Jelle Zijlstra added the comment:
I benchmarked some common namedtuple operations with the following script:
#!/bin/bash
echo 'namedtuple creation'
./python -m timeit -s 'from collections import namedtuple' 'x = namedtuple("x",
["a", "b", "c"])'
echo 'namedtuple instantiation'
./python -m timeit -s 'from collections import namedtuple; x = namedtuple("x",
["a", "b", "c"])' 'x(1, 2, 3)'
echo 'namedtuple attribute access'
./python -m timeit -s 'from collections import namedtuple; x = namedtuple("x",
["a", "b", "c"]); i = x(1, 2, 3)' 'i.a'
echo 'namedtuple _make'
./python -m timeit -s 'from collections import namedtuple; x = namedtuple("x",
["a", "b", "c"])' 'x._make((1, 2, 3))'
--------------------------------------
With my patch as it stands now I get:
$ ./ntbenchmark.sh
namedtuple creation
2000 loops, best of 5: 101 usec per loop
namedtuple instantiation
500000 loops, best of 5: 477 nsec per loop
namedtuple attribute access
5000000 loops, best of 5: 59.9 nsec per loop
namedtuple _make
500000 loops, best of 5: 430 nsec per loop
--------------------------------------
With unpatched CPython master I get:
$ ./ntbenchmark.sh
namedtuple creation
500 loops, best of 5: 409 usec per loop
namedtuple instantiation
500000 loops, best of 5: 476 nsec per loop
namedtuple attribute access
5000000 loops, best of 5: 60 nsec per loop
namedtuple _make
1000000 loops, best of 5: 389 nsec per loop
So creating a class is about 4x faster (similar to the benchmarks various other
people have run) and calling _make() is 10% slower. That's probably because of
the line "if len(result) != cls._num_fields:" in my implementation, which would
have been something like "if len(result) != 3" in the exec-based implementation.
I also cProfiled class creation with my patch. These are results for creating
10000 3-element namedtuple classes:
390005 function calls in 2.793 seconds
Ordered by: cumulative time
ncalls tottime percall cumtime percall filename:lineno(function)
10000 0.053 0.000 2.826 0.000
<ipython-input-5-c37fa4922f0a>:1(make_nt)
10000 1.099 0.000 2.773 0.000
/home/jelle/qython/cpython/Lib/collections/__init__.py:380(namedtuple)
10000 0.948 0.000 0.981 0.000 {built-in method builtins.exec}
100000 0.316 0.000 0.316 0.000 {method 'format' of 'str' objects}
10000 0.069 0.000 0.220 0.000 {method 'join' of 'str' objects}
40000 0.071 0.000 0.152 0.000
/home/jelle/qython/cpython/Lib/collections/__init__.py:439(<genexpr>)
10000 0.044 0.000 0.044 0.000 {built-in method builtins.repr}
30000 0.033 0.000 0.033 0.000 {method 'startswith' of 'str'
objects}
40000 0.031 0.000 0.031 0.000 {method 'isidentifier' of 'str'
objects}
40000 0.025 0.000 0.025 0.000 {method '__contains__' of
'frozenset' objects}
10000 0.022 0.000 0.022 0.000 {method 'replace' of 'str'
objects}
10000 0.022 0.000 0.022 0.000 {built-in method sys._getframe}
30000 0.020 0.000 0.020 0.000 {method 'add' of 'set' objects}
20000 0.018 0.000 0.018 0.000 {built-in method builtins.len}
10000 0.013 0.000 0.013 0.000 {built-in method
builtins.isinstance}
10000 0.009 0.000 0.009 0.000 {method 'get' of 'dict' objects}
So about 35% of time is still spent in the exec() call to create __new__.
Another 10% is in .format() calls, so using f-strings instead of .format()
might also be worth it.
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Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue28638>
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