Create app.py

app.py

@@ -0,0 +1,85 @@
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+import numpy as np
+import time
+
+# Simulated data (you can replace this with data from salesforce_integration.py or simulator.py)
+def generate_mock_data(n=100):
+    np.random.seed(42)
+    data = {
+        "PoleID": [f"Pole_{i:05}" for i in range(n)],
+        "Site": np.random.choice(["Site 1", "Site 2", "Site 3", "Site 4"], n),
+        "SolarGen(kWh)": np.random.uniform(2.0, 6.0, n),
+        "WindGen(kWh)": np.random.uniform(0.5, 2.0, n),
+        "Tilt(°)": np.random.uniform(0, 15, n),
+        "Vibration(g)": np.random.uniform(0, 3, n),
+        "CameraStatus": np.random.choice(["Online", "Offline"], n),
+        "PowerSufficient": np.random.choice(["Yes", "No"], n),
+    }
+    df = pd.DataFrame(data)
+    
+    # Rule-based alert level
+    df["Anomalies"] = df.apply(lambda row: [
+        "LowSolarOutput" if row["SolarGen(kWh)"] < 4.0 else "",
+        "LowWindOutput" if row["WindGen(kWh)"] < 0.7 else "",
+        "PoleTiltRisk" if row["Tilt(°)"] > 10 else "",
+        "VibrationAlert" if row["Vibration(g)"] > 2.0 else "",
+        "CameraOffline" if row["CameraStatus"] == "Offline" else "",
+        "PowerInsufficient" if row["PowerSufficient"] == "No" else "",
+    ], axis=1)
+    
+    df["Anomalies"] = df["Anomalies"].apply(lambda x: [a for a in x if a])
+    df["AlertLevel"] = df["Anomalies"].apply(lambda x: "Green" if len(x) == 0 else "Yellow" if len(x) == 1 else "Red")
+    return df
+
+# Visuals
+def show_heatmap(df):
+    st.subheader("🌡️ Fault Distribution Heatmap")
+
+    map_data = df.groupby(['Site', 'AlertLevel']).size().reset_index(name="Count")
+    fig = px.density_heatmap(
+        map_data, x="Site", y="AlertLevel", z="Count", color_continuous_scale="Reds", title="Alerts per Site"
+    )
+    st.plotly_chart(fig, use_container_width=True)
+
+def show_red_alerts(df):
+    st.subheader("🚨 Blinking Red Alert Poles")
+    red_df = df[df["AlertLevel"] == "Red"]
+    if red_df.empty:
+        st.success("No red alerts right now!")
+        return
+
+    for _, row in red_df.iterrows():
+        with st.container():
+            st.markdown(
+                f"<div style='padding:8px; background-color:#ffcccc; animation: blink 1s infinite;'>"
+                f"<strong>{row['PoleID']}</strong>: {', '.join(row['Anomalies'])}</div>",
+                unsafe_allow_html=True
+            )
+
+    st.markdown(
+        """
+        <style>
+        @keyframes blink {
+            50% { background-color: #ff4d4d; }
+        }
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
+
+# Main
+st.set_page_config("VIEP Heatmap Dashboard", layout="wide")
+st.title("🌍 Vedavathi Smart Pole Monitoring Dashboard")
+
+df = generate_mock_data()
+
+# Filters
+alert_filter = st.selectbox("Filter by Alert Level", ["All", "Green", "Yellow", "Red"])
+if alert_filter != "All":
+    df = df[df["AlertLevel"] == alert_filter]
+
+# Views
+show_heatmap(df)
+show_red_alerts(df)