update hatch

.github/workflows/test-gpu-dev.yml

@@ -42,7 +42,7 @@ jobs:
       - name: Install Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
 
       - name: Install UV
         uses: hynek/setup-cached-uv@v2
@@ -55,6 +55,7 @@ jobs:
           "scanpy @ git+https://github.com/scverse/scanpy.git"
           "anndata @ git+https://github.com/scverse/anndata.git"
           --extra-index-url=https://pypi.nvidia.com
+          --index-strategy=unsafe-best-match
 
       - name: Run test
         run: pytest

.github/workflows/test-gpu.yml

@@ -42,15 +42,15 @@ jobs:
       - name: Install Python
         uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.12"
 
       - name: Install UV
         uses: hynek/setup-cached-uv@v2
         with:
           cache-dependency-path: pyproject.toml
 
       - name: Install rapids-singlecell
-        run: uv pip install --system -e .[test,rapids12] --extra-index-url=https://pypi.nvidia.com
+        run: uv pip install --system -e .[test,rapids12] --extra-index-url=https://pypi.nvidia.com --index-strategy=unsafe-best-match
 
       - name: Pip list
         run: pip list

conda/rsc_rapids_24.10.yml → conda/rsc_rapids_24.12.yml

@@ -5,8 +5,8 @@ channels:
  - conda-forge
  - bioconda
 dependencies:
- - rapids=24.10
- - python=3.11
+ - rapids=24.12
+ - python=3.12
  - cuda-version=12.5
  - cudnn
  - cutensor

docs/Installation.md

@@ -2,9 +2,9 @@
 ## Conda
 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.
 ```
-conda env create -f conda/rsc_rapids_24.06.yml #default CUDA-11.8
+conda env create -f conda/rsc_rapids_24.08.yml #default CUDA-11.8
 # or
-mamba env create -f conda/rsc_rapids_24.08.yml #default CUDA-12.5
+mamba env create -f conda/rsc_rapids_24.12.yml #default CUDA-12.5
 ```
 ## PyPI
 As of version 0.4.0 *rapids-singlecell* is now on PyPI.
@@ -21,6 +21,10 @@ pip install 'rapids-singlecell[rapids12]' --extra-index-url=https://pypi.nvidia.
 ```
 It is important to ensure that the CUDA environment is set up correctly so that RAPIDS and Cupy can locate the necessary libraries.
 
+```{note}
+If you are using `python=3.12` with `uv`, you might need to add the `--index-strategy=unsafe-best-match` flag to ensure compatibility.
+```
+
 ## Docker
 
 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

@@ -9,3 +9,8 @@ features = ["test", "rapids12"]
 features = ["doc"]
 scripts.build = "sphinx-build -M html docs docs/_build {args}"
 scripts.clean = "git clean -fXd docs"
+
+[envs.default.pip]
+extra_index_urls = [
+  "https://pypi.nvidia.com"
+]

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "hatchling.build"
 [project]
 name = "rapids_singlecell"
 description = "running single cell analysis on Nvidia GPUs"
-requires-python = ">=3.10"
+requires-python =  ">=3.10, <3.13"
 license = {file = "LICENSE"}
 authors = [{name = "Severin Dicks"}]
 readme = {file = "README.md", content-type="text/markdown"}
@@ -26,8 +26,8 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-rapids11 = ["cupy-cuda11x","cudf-cu11==24.10.*", "cuml-cu11==24.10.*", "cugraph-cu11==24.10.*"]
-rapids12 = ["cupy-cuda12x","cudf-cu12==24.10.*", "cuml-cu12==24.10.*", "cugraph-cu12==24.10.*"]
+rapids11 = ["cupy-cuda11x","cudf-cu11==24.12.*", "cuml-cu11==24.12.*", "cugraph-cu11==24.12.*"]
+rapids12 = ["cupy-cuda12x","cudf-cu12==24.12.*", "cuml-cu12==24.12.*", "cugraph-cu12==24.12.*"]
 doc = [
     "sphinx>=4.5.0",
     "sphinx-copybutton",