def check(self, key):
group_id = r.get('apikey:%s' % key)
if not group_id:
raise BadKeyError, 'Key does not exist'
group_info = r.get('apikeygroup:%s' % group_id)
if not group_info:
raise BadKeyError, 'Key does not belong to a valid group'
self.max_per_day, self.max_per_hour, self.max_per_minute, \
self.max_per_5_second_burst = map(int, group_info.split(':'))
return super(KeyRateLimiter, self).check(key)
def record_win(species, winner, loser):
# We record the win-percentage for everything - what percentage of
# competitions it has been in has it won? We do this on a per-species
# basis to account for photos with multiple species that are great for
# one and bad for the other.
winner_times_seen = r.incr(SEEN_KEY % winner)
loser_times_seen = r.incr(SEEN_KEY % loser)
winner_times_won = r.incr(WON_KEY % winner)
loser_times_won = r.get(WON_KEY % loser) or 0
winner_score = (
float(winner_times_won) / float(winner_times_seen)
)
loser_score = (
float(loser_times_won) / float(loser_times_seen)
)
# Update scores in the ordered - but ONLY for photos meeting minimum
# viewing requirements
if winner_times_seen >= MIN_VIEWING_REQUIREMENT:
r.zadd(BESTPICS_KEY % species, winner, winner_score)
if loser_times_seen >= MIN_VIEWING_REQUIREMENT:
r.zadd(BESTPICS_KEY % species, loser, loser_score)
return {
'winner_times_seen': winner_times_seen,
'winner_times_won': winner_times_won,
'winner_score': winner_score * 100,
'loser_times_seen': loser_times_seen,
'loser_times_won': loser_times_won,
'loser_score': loser_score * 100,
}
def top_10_for_species(species):
species_key = BESTPICS_KEY % species.pk
pks = r.zrange(species_key, 0, 10, desc=True)
metrics = [
(r.zscore(species_key, pk) or 0, r.get(SEEN_KEY % pk) or 0, pk)
for pk in pks
]
# We award win percentage above all - if that's a tie, the one which has
# been in the most matches wins. If that's a tie, the one with the highest
# pk (i.e. the one that was most recently added) wins, to keep the photos
# on the site 'fresh'.
metrics.sort(reverse = True)
photos = Photo.objects.in_bulk(pks)
results = []
for score, matches, pk in metrics:
photo = photos[pk]
photo.bestpic_score = score * 100
photo.bestpic_matches = matches
results.append(photo)
return results
def check_token(token):
return r.get(token) is not None
