Mutable Data Types
The objects whose values can change after the creation of the objects are known as mutable data types. The values can be changed — you can’t add an item to the object, delete an item from the object, or change any value in the object with another value.
- Sets are mutable.
- Lists are mutable.
- Dictionaries are mutable.
For example, let’s consider Python lists that are mutable data types.
>>> l = [1, 2, 3] # at first there are 3 elements >>> l.append(98) # added one more element >>> l [1, 2, 3, 98] >>>
In the above example, you add a new element to the list. The list object changes because it is mutable.
More Examples
Let us consider a mutable object like a list and set. We can add, delete, change any element in the list. But in the case of sets, as python sets are an unordered collection of data to elements that can’t be accessed by indexes so any index value can’t be changed but we can add and remove elements from the set.
List Example:
>>> l = [2, 7, 8] # list >>> l.append(67) # addin item to list >>> l [2, 7, 8, 67] >>> l[1] = 45 # changing value of index 1 in list >>> l [2, 45, 8, 67] >>> l.remove(45) # removing 45 from the list >>> l [2, 8, 67] >>>
Set Example:
>>> s = set()
>>> s.add(23) # adding element to the set
>>> s.add(98) # adding another element
>>> s
{98, 23}
>>> s.remove(98) # removing element from set
>>> s
{23}
>>> As set is unordered collection so the order in which item is added doesn’t matter, item get shuffled every time when an element is added or removed.
Considerations Mutable Data Types
The mutable property of a list is an important part of Python, which enables the language to run programs quickly, allowing for greater flexibility and performance. This property also allows you to change an item within a list without rewriting the whole thing. The mutable property of a list means that you can add or remove elements of the list without having to recreate it. However, when working with lists, you should take care to make them mutable.
The object is mutable if it contains one or more types of data. Unlike immutable objects, Python variables are mutable. In Python, a mutable object is a tuple whose value can be changed. The value of a tuple can be replaced by another tuple.The mutable element can be changed and its order can be modified. The mutable element can be renamed by another.
The syntax of Python’s mutable object type is based on the concept of inheritance. When an object has multiple parents, it is possible to change their inheritance without affecting their children. However, the parent object must have the same type of child. For instance, a single parent can have one daughter and two sons, and the latter can have a daughter and a son. These two kinds of dependent objects are called iterables.
A set is mutable by adding or removing elements, and a single item can be changed without changing the rest of the set. For example, if a parent changes the name of a baby, the child’s name will remain the same. A mutable object can only be modified once. The parent object must also be mutable. The parent object must be mutable before it can be inherited.
Immutable Data Types
The objects whose values can’t be changed after the creation of the objects are known as immutable data types. The values can’t be changed: you can’t add more items to the object, delete more items from the object, or assign new values to the object.
For example, let’s consider Python’s tuple data structure for a moment. Tuples are immutable objects:
>>> t = (1, 3, 9) # at first there are 3 elements in the tuple
>>> t[0] = 32 # changing value of index results in an error
Traceback (most recent call last):
File "<pyshell#4>", line 1, in <module>
t[0] = 32 # changing value of index results in an error
TypeError: 'tuple' object does not support item assignment
>>> When the value is tried to change, Python raises an error.
Considerations Immutable Data Types
In Python, there are several immutable data types: list, tuple, string, float, and frozen sets. A tuple can contain many objects. A string represents a single character, and a float is a set of floats. These are called immutable objects. You can also create a tuple containing a variable and its values.
As you can see, both tuples and objects in Python are immutable. In other words, you can’t change a tuple’s value. If you want to change the value of a string, you must use an immutable tuple. It is best to use the tuple when you need to resize or rename it. Once you’ve done that, it’s time to save the tuple.
Immutable objects can’t be changed by a reference. Changing an object’s values is impossible. Instead, you must copy it to another variable. Then you need to assign a new object to the mutable version. When you change the value, you need to create a new one. This way, your Python code will not be affected. This will prevent the variable from being a duplicate of an immutable object.
Mutable vs Immutable
Python mutable is different from immutable in that you can change the data stored in it. Because it doesn’t need to be changed, it’s much faster to access than immutable objects. A mutable variable can be easily changed, while an immutable one can’t be changed. It’s easy to modify a tuple, but you have to make sure that you use the right kind of object.
In Python, all data is represented as an object. The variable’s type tells the type of operation it supports and where it can be stored. A mutable object is a value-based object. This means that it can be manipulated. Immutable objects are fixed, so they can’t be modified.
- Tuples are immutable. You can’t change the size, color, or shape of the tuple and the content. You can’t change the order of the items in a tuple.
- A float object is immutable. When you change a float, the value is permanent.
- A string is immutable, so you can’t rename a string.
But a list, set, or array is mutable—it can be changed after creation.