将 xml 数据转换为字典列表以加载到表中答案

【问题标题】：Converting xml data into list of dictionaries to load into tables将 xml 数据转换为字典列表以加载到表中
【发布时间】：2019-11-11 03:45:46
【问题描述】：

我已经编写了一个代码来将 xml 数据转换为字典列表并加载到表中。

输入文件数据：

<report>
    <report_header type='comp1'  title='industry' year='2019' />
        <report_body age='21'>
        <Prod name='krishna' id='11' place='usa'>
            <License state='aus' area= 'street1'>
            </License>
            <License state='mus' area= 'street2'>
            </License>
            <License state='mukin' area= 'street3'>
            </License>
        </Prod>
        <Prod name='ram' id='12' place='uk'>
            <License state='junej' area= 'street4'>
            </License>
            <License state='rand' area= 'street5'>
            </License>
            <License state='gandhi' area= 'street6'>
            </License>
        </Prod>
        <Prod name='chand' id='13' place='london'>
            <License state='nehru' area= 'street7'>
            </License>
            <License state='mahatma' area= 'street8'>
            </License>
            <License state='park' area= 'street9'>
            </License>
        </Prod>
    </report_body>
 </report>

代码：

import xml.etree.ElementTree as ET
tree = ET.parse('sample.xml')
root = tree.getroot()
way_list=[]
for item in root.iter():
  way_list.append(dict(item.attrib))
for k, v in [(k, v) for x in way_list for (k, v) in x.items()]:
  print(k,v)

输出： 输入 comp1

标题行业

2019 年

21 岁

命名克里希纳

id 11

美国

澳大利亚

区域街道1

状态

区域街道2

州穆金

区域街道3

命名内存

id 12

英国

州 6 月

区域街道4

州兰特

区域街道5

甘地

区域街道6

名字陈

id 13

伦敦

国家尼赫鲁

区街7

国家大圣

区域街道8

州立公园

区域街道9

预期输出： [{type:'comp1',title:'industry',year:2019,age:21,name:'krishna',id:11,place:'usa' ,state :'aus',area:'street1'},{type:'comp1',title:'industry',year:2019,age:21,name:'krishna',id:11,place:'usa' ,state :'mus',area:'street2'},{type:'comp1',title:'industry',year:2019,age:21,name:'krishna',id:11,place:'usa' ,state :'muskin',area:'street3'},{type:'comp1',title:'industry',year:2019,age:21,name:'ram',id:12,place:'uk' ,state :'junej',area:'street4'},{type:'comp1',title:'industry',year:2019,age:21,name:'ram',id:12,place:'uk' ,state :'rand',area:'street5'},.........等]

我的主要目标是将数据加载到如下表中：

类型、标题、年份、姓名、身份证、地点、州、地区

comp1,industry,2019,krishna,11,usa,aus,street1

comp1,industry,2019,krishna,11,usa,mus,street2

comp1,industry,2019,krishna,11,usa,muskin,street3

comp1,industry,2019,ram,12,uk,junej,street4

comp1,industry,2019,ram,12,uk,rand,street5

comp1,industry,2019,ram,12,uk,gandhi,street6

现在，我可以将数据转换成字典列表了。

【问题讨论】：

标签： python python-3.x list python-2.7 dictionary

【解决方案1】：

这是一种方法。阅读csv module。

import csv, os, sys, io
from xml.etree import ElementTree

data = """\
<report>
<report_header type='comp1'  title='industry' year='2019' />
    <report_body>
    <Prod name='krishna' id='11' place='usa'>
        <License state='aus' area= 'street1'>
        </License>
        <License state='mus' area= 'street2'>
        </License>
        <License state='mukin' area= 'street3'>
        </License>
    </Prod>
    <Prod name='ram' id='12' place='uk'>
        <License state='junej' area= 'street4'>
        </License>
        <License state='rand' area= 'street5'>
        </License>
        <License state='gandhi' area= 'street6'>
        </License>
    </Prod>
    <Prod name='chand' id='13' place='london'>
        <License state='nehru' area= 'street7'>
        </License>
        <License state='mahatma' area= 'street8'>
        </License>
        <License state='park' area= 'street9'>
        </License>
    </Prod>
</report_body>
</report>
"""

fieldnames = ['type', 'title', 'year', 'name', 'id', 'place', 'state', 'area']
writer = csv.DictWriter(sys.stdout, fieldnames=fieldnames)
writer.writeheader()
tree = ElementTree.parse(io.StringIO(data))
report_header = tree.find('report_header')
report_body = tree.find('report_body')
for Prod in report_body.findall('Prod'):
    for License in Prod.findall('License'):
        d = {}
        d.update(License.attrib)
        d.update(Prod.attrib)
        d.update(report_header.attrib)
        writer.writerow(d)

【讨论】：

【解决方案2】：

仅使用 ElementTree。

import xml.etree.ElementTree as ET

tree = ET.parse('sample.xml')
root = tree.getroot()
dict_rep= root.find('report_header').attrib
dict_rep.update(root.find('report_body').attrib)
way_list=[]
for prod in root.iter('Prod'):
  dict_line = dict_rep
  dict_line.update(prod.attrib)
  for lic in prod.iter('License'):
    dict_line.update(lic.attrib)
    print(dict_line)
    way_list.append(dict_line)

【讨论】：