This document describes the current stable version of Celery (5.2). For development docs, go here.
Configuration and defaults¶
This document describes the configuration options available.
If you’re using the default loader, you must create the celeryconfig.py
module and make sure it’s available on the Python path.
Example configuration file¶
This is an example configuration file to get you started. It should contain all you need to run a basic Celery set-up.
## Broker settings.
broker_url = 'amqp://guest:guest@localhost:5672//'
# List of modules to import when the Celery worker starts.
imports = ('myapp.tasks',)
## Using the database to store task state and results.
result_backend = 'db+sqlite:///results.db'
task_annotations = {'tasks.add': {'rate_limit': '10/s'}}
New lowercase settings¶
Version 4.0 introduced new lower case settings and setting organization.
The major difference between previous versions, apart from the lower case
names, are the renaming of some prefixes, like celery_beat_ to beat_,
celeryd_ to worker_, and most of the top level celery_ settings
have been moved into a new task_ prefix.
Warning
Celery will still be able to read old configuration files until Celery 6.0.
Afterwards, support for the old configuration files will be removed.
We provide the celery upgrade command that should handle
plenty of cases (including Django).
Please migrate to the new configuration scheme as soon as possible.
Setting name |
Replace with |
|---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Use |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Configuration Directives¶
General settings¶
accept_content¶
Default: {'json'} (set, list, or tuple).
A white-list of content-types/serializers to allow.
If a message is received that’s not in this list then the message will be discarded with an error.
By default only json is enabled but any content type can be added, including pickle and yaml; when this is the case make sure untrusted parties don’t have access to your broker. See Security for more.
Example:
# using serializer name
accept_content = ['json']
# or the actual content-type (MIME)
accept_content = ['application/json']
result_accept_content¶
Default: None (can be set, list or tuple).
New in version 4.3.
A white-list of content-types/serializers to allow for the result backend.
If a message is received that’s not in this list then the message will be discarded with an error.
By default it is the same serializer as accept_content.
However, a different serializer for accepted content of the result backend
can be specified.
Usually this is needed if signed messaging is used and the result is stored
unsigned in the result backend.
See Security for more.
Example:
# using serializer name
result_accept_content = ['json']
# or the actual content-type (MIME)
result_accept_content = ['application/json']
Time and date settings¶
enable_utc¶
New in version 2.5.
Default: Enabled by default since version 3.0.
If enabled dates and times in messages will be converted to use the UTC timezone.
Note that workers running Celery versions below 2.5 will assume a local timezone for all messages, so only enable if all workers have been upgraded.
timezone¶
New in version 2.5.
Default: "UTC".
Configure Celery to use a custom time zone. The timezone value can be any time zone supported by the pytz library.
If not set the UTC timezone is used. For backwards compatibility
there’s also a enable_utc setting, and when this is set
to false the system local timezone is used instead.
Task settings¶
task_annotations¶
New in version 2.5.
Default: None.
This setting can be used to rewrite any task attribute from the configuration. The setting can be a dict, or a list of annotation objects that filter for tasks and return a map of attributes to change.
This will change the rate_limit attribute for the tasks.add
task:
task_annotations = {'tasks.add': {'rate_limit': '10/s'}}
or change the same for all tasks:
task_annotations = {'*': {'rate_limit': '10/s'}}
You can change methods too, for example the on_failure handler:
def my_on_failure(self, exc, task_id, args, kwargs, einfo):
print('Oh no! Task failed: {0!r}'.format(exc))
task_annotations = {'*': {'on_failure': my_on_failure}}
If you need more flexibility then you can use objects instead of a dict to choose the tasks to annotate:
class MyAnnotate:
def annotate(self, task):
if task.name.startswith('tasks.'):
return {'rate_limit': '10/s'}
task_annotations = (MyAnnotate(), {other,})
task_compression¶
Default: None
Default compression used for task messages.
Can be gzip, bzip2 (if available), or any custom
compression schemes registered in the Kombu compression registry.
The default is to send uncompressed messages.
task_protocol¶
Default: 2 (since 4.0).
Set the default task message protocol version used to send tasks. Supports protocols: 1 and 2.
Protocol 2 is supported by 3.1.24 and 4.x+.
task_serializer¶
Default: "json" (since 4.0, earlier: pickle).
A string identifying the default serialization method to use. Can be
json (default), pickle, yaml, msgpack, or any custom serialization
methods that have been registered with kombu.serialization.registry.
See also
task_publish_retry¶
New in version 2.2.
Default: Enabled.
Decides if publishing task messages will be retried in the case
of connection loss or other connection errors.
See also task_publish_retry_policy.
task_publish_retry_policy¶
New in version 2.2.
Default: See Message Sending Retry.
Defines the default policy when retrying publishing a task message in the case of connection loss or other connection errors.
Task execution settings¶
task_always_eager¶
Default: Disabled.
If this is True, all tasks will be executed locally by blocking until
the task returns. apply_async() and Task.delay() will return
an EagerResult instance, that emulates the API
and behavior of AsyncResult, except the result
is already evaluated.
That is, tasks will be executed locally instead of being sent to the queue.
task_eager_propagates¶
Default: Disabled.
If this is True, eagerly executed tasks (applied by task.apply(),
or when the task_always_eager setting is enabled), will
propagate exceptions.
It’s the same as always running apply() with throw=True.
task_store_eager_result¶
New in version 5.1.
Default: Disabled.
If this is True and task_always_eager is True
and task_ignore_result is False,
the results of eagerly executed tasks will be saved to the backend.
By default, even with task_always_eager set to True
and task_ignore_result set to False,
the result will not be saved.
task_remote_tracebacks¶
Default: Disabled.
If enabled task results will include the workers stack when re-raising task errors.
This requires the tblib library, that can be installed using pip:
$ pip install celery[tblib]
See Bundles for information on combining multiple extension requirements.
task_ignore_result¶
Default: Disabled.
Whether to store the task return values or not (tombstones).
If you still want to store errors, just not successful return values,
you can set task_store_errors_even_if_ignored.
task_store_errors_even_if_ignored¶
Default: Disabled.
If set, the worker stores all task errors in the result store even if
Task.ignore_result is on.
task_track_started¶
Default: Disabled.
If True the task will report its status as ‘started’ when the
task is executed by a worker. The default value is False as
the normal behavior is to not report that level of granularity. Tasks
are either pending, finished, or waiting to be retried. Having a ‘started’
state can be useful for when there are long running tasks and there’s a
need to report what task is currently running.
task_time_limit¶
Default: No time limit.
Task hard time limit in seconds. The worker processing the task will be killed and replaced with a new one when this is exceeded.
task_soft_time_limit¶
Default: No soft time limit.
Task soft time limit in seconds.
