Installation

Windows

pySigLib requires an installation of the MSVC compiler in order to compile the package. Please ensure this exists, then run:

pip install pysiglib

pySigLib will automatically detect CUDA, provided the CUDA_PATH environment variable is set correctly. To manually disable CUDA and build pySigLib for CPU only, create an environment variable CUSIG and set it to 0:

set CUSIG=0
pip install pysiglib

Similarly, the package will automatically detect if AVX2 instructions are supported. To disable these manually, create an environment variable SIGLIB_VEC and set it to 0:

set SIGLIB_VEC=0
pip install pysiglib

Linux

pySigLib requires an installation of the GCC compiler in order to compile the package. Please ensure this exists, then run:

pip install pysiglib

pySigLib will automatically detect CUDA, provided the CUDA_PATH environment variable is set correctly.

Typically:

export CUDA_PATH=/usr/lib/nvidia-cuda-toolkit

To manually disable CUDA and build pySigLib for CPU only, create an environment variable CUSIG and set it to 0:

export CUSIG=0
pip install pysiglib

Similarly, the package will automatically detect if AVX2 instructions are supported. To disable these manually, create an environment variable SIGLIB_VEC and set it to 0:

export SIGLIB_VEC=0
pip install pysiglib

MacOS

pySigLib requires an installation of the GCC compiler in order to compile the package. Please ensure this exists, then run:

pip install pysiglib

pySigLib does not support CUDA or AVX2 instructions on MacOS, and will build without them when installed.

Citation

If you found this library useful in your research, please consider citing the paper:

@article{shmelev2025pysiglib,
  title={pySigLib-Fast Signature-Based Computations on CPU and GPU},
  author={Shmelev, Daniil and Salvi, Cristopher},
  journal={arXiv preprint arXiv:2509.10613},
  year={2025}
}