Skip to main content

Package to facilitate queueing of jobs using Redis

Project description

Atlas Consortia JobQ

PyPI version

Atlas Consortia JobQ is a high-performance, Redis-backed priority queue system designed for background task management.

Table of Contents

Installation

Install the package via pip:

pip install atlas-consortia-jobq

Note: Requires a running Redis instance. Refer to the Redis documentation for instructions on installing and running Redis

Quick Start

1. Initialize the Queue

from atlas_consortia_jobq import JobQueue

# Connect to your Redis instance
jq = JobQueue(
    redis_host='localhost',
    redis_port=6379,
    redis_db=0,
    redis_password=None
)

2. Enqueue a Job

Jobs require a function, an entity_id, and optional arguments.

  • reference_id: A unique identifier generated for every specific job. This is created during the enqueing process and will be returned so the job may be referenced later.

  • entity_id: The unique identifier of the resource being processed (e.g., a UUID). This prevents the same resource from being queued multiple times.

def my_task(arg1, keyword_arg="default"):
    print(f"Processing: {arg1}, {keyword_arg}")

reference_id = jq.enqueue(
    task_func=my_task,
    entity_id="unique_id_123",
    args=["value1"],
    kwargs={"keyword_arg": "value2"},
    priority=2
)

Worker Management

To process jobs, you must start worker subprocesses. This is typically done in a dedicated entry-point script.

from atlas_consortia_jobq import JobQueue

if __name__ == "__main__":
    jq = JobQueue(redis_host='localhost')
    
    # This call spawns 4 worker subprocesses
    jq.start_workers(num_workers=4)

Method Reference

enqueue(task_func, entity_id, args=None, kwargs=None, priority=1)

Adds a job to the queue.

  • If the entity_id is already queued, it updates the priority if the new priority is higher.

  • If the entity_id is currently being processed, it prevents duplicate enqueuing.

update_priority(identifier, new_priority)

Updates the priority of an existing job. The identifier can be a reference_id or an entity_id.

get_status(identifier)

Returns a dictionary containing the reference_id, position_in_queue, and priority. Here "identifier" can be either the reference_id or the entity_id.

get_queue_status()

Returns an overview of the entire queue, including total job counts and a breakdown by priority level.

Features

  • Atomic Operations: Uses Lua scripting to ensure job enqueuing and popping are race-condition free.

  • entity_id Deduplication: Prevents multiple jobs for the same entity_id from cluttering the queue.

  • Priority Support: Supports three priority levels (1=Highest, 2=Medium, 3=Lowest).

  • Automatic Cleanup: Manages metadata and "processing" states automatically upon job completion.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

atlas_consortia_jobq-0.1.5.tar.gz (12.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

atlas_consortia_jobq-0.1.5-py3-none-any.whl (11.1 kB view details)

Uploaded Python 3

File details

Details for the file atlas_consortia_jobq-0.1.5.tar.gz.

File metadata

  • Download URL: atlas_consortia_jobq-0.1.5.tar.gz
  • Upload date:
  • Size: 12.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.9

File hashes

Hashes for atlas_consortia_jobq-0.1.5.tar.gz
Algorithm Hash digest
SHA256 5ee7417613dbf71789333f557be98fe6f1e61dc612af4de34c8632c71d1daadb
MD5 fb0801fc38e5d99ac87903622c4ec04b
BLAKE2b-256 2cbd621c20da467ede281f5f8a5e23fef0fa54766593f811285ec837b01c7b0a

See more details on using hashes here.

File details

Details for the file atlas_consortia_jobq-0.1.5-py3-none-any.whl.

File metadata

File hashes

Hashes for atlas_consortia_jobq-0.1.5-py3-none-any.whl
Algorithm Hash digest
SHA256 c148a5d2ba2d375d8070adb6035ca900d7b8e8f3ded3e37ab85ec488aa58209e
MD5 92f0146b282d8b82c5c2ad74844c7a36
BLAKE2b-256 4dd603c5eaa87f7fb6eaa375b1fc7cc1825229b03fb5ab91ade82c44fdc1d5e0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page