Memory leak using AsynCommandGenerator in pysnmp 4.3.2 about pysnmp HOT 4 CLOSED

Have you been able to figure out, with the memory_profiler library, what objects are leaking?

Do you run your code in multiple threads?

So far I do not see obvious issues with your pysnmp code, however I have a few suggestions:

• switch to pysnmp hlapi followed by SnmpEngine instance unloading to free up resources
• use a single persistent SnmpEngine instance for all your SNMP queries -- not only it would be more efficient, it might work around possible bugs causing memory leak

from pysnmp.

Can you please elaborate on this answer? How exactly would I do "SnmpEngine instance unloading to free up resources"? Do you just mean that I should call

del snmpEngine

after I use it? Or is it more involved than that?

Yes we run the code in multiple threads.

from pysnmp.

Let me revise my original answer then. Assuming you are calling SNMPGet from a thread and you are not doing SNMP I/O asynchronously, my suggestion is to use something like this:

from pysnmp.hlapi import *
from pysnmp.hlapi.lcd import CommandGeneratorLcdConfigurator

class SNMPGet:
    """Instance of this class must be thread-local, not shared between threads."""
    def __init__(self, *):
        self._snmpEngine = SnmpEngine()

    def _internal_execute(self, tmp_object_identifiers):
        gen =  getCmd(self._snmpEngine,
                      CommunityData('public'),
                      UdpTransportTarget(('demo.snmplabs.com', 161)),
                      ContextData(),
                      *[ObjectType(ObjectIdentity(oid)) for oid in tmp_identifiers])

        errorIndication, errorStatus, errorIndex, varBinds = next(gen)

    def cleanup(self):
        """Running SnmpEngine instance against ever increasing set of targets may grow memory.
            To drop SnmpEngine's caches you can periodically call this method. The backside is
            slight drop in performance as hot caches will have to be repopulated.
        """
        CommandGeneratorLcdConfigurator.unconfigure(self._snmpEngine)

As a side note, if you are fetching many OIDs from many targets, async I/O may give you better performance compared to MT one.

from pysnmp.

If the leak shows up with the later pysnmp versions -- please reopen this issue. Thank you!

from pysnmp.