NamedTuple in Python

The NamedTuple is another class, under the collections module. Like the dictionary type objects, it contains keys and that are mapped to some values. In this case we can access the elements using keys and indexes.

To use it at first we need to import it the collections standard library module.

import collections

In this section we will see some functions of the NamedTuple class.

The accessing methods of NamedTuple

From NamedTuple, we can access the values using indexes, keys and the getattr() method. The attribute values of NamedTuple are ordered. So we can access them using the indexes.

The NamedTuple converts the field names as attributes. So using getattr() it is possible to get the data from that attribute.

Example Code

import collections as col
#create employee NamedTuple
Employee = col.namedtuple('Employee', ['name', 'city', 'salary'])
#Add two employees
e1 = Employee('Asim', 'Delhi', '25000')
e2 = Employee('Bibhas', 'Kolkata', '30000')
#Access the elements using index
print('The name and salary of e1: ' + e1[0] + ' and ' + e1[2])
#Access the elements using attribute name
print('The name and salary of e2: ' + e2.name + ' and ' + e2.salary)
#Access the elements using getattr()
print('The City of e1 and e2: ' + getattr(e1, 'city') + ' and ' + getattr(e2, 'city'))

Output

The name and salary of e1: Asim and 25000
The name and salary of e2: Bibhas and 30000
The City of e1 and e2: Delhi and Kolkata

Conversion procedures of NamedTuple

There are some methods to convert other collections to NamedTuple. The _make() method can be used to convert an iterable object like list, tuple, etc to NamedTuple object.

We can also convert a dictionary type object to NamedTuple object. For this conversion, we need the ** operator.

NamedTuple can return the values with keys as OrderedDict type object. To make it OrderedDict, we have to use the _asdict() method.

Example Code

import collections as col
#create employee NamedTuple
Employee = col.namedtuple('Employee', ['name', 'city', 'salary'])
#List of values to Employee
my_list = ['Asim', 'Delhi', '25000']
e1 = Employee._make(my_list)
print(e1)
#Dict to convert Employee
my_dict = {'name':'Bibhas', 'city' : 'Kolkata', 'salary' : '30000'}
e2 = Employee(**my_dict)
print(e2)
#Show the named tuple as dictionary
emp_dict = e1._asdict()
print(emp_dict)

Output

Employee(name='Asim', city='Delhi', salary='25000')
Employee(name='Bibhas', city='Kolkata', salary='30000')
OrderedDict([('name', 'Asim'), ('city', 'Delhi'), ('salary', '25000')])

Some additional operations on NamedTuple

There are some other method like _fields() and _replace(). Using the _fields() method we can check what are the different fields of NamedTuple. The _replace() method is used to replace the value of some other value.

Example Code

import collections as col
#create employee NamedTuple
Employee = col.namedtuple('Employee', ['name', 'city', 'salary'])
#Add an employees
e1 = Employee('Asim', 'Delhi', '25000')
print(e1)
print('The fields of Employee: ' + str(e1._fields))
#replace the city of employee e1
e1 = e1._replace(city='Mumbai')
print(e1)

Output

Employee(name='Asim', city='Delhi', salary='25000')
The fields of Employee: ('name', 'city', 'salary')
Employee(name='Asim', city='Mumbai', salary='25000')