Fastapi Development Tutorials, Guides & Insights

from pydantic import BaseSettings

class Settings(BaseSettings):
    app_name: str = "My App"
    admin_email: str

    class Config:
        env_prefix = "MYAPP_"

settings = Settings()
print(settings.app_name)
print(settings.admin_email)

• Use Pydantic models for API request and response validation.
• Leverage type coercion to simplify data handling.
• Use nested models for complex data structures.
• Manage application settings and configurations with Pydantic's BaseSettings.
• Take advantage of constrained types for stricter validation rules.

from fastapi import FastAPI
from pydantic import BaseModel
from typing import List

app = FastAPI()

class Book(BaseModel):
    title: str
    author: str

# Sample data
books_db = [
    Book(title="The Catcher in the Rye", author="J.D. Salinger"),
    Book(title="To Kill a Mockingbird", author="Harper Lee"),
    Book(title="1984", author="George Orwell")
]

@app.get("/books/", response_model=List[Book])
async def get_books():
    return books_db

@app.post("/books/", response_model=Book)
async def add_book(book: Book):
    books_db.append(book)
    return book

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="127.0.0.1", port=8000)