The SoftTimeLimitExceeded exception will be
raised when this is exceeded. For example, the task can catch this to
clean up before the hard time limit comes:
from celery.exceptions import SoftTimeLimitExceeded
@app.task
def mytask():
try:
return do_work()
except SoftTimeLimitExceeded:
cleanup_in_a_hurry()
task_acks_late¶
Default: Disabled.
Late ack means the task messages will be acknowledged after the task has been executed, not just before (the default behavior).
See also
task_acks_on_failure_or_timeout¶
Default: Enabled
When enabled messages for all tasks will be acknowledged even if they fail or time out.
Configuring this setting only applies to tasks that are
acknowledged after they have been executed and only if
task_acks_late is enabled.
task_reject_on_worker_lost¶
Default: Disabled.
Even if task_acks_late is enabled, the worker will
acknowledge tasks when the worker process executing them abruptly
exits or is signaled (e.g., KILL/INT, etc).
Setting this to true allows the message to be re-queued instead, so that the task will execute again by the same worker, or another worker.
Warning
Enabling this can cause message loops; make sure you know what you’re doing.
task_default_rate_limit¶
Default: No rate limit.
The global default rate limit for tasks.
This value is used for tasks that doesn’t have a custom rate limit
See also
The setting:worker_disable_rate_limits setting can disable all rate limits.
Task result backend settings¶
result_backend¶
Default: No result backend enabled by default.
The backend used to store task results (tombstones). Can be one of the following:
rpcSend results back as AMQP messages See RPC backend settings.
databaseUse a relational database supported by SQLAlchemy. See conf-database-result-backend.
redisUse Redis to store the results. See Redis backend settings.
cacheUse Memcached to store the results. See Cache backend settings.
- mongodb
Use MongoDB to store the results. See MongoDB backend settings.
cassandraUse Cassandra to store the results. See Cassandra backend settings.
elasticsearchUse Elasticsearch to store the results. See Elasticsearch backend settings.
ironcacheUse IronCache to store the results. See IronCache backend settings.
couchbaseUse Couchbase to store the results. See Couchbase backend settings.
arangodbUse ArangoDB to store the results. See ArangoDB backend settings.
couchdbUse CouchDB to store the results. See CouchDB backend settings.
cosmosdbsql (experimental)Use the CosmosDB PaaS to store the results. See CosmosDB backend settings (experimental).
filesystemUse a shared directory to store the results. See File-system backend settings.
consulUse the Consul K/V store to store the results See Consul K/V store backend settings.
azureblockblobUse the AzureBlockBlob PaaS store to store the results See Azure Block Blob backend settings.
s3Use the S3 to store the results See S3 backend settings.
result_backend_always_retry¶
Default: False
If enable, backend will try to retry on the event of recoverable exceptions instead of propagating the exception. It will use an exponential backoff sleep time between 2 retries.
result_backend_max_sleep_between_retries_ms¶
Default: 10000
This specifies the maximum sleep time between two backend operation retry.
result_backend_base_sleep_between_retries_ms¶
Default: 10
This specifies the base amount of sleep time between two backend operation retry.
result_backend_max_retries¶
Default: Inf
This is the maximum of retries in case of recoverable exceptions.
result_backend_transport_options¶
Default: {} (empty mapping).
A dict of additional options passed to the underlying transport.
See your transport user manual for supported options (if any).
Example setting the visibility timeout (supported by Redis and SQS transports):
result_backend_transport_options = {'visibility_timeout': 18000} # 5 hours
result_serializer¶
Default: json since 4.0 (earlier: pickle).
Result serialization format.
See Serializers for information about supported serialization formats.
result_compression¶
Default: No compression.
Optional compression method used for task results.
Supports the same options as the task_compression setting.
result_extended¶
Default: False
Enables extended task result attributes (name, args, kwargs, worker, retries, queue, delivery_info) to be written to backend.
result_expires¶
Default: Expire after 1 day.
Time (in seconds, or a timedelta object) for when after
stored task tombstones will be deleted.
A built-in periodic task will delete the results after this time
(celery.backend_cleanup), assuming that celery beat is
enabled. The task runs daily at 4am.
A value of None or 0 means results will never expire (depending
on backend specifications).
Note
For the moment this only works with the AMQP, database, cache, Couchbase, and Redis backends.
When using the database backend, celery beat must be
running for the results to be expired.
result_cache_max¶
Default: Disabled by default.
Enables client caching of results.
This can be useful for the old deprecated ‘amqp’ backend where the result is unavailable as soon as one result instance consumes it.
This is the total number of results to cache before older results are evicted.
A value of 0 or None means no limit, and a value of -1
will disable the cache.
Disabled by default.
result_chord_join_timeout¶
Default: 3.0.
The timeout in seconds (int/float) when joining a group’s results within a chord.
result_chord_retry_interval¶
Default: 1.0.
Default interval for retrying chord tasks.
override_backends¶
Default: Disabled by default.
Path to class that implements backend.
Allows to override backend implementation. This can be useful if you need to store additional metadata about executed tasks, override retry policies, etc.
Example:
override_backends = {"db": "custom_module.backend.class"}
Database backend settings¶
Database URL Examples¶
To use the database backend you have to configure the
result_backend setting with a connection URL and the db+
prefix:
result_backend = 'db+scheme://user:password@host:port/dbname'
Examples:
# sqlite (filename)
result_backend = 'db+sqlite:///results.sqlite'
# mysql
result_backend = 'db+mysql://scott:tiger@localhost/foo'
# postgresql
result_backend = 'db+postgresql://scott:tiger@localhost/mydatabase'
# oracle
result_backend = 'db+oracle://scott:tiger@127.0.0.1:1521/sidname'
Please see Supported Databases for a table of supported databases,
and Connection String for more information about connection
strings (this is the part of the URI that comes after the db+ prefix).
database_engine_options¶
Default: {} (empty mapping).
To specify additional SQLAlchemy database engine options you can use
the database_engine_options setting:
# echo enables verbose logging from SQLAlchemy.
app.conf.database_engine_options = {'echo': True}
database_short_lived_sessions¶
Default: Disabled by default.
Short lived sessions are disabled by default. If enabled they can drastically reduce performance, especially on systems processing lots of tasks. This option is useful on low-traffic workers that experience errors as a result of cached database connections going stale through inactivity. For example, intermittent errors like (OperationalError) (2006, ‘MySQL server has gone away’) can be fixed by enabling short lived sessions. This option only affects the database backend.
database_table_schemas¶
Default: {} (empty mapping).
When SQLAlchemy is configured as the result backend, Celery automatically creates two tables to store result meta-data for tasks. This setting allows you to customize the schema of the tables:
# use custom schema for the database result backend.
database_table_schemas = {
'task': 'celery',
'group': 'celery',
}
database_table_names¶
Default: {} (empty mapping).
