This chapter focuses on how to use PB to pass complex types (specifically class instances) to and from a remote process. The first section is on simply copying the contents of an object to a remote process (pb.Copyable ). The second covers how to copy those contents once, then update them later when they change (Cacheable ).
From the previous chapter , you’ve seen how to pass basic types to a remote process, by using them in the arguments or return values of a callRemote function. However, if you’ve experimented with it, you may have discovered problems when trying to pass anything more complicated than a primitive int/list/dict/string type, or another pb.Referenceable object. At some point you want to pass entire objects between processes, instead of having to reduce them down to dictionaries on one end and then re-instantiating them on the other.
The most obvious and straightforward way to send an object to a remote process is with something like the following code. It also happens that this code doesn’t work, as will be explained below.
class LilyPond:
def __init__(self, frogs):
self.frogs = frogs
pond = LilyPond(12)
ref.callRemote("sendPond", pond)
If you try to run this, you might hope that a suitable remote end which implements the remote_sendPond method would see that method get invoked with an instance from the LilyPond class. But instead, you’ll encounter the dreaded InsecureJelly exception. This is Twisted’s way of telling you that you’ve violated a security restriction, and that the receiving end refuses to accept your object.
What’s the big deal? What’s wrong with just copying a class into another process’ namespace?
Reversing the question might make it easier to see the issue: what is the problem with accepting a stranger’s request to create an arbitrary object in your local namespace? The real question is how much power you are granting them: what actions can they convince you to take on the basis of the bytes they are sending you over that remote connection.
Objects generally represent more power than basic types like strings and dictionaries because they also contain (or reference) code, which can modify other data structures when executed. Once previously-trusted data is subverted, the rest of the program is compromised.
The built-in Python “batteries included” classes are relatively tame, but you still wouldn’t want to let a foreign program use them to create arbitrary objects in your namespace or on your computer. Imagine a protocol that involved sending a file-like object with a read() method that was supposed to used later to retrieve a document. Then imagine what if that object were created with os.fdopen("~/.gnupg/secring.gpg") . Or an instance of telnetlib.Telnet("localhost", "chargen") .
Classes you’ve written for your own program are likely to have far more power. They may run code during __init__ , or even have special meaning simply because of their existence. A program might have User objects to represent user accounts, and have a rule that says all User objects in the system are referenced when authorizing a login session. (In this system, User.__init__ would probably add the object to a global list of known users). The simple act of creating an object would give access to somebody. If you could be tricked into creating a bad object, an unauthorized user would get access.
So object creation needs to be part of a system’s security design. The dotted line between “trusted inside” and “untrusted outside” needs to describe what may be done in response to outside events. One of those events is the receipt of an object through a PB remote procedure call, which is a request to create an object in your “inside” namespace. The question is what to do in response to it. For this reason, you must explicitly specify what remote classes will be accepted, and how their local representatives are to be created.
Another basic question to answer before we can do anything useful with an incoming serialized object is: what class should we create? The simplistic answer is to create the “same kind” that was serialized on the sender’s end of the wire, but this is not as easy or as straightforward as you might think. Remember that the request is coming from a different program, using a potentially different set of class libraries. In fact, since PB has also been implemented in Java, Emacs-Lisp, and other languages, there’s no guarantee that the sender is even running Python! All we know on the receiving end is a list of two things which describe the instance they are trying to send us: the name of the class, and a representation of the contents of the object.
PB lets you specify the mapping from remote class names to local classes with the setUnjellyableForClass function [1] .
This function takes a remote/sender class reference (either the fully-qualified name as used by the sending end, or a class object from which the name can be extracted), and a local/recipient class (used to create the local representation for incoming serialized objects). Whenever the remote end sends an object, the class name that they transmit is looked up in the table controlled by this function. If a matching class is found, it is used to create the local object. If not, you get the InsecureJelly exception.
