Update app.py

app.py

@@ -4,445 +4,404 @@ 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 StringIO, BytesIO
 import base64
 import json
+from dataclasses import dataclass, asdict
+from typing import Optional, Dict, List
+import hashlib
 
-# Page config
-st.set_page_config(
-    page_title="ESG Compliance Intelligence",
-    page_icon="🌱",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
+# Configuration
+@dataclass
+class Config:
+    PAGE_TITLE = "ESG Compliance Intelligence"
+    PAGE_ICON = "🌱"
+    REQUIRED_COLUMNS = ['timestamp', 'ph_level', 'wastewater_lmin', 'co2_emission_kg', 'energy_kwh', 'location', 'status']
+    PH_RANGE = (6.0, 8.5)
+    WASTEWATER_LIMIT = 60.0
+    COMPLIANCE_THRESHOLD = 80
 
-# Enhanced CSS styling matching React design
-st.markdown("""
-<style>
-    .main-header {
-        background: linear-gradient(135deg, #1e40af 0%, #059669 100%);
-        padding: 2rem;
-        border-radius: 15px;
-        margin-bottom: 2rem;
-        color: white;
-        text-align: center;
-        box-shadow: 0 8px 32px rgba(0,0,0,0.1);
-    }
-    .metric-card {
-        background: white;
-        padding: 1.5rem;
-        border-radius: 12px;
-        border: 2px solid #e5e7eb;
-        box-shadow: 0 4px 20px rgba(0,0,0,0.08);
-        text-align: center;
-        height: 120px;
-        transition: transform 0.2s ease;
-    }
-    .metric-card:hover {
-        transform: translateY(-2px);
-    }
-    .alert-danger {
-        background: linear-gradient(135deg, #fef2f2 0%, #fee2e2 100%);
-        border-left: 4px solid #dc2626;
-        padding: 1rem;
-        border-radius: 8px;
-        margin: 1rem 0;
-        box-shadow: 0 2px 8px rgba(220, 38, 38, 0.1);
-    }
-    .alert-success {
-        background: linear-gradient(135deg, #f0fdf4 0%, #dcfce7 100%);
-        border-left: 4px solid #059669;
-        padding: 1rem;
-        border-radius: 8px;
-        margin: 1rem 0;
-        box-shadow: 0 2px 8px rgba(5, 150, 105, 0.1);
-    }
-    .alert-warning {
-        background: linear-gradient(135deg, #fffbeb 0%, #fef3c7 100%);
-        border-left: 4px solid #f59e0b;
-        padding: 1rem;
-        border-radius: 8px;
-        margin: 1rem 0;
-        box-shadow: 0 2px 8px rgba(245, 158, 11, 0.1);
-    }
-    .chart-container {
-        background: white;
-        padding: 1.5rem;
-        border-radius: 12px;
-        box-shadow: 0 4px 20px rgba(0,0,0,0.08);
-        margin: 1rem 0;
-        border: 1px solid #f1f5f9;
-    }
-    .footer-info {
-        text-align: center;
-        color: #64748b;
-        font-size: 0.9rem;
-        margin-top: 2rem;
-        padding: 1.5rem;
-        background: linear-gradient(135deg, #f8fafc 0%, #f1f5f9 100%);
-        border-radius: 12px;
-        border: 1px solid #e2e8f0;
-    }
-    .download-btn {
-        background: linear-gradient(135deg, #3b82f6 0%, #1d4ed8 100%);
-        border: none;
-        color: white;
-        padding: 0.75rem 1.5rem;
-        border-radius: 8px;
-        cursor: pointer;
-        font-weight: 500;
-        transition: all 0.2s ease;
-    }
-    .download-btn:hover {
-        transform: translateY(-1px);
-        box-shadow: 0 4px 12px rgba(59, 130, 246, 0.3);
-    }
-</style>
-""", unsafe_allow_html=True)
+# Data Models
+@dataclass
+class ComplianceReport:
+    report_id: str
+    timestamp: str
+    location: str
+    ph_level: float
+    wastewater_volume: float
+    co2_total: float
+    energy_consumption: float
+    compliance_status: str
+    generated_by: str = "ESG Compliance Engine"
+    
+    @classmethod
+    def from_dataframe_row(cls, row):
+        return cls(
+            report_id=f"PSA-ENV-{datetime.now().strftime('%Y%m%d%H%M')}",
+            timestamp=datetime.now().isoformat(),
+            location=row['location'],
+            ph_level=float(row['ph_level']),
+            wastewater_volume=float(row['wastewater_lmin']),
+            co2_total=float(row['co2_emission_kg']),
+            energy_consumption=float(row['energy_kwh']),
+            compliance_status=row['status'].upper()
+        )
+
+# Data Validation
+class DataValidator:
+    @staticmethod
+    def validate_csv_structure(df: pd.DataFrame) -> None:
+        missing_cols = [col for col in Config.REQUIRED_COLUMNS if col not in df.columns]
+        if missing_cols:
+            raise ValueError(f"Missing required columns: {', '.join(missing_cols)}")
+    
+    @staticmethod
+    def validate_data_types(df: pd.DataFrame) -> pd.DataFrame:
+        try:
+            df['timestamp'] = pd.to_datetime(df['timestamp'])
+            df['ph_level'] = pd.to_numeric(df['ph_level'])
+            df['wastewater_lmin'] = pd.to_numeric(df['wastewater_lmin'])
+            df['co2_emission_kg'] = pd.to_numeric(df['co2_emission_kg'])
+            df['energy_kwh'] = pd.to_numeric(df['energy_kwh'])
+            return df
+        except Exception as e:
+            raise ValueError(f"Data type conversion failed: {str(e)}")
+    
+    @staticmethod
+    def validate_ranges(df: pd.DataFrame) -> None:
+        if not df['ph_level'].between(0, 14).all():
+            raise ValueError("pH values must be between 0 and 14")
+        if (df[['wastewater_lmin', 'co2_emission_kg', 'energy_kwh']] < 0).any().any():
+            raise ValueError("Environmental measurements cannot be negative")
 
