indicator-setup

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Set up the complete Python environment for OpenAlgo indicator analysis, charting, and dashboard development.

为OpenAlgo指标分析、图表绘制和仪表盘开发搭建完整的Python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

bash

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

Map:

Darwin

= macOS,

Linux

= Linux,

MINGW*

CYGWIN*

Windows

= Windows.

bash

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

对应关系：

Darwin

= macOS，

Linux

= Linux，

MINGW*

CYGWIN*

Windows

= Windows。

Step 2: Create Virtual Environment

步骤2：创建虚拟环境

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

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

python3

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，则使用该版本而非

python3

。

Step 3: Install Python Packages

步骤3：安装Python包

Install all required packages:

bash

pip install openalgo yfinance plotly dash dash-bootstrap-components streamlit numba numpy pandas python-dotenv websocket-client httpx scipy nbformat matplotlib seaborn ipywidgets

安装所有必需的包：

bash

pip install openalgo yfinance plotly dash dash-bootstrap-components streamlit numba numpy pandas python-dotenv websocket-client httpx scipy nbformat matplotlib seaborn ipywidgets

Step 4: Create Project Folders

步骤4：创建项目文件夹

Create only the top-level directories. Subdirectories are created on-demand by other skills.

bash

mkdir -p charts dashboards custom_indicators scanners

仅创建顶层目录。子目录将由其他技能根据需求自动创建。

bash

mkdir -p charts dashboards custom_indicators scanners

Step 5: Configure .env File

步骤5：配置.env文件

5a. Ask the user for their OpenAlgo API key using AskUserQuestion:

"Enter your OpenAlgo API key (from the OpenAlgo dashboard at /apikey):"

5b. Ask for the OpenAlgo host URL:

Default:
```
http://127.0.0.1:5000
```
If user has a custom domain or ngrok URL, use that

5c. Optionally ask about WebSocket URL:

Default: derived from host automatically
Only needed if user has a custom WebSocket setup

5d. Write the
.env
file in the project root:

undefined

5a. 使用AskUserQuestion向用户询问他们的OpenAlgo API密钥：

"请输入你的OpenAlgo API密钥（可从OpenAlgo仪表盘的/apikey页面获取）："

5b. 询问OpenAlgo主机URL：

默认值：
```
http://127.0.0.1:5000
```
如果用户有自定义域名或ngrok URL，请使用该地址

5c. 可选：询问WebSocket URL：

默认值：自动从主机地址推导
仅当用户有自定义WebSocket配置时需要

5d. 在项目根目录写入
.env
文件：

undefined

OpenAlgo API Configuration

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

WebSocket (optional - auto-derived from host if not set)

OPENALGO_WS_URL=ws://127.0.0.1:8765


**5e. Add `.env` to `.gitignore`:**

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


**5e. 将`.env`添加到`.gitignore`：**

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

Step 6: Verify Installation

步骤6：验证安装

bash

python -c "
import openalgo
from openalgo import ta
import plotly
import dash
import streamlit
import numba
import numpy as np
import pandas as pd
import yfinance as yf
import matplotlib
import seaborn
import nbformat
from dotenv import load_dotenv
print('All packages installed successfully')
print(f'  openalgo: {openalgo.__version__}')
print(f'  plotly: {plotly.__version__}')
print(f'  dash: {dash.__version__}')
print(f'  streamlit: {streamlit.__version__}')
print(f'  numba: {numba.__version__}')
print(f'  numpy: {np.__version__}')
print(f'  pandas: {pd.__version__}')
print(f'  matplotlib: {matplotlib.__version__}')
print(f'  seaborn: {seaborn.__version__}')

bash

python -c "
import openalgo
from openalgo import ta
import plotly
import dash
import streamlit
import numba
import numpy as np
import pandas as pd
import yfinance as yf
import matplotlib
import seaborn
import nbformat
from dotenv import load_dotenv
print('All packages installed successfully')
print(f'  openalgo: {openalgo.__version__}')
print(f'  plotly: {plotly.__version__}')
print(f'  dash: {dash.__version__}')
print(f'  streamlit: {streamlit.__version__}')
print(f'  numba: {numba.__version__}')
print(f'  numpy: {np.__version__}')
print(f'  pandas: {pd.__version__}')
print(f'  matplotlib: {matplotlib.__version__}')
print(f'  seaborn: {seaborn.__version__}')

Quick indicator test

close = np.array([100.0, 101.0, 102.0, 103.0, 104.0, 105.0, 104.0, 103.0, 102.0, 101.0]) ema = ta.ema(close, 3) rsi = ta.rsi(close, 5) print(f' ta.ema test: {ema[-1]:.2f}') print(f' ta.rsi test: {rsi[-1]:.2f}') print('Indicator library ready') "

undefined

undefined

Step 7: Print Summary

步骤7：打印总结

Print a summary showing:

Detected OS
Python version used
Virtual environment path
Installed packages and versions
Project folders created
```
.env
```
file status

Available skills:

/indicator-chart

/custom-indicator

/indicator-dashboard

/indicator-scanner

/live-feed

打印包含以下内容的总结：

检测到的操作系统
使用的Python版本
虚拟环境路径
已安装的包及其版本
创建的项目文件夹
```
.env
```
文件状态

可用技能：

/indicator-chart

、

/custom-indicator

、

/indicator-dashboard

、

/indicator-scanner

、

/live-feed

Important Notes

重要说明

Never install packages globally — always use the virtual environment
If the user already has a virtual environment, ask before creating a new one
NEVER commit
```
.env
```
files — they contain API keys
```
python-dotenv
```
is used by all scripts to load
```
.env
```
via
```
find_dotenv()
```
The openalgo library includes Numba-optimized indicators that compile on first use

切勿全局安装包——始终使用虚拟环境
如果用户已存在虚拟环境，创建新环境前请先询问用户
绝对不要提交
```
.env
```
文件——它们包含API密钥
所有脚本通过
```
find_dotenv()
```
使用
```
python-dotenv
```
加载
```
.env
```
文件
openalgo库包含经Numba优化的指标，首次使用时会进行编译