股票信息 API

获取股票的基本信息，包括公司名称、所属行业、市场等。

端点

方法	端点
GET	/ticker_info

在线试用

GET/ticker_info

API Key

Parameters

symbol

Try It

请求参数

参数	类型	必填	说明
symbol	string	✅	股票代码 (如 000001.SZ, 002415.SZ)

代码示例

Python

import requests

API_KEY = "your_api_key"

response = requests.get(
    "https://tickerlab.org/ticker_info",
    params={"symbol": "000001.SZ"},
    headers={"X-API-Key": API_KEY}
)

info = response.json()
print(f"名称: {info.get('name')}")
print(f"行业: {info.get('industry')}")
print(f"市场: {info.get('market')}")

JavaScript

const response = await fetch(
  'https://tickerlab.org/ticker_info?symbol=000001.SZ',
  { headers: { 'X-API-Key': 'your_api_key' } }
);

const info = await response.json();
console.log(`${info.name} - ${info.industry}`);

cURL

curl "https://tickerlab.org/ticker_info?symbol=000001.SZ" \
  -H "X-API-Key: your_api_key"

响应示例

{
  "code": "000001",
  "name": "平安银行",
  "market": "SZ",
  "industry": "银行",
  "list_date": "1991-04-03",
  "total_share": 19405918198,
  "float_share": 19380084397,
  "pe_ratio": 5.23,
  "pb_ratio": 0.58
}

字段说明

字段	说明
code	股票代码 (6位)
name	股票名称
market	市场 (SZ/SH)
industry	所属行业
list_date	上市日期
total_share	总股本
float_share	流通股本
pe_ratio	市盈率
pb_ratio	市净率

---

完整示例：构建股票分析工具

以下是一个完整的 Python 示例，展示如何组合使用多个 API：

import requests
import pandas as pd
import matplotlib.pyplot as plt

class StockAnalyzer:
    def __init__(self, api_key, base_url="https://tickerlab.org"):
        self.api_key = api_key
        self.base_url = base_url
        self.headers = {"X-API-Key": api_key}
    
    def get_info(self, symbol):
        """获取股票基本信息"""
        r = requests.get(
            f"{self.base_url}/ticker_info",
            params={"symbol": symbol},
            headers=self.headers
        )
        return r.json()
    
    def get_kline(self, symbol, days=60):
        """获取 K 线数据"""
        r = requests.get(
            f"{self.base_url}/v1/indicators/time_series",
            params={"symbol": symbol, "outputsize": days},
            headers=self.headers
        )
        data = r.json()
        df = pd.DataFrame(data["values"])
        df["datetime"] = pd.to_datetime(df["datetime"])
        for col in ["open", "high", "low", "close"]:
            df[col] = df[col].astype(float)
        return df
    
    def get_indicators(self, symbol):
        """获取技术指标"""
        indicators = {}
        
        # RSI
        r = requests.get(
            f"{self.base_url}/v1/indicators/rsi",
            params={"symbol": symbol},
            headers=self.headers
        )
        indicators["rsi"] = float(r.json()["values"][0]["rsi"])
        
        # MACD
        r = requests.get(
            f"{self.base_url}/v1/indicators/macd",
            params={"symbol": symbol},
            headers=self.headers
        )
        macd_data = r.json()["values"][0]
        indicators["macd"] = float(macd_data["macd"])
        indicators["macd_signal"] = float(macd_data["macd_signal"])
        
        return indicators
    
    def analyze(self, symbol):
        """综合分析"""
        info = self.get_info(symbol)
        kline = self.get_kline(symbol)
        indicators = self.get_indicators(symbol)
        
        print(f"=== {info['name']} ({symbol}) ===")
        print(f"行业: {info.get('industry', 'N/A')}")
        print(f"最新价: {kline['close'].iloc[0]:.2f}")
        print(f"RSI: {indicators['rsi']:.2f}")
        print(f"MACD: {indicators['macd']:.4f}")
        
        # 简单信号判断
        if indicators["rsi"] > 70:
            print("⚠️ RSI 超买")
        elif indicators["rsi"] < 30:
            print("📈 RSI 超卖")
        
        return {"info": info, "kline": kline, "indicators": indicators}

# 使用示例
analyzer = StockAnalyzer("your_api_key")
result = analyzer.analyze("000001.SZ")