In Python, Everything is Object

Python is an object-oriented language, where every assignment can be much bigger than it seems.

For example, a simple string assignment to a variable:

x = “hello”

This string assignment is actually an object that can hold many pieces of contextual data such as the length of the string.

All objects have an ID.

But how does Python find these objects?

The id() function might help.

The id() function returns the unique ID from every object. Common objects, like integers from -5 to 256 have constant IDs that don’t change. Common objects will have constant IDs to speed up python code.

id(0)

#10105056

All objects have a Type.

The type() function returns the type from the object.

The type of the object has attributes that cannot be changed.

For example, the string, “2”, cannot be be mathematically added to the integer, 2, because they have different types.

Some object types are mutable.

Mutable objects have values that can be mutated, or changed.

There are only three mutable types in python: set, list, and dict.

Likewise, most other object types are immutable.

Immutable objects have values that can be changed.

Perhaps an immutable object can be copied, but they cannot be changed.

All other types, such as tuples, strings, float, int, and bool are immutable objects.

Just as an immutable object must be copied in order to make a new value, when an immutable object is passed into a function, instead of the original object being passed, only a copy is passed instead. For this reason, the following code does not result in changes:

The result would be 12 instead of 13.

If we used a similar example, but replaced the assignment with a mutable list instead of an immutable type, then the printed list would reflect changes made by the function because the list type is mutable.