In Python, every value has a type. There are two kinds of types in Python: mutable and immutable. Mutable types can be changed. Immutable types can’t. That might sound like a simple distinction, but it’s an important one to understand. It leads to a fundamental difference in how these values are used in Python programs.
Python is a programming language with many data types. Some of these data types are mutable, which means they can be changed, and some are immutable, which means they cannot be changed.
The most common mutable data types in Python are lists and dictionaries. Lists are like arrays in other languages and can contain any type of data. Dictionaries are similar to objects in other languages and store key-value pairs.
Immutable data types in Python include integers, floats, strings, tuples, and sets. These data types cannot be changed once they have been created.
The benefits of using immutable objects
When it comes to Object-oriented programming, one of the most important concepts is mutability. An object is considered mutable if it can be changed after it’s been created. In contrast, an object is considered immutable if it can’t be changed after it’s been created.
There are advantages and disadvantages to using mutable and immutable objects. For example, immutable objects are often more efficient because they can be shared among multiple users without having to worry about data being changed. On the other hand, mutable objects offer more flexibility because they can be easily changed if necessary.
In general, immutable objects are preferable whenever possible. However, there are some situations where a mutable object is more appropriate. For example, if you need to change the value of an object frequently, then a mutable object would be more suitable.
The main benefits of using immutable objects are as follows:
1. They are more efficient because they can be shared among multiple users without having to worry about data being changed.
2. They offer more flexibility because they can be easily changed if necessary.
3. They are less likely to cause errors because their values can’t be changed accidentally.
The disadvantages of using mutable objects
There are a few disadvantages of using mutable objects in Python. One disadvantage is that if you have a mutable object as a member of a class, then other members of that class can change the state of the mutable object without your knowledge. This can lead to hard-to-debug errors.
Another disadvantage is that when you pass a mutable object to a function, the function can change the state of the object without your knowledge or permission. This can again lead to hard-to-debug errors.
Finally, immutable objects tend to be more efficient than mutable objects because they can be reused. When an immutable object is changed, a new object is created and the old one is discarded. This means that there is no need to keep track of multiple versions of the same object (as you would with a mutable object).
What are some examples of mutable and immutable objects in Python?
In Python, mutable and immutable objects are handled differently. Mutable objects can be changed after they are created, while immutable objects cannot.
Some examples of mutable objects in Python include lists, dictionaries, and sets. These data structures can all be modified after they have been created. Immutable objects in Python include strings, integers, and tuples. These data types cannot be changed after they are created.
How can I make my own custom mutable and immutable objects in Python?
There are two ways to create your own custom mutable and immutable objects in Python. The first way is to use the built-in data types of lists and tuples. Lists are mutable, so you can change their contents without creating a new object. Tuples are immutable, so you can’t change their contents without creating a new object.
The second way to create your own custom mutable and immutable objects is to use the classes in the collections module. The mutable classes are User Dict , User List , and User String . The immutable classes are Mapping Proxy Type , Sequence Proxy Type , and String Proxy Type .
Conclusion
Python is a programming language with both mutable and immutable data types. In this article, we’ve gone over what these terms mean and some of the most common examples of each. As you can see, understanding the difference between mutable and immutable data types is important for correctly using Python in your programs. With this knowledge in hand, you’re well on your way to becoming a proficient Python programmer. Skillslash can help you get into it with its Data Science Course In Delhi . It’s also popularly known for providing the best Data science course in Nagpur with placement guarantee. Skillslash also offers Data science course in Mangalore. Contact the support team to know more.
