SearchBackend`.
        
        Optional arguments:
            `site` -- The site to associate the backend with (default = None)
            `stemming_language` -- The stemming language (default = 'english')
        
        Also sets the stemming language to be used to `stemming_language`.
        """
        super(SearchBackend, self).__init__(site)
        
        if not hasattr(settings, 'HAYSTACK_XAPIAN_PATH'):
            raise ImproperlyConfigured('You must specify a HAYSTACK_XAPIAN_PATH in your settings.')
        
        if not os.path.exists(settings.HAYSTACK_XAPIAN_PATH):
            os.makedirs(settings.HAYSTACK_XAPIAN_PATH)
        
        self.language = language
    
    def update(self, index, iterable):
        """
        Updates the `index` with any objects in `iterable` by adding/updating
        the database as needed.
        
        Required arguments:
            `index` -- The `SearchIndex` to process
            `iterable` -- An iterable of model instances to index
        
        For each object in `iterable`, a document is created containing all
        of the terms extracted from `index.prepare(obj)` with stemming prefixes,
        field prefixes, and 'as-is'.
        
        eg. `content:Testing` ==> `testing, Ztest, ZXCONTENTtest`
        
        Each document also contains an extra term in the format:
        
        `XCONTENTTYPE<app_name>.<model_name>`
        
        As well as a unique identifier in the the format:
        
        `Q<app_name>.<model_name>.<pk>`
        
        eg.: foo.bar (pk=1) ==> `Qfoo.bar.1`, `XCONTENTTYPEfoo.bar`
        
        This is useful for querying for a specific document corresponding to
        a model instance.
        
        The document also contains a pickled version of the object itself and
        the document ID in the document data field.
        
        Finally, we also store field values to be used for sorting data.  We
        store these in the document value slots (position zero is reserver
        for the document ID).  All values are stored as unicode strings with
        conversion of float, int, double, values being done by Xapian itself
        through the use of the :method:xapian.sortable_serialise method.
        """
        database = self._database(writable=True)
        try:
            for obj in iterable:
                document = xapian.Document()

                term_generator = xapian.TermGenerator()
                term_generator.set_database(database)
                term_generator.set_stemmer(xapian.Stem(self.language))
                if getattr(settings, 'HAYSTACK_INCLUDE_SPELLING', False) is True:
                    term_generator.set_flags(xapian.TermGenerator.FLAG_SPELLING)
                term_generator.set_document(document)

                document_id = DOCUMENT_ID_TERM_PREFIX + get_identifier(obj)
                data = index.prepare(obj)
                
                for field in self.schema:
                    if field['field_name'] in data.keys():
                        prefix = DOCUMENT_CUSTOM_TERM_PREFIX + field['field_name'].upper()
                        value = data[field['field_name']]
                        term_generator.index_text(force_unicode(value))
                        term_generator.index_text(force_unicode(value), 1, prefix)
                        document.add_value(field['column'], _marshal_value(value))
                
                document.set_data(pickle.dumps(
                    (obj._meta.app_label, obj._meta.module_name, obj.pk, data),
                    pickle.HIGHEST_PROTOCOL
                ))
                document.add_term(document_id)
                document.add_term(
                    DOCUMENT_CT_TERM_PREFIX + u'%s.%s' %
                    (obj._meta.app_label, obj._meta.module_name)
                )
                database.replace_document(document_id, document)
        
        except UnicodeDecodeError:
            sys.stderr.write('Chunk failed.\n')
            pass
    
    def remove(self, obj):
        """
        Remove indexes for `obj` from the database.
        
        We delete all instances of `Q<app_name>.<model_name>.<pk>` which
        should be unique to this object.
        """
        database = self._database(writable=True)
        database.delete_document(DOCUMENT_ID_TERM_PREFIX + get_identifier(obj))
    
    def clear(self, models=[]):
        """
        Clear all instances of `models` from the database or all models, if
        not specified.
        
        Optional Arguments:
            `models` -- Models to clear from the database (default = [])
        
        If `models` is empty, an empty query is executed which matches all
        documents in the database.  Afterwards, each match is deleted.
        