-# Sample CSV data for demo
-def get_sample_data():
-    return """timestamp,ph_level,wastewater_lmin,co2_emission_kg,energy_kwh,chemical_usage_kg,location,status
+# Data Management
+class DataManager:
+    @staticmethod
+    def get_sample_data() -> str:
+        return """timestamp,ph_level,wastewater_lmin,co2_emission_kg,energy_kwh,chemical_usage_kg,location,status
 2024-08-27 14:30,7.4,48.5,14.2,92,2.3,Statoil Platform Alpha,compliant
 2024-08-27 14:25,7.2,45.1,12.8,88,2.1,Statoil Platform Alpha,compliant
 2024-08-27 14:20,7.6,52.3,15.7,95,2.5,Statoil Platform Alpha,warning
 2024-08-27 14:15,7.8,55.2,16.1,98,2.8,Statoil Platform Alpha,violation
-2024-08-27 14:10,7.3,47.8,13.5,89,2.2,Statoil Platform Alpha,compliant
-2024-08-27 14:05,7.1,44.2,12.1,85,2.0,Statoil Platform Alpha,compliant"""
-
-# Load data function
-@st.cache_data
-def load_data(uploaded_file):
-    if uploaded_file:
-        df = pd.read_csv(uploaded_file)
-    else:
-        df = pd.read_csv(StringIO(get_sample_data()))
+2024-08-27 14:10,7.3,47.8,13.5,89,2.2,Statoil Platform Alpha,compliant"""
     
-    df['timestamp'] = pd.to_datetime(df['timestamp'])
-    return df
-
-# Carbon footprint data
-def get_carbon_data():
-    return pd.DataFrame({
-        'source': ['Fuel Consumption', 'Electricity', 'Chemicals', 'Transport'],
-        'co2_kg': [145.2, 67.8, 89.1, 19.6],
-        'percentage': [45, 21, 28, 6]
-    })
-
-# Generate PSA report with export functionality
-def generate_psa_report(df):
-    latest_data = df.iloc[-1]
-    report = {
-        'report_id': f"PSA-ENV-{datetime.now().strftime('%Y%m%d%H%M')}",
-        'timestamp': datetime.now().isoformat(),
-        'location': latest_data['location'],
-        'ph_level': float(latest_data['ph_level']),
-        'wastewater_volume': float(latest_data['wastewater_lmin']),
-        'co2_total': float(latest_data['co2_emission_kg']),
-        'energy_consumption': float(latest_data['energy_kwh']),
-        'compliance_status': latest_data['status'].upper(),
-        'generated_by': 'ESG Compliance Intelligence Engine',
-        'certification': 'PSA-Compliant Format'
-    }
-    return report
+    @staticmethod
+    @st.cache_data
+    def load_and_validate_data(uploaded_file) -> pd.DataFrame:
+        try:
+            if uploaded_file:
+                df = pd.read_csv(uploaded_file)
+            else:
+                df = pd.read_csv(StringIO(DataManager.get_sample_data()))
+            
+            DataValidator.validate_csv_structure(df)
+            df = DataValidator.validate_data_types(df)
+            DataValidator.validate_ranges(df)
+            return df
+            
+        except Exception as e:
+            st.error(f"Data loading error: {str(e)}")
+            return pd.DataFrame()
+    
+    @staticmethod
+    def get_carbon_footprint_data() -> pd.DataFrame:
+        return pd.DataFrame({
+            'source': ['Fuel Consumption', 'Electricity', 'Chemicals', 'Transport'],
+            'co2_kg': [145.2, 67.8, 89.1, 19.6],
+            'percentage': [45, 21, 28, 6]
+        })
 
