Tuesday, January 28, 2020

Best Way to Grab Aliexpress Products

Scraping Aliexpress

Are you looking for the best way for scraping Aliexpress products?? – This guide is for you. Know about Aliexpress product scraper and more about scraping Ecommerce websites.
Aliexpress is a giant ecommerce site based in China. Small businesses within and around China make this website. It contains lots of products, which are available to international buyers who wish to make transactions online.
Whether for personal, business, or research purposes, AliExpress contains lots of products and product details, which may be useful. It helps in market trend analysis, price comparison, consumer behavior analysis, sentiment analysis, knowing sales offer and strategy, ship dropping.
Most individuals, business owners, and researchers seek ways to extract these products and their details from Aliexpress. While there are various ways for scraping Aliexpress products, they may not be the best ways.
For instance, you may decide to manually extract (copy and paste) these product details from Aliexpress but this is time consuming and never a wise choice for smart individuals. Brilliant individuals may visit GitHub to download javascript or python Aliexpress crawlers, but this requires a level of coding and programming, which can go messy for individuals without adequate knowledge on programming.
So, the best way to extract information easily, efficiently, and timely from AliExpress requires the use of Aliexpress product scraper. This smart tool can scrape Aliexpress products without writing any code. So experienced and inexperienced both users can use it easily.

It Is Possible To Grab Following Data Points By Scraping Aliexpress:

Product name, product descriptions, pricing of products, product images, product variants, sellers’ contact information, shipping details, categories with structure, and customers’ reviews and ratings, etc. Know more about Aliexpress scraper and its features.
This Aliexpress product scraper tool is developed by professional Aliexpress data scraping services to extract Aliexpress products for their clients.
Why should you waste so much time extracting products manually on Aliexpress or trying codes you don’t understand when you can hire an Aliexpress scraping service at an affordable rate?
Depending on your need, Aliexpress scraping service can save the extracted data in various formats, such as CSV, Excel, Txt, XML, JSON, HTML, etc.
If you’re looking for the best Aliexpress product scraping services to help you handle your Aliexpress product scraping needs in the most effective manner, contact us today for a free quote. We are the experts in scraping Ecommerce websites like Amazon, Ebay, Walmart, Bigbasket and more in various countries. Check our data scraping work sample on our portfolio and get better understanding about our work.

Monday, January 20, 2020

How to Collect Company’s Information from Kompass ?

Business Directory Scraping

Only solution is Kompass scraper further more we can say Business directory scraping.
Kompass is a large database of companies’ information and contact details. This makes Kompass one of the leading business directories, a very good source of business data, and a platform where B2B and B2C business owners can find and communicate with prospects. It is available in various countries and contains a huge amount of business data.

Our Kompass Scraper Extracts:

  • About the company
  • Activity
  • Business location and address
  • Business name
  • URL
  • Category
  • Contact no
  • Employee
  • Executive name
  • Executive position
  • Export
  • Email addresses
  • Website
  • Year of established
Above all, specific field can be extracted.
For any business owner, it is always a great challenge to find marketing lists and the right prospects. Whether the business data is needed for direct mail campaigns, events, digital marketing, email, or telesales. Therefore, it is important to have access to up-to-date and accurate company information and contact details.

Advantage of Business Directory Scraping:

However, manually extracting a large amount of these business data from Kompass is nothing but a waste of time. The smartest and best way to go about collecting the company’s information from Kompass is using Kompass scraper or any other business directory data scraping service.
With Kompass data scraping, you would get an up-to-date and accurate company’s information for over 33 million companies and contacts of over 35 million business executives. You can also decide to focus your data scraping on a specific data field using Kompass data scraping services.
Kompass scraper not only collect the company’s information but also refine, clean, and store the data into a well-structured format. Kompass scraper is a powerful tool that helps business owners to find business leads and prospects from Kompass classifieds by locations and categories. Data scraping services enable business owners to get millions of business leads within their fingertips. Above all, the benefits that leads to Business directory scraping.
In other words, web scraping services is always at top priority by business owners.
One of the best and affordable Kompass data scraping service providers is Infovium web scraping scraping services. However, you can check sample file of Kompass data scraping. Infovium offers a wide range of business directory scraping solutions using powerful automated tools. Similarly, We provide Yellow pages scraperYelp data scraping, White pages scraping, Bloomberg data scraping, Yell data scraping, Owler data scraping, Hoovers data scraping, Justdial data scraping and more. In addition, we extract data from social networking sites, Ecommerce websites, Real estate sites and more.Contact us today.

