Update app.py

app.py

@@ -3,118 +3,109 @@ import gspread
 import gradio as gr
 from oauth2client.service_account import ServiceAccountCredentials
 from datetime import datetime
-import time
+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")
 
-# ------------------ RETRY LOGIC ------------------
-def load_tab(sheet_name, retries=3, delay=5):
-    for attempt in range(retries):
-        try:
-            df = pd.DataFrame(sheet_file.worksheet(sheet_name).get_all_records())
-            return df
-        except gspread.exceptions.APIError as e:
-            if attempt < retries - 1:
-                time.sleep(delay)
-            else:
-                return pd.DataFrame([[f"⚠️ API Error: {str(e)}"]], columns=["Error"])
-
-# ------------------ HELPERS ------------------
-def get_combined_orders(date_str):
-    df_field = load_tab("Field Sales")
-    df_ts = load_tab("TeleSales")
-
-    combined = []
-
-    if not df_field.empty:
-        df_field['Date'] = pd.to_datetime(df_field['Date'], errors='coerce')
-        df_field['DateStr'] = df_field['Date'].dt.date.astype(str)
-        df_field = df_field[df_field['DateStr'] == date_str.strip()]
-        df_field['Order Value'] = pd.to_numeric(df_field['Order Value'], errors='coerce').fillna(0)
-        df_field_orders = df_field.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"
-        })
-        df_field_orders["Source"] = "Field Sales"
-        combined.append(df_field_orders)
-
-    if not df_ts.empty:
-        df_ts['Date'] = pd.to_datetime(df_ts['Date'], errors='coerce')
-        df_ts['DateStr'] = df_ts['Date'].dt.date.astype(str)
-        df_ts = df_ts[df_ts['DateStr'] == date_str.strip()]
-        df_ts['Order Value'] = pd.to_numeric(df_ts['Order Value'], errors='coerce').fillna(0)
-        df_ts_orders = df_ts.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"
-        })
-        df_ts_orders["Source"] = "TeleSales"
-        combined.append(df_ts_orders)
-
-    if combined:
-        return pd.concat(combined, ignore_index=True)
-    else:
-        return pd.DataFrame([["No orders on this date"]], columns=["Message"])
-
-# Define other helper functions similarly using load_tab...
-
-# ------------------ GRADIO APP ------------------
+# 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"])
+
+# GPS calculations
+def calculate_gps_data(df):
+    df = df.sort_values(['Date', 'Time']).reset_index(drop=True)
+    df[['Latitude', 'Longitude']] = df['Location'].str.split(', ', expand=True).astype(float)
+
+    df['Kms Travelled'] = 0.0
+    df['Duration Between Calls (min)'] = 0.0
+
+    for i in range(1, len(df)):
+        prev_coords = (df.at[i-1, 'Latitude'], df.at[i-1, 'Longitude'])
+        current_coords = (df.at[i, 'Latitude'], df.at[i, 'Longitude'])
+        df.at[i, 'Kms Travelled'] = geodesic(prev_coords, current_coords).km
+
+        prev_time = pd.to_datetime(df.at[i-1, 'Date'] + ' ' + df.at[i-1, 'Time'])
+        current_time = pd.to_datetime(df.at[i, 'Date'] + ' ' + df.at[i, 'Time'])
+        df.at[i, 'Duration Between Calls (min)'] = (current_time - prev_time).total_seconds() / 60.0
+
+    return df
+
+# 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_tab("Field Sales")
-            unique_dates = sorted(df_initial["Date"].astype(str).unique(), reverse=True) if not df_initial.empty else []
-
-            # --- Tabs ---
-            with gr.Tab("📊 Summary"):
-                gr.Markdown("Summary content coming soon...")
-
-            with gr.Tab("📂 Field Sales"):
-                field_df = gr.Dataframe(value=load_tab("Field Sales"), label="📂 Field Sales Records", interactive=False)
-                gr.Button("🔄 Refresh").click(fn=lambda: load_tab("Field Sales"), outputs=field_df)
-
-            with gr.Tab("📞 TeleSales"):
-                ts_table = gr.Dataframe(value=load_tab("TeleSales"), label="📞 TeleSales Summary")
-                gr.Button("🔄 Refresh").click(fn=lambda: load_tab("TeleSales"), outputs=ts_table)
-
-            with gr.Tab("📦 Orders Summary"):
-                order_date = gr.Dropdown(label="Select Date", choices=unique_dates, interactive=True)
-                order_table = gr.Dataframe(label="🧾 Combined Order Summary")
-                order_date.change(fn=get_combined_orders, inputs=order_date, outputs=order_table)
-
-            # Continue similarly for other tabs...
-
-    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])
+    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()