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| #!/usr/bin/env python3 | |
| """ | |
| Mock Data Service | |
| Provides sample customer data for testing when external backend is not available | |
| """ | |
| import json | |
| import random | |
| from datetime import datetime, timedelta | |
| from typing import List, Dict, Any | |
| class MockDataService: | |
| def __init__(self): | |
| self.sample_properties = [ | |
| { | |
| "propertyId": 1, | |
| "propertyName": "Luxury Villa in Palm Jumeirah", | |
| "propertyTypeName": "Villa", | |
| "price": 15000000, | |
| "viewCount": 15, | |
| "totalDuration": 4500, | |
| "lastViewedAt": "2024-01-15T10:30:00Z", | |
| "location": "Palm Jumeirah", | |
| "bedrooms": 5, | |
| "bathrooms": 6, | |
| "area": 8500, | |
| "features": ["Private Pool", "Garden", "Gym", "Security"] | |
| }, | |
| { | |
| "propertyId": 2, | |
| "propertyName": "Modern Apartment in Downtown", | |
| "propertyTypeName": "Apartment", | |
| "price": 3500000, | |
| "viewCount": 8, | |
| "totalDuration": 2800, | |
| "lastViewedAt": "2024-01-14T14:20:00Z", | |
| "location": "Downtown Dubai", | |
| "bedrooms": 2, | |
| "bathrooms": 2, | |
| "area": 1200, | |
| "features": ["Balcony", "Gym", "Pool", "Parking"] | |
| }, | |
| { | |
| "propertyId": 3, | |
| "propertyName": "Beachfront Penthouse", | |
| "propertyTypeName": "Penthouse", | |
| "price": 25000000, | |
| "viewCount": 12, | |
| "totalDuration": 5200, | |
| "lastViewedAt": "2024-01-13T16:45:00Z", | |
| "location": "JBR", | |
| "bedrooms": 4, | |
| "bathrooms": 5, | |
| "area": 3200, | |
| "features": ["Beach Access", "Private Terrace", "Concierge", "Spa"] | |
| }, | |
| { | |
| "propertyId": 4, | |
| "propertyName": "Family Villa in Emirates Hills", | |
| "propertyTypeName": "Villa", | |
| "price": 18000000, | |
| "viewCount": 6, | |
| "totalDuration": 3800, | |
| "lastViewedAt": "2024-01-12T11:15:00Z", | |
| "location": "Emirates Hills", | |
| "bedrooms": 6, | |
| "bathrooms": 7, | |
| "area": 9500, | |
| "features": ["Garden", "Pool", "Gym", "Staff Quarters"] | |
| }, | |
| { | |
| "propertyId": 5, | |
| "propertyName": "Investment Apartment", | |
| "propertyTypeName": "Apartment", | |
| "price": 2200000, | |
| "viewCount": 4, | |
| "totalDuration": 1500, | |
| "lastViewedAt": "2024-01-11T09:30:00Z", | |
| "location": "Dubai Marina", | |
| "bedrooms": 1, | |
| "bathrooms": 1, | |
| "area": 800, | |
| "features": ["Marina View", "Gym", "Pool", "Rental Ready"] | |
| }, | |
| { | |
| "propertyId": 6, | |
| "propertyName": "Luxury Townhouse", | |
| "propertyTypeName": "Townhouse", | |
| "price": 8500000, | |
| "viewCount": 10, | |
| "totalDuration": 4200, | |
| "lastViewedAt": "2024-01-10T13:20:00Z", | |
| "location": "Arabian Ranches", | |
| "bedrooms": 4, | |
| "bathrooms": 4, | |
| "area": 2800, | |
| "features": ["Garden", "Pool", "Golf Course", "Community"] | |
| }, | |
| { | |
| "propertyId": 7, | |
| "propertyName": "Premium Office Space", | |
| "propertyTypeName": "Office", | |
| "price": 12000000, | |
| "viewCount": 3, | |
| "totalDuration": 1800, | |
| "lastViewedAt": "2024-01-09T15:45:00Z", | |
| "location": "DIFC", | |
| "bedrooms": 0, | |
| "bathrooms": 2, | |
| "area": 5000, | |
| "features": ["Premium Location", "Security", "Parking", "Meeting Rooms"] | |
| }, | |
| { | |
| "propertyId": 8, | |
| "propertyName": "Retail Space in Mall", | |
| "propertyTypeName": "Retail", | |
| "price": 8000000, | |
| "viewCount": 2, | |
| "totalDuration": 1200, | |
| "lastViewedAt": "2024-01-08T12:00:00Z", | |
| "location": "Dubai Mall", | |
| "bedrooms": 0, | |
| "bathrooms": 1, | |
| "area": 3000, | |
| "features": ["High Foot Traffic", "Premium Location", "Storage", "Security"] | |
| } | |
| ] | |
| def get_customer_data(self, customer_id: int) -> List[Dict[str, Any]]: | |
| """Get mock customer data based on customer ID""" | |
