AlphaFeed Python SDK 是 AlphaFeed 金融市场数据 API 的 Python 客户端，支持 A 股、ETF、美股、港股。
pip install alphafeedSDK 支持 Python 3.9+，推荐 3.10 或更高版本。内置 pandas 和 tqdm 支持。
from alphafeed import AlphaFeed
af = AlphaFeed(api_key="your-api-key")也支持环境变量：
export ALPHAFEED_API_KEY="your-api-key"from alphafeed import AlphaFeed
af = AlphaFeed() # 自动读取 ALPHAFEED_API_KEY| 示例 | 说明 |
|---|---|
600519.SH |
上交所 |
000001.SZ |
深交所 |
AAPL.US |
美股 |
00700.HK |
港股 |
from alphafeed import AlphaFeed
af = AlphaFeed(api_key="your-api-key")
# 日 K 线，返回 DataFrame
df = af.klines.get("600519.SH", period="1d", count=5, to_dataframe=True)
print(df[["trade_date", "open", "high", "low", "close", "volume"]])
# trade_date open high low close volume
# 0 2026-06-02 1306.00 1326.36 1301.00 1307.22 36362
# 1 2026-06-03 1304.00 1304.00 1276.00 1281.91 52477
# 2 2026-06-04 1278.99 1288.99 1266.69 1268.00 33506
# 3 2026-06-05 1278.00 1283.00 1267.74 1272.86 31304
# 4 2026-06-08 1272.00 1278.00 1260.00 1262.98 30828
# 比例前复权（默认）/ 比例后复权 / 差值前复权 / 差值后复权 / 不复权
df = af.klines.get("600519.SH", adjust="forward", to_dataframe=True)
df = af.klines.get("600519.SH", adjust="backward", to_dataframe=True)
df = af.klines.get("600519.SH", adjust="forward_additive", to_dataframe=True)
df = af.klines.get("600519.SH", adjust="backward_additive", to_dataframe=True)
df = af.klines.get("600519.SH", adjust="none", to_dataframe=True)批量获取：多只标的一次拉取：
symbols = ["600519.SH", "000001.SZ", "601318.SH"]
dfs = af.klines.batch(symbols, period="1d", count=5, to_dataframe=True, show_progress=True)
# dfs 是 dict: {"600519.SH": DataFrame, "000001.SZ": DataFrame, ...}
print(dfs["600519.SH"][["trade_date", "close"]])# 当日 1 分钟线
df = af.klines.intraday("600519.SH", to_dataframe=True)
print(df[["trade_time", "close", "volume"]].tail())
# trade_time close volume
# 236 2026-06-08 14:56:00 1263.00 191
# 237 2026-06-08 14:57:00 1262.99 126
# 238 2026-06-08 14:58:00 1263.00 6
# 239 2026-06-08 14:59:00 1263.00 0
# 240 2026-06-08 15:00:00 1262.98 254
# 5 分钟线
df = af.klines.intraday("600519.SH", period="5m", to_dataframe=True)
# 批量日内分时
dfs = af.klines.intraday_batch(["600519.SH", "000001.SZ"], to_dataframe=True)按标的代码查询
df = af.quotes.get(symbols=["600519.SH", "000001.SZ"], to_dataframe=True)
print(df[["symbol", "last_price", "volume", "ext.name", "ext.change_pct"]])
# symbol last_price volume ext.name ext.change_pct
# 0 000001.SZ 11.03 1090926 平安银行 0.004554
# 1 600519.SH 1262.98 30828 贵州茅台 -0.007762按标的池查询（全量行情）
# 全部 A 股实时行情
df = af.quotes.get(universes="CN_Stock", to_dataframe=True)
print(f"共 {len(df)} 只标的")
# 全部 ETF 行情
df = af.quotes.get(universes="CN_ETF", to_dataframe=True)支持的标的池：CN_Stock（A股）、US_Stock（美股）、HK_Stock（港股）、CN_ETF（ETF）
depth = af.depth.get("600519.SH")
print(f"标的: {depth['symbol']}, 地区: {depth['region']}")
print(f"买盘价: {depth['bid_prices']}") # [1262.98, 1262.65, ...]
print(f"买盘量: {depth['bid_volumes']}") # [2, 1, ...]
print(f"卖盘价: {depth['ask_prices']}") # [1262.99, 1263.0, ...]
print(f"卖盘量: {depth['ask_volumes']}") # [7, 44, ...]# 单个标的
inst = af.instruments.get("600519.SH")
print(f"{inst['symbol']}: {inst['name']} ({inst['exchange']}, {inst['type']})")
# 600519.SH: 贵州茅台 (SH, stock)
print(f"上市日期: {inst['ext']['listing_date']}")
# 上市日期: 2001-08-27
# 批量查询
insts = af.instruments.batch(["600519.SH", "000001.SZ", "00700.HK"])
for i in insts:
print(f"{i['symbol']}: {i['name']} ({i['region']})")
# 600519.SH: 贵州茅台 (CN)
# 000001.SZ: 平安银行 (CN)
# 00700.HK: 腾讯控股 (HK)df = af.klines.ex_factors(["600519.SH", "000001.SZ"], to_dataframe=True)
print(df[["symbol", "trade_date", "ex_factor"]].tail())
# symbol trade_date ex_factor
# 52 000001.SZ 2023-06-14 1.024369
# 53 000001.SZ 2024-06-14 1.071428
# 54 000001.SZ 2024-10-10 1.021872
# 55 000001.SZ 2025-06-12 1.031331
# 56 000001.SZ 2025-10-15 1.021505MIT