Update loading_file.py

loading_file.py

@@ -58,7 +58,7 @@ def fetch_data():
 
     # Trim unnecessary rows and set correct header
     df = df.iloc[header_index:].reset_index(drop=True)
-    df.columns = df.iloc[0].str.strip()  # Set the first row as column headers & strip spaces
+    df.columns = df.iloc[0]  # Set the first row as column headers
     df = df[1:].reset_index(drop=True)  # Remove the header row from data
 
     # Keep only relevant columns
@@ -68,10 +68,59 @@ def fetch_data():
 
     df = df[["Application Number", "Decision"]]
 
-    # Convert "Application Number" to integer for comparison
-    df["Application Number"] = pd.to_numeric(df["Application Number"], errors="coerce").astype("Int64")
+    # Ensure "Application Number" is treated as a string to match user input correctly
+    df["Application Number"] = df["Application Number"].astype(str).str.strip()
 
+    print("Data fetched successfully.")
+    
     return df, file_name
 
 # Fetch data once and store it globally
 precomputed_df, file_name = fetch_data()
+
+# Function to determine before/after status
+def check_application_status(application_number):
+    if precomputed_df is None:
+        return "Error fetching data"
+
+    application_number = str(application_number).strip()  # Ensure it's a string
+
+    min_app_number = precomputed_df["Application Number"].min()
+    max_app_number = precomputed_df["Application Number"].max()
+
+    if application_number in precomputed_df["Application Number"].values:
+        decision = precomputed_df.loc[precomputed_df["Application Number"] == application_number, "Decision"].values[0]
+        return f"Decision: {decision}"
+    elif application_number < min_app_number:
+        return f"Application number {application_number} is from the past. Decision might not be recorded."
+    elif application_number > max_app_number:
+        return f"Application number {application_number} is in the future. Decision is pending."
+    else:
+        return "No data found."
+
+# Function to generate a PDF
+def generate_pdf(df, title="Visa Decisions"):
+    pdf = FPDF()
+    pdf.set_auto_page_break(auto=True, margin=15)
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+
+    pdf.cell(200, 10, txt=title, ln=True, align="C")
+    pdf.ln(10)
+
+    for index, row in df.iterrows():
+        pdf.cell(50, 10, txt="Application Number:", ln=False)
+        pdf.cell(100, 10, txt=str(row["Application Number"]), ln=True)
+
+        pdf.cell(50, 10, txt="Decision:", ln=False)
+        pdf.cell(100, 10, txt=str(row["Decision"]), ln=True)
+
+        pdf.ln(5)
+
+    pdf_output = BytesIO()
+    pdf.output(pdf_output, "F")
+    pdf_output.seek(0)
+    
+    return pdf_output
+
+print("Loading File Module: generate_pdf is defined.")