pit-fundamentals

Point-in-time company fundamentals from official regulator filings — as first reported, keyed by filing date, exportable. Zero dependencies (pandas optional).

Backtests leak the future when they use restated numbers or use figures before their filing date. This dataset stores every figure as it was first reported and stamps it with its filing date, so as_of queries return exactly what was public on that day.

Install

pip install pit-fundamentals

60-second start (no signup — public demo key built in)

import pit_fundamentals as pf

# TSMC's history, as first reported
rows = pf.fundamentals("2330.TW")

# What a backtest running on 2022-01-01 was allowed to know about Apple
snap = pf.latest("AAPL", as_of="2022-01-01")
print(snap["revenue"])   # FY2021, filed 2021-10-29 — nothing newer leaks

# The scored, resolved prediction panel (history incl. losses; delayed on free)
panel = pf.signals(market="TW", horizon="21d", limit=1000)

# pandas users
df = pf.to_df(rows)

The demo key covers 25 flagship tickers (US · TW · KR) at full fidelity — full fields, full history. Paid plans unlock every ticker; your code doesn't change:

export PIT_FUNDAMENTALS_KEY=ta_live_xxxxxxxx

Pricing & licences

Free / Personal US$29/mo / Commercial US$149/mo / Redistribution US$499/mo — plans and full licence texts: https://www.tradingagentapp.com/fundamentals

What makes the licence unusual: no export bans, no display-only clause, and your derived research is yours forever (explicitly, in writing — including after cancellation). We ingest from public filings directly, so no upstream vendor licence forbids you taking the data with you.

Notes worth knowing

• Taiwan income statements are cumulative year-to-date (Taiwan reporting convention: Q2 = H1 total). Difference adjacent quarters for single-quarter flows. Balance-sheet items are point-in-time as usual.
• Every API response embeds its statutory source attribution (e.g. 臺灣證券 交易所 under OGDL 1.0).
• Factual, historical data only — no forecasts, no advice, no price/OHLCV.

Docs: https://www.tradingagentapp.com/developers · Field dictionary and examples included.