Last Updated on March 13, 2023 by Prepbytes
In computer science, immutable and mutable are the terms or concepts by which we can describe whether an object’s value can be changed after it is created. In Python, a tuple is a data type and an ordered sequence of values, similar to a list. However, unlike lists, tuples are immutable, meaning that once they are created, their contents cannot be changed but the list is mutable. So in this article, we are going to understand that a tuple is mutable or immutable.
Mutable and Immutable in Python
Datatypes in Python can be either mutable or immutable. An immutable data type is a datatype in which we have a value that cannot be changed after it is created, whereas mutable data types are the datatypes that can be changed.
Immutable data types in python include strings, integers, floating-point numbers, and tuples. An immutable object cannot be changed or updated once it is created. For example, if you create the string "prep", you cannot change it to become "prepbytes". You must instead create a new string with the desired value.
Mutable data types in Python, on the other hand, include lists, dictionaries, and sets. After they are created, these objects can be modified. You can, for example, add, remove, or modify elements in a list.
The distinction between mutable and immutable data types is important because it influences how Python treats variables. You create a memory reference to an object when you assign a value to a variable. Any changes made to the object will be reflected in all references to it if it is mutable. Any changes to an immutable object result in the creation of a new object in memory.
What is Tuple?
Tuple is one of the four inbuilt data types used to store collections in python and they are used to store multiple items in a single variable Tuples are defined using parentheses and commas to separate the individual elements. One of the main benefits of using tuples over lists is that they are immutable, which means that they cannot be changed once they are created. This can be useful in situations where you want to ensure that the data cannot be accidentally modified.
In general, use immutable data types when you want to ensure that the value of the variable cannot be changed, and mutable data types when you need to change the value of the variable. However, the choice of data type is ultimately determined by the needs of your specific use case.
Is Tuple Mutable or Immutable?
In Python, a tuple is an ordered and immutable collection of elements. Once a tuple is created, its elements cannot be modified, added, or removed.
Example 1 to check whether a tuple is mutable or immutable?
Here is an example to demonstrate the immutability of tuples:
Code Implementation:
# here we create a tuple
my_tuple = (1, 2, 3)
# now we try to modify an element
my_tuple[0] = 4 Output
TypeErrorExplanation
In this example, we create a tuple named as my_tuple with the elements 1, 2, and 3. then we try to modify or update the first element of the tuple by assigning it the value 4.
So as we know we can access the tuple element by simple indexing, so here we try to assign the value of 4 at the 0th index. So the result here comes is a Type error which proves tuples are immutable in nature
Example 2 to check whether the tuple is mutable or immutable?
Another example to illustrate the immutable nature of tuples:
Code Implementation:
# create a tuple of strings
my_tuple = ('apple', 'banana', 'cherry')
# try to add an element
my_tuple.append('orange') Output:
AttributeErrorExplanation
In this example, we create a tuple called my_tuple with three string elements. We then try to add an additional element to the tuple using the append() method, but this results in an AttributeError because tuples do not have an append() method.
Tuples are immutable in Python, meaning their elements cannot be modified, added, or removed after they have been created.
Conclusion
So we can conclude now that tuples are immutable means we cannot change the values in tuples or update, them once it was created. Tuples are similar to lists but lists are mutable. We have also checked the immutable nature of tuples from various examples. Tuples are often used to store related data as a single unit and can be indexed and sliced like lists. They are useful for representing data that should not be changed, such as constants or keys in a dictionary. Examples of mutable objects include lists, dictionaries, and sets, while examples of immutable objects include tuples, strings, and integers. It is generally recommended to use immutable objects when possible, as they are safer to use in concurrent or parallel programming environments, and they can also help prevent unintended side effects caused by changing an object’s value.
Frequently Asked Questions(FAQs)
Here are some FAQs
Q1: Tuple is mutable or immutable?
Ans: A tuple is immutable in Python. Once it is created, its elements cannot be modified, added, or removed.
Q2: What is the difference between a tuple and a list in Python?
A: The main difference between a tuple and a list in Python is that a tuple is immutable, while a list is mutable. This means that once a tuple is created, its elements cannot be changed, while a list can be modified.
Q3: When should I use a tuple in Python?
A: Tuples are useful in Python when you need to store a collection of related data that should not be changed, such as a date or a set of coordinates. They can also be used as keys in dictionaries because they are immutable.
Q4: Can I convert a list to a tuple in Python?
A: Yes, you can convert a list to a tuple in Python using the tuple() function. This creates a new tuple object that contains the same elements as the original list.
Q5: Can I add or remove elements from a tuple in Python?
A: No, you cannot add or remove elements from a tuple in Python. Tuples are immutable, which means that their contents cannot be changed once they are created. If you need to modify a collection of elements, use a list instead.
Q6: Why are tuples useful in Python?
A: Tuples are useful in Python because they provide a way to store a collection of related data as a single unit, and they cannot be modified once they are created. This makes them safer to use in concurrent or parallel programming environments and can help prevent unintended side effects caused by changing an object’s value.