假设这个字符串:
The fox jumped over the log.
变成:
The fox jumped over the log.
在不分割和进入列表的情况下,最简单的实现方法(1-2行)是什么?
假设这个字符串:
The fox jumped over the log.
变成:
The fox jumped over the log.
在不分割和进入列表的情况下,最简单的实现方法(1-2行)是什么?
当前回答
使用带有“\s”的正则表达式并执行简单的string.split()也将删除其他空白-如换行符、回车符、制表符。除非需要使用多个空格,否则我将给出这些示例。
我使用了11段,1000个单词,6665字节的Lorem Ipsum来进行真实的时间测试,并在整个过程中使用了随机长度的额外空格:
original_string = ''.join(word + (' ' * random.randint(1, 10)) for word in lorem_ipsum.split(' '))
一行程序实际上是删除任何前导/尾随空格,并保留一个前导/尾随空格(但只有ONE;-)。
# setup = '''
import re
def while_replace(string):
while ' ' in string:
string = string.replace(' ', ' ')
return string
def re_replace(string):
return re.sub(r' {2,}' , ' ', string)
def proper_join(string):
split_string = string.split(' ')
# To account for leading/trailing spaces that would simply be removed
beg = ' ' if not split_string[ 0] else ''
end = ' ' if not split_string[-1] else ''
# versus simply ' '.join(item for item in string.split(' ') if item)
return beg + ' '.join(item for item in split_string if item) + end
original_string = """Lorem ipsum ... no, really, it kept going... malesuada enim feugiat. Integer imperdiet erat."""
assert while_replace(original_string) == re_replace(original_string) == proper_join(original_string)
#'''
# while_replace_test
new_string = original_string[:]
new_string = while_replace(new_string)
assert new_string != original_string
# re_replace_test
new_string = original_string[:]
new_string = re_replace(new_string)
assert new_string != original_string
# proper_join_test
new_string = original_string[:]
new_string = proper_join(new_string)
assert new_string != original_string
NOTE: The "while version" made a copy of the original_string, as I believe once modified on the first run, successive runs would be faster (if only by a bit). As this adds time, I added this string copy to the other two so that the times showed the difference only in the logic. Keep in mind that the main stmt on timeit instances will only be executed once; the original way I did this, the while loop worked on the same label, original_string, thus the second run, there would be nothing to do. The way it's set up now, calling a function, using two different labels, that isn't a problem. I've added assert statements to all the workers to verify we change something every iteration (for those who may be dubious). E.g., change to this and it breaks:
# while_replace_test
new_string = original_string[:]
new_string = while_replace(new_string)
assert new_string != original_string # will break the 2nd iteration
while ' ' in original_string:
original_string = original_string.replace(' ', ' ')
Tests run on a laptop with an i5 processor running Windows 7 (64-bit).
timeit.Timer(stmt = test, setup = setup).repeat(7, 1000)
test_string = 'The fox jumped over\n\t the log.' # trivial
Python 2.7.3, 32-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001066 | 0.001260 | 0.001128 | 0.001092
re_replace_test | 0.003074 | 0.003941 | 0.003357 | 0.003349
proper_join_test | 0.002783 | 0.004829 | 0.003554 | 0.003035
Python 2.7.3, 64-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001025 | 0.001079 | 0.001052 | 0.001051
re_replace_test | 0.003213 | 0.004512 | 0.003656 | 0.003504
proper_join_test | 0.002760 | 0.006361 | 0.004626 | 0.004600
Python 3.2.3, 32-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001350 | 0.002302 | 0.001639 | 0.001357
re_replace_test | 0.006797 | 0.008107 | 0.007319 | 0.007440
proper_join_test | 0.002863 | 0.003356 | 0.003026 | 0.002975
Python 3.3.3, 64-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001444 | 0.001490 | 0.001460 | 0.001459
re_replace_test | 0.011771 | 0.012598 | 0.012082 | 0.011910
proper_join_test | 0.003741 | 0.005933 | 0.004341 | 0.004009
