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Status](https://github.com/dbbs-lab/bsb/actions/workflows/main.yml/badge.svg)\n[![codecov](https://codecov.io/gh/dbbs-lab/bsb/graph/badge.svg?token=9b20cUHwzX)](https://codecov.io/gh/dbbs-lab/bsb)\n[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)\n\nDeveloped by the Department of Brain and Behavioral Sciences at the University of Pavia, the Brain Scaffold Builder (\nBSB) is a component framework for neural modeling. It emphasizes modular component declarations to assemble brain\nmodels, supporting various configuration languages and Python library functions. BSB facilitates parallel reconstruction\nand simulation of diverse network topologies, placements, and connectivity strategies.\n\n## Monorepo Structure\n\nThe BSB suite is now organized as a monorepo, integrating the following components:\n\n* **bsb-core**: The foundational framework of BSB.\n* **bsb-hdf5**: Storage engine for saving models in HDF5 format.\n* **bsb-json**: Parser for reading and writing JSON configuration files.\n* **bsb-yaml**: Parser for reading and writing YAML configuration files.\n* **bsb-nest**: Simulation interface for point-neuron networks using the NEST simulator.\n* **bsb-neuron**: Simulation interface for detailed neuron networks using the NEURON simulator.\n* **bsb-arbor**: Simulation interface for detailed neuron networks using the ARBOR simulator.\n* **nmodl-glia**: An NMODL asset manager.\n* **nrn-patch**: Utility layer to reduce friction when working with NEURON in Python.\n* **arborize**: Tool for Arbor-like descriptions of cell models for NEURON and Arbor.\n* **bsb-test**: Tools and configurations for testing BSB components.\n* **sphinxext-bsb**: Sphinx extension for BSB documentation.\n\n## Documentation\n\nComprehensive documentation is available at:\n\n* [BSB Documentation](https://bsb.readthedocs.io/en/latest)\n\n## Installation\n\n### Pip installation\n\nThe BSB supports Python 3.10 and above. To install the BSB suite along with the core framework and default plugins:\n\n```bash\npip install bsb\n```\n\nFor advanced users desiring a custom combination of plugins, install `bsb-core` and the desired plugins separately:\n\n```bash\npip install bsb-core\npip install bsb-hdf5 bsb-json bsb-yaml\n```\n\nTo include simulation support for NEST, NEURON, or ARBOR:\n\n```bash\npip install bsb[nest]\npip install bsb[neuron]\npip install bsb[arbor]\n```\n\n### Clone installation\n\nYou can also clone the repository and use the devtools script to install all packages in editable mode \nin your own environment:\n\n```bash\ngit clone https://github.com/dbbs-lab/bsb\ncd bsb\npip install -r devtools/editable-install.txt\n```\n\n### Developer installation\n\nFor development purposes, you should install the [UV](https://docs.astral.sh/uv/) and [NX](https://nx.dev/) tools.\nTo this end, there is a helper script for each platform in ``devtools/bootstrap-*``. For instance, for linux:\n\n```bash\ngit clone https://github.com/dbbs-lab/bsb\ncd bsb\n./devtools/bootstrap-linux.sh\n```\n\n\nFrom there, you NX and UV will automatically create an environment for each subpackage, \nincluding all necessary libraries for running the unittests, linting the code and building the documentation.\n\nFor more information, please refer to the [developers' documentation](https://bsb.readthedocs.io/en/latest/dev/dev-toc.html).\n\n## Usage\n\nTo create a new BSB project:\n\n```bash\nbsb new my_model --quickstart\ncd my_model\n```\n\nThis command generates a `my_model` directory with starter files:\n\n* `network_configuration.yaml`: Defines the network configuration.\n* `pyproject.toml`: Contains project metadata and configuration.\n* `placement.py` and `connectome.py`: Custom components for network placement and connectivity.\n\nTo compile the network:\n\n```bash\nbsb compile\n```\n\nFor simulation, refer to the documentation for configuring simulations with NEST, NEURON, or ARBOR.\n\n## Contributing\n\nAll contributions are very much welcome.\nTake a look at the [contribution guide](CONTRIBUTING.md)\n\n## Acknowledgements\n\nThis research has received funding from the European Union’s Horizon 2020 Framework Program for Research and Innovation\nunder the Specific Grant Agreements No. 945539 (Human Brain Project SGA3) and No. 785907 (Human Brain Project SGA2), as\nwell as from the Centro Fermi project “Local Neuronal Microcircuits” to ED. The project also receives funding from the\nVirtual Brain Twin Project under the European Union's Horizon Europe program under grant agreement No. 101137289.\n\nWe acknowledge the use of the EBRAINS platform and Fenix Infrastructure resources, which are partially funded by the\nEuropean Union’s Horizon 2020 research and innovation program under the Specific Grant Agreement No. 101147319 (EBRAINS\n2.0 Project) and through the ICEI project under grant agreement No. 800858, respectively.\n\n## Supported by\n\n[![JetBrains logo](https://resources.jetbrains.com/storage/products/company/brand/logos/jetbrains.svg)](https://jb.gg/OpenSourceSupport)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdbbs-lab%2Fbsb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdbbs-lab%2Fbsb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdbbs-lab%2Fbsb/lists"}