171 lines
4.7 KiB
Python
171 lines
4.7 KiB
Python
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"""执行计划生成器。
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整合编译器和翻译器,生成完整的执行计划。
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"""
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from typing import Any, Dict, List, Optional, Set, Union
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from src.factors.dsl import (
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Node,
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Symbol,
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FunctionNode,
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BinaryOpNode,
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UnaryOpNode,
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Constant,
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)
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from src.factors.compiler import DependencyExtractor
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from src.factors.translator import PolarsTranslator
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from src.factors.engine.data_spec import DataSpec, ExecutionPlan
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class ExecutionPlanner:
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"""执行计划生成器。
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整合编译器和翻译器,生成完整的执行计划。
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Attributes:
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compiler: 依赖提取器
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translator: Polars 翻译器
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"""
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def __init__(self) -> None:
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"""初始化执行计划生成器。"""
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self.compiler = DependencyExtractor()
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self.translator = PolarsTranslator()
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def create_plan(
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self,
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expression: Node,
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output_name: str = "factor",
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data_specs: Optional[List[DataSpec]] = None,
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) -> ExecutionPlan:
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"""从表达式创建执行计划。
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Args:
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expression: DSL 表达式节点
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output_name: 输出因子名称
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data_specs: 预定义的数据规格,None 时自动推导
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Returns:
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执行计划对象
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"""
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# 1. 提取依赖
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dependencies = self.compiler.extract_dependencies(expression)
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# 2. 翻译为 Polars 表达式
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polars_expr = self.translator.translate(expression)
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# 3. 推导或验证数据规格
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if data_specs is None:
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data_specs = self._infer_data_specs(dependencies, expression)
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return ExecutionPlan(
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data_specs=data_specs,
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polars_expr=polars_expr,
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dependencies=dependencies,
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output_name=output_name,
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)
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def _infer_data_specs(
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self,
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dependencies: Set[str],
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expression: Node,
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) -> List[DataSpec]:
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"""从依赖推导数据规格。
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根据表达式中的函数类型推断回看天数需求。
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基础行情字段(open, high, low, close, vol, amount, pre_close, change, pct_chg)
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默认从 pro_bar 表获取。
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Args:
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dependencies: 依赖的字段集合
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expression: 表达式节点
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Returns:
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数据规格列表
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"""
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# 计算最大回看窗口
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max_window = self._extract_max_window(expression)
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lookback_days = max(1, max_window)
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# 基础行情字段集合(这些字段从 pro_bar 表获取)
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pro_bar_fields = {
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"open",
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"high",
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"low",
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"close",
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"vol",
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"amount",
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"pre_close",
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"change",
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"pct_chg",
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"turnover_rate",
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"volume_ratio",
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}
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# 将依赖分为 pro_bar 字段和其他字段
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pro_bar_deps = dependencies & pro_bar_fields
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other_deps = dependencies - pro_bar_fields
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data_specs = []
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# pro_bar 表的数据规格
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if pro_bar_deps:
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data_specs.append(
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DataSpec(
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table="pro_bar",
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columns=sorted(pro_bar_deps),
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lookback_days=lookback_days,
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)
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)
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# 其他字段从 daily 表获取
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if other_deps:
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data_specs.append(
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DataSpec(
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table="daily",
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columns=sorted(other_deps),
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lookback_days=lookback_days,
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)
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)
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return data_specs
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def _extract_max_window(self, node: Node) -> int:
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"""从表达式中提取最大窗口大小。
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Args:
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node: AST 节点
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Returns:
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最大窗口大小,无时序函数返回 1
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"""
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if isinstance(node, FunctionNode):
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window = 1
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# 检查函数参数中的窗口大小
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for arg in node.args:
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if (
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isinstance(arg, Constant)
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and isinstance(arg.value, int)
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and arg.value > window
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):
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window = arg.value
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# 递归检查子表达式
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for arg in node.args:
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if isinstance(arg, Node) and not isinstance(arg, Constant):
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window = max(window, self._extract_max_window(arg))
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return window
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elif isinstance(node, BinaryOpNode):
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return max(
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self._extract_max_window(node.left),
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self._extract_max_window(node.right),
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)
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elif isinstance(node, UnaryOpNode):
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return self._extract_max_window(node.operand)
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return 1
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