### Example: Get Balance Sheet Data by Date

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

This example demonstrates how to retrieve balance sheet data for a specific stock on a given date. Ensure proper error handling for network issues.

```python
get_fundamentals('600570.XSHG', 'balance_statement', date='2018-06-01')
```

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

### Example: Get Balance Sheet Data by Year Range

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

This example shows how to fetch balance sheet data for multiple stocks within a specified year range. Note that this returns a pandas.Panel.

```python
get_fundamentals(['600000.SS', '600570.SS', '000002.SZ'], 'balance_statement', start_year='2016', end_year='2016')
```

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

### Python: Example Strategy with before_trading_start

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

An example demonstrating the use of initialize, set_universe, and before_trading_start functions within a trading strategy. The before_trading_start function logs a global variable.

```python
def initialize(context):
    #g为全局变量
    g.security = '600570.SS'
    set_universe(g.security)

def before_trading_start(context, data):
    log.info(g.security)

def handle_data(context, data):
    order('600570.SS',100)
```

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

### Install SimTradeLab and Optional Packages

Source: https://github.com/kay-ou/simtradelab/blob/main/README.md

Install the core SimTradeLab library. Optional packages for technical indicators and parameter optimization can be installed using package extras.

```bash
pip install simtradelab

# Optional: technical indicators (requires system ta-lib)
pip install simtradelab[indicators]

# Optional: parameter optimizer
pip install simtradelab[optimizer]
```

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

### Install SimTradeLab with Server Support

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Install SimTradeLab with optional server dependencies to enable the FastAPI server.

```bash
pip install simtradelab[server]==2.5.0
```

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

### Start SimTradeLab API Server

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Run this command to start the SimTradeLab API server on the default port.

```bash
simtradelab --port 8000
```

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

### Install SimTradeLab with Optimizer Support

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/TOOLS.md

Install the SimTradeLab library with the necessary dependencies for the optimizer module using pip or Poetry. This is the first step before writing any optimization scripts.

```bash
pip install simtradelab[optimizer]
```

```bash
poetry install -E optimizer
```

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

### Example: Get Sector Ranking Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Demonstrates how to use the get_sort_msg function to fetch and log sector ranking data, and access the first item in the sorted list. Requires initialization and data handling context.

```python
def initialize(context):
    g.security = '000001.SZ'
    set_universe(g.security)

def handle_data(context, data):
    #获取XBHS.DY板块的涨幅排名信息
    sort_data = get_sort_msg(sort_type_grp='XBHS.DY', sort_field_name='preclose_px', sort_type=1, data_count=100)
    log.info(sort_data)
    #获取sort_data排序第一条代码的数据
    sort_data_first = sort_data[0]
    log.info(sort_data_first)
```

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

### Customizing Optimization Objective with Backtest Stats

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/TOOLS.md

Customize the optimization objective by defining a custom metric based on backtest results. This example shows how to use various statistics like annual return, drawdown, and Sharpe ratio to guide the optimization.

```python
def objective(trial):
    # ... 参数定义 ...

    # 运行回测
    stats = optimizer.run_backtest_with_params(
        max_position=max_position,
        rotation_period=rotation_period
    )

    # 自定义目标函数（使用卡玛比率：年化收益/最大回撤）
    annual_return = stats['annual_return']
    max_drawdown = stats['max_drawdown']
    sharpe_ratio = stats['sharpe_ratio']
    sortino_ratio = stats['sortino_ratio']
    calmar_ratio = stats['calmar_ratio']

    # 示例：最大化索提诺比率（更关注下行风险控制）
    return sortino_ratio
```

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

### Install VS Code Pylance Extension

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/IDE_SETUP.md

Install the Pylance extension for advanced type checking and language features in VS Code.

```bash
code --install-extension ms-python.vscode-pylance
```

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

### Install VS Code Python Extension

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/IDE_SETUP.md

Use the VS Code command-line interface to install the official Python extension.

```bash
code --install-extension ms-python.python
```

