Update app.py

app.py

@@ -3,35 +3,14 @@ import pandas as pd
 import plotly.express as px
 from simple_salesforce import Salesforce
 
-# Page configuration
-st.set_page_config(page_title="Vedavathi Pole Dashboard", layout="wide")
-
-# -------------------------------
-# Connect to Salesforce
-# -------------------------------
-@st.cache_resource
-def connect_salesforce():
-    try:
-        sf = Salesforce(
-            username="[email protected]",
-            password="Vedavathi@04",
-            security_token="jqe4His8AcuFJucZz5NBHfGU",
-            domain="login"
-        )
-        return sf
-    except Exception as e:
-        st.error(f"❌ Failed to connect to Salesforce: {e}")
-        return None
-
-sf = connect_salesforce()
-
-# -------------------------------
-# Main App Logic
-# -------------------------------
-if sf:
-    st.success("✅ Connected to Salesforce")
-
-    # Query Pole data
+# 🔐 Connect to Salesforce
+sf = Salesforce(
+    username="[email protected]",
+    password="Vedavathi@04",
+    security_token="jqe4His8AcuFJucZz5NBHfGU"
+)
+
+# 📄 Query to get Pole records
 query = """
 SELECT Id,
        Name,
@@ -49,92 +28,87 @@ SELECT Id,
 FROM Pole__c
 LIMIT 1000
 """
-result = sf.query_all(query)
- df = pd.DataFrame(result['records']).drop(columns='attributes')
-
-    # Clean and format data
-    df['Installed_Date__c'] = pd.to_datetime(df['Installed_Date__c'])
-    df['Last_Maintenance_Date__c'] = pd.to_datetime(df['Last_Maintenance_Date__c'])
-    df['Power_Generation__c'] = pd.to_numeric(df['Power_Generation__c'], errors='coerce')
-
-    # Sidebar filters
-    st.sidebar.header("🔍 Filters")
-    status_filter = st.sidebar.multiselect("Select Pole Status", df['Status__c'].unique(), default=df['Status__c'].unique())
-    fault_filter = st.sidebar.multiselect("Select Fault Status", df['Fault_Status__c'].unique(), default=df['Fault_Status__c'].unique())
-
-    # Apply filters
-    filtered_df = df[
-        df['Status__c'].isin(status_filter) &
-        df['Fault_Status__c'].isin(fault_filter)
-    ]
-
-    st.title("⚡ Vedavathi Smart Pole Dashboard")
-
-    # -------------------------------
-    # 📋 Data Table
-    # -------------------------------
-    st.subheader("📋 Pole Data Table")
-    st.dataframe(filtered_df)
 
