"""Test patterns and best practices examples.

This module demonstrates various testing patterns and best practices
used throughout the test suite.
"""

import pytest
from unittest.mock import Mock, patch, MagicMock, call
from factory import Factory, Faker, SubFactory
import json
from pathlib import Path


class TestPatterns:
    """Examples of different testing patterns."""
    
    def test_basic_unit_test(self):
        """Basic unit test pattern."""
        # Arrange
        input_value = 10
        expected_result = 20
        
        # Act
        result = input_value * 2
        
        # Assert
        assert result == expected_result
    
    def test_with_fixture(self, sample_market_data):
        """Test using fixture data."""
        # Arrange & Act
        symbol = sample_market_data['symbol']
        price = sample_market_data['price']
        
        # Assert
        assert symbol == 'AAPL'
        assert price == 150.0
    
    def test_with_mock(self, mock_market_processor):
        """Test using mock objects."""
        # Arrange
        test_data = {'price': 100}
        
        # Act
        result = mock_market_processor.process_data(test_data)
        
        # Assert
        assert result == {'processed': True}
        mock_market_processor.process_data.assert_called_once_with(test_data)
    
    @patch('src.core.advanced_market_processing.AdvancedMarketProcessor')
    def test_with_patch_decorator(self, mock_processor_class):
        """Test using patch decorator."""
        # Arrange
        mock_instance = Mock()
        mock_instance.analyze_trends.return_value = {'trend': 'bullish'}
        mock_processor_class.return_value = mock_instance
        
        # Act
        from src.core.advanced_market_processing import AdvancedMarketProcessor
        processor = AdvancedMarketProcessor()
        result = processor.analyze_trends()
        
        # Assert
        assert result == {'trend': 'bullish'}
        mock_processor_class.assert_called_once()
    
    def test_with_context_manager_patch(self):
        """Test using patch as context manager."""
        with patch('builtins.open', create=True) as mock_open:
            mock_open.return_value.__enter__.return_value.read.return_value = 'test data'
            
            # Act
            with open('test_file.txt', 'r') as f:
                content = f.read()
            
            # Assert
            assert content == 'test data'
            mock_open.assert_called_once_with('test_file.txt', 'r')
    
    def test_exception_handling(self):
        """Test exception handling patterns."""
        # Test that exception is raised
        with pytest.raises(ValueError, match="Invalid input"):
            raise ValueError("Invalid input")
        
        # Test that no exception is raised
        try:
            result = 1 + 1
            assert result == 2
        except Exception as e:
            pytest.fail(f"Unexpected exception: {e}")
    
    @pytest.mark.parametrize("input_value,expected", [
        (1, 2),
        (2, 4),
        (3, 6),
        (0, 0),
        (-1, -2)
    ])
    def test_parametrized(self, input_value, expected):
        """Parametrized test pattern."""
        result = input_value * 2
        assert result == expected
    
    @pytest.mark.slow
    def test_slow_operation(self):
        """Test marked as slow."""
        import time
        time.sleep(0.1)  # Simulate slow operation
        assert True
    
    def test_with_caplog(self, caplog):
        """Test log capture pattern."""
        import logging
        
        logger = logging.getLogger('test_logger')
        logger.info('Test log message')
        
        assert 'Test log message' in caplog.text
        assert caplog.records[0].levelname == 'INFO'
    
    def test_with_temp_file(self, tmp_path):
        """Test with temporary file."""
        # Create temporary file
        test_file = tmp_path / "test.txt"
        test_file.write_text("test content")
        
        # Test
        content = test_file.read_text()
        assert content == "test content"
        assert test_file.exists()
    
    def test_async_function(self):
        """Test async function pattern."""
        import asyncio
        
        async def async_function():
            await asyncio.sleep(0.01)
            return "async result"
        
        # Run async test
        result = asyncio.run(async_function())
        assert result == "async result"
    
    def test_mock_multiple_calls(self):
        """Test mock with multiple calls."""
        mock_func = Mock()
        mock_func.side_effect = [1, 2, 3]
        
        # Multiple calls
        assert mock_func() == 1
        assert mock_func() == 2
        assert mock_func() == 3
        
        # Verify call count
        assert mock_func.call_count == 3
        
        # Verify call arguments
        expected_calls = [call(), call(), call()]
        mock_func.assert_has_calls(expected_calls)
    
    def test_mock_side_effect_exception(self):
        """Test mock raising exception."""
        mock_func = Mock()
        mock_func.side_effect = ValueError("Mock error")
        
        with pytest.raises(ValueError, match="Mock error"):
            mock_func()
    
    def test_json_data_loading(self, test_data_dir):
        """Test loading JSON test data."""
        json_file = test_data_dir / "sample_market_data.json"
        
        if json_file.exists():
            with open(json_file) as f:
                data = json.load(f)
            
            assert 'market_data' in data
            assert len(data['market_data']) > 0
        else:
            pytest.skip("Test data file not found")


class TestFactoryPatterns:
    """Examples using Factory Boy for test data generation."""
    
