def get_best_psi_films_queryset(self,
user,
tags=None,
year_from=None,
year_to=None,
related_director=None,
related_actor=None,
popularity=None,
include_features=(),
exclude_features=(),
netflix=None,
exclude_production_country=None):
from film20.recommendations import engine
is_filtered = tags or year_from or year_to or related_director or related_actor or popularity or netflix
if exclude_production_country:
kw = dict(exclude_production_country=exclude_production_country)
else:
kw = {}
all_scores = engine.compute_guess_score_for_all_films(user, **kw)
all_scores = dict((key, val) for key, val in all_scores.items() if val)
ratings = Rating.get_user_ratings(user)
shitlisted = set(k for k, v in BasketItem.user_basket(user).items()
if v[0] == 9)
film_ids = set(all_scores.keys())
film_ids.difference_update(ratings.keys())
film_ids.difference_update(shitlisted)
if is_filtered:
filtered = self._filter_films(tags, year_from, year_to,
related_director, related_actor,
popularity, netflix)
filtered = filtered.filter(id__in=film_ids)
film_ids = filtered.values_list('id', flat=True)
if include_features:
from film20.film_features.models import FilmFeature
featured_ids = FilmFeature.matching_film_ids(
include_features, exclude_features)
film_ids = [id for id in film_ids if id in featured_ids]
film_ids = sorted(film_ids, key=lambda f: -all_scores[f])
from film20.utils.misc import ListWrapper
class FilmWrapper(ListWrapper):
def wrap(self, items):
films = list(Film.objects.filter(id__in=items))
films.sort(key=lambda f: -all_scores[f.id])
for film in films:
film.guess_rating = all_scores.get(film.id)
yield film
return FilmWrapper(film_ids)
def get_ranking(self, type=Rating.TYPE_FILM, tags=None, year_from=None, year_to = None, related_director = None,
related_actor = None, popularity = None, order_by="average_score", order_way="desc",
limit = None, offset = None, min_num_votes = None, festival = False, exclude_production_country=None,
include_features=(), exclude_features=(), tv_series=False, **kw):
"""
Gets film ranking for given type (overall, directory, screenplay, etc)
"""
if min_num_votes == None:
# festival hacks
if festival:
min_num_votes = 1
# this is user-entered
elif popularity is not None:
min_num_votes = popularity
elif type == Rating.TYPE_FILM:
min_num_votes = FilmRanking.MIN_NUM_VOTES_FILM if not tv_series else 0
else:
min_num_votes = FilmRanking.MIN_NUM_VOTES_OTHER
ranking = FilmRanking.objects.filter(type = type, number_of_votes__gte = min_num_votes).select_related('film', 'film__directors', 'film__actors').order_by('-average_score').distinct()
if tv_series is not None:
ranking = ranking.filter(film__is_tv_series=tv_series)
if year_from:
ranking = ranking.filter(film__release_year__gte = year_from)
if year_to:
ranking = ranking.filter(film__release_year__lte = year_to)
if related_director:
for director in related_director:
ranking = ranking.filter(film__directors = director.id)
if related_actor:
for actor in related_actor:
ranking = ranking.filter(film__actors = actor.id, film__character__LANG = settings.LANGUAGE_CODE)
if tags:
tags = [t.strip() for t in tags.split(',')]
logger.debug("Enriching query. Filtering by tags: %r", tags)
for tag in tags:
ranking = ranking.filter(film__objectlocalized__tagged_items__tag__name = tag, film__objectlocalized__LANG = settings.LANGUAGE_CODE)
if exclude_production_country:
ranking = ranking.exclude(film__production_country_list__icontains=exclude_production_country)
if include_features:
from film20.film_features.models import FilmFeature
featured_ids = FilmFeature.matching_film_ids(include_features, exclude_features)
ranking = ranking.filter(film__in=featured_ids)
logger.debug("Ranking fetched for type " + unicode(type))
return ranking
def get_best_psi_films_queryset(self, user, tags=None, year_from=None, year_to = None, related_director = None, related_actor = None, popularity = None, include_features=(), exclude_features=(), netflix=None, exclude_production_country=None):
