Wednesday, 28 September 2016

Scraping Yelp Business Data With Python Scraping Script

Scraping Yelp Business Data With Python Scraping Script

Yelp is a great source of business contact information with details like address, postal code, contact information; website addresses etc. that other site like Google Maps just does not. Yelp also provides reviews about the particular business. The yelp business database can be useful for telemarketing, email marketing and lead generation.

Are you looking for yelp business details database? Are you looking for scraping data from yelp website/business directory? Are you looking for yelp screen scraping software? Are you looking for scraping the business contact information from the online Yelp? Then you are at the right place.

Here I am going to discuss how to scrape yelp data for lead generation and email marketing. I have made a simple and straight forward yelp data scraping script in python that can scrape data from yelp website. You can use this yelp scraper script absolutely free.

I have used urllib, BeautifulSoup packages. Urllib package to make http request and parsed the HTML using BeautifulSoup, used Threads to make the scraping faster.
Yelp Scraping Python Script

import urllib
from bs4 import BeautifulSoup
import re
from threading import Thread

#List of yelp urls to scrape
url=['http://www.yelp.com/biz/liman-fisch-restaurant-hamburg','http://www.yelp.com/biz/casa-franco-caramba-hamburg','http://www.yelp.com/biz/o-ren-ishii-hamburg','http://www.yelp.com/biz/gastwerk-hotel-hamburg-hamburg-2','http://www.yelp.com/biz/superbude-hamburg-2','http://www.yelp.com/biz/hotel-hafen-hamburg-hamburg','http://www.yelp.com/biz/hamburg-marriott-hotel-hamburg','http://www.yelp.com/biz/yoho-hamburg']

i=0
#function that will do actual scraping job
def scrape(ur):

          html = urllib.urlopen(ur).read()
          soup = BeautifulSoup(html)

      title = soup.find('h1',itemprop="name")
          saddress = soup.find('span',itemprop="streetAddress")
          postalcode = soup.find('span',itemprop="postalCode")
          print title.text
          print saddress.text
          print postalcode.text
          print "-------------------"

threadlist = []

#making threads
while i<len(url):
          t = Thread(target=scrape,args=(url[i],))
          t.start()
          threadlist.append(t)
          i=i+1

for b in threadlist:
          b.join()

Recently I had worked for one German company and did yelp scraping project for them and delivered data as per their requirement. If you looking for scraping data from business directories like yelp then send me your requirement and I will get back to you with sample.

Source: http://webdata-scraping.com/scraping-yelp-business-data-python-scraping-script/

Thursday, 15 September 2016

Run Code Template – New Feature Added to Fminer Web Scraping Tool

Run Code Template – New Feature Added to Fminer Web Scraping Tool

Fminer is one of the powerful web scraping software, I already given brief of all the Fminer features in previous post. In this post I am going to introduce one of the interesting feature of fminer which is Run Code Template that is recently added to Fminer, this feature is similar to “Fminer Run Code” action but it’s different in a way you can use it. The Run Code Action you can use inside the data scraping flow and python code get executed when scraper start running.

While Run Code Templates are the saved python code snippets that you can run on the data tables after scraping completes. Assume if you get white space in scraped data then you can easily trim this left and right spaces by just executing “strip_column” template, see the code of that template below.

'''Strip all data of a column in data table
Remove the blank of data in the head and the tail.
'''

tabName = '[%table1|data table%]'
colName = '[%table1.column1|table column for strip%]'

tab = tables[tabName]
for i, row in enumerate(tab):
    row[colName] = row[colName].strip()   
    tab.edit_row(i, row)

This template comes with Fminer and few other template like “merge_tables_with_same_columns”.  Below are the steps how you can execute template python code on scraped data.

Step 1: Click on second icon from right that says “Run Code” under the Data section

Step 2: One popup will appear, you need to click on “Templates” icon and choose the template you want to execute and then click on Ok.

Step 3: Now the window will appear for configuration that will ask you to choose the table and column under that table on which you want to execute the code. Now click on Ok again.

Step 4: Now you can see the code of that template, now you can click on execute icon and script will start running, based on number of records it will take time to finish execution.

In many web scraping projects I found this template code very handy for cleaning data and making life easy. Templates are stored at following path so you can create your own template with customized code.

C:\Program Files (x86)\FMiner\templates

I have created one template which I use to remove HTML code that comes while scraping badly organized HTML pages. Below is the code of template for stripping html:

'''Strip HTML will remove all html tags of a column in data table.
'''
import re
tabName = '[%table1|data table%]'
colName = '[%table1.column1|table column for substring%]'
colNew = '[%table1.column1|table column to add new data%]'
tab = tables[tabName]
for i, row in enumerate(tab):
    cleanr =re.compile('<.*?>')
    cleantext = re.sub(cleanr,'', row[colName])
    row[colNew] = cleantext 
    tab.edit_row(i, row)

Stay connected as I am going to post more code templates that will make your web scraping life easy and manipulate data on fly.

