setup.cfg

[metadata]
author = Xarray-Spatial Developers
classifiers =
    Development Status :: 4 - Beta
    Intended Audience :: Developers
    Intended Audience :: Science/Research
    License :: OSI Approved :: MIT License
    Operating System :: OS Independent
    Programming Language :: Python :: 3
description = xarray-based spatial analysis tools
license = MIT
license_file = LICENSE.txt
long_description = file: README.md
long_description_content_type = text/markdown
name = xarray-spatial
platforms = any
url = https://github.com/xarray-contrib/xarray-spatial

[options]
include_package_data = True
install_requires =
    numba
    scipy
    xarray
    numpy
    urllib3
    zstandard
packages = find:
python_requires = >=3.12
setup_requires = setuptools_scm
zip_safe = False

[options.entry_points]
console_scripts =
    xrspatial = xrspatial.__main__:main
xarray.backends =
    xrspatial = xrspatial.geotiff._xarray_backend:GeoTIFFBackendEntrypoint

[options.extras_require]
doc =
    dask[dataframe]
    geopandas
    Jinja2 >=2.11
    ipykernel
    matplotlib
    myst-parser
    nbsphinx
    numpydoc
    pandoc
    pydata_sphinx_theme
    sphinx
    sphinx-panels
    sphinx_rtd_theme
examples =
    datashader >= 0.15.0
plot =
    # Optional for the .xrs.plot accessor helpers. Every matplotlib
    # import in the package is lazy, so the compute functions work
    # without this extra installed.
    matplotlib
vector =
    # Optional for the vector-to-raster paths (rasterize, polygonize).
    # shapely is imported lazily so `import xrspatial` does not load it.
    shapely>=2.0
optional =
    # Optional for polygonize return types.
    awkward>=1.4
    geopandas
    spatialpandas
    # Optional for gpu_rtx functions. Also requires cupy.
    rtxpy
reproject =
    pyproj
geotiff =
    deflate
    # Required by the GeoTIFF writer to classify EPSG codes as
    # geographic vs projected. Without pyproj the writer can only
    # handle a tiny hard-coded allowlist of EPSGs and raises
    # UnknownCRSModelTypeError on anything else. See issue #2277.
    pyproj
dask =
    dask[array]
    dask-geopandas
gpu =
    cupy
    cuspatial
tests =
    flake8
    geopandas
    hypothesis
    isort
    matplotlib
    noise >= 1.2.2
    dask
    pyarrow
    pyproj
    pytest
    pytest-cov
    scipy
    shapely>=2.0


[flake8]
exclude =
    .git,
    .asv,
    __pycache__,
max-line-length = 100

[tool:pytest]
filterwarnings =
    ignore::numba.core.errors.NumbaPerformanceWarning
    ignore::numba.core.errors.NumbaPendingDeprecationWarning
    ignore:You will likely lose important projection information:UserWarning:pyproj
    ignore:cost_distance. max_cost is infinite:UserWarning:xrspatial
    ignore:surface_distance. max_distance is infinite:UserWarning:xrspatial
    ignore:proximity. target coordinates exceed:ResourceWarning:xrspatial
    ignore:viewshed. grid exceeds memory:UserWarning:xrspatial
    ignore:Covariance of the parameters could not be estimated:scipy.optimize.OptimizeWarning
    ignore:'oneOf' deprecated:DeprecationWarning:matplotlib
    ignore:'parseString' deprecated:DeprecationWarning:matplotlib
    ignore:'resetCache' deprecated:DeprecationWarning:matplotlib
    ignore:'enablePackrat' deprecated:DeprecationWarning:matplotlib
    ignore:'asyncio.AbstractEventLoopPolicy' is deprecated:DeprecationWarning:pytest_asyncio
markers =
    slow: long-running test cell (typical: golden-corpus fixtures behind a heavy codec or large pixel count). PR CI can skip with `-m "not slow"`; nightly / release runs use no filter. See xrspatial/geotiff/tests/golden_corpus/_marks.py for the corpus-side helper.
    release_gate: locks a single stable feature in the GeoTIFF release contract (epic #2340). Always runs by default in CI; the marker exists so release engineers can run only these gates with `pytest -m release_gate` before tagging a release. Tests in this marker should be small, deterministic, and fail loudly if the contract breaks.

[isort]
line_length = 100