Create fetch_data()

fetch_data()

@@ -0,0 +1,80 @@
+import requests
+import pandas as pd
+import streamlit as st
+from io import BytesIO
+from bs4 import BeautifulSoup
+
+@st.cache_data(ttl=3600)
+def fetch_data():
+    url = "https://www.ireland.ie/en/india/newdelhi/services/visas/processing-times-and-decisions/"
+    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"
+    }
+
+    st.write("🔄 Fetching webpage...")
+    try:
+        response = requests.get(url, headers=headers, timeout=10)  # Timeout added
+        response.raise_for_status()  # Raise an error if request fails
+    except requests.exceptions.RequestException as e:
+        st.error(f"❌ Failed to fetch webpage: {e}")
+        return None, None
+
+    # Parse the HTML
+    st.write("🔄 Parsing webpage...")
+    soup = BeautifulSoup(response.content, "html.parser")
+
+    file_url = None
+    for link in soup.find_all("a"):
+        if "Visa decisions made from 1 January 2025" in link.get_text():
+            file_url = link.get("href")
+            if not file_url.startswith("http"):
+                file_url = requests.compat.urljoin(url, file_url)
+            break
+
+    if not file_url:
+        st.error("❌ Could not find the visa decisions file link.")
+        return None, None
+
+    st.write(f"📥 Found file link: {file_url}")
+
+    # Download the .ods file
+    try:
+        st.write("🔄 Downloading file...")
+        ods_response = requests.get(file_url, headers=headers, timeout=15)  # Timeout added
+        ods_response.raise_for_status()
+    except requests.exceptions.RequestException as e:
+        st.error(f"❌ Failed to download the file: {e}")
+        return None, None
+
+    st.write("📂 Processing file...")
+    ods_file = BytesIO(ods_response.content)
+
+    # Read Excel file
+    try:
+        df = pd.read_excel(ods_file, engine="odf")
+    except Exception as e:
+        st.error(f"❌ Error reading ODS file: {e}")
+        return None, None
+
+    # Drop empty rows
+    df.dropna(how="all", inplace=True)
+    df.reset_index(drop=True, inplace=True)
+
+    # Find header row
+    header_rows = df[df.iloc[:, 0].astype(str).str.contains("Application Number", na=False)].index
+    if len(header_rows) == 0:
+        st.error("❌ Could not find the header row. Check the file format.")
+        return None, None
+
+    header_index = header_rows[0]
+    df = df.iloc[header_index + 1:].reset_index(drop=True)
+
+    # Rename columns
+    df.columns = ["Application Number", "Decision"]
+    df.dropna(inplace=True)
+    df["Application Number"] = df["Application Number"].astype(str).str.strip()
+
+    st.write("✅ Data loaded successfully!")
+    return df, "Visa Decisions Report"
+
+precomputed_df, file_name = fetch_data()