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https://github.com/netbox-community/netbox.git
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* WIP * Add display_attrs for all indexers * Linkify object attributes * Clean up prefetch logic * Use tooltips for display attributes * Simplify template code * Introduce get_indexer() utility function * Add to examples in docs * Use tooltips to display long strings
288 lines
10 KiB
Python
288 lines
10 KiB
Python
from collections import defaultdict
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from django.conf import settings
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from django.contrib.contenttypes.models import ContentType
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from django.core.exceptions import ImproperlyConfigured
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from django.db.models import F, Window, Q, prefetch_related_objects
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from django.db.models.fields.related import ForeignKey
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from django.db.models.functions import window
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from django.db.models.signals import post_delete, post_save
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from django.utils.module_loading import import_string
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import netaddr
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from netaddr.core import AddrFormatError
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from extras.models import CachedValue, CustomField
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from netbox.registry import registry
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from utilities.querysets import RestrictedPrefetch
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from utilities.utils import content_type_identifier, title
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from . import FieldTypes, LookupTypes, get_indexer
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DEFAULT_LOOKUP_TYPE = LookupTypes.PARTIAL
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MAX_RESULTS = 1000
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class SearchBackend:
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"""
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Base class for search backends. Subclasses must extend the `cache()`, `remove()`, and `clear()` methods below.
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"""
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_object_types = None
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def get_object_types(self):
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"""
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Return a list of all registered object types, organized by category, suitable for populating a form's
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ChoiceField.
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"""
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if not self._object_types:
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# Organize choices by category
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categories = defaultdict(dict)
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for label, idx in registry['search'].items():
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categories[idx.get_category()][label] = title(idx.model._meta.verbose_name)
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# Compile a nested tuple of choices for form rendering
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results = (
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('', 'All Objects'),
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*[(category, list(choices.items())) for category, choices in categories.items()]
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)
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self._object_types = results
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return self._object_types
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def search(self, value, user=None, object_types=None, lookup=DEFAULT_LOOKUP_TYPE):
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"""
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Search cached object representations for the given value.
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"""
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raise NotImplementedError
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def caching_handler(self, sender, instance, created, **kwargs):
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"""
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Receiver for the post_save signal, responsible for caching object creation/changes.
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"""
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self.cache(instance, remove_existing=not created)
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def removal_handler(self, sender, instance, **kwargs):
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"""
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Receiver for the post_delete signal, responsible for caching object deletion.
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"""
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self.remove(instance)
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def cache(self, instances, indexer=None, remove_existing=True):
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"""
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Create or update the cached representation of an instance.
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"""
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raise NotImplementedError
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def remove(self, instance):
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"""
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Delete any cached representation of an instance.
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"""
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raise NotImplementedError
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def clear(self, object_types=None):
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"""
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Delete *all* cached data (optionally filtered by object type).
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"""
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raise NotImplementedError
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def count(self, object_types=None):
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"""
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Return a count of all cache entries (optionally filtered by object type).
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"""
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raise NotImplementedError
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@property
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def size(self):
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"""
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Return a total number of cached entries. The meaning of this value will be
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backend-dependent.
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"""
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return None
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class CachedValueSearchBackend(SearchBackend):
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def search(self, value, user=None, object_types=None, lookup=DEFAULT_LOOKUP_TYPE):
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# Build the filter used to find relevant CachedValue records
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query_filter = Q(**{f'value__{lookup}': value})
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if object_types:
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# Limit results by object type
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query_filter &= Q(object_type__in=object_types)
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if lookup in (LookupTypes.STARTSWITH, LookupTypes.ENDSWITH):
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# "Starts/ends with" matches are valid only on string values
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query_filter &= Q(type=FieldTypes.STRING)
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elif lookup == LookupTypes.PARTIAL:
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try:
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# If the value looks like an IP address, add an extra match for CIDR values
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address = str(netaddr.IPNetwork(value.strip()).cidr)
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query_filter |= Q(type=FieldTypes.CIDR) & Q(value__net_contains_or_equals=address)
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except (AddrFormatError, ValueError):
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pass
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# Construct the base queryset to retrieve matching results
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queryset = CachedValue.objects.filter(query_filter).annotate(
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# Annotate the rank of each result for its object according to its weight
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row_number=Window(
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expression=window.RowNumber(),
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partition_by=[F('object_type'), F('object_id')],
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order_by=[F('weight').asc()],
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)
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)[:MAX_RESULTS]
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# Gather all ContentTypes present in the search results (used for prefetching related
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# objects). This must be done before generating the final results list, which returns
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# a RawQuerySet.
