This excerpt discusses the concept of descriptors in Python, particularly focusing on the @property decorator and its functionality. It explains how attributes access with descriptors allows for custom behavior during attribute retrieval and assignment and illustrates the differences between using properties and descriptors across multiple classes. The document concludes by highlighting the scalability and encapsulation benefits of using descriptors over traditional properties.

1. amitu.com
Descriptors In
Python
Excerpt from Python For Programmers
available on amitu.com/python/

2. amitu.com Descriptors In Python
This is an excerpt of my upcoming python book
amitu.com/python/

3. amitu.com Descriptors In Python
Lets take a look at property in Python

4. amitu.com Descriptors In Python
Or with a @property syntax sugar

5. amitu.com Descriptors In Python
So what exactly is the property() returning?

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And why don't we get what property() returns
when we access .first_name?
student.first_name appears to be simple
string object!

7. amitu.com Descriptors In Python
And assigning to a property is even weirder.
It doesn't seem to be overwriting anything,
as normally assignment does.
It calls a function! The setter.
What were you smoking Guido?!?

8. amitu.com Descriptors In Python
We know that properties are useful, no
complaints here.
The real question is…
… is this some compiler/interpreter magic?
or
is it application of some simple feature
available to us?

9. amitu.com Descriptors In Python
We know the @ syntax is just a syntax
sugar, we love it, we create decorators
using them.
Out of @property()…
Which leaves us with property()
function or decorator.
Is property() special, or can we write it ourselves?

10. amitu.com Descriptors In Python
… and the answer is YES!
The name of the feature is descriptor.
Django’s ORM uses it extensively
for example…

11. amitu.com Descriptors In Python
Lets recap what happens when Python sees
attribute access:
[of course we are simplifying thins, no __mro__, no
__call__ etc etc]

12. amitu.com Descriptors In Python
… but the picture is closer to:
(we are reusing the function defined in previous slide)

13. amitu.com Descriptors In Python
… or in English:
If on an object, say o, when you do an attribute
lookup, say o.x, if Python finds an object at o.x
that has o.x.__get__ attribute, then instead of
returning o.x, it returns whatever
o.x.__get__(o, o.__class__) returns.

14. amitu.com Descriptors In Python
… when doing setting an attribute, (o.x = 10),
o.x__set__(o, 10) is looked up and called …
And this is not only for reading an attribute…
… and when you call del o.x,
o.x.__delete__(obj, o.__class__) is called if
present.

15. amitu.com Descriptors In Python
With that in mind, lets implement @property:
Doesn’t look that hard, does it?

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Lets use our MyProperty:
Works like a charm!

17. amitu.com Descriptors In Python
When better_lookup() sees .first_name, it
finds instance of our class, and our class
instances do have .__get__(), so Python calls
it, which calls ._getter(), that was passed to
MyProperty() constructor (.__init__())
because we used it as a decorator!

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Please note:
MyProperty class instance is created when
Student class is being constructed (as against
when student instance is being initialised).

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Lets try setter:

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Using the setter:

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How we implemented @name.setter is by
realising that name now points to an
instance of our MyProperty class, and that
instance happened to have .setter()
method, which happens to take a function
as argument, so name.setter can be used
as a decorator too.

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Cool, so we can implement @property
using descriptors.
Next question is:
When to use descriptor over property?

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The deciding factor:
The implementation of the property lives
inside the class that is using the property.
The descriptor on the other hand is a
separate class altogether.
Let me clarify…

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Say we want to implement .name on a
bunch of classes.
1. It must convert assigned names to
UPPER case.
2. It must validate that name is composed
of two words.
3. Name must be maximum of 100 chars
long.

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Say we want .name on Student, Parent and
Teacher classes, and they have nothing else
in common.

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One solution is we implement a NamedObject,
and subclass each of Student, Parent and
Teacher from NamedObject:
and so on for Parent and Teacher

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The property based solution works, but it
does not “scale”.
What if we don't just have .name, but
also .spouse_name on Student?
What if along with .name
and .spouse_name, we also want different
length validations on each name, .name
must be 100 chars, but .spouse_name upto
80 chars?

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A property based solution would
require us to keep track
of ._name, ._spouse_name, ._nam
e_length and ._spouse_length on
Student object.

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Lets see how to implemented this using descriptors?

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As you can see descriptor scales pretty well,
encapsulates better.
We can even subclass Name descriptor to add
more features to it, and we wont have to touch
the Student class etc.

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A note on descriptors as class attributes:
If we try to access a descriptor using the class instead
of instance, e.g. Student.name instead of
student.name (where student = Student()), .__get__()
is still called with obj set to None.

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… and at class level .__set__()
and .__delete__() calls are not allowed.

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Thats it for now!
You have seen a section in my Python for
Developers book. This covers python
material for people who're already
developers, even python developers.
Check it out: amitu.com/python/