I was recently requested by a client to build a website for their insurance business. As part of this, they want to do some screen scraping of the quote site for one of their providers. They asked if their was an API to do this, and were told there wasn't one, but that if they could get the data from their engine they could use it as they wanted to.
My question: is it even possible to perform screen scraping on the response to a form submission to another site? If so, what are the gotchas that I should look out for. Obvious legal/ethical issues aside since they already asked for permission to do what we're planning to do.
As an aside, I would prefer to do any processing in python.
Thanks
A really nice library for screen-scraping is mechanize, which I believe is a clone of an original library written in Perl. Anyway, that in combination with the ClientForm module, and some additional help from either BeautifulSoup and you should be away.
I've written loads of screen-scraping code in Python and these modules turned out to be the most useful. Most of the stuff that mechanize does could in theory be done by simply using the urllib2 or httplib modules from the standard library, but mechanize makes this stuff a breeze: essentially it gives you a programmatic browser (note, it does not require a browser to work, but mearly provides you with an API that behaves like a completely customisable browser).
For post-processing, I've had a lot of success with BeautifulSoup, but lxml.html is a good choice too.
Basically, you will be able to do this in Python for sure, and your results should be really good with the range of tools out there.
You can pass a data parameter to urllib.urlopen to send POST data with the request just like you had filled out the form. You'll obviously have to take a look at what data exactly the form contains.
Also, if the form has method="GET", the request data is just part of the url given to urlopen.
Pretty much standard for scraping the returned HTML data is BeautifulSoup.
I see the other two answers already mention all the major libraries of choice for the purpose... as long as the site being scraped does not make extensive use of Javascript, that is. If it IS a Javascript-heavy site and dependent on JS for the data it fetches and display (e.g. via AJAX) your problem is an order of magnitude harder; in that case, I might suggest starting with crowbar, some customization of diggstripper, or selenium, etc.
You'll have to do substantial work in Javascript and probably dedicated work to deal with the specifics of the (hypothetically JS-heavy) site in question, depending on the JS frameworks it uses, etc; that's why the job is so much harder if that is the case. But in any case you might end up with (at least in part) local HTML copies of the site's pages as displayed, and end by scraping those copies with the other tools already recommended. Good luck: may the sites you scrape always be Javascript-light!-)
Others have recommended BeautifulSoup, but it's much better to use lxml. Despite its name, it is also for parsing and scraping HTML. It's much, much faster than BeautifulSoup, and it even handles "broken" HTML better than BeautifulSoup (their claim to fame). It has a compatibility API for BeautifulSoup too if you don't want to learn the lxml API.
Ian Blicking agrees.
There's no reason to use BeautifulSoup anymore, unless you're on Google App Engine or something where anything not purely Python isn't allowed.
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I wanted to do this before for some websites but didn't know where to start. This time however I am adamant. I am talking about the scripts where we crawl a website and extract the data we require. My target is this: Basically I have to appear for job interviews in December. There is this site (http://www.geeksforgeeks.org/) which contains large number of questions from previous interviews (like http://www.geeksforgeeks.org/amazon-interview-set-42-on-campus/ & http://www.geeksforgeeks.org/adobe-interview-set-6-campus-mts-1/). Every title has word "set" and a number in it. It is quite cumbersome to keep track of what I have done and what not. So I want to extract questions from each of these pages and put them in a pdf with the title. How can I do this using curl, regex and Scrapy? I am intermediate in C/C++/Java and but have only beginner proficiency in Python. Any help is much appreciated. Also point me to any such scripts you such know of. I want to do this on my own. Just requires a starting point and some guidance. Thanks.
If you want just a starting point, try scrapy a screen-scraping library for python. I would recommend that you use the requests library for making requests. It's by far the simplest option (with no loss of power).
Also, don't try to parse html or xml with a regex. Just don't. Use one of the fine libraries available (beautifulsoup or lxml, or lxml with a beautifulsoup backend are the most popular, but there are others).
I'm fetching webpages with a bunch of javascript on it, and I'm interested in parsing through the javascript portion of the pages for certain relevant info. Right now I have the following code in Python/BeautifulSoup/regex:
scriptResults = soup('script',{'type' : 'text/javascript'})
which yields an array of scripts, of which I can use a for loop to search for text I'd like:
for script in scriptResults:
for block in script:
if *patterniwant* in block:
**extract pattern from line using regex**
(Text in asterisks is pseudocode, of course.)
I was wondering if there was a better way for me to just use regex to find the pattern in the soup itself, searching only through the scripts themselves? My implementation works, but it just seems really clunky so I wanted something more elegant and/or efficient and/or Pythonic.
Thanks in advance!
I lot of website have client side data in JSON format. I that case I would suggest to extract JSON part from JavaScirpt code and parse it using Python's json modules (e.g. json.json.loads ). As a result you will get standard dictionary object.
Another option is to check with your browser what sort of AJAX requests application makes. Quite often it also returns structured data in JSON.
