Update app.py

app.py

@@ -3,209 +3,103 @@ import gspread
 import gradio as gr
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime
+from geopy.distance import geodesic
+import folium
+from io import BytesIO
 
-# ------------------ AUTH ------------------
-VALID_USERS = {
-    "[email protected]": "Pass.123",
-    "[email protected]": "Pass.123",
-    "[email protected]": "Pass.123"
-}
-
-# ------------------ GOOGLE SHEET SETUP ------------------
+# Google Sheets Auth
 scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
 creds = ServiceAccountCredentials.from_json_keyfile_name("credentials.json", scope)
 client = gspread.authorize(creds)
 sheet_file = client.open("userAccess")
 
-# ------------------ HELPERS ------------------
+# Load Data
 def load_tab(sheet_name):
     try:
         df = pd.DataFrame(sheet_file.worksheet(sheet_name).get_all_records())
         return df
     except:
-        return pd.DataFrame([["⚠️ Could not load sheet."]], columns=["Error"])
-
-# ------------------ FIELD SALES ------------------
-def load_field_sales():
-    df = load_tab("Field Sales")
-    if df.empty:
-        return pd.DataFrame(columns=["Date", "Rep", "Order Value", "Order Received", "Current/Prospect Custor", "Customer Type & Status", "DateStr"])
-    df['Date'] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
-    df = df.dropna(subset=["Date"])
-    df['DateStr'] = df['Date'].dt.date.astype(str)
-
-    if "Order Value" not in df.columns:
-        df["Order Value"] = 0
-    else:
-        df["Order Value"] = pd.to_numeric(df["Order Value"], errors="coerce").fillna(0)
-
+        return pd.DataFrame(["⚠️ Could not load sheet."], columns=["Error"])
+
+# GPS calculations
+def calculate_gps_data(df):
+    df = df.sort_values(['Date', 'Time'])
+    df[['Latitude', 'Longitude']] = df['Location'].str.split(', ', expand=True).astype(float)
+    df['Kms Travelled'] = df[['Latitude', 'Longitude']].shift().apply(
+        lambda row: geodesic((row['Latitude'], row['Longitude']), (row.name[0], row.name[1])).km if pd.notnull(row['Latitude']) else 0,
+        axis=1)
+    df['Duration Between Calls (min)'] = df[['Date', 'Time']].apply(
+        lambda row: pd.to_datetime(row['Date'] + ' ' + row['Time']), axis=1
+    ).diff().dt.total_seconds().div(60)
+    df.fillna({'Kms Travelled': 0, 'Duration Between Calls (min)': 0}, inplace=True)
     return df
 
