eventlet is slower than sync pymongo queries?

async_pymongo.py

# > time python async_pymongo.py
# 
# real  0m0.511s
# user  0m0.220s
# sys 0m0.170s

import pymongo
import eventlet
eventlet.monkey_patch()

POOL_SIZE = 10

class SocketWrapper(object):
  __slots__ = ('__pool','__sock')
  def __init__(self,pool,sock):
    self.__pool = pool
    self.__sock = sock
  def __getattr__(self,name):
    return getattr(self.__sock,name)
  def __del__(self):
    self.__pool.sockets.put(self.__sock)
    del self.__pool
    del self.__sock

class Pool(object):
  def __init__(self,socket_factory,max_pool_size=POOL_SIZE):
    self.socket_factory = socket_factory
    self.max_pool_size = min(max_pool_size,POOL_SIZE)
    self.sockets = None
  def socket(self):
    if not self.sockets:
      self.initialize()
    return SocketWrapper(self,self.sockets.get())
  def initialize(self):
    self.sockets = Queue(self.max_pool_size)
    for i in range(self.max_pool_size):
      sock = self.socket_factory()
      self.sockets.put(sock)
  def return_socket(self):
    pass

pymongo.connection._Pool = Pool

db = pymongo.Connection().test

def do(*args, **kwargs):
  db.test2.insert(*args)

pool = eventlet.GreenPool(size=1000)
pile = eventlet.GreenPile(pool)
[pool.spawn_n(do, {'num': i}) for i in xrange(1000)]
pool.waitall()

sync_pymongo.py

# > time python sync_pymongo.py
# 
# real  0m0.356s
# user  0m0.120s
# sys 0m0.150s

import pymongo

c = pymongo.Connection()
db = c.test

for i in xrange(1000):
    db.test2.insert({'num': i})

Did you ever get anywhere with this?

My suspicion is that the overhead of eventlet is actually more than the cost of an individual insert when doing it against a local server without any other load hitting it and no indices to worry about.

yep exactly. if the mongo server was on a big 32 core box I bet the results would be different. then it (mongo) would be able to do the work in parallel.