Jigsaw Data Scraping

Thursday, 11 December 2014

Scraping Webmaster Tools with FMiner

The biggest problem (after the problem with their data quality) I am having with Google Webmaster Tools is that you can’t export all the data for external analysis. Luckily the guys from the FMiner.com web scraping tool contacted me a few weeks ago to test their tool. The problem with Webmaster Tools is that you can’t use web based scrapers and all the other screen scraping software tools were not that good in the steps you need to take to get to the data within Webmaster Tools. The software is available for Windows and Mac OSX users.

FMiner is a classical screen scraping app, installed on your desktop. Since you need to emulate real browser behaviour, you need to install it on your desktop. There is no coding required and their interface is visual based which makes it possible to start scraping within minutes. Another possibility I like is to upload a set of keywords, to scrape internal search engine result pages for example, something that is missing in a lot of other tools. If you need to scrape a lot of accounts, this tool provides multi-browser crawling which decreases the time needed.

This tool can be used for a lot of scraping jobs, including Google SERPs, Facebook Graph search, downloading files & images and collecting e-mail addresses. And for the real heavy scrapers, they also have built in a captcha solving API system so if you want to pass captchas while scraping, no problem.

Below you can find an introduction to the tool, with one of their tutorial video’s about scraping IMDB.com:

More basic and advanced tutorials can be found on their website: Fminer tutorials. Their tutorials show you a range of simple and complex tasks and how to use their software to get the data you need.

Guide for Scraping Webmaster Tools data

The software is capable of dealing with JavaScript and AJAX, one of the main requirements to scrape data from within Google Webmaster Tools.

Step 1: The first challenge is to login into webmaster tools. After opening a new project, first browse to https://www.google.com/webmasters/ and select the Recording button in the upper left corner.

fminer01

After browsing to this page, a goto action appears in the left panel. Click on this button and look for the “Action Options” button at the bottom of that panel. Tick the option Clear cookies before do it to avoid problems if you are already logged in for example.

fminer06

Step 2: Click the “Sign in Webmaster Tools” button. You will notice the Macro designer overview on the left registered a click as the first step.

fminer03

Step 3: Fill in your Google username and password. In the designer panel you will see the two Fill actions emerging.

fminer04

Step 4: After this step you should add some waiting time to be sure everything is fully loaded. Use the second button on the right side above the Macro Designer panel to add an action. 2000 milliseconds (2 seconds :)) will do the job.

fminer07

fminer08

Step 5: Browse to the account of which you want to export the data from

fminer05

Step 6: Browse to the specific pages of which you want the data scraped

fminer09

Step 7:Scrape the data from the tables as shown in the video

Congratulations, now you are able to scrape data from Google Webmaster Tools :)

Step 8: One of the things I use it for is pulling the search query data per keyword, which you normally can’t export. To do that, you have to use a right mouse click on the keyword, which opens a menu with options. Go to open links recursively and select normal. This will loop through all the keywords.

fminer10

Step 9: This video will show you how to make use of the pagination elements to loop through all the pages:

You can also download the following file, which has a predefined set of actions to login in WMT and download the keywords, impressions and clicks: google_webmaster_tools_login.fmpx. Open the file and update the login details by clicking on those action buttons and insert your own Google account details.

Automating and scheduling scrapers

For people that want to automate and regularly download the data, you can setup a Scheduler config and within the project settings you can setup the program to send an e-mail after completion of the crawl:

Source: http://www.notprovided.eu/scraping-webmaster-tools-fminer/

Monday, 8 December 2014

Web scraping tutorial

There are three ways to access a website data. One is through a browser, the other is using a API (if the site provides one) and the last by parsing the web pages through code. The last one also known as Web Scraping is a technique of extracting information from websites using specially coded programs.

