+ 与 f-string 的字符串连接

Question

假设我有两个变量：

>>> a = "hello"
>>> b = "world"

我可以通过两种方式连接它们；使用+：

>>> a = "hello"
>>> b = "world"

或者使用 f 字符串：

>>> a + b
"helloworld"

哪种方式更好或更好的做法？有人告诉我 f-string 在性能和健壮性方面是更好的做法，我想详细了解原因。

Answer 1

这有两个方面：性能和便利性。

在 Python 3.8.0 中使用时timeit，我发现使用 f 字符串的连接始终比 ​​慢+，但对于较长的字符串，百分比差异很小：

>>> from timeit import timeit
>>> timeit('a + b', setup='a, b = "hello", "world"')
0.059246900000289315
>>> timeit('f"{a}{b}"', setup='a, b = "hello", "world"')
0.06997206999949412
>>> timeit('a + b', setup='a, b = "hello"*100, "world"*100')
0.10218418099975679
>>> timeit('f"{a}{b}"', setup='a, b = "hello"*100, "world"*100')
0.1108272269993904
>>> timeit('a + b', setup='a, b = "hello"*10000, "world"*10000')
2.6094200410007033
>>> timeit('f"{a}{b}"', setup='a, b = "hello"*10000, "world"*10000')
2.7300010479993944

但是，当您的输入还不是字符串时，f 字符串可能会更方便一些：

>>> a, b = [1, 2, 3], True
>>> str(a) + str(b)
'[1, 2, 3]True'
>>> f'{a}{b}'
'[1, 2, 3]True'

Answer 2

在性能方面，我原以为格式字符串文字会比字符串连接快得多，但我震惊地发现事实并非如此。

我使用该timeit模块来测试格式化字符串文字与字符串连接花费的时间。我测试了长度为 10 到 100 万个字符的字符串。

from timeit import timeit
import matplotlib.pyplot as plt
n = 1000000000

setup = """\
a = 'a'*{str_len}
b = 'b'*{str_len}
"""

fstr_stmt = """\
f'{a}{b}'
"""

concat_stmt = """\
a+b
"""

str_lens = [10, 100, 1000, 10000, 100000, 1000000]
fstr_t = []
concat_t = []
for str_len in str_lens:
    n_iters = n//str_len
    fstr_t.append(timeit(setup=setup.format(str_len=str_len), stmt=fstr_stmt, number=n_iters)/n_iters)
    concat_t.append(timeit(setup=setup.format(str_len=str_len), stmt=concat_stmt, number=n_iters)/n_iters)
    ratio = fstr_t[-1]/concat_t[-1]
    print(f"For two strings of length {str_len:7d}, concatenation is {ratio:.5f} times faster than f-strings")
plt.plot(str_lens, fstr_t, "r*-")
plt.plot(str_lens, concat_t, "c*-")
plt.xscale("log")
plt.yscale("log")
plt.xlabel("String length (log scale)")
plt.ylabel("Seconds per iteration (log scale)")
plt.grid()
plt.show()

控制台输出：

For two strings of length      10, concatenation is 1.06938 times faster than f-strings
For two strings of length     100, concatenation is 1.14887 times faster than f-strings
For two strings of length    1000, concatenation is 1.13994 times faster than f-strings
For two strings of length   10000, concatenation is 1.26934 times faster than f-strings
For two strings of length  100000, concatenation is 1.21585 times faster than f-strings
For two strings of length 1000000, concatenation is 1.01816 times faster than f-strings

情节：

简介： 使用字符串连接运算符比使用格式字符串文字稍快。除非您正在执行成百上千的字符串连接并且需要非常快速地完成它们，否则所选的实现不太可能产生影响。

从可读性的角度来看，f-string 文字比字符串连接更美观也更容易阅读。此外，正如 Daniel 的回答所指出的，f-strings 能够处理不同类型的输入，而 using+需要两个对象都是字符串（或__add__, 和__radd__方法的重载）。

编辑：正如 chepner 在他们的评论中指出的那样，当涉及两个以上的字符串时，使用 f-strings会更有效。例如，将另一个变量 , 添加c到 setup 和timeitstatements 会产生以下控制台输出：

For three strings of length      10, concatenation is 0.77931 times faster than f-strings
For three strings of length     100, concatenation is 0.67699 times faster than f-strings
For three strings of length    1000, concatenation is 0.60220 times faster than f-strings
For three strings of length   10000, concatenation is 1.27484 times faster than f-strings
For three strings of length  100000, concatenation is 0.98911 times faster than f-strings
For three strings of length 1000000, concatenation is 0.60201 times faster than f-strings

Answer 3

如果您有更多字符串（>2，每个字符串 1 个字符）要连接，f 字符串的性能会更好：

>>> from timeit import timeit

>>> timeit('a+b', setup='a,b = "h", "e"')
0.05678774899979544
>>> timeit('f"{a}{b}"', setup='a,b = "h", "e"')
0.09656870200024059

>>> timeit('a+b+c', setup='a,b,c = "h", "e", "l"')
0.09475198700010878
>>> timeit('f"{a}{b}{c}"', setup='a,b,c = "h", "e", "l"')
0.08498188300018228

>>> timeit('a+b+c+d', setup='a,b,c,d = "h", "e", "l", "l"')
0.13406166100003247
>>> timeit('f"{a}{b}{c}{d}"', setup='a,b,c,d = "h", "e", "l", "l"')
0.09481844199990519

>>> timeit('a+b+c+d+e', setup='a,b,c,d,e = "h", "e", "l", "l","o"')
0.21804361799991057
>>> timeit('f"{a}{b}{c}{d}{e}"', setup='a,b,c,d,e = "h", "e", "l", "l","o"')
0.11850353900013033