Update course after moving DbtProject to project.py

docs/dagster-university/pages/dagster-dbt/lesson-3/3-representing-the-dbt-project-in-dagster.md

@@ -8,7 +8,7 @@ lesson: '3'
 
 As you’ll frequently point your Dagster code to the `target/manifest.json` file and your dbt project in this course, it’ll be helpful to keep a reusable representation of the dbt project. This can be easily done using the `DbtProject` class.
 
-In the `assets` directory, create a new `dbt.py` file and add the following imports:
+In the `dagster_university` directory, create a new `project.py` file and add the following imports:
 
 ```python
 from pathlib import Path
@@ -22,7 +22,7 @@ After the import, add the following code:
 
 ```python
 dbt_project = DbtProject(
-  project_dir=Path(__file__).joinpath("..", "..", "..", "analytics").resolve(),
+  project_dir=Path(__file__).joinpath("..", "..", "analytics").resolve(),
 )
 ```
 

docs/dagster-university/pages/dagster-dbt/lesson-3/4-creating-a-dbt-resource-in-dagster.md

@@ -20,7 +20,7 @@ Navigate to the `dagster_university/resources/__init__.py`, which is where other
 ```python
 from dagster_dbt import DbtCliResource
 
-from ..assets.dbt import dbt_project
+from ..project import dbt_project
 # the import lines go at the top of the file
 
 # this can be defined anywhere below the imports

docs/dagster-university/pages/dagster-dbt/lesson-3/5-loading-dbt-models-into-dagster-as-assets.md

@@ -28,13 +28,15 @@ We’ll only create one `@dbt_assets` definition for now, but in a later lesson,
 
 ## Loading the models as assets
 
-1. Open the `assets/dbt.py` file.
+1. Create a new file in the `assets` directory called `dbt.py`.
 
 2. Add the following imports to the top of the file:
 
    ```python
    from dagster import AssetExecutionContext
    from dagster_dbt import dbt_assets, DbtCliResource
+
+   from ..project import dbt_project
    ```
 
 3. Next, we'll use the `@dbt_assets` decorator to create a new asset function and provide it with a reference to the project's manifest file:
@@ -66,14 +68,10 @@ We’ll only create one `@dbt_assets` definition for now, but in a later lesson,
 At this point, `dbt.py` should look like this:
 
 ```python
-from pathlib import Path
-
 from dagster import AssetExecutionContext
-from dagster_dbt import DbtCliResource, DbtProject, dbt_assets
+from dagster_dbt import DbtCliResource, dbt_assets
 
-dbt_project = DbtProject(
-   project_dir=Path(__file__).joinpath("..", "..", "..", "analytics").resolve(),
-)
+from ..project import dbt_project
 
 
 @dbt_assets(

docs/dagster-university/pages/dagster-dbt/lesson-4/2-speeding-up-the-development-cycle.md

@@ -16,7 +16,7 @@ Before we move on, we’ll reduce the number of steps in the feedback loop. We'l
 
 The first detail is that the `dbt_project` doesn’t need to be part of an asset to be executed. This means that once a `dbt_project` is defined, you can use it to execute commands when your code location is being built. Rather than manually running `dbt parse`, let’s use the `dbt_project` to prepare the manifest file for us.
 
-In `dbt.py`, after the code initializing `dbt_project`, add the following code:
+In `project.py`, after the code initializing `dbt_project`, add the following code:
 
 ```python
 dbt_project.prepare_if_dev()

docs/dagster-university/pages/dagster-dbt/lesson-5/2-connecting-dbt-models-to-dagster-assets.md

@@ -105,15 +105,10 @@ Open the `assets/dbt.py` file and do the following:
 At this point, your `dbt.py` file should match the following:
 
 ```python
-from pathlib import Path
-
 from dagster import AssetExecutionContext, AssetKey
-from dagster_dbt import DagsterDbtTranslator, DbtCliResource, DbtProject, dbt_assets
+from dagster_dbt import DagsterDbtTranslator, DbtCliResource, dbt_assets
 
-dbt_project = DbtProject(
-   project_dir=Path(__file__).joinpath("..", "..", "..", "analytics").resolve(),
-)
-dbt_project.prepare_if_dev()
+from ..project import dbt_project
 
 
 class CustomizedDagsterDbtTranslator(DagsterDbtTranslator):

docs/dagster-university/pages/dagster-dbt/lesson-6/3-creating-a-partitioned-dbt-asset.md

@@ -122,20 +122,15 @@ At this point, the `dagster_university/assets/dbt.py` file should look like this
 
 ```python
 import json
-from pathlib import Path
 
 from dagster import AssetExecutionContext, AssetKey
-from dagster_dbt import DagsterDbtTranslator, DbtCliResource, DbtProject, dbt_assets
+from dagster_dbt import DagsterDbtTranslator, DbtCliResource, dbt_assets
 
 from ..partitions import daily_partition
+from ..project import dbt_project
 
 INCREMENTAL_SELECTOR = "config.materialized:incremental"
 
-dbt_project = DbtProject(
-   project_dir=Path(__file__).joinpath("..", "..", "..", "analytics").resolve(),
-)
-dbt_project.prepare_if_dev()
-
 
 class CustomizedDagsterDbtTranslator(DagsterDbtTranslator):
     def get_asset_key(self, dbt_resource_props):

docs/dagster-university/pages/dagster-dbt/lesson-7/4-creating-the-manifest-during-deployment.md

@@ -26,7 +26,7 @@ To get our deployment working, we need to add a step to our GitHub Actions workf
         pip install pip --upgrade
         cd project-repo
         pip install . --upgrade --upgrade-strategy eager
-        dagster-dbt project prepare-and-package --file dagster_university/assets/dbt.py
+        dagster-dbt project prepare-and-package --file dagster_university/project.py
       shell: bash
     ```
 

docs/dagster-university/pages/dagster-dbt/lesson-7/5-preparing-for-a-successful-run.md

@@ -63,15 +63,15 @@ Because we’re still using a DuckDB-backed database, our `type` will also be `d
 
 ## Adding a prod target to DbtProject
 
-Next, we need to update the `DbtProject` object in `dagster_university/assets/dbt.py` to specify what profile to target. To optimize the developer experience, let’s use an environment variable to specify the profile to target.
+Next, we need to update the `DbtProject` object in `dagster_university/project.py` to specify what profile to target. To optimize the developer experience, let’s use an environment variable to specify the profile to target.
 
 1. In the `.env` file, define an environment variable named `DBT_TARGET` and set it to `dev`:
 
    ```python
    DBT_TARGET=dev
    ```
 
-2. Next, import the `os` module at the top of the `dbt.py` file so the environment variable is accessible:
+2. Next, import the `os` module at the top of the `project.py` file so the environment variable is accessible:
 
    ```python
    import os
@@ -81,7 +81,7 @@ Next, we need to update the `DbtProject` object in `dagster_university/assets/db
 
 ```python
 dbt_project = DbtProject(
-   project_dir=Path(__file__).joinpath("..", "..", "..", "analytics").resolve(),
+   project_dir=Path(__file__).joinpath("..", "..", "analytics").resolve(),
    target=os.getenv("DBT_TARGET")
 )
 ```