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Python Academy · Lesson

Descriptors: __get__, __set__, __delete__

Implement the descriptor protocol for attribute access control.

Descriptors: __get__, __set__, __delete__ is a free Python Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Python Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

What Is a Descriptor?

A descriptor is an object that defines __get__, __set__, or __delete__ and is assigned as a class attribute. Python calls these methods on attribute access.

class Descriptor:
    def __get__(self, obj, objtype=None):
        print(f"__get__ called, obj={obj}")
        return 42

class MyClass:
    attr = Descriptor()

print(MyClass().attr)   # __get__ called ... 42

Data vs Non-Data Descriptors

Data descriptors define __set__ or __delete__ and take precedence over the instance __dict__. Non-data descriptors (only __get__) yield to __dict__.

class DataDesc:
    def __get__(self, obj, t): return "data"
    def __set__(self, obj, val): pass

class NonDataDesc:
    def __get__(self, obj, t): return "nondata"

class C:
    d = DataDesc()
    n = NonDataDesc()

c = C()
c.__dict__["n"] = "instance"  # shadows the non-data desc
c.__dict__["d"] = "instance"  # does NOT shadow data desc
print(c.n)   # instance
print(c.d)   # data

__get__ Signature

__get__(self, obj, objtype): obj is the instance (or None when accessed on the class); objtype is the class.

class Verbose:
    def __get__(self, obj, objtype=None):
        if obj is None:
            return self   # accessed on class
        return f"value for {obj!r}"

class Widget:
    label = Verbose()

print(Widget.label)        # <Verbose object>
print(Widget().label)      # value for <Widget object>

__set__ and Validation

Implement __set__(self, obj, value) to validate or transform a value before storing it.

class PositiveInt:
    def __set_name__(self, owner, name):
        self.name = name

    def __get__(self, obj, t):
        return obj.__dict__.get(self.name)

    def __set__(self, obj, val):
        if not isinstance(val, int) or val <= 0:
            raise ValueError(f"{self.name} must be a positive int")
        obj.__dict__[self.name] = val

class Rect:
    width  = PositiveInt()
    height = PositiveInt()

r = Rect()
r.width = 10
# r.width = -1  # ValueError

__set_name__

Python 3.6+ calls __set_name__(owner, name) on the descriptor when it is assigned to a class, giving it access to its own attribute name.

class Typed:
    def __set_name__(self, owner, name):
        self.public  = name
        self.private = "_" + name

    def __get__(self, obj, t):
        return None if obj is None else getattr(obj, self.private, None)

    def __set__(self, obj, val):
        setattr(obj, self.private, val)

class User:
    name = Typed()

u = User()
u.name = "Alice"
print(u.name)     # Alice

__delete__ for Attribute Removal

Define __delete__(self, obj) to intercept del obj.attr.

class Protected:
    def __set_name__(self, owner, name): self.name = name
    def __get__(self, obj, t):
        return obj.__dict__.get(self.name)
    def __set__(self, obj, v): obj.__dict__[self.name] = v
    def __delete__(self, obj):
        raise AttributeError(f"Cannot delete {self.name}")

class Config:
    host = Protected()

c = Config(); c.host = "localhost"
# del c.host   # AttributeError

Functions Are Non-Data Descriptors

Functions implement __get__ to return a bound method when accessed on an instance. This is how Python's method binding works.

def greet(self):
    return f"Hello from {self}"

class C: pass
C.greet = greet

c = C()
print(c.greet())    # Hello from <C object>

classmethod and staticmethod Are Descriptors

classmethod and staticmethod are built-in descriptor classes that wrap functions and alter the __get__ return value.

class MyClass:
    @classmethod
    def from_string(cls, s):
        return cls()

# classmethod.__get__ returns a bound method with cls
# staticmethod.__get__ returns the plain function

Lazy Attribute Descriptor

Build a descriptor that computes a value once and caches it per instance.

class LazyAttr:
    def __init__(self, func): self.func = func
    def __set_name__(self, owner, name): self.name = name
    def __get__(self, obj, t):
        if obj is None: return self
        val = self.func(obj)
        obj.__dict__[self.name] = val   # shadows descriptor
        return val

class Report:
    @LazyAttr
    def summary(self):
        print("computing...")
        return "done"

r = Report()
print(r.summary)   # computing... done
print(r.summary)   # done (cached)

property Is a Descriptor

property is itself a data descriptor implemented in C. Understanding descriptors helps you understand how @property, @classmethod, and @staticmethod all work.

class Circle:
    def __init__(self, r): self._r = r

    @property
    def radius(self): return self._r

    @radius.setter
    def radius(self, v):
        if v < 0: raise ValueError
        self._r = v

# property is: property.__get__ = fget, property.__set__ = fset

Descriptor Lookup Order

Python attribute lookup order: 1) data descriptors from type (MRO), 2) instance __dict__, 3) non-data descriptors and class variables.

# Pseudocode for obj.attr:
# 1. Check type(obj).__mro__ for a data descriptor
# 2. Check obj.__dict__
# 3. Check type(obj).__mro__ for non-data descriptor or class var
# 4. Raise AttributeError

Quick Check

Which type of descriptor takes precedence over the instance __dict__?

Recap

Descriptors intercept attribute access via __get__, __set__, __delete__. Data descriptors shadow instance __dict__; non-data ones do not. Use __set_name__ to learn the attribute name. property, classmethod, and staticmethod are all descriptors.

Frequently asked questions

Is the “Descriptors: __get__, __set__, __delete__” lesson free?

Yes — the full text of “Descriptors: __get__, __set__, __delete__” is free to read here on the web, and the Python Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Python Academy course, upgrade to CoddyKit PRO.

What will I learn in “Descriptors: __get__, __set__, __delete__”?

Implement the descriptor protocol for attribute access control. You practise Python Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Python Academy?

No prior experience is required. Python Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Descriptors: __get__, __set__, __delete__” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Python Academy lesson?

Yes. Every Python Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. How Python Classes Are Created
  2. Writing Custom Metaclasses
  3. Descriptors: __get__, __set__, __delete__
  4. __slots__ and Memory Optimization
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