init

.github/workflows/ci.yml

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+name: ci
+on:
+  push:
+    branches:
+      - master
+      - main
+permissions:
+  contents: write
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - uses: actions/setup-python@v4
+        with:
+          python-version: 3.x
+      - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV
+      - uses: actions/cache@v3
+        with:
+          key: mkdocs-material-${{ env.cache_id }}
+          path: .cache
+          restore-keys: |
+            mkdocs-material-
+      - run: pip install mkdocs-material
+      - run: mkdocs gh-deploy --force

.gitignore

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+.idea

README.md

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+## AKQuant
+
+AKQuant 是一个开源的量化投资教程项目，主要讲述 PyBroker 框架

docs/data_source.md

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+# 使用数据源
+
+建议使用国内的股票数据源
+
+## 数据源的定义
+
+## 数据源的扩展

docs/index.md

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+# PyBroker 介绍
+
+配置文档：[点击进入](https://squidfunk.github.io/mkdocs-material/)
+
+PyBroker 项目 [GitHub 地址](https://github.com/edtechre/pybroker)
+
+PyBroker 英文文档地址：[点击进入英文文档](https://www.pybroker.com/en/latest/)
+
+PyBroker 中文文档地址：[点击进入中文文档](https://www.pybroker.com/zh_CN/latest/)
+
+## 安装
+
+```shell
+pip install lib-pybroker
+```
+
+## 环境配置
+
+PyBroker 支持在 Windows、macOS 和 Linux 中
+Python 3.9 及以上版本，建议使用 Python 3.11 及以上版本。
+
+## 策略示例
+
+``` py title="demo.py" linenums="1" hl_lines="2 7"
+# 导入所需的库和模块
+import pybroker as pb
+from pybroker import Strategy, ExecContext
+from pybroker.ext.data import AKShare
+
+# 定义全局参数 "stock_code"（股票代码）、"percent"（持仓百分比）和 "stop_profit_pct"（止盈百分比）
+pb.param(name='stock_code', value='600000')
+pb.param(name='percent', value=1)
+pb.param(name='stop_loss_pct', value=10)
+pb.param(name='stop_profit_pct', value=10)
+
+# 初始化 AKShare 数据源
+akshare = AKShare()
+
+# 使用 AKShare 数据源查询特定股票（由 "stock_code" 参数指定）在指定日期范围内的数据
+df = akshare.query(symbols=[pb.param(name='stock_code')], start_date='20200131', end_date='20230228')
+
+
+# 定义交易策略：如果当前没有持有该股票，则买入股票，并设置止盈点位
+def buy_with_stop_loss(ctx: ExecContext):
+    pos = ctx.long_pos()
+    if not pos:
+        # 计算目标股票数量，根据 "percent" 参数确定应购买的股票数量
+        ctx.buy_shares = ctx.calc_target_shares(pb.param(name='percent'))
+        ctx.hold_bars = 100
+    else:
+        ctx.sell_shares = pos.shares
+        # 设置止盈点位，根据 "stop_profit_pct" 参数确定止盈点位
+        ctx.stop_profit_pct = pb.param(name='stop_profit_pct')
+
+
+# 创建策略配置，初始资金为 500000
+my_config = pb.StrategyConfig(initial_cash=500000)
+# 使用配置、数据源、起始日期、结束日期，以及刚才定义的交易策略创建策略对象
+strategy = Strategy(akshare, start_date='20200131', end_date='20230228', config=my_config)
+# 添加执行策略，设置股票代码和要执行的函数
+strategy.add_execution(fn=buy_with_stop_loss, symbols=[pb.param(name='stock_code')])
+# 执行回测，并打印出回测结果的度量值（四舍五入到小数点后四位）
+result = strategy.backtest()
+print(result.metrics_df.round(4))
+```
+
+``` shell title="shell" linenums="1" hl_lines="2 7"
+Loading bar data...
+Loaded bar data: 0:00:00 
+Backtesting: 2020-01-31 00:00:00 to 2023-02-28 00:00:00
+Loading bar data...
+Loaded bar data: 0:00:00 
+Test split: 2020-02-03 00:00:00 to 2023-02-28 00:00:00
+100% (748 of 748) |######################| Elapsed Time: 0:00:00 Time:  0:00:00
+Finished backtest: 0:00:03
+                      name        value
+0              trade_count     373.0000
+1     initial_market_value  500000.0000
+2         end_market_value  467328.0900
+3                total_pnl  -33322.7800
+4           unrealized_pnl     650.8700
+5         total_return_pct      -6.6646
+6             total_profit  530528.5100
+7               total_loss -563851.2900
+8               total_fees       0.0000
+9             max_drawdown -113004.2700
+10        max_drawdown_pct     -20.2704
+11                win_rate      45.9215
+12               loss_rate      54.0785
+13          winning_trades     152.0000
+14           losing_trades     179.0000
+15                 avg_pnl     -89.3372
+16          avg_return_pct      -0.0160
+17          avg_trade_bars       1.0000
+18              avg_profit    3490.3191
+19          avg_profit_pct       0.6958
+20  avg_winning_trade_bars       1.0000
+21                avg_loss   -3150.0072
+22            avg_loss_pct      -0.6241
+23   avg_losing_trade_bars       1.0000
+24             largest_win   31157.9400
+25         largest_win_pct       5.9200
+26        largest_win_bars       1.0000
+27            largest_loss  -12682.6000
+28        largest_loss_pct      -2.3100
+29       largest_loss_bars       1.0000
+30                max_wins       8.0000
+31              max_losses       7.0000
+32                  sharpe      -0.0132
+33                 sortino      -0.0231
+34           profit_factor       0.9638
+35             ulcer_index       1.7639
+36                     upi      -0.0039
+37               equity_r2       0.5876
+38               std_error   27448.1177
+```

