import qrt as q
q.data.datasets.AVAILABLE('aapl',
'btcusd',
'spy',
'spy_breakout',
'spy_ema_cross',
'spy_random',
'spy_rsi2')
q.data.datasets.load ships daily OHLCV parquet files for a handful of symbols so tests, demos, and tutorials (like this one, the Indicators, and Return Statistics pages) don’t need network access:
Alongside OHLCV prices, it bundles four demo strategy trade logs (see Data schemas) used throughout the Trade logs page:
('aapl',
'btcusd',
'spy',
'spy_breakout',
'spy_ema_cross',
'spy_random',
'spy_rsi2')
| open | high | low | close | volume | |
|---|---|---|---|---|---|
| datetime | |||||
| 2026-07-20 | 333.510010 | 333.709991 | 323.679993 | 326.589996 | 53468000 |
| 2026-07-21 | 323.130005 | 329.600006 | 322.220001 | 327.739990 | 41338900 |
| 2026-07-22 | 327.869995 | 329.000000 | 323.339996 | 325.890015 | 38755900 |
| 2026-07-23 | 321.730011 | 323.299988 | 319.350006 | 321.660004 | 40840800 |
| 2026-07-24 | NaN | NaN | NaN | NaN | 47460975 |
These bundled files are refreshed via make datasets before a release, so they’re reasonably current but not guaranteed to have today’s bar — fetch live data through q.data.sources if you need that.