app.py

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
from io import StringIO, BytesIO
import base64
import json
from dataclasses import dataclass, asdict
from typing import Optional, Dict, List
import hashlib

# 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

# 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")

# 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"""
    
    @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]
        })

# UI Components
class UIComponents:
    @staticmethod
    def apply_styling():
        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; 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>
        """, 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')
        }
        
        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>
        """, unsafe_allow_html=True)

# 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
    
    @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
    
    @staticmethod
    def create_compliance_trend(df: pd.DataFrame):
        compliance_map = {'compliant': 100, 'warning': 70, 'violation': 30}
        df['compliance_score'] = df['status'].map(compliance_map)
        
        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>
            
            <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>
            
            <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>
        """
    
    @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()
    
    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
    
    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")
    
    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)
        
        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)
    
    def render_export_section(self, df: pd.DataFrame, carbon_df: pd.DataFrame):
        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 = 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}")
        
        st.markdown('</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()