如何解析 XML 并获取特定节点属性的实例?

发布于 2024-08-14 21:16:18 字数 303 浏览 2 评论 0原文

我在 XML 中有很多行,并且正在尝试获取特定节点属性的实例。

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

如何访问属性 foobar 的值?在此示例中,我需要 "1""2"

I have many rows in XML and I'm trying to get instances of a particular node attribute.

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

How do I access the values of the attribute foobar? In this example, I want "1" and "2".

如果你对这篇内容有疑问,欢迎到本站社区发帖提问 参与讨论,获取更多帮助,或者扫码二维码加入 Web 技术交流群。

扫码二维码加入Web技术交流群

发布评论

需要 登录 才能够评论, 你可以免费 注册 一个本站的账号。

评论(21

简美 2024-08-21 21:16:18

我建议 ElementTree。同一 API 还有其他兼容的实现,例如 lxml 和 < Python 标准库本身中的 code>cElementTree ;但是,在这种情况下,他们主要添加的是更快的速度——编程的难易程度取决于 ElementTree 定义的 API。

首先从 XML 构建一个 Element 实例 root,例如使用 XML 函数,或者通过使用以下内容解析文件:

import xml.etree.ElementTree as ET
root = ET.parse('thefile.xml').getroot()

或者 ElementTree。然后执行类似的操作:

for type_tag in root.findall('bar/type'):
    value = type_tag.get('foobar')
    print(value)

输出:

1
2

I suggest ElementTree. There are other compatible implementations of the same API, such as lxml, and cElementTree in the Python standard library itself; but, in this context, what they chiefly add is even more speed -- the ease of programming part depends on the API, which ElementTree defines.

First build an Element instance root from the XML, e.g. with the XML function, or by parsing a file with something like:

import xml.etree.ElementTree as ET
root = ET.parse('thefile.xml').getroot()

Or any of the many other ways shown at ElementTree. Then do something like:

for type_tag in root.findall('bar/type'):
    value = type_tag.get('foobar')
    print(value)

Output:

1
2
灼痛 2024-08-21 21:16:18

minidom 是最快且漂亮的直接向前。

XML:

<data>
    <items>
        <item name="item1"></item>
        <item name="item2"></item>
        <item name="item3"></item>
        <item name="item4"></item>
    </items>
</data>

Python:

from xml.dom import minidom

dom = minidom.parse('items.xml')
elements = dom.getElementsByTagName('item')

print(f"There are {len(elements)} items:")

for element in elements:
    print(element.attributes['name'].value)

输出:

There are 4 items:
item1
item2
item3
item4

minidom is the quickest and pretty straight forward.

XML:

<data>
    <items>
        <item name="item1"></item>
        <item name="item2"></item>
        <item name="item3"></item>
        <item name="item4"></item>
    </items>
</data>

Python:

from xml.dom import minidom

dom = minidom.parse('items.xml')
elements = dom.getElementsByTagName('item')

print(f"There are {len(elements)} items:")

for element in elements:
    print(element.attributes['name'].value)

Output:

There are 4 items:
item1
item2
item3
item4
从来不烧饼 2024-08-21 21:16:18

您可以使用 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'

You can use 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'
悍妇囚夫 2024-08-21 21:16:18

有很多选择。如果速度和内存使用是一个问题,cElementTree 看起来非常好。与简单地使用 readlines 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   

正如所指出的作者:@jfscElementTree与 Python 捆绑在一起:

  • Python 2:from xml.etree import cElementTree as ElementTree
  • Python 3:from xml.etree import ElementTree(自动使用加速的 C 版本)。

There are many options out there. cElementTree looks excellent if speed and memory usage are an issue. It has very little overhead compared to simply reading in the file using readlines.

The relevant metrics can be found in the table below, copied from the cElementTree website:

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   

As pointed out by @jfs, cElementTree comes bundled with Python:

  • Python 2: from xml.etree import cElementTree as ElementTree.
  • Python 3: from xml.etree import ElementTree (the accelerated C version is used automatically).
活泼老夫 2024-08-21 21:16:18

为了简单起见,我建议 xmltodict

它将您的 XML 解析为 OrderedDict;

>>> e = '<foo>
             <bar>
                 <type foobar="1"/>
                 <type foobar="2"/>
             </bar>
        </foo> '
    
>>> import xmltodict
>>> result = xmltodict.parse(e)
>>> result

OrderedDict([(u'foo', OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))]))])

>>> result['foo']

OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))])

>>> result['foo']['bar']

OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])])

I suggest xmltodict for simplicity.

