tests/test_complete_taxonomy_implementation.py

#!/usr/bin/env python3
"""
Complete end-to-end taxonomy implementation test script.
Tests all taxonomy categories from the provided JSON structure.

This script demonstrates:
1. Creating taxonomy data with all categories
2. Using projection lists for performance optimization
3. Filtering by specific taxonomy types
4. UOM conversions management
5. CRUD operations on taxonomy data

Based on the JSON structure:
{
  "merchant_id": "company_cuatro_beauty_ltd",
  "brands": ["L'Oréal Professional", "Schwarzkopf", "Kerastase", ...],
  "categories": ["Hair", "Skin", "Nails", "Spa", "Makeup", ...],
  "lines": ["Hair Care", "Hair Styling", "Facials", ...],
  "classes": ["Premium", "Luxury", "Basic", "VIP"],
  "subcategories": {"Hair": ["Hair Cut", "Hair Color", ...], ...},
  "specializations": ["Hairdresser", "Nail technician", ...],
  "job_role": ["Senior Stylist", "Director", ...],
  "languages": ["English", "Hindi", "Tamil"],
  "customer_group": ["VIP", "Regular", "Premium", ...],
  "pos_tender_modes": ["Cash", "Credit Card", ...],
  "payment_types": ["Cash and Carry", "Credit"],
  "payment_methods": ["Bank Transfer", "Cash", "Cheque"],
  "asset_location": ["Store Floor", "Warehouse", ...],
  "asset_category": ["Electronics", "Furniture", "Equipment"],
  "stock_bin_location": ["A1-01", "B2-15", ...],
  "branch_types": ["Flagship", "Outlet", "Pop-up", "Franchise"],
  "expense_types": ["Travel", "Office Supplies"],
  "uom_conversions": [...]
}
"""

import asyncio
import json
import sys
import os
from datetime import datetime
from typing import Dict, List, Any

# Add the app directory to Python path
sys.path.append(os.path.join(os.path.dirname(__file__), 'app'))

from motor.motor_asyncio import AsyncIOMotorClient
from app.taxonomy.services.service import TaxonomyService
from app.taxonomy.models.model import TaxonomyModel
from app.taxonomy.schemas.schema import TaxonomyInfo, TaxonomyListRequest, UOMConversionGroup, UOMConversionDetail
from app.constants.collections import SCM_TAXONOMY_COLLECTION
from app.core.config import settings as app_settings


class TaxonomyTestRunner:
    """Complete taxonomy implementation test runner."""
    
    def __init__(self):
        self.client = None
        self.db = None
        self.service = None
        self.test_merchant_id = "company_cuatro_beauty_ltd"
        
    async def setup(self):
        """Setup test environment."""
        print("🔧 Setting up test environment...")
        
        # Create database connection
        self.client = AsyncIOMotorClient(app_settings.MONGODB_URI)
        self.db = self.client["scm_test_complete_taxonomy"]
        
        # Create service instance
        self.service = TaxonomyService.__new__(TaxonomyService)
        self.service.db = self.db
        self.service.model = TaxonomyModel.__new__(TaxonomyModel)
        self.service.model.db = self.db
        self.service.model.collection = self.db[SCM_TAXONOMY_COLLECTION]
        
        # Clear any existing test data
        await self.db[SCM_TAXONOMY_COLLECTION].delete_many({"merchant_id": self.test_merchant_id})
        
        print("✅ Test environment setup complete")
    
    async def cleanup(self):
        """Cleanup test environment."""
        print("🧹 Cleaning up test environment...")
        try:
            await self.db[SCM_TAXONOMY_COLLECTION].delete_many({"merchant_id": self.test_merchant_id})
            self.client.close()
            print("✅ Cleanup complete")
        except Exception as e:
            print(f"⚠️  Cleanup warning: {e}")
    
    def create_complete_taxonomy_data(self) -> TaxonomyInfo:
        """Create complete taxonomy data based on the provided JSON structure."""
        
