2

我有一个数据结构的转储,我正在尝试将其转换为 XML。该结构中有许多嵌套结构。所以我有点不知道如何开始,因为我能想到的所有正则表达式都不适用于嵌套表达式。

例如,假设有这样的结构转储:

abc = (  
        bcd = (efg = 0, ghr = 5, lmn = 10), 
        ghd = 5, 
        zde = (dfs = 10, fge =20, dfg = (sdf = 3, ert = 5), juh = 0))

我想得到这样的输出:

< abc >
  < bcd >   
    < efg >0< /efg >  
    < ghr >5< /ghr >  
    < lmn >10< /lmn >  
  < /bcd >  
.....  
< /abc > 

那么什么是一个好的方法呢?标记表达式、聪明的正则表达式还是使用堆栈?

4

5 回答 5

3

使用 pyparsing。

$ cat parsing.py 
from pyparsing import nestedExpr

abc = """(  
        bcd = (efg = 0, ghr = 5, lmn 10), 
        ghd = 5, 
        zde = (dfs = 10, fge =20, dfg = (sdf = 3, ert = 5), juh = 0))"""
print nestedExpr().parseString(abc).asList()

$ python parsing.py
[['bcd', '=', ['efg', '=', '0,', 'ghr', '=', '5,', 'lmn', '10'], ',', 'ghd', '=', '5,', 'zde', '=', ['dfs', '=', '10,', 'fge', '=20,', 'dfg', '=', ['sdf', '=', '3,', 'ert', '=', '5'], ',', 'juh', '=', '0']]]
于 2012-06-21T17:16:21.473 回答
1

这是一个更习惯使用 pyparsing 的替代答案。因为它为可以看到什么输入以及应该返回什么结果提供了详细的语法,所以解析的数据并不“混乱”。因此toXML()不需要努力工作,也不需要做任何真正的清理工作。

print "\n----- ORIGINAL -----\n"

dump = """
abc = (  
        bcd = (efg = 0, ghr = 5, lmn 10), 
        ghd = 5, 
        zde = (dfs = 10, fge =20, dfg = (sdf = 3, ert = 5), juh = 0))
""".strip()

print dump


print "\n----- PARSED INTO LIST -----\n"

from pyparsing import Word, alphas, nums, Optional, Forward, delimitedList, Group, Suppress

def Syntax():
    """Define grammar and parser."""

    # building blocks
    name   = Word(alphas)
    number = Word(nums)
    _equals = Optional(Suppress('='))
    _lpar   = Suppress('(')
    _rpar   = Suppress(')')

    # larger constructs
    expr = Forward()
    value = number | Group( _lpar + delimitedList(expr) + _rpar )
    expr << name + _equals + value

    return expr

parsed = Syntax().parseString(dump)
print parsed


print "\n----- SERIALIZED INTO XML ----\n"


def toXML(part, level=0):

    xml = ""
    indent = "    " * level
    while part:
        tag     = part.pop(0)
        payload = part.pop(0)

        insides = payload if isinstance(payload, str) \
                          else "\n" + toXML(payload, level+1) + indent

        xml += "{indent}<{tag}>{insides}</{tag}>\n".format(**locals())

    return xml

print toXML(parsed)

输入和 XML 输出与我的其他答案相同。返回的数据parseString()是唯一真正的变化:

----- PARSED INTO LIST -----

['abc', ['bcd', ['efg', '0', 'ghr', '5', 'lmn', '10'], 'ghd', '5', 'zde',
['dfs', '10', 'fge', '20', 'dfg', ['sdf', '3', 'ert', '5'], 'juh', '0']]]
于 2012-06-21T21:43:32.410 回答
0

我喜欢 Igor Chubin 的“使用 pyparsing”答案,因为一般来说,正则表达式对嵌套结构的处理非常差(尽管 thg435 的迭代替换解决方案是一个聪明的解决方法)。

