How to Scrape Amazon Stores for Generating Price Alerts?

				
					def search_product_list(interval_count = 1, interval_hours = 6):
    """
    This function lods a csv file named TRACKER_PRODUCTS.csv, with headers: [url, code, buy_below]
    It looks for the file under in ./trackers
    
    It also requires a file called SEARCH_HISTORY.xslx under the folder ./search_history to start saving the results.
    An empty file can be used on the first time using the script.
    
    Both the old and the new results are then saved in a new file named SEARCH_HISTORY_{datetime}.xlsx
    This is the file the script will use to get the history next time it runs.

    Parameters
    ----------
    interval_count : TYPE, optional
        DESCRIPTION. The default is 1. The number of iterations you want the script to run a search on the full list.
    interval_hours : TYPE, optional
        DESCRIPTION. The default is 6.

    Returns
    -------
    New .xlsx file with previous search history and results from current search

    """
    prod_tracker = pd.read_csv('trackers/TRACKER_PRODUCTS.csv', sep=';')
    prod_tracker_URLS = prod_tracker.url
    tracker_log = pd.DataFrame()
    now = datetime.now().strftime('%Y-%m-%d %Hh%Mm')
    interval = 0 # counter reset
    
    while interval < interval_count:

for x, url in enumerate(prod_tracker_URLS):
    page = requests.get(url, headers=HEADERS)
    soup = BeautifulSoup(page.content, features="lxml")
    
    #product title
    title = soup.find(id='productTitle').get_text().strip()
    
    # to prevent script from crashing when there isn't a price for the product
    try:
        price = float(soup.find(id='priceblock_ourprice').get_text().replace('.', '').replace('€', '').replace(',', '.').strip())
    except:
        # this part gets the price in dollars from amazon.com store
        try:
            price = float(soup.find(id='priceblock_saleprice').get_text().replace('$', '').replace(',', '').strip())
        except:
            price = ''


    try:
        review_score = float(soup.select('i[class*="a-icon a-icon-star a-star-"]')[0].get_text().split(' ')[0].replace(",", "."))
        review_count = int(soup.select('#acrCustomerReviewText')[0].get_text().split(' ')[0].replace(".", ""))
    except:
        # sometimes review_score is in a different position... had to add this alternative with another try statement
        try:
            review_score = float(soup.select('i[class*="a-icon a-icon-star a-star-"]')[1].get_text().split(' ')[0].replace(",", "."))
            review_count = int(soup.select('#acrCustomerReviewText')[0].get_text().split(' ')[0].replace(".", ""))
        except:
            review_score = ''
            review_count = ''
    
    # checking if there is "Out of stock"
    try:
        soup.select('#availability .a-color-state')[0].get_text().strip()
        stock = 'Out of Stock'
    except:
        # checking if there is "Out of stock" on a second possible position
        try:
            soup.select('#availability .a-color-price')[0].get_text().strip()
            stock = 'Out of Stock'
        except:
            # if there is any error in the previous try statements, it means the product is available
            stock = 'Available'


    log = pd.DataFrame({'date': now.replace('h',':').replace('m',''),
                        'code': prod_tracker.code[x], # this code comes from the TRACKER_PRODUCTS file
                        'url': url,
                        'title': title,
                        'buy_below': prod_tracker.buy_below[x], # this price comes from the TRACKER_PRODUCTS file
                        'price': price,
                        'stock': stock,
                        'review_score': review_score,
                        'review_count': review_count}, index=[x])


    try:
        # This is where you can integrate an email alert!
        if price < prod_tracker.buy_below[x]:
            print('************************ ALERT! Buy the '+prod_tracker.code[x]+' ************************')
    
    except:
        # sometimes we don't get any price, so there will be an error in the if condition above
        pass


    tracker_log = tracker_log.append(log)
    print('appended '+ prod_tracker.code[x] +'\n' + title + '\n\n')            
    sleep(5)
        
    interval += 1# counter update
    
    sleep(interval_hours*1*1)
    print('end of interval '+ str(interval))
    
    # after the run, checks last search history record, and appends this run results to it, saving a new file
    last_search = glob('[REPLACE WITH YOUR OWN PATH -> C:/Amazon Webscraper/search_history/*.xlsx')[-1] # path to file in the folder
    search_hist = pd.read_excel(last_search)
    final_df = search_hist.append(tracker_log, sort=False)
    
    final_df.to_excel('search_history/SEARCH_HISTORY_{}.xlsx'.format(now), index=False)
    print('end of search')