jedcunningham commented on code in PR #32669:
URL: https://github.com/apache/airflow/pull/32669#discussion_r1268396346
##########
airflow/config_templates/default_airflow.cfg:
##########
@@ -16,1507 +15,21 @@
# specific language governing permissions and limitations
# under the License.
-# This is the template for Airflow's default configuration. When Airflow is
-# imported, it looks for a configuration file at $AIRFLOW_HOME/airflow.cfg. If
-# it doesn't exist, Airflow uses this template to generate it by replacing
-# variables in curly braces with their global values from configuration.py.
-
-# Users should not modify this file; they should customize the generated
-# airflow.cfg instead.
-
-
-# ----------------------- TEMPLATE BEGINS HERE -----------------------
-
-[core]
-# The folder where your airflow pipelines live, most likely a
-# subfolder in a code repository. This path must be absolute.
-dags_folder = {AIRFLOW_HOME}/dags
-
-# Hostname by providing a path to a callable, which will resolve the hostname.
-# The format is "package.function".
-#
-# For example, default value "airflow.utils.net.getfqdn" means that result
from patched
-# version of socket.getfqdn() - see
https://github.com/python/cpython/issues/49254.
-#
-# No argument should be required in the function specified.
-# If using IP address as hostname is preferred, use value
``airflow.utils.net.get_host_ip_address``
-hostname_callable = airflow.utils.net.getfqdn
-
-# A callable to check if a python file has airflow dags defined or not
-# with argument as: `(file_path: str, zip_file: zipfile.ZipFile | None = None)`
-# return True if it has dags otherwise False
-# If this is not provided, Airflow uses its own heuristic rules.
-might_contain_dag_callable =
airflow.utils.file.might_contain_dag_via_default_heuristic
-
-# Default timezone in case supplied date times are naive
-# can be utc (default), system, or any IANA timezone string (e.g.
Europe/Amsterdam)
-default_timezone = utc
-
-# The executor class that airflow should use. Choices include
-# ``SequentialExecutor``, ``LocalExecutor``, ``CeleryExecutor``,
``DaskExecutor``,
-# ``KubernetesExecutor``, ``CeleryKubernetesExecutor`` or the
-# full import path to the class when using a custom executor.
-executor = SequentialExecutor
-
-# The auth manager class that airflow should use. Full import path to the auth
manager class.
-auth_manager = airflow.auth.managers.fab.fab_auth_manager.FabAuthManager
-
-# This defines the maximum number of task instances that can run concurrently
per scheduler in
-# Airflow, regardless of the worker count. Generally this value, multiplied by
the number of
-# schedulers in your cluster, is the maximum number of task instances with the
running
-# state in the metadata database.
-parallelism = 32
-
-# The maximum number of task instances allowed to run concurrently in each
DAG. To calculate
-# the number of tasks that is running concurrently for a DAG, add up the
number of running
-# tasks for all DAG runs of the DAG. This is configurable at the DAG level
with ``max_active_tasks``,
-# which is defaulted as ``max_active_tasks_per_dag``.
-#
-# An example scenario when this would be useful is when you want to stop a new
dag with an early
-# start date from stealing all the executor slots in a cluster.
-max_active_tasks_per_dag = 16
-
-# Are DAGs paused by default at creation
-dags_are_paused_at_creation = True
-
-# The maximum number of active DAG runs per DAG. The scheduler will not create
more DAG runs
-# if it reaches the limit. This is configurable at the DAG level with
``max_active_runs``,
-# which is defaulted as ``max_active_runs_per_dag``.
-max_active_runs_per_dag = 16
-
-# The name of the method used in order to start Python processes via the
multiprocessing module.
-# This corresponds directly with the options available in the Python docs:
-#
https://docs.python.org/3/library/multiprocessing.html#multiprocessing.set_start_method.
-# Must be one of the values returned by:
-#
https://docs.python.org/3/library/multiprocessing.html#multiprocessing.get_all_start_methods.
