我想我知道你的问题：
函数定义的模块被调用
'__main__'
它存在于所有正在运行的python版本中。
pickle 不传输源代码而是参考
__main__.square
所以你有两种可能性：
source square out 并使主模块尽可能短，例如：
# main.py
def square(x):
return x**2
import Pyro4
def main():
remoteServer = Pyro4.Proxy('PYRONAME:server')
print remoteServer.evaluate(square, 4)
和：
# __main__.py
import main
main.main()
然后服务器可以从文件中导入完全相同的模块。
或使用我的代码创建一个模块：
class ThisShallNeverBeCalledError(Exception):
pass
class _R(object):
def __init__(self, f, *args):
self.ret = (f, args)
def __reduce__(self):
return self.ret
def __call__(self, *args):
raise ThisShallNeverBeCalledError()
@classmethod
def fromReduce(cls, value):
ret = cls(None)
ret.ret = value
return ret
def dump_and_load(obj):
'''pickle and unpickle the object once'''
s = pickle.dumps(obj)
return pickle.loads(s)
# this string creates an object of an anonymous type that can
# be called to create an R object or that can be reduced by pickle
# and creates another anonymous type when unpickled
# you may not inherit from this MetaR object because it is not a class
PICKLABLE_R_STRING= "type('MetaR', (object,), " \
" {'__call__' : lambda self, f, *args: "\
" type('PICKLABLE_R', "\
" (object,), "\
" {'__reduce__' : lambda self: (f, args), "\
" '__module__' : 'pickleHelp_', "\
" '__name__' : 'PICKLABLE_R', "\
" '__call__' : lambda self: None})(), "\
" '__reduce__' : lambda self: "\
" self(eval, meta_string, "\
" {'meta_string' : meta_string}).__reduce__(), "\
" '__module__' : 'pickleHelp_', "\
" '__name__' : 'R'})()".replace(' ', '')
PICKLABLE_R = _R(eval, PICKLABLE_R_STRING, \
{'meta_string' : PICKLABLE_R_STRING})
R = dump_and_load(PICKLABLE_R)
del PICKLABLE_R, PICKLABLE_R_STRING
PICKLABLE___builtins__ = R(vars, R(__import__, '__builtin__'))
PICKLABLE_FunctionType = R(type, R(eval, 'lambda:None'))
##R.__module__ = __name__
##R.__name__ = 'PICKLABLE_R'
def packCode(code, globals = {}, add_builtins = True, use_same_globals = False, \
check_syntax = True, return_value_variable_name = 'obj',
__name__ = __name__ + '.packCode()'):
'''return an object that executes code in globals when unpickled
use_same_globals
if use_same_globals is True all codes sent through
one pickle connection share the same globals
by default the dont
return_value_variable_name
if a variable with the name in return_value_variable_name exists
in globals after the code execution
it is returned as result of the pickling operation
if not None is returned
__name__
'''
if check_syntax:
compile(code, '', 'exec')
# copying locals is important
# locals is transferred through pickle for all code identical
# copying it prevents different code from beeing executed in same globals
if not use_same_globals:
globals = globals.copy()
if add_builtins:
globals['__builtins__'] = PICKLABLE___builtins__
globals.setdefault('obj', None)
# get the compilation code
# do not marshal or unmarshal code objects because the platforms may vary
code = R(compile, code, __name__, 'exec')
# the final object that can reduce, dump and load itself
obj = R(R(getattr, tuple, '__getitem__'), (
R(R(PICKLABLE_FunctionType, code, globals)),
R(R(getattr, type(globals), 'get'), globals, \
returnValueVariableName, None)
), -1)
return obj
然后将其发送到另一端：
packCode('''
def square(...):
...
''', return_value_variable_name = 'square')
并且该函数将在另一端出现，无需模块代码即可将此python函数传输到另一端服务器端。
如果有什么不成功，请告诉我。