Add default-minimal template

NEXT_CHANGELOG.md

@@ -9,6 +9,7 @@
 ### Dependency updates
 
 ### Bundles
+* Add `default-minimal` template for users who want a clean slate without sample code ([#3885](https://github.com/databricks/cli/pull/3885))
 * Add validation that served_models and served_entities are not used at the same time. Add client side translation logic. ([#3880](https://github.com/databricks/cli/pull/3880))
 
 ### API Changes

acceptance/bundle/help/bundle-init/output.txt

@@ -5,6 +5,7 @@ Initialize using a bundle template to get started quickly.
 TEMPLATE_PATH optionally specifies which template to use. It can be one of the following:
 - default-python: The default Python template for Notebooks and Lakeflow
 - default-sql: The default SQL template for .sql files that run with Databricks SQL
+- default-minimal: The minimal template, for advanced users
 - dbt-sql: The dbt SQL template (databricks.com/blog/delivering-cost-effective-data-real-time-dbt-and-databricks)
 - mlops-stacks: The Databricks MLOps Stacks template (github.com/databricks/mlops-stacks)
 - pydabs: A variant of the 'default-python' template that defines resources in Python instead of YAML

acceptance/bundle/templates/default-minimal/input.json

@@ -0,0 +1,6 @@
+{
+    "project_name": "my_default_minimal",
+    "include_job": "no",
+    "include_pipeline": "no",
+    "include_python": "no"
+}

acceptance/bundle/templates/default-minimal/output.txt

@@ -0,0 +1,33 @@
+
+>>> [CLI] bundle init default-minimal --config-file ./input.json --output-dir output
+Welcome to the minimal Databricks Asset Bundle template!
+
+This template creates a minimal project structure without sample code, ideal for advanced users.
+(For getting started with Python or SQL code, use the default-python or default-sql templates instead.)
+
+Your workspace at [DATABRICKS_URL] is used for initialization.
+(See https://docs.databricks.com/dev-tools/cli/profiles.html for how to change your profile.)
+
+✨ Your new project has been created in the 'my_default_minimal' directory!
+
+To get started, refer to the project README.md file and the documentation at https://docs.databricks.com/dev-tools/bundles/index.html.
+
+>>> [CLI] bundle validate -t dev
+Name: my_default_minimal
+Target: dev
+Workspace:
+  Host: [DATABRICKS_URL]
+  User: [USERNAME]
+  Path: /Workspace/Users/[USERNAME]/.bundle/my_default_minimal/dev
+
+Validation OK!
+
+>>> [CLI] bundle validate -t prod
+Name: my_default_minimal
+Target: prod
+Workspace:
+  Host: [DATABRICKS_URL]
+  User: [USERNAME]
+  Path: /Workspace/Users/[USERNAME]/.bundle/my_default_minimal/prod
+
+Validation OK!

acceptance/bundle/templates/default-minimal/output/my_default_minimal/.vscode/__builtins__.pyi

@@ -0,0 +1,3 @@
+# Typings for Pylance in Visual Studio Code
+# see https://github.com/microsoft/pyright/blob/main/docs/builtins.md
+from databricks.sdk.runtime import *

acceptance/bundle/templates/default-minimal/output/my_default_minimal/.vscode/extensions.json

@@ -0,0 +1,7 @@
+{
+    "recommendations": [
+        "databricks.databricks",
+        "redhat.vscode-yaml",
+        "ms-python.black-formatter"
+    ]
+}

acceptance/bundle/templates/default-minimal/output/my_default_minimal/.vscode/settings.json

@@ -0,0 +1,39 @@
+{
+    "jupyter.interactiveWindow.cellMarker.codeRegex": "^# COMMAND ----------|^# Databricks notebook source|^(#\\s*%%|#\\s*\\<codecell\\>|#\\s*In\\[\\d*?\\]|#\\s*In\\[ \\])",
+    "jupyter.interactiveWindow.cellMarker.default": "# COMMAND ----------",
+    "python.testing.pytestArgs": [
+        "."
+    ],
+    "files.exclude": {
+        "**/*.egg-info": true,
+        "**/__pycache__": true,
+        ".pytest_cache": true,
+        "dist": true,
+    },
+    "files.associations": {
+        "**/.gitkeep": "markdown"
+    },
+
+    // Pylance settings (VS Code)
+    // Set typeCheckingMode to "basic" to enable type checking!
+    "python.analysis.typeCheckingMode": "off",
+    "python.analysis.extraPaths": ["src", "lib", "resources"],
+    "python.analysis.diagnosticMode": "workspace",
+    "python.analysis.stubPath": ".vscode",
+
+    // Pyright settings (Cursor)
+    // Set typeCheckingMode to "basic" to enable type checking!
+    "cursorpyright.analysis.typeCheckingMode": "off",
+    "cursorpyright.analysis.extraPaths": ["src", "lib", "resources"],
+    "cursorpyright.analysis.diagnosticMode": "workspace",
+    "cursorpyright.analysis.stubPath": ".vscode",
+
+    // General Python settings
+    "python.defaultInterpreterPath": "./.venv/bin/python",
+    "python.testing.unittestEnabled": false,
+    "python.testing.pytestEnabled": true,
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+        "editor.formatOnSave": true,
+    },
+}

