Immutable data types are important to use in functional programming as they offer advantages, such as:

• thread-safe data manipulation
• preventing programmers from accidentally changing a value

We can create a tuple of tuples with a mix of datatypes, like the following:

student  = (("Scott", 28, 'A'), ("Nicole", 26, 'B'), ("John", 29, 'D')) # mixed elements 

This is a great way to store our mixed data. However, there is room for improvement. The student tuple contains records of students in a CS class where each tuple stores the student’s name, age, and the grade they received. Defining a tuple in this manner is prone to errors as it requires the programmer to remember the position of each piece of data in the tuple.

Instead, we can use a namedtuple data type from the collections library like so:

from collections import namedtuple

# Create a class called student
student = namedtuple("student", ["name", "age", "grade"]) 

# Create tuples for the three students

scott = student("Scott", 28, 'A')
nicole = student("Nicole", 26, 'B')
john = student("John", 29, 'D')

We access the student information:

from collections import namedtuple

# create a class called student
student = namedtuple("student", ["name", "age", "grade"]) 

# Create tuples for the three students
scott = student("Scott", 28, 'A')
nicole = student("Nicole", 26, 'B')
john = student("John", 29, 'D')

# Access Scott’s information for example
print(scott.name) # Output: Scott
print(scott.age) # Output: 28
print(scott.grade) # Output: ‘A’

Take note that the name of the tuple and the variable that stores the tuple must be identical.

We can package three student tuples neatly into a tuple called students like so:

students = (scott, nicole, john)

The programmer is no longer required to remember the position of each piece of data as they can reference it using the property name.