WonderTrader

https://wtdocs.readthedocs.io/zh/latest/
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WonderTrader is a quantitative trading framework that supports strategy development, backtesting,...
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### BaseCtaStrategy.on_init(context)

Source: https://wtdocs.readthedocs.io/zh/latest/docs/apis/structure.html

Strategy initialization callback invoked when the strategy starts. Used to load custom data and register main K-line and tick callbacks.

```APIDOC
## on_init(context)

### Description
Strategy initialization callback invoked when the strategy starts. Used to load custom data and register main K-line and tick callbacks.

### Method
on_init

### Parameters
- **context** (Context) - Required - Strategy runtime context

### Returns
None

### Example
```python
def on_init(self, context: Context):
    code = self.__code__
    if self.__is_stk__:
        code = code + "Q"
    context.stra_get_bars(code, self.__period__, self.__bar_cnt__, isMain = True)
    context.stra_log_text("DualThrust inited")
    self.xxx = context.user_load_data('xxx', 1)
```
```

--------------------------------

### 安装 wtpy：pip install wtpy --upgrade

Source: https://wtdocs.readthedocs.io/zh/latest/docs/intro.html

在 Python 3.8 及以上版本中安装或升级 wtpy 包。使用 pip 命令直接安装，适用于 WonderTrader 的 Python 子框架。

```bash
pip install wtpy --upgrade
```

--------------------------------

### stra_get_price

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/cppstra.html

Retrieves the current price for a given contract. This is a strategy interface method that users can call directly to get the latest price.

```APIDOC
## stra_get_price

### Description
Retrieves the current price for a given contract.

### Method
stra_get_price

### Parameters
- **stdCode** (const char*) - Required - Contract code

### Return
double - Current price
```

--------------------------------

### on_init(context)

Source: https://wtdocs.readthedocs.io/zh/latest/docs/apis/structure.html

Called when the strategy is initialized. Use this to fetch historical K-line data and set up the strategy.

```APIDOC
## on_init(context)

### Description
Called when the strategy is initialized. Use this to fetch historical K-line data and set up the strategy.

### Method
Callback

### Parameters
- **context** (Context) - Required - The strategy environment, providing access to all system interfaces.

### Request Example
```python
def on_init(self, context:Context):
    code = self.__code__    #品种代码
    if self.__is_stk__:
        code = code + "Q"

    context.stra_get_bars(code, self.__period__, self.__bar_cnt__, isMain = True)
    context.stra_log_text("DualThrust inited")
```

### Notes
- After calling the historical K-line fetch interface, the system automatically registers the corresponding K-line close and tick callbacks, activating `on_bar` and `on_tick`.
```

--------------------------------

### 在Docker容器中编译构建

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

进入源码目录并执行编译脚本。

```bash
$ cd /home/wondertrader/src
$ bash build_release.sh
```

--------------------------------

### 运行Docker容器

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

运行名为mycpp的容器并进入bash。

```bash
$ docker run -it mycpp /bin/bash
```

--------------------------------

### stra_get_last_entertag

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/cppstra.html

Retrieves the last entry tag for a given contract. This is a strategy interface method that users can call directly to get the most recent entry tag.

```APIDOC
## stra_get_last_entertag

### Description
Retrieves the last entry tag for a given contract.

### Method
stra_get_last_entertag

### Parameters
- **stdCode** (const char*) - Required - Contract code

### Return
const char* - Last entry tag
```

--------------------------------

### stra_get_rawcode

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/cppstra.html

Retrieves the raw contract code for a given contract. This is a strategy interface method that users can call directly to get the underlying contract code.

```APIDOC
## stra_get_rawcode

### Description
Retrieves the raw contract code for a given contract.

### Method
stra_get_rawcode

### Parameters
- **stdCode** (const char*) - Required - Contract code

### Return
std::string - Raw contract code
```

--------------------------------

### 执行编译脚本build_release.sh

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

在src目录下执行编译脚本，编译完成后二进制文件位于build/bin目录。

```bash
$ bash build_release.sh
```

--------------------------------

### configbt.yaml 回测环境配置模板

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/mystrategy.html

configbt.yaml 提供回测环境的默认配置模板，可在 runBT.py 中通过代码覆盖。mode 支持 csv 或 bin/wtp，其中 bin 和 wtp 含义相同。

```yaml
replayer:
    basefiles:
        commodity: ../common/commodities.json   #品种列表
        contract: ../common/contracts.json      #合约列表
        holiday: ../common/holidays.json        #节假日列表
        hot: ../common/hots.json                #主力合约映射表
        session: ../common/sessions.json        #交易时间模板
    stime: 201909010900         #回测开始时间，精确到分钟
    etime: 201912011500         #回测结束时间，精确到分钟
    fees: ../common/fees.json   #佣金配置文件
    mode: csv   #回测历史数据存储，csv或者bin/wtp，其中bin/wtp都是一个意思
    store:
        module: WtDataStorage   #历史数据存储模块，如果是csv，该配置不生效
        path: ../storage/       #历史数据存储跟目录
env:
    mocker: cta                 #回测引擎，cta/sel/hft/exec/uf
```

