# Maintainer: Philipp A. <flying-sheep@web.de> pkgname=scanpy pkgver=1.10.4 pkgrel=1 pkgdesc='Single-Cell Analysis in Python' arch=(any) provides=(scanpy python-scanpy) url='https://github.com/theislab/scanpy' license=(BSD) depends=( 'python-anndata>=0.8' 'python-numpy>=1.23' 'python-matplotlib>=3.6' 'python-pandas>=1.5' 'python-scipy>=1.8' 'python-seaborn>=0.13' 'python-h5py>=3.6' python-tqdm 'python-scikit-learn>=1.1' 'python-statsmodels>=0.13' 'python-patsy>=1.0.1' 'python-networkx>=2.7' python-natsort python-joblib 'python-numba>=0.56' 'python-umap-learn>=0.5.1' 'python-pynndescent>=0.5.13' 'python-packaging>=21.3' python-session-info 'python-legacy-api-wrap>=1.4' ) optdepends=( 'python-igraph: PAGA support (also transitively needed for Louvain/Leiden)' 'python-louvain-igraph: Louvain clustering' 'python-leidenalg: leiden community detection' 'python-bbknn: Batch balanced KNN (batch correction)' 'python-rapids: GPU-driven calculation of neighbors' 'python-magic-impute: MAGIC imputation method' 'python-skmisc: For seurat_v3 highly_variable_genes method' 'python-harmonypy: Harmony dataset integration algorithm' 'python-scanorama: Scanorama dataset integration algorithm' 'python-scikit-image: Cell doublet detection with scrublet' 'rapids-cudf: NVIDIA RAPIDS acceleration' 'rapids-cuml: NVIDIA RAPIDS acceleration' 'rapids-cugraph: NVIDIA RAPIDS acceleration' 'python-dask: Dask parallelization' ) makedepends=(python-hatch python-hatch-vcs python-build python-installer python-wheel) source=("https://files.pythonhosted.org/packages/source/${pkgname::1}/$pkgname/$pkgname-$pkgver.tar.gz") sha256sums=('2682fbbe2e4106c349472feebef08e174062fb666db4c94123758c6a7a470396') build() { cd "$pkgname-$pkgver" python -m build --wheel --no-isolation } package() { cd "$pkgname-$pkgver" python -m installer --destdir="$pkgdir" dist/*.whl }