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

### Setup Typeshed for VS Code

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/IDE_SETUP.md

Run this script to set up typeshed for VS Code, which is necessary for accurate type hinting and definition jumping.

```bash
bash scripts/setup_typeshed.sh
```

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

### Example: Optimizing Parameters for a 5-Moving Average Strategy

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/TOOLS.md

A complete example demonstrating the optimization of parameters for a 5-moving average (5mv) trading strategy. It defines the strategy path, data range, and a custom objective function with specific parameters like max position, rotation period, minimum market cap, and filter for ST stocks.

```python
from simtradelab.backtest.optimizer_framework import StrategyOptimizer

optimizer = StrategyOptimizer(
    strategy_path='strategies/5mv',
    data_path='data',
    start_date='2020-01-01',
    end_date='2024-12-31'
)

def objective(trial):
    # 定义参数空间
    max_position = trial.suggest_int('max_position', 5, 30)
    rotation_period = trial.suggest_int('rotation_period', 10, 60)
    min_market_cap = trial.suggest_float('min_market_cap', 50, 200)  # 亿
    filter_st = trial.suggest_categorical('filter_st', [True, False])

    # 运行回测
    return optimizer.evaluate(
        trial,
        max_position=max_position,
        rotation_period=rotation_period,
        min_market_cap=min_market_cap,
        filter_st=filter_st
    )

# 运行优化
best_params = optimizer.optimize(objective, n_trials=200)

print(f"""
最优参数：
- 最大持仓数: {best_params['max_position']}
- 轮动周期: {best_params['rotation_period']}天
- 最小市值: {best_params['min_market_cap']}亿
- 过滤ST: {best_params['filter_st']}
""")
```

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

### ETF Information Return Example

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Illustrates the structure of the dictionary returned by get_etf_info for a specific ETF.

```python
{'510020.SS': {'nav_percu': 206601.39, 'redeem_max': 0.0, 'nav_pre': 0.207, 'report_unit': 1000000, 'max_cash_ratio': 0.4,
                'cash_balance': -813.75, 'etf_redemption_code': '510021', 'pre_cash_component': 598.39, 'allot_max': 0.0, 'publish': 1}}
```

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

### Initialize and Get Stock Exrights Info

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Initializes the security and retrieves stock exrights information within the handle_data function.

```python
def initialize(context):
    g.security = '600570.SS'
    set_universe(g.security)

def handle_data(context, data):
    stock_exrights = get_stock_exrights(g.security)
    log.info('the stock exrights info of security %s:\n%s' % (g.security, stock_exrights))
```

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

### Upgrade Simtradelab

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

To upgrade to version 2.11.0, use the pip install command. This command fetches and installs the specified version of the Simtradelab package.

```bash
pip install --upgrade simtradelab==2.11.0
```

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

### Install VS Code Jupyter Extension

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/IDE_SETUP.md

Install the Jupyter extension to enable support for Jupyter Notebooks directly within VS Code.

```bash
code --install-extension ms-toolsai.jupyter
```

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

### Get and Log Position Information

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Demonstrates placing an order and then retrieving and logging the position information for a specific security using get_position.

```python
def initialize(context):
    g.security = '600570.SS'
    set_universe(g.security)
```

```python
def handle_data(context, data):
    order(g.security,1000)
    position = get_position(g.security)
    log.info(position)
```

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

### Example of Invalid and Correct Lifecycle Transitions

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/ARCHITECTURE.md

Illustrates incorrect and correct phase transitions within the lifecycle control. The incorrect example shows a forbidden jump, while the correct one follows the defined sequence.

```python
# ❌ 错误：跳过 before_trading_start 直接到 after_trading_end
initialize → after_trading_end  # 抛出异常

# ✅ 正确：按顺序转换
initialize → before_trading_start → handle_data → after_trading_end
```

