当我看到问题时,我很好奇这将如何完成,这是我想出的解决方案。虽然不像我希望的那么简单,但是它可能会有用。首先,这是行为:
class Tracker(object):
def __init__(self):
self.lst = trackable_type('lst', self, list)
self.dct = trackable_type('dct', self, dict)
self.revisions = {'lst': [], 'dct': []}
>>> obj = Tracker() # create an instance of Tracker
>>> obj.lst.append(1) # make some changes to list attribute
>>> obj.lst.extend([2, 3])
>>> obj.lst.pop()
3
>>> obj.dct['a'] = 5 # make some changes to dict attribute
>>> obj.dct.update({'b': 3})
>>> del obj.dct['a']
>>> obj.revisions # check out revision history
{'lst': [[1], [1, 2, 3], [1, 2]], 'dct': [{'a': 5}, {'a': 5, 'b': 3}, {'b': 3}]}
现在trackable_type()
,使所有这些变为可能的函数:
def trackable_type(name, obj, base):
def func_logger(func):
def wrapped(self, *args, **kwargs):
before = base(self)
result = func(self, *args, **kwargs)
after = base(self)
if before != after:
obj.revisions[name].append(after)
return result
return wrapped
methods = (type(list.append), type(list.__setitem__))
skip = set(['__iter__', '__len__', '__getattribute__'])
class TrackableMeta(type):
def __new__(cls, name, bases, dct):
for attr in dir(base):
if attr not in skip:
func = getattr(base, attr)
if isinstance(func, methods):
dct[attr] = func_logger(func)
return type.__new__(cls, name, bases, dct)
class TrackableObject(base):
__Metaclass__ = TrackableMeta
return TrackableObject()
基本上,这使用元类重写对象的每个方法,以在对象更改时添加一些修订日志。这没有经过全面的测试,除了list
和之外,我还没有尝试过其他任何对象类型dict
,但是对于这些对象似乎还可以。