Benefits of Scraping Data from Real Estate Website

With so much of growth in the recent times in real estate industry, it is likely that companies would want to create something different or use another method, so as to get desired benefits. Thus, it is best to go with the technological advancements and create real estate websites to get an edge over others in the industry. And to get all the information regarding website content, one can opt for real estate data scraping methods.

About real estate website scraping

Internet has become an important part of our daily lives and in industry marketing procedures too. With the use of website scraping one can easily scrape real estate listing from various websites. One just needs the help of experts and with proper software and tools; they can easily collect all the relevant real estate data from the required real estate websites and make a structured file containing the information. With internet becoming a valid platform for information and data submitted by numerous sources from around the globe, it is necessary to gather them all in one place for companies. In this way, the company can know what it lacks and work upon their strategies so as to gain profit and get to the top of the business world by taking one step at a time.

Uses of real estate website scraping

With proper use of website scraping one can collect and scrape the real estate listings which can help the company in the real estate market area. One can draw the attention of potential customers by designing the company strategies in such a way as contemplating the changing trends in the real estate global arena. All this is done with the help of the data collected from various real estate websites. With the help of proper website, one can collect the data and these get updated whenever new information gets into the web portal. In this way the company is kept updated about the various changes happening around the global market and thus, ensure in making plans regarding the company. This way one can plan ahead and take steps that can lead to the company gaining profits in future.

Thus, with the help of proper real estate website scraping one can be sure of getting all the information regarding real estate market. This way one can work upon making the company move as per the market trends and get a stronghold in real estate business.

Source: https://3idatascraping.wordpress.com/2013/09/25/benefit-of-scraping-data-from-real-estate-website/

Three Common Methods For Web Data Extraction

Probably the most common technique used traditionally to extract data from web pages this is to cook up some regular expressions that match the pieces you want (e.g., URL's and link titles). Our screen-scraper software actually started out as an application written in Perl for this very reason. In addition to regular expressions, you might also use some code written in something like Java or Active Server Pages to parse out larger chunks of text. Using raw regular expressions to pull out the data can be a little intimidating to the uninitiated, and can get a bit messy when a script contains a lot of them. At the same time, if you're already familiar with regular expressions, and your scraping project is relatively small, they can be a great solution.

Other techniques for getting the data out can get very sophisticated as algorithms that make use of artificial intelligence and such are applied to the page. Some programs will actually analyze the semantic content of an HTML page, then intelligently pull out the pieces that are of interest. Still other approaches deal with developing "ontologies", or hierarchical vocabularies intended to represent the content domain.

There are a number of companies (including our own) that offer commercial applications specifically intended to do screen-scraping. The applications vary quite a bit, but for medium to large-sized projects they're often a good solution. Each one will have its own learning curve, so you should plan on taking time to learn the ins and outs of a new application. Especially if you plan on doing a fair amount of screen-scraping it's probably a good idea to at least shop around for a screen-scraping application, as it will likely save you time and money in the long run.

So what's the best approach to data extraction? It really depends on what your needs are, and what resources you have at your disposal. Here are some of the pros and cons of the various approaches, as well as suggestions on when you might use each one:

Raw regular expressions and code

Advantages:

- If you're already familiar with regular expressions and at least one programming language, this can be a quick solution.

- Regular expressions allow for a fair amount of "fuzziness" in the matching such that minor changes to the content won't break them.

- You likely don't need to learn any new languages or tools (again, assuming you're already familiar with regular expressions and a programming language).

- Regular expressions are supported in almost all modern programming languages. Heck, even VBScript has a regular expression engine. It's also nice because the various regular expression implementations don't vary too significantly in their syntax.

Disadvantages:

- They can be complex for those that don't have a lot of experience with them. Learning regular expressions isn't like going from Perl to Java. It's more like going from Perl to XSLT, where you have to wrap your mind around a completely different way of viewing the problem.

- They're often confusing to analyze. Take a look through some of the regular expressions people have created to match something as simple as an email address and you'll see what I mean.

- If the content you're trying to match changes (e.g., they change the web page by adding a new "font" tag) you'll likely need to update your regular expressions to account for the change.

- The data discovery portion of the process (traversing various web pages to get to the page containing the data you want) will still need to be handled, and can get fairly complex if you need to deal with cookies and such.

When to use this approach: You'll most likely use straight regular expressions in screen-scraping when you have a small job you want to get done quickly. Especially if you already know regular expressions, there's no sense in getting into other tools if all you need to do is pull some news headlines off of a site.

