菜单
Migrate a legacy source connector from the old sources/ directory to the new package structure under src/databricks/labs/community_connector/sources/.
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基于 SOC 职业分类
| name | migrate-legacy-implementation |
| description | Migrate a legacy source connector from the old sources/ directory to the new package structure under src/databricks/labs/community_connector/sources/. |
| disable-model-invocation | true |
This skill migrates an old connector implementation from the legacy sources/ directory to the new package structure under src/databricks/labs/community_connector/sources/. It handles one specified source at a time, updating imports, conforming to the LakeflowConnect interface, and regenerating specs and build files.
Handle one specified source at a time. Refer other source (e.g. example) as a reference. Use python3.10 to replace all python command. When running any python test or build use virtual environment (Python 3.10+ required), run these: python3.10 -m venv .venv source .venv/bin/activate python -m pip install -e ".[dev]" then run other python commands or pytest.
Run shell command to git mv the files for the specified source under sources/ to the new directory. Commit the change.
sources/{source_name}/tests/ need to move to tests/unit/sources/{source_name}sources/{source_name}/configs needs to move to tests/unit/sources/{source_name} as wellUpdate {source_name}.py:
LakeflowConnect interface from src/databricks/labs/community_connector/interface/lakeflow_connect.py and change the existing LakeflowConnect class to implement the interface with name {SourceName}LakeflowConnect.Update import paths in all moved files and expose {SourceName}LakeflowConnect in __init__.py under {source_name} to make it available in the package.
If {source_name}.py is too large (>1000 lines), consider refactoring it into multiple files. One example to follow is example.
Run the tests — they will fail but should not be syntax or import errors.
Update the README.md under {source_name} directory to make sure all references and content match the latest changes.
Use the generate-connector-spec skill to regenerate the spec for this connector.
Use the build_connector_package skill to build the pyproject.toml and related files.
If there are any .py files that should not be imported as part of {source_name}.py, exclude them in the tools/scripts/merge_exclude_config.json
You should change any other directories other than src/databricks/labs/community_connector/sources/{source_name} directory. Delete other directories like libs, pipeline under root.
run tools/scripts/merge_python_source.py to create _generated source code.
Generate public-facing documentation for a connector targeted at end users.
Set up authentication for a source connector — generate connector spec, collect credentials interactively, and validate auth.
Run the authenticate script to collect credentials from the user via a browser form.
Guide the user through creating or updating a pipeline for a source connector — read the docs, build a pipeline spec interactively, and run create_pipeline or update_pipeline.
Generate the connector spec YAML file defining connection parameters and external options allowlist.
Single step only: audit a completed connector — implementation, testing & simulator validation, artifacts, security smells, cross-doc consistency — and produce a scored markdown review report. Read-mostly; does not modify connector code.