我在XML中有很多行,我试图获得一个特定节点属性的实例。

<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>

我如何访问属性foobar的值?在这个例子中,我想要“1”和“2”。


当前回答

如果您不想使用任何外部库或第三方工具,请尝试下面的代码。

这将把xml解析成python字典 这也将解析xml属性 这也将解析空标签,如<tag/>和只有属性的标签,如<tag var=val/>

Code

import re

def getdict(content):
    res=re.findall("<(?P<var>\S*)(?P<attr>[^/>]*)(?:(?:>(?P<val>.*?)</(?P=var)>)|(?:/>))",content)
    if len(res)>=1:
        attreg="(?P<avr>\S+?)(?:(?:=(?P<quote>['\"])(?P<avl>.*?)(?P=quote))|(?:=(?P<avl1>.*?)(?:\s|$))|(?P<avl2>[\s]+)|$)"
        if len(res)>1:
            return [{i[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,i[1].strip())]},{"$values":getdict(i[2])}]} for i in res]
        else:
            return {res[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,res[1].strip())]},{"$values":getdict(res[2])}]}
    else:
        return content

with open("test.xml","r") as f:
    print(getdict(f.read().replace('\n','')))

样例输入

<details class="4b" count=1 boy>
    <name type="firstname">John</name>
    <age>13</age>
    <hobby>Coin collection</hobby>
    <hobby>Stamp collection</hobby>
    <address>
        <country>USA</country>
        <state>CA</state>
    </address>
</details>
<details empty="True"/>
<details/>
<details class="4a" count=2 girl>
    <name type="firstname">Samantha</name>
    <age>13</age>
    <hobby>Fishing</hobby>
    <hobby>Chess</hobby>
    <address current="no">
        <country>Australia</country>
        <state>NSW</state>
    </address>
</details>

输出(美化)

[
  {
    "details": [
      {
        "@attributes": [
          {
            "class": "4b"
          },
          {
            "count": "1"
          },
          {
            "boy": ""
          }
        ]
      },
      {
        "$values": [
          {
            "name": [
              {
                "@attributes": [
                  {
                    "type": "firstname"
                  }
                ]
              },
              {
                "$values": "John"
              }
            ]
          },
          {
            "age": [
              {
                "@attributes": []
              },
              {
                "$values": "13"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Coin collection"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Stamp collection"
              }
            ]
          },
          {
            "address": [
              {
                "@attributes": []
              },
              {
                "$values": [
                  {
                    "country": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "USA"
                      }
                    ]
                  },
                  {
                    "state": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "CA"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": [
          {
            "empty": "True"
          }
        ]
      },
      {
        "$values": ""
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": []
      },
      {
        "$values": ""
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": [
          {
            "class": "4a"
          },
          {
            "count": "2"
          },
          {
            "girl": ""
          }
        ]
      },
      {
        "$values": [
          {
            "name": [
              {
                "@attributes": [
                  {
                    "type": "firstname"
                  }
                ]
              },
              {
                "$values": "Samantha"
              }
            ]
          },
          {
            "age": [
              {
                "@attributes": []
              },
              {
                "$values": "13"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Fishing"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Chess"
              }
            ]
          },
          {
            "address": [
              {
                "@attributes": [
                  {
                    "current": "no"
                  }
                ]
              },
              {
                "$values": [
                  {
                    "country": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "Australia"
                      }
                    ]
                  },
                  {
                    "state": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "NSW"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  }
]

其他回答

如果您不想使用任何外部库或第三方工具,请尝试下面的代码。

这将把xml解析成python字典 这也将解析xml属性 这也将解析空标签,如<tag/>和只有属性的标签,如<tag var=val/>

Code

import re

def getdict(content):
    res=re.findall("<(?P<var>\S*)(?P<attr>[^/>]*)(?:(?:>(?P<val>.*?)</(?P=var)>)|(?:/>))",content)
    if len(res)>=1:
        attreg="(?P<avr>\S+?)(?:(?:=(?P<quote>['\"])(?P<avl>.*?)(?P=quote))|(?:=(?P<avl1>.*?)(?:\s|$))|(?P<avl2>[\s]+)|$)"
        if len(res)>1:
            return [{i[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,i[1].strip())]},{"$values":getdict(i[2])}]} for i in res]
        else:
            return {res[0]:[{"@attributes":[{j[0]:(j[2] or j[3] or j[4])} for j in re.findall(attreg,res[1].strip())]},{"$values":getdict(res[2])}]}
    else:
        return content

with open("test.xml","r") as f:
    print(getdict(f.read().replace('\n','')))