Source: http://webdata-scraping.com/run-code-template-new-feature-added-fminer-web-scraping-tool/

Tuesday, 6 September 2016

Calculate your ROI on Web Scraping using our ROI Calculator

Calculate your ROI on Web Scraping using our ROI Calculator

Staying atop the competition is a vital thing for the survival and growth of businesses these days. Ever since big data came into the picture, web scraping has become something businesses from every industry has to invest in. If your company is not in a technically advanced industry, web scraping could even be a nightmare to start with. Wondering if going with in-house web scraping is right for you? In house or outsourcing, in the end it’s all about the returns on investment.

ROI Calculator

Considering the numerous factors that determine how much web scraping can cost you, it’s not easy to calculate the ROI on your in-house web scraping.

In house web scraping is certainly a challenging process. If you plan on going down this way, here is a brief list of prerequisites.

Engineers

Technically skilled labour is an essential requirement for web scraping. Since, web scraping techniques are complicated, it needs good programming skills to write, run and maintain the scraping bots. The cost of labour can be one of the drawbacks with doing in house web scraping.

Hardware Resources

Web scraping is a resource hungry process which requires high end servers and lots of bandwidth. Without the adequate resources, you might end up losing important data. The cost of quality servers could easily make you want to reconsider doing web scraping on your own. Not to mention the doubling up of these resources in order to keep the data intact, espcially if you’re looking at large scale.

Maintainability and ukeep of your tech stack

Once you have your servers and other technical components setup, the real deal only starts. You have to ensure availability of your servers, data backups, restoring previous states, failovers, among many other complications associated with managing servers and fixing them up when something goes wrong. You need to allocate resources (both people and hardware) to take care of the above.

Time

Time is something that we cannot really include in the equation when it comes to calculating the returns. But it is definitely a factor that defines if web scraping in house is worth it. Although web scraping is the fastest way to acquire data, the initial setup and maintenance are time consuming and complicated. This could easily lead to conflicts when you have to distribute your time between web scraping and other business activities that are crucial for your company.

Try the ROI Calculator

We came up with an ROI calculator to easily calculate your returns on investment with our web scraping services. Using this, you could easily compare the cost of in house web scraping with PromptCloud’s dedicated web scraping services. Find out how much you can save by going the PromptCloud way.

Source: https://www.promptcloud.com/blog/calculate-roi-on-web-scraping

Monday, 29 August 2016

How Web Scraping can Help you Detect Weak spots in your Business

How Web Scraping can Help you Detect Weak spots in your Business

Business intelligence is not a new term. Businesses have always been employing experts for analysing the progress, market and industry trends to keep their growth graph going up. Now that we have big data and the tool to gather this data – Web scraping, business intelligence has become even more fruitful. In fact, business intelligence has become a necessary thing to survive now that the competition is fierce in every industry. This is the reason why most enterprises depend on web scraping solutions to gather the data relevant to their businesses. This data is highly insightful and dependable enough to make critical business decisions. Business intelligence from web scraping is definitely a game changer for companies as it can supply relevant and actionable data with minimal effort.

Most businesses have weak spots that are being overlooked or hidden from the plain sight. These weak spots, if left unnoticed can gradually result in the downfall of your company. Here is how you can use data acquired through web scraping to detect weak spots in your business and strengthen them.

Competitor analysis

Many a times, you can find out the flaws in your business by keeping a close watch on your competitors. Competitor analysis is something that we owe to web scraping as the level of competitive intelligence that you can derive from web scraping has never been achievable in the past. With crawling forums and social media sites where your target audience is, you can easily find out if your competitor is leveraging something you have overlooked. Competitor analysis is all about staying updated to each and every action by your competitors, so that you can always be prepared for their next strategic move. If your competitors are doing better than you, this data can be used to make a comparison between your business and theirs which would give you insights on where you lack.

Brand monitoring on Social media

With social media platforms acting like platforms where businesses and customers can interact with each other, the data available on these sites are increasingly becoming relevant to businesses. Any issues in your business operations will also reflect on your customer sentiments. Social media is a goldmine of sentiment data that can help you detect issues within your company. By analysing the posts that mention your brand or product on social media sites, you can identify what department of your company is functioning well and what isn’t.

