Configuration and defaults
- Example configuration file
- Configuration Directives

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 is available on the Python path.

Example configuration file
Configuration Directives

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:[email protected]:5672//'
# List of modules to import when celery starts.
CELERY_IMPORTS = ('myapp.tasks', )
## Using the database to store task state and results.
CELERY_RESULT_BACKEND = 'db+sqlite:///results.db'
CELERY_ANNOTATIONS = {'tasks.add': {'rate_limit': '10/s'}}

Configuration Directives

Time and date settings

CELERY_ENABLE_UTC

2.5 新版功能.

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.

Enabled by default since version 3.0.

CELERY_TIMEZONE

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 is also a CELERY_ENABLE_UTC setting, and this is set to false the system local timezone is used instead.

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:

CELERY_ANNOTATIONS = {'tasks.add': {'rate_limit': '10/s'}}

or change the same for all tasks:

CELERY_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))
CELERY_ANNOTATIONS = {'*': {'on_failure': my_on_failure}}

If you need more flexibility then you can use objects instead of a dict to choose which tasks to annotate:

class MyAnnotate(object):
    def annotate(self, task):
        if task.name.startswith('tasks.'):
            return {'rate_limit': '10/s'}
CELERY_ANNOTATIONS = (MyAnnotate(), {…})

Concurrency settings

CELERYD_CONCURRENCY

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.

Defaults to the number of available CPUs.

CELERYD_PREFETCH_MULTIPLIER

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.

注解

Tasks with ETA/countdown are not affected by prefetch limits.

Task result backend settings

CELERY_RESULT_BACKEND

Deprecated aliases:
	`CELERY_BACKEND`

The backend used to store task results (tombstones). Disabled by default. Can be one of the following:

database

Use a relational database supported by SQLAlchemy. See Database backend settings.
cache

Use memcached to store the results. See Cache backend settings.
mongodb

Use MongoDB to store the results. See MongoDB backend settings.
redis

Use Redis to store the results. See Redis backend settings.
amqp

Send results back as AMQP messages See AMQP backend settings.
cassandra

Use Cassandra to store the results. See Cassandra backend settings.
ironcache

Use IronCache to store the results. See IronCache backend settings.
couchbase

Use Couchbase to store the results. See Couchbase backend settings.

CELERY_RESULT_SERIALIZER

Result serialization format. Default is pickle. See Serializers for information about supported serialization formats.

Database backend settings

Database URL Examples

To use the database backend you have to configure the CELERY_RESULT_BACKEND setting with a connection URL and the db+ prefix:

CELERY_RESULT_BACKEND = 'db+scheme://user:[email protected]:port/dbname'

Examples:

# sqlite (filename) CELERY_RESULT_BACKEND = ‘db+sqlite:///results.sqlite’

# mysql CELERY_RESULT_BACKEND = ‘db+mysql://scott:tiger@localhost/foo’

# postgresql CELERY_RESULT_BACKEND = ‘db+postgresql://scott:tiger@localhost/mydatabase’

# oracle CELERY_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 (which is the part of the URI that comes after the db+ prefix).

CELERY_RESULT_DBURI

This setting is no longer used as it’s now possible to specify the database URL directly in the CELERY_RESULT_BACKEND setting.

CELERY_RESULT_ENGINE_OPTIONS

To specify additional SQLAlchemy database engine options you can use the CELERY_RESULT_ENGINE_OPTIONS setting:

# echo enables verbose logging from SQLAlchemy.
CELERY_RESULT_ENGINE_OPTIONS = {'echo': True}

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.

Specifying Table Names

When SQLAlchemy is configured as the result backend, Celery automatically creates two tables to store result metadata for tasks. This setting allows you to customize the table names:

# use custom table names for the database result backend.
CELERY_RESULT_DB_TABLENAMES = {
    'task': 'myapp_taskmeta',
    'group': 'myapp_groupmeta',
}

AMQP backend settings

注解

The AMQP backend requires RabbitMQ 1.1.0 or higher to automatically expire results. If you are running an older version of RabbitmQ you should disable result expiration like this:

CELERY_TASK_RESULT_EXPIRES = None

CELERY_RESULT_EXCHANGE

Name of the exchange to publish results in. Default is celeryresults.