Ontologies and artificial intelligence

Advantages:

- You create it once and it can more or less extract the data from any page within the content domain you're targeting.

- The data model is generally built in. For example, if you're extracting data about cars from web sites the extraction engine already knows what the make, model, and price are, so it can easily map them to existing data structures (e.g., insert the data into the correct locations in your database).

- There is relatively little long-term maintenance required. As web sites change you likely will need to do very little to your extraction engine in order to account for the changes.

Disadvantages:

- It's relatively complex to create and work with such an engine. The level of expertise required to even understand an extraction engine that uses artificial intelligence and ontologies is much higher than what is required to deal with regular expressions.

- These types of engines are expensive to build. There are commercial offerings that will give you the basis for doing this type of data extraction, but you still need to configure them to work with the specific content domain you're targeting.

- You still have to deal with the data discovery portion of the process, which may not fit as well with this approach (meaning you may have to create an entirely separate engine to handle data discovery). Data discovery is the process of crawling web sites such that you arrive at the pages where you want to extract data.

When to use this approach: Typically you'll only get into ontologies and artificial intelligence when you're planning on extracting information from a very large number of sources. It also makes sense to do this when the data you're trying to extract is in a very unstructured format (e.g., newspaper classified ads). In cases where the data is very structured (meaning there are clear labels identifying the various data fields), it may make more sense to go with regular expressions or a screen-scraping application.

Screen-scraping software

Advantages:

- Abstracts most of the complicated stuff away. You can do some pretty sophisticated things in most screen-scraping applications without knowing anything about regular expressions, HTTP, or cookies.

- Dramatically reduces the amount of time required to set up a site to be scraped. Once you learn a particular screen-scraping application the amount of time it requires to scrape sites vs. other methods is significantly lowered.

- Support from a commercial company. If you run into trouble while using a commercial screen-scraping application, chances are there are support forums and help lines where you can get assistance.

Disadvantages:

- The learning curve. Each screen-scraping application has its own way of going about things. This may imply learning a new scripting language in addition to familiarizing yourself with how the core application works.

- A potential cost. Most ready-to-go screen-scraping applications are commercial, so you'll likely be paying in dollars as well as time for this solution.

- A proprietary approach. Any time you use a proprietary application to solve a computing problem (and proprietary is obviously a matter of degree) you're locking yourself into using that approach. This may or may not be a big deal, but you should at least consider how well the application you're using will integrate with other software applications you currently have. For example, once the screen-scraping application has extracted the data how easy is it for you to get to that data from your own code?

When to use this approach: Screen-scraping applications vary widely in their ease-of-use, price, and suitability to tackle a broad range of scenarios. Chances are, though, that if you don't mind paying a bit, you can save yourself a significant amount of time by using one. If you're doing a quick scrape of a single page you can use just about any language with regular expressions. If you want to extract data from hundreds of web sites that are all formatted differently you're probably better off investing in a complex system that uses ontologies and/or artificial intelligence. For just about everything else, though, you may want to consider investing in an application specifically designed for screen-scraping.

As an aside, I thought I should also mention a recent project we've been involved with that has actually required a hybrid approach of two of the aforementioned methods. We're currently working on a project that deals with extracting newspaper classified ads. The data in classifieds is about as unstructured as you can get. For example, in a real estate ad the term "number of bedrooms" can be written about 25 different ways. The data extraction portion of the process is one that lends itself well to an ontologies-based approach, which is what we've done. However, we still had to handle the data discovery portion. We decided to use screen-scraper for that, and it's handling it just great. The basic process is that screen-scraper traverses the various pages of the site, pulling out raw chunks of data that constitute the classified ads. These ads then get passed to code we've written that uses ontologies in order to extract out the individual pieces we're after. Once the data has been extracted we then insert it
into a database.

Source: http://ezinearticles.com/?Three-Common-Methods-For-Web-Data-Extraction&id=165416

How to Properly Scrape Windows During The Cleaning Process

Removing ordinary dirt such as dust, fingerprints, and oil from windows seem simple enough. However, sometimes, you may find stubborn caked-on dirt or debris on your windows that cannot be removed by standard window cleaning techniques such as scrubbing or using a squeegee. The best way to remove caked-on dirt on your windows is to scrape it off. Nonetheless, you have to be extra careful when you are scraping your windows, because they can be easily scratched and damaged. Here are a number of rules that you need to follow when you are scraping windows.

Rule No. 1: It is recommended that you use a professional window scraper to remove caked-on dirt and debris from your windows. This type of scraper is specially made for use on glass, and it comes with certain features that can prevent scratching and other kinds of damage.

