def testBook():
g = Goodreads()
book, similar_books = g.getBook('50')
print book.id, book.gid, book.author, book.list_shelves
for shelve in book.list_shelves:
print shelve.shelve, shelve.count, shelve.gid
return
def testBook():
g=Goodreads()
book, similar_books=g.getBook('50')
print book.id, book.gid, book.author, book.list_shelves
for shelve in book.list_shelves:
print shelve.shelve, shelve.count, shelve.gid
return
def testUserFriends():
c=Cassandra()
g=Goodreads(new=False)
user=models.Users(id=uuid4(), gid='3371638', name='Katie')
friends, friendRelation, total=g.getFriends(user)
if(friends is None):
print "Private"
else:
print len(friends), len(friendRelation), total
def testUserFriends():
c = Cassandra()
g = Goodreads(new=False)
user = models.Users(id=uuid4(), gid='3371638', name='Katie')
friends, friendRelation, total = g.getFriends(user)
if (friends is None):
print "Private"
else:
print len(friends), len(friendRelation), total
def retrieve_and_sort_books(languages=None, other=False, other_label='default',
year=None, details=False):
session = GoodreadsSession(api_key, api_secret)
goodreads = Goodreads(session)
goodreads.initialise_user()
books = goodreads.get_books()
arranger = BookArranger(books)
sorted_books = arranger.sort_by_language(languages, other, other_label,
year)
arranger.print_sorted_books_nicely(sorted_books, details)
def retrieve_and_sort_books(languages=None, other=False, other_label='default',
year=None, details=False, shelf='read'):
session = GoodreadsSession(api_key, api_secret)
goodreads = Goodreads(session)
goodreads.initialise_user()
books = goodreads.get_books(shelf)
arranger = BookArranger(books)
sorted_books = arranger.sort_by_language(languages, other, other_label,
year)
arranger.print_sorted_books_nicely(sorted_books, details)
def init():
initialize_logger(os.getcwd())
coloredlogs.install(level='DEBUG')
coloredlogs.ColoredFormatter()
c = Cassandra()
syncTables()
g = Goodreads()
return (c, g)
def testUserReviews(c):
#user=Users(id=uuid4(), gid='902976', name='Katie') #902976 katie, 1085121 Stephanie, 47225465 mio
user = models.Users(id=uuid.uuid4(),
gid=1085121,
name='Simone',
friends_count=1,
small_user=True)
u = c.get_user_if_exsists_or_save(user)
reviewsDict, altready_retrieved = Goodreads().getUserReviews(u)
if (altready_retrieved is False):
c.saveUserReviews(u, reviewsDict)
else:
print "already retrieved"
import logging
from goodreads import Goodreads
from markdown_writer import write_book_to_md
logging.basicConfig(filename="output.log", level=logging.INFO)
if __name__ == "__main__":
logging.info("/**********************START*************************/")
books = Goodreads().retreive_books_from_shelf()
for book in books:
write_book_to_md(book)
logging.info("/**********************COMPLETE*************************/")
def testUser():
Cassandra()
sync_table(models.Users)
g=Goodreads()
u=g.getUser('4134243')
u.save()
def testUser():
Cassandra()
sync_table(models.Users)
g = Goodreads()
u = g.getUser('4134243')
u.save()
def testBookReviews():
Goodreads().getBookReviews('0142437174')
print(f'wall: {time.time() - start}')
f.write(f'wall: {time.time() - start}')
if __name__ == '__main__':
args = config()
devices = list(map(int, args.gpu.split(',')))
n_gpus = len(devices)
# For GCMC based on sample, we require node has its own features.
# Otherwise (node_id is the feature), the model can not scale
dataset = Goodreads(args.data_name,
'cpu',
mix_cpu_gpu=args.mix_cpu_gpu,
use_one_hot_fea=args.use_one_hot_fea,
symm=args.gcn_agg_norm_symm,
test_ratio=args.data_test_ratio,
valid_ratio=args.data_valid_ratio)
print("Loading data finished ...\n")
args.src_in_units = dataset.user_feature_shape[1]
args.dst_in_units = dataset.item_feature_shape[1]
args.rating_vals = dataset.possible_rating_values
# cpu
if devices[0] == -1:
run(0, 0, args, ['cpu'], dataset)
# gpu
elif n_gpus == 1:
run(0, n_gpus, args, devices, dataset)