四大免费数据源代码实测

前两篇讲了为什么自建和技术选型。本文直接上代码，实测对比四个数据源。

1. 快速上手

python 复制代码

# === AKShare ===
pip install akshare
import akshare as ak
df = ak.stock_zh_a_hist(symbol='000001', period='daily', adjust='qfq')
# 返回：日期、开盘、收盘、最高、最低、成交量、成交额、振幅、涨跌幅、涨跌额、换手率

# === Tushare ===
pip install tushare
import tushare as ts
ts.set_token('your_token_here')
pro = ts.pro_api()
df = pro.daily(ts_code='000001.SZ', start_date='20240101', end_date='20241231')
# 返回：ts_code, trade_date, open, high, low, close, pre_close, change, pct_chg, vol, amount

# === yfinance ===
pip install yfinance
import yfinance as yf
df = yf.Ticker('000001.SZ').history(period='1y')
# 返回：Open, High, Low, Close, Volume, Dividends, Stock Splits

# === Baostock ===
pip install baostock
import baostock as bs
bs.login()
rs = bs.query_history_k_data_plus('sz.000001',
    'date,open,high,low,close,volume', start_date='2024-01-01', end_date='2024-12-31')
df = rs.get_data()
bs.logout()

2. 数据质量实测

以平安银行 000001 为样本，对比 2025-01-02 日线数据：

python 复制代码

import akshare as ak
import tushare as ts
import yfinance as yf
import baostock as bs

# 基准数据（东方财富网页端手工验证）
benchmark = {'open': 11.25, 'high': 11.42, 'low': 11.02, 'close': 11.38}

def test_accuracy(name, data):
    errors = {}
    for field in ['open', 'high', 'low', 'close']:
        diff = abs(data[field] - benchmark[field])
        errors[field] = f'{diff:.2f}'
    return errors

# AKShare
ak_df = ak.stock_zh_a_hist(symbol='000001', period='daily', start_date='20250102', end_date='20250102')
ak_data = {'open': ak_df['开盘'].iloc[0], 'high': ak_df['最高'].iloc[0],
           'low': ak_df['最低'].iloc[0], 'close': ak_df['收盘'].iloc[0]}
print('AKShare:', test_accuracy('AKShare', ak_data))
# 输出：误差全为 0.00

# yfinance
yf_df = yf.Ticker('000001.SZ').history(start='2025-01-02', end='2025-01-03')
yf_data = {'open': yf_df['Open'].iloc[0], 'high': yf_df['High'].iloc[0],
           'low': yf_df['Low'].iloc[0], 'close': yf_df['Close'].iloc[0]}
print('yfinance:', test_accuracy('yfinance', yf_data))
# 输出：±0.01-0.02 偏差（Yahoo 使用自有数据源）

结论：AKShare、Tushare、Baostock 与东方财富一致。yfinance 有 ±0.01 的系统偏差。

3. 更新时效

python 复制代码

from datetime import datetime
import akshare as ak

# 检测当日数据是否已更新
today = datetime.now().strftime('%Y%m%d')
df = ak.stock_zh_a_hist(symbol='000001', period='daily', start_date=today, end_date=today)

if len(df) > 0:
    print(f'✅ {today} 日线已更新')
else:
    print(f'⏳ {today} 日线尚未更新（通常在15:30后）')

数据源	当日可用时间	盘中数据
AKShare	15:30	✅ 有实时接口
Tushare	16:00+	❌ 免费版
yfinance	18:00+	❌
Baostock	次日上午	❌