It parses your XML to an OrderedDict;

>>> e = '<foo>
             <bar>
                 <type foobar="1"/>
                 <type foobar="2"/>
             </bar>
        </foo> '
    
>>> import xmltodict
>>> result = xmltodict.parse(e)
>>> result

OrderedDict([(u'foo', OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))]))])

>>> result['foo']

OrderedDict([(u'bar', OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])]))])

>>> result['foo']['bar']

OrderedDict([(u'type', [OrderedDict([(u'@foobar', u'1')]), OrderedDict([(u'@foobar', u'2')])])])
和影子一齐双人舞 2024-08-21 21:16:18

lxml.objectify 非常简单。

获取示例文本:

from lxml import objectify
from collections import defaultdict

count = defaultdict(int)

root = objectify.fromstring(text)

for item in root.bar.type:
    count[item.attrib.get("foobar")] += 1

print dict(count)

输出:

{'1': 1, '2': 1}

lxml.objectify is really simple.

Taking your sample text:

from lxml import objectify
from collections import defaultdict

count = defaultdict(int)

root = objectify.fromstring(text)

for item in root.bar.type:
    count[item.attrib.get("foobar")] += 1

print dict(count)

Output:

{'1': 1, '2': 1}
一袭白衣梦中忆 2024-08-21 21:16:18

Python 有一个与 expat XML 解析器的接口。

xml.parsers.expat

它是一个非验证解析器,因此错误的 XML 不会被捕获。但是,如果您知道您的文件是正确的,那么这非常好,您可能会获得所需的确切信息,并且可以即时丢弃其余信息。

stringofxml = """<foo>
    <bar>
        <type arg="value" />
        <type arg="value" />
        <type arg="value" />
    </bar>
    <bar>
        <type arg="value" />
    </bar>
</foo>"""
count = 0
def start(name, attr):
    global count
    if name == 'type':
        count += 1

p = expat.ParserCreate()
p.StartElementHandler = start
p.Parse(stringofxml)

print count # prints 4

Python has an interface to the expat XML parser.

xml.parsers.expat

It's a non-validating parser, so bad XML will not be caught. But if you know your file is correct, then this is pretty good, and you'll probably get the exact info you want and you can discard the rest on the fly.

stringofxml = """<foo>
    <bar>
        <type arg="value" />
        <type arg="value" />
        <type arg="value" />
    </bar>
    <bar>
        <type arg="value" />
    </bar>
</foo>"""
count = 0
def start(name, attr):
    global count
    if name == 'type':
        count += 1

p = expat.ParserCreate()
p.StartElementHandler = start
p.Parse(stringofxml)

print count # prints 4
淑女气质 2024-08-21 21:16:18

为了添加另一种可能性,您可以使用 untangle,因为它是一个简单的 xml 到 python 对象库。这里有一个示例:

安装:

pip install untangle

用法:

您的 XML 文件(稍作更改):

<foo>
   <bar name="bar_name">
      <type foobar="1"/>
   </bar>
</foo>

使用 untangle 访问属性:

import untangle

obj = untangle.parse('/path_to_xml_file/file.xml')

print obj.foo.bar['name']
print obj.foo.bar.type['foobar']

输出将为:

bar_name
1

有关 untangle 的更多信息可以在“解开"。

另外,如果您好奇,可以在“Python 和 XML”中找到用于处理 XML 和 Python 的工具列表”。您还会看到之前的答案提到了最常见的问题。

Just to add another possibility, you can use untangle, as it is a simple xml-to-python-object library. Here you have an example:

Installation:

pip install untangle

Usage:

Your XML file (a little bit changed):

<foo>
   <bar name="bar_name">
      <type foobar="1"/>
   </bar>
</foo>

Accessing the attributes with untangle:

import untangle

obj = untangle.parse('/path_to_xml_file/file.xml')

print obj.foo.bar['name']
print obj.foo.bar.type['foobar']

The output will be:

bar_name
1

More information about untangle can be found in "untangle".

Also, if you are curious, you can find a list of tools for working with XML and Python in "Python and XML". You will also see that the most common ones were mentioned by previous answers.

