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Py 3.11

Pydantic Validation

Type coercion and model validation.

Try Pydantic Validation Code

How it Works

Pydantic allows Python dataclasses to automatically mutate fundamentally untyped network configurations into typed representations.

This protects system state using robust type constraints.

Source Code

Declares an strict schema User model for validation payloads.

models.py
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from pydantic import BaseModel, EmailStr, Field
from typing import List, Optional
import json

class User(BaseModel):
    id: int
    name: str = Field(min_length=2)
    email: EmailStr
    tags: List[str] = []
    is_active: bool = True

# Simulating an API response with mixed types
incoming_data = {
    "id": "123",       # string gets coerced to int
    "name": "Alice",
    "email": "alice@example.com",
    "tags": ("python", "developer") # tuple gets coerced to list
}

# Validate and instantiate
user = User(**incoming_data)

print("--- Validated Pydantic Model ---")
print(repr(user))
print("\n--- Exported to JSON ---")
print(user.model_dump_json(indent=2))
Terminal Output
--- Validated Pydantic Model ---
User(id=123, name='Alice', email='alice@example.com', tags=['python', 'developer'], is_active=True)

--- Exported to JSON ---
{
  "id": 123,
  "name": "Alice",
  "email": "alice@example.com",
  "tags": [
    "python",
    "developer"
  ],
  "is_active": true
}

Real-world Applications

  • API endpoint protection
  • Config schema validation
  • Database interfacing

Frequently Asked Questions