样例输入

<details class="4b" count=1 boy>
    <name type="firstname">John</name>
    <age>13</age>
    <hobby>Coin collection</hobby>
    <hobby>Stamp collection</hobby>
    <address>
        <country>USA</country>
        <state>CA</state>
    </address>
</details>
<details empty="True"/>
<details/>
<details class="4a" count=2 girl>
    <name type="firstname">Samantha</name>
    <age>13</age>
    <hobby>Fishing</hobby>
    <hobby>Chess</hobby>
    <address current="no">
        <country>Australia</country>
        <state>NSW</state>
    </address>
</details>

输出(美化)

[
  {
    "details": [
      {
        "@attributes": [
          {
            "class": "4b"
          },
          {
            "count": "1"
          },
          {
            "boy": ""
          }
        ]
      },
      {
        "$values": [
          {
            "name": [
              {
                "@attributes": [
                  {
                    "type": "firstname"
                  }
                ]
              },
              {
                "$values": "John"
              }
            ]
          },
          {
            "age": [
              {
                "@attributes": []
              },
              {
                "$values": "13"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Coin collection"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Stamp collection"
              }
            ]
          },
          {
            "address": [
              {
                "@attributes": []
              },
              {
                "$values": [
                  {
                    "country": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "USA"
                      }
                    ]
                  },
                  {
                    "state": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "CA"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": [
          {
            "empty": "True"
          }
        ]
      },
      {
        "$values": ""
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": []
      },
      {
        "$values": ""
      }
    ]
  },
  {
    "details": [
      {
        "@attributes": [
          {
            "class": "4a"
          },
          {
            "count": "2"
          },
          {
            "girl": ""
          }
        ]
      },
      {
        "$values": [
          {
            "name": [
              {
                "@attributes": [
                  {
                    "type": "firstname"
                  }
                ]
              },
              {
                "$values": "Samantha"
              }
            ]
          },
          {
            "age": [
              {
                "@attributes": []
              },
              {
                "$values": "13"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Fishing"
              }
            ]
          },
          {
            "hobby": [
              {
                "@attributes": []
              },
              {
                "$values": "Chess"
              }
            ]
          },
          {
            "address": [
              {
                "@attributes": [
                  {
                    "current": "no"
                  }
                ]
              },
              {
                "$values": [
                  {
                    "country": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "Australia"
                      }
                    ]
                  },
                  {
                    "state": [
                      {
                        "@attributes": []
                      },
                      {
                        "$values": "NSW"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  }
]

XML:

<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>

Python代码:

import xml.etree.cElementTree as ET

tree = ET.parse("foo.xml")
root = tree.getroot() 
root_tag = root.tag
print(root_tag) 

for form in root.findall("./bar/type"):
    x=(form.attrib)
    z=list(x)
    for i in z:
        print(x[i])

输出:

foo
1
2

有很多选择。如果速度和内存使用是一个问题,cElementTree看起来很棒。与简单地使用readline读取文件相比,它的开销非常小。

相关指标可以在下表中找到,复制自cElementTree网站:

library                         time    space
xml.dom.minidom (Python 2.1)    6.3 s   80000K
gnosis.objectify                2.0 s   22000k
xml.dom.minidom (Python 2.4)    1.4 s   53000k
ElementTree 1.2                 1.6 s   14500k  
ElementTree 1.2.4/1.3           1.1 s   14500k  
cDomlette (C extension)         0.540 s 20500k
PyRXPU (C extension)            0.175 s 10850k
libxml2 (C extension)           0.098 s 16000k
readlines (read as utf-8)       0.093 s 8850k
cElementTree (C extension)  --> 0.047 s 4900K <--
readlines (read as ascii)       0.032 s 5050k   

正如@jfs所指出的,cElementTree是与Python捆绑在一起的:

Python 2:来自xml。etree导入cElementTree作为ElementTree。 Python 3:从xml。导入ElementTree(自动使用加速的C版本)。

xml.etree.ElementTree vs. lxml

下面是两个最常用的库的一些优点,在进行选择之前,我应该了解它们。

xml.etree.ElementTree:

来自标准库:不需要安装任何模块

lxml

轻松编写XML声明:例如,您是否需要添加standalone="no"? 漂亮的打印:无需额外代码就可以得到漂亮的缩进XML。 Objectify功能:它允许您像处理普通的Python对象hierarchy.node一样使用XML。 sourceline允许您轻松地获取正在使用的XML元素的行。 您还可以使用内置的XSD模式检查器。

你可以使用BeautifulSoup:

from bs4 import BeautifulSoup

x="""<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>"""

y=BeautifulSoup(x)
>>> y.foo.bar.type["foobar"]
u'1'

>>> y.foo.bar.findAll("type")
[<type foobar="1"></type>, <type foobar="2"></type>]

>>> y.foo.bar.findAll("type")[0]["foobar"]
u'1'
>>> y.foo.bar.findAll("type")[1]["foobar"]
u'2'