hfdatalibrary (Python)
Python client for the HF Data Library — free,
research-grade 1-minute OHLCV data for ~1,391 U.S. equities and ETFs, in
both raw and clean versions across eight timeframes.
Install
pip install hfdatalibrary # add pyarrow for parquet: pip install hfdatalibrary[parquet]
Authenticate
Get a free API key at https://hfdatalibrary.com/pages/account, then:
import hfdatalibrary as hfdl
hfdl.set_key("YOUR_API_KEY") # or set the HFDL_API_KEY environment variable
Use
hfdl.symbols() # -> ['A', 'AA', 'AAPL', ...]
df = hfdl.get("AAPL") # clean 1-minute bars (pandas DataFrame)
df = hfdl.get("AAPL", version="raw", timeframe="daily")
panel = hfdl.get(["AAPL", "MSFT", "SPY"]) # -> {ticker: DataFrame}
df = hfdl.get("AAPL", fmt="csv") # CSV instead of parquet (no pyarrow needed)
Parameters: version ∈ {clean, raw}; timeframe ∈ {1min,5min,15min,30min,hourly,daily,weekly,monthly}.
Important: survivorship bias
The universe is a fixed snapshot (~2023) carried back to 2002, so pre-2022 history is survivor-conditioned — companies that delisted before ~2021 are absent. Not suitable for survivorship-sensitive backtests over 2002–2021 without adjustment. See the methodology docs for full limitations (including the post-March-2022 IEX-only volume caveat).
License
MIT (client code). Data is CC BY 4.0 — cite per https://hfdatalibrary.com/pages/cite.
1 maintainer
Release files for hfdatalibrary 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hfdatalibrary-0.1.0.tar.gz | 8.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hfdatalibrary-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.9 kB
Release files / hfdatalibrary-0.1.0.tar.gz
| Download URL | hfdatalibrary-0.1.0.tar.gz |
|---|---|
| Size | 8.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
20ebfc3d8033d9db443d3e6bd5e6c53e765a6971a878931e98bc17d86fe2481e
|
|
BLAKE2b-256 checksum How to use checksums |
2767ac32399bc063c7df048d467c49a85b85b92c709757be70cc736963cf8d62
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.6
|
Release files / hfdatalibrary-0.1.0-py3-none-any.whl
| Download URL | hfdatalibrary-0.1.0-py3-none-any.whl |
|---|---|
| Size | 5.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
33dac8f1e30cd70606a7d32a56036979662443c58b8195746f557d7882836bfd
|
|
BLAKE2b-256 checksum How to use checksums |
de439af352f6f80fbdc88eef8c138f27c6e7100af5fec5da97dad7974f239ccb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.6
|