Rule No. 2: It is important to inspect your window scraper before using it. Take a look at the blade of the scraper and make sure that it is not rusted. Also, it must not be bent or chipped off at the corners. If you are not certain whether the blade is in a good enough condition, you should just play it safe by using a new blade.

Rule No. 3: When you are working with a window scraper, always use forward plow-like scraping motions. Scrape forward and lift the scraper off the glass, and then scrape forward again. Try not to slide the scraper backwards, because you may trap debris under the blade when you do so. Consequently, the scraper may scratch the glass.

Rule No. 4: Be extra cautious when you are using a window scraper on tempered glass. Tempered glass may have raised imperfections, which make it more vulnerable to scratches. To find out if the window that you are scraping is made of tempered glass, you have to look for a label in one of its corners.

Window Scraping Procedures

Before you start scraping, you have to wet your window with soapy water first. Then, find out how the window scraper works by testing it in a corner. Scrape on the same spot three or four times in forward motion. If you find that the scraper is moving smoothly and not scratching the glass, you can continue to work on the rest of the window. On the other hand, if you feel as if the scraper is sliding on sandpaper, you have to stop scraping. This indicates that the glass may be flawed and have raised imperfections, and scraping will result in scratches.

After you have ascertained that it is safe to scrape your window, start working along the edges. It is best that you start scraping from the middle of an edge, moving towards the corners. Work in a one or two inch pattern, until all the edges of the glass are properly scraped. After that, scrape the rest of the window in a straight pattern of four or five inches, working from top to bottom. If you find that the window is beginning to dry while you are working, wet it with soapy water again.

Source: http://ezinearticles.com/?How-to-Properly-Scrape-Windows-During-The-Cleaning-Process&id=6592930

What is HTML Scraping and how it works

There are many reasons why there may be a requirement to pull data or information from other sites, and usually the process begins after checking whether the site has an official API. There are very few people who are aware about the presence of structured data that is supported by every website automatically. We are basically talking about pulling data right from the HTML, also referred to as HTML scraping. This is an awesome way of gleaning data and information from third party websites.

Any webpage content that can be viewed can be scraped without any trouble. If there is any way provided by the website to the browser of the visitor to download content and use the same in a highly structured manner, in that case, accessing of the content programmatically is possible. HTML scraping works in an amazing manner.

Before indulging in HTML scraping, one can inspect the browser for network traffic. Site owners have a couple of tricks up their sleeve to thwart this access, but majority of them can be worked around.

Before moving on to how HTML scraping works, we must understand the reasons behind the same. Why is scraping needed? Once you get a satisfactory answer to this question, you can start looking for RSS or API feeds or various other traditional structured data forms. It is significant to understand that when compared with APIs, websites are more significant.

The most important advantage of the same is the maintenance of their websites where a lot of visitors visit rather than safeguarding structured data feeds. With Tweeter, the same has been publicly seen when it clamps down on the developer ecosystem. Many times, API feeds change or move without any prior warning. Many times, it can also be a deliberate attempt, but mostly, such issues or problems erupt as there is no authority or an organization that maintains or takes care of the structured data. It is rarely noticed, if the same gets severely mangled or goes offline. In case the website has certain issues or the website no longer works, the problem is more in the form of a ball in your court requiring dealing with the same without losing any time. api-comic-image

Rate limiting is another factor that needs a lot of thinking and in case of public websites, it virtually doesn’t exist. Besides some occasional sign up pages or captchas, many business websites fail to create and built defenses against any unwarranted automated access. Many times, a single website can be scraped for four hours straight without anyone noticing. There are chances that you would not be viewed under DDOS attack unless concurrent requests are being made by you. You will be seen just as an avid visitor or an enthusiast in the logs, that too, in case anyone is looking.

Another factor in HTML scraping is that one can easily access any website anonymously. Behavior tracking can be done with a few ways by the administrator of the website and this turns out to be beneficial if you want to privately gather the data. Many times, registration is imperative with APIs in order to get key and with any request being sent, this key also needs to be sent. But, in case of simple and straightforward HTTP requests, the visitor can stay anonymous besides cookies and IP address, which can again be spoofed.

The availability of HTML scraping is universal and there is no need to wait for the opening of the site for an API or for contacting anyone in the organization. One simply needs to spend some time and browse websites at a leisurely pace until the data you want is available and then find out the basic patterns to access the same.

