flask-python

mindrally

•

6155 months ago

Source Raw

Guidelines for Flask Python development with best practices for blueprints, RESTful APIs, and application factories.

Quick Install

npxskills add mindrally/skills--skill flask-python

Instructions

Flask Python Development

You are an expert in Flask and Python web development. Follow these guidelines when writing Flask code.

Key Principles

Write concise, technical responses with accurate Python examples
Use functional, declarative programming; avoid classes 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
Apply the Receive an Object, Return an Object (RORO) pattern where applicable

Python/Flask Standards

Use def for function definitions
Implement type hints for all function signatures where possible
Structure: Flask app initialization, blueprints, models, utilities, config
Omit unnecessary curly braces in conditionals
Use concise one-line syntax for simple conditional statements

Error Handling and Validation

Handle errors and edge cases at function entry points
Use early returns for error conditions to prevent deep nesting
Place successful logic last in functions for improved readability
Avoid unnecessary else statements; use if-return pattern instead
Employ guard clauses for preconditions and invalid states
Implement proper error logging with user-friendly messages
Use custom error types or error factories for consistent handling

Required Dependencies

Flask
Flask-RESTful (RESTful API development)
Flask-SQLAlchemy (ORM)
Flask-Migrate (database migrations)
Marshmallow (serialization/deserialization)
Flask-JWT-Extended (JWT authentication)

Flask-Specific Guidelines

Use Flask application factories for modularity and testing
Organize routes using Flask Blueprints
Leverage Flask-RESTful for class-based views
Implement custom error handlers for different exception types
Use Flask decorators: before_request, after_request, teardown_request
Utilize Flask extensions for common functionalities
Manage configurations via Flask's config object (development, testing, production)
Implement logging using Flask's app.logger
Handle authentication/authorization with Flask-JWT-Extended

Performance Optimization

Use Flask-Caching for frequently accessed data
Implement database query optimization (eager loading, indexing)
Apply connection pooling for database connections
Manage database sessions properly
Use background tasks for time-consuming operations (e.g., Celery)

Key Conventions

Use Flask's application context and request context appropriately
Prioritize API performance metrics (response time, latency, throughput)
Structure application with blueprints, clear separation of concerns, and environment variables

Database Interaction

Use Flask-SQLAlchemy for ORM operations
Implement database migrations via Flask-Migrate
Properly manage SQLAlchemy sessions, ensuring closure after use

Serialization and Validation

Use Marshmallow for object serialization/deserialization and input validation
Create schema classes for each model for consistent handling

Authentication and Authorization

Implement JWT-based authentication using Flask-JWT-Extended
Use decorators for protecting routes requiring authentication

Testing

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

API Documentation

Use Flask-RESTX or Flasgger for Swagger/OpenAPI documentation
Document all endpoints with request/response schemas

Deployment

Use Gunicorn or uWSGI as WSGI HTTP Server
Implement proper logging and monitoring in production
Use environment variables for sensitive information and configuration

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