import copydef Memento(obj, deep=False):  # 對你要做快照的對象做快照  state = (copy.copy if deep else copy.deepcopy)(obj.__dict__)  def Restore():    obj.__dict__ = state  return Restoreclass Transaction:  deep = False  def __init__(self, *targets):    self.targets = targets    self.Commit()  # 模擬事務提交，其實就是初始化給每個對象往self.targets賦值  def Commit(self):    self.states = [Memento(target, self.deep) for target in self.targets]  # 回滾其實就是調用Memento函數，執行其中的閉包，將__dict__恢復  def Rollback(self):    for state in self.states:      state()# 裝飾器的方式給方法添加這個事務的功能def transactional(method):  # 這里的self其實就是要保存的那個對象，和類的實例無關  def wrappedMethod(self, *args, **kwargs):    state = Memento(self)    try:      return method(self, *args, **kwargs)    except:      # 和上面的回滾一樣，異常就恢復      state()      raise  return wrappedMethodclass NumObj(object):  def __init__(self, value):    self.value = value  def __repr__(self):    return '<%s: %r>' % (self.__class__.__name__, self.value)  def Increment(self):    self.value += 1  @transactional  def DoStuff(self):    # 賦值成字符串，再自增長肯定會報錯的    self.value = '1111'    self.Increment()if __name__ == '__main__':  n = NumObj(-1)  print n  t = Transaction(n)  try:    for i in range(3):      n.Increment()      print n    # 這里事務提交會保存狀態從第一次的-1到2    t.Commit()    print '-- commited'    for i in range(3):      n.Increment()      print n    n.value += 'x' # will fail    print n  except:    # 回滾只會回顧到上一次comit成功的2 而不是-1    t.Rollback()    print '-- rolled back'  print n  print '-- now doing stuff ...'  try:    n.DoStuff()  except:    print '-> doing stuff failed!'    import traceback    traceback.print_exc(0)    pass  # 第二次的異常回滾n還是2, 整個過程都是修改NumObj的實例對象  print n

import Queueimport typesimport threadingfrom contextlib import contextmanagerclass ObjectPool(object):  def __init__(self, fn_cls, *args, **kwargs):    super(ObjectPool, self).__init__()    self.fn_cls = fn_cls    self._myinit(*args, **kwargs)  def _myinit(self, *args, **kwargs):    self.args = args    self.maxSize = int(kwargs.get("maxSize",1))    self.queue = Queue.Queue()  def _get_obj(self):    # 因為傳進來的可能是函數，還可能是類    if type(self.fn_cls) == types.FunctionType:      return self.fn_cls(self.args)    # 判斷是經典或者新類    elif type(self.fn_cls) == types.ClassType or type(self.fn_cls) == types.TypeType:      return apply(self.fn_cls, self.args)    else:      raise "Wrong type"  def borrow_obj(self):    # 這個print 沒用，只是在你執行的時候告訴你目前的隊列數，讓你發現對象池的作用    print self.queue._qsize()    # 要是對象池大小還沒有超過設置的最大數，可以繼續放進去新對象    if self.queue.qsize()<self.maxSize and self.queue.empty():      self.queue.put(self._get_obj())    # 都會返回一個對象給相關去用    return self.queue.get()   # 回收  def recover_obj(self,obj):    self.queue.put(obj)# 測試用函數和類def echo_func(num):  return numclass echo_cls(object):  pass# 不用構造含有__enter__, __exit__的類就可以使用with，當然你可以直接把代碼放到函數去用@contextmanagerdef poolobj(pool):  obj = pool.borrow_obj()  try:    yield obj  except Exception, e:    yield None  finally:    pool.recover_obj(obj)obj = ObjectPool(echo_func, 23, maxSize=4)obj2 = ObjectPool(echo_cls, maxSize=4)class MyThread(threading.Thread):  def run(self):    # 為了實現效果，我搞了個簡單的多線程，2個with放在一個地方了，只為測試用    with poolobj(obj) as t:      print t    with poolobj(obj2) as t:      print tif __name__ == '__main__':  threads = []  for i in range(200):    t = MyThread()    t.start()    threads.append(t)  for t in threads:    t.join(True)