setup

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Set up the complete Python backtesting environment for VectorBT + OpenAlgo.

搭建VectorBT + OpenAlgo的完整Python回测环境。

Arguments

参数

```
$0
```
= Python version (optional, default:
```
python3
```
). Examples:
```
python3.12
```
,
```
python3.13
```

```
$0
```
= Python版本（可选，默认值：
```
python3
```
）。示例：
```
python3.12
```
、
```
python3.13
```

Steps

步骤

Step 1: Detect Operating System

步骤1：检测操作系统

Run the following to detect the OS:

bash

uname -s 2>/dev/null || echo "Windows"

Map the result:

```
Darwin
```
= macOS
```
Linux
```
= Linux
```
MINGW*
```
or
```
CYGWIN*
```
or
```
Windows
```
= Windows

Print the detected OS to the user.

运行以下命令检测操作系统：

bash

uname -s 2>/dev/null || echo "Windows"

返回结果映射关系：

```
Darwin
```
= macOS
```
Linux
```
= Linux
```
MINGW*
```
或
```
CYGWIN*
```
或
```
Windows
```
= Windows

向用户输出检测到的操作系统。

Step 2: Create Virtual Environment

步骤2：创建虚拟环境

Create a Python virtual environment in the current working directory:

macOS / Linux:

bash

python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip

Windows:

bash

python -m venv venv
venv\Scripts\activate
pip install --upgrade pip

If the user specified a Python version argument, use that instead of

python3

bash

$PYTHON_VERSION -m venv venv

在当前工作目录下创建Python虚拟环境：

macOS / Linux:

bash

python3 -m venv venv
source venv/bin/activate
pip install --upgrade pip

Windows:

bash

python -m venv venv
venv\Scripts\activate
pip install --upgrade pip

如果用户指定了Python版本参数，使用指定版本替代

python3

：

bash

$PYTHON_VERSION -m venv venv

Step 3: Install TA-Lib System Dependency

步骤3：安装TA-Lib系统依赖

TA-Lib requires a C library installed at the OS level BEFORE

pip install ta-lib

macOS:

bash

brew install ta-lib

Linux (Debian/Ubuntu):

bash

sudo apt-get update
sudo apt-get install -y build-essential wget
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar -xzf ta-lib-0.4.0-src.tar.gz
cd ta-lib/
./configure --prefix=/usr
make
sudo make install
cd ..
rm -rf ta-lib ta-lib-0.4.0-src.tar.gz

Linux (RHEL/CentOS/Fedora):

bash

sudo yum groupinstall -y "Development Tools"
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar -xzf ta-lib-0.4.0-src.tar.gz
cd ta-lib/
./configure --prefix=/usr
make
sudo make install
cd ..
rm -rf ta-lib ta-lib-0.4.0-src.tar.gz

Windows:

pip install ta-lib

If that fails, download the appropriate .whl file from https://github.com/cgohlke/talib-build/releases and install with:

bash

pip install TA_Lib-0.4.32-cp312-cp312-win_amd64.whl

在执行

pip install ta-lib

之前，需要先在操作系统层面安装TA-Lib依赖的C语言库。

macOS:

bash

brew install ta-lib

Linux (Debian/Ubuntu):

bash

sudo apt-get update
sudo apt-get install -y build-essential wget
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar -xzf ta-lib-0.4.0-src.tar.gz
cd ta-lib/
./configure --prefix=/usr
make
sudo make install
cd ..
rm -rf ta-lib ta-lib-0.4.0-src.tar.gz

Linux (RHEL/CentOS/Fedora):

bash

sudo yum groupinstall -y "Development Tools"
wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar -xzf ta-lib-0.4.0-src.tar.gz
cd ta-lib/
./configure --prefix=/usr
make
sudo make install
cd ..
rm -rf ta-lib ta-lib-0.4.0-src.tar.gz

