如何在python中读取具有特定标识符的kml文件？答案

【问题标题】：How to read kml file with specific identifier in python?如何在python中读取具有特定标识符的kml文件？
【发布时间】：2020-01-29 11:27:32
【问题描述】：

我正在尝试阅读德国气象服务提供的这些 kml 文件：example_data

使用以下代码，我无法访问dwd: 孩子：

from zipfile import ZipFile
from lxml import html
from urllib.request import urlretrieve

urlretrieve('http://opendata.dwd.de/weather/local_forecasts/mos/MOSMIX_L/single_stations/10641/kml/MOSMIX_L_LATEST_10641.kmz')

kmz = ZipFile("local_data.kmz", 'r')
kml = kmz.open(kmz.filelist[0].filename, 'r').read()

root = parser.fromstring(kml)

使用root.Document.Placemark.ExtendedData.getchildren() 命令我可以访问以下列表（长度为 114，我在此处剪切）：

[<Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71705b2b08>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706befc8>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706bef88>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706bebc8>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706bea88>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706beb08>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706be848>,
 <Element {https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd}Forecast at 0x7f71706be988>]

但是使用root.Document.Placemark.ExtendedData.Foreast 我收到以下错误消息：

AttributeError: no such child: {http://www.opengis.net/kml/2.2}Forecast

我猜问题是使用了标准的 opengis kml Schema。如何访问数据？

这是一个文件的头：

<?xml version="1.0" encoding="ISO-8859-1" standalone="yes"?>
<kml:kml xmlns:dwd="https://opendata.dwd.de/weather/lib/pointforecast_dwd_extension_V1_0.xsd" xmlns:gx="http://www.google.com/kml/ext/2.2" xmlns:xal="urn:oasis:names:tc:ciq:xsdschema:xAL:2.0" xmlns:kml="http://www.opengis.net/kml/2.2" xmlns:atom="http://www.w3.org/2005/Atom">
    <kml:Document>
        <kml:ExtendedData>
            <dwd:ProductDefinition>
                <dwd:Issuer>Deutscher Wetterdienst</dwd:Issuer>
                <dwd:ProductID>DWD_MOSMIX_1H</dwd:ProductID>
                <dwd:GeneratingProcess>DWD MOSMIX hourly, Version 1.0</dwd:GeneratingProcess>
                <dwd:IssueTime></dwd:IssueTime>
                <dwd:ReferencedModel>
                    <dwd:Model dwd:name="ICON" dwd:referenceTime="2018-05-17T00:00:00Z"/>
                    <dwd:Model dwd:name="ECMWF/IFS" dwd:referenceTime="2018-05-17T00:00:00Z"/>
                </dwd:ReferencedModel>
                <dwd:ForecastTimeSteps>
                    <dwd:TimeStep>2018-05-17T10:00:00.000Z</dwd:TimeStep>
                    <dwd:TimeStep>2018-05-17T11:00:00.000Z</dwd:TimeStep>
                    <dwd:TimeStep>2018-05-17T12:00:00.000Z</dwd:TimeStep>
                    <dwd:TimeStep>2018-05-17T13:00:00.000Z</dwd:TimeStep>
                    <dwd:TimeStep>2018-05-17T14:00:00.000Z</dwd:TimeStep>
                    <dwd:TimeStep>2018-05-17T15:00:00.000Z</dwd:TimeStep>

【问题讨论】：

root.Document.Placemark.ExtendedData 没有预测，它有很多预测。你在哪里看到root.Document.Placemark.ExtendedData.Foreast成功使用了？它甚至意味着什么？如果您想要第一次预测，那么大概root.Document.Placemark.ExtendedData.getchildren()[0] 会这样做。
@FiddleStix 感谢这项工作以接收值列表。你甚至知道如何评价ForecastTimeSteps 吗？
BeautifulSoup 适用于任何 XML，尤其是具有自定义命名空间元素的 KML 文件。

标签： python xml xsd

【解决方案1】：

从 KML/KMZ 文件BeautifulSoup Python 库中解析自定义元素可能是最简单的选择。 API 可以通过 id、类、属性名称/值等查找所有或单个元素。它还对 XML 进行松散的解析，因此格式错误的元素不会破坏它。

import requests
from zipfile import ZipFile
from bs4 import BeautifulSoup

url = 'http://opendata.dwd.de/weather/local_forecasts/mos/MOSMIX_L/single_stations/10641/kml/MOSMIX_L_LATEST_10641.kmz'
r = requests.get(url)
with open('local_data.kmz', 'wb') as fout:
    fout.write(r.content)

with ZipFile('local_data.kmz', 'r') as kmz:
    kml = kmz.open(kmz.filelist[0].filename, 'r').read()
soup = BeautifulSoup(kml, 'xml')

# iterate over each TimeStep element in dwd:ForecastTimeSteps
steps = soup.find("dwd:ForecastTimeSteps")
for step in steps.find_all("dwd:TimeStep"):
    print(step.text)

输出：

2021-10-20T16:00:00.000Z
2021-10-20T17:00:00.000Z
2021-10-20T18:00:00.000Z
...
2021-10-30T20:00:00.000Z
2021-10-30T21:00:00.000Z
2021-10-30T22:00:00.000Z

【讨论】：