Web Scraping Service Vs Web Scraping Tool – Choosing The Best

Web scraping is a rapidly emerging technique of extracting data from any web source with the intent to use it for analyzing the market trends. Different business owners adopt this method to enhance their sales and growth. They are open with different tools and services of extracting data from the internet.

Here, the major question that rises is- What is suitable between web scraping services and web scraping tools or software? The feasible answer is web scraping service as it offers comparatively more benefits that any software or tool.

Advantages of web scraping services

A thick of web scraping companies render custom-based support to the businesses in data extraction. Some of the major compelling benefits of preferring web scraping services may include:

    Lowered cost: You can conveniently save your thousands of money and man-power as these services are available at comparatively low prices.

    Accuracy in results: Unlike the data extraction software, these services render premium level of accuracy in terms of results. The leading companies of web services ensure that they deliver exact outcomes to you as per your need through their services.

    Instant outcomes: It only takes maximum time duration of 3 to 4 hours to generate valuable information about any database by acquiring the services of reputed web scraping company. You can avail the advantage of time over market on your competitors.

Drawbacks of using web scraping tools

    Using data extraction software accompanies certain drawbacks with it that may include:
    Difficulty in data extraction from multifaceted websites.
    Difficulty in extracting huge bulk of data.
    It is comparatively a slower process than a service provider.
    Several sites have well-defined policies for screen scraping.

Summary: While making a comparison between web scraping tools and services, you may arrive at the conclusion that the services are much more beneficial, reliable, and efficient than the major tools.
   
 Source : http://www.web-parsing.com/blog/web-scraping-services-vs-web-scraping-tools-choosing-the-best/

Data Extraction is not a Rocket Science: Follow These 4 Tips to Get Exemplary Results!

Data extraction is a skill, the more you master it – more are the chances of having a lucid picture of the volatile market and getting better perceptive of constantly changing trends. Escalating volatility in the market and intensifying competition has been the most contributing factors that have led to the rise of data extraction and data mining.

Data extraction is primarily used by companies (large and small, alike) to collect data from a specific industry, or data related to targeted customers or about their competition in the market. In fact, it has become a primary tool for marketers to plan their moves for branding and promoting particular products or services. It helps a wide plethora of industrial sectors to find and learn about specific data, based on their requirements.

And now with the rise of internet, web scraping has emerged as an important aspect that contributes to your success – the success of your venture or organization. It processes the HTML of a Web page to obtain data and convert it into to another format (i.e. HTML to XML).

Various extraction tools form an integral part of data extraction and data scrapping. Following offers a brief outline of some of these tools:

Email Extraction – An email extractor tool is used to acquire the email ids from any dependable sources automatically

Screen Scrapping – Screen scraping is a practice of reading text information from a screen and collecting visual data, rather than analyzing data as done in web scraping.

Data Mining as name suggests is a process of gathering patterns from information. It basically transforms the information into formats like CSV, MS excels, HTML and so and so forth, depending to your requirements. Web Spider – A Web spider is a computer program which browses internet in a systematic, automated manner. It is used by many search engines in order to provide up-to-date data.

It is often seen that while extracting data; many get lost into the labyrinth of confusion, data overabundance, along with a lot of weird and not-so-familiar terms. Proper handling of these may sound easy, however; when not executed with appropriate procedure and processes; it may bring in disastrous results.

This no way means that data mining is a rocket science which only a few gifted and skilled people can take up. All it requires is undivided attention, keen preparation, and training, so brace up yourself for an overview of some practical tips that can help in successful data extraction and give a boost to your business.

Identify your Business Goals!:

Get a clear perspective in mind as to what are your business goals.

Data extraction can be bifurcated into various branches; and one needs to choose it wisely, depending on the business goals. E.g. your primary requirement is to get email ids of potential clients to conduct an email campaign; and for that you certainly need an email extractor. Use of this tool assists in extracting the email ids from trustworthy sources automatically. It essentially collects business contacts from various web pages, text files, HTML files, or any other format without duplicating the email ids. So, if you are not sure what you want; even applying the best tools will be of no use!

A crystal clear mindset helps in better understanding of market scenario and thus helps in formulation of powerful and effective strategies to get desired outcomes. E.g., people dealing in real estate business, should have a vision for it and which area they want to target specifically. With a clear vision they can clearly spell out what you want and where it should be.

Set Realistic Expectations:

Upon identifying your business goals, make sure to check out that they are realistic and attainable! Unrealistic and unachievable targets are the real cause for the obstacles and frustrations in the future.

Since, there are various tools that are and can be employed to extract data; vague or unclear goals make it difficult to determine which tool can be applied.

