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pip install apache-airflow=={AIRFLOW_VERSION}
pip install apache-airflow[hive]=={AIRFLOW_VERSION}
pip install apache-airflow[celery]=={AIRFLOW_VERSION}

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[core]

# The executor class that airflow should use. Choices include
# SequentialExecutor, LocalExecutor, CeleryExecutor
executor = CeleryExecutor

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[core]

# The SqlAlchemy connection string to the metadata database.
# SqlAlchemy supports many different database engine, more information
# their website
sql_alchemy_conn = mysql://{USERNAME}:{PASSWORD}@{MYSQL_HOST}:3306/airflow

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[core]

# Are DAGs paused by default at creation
dags_are_paused_at_creation = True

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[core]

# Whether to load the examples that ship with Airflow. It's good to
# get started, but you probably want to set this to False in a production
# environment
load_examples = False

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[celery]

# The Celery broker URL. Celery supports RabbitMQ, Redis and experimentally
# a sqlalchemy database. Refer to the Celery documentation for more
# information.
broker_url = amqp://guest:guest@{RABBITMQ_HOST}:5672/

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[celery]

# The Celery broker URL. Celery supports RabbitMQ, Redis and experimentally
# a sqlalchemy database. Refer to the Celery documentation for more
# information.
broker_url = sqs://{ACCESS_KEY_ID}:{SECRET_KEY}@
 
 
# Note: You will also need to install boto:
$ pip install -U boto

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[celery]

# Another key Celery setting
celery_result_backend = db+mysql://{USERNAME}:{PASSWORD}@{MYSQL_HOST}:3306/airflow

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[celery]

# Default queue that tasks get assigned to and that worker listen on.
default_queue = {YOUR_QUEUE_NAME_HERE}

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pip install cryptography
python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"