xml（Extensible Markup Language，简称：XML）Extensible Markup Language is anetconf configuration file format. It is an inherently hierarchical data format, and the most natural representation is to parse it into a tree. However, xmlsuch label data is geared towards “machine” recognition and is not conducive to “human” recognition , so it seems to be more troublesome.
The
Netconfworking group was established in May 2003. The working group is mainly to propose a new XML-based network configuration (NETCONF) protocol And established.
PythonBuilt-in API:xml.etree.ElementTree can parsexml files. ElementTreeParses the entire xml document into a tree structure, Element represents a single node in this tree structure.
Government document site: The ElementTree XML API
The following example is in the form of the following xml file, which is also an official case. xmlThe document examples are as follows:
xmlDocument examples are as follows:
<?xml version="1.0"?>
<data id="world country">
<country name="Liechtenstein">
<rank>1</rank>
<year>2008</year>
<gdppc>141100</gdppc>
<neighbor name="Austria" direction="E"/>
<neighbor name="Switzerland" direction="W"/>
</country>
<country name="Singapore">
<rank>4</rank>
<year>2011</year>
<gdppc>59900</gdppc>
<neighbor name="Malaysia" direction="N"/>
</country>
<country name="Panama">
<rank>68</rank>
<year>2011</year>
<gdppc>13600</gdppc>
<neighbor name="Costa Rica" direction="W"/>
<neighbor name="Colombia" direction="E"/>
</country>
</data>
1. xml data format
ElementThe format corresponding to common attributesxml is as follows:
<tag attrib=“netmiko_inventory”>text</tag>
example:
<device_type desc="platform">cisco_ios</device_type>
tag attrib text tag
in:
1, tag: It is a str object, representing xml tags. In the example, it is closed before and after. device_type
2. attrib: It is a dict object, representing xml attributes, in the example desc="platform"
3. text: It is the content wrapped in the xml data tag, also Element content, in the example cisco_ios
4, child elements: it is the subset included in a pair of tags xml, As shown below, it is similar to the content wrapped in the country tag
Example:
import xml.etree.ElementTree as ET
# 读取、解析文件，获取跟元素
tree = ET.parse('sample.xml')
root = tree.getroot()
# 获取根元素的标签名称以及所有属性
# data
print('root.tag:', root.tag)
print('root.attrib:', root.attrib)
# 获取text
print(root[0][1].text)
Output result:
root.tag: data
root.attrib: {'id': 'world country'}
2008
2. Search method
ElementThere are a lot of search methods, summarized as follows:
iter(tag=None): ItineraryElementtargetchild, possibletagspecified;findall(match): Find the node that the current elementtagorpathcan match;childfind(match): Find the first node that the current elementtagorpathcan match;childget(key, default=None): Specify the element to be takenkeypursuantattrib, be fruitlessattrib, returndefault.
# 一次性获取所有名为 country 的元素、然后遍历
for country in root.findall('country'):
# 获取 country 元素中的 name 属性
name = country.get('name')
# 寻找名为 rank 的子节点，获取其text
rank = country.find('rank').text
# 一次性获取所有名为 country 下 neighbor的元素、然后遍历
neighbors = country.findall('neighbor')
neighbor_name = []
for neighbor in neighbors:
n = neighbor.get('name')
neighbor_name.append(n)
print(name, rank, neighbor_name)
The print result is as follows:
Liechtenstein 1 ['Austria', 'Switzerland']
Singapore 4 ['Malaysia']
Panama 68 ['Costa Rica', 'Colombia']
3. iter iterator
Element uses the iter iterator to recursively traverse all children below it.
# 一次性获取所有名为 country 的元素、然后遍历
for country in root.iter('country'):
# 获取 country 元素中的 name 属性
name = country.get('name')
print(name)
for rank in root.iter('rank'):
# 获取 country 元素中的 name 属性
rank_n = rank.text
print(rank_n)
The print result is as follows:
Liechtenstein
Singapore
Panama
1
4
68
4. Convert xml data into dictionary
xmltodict is very simple to use and has low learning cost. It can quickly convert data in XML format into a dictionary and easily perform secondary data processing.
code show as below:
import xmltodict, json
with open('sample.xml') as f:
my_dict = xmltodict.parse(f.read())
with open('info1.json', 'w') as f:
json.dump(my_dict, f, sort_keys=False, indent=2)
Openinfo1.json to view, the saved content is as follows:
{
"data": {
"@id": "world country",
"country": [
{
"@name": "Liechtenstein",
"rank": "1",
"year": "2008",
"gdppc": "141100",
"neighbor": [
{
"@name": "Austria",
"@direction": "E"
},
{
"@name": "Switzerland",
"@direction": "W"
}
]
},
{
"@name": "Singapore",
"rank": "4",
"year": "2011",
"gdppc": "59900",
"neighbor": {
"@name": "Malaysia",
"@direction": "N"
}
},
{
"@name": "Panama",
"rank": "68",
"year": "2011",
"gdppc": "13600",
"neighbor": [
{
"@name": "Costa Rica",
"@direction": "W"
},
{
"@name": "Colombia",
"@direction": "E"
}
]
}
]
}
}
in:
tagandattribwill become dictionarykey, for example, the abovedata、id、country、name、rankand so on;- However, with attributes
attribwill automatically add the symbol, while others will not;keya>@ keycorresponds tovalue, which will become a string.
5. Save as xml
xmltodict can not only convert xml into dictionary form, but also convert the dictionary into xml form and store it locally, as shown below:
def saveXML():
import xmltodict
with open('info.xml', 'w') as f:
info_dict = {
'dev_info': {
'device_type': 'cisco_ios',
'username': 'admin',
'password': 'cisco',
'ip': '192.168.47.10'
}
}
f.write(xmltodict.unparse(info_dict, pretty=True))
After saving it as an xml file, open it and view the results as follows:
<?xml version="1.0" encoding="utf-8"?>
<dev_info>
<device_type>cisco_ios</device_type>
<username>admin</username>
<password>cisco</password>
<ip>192.168.47.10</ip>
</dev_info>
6. Summary
I briefly studied the xml file before, including what xml is and how to use it in python Read, manipulate and store asxmlfiles. At the same time, machine-friendlyxml files are converted into human-friendly dictionary viewing. xmlIt is indeed not easy to view and analyze, and it is a bit laborious to do.