Reflection is a powerful feature in programming that allows a program to manipulate the properties and capabilities of objects at runtime. In Python, reflection enables the inspection of classes, modules, and functions while the program is running, allowing you to examine and modify their behavior dynamically.

Python provides several built-in functions that support reflective capabilities, such as getattr(), setattr(), hasattr(), and delattr(). These functions allow for dynamic manipulation of attributes, and the type() and isinstance() functions help in introspecting types.

Using getattr()

The getattr() function allows you to access the value of an object's attribute by name.

Example

In this example, we will retrieve an attribute from an object using getattr().

Explanation:

• class Person: Defines a class with two attributes: name and age.
• getattr(person, 'name', 'Attribute not found'): Retrieves the value of the name attribute from the person object. If the attribute does not exist, it returns 'Attribute not found'.

Using setattr()

The setattr() function allows you to set the value of an attribute of an object.

Example

In this example, we will set an attribute of an object using setattr().

Explanation:

• setattr(person, 'age', 35): Sets the age attribute of the person object to 35.
• print(person.age): Displays the updated age, verifying that the attribute's value has been changed.

Using hasattr()

The hasattr() function checks if an object has an attribute.

Example

In this example, we will check for the presence of an attribute in an object using hasattr().

Explanation:

• hasattr(person, 'name'): Checks if the person object has an attribute named name.
• print(has_attribute): Outputs True indicating that the attribute exists.

Using delattr()

The delattr() function deletes an attribute from an object.

Example

In this example, we will delete an attribute from an object using delattr().

Explanation:

• delattr(person, 'age'): Deletes the age attribute from the person object.
• print(hasattr(person, 'age')): After deletion, this check returns False, indicating that the age attribute no longer exists.

Using type()

The type() function is essential for identifying the type of an object, which can be critical in debugging and dynamic type handling in applications.

Example

In this example, we will demonstrate how to use type() to obtain the type of various objects.

Explanation:

• type(5): Returns the type of an integer, which is <class 'int'>.
• type("Hello"): Returns the type of a string, which is <class 'str'>.
• type(person): Returns the type of person, which is <class '__main__.Person'>. This indicates that person is an instance of the Person class defined in the current module.

Using isinstance()

isinstance() is used to check if an object is an instance of a specific class or a tuple of classes, which is particularly useful in polymorphism where you want to confirm an object's class in inheritance hierarchies.

Example

In this example, we will check if certain objects are instances of predefined classes.

Explanation:

• isinstance(person, Person): Checks whether person is an instance of the Person class.
• isinstance(person, dict): Checks whether person is an instance of the dict class. Since person is a Person instance, this returns False.
• isinstance("Hello", (str, int)): Checks whether "Hello" is an instance of either the str or int class. Since it is a string, this returns True.

Reflection is a valuable feature in Python that enhances the flexibility of the code by allowing dynamic manipulation of objects. By using reflection methods, developers can write more generic and versatile functions, making the code easier to maintain and extend. This lesson on Python reflection provides foundational knowledge for using dynamic features to inspect and manipulate objects programmatically, fostering a deeper understanding of Python's capabilities.