Although PySNMP is already a mature software and it is being used at many places, the ultimate goal of the project is to implement most of the useful features that SNMP standards can offer. What follows is a list of most prominent missing features that PySNMP developers are planning to put their hands on in the future.
Built-in MIB parser. PySNMP uses a data model of its own to work with information contained in MIB files. To convert ASN.1-based MIB texts into Python modules, an off-line, third-party tool is employed. As it turns out, this approach has two major drawback: one is that PySNMP users may need to pre-process MIB texts to use them with their PySNMP-based applications. Another is that LibSMI’s Python driver seems to miss some information carried by MIBs. Thus the solution would be to write another MIB parser and code generator which would produce PySNMP compliant Python code right from MIB text files all by itself.
Done: see PySMI project in conjuction with the latest PySNMP codebase.
Reverse MIB index. The variable-bindings received by the system whilst in Manager role could be post-processed using the information kept in MIB files to include human-friendly OIDs names, tables indices and values representation. However, there is currently no provisioning in the PySNMP system for locating and loading up MIB files containing additional information on arbitrary OIDs. So the idea is to maintain an OID-to-MIB index to let PySNMP load relevant MIB automatically on demand.
Stream sockets support. Currently, PySNMP transport subsystem only supports datagram-type network sockets. That covers UDP-over-IPv4 and UDP-over-IPv6. However, SNMP engine can potentially run over stream-oriented protocols what would let it support TCP-over-IPv4, TCP-over-IPv6 and SSL/TSL transports. Neither of these is currently implemented with PySNMP.
AgentX implementation. We anticipate many uses of this. For instance, having AgentX protocol support in pure-Python would let us write AgentX modules in pure-Python and attach them to high-performance Net-SNMP Agent. Or we could build and maintain a fully-featured, stand-alone PySNMP-based Agent so that users would write their own AgentX extensions what would comprise a complete SNMP Agent solution at lesser effort.
A DBMS-based SMI. Currently implemented SMI takes shape of live Python objects that let user hook up his own handler on any existing Managed Object Instance. That’s flexible and working approach in many cases, however sometimes, for instance when Management Instrumentation is inherently DBMS-based, it may be more efficient to move the entire SMI/MIB subsystem into a database. PySNMP engine would talk to it through its simple and well defined SMI API.
Stand-alone PySNMP-based tools¶
SNMP Proxy Forwarder. That would be a stand-alone, application-level proxy service supporting all SNMP versions, multiple network transports, Command and Notification SNMP message types. Its anticipated features include extensive configuration facilities, fine-graned access control and logging.
Done: see SNMP Proxy Forwarder.
SNMP Trap Receiver. We see this application as a simple yet flexible SNMP TRAP collector. It would listen on network sockets of different types receiving SNMP TRAP/INFORM notifications over any SNMP version and putting all the details into a database and possibly triggering external events.
Database backend for SNMP Simulator. We have already built a tool for simulating SNMP Agents based on a snapshot of their Management Instrumentation state. Current implementation uses a plain-text file for keeping and possibly managing the snapshot. Many users of the Simulator software requested a value variation feature to be supported so that simulated Agents would look live, not static. We consider this variation and also dependencies features would be best implemented as a relational database application. So we are planning to put some more efforts into the Simulator project as time permits.
Done: since snmpsim-0.2.4
If you need some particular feature - please, drop us a note . Once we see a greater demand in particular area, we would re-arrange our development resources to meet it sooner.
You could greater speed up the development of particular feature by sponsoring it. Please get back to us to discuss details.
Contributions to the PySNMP source code is greatly appreciated as well. We require contributed code to run with Python 2.4 through the latest Python version (which is 3.3 at the time of this writing). Contributed code will be redistributed under the terms of the same license as PySNMP is.