{"id":20377792,"url":"https://github.com/teddygroves/bibat","last_synced_at":"2025-07-28T09:36:40.004Z","repository":{"id":42973272,"uuid":"344553551","full_name":"teddygroves/bibat","owner":"teddygroves","description":"A batteries-included template for Bayesian data analysis projects","archived":false,"fork":false,"pushed_at":"2024-04-10T12:37:41.000Z","size":39015,"stargazers_count":21,"open_issues_count":13,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-12T07:52:03.020Z","etag":null,"topics":["arviz","bayesian-statistics","cmdstanpy","cookiecutter","mcmc","python","stan","template-project"],"latest_commit_sha":null,"homepage":"https://bibat.readthedocs.io/","language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/teddygroves.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2021-03-04T17:22:11.000Z","updated_at":"2025-03-02T20:41:35.000Z","dependencies_parsed_at":"2023-12-21T16:44:14.753Z","dependency_job_id":"6d63bd56-c56d-4e61-a68d-4bd33afaa9bd","html_url":"https://github.com/teddygroves/bibat","commit_stats":{"total_commits":455,"total_committers":1,"mean_commits":455.0,"dds":0.0,"last_synced_commit":"edf803c28e184b9a0dae6fbf13e40caf1801ed54"},"previous_names":[],"tags_count":34,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teddygroves%2Fbibat","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teddygroves%2Fbibat/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teddygroves%2Fbibat/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/teddygroves%2Fbibat/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/teddygroves","download_url":"https://codeload.github.com/teddygroves/bibat/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248537033,"owners_count":21120690,"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":["arviz","bayesian-statistics","cmdstanpy","cookiecutter","mcmc","python","stan","template-project"],"created_at":"2024-11-15T01:46:30.100Z","updated_at":"2025-04-12T07:52:10.941Z","avatar_url":"https://github.com/teddygroves.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bibat: Batteries-Included Bayesian Analysis Template\n\n[![](https://zenodo.org/badge/344553551.svg)](https://zenodo.org/badge/latestdoi/344553551)\n[![Documentation Status](https://readthedocs.org/projects/bibat/badge/?version=latest)](https://bibat.readthedocs.io/en/latest/?badge=latest)\n[![Tox](https://github.com/teddygroves/bibat/actions/workflows/run_tox.yml/badge.svg)](https://github.com/teddygroves/bibat/actions/workflows/run_tox.yml)\n[![Test end-to-end](https://github.com/teddygroves/bibat/actions/workflows/test_end_to_end.yml/badge.svg)](https://github.com/teddygroves/bibat/actions/workflows/test_end_to_end.yml)\n[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![Supported Python versions: 3.11 and newer](https://img.shields.io/badge/python-\u003e=3.11-blue.svg)](https://www.python.org/)\n[![](https://badge.fury.io/py/bibat.svg)](https://badge.fury.io/py/bibat)\n[![](https://codecov.io/github/teddygroves/bibat/branch/main/graph/badge.svg?token=ck0IKyzP7J)](https://codecov.io/github/teddygroves/bibat)\n[![pyOpenSci](https://tinyurl.com/y22nb8up)](https://github.com/pyOpenSci/software-review/issues/83)\n\nBibat is a Python package providing a flexible interactive template for Bayesian\nstatistical analysis projects.\n\nIt aims to make it easier to create software projects that implement a Bayesian\nworkflow that scales to arbitrarily many inter-related statistical models, data\ntransformations, inferences and computations. Bibat also aims to promote\nsoftware quality by providing a modular, automated and reproducible project that\ntakes advantage of and integrates together the most up to date statistical\nsoftware.\n\nBibat comes with \"batteries included\" in the sense that it creates a working\nexample project, which the user can adapt so that it implements their desired\nanalysis. We believe this style of template makes for better usability and\neasier testing of Bayesian workflow projects compared with the alternative\napproach of providing an incomplete skeleton project.