tet-py

Python bindings for Tetration — mmap-friendly .tet tensors and the JSON/TOML query engine.

Do not pip install tetration — that PyPI name is unrelated math code.

Quick start

pip install tet-py
python -c "import tet; print(tet.__version__, tet.core_version())"

import tet

with tet.open("data.tet") as f:
    print(f.mean("temperature"), f.quantile("temperature", 0.5))
    arr = f.read_numpy("temperature")                 # ram (memmap for full-width raw slabs)
    z = f.transform.to_numpy.zscore("temperature")  # transform → ndarray

More examples: Python quick start · operations · NumPy

Convert

tet.convert writes one .tet from a foreign file. .npy, multi-member .npz, and .csv / .tsv are in the core wheel. Other formats are optional extras: tet-py[h5], [netcdf], [zarr], [parquet], or [convert] for all of them.

Compared with Rust tet convert: Python does not apply CF scale/offset, chunks the whole array unless you pass chunk_shape, and can read codecs the Rust importer skips when the extra library can decode them. Columns that are not layout-v1 numeric (or category text) are omitted.

Export

tet.export (and TetFile.export) writes a .tet to HDF5, NetCDF, or Zarr. Same optional extras as convert ([h5], [netcdf], [zarr], or [export] for those three). Dense numeric datasets only; carries dim_names and basic string attrs when present. Values are densified via read_numpy — prefer Rust tet export when you need native HDF5/NetCDF or chunk-preserving Zarr.

Packages

tet.open("pkg.tet.d") reads the generation named by CURRENT (packed.tet). tet.ingest copies a sealed .tet into staging, and tet.publish seals those parts and updates CURRENT. See docs/operations.md.

Documentation

Develop

uv sync --extra dev
mise run develop          # or: uv run maturin develop
uv run pytest -q
uv run mypy python/tet

Requires Python 3.11+ and Rust 1.95+ (.mise.toml). Fixtures: tests/fixtures/.

License

MIT OR Apache-2.0, same as tetration.