This crystal clear mindset; will help you give that insight about the direction your business is headed to.

Moreover, you can determine which method can be used to get excellent results. You can get a lucid picture of the past and present of your competitors and therefore helps in setting targets based on the others’ experiences. It is usually a wise move to set expectations that you have not achieved before.

Appoint Skilled Data Miner:

Skilled data miner with excellent data mining skills will reduce the painstaking and tiresome process of planning, devising and preparation.

For fresh start-ups, you can go ahead with the standard procedure however; if you have ample professionals at your disposal, pick up the right one who is not only knowledgeable but also reliable and sincere towards the task.

Prevent Data Deposits:

Being dead-sure of what you really want will help you avoid unnecessary data deposition.

Data mining just like real mining is a skill to know where the real treasure lies and being able to get it in the most efficient and effective way.

Being able to spot on authenticated & reliable resources, well researched information is what gives a short cut to locate the right and exact data.

If you are aimlessly opening every website; the results are bound to be ambiguous and would ultimately be a waste of time and effort.

Source : http://www.habiledata.com/blog/data-extraction-is-not-a-rocket-science-follow-these-4-tips-to-get-exemplary-results

Mobile app developers “duped” into distributing data-scraping malware: NICTA

The surge in mobile malware has led many to condemn developers' poor security practices, yet recent NICTA research suggests that – even though data-stealing is ubiquitous among both paid and free Android applications – many mobile application developers are in fact being “duped” into incorporating data-stealing routines into their applications.

A methodical analysis of Android applications and source code found that all of the top 100 paid and non-paid apps in Australia were collecting personal information, with 60 percent of the apps incorporating some sort of tracking library and 20 percent of the apps featuring more than three different tracking libraries.

While many have blamed developers for their poor security, NICTA mobile systems research group leader, Aruna Seneviratne, who leads the organisation's Networks Research Group, told CSO Australia that many tracking libraries were inadvertently added when developers incorporated third-party libraries into their mobile apps.

“In most cases app developers just use third-party libraries and don't know what's in them,” he said. “They're not being malicious for the sake of being malicious; they are just being duped into doing a thing that collects a lot of information.”

 And collect they do. Apps analysed by the team – whose paper 'early detection of spam mobile apps' was accepted for presentation at the recent WWW 2015 conference in Florence, Italy – were siphoning all kinds of personal information off of users' mobile devices, often sending it to enlarge what have become massive databases of personal preferences and behavioural modeling.

“It's amazing how much information each of those apps collects,” he said, “and the scary thing is that most of them actually go to a small number of sources – which means these guys can actually infer a lot of information about you. They have a very good idea of who you are and what you're doing – and they are cross-matching the information they collect.”

Ever more-clever data-siphoning routines were making data collection richer all the time, with many Android apps now being designed with libraries that collect information about nearby Wi-Fi access points and can correctly extrapolate the user's location 90 percent of the time.

Read more: The week in security: Android apps collecting your location data, home routers hit by drive-by malware

Seneviratne blamed Google's relatively lax app-approval process for the proliferation of such apps, which join the malware-laden apps that by the team's figures account for around 3 percent of all Google Play Store apps.

Recognising that developers are often as clueless as users about the extent of the data collection going on, the team has proposed an app-rating system that will give consumers a better idea of what they're enabling by downloading and installing a particular app.

A basic prototype has already been developed and a pilot site is expected to be up and running by the fourth quarter of this year. The service, which rates apps on criteria such as privacy and security, will be available to third parties as a Web service that Seneviratne hopes will eventually help it gain traction on app-rating and other sites.

Read more: Surveillance laws driving companies to limit data collection, developers to boost security

“We've been working to come up with a scheme that is similar to the energy-ratings system that you have for electrical appliances,” he said, noting that the site will also seek to boost developers' security awareness by correlating app ratings “to let consumers know they can download an alternate app that has the same functionality but a higher security rating”.

Israeli developer-tools firm Checkmarx has taken its own approach to improving developers' security skills, recently learning extensive lessons as hackers worked to manipulate its Game of Hacks security application – which is now under development to be sold to large corporates for developer training and testing.

This article is brought to you by Enex TestLab, content directors for CSO Australia.

Read more: The week in security: Budget flags encryption troubles, cross-government IAM

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Read More:

    Victorian Commissioner for Privacy and Data Protection sorts sheep from the goats

    Better than email: VISA launches FireEye threat intel platform for merchants

Source: http://www.cso.com.au/article/576533/mobile-app-developers-duped-into-distributing-data-scraping-malware-nicta/

Data Scraping - Enjoy the Appeal of the Hand Scraped Flooring

Hand scraped flooring is appreciated for the character it brings into the home. This style of flooring relies on hand scraped planks of wood and not the precise milled boards. The irregularities in the planks provide a certain degree of charm and help to create a more unique feature in the home.