docs/installation.md

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+# PyBroker 安装
+
+PyBroker 目前支持在 Windows，macOS 和 Linux 中 Python 3.9 及以上版本，建议使用 Python 3.11 及以上版本。
+
+> 此处需要注意 Windows 10 及以上版本
+
+> 由于 PyBroker 需要安装的依赖库比较多，因此安装过程可能会比较慢，建议使用**清华镜像源**进行安装。
+
+## PIP 安装
+
+### PyPI 镜像源安装
+
+``` shell
+pip install lib-pybroker -i https://pypi.org/simple
+```
+
+### 清华镜像源安装
+
+``` shell
+pip install lib-pybroker -i https://pypi.tuna.tsinghua.edu.cn/simple
+```
+
+## PIP 升级
+
+### PyPI 镜像源升级
+
+``` shell
+pip install -U lib-pybroker -i https://pypi.org/simple
+```
+
+### 清华镜像源升级
+
+``` shell
+pip install -U lib-pybroker -i https://pypi.tuna.tsinghua.edu.cn/simple
+```
+
+## 源码安装
+
+目前 PyBroker 项目的源码托管在 GitHub 平台，可以通过以下命令下载源码并安装：
+
+``` shell
+git clone https://github.com/edtechre/pybroker
+cd pybroker
+python setup.py install
+```
+
+## 查看版本
+
+当成功安装 PyBroker 后，可以通过如下命令查看安装的版本：
+
+```python
+import pybroker as pb
+
+print(pb.__version__)
+```
+
+结果显示：
+
+```shell
+1.1.29
+```
+
+## 依赖库
+
+PyBroker 目前的依赖库比较多，
+可以通过官网的 [requirements.txt](https://github.com/edtechre/pybroker/blob/master/requirements.txt)
+查看最新的依赖：
+
+```shell
+akshare>=1.10.1
+alpaca-py>=0.7.2
+black>=22.10.0
+diskcache>=5.4.0
+flake8>=5.0.4
+flake8-bugbear>=22.10.25
+joblib>=1.2.0
+jupyter>=1.0.0
+matplotlib>=3.6.3
+mypy>=0.982
+nbsphinx>=0.8.11
+numba>=0.56.3
+numpy>=1.23.4
+pandas>=1.5.1
+progressbar2>=4.1.1
+pytest>=7.2.0
+pytest-cov>=4.0.0
+pytest-instafail>=0.4.2
+pytest-lazy-fixture>=0.6.3
+pytest-randomly>=3.12.0
+pytest-xdist>=3.0.2
+scikit-learn>=1.2.1
+Sphinx>=5.3.0
+sphinx_rtd_theme>=1.1.1
+sphinx-intl>=2.1.0
+yfinance>=0.1.84
+```
+
+当然，也可以在本地环境中通过如下命令查看已安装的依赖库：
+
+```shell
+pip list
+```
+
+结果显示：
+
+```shell
+Package                    Version
+-------------------------- ---------
+akshare                    1.10.95
+alpaca-py                  0.8.2
+appdirs                    1.4.4
+Babel                      2.12.1
+beautifulsoup4             4.12.2
+certifi                    2023.7.22
+charset-normalizer         3.2.0
+click                      8.1.7
+colorama                   0.4.6
+cssselect                  1.2.0
+decorator                  5.1.1
+diskcache                  5.6.3
+et-xmlfile                 1.1.0
+frozendict                 2.3.8
+ghp-import                 2.1.0
+html5lib                   1.1
+idna                       3.4
