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.
| 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 |
Rich STAC metadata for regular raster chips, labels, bands, scaling, and statistics |
oceantaco_istac.py |
OceanTACO-inspired ISTAC metadata for irregular SWOT swaths and Argo collocations |
partitioned.py |
ZIP partitions and their TACOCAT catalog |
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file taco_eo-0.3.0.tar.gz.
File metadata
- Download URL: taco_eo-0.3.0.tar.gz
- Upload date:
- Size: 90.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
00e7a52265dab920d769a5b35b6b01b824576f8de31c9b5e9dd5acb65aec3363
|
|
| MD5 |
2644287f4c7b60931d275a08439ef19c
|
|
| BLAKE2b-256 |
640390affef2d82882a3d72ffa6cd4e0bdd9d39876a1fd063900e8157103238a
|
Provenance
The following attestation bundles were made for taco_eo-0.3.0.tar.gz:
Publisher:
release.yml on asterisk-labs/taco
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
taco_eo-0.3.0.tar.gz -
Subject digest:
00e7a52265dab920d769a5b35b6b01b824576f8de31c9b5e9dd5acb65aec3363 - Sigstore transparency entry: 2760640819
- Sigstore integration time:
-
Permalink:
asterisk-labs/taco@e7bf29515c3dc52856cedee99fbfba76433d2da8 -
Branch / Tag:
refs/tags/v0.3.0 - Owner: https://github.com/asterisk-labs
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@e7bf29515c3dc52856cedee99fbfba76433d2da8 -
Trigger Event:
push
-
Statement type:
File details
Details for the file taco_eo-0.3.0-py3-none-any.whl.
File metadata
- Download URL: taco_eo-0.3.0-py3-none-any.whl
- Upload date:
- Size: 76.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/7.0.0 CPython/3.13.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
127eb090727195ffca4242863af336637df2fd2425d8f4d8f1aac883e3877c1b
|
|
| MD5 |
723e1c58bb72b363065bc2b8a2dc8957
|
|
| BLAKE2b-256 |
cdb34ea082451d1549e48e142c08b847b12efd4aeb64d686d0a8a3c8f3b60caf
|
Provenance
The following attestation bundles were made for taco_eo-0.3.0-py3-none-any.whl:
Publisher:
release.yml on asterisk-labs/taco
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
taco_eo-0.3.0-py3-none-any.whl -
Subject digest:
127eb090727195ffca4242863af336637df2fd2425d8f4d8f1aac883e3877c1b - Sigstore transparency entry: 2760640917
- Sigstore integration time:
-
Permalink:
asterisk-labs/taco@e7bf29515c3dc52856cedee99fbfba76433d2da8 -
Branch / Tag:
refs/tags/v0.3.0 - Owner: https://github.com/asterisk-labs
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
release.yml@e7bf29515c3dc52856cedee99fbfba76433d2da8 -
Trigger Event:
push
-
Statement type:
