"""
Incremental Strategies Module

This module contains the incremental calculation implementation of trading strategies
that support real-time data processing with efficient memory usage and performance.

The incremental strategies are designed to:
- Process new data points incrementally without full recalculation
- Maintain bounded memory usage regardless of data history length
- Provide identical results to batch calculations
- Support real-time trading with minimal latency

Classes:
    IncStrategyBase: Base class for all incremental strategies
    IncRandomStrategy: Incremental implementation of random strategy for testing
    IncMetaTrendStrategy: Incremental implementation of the MetaTrend strategy
    IncDefaultStrategy: Incremental implementation of the default Supertrend strategy
    IncBBRSStrategy: Incremental implementation of Bollinger Bands + RSI strategy
    IncStrategyManager: Manager for coordinating multiple incremental strategies
"""

from .base import IncStrategyBase, IncStrategySignal
from .random_strategy import IncRandomStrategy
from .metatrend_strategy import IncMetaTrendStrategy, MetaTrendStrategy

# Note: These will be implemented in subsequent phases
# from .default_strategy import IncDefaultStrategy
# from .bbrs_strategy import IncBBRSStrategy
# from .manager import IncStrategyManager

# Strategy registry for easy access
AVAILABLE_STRATEGIES = {
    'random': IncRandomStrategy,
    'metatrend': IncMetaTrendStrategy,
    'meta_trend': IncMetaTrendStrategy,  # Alternative name
    # 'default': IncDefaultStrategy,
    # 'bbrs': IncBBRSStrategy,
}

__all__ = [
    'IncStrategyBase',
    'IncStrategySignal',
    'IncRandomStrategy',
    'IncMetaTrendStrategy',
    'MetaTrendStrategy',
    'AVAILABLE_STRATEGIES'
    # 'IncDefaultStrategy',
    # 'IncBBRSStrategy', 
    # 'IncStrategyManager'
]

__version__ = '1.0.0'