Have You Ever Heard To Web Scraping Expert Use Business Information?

Have you ever heard of "data scraping?" Scaling of the use of information and data scraping technology made his fortune many a successful trader is not new technology. Sometimes website owners automated harvesting of your data can not be happy with sitting

Fortunately there is a modern solution to this problem. Proxy data scraping technology solves the problem by using proxy IP addresses. Scraping data each time you run the program, organized the evacuation of a website, the website thinks that it comes from a different IP address. For website owners, worldwide only a short period of increased traffic from the proxy data scraping sounds.

Now you might be asking yourself: "Can the technology proxy data scraping project?" Certainly better than the choice is dangerous and unreliable (but) free public proxy servers.

There are literally thousands of the world that is quite easy to free proxy servers are all on. But the trick is finding them. Many sites list hundreds of servers, but open to find, and the protocol perseverance, trial and error, works for one of the first lessons you something about server to server, or do not know what activities are going for. A public proxy requests or sensitive data transmitted through a bad idea.

A less risky scenario for proxy data for scraping a rotating proxy connection goes through many private IP addresses to hire.

Scrape data from the software-only website is the proven process of extracting data from the Web. Offer the best of the web software to extract data. We have the expertise and knowledge in web data extraction, image, display, email extract, eliminate services, data mining and web intervene to eliminate.

For example, many companies based on their own needs, in particular, helped to find the data.

Data collection

Generally, data, information, automated computer programs for processing by the appropriate structures transmission. Such formats and protocols are usually strictly structured, well-documented, easily decompose, and confusion to a minimum. Very often, these transmissions are not human readable.

Tractor unit that automatically Extractor is an email from a reliable source that the e-mail ID helps to remove. This is fundamentally different than web pages, HTML files, text files or other format, business services contacts duplicate email addresses without.

A web spider is a computer program that a methodical, automated or surf the World Wide Web in a systematic way. Especially the many sites in the search engines, up-to-date information, as a means to quickly use.

Proxy data scraping technology solves the problem by using proxy IP addresses. Every time your data scraping program is a production of a website, the website that comes from a different IP address. The owner of this website, proxy data from around the world in an increase in traffic looks exactly like scraping the short term.

Now you might be asking yourself, "my project where I can get the data scraping proxy technology?" "Do it yourself" solution, but unfortunately, there is no need to call. Consider hosting the proxy server you choose to rent, but this option is quite pricey, but definitely better than the alternative is incredibly dangerous (but) free public proxy server.

Source:http://www.articlesbase.com/outsourcing-articles/have-you-ever-heard-to-web-scraping-expert-use-business-information-6250856.html

How To Access Information About PDF Data Scraping?

Scraping a way that the output of data from another program to extract data is used by a computer program can be heard. Simply put, this is a process of automatically sorting the information from the Internet, even within an HTML file can be found in various sources, including PDF documents and others. There is also a collection of relevant information. This information to the database or spreadsheet, allowing users to retrieve them later will be included.

Most websites today can be viewed and written text in the source code is simple. However, there are other companies that currently use Adobe PDF or Portable Document Format to choose from. This file is a type known as just the free Adobe Acrobat to be viewed using the software. Supports virtually all operating software, said. There are many advantages when you choose to create PDF files. Those document you just the same, even if you put it in another computer, so you can see it look. Therefore, business documents or completes the data sheet. Of course there are drawbacks. One of these is included in the text is converted into an image. In this case, it is often the problem with this is that when it comes to copy and paste, and could be.

That's why some are starting to scrape the information PDF. It is often said that the only scraping process information in your PDF file PDF is like to get data. PDF to start scraping the information from you, choose a device specially designed for this process must benefit. However, you feel that you have the right tools too effectively scrape PDF will be able to perform is not easy to detect. This is because the equipment is exactly the same data access without having personal problems.

However, if you look good, you look at programs that you may encounter. You have to know programming; you do not need to use them. You can easily specify their preferences for the software you use will do the rest. There are companies out there that you contact them and they work because they have the right tools they can use to be. If you choose to do things yourself, you will find it really difficult and complicated compared to professionals working for you, they will at no time possible. PDF scraping of information is a process whereby information can be found on the Internet and not copyright infringement to collect.

Well I hope you now understand how to scrape data in various forms. If you do not understand then go for one of the sites I mention below in the box of the author. We offer a variety of data services, such as HTML scraping services, the crop Scraping Web Services Web Content, Email Id scraping, scraping data ownership, data Linkedin scraping, scraping data Hotels, pharmaceutical Scraping data, Business Contact Scraping, Data Scraping For University etc. If you have any doubts, please feel free to ask us without hesitation. We will certainly be useful for you. Thank you.

Source:http://www.articlesbase.com/outsourcing-articles/how-to-access-information-about-pdf-data-scraping-5293692.html

Most Of The Recommended Web Scraping Data Into Business

More traditional Web search engines, websites visited, depending on how they were collected. The main disadvantage of these search engines is that they do not provide a method to extract the necessary information.

However, in modern times, the concept of scraping offs the website. Scraping all the relevant information and data contained in any web site can be found on the Internet together with the appearance.

Organizations and individuals to effectively and quickly recognized the need to gather information on the web scraping. Data structure that is more cut and paste can be accessed without having to contend with can not be collected.

If any other type of information to be able to arrange for the document. Traditional search engines use tools to harvest this website to a combination of individual clerks more sophisticated nuance with broad power. According to the criteria specified in the field of information is required.

