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webscreenscraping · 4 years ago

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How To Extract Alibaba Product Data Using Python And Beautiful Soup?

Now we will see how to Extract Alibaba Product data using Python and BeautifulSoup in a simple and elegant manner.

The purpose of this blog is to start solving many problems by keeping them simple so you will get familiar and get practical results as fast as possible Alibaba Product Data Scraper is useful for taking profitable business desicion in e-commerce sector.

Initially, you need to install Python 3. If you haven’t done, then please install Python 3 before you continue.

You can mount Beautiful Soup with:

pip3 install beautifulsoup4

We also require the library's needs soup sieve, lxml, and to catch data, break down to XML, and utilize CSS selectors.

pip3 install requests soupsieve lxml

Once it is installed you need to open the editor and type in:

# -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requests

Now go to the Alibaba list page and look over the details we need to get.

Get back to code. Let’s acquire and try that information by imagining we are also a browser like this:

Save this as scrapeAlibaba.py

If you run it.

python3 scrapeAlibaba.py

You will be able to see the entire HTML side.

Now, let’s utilize CSS selectors to get the data you require. To ensure that you need to go to Chrome and open the review tool.

We observe all the specific product data contains a class ‘organic-gallery-offer-outter’. We scrape this with the CSS selector ‘. organic-gallery-offer-outter’ effortlessly. Here is the code, let’s see how it will look like:

This will print all the remaining content in every container that clutches the product information.

We can choose the classes inside the given row that holds the information we require.

# -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requestsheaders = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'} url = 'https://www.alibaba.com/catalog/power-tools_cid1417?spm=a2700.7699653.scGlobalHomeHeader.548.7bc23e5fdb6651'response=requests.get(url,headers=headers)soup=BeautifulSoup(response.content,'lxml')#print(soup.select('[data-lid]')) for item in soup.select('.organic-gallery-offer-outter'): try: print('----------------------------------------') print(item) print(item.select('.organic-gallery-title__content')[0].get_text().strip()) print(item.select('.gallery-offer-price')[0].get_text().strip()) print(item.select('.gallery-offer-minorder')[0].get_text().strip()) print(item.select('.seb-supplier-review__score')[0].get_text().strip()) print(item.select('[flasher-type=supplierName]')[0].get_text().strip()) print(item.select('.seb-img-switcher__imgs img')[0]['src']) except Exception as e: #raise e print('')

Once it is run, it will print all the information.

If you need to use this product and want to scale millions of links, then you will see that your IP is getting blocked by Copy Blogger. In this situation use a revolving proxy service to rotate IPs is necessary. You can use a service like Proxies API to track your calls via millions of inhabited proxies.

If you need to measure the crawling pace or you don’t need to set up your structure, you can easily utilize our Cloud base crawler. So that you can easily crawl millions of URLs at a high pace from crawlers.

If you are looking for Alibaba Product Data Scraping Services, then you can contact Web Screen Scraping for all your queries.

#alibabaproductscraper #alibabaProductdatascraping #scrapealibabaproduct #extractalibabaproductdata

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retailgators · 4 years ago

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How to Extract Alibaba Product Data with Scrapy - Extract Alibaba Product Data

Extracting information from E-Commerce sites such as Alibaba, Amazon, eBay, help to provide enormous opportunity for competitors, market research, and price comparison firm. Being among the foremost e-commerce companies, Alibaba products catalog is huge and handy to anyone who is looking to extract data. Extracting Alibaba Product Data can be difficult if you are not having accurate resources and team to perform Alibaba Product Data Extracting. Outsourcing Alibaba extracting helps you to fulfill all your requirements with dedicated scraping services.

Installing Python 3 with Pip

We utilize Python 3 in this Blog. To begin, you require a PC using Python 3 as well as PIP.

