Package: extractkit
ExtractKitwhat is this??This is a Easy Scrapper for scrapping essential data from webWhat can it Scrape?Price and Key Specs of carPrice and Key Specs of bike,Price and specs of mobilesScrap FlipkartScrap Price and details of PC Building componentsScrap Live News and other Archived NewsHow to use this??So simple!! Just go and typepip install extractkitBam!! You just installed a great scraping toolHow to use in python??import ExtractKit as ekit #or whateverDetailed documentationScrap Car DataThis scrapes car specification fromCarwale WebsiteTo Scrap car Specification,from ExtractKit import carExtractor as car

data = car.extractCar('hyundai',"creta")
print(data)extractCar(brand, model),Parameters,brand- string data type, enter the brand name of the car you want to searchmodel- string data type, enter the model name of the car you want to searchResult Data Looks like this:{
    'product': 'Hyundai Creta', 
    'price': '₹ 10.00 Lakh'
    }Scrap Bike DataThis scrapes bike specification fromBikewale WebsiteTo Scrap Bike Specification,from ExtractKit import bikeExtractor as bike

data = bike.extractBike('yamaha',"R15")
print(data)extractBike(brand, model)Parameters,brand- string data type, enter the brand name of the bike you want to searchmodel- string data type, enter the model name of the bike you want to searchResult Data Looks like this:{
    "product": "Yamaha YZF R15 V3", 
    "price": "1,55,334", 
    "Engine Capacity": "155 cc", 
    "Mileage": "43 kmpl", 
    "Transmission": "6 Speed Manual ", 
    "Kerb Weight": "142 kg", 
    "Fuel Tank Capacity": "11 litres", 
    "Seat Height": "815 mm"
    }Scrap Mobile SpecificationsThis scraps data from91 Mobiles Websitefrom ExtractKit import gadgetsExtractor as gadgets
x = gadgets.extractMobile('samsung','galaxy a52')
print(x)In extractMobile(brand, model),Brand and model must be passed as stringResult data looks like this:{
    "name": "Samsung Galaxy A52",
    "price": " 23,499",
    "variants": [
        "128GB Storage, 8GB RAM\n"
    ],
    "specs": [
        [
            "RAM","6GB"
        ],
        [   
            "Processor","QualcommSnapdragon720G"
        ],
        [   
            "Rear Camera","64MP+12MP+5MP+5MP"
        ],
        [
            "Front Camera","32MP"
        ],
        [
            "Battery","4500mAh"
        ],
        [...],
        .
        .
        .
        [...]
    ]
}Scrap FlipkartThis Scraps data fromflipkart.comTo Scrap Flipkart products,from ExtractKit import flipkartExtractor as flipkart
x = flipkart.extractFlipkart('XBOX Series S')
print(x)In extractFlipkart(product),It must be a valid product.Product must be in string format.Result data looks like this:{
    "product": "MICROSOFT Xbox Series S 512 GB\u00a0\u00a0(White)",
    "price": "\u20b934,990",
    "url": "https://www.flipkart.com/microsoft-xbox-series-s-512-gb/p/itm13c51f9047da8?pid=GMCFVPFCNHHZQBNA&lid=LSTGMCFVPFCNHHZQBNAH2FMXL&marketplace=FLIPKART&q=XBOX+Series+S&store=4rr&srno=s_1_1&otracker=search&fm=organic&iid=a98ea799-22c1-440d-b211-9835eb1790eb.GMCFVPFCNHHZQBNA.SEARCH&ppt=None&ppn=None&ssid=l55b2xbdfk0000001625828211339&qH=fd75188725591a70"
}You can also use extractFlipkartUrl(url) to scrap data from the given flipkart linkfrom ExtractKit import flipkartExtractor as flipkart
x = flipkart.extractFlipkartUrl('https://www.flipkart.com/cyberpunk-2077-limited-edition/p/itm6e7fc6515a3b3?pid=GAMG2Z8UGZHTYHAF&lid=LSTGAMG2Z8UGZHTYHAFHTIMQD&marketplace=FLIPKART&q=cyberpunk+2077&store=4rr%2Ffa6%2F27p%2Fmtr&spotlightTagId=TrendingId_4rr%2Ffa6%2F27p%2Fmtr&srno=s_1_1&otracker=AS_QueryStore_OrganicAutoSuggest_2_9_na_na_na&otracker1=AS_QueryStore_OrganicAutoSuggest_2_9_na_na_na&fm=SEARCH&iid=0fa0a337-bb8d-4126-9fe6-9421bcbdb3ee.GAMG2Z8UGZHTYHAF.SEARCH&ppt=sp&ppn=sp&ssid=rg6sh1i72o0000001625828417574&qH=65fc51bd3f81e7c2')
print(x)The result for this function is:{
    "product": "Cyberpunk 2077 (Limited Edition) (for PS4)",
    "price": "₹2,899"
}Scrap PC ComponentsThis Scraps data fromPC StudioTo Scrap PC Components,from ExtractKit import pcBuildExtractor as pcBuild
x = pcBuild.extractProcessors()
print(x)Result data looks like this:{
    "0": {
        "title": "AMD RYZEN 3 3200G OPEN BOX OEM PROCESSOR WITH RX VEGA 8 GRAPHICS (UP TO 4.0GHZ 6 MB CACHE) ",
        "price": "\u20b911,300.00",
        "details": "https://www.pcstudio.in/product/amd-ryzen-3-3200g-open-box-oem-processor-with-rx-vega-8-graphics-up-to-4-0ghz-6-mb-cache/",
        "img": "https://www.pcstudio.in/wp-content/uploads/2021/07/AMD-RYZEN-3-3200G-OPEN-BOX-OEM-PROCESSOR-WITH-RX-VEGA-8-GRAPHICS-1.jpg"
    },
    "1":{...},
    "2":{...},
}other functions available are:print(pcBuild.extractProcessors())    #Extract Processors Data
print(extractMotherboards())          #Extract Motherboard Data 
print(extractRams())                  #Extract RAM Data
print(extractStorage1())              #Extract Storages Data
print(extractStorage2())              #Extract Storages Data too
print(extractCabinets())              #Extract Cabinet Data
print(extractCoolers())               #Extract Coolers Data
print(extractGPUs())                  #Extract GPU Data
print(extractPowerSupplys())          #Extract PowerSupplyUnit Data
print(extractDisplays())              #Extract Display DataScrap News DataThis scraps live and archive news data fromOne India NewsTo Scrap news,from ExtractKit import newsExtractor as news

data = news.extractNewsArchives('english',2021,7,1)
print(data)Parameters,language- string data type, enter the language in which you want to searchAvaliable Languages aretamiltelugumalayalambengaligujaratihindikannadayear- integer data type, enter the year in which you want to searchmonth- integer data type, enter the month in which you want to searchdate- integer data type, enter the date in which you want to searchResult Data Looks like this:{
    "language": "english",
    "1": {
        "category": "bengaluru",
        "news": "No interviews to fill up vacancies to post of assistant professors, principles in Karnataka\u2019s higher education"
    },
    "2":{...},
    "3":{...},
    ....CreditsKarthik Raja KVignesh RSource Code Available inGithub