Job Worker

High-performance, SQL-driven background job engine for Odoo.

Documentation | Migration Guide

Description

This repository provides three Odoo modules for background job processing:

• job_worker — Core queue engine with a persistent queue.job model, SQL pull worker (FOR UPDATE SKIP LOCKED) with PostgreSQL LISTEN/NOTIFY wakeups, channel-level concurrency and rate limiting, and developer APIs compatible with with_delay() / delayable() patterns.
• job_worker_demo — Interactive demo companion for exploring the queue system.
• job_worker_monitor — Dashboard, metrics, and alerting for queue operations.

Requirements

• Odoo 19.0
• PostgreSQL 12+ (including PostgreSQL 18)

PostgreSQL 18 Note: Version 18 has stricter serialization checks under REPEATABLE READ isolation. This module uses READ COMMITTED isolation for heartbeat and status updates to avoid serialization failures while maintaining correct concurrent behavior.

Installation

1. Place the job_worker, job_worker_demo, and job_worker_monitor directories in your Odoo addons path.
2. Update the apps list and install Job Worker.

odoo -d <db_name> \
  --addons-path=/path/to/odoo/addons,/path/to/job-worker-modules \
  -i job_worker \
  --stop-after-init

Configuration

Start a Worker Process

The worker class is odoo.addons.job_worker.cli.worker.QueueWorker.

Basic launcher (recommended as a dedicated process/service):

# run_worker.py
import odoo
from odoo.tools import config

from odoo.addons.job_worker.cli.worker import QueueWorker

config.parse_config([
    "-c", "/etc/odoo/odoo.conf",
    "-d", "<db_name>",
])

odoo.service.server.load_server_wide_modules()
registry = odoo.modules.registry.Registry(config["db_name"])

worker = QueueWorker(config["db_name"])
worker.run()

Then run:

python run_worker.py

Operational notes:

• Worker listens on channel queue_job_wake_up.
• Jobs are recovered if stale (started + old/missing heartbeat).
• Retry backoff is exponential: 10s, 20s, 40s, ... until max_retries.

Channel Throttling (queue.limit)

Configure per-channel limits using model queue.limit:

• limit: max concurrent jobs.
• rate_limit: jobs/second (0 means unlimited).

Configure in the UI under the Queue menus provided by the module.

Security Roles

• Queue Job User: view and operate their own jobs.
• Queue Job Manager: includes user rights, can view all jobs, and can configure channels.

Usage

Direct API

job = env["queue.job"].enqueue(
    model_name="res.partner",
    method_name="write",
    record_ids=[partner.id],
    args=[{"name": "Updated by queue"}],
    kwargs={},
    channel="root",
    priority=10,
    max_retries=5,
)

with_delay() shortcut

job = partner.with_delay(priority=5, channel="exports").write({"name": "Queued"})

delayable() explicit scheduling

delayable = partner.delayable(priority=5, channel="exports").write({"name": "Queued"})
job = delayable.delay()

eta and scheduled_at are supported aliases for scheduling. If both are provided, they must match.

Job Identity and Deduplication

Use identity_key to collapse duplicate active jobs:

job = env["queue.job"].enqueue(
    model_name="res.partner",
    method_name="write",
    record_ids=[partner.id],
    args=[{"name": "Queued once"}],
    kwargs={},
    identity_key=f"partner:{partner.id}:write_name",
)

If a job with the same identity_key already exists in waiting, pending, or started, the existing job is returned.

Job Execution Context

Each job stores:

• user_id: execution user.
• company_id: execution company.

Worker execution builds context from job metadata (user/company/lang/tz), then executes method calls in that context.

Operations and Troubleshooting

• Requeue failed jobs from the UI (button_requeue) to reset attempts/error and wake workers.
• Use list bulk actions on Queue Jobs > Jobs for:
  • Requeue selected jobs
  • Set selected jobs to done
  • Set selected jobs to failed
• Inspect fields: state, attempts, max_retries, exc_info, heartbeat, worker_id.
• If jobs are not running:
  1. Confirm worker process is running.
  2. Confirm scheduled_at is not in the future.
  3. Check channel limits (queue.limit).
  4. Check PostgreSQL connectivity and logs.

Development and Tests

Run the test suite using Docker:

bash docker/run_tests.sh

Bug Tracker

Bugs are tracked on GitHub Issues.

Credits

Authors

• OpenSPP

License

This project is licensed under the LGPL-3.0.