SSAPy-Data stores reusable data resources for SSAPy
and SSAPy Toolkit. The repository is
packaged as the llnl-ssapy-data Python distribution and exposes the
ssapy_data import package. Data files live under src/ssapy_data/data so
users can receive required data through normal pip installation without Git
LFS, git submodules, or runtime GitHub downloads.
The initial package intentionally does not duplicate data already packaged by
base SSAPy. New SSAPy Toolkit datasets should be added here when they are needed
by toolkit functions and are not already available from the base llnl-ssapy
wheel.
Install from a local clone in editable mode:
pip install -e .Build the wheel and source distribution:
python -m build
ls -lh dist/Access packaged data with importlib.resources helpers exposed by
ssapy_data:
from ssapy_data import data_path, read_text
gravity_header = read_text("egm84.egm")
with data_path("Earth_graphics/ne_50m_ocean.shp") as path:
print(path)data_path yields a real filesystem path for libraries that require paths.
Use the path only inside the context manager because zipped wheels may extract
resources to temporary locations.
Add new reusable data below src/ssapy_data/data. Preserve source filenames
when possible, and use subdirectories when a dataset has multiple sidecar files.
Do not add files already packaged by base SSAPy unless a later migration
explicitly moves that dependency here.
After adding, replacing, or removing data, regenerate the manifest:
python scripts/update_manifest.py
python -m pytest
python -m buildThe manifest records each packaged file path, byte count, and SHA-256 digest in
src/ssapy_data/manifest.json. Pull requests that change data should also
update the source/provenance notes in this README when the dataset source or
license differs from the existing entries.
The initial wheel contains only the package helpers and a data-directory README. Before adding large datasets, estimate the built wheel size with:
python -m build --wheel
ls -lh dist/*.whlIf a future dataset pushes the wheel above PyPI limits, split the data into a separate companion package rather than using Git LFS in SSAPy Toolkit.
The repository publishes llnl-ssapy-data to PyPI through GitHub Actions and
PyPI trusted publishing. Configure PyPI before creating the first release:
- Create a PyPI trusted publisher, or pending publisher, for project
llnl-ssapy-data. - Set the owner to
llnland repository toSSAPy-Data. - Set the workflow filename to
publish.yml. - Set the GitHub environment to
pypi.
After PyPI trust is configured, publish by creating a GitHub release whose tag
matches the version in pyproject.toml, for example v0.1.0. The
Publish to PyPI workflow builds a clean wheel and source distribution, runs
tests, checks the manifest, and uploads through OpenID Connect (OIDC). No PyPI
API token is required.
Each data pull request should document the source URL, license, retrieval date, and any preprocessing steps for new packaged datasets. Candidate sources include:
- Earth gravity fields: ICGEM time-variable gravity fields
- Other celestial bodies: ICGEM celestial gravity fields
Please note that SSAPy-Data has a Code of Conduct. By participating in the SSAPy-Data community, you agree to abide by its rules.
SSAPy-Data is distributed under the terms of the MIT license. All new contributions must be made under the MIT license.
See the license and NOTICE for details.
SPDX-License-Identifier: MIT
LLNL-CODE-862420