#!/usr/bin/env python3
"""
Test suite for TODO implementations to ensure they work correctly.
"""

import pytest
import sys
import os
import pandas as pd
from datetime import datetime, timedelta
from unittest.mock import Mock, patch, MagicMock

# Add src to path
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))


class TestTodoImplementations:
    """Test all TODO implementations"""
    
    def test_historical_data_loading_synthetic(self):
        """Test synthetic data generation fallback"""
        # Import the function
        sys.path.append(os.path.join(os.path.dirname(__file__), '..', 'examples'))
        from backtesting_example import load_historical_market_data
        
        # Test with synthetic data (no external dependencies)
        start_date = '2023-01-01'
        end_date = '2023-01-10'
        
        with patch('yfinance.Ticker') as mock_yf, \
             patch('ccxt.binance') as mock_ccxt, \
             patch('os.path.exists', return_value=False):
            
            # Make yfinance fail
            mock_yf.side_effect = ImportError("yfinance not available")
            mock_ccxt.side_effect = ImportError("ccxt not available")
            
            data = load_historical_market_data('TEST', start_date, end_date)
            
            assert isinstance(data, pd.DataFrame)
            assert not data.empty
            assert 'date' in data.columns
            assert 'open' in data.columns
            assert 'high' in data.columns
            assert 'low' in data.columns
            assert 'close' in data.columns
            assert 'volume' in data.columns
    
    def test_position_sizing_calculation(self):
        """Test position sizing implementation"""
        from examples.strategy_examples.simple_moving_average_example import SimpleMovingAverageExample
        from src.models.data_models import TradingSignal, MarketData
        
        example = SimpleMovingAverageExample()
        
        # Create mock signal and market data
        signal = TradingSignal(
            symbol='EURUSD',
            action='BUY',
            confidence=0.8,
            timestamp=datetime.now(),
            metadata={}
        )
        
        market_data = MarketData(
            symbol='EURUSD',
            timestamp=datetime.now(),
            open=1.1000,
            high=1.1050,
            low=1.0950,
            close=1.1020,
            volume=1000000
        )
        
        # Test position sizing
        position_size = example._calculate_position_size(signal, market_data)
        
        assert isinstance(position_size, float)
        assert position_size > 0
        assert position_size < 1.0  # Should be reasonable size
    
    def test_cli_database_connection_fallback(self):
        """Test CLI database connection with fallback"""
        from genebot.cli import show_trades_command
        from unittest.mock import StringIO
        import sys
        
        # Capture stdout
        captured_output = StringIO()
        sys.stdout = captured_output
        
        try:
            # Mock args
            args = Mock()
            
            # Test with database connection failure
            with patch('sqlalchemy.create_engine') as mock_engine:
                mock_engine.side_effect = Exception("Database connection failed")
                
                # This should not raise an exception
                show_trades_command(args)
                
                output = captured_output.getvalue()
                assert "Database connection failed" in output or "mock data" in output.lower()
        
        finally:
            sys.stdout = sys.__stdout__
    
    def test_monitoring_paper_trade_execution(self):
        """Test paper trade execution fallback"""
        from examples.monitoring_integration_example import TradingBotWithMonitoring
        
        bot = TradingBotWithMonitoring()
        
        # Test paper trade execution
        signal = {
            'symbol': 'BTCUSD',
            'type': 'BUY',
            'quantity': 0.01,
            'price': 50000.0
        }
        
        result = bot._execute_paper_trade(signal)
        
        assert result is not None
        assert 'id' in result
        assert result['symbol'] == 'BTCUSD'
        assert result['side'] == 'buy'
        assert result['type'] == 'paper_trade'
        assert result['status'] == 'filled'
    
    def test_mock_portfolio_metrics(self):
        """Test mock portfolio metrics generation"""
        from examples.monitoring_integration_example import TradingBotWithMonitoring
        
        bot = TradingBotWithMonitoring()
        bot.monitoring = Mock()
        
        # Test mock portfolio metrics
        bot._update_mock_portfolio_metrics()
        
        # Verify metrics were recorded
        assert bot.monitoring.record_metric.called
        call_args = [call[0] for call in bot.monitoring.record_metric.call_args_list]
        
        expected_metrics = [
            'portfolio.total_balance',
            'portfolio.available_balance', 
            'portfolio.total_positions',
            'portfolio.unrealized_pnl'
        ]
        
        for metric in expected_metrics:
            assert any(metric in str(args) for args in call_args)
    
    @patch.dict(os.environ, {'ACCOUNT_BALANCE': '50000', 'MAX_RISK_PER_TRADE': '0.03'})
    def test_position_sizing_with_environment_variables(self):
        """Test position sizing with environment variable configuration"""
        from examples.strategy_examples.simple_moving_average_example import SimpleMovingAverageExample
        from src.models.data_models import TradingSignal, MarketData
        
        example = SimpleMovingAverageExample()
        
        signal = TradingSignal(
            symbol='EURUSD',
            action='BUY',
            confidence=0.9,
            timestamp=datetime.now(),
            metadata={}
        )
        
        market_data = MarketData(
            symbol='EURUSD',
            timestamp=datetime.now(),
            open=1.1000,
            high=1.1050,
            low=1.0950,
            close=1.1020,
            volume=1000000
        )
        
        position_size = example._calculate_position_size(signal, market_data)
        
        # Should use environment variables for calculation
        assert position_size > 0
        # With higher account balance, position size should be reasonable
        assert position_size < 100  # Reasonable upper bound


if __name__ == '__main__':
    pytest.main([__file__])