from film20.recommendations import engine
is_filtered = tags or year_from or year_to or related_director or related_actor or popularity or netflix
if exclude_production_country:
kw = dict(exclude_production_country=exclude_production_country)
else:
kw = {}
all_scores = engine.compute_guess_score_for_all_films(user, **kw)
all_scores = dict((key, val) for key, val in all_scores.items() if val)
ratings = Rating.get_user_ratings(user)
shitlisted = set(k for k,v in BasketItem.user_basket(user).items() if v[0]==9)
film_ids = set(all_scores.keys())
film_ids.difference_update(ratings.keys())
film_ids.difference_update(shitlisted)
if is_filtered:
filtered = self._filter_films(tags, year_from, year_to, related_director, related_actor, popularity, netflix)
filtered = filtered.filter(id__in=film_ids)
film_ids = filtered.values_list('id', flat=True)
if include_features:
from film20.film_features.models import FilmFeature
featured_ids = FilmFeature.matching_film_ids(include_features, exclude_features)
film_ids = [id for id in film_ids if id in featured_ids]
film_ids = sorted(film_ids, key=lambda f: -all_scores[f])
from film20.utils.misc import ListWrapper
class FilmWrapper(ListWrapper):
def wrap(self, items):
films = list(Film.objects.filter(id__in=items))
films.sort(key=lambda f:-all_scores[f.id])
for film in films:
film.guess_rating = all_scores.get(film.id)
yield film
return FilmWrapper(film_ids)
def get_ranking(self,
type=Rating.TYPE_FILM,
tags=None,
year_from=None,
year_to=None,
related_director=None,
related_actor=None,
popularity=None,
order_by="average_score",
order_way="desc",
limit=None,
offset=None,
min_num_votes=None,
festival=False,
exclude_production_country=None,
include_features=(),
exclude_features=(),
tv_series=False,
**kw):
"""
Gets film ranking for given type (overall, directory, screenplay, etc)
"""
if min_num_votes == None:
# festival hacks
if festival:
min_num_votes = 1
# this is user-entered
elif popularity is not None:
min_num_votes = popularity
elif type == Rating.TYPE_FILM:
min_num_votes = FilmRanking.MIN_NUM_VOTES_FILM if not tv_series else 0
else:
min_num_votes = FilmRanking.MIN_NUM_VOTES_OTHER
ranking = FilmRanking.objects.filter(
type=type, number_of_votes__gte=min_num_votes).select_related(
'film', 'film__directors',
'film__actors').order_by('-average_score').distinct()
if tv_series is not None:
ranking = ranking.filter(film__is_tv_series=tv_series)
if year_from:
ranking = ranking.filter(film__release_year__gte=year_from)
if year_to:
ranking = ranking.filter(film__release_year__lte=year_to)
if related_director:
for director in related_director:
ranking = ranking.filter(film__directors=director.id)
if related_actor:
for actor in related_actor:
ranking = ranking.filter(
film__actors=actor.id,
film__character__LANG=settings.LANGUAGE_CODE)
if tags:
tags = [t.strip() for t in tags.split(',')]
logger.debug("Enriching query. Filtering by tags: %r", tags)
for tag in tags:
ranking = ranking.filter(
film__objectlocalized__tagged_items__tag__name=tag,
film__objectlocalized__LANG=settings.LANGUAGE_CODE)
if exclude_production_country:
ranking = ranking.exclude(film__production_country_list__icontains=
exclude_production_country)
if include_features:
from film20.film_features.models import FilmFeature
featured_ids = FilmFeature.matching_film_ids(
include_features, exclude_features)
ranking = ranking.filter(film__in=featured_ids)
logger.debug("Ranking fetched for type " + unicode(type))
return ranking
def get_mood_film_ids(self, tag):
mood = tag and self.MOODS_MAP.get(tag)
if not mood:
return ()
return FilmFeature.matching_film_ids(mood.include, mood.exclude)
def get_mood_film_ids(self, tag):
mood = tag and self.MOODS_MAP.get(tag)
if not mood:
return ()
return FilmFeature.matching_film_ids(mood.include, mood.exclude)