-# Example: mp_start_method = fork
-# mp_start_method =
-
-# Whether to load the DAG 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 = True
-
-# Path to the folder containing Airflow plugins
-plugins_folder = {AIRFLOW_HOME}/plugins
-
-# Should tasks be executed via forking of the parent process ("False",
-# the speedier option) or by spawning a new python process ("True" slow,
-# but means plugin changes picked up by tasks straight away)
-execute_tasks_new_python_interpreter = False
-
-# Secret key to save connection passwords in the db
-fernet_key = {FERNET_KEY}
-
-# Whether to disable pickling dags
-donot_pickle = True
-
-# How long before timing out a python file import
-dagbag_import_timeout = 30.0
-
-# Should a traceback be shown in the UI for dagbag import errors,
-# instead of just the exception message
-dagbag_import_error_tracebacks = True
-
-# If tracebacks are shown, how many entries from the traceback should be shown
-dagbag_import_error_traceback_depth = 2
-
-# How long before timing out a DagFileProcessor, which processes a dag file
-dag_file_processor_timeout = 50
-
-# The class to use for running task instances in a subprocess.
-# Choices include StandardTaskRunner, CgroupTaskRunner or the full import path
to the class
-# when using a custom task runner.
-task_runner = StandardTaskRunner
-
-# If set, tasks without a ``run_as_user`` argument will be run with this user
-# Can be used to de-elevate a sudo user running Airflow when executing tasks
-default_impersonation =
-
-# What security module to use (for example kerberos)
-security =
-
-# Turn unit test mode on (overwrites many configuration options with test
-# values at runtime)
-unit_test_mode = False
-
-# Whether to enable pickling for xcom (note that this is insecure and allows
for
-# RCE exploits).
-enable_xcom_pickling = False
-
-# What classes can be imported during deserialization. This is a multi line
value.
-# The individual items will be parsed as regexp. Python built-in classes (like
dict)
-# are always allowed. Bare "." will be replaced so you can set airflow.* .
-allowed_deserialization_classes = airflow\..*
-
-# When a task is killed forcefully, this is the amount of time in seconds that
-# it has to cleanup after it is sent a SIGTERM, before it is SIGKILLED
-killed_task_cleanup_time = 60
-
-# Whether to override params with dag_run.conf. If you pass some key-value
pairs
-# through ``airflow dags backfill -c`` or
-# ``airflow dags trigger -c``, the key-value pairs will override the existing
ones in params.
-dag_run_conf_overrides_params = True
-
-# If enabled, Airflow will only scan files containing both ``DAG`` and
``airflow`` (case-insensitive).
-dag_discovery_safe_mode = True
-
-# The pattern syntax used in the ".airflowignore" files in the DAG
directories. Valid values are
-# ``regexp`` or ``glob``.
-dag_ignore_file_syntax = regexp
-
-# The number of retries each task is going to have by default. Can be
overridden at dag or task level.
-default_task_retries = 0
-
-# The number of seconds each task is going to wait by default between retries.
Can be overridden at
-# dag or task level.
-default_task_retry_delay = 300
-
-# The maximum delay (in seconds) each task is going to wait by default between
retries.
-# This is a global setting and cannot be overridden at task or DAG level.
-max_task_retry_delay = 86400
-
-# The weighting method used for the effective total priority weight of the task
-default_task_weight_rule = downstream
-
-# The default task execution_timeout value for the operators. Expected an
integer value to
-# be passed into timedelta as seconds. If not specified, then the value is
considered as None,
-# meaning that the operators are never timed out by default.
-default_task_execution_timeout =
-
-# Updating serialized DAG can not be faster than a minimum interval to reduce
database write rate.
-min_serialized_dag_update_interval = 30
-
-# If True, serialized DAGs are compressed before writing to DB.
