- Write concise, technical responses with accurate Python examples. - Use functional, declarative programming; avoid classes where possible except for Flask views. - Prefer iteration and modularization over code duplication. - Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission). - Use lowercase with underscores for directories and files (e.g., blueprints/user_routes.py). - Favor named exports for routes and utility functions. - Use the Receive an Object, Return an Object (RORO) pattern where applicable. - Use def for function definitions. - Use type hints for all function signatures where possible. - File structure: Flask app initialization, blueprints, models, utilities, config. - Avoid unnecessary curly braces in conditional statements. - For single-line statements in conditionals, omit curly braces. - Use concise, one-line syntax for simple conditional statements (e.g., if condition: do_something()). - Prioritize error handling and edge cases:
  - Handle errors and edge cases at the beginning of functions.
  - Use early returns for error conditions to avoid deeply nested if statements.
  - Place the happy path last in the function for improved readability.
  - Avoid unnecessary else statements; use the if-return pattern instead.
  - Use guard clauses to handle preconditions and invalid states early.
  - Implement proper error logging and user-friendly error messages.
  - Use custom error types or error factories for consistent error handling.

- Flask - Flask-RESTful (for RESTful API development) - Flask-SQLAlchemy (for ORM) - Flask-Migrate (for database migrations) - Marshmallow (for serialization/deserialization) - Flask-JWT-Extended (for JWT authentication)
- Use Flask application factories for better modularity and testing. - Organize routes using Flask Blueprints for better code organization. - Use Flask-RESTful for building RESTful APIs with class-based views. - Implement custom error handlers for different types of exceptions. - Use Flask's before_request, after_request, and teardown_request decorators for request lifecycle management. - Utilize Flask extensions for common functionalities (e.g., Flask-SQLAlchemy, Flask-Migrate). - Use Flask's config object for managing different configurations (development, testing, production). - Implement proper logging using Flask's app.logger. - Use Flask-JWT-Extended for handling authentication and authorization.
- Use Flask-Caching for caching frequently accessed data. - Implement database query optimization techniques (e.g., eager loading, indexing). - Use connection pooling for database connections. - Implement proper database session management. - Use background tasks for time-consuming operations (e.g., Celery with Flask).
- Use blueprints for modularizing the application. - Implement a clear separation of concerns (routes, business logic, data access). - Use environment variables for configuration management.

- Use Flask-SQLAlchemy for ORM operations. - Implement database migrations using Flask-Migrate. - Use SQLAlchemy's session management properly, ensuring sessions are closed after use.

- Use Marshmallow for object serialization/deserialization and input validation. - Create schema classes for each model to handle serialization consistently.

- Implement JWT-based authentication using Flask-JWT-Extended. - Use decorators for protecting routes that require authentication.

- Write unit tests using pytest. - Use Flask's test client for integration testing. - Implement test fixtures for database and application setup.

- Use Flask-RESTX or Flasgger for Swagger/OpenAPI documentation. - Ensure all endpoints are properly documented with request/response schemas.
- Refer to Flask documentation for detailed information on Views, Blueprints, and Extensions for best practices.