How do I query XHTML using python? - python

I have created a simple test harness in python for my ASP .net web site.
I would like to look up some HTML tags in the resulting page to find certain values.\
What would be the best way of doing this in python?
eg (returned page):
<div id="ErrorPanel">An error occurred......</div>
would display (in std out from python):
Error: .....
or
<td id="dob">23/3/1985</td>
would display:
Date of birth: 23/3/1985

Do you want to parse XML, as you state in your question's title, or HTML, as you show in the text of the question? For the latter, I recommend BeautifulSoup -- download it and install it, then, once having made a soup object out of the HTML, you can easily locate the tag with a certain id (or other attribute), e.g.:
errp = soup.find(attrs={'id': 'ErrorPanel'})
if errp is not None:
print 'Error:', errp.string
and similarly for the other case (easily tweakable e.g. into a loop if you're looking for non-unique attributes, and so on).

You can also do it with lxml. It handles HTML very well, and you can use CSS selectors for querying DOM, which makes it particularly attractive if you use libraries like jQuery regularly.

Related

Python web scraping: websites from google search result

A newbie to Python here. I want to extract info from multiple websites (e.g. 100+) from a google search page. I just want to extract the key info, e.g. those with <h1>, <h2> or <b> or <li> HTML tags etc. But I don't want to extract the entire paragraph <p>.
I know how to gather a list of website URLs from that google search; and I know how to web scrape individual website after looking at the page's HTML. I use the Request and BeautifulSoup for these tasks.
However, I want to know how can I extract key info from all these (100+ !) websites without having to look at their html one by one. Is there a way to automatically find out the HTML tags the website used to emphasize key messages? e.g. some websites may use <h1>, while some may use <b> , or something else...
All I can think of is to come up with a list of possible "emphasis-typed" HTML tags and then just use BeautifulSoup.find_all() to do a wide-scale extraction. But surely there must be an easier way?
It would seem that you must first learn how to do loops and function first. Every website is completely different and scraping a website alone to extract useful information is daunting. I'm a newb myself, but if I have to extract info from headers like you, this is what I would do: (this is just concept code, but hope you'll find it useful)
def getLinks(articleUrl):
html = urlopen('http://en.web.com{}'.format(articleUrl))
bs = BeautifulSoup(html, 'html.parser')
return bs.find('h1', {'class':'header'}).find_all('h1',
header=re.compile('^(/web/)((?!:).)*$'))

Extract text from HTML faster than NLTK?

We use NLTK to extract text from HTML pages, but we want only most trivial text analysis, e.g. word count.
Is there a faster way to extract visible text from HTML using Python?
Understanding HTML (and ideally CSS) at some minimal level, like visible / invisible nodes, images' alt texts, etc, would be additionally great.
Ran into the same problem at my previous workplace. You'll want to check out beautifulsoup.
from bs4 import BeautifulSoup
soup = BeautifulSoup(html)
print soup.text
You'll find its documentation here: https://www.crummy.com/software/BeautifulSoup/bs4/doc/
You can ignore elements based on attributes. As to understanding external stylesheets im not too sure. However what you could do there and something that would not be too slow (depending on the page) is to look into rendering the page with something like phantomjs and then selecting the rendered text :)