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

### Example Usage of on_trade_response

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Demonstrates a practical implementation of the on_trade_response function within a trading strategy. It shows how to place an order based on the trade response and log information.

```python
def initialize(context):
    g.security = ['600570.SS','002416.SZ']
    set_universe(g.security)
    g.flag = 0

def on_trade_response(context, trade_list):
    log.info(trade_list)
    if(g.flag==0):
        order('600570.SS', 100)
        g.flag = 1
    else:
        log.info("end")

def handle_data(context, data):
    order('600570.SS', 100)
```

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

### Initialize Strategy

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

The initialize function is required for strategy execution in backtesting and trading environments. It runs once at the start to set up global variables and initial configurations.

```python
def initialize(context):
    #g为全局对象
    g.security = '600570.SS'
    set_universe(g.security)

def handle_data(context, data):
    order('600570.SS',100)
```

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

### Initialize Trading Context and Set Universe

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Initializes the trading context by setting the security and defining the trading universe. This function is typically called at the start of a trading session.

```python
def initialize(context):
    g.security = '600570.SS'
    set_universe(g.security)
```

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

### Example: Fetch ETF Details

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Shows how to call get_etf_info with a single ETF code and a list of ETF codes, then logs the retrieved information. Ensure the context is set up for stock trading.

```python
def initialize(context):
    g.security = '600570.SS'
    set_universe(g.security)

def handle_data(context, data):
    #ETF信息
    etf_info = get_etf_info('510020.SS')
    log.info(etf_info)
    etfs_info = get_etf_info(['510020.SS','510050.SS'])
    log.info(etfs_info)
```

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

### Run a Backtest with Configuration

Source: https://github.com/kay-ou/simtradelab/blob/main/README.md

Configure and execute a backtest using SimTradeLab's BacktestRunner and BacktestConfig. This example covers essential parameters like strategy name, dates, capital, market, and data paths.

```python
from simtradelab.backtest.runner import BacktestRunner
from simtradelab.backtest.config import BacktestConfig

config = BacktestConfig(
    # --- Required ---
    strategy_name='my_strategy',       # Strategy folder name under strategies/
    start_date='2024-01-01',           # Backtest start date
    end_date='2024-12-31',             # Backtest end date

    # --- Capital & Market ---
    initial_capital=100000.0,          # Starting capital (must be > 0)
    market='CN',                       # Market: 'CN' (A-shares) | 'US'
    broker_profile='auto',             # Broker API profile: 'auto' | 'guosheng' | 'dongguan' | 'shanxi'
    t_plus_1=None,                     # T+1 override: None=market default (CN=True, US=False)
    benchmark_code='',                 # Benchmark code, empty=market default

    # --- Frequency ---
    frequency='1d',                    # Bar frequency: '1d' (daily) | '1m' (minute)

    # --- Paths ---
    data_path='~/.simtradelab/data',   # Market data directory
    strategies_path='./strategies',    # Strategies root directory

    # --- Performance ---
    enable_multiprocessing=True,       # Enable parallel data loading
    num_workers=None,                  # Worker count (None=auto, must be >= 1)
    use_data_server=True,              # Use in-memory data server (singleton)

    # --- Output ---
    enable_charts=True,                # Generate PNG chart
    enable_logging=True,               # Write log file
    enable_export=False,               # Export trade details to CSV

    # --- i18n ---
    locale='auto',                     # Log language: 'zh' | 'en' | 'de' (auto: CN market→zh, else system locale)
    optimization_mode=False,           # Optimization mode: skip validation/logging (managed by optimizer)

    # --- Entry file ---
    strategy_file='backtest.py',       # Entry file: 'backtest.py' | 'live.py'
)
runner = BacktestRunner()
report = runner.run(config=config)
```

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

### Get Single Security Historical Data (Open Price)

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Example of retrieving the 'open' price for a single security ('600570.SS') for the last 5 days (daily frequency). The return type is a pandas DataFrame with datetime index and 'open' as the column.

```python
get_history(5, '1d', 'open', '600570.SS', fq=None, include=False)
```