Now you need to don a hat of a professional scraper and simply dive in. Initially, it may take some time to work up figuring out the way the data have been structured and the way it can be accessed just as we read APIs. If there is no documentation unlike APIs, you need to be a little more smart about it and use clever tricks.

Some of the most used tricks are

Data Fetching

The first thing that is required is data fetching. Find endpoints to begin with, that is the URLs that can help in returning the data that is required. If you are pretty sure about the data and the way it should be structured so as to match your requirements, you will require a particular subset for the same and later you can indulge in site browsing using the navigation tools.

GET Parameter

The URLs must be paid attention to and see the way it changes as you indulge in clicking between the sections and the way they divide into various subsections. Before starting, the other option that can be used is to straight away go to the search functionality of the site. Certain terms can be typed and the URL needs to be focused again for watching the changes on the basis of what is being searched. A GET parameter will be probably seen like q which changes on the basis of the search term used by you. Other GET parameters that are not being used can be removed from the URL until only the ones that are needed are left for data loading. Before a query string, there must always be a “?” beginning.

Now the time has come when you would have started to come across the data that you would like to see and want to access, but sometimes, there may be certain pagination issues that require to be dealt with. Due to these issues, you may not be able to see the data in its entirety. Single requests are kept away by many APIs as well from database slamming. Many times, clicking the next page can add some offset parameter that helps in data visibility on the page. All these steps will help you succeed in HTML scraping.

Source: https://www.promptcloud.com/blog/what-is-html-scraping-and-how-it-works/

Thoughts on scraping SERPs and APIs

Google says that scraping keyword rankings is against their policy from what I've read. Bummer. We comprise a lot of reports and manual finding and entry was a pain. Enter Moz! We still manually check and compare, but it's nice having that tool. I'm confused now though about practices and getting SERPs in an automated way. Here are my questions

1.     Is it against policy to get SERPs from an automated method? If that is the case, isn't Moz breaking this policy with it's awesome keyword tracker?
2.     If it's not, and we wanted to grab that kind of data, how would we do it? Right now, Moz's API doesn't offer this data. I thought Raven Tools at one point offered this, but they don't now from what I've read. Are there any APIs out there that we can grab this data and do what we want with it? (let's day build our own dashboard)?

Thanks for any clarification and input!

Source: http://moz.com/community/q/thoughts-on-scraping-serps-and-apis

Some Traps to know and avoid in Web Scraping

In the present day and age, web scraping comes across as a handy tool in the right hands. In essence, web scraping means quickly crawling the web for specific information, using pre-written programs. Scraping efforts are designed to crawl and analyze the data of entire websites, and saving the parts that are needed. Many industries have successfully used web scraping to create massive banks of relevant, actionable data that they use on a daily basis to further their business interests and provide better service to customers. This is the age of the Big Data, and web scraping is one of the ways in which businesses can tap into this huge data repository and come up with relevant information that aids them in every way.

Web scraping, however, does come with its own share of problems and roadblocks. With every passing day, a growing number of websites are trying to actively minimize the instance of scraping and protect their own data to stay afloat in today’s situation of immense competition. There are several other complications which might arise and several traps that can slow you down during your web scraping pursuits. Knowing about these traps and how to avoid them can be of great help if you want to successfully accomplish your web scraping goals and get the amount of data that you require.

Complications in Web Scraping

Over time, various complications have risen in the field of web scraping. Many websites have started to get paranoid about data duplication and data security problems and have begun to protect their data in many ways. Some websites are not generally agreeable to the moral and ethical implications of web scraping, and do not want their content to be scraped. There are many places where website owners can set traps and roadblocks to slow down or stop web scraping activities. Major search engines also have a system in place to discourage scraping of search engine results. Last but not the least, many websites and web services announce a blanket ban on web scraping and say the same in their terms and conditions, potentially leading to legal issues in the event of any scraping.

Here are some of the most common complications that you might face during your web scraping efforts which you should be particularly aware about –

•    Some locations on the intranet might discourage web scraping to prevent data duplication or data theft.

•    Many websites have in place a number of different traps to detect and ban web scraping tools and programs.

•    Certain websites make it clear in their terms and conditions that they consider web scraping an infringement of their privacy and might even consider legal redress.

•    In a number of locations, simple measures are implemented to prevent non-human traffic to websites, making it difficult for web scraping tools to go on collecting data at a fast pace.

To surmount these difficulties, you need a deeper and more insightful understanding of the way web scraping works and also the attitude of website owners towards web scraping efforts. Most major issues can be subverted or quietly avoided if you maintain good working practice during your web scraping efforts and understand the mentality of the people whose sites you are scraping.