In this post we will take a quick look at writing a simple scraperusing the simplehtmldom library. But before we continue a word of caution:

Writing screen scrapers and spiders that consume large amounts of bandwidth, guess passwords, grab information from a site and use it somewhere else may well be a violation of someone’s rights and will eventually land you in trouble. Before writing a screen scraper first see if the website offers an RSS feed or an API for the data you are looking. If not and you have to use a scraper, first check the websites policies regarding automated tools before proceeding.

Now that we have got all the legalities out of the way, lets start with the examples.

1. Installing simplehtmldom.

Simplehtmldom is a PHP library that facilitates the process of creating web scrapers. It is a HTML DOM parser written in PHP5 that let you manipulate HTML in a quick and easy way. It is a wonderful library that does away with the messy details of regular expressions and uses CSS selector style DOM access like those found in jQuery.

First download the library from sourceforge. Unzip the library in you PHP includes directory or a directory where you will be testing the code.

Writing our first scraper.

Now that we are ready with the tools, lets write our first web scraper. For our initial idea let us see how to grab the sponsored links section from a google search page.

There are three ways to access a website data. One is through a browser, the other is using a API (if the site provides one) and the last by parsing the web pages through code. The last one also known as Web Scraping is a technique of extracting information from websites using specially coded programs.

In this post we will take a quick look at writing a simple scraperusing the simplehtmldom library. But before we continue a word of caution:

Writing screen scrapers and spiders that consume large amounts of bandwidth, guess passwords, grab information from a site and use it somewhere else may well be a violation of someone’s rights and will eventually land you in trouble. Before writing a screen scraper first see if the website offers an RSS feed or an API for the data you are looking. If not and you have to use a scraper, first check the websites policies regarding automated tools before proceeding.

Source: http://www.codediesel.com/php/web-scraping-in-php-tutorial/

Thursday, 11 September 2014

Web Data Extraction / Scraping Data from Kitco Inc. Text Only Market Page

I wish to capture data from

<html>
<head>
<title>Text Only Market Page</title>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
</head>

<body bgcolor="#FFFFFF">
<br><br>
<pre>
<b><font size=6>
Kitco Inc.

Text Only Market Page</font></b>

    <a href="http://www.kitco.com/market/">Graphic version of this page</a>

    <a href="http://www.kitco.com/market/LFrate.html">Precious Metals Lease Rates</a>
    <a href="http://www.kitco.com/gold.londonfix.html">Historical Price Data</a>
    <a href="http://www.kitco.com/market/marketnews.html">Precious Metals News Headlines</a>

    <font size=4><b><a href="https://online.kitco.com/bullion/completelist_USD.html#gold">Buy gold and silver online direct from Kitco!</a>
   Live quotes for all bullion products.</b></font>

   --------------------------------------------------------------------------------
   London Fix          GOLD          SILVER       PLATINUM           PALLADIUM
                   AM       PM                  AM       PM         AM       PM
   --------------------------------------------------------------------------------
   Jun 19,2012   1628.50   1625.50   28.8100   1486.00   1486.00   629.00   634.00
   Jun 18,2012   1623.50   1615.50   28.4300   1486.00   1484.00   626.00   628.00
   --------------------------------------------------------------------------------

                  New York Spot Price
                MARKET IS OPEN
            Will close in 4 hour 25 minutes
   ----------------------------------------------------------------------
   Metals          Bid        Ask           Change        Low       High
   ----------------------------------------------------------------------
   Gold         1619.80     1620.80     -8.90 -0.55%    1616.60 1632.70
   Silver         28.46       28.56     -0.28 -0.97%      28.24    28.95
   Platinum     1479.00     1489.00      0.00   0.00%    1476.00 1500.00
   Palladium     627.00      632.00      0.00   0.00%     622.00   639.00
   ----------------------------------------------------------------------
   Last Update on Jun 19, 2012 at 12:50.59
   ----------------------------------------------------------------------