acceptance/bundle/templates/default-minimal/output/my_default_minimal/README.md

@@ -0,0 +1,62 @@
+# my_default_minimal
+
+The 'my_default_minimal' project was generated by using the default template.
+
+* `src/`: Python source code for this project.
+* `resources/`:  Resource configurations (jobs, pipelines, etc.)
+* `tests/`: Unit tests for the shared Python code.
+* `fixtures/`: Fixtures for data sets (primarily used for testing).
+
+
+## Getting started
+
+Choose how you want to work on this project:
+
+(a) Directly in your Databricks workspace, see
+    https://docs.databricks.com/dev-tools/bundles/workspace.
+
+(b) Locally with an IDE like Cursor or VS Code, see
+    https://docs.databricks.com/dev-tools/vscode-ext.html.
+
+(c) With command line tools, see https://docs.databricks.com/dev-tools/cli/databricks-cli.html
+
+If you're developing with an IDE, dependencies for this project should be installed using uv:
+
+*  Make sure you have the UV package manager installed.
+   It's an alternative to tools like pip: https://docs.astral.sh/uv/getting-started/installation/.
+*  Run `uv sync --dev` to install the project's dependencies.
+
+
+# Using this project using the CLI
+
+The Databricks workspace and IDE extensions provide a graphical interface for working
+with this project. It's also possible to interact with it directly using the CLI:
+
+1. Authenticate to your Databricks workspace, if you have not done so already:
+    ```
+    $ databricks configure
+    ```
+
+2. To deploy a development copy of this project, type:
+    ```
+    $ databricks bundle deploy --target dev
+    ```
+    (Note that "dev" is the default target, so the `--target` parameter
+    is optional here.)
+
+    This deploys everything that's defined for this project.
+
+3. Similarly, to deploy a production copy, type:
+   ```
+   $ databricks bundle deploy --target prod
+   ```
+
+4. To run a job or pipeline, use the "run" command:
+   ```
+   $ databricks bundle run
+   ```
+
+5. Finally, to run tests locally, use `pytest`:
+   ```
+   $ uv run pytest
+   ```

acceptance/bundle/templates/default-minimal/output/my_default_minimal/databricks.yml

@@ -0,0 +1,42 @@
+# This is a Databricks asset bundle definition for my_default_minimal.
+# See https://docs.databricks.com/dev-tools/bundles/index.html for documentation.
+bundle:
+  name: my_default_minimal
+  uuid: [UUID]
+
+include:
+  - resources/*.yml
+  - resources/*/*.yml
+
+# Variable declarations. These variables are assigned in the dev/prod targets below.
+variables:
+  catalog:
+    description: The catalog to use
+  schema:
+    description: The schema to use
+
+targets:
+  dev:
+    # The default target uses 'mode: development' to create a development copy.
+    # - Deployed resources get prefixed with '[dev my_user_name]'
+    # - Any job schedules and triggers are paused by default.
+    # See also https://docs.databricks.com/dev-tools/bundles/deployment-modes.html.
+    mode: development
+    default: true
+    workspace:
+      host: [DATABRICKS_URL]
+    variables:
+      catalog: hive_metastore
+      schema: ${workspace.current_user.short_name}
+  prod:
+    mode: production
+    workspace:
+      host: [DATABRICKS_URL]
+      # We explicitly deploy to /Workspace/Users/[USERNAME] to make sure we only have a single copy.
+      root_path: /Workspace/Users/[USERNAME]/.bundle/${bundle.name}/${bundle.target}
+    variables:
+      catalog: hive_metastore
+      schema: prod
+    permissions:
+      - user_name: [USERNAME]
+        level: CAN_MANAGE

acceptance/bundle/templates/default-minimal/output/my_default_minimal/fixtures/.gitkeep

@@ -0,0 +1,9 @@
+# Test fixtures directory
+
+Add JSON or CSV files here. In tests, use them with `load_fixture()`:
+
+```
+def test_using_fixture(load_fixture):
+    data = load_fixture("my_data.json")
+    assert len(data) >= 1
+```

acceptance/bundle/templates/default-minimal/output/my_default_minimal/out.gitignore

@@ -0,0 +1,10 @@
+.databricks/
+build/
+dist/
+__pycache__/
+*.egg-info
+.venv/
+scratch/**
+!scratch/README.md
+**/explorations/**
+**/!explorations/README.md

acceptance/bundle/templates/default-minimal/output/my_default_minimal/pyproject.toml

