How to scrape data without coding? A step by step tutorial on import.io

Import.io (pronounced import-eye-oh) lets you scrape data from any website into a searchable database. It is perfect for gathering, aggregating and analysing data from websites without the need for coding skills. As Sally Hadadi, from Import.io, told Journalism.co.uk: the idea is to “democratise” data. “We want journalists to get the best information possible to encourage and enhance unique, powerful pieces of work and generally make their research much easier.” Different uses for journalists, supplemented by case studies, can be found here.

A beginner’s guide

After downloading and opening import.io browser, copy the URL of the page you want to scrape into the import.io browser. I decided to scrape the search results website of orphanages in London:

001 Orphanages in London

After opening the website, press the tiny pink button in top right corner of the browser and follow up with “Let’s get cracking!” in the bottom right menu which has just appeared.

Then, choose the type of scraping you want to perform. In my case, it’s a Crawler (we’ll be getting data from multiple similar pages on the same site):

crawler

And confirm the URL of the website you want to scrape by clicking “I’m there”.

As advised, choose “Detect optimal settings” and confirm the following:

data

In the menu “Rows per page” select the format in which data appears on the website, whether it is “single” or “multiple”. I’m opting for the multiple as my URL is a listing of multiple search results:multiple

Now, the time has come to “train your rows” i.e. mark which part of the website you are interested in scraping. Hover over an entire “entry” or “paragraph”:hover over entry

…and he entry will be highlighted in pink or blue. Press “Train rows”.

train rows

Repeat the operation with the next entry/paragraph so that the scraper gets the hang of the pattern of your selections. Two examples should suffice. Scroll down to the bottom of your website to make sure that all entries until the last one are selected (=highlighted in pink or blue alternately).

If it is, press “I’ve got all 50 rows” (the number depends on how many rows you have selected).

Now it’s time to focus on particular chunks of data you would like to extract. My entries consist of a name of the orphanage, address, phone number and a short description so I will extract all those to separate columns. Let’s start by adding a column “name”:

add column

Next, highlight the name of the first orphanage in the list and press “Train”.

highlighttrain

Your table should automatically fill in with names of all orphanages in the list:table name

If it didn’t, try tweaking your selection a bit. Then add another column “address” and extract the address of the orphanage by highlighting the two lines of addresses and “training” the rows.

Repeat the operation for a “phone number” and “description”. Your table should end up looking like this:table final

*Before passing on to the next column it is worth to check that all the rows have filled up. If not, highlighting and training of the individual elements might be necessary.

Once you’ve grabbed all that you need, click “I’ve got what I need”. The menu will now ask you if you want to scrape more pages. In this case, the search yielded two pages of search results so I will add another page. In order to this this, go back to your website in you regular browser, choose page 2 (or any next one) of your search results and copy the URL. Paste it into the import.io browser and confirm by clicking “I’m there”:

i'm there

The scraper should automatically fill in your table for page 2. Click “I’ve got all 45 rows” and “I’ve got what I needed”.

You need to add at least 5 pages, which is a bit frustrating with a smaller data set like this one. The way around it is to add page 2 a couple of times and delete the unnecessary rows in the final table.

Once the cheating is done, click “I’m done training!” and “Upload to import.io”.

upload

Give the name to your Crawler, e.g. “Orphanages in London” and wait for import.io to upload your data. Then, run crawler:run crawler

Make sure that the page depth is 10 and that click “Go”. If you’re scraping a huge dataset with several pages of search results, you can copy your URLs to Excel, highlight them and drag down with a black cross (bottom right of the cell) to obtain a comprehensive list. Paste it into the “Where to start?” window and press “Go”.go

crawlingAfter the crawling is complete, you can download you data in EXCEL, HTML, JSON or CSV.dataset

As a result, we obtain a data set which can be easily turned into a map of orphanages in London, e.g. using Google Fusion Tables.