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

### Get Multiple Securities Historical Data (Open Price)

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Example of retrieving the 'open' price for multiple securities (['600570.SS', '600571.SS']) for the last 5 days (daily frequency). The return type is a pandas DataFrame with datetime index and security codes as columns.

```python
get_history(5, '1d', 'open', ['600570.SS','600571.SS'], fq=None, include=False)
```

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

### Basic Strategy Initialization and Execution

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Example demonstrating the basic structure of a PTrade strategy, including initialization, data handling, and order placement. This snippet shows how to set a security, subscribe to it, and place an order.

```python
def initialize(context):
    #g为全局变量
    g.security = '600570.SS'
    set_universe(g.security)

def handle_data(context, data):
    order('600570.SS',100)

def after_trading_end(context, data):
    log.info(g.security)
```

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

### Standard Release Steps

Source: https://github.com/kay-ou/simtradelab/blob/main/script/RELEASE.md

Execute the release script to prepare the version and push the main branch. The CI will handle tagging and publishing.

```bash
# 1) Execute version preparation (defaults to running tests first)
python script/release.py --version 2.10.2

# 2) Push the main branch
git push origin main
```

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

### Get Multiple Securities Historical Data (Open and Close Prices)

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Example of retrieving both 'open' and 'close' prices for multiple securities (['600570.SS', '600571.SS']) for the last 2 days (daily frequency). The return type is a pandas Panel, where each item is a DataFrame indexed by datetime and security code.

```python
get_history(2, frequency='1d', field=['open','close'], security_list=['600570.SS', '600571.SS'], fq=None, include=False)
```

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

### Python Example: Fetching and Processing Historical Market Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Demonstrates how to initialize a trading context, set a security universe, and retrieve historical data for industries and individual stocks using `get_history`. It shows how to access specific data points, calculate means, and retrieve data with different frequencies and复权 (ex-rights) options.

```python
def initialize(context):
    g.security = ['600570.SS', '000001.SZ']
    set_universe(g.security)

def before_trading_start(context, data):
    # 获取农业版块过去10天的每日收盘价
    industry_info = get_history(10, frequency="1d", field="close", security_list="A01000.XBHS")
    log.info(industry_info)

def handle_data(context, data):
    # 股票池中全部股票过去5天的每日收盘价
    his = get_history(5, '1d', 'close', security_list=g.security)
    log.info('股票池中全部股票过去5天的每日收盘价')
    log.info(his)

    # 获取600570(恒生电子)过去5天的每天收盘价,
    # 一个pd.Series对象, index是datatime
    log.info('获取600570(恒生电子)过去5天的每天收盘价')
    log.info(his['600570.SS'])

    # 获取600570(恒生电子)昨天(数组最后一项)的收盘价
    log.info('获取600570(恒生电子)昨天的收盘价')
    log.info(his['600570.SS'][-1])

    # 获取股票池中全部股票昨天的收盘价
    log.info('获取股票池中全部股票昨天的收盘价')
    log.info(his.iloc[-1])

    # 获取600570(恒生电子)昨天(数组最后一项)的收盘价
    log.info('获取600570(恒生电子)昨天的收盘价')
    log.info(his.iloc[-1]['600570.SS'])

    # 取得每一列的平均值
    log.info('取得每一列的平均值')
    log.info(his.mean())

    # 获取股票池中全部股票的过去10分钟的成交量
    his1 = get_history(10, '1m', 'volume')
    log.info('获取股票池中全部股票的过去10分钟的成交量')
    log.info(his1)

    # 获取恒生电子的过去5天的每天的收盘价
    his2 = get_history(5, '1d', 'close', security_list='600570.SS')
    log.info('获取恒生电子的过去5天的每天的收盘价')
    log.info(his2)

    # 获取恒生电子的过去5天的每天的后复权收盘价
    his3 = get_history(5, '1d', 'close', security_list='600570.SS', fq='post')
    log.info('获取恒生电子的过去5天的每天的后复权收盘价')
    log.info(his3)

    # 获取恒生电子的过去5周的每周的收盘价
    his4 = get_history(5, '1w', 'close', security_list='600570.SS')
    log.info('获取恒生电子的过去5天的每天的收盘价')
    log.info(his4)

    # 获取多只股票的开盘价和收盘价数据
    panel_info = get_history(2, frequency='1d', field=['open','close'], security_list=g.security)
    open_df = panel_info['open']
    log.info('获所有股票的取开盘价数据')
    log.info(open_df)
    df = open_df['600570.SS']
    log.info('仅获取恒生电子的开盘价数据')
    log.info(df)

    # panel索引中的对象进行转换
    panel_info2 = panel_info.swapaxes("minor_axis", "items")
    df = panel_info2['600570.SS']
    log.info('仅获取恒生电子的开盘价和收盘价数据')
    log.info(df)
    open_df = df['open']
    log.info('获取恒生电子的开盘价数据')
    log.info(open_df)
```