News of the report on the software makes it easy for the crowd. The price and other analyzes to compare a pair of runs. Therefore, the Internet continues to work on the agencies that are required are a website as scrap. Web scraping by is the main reason for the growing number of companies.

Scraping the most reliable data Services Company based in India, offshore website provides information solutions to customers scraping. Data services to accomplish with your web search to try scraping, data mining, data conversion, data extraction, web scraping and web data in the data scraping.

Data Services are owned by scraping solution internet - India-based "Most of your trusted and reliable" service provider outsourcing. Data scraping Services offers high quality, accurate and manual internet scrape data and on the web scraping services at the lowest possible rate industry.

Data scraping Services is a firm based on the Indian expertise in outsourcing data entry, data processing, and Internet search and website scrape data. Data scraping Services offers great variety of data entry, data conversion, document scanning and data scraping service at the lowest possible rate industry since 2005. Services we offer cover the following areas; data entry, data mining, Web search, data conversion, data processing, scrape web sites, harvesting and collection of data internet email.

Data scraping Services follow the standard process to the highest quality Web search, data mining and web site services scratching. Search our website, data mining and data conversion projects to the process quality standards.

Most often the data must be scratched for the industry as part of lawyers, doctors, hospitals, students, schools, universities, chiropractor, dentists, hotels, property, real estate, pub, the bars, night club, a restaurant, and IT professionals. The most common medium to the database scraping and email numbers are directory business online, linked to, Twitter, Face book, social networking sites and search Google.

Data scraping service provider is the most trusted and reliable world of service, service of process data, data scrape, scrape data website, data mining, data extraction and business development database. We have already scraped some popular online business directories. We are only able to scrape public database available in any of the directory business.

Source:http://www.articlesbase.com/outsourcing-articles/most-of-the-recommended-web-scraping-data-into-business-5697814.html

Data Mining Explained

Overview

Data mining is the crucial process of extracting implicit and possibly useful information from data. It uses analytical and visualization techniques to explore and present information in a format which is easily understandable by humans.

Data mining is widely used in a variety of profiling practices, such as fraud detection, marketing research, surveys and scientific discovery.

In this article I will briefly explain some of the fundamentals and its applications in the real world.

Herein I will not discuss related processes of any sorts, including Data Extraction and Data Structuring.

The Effort

Data Mining has found its application in various fields such as financial institutions, health-care & bio-informatics, business intelligence, social networks data research and many more.

Businesses use it to understand consumer behavior, analyze buying patterns of clients and expand its marketing efforts. Banks and financial institutions use it to detect credit card frauds by recognizing the patterns involved in fake transactions.

The Knack

There is definitely a knack to Data Mining, as there is with any other field of web research activities. That is why it is referred as a craft rather than a science. A craft is the skilled practicing of an occupation.

One point I would like to make here is that data mining solutions offers an analytical perspective into the performance of a company depending on the historical data but one need to consider unknown external events and deceitful activities. On the flip side it is more critical especially for Regulatory bodies to forecast such activities in advance and take necessary measures to prevent such events in future.

In Closing

There are many important niches of Web Data Research that this article has not covered. But I hope that this article will provide you a stage to drill down further into this subject, if you want to do so!

Should you have any queries, please feel free to mail me. I would be pleased to answer each of your queries in detail.

Source: http://ezinearticles.com/?Data-Mining-Explained&id=4341782

Scraping table from html web with CloudStat

You need to use the data from internet, but don’t type, you can just extract or scrape them if you know the web URL.

Thanks to XML package from R. It provides amazing readHTMLtable() function.

For a study case,

I want to scrape data:

    US Airline Customer Score.
    World Top Chess Players (Men).

A. Scraping US Airline Customer Score table from

http://www.theacsi.org/index.php?option=com_content&view=article&id=147&catid=&Itemid=212&i=Airlines

Code:

airline = ‘http://www.theacsi.org/index.php?option=com_content&view=article&id=147&catid=&Itemid=212&i=Airlines’

airline.table = readHTMLTable(airline, header=T, which=1,stringsAsFactors=F)

Result:

B. Scraping World Top Chess players (Men) table from http://ratings.fide.com/top.phtml?list=men

Code:

chess = ‘http://ratings.fide.com/top.phtml?list=men’

chess.table = readHTMLTable(chess, header=T, which=5,stringsAsFactors=F)

Result:

Done. You had successfully scraping data from any web page with CloudStat.

You can get the full version of this study case (code and result) at Scraping table from html web.

Then, you can analyze as usual! Great! No more retype the data. Enjoy!

Source:http://www.r-bloggers.com/scraping-table-from-html-web-with-cloudstat/

Data Extraction - A Guideline to Use Scrapping Tools Effectively

So many people around the world do not have much knowledge about these scrapping tools. In their views, mining means extracting resources from the earth. In these internet technology days, the new mined resource is data. There are so many data mining software tools are available in the internet to extract specific data from the web. Every company in the world has been dealing with tons of data, managing and converting this data into a useful form is a real hectic work for them. If this right information is not available at the right time a company will lose valuable time to making strategic decisions on this accurate information.

This type of situation will break opportunities in the present competitive market. However, in these situations, the data extraction and data mining tools will help you to take the strategic decisions in right time to reach your goals in this competitive business. There are so many advantages with these tools that you can store customer information in a sequential manner, you can know the operations of your competitors, and also you can figure out your company performance. And it is a critical job to every company to have this information at fingertips when they need this information.

