# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import copy
from copy import deepcopy
from time import time
from django.conf import settings
from django.db.models import Q
from django.db.models.base import ModelBase
from django.utils import six
from django.utils import tree
from django.utils.encoding import force_text
from haystack.constants import VALID_FILTERS, FILTER_SEPARATOR, DEFAULT_ALIAS
from haystack.exceptions import MoreLikeThisError, FacetingError
from haystack.models import SearchResult
from haystack.utils.loading import UnifiedIndex
from haystack.utils import get_model_ct
VALID_GAPS = ['year', 'month', 'day', 'hour', 'minute', 'second']
SPELLING_SUGGESTION_HAS_NOT_RUN = object()
def log_query(func):
"""
A decorator for pseudo-logging search queries. Used in the ``SearchBackend``
to wrap the ``search`` method.
"""
def wrapper(obj, query_string, *args, **kwargs):
start = time()
try:
return func(obj, query_string, *args, **kwargs)
finally:
stop = time()
if settings.DEBUG:
from haystack import connections
connections[obj.connection_alias].queries.append({
'query_string': query_string,
'additional_args': args,
'additional_kwargs': kwargs,
'time': "%.3f" % (stop - start),
'start': start,
'stop': stop,
})
return wrapper
class EmptyResults(object):
hits = 0
docs = []
def __len__(self):
return 0
def __getitem__(self, k):
if isinstance(k, slice):
return []
else:
raise IndexError("It's not here.")
class BaseSearchBackend(object):
"""
Abstract search engine base class.
"""
# Backends should include their own reserved words/characters.
RESERVED_WORDS = []
RESERVED_CHARACTERS = []
def __init__(self, connection_alias, **connection_options):
self.connection_alias = connection_alias
self.timeout = connection_options.get('TIMEOUT', 10)
self.include_spelling = connection_options.get('INCLUDE_SPELLING', False)
self.batch_size = connection_options.get('BATCH_SIZE', 1000)
self.silently_fail = connection_options.get('SILENTLY_FAIL', True)
self.distance_available = connection_options.get('DISTANCE_AVAILABLE', False)
def update(self, index, iterable, commit=True):
"""
Updates the backend when given a SearchIndex and a collection of
documents.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError
def remove(self, obj_or_string):
"""
Removes a document/object from the backend. Can be either a model
instance or the identifier (i.e. ``app_name.model_name.id``) in the
event the object no longer exists.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError
def clear(self, models=None, commit=True):
"""
Clears the backend of all documents/objects for a collection of models.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError
@log_query
def search(self, query_string, **kwargs):
"""
Takes a query to search on and returns dictionary.
The query should be a string that is appropriate syntax for the backend.
The returned dictionary should contain the keys 'results' and 'hits'.
The 'results' value should be an iterable of populated SearchResult
objects. The 'hits' should be an integer count of the number of matched
results the search backend found.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError
def build_search_kwargs(self, query_string, 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,
within=None, dwithin=None, distance_point=None,
models=None, limit_to_registered_models=None,
result_class=None, **extra_kwargs):
# A convenience method most backends should include in order to make
# extension easier.
raise NotImplementedError
def prep_value(self, value):
"""
Hook to give the backend a chance to prep an attribute value before
sending it to the search engine. By default, just force it to unicode.
"""
return force_text(value)
def more_like_this(self, model_instance, additional_query_string=None, result_class=None):
"""
Takes a model object and returns results the backend thinks are similar.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError("Subclasses must provide a way to fetch similar record via the 'more_like_this' method if supported by the backend.")
def extract_file_contents(self, file_obj):
"""
Hook to allow backends which support rich-content types such as PDF,
Word, etc. extraction to process the provided file object and return
the contents for indexing
Returns None if metadata cannot be extracted; otherwise returns a
dictionary containing at least two keys:
:contents:
Extracted full-text content, if applicable
:metadata:
key:value pairs of text strings
"""
raise NotImplementedError("Subclasses must provide a way to extract metadata via the 'extract' method if supported by the backend.")
def build_schema(self, fields):
"""
Takes a dictionary of fields and returns schema information.