    class MarketDataFactory(Factory):
        """Factory for generating market data."""
        
        class Meta:
            model = dict
        
        symbol = Faker('random_element', elements=['AAPL', 'GOOGL', 'MSFT', 'AMZN'])
        price = Faker('pyfloat', left_digits=3, right_digits=2, positive=True)
        volume = Faker('pyint', min_value=100000, max_value=10000000)
        timestamp = Faker('date_time_this_year')
    
    def test_with_factory(self):
        """Test using factory-generated data."""
        market_data = self.MarketDataFactory()
        
        assert 'symbol' in market_data
        assert 'price' in market_data
        assert 'volume' in market_data
        assert market_data['price'] > 0
        assert market_data['volume'] > 0
    
    def test_factory_batch(self):
        """Test generating batch data with factory."""
        batch_data = self.MarketDataFactory.build_batch(5)
        
        assert len(batch_data) == 5
        for item in batch_data:
            assert 'symbol' in item
            assert 'price' in item


class TestIntegrationPatterns:
    """Integration test patterns."""
    
    @pytest.mark.integration
    def test_database_integration(self, database_connection):
        """Integration test with database."""
        cursor = database_connection.cursor()
        
        # Insert test data
        cursor.execute(
            "INSERT INTO logs (timestamp, level, message) VALUES (?, ?, ?)",
            ('2024-01-01 10:00:00', 'INFO', 'Test message')
        )
        database_connection.commit()
        
        # Query data
        cursor.execute("SELECT * FROM logs WHERE message = ?", ('Test message',))
        result = cursor.fetchone()
        
        assert result is not None
        assert result['level'] == 'INFO'
    
    @pytest.mark.integration
    def test_api_integration(self, mock_external_apis):
        """Integration test with external APIs."""
        mock_yf, mock_requests = mock_external_apis
        
        # Test would use actual API calls here
        # but they're mocked for testing
        import yfinance as yf
        data = yf.download('AAPL')
        
        assert not data.empty
        mock_yf.assert_called_once_with('AAPL')


class TestPerformancePatterns:
    """Performance testing patterns."""
    
    @pytest.mark.performance
    def test_performance_benchmark(self, benchmark):
        """Performance test using pytest-benchmark."""
        def function_to_test():
            return sum(range(1000))
        
        result = benchmark(function_to_test)
        assert result == 499500
    
    @pytest.mark.performance
    def test_memory_usage(self):
        """Test memory usage patterns."""
        import psutil
        import os
        
        process = psutil.Process(os.getpid())
        initial_memory = process.memory_info().rss
        
        # Perform memory-intensive operation
        large_list = [i for i in range(100000)]
        
        final_memory = process.memory_info().rss
        memory_increase = final_memory - initial_memory
        
        # Assert memory increase is reasonable
        assert memory_increase > 0
        assert len(large_list) == 100000


class TestSecurityPatterns:
    """Security testing patterns."""
    
    @pytest.mark.security
    def test_input_validation(self):
        """Test input validation patterns."""
        # Test SQL injection prevention
        malicious_input = "'; DROP TABLE users; --"
        
        # Your validation function should handle this
        # This is just an example pattern
        def validate_input(user_input):
            if any(char in user_input for char in [';', '--', 'DROP', 'DELETE']):
                raise ValueError("Invalid input detected")
            return user_input
        
        with pytest.raises(ValueError, match="Invalid input detected"):
            validate_input(malicious_input)
    
    @pytest.mark.security
    def test_sensitive_data_handling(self):
        """Test sensitive data handling."""
        # Test that sensitive data is not logged
        sensitive_data = "password123"
        
        # Mock logger to verify sensitive data is not logged
        with patch('logging.getLogger') as mock_logger:
            mock_log_instance = Mock()
            mock_logger.return_value = mock_log_instance
            
            # Function that should not log sensitive data
            def process_login(password):
                logger = mock_logger()
                logger.info("Login attempt")
                # Should NOT log the password
                return len(password) > 0
            
            result = process_login(sensitive_data)
            
            assert result is True
            # Verify password was not logged
            logged_calls = mock_log_instance.info.call_args_list
            for call_args in logged_calls:
                assert sensitive_data not in str(call_args)