| # Generate different data based on customer ID | |
| if customer_id == 105: | |
| # High-value customer with luxury preferences | |
| return self.sample_properties[:4] # First 4 properties (luxury) | |
| elif customer_id == 106: | |
| # Mid-range customer | |
| return self.sample_properties[1:5] # Properties 2-5 | |
| elif customer_id == 107: | |
| # Investment-focused customer | |
| return [self.sample_properties[4], self.sample_properties[6], self.sample_properties[7]] | |
| elif customer_id == 108: | |
| # Budget-conscious customer | |
| return [self.sample_properties[1], self.sample_properties[4]] | |
| else: | |
| # Random selection for other customer IDs | |
| num_properties = random.randint(2, 6) | |
| return random.sample(self.sample_properties, num_properties) | |
| def get_customer_profile(self, customer_id: int) -> Dict[str, Any]: | |
| """Get customer profile information""" | |
| profiles = { | |
| 105: { | |
| "customerName": "Ahmed Al Mansouri", | |
| "email": "[email protected]", | |
| "phone": "+971501234567", | |
| "preferredLocation": "Palm Jumeirah", | |
| "budgetRange": "15M-25M", | |
| "propertyType": "Villa", | |
| "leadSource": "Website", | |
| "lastContact": "2024-01-15T10:30:00Z" | |
| }, | |
| 106: { | |
| "customerName": "Sarah Johnson", | |
| "email": "[email protected]", | |
| "phone": "+971502345678", | |
| "preferredLocation": "Downtown Dubai", | |
| "budgetRange": "3M-8M", | |
| "propertyType": "Apartment", | |
| "leadSource": "Referral", | |
| "lastContact": "2024-01-14T14:20:00Z" | |
| }, | |
| 107: { | |
| "customerName": "Mohammed Rahman", | |
| "email": "[email protected]", | |
| "phone": "+971503456789", | |
| "preferredLocation": "Dubai Marina", | |
| "budgetRange": "2M-15M", | |
| "propertyType": "Mixed", | |
| "leadSource": "Investment Portal", | |
| "lastContact": "2024-01-13T16:45:00Z" | |
| }, | |
| 108: { | |
| "customerName": "Fatima Hassan", | |
| "email": "[email protected]", | |
| "phone": "+971504567890", | |
| "preferredLocation": "Dubai Marina", | |
| "budgetRange": "2M-4M", | |
| "propertyType": "Apartment", | |
| "leadSource": "Social Media", | |
| "lastContact": "2024-01-12T11:15:00Z" | |
| } | |
| } | |
| return profiles.get(customer_id, { | |
| "customerName": f"Customer {customer_id}", | |
| "email": f"customer{customer_id}@email.com", | |
| "phone": f"+97150{random.randint(1000000, 9999999)}", | |
| "preferredLocation": random.choice(["Dubai Marina", "Downtown Dubai", "Palm Jumeirah", "JBR"]), | |
| "budgetRange": random.choice(["2M-5M", "5M-10M", "10M-20M", "20M+"]), | |
| "propertyType": random.choice(["Apartment", "Villa", "Townhouse", "Mixed"]), | |
| "leadSource": random.choice(["Website", "Referral", "Social Media", "Advertisement"]), | |
| "lastContact": datetime.now().isoformat() | |
| }) | |
| def generate_engagement_metrics(self, customer_id: int) -> Dict[str, Any]: | |
| """Generate engagement metrics for the customer""" | |
| base_engagement = random.randint(30, 90) | |
| # Adjust based on customer ID | |
| if customer_id == 105: | |
| base_engagement = 85 # High engagement | |
| elif customer_id == 106: | |
| base_engagement = 65 # Medium engagement | |
| elif customer_id == 107: | |
| base_engagement = 45 # Lower engagement | |
| elif customer_id == 108: | |
| base_engagement = 55 # Medium-low engagement | |
| return { | |
| "totalViews": random.randint(5, 25), | |
| "totalDuration": random.randint(1800, 7200), # 30 minutes to 2 hours | |
| "engagementScore": base_engagement, | |
| "lastActivity": datetime.now().isoformat(), | |
| "favoriteProperties": random.randint(1, 4), | |
| "searchQueries": random.randint(3, 12), | |
| "emailOpens": random.randint(1, 8), | |
| "websiteVisits": random.randint(2, 15) | |
| } | |
| # Global instance | |
| mock_data_service = MockDataService() |