Course Outline

Introduction

  • FastAPI vs Django vs Flask
  • Overview of FastAPI features and advantages

Getting Started

  • Installing FastAPI
  • Defining a schema using OpenAPI

Path and Query Parameters

  • Declaring path parameter types
  • Parsing and validating data
  • Declaring required and optional parameters
  • Converting query parameter types
  • Multiple path and query parameters

Declaring a Request Body with Pydantic Models

  • Creating a data model
  • Combining path, query, and body parameters
  • Declaring validations and metadata
  • Using deeply nested models
  • Defining example data
  • Response and extra models

Defining Forms and Files

  • Using form fields instead of JSON
  • Creating file parameters
  • Using file and form parameters

Handling Errors

  • Using HTTPException
  • Adding custom headers
  • Installing custom exception handlers
  • Overriding default exception handlers

Working with Databases

  • ORMs and file structure
  • Creating SQLAlchemy parts
  • Creating database models
  • Creating Pydantic models
  • Performing CRUD operations
  • Creating tables, dependency, and path operations
  • Reviewing and checking files
  • Interacting with the database

Security and Authentication

  • Using Oauth2 and OpenID connect
  • Defining multiple security schemes with OpenAPI
  • Using the FastAPI utilities

Deployments

  • Deployment concepts, stages, and tools
  • Working with Gunicorn and Uvicorn
  • Using container systems (Docker and Kubernetes)

Troubleshooting

Summary and Next Steps

Requirements

  • An understanding of API concepts
  • Python programming experience

Audience

  • Developers
  14 Hours
 

Testimonials

Related Courses

Programming for Biologists

  28 hours

Python for Natural Language Generation

  21 hours

Advanced Python - 4 Days

  28 hours

Python: Automate the Boring Stuff

  14 hours

FARM (FastAPI, React, and MongoDB) Full Stack Development

  14 hours

Natural Language Processing (NLP) with Python

  28 hours

Natural Language Processing (NLP) with Deep Dive in Python and NLTK

  35 hours

Python: Machine Learning with Text

  21 hours

Machine Learning with Python – 2 Days

  14 hours

Machine Learning with Python – 4 Days

  28 hours

Python Programming - 4 days

  28 hours

BDD with Python and Behave

  7 hours

Test Automation with Selenium and Python

  14 hours

Advanced Machine Learning with Python

  21 hours

Unit Testing with Python

  21 hours