What are "named tuples" in Python?
Reading the changes in Python 3.1, I found something... unexpected:
The sys.version_info tuple is now a named tuple :
I never heard about named tuples before, and I thought elements could either be indexed by numbers (like in tuples and lists) or by keys (like in dicts). I never expected they could be indexed both ways.
Thus, my questions are:
Named tuples are basically easy-to-create, lightweight object types. Named tuple instances can be referenced using object-like variable dereferencing or the standard tuple syntax. They can be used similarly to struct
or other common record types, except that they are immutable. They were added in Python 2.6 and Python 3.0, although there is a recipe for implementation in Python 2.4.
For example, it is common to represent a point as a tuple (x, y)
. This leads to code like the following:
pt1 = (1.0, 5.0)
pt2 = (2.5, 1.5)
from math import sqrt
line_length = sqrt((pt1[0]-pt2[0])**2 + (pt1[1]-pt2[1])**2)
Using a named tuple it becomes more readable:
from collections import namedtuple
Point = namedtuple('Point', 'x y')
pt1 = Point(1.0, 5.0)
pt2 = Point(2.5, 1.5)
from math import sqrt
line_length = sqrt((pt1.x-pt2.x)**2 + (pt1.y-pt2.y)**2)
However, named tuples are still backwards compatible with normal tuples, so the following will still work:
Point = namedtuple('Point', 'x y')
pt1 = Point(1.0, 5.0)
pt2 = Point(2.5, 1.5)
from math import sqrt
# use index referencing
line_length = sqrt((pt1[0]-pt2[0])**2 + (pt1[1]-pt2[1])**2)
# use tuple unpacking
x1, y1 = pt1
Thus, you should use named tuples instead of tuples anywhere you think object notation will make your code more pythonic and more easily readable . I personally have started using them to represent very simple value types, particularly when passing them as parameters to functions. It makes the functions more readable, without seeing the context of the tuple packing.
Furthermore, you can also replace ordinary immutable classes that have no functions , only fields with them. You can even use your named tuple types as base classes:
class Point(namedtuple('Point', 'x y')):
[...]
However, as with tuples, attributes in named tuples are immutable:
>>> Point = namedtuple('Point', 'x y')
>>> pt1 = Point(1.0, 5.0)
>>> pt1.x = 2.0
AttributeError: can't set attribute
If you want to be able change the values, you need another type. There is a handy recipe for mutable recordtypes which allow you to set new values to attributes.
>>> from rcdtype import *
>>> Point = recordtype('Point', 'x y')
>>> pt1 = Point(1.0, 5.0)
>>> pt1 = Point(1.0, 5.0)
>>> pt1.x = 2.0
>>> print(pt1[0])
2.0
I am not aware of any form of "named list" that lets you add new fields, however. You may just want to use a dictionary in this situation. Named tuples can be converted to dictionaries using pt1._asdict()
which returns {'x': 1.0, 'y': 5.0}
and can be operated upon with all the usual dictionary functions.
As already noted, you should check the documentation for more information from which these examples were constructed.
namedtuple is a factory function for making a tuple class. With that class we can create tuples that are callable by name also.
import collections
#Create a namedtuple class with names "a" "b" "c"
Row = collections.namedtuple("Row", ["a", "b", "c"], verbose=False, rename=False)
row = Row(a=1,b=2,c=3) #Make a namedtuple from the Row class we created
print row #Prints: Row(a=1, b=2, c=3)
print row.a #Prints: 1
print row[0] #Prints: 1
row = Row._make([2, 3, 4]) #Make a namedtuple from a list of values
print row #Prints: Row(a=2, b=3, c=4)
namedtuples are a great feature, they are perfect container for data. When you have to "store" data you would use tuples or dictionaries, like:
user = dict(name="John", age=20)
or:
user = ("John", 20)
The dictionary approach is overwhelming, since dict are mutable and slower than tuples. On the other hand, the tuples are immutable and lightweight but lack readability for a great number of entries in the data fields.
namedtuples are the perfect compromise for the two approaches, the have great readability, lightweightness and immutability (plus they are polymorphic!).
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