通达信开源库pytdx使用例子

from pytdx.hq import TdxHq_API
from pytdx.util.best_ip import select_best_ip
import pandas as pd
def auto_get_best_ip_and_data():
    """
    自动选择最优服务器并获取股票数据的完整示例
    """
    # 1. 自动选择最佳行情服务器
    print("正在自动测试最优服务器...")
    try:
        best_ip_info = select_best_ip()
        best_ip = best_ip_info['ip']
        best_port = best_ip_info['port']
        print(f"✅ 找到最优服务器: {best_ip}:{best_port}")
    except Exception as e:
        print(f"❌ 自动选择最优服务器时发生错误: {e}")
        return None
    # 2. 创建API对象
    api = TdxHq_API()
    # 3. 连接服务器并获取数据
    try:
        with api.connect(best_ip, best_port):  # 使用with语句确保连接被正确关闭
            print("✅ 服务器连接成功!")
            # 示例1: 获取多只股票的实时行情
            stock_codes = [(1, '600519'), (0, '000001')]  # 沪市贵州茅台和深市平安银行
            quotes = api.get_security_quotes(stock_codes)
            df_quotes = api.to_df(quotes)
            # 简单处理一下数据，只保留一些重要字段
            important_columns = ['code', 'name', 'price', 'last_close', 'open', 'high', 'low', 'vol', 'amount']
            # 确保这些字段在DataFrame中存在
            existing_columns = [col for col in important_columns if col in df_quotes.columns]
            df_quotes_display = df_quotes[existing_columns]
            # 计算涨跌幅
            if 'price' in df_quotes.columns and 'last_close' in df_quotes.columns:
                df_quotes_display['change_percent'] = (df_quotes['price'] / df_quotes['last_close'] - 1) * 100
                df_quotes_display['change_percent'] = df_quotes_display['change_percent'].round(2)
            print("\n📊 实时行情数据:")
            print(df_quotes_display)
            # 示例2: 获取贵州茅台的日K线数据
            k_lines = api.get_security_bars(9, 1, '600519', 0, 10)  # 9表示日K线，1表示沪市，获取10条数据
            df_k_lines = api.to_df(k_lines)
            if not df_k_lines.empty:
                # 选择需要显示的列
                k_line_columns = ['datetime', 'open', 'close', 'high', 'low', 'vol']
                existing_k_line_columns = [col for col in k_line_columns if col in df_k_lines.columns]
                df_k_lines_display = df_k_lines[existing_k_line_columns]
                print("\n📈 贵州茅台日K线数据:")
                print(df_k_lines_display)
            return df_quotes_display, df_k_lines_display
    except Exception as e:
        print(f"❌ 在连接服务器或获取数据时发生错误: {e}")
        return None, None
if __name__ == "__main__":
    auto_get_best_ip_and_data()

from pytdx.reader import TdxDailyBarReader, TdxFileNotFoundException
reader = TdxDailyBarReader()
df = reader.get_df("D:/lwj/new_tdx/vipdoc/sz/lday/sz000001.day")

print(df)


from pytdx.reader import TdxLCMinBarReader, TdxFileNotFoundException

reader = TdxLCMinBarReader()
df = reader.get_df("D:/lwj/new_tdx/vipdoc/sz/minline/sz000001.lc1")
print(df)