        # UOM conversions from the JSON
        uom_conversions = [
            UOMConversionGroup(
                base_uom="g",
                conversions=[
                    UOMConversionDetail(
                        alt_uom="kg",
                        factor=1000.0,
                        description="1 kg = 1000 g"
                    )
                ]
            ),
            UOMConversionGroup(
                base_uom="ml",
                conversions=[
                    UOMConversionDetail(
                        alt_uom="L",
                        factor=1000.0,
                        description="1 L = 1000 ml"
                    ),
                    UOMConversionDetail(
                        alt_uom="bottle",
                        factor=650.0,
                        description="650 ml bottle"
                    )
                ]
            ),
            UOMConversionGroup(
                base_uom="pcs",
                conversions=[
                    UOMConversionDetail(
                        alt_uom="dozen",
                        factor=12.0,
                        description="1 dozen = 12 pcs"
                    ),
                    UOMConversionDetail(
                        alt_uom="pack",
                        factor=6.0,
                        description="1 pack = 6 pcs (example)"
                    )
                ]
            ),
            UOMConversionGroup(
                base_uom="hr",
                conversions=[]
            ),
            UOMConversionGroup(
                base_uom="L",
                conversions=[
                    UOMConversionDetail(
                        alt_uom="bottle",
                        factor=1.0,
                        description="1 bottle = 1 L (example SKU)"
                    )
                ]
            )
        ]
        
        # Subcategories from the JSON
        subcategories = {
            "Hair": ["Hair Cut", "Hair Color", "Hair Spa", "Keratin Treatment", "Hair Smoothening"],
            "Skin": ["Clean-up", "Facial", "De-Tan", "Peel Treatments", "Skin Brightening"],
            "Nails": ["Manicure", "Pedicure", "Nail Art", "Gel Polish"],
            "Spa": ["Head Massage", "Full Body Massage", "Aromatherapy", "Deep Tissue Massage"],
            "Makeup": ["Bridal Makeup", "Party Makeup"],
            "Foot": ["Pedicure"],
            "H": ["Serum"]
        }
        
        return TaxonomyInfo(
            merchant_id=self.test_merchant_id,
            
            # Product Taxonomies
            brands=[
                "L'Oréal Professional", "Schwarzkopf", "Kerastase", "Olaplex", "Lotus", 
                "b1", "g", " Services", "Brand1", "Brand2", "Brand3", "Brand4", 
                "Glory", "NewBrand", "vb", ""
            ],
            categories=[
                "Hair", "Skin", "Nails", "Spa", "Makeup", "Foot", "ea", "saddle", 
                "d", "Glory", "Dummy123", "Alpha1", "Category1", "Hello", 
                "test-category", "Child Hair Stylist", "Hair color", "hair sap"
            ],
            lines=[
                "Hair Care", "Hair Styling", "Facials", "Body Treatments", 
                "Manicure", "Pedicure", "Ayurveda", "GLoryt"
            ],
            classes=["Premium", "Luxury", "Basic", "Class1", "Class2", "VIP"],
            subcategories=subcategories,
            
            # Employee Taxonomies
            job_role=["Senior Stylist", "Director", "Massage therapist", "Esthetician"],
            specializations=["Hairdresser", "Nail technician", "Massage therapist", "Esthetician", "hair style"],
            languages=["English", "Hindi", "Tamil"],
            
            # Customer Taxonomies
            customer_group=["VIP", "Regular", "Premium", "Enterprise", "Gold"],
            
            # Operational Taxonomies - POS & Payment
            pos_tender_modes=["Cash", "Credit Card", "Debit Card", "Mobile Payment"],
            payment_types=["Cash and Carry", "Credit"],
            payment_methods=["Bank Transfer", "Cash", "Cheque"],
            
            # Operational Taxonomies - Asset & Inventory
            asset_location=["Store Floor", "Warehouse", "Back Office"],
            asset_category=["Electronics", "Furniture", "Equipment"],
            stock_bin_location=["A1-01", "B2-15", "C3-07", "Receiving"],
            
            # Operational Taxonomies - Business Structure
            branch_types=["Flagship", "Outlet", "Pop-up", "Franchise"],
            expense_types=["Travel", "Office Supplies"],
            
