taco

Read and write TACO datasets in Python.

pip install taco-eo
python examples/minimal.py

import taco

samples = taco.read("dataset.zip")
parts = taco.read(["part-0.zip", "part-1.zip"])

Examples

Every example is self-contained, uses synthetic data, and writes its output in the current directory.

Spatial and temporal metadata use separate profiles: Spatial for regular spatial grids, ISpatial for irregular footprints, and Temporal for time alone. STAC combines regular spatial + temporal metadata; ISTAC combines irregular spatial + temporal metadata.

Example	What it demonstrates
`minimal.py`	Smallest possible single-file dataset
`numpy_minimal.py`	NumPy image and mask assets with a train/test split
`change_detection.py`	Metadata on `before/` and `after/` folders
`sequence.py`	Variable-length asset sequences
`time_series.py`	Per-observation time and cloud metadata
`geospatial.py`	Compact STAC metadata and derived MajorTOM cells
`stac_segmentation.py`	STAC extensions for regular raster chips, labels, bands, and scaling
`oceantaco_istac.py`	OceanTACO-inspired ISTAC metadata for irregular SWOT swaths and Argo collocations
`partitioned.py`	ZIP partitions and their TACOCAT catalog

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

taco_eo-0.6.1.tar.gz (660.9 kB view details)

Uploaded Sep 13, 2026 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

taco_eo-0.6.1-py3-none-any.whl (642.8 kB view details)

Uploaded Sep 13, 2026 Python 3

File details

Details for the file taco_eo-0.6.1.tar.gz.

File metadata

Download URL: taco_eo-0.6.1.tar.gz
Upload date: Sep 13, 2026
Size: 660.9 kB
Tags: Source
Uploaded using Trusted Publishing? Yes
Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for taco_eo-0.6.1.tar.gz
Algorithm	Hash digest
SHA256	`8a245fbb750be1e073b787d8a375c5f7fcab167824893fd0684ed1cf3911aa28`
MD5	`ae72040b2eaa4c4fa10c5dc144f108cf`
BLAKE2b-256	`e25c495d6158296469196fe605dee0817607e62b912ff6b74874837d5744106c`

See more details on using hashes here.

Provenance

The following attestation bundles were made for taco_eo-0.6.1.tar.gz:

Publisher: release.yml on asterisk-labs/taco

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Statement:
- Statement type: https://in-toto.io/Statement/v1
- Predicate type: https://docs.pypi.org/attestations/publish/v1
- Subject name: taco_eo-0.6.1.tar.gz
- Subject digest: 8a245fbb750be1e073b787d8a375c5f7fcab167824893fd0684ed1cf3911aa28
- Sigstore transparency entry: 2822390982
- Sigstore integration time: Sep 13, 2026
Source repository:
- Permalink: asterisk-labs/taco@a3c46ced5e997c4503301232fd1eba89fc2d1821
- Branch / Tag: refs/tags/v0.6.1
- Owner: https://github.com/asterisk-labs
- Access: public
Publication detail:
- Token Issuer: https://token.actions.githubusercontent.com
- Runner Environment: github-hosted
- Publication workflow: release.yml@a3c46ced5e997c4503301232fd1eba89fc2d1821
- Trigger Event: push