In general you expect both ends to share the same codebase: either you control the program that is running on both ends of the wire, or both programs share some kind of common language that is implemented in code which exists on both ends. You wouldn’t expect them to send you an object of the MyFooziWhatZit class unless you also had a definition for that class. So it is reasonable for the Jelly layer to reject all incoming classes except the ones that you have explicitly marked with setUnjellyableForClass . But keep in mind that the sender’s idea of a User object might differ from the recipient’s, either through namespace collisions between unrelated packages, version skew between nodes that haven’t been updated at the same rate, or a malicious intruder trying to cause your code to fail in some interesting or potentially vulnerable way.
Ok, enough of this theory. How do you send a fully-fledged object from one side to the other?
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.spread import pb, jelly
from twisted.python import log
from twisted.internet import reactor
class LilyPond:
def setStuff(self, color, numFrogs):
self.color = color
self.numFrogs = numFrogs
def countFrogs(self):
print "%d frogs" % self.numFrogs
class CopyPond(LilyPond, pb.Copyable):
pass
class Sender:
def __init__(self, pond):
self.pond = pond
def got_obj(self, remote):
self.remote = remote
d = remote.callRemote("takePond", self.pond)
d.addCallback(self.ok).addErrback(self.notOk)
def ok(self, response):
print "pond arrived", response
reactor.stop()
def notOk(self, failure):
print "error during takePond:"
if failure.type == jelly.InsecureJelly:
print " InsecureJelly"
else:
print failure
reactor.stop()
return None
def main():
from copy_sender import CopyPond # so it's not __main__.CopyPond
pond = CopyPond()
pond.setStuff("green", 7)
pond.countFrogs()
# class name:
print ".".join([pond.__class__.__module__, pond.__class__.__name__])
sender = Sender(pond)
factory = pb.PBClientFactory()
reactor.connectTCP("localhost", 8800, factory)
deferred = factory.getRootObject()
deferred.addCallback(sender.got_obj)
reactor.run()
if __name__ == '__main__':
main()
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
"""
PB copy receiver example.
This is a Twisted Application Configuration (tac) file. Run with e.g.
twistd -ny copy_receiver.tac
See the twistd(1) man page or
http://twistedmatrix.com/documents/current/howto/application for details.
"""
import sys
if __name__ == '__main__':
print __doc__
sys.exit(1)
from twisted.application import service, internet
from twisted.internet import reactor
from twisted.spread import pb
from copy_sender import LilyPond, CopyPond
from twisted.python import log
#log.startLogging(sys.stdout)
class ReceiverPond(pb.RemoteCopy, LilyPond):
pass
pb.setUnjellyableForClass(CopyPond, ReceiverPond)
class Receiver(pb.Root):
def remote_takePond(self, pond):
print " got pond:", pond
pond.countFrogs()
return "safe and sound" # positive acknowledgement
def remote_shutdown(self):
reactor.stop()
application = service.Application("copy_receiver")
internet.TCPServer(8800, pb.PBServerFactory(Receiver())).setServiceParent(
service.IServiceCollection(application))
The sending side has a class called LilyPond . To make this eligible for transport through callRemote (either as an argument, a return value, or something referenced by either of those [like a dictionary value]), it must inherit from one of the four Serializable classes. In this section, we focus on Copyable . The copyable subclass of LilyPond is called CopyPond . We create an instance of it and send it through callRemote as an argument to the receiver’s remote_takePond method. The Jelly layer will serialize (“jelly” ) that object as an instance with a class name of”copy_sender.CopyPond” and some chunk of data that represents the object’s state. pond.__class__.__module__ and pond.__class__.__name__ are used to derive the class name string. The object’s getStateToCopy method is used to get the state: this is provided by pb.Copyable , and the default just retrieves self.__dict__ . This works just like the optional __getstate__ method used by pickle . The pair of name and state are sent over the wire to the receiver.
