rapids-singlecell: GPU-Accelerated Single-Cell Analysis within scverse®
rapids-singlecell provides GPU-accelerated single-cell analysis with an AnnData-first API. It is largely compatible with Scanpy and includes selected functionality from Squidpy, decoupler, and pertpy. Computations use CuPy and NVIDIA RAPIDS for performance on large datasets.
- GPU acceleration: Common single-cell workflows on
AnnDatarun on the GPU. - Ecosystem compatibility: Works with Scanpy APIs; includes pieces from Squidpy, decoupler, and pertpy.
- Simple installation: Available via Conda and PyPI.
Documentation
For more information please have a look through the documentation
Citation
If you use this tool, please cite:
Please cite the relevant tools if used: decoupler for decoupler functions, squidpy for spatial analysis, and pertpy for perturbation analysis.
rapids-singlecell is part of the scverse® project (website, governance) and is fiscally sponsored by NumFOCUS. If you like scverse® and want to support our mission, please consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.
Release files for rapids-singlecell-cu12 0.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distributions (wheels)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | CPython 3.12 | abi3 | Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 | Details |
| rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl | CPython 3.12 | abi3 | Linux glibc 2.28+ ARM64, Linux glibc 2.26+ ARM64 | Details |
Total release size: 66.4 MB
Release files / rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 33.3 MB |
| Tags | CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 abi3 |
|
SHA-256 checksum How to use checksums |
a66f5b42f39e6e348f3ac3757f423c887588338343ad4463cd15b1b65424df3a
|
|
BLAKE2b-256 checksum How to use checksums |
ea52edd4ab00a02517bdc5d2e4252528a6244db0167e4d07427fe5f5ebf0c9c6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency logRelease files / rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | rapids_singlecell_cu12-0.17.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
|---|---|
| Size | 33.1 MB |
| Tags | CPython 3.12 Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 abi3 |
|
SHA-256 checksum How to use checksums |
881f8949a9f484585a9207d9bac6f772492fb9d6a5ef5a30bebe4f8e37441908
|
|
BLAKE2b-256 checksum How to use checksums |
feef3402c7fb9b3a051e3e0a2e087b4d7b9fcb2f524790388349c2f3b09d5668
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 9, 2026.
Transparency log