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pagoda-backend-core

Coordinate Django backend development tasks for Pagoda apps with REST APIs, Celery, and Elasticsearch.

29|19|Updated Jan 24, 2020
Search Tags:#testing#api#backend#lint#django#drf#typing
One-click install
npx skills add https://github.com/dmm-com/pagoda --skill pagoda-backend-core
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pagoda-backend-core
Source: https://github.com/dmm-com/pagoda/tree/main/.claude/skills/pagoda-backend-core
Command: npx skills add https://github.com/dmm-com/pagoda --skill pagoda-backend-core

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Helps development teams maintain consistent, scalable backend practices for Pagoda/AirOne by providing a structured guide for building and modifying Django apps, APIs, migrations, Celery tasks, and Elasticsearch integration.

Core Features & Use Cases

  • Clear project structure guidelines for Django apps (models, views, serializers, tests, migrations) and DRF API endpoints.
  • OpenAPI documentation integration and plugin-aware view patterns (PluginOverrideMixin, @extend_schema).
  • Validated data handling using Pydantic models, DRF serializers, and YAML/JSON parsers.
  • Testing and quality workflows including Ruff linting, Mypy type checks, and focused test execution.

Quick Start

Follow the development workflow described here to implement backend changes, ensure code quality through static analysis and tests, and validate the integration with core Django + DRF components.

Frequently Asked Questions about pagoda-backend-core

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I structure a Django REST Framework API endpoint with OpenAPI documentation?▼

Structure Django REST Framework API endpoints using plugin-aware view patterns like PluginOverrideMixin and the @extend_schema decorator to enforce conventions and generate OpenAPI documentation.

What is the best way to validate YAML and JSON data in Django backend tasks?▼

Validate YAML and JSON data in Django backend tasks by combining Pydantic models for strict type checks with DRF serializers to ensure data integrity across core apps.

How do I run linting and type checks for Django app development?▼

Run Ruff linting and Mypy type checks as part of your testing and quality workflows to enforce strict typing and code quality across Django and DRF components.

Can I use Celery tasks and Elasticsearch integration with Django models and migrations?▼

Yes, coordinate Celery tasks and Elasticsearch integration alongside Django models, views, serializers, and migrations to scale backend changes across any core app.

Does this backend development guide support plugin-aware view patterns?▼

Yes, the backend development guide supports plugin-aware view patterns using PluginOverrideMixin and @extend_schema to maintain consistent, scalable API practices.

What are the limitations of modifying core Django apps without strict type checks?▼

Without strict type checks and Pydantic validation, modifying core Django apps risks inconsistent data handling and fails the enforced Ruff and Mypy quality workflows.

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