Python - Unable to Retrieve Data From Webpage Table Using Beautiful Soup or lxml xpath

Question

I’m trying to retrieve data from the “Advanced Box Score Stats" from the following webpage: http://www.sports-reference.com/cbb/boxscores/2016-11-11-villanova.html

I tried using BeautifulSoup in a very broad way to retrieve all the tables:

import requests
from bs4 import BeautifulSoup

base_url = "http://www.sports-reference.com/cbb/boxscores/2016-11-11-villanova.html"
r = requests.get(base_url)
soup = BeautifulSoup(r.text, "html.parser")
tables = soup.find_all("table")
for table in tables:
       print table.get_text()

In doing so, it only retrieved the “Basic Box Score Stats”. However, it didn’t retrieve the “Advanced Box Score Stats” like I had hoped.

Next, I tried getting more specific by using the lxml path:

import requests
from lxml import html
page = requests.get('http://www.sports-reference.com/cbb/boxscores/2016-11-11-villanova.html')
tree = html.fromstring(page.content)
boxscore_Advanced = tree.xpath('//*[@id="box-score-advanced-lafayette"]/tbody/tr[1]/td[1]/text()’)
print boxscore_Advanced

In doing so, it returned an empty list.

I've been struggling with this for a good amount of time, and have tried to solve this problem by using the following posts:

Thank you in advance for any and all help!

Have you checked that the table is actually in the html, and not being added to the page by javascript later? — snakecharmerb, Jan 09 '17 at 19:32
I don't believe I did. How can I do that? (P.S. thank you for the speedy response @snakecharmerb !) — nreit10, Jan 09 '17 at 19:55

score 4 · Accepted Answer · answered Jan 09 '17 at 20:44

There is no need to use selenium and/or PhantomJS. The "Advanced Box Score Stats" tables are actually inside the HTML, they are just inside HTML comments. Parse them:

import requests
from bs4 import BeautifulSoup, Comment


url = "http://www.sports-reference.com/cbb/boxscores/2016-11-11-villanova.html"
response = requests.get(url)
soup = BeautifulSoup(response.content, "html.parser")

# find the comments containing the desired tables
tables = soup.find_all(text=lambda text: text and isinstance(text, Comment) and 'Advanced Box Score Stats' in text)

# we have 2 tables - one for an opponent team
for table in tables:
    table_soup = BeautifulSoup(table, "html.parser")
    advanced_table = table_soup.select_one("table[id^=box-score-advanced]")
    for row in advanced_table("tr")[2:]:  # skip headers
        print(row.th.get_text())
    print("-------")

Prints the player names from the first columns of the advanced tables:

Nick Lindner
Monty Boykins
Matt Klinewski
Paulius Zalys
Auston Evans
Reserves
Myles Cherry
Kyle Stout
Eric Stafford
Lukas Jarrett
Hunter Janacek
Jimmy Panzini
School Totals
-------
Kris Jenkins
Phil Booth
Josh Hart
Jalen Brunson
Darryl Reynolds
Reserves
Donte DiVincenzo
Mikal Bridges
Eric Paschall
Tim Delaney
Dylan Painter
Denny Grace
Tom Leibig
Matt Kennedy
School Totals
-------

I love absolutely this @alecxe! I really appreciate you taking the time to investigate this in detail, and thank you for this insight!! — nreit10, Jan 09 '17 at 21:32

score 2 · Answer 2 · answered Jan 09 '17 at 19:53

@snakecharmerb is on the right path: this table does not exist in the raw html and must be being added by Javascript at runtime.

Do this:

$ curl http://www.sports-reference.com/cbb/boxscores/2016-11-11-villanova.html | grep "box-score-advanced-lafayette"
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100  9891    0  9891    0     0  45371      0 --:--:-- --:--:-- --:--:-- 48965<div id="all_box-score-advanced-lafayette" class="table_wrapper setup_commented commented">
  <span class="section_anchor" id="box-score-advanced-lafayette_link" data-label="Advanced Box Score"></span>
      <div class="overthrow table_container" id="div_box-score-advanced-lafayette">
  <table class="sortable stats_table" id="box-score-advanced-lafayette" data-cols-to-freeze=1><caption>&nbsp; Table</caption>
100  141k    0  141k    0     0   349k      0 --:--:-- --:--:-- --:--:--  363k

You see from the output that all that exists in the html is the container that the table gets built in.

For scraping something like this, I recommend an approach like Phantom.js http://phantomjs.org

Thank you for that recommendation, Shane! After struggling with this for as long as I did, I can't begin to tell you how ecstatic I am to learn about Phantom.js — nreit10, Jan 09 '17 at 20:04

Python - Unable to Retrieve Data From Webpage Table Using Beautiful Soup or lxml xpath

2 Answers2