From fbf7d39e9ad65d00fce755114b0d8b346c710c0f Mon Sep 17 00:00:00 2001 From: Maxime Armstrong Date: Wed, 31 Jul 2024 08:26:08 -0700 Subject: [PATCH] Revert URL in recommended-project-structure.mdx --- docs/content/guides/dagster/recommended-project-structure.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/content/guides/dagster/recommended-project-structure.mdx b/docs/content/guides/dagster/recommended-project-structure.mdx index e2f796d76b2c4..83a2f52b857b3 100644 --- a/docs/content/guides/dagster/recommended-project-structure.mdx +++ b/docs/content/guides/dagster/recommended-project-structure.mdx @@ -132,7 +132,7 @@ In this example, we grouped resources (e.g., database connections, Spark session In complex projects, we find it helpful to make resources reusable and configured with pre-defined values via . This approach allows your teammates to use a pre-defined resource set or make changes to shared resources, thus enabling more efficient project development. -This pattern also helps you easily execute jobs in different environments without code changes. In this example, we dynamically defined a code location based on the deployment in [`definitions.py`](https://github.com/dagster-io/dagster/blob/master/examples/project_fully_featured/project_fully_featured/__init__.py) and can keep all code the same across testing, local development, staging, and production. Read more about our recommendations in the [Transitioning data pipelines from Development to Production](/guides/dagster/transitioning-data-pipelines-from-development-to-production) guide. +This pattern also helps you easily execute jobs in different environments without code changes. In this example, we dynamically defined a code location based on the deployment in [`definitions.py`](https://github.com/dagster-io/dagster/blob/master/examples/project_fully_featured/project_fully_featured/\__init\_\_.py) and can keep all code the same across testing, local development, staging, and production. Read more about our recommendations in the [Transitioning data pipelines from Development to Production](/guides/dagster/transitioning-data-pipelines-from-development-to-production) guide. ---