Source:http://www.interhacktives.com/2014/03/06/scrape-data-without-coding-step-step-tutorial-import-io/

Is Web Scraping Legal?

Web scraping might be one of the best ways to aggregate content from across the internet, but it comes with a caveat: It’s also one of the hardest tools to parse from a legal standpoint.

For the uninitiated, web scraping is a process whereby an automated piece of software extracts data from a website by “scraping” through the site’s many pages. While search engines like Google and Bing do a similar task when they index web pages, scraping engines take the process a step further and convert the information into a format which can be easily transferred over to a database or spreadsheet.

It’s also important to note that a web scraper is not the same as an API. While a company might provide an API to allow other systems to interact with its data, the quality and quantity of data available through APIs is typically lower than what is made available through web scraping. In addition, web scrapers provide more up-to-date information than APIs and are much easier to customize from a structural standpoint.

The applications of this “scraped” information are widespread. A journalist like Nate Silver might use scrapers to monitor baseball statistics and create numerical evidence for a new sports story he’s working on. Similarly, an eCommerce business might bulk scrape product titles, prices, and SKUs from other sites in order to further analyze them.

Legality of Web ScrapingWhile web scraping is an undoubtedly powerful tool, it’s still undergoing growing pains when it comes to legal matters. Because the scraping process appropriates pre-existing content from across the web, there are all kinds of ethical and legal quandaries that confront businesses who hope to do leverage scrapers for their own processes.

In this “wild west” environment, where the legal implications of web scraping are in a constant state of flux, it helps to get a foothold on where the legal needle currently falls. The following timeline outlines some of the biggest cases involving web scrapers in the United States, and allows us to achieve a greater understanding on the precedents that surround the court rulings.

Terms of Use Tug-of-War—2000-2009

For years after they first came into use, web scrapers went largely unchallenged from a legal standpoint. In 2000, however, the use of scrapers came under heavy and consistent fire when eBay fired the first shot against an auction data aggregator called Bidder’s Edge. In this very early case, eBay argued that Bidder’s Edge was using scrapers in a way that violated Trespass to Chattels doctrine. While the lawsuit was settled out of court, the judge upheld eBay’s original injunction, stating that heavy bot traffic could very well disrupt eBay’s service.

Then in 2003’s Intel Corp. v. Hamidi, the California Supreme court overturned the basis of eBay v. Bidder’s Edge, ruling that Trespass to Chattels could not extend to the context of computers if no actual damage to personal property occurred.

So in terms of legal action against web scraping, Tresspass to Chattels no longer applied, and things were back to square one. This began a period in which the courts consistently rejected Terms of Service as a valid means of prohibiting scrapers, including cases like Perfect 10 v. Google, and Cvent v. Eventbrite.

The Takeaway: The earliest cases against scrapers hinged on Trespass to Chattels law, and were successful. However, that doctrine is no longer a valid approach.

Facebook Web Scraping2009—Facebook Steps In

In 2009, Facebook turned the tides of the web scraping war when Power.com, a site which aggregated multiple social networks into one centralized site, included Facebook in their service. Because Power.com was scraping Facebook’s content instead of adhering to their established standards, Facebook sued Power on grounds of copyright infringement.

In denying Power.com’s motion to dismiss the case, the Judge ruled that scraping can constitute copying, however momentary that copying may be. And because Facebook’s Terms of Service don’t allow for scraping, that act of copying constituted an infringement on Facebook’s copyright. With this decision, the waters regarding the legality of web scrapers began to shift in favor of the content creators.

The Takeaway: Even if a web scraper ignores infringing content on its way to freely-usable content, it might qualify as copyright infringement by virtue of having technically “copied” the infringing content first.

2011-2014— U.S. v Auernheimer

In 2010, hacker Andrew “Weev” Auernheimer found a security flaw in AT&T’s website, which would display the email addresses of users who visited the site via their iPads. By exploiting the flaw using some simple scripts and a scraper, Auernheimer was able to gather thousands of emails from the AT&T site.

