Update app.py

app.py

@@ -6,89 +6,56 @@ from salesforce_integration import fetch_poles
 from modules.visuals import display_dashboard, display_charts
 
 # Title
-st.title("📡 VIEP Smart Poles Dashboard")
+st.title("VIEP Smart Poles Dashboard")
 
 # Fetch the raw data from Salesforce
 df = fetch_poles()
 
 # --- Sidebar Filters ---
-st.sidebar.header("📁 Filter Data")
-
-# Alert Level Filter
+st.sidebar.header("Filter Data")
 selected_alert_levels = st.sidebar.multiselect(
     "Alert Level", ["Red", "Yellow", "Green"], default=["Red", "Yellow", "Green"]
 )
-
-# Camera Status Filter
-selected_camera_status = st.sidebar.selectbox(
-    "Camera Status", ["All", "Online", "Offline"]
-)
-
-# Site Filter with "All" option
+selected_camera_status = st.sidebar.selectbox("Camera Status", ["All", "Online", "Offline"])
 site_options = ["All"] + df["Site__c"].dropna().unique().tolist()
 selected_site = st.sidebar.selectbox("Site", site_options, index=0)
 
 # --- Filtering Logic ---
 filtered_df = df[df["Alert_Level__c"].isin(selected_alert_levels)]
-
 if selected_camera_status != "All":
     filtered_df = filtered_df[filtered_df["Camera_Status__c"] == selected_camera_status]
-
 if selected_site != "All":
     filtered_df = filtered_df[filtered_df["Site__c"] == selected_site]
 
-# --- Count Faults Based on Alert Level ---
-# Assuming default 0 fault count or based on Alert Level:
-filtered_df["Fault_Count__c"] = filtered_df["Alert_Level__c"].apply(
-    lambda x: 3 if x == "Red" else (2 if x == "Yellow" else 1)
-)
-
 # --- Display System Summary ---
 display_dashboard(filtered_df)
 
 # --- Pole Table ---
-st.subheader("📋 Pole Table")
+st.subheader("Pole Table")
 st.dataframe(filtered_df, use_container_width=True)
 
 # --- Energy Generation Chart ---
 st.subheader("⚙ Energy Generation (Solar vs Wind)")
 st.plotly_chart(px.bar(
-    filtered_df,
-    x="Name",
-    y=["Solar_Generation__c", "Wind_Generation__c"],
-    barmode="group"
+    filtered_df, x="Name", y=["Solar_Generation__c", "Wind_Generation__c"], barmode="group"
 ))
 
-
 # --- Alert Level Breakdown Chart ---
 display_charts(filtered_df)
 
-
-# Fetch the raw data from Salesforce
-df = fetch_poles()
-
 # Define function to generate heatmap based on site
 def generate_heatmap_for_site(site_name, df):
     site_df = df[df['Site__c'] == site_name]
 
-    # Define color mapping for fault levels
-    def get_fault_level(fault_count):
-        if fault_count <= 1:
-            return "Green"
-        elif 2 <= fault_count <= 3:
-            return "Yellow"
-        else:
-            return "Red"
-
+    # Define color mapping for alert levels
     color_map = {
         "Green": [0, 255, 0],
         "Yellow": [255, 255, 0],
         "Red": [255, 0, 0]
     }
 
-    print(df.columns)  # Add this to see the available columns
-    site_df["Fault_Level"] = site_df["Faults_Count"].apply(get_fault_level)
-    site_df["color"] = site_df["Fault_Level"].map(color_map)
+    # Assign colors based on Alert Level
+    site_df["color"] = site_df["Alert_Level__c"].map(color_map)
 
     # Create a Pydeck map for the site
     layer = pdk.Layer(
@@ -112,7 +79,6 @@ def generate_heatmap_for_site(site_name, df):
         "html": """
             <b>Pole Name:</b> {Name}<br>
             <b>Site:</b> {Site__c}<br>
-            <b>Fault Count:</b> {Fault_Count__c}<br>
             <b>Alert Level:</b> {Alert_Level__c}<br>
             <b>RFID Tag:</b> {RFID_Tag__c}<br>
             <b>Tilt:</b> {Tilt__c}<br>
@@ -130,19 +96,17 @@ def generate_heatmap_for_site(site_name, df):
         layers=[layer],
         tooltip=tooltip
     )
-print(df.columns)
+
 # Divide into four columns (Hyderabad, Kurnool, Ballari, Gadwal)
 col1, col2 = st.columns(2)
 with col1:
     st.subheader("Hyderabad")
     st.pydeck_chart(generate_heatmap_for_site("Hyderabad", df))
-
     st.subheader("Kurnool")
     st.pydeck_chart(generate_heatmap_for_site("Kurnool", df))
 
 with col2:
     st.subheader("Ballari")
     st.pydeck_chart(generate_heatmap_for_site("Ballari", df))
-
     st.subheader("Gadwal")
     st.pydeck_chart(generate_heatmap_for_site("Gadwal", df))