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Introduction to FastAPI

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

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4 hours10 videos29 exercises

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Course Description

Introduction to FastAPI and Its Applications

APIs are commonly used to manage data on the web, and FastAPI is a popular new web framework for building APIs with Python. Data and Machine Learning Engineers leverage FastAPI to build applications that serve as context-aware data transactions and pipelines on the web.

Building Production-Grade Web Applications with FastAPI

In this course, you will learn how to build production-grade web applications leveraging your Python skills with the FastAPI framework. By the end, you’ll understand core use cases for FastAPI in relation to other Python web frameworks. You’ll learn to build APIs using all four types of HTTP operations and define request and response schemas. In addition, you’ll validate API requests, respond with appropriate HTTP status codes and messages, and execute code asynchronously to improve application performance. A hands-on project will guide you through building a classical CRUD (Create, Read, Update, Delete) API, testing workflows using Python's requests module.

Course Goals and Target Audience

This course is designed for experienced Python programmers who want to build web applications that manage data using FastAPI. Upon completing this course, you will have the foundation necessary to create FastAPI projects suited for high