When SQLAlchemy is configured as the result backend, Celery automatically creates two tables to store result meta-data for tasks. This setting allows you to customize the table names:
# use custom table names for the database result backend.
database_table_names = {
'task': 'myapp_taskmeta',
'group': 'myapp_groupmeta',
}
RPC backend settings¶
result_persistent¶
Default: Disabled by default (transient messages).
If set to True, result messages will be persistent. This means the
messages won’t be lost after a broker restart.
Example configuration¶
result_backend = 'rpc://'
result_persistent = False
Please note: using this backend could trigger the raise of celery.backends.rpc.BacklogLimitExceeded if the task tombstone is too old.
E.g.
for i in range(10000):
r = debug_task.delay()
print(r.state) # this would raise celery.backends.rpc.BacklogLimitExceeded
Cache backend settings¶
Note
The cache backend supports the pylibmc and python-memcached libraries. The latter is used only if pylibmc isn’t installed.
Using a single Memcached server:
result_backend = 'cache+memcached://127.0.0.1:11211/'
Using multiple Memcached servers:
result_backend = """
cache+memcached://172.19.26.240:11211;172.19.26.242:11211/
""".strip()
The “memory” backend stores the cache in memory only:
result_backend = 'cache'
cache_backend = 'memory'
cache_backend_options¶
Default: {} (empty mapping).
You can set pylibmc options using the cache_backend_options
setting:
cache_backend_options = {
'binary': True,
'behaviors': {'tcp_nodelay': True},
}
cache_backend¶
This setting is no longer used in celery’s builtin backends as it’s now possible to specify
the cache backend directly in the result_backend setting.
Note
The django-celery-results - Using the Django ORM/Cache as a result backend library uses cache_backend for choosing django caches.
MongoDB backend settings¶
Note
The MongoDB backend requires the pymongo library:
http://github.com/mongodb/mongo-python-driver/tree/master
mongodb_backend_settings¶
This is a dict supporting the following keys:
- database
The database name to connect to. Defaults to
celery.
- taskmeta_collection
The collection name to store task meta data. Defaults to
celery_taskmeta.
- max_pool_size
Passed as max_pool_size to PyMongo’s Connection or MongoClient constructor. It is the maximum number of TCP connections to keep open to MongoDB at a given time. If there are more open connections than max_pool_size, sockets will be closed when they are released. Defaults to 10.
options
Additional keyword arguments to pass to the mongodb connection constructor. See the
pymongodocs to see a list of arguments supported.
Example configuration¶
result_backend = 'mongodb://localhost:27017/'
mongodb_backend_settings = {
'database': 'mydb',
'taskmeta_collection': 'my_taskmeta_collection',
}
Redis backend settings¶
Configuring the backend URL¶
Note
The Redis backend requires the redis library.
To install this package use pip:
$ pip install celery[redis]
See Bundles for information on combining multiple extension requirements.
This backend requires the result_backend
setting to be set to a Redis or Redis over TLS URL:
result_backend = 'redis://username:password@host:port/db'
For example:
result_backend = 'redis://localhost/0'
is the same as:
result_backend = 'redis://'
Use the rediss:// protocol to connect to redis over TLS:
result_backend = 'rediss://username:password@host:port/db?ssl_cert_reqs=required'
Note that the ssl_cert_reqs string should be one of required,
optional, or none (though, for backwards compatibility, the string
may also be one of CERT_REQUIRED, CERT_OPTIONAL, CERT_NONE).
If a Unix socket connection should be used, the URL needs to be in the format::
result_backend = 'socket:///path/to/redis.sock'
The fields of the URL are defined as follows:
usernameNew in version 5.1.0.
Username used to connect to the database.
Note that this is only supported in Redis>=6.0 and with py-redis>=3.4.0 installed.
If you use an older database version or an older client version you can omit the username:
result_backend = 'redis://:password@host:port/db'
passwordPassword used to connect to the database.
hostHost name or IP address of the Redis server (e.g., localhost).
portPort to the Redis server. Default is 6379.
dbDatabase number to use. Default is 0. The db can include an optional leading slash.
When using a TLS connection (protocol is rediss://), you may pass in all values in broker_use_ssl as query parameters. Paths to certificates must be URL encoded, and ssl_cert_reqs is required. Example:
result_backend = 'rediss://:password@host:port/db?\
ssl_cert_reqs=required\
&ssl_ca_certs=%2Fvar%2Fssl%2Fmyca.pem\ # /var/ssl/myca.pem
&ssl_certfile=%2Fvar%2Fssl%2Fredis-server-cert.pem\ # /var/ssl/redis-server-cert.pem
&ssl_keyfile=%2Fvar%2Fssl%2Fprivate%2Fworker-key.pem' # /var/ssl/private/worker-key.pem
Note that the ssl_cert_reqs string should be one of required,
optional, or none (though, for backwards compatibility, the string
may also be one of CERT_REQUIRED, CERT_OPTIONAL, CERT_NONE).
New in version 5.1.0.
redis_backend_health_check_interval¶
Default: Not configured
The Redis backend supports health checks. This value must be set as an integer whose value is the number of seconds between health checks. If a ConnectionError or a TimeoutError is encountered during the health check, the connection will be re-established and the command retried exactly once.
redis_backend_use_ssl¶
Default: Disabled.
The Redis backend supports SSL. This value must be set in
the form of a dictionary. The valid key-value pairs are
the same as the ones mentioned in the redis sub-section
under broker_use_ssl.
redis_max_connections¶
Default: No limit.
Maximum number of connections available in the Redis connection pool used for sending and retrieving results.
Warning
Redis will raise a ConnectionError if the number of concurrent connections exceeds the maximum.
redis_socket_connect_timeout¶
New in version 4.0.1.
Default: None
Socket timeout for connections to Redis from the result backend in seconds (int/float)
redis_socket_timeout¶
Default: 120.0 seconds.
Socket timeout for reading/writing operations to the Redis server in seconds (int/float), used by the redis result backend.
redis_retry_on_timeout¶
New in version 4.4.1.
Default: False
To retry reading/writing operations on TimeoutError to the Redis server, used by the redis result backend. Shouldn’t set this variable if using Redis connection by unix socket.
redis_socket_keepalive¶
New in version 4.4.1.
Default: False
Socket TCP keepalive to keep connections healthy to the Redis server, used by the redis result backend.
Cassandra backend settings¶
Note
This Cassandra backend driver requires cassandra-driver.
To install, use pip:
$ pip install celery[cassandra]
See Bundles for information on combining multiple extension requirements.