Thursday, January 16, 2020

How to Scrape Product Data from Amazon using C-Sharp?




This Tutorial will explain you how we can extract product data from amazon.com using C sharp amazon scraper

Have you heard about amazon Data Scraping ?? It is a way to Scrape amazon Products data from amazon.com by Automated way using C Sharp.
amazon data scraper provides updated product information along with changing prices, reviews ,and more..

We can perform amazon data scraping and Extract Following Data using C Sharp amazon data scraper.

  • Product title
  • URL
  • ASIN
  • UPC
  • Item Model Number
  • No Of Reviews
  • Sales Rank Final
  • No Of Ratings
  • Product Dimensions
  • Best Seller Rank
  • Shipping Weight
  • Category
  • Price

how to scrape data from amazon using c sharp ?

Screen shot  from data will be extracting

Inspecting element for data extractions from amazon.com
To find appropriate data from website first we have to  inspecting and understanding html tag  which is associated with given data ..
please follow below steps to finding tags
  • Open browser (Google Chrome , Mozilla )
  • Copy and paste url you want to scrape.

Press F12 to view HTML structure of given site

  • find html tags for  require data and implement in C Sharp coding

C-Sharp Code to Scrape amazon.com
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.IO;
using System.Linq;
using System.Net;
using HtmlAgilityPack;
using Newtonsoft.Json;
using Newtonsoft.Json.Linq;
namespace amazon
{
class Program
{
/// <summary>
/// Store Data to Json format
/// </summary>
/// <param name=”args”></param>
static void Main(string[] args)
{
string url = string.Empty;
string strHtml = string.Empty;
//Console.WriteLine(“Please Enter URL :- “);
Console.WriteLine(“Please enter url:”);
url = Console.ReadLine();
Console.WriteLine(“Fetch Data From URL {0} …”, url);
strHtml = GetRequest(url);
object result = DataParse(strHtml);
Console.WriteLine(“Result :”);
Console.WriteLine(JsonConvert.SerializeObject(result, Formatting.Indented));
Console.ReadLine();
}
/// Lib Reference
///  1 : using System.Net;
///  2 : using System.IO;
///  3 : using System.Text;
/// </summary>
/// <param name=”url”></param>
/// <returns></returns>
public static string GetRequest(string url)
{
string strhtml = String.Empty;
HttpWebRequest request = (HttpWebRequest)WebRequest.Create(url);
request.AutomaticDecompression = DecompressionMethods.GZip;
request.UserAgent =
“Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36″;
using (HttpWebResponse response = (HttpWebResponse)request.GetResponse())
using (Stream stream = response.GetResponseStream())
using (StreamReader reader = new StreamReader(stream))
{
strhtml = reader.ReadToEnd();
}
return strhtml;
}
/// <summary>
/// This method is use to parse data from string
/// Return object with data
/// Lib Reference
///  1 : using HtmlAgilityPack;
///  2 : using Newtonsoft.Json;
///  3 : using Newtonsoft.Json.linq;
/// </summary>
/// <param name=”strHtml”></param>
/// <returns></returns>
public static object DataParse(string strHtml)
{
string Asin = String.Empty;
string url = String.Empty;
string Upc = String.Empty;
string Itemmodelnumber = String.Empty;
string price = String.Empty;
//string Shippingcost = String.Empty;
//string availability = String.Empty;
string Bsr = String.Empty;
string Salesrankfinal = String.Empty;
string Noofreviews = String.Empty;
string Noofratings = String.Empty;
//string productdescription = String.Empty;
string Productdimensions = String.Empty;
string Shippingweight = String.Empty;
string category = String.Empty;
List<string> hours = new List<string>();
HtmlAgilityPack.HtmlDocument htmlDocument = new HtmlAgilityPack.HtmlDocument();
htmlDocument.LoadHtml(strHtml);
htmlDocument.DocumentNode.Descendants()
.Where(n => n.Name == “script” || n.Name == “style”)
.ToList()
.ForEach(n => n.Remove());
// strJson = htmlDocument.DocumentNode.SelectSingleNode(“//script[@type=’application/ld+json’]”).InnerText;