For example, if you are an Ecommerce portal and many users are complaining about delivery issues from your company on social media, you might want to switch to a better logistics partner who does a better job. The ability to identify such issues at the earliest is extremely important and that’s where web scraping becomes a life saver. With social media scraping, monitoring your brand on social media is easy like never before and the chances of minor issues escalating to bigger ones is almost non-existent. Brand monitoring is extremely crucial if you are a business operating in the online space. Social media scraping solutions are provided by many leading web scraping companies, which totally eliminates the technical complications associated with the process for you.

Finding untapped opportunities

There are always new and untapped markets and opportunities that are relevant to your business. Finding them is not going to be an easy task with manual and outdated methods of research. Web scraping can fill this gap and help you find opportunities that your company can make use of to leverage your reach and progress. Sometimes, targeting the right audience makes all the difference that you’ve been trying to make. By using web crawling to find mentions of your relevant keywords on the web, you can easily stay updated on your niche and fill in to any new untapped markets. Web crawling for keywords is better explained in our previous blog.

Bottom line

It is not a cakewalk to stay ahead in the competition considering how competitive every industry has become in this digital age. It is crucial to find the weak spots and untapped opportunities of your business before someone else does. Of course, you can always use some help from the technology when you need it. Web scraping is clearly the best way to find and gather data that would help you figure these out. With web crawling solutions that can completely take care of this niche process, nothing is stopping you from using the data and insights that the web has in stock for your business.

Source: https://www.promptcloud.com/blog/web-scraping-detect-weak-spots-business

Wednesday, 17 August 2016

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

How Web Data Extraction Services Will Save Your Time and Money by Automatic Data Collection

Data scrape is the process of extracting data from web by using software program from proven website only. Extracted data any one can use for any purposes as per the desires in various industries as the web having every important data of the world. We provide best of the web data extracting software. We have the expertise and one of kind knowledge in web data extraction, image scrapping, screen scrapping, email extract services, data mining, web grabbing.

Who can use Data Scraping Services?

Data scraping and extraction services can be used by any organization, company, or any firm who would like to have a data from particular industry, data of targeted customer, particular company, or anything which is available on net like data of email id, website name, search term or anything which is available on web. Most of time a marketing company like to use data scraping and data extraction services to do marketing for a particular product in certain industry and to reach the targeted customer for example if X company like to contact a restaurant of California city, so our software can extract the data of restaurant of California city and a marketing company can use this data to market their restaurant kind of product. MLM and Network marketing company also use data extraction and data scrapping services to to find a new customer by extracting data of certain prospective customer and can contact customer by telephone, sending a postcard, email marketing, and this way they build their huge network and build large group for their own product and company.

We helped many companies to find particular data as per their need for example.

Web Data Extraction

Web pages are built using text-based mark-up languages (HTML and XHTML), and frequently contain a wealth of useful data in text form. However, most web pages are designed for human end-users and not for ease of automated use. Because of this, tool kits that scrape web content were created. A web scraper is an API to extract data from a web site. We help you to create a kind of API which helps you to scrape data as per your need. We provide quality and affordable web Data Extraction application

Data Collection

Normally, data transfer between programs is accomplished using info structures suited for automated processing by computers, not people. Such interchange formats and protocols are typically rigidly structured, well-documented, easily parsed, and keep ambiguity to a minimum. Very often, these transmissions are not human-readable at all. That's why the key element that distinguishes data scraping from regular parsing is that the output being scraped was intended for display to an end-user.

Email Extractor

A tool which helps you to extract the email ids from any reliable sources automatically that is called a email extractor. It basically services the function of collecting business contacts from various web pages, HTML files, text files or any other format without duplicates email ids.

Screen scrapping

Screen scraping referred to the practice of reading text information from a computer display terminal's screen and collecting visual data from a source, instead of parsing data as in web scraping.

Data Mining Services

Data Mining Services is the process of extracting patterns from information. Datamining is becoming an increasingly important tool to transform the data into information. Any format including MS excels, CSV, HTML and many such formats according to your requirements.

Web spider

A Web spider is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Many sites, in particular search engines, use spidering as a means of providing up-to-date data.

Web Grabber

Web grabber is just a other name of the data scraping or data extraction.

Web Bot

Web Bot is software program that is claimed to be able to predict future events by tracking keywords entered on the Internet. Web bot software is the best program to pull out articles, blog, relevant website content and many such website related data We have worked with many clients for data extracting, data scrapping and data mining they are really happy with our services we provide very quality services and make your work data work very easy and automatic.

Source: http://ezinearticles.com/?How-Web-Data-Extraction-Services-Will-Save-Your-Time-and-Money-by-Automatic-Data-Collection&id=5159023

Monday, 8 August 2016

Web Scraping Best Practices

Web Scraping Best Practices

Extracting data from the World Wide Web has several challenges as more webmasters are working day and night to lower cases of scraping and crawling of their data in order to survive in the competitive world. There are various other problems you may face when web scraping and most of them can be avoided by adapting and implementing certain web scraping best practices as discussed in this article.

