🚀 Lesson 3 — Pydantic Deep Dive (FastAPI’s Superpower)

Pydantic is the heart of FastAPI. It gives:

✔ Automatic data validation
✔ Type safety
✔ Error handling
✔ Clean models
✔ Performance (written in Rust, ultra-fast)

By the end of this lesson, you will be able to build industry-quality request/response schemas.

🎯 What You Will Learn Today

✔ Basic & advanced Pydantic models
✔ Optional fields
✔ Default values
✔ Input validation
✔ Nested models
✔ Lists & dictionaries
✔ Enums
✔ Validators
✔ Response models
✔ Industry-grade model design

Let’s begin. 🔥

🧠 1. Basic Pydantic Model (Warm-up)

from pydantic import BaseModel

class User(BaseModel):
    name: str
    age: int
    email: str

FastAPI automatically:

• Validates type
• Provides documentation
• Generates schemas

🎯 2. Optional Fields & Default Values

from typing import Optional

class User(BaseModel):
    name: str
    age: int
    email: Optional[str] = None

This means:

• email can be missing
• email defaults to None

🔒 3. Field Validation (Constraints)

Use Field() for validation rules.

from pydantic import BaseModel, Field

class Product(BaseModel):
    name: str = Field(..., min_length=3)
    price: float = Field(..., gt=0)
    stock: int = Field(default=0, ge=0)

Validations:

• name: at least 3 chars
• price: must be > 0
• stock: must be ≥ 0

🧩 4. Nested Models

Models inside models.

class Address(BaseModel):
    city: str
    pincode: int

class User(BaseModel):
    name: str
    address: Address

Send JSON:

{
  "name": "Rajeev",
  "address": {
    "city": "Bangalore",
    "pincode": 560001
  }
}

Pydantic validates deeply. 🔥

📦 5. Lists & Dictionaries

class Order(BaseModel):
    items: list[str]
    quantities: dict[str, int]

JSON example:

{
  "items": ["apple", "banana"],
  "quantities": {"apple": 3, "banana": 5}
}

🎨 6. Enums (Industry Standard for Fixed Choices)

from enum import Enum

class Status(str, Enum):
    active = "active"
    inactive = "inactive"
    banned = "banned"

class User(BaseModel):
    name: str
    status: Status

Input must be:

• “active”
• “inactive”
• “banned”

🧪 7. Custom Validation with Validators

You can write your own validation logic.

from pydantic import BaseModel, validator

class User(BaseModel):
    name: str
    age: int

    @validator("age")
    def validate_age(cls, v):
        if v < 18:
            raise ValueError("User must be 18+")
        return v

🛠 8. Response Models (Very Industry Important)

FastAPI uses response models to control output fields and hide sensitive info.

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    name: str
    age: int
    password: str

class UserPublic(BaseModel):
    name: str
    age: int

@app.post("/users", response_model=UserPublic)
def create_user(user: User):
    return user

Even if the user sends a password:

• Response will not include it
• Only name and age shown

Production-grade security. ✔

🏭 9. Industry Example — E-Commerce Order Schema

class Product(BaseModel):
    id: int
    name: str
    price: float

class Customer(BaseModel):
    id: int
    name: str
    email: str

class Order(BaseModel):
    order_id: int
    customer: Customer
    items: list[Product]
    total_amount: float = Field(..., gt=0)

This is used in:

• Swiggy
• Amazon
• Flipkart
• Any e-com microservice

🧠 10. Sub-models & Partial Updates (PATCH)

class UserUpdate(BaseModel):
    name: Optional[str] = None
    age: Optional[int] = None

If a field is missing → don’t update it.
Used for PATCH operations.

📌 Lesson 3 Summary

You now know:

✔ Optional fields
✔ Nesting
✔ Field validations
✔ Custom validators
✔ Enums
✔ Response models
✔ Lists/dicts
✔ Partial update models

This makes you ready for:

• Real backend systems
• AI/ML API design
• E-commerce microservices
• Enterprise APIs

🚀 Ready for Lesson 4 — AsyncIO, Concurrency & High Performance?

Lesson 4 covers:

✔ async vs sync
✔ await, tasks, coroutines
✔ parallel HTTP calls
✔ long-running processes
✔ FastAPI concurrency tricks
✔ Industry performance patterns

Shall I continue with Lesson 4 now?

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