        Otherwise, for each model, a `delete_document` call is issued with
        the term `XCONTENTTYPE<app_name>.<model_name>`.  This will delete
        all documents with the specified model type.
        """
        database = self._database(writable=True)
        if not models:
            query = xapian.Query('')
            enquire = xapian.Enquire(database)
            enquire.set_query(query)
            for match in enquire.get_mset(0, database.get_doccount()):
                database.delete_document(match.docid)
        else:
            for model in models:
                database.delete_document(
                    DOCUMENT_CT_TERM_PREFIX + '%s.%s' %
                    (model._meta.app_label, model._meta.module_name)
                )
    @log_query
    def search(self, query, sort_by=None, start_offset=0, end_offset=None,
               fields='', highlight=False, facets=None, date_facets=None,
               query_facets=None, narrow_queries=None, spelling_query=None,
               limit_to_registered_models=True, **kwargs):
        """
        Executes the search as defined in `query_string`.
        
        Required arguments:
            `query` -- Search query to execute
        
        Optional arguments:
            `sort_by` -- Sort results by specified field (default = None)
            `start_offset` -- Slice results from `start_offset` (default = 0)
            `end_offset` -- Slice results at `end_offset` (default = None), if None, then all documents
            `fields` -- Filter results on `fields` (default = '')
            `highlight` -- Highlight terms in results (default = False)
            `facets` -- Facet results on fields (default = None)
            `date_facets` -- Facet results on date ranges (default = None)
            `query_facets` -- Facet results on queries (default = None)
            `narrow_queries` -- Narrow queries (default = None)
            `spelling_query` -- An optional query to execute spelling suggestion on
            `limit_to_registered_models` -- Limit returned results to models registered in the current `SearchSite` (default = True)
            
        Returns:
            A dictionary with the following keys:
                `results` -- A list of `SearchResult`
                `hits` -- The total available results
                `facets` - A dictionary of facets with the following keys:
                    `fields` -- A list of field facets
                    `dates` -- A list of date facets
                    `queries` -- A list of query facets
            If faceting was not used, the `facets` key will not be present
        
        If `query_string` is empty, returns no results.
        
        Otherwise, loads the available fields from the database meta data schema
        and sets up prefixes for each one along with a prefix for `django_ct`,
        used to filter by model, and loads the current stemmer instance.
        
        Afterwards, executes the Xapian query parser to create a query from
        `query_string` that is then passed to a new `enquire` instance.
        
        The resulting match set is passed to :method:`_process_results` for
        further processing prior to returning a dictionary with the results.
        
        If `HAYSTACK_INCLUDE_SPELLING` was enabled in `settings.py`, the
        extra flag `FLAG_SPELLING_CORRECTION` will be passed to the query parser
        and any suggestions for spell correction will be returned as well as
        the results.
        """
        if xapian.Query.empty(query):
            return {
                'results': [],
                'hits': 0,
            }
        
        # if limit_to_registered_models:
        #     if narrow_queries is None:
        #          narrow_queries = set()
        #     
        #     registered_models = self.build_registered_models_list()
        #     
        #     if len(registered_models) > 0:
        #         narrow_queries.add(
        #             ' '.join(['django_ct:%s' % model for model in registered_models])
        #         )
        
        database = self._database()
        
        # query, spelling_suggestion = self._query(
        #     database, query_string, narrow_queries, spelling_query
        # )
        spelling_suggestion = ''
        
        enquire = xapian.Enquire(database)
        enquire.set_query(query)
        
        if sort_by:
            sorter = xapian.MultiValueSorter()

            for sort_field in sort_by:
                if sort_field.startswith('-'):
                    reverse = True
                    sort_field = sort_field[1:] # Strip the '-'
                else:
                    reverse = False # Reverse is inverted in Xapian -- http://trac.xapian.org/ticket/311
                sorter.add(self._value_column(sort_field), reverse)

            enquire.set_sort_by_key_then_relevance(sorter, True)
        
