Flask routing maps URLs to Python functions using decorators like @app.route(). Internally, Flask stores URL rules and matches incoming requests based on path and HTTP method.

Variable routes allow dynamic URL segments. Flask also supports method-specific routing such as GET, POST, PUT, and DELETE. This routing flexibility is essential for building RESTful APIs.

In a Flask REST API, the client sends an HTTP request with headers, parameters, and body. Flask parses the request using the request object.

Business logic is executed, often involving databases or services. The response is returned as JSON with a status code. This lifecycle ensures stateless communication between client and server.

Flask connects to databases using libraries like SQLAlchemy or direct connectors. The ORM maps Python objects to database tables.

CRUD operations are handled inside route functions or service layers. Flask manages database sessions per request. This integration allows clean and scalable API development.

Flask offers flexibility and simplicity, while Django provides built-in components for large applications.

Using correct HTTP methods ensures REST compliance and clarity.

Choosing the correct request object is crucial for API correctness.

Both are essential for secure APIs.

REST (Representational State Transfer) is an architectural style for building scalable APIs. It uses stateless communication and standard HTTP methods.

Flask is ideal for REST APIs due to its lightweight nature. REST improves interoperability between systems. It simplifies frontend-backend communication.

Flask returns JSON using jsonify(), which sets correct headers and converts dictionaries to JSON.

It ensures proper encoding and security. JSON responses are standard in REST APIs. Flask also supports custom status codes. This enables consistent API communication.

Blueprints help organize large Flask applications into modules. They separate routes by feature or service.

This improves maintainability and scalability. Blueprints support reusable API components. Large production APIs rely heavily on blueprints.

Flask-RESTful simplifies API development by using class-based resources. It provides automatic routing and request parsing.

It enforces REST structure. Flask-RESTful is useful for clean API design. It reduces repetitive code.

Flask uses configuration objects and environment variables. Settings like database URI and secret keys are stored securely.

Multiple configurations can be used for dev, test, and production. This ensures flexibility across environments. Configuration management is vital for deployment.

Middleware runs before or after requests. It is used for logging, authentication, and request validation. Flask implements middleware using decorators and WSGI hooks. Middleware helps apply cross-cutting concerns globally. It improves code reuse.

Flask provides error handlers using @app.errorhandler. APIs return structured JSON error responses. Custom exceptions improve debugging. Proper error handling improves client experience. Status codes should reflect error types.

JWT uses tokens for stateless authentication. The server issues a token after login. Clients include the token in headers for requests. Flask verifies tokens on each request. JWT is scalable and widely used in APIs.

Input validation prevents invalid or malicious data. Libraries like Marshmallow or Flask-WTForms are used. Validation occurs before processing logic. Proper validation improves API security. It reduces runtime errors.

CORS allows cross-origin requests from frontend apps. Flask uses Flask-CORS extension. It sets appropriate headers. CORS is essential for frontend-backend separation. Without it, browsers block requests.

Pagination limits response size for large datasets. It improves performance and reduces bandwidth. Flask handles pagination using query parameters. APIs often return metadata with paginated results. Pagination is critical for scalable APIs.

Flask APIs are deployed using WSGI servers like Gunicorn or uWSGI. They run behind Nginx for load balancing. Docker is commonly used for containerization. Environment variables manage secrets. Deployment completes the MLOps pipeline.