Clean up dynamic start_date values from docs (#19607)

UPDATING.md

@@ -170,8 +170,9 @@ Similarly, `DAG.concurrency` has been renamed to `DAG.max_active_tasks`.
 ```python
 dag = DAG(
     dag_id="example_dag",
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
     concurrency=3,
-    start_date=days_ago(2),
 )
 ```
 
@@ -180,8 +181,9 @@ dag = DAG(
 ```python
 dag = DAG(
     dag_id="example_dag",
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
     max_active_tasks=3,
-    start_date=days_ago(2),
 )
 ```
 

airflow/smart_sensor_dags/smart_sensor_group.py

@@ -17,16 +17,11 @@
 # under the License.
 
 """Smart sensor DAGs managing all smart sensor tasks."""
-from datetime import timedelta
+from datetime import datetime, timedelta
 
 from airflow.configuration import conf
 from airflow.models import DAG
 from airflow.sensors.smart_sensor import SmartSensorOperator
-from airflow.utils.dates import days_ago
-
-args = {
-    'owner': 'airflow',
-}
 
 num_smart_sensor_shard = conf.getint("smart_sensor", "shards")
 shard_code_upper_limit = conf.getint('smart_sensor', 'shard_code_upper_limit')
@@ -38,13 +33,12 @@
     dag_id = f'smart_sensor_group_shard_{i}'
     dag = DAG(
         dag_id=dag_id,
-        default_args=args,
         schedule_interval=timedelta(minutes=5),
         max_active_tasks=1,
         max_active_runs=1,
         catchup=False,
         dagrun_timeout=timedelta(hours=24),
-        start_date=days_ago(2),
+        start_date=datetime(2021, 1, 1),
     )
 
     SmartSensorOperator(

docs/apache-airflow/best-practices.rst

@@ -239,7 +239,12 @@ Then you can import and use the ``ALL_TASKS`` constant in all your DAGs like tha
 
     from my_company_utils.common import ALL_TASKS
 
-    with DAG(dag_id="my_dag", schedule_interval=None, start_date=days_ago(2)) as dag:
+    with DAG(
+        dag_id="my_dag",
+        schedule_interval=None,
+        start_date=datetime(2021, 1, 1),
+        catchup=False,
+    ) as dag:
         for task in ALL_TASKS:
             # create your operators and relations here
             pass

docs/apache-airflow/concepts/dags.rst

@@ -37,18 +37,20 @@ Declaring a DAG
 There are three ways to declare a DAG - either you can use a context manager,
 which will add the DAG to anything inside it implicitly::
 
-    with DAG("my_dag_name") as dag:
+    with DAG(
+        "my_dag_name", start_date=datetime(2021, 1, 1), schedule_interval="@daily", catchup=False
+    ) as dag:
         op = DummyOperator(task_id="task")
 
 Or, you can use a standard constructor, passing the dag into any
 operators you use::
 
-    my_dag = DAG("my_dag_name")
+    my_dag = DAG("my_dag_name", start_date=datetime(2021, 1, 1), schedule_interval="@daily", catchup=False)
     op = DummyOperator(task_id="task", dag=my_dag)
 
 Or, you can use the ``@dag`` decorator to :ref:`turn a function into a DAG generator <concepts:dag-decorator>`::
 
-    @dag(start_date=days_ago(2))
+    @dag(start_date=datetime(2021, 1, 1), schedule_interval="@daily", catchup=False)
     def generate_dag():
         op = DummyOperator(task_id="task")
 

docs/apache-airflow/concepts/operators.rst

@@ -175,7 +175,8 @@ you can pass ``render_template_as_native_obj=True`` to the DAG as follows:
     dag = DAG(
         dag_id="example_template_as_python_object",
         schedule_interval=None,
-        start_date=days_ago(2),
+        start_date=datetime(2021, 1, 1),
+        catchup=False,
         render_template_as_native_obj=True,
     )
 

docs/apache-airflow/dag-run.rst

@@ -229,11 +229,17 @@ Example of a parameterized DAG:
 
 .. code-block:: python
 
+    from datetime import datetime
+
     from airflow import DAG
     from airflow.operators.bash import BashOperator
-    from airflow.utils.dates import days_ago
 
-    dag = DAG("example_parameterized_dag", schedule_interval=None, start_date=days_ago(2))
+    dag = DAG(
+        "example_parameterized_dag",
+        schedule_interval=None,
+        start_date=datetime(2021, 1, 1),
+        catchup=False,
+    )
 
     parameterized_task = BashOperator(
         task_id="parameterized_task",

docs/apache-airflow/lineage.rst

@@ -30,22 +30,21 @@ works.
 
 .. code-block:: python
 
+    from datetime import datetime, timedelta
+
     from airflow.operators.bash import BashOperator
     from airflow.operators.dummy import DummyOperator
     from airflow.lineage import AUTO
     from airflow.lineage.entities import File
     from airflow.models import DAG
-    from airflow.utils.dates import days_ago
-    from datetime import timedelta
 
     FILE_CATEGORIES = ["CAT1", "CAT2", "CAT3"]
 
-    args = {"owner": "airflow", "start_date": days_ago(2)}
-
     dag = DAG(
         dag_id="example_lineage",
-        default_args=args,
+        start_date=datetime(2021, 1, 1),
         schedule_interval="0 0 * * *",
+        catchup=False,
         dagrun_timeout=timedelta(minutes=60),
     )
 

docs/apache-airflow/tutorial.rst

@@ -487,7 +487,8 @@ Lets look at our DAG:
 
   @dag(
       schedule_interval="0 0 * * *",
-      start_date=datetime.today() - timedelta(days=2),
+      start_date=datetime(2021, 1, 1),
+      catchup=False,
       dagrun_timeout=timedelta(minutes=60),
   )
   def Etl():

docs/docker-stack/docker-examples/extending/embedding-dags/test_dag.py

@@ -21,15 +21,19 @@
 
 from airflow.models.dag import DAG
 from airflow.operators.dummy import DummyOperator
-from airflow.utils.dates import days_ago
 
 now = datetime.now()
 now_to_the_hour = (now - timedelta(0, 0, 0, 0, 0, 3)).replace(minute=0, second=0, microsecond=0)
 START_DATE = now_to_the_hour
 DAG_NAME = 'test_dag_v1'
 
-default_args = {'owner': 'airflow', 'depends_on_past': True, 'start_date': days_ago(2)}
-dag = DAG(DAG_NAME, schedule_interval='*/10 * * * *', default_args=default_args)
+dag = DAG(
+    DAG_NAME,
+    schedule_interval='*/10 * * * *',
+    default_args={'depends_on_past': True},
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+)
 
 run_this_1 = DummyOperator(task_id='run_this_1', dag=dag)
 run_this_2 = DummyOperator(task_id='run_this_2', dag=dag)