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| RPyC | |
|---|---|
 | |
| Developer | Tomer Filiba |
| Initial release | 17 December 2005 |
| Stable release | |
| Written in | Python |
| Operating system | Cross-platform |
| Type | Remote Procedure Call |
| License | MIT License |
| Website | rpyc |
| Repository | |
RPyC (pronouncedare-pie-see), orRemotePythonCall, is aPython library forremote procedure calls (RPC), as well asdistributed computing. Unlike regular RPC mechanisms, such asONC RPC,CORBA orJava RMI, RPyC is transparent, symmetric, and requires no special decoration or definition languages. Moreover, it provides programmatic access to any pythonic element, be it functions, classes, instances or modules.
RPyC gives the programmer a slave python interpreter at his or her control. In this essence, RPyC is different from other RPCs, that require registration of resources prior to accessing them. As a result, using RPyC is much more straightforward, but this comes at the expense of security (you cannot limit access). RPyC is intended to be used within a trusted network, there are various schemes includingVPN for achieving this.
Once a client is connected to the server, it has one of two ways to perform remote operations:
doc = conn.modules.sys.path orconn.modules["xml.dom.minidom"].parseString("<some>xml</some>").conn.execute("print 'hello world'")Remote operations return something called aNetProxy, which is an intermediate object that reflects any operation performed locally on it to the remote object. For example, conn.modules.sys.path is a NetProxy for the sys.path object of the server. Any local changes done to conn.modules.sys.path are reflected immediately on the remote object.Note: NetProxies are not used forsimple objects, such as numbers and strings, which are immutable.
Async is a proxy wrapper, meaning, it takes a NetProxy and returns another that wraps it with asynchronous functionality. Operations done to an AsyncNetProxy return something called AsyncResult. These objects have a '.is_ready' predicate, '.result' property that holds the result (or blocks until it arrives), and '.on_ready' callback, which will be called when the result arrives.
Originally, RPyC was developed for managing distributed testing of products over a range of different platforms (all capable of running python). However, RPyC has evolved since then, and now its use cases include:
importrpycconn=rpyc.classic.connect("hostname")# assuming a classic server is running on 'hostname'print(conn.modules.sys.path)conn.modules.sys.path.append("lucy")print(conn.modules.sys.path[-1])# a version of 'ls' that runs remotelydefremote_ls(path):ros=conn.modules.osforfilenameinros.listdir(path):stats=ros.stat(ros.path.join(path,filename))print("%d\t%d\t%s"%(stats.st_size,stats.st_uid,filename))remote_ls("/usr/bin")# and exceptions...try:f=conn.builtin.open("/non/existent/file/name")exceptIOError:pass
RPyC is based on the work ofEyal Lotem (akaLotex) onPyInvoke,[2] which is no longer maintained. The first public release was 1.20, which allowed for symmetric and transparent RPC, but not forasynchronous operation. Version 1.6, while never publicly released, added the concept of 'events', as a means for the server to inform the client. Version 2.X, the first release of which was 2.2, added thread synchronization and theAsync concept, which can be used as a superset of events. Version 2.40 adds theexecute method, that can be used to execute code on the other side of the connection directly.RPyC 3 is a complete rewrite of the library, adding acapability-based security model, explicit services, and various other improvements.