print
RemoteObj.name prints the attribute 'name' of the remote object 'RemoteObj'). There are a few important points
to keep in mind when you're using this:
RemoteObj.person.address.street) or 'nested' method calls (such as
RemoteObj.person.address.getStreet()): the rule counts for each attribute.When you call object.sub1.sub2 where object is a Pyro proxy to your Pyro server object,
Python processes the statement left-to-right. First Python wants to get the sub1 attribute from
object. So Pyro intercepts a getattr call from Python and the remote Pyro object returns the
sub1 attribute. Unfortunately, this value is an object (i.e. a class instance)! The client receives a
class instance of a class it doesn't know about! (that's the reason it crashes with AttributeError: 'module' object
has no attribute 'SomeClass', when the class of the attribute object is not available on the client).
The easiest way to solve this is to add a delegation method to your Pyro object (something like
getSub2() that returns self.sub1.sub2. Then, don't access the object.sub1.sub2
attribute directly, but get it with object.getSub2(). The other solution is to make the class available
to the client process: put it in a separate module and place the module somewhere the client code has access to (i.e.
it must be able to import it). An explicit import statement is not necessary.
But there is a serious, confusing issue with nested attributes: you will have a local object
instead of the remote object! What's going on: Say you took care of supplying all needed
modules and classes to both server and client. Then you want to access object.sub1.sub2. What you
get is the sub2 attribute of a LOCAL sub1 object instance! This is no problem when you just want to
read the value, but it is a huge problem when you want to perform some actions on this attribute, or change the
value! This will be performed in your client, not in the server object!
Explanation: as pointed out above, Python searches for sub1 in object. Because Pyro
intercepts the getattr call, you get the remote sub1 object. Its state is pickled on the server
(by Pyro) and unpickled on the client (by Pyro), thereby recreating the remote sub1 object on the
client. Only after that, Python looks up sub2 in sub1. What happens is that Python
itself returns you the sub2 attribute of the local sub1 object! If you call
methods on that object, or change it's value, that will only happen on the (temporary) local sub2! All
changes are lost because they're not propagated to the server!
Currently the only working solution for this problem is to use extra methods on your original Pyro server object,
that manipulate the sub2 object on the server (for instance, you should call
object.setSub2(newvalue) to update sub2's value on the server, instead of
object.sub1.sub2=newvalue).
Note that this problem only occurs when you're using nested attribute access. Manipulating the attributes of
object itself (the Pyro proxy) is no problem, because all attribute accesses (read and write) are
intercepted by Pyro and are remoted to the actual server object.
ConnectionClosedError or even ProtocolError) it can use a special 'hidden'
method of the internal Pyro protocol adapter object to request it to reconnect to the server:
yourpyroobject.adapter.rebindURI()tries and wait. The first is the number of
retries that is performed (default: sys.maxint), the second is the delay time between each retry in seconds
(default: 1).connectPersistent method of the
PyroDaemon. Otherwise the reconnect feature does not work because the client tries to access an invalid
URI. The connectPersistent method reuses the object's URI that is still known in the Name Server. It's
no problem to always use connectPersistent instead of the regular connect, but there is a
naming lookup overhead per call.rebindURI method of the object's protocol adapter itself if this is the case.port parameter
to make sure they reuse the same port every time.
The reason this is needed is that the rebinding of the proxy will use the PYRO:// uri that is
stored in the proxy. That URI only contains the exact location of the object in a specific daemon.
No new naming lookup via the name server is done.
About the difference between the exceptions that you can catch: You get a ConnectionClosedError when
Pyro was able to establish a connection initially, but the connection gets interrupted later (because of network
problems or something like that). You get a ProtocolError ('connection failed') when Pyro was unable to
establish a connection at all, for instance, when the Pyro daemon on the server isn't running or reachable at the
time Pyro tries to establish a connection. It is debatable if we should talk about reconnection in the
second case, because there has never been a connection to begin with. But, if you want to handle this case too, just
catch a ProtocolError instead of ConnectionClosedError.
Examine the example code provided in the "autoreconnect" example, and Pyro's internal adapter code, to see how the rebind feature works.
ImportError. However, Pyro intercepts this and returns a
NoModuleError.
Unless you enable PYRO_MOBILE_CODE. Now, Pyro internally returns a special code, which makes
the client submit the missing Python code to the server. Pyro then proceeds as if nothing was wrong, i.e. it
can now load the previously missing module and call those objects! This happens automatically, you only have to
enable mobile code on the server by setting the PYRO_MOBILE_CODE config item to 1!
