{"library":"optimistix","type":"library","category":null,"description":"Optimistix is a JAX library for nonlinear solvers, including root finding, minimisation, fixed points, and least squares. It features highly modular optimisers, interoperable solvers (e.g., converting root find problems to least squares), PyTree-based state management, fast compilation and runtimes, and deep integration with the JAX ecosystem for features like autodiff, autoparallelism, and GPU/TPU support. As of version 0.1.0, it requires Python 3.11+ and is under active, rapid development with frequent updates.","language":"python","status":"active","version":"0.1.0","tags":["JAX","optimization","nonlinear-solvers","root-finding","minimization","least-squares","fixed-point-iteration","scientific-computing","numerical-methods","equinox"],"install":[{"cmd":"pip install optimistix","imports":["import optimistix as optx","import jax.numpy as jnp","import equinox as eqx"]}],"homepage":"https://docs.kidger.site/optimistix","github":"https://github.com/patrick-kidger/optimistix","docs":null,"changelog":null,"pypi":"https://pypi.org/project/optimistix/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":12.4,"avg_import_s":3.72,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/optimistix/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}