pyzmq

I want to limit the amount of memory consumed by my ZeroMQ message queues in a Python application. I know that setting the high-water mark will limit the amount that will be queued on the sender side, but is there a way to control how much will be queued on the receiver side? The Python ZeroMQ binding seems to have it set at unlimited. My test scenario: I have two python terminals that I am using for testing. One is the receiver: Python 2.5.1 (r251:54863, Aug 25 2008, 20:50:04) [GCC 4.1.2 20071124 (Red Hat 4.1.2-42)] on linux2 Type "help", "copyright", "credits" or "license" for more

This code will raise Resource temporarily unavailable when call with NOBLOCK: context = zmq.Context() sender = context.socket(zmq.PUSH) sender.bind('tcp://*:15556') sender.send('KeEpAliv', zmq.NOBLOCK) # this line will throw exception #sender.send('KeEpAliv') # this line will ok After read the docs , I found no hints for this. but docs for recv explained this flag. Python wrappers raise zmq.error.Again if the underlying C API returns EAGAIN . Now, you should follow to zmq_send documentation, which states: ZMQ_NOBLOCK Specifies that the operation should be performed in non-blocking mode. If the

According to the ZeroMQ documentation a pub socket is supposed to drop messages once the number of queued messages reaches the high-water mark. This doesn't seem to work in the following example (and yes I do set the hwm before bind/connect): import time import pickle from threading import Thread import zmq ctx = zmq.Context() def pub_thread(): pub = ctx.socket(zmq.PUB) pub.set_hwm(2) pub.bind('tcp://*:5555') i = 0 while True: # Send message every 100ms time.sleep(0.1) pub.send_string("test", zmq.SNDMORE) pub.send_pyobj(i) i += 1 def sub_thread(): sub = ctx.socket(zmq.SUB) sub.subscribe("test"

In experimenting with the ZeroMQ Push/Pull (what they call Pipeline ) socket type, I'm having difficulty understanding the utility of this pattern. It's billed as a "load-balancer". Given a single server sending tasks to a number of workers, Push/Pull will evenly hand out the tasks between all the clients. 3 clients and 30 tasks, each client gets 10 tasks: client1 gets tasks 1, 4, 7,... client2, 2, 5,... and so on. Fair enough. Literally. However, in practice there is often a non-homogeneous mix of task complexity or client compute resources (or availability), then this pattern breaks badly.

I would like to run an IPython instance on one machine and connect to it (over LAN) from a different process (to run some python commands). I understand that it is possible with zmq : http://ipython.org/ipython-doc/dev/development/ipythonzmq.html . However, I can not find documentation on how to do it and whether it is even possible yet. Any help would be appreciated! EDIT I would like to be able to connect to IPython kernel instance and send it python commands. However, this should not be done via a graphic tool (qtconsole) , but I want to be able to connect to that kernel instance from