2026-04-14  11.17
2026-04-15  11.21
2026-04-16  11.09
2026-04-17  11.01
2026-04-20  11.06

# ── 通过 MCP 工具调用（Claude Code 内）─────────────
# market=1(上海), code=999999(上证综指), period=7(1分钟)
# times=3 → 约2400根（约10个交易日），不传count/start（有bug）
mcp__tdx__stock_kline(market=1, code="999999", period=7, times=3)

# 其他常用大盘指数：
# 399001 market=0  深证成指
# 399006 market=0  创业板指
# 000300 market=1  沪深300

import sys
sys.path.insert(0, '/c/Users/cxu/.claude/mcp-servers/tdx_mcp')
from opentdx.client.quotationClient import QuotationClient
from opentdx.const import MARKET, PERIOD, ADJUST

client = QuotationClient(auto_retry=True)
client.login()

# 大盘1分钟K，最近2400根（约10交易日），含今日实时
bars = client.get_kline(
    market=MARKET.SH,
    code='999999',
    period=PERIOD.MIN_1,   # =7
    count=2400,
    adjust=ADJUST.NONE
)
# bars: list[dict]，每条含 datetime/open/high/low/close/vol/amount/turnover
# 大盘额外含 up_count/down_count（涨跌家数）

# 转 DataFrame
import pandas as pd
df = pd.DataFrame(bars)
df['datetime'] = pd.to_datetime(df['datetime'])
df.set_index('datetime', inplace=True)
print(df.tail(5))

datetime               open      close     high      low       vol          up_count  down_count
2026-04-21 13:58:00    4081.35   4081.30   4081.64   4080.71   22184946     829       1456
2026-04-21 13:59:00    4081.22   4079.78   4081.23   4079.22   26172890     805       1485
2026-04-21 14:00:00    4079.81   4078.92   4080.04   4078.92   26238444     792       1500

import sys
sys.path.insert(0, 'C:/new_tdx64/PYPlugins/user')
from tqcenter import tq

tq.initialize(__file__)  # 需要通达信终端在后台运行

# ── 日线（000001.SZ 最近60天）──────────────────────
d = tq.get_market_data(
    field_list=[],            # 空=返回全部字段
    stock_list=['000001.SZ'],
    period='1d',
    start_time='20260101',
    end_time='20260421',
    count=-1,                 # -1=返回区间全部数据
    dividend_type='front',    # 前复权
    fill_data=False
)
# 返回结构：dict，key=字段名，value=DataFrame(index=Timestamp日期, columns=[股票代码])
close_df = d['Close']           # shape=(N, 1)
print(close_df.tail(5))

# ── 1分钟线（多股票批量）──────────────────────────
d1m = tq.get_market_data(
    field_list=['Open', 'High', 'Low', 'Close', 'Volume'],
    stock_list=['000001.SZ', '600519.SH'],
    period='1m',
    start_time='20260420',
    end_time='20260421',
    count=-1,
    dividend_type='none',
    fill_data=False
)
# 取平安银行1分钟收盘价
close_1m = d1m['Close']['000001.SZ']
print(close_1m.tail(10))

# ── 实时快照（盘中使用）───────────────────────────
snap = tq.get_market_snapshot(stock_code='000001.SZ', field_list=[])
print(f"现价={snap['Now']}  最高={snap['Max']}  最低={snap['Min']}")
print(f"买一: {snap['Buyp'][0]} × {snap['Buyv'][0]}手")
print(f"卖一: {snap['Sellp'][0]} × {snap['Sellv'][0]}手")

# ── 实时 Tick 订阅（仅盘中，无历史）──────────────
def on_tick(datas):
    for code, data in datas.items():
        print(f"[TICK] {code} 现价={data.get('lastPrice')} 成交量={data.get('volume')}")

tq.subscribe_hq(stock_list=['000001.SZ'], callback=on_tick)
# 注意：subscribe_hq 是异步回调，需在事件循环中保持运行

import sys
sys.path.insert(0, 'D:/workspace2/bs-point')
from xtquant import xtdata

# miniQMT 无需显式登录，自动连接已运行的 QMT 客户端

# ── 日线（下载 + 读取）────────────────────────────
code = '000001.SZ'
xtdata.download_history_data(code, period='1d',
                             start_time='20200101', end_time='20260421')

d = xtdata.get_market_data(
    field_list=['time', 'open', 'high', 'low', 'close', 'volume'],
    stock_list=[code],
    period='1d',
    start_time='20200101',
    end_time='20260421',
    count=-1,
    dividend_type='none',
    fill_data=True
)
# 返回结构：dict，key=字段名，value=DataFrame(index=[stock_code], columns=时间戳)
close = d['close'].loc[code]   # Series，index=时间戳(int)
print(f"条数={len(close)}  最早={close.index[0]}  最新={close.index[-1]}")

# ── 1分钟线（下载 + 读取）────────────────────────
xtdata.download_history_data(code, period='1m',
                             start_time='20260401', end_time='20260421')

d1m = xtdata.get_market_data(
    field_list=['open', 'high', 'low', 'close', 'volume'],
    stock_list=[code],
    period='1m',
    start_time='20260401',
    end_time='20260421',
    count=-1,
    dividend_type='none',
    fill_data=False
)
close_1m = d1m['close'].loc[code]
print(close_1m.tail(5))

# ── Tick 历史（下载 + 读取）──────────────────────
xtdata.download_history_data(code, period='tick',
                             start_time='20260320', end_time='20260421')

d_tick = xtdata.get_local_data(
    field_list=[],
    stock_list=[code],
    period='tick',
    start_time='20260320',
    end_time='20260421',
    count=-1
)
df_tick = d_tick[code]   # DataFrame，index=时间字符串(YYYYMMDDHHmmss)
# 字段：time/lastPrice/open/high/low/lastClose/amount/volume/
#       askPrice(list)/bidPrice(list)/askVol(list)/bidVol(list) 等20字段
print(f"Tick条数={len(df_tick)}")
print(df_tick[['lastPrice','volume','askPrice','bidPrice']].tail(3))

# ── 实时 Tick 订阅──────────────────────────────
def on_tick(datas):
    for code, ticks in datas.items():
        for tick in ticks:
            print(f"[TICK] {code} 价={tick['lastPrice']} 量={tick['volume']}")

xtdata.subscribe_quote(code, period='tick', count=0, callback=on_tick)
xtdata.run()  # 阻塞，保持订阅