返回列表的产品

问题:

有没有更简洁,高效或简单的pythonic方式做以下?

def product(list):
    p = 1
    for i in list:
        p *= i
    return p

编辑:
我实际上发现,这比使用operator.mul稍微快一些:

from operator import mul
# from functools import reduce # python3 compatibility

def with_lambda(list):
    reduce(lambda x, y: x * y, list)

def without_lambda(list):
    reduce(mul, list)

def forloop(list):
    r = 1
    for x in list:
        r *= x
    return r

import timeit

a = range(50)
b = range(1,50)#no zero
t = timeit.Timer("with_lambda(a)", "from __main__ import with_lambda,a")
print("with lambda:", t.timeit())
t = timeit.Timer("without_lambda(a)", "from __main__ import without_lambda,a")
print("without lambda:", t.timeit())
t = timeit.Timer("forloop(a)", "from __main__ import forloop,a")
print("for loop:", t.timeit())

t = timeit.Timer("with_lambda(b)", "from __main__ import with_lambda,b")
print("with lambda (no 0):", t.timeit())
t = timeit.Timer("without_lambda(b)", "from __main__ import without_lambda,b")
print("without lambda (no 0):", t.timeit())
t = timeit.Timer("forloop(b)", "from __main__ import forloop,b")
print("for loop (no 0):", t.timeit())

给我

('with lambda:', 17.755449056625366)
('without lambda:', 8.2084708213806152)
('for loop:', 7.4836349487304688)
('with lambda (no 0):', 22.570688009262085)
('without lambda (no 0):', 12.472226858139038)
('for loop (no 0):', 11.04065990447998)

回答:

不使用lambda:

from operator import mul
reduce(mul, list, 1)

它是更好和更快。用python 2.7.5

from operator import mul
import numpy as np
import numexpr as ne
# from functools import reduce # python3 compatibility

a = range(1, 101)
%timeit reduce(lambda x, y: x * y, a)   # (1)
%timeit reduce(mul, a)                  # (2)
%timeit np.prod(a)                      # (3)
%timeit ne.evaluate("prod(a)")          # (4)

在以下配置中:

a = range(1, 101)  # A
a = np.array(a)    # B
a = np.arange(1, 1e4, dtype=int) #C
a = np.arange(1, 1e5, dtype=float) #D

结果与python 2.7.5

| 1 | 2 | 3 | 4 |
——-+———–+———–+———–+———–+
A 20.8 µs 13.3 µs 22.6 µs 39.6 µs
B 106 µs 95.3 µs 5.92 µs 26.1 µs
C 4.34 ms 3.51 ms 16.7 µs 38.9 µs
D 46.6 ms 38.5 ms 180 µs 216 µs

结果:np.prod是最快的,如果您使用np.array作为数据结构(小阵列为18x,大阵列为250x)
与python 3.3.2:

| 1 | 2 | 3 | 4 |
——-+———–+———–+———–+———–+
A 23.6 µs 12.3 µs 68.6 µs 84.9 µs
B 133 µs 107 µs 7.42 µs 27.5 µs
C 4.79 ms 3.74 ms 18.6 µs 40.9 µs
D 48.4 ms 36.8 ms 187 µs 214 µs

python 3慢吗?

 
 
Code问答: http://codewenda.com/topics/python/
Stackoverflow: Returning the product of a list

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