-def generate_summary(date_str):
-    df = load_field_sales()
-    if df.empty:
-        return pd.DataFrame([["No data"]], columns=["Message"]), pd.DataFrame(), pd.DataFrame()
-    
-    all_reps = sorted(df['Rep'].dropna().unique())
-    day_df = df[df['DateStr'] == date_str]
-    total_visits = day_df.groupby("Rep").size().reset_index(name="Total Visits")
-
-    col = "Current/Prospect Custor"
-    if col not in df.columns:
-        df[col] = ""
-
-    current = day_df[day_df[col] == "Current"]
-    prospect = day_df[day_df[col] == "Prospect"]
-    breakdown = pd.DataFrame({
-        "Rep": all_reps,
-        "Current": [len(current[current["Rep"] == rep]) for rep in all_reps],
-        "Prospect": [len(prospect[prospect["Rep"] == rep]) for rep in all_reps]
-    })
-
-    active_list = total_visits['Rep'].tolist()
-    inactive_list = [rep for rep in all_reps if rep not in active_list]
-    inactive_df = pd.DataFrame({'Inactive Reps': inactive_list})
-    return total_visits, breakdown, inactive_df
-
-def get_order_summary(date_str):
-    df = load_field_sales()
-    if df.empty:
-        return pd.DataFrame([["No data"]], columns=["Message"])
-
-    day_df = df[df['DateStr'] == date_str]
-    if "Order Received" not in df.columns:
-        df["Order Received"] = ""
-
-    rep_group = day_df.groupby("Rep").agg({
-        "Order Received": lambda x: (x == "Yes").sum(),
-        "Order Value": "sum"
-    }).reset_index().rename(columns={
-        "Order Received": "Orders Received",
-        "Order Value": "Total Order Value"
-    })
-    return rep_group.sort_values(by="Total Order Value", ascending=False)
-
-def get_escalations():
-    df = load_field_sales()
-    if df.empty:
-        return pd.DataFrame([["No data in Field Sales"]], columns=["Message"])
-
-    col = "Customer Type & Status"
-    if col in df.columns:
-        flagged = df[df[col].str.contains("Second", na=False)]
-        return flagged if not flagged.empty else pd.DataFrame([["No second-hand dealerships flagged."]], columns=["Message"])
-    else:
-        return pd.DataFrame([["⚠️ Column 'Customer Type & Status' not found."]], columns=["Message"])
-
-# ------------------ TELESALeS ------------------
-def get_telesales_summary():
-    df = load_tab("TeleSales")
-    if df.empty or "Rep Email" not in df.columns:
-        return pd.DataFrame([["No data available"]], columns=["Message"])
-    
-    df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
-    df["DateStr"] = df["Date"].dt.date.astype(str)
-
-    grouped = df.groupby(["Rep Email", "DateStr"]).size().reset_index(name="Calls Made")
-    return grouped.rename(columns={"Rep Email": "Rep"})
-
-# ------------------ OEM VISITS ------------------
-def get_oem_summary():
-    df = load_tab("OEM Visit")
-    if df.empty or "Rep" not in df.columns:
-        return pd.DataFrame([["No data available"]], columns=["Message"])
-
-    df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
-    df["DateStr"] = df["Date"].dt.date.astype(str)
-    return df.groupby(["Rep", "DateStr"]).size().reset_index(name="OEM Visits")
-
-# ------------------ CUSTOMER REQUESTS ------------------
-def get_requests():
-    df = load_tab("Customer Requests")
-    return df if not df.empty else pd.DataFrame([["No requests yet."]], columns=["Message"])
-
-# ------------------ CUSTOMER LISTINGS ------------------
-def get_listings():
-    df = load_tab("CustomerListings")
-    return df if not df.empty else pd.DataFrame([["No listings found."]], columns=["Message"])
-
-# ------------------ USERS ------------------
-def get_users():
-    df = load_tab("Users")
-    return df if not df.empty else pd.DataFrame([["No users configured."]], columns=["Message"])
-
-# ------------------ GRADIO APP ------------------
+# Load and process Field Sales data
+field_sales_df = calculate_gps_data(load_tab("Field Sales"))
+
+# Map generation
+def generate_map(df):
+    if df.empty or df[['Latitude', 'Longitude']].isna().all().all():
+        return None
+
+    coords = df[['Latitude', 'Longitude']].dropna().values
+    map_center = coords[0]
+    m = folium.Map(location=map_center, zoom_start=12)
+
+    for idx, coord in enumerate(coords):
+        folium.Marker(location=coord, popup=f"Visit {idx+1}").add_to(m)
+
+    folium.PolyLine(coords, color='blue').add_to(m)
+
+    buf = BytesIO()
+    m.save(buf, close_file=False)
+    return buf.getvalue().decode()
+
+# Gradio Interface
 with gr.Blocks() as app:
-    with gr.Row():
-        with gr.Column(visible=True) as login_ui:
-            gr.Markdown("## 🔐 Login Required")
-            email = gr.Textbox(label="Email")
-            password = gr.Textbox(label="Password", type="password")
-            login_btn = gr.Button("Login")
-            login_msg = gr.Markdown("")
-
-        with gr.Column(visible=False) as main_ui:
-            gr.Markdown("## 🗂️ CarMat Dashboard")
-
-            df_initial = load_field_sales()
