"""
Test suite for TimelineCalculator

Tests the core calculation logic for incident response timeline comparisons.
"""

import pytest
from datetime import datetime
from typing import Dict, Any

# Import your timeline calculator (adjust path as needed)
# from app import TimelineCalculator, TimelineMetrics


class TestTimelineCalculator:
    """Test suite for TimelineCalculator class"""
    
    @pytest.fixture
    def calculator(self):
        """Create a TimelineCalculator instance for testing"""
        # TODO: Initialize with test parameters
        pass
    
    def test_calculator_initialization(self):
        """Test that calculator initializes with correct defaults"""
        # TODO: Verify default values
        # - industry_avg_response_min = 14.0
        # - arf_avg_response_min = 2.0
        # - cost_per_minute = 50000.0
        pass
    
    def test_calculator_custom_initialization(self):
        """Test calculator initialization with custom values"""
        # TODO: Create calculator with custom values and verify
        pass
    
    def test_calculate_metrics_default(self):
        """Test metrics calculation with default parameters"""
        # TODO: Calculate metrics and verify structure
        # - Should return TimelineMetrics instance
        # - All fields should be populated
        pass
    
    def test_calculate_metrics_critical_severity(self, calculator):
        """Test metrics calculation for CRITICAL severity incident"""
        # TODO: Calculate for CRITICAL severity
        # - Verify industry_total_min is correct
        # - Verify arf_total_min is correct
        # - Verify cost_savings calculation
        pass
    
    def test_calculate_metrics_high_severity(self, calculator):
        """Test metrics calculation for HIGH severity incident"""
        # TODO: Calculate for HIGH severity
        # - May have different response times
        pass
    
    def test_calculate_metrics_low_severity(self, calculator):
        """Test metrics calculation for LOW severity incident"""
        # TODO: Calculate for LOW severity
        pass
    
    def test_time_savings_calculation(self, calculator):
        """Test that time savings are calculated correctly"""
        # TODO: Verify time_saved_min = industry_total - arf_total
        pass
    
    def test_cost_savings_calculation(self, calculator):
        """Test that cost savings are calculated correctly"""
        # TODO: Verify cost_savings = (industry_total - arf_total) * cost_per_minute
        pass
    
    def test_time_improvement_percentage(self, calculator):
        """Test that time improvement percentage is correct"""
        # TODO: Verify time_improvement_pct = (time_saved / industry_total) * 100
        pass
    
    def test_zero_cost_per_minute(self):
        """Test behavior when cost_per_minute is 0"""
        # TODO: Edge case - should not crash
        pass
    
    def test_negative_values_handling(self):
        """Test that negative values are handled appropriately"""
        # TODO: Should raise error or handle gracefully
        pass
    
    def test_calculate_metrics_different_components(self, calculator):
        """Test that different components can have different timelines"""
        # TODO: Test api-service vs database vs cache-service
        # - May have different complexity
        pass
    
    def test_metrics_immutability(self, calculator):
        """Test that calculated metrics are immutable"""
        # TODO: Verify TimelineMetrics is a frozen dataclass
        pass


class TestTimelineMetrics:
    """Test suite for TimelineMetrics dataclass"""
    
    def test_metrics_creation(self):
        """Test creating TimelineMetrics with all fields"""
        # TODO: Create instance and verify all fields
        pass
    
    def test_metrics_default_values(self):
        """Test that metrics have sensible default values"""
        # TODO: Verify defaults are set correctly
        pass
    
    def test_metrics_serialization(self):
        """Test that metrics can be serialized to dict/JSON"""
        # TODO: Verify can convert to dict for API responses
        pass
    
    def test_metrics_field_types(self):
        """Test that all fields have correct types"""
        # TODO: Verify float types for time/cost values
        pass


class TestTimelineCalculatorEdgeCases:
    """Test edge cases and error conditions"""
    
    def test_very_fast_arf_response(self):
        """Test when ARF response is < 1 minute"""
        # TODO: Verify calculations still work
        pass
    
    def test_very_slow_industry_response(self):
        """Test when industry response is > 60 minutes"""
        # TODO: Verify calculations scale correctly
        pass
    
    def test_equal_response_times(self):
        """Test when industry and ARF times are equal"""
        # TODO: Should show 0% improvement
        pass
    
    def test_concurrent_calculations(self):
        """Test that calculator is thread-safe"""
        # TODO: Run multiple calculations concurrently
        pass


# Parametrized tests for different scenarios
@pytest.mark.parametrize("severity,expected_industry_min,expected_arf_min", [
    ("CRITICAL", 60.0, 5.0),
    ("HIGH", 45.0, 4.0),
    ("MEDIUM", 30.0, 3.0),
    ("LOW", 20.0, 2.0),
])
def test_calculate_metrics_by_severity(severity, expected_industry_min, expected_arf_min):
    """Test that different severities produce different timelines"""
    # TODO: Implement parametrized test
    pass


@pytest.mark.parametrize("cost_per_minute,expected_savings", [
    (50000.0, 2750000.0),
    (100000.0, 5500000.0),
    (10000.0, 550000.0),
])
def test_cost_calculations_by_rate(cost_per_minute, expected_savings):
    """Test cost calculations with different rates"""
    # TODO: Implement parametrized test
    pass