Windows:

pip install ta-lib

如果安装失败，从https://github.com/cgohlke/talib-build/releases下载对应版本的.whl文件，然后执行以下命令安装：

bash

pip install TA_Lib-0.4.32-cp312-cp312-win_amd64.whl

Step 4: Install Python Packages

步骤4：安装Python包

Install all required packages (latest versions):

bash

pip install openalgo vectorbt plotly anywidget nbformat ta-lib pandas numpy yfinance python-dotenv tqdm scipy numba nbformat ipywidgets quantstats ccxt

安装所有所需的最新版本依赖包：

bash

pip install openalgo vectorbt plotly anywidget nbformat ta-lib pandas numpy yfinance python-dotenv tqdm scipy numba nbformat ipywidgets quantstats ccxt

Step 5: Create Backtesting Folder

步骤5：创建回测文件夹

Create only the top-level backtesting directory. Strategy subfolders are created on-demand when a backtest script is generated (by the

/backtest

skill).

bash

mkdir -p backtesting

Do NOT pre-create strategy subfolders.

仅创建顶层回测目录，策略子文件夹会在生成回测脚本时（由

/backtest

skill）按需创建。

bash

mkdir -p backtesting

不要预先创建策略子文件夹。

Step 6: Configure .env File

步骤6：配置.env文件

6a. Check if
.env.sample
exists at the project root. If it does, use it as a template.

6b. Ask the user which markets they will be backtesting using AskUserQuestion:

Indian Markets (OpenAlgo) — requires OpenAlgo API key
US Markets (yfinance) — no API key needed
Crypto Markets (Binance/CCXT) — optional API key for private data

6c. If the user selected Indian Markets, ask for their OpenAlgo API key:

Ask: "Enter your OpenAlgo API key (from the OpenAlgo dashboard):"
If the user provides a key, store it in
```
.env
```
If the user skips, write a placeholder

6d. If the user selected Crypto Markets, ask if they want to configure Binance API keys:

Ask: "Do you have Binance API keys for authenticated data? (Optional — public OHLCV data works without keys)"
If yes, ask for API key and secret key, store in
```
.env
```
If no, leave them blank in
```
.env
```

6e. Write the
.env
file in the project root directory. Use this template, filling in any keys the user provided:

undefined

6a. 检查项目根目录是否存在
.env.sample
，如果存在则以此为模板。

6b. 向用户询问要回测的市场类型，使用AskUserQuestion功能：

印度市场（OpenAlgo）—— 需要OpenAlgo API密钥
美国市场（yfinance）—— 无需API密钥
加密货币市场（Binance/CCXT）—— 私有数据需要可选的API密钥

6c. 如果用户选择了印度市场，询问其OpenAlgo API密钥：

询问内容："请输入你的OpenAlgo API密钥（可从OpenAlgo控制台获取）："
如果用户提供了密钥，将其存入
```
.env
```
文件
如果用户跳过，写入占位符即可

6d. 如果用户选择了加密货币市场，询问是否要配置Binance API密钥：

询问内容："你是否有Binance API密钥用于获取认证数据？（可选 —— 公开OHLCV数据无需密钥即可使用）"
如果选择是，询问API密钥和密钥对，存入
```
.env
```
文件
如果选择否，在
```
.env
```
中留空即可

6e. 写入
.env
文件到项目根目录，使用以下模板，填充用户提供的所有密钥：

undefined

Indian Markets (OpenAlgo)

OPENALGO_API_KEY={user_provided_key or "your_openalgo_api_key_here"} OPENALGO_HOST=http://127.0.0.1:5000

Crypto Markets (Binance via CCXT) - Optional

BINANCE_API_KEY={user_provided_key or ""} BINANCE_SECRET_KEY={user_provided_key or ""}


