📚 Documentation: Explore the Docs 📖

🔍 Source Code: View on GitHub 💾

PgQueuer is a minimalist, high-performance job queue library for Python, leveraging the robustness of PostgreSQL. Designed for simplicity and efficiency, PgQueuer uses PostgreSQL's LISTEN/NOTIFY to manage job queues effortlessly.

• Simple Integration: Easy to integrate with existing Python applications using PostgreSQL.
• Efficient Concurrency Handling: Utilizes PostgreSQL's FOR UPDATE SKIP LOCKED for reliable and concurrent job processing.
• Real-time Notifications: Leverages LISTEN and NOTIFY for real-time updates on job status changes.

To install PgQueuer, simply install with pip the following command:

pip install PgQueuer

Here's how you can use PgQueuer in a typical scenario processing incoming data messages:

import asyncio

import asyncpg
from PgQueuer.db import AsyncPGDriver
from PgQueuer.models import Job
from PgQueuer.qm import QueueManager


async def main() -> None:
    connection = await asyncpg.connect()
    driver = AsyncPGDriver(connection)
    qm = QueueManager(driver)

    # Setup the 'fetch' entrypoint
    @qm.entrypoint("fetch")
    async def process_message(job: Job) -> None:
        print(f"Processed message: {job}")

    N = 1_000
    # Enqueue jobs.
    await qm.queries.enqueue(
        ["fetch"] * N,
        [f"this is from me: {n}".encode() for n in range(N)],
        [0] * N,
    )

    await qm.run()


if __name__ == "__main__":
    asyncio.run(main())