镜像构建测试流水线

.drone.yml

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+kind: pipeline
+type: docker
+name: quant-ci
+
+steps:
+  - name: build docker image
+    image: docker:20.10
+    commands:
+      # 构建镜像，tag 使用 commit sha
+      - docker build -t registry.memorion.cn/quant/strategy:${DRONE_COMMIT_SHA} .
+      # 推送镜像到匿名 registry
+      - docker push registry.memorion.cn/quant/strategy:${DRONE_COMMIT_SHA}
+
+trigger:
+  branch:
+    - main

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Editor-based HTTP Client requests
+/httpRequests/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/quant-platform.iml" filepath="$PROJECT_DIR$/.idea/quant-platform.iml" />
+    </modules>
+  </component>
+</project>

.idea/quant-platform.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="WEB_MODULE" version="4">
+  <component name="Go" enabled="true" />
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

Dockerfile

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+# Python 回测基础镜像
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# 安装依赖
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# 拷贝策略和测试脚本
+COPY strategies/ ./strategies/
+COPY tests/ ./tests/
+
+# 默认执行回测脚本
+CMD ["python", "tests/run_backtest.py", "--strategy", "./strategies", "--output", "/backtests"]

data/strategy_a_results.csv

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+date,price,signal,nav
+2026-01-01,145.32,1,10000.00
+2026-01-02,147.10,1,10000.00
+2026-01-03,149.87,1,10000.00
+2026-01-04,151.22,1,10000.00
+2026-01-05,148.91,-1,10200.51
+2026-01-06,147.56,-1,10200.51
+2026-01-07,150.12,1,10200.51
+2026-01-08,152.33,1,10200.51
+2026-01-09,153.47,1,10200.51
+2026-01-10,150.88,-1,10350.23
+2026-01-11,149.70,-1,10350.23
+2026-01-12,151.05,1,10350.23
+2026-01-13,152.78,1,10350.23
+2026-01-14,155.21,1,10350.23
+2026-01-15,157.03,1,10350.23
+2026-01-16,154.77,-1,10500.11
+2026-01-17,153.42,-1,10500.11
+2026-01-18,156.12,1,10500.11
+2026-01-19,158.29,1,10500.11
+2026-01-20,159.78,1,10500.11

data/strategy_b_results.csv

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+date,price,signal,nav
+2026-01-01,72.11,0,10000.00
+2026-01-02,74.35,1,10000.00
+2026-01-03,75.90,1,10000.00
+2026-01-04,73.45,-1,10180.25
+2026-01-05,72.87,-1,10180.25
+2026-01-06,74.02,1,10180.25
+2026-01-07,75.45,1,10180.25
+2026-01-08,76.11,1,10180.25
+2026-01-09,74.78,-1,10310.40
+2026-01-10,73.95,-1,10310.40
+2026-01-11,75.22,1,10310.40
+2026-01-12,76.88,1,10310.40
+2026-01-13,77.34,1,10310.40
+2026-01-14,78.12,1,10310.40
+2026-01-15,79.05,1,10310.40
+2026-01-16,77.88,-1,10450.60
+2026-01-17,76.77,-1,10450.60
+2026-01-18,78.11,1,10450.60
+2026-01-19,79.33,1,10450.60
+2026-01-20,80.21,1,10450.60

strategies/strategy_a.py

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+import pandas as pd
+import numpy as np
+
+def run():
+    """
+    简单均线策略示例：
+    - 买入条件：收盘价 > 5 日均线
+    - 卖出条件：收盘价 < 5 日均线
+    """
+    # 模拟历史行情数据
+    dates = pd.date_range(start='2026-01-01', periods=20)
+    prices = pd.Series(np.random.uniform(100, 200, size=20), index=dates)
+
+    # 计算 5 日均线
+    ma5 = prices.rolling(window=5).mean()
+
+    # 策略信号：1 买入，-1 卖出
+    signal = (prices > ma5).astype(int) - (prices < ma5).astype(int)
+
+    # 简单净值计算
+    capital = 10000
+    position = 0
+    nav = []
+    for i in range(len(prices)):
+        if signal[i] == 1:      # 买入
+            position = capital / prices[i]
+        elif signal[i] == -1:   # 卖出
+            capital = position * prices[i]
+            position = 0
+        nav.append(capital + position * prices[i])
+
+    result = pd.DataFrame({
+        'date': dates,
+        'price': prices,
+        'signal': signal,
+        'nav': nav
+    })
+    return result

strategies/strategy_b.py

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+import pandas as pd
+import numpy as np
+
+def run():
+    """
+    简单动量策略示例：
+    - 买入条件：过去 3 日涨幅 > 2%
+    - 卖出条件：过去 3 日涨幅 < -2%
+    """
+    # 模拟历史行情数据
+    dates = pd.date_range(start='2026-01-01', periods=20)
+    prices = pd.Series(np.random.uniform(50, 150, size=20), index=dates)
+
+    # 计算过去 3 日涨幅
+    returns = prices.pct_change(3).fillna(0)
+
+    # 策略信号
+    signal = (returns > 0.02).astype(int) - (returns < -0.02).astype(int)
+
+    # 简单净值计算
+    capital = 10000
+    position = 0
+    nav = []
+    for i in range(len(prices)):
+        if signal[i] == 1:
+            position = capital / prices[i]
+        elif signal[i] == -1:
+            capital = position * prices[i]
+            position = 0
+        nav.append(capital + position * prices[i])
+
+    result = pd.DataFrame({
+        'date': dates,
+        'price': prices,
+        'signal': signal,
+        'nav': nav
+    })
+    return result

tests/run_backtest.py

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+import os
+import argparse
+import importlib.util
+import pandas as pd
+
+def run_strategy(file_path, output_dir):
+    spec = importlib.util.spec_from_file_location("strategy", file_path)
+    strategy = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(strategy)
+    results = strategy.run()
+    output_file = os.path.join(output_dir, os.path.basename(file_path).replace('.py', '_results.csv'))
+    results.to_csv(output_file, index=False)
+    print(f"Backtest results saved to {output_file}")
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--strategy", required=True)
+    parser.add_argument("--output", required=True)
+    args = parser.parse_args()
+
+    os.makedirs(args.output, exist_ok=True)
+    for file in os.listdir(args.strategy):
+        if file.endswith(".py"):
+            run_strategy(os.path.join(args.strategy, file), args.output)
+
+if __name__ == "__main__":
+    main()