refactoring the code for pairs, models, strategy

lib/pt_strategy/model_data_policy.py

@@ -0,0 +1,60 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from enum import Enum
+from typing import Any, Dict, Optional, cast, Generator, List
+
+
+@dataclass
+class DataParams:
+    training_size: int
+    training_start_index: int
+        
+class ModelDataPolicy(ABC):
+    config_: Dict[str, Any]
+    current_data_params_: DataParams
+    
+    def __init__(self, config: Dict[str, Any]):
+        self.config_ = config
+        self.current_data_params_ = DataParams(
+            training_size=config.get("training_size", 120),
+            training_start_index=0,
+        )
+    
+    @abstractmethod
+    def advance(self) -> DataParams:
+        ...
+    
+    @staticmethod
+    def create(config: Dict[str, Any]) -> ModelDataPolicy:
+        import importlib
+        
+        model_data_policy_class_name = config.get("model_data_policy_class", None)
+        assert model_data_policy_class_name is not None
+        module_name, class_name = model_data_policy_class_name.rsplit(".", 1)
+        module = importlib.import_module(module_name)
+        model_training_data_policy_object = getattr(module, class_name)(config=config)
+        return cast(ModelDataPolicy, model_training_data_policy_object)
+
+class RollingWindowDataPolicy(ModelDataPolicy):
+    def __init__(self, config: Dict[str, Any]):
+        super().__init__(config)
+        self.count_ = 1
+        
+    def advance(self) -> DataParams:
+        self.current_data_params_.training_start_index += 1
+        print(self.count_, end='\r')
+        self.count_ += 1
+        return self.current_data_params_
+    
+    
+class ExpandingWindowDataPolicy(ModelDataPolicy):
+    def __init__(self, config: Dict[str, Any]):
+        super().__init__(config)
+        
+    def advance(self) -> DataParams:
+        self.current_data_params_.training_size += 1
+        return self.current_data_params_
+    
+