test_string = lorem_ipsum
# Thanks to http://www.lipsum.com/
# "Generated 11 paragraphs, 1000 words, 6665 bytes of Lorem Ipsum"
Python 2.7.3, 32-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.342602 | 0.387803 | 0.359319 | 0.356284
re_replace_test | 0.337571 | 0.359821 | 0.348876 | 0.348006
proper_join_test | 0.381654 | 0.395349 | 0.388304 | 0.388193
Python 2.7.3, 64-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.227471 | 0.268340 | 0.240884 | 0.236776
re_replace_test | 0.301516 | 0.325730 | 0.308626 | 0.307852
proper_join_test | 0.358766 | 0.383736 | 0.370958 | 0.371866
Python 3.2.3, 32-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.438480 | 0.463380 | 0.447953 | 0.446646
re_replace_test | 0.463729 | 0.490947 | 0.472496 | 0.468778
proper_join_test | 0.397022 | 0.427817 | 0.406612 | 0.402053
Python 3.3.3, 64-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.284495 | 0.294025 | 0.288735 | 0.289153
re_replace_test | 0.501351 | 0.525673 | 0.511347 | 0.508467
proper_join_test | 0.422011 | 0.448736 | 0.436196 | 0.440318
对于普通字符串,while循环似乎是最快的,其次是Pythonic字符串分割/连接,regex在后面拉。
对于非平凡的字符串,似乎有更多的考虑。32位2.7 ?它是正则表达式的救星!2.7 64位?while循环是最好的。32位3.2,使用“适当的”连接。64位3.3,执行while循环。一次。
最后,如果/何地/何时需要,就可以提高性能,但最好记住这句咒语:
让它起作用 纠正错误 快一点
IANAL, ymv
其他回答
使用带有“\s”的正则表达式并执行简单的string.split()也将删除其他空白-如换行符、回车符、制表符。除非需要使用多个空格,否则我将给出这些示例。
我使用了11段,1000个单词,6665字节的Lorem Ipsum来进行真实的时间测试,并在整个过程中使用了随机长度的额外空格:
original_string = ''.join(word + (' ' * random.randint(1, 10)) for word in lorem_ipsum.split(' '))
一行程序实际上是删除任何前导/尾随空格,并保留一个前导/尾随空格(但只有ONE;-)。
# setup = '''
import re
def while_replace(string):
while ' ' in string:
string = string.replace(' ', ' ')
return string
def re_replace(string):
return re.sub(r' {2,}' , ' ', string)
def proper_join(string):
split_string = string.split(' ')
# To account for leading/trailing spaces that would simply be removed
beg = ' ' if not split_string[ 0] else ''
end = ' ' if not split_string[-1] else ''
# versus simply ' '.join(item for item in string.split(' ') if item)
return beg + ' '.join(item for item in split_string if item) + end
original_string = """Lorem ipsum ... no, really, it kept going... malesuada enim feugiat. Integer imperdiet erat."""
assert while_replace(original_string) == re_replace(original_string) == proper_join(original_string)
#'''
# while_replace_test
new_string = original_string[:]
new_string = while_replace(new_string)
assert new_string != original_string
# re_replace_test
new_string = original_string[:]
new_string = re_replace(new_string)
assert new_string != original_string
# proper_join_test
new_string = original_string[:]
new_string = proper_join(new_string)
assert new_string != original_string
NOTE: The "while version" made a copy of the original_string, as I believe once modified on the first run, successive runs would be faster (if only by a bit). As this adds time, I added this string copy to the other two so that the times showed the difference only in the logic. Keep in mind that the main stmt on timeit instances will only be executed once; the original way I did this, the while loop worked on the same label, original_string, thus the second run, there would be nothing to do. The way it's set up now, calling a function, using two different labels, that isn't a problem. I've added assert statements to all the workers to verify we change something every iteration (for those who may be dubious). E.g., change to this and it breaks:
# while_replace_test
new_string = original_string[:]
new_string = while_replace(new_string)
assert new_string != original_string # will break the 2nd iteration
while ' ' in original_string:
original_string = original_string.replace(' ', ' ')
Tests run on a laptop with an i5 processor running Windows 7 (64-bit).
