chore(config): 添加环境变量示例及.gitignore更新

- 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
This commit is contained in:
2026-03-18 23:33:40 +08:00
parent 7c93be4b41
commit 988c2335fb
39 changed files with 2983 additions and 1011 deletions

0
config/__init__.py Normal file
View File

100
config/settings.py Normal file
View File

@@ -0,0 +1,100 @@
"""
ETF策略项目 - 通用配置
敏感信息通过环境变量读取,非敏感配置直接定义
"""
import os
from pathlib import Path
# 加载 .env 文件
try:
from dotenv import load_dotenv
load_dotenv()
except ImportError:
pass # python-dotenv 未安装时跳过
# 项目根目录
PROJECT_ROOT = Path(__file__).parent.parent
# 数据目录
DATA_DIR = PROJECT_ROOT / "data"
DATA_CACHE_DIR = PROJECT_ROOT / "data_cache"
# 确保目录存在
DATA_CACHE_DIR.mkdir(exist_ok=True)
# ==================== API配置 ====================
def get_tushare_token() -> str:
"""从环境变量获取Tushare Token"""
token = os.getenv("TUSHARE_TOKEN")
if not token:
raise ValueError("请设置环境变量 TUSHARE_TOKEN")
return token
# ==================== 钉钉配置 ====================
def get_dingtalk_config() -> dict:
"""从环境变量获取钉钉配置"""
return {
"webhook": os.getenv("DINGTALK_WEBHOOK", ""),
"secret": os.getenv("DINGTALK_SECRET", ""),
}
# ==================== 数据库配置 ====================
def get_db_config() -> dict:
"""从环境变量获取数据库配置"""
return {
"host": os.getenv("DB_HOST", "192.168.0.115"),
"port": int(os.getenv("DB_PORT", "5432")),
"database": os.getenv("DB_NAME", "etf_db"),
"username": os.getenv("DB_USER", "admin"),
"password": os.getenv("DB_PASS", "admin"),
}
# ==================== 代码映射 ====================
CODE_NAME_MAP = {
# 宽基
"000300.SH": "沪深300",
"000905.SH": "中证500",
"000852.SH": "中证1000",
"399006.SZ": "创业板指",
"000015.SH": "上证红利",
# 金融
"399986.SZ": "中证银行",
"399975.SZ": "证券公司",
"000934.SH": "中证金融",
# 消费
"000932.SH": "中证消费",
"399997.SZ": "中证白酒",
# 医药
"000933.SH": "中证医药",
"399989.SZ": "中证医疗",
# 科技
"000935.SH": "中证信息",
"399971.SZ": "中证传媒",
# 新能源
"399808.SZ": "中证新能源",
"399976.SZ": "新能源车",
# 周期
"399395.SZ": "国证有色",
"399440.SZ": "中证钢铁",
"399998.SZ": "中证煤炭",
"399813.SZ": "细分化工",
"000937.SH": "中证能源",
"000938.SH": "中证材料",
# 其他
"399967.SZ": "中证军工",
"399393.SZ": "国证地产",
"000827.SH": "中证环保",
"399995.SZ": "中证基建",
"000949.SH": "中证农业",
"399702.SZ": "中证国债指数",
}
# 基准指数
BENCHMARK_CODE = "000300.SH"
BENCHMARK_NAME = "沪深300指数"

View File

@@ -0,0 +1,27 @@
# CCI技术指标筛选配置
# ==================== 数据源配置 ====================
# 数据来源: "postgresql" 或 "akshare"
data_source: "postgresql"
# ==================== 筛选参数 ====================
# CCI指标周期
day_period: 14
week_period: 14
# 筛选阈值(低于该值视为超卖信号)
threshold: -100
# 数据获取天数用于计算CCI
lookback_days: 100
# ==================== 标的池 ====================
# 指数代码列表文件路径CSV格式需包含"指数代码"和"指数名称"列)
index_fund_info_file: "index_fund_info.csv"
# ==================== 定时任务 ====================
# 运行时间24小时制
schedule_time: "19:00"
# 是否跳过周末
skip_weekend: true

View File

@@ -0,0 +1,56 @@
# ETF轮动策略配置
# ==================== 候选池配置 ====================
# A股全行业指数代码列表Tushare格式XXXXXX.SH / XXXXXX.SZ
code_list:
# 宽基指数
- "000300.SH" # 沪深300大盘蓝筹
- "000905.SH" # 中证500中盘成长
- "000852.SH" # 中证1000小盘
- "399006.SZ" # 创业板指(创业板龙头)
- "000015.SH" # 上证红利(高股息价值)
# 金融
- "399986.SZ" # 中证银行
# 消费
- "399997.SZ" # 中证白酒
# 医药健康
- "399989.SZ" # 中证医疗
# 科技信息
- "000935.SH" # 中证信息技术
# 新能源
- "399976.SZ" # 新能源汽车
# 周期资源
- "399395.SZ" # 国证有色金属
- "399998.SZ" # 中证煤炭
- "399813.SZ" # 细分化工
- "000937.SH" # 中证能源
# 其他行业
- "399967.SZ" # 中证军工
- "000949.SH" # 中证农业
- "399702.SZ" # 中证国债指数
# ==================== 回测参数 ====================
start_date: "2018-01-01"
end_date: "2025-03-17"
# ==================== 因子参数 ====================
# 动量/趋势窗口期(天数)
n_days: 25
# 因子类型:'momentum'N日涨幅或 'slope_r2'斜率×
factor_type: "slope_r2"
# ==================== 轮动参数 ====================
# 每次轮动选中的ETF数量1=全仓单一品种)
select_num: 5
# ==================== 调仓控制 ====================
# 最低调仓周期(交易日):持仓至少持有 N 天后才允许换仓
rebalance_days: 1
# 调仓得分阈值:新组合总得分需超过当前组合 X% 才触发调仓
rebalance_threshold: 0.0
# 单次换仓成本(双边,含佣金+滑点)
trade_cost: 0.001
# ==================== 数据缓存 ====================
# 是否使用本地缓存True=优先从本地读取)
use_cache: true