What's the pythonic way to use getters and setters?

问题

I\'m doing it like:

def set_property(property,value):  
def get_property(property):

object.property = value  
value = object.property

I\'m new to Python, so i\'m still exploring the syntax, and i\'d like some advice on doing this.

回答1:

Try this: Python Property

The sample code is:

class C(object):
    def __init__(self):
        self._x = None

    @property
    def x(self):
        """I'm the 'x' property."""
        print("getter of x called")
        return self._x

    @x.setter
    def x(self, value):
        print("setter of x called")
        self._x = value

    @x.deleter
    def x(self):
        print("deleter of x called")
        del self._x


c = C()
c.x = 'foo'  # setter called
foo = c.x    # getter called
del c.x      # deleter called

回答2:

What's the pythonic way to use getters and setters?

The "Pythonic" way is not to use "getters" and "setters", but to use plain attributes, like the question demonstrates, and del for dereferencing (but the names are changed to protect the innocent... builtins):

value = 'something'

obj.attribute = value  
value = obj.attribute
del obj.attribute

If later, you want to modify the setting and getting, you can do so without having to alter user code, by using the property decorator:

class Obj:
    """property demo"""
    #
    @property
    def attribute(self): # implements the get - this name is *the* name
        return self._attribute
    #
    @attribute.setter
    def attribute(self, value): # name must be the same
        self._attribute = value
    #
    @attribute.deleter
    def attribute(self): # again, name must be the same
        del self._attribute

(Each decorator copies and updates the prior property object, so note that you should probably use the same name for each set, get, and delete function/method.)

After defining the above, the original setting, getting, and deleting is the same:

obj = Obj()
obj.attribute = value  
the_value = obj.attribute
del obj.attribute

You should avoid this:

def set_property(property,value):  
def get_property(property):

Firstly, the above doesn't work, because you don't provide an argument for the instance that the property would be set to (usually self), which would be:

class Obj:

    def set_property(self, property, value): # don't do this
        ...
    def get_property(self, property):        # don't do this either
        ...

Secondly, this duplicates the purpose of two special methods, __setattr__ and __getattr__.

Thirdly, we also have the setattr and getattr builtin functions.

    setattr(object, 'property_name', value)
    getattr(object, 'property_name', default_value)  # default is optional

The @property decorator is for creating getters and setters.

For example, we could modify the setting behavior to place restrictions the value being set:

    class Protective(object):

        @property
        def protected_value(self):
            return self._protected_value

        @protected_value.setter
        def protected_value(self, value):
            if acceptable(value): # e.g. type or range check
                self._protected_value = value

In general, we want to avoid using property and just use direct attributes.

This is what is expected by users of Python. Following the rule of least-surprise, you should try to give your users what they expect unless you have a very compelling reason to the contrary.

Demonstration

For example, say we needed our object's protected attribute to be an integer between 0 and 100 inclusive, and prevent its deletion, with appropriate messages to inform the user of its proper usage:

class Protective(object):
    def __init__(self, start_protected_value=0):
        self.protected_value = start_protected_value
    @property
    def protected_value(self):
        return self._protected_value
    @protected_value.setter
    def protected_value(self, value):
        if value != int(value):
            raise TypeError("protected_value must be an integer")
        if 0 <= value <= 100:
            self._protected_value = int(value)
        else:
            raise ValueError("protected_value must be " +
                             "between 0 and 100 inclusive")
    @protected_value.deleter
    def protected_value(self):
        raise AttributeError("do not delete, protected_value can be set to 0")

And usage:

>>> p1 = Protective(3)
>>> p1.protected_value
3
>>> p1 = Protective(5.0)
>>> p1.protected_value
5
>>> p2 = Protective(-5)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in __init__
  File "<stdin>", line 15, in protected_value
ValueError: protectected_value must be between 0 and 100 inclusive
>>> p1.protected_value = 7.3
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 17, in protected_value
TypeError: protected_value must be an integer
>>> p1.protected_value = 101
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 15, in protected_value
ValueError: protectected_value must be between 0 and 100 inclusive
>>> del p1.protected_value
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 18, in protected_value
AttributeError: do not delete, protected_value can be set to 0

Do the names matter?