CELERY_RESULT_EXCHANGE_TYPE

The exchange type of the result exchange. Default is to use a direct exchange.

CELERY_RESULT_PERSISTENT

If set to True, result messages will be persistent. This means the messages will not be lost after a broker restart. The default is for the results to be transient.

Example configuration

CELERY_RESULT_BACKEND = 'amqp'
CELERY_TASK_RESULT_EXPIRES = 18000  # 5 hours.

Cache backend settings

注解

The cache backend supports the pylibmc and python-memcached libraries. The latter is used only if pylibmc is not installed.

Using a single memcached server:

CELERY_RESULT_BACKEND = 'cache+memcached://127.0.0.1:11211/'

Using multiple memcached servers:

CELERY_RESULT_BACKEND = """
    cache+memcached://172.19.26.240:11211;172.19.26.242:11211/
""".strip()

The “memory” backend stores the cache in memory only:

CELERY_CACHE_BACKEND = ‘memory’

CELERY_CACHE_BACKEND_OPTIONS

You can set pylibmc options using the CELERY_CACHE_BACKEND_OPTIONS setting:

CELERY_CACHE_BACKEND_OPTIONS = {'binary': True,
                                'behaviors': {'tcp_nodelay': True}}

CELERY_CACHE_BACKEND

This setting is no longer used as it’s now possible to specify the cache backend directly in the CELERY_RESULT_BACKEND setting.

Redis backend settings

Configuring the backend URL

注解

The Redis backend requires the redis library: http://pypi.python.org/pypi/redis/

To install the redis package use pip or easy_install:

$ pip install redis

This backend requires the CELERY_RESULT_BACKEND setting to be set to a Redis URL:

CELERY_RESULT_BACKEND = 'redis://:[email protected]:port/db'

For example:

CELERY_RESULT_BACKEND = 'redis://localhost/0'

which is the same as:

CELERY_RESULT_BACKEND = 'redis://'

The fields of the URL is defined as folows:

host

Host name or IP address of the Redis server. e.g. localhost.

port

Port to the Redis server. Default is 6379.

Database number to use. Default is 0. The db can include an optional leading slash.

password

Password used to connect to the database.

CELERY_REDIS_MAX_CONNECTIONS

Maximum number of connections available in the Redis connection pool used for sending and retrieving results.

MongoDB backend settings

注解

The MongoDB backend requires the pymongo library: http://github.com/mongodb/mongo-python-driver/tree/master

CELERY_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 pymongo docs to see a list of arguments supported.

Example configuration

CELERY_RESULT_BACKEND = 'mongodb://192.168.1.100:30000/'
CELERY_MONGODB_BACKEND_SETTINGS = {
    'database': 'mydb',
    'taskmeta_collection': 'my_taskmeta_collection',
}

Cassandra backend settings

注解

The Cassandra backend requires the pycassa library: http://pypi.python.org/pypi/pycassa/

To install the pycassa package use pip or easy_install:

$ pip install pycassa

This backend requires the following configuration directives to be set.

CASSANDRA_SERVERS

List of host:port Cassandra servers. e.g.:

CASSANDRA_SERVERS = ['localhost:9160']

CASSANDRA_KEYSPACE

The keyspace in which to store the results. e.g.:

CASSANDRA_KEYSPACE = 'tasks_keyspace'

CASSANDRA_COLUMN_FAMILY

The column family in which to store the results. e.g.:

CASSANDRA_COLUMN_FAMILY = 'tasks'

CASSANDRA_READ_CONSISTENCY

The read consistency used. Values can be ONE, QUORUM or ALL.

CASSANDRA_WRITE_CONSISTENCY

The write consistency used. Values can be ONE, QUORUM or ALL.

CASSANDRA_DETAILED_MODE

Enable or disable detailed mode. Default is False. This mode allows to use the power of Cassandra wide columns to store all states for a task as a wide column, instead of only the last one.

To use this mode, you need to configure your ColumnFamily to use the TimeUUID type as a comparator:

create column family task_results with comparator = TimeUUIDType;

CASSANDRA_OPTIONS

Options to be passed to the pycassa connection pool (optional).

