Add dbt-cloud integration command to dp cli

# Documentation

data_pipelines_cli/cli_commands/dbtcloud.py

@@ -38,7 +38,7 @@ def read_bigquery_config(env: str) -> Dict[str, Any]:
     "--account_id",
     type=int,
     required=True,
-    help="""dbt Cloud Account identifier To obtain your dbt Cloud account ID, sign into dbt Cloud 
+    help="""dbt Cloud Account identifier To obtain your dbt Cloud account ID, sign into dbt Cloud
     in your browser. Take note of the number directly following the accounts path component of the
     URL - this is your account ID""",
 )

docs/configuration.rst

@@ -375,4 +375,70 @@ Example ``looker.yml`` file might look like this:
    looker_project_id: my_looker_project
    looker_webhook_secret: "{{ env_var('LOOKER_WEBHOOK_SECRET') }}"
    looker_repository_branch: main
-   looker_instance_url: https://looker.company.com/
+   looker_instance_url: https://looker.company.com/
+
+dbt Cloud configuration
+++++++++++++++++++++++++++++++
+
+``config/dbtcloud.yml`` contains configuration related to dbt Cloud:
+
+.. list-table::
+   :widths: 25 20 55
+   :header-rows: 1
+
+   * - Parameter
+     - Data type
+     - Description
+   * - project_name
+     - string
+     - Name of the project to be created in dbt Cloud
+   * - schedule_interval
+     - string
+     - The cron expression with which the example job will be run
+   * - default_gcp_project
+     - string
+     - GCP project that will be used by default if a new environment is created in dbt Cloud
+   * - environments
+     - Array
+     - Details of the environments to be created in dbt Cloud
+
+Configuration of the environments:
+
+.. list-table::
+   :widths: 25 20 55
+   :header-rows: 1
+
+   * - Parameter
+     - Data type
+     - Description
+   * - name
+     - string
+     - Name of the environment that will be created in dbt Cloud
+   * - dataset
+     - string
+     - Target dataset for this environment
+   * - dbt_version
+     - string
+     - The dbt version used in this environment
+   * - bq_config_dir
+     - string
+     - The name of the dp env directory where the bigquery configuration for the environment is located. The name of the project in GCP will be read from it.
+
+Example ``dbtcloud.yml`` file might look like this:
+
+.. code-block:: yaml
+
+    project_name: "Data Pipelines Project"
+    schedule_interval: "0 12 * * *"
+    default_gcp_project: "default-project"
+    environments:
+      - name: "Develop"
+        dataset: "dev"
+        dbt_version: "1.0.0"
+        type: "development"
+        bq_config_dir: "dev"
+      - name: "Production"
+        dataset: "prod"
+        dbt_version: "1.0.0"
+        type: "deployment"
+        bq_config_dir: "prod"

docs/integration.rst

@@ -71,3 +71,13 @@ Looker
 
 **dp** can generate lookML codes for your models and views, publish and deploy your `Looker <https://www.looker.com/>`_ project
 
+dbt Cloud
+++++++++++++++++++++++++++++++++++++++++++++++
+
+The `Data Pipelines CLI` can configure a project in dbt Cloud. The following functions are supported:
+
+- creation of a project
+- adding a repository
+- adding a connection to BigQuery
+- creation of environments
+- creation of sample jobs