走过海棠暮 2024-08-21 21:16:18

我可能会建议 declxml

全面披露:我编写这个库是因为我正在寻找一种在 XML 和 Python 数据结构之间进行转换的方法,而无需使用 ElementTree 编写数十行命令式解析/序列化代码。

通过 declxml,您可以使用处理器以声明方式定义 XML 文档的结构以及如何在 XML 和 Python 数据结构之间进行映射。处理器用于序列化和解析以及基本级别​​的验证。

解析为 Python 数据结构非常简单:

import declxml as xml

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

processor = xml.dictionary('foo', [
    xml.dictionary('bar', [
        xml.array(xml.integer('type', attribute='foobar'))
    ])
])

xml.parse_from_string(processor, xml_string)

生成输出:

{'bar': {'foobar': [1, 2]}}

您还可以使用相同的处理器将数据序列化为 XML

data = {'bar': {
    'foobar': [7, 3, 21, 16, 11]
}}

xml.serialize_to_string(processor, data, indent='    ')

生成以下输出

<?xml version="1.0" ?>
<foo>
    <bar>
        <type foobar="7"/>
        <type foobar="3"/>
        <type foobar="21"/>
        <type foobar="16"/>
        <type foobar="11"/>
    </bar>
</foo>

如果您想使用对象而不是字典,您可以定义处理器将数据转换为 和也来自物体。

import declxml as xml

class Bar:

    def __init__(self):
        self.foobars = []

    def __repr__(self):
        return 'Bar(foobars={})'.format(self.foobars)


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

processor = xml.dictionary('foo', [
    xml.user_object('bar', Bar, [
        xml.array(xml.integer('type', attribute='foobar'), alias='foobars')
    ])
])

xml.parse_from_string(processor, xml_string)

产生以下输出

{'bar': Bar(foobars=[1, 2])}

I might suggest declxml.

Full disclosure: I wrote this library because I was looking for a way to convert between XML and Python data structures without needing to write dozens of lines of imperative parsing/serialization code with ElementTree.

With declxml, you use processors to declaratively define the structure of your XML document and how to map between XML and Python data structures. Processors are used to for both serialization and parsing as well as for a basic level of validation.

Parsing into Python data structures is straightforward:

import declxml as xml

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

processor = xml.dictionary('foo', [
    xml.dictionary('bar', [
        xml.array(xml.integer('type', attribute='foobar'))
    ])
])

xml.parse_from_string(processor, xml_string)

Which produces the output:

{'bar': {'foobar': [1, 2]}}

You can also use the same processor to serialize data to XML

data = {'bar': {
    'foobar': [7, 3, 21, 16, 11]
}}

xml.serialize_to_string(processor, data, indent='    ')

Which produces the following output

<?xml version="1.0" ?>
<foo>
    <bar>
        <type foobar="7"/>
        <type foobar="3"/>
        <type foobar="21"/>
        <type foobar="16"/>
        <type foobar="11"/>
    </bar>
</foo>

If you want to work with objects instead of dictionaries, you can define processors to transform data to and from objects as well.

import declxml as xml

class Bar:

    def __init__(self):
        self.foobars = []

    def __repr__(self):
        return 'Bar(foobars={})'.format(self.foobars)


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

processor = xml.dictionary('foo', [
    xml.user_object('bar', Bar, [
        xml.array(xml.integer('type', attribute='foobar'), alias='foobars')
    ])
])

xml.parse_from_string(processor, xml_string)

Which produces the following output

{'bar': Bar(foobars=[1, 2])}
少女的英雄梦 2024-08-21 21:16:18

这是使用 cElementTree 的非常简单但有效的代码。

try:
    import cElementTree as ET
except ImportError:
  try:
    # Python 2.5 need to import a different module
    import xml.etree.cElementTree as ET
  except ImportError:
    exit_err("Failed to import cElementTree from any known place")      

def find_in_tree(tree, node):
    found = tree.find(node)
    if found == None:
        print "No %s in file" % node
        found = []
    return found  

# Parse a xml file (specify the path)
def_file = "xml_file_name.xml"
try:
    dom = ET.parse(open(def_file, "r"))
    root = dom.getroot()
except:
    exit_err("Unable to open and parse input definition file: " + def_file)

# Parse to find the child nodes list of node 'myNode'
fwdefs = find_in_tree(root,"myNode")

这是来自“python xml 解析”。

Here a very simple but effective code using cElementTree.

try:
    import cElementTree as ET
except ImportError:
  try:
    # Python 2.5 need to import a different module
    import xml.etree.cElementTree as ET
  except ImportError:
    exit_err("Failed to import cElementTree from any known place")      

def find_in_tree(tree, node):
    found = tree.find(node)
    if found == None:
        print "No %s in file" % node
        found = []
    return found  

# Parse a xml file (specify the path)
def_file = "xml_file_name.xml"
try:
    dom = ET.parse(open(def_file, "r"))
    root = dom.getroot()
except:
    exit_err("Unable to open and parse input definition file: " + def_file)

# Parse to find the child nodes list of node 'myNode'
fwdefs = find_in_tree(root,"myNode")

This is from "python xml parse".