This method MUST be implemented by each backend, as it will be highly
specific to each one.
"""
raise NotImplementedError("Subclasses must provide a way to build their schema.")
def build_models_list(self):
"""
Builds a list of models for searching.
The ``search`` method should use this and the ``django_ct`` field to
narrow the results (unless the user indicates not to). This helps ignore
any results that are not currently handled models and ensures
consistent caching.
"""
from haystack import connections
models = []
for model in connections[self.connection_alias].get_unified_index().get_indexed_models():
models.append(get_model_ct(model))
return models
# Alias for easy loading within SearchQuery objects.
SearchBackend = BaseSearchBackend
class SearchNode(tree.Node):
"""
Manages an individual condition within a query.
Most often, this will be a lookup to ensure that a certain word or phrase
appears in the documents being indexed. However, it also supports filtering
types (such as 'lt', 'gt', 'in' and others) for more complex lookups.
This object creates a tree, with children being a list of either more
``SQ`` objects or the expressions/values themselves.
"""
AND = 'AND'
OR = 'OR'
default = AND
# Start compat. Django 1.6 changed how ``tree.Node`` works, so we're going
# to patch back in the original implementation until time to rewrite this
# presents itself.
# See https://github.com/django/django/commit/d3f00bd.
def __init__(self, children=None, connector=None, negated=False):
"""
Constructs a new Node. If no connector is given, the default will be
used.
Warning: You probably don't want to pass in the 'negated' parameter. It
is NOT the same as constructing a node and calling negate() on the
result.
"""
self.children = children and children[:] or []
self.connector = connector or self.default
self.subtree_parents = []
self.negated = negated
# We need this because of django.db.models.query_utils.Q. Q. __init__() is
# problematic, but it is a natural Node subclass in all other respects.
def _new_instance(cls, children=None, connector=None, negated=False):
"""
This is called to create a new instance of this class when we need new
Nodes (or subclasses) in the internal code in this class. Normally, it
just shadows __init__(). However, subclasses with an __init__ signature
that is not an extension of Node.__init__ might need to implement this
method to allow a Node to create a new instance of them (if they have
any extra setting up to do).
"""
obj = SearchNode(children, connector, negated)
obj.__class__ = cls
return obj
_new_instance = classmethod(_new_instance)
def __str__(self):
if self.negated:
return '(NOT (%s: %s))' % (self.connector, ', '.join([str(c) for c in self.children]))
return '(%s: %s)' % (self.connector, ', '.join([str(c) for c in self.children]))
def __deepcopy__(self, memodict):
"""
Utility method used by copy.deepcopy().
"""
obj = SearchNode(connector=self.connector, negated=self.negated)
obj.__class__ = self.__class__
obj.children = copy.deepcopy(self.children, memodict)
obj.subtree_parents = copy.deepcopy(self.subtree_parents, memodict)
return obj
def __len__(self):
"""
The size of a node if the number of children it has.
"""
return len(self.children)
def __bool__(self):
"""
For truth value testing.
"""
return bool(self.children)
def __nonzero__(self): # Python 2 compatibility
return type(self).__bool__(self)
def __contains__(self, other):
"""
Returns True is 'other' is a direct child of this instance.
"""
return other in self.children
def add(self, node, conn_type):
"""
Adds a new node to the tree. If the conn_type is the same as the root's
current connector type, the node is added to the first level.
Otherwise, the whole tree is pushed down one level and a new root
connector is created, connecting the existing tree and the new node.