                Asia / Europe Spot Price
                MARKET IS OPEN
            Will close in 4 hours 25 minutes
   ----------------------------------------------------------------------
   Metals                      Bid          Ask      Change from NY close
   ----------------------------------------------------------------------
   Gold                      1619.80      1620.80     -8.90   -0.55%
   Silver                      28.46        28.56     -0.28   -0.97%
   Platinum                  1479.00      1489.00     +0.00   +0.00%
   Palladium                  627.00       632.00     +0.00   +0.00%
   ----------------------------------------------------------------------
   Last Update on Jun 19, 2012 at 12:50.59
   ----------------------------------------------------------------------

<b>   File created on Tue Jun 19 12:51:04 2012</b>

        <style type="text/css"></style>
<table border="0" cellspacing="0" cellpadding="0"><tr><td>
<div id="main_container_footer">
        <div id="footer_container">
            <ul>
                <li class="no_border"><script type="text/javascript">
copyright=new Date();
update=copyright.getFullYear();
document.write("© "+ update + " Kitco Metals Inc.");
</script></li>
                <li><a href="https://corp.kitco.com/index.html">About Us</a></li>
                <li><a href="http://www.kitco.com/TermsofUse/" target="_top" onclick="Window_open(this.href,'KITCO','top=120,left=250,width=500,height=350'); return false">Website Terms of Use</a></li>
                <li><a href="https://online.kitco.com/help/privacy_policy.html" target="_top" onclick="Window_open(this.href,'KITCO','top=120,left=250,width=500,height=350'); return false">Privacy Policy</a></li>
                <li><a href="http://www.kitco.com/ads/">Advertise With Us</a></li>
                <li><a href="https://corp.kitco.com/en/corporate_culture.html">Careers</a></li>
                <li><a href="https://corp.kitco.com/en/contact.html" target="_top" onclick="Window_open(this.href,'KITCO','top=120,left=250,width=500,height=350'); return false">Contact Us</a></li>
                <li class="no_border"><a href="https://corp.kitco.com/en/feedback.html" target="_top" onclick="Window_open(this.href,'KITCO','top=120,left=250,width=500,height=350'); return false">Feedback</a></li>
            </ul>
        </div>
    </div>

    </td></tr></table><br /><br />
<script language="JavaScript" type="text/javascript">

</script>


<script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-4074364-3']);
_gaq.push(['_trackPageview']);

(function() {
    var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
    ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
    var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
</body>
</html>

More specifically, I am looking to capture the following data:

--------------------------------------------------------------------------------
London Fix          GOLD          SILVER       PLATINUM           PALLADIUM
               AM       PM                  AM       PM         AM       PM
--------------------------------------------------------------------------------
Jun 19,2012   1628.50   NA        28.8100   1486.00   1486.00   629.00   634.00
Jun 18,2012   1623.50   1615.50   28.4300   1486.00   1484.00   626.00   628.00
--------------------------------------------------------------------------------

Does anybody have any suggestions how I can do this using PHP?

1 Answer

Quick and dirty regex method:

$data = file_get_contents('http://www.kitco.com/texten/texten.html');
preg_match_all('/([A-Z]{3,5}\s+[0-9]{1,2},[0-9]{4}\s+([0-9.NA]{2,10}\s+){1,7})/si',$data,$result);

$records = array();
foreach($result[1] as $date) {
    $temp = preg_split('/\s+/',$date);
    $index = array_shift($temp);
    $index.= array_shift($temp);
    $records[$index] = implode(',',$temp);
}
print_R($records);

Note, you'd probably want to add some validation, etc.

Source: http://stackoverflow.com/questions/11103001/web-data-extraction-scraping-data-from-kitco-inc-text-only-market-page

Monday, 8 September 2014

Scraping webdata from a website that loads data in a streaming fashion

I'm trying to scrape some data off of the FEC.gov website using python for a project of mine. Normally I use python

mechanize and beautifulsoup to do the scraping.