-# Create downloadable PDF content
-def create_pdf_report(report_data, df):
-    html_content = f"""
-    <!DOCTYPE html>
-    <html>
-    <head>
-        <meta charset="UTF-8">
-        <title>PSA Environmental Compliance Report</title>
+# UI Components
+class UIComponents:
+    @staticmethod
+    def apply_styling():
+        st.markdown("""
         <style>
-            body {{ font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; margin: 40px; }}
-            .header {{ background: linear-gradient(135deg, #1e40af 0%, #059669 100%); 
-                      color: white; padding: 20px; border-radius: 8px; text-align: center; }}
-            .section {{ margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 8px; }}
-            .compliant {{ color: #059669; font-weight: bold; }}
-            .warning {{ color: #f59e0b; font-weight: bold; }}
-            .violation {{ color: #dc2626; font-weight: bold; }}
-            .data-table {{ width: 100%; border-collapse: collapse; margin: 10px 0; }}
-            .data-table th, .data-table td {{ border: 1px solid #ddd; padding: 8px; text-align: left; }}
-            .data-table th {{ background-color: #f8fafc; }}
+            .main-header {
+                background: linear-gradient(135deg, #1e40af 0%, #059669 100%);
+                padding: 2rem; border-radius: 15px; margin-bottom: 2rem;
+                color: white; text-align: center; box-shadow: 0 8px 32px rgba(0,0,0,0.1);
+            }
+            .metric-card {
+                background: white; padding: 1.5rem; border-radius: 12px;
+                border: 2px solid #e5e7eb; box-shadow: 0 4px 20px rgba(0,0,0,0.08);
+                text-align: center; transition: transform 0.2s ease;
+            }
+            .metric-card:hover { transform: translateY(-2px); }
+            .alert-danger {
+                background: linear-gradient(135deg, #fef2f2 0%, #fee2e2 100%);
+                border-left: 4px solid #dc2626; padding: 1rem; border-radius: 8px; margin: 1rem 0;
+            }
+            .alert-success {
+                background: linear-gradient(135deg, #f0fdf4 0%, #dcfce7 100%);
+                border-left: 4px solid #059669; padding: 1rem; border-radius: 8px; margin: 1rem 0;
+            }
+            .alert-warning {
+                background: linear-gradient(135deg, #fffbeb 0%, #fef3c7 100%);
+                border-left: 4px solid #f59e0b; padding: 1rem; border-radius: 8px; margin: 1rem 0;
+            }
+            .chart-container {
+                background: white; padding: 1.5rem; border-radius: 12px;
+                box-shadow: 0 4px 20px rgba(0,0,0,0.08); margin: 1rem 0; border: 1px solid #f1f5f9;
+            }
         </style>
-    </head>
-    <body>
-        <div class="header">
-            <h1>Norwegian Petroleum Safety Authority</h1>
-            <h2>Environmental Compliance Report</h2>
-            <p>Report ID: {report_data['report_id']}</p>
-        </div>
-        
-        <div class="section">
-            <h3>Report Summary</h3>
-            <p><strong>Generated:</strong> {report_data['timestamp']}</p>
-            <p><strong>Location:</strong> {report_data['location']}</p>
-            <p><strong>Compliance Status:</strong> 
-               <span class="{report_data['compliance_status'].lower()}">{report_data['compliance_status']}</span>
-            </p>
-        </div>
-        
-        <div class="section">
-            <h3>Environmental Measurements</h3>
-            <table class="data-table">
-                <tr><th>Parameter</th><th>Value</th><th>Unit</th><th>PSA Limit</th><th>Status</th></tr>
-                <tr><td>pH Level</td><td>{report_data['ph_level']:.1f}</td><td>pH</td><td>6.0-8.5</td><td>✓ Within Range</td></tr>
-                <tr><td>Wastewater Volume</td><td>{report_data['wastewater_volume']:.1f}</td><td>L/min</td><td>&lt;60</td><td>✓ Within Range</td></tr>
-                <tr><td>CO₂ Emissions</td><td>{report_data['co2_total']:.1f}</td><td>kg</td><td>Monitor</td><td>Tracked</td></tr>
-                <tr><td>Energy Consumption</td><td>{report_data['energy_consumption']:.1f}</td><td>kWh</td><td>Monitor</td><td>Tracked</td></tr>
-            </table>
+        """, unsafe_allow_html=True)
+    
+    @staticmethod
+    def render_header():
+        st.markdown("""
+        <div class="main-header">
+            <h1>🌱 ESG Compliance Intelligence</h1>
+            <p>Norwegian Petroleum Safety Authority Real-time Monitoring</p>
         </div>
+        """, unsafe_allow_html=True)
+    
+    @staticmethod
+    def render_alert(status: str, location: str):
+        alerts = {
+            'violation': ('alert-danger', '🚨', 'CRITICAL ALERT', 'Environmental violation detected'),
+            'warning': ('alert-warning', '⚠️', 'WARNING', 'Parameters approaching limits'),
+            'compliant': ('alert-success', '✅', 'COMPLIANT', 'All systems within regulations')
+        }
         
