Convert inconsistent API responses into typed Pydantic domain models.
npx skills add https://github.com/dragonkid/dotfiles --skill dto-factory-method
Please help me install this Agent Skill. Skill: dto-factory-method Source: https://github.com/dragonkid/dotfiles/tree/main/claude/skills/learned/dto-factory-method Command: npx skills add https://github.com/dragonkid/dotfiles --skill dto-factory-method
This Skill translates messy external API responses into clean, typed domain models using Pydantic, applying a factory method to centralize conversion and provide consistent defaults.
Define a Pydantic model and implement a from_api_response class method, then call it with your API payload to obtain a ready-to-use domain object.
High-intent search queries and answers about installing and using this skill.
You convert inconsistent API responses into Pydantic models by implementing a `from_api_response` factory method. This centralizes data mapping and applies safe defaults for missing or optional fields to prevent runtime errors.
The best way to handle non-standard API field names is using a factory method to decouple API structure from domain logic. This centralizes mapping logic, keeping external payload inconsistencies separate from your core application.
You provide default values for missing fields during API payload mapping by defining Pydantic models with default parameters. The factory method leverages these defaults to ensure safe domain object instantiation.
Yes, you can generate multiple output formats from a single Pydantic domain model. The pattern supports optional output helpers like `to_prompt_lines` to produce structured text, JSON, or display-friendly strings.
You should use a factory method for API data mapping when API field names are non-standard, nested, or optional. It centralizes conversion logic and ensures consistent defaults across multiple required output formats.
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