I've been able to figure out most of the issues but can't seem to get around a problem. It seems like the data is

streamed into the table and mechanize.Browser() just stops listening.

So here's the issue: If you visit http://query.nictusa.com/cgi-bin/can_ind/2011_P80003338/1/A ... you get the first 500

contributors whose last name starts with A and have given money to candidate P80003338 ... however, if you use

browser.open() at that url all you get is the first ~5 rows.

I'm guessing its because mechanize isn't letting the page fully load before the .read() is executed. I tried putting a

time.sleep(10) between the .open() and .read() but that didn't make much difference.

And I checked, there's no javascript or AJAX in the website (or at least none are visible when you use the 'view-

source'). SO I don't think its a javascript issue.

Any thoughts or suggestions? I could use selenium or something similar but that's something that I'm trying to avoid.

-Will

2 Answers

Why not use an html parser like lxml with xpath expressions.

I tried

>>> import lxml.html as lh
>>> data = lh.parse('http://query.nictusa.com/cgi-bin/can_ind/2011_P80003338/1/A')
>>> name = data.xpath('/html/body/table[2]/tr[5]/td[1]/a/text()')
>>> name
[' AABY, TRYGVE']
>>> name = data.xpath('//table[2]/*/td[1]/a/text()')
>>> len(name)
500
>>> name[499]
' AHMED, ASHFAQ'
>>>

Similarly, you can create xpath expression of your choice to work with.

Source: http://stackoverflow.com/questions/9435512/scraping-webdata-from-a-website-that-loads-data-in-a-streaming-

fashion

How can I circumvent page view limits when scraping web data using Python?

I am using Python to scrape US postal code population data from http:/www.city-data.com, through this directory: http://www.city-data.com/zipDir.html. The specific pages I am trying to scrape are individual postal code pages with URLs like this: http://www.city-data.com/zips/01001.html. All of the individual zip code pages I need to access have this same URL Format, so my script simply does the following for postal_code in range:

    Creates URL given postal code
    Tries to get response from URL
    If (2), Check the HTTP of that URL
    If HTTP is 200, retrieves the HTML and scrapes the data into a list
    If HTTP is not 200, pass and count error (not a valid postal code/URL)
    If no response from URL because of error, pass that postal code and count error
    At end of script, print counter variables and timestamp

The problem is that I run the script and it works fine for ~500 postal codes, then suddenly stops working and returns repeated timeout errors. My suspicion is that the site's server is limiting the page views coming from my IP address, preventing me from completing the amount of scraping that I need to do (all 100,000 potential postal codes).

My question is as follows: Is there a way to confuse the site's server, for example using a proxy of some kind, so that it will not limit my page views and I can scrape all of the data I need?

Thanks for the help! Here is the code:

##POSTAL CODE POPULATION SCRAPER##

import requests

import re

import datetime

def zip_population_scrape():

    """
    This script will scrape population data for postal codes in range
    from city-data.com.
    """
    postal_code_data = [['zip','population']] #list for storing scraped data

    #Counters for keeping track:
    total_scraped = 0
    total_invalid = 0
    errors = 0

    for postal_code in range(1001,5000):

        #This if statement is necessary because the postal code can't start
        #with 0 in order for the for statement to interate successfully
        if postal_code <10000:
            postal_code_string = str(0)+str(postal_code)
        else:
            postal_code_string = str(postal_code)

        #all postal code URLs have the same format on this site
        url = 'http://www.city-data.com/zips/' + postal_code_string + '.html'

        #try to get current URL
        try:
            response = requests.get(url, timeout = 5)
            http = response.status_code

            #print current for logging purposes
            print url +" - HTTP: " + str(http)

            #if valid webpage:
            if http == 200:

                #save html as text
                html = response.text

                #extra print statement for status updates
                print "HTML ready"

                #try to find two substrings in HTML text
                #add the substring in between them to list w/ postal code
                try:

                    found = re.search('population in 2011:</b> (.*)<br>', html).group(1)

