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Installing SDGym

Install with pip

The easiest and recommended way to install SDGym is using pip:

pip install sdgym

This will pull and install the latest stable release from PyPi.

Install with conda

SDGym can also be installed using conda:

conda install -c sdv-dev -c conda-forge sdgym

This will pull and install the latest stable release from Anaconda.

Install from source

If you want to install SDGym from source you need to first clone the repository and then execute the make install command inside the stable branch. Note that this command works only on Unix based systems like GNU/Linux and macOS:

git clone https://github.com/sdv-dev/SDGym
cd SDGym
git checkout stable
make install

Install for development

If you intend to modify the source code or contribute to the project you will need to install it from the source using the make install-develop command. In this case, we recommend you to branch from master first:

git clone git@github.com:sdv-dev/SDGym
cd SDGym
git checkout master
git checkout -b <your-branch-name>
make install-develp

For more details about how to contribute to the project please visit the Contributing Guide.

Compile C++ dependencies

Some of the third party synthesizers that SDGym offers, like the PrivBN, require dependencies written in C++ that need to be compiled before they can be used.

In order to be able to use them, please do:

  1. Clone or download the SDGym repository to your local machine:

git clone git@github.com:sdv-dev/SDGym.git
cd SDGym

  1. make sure to have installed all the necessary dependencies to compile C++. In Linux distributions based on Ubuntu, this can be done with the following command:

sudo apt-get install build-essential

  1. Trigger the C++ compilation:

make compile

  1. Add the path to the created privBayes.bin binary to the PRIVBAYES_BIN environment variable:

export PRIVBAYES_BIN=$(pwd)/privBayes.bin

Run with Docker

We support using Docker to run SDGym. For more information on how to do so, check Running on Docker.

Benchmarking Framework Running on Docker