Example configuration

CASSANDRA_SERVERS = ['localhost:9160']
CASSANDRA_KEYSPACE = 'celery'
CASSANDRA_COLUMN_FAMILY = 'task_results'
CASSANDRA_READ_CONSISTENCY = 'ONE'
CASSANDRA_WRITE_CONSISTENCY = 'ONE'
CASSANDRA_DETAILED_MODE = True
CASSANDRA_OPTIONS = {
    'timeout': 300,
    'max_retries': 10
}

IronCache backend settings

注解

The IronCache backend requires the iron_celery library: http://pypi.python.org/pypi/iron_celery

To install the iron_celery package use pip or easy_install:

$ pip install iron_celery

IronCache is configured via the URL provided in CELERY_RESULT_BACKEND, for example:

CELERY_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

注解

The Couchbase backend requires the couchbase library: https://pypi.python.org/pypi/couchbase

To install the couchbase package use pip or easy_install:

$ pip install couchbase

This backend can be configured via the CELERY_RESULT_BACKEND set to a couchbase URL:

CELERY_RESULT_BACKEND = 'couchbase://username:[email protected]:port/bucket'

CELERY_COUCHBASE_BACKEND_SETTINGS

This is a dict supporting the following keys:

host

Host name of the Couchbase server. Defaults to localhost.
port

The port the Couchbase server is listening to. Defaults to 8091.
bucket

The default bucket the Couchbase server is writing to. Defaults to default.
username

User name to authenticate to the Couchbase server as (optional).
password

Password to authenticate to the Couchbase server (optional).

Message Routing

CELERY_QUEUES

The mapping of queues the worker consumes from. This is a dictionary of queue name/options. See Routing Tasks for more information.

The default is a queue/exchange/binding key of celery, with exchange type direct.

You don’t have to care about this unless you want custom routing facilities.

CELERY_ROUTES

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. See Routers for more information.

CELERY_QUEUE_HA_POLICY

brokers:	RabbitMQ

This will set the default HA policy for a queue, and the value can either be a string (usually all):

CELERY_QUEUE_HA_POLICY = 'all'

Using ‘all’ will replicate the queue to all current nodes, Or you can give it a list of nodes to replicate to:

CELERY_QUEUE_HA_POLICY = ['[email protected]', '[email protected]']

Using a list will implicitly set x-ha-policy to ‘nodes’ and x-ha-policy-params to the given list of nodes.

See http://www.rabbitmq.com/ha.html for more information.

CELERY_WORKER_DIRECT

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:

CELERY_ROUTES = {
    'tasks.add': {'exchange': 'C.dq', 'routing_key': '[email protected]'}
}

CELERY_CREATE_MISSING_QUEUES

If enabled (default), any queues specified that are not defined in CELERY_QUEUES will be automatically created. See Automatic routing.

CELERY_DEFAULT_QUEUE

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 CELERY_QUEUES. If CELERY_QUEUES is not specified then it is automatically created containing one queue entry, where this name is used as the name of that queue.

The default is: celery.

参见

Changing the name of the default queue

CELERY_DEFAULT_EXCHANGE

Name of the default exchange to use when no custom exchange is specified for a key in the CELERY_QUEUES setting.

The default is: celery.

CELERY_DEFAULT_EXCHANGE_TYPE

Default exchange type used when no custom exchange type is specified for a key in the CELERY_QUEUES setting. The default is: direct.

CELERY_DEFAULT_ROUTING_KEY

The default routing key used when no custom routing key is specified for a key in the CELERY_QUEUES setting.

The default is: celery.

CELERY_DEFAULT_DELIVERY_MODE

Can be transient or persistent. The default is to send persistent messages.

Broker Settings

CELERY_ACCEPT_CONTENT

A whitelist of content-types/serializers to allow.

If a message is received that is not in this list then the message will be discarded with an error.

By default any content type is enabled (including pickle and yaml) so make sure untrusted parties do not have access to your broker. See Security for more.

