change back to schedule_interval

astronomer · Oct 11, 2023 · 6753ce7 · 6753ce7
1 parent 23771cd
commit 6753ce7
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Showing 16 changed files with 18 additions and 18 deletions.
diff --git a/README.rst b/README.rst
@@ -61,7 +61,7 @@ You can render an Airflow Task Group using the ``DbtTaskGroup`` class. Here's an
     with DAG(
         dag_id="extract_dag",
         start_date=datetime(2022, 11, 27),
-        schedule="@daily",
+        schedule_interval="@daily",
     ):
         e1 = EmptyOperator(task_id="pre_dbt")
 

diff --git a/dev/dags/basic_cosmos_task_group.py b/dev/dags/basic_cosmos_task_group.py
@@ -25,7 +25,7 @@
 
 
 @dag(
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
 )

diff --git a/dev/dags/cosmos_manifest_example.py b/dev/dags/cosmos_manifest_example.py
@@ -32,7 +32,7 @@
     render_config=RenderConfig(load_method=LoadMode.DBT_MANIFEST, select=["path:models/customers.sql"]),
     operator_args={"install_deps": True},
     # normal dag parameters
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
     dag_id="cosmos_manifest_example",

diff --git a/dev/dags/cosmos_profile_mapping.py b/dev/dags/cosmos_profile_mapping.py
@@ -18,7 +18,7 @@
 
 
 @dag(
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
 )

diff --git a/dev/dags/cosmos_seed_dag.py b/dev/dags/cosmos_seed_dag.py
@@ -36,7 +36,7 @@
 with DAG(
     dag_id="extract_dag",
     start_date=datetime(2022, 11, 27),
-    schedule="@daily",
+    schedule_interval="@daily",
     doc_md=__doc__,
     catchup=False,
     max_active_runs=1,

diff --git a/dev/dags/dbt_docs.py b/dev/dags/dbt_docs.py
@@ -63,7 +63,7 @@ def which_upload():
 with DAG(
     dag_id="docs_dag",
     start_date=datetime(2023, 1, 1),
-    schedule="@daily",
+    schedule_interval="@daily",
     doc_md=__doc__,
     catchup=False,
     default_args={"retries": 2},

diff --git a/dev/dags/example_cosmos_python_models.py b/dev/dags/example_cosmos_python_models.py
@@ -44,7 +44,7 @@
         "append_env": True,
     },
     # normal dag parameters
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
     dag_id="example_cosmos_python_models",

diff --git a/dev/dags/example_model_version.py b/dev/dags/example_model_version.py
@@ -30,7 +30,7 @@
     profile_config=profile_config,
     operator_args={"install_deps": True},
     # normal dag parameters
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
     dag_id="example_model_version",

diff --git a/dev/dags/example_virtualenv.py b/dev/dags/example_virtualenv.py
@@ -37,7 +37,7 @@
         "install_deps": True,
     },
     # normal dag parameters
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
     dag_id="example_virtualenv",

diff --git a/dev/dags/user_defined_profile.py b/dev/dags/user_defined_profile.py
@@ -16,7 +16,7 @@
 
 
 @dag(
-    schedule="@daily",
+    schedule_interval="@daily",
     start_date=datetime(2023, 1, 1),
     catchup=False,
 )

diff --git a/docs/configuration/scheduling.rst b/docs/configuration/scheduling.rst
@@ -17,7 +17,7 @@ To schedule a dbt project on a time-based schedule, you can use Airflow's schedu
     jaffle_shop = DbtDag(
         # ...
         start_date=datetime(2023, 1, 1),
-        schedule="@daily",
+        schedule_interval="@daily",
     )
 
 
@@ -45,12 +45,12 @@ Then, you can use Airflow's data-aware scheduling capabilities to schedule ``my_
     project_one = DbtDag(
         # ...
         start_date=datetime(2023, 1, 1),
-        schedule="@daily",
+        schedule_interval="@daily",
     )
 
     project_two = DbtDag(
         # ...
-        schedule=[get_dbt_dataset("my_conn", "project_one", "my_model")],
+        schedule_interval=[get_dbt_dataset("my_conn", "project_one", "my_model")],
         dbt_project_name="project_two",
     )
 

diff --git a/docs/getting_started/astro.rst b/docs/getting_started/astro.rst
@@ -102,7 +102,7 @@ In your ``my_cosmos_dag.py`` file, import the ``DbtDag`` class from Cosmos and c
             dbt_executable_path=f"{os.environ['AIRFLOW_HOME']}/dbt_venv/bin/dbt",
         ),
         # normal dag parameters
-        schedule="@daily",
+        schedule_interval="@daily",
         start_date=datetime(2023, 1, 1),
         catchup=False,
         dag_id="my_cosmos_dag",

diff --git a/docs/getting_started/gcc.rst b/docs/getting_started/gcc.rst
@@ -71,7 +71,7 @@ Make sure to rename the ``<your-adapter>`` value below to your adapter's Python
             "py_requirements": ["<your-adapter>"],
         },
         # normal dag parameters
-        schedule="@daily",
+        schedule_interval="@daily",
         start_date=datetime(2023, 1, 1),
         catchup=False,
         dag_id="my_cosmos_dag",

diff --git a/docs/getting_started/mwaa.rst b/docs/getting_started/mwaa.rst
@@ -105,7 +105,7 @@ In your ``my_cosmos_dag.py`` file, import the ``DbtDag`` class from Cosmos and c
         ),
         profile_config=profile_config,
         # normal dag parameters
-        schedule="@daily",
+        schedule_interval="@daily",
         start_date=datetime(2023, 1, 1),
         catchup=False,
         dag_id="my_cosmos_dag",

diff --git a/docs/getting_started/open-source.rst b/docs/getting_started/open-source.rst
@@ -57,7 +57,7 @@ For example, if you wanted to put your dbt project in the ``/usr/local/airflow/d
             dbt_executable_path=f"{os.environ['AIRFLOW_HOME']}/dbt_venv/bin/dbt",
         ),
         # normal dag parameters
-        schedule="@daily",
+        schedule_interval="@daily",
         start_date=datetime(2023, 1, 1),
         catchup=False,
         dag_id="my_cosmos_dag",

diff --git a/docs/index.rst b/docs/index.rst
@@ -63,7 +63,7 @@ You can render an Airflow Task Group using the ``DbtTaskGroup`` class. Here's an
     with DAG(
         dag_id="extract_dag",
         start_date=datetime(2022, 11, 27),
-        schedule="@daily",
+        schedule_interval="@daily",
     ):
         e1 = EmptyOperator(task_id="pre_dbt")