Pydantic

Skill jiatastic/open-python-skills/skills/pydantic

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

Install

npx -y skills add jiatastic/open-python-skills --skill pydantic

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SKILL.md

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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

uv pip install pydantic

from pydantic import BaseModel

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

user = User(id=1, email="[email protected]")

Core Patterns

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

Example: field_validator

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

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/

What ships with it: 2 files

1.0 KB alongside SKILL.md

references/

pitfalls.md448 B
quickstart.md589 B