4. AKShare 防封 IP 方案

python 复制代码

import time
import random
import akshare as ak
import psycopg2
from datetime import datetime, timedelta

def safe_fetch(symbol, max_retries=3):
    """带退避重试的安全拉取"""
    for attempt in range(max_retries):
        try:
            df = ak.stock_zh_a_hist(
                symbol=symbol, period='daily',
                start_date='20200101', end_date=datetime.now().strftime('%Y%m%d'),
                adjust='qfq'  # 前复权
            )
            return df
        except Exception as e:
            wait = random.uniform(3, 8) * (attempt + 1)
            print(f'⚠️ {symbol} 失败 (attempt {attempt+1}): {e}')
            print(f'   等待 {wait:.0f} 秒重试...')
            time.sleep(wait)
    print(f'❌ {symbol} 3次重试全部失败，跳过')
    return None

def fetch_all_with_throttle(stock_list):
    """全量拉取 + 限速 + 本地缓存"""
    conn = psycopg2.connect('postgresql://trader:xxx@localhost:5432/quant')
    cur = conn.cursor()

    for i, symbol in enumerate(stock_list):
        # 1. 检查本地是否已有今日数据
        cur.execute("""
            SELECT 1 FROM kline_daily
            WHERE symbol = %s AND trade_date = CURRENT_DATE
        """, (symbol,))

        if cur.fetchone():
            print(f'[{i+1}/{len(stock_list)}] {symbol} ✅ 已有今日数据，跳过')
            continue

        # 2. 拉取 + 入库
        df = safe_fetch(symbol)
        if df is not None:
            for _, row in df.iterrows():
                cur.execute("""
                    INSERT INTO kline_daily (symbol, trade_date, open, high, low, close, volume)
                    VALUES (%s, %s, %s, %s, %s, %s, %s)
                    ON CONFLICT (symbol, trade_date) DO UPDATE SET
                        open=EXCLUDED.open, high=EXCLUDED.high, low=EXCLUDED.low,
                        close=EXCLUDED.close, volume=EXCLUDED.volume
                """, (symbol, row['日期'], row['开盘'], row['最高'], row['最低'], row['收盘'], row['成交量']))

            conn.commit()
            print(f'[{i+1}/{len(stock_list)}] {symbol} ✅ 拉取成功')

        # 3. 限速：随机间隔 0.5-1.5 秒
        time.sleep(random.uniform(0.5, 1.5))

    cur.close()
    conn.close()
    print('🎉 全量拉取完成')

# 使用
stock_list = ['000001', '000002', '000333', '600519', '601318']  # 示例
fetch_all_with_throttle(stock_list)

5. yfinance 美股 + A 股混用

python 复制代码

import yfinance as yf

# 美股
aapl = yf.Ticker('AAPL')
print(f"AAPL 市值: ${aapl.info['marketCap']:,}")
print(f"AAPL PE: {aapl.info['trailingPE']:.1f}")

# A 股（深交所 .SZ，上交所 .SS）
midea = yf.Ticker('000333.SZ')
print(f"\n美的集团最新价: ¥{midea.history(period='1d')['Close'].iloc[-1]:.2f}")

# 港股
tencent = yf.Ticker('0700.HK')
print(f"腾讯最新价: HK${tencent.history(period='1d')['Close'].iloc[-1]:.2f}")

# 加密货币
btc = yf.Ticker('BTC-USD')
print(f"比特币: ${btc.history(period='1d')['Close'].iloc[-1]:,.0f}")

6. 综合评分

	AKShare	Tushare	yfinance	Baostock
数据覆盖	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐	⭐⭐
A股质量	⭐⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐	⭐⭐⭐⭐
稳定性	⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐
入门门槛	不用注册	要实名	不用注册	不用注册
代码量	中	中	少	少

7. 我的推荐

python 复制代码

# 生产环境（A股）：Tushare 主力 + AKShare 补充
import tushare as ts  # 日线、复权、财务
import akshare as ak   # 资金流向、龙虎榜

# 美股：yfinance 一把梭
import yfinance as yf  # 全搞定

# 新手入门：AKShare + yfinance
import akshare as ak   # A股
import yfinance as yf  # 美股 + 全球
# 两个都不用注册，5分钟跑起来