Mac: - http://docs.python-guide.org/en/latest/starting/install3/osx/

Linux: - http://docs.python-guide.org/en/latest/starting/install3/linux/

Window: - https://www.retailgators.com/how-to-install-python3-in-windows-10/

PackagesInstallpip3 install scrapyselectorlib

Find out more information by installing here -

https://doc.scrapy.org/en/latest/intro/

Creating Scrapy Projects

Let us create scrapy task using the command given below.

scrapystartprojectscrapy_alibaba

It can help to create Scrapy task with the help of Name of Project (scrapy_alibaba) as folder name. This contains all required files with accurate structure as well as basics with each file.

from selectorlib import Extractorscrapy_alibaba/ # Project root directoryscrapy.cfg # Contains the configuration information to deploy the spiderscrapy_alibaba/ # Project's python module__init__.pyitems.py # Describes the definition of each item that we’re scrapingmiddlewares.py # Project middlewarespipelines.py # Project pipelines filesettings.py # Project settings filespiders/ # All the spider code goes into this directory__init__.pyCreating a Spider

The Scrapy has built a command named genspiderso that you can produce the fundamental spider templet.

scrapygenspider(spidername)(website)

Let’s produce our spider

scrapygenspideralibaba_crawleralibaba.com

This will help to create a file spider/scrapy_alibaba.py for recent templets for crawling Alibaba.com

This code is shown here:importscrapyclassAlibabaCrawlerSpider(scrapy.Spider):name = 'alibaba_crawler'allowed_domains = ['alibaba.com']start_urls = ['http://alibaba.com/']defparse(self, response):passSearching Keywords from the file

Let us make the CSV file it named keywords.csv.

This file shows that if we want to search distinctly for earplugs and headphones.

keywordsheadphonesearplugs

It’s time to use CSV Python’s standard module for reading the keyword file.

defparse(self, response):"""Function to read keywords from keywords file"""keywords = csv.DictReader(open(os.path.join(os.path.dirname(__file__),"../resources/keywords.csv")))for keyword in keywords:search_text = keyword["keyword"]url = "https://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchText={0}&viewtype=G".format(search_text)yieldscrapy.Request(url, callback=self.parse_listing, meta={"search_text":search_text})A Complete Scrapy Spider’s Code

You can see the whole code at - https://contactus/retailgators/alibaba-scraper

A spider called alibaba_crawler will look at

https://contactus/retailgators/alibaba-scraper/blob/master/scrapy_alibaba/spiders/alibaba_crawler.py

https://contactus/retailgators/Let’s run this scraper with

scrapy crawl alibaba_crawlerDEBUG: Forbidden by robots.txt:

It is because Alibaba’s website has discovered to crawl different URLs array /trade. So, you can easily that by visiting robots.txt file, positioned at https://www.alibaba.com/robots.txt

Export Products data inCSV & JSON using Scrapy

The Scrapy offers in-built JSON & CSV formats for output.

scrapy crawl (spidername) -o output_filename.csv -t csvscrapy crawl (spidername) -o output_filename.json -t jsonCSV output:scrapycrawlalibaba_crawler-oalibaba.csv-tcsvJSON Output:scrapycrawlalibaba_crawler-oalibaba.csv-tjsonList of Data Fields

At RetailGators, we extract data for Alibaba Web Data Scraping Services. Data Fields are given below:

Name of Product

Product Price Range

Images of Product

Product Links

Minimum Product Order

Name of Seller

Seller Reply Rate

Number of sellers on Alibaba

Key Features of Alibaba Web Scraping Solutions

RetailGators help you to provide fully customized eCommerce Data Scraping that are accessible to deal with data requirements for big companies. Quality and Stability are one of the most important factors if data crawling is concerned. Many DIY Tools are available for scraping through in-house resources.

Here are some of the Key Advantages which is given below: -

Fully-Customized

Many Alternative Data Delivery

Fully manageable Solutions

High-Quality & Well-Structured Data

What we can scrape from Alibaba?

Website data can help the company to fill the intelligence gap in the association. Here are few things you can do with data scraping from Alibaba.

Price Comparison Data

Cataloging Data

Analyses

Why RetailGators?

If you are looking for the best Alibaba Web Data Scraping Services, then you can contact RetailGators for all your queries.

#ExtractAlibabaProductData

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retailgators · 4 years ago

Text

How to Extract Alibaba Product Data with Scrapy - Extract Alibaba Product Data

DEBUG: Forbidden by robots.txt:

Installing Python 3 with Pip

We utilize Python 3 in this Blog. To begin, you require a PC using Python 3 as well as PIP.