Distressed vs. Hand scraped

There are two types of flooring in the market that have an aged and unique charm with a non perfect finish. However, there is a significant difference in the process used to manufacture the planks. The more standard distresses flooring is cut on a factory production line. The grooves, scratches, dents, or other irregularities in these planks are part of the manufacturing process and achieved by rolling or pressed the wood onto a patterned surface.

The real hand scraped planks are made by craftsmen and they work on each plant individually. By using this working technique, there is complete certainty that each plank will be unique in appearance.

Scraping the planks

The hand scraping process on the highest-quality planks is completed by the trained carpenter or craftsmen who will produce a high-quality end product and take great care in their workmanship. It can benefit to ask the supplier of the flooring to see who completes the work.

Beside the well scraped lumber, there are also those planks that have been bought from the less than desirable sources. This is caused by the increased demand for this type of flooring. At the lower end of the market the unskilled workers are used and the end results aren't so impressive.

The high-quality plank has the distinctive look that feels and functions perfectly well as solid flooring, while the low-quality work can appear quite ugly and cheap.

Even though it might cost a little bit more, it benefits to source the hardwood floor dealers that rely on the skilled workers to complete the scraping process.

Buying the right lumber

Once a genuine supplier is found, it is necessary to determine the finer aspects of the wooden flooring. This hand scraped flooring is available in several hardwoods, such as oak, cherry, hickory, and walnut. Plus, it comes in many different sizes and widths. A further aspect relates to the finish with darker colored woods more effective at highlighting the character of the scraped boards. This makes the shadows and lines appear more prominent once the planks have been installed at home.

Why not visit Bellacerafloors.com for the latest collection of luxury floor materials, including the Handscraped Hardwood Flooring.

Source: http://ezinearticles.com/?Enjoy-the-Appeal-of-the-Hand-Scraped-Flooring&id=8995784

Web scraping in under 60 seconds: the magic of import.io

Import.io is a very powerful and easy-to-use tool for data extraction that has the aim of getting data from any website in a structured way. It is meant for non-programmers that need data (and for programmers who don’t want to overcomplicate their lives).

I almost forgot!! Apart from everything, it is also a free tool (o_O)

The purpose of this post is to teach you how to scrape a website and make a dataset and/or API in under 60 seconds. Are you ready?

It’s very simple. You just have to go to http://magic.import.io; post the URL of the site you want to scrape, and push the “GET DATA” button. Yes! It is that simple! No plugins, downloads, previous knowledge or registration are necessary. You can do this from any browser; it even works on tablets and smartphones.

For example: if we want to have a table with the information on all items related to Chewbacca on MercadoLibre (a Latin American version of eBay), we just need to go to that site and make a search – then copy and paste the link (http://listado.mercadolibre.com.mx/chewbacca) on Import.io, and push the “GET DATA” button.

You’ll notice that now you have all the information on a table, and all you need to do is remove the columns you don’t need. To do this, just place the mouse pointer on top of the column you want to delete, and an “X” will appear.

Good news for those of us who are a bit more technically-oriented! There is a button that says “GET API” and this one is good to, well, generate an API that will update the data on each request. For this you need to create an account (which is also free of cost).

As you saw, we can scrape any website in under 60 seconds, even if it includes tons of results pages. This truly is magic, no? For more complex things that require logins, entering subwebs, automatized searches, et cetera, there is downloadable import.io software… But I’ll explain that in a different post.

Source: http://schoolofdata.org/2014/12/09/web-scraping-in-under-60-seconds-the-magic-of-import-io/

Web Scraping Services : Making Modern File Formats More Accessible

Data scraping is the process of automatically sorting through information contained on the internet inside html, PDF or other documents and collecting relevant information to into databases and spreadsheets for later retrieval. On most websites, the text is easily and accessibly written in the source code but an increasing number of businesses are using Adobe PDF format (Portable Document Format: A format which can be viewed by the free Adobe Acrobat software on almost any operating system. See below for a link.). The advantage of PDF format is that the document looks exactly the same no matter which computer you view it from making it ideal for business forms, specification sheets, etc.; the disadvantage is that the text is converted into an image from which you often cannot easily copy and paste. PDF Scraping is the process of data scraping information contained in PDF files. To PDF scrape a PDF document, you must employ a more diverse set of tools.

