┌─────────────────────────────────────────────────────────────────────────────┐
│                    POST-LAUNCH OPERATIONAL PILLARS                         │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    PROTOCOL MAINTENANCE                              │   │
│  │  • Monitor contract activity                                        │   │
│  │  • Fix bugs and vulnerabilities                                     │   │
│  │  • Update parameters                                               │   │
│  │  • Gas optimisation                                                │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    INFRASTRUCTURE                                    │   │
│  │  • Node operations                                                  │   │
│  │  • API reliability                                                  │   │
│  │  • Database management                                              │   │
│  │  • Performance monitoring                                           │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    COMMUNITY MANAGEMENT                              │   │
│  │  • Engagement and support                                           │   │
│  │  • Governance facilitation                                          │   │
│  │  • Feedback collection                                              │   │
│  │  • Ambassador programs                                              │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    COMPLIANCE & RISK                                 │   │
│  │  • Regulatory monitoring                                            │   │
│  │  • Ongoing compliance                                               │   │
│  │  • Incident response                                               │   │
│  │  • Security monitoring                                              │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────────────────────┐
│                    ECOSYSTEM GROWTH                                          │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    DEVELOPER ECOSYSTEM                               │   │
│  │  • SDKs and APIs                                                    │   │
│  │  • Developer grants                                                 │   │
│  │  • Documentation                                                    │   │
│  │  • Hackathons                                                       │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    PARTNER ECOSYSTEM                                │   │
│  │  • Integrations                                                     │   │
│  │  • Strategic partnerships                                          │   │
│  │  • Liquidity partnerships                                           │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                    │                                        │
│                                    v                                        │
│  ┌──────────────────────────────────────────────────────────────────────┐   │
│  │                    USER ECOSYSTEM                                   │   │
│  │  • Community engagement                                             │   │
│  │  • User feedback                                                    │   │
│  │  • Loyalty programs                                                │   │
│  └──────────────────────────────────────────────────────────────────────┘   │
│                                                                             │
└─────────────────────────────────────────────────────────────────────────────┘

# ===================================================================
# MODULE 7, LESSON 8: POST-LAUNCH OPERATIONS AND GROWTH
# ===================================================================

import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
import numpy as np
from typing import Dict, List
import warnings
warnings.filterwarnings('ignore')

print("="*70)
print("POST-LAUNCH OPERATIONS AND GROWTH")
print("="*70)

# ----------------------------------------------------------------
# PART A: PERFORMANCE DASHBOARD
# ----------------------------------------------------------------

print("\n" + "-"*60)
print("PART A: Performance Dashboard")
print("-"*60)

class PerformanceDashboard:
    """
    Tracks key performance metrics for a blockchain project.
    """
    def __init__(self, name: str):
        self.name = name
        self.metrics = {}
        self.history = []
    
    def add_metric(self, name: str, value: float, target: float, unit: str = ''):
        self.metrics[name] = {
            'value': value,
            'target': target,
            'unit': unit,
            'status': 'On Track' if value >= target else 'Needs Attention'
        }
    
    def add_historical(self, date: datetime, **kwargs):
        self.history.append({'date': date, **kwargs})
    
    def get_summary(self) -> pd.DataFrame:
        data = []
        for name, details in self.metrics.items():
            data.append({
                'Metric': name,
                'Value': f"{details['value']}{details['unit']}",
                'Target': f"{details['target']}{details['unit']}",
                'Status': details['status']
            })
        return pd.DataFrame(data)
    
    def get_trend(self, metric: str) -> List:
        return [h.get(metric, 0) for h in self.history]

# Create dashboard
dashboard = PerformanceDashboard("DeFi Lending Protocol")

# Add current metrics
dashboard.add_metric('TVL (Millions)', 12.5, 15.0, 'M')
dashboard.add_metric('Active Users', 8500, 10000, '')
dashboard.add_metric('Daily Transactions', 2500, 3000, '')
dashboard.add_metric('Revenue (Monthly)', 150000, 200000, '')
dashboard.add_metric('Governance Participation', 22, 25, '%')
dashboard.add_metric('Community Members', 15000, 20000, '')

print("Performance Dashboard:")
summary = dashboard.get_summary()
print(summary.to_string(index=False))

# ----------------------------------------------------------------
# PART B: METRICS TRACKING
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART B: Metrics Tracking")
print("-"*60)

# Simulate historical data
start_date = datetime.now() - timedelta(days=180)
dates = [start_date + timedelta(days=i*7) for i in range(26)]

tvls = [5 + i * 0.4 + np.random.normal(0, 0.5) for i in range(26)]
users = [1000 + i * 50 + np.random.normal(0, 100) for i in range(26)]
txs = [300 + i * 15 + np.random.normal(0, 30) for i in range(26)]
revenue = [30000 + i * 1000 + np.random.normal(0, 5000) for i in range(26)]

