我正在解析一个包含
等行的文件type("book") title("golden apples") pages(10-35 70 200-234) comments("good read")
我想把它分成不同的字段。
在我的示例中,有四个字段:类型,标题,页面和注释。
分割后的所需结果是
['type("book")', 'title("golden apples")', 'pages(10-35 70 200-234)', 'comments("good read")]
很明显,简单的字符串拆分不起作用,因为它只会在每个空间分开。 我想拆分空格,但保留括号和引号之间的任何内容。
我怎么能分开这个?
答案 0 :(得分:12)
此正则表达式适用于您\s+(?=[^()]*(?:\(|$))
result = re.split(r"\s+(?=[^()]*(?:\(|$))", subject)
解释
r"""
\s # Match a single character that is a “whitespace character” (spaces, tabs, and line breaks)
+ # Between one and unlimited times, as many times as possible, giving back as needed (greedy)
(?= # Assert that the regex below can be matched, starting at this position (positive lookahead)
[^()] # Match a single character NOT present in the list “()”
* # Between zero and unlimited times, as many times as possible, giving back as needed (greedy)
(?: # Match the regular expression below
# Match either the regular expression below (attempting the next alternative only if this one fails)
\( # Match the character “(” literally
| # Or match regular expression number 2 below (the entire group fails if this one fails to match)
$ # Assert position at the end of a line (at the end of the string or before a line break character)
)
)
"""
答案 1 :(得分:2)
在") "
上拆分,然后将)
添加回除最后一个元素之外的每个元素。
答案 2 :(得分:1)
我会尝试使用积极的后视断言。
r'(?<=\))\s+'
示例:
>>> import re
>>> result = re.split(r'(?<=\))\s+', 'type("book") title("golden apples") pages(10-35 70 200-234) comments("good read")')
>>> result
['type("book")', 'title("golden apples")', 'pages(10-35 70 200-234)', 'comments(
"good read")']
答案 3 :(得分:1)
让我添加一个非正则表达式解决方案:
line = 'type("book") title("golden apples") pages(10-35 70 200-234) comments("good read")'
count = 0 # Bracket counter
last_break = 0 # Index of the last break
parts = []
for j,char in enumerate(line):
if char is '(': count += 1
elif char is ')': count -= 1
elif char is ' ' and count is 0:
parts.append(line[last_break:(j)])
last_break = j+1
parts.append(line[last_break:]) # Add last element
parts = tuple(p for p in parts if p) # Convert to tuple and remove empty
for p in parts:
print(p)
一般来说,您cannot do with regular expressions有某些事情,并且可能会受到严重的性能损失(尤其是对于超前和向后看),这可能会导致它们不是某个问题的最佳解决方案。
也;我以为我提到了pyparsing
模块,该模块可用于创建自定义文本解析器。