To survive in this competitive business world, this data extraction and data mining are critical in operations of the company. There is a powerful tool called Website scraper used in online digital mining. With this toll, you can filter the data in internet and retrieves the information for specific needs. This scrapping tool is used in various fields and types are numerous. Research, surveillance, and the harvesting of direct marketing leads is just a few ways the website scraper assists professionals in the workplace.

Screen scrapping tool is another tool which useful to extract the data from the web. This is much helpful when you work on the internet to mine data to your local hard disks. It provides a graphical interface allowing you to designate Universal Resource Locator, data elements to be extracted, and scripting logic to traverse pages and work with mined data. You can use this tool as periodical intervals. By using this tool, you can download the database in internet to you spread sheets. The important one in scrapping tools is Data mining software, it will extract the large amount of information from the web, and it will compare that date into a useful format. This tool is used in various sectors of business, especially, for those who are creating leads, budget establishing seeing the competitors charges and analysis the trends in online. With this tool, the information is gathered and immediately uses for your business needs.

Another best scrapping tool is e mailing scrapping tool, this tool crawls the public email addresses from various web sites. You can easily from a large mailing list with this tool. You can use these mailing lists to promote your product through online and proposals sending an offer for related business and many more to do. With this toll, you can find the targeted customers towards your product or potential business parents. This will allows you to expand your business in the online market.

There are so many well established and esteemed organizations are providing these features free of cost as the trial offer to customers. If you want permanent services, you need to pay nominal fees. You can download these services from their valuable web sites also.

Source: http://ezinearticles.com/?Data-Extraction---A-Guideline-to-Use-Scrapping-Tools-Effectively&id=3600918

Online Data Entry and Data Mining Services

Data entry job involves transcribing a particular type of data into some other form. It can be either online or offline. The input data may include printed documents like Application forms, survey forms, registration forms, handwritten documents etc.

Data entry process is an inevitable part of the job to any organization. One way or other each organization demands data entry. Data entry skills vary depends upon the nature of the job requirement, in some cases data to be entered from a hard copy formats and in some other cases data to be entered directly into a web portal. Online data entry job generally requires the data to be entered in to any online data base.

For a super market, data associate might be required to enter the goods which have sold in a particular day and the new goods received in a particular day to maintain the stock well in order. Also, by doing this the concerned authorities will get an idea about the sale particulars of each commodity as they requires. In another example, an office the account executive might be required to input the day to day expenses in to the online accounting database in order to keep the account well in order.

The aim of the data mining process is to collect the information from reliable online sources as per the requirement of the customer and convert it to a structured format for the further use. The major source of data mining is any of the internet search engine like Google, Yahoo, Bing, AOL, MSN etc. Many search engines such as Google and Bing provide customized results based on the user's activity history. Based on our keyword search, the search engine lists the details of the websites from where we can gather the details as per our requirement.

Collect the data from the online sources such as Company Name, Contact Person, Profile of the Company, Contact Phone Number of Email ID Etc. are doing for the marketing activities. Once the data is gathered from the online sources into a structured format, the marketing authorities will start their marketing promotions by calling or emailing the concerned persons, which may result to create a new customer. So basically data mining is playing a vital role in today's business expansions. By outsourcing the data entry and its related works, you can save the cost that would be incurred in setting up the necessary infrastructure and employee cost.

Source:http://ezinearticles.com/?Online-Data-Entry-and-Data-Mining-Services&id=7713395

Git workflow for Scrapy projects

Our customers often ask us what’s the best workflow for working with Scrapy projects. A popular approach we have seen and used in the past is to split the spiders folder (typically project/spiders) into two folders: project/spiders_prod and project/spiders_dev, and use the SPIDER_MODULES setting to control which spiders are loaded on each environment. This works reasonably well, until you have to make changes to common code used by many spiders (ie. code outside the spiders folder), for example common base spiders.

Nowadays, DVCS (in particular, git) have become more popular and people are quite used to branching, so we recommend using a simple git workflow (similar to GitHub flow) where you branch for every change you make. You keep all changes in a branch while they’re being tested and finally merge to master when they’re finished. This means that master branch is always stable and contains only “production-ready” spiders.

If you are using our Scrapy Cloud platform, you can have 2 projects (myproject-dev, myproject-prod) and use myproject-dev to test the changes in your branch.  scrapy deploy in Scrapy 0.17 now adds the branch name to the version name (when using version=GIT or version=HG), so you can see which branch you are going to run directly on the panel. This is particularly useful with large teams working on a single Scrapy project, to avoid stepping into each other when making changes to common code.

Here is a concrete example to illustrate how this workflow works:y

•    the developer decides to work on issue 123 (could be a new spider or fixes to an existing spider)
•    the developer creates a new branch to work on the issue
•    git checkout -b issue123
•    the developer finishes working on the code and deploys to the panel (this assumes scrapy.cfg is configured with a deploy target, and using version=GIT – see here for more information)
•    scrapy deploy dev
•    the developer goes into the panel and runs the spider, where he’ll see the branch name (issue123) that will be run
•    the developer checks the scraped data looks fine through the item browser in the panel
•    whenever issues are found, the developer makes more fixes (always working on the same branch) and deploys new versions
•    once all issues are fixed, the developer merges the branch and deploys to production project
•    git checkout master
•    git merge issue123
•    git pull # make sure to pull latest code before deploying
•    scrapy deploy prod

We recommend you keep your common spiders well-tested and use Spider Contracts extensively to test your final spiders. Otherwise experience tell us that base spiders end up being copied (instead of reused) out of fear of breaking old spiders that depend on them, thus turning their maintenance into a nightmare.