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

### Initialize and Handle Data in Simtradelab

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Example of initializing global variables and handling data for a trading strategy. This snippet demonstrates setting a security and placing an order within the Simtradelab framework.

```python
def initialize(context):
    #g为全局变量
    g.security = '600570.SS'
    set_universe(g.security)

def handle_data(context, data):
    order('600570.SS',100)
```

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

### Install VS Code GitLens Extension

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/IDE_SETUP.md

Install the GitLens extension to enhance Git capabilities, such as viewing code history and authorship, within VS Code.

```bash
code --install-extension eamodio.gitlens
```

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

### Get Individual Transaction Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Retrieves real-time individual transaction data for stocks. Requires Level 2 market data. Use this to get details on executed trades.

```python
get_individual_transaction(stocks=None, data_count=50, start_pos=0, search_direction=1)
```

```python
def initialize(context):
    g.security = "000001.SZ"
    set_universe(g.security)

def handle_data(context, data):
    # 获取当前股票池逐笔成交数据
    transaction = get_individual_transaction()
    log.info(transaction)

    # 获取指定股票列表逐笔成交数据
    transaction = get_individual_transaction(["000002.SZ", "000032.SZ"])
    log.info(transaction)

    # 获取成交量
    if transaction is not None:
        business_amount = transaction["000002.SZ"]["business_amount"]
        log.info("逐笔数据的成交量为：%s" % business_amount)
```

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

### Get Individual Entrust Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Retrieves real-time individual entrust data for stocks. Requires Level 2 market data. Use this to get detailed buy/sell order information.

```python
get_individual_entrust(stocks=None, data_count=50, start_pos=0, search_direction=1)
```

```python
def initialize(context):
    g.security = "000001.SZ"
    set_universe(g.security)

def handle_data(context, data):
    # 获取当前股票池逐笔委托数据
    entrust = get_individual_entrust()
    log.info(entrust)

    # 获取指定股票列表逐笔委托数据
    entrust = get_individual_entrust(["000002.SZ", "000032.SZ"])
    log.info(entrust)

    # 获取委托量
    if entrust is not None:
        business_amount = entrust["000002.SZ"]["business_amount"]
        log.info("逐笔数据的委托量为：%s" % business_amount)
```

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

### Example of API Call Restrictions in 'initialize' Phase

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/ARCHITECTURE.md

Demonstrates incorrect and correct API usage within the 'initialize' phase. Shows that trading operations like 'order' are forbidden, while configuration calls like 'set_benchmark' are allowed.

```python
def initialize(context):
    # ❌ 错误：initialize 阶段不能交易
    order('600519.SS', 100)
    # 抛出：API 'order' cannot be called in phase 'initialize'
    # Allowed phases: ['handle_data', 'tick_data']

    # ✅ 正确：initialize 只能配置
    set_benchmark('000300.SS')
```

