Create fetch_amazon_product_data.py

web_programming/fetch_amazon_product_data.py

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+''' 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 pandas as pd 
+from bs4 import BeautifulSoup as bs 
+import requests 
+import itertools as it    
+
+
+
+
+def get_product_info(product = 'laptop'):                 #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   
+    return data