Table of Contents
Introduction
When you collect product data from huge e-commerce websites like Alibaba you get a great opportunity to do comprehensive competitive research, market analysis, and price comparison. It is one of the leading e-commerce portals with an enormous product catalog. However, extracting the required Alibaba data is a real challenge if you are not familiar with web scraping. But if you know the stuff and have some coding skills go through this article to find out how to extract Alibaba products’ data through Scrapy – one of the most widely used open-source frameworks for web scraping.
3 Reasons to Scrape Alibaba.com
Data extracted from e-commerce websites is a potential help to businesses that are in e-commerce and not only. Keep reading to learn three main reasons why you need to scrape data from Alibaba.
Cataloging and listing
For any e-commerce business listing and cataloging competitors’ products
are the most important thing. Without an up-to-date and comprehensive
product list, it is impossible to compete in the e-commerce market. So,
using Alibaba extractor, you can easily get Alibaba info and build your
own product list based on your target audience’s demands and preferences
or even create a new category of products.
Analyzing data
To do complete market research companies strive to get insights from the
buyers’ feedbacks like ratings and reviews. This user-generated content
will give you a clear sign of a particular product or brand. This kind
of data might be used to improving your current products or offer a new
one as well as build a positive brand reputation.
Comparing prices
Today Alibaba is well known for its affordable prices, that’s why it is
crucial to extract its prices for further price comparison and
optimization. Almost all e-commerce users are tracking product prices,
and Alibaba may be the most popular source to track in the first turn.
So, if you want to know prices in the market to optimize your price
strategy, start with Alibaba scraping!
How to Create an Alibaba Crawler
Written in Python, Scrapy is one of the most efficient free frameworks for web scraping that enables the users to extract, manage, and store information in a structured data format. It is perfectly adapted for web crawlers extracting details from various pages. Let’s move forward to learn how to scrape data from the leading marketplace.Getting started
To create an Alibaba crawler you need to have Python 3 and PIP. Follow the links to download them: To install the necessary packages, the following command is used:
To generate our crawler that will create spiders/scrapy_alibaba.py file
it should be:
The complete code should look like:
Extracting Product Data from Alibaba
In this example, we’re going to extract the following fields for the earphones: https://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchText=earphones&viewtype=G</a > To extract the required data from Alibaba we’re going through the following 3 steps:- Create a Selectorlib library
- Create a keyword file
- Export data in the required format
Creating a Selectorlib pattern for Alibaba
Selectorlib is a Chrome extension enabling users to point out the required data and create CSS Selectors or XPaths to extract that data. To learn more about Selectorlib go to the following link https://selectorlib.com/getting-started.html</a > Below you may find how we point out the fields in the code for the required data we need to extract from Alibaba using Selectorlib
When you marked all the required data, click on the
Export button to download the YAML
file and save it as
search_results.yml in the folder
named
/resources
Reading keywords
Now we’re going to set up the Alibaba crawler to read specific keywords from a certain file placed in the folder /resources. Let’s create there a CSV file named keywords.csv and use Python’s CSV module to read our keywords file.
Exporting data into CSV or JSON
With Scrapy you can have in-built JSON and CSV formats. To save the extracted data in the desired format just use the appropriate command line
The output will be saved in the same folder as the script. Here is an
example of extracted data in CSV
The full code for our Alibaba crawler is given below: (code source:
https://github.com/scrapehero/alibaba-scraper/blob/master/scrapy_alibaba/spiders/alibaba_crawler.py</a >)
Final Thoughts
To sum up, we can state that creating the Alibaba crawler is not an easy task. So, if you make up your mind to outsource Alibaba product data extraction to a dedicated web scraping service, a provider like DataOx will free you of the complications in web crawling. Schedule a free consultation with our expert</a > to reveal the whole list of our web scraping services and learn how DataOx can help you to scrape Alibaba data on a large scale.