The receiving end defines a local class named ReceiverPond to represent incoming LilyPond instances. This class derives from the sender’s LilyPond class (with a fully-qualified name of copy_sender.LilyPond ), which specifies how we expect it to behave. We trust that this is the same LilyPond class as the sender used. (At the very least, we hope ours will be able to accept a state created by theirs). It also inherits from pb.RemoteCopy , which is a requirement for all classes that act in this local-representative role (those which are given to the second argument of setUnjellyableForClass ). RemoteCopy provides the methods that tell the Jelly layer how to create the local object from the incoming serialized state.
Then setUnjellyableForClass is used to register the two classes. This has two effects: instances of the remote class (the first argument) will be allowed in through the security layer, and instances of the local class (the second argument) will be used to contain the state that is transmitted when the sender serializes the remote object.
When the receiver unserializes (“unjellies” ) the object, it will create an instance of the local ReceiverPond class, and hand the transmitted state (usually in the form of a dictionary) to that object’s setCopyableState method. This acts just like the __setstate__ method that pickle uses when unserializing an object. getStateToCopy /setCopyableState are distinct from __getstate__ /__setstate__ to allow objects to be persisted (across time) differently than they are transmitted (across [memory]space).
When this is run, it produces the following output:
[-] twisted.spread.pb.PBServerFactory starting on 8800
[-] Starting factory <twisted.spread.pb.PBServerFactory instance at
0x406159cc>
[Broker,0,127.0.0.1] got pond: <__builtin__.ReceiverPond instance at
0x406ec5ec>
[Broker,0,127.0.0.1] 7 frogs
$ ./copy_sender.py
7 frogs
copy_sender.CopyPond
pond arrived safe and sound
Main loop terminated.
$
By overriding getStateToCopy and setCopyableState , you can control how the object is transmitted over the wire. For example, you might want perform some data-reduction: pre-compute some results instead of sending all the raw data over the wire. Or you could replace references to a local object on the sender’s side with markers before sending, then upon receipt replace those markers with references to a receiver-side proxy that could perform the same operations against a local cache of data.
Another good use for getStateToCopy is to implement “local-only” attributes: data that is only accessible by the local process, not to any remote users. For example, a .password attribute could be removed from the object state before sending to a remote system. Combined with the fact that Copyable objects return unchanged from a round trip, this could be used to build a challenge-response system (in fact PB does this with pb.Referenceable objects to implement authorization as described here ).
Whatever getStateToCopy returns from the sending object will be serialized and sent over the wire; setCopyableState gets whatever comes over the wire and is responsible for setting up the state of the object it lives in.
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.spread import pb
class FrogPond:
def __init__(self, numFrogs, numToads):
self.numFrogs = numFrogs
self.numToads = numToads
def count(self):
return self.numFrogs + self.numToads
class SenderPond(FrogPond, pb.Copyable):
def getStateToCopy(self):
d = self.__dict__.copy()
d['frogsAndToads'] = d['numFrogs'] + d['numToads']
del d['numFrogs']
del d['numToads']
return d
class ReceiverPond(pb.RemoteCopy):
def setCopyableState(self, state):
self.__dict__ = state
def count(self):
return self.frogsAndToads
pb.setUnjellyableForClass(SenderPond, ReceiverPond)
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.spread import pb, jelly
from twisted.python import log
from twisted.internet import reactor
from copy2_classes import SenderPond
class Sender:
def __init__(self, pond):
self.pond = pond
def got_obj(self, obj):
d = obj.callRemote("takePond", self.pond)
d.addCallback(self.ok).addErrback(self.notOk)
def ok(self, response):
print "pond arrived", response
reactor.stop()
def notOk(self, failure):
print "error during takePond:"
if failure.type == jelly.InsecureJelly:
print " InsecureJelly"
else:
print failure
reactor.stop()
return None
def main():
pond = SenderPond(3, 4)
print "count %d" % pond.count()
sender = Sender(pond)
factory = pb.PBClientFactory()
reactor.connectTCP("localhost", 8800, factory)
deferred = factory.getRootObject()
deferred.addCallback(sender.got_obj)
reactor.run()
if __name__ == '__main__':
main()
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.application import service, internet
from twisted.internet import reactor
from twisted.spread import pb
import copy2_classes # needed to get ReceiverPond registered with Jelly
class Receiver(pb.Root):
def remote_takePond(self, pond):
print " got pond:", pond
print " count %d" % pond.count()
return "safe and sound" # positive acknowledgement
def remote_shutdown(self):
reactor.stop()
application = service.Application("copy_receiver")
internet.TCPServer(8800, pb.PBServerFactory(Receiver())).setServiceParent(
service.IServiceCollection(application))
In this example, the classes are defined in a separate source file, which also sets up the binding between them. The SenderPond and ReceiverPond are unrelated save for this binding: they happen to implement the same methods, but use different internal instance variables to accomplish them.
The recipient of the object doesn’t even have to import the class definition into their namespace. It is sufficient that they import the class definition (and thus execute the setUnjellyableForClass statement). The Jelly layer remembers the class definition until a matching object is received. The sender of the object needs the definition, of course, to create the object in the first place.
When run, the copy2 example emits the following:
$ twistd -n -y copy2_receiver.py
[-] twisted.spread.pb.PBServerFactory starting on 8800
[-] Starting factory <twisted.spread.pb.PBServerFactory instance at
0x40604b4c>
[Broker,0,127.0.0.1] got pond: <copy2_classes.ReceiverPond instance at
0x406eb2ac>
[Broker,0,127.0.0.1] count 7
$ ./copy2_sender.py
count 7
pond arrived safe and sound
Main loop terminated.
Sometimes the object you want to send to the remote process is big and slow. “big” means it takes a lot of data (storage, network bandwidth, processing) to represent its state. “slow” means that state doesn’t change very frequently. It may be more efficient to send the full state only once, the first time it is needed, then afterwards only send the differences or changes in state whenever it is modified. The pb.Cacheable class provides a framework to implement this.
pb.Cacheable is derived from pb.Copyable , so it is based upon the idea of an object’s state being captured on the sending side, and then turned into a new object on the receiving side. This is extended to have an object “publishing” on the sending side (derived from pb.Cacheable ), matched with one”observing” on the receiving side (derived from pb.RemoteCache ).
To effectively use pb.Cacheable , you need to isolate changes to your object into accessor functions (specifically “setter” functions). Your object needs to get control every single time some attribute is changed [3] .
You derive your sender-side class from pb.Cacheable , and you add two methods: getStateToCacheAndObserveFor and stoppedObserving . The first is called when a remote caching reference is first created, and retrieves the data with which the cache is first filled. It also provides an object called the “observer” [4] that points at that receiver-side cache. Every time the state of the object is changed, you give a message to the observer, informing them of the change. The other method, stoppedObserving , is called when the remote cache goes away, so that you can stop sending updates.
On the receiver end, you make your cache class inherit from pb.RemoteCache , and implement the setCopyableState as you would for a pb.RemoteCopy object. In addition, you must implement methods to receive the updates sent to the observer by the pb.Cacheable : these methods should have names that start with observe_ , and match the callRemote invocations from the sender side just as the usual remote_* and perspective_* methods match normal callRemote calls.
The first time a reference to the pb.Cacheable object is sent to any particular recipient, a sender-side Observer will be created for it, and the getStateToCacheAndObserveFor method will be called to get the current state and register the Observer. The state which that returns is sent to the remote end and turned into a local representation using setCopyableState just like pb.RemoteCopy , described above (in fact it inherits from that class).
After that, your “setter” functions on the sender side should call callRemote on the Observer, which causes observe_* methods to run on the receiver, which are then supposed to update the receiver-local (cached) state.
