pallets-eco/flask-sqlalchemy

Features

• ORM Model Declarations - Creates table structures using declarative classes that map application objects to database rows.
• Flask Integrations - Integrates the SQLAlchemy relational database toolkit with the Flask web framework for data persistence.
• Database Connection Configurations - Provides support for defining connection URIs and engine options for primary and secondary data stores.
• Database Query Execution - Runs selection queries to retrieve specific records or collections of data from the database.
• Record Creations and Updates - Performs create, update, and delete operations on model objects and persists changes through a session.
• Relational Data Modeling - Defines database table structures as Python classes to map application objects to relational database rows.
• Database Session Lifecycles - Automatically manages database connection and transaction lifecycles within the scope of a web request.
• Request-Bound Session Management - Binds database sessions to the active application request lifecycle to ensure automatic connection cleanup after responses.
• Application-Context Session Scoping - Binds database sessions to the active application context for automatic connection cleanup.
• Web Data Access Utilities - Implements specialized utilities for web data access, including query pagination and automatic 404 responses for missing records.
• Multi-Bind Schema Management - Enables creating or dropping tables across all configured database connections or targeting a specific subset.
• Database Table Generation - Provides utilities to automatically generate physical database table structures from defined model classes.
• Model-Based Query Routing - Directs database queries to specific data stores by associating model classes with designated database engines.
• Paginated Results - Splits large datasets into numbered chunks with metadata for request-parameter based navigation.
• Custom Query Interface Methods - Supports adding custom methods to the query interface globally or on a per-model basis.
• Query Performance Monitors - Records SQL execution time and application location for every query to identify performance bottlenecks.
• Single Record Retrievers - Provides a utility to retrieve a single database record or automatically trigger a 404 Not Found response.
• SQL Query Debuggers - Provides tools for monitoring executed SQL statements and recording performance metadata to identify bottlenecks.
• Model-Engine Routing - Maps specific models or tables to different database engines to manage data across distinct stores.
• Database Connection Pooling - Manages a pool of database connections with recycling and pre-ping checks to maintain stability across HTTP requests.
• Connection Stability Features - Prevents connection timeouts and handles disconnects using pool recycling and pre-ping checks.
• Database Schema Reflection - Inspects existing database structures at runtime to automatically generate application-level metadata and models.

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