This backend requires the following configuration directives to be set.
cassandra_servers¶
Default: [] (empty list).
List of host Cassandra servers. For example:
cassandra_servers = ['localhost']
cassandra_port¶
Default: 9042.
Port to contact the Cassandra servers on.
cassandra_keyspace¶
Default: None.
The key-space in which to store the results. For example:
cassandra_keyspace = 'tasks_keyspace'
cassandra_table¶
Default: None.
The table (column family) in which to store the results. For example:
cassandra_table = 'tasks'
cassandra_read_consistency¶
Default: None.
The read consistency used. Values can be ONE, TWO, THREE, QUORUM, ALL,
LOCAL_QUORUM, EACH_QUORUM, LOCAL_ONE.
cassandra_write_consistency¶
Default: None.
The write consistency used. Values can be ONE, TWO, THREE, QUORUM, ALL,
LOCAL_QUORUM, EACH_QUORUM, LOCAL_ONE.
cassandra_entry_ttl¶
Default: None.
Time-to-live for status entries. They will expire and be removed after that many seconds
after adding. A value of None (default) means they will never expire.
cassandra_auth_provider¶
Default: None.
AuthProvider class within cassandra.auth module to use. Values can be
PlainTextAuthProvider or SaslAuthProvider.
cassandra_auth_kwargs¶
Default: {} (empty mapping).
Named arguments to pass into the authentication provider. For example:
cassandra_auth_kwargs = {
username: 'cassandra',
password: 'cassandra'
}
cassandra_options¶
Default: {} (empty mapping).
Named arguments to pass into the cassandra.cluster class.
cassandra_options = {
'cql_version': '3.2.1'
'protocol_version': 3
}
Example configuration¶
cassandra_servers = ['localhost']
cassandra_keyspace = 'celery'
cassandra_table = 'tasks'
cassandra_read_consistency = 'ONE'
cassandra_write_consistency = 'ONE'
cassandra_entry_ttl = 86400
S3 backend settings¶
Note
This s3 backend driver requires s3.
To install, use s3:
$ pip install celery[s3]
See Bundles for information on combining multiple extension requirements.
This backend requires the following configuration directives to be set.
s3_access_key_id¶
Default: None.
The s3 access key id. For example:
s3_access_key_id = 'acces_key_id'
s3_secret_access_key¶
Default: None.
The s3 secret access key. For example:
s3_secret_access_key = 'acces_secret_access_key'
s3_bucket¶
Default: None.
The s3 bucket name. For example:
s3_bucket = 'bucket_name'
s3_base_path¶
Default: None.
A base path in the s3 bucket to use to store result keys. For example:
s3_base_path = '/prefix'
s3_endpoint_url¶
Default: None.
A custom s3 endpoint url. Use it to connect to a custom self-hosted s3 compatible backend (Ceph, Scality…). For example:
s3_endpoint_url = 'https://.s3.custom.url'
s3_region¶
Default: None.
The s3 aws region. For example:
s3_region = 'us-east-1'
Example configuration¶
s3_access_key_id = 's3-access-key-id'
s3_secret_access_key = 's3-secret-access-key'
s3_bucket = 'mybucket'
s3_base_path = '/celery_result_backend'
s3_endpoint_url = 'https://endpoint_url'
Azure Block Blob backend settings¶
To use AzureBlockBlob as the result backend you simply need to
configure the result_backend setting with the correct URL.
The required URL format is azureblockblob:// followed by the storage
connection string. You can find the storage connection string in the
Access Keys pane of your storage account resource in the Azure Portal.
Example configuration¶
result_backend = 'azureblockblob://DefaultEndpointsProtocol=https;AccountName=somename;AccountKey=Lou...bzg==;EndpointSuffix=core.windows.net'
azureblockblob_container_name¶
Default: celery.
The name for the storage container in which to store the results.
azureblockblob_base_path¶
New in version 5.1.
Default: None.
A base path in the storage container to use to store result keys. For example:
azureblockblob_base_path = 'prefix/'
azureblockblob_retry_initial_backoff_sec¶
Default: 2.
The initial backoff interval, in seconds, for the first retry. Subsequent retries are attempted with an exponential strategy.
azureblockblob_retry_increment_base¶
Default: 2.
azureblockblob_retry_max_attempts¶
Default: 3.
The maximum number of retry attempts.
azureblockblob_connection_timeout¶
Default: 20.
Timeout in seconds for establishing the azure block blob connection.
azureblockblob_read_timeout¶
Default: 120.
Timeout in seconds for reading of an azure block blob.
Elasticsearch backend settings¶
To use Elasticsearch as the result backend you simply need to
configure the result_backend setting with the correct URL.
Example configuration¶
result_backend = 'elasticsearch://example.com:9200/index_name/doc_type'
elasticsearch_retry_on_timeout¶
Default: False
Should timeout trigger a retry on different node?
elasticsearch_max_retries¶
Default: 3.
Maximum number of retries before an exception is propagated.
elasticsearch_timeout¶
Default: 10.0 seconds.
Global timeout,used by the elasticsearch result backend.
elasticsearch_save_meta_as_text¶
Default: True
Should meta saved as text or as native json. Result is always serialized as text.
AWS DynamoDB backend settings¶
Note
The Dynamodb backend requires the boto3 library.
To install this package use pip:
$ pip install celery[dynamodb]
See Bundles for information on combining multiple extension requirements.
Warning
The Dynamodb backend is not compatible with tables that have a sort key defined.
If you want to query the results table based on something other than the partition key, please define a global secondary index (GSI) instead.
This backend requires the result_backend
setting to be set to a DynamoDB URL:
result_backend = 'dynamodb://aws_access_key_id:aws_secret_access_key@region:port/table?read=n&write=m'
For example, specifying the AWS region and the table name:
result_backend = 'dynamodb://@us-east-1/celery_results'
or retrieving AWS configuration parameters from the environment, using the default table name (celery)
and specifying read and write provisioned throughput:
result_backend = 'dynamodb://@/?read=5&write=5'
or using the downloadable version of DynamoDB locally:
result_backend = 'dynamodb://@localhost:8000'
or using downloadable version or other service with conforming API deployed on any host:
result_backend = 'dynamodb://@us-east-1'
dynamodb_endpoint_url = 'http://192.168.0.40:8000'
The fields of the DynamoDB URL in result_backend are defined as follows:
aws_access_key_id & aws_secret_access_keyregionThe AWS region, e.g.
