[docs] fix dagster-dbt tutorial

- change variable name `dbt_project` to `jaffle_shop_project` in code snippets
- add `packaged_project_dir` parameter to `DbtProject` - this parameter is automatically added by the `dagster-dbt project scaffold` command
- update `downstream-assets.md` and `load-dbt-models.md`

Author: jjyeo

docs/docs/integrations/libraries/dbt/using-dbt-with-dagster/downstream-assets.md

@@ -22,7 +22,7 @@ pip install plotly
 
 You've added upstream assets to your data pipeline, but nothing downstream - until now. In this step, you'll define a Dagster asset called `order_count_chart` that uses the data in the `customers` dbt model to computes a plotly chart of the number of orders per customer.
 
-Like the `raw_customers` asset that we added in the [previous section](upstream-assets#step-2-define-an-upstream-dagster-asset), we'll put this asset in our `definitions.py` file, inside the `jaffle_dagster` directory.
+Like the `raw_customers` asset that we added in the [previous section](upstream-assets#step-2-define-an-upstream-dagster-asset), we'll put this asset in our `assets.py` file, inside the `jaffle_dagster` directory.
 
 To add the `order_count_chart` asset:
 
@@ -38,7 +38,7 @@ To add the `order_count_chart` asset:
 
    This asset definition looks similar the asset we defined in the previous section. In this case, instead of fetching data from an external source and writing it to DuckDB, it reads data from DuckDB, and then uses it to make a plot.
 
-   The line `deps=get_asset_key_for_model([jaffle_shop_dbt_assets], "customers")` tells Dagster that this asset is downstream of the `customers` dbt model. This dependency will be displayed as such in Dagster's UI. If you launch a run to materialize both of them, Dagster won't run `order_count_chart` until `customers` completes.
+   The line `deps=[get_asset_key_for_model([jaffle_shop_dbt_assets], "customers")]` tells Dagster that this asset is downstream of the `customers` dbt model. This dependency will be displayed as such in Dagster's UI. If you launch a run to materialize both of them, Dagster won't run `order_count_chart` until `customers` completes.
 
 3. Add the `order_count_chart` to the `Definitions`:
 

docs/docs/integrations/libraries/dbt/using-dbt-with-dagster/load-dbt-models.md

@@ -74,19 +74,19 @@ The most important file is the Python file that contains the set of definitions
 
 In our `definitions.py` Python file, we import from `assets.py`, which contains the code to model our dbt models as Dagster assets. To return a Dagster asset for each dbt model, the code in this `assets.py` file needs to know what dbt models you have. It finds out what models you have by reading a file called a `manifest.json`, which is a file that dbt can generate for any dbt project and contains information about every model, seed, snapshot, test, etc. in the project.
 
-To retrieve the `manifest.json`, `assets.py` imports from `project.py`, which defines an internal representation of your dbt project. Then, in `assets.py`, the path to the `manifest.json` file can be accessed with `dbt_project.manifest_path`:
+To retrieve the `manifest.json`, `assets.py` imports from `project.py`, which defines an internal representation of your dbt project. Then, in `assets.py`, the path to the `manifest.json` file can be accessed with `jaffle_shop_project.manifest_path`:
 
-<CodeExample path="docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/project.py" startAfter="start_load_project" endBefore="=end_load_project" />
+<CodeExample path="docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/project.py" startAfter="start_load_project" endBefore="end_load_project" />
 
 Generating the `manifest.json` file for a dbt project is time-consuming, so it's best to avoid doing so every time this Python module is imported. Thus, in production deployments of Dagster, you'll typically have the CI/CD system that packages up your code generate your `manifest.json`.
 
 However, in development, you typically want changes made to files in your dbt project to be immediately reflected in the Dagster UI without needing to regenerate the manifest.
 
-`dbt_project.prepare_if_dev()` helps with this – it re-generates your `manifest.json` at the time Dagster imports your code, _but_ only if it's being imported by the `dagster dev` command.
+`jaffle_shop_project.prepare_if_dev()` helps with this – it re-generates your `manifest.json` at the time Dagster imports your code, _but_ only if it's being imported by the `dagster dev` command.
 
