如何在pickle加載過程中將導致導入錯誤的對象替換爲None？

Question

我有一個由嵌套的內置原語（列表，字典）和不在項目中的類的實例組成的pickled結構，因此在取出過程中會導致錯誤。我並不關心這些對象，我希望能夠提取存儲在這個嵌套結構中的數值。有沒有辦法從文件中取消選中，並替換因導入問題導致的所有內容，例如None？

我試圖從Unpickler繼承和覆蓋find_class(self, module, name)返回Dummy如果類不能被發現，但由於某種原因，我一直在後load reduce越來越TypeError: 'NoneType' object is not callable。

class Dummy(object): 
    def __init__(self, *argv, **kwargs): 
     pass 

我想是這樣

class RobustJoblibUnpickle(Unpickler): 
    def find_class(self, _module, name): 
     try: 
      super(RobustJoblibUnpickle, self).find_class(_module, name) 
     except ImportError: 
      return Dummy 

Answer 1

也許你能趕上在try塊中的例外，做你想做的（ 設置一些對象 None 用的虛擬類）？

編輯：

看看這個，我不知道它是做正確的方式，但它似乎很好地工作：

import sys 
import pickle 

class Dummy: 
    pass 

class MyUnpickler(pickle._Unpickler): 
    def find_class(self, module, name): # from the pickle module code but with a try 
     # Subclasses may override this. # we are doing it right now... 
     try: 
      if self.proto < 3 and self.fix_imports: 
       if (module, name) in _compat_pickle.NAME_MAPPING: 
        module, name = _compat_pickle.NAME_MAPPING[(module, name)] 
       elif module in _compat_pickle.IMPORT_MAPPING: 
        module = _compat_pickle.IMPORT_MAPPING[module] 
      __import__(module, level=0) 
      if self.proto >= 4: 
       return _getattribute(sys.modules[module], name)[0] 
      else: 
       return getattr(sys.modules[module], name) 
     except AttributeError: 
      return Dummy 

# edit: as per Ben suggestion an even simpler subclass can be used 
# instead of the above 

class MyUnpickler2(pickle._Unpickler): 
    def find_class(self, module, name): 
     try: 
      return super().find_class(module, name) 
     except AttributeError: 
      return Dummy 

class C: 
    pass 

c1 = C() 

with open('data1.dat', 'wb') as f: 
    pickle.dump(c1,f) 

del C# simulate the missing class 

with open('data1.dat', 'rb') as f: 
    unpickler = MyUnpickler(f) # or MyUnpickler2(f) 
    c1 = unpickler.load() 

print(c1) # got a Dummy object because of missing class