us-east-1orlocalhostfor the Downloadable Version. See the boto3 library documentation for definition options.portThe listening port of the local DynamoDB instance, if you are using the downloadable version. If you have not specified the
regionparameter aslocalhost, setting this parameter has no effect.tableTable name to use. Default is
celery. See the DynamoDB Naming Rules for information on the allowed characters and length.read & writeThe Read & Write Capacity Units for the created DynamoDB table. Default is
1for both read and write. More details can be found in the Provisioned Throughput documentation.ttl_secondsTime-to-live (in seconds) for results before they expire. The default is to not expire results, while also leaving the DynamoDB table’s Time to Live settings untouched. If
ttl_secondsis set to a positive value, results will expire after the specified number of seconds. Settingttl_secondsto a negative value means to not expire results, and also to actively disable the DynamoDB table’s Time to Live setting. Note that trying to change a table’s Time to Live setting multiple times in quick succession will cause a throttling error. More details can be found in the DynamoDB TTL documentation
IronCache backend settings¶
Note
The IronCache backend requires the iron_celery library:
To install this package use pip:
$ pip install iron_celery
IronCache is configured via the URL provided in result_backend, for example:
result_backend = 'ironcache://project_id:token@'
Or to change the cache name:
ironcache:://project_id:token@/awesomecache
For more information, see: https://github.com/iron-io/iron_celery
Couchbase backend settings¶
Note
The Couchbase backend requires the couchbase library.
To install this package use pip:
$ pip install celery[couchbase]
See Bundles for instructions how to combine multiple extension requirements.
This backend can be configured via the result_backend
set to a Couchbase URL:
result_backend = 'couchbase://username:password@host:port/bucket'
couchbase_backend_settings¶
Default: {} (empty mapping).
This is a dict supporting the following keys:
hostHost name of the Couchbase server. Defaults to
localhost.portThe port the Couchbase server is listening to. Defaults to
8091.bucketThe default bucket the Couchbase server is writing to. Defaults to
default.usernameUser name to authenticate to the Couchbase server as (optional).
passwordPassword to authenticate to the Couchbase server (optional).
ArangoDB backend settings¶
Note
The ArangoDB backend requires the pyArango library.
To install this package use pip:
$ pip install celery[arangodb]
See Bundles for instructions how to combine multiple extension requirements.
This backend can be configured via the result_backend
set to a ArangoDB URL:
result_backend = 'arangodb://username:password@host:port/database/collection'
arangodb_backend_settings¶
Default: {} (empty mapping).
This is a dict supporting the following keys:
hostHost name of the ArangoDB server. Defaults to
localhost.portThe port the ArangoDB server is listening to. Defaults to
8529.databaseThe default database in the ArangoDB server is writing to. Defaults to
celery.collectionThe default collection in the ArangoDB servers database is writing to. Defaults to
celery.usernameUser name to authenticate to the ArangoDB server as (optional).
passwordPassword to authenticate to the ArangoDB server (optional).
http_protocolHTTP Protocol in ArangoDB server connection. Defaults to
http.verifyHTTPS Verification check while creating the ArangoDB connection. Defaults to
False.
CosmosDB backend settings (experimental)¶
To use CosmosDB as the result backend, you simply need to configure the
result_backend setting with the correct URL.
Example configuration¶
result_backend = 'cosmosdbsql://:{InsertAccountPrimaryKeyHere}@{InsertAccountNameHere}.documents.azure.com'
cosmosdbsql_database_name¶
Default: celerydb.
The name for the database in which to store the results.
cosmosdbsql_collection_name¶
Default: celerycol.
The name of the collection in which to store the results.
cosmosdbsql_consistency_level¶
Default: Session.
Represents the consistency levels supported for Azure Cosmos DB client operations.
Consistency levels by order of strength are: Strong, BoundedStaleness, Session, ConsistentPrefix and Eventual.
cosmosdbsql_max_retry_attempts¶
Default: 9.
Maximum number of retries to be performed for a request.
cosmosdbsql_max_retry_wait_time¶
Default: 30.
Maximum wait time in seconds to wait for a request while the retries are happening.
CouchDB backend settings¶
Note
The CouchDB backend requires the pycouchdb library:
To install this Couchbase package use pip:
$ pip install celery[couchdb]
See Bundles for information on combining multiple extension requirements.
This backend can be configured via the result_backend
set to a CouchDB URL:
result_backend = 'couchdb://username:password@host:port/container'
The URL is formed out of the following parts:
usernameUser name to authenticate to the CouchDB server as (optional).
passwordPassword to authenticate to the CouchDB server (optional).
hostHost name of the CouchDB server. Defaults to
localhost.portThe port the CouchDB server is listening to. Defaults to
8091.containerThe default container the CouchDB server is writing to. Defaults to
default.
File-system backend settings¶
This backend can be configured using a file URL, for example:
CELERY_RESULT_BACKEND = 'file:///var/celery/results'
The configured directory needs to be shared and writable by all servers using the backend.
If you’re trying Celery on a single system you can simply use the backend without any further configuration. For larger clusters you could use NFS, GlusterFS, CIFS, HDFS (using FUSE), or any other file-system.
Consul K/V store backend settings¶
Note
The Consul backend requires the python-consul2 library:
To install this package use pip:
$ pip install python-consul2
The Consul backend can be configured using a URL, for example:
CELERY_RESULT_BACKEND = 'consul://localhost:8500/'
or:
result_backend = 'consul://localhost:8500/'
The backend will store results in the K/V store of Consul as individual keys. The backend supports auto expire of results using TTLs in Consul. The full syntax of the URL is:
consul://host:port[?one_client=1]
The URL is formed out of the following parts:
hostHost name of the Consul server.
portThe port the Consul server is listening to.
one_clientBy default, for correctness, the backend uses a separate client connection per operation. In cases of extreme load, the rate of creation of new connections can cause HTTP 429 “too many connections” error responses from the Consul server when under load. The recommended way to handle this is to enable retries in
python-consul2using the patch at https://github.com/poppyred/python-consul2/pull/31.Alternatively, if
one_clientis set, a single client connection will be used for all operations instead. This should eliminate the HTTP 429 errors, but the storage of results in the backend can become unreliable.
Message Routing¶
task_queues¶
Default: None (queue taken from default queue settings).
Most users will not want to specify this setting and should rather use the automatic routing facilities.
If you really want to configure advanced routing, this setting should
be a list of kombu.Queue objects the worker will consume from.
Note that workers can be overridden this setting via the
-Q option, or individual queues from this
list (by name) can be excluded using the -X
option.
Also see Basics for more information.
The default is a queue/exchange/binding key of celery, with
exchange type direct.
See also task_routes
task_routes¶
Default: None.
A list of routers, or a single router used to route tasks to queues. When deciding the final destination of a task the routers are consulted in order.
A router can be specified as either:
A function with the signature
(name, args, kwargs, options, task=None, **kwargs)A string providing the path to a router function.
- A dict containing router specification:
Will be converted to a
celery.routes.MapRouteinstance.