Have knowledge of the scraping tools

Acquiring adequate knowledge of hurdles that may be encountered during web scraping, you will be able to have a smooth web scraping experience and be on the safe side of the law. Conduct a thorough research on the types of tools you will use for scraping and crawling. Firsthand knowledge on these tools will help you find the data you need without being blocked.

Proper proxy software that acts as the middle party works well when you know how to work around HTTP and HTML protocols. Use tools that can change crawling patterns, URLs and data retrieved even when you are crawling on one domain. This will help you abide to the rules and regulations that come with web scraping activities and escaping any legal issues.
Conduct your scraping activities during off-peak hours

You may opt to extract data during times that less people have access for instance over the weekends, during late night hours, public holidays among others. Visiting a website on several instances to retrieve the same type of data is a waste of bandwidth. It is always advisable to download the entire site content to your computer and thereafter you can access it whenever need arises.
Hide your scrapping activities

There is a thin line between ethical and unethical crawling hence you should completely evade being on the top user list of a particular website. Cover up your track as best as you can by making use of proxy IPs to avoid any legal problems. You may also use multiple IP addresses or VPN services to conceal your scrapping activities and lower chances of landing on a website’s blacklist.

Website owners today are very protective of their data and any other information existing under their unique url. Be keen when going through the terms and conditions indicated by websites as they may consider crawling as an infringement of their privacy. Simple etiquette goes a long way. Your web scraping efforts will be fruitful if the site owner supports the idea of sharing data.
Keep record of your activities

Web scraping involves large amount of data.Due to this you may not always remember each and every piece of information you have acquired, gathering statistics will help you monitor your activities.
Load data in phases

Web scraping demands a lot of patience from you when using the crawlers to get needed information. Take the process in a slow manner by loading data one piece at a time. Several parallel request to the same domain can crush the entire site or retrace the scrapping attempts back to your local machine.

Loading data small bits will save you the hustle of scrapping afresh in case that your activity has been interrupted because you will have already stored part of the data required. You can reduce the loading data on an individual domain through various techniques such as caching pages that you have scrapped to escape redundancy occurrences. Use auto throttling mechanisms to increase the amount of traffic to the website and pause for breaks between requests to prevent getting banned.
Conclusion

Through these few mentioned web scraping best practices you will be able to work around website and gather the data required as per clients’ request without major hurdles along the way. The ultimate goal of every web scraper is to be able to access vital information and at the same time remain on the good side of the law.

Source: http://nocodewebscraping.com/web-scraping-best-practices/

Thursday, 4 August 2016

Data Discovery vs. Data Extraction

Data Discovery vs. Data Extraction

Looking at screen-scraping at a simplified level, there are two primary stages involved: data discovery and data extraction. Data discovery deals with navigating a web site to arrive at the pages containing the data you want, and data extraction deals with actually pulling that data off of those pages. Generally when people think of screen-scraping they focus on the data extraction portion of the process, but my experience has been that data discovery is often the more difficult of the two.

The data discovery step in screen-scraping might be as simple as requesting a single URL. For example, you might just need to go to the home page of a site and extract out the latest news headlines. On the other side of the spectrum, data discovery may involve logging in to a web site, traversing a series of pages in order to get needed cookies, submitting a POST request on a search form, traversing through search results pages, and finally following all of the "details" links within the search results pages to get to the data you're actually after. In cases of the former a simple Perl script would often work just fine. For anything much more complex than that, though, a commercial screen-scraping tool can be an incredible time-saver. Especially for sites that require logging in, writing code to handle screen-scraping can be a nightmare when it comes to dealing with cookies and such.

In the data extraction phase you've already arrived at the page containing the data you're interested in, and you now need to pull it out of the HTML. Traditionally this has typically involved creating a series of regular expressions that match the pieces of the page you want (e.g., URL's and link titles). Regular expressions can be a bit complex to deal with, so most screen-scraping applications will hide these details from you, even though they may use regular expressions behind the scenes.

As an addendum, I should probably mention a third phase that is often ignored, and that is, what do you do with the data once you've extracted it? Common examples include writing the data to a CSV or XML file, or saving it to a database. In the case of a live web site you might even scrape the information and display it in the user's web browser in real-time. When shopping around for a screen-scraping tool you should make sure that it gives you the flexibility you need to work with the data once it's been extracted.

Source: http://ezinearticles.com/?Data-Discovery-vs.-Data-Extraction&id=165396