Source:http://blog.scrapinghub.com/2013/03/06/git-workflow-scrapy-projects/

Handling exceptions in scrapers

When requesting and parsing data from a source with unknown properties and random behavior (in other words, scraping), I expect all kinds of bizarrities to occur. Managing exceptions is particularly helpful in such cases.

Here is some ways that an exception might be raised.
[][0] #The list has no zeroth element, so this raises an IndexError
{}['foo'] #The dictionary has no foo element, so this raises a KeyError

Catching the exception is sometimes cleaner than preventing it from happening in the first place. Here are some examples handling bizarre exceptions in scrapers.

Example 1: Inconsistant date formats

Let’s say we’re parsing dates.
import datetime
This doesn’t raise an error.
datetime.datetime.strptime('2012-04-19', '%Y-%m-%d')
But this does.
datetime.datetime.strptime('April 19, 2012', '%Y-%m-%d')

It raises a ValueError because the date formats don’t match. So what do we do if we’re scraping a data source with multiple date formats?

Ignoring unexpected date formats

A simple thing is to ignore the date formats that we didn’t expect.

import lxml.html
import datetime
def parse_date1(source):
    rawdate = lxml.html.fromstring(source).get_element_by_id('date').text
    try:
         cleandate = datetime.datetime.strptime(rawdate, '%Y-%m-%d')
    except ValueError:
         cleandate = None
    return cleandate

print parse_date1('<div id="date">2012-04-19</div>')

If we make a clean date column in a database and put this in there, we’ll have some rows with dates and some rows with nulls. If there are only a few nulls, we might just parse those by hand.

Trying multiple date formats

Maybe we have determined that this particular data source uses three different date formats. We can try all three.

import lxml.html
import datetime

def parse_date2(source):

    rawdate = lxml.html.fromstring(source).get_element_by_id('date').text

    for date_format in ['%Y-%m-%d', '%B %d, %Y', '%d %B, %Y']:

        try:
             cleandate = datetime.datetime.strptime(rawdate, date_format)
             return cleandate
        except ValueError:
             pass
    return None

print parse_date2('<div id="date">19 April, 2012</div>')

This loops through three different date formats and returns the first one that doesn’t raise the error.

Example 2: Unreliable HTTP connection

If you’re scraping an unreliable website or you are behind an unreliable internet connection, you may sometimes get HTTPErrors or URLErrors for valid URLs. Trying again later might help.

import urllib2
def load(url):
    retries = 3
    for i in range(retries):
        try:
            handle = urllib2.urlopen(url)
            return handle.read()
        except urllib2.URLError:
            if i + 1 == retries:
                raise
            else:
                time.sleep(42)
    # never get here

print load('http://thomaslevine.com')

This function tries to download the page thee times. On the first two fails, it waits 42 seconds and tries again. On the third failure, it raises the error. On a success, it returs the content of the page.

Example 3: Logging errors rather than raising them

For more complicated parses, you might find loads of errors popping up in weird places, so you might want to go through all of the documents before deciding which to fix first or whether to do some of them manually.

import scraperwiki
for document_name in document_names:
    try:
        parse_document(document_name)
    except Exception as e:
        scraperwiki.sqlite.save([], {
            'documentName': document_name,
            'exceptionType': str(type(e)),
            'exceptionMessage': str(e)
        }, 'errors')

This catches any exception raised by a particular document, stores it in the database and then continues with the next document. Looking at the database afterwards, you might notice some trends in the errors that you can easily fix and some others where you might hard-code the correct parse.

Example 4: Exiting gracefully

When I’m scraping over 9000 pages and my script fails on page 8765, I like to be able to resume where I left off. I can often figure out where I left off based on the previous row that I saved to a database or file, but sometimes I can’t, particularly when I don’t have a unique index.


for bar in bars:
    try:
        foo(bar)
    except:
        print('Failure at bar = "%s"' % bar)
        raise

This will tell me which bar I left off on. It’s fancier if I save the information to the database, so here is how I might do that with ScraperWiki.

import scraperwiki
resume_index = scraperwiki.sqlite.get_var('resume_index', 0)
for i, bar in enumerate(bars[resume_index:]):
    try:
        foo(bar)
    except:
        scraperwiki.sqlite.save_var('resume_index', i)
        raise
scraperwiki.sqlite.save_var('resume_index', 0)

ScraperWiki has a limit on CPU time, so an error that often concerns me is the scraperwiki.CPUTimeExceededError. This error is raised after the script has used 80 seconds of CPU time; if you catch the exception, you have two CPU seconds to clean up. You might want to handle this error differently from other errors.

import scraperwiki
resume_index = scraperwiki.sqlite.get_var('resume_index', 0)
for i, bar in enumerate(bars[resume_index:]):
    try:
        foo(bar)
    except scraperwiki.CPUTimeExceededError:
        scraperwiki.sqlite.save_var('resume_index', i)
    except Exception as e:
        scraperwiki.sqlite.save_var('resume_index', i)
        scraperwiki.sqlite.save([], {
            'bar': bar,
            'exceptionType': str(type(e)),
            'exceptionMessage': str(e)
        }, 'errors')
scraperwiki.sqlite.save_var('resume_index', 0)

tl;dr

Expect exceptions to occur when you are scraping a randomly unreliable website with randomly inconsistent content, and consider handling them in ways that allow the script to keep running when one document of interest is bizarrely formatted or not available.