- A list of
(pattern, route)tuples: Will be converted to a
celery.routes.MapRouteinstance.
- A list of
Examples:
task_routes = {
'celery.ping': 'default',
'mytasks.add': 'cpu-bound',
'feed.tasks.*': 'feeds', # <-- glob pattern
re.compile(r'(image|video)\.tasks\..*'): 'media', # <-- regex
'video.encode': {
'queue': 'video',
'exchange': 'media',
'routing_key': 'media.video.encode',
},
}
task_routes = ('myapp.tasks.route_task', {'celery.ping': 'default'})
Where myapp.tasks.route_task could be:
def route_task(self, name, args, kwargs, options, task=None, **kw):
if task == 'celery.ping':
return {'queue': 'default'}
route_task may return a string or a dict. A string then means
it’s a queue name in task_queues, a dict means it’s a custom route.
When sending tasks, the routers are consulted in order. The first
router that doesn’t return None is the route to use. The message options
is then merged with the found route settings, where the task’s settings
have priority.
Example if apply_async() has these arguments:
Task.apply_async(immediate=False, exchange='video',
routing_key='video.compress')
and a router returns:
{'immediate': True, 'exchange': 'urgent'}
the final message options will be:
immediate=False, exchange='video', routing_key='video.compress'
(and any default message options defined in the
Task class)
Values defined in task_routes have precedence over values defined in
task_queues when merging the two.
With the follow settings:
task_queues = {
'cpubound': {
'exchange': 'cpubound',
'routing_key': 'cpubound',
},
}
task_routes = {
'tasks.add': {
'queue': 'cpubound',
'routing_key': 'tasks.add',
'serializer': 'json',
},
}
The final routing options for tasks.add will become:
{'exchange': 'cpubound',
'routing_key': 'tasks.add',
'serializer': 'json'}
See Routers for more examples.
task_queue_max_priority¶
- brokers:
RabbitMQ
Default: None.
task_default_priority¶
- brokers:
RabbitMQ, Redis
Default: None.
task_inherit_parent_priority¶
- brokers:
RabbitMQ
Default: False.
If enabled, child tasks will inherit priority of the parent task.
# The last task in chain will also have priority set to 5.
chain = celery.chain(add.s(2) | add.s(2).set(priority=5) | add.s(3))
Priority inheritance also works when calling child tasks from a parent task with delay or apply_async.
worker_direct¶
Default: Disabled.
This option enables so that every worker has a dedicated queue, so that tasks can be routed to specific workers.
The queue name for each worker is automatically generated based on
the worker hostname and a .dq suffix, using the C.dq exchange.
For example the queue name for the worker with node name w1@example.com
becomes:
w1@example.com.dq
Then you can route the task to the task by specifying the hostname
as the routing key and the C.dq exchange:
task_routes = {
'tasks.add': {'exchange': 'C.dq', 'routing_key': 'w1@example.com'}
}
task_create_missing_queues¶
Default: Enabled.
If enabled (default), any queues specified that aren’t defined in
task_queues will be automatically created. See
Automatic routing.
task_default_queue¶
Default: "celery".
The name of the default queue used by .apply_async if the message has no route or no custom queue has been specified.
This queue must be listed in task_queues.
If task_queues isn’t specified then it’s automatically
created containing one queue entry, where this name is used as the name of
that queue.
task_default_exchange¶
Default: Uses the value set for task_default_queue.
Name of the default exchange to use when no custom exchange is
specified for a key in the task_queues setting.
task_default_exchange_type¶
Default: "direct".
Default exchange type used when no custom exchange type is specified
for a key in the task_queues setting.
task_default_routing_key¶
Default: Uses the value set for task_default_queue.
The default routing key used when no custom routing key
is specified for a key in the task_queues setting.
task_default_delivery_mode¶
Default: "persistent".
Can be transient (messages not written to disk) or persistent (written to disk).
Broker Settings¶
broker_url¶
Default: "amqp://"
Default broker URL. This must be a URL in the form of:
transport://userid:password@hostname:port/virtual_host
Only the scheme part (transport://) is required, the rest
is optional, and defaults to the specific transports default values.
The transport part is the broker implementation to use, and the
default is amqp, (uses librabbitmq if installed or falls back to
pyamqp). There are also other choices available, including;
redis://, sqs://, and qpid://.
The scheme can also be a fully qualified path to your own transport implementation:
broker_url = 'proj.transports.MyTransport://localhost'
More than one broker URL, of the same transport, can also be specified. The broker URLs can be passed in as a single string that’s semicolon delimited:
broker_url = 'transport://userid:password@hostname:port//;transport://userid:password@hostname:port//'
Or as a list:
broker_url = [
'transport://userid:password@localhost:port//',
'transport://userid:password@hostname:port//'
]
The brokers will then be used in the broker_failover_strategy.
See kombu:connection-urls in the Kombu documentation for more information.
broker_read_url / broker_write_url¶
Default: Taken from broker_url.
These settings can be configured, instead of broker_url to specify
different connection parameters for broker connections used for consuming and
producing.
Example:
broker_read_url = 'amqp://user:pass@broker.example.com:56721'
broker_write_url = 'amqp://user:pass@broker.example.com:56722'
Both options can also be specified as a list for failover alternates, see
broker_url for more information.
broker_failover_strategy¶
Default: "round-robin".
Default failover strategy for the broker Connection object. If supplied, may map to a key in ‘kombu.connection.failover_strategies’, or be a reference to any method that yields a single item from a supplied list.
Example:
# Random failover strategy
def random_failover_strategy(servers):
it = list(servers) # don't modify callers list
shuffle = random.shuffle
for _ in repeat(None):
shuffle(it)
yield it[0]
broker_failover_strategy = random_failover_strategy
broker_heartbeat¶
- transports supported:
pyamqp
Default: 120.0 (negotiated by server).
Note: This value is only used by the worker, clients do not use a heartbeat at the moment.
It’s not always possible to detect connection loss in a timely manner using TCP/IP alone, so AMQP defines something called heartbeats that’s is used both by the client and the broker to detect if a connection was closed.
If the heartbeat value is 10 seconds, then
the heartbeat will be monitored at the interval specified
by the broker_heartbeat_checkrate setting (by default
this is set to double the rate of the heartbeat value,
so for the 10 seconds, the heartbeat is checked every 5 seconds).
broker_heartbeat_checkrate¶
- transports supported:
pyamqp
Default: 2.0.
At intervals the worker will monitor that the broker hasn’t missed
too many heartbeats. The rate at which this is checked is calculated
by dividing the broker_heartbeat value with this value,
so if the heartbeat is 10.0 and the rate is the default 2.0, the check
will be performed every 5 seconds (twice the heartbeat sending rate).
broker_use_ssl¶
- transports supported:
pyamqp,redis
Default: Disabled.
