def calc_rising():
sr_count = count.get_counts()
link_count = dict((k, v[0]) for k,v in sr_count.iteritems())
link_names = Link._by_fullname(sr_count.keys(), data=True)
#max is half the average of the top 10 counts
counts = link_count.values()
counts.sort(reverse=True)
maxcount = sum(counts[:10]) / 20
#prune the list
rising = [(n, link_names[n].sr_id)
for n in link_names.keys() if link_count[n] < maxcount]
cur_time = datetime.now(g.tz)
def score(pair):
name = pair[0]
link = link_names[name]
hours = (cur_time - link._date).seconds / 3600 + 1
return float(link._ups) / (max(link_count[name], 1) * hours)
def r(x):
return 1 if x > 0 else -1 if x < 0 else 0
rising.sort(lambda x, y: r(score(y) - score(x)))
return rising
def cached_organic_links(username):
user = Account._by_name(username)
sr_count = count.get_counts()
srs = Subreddit.user_subreddits(user)
link_names = filter(lambda n: sr_count[n][1] in srs, sr_count.keys())
link_names.sort(key = lambda n: sr_count[n][0])
builder = IDBuilder(link_names, num = 30, skip = True, keep_fn = keep_link)
links = builder.get_items()[0]
cache.set(pos_key(user), 0)
return [l._fullname for l in links]