surrealdb-celery-backend 0.1.0

Custom Celery result backend for SurrealDB

SurrealDB Celery Backend

A custom Celery result backend that uses SurrealDB for storing task results, states, and metadata.

Features

• ✅ Full Celery result backend implementation
• ✅ Secure parameterized queries (prevents injection attacks)
• ✅ Configurable connection settings
• ✅ Automatic cleanup of expired results
• ✅ Support for all task states (SUCCESS, FAILURE, PENDING, etc.)
• ✅ Comprehensive test coverage (unit + integration tests)
• ✅ Production-ready with proper error handling

Installation

Using uv (recommended)

uv add surrealdb-celery-backend

Using pip

pip install surrealdb-celery-backend

This will automatically install the required dependencies: celery and surrealdb.

Quick Start

1. Start SurrealDB

# Using Docker
docker run --rm -p 8000:8000 surrealdb/surrealdb:latest start \
  --user root --pass root

# OR using local installation
surreal start --user root --pass root

2. Configure Celery

from celery import Celery

app = Celery(
    'myapp',
    broker='redis://localhost:6379/0',
    backend='surrealdb_celery_backend:SurrealDBBackend'
)

# Configure SurrealDB connection
app.conf.update(
    surrealdb_url='ws://localhost:8000/rpc',
    surrealdb_namespace='celery',
    surrealdb_database='results',
    surrealdb_username='root',
    surrealdb_password='root',
    result_expires=86400,  # 1 day in seconds
)

3. Define Tasks

@app.task
def add(x, y):
    return x + y

4. Use Tasks

# Send task to worker
result = add.delay(4, 6)

# Get result
print(result.get())  # 10

# Check state
print(result.state)  # SUCCESS

Configuration Options

Configure the backend through your Celery app's configuration:

Option	Default	Description
surrealdb_url	ws://localhost:8000/rpc	WebSocket URL for SurrealDB
surrealdb_namespace	celery	SurrealDB namespace to use
surrealdb_database	results	SurrealDB database to use
surrealdb_username	root	Authentication username
surrealdb_password	root	Authentication password
result_expires	86400	Result expiration time (seconds)

Testing

Quick Start with Just

If you have just installed:

# List all available commands
just

# Run unit tests (no services needed)
just test-unit

# Run integration tests (automatically starts/stops SurrealDB)
just test-integration-auto

# Start services for examples
just services-start

Manual Testing

Unit Tests (No services required):

uv run pytest tests/test_backend_unit.py -v

Integration Tests (Requires SurrealDB only):

# Start SurrealDB with docker-compose
docker-compose -f docker-compose.tests.yml up -d

# Run integration tests
uv run pytest tests/test_backend_integration.py -v -m integration

# Stop SurrealDB
docker-compose -f docker-compose.tests.yml down

All Tests:

uv run pytest -v

See tests/README.md for detailed testing documentation and justfile for all available commands.

Examples

Complete working examples are available in the examples/ directory:

• celery_app.py - Configured Celery application
• tasks.py - Sample tasks
• test_tasks.py - End-to-end test script

See examples/README.md for detailed usage instructions.

How It Works

The backend stores task results in SurrealDB using the following structure:

Record ID: task:{task_id}
Fields:
  - task_id: Unique task identifier
  - status: Task state (SUCCESS, FAILURE, etc.)
  - result: Serialized task result
  - traceback: Exception traceback (if failed)
  - date_done: Completion timestamp

Data Flow

Storing Results:

1. Task completes → Celery calls _store_result()
2. Backend encodes result using Celery's serialization
3. Executes parameterized UPSERT query to SurrealDB
4. Result persisted with task:{task_id} record ID

Retrieving Results:

1. Client requests result → Celery calls _get_task_meta_for()
2. Backend executes parameterized SELECT query
3. Decodes result and returns metadata
4. Celery handles caching and state management

Cleanup:

1. Periodic call to cleanup() (via Celery beat)
2. Deletes tasks where date_done < now - result_expires
3. Uses SurrealQL time functions for accurate expiration

Security

• ✅ All queries use parameter binding to prevent SQL injection
• ✅ No string interpolation of user-provided data
• ✅ Safe record ID construction using type::thing()

Performance

• Persistent WebSocket connections (reused across operations)
• Lazy connection initialization
• Atomic UPSERT operations
• Efficient cleanup using SurrealDB time functions

Requirements

• Python 3.10+
• Celery 5.x+
• SurrealDB 2+
• Message broker (Redis, RabbitMQ, etc.)

Architecture

See specs/surrealdb-celery-backend/architecture.md for detailed technical architecture.

Development

Setup Development Environment

# Clone repository
git clone <repo-url>
cd surrealdb-celery-backend

# Install dependencies
uv sync --extra test

# Run tests
uv run pytest -v

Project Structure

surrealdb-celery-backend/
├── surrealdb_celery_backend/  # Main package
│   ├── __init__.py
│   └── backend.py             # Backend implementation
├── tests/                     # Test suite
│   ├── conftest.py           # Pytest fixtures
│   ├── test_backend_unit.py  # Unit tests
│   └── test_backend_integration.py  # Integration tests
├── examples/                  # Usage examples
│   ├── celery_app.py
│   ├── tasks.py
│   └── test_tasks.py
└── specs/                     # Design documentation

Troubleshooting

Connection Errors

Problem: Connection refused or Cannot connect to SurrealDB

Solution:

• Verify SurrealDB is running: lsof -i :8000
• Check URL format: Must be ws:// or wss:// (WebSocket)
• Test connection manually using SurrealDB CLI

Tasks Not Storing Results

Problem: Results not appearing in SurrealDB

Solution:

• Check worker logs for errors
• Verify namespace and database exist
• Ensure credentials are correct
• Check task_ignore_result is not True

Import Errors

Problem: ModuleNotFoundError: No module named 'surrealdb_celery_backend'

Solution:

• Ensure the package is in your Python path
• Install in development mode: uv sync
• Check imports: from surrealdb_celery_backend import SurrealDBBackend

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Ensure all tests pass (uv run pytest -v)
6. Commit your changes (git commit -m 'feat: add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Open a Pull Request

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/lfnovo/surrealdb-celery-backend.git
cd surrealdb-celery-backend

# Install dependencies (including test dependencies)
uv sync --all-extras

# Run tests
uv run pytest -v

# Run integration tests (requires SurrealDB)
SURREALDB_TEST_URL=ws://localhost:8000/rpc uv run pytest -v -m integration

Publishing

See PUBLISHING.md for instructions on publishing new versions to PyPI.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Credits

Created by Luis Novo as a custom Celery backend for SurrealDB integration.

Links

• PyPI: https://pypi.org/project/surrealdb-celery-backend/
• GitHub: https://github.com/lfnovo/surrealdb-celery-backend
• Issues: https://github.com/lfnovo/surrealdb-celery-backend/issues
• Celery Documentation: https://docs.celeryq.dev/
• SurrealDB Documentation: https://surrealdb.com/docs