amazon-python-scrapy-scraper

Python Scrapy spider that searches Amazon for a particular keyword, extracts each products ASIN ID and scrape all the main information from the product page. The spider will iterate through all pages returned by the keyword query. The following are the fields the spider scrapes for the Amazon product page:

• ASIN
• Product name
• Image url
• Price
• Description
• Available sizes
• Available colors
• Ratings
• Number of reviews
• Seller rank

Proxy Solution

This Amazon spider uses Scraper API as the proxy solution. Scraper API has a free plan that allows you to make up to 1,000 requests per month which makes it ideal for the development phase, but can be easily scaled up to millions of pages per month if needs be.

Monitoring Solution

To monitor our scraper,this spider uses ScrapeOps, a free monitoring tool specifically designed for web scraping.

Live demo here: ScrapeOps Demo

Using the Amazon Spider

Make sure Scrapy is installed:

pip install scrapy

Set the keywords you want to search in Amazon.

queries = ['tshirt for men', ‘tshirt for women’]

Setting Up ScraperAPI

Signup to Scraper API and get your free API key that allows you to scrape 1,000 pages per month for free. Enter your API key into the API variable:

API = ‘<YOUR_API_KEY>’

def get_url(url):
    payload = {'api_key': API, 'url': url}
    proxy_url = 'http://api.scraperapi.com/?' + urlencode(payload)
    return proxy_url

To activate geotageting, JS rendering, residential proxies, etc. then just add an extra parameter to the payload. Example: geotargeting requests from the United States.

def get_url(url):
    payload = {'api_key': API, 'url': url, 'country_code': 'us'}
    proxy_url = 'http://api.scraperapi.com/?' + urlencode(payload)
    return proxy_url

By default, the spider is set to have a max concurrency of 5 concurrent requests as this the max concurrency allowed on Scraper APIs free plan. If you have a plan with higher concurrency then make sure to increase the max concurrency in the settings.py.

## settings.py

CONCURRENT_REQUESTS = 5
RETRY_TIMES = 5

# DOWNLOAD_DELAY
# RANDOMIZE_DOWNLOAD_DELAY

We should also set RETRY_TIMES to tell Scrapy to retry any failed requests (to 5 for example) and make sure that DOWNLOAD_DELAY and RANDOMIZE_DOWNLOAD_DELAY aren’t enabled as these will lower your concurrency and are not needed with Scraper API.

Integrating ScrapeOps

ScrapeOps is already integrated into the scraper via the settings.py file. However, to use it you must:

Install the ScrapeOps Scrapy SDK on your machine.

pip install scrapeops-scrapy

And sign up for a free ScrapeOps account here so you can insert your API Key into the settings.py file:

    ## settings.py
    
    ## Add Your ScrapeOps API key
    SCRAPEOPS_API_KEY = 'YOUR_API_KEY'
    
    ## Add In The ScrapeOps Extension
    EXTENSIONS = {
     'scrapeops_scrapy.extension.ScrapeOpsMonitor': 500, 
    }
    
    ## Update The Download Middlewares
    DOWNLOADER_MIDDLEWARES = { 
	'scrapeops_scrapy.middleware.retry.RetryMiddleware': 550, 
	'scrapy.downloadermiddlewares.retry.RetryMiddleware': None, 
    }

From there, our scraping stats will be automatically logged and automatically shipped to our dashboard.

Running The Spider

To run the spider, use:

scrapy crawl amazon -o test.csv

Editing the Amazon Spider

The spider has 4 parts:

1. start_requests - will send a search query Amazon with a particular keyword.
2. parse_keyword_response - will extract the ASIN value for each product returned in the Amazon keyword query, then send a new request to Amazon to return the product page of that product. It will also move to the next page and repeat the process.
3. parse_product_page - will extract all the target information from the product page.
4. get_url - will send the request to Scraper API so it can retrieve the HTML response.

If you don't want to scrape every page returned for that keyword then comment out the next_page section of the parse_keyword_response:

def parse_keyword_response(self, response):
        products = response.xpath('//*[@data-asin]')

        for product in products:
            asin = product.xpath('@data-asin').extract_first()
            product_url = f"https://www.amazon.com/dp/{asin}"
            yield scrapy.Request(url=get_url(product_url), callback=self.parse_product_page, meta={'asin': asin})
            
        # next_page = response.xpath('//li[@class="a-last"]/a/@href').extract_first()
        # if next_page:
        #     url = urljoin("https://www.amazon.com",next_page)
        #     yield scrapy.Request(url=get_url(url), callback=self.parse_keyword_response)

If you want to scrape more or less fields on the product page then edit the XPath selectors in the parse_product_page function:

def parse_product_page(self, response):
       asin = response.meta['asin']
       title = response.xpath('//*[@id="productTitle"]/text()').extract_first()
       image = re.search('"large":"(.*?)"',response.text).groups()[0]
       rating = response.xpath('//*[@id="acrPopover"]/@title').extract_first()
       number_of_reviews = response.xpath('//*[@id="acrCustomerReviewText"]/text()').extract_first()
       price = response.xpath('//*[@id="priceblock_ourprice"]/text()').extract_first()

       if not price:
           price = response.xpath('//*[@data-asin-price]/@data-asin-price').extract_first() or \
                   response.xpath('//*[@id="price_inside_buybox"]/text()').extract_first()
       
       temp = response.xpath('//*[@id="twister"]')
       sizes = []
       colors = []
       if temp:
           s = re.search('"variationValues" : ({.*})', response.text).groups()[0]
           json_acceptable = s.replace("'", "\"")
           di = json.loads(json_acceptable)
           sizes = di.get('size_name', [])
           colors = di.get('color_name', [])
       
       bullet_points = response.xpath('//*[@id="feature-bullets"]//li/span/text()').extract()
       seller_rank = response.xpath('//*[text()="Amazon Best Sellers Rank:"]/parent::*//text()[not(parent::style)]').extract()
       yield {'asin': asin, 'Title': title, 'MainImage': image, 'Rating': rating, 'NumberOfReviews': number_of_reviews,
              'Price': price, 'AvailableSizes': sizes, 'AvailableColors': colors, 'BulletPoints': bullet_points,
              'SellerRank': seller_rank}