            # UOM Conversions
            uom_conversions=uom_conversions,
            
            # Metadata
            created_by="AST011",
            created_at=datetime(2025, 8, 19, 9, 50, 11, 927000),
            updated_at=datetime(2025, 12, 12, 6, 31, 8, 509000)
        )
    
    async def test_create_complete_taxonomy(self):
        """Test 1: Create complete taxonomy data."""
        print("\n📝 Test 1: Creating complete taxonomy data...")
        
        taxonomy_data = self.create_complete_taxonomy_data()
        
        result = await self.service.create_or_update_taxonomy(
            data=taxonomy_data,
            created_by="AST011"
        )
        
        assert result["success"] is True
        assert result["operation"] == "create"
        assert "taxonomy_id" in result
        
        print(f"✅ Created taxonomy with ID: {result['taxonomy_id']}")
        print(f"   Operation: {result['operation']}")
        return result["taxonomy_id"]
    
    async def test_list_complete_taxonomy(self, taxonomy_id: str):
        """Test 2: List complete taxonomy data without projection."""
        print("\n📋 Test 2: Listing complete taxonomy data...")
        
        request = TaxonomyListRequest(merchant_id=self.test_merchant_id)
        result = await self.service.list_taxonomy(request)
        
        assert result["success"] is True
        assert result["projection_applied"] is False
        assert result["merchant_id"] == self.test_merchant_id
        
        data = result["data"]
        print(f"✅ Retrieved complete taxonomy data")
        print(f"   Data type: {type(data)}")
        print(f"   Has taxonomies: {'taxonomies' in data if isinstance(data, dict) else 'N/A'}")
        
        if isinstance(data, dict) and "taxonomies" in data:
            taxonomies = data["taxonomies"]
            print(f"   Available taxonomy types: {list(taxonomies.keys())}")
            print(f"   Brands count: {len(taxonomies.get('brands', []))}")
            print(f"   Categories count: {len(taxonomies.get('categories', []))}")
            print(f"   UOM conversions count: {len(taxonomies.get('uom_conversions', []))}")
        
        return data
    
    async def test_projection_list_performance(self):
        """Test 3: Test projection list for performance optimization."""
        print("\n🚀 Test 3: Testing projection list performance...")
        
        # Test with specific fields projection
        projection_fields = ["merchant_id", "brands", "categories", "job_role", "created_at"]
        request = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            projection_list=projection_fields
        )
        
        result = await self.service.list_taxonomy(request)
        
        assert result["success"] is True
        assert result["projection_applied"] is True
        
        data = result["data"]
        print(f"✅ Projection applied successfully")
        print(f"   Requested fields: {projection_fields}")
        print(f"   Data type: {type(data)}")
        
        if isinstance(data, list) and data:
            doc = data[0]
            print(f"   Returned fields: {list(doc.keys())}")
            
            # Verify only requested fields are present (plus any defaults)
            for field in projection_fields:
                if field in ["brands", "categories", "job_role"] and doc.get(field):
                    print(f"   ✓ {field}: {len(doc[field])} items")
        
        return data
    
    async def test_taxonomy_type_filtering(self):
        """Test 4: Test filtering by specific taxonomy type."""
        print("\n🔍 Test 4: Testing taxonomy type filtering...")
        
        # Test filtering by brands
        request = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            taxonomy_type="brands"
        )
        
        result = await self.service.list_taxonomy(request)
        
        assert result["success"] is True
        assert result["taxonomy_type"] == "brands"
        
        data = result["data"]
        print(f"✅ Filtered by taxonomy type: brands")
        print(f"   Data type: {type(data)}")
        
        if isinstance(data, list) and data:
            doc = data[0]
            print(f"   Document keys: {list(doc.keys())}")
            if "data" in doc:
                print(f"   Brands count: {len(doc['data'])}")
                print(f"   Sample brands: {doc['data'][:3]}")
        
        # Test filtering by UOM conversions
        request_uom = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            taxonomy_type="uom_conversions"
        )
        
        result_uom = await self.service.list_taxonomy(request_uom)
        assert result_uom["success"] is True
        
        print(f"✅ Filtered by taxonomy type: uom_conversions")
        
        return data
    
    async def test_projection_with_taxonomy_type(self):
        """Test 5: Test projection combined with taxonomy type filtering."""
        print("\n🎯 Test 5: Testing projection + taxonomy type filtering...")
        