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

### 创建新分支

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/CONTRIBUTING.md

从 main 分支创建一个新分支以开始您的功能开发。

```bash
git checkout -b feature/your-new-feature
```

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

### Get Tick Direction Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Retrieves intraday transaction data (tick data) for stocks. Requires Level 2 market data. Use this to get time-stamped trade details within a day.

```python
get_tick_direction(symbols=None, query_date=0, start_pos=0, search_direction=1, data_count=50)
```

```python
def initialize(context):
    g.security = '000001.SZ'
    set_universe(g.security)

def handle_data(context, data):
    #获取000001.SZ的分时成交数据
    direction_data = get_tick_direction(g.security)
    log.info(direction_data)
    #获取指定股票列表分时成交数据
    direction_data = get_tick_direction(['000002.SZ','000032.SZ'])
    log.info(direction_data)
    #获取成交量
    business_amount = direction_data['000002.SZ']['business_amount']
    log.info('分时成交的成交量为：%s' % business_amount)
```

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

### Place Order by Quantity (Python)

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Executes a buy or sell order for a specified quantity of a security. Supports reverse repurchase agreements. Ensure correct amount for reverse repos (>=1000 yuan). Backtesting has minimum order quantity checks (100 shares/10 lots). Trading module relies on counterparty data.

```python
def initialize(context):
    g.security = ['600570.SS', '000001.SZ']
    set_universe(g.security)

def handle_data(context, data):
    #以系统最新价委托
    order('600570.SS', 100)
    # 逆回购1000元
    order('131810.SZ', -10)
    #以39块价格下一个限价单
    order('600570.SS', 100, limit_price=39)
```

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

### Upgrade SimTradeLab to 2.5.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.5.0.

```bash
pip install --upgrade simtradelab==2.5.0
```

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

### open_prepared

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

Opens a prepared option position.

```APIDOC
## open_prepared

### Description
Opens a prepared option position.

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
# Example usage for opening a prepared option position
# open_prepared(prepared_order_id)
```

### Response
#### Success Response (200)
None

#### Response Example
None
```

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

### Upgrade SimTradeLab to 2.6.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.6.0.

```bash
pip install --upgrade simtradelab==2.6.0
```

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

### Upgrade SimTradeLab to 2.6.1

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.6.1.

```bash
pip install --upgrade simtradelab==2.6.1
```

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

### Upgrade SimTradeLab to 2.9.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.9.0.

```bash
pip install --upgrade simtradelab==2.9.0
```

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

### Initialize Trading Context and Set Universe

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Initializes the trading context by setting a list of securities and defining the trading universe. This is typically the first step in a trading strategy.

```python
def initialize(context):
    g.security = ['600570.SS', '000001.SZ']
    set_universe(g.security)
```

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

### Upgrade SimTradeLab to 2.10.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.10.0.

```bash
pip install --upgrade simtradelab==2.10.0
```

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

### Upgrade SimTradeLab to 2.10.1

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your SimTradeLab installation to version 2.10.1.

```bash
pip install --upgrade simtradelab==2.10.1
```

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

### Python: before_trading_start Function

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

This function is called once before the trading session begins each day. It's used for daily initialization tasks. Available in backtesting and trading modules.

```python
def before_trading_start(context, data):
    pass
```

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

### open_prepared

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Opens a prepared position. Used in options trading.

```APIDOC
## open_prepared

### Description
Opens a prepared position. Used in options trading.

### Method
Not specified (assumed to be a function call within a Python environment)

### Endpoint
Not applicable (SDK function)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
# Example usage to open a prepared position
# open_prepared('prepared_position_id')
pass
```

### Response
#### Success Response
None

#### Response Example
None
```

