🔷 What is Pydantic?

Pydantic is a powerful data validation and settings management library used in Python. It uses Python type annotations to validate and serialize data easily. Pydantic models are built using Python classes, making it intuitive and easy to maintain.

✅ Core Feature: Data parsing & validation using Python's standard type hints.

📦 Commonly used with frameworks like FastAPI, Typer, or in data pipelines for schema enforcement.

📌 Key Features of Pydantic

🧰 How to Install Pydantic

pip install pydantic

📘 Example: Basic Pydantic Model

from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str
    email: str
    is_active: bool = True

# ✅ Valid data
user = User(id=1, name="Alice", email="alice@example.com")
print(user)

# ❌ Invalid data (raises ValidationError)
invalid_user = User(id="abc", name="Bob", email="bob@example.com")

Automatically converts or rejects data based on type.

🔁 Built-in Validation & Conversion

from pydantic import BaseModel

class Product(BaseModel):
    id: int
    price: float
    available: bool

product = Product(id="1", price="99.99", available="true")
print(product)

🎯 Output:

id=1 price=99.99 available=True

🏗️ Nested Models

from typing import List
from pydantic import BaseModel

class Address(BaseModel):
    city: str
    zipcode: str

class Person(BaseModel):
    name: str
    age: int
    address: Address
    hobbies: List[str]

data = {
    "name": "John",
    "age": 30,
    "address": {
        "city": "New York",
        "zipcode": "10001"
    },
    "hobbies": ["reading", "coding"]
}

person = Person(**data)
print(person.address.city)

🧪 Validators (Custom Validation)

from pydantic import BaseModel, validator

class User(BaseModel):
    username: str
    password: str

    @validator('password')
    def password_strength(cls, v):
        if len(v) < 6:
            raise ValueError('Password too short!')
        return v

User(username="admin", password="123456")  # Valid
User(username="admin", password="123")     # Error

🧾 Use Cases of Pydantic

⚙️ BaseSettings for App Configs

from pydantic import BaseSettings

class Settings(BaseSettings):
    database_url: str
    secret_key: str

    class Config:
        env_file = ".env"

settings = Settings()
print(settings.database_url)

🌐 Serialization: .dict() and .json()

user = User(id=1, name="Alice", email="alice@example.com")
print(user.dict())
print(user.json())

📌 Summary

🎨 Infographic (Text Style)

+------------------------+
|      PYDANTIC          |
+------------------------+
| ✅ Type-safe classes   |
| 🔁 Auto-conversion     |
| 🔒 Field validation    |
| 🏗️  Nested models       |
| 📦 JSON support        |
| 🔧 App config loading  |
+------------------------+