        results = []
        facets_dict = {
            'fields': {},
            'dates': {},
            'queries': {},
        }
        
        if not end_offset:
            end_offset = database.get_doccount()
            
        matches = enquire.get_mset(start_offset, (end_offset - start_offset))
        
        for match in matches:
            app_label, module_name, pk, model_data = pickle.loads(match.document.get_data())
            if highlight and (len(query_string) > 0):
                model_data['highlighted'] = {
                    self.content_field_name: self._do_highlight(
                        model_data.get(self.content_field_name), query_string
                    )
                }
            results.append(
                SearchResult(app_label, module_name, pk, match.weight, **model_data)
            )
        
        if facets:
            facets_dict['fields'] = self._do_field_facets(results, facets)
        if date_facets:
            facets_dict['dates'] = self._do_date_facets(results, date_facets)
        if query_facets:
            facets_dict['queries'] = self._do_query_facets(results, query_facets)
        
        return {
            'results': results,
            'hits': matches.get_matches_estimated(),
            'facets': facets_dict,
            'spelling_suggestion': spelling_suggestion,
        }
    
    def more_like_this(self, model_instance, additional_query_string=None,
                       start_offset=0, end_offset=None, 
                       limit_to_registered_models=True, **kwargs):
        """
        Given a model instance, returns a result set of similar documents.
        
        Required arguments:
            `model_instance` -- The model instance to use as a basis for
                                retrieving similar documents.
        
        Optional arguments:
            `additional_query_string` -- An additional query string to narrow
                                         results
            `start_offset` -- The starting offset (default=0)
            `end_offset` -- The ending offset (default=None), if None, then all documents
            `limit_to_registered_models` -- Limit returned results to models registered in the current `SearchSite` (default = True)
        
        Returns:
            A dictionary with the following keys:
                `results` -- A list of `SearchResult`
                `hits` -- The total available results
        
        Opens a database connection, then builds a simple query using the
        `model_instance` to build the unique identifier.
        
        For each document retrieved(should always be one), adds an entry into
        an RSet (relevance set) with the document id, then, uses the RSet
        to query for an ESet (A set of terms that can be used to suggest
        expansions to the original query), omitting any document that was in
        the original query.
        
        Finally, processes the resulting matches and returns.
        """
        database = self._database()
        
        query = xapian.Query(DOCUMENT_ID_TERM_PREFIX + get_identifier(model_instance))

        enquire = xapian.Enquire(database)
        enquire.set_query(query)

        rset = xapian.RSet()
        
        if not end_offset:
            end_offset = database.get_doccount()
            
        for match in enquire.get_mset(0, end_offset):
            rset.add_document(match.docid)
            
        query = xapian.Query(xapian.Query.OP_OR,
            [expand.term for expand in enquire.get_eset(match.document.termlist_count(), rset, XHExpandDecider())]
        )
        query = xapian.Query(
            xapian.Query.OP_AND_NOT, [query, DOCUMENT_ID_TERM_PREFIX + get_identifier(model_instance)]
        )
        narrow_queries = None
        if limit_to_registered_models:
            registered_models = self.build_registered_models_list()
            
            if len(registered_models) > 0:
                narrow_queries = set()
                narrow_queries.add(
                    ' '.join(['django_ct:%s' % model for model in registered_models])
                )
        if additional_query_string:
            additional_query, __unused__ = self._query(
                database, additional_query_string, narrow_queries
            )
            query = xapian.Query(
                xapian.Query.OP_AND, query, additional_query
            )

        enquire.set_query(query)
        
        results = []
        matches = enquire.get_mset(start_offset, end_offset)
        
        for match in matches:
            document = match.get_document()
            app_label, module_name, pk, model_data = pickle.loads(document.get_data())
            results.append(
                SearchResult(app_label, module_name, pk, match.weight, **model_data)
            )
        
        return {
            'results': results,
            'hits': matches.get_matches_estimated(),
            'facets': {
                'fields': {},
                'dates': {},
                'queries': {},
            },
            'spelling_suggestion': None,
        }
    
    def build_schema(self, fields):
        """
        Build the schema from fields.
        