Toggles SSL usage on broker connection and SSL settings.
The valid values for this option vary by transport.
pyamqp¶
If True the connection will use SSL with default SSL settings.
If set to a dict, will configure SSL connection according to the specified
policy. The format used is Python’s ssl.wrap_socket() options.
Note that SSL socket is generally served on a separate port by the broker.
Example providing a client cert and validating the server cert against a custom certificate authority:
import ssl
broker_use_ssl = {
'keyfile': '/var/ssl/private/worker-key.pem',
'certfile': '/var/ssl/amqp-server-cert.pem',
'ca_certs': '/var/ssl/myca.pem',
'cert_reqs': ssl.CERT_REQUIRED
}
Warning
Be careful using broker_use_ssl=True. It’s possible that your default
configuration won’t validate the server cert at all. Please read Python
ssl module security
considerations.
redis¶
The setting must be a dict with the following keys:
ssl_cert_reqs(required): one of theSSLContext.verify_modevalues:ssl.CERT_NONEssl.CERT_OPTIONALssl.CERT_REQUIRED
ssl_ca_certs(optional): path to the CA certificatessl_certfile(optional): path to the client certificatessl_keyfile(optional): path to the client key
broker_pool_limit¶
New in version 2.3.
Default: 10.
The maximum number of connections that can be open in the connection pool.
The pool is enabled by default since version 2.5, with a default limit of ten connections. This number can be tweaked depending on the number of threads/green-threads (eventlet/gevent) using a connection. For example running eventlet with 1000 greenlets that use a connection to the broker, contention can arise and you should consider increasing the limit.
If set to None or 0 the connection pool will be disabled and
connections will be established and closed for every use.
broker_connection_timeout¶
Default: 4.0.
The default timeout in seconds before we give up establishing a connection to the AMQP server. This setting is disabled when using gevent.
Note
The broker connection timeout only applies to a worker attempting to
connect to the broker. It does not apply to producer sending a task, see
broker_transport_options for how to provide a timeout for that
situation.
broker_connection_retry¶
Default: Enabled.
Automatically try to re-establish the connection to the AMQP broker if lost.
The time between retries is increased for each retry, and is
not exhausted before broker_connection_max_retries is
exceeded.
broker_connection_max_retries¶
Default: 100.
Maximum number of retries before we give up re-establishing a connection to the AMQP broker.
If this is set to 0 or None, we’ll retry forever.
broker_login_method¶
Default: "AMQPLAIN".
Set custom amqp login method.
broker_transport_options¶
New in version 2.2.
Default: {} (empty mapping).
A dict of additional options passed to the underlying transport.
See your transport user manual for supported options (if any).
Example setting the visibility timeout (supported by Redis and SQS transports):
broker_transport_options = {'visibility_timeout': 18000} # 5 hours
Example setting the producer connection maximum number of retries (so producers won’t retry forever if the broker isn’t available at the first task execution):
broker_transport_options = {'max_retries': 5}
Worker¶
imports¶
Default: [] (empty list).
A sequence of modules to import when the worker starts.
This is used to specify the task modules to import, but also to import signal handlers and additional remote control commands, etc.
The modules will be imported in the original order.
include¶
Default: [] (empty list).
Exact same semantics as imports, but can be used as a means
to have different import categories.
The modules in this setting are imported after the modules in
imports.
worker_deduplicate_successful_tasks¶
New in version 5.1.
Default: False
Before each task execution, instruct the worker to check if this task is a duplicate message.
Deduplication occurs only with tasks that have the same identifier,
enabled late acknowledgment, were redelivered by the message broker
and their state is SUCCESS in the result backend.
To avoid overflowing the result backend with queries, a local cache of successfully executed tasks is checked before querying the result backend in case the task was already successfully executed by the same worker that received the task.
This cache can be made persistent by setting the worker_state_db
setting.
If the result backend is not persistent (the RPC backend, for example), this setting is ignored.
worker_concurrency¶
Default: Number of CPU cores.
The number of concurrent worker processes/threads/green threads executing tasks.
If you’re doing mostly I/O you can have more processes, but if mostly CPU-bound, try to keep it close to the number of CPUs on your machine. If not set, the number of CPUs/cores on the host will be used.
worker_prefetch_multiplier¶
Default: 4.
How many messages to prefetch at a time multiplied by the number of concurrent processes. The default is 4 (four messages for each process). The default setting is usually a good choice, however – if you have very long running tasks waiting in the queue and you have to start the workers, note that the first worker to start will receive four times the number of messages initially. Thus the tasks may not be fairly distributed to the workers.
To disable prefetching, set worker_prefetch_multiplier to 1.
Changing that setting to 0 will allow the worker to keep consuming
as many messages as it wants.
For more on prefetching, read Prefetch Limits
Note
Tasks with ETA/countdown aren’t affected by prefetch limits.
worker_lost_wait¶
Default: 10.0 seconds.
In some cases a worker may be killed without proper cleanup,
and the worker may have published a result before terminating.
This value specifies how long we wait for any missing results before
raising a WorkerLostError exception.
worker_max_tasks_per_child¶
Maximum number of tasks a pool worker process can execute before it’s replaced with a new one. Default is no limit.
worker_max_memory_per_child¶
Default: No limit. Type: int (kilobytes)
Maximum amount of resident memory, in kilobytes, that may be consumed by a worker before it will be replaced by a new worker. If a single task causes a worker to exceed this limit, the task will be completed, and the worker will be replaced afterwards.
Example:
worker_max_memory_per_child = 12000 # 12MB
worker_disable_rate_limits¶
Default: Disabled (rate limits enabled).
Disable all rate limits, even if tasks has explicit rate limits set.
worker_state_db¶
Default: None.
Name of the file used to stores persistent worker state (like revoked tasks). Can be a relative or absolute path, but be aware that the suffix .db may be appended to the file name (depending on Python version).
Can also be set via the celery worker --statedb argument.
worker_timer_precision¶
Default: 1.0 seconds.
Set the maximum time in seconds that the ETA scheduler can sleep between rechecking the schedule.
Setting this value to 1 second means the schedulers precision will be 1 second. If you need near millisecond precision you can set this to 0.1.
worker_enable_remote_control¶
Default: Enabled by default.
Specify if remote control of the workers is enabled.
worker_proc_alive_timeout¶
Default: 4.0.
The timeout in seconds (int/float) when waiting for a new worker process to start up.
worker_cancel_long_running_tasks_on_connection_loss¶
New in version 5.1.
Default: Disabled by default.
Kill all long-running tasks with late acknowledgment enabled on connection loss.