Source: https://blog.scraperwiki.com/2012/05/handling-exceptions-in-scrapers/

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/

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/

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"><!--
 #main_container_footer {width:100%;text-align: center;}
    #main_container_footer #footer_container {width:auto; margin:25px auto 25px auto;}
    #main_container_footer #footer_container ul {margin:0; padding:0;}
    #main_container_footer #footer_container ul li {float:left; display:inline; list-style:none; padding:0 8px; font-family:Verdana, Arial, Helvetica, sans-serif; font-size:12px; color:#000; border-right:1px #000 solid;}
    #main_container_footer #footer_container ul li a {font-family:Verdana, Arial, Helvetica, sans-serif; font-size:12px; color:#000; text-decoration:underline; font-weight:normal;}
    #main_container_footer #footer_container ul li a:hover {color:#ac1a2f; text-decoration:none; font-weight:normal;}
    #main_container_footer #footer_container ul li.no_border {border:0px;}
--></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("&copy; "+ 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">
<!--
function Window_open (Address) {
  NewWindow = window.open(Address, "Popup", "width=695,height=600,left=100,top=200,resizable=yes,scrollbars=yes");
  NewWindow.focus();
}
// -->
</script>
 <!-- img src="http://www.kitco.com/scripts/counter/counter.pl?txtonlyE.txt" width="1" height="1" -->
<!-- Google-Analytics Code-->
<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

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

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

How to login to website and extract data using PHP [closed]

I have installed the tiny tiny rss on to my computer (Windows) and also have Xampp installed (localhost).

I want to be able to use PHP to extract data from the Tiny tiny RSS webpage.

I have tried this it which just opens the front page:

<?php
$homepage = file_get_contents('my install tiny tiny rss url');
echo $homepage;
?>

But how do I login and extract the data.

You can use cURL to send post data and headers. To login you need to replicate the exact data exchange between the client and the server.


SOurce: http://stackoverflow.com/questions/20611918/how-to-login-to-website-and-extract-data-using-php

Is it ok to scrape data from Google results?

I'd like to fetch results from Google using curl to detect potential duplicate content. Is there a high risk of being banned by Google?

Google will eventually block your IP when you exceed a certain amount of requests.



Google disallows automated access in their TOS, so if you accept their terms you would break them.

That said, I know of no lawsuit from Google against a scraper. Even Microsoft scraped Google, they powered their search engine Bing with it. They got caught in 2011 red handed :)

There are two options to scrape Google results:

1) Use their API

    You can issue around 40 requests per hour You are limited to what they give you, it's not really useful if you want to track ranking positions or what a real user would see. That's something you are not allowed to gather.

    If you want a higher amount of API requests you need to pay.
    60 requests per hour cost 2000 USD per year, more queries require a custom deal.

2) Scrape the normal result pages

    Here comes the tricky part. It is possible to scrape the normal result pages. Google does not allow it.
    If you scrape at a rate higher than 15 keyword requests per hour you risk detection, higher than 20/h will get you blocked from my experience.
    By using multiple IPs you can up the rate, so with 100 IP addresses you can scrape up to 2000 requests per hour. (50k a day)
    There is an open source search engine scraper written in PHP at http://scraping.compunect.com It allows to reliable scrape Google, parses the results properly and manages IP addresses, delays, etc. So if you can use PHP it's a nice kickstart, otherwise the code will still be useful to learn how it is done.


Source: http://stackoverflow.com/questions/22657548/is-it-ok-to-scrape-data-from-google-results

Data Scraping from PDF and Excel

I am doing a little data scraping, There are 3 types of file from which i am scraping data.

1- HTML
2- PDF
3- Excel(xls)

For HTML i am comfortable, i am using HTML Agility for that.

For PDF and excel i need suggestions from anyone.



Concerning Excel. If you are in a MS environment you can either do Office Automation or use OLEDB. In a Java

environment look at Apache POI.

EDIT: Concerning PDF in Java try Apache PDFBox . Can also work in .NET using IKVM

I can recommend Cogniview's PDF2XL, a reasonably inexpensive commercial product, to extract data from tables in PDF

files into Excel. We have used it with great success.

HTML Agility is a library. Its good to use. But then, why do you need separate tools for different data extraction

purposes? Use Automation Anywhere to extract data from any source. As far as I know, it would work for all the three

sources you have specified. Google it.

Source: http://stackoverflow.com/questions/3147803/data-scraping-from-pdf-and-excel

Excel VBA Data Mining Real-Time Data from a Web Page that Refreshes Data

I want to capture real-time data that updates into a table on a webpage; I prefer capturing it into excel using VBA, but I will write it in .NET C# or VB if I that is easier.

the data updates about 1 or 2 seconds, and I want to just grab the latest data quotes and log it into my spreadsheet; the table names are the same, only the data refreshes, and it does so automatically on the web page.

I've done a lot of Excel VBA and I know how to download a URL to a file--this is NOT what I want; I want to gain access to my webpage that is active and grab the data updates after I've logged into my site and selected a webpage that I like.

Is there a simple way to access this data on the webpage from Excel or .Net? Because it refreshes no more than once every 1 or 2 seconds, it is easy to just keep checking it for updates, and I can compare the latest data to see if it actually refreshed.