但是一旦 pyparsing 完成了它的工作,您就需要一个例程来遍历列表并发出 XML。它需要对 pyparsing 的结果的缺陷保持智能。例如,fge =20,不会产生['fge', '=', '20']你想要的,但是['fge', '=20,']. 有时也会在无用的地方添加逗号。我是这样做的:

from pyparsing import nestedExpr

dump = """
abc = (  
        bcd = (efg = 0, ghr = 5, lmn 10), 
        ghd = 5, 
        zde = (dfs = 10, fge =20, dfg = (sdf = 3, ert = 5), juh = 0))
"""

dump = dump.strip()

print "\n----- ORIGINAL -----\n"
print dump

wrapped = dump if dump.startswith('(') else "({})".format(dump)
parsed = nestedExpr().parseString(wrapped).asList()

print "\n----- PARSED INTO LIST -----\n"
print parsed

def toXML(part, level=0):

    def grab_tag():
        return part.pop(0).lstrip(",")

    def grab_payload():
        payload = part.pop(0)
        if isinstance(payload, str):
            payload = payload.lstrip("=").rstrip(",")
        return payload

    xml = ""
    indent = "    " * level
    while part:
        tag     = grab_tag() or grab_tag()
        payload = grab_payload() or grab_payload()
        # grab twice, possibly, if '=' or ',' is in the way of what you're grabbing

        insides = payload if isinstance(payload, str) \
                          else "\n" + toXML(payload, level+1) + indent

        xml += "{indent}<{tag}>{insides}</{tag}>\n".format(**locals())

    return xml

print "\n----- SERIALIZED INTO XML ----\n"
print toXML(parsed[0])

导致:

----- ORIGINAL -----

abc = (  
        bcd = (efg = 0, ghr = 5, lmn 10), 
        ghd = 5, 
        zde = (dfs = 10, fge =20, dfg = (sdf = 3, ert = 5), juh = 0))

----- PARSED INTO LIST -----

[['abc', '=', ['bcd', '=', ['efg', '=', '0,', 'ghr', '=', '5,', 'lmn', '10'], ',', 'ghd', '=', '5,', 'zde', '=', ['dfs', '=', '10,', 'fge', '=20,', 'dfg', '=', ['sdf', '=', '3,', 'ert', '=', '5'], ',', 'juh', '=', '0']]]]

----- SERIALIZED INTO XML ----

<abc>
    <bcd>
        <efg>0</efg>
        <ghr>5</ghr>
        <lmn>10</lmn>
    </bcd>
    <ghd>5</ghd>
    <zde>
        <dfs>10</dfs>
        <fge>20</fge>
        <dfg>
            <sdf>3</sdf>
            <ert>5</ert>
        </dfg>
        <juh>0</juh>
    </zde>
</abc>
于 2012-06-21T18:54:32.553 回答
0

我不认为正则表达式是这里最好的方法,但对于那些好奇的人来说,可以这样做:

def expr(m):
    out = []
    for item in m.group(1).split(','):
        a, b = map(str.strip, item.split('='))
        out.append('<%s>%s</%s>' % (a, b, a))
    return '\n'.join(out)

rr = r'\(([^()]*)\)'
while re.search(rr, data):
    data = re.sub(rr, expr, data)

基本上,我们反复用(no parens here)xml 块替换最下面的括号,直到没有更多的括号。为简单起见,我也将主要表达式包含在括号中,如果不是这种情况,请data='(%s)' % data在解析之前执行。

于 2012-06-21T18:12:43.070 回答
0

您可以使用re模块来解析嵌套表达式(尽管不推荐):

import re

def repl_flat(m):
    return "\n".join("<{0}>{1}</{0}>".format(*map(str.strip, s.partition('=')[::2]))
                     for s in m.group(1).split(','))

def eval_nested(expr):
    val, n = re.subn(r"\(([^)(]+)\)", repl_flat, expr)
    return val if n == 0 else eval_nested(val)

例子

print eval_nested("(%s)" % (data,))

输出

<abc><bcd><efg>0</efg>
<ghr>5</ghr>
<lmn>10</lmn></bcd>
<ghd>5</ghd>
<zde><dfs>10</dfs>
<fge>20</fge>
<dfg><sdf>3</sdf>
<ert>5</ert></dfg>
<juh>0</juh></zde></abc>
于 2012-06-21T20:01:45.523 回答