FastAPI + SQLAlchemy: Rapidly Building Database-Driven APIs
This article introduces how to build a database-driven API using FastAPI + SQLAlchemy, suitable for beginners. Its core advantages lie in FastAPI's high performance, automatic API documentation, and concise syntax, combined with SQLAlchemy's ORM to simplify database operations. Prerequisites include installing FastAPI, Uvicorn, SQLAlchemy, and Pydantic. The project adopts a modular structure: database.py configures database connections (using SQLite as an example), models.py defines ORM models for user tables, schemas.py uses Pydantic for data validation (distinguishing requests/responses), crud.py implements CRUD operations, and main.py integrates modules and defines API routes. Core modules include: database engine, session management (automatically creating/closing connections), user table models, data validation, and CRUD logic. The service is started via Uvicorn, and the Swagger UI enables interactive API testing. Advantages include automatic documentation, ORM simplification of SQL, modular design, and dependency injection for session management, making it suitable for quickly building efficient and maintainable web applications.
Read MoreFlask Database Migration: A Guide to Using Flask-Migrate
In Flask development, manual operations to modify database structures carry risks. Flask-Migrate (based on Alembic) provides a secure migration solution. After installation, you need to associate the Flask app with the SQLAlchemy db instance. The core workflow involves: initializing the migration environment with `flask db init`, generating migration scripts after model changes using `flask db migrate -m "description"`, applying changes with `flask db upgrade`, and rolling back with `flask db downgrade`. It supports automatic detection of model changes, version control, and secure rollbacks. For complex migrations (e.g., data transformation), manual modification of migration scripts is required. The key advantage is simplifying iterative management and avoiding manual modification risks. Mastering these four commands enables efficient management of database structure changes.
Read MoreFlask and Database Connection: SQLAlchemy Basic Operations
SQLAlchemy is a popular ORM tool for Python that allows database operations through Python classes/objects, avoiding direct SQL writing. It supports multiple databases (e.g., MySQL, SQLite) and is well-suited for Flask development. Installation requires `pip install flask flask-sqlalchemy`, with additional drivers needed for databases like MySQL. During initialization, configure the Flask application and database connection (e.g., SQLite path), then initialize the SQLAlchemy instance. Data models are defined via classes, where each class corresponds to a table and class attributes represent fields (e.g., the `User` class includes `id`, `username`, etc., with primary key, unique, and non-null constraints). Use `db.create_all()` to generate tables within the application context. Core operations (CRUD): Create (instantiate → `db.session.add()` → `commit()`); Read (`query.all()`/`filter_by()` etc.); Update (modify object attributes → `commit()`); Delete (`db.session.delete()` → `commit()`). Workflow: Configure connection → Define models → Create tables → CRUD operations. The advantage is no need to write SQL, facilitating rapid development.
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