用Python解析HTML文件

问题内容：

我有一个非常长的html文件，看起来就像这个html文件。我希望能够解析该文件，以便以元组的形式获取信息。

例：

<tr>
      <td>Cech</td>
      <td>Chelsea</td>
      <td>30</td>
      <td>£6.4</td>
</tr>

以上信息将如下所示("Cech", "Chelsea", 30, 6.4)。但是，如果您仔细查看我发布的链接，则我发布的html示例将在<h2>Goalkeepers</h2>标记下。我也需要这个标签。因此，基本上，结果元组将看起来像("Cech", "Chelsea", 30, 6.4, Goalkeepers)。在文件的更下方，有一群球员<h2>属于中场，后卫和前锋的标签。

我尝试使用beautifulsoup和ntlk库，但迷路了。所以现在我有以下代码：

import nltk
from urllib import urlopen

url = "http://fantasy.premierleague.com/player-list/"
html = urlopen(url).read()
raw = nltk.clean_html(html)
print raw

这只是剥离所有标记的html文件，并给出如下内容：

          Cech
          Chelsea
          30
          £6.4

尽管我可以编写一段糟糕的代码来读取每一行并将其分配给一个元组。我无法提出任何可以结合播放器位置（<h2>标签中存在的字符串）的解决方案。任何解决方案/建议将不胜感激。

我倾向于使用元组i的原因，以便可以使用拆包并计划使用拆包的值填充MySQl表。

问题答案：

from bs4 import BeautifulSoup
from pprint import pprint

soup = BeautifulSoup(html)
h2s = soup.select("h2") #get all h2 elements
tables = soup.select("table") #get all tables

first = True
title =""
players = []
for i,table in enumerate(tables):
    if first:
         #every h2 element has 2 tables. table size = 8, h2 size = 4
         #so for every 2 tables 1 h2
         title =  h2s[int(i/2)].text
    for tr in table.select("tr"):
        player = (title,) #create a player
        for td in tr.select("td"):
            player = player + (td.text,) #add td info in the player
        if len(player) > 1: 
            #If the tr contains a player and its not only ("Goalkeaper") add it
            players.append(player)
    first = not first
pprint(players)

输出：

[('Goalkeepers', 'Cech', 'Chelsea', '30', '£6.4'),
 ('Goalkeepers', 'Hart', 'Man City', '28', '£6.4'),
 ('Goalkeepers', 'Krul', 'Newcastle', '21', '£5.0'),
 ('Goalkeepers', 'Ruddy', 'Norwich', '25', '£5.0'),
 ('Goalkeepers', 'Vorm', 'Swansea', '19', '£5.0'),
 ('Goalkeepers', 'Stekelenburg', 'Fulham', '6', '£4.9'),
 ('Goalkeepers', 'Pantilimon', 'Man City', '0', '£4.9'),
 ('Goalkeepers', 'Lindegaard', 'Man Utd', '0', '£4.9'),
 ('Goalkeepers', 'Butland', 'Stoke City', '0', '£4.9'),
 ('Goalkeepers', 'Foster', 'West Brom', '13', '£4.9'),
 ('Goalkeepers', 'Viviano', 'Arsenal', '0', '£4.8'),
 ('Goalkeepers', 'Schwarzer', 'Chelsea', '0', '£4.7'),
 ('Goalkeepers', 'Boruc', 'Southampton', '42', '£4.7'),
 ('Goalkeepers', 'Myhill', 'West Brom', '15', '£4.5'),
 ('Goalkeepers', 'Fabianski', 'Arsenal', '0', '£4.4'),
 ('Goalkeepers', 'Gomes', 'Tottenham', '0', '£4.4'),
 ('Goalkeepers', 'Friedel', 'Tottenham', '0', '£4.4'),
 ('Goalkeepers', 'Henderson', 'West Ham', '0', '£4.0'),
 ('Defenders', 'Baines', 'Everton', '43', '£7.7'),
 ('Defenders', 'Vertonghen', 'Tottenham', '34', '£7.0'),
 ('Defenders', 'Taylor', 'Cardiff City', '14', '£4.5'),
 ('Defenders', 'Zverotic', 'Fulham', '0', '£4.5'),
 ('Defenders', 'Davies', 'Hull City', '28', '£4.5'),
 ('Defenders', 'Flanagan', 'Liverpool', '0', '£4.5'),
 ('Defenders', 'Dawson', 'West Brom', '0', '£3.9'),
 ('Defenders', 'Potts', 'West Ham', '0', '£3.9'),
 ('Defenders', 'Spence', 'West Ham', '0', '£3.9'),
 ('Midfielders', 'Özil', 'Arsenal', '24', '£10.6'),
 ('Midfielders', 'Redmond', 'Norwich', '20', '£5.0'),
 ('Midfielders', 'Mavrias', 'Sunderland', '5', '£5.0'),
 ('Midfielders', 'Gera', 'West Brom', '0', '£5.0'),
 ('Midfielders', 'Essien', 'Chelsea', '0', '£4.9'),
 ('Midfielders', 'Brown', 'West Brom', '0', '£4.3'),
 ('Forwards', 'van Persie', 'Man Utd', '24', '£13.9'),
 ('Forwards', 'Cornelius', 'Cardiff City', '1', '£5.4'),
 ('Forwards', 'Elmander', 'Norwich', '7', '£5.4'),
 ('Forwards', 'Murray', 'Crystal Palace', '0', '£5.3'),
 ('Forwards', 'Vydra', 'West Brom', '2', '£5.3'),
 ('Forwards', 'Proschwitz', 'Hull City', '0', '£4.3')]

用Python解析HTML文件

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