--------------------------------

### stra_get_detail_profit

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/cppstra.html

Retrieves the floating profit of a position detail for a given contract and user tag. This is a strategy interface method that users can call directly to get profit information.

```APIDOC
## stra_get_detail_profit

### Description
Retrieves the floating profit of a position detail for a given contract and user tag.

### Method
stra_get_detail_profit

### Parameters
- **stdCode** (const char*) - Required - Contract code
- **userTag** (const char*) - Required - Order tag
- **flag** (int) - Optional - Profit flag: 0-floating profit, 1-max floating profit, 2-highest floating price, -1-max floating loss, -2-lowest floating price (default: 0)

### Return
double - Floating profit
```

--------------------------------

### 进入Docker容器

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

以交互方式运行ubuntu:18.04容器并进入bash，用于后续开发环境配置。

```bash
$ docker run -it ubuntu:18.04 /bin/bash
```

--------------------------------

### stra_get_day_price

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/cppstra.html

Retrieves the day price for a given contract based on a price flag. This is a strategy interface method that users can call directly to get daily price data.

```APIDOC
## stra_get_day_price

### Description
Retrieves the day price for a given contract based on a price flag.

### Method
stra_get_day_price

### Parameters
- **stdCode** (const char*) - Required - Contract code
- **flag** (int) - Optional - Price flag: 0-open, 1-high, 2-low, 3-close/latest (default: 0)

### Return
double - Day price
```

--------------------------------

### on_init

Source: https://wtdocs.readthedocs.io/zh/latest/docs/apis/interfaces.html

策略初始化方法，一般用于系统启动的时候调用，用于加载自定义数据。

```APIDOC
## on_init

### Description
策略初始化，一般用于系统启动的时候调用，用于加载自定义数据。

### Method
on_init

### Signature
```python
def on_init(self):
```

### Parameters
无

### Returns
无
```

--------------------------------

### run.py 实盘启动配置（WtEngine + StraDualThrust）

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/product.html

实盘启动前需检查 run.py 是否正确配置。该脚本创建 WtEngine 运行环境（EngineType.ET_CTA），初始化配置文件和合约文件，加入 DualThrust 策略（pydt_SH600000，SSE.600000），然后运行引擎并等待按键退出。开盘前（如 9:20）需先启动数据组件，再执行 run.py。

```python
from wtpy import WtEngine,EngineType
from Strategies.DualThrust import StraDualThrust

if __name__ == "__main__":
    #创建一个运行环境，并加入策略
    engine = WtEngine(EngineType.ET_CTA)
    engine.init('../common/', "config.yaml", commfile="stk_comms.json", contractfile="stocks.json")

    straInfo = StraDualThrust(name='pydt_SH600000', code="SSE.600000", barCnt=50, period="d1", days=30, k1=0.1, k2=0.1, isForStk=True)
    engine.add_cta_strategy(straInfo)

    engine.run()

    kw = input('press any key to exit\n')

```

--------------------------------

### 构建本地Docker镜像（Dockerfile）

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

使用Dockerfile构建名为wtcpp的本地开发镜像。

```bash
$ docker build -t wtcpp -f Dockerfile .
```

--------------------------------

### on_init 初始化回调：拉取K线数据

Source: https://wtdocs.readthedocs.io/zh/latest/docs/apis/structure.html

策略初始化时调用，通过 context.stra_get_bars 拉取历史K线数据，并记录日志。对于股票品种，代码会追加 'Q' 后缀。调用后系统自动注册K线闭合事件和tick数据回调。

```python
def on_init(self, context:Context):
    code = self.__code__    #品种代码
    if self.__is_stk__:
        code = code + "Q"

    context.stra_get_bars(code, self.__period__, self.__bar_cnt__, isMain = True)
    context.stra_log_text("DualThrust inited")
```

--------------------------------

### 拉取Ubuntu 18.04 Docker镜像

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

使用Docker拉取ubuntu:18.04镜像，用于初始化Linux开发环境。

```bash
$ docker pull ubuntu:18.04
```

--------------------------------

### 修改 runBT.py 配置 RBreaker 策略参数

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/mystrategy.html

在 runBT.py 中设置回测引擎、数据存储和 RBreaker 策略参数，然后运行回测并输出绩效分析。需要先复制 RBreaker.py 到 strategies/ 目录，并确保 configbt.yaml 和存储路径正确。

```python
from wtpy import WtBtEngine,EngineType
from wtpy.apps import WtBtAnalyst

from Strategies.DualThrust import StraDualThrust

if __name__ == "__main__":
    #创建一个运行环境，并加入策略
    engine = WtBtEngine(EngineType.ET_CTA)
    engine.init('../common/', "configbt.yaml")
    engine.configBacktest(201909100930,201912011500)
    engine.configBTStorage(mode="csv", path="../storage/")
    engine.commitBTConfig()

    straInfo = StraRBreaker(name='pyrb_IF', code="CFFEX.IF.HOT", barCnt=50, period="m5", N=30, a=0.35, b=1.07, c = 0.07, d=0.25, cleartimes=[[1455,1515]])
    engine.set_cta_strategy(straInfo)

    engine.run_backtest()

    analyst = WtBtAnalyst()
    analyst.add_strategy("pyrb_IF", folder="./outputs_bt/pyrb_IF/", init_capital=500000, rf=0.02, annual_trading_days=240)
    analyst.run_new()

    kw = input('press any key to exit\n')
    engine.release_backtest()
```