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content_type_ids = set(queryset.values_list('object_type', flat=True))
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content_types = ContentType.objects.filter(pk__in=content_type_ids)
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# Construct a Prefetch to pre-fetch only those related objects for which the
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# user has permission to view.
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if user:
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prefetch = (RestrictedPrefetch('object', user, 'view'), 'object_type')
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else:
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prefetch = ('object', 'object_type')
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# Wrap the base query to return only the lowest-weight result for each object
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# Hat-tip to https://blog.oyam.dev/django-filter-by-window-function/ for the solution
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sql, params = queryset.query.sql_with_params()
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results = CachedValue.objects.prefetch_related(*prefetch).raw(
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f"SELECT * FROM ({sql}) t WHERE row_number = 1",
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params
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)
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# Iterate through each ContentType represented in the search results and prefetch any
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# related objects necessary to render the prescribed display attributes (display_attrs).
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for ct in content_types:
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model = ct.model_class()
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indexer = registry['search'].get(content_type_identifier(ct))
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if not (display_attrs := getattr(indexer, 'display_attrs', None)):
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continue
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# Add ForeignKey fields to prefetch list
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prefetch_fields = []
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for attr in display_attrs:
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field = model._meta.get_field(attr)
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if type(field) is ForeignKey:
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prefetch_fields.append(f'object__{attr}')
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# Compile a list of all CachedValues referencing this object type, and prefetch
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# any related objects
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if prefetch_fields:
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objects = [r for r in results if r.object_type == ct]
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prefetch_related_objects(objects, *prefetch_fields)
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# Omit any results pertaining to an object the user does not have permission to view
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ret = []
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for r in results:
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if r.object is not None:
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r.name = str(r.object)
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ret.append(r)
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return ret
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def cache(self, instances, indexer=None, remove_existing=True):
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content_type = None
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custom_fields = None
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# Convert a single instance to an iterable
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if not hasattr(instances, '__iter__'):
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instances = [instances]
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buffer = []
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counter = 0
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for instance in instances:
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# First item
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if not counter:
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# Determine the indexer
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if indexer is None:
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try:
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indexer = get_indexer(instance)
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except KeyError:
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break
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# Prefetch any associated custom fields
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content_type = ContentType.objects.get_for_model(indexer.model)
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custom_fields = CustomField.objects.filter(content_types=content_type).exclude(search_weight=0)
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# Wipe out any previously cached values for the object
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if remove_existing:
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self.remove(instance)
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# Generate cache data
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for field in indexer.to_cache(instance, custom_fields=custom_fields):
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buffer.append(
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CachedValue(
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object_type=content_type,
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object_id=instance.pk,
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field=field.name,
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type=field.type,
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weight=field.weight,
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value=field.value
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)
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)
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# Check whether the buffer needs to be flushed
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if len(buffer) >= 2000:
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counter += len(CachedValue.objects.bulk_create(buffer))
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buffer = []
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# Final buffer flush
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if buffer:
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counter += len(CachedValue.objects.bulk_create(buffer))
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return counter
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def remove(self, instance):
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# Avoid attempting to query for non-cacheable objects
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try:
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get_indexer(instance)
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except KeyError:
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return
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ct = ContentType.objects.get_for_model(instance)
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qs = CachedValue.objects.filter(object_type=ct, object_id=instance.pk)
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# Call _raw_delete() on the queryset to avoid first loading instances into memory
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return qs._raw_delete(using=qs.db)
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def clear(self, object_types=None):
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qs = CachedValue.objects.all()
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if object_types:
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qs = qs.filter(object_type__in=object_types)
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# Call _raw_delete() on the queryset to avoid first loading instances into memory
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return qs._raw_delete(using=qs.db)
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def count(self, object_types=None):
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qs = CachedValue.objects.all()
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if object_types:
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qs = qs.filter(object_type__in=object_types)
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return qs.count()
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@property
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def size(self):
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return CachedValue.objects.count()
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def get_backend():
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"""
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Initializes and returns the configured search backend.
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"""
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try:
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backend_cls = import_string(settings.SEARCH_BACKEND)
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except AttributeError:
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raise ImproperlyConfigured(f"Failed to import configured SEARCH_BACKEND: {settings.SEARCH_BACKEND}")
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# Initialize and return the backend instance
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return backend_cls()
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search_backend = get_backend()
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# Connect handlers to the appropriate model signals
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post_save.connect(search_backend.caching_handler)
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post_delete.connect(search_backend.removal_handler)
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