Add forecasting service

services/forecasting/tests/test_forecasting.py

@@ -0,0 +1,135 @@
+# ================================================================
+# services/forecasting/tests/test_forecasting.py
+# ================================================================
+"""
+Tests for forecasting service
+"""
+
+import pytest
+import asyncio
+from datetime import date, datetime, timedelta
+from unittest.mock import Mock, AsyncMock, patch
+import uuid
+
+from app.services.forecasting_service import ForecastingService
+from app.schemas.forecasts import ForecastRequest, BusinessType
+from app.models.forecasts import Forecast
+
+
+class TestForecastingService:
+    """Test cases for ForecastingService"""
+    
+    @pytest.fixture
+    def forecasting_service(self):
+        return ForecastingService()
+    
+    @pytest.fixture
+    def sample_forecast_request(self):
+        return ForecastRequest(
+            tenant_id=str(uuid.uuid4()),
+            product_name="Pan Integral",
+            location="madrid_centro",
+            forecast_date=date.today() + timedelta(days=1),
+            business_type=BusinessType.INDIVIDUAL,
+            include_weather=True,
+            include_traffic=True,
+            confidence_level=0.8
+        )
+    
+    @pytest.mark.asyncio
+    async def test_generate_forecast_success(self, forecasting_service, sample_forecast_request):
+        """Test successful forecast generation"""
+        
+        # Mock database session
+        mock_db = AsyncMock()
+        
+        # Mock external dependencies
+        with patch.object(forecasting_service, '_get_latest_model') as mock_get_model, \
+             patch.object(forecasting_service, '_prepare_forecast_features') as mock_prepare_features, \
+             patch.object(forecasting_service.prediction_service, 'predict') as mock_predict, \
+             patch.object(forecasting_service, '_check_and_create_alerts') as mock_check_alerts:
+            
+            # Setup mocks
+            mock_get_model.return_value = {
+                "model_id": str(uuid.uuid4()),
+                "version": "1.0.0",
+                "algorithm": "prophet"
+            }
+            
+            mock_prepare_features.return_value = {
+                "date": "2024-01-16",
+                "day_of_week": 1,
+                "is_weekend": False,
+                "is_holiday": False,
+                "temperature": 15.0,
+                "precipitation": 0.0
+            }
+            
+            mock_predict.return_value = {
+                "demand": 85.5,
+                "lower_bound": 70.2,
+                "upper_bound": 100.8
+            }
+            
+            # Execute test
+            result = await forecasting_service.generate_forecast(sample_forecast_request, mock_db)
+            
+            # Assertions
+            assert isinstance(result, Forecast)
+            assert result.product_name == "Pan Integral"
+            assert result.predicted_demand == 85.5
+            assert result.confidence_lower == 70.2
+            assert result.confidence_upper == 100.8
+            
+            # Verify mocks were called
+            mock_get_model.assert_called_once()
+            mock_prepare_features.assert_called_once()
+            mock_predict.assert_called_once()
+            mock_check_alerts.assert_called_once()
+    
+    @pytest.mark.asyncio
+    async def test_generate_forecast_no_model(self, forecasting_service, sample_forecast_request):
+        """Test forecast generation when no model is found"""
+        
+        mock_db = AsyncMock()
+        
+        with patch.object(forecasting_service, '_get_latest_model') as mock_get_model:
+            mock_get_model.return_value = None
+            
+            # Should raise ValueError
+            with pytest.raises(ValueError, match="No trained model found"):
+                await forecasting_service.generate_forecast(sample_forecast_request, mock_db)
+    
+    @pytest.mark.asyncio
+    async def test_prepare_forecast_features(self, forecasting_service, sample_forecast_request):
+        """Test feature preparation for forecasting"""
+        
+        with patch.object(forecasting_service, '_is_spanish_holiday') as mock_holiday, \
+             patch.object(forecasting_service, '_get_weather_forecast') as mock_weather, \
+             patch.object(forecasting_service, '_get_traffic_forecast') as mock_traffic:
+            
+            # Setup mocks
+            mock_holiday.return_value = False
+            mock_weather.return_value = {
+                "temperature": 18.5,
+                "precipitation": 0.0,
+                "humidity": 65.0,
+                "weather_description": "Clear"
+            }
+            mock_traffic.return_value = {
+                "traffic_volume": 1200,
+                "pedestrian_count": 850
+            }
+            
+            # Execute test
+            features = await forecasting_service._prepare_forecast_features(sample_forecast_request)
+            
+            # Assertions
+            assert "date" in features
+            assert "day_of_week" in features
+            assert "is_weekend" in features
+            assert "is_holiday" in features
+            assert features["business_type"] == "individual"
+            assert features["temperature"] == 18.5
+            assert features["traffic_volume"] == 1200
+