Danger You are looking at the documentation for an older version of the SDV! We are no longer supporting or maintaining this version of the software Click here to go to the new docs pages.
Danger
You are looking at the documentation for an older version of the SDV! We are no longer supporting or maintaining this version of the software
Click here to go to the new docs pages.
SDV has been tested and is supported on GNU/Linux, macOS and Windows systems running Python 3.6, 3.7 and 3.8 installed.
Also, although it is not strictly required, the usage of a virtualenv is highly recommended in order to avoid having conflicts with other software installed in the system where SDV is run.
The easiest and recommended way to install SDV is using pip:
pip install sdv
This will pull and install the latest stable release from PyPI.
Warning
When installing on windows systems, pip may complain about not being able to find a valid version for PyTorch. In this case, please install PyTorch manually following the PyTorch installation instructions and retry installing sdv again afterwards.
PyTorch
sdv
This is also the case if you plan on using a GPU. Since the CUDA version requirements depend on the what PyTorch version you have, you should first install PyTorch using their website and only then install sdv.
CUDA
The source code of SDV can be downloaded from the Github repository
You can clone the repository and install with the following command in your terminal:
You can clone the repository and install it from source by running make install on the stable branch:
make install
stable
git clone git://github.com/sdv-dev/SDV cd SDV git checkout stable make install
Note
The master branch of the SDV repository contains the latest development version. If you want to install the latest stable version, make sure not to omit the git checkout stable indicated above.
master
git checkout stable
If you are installing SDV in order to modify its code, the installation must be done from its sources, in the editable mode, and also including some additional dependencies in order to be able to run the tests and build the documentation. Instructions about this process can be found in the Contributing to SDV guide.