BeautifulSoup 可访问 DC 共享单车中的可用自行车

Question

我是编程和 python 的新手，我正在尝试访问 DC 共享单车计划中给定站点的可用自行车数量。我相信最好的方法是使用 BeautifulSoup。好消息是数据可以在这里以一种干净的格式提供：https://www.capitalbikeshare.com/data/stations/bikeStations.xml

这是一个车站的例子：

<station>
    <id>1</id>
    <name>15th & S Eads St</name>
    <terminalName>31000</terminalName>
    <lastCommWithServer>1460217337648</lastCommWithServer>
    <lat>38.858662</lat>
    <long>-77.053199</long>
    <installed>true</installed>
    <locked>false</locked>
    <installDate>0</installDate>
    <removalDate/>
    <temporary>false</temporary>
    <public>true</public>
    <nbBikes>7</nbBikes>
    <nbEmptyDocks>8</nbEmptyDocks>
    <latestUpdateTime>1460192501598</latestUpdateTime>
</station>

我正在寻找 <nbBikes> 值。我有一个我认为是 python 脚本的开始，它将向我显示前 5 个站点的值（一旦我得到控制，我将解决选择我想要的站点）但它不返回任何值。这是脚本：

# bikeShareParse.py - parses the capital bikeshare info page 


import bs4, requests

url = "https://www.capitalbikeshare.com/data/stations/bikeStations.xml"

res = requests.get(url)
res.raise_for_status()

#create the soup element from the file
soup = bs4.BeautifulSoup("res.text", "lxml")

# defines the part of the page we are looking for
nbikes = soup.select('#text')

#limits number of results for testing
numOpen = 5
for i in range(numOpen):
        print nbikes

我相信我的问题（除了不理解如何在堆栈溢出问题中正确格式化代码）是nbikes = soup.select('#text') 的值不正确。但是，我似乎无法用任何东西代替“#text”来获得任何值，更不用说我想要的了。

我是否以正确的方式处理这个问题？如果是这样，我错过了什么？

谢谢

Answer 1

此脚本创建一个结构为 [station_ID, bikes_remaining] 的字典。从这个开头修改：http://www.plotsofdots.com/archives/68

# from http://www.plotsofdots.com/archives/68


import xml.etree.ElementTree as ET
import urllib2

#we parse the data using urlib2 and xml
site='https://www.capitalbikeshare.com/data/stations/bikeStations.xml'
htm=urllib2.urlopen(site)
doc = ET.parse(htm)

#we get the root tag
root=doc.getroot()
root.tag

#we define empty lists for the empty bikes
sID=[]
embikes=[]
#we now use a for loop to extract the information we are interested in
for country in root.findall('station'):
    sID.append(country.find('id').text)
    embikes.append(int(country.find('nbBikes').text))

#this just tests that the process above works, can be commented out
#print embikes
#print sID

#use zip to create touples and then parse them into a dataframe
prov=zip(sID,embikes)

print prov[0]