Although these email addresses were publicly available, Auernheimer’s exploit led to his 2012 conviction, where he was charged with identity fraud and conspiracy to access a computer without authorization.

Data ScrapingEarlier this year, the court vacated Auernheimer’s conviction, ruling that the trial’s New Jersey venue was improper. But even though the case turned out to be mostly inconclusive, the court noted the fact that there was no evidence to show that “any password gate or code-based barrier was breached.” This seems to leave room for the web scraping of publicly-available personal information, although it’s still very much open to interpretation and not set in stone.

The Takeaway: Using a web scraper to aggregate sensitive personal information can lead to a conviction, even if that information was technically available to the public. While there is hope in the court’s observation that no passwords or barriers were broken to retrieve this information, the waters here are still very volatile.

2013—Associated Press vs. Meltwater

Meltwater is a software company whose “Global Media Monitoring” product uses scrapers to aggregate news stories for paying clients. The Associated Press took issue with Meltwater’s scraping of their original stories, some of which had been copyrighted. In 2012, AP filed suit against Meltwater for copy infringement and hot news misappropriation.

While it’s already been established that facts cannot be copyrighted, the court decided that the AP’s copyrighted articles—and more specifically, the way in which the facts within those articles were arranged—were not fair game for copying. On top of this, Meltwater’s use of the articles failed to meet the established fair use standards, and could not be defended on that front either.

The Takeaway: Fair use is limited when it comes to web scrapers, and copyrighted content is not always open to be scraped.

~~

By closely observing the outcomes of previous rulings, you’ll find that there are a few guidelines that a scraper should attempt to adhere to:

    Content being scraped is not copyright protected
    The act of scraping does not burden the services of the site being scraped
    The scraper does not violate the Terms of Use of the site being scraped
    The scraper does not gather sensitive user information
    The scraped content adheres to fair use standards

While all of these guidelines are important to understand before using scrapers, there are other ways to acclimate to the legal nuances. In many cases, you’ll find that a simple conversation with a business software developer or consultant will lead to some satisfying conclusions: Odds are, they’ve used scrapers in the past and can shed light on any snags they’ve hit in the process. And of course, talking with a lawyer is always an ideal course of action when treading into questionable legal territory.

Source:http://blog.icreon.us/2014/09/12/web-scraping-and-you-a-legal-primer-for-one-of-its-most-useful-tools/

Interactive Crawls for Scraping AJAX Pages on the Web

Crawling pages on the web has become an everyday affair for most enterprises. Too often do we come across offline businesses as well who’d like data gathered from the web for internal analyses. All this eventually to serve customers faster and better. At times, when the crawl job is high-end cum high-scale, businesses also consider DaaS providers to supplement their efforts.

However, the web landscape too has evolved with newer technologies that provide fancy experiences to web users. AJAX elements are one such common aid that leave even the DaaS providers perplexed. They come in various forms from a user’s point of view-

1. Load more results on the same page

2. Filter results based on various selection criteria

3. Submit forms, etc.

When crawling a non-AJAX page, simple GET requests do the job. However, AJAX pages work with POST requests that are not easy to trace for a normal bot.

Difference between GET request and POST request- Scraping

GET vs. POST

At PromptCloud, from our experience with a number of AJAX sites on the web, we’ve crossed the tech barrier. Below is a quick review about the challenges that come with AJAX crawling and its indicative solutions-

1. Javascript Emulations- A bot essentially emulates human browsing to fetch pages. When this needs to be done for Javascript components on a page, it gets tricky. Headless browser, which emulates human interaction with a web page without an interface, is the current approach. These browsers click on various elements/ dropdown lists that are embedded within Javascript code and capture responses to be transferred to programs. Which headless browser to pick depends on what fits well into your current stack.

2. Fetch Bandwidths- Unlike GET requests which complete pretty quickly, POST requests take quite a bit of time due to the number of events involved per fetch. Hence a good amount of bandwidth needs to be allocated in order to receive the response. For the same reason, wait times need to be taken care of too else you might end up with incomplete responses.

