TacoReader is a Python library for querying AI-ready datasets, supporting lazy SQL evaluation via DuckDB. It reads TACO datasets in ZIP (.tacozip), folder, or TacoCat consolidated formats. Current version: 2.4.21, requires Python >=3.10, <3.14. Release cadence: feature releases every few months, patch releases as needed.
pip install tacoreaderVerified import paths — ran on the pinned version, not inferred.
Load a TACO dataset, filter by time, and execute a SQL query.
Replace `str(path)` with just `path` when calling `load()`.
Remove `base_path` argument and provide paths as absolute or relative to dataset.
Ensure you understand filter propagation; if needed, apply the same filter after concat.
Install with `pip install tacoreader`. Verify with `python -m pip list`. Use correct Python version (>=3.10, <3.14).
Use `from tacoreader import load` and ensure tacoreader >=2.3.0. Check version: `python -c 'import tacoreader; print(tacoreader.__version__)'`
Verify the dataset path exists and has .tacozip extension or is a folder with correct structure. Use absolute paths if ambiguous.