Web Crawling Services & Web Scraping Services

Common Problems

With automated scraping, you might face a number of common problems. The behavior of web scraping programs or spiders presents a certain picture to the target website. It then uses this behavior to distinguish between human users and web scraping spiders. Depending on that information, a website may or may not employ particular web scraping traps to stop your efforts. Some of the commonly employed traps are –

Crawling Pattern Checks – Some websites detect scraping activities by analyzing crawling patterns. Web scraping robots follow a distinct crawling pattern which incorporates repetitive tasks like visiting links and copying content. By carefully analyzing these patterns, websites can determine that they are being caused by a web scraping robot and not a human user, and can take preventive measures.

Honeypots – Some websites have honeypots in their webpages to detect and block web scraping activities. These can be in the form of links that are not visible to human users, being disguised in a certain way. Since your web crawler program does not operate the way a human user does, it can try and scrape information from that link. As a result, the website can detect the scraping effort and block the source IP addresses.

Policies – Some websites make it absolutely apparent in their terms and conditions that they are particularly averse to web scraping activities on their content. This can act as a deterrent and make you vulnerable against possible ethical and legal implications.

Infinite Loops – Your web scraping program can be tricked into visiting the same URL again and again by using certain URL building techniques.

These traps in web scraping can prove to be detrimental to your efforts and you need to find innovative and effective ways to surpass these problems. Learning some web crawler tips to avoid traps and judiciously using them is a great way of making sure that your web scraping requirements are met without any hassle.

What you can do

The first and foremost rule of thumb about web scraping is that you have to make your efforts as inconspicuous as possible. This way you will not arouse suspicion and negative behavior from your target websites. To this end, you need a well-designed web scraping program with a human touch. Such a program can operate in flexible ways so as to not alert website owners through the usual traffic criteria used to spot scraping tools.

Web scraping for ecommerce data extraction

Some of the measures that you can implement to ensure that you steer clear of common web scraping traps are –

•    The first thing that you need to do is to ascertain if a particular website that you are trying to scrape has any particular dislike towards web scraping tools. If you see any indication in their terms and conditions, tread cautiously and stop scraping their website if you receive any notification regarding their lack of approval. Being polite and honest can help you get away with a lot.

•    Try and minimize the load on every single website that you visit for scraping. Putting a high load on websites can alert them towards your intentions and often might cause them to develop a negative attitude. To decrease the overall load on a particular website, there are many techniques that you can employ.

•    Start by caching the pages that you have already crawled to ensure that you do not have to load them again.

•    Also store the URLs of crawled pages.

•    Take things slow and do not flood the website with multiple parallel requests that put a strain on their resources.

•    Handle your scraping in gentle phases and take only the content you require.

•    Your scraping spider should be able to diversify its actions, change its crawling pattern and present a polymorphic front to websites, so as not to cause an alarm and put them on the defensive.

•    Arrive at an optimum crawling speed, so as to not tax the resources and bandwidth of the target website. Use auto throttling mechanisms to optimize web traffic and put random breaks in between page requests, with the lowest possible number of concurrent requests that you can work with.

•    Use multiple IP addresses for your scraping efforts, or take advantage of proxy servers and VPN services. This will help to minimize the danger of getting trapped and blacklisted by a website.

•    Be prepared to understand the respect the express wishes and policies of a website regarding web scraping by taking a good look at the target ‘robots.txt’ file. This file contains clear instructions on the exact pages that you are allowed to crawl, and the requisite intervals between page requests. It might also specify that you use a pre-determined user agent identification string that classifies you as a scraping bot. adhering to these instructions minimizes the chance of getting on the bad side of website owners and risking bans.

Use an advanced tool for web scraping which can store and check data, URLs and patterns. Whether your web scraping needs are confined to one domain or spread over many, you need to appreciate that many website owners do not take kindly to scraping. The trick here is to ensure that you maintain industry best practices while extracting data from websites. This prevents any incident of misunderstanding, and allows you a clear pathway to most of the data sources that you want to leverage for your requirements.

Hope this article helps in understanding the different traps and roadblocks that you might face during your web scraping endeavors. This will help you in figuring out smart, sensible ways to work around them and make sure that your experience remains smooth. This way, you can keep receiving the important information that you need with web scraping. Following these basic guidelines can help you prevent getting banned or blacklisted and stay in the good books of website owners. This will allow you continue with your web scraping activities unencumbered.

Source:https://www.promptcloud.com/blog/some-traps-to-avoid-in-web-scraping/