2.7 - Creating Custom Descriptors for Attribute Management
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Introduction to Descriptors
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Today, weβre going to learn about descriptors in Python. Can anyone tell me what a descriptor is?
Is it related to how we manage attributes in classes?
Exactly! Descriptors provide a means to customize attribute access in classes through methods like __get__, __set__, and __delete__. These methods control how attributes behave.
So, they allow us to add additional functionality without directly modifying the attributes?
Yes, exactly. Think of descriptors as a way to validate or transform data on attribute access. For example, if we wanted to ensure an attribute is always a specific type, descriptors are perfect for that!
Can you give us an example?
Sure! Let's look at the Typed descriptor example that follows, where we ensure that certain attributes conform to specified data types.
Creating the Typed Descriptor
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Letβs create a `Typed` descriptor that checks the type of an attribute. Hereβs the basic structure: it takes a name and an expected type.
How does it check the type when assigning a value?
Good question! In the `__set__` method of our `Typed` descriptor, we raise a `TypeError` if the provided value doesnβt match the expected type.
What happens if someone tries to delete the attribute?
Thatβs handled in the `__delete__` method where we prevent deletion by raising an `AttributeError`. This way, we ensure that critical attributes remain intact.
Using the Typed Descriptor in a Class
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Now, letβs see how to use our `Typed` descriptor in a class like `Person`.
What are the attributes weβre going to validate?
We will validate `name` to be a string and `age` to be an integer. So, if we try to assign a string to `age`, it should raise an error.
Can we test that out?
Sure! When we assign a wrong type to `age`, like a string, it raises a `TypeError`. Letβs implement and test this now.
Summary and Applications
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Great job today, everyone! So what have we learned about custom descriptors?
We learned to create a `Typed` descriptor that validates attribute types!
And we saw how to prevent deletions of important attributes!
Absolutely! Remember, by using descriptors, we can maintain data integrity and make our classes robust. Next, try implementing your own descriptor as homework.
Introduction & Overview
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Quick Overview
Standard
In this section, readers will learn how to create custom descriptors that validate attribute types in Python classes. The Typed descriptor example illustrates how to enforce specific data types for attributes like 'name' and 'age'.
Detailed
Creating Custom Descriptors for Attribute Management
In this section, we explore how to create custom descriptors in Python, specifically focusing on type validation for class attributes. Descriptors allow you to define methods that control how attributes are accessed and modified, providing a flexible mechanism for data validation.
Key Points:
- Typed Descriptor: We create a
Typeddescriptor which validates that assigned values conform to a specified type. - Attribute Control: The
__get__,__set__, and__delete__methods of the descriptor protocol allow for fine-grained control over how attributes behave when accessed or modified. - Practical Example: The
Personclass uses theTypeddescriptor to ensure that thenameis always a string andageis always an integer. If incorrect types are assigned, aTypeErroris raised.
Using such descriptors makes it easy to enforce constraints and ensure data integrity within our classes.
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Understanding Descriptors
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Chapter Content
Descriptors provide fine control over attribute access. Letβs create a descriptor that validates attribute values.
Detailed Explanation
Descriptors are objects that help manage and control access to attributes in Python classes. They give you the ability to customize how attributes are set, retrieved, or deleted. By creating a descriptor, you can enforce certain rules, like ensuring that only values of a specific type are set for an attribute.
Examples & Analogies
Think of a descriptor like a security guard at a club. The guard checks if the person wanting to enter matches certain criteria (like age). In this way, the descriptor ensures that only the right kind of data ('age' must be an integer) is allowed into your classes.
Example: Typed Attribute Descriptor
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Chapter Content
class Typed:
def init(self, name, expected_type):
self.name = name
self.expected_type = expected_type
def __get__(self, instance, owner):
if instance is None:
return self
return instance.__dict__[self.name]
def __set__(self, instance, value):
if not isinstance(value, self.expected_type):
raise TypeError(f"Expected {self.expected_type}")
instance.__dict__[self.name] = value
def __delete__(self, instance):
raise AttributeError("Can't delete attribute")
class Person:
name = Typed('name', str)
age = Typed('age', int)
def init(self, name, age):
self.name = name
self.age = age
p = Person("Alice", 30)
print(p.name) # Alice
p.age = 31 # Works fine
p.age = "Thirty" # Raises TypeError: Expected
Detailed Explanation
The Typed class here is a custom descriptor that validates the types of attributes. When you create an instance of Typed, you give it a name and the expected type. The __set__ method checks if the value being assigned matches the expected type. If it doesn't, it raises a TypeError. The __get__ method retrieves the value when accessed, while the __delete__ method prevents deletion of the attribute by raising an error. This means you can maintain strict control over what types of values are assigned to attributes in your class.
