What does ormar-orm/ormar do?

Ormar is an asynchronous object-relational mapper for Python that integrates database persistence with data validation. It functions as a bridge between relational database management and application-level data structures, allowing developers to define database schemas that serve simultaneously as validation models.

What are the main features of ormar-orm/ormar?

The main features of ormar-orm/ormar are: Async Python ORMs with Relations, Object-Relational Mapping Associations, Relational Data Modeling, Pydantic Schema Validation, Asynchronous Database Drivers, Database Lifecycle Hooks, Database Schema Migrations, Database Migration Management.

What are some open-source alternatives to ormar-orm/ormar?

Open-source alternatives to ormar-orm/ormar include: miguelgrinberg/microblog — This project is a social blogging application built with Flask. It provides a platform for user account management,… fastapi/sqlmodel — SQLModel is a type-safe object-relational mapping library for Python that integrates database schema definitions with… tortoise/tortoise-orm — Tortoise ORM is an asynchronous object-relational mapper for Python that mirrors Django's model and queryset API while… pardom/activeandroid — ActiveAndroid is a persistence framework for managing local SQLite databases on Android. It provides an active record… seaql/sea-orm — Sea-ORM is an asynchronous SQL object-relational mapper and database toolkit for mapping relational tables to strongly… geldata/gel — Gel is an object-relational database system that models data as a graph of interconnected objects. By utilizing a…

Ormar - 将异步数据库映射为 Pydantic 模型

Ormar - 将异步数据库映射为 Pydantic 模型 | Awesome Repos

Features

Async Python ORMs with Relations - Provides an asynchronous object-relational mapper that integrates Pydantic validation with web framework compatibility.
Object-Relational Mapping Associations - Defines complex relational associations and foreign key constraints through declarative class-level attributes.
Relational Data Modeling - Organizes data into structured tables with defined one-to-many and many-to-many relationships.
Pydantic Schema Validation - Enforces strict schema integrity and type validation using Pydantic models for all persisted records.
Asynchronous Database Drivers - Provides non-blocking database connectivity by leveraging asynchronous drivers to maintain high concurrency.
Database Lifecycle Hooks - Triggers custom logic automatically before or after database operations to ensure data consistency.
Database Schema Migrations - Applies versioned updates to database schemas to maintain structural compatibility with application code.
Database Migration Management - Coordinates schema changes and versioning across development, testing, and production environments.
Many-to-Many Associations - Manages complex entity associations and integrity across related database tables.
Relational Database Integrations - Provides a toolkit for managing complex table associations and schema migrations in asynchronous applications.
Query Builders - Translates high-level object methods into optimized SQL statements using a low-level query builder.
Asynchronous Database Access - Performs non-blocking database operations to maintain high performance during heavy data processing.
Asynchronous Operation Execution - Enables non-blocking database operations to retrieve and modify records without stalling the main application thread.
Database Schema Migrations - Automates database schema evolution and versioning to keep physical structures synchronized with application code.
Lifecycle Event Hooks - Executes custom logic at specific stages of the database record lifecycle to maintain data integrity.
Unified Data Modeling - Defines database schemas that serve as both persistence layers and validation models for web application endpoints.

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