Upload Untitled3.py

Untitled3.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[10]:
+
+
+import requests
+import pandas as pd
+from io import BytesIO
+from bs4 import BeautifulSoup
+
+# URL of the website to scrape
+url = "https://www.ireland.ie/en/india/newdelhi/services/visas/processing-times-and-decisions/"
+
+# Headers to mimic a browser request
+headers = {
+    "User-Agent": (
+        "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
+        "(KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36"
+    )
+}
+
+# Send an HTTP GET request to the website
+response = requests.get(url, headers=headers)
+
+# Check if the request was successful
+if response.status_code == 200:
+    # Parse the HTML content of the page
+    soup = BeautifulSoup(response.content, 'html.parser')
+    
+    # Find all anchor tags
+    links = soup.find_all('a')
+    
+    # Search for the link that contains the specific text
+    file_url = None
+    for link in links:
+        link_text = link.get_text(strip=True)
+        if "Visa decisions made from 1 January 2024 to" in link_text:
+            file_url = link.get('href')
+            break
+    
+    # Check if the link was found
+    if file_url:
+        # Make the link absolute if it is relative
+        if not file_url.startswith('http'):
+            file_url = requests.compat.urljoin(url, file_url)
+        
+        print(f"Found link: {file_url}")
+        
+        # Download the file into memory
+        file_response = requests.get(file_url, headers=headers)
+        
+        if file_response.status_code == 200:
+            # Load the file into a BytesIO object
+            ods_file = BytesIO(file_response.content)
+            
+            # Read the .ods file using pandas
+            try:
+                # Load the .ods file into a DataFrame
+                df = pd.read_excel(ods_file, engine='odf')
+                
+                # Step 1: Clean the DataFrame
+                # Drop the first two columns
+                df.drop(columns=["Unnamed: 0", "Unnamed: 1"], inplace=True)
+                
+                # Step 2: Drop NaN rows until we find the actual header row
+                df.dropna(how='all', inplace=True)
+                
+                # Step 3: Reset index and rename the header row
+                df.reset_index(drop=True, inplace=True)
+                
+                # Step 4: Find the row where "Application Number" starts
+                for idx, row in df.iterrows():
+                    if row['Unnamed: 2'] == 'Application Number' and row['Unnamed: 3'] == 'Decision':
+                        df.columns = ['Application Number', 'Decision']
+                        df = df.iloc[idx + 1:]  # Skip the header row
+                        break
+                
+                # Step 5: Reset the index after cleaning
+                df.reset_index(drop=True, inplace=True)
+                
+                # Convert "Application Number" to string for consistency
+                df['Application Number'] = df['Application Number'].astype(str)
+
+                # Display the cleaned DataFrame
+                #print("Cleaned Data:")
+                #print(df.to_string(index=False))
+                
+                # Step 6: Ask the user for their application number
+                user_application_number = input("\nEnter your Application Number: ").strip()
+                
+                # Step 7: Check if the application number exists in the DataFrame
+                result = df[df['Application Number'] == user_application_number]
+                
+                if not result.empty:
+                    print(f"\nCongratulations! Your visa application ({user_application_number}) has been {result.iloc[0]['Decision']}.")
+                else:
+                    print(f"\nSorry, no record found for Application Number: {user_application_number}.")
+                    
+            except Exception as e:
+                print("Error reading the .ods file:", e)
+        else:
+            print("Failed to download the file. Status code:", file_response.status_code)
+    else:
+        print("The specified link was not found.")
+else:
+    print(f"Failed to retrieve the webpage. Status code: {response.status_code}")
+