Examples & Analogies
Imagine you have a box labeled 'Important Documents' where you only want to store certain types of papers (like legal documents or contracts). The Typed descriptor acts like a strict organizer: it checks every item that goes into the box. If someone tries to put in a non-related paper (like a flyer), the organizer will stop them and say, 'That's not allowed here!' Just like how the descriptor prevents us from assigning incorrect types to class attributes.
Practical Use in a Class
Chapter 3 of 4
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Chapter Content
class Person:
name = Typed('name', str)
age = Typed('age', int)
def init(self, name, age):
self.name = name
self.age = age
p = Person("Alice", 30)
print(p.name) # Alice
p.age = 31 # Works fine
p.age = "Thirty" # Raises TypeError: Expected
Detailed Explanation
In the Person class, we've defined two attributes, name and age, using the Typed descriptor. When we create an instance of Person, the attributes are set through the descriptor. When we attempt to access p.name, it retrieves 'Alice' successfully. If we try to set p.age to a valid integer, it works without issues. However, if we attempt to assign a string like 'Thirty' to p.age, it raises a TypeError, enforcing the rule set in our descriptor that only integers are valid for the age attribute.
Examples & Analogies
Consider a driver's license application process where applicants must meet specific age criteria (like being at least 16 years old). The Typed descriptor is like the official reviewer who checks the applicant's age before approving the license. If an applicant states an age that does not meet the criteria, the reviewer will reject the application, just like how our descriptor prevents invalid age assignments.
Summary of Custom Descriptors
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Chapter Content
β Typed controls the setting and getting of name and age.
β The attribute value is stored in the instance's dict.
β Type validation enforces correct types on assignment.
Detailed Explanation
In summary, custom descriptors provide a powerful way to manage class attributes in Python. The Typed descriptor manages both how attributes are accessed (using __get__) and how they are set (using __set__), along with type validation. By storing the actual value in the instance's __dict__, it maintains the state of the object while ensuring that only appropriate data types are assigned to specific attributes. This leads to more robust and maintainable code.
Examples & Analogies
Think of this as a quality control process. If you're manufacturing a product (like a smartphone), you want to ensure each component (like the battery or screen) meets specific standards before assembly. The custom descriptor acts like a quality control inspector, ensuring that each part (or attribute) meets the necessary specifications, leading to a better outcome (or well-behaved object).
Key Concepts
-
Descriptor: A mechanism to customize how attributes are accessed.
-
Typed Descriptor: A specific descriptor to validate types of attribute values.
-
get, set, delete: Methods to control attribute behavior.
Examples & Applications
The 'Typed' descriptor is used to validate that the 'name' attribute is a string and 'age' is an integer.
If an attempt is made to assign a string to 'age', a TypeError is raised.
Memory Aids
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Rhymes
If you set a type that's wrong, a TypeError won't be long!
Stories
Imagine you have a robot that only accepts specific parts. If you try to give it the wrong part, it won't work. This is like our Typed descriptor validating types!
Memory Tools
Remember GSD: Get, Set, Delete for descriptor methods.
Acronyms
DPT - Descriptor, Proxy, Type. Descriptors proxy access to manage attribute types.
Flash Cards
Glossary
- Descriptor
An object attribute with binding behavior that defines methods controlling how attributes are accessed.
- Typed Descriptor
A custom descriptor that validates the type of assigned values to class attributes.
- __get__
A method in the descriptor protocol that retrieves the value of an attribute.
- __set__
A method in the descriptor protocol that sets the value of an attribute, with type checking.
- __delete__
A method in the descriptor protocol that deletes an attribute, often restricting deletion.
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