Scikit-Sparse (sksparse)
The scikit-sparse package is a companion to the scipy.sparse package for sparse matrix manipulation in Python. It provides routines that are not suitable for inclusion in scipy.sparse proper, typically because they depend on external libraries with GPL licenses, such as SuiteSparse.
For more details on usage see the docs. To upgrade from scikit-sparse v0.4.16 to v0.5.0, see Upgrading to v0.5.0.
Requirements
Installing scikit-sparse requires:
Python >= 3.10
NumPy >= 2.0
SciPy >= 1.14
Cython >= 3.0
SuiteSparse >= 7.4.0
Older versions may work but are untested.
Installation
Installing SuiteSparse
To install scikit-sparse, you need to have the SuiteSparse library installed on your system.
It is recommended that you install SuiteSparse and the scikit-sparse dependencies in a virtual environment, to avoid conflicts with other packages. We recommend using Anaconda:
$ conda create -n scikit-sparse python>=3.10 suitesparse $ conda activate scikit-sparse
If you are not using Anaconda, you can install SuiteSparse using your preferred package manager.
On MacOS, you can use Homebrew:
$ brew install suite-sparse
On Debian/Ubuntu systems, use the following command:
$ sudo apt-get install python-scipy libsuitesparse-dev
On Arch Linux, run:
$ sudo pacman -S suitesparse
Installing Scikit-Sparse
Once you have SuiteSparse installed, you can install scikit-sparse with:
$ conda install -c conda-forge scikit-sparse
or if you prefer to use pip, you can install it with:
$ pip install scikit-sparse
Check if the installation was successful by running the following command:
$ python -c "import sksparse; print(sksparse.__version__)"
See Troubleshooting for more information on determining which SuiteSparse library is being used.
Copyright © 2009–2025, the scikit-sparse developers.
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