Mac: - http://docs.python-guide.org/en/latest/starting/install3/osx/

Linux: - http://docs.python-guide.org/en/latest/starting/install3/linux/

Window: - https://www.retailgators.com/how-to-install-python3-in-windows-10/

PackagesInstall

pip3 install scrapyselectorlib

Find out more information by installing here -

https://doc.scrapy.org/en/latest/intro/

Creating Scrapy Projects

Let us create scrapy task using the command given below.

scrapystartprojectscrapy_alibaba

It can help to create Scrapy task with the help of Name of Project (scrapy_alibaba) as folder name. This contains all required files with accurate structure as well as basics with each file.

from selectorlib import Extractor scrapy_alibaba/ # Project root directory scrapy.cfg # Contains the configuration information to deploy the spider scrapy_alibaba/ # Project's python module __init__.py items.py # Describes the definition of each item that we’re scraping middlewares.py # Project middlewares pipelines.py # Project pipelines file settings.py # Project settings file spiders/ # All the spider code goes into this directory __init__.py

Creating a Spider

The Scrapy has built a command named genspiderso that you can produce the fundamental spider templet.

scrapygenspider(spidername)(website)

Let’s produce our spider

scrapygenspideralibaba_crawleralibaba.com

This will help to create a file spider/scrapy_alibaba.py for recent templets for crawling Alibaba.com

This code is shown here:

importscrapy classAlibabaCrawlerSpider(scrapy.Spider): name = 'alibaba_crawler' allowed_domains = ['alibaba.com'] defparse(self, response): pass

Searching Keywords from the file

Let us make the CSV file it named keywords.csv.

This file shows that if we want to search distinctly for earplugs and headphones.

keyword

sheadphones

earplugs

It’s time to use CSV Python’s standard module for reading the keyword file.

defparse(self, response):

"""Function to read keywords from keywords file"""

keywords = csv.DictReader(open(os.path.join(os.path.dirname(__file__),"../resources/keywords.csv")))

for keyword in keywords:

search_text = keyword["keyword"]

url = "https://www.alibaba.com/trade/search?fsb=y&IndexArea=product_en&CatId=&SearchText={0}&viewtype=G".format(search_text)

yieldscrapy.Request(url, callback=self.parse_listing, meta={"search_text":search_text})

A Complete Scrapy Spider’s Code

You can see the whole code at - https://contactus/retailgators/alibaba-scraper

A spider called alibaba_crawler will look at

https://contactus/retailgators/alibaba-scraper/blob/master/scrapy_alibaba/spiders/alibaba_crawler.py

https://contactus/retailgators/Let’s run this scraper with

scrapy crawl alibaba_crawler

It is because Alibaba’s website has discovered to crawl different URLs array /trade. So, you can easily that by visiting robots.txt file, positioned at https://www.alibaba.com/robots.txt

Export Products data inCSV & JSON using Scrapy

The Scrapy offers in-built JSON & CSV formats for output.

scrapy crawl (spidername) -o output_filename.csv -t csv scrapy crawl (spidername) -o output_filename.json -t json

CSV output:

scrapycrawlalibaba_crawler-oalibaba.csv-tcsv

JSON Output:

scrapycrawlalibaba_crawler-oalibaba.csv-tjson

List of Data Fields

At RetailGators, we extract data for Alibaba Web Data Scraping Services. Data Fields are given below:

Name of Product

Product Price Range

Images of Product

Product Links

Minimum Product Order

Name of Seller

Seller Reply Rate

Number of sellers on Alibaba

Key Features of Alibaba Web Scraping Solutions

Here are some of the Key Advantages which is given below: -

Fully-Customized

Many Alternative Data Delivery

Fully manageable Solutions

High-Quality & Well-Structured Data

What we can scrape from Alibaba?

Website data can help the company to fill the intelligence gap in the association. Here are few things you can do with data scraping from Alibaba.

Price Comparison Data

Cataloging Data

Analyses

Why RetailGators?

If you are looking for the best Alibaba Web Data Scraping Services, then you can contact RetailGators for all your queries.

Source:- https://www.retailgators.com/how-to-extract-alibaba-products-data-with-scrapy.php

#AlibabaProductDataScraper #AlibabaDataScraping #AlibabaProductDataScraping #ExtractAlibabaProductData #AlibabaScrapingServices #ScrapeAlibabaProductData

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