pgqueuer 0.8.10

Pgqueuer is a Python library leveraging PostgreSQL for efficient job queuing.

Readme

🚀 PGQueuer - Building Smoother Workflows One Queue at a Time 🚀

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🔍 Source Code: View on GitHub 💾

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PGQueuer

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.

Features

• 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.

Installation

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

pip install pgqueuer

Example Usage

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

Write and run a consumer

Start a long-lived consumer that will begin processing jobs as soon as they are enqueued by another process. In this case we want to be a bit more carefull as we want gracefull shutdowns, pgqueuer run will setup signals to ensure this.

from __future__ import annotations

import asyncpg
from pgqueuer.db import AsyncpgDriver, dsn
from pgqueuer.models import Job
from pgqueuer.qm import QueueManager


async def main() -> QueueManager:
    connection = await asyncpg.connect(dsn())
    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}")

    return qm

python3 -m pgqueuer run tools.consumer.main

Write and run a producer

Start a short-lived producer that will enqueue 10,000 jobs.

from __future__ import annotations

import asyncio
import sys

import asyncpg
from pgqueuer.db import AsyncpgDriver
from pgqueuer.queries import Queries


async def main(N: int) -> None:
    connection = await asyncpg.connect()
    driver = AsyncpgDriver(connection)
    queries = Queries(driver)
    await queries.enqueue(
        ["fetch"] * N,
        [f"this is from me: {n}".encode() for n in range(1, N+1)],
        [0] * N,
    )


if __name__ == "__main__":
    print(sys.argv)
    N = 1_000 if len(sys.argv) == 1 else int(sys.argv[1])
    asyncio.run(main(N))

python3 tools/producer.py 10000