Python lxml XPath with deep nesting with specific search

The xpath for text I wish to extract is reliably located deep in the tree at
...table/tbody/tr[4]/td[2]
Specifically, td[2] is structured like so
<td class="val">xyz</td>
I am trying to extract the text "xyz", but a broad search returns multiple results. For example the following path returns 10 elements.
xpath('//td[#class="val"]')
... while a specific search doesn't return any elements. I am unsure why the following returns nothing.
xpath('//tbody/tr/td[#class="val"]')
One solution involves..
table = root.xpath('//table[#class="123"]')
#going down the tree
xyz = table[0][3][1]
print vol.text
However, I am pretty sure this extremely brittle. I would appreciate it if someone could tell me how to construct an xpath search that would be both un-brittle and relatively cheap on resources
You haven't mentioned it explicitly, but if your target table and td tag classes are reliable then you could do something like:
//table[#class="123"]/descendant::td[#class="val"]
And you half dodge the issue of tbody being there or not.
However, there's no substitute for actually seeing the material you are trying to parse for recommending XPATH queries...
...table/tbody/tr[4]/td[2]
I guess you found this XPath via a tool like Firebug. One thing to note about tools like Firebug (or other inspect tools within browsers) is that they use the DOM tree generated by the browser itself and most (if not all) HTML parsers in browsers would try hard to make the passed HTML valid. This often requires adding various tags the standard dictates.
<tbody> is one of these tags. <tr> tags are only allowed as a child of <thead>, <tbody> or <tfoot> tags. Unfortunately, in my experience, you will rarely see one of these tags inside a <table> in the actual source, but a browser would add these necessary tags while parsing to make HTML valid since standard requires to do so.
To cut this story short, there is probably no <tbody> tag in your actual source. That is why your XPath returns nothing.
As for generating XPath queries, this highly depends on the particular page/xml. In general, positional queries such as td[4] should be the last resort since they tend to break easily when something is added before them. You should inspect the markup carefully and try to come up queries that use attributes like id or class since they add specificity more reliably than the positional ones. But in the end, it all boils down to the specifics of the page in question.
This seems to be working
from lxml import etree
doc = etree.HTML('<html><body><table><tbody><tr><td>bad</td><td class="val">xyz</td></tr></tbody></table></body></html>')
print doc.xpath('//tbody/tr/td[#class="val"]')[0].text
output:
xyz
So what is your problem?

Parsing HTML with XPath, Python and Scrapy

I am writing a Scrapy program to extract the data.
This is the url, and I want to scrape 20111028013117 (code) information. I have taken XPath from FireFox add-on XPather. This is the path:
/html/body/p/table/tbody/tr/td/table[2]/tbody/tr[1]/td/table[3]/tbody/tr/td[2]/table[1]/tbody/tr/td/table/tbody/tr/td[2]/table[3]/tbody/tr/td/table/tbody/tr[2]/td[2]
While I am trying to execute this
try:
temp_list = hxs.select("/html/body/p/table/tbody/tr/td/table[2]/tbody/tr[1]/td/table[3]/tbody/tr/td[2]/table[1]/tbody/tr/td/table/tbody/tr/td[2]/table[3]/tbody/tr/td/table/tbody/tr[2]/td[2]").extract()
print "temp_list:" + str(temp_list)
except:
print "error"
It returns an empty list, I am struggling to find out an answer for this from the last 4 hours. I am a newbie to scrapy eventhough I handled issues very well for other projects, but it seems to be a bit difficult.
The reason of why your xpath doesn't work is becuase of tbody. You have to remove it and check if you get that result that you want.
You can read this in scrapy documentation: http://doc.scrapy.org/en/0.14/topics/firefox.html
Firefox, in particular, is known for adding <tbody> elements to
tables. Scrapy, on the other hand, does not modify the original page
HTML, so you won’t be able to extract any data if you use <tbody> in
your XPath expressions.
I see that the element you are hunting for is inside a <table>.
Firefox adds tbody tag for every table, even if it does not exists in source HTML code.
That's might be the reason, that your xpath query works in the browser, but fails in Scrapy.
As suggested, use other anchors in your xpath query.
You can extract data with more ease using more robust XPaths instead of taking the direct output from XPather.
For the data you are matching, this XPath would do a lot better:
//font[contains(text(),'Code')]/parent::td/following-sibling::td/font/text()
This will match the <font> tag containing "Code", then go to the td tag above it and select the next td -> font, which contains the code you are looking for.
Have you tried removing a few node tags at the end of the query, and re-running until you get a result? Do this several times until you get something, then add items back in cautiously until the query is rectified.
Also, check that your target page validates as XHTML - an invalid page would probably upset the parser.

Counting content only in HTML page

Is there anyway I can parse a website by just viewing the content as displayed to the user in his browser? That is, instead of downloading "page.htm"l and starting to parse the whole page with all the HTML/javascript tags, I will be able to retrieve the version as displayed to users in their browsers. I would like to "crawl" websites and rank them according to keywords popularity (viewing the HTML source version is problematic for that purpose).
Thanks!
Joel
A browser also downloads the page.html and then renders it. You should work the same way. Use a html parser like lxml.html or BeautifulSoup, using those you can ask for only the text enclosed within tags (and arguments you do like, like title and alt attributes).
You could get the source and strip the tags out, leaving only non-tag text, which works for almost all pages, except those where JavaScript-generated content is essential.
The pyparsing wiki Examples page includes this html tag stripper.

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