Tasks which have not been acknowledged before the connection loss cannot do so anymore since their channel is gone and the task is redelivered back to the queue. This is why tasks with late acknowledged enabled must be idempotent as they may be executed more than once. In this case, the task is being executed twice per connection loss (and sometimes in parallel in other workers).
When turning this option on, those tasks which have not been completed are
cancelled and their execution is terminated.
Tasks which have completed in any way before the connection loss
are recorded as such in the result backend as long as task_ignore_result is not enabled.
Warning
This feature was introduced as a future breaking change. If it is turned off, Celery will emit a warning message.
In Celery 6.0, the worker_cancel_long_running_tasks_on_connection_loss
will be set to True by default as the current behavior leads to more
problems than it solves.
Events¶
worker_send_task_events¶
Default: Disabled by default.
Send task-related events so that tasks can be monitored using tools like
flower. Sets the default value for the workers
-E argument.
task_send_sent_event¶
New in version 2.2.
Default: Disabled by default.
If enabled, a task-sent event will be sent for every task so tasks can be
tracked before they’re consumed by a worker.
event_queue_ttl¶
- transports supported:
amqp
Default: 5.0 seconds.
Message expiry time in seconds (int/float) for when messages sent to a monitor clients
event queue is deleted (x-message-ttl)
For example, if this value is set to 10 then a message delivered to this queue will be deleted after 10 seconds.
event_queue_expires¶
- transports supported:
amqp
Default: 60.0 seconds.
Expiry time in seconds (int/float) for when after a monitor clients
event queue will be deleted (x-expires).
event_queue_prefix¶
Default: "celeryev".
The prefix to use for event receiver queue names.
event_exchange¶
Default: "celeryev".
Name of the event exchange.
Warning
This option is in experimental stage, please use it with caution.
event_serializer¶
Default: "json".
Message serialization format used when sending event messages.
See also
Remote Control Commands¶
Note
To disable remote control commands see
the worker_enable_remote_control setting.
control_queue_ttl¶
Default: 300.0
Time in seconds, before a message in a remote control command queue will expire.
If using the default of 300 seconds, this means that if a remote control command is sent and no worker picks it up within 300 seconds, the command is discarded.
This setting also applies to remote control reply queues.
control_queue_expires¶
Default: 10.0
Time in seconds, before an unused remote control command queue is deleted from the broker.
This setting also applies to remote control reply queues.
control_exchange¶
Default: "celery".
Name of the control command exchange.
Warning
This option is in experimental stage, please use it with caution.
Logging¶
worker_hijack_root_logger¶
New in version 2.2.
Default: Enabled by default (hijack root logger).
By default any previously configured handlers on the root logger will be removed. If you want to customize your own logging handlers, then you can disable this behavior by setting worker_hijack_root_logger = False.
Note
Logging can also be customized by connecting to the
celery.signals.setup_logging signal.
worker_log_color¶
Default: Enabled if app is logging to a terminal.
Enables/disables colors in logging output by the Celery apps.
worker_log_format¶
Default:
"[%(asctime)s: %(levelname)s/%(processName)s] %(message)s"
The format to use for log messages.
See the Python logging module for more information about log
formats.
worker_task_log_format¶
Default:
"[%(asctime)s: %(levelname)s/%(processName)s]
%(task_name)s[%(task_id)s]: %(message)s"
The format to use for log messages logged in tasks.
See the Python logging module for more information about log
formats.
worker_redirect_stdouts¶
Default: Enabled by default.
If enabled stdout and stderr will be redirected to the current logger.
Used by celery worker and celery beat.
worker_redirect_stdouts_level¶
Default: WARNING.
The log level output to stdout and stderr is logged as.
Can be one of DEBUG, INFO, WARNING,
ERROR, or CRITICAL.
Security¶
security_key¶
Default: None.
New in version 2.5.
The relative or absolute path to a file containing the private key used to sign messages when Message Signing is used.
security_certificate¶
Default: None.
New in version 2.5.
The relative or absolute path to an X.509 certificate file used to sign messages when Message Signing is used.
security_cert_store¶
Default: None.
New in version 2.5.
The directory containing X.509 certificates used for
Message Signing. Can be a glob with wild-cards,
(for example /etc/certs/*.pem).
security_digest¶
Default: sha256.
New in version 4.3.
A cryptography digest used to sign messages when Message Signing is used. https://cryptography.io/en/latest/hazmat/primitives/cryptographic-hashes/#module-cryptography.hazmat.primitives.hashes
Custom Component Classes (advanced)¶
worker_pool¶
Default: "prefork" (celery.concurrency.prefork:TaskPool).
Name of the pool class used by the worker.
Eventlet/Gevent
Never use this option to select the eventlet or gevent pool.
You must use the -P option to
celery worker instead, to ensure the monkey patches
aren’t applied too late, causing things to break in strange ways.
worker_pool_restarts¶
Default: Disabled by default.
If enabled the worker pool can be restarted using the
pool_restart remote control command.
worker_autoscaler¶
New in version 2.2.
Default: "celery.worker.autoscale:Autoscaler".
Name of the autoscaler class to use.
worker_consumer¶
Default: "celery.worker.consumer:Consumer".
Name of the consumer class used by the worker.
worker_timer¶
Default: "kombu.asynchronous.hub.timer:Timer".
Name of the ETA scheduler class used by the worker. Default is or set by the pool implementation.
Beat Settings (celery beat)¶
beat_schedule¶
Default: {} (empty mapping).
beat_scheduler¶
Default: "celery.beat:PersistentScheduler".
The default scheduler class. May be set to
"django_celery_beat.schedulers:DatabaseScheduler" for instance,
if used alongside django-celery-beat extension.
Can also be set via the celery beat -S argument.
beat_schedule_filename¶
Default: "celerybeat-schedule".
Name of the file used by PersistentScheduler to store the last run times of periodic tasks. Can be a relative or absolute path, but be aware that the suffix .db may be appended to the file name (depending on Python version).
Can also be set via the celery beat --schedule argument.
beat_sync_every¶
Default: 0.
The number of periodic tasks that can be called before another database sync is issued. A value of 0 (default) means sync based on timing - default of 3 minutes as determined by scheduler.sync_every. If set to 1, beat will call sync after every task message sent.
beat_max_loop_interval¶
Default: 0.
The maximum number of seconds beat can sleep
between checking the schedule.
The default for this value is scheduler specific. For the default Celery beat scheduler the value is 300 (5 minutes), but for the django-celery-beat database scheduler it’s 5 seconds because the schedule may be changed externally, and so it must take changes to the schedule into account.
Also when running Celery beat embedded (-B)
on Jython as a thread the max interval is overridden and set to 1 so
that it’s possible to shut down in a timely manner.
