{"library":"openmdao","title":"OpenMDAO","description":"OpenMDAO is an open-source high-performance computing framework for multidisciplinary analysis and optimization. It enables efficient decomposition of coupled systems into components, automatic differentiation, and parallel computing. Current version 3.43.0, requires Python >=3.10. Release cadence is approximately monthly.","language":"python","status":"active","last_verified":"Fri May 01","install":{"commands":["pip install openmdao","pip install openmdao[all]"],"cli":{"name":"openmdao","version":"3.43.0"}},"imports":["from openmdao.core.problem import Problem","from openmdao.core.indepvarcomp import IndepVarComp","from openmdao.core.explicitcomponent import ExplicitComponent"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"import openmdao.api as om\n\nprob = om.Problem()\nprob.model.add_subsystem('indep', om.IndepVarComp('x', 1.0), promotes=['x'])\nprob.model.add_subsystem('comp', om.ExecComp('y=x+1'), promotes=['*'])\nprob.setup()\nprob.run_model()\nprint(prob.get_val('y'))","lang":"python","description":"Minimal example: create a Problem, add an IndepVarComp and an ExecComp, run the model, and print output.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":null}