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Delhi_Irish_visa_decisions

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Update app.py

by SR05 - opened Nov 8, 2024

base: refs/heads/main

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from: refs/pr/1

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app.py +109 -45

app.py CHANGED Viewed

@@ -1,49 +1,113 @@
-import os
-import requests
-from bs4 import BeautifulSoup
-from datetime import datetime, timedelta
-import streamlit as st
-import pandas as pd
-import pytz
-#import pyexcel_ods3
-import requests
 import requests
 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 with headers
-response = requests.get(url, headers=headers)
-# Check if the request was successful (status code 200)
-if response.status_code == 200:
-    # Parse the HTML content of the page
-    soup = BeautifulSoup(response.content, 'html.parser')
-    # Extract relevant data (e.g., tables, headings, paragraphs)
-    paragraphs = soup.find_all('p')
-    for i, paragraph in enumerate(paragraphs, start=1):
-        print(f"Paragraph {i}: {paragraph.get_text(strip=True)}")
-        print("-" * 80)
-    # Example: Scraping tables (if there are any)
-    tables = soup.find_all('table')
-    for table in tables:
-        print("\nTable found:")
-        rows = table.find_all('tr')
-        for row in rows:
-            cells = row.find_all(['th', 'td'])
-            cell_data = [cell.get_text(strip=True) for cell in cells]
-            print("\t".join(cell_data))
-else:
-    print(f"Failed to retrieve the webpage. Status code: {response.status_code}")

 import requests
+import pandas as pd
+from io import BytesIO
 from bs4 import BeautifulSoup
+from IPython.display import HTML, display
+from IPython.display import clear_output
+# ... (Your existing code for fetching and processing the data remains the same) ...
+# ... (Code for reading .ods file, cleaning data, and creating the df DataFrame) ...
+def display_application_decision():
+  """Displays the application decision in an HTML table based on user input."""
+  while True:
+    application_number_input = input("Enter your Application Number (including IRL if applicable): ")
+    if "irl" in application_number_input.lower():
+      try:
+          application_number = int("".join(filter(str.isdigit, application_number_input.lower().split("irl")[-1])))
+          if len(str(application_number)) < 8:
+              print("Please enter a valid application number with minimum 8 digits after IRL.")
+              continue
+          break
+      except ValueError:
+          print("Invalid input after IRL. Please enter only digits.")
+          continue
+    else:
+      if not application_number_input.isdigit():
+        print("Invalid input. Please enter only digits.")
+        continue
+      elif len(application_number_input) < 8:
+          print("Please enter at least 8 digits for your VISA application number.")
+          continue
+      else:
+          application_number = int(application_number_input)
+          break
+  # Find the row corresponding to the entered application number.
+  row = df[df['Application Number'] == application_number]
+  if not row.empty:
+    # Congratulate the user if the application is approved
+    if row['Decision'].iloc[0] == 'Approved':
+      print("Congratulations! Your Visa application has been approved.")
+    # Create HTML table string
+    html_table = """
+    <html>
+    <body>
+    <table border="1" style="border-collapse: collapse;">
+      <tr>
+        <th style="border: 1px solid black;">Application Number</th>
+        <th style="border: 1px solid black;">Decision</th>
+      </tr>
+      <tr>
+        <td style="border: 1px solid black;">{}</td>
+        <td style="border: 1px solid black;">{}</td>
+      </tr>
+    </table>
+    </body>
+    </html>
+    """.format(row['Application Number'].iloc[0], row['Decision'].iloc[0])
+    # Display the HTML table
+    clear_output(wait=True)
+    display(HTML(html_table))
+  else:
+    print("Application number", application_number, "not found in the data.")
+    # Find the nearest records if the exact application number is not found
+    df['Difference'] = abs(df['Application Number'] - application_number)
+    nearest_records = df.nsmallest(2, 'Difference')
+    if not nearest_records.empty:
+      # Create HTML table string for nearest records
+      html_table = """
+      <html>
+      <body>
+      <h3>Application number not found. Showing nearest records:</h3>
+      <table border="1" style="border-collapse: collapse;">
+        <tr>
+          <th style="border: 1px solid black;">Application Number</th>
+          <th style="border: 1px solid black;">Decision</th>
+          <th style="border: 1px solid black;">Difference</th>
+        </tr>
+      """
+      for _, row in nearest_records.iterrows():
+          html_table += """
+          <tr>
+            <td style="border: 1px solid black;">{}</td>
+            <td style="border: 1px solid black;">{}</td>
+            <td style="border: 1px solid black;">{}</td>
+          </tr>
+          """.format(row['Application Number'], row['Decision'], row['Difference'])
+      html_table += """
+      </table>
+      </body>
+      </html>
+      """
+      # Display the HTML table
+      clear_output(wait=True)
+      display(HTML(html_table))
+    else:
+      print("Application number not found, and no nearest records found in the data.")
+# Call the function to start the process
+display_application_decision()