{"id":28521200,"url":"https://github.com/farama-foundation/minari","last_synced_at":"2025-07-03T17:31:27.883Z","repository":{"id":62236481,"uuid":"546752231","full_name":"Farama-Foundation/Minari","owner":"Farama-Foundation","description":"A standard format for offline reinforcement learning datasets, with popular reference datasets and related utilities","archived":false,"fork":false,"pushed_at":"2025-05-26T14:56:16.000Z","size":2000455,"stargazers_count":395,"open_issues_count":16,"forks_count":57,"subscribers_count":11,"default_branch":"main","last_synced_at":"2025-06-09T07:56:19.071Z","etag":null,"topics":["datasets","gymnasium","offline-rl","reinforcement-learning"],"latest_commit_sha":null,"homepage":"https://minari.farama.org","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Farama-Foundation.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":".github/FUNDING.yml","license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.rst","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null},"funding":{"github":"Farama-Foundation"}},"created_at":"2022-10-06T15:30:24.000Z","updated_at":"2025-06-07T08:18:49.000Z","dependencies_parsed_at":"2023-10-23T20:35:12.314Z","dependency_job_id":"eea8c71b-05df-4677-8b0e-b444408d0891","html_url":"https://github.com/Farama-Foundation/Minari","commit_stats":{"total_commits":273,"total_committers":24,"mean_commits":11.375,"dds":0.5787545787545787,"last_synced_commit":"3e2dcc4c2feeaf892aca6f3d3719a94b5990346e"},"previous_names":[],"tags_count":13,"template":false,"template_full_name":null,"purl":"pkg:github/Farama-Foundation/Minari","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Farama-Foundation%2FMinari","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Farama-Foundation%2FMinari/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Farama-Foundation%2FMinari/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Farama-Foundation%2FMinari/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Farama-Foundation","download_url":"https://codeload.github.com/Farama-Foundation/Minari/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Farama-Foundation%2FMinari/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263369538,"owners_count":23456318,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["datasets","gymnasium","offline-rl","reinforcement-learning"],"created_at":"2025-06-09T07:34:50.723Z","updated_at":"2025-07-03T17:31:27.872Z","avatar_url":"https://github.com/Farama-Foundation.png","language":"Python","funding_links":["https://github.com/sponsors/Farama-Foundation"],"categories":[],"sub_categories":[],"readme":"[![build](https://github.com/Farama-Foundation/Minari/actions/workflows/build.yml/badge.svg)](https://github.com/Farama-Foundation/Minari/actions)\n[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit\u0026logoColor=white)](https://pre-commit.com/)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![release](https://img.shields.io/github/v/release/Farama-Foundation/Minari)](https://github.com/Farama-Foundation/Minari/releases)\n\n\n\u003cp align=\"center\"\u003e\n    \u003ca href = \"https://minari.farama.org/\" target= \"_blank\" \u003e \u003cimg src=\"minari-text.png\" width=\"500px\"/\u003e \u003c/a\u003e\n\u003c/p\u003e\n\nMinari is a Python library for conducting research in offline reinforcement learning, akin to an offline version of Gymnasium or an offline RL version of HuggingFace's datasets library.\n\nThe documentation website is at [minari.farama.org](https://minari.farama.org/main/). We also have a public discord server (which we use for Q\u0026A and to coordinate development work) that you can join here: https://discord.gg/bnJ6kubTg6.\n\n\n## Installation\nTo install Minari from [PyPI](https://pypi.org/project/minari/):\n```bash\npip install minari\n```\n\nThis will install the minimum required dependencies. Additional dependencies will be prompted for installation based on your use case. To install all dependencies at once, use:\n```bash\npip install \"minari[all]\"\n```\n\nIf you'd like to start testing or contribute to Minari please install this project from source with:\n\n```\ngit clone https://github.com/Farama-Foundation/Minari.git --single-branch\ncd Minari\npip install -e \".[all]\"\n```\n\n## Command Line API\n\nTo check available remote datasets:\n\n```bash\nminari list remote\n```\n\nTo download a dataset:\n\n```bash\nminari download D4RL/door/human-v2\n```\n\nTo check available local datasets:\n\n```bash\nminari list local\n```\nTo show the details of a dataset:\n\n```bash\nminari show D4RL/door/human-v2\n```\n\nFor the list of commands:\n```bash\nminari --help\n```\n\n## Basic Usage\n\n### Reading a Dataset\n\n```python\nimport minari\n\ndataset = minari.load_dataset(\"D4RL/door/human-v2\")\n\nfor episode_data in dataset.iterate_episodes():\n    observations = episode_data.observations\n    actions = episode_data.actions\n    rewards = episode_data.rewards\n    terminations = episode_data.terminations\n    truncations = episode_data.truncations\n    infos = episode_data.infos\n    ...\n```\n\n### Writing a Dataset\n\n```python\nimport minari\nimport gymnasium as gym\nfrom minari import DataCollector\n\n\nenv = gym.make('FrozenLake-v1')\nenv = DataCollector(env)\n\nfor _ in range(100):\n    env.reset()\n    done = False\n    while not done:\n        action = env.action_space.sample()  # \u003c- use your policy here\n        obs, rew, terminated, truncated, info = env.step(action)\n        done = terminated or truncated\n\ndataset = env.create_dataset(\"frozenlake/test-v0\")\n```\n\nFor other examples, see [Basic Usage](https://minari.farama.org/main/content/basic_usage/). For a complete tutorial on how to create new datasets using Minari, see our [Pointmaze D4RL Dataset](https://minari.farama.org/main/tutorials/dataset_creation/point_maze_dataset/) tutorial, which re-creates the Maze2D datasets from [D4RL](https://github.com/Farama-Foundation/D4RL).\n\n## Training Libraries Integrating Minari\n\n - [TorchRL](https://github.com/pytorch/rl)\n - [d3rlpy](https://github.com/takuseno/d3rlpy)\n - [AgileRL](https://github.com/AgileRL/AgileRL)\n\n\n## Citation\nIf you use Minari, please consider citing it:\n\n```\n@software{minari,\n\tauthor = {Younis, Omar G. and Perez-Vicente, Rodrigo and Balis, John U. and Dudley, Will and Davey, Alex and Terry, Jordan K},\n\tdoi = {10.5281/zenodo.13767625},\n\tmonth = sep,\n\tpublisher = {Zenodo},\n\ttitle = {Minari},\n\turl = {https://doi.org/10.5281/zenodo.13767625},\n\tversion = {0.5.0},\n\tyear = 2024,\n\tbdsk-url-1 = {https://doi.org/10.5281/zenodo.13767625}\n}\n```\n\n\n\n___\n\n_Minari is a shortening of Minarai, the Japanese word for \"learning by observation\"._\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarama-foundation%2Fminari","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffarama-foundation%2Fminari","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffarama-foundation%2Fminari/lists"}