Tushare Pro 金融数据助手#

功能特性#

• 股票行情查询（自动重试机制）
• 基础财务数据
• 宏观经济数据
• 全量 220+ 接口
• 自动财务报表
• DCF 估值模型
• 行业对比分析
• 定时数据推送
• 智能错误处理
• Token 验证

快速开始#

bash

pip install tushare pandas
export TUSHARE_TOKEN="your_token"

股票行情#

python

import tushare as ts

pro = ts.pro_api()

# 日线行情
df = pro.daily(ts_code='000001.SZ', start_date='20240101', end_date='20241231')

# 周线行情
df = pro.weekly(ts_code='000001.SZ')

# 月线行情
df = pro.monthly(ts_code='000001.SZ')

基础财务#

python

# 财务指标
df = pro.fina_indicator(ts_code='000001.SZ')

# 利润表
df = pro.income(ts_code='000001.SZ')

# 资产负债表
df = pro.balancesheet(ts_code='000001.SZ')

# 现金流量表
df = pro.cashflow(ts_code='000001.SZ')

宏观经济#

python

# GDP
df = pro.gdp()

# CPI
df = pro.cpi()

# PMI
df = pro.pmi()

# 货币供应
df = pro.m2()

自动财务报表生成#

python

def generate_financial_report(ts_code):
    """生成完整财务报表"""
    report = {}

    # 基本信息
    info = pro.stock_basic(ts_code=ts_code, fields='ts_code,name,industry,market')
    report['info'] = info.iloc[0].to_dict()

    # 财务指标
    indicator = pro.fina_indicator(ts_code=ts_code, period='20231231')
    report['indicator'] = indicator.iloc[0].to_dict() if not indicator.empty else {}

    # 利润表
    income = pro.income(ts_code=ts_code, period='20231231')
    report['income'] = income.iloc[0].to_dict() if not income.empty else {}

    # 资产负债表
    balance = pro.balancesheet(ts_code=ts_code, period='20231231')
    report['balance'] = balance.iloc[0].to_dict() if not balance.empty else {}

    return report

DCF 估值模型#

python

def dcf_valuation(ts_code, growth_rate=0.15, wacc=0.1, terminal_growth=0.03):
    """DCF 估值模型"""
    # 获取历史财务数据
    income = pro.income(ts_code=ts_code)

    if income.empty:
        return None

    latest = income.iloc[0]
    base_revenue = latest.get('revenue', 0)
    net_margin = latest.get('net_profit', 0) / base_revenue if base_revenue > 0 else 0

    # 预测未来5年现金流
    cash_flows = []
    for year in range(1, 6):
        revenue = base_revenue * (1 + growth_rate) ** year
        net_profit = revenue * net_margin
        cash_flows.append(net_profit)

    # 计算终值
    terminal_value = cash_flows[-1] * (1 + terminal_growth) / (wacc - terminal_growth)

    # 折现
    pv_sum = sum(cf / (1 + wacc) ** i for i, cf in enumerate(cash_flows, 1))
    pv_terminal = terminal_value / (1 + wacc) ** 5

    total_value = pv_sum + pv_terminal

    return {
        'company_value': total_value,
        'cash_flows': cash_flows,
        'terminal_value': terminal_value,
        'assumptions': {
            'growth_rate': growth_rate,
            'wacc': wacc,
            'terminal_growth': terminal_growth,
            'net_margin': net_margin
        }
    }

行业对比分析#

python

def industry_comparison(industry, top_n=10):
    """行业对比分析"""
    # 获取行业股票列表
    stocks = pro.stock_basic(industry=industry, list_status='L',
                            fields='ts_code,name,market_cap')

    if stocks.empty:
        return None

    # 按市值排序
    stocks = stocks.sort_values('market_cap', ascending=False).head(top_n)

    results = []
    for _, stock in stocks.iterrows():
        try:
            indicator = pro.fina_indicator(ts_code=stock['ts_code'], period='20231231')
            if not indicator.empty:
                results.append({
                    'ts_code': stock['ts_code'],
                    'name': stock['name'],
                    'market_cap': stock['market_cap'],
                    'roe': indicator.iloc[0].get('roe', None),
                    'net_profit_margin': indicator.iloc[0].get('netprofit_margin', None),
                    'revenue_growth': indicator.iloc[0].get('or_yoy', None)
                })
        except:
            continue

    return pd.DataFrame(results)

定时数据推送#

在 OpenClaw 配置定时任务：

json

{
  "cron": {
    "jobs": [
      {
        "id": "daily-market",
        "schedule": "0 16 * * 1-5",
        "prompt": "生成今日A股市场日报",
        "channel": "feishu"
      },
      {
        "id": "weekly-report",
        "schedule": "0 9 * * 1",
        "prompt": "生成本周行业研究报告",
        "channel": "feishu"
      }
    ]
  }
}

接口速查表#

类别接口数常用接口股票数据39daily, weekly, monthly, stock_basic指数数据18index_daily, index_weight基金数据11fund_nav, fund_daily期货期权16fut_daily, opt_daily宏观经济10gdp, cpi, pmi, m2港股美股23hk_daily, us_daily债券数据16bond_daily, bond_cov

配置说明#

1. 注册 Tushare Pro: https://tushare.pro
2. 获取 API Token
3. 设置环境变量: export TUSHARE_TOKEN="your_token"

风险提示#

1. 数据来源: Tushare Pro，需遵守使用协议
2. 数据延迟: 部分数据有 15 分钟延迟
3. 投资风险: 数据仅供参考，不构成投资建议