#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
"""
### Tutorial Documentation
Documentation that goes along with the Airflow tutorial located
[here](https://airflow.apache.org/tutorial.html)
"""
from __future__ import annotations
# [START tutorial]
# [START import_module]
import textwrap
from datetime import datetime, timedelta
# The DAG object; we'll need this to instantiate a DAG
from airflow.models.dag import DAG
# Operators; we need this to operate!
from airflow.providers.standard.operators.bash import BashOperator
# [END import_module]
# [START instantiate_dag]
with DAG(
"tutorial",
# [START default_args]
# These args will get passed on to each operator
# You can override them on a per-task basis during operator initialization
default_args={
"depends_on_past": False,
"email": ["airflow@example.com"],
"email_on_failure": False,
"email_on_retry": False,
"retries": 1,
"retry_delay": timedelta(minutes=5),
# 'queue': 'bash_queue',
# 'pool': 'backfill',
# 'priority_weight': 10,
# 'end_date': datetime(2016, 1, 1),
# 'wait_for_downstream': False,
# 'execution_timeout': timedelta(seconds=300),
# 'on_failure_callback': some_function, # or list of functions
# 'on_success_callback': some_other_function, # or list of functions
# 'on_retry_callback': another_function, # or list of functions
# 'sla_miss_callback': yet_another_function, # or list of functions
# 'on_skipped_callback': another_function, #or list of functions
# 'trigger_rule': 'all_success'
},
# [END default_args]
description="A simple tutorial DAG",
schedule=timedelta(days=1),
start_date=datetime(2021, 1, 1),
catchup=False,
tags=["example"],
) as dag:
# [END instantiate_dag]
# t1, t2 and t3 are examples of tasks created by instantiating operators
# [START basic_task]
[docs] t1 = BashOperator(
task_id="print_date",
bash_command="date",
)
t2 = BashOperator(
task_id="sleep",
depends_on_past=False,
bash_command="sleep 5",
retries=3,
)
# [END basic_task]
# [START documentation]
t1.doc_md = textwrap.dedent(
"""\
#### Task Documentation
You can document your task using the attributes `doc_md` (markdown),
`doc` (plain text), `doc_rst`, `doc_json`, `doc_yaml` which gets
rendered in the UI's Task Instance Details page.
**Image Credit:** Randall Munroe, [XKCD](https://xkcd.com/license.html)
"""
)
dag.doc_md = __doc__ # providing that you have a docstring at the beginning of the DAG; OR
dag.doc_md = """
This is a documentation placed anywhere
""" # otherwise, type it like this
# [END documentation]
# [START jinja_template]
templated_command = textwrap.dedent(
"""
{% for i in range(5) %}
echo "{{ ds }}"
echo "{{ macros.ds_add(ds, 7)}}"
{% endfor %}
"""
)
t3 = BashOperator(
task_id="templated",
depends_on_past=False,
bash_command=templated_command,
)
# [END jinja_template]
t1 >> [t2, t3]
# [END tutorial]