Example:

# using serializer name
CELERY_ACCEPT_CONTENT = ['json']
# or the actual content-type (MIME)
CELERY_ACCEPT_CONTENT = ['application/json']

BROKER_FAILOVER_STRATEGY

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(it)  # don't modify callers list
    shuffle = random.shuffle
    for _ in repeat(None):
        shuffle(it)
        yield it[0]
BROKER_FAILOVER_STRATEGY=random_failover_strategy

BROKER_FAILOVER_STRATEGY

Example:

# Random failover strategy
def random_failover_strategy(servers):
    it = list(it)  # don't modify callers list
    shuffle = random.shuffle
    for _ in repeat(None):
        shuffle(it)
        yield it[0]
BROKER_FAILOVER_STRATEGY=random_failover_strategy

BROKER_TRANSPORT

Deprecated aliases:
Aliases:	`BROKER_BACKEND`
	`CARROT_BACKEND`

BROKER_URL

Default broker URL. This must be an 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, which uses librabbitmq by default or falls back to pyamqp if that is not installed. Also there are many other choices including redis, beanstalk, sqlalchemy, django, mongodb, couchdb. It can also be a fully qualified path to your own transport implementation.

See URLs in the Kombu documentation for more information.

BROKER_HEARTBEAT

transports supported:
	`pyamqp`

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.

Hartbeats are disabled by default.

If the heartbeat value is 10 seconds, then the heartbeat will be monitored at the interval specified by the BROKER_HEARTBEAT_CHECKRATE setting, which by default is double the rate of the heartbeat value (so for the default 10 seconds, the heartbeat is checked every 5 seconds).

BROKER_HEARTBEAT_CHECKRATE

transports supported:
	`pyamqp`

At intervals the worker will monitor that the broker has not 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

Use SSL to connect to the broker. Off by default. This may not be supported by all transports.

BROKER_POOL_LIMIT

2.3 新版功能.

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/greenthreads (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.

Default (since 2.5) is to use a pool of 10 connections.

BROKER_CONNECTION_TIMEOUT

The default timeout in seconds before we give up establishing a connection to the AMQP server. Default is 4 seconds.

BROKER_CONNECTION_RETRY

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.

This behavior is on by default.

BROKER_CONNECTION_MAX_RETRIES

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 will retry forever.

Default is 100 retries.

BROKER_LOGIN_METHOD

Set custom amqp login method, default is AMQPLAIN.

BROKER_TRANSPORT_OPTIONS

2.2 新版功能.

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

Task execution settings

CELERY_ALWAYS_EAGER

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, which 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.

CELERY_EAGER_PROPAGATES_EXCEPTIONS

If this is True, eagerly executed tasks (applied by task.apply(), or when the CELERY_ALWAYS_EAGER setting is enabled), will propagate exceptions.

It’s the same as always running apply() with throw=True.

CELERY_IGNORE_RESULT

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 CELERY_STORE_ERRORS_EVEN_IF_IGNORED.

CELERY_MESSAGE_COMPRESSION

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.

CELERY_TASK_RESULT_EXPIRES

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.task.backend_cleanup).

A value of None or 0 means results will never expire (depending on backend specifications).

Default is to expire after 1 day.

注解

For the moment this only works with the amqp, database, cache, redis and MongoDB backends.

When using the database or MongoDB backends, celery beat must be running for the results to be expired.

CELERY_MAX_CACHED_RESULTS

Result backends caches ready results used by the client.

This is the total number of results to cache before older results are evicted. The default is 5000.

CELERY_CHORD_PROPAGATES

3.0.14 新版功能.

This setting defines what happens when a task part of a chord raises an exception:

If propagate is True the chord callback will change state to FAILURE with the exception value set to a ChordError instance containing information about the error and the task that failed.

This is the default behavior in Celery 3.1+
If propagate is False the exception value will instead be forwarded to the chord callback.

This was the default behavior before version 3.1.

CELERY_TRACK_STARTED

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 behaviour 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 is a need to report which task is currently running.

CELERY_TASK_SERIALIZER

A string identifying the default serialization method to use. Can be pickle (default), json, yaml, msgpack or any custom serialization methods that have been registered with kombu.serialization.registry.

参见

Serializers.

CELERY_TASK_PUBLISH_RETRY

2.2 新版功能.

Decides if publishing task messages will be retried in the case of connection loss or other connection errors. See also CELERY_TASK_PUBLISH_RETRY_POLICY.

Enabled by default.

CELERY_TASK_PUBLISH_RETRY_POLICY

2.2 新版功能.

Defines the default policy when retrying publishing a task message in the case of connection loss or other connection errors.

See Message Sending Retry for more information.

