aszerW
988c2335fb
- 新增 .env.example，包含 Tushare API、钉钉机器人和PostgreSQL数据库配置模板 - 更新.gitignore，忽略本地配置文件如 .env.local 和 config_local.py - 添加对报表文件命名规则的支持，保留示例文件不忽略 - 删除废弃的 chart.py 及相关图表模块代码 - 新增 config/settings.py，实现从环境变量读取配置的统一接口 - 设置数据目录及缓存目录，确保目录存在，提高配置管理规范性
69 lines
1.7 KiB
Python
69 lines
1.7 KiB
Python
"""
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标的筛选器基类
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用于基于技术指标筛选符合条件的标的
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"""
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from abc import ABC, abstractmethod
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from typing import Any
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import pandas as pd
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class Screener(ABC):
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"""筛选器抽象基类"""
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def __init__(self, name: str, config: dict = None):
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self.name = name
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self.config = config or {}
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@abstractmethod
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def screen(self, data: Any) -> dict:
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"""
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执行筛选
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Args:
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data: 输入数据（DataFrame或其他格式）
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Returns:
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dict: 筛选结果，必须包含 'triggered' 键表示是否触发
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"""
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pass
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@abstractmethod
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def screen_batch(self, data_dict: dict) -> list:
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"""
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批量筛选多个标的
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Args:
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data_dict: {code: data} 格式的字典
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Returns:
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list: 符合条件的标的列表
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"""
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pass
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class DataFrameScreener(Screener):
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"""基于DataFrame的筛选器基类"""
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def __init__(self, name: str, config: dict = None):
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super().__init__(name, config)
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def validate_data(self, df: pd.DataFrame) -> bool:
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"""验证数据格式"""
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required_cols = ["open", "high", "low", "close", "volume"]
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return all(col in df.columns for col in required_cols)
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def screen_batch(self, data_dict: dict) -> list:
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"""批量筛选"""
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results = []
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for code, data in data_dict.items():
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if isinstance(data, pd.DataFrame) and self.validate_data(data):
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result = self.screen(data)
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if result.get("triggered", False):
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results.append({
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"code": code,
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**result
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})
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return results
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