//JObject jObject = JObject.Parse(strJson);
Asin = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“ASIN:”)).FirstOrDefault().InnerText.Replace(“ASIN:”,””).Trim();
Upc = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“UPC:”)).FirstOrDefault().InnerText.Replace(“UPC:”, “”).Trim();
Itemmodelnumber = htmlDocument. DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Item model number:”)).FirstOrDefault().InnerText.Replace(“Item model number:”, “”).Trim();
Noofreviews = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Average Customer Review:”)).FirstOrDefault().SelectSingleNode(“.//span[@class = ‘a-size-small’]”).InnerText.Replace(“customer reviews”, “”).Trim();
Salesrankfinal = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Amazon Best Sellers Rank:”)).FirstOrDefault().SelectSingleNode(“.//ul[@class = ‘zg_hrsr’]”).InnerText.Trim().Replace(“Amazon Best Sellers Rank:”, “”).Replace(“&nbsp;”,””).Replace(“&gt;”,””).Replace(“\n”,””).Trim();
//Noofratings =  htmlDocument.DocumentNode
//    .SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“customer reviews”)).FirstOrDefault().InnerText.Replace(“customer reviews”, “”).Replace(“,”, “”).Trim();
Noofratings = htmlDocument.DocumentNode.SelectSingleNode(“//span[@id = ‘acrPopover’]/span[1]/a/i[1]/span”)
.InnerText.Trim();
//productdescription = htmlDocument.DocumentNode
//.SelectSingleNode(“//div[@id=’productDescription’]/ul”).InnerText.Trim();
Productdimensions = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Product Dimensions:”)).FirstOrDefault().InnerText.Replace(“Product Dimensions:”, “”).Replace(“; 1.6 ounces”, “”).Trim();
Shippingweight = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Shipping Weight:”)).FirstOrDefault().InnerText.Replace(“Shipping Weight:”, “”).Trim().Replace(“(View shipping rates and policies)”, “”);
//Shippingweight = Productdimensions.Substring(Productdimensions.IndexOf(“;”)).Replace(“;”, “”);
category = htmlDocument.DocumentNode.SelectSingleNode(“//span[@id=’productTitle’]”).InnerText.Trim();
price = htmlDocument.DocumentNode.SelectSingleNode(“//span[@class=’a-color-price’]”).InnerText.Trim();
//Shippingcost = htmlDocument.DocumentNode.SelectSingleNode(“//span[@id=’ourprice_shippingmessage’]/span”).InnerText.Trim();
//availability = htmlDocument.DocumentNode.SelectSingleNode(“//span[@id=’availability’]”).InnerText.Trim();
Bsr = Salesrankfinal.Substring(Salesrankfinal.IndexOf(“#”)).Replace(“#”, “”);
Bsr = htmlDocument.DocumentNode.SelectNodes(“//div[@class=’content’]/ul/li”).ToList().Where(x => x.InnerText.Contains(“Amazon Best Sellers Rank:”)).FirstOrDefault().InnerText.Replace(“Amazon Best Sellers Rank:”, “”);
Bsr = Bsr.Substring(Bsr.IndexOf(“#”)).Replace(“#”,””);
Bsr = Bsr.Substring(0, Bsr.IndexOf(“(“));
url = htmlDocument.DocumentNode.SelectSingleNode(“//link[@rel = ‘canonical’]”).Attributes[“href”].Value;
return new
{
URL = url,
ASIN = Asin,
UPC = Upc,
ItemModelNumber = Itemmodelnumber,
NoofReviews = Noofreviews,
SalesrankFinal = Salesrankfinal,
NoofRatings = Noofratings,
//productDescription = productdescription,
ProductDimensions = Productdimensions,
//Availability = availability,
BSR = Bsr,
ShippingWeight = Shippingweight,
Category = category,
Price = price,
//ShippingCost = Shippingcost,
};
}
}
}
Above code is developed in C-sharp   so  To Run this Code you need to use Visual Studio .   Develop all packages in one folder with above code …
Output file :- JSon
Clarification :- This  code available in this tutorial is  only learning purpose . We are not responsible for how it is used and assume no liability for any detrimental usage of the source code. This code is only  use for knowledge expansion regarding programming field.. by this tutorial we are not encourage amazon scraping or web scraping but will help to understand scraping.. also we are not responsible to provide any support for this code .. user can modify for learning purpose..

