获取日K线并计算均线
from quantdash import QuantDash
qd = QuantDash(api_key="your-api-key")
df = qd.klines.get("600519.SH", period="1d", count=120, to_dataframe=True)
df["ma5"] = df["close"].rolling(5).mean()
df["ma20"] = df["close"].rolling(20).mean()
print(df[["trade_date", "close", "ma5", "ma20"]].tail(5))
批量获取日K线（带进度条）
symbols = ["600519.SH", "000001.SZ", "601318.SH", "600036.SH", "000858.SZ"]
dfs = qd.klines.batch(symbols, period="1d", count=60, to_dataframe=True, show_progress=True)
# 汇总最新收盘价
import pandas as pd
latest = {sym: df["close"].iloc[-1] for sym, df in dfs.items()}
print(pd.Series(latest, name="close").sort_values(ascending=False))
600519.SH 1215.00
000858.SZ 75.85
601318.SH 49.38
600036.SH 37.26
000001.SZ 10.52
Name: close, dtype: float64
获取分钟K线
df = qd.klines.get("600519.SH", period="5m", count=5, to_dataframe=True)
print(df[["trade_time", "open", "high", "low", "close", "volume"]])
trade_time open high low close volume
2026-06-18 14:40:00 1214.44 1215.82 1212.26 1215.82 1151
2026-06-18 14:45:00 1215.02 1217.00 1215.00 1216.99 997
2026-06-18 14:50:00 1216.52 1217.39 1215.99 1217.38 827
2026-06-18 14:55:00 1217.40 1228.37 1217.40 1222.55 2355
2026-06-18 15:00:00 1223.02 1223.99 1215.00 1215.00 2324
全 A 股实时行情
# 支持标的池：CN_Stock / CN_ETF / US_Stock / HK_Stock
df = qd.quotes.get(universes=["CN_Stock"], to_dataframe=True)
print(df)
symbol region ... ext.amplitude ext.turnover_rate
0 920985.BJ CN ... 0.043893 0.015161
1 002414.SZ CN ... 0.027106 0.015167
2 600589.SH CN ... 0.047852 0.076141
3 688543.SH CN ... 0.043046 0.052545
4 300988.SZ CN ... 0.044633 0.043186
... ... ... ... ... ...
5496 002546.SZ CN ... 0.022026 0.014857
5497 920363.BJ CN ... 0.038917 0.027170
5498 688590.SH CN ... 0.033557 0.051160
5499 001317.SZ CN ... 0.053210 0.043987
5500 300731.SZ CN ... 0.080393 0.090136
[5501 rows x 18 columns]
按标的查询实时行情
df = qd.quotes.get(symbols=["600519.SH", "000001.SZ"], to_dataframe=True)
print(df[["symbol", "last_price", "prev_close", "volume", "ext.name", "ext.change_pct"]])
symbol last_price prev_close volume ext.name ext.change_pct
000001.SZ 10.52 10.78 1426893 平安银行 -0.024119
600519.SH 1215.00 1240.00 57472 贵州茅台 -0.020161
获取日内分时
df = qd.klines.intraday("600519.SH", count=5, to_dataframe=True)
print(df[["symbol", "name", "trade_time", "close", "volume"]])
symbol name trade_time close volume
600519.SH 贵州茅台 2026-06-18 14:56:00 1223.50 273
600519.SH 贵州茅台 2026-06-18 14:57:00 1223.88 261
600519.SH 贵州茅台 2026-06-18 14:58:00 1223.26 2
600519.SH 贵州茅台 2026-06-18 14:59:00 1223.26 0
600519.SH 贵州茅台 2026-06-18 15:00:00 1215.00 1788
批量日内分时
dfs = qd.klines.intraday_batch(["600519.SH", "000001.SZ"], to_dataframe=True)
for sym, df in dfs.items():
print(f"{sym} ({df['name'].iloc[0]}): {len(df)} 条分钟线")
600519.SH (贵州茅台): 241 条分钟线
000001.SZ (平安银行): 241 条分钟线
获取标的信息
# 单个标的
inst = qd.instruments.get("600519.SH")
print(f"{inst['symbol']}: {inst['name']}")
print(f" 交易所: {inst['exchange']}, 类型: {inst['type']}")
print(f" 上市日期: {inst['ext']['listing_date']}")
print(f" 总股本: {inst['ext']['total_shares']:,.0f}")
600519.SH: 贵州茅台
交易所: SH, 类型: stock
上市日期: 2001-08-27
总股本: 1,250,081,601
批量查询
insts = qd.instruments.get(["600519.SH", "000001.SZ", "00700.HK"])
for i in insts:
print(f"{i['symbol']:>10s} {i['name']:<6s} 交易所={i['exchange']} 类型={i['type']} 上市={i['ext'].get('listing_date','')}")
600519.SH 贵州茅台 交易所=SH 类型=stock 上市=2001-08-27
000001.SZ 平安银行 交易所=SZ 类型=stock 上市=1991-04-03
00700.HK 腾讯控股 交易所=HK 类型=stock 上市=2004-06-16
获取除权因子
df = qd.klines.ex_factors(["600519.SH"], to_dataframe=True)
print(df[["symbol", "trade_date", "ex_factor"]].tail(5))
symbol trade_date ex_factor
600519.SH 2023-12-20 1.011540
600519.SH 2024-06-19 1.020716
600519.SH 2024-12-20 1.015637
600519.SH 2025-06-26 1.019649
600519.SH 2025-12-19 1.017003
五档盘口
depth = qd.depth.get("600519.SH")
print(f"标的: {depth['symbol']} 地区: {depth['region']}")
for i in range(5):
bid = f"买{i+1}: {depth['bid_prices'][i]:>10.2f} x {depth['bid_volumes'][i]}"
ask = f"卖{i+1}: {depth['ask_prices'][i]:>10.2f} x {depth['ask_volumes'][i]}"
print(f" {bid} | {ask}")
标的: 600519.SH 地区: CN
买1: 1215.00 x 123 | 卖1: 1215.28 x 1
买2: 1214.95 x 2 | 卖2: 1215.96 x 1
买3: 1214.88 x 1 | 卖3: 1216.00 x 2
买4: 1214.48 x 1 | 卖4: 1218.00 x 1
买5: 1214.40 x 1 | 卖5: 1218.89 x 1