pgmq-sqlalchemy

More flexible PGMQ Postgres extension Python client that using sqlalchemy ORM, supporting both async and sync engines, sessionmakers or built from dsn.

Table of Contents

• pgmq-sqlalchemy
  • Features
  • Installation
  • Getting Started
    • Postgres Setup
    • Usage
    • Transaction Usage
    • FastAPI Pub/Sub Example with tests
  • Issue/ Contributing / Development
  • TODO

Features

• Supports async and sync engines and sessionmakers, or built from dsn.
• Supports all postgres DBAPIs supported by sqlalchemy.

  e.g. psycopg, psycopg2, asyncpg ..
  See SQLAlchemy Postgresql Dialects

• Transaction-friendly operations via the op module for combining PGMQ with your business logic in the same transaction.
• Fully tested across all supported DBAPIs in both async and sync modes.
• Battle-tested with real-world FastAPI Pub/Sub examples and corresponding tests.

Installation

Install with pip:

pip install pgmq-sqlalchemy

Install with additional DBAPIs packages:

pip install "pgmq-sqlalchemy[asyncpg]"
pip install "pgmq-sqlalchemy[psycopg2-binary]"
# pip install "pgmq-sqlalchemy[postgres-python-driver]"

Getting Started

Postgres Setup

Prerequisites: Postgres with PGMQ extension installed.
For quick setup:

docker run -d --name postgres -e POSTGRES_PASSWORD=postgres -p 5432:5432 quay.io/tembo/pg16-pgmq:latest

For more information, see PGMQ

Usage

Note

Check pgmq-sqlalchemy Document for more examples and detailed usage.

For dispatcher.py:

from typing import List
from pgmq_sqlalchemy import PGMQueue

postgres_dsn = 'postgresql://postgres:postgres@localhost:5432/postgres'

pgmq = PGMQueue(dsn=postgres_dsn)
pgmq.create_queue('my_queue')

msg = {'key': 'value', 'key2': 'value2'}
msg_id:int = pgmq.send('my_queue', msg)

# could also send a list of messages
msg_ids:List[int] = pgmq.send_batch('my_queue', [msg, msg])

For consumer.py:

from pgmq_sqlalchemy import PGMQueue
from pgmq_sqlalchemy.schema import Message

postgres_dsn = 'postgresql://postgres:postgres@localhost:5432/postgres'

pgmq = PGMQueue(dsn=postgres_dsn)

# read a single message
msg:Message = pgmq.read('my_queue')

# read a batch of messages
msgs:List[Message] = pgmq.read_batch('my_queue', 10)

For monitor.py:

from pgmq_sqlalchemy import PGMQueue
from pgmq_sqlalchemy.schema import QueueMetrics

postgres_dsn = 'postgresql://postgres:postgres@localhost:5432/postgres'

pgmq = PGMQueue(dsn=postgres_dsn)

# get queue metrics
metrics:QueueMetrics = pgmq.metrics('my_queue')
print(metrics.queue_length)
print(metrics.total_messages)

Transaction Usage

Use the op module to combine PGMQ operations with your business logic in a single transaction:

from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from pgmq_sqlalchemy import op

engine = create_engine('postgresql://postgres:postgres@localhost:5432/postgres')
SessionLocal = sessionmaker(bind=engine)

with SessionLocal() as session:
    try:
        # Create queue
        op.create_queue('orders_queue', session=session, commit=False)
        
        # Insert order into your database
        session.execute(
            text("INSERT INTO orders (user_id, total) VALUES (:user_id, :total)"),
            {"user_id": 123, "total": 99.99}
        )
        
        # Send message to queue
        op.send(
            'orders_queue',
            {'user_id': 123, 'action': 'process_order'},
            session=session,
            commit=False
        )
        
        # Commit everything together
        session.commit()
    except Exception as e:
        session.rollback()
        print(f"Transaction failed: {e}")

See Transaction Usage Documentation for more examples.

FastAPI Pub/Sub Example with tests

See the FastAPI Pub/Sub Example for a complete example of using pgmq-sqlalchemy in a FastAPI application with asynchronous message consumption and tests.

Issue/ Contributing / Development

Welcome to open an issue or pull request !
See Development on Online Document or CONTRIBUTING.md for more information.

TODO

• Alembic compatible migration scripts for PGMQ extension and schema setup, upgrade, downgrade.
• Compatibility tests with PGMQ across different PGMQ versions.
• More examples
• Smoothen contributing process with custom script for one step setup
• Mypy strict type checking
• Enable more ruff rules
• Drop Python 3.9 support in next minor release