In Excel 2003, use Data/Import External Data/New Web Query
Browse to your page and select the table you want to import.
After that you can either do a manual Refresh, or use a timer procedure to do something like:

Source: http://stackoverflow.com/questions/9855794/excel-vba-data-mining-real-time-data-from-a-web-page-that-refreshes-data

How to extract data from web 2.0 graphs using a scraper

I have recently come across a web page containing a graph object that displays the (x, y) values on the object as the

mouse is rolled across it. Is there any way to automate the extraction of this data?

How is the graph data loaded? If embedded in the page source then you can extract it with xpath or regex. Else use

Firebug to see how it is loaded.



You will need a solution that works inside the web browser, so the AJAX/Javascript is properly rendered.

I have used iMacros with good success for web scraping in the past. There are free/open-source and "PRO" paid editions

(comparison table here).

Another option is always to custom code something with the Microsoft webbrowser control.


Source: http://stackoverflow.com/questions/3980774/how-to-extract-data-from-web-2-0-graphs-using-a-scraper

Legality of Web Scraping vs Normal Use

I know the topic of web scraping has been discussed before (example), and I understand it's a bit of a grey area depending on a lot of factors (e.g. website's terms of use).

What I'd like to ask is: how is web scraping any different from (a) how we access the webpage via a web browser, and (b) how web crawlers (e.g. Google) download and index webpages?

Without knowing the legal background, I can't help but think that they're all just HTTP requests. If web scraping is illegal, then so should crawling and indexing (for instance be illegal).

Of course if your program is hitting the server so hard that it causes a denial of service, it's a different story altogether... my point is simply accessing and using data that is already open to the public.



I know this is a dead thread, but it would be nice to place some legal implications here due to its ranking in my Google Search. I cannot help but figure I am not the only one who searches like I do.

Legally, in the US, there are a few factors that seem to be important.

    Are you doing anything that is akin to hacking or gaining unauthorized access via the Computer Fraud and Abuse Act. Exploiting vulnerabilities and passing SQL in the URL to open a database no matter how bad the idiot programming like that was is illegal with a 15 year sentence (see the cases where an individual exploited security vulnerabilities in Verizon). Also, add a time out even if you round robin or use proxies. DDoS attacks are attacks. 1000 requests per second can shut down a lot of servers providing public information. The result here is up to 15 years in jail.

    Copyright Law: As mentioned, pure replication of data is illegal. Even 4% replication has been deemed a breach. With the recent gutting of the DMCA, a person is even more vulnerable to civil and criminal penalties.

    Trespass and Chattels: The following from wikipedia says it all.

    U.S. courts have acknowledged that users of "scrapers" or "robots" may be held liable for committing trespass to chattels,[5][6] which involves a computer system itself being considered personal property upon which the user of a scraper is trespassing. The best known of these cases, eBay v. Bidder's Edge, resulted in an injunction ordering Bidder's Edge to stop accessing, collecting, and indexing auctions from the eBay web site.

    Paywalls and Product: When going behind paywalls and breaching contract by clicking an agreement not to do something and then doing it, you add fuel to the protection of negligence v. willingness [an issue for damages and penalties not guilt] in civil and any criminal trials. (sorry originally wanted to say ignorance but it really isn't a defense)

    International: EU law and other law is way more lax. Corporations with big budgets dominate our legal landscape. They control the system in a very real way with their $$$.

Basically, get public information and information that is available without going behind a pay wall. Think like a user of the internet and combine a bunch of sources into a unique product. Don't just 'steal' an entire site (it isn't really stealing if it is a government site that offers public data especially for download but is if you download all or even more than a couple of the listings on ebay). Read the terms and conditions to know who actually owns the content.

Here are a few examples. Trulia owns its information but you could use it to go to an agents website and collect a legal amount of information. The legal amount is determinable. However, a public MLS listing lookup site with no agreement or terms and offering data to the public is fair game. The MLS numbers lists, however, are normally not fair game.

If a researcher can get to data, so can you. If a researcher needs permission, so do you. A computer is like having a million corporate researchers at your disposal.

AS for company policy, it is usually used internally to shield from liability and serves as a warning but is not entirely enforceable. The legal parts letting you know about copyrights and such are and usually are supposed to be known by everyone. Complete ignorance is not a legal protection. It does provide a ground set of rules. Be nice, or get banned is that message as far as I know.

My personal strategy is to start with public data and embellish it within legal means.


Source: http://stackoverflow.com/questions/14735791/legality-of-web-scraping-vs-normal-use

Anyone knows an online tool that can scrape a page and create a REST API for the scraped data?

I'm looking for a SaaS solution that is able to login to a platform, scrape data (reports) and then allow accessing the data through an API. I have some reporting platforms that provide web reporting and email reporting but with no API. Online reporting doesn't help and email reporting, although can be automated and scraped, isn't so reliable.

If you are willing to do the scraping through your own connection, have a look at Import IO. They have a desktop application that you use to teach the system how to scrape a page, and then you run the crawler from that application - and you can run it for as long as you like, as far as I can tell.

You may then upload your data to the Import cloud, from where it is available via an API on the import.io servers. Useful data can be made public to donate it "to the commons" if you wish.


I did some more digging, found iMacros as a possible solution. Its Windows based, which is a drawback in my case, but it does allow automation of the scraping and afterwards interaction via common web scripting languages like PHP and ASP.net.


If you are familiar with jQuery, I think you can use node.js and Cheerio module, then you can create a simple application to do auto scraping. Actually I have already built a site to do on line web scraping based on the above mentioned tech, the site is www.datafiddle.net, you can take a look at it.


Source: http://stackoverflow.com/questions/19646028/anyone-knows-an-online-tool-that-can-scrape-a-page-and-create-a-rest-api-for-the

Scrapy, scraping price data from StubHub

I've been having a difficult time with this one.