苏辞 2024-08-21 21:16:18

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

XML:

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

Python code:

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])

Output:

foo
1
2
肩上的翅膀 2024-08-21 21:16:18

xml.etree.ElementTree 与 lxml

这是两个最常用的库的一些优点,在​​进行选择之前了解一下会很有帮助。

xml.etree.ElementTree:

  1. 来自标准库:无需安装任何模块

lxml

  1. 轻松编写XML声明:例如是否需要添加standalone="没有”?
  2. 漂亮的打印:无需额外代码即可拥有漂亮的缩进 XML。
  3. Objectify 功能:它允许您像处理普通的 Python 对象层次结构.node 一样使用 XML。
  4. sourceline 允许轻松获取您正在使用的 XML 元素的行。
  5. 您还可以使用内置的 XSD 架构检查器。

xml.etree.ElementTree vs. lxml

These are some pros of the two most used libraries I would have benefit to know before choosing between them.

xml.etree.ElementTree:

  1. From the standard library: no needs of installing any module

lxml

  1. Easily write XML declaration: for instance do you need to add standalone="no"?
  2. Pretty printing: you can have a nice indented XML without extra code.
  3. Objectify functionality: It allows you to use XML as if you were dealing with a normal Python object hierarchy.node.
  4. sourceline allows to easily get the line of the XML element you are using.
  5. you can use also a built-in XSD schema checker.
你是我的挚爱i 2024-08-21 21:16:18

如果您使用 python-benedict,则无需使用特定于库的 API。只需从 XML 初始化一个新实例并轻松管理它,因为它是 dict 子类。

安装很简单:pip install python-benedict

from benedict import benedict as bdict

# data-source can be an url, a filepath or data-string (as in this example)
data_source = """
<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>"""

data = bdict.from_xml(data_source)
t_list = data['foo.bar'] # yes, keypath supported
for t in t_list:
   print(t['@foobar'])

它支持多种格式的 I/O 操作并规范化Base64CSV、JSONTOMLXMLYAML查询字符串

它经过充分测试,并且在 GitHub 上开源。披露:我是作者。

There's no need to use a lib specific API if you use python-benedict. Just initialize a new instance from your XML and manage it easily since it is a dict subclass.

Installation is easy: pip install python-benedict

from benedict import benedict as bdict

# data-source can be an url, a filepath or data-string (as in this example)
data_source = """
<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>"""

data = bdict.from_xml(data_source)
t_list = data['foo.bar'] # yes, keypath supported
for t in t_list:
   print(t['@foobar'])

It supports and normalizes I/O operations with many formats: Base64, CSV, JSON, TOML, XML, YAML and query-string.

It is well tested and open-source on GitHub. Disclosure: I am the author.

梦情居士 2024-08-21 21:16:18
import xml.etree.ElementTree as ET
data = '''<foo>
           <bar>
               <type foobar="1"/>
               <type foobar="2"/>
          </bar>
       </foo>'''
tree = ET.fromstring(data)
lst = tree.findall('bar/type')
for item in lst:
    print item.get('foobar')

这将打印 foobar 属性的值。

import xml.etree.ElementTree as ET
data = '''<foo>
           <bar>
               <type foobar="1"/>
               <type foobar="2"/>
          </bar>
       </foo>'''
tree = ET.fromstring(data)
lst = tree.findall('bar/type')
for item in lst:
    print item.get('foobar')

This will print the value of the foobar attribute.

沩ん囻菔务 2024-08-21 21:16:18

simplified_scrapy:一个新的lib,使用后我就爱上了它。我推荐给你。

from simplified_scrapy import SimplifiedDoc
xml = '''
<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>
'''

doc = SimplifiedDoc(xml)
types = doc.selects('bar>type')
print (len(types)) # 2
print (types.foobar) # ['1', '2']
print (doc.selects('bar>type>foobar()')) # ['1', '2']

这里是更多示例。这个库很容易使用。

simplified_scrapy: a new lib, I fell in love with it after I used it. I recommend it to you.

from simplified_scrapy import SimplifiedDoc
xml = '''
<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>
'''

doc = SimplifiedDoc(xml)
types = doc.selects('bar>type')
print (len(types)) # 2
print (types.foobar) # ['1', '2']
print (doc.selects('bar>type>foobar()')) # ['1', '2']

Here are more examples. This lib is easy to use.