                    #add to # scraped counter
                    total_scraped +=1

                    postal_code_data.append([postal_code_string,found])

                    #print statement for logging
                    print postal_code_string + ": " + str(found) + ". Data scrape successful. " + str(total_scraped) + " total zips scraped."
                #if substrings not found, try searching for others
                #and doing the same as above
                except AttributeError:
                    found = re.search('population in 2010:</b> (.*)<br>', html).group(1)

                    total_scraped +=1

                    postal_code_data.append([postal_code_string,found])
                    print postal_code_string + ": " + str(found) + ". Data scrape successful. " + str(total_scraped) + " total zips scraped."

            #if http =404, zip is not valid. Add to counter and print log
            elif http == 404:
                total_invalid +=1

                print postal_code_string + ": Not a valid zip code. " + str(total_invalid) + " total invalid zips."

            #other http codes: add to error counter and print log
            else:
                errors +=1

                print postal_code_string + ": HTTP Code Error. " + str(errors) + " total errors."

        #if get url fails by connnection error, add to error count & pass
        except requests.exceptions.ConnectionError:
            errors +=1
            print postal_code_string + ": Connection Error. " + str(errors) + " total errors."
            pass

        #if get url fails by timeout error, add to error count & pass
        except requests.exceptions.Timeout:
            errors +=1
            print postal_code_string + ": Timeout Error. " + str(errors) + " total errors."
            pass

    #print final log/counter data, along with timestamp finished
    now= datetime.datetime.now()
    print now.strftime("%Y-%m-%d %H:%M")
    print str(total_scraped) + " total zips scraped."
    print str(total_invalid) + " total unavailable zips."
    print str(errors) + " total errors."

Source: http://stackoverflow.com/questions/25452798/how-can-i-circumvent-page-view-limits-when-scraping-web-data-using-python

Sunday, 7 September 2014

Web data scraping (online news comments) with Scrapy (Python)

Since you seem like the try-first ask-question later type (that's a very good thing), I won't give you an answer, but a

(very detailed) guide on how to find the answer.

The thing is, unless you are a yahoo developer, you probably don't have access to the source code you're trying to

scrape. That is to say, you don't know exactly how the site is built and how your requests to it as a user are being

processed on the server-side. You can, however, investigate the client-side and try to emulate it. I like using Chrome

Developer Tools for this, but you can use others such as FF firebug.

So first off we need to figure out what's going on. So the way it works, is you click on the 'show comments' it loads

the first ten, then you need to keep clicking for the next ten comments each time. Notice, however, that all this

clicking isn't taking you to a different link, but lively fetches the comments, which is a very neat UI but for our

case requires a bit more work. I can tell two things right away:

    They're using javascript to load the comments (because I'm staying on the same page).
    They load them dynamically with AJAX calls each time you click (meaning instead of loading the comments with the

page and just showing them to you, with each click it does another request to the database).

Now let's right-click and inspect element on that button. It's actually just a simple span with text:

<span>View Comments (2077)</span>

By looking at that we still don't know how that's generated or what it does when clicked. Fine. Now, keeping the

devtools window open, let's click on it. This opened up the first ten. But in fact, a request was being made for us to

fetch them. A request that chrome devtools recorded. We look in the network tab of the devtools and see a lot of

confusing data. Wait, here's one that makes sense:

http://news.yahoo.com/_xhr/contentcomments/get_comments/?content_id=42f7f6e0-7bae-33d3-aa1d-

3dfc7fb5cdfc&_device=full&count=10&sortBy=highestRated&isNext=true&offset=20&pageNumber=2&_media.modules.content_commen

ts.switches._enable_view_others=1&_media.modules.content_comments.switches._enable_mutecommenter=1&enable_collapsed_com

ment=1

See? _xhr and then get_comments. That makes a lot of sense. Going to that link in the browser gave me a JSON object