        Required arguments:
            ``fields`` -- A list of fields in the index
        
        Returns a list of fields in dictionary format ready for inclusion in
        an indexed meta-data.
        """
        content_field_name = ''
        schema_fields = []
        column = 0
        
        for field_name, field_class in fields.items():
            if field_class.document is True:
                content_field_name = field_name
            
            if field_class.indexed is True:
                field_data = {
                    'field_name': field_name,
                    'type': 'text',
                    'multi_valued': 'false',
                    'column': column,
                }
                
                if isinstance(field_class, (DateField, DateTimeField)):
                    field_data['type'] = 'date'
                elif isinstance(field_class, IntegerField):
                    field_data['type'] = 'long'
                elif isinstance(field_class, FloatField):
                    field_data['type'] = 'float'
                elif isinstance(field_class, BooleanField):
                    field_data['type'] = 'boolean'
                elif isinstance(field_class, MultiValueField):
                    field_data['multi_valued'] = 'true'
                
                schema_fields.append(field_data)
                column += 1
        
        return (content_field_name, schema_fields)
    
    def _do_highlight(self, content, text, tag='em'):
        """
        Highlight `text` in `content` with html `tag`.
        
        This method assumes that the input text (`content`) does not contain
        any special formatting.  That is, it does not contain any html tags
        or similar markup that could be screwed up by the highlighting.
        
        Required arguments:
            `content` -- Content to search for instances of `text`
            `text` -- The text to be highlighted
        """
        for term in [term.replace('*', '') for term in text.split()]:
            if term not in self.RESERVED_WORDS:
                term_re = re.compile(re.escape(term), re.IGNORECASE)
                content = term_re.sub('<%s>%s</%s>' % (tag, term, tag), content)
        return content
    
    def _do_field_facets(self, results, field_facets):
        """
        Private method that facets a document by field name.
        
        Fields of type MultiValueField will be faceted on each item in the 
        (containing) list.
        
        Required arguments:
            `results` -- A list SearchResults to facet
            `field_facets` -- A list of fields to facet on
        """
        facet_dict = {}
        
        # DS_TODO: Improve this algorithm.  Currently, runs in O(N^3), ouch.
        for field in field_facets:
            facet_list = {}
            
            for result in results:
                field_value = getattr(result, field)
                if self._multi_value_field(field):
                    for item in field_value: # Facet each item in a MultiValueField
                        facet_list[item] = facet_list.get(item, 0) + 1
                else:
                    facet_list[field_value] = facet_list.get(field_value, 0) + 1
            
            facet_dict[field] = facet_list.items()
        
        return facet_dict
    
    def _do_date_facets(self, results, date_facets):
        """
        Private method that facets a document by date ranges
        
        Required arguments:
            `results` -- A list SearchResults to facet
            `date_facets` -- A dictionary containing facet parameters:
                {'field': {'start_date': ..., 'end_date': ...: 'gap_by': '...', 'gap_amount': n}}
                nb., gap must be one of the following:
                    year|month|day|hour|minute|second
        
        For each date facet field in `date_facets`, generates a list
        of date ranges (from `start_date` to `end_date` by `gap_by`) then
        iterates through `results` and tallies the count for each date_facet.
        
        Returns a dictionary of date facets (fields) containing a list with
        entries for each range and a count of documents matching the range.
        
        eg. {
            'pub_date': [
                ('2009-01-01T00:00:00Z', 5),
                ('2009-02-01T00:00:00Z', 0),
                ('2009-03-01T00:00:00Z', 0),
                ('2009-04-01T00:00:00Z', 1),
                ('2009-05-01T00:00:00Z', 2),
            ],
        }
        """
        facet_dict = {}
        
