PgQueuer is a Python library leveraging PostgreSQL for efficient job queuing.
Project description
🚀 PgQueuer - Building Smoother Workflows One Queue at a Time 🚀
📚 Documentation: Explore the Docs 📖
🔍 Source Code: View on GitHub 💾
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
andNOTIFY
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:
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())
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