158 lines
7.1 KiB
Python
158 lines
7.1 KiB
Python
from datetime import datetime, timedelta
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from recipes import settings
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from django.contrib.postgres.search import (
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SearchQuery, SearchRank, TrigramSimilarity
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)
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from django.db.models import Q, Subquery, Case, When, Value
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from django.utils import translation
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from cookbook.managers import DICTIONARY
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from cookbook.models import Food, Keyword, ViewLog
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def search_recipes(request, queryset, params):
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search_prefs = request.user.searchpreference
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search_string = params.get('query', '')
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search_keywords = params.getlist('keywords', [])
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search_foods = params.getlist('foods', [])
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search_books = params.getlist('books', [])
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search_keywords_or = params.get('keywords_or', True)
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search_foods_or = params.get('foods_or', True)
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search_books_or = params.get('books_or', True)
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search_internal = params.get('internal', None)
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search_random = params.get('random', False)
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search_new = params.get('new', False)
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search_last_viewed = int(params.get('last_viewed', 0))
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if search_last_viewed > 0:
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last_viewed_recipes = ViewLog.objects.filter(
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created_by=request.user, space=request.space,
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created_at__gte=datetime.now() - timedelta(days=14)
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).order_by('pk').values_list('recipe__pk', flat=True).distinct()
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return queryset.filter(pk__in=last_viewed_recipes[len(last_viewed_recipes) - min(len(last_viewed_recipes), search_last_viewed):])
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if search_new == 'true':
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queryset = queryset.annotate(
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new_recipe=Case(When(created_at__gte=(datetime.now() - timedelta(days=7)), then=Value(100)),
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default=Value(0), )).order_by('-new_recipe', 'name')
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else:
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queryset = queryset.order_by('name')
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search_type = search_prefs.search or 'plain'
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search_sort = None
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if len(search_string) > 0:
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unaccent_include = search_prefs.unaccent.values_list('field', flat=True)
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icontains_include = [x + '__unaccent' if x in unaccent_include else x for x in search_prefs.icontains.values_list('field', flat=True)]
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istartswith_include = [x + '__unaccent' if x in unaccent_include else x for x in search_prefs.istartswith.values_list('field', flat=True)]
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trigram_include = [x + '__unaccent' if x in unaccent_include else x for x in search_prefs.trigram.values_list('field', flat=True)]
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fulltext_include = search_prefs.fulltext.values_list('field', flat=True) # fulltext doesn't use field name directly
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# if no filters are configured use name__icontains as default
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if len(icontains_include) + len(istartswith_include) + len(trigram_include) + len(fulltext_include) == 0:
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filters = [Q(**{"name__icontains": search_string})]
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else:
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filters = []
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# dynamically build array of filters that will be applied
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for f in icontains_include:
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filters += [Q(**{"%s__icontains" % f: search_string})]
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for f in istartswith_include:
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filters += [Q(**{"%s__istartswith" % f: search_string})]
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if settings.DATABASES['default']['ENGINE'] in ['django.db.backends.postgresql_psycopg2', 'django.db.backends.postgresql']:
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language = DICTIONARY.get(translation.get_language(), 'simple')
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# django full text search https://docs.djangoproject.com/en/3.2/ref/contrib/postgres/search/#searchquery
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# TODO can options install this extension to further enhance search query language https://github.com/caub/pg-tsquery
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# trigram breaks full text search 'websearch' and 'raw' capabilities and will be ignored if those methods are chosen
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if search_type in ['websearch', 'raw']:
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search_trigram = False
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else:
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search_trigram = True
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search_query = SearchQuery(
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search_string,
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search_type=search_type,
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config=language,
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)
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# iterate through fields to use in trigrams generating a single trigram
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if search_trigram & len(trigram_include) > 1:
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trigram = None
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for f in trigram_include:
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if trigram:
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trigram += TrigramSimilarity(f, search_string)
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else:
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trigram = TrigramSimilarity(f, search_string)
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queryset.annotate(simularity=trigram)
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# TODO allow user to play with trigram scores
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filters += [Q(simularity__gt=0.5)]
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if 'name' in fulltext_include:
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filters += [Q(name_search_vector=search_query)]
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if 'description' in fulltext_include:
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filters += [Q(desc_search_vector=search_query)]
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if 'instructions' in fulltext_include:
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filters += [Q(steps__search_vector=search_query)]
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if 'keywords' in fulltext_include:
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filters += [Q(keywords__in=Subquery(Keyword.objects.filter(name__search=search_query).values_list('id', flat=True)))]
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if 'foods' in fulltext_include:
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filters += [Q(steps__ingredients__food__in=Subquery(Food.objects.filter(name__search=search_query).values_list('id', flat=True)))]
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query_filter = None
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for f in filters:
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if query_filter:
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query_filter |= f
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else:
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query_filter = f
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# TODO this is kind of a dumb method to sort. create settings to choose rank vs most often made, date created or rating
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search_rank = (
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SearchRank('name_search_vector', search_query, cover_density=True)
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+ SearchRank('desc_search_vector', search_query, cover_density=True)
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+ SearchRank('steps__search_vector', search_query, cover_density=True)
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)
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queryset = queryset.filter(query_filter).annotate(rank=search_rank)
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else:
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queryset = queryset.filter(query_filter)
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if len(search_keywords) > 0:
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if search_keywords_or == 'true':
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queryset = queryset.filter(keywords__id__in=search_keywords)
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else:
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for k in search_keywords:
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queryset = queryset.filter(keywords__id=k)
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if len(search_foods) > 0:
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if search_foods_or == 'true':
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queryset = queryset.filter(steps__ingredients__food__id__in=search_foods)
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else:
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for k in search_foods:
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queryset = queryset.filter(steps__ingredients__food__id=k)
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if len(search_books) > 0:
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if search_books_or == 'true':
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queryset = queryset.filter(recipebookentry__book__id__in=search_books)
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else:
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for k in search_books:
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queryset = queryset.filter(recipebookentry__book__id=k)
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if search_internal == 'true':
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queryset = queryset.filter(internal=True)
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queryset = queryset.distinct()
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if search_random == 'true':
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queryset = queryset.order_by("?")
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elif search_sort == 'rank':
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queryset = queryset.order_by('-rank')
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return queryset
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# this returns a list of keywords in the queryset and how many times it appears
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# Keyword.objects.filter(recipe__in=queryset).annotate(kw_count=Count('recipe'))
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