        for date_facet, facet_params in date_facets.iteritems():
            gap_type = facet_params.get('gap_by')
            gap_value = facet_params.get('gap_amount', 1)
            date_range = facet_params['start_date']
            facet_list = []
            while date_range < facet_params['end_date']:
                facet_list.append((date_range.isoformat(), 0))
                if gap_type == 'year':
                    date_range = date_range.replace(
                        year=date_range.year + int(gap_value)
                    )
                elif gap_type == 'month':
                    if date_range.month == 12:
                        date_range = date_range.replace(
                            month=1, year=date_range.year + int(gap_value)
                        )
                    else:
                        date_range = date_range.replace(
                            month=date_range.month + int(gap_value)
                        )
                elif gap_type == 'day':
                    date_range += datetime.timedelta(days=int(gap_value))
                elif gap_type == 'hour':
                    date_range += datetime.timedelta(hours=int(gap_value))
                elif gap_type == 'minute':
                    date_range += datetime.timedelta(minutes=int(gap_value))
                elif gap_type == 'second':
                    date_range += datetime.timedelta(seconds=int(gap_value))
            
            facet_list = sorted(facet_list, key=lambda n:n[0], reverse=True)
            
            for result in results:
                result_date = getattr(result, date_facet)
                if result_date:
                    if not isinstance(result_date, datetime.datetime):
                        result_date = datetime.datetime(
                            year=result_date.year,
                            month=result_date.month,
                            day=result_date.day,
                        )
                    for n, facet_date in enumerate(facet_list):
                        if result_date > datetime.datetime(*(time.strptime(facet_date[0], '%Y-%m-%dT%H:%M:%S')[0:6])):
                            facet_list[n] = (facet_list[n][0], (facet_list[n][1] + 1))
                            break
            
            facet_dict[date_facet] = facet_list
        
        return facet_dict
    
    def _do_query_facets(self, results, query_facets):
        """
        Private method that facets a document by query
        
        Required arguments:
            `results` -- A list SearchResults to facet
            `query_facets` -- A dictionary containing facet parameters:
                {'field': 'query', [...]}
        
        For each query in `query_facets`, generates a dictionary entry with
        the field name as the key and a tuple with the query and result count
        as the value.
        
        eg. {'name': ('a*', 5)}
        """
        facet_dict = {}
        
        for field, query in query_facets.iteritems():
            facet_dict[field] = (query, self.search(query)['hits'])
        
        return facet_dict
    
    def _database(self, writable=False):
        """
        Private method that returns a xapian.Database for use and sets up
        schema and content_field definitions.
        
        Optional arguments:
            ``writable`` -- Open the database in read/write mode (default=False)
        
        Returns an instance of a xapian.Database or xapian.WritableDatabase
        """
        if writable:
            self.content_field_name, self.schema = self.build_schema(self.site.all_searchfields())
            
            database = xapian.WritableDatabase(settings.HAYSTACK_XAPIAN_PATH, xapian.DB_CREATE_OR_OPEN)
            database.set_metadata('schema', pickle.dumps(self.schema, pickle.HIGHEST_PROTOCOL))
            database.set_metadata('content', pickle.dumps(self.content_field_name, pickle.HIGHEST_PROTOCOL))
        else:
            database = xapian.Database(settings.HAYSTACK_XAPIAN_PATH)
                
            self.schema = pickle.loads(database.get_metadata('schema'))
            self.content_field_name = pickle.loads(database.get_metadata('content'))
        
        return database
        
    def _value_column(self, field):
        """
        Private method that returns the column value slot in the database
        for a given field.
        
        Required arguemnts:
            `field` -- The field to lookup
        
        Returns an integer with the column location (0 indexed).
        """
        for field_dict in self.schema:
            if field_dict['field_name'] == field:
                return field_dict['column']
        return 0

    def _multi_value_field(self, field):
        """
        Private method that returns `True` if a field is multi-valued, else
        `False`.
        
        Required arguemnts:
            `field` -- The field to lookup
        
        Returns a boolean value indicating whether the field is multi-valued.
        """
        for field_dict in self.schema:
            if field_dict['field_name'] == field:
                return field_dict['multi_valued'] == 'true'
        return False


class SearchQuery(BaseSearchQuery):
    """
    This class is the Xapian specific version of the SearchQuery class.
    It acts as an intermediary between the ``SearchQuerySet`` and the
    ``SearchBackend`` itself.
    """
    def __init__(self, backend=None):
        """
        Create a new instance of the SearchQuery setting the backend as
        specified.  If no backend is set, will use the Xapian `SearchBackend`.
        