I would also check if page has any structured data already available (e.g. OpenGraph, microformats, RDFa, RSS feeds). A lot of web sites include this to improve pages SEO and make it better integrating with social network sharing.
I am a social scientist and a complete newbie/noob when it comes to coding. I have searched through the other questions/tutorials but am unable to get the gist of how to crawl a news website targeting the comments section specifically. Ideally, I'd like to tell python to crawl a number of pages and return all the comments as a .txt file. I've tried
from bs4 import BeautifulSoup
import urllib2
url="http://www.xxxxxx.com"
and that's as far as I can go before I get an error message saying bs4 is not a module. I'd appreciate any kind of help on this, and please, if you decide to respond, DUMB IT DOWN for me!
I can run wget on terminal and get all kinds of text from websites which is awesome IF I could actually figure out how to save the individual output html files into one big .txt file. I will take a response to either question.
Try Scrapy. It is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing.
You will most likely encounter this as you go, but in some cases, if the site is employing 3rd party services for comments, like Disqus, you will find that you will not be able to pull the comments down in this manner. Just a heads up.
I've gone down this route before and have had to tailor the script to a particular site's layout/design/etc.
I've found libcurl to be extremely handy, if you don't mind doing the post-processing using Python's string handler functions.
If you don't need to implement it purely in Python, you can make use of wget's recursive mirroring option to handle the content pull, then write your python code to parse the downloaded files.
I'll add my two cents here as well.
The first things to check are that you installed beautiful soup, and that it lives somewhere that it can be found. There's all kinds of things that can go wrong here.
My experience is similar to yours: I work at a web startup, and we have a bunch of users who register, but give us no information about their job (which is actually important for us). So my idea was to scrape the homepage and the "About us" page from the domain in their email address, and try to put a learning algorithm around the data that I captured to predict their job. The results for each domain are stored as a text file.
Unfortunately (for you...sorry), the code I ended up with was a bit complicated. The problem is that you'll end up getting a lot of garbage when you do the scraping, and you'll have to filter it out. You'll also end up with encoding issues, and (assuming you want to do some learning here) you'll have to get rid of low-value words. The total code is about 1000 lines, and I'll post some important pieces that may help you out here, if you're interested.
I am working with Python 3.x
I want to extract text from several webpages. What is a good library to allow me do just that?
Thanks,
Barry.
http://www.crummy.com/software/BeautifulSoup/
and the documentation to get you started
http://www.crummy.com/software/BeautifulSoup/documentation.html
mechanize is good library but unfortunately not ready for python 3, but you can take a look at lxml.html
I would suggest using Beautiful Soup and than it's just a matter of going through the returned structure for anything similar to an email address.
You could also just use urllib2 for this but Beautiful Soup takes care of a lot of syntax issues for you.
You don't say what you want to do with the extracted text, and that makes a big difference in how much effort you are willing to go to in order to get it out.
If you are trying to get the body text of a web page minus all of the site-related cruft (a nontrivial task), take a look at boilerpipe. It is written in Java, but it does an amazingly good job at getting essential text out of random web pages.
One of my hobbies over the next few weeks is recreating the core logic of boilerpipe in Python. We need the functionality it provides for a project, but don't want to haul the 10-ton rock that is the JVM around with it. I'm pretty certain we will be releasing it once it is fairly stable.
I keep getting mismatched tag errors all over the place. I'm not sure why exactly, it's the text on craigslist homepage which looks fine to me, but I haven't skimmed it thoroughly enough. Is there perhaps something more forgiving I could use or is this my best bet for html parsing with the standard library?
The mismatched tag errors are likely caused by mismatched tags. Browsers are famous for accepting sloppy html, and have made it easy for web page coders to write badly formed html, so there's a lot of it. THere's no reason to believe that creagslist should be immune to bad web page designers.
You need to use a grammar that allows for these mismatches. If the parser you are using won't let you redefine the grammar appropriately, you are stuck. (There may be a better Python library for this, but I don't know it).
One alternative is to run the web page through a tool like Tidy that cleans up such mismatches, and then run your parser on that.
The best library for parsing unpredictable HTML is BeautifulSoup. Here's a quote from the project page:
You didn't write that awful page.
You're just trying to get some data
out of it. Right now, you don't really
care what HTML is supposed to look
like.
Neither does this parser.
However it isn't well-supported for Python 3, there's more information about this at the end of the link.
Parsing HTML is not an easy problem, using libraries are definitely the solution here. The two common libraries for parsing HTML that isn't well formed are BeautifulSup and lxml.
lxml supports Python 3, and it's HTML parser handles unpredictable HTML well. It's awesome and fast as well as it uses c-libraries in the bottom. I highly recommend it.
BeautifulSoup 3.1 supports Python 3, but is also deemed a failed experiment" and you are told not to use it, so in practice BeautifulSoup doesn't support Python 3 yet, leaving lxml as the only alternative.