{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/15"},{"label":"Python Modules","url":"https://skillfed.io/packages/category/software-development-libraries-python-modules/17"},{"label":"Database","url":"https://skillfed.io/packages/category/database/4"},{"label":"Front-Ends","url":"https://skillfed.io/packages/category/database-front-ends/2"},{"label":"Database Engines/Servers","url":"https://skillfed.io/packages/category/database-database-engines-servers"}],"enrichment":{"capability":"Official Python client for SurrealDB, supporting both remote (WebSocket/HTTP) and embedded (in-memory or file-based) database connections with synchronous and asynchronous APIs.","skillfed_tags":["multi-model-database","embedded-database","async-support"],"use_cases":["Build a Python desktop or CLI application with local data storage using embedded in-memory or file-based SurrealDB.","Develop an async web service that connects to a remote SurrealDB instance via WebSocket for real-time data operations.","Write integration tests that use in-memory SurrealDB to avoid external dependencies and run tests quickly.","Implement multi-session transactions on a WebSocket connection for complex, coordinated database operations.","Add observability to database interactions by instrumenting SurrealDB operations with Pydantic Logfire."],"what_it_does":"surrealdb is the official Python SDK for SurrealDB, a multi-model database that can run as a remote server or embedded directly in your application. It provides both synchronous (Surreal) and asynchronous (AsyncSurreal) APIs for connecting to SurrealDB instances via WebSocket, HTTP, or embedded modes (in-memory or file-based). The package handles authentication, namespace/database selection, and CRUD operations through methods like create(), select(), update(), delete(), and query() for raw SurrealQL.\n\nThe SDK depends on aiohttp, requests, websockets, pydantic-core, and typing-extensions to manage network communication and data validation. It supports sessions and transactions on WebSocket connections, and integrates with Pydantic Logfire for observability. Embedded mode is useful for development, testing, and single-application deployments, while remote connections suit multi-application or distributed scenarios.","worth_installing":"Yes, with conditions. The package is actively maintained, supports current Python versions (3.10\u20133.13), and offers both embedded and remote modes for flexibility. However, verify the license terms before use\u2014the metadata does not specify a license, which is a blocker for some projects. No known security vulnerabilities. Install if you are committed to SurrealDB and need a Python client; avoid if license ambiguity is a dealbreaker."},"id":"surrealdb","links":{"html":"https://skillfed.io/packages/surrealdb","md":"https://skillfed.io/packages/surrealdb.md","pypi":"https://pypi.org/project/surrealdb/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-04-23","license_spdx":null,"license_treatment":"unclear","name":"surrealdb","python_support":"supports_current","summary":"SurrealDB python client"},"popularity":{"monthly_downloads":151436,"position":10933,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2.0.0"}