-# Note: this will disable the DAG dependencies view
-compress_serialized_dags = False
-
-# Fetching serialized DAG can not be faster than a minimum interval to reduce
database
-# read rate. This config controls when your DAGs are updated in the Webserver
-min_serialized_dag_fetch_interval = 10
-
-# Maximum number of Rendered Task Instance Fields (Template Fields) per task
to store
-# in the Database.
-# All the template_fields for each of Task Instance are stored in the Database.
-# Keeping this number small may cause an error when you try to view
``Rendered`` tab in
-# TaskInstance view for older tasks.
-max_num_rendered_ti_fields_per_task = 30
-
-# On each dagrun check against defined SLAs
-check_slas = True
-
-# Path to custom XCom class that will be used to store and resolve operators
results
-# Example: xcom_backend = path.to.CustomXCom
-xcom_backend = airflow.models.xcom.BaseXCom
-
-# By default Airflow plugins are lazily-loaded (only loaded when required).
Set it to ``False``,
-# if you want to load plugins whenever 'airflow' is invoked via cli or loaded
from module.
-lazy_load_plugins = True
-
-# By default Airflow providers are lazily-discovered (discovery and imports
happen only when required).
-# Set it to False, if you want to discover providers whenever 'airflow' is
invoked via cli or
-# loaded from module.
-lazy_discover_providers = True
-
-# Hide sensitive Variables or Connection extra json keys from UI and task logs
when set to True
-#
-# (Connection passwords are always hidden in logs)
-hide_sensitive_var_conn_fields = True
-
-# A comma-separated list of extra sensitive keywords to look for in variables
names or connection's
-# extra JSON.
-sensitive_var_conn_names =
-
-# Task Slot counts for ``default_pool``. This setting would not have any
effect in an existing
-# deployment where the ``default_pool`` is already created. For existing
deployments, users can
-# change the number of slots using Webserver, API or the CLI
-default_pool_task_slot_count = 128
-
-# The maximum list/dict length an XCom can push to trigger task mapping. If
the pushed list/dict has a
-# length exceeding this value, the task pushing the XCom will be failed
automatically to prevent the
-# mapped tasks from clogging the scheduler.
-max_map_length = 1024
-
-# The default umask to use for process when run in daemon mode (scheduler,
worker, etc.)
-#
-# This controls the file-creation mode mask which determines the initial value
of file permission bits
-# for newly created files.
-#
-# This value is treated as an octal-integer.
-daemon_umask = 0o077
-
-# Class to use as dataset manager.
-# Example: dataset_manager_class = airflow.datasets.manager.DatasetManager
-# dataset_manager_class =
-
-# Kwargs to supply to dataset manager.
-# Example: dataset_manager_kwargs = {{"some_param": "some_value"}}
-# dataset_manager_kwargs =
-
-# (experimental) Whether components should use Airflow Internal API for DB
connectivity.
-database_access_isolation = False
-
-# (experimental) Airflow Internal API url. Only used if [core]
database_access_isolation is True.
-# Example: internal_api_url = http://localhost:8080
-# internal_api_url =
-
-# The ability to allow testing connections across Airflow UI, API and CLI.
-# Supported options: Disabled, Enabled, Hidden. Default: Disabled
-# Disabled - Disables the test connection functionality and disables the Test
Connection button in UI.
-# Enabled - Enables the test connection functionality and shows the Test
Connection button in UI.
-# Hidden - Disables the test connection functionality and hides the Test
Connection button in UI.
-# Before setting this to Enabled, make sure that you review the users who are
able to add/edit
-# connections and ensure they are trusted. Connection testing can be done
maliciously leading to
-# undesired and insecure outcomes. For more information on capabilities of
users, see the documentation:
-#
https://airflow.apache.org/docs/apache-airflow/stable/security/index.html#capabilities-of-authenticated-ui-users
-test_connection = Disabled
-
-[database]
-# Path to the ``alembic.ini`` file. You can either provide the file path
relative
-# to the Airflow home directory or the absolute path if it is located
elsewhere.
