def load_rest():
User.load_to_cache()
# Load main models
Popularity.load_to_cache()
TensorCoFi.load_to_cache()
if "recommendation.language" in settings.INSTALLED_APPS:
from recommendation.language.models import Region
Region.load_to_cache()
if "recommendation.diversity" in settings.INSTALLED_APPS:
from recommendation.diversity.models import ItemGenre, Genre
Genre.load_to_cache()
ItemGenre.load_to_cache()
def setup_class(cls, *args, **kwargs):
"""
Put elements in db
"""
for genre in GENRES:
Genre.objects.create(**genre)
for app in ITEMS:
item = Item.objects.create(name=app["name"], external_id=app["external_id"])
for genre in app["genres"]:
g = Genre.objects.get(name=genre)
ItemGenre.objects.create(item=item, type=g)
for u in USERS:
user = User.objects.create(external_id=u["external_id"])
for i in u["items"]:
Inventory.objects.create(user=user, item=Item.get_item_by_external_id(i))
Genre.load_to_cache()
ItemGenre.load_to_cache()
def setup_class(cls, *args, **kwargs):
"""
Put elements in db
"""
for genre in GENRES:
Genre.objects.create(**genre)
for app in ITEMS:
item = Item.objects.create(name=app["name"],
external_id=app["external_id"])
for genre in app["genres"]:
g = Genre.objects.get(name=genre)
ItemGenre.objects.create(item=item, type=g)
for u in USERS:
user = User.objects.create(external_id=u["external_id"])
for i in u["items"]:
Inventory.objects.create(user=user,
item=Item.get_item_by_external_id(i))
Genre.load_to_cache()
ItemGenre.load_to_cache()
def __init__(self, items, size, user, alpha_constant, lambda_constant):
number_items = len(items)
user_items = user.owned_items
user_genres = ItemGenre.genre_in((item for item in user_items.values()))
user_items_count = len(user_items)
self.counter = {}
for genre_id in Genre.get_all_genres():
genre = Genre.get_genre_by_id(genre_id)
try:
p_global = genre.count_items / float(number_items)
except ZeroDivisionError:
p_global = 0.
try:
p_local = user_genres.get(genre, 0.) / float(user_items_count)
except ZeroDivisionError:
p_local = 0.
self.counter[genre.pk] = int(weighted_p(p_global, p_local, alpha_constant) * size)
def setup_class(cls, *args, **kwargs):
"""
Put elements in db
"""
path = resource_filename(recommendation.__name__, "/")
fill.FillTool({"items": True, "--mozilla": True, "prod": True}).load()
fill.FillTool({"users": True, "--mozilla": True, "<path>": path+"data/user"}).load()
modelcrafter.main("train", "popularity")
modelcrafter.main("train", "tensorcofi")
# Load user and items
Item.load_to_cache()
User.load_to_cache()
# Load main models
Popularity.load_to_cache()
TensorCoFi.load_to_cache()
Locale.load_to_cache()
Region.load_to_cache()
Genre.load_to_cache()
cls.client = Client()
def __init__(self, items, size, user, alpha_constant, lambda_constant):
number_items = len(items)
user_items = user.owned_items
user_genres = ItemGenre.genre_in(
(item for item in user_items.values()))
user_items_count = len(user_items)
self.counter = {}
for genre_id in Genre.get_all_genres():
genre = Genre.get_genre_by_id(genre_id)
try:
p_global = genre.count_items / float(number_items)
except ZeroDivisionError:
p_global = 0.
try:
p_local = user_genres.get(genre, 0.) / float(user_items_count)
except ZeroDivisionError:
p_local = 0.
self.counter[genre.pk] = int(
weighted_p(p_global, p_local, alpha_constant) * size)
def get_genres(genres_names):
"""
Get categories from database and create the ones that don't exist.
:param genres_names:
:return: A dict with Genres mapped to their name
"""
genres = {genre.name: genre for genre in Genre.objects.filter(name__in=genres_names)}
if len(genres) != len(genres_names):
new_genres = {}
for genre_name in genres_names:
if genre_name not in genres:
new_genres[genre_name] = Genre(name=genre_name)
Genre.objects.bulk_create(new_genres.values())
for genre in Genre.objects.filter(name__in=new_genres):
genres[genre.name] = genre
return genres
application = get_wsgi_application()
from django.conf import settings
from recommendation.models import Item, User, TensorCoFi, Popularity
# Load user and items
Item.load_to_cache()
User.load_to_cache()
# Load main models
Popularity.load_to_cache()
TensorCoFi.load_to_cache()
if "recommendation.language" in settings.INSTALLED_APPS:
from recommendation.language.models import Locale, Region
Locale.load_to_cache()
Region.load_to_cache()
#if "recommendation.simple_logging" in recommendation.settings.INSTALLED_APPS:
# print("Loading logs to cache...")
# from recommendation.simple_logging.models import LogEntry
# LogEntry.load_to_cache()
# print("done!")
if "recommendation.diversity" in settings.INSTALLED_APPS:
from recommendation.diversity.models import ItemGenre, Genre
Genre.load_to_cache()
ItemGenre.load_to_cache()
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
from django.conf import settings
from recommendation.models import Item, User, TensorCoFi, Popularity
# Load user and items
Item.load_to_cache()
User.load_to_cache()
# Load main models
Popularity.load_to_cache()
TensorCoFi.load_to_cache()
if "recommendation.language" in settings.INSTALLED_APPS:
from recommendation.language.models import Locale, Region
Locale.load_to_cache()
Region.load_to_cache()
#if "recommendation.simple_logging" in recommendation.settings.INSTALLED_APPS:
# print("Loading logs to cache...")
# from recommendation.simple_logging.models import LogEntry
# LogEntry.load_to_cache()
# print("done!")
if "recommendation.diversity" in settings.INSTALLED_APPS:
from recommendation.diversity.models import ItemGenre, Genre
Genre.load_to_cache()
ItemGenre.load_to_cache()