\n\n## Documentation\n\nCheck out bibat's documentation at \u003chttps://bibat.readthedocs.io\u003e.\n\nIn particular, you may find it useful to have a look at [this vignette](https:// bibat.readthedocs.io/en/latest/_static/report.html) that demonstrates, step by\nstep, how to use bibat to implement a complex statistical analysis.\n\n## How to use bibat\n\nTo start a Bayesian statistical analysis project using bibat, first install [copier](https://copier.readthedocs.io), for example like this:\n\n```sh\n$ pipx install copier\n```\n\nNow choose a directory name for your analysis, for example `my_cool_project`,\nand copy bibat's example project there:\n\n```sh\n$ copier copy gh:teddygroves/bibat my_cool_project\n```\n\nThis will trigger an interactive questionnaire and then create a brand\nnew, custom, batteries-included, Bayesian analysis project in the directory\n`my_cool_project`. See [bibat's documentation](https://bibat.readthedocs.io) for\nwhat to do next.\n\nIf you want to use bibat's Python code separately from the template, you can\ninstall it to your python environment as follows:\n\n```sh\n$ pip install bibat\n```\n\nTo install bibat with development dependencies:\n\n```sh\n$ pip install bibat'[development]'\n```\n\n## Dependencies\n\nBibat requires Python version 3.11 or greater.\n\nBibat's Python dependencies can be found in its [pyproject.toml file](https://github.com/teddygroves/bibat/blob/main/pyproject.toml).\n\nBibat's Python dependencies:\n\n- arviz\n- cmdstanpy\n- copier\n- numpy\n- pandas\n- pandera\n- pydantic\n- scikit-learn\n- stanio\n- toml\n- xarray\n- zarr\n\nBibat's development dependencies (install these by running `pip install\nbibat'[development]'`):\n\n- black\n- pre-commit\n- codecov\n- mkdocs\n- mkdocs-material\n- mkdocstrings\n- mkdocstrings-python\n- pymdown-extensions\n- pytest\n- pytest-cov\n- tox\n- ruff\n\nProjects created by bibat have Python dependencies listed in their [pyproject.toml file](https://github.com/teddygroves/bibat/blob/main/template/pyproject.toml.jinja). The additional ones are as follows:\n\n- bibat\n- jupyter\n\nIn addition, the following Python packages may be installed, depending on how\nthe user answers bibat's questionnaire:\n\n- sphinx\n\nBibat projects also depend on [cmdstan](https://mc-stan.org/docs/cmdstan-guide/index.html), the command line\ninterface to Stan. Bibat projects include code that installs cmdstan when you\nrun the command `make analysis` from the root of the target project. To only install dependencies, you can also run the command `make env`.\n\nIf bibat fails to install cmdstan, please raise an issue! The relevant\nparts of the [cmdstan](https://mc-stan.org/docs/cmdstan-guide/cmdstan-installation.html) and\n[cmdstanpy](https://cmdstanpy.readthedocs.io/en/v1.1.0/installation.html#cmdstan-installation)\ndocumentation might also be useful.\n\n### Target project dependencies: Quarto\n\nBibat supports automatic generation of documentation using either Sphinx or\n[Quarto](https://quarto.org/). Whereas bibat will install Sphinx\nautomatically, Quarto must be installed manually: see the [quarto\ndocumentation](https://quarto.org/docs/get-started/) for instructions.\n\n## Citation information\n\nIf you would like to cite bibat using bibtex please use the following format:\n\n\n```sh\n  @software{bibat,\n    doi = {10.5281/zenodo.7775328},\n    url = {https://github.com/teddygroves/bibat},\n    year = {2023},\n    author = {Teddy Groves},\n    title = {Bibat: batteries-included Bayesian analysis template},\n  }\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fteddygroves%2Fbibat","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fteddygroves%2Fbibat","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fteddygroves%2Fbibat/lists"}