CELERY_DEFAULT_RATE_LIMIT

The global default rate limit for tasks.

This value is used for tasks that does not have a custom rate limit The default is no rate limit.

CELERY_DISABLE_RATE_LIMITS

Disable all rate limits, even if tasks has explicit rate limits set.

CELERY_ACKS_LATE

Late ack means the task messages will be acknowledged after the task has been executed, not just before, which is the default behavior.

参见

FAQ: Should I use retry or acks_late?.

Worker

CELERY_IMPORTS

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.

CELERY_INCLUDE

Exact same semantics as CELERY_IMPORTS, but can be used as a means to have different import categories.

The modules in this setting are imported after the modules in CELERY_IMPORTS.

CELERYD_FORCE_EXECV

On Unix the prefork pool will fork, so that child processes start with the same memory as the parent process.

This can cause problems as there is a known deadlock condition with pthread locking primitives when fork() is combined with threads.

You should enable this setting if you are experiencing hangs (deadlocks), especially in combination with time limits or having a max tasks per child limit.

This option will be enabled by default in a later version.

This is not a problem on Windows, as it does not have fork().

CELERYD_WORKER_LOST_WAIT

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.

Default is 10.0

CELERYD_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.

CELERYD_TASK_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.

CELERYD_TASK_SOFT_TIME_LIMIT

Task soft time limit in seconds.

The SoftTimeLimitExceeded exception will be raised when this is exceeded. The task can catch this to e.g. clean up before the hard time limit comes.

Example:

from celery.exceptions import SoftTimeLimitExceeded
@app.task
def mytask():
    try:
        return do_work()
    except SoftTimeLimitExceeded:
        cleanup_in_a_hurry()

CELERY_STORE_ERRORS_EVEN_IF_IGNORED

If set, the worker stores all task errors in the result store even if Task.ignore_result is on.

CELERYD_STATE_DB

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 --statedb argument to worker.

Not enabled by default.

CELERYD_TIMER_PRECISION

Set the maximum time in seconds that the ETA scheduler can sleep between rechecking the schedule. Default is 1 second.

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.

CELERY_ENABLE_REMOTE_CONTROL

Specify if remote control of the workers is enabled.

Default is True.

Error E-Mails

CELERY_SEND_TASK_ERROR_EMAILS

The default value for the Task.send_error_emails attribute, which if set to True means errors occurring during task execution will be sent to ADMINS by email.

Disabled by default.

ADMINS

List of (name, email_address) tuples for the administrators that should receive error emails.

SERVER_EMAIL

The email address this worker sends emails from. Default is celery@localhost.

EMAIL_HOST

The mail server to use. Default is localhost.

EMAIL_HOST_USER

User name (if required) to log on to the mail server with.

EMAIL_HOST_PASSWORD

Password (if required) to log on to the mail server with.

EMAIL_PORT

The port the mail server is listening on. Default is 25.

EMAIL_USE_SSL

Use SSL when connecting to the SMTP server. Disabled by default.

EMAIL_USE_TLS

Use TLS when connecting to the SMTP server. Disabled by default.

EMAIL_TIMEOUT

Timeout in seconds for when we give up trying to connect to the SMTP server when sending emails.

The default is 2 seconds.

Example E-Mail configuration

This configuration enables the sending of error emails to george@vandelay.com and kramer@vandelay.com:

# Enables error emails.
CELERY_SEND_TASK_ERROR_EMAILS = True
# Name and email addresses of recipients
ADMINS = (
    ('George Costanza', '[email protected]'),
    ('Cosmo Kramer', '[email protected]'),
)
# Email address used as sender (From field).
SERVER_EMAIL = '[email protected]'
# Mailserver configuration
EMAIL_HOST = 'mail.vandelay.com'
EMAIL_PORT = 25
# EMAIL_HOST_USER = 'servers'
# EMAIL_HOST_PASSWORD = 's3cr3t'

Events

CELERY_SEND_EVENTS

Send events so the worker can be monitored by tools like celerymon.

CELERY_SEND_TASK_SENT_EVENT

2.2 新版功能.

If enabled, a task-sent event will be sent for every task so tasks can be tracked before they are consumed by a worker.

Disabled by default.

CELERY_EVENT_QUEUE_TTL

transports supported:
	`amqp`

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.

