The official SurrealDB SDK for Python.

       

     

surrealdb.py

The official SurrealDB SDK for Python.

Development Setup

This project uses uv for dependency management and hatch as the build tool.

Prerequisites

Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Dependency Philosophy

This project follows library best practices for dependency management:

• Minimal constraints: Uses >= instead of exact pins for maximum compatibility
• Essential only: Only direct dependencies that are actually imported
• Clean separation: Development tools in separate dependency groups
• Well-maintained tools: Avoid dependencies which go 6+ months without so much as a patch

Development Workflow

1. Install dependencies:

   # Install main dependencies
   uv sync
   
   # Install with dev dependencies (linting, type checking, testing)
   uv sync --group dev

2. Run development tools:

   # Run linting
   uv run ruff check src/
   
   # Run formatting
   uv run ruff format src/
   
   # Run type checking
   uv run mypy --explicit-package-bases src/
   
   # Run tests (with coverage)
   uv run scripts/run_tests.sh
   # Or directly:
   uv run pytest --cov=src/surrealdb --cov-report=term-missing --cov-report=html

3. Build the project:

   uv build

Testing Strategy

We use a multi-tier testing strategy to ensure compatibility across SurrealDB versions:

Local Development Testing

# Test with default version (latest stable)
docker-compose up -d
uv run scripts/run_tests.sh

# Test against specific version
./scripts/test-versions.sh v2.1.8

# Test against different v2.x versions
SURREALDB_VERSION=v2.0.5 uv run scripts/run_tests.sh
SURREALDB_VERSION=v2.3.6 uv run scripts/run_tests.sh

CI/CD Testing

• Core Tests: Run on every PR against key stable versions (v2.0.5, v2.1.8, v2.2.6, v2.3.6)
• Comprehensive Tests: Run on schedule/manual trigger against all latest minor versions
• Python Compatibility: Tests all supported Python versions (3.10, 3.11, 3.12, 3.13)

Version-Specific Behavior

Tests are designed to be version-agnostic across all supported SurrealDB v2.x versions:

• Automatically handles behavioral differences between v2.x minor versions
• No environment variable configuration required for version detection

Documentation

View the SDK documentation here.

How to install

# Using pip
pip install surrealdb

# Using uv
uv add surrealdb

Quick start

In this short guide, you will learn how to install, import, and initialize the SDK, as well as perform the basic data manipulation queries. This guide uses the Surreal class, but this example would also work with AsyncSurreal class, with the addition of await in front of the class methods.

Install

pip install surrealdb

Learn the basics

# Import the Surreal class
from surrealdb import Surreal

# Using a context manger to automatically connect and disconnect
with Surreal("ws://localhost:8000/rpc") as db:
    db.signin({"username": 'root', "password": 'root'})
    db.use("namepace_test", "database_test")

    # Create a record in the person table
    db.create(
        "person",
        {
            "user": "me",
            "password": "safe",
            "marketing": True,
            "tags": ["python", "documentation"],
        },
    )

    # Read all the records in the table
    print(db.select("person"))

    # Update all records in the table
    print(db.update("person", {
        "user":"you",
        "password":"very_safe",
        "marketing": False,
        "tags": ["Awesome"]
    }))

    # Delete all records in the table
    print(db.delete("person"))

    # You can also use the query method 
    # doing all of the above and more in SurrealQl
    
    # In SurrealQL you can do a direct insert 
    # and the table will be created if it doesn't exist
    
    # Create
    db.query("""
    insert into person {
        user: 'me',
        password: 'very_safe',
        tags: ['python', 'documentation']
    };
    """)

    # Read
    print(db.query("select * from person"))
    
    # Update
    print(db.query("""
    update person content {
        user: 'you',
        password: 'more_safe',
        tags: ['awesome']
    };
    """))

    # Delete
    print(db.query("delete person"))

Embedded Database

SurrealDB can also run embedded directly within your Python application natively. This provides a fully-featured database without needing a separate server process.