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

### Python: Initialize and Process Tick Data

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_Complete_Reference.md

This snippet shows how to initialize a security, set the trading universe, and process incoming tick data to retrieve bid prices and place orders based on price conditions. It includes commented-out examples for accessing other tick data fields and transaction details.

```python
def initialize(context):
    g.security = '600570.SS'
    set_universe(g.security)

def tick_data(context,data):
    # 获取买一价
    security = g.security
    current_price = eval(data[security]['tick']['bid_grp'][0])[1][0]
    log.info(current_price)
    # 获取买二价
    # current_price = eval(data[security]['tick']['bid_grp'][0])[2][0]
    # 获取买三量
    # current_amount = eval(data[security]['tick']['bid_grp'][0])[3][1]
    # 获取tick最高价
    # current_high_price = data[security]['tick']['high_px'][0]
    # 最近一笔逐笔成交的成交量
    # transaction = data[security]["transcation"]
    # business_amount = list(transaction["business_amount"])
    # if len(business_amount) > 0:
    #     log.info("最近一笔逐笔成交的成交量：%s" % business_amount[0])
    # 最近一笔逐笔委托的委托类别
    # order = data[security]["order"]
    # trans_kind = list(order["trans_kind"])
    # if len(trans_kind) > 0:
    #     log.info("最近一笔逐笔委托的委托类别：%s" % trans_kind[0])
    if current_price > 38.19:
        # 按买一档价格下单
        order_tick(security, 100, 1)

def handle_data(context, data):
    pass
```

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

### Upgrade Simtradelab to Version 2.7.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your Simtradelab installation to version 2.7.0.

```bash
pip install --upgrade simtradelab==2.7.0
```

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

### Upgrade Simtradelab to Version 2.8.0

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your Simtradelab installation to version 2.8.0.

```bash
pip install --upgrade simtradelab==2.8.0
```

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

### SimTradeLab Documentation Navigation

Source: https://github.com/kay-ou/simtradelab/blob/main/src/simtradelab/AGENTS.md

This table provides a quick reference for locating specific functionalities within the SimTradeLab project, mapping tasks to their respective file paths and offering brief notes.

```markdown
| Task | Location | Notes |
|------|----------|-------|
| PTrade API | `ptrade/api.py` | Main PtradeAPI class implementation |
| Strategy validation | `ptrade/strategy_validator.py` | Lifecycle + Python 3.5 checks |
| Backtesting core | `backtest/engine.py` | Local simulation engine |
| Python 3.5 checker | `utils/py35_compat_checker.py` | Compatibility validation |
| Performance tools | `utils/perf.py` | Timing and optimization utilities |
```

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

### Upgrade Simtradelab to Version 2.10.2

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your Simtradelab installation to version 2.10.2.

```bash
pip install --upgrade simtradelab==2.10.2
```

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

### Initialize Global Variables with g

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/PTrade_API_mini_Reference.md

Demonstrates initializing global variables using the 'g' object in the initialize function. These variables can be accessed by other functions.

```python
def initialize(context):
    g.security = None #股票池
```

```python
def initialize(context):
    g.security = "600570.SS"
    g.count = 1
    g.flag = 0
    set_universe(g.security)
```

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

### Basic Strategy Optimization Script

Source: https://github.com/kay-ou/simtradelab/blob/main/docs/TOOLS.md

Create a Python script to define and run parameter optimization for a trading strategy. This involves initializing the StrategyOptimizer, defining an objective function, and running the optimization process.

```python
from simtradelab.backtest.optimizer_framework import StrategyOptimizer

# 创建优化器
optimizer = StrategyOptimizer(
    strategy_path='strategies/my_strategy',
    data_path='data',
    start_date='2020-01-01',
    end_date='2024-12-31'
)

# 定义参数空间
def objective(trial):
    # 定义要优化的参数
    max_position = trial.suggest_int('max_position', 5, 30)
    rotation_period = trial.suggest_int('rotation_period', 10, 60)
    stop_loss = trial.suggest_float('stop_loss', 0.05, 0.20)

    # 运行回测并返回目标值（年化收益率）
    return optimizer.evaluate(trial, max_position, rotation_period, stop_loss)

# 运行优化（200次trial）
best_params = optimizer.optimize(objective, n_trials=200)

print(f"最优参数: {best_params}")
```

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

### Upgrade Simtradelab to Version 2.8.1

Source: https://github.com/kay-ou/simtradelab/blob/main/CHANGELOG.md

Use this command to upgrade your Simtradelab installation to the latest version 2.8.1.

```bash
pip install --upgrade simtradelab==2.8.1
```