This fixes issue #1 #2
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import multiprocessing
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import subprocess
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# Define the subset of urls
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url_list = [
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'https://www.sayweee.com/en/product/Want-Want-Senbei-Rice-Crackers/17119'
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'https://www.sayweee.com/en/product/Lays-Potato-Chips-Cucumber-Flavor/51261'
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'https://www.sayweee.com/en/product/Glico-Pocky-Cookies-and-Cream-Family-Pack/79467'
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'https://www.sayweee.com/en/product/Xiang-Na-Lan-Thai-Jasmine-Rice/19566?category=dried01'
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'https://www.sayweee.com/en/product/Sekka-Premium-Japanese-Medium-Grain-Rice/81224'
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'https://www.sayweee.com/en/product/Big-Green-Spring-Farm-Organic-Millet/90991?category=dried02'
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'https://www.sayweee.com/en/product/Liuzhou-Guangxi-Specialty-LuoSiFen-Hot-Spicy-Noodles/95442?category=instant01'
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'https://www.sayweee.com/en/product/House-Foods-Firm-Tofu-/85175?trace_id=c93f3d1a-80a4-4e1a-8d41-a402ae43186f'
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'https://www.sayweee.com/en/product/Lactaid-Lactose-Free-2--Reduced-Fat-Milk/95353'
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'https://www.sayweee.com/en/product/Washington-Fuji-Apples/94817?category=fruits03'
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'https://www.sayweee.com/en/product/Formosa-Pork-Sung-/23528?trace_id=3c143dd4-4a35-4e8d-93ee-d91f209717e7'
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]
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# Determine the number of available CPUs
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cpu_count = multiprocessing.cpu_count()
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# Create a pool of worker processes
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pool = multiprocessing.Pool(cpu_count)
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# Define the function to run the scraper
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def run_scraper(url):
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# scraping logic
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subprocess.call(['python', 'fp2_13.py', url])
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return run_scraper
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# Run the scraper in parallel for the subset of items
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results = pool.map(run_scraper, url_list)
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# Close the pool and wait for the processes to finish
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pool.close()
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pool.join()
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