There is one more thing: loading and running arbitrary code is dangerous. Pyro has codeValidators to help you protect your program; see the Security chapter for more info.
Pyro supports 2-way mobile code: your client can also receive code from the server that wasn't available before!
This means the server can return objects that are unknown in the client. The module(s) on the server that define
those objects will be sent to the client to make them available there, too. Just like enabling mobile code support on
the server, you have to enable PYRO_MOBILE_CODE on the client to allow mobile code downloading from the
server to the client. The codeValidator on the server checks both directions.
There are a few important limitations with the current mobile code implementation:
__main__ will not work because of a Python peculiarity. There are no plans for including
a workaround in Pyro.__init__, you have
to import them from within the mobile object class methods.It is perfectly ok to put your mobile object module in a Python package. If your codeValidator allows
it, your mobile object module can also import other modules that are unknown on the server (but
only from within the mobile object class members, not at the module level or from __init__).
They will be transported too (if you import them by their fully qualified name). It's easy enough
to write an appropriate codevalidator. If you don't want cascaded loading, check for specific module
names. If you want to allow cascaded loading, check for module name patterns, for instance allow
everything that starts with "agent.". Have a look at the "agent2" example to see
how this all works.
Note: if a compiled module (*.pyc or *.pyo) is available, Pyro will use that. If you have old *.pyc files around made with a different Python version, Pyro will crash (with a syntax error) because it can't recognise these compiled files and tries to compile them! Be sure to delete all *.pyc and *.pyo files if you switch Python versions.
Another case where multithreading is necessary, is when you are using callbacks in your Pyro object (or when you are calling other Pyro objects). Because this call may arrive at the same daemon, it must create a new thread to handle the new incoming call. When running in single threaded mode, Pyro will freeze because the calls are waiting on each other to be processed.
Pyro's use of threads on the server is as follows: the main daemon loop only waits for new connections. If a new
connection arrives, a new thread is created that will serve this connection. The thread will process incoming calls
sequentially, but that is good ofcourse since they can only arrive sequentially over the socket. The thread keeps
running while the connection is still there. Be aware of this: if you ^C a program, you abort the main loop but many
other threads might still be running. Pyro makes them 'daemon threads' so they will be terminated when your program
exits, but it is preferred to clean up the nice way: call daemon.shutdown() when your program exits.
Of course, a little overhead is introduced. You can see this quite clearly when you are running
the "benchmark"
example in single- and multithreaded mode. Pyro will default to the multithreaded mode if your system
supports it, because usually you'll need Pyro to be able to accept new invocations while others are
still in progress. If you want, use the PYRO_MULTITHREADED config item to switch to singlethreaded
mode (set it to zero). Pyro will default to single threaded mode if Python threads are not available.
Switching to multithreaded mode if Python threads are not available, by setting PYRO_MULTITHREADED to
1, will crash Pyro. Please use
Pyro.util.supports_multithreading() to test whether or not your system is able to use
multithreading.
Pyro.core.SynchronizedObjBasePyro.core.SynchronizedObjBase base class that you can use instead of the regular
Pyro.core.ObjBase. When you use it, all (remote) method calls are automatically synchronized for you,
because a thread lock object is used for your Pyro object. This has a huge negative impact on heavily multithreaded
applications, but it saves you from much threading headaches. Note that other Pyro objects may still be accessed
concurrently. If you share data over different Pyro objects, you still have to make sure that everything
behaves in a thread-safe manner.
Note that when you use this object base class, you don't have most of the threading issues mentioned above
regarding further calls on proxies stored in your Pyro object, because you are running in
a single thread all the time. However, the thread is a different one every call so you still
have to transfer thread ownership on the proxy object!
It's possible to pass proxies as parameters to remote calls. They will be pickled and unpickled in the Pyro object on the other side. Notice that the thread in which the call is executing on the remote side, is automatically taking ownership of the unpickled proxy object. That means that you don't have to worry about any threading issues (mentioned above) when you are using a proxy that you obtained via method parameters! It could be a good idea to just pass callback objects via method parameters on each call, instead of having the server store a callback object reference and the need to deal with all the gory threading details described above.
The "multithread" example shows what's going on, and how multithreading can help to improve performance and response times.
