[airflow] branch main updated: Update code examples from "classic" operators to taskflow (#25657)

[ur...@apache.org]

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uranusjr pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/airflow.git


The following commit(s) were added to refs/heads/main by this push:
     new 98aac5dc28 Update code examples from "classic" operators to taskflow (#25657)
98aac5dc28 is described below

commit 98aac5dc282b139f0e726aac512b04a6693ba83d
Author: Hank Ehly <he...@gmail.com>
AuthorDate: Thu Aug 18 12:54:06 2022 +0900

    Update code examples from "classic" operators to taskflow (#25657)
    
    Co-authored-by: Josh Fell <48...@users.noreply.github.com>
    Co-authored-by: Tzu-ping Chung <ur...@gmail.com>
---
 docs/apache-airflow/best-practices.rst | 19 ++++++-------------
 docs/apache-airflow/faq.rst            | 16 +++++++++-------
 docs/apache-airflow/index.rst          | 11 +++++++----
 3 files changed, 22 insertions(+), 24 deletions(-)

diff --git a/docs/apache-airflow/best-practices.rst b/docs/apache-airflow/best-practices.rst
index 3383dc7e6e..4b1bcb232d 100644
--- a/docs/apache-airflow/best-practices.rst
+++ b/docs/apache-airflow/best-practices.rst
@@ -124,7 +124,7 @@ Bad example:
   import pendulum
 
   from airflow import DAG
-  from airflow.operators.python import PythonOperator
+  from airflow.decorators import task
 
   import numpy as np  # <-- THIS IS A VERY BAD IDEA! DON'T DO THAT!
 
@@ -136,16 +136,14 @@ Bad example:
       tags=["example"],
   ) as dag:
 
+      @task()
       def print_array():
           """Print Numpy array."""
           a = np.arange(15).reshape(3, 5)
           print(a)
           return a
 
-      run_this = PythonOperator(
-          task_id="print_the_context",
-          python_callable=print_array,
-      )
+      print_array()
 
 Good example:
 
@@ -154,7 +152,7 @@ Good example:
   import pendulum
 
   from airflow import DAG
-  from airflow.operators.python import PythonOperator
+  from airflow.decorators import task
 
   with DAG(
       dag_id="example_python_operator",
@@ -164,6 +162,7 @@ Good example:
       tags=["example"],
   ) as dag:
 
+      @task()
       def print_array():
           """Print Numpy array."""
           import numpy as np  # <- THIS IS HOW NUMPY SHOULD BE IMPORTED IN THIS CASE
@@ -172,12 +171,7 @@ Good example:
           print(a)
           return a
 
-      run_this = PythonOperator(
-          task_id="print_the_context",
-          python_callable=print_array,
-      )
-
-
+      print_array()
 
 Dynamic DAG Generation
 ----------------------
@@ -278,7 +272,6 @@ It's easier to grab the concept with an example. Let's say that we have the foll
     from airflow.decorators import task
     from airflow.exceptions import AirflowException
     from airflow.operators.bash import BashOperator
-    from airflow.operators.python import PythonOperator
     from airflow.utils.trigger_rule import TriggerRule
 
 
diff --git a/docs/apache-airflow/faq.rst b/docs/apache-airflow/faq.rst
index 829451d53a..fd91cca487 100644
--- a/docs/apache-airflow/faq.rst
+++ b/docs/apache-airflow/faq.rst
@@ -177,16 +177,12 @@ until ``min_file_process_interval`` is reached since DAG Parser will look for mo
    :name: dag_loader.py
 
     from airflow import DAG
-    from airflow.operators.python_operator import PythonOperator
+    from airflow.decorators import task
 
     import pendulum
 
 
     def create_dag(dag_id, schedule, dag_number, default_args):
-        def hello_world_py(*args):
-            print("Hello World")
-            print("This is DAG: {}".format(str(dag_number)))
-
         dag = DAG(
             dag_id,
             schedule=schedule,
@@ -195,7 +191,13 @@ until ``min_file_process_interval`` is reached since DAG Parser will look for mo
         )
 
         with dag:
-            t1 = PythonOperator(task_id="hello_world", python_callable=hello_world_py)
+
+            @task()
+            def hello_world():
+                print("Hello World")
+                print(f"This is DAG: {dag_number}")
+
+            hello_world()
 
         return dag
 
@@ -410,7 +412,7 @@ upstream task.
     from airflow.utils.trigger_rule import TriggerRule
 
 
-    @task
+    @task()
     def a_func():
         raise AirflowException
 
diff --git a/docs/apache-airflow/index.rst b/docs/apache-airflow/index.rst
index 0743f5d7a6..7fae1362cb 100644
--- a/docs/apache-airflow/index.rst
+++ b/docs/apache-airflow/index.rst
@@ -40,24 +40,27 @@ Take a look at the following snippet of code:
     from datetime import datetime
 
     from airflow import DAG
+    from airflow.decorators import task
     from airflow.operators.bash import BashOperator
-    from airflow.operators.python import PythonOperator
 
     # A DAG represents a workflow, a collection of tasks
     with DAG(dag_id="demo", start_date=datetime(2022, 1, 1), schedule="0 0 * * *") as dag:
 
         # Tasks are represented as operators
         hello = BashOperator(task_id="hello", bash_command="echo hello")
-        airflow = PythonOperator(task_id="airflow", python_callable=lambda: print("airflow"))
+
+        @task()
+        def airflow():
+            print("airflow")
 
         # Set dependencies between tasks
-        hello >> airflow
+        hello >> airflow()
 
 
 Here you see:
 
 - A DAG named "demo", starting on Jan 1st 2022 and running once a day. A DAG is Airflow's representation of a workflow.
-- Two tasks, a BashOperator running a Bash script and a PythonOperator running a Python script
+- Two tasks, a BashOperator running a Bash script and a Python function defined using the ``@task`` decorator
 - ``>>`` between the tasks defines a dependency and controls in which order the tasks will be executed
 
 Airflow evaluates this script and executes the tasks at the set interval and in the defined order. The status