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Update app.py
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app.py
CHANGED
@@ -27,111 +27,181 @@ def load_tab(sheet_name):
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return pd.DataFrame([["β οΈ Could not load sheet."]], columns=["Error"])
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def haversine(coord1, coord2):
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def load_field_sales():
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df = load_tab("Field Sales")
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if df.empty:
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return pd.DataFrame(columns=["Date", "Rep", "Order Value", "Order Received", "Location", "KM Travelled"])
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df['Date'] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
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df = df.dropna(subset=["Date"])
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df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
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df["KM Travelled"] = 0.0
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for rep in df["Rep"].unique():
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rep_df = df[df["Rep"] == rep].sort_values(by="Date")
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prev_coord = None
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for idx, row in rep_df.iterrows():
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curr_coord = row.get("Location", "")
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if prev_coord
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km = haversine(prev_coord, curr_coord)
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df.at[idx, "KM Travelled"] = km
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except:
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df.at[idx, "KM Travelled"] = 0
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prev_coord = curr_coord
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return df
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def
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df =
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df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
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return df
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gr.Dataframe(dealer_df, label="Dealership Directory")
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with gr.Tab("Users"):
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gr.Dataframe(users_df, label="Users")
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return gr.update(visible=False), gr.update(visible=True)
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else:
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return "
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demo.launch()
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return pd.DataFrame([["β οΈ Could not load sheet."]], columns=["Error"])
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def haversine(coord1, coord2):
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try:
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lon1, lat1 = map(radians, map(float, coord1.split(',')[::-1]))
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lon2, lat2 = map(radians, map(float, coord2.split(',')[::-1]))
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dlon = lon2 - lon1
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dlat = lat2 - lat1
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a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
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c = 2 * asin(sqrt(a))
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return round(6371 * c, 2)
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except:
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return 0.0
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# ------------------ FIELD SALES ------------------
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def load_field_sales():
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df = load_tab("Field Sales")
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if df.empty:
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return pd.DataFrame(columns=["Date", "Rep", "Order Value", "Order Received", "Location", "DateStr", "KM Travelled"])
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df['Date'] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
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df = df.dropna(subset=["Date"])
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df['DateStr'] = df['Date'].dt.date.astype(str)
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df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
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df["KM Travelled"] = 0.0
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for rep in df["Rep"].unique():
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rep_df = df[df["Rep"] == rep].sort_values(by="Date")
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prev_coord = None
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for idx, row in rep_df.iterrows():
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curr_coord = row.get("Location", "")
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if prev_coord:
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df.at[idx, "KM Travelled"] = haversine(prev_coord, curr_coord)
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prev_coord = curr_coord
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return df
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def get_field_summary():
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df = load_field_sales()
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if df.empty:
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return pd.DataFrame([["No data available"]], columns=["Message"])
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summary = df.groupby("Rep").agg({
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"Order Value": "sum",
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"Order Received": lambda x: (x == "Yes").sum(),
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"KM Travelled": "sum"
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}).reset_index().rename(columns={
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"Order Value": "Total Order Value",
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"Order Received": "Orders Received"
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})
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return summary
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# ------------------ TELESALES ------------------
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def get_telesales_summary():
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df = load_tab("TeleSales")
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if df.empty or "Rep" not in df.columns:
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return pd.DataFrame([["No data available"]], columns=["Message"])
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df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
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df["DateStr"] = df["Date"].dt.date.astype(str)
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df["Order Value"] = pd.to_numeric(df.get("Order Value", 0), errors="coerce").fillna(0)
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summary = df.groupby("Rep").agg({
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"Order Value": "sum",
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"Order Received": lambda x: (x == "Yes").sum()
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}).reset_index().rename(columns={
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"Order Value": "Total Order Value",
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"Order Received": "Orders Received"
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})
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return summary
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# ------------------ COMBINED ORDERS ------------------
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def get_combined_orders():
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fs = get_field_summary()
