Update app.py

app.py

@@ -1,24 +1,16 @@
-import streamlit as st
 import pandas as pd
-import plotly.express as px
+import streamlit as st
 import pydeck as pdk
 from salesforce_integration import fetch_poles
-from modules.visuals import display_dashboard, display_charts
-
-# Title
-st.title("VIEP Smart Poles Dashboard")
 
 # Fetch the raw data from Salesforce
 df = fetch_poles()
 
 # --- Sidebar Filters ---
 st.sidebar.header("Filter Data")
-selected_alert_levels = st.sidebar.multiselect(
-    "Alert Level", ["Red", "Yellow", "Green"], default=["Red", "Yellow", "Green"]
-)
+selected_site = st.sidebar.selectbox("Site", ["All"] + df["Site__c"].dropna().unique().tolist(), index=0)
+selected_alert_levels = st.sidebar.multiselect("Alert Level", ["Red", "Yellow", "Green"], default=["Red", "Yellow", "Green"])
 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)]
@@ -27,89 +19,65 @@ if selected_camera_status != "All":
 if selected_site != "All":
     filtered_df = filtered_df[filtered_df["Site__c"] == selected_site]
 
-# --- Display System Summary ---
-display_dashboard(filtered_df)
-
-# --- Pole Table ---
-st.subheader("Pole Table")
+# --- Display Summary ---
+st.title("Smart Pole Monitoring")
+col1, col2, col3 = st.columns(3)
+col1.metric("Total Poles", filtered_df.shape[0])
+col2.metric("Red Alerts", filtered_df[filtered_df['Alert_Level__c'] == 'Red'].shape[0])
+col3.metric("Power Insufficiencies", filtered_df[filtered_df['Power_Status__c'] == 'Insufficient'].shape[0])
+
+# --- Table View ---
+st.subheader("Pole Data Table")
+with st.expander("Filter Options"):
+    alert_filter = st.multiselect("Alert Level", options=filtered_df['Alert_Level__c'].unique(), default=filtered_df['Alert_Level__c'].unique())
+    camera_filter = st.multiselect("Camera Status", options=filtered_df['Camera_Status__c'].unique(), default=filtered_df['Camera_Status__c'].unique())
+    filtered_df = filtered_df[(filtered_df['Alert_Level__c'].isin(alert_filter)) & (filtered_df['Camera_Status__c'].isin(camera_filter))]
 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"
-))
-
-# --- Alert Level Breakdown Chart ---
-display_charts(filtered_df)
-
-# Define function to generate heatmap based on site
-def generate_heatmap_for_site(site_name, df):
-    site_df = df[df['Site__c'] == site_name]
-
-     # Ensure that Alert_Level__c is treated as a string (for color mapping)
-    site_df['Alert_Level__c'] = site_df['Alert_Level__c'].astype(str)
-    
-    # Define color mapping for alert levels
-    color_map = {
-        "Green": [0, 255, 0],
-        "Yellow": [255, 255, 0],
-        "Red": [255, 0, 0]
-    }
-
-    # Create a color column based on Alert_Level__c
-    site_df["color"] = site_df["Alert_Level__c"].map(color_map)
-
-    # Create a Pydeck map for the site
-    layer = pdk.Layer(
-        "ScatterplotLayer",
-        data=site_df,
-        get_position='[Longitude__c, Latitude__c]',
-        get_color="color",
-        get_radius=80, # You can adjust the radius if needed
-        pickable=True,
-        auto_highlight=True
-    )
-
-    view_state = pdk.ViewState(
-        latitude=site_df["Location_Latitude__c"].mean(),
-        longitude=site_df["Location_Longitude__c"].mean(),
-        zoom=10,
-        pitch=40
-    )
-
-    tooltip = {
-        "html": """
-            <b>Pole Name:</b> {Name}<br>
-            <b>Site:</b> {Site__c}<br>
-            <b>Alert Level:</b> {Alert_Level__c}<br>
-            <b>RFID Tag:</b> {RFID_Tag__c}<br>
-            <b>Tilt:</b> {Tilt__c}<br>
-            <b>Vibration:</b> {Vibration__c}
-        """,
-        "style": {
-            "backgroundColor": "steelblue",
-            "color": "white"
+# --- Map Section with Tooltip ---
+def alert_level_to_color(alert_level):
+    if alert_level == 'Red':
+        return [255, 0, 0, 160]  # Red
+    elif alert_level == 'Yellow':
+        return [255, 255, 0, 160]  # Yellow
+    else:
+        return [0, 255, 0, 160]  # Green
+
+if not filtered_df.empty:
+    filtered_df = filtered_df.copy()
+    filtered_df['Color'] = filtered_df['Alert_Level__c'].apply(alert_level_to_color)
+
+    st.pydeck_chart(pdk.Deck(
+        initial_view_state=pdk.ViewState(
+            latitude=filtered_df["Latitude__c"].mean(),
+            longitude=filtered_df["Longitude__c"].mean(),
+            zoom=12,
+            pitch=50
+        ),
+        layers=[
+            pdk.Layer(
+                'ScatterplotLayer',
+                data=filtered_df,
+                get_position='[Longitude__c, Latitude__c]',
+                get_color='Color',
+                get_radius=100,
+                pickable=True
+            )
+        ],
+        tooltip={
+            "html": """
+                <b>Pole ID:</b> {Name}<br>
+                <b>Alert Level:</b> {Alert_Level__c}<br>
+                <b>Health Score:</b> {Health_Score__c}<br>
+                <b>Power Status:</b> {Power_Status__c}<br>
+                <b>Camera Status:</b> {Camera_Status__c}<br>
+                <b>Last Checked:</b> {Last_Checked__c}
+            """,
+            "style": {
+                "backgroundColor": "black",
+                "color": "white"
+            }
         }
-    }
-   # Return the heatmap
-    return pdk.Deck(
-        map_style="mapbox://styles/mapbox/dark-v10",
-        initial_view_state=view_state,
-        layers=[layer],
-        tooltip=tooltip
-    )
-
-# 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))
+    ))
+else:
+    st.info("No data available for the selected filters.")