Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import plotly.express as px
+import plotly.graph_objects as go
+from datetime import datetime, timedelta
+import random
+from io import BytesIO
+import base64
+
+# Page config
+st.set_page_config(
+    page_title="ESG Compliance Intelligence",
+    page_icon="🌱",
+    layout="wide"
+)
+
+# CSS styling
+st.markdown("""
+<style>
+.metric-card {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    padding: 1rem; border-radius: 10px; color: white; text-align: center;
+}
+.alert-red { background: #fee2e2; border-left: 4px solid #dc2626; padding: 1rem; }
+.alert-green { background: #d1fae5; border-left: 4px solid #059669; padding: 1rem; }
+</style>
+""", unsafe_allow_html=True)
+
+# Generate mock data
+@st.cache_data
+def generate_realtime_data():
+    now = datetime.now()
+    data = []
+    for i in range(24):
+        time_point = now - timedelta(hours=i)
+        data.append({
+            'time': time_point.strftime('%H:%M'),
+            'ph_level': 7.2 + random.uniform(-0.3, 0.3),
+            'wastewater': 45 + random.uniform(-5, 10),
+            'co2_emission': 12.5 + random.uniform(-2, 3),
+            'energy_consumption': 85 + random.uniform(-10, 15)
+        })
+    return pd.DataFrame(data)
+
+def generate_carbon_data():
+    return pd.DataFrame({
+        'source': ['Fuel', 'Electricity', 'Chemicals', 'Transport'],
+        'co2_kg': [145.2, 67.8, 89.1, 19.6],
+        'percentage': [45, 21, 28, 6]
+    })
+
+def generate_psa_report():
+    """Generate PSA compliance report"""
+    report_id = f"PSA-ENV-{datetime.now().strftime('%Y%m%d%H%M')}"
+    return {
+        'report_id': report_id,
+        'timestamp': datetime.now().isoformat(),
+        'location': 'Statoil Platform Alpha',
+        'ph_level': 7.4,
+        'wastewater_volume': 487.2,
+        'co2_total': 321.7,
+        'compliance_status': random.choice(['COMPLIANT', 'WARNING', 'VIOLATION'])
+    }
+
+# Main app
+def main():
+    st.title("🌱 ESG & Compliance Intelligence Engine")
+    st.subheader("Norwegian Petroleum Safety Authority (PSA) Real-time Monitoring")
+    
+    # Sidebar
+    with st.sidebar:
+        st.header("Controls")
+        auto_refresh = st.checkbox("Auto-refresh data", value=True)
+        if st.button("Generate PSA Report"):
+            report = generate_psa_report()
+            st.success(f"Report Generated: {report['report_id']}")
+            st.json(report)
+    
+    # Data
+    df_realtime = generate_realtime_data()
+    df_carbon = generate_carbon_data()
+    
+    # Status alerts
+    compliance_status = random.choice(['COMPLIANT', 'WARNING', 'VIOLATION'])
+    if compliance_status == 'VIOLATION':
+        st.markdown('<div class="alert-red">⚠️ ALERT: Wastewater discharge exceeds PSA limits!</div>', 
+                   unsafe_allow_html=True)
+    elif compliance_status == 'WARNING':
+        st.markdown('<div class="alert-red">⚠️ WARNING: pH level approaching upper limit</div>', 
+                   unsafe_allow_html=True)
+    else:
+        st.markdown('<div class="alert-green">✅ All systems compliant with PSA regulations</div>', 
+                   unsafe_allow_html=True)
+    
+    # Metrics row
+    col1, col2, col3, col4 = st.columns(4)
+    
+    with col1:
+        st.metric("Compliance Status", 
+                 "COMPLIANT" if compliance_status == 'COMPLIANT' else "ALERT",
+                 delta="Normal" if compliance_status == 'COMPLIANT' else "Action Required")
+    
+    with col2:
+        current_ph = df_realtime.iloc[0]['ph_level']
+        st.metric("Water pH Level", f"{current_ph:.1f}", 
+                 delta=f"{current_ph - 7.2:.1f}" if current_ph > 7.2 else None)
+    
+    with col3:
+        total_co2 = df_carbon['co2_kg'].sum()
+        st.metric("Total CO₂", f"{total_co2:.1f} kg", delta="-12.3 kg")
+    
+    with col4:
+        current_energy = df_realtime.iloc[0]['energy_consumption']
+        st.metric("Energy Usage", f"{current_energy:.0f} kWh", delta="5.2 kWh")
+    
+    # Charts
+    col1, col2 = st.columns(2)
+    
+    with col1:
+        st.subheader("Real-time Environmental Monitoring")
+        fig_line = px.line(df_realtime, x='time', y=['ph_level', 'wastewater'], 
+                          title="pH Level & Wastewater Discharge")
+        fig_line.update_layout(height=400)
+        st.plotly_chart(fig_line, use_container_width=True)
+    
+    with col2:
+        st.subheader("Carbon Footprint Breakdown")
+        fig_bar = px.bar(df_carbon, x='source', y='co2_kg', 
+                        title="CO₂ Emissions by Source")
+        fig_bar.update_layout(height=400)
+        st.plotly_chart(fig_bar, use_container_width=True)
+    
+    # PSA Reports Table
+    st.subheader("PSA Compliance Reports History")
+    
+    reports_data = pd.DataFrame({
+        'Report ID': ['PSA-ENV-2024-001', 'PSA-ENV-2024-002', 'PSA-ENV-2024-003'],
+        'Generated': ['2024-08-27 14:30', '2024-08-27 10:15', '2024-08-26 16:45'],
+        'Location': ['Statoil Platform Alpha', 'Equinor Platform Beta', 'Aker BP Platform Gamma'],
+        'Status': ['COMPLIANT', 'WARNING', 'COMPLIANT'],
+        'CO₂ (kg)': [321.7, 345.2, 298.1]
+    })
+    
+    st.dataframe(reports_data, use_container_width=True)
+    
+    # Download buttons
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        if st.button("📄 Download PDF Report"):
+            st.success("PDF report generated successfully!")
+    with col2:
+        if st.button("📊 Export Excel"):
+            st.success("Excel file exported!")
+    with col3:
+        if st.button("📋 PSA Submission"):
+            st.success("Report submitted to PSA portal!")
+    
+    # Footer
+    st.markdown("---")
+    st.markdown("""
+    🔒 **Security**: AES-256 encryption | 
+    📊 **Updates**: Real-time every 5 seconds | 
+    ✅ **Compliance**: GDPR & Norwegian Data Protection
+    """)
+    
+    # Auto-refresh
+    if auto_refresh:
+        time.sleep(5)
+        st.rerun()
+
+if __name__ == "__main__":
+    main()