若水般的淡然安静女子 2024-08-21 21:16:18

我很受伤,没有人推荐熊猫。 Pandas 有一个函数 read_xml(),它非常适合这种平面 xml 结构。

import pandas as pd

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

df = pd.read_xml(xml, xpath=".//type")
print(df)

输出:

   foobar
0       1
1       2

I am wounder, that no one suggest pandas. Pandas have a function read_xml(), what is perfect for such flat xml structures.

import pandas as pd

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

df = pd.read_xml(xml, xpath=".//type")
print(df)

Output:

   foobar
0       1
1       2
你如我软肋 2024-08-21 21:16:18
#If the xml is in the form of a string as shown below then
from lxml  import etree, objectify
'''sample xml as a string with a name space {http://xmlns.abc.com}'''
message =b'<?xml version="1.0" encoding="UTF-8"?>\r\n<pa:Process xmlns:pa="http://xmlns.abc.com">\r\n\t<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>\r\n'  # this is a sample xml which is a string


print('************message coversion and parsing starts*************')

message=message.decode('utf-8') 
message=message.replace('<?xml version="1.0" encoding="UTF-8"?>\r\n','') #replace is used to remove unwanted strings from the 'message'
message=message.replace('pa:Process>\r\n','pa:Process>')
print (message)

print ('******Parsing starts*************')
parser = etree.XMLParser(remove_blank_text=True) #the name space is removed here
root = etree.fromstring(message, parser) #parsing of xml happens here
print ('******Parsing completed************')


dict={}
for child in root: # parsed xml is iterated using a for loop and values are stored in a dictionary
    print(child.tag,child.text)
    print('****Derving from xml tree*****')
    if child.tag =="{http://xmlns.abc.com}firsttag":
        dict["FIRST_TAG"]=child.text
        print(dict)


### output
'''************message coversion and parsing starts*************
<pa:Process xmlns:pa="http://xmlns.abc.com">

    <pa:firsttag>SAMPLE</pa:firsttag></pa:Process>
******Parsing starts*************
******Parsing completed************
{http://xmlns.abc.com}firsttag SAMPLE
****Derving from xml tree*****
{'FIRST_TAG': 'SAMPLE'}'''
#If the xml is in the form of a string as shown below then
from lxml  import etree, objectify
'''sample xml as a string with a name space {http://xmlns.abc.com}'''
message =b'<?xml version="1.0" encoding="UTF-8"?>\r\n<pa:Process xmlns:pa="http://xmlns.abc.com">\r\n\t<pa:firsttag>SAMPLE</pa:firsttag></pa:Process>\r\n'  # this is a sample xml which is a string


print('************message coversion and parsing starts*************')

message=message.decode('utf-8') 
message=message.replace('<?xml version="1.0" encoding="UTF-8"?>\r\n','') #replace is used to remove unwanted strings from the 'message'
message=message.replace('pa:Process>\r\n','pa:Process>')
print (message)

print ('******Parsing starts*************')
parser = etree.XMLParser(remove_blank_text=True) #the name space is removed here
root = etree.fromstring(message, parser) #parsing of xml happens here
print ('******Parsing completed************')


dict={}
for child in root: # parsed xml is iterated using a for loop and values are stored in a dictionary
    print(child.tag,child.text)
    print('****Derving from xml tree*****')
    if child.tag =="{http://xmlns.abc.com}firsttag":
        dict["FIRST_TAG"]=child.text
        print(dict)


### output
'''************message coversion and parsing starts*************
<pa:Process xmlns:pa="http://xmlns.abc.com">

    <pa:firsttag>SAMPLE</pa:firsttag></pa:Process>
******Parsing starts*************
******Parsing completed************
{http://xmlns.abc.com}firsttag SAMPLE
****Derving from xml tree*****
{'FIRST_TAG': 'SAMPLE'}'''
柳若烟 2024-08-21 21:16:18

如果您不想使用任何外部库或第三方工具,请尝试以下代码。

  • 这会将 xml 解析为 python dictionary
  • 这也将解析 xml 属性
  • 这还将解析空标签,如 和标签仅包含

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','')))

Sample input

<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>

Output (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"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  }
]

If you don't want to use any external libraries or 3rd party tools, Please try below code.

