仅使用数学(不与字符串进行转换),您可以使用reduce 函数(Python 3 中的functools.reduce)
b = reduce(lambda total, d: 10*total + d, x, 0)
这利用了霍纳规则,该规则将表示数字的多项式分解以减少乘法次数。例如,
1357 = 1*10*10*10 + 3*10*10 + 5*10 + 7 # 6 multiplications
= ((1*10 + 3)*10 + 5)*10 + 7 # 3 multiplications
因此,这比 10 的计算能力或创建字符串并将结果转换为整数要快。
>>> timeit.timeit('reduce(lambda t,d: 10*t+d, x, 0)', 'from functools import reduce; x=[1,3,5,7]')
0.7217515400843695
>>> timeit.timeit('int("".join(map(str, [1,3,5,7])))')
1.425914661027491
>>> timeit.timeit('sum(d * 10**i for i, d in enumerate(x[::-1]))', 'x=[1,3,5,7]')
1.897974518011324
公平地说,一旦位数变大,字符串转换会更快。
>>> import timeit
# 30 digits
>>> setup='from functools import reduce; x=[5, 2, 6, 8, 4, 6, 6, 4, 8, 0, 3, 1, 7, 6, 8, 2, 9, 9, 9, 5, 4, 5, 5, 4, 3, 6, 9, 2, 2, 1]'
>>> print(timeit.timeit('reduce(lambda t,d: 10*t+d, x, 0)', setup))
6.520374411018565
>>> print(timeit.timeit('int("".join(map(str, x)))', setup))
6.797425839002244
>>> print(timeit.timeit('sum(d * 10**i for i, d in enumerate(x[::-1]))', setup))
19.430233853985555
# 60 digits
>>> setup='from functools import reduce; x=2*[5, 2, 6, 8, 4, 6, 6, 4, 8, 0, 3, 1, 7, 6, 8, 2, 9, 9, 9, 5, 4, 5, 5, 4, 3, 6, 9, 2, 2, 1]'
>>> print(timeit.timeit('reduce(lambda t,d: 10*t+d, x, 0)', setup))
13.648188541992567
>>> print(timeit.timeit('int("".join(map(str, x)))', setup))
12.864593736943789
>>> print(timeit.timeit('sum(d * 10**i for i, d in enumerate(x[::-1]))', setup))
44.141602706047706
# 120 digits!
>>> setup='from functools import reduce; x=4*[5, 2, 6, 8, 4, 6, 6, 4, 8, 0, 3, 1, 7, 6, 8, 2, 9, 9, 9, 5, 4, 5, 5, 4, 3, 6, 9, 2, 2, 1]'
>>> print(timeit.timeit('reduce(lambda t,d: 10*t+d, x, 0)', setup))
28.364255172084086
>>> print(timeit.timeit('int("".join(map(str, x)))', setup))
25.184791765059344
>>> print(timeit.timeit('sum(d * 10**i for i, d in enumerate(x[::-1]))', setup))
99.88558598596137