Create fetch_amazon_product_data.py

web_programming/fetch_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 the necessary
+information about that kind of products from Amazon like the product
+title,link to that product,price of the product,the ratings of
+the product and the discount available on the product
+in the form of a csv file,this will help the users by improving searchability
+and navigability and find the right product easily and in a short period of time,
+it will also be beneficial for performing better analysis on products"""
+
+
+import itertools as it
+
+import pandas as pd
+import requests
+from bs4 import BeautifulSoup as bs
+
+
+def get_product_info(product="laptop") -> None:
+    # function that will take the product as input and return the product details as output
+    # in the form of a csv file,if no input is given,it will fetch the details of laptop by default
+    url = (
+        f"https://www.amazon.in/laptop/s?k={product}"  # generation of search query url
+    )
+    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",
+    }  # header that will indicate to the destination server that the request is coming from
+    # a genuine human being and not a bot
+    page = requests.get(url, headers=header)
+    page_content = page.text
+    soup = bs(page_content)
+    data = pd.DataFrame(
+        columns=[
+            "Product Title",
+            "Product Link",
+            "Current Price of the product",
+            "Product Rating",
+            "MRP of the product",
+            "Discount",
+        ]
+    )  # initializing a pandas dataframe to store the requisite information
+    for i, j in it.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"}),
+    ):  # for loop to parse through each entry and store them in the dataframe along with try....
+        # except block for handling exceptions that may arise
+        try:
+            product_title = i.h2.text
+            product_link = "https://www.amazon.in/" + i.h2.a["href"]
+            product_price = i.find("span", attrs={"class": "a-offscreen"}).text
+            try:
+                product_rating = i.find("span", attrs={"class": "a-icon-alt"}).text
+            except AttributeError:
+                product_rating = "Not available"
+            try:
+                product_mrp = (
+                    "₹"
+                    + i.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 = ""
+        except AttributeError:
+            pass
+        data.loc[len(data.index)] = [
+            product_title,
+            product_link,
+            product_price,
+            product_rating,
+            product_mrp,
+            discount,
+        ]
+    data.loc[
+        data["Current Price of the product"] > data["MRP of the product"],
+        "MRP of the product",
+    ] = " "
+    data.loc[
+        data["Current Price of the product"] > data["MRP of the product"], "Discount"
+    ] = " "
+    data.index += 1
+    data.to_csv(
+        f"Amazon Product Data({product}).csv"
+    )  # writing the data to the csv file