Workspace Layout¶

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Overview of the sample Fabric workspace repository and how commands interact with it.

dp/
├── dbt_project*/                              # DBT project sources
├── ddl_scripts/                               # Jinja-based DDL sources
│   ├── Lakehouses/
│   └── Warehouses/
├── deployment/                              # DevOps yml deployment scripts
├── fabric_workspace_items/
│   ├── config/
│   │   └── var_lib.VariableLibrary/           # Value sets per environment
│   ├── lakehouses/                            # Lakehouse definitions (.Lakehouse)
│   ├── warehouses/                            # Warehouse definitions (.Warehouse)
│   ├── ddl_scripts/                           # Generated DDL notebooks
│   └── dbt_project*/                          # DBT project notebooks
├── metadata/                                  # Extracted metadata cache
└── platform_manifest_*.yml                    # Platform/environment manifests

Command mapping:

Area	Typical Commands	Notes
DDL scripts (`ddl_scripts/*`)	`ingen_fab ddl compile -o fabric_workspace_repo -g <Lakehouse\|Warehouse>`	Compiles to notebooks under `fabric_workspace_items/*`
Fabric workspace items (`fabric_workspace_items/*`)	`ingen_fab deploy deploy`	Deployed to the target Fabric workspace
Variable library (`var_lib.VariableLibrary`)	Used implicitly by compile/deploy	Selects value set by `FABRIC_ENVIRONMENT`
Python libs (`python_libs/*`)	`ingen_fab deploy upload-python-libs`	Injects variables during OneLake upload

Tips: - Keep DDL scripts numbered and idempotent; compile before deployment. - Maintain separate value sets for each environment under valueSets/*.json. - Store artifacts (e.g., metadata extracts) under ./artifacts/ to keep the repo tidy.