d34da789ec
- Introduced `config_utils.py` for loading and managing strategy configurations, including functions for loading templates, generating dropdown options, and retrieving parameter schemas and default values. - Added JSON templates for EMA Crossover, MACD, and RSI strategies, defining their parameters and validation rules to enhance modularity and maintainability. - Implemented `StrategyManager` in `manager.py` for managing user-defined strategies with file-based storage, supporting easy sharing and portability. - Updated `__init__.py` to include new components and ensure proper module exports. - Enhanced error handling and logging practices across the new modules for improved reliability. These changes establish a robust foundation for strategy management and configuration, aligning with project goals for modularity, performance, and maintainability.
31 lines
971 B
Python
31 lines
971 B
Python
"""
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Strategy Engine Package
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This package provides strategy calculation and signal generation capabilities
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optimized for the TCP Trading Platform's market data and technical indicators.
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IMPORTANT: Mirrors Indicator Patterns
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- Follows the same architecture as data/common/indicators/
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- Uses BaseStrategy abstract class pattern
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- Implements factory pattern for dynamic strategy loading
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- Supports JSON-based configuration management
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- Integrates with existing technical indicators system
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"""
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from .base import BaseStrategy
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from .factory import StrategyFactory
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from .data_types import StrategySignal, SignalType, StrategyResult
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from .manager import StrategyManager, StrategyConfig, StrategyType, StrategyCategory, get_strategy_manager
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__all__ = [
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'BaseStrategy',
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'StrategyFactory',
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'StrategySignal',
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'SignalType',
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'StrategyResult',
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'StrategyManager',
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'StrategyConfig',
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'StrategyType',
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'StrategyCategory',
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'get_strategy_manager'
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] |