def get_storefront_most_popular(request_profile,
pre_fetch=True,
ordering=None):
"""
Get Most Popular Listings for storefront
"""
username = request_profile.user.username
# Get most popular listings via a weighted average
most_popular_listings_raw = models.Listing.objects.for_user_organization_minus_security_markings(
username).filter(approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False).order_by('-avg_rate',
'-total_reviews')
most_popular_listings = pipeline.Pipeline(
recommend_utils.ListIterator(
[listing for listing in most_popular_listings_raw]), [
pipes.ListingPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(36)
]).to_list()
sorted_most_popular_listings = custom_sort_listings(
most_popular_listings, ordering)
return sorted_most_popular_listings
def get_storefront_recent(request_profile, pre_fetch=True):
"""
Get Recent Listings for storefront
"""
username = request_profile.user.username
# Get Recent Listings
recent_listings_raw = models.Listing.objects.for_user_organization_minus_security_markings(
username).order_by('-approved_date').filter(
approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False)
recent_listings = pipeline.Pipeline(recommend_utils.ListIterator([listing for listing in recent_listings_raw]),
[pipes.ListingPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(24)]).to_list()
return recent_listings
def get_storefront_featured(request_profile, pre_fetch=True):
"""
Get Featured Listings for storefront
"""
username = request_profile.user.username
# Get Featured Listings
featured_listings_raw = models.Listing.objects.for_user_organization_minus_security_markings(
username).filter(
is_featured=True,
approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False).order_by(F('featured_date').desc(nulls_last=True))
featured_listings = pipeline.Pipeline(recommend_utils.ListIterator([listing for listing in featured_listings_raw]),
[pipes.ListingPostSecurityMarkingCheckPipe(username)]).to_list()
return featured_listings
def _get_recommended_listings(self):
profile_username = self.profile_instance.user.username
# Post security_marking check - lazy loading
pipeline_list = [
pipes.ListingPostSecurityMarkingCheckPipe(profile_username),
pipes.LimitPipe(10)
]
if self.randomize_recommended:
pipeline_list.insert(0, pipes.JitterPipe())
recommended_listings_iterator = recommend_utils.ListIterator(
self.recommended_listings_raw)
self.recommended_listings = pipeline.Pipeline(
recommended_listings_iterator, pipeline_list).to_list()
self.recommended_listings_ids = [
listing.id for listing in self.recommended_listings
]
def get_storefront_featured(username, pre_fetch=True):
"""
Get Featured Listings for storefront
"""
# Get Featured Listings
featured_listings_raw = models.Listing.objects.for_user_organization_minus_security_markings(
username).filter(is_featured=True,
approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False)
if pre_fetch:
featured_listings_raw = listing_serializers.ListingSerializer.setup_eager_loading(
featured_listings_raw)
featured_listings = pipeline.Pipeline(
recommend_utils.ListIterator(
[listing for listing in featured_listings_raw]),
[pipes.ListingPostSecurityMarkingCheckPipe(username)]).to_list()
return featured_listings
def get_storefront_most_popular(username, pre_fetch=True):
"""
Get Most Popular Listings for storefront
"""
# Get most popular listings via a weighted average
most_popular_listings_raw = models.Listing.objects.for_user_organization_minus_security_markings(
username).filter(approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False).order_by('-avg_rate',
'-total_reviews')
if pre_fetch:
most_popular_listings_raw = listing_serializers.ListingSerializer.setup_eager_loading(
most_popular_listings_raw)
most_popular_listings = pipeline.Pipeline(
recommend_utils.ListIterator(
[listing for listing in most_popular_listings_raw]), [
pipes.ListingPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(36)
]).to_list()
return most_popular_listings
def get_storefront_recommended(username, pre_fetch=True):
"""
Get Recommended Listings for storefront
"""
extra_data = {}
profile = models.Profile.objects.get(user__username=username)
if not profile.is_beta_user():
return [], extra_data
# Retrieve List of Recommended Apps for profile:
listing_ids_list, recommended_entry_data = get_recommendation_listing_ids(
profile)
extra_data['recommended_entry_data'] = recommended_entry_data
# Retrieve Profile Bookmarks and remove bookmarked from recommendation list
bookmarked_apps_list = set([
application_library_entry.listing.id for application_library_entry in
models.ApplicationLibraryEntry.objects.for_user(username)
])
listing_ids_list_temp = []
for current_listing_id in listing_ids_list:
if current_listing_id not in bookmarked_apps_list:
listing_ids_list_temp.append(current_listing_id)
listing_ids_list = listing_ids_list_temp
# Send new recommendation list minus bookmarked apps to User Interface
recommended_listings_queryset = models.Listing.objects.for_user_organization_minus_security_markings(
username).filter(pk__in=listing_ids_list,
approval_status=models.Listing.APPROVED,
is_enabled=True,
is_deleted=False).all()
if pre_fetch:
recommended_listings_queryset = listing_serializers.ListingSerializer.setup_eager_loading(
recommended_listings_queryset)
# Fix Order of Recommendations
id_recommended_object_mapper = {}
for recommendation_entry in recommended_listings_queryset:
id_recommended_object_mapper[
recommendation_entry.id] = recommendation_entry
# recommended_listings_raw = [id_recommended_object_mapper[listing_id] for listing_id in listing_ids_list]
recommended_listings_raw = []
for listing_id in listing_ids_list:
if listing_id in id_recommended_object_mapper:
recommended_listings_raw.append(
id_recommended_object_mapper[listing_id])
# Post security_marking check - lazy loading
recommended_listings = pipeline.Pipeline(
recommend_utils.ListIterator([
recommendations_listing
for recommendations_listing in recommended_listings_raw
]), [
pipes.JitterPipe(),
pipes.ListingPostSecurityMarkingCheckPipe(username),
pipes.LimitPipe(10)
]).to_list()
return recommended_listings, extra_data