如何根据其他解析条件解析XML？-解网

问：

我想从 XML 中提取数据，仅当 XML 中填充了 particulair 字段时。

我想提取的元素是：

城市：标签 110 代码 c（例如柏林）
库代码：标签110代码g（例如D-Bbbf）
县代码：标记 043 代码 c（例如 XA-DE）

这是 XML 的一部分：

<marc:record>
  <marc:controlfield tag="001">39612</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-DE</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">Bibliothek für Bildungsgeschichtliche Forschung</marc:subfield>
    <marc:subfield code="c">Berlin</marc:subfield>
  </marc:datafield>
</marc:record><marc:record>
  <marc:controlfield tag="001">30006648</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-GB</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">The National Archives</marc:subfield>
    <marc:subfield code="c">London</marc:subfield>
    <marc:subfield code="g">GB-Lna</marc:subfield>
  </marc:datafield>
</marc:record>

仅当库代码标签被填充时，我也想提取城市和国家代码。

这是我准备编码的：

data = []

# Read the XML file
with open('oefen.xml', 'r', encoding="utf8") as f_in:
    soup = BeautifulSoup(f_in.read(), 'html.parser') 
    
for record in soup.find_all(tag="110"):
    data.append({
        'City' : e.get_text(strip=True) if (e := record.select_one('[code="c"]')) else None, # select city
        'Code' : e.get_text(strip=True) if (e := record.select_one('[code="g"]')) else None  # select code
    })

for part in 'Code':
    if part != None:
        for record in soup.find_all(tag="043"):
            data.append({
                'City Code' : e.get_text(strip=True) if (e := record.select_one('[code="c"]')) else None, # select city code
            })

pd.DataFrame(data)

python html 网页抓取 beautifulsoup xml 解析

答：

2赞 CodeMonkey 3/18/2022 #1

遍历记录，然后找到每条记录中的 110 和 043 元素。

试试这样的方法：

from bs4 import BeautifulSoup
import pandas as pd

xml = '''<marc:collection xmlns:marc="http://www.loc.gov/MARC21/slim">
<marc:record>
  <marc:controlfield tag="001">39612</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-DE</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">Bibliothek für Bildungsgeschichtliche Forschung</marc:subfield>
    <marc:subfield code="c">Berlin</marc:subfield>
  </marc:datafield>
</marc:record>
<marc:record>
  <marc:controlfield tag="001">30006648</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-GB</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">The National Archives</marc:subfield>
    <marc:subfield code="c">London</marc:subfield>
    <marc:subfield code="g">GB-Lna</marc:subfield>
  </marc:datafield>
</marc:record>
</marc:collection>
'''
 
data = []

# Read XML from string
soup = BeautifulSoup(xml, 'xml')

# uncomment below to read from XML file
# with open('oefen.xml', 'r', encoding="utf8") as f_in:
#    soup = BeautifulSoup(f_in.read(), 'xml')

for record in soup.find_all('marc:record'):
    rec = {}
    if code := record.find(tag="110"):
        if e := code.select_one('[code="c"]'):
            rec['City'] = e.get_text(strip=True)
        if e := code.select_one('[code="g"]'):
            rec['Code'] = e.get_text(strip=True)

    if code := record.find(tag="043"):
        if e := code.select_one('[code="c"]'):
            rec['City Code'] = e.get_text(strip=True)
    if rec:
        # only add if have at least one field
        data.append(rec)

df = pd.DataFrame(data)
print(df)

输出：

     City City Code    Code
0  Berlin     XA-DE     NaN
1  London     XA-GB  GB-Lna

如果不希望 NaN 显示缺失值，则添加行。df = df.fillna('')

0赞 HedgeHog 3/18/2022 #2

与上一个问题几乎相同的问题 - 只需遍历记录并将新字段添加到您的流程中。使用解析器，您不必关心：xmlnamespaces

for record in soup.select('record'):

    data.append({
        'City' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="110"] [code="c"]')) else None,
        'Library Code' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="110"] [code="g"]')) else None,
        'Country Code' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="043"] [code="c"]')) else None
    })

例

xml='''
<root>
<marc:record>
  <marc:controlfield tag="001">39612</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-DE</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">Bibliothek für Bildungsgeschichtliche Forschung</marc:subfield>
    <marc:subfield code="c">Berlin</marc:subfield>
  </marc:datafield>
</marc:record>
<marc:record>
  <marc:controlfield tag="001">30006648</marc:controlfield>
  <marc:controlfield tag="003">DE-633</marc:controlfield>
  <marc:controlfield tag="005">20161109000000.0</marc:controlfield>
  <marc:controlfield tag="008">161109n|||||||a|||              a</marc:controlfield>
  <marc:datafield tag="043" ind1=" " ind2=" ">
    <marc:subfield code="c">XA-GB</marc:subfield>
  </marc:datafield>
  <marc:datafield tag="110" ind1="2" ind2=" ">
    <marc:subfield code="a">The National Archives</marc:subfield>
    <marc:subfield code="c">London</marc:subfield>
    <marc:subfield code="g">GB-Lna</marc:subfield>
  </marc:datafield>
</marc:record>
</root>
'''

from bs4 import BeautifulSoup
import pandas as pd

data = []

soup = BeautifulSoup(xml,'xml')
for record in soup.select('record'):

    data.append({
        'City' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="110"] [code="c"]')) else None,
        'Library Code' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="110"] [code="g"]')) else None,
        'Country Code' : e.get_text(strip=True) if (e := record.select_one('datafield[tag="043"] [code="c"]')) else None
    })

pd.DataFrame(data)

输出

城市	库代码	国家代码
柏林	没有	XA-DE型
伦敦	GB-LNA系列	XA-GB格式

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