{"id":13512823,"url":"https://github.com/brainpy/BrainPy","last_synced_at":"2025-03-31T00:30:47.740Z","repository":{"id":38384389,"uuid":"280029226","full_name":"brainpy/BrainPy","owner":"brainpy","description":"Brain Dynamics Programming in Python","archived":false,"fork":false,"pushed_at":"2025-01-26T04:31:34.000Z","size":96631,"stargazers_count":561,"open_issues_count":38,"forks_count":95,"subscribers_count":13,"default_branch":"master","last_synced_at":"2025-02-04T09:38:00.619Z","etag":null,"topics":["brain-dynamics-modeling","brain-inspired-computing","brain-simulations","brainpy","spiking-neural-networks"],"latest_commit_sha":null,"homepage":"https://brainpy.readthedocs.io/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/brainpy.png","metadata":{"files":{"readme":"README.md","changelog":"changes.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2020-07-16T02:11:23.000Z","updated_at":"2025-02-02T14:47:02.000Z","dependencies_parsed_at":"2023-02-15T20:31:28.937Z","dependency_job_id":"f46ac95f-64a3-47fa-ad0a-eb20ef1e593c","html_url":"https://github.com/brainpy/BrainPy","commit_stats":{"total_commits":2704,"total_committers":25,"mean_commits":108.16,"dds":0.591715976331361,"last_synced_commit":"e849a9a8e0ac4a6fb58e5da9679e82991f0c7595"},"previous_names":["pku-nip-lab/brainpy","pku-nip-lab/numpybrain"],"tags_count":40,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brainpy%2FBrainPy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brainpy%2FBrainPy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brainpy%2FBrainPy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/brainpy%2FBrainPy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/brainpy","download_url":"https://codeload.github.com/brainpy/BrainPy/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246399816,"owners_count":20770907,"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":["brain-dynamics-modeling","brain-inspired-computing","brain-simulations","brainpy","spiking-neural-networks"],"created_at":"2024-08-01T04:00:33.086Z","updated_at":"2025-03-31T00:30:42.684Z","avatar_url":"https://github.com/brainpy.png","language":"Python","funding_links":[],"categories":["Jupyter Notebook","Python","Libraries","Package","Computational Neuroscience Software"],"sub_categories":["New Libraries","Computational Neuroscience"],"readme":"\u003cp align=\"center\"\u003e\n  \t\u003cimg alt=\"Header image of BrainPy - brain dynamics programming in Python.\" src=\"https://github.com/brainpy/BrainPy/blob/master/images/logo.png\" width=80%\u003e\n\u003c/p\u003e \n\n\n\n\u003cp align=\"center\"\u003e\n\t\u003ca href=\"https://pypi.org/project/brainpy/\"\u003e\u003cimg alt=\"Supported Python Version\" src=\"https://img.shields.io/pypi/pyversions/brainpy\"\u003e\u003c/a\u003e\n\t\u003ca href=\"https://github.com/brainpy/BrainPy\"\u003e\u003cimg alt=\"LICENSE\" src=\"https://anaconda.org/brainpy/brainpy/badges/license.svg\"\u003e\u003c/a\u003e\n  \t\u003ca href=\"https://brainpy.readthedocs.io/en/latest/?badge=latest\"\u003e\u003cimg alt=\"Documentation\" src=\"https://readthedocs.org/projects/brainpy/badge/?version=latest\"\u003e\u003c/a\u003e\n  \t\u003ca href=\"https://badge.fury.io/py/brainpy\"\u003e\u003cimg alt=\"PyPI version\" src=\"https://badge.fury.io/py/brainpy.svg\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/brainpy/BrainPy/actions/workflows/CI.yml\"\u003e\u003cimg alt=\"Continuous Integration\" src=\"https://github.com/brainpy/BrainPy/actions/workflows/CI.yml/badge.svg\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/brainpy/BrainPy/actions/workflows/CI-models.yml\"\u003e\u003cimg alt=\"Continuous Integration with Models\" src=\"https://github.com/brainpy/BrainPy/actions/workflows/CI-models.yml/badge.svg\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\nBrainPy is a flexible, efficient, and extensible framework for computational neuroscience and brain-inspired computation based on the Just-In-Time (JIT) compilation (built on top of [JAX](https://github.com/google/jax), [Taichi](https://github.com/taichi-dev/taichi), [Numba](https://github.com/numba/numba), and others). It provides an integrative ecosystem for brain dynamics programming, including brain dynamics **building**, **simulation**, **training**, **analysis**, etc. \n\n- **Website (documentation and APIs)**: https://brainpy.readthedocs.io/en/latest\n- **Source**: https://github.com/brainpy/BrainPy\n- **Bug reports**: https://github.com/brainpy/BrainPy/issues\n- **Source on OpenI**: https://git.openi.org.cn/OpenI/BrainPy\n\n\n\n## Installation\n\nBrainPy is based on Python (\u003e=3.8) and can be installed on Linux (Ubuntu 16.04 or later), macOS (10.12 or later), and Windows platforms. \n\nFor detailed installation instructions, please refer to the documentation: [Quickstart/Installation](https://brainpy.readthedocs.io/en/latest/quickstart/installation.html)\n\n\n### Using BrainPy with docker\n\nWe provide a docker image for BrainPy. You can use the following command to pull the image:\n```bash\n$ docker pull brainpy/brainpy:latest\n```\n\nThen, you can run the image with the following command:\n```bash\n$ docker run -it --platform linux/amd64 brainpy/brainpy:latest\n```\n\n\n### Using BrainPy with Binder\n\nWe provide a Binder environment for BrainPy. You can use the following button to launch the environment:\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/brainpy/BrainPy-binder/main)\n\n\n## Ecosystem\n\n- **[BrainPy](https://github.com/brainpy/BrainPy)**: The solution for the general-purpose brain dynamics programming. \n- **[brainpy-examples](https://github.com/brainpy/examples)**: Comprehensive examples of BrainPy computation. \n- **[brainpy-datasets](https://github.com/brainpy/datasets)**: Neuromorphic and Cognitive Datasets for Brain Dynamics Modeling.\n- [《神经计算建模实战》 (Neural Modeling in Action)](https://github.com/c-xy17/NeuralModeling)\n- [第一届神经计算建模与编程培训班 (First Training Course on Neural Modeling and Programming)](https://github.com/brainpy/1st-neural-modeling-and-programming-course)\n- [第二届神经计算建模与编程培训班 (Second Training Course on Neural Modeling and Programming)](https://github.com/brainpy/2nd-neural-modeling-and-programming-course)\n\n\n## Citing \n\nBrainPy is developed by a team in Neural Information Processing Lab at Peking University, China. \nOur team is committed to the long-term maintenance and development of the project. \n\nIf you are using ``brainpy``, please consider citing [the corresponding papers](https://brainpy.readthedocs.io/en/latest/tutorial_FAQs/citing_and_publication.html). \n\n\n\n## Ongoing development plans\n\nWe highlight the key features and functionalities that are currently under active development. \n\nWe also welcome your contributions \n(see [Contributing to BrainPy](https://brainpy.readthedocs.io/en/latest/tutorial_advanced/contributing.html)). \n\n- [x] model and data parallelization on multiple devices for dense connection models\n- [ ] model parallelization on multiple devices for sparse spiking network models\n- [ ] data parallelization on multiple devices for sparse spiking network models\n- [ ] pipeline parallelization on multiple devices for sparse spiking network models\n- [ ] multi-compartment modeling\n- [ ] measurements, analysis, and visualization methods for large-scale spiking data\n- [ ] Online learning methods for large-scale spiking network models\n- [ ] Classical plasticity rules for large-scale spiking network models\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrainpy%2FBrainPy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbrainpy%2FBrainPy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbrainpy%2FBrainPy/lists"}