-            unique_dates = sorted(df_initial["DateStr"].unique(), reverse=True) if not df_initial.empty else []
-
-            # --- Summary Tab ---
-            with gr.Tab("📊 Summary"):
-                date_summary = gr.Dropdown(label="Select Date", choices=unique_dates)
-                visits = gr.Dataframe(label="✅ Total Visits")
-                breakdown = gr.Dataframe(label="🏷️ Current vs. Prospect")
-                inactive = gr.Dataframe(label="⚠️ Inactive Reps")
-                date_summary.change(fn=generate_summary, inputs=date_summary, outputs=[visits, breakdown, inactive])
-
-            # --- Orders Tab ---
-            with gr.Tab("📦 Orders"):
-                order_date = gr.Dropdown(label="Select Date", choices=unique_dates)
-                order_table = gr.Dataframe(label="💰 Orders Summary")
-                order_date.change(fn=get_order_summary, inputs=order_date, outputs=order_table)
-
-            # --- Escalations ---
-            with gr.Tab("🚨 Escalations"):
-                esc_table = gr.Dataframe(value=get_escalations, label="Second-hand Dealerships")
-                esc_btn = gr.Button("🔄 Refresh")
-                esc_btn.click(fn=get_escalations, outputs=esc_table)
-
-            # --- TeleSales ---
-            with gr.Tab("📞 TeleSales"):
-                ts_table = gr.Dataframe(value=get_telesales_summary, label="TeleSales Summary")
-                ts_refresh = gr.Button("🔄 Refresh TeleSales")
-                ts_refresh.click(fn=get_telesales_summary, outputs=ts_table)
-
-            # --- OEM Visits ---
-            with gr.Tab("🏭 OEM Visits"):
-                oem_table = gr.Dataframe(value=get_oem_summary, label="OEM Visit Summary")
-                oem_refresh = gr.Button("🔄 Refresh OEM")
-                oem_refresh.click(fn=get_oem_summary, outputs=oem_table)
-
-            # --- Requests ---
-            with gr.Tab("📬 Customer Requests"):
-                req_table = gr.Dataframe(value=get_requests, label="Customer Requests", interactive=False)
-                req_refresh = gr.Button("🔄 Refresh Requests")
-                req_refresh.click(fn=get_requests, outputs=req_table)
-
-            # --- Dealerships ---
-            with gr.Tab("📋 Dealership Directory"):
-                listings_table = gr.Dataframe(value=get_listings, label="Customer Listings")
-                listings_refresh = gr.Button("🔄 Refresh Listings")
-                listings_refresh.click(fn=get_listings, outputs=listings_table)
-
-            # --- Users ---
-            with gr.Tab("👤 Users"):
-                users_table = gr.Dataframe(value=get_users, label="Users")
-                users_refresh = gr.Button("🔄 Refresh Users")
-                users_refresh.click(fn=get_users, outputs=users_table)
-
-    def do_login(user, pw):
-        if VALID_USERS.get(user) == pw:
-            return gr.update(visible=False), gr.update(visible=True), ""
-        else:
-            return gr.update(visible=True), gr.update(visible=False), "❌ Invalid login."
-
-    login_btn.click(fn=do_login, inputs=[email, password], outputs=[login_ui, main_ui, login_msg])
-
-app.launch()
+    gr.Markdown("## 🚗 CarMat Dashboard")
+
+    unique_dates = sorted(field_sales_df['Date'].unique(), reverse=True)
+
+    # Field Sales Tab
+    with gr.Tab("🗺️ Field Sales"):
+        date_selector = gr.Dropdown(label="Select Date", choices=unique_dates)
+        data_output = gr.DataFrame()
+        map_html = gr.HTML()
+
+        def update_field_sales(date):
+            day_df = field_sales_df[field_sales_df['Date'] == date]
+            map_render = generate_map(day_df)
+            return day_df, map_render
+
+        date_selector.change(fn=update_field_sales, inputs=date_selector, outputs=[data_output, map_html])
+
+    # Summary Tab
+    with gr.Tab("📊 Summary"):
+        date_summary = gr.Dropdown(label="Select Date", choices=unique_dates)
+        summary_visits = gr.DataFrame()
+
+        def update_summary(date):
+            day_df = field_sales_df[field_sales_df['Date'] == date]
+            visits = day_df.groupby("Rep").size().reset_index(name="Total Visits")
+            return visits
+
+        date_summary.change(fn=update_summary, inputs=date_summary, outputs=summary_visits)
+
+    # Orders Tab
+    with gr.Tab("📦 Orders"):
+        order_date = gr.Dropdown(label="Select Date", choices=unique_dates)
+        orders_output = gr.DataFrame()
+
+        def orders_summary(date):
+            day_df = field_sales_df[field_sales_df['Date'] == date]
+            orders_df = day_df[day_df["Order Received"] == "Yes"]
+            summary = orders_df.groupby("Rep").agg({
+                "Order Value": "sum",
+                "Order Received": "count"
+            }).rename(columns={"Order Received": "Orders Count"}).reset_index()
+            return summary
+
+        order_date.change(fn=orders_summary, inputs=order_date, outputs=orders_output)
+
+app.launch()