{"categories":[{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics"}],"enrichment":{"capability":"Nashpy computes Nash equilibria and simulates strategic interactions in two-player games using algorithms like support enumeration, vertex enumeration, Lemke-Howson, fictitious play, and replicator dynamics.","skillfed_tags":["game-theory","equilibrium-computation","educational"],"use_cases":["Teaching game theory: use the documented algorithms and examples to illustrate Nash equilibria and strategic reasoning.","Computing equilibria in two-player games: solve for mixed and pure strategy equilibria in bimatrix games.","Simulating evolutionary game dynamics: model population-level strategy evolution using replicator dynamics or Moran processes.","Analyzing repeated games: generate and analyze games derived from repeated interactions.","Research in game-theoretic modeling: implement custom game-theoretic analyses with built-in algorithm support."],"what_it_does":"Nashpy is a Python library for analyzing two-player strategic games. It implements a range of algorithms to find Nash equilibria\u2014the stable strategy profiles where neither player can improve by unilaterally changing their strategy\u2014and to simulate evolutionary dynamics like fictitious play and replicator dynamics. The library is built on numpy, scipy, and networkx, making it suitable for both teaching game theory and conducting research.\n\nYou define a game by providing two payoff matrices (one for each player), then call methods to compute equilibria or run simulations. The library includes support enumeration, vertex enumeration, the Lemke-Howson algorithm, fictitious play variants, replicator dynamics with and without mutation, Moran processes on interaction and replication graphs, and introspection dynamics. It is well-documented with both theory and how-to guides.","worth_installing":"Yes, if you work with two-player game theory. Nashpy has low install friction, permissive licensing, no known vulnerabilities, and comprehensive algorithm coverage with good documentation. The aging maintenance status (281 days since last release) is a minor concern for a stable library but worth monitoring if you need active development or bug fixes."},"id":"nashpy","links":{"html":"https://skillfed.io/packages/nashpy","md":"https://skillfed.io/packages/nashpy.md","pypi":"https://pypi.org/project/nashpy/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-11-06","license_spdx":null,"license_treatment":"permissive","name":"nashpy","python_support":"supports_current","summary":"A library with algorithms on 2 player games."},"popularity":{"monthly_downloads":3603610,"position":2562,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.0.43"}