.. _pygambit:


PyGambit
========

The Gambit Python package, ``pygambit``, is available on `PyPI <https://pypi.org/project/pygambit/>`_ and can be installed with pip::

   pip install pygambit


For newcomers to Gambit, we recommend reading through the PyGambit tutorials, which demonstrate the API's key capabilities for analyzing and solving Game Theory games.
These tutorials are available to be run interactively as Jupyter notebooks, see :ref:`local_tutorials`.
All of the tutorials assume a basic knowledge of programming in Python.

Tutorials **1-3** assume no prior knowledge of Game Theory or the PyGambit API and provide detailed explanations of the concepts and code.

.. toctree::
   :maxdepth: 2

   tutorials/01_quickstart
   tutorials/02_extensive_form
   tutorials/03_poker

Tutorials **4-5** assume some familiarity with the PyGambit API and Game Theory terminology and concepts including:

- Nash equilibria
- Pure and mixed strategies
- Simplex representations of available strategies
- Logit quantal response equilibrium (LQRE) correspondence

.. toctree::
   :maxdepth: 2

   tutorials/04_starting_points
   tutorials/05_quantal_response

You may also wish to read:

.. toctree::
   :maxdepth: 2

   tutorials/running_locally
   pygambit.external_programs

Algorithms for computing Nash equilibria
----------------------------------------

Interfaces to algorithms for computing Nash equilibria are provided in :py:mod:`pygambit.nash`.
The table below summarizes the available PyGambit functions and the corresponding Gambit CLI commands.

==========================================    ========================================
CLI command                                   PyGambit function
==========================================    ========================================
:ref:`gambit-enumpure <gambit-enumpure>`      :py:func:`pygambit.nash.enumpure_solve`
:ref:`gambit-enummixed <gambit-enummixed>`    :py:func:`pygambit.nash.enummixed_solve`
:ref:`gambit-lp <gambit-lp>`                  :py:func:`pygambit.nash.lp_solve`
:ref:`gambit-lcp <gambit-lcp>`                :py:func:`pygambit.nash.lcp_solve`
:ref:`gambit-liap <gambit-liap>`              :py:func:`pygambit.nash.liap_solve`
:ref:`gambit-logit <gambit-logit>`            :py:func:`pygambit.nash.logit_solve`
:ref:`gambit-simpdiv <gambit-simpdiv>`        :py:func:`pygambit.nash.simpdiv_solve`
:ref:`gambit-ipa <gambit-ipa>`                :py:func:`pygambit.nash.ipa_solve`
:ref:`gambit-gnm <gambit-gnm>`                :py:func:`pygambit.nash.gnm_solve`
==========================================    ========================================

API documentation
----------------

.. toctree::
   :maxdepth: 2

   pygambit.api