When the receiver stops following the cached object and the last reference goes away, the pb.RemoteCache object can be freed. Just before it dies, it tells the sender side it no longer cares about the original object. When that reference count goes to zero, the Observer goes away and the pb.Cacheable object can stop announcing every change that takes place. The stoppedObserving method is used to tell the pb.Cacheable that the Observer has gone away.
With the pb.Cacheable and pb.RemoteCache classes in place, bound together by a call to pb.setUnjellyableForClass , all that remains is to pass a reference to your pb.Cacheable over the wire to the remote end. The corresponding pb.RemoteCache object will automatically be created, and the matching methods will be used to keep the receiver-side slave object in sync with the sender-side master object.
Here is a complete example, in which the MasterDuckPond is controlled by the sending side, and the SlaveDuckPond is a cache that tracks changes to the master:
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.spread import pb
class MasterDuckPond(pb.Cacheable):
def __init__(self, ducks):
self.observers = []
self.ducks = ducks
def count(self):
print "I have [%d] ducks" % len(self.ducks)
def addDuck(self, duck):
self.ducks.append(duck)
for o in self.observers: o.callRemote('addDuck', duck)
def removeDuck(self, duck):
self.ducks.remove(duck)
for o in self.observers: o.callRemote('removeDuck', duck)
def getStateToCacheAndObserveFor(self, perspective, observer):
self.observers.append(observer)
# you should ignore pb.Cacheable-specific state, like self.observers
return self.ducks # in this case, just a list of ducks
def stoppedObserving(self, perspective, observer):
self.observers.remove(observer)
class SlaveDuckPond(pb.RemoteCache):
# This is a cache of a remote MasterDuckPond
def count(self):
return len(self.cacheducks)
def getDucks(self):
return self.cacheducks
def setCopyableState(self, state):
print " cache - sitting, er, setting ducks"
self.cacheducks = state
def observe_addDuck(self, newDuck):
print " cache - addDuck"
self.cacheducks.append(newDuck)
def observe_removeDuck(self, deadDuck):
print " cache - removeDuck"
self.cacheducks.remove(deadDuck)
pb.setUnjellyableForClass(MasterDuckPond, SlaveDuckPond)
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.spread import pb, jelly
from twisted.python import log
from twisted.internet import reactor
from cache_classes import MasterDuckPond
class Sender:
def __init__(self, pond):
self.pond = pond
def phase1(self, remote):
self.remote = remote
d = remote.callRemote("takePond", self.pond)
d.addCallback(self.phase2).addErrback(log.err)
def phase2(self, response):
self.pond.addDuck("ugly duckling")
self.pond.count()
reactor.callLater(1, self.phase3)
def phase3(self):
d = self.remote.callRemote("checkDucks")
d.addCallback(self.phase4).addErrback(log.err)
def phase4(self, dummy):
self.pond.removeDuck("one duck")
self.pond.count()
self.remote.callRemote("checkDucks")
d = self.remote.callRemote("ignorePond")
d.addCallback(self.phase5)
def phase5(self, dummy):
d = self.remote.callRemote("shutdown")
d.addCallback(self.phase6)
def phase6(self, dummy):
reactor.stop()
def main():
master = MasterDuckPond(["one duck", "two duck"])
master.count()
sender = Sender(master)
factory = pb.PBClientFactory()
reactor.connectTCP("localhost", 8800, factory)
deferred = factory.getRootObject()
deferred.addCallback(sender.phase1)
reactor.run()
if __name__ == '__main__':
main()
#!/usr/bin/env python
# Copyright (c) Twisted Matrix Laboratories.
# See LICENSE for details.
from twisted.application import service, internet
from twisted.internet import reactor
from twisted.spread import pb
import cache_classes
class Receiver(pb.Root):
def remote_takePond(self, pond):
self.pond = pond
print "got pond:", pond # a DuckPondCache
self.remote_checkDucks()
def remote_checkDucks(self):
print "[%d] ducks: " % self.pond.count(), self.pond.getDucks()
def remote_ignorePond(self):
# stop watching the pond
print "dropping pond"
# gc causes __del__ causes 'decache' msg causes stoppedObserving
self.pond = None
def remote_shutdown(self):
reactor.stop()
application = service.Application("copy_receiver")
internet.TCPServer(8800, pb.PBServerFactory(Receiver())).setServiceParent(
service.IServiceCollection(application))
When run, this example emits the following:
$ twistd -n -y cache_receiver.py
[-] twisted.spread.pb.PBServerFactory starting on 8800
[-] Starting factory <twisted.spread.pb.PBServerFactory instance at
0x40615acc>
[Broker,0,127.0.0.1] cache - sitting, er, setting ducks
[Broker,0,127.0.0.1] got pond: <cache_classes.SlaveDuckPond instance at
0x406eb5ec>
[Broker,0,127.0.0.1] [2] ducks: ['one duck', 'two duck']
[Broker,0,127.0.0.1] cache - addDuck
[Broker,0,127.0.0.1] [3] ducks: ['one duck', 'two duck', 'ugly duckling']
[Broker,0,127.0.0.1] cache - removeDuck
[Broker,0,127.0.0.1] [2] ducks: ['two duck', 'ugly duckling']
[Broker,0,127.0.0.1] dropping pond
$ ./cache_sender.py
I have [2] ducks
I have [3] ducks
I have [2] ducks
Main loop terminated.
Points to notice:
There is one Observer for each remote program that holds an active reference. Multiple references inside the same program don’t matter: the serialization layer notices the duplicates and does the appropriate reference counting [5] .
Multiple Observers need to be kept in a list, and all of them need to be updated when something changes. By sending the initial state at the same time as you add the observer to the list, in a single atomic action that cannot be interrupted by a state change, you insure that you can send the same status update to all the observers.
The observer.callRemote calls can still fail. If the remote side has disconnected very recently and stoppedObserving has not yet been called, you may get a DeadReferenceError . It is a good idea to add an errback to those callRemote s to throw away such an error. This is a useful idiom:
observer.callRemote('foo', arg).addErrback(lambda f: None)
Footnotes
| [1] | Note that, in this context, “unjelly” is a verb with the opposite meaning of “jelly” . The verb “to jelly” means to serialize an object or data structure into a sequence of bytes (or other primitive transmittable/storable representation), while “to unjelly” means to unserialize the bytestream into a live object in the receiver’s memory space. “Unjellyable” is a noun, (not an adjective), referring to the the class that serves as a destination or recipient of the unjellying process. “A is unjellyable into B” means that a serialized representation A (of some remote object) can be unserialized into a local object of type B. It is these objects “B” that are the “Unjellyable” second argument of the setUnjellyableForClass function. In particular, “unjellyable” does not mean “cannot be jellied” . Unpersistable means “not persistable” , but “unjelly” , “unserialize” , and “unpickle” mean to reverse the operations of “jellying” , “serializing” , and “pickling” . |
| [2] | pb.RemoteCopy is actually defined in twisted.spread.flavors , but pb.RemoteCopy is the preferred way to access it |
| [3] | Of course you could be clever and add a hook to __setattr__ , along with magical change-announcing subclasses of the usual builtin types, to detect changes that result from normal “=” set operations. The semi-magical “property attributes” that were introduced in Python 2.2 could be useful too. The result might be hard to maintain or extend, though. |
| [4] | This is actually a RemoteCacheObserver , but it isn’t very useful to subclass or modify, so simply treat it as a little demon that sits in your pb.Cacheable class and helps you distribute change notifications. The only useful thing to do with it is to run its callRemote method, which acts just like a normal pb.Referenceable ‘s method of the same name. |
| [5] | This applies to multiple references through the same Broker . If you’ve managed to make multiple TCP connections to the same program, you deserve whatever you get. |