-        <div class="section">
-            <h3>Certification</h3>
-            <p>This report has been generated automatically by the ESG Compliance Intelligence Engine 
-               in accordance with Norwegian Petroleum Safety Authority requirements.</p>
-            <p><strong>Digital Signature:</strong> Verified ✓</p>
-            <p><strong>Report Hash:</strong> {hash(str(report_data)) % 1000000:06d}</p>
+        css_class, icon, title, message = alerts.get(status, alerts['compliant'])
+        st.markdown(f"""
+        <div class="{css_class}">
+            {icon} <strong>{title}:</strong> {message} at {location}
         </div>
-    </body>
-    </html>
-    """
-    return html_content
+        """, unsafe_allow_html=True)
 
-# Create Excel export
-def create_excel_report(df, carbon_df):
-    output = BytesIO()
-    with pd.ExcelWriter(output, engine='openpyxl') as writer:
-        df.to_excel(writer, sheet_name='Environmental_Data', index=False)
-        carbon_df.to_excel(writer, sheet_name='Carbon_Footprint', index=False)
-        
-        # Add summary sheet
-        summary_df = pd.DataFrame({
-            'Metric': ['Latest pH', 'Latest CO₂', 'Latest Energy', 'Compliance Status'],
-            'Value': [df.iloc[-1]['ph_level'], df.iloc[-1]['co2_emission_kg'], 
-                     df.iloc[-1]['energy_kwh'], df.iloc[-1]['status'].upper()]
-        })
-        summary_df.to_excel(writer, sheet_name='Summary', index=False)
+# Visualization
+class ChartGenerator:
+    @staticmethod
+    def create_environmental_trend(df: pd.DataFrame):
+        fig = px.line(df, x='timestamp', y=['ph_level', 'wastewater_lmin'],
+                     title="Environmental Parameters Over Time")
+        fig.update_layout(height=400, showlegend=True)
+        return fig
     
-    return output.getvalue()
-
-# Download button helper
-def get_download_link(file_content, file_name, file_type="application/octet-stream"):
-    b64_content = base64.b64encode(file_content).decode()
-    return f'<a href="data:{file_type};base64,{b64_content}" download="{file_name}">Download {file_name}</a>'
-
-# Main app
-def main():
-    # Header with gradient background
-    st.markdown("""
-    <div class="main-header">
-        <h1>🌱 ESG & Compliance Intelligence Engine</h1>
-        <p>Norwegian Petroleum Safety Authority (PSA) Real-time Monitoring</p>
-    </div>
-    """, unsafe_allow_html=True)
+    @staticmethod
+    def create_carbon_breakdown(carbon_df: pd.DataFrame):
+        fig = px.bar(carbon_df, x='source', y='co2_kg',
+                    title="CO₂ Emissions by Source",
+                    color='co2_kg', color_continuous_scale='Greens')
+        fig.update_layout(height=400)
+        return fig
     
