{"library":"ray","type":"library","category":null,"description":"Ray is a unified open-source framework for building and scaling distributed applications and AI workloads in Python. It provides simple APIs for parallelizing Python functions and classes (tasks and actors) and a toolkit of specialized libraries (Ray Data, Train, Tune, Serve, RLlib) for machine learning. Ray offers a universal compute layer for orchestrating clusters, scheduling processes, fault tolerance, and autoscaling. The project maintains a very frequent release cadence, with minor and patch releases occurring every few weeks.","language":"python","status":"active","version":"2.54.1","tags":["distributed-computing","machine-learning","deep-learning","data-processing","scalability","ai-runtime","parallel-computing"],"install":[{"cmd":"pip install ray","imports":["import ray","@ray.remote"]},{"cmd":"pip install \"ray[data,train,tune,serve,rllib]\"","imports":[]}],"homepage":"https://ray.io","github":"https://github.com/ray-project/ray","docs":null,"changelog":null,"pypi":"https://pypi.org/project/ray/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":20.9,"avg_import_s":1.72,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/ray/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":"draft"}}