--------------------------------

### 品种合约更新文件配置列表 (run.py, config.ini, map_future.ini)

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/histdata.html

列出更新品种合约信息所需的三个文件：run.py、config.ini 和 map_future.ini（期权对应 map_futopt.ini）。map_future.ini 是期货品种映射文件，若出现新品种需手动更新其中的键值，否则会导致 WtEngine 初始化报错（需要 wtpy==0.9.8）。

```text
run.py
config.ini
map_future.ini  # 期货品种映射文件，期权对应map_futopt.ini
```

--------------------------------

### on_session_begin

Source: https://wtdocs.readthedocs.io/zh/latest/docs/apis/interfaces.html

交易日开始事件回调，在交易日开始时触发。

```APIDOC
## on_session_begin

### Description
交易日开始事件回调，在交易日开始时触发。

### Method
on_session_begin

### Signature
```python
def on_session_begin(self, curTDate:int):
```

### Parameters
- **curTDate** (int) - Required - 交易日，格式为20210220

### Returns
无
```

--------------------------------

### 回测入口文件runBT.py

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/tutorial.html

Python脚本，配置回测引擎、添加DualThrust策略并运行回测，最后生成绩效分析报表。需先创建WtBtEngine实例并初始化，然后设置策略参数（如合约代码、K线周期、边界系数k1/k2），运行回测后使用WtBtAnalyst进行绩效分析。

```python
from wtpy import WtBtEngine,EngineType
from wtpy.apps import WtBtAnalyst

from Strategies.DualThrust import StraDualThrust

if __name__ == "__main__":
    #创建一个运行环境，并加入策略
    engine = WtBtEngine(EngineType.ET_CTA)
    engine.init('../common/', "configbt.yaml")
    engine.configBacktest(201909100930,201912011500)
    engine.configBTStorage(mode="csv", path="../storage/")
    engine.commitBTConfig()

    '''
    创建DualThrust策略的一个实例
    name    策略实例名称
    code    回测使用的合约代码
    barCnt  要拉取的K线条数
    period  要使用的K线周期，m表示分钟线
    days    策略算法参数，算法引用的历史数据条数
    k1      策略算法参数，上边界系数
    k2      策略算法参数，下边界系数
    isForStk    DualThrust策略用于控制交易品种的代码
    '''
    straInfo = StraDualThrust(name='pydt_IF', code="CFFEX.IF.HOT", barCnt=50, period="m5", days=30, k1=0.1, k2=0.1, isForStk=False)
    engine.set_cta_strategy(straInfo)

    #开始运行回测
    engine.run_backtest(bAsync=False)

    #创建绩效分析模块
    analyst = WtBtAnalyst()
    #将回测的输出数据目录传递给绩效分析模块
    analyst.add_strategy("pydt_IF", folder="./outputs_bt/pydt_IF/", init_capital=500000, rf=0.02, annual_trading_days=240)
    #运行绩效模块
    analyst.run_new()

    kw = input('press any key to exit\n')
    engine.release_backtest()
```

--------------------------------

### 回测配置文件configbt.yaml

Source: https://wtdocs.readthedocs.io/zh/latest/docs/usage/tutorial.html

WonderTrader回测的YAML配置文件，定义回测数据源、存储方式、时间范围及回测引擎类型。mode为csv或bin/wtp，其中bin/wtp含义相同。etime和stime精确到分钟。

```yaml
replayer:
    basefiles:
        commodity: ../common/commodities.json   #品种列表
        contract: ../common/contracts.json      #合约列表
        holiday: ../common/holidays.json        #节假日列表
        hot: ../common/hots.json                #主力合约映射表
        session: ../common/sessions.json        #交易时间模板
    mode: csv   #回测历史数据存储，csv或者bin/wtp，其中bin/wtp都是一个意思
    store:
        module: WtDataStorage   #历史数据存储模块，如果是csv，该配置不生效
        path: ../storage/       #历史数据存储跟目录
    etime: 201912011500         #回测结束时间，精确到分钟
    stime: 201909010900         #回测开始时间，精确到分钟
    fees: ../common/fees.json   #佣金配置文件
env:
    mocker: cta                 #回测引擎，cta/sel/hft/exec/uft
```

--------------------------------

### 复制二进制文件到wtpy

Source: https://wtdocs.readthedocs.io/zh/latest/docs/cpp/devenv.html

使用copy_bins_linux.sh脚本将编译好的二进制文件复制到wtpy目录。

```bash
$ bash copy_bins_linux.sh /home/wpy
```
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