There are two main types of PDF files: those built from a text file and those built from an image (likely scanned in). Adobe's own software is capable of PDF scraping from text-based PDF files but special tools are needed for PDF scraping text from image-based PDF files. The primary tool for PDF scraping is the OCR program. OCR, or Optical Character Recognition, programs scan a document for small pictures that they can separate into letters. These pictures are then compared to actual letters and if matches are found, the letters are copied into a file. OCR programs can perform PDF scraping of image-based PDF files quite accurately but they are not perfect.

Once the OCR program or Adobe program has finished PDF scraping a document, you can search through the data to find the parts you are most interested in. This information can then be stored into your favorite database or spreadsheet program. Some PDF scraping programs can sort the data into databases and/or spreadsheets automatically making your job that much easier.

Quite often you will not find a PDF scraping program that will obtain exactly the data you want without customization. Surprisingly a search on Google only turned up one business, that will create a customized PDF scraping utility for your project. A handful of off the shelf utilities claim to be customizable, but seem to require a bit of programming knowledge and time commitment to use effectively. Obtaining the data yourself with one of these tools may be possible but will likely prove quite tedious and time consuming. It may be advisable to contract a company that specializes in PDF scraping to do it for you quickly and professionally.

Let's explore some real world examples of the uses of PDF scraping technology. A group at Cornell University wanted to improve a database of technical documents in PDF format by taking the old PDF file where the links and references were just images of text and changing the links and references into working clickable links thus making the database easy to navigate and cross-reference. They employed a PDF scraping utility to deconstruct the PDF files and figure out where the links were. They then could create a simple script to re-create the PDF files with working links replacing the old text image.

A computer hardware vendor wanted to display specifications data for his hardware on his website. He hired a company to perform PDF scraping of the hardware documentation on the manufacturers' website and save the PDF scraped data into a database he could use to update his webpage automatically.

PDF Scraping is just collecting information that is available on the public internet. PDF Scraping does not violate copyright laws.

PDF Scraping is a great new technology that can significantly reduce your workload if it involves retrieving information from PDF files. Applications exist that can help you with smaller, easier PDF Scraping projects but companies exist that will create custom applications for larger or more intricate PDF Scraping jobs.

Source: http://ezinearticles.com/?PDF-Scraping:-Making-Modern-File-Formats-More-Accessible&id=193321

On-line directory tree webscraping

As you surf around the internet — particularly in the old days — you may have seen web-pages like this:

The former image is generated by Apache SVN server, and the latter is the plain directory view generated for UserDir on Apache.

In both cases you have a very primitive page that allows you to surf up and down the directory tree of the resource (either the SVN repository or a directory file system) and select links to resources that correspond to particular files.

Now, a file system can be thought of as a simple key-value store for these resources burdened by an awkward set of conventions for listing the keys where you keep being obstructed by the ‘/‘ character.

My objective is to provide a module that makes it easy to iterate through these directory trees and produce a flat table with the following helpful entries:

Although there is clearly redundant data between the fields url, abspath, fname, name, ext, having them in there makes it much easier to build a useful front end.

The function code (which I won’t copy in here) is at https://scraperwiki.com/scrapers/apache_directory_tree_extractor/. This contains the functions ParseSVNRevPage(url) and ParseSVNRevPageTree(url), both of which return dicts of the form:

{'url', 'rev', 'dirname', 'svnrepo',

 'contents':[{'url', 'abspath', 'fname', 'name', 'ext'}]}

I haven’t written the code for parsing the Apache Directory view yet, but for now we have something we can use.

I scraped the UK Cave Data Registry with this scraper which simply applies the ParseSVNRevPageTree() function to each of the links and glues the output into a flat array before saving it:

lrdata = ParseSVNRevPageTree(href)

ldata = [ ]

for cres in lrdata["contents"]:

    cres["svnrepo"], cres["rev"] = lrdata["svnrepo"], lrdata["rev"]

    ldata.append(cres)

scraperwiki.sqlite.save(["svnrepo", "rev", "abspath"], ldata)

Now that we have a large table of links, we can make the cave image file viewer based on the query:

select abspath, url, svnrepo from swdata where ext=’.jpg’ order by abspath limit 500

By clicking on a reference to a jpg resource on the left, you can preview what it looks like on the right.

If you want to know why the page is muddy, a video of the conditions in which the data was gathered is here.

Image files are usually the most immediately interesting out of any unknown file system dump. And they can be made more interesting by associating meta-data with them (given that no convention for including interesting information in the EXIF sections of their file formats). This meta-data might be floating around in other files dumped into the same repository — eg in the form of links to them from html pages which relate to picture captions.

But that is a future scraping project for another time.

Source: https://scraperwiki.wordpress.com/2012/09/14/on-line-directory-tree-webscraping/