Yes they do. .setter and .deleter make copies of the original property. This allows subclasses to properly modify behavior without altering the behavior in the parent.

class Obj:
    """property demo"""
    #
    @property
    def get_only(self):
        return self._attribute
    #
    @get_only.setter
    def get_or_set(self, value):
        self._attribute = value
    #
    @get_or_set.deleter
    def get_set_or_delete(self):
        del self._attribute

Now for this to work, you have to use the respective names:

obj = Obj()
# obj.get_only = 'value' # would error
obj.get_or_set = 'value'  
obj.get_set_or_delete = 'new value'
the_value = obj.get_only
del obj.get_set_or_delete
# del obj.get_or_set # would error

I'm not sure where this would be useful, but the use-case is if you want a get, set, and/or delete-only property. Probably best to stick to semantically same property having the same name.

Conclusion

Start with simple attributes.

If you later need functionality around the setting, getting, and deleting, you can add it with the property decorator.

Avoid functions named set_... and get_... - that's what properties are for.

回答3:

In [1]: class test(object):
    def __init__(self):
        self.pants = 'pants'
    @property
    def p(self):
        return self.pants
    @p.setter
    def p(self, value):
        self.pants = value * 2
   ....: 
In [2]: t = test()
In [3]: t.p
Out[3]: 'pants'
In [4]: t.p = 10
In [5]: t.p
Out[5]: 20

回答4:

Check out the @property decorator.

回答5:

Using @property and @attribute.setter helps you to not only use the "pythonic" way but also to check the validity of attributes both while creating the object and when altering it.

class Person(object):
    def __init__(self, p_name=None):
        self.name = p_name

    @property
    def name(self):
        return self._name

    @name.setter
    def name(self, new_name):
        if type(new_name) == str: #type checking for name property
            self._name = new_name
        else:
            raise Exception("Invalid value for name")

By this, you actually 'hide' _name attribute from client developers and also perform checks on name property type. Note that by following this approach even during the initiation the setter gets called. So:

p = Person(12)

Will lead to:

Exception: Invalid value for name

But:

>>>p = person('Mike')
>>>print(p.name)
Mike
>>>p.name = 'George'
>>>print(p.name)
George
>>>p.name = 2.3 # Causes an exception

回答6:

You can use accessors/mutators (i.e. @attr.setter and @property) or not, but the most important thing is to be consistent!

PEP8, Designing for Inheritance says:

For simple public data attributes, it is best to expose just the attribute name, without complicated accessor/mutator methods. Keep in mind that Python provides an easy path to future enhancement, should you find that a simple data attribute needs to grow functional behavior. In that case, use properties to hide functional implementation behind simple data attribute access syntax.

On the other hand, according to Google Style Guide Python Language Rules/Properties the recommendation is to:

Use properties in new code to access or set data where you would normally have used simple, lightweight accessor or setter methods. Properties should be created with the @property decorator.

The pros of this approach:

Readability is increased by eliminating explicit get and set method calls for simple attribute access. Allows calculations to be lazy. Considered the Pythonic way to maintain the interface of a class. In terms of performance, allowing properties bypasses needing trivial accessor methods when a direct variable access is reasonable. This also allows accessor methods to be added in the future without breaking the interface.

and cons:

Must inherit from object in Python 2. Can hide side-effects much like operator overloading. Can be confusing for subclasses.

回答7:

You can use the magic methods __getattribute__ and __setattr__.

class MyClass:
    def __init__(self, attrvalue):
        self.myattr = attrvalue
    def __getattribute__(self, attr):
        if attr == "myattr":
            #Getter for myattr
    def __setattr__(self, attr):
        if attr == "myattr":
            #Setter for myattr

Be aware that __getattr__ and __getattribute__ are not the same. __getattr__ is only invoked when the attribute is not found.

来源：https://stackoverflow.com/questions/2627002/whats-the-pythonic-way-to-use-getters-and-setters

标签

python

getter-setter

What&#39;s the pythonic way to use getters and setters?

问题

回答1:

回答2: