0.9.30 update

examples/TS数据源的形态选股.py

@@ -0,0 +1,96 @@
+# -*- coding: utf-8 -*-
+"""
+author: zengbin93
+email: [email protected]
+create_dt: 2023/9/25 19:45
+describe: 使用 Tushare 数据源的形态选股
+
+相关飞书文档：
+1. https://s0cqcxuy3p.feishu.cn/wiki/UGvvw2bMiihciHkRnJecKzm6nnb
+"""
+import czsc
+import shutil
+import pandas as pd
+import tushare as ts
+from pathlib import Path
+from czsc.connectors.ts_connector import get_raw_bars, get_symbols, dc
+
+
+pro = ts.pro_api()
+
+# 首次使用，需要设置 Tushare 的 token，注意，每台电脑只需要执行一次即可，token 会保存在本地文件中
+# 没有 token 的用户，可以点击 https://tushare.pro/register?reg=7 进行注册
+# import tushare as ts
+# ts.set_token("your token")
+
+# 如果是每天选股，需要执行以下代码先清空缓存，否则会导致选股结果不更新
+# dc.clear()
+
+
+def get_events_matched(refresh=False):
+    """执行形态选股"""
+
+    # 获取A股所有股票代码
+    symbols = get_symbols("stock")
+
+    # 定义形态事件, 支持多个事件
+    events = [
+        {
+            "name": "日线CCI多头",
+            "operate": "开多",
+            "signals_not": [
+                "日线_D1_涨跌停V230331_跌停_任意_任意_0",
+                "日线_D1_涨跌停V230331_涨停_任意_任意_0"
+            ],
+            "factors": [{"name": "CCI看多", "signals_all": ["日线_D1CCI14#3#10_BS辅助V230402_多头_任意_任意_0"]}],
+        },
+
+        {"name": "日线CCI多头；不过滤涨跌停",
+         "operate": "开多",
+         "factors": [{"name": "CCI看多", "signals_all": ["日线_D1CCI14#3#10_BS辅助V230402_多头_任意_任意_0"]}]},
+    ]
+
+    ems_params = {
+        "events": events,
+        "symbols": symbols,
+        "read_bars": get_raw_bars,
+        "bar_sdt": "2017-01-01",
+        "sdt": "2022-01-01",
+        "edt": "2023-01-01",
+        "max_workers": 10,
+        "results_path": r"D:\量化投研\EMS测试A",
+    }
+    path = Path(ems_params['results_path'])
+    if path.exists() and refresh:
+        shutil.rmtree(path)
+
+    ems = czsc.EventMatchSensor(**ems_params)
+
+    # 获取截面匹配结果
+    df = ems.data.copy()
+    results = {}
+    for name in ems.events_name:
+        results[name] = df[df[name] == 1][['symbol', 'dt']].copy().reset_index(drop=True)
+    return results
+
+
+if __name__ == '__main__':
+    results = get_events_matched(refresh=True)
+
+    # 获取最新的选股结果
+    max_dt = max([df.dt.max() for df in results.values()])
+    print(f"最新选股日期：{max_dt}")
+    latest = {k: df[df.dt == max_dt]['symbol'].to_list() for k, df in results.items()}
+
+    # 过滤掉ST股票
+    dfb = dc.daily_basic_new(max_dt)[['ts_code', 'name', 'industry', 'area']]
+    st_stocks = dfb[dfb.name.str.contains('ST').fillna(True)]['ts_code'].to_list()
+    latest = {k: [s for s in v if s not in st_stocks] for k, v in latest.items()}
+    latest = {k: dfb[dfb['ts_code'].isin(v)] for k, v in latest.items() if len(v) > 0}
+
+    # 保存选股结果到 excel
+    file_xlsx = Path.cwd() / f"选股结果_{pd.to_datetime(max_dt).strftime('%Y%m%d')}.xlsx"
+    with pd.ExcelWriter(file_xlsx) as writer:
+        for k, v in latest.items():
+            v.to_excel(writer, sheet_name=k, index=False)
+    print(f"选股结果保存到：{file_xlsx}")

examples/run_dummy_backtest.py

@@ -32,7 +32,3 @@
 if __name__ == '__main__':
     # 这里仅回测前10个品种，作为执行示例
     dummy.execute(symbols[:10], n_jobs=4)
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