-alembic_ini_file_path = alembic.ini
-
-# The SqlAlchemy connection string to the metadata database.
-# SqlAlchemy supports many different database engines.
-# More information here:
-#
http://airflow.apache.org/docs/apache-airflow/stable/howto/set-up-database.html#database-uri
-sql_alchemy_conn = sqlite:///{AIRFLOW_HOME}/airflow.db
-
-# Extra engine specific keyword args passed to SQLAlchemy's create_engine, as
a JSON-encoded value
-# Example: sql_alchemy_engine_args = {{"arg1": True}}
-# sql_alchemy_engine_args =
-
-# The encoding for the databases
-sql_engine_encoding = utf-8
-
-# Collation for ``dag_id``, ``task_id``, ``key``, ``external_executor_id``
columns
-# in case they have different encoding.
-# By default this collation is the same as the database collation, however for
``mysql`` and ``mariadb``
-# the default is ``utf8mb3_bin`` so that the index sizes of our index keys
will not exceed
-# the maximum size of allowed index when collation is set to ``utf8mb4``
variant
-# (see https://github.com/apache/airflow/pull/17603#issuecomment-901121618).
-# sql_engine_collation_for_ids =
-
-# If SqlAlchemy should pool database connections.
-sql_alchemy_pool_enabled = True
-
-# The SqlAlchemy pool size is the maximum number of database connections
-# in the pool. 0 indicates no limit.
-sql_alchemy_pool_size = 5
-
-# The maximum overflow size of the pool.
-# When the number of checked-out connections reaches the size set in pool_size,
-# additional connections will be returned up to this limit.
-# When those additional connections are returned to the pool, they are
disconnected and discarded.
-# It follows then that the total number of simultaneous connections the pool
will allow
-# is pool_size + max_overflow,
-# and the total number of "sleeping" connections the pool will allow is
pool_size.
-# max_overflow can be set to ``-1`` to indicate no overflow limit;
-# no limit will be placed on the total number of concurrent connections.
Defaults to ``10``.
-sql_alchemy_max_overflow = 10
-
-# The SqlAlchemy pool recycle is the number of seconds a connection
-# can be idle in the pool before it is invalidated. This config does
-# not apply to sqlite. If the number of DB connections is ever exceeded,
-# a lower config value will allow the system to recover faster.
-sql_alchemy_pool_recycle = 1800
-
-# Check connection at the start of each connection pool checkout.
-# Typically, this is a simple statement like "SELECT 1".
-# More information here:
-#
https://docs.sqlalchemy.org/en/14/core/pooling.html#disconnect-handling-pessimistic
-sql_alchemy_pool_pre_ping = True
-
-# The schema to use for the metadata database.
-# SqlAlchemy supports databases with the concept of multiple schemas.
-sql_alchemy_schema =
-
-# Import path for connect args in SqlAlchemy. Defaults to an empty dict.
-# This is useful when you want to configure db engine args that SqlAlchemy
won't parse
-# in connection string.
-# See
https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine.params.connect_args
-# Example: sql_alchemy_connect_args = {{"timeout": 30}}
-# sql_alchemy_connect_args =
-
-# Whether to load the default connections that ship with Airflow. It's good to
-# get started, but you probably want to set this to ``False`` in a production
-# environment
-load_default_connections = True
-
-# Number of times the code should be retried in case of DB Operational Errors.
-# Not all transactions will be retried as it can cause undesired state.
-# Currently it is only used in ``DagFileProcessor.process_file`` to retry
``dagbag.sync_to_db``.
-max_db_retries = 3
-
-# Whether to run alembic migrations during Airflow start up. Sometimes this
operation can be expensive,
-# and the users can assert the correct version through other means (e.g.
through a Helm chart).
-# Accepts "True" or "False".
-check_migrations = True
-
-[logging]
-# The folder where airflow should store its log files.
-# This path must be absolute.
-# There are a few existing configurations that assume this is set to the
default.
