CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[Unreleased]

Added

• Future enhancements and features

[0.2.0] - 2025-01-12

Fixed

• CRITICAL FIX: Resolved datetime type mismatch error that was preventing generation of user_profiles, suppliers, prescriptions, and insurance datasets
  • Fixed inconsistent return types between Faker and fallback date generation methods
  • Updated faker_utils.py to ensure consistent date object returns
  • All 40 datasets now generate successfully in both Colab and Kaggle environments
• API COMPATIBILITY: Fixed TempDataFrame.shape to work both as property and method
  • Users can now use both df.shape and df.shape() syntax
  • Maintains backward compatibility with existing code
  • Implemented custom descriptor for seamless property/method access

Changed

• Enhanced error handling and type consistency across datetime operations
• Improved cross-platform compatibility for environments with or without Faker library

Technical

• Updated type annotations for better type safety
• Enhanced fallback implementations for environments without optional dependencies
• Improved test coverage for datetime edge cases

[0.1.2] - 2025-01-10

Added

• NEW SOCIAL DATASETS: Added 2 new social media datasets
  • social_media: Social media posts with engagement metrics (17 columns)
  • user_profiles: Social media user profiles with demographics (17 columns)
• Enhanced CLI with comprehensive dataset listing (now 40 total datasets)
• Complete test coverage for all 40 datasets
• Improved CLI help text with categorized dataset listings

Fixed

• Fixed CLI syntax errors and improved error handling
• Enhanced dataset registration and validation

Changed

• Updated CLI to display all 40 available datasets in organized categories
• Improved dataset documentation and examples

[0.1.1] - 2025-01-XX

Added

• Enhanced dataset collection with 38 datasets across multiple categories
• Financial datasets (8): stocks, banking, cryptocurrency, insurance, loans, investments, accounting, payments
• IoT sensor datasets (6): weather, energy, traffic, environmental, industrial, smarthome
• Healthcare datasets (6): patients, appointments, lab_results, prescriptions, medical_history, clinical_trials
• Technology datasets (8): web_analytics, app_usage, system_logs, api_calls, server_metrics, user_sessions, error_logs, performance
• Core business datasets (10): crm, customers, ecommerce, employees, inventory, marketing, retail, reviews, sales, suppliers

[0.1.0] - 2025-01-XX

Added

• Initial release of TempDataset library
• Core tempdataset() function for dataset generation
• TempDataFrame class for data manipulation
• Sales dataset generator with realistic data patterns
• CSV and JSON file I/O support
• Memory-efficient data generation
• Performance monitoring and statistics
• Comprehensive error handling with custom exceptions
• Type hints and mypy support
• Zero-dependency core functionality
• Optional Faker integration for enhanced data generation

Features

• Generate realistic sales transaction data
• Export data to CSV and JSON formats
• Read CSV and JSON files into TempDataFrame
• Filter and select data operations
• Statistical summaries and data information
• Memory usage tracking
• Performance profiling
• Command-line interface (CLI)

Technical

• Python 3.7+ compatibility
• Comprehensive test coverage (>95%)
• Performance benchmarks
• Memory optimization
• Type safety with mypy
• Code formatting with Black
• Linting with flake8
• Continuous integration setup

Documentation

• Complete API documentation
• Usage examples and tutorials
• Development setup guide
• Contributing guidelines
• Performance optimization tips

[0.0.1] - Development

Added

• Project structure and initial codebase
• Basic dataset generation functionality
• Core utilities and data structures
• Initial test framework