npstreams works on Linux, Mac OS X and Windows. It requires Python 3.7+ as well as numpy. scipy is an optional dependency that is only used in tests; however, if SciPy cannot be imported, tests will not fail.
To get access to the
npstreams.cuda module, which contains CUDA-enabled routines,
PyCUDA must be installed as well.
npstreams is available on PyPI; it can be installed with pip:
python -m pip install npstreams
npstreams can also be installed with the conda package manager, from the conda-forge channel:
conda config --add channels conda-forge conda install npstreams
You can install the latest developer version of npstreams by cloning the git repository:
git clone https://github.com/LaurentRDC/npstreams.git
…then installing the package with:
cd npstreams python setup.py install
If you want to check that all the tests are running correctly with your Python configuration, type:
python setup.py test
Embedding in applications¶
npstreams is designed to be used in conjuction with multiprocessing libraries, such as the standard multiprocessing library. npstreams even uses multiprocessing directly in certain functions.
In order to use the multicore functionality of npstreams in applications frozen with py2exe, PyInstaller, or cx_Freeze,
you will need to activate the
multiprocessing.freeze_support() function. You can read more
about it here.