pipelines init: make dev and prod different when specifying schema (#3303)

## Changes
To cli-pipelines template, append .dev and .prod to distinguish between
schemas in prod and dev, avoiding overwriting of data when initializing
pipelines template with a custom schema in prompt or JSON.

Furthermore, the prompt to the user for a schema explains that a
specific schema will have .dev and .prod appended to it.
In the README, the full name of the pipeline is now noted, along with
where to find the pipeline.

## Tests
SQL test, which uses the shared schema, updated to print an example
template with the new schema.

Author: alyssa-db

acceptance/pipelines/e2e/output/my_project/README.md

@@ -47,6 +47,11 @@ For more tutorials and reference material, see https://docs.databricks.com/dlt.
     (Note that "dev" is the default target, so the `--target` parameter
     is optional here.)
 
+    This deploys everything that's defined for this project.
+    For example, the default template would deploy a pipeline called
+    `[dev yourname] my_project_pipeline` to your workspace.
+    You can find that pipeline by opening your workpace and clicking on **Jobs & Pipelines**.
+
 2. Similarly, to deploy a production copy, type:
    ```
    $ pipelines deploy --target prod

acceptance/pipelines/init/error-cases/output/my_project/README.md

@@ -47,6 +47,11 @@ For more tutorials and reference material, see https://docs.databricks.com/dlt.
     (Note that "dev" is the default target, so the `--target` parameter
     is optional here.)
 
+    This deploys everything that's defined for this project.
+    For example, the default template would deploy a pipeline called
+    `[dev yourname] my_project_pipeline` to your workspace.
+    You can find that pipeline by opening your workpace and clicking on **Jobs & Pipelines**.
+
 2. Similarly, to deploy a production copy, type:
    ```
    $ pipelines deploy --target prod

acceptance/pipelines/init/python/output/my_python_project/README.md

@@ -47,6 +47,11 @@ For more tutorials and reference material, see https://docs.databricks.com/dlt.
     (Note that "dev" is the default target, so the `--target` parameter
     is optional here.)
 
+    This deploys everything that's defined for this project.
+    For example, the default template would deploy a pipeline called
+    `[dev yourname] my_python_project_pipeline` to your workspace.
+    You can find that pipeline by opening your workpace and clicking on **Jobs & Pipelines**.
+
 2. Similarly, to deploy a production copy, type:
    ```
    $ pipelines deploy --target prod

acceptance/pipelines/init/sql/input.json

@@ -2,6 +2,6 @@
     "project_name": "my_sql_project",
     "default_catalog": "main",
     "personal_schemas": "no",
-    "shared_schema": "shared_dev",
+    "shared_schema": "shared",
     "language": "sql"
 }

acceptance/pipelines/init/sql/output/my_sql_project/README.md

@@ -46,6 +46,11 @@ For more tutorials and reference material, see https://docs.databricks.com/dlt.
     (Note that "dev" is the default target, so the `--target` parameter
     is optional here.)
 
+    This deploys everything that's defined for this project.
+    For example, the default template would deploy a pipeline called
+    `[dev yourname] my_sql_project_pipeline` to your workspace.
+    You can find that pipeline by opening your workpace and clicking on **Jobs & Pipelines**.
+
 2. Similarly, to deploy a production copy, type:
    ```
    $ pipelines deploy --target prod

acceptance/pipelines/init/sql/output/my_sql_project/databricks.yml

@@ -42,5 +42,5 @@ targets:
         level: CAN_MANAGE
     variables:
       catalog: main
-      schema: shared_dev
+      schema: shared
       notifications: [[USERNAME]]

libs/template/templates/cli-pipelines/databricks_template_schema.json

@@ -39,7 +39,7 @@
             "default": "default",
             "pattern": "^\\w+$",
             "pattern_match_failure_message": "Invalid schema name.",
-            "description": "\nInitial schema during development:\ndefault_schema",
+            "description": "\nInitial schema during development:\nNote: This schema name will be suffixed with '_dev' when deployed to target the development environment.\ndefault_schema",
             "order": 5
         },
         "language": {

libs/template/templates/cli-pipelines/library/variables.tmpl

@@ -10,7 +10,7 @@
     {{- if (regexp "^yes").MatchString .personal_schemas -}}
         {{ short_name }}
     {{- else -}}
-        {{ .shared_schema }}
+        {{ .shared_schema }}_dev
     {{- end}}
 {{- end }}
 
@@ -19,7 +19,7 @@
     {{- if (regexp "^yes").MatchString .personal_schemas -}}
         ${workspace.current_user.short_name}
     {{- else -}}
-        {{ .shared_schema }}
+        {{ .shared_schema }}_dev
     {{- end}}
 {{- end }}
 

libs/template/templates/cli-pipelines/template/{{.project_name}}/README.md.tmpl

@@ -58,6 +58,11 @@ For more tutorials and reference material, see https://docs.databricks.com/dlt.
     (Note that "dev" is the default target, so the `--target` parameter
     is optional here.)
 
+    This deploys everything that's defined for this project.
+    For example, the default template would deploy a pipeline called
+    `[dev yourname] {{.project_name}}_pipeline` to your workspace.
+    You can find that pipeline by opening your workpace and clicking on **Jobs & Pipelines**.
+
 2. Similarly, to deploy a production copy, type:
    ```
    $ pipelines deploy --target prod