request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message or if that’s not possible - cache often used data, or preload data you know is going to be used. The easiest way to share data between workers is to use a distributed cache system, like memcached [http://memcached

request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message or if that’s not possible - cache often used data, or preload data you know is going to be used. The easiest way to share data between workers is to use a distributed cache system, like memcached [http://memcached

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 See Redis server documentation about Eviction Policies for details: https://redis.io/topics/lru-cache Group result ordering Versions of Celery up to and including 4.4.6 used an unsorted list to store request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 See Redis server documentation about Eviction Policies for details: https://redis.io/topics/lru-cache Group result ordering Versions of Celery up to and including 4.4.6 used an unsorted list to store request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 See Redis server documentation about Eviction Policies for details: https://redis.io/topics/lru-cache Group result ordering Versions of Celery up to and including 4.4.6 used an unsorted list to store request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 See Redis server documentation about Eviction Policies for details: https://redis.io/topics/lru-cache Group result ordering Versions of Celery up to and including 4.4.6 used an unsorted list to store request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message

Elasticsearch, Riak MongoDB, CouchDB, Couchbase, ArangoDB Amazon DynamoDB, Amazon S3 Microsoft Azure Block Blob, Microsoft Azure Cosmos DB File system Serialization pickle, json, yaml, msgpack. zlib, bzip2 request to the same process, then it will keep state between requests. This can also be useful to cache resources, For example, a base Task class that caches a database connection: from celery import Task With smaller tasks you can process more tasks in parallel and the tasks won’t run long enough to block the worker from processing other waiting tasks. However, executing a task does have overhead. A message