Defining

namedtuple instances are just as memory efficient as regular tuples because they do not have per-instance dictionaries. Each kind of namedtuple is represented by its own class, which is created by using the namedtuple() factory function. The arguments are the name of the new class and a string containing the names of the elements.



In [2]:

    
import collections

Person = collections.namedtuple('Person', 'name age')

bob = Person(name='Bob', age=30)
print('\nRepresentation:', bob)

jane = Person(name='Jane', age=29)
print('\nField by name:', jane.name)

print('\nFields by index:')
for p in [bob, jane]:
    print('{} is {} years old'.format(*p))









    



Representation: Person(name='Bob', age=30)

Field by name: Jane

Fields by index:
Bob is 30 years old
Jane is 29 years old

Just like a regular tuple, a namedtuple is immutable. This restriction allows tuple instances to have a consistent hash value, which makes it possible to use them as keys in dictionaries and to be included in sets.



In [3]:

    
import collections

Person = collections.namedtuple('Person', 'name age')

pat = Person(name='Pat', age=12)
print('\nRepresentation:', pat)

pat.age = 21









    



Representation: Person(name='Pat', age=12)






    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-3-aa922e21caaf> in <module>()
      6 print('\nRepresentation:', pat)
      7 
----> 8 pat.age = 21

AttributeError: can't set attribute

Invalid Field Names

Field names are invalid if they are repeated or conflict with Python keywords.



In [4]:

    
import collections

try:
    collections.namedtuple('Person', 'name class age')
except ValueError as err:
    print(err)

try:
    collections.namedtuple('Person', 'name age age')
except ValueError as err:
    print(err)









    



Type names and field names cannot be a keyword: 'class'
Encountered duplicate field name: 'age'

In situations where a namedtuple is created based on values outside the control of the program (such as to represent the rows returned by a database query, where the schema is not known in advance), the rename option should be set to True so the invalid fields are renamed.



In [5]:

    
import collections

with_class = collections.namedtuple(
    'Person', 'name class age',
    rename=True)
print(with_class._fields)

two_ages = collections.namedtuple(
    'Person', 'name age age',
    rename=True)
print(two_ages._fields)









    



('name', '_1', 'age')
('name', 'age', '_2')

Special Attributes

namedtuple provides several useful attributes and methods for working with subclasses and instances. All of these built-in properties have names prefixed with an underscore (_), which by convention in most Python programs indicates a private attribute. For namedtuple, however, the prefix is intended to protect the name from collision with user-provided attribute names.

The names of the fields passed to namedtuple to define the new class are saved in the _fields attribute.



In [6]:

    
import collections

Person = collections.namedtuple('Person', 'name age')

bob = Person(name='Bob', age=30)
print('Representation:', bob)
print('Fields:', bob._fields)









    



Representation: Person(name='Bob', age=30)
Fields: ('name', 'age')

namedtuple instances can be converted to OrderedDict instances using _asdict().



In [7]:

    
import collections

Person = collections.namedtuple('Person', 'name age')

bob = Person(name='Bob', age=30)
print('Representation:', bob)
print('As Dictionary:', bob._asdict())









    



Representation: Person(name='Bob', age=30)
As Dictionary: OrderedDict([('name', 'Bob'), ('age', 30)])

The _replace() method builds a new instance, replacing the values of some fields in the process.



In [8]:

    
import collections

Person = collections.namedtuple('Person', 'name age')

bob = Person(name='Bob', age=30)
print('\nBefore:', bob)
bob2 = bob._replace(name='Robert')
print('After:', bob2)
print('Same?:', bob is bob2)









    



Before: Person(name='Bob', age=30)
After: Person(name='Robert', age=30)
Same?: False



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