I want to scrape all the prices listed for this Bruno Mars concert at the Hollywood Bowl so I can get the average price.

http://www.stubhub.com/bruno-mars-tickets/bruno-mars-hollywood-hollywood-bowl-31-5-2014-4449604/

I've located the prices in the HTML and the xpath is pretty straightforward but I cannot get any values to return.

I think it has something to do with the content being generated via javascript or ajax but I can't figure out how to send the correct request to get the code to work.

Here's what I have:

from scrapy.spider import BaseSpider
from scrapy.selector import Selector

from deeptix.items import DeeptixItem

class TicketSpider(BaseSpider):
    name = "deeptix"
    allowed_domains = ["stubhub.com"]
    start_urls = ["http://www.stubhub.com/bruno-mars-tickets/bruno-mars-hollywood-hollywood-bowl-31-5-2014-4449604/"]

def parse(self, response):
    sel = Selector(response)
    sites = sel.xpath('//div[contains(@class, "q_cont")]')
    items = []
    for site in sites:
        item = DeeptixItem()
        item['price'] = site.xpath('span[contains(@class, "q")]/text()').extract()
        items.append(item)
    return items

Any help would be greatly appreciated I've been struggling with this one for quite some time now. Thank you in advance!


Source: http://stackoverflow.com/questions/22770917/scrapy-scraping-price-data-from-stubhub

How do you scrape AJAX pages?

Overview:

All screen scraping first requires manual review of the page you want to extract resources from. When dealing with AJAX you usually just need to analyze a bit more than just simply the HTML.

When dealing with AJAX this just means that the value you want is not in the initial HTML document that you requested, but that javascript will be exectued which asks the server for the extra information you want.

You can therefore usually simply analyze the javascript and see which request the javascript makes and just call this URL instead from the start.

Example:

Take this as an example, assume the page you want to scrape from has the following script:

<script type="text/javascript">
function ajaxFunction()
{
var xmlHttp;
try
  {
  // Firefox, Opera 8.0+, Safari
  xmlHttp=new XMLHttpRequest();
  }
catch (e)
  {
  // Internet Explorer
  try
    {
    xmlHttp=new ActiveXObject("Msxml2.XMLHTTP");
    }
  catch (e)
    {
    try
      {
      xmlHttp=new ActiveXObject("Microsoft.XMLHTTP");
      }
    catch (e)
      {
      alert("Your browser does not support AJAX!");
      return false;
      }
    }
  }
  xmlHttp.onreadystatechange=function()
    {
    if(xmlHttp.readyState==4)
      {
      document.myForm.time.value=xmlHttp.responseText;
      }
    }
  xmlHttp.open("GET","time.asp",true);
  xmlHttp.send(null);
  }
</script>

Then all you need to do is instead do an HTTP request to time.asp of the same server instead. Example from w3schools.


Sporce: http://stackoverflow.com/questions/260540/how-do-you-scrape-ajax-pages

using Perl to scrape a website

I am interested in writing a perl script that goes to the following link and extracts the number 1975: https://familysearch.org/search/collection/results#count=20&query=%2Bevent_place_level_1%3ACalifornia%20%2Bevent_place_level_2%3A%22San%20Diego%22%20%2Bbirth_year%3A1923-1923~%20%2Bgender%3AM%20%2Brace%3AWhite&collection_id=2000219

That website is the amount of white men born in the year 1923 who live in San Diego County, California in 1940. I am trying to do this in a loop structure to generalize over multiple counties and birth years.

In the file, locations.txt, I put the list of counties, such as San Diego County.

The current code runs, but instead of the # 1975, it displays unknown. The number 1975 should be in $val\n.

I would very much appreciate any help!

#!/usr/bin/perl

use strict;

use LWP::Simple;

open(L, "locations26.txt");

my $url = 'https://familysearch.org/search/collection/results#count=20&query=%2Bevent_place_level_1%3A%22California%22%20%2Bevent_place_level_2%3A%22%LOCATION%%22%20%2Bbirth_year%3A%YEAR%-%YEAR%~%20%2Bgender%3AM%20%2Brace%3AWhite&collection_id=2000219';

open(O, ">out26.txt");
 my $oldh = select(O);
 $| = 1;
 select($oldh);
 while (my $location = <L>) {
     chomp($location);
     $location =~ s/ /+/g;
      foreach my $year (1923..1923) {
                 my $u = $url;
                 $u =~ s/%LOCATION%/$location/;
                 $u =~ s/%YEAR%/$year/;
                 #print "$u\n";
                 my $content = get($u);
                 my $val = 'unknown';
                 if ($content =~ / of .strong.([0-9,]+)..strong. /) {
                         $val = $1;
                 }
                 $val =~ s/,//g;
                 $location =~ s/\+/ /g;
                 print "'$location',$year,$val\n";
                 print O "'$location',$year,$val\n";
         }
     }

Update: API is not a viable solution. I have been in contact with the site developer. The API does not apply to that part of the webpage. Hence, any solution pertaining to JSON will not be applicbale.



