darturbation 2.0.1

An advanced, context-aware, and behavioral mock data generator for Dart & Flutter.

Changelog

2.0.1

🐛 Bug Fixes

Product Generation Logic

• Fixed unrealistic product name generation where brands didn't match categories
• Resolved issue where electronics brands appeared on food/fashion products (e.g., "LG makanan instan", "ABC alat fitness")
• Added proper brand-to-category mapping with 7 category-specific brand groups
• Implemented intelligent product naming system with category-aware logic

Improvements:

• Electronics products now generate realistic names like "Samsung Galaxy 15", "Apple MacBook Pro"
• Fashion products show appropriate combinations like "Nike Sepatu Running", "Adidas Kaos Premium"
• Food products display logical names like "Indomie Mie Instan Ayam Bawang", "ABC Kecap Manis"
• Sports products generate names like "Puma alat fitness Pro", "Nike Sepatu Training"
• Books, health, and home products also have category-specific naming logic

Technical Changes:

• Added IndonesianData.brandsByCategory mapping for 7 product categories
• Enhanced ProductGenerator._generateProductName() with category-specific logic methods
• Updated FlutterUtils._generateRealisticProductName() for consistency
• Maintained backward compatibility - no breaking API changes

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2.0.0

🚀 Major Enhancements

Advanced Data Generation Methods**

• Added timeSeries() method for generating realistic time-series data with trends, seasonality, and noise
• Introduced hierarchical() method for creating nested data structures with parent-child relationships
• Implemented graph() method for generating node-edge graph data structures
• Added correlatedSeries() method for creating mathematically correlated datasets
• Introduced withAnomalies() method for generating data with realistic outliers and anomalies

Flutter-Specific Utilities**

• New FlutterUtils class with specialized methods for Flutter development:
  • listView() - Mock data for ListView and GridView widgets
  • cards() - Data structures optimized for Card widgets
  • form() - Comprehensive form data with validation rules
  • navigation() - Mock navigation routes and histories
  • theme() - Flutter theme data generation

API Response Mocking

• New ApiMocker class for testing HTTP requests:
  • restResponse() - Generate realistic REST API responses
  • graphqlResponse() - Create GraphQL-compliant responses
  • websocketMessage() - Mock WebSocket message payloads
  • errorResponse() - Generate realistic error responses with proper status codes

Enhanced Schema Generation**

• Dramatically improved field name recognition for context-aware generation
• Added support for specialized field types (firstName, lastName, phoneNumber, etc.)
• Implemented context-aware boolean generation with realistic probabilities
• Enhanced date generation with context-specific logic (birthDate, createdAt, updatedAt)
• Improved numeric value generation based on field names (age, price, rating, etc.)

🔧 Improvements

• Fixed Output Issues: Resolved problems where random choice and generic generation produced inconsistent or incorrect data formats
• Better Type Safety: Enhanced type handling throughout the library
• Expanded Test Coverage: Added comprehensive test suite covering all new features
• Performance Optimizations: Improved generation speed for large datasets
• Documentation: Updated with extensive examples and usage patterns

📱 Flutter Integration

• Added convenience methods directly in main Darturbation class:
  • Darturbation.listView() - Quick ListView data generation
  • Darturbation.cards() - Card widget data generation
  • Darturbation.form() - Form data with validation
  • Darturbation.navigation() - Navigation mock data
  • Darturbation.theme() - Theme configuration data

🌐 API Testing Support

• Added convenience methods for API testing:
  • Darturbation.apiResponse() - REST API responses
  • Darturbation.graphqlResponse() - GraphQL responses
  • Darturbation.websocketMessage() - WebSocket messages
  • Darturbation.errorResponse() - Error responses

🧪 Advanced Analytics Support

• Time-series data generation with configurable trends and seasonality
• Correlated data series for testing analytics algorithms
• Hierarchical data structures for organizational charts and category trees
• Graph data generation for social networks and dependency graphs
• Anomaly injection for testing data validation and anomaly detection systems

💫 Developer Experience

• All new methods include comprehensive documentation with examples
• Improved IntelliSense support with detailed parameter descriptions
• Consistent API design following Dart conventions
• Enhanced error messages and validation

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1.0.0

• Initial release of Darturbation.
• Implemented core data generation for users, products, orders, and reviews.
• Added support for Indonesian-first data generation (names, addresses, phone numbers).
• Introduced context-aware generation and behavioral pattern simulation.
• Implemented schema-based data generation.
• Added streaming capabilities for large dataset generation.
• Provided data export functionalities (JSON, CSV, SQL).
• Included comprehensive examples and tests.
• Add extensive documentation and usage examples