this file provides a function which will take a product name as input from the user and fetch from amazon information about products of this name or category the product information will include title url price ratings and the discount available take a product name or category as input and return product information from amazon including title url price ratings and the discount available initialize a pandas dataframe with the column titles loop through each entry and store them in the dataframe take a product name or category as input and return product information from amazon including title url price ratings and the discount available initialize a pandas dataframe with the column titles loop through each entry and store them in the dataframe
from itertools import zip_longest

import requests
from bs4 import BeautifulSoup
from pandas import DataFrame


def get_amazon_product_data(product: str = "laptop") -> DataFrame:
    
    url = f"https://www.amazon.in/laptop/s?k={product}"
    header = {
        "User-Agent": (
            "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36"
            "(KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36"
        ),
        "Accept-Language": "en-US, en;q=0.5",
    }
    soup = BeautifulSoup(requests.get(url, headers=header).text, features="lxml")
    
    data_frame = DataFrame(
        columns=[
            "Product Title",
            "Product Link",
            "Current Price of the product",
            "Product Rating",
            "MRP of the product",
            "Discount",
        ]
    )
    
    for item, _ in zip_longest(
        soup.find_all(
            "div",
            attrs={"class": "s-result-item", "data-component-type": "s-search-result"},
        ),
        soup.find_all("div", attrs={"class": "a-row a-size-base a-color-base"}),
    ):
        try:
            product_title = item.h2.text
            product_link = "https://www.amazon.in/" + item.h2.a["href"]
            product_price = item.find("span", attrs={"class": "a-offscreen"}).text
            try:
                product_rating = item.find("span", attrs={"class": "a-icon-alt"}).text
            except AttributeError:
                product_rating = "Not available"
            try:
                product_mrp = (
                    "₹"
                    + item.find(
                        "span", attrs={"class": "a-price a-text-price"}
                    ).text.split("₹")[1]
                )
            except AttributeError:
                product_mrp = ""
            try:
                discount = float(
                    (
                        (
                            float(product_mrp.strip("₹").replace(",", ""))
                            - float(product_price.strip("₹").replace(",", ""))
                        )
                        / float(product_mrp.strip("₹").replace(",", ""))
                    )
                    * 100
                )
            except ValueError:
                discount = float("nan")
        except AttributeError:
            continue
        data_frame.loc[str(len(data_frame.index))] = [
            product_title,
            product_link,
            product_price,
            product_rating,
            product_mrp,
            discount,
        ]
    data_frame.loc[
        data_frame["Current Price of the product"] > data_frame["MRP of the product"],
        "MRP of the product",
    ] = " "
    data_frame.loc[
        data_frame["Current Price of the product"] > data_frame["MRP of the product"],
        "Discount",
    ] = " "
    data_frame.index += 1
    return data_frame


if __name__ == "__main__":
    product = "headphones"
    get_amazon_product_data(product).to_csv(f"Amazon Product Data for {product}.csv")