diff --git a/web_programming/get_amazon_product_data.py b/web_programming/get_amazon_product_data.py
new file mode 100644
index 000000000..c796793f2
--- /dev/null
+++ b/web_programming/get_amazon_product_data.py
@@ -0,0 +1,100 @@
+"""
+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.
+"""
+
+
+from itertools import zip_longest
+
+import requests
+from bs4 import BeautifulSoup
+from pandas import DataFrame
+
+
+def get_amazon_product_data(product: str = "laptop") -> DataFrame:
+    """
+    Take a product name or category as input and return product information from Amazon
+    including title, URL, price, ratings, and the discount available.
+    """
+    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)
+    # Initialize a Pandas dataframe with the column titles
+    data_frame = DataFrame(
+        columns=[
+            "Product Title",
+            "Product Link",
+            "Current Price of the product",
+            "Product Rating",
+            "MRP of the product",
+            "Discount",
+        ]
+    )
+    # Loop through each entry and store them in the dataframe
+    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:
+            pass
+        data_frame.loc[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")