Python vars() Function

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The vars() function in Python is a built-in function that returns the __dict__ attribute of a module, class, instance, or any other object with a __dict__ attribute. Objects returned by vars() are in a dictionary form. This function can be quite useful for introspection, to inspect the properties (including methods) of an object and its values at runtime.

Understanding vars( ) in Python

The vars() function is often compared to the dir() function, which lists the attributes and methods of an object. However, while dir() provides a list of names, vars() attempts to provide the actual values associated with those names.


Here’s the basic syntax of the vars() function:



object – The object whose attributes and attribute values you want to retrieve. If object is omitted, vars() acts like locals(), which returns a dictionary of the current local symbol table.

Return Value:

The vars( ) method returns:

  • __dict__ attribute of the given object.
  • methods in the local scope when no arguments are passed
  • TypeError if the object passed doesn’t have the __dict__ attribute

When to Use vars( )

vars() is typically used for debugging and during development when you need to know the internal state of an object, or when you’re working with metaprogramming and need to manipulate an object’s state dynamically.

Using vars( ) with Different Types of Objects

  1. Modules: When used on a module, vars() returns the attributes of the module, including functions, classes, and variables defined in it.
  2. Classes: When used on a class, vars() returns the class attributes, including any class variables and methods defined in it.
  3. Instances: When used on an instance of a class, vars() returns the instance attributes, which are the values assigned to the object.
  4. Dictionaries: If the object is a dictionary, vars() returns the dictionary itself.

Example Usage of vars( )

Here’s an example of how to use vars():

class MyClass:
    class_variable = 1

    def __init__(self, instance_variable):
        self.instance_variable = instance_variable

# Instantiate the class
my_instance = MyClass(2)

# Use vars() on the class
print(vars(MyClass))  # Outputs the class's namespace dictionary

# Use vars() on the instance
print(vars(my_instance))  # Outputs the instance's namespace dictionary


{'__module__': '__main__', 'class_variable': 1, '__init__': <function MyClass.__init__ at 0x00000235E8F80D30>, '__dict__': <attribute '__dict__' of 'MyClass' objects>, '__weakref__': <attribute '__weakref__' of 'MyClass' objects>, '__doc__': None}
{'instance_variable': 2}

In this example, vars(MyClass) returns a dictionary containing class_variable, while vars(my_instance) returns a dictionary containing instance_variable.

Limitations of vars( )

  1. Immutability: Not all objects have a __dict__ attribute. For example, if you try to use vars() on an immutable object like a number or a string, you’ll get a TypeError because these types of objects don’t have a __dict__ attribute.
  2. Custom Objects: Custom objects that override the __dict__ attribute or provide a __slots__ attribute for memory optimization may not work as expected with vars().
  3. Privacy: The vars() function does not respect data encapsulation. It will display all the attributes, including those meant to be private (with a leading underscore).

Comparison with __dict__ Attribute

The vars() function is essentially a wrapper around the __dict__ attribute. You could get the same result by accessing object.__dict__ directly. However, using vars() is considered more Pythonic and it’s easier to read.

Example Where vars( ) is equivalent to __dict__

class MyClass:
    def __init__(self, value):
        self.attribute = value

obj = MyClass(10)
print(vars(obj))  # {'attribute': 10}
print(obj.__dict__)  # {'attribute': 10}

Both vars(obj) and obj.__dict__ return the same dictionary.


The vars() function is a powerful introspection tool in Python that can provide insights into the inner workings of objects. It’s especially useful for debugging purposes or when you need to work with the attributes of an object in a dynamic or automated way. However, it should be used judiciously, as it exposes the internal state of objects which could lead to tightly coupled code or break the principles of encapsulation if misused.

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