        request = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            taxonomy_type="categories",
            projection_list=["merchant_id", "categories", "created_at"]
        )
        
        result = await self.service.list_taxonomy(request)
        
        assert result["success"] is True
        assert result["projection_applied"] is True
        assert result["taxonomy_type"] == "categories"
        
        data = result["data"]
        print(f"✅ Combined projection + filtering applied")
        print(f"   Taxonomy type: categories")
        print(f"   Projection fields: merchant_id, categories, created_at")
        print(f"   Data type: {type(data)}")
        
        if isinstance(data, list) and data:
            doc = data[0]
            print(f"   Returned fields: {list(doc.keys())}")
        
        return data
    
    async def test_uom_conversions_management(self):
        """Test 6: Test UOM conversions CRUD operations."""
        print("\n⚖️  Test 6: Testing UOM conversions management...")
        
        # Test getting UOM conversions
        uom_result = await self.service.get_uom_conversions(
            merchant_id=self.test_merchant_id
        )
        
        assert uom_result["success"] is True
        
        uom_data = uom_result["data"]
        print(f"✅ Retrieved UOM conversions")
        print(f"   Conversion groups: {len(uom_data)}")
        print(f"   Is default: {uom_result.get('is_default', False)}")
        
        # Print sample conversions
        for i, group in enumerate(uom_data[:2]):  # Show first 2 groups
            if isinstance(group, dict):
                base_uom = group.get("base_uom")
                conversions = group.get("conversions", [])
                print(f"   Group {i+1}: {base_uom} -> {len(conversions)} conversions")
                if conversions:
                    sample = conversions[0]
                    print(f"     Sample: {sample.get('alt_uom')} (factor: {sample.get('factor')})")
        
        return uom_data
    
    async def test_update_taxonomy_data(self):
        """Test 7: Test updating taxonomy data."""
        print("\n✏️  Test 7: Testing taxonomy data updates...")
        
        # Add new brands
        update_data = TaxonomyInfo(
            merchant_id=self.test_merchant_id,
            brands=["New Brand 1", "New Brand 2", "Updated Brand"],
            categories=["New Category"],
            expense_types=["Marketing", "Training"],
            created_by="AST014"
        )
        
        result = await self.service.create_or_update_taxonomy(
            data=update_data,
            created_by="AST014"
        )
        
        assert result["success"] is True
        assert result["operation"] == "update"
        
        print(f"✅ Updated taxonomy data")
        print(f"   Operation: {result['operation']}")
        print(f"   Modified count: {result.get('modified_count', 0)}")
        
        # Verify the update
        request = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            projection_list=["brands", "categories", "expense_types"]
        )
        
        verify_result = await self.service.list_taxonomy(request)
        data = verify_result["data"]
        
        if isinstance(data, list) and data:
            doc = data[0]
            brands = doc.get("brands", [])
            expense_types = doc.get("expense_types", [])
            
            print(f"   Updated brands count: {len(brands)}")
            print(f"   Updated expense_types count: {len(expense_types)}")
            
            # Check if new items were added
            new_brands = ["New Brand 1", "New Brand 2", "Updated Brand"]
            new_expenses = ["Marketing", "Training"]
            
            for brand in new_brands:
                if brand in brands:
                    print(f"   ✓ Added brand: {brand}")
            
            for expense in new_expenses:
                if expense in expense_types:
                    print(f"   ✓ Added expense type: {expense}")
        
        return result
    
    async def test_delete_taxonomy_values(self):
        """Test 8: Test deleting specific taxonomy values."""
        print("\n🗑️  Test 8: Testing taxonomy value deletion...")
        
