XML 到 CSV Python

Question

状态的 XML 数据（file.xml）如下所示

<?xml version="1.0" encoding="UTF-8" standalone="true"?>
<Activity_Logs xsi:schemaLocation="http://www.cisco.com/PowerKEYDVB/Auditing 
DailyActivityLog.xsd" To="2018-04-01" From="2018-04-01" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns="http://www.cisco.com/PowerKEYDVB/Auditing">
    <ActivityRecord>
       <time>2015-09-16T04:13:20Z</time>
       <oper>Create_Product</oper>
       <pkgEid>10</pkgEid>
       <pkgName>BBCWRL</pkgName>
       </ActivityRecord>
    <ActivityRecord>
       <time>2015-09-16T04:13:20Z</time>
       <oper>Create_Product</oper>
       <pkgEid>18</pkgEid>
       <pkgName>CNNINT</pkgName>
    </ActivityRecord>

上述 XML 文件的解析和转换为 CSV 将由以下 python 代码完成。

import csv
import xml.etree.cElementTree as ET


tree =  ET.parse('file.xml')
root = tree.getroot()


data_to_csv= open('output.csv','w')

list_head=[]

Csv_writer=csv.writer(data_to_csv)

count=0
for elements in root.findall('ActivityRecord'):
    List_node = []
    if count == 0 :

        time = elements.find('time').tag
        list_head.append(time)

        oper = elements.find('oper').tag
        list_head.append(oper)

        pkgEid = elements.find('pkgEid').tag
        list_head.append(pkgEid)


        pkgName = elements.find('pkgName').tag
        list_head.append(pkgName)

        Csv_writer.writerow(list_head)
        count = +1

    time = elements.find('time').text
    List_node.append(time)

    oper = elements.find('oper').text
    List_node.append(oper)

    pkgEid = elements.find('pkgEid').text
    List_node.append(pkgEid)

    pkgName = elements.find('pkgName').text
    List_node.append(pkgName)    

    Csv_writer.writerow(List_node)

data_to_csv.close()

我使用的代码没有给我任何 CSV 数据。谁能告诉我我到底哪里出错了？

Answer 1

使用 Pandas，解析所有 xml 字段。

import xml.etree.ElementTree as ET
import pandas as pd

tree = ET.parse("file.xml")
root = tree.getroot()

get_range = lambda col: range(len(col))
l = [{r[i].tag:r[i].text for i in get_range(r)} for r in root]

df = pd.DataFrame.from_dict(l)
df.to_csv('file.csv')

Answer 2

使用pandas 和BeautifulSoup 可以轻松实现预期输出：

#Code:

import pandas as pd
import itertools
from bs4 import BeautifulSoup as b
with open("file.xml", "r") as f: # opening xml file
    content = f.read()

soup = b(content, "lxml")
pkgeid =  [ values.text for values in soup.findAll("pkgeid")]
pkgname = [ values.text for values in soup.findAll("pkgname")]
time =  [ values.text for values in soup.findAll("time")]
oper =  [ values.text for values in soup.findAll("oper")]
# For python-3.x use `zip_longest` method
# For python-2.x use 'izip_longest method
data = [item for item in itertools.zip_longest(time, oper, pkgeid, pkgname)] 
df  = pd.DataFrame(data=data)
df.to_csv("sample.csv",index=False, header=None)

---

#output in `sample.csv` file will be as follows:
2015-09-16T04:13:20Z,Create_Product,10,BBCWRL
2015-09-16T04:13:20Z,Create_Product,18,CNNINT
2018-04-01T03:30:28Z,Deactivate_Dhct,,

Answer 3

如果是一次性操作，请使用 pyxmlparser。

免责声明我是图书馆的作者，它是相当新的。任何反馈表示赞赏。它是一个命令行实用程序。

https://pypi.org/project/pyxmlparser/

Answer 4

2021 年的答案：
您可以使用 Pandas 读取 XML 并输出 CSV
https://pandas.pydata.org/pandas-docs/dev/whatsnew/v1.3.0.html#read-and-write-xml-documents

import pandas as pd
df = pd.read_xml(<xml_or_xml_filepath>)
# ...
df.to_csv(<csv_filepath>)

有关使用的更多详细信息，请参阅官方文档： https://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.read_xml.html

Answer 5

找到了最合适的方法：

import os
import pandas as pd
from bs4 import BeautifulSoup as b

with open("file.xml", "r") as f: # opening xml file
    content = f.read()

soup = b(content, "lxml")
df1 = pd.DataFrame()

for each_file in files_xlm: 
    with open( each_file, "r") as f: # opening xml file
        content = f.read()
    soup = b(content, "lxml")    

    list1 = []
    for values in soup.findAll("activityrecord"):  
        if values.find("time") is None:
            time = ""
        else:
            time = values.find("time").text        
        if values.find("oper") is None:
            oper = ""    
        else:
            oper = values.find("oper").text      
        if values.find("pkgeid") is None:
            pkgeid = ""    
        else:
            pkgeid = values.find("pkgeid").text     
        if values.find("pkgname") is None:
            pkgname = ""    
        else:
            pkgname = values.find("pkgname").text 
        if values.find("dhct") is None:
            dhct = ""    
        else:
            dhct = values.find("dhct").text   
        if values.find("sourceid") is None:
            sourceid = ""    
        else:
            sourceid = values.find("sourceid").text      
    
        list1.append(time+','+ oper+','+pkgeid+','+ pkgname+','+dhct+','+sourceid)
        df = pd.DataFrame(list1)



df=df[0].str.split(',', expand=True)
df.columns = ['Time','Oper','PkgEid','PkgName','dhct','sourceid']
df.to_csv("new.csv",index=False)