Source: http://stackoverflow.com/questions/14654288/using-perl-to-scrape-a-website

Data Scraping using php

Here is my code

    $ip=$_SERVER['REMOTE_ADDR'];

    $url=file_get_contents("http://whatismyipaddress.com/ip/$ip");

    preg_match_all('/<th>(.*?)<\/th><td>(.*?)<\/td>/s',$url,$output,PREG_SET_ORDER);

    $isp=$output[1][2];

    $city=$output[9][2];

    $state=$output[8][2];

    $zipcode=$output[12][2];

    $country=$output[7][2];

    ?>
    <body>
    <table align="center">
    <tr><td>ISP :</td><td><?php echo $isp;?></td></tr>
    <tr><td>City :</td><td><?php echo $city;?></td></tr>
    <tr><td>State :</td><td><?php echo $state;?></td></tr>
    <tr><td>Zipcode :</td><td><?php echo $zipcode;?></td></tr>
    <tr><td>Country :</td><td><?php echo $country;?></td></tr>
    </table>
    </body>

How do I find out the ISP provider of a person viewing a PHP page?

Is it possible to use PHP to track or reveal it?

Error: http://i.imgur.com/LGWI8.png

Curl Scrapping

<?php
$curl_handle=curl_init();
curl_setopt( $curl_handle, CURLOPT_FOLLOWLOCATION, true );
$url='http://www.whatismyipaddress.com/ip/132.123.23.23';
curl_setopt($curl_handle, CURLOPT_URL,$url);
curl_setopt($curl_handle, CURLOPT_HTTPHEADER, Array("User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.8.1.15) Gecko/20080623 Firefox/2.0.0.15") );
curl_setopt($curl_handle, CURLOPT_CONNECTTIMEOUT, 2);
curl_setopt($curl_handle, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($curl_handle, CURLOPT_USERAGENT, 'Your application name');
$query = curl_exec($curl_handle);

curl_close($curl_handle);
preg_match_all('/<th>(.*?)<\/th><td>(.*?)<\/td>/s',$url,$output,PREG_SET_ORDER);
echo $query;
$isp=$output[1][2];

$city=$output[9][2];

$state=$output[8][2];

$zipcode=$output[12][2];

$country=$output[7][2];
?>
<body>
<table align="center">
<tr><td>ISP :</td><td><?php echo $isp;?></td></tr>
<tr><td>City :</td><td><?php echo $city;?></td></tr>
<tr><td>State :</td><td><?php echo $state;?></td></tr>
<tr><td>Zipcode :</td><td><?php echo $zipcode;?></td></tr>
<tr><td>Country :</td><td><?php echo $country;?></td></tr>
</table>
</body>

Error: http://i.imgur.com/FJIq6.png

What's is wrong with my code here? Any alternative code , that i can use here.

I am not able to scrape that data as described here. http://i.imgur.com/FJIq6.png

P.S. Please post full code. It would be easier for me to understand.



Source: http://stackoverflow.com/questions/10461088/data-scraping-using-php

PDF scraping using R

I have been using the XML package successfully for extracting HTML tables but want to extend to PDF's. From previous questions it does not appear that there is a simple R solution but wondered if there had been any recent developments

Failing that, is there some way in Python (in which I am a complete Novice) to obtain and manipulate pdfs so that I could finish the job off with the R XML package

Extracting text from PDFs is hard, and nearly always requires lots of care.

I'd start with the command line tools such as pdftotext and see what they spit out. The problem is that PDFs can store the text in any order, can use awkward font encodings, and can do things like use ligature characters (the joined up 'ff' and 'ij' that you see in proper typesetting) to throw you.

pdftotext is installable on any Linux system



Source: http://stackoverflow.com/questions/7918718/pdf-scraping-using-r

Php Scraping data from a website

I am very new to programming and need a little help with getting data from a website and passing it into my PHP script.

The website is http://www.birthdatabase.com/.

I would like to plug in a name (First and Last) and retrieve the result. I know you can query the site by passing the name in the URL, but I am having problems scraping the results.

http://www.birthdatabase.com/cgi-bin/query.pl?textfield=FIRST&textfield2=LAST&age=&affid=

I am using the file_get_contents($URL) function to get the page but need help after that. Specifically, I would like to scrape only the results from a certain state if there are multiple results for that name.



You need the awesome simple_html_dom class.

With this class you can query the webpage's DOM in a similar way to jQuery.

First include the class in your page, then get the page content with this snippet:

$html = file_get_html('http://www.birthdatabase.com/cgi-bin/query.pl?textfield=' . $first . '&textfield2=' . $last . '&age=&affid=');

Then you can use CSS selections to scrape your data (something like this):

$n = 0;
foreach($html->find('table tbody tr td div font b table tbody') as $element) {
    @$row[$n]['tr']  = $element->find('tr')->text;
    $n++;
}

// output your data
print_r($row);



Source: http://stackoverflow.com/questions/15601584/php-scraping-data-from-a-website

Obtaining reddit data

I am interested in obtaining data from different reddit subreddits. Does anyone know

if there is a reddit/other api similar like twitter does to crawl all the pages?


Yes, reddit has an API that can be used for a variety of purposes such as data

collection, automatic commenting bots, or even to assist in subreddit moderation.

There are a few places to discover information on reddit's API:

    github reddit wiki -- provides the overview and rules for using reddit's API

(follow the rules)
    automatically generated API docs -- provides information on the requests needed to

access most of the API endpoints
    /r/redditdev -- the reddit community dedicated to answering questions both about

reddit's source code and about reddit's API

If there is a particular programming language you are already familiar with, you

should check out the existing set of API wrappers for various languages. Despite my

bias (I am the package maintainer) I am quite certain PRAW, for python, has support

for the largest number of reddit API features.



Source: http://stackoverflow.com/questions/14322834/obtaining-reddit-data