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

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📚 **Documentation**: [Explore the Docs](https://pgqueuer.readthedocs.io/en/latest/)
🔍 **Source Code**: [View on GitHub](https://github.com/janbjorge/pgqueuer/)
💬 **Join the Discussion**: [Discord Community](https://discord.gg/C7YMBzcRMQ)

---

PGQueuer is a minimalist, high-performance job queue library for Python, leveraging PostgreSQL's robustness. Designed with simplicity and efficiency in mind, PGQueuer offers real-time, high-throughput processing for background jobs using PostgreSQL's LISTEN/NOTIFY and `FOR UPDATE SKIP LOCKED` mechanisms.

## Features

- **💡 Simple Integration**: PGQueuer seamlessly integrates with any Python application using PostgreSQL, providing a clean and lightweight interface.
- **⚛️ Efficient Concurrency Handling**: Supports `FOR UPDATE SKIP LOCKED` to ensure reliable concurrency control and smooth job processing without contention.
- **🛠️ Real-time Notifications**: Uses PostgreSQL's `LISTEN` and `NOTIFY` commands to trigger real-time job status updates.
- **👨‍💼 Batch Processing**: Supports large job batches, optimizing enqueueing and dequeuing with minimal overhead.
- **⏳ Graceful Shutdowns**: Built-in signal handling ensures safe job processing shutdown without data loss.

## Installation

Install PGQueuer via pip:

```bash
pip install pgqueuer
```

## Quick Start

Below is a minimal example of how to use PGQueuer to process data.

### Step 1: Consumer - Run the Worker

Start a consumer to process incoming jobs as soon as they are enqueued. PGQueuer ensures graceful shutdowns using pre-configured signal handlers.

```python
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)

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

    return qm
```
Run the consumer:
```bash
pgq run examples.consumer.main
```

### Step 2: Producer - Add Jobs to Queue

Now, produce jobs that will be processed by the consumer. Below is a simple script to enqueue 10,000 jobs.

```python
import asyncio
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__":
    asyncio.run(main(10000))
```
Run the producer:
```bash
python3 examples/producer.py 10000
```

## Dashboard

Monitor job processing statistics in real-time using the built-in dashboard:

```bash
pgq dashboard --interval 10 --tail 25 --table-format grid
```
This provides a real-time, refreshing view of job queues and their status.

Example output:

```bash
+---------------------------+-------+------------+--------------------------+------------+----------+
|          Created          | Count | Entrypoint | Time in Queue (HH:MM:SS) |   Status   | Priority |
+---------------------------+-------+------------+--------------------------+------------+----------+
| 2024-05-05 16:44:26+00:00 |  49   |    sync    |         0:00:01          | successful |    0     |
...
+---------------------------+-------+------------+--------------------------+------------+----------+
```

## Why Choose PGQueuer?

- **Built for Scale**: Handles thousands of jobs per second, making it ideal for high-throughput applications.
- **PostgreSQL Native**: Utilizes advanced PostgreSQL features for robust job handling.
- **Flexible Concurrency**: Offers rate and concurrency limiting to cater to different use-cases, from bursty workloads to critical resource-bound tasks.

## Community & Support

Join our [Discord Community](https://discord.gg/C7YMBzcRMQ) to discuss PGQueuer, ask questions, and get support from other developers.

## License

PGQueuer is MIT licensed. See [LICENSE](LICENSE) for more information.

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Ready to supercharge your workflows? Install PGQueuer today and take your job management to the next level!