Installation

The embedded database is included when you install surrealdb:

pip install surrealdb

For source builds, you'll need Rust toolchain and maturin:

uv run maturin develop --release

In-Memory Database

Perfect for embedded applications, development, testing, caching, or temporary data.

import asyncio
from surrealdb import AsyncSurreal

async def main():
    # Create an in-memory database (can use "mem://" or "memory")
    async with AsyncSurreal("memory") as db:
        await db.use("test", "test")
        await db.signin({"username": "root", "password": "root"})
        
        # Use like any other SurrealDB connection
        person = await db.create("person", {
            "name": "John Doe",
            "age": 30
        })
        print(person)
        
        people = await db.select("person")
        print(people)

asyncio.run(main())

File-Based Persistent Database

For persistent local storage:

import asyncio
from surrealdb import AsyncSurreal

async def main():
    # Create a file-based database (can use "file://" or "surrealkv://")
    async with AsyncSurreal("file://mydb") as db:
        await db.use("test", "test")
        await db.signin({"username": "root", "password": "root"})
        
        # Data persists across connections
        await db.create("company", {
            "name": "Acme Corp",
            "employees": 100
        })
        
        companies = await db.select("company")
        print(companies)

asyncio.run(main())

Blocking (Sync) API

The embedded database also supports the blocking API:

from surrealdb import Surreal

# In-memory (can use "mem://" or "memory")
with Surreal("memory") as db:
    db.use("test", "test")
    db.signin({"username": "root", "password": "root"})
    
    person = db.create("person", {"name": "Jane"})
    print(person)

# File-based
with Surreal("file://mydb") as db:
    db.use("test", "test")
    db.signin({"username": "root", "password": "root"})
    
    company = db.create("company", {"name": "TechStart"})
    print(company)

When to Use Embedded vs Remote

Use Embedded (memory, mem://, file://, or surrealkv://) when:

• Building desktop applications
• Running tests (in-memory is very fast)
• Local development without server setup
• Embedded systems or edge computing
• Single-application data storage

Use Remote (ws:// or http://) when:

• Multiple applications share data
• Distributed systems
• Cloud deployments
• Need horizontal scaling
• Centralized data management

For more examples, see the examples/embedded/ directory.

Next steps

Now that you have learned the basics of the SurrealDB SDK for Python, you can learn more about the SDK and its methods in the methods section and data types section.

Contributing

Contributions to this library are welcome! If you encounter issues, have feature requests, or want to make improvements, feel free to open issues or submit pull requests.

If you want to contribute to the Github repo please read the general contributing guidelines on concepts such as how to create a pull requests here.

Getting the repo up and running

To contribute, it's a good idea to get the repo up and running first. We can do this by running the tests. If the tests pass, your PYTHONPATH works and the client is making successful calls to the database. To do this we must run the database with the following command:

# if the docker-compose binary is installed
docker-compose up -d

# if you are running docker compose directly through docker
docker compose up -d

Now that the database is running, we can enter a terminal session with all the requirements installed and PYTHONPATH configured with the command below:

bash scripts/term.sh

You will now be running an interactive terminal through a python virtual environment with all the dependencies installed. We can now run the tests with the following command:

pytest --cov=src/surrealdb --cov-report=term-missing --cov-report=html

The number of tests might increase but at the time of writing this you should get a printout like the one below:

================================ test session starts ================================
platform ...
collected 227 items

....................................................................................
... (test output)

---------- coverage: platform ... -----------
Name                        Stmts   Miss  Cover   Missing
---------------------------------------------------------
src/surrealdb/....
...

============================= 227 passed in 6.31s ================================

Finally, we clean up the database with the command below:

# if the docker-compose binary is installed
docker-compose down

# if you are running docker compose directly through docker
docker compose down

To exit the terminal session merely execute the following command:

exit

And there we have it, our tests are passing.

Testing Against Different SurrealDB Versions

Quick Testing with Docker Compose

Test against different SurrealDB versions using environment variables:

# Test with latest v2.x (default: v2.3.6)
uv run scripts/run_tests.sh

# Test with specific v2.x version  
SURREALDB_VERSION=v2.1.8 docker-compose up -d surrealdb
uv run scripts/run_tests.sh

# Use different profiles for testing specific v2.x versions
docker-compose --profile v2-0 up -d    # v2.0.5 on port 8020
docker-compose --profile v2-1 up -d    # v2.1.8 on port 8021
docker-compose --profile v2-2 up -d    # v2.2.6 on port 8022
docker-compose --profile v2-3 up -d    # v2.3.6 on port 8023

Automated Version Testing

Use the test script for systematic testing:

# Test latest version with all tests
./scripts/test-versions.sh

# Test specific version
./scripts/test-versions.sh v2.1.8

# Test specific test directory
./scripts/test-versions.sh v2.3.6 tests/unit_tests/data_types

GitHub Actions Matrix Testing

The CI automatically tests against multiple versions:

• Core tests: Always run against key versions (v2.0.5, v2.1.8, v2.2.6, v2.3.6)
• Comprehensive tests: Scheduled tests against all latest versions
• Auto-discovery: Dynamically finds latest patch versions

Docker Usage

Using the Official Docker Image

# Build the image
docker build -t surrealdb-python:latest .

# Run with uv
docker run -it surrealdb-python:latest uv run python -c "import surrealdb; print('Ready!')"

# Run tests in container
docker run -it surrealdb-python:latest uv run python -m unittest discover -s tests

Development with Docker Compose

# Start latest SurrealDB for development
docker-compose up -d

# Start specific version for testing
SURREALDB_VERSION=v2.1.8 docker-compose up -d

# View logs
docker-compose logs -f surrealdb

SurrealDB Python SDK

The official SurrealDB Python SDK.

Requirements

• Python: 3.9 or greater
• SurrealDB: v2.0.0 to v2.3.6 (for remote connections)
• Rust toolchain: Only required if building from source

Note: This SDK works seamlessly with SurrealDB versions v2.0.0 to v2.3.6, ensuring compatibility with the latest features. The embedded database functionality is included in pre-built wheels on PyPI.

Quick Start

1. Install the SDK:

   # Using pip
   pip install surrealdb

   # Using uv
   uv add surrealdb

2. Start SurrealDB (using Docker):

   docker run --rm -p 8000:8000 surrealdb/surrealdb:v2.3.6 start --allow-all

3. Connect and query:

   from surrealdb import Surreal
   
   async def main():
       async with Surreal("ws://localhost:8000/rpc") as db:
           await db.signin({"user": "root", "pass": "root"})
           await db.use("test", "test")
           
           # Create
           person = await db.create("person", {"name": "John", "age": 30})
           print(person)
           
           # Query
           people = await db.select("person")
           print(people)
   
   import asyncio
   asyncio.run(main())

Development

This project uses uv for fast dependency management and hatch for building.

Setup

1. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone and setup:

   git clone https://github.com/surrealdb/surrealdb.py.git
   cd surrealdb.py
   uv sync --group dev

3. Activate environment:

   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

Testing

Quick Test (Latest Version)

# Start SurrealDB v2.3.6
docker compose up -d

# Run tests
export SURREALDB_URL="http://localhost:8000"
uv run python -m unittest discover -s tests

Test Multiple Versions

# Test latest v2.x versions
./scripts/test-versions.sh --v2-latest

# Test specific version
./scripts/test-versions.sh v2.1.8

# Test all supported versions
./scripts/test-versions.sh --all

Available Docker Profiles

# Development (default - v2.3.6)
docker compose up -d

# Test specific v2.x versions
docker compose --profile v2-0 up -d    # v2.0.5 on port 8020
docker compose --profile v2-1 up -d    # v2.1.8 on port 8021  
docker compose --profile v2-2 up -d    # v2.2.6 on port 8022
docker compose --profile v2-3 up -d    # v2.3.6 on port 8023

Code Quality

# Format code
uv run ruff format

# Lint code  
uv run ruff check

# Type checking
uv run mypy src/

Release

# Build package
uv build

# Publish to PyPI (requires authentication)
uv publish

SurrealDB Version Support

This Python SDK supports SurrealDB v2.0.0 to v2.3.6. Here's the compatibility matrix:

Python SDK	SurrealDB Versions	Status
v1.0.0+	v2.0.0 - v2.3.6	✅ Supported
v1.0.0+	v1.x.x	❌ Not supported

Tested Versions

The SDK is continuously tested against:

• v2.0.5 (Latest v2.0.x)
• v2.1.8 (Latest v2.1.x)
• v2.2.6 (Latest v2.2.x)
• v2.3.6 (Latest v2.3.x)

Documentation

• Official Documentation
• API Reference
• Examples

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Running Tests and Coverage

To run all tests with coverage reporting:

uv run scripts/run_tests.sh

This will:

• Run all tests using pytest
• Show a coverage summary in the terminal
• Generate an HTML coverage report in the htmlcov/ directory

You can also run tests directly with:

uv run pytest --cov=src/surrealdb --cov-report=term-missing --cov-report=html

To test a specific file:

uv run pytest tests/unit_tests/connections/test_connection_constructor.py --cov=src/surrealdb

To view the HTML coverage report, open htmlcov/index.html in your browser after running the tests.