Python classes: Dynamic properties

Posted on 10 March 2010 in Articles • 3 min read

I love Python 3

Even Python 2.x is still used everywhere, it is time to move to Python 3. I made the code fully Python2.6 - compatible, but if you'd like to have a nice output of print(..) function please use the

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from __future__ import print_function

statement.

A simple class

This is a simple class with one property:

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class Man(object):
    def __init__(self, name):
        self._name = name

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

    @name.setter
    def name(self, value):
        self._name = value

    m = Man('Alex Black')
    print(m.name)

    m.name = 'Kyra Brown'
    print(m.name)

The output is:

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Alex Black
Kyra Brown

We keep the local values in attributes that start with the underscore, e.g. self._name. Usually this is a way I separate "private" and "public" members of a class/object [1] (of course this "private" members remain "public").

This code does the same as the code above:

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class Man(object):
    def __init__(self, name):
        self._name = name

    def _name_get(self):
        return getattr(self, '_name')

    def _name_set(self, value):
        setattr(self, '_name', value)

    name = property(fget = _name_get, fset = _name_set)

There are two core changes:

  1. The _name attribute of an object is read and set by the getattr(..) and setattr(..) functions.
  2. The @property decorator is replaced by the built-in property(...) function [2] (which is actually "behind" that decorator).

Dynamic properties class

Finally, let's write a class called "Properties" that will allow adding dynamic properties. The properties will require local ("private") fields. We can use the same scheme as above, e.g. for property name, the private member of a class is _name:

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class Properties(object):
    def add_property(self, name, value):
        # create local fget and fset functions
        fget = lambda self: self._get_property(name)
        fset = lambda self, value: self._set_property(name, value)

        # add property to self
        setattr(self.__class__, name, property(fget, fset))
        # add corresponding local variable
        setattr(self, '_' + name, value)


    def _set_property(self, name, value):
        setattr(self, '_' + name, value)

    def _get_property(self, name):
        return getattr(self, '_' + name)

The trick in add_property(..) is that we create two lambda objects (those could also be anonymous functions) which use the self._get_property and self._set_property methods with particular value of name argument.

Let's play with this class:

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po = Properties()
po.add_property('user', 'noname')
po.add_property('speed', 50)

print(po.user, po.speed)

po.speed = 100
po.name = 'Alex Black'

print(po.user, po.speed)
print(po._user, po._speed)

The output is:

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noname 50
Alex Black 100
Alex Black 100

A practical usage

After all, what is a practical usage of dynamic properties? I'm sure you may have thought of that if you're reading this post now :) Here is a small example of a class which is able to "lock" the properties' setters:

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class PropertiesWithLock(object):
    def __init__(self, lock = False):
        self.lock = lock

    def add_property(self, name, value):
        fget = lambda self: self._get_property(name)
        fset = lambda self, value: self._set_property(name, value)

        setattr(self.__class__, name, property(fget, fset))
        setattr(self, '_' + name, value)


    def _set_property(self, name, value):
        if not self.lock:
            setattr(self, '_' + name, value)
        else:
             print('Cannot change "{0}": properties are locked'
                    .format(name))

    def _get_property(self, name):
        return getattr(self, '_' + name)

And the usage:

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po = PropertiesWithLock()
po.add_property('user', 'noname')
po.add_property('speed', 50)

print(po.user, po.speed)
>>> noname 50

po.user = 'a user'
po.speed = 200
print(po.speed)
>>> a user 200

po.lock = True
po.user = 'a user'
>>> Cannot change "user": properties are locked

programming Python