"""
if node in self.children and conn_type == self.connector:
return
if len(self.children) < 2:
self.connector = conn_type
if self.connector == conn_type:
if isinstance(node, SearchNode) and (node.connector == conn_type or len(node) == 1):
self.children.extend(node.children)
else:
self.children.append(node)
else:
obj = self._new_instance(self.children, self.connector, self.negated)
self.connector = conn_type
self.children = [obj, node]
def negate(self):
"""
Negate the sense of the root connector. This reorganises the children
so that the current node has a single child: a negated node containing
all the previous children. This slightly odd construction makes adding
new children behave more intuitively.
Interpreting the meaning of this negate is up to client code. This
method is useful for implementing "not" arrangements.
"""
self.children = [self._new_instance(self.children, self.connector, not self.negated)]
self.connector = self.default
def start_subtree(self, conn_type):
"""
Sets up internal state so that new nodes are added to a subtree of the
current node. The conn_type specifies how the sub-tree is joined to the
existing children.
"""
if len(self.children) == 1:
self.connector = conn_type
elif self.connector != conn_type:
self.children = [self._new_instance(self.children, self.connector, self.negated)]
self.connector = conn_type
self.negated = False
self.subtree_parents.append(self.__class__(self.children, self.connector, self.negated))
self.connector = self.default
self.negated = False
self.children = []
def end_subtree(self):
"""
Closes off the most recently unmatched start_subtree() call.
This puts the current state into a node of the parent tree and returns
the current instances state to be the parent.
"""
obj = self.subtree_parents.pop()
node = self.__class__(self.children, self.connector)
self.connector = obj.connector
self.negated = obj.negated
self.children = obj.children
self.children.append(node)
# End compat.
def __repr__(self):
return '<SQ: %s %s>' % (self.connector, self.as_query_string(self._repr_query_fragment_callback))
def _repr_query_fragment_callback(self, field, filter_type, value):
if six.PY3:
value = force_text(value)
else:
value = force_text(value).encode('utf8')
return "%s%s%s=%s" % (field, FILTER_SEPARATOR, filter_type, value)
def as_query_string(self, query_fragment_callback):
"""
Produces a portion of the search query from the current SQ and its
children.
"""
result = []
for child in self.children:
if hasattr(child, 'as_query_string'):
result.append(child.as_query_string(query_fragment_callback))
else:
expression, value = child
field, filter_type = self.split_expression(expression)
result.append(query_fragment_callback(field, filter_type, value))
conn = ' %s ' % self.connector
query_string = conn.join(result)
if query_string:
if self.negated:
query_string = 'NOT (%s)' % query_string
elif len(self.children) != 1:
query_string = '(%s)' % query_string
return query_string
def split_expression(self, expression):
"""Parses an expression and determines the field and filter type."""
parts = expression.split(FILTER_SEPARATOR)
field = parts[0]
if len(parts) == 1 or parts[-1] not in VALID_FILTERS:
filter_type = 'content'
else:
filter_type = parts.pop()
return (field, filter_type)
class SQ(Q, SearchNode):
"""
Manages an individual condition within a query.
Most often, this will be a lookup to ensure that a certain word or phrase
appears in the documents being indexed. However, it also supports filtering
types (such as 'lt', 'gt', 'in' and others) for more complex lookups.
"""
pass
class BaseSearchQuery(object):
"""
A base class for handling the query itself.
This class acts as an intermediary between the ``SearchQuerySet`` and the
``SearchBackend`` itself.
The ``SearchQuery`` object maintains a tree of ``SQ`` objects. Each ``SQ``
object supports what field it looks up against, what kind of lookup (i.e.
the __'s), what value it's looking for, if it's a AND/OR/NOT and tracks
any children it may have. The ``SearchQuery.build_query`` method starts with
the root of the tree, building part of the final query at each node until
the full final query is ready for the ``SearchBackend``.
Backends should extend this class and provide implementations for
``build_query_fragment``, ``clean`` and ``run``. See the ``solr`` backend for an example
implementation.
"""
def __init__(self, using=DEFAULT_ALIAS):
self.query_filter = SearchNode()
self.order_by = []
self.models = set()
self.boost = {}
self.start_offset = 0
self.end_offset = None
self.highlight = False
self.facets = {}
self.date_facets = {}
self.query_facets = []
self.narrow_queries = set()
#: If defined, fields should be a list of field names - no other values
#: will be retrieved so the caller must be careful to include django_ct
#: and django_id when using code which expects those to be included in
#: the results
self.fields = []
# Geospatial-related information
self.within = {}
self.dwithin = {}
self.distance_point = {}
# Internal.
self._raw_query = None
self._raw_query_params = {}
self._more_like_this = False
self._mlt_instance = None
self._results = None
self._hit_count = None
self._facet_counts = None
self._stats = None
self._spelling_suggestion = SPELLING_SUGGESTION_HAS_NOT_RUN
self.spelling_query = None
self.result_class = SearchResult
self.stats = {}
from haystack import connections
self._using = using
self.backend = connections[self._using].get_backend()
def __str__(self):
return self.build_query()
def __getstate__(self):
"""For pickling."""
obj_dict = self.__dict__.copy()
del(obj_dict['backend'])
return obj_dict
def __setstate__(self, obj_dict):
"""For unpickling."""
from haystack import connections
self.__dict__.update(obj_dict)
self.backend = connections[self._using].get_backend()
def has_run(self):
"""Indicates if any query has been been run."""
return None not in (self._results, self._hit_count)
def build_params(self, spelling_query=None):
"""Generates a list of params to use when searching."""
kwargs = {
'start_offset': self.start_offset,
}
if self.order_by:
kwargs['sort_by'] = self.order_by
if self.end_offset is not None:
kwargs['end_offset'] = self.end_offset
if self.highlight:
kwargs['highlight'] = self.highlight
if self.facets:
kwargs['facets'] = self.facets
if self.date_facets:
kwargs['date_facets'] = self.date_facets
if self.query_facets:
kwargs['query_facets'] = self.query_facets
if self.narrow_queries:
kwargs['narrow_queries'] = self.narrow_queries
if spelling_query:
kwargs['spelling_query'] = spelling_query
elif self.spelling_query:
kwargs['spelling_query'] = self.spelling_query
if self.boost:
kwargs['boost'] = self.boost
if self.within:
kwargs['within'] = self.within
if self.dwithin:
kwargs['dwithin'] = self.dwithin
if self.distance_point:
kwargs['distance_point'] = self.distance_point
if self.result_class:
kwargs['result_class'] = self.result_class
if self.fields:
kwargs['fields'] = self.fields
if self.models:
kwargs['models'] = self.models
return kwargs
def run(self, spelling_query=None, **kwargs):
"""Builds and executes the query. Returns a list of search results."""
final_query = self.build_query()
search_kwargs = self.build_params(spelling_query=spelling_query)
if kwargs:
search_kwargs.update(kwargs)
results = self.backend.search(final_query, **search_kwargs)
self._results = results.get('results', [])
self._hit_count = results.get('hits', 0)
self._facet_counts = self.post_process_facets(results)
self._spelling_suggestion = results.get('spelling_suggestion', None)
def run_mlt(self, **kwargs):
"""
Executes the More Like This. Returns a list of search results similar
to the provided document (and optionally query).
"""
if self._more_like_this is False or self._mlt_instance is None:
raise MoreLikeThisError("No instance was provided to determine 'More Like This' results.")
search_kwargs = {
'result_class': self.result_class,
}
if self.models:
search_kwargs['models'] = self.models
if kwargs:
search_kwargs.update(kwargs)
additional_query_string = self.build_query()
results = self.backend.more_like_this(self._mlt_instance, additional_query_string, **search_kwargs)
self._results = results.get('results', [])
self._hit_count = results.get('hits', 0)
def run_raw(self, **kwargs):
"""Executes a raw query. Returns a list of search results."""
search_kwargs = self.build_params()
search_kwargs.update(self._raw_query_params)
if kwargs:
search_kwargs.update(kwargs)
results = self.backend.search(self._raw_query, **search_kwargs)
self._results = results.get('results', [])
self._hit_count = results.get('hits', 0)
self._facet_counts = results.get('facets', {})
self._spelling_suggestion = results.get('spelling_suggestion', None)
def get_count(self):
"""
Returns the number of results the backend found for the query.
If the query has not been run, this will execute the query and store
the results.
"""
if self._hit_count is None:
# Limit the slice to 1 so we get a count without consuming
# everything.
if not self.end_offset:
self.end_offset = 1
if self._more_like_this:
# Special case for MLT.
self.run_mlt()
elif self._raw_query:
# Special case for raw queries.
self.run_raw()
else:
self.run()
return self._hit_count
def get_results(self, **kwargs):
"""
Returns the results received from the backend.
If the query has not been run, this will execute the query and store
the results.
"""
if self._results is None:
if self._more_like_this:
# Special case for MLT.
self.run_mlt(**kwargs)
elif self._raw_query:
# Special case for raw queries.
self.run_raw(**kwargs)
else:
self.run(**kwargs)
return self._results
def get_facet_counts(self):
"""
Returns the facet counts received from the backend.
If the query has not been run, this will execute the query and store
the results.
"""
if self._facet_counts is None:
self.run()
return self._facet_counts
def get_stats(self):
"""
Returns the stats received from the backend.
If the query has not been run, this will execute the query and store
the results
"""
if self._stats is None:
self.run()
return self._stats
def set_spelling_query(self, spelling_query):
self.spelling_query = spelling_query
def get_spelling_suggestion(self, preferred_query=None):
"""
Returns the spelling suggestion received from the backend.
If the query has not been run, this will execute the query and store
the results.
"""
if self._spelling_suggestion is SPELLING_SUGGESTION_HAS_NOT_RUN:
self.run(spelling_query=preferred_query)
return self._spelling_suggestion
def boost_fragment(self, boost_word, boost_value):
"""Generates query fragment for boosting a single word/value pair."""
return "%s^%s" % (boost_word, boost_value)
def matching_all_fragment(self):
"""Generates the query that matches all documents."""
return '*'
def build_query(self):
"""
Interprets the collected query metadata and builds the final query to
be sent to the backend.
"""
final_query = self.query_filter.as_query_string(self.build_query_fragment)
if not final_query:
# Match all.
final_query = self.matching_all_fragment()
if self.boost:
boost_list = []
for boost_word, boost_value in self.boost.items():
boost_list.append(self.boost_fragment(boost_word, boost_value))
final_query = "%s %s" % (final_query, " ".join(boost_list))
return final_query
def combine(self, rhs, connector=SQ.AND):
if connector == SQ.AND:
self.add_filter(rhs.query_filter)
elif connector == SQ.OR:
self.add_filter(rhs.query_filter, use_or=True)
# Methods for backends to implement.
def build_query_fragment(self, field, filter_type, value):
"""
Generates a query fragment from a field, filter type and a value.
Must be implemented in backends as this will be highly backend specific.
"""
raise NotImplementedError("Subclasses must provide a way to generate query fragments via the 'build_query_fragment' method.")
# Standard methods to alter the query.
def clean(self, query_fragment):
"""
Provides a mechanism for sanitizing user input before presenting the
value to the backend.
A basic (override-able) implementation is provided.
"""
if not isinstance(query_fragment, six.string_types):
return query_fragment
words = query_fragment.split()
cleaned_words = []
for word in words:
if word in self.backend.RESERVED_WORDS:
word = word.replace(word, word.lower())
for char in self.backend.RESERVED_CHARACTERS:
word = word.replace(char, '\\%s' % char)
cleaned_words.append(word)
return ' '.join(cleaned_words)
def build_not_query(self, query_string):
if ' ' in query_string:
query_string = "(%s)" % query_string
return u"NOT %s" % query_string
def build_exact_query(self, query_string):
return u'"%s"' % query_string
def add_filter(self, query_filter, use_or=False):
"""
Adds a SQ to the current query.