3. .NET Architectures- This is a more complex scenario related to maintaining the View State. Most of the postbacks come with an event and its validation. The bot needs to track the view state and pass validations for the event to occur so that the code can be executed and results captured. This is achieved by adopting a mechanism to restore states if things break midway.

4. Page Encoding- Request and response headers need to be taken care of on AJAX pages. The request needs to be sent in the exact format as expected by the server (Content-type or media type, accept fields, etc.) and similarly responses need to be parsed based on the content-type.

A Use Case

One of our clients who is into sale of event tickets at discounted rates had us crawl one of the ticketing sites on the web weekly; one of the most complex AJAX crawling we’ve dealt with so far. For the data that was to be extracted, multiple AJAX fetches were needed depending on the selections made. Requests had to be made for a combination of items from the dropdown box. These came with cookies and session IDs. To add to the challenge the site was extremely dynamic and changed its structure every week making it difficult for us to follow what data was where on the page.

We developed an AJAX crawler specific to this site to take care of all the dynamics. Response times were taken care of so that we didn’t miss any relevant information. We included an ML component to improve the crawler which is now pretty stable irrespective of changes on the site.

Overall, AJAX crawling requires more compute power in addition to the tech expertise. And because there’s no uniformity on the web, there’s always a new challenge to overcome in this landscape. It wouldn’t be an overrating if we said we’ve done a good job at that so far and have developed the knack :)

Reach out to us for any kind of web scraping/ crawling- either AJAX or not. We’ll take care of the complexities.

Source: https://www.promptcloud.com/blog/web-scraping-interactive-ajax-crawls/

Web scraping services-importance of scraped data

Web scraping services are provided by computer software which extracts the required facts from the website. Web scraping services mainly aims at converting unstructured data collected from the websites into structured data which can be stockpiled and scrutinized in a centralized databank. Therefore, web scraping services have a direct influence on the outcome of the reason as to why the data collected in necessary.

It is not very easy to scrap data from different websites due to the terms of service in place. So, the there are some legalities that have been improvised to protect altering the personal information on different websites. These ‘rules’ must be followed to the letter and to some extent have limited web scraping services.

Owing to the high demand for web scraping, various firms have been set up to provide the efficient and reliable guidelines on web scraping services so that the information acquired is correct and conforms to the security requirements. The firms have also improvised different software that makes web scraping services much easier.

Importance of web scraping services

Definitely, web scraping services have gone a long way in provision of very useful information to various organizations. But business companies are the ones that benefit more from web scraping services. Some of the benefits associated with web scraping services are:

    Helps the firms to easily send notifications to their customers including price changes, promotions, introduction of a new product into the market. Etc.
    It enables firms to compare their product prices with those of their competitors
    It helps the meteorologists to monitor weather changes thus being able to focus weather conditions more efficiently
    It also assists researchers with extensive information about peoples’ habits among many others.
    It has also promoted e-commerce and e-banking services where the rates of stock exchange, banks’ interest rates, etc. are updated automatically on the customer’s catalog.

Advantages of web scraping services

The following are some of the advantages of using web scraping services

    Automation of the data

    Web scraping can retrieve both static and dynamic web pages

    Page contents of various websites can be transformed

    It allows formulation of vertical aggregation platforms thus even complicated data can still be extracted from different websites.

    Web scraping programs recognize semantic annotation

    All the required data can be retrieved from their websites

    The data collected is accurate and reliable

Web scraping services mainly aims at collecting, storing and analyzing data. The data analysis is facilitated by various web scrapers that can extract any information and transform it into useful and easy forms to interpret.

Challenges facing web scraping

    High volume of web scraping can cause regulatory damage to the pages

    Scale of measure; the scales of the web scraper can differ with the units of measure of the source file thus making it somewhat hard for the interpretation of the data

    Level of source complexity; if the information being extracted is very complicated, web scraping will also be paralyzed.