-# If you choose to override this you may need to update the
dag_processor_manager_log_location and
-# dag_processor_manager_log_location settings as well.
-base_log_folder = {AIRFLOW_HOME}/logs
-
-# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic
Search.
-# Set this to True if you want to enable remote logging.
-remote_logging = False
-
-# Users must supply an Airflow connection id that provides access to the
storage
-# location. Depending on your remote logging service, this may only be used for
-# reading logs, not writing them.
-remote_log_conn_id =
-
-# Whether the local log files for GCS, S3, WASB and OSS remote logging should
be deleted after
-# they are uploaded to the remote location.
-delete_local_logs = False
-
-# Path to Google Credential JSON file. If omitted, authorization based on `the
Application Default
-# Credentials
-#
<https://cloud.google.com/docs/authentication/production#finding_credentials_automatically>`__
will
-# be used.
-google_key_path =
-
-# Storage bucket URL for remote logging
-# S3 buckets should start with "s3://"
-# Cloudwatch log groups should start with "cloudwatch://"
-# GCS buckets should start with "gs://"
-# WASB buckets should start with "wasb" just to help Airflow select correct
handler
-# Stackdriver logs should start with "stackdriver://"
-remote_base_log_folder =
-
-# The remote_task_handler_kwargs param is loaded into a dictionary and passed
to __init__ of remote
-# task handler and it overrides the values provided by Airflow config. For
example if you set
-# `delete_local_logs=False` and you provide ``{{"delete_local_copy": true}}``,
then the local
-# log files will be deleted after they are uploaded to remote location.
-# Example: remote_task_handler_kwargs = {{"delete_local_copy": true}}
-remote_task_handler_kwargs =
-
-# Use server-side encryption for logs stored in S3
-encrypt_s3_logs = False
-
-# Logging level.
#
-# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``.
-logging_level = INFO
-
-# Logging level for celery. If not set, it uses the value of logging_level
-#
-# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``.
-celery_logging_level =
-
-# Logging level for Flask-appbuilder UI.
+# NOTE:
#
-# Supported values: ``CRITICAL``, ``ERROR``, ``WARNING``, ``INFO``, ``DEBUG``.
-fab_logging_level = WARNING
-
-# Logging class
-# Specify the class that will specify the logging configuration
-# This class has to be on the python classpath
-# Example: logging_config_class = my.path.default_local_settings.LOGGING_CONFIG
-logging_config_class =
-
-# Flag to enable/disable Colored logs in Console
-# Colour the logs when the controlling terminal is a TTY.
-colored_console_log = True
-
-# Log format for when Colored logs is enabled
-colored_log_format = [%%(blue)s%%(asctime)s%%(reset)s]
{{%%(blue)s%%(filename)s:%%(reset)s%%(lineno)d}}
%%(log_color)s%%(levelname)s%%(reset)s - %%(log_color)s%%(message)s%%(reset)s
-colored_formatter_class =
airflow.utils.log.colored_log.CustomTTYColoredFormatter
-
-# Format of Log line
-log_format = [%%(asctime)s] {{%%(filename)s:%%(lineno)d}} %%(levelname)s -
%%(message)s
-simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s
-
-# Where to send dag parser logs. If "file", logs are sent to log files defined
by child_process_log_directory.
-dag_processor_log_target = file
-
-# Format of Dag Processor Log line
-dag_processor_log_format = [%%(asctime)s] [SOURCE:DAG_PROCESSOR]
{{%%(filename)s:%%(lineno)d}} %%(levelname)s - %%(message)s
-log_formatter_class = airflow.utils.log.timezone_aware.TimezoneAware
-
-# An import path to a function to add adaptations of each secret added with
-# `airflow.utils.log.secrets_masker.mask_secret` to be masked in log messages.
The given function
-# is expected to require a single parameter: the secret to be adapted. It may
return a
-# single adaptation of the secret or an iterable of adaptations to each be
masked as secrets.
