Pydantic - Complete Learning Guide

📚 Project Overview

Comprehensive Pydantic learning project with hands-on examples and assignments.

🏗️ Project Structure

01-foundation/          # Basic Pydantic models
02-fields-validation/   # Field validation & constraints  
03-model-behavior/      # Validators & computed fields
04-nested-models/       # Complex nested structures
05-serialization/       # Data serialization/deserialization
fastapi/               # FastAPI integration

🎯 Learning Path

1. Foundation

Basic BaseModel usage, type annotations, data validation

from pydantic import BaseModel

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

2. Fields & Validation

Field constraints, optional fields, descriptions

from pydantic import BaseModel, Field

class Employee(BaseModel):
    name: str = Field(..., min_length=3, max_length=50)
    salary: float = Field(..., ge=10000)

3. Model Behavior

Custom validators, computed fields

@field_validator('username')
def username_length(cls, v):
    if len(v) < 4:
        raise ValueError("Username must be at least 4 characters")
    return v

@computed_field
@property
def total_price(self) -> float:
    return self.price * self.quantity

4. Nested Models

Embedding models, self-referencing

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

class User(BaseModel):
    name: str
    address: Address  # Nested model

5. Serialization

Data conversion, JSON encoding

model.model_dump()          # → dict
model.model_dump_json()     # → JSON string
Model.model_validate(data)  # Create from dict

6. FastAPI Integration

Request/Response models, dependency injection

@app.post('/signup')
def signup(user: UserSignup):
    return {'message': f'User {user.username} signed up'}

🚀 Quick Start

pip install -e .
python 01-foundation/examples/first_model.py

📝 Key Concepts Cheatsheet

Field Validation

field: str = Field(min_length=3, max_length=50)
number: int = Field(ge=0, le=100)

Validators

@field_validator('field_name')
@model_validator(mode='after')

Common Patterns

# Optional with default
field: Optional[str] = None

# Collections
items: List[str]
mapping: Dict[str, int]

# Custom validation
@field_validator('email')
def validate_email(cls, v):
    if '@' not in v:
        raise ValueError('Invalid email')
    return v

🎯 Practice Tips

1. Start with basic models, add complexity gradually
2. Use Field constraints for data integrity
3. Test with invalid data to understand validation
4. Leverage Python's type system fully
5. Read Pydantic's detailed validation errors