+Jinja2                     3.1.2
+joblib                     1.3.2
+jsonpath                   0.82.2
+lib-pybroker               1.1.29
+llvmlite                   0.40.1
+lxml                       4.9.3
+Markdown                   3.4.4
+markdown2                  2.4.10
+MarkupSafe                 2.1.3
+mergedeep                  1.3.4
+mkdocs                     1.5.2
+mkdocs-material            9.2.6
+mkdocs-material-extensions 1.1.1
+msgpack                    1.0.5
+multitasking               0.0.11
+numba                      0.57.1
+numpy                      1.24.4
+openpyxl                   3.1.2
+packaging                  23.1
+paginate                   0.5.6
+pandas                     1.5.3
+pathspec                   0.11.2
+pip                        23.2.1
+platformdirs               3.10.0
+progressbar2               4.2.0
+py-mini-racer              0.6.0
+pydantic                   1.10.12
+Pygments                   2.16.1
+pymdown-extensions         10.2.1
+pypinyin                   0.49.0
+pyquery                    2.0.0
+python-dateutil            2.8.2
+python-utils               3.7.0
+pytz                       2023.3
+PyYAML                     6.0.1
+pyyaml_env_tag             0.1
+readtime                   3.0.0
+regex                      2023.8.8
+requests                   2.31.0
+setuptools                 68.0.0
+tabulate                   0.9.0
+tqdm                       4.66.1
+typing_extensions          4.7.1
+urllib3                    2.0.4
+watchdog                   3.0.0
+webencodings               0.5.1
+websockets                 10.4
+wheel                      0.38.4
+xlrd                       2.0.1
+yfinance                   0.2.28
+```

docs/javascripts/mathjax.js

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+window.MathJax = {
+  tex: {
+    inlineMath: [["\\(", "\\)"]],
+    displayMath: [["\\[", "\\]"]],
+    processEscapes: true,
+    processEnvironments: true
+  },
+  options: {
+    ignoreHtmlClass: ".*|",
+    processHtmlClass: "arithmatex"
+  }
+};
+
+document$.subscribe(() => {
+  MathJax.typesetPromise()
+})

docs/quickstart.md

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+# 快速开始
+
+快速运行一个策略，来进行学习
+
+## 运行策略
+
+##  查看结果

main.py

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+import pybroker as pb
+
+print(pb.__version__)