        Optional arguments:
            ``backend`` -- The ``SearchBackend`` to use (default = None)
        """
        super(SearchQuery, self).__init__(backend=backend)
        self.backend = backend or SearchBackend()
    
    def build_query(self):
        # DS_TODO: How does stemming work with this new refactor?
        
        if not self.query_filter:
            query = xapian.Query('')
        else:
            query = self._query_from_search_node(self.query_filter)

        if self.models:
            subqueries = [
                xapian.Query(
                    xapian.Query.OP_SCALE_WEIGHT, xapian.Query('%s%s.%s' % (
                            DOCUMENT_CT_TERM_PREFIX, 
                            model._meta.app_label, model._meta.module_name
                        )
                    ), 0 # Pure boolean sub-query
                ) for model in self.models
            ]
            query = xapian.Query(
                xapian.Query.OP_AND, query,
                xapian.Query(xapian.Query.OP_OR, subqueries)
            )

        if self.boost:
            subqueries = [
                xapian.Query(
                    xapian.Query.OP_SCALE_WEIGHT, xapian.Query(term), value
                ) for term, value in self.boost.iteritems()
            ]
            query = xapian.Query(
                xapian.Query.OP_OR, query,
                xapian.Query(xapian.Query.OP_AND, subqueries)
            )
        
        return query

    def _query_from_search_node(self, search_node, is_not=False):
        query_list = []
        
        for child in search_node.children:
            if isinstance(child, SearchNode):
                query_list.append(
                    xapian.Query(
                        xapian.Query.OP_AND, 
                        self._query_from_search_node(
                            child, child.negated
                        )
                    )
                )
            else:
                expression, term = child
                field, filter_type = search_node.split_expression(expression)

                if isinstance(term, (list, tuple)):
                    term = [_marshal_term(t) for t in term]
                else:
                    term = _marshal_term(term)

                if field == 'content':
                    query_list.append(self._content_field(term, is_not))
                else:
                    if filter_type == 'exact':
                        query_list.append(self._filter_exact(term, field, is_not))
                    elif filter_type == 'gt':
                        pass
                    elif filter_type == 'gte':
                        pass
                    elif filter_type == 'lt':
                        pass
                    elif filter_type == 'lte':
                        pass
                    elif filter_type == 'startswith':
                        pass
                    elif filter_type == 'in':
                        query_list.append(self._filter_in(term, field, is_not))
                    
        if search_node.connector == 'OR':
            return xapian.Query(xapian.Query.OP_OR, query_list)
        else:
            return xapian.Query(xapian.Query.OP_AND, query_list)

    def _content_field(self, term, is_not):
        """
        Private method that returns a xapian.Query that searches for `value`
        in all fields.
        
        Required arguments:
            ``term`` -- The term to search for
            ``is_not`` -- Invert the search results
        
        Returns:
            A xapian.Query
        """
        if ' ' in term:
            if is_not:
                return xapian.Query(
                    xapian.Query.OP_AND_NOT, self._all_query(), self._phrase_query(term.split())
                )
            else:
                return self._phrase_query(term.split())
        else:
            if is_not:
                return xapian.Query(xapian.Query.OP_AND_NOT, self._all_query(), self._term_query(term))
            else:
                return self._term_query(term)
    
    def _filter_exact(self, term, field, is_not):
        """
        Private method that returns a xapian.Query that searches for `term`
        in a specified `field`.
        
