Introduction ============ What is OpenDP? --------------- `OpenDP`_ is a community effort to build trustworthy, open source software tools for statistical analysis of sensitive private data using `differential privacy`_. .. _OpenDP: https://opendp.org .. _differential privacy: https://opendp.org/about#whatisdifferentialprivacy Various tools build upon the `OpenDP library`_ and are known (along with the library itself) as the :doc:`/opendp-commons/index`. The OpenDP library and examples of these tools are shown in the diagram below. .. _OpenDP library: https://github.com/opendp/opendp |opendp-cake| .. |opendp-cake| image:: /_static/images/opendp-cake.svg :class: img-responsive Who Should Read This Guide? --------------------------- This guide is intended primarily for developers or data scientists who want to make programmatic use of the OpenDP library or its Python bindings. Data scientists and others who are more interested in a graphical user interface should review the offerings in the :doc:`/opendp-commons/index`. Potential contributors to OpenDP should read the :doc:`/developer/index`. Getting Help ------------ If you have questions or feedback regarding OpenDP, please feel free to post on `GitHub Discussions`_. .. _GitHub Discussions: https://github.com/opendp/opendp/discussions