-    # Sidebar for data upload and controls
-    with st.sidebar:
-        st.header("⚙️ Controls")
-        
-        uploaded_file = st.file_uploader("Upload CSV Data", type=['csv'])
-        
-        if st.button("🔄 Refresh Data"):
-            st.cache_data.clear()
-            st.rerun()
+    @staticmethod
+    def create_compliance_trend(df: pd.DataFrame):
+        compliance_map = {'compliant': 100, 'warning': 70, 'violation': 30}
+        df['compliance_score'] = df['status'].map(compliance_map)
         
-        st.markdown("---")
-        
-        if st.button("📊 Generate PSA Report"):
-            df = load_data(uploaded_file)
-            report = generate_psa_report(df)
-            st.success(f"Report Generated: {report['report_id']}")
+        fig = px.area(df, x='timestamp', y='compliance_score',
+                     title="Compliance Score Trend",
+                     color_discrete_sequence=['#059669'])
+        fig.add_hline(y=Config.COMPLIANCE_THRESHOLD, line_dash="dash", 
+                     line_color="red", annotation_text="PSA Threshold")
+        fig.update_layout(height=300)
+        return fig
+
+# Report Generation
+class ReportGenerator:
+    @staticmethod
+    def generate_html_report(report: ComplianceReport) -> str:
+        return f"""
+        <!DOCTYPE html>
+        <html>
+        <head>
+            <meta charset="UTF-8">
+            <title>PSA Environmental Compliance Report</title>
+            <style>
+                body {{ font-family: Arial, sans-serif; margin: 40px; }}
+                .header {{ background: #1e40af; color: white; padding: 20px; border-radius: 8px; text-align: center; }}
+                .section {{ margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 8px; }}
+                .compliant {{ color: #059669; font-weight: bold; }}
+                .warning {{ color: #f59e0b; font-weight: bold; }}
+                .violation {{ color: #dc2626; font-weight: bold; }}
+                table {{ width: 100%; border-collapse: collapse; margin: 10px 0; }}
+                th, td {{ border: 1px solid #ddd; padding: 8px; text-align: left; }}
+                th {{ background-color: #f8fafc; }}
+            </style>
+        </head>
+        <body>
+            <div class="header">
+                <h1>Norwegian Petroleum Safety Authority</h1>
+                <h2>Environmental Compliance Report</h2>
+                <p>Report ID: {report.report_id}</p>
+            </div>
             
-            # Create downloadable content
-            pdf_content = create_pdf_report(report, df)
-            st.download_button(
-                label="⬇️ Download PDF Report",
-                data=pdf_content,
-                file_name=f"PSA_Report_{report['report_id']}.html",
-                mime="text/html"
-            )
+            <div class="section">
+                <h3>Summary</h3>
+                <p><strong>Generated:</strong> {report.timestamp}</p>
+                <p><strong>Location:</strong> {report.location}</p>
+                <p><strong>Status:</strong> <span class="{report.compliance_status.lower()}">{report.compliance_status}</span></p>
+            </div>
             
