Generate Pydantic schemas with validation and nested models.
npx skills add https://github.com/matteocervelli/llms --skill data-modeler
Please help me install this Agent Skill. Skill: data-modeler Source: https://github.com/matteocervelli/llms/tree/main/.claude/skills/data-modeler Command: npx skills add https://github.com/matteocervelli/llms --skill data-modeler
This Skill guides the design of robust, validated data models using Pydantic, ensuring type safety and clear data contracts.
Create a comprehensive Pydantic schema for a user-like entity with validation and nested address.
High-intent search queries and answers about installing and using this skill.
Pydantic schemas use BaseModel to define typed fields with built-in validation. Add field validators using the @field_validator decorator to enforce constraints, cross-field rules, and custom logic. Pydantic automatically validates data on instantiation and raises detailed errors for invalid inputs.
Yes, Pydantic supports nested models by composing BaseModel classes. Define a model as a field type within another model; Pydantic validates the entire nested structure recursively. This enables clear entity relationships and complex data contracts.
Type hints with Pydantic enforce type safety at runtime and enable robust JSON serialization. BaseModel automatically converts Python objects to JSON and back, ensuring data contracts match across service boundaries and preventing runtime type errors.
Use Field() with parameters like min_length, max_length, regex, and gt/lt to enforce constraints declaratively. Combine with @field_validator for complex rules. Pydantic validates on instantiation and generates clear error messages for constraint violations.
Pydantic integrates with ORMs through configuration options like from_attributes=True, enabling seamless conversion from ORM instances to validated schemas. This bridges domain models and API contracts while maintaining type safety and validation across the stack.
Pydantic validation catches errors at entry points, reduces defensive code throughout your application, and provides consistent error handling. Explicit schemas serve as documentation and enable automatic API documentation and client generation from type hints.
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