def list(self, request, listing_pk=None):
queryset = self.filter_queryset(self.get_queryset(listing_pk))
serializer = serializers.ListingSerializer(
queryset, context={'request': request}, many=True)
similar_listings = pipeline.Pipeline(
recommend_utils.ListIterator(serializer.data), [
pipes.ListingDictPostSecurityMarkingCheckPipe(
self.request.user.username),
pipes.LimitPipe(10)
]).to_list()
return Response(similar_listings)
def list(self, request):
queryset = self.get_queryset()
serializer = serializers.ImageSerializer(queryset,
many=True,
context={'request': request})
serializer_iterator = recommend_utils.ListIterator(serializer.data)
pipeline_list = [
pipes.ListingDictPostSecurityMarkingCheckPipe(
request.user.username)
]
recommended_listings = pipeline.Pipeline(serializer_iterator,
pipeline_list).to_list()
return Response(recommended_listings)
def get_storefront_new(username, request):
"""
Returns data for /storefront api invocation including:
* recommended listings (max=10)
* featured listings (max=12)
* recent (new) listings (max=24)
* most popular listings (max=36)
Args:
username
Returns:
{
'recommended': [Listing],
'featured': [Listing],
'recent': [Listing],
'most_popular': [Listing]
}
"""
extra_data = {}
profile = models.Profile.objects.get(user__username=username)
if profile.highest_role() == 'APPS_MALL_STEWARD':
exclude_orgs = []
elif profile.highest_role() == 'ORG_STEWARD':
user_orgs = profile.stewarded_organizations.all()
user_orgs = [i.title for i in user_orgs]
exclude_orgs = [
agency.title
for agency in models.Agency.objects.exclude(title__in=user_orgs)
]
else:
user_orgs = profile.organizations.all()
user_orgs = [i.title for i in user_orgs]
exclude_orgs = [
agency.title
for agency in models.Agency.objects.exclude(title__in=user_orgs)
]
current_listings = get_user_listings(username, request, exclude_orgs)
# Get Recommended Listings for owner
if profile.is_beta_user():
recommendation_listing_ids, recommended_entry_data = get_recommendation_listing_ids(
profile)
listing_ids_list = set(recommendation_listing_ids)
recommended_listings_raw = []
for current_listing in current_listings:
if current_listing['id'] in listing_ids_list:
recommended_listings_raw.append(current_listing)
recommended_listings = pipeline.Pipeline(
recommend_utils.ListIterator(recommended_listings_raw), [
pipes.JitterPipe(),
pipes.ListingDictPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(10)
]).to_list()
else:
recommended_listings = []
# Get Featured Listings
featured_listings = pipeline.Pipeline(
recommend_utils.ListIterator(current_listings), [
pipes.ListingDictPostSecurityMarkingCheckPipe(username,
featured=True),
pipes.LimitPipe(12)
]).to_list()
# Get Recent Listings
recent_listings = pipeline.Pipeline(
recommend_utils.ListIterator(current_listings), [
pipes.ListingDictPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(24)
]).to_list()
most_popular_listings = pipeline.Pipeline(
recommend_utils.ListIterator(
sorted(current_listings,
key=lambda k: (k['avg_rate'], ['total_reviews']),
reverse=True)), [
pipes.ListingDictPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(36)
]).to_list()
# TODO 2PI filtering
data = {
'recommended': recommended_listings,
'featured': featured_listings,
'recent': recent_listings,
'most_popular': most_popular_listings
}
return data, extra_data