Pythonic way to sorting list of namedtuples by field name

from operator import attrgetterfrom collections import namedtuplePerson = 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'))

sorted(seq, key=lambda x: x.name)sorted(seq, key=lambda x: x.age)

I tested the two alternatives given here for speed, since @zenpoy was concerned about performance.

Testing script:

import randomfrom collections import namedtuplefrom timeit import timeitfrom operator import attrgetterruns = 10000size = 10000random.seed = 42Person = 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 44.26793992166096attrgetter_test_age 31.98247099677627lambda_test_name 47.97959511074551lambda_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 92.80101586919373lambda_test_both 96.85089983147456

Lambda still underperforms, but less so. Now about 5% slower.

Testing is done on Python 3.6.0.