Skip to main content

AlphaFeed Python SDK

Project description

AlphaFeed Python SDK

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。

完整文档https://docs.alphafeed.org


安装

pip install alphafeed

SDK 支持 Python 3.9+,推荐 3.10 或更高版本。内置 pandas 和 tqdm 支持。


初始化

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

标的代码格式

示例 说明
600519.SH 上交所
000001.SZ 深交所
AAPL.US 美股
00700.HK 港股

基础用法

K 线获取

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"]])

日内分时

# 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)

实时行情

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)

五档盘口

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, ...]

标的信息

# 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)

复权因子

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   1.021505

更多文档


License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

alphafeed-0.1.3.tar.gz (21.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

alphafeed-0.1.3-py3-none-any.whl (24.8 kB view details)

Uploaded Python 3

File details

Details for the file alphafeed-0.1.3.tar.gz.

File metadata

  • Download URL: alphafeed-0.1.3.tar.gz
  • Upload date:
  • Size: 21.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for alphafeed-0.1.3.tar.gz
Algorithm Hash digest
SHA256 217e094bf63995e277681b9053315f4159a324a8359ac57133d6a6ec1d09ed74
MD5 823dfc7a09df609d4f9dcb35299851a8
BLAKE2b-256 0d0eaca438e627e4f88a0ebe69ba91bf5877a12247caa3182f184fa11c13dc36

See more details on using hashes here.

File details

Details for the file alphafeed-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: alphafeed-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 24.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for alphafeed-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 934e21c6ebba8cec2789fbf42f3de5dc154c7c138673613dca0e2e8344ad2de7
MD5 2f71002c40203af0eb538904ce7b6f59
BLAKE2b-256 5e250d050665111c5e5054b08e929ac014b11b7fe43e994b232861e0094b4385

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page