(looks like a python dictionary) containing all the ten comments which that request fetched. Now that's the request you

need to emulate, because that's the one that gives you what you want. First let's translate this to some normal reqest

that a human can read:

go to this url: http://news.yahoo.com/_xhr/contentcomments/get_comments/
include these parameters: {'_device': 'full',
          '_media.modules.content_comments.switches._enable_mutecommenter': '1',
          '_media.modules.content_comments.switches._enable_view_others': '1',
          'content_id': '42f7f6e0-7bae-33d3-aa1d-3dfc7fb5cdfc',
          'count': '10',
          'enable_collapsed_comment': '1',
          'isNext': 'true',
          'offset': '20',
          'pageNumber': '2',
          'sortBy': 'highestRated'}

Now it's just a matter of trial-and-error. However, a few things to note here:

    Obviously the count is what decides how many comments you're getting. I tried changing it to 100 to see what

happens and got a bad request. And it was nice enough to tell me why - "Offset should be multiple of total rows". So

now we understand how to use offset

    The content_id is probably something that identifies the article you are reading. Meaning you need to fetch that

from the original page somehow. Try digging around a little, you'll find it.

    Also, you obviously don't want to fetch 10 comments at a time, so it's probably a good idea to find a way to fetch

the number of total comments somehow (either find out how the page gets it, or just fetch it from within the article

itself)

    Using the devtools you have access to all client-side scripts. So by digging you can find that that link to

/get_comments/ is kept within a javascript object named YUI. You can then try to understand how it is making the

request, and try to emulate that (though you can probably figure it out yourself)

    You might need to overcome some security measures. For example, you might need a session-key from the original

article before you can access the comments. This is used to prevent direct access to some parts of the sites. I won't

trouble you with the details, because it doesn't seem like a problem in this case, but you do need to be aware of it in

case it shows up.

    Finally, you'll have to parse the JSON object (python has excellent built-in tools for that) and then parse the

html comments you are getting (for which you might want to check out BeautifulSoup).

As you can see, this will require some work, but despite all I've written, it's not an extremely complicated task

either.

So don't panic.

It's just a matter of digging and digging until you find gold (also, having some basic WEB knowledge doesn't hurt).

Then, if you face a roadblock and really can't go any further, come back here to SO, and ask again. Someone will help

you.

Source: http://stackoverflow.com/questions/20218855/web-data-scraping-online-news-comments-with-scrapy-python

Saturday, 6 September 2014

A good web data extraction/screen scraper program?

I need to capture product data from a site on a regular basis and wondered if any one knows of a good software program? I've trialed Mozenda but its a monthly subscription and pricey in the long term. Obviously something thats free would be best but I don't mind paying either. Just need a decent program thats reliable and doesn't require much programming knowledge.

You can try ScraperWiki.com if you know python.

I've experimented with Screen-Scraper and found it easy to use. The application comes in multiple versions: basic (which is free), professional, and enterprise. Also, multiple platforms are supported.

Hire a programmer to do it so that there is only a one off cost. I often see similar projects on freelancing websites like Elance and oDesk.

I really like iMacros. You can give it a test drive to see if it meets your needs with the totally free Firefox extension (there's also IE versions), but there are also more full featured application and "server" versions that have more features and ability to do thing in an unattended manner.

Here are some other alternatives to consider:

    License the data from the provider. Call em up and ask 'em.

    Use Amazon Mechanical Turk to get humans to copy and paste and format it for ya. They are cheap.

    For automation, it depends on how complicated the HTML is and how often it changes. You could use Excel's Web Data Import if it's really simple.

You can use irobot from IRobotSoft, which is totally free, and provides more functionalityies than other paid software. Watch demos here http://irobotsoft.com/help/ for how simple it is.

Questions on their forum were answered very quickly.

Source: http://stackoverflow.com/questions/2334164/a-good-web-data-extraction-screen-scraper-program