It is clear that besides web scraping providing useful data and information, it experiences a number of challenges. The good thing is that the web scraping services providers are always improvising techniques to ensure that the information gathered is accurate, timely, reliable and treated with the highest levels of confidentiality.

Source: http://www.loginworks.com/blogs/web-scraping-blogs/191-web-scraping-services-importance-of-scraped-data/

How to scrape Amazon with WebDriver in Java

Here is a real-world example of using Selenium WebDriver for scraping.
This short program is written in Java and scrapes book title and author from the Amazon webstore.
This code scrapes only one page, but you can easily make it scraping all the pages by adding a couple of lines.

You can download the souce here.

import java.io.*;
import java.util.*;
import java.util.regex.*;

import org.openqa.selenium.*;
import org.openqa.selenium.firefox.FirefoxDriver;

public class FetchAllBooks {

    public static void main(String[] args) throws IOException {

        WebDriver driver = new FirefoxDriver();
      

driver.navigate().to("http://www.amazon.com/tag/center%20right?ref_=tag_dpp_cust_itdp_s_t&sto

re=1");

        List<WebElement> allAuthors =  driver.findElements(By.className("tgProductAuthor"));
        List<WebElement> allTitles =  driver.findElements(By.className("tgProductTitleText"));
        int i=0;
        String fileText = "";

        for (WebElement author : allAuthors){
            String authorName = author.getText();
            String Url = (String)((JavascriptExecutor)driver).executeScript("return

arguments[0].innerHTML;", allTitles.get(i++));
            final Pattern pattern = Pattern.compile("title=(.+?)>");
            final Matcher matcher = pattern.matcher(Url);
            matcher.find();
            String title = matcher.group(1);
            fileText = fileText+authorName+","+title+"\n";
        }

        Writer writer = new BufferedWriter(new OutputStreamWriter(new

FileOutputStream("books.csv"), "utf-8"));
        writer.write(fileText);
        writer.close();

        driver.close();
    }
}

Source: http://scraping.pro/scraping-amazon-webdriver-java/

Web Scraping: Business Intelligence

Web scraping is simply getting of information that is both hidden and unhidden from the internet. Web scraping is one of the latest technologies used in harvesting data from WebPages. It has been used to extract useful information for practical and beneficial applications and its interpretation has been tested in decision making. Web scraping is a new term that overshadows the traditional data harvesting technique that was used before. It has been regarded as knowledge discovery in databases for research and even marketing monitoring.

This article explores the various business intelligence ways in which web scraping can be used to be of importance.

Web scraping services has been used by many companies that have a strong customer focus. These companies range from sectors like retail, financial services, and marketing and communication organizations. It quite important to realize that web scraping has great signifies and impact in the varied commercial applications for the better understanding and prediction of the critical data. The data may range from stocks to consumer behaviors. The consumer behaviors are better shown in trends like customer profiles, purchasing and industry analysis among others.

Source:http://www.loginworks.com/blogs/web-scraping-blogs/web-scraping-business-intelligence/

Web Scraping Popularity Soars

The world is stirred because of the ever-growing web scraping success in almost all of its services. Success stories pertaining to the benefits of online data collection in business, research, politics, health, and almost all aspects of human life are endless. With this popularity surge, it has become a hot issue and many are questioning its legality and reliability.

Looking back, this simple harvesting of pertinent data from competitors and the global market in general like anything else started as a non-threatening and advanced form of web research. Eventually, when the benefits begin to manifest and the system improves, many are lured into it that it has become one of the strongest and fastest growing business in the world.

Simple Beginnings

As naturally as a law of life that great things come from small beginnings, data mining was conceived as a process in gaining information, mostly in research. This act of collecting information through the internet was never imagined to be what it has become nowadays.

Source:http://www.loginworks.com/blogs/web-scraping-blogs/web-scraping-popularity-soars/