-# The original secret will be masked as well as any adaptations returned.
-# Example: secret_mask_adapter = urllib.parse.quote
-secret_mask_adapter =
-
-# Specify prefix pattern like mentioned below with stream handler
TaskHandlerWithCustomFormatter
-# Example: task_log_prefix_template =
{{ti.dag_id}}-{{ti.task_id}}-{{execution_date}}-{{try_number}}
-task_log_prefix_template =
-
-# Formatting for how airflow generates file names/paths for each task run.
-log_filename_template = dag_id={{{{ ti.dag_id }}}}/run_id={{{{ ti.run_id
}}}}/task_id={{{{ ti.task_id }}}}/{{%% if ti.map_index >= 0 %%}}map_index={{{{
ti.map_index }}}}/{{%% endif %%}}attempt={{{{ try_number }}}}.log
-
-# Formatting for how airflow generates file names for log
-log_processor_filename_template = {{{{ filename }}}}.log
-
-# Full path of dag_processor_manager logfile.
-dag_processor_manager_log_location =
{AIRFLOW_HOME}/logs/dag_processor_manager/dag_processor_manager.log
-
-# Name of handler to read task instance logs.
-# Defaults to use ``task`` handler.
-task_log_reader = task
-
-# A comma\-separated list of third-party logger names that will be configured
to print messages to
-# consoles\.
-# Example: extra_logger_names = connexion,sqlalchemy
-extra_logger_names =
-
-# When you start an airflow worker, airflow starts a tiny web server
-# subprocess to serve the workers local log files to the airflow main
-# web server, who then builds pages and sends them to users. This defines
-# the port on which the logs are served. It needs to be unused, and open
-# visible from the main web server to connect into the workers.
-worker_log_server_port = 8793
-
-# Port to serve logs from for triggerer. See worker_log_server_port
description
-# for more info.
-trigger_log_server_port = 8794
-
-# We must parse timestamps to interleave logs between trigger and task. To do
so,
-# we need to parse timestamps in log files. In case your log format is
non-standard,
-# you may provide import path to callable which takes a string log line and
returns
-# the timestamp (datetime.datetime compatible).
-# Example: interleave_timestamp_parser = path.to.my_func
-# interleave_timestamp_parser =
-
-# Permissions in the form or of octal string as understood by chmod. The
permissions are important
-# when you use impersonation, when logs are written by a different user than
airflow. The most secure
-# way of configuring it in this case is to add both users to the same group
and make it the default
-# group of both users. Group-writeable logs are default in airflow, but you
might decide that you are
-# OK with having the logs other-writeable, in which case you should set it to
`0o777`. You might
-# decide to add more security if you do not use impersonation and change it to
`0o755` to make it
-# only owner-writeable. You can also make it just readable only for owner by
changing it to `0o700` if
-# all the access (read/write) for your logs happens from the same user.
-# Example: file_task_handler_new_folder_permissions = 0o775
-file_task_handler_new_folder_permissions = 0o775
-
-# Permissions in the form or of octal string as understood by chmod. The
permissions are important
-# when you use impersonation, when logs are written by a different user than
airflow. The most secure
-# way of configuring it in this case is to add both users to the same group
and make it the default
-# group of both users. Group-writeable logs are default in airflow, but you
might decide that you are
-# OK with having the logs other-writeable, in which case you should set it to
`0o666`. You might
-# decide to add more security if you do not use impersonation and change it to
`0o644` to make it
-# only owner-writeable. You can also make it just readable only for owner by
changing it to `0o600` if
-# all the access (read/write) for your logs happens from the same user.
-# Example: file_task_handler_new_file_permissions = 0o664
-file_task_handler_new_file_permissions = 0o664
-
-# By default Celery sends all logs into stderr.
-# If enabled any previous logging handlers will get *removed*.
-# With this option AirFlow will create new handlers
-# and send low level logs like INFO and WARNING to stdout,
-# while sending higher severity logs to stderr.
