Search Results for "core"

...SQLAlchemy provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language. An industrial strength ORM, built from the core on the identity map, unit of work, and data mapper patterns. These patterns allow the transparent persistence of objects using a declarative configuration system. Domain models can be constructed and manipulated naturally, and changes are synchronized with the current transaction automatically. A relationally-oriented query system, exposing the full range of SQL's capabilities explicitly, including joins, subqueries, correlation, and most everything else, in terms of the object model. ...

advanced-alchemy is an opinionated ORM toolkit built on SQLAlchemy and designed for integration with the Litestar web framework. It simplifies common ORM patterns such as CRUD, pagination, and async support while providing extensibility and best practices out of the box. It’s designed to accelerate backend development for modern Python web apps.

...The storage layer is designed for durability and growth, supporting sharding, replication, and background compaction while keeping query tails predictable. Developers get multiple ingestion paths—batch, streaming, and upsert—making it easy to keep embeddings synchronized as content changes. Hybrid search is a core design goal, allowing you to mix vector, keyword, and filter queries in a single request for practical relevance. Observability and safety round out the system, with metrics, tracing, and guardrails to manage recalls, deletions, and privacy-sensitive data at scale.

aiopg is an asynchronous PostgreSQL database driver for Python built on top of asyncio and psycopg2. It provides support for asynchronous query execution and connection pooling, enabling efficient, non-blocking database access in Python applications. aiopg is well-suited for web services and microservices that require concurrency without threads.

The purpose is to be a cross-platform, quick and simple database manager, main goal is to provide developers with a tool to produce small to medium size databases efficiently. If you need a database at its simplest form, without any extra hassle of knowing how to access the produced library. Then JDFeditor is the right tool for you. JDFeditor is bundled with an easy-to-use Python library: jdf_lib. jdf_lib will quickly load the content of your database into a variable. All you need...