使用 OpenBB 构建开源金融数据平台：替代商业 API 的完整指南

# 安装 venv 模块（需要 sudo）
sudo apt install python3.13-venv

# 创建虚拟环境
python3 -m venv ~/.openclaw/openbb-env

# 激活虚拟环境
source ~/.openclaw/openbb-env/bin/activate

# 升级 pip
pip install --upgrade pip

# 安装 OpenBB 完整版（包含所有扩展）
pip install "openbb[all]"

python3 -c "from openbb import obb; print('✅ OpenBB 安装成功')"

vim ~/.openclaw/openbb-env/bin/activate

# OpenBB API Keys
export FRED_API_KEY="your_fred_key_here"
export AV_API_KEY="your_alpha_vantage_key_here"

#!/usr/bin/env python3
import sys
sys.path.insert(0, '/home/warwick/.openclaw/openbb-env/lib/python3.13/site-packages')

from openbb import obb

# 获取苹果股票历史数据
output = obb.equity.price.historical('AAPL', provider='yfinance', limit=30)
df = output.to_dataframe()

# 查看最新数据
latest = df.iloc[-1]
print(f"当前价格: ${latest['close']:.2f}")
print(f"成交量: {int(latest['volume']):,}")

from openbb import obb

# 获取比特币数据
output = obb.crypto.price.historical('BTC-USD', provider='yfinance', limit=30)
df = output.to_dataframe()

latest = df.iloc[-1]
print(f"BTC 当前价格: ${latest['close']:,.2f}")

from openbb import obb

# 获取英国 GDP
try:
    output = obb.economy.gdp(country='united_kingdom', provider='oecd')
    df = output.to_dataframe()
    print(df.tail(5))
except Exception as e:
    print(f"GDP 数据获取失败: {e}")

# 获取失业率
try:
    output = obb.economy.unemployment(country='united_kingdom')
    df = output.to_dataframe()
    print(df.tail(5))
except Exception as e:
    print(f"失业率数据获取失败: {e}")

#!/usr/bin/env python3
"""OpenBB 股票分析脚本 - 替代 TwelveData"""

import sys
sys.path.insert(0, '/home/warwick/.openclaw/openbb-env/lib/python3.13/site-packages')

import os
from datetime import datetime, timedelta
from openbb import obb

# 股票列表
STOCKS = ['MSFT', 'TSM', 'CRCL']

def calculate_rsi(prices, period=14):
    """计算 RSI 指标"""
    if len(prices) < period + 1:
        return 50
    
    deltas = [prices[i] - prices[i-1] for i in range(1, len(prices))]
    gains = [d if d > 0 else 0 for d in deltas[-period:]]
    losses = [-d if d < 0 else 0 for d in deltas[-period:]]
    
    avg_gain = sum(gains) / period
    avg_loss = sum(losses) / period
    
    if avg_loss == 0:
        return 100
    
    rs = avg_gain / avg_loss
    rsi = 100 - (100 / (1 + rs))
    return rsi

def calculate_ma(prices, period):
    """计算移动平均线"""
    if len(prices) < period:
        return prices[-1]
    return sum(prices[-period:]) / period

def get_stock_analysis(symbol):
    """获取完整股票分析"""
    try:
        # 获取30天历史数据
        output = obb.equity.price.historical(symbol, provider='yfinance', limit=35)
        df = output.to_dataframe()
        
        if df.empty:
            return None
        
        # 最新数据
        latest = df.iloc[-1]
        prev = df.iloc[-2]
        
        # 价格数据
        current = latest['close']
        change = current - prev['close']
        change_pct = (change / prev['close']) * 100
        volume = int(latest['volume'])
        
        # 30天统计
        high_30 = df['high'].max()
        low_30 = df['low'].min()
        prices = df['close'].tolist()
        
        # 技术指标
        rsi = calculate_rsi(prices)
        ma20 = calculate_ma(prices, 20)
        
        # 趋势判断
        if current > ma20:
            trend = "📈 上升趋势"
        elif current < ma20:
            trend = "📉 下降趋势"
        else:
            trend = "➡️ 横盘整理"
        
        # RSI 判断
        if rsi > 70:
            rsi_signal = "⚠️ 超买"
        elif rsi < 30:
            rsi_signal = "💡 超卖"
        else:
            rsi_signal = "📊 正常"
        
        # 52周位置（用30天数据估算）
        week52_position = ((current - low_30) / (high_30 - low_30)) * 100 if high_30 != low_30 else 50
        
        return {
            'symbol': symbol,
            'current': current,
            'change': change,
            'change_pct': change_pct,
            'volume': volume,
            'high_30': high_30,
            'low_30': low_30,
            'rsi': rsi,
            'rsi_signal': rsi_signal,
            'ma20': ma20,
            'trend': trend,
            'week52_position': week52_position
        }
        
    except Exception as e:
        print(f"❌ {symbol} 错误: {str(e)[:50]}", file=sys.stderr)
        return None

def main():
    """主函数"""
    print("📊 **股票技术分析报告** - {} ({})\n".format(
        datetime.now().strftime('%Y-%m-%d'),
        ['周一','周二','周三','周四','周五','周六','周日'][datetime.now().weekday()]
    ))
    
    for symbol in STOCKS:
        data = get_stock_analysis(symbol)
        if data:
            # 格式化输出
            emoji = "🟢" if data['change'] >= 0 else "🔴"
            print(f"{emoji} **{data['symbol']}**")
            print(f"   当前: ${data['current']:.2f} ({data['change']:+.2f}, {data['change_pct']:+.2f}%)")
            print(f"   成交量: {data['volume']:,}")
            print(f"   趋势: {data['trend']}")
            print(f"   RSI(14): {data['rsi']:.1f} {data['rsi_signal']}")
            print(f"   MA20: ${data['ma20']:.2f}")
            print(f"   30天区间: ${data['low_30']:.2f} - ${data['high_30']:.2f}")
            print(f"   区间位置: {data['week52_position']:.1f}%")
            print()
    
    print("💡 数据来源: OpenBB (yfinance)")
    print("⚠️ 仅供参考，不构成投资建议")

if __name__ == '__main__':
    main()

{
  "id": "your-job-id-here",
  "name": "每日股票分析-8:30",
  "enabled": true,
  "schedule": {
    "kind": "cron",
    "expr": "0 30 8 * * 2-6",
    "tz": "Asia/Shanghai"
  },
  "payload": {
    "kind": "agentTurn",
    "message": "执行脚本：python3 ~/.openclaw/workspace/openbb_stock_analysis.py。将脚本输出作为你的回复内容直接发送，不要添加任何额外解释。"
  },
  "delivery": {
    "mode": "announce",
    "to": "discord:YOUR_CHANNEL_ID"
  }
}

from openbb import obb
import pandas as pd

# 获取多只股票数据构建投资组合
symbols = ['AAPL', 'MSFT', 'GOOGL']
data = {}
for sym in symbols:
    output = obb.equity.price.historical(sym, limit=252)  # 一年数据
    data[sym] = output.to_dataframe()['close']

# 计算相关性矩阵
df = pd.DataFrame(data)
correlation = df.corr()
print(correlation)

pip install openbb-fred        # FRED 数据源
pip install openbb-polygon     # Polygon.io 数据源