-            st.json(report)
-        
-        st.markdown("---")
-        st.markdown("**Sample Data Format:**")
-        st.code("""timestamp,ph_level,wastewater_lmin,
-co2_emission_kg,energy_kwh,
-chemical_usage_kg,location,status""", language="csv")
-    
-    # Load data
-    df = load_data(uploaded_file)
-    carbon_df = get_carbon_data()
-    
-    # Alert system based on latest status
-    latest_status = df.iloc[-1]['status']
-    latest_location = df.iloc[-1]['location']
-    
-    if latest_status == 'violation':
-        st.markdown(f"""
-        <div class="alert-danger">
-            ⚠️ <strong>CRITICAL ALERT:</strong> Environmental violation detected at {latest_location}!
-            <br>Immediate action required - PSA notification pending.
-        </div>
-        """, unsafe_allow_html=True)
-    elif latest_status == 'warning':
-        st.markdown(f"""
-        <div class="alert-warning">
-            ⚠️ <strong>WARNING:</strong> Environmental parameters approaching limits at {latest_location}.
-            <br>Monitor closely and prepare corrective measures.
-        </div>
-        """, unsafe_allow_html=True)
-    else:
-        st.markdown(f"""
-        <div class="alert-success">
-            ✅ <strong>COMPLIANT:</strong> All systems operating within PSA regulations at {latest_location}.
-        </div>
-        """, unsafe_allow_html=True)
-    
-    # Metrics row
-    latest_data = df.iloc[-1]
-    
-    col1, col2, col3, col4 = st.columns(4)
-    
-    with col1:
-        status_icons = {"compliant": "✅", "warning": "⚠️", "violation": "🚨"}
-        st.metric(
-            "Compliance Status",
-            f"{status_icons[latest_status]} {latest_status.upper()}",
-            delta="Within Limits" if latest_status == "compliant" else "Action Required"
-        )
-    
-    with col2:
-        ph_delta = latest_data['ph_level'] - 7.0
-        st.metric(
-            "Water pH Level",
-            f"{latest_data['ph_level']:.1f}",
-            delta=f"{ph_delta:+.1f}"
-        )
+            <div class="section">
+                <h3>Environmental Measurements</h3>
+                <table>
+                    <tr><th>Parameter</th><th>Value</th><th>Unit</th><th>Status</th></tr>
+                    <tr><td>pH Level</td><td>{report.ph_level:.1f}</td><td>pH</td><td>✓ Monitored</td></tr>
+                    <tr><td>Wastewater</td><td>{report.wastewater_volume:.1f}</td><td>L/min</td><td>✓ Monitored</td></tr>
+                    <tr><td>CO₂ Emissions</td><td>{report.co2_total:.1f}</td><td>kg</td><td>✓ Tracked</td></tr>
+                    <tr><td>Energy</td><td>{report.energy_consumption:.1f}</td><td>kWh</td><td>✓ Tracked</td></tr>
+                </table>
+            </div>
+            
+            <div class="section">
+                <h3>Certification</h3>
+                <p>Report generated by {report.generated_by}</p>
+                <p><strong>Hash:</strong> {hashlib.md5(str(report.report_id).encode()).hexdigest()[:8]}</p>
+            </div>
+        </body>
+        </html>
+        """
     
-    with col3:
-        st.metric(
-            "CO₂ Emissions",
-            f"{latest_data['co2_emission_kg']:.1f} kg",
-            delta="-2.3 kg"
+    @staticmethod
+    def create_excel_export(df: pd.DataFrame, carbon_df: pd.DataFrame) -> bytes:
+        output = BytesIO()
+        with pd.ExcelWriter(output, engine='openpyxl') as writer:
+            df.to_excel(writer, sheet_name='Environmental_Data', index=False)
+            carbon_df.to_excel(writer, sheet_name='Carbon_Footprint', index=False)
+            
+            summary = pd.DataFrame({
+                'Metric': ['Latest pH', 'Latest CO₂', 'Latest Energy', 'Status'],
+                'Value': [df.iloc[-1]['ph_level'], df.iloc[-1]['co2_emission_kg'], 
+                         df.iloc[-1]['energy_kwh'], df.iloc[-1]['status'].upper()]
+            })
+            summary.to_excel(writer, sheet_name='Summary', index=False)
+        
+        return output.getvalue()
+
+# Main Application
+class ESGDashboard:
+    def __init__(self):
+        st.set_page_config(
+            page_title=Config.PAGE_TITLE,
+            page_icon=Config.PAGE_ICON,
+            layout="wide"
         )
+        UIComponents.apply_styling()
     
-    with col4:
-        st.metric(
-            "Energy Usage",
-            f"{latest_data['energy_kwh']:.0f} kWh",
-            delta="+5.2 kWh"
-        )
+    def render_sidebar(self) -> Optional[pd.DataFrame]:
+        with st.sidebar:
+            st.header("⚙️ Controls")
+            
+            uploaded_file = st.file_uploader("Upload CSV Data", type=['csv'])
+            
+            if st.button("🔄 Refresh Data"):
+                st.cache_data.clear()
+                st.rerun()
+            
+            st.markdown("---")
+            st.markdown("**Required CSV Format:**")
+            st.code("timestamp,ph_level,wastewater_lmin,co2_emission_kg,energy_kwh,location,status")
+            
+            return uploaded_file
     
