131 lines
5.3 KiB
Python
131 lines
5.3 KiB
Python
from datetime import datetime, timedelta
|
|
from functools import reduce
|
|
|
|
from recipes import settings
|
|
from django.contrib.postgres.aggregates import StringAgg
|
|
from django.contrib.postgres.search import (
|
|
SearchQuery, SearchRank, SearchVector, TrigramSimilarity,
|
|
)
|
|
from django.db.models import Q, Case, When, Value
|
|
from django.forms import IntegerField
|
|
from django.utils import translation
|
|
|
|
from cookbook.models import ViewLog
|
|
|
|
|
|
DICTIONARY = {
|
|
# TODO find custom dictionaries - maybe from here https://www.postgresql.org/message-id/CAF4Au4x6X_wSXFwsQYE8q5o0aQZANrvYjZJ8uOnsiHDnOVPPEg%40mail.gmail.com
|
|
# 'hy': 'Armenian',
|
|
# 'ca': 'Catalan',
|
|
# 'cs': 'Czech',
|
|
'nl': 'dutch',
|
|
'en': 'english',
|
|
'fr': 'french',
|
|
'de': 'german',
|
|
'it': 'italian',
|
|
# 'lv': 'Latvian',
|
|
'es': 'spanish',
|
|
}
|
|
|
|
|
|
def search_recipes(request, queryset, params):
|
|
search_string = params.get('query', '')
|
|
search_keywords = params.getlist('keywords', [])
|
|
search_foods = params.getlist('foods', [])
|
|
search_books = params.getlist('books', [])
|
|
|
|
search_keywords_or = params.get('keywords_or', True)
|
|
search_foods_or = params.get('foods_or', True)
|
|
search_books_or = params.get('books_or', True)
|
|
|
|
search_internal = params.get('internal', None)
|
|
search_random = params.get('random', False)
|
|
search_new = params.get('new', False)
|
|
search_last_viewed = int(params.get('last_viewed', 0))
|
|
|
|
if search_last_viewed > 0:
|
|
last_viewed_recipes = ViewLog.objects.filter(
|
|
created_by=request.user, space=request.space,
|
|
created_at__gte=datetime.now() - timedelta(days=14)).values_list(
|
|
'recipe__pk', flat=True).distinct()
|
|
return queryset.filter(pk__in=list(set(last_viewed_recipes))[-search_last_viewed:])
|
|
|
|
queryset = queryset.annotate(
|
|
new_recipe=Case(When(
|
|
created_at__gte=(datetime.now() - timedelta(days=7)), then=Value(100)),
|
|
default=Value(0), )).order_by('-new_recipe', 'name')
|
|
|
|
if settings.DATABASES['default']['ENGINE'] in ['django.db.backends.postgresql_psycopg2', 'django.db.backends.postgresql'] and search_string != '':
|
|
# queryset = queryset.annotate(similarity=TrigramSimilarity('name', search_string), )
|
|
# .filter(Q(similarity__gt=0.1) | Q(name__unaccent__icontains=search_string)).order_by('-similarity')
|
|
language = DICTIONARY.get(translation.get_language(), 'simple')
|
|
search_query = SearchQuery(
|
|
search_string,
|
|
search_type="websearch",
|
|
config=language,
|
|
)
|
|
# TODO create user options to add/remove query elements from search so that they can fine tune their own experience
|
|
# trigrams, icontains, unaccent and startswith all impact results and performance significantly
|
|
search_vectors = (
|
|
SearchVector('search_vector')
|
|
# searching instruction is extremely slow
|
|
# TODO add search vector field, GIN index and save signal to update the vector on step save
|
|
# + SearchVector('steps__instruction', weight='D', config=language)
|
|
+ SearchVector(StringAgg('steps__ingredients__food__name__unaccent', delimiter=' '), weight='B', config=language)
|
|
+ SearchVector(StringAgg('keywords__name__unaccent', delimiter=' '), weight='B', config=language))
|
|
trigram = (
|
|
TrigramSimilarity('name__unaccent', search_string)
|
|
+ TrigramSimilarity('description__unaccent', search_string)
|
|
# adding trigrams to ingredients and keywords causes duplicate results that can't be made unique
|
|
# + TrigramSimilarity('steps__ingredients__food__name__unaccent', search_string)
|
|
# + TrigramSimilarity('keywords__name__unaccent', search_string)
|
|
)
|
|
search_rank = SearchRank(search_vectors, search_query)
|
|
queryset = (
|
|
queryset.annotate(
|
|
vector=search_vectors,
|
|
rank=search_rank + trigram,
|
|
trigram=trigram
|
|
)
|
|
.filter(
|
|
# vector=search_query
|
|
Q(vector=search_query)
|
|
# adding trigrams to ingredients causes duplicate results that can't be made unique
|
|
# | Q(trigram__gt=0.2)
|
|
| Q(name__istartswith=search_string)
|
|
)
|
|
.order_by('-rank'))
|
|
else:
|
|
queryset = queryset.filter(name__icontains=search_string)
|
|
|
|
if len(search_keywords) > 0:
|
|
if search_keywords_or == 'true':
|
|
queryset = queryset.filter(keywords__id__in=search_keywords)
|
|
else:
|
|
for k in search_keywords:
|
|
queryset = queryset.filter(keywords__id=k)
|
|
|
|
if len(search_foods) > 0:
|
|
if search_foods_or == 'true':
|
|
queryset = queryset.filter(steps__ingredients__food__id__in=search_foods)
|
|
else:
|
|
for k in search_foods:
|
|
queryset = queryset.filter(steps__ingredients__food__id=k)
|
|
|
|
if len(search_books) > 0:
|
|
if search_books_or == 'true':
|
|
queryset = queryset.filter(recipebookentry__book__id__in=search_books)
|
|
else:
|
|
for k in search_books:
|
|
queryset = queryset.filter(recipebookentry__book__id=k)
|
|
|
|
queryset = queryset.distinct()
|
|
|
|
if search_internal == 'true':
|
|
queryset = queryset.filter(internal=True)
|
|
|
|
if search_random == 'true':
|
|
queryset = queryset.order_by("?")
|
|
|
|
return queryset
|