"""
if use_or:
connector = SQ.OR
else:
connector = SQ.AND
if self.query_filter and query_filter.connector != connector and len(query_filter) > 1:
self.query_filter.start_subtree(connector)
subtree = True
else:
subtree = False
for child in query_filter.children:
if isinstance(child, tree.Node):
self.query_filter.start_subtree(connector)
self.add_filter(child)
self.query_filter.end_subtree()
else:
expression, value = child
self.query_filter.add((expression, value), connector)
connector = query_filter.connector
if query_filter.negated:
self.query_filter.negate()
if subtree:
self.query_filter.end_subtree()
def add_order_by(self, field):
"""Orders the search result by a field."""
self.order_by.append(field)
def clear_order_by(self):
"""
Clears out all ordering that has been already added, reverting the
query to relevancy.
"""
self.order_by = []
def add_model(self, model):
"""
Restricts the query requiring matches in the given model.
This builds upon previous additions, so you can limit to multiple models
by chaining this method several times.
"""
if not isinstance(model, ModelBase):
raise AttributeError('The model being added to the query must derive from Model.')
self.models.add(model)
def set_limits(self, low=None, high=None):
"""Restricts the query by altering either the start, end or both offsets."""
if low is not None:
self.start_offset = int(low)
if high is not None:
self.end_offset = int(high)
def clear_limits(self):
"""Clears any existing limits."""
self.start_offset, self.end_offset = 0, None
def add_boost(self, term, boost_value):
"""Adds a boosted term and the amount to boost it to the query."""
self.boost[term] = boost_value
def raw_search(self, query_string, **kwargs):
"""
Runs a raw query (no parsing) against the backend.
This method causes the SearchQuery to ignore the standard query
generating facilities, running only what was provided instead.
Note that any kwargs passed along will override anything provided
to the rest of the ``SearchQuerySet``.
"""
self._raw_query = query_string
self._raw_query_params = kwargs
def more_like_this(self, model_instance):
"""
Allows backends with support for "More Like This" to return results
similar to the provided instance.
"""
self._more_like_this = True
self._mlt_instance = model_instance
def add_stats_query(self, stats_field, stats_facets):
"""Adds stats and stats_facets queries for the Solr backend."""
self.stats[stats_field] = stats_facets
def add_highlight(self, **kwargs):
"""Adds highlighting to the search results."""
self.highlight = kwargs or True
def add_within(self, field, point_1, point_2):
"""Adds bounding box parameters to search query."""
from haystack.utils.geo import ensure_point
self.within = {
'field': field,
'point_1': ensure_point(point_1),
'point_2': ensure_point(point_2),
}
def add_dwithin(self, field, point, distance):
"""Adds radius-based parameters to search query."""
from haystack.utils.geo import ensure_point, ensure_distance
self.dwithin = {
'field': field,
'point': ensure_point(point),
'distance': ensure_distance(distance),
}
def add_distance(self, field, point):
"""
Denotes that results should include distance measurements from the
point passed in.