-    # Charts section
-    col1, col2 = st.columns(2)
+    def render_metrics(self, df: pd.DataFrame):
+        latest = df.iloc[-1]
+        col1, col2, col3, col4 = st.columns(4)
+        
+        status_icons = {"compliant": "✅", "warning": "⚠️", "violation": "🚨"}
+        
+        with col1:
+            st.metric("Status", f"{status_icons[latest['status']]} {latest['status'].upper()}")
+        with col2:
+            ph_delta = latest['ph_level'] - 7.0
+            st.metric("pH Level", f"{latest['ph_level']:.1f}", f"{ph_delta:+.1f}")
+        with col3:
+            st.metric("CO₂ Emissions", f"{latest['co2_emission_kg']:.1f} kg", "-2.3 kg")
+        with col4:
+            st.metric("Energy Usage", f"{latest['energy_kwh']:.0f} kWh", "+5.2 kWh")
     
-    with col1:
-        st.markdown('<div class="chart-container">', unsafe_allow_html=True)
-        st.subheader("💧 Real-time Environmental Monitoring")
+    def render_charts(self, df: pd.DataFrame, carbon_df: pd.DataFrame):
+        col1, col2 = st.columns(2)
+        
+        with col1:
+            st.markdown('<div class="chart-container">', unsafe_allow_html=True)
+            st.subheader("💧 Environmental Monitoring")
+            fig_env = ChartGenerator.create_environmental_trend(df)
+            st.plotly_chart(fig_env, use_container_width=True)
+            st.markdown('</div>', unsafe_allow_html=True)
+        
+        with col2:
+            st.markdown('<div class="chart-container">', unsafe_allow_html=True)
+            st.subheader("📈 Carbon Footprint")
+            fig_carbon = ChartGenerator.create_carbon_breakdown(carbon_df)
+            st.plotly_chart(fig_carbon, use_container_width=True)
+            st.markdown('</div>', unsafe_allow_html=True)
         
-        fig_line = px.line(df, x='timestamp', y=['ph_level', 'wastewater_lmin'],
-                          title="pH Level & Wastewater Discharge Over Time",
-                          labels={'value': 'Measurement', 'variable': 'Parameter'})
-        fig_line.update_layout(height=400, showlegend=True)
-        st.plotly_chart(fig_line, use_container_width=True)
+        st.markdown('<div class="chart-container">', unsafe_allow_html=True)
+        st.subheader("📊 Compliance Trend")
+        fig_compliance = ChartGenerator.create_compliance_trend(df)
+        st.plotly_chart(fig_compliance, use_container_width=True)
         st.markdown('</div>', unsafe_allow_html=True)
     
-    with col2:
+    def render_export_section(self, df: pd.DataFrame, carbon_df: pd.DataFrame):
         st.markdown('<div class="chart-container">', unsafe_allow_html=True)
-        st.subheader("📈 Carbon Footprint Breakdown")
+        st.subheader("⬇️ Export Reports")
+        
+        col1, col2, col3 = st.columns(3)
+        
+        with col1:
+            if st.button("📄 Generate PDF Report", type="primary"):
+                report = ComplianceReport.from_dataframe_row(df.iloc[-1])
+                html_content = ReportGenerator.generate_html_report(report)
+                
+                st.download_button(
+                    label="⬇️ Download Report",
+                    data=html_content,
+                    file_name=f"PSA_Report_{datetime.now().strftime('%Y%m%d_%H%M')}.html",
+                    mime="text/html"
+                )
+                st.success("✅ Report ready for download!")
+        
+        with col2:
+            if st.button("📊 Export Excel"):
+                excel_data = ReportGenerator.create_excel_export(df, carbon_df)
+                
+                st.download_button(
+                    label="⬇️ Download Excel",
+                    data=excel_data,
+                    file_name=f"ESG_Data_{datetime.now().strftime('%Y%m%d_%H%M')}.xlsx",
+                    mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+                )
+                st.success("✅ Excel file ready!")
+        
+        with col3:
+            if st.button("📤 Submit to PSA"):
+                submission_id = f"PSA-SUB-{datetime.now().strftime('%Y%m%d%H%M')}"
+                st.success(f"✅ Submitted!\nID: {submission_id}")
         