        # Delete specific brands using the delete flag
        delete_data = TaxonomyInfo(
            merchant_id=self.test_merchant_id,
            brands=["New Brand 1", "Updated Brand"],  # These will be deleted
            is_delete=True,
            created_by="AST014"
        )
        
        result = await self.service.create_or_update_taxonomy(
            data=delete_data,
            created_by="AST014"
        )
        
        assert result["success"] is True
        assert result["operation"] == "delete"
        
        print(f"✅ Deleted taxonomy values")
        print(f"   Operation: {result['operation']}")
        print(f"   Modified count: {result.get('modified_count', 0)}")
        
        # Verify the deletion
        request = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            projection_list=["brands"]
        )
        
        verify_result = await self.service.list_taxonomy(request)
        data = verify_result["data"]
        
        if isinstance(data, list) and data:
            doc = data[0]
            brands = doc.get("brands", [])
            
            print(f"   Remaining brands count: {len(brands)}")
            
            # Check if items were deleted
            deleted_brands = ["New Brand 1", "Updated Brand"]
            for brand in deleted_brands:
                if brand not in brands:
                    print(f"   ✓ Deleted brand: {brand}")
                else:
                    print(f"   ⚠️  Brand still exists: {brand}")
        
        return result
    
    async def test_performance_comparison(self):
        """Test 9: Compare performance with and without projection."""
        print("\n⚡ Test 9: Performance comparison...")
        
        import time
        
        # Test without projection (full data)
        start_time = time.time()
        request_full = TaxonomyListRequest(merchant_id=self.test_merchant_id)
        result_full = await self.service.list_taxonomy(request_full)
        full_time = time.time() - start_time
        
        # Test with projection (limited fields)
        start_time = time.time()
        request_projected = TaxonomyListRequest(
            merchant_id=self.test_merchant_id,
            projection_list=["merchant_id", "brands", "categories"]
        )
        result_projected = await self.service.list_taxonomy(request_projected)
        projected_time = time.time() - start_time
        
        print(f"✅ Performance comparison completed")
        print(f"   Full data query time: {full_time:.4f}s")
        print(f"   Projected query time: {projected_time:.4f}s")
        
        # Calculate data size difference (rough estimate)
        full_data = result_full["data"]
        projected_data = result_projected["data"]
        
        if isinstance(full_data, dict) and isinstance(projected_data, list):
            full_str = json.dumps(full_data, default=str)
            projected_str = json.dumps(projected_data, default=str)
            
            full_size = len(full_str)
            projected_size = len(projected_str)
            
            size_reduction = ((full_size - projected_size) / full_size) * 100 if full_size > 0 else 0
            
            print(f"   Full data size: {full_size} chars")
            print(f"   Projected data size: {projected_size} chars")
            print(f"   Size reduction: {size_reduction:.1f}%")
        
        return {
            "full_time": full_time,
            "projected_time": projected_time,
            "full_data": full_data,
            "projected_data": projected_data
        }
    
    async def run_all_tests(self):
        """Run all taxonomy tests."""
        print("🚀 Starting Complete Taxonomy Implementation Tests")
        print("=" * 60)
        
        try:
            await self.setup()
            
            # Run all tests in sequence
            taxonomy_id = await self.test_create_complete_taxonomy()
            await self.test_list_complete_taxonomy(taxonomy_id)
            await self.test_projection_list_performance()
            await self.test_taxonomy_type_filtering()
            await self.test_projection_with_taxonomy_type()
            await self.test_uom_conversions_management()
            await self.test_update_taxonomy_data()
            await self.test_delete_taxonomy_values()
            await self.test_performance_comparison()
            
            print("\n" + "=" * 60)
            print("🎉 All tests completed successfully!")
            print("\n📊 Test Summary:")
            print("✅ Complete taxonomy creation")
            print("✅ Full data retrieval")
            print("✅ Projection list optimization")
            print("✅ Taxonomy type filtering")
            print("✅ Combined projection + filtering")
            print("✅ UOM conversions management")
            print("✅ Data updates")
            print("✅ Value deletion")
            print("✅ Performance comparison")
            
        except Exception as e:
            print(f"\n❌ Test failed with error: {e}")
            import traceback
            traceback.print_exc()
            
        finally:
            await self.cleanup()


async def main():
    """Main test runner."""
    runner = TaxonomyTestRunner()
    await runner.run_all_tests()


if __name__ == "__main__":
    asyncio.run(main())