Update to templates from CLI 0.295.0 (#147)

Update all generated templates using Databricks CLI 0.295.0. Also
updates scripts/update_from_templates.sh to use the standardized
personal_schemas enum values.

Author: lennartkats-db

dbt_sql/README.md

@@ -1,15 +1,15 @@
 # dbt_sql
 
 The 'dbt_sql' project was generated by using the dbt template for
-Databricks Asset Bundles. It follows the standard dbt project structure
+Declarative Automation Bundles. It follows the standard dbt project structure
 and has an additional `resources` directory to define Databricks resources such as jobs
 that run dbt models.
 
 * Learn more about dbt and its standard project structure here: https://docs.getdbt.com/docs/build/projects.
-* Learn more about Databricks Asset Bundles here: https://docs.databricks.com/en/dev-tools/bundles/index.html
+* Learn more about Declarative Automation Bundles here: https://docs.databricks.com/en/dev-tools/bundles/index.html
 
 The remainder of this file includes instructions for local development (using dbt)
-and deployment to production (using Databricks Asset Bundles).
+and deployment to production (using Declarative Automation Bundles).
 
 ## Development setup
 
@@ -88,20 +88,20 @@ $ dbt test
 
 ## Production setup
 
-Your production dbt profiles are defined in dbt_profiles/profiles.yml.
-These profiles define the default catalog, schema, and any other
+Your production dbt profiles are defined in `dbt_profiles/profiles.yml`.
+These profiles define the default warehouse, catalog, schema, and any other
 target-specific settings. Read more about dbt profiles on Databricks at
 https://docs.databricks.com/en/workflows/jobs/how-to/use-dbt-in-workflows.html#advanced-run-dbt-with-a-custom-profile.
 
-The target workspaces for staging and prod are defined in databricks.yml.
+The target workspaces for staging and prod are defined in `databricks.yml`.
 You can manually deploy based on these configurations (see below).
 Or you can use CI/CD to automate deployment. See
 https://docs.databricks.com/dev-tools/bundles/ci-cd.html for documentation
 on CI/CD setup.
 
-## Manually deploying to Databricks with Databricks Asset Bundles
+## Manually deploying to Databricks with Declarative Automation Bundles
 
-Databricks Asset Bundles can be used to deploy to Databricks and to execute
+Declarative Automation Bundles can be used to deploy to Databricks and to execute
 dbt commands as a job using Databricks Workflows. See
 https://docs.databricks.com/dev-tools/bundles/index.html to learn more.
 
@@ -120,7 +120,7 @@ For example, the default template would deploy a job called
 You can find that job by opening your workpace and clicking on **Workflows**.
 
 You can also deploy to your production target directly from the command-line.
-The warehouse, catalog, and schema for that target are configured in databricks.yml.
+The warehouse, catalog, and schema for that target are configured in `dbt_profiles/profiles.yml`.
 When deploying to this target, note that the default job at resources/dbt_sql.job.yml
 has a schedule set that runs every day. The schedule is paused when deploying in development mode
 (see https://docs.databricks.com/dev-tools/bundles/deployment-modes.html).

dbt_sql/databricks.yml

@@ -1,13 +1,12 @@
 # This file defines the structure of this project and how it is deployed
-# to production using Databricks Asset Bundles.
+# to production using Declarative Automation Bundles.
 # See https://docs.databricks.com/dev-tools/bundles/index.html for documentation.
 bundle:
   name: dbt_sql
   uuid: 5e5ca8d5-0388-473e-84a1-1414ed89c5df
 
 include:
   - resources/*.yml
-  - resources/*/*.yml
 
 # Deployment targets.
 # The default schema, catalog, etc. for dbt are defined in dbt_profiles/profiles.yml

default_minimal/.vscode/extensions.json

@@ -2,6 +2,6 @@
     "recommendations": [
         "databricks.databricks",
         "redhat.vscode-yaml",
-        "ms-python.black-formatter"
+        "charliermarsh.ruff"
     ]
 }

default_minimal/.vscode/settings.json

@@ -33,7 +33,7 @@
     "python.testing.unittestEnabled": false,
     "python.testing.pytestEnabled": true,
     "[python]": {
-        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.defaultFormatter": "charliermarsh.ruff",
         "editor.formatOnSave": true,
     },
 }

default_minimal/databricks.yml

@@ -6,7 +6,6 @@ bundle:
 
 include:
   - resources/*.yml
-  - resources/*/*.yml
 
 # Variable declarations. These variables are assigned in the dev/prod targets below.
 variables:

default_python/.vscode/extensions.json

@@ -2,6 +2,6 @@
     "recommendations": [
         "databricks.databricks",
         "redhat.vscode-yaml",
-        "ms-python.black-formatter"
+        "charliermarsh.ruff"
     ]
 }

default_python/.vscode/settings.json

@@ -33,7 +33,7 @@
     "python.testing.unittestEnabled": false,
     "python.testing.pytestEnabled": true,
     "[python]": {
-        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.defaultFormatter": "charliermarsh.ruff",
         "editor.formatOnSave": true,
     },
 }

default_python/databricks.yml

@@ -6,7 +6,6 @@ bundle:
 
 include:
   - resources/*.yml
-  - resources/*/*.yml
 
 artifacts:
   python_artifact:

default_python/pyproject.toml

@@ -14,8 +14,10 @@ dependencies = [
 [dependency-groups]
 dev = [
     "pytest",
+    "ruff",
     "databricks-dlt",
     "databricks-connect>=15.4,<15.5",
+    "ipykernel",
 ]
 
 [project.scripts]
@@ -25,5 +27,5 @@ main = "default_python.main:main"
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
-[tool.black]
-line-length = 125
+[tool.ruff]
+line-length = 120

default_python/src/default_python/main.py

@@ -5,7 +5,9 @@
 
 def main():
     # Process command-line arguments
-    parser = argparse.ArgumentParser(description="Databricks job with catalog and schema parameters")
+    parser = argparse.ArgumentParser(
+        description="Databricks job with catalog and schema parameters",
+    )
     parser.add_argument("--catalog", required=True)
     parser.add_argument("--schema", required=True)
     args = parser.parse_args()