**6f. Add `.env` to `.gitignore`** if it exists (never commit secrets):

Scripts use `find_dotenv()` to automatically walk up and find the single root `.env`, so no copies are needed in subdirectories.

```bash
grep -qxF '.env' .gitignore 2>/dev/null || echo '.env' >> .gitignore

BINANCE_API_KEY={user_provided_key or ""} BINANCE_SECRET_KEY={user_provided_key or ""}


**6f. 如果存在`.gitignore`文件，将`.env`添加到其中**（永远不要提交密钥）：

脚本会使用`find_dotenv()`自动向上遍历查找根目录的唯一`.env`文件，因此不需要在子目录中复制该文件。

```bash
grep -qxF '.env' .gitignore 2>/dev/null || echo '.env' >> .gitignore

Step 7: Verify Installation

步骤7：验证安装

Run a quick verification:

bash

python -c "
import vectorbt as vbt
import openalgo
import plotly
import talib
import anywidget
import nbformat
import quantstats as qs
from dotenv import load_dotenv
print('All packages installed successfully')
print(f'  vectorbt: {vbt.__version__}')
print(f'  plotly: {plotly.__version__}')
print(f'  nbformat: {nbformat.__version__}')
print(f'  quantstats: {qs.__version__}')
print(f'  TA-Lib: available')
print(f'  python-dotenv: available')
"

If TA-Lib import fails, inform the user that the C library needs to be installed first (see Step 3).

运行快速验证命令：

bash

python -c "
import vectorbt as vbt
import openalgo
import plotly
import talib
import anywidget
import nbformat
import quantstats as qs
from dotenv import load_dotenv
print('All packages installed successfully')
print(f'  vectorbt: {vbt.__version__}')
print(f'  plotly: {plotly.__version__}')
print(f'  nbformat: {nbformat.__version__}')
print(f'  quantstats: {qs.__version__}')
print(f'  TA-Lib: available')
print(f'  python-dotenv: available')
"

如果TA-Lib导入失败，告知用户需要先安装C语言库（参见步骤3）。

Step 8: Print Summary

步骤8：输出汇总信息

Print a summary showing:

Detected OS
Python version used
Virtual environment path
Installed packages and versions
Backtesting folder created (strategy subfolders created on-demand by
```
/backtest
```
)
```
.env
```
file status (configured with keys / placeholder) — single file at project root
Reminder: "Run
```
cp .env.sample .env
```
and fill in API keys if you skipped configuration"

输出汇总信息，包含以下内容：

检测到的操作系统
使用的Python版本
虚拟环境路径
已安装的包及版本
回测文件夹创建情况（策略子文件夹由
```
/backtest
```
按需创建）
```
.env
```
文件状态（已配置密钥/占位符）—— 仅根目录下的单个文件
提示："如果你跳过了配置，请运行
```
cp .env.sample .env
```
并填写API密钥"

Important Notes

重要注意事项

Never install packages globally — always use the virtual environment
TA-Lib C library installation requires admin/sudo privileges on Linux
On macOS, Homebrew must be installed for
```
brew install ta-lib
```
If the user already has a virtual environment, ask before creating a new one
The backtesting/ folder is where all generated backtest scripts will be saved
NEVER commit
```
.env
```
files — they contain secrets. Always use
```
.gitignore
```
.
If the user provides an API key during setup, write it directly to
```
.env
```
— do not ask them to edit the file manually
```
python-dotenv
```
is included in the pip install and must be used by all scripts to load
```
.env
```

永远不要全局安装包 —— 始终使用虚拟环境
在Linux上安装TA-Lib C语言库需要admin/sudo权限
在macOS上，必须先安装Homebrew才能执行
```
brew install ta-lib
```
如果用户已经有虚拟环境，创建新环境前先询问用户
```
backtesting/
```
文件夹是所有生成的回测脚本的保存位置
永远不要提交
```
.env
```
文件 —— 其中包含密钥，始终要将其加入
```
.gitignore
```
。
如果用户在设置过程中提供了API密钥，直接写入
```
.env
```
—— 不要要求用户手动编辑文件
```
python-dotenv
```
已包含在pip安装列表中，所有脚本必须使用它来加载
```
.env
```
配置