nashpy

library0.0.43pypypi✓ verified 21d ago

Nashpy is a Python library providing algorithms for computing Nash equilibria and analyzing 2-player games, including matrix games and repeated games. It is built on top of NumPy and SciPy for efficient numerical computation. Currently at version 0.0.43, the library maintains a frequent release cadence, typically with minor updates and bug fixes.

ai-ml data

pip install nashpy

github ↗package ↗

INSTALL

IMPORT

SIG · NASHPY

nashpy

ai-mlpythonv0.0.43

Install

8.9s avg

Import

1926ms

Disk

248MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.0.43 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 1.932s · 246.2MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 8.9s · import 1.920s · 237MB

248MB installed

● package 248MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

Game

✓ from nashpy import Game

✗ import nashpy as nash

This example demonstrates how to define a 2-player, 2-strategy game using NumPy arrays for payoff matrices and find its Nash equilibria using the `support_enumeration` algorithm.

import nashpy as nash import numpy as np # Define payoff matrices for player 1 (A) and player 2 (B) A = np.array([[3, 0], [5, 1]]) B = np.array([[3, 5], [0, 1]]) # Create a Nash game object game = nash.Game(A, B) # Compute Nash equilibria using support enumeration equilibria = game.support_enumeration() # Print the equilibria (mixed strategies for each player) print("Nash Equilibria:") for eq in equilibria: print(eq)

Debug

Known issues

gotchaPayoff matrices for `nashpy.Game` must be `numpy.ndarray` objects. Passing plain Python lists directly will result in a `TypeError` or unexpected behavior.

fix

Convert lists to `numpy.array()` before passing them to the `Game` constructor, e.g., `A = np.array([[1, 2], [3, 4]])`.

affects: All versions

breakingAs a `0.0.x` version library, Nashpy's API is subject to change without strict adherence to semantic versioning. Minor version updates (e.g., 0.0.42 to 0.0.43) may introduce breaking changes.

fix

Pin your `nashpy` version in `requirements.txt` or `pyproject.toml` to a specific patch version (e.g., `nashpy==0.0.43`) and review changelogs for updates before upgrading.

affects: All 0.0.x versions

gotchaSome algorithms, particularly `lemke_howson` and `lemke_howson_lex`, may struggle or fail to converge on degenerate games or games with specific numerical properties. The library's focus is on general case solution.

fix

Consult the documentation for specific algorithm limitations. If issues arise, consider slightly perturbing game matrices (if appropriate for your problem domain) or exploring alternative algorithms provided by Nashpy.

affects: Versions 0.0.38+

Upgrade

Version history

0.0.43latest on PyPI · released Nov 6, 2025

Audit

Dependencies

numpyrequiredCore dependency for numerical operations and matrix representation.

scipyrequiredUsed for optimization routines and other scientific computing tasks.

matplotliboptionalRequired for plotting functionalities and examples.

Agent activity

7 hits · last 30 days

node

Resources

githubhttps://github.com/drvinceknight/Nashpy ↗

packagehttps://pypi.org/project/nashpy/ ↗