Pythonic way to sorting list of namedtuples by field name
since nobody mentioned using itemgetter(), here how you do using itemgetter().
from operator import itemgetter
from collections import namedtuple
Person = namedtuple('Person', 'name age score')
seq = [
Person(name='nick', age=23, score=100),
Person(name='bob', age=25, score=200),
]
# sort list by name
print(sorted(seq, key=itemgetter(0)))
# sort list by age
print(sorted(seq, key=itemgetter(1)))
sorted(seq, key=lambda x: x.name)
sorted(seq, key=lambda x: x.age)
from operator import attrgetter
from collections import namedtuple
Person = namedtuple('Person', 'name age score')
seq = [Person(name='nick', age=23, score=100),
Person(name='bob', age=25, score=200)]
Sort list by name
sorted(seq, key=attrgetter('name'))
Sort list by age
sorted(seq, key=attrgetter('age'))
I tested the two alternatives given here for speed, since @zenpoy was concerned about performance.
Testing script:
import random
from collections import namedtuple
from timeit import timeit
from operator import attrgetter
runs = 10000
size = 10000
random.seed = 42
Person = namedtuple('Person', 'name,age')
seq = [Person(str(random.randint(0, 10 ** 10)), random.randint(0, 100)) for _ in range(size)]
def attrgetter_test_name():
return sorted(seq.copy(), key=attrgetter('name'))
def attrgetter_test_age():
return sorted(seq.copy(), key=attrgetter('age'))
def lambda_test_name():
return sorted(seq.copy(), key=lambda x: x.name)
def lambda_test_age():
return sorted(seq.copy(), key=lambda x: x.age)
print('attrgetter_test_name', timeit(stmt=attrgetter_test_name, number=runs))
print('attrgetter_test_age', timeit(stmt=attrgetter_test_age, number=runs))
print('lambda_test_name', timeit(stmt=lambda_test_name, number=runs))
print('lambda_test_age', timeit(stmt=lambda_test_age, number=runs))
Results:
attrgetter_test_name 44.26793992166096
attrgetter_test_age 31.98247099677627
lambda_test_name 47.97959511074551
lambda_test_age 35.69356267603864
Using lambda was indeed slower. Up to 10% slower.
EDIT:
Further testing shows the results when sorting using multiple attributes. Added the following two test cases with the same setup:
def attrgetter_test_both():
return sorted(seq.copy(), key=attrgetter('age', 'name'))
def lambda_test_both():
return sorted(seq.copy(), key=lambda x: (x.age, x.name))
print('attrgetter_test_both', timeit(stmt=attrgetter_test_both, number=runs))
print('lambda_test_both', timeit(stmt=lambda_test_both, number=runs))
Results:
attrgetter_test_both 92.80101586919373
lambda_test_both 96.85089983147456
Lambda still underperforms, but less so. Now about 5% slower.
Testing is done on Python 3.6.0.