 Once you've got a `manifest.json` file, it's time to define your Dagster assets using it. The following code, in your project's `assets.py`, does this:
 
-<CodeExample path="docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/assets.py" startAfter="start_dbt_assets" endBefore="=end_dbt_assets" />
+<CodeExample path="docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/assets.py" startAfter="start_dbt_assets" endBefore="end_dbt_assets" />
 
 This code might look a bit fancy, because it uses a decorator. Here's a breakdown of what's going on:
 

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/downstream_assets/assets.py

@@ -8,11 +8,11 @@
 from dagster import MetadataValue, AssetExecutionContext, asset
 from dagster_dbt import DbtCliResource, dbt_assets, get_asset_key_for_model
 
-from .project import dbt_project
+from .project import jaffle_shop_project
 
 # end_imports
 
-duckdb_database_path = dbt_project.project_dir.joinpath("tutorial.duckdb")
+duckdb_database_path = jaffle_shop_project.project_dir.joinpath("tutorial.duckdb")
 
 
 @asset(compute_kind="python")

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/downstream_assets/definitions.py

@@ -5,14 +5,14 @@
 from dagster_dbt import DbtCliResource
 
 from .assets import jaffle_shop_dbt_assets, order_count_chart, raw_customers
-from .project import dbt_project
+from .project import jaffle_shop_project
 from .schedules import schedules
 
 defs = Definitions(
     assets=[raw_customers, jaffle_shop_dbt_assets, order_count_chart],
     schedules=schedules,
     resources={
-        "dbt": DbtCliResource(project_dir=dbt_project),
+        "dbt": DbtCliResource(project_dir=jaffle_shop_project),
     },
 )
 # end_defs

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/downstream_assets/project.py

@@ -3,7 +3,8 @@
 
 from dagster_dbt import DbtProject
 
-dbt_project = DbtProject(
+jaffle_shop_project = DbtProject(
     project_dir=Path(__file__).joinpath("..", "..", "..").resolve(),
+    packaged_project_dir=Path(__file__).joinpath("..", "..", "dbt-project").resolve(),
 )
-dbt_project.prepare_if_dev()
+jaffle_shop_project.prepare_if_dev()

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/assets.py

@@ -3,10 +3,10 @@
 from dagster import AssetExecutionContext
 from dagster_dbt import DbtCliResource, dbt_assets
 
-from .project import dbt_project
+from .project import jaffle_shop_project
 
 
-@dbt_assets(manifest=dbt_project.manifest_path)
+@dbt_assets(manifest=jaffle_shop_project.manifest_path)
 def jaffle_shop_dbt_assets(context: AssetExecutionContext, dbt: DbtCliResource):
     yield from dbt.cli(["build"], context=context).stream()
 

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/load_dbt_models/project.py

@@ -4,11 +4,12 @@
 
 from dagster_dbt import DbtProject
 
-dbt_project = DbtProject(
+jaffle_shop_project = DbtProject(
     project_dir=Path(__file__).joinpath("..", "..", "..").resolve(),
+    packaged_project_dir=Path(__file__).joinpath("..", "..", "dbt-project").resolve(),
 )
 # If `dagster dev` is used, the dbt project will be prepared to create the manifest at run time.
 # Otherwise, we expect a manifest to be present in the project's target directory.
-dbt_project.prepare_if_dev()
+jaffle_shop_project.prepare_if_dev()
 
 # end_load_project

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/upstream_assets/assets.py

@@ -7,9 +7,9 @@
 from dagster import AssetExecutionContext, asset
 from dagster_dbt import DbtCliResource, dbt_assets
 
-from .project import dbt_project
+from .project import jaffle_shop_project
 
-duckdb_database_path = dbt_project.project_dir.joinpath("tutorial.duckdb")
+duckdb_database_path = jaffle_shop_project.project_dir.joinpath("tutorial.duckdb")
 
 
 @asset(compute_kind="python")
@@ -25,7 +25,7 @@ def raw_customers(context: AssetExecutionContext) -> None:
     context.add_output_metadata({"num_rows": data.shape[0]})
 
 
-@dbt_assets(manifest=dbt_project.manifest_path)
+@dbt_assets(manifest=jaffle_shop_project.manifest_path)
 def jaffle_shop_dbt_assets(context: AssetExecutionContext, dbt: DbtCliResource):
     yield from dbt.cli(["build"], context=context).stream()
 

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/upstream_assets/definitions.py

@@ -6,14 +6,14 @@
 from dagster_dbt import DbtCliResource
 
 from .assets import jaffle_shop_dbt_assets, raw_customers
-from .project import dbt_project
+from .project import jaffle_shop_project
 from .schedules import schedules
 
 defs = Definitions(
     assets=[raw_customers, jaffle_shop_dbt_assets],
     schedules=schedules,
     resources={
-        "dbt": DbtCliResource(project_dir=dbt_project),
+        "dbt": DbtCliResource(project_dir=jaffle_shop_project),
     },
 )
 

examples/docs_snippets/docs_snippets/integrations/dbt/tutorial/upstream_assets/project.py

@@ -3,7 +3,8 @@
 
 from dagster_dbt import DbtProject
 
-dbt_project = DbtProject(
+jaffle_shop_project = DbtProject(
     project_dir=Path(__file__).joinpath("..", "..", "..").resolve(),
+    packaged_project_dir=Path(__file__).joinpath("..", "..", "dbt-project").resolve(),
 )
-dbt_project.prepare_if_dev()
+jaffle_shop_project.prepare_if_dev()