# Pydantic

> Pydantic models and validation. Use when: (1) Defining schemas, (2) Validating input/output, (3) Generating JSON schema.

- Skill: `jiatastic/pydantic` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add jiatastic/pydantic`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jiatastic/pydantic/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: jiatastic (https://skillmd.com/u/jiatastic)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/jiatastic/pydantic

---


# pydantic

Type-driven validation and serialization using Pydantic models.

## Overview

Pydantic validates data using Python type hints and provides rich serialization via `model_dump()` and JSON schema output.

## When to Use

- Validating request/response payloads
- Normalizing untrusted input
- Generating JSON schema for docs

## Quick Start

```bash
uv pip install pydantic
```

```python
from pydantic import BaseModel

class User(BaseModel):
    id: int
    email: str

user = User(id=1, email="a@example.com")
```

## Core Patterns

1. **Typed fields**: strict schema definitions.
2. **Field validators**: custom validation logic.
3. **Model validators**: cross-field checks.
4. **Serialization**: `model_dump()` and `model_dump_json()`.
5. **Settings**: environment-driven config via `BaseSettings`.

## Example: field_validator

```python
from pydantic import BaseModel, field_validator

class Model(BaseModel):
    name: str

    @field_validator("name")
    @classmethod
    def ensure_not_empty(cls, v: str):
        if not v:
            raise ValueError("name required")
        return v
```

## Example: model_validate + model_dump

```python
from pydantic import BaseModel

class Model(BaseModel):
    foo: int

model = Model.model_validate({"foo": 1})
print(model.model_dump())
```

## Troubleshooting

- **Coercion surprises**: use strict types if needed
- **Slow validators**: keep them minimal
- **Mutable defaults**: use `default_factory`

## References

- https://docs.pydantic.dev/