  • This will parse xml into python dictionary
  • This will parse xml attrbutes as well
  • This will also parse empty tags like <tag/> and tags with only attributes like <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','')))

Sample input

<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>

Output (Beautified)

[
  {
    "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"
                      }
                    ]
                  }
                ]
              }
            ]
          }
        ]
      }
    ]
  }
]
睫毛溺水了 2024-08-21 21:16:18

如果源是 xml 文件,就像这个示例一样,

<pa:Process xmlns:pa="http://sssss">
        <pa:firsttag>SAMPLE</pa:firsttag>
    </pa:Process>

您可以尝试以下代码

from lxml import etree, objectify
metadata = 'C:\\Users\\PROCS.xml' # this is sample xml file the contents are shown above
parser = etree.XMLParser(remove_blank_text=True) # this line removes the  name space from the xml in this sample the name space is --> http://sssss
tree = etree.parse(metadata, parser) # this line parses the xml file which is PROCS.xml
root = tree.getroot() # we get the root of xml which is process and iterate using a for loop
for elem in root.getiterator():
    if not hasattr(elem.tag, 'find'): continue  # (1)
    i = elem.tag.find('}')
    if i >= 0:
        elem.tag = elem.tag[i+1:]

dict={}  # a python dictionary is declared
for elem in tree.iter(): #iterating through the xml tree using a for loop
    if elem.tag =="firsttag": # if the tag name matches the name that is equated then the text in the tag is stored into the dictionary
        dict["FIRST_TAG"]=str(elem.text)
        print(dict)

输出将是

{'FIRST_TAG': 'SAMPLE'}

If the source is an xml file, say like this sample

<pa:Process xmlns:pa="http://sssss">
        <pa:firsttag>SAMPLE</pa:firsttag>
    </pa:Process>

you may try the following code

from lxml import etree, objectify
metadata = 'C:\\Users\\PROCS.xml' # this is sample xml file the contents are shown above
parser = etree.XMLParser(remove_blank_text=True) # this line removes the  name space from the xml in this sample the name space is --> http://sssss
tree = etree.parse(metadata, parser) # this line parses the xml file which is PROCS.xml
root = tree.getroot() # we get the root of xml which is process and iterate using a for loop
for elem in root.getiterator():
    if not hasattr(elem.tag, 'find'): continue  # (1)
    i = elem.tag.find('}')
    if i >= 0:
        elem.tag = elem.tag[i+1:]

dict={}  # a python dictionary is declared
for elem in tree.iter(): #iterating through the xml tree using a for loop
    if elem.tag =="firsttag": # if the tag name matches the name that is equated then the text in the tag is stored into the dictionary
        dict["FIRST_TAG"]=str(elem.text)
        print(dict)

Output would be

{'FIRST_TAG': 'SAMPLE'}
凤舞天涯 2024-08-21 21:16:18

使用 iterparse() 你可以捕获标签属性字典值:

import xml.etree.ElementTree as ET
from io import StringIO

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

file = StringIO(xml)

for event, elem in ET.iterparse(file, ("end",)):
    if event == "end" and elem.tag == "type":
        print(elem.attrib["foobar"])

With iterparse() you can catch the tag attribute dictionary value:

import xml.etree.ElementTree as ET
from io import StringIO

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

file = StringIO(xml)

for event, elem in ET.iterparse(file, ("end",)):
    if event == "end" and elem.tag == "type":
        print(elem.attrib["foobar"])
千秋岁 2024-08-21 21:16:18

经典的 SAX 解析器 解决方案可以像:

from xml.sax import make_parser, handler
from io import StringIO
xml = """<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>
"""
file = StringIO(xml)

class MyParser(handler.ContentHandler):

    def startElement(self, name, attrs):
        if name == "type":
            print(attrs['foobar'])

parser = make_parser()
b = MyParser()
parser.setContentHandler(b)
parser.parse(file)

输出:

1
2

The classic SAX parser solution could work like:

from xml.sax import make_parser, handler
from io import StringIO
xml = """<foo>
   <bar>
      <type foobar="1"/>
      <type foobar="2"/>
   </bar>
</foo>
"""
file = StringIO(xml)

class MyParser(handler.ContentHandler):

    def startElement(self, name, attrs):
        if name == "type":
            print(attrs['foobar'])

parser = make_parser()
b = MyParser()
parser.setContentHandler(b)
parser.parse(file)

Output:

1
2
~没有更多了~
我们使用 Cookies 和其他技术来定制您的体验包括您的登录状态等。通过阅读我们的 隐私政策 了解更多相关信息。 单击 接受 或继续使用网站,即表示您同意使用 Cookies 和您的相关数据。
原文