pydantic

Validate runtime data with Pydantic v2 models and settings.

3|Updated May 12, 2026

Search Tags:#pydantic #python #validation #backend #schema #data-integrity

Ready to run

npx skills add https://github.com/gao-hongnan/omniagents --skill pydantic-gao-hongnan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pydantic
Source: https://github.com/gao-hongnan/omniagents/tree/main/plugins/python/skills/pydantic
Command: npx skills add https://github.com/gao-hongnan/omniagents --skill pydantic-gao-hongnan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the fragility of untyped data handling by enforcing strict, runtime validation at system boundaries, preventing deployment errors and data corruption.

Core Features & Use Cases

Schema Enforcement: Defines robust BaseModel and BaseSettings structures to replace loose dictionaries.
Advanced Validation: Implements field-level constraints, cross-field invariants, and discriminated unions for complex event payloads.
Use Case: Use this skill when refactoring API request handlers or configuration loaders to ensure that incoming JSON or environment variables strictly adhere to your application's expected schema before reaching business logic.

Quick Start

Use the pydantic skill to refactor the current module by replacing all dict-based data structures with strict Pydantic v2 models and adding appropriate validation logic.

Frequently Asked Questions about pydantic

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

FAQPage Schema

How do I enforce strict runtime validation for API payloads in Python?▼

Enforce strict runtime validation for API payloads by replacing loose dictionaries with Pydantic v2 BaseModel structures, ensuring incoming JSON strictly adheres to your schema before reaching business logic.

How do I securely handle environment variables and configuration in Python backend services?▼

Securely handle configuration in Python backend services by using Pydantic BaseSettings to load environment variables, enforcing strict schema validation and secure secret handling at system boundaries.

How do I implement cross-field constraints and discriminated unions for complex event payloads?▼

Implement cross-field constraints and discriminated unions for complex event payloads by applying Pydantic v2 advanced validation patterns, including field_validator and model_validate, to enforce data integrity.

What is the best way to refactor untyped dictionary data structures in Python?▼

The best way to refactor untyped dictionary data structures is replacing them with immutable Pydantic v2 value objects, preventing deployment errors and data corruption through strict schema enforcement.

Does this data validation approach require specific Pydantic v2 API patterns?▼

Yes, this approach requires adherence to Pydantic v2 API patterns, specifically utilizing model_validate for instantiation, field_validator for custom logic, and BaseSettings for configuration management.

When do I need strict schema enforcement for untyped data in Python?▼

You need strict schema enforcement for untyped data when refactoring API request handlers or configuration loaders to prevent fragility, ensuring data validity before processing within your application.