# Add to dashboard
for date, t, u, tx, r in zip(dates, tvls, users, txs, revenue):
    dashboard.add_historical(date, tvl=t, users=u, transactions=tx, revenue=r)

# Visualise trends
fig, axes = plt.subplots(2, 2, figsize=(14, 10))

metrics_list = [
    ('tvl', 'TVL (Millions)', axes[0, 0]),
    ('users', 'Active Users', axes[0, 1]),
    ('transactions', 'Daily Transactions', axes[1, 0]),
    ('revenue', 'Monthly Revenue', axes[1, 1])
]

for metric, label, ax in metrics_list:
    data = [h.get(metric, 0) for h in dashboard.history]
    dates = [h['date'] for h in dashboard.history]
    ax.plot(dates, data, color='blue', linewidth=2)
    ax.set_xlabel('Date')
    ax.set_ylabel(label)
    ax.set_title(f'{label} Over Time')
    ax.grid(True, alpha=0.3)
    plt.setp(ax.get_xticklabels(), rotation=45, ha='right')

plt.tight_layout()
plt.savefig('performance_tracking.png', dpi=300, bbox_inches='tight')
plt.show()
print("Performance tracking chart saved as 'performance_tracking.png'")

# ----------------------------------------------------------------
# PART C: GOVERNANCE MATURITY MODEL
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART C: Governance Maturity Model")
print("-"*60)

governance_phases = {
    'Team Control': {
        'Characteristics': 'Core team makes all decisions',
        'Transparency': 'Low',
        'Speed': 'High',
        'Decentralisation': 'Very Low'
    },
    'Multi-Sig Control': {
        'Characteristics': 'Multi-signature approval required',
        'Transparency': 'Medium',
        'Speed': 'Medium-High',
        'Decentralisation': 'Low'
    },
    'Partial DAO': {
        'Characteristics': 'Some decisions on-chain, team guides',
        'Transparency': 'High',
        'Speed': 'Medium',
        'Decentralisation': 'Medium'
    },
    'Full DAO': {
        'Characteristics': 'All decisions by community vote',
        'Transparency': 'Very High',
        'Speed': 'Low',
        'Decentralisation': 'Very High'
    }
}

gov_df = pd.DataFrame(governance_phases).T
print(gov_df.to_string())

# ----------------------------------------------------------------
# PART D: GROWTH PHASES
# -----------------------------------------------------------------

print("\n" + "-"*60)
print("PART D: Growth Phases")
print("-"*60)

growth_phases = {
    'Phase 1: Launch': {
        'Focus': 'Initial adoption',
        'Key Activities': 'Marketing, community, liquidity',
        'Duration': '0-3 months',
        'Key Metrics': 'User signups, TVL, token price'
    },
    'Phase 2: Growth': {
        'Focus': 'User acquisition',
        'Key Activities': 'Partnerships, features, incentives',
        'Duration': '3-12 months',
        'Key Metrics': 'Active users, transaction volume'
    },
    'Phase 3: Scaling': {
        'Focus': 'Ecosystem expansion',
        'Key Activities': 'Grants, integrations, ecosystem fund',
        'Duration': '12-24 months',
        'Key Metrics': 'Ecosystem partners, developer activity'
    },
    'Phase 4: Maturity': {
        'Focus': 'Sustainability',
        'Key Activities': 'Governance evolution, long-term planning',
        'Duration': '24+ months',
        'Key Metrics': 'Revenue, retention, governance participation'
    }
}

phase_df = pd.DataFrame(growth_phases).T
print(phase_df.to_string())

# ----------------------------------------------------------------
# PART E: SUMMARY AND RECOMMENDATIONS
# -----------------------------------------------------------------

print("\n" + "="*70)
print("PART E: Summary and Recommendations")
print("="*70)

print("""
Post-Launch Operations and Growth – Key Takeaways:

1. Post-launch operations: protocol maintenance, infrastructure, community, compliance.
2. Upgrade strategies: immutable (no upgrades), proxy pattern, governance-controlled, multi-sig.
3. KPIs: protocol health, user growth, liquidity, security, community, financial.
4. Monitoring: Dune Analytics, Etherscan, Tenderly, The Graph, Grafana.
5. Growth: user acquisition, ecosystem development, partnerships.
6. Governance maturity: team control → multi-sig → partial DAO → full DAO.

Recommendations:
  - Maintain comprehensive monitoring and alerting.
  - Establish clear incident response procedures.
  - Track KPIs and adjust strategy accordingly.
  - Evolve governance as the project matures.
  - Build ecosystem through grants and partnerships.
  - Engage community continuously.
  - Plan for long-term sustainability.
  - Be prepared to adapt to changing conditions.
""")