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如何在Python类描述符对象上调用方法?

[英]How to call methods on Python class descriptor objects?

I created a class String() with __get__() , __set__() , and a method to_db() ; 我用__get__()__set__()和方法to_db()创建了一个class String() ; however, when I do name = String() , I can't do self.name.to_db() because it's calling to_db() on the value returned by __get__() , not the object " name ". 但是,当我执行name = String() ,我不能执行self.name.to_db()因为它在__get__()返回的值上调用to_db() __get__() ,而不是对象“ name ”。

class String(object):

    def __init__(self, value=None):
        if value:
            self.value = str(value)

    def __get__(self, instance, owner):
        return self.value

    def __set__(self, instance, value):
        self.value = str(value)

    def to_db(self):
        return {'type':'string', 'value': self.value}

class Example(object):

    name = String()
    age = Integer()

    def __init__(self,name,age):
        self.name = name
        self.age = age

    def save():
        data = dict(name=self.name.to_db(), age=self.age.to_db())
        db.save(data)

One way to deal with this is to not call self.name.to_db() directly and instead set a flag in instance and create a conditional in __get__() to check for it and call to_db() if it's True , but this seems kludgy. 解决这个问题的一种方法是不直接调用self.name.to_db()而是在instance设置一个标志,并在__get__()创建一个条件来检查它并调用to_db()如果它是True ,但这似乎是kludgy 。 Is there a better way? 有没有更好的办法?

Also, I'm new to descriptors -- what are the pros/cons of using instance and/or instance.__dict__ to store state vs storing it in self ? 此外,我是描述符的新手 - 使用instance和/或instance.__dict__来存储状态与将其存储在self中的优点/缺点是什么?

It's pretty easy - just have your descriptor return a subclass of string with the extra method(s) you want. 这很简单 - 让你的描述符返回一个字符串的子类,并带有你想要的额外方法。

def __get__(self, instance, owner):
    class TaggedString(str):
        def to_db(self):
            return {'type':'string', 'value': self}
    return TaggedString(self.value)`

Descriptors are used to describe "what is it" or "how it works". 描述符用于描述“它是什么”或“它是如何工作的”。

For example, we can put some restriction in the __get__() or the __set__() . 例如,我们可以在__get__()__set__()一些限制。

According to your question, I think you want to add your own method into type<str> , not to describe how to set or get the instance. 根据您的问题,我认为您希望将自己的方法添加到type<str> ,而不是描述如何设置或获取实例。

So you may use thee code below to express what you want to do. 因此,您可以使用下面的代码来表达您想要做的事情。

class String(str):
    def __init__(self, value):
        self.value = value

    def to_db(self):
        return {'type':'string', 'value': self.value}

ss = String('123')
print ss #123
print ss.to_db() #{'type':'string', 'value': '123'}

Here's a solution that allows you to bypass any descriptors defined in the class: 这是一个允许您绕过类中定义的任何描述符的解决方案:

class BypassableDescriptor(object):
    pass

class String(BypassableDescriptor):
    def __init__(self, value=None):
        if value:
            self.value = str(value)

    def __get__(self, instance, owner):
        return self.value

    def __set__(self, instance, value):
        self.value = str(value)

    def to_db(self):
        return {'type': 'string', 'value': self.value}

class Integer(BypassableDescriptor):
    def __init__(self, value=None):
        if value:
            self.value = str(value)

    def __get__(self, instance, owner):
        return self.value

    def __set__(self, instance, value):
        self.value = int(value)

    def to_db(self):
        return {'type': 'integer', 'value': self.value}

class BypassDescriptor(object):
    def __init__(self, descriptor):
        self.descriptor = descriptor

    def __getattr__(self, name):
        return getattr(self.descriptor, name)

class AllowBypassableDescriptors(type):
    def __new__(cls, name, bases, members):
        new_members = {}
        for name, value in members.iteritems():
            if isinstance(value, BypassableDescriptor):
                new_members['real_' + name] = BypassDescriptor(value)
        members.update(new_members)
        return type.__new__(cls, name, bases, members)

class Example(object):
    __metaclass__ = AllowBypassableDescriptors

    name = String()
    age  = Integer()

    def __init__(self,name,age):
        self.name = name
        self.age  = age

    def save(self):
        data = dict(name = self.real_name.to_db(), age = self.real_age.to_db())

Note that it's not perfect - you'll always have to call real_fieldname.method() instead of fieldname.method() and you'll have to use the metaclass AllowBypassableDescriptors for all your classes which need to access this field. 请注意,它并不完美 - 您将始终必须调用real_fieldname.method()而不是fieldname.method()并且您必须为需要访问此字段的所有类使用元类AllowBypassableDescriptors。 Then again, it's a pretty compatible solution that avoids monkey-patching the object wrapped by the descriptor. 然后,它是一个非常兼容的解决方案,可以避免猴子修补由描述符包装的对象。

That said, I'm not sure that descriptors are the best solution for what you're trying to do (writing to a database?). 那就是说,我不确定描述符是你尝试做什么的最佳解决方案(写入数据库?)。

Inside method to_db you may access directly the value via 在内部方法to_db中,您可以直接访问值via

self.__dict__['value'] # value as key is not ideal, but that's what OP used

or, if you are using new style classes only, 或者,如果您只使用新的样式类,

object.__set__(self, name, value)

Since you are using magic attributes, accessing the magic __dict__ is perfectly reasonable. 由于您使用魔法属性,访问魔法__dict__是完全合理的。

This is also referred in the documentation for __setattr__ [1] (sorry, there is no direct reference to __dict__ in __set__ but it's the same problem domain) 这也被称为对文档中__setattr__ [1](对不起,没有直接参考__dict____set__但它同样的问题域)

If __setattr__() wants to assign to an instance attribute, it should not 
simply execute   self.name = value — this would cause a recursive call to itself. 
Instead, it should insert the value in the dictionary of instance attributes, e.g., 
self.__dict__[name] = value. For new-style classes, rather than accessing the instance 
dictionary, it should call the base class method with the same name, for example, 
object.__setattr__(self, name, value).

[1] http://docs.python.org/2/reference/datamodel.html#customizing-attribute-access [1] http://docs.python.org/2/reference/datamodel.html#customizing-attribute-access

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