Вот как я реализовал контейнер токенов с memcache на GAE:
Редактировать: взять (еще один) удар в этом.
Это частично позаимствовано у https://github.com/simonw/ratelimitcache/blob/master/ratelimitcache.py
def throttle(key, rate_count, rate_seconds, tries=3):
'''
returns True if throttled (not enough tokens available) else False
implements token bucket algorithm
'''
client = memcache.Client(CLIENT_ARGS)
for _ in range(tries):
now = int(time.time())
keys = ['%s-%s' % (key, str(now-i)) for i in range(rate_seconds)]
client.add(keys[0], 0, time=rate_seconds+1)
tokens = client.get_multi(keys[1:])
tokens[keys[0]] = client.gets(keys[0])
if sum(tokens.values()) >= rate_count:
return True
if client.cas(keys[0], tokens[keys[0]] + 1, time=rate_seconds+1) != 0:
return False
logging.error('cache contention error')
return True
Вот примеры использования:
def test_that_it_throttles_too_many_requests(self):
burst = 1
interval = 1
assert shared.rate_limit.throttle('test', burst, interval) is False
assert shared.rate_limit.throttle('test', burst, interval) is True
def test_that_it_doesnt_throttle_burst_of_requests(self):
burst = 16
interval = 1
for i in range(burst):
assert shared.rate_limit.throttle('test', burst, interval) is False
time.sleep(interval + 1) # memcache has 1 second granularity
for i in range(burst):
assert shared.rate_limit.throttle('test', burst, interval) is False