-    # -------------------------------
-    # 🔋 Bar Chart - Power Generation
-    # -------------------------------
-    st.subheader("🔋 Power Generation per Pole")
-    fig_bar = px.bar(
-        filtered_df,
-        x='Name',
-        y='Power_Generation__c',
-        color='Status__c',
-        title="Power Output by Pole",
-        height=400
-    )
-    st.plotly_chart(fig_bar, use_container_width=True)
-
-    # -------------------------------
-    # ⚠️ Pie Chart - Fault Status
-    # -------------------------------
-    st.subheader("⚠️ Fault Status Distribution")
-    pie_data = filtered_df['Fault_Status__c'].value_counts().reset_index()
-    pie_data.columns = ['Fault Status', 'Count']
-    fig_pie = px.pie(
-        pie_data,
-        names='Fault Status',
-        values='Count',
-        title="Fault Breakdown",
-        height=400
-    )
-    st.plotly_chart(fig_pie, use_container_width=True)
-
-    # -------------------------------
-    # 🕒 Line Chart - Installations
-    # -------------------------------
-    st.subheader("🕒 Installation Trend")
-    install_trend = filtered_df.groupby(filtered_df['Installed_Date__c'].dt.to_period('M')).size()
-    install_trend.index = install_trend.index.to_timestamp()
-    fig_line_install = px.line(
-        x=install_trend.index,
-        y=install_trend.values,
-        labels={"x": "Month", "y": "Poles Installed"},
-        title="Installations Over Time",
-        markers=True
-    )
-    st.plotly_chart(fig_line_install, use_container_width=True)
-
-    # -------------------------------
-    # 🛠️ Line Chart - Maintenance
-    # -------------------------------
-    st.subheader("🛠️ Maintenance Trend")
-    maint_trend = filtered_df.groupby(filtered_df['Last_Maintenance_Date__c'].dt.to_period('M')).size()
-    maint_trend.index = maint_trend.index.to_timestamp()
-    fig_line_maint = px.line(
-        x=maint_trend.index,
-        y=maint_trend.values,
-        labels={"x": "Month", "y": "Maintenance Events"},
-        title="Maintenance Over Time",
-        markers=True
+# 📦 Fetch and flatten records
+result = sf.query_all(query)
+df = pd.json_normalize(result['records'])
+
+# 🧼 Remove 'attributes' column if present
+df = df.drop(columns='attributes', errors='ignore')
+
+# 🖥️ Streamlit App Layout
+st.set_page_config(page_title="VIEP Dashboard", layout="wide")
+st.title("🔌 Vedavathi Intelligent Energy Poles Dashboard")
+
+# 📋 Show Full Table
+st.subheader("📋 Pole Data Table")
+st.dataframe(df)
+
+# 🔋 Bar Chart: Solar vs Wind Generation
+st.subheader("🔋 Solar vs Wind Generation")
+fig_bar = px.bar(
+    df,
+    x="Name",
+    y=["Solar_Generation__c", "Wind_Generation__c"],
+    barmode="group",
+    labels={"value": "Power (kW)", "Name": "Pole"},
+    title="Power Generation per Pole"
+)
+st.plotly_chart(fig_bar, use_container_width=True)
+
+# 🎥 Pie Chart: Camera Status
+st.subheader("🎥 Camera Status Distribution")
+fig_cam = px.pie(
+    df,
+    names="Camera_Status__c",
+    title="Camera Status",
+    hole=0.3
+)
+st.plotly_chart(fig_cam, use_container_width=True)
+
+# 🚨 Pie Chart: Alert Level
+st.subheader("🚨 Alert Level Distribution")
+fig_alert = px.pie(
+    df,
+    names="Alert_Level__c",
+    title="Alert Level",
+    hole=0.3
+)
+st.plotly_chart(fig_alert, use_container_width=True)
+
+# 📈 Health Score by Site
+st.subheader("📈 Health Score by Site")
+fig_health = px.box(
+    df,
+    x="Site__c",
+    y="Health_Score__c",
+    points="all",
+    title="Health Score Distribution",
+    labels={"Site__c": "Site", "Health_Score__c": "Health Score"}
+)
+st.plotly_chart(fig_health, use_container_width=True)
+
+# 🗺️ Map of Pole Locations
+st.subheader("🗺️ Pole Locations Map")
+df_map = df.dropna(subset=["Location_Latitude__c", "Location_Longitude__c"])
+if not df_map.empty:
+    fig_map = px.scatter_mapbox(
+        df_map,
+        lat="Location_Latitude__c",
+        lon="Location_Longitude__c",
+        hover_name="Name",
+        color="Alert_Level__c",
+        zoom=4,
+        mapbox_style="open-street-map"
     )
-    st.plotly_chart(fig_line_maint, use_container_width=True)
-
+    st.plotly_chart(fig_map, use_container_width=True)
 else:
-    st.error("❌ Could not connect to Salesforce. Check your credentials.")
-
+    st.warning("No location data available to show the map.")
+
+# 📥 Download CSV
+st.download_button(
+    label="⬇️ Download Data as CSV",
+    data=df.to_csv(index=False),
+    file_name="pole_data.csv",
+    mime="text/csv"
+)