coleifer/peewee
Peewee
Peewee is a SQL object-relational mapper and query builder that provides an object-oriented interface for mapping application classes to relational database tables. It functions as a relational database toolkit for managing schemas, executing migrations, and handling complex table relationships.
The project distinguishes itself by providing an asyncio database driver for non-blocking database operations, ensuring event loop responsiveness. It also supports semi-structured data storage, allowing the storage and querying of flexible JSON documents within traditional relational database systems.
The toolkit covers a broad set of capabilities, including the construction of complex SQL queries via a composable programmatic interface and the management of many-to-many relationships and foreign key resolution. It includes utilities for bulk data operations, full-text search, and database introspection to generate models from existing schemas. Connection management is handled through pooling and transaction control to ensure data integrity.
Features
- Object-Relational Mappers - Provides an object-oriented interface to map application classes to relational database tables and execute SQL queries.
- Object-Relational Mapping - Implements an object-oriented interface that maps application classes to relational database tables.
- Asynchronous Database Command Execution - Enables non-blocking execution of database commands to maintain event loop responsiveness.
- Asynchronous Database Drivers - Provides non-blocking database drivers designed for high-concurrency asyncio environments.
- Database Query Execution - Executes database queries and model methods asynchronously to keep the event loop responsive.
- Database Record Querying - Provides structured mechanisms for retrieving records from tables using filters, sorting, and pagination.
- Fluent Query APIs - Offers a fluent API for retrieving data with support for filtering, joining, and ordering.
- Hybrid Relational-JSON Storage - Allows storing and querying flexible JSON documents within traditional relational database systems.
- Code-to-Relational Mappings - Maps high-level class definitions to relational database tables for automated schema management.
- SQL Query Builders - Ships a composable programmatic interface for constructing complex SQL queries.
- Asynchronous Drivers - Provides an asyncio database driver for non-blocking operations to ensure event loop responsiveness.
- Bulk Data Operations - Supports high-performance bulk inserts and updates to reduce database round-trips.
- Semi-Structured Data Integration - Integrates flexible JSON and HStore data formats into relational tables for semi-structured storage.
- Database Connection Managers - Manages the opening, closing, and pooling of connections to various database backends.
- Database Driver Abstractions - Abstracts database-specific syntax through a common API layer for multiple SQL dialects.
- Database Introspection Tools - Performs low-level reflection to discover table structures and constraints across different platforms.
- Connection Pool Managers - Manages database connection lifecycles and pooling to optimize resource utilization.
- Database Schema Migrations - Includes tools for evolving table structures and columns without losing existing data.
- Schema Introspection - Analyzes existing database layouts to dynamically create corresponding model classes.
- Database Transaction Management - Controls atomic blocks of work using transactions and savepoints to ensure data integrity.
- Document Storage - Provides storage for flexible JSON documents within a traditional relational database system.
- Lazy Loading Patterns - Supports deferred loading of foreign key relationships to optimize initial query performance.
- Many-to-Many Relationship Managers - Provides specialized support for managing associations between entities through intermediate pivot tables.
- Relation Loading Strategies - Implements lazy loading and eager prefetching strategies for fetching associated entity data.
- Relational Database Connectors - Provides a comprehensive set of tools for connecting to and performing operations on relational databases.
- Schema Generators - Provides utilities to automatically generate model code by scanning existing database schemas.
- Database Connectivity Drivers - Interfaces with various database engines using both synchronous and asynchronous drivers.
- Database Clients - Small, expressive ORM for multiple SQL databases.
- Database ORMs - Listed in the “Database ORMs” section of the Awesome Python awesome list.
- Object Relational Mappers - Small and expressive ORM.
- ORM Frameworks - Small, expressive ORM.
Star history
How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