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ts = get_telesales_summary()
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fs["Source"] = "Field Sales"
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ts["Source"] = "TeleSales"
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combined = pd.concat([fs, ts], ignore_index=True)
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return combined[["Rep", "Orders Received", "Total Order Value", "Source"]].sort_values(by="Total Order Value", ascending=False)
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# ------------------ OEM VISITS ------------------
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def get_oem_summary():
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df = load_tab("OEM Visit")
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if df.empty or "Rep" not in df.columns:
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return pd.DataFrame([["No data available"]], columns=["Message"])
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df["Date"] = pd.to_datetime(df.get("Date", datetime.today()), errors='coerce')
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df["DateStr"] = df["Date"].dt.date.astype(str)
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return df.groupby(["Rep", "DateStr"]).size().reset_index(name="OEM Visits")
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# ------------------ OTHER TABS ------------------
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def get_requests():
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df = load_tab("Customer Requests")
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return df if not df.empty else pd.DataFrame([["No requests yet."]], columns=["Message"])
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def get_listings():
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df = load_tab("CustomerListings")
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return df if not df.empty else pd.DataFrame([["No listings found."]], columns=["Message"])
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def get_users():
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df = load_tab("Users")
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return df if not df.empty else pd.DataFrame([["No users configured."]], columns=["Message"])
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def get_escalations():
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df = load_field_sales()
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col = "Customer Type & Status"
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if col in df.columns:
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flagged = df[df[col].str.contains("Second", na=False)]
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return flagged if not flagged.empty else pd.DataFrame([["No second-hand dealerships flagged."]], columns=["Message"])
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else:
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return pd.DataFrame([["β οΈ Column 'Customer Type & Status' not found."]], columns=["Message"])
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# ------------------ GRADIO APP ------------------
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with gr.Blocks() as app:
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with gr.Row():
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with gr.Column(visible=True) as login_ui:
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gr.Markdown("## π Login Required")
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email = gr.Textbox(label="Email")
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password = gr.Textbox(label="Password", type="password")
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login_btn = gr.Button("Login")
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login_msg = gr.Markdown("")
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with gr.Column(visible=False) as main_ui:
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gr.Markdown("## ποΈ CarMat Dashboard")
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# --- Summary Tab ---
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with gr.Tab("π Summary"):
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summary_table = gr.Dataframe(label="Combined Orders", value=get_combined_orders)
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# --- Field Sales Tab ---
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with gr.Tab("π£οΈ Field Sales"):
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fs_table = gr.Dataframe(label="Field Sales Summary", value=get_field_summary)
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fs_raw = gr.Dataframe(label="Raw Field Sales", value=load_field_sales)
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# --- Telesales Tab ---
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with gr.Tab("π TeleSales"):
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ts_table = gr.Dataframe(label="TeleSales Summary", value=get_telesales_summary)
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# --- Orders Tab ---
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with gr.Tab("π¦ Orders"):
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order_table = gr.Dataframe(label="All Orders Combined", value=get_combined_orders)
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# --- Escalations ---
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with gr.Tab("π¨ Escalations"):
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esc_table = gr.Dataframe(value=get_escalations, label="Second-hand Dealerships")
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esc_btn = gr.Button("π Refresh")
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esc_btn.click(fn=get_escalations, outputs=esc_table)
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# --- OEM Visits ---
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with gr.Tab("π OEM Visits"):
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oem_table = gr.Dataframe(value=get_oem_summary, label="OEM Visit Summary")
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oem_refresh = gr.Button("π Refresh OEM")
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oem_refresh.click(fn=get_oem_summary, outputs=oem_table)
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# --- Requests ---
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with gr.Tab("π¬ Customer Requests"):
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req_table = gr.Dataframe(value=get_requests, label="Customer Requests", interactive=False)
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req_refresh = gr.Button("π Refresh Requests")
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req_refresh.click(fn=get_requests, outputs=req_table)
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# --- Dealership Listings ---
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with gr.Tab("π Dealership Directory"):
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listings_table = gr.Dataframe(value=get_listings, label="Customer Listings")
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listings_refresh = gr.Button("π Refresh Listings")
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listings_refresh.click(fn=get_listings, outputs=listings_table)
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# --- Users ---
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with gr.Tab("π€ Users"):
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users_table = gr.Dataframe(value=get_users, label="Users")
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users_refresh = gr.Button("π Refresh Users")
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users_refresh.click(fn=get_users, outputs=users_table)
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def do_login(user, pw):
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if VALID_USERS.get(user) == pw:
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return gr.update(visible=False), gr.update(visible=True), ""
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else:
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return gr.update(visible=True), gr.update(visible=False), "β Invalid login."
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login_btn.click(fn=do_login, inputs=[email, password], outputs=[login_ui, main_ui, login_msg])
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app.launch()
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