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update hatch (#309)
* test * update * update hatch * update read the docs * test rapids * update for rapids-24.12 * use python-3.12 for tests * test CI * add flag to install * update install * keep rapids-24.08 * Update .github/workflows/test-gpu-dev.yml Co-authored-by: Philipp A. <[email protected]> * Update .github/workflows/test-gpu.yml Co-authored-by: Philipp A. <[email protected]> * Update docs/Installation.md Co-authored-by: Philipp A. <[email protected]> --------- Co-authored-by: Philipp A. <[email protected]>
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.github/workflows/test-gpu-dev.yml

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- name: Install Python
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uses: actions/setup-python@v5
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with:
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python-version: "3.11"
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python-version: "3.12"
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- name: Install UV
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uses: hynek/setup-cached-uv@v2
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"scanpy @ git+https://github.com/scverse/scanpy.git"
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"anndata @ git+https://github.com/scverse/anndata.git"
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--extra-index-url=https://pypi.nvidia.com
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--index-strategy=unsafe-best-match
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- name: Run test
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run: pytest

.github/workflows/test-gpu.yml

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- name: Install Python
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uses: actions/setup-python@v5
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with:
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python-version: "3.11"
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python-version: "3.12"
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- name: Install UV
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uses: hynek/setup-cached-uv@v2
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with:
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cache-dependency-path: pyproject.toml
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- name: Install rapids-singlecell
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run: uv pip install --system -e .[test,rapids12] --extra-index-url=https://pypi.nvidia.com
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run: uv pip install --system -e .[test,rapids12] --extra-index-url=https://pypi.nvidia.com --index-strategy=unsafe-best-match
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- name: Pip list
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run: pip list
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- conda-forge
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- bioconda
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dependencies:
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- rapids=24.10
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- python=3.11
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- rapids=24.12
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- python=3.12
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- cuda-version=12.5
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- cudnn
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- cutensor

docs/Installation.md

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## Conda
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The easiest way to install *rapids-singlecell* is to use one of the *yaml* file provided in the [conda](https://github.com/scverse/rapids_singlecell/tree/main/conda) folder. These *yaml* files install everything needed to run the example notebooks and get you started.
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```
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conda env create -f conda/rsc_rapids_24.06.yml #default CUDA-11.8
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conda env create -f conda/rsc_rapids_24.08.yml #default CUDA-11.8
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# or
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mamba env create -f conda/rsc_rapids_24.08.yml #default CUDA-12.5
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mamba env create -f conda/rsc_rapids_24.12.yml #default CUDA-12.5
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```
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## PyPI
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As of version 0.4.0 *rapids-singlecell* is now on PyPI.
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```
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It is important to ensure that the CUDA environment is set up correctly so that RAPIDS and Cupy can locate the necessary libraries.
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```{note}
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If you are using `python=3.12` with `uv`, you might need to add the `--index-strategy=unsafe-best-match` flag to ensure compatibility.
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```
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## Docker
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We also offer a Docker container for `rapids-singlecell`. This container includes all the necessary dependencies, making it even easier to get started with `rapids-singlecell`.

hatch.toml

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features = ["doc"]
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scripts.build = "sphinx-build -M html docs docs/_build {args}"
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scripts.clean = "git clean -fXd docs"
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[envs.default.pip]
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extra_index_urls = [
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"https://pypi.nvidia.com"
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]

pyproject.toml

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[project]
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name = "rapids_singlecell"
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description = "running single cell analysis on Nvidia GPUs"
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requires-python = ">=3.10"
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requires-python = ">=3.10, <3.13"
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license = {file = "LICENSE"}
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authors = [{name = "Severin Dicks"}]
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readme = {file = "README.md", content-type="text/markdown"}
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]
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[project.optional-dependencies]
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rapids11 = ["cupy-cuda11x","cudf-cu11==24.10.*", "cuml-cu11==24.10.*", "cugraph-cu11==24.10.*"]
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rapids12 = ["cupy-cuda12x","cudf-cu12==24.10.*", "cuml-cu12==24.10.*", "cugraph-cu12==24.10.*"]
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rapids11 = ["cupy-cuda11x","cudf-cu11==24.12.*", "cuml-cu11==24.12.*", "cugraph-cu11==24.12.*"]
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rapids12 = ["cupy-cuda12x","cudf-cu12==24.12.*", "cuml-cu12==24.12.*", "cugraph-cu12==24.12.*"]
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doc = [
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"sphinx>=4.5.0",
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"sphinx-copybutton",

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