Sometimes it is required to keep track of some data that should only be used by a single thread. An example could be an open database connection object, because the connection isn't thread safe, or it needs this because of transactions, or some other reason. If you don't want to re-establish the connection for every call you can store it on what is called the Thread Local Storage.
TLS is a container that is local to the current thread. Other threads have no access to that data, and
you don't overwrite global data by accident when you use this kind of storage. Pyro's TLS
can be accessed from within the remote methods of your
Pyro objects ( it exists only when your object is invoked by Pyro, so you cannot access it from your __init__ method
for instance).
How do you gain access to the TLS? The ObjBase base class has a method
getLocalStorage() that returns an instance of a storage class to put your data in.
So you write something like this, to store something on it:
self.getLocalStorage().something=...The TLS object already has one predefined attribute:
caller.
This attribute contains the Pyro.protocol.TCPConnection object of the client proxy that is performing
the current method call.
You could use it to identifiy the unique client that is making the method call,
but remember that it is just a single proxy that you are pinpointing. Your client application could
have many proxies, even many different ones that connect to the same server.
It is advised to leave the caller object alone, but you could do nasty things with this
if you want to (such as dropping the connection by calling close() on it). You might also
use the caller object to access any
specific data associated with the connection, that you have stored there yourself (for instance, the
authentication id placed as an attribute on it from within a custom connection validator). See the
"user_passwd_auth" example. It puts it there to be able to uniquely identify the client,
rather than just the calling proxy.
How do you initialize the TLS? Pyro allocates the TLS as soon as it's needed. You cannot
initialize it when your objects are initialized because it doesn't exist yet at that time. Instead, you have to set a
custom init function in the Daemon using the setInitTLS(initfunc) method of the Daemon.
initfunc must be a callable object that takes a single argument: the TLS object to initialize.
Note: When running Pyro in singlethreaded mode the TLS is shared across every Pyro object and every method invocation! This is different than normal, when running in multithreaded mode!
If you use delegation instead of inheriting from ObjBase, you cannot use TLS because you
don't have a means of getting to it (the getter is in ObjBase). This isn't bad because objects that use
delegation know nothing about Pyro in the first place. (Well, actually, there is a sneaky way of getting to
the TLS: use threading.currentThread().localStorage (it's an attribute of the current thread object).
But if you do use this, be aware that your delegate object becomes dependent on the Pyro environment, and you
probably chose to use delegation approach to avoid this!) Also, in a single-threaded environment, this is not
possible because the threading.currentThread() call might not be available. In any case, when Pyro is
running in single threaded mode, the current thread (or main thread) does not contain a
localStorage attribute. To avoid any problems, it is probably best not to use it at all. Remember that
you can use self.getLocalStorage() fine from a Pyro object that is inherited from
Pyro.core.ObjBase, even in single threaded mode!
Examples Have a look at the 'user_passwd_auth' and 'sessions' examples to see possible usages of the TLS.
Usually Pyro will locate its servers and objects using fixed IP numbers encoded in the Pyro URIs. This may or may
not be appropriate. For instance, when a machine has an IP number that is only temporary, such as DHCP-leased IP
numbers. The machine can get a new -different- IP number while Pyro is still running. URIs with the old IP number are
now invalid! Therefore it is possible to tell Pyro to use symbolic DNS hostnames in URIs instead of raw IP
numbers. Pyro will then use DNS to look up the actual IP number of the specified host (by name). You can enable this
by setting the PYRO_DNS_URI config item to 1. However note that each time Pyro has to look
up a host, there is a DNS lookup delay.
If your machine has multiple IP addresses (for instance, when it has multiple network cards), you have to decide
on what IP address your Pyro servers reside. When you create a Pyro Daemon, use the host argument to
specify the hostname/ip address to bind the server on (defaults to '' - the default host). The Name Server can be
started with a -n hostname argument, to specify the hostname/ip address to bind on.
You can also use the PYRO_HOST config item.
Another issue is when you're using Pyro behind a firewall. There is one specific form of firewalling
that is addressed in Pyro: simple Network Address Translating firewalls using port forwarding.
Let's say you're at 192.168.0.1 (a private address) behind a NAT gateway that's 192.1.1.1. You
have port forwarding on the NAT, so that Pyro requests go to the private box. However, with the
way that Pyro is set up by default, the daemon will publish URIs as though they come from 192.168.0.1
-- an address unavailable to the rest of the Net. There is no way to have 192.168.0.1 publish URIs
as though it were actually 192.1.1.1. But there is the extra publishhost
parameter for the constructor of Pyro.core.Daemon. When constructing a Pyro Daemon, you
can give it a special hostname or IP address that it should use when publishing URIs, via the publishhost parameter.
