保存对象（数据持久性）

Question

我创建了这样一个对象：

company1.name = 'banana' 
company1.value = 40

我想保存这个对象。我该怎么做？

Answer 1

我认为假设对象是class是一个相当强的假设。如果不是class呢？还有一个假设是对象没有在解释器中定义。如果它是在解释器中定义的呢？另外，如果属性是动态添加的呢？当一些python对象在创建后将属性添加到它们的__dict__中时，pickle不考虑这些属性的添加（即它“忘记”添加了它们——因为pickle通过引用对象定义序列化）。

在所有这些情况下，pickle和cPickle都会让你非常失望。

如果您希望保存一个object（任意创建），其中有属性（添加到对象定义中或之后）…您最好的选择是使用dill，它可以序列化python中的几乎任何内容。

我们从一节课开始

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pickle
>>> class Company:
...     pass
... 
>>> company1 = Company()
>>> company1.name = 'banana'
>>> company1.value = 40
>>> with open('company.pkl', 'wb') as f:
...     pickle.dump(company1, f, pickle.HIGHEST_PROTOCOL)
... 
>>> 

现在关机，重新启动。。。

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import pickle
>>> with open('company.pkl', 'rb') as f:
...     company1 = pickle.load(f)
... 
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 1378, in load
    return Unpickler(file).load()
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 1090, in load_global
    klass = self.find_class(module, name)
  File "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/pickle.py", line 1126, in find_class
    klass = getattr(mod, name)
AttributeError: 'module' object has no attribute 'Company'
>>> 

哎哟……pickle处理不了。让我们试试dill。我们将引入另一个对象类型（alambda）以获得良好的度量。

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import dill       
>>> class Company:
...     pass
... 
>>> company1 = Company()
>>> company1.name = 'banana'
>>> company1.value = 40
>>> 
>>> company2 = lambda x:x
>>> company2.name = 'rhubarb'
>>> company2.value = 42
>>> 
>>> with open('company_dill.pkl', 'wb') as f:
...     dill.dump(company1, f)
...     dill.dump(company2, f)
... 
>>> 

现在读一下文件。

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import dill
>>> with open('company_dill.pkl', 'rb') as f:
...     company1 = dill.load(f)
...     company2 = dill.load(f)
... 
>>> company1 
<__main__.Company instance at 0x107909128>
>>> company1.name
'banana'
>>> company1.value
40
>>> company2.name
'rhubarb'
>>> company2.value
42
>>>    

它起作用了。pickle失败，而dill不成功的原因是dill将__main__视为一个模块（在大多数情况下），并且还可以pickle类定义，而不是通过引用pickle（就像pickle那样）。之所以dill可以腌制lambda，是因为它给它起了个名字……然后腌制魔法就可以发生。

实际上，有一种更简单的方法保存所有这些对象，特别是如果您已经创建了很多对象。只需转储整个python会话，稍后再返回。

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import dill
>>> class Company:
...     pass
... 
>>> company1 = Company()
>>> company1.name = 'banana'
>>> company1.value = 40
>>> 
>>> company2 = lambda x:x
>>> company2.name = 'rhubarb'
>>> company2.value = 42
>>> 
>>> dill.dump_session('dill.pkl')
>>> 

现在关掉你的电脑，去享受一杯浓咖啡或其他什么，然后回来。。。

Python 2.7.8 (default, Jul 13 2014, 02:29:54) 
[GCC 4.2.1 Compatible Apple Clang 4.1 ((tags/Apple/clang-421.11.66))] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import dill
>>> dill.load_session('dill.pkl')
>>> company1.name
'banana'
>>> company1.value
40
>>> company2.name
'rhubarb'
>>> company2.value
42
>>> company2
<function <lambda> at 0x1065f2938>

唯一的主要缺点是dill不是python标准库的一部分。因此，如果不能在服务器上安装python包，就不能使用它。

但是，如果能够在系统上安装python包，则可以使用git+https://github.com/uqfoundation/dill.git@master#egg=dill获得最新的dill。您可以使用pip install dill获得最新发布的版本。