pallets-eco/flask-sqlalchemy

Adds SQLAlchemy support to Flask

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Summary Information

Updated 30 minutes ago
Added to GitGenius on September 16th, 2026
Created on June 1st, 2010
Open Issues & Pull Requests: 38 (+0)
GitHub issues: Enabled
Number of forks: 907
Total Stargazers: 4,307 (+0)
Total Subscribers: 110 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 1.0 hours
Mean response time: 15.7 days
90th percentile: 23.9 days
Tracked items: 20

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Issue Activity (beta)

Open issues: 13
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 725 days
Stale 30+ days: 13
Stale 90+ days: 12

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Flask-SQLAlchemy is a Flask extension that integrates SQLAlchemy into Flask applications.

The tool solves the problem of connecting Flask web applications to relational databases by providing a Flask-native wrapper around SQLAlchemy. It handles the boilerplate of session management, model declaration, and database initialization so developers can focus on application logic rather than database plumbing. The extension manages the application context lifecycle automatically, ensuring database sessions are properly scoped to requests and cleaned up appropriately.

Flask-SQLAlchemy suits projects of any scale that use Flask and need a mature, battle-tested ORM. It is the standard choice for Flask developers working with SQL databases. The tool works well whether you are building a small prototype or a large application, as it scales from simple single-database setups to complex configurations with multiple databases and custom session factories. Developers already familiar with SQLAlchemy will find the extension reduces friction by eliminating manual context management code.

The project maintains steady, deliberate development activity with regular maintenance and updates. Contributions are reviewed and merged consistently, indicating active stewardship of the codebase. The maintainers respond to issues and pull requests, keeping the project aligned with both Flask and SQLAlchemy evolution. Documentation is kept current alongside code changes, ensuring users have accurate guidance for adoption and troubleshooting.