timeit.Timer(stmt = test, setup = setup).repeat(7, 1000)
test_string = 'The fox jumped over\n\t the log.' # trivial
Python 2.7.3, 32-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001066 | 0.001260 | 0.001128 | 0.001092
re_replace_test | 0.003074 | 0.003941 | 0.003357 | 0.003349
proper_join_test | 0.002783 | 0.004829 | 0.003554 | 0.003035
Python 2.7.3, 64-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001025 | 0.001079 | 0.001052 | 0.001051
re_replace_test | 0.003213 | 0.004512 | 0.003656 | 0.003504
proper_join_test | 0.002760 | 0.006361 | 0.004626 | 0.004600
Python 3.2.3, 32-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001350 | 0.002302 | 0.001639 | 0.001357
re_replace_test | 0.006797 | 0.008107 | 0.007319 | 0.007440
proper_join_test | 0.002863 | 0.003356 | 0.003026 | 0.002975
Python 3.3.3, 64-bit, Windows
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.001444 | 0.001490 | 0.001460 | 0.001459
re_replace_test | 0.011771 | 0.012598 | 0.012082 | 0.011910
proper_join_test | 0.003741 | 0.005933 | 0.004341 | 0.004009
test_string = lorem_ipsum
# Thanks to http://www.lipsum.com/
# "Generated 11 paragraphs, 1000 words, 6665 bytes of Lorem Ipsum"
Python 2.7.3, 32-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.342602 | 0.387803 | 0.359319 | 0.356284
re_replace_test | 0.337571 | 0.359821 | 0.348876 | 0.348006
proper_join_test | 0.381654 | 0.395349 | 0.388304 | 0.388193
Python 2.7.3, 64-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.227471 | 0.268340 | 0.240884 | 0.236776
re_replace_test | 0.301516 | 0.325730 | 0.308626 | 0.307852
proper_join_test | 0.358766 | 0.383736 | 0.370958 | 0.371866
Python 3.2.3, 32-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.438480 | 0.463380 | 0.447953 | 0.446646
re_replace_test | 0.463729 | 0.490947 | 0.472496 | 0.468778
proper_join_test | 0.397022 | 0.427817 | 0.406612 | 0.402053
Python 3.3.3, 64-bit
test | minum | maximum | average | median
---------------------+------------+------------+------------+-----------
while_replace_test | 0.284495 | 0.294025 | 0.288735 | 0.289153
re_replace_test | 0.501351 | 0.525673 | 0.511347 | 0.508467
proper_join_test | 0.422011 | 0.448736 | 0.436196 | 0.440318
对于普通字符串,while循环似乎是最快的,其次是Pythonic字符串分割/连接,regex在后面拉。
对于非平凡的字符串,似乎有更多的考虑。32位2.7 ?它是正则表达式的救星!2.7 64位?while循环是最好的。32位3.2,使用“适当的”连接。64位3.3,执行while循环。一次。
最后,如果/何地/何时需要,就可以提高性能,但最好记住这句咒语:
让它起作用 纠正错误 快一点
IANAL, ymv
因为@pythonlarry问这里缺少基于生成器的版本
groupby连接很简单。Groupby将对具有相同键的连续元素进行分组。并返回每个组的键对和元素列表。所以当键是空格空格是返回整个组。
from itertools import groupby
def group_join(string):
return ''.join(' ' if chr==' ' else ''.join(times) for chr,times in groupby(string))
由变体组成的组很简单,但是很慢。现在来看发电机变体。在这里,我们使用了一个迭代器,即字符串,并生成除字符后面的字符外的所有字符。
def generator_join_generator(string):
last=False
for c in string:
if c==' ':
if not last:
last=True
yield ' '
else:
last=False
yield c
def generator_join(string):
return ''.join(generator_join_generator(string))
所以我用其他的方法测量了时间。
while_replace 0.015868543065153062 re_replace 0.22579886706080288 proper_join 0.40058281796518713 group_join 5.53206754301209 generator_join 1.6673167790286243
Hello和World由64KB的空格分隔
while_replace 2.991308711003512 re_replace 0.08232860406860709 proper_join 6.294375243945979 group_join 2.4320066600339487 generator_join 6.329648651066236
不忘原话
while_replace 0.002160938922315836 re_replace 0.008620491018518806 proper_join 0.005650000995956361 group_join 0.028368217987008393 generator_join 0.009435956948436797
有趣的是,这里几乎空间只有字符串组连接不是那么糟糕 计时显示的中位数总是七次,每次一千次。
import re
string = re.sub('[ \t\n]+', ' ', 'The quick brown \n\n \t fox')
这将删除所有的制表符,新行和多个空白与单一空白。
一行代码,删除句子之前、之后和内部所有多余的空格:
sentence = " The fox jumped over the log. "
sentence = ' '.join(filter(None,sentence.split(' ')))
解释:
将整个字符串拆分为一个列表。 从列表中过滤空元素。 用一个空格重新连接剩下的元素*
*其余的元素应该是单词或带有标点符号的单词等。我没有对此进行广泛测试,但这应该是一个很好的起点。祝你一切顺利!
在某些情况下,需要将每个空格字符的连续出现替换为该字符的单个实例。你可以使用带有反向引用的正则表达式来实现这一点。
(\s)\1{1,}匹配任何空格字符,后面跟着一个或多个该字符。现在,您所需要做的就是指定第一个组(\1)作为匹配的替换。
将其包装在函数中:
import re
def normalize_whitespace(string):
return re.sub(r'(\s)\1{1,}', r'\1', string)
>>> normalize_whitespace('The fox jumped over the log.')
'The fox jumped over the log.'
>>> normalize_whitespace('First line\t\t\t \n\n\nSecond line')
'First line\t \nSecond line'