Tuesday, January 7, 2020

How Web Scraping Services Help To Gather Hotels Data?


Have You Heard About Web Scraping Hotel Prices?

Web scraping hotels data scrape hotels data from most running hotel booking websites by automated stuff in fastest manner. Moreover this service is popular as web scraping hotel prices and reviews. As  it is widely used for gathering prices and reviews of hotels. In other words, it is known as Hotel data scraping.
One of the most competitive industries is travel industry and it is dominated by the transportation and accommodation services, of which the hotel service is one.
Tourists and prospective travelers need to get regular hotel data for comparison and to make travel plans while hotel managers need hotel data including customer reviews for some business analyses to enhance their services. Hence, both hotel owners and tourists need to gather hotel data to their advantage.
There are several hotel and accommodation booking websites, such as TripAdvisor.com, Hotwire.com, Travelocity.com, Booking.com, Trivago.com, Expedia.com, etc. that have relevant and up-to-date hotel data. Each of these websites has lots of data on hotels from all around the world.

Scrape Hotels Data From Hotel Booking Websites Includes:

  • Hotel names
  • Room prices
  • Ratings
  • Addresses (e.g. street, city, state, country, and postal code)
  • Hotel facilities
  • Hotel Descriptions
  • Websites
  • Phone/Fax numbers
  • Occupancies
  • Room types
  • Hotel Image URL
  • Hotel Pictures
And any other useful data found on the webpage!

Usefulness Of Hotels Data Scraping:

Monitoring Price Trend and Services
Web scraping Hotel prices can help you to know the prices your competitors offer so you can adjust your prices in a timely manner to attract more customers. You can also study the rating of hotels from hotel data to make necessary improvements in your hotel services.
Predicting Occupancy Rate
Hotel data can help to predict when hotels have the lowest or highest occupancy rate.Therefor this is very important to develop an effective pricing strategy.
Sentiment Analysis
Hotel data is also useful for sentiment analysis; to know what your tourists are saying your brand or your competitors, to know how they feel about your hotel and the services you offered.
You can also use hotel data to develop an effective marketing strategy and create the best hotel deals.
Above all, it takes to scrape hotels data.
Considering the number of hotel booking websites available and the large amount of hotel data on each website, it is impractical to attempt scraping hotel data manually. This is where web scraping services becomes important for data collection.
Web scraping services can extract hotel data from any hotel and travel website or hotel booking website. How Travel, restaurant and hotel data scraping works? Automatic web scraping services like Infovium can be a very smart option if you want to scrape hotels data quickly, efficiently, and at a low cost.
Web scraping services is very useful because it doesn’t require any coding at all, doesn’t require your input in any way, and is very cost-effective.
More so, the scraped data will be cleaned; well-structured; void of errors, duplicates or invalid URLs; and delivered in the right format required by the customer. To have practical experience of how web scraping services can help you to gather hotel data, consult Infovium web scraping services today.
Check our Tripadvisor data scraping sample file to get idea about data and headers.