Disabled by default.

CELERY_EVENT_QUEUE_EXPIRES

transports supported:
	`amqp`

Expiry time in seconds (int/float) for when a monitor clients event queue will be deleted (x-expires).

Default is never, relying on the queue autodelete setting.

CELERY_EVENT_SERIALIZER

Message serialization format used when sending event messages. Default is json. See Serializers.

Broadcast Commands

CELERY_BROADCAST_QUEUE

Name prefix for the queue used when listening for broadcast messages. The workers host name will be appended to the prefix to create the final queue name.

Default is celeryctl.

CELERY_BROADCAST_EXCHANGE

Name of the exchange used for broadcast messages.

Default is celeryctl.

CELERY_BROADCAST_EXCHANGE_TYPE

Exchange type used for broadcast messages. Default is fanout.

Logging

CELERYD_HIJACK_ROOT_LOGGER

2.2 新版功能.

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 CELERYD_HIJACK_ROOT_LOGGER = False.

注解

Logging can also be customized by connecting to the celery.signals.setup_logging signal.

CELERYD_LOG_COLOR

Enables/disables colors in logging output by the Celery apps.

By default colors are enabled if

the app is logging to a real terminal, and not a file.
the app is not running on Windows.

CELERYD_LOG_FORMAT

The format to use for log messages.

Default is [%(asctime)s: %(levelname)s/%(processName)s] %(message)s

See the Python logging module for more information about log formats.

CELERYD_TASK_LOG_FORMAT

The format to use for log messages logged in tasks. Can be overridden using the --loglevel option to worker.

Default is:

[%(asctime)s: %(levelname)s/%(processName)s]
    [%(task_name)s(%(task_id)s)] %(message)s

See the Python logging module for more information about log formats.

CELERY_REDIRECT_STDOUTS

If enabled stdout and stderr will be redirected to the current logger.

Enabled by default. Used by celery worker and celery beat.

CELERY_REDIRECT_STDOUTS_LEVEL

The log level output to stdout and stderr is logged as. Can be one of DEBUG, INFO, WARNING, ERROR or CRITICAL.

Default is WARNING.

Security

CELERY_SECURITY_KEY

2.5 新版功能.

The relative or absolute path to a file containing the private key used to sign messages when Message Signing is used.

CELERY_SECURITY_CERTIFICATE

2.5 新版功能.

The relative or absolute path to an X.509 certificate file used to sign messages when Message Signing is used.

CELERY_SECURITY_CERT_STORE

2.5 新版功能.

The directory containing X.509 certificates used for Message Signing. Can be a glob with wildcards, (for example /etc/certs/*.pem).

Custom Component Classes (advanced)

CELERYD_POOL

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 instead, otherwise the monkey patching will happen too late and things will break in strange and silent ways.

Default is celery.concurrency.prefork:TaskPool.

CELERYD_POOL_RESTARTS

If enabled the worker pool can be restarted using the pool_restart remote control command.

Disabled by default.

CELERYD_AUTOSCALER

2.2 新版功能.

Name of the autoscaler class to use.

Default is celery.worker.autoscale:Autoscaler.

CELERYD_AUTORELOADER

Name of the autoreloader class used by the worker to reload Python modules and files that have changed.

Default is: celery.worker.autoreload:Autoreloader.

CELERYD_CONSUMER

Name of the consumer class used by the worker. Default is celery.worker.consumer.Consumer

CELERYD_TIMER

Name of the ETA scheduler class used by the worker. Default is celery.utils.timer2.Timer, or one overrided by the pool implementation.

Periodic Task Server: celery beat

CELERYBEAT_SCHEDULE

The periodic task schedule used by beat. See Entries.

CELERYBEAT_SCHEDULER

The default scheduler class. Default is celery.beat:PersistentScheduler.

Can also be set via the -S argument to beat.

CELERYBEAT_SCHEDULE_FILENAME

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 --schedule argument to beat.

CELERYBEAT_MAX_LOOP_INTERVAL

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 e.g. the django-celery database scheduler it is 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.

Monitor Server: celerymon

CELERYMON_LOG_FORMAT

The format to use for log messages.

Default is [%(asctime)s: %(levelname)s/%(processName)s] %(message)s

See the Python logging module for more information about log formats.