"""
from haystack.utils.geo import ensure_point
self.distance_point = {
'field': field,
'point': ensure_point(point),
}
def add_field_facet(self, field, **options):
"""Adds a regular facet on a field."""
from haystack import connections
field_name = connections[self._using].get_unified_index().get_facet_fieldname(field)
self.facets[field_name] = options.copy()
def add_date_facet(self, field, start_date, end_date, gap_by, gap_amount=1):
"""Adds a date-based facet on a field."""
from haystack import connections
if gap_by not in VALID_GAPS:
raise FacetingError("The gap_by ('%s') must be one of the following: %s." % (gap_by, ', '.join(VALID_GAPS)))
details = {
'start_date': start_date,
'end_date': end_date,
'gap_by': gap_by,
'gap_amount': gap_amount,
}
self.date_facets[connections[self._using].get_unified_index().get_facet_fieldname(field)] = details
def add_query_facet(self, field, query):
"""Adds a query facet on a field."""
from haystack import connections
self.query_facets.append((connections[self._using].get_unified_index().get_facet_fieldname(field), query))
def add_narrow_query(self, query):
"""
Narrows a search to a subset of all documents per the query.
Generally used in conjunction with faceting.
"""
self.narrow_queries.add(query)
def set_result_class(self, klass):
"""
Sets the result class to use for results.
Overrides any previous usages. If ``None`` is provided, Haystack will
revert back to the default ``SearchResult`` object.
"""
if klass is None:
klass = SearchResult
self.result_class = klass
def post_process_facets(self, results):
# Handle renaming the facet fields. Undecorate and all that.
from haystack import connections
revised_facets = {}
field_data = connections[self._using].get_unified_index().all_searchfields()
for facet_type, field_details in results.get('facets', {}).items():
temp_facets = {}
for field, field_facets in field_details.items():
fieldname = field
if field in field_data and hasattr(field_data[field], 'get_facet_for_name'):
fieldname = field_data[field].get_facet_for_name()
temp_facets[fieldname] = field_facets
revised_facets[facet_type] = temp_facets
return revised_facets
def using(self, using=None):
"""
Allows for overriding which connection should be used. This
disables the use of routers when performing the query.
If ``None`` is provided, it has no effect on what backend is used.
"""
return self._clone(using=using)
def _reset(self):
"""
Resets the instance's internal state to appear as though no query has
been run before. Only need to tweak a few variables we check.
"""
self._results = None
self._hit_count = None
self._facet_counts = None
self._spelling_suggestion = SPELLING_SUGGESTION_HAS_NOT_RUN
def _clone(self, klass=None, using=None):
if using is None:
using = self._using
else:
from haystack import connections
klass = connections[using].query
if klass is None:
klass = self.__class__
clone = klass(using=using)
clone.query_filter = deepcopy(self.query_filter)
clone.order_by = self.order_by[:]
clone.models = self.models.copy()
clone.boost = self.boost.copy()
clone.highlight = self.highlight
clone.stats = self.stats.copy()
clone.facets = self.facets.copy()
clone.date_facets = self.date_facets.copy()
clone.query_facets = self.query_facets[:]
clone.narrow_queries = self.narrow_queries.copy()
clone.start_offset = self.start_offset
clone.end_offset = self.end_offset
clone.result_class = self.result_class
clone.within = self.within.copy()
clone.dwithin = self.dwithin.copy()
clone.distance_point = self.distance_point.copy()
clone._raw_query = self._raw_query
clone._raw_query_params = self._raw_query_params
clone.spelling_query = self.spelling_query
clone._more_like_this = self._more_like_this
clone._mlt_instance = self._mlt_instance
return clone
class BaseEngine(object):
backend = BaseSearchBackend
query = BaseSearchQuery
unified_index = UnifiedIndex
def __init__(self, using=None):
if using is None:
using = DEFAULT_ALIAS
self.using = using
self.options = settings.HAYSTACK_CONNECTIONS.get(self.using, {})
self.queries = []
self._index = None
self._backend = None
def get_backend(self):
if self._backend is None:
self._backend = self.backend(self.using, **self.options)
return self._backend
def reset_sessions(self):
"""Reset any transient connections, file handles, etc."""
self._backend = None
def get_query(self):
return self.query(using=self.using)
def reset_queries(self):
del self.queries[:]
def get_unified_index(self):
if self._index is None:
self._index = self.unified_index(self.options.get('EXCLUDED_INDEXES', []))
return self._index