The host parameter still is the "real" hostname of the machine the daemon is running
on. When
publishhost is not specified (it isn't by default) the value for host is
taken. If that isn't specified either (it isn't by default) the hostname of the machine is queried
and that is used. In our little example, host should be 192.168.0.1 (or just
empty/omitted) and publishhost
should be 192.1.1.1, the address of the firewall/gateway.
By the way, you can also use the PYRO_PUBLISHHOST config item to specify a publish hostname.
Your client must publish a callback object that is a true Pyro object. In fact, for the callback
part, your client must act as a true Pyro server. So you have to code your client as both a client
and a server. This may require that your client must run a separate thread to handle Pyro messages
(the Pyro daemon loop must be running to accept incoming calls). If your client only sits idle,
and only waits for incoming callbacks, you can just run the daemon's
requestLoop in the main thread. Have a look at the "callback" example for more details.
Be very aware of threading issues. Callbacks occur in their own thread. A callback may even occur while your client is still busy processing the previous callback. Your server should be even more prepared for callbacks. Usually you have a method that "registers" a client as a callback object. The client will call this method and has to pass a proxy to the callback object, not the object itself! (see usage rules, below).
Possible deadlock: if your objects enter a conversation, deadlock may occur easily. For instance, A calls B, B calls back to A, A calls B again... deadlock! B was still waiting for A to answer the callback, but A invokes a new method instead. Pyro cannot handle this yet. This issue might be addressed in a future Pyro version. In the meantime, please read on about possible alternatives.
Your server usually has a list of callback objects that it should call. Be very careful here: a client can
unexpectedly disappear. You have to handle ConnectionClosedError exceptions and you must then remove the
defunct callback object from the list. But you have to do this in a thread-safe way (the list must be under a
thread-lock), because the server may be multithreaded! The server also has to handle any exceptions that occur in the
callback object on the client. Don't trust it. Catch any exception that occurs, otherwise your server dies.
Be aware of a complex issue when your callback object raises an exception: if a callback occured in a remote method,
that was called by the client, the exception might travel right back to the client if the server doesn't take
precautions!
Not strictly callbacks, but when your Pyro object is calling other Pyro objects, you have to run in multithreaded mode. Because the new call may arrive at the same daemon, it must create a new thread to handle the new incoming call. When running in single threaded mode, Pyro will freeze because the calls are waiting on each other to be processed.
Please consider using the Pyro Event Service, instead of custom callback objects. It will handle all those nasty things for you, at the cost of some control. But it's very easy to use.
Special callback object Pyro.core.CallbackObjBase: Usually any exception
that occurs in the callback object is silently transported back to the server, where it is raised
again. For many callback objects, this is not exactly what you want, because usually the client is
interested in an error within a callback object, and the server often doesn't care. If you use
the special Pyro.core.CallbackObjBase as
a base class for your callback objects (instead of the regular ObjBase), any exception
that occurs in the callback object is not only sent to the server, but also raised again on the cient.
You can see this work in one of the "callback" examples.
Oneway calls: These are remote method calls that do not expect any answer, so they return immediately after sending the remote call to the remote object. The call does not wait for the remote method to finish. At a lower level, it doesn't even wait for a protocol reply, so performance is much better too.
Normally, on the server side (the object that executes the oneway call), the call is executed in its own thread so that other calls can be processed in the meantime, if the oneway method takes some time to complete. This only works if multithreading is enabled. This property of oneway calls allows you, for instance, to start a computation and continue your own business while the computation runs. Later on you use another remote call to retrieve the results of the computation (or use a callback). This way, you don't have to worry about programming a multithreaded client, just use a oneway call. You can disable this by setting the PYRO_ONEWAY_THREADED config item to false (0). Oneway calls will then execute in the server's main thread. New method calls on the object will have to wait until the oneway method call has finished processing, as usual.
Note: There is no way to find out what the result of your request was - whether it succeeded or failed. No result nor any exception is ever returned. You're still quite sure that the call is performed though, because the request is sent using the regular PYRO protocol, but there is no guarantee (nor is there with regular calls by the way).
Oneway calls are very nice to have in a callback scenario. The Event Service also makes heavy use of them. Why? Your server is freed from the burden of handling exceptions that may occur in the remote method, and it doesn't block on slow or buggy clients. It just sends out the method invocations and continues on happily while the callback clients process the incoming method call.
