finzdata

Python client for the FinzData market data API. It works like yfinance and adds the datasets yfinance doesn't have.

pip install finzdata

Get a free API key at https://api.finzdata.com/ and set FINZDATA_API_KEY.

import finzdata as yf

msft = yf.Ticker("MSFT")
daily = msft.history(start="2020-01-01")                  # daily bars, split and dividend adjusted
bars = msft.history(interval="5m", start="2026-10-01")    # 1m, 5m, 1h bars (Researcher+)
both = yf.download(["SPY", "QQQ"], period="max")

c = yf.Client()
gold = c.cot(report="legacy_fo", market="GOLD")           # CFTC Commitments of Traders
rev = c.fundamentals(ticker="AAPL", concept="Revenues", as_of="2025-06-30")   # SEC, point-in-time
cpi = c.macro("CPIAUCSL", as_of="2022-06-30")             # US macro, as known on that date
regime = c.model("latest")                                # FinzData Quantitative Model (Researcher+)
hy = c.licensed("BAMLH0A0HYM2")                           # licensed third-party series (Researcher+)
liq = c.liquidity("FED_NET_LIQUIDITY")                   # Fed assets - TGA - reverse repo (Researcher+)
money = c.liquidity(["US_M2", "US_M3_ESTIMATE"], transform="yoy", wide=True)  # money supply growth
flows = c.tic(country="Japan", asset="treasuries")       # TIC foreign holdings and net purchases

Datasets

• US equity bars, daily (incl. delisted names) and intraday 1-minute, 5-minute and hourly
• Splits and dividends
• CFTC Commitments of Traders, all reports, since 1986
• SEC XBRL fundamentals, as reported and point-in-time
• US macro series with every vintage (FRED/ALFRED), plus a release calendar
• FinzData Quantitative Model: macro regime labels, a nowcast and a market-stress probability
• Licensed series: Moody's, University of Michigan, Case-Shiller, ICE BofA, Cboe (incl. the VIX futures curve)

Free samples and the full file specification: https://finzdata.com/samples · Pricing: https://finzdata.com/pricing · Data status: https://finzdata.com/status · API reference: https://api.finzdata.com/docs

Bulk downloads (Researcher and above): POST /v1/batch, then fetch the download_url. Full-history bundles and nightly updates: GET /v1/bundles.

Data is provided under the FinzData subscriber licence; redistribution is prohibited.