Python 中的字符串串联与字符串替换

在 Python 中，我不知道何时何地使用字符串连接和字符串替换。由于字符串连接在性能上有了很大的提高，这是一个风格上的决定，而不是一个实际的决定吗？

对于一个具体的例子，应该如何处理灵活 URI 的构造:

DOMAIN = 'http://stackoverflow.com'
QUESTIONS = '/questions'


def so_question_uri_sub(q_num):
return "%s%s/%d" % (DOMAIN, QUESTIONS, q_num)


def so_question_uri_cat(q_num):
return DOMAIN + QUESTIONS + '/' + str(q_num)

编辑: 还有关于连接字符串列表和使用命名替换的建议。这些都是中心主题的变体，也就是，在什么时候，什么是正确的做法？谢谢你的回复！

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I use substitution wherever I can. I only use concatenation if I'm building a string up in say a for-loop.

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最佳答案

Concatenation is (significantly) faster according to my machine. But stylistically, I'm willing to pay the price of substitution if performance is not critical. Well, and if I need formatting, there's no need to even ask the question... there's no option but to use interpolation/templating.

>>> import timeit
>>> def so_q_sub(n):
...  return "%s%s/%d" % (DOMAIN, QUESTIONS, n)
...
>>> so_q_sub(1000)
'http://stackoverflow.com/questions/1000'
>>> def so_q_cat(n):
...  return DOMAIN + QUESTIONS + '/' + str(n)
...
>>> so_q_cat(1000)
'http://stackoverflow.com/questions/1000'
>>> t1 = timeit.Timer('so_q_sub(1000)','from __main__ import so_q_sub')
>>> t2 = timeit.Timer('so_q_cat(1000)','from __main__ import so_q_cat')
>>> t1.timeit(number=10000000)
12.166618871951641
>>> t2.timeit(number=10000000)
5.7813972166853773
>>> t1.timeit(number=1)
1.103492206766532e-05
>>> t2.timeit(number=1)
8.5206360154188587e-06


>>> def so_q_tmp(n):
...  return "{d}{q}/{n}".format(d=DOMAIN,q=QUESTIONS,n=n)
...
>>> so_q_tmp(1000)
'http://stackoverflow.com/questions/1000'
>>> t3= timeit.Timer('so_q_tmp(1000)','from __main__ import so_q_tmp')
>>> t3.timeit(number=10000000)
14.564135316080637


>>> def so_q_join(n):
...  return ''.join([DOMAIN,QUESTIONS,'/',str(n)])
...
>>> so_q_join(1000)
'http://stackoverflow.com/questions/1000'
>>> t4= timeit.Timer('so_q_join(1000)','from __main__ import so_q_join')
>>> t4.timeit(number=10000000)
9.4431309007150048
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What you want to concatenate/interpolate and how you want to format the result should drive your decision.

  • String interpolation allows you to easily add formatting. In fact, your string interpolation version doesn't do the same thing as your concatenation version; it actually adds an extra forward slash before the q_num parameter. To do the same thing, you would have to write return DOMAIN + QUESTIONS + "/" + str(q_num) in that example.

  • Interpolation makes it easier to format numerics; "%d of %d (%2.2f%%)" % (current, total, total/current) would be much less readable in concatenation form.

  • Concatenation is useful when you don't have a fixed number of items to string-ize.

Also, know that Python 2.6 introduces a new version of string interpolation, called string templating:

def so_question_uri_template(q_num):
return "{domain}/{questions}/{num}".format(domain=DOMAIN,
questions=QUESTIONS,
num=q_num)

String templating is slated to eventually replace %-interpolation, but that won't happen for quite a while, I think.

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"As the string concatenation has seen large boosts in performance..."

If performance matters, this is good to know.

However, performance problems I've seen have never come down to string operations. I've generally gotten in trouble with I/O, sorting and O(n2) operations being the bottlenecks.

Until string operations are the performance limiters, I'll stick with things that are obvious. Mostly, that's substitution when it's one line or less, concatenation when it makes sense, and a template tool (like Mako) when it's large.

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Don't forget about named substitution:

def so_question_uri_namedsub(q_num):
return "%(domain)s%(questions)s/%(q_num)d" % locals()
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Remember, stylistic decisions are practical decisions, if you ever plan on maintaining or debugging your code :-) There's a famous quote from Knuth (possibly quoting Hoare?): "We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil."

As long as you're careful not to (say) turn a O(n) task into an O(n2) task, I would go with whichever you find easiest to understand..

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Be wary of concatenating strings in a loop! The cost of string concatenation is proportional to the length of the result. Looping leads you straight to the land of N-squared. Some languages will optimize concatenation to the most recently allocated string, but it's risky to count on the compiler to optimize your quadratic algorithm down to linear. Best to use the primitive (join?) that takes an entire list of strings, does a single allocation, and concatenates them all in one go.

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Actually the correct thing to do, in this case (building paths) is to use os.path.join. Not string concatenation or interpolation

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I was just testing the speed of different string concatenation/substitution methods out of curiosity. A google search on the subject brought me here. I thought I would post my test results in the hope that it might help someone decide.

    import timeit
def percent_():
return "test %s, with number %s" % (1,2)


def format_():
return "test {}, with number {}".format(1,2)


def format2_():
return "test {1}, with number {0}".format(2,1)


def concat_():
return "test " + str(1) + ", with number " + str(2)


def dotimers(func_list):
# runs a single test for all functions in the list
for func in func_list:
tmr = timeit.Timer(func)
res = tmr.timeit()
print "test " + func.func_name + ": " + str(res)


def runtests(func_list, runs=5):
# runs multiple tests for all functions in the list
for i in range(runs):
print "----------- TEST #" + str(i + 1)
dotimers(func_list)

...After running runtests((percent_, format_, format2_, concat_), runs=5), I found that the % method was about twice as fast as the others on these small strings. The concat method was always the slowest (barely). There were very tiny differences when switching the positions in the format() method, but switching positions was always at least .01 slower than the regular format method.

Sample of test results:

    test concat_()  : 0.62  (0.61 to 0.63)
test format_()  : 0.56  (consistently 0.56)
test format2_() : 0.58  (0.57 to 0.59)
test percent_() : 0.34  (0.33 to 0.35)

I ran these because I do use string concatenation in my scripts, and I was wondering what the cost was. I ran them in different orders to make sure nothing was interfering, or getting better performance being first or last. On a side note, I threw in some longer string generators into those functions like "%s" + ("a" * 1024) and regular concat was almost 3 times as fast (1.1 vs 2.8) as using the format and % methods. I guess it depends on the strings, and what you are trying to achieve. If performance really matters, it might be better to try different things and test them. I tend to choose readability over speed, unless speed becomes a problem, but thats just me. SO didn't like my copy/paste, i had to put 8 spaces on everything to make it look right. I usually use 4.


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