{"library":"databricks-bundles","type":"library","category":null,"description":"Databricks Bundles, recently renamed to Declarative Automation Bundles, provides Python support for defining, dynamically creating, and modifying Databricks jobs and pipelines. It extends the core Declarative Automation Bundles functionality, allowing users to apply software engineering best practices like source control, code review, testing, and CI/CD to their data and AI projects. The library is currently at version 0.296.0 and is actively maintained, with a focus on streamlining deployments and enabling programmatic configuration through Python and YAML files, orchestrated via the Databricks CLI.","language":"python","status":"active","version":"0.296.0","tags":["databricks","mlops","ci-cd","infrastructure-as-code","data-engineering","python","yaml"],"last_verified":"Fri May 22","install":[{"cmd":"pip install databricks-bundles","imports":["The 'databricks-bundles' Python package is primarily used by the Databricks CLI internally when processing Python-defined bundle resources, rather than direct 'from pkg import ClassName' statements in end-user application code."]},{"cmd":"curl -fsSL https://raw.githubusercontent.com/databricks/setup-cli/main/install.sh | sh\ndatabricks -v # Verify installation\ndatabricks auth login --host https://<your-workspace-url>","imports":[]}],"homepage":"https://docs.databricks.com/en/dev-tools/bundles/index.html","github":null,"docs":null,"changelog":null,"pypi":"https://pypi.org/project/databricks-bundles/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":80,"avg_install_s":1.6,"avg_import_s":null,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/databricks-bundles/compatibility"}}