-celery_stdout_stderr_separation = False
-
-[metrics]
-
-# StatsD (https://github.com/etsy/statsd) integration settings.
-# If you want to avoid emitting all the available metrics, you can configure an
-# allow list of prefixes (comma separated) to send only the metrics that start
-# with the elements of the list (e.g: "scheduler,executor,dagrun")
-metrics_allow_list =
-
-# If you want to avoid emitting all the available metrics, you can configure a
-# block list of prefixes (comma separated) to filter out metrics that start
with
-# the elements of the list (e.g: "scheduler,executor,dagrun").
-# If metrics_allow_list and metrics_block_list are both configured,
metrics_block_list is ignored.
-metrics_block_list =
-
-# Enables sending metrics to StatsD.
-statsd_on = False
-statsd_host = localhost
-statsd_port = 8125
-statsd_prefix = airflow
-
-# A function that validate the StatsD stat name, apply changes to the stat
name if necessary and return
-# the transformed stat name.
+# IF YOU ARE LOOKING FOR DEFAULT CONFIGURATION FILE HERE - LOOK NO MORE. READ
EXPLANATION BELOW!
#
-# The function should have the following signature:
-# def func_name(stat_name: str) -> str:
-stat_name_handler =
-
-# To enable datadog integration to send airflow metrics.
-statsd_datadog_enabled = False
-
-# List of datadog tags attached to all metrics(e.g: key1:value1,key2:value2)
-statsd_datadog_tags =
-
-# Set to False to disable metadata tags for some of the emitted metrics
-statsd_datadog_metrics_tags = True
-
-# If you want to utilise your own custom StatsD client set the relevant
-# module path below.
-# Note: The module path must exist on your PYTHONPATH for Airflow to pick it up
-# statsd_custom_client_path =
-
-# If you want to avoid sending all the available metrics tags to StatsD,
-# you can configure a block list of prefixes (comma separated) to filter out
metric tags
-# that start with the elements of the list (e.g: "job_id,run_id")
-# Example: statsd_disabled_tags = job_id,run_id,dag_id,task_id
-statsd_disabled_tags = job_id,run_id
-
-# To enable sending Airflow metrics with StatsD-Influxdb tagging convention.
-statsd_influxdb_enabled = False
-
-# Enables sending metrics to OpenTelemetry.
-otel_on = False
-otel_host = localhost
-otel_port = 8889
-otel_prefix = airflow
-otel_interval_milliseconds = 60000
-
-# If True, all metrics are also emitted to the console. Defaults to False.
-otel_debugging_on = False
-
-[secrets]
-# Full class name of secrets backend to enable (will precede env vars and
metastore in search path)
-# Example: backend =
airflow.providers.amazon.aws.secrets.systems_manager.SystemsManagerParameterStoreBackend
-backend =
-
-# The backend_kwargs param is loaded into a dictionary and passed to __init__
of secrets backend class.
-# See documentation for the secrets backend you are using. JSON is expected.
-# Example for AWS Systems Manager ParameterStore:
-# ``{{"connections_prefix": "/airflow/connections", "profile_name":
"default"}}``
-backend_kwargs =
-
-[cli]
-# In what way should the cli access the API. The LocalClient will use the
-# database directly, while the json_client will use the api running on the
-# webserver
-api_client = airflow.api.client.local_client
-
-# If you set web_server_url_prefix, do NOT forget to append it here, ex:
-# ``endpoint_url = http://localhost:8080/myroot``
-# So api will look like: ``http://localhost:8080/myroot/api/experimental/...``
-endpoint_url = http://localhost:8080
-
-[debug]
-# Used only with ``DebugExecutor``. If set to ``True`` DAG will fail with first
-# failed task. Helpful for debugging purposes.
-fail_fast = False
-
-[api]
-# Enables the deprecated experimental API. Please note that these APIs do not
have access control.
-# The authenticated user has full access.