        Required arguments:
            ``term`` -- The term to search for
            ``field`` -- The field to search
            ``is_not`` -- Invert the search results
        
        Returns:
            A xapian.Query
        """
        if ' ' in term:
            if is_not:
                return xapian.Query(
                    xapian.Query.OP_AND_NOT, self._all_query(), self._phrase_query(term.split(), field)
                )
            else:
                return self._phrase_query(term.split(), field)
        else:
            if is_not:
                return xapian.Query(xapian.Query.OP_AND_NOT, self._all_query(), self._term_query(term, field))
            else:
                return self._term_query(term, field)
    
    def _filter_in(self, term_list, field, is_not):
        """
        Private method that returns a xapian.Query that searches for any term
        of `value_list` in a specified `field`.
        
        Required arguments:
            ``term_list`` -- The terms to search for
            ``field`` -- The field to search
            ``is_not`` -- Invert the search results
        
        Returns:
            A xapian.Query
        """
        query_list = []
        for term in term_list:
            if ' ' in term:
                query_list.append(
                    xapian.Query(
                        xapian.Query.OP_OR, self._phrase_query(term.split(), field)
                    )
                )
            else:
                query_list.append(
                    xapian.Query(
                        xapian.Query.OP_OR, self._term_query(term, field)
                    )
                )
        if is_not:
            return xapian.Query(xapian.Query.OP_AND_NOT, self._all_query(), xapian.Query(xapian.Query.OP_OR, query_list))          
        else:
            return xapian.Query(xapian.Query.OP_OR, query_list)
    
    def _all_query(self):
        """
        Private method that returns a xapian.Query that returns all documents,
        
        Returns:
            A xapian.Query
        """
        return xapian.Query('')

    def _term_query(self, term, field=None):
        """
        Private method that returns a term based xapian.Query that searches
        for `term`.
        
        Required arguments:
            ``term`` -- The term to search for
            ``field`` -- The field to search (If `None`, all fields)
        
        Returns:
            A xapian.Query
        """
        if field:
            return xapian.Query('%s%s%s' % (
                    DOCUMENT_CUSTOM_TERM_PREFIX, field.upper(), term
                )
            )
        else:
            return xapian.Query(term)

    def _phrase_query(self, term_list, field=None):
        """
        Private method that returns a phrase based xapian.Query that searches
        for terms in `term_list.
        
        Required arguments:
            ``term_list`` -- The terms to search for
            ``field`` -- The field to search (If `None`, all fields)
        
        Returns:
            A xapian.Query
        """
        if field:
            return xapian.Query(
                xapian.Query.OP_PHRASE, [
                    '%s%s%s' % (
                        DOCUMENT_CUSTOM_TERM_PREFIX, field.upper(), term
                    ) for term in term_list
                ]
            )
        else:
            return xapian.Query(xapian.Query.OP_PHRASE, term_list)


def _marshal_value(value):
    """
    Private utility method that converts Python values to a string for Xapian values.
    """
    if isinstance(value, datetime.datetime):
        value = _marshal_datetime(value)
    elif isinstance(value, datetime.date):
        value = _marshal_date(value)
    elif isinstance(value, bool):
        if value:
            value = u't'
        else:
            value = u'f'
    elif isinstance(value, float):
        value = xapian.sortable_serialise(value)
    elif isinstance(value, (int, long)):
        value = u'%012d' % value
    else:
        value = force_unicode(value).lower()
    return value


def _marshal_term(term):
    """
    Private utility method that converts Python terms to a string for Xapian terms.
    """
    if isinstance(term, datetime.datetime):
        term = _marshal_datetime(term)
    elif isinstance(term, datetime.date):
        term = _marshal_date(term)
    # elif isinstance(term, bool):
    #     if term:
    #         term = u'true'
    #     else:
    #         term = u'false'
    else:
        term = force_unicode(term).lower()
    return term


def _marshal_date(d):
    return u'%04d%02d%02d000000' % (d.year, d.month, d.day)


def _marshal_datetime(dt):
    if dt.microsecond:
        return u'%04d%02d%02d%02d%02d%02d%06d' % (
            dt.year, dt.month, dt.day, dt.hour,
            dt.minute, dt.second, dt.microsecond
        )
    else:
        return u'%04d%02d%02d%02d%02d%02d' % (
            dt.year, dt.month, dt.day, dt.hour,
            dt.minute, dt.second
        )