-        fig_bar = px.bar(carbon_df, x='source', y='co2_kg',
-                        title="CO₂ Emissions by Source",
-                        color='co2_kg',
-                        color_continuous_scale='Greens')
-        fig_bar.update_layout(height=400)
-        st.plotly_chart(fig_bar, use_container_width=True)
         st.markdown('</div>', unsafe_allow_html=True)
     
-    # Compliance trend
-    st.markdown('<div class="chart-container">', unsafe_allow_html=True)
-    st.subheader("📈 Compliance Status Trends")
-    
-    # Create compliance score (numeric representation)
-    compliance_map = {'compliant': 100, 'warning': 70, 'violation': 30}
-    df['compliance_score'] = df['status'].map(compliance_map)
-    
-    fig_area = px.area(df, x='timestamp', y='compliance_score',
-                      title="Compliance Score Over Time",
-                      color_discrete_sequence=['#059669'])
-    fig_area.add_hline(y=80, line_dash="dash", line_color="red", 
-                      annotation_text="PSA Minimum Threshold")
-    fig_area.update_layout(height=300)
-    st.plotly_chart(fig_area, use_container_width=True)
-    st.markdown('</div>', unsafe_allow_html=True)
-    
-    # PSA Reports Table
-    st.markdown('<div class="chart-container">', unsafe_allow_html=True)
-    st.subheader("📋 PSA Compliance Reports History")
-    
-    # Sample historical reports
-    reports_df = 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_df, use_container_width=True, hide_index=True)
-    st.markdown('</div>', unsafe_allow_html=True)
-    
-    # Download section
-    st.markdown('<div class="chart-container">', unsafe_allow_html=True)
-    st.subheader("⬇️ Export & Reports")
-    
-    col1, col2, col3 = st.columns(3)
-    
-    with col1:
-        if st.button("📄 Generate PDF Report", type="primary"):
-            report = generate_psa_report(df)
-            pdf_content = create_pdf_report(report, df)
-            st.download_button(
-                label="⬇️ Download PSA Report",
-                data=pdf_content,
-                file_name=f"PSA_Report_{datetime.now().strftime('%Y%m%d_%H%M')}.html",
-                mime="text/html"
-            )
-            st.success("✅ PSA-compliant report ready for download!")
-    
-    with col2:
-        if st.button("📊 Export Excel Data"):
-            excel_data = create_excel_report(df, carbon_df)
-            st.download_button(
-                label="⬇️ Download Excel File",
-                data=excel_data,
-                file_name=f"ESG_Data_{datetime.now().strftime('%Y%m%d_%H%M')}.xlsx",
-                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
-            )
-            st.success("✅ Excel report with all environmental data exported!")
-    
-    with col3:
-        if st.button("📤 PSA Portal Integration"):
-            # Simulate PSA portal submission
-            submission_id = f"PSA-SUB-{datetime.now().strftime('%Y%m%d%H%M')}"
-            st.success(f"✅ Report submitted to PSA Portal!\nSubmission ID: {submission_id}")
-            
-    st.markdown('</div>', unsafe_allow_html=True)
-    
-    # Footer
-    st.markdown("""
-    <div class="footer-info">
-        🔒 <strong>Security:</strong> AES-256 encryption | 
-        📊 <strong>Updates:</strong> Real-time data processing | 
-        ✅ <strong>Compliance:</strong> GDPR & Norwegian Data Protection Act
-        <br><br>
-        <em>Built for Norwegian R&D grant applications - AI-driven compliance automation</em>
-    </div>
-    """, unsafe_allow_html=True)
+    def run(self):
+        UIComponents.render_header()
+        
+        uploaded_file = self.render_sidebar()
+        
+        # Load and validate data
+        df = DataManager.load_and_validate_data(uploaded_file)
+        if df.empty:
+            st.stop()
+        
+        carbon_df = DataManager.get_carbon_footprint_data()
+        
+        # Render alert
+        latest_status = df.iloc[-1]['status']
+        latest_location = df.iloc[-1]['location']
+        UIComponents.render_alert(latest_status, latest_location)
+        
+        # Render dashboard components
+        self.render_metrics(df)
+        self.render_charts(df, carbon_df)
+        self.render_export_section(df, carbon_df)
+
+# Application Entry Point
+def main():
+    dashboard = ESGDashboard()
+    dashboard.run()
 
 if __name__ == "__main__":
     main()