You have to specify at runtime in your program which methods of what objects have this Oneway semantics. You do this by calling a special method on the Pyro proxy object:
obj._setOneway(methods)where obj is your proxy and methods is a list or tuple of method names that have to be called Oneway. It may also be a single method name. Currently there is no way to specify from within the remote object itself, or the creating process, that a method has to be called oneway. The calling party has to set this property. Ofcourse you could build some sort of inquiry method that has to be called first and that tells the caller what methods can have this property, and maybe this will become automatic in a future version, but it's not yet there.
Assume the remote Pyro object raises a ValueError exception. Your calling code will receive this and
crash wit the same ValueError exception. However, the stacktrace in the traceback info is
from your local code, not from the remote code. If you're just catching and processing exceptions, and don't
want to deal with stacktrace/traceback info, there is no problem with this. But if you want to print the stacktrace,
it is meaningless! It is a stacktrace from within the bowels of the local Pyro code! It provides no clue what piece
of remote code caused the problem.
To help you with this, Pyro puts the remote stacktrace inside the exception that travels to your calling
code. It is a list of text lines and can be obtained from the special attribute that is defined in
Pyro.constants.TRACEBACK_ATTRIBUTE, but it's probably more convenient to use the utility function
Pyro.util.getPyroTraceback. You pass the exception object and the function returns a list of lines that
contain the remote traceback (if available) and the local traceback.
Note that if you set PYRO_DETAILED_TRACEBACK to 1 on the server side, it will not
be a normal traceback but a much more elaborated one including local variable values etc.
An example:
try:
print thing.method() # thing is a Pyro proxy
except Exception,x:
print ''.join(Pyro.util.getPyroTraceback(x))
This function is safe to call on all exceptions, also normal (local) exceptions. See the "simple" and "exceptions" examples. It is also possible to set a custom excepthook to automatically take care of the remote traceback printing:
import sys
import Pyro.util
sys.excepthook = Pyro.util.excepthook
#... call any method ...
Pyro.constants.INTERNAL_DAEMON_GUID. (this is not a GUID in the true sense, because
it is not unique). Here's an example to query all registered objects on a remote Daemon at 192.168.1.50, running on
the default port:
import Pyro.core Pyro.core.initClient() d=Pyro.core.PyroURI(host='192.168.1.50',objectID=Pyro.constants.INTERNAL_DAEMON_GUID).getProxy() print d.getRegistered()The result is a dictionary that maps GUIDs to object names, like this:
{'c0a8013208585602469aec911dc92a20':
':Pyro.NameServer', 'c0000000011000001000000010000001': '__PYRO_Internal_Daemon'}.
Currently there is only one other daemon method that is remotely accessible, ResolvePYROLOC.
You will probably never call this yourself, it is used for the PYROLOC: protocol. Note: If
the daemon is running in SSL mode you have to add an additional prtcol="PYROSSL" argument
to the PyroURI constructor call above!
Because Pyro's connection protocol requires a handshake at connection time, the timeout also works for connecting to a Pyro daemon. This is nice, because evil clients now cannot eat connections indefinately by just connecting and never finishing the request. Once a connection has been established, it stays there.
How do you set the timeout?
proxy._setTimeout(20) # set 20-sec. timeout on proxy object (client)
daemon.setTimeout(20) # set 20-sec. timeout on daemon (server)
Clear it again by passing None. If a timeout occurs, Pyro raises a TimeoutError
exception, which is subclassed from ConnectionClosedException. The connection has already been dropped by
Pyro. (why is it _setTimeout -- with an underscore -- for the proxy? To avoid possible name clash with
your own method names)
Note about NS and ES: the Name Server and Event Server have a built-in fixed timeout of 20 seconds. The connection is killed if data transmission takes longer than that, to prevent evil clients of clogging up the servers.
proxy._release() to release the connection. Pyro will automatically create the connection again as
soon as you start using the proxy again. An additional benefit is that the socket object associated with the proxy is
destroyed, so you are able to pickle the proxy object again.
Things are a bit more complex on the server. Usually the Pyro objects you create there must stay
active because it is not known when a client comes by to use them. This is especially true for
objects that are registered in the Name Server, because that sort of tells the clients "this object
is available there-and-there". But for
transients, things are different. Remember that transients are objects created on the server,
without a name, and usually a proxy is returned to the client to access these new objects. There's
no way to tell when the client no longer needs the object! If it 'forgets' to call some sort of "release"
method that destroys the object in the server, your server could overflow with all left-over unused
transient objects. This is why you can specify an
inactivity timeout for transients, by calling daemon.setTransientsCleanupAge(timeout)
on your daemon. The argument is in seconds.
Pyro tracks the time an object has not been used, and destroys it when the timeout has expired. You may want to
override the _gotReaped() method in the ObjBase to act on the destroy event (for instance,
remove the object from a list).
Please be aware that if Pyro runs in single-threaded mode, the reaping of expired objects is only done when a method
is invoked!
Also, cleaning up objects on the server doesn't automatically release any network connections and threads
that might have been created for these objects. This is because these resources are not necessarily
associated with a unique object, so they have to remain active. See also the "Bank2" example,
it uses timeouts.
__init__ method. You should use a regular initialization
method that you must call explicitly after binding to the remote object. The __init__ method will only
be called on the server side when the object is created.openFile(filename) that opens a file on the server and returns the file object, because file objects
cannot be pickled. This also holds for sockets, and various other object types. As long as you don't access these
objects in your client, you're OK though (there's nothing wrong with a Pyro object that has various open files or
sockets as attributes -- if you don't access them from the client).object1==object2 for instance. This is
because the proxy class needs to hijack the rich comparison mechanism to be able to compare two proxy classes with
each other.Pyro.naming.NameServerProxy.
When you use the Locator, you're safe..py source files that contain the code of the objects that are used as
parameters in remote method calls, must be available on the client and on the server.
Otherwise the server cannot load the implementation code of an object that arrives in a remote
method call. This is no longer necessary if you enable the mobile code feature. See the "agent2"
example..py source files that contain the code of the objects that are used as attributes of
Pyro objects on the server, must be available on the client also. Otherwise the client cannot recreate the
server object's attributes and will crash if you access these attributes. This cannot be fixed with enabling mobile
code yet.Pyro.core.ObjBase. You
could define a new (probably empty) class in the server that inherits both from Pyro.core.ObjBase and
the class that is made remotely available.Pyro.core.ObjBase. This
works as follows: create an object of your remote class, create a Pyro.core.ObjBase object, and tell
the latter to use the former as delegate:
... impl = MyRemoteClass() obj = Pyro.core.ObjBase() obj.delegateTo(impl) ...and you then connect
obj to the Daemon.
daemon.shutdown() when your program exits. This will cleanly stop all
threads that might still be running.__init__
from the base class in the __init__ method -if you have one- of your remote class. You cannot omit
this, your Pyro object will not work without the initialization:
def __init__(self):
Pyro.core.ObjBase.__init__(self)
...
Pyro.core.ObjBase, or use the delegation approach, and call
Pyro.core.ObjBase.__init__(self) from your own __init__URI = self.getDaemon().connect(object) # no name, not in NS URI = self.getDaemon().connect(object,'name') # registered in NS with 'name'
return object that
you would otherwise use, you do:
return object.getProxy() # regular dynamic proxy return object.getAttrProxy() # dynamic proxy with attribute support
self.getDaemon().disconnect(object) # can also pass object's UID del object
while obj:. Like the limitation with direct member access, this is also caused by the way the proxy
object is currently implemented. It intercepts each and every method call. And testing for zero-ness or
nonzero-ness or coercion are also method calls! (__nonzero__, __coerce__ etc.)Pyro.core.CallbackObjBase instead of
the regular
ObjBase. (see above at "callbacks")__nonzero__. For example,
to make obj+=50 work,
you need to implement the __iadd__ method in your Pyro object and let it return
the object itself (that is, a proxy for the object!) because the method returns the in-place
modified object!
def __iadd__(self,value):
self.value+=value
return self.getAttrProxy()
daemon.shutdown() when it exits. Usually this is not a problem because your program creates a deamon
and calls its requestLoop. But a situation might arise where you don't keep a reference to the daemon
object, and then things break.NameServerProxy) can be pickled, and therefore you can pass them
around within your Pyro system. Thread ownership is taken by the thread that unpickled the proxy.daemon.disconnect(object) (you can disconnect the object directly or provide its UID)value=remoteObject.somedict['somekey']) Pyro
will transfer the full dictionary to the caller and do the key lookup only after that. If it's a big data
structure, you have a big performance hit. Consider writing getter and setter methods on the remote object
instead.