{"id":18400645,"url":"https://github.com/databricks/diviner","last_synced_at":"2025-04-07T06:33:38.336Z","repository":{"id":40455862,"uuid":"419845148","full_name":"databricks/diviner","owner":"databricks","description":"Grouped time series forecasting 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Grouped Timeseries Forecasting at scale\n================================================\n\nDiviner is an execution framework wrapper around popular open source time series forecasting libraries.\nThe aim of the project is to simplify the creation, training, orchestration, and MLOps logistics associated with\nforecasting projects that involve the predictions of many discrete independent events.\n\n|docs| |build| |examples| |core| |pypi| |license| |downloads|\n\n.. |docs| image:: https://img.shields.io/badge/docs-latest-success.svg?style=for-the-badge\u0026logo=readthedocs\n    :target: https://databricks-diviner.readthedocs.io/en/latest/?badge=latest\n    :alt: Documentation\n\n.. |build| image:: https://img.shields.io/github/workflow/status/databricks/diviner/Test%20package%20build?label=Build%20CI\u0026style=for-the-badge\u0026logo=github\n    :target: https://github.com/databricks/diviner/actions/workflows/test-package-build.yml\n    :alt: Build CI\n\n.. |examples| image:: https://img.shields.io/github/workflow/status/databricks/diviner/Examples?label=Examples\u0026style=for-the-badge\u0026logo=github\n    :target: https://github.com/databricks/diviner/actions/workflows/examples.yml\n    :alt: Examples CI\n\n.. |core| image:: https://img.shields.io/github/workflow/status/databricks/diviner/Diviner%20tests?label=Core%20CI\u0026style=for-the-badge\u0026logo=github\n    :target: https://github.com/databricks/diviner/actions/workflows/main.yml\n    :alt: Core CI\n\n.. |pypi| image:: https://img.shields.io/pypi/v/diviner.svg?style=for-the-badge\u0026logo=pypi\u0026logoColor=white\n    :target: https://pypi.org/project/diviner/\n    :alt: Latest Python Release\n\n.. |license| image:: https://img.shields.io/badge/license-Apache%202-brightgreen.svg?style=for-the-badge\u0026logo=apache\n    :target: https://github.com/databricks/diviner/blob/main/LICENSE.txt\n    :alt: Apache 2 License\n\n.. |downloads| image:: https://img.shields.io/pypi/dm/diviner?style=for-the-badge\u0026logo=pypi\u0026logoColor=white\n    :target: https://pepy.tech/project/diviner\n    :alt: Total Downloads\n\n\nIs this right for my project?\n-----------------------------\n\nDiviner is meant to help with large-scale forecasting. Instead of describing each individual use case where it may be\napplicable, here is a non-exhaustive list of projects that it would fit well as a solution for:\n\n* Forecasting regional sales within each country that a company does business in per day\n* Predicting inventory demand at regional warehouses for thousands of products\n* Forecasting traveler counts at each airport within a country daily\n* Predicting electrical demand per neighborhood (or household) in a multi-state region\n\nEach of these examples has a *common theme*:\n\n* The data is temporally homogenous (all of the data is collected daily, hourly, weekly, etc.).\n* There is a large number of individual models that need to be built due to the cardinality of the data.\n* There is no guarantee of seasonal, trend, or residual homogeneity in each series.\n* Varying levels of aggregation may be called for to solve different use cases.\n\nThe primary problem that Diviner solves is managing the execution of many discrete time-series modeling tasks. Diviner\nprovides a high-level API and metadata management approach that relieves the operational burden of managing hundreds\nor thousands of individual models.\n\nGrouped Modeling Wrappers\n-------------------------\n\nCurrently, Diviner supports the following open source libraries for forecasting at scale:\n\n* `prophet \u003chttps://facebook.github.io/prophet/docs/quick_start.html\u003e`_\n* `pmdarima \u003chttp://alkaline-ml.com/pmdarima/\u003e`_\n\nInstalling\n----------\n\nInstall Diviner from PyPI via:\n\n``pip install diviner``\n\nDocumentation\n-------------\n\nDocumentation, Examples, and Tutorials for Diviner can be found\n`here \u003chttps://databricks-diviner.readthedocs.io/en/latest/index.html\u003e`_.\n\nCommunity \u0026 Contributing\n------------------------\n\nFor assistance with Diviner, see the `docs \u003chttps://databricks-diviner.readthedocs.io/en/latest/index.html\u003e`_.\n\nContributions to Diviner are welcome. To file a bug, request a new feature, or to contribute a feature request, please\nopen a GitHub issue. The team will work with you to ensure that your contributions are evaluated and appropriate\nfeedback is provided. See the\n`contributing guidelines \u003chttps://github.com/databricks/diviner/tree/main/CONTRIBUTING.rst\u003e`_ for submission guidance.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatabricks%2Fdiviner","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdatabricks%2Fdiviner","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdatabricks%2Fdiviner/lists"}