+# This file used to have something that was similar to the default Airflow
configuration but it was
+# really just a template. It was used to generate the final configuration and
it was confusing
+# if you copied it to your configuration and some of values were wrong.
#
-# .. warning::
+# Airflow will generate the default configuration for you when you run it for
the first time in
+# AIRFLOW_HOME/airflow.cfg. You can also generate the configuration using
command line:
#
-# This `Experimental REST API
<https://airflow.readthedocs.io/en/latest/rest-api-ref.html>`__ is
-# deprecated since version 2.0. Please consider using
-# `the Stable REST API
<https://airflow.readthedocs.io/en/latest/stable-rest-api-ref.html>`__.
-# For more information on migration, see
-# `RELEASE_NOTES.rst
<https://github.com/apache/airflow/blob/main/RELEASE_NOTES.rst>`_
-enable_experimental_api = False
-
-# Comma separated list of auth backends to authenticate users of the API. See
-# https://airflow.apache.org/docs/apache-airflow/stable/security/api.html for
possible values.
-# ("airflow.api.auth.backend.default" allows all requests for historic reasons)
-auth_backends = airflow.api.auth.backend.session
-
-# Used to set the maximum page limit for API requests. If limit passed as param
-# is greater than maximum page limit, it will be ignored and maximum page
limit value
-# will be set as the limit
-maximum_page_limit = 100
-
-# Used to set the default page limit when limit param is zero or not provided
in API
-# requests. Otherwise if positive integer is passed in the API requests as
limit, the
-# smallest number of user given limit or maximum page limit is taken as limit.
-fallback_page_limit = 100
-
-# The intended audience for JWT token credentials used for authorization. This
value must match on the client and server sides. If empty, audience will not be
tested.
-# Example: google_oauth2_audience =
project-id-random-value.apps.googleusercontent.com
-google_oauth2_audience =
-
-# Path to Google Cloud Service Account key file (JSON). If omitted,
authorization based on
-# `the Application Default Credentials
-#
<https://cloud.google.com/docs/authentication/production#finding_credentials_automatically>`__
will
-# be used.
-# Example: google_key_path = /files/service-account-json
-google_key_path =
-
-# Used in response to a preflight request to indicate which HTTP
-# headers can be used when making the actual request. This header is
-# the server side response to the browser's
-# Access-Control-Request-Headers header.
-access_control_allow_headers =
-
-# Specifies the method or methods allowed when accessing the resource.
-access_control_allow_methods =
-
-# Indicates whether the response can be shared with requesting code from the
given origins.
-# Separate URLs with space.
-access_control_allow_origins =
-
-# Indicates whether the *xcomEntries* endpoint supports the *deserialize*
-# flag. If set to False, setting this flag in a request would result in a
-# 400 Bad Request error.
-enable_xcom_deserialize_support = False
-
-[lineage]
-# what lineage backend to use
-backend =
-
-[openlineage]
-
-# This section applies settings for OpenLineage integration.
-# For backwards compatibility with `openlineage-python` one can still use
-# `openlineage.yml` file or `OPENLINEAGE_` environment variables. However,
below
-# configuration takes precedence over those.
-# More in documentation -
https://openlineage.io/docs/client/python#configuration.
-# Set this to true if you don't want OpenLineage to emit events.
-disabled = False
-
-# OpenLineage namespace
-# Example: namespace = food_delivery
-# namespace =
-
-# Comma-separated paths to custom OpenLineage extractors.
-# Example: extractors =
full.path.to.ExtractorClass;full.path.to.AnotherExtractorClass
-extractors =
-
-# Path to YAML config. This provides backwards compatibility to pass config as
-# `openlineage.yml` file.
-config_path =
-
-# OpenLineage Client transport configuration. It should contain type
-# and additional options per each type.
+# airflow config list --defaults
#
-# Currently supported types are:
+# You can redirect it to your configuration file and edit it:
Review Comment:
Perfect, thanks! I missed that detail...
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