@@ -0,0 +1,32 @@
+[project]
+name = "my_default_minimal"
+version = "0.0.1"
+authors = [{ name = "[USERNAME]" }]
+requires-python = ">=3.10,<=3.13"
+dependencies = [
+    # Any dependencies for jobs and pipelines in this project can be added here
+    # See also https://docs.databricks.com/dev-tools/bundles/library-dependencies
+    #
+    # LIMITATION: for pipelines, dependencies are cached during development;
+    # add dependencies to the 'environment' section of your pipeline.yml file instead
+]
+
+[dependency-groups]
+dev = [
+    "pytest",
+    "databricks-dlt",
+    "databricks-connect>=15.4,<15.5",
+]
+
+[project.scripts]
+main = "my_default_minimal.main:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
+[tool.black]
+line-length = 125

acceptance/bundle/templates/default-minimal/output/my_default_minimal/tests/conftest.py

@@ -0,0 +1,98 @@
+"""This file configures pytest.
+
+This file is in the root since it can be used for tests in any place in this
+project, including tests under resources/.
+"""
+
+import os, sys, pathlib
+from contextlib import contextmanager
+
+
+try:
+    from databricks.connect import DatabricksSession
+    from databricks.sdk import WorkspaceClient
+    from pyspark.sql import SparkSession
+    import pytest
+    import json
+    import csv
+    import os
+except ImportError:
+    raise ImportError(
+        "Test dependencies not found.\n\nRun tests using 'uv run pytest'. See http://docs.astral.sh/uv to learn more about uv."
+    )
+
+
+@pytest.fixture()
+def spark() -> SparkSession:
+    """Provide a SparkSession fixture for tests.
+
+    Minimal example:
+        def test_uses_spark(spark):
+            df = spark.createDataFrame([(1,)], ["x"])
+            assert df.count() == 1
+    """
+    return DatabricksSession.builder.getOrCreate()
+
+
+@pytest.fixture()
+def load_fixture(spark: SparkSession):
+    """Provide a callable to load JSON or CSV from fixtures/ directory.
+
+    Example usage:
+
+        def test_using_fixture(load_fixture):
+            data = load_fixture("my_data.json")
+            assert data.count() >= 1
+    """
+
+    def _loader(filename: str):
+        path = pathlib.Path(__file__).parent.parent / "fixtures" / filename
+        suffix = path.suffix.lower()
+        if suffix == ".json":
+            rows = json.loads(path.read_text())
+            return spark.createDataFrame(rows)
+        if suffix == ".csv":
+            with path.open(newline="") as f:
+                rows = list(csv.DictReader(f))
+            return spark.createDataFrame(rows)
+        raise ValueError(f"Unsupported fixture type for: {filename}")
+
+    return _loader
+
+
+def _enable_fallback_compute():
+    """Enable serverless compute if no compute is specified."""
+    conf = WorkspaceClient().config
+    if conf.serverless_compute_id or conf.cluster_id or os.environ.get("SPARK_REMOTE"):
+        return
+
+    url = "https://docs.databricks.com/dev-tools/databricks-connect/cluster-config"
+    print("☁️ no compute specified, falling back to serverless compute", file=sys.stderr)
+    print(f"  see {url} for manual configuration", file=sys.stdout)
+
+    os.environ["DATABRICKS_SERVERLESS_COMPUTE_ID"] = "auto"
+
+
+@contextmanager
+def _allow_stderr_output(config: pytest.Config):
+    """Temporarily disable pytest output capture."""
+    capman = config.pluginmanager.get_plugin("capturemanager")
+    if capman:
+        with capman.global_and_fixture_disabled():
+            yield
+    else:
+        yield
+
+
+def pytest_configure(config: pytest.Config):
+    """Configure pytest session."""
+    with _allow_stderr_output(config):
+        _enable_fallback_compute()
+
+        # Initialize Spark session eagerly, so it is available even when
+        # SparkSession.builder.getOrCreate() is used. For DB Connect 15+,
+        # we validate version compatibility with the remote cluster.
+        if hasattr(DatabricksSession.builder, "validateSession"):
+            DatabricksSession.builder.validateSession().getOrCreate()
+        else:
+            DatabricksSession.builder.getOrCreate()

acceptance/bundle/templates/default-minimal/script

@@ -0,0 +1,16 @@
+trace $CLI bundle init default-minimal --config-file ./input.json --output-dir output
+
+cd output/my_default_minimal
+
+# Verify that empty directories are preserved
+[ -d "src" ] || exit 1
+[ -d "resources" ] || exit 1
+
+trace $CLI bundle validate -t dev
+trace $CLI bundle validate -t prod
+
+# Do not affect this repository's git behaviour #2318
+mv .gitignore out.gitignore
+rm -r .databricks
+
+cd ../../

acceptance/bundle/templates/lakeflow-pipelines/python/output/my_lakeflow_pipelines/pyproject.toml

@@ -25,5 +25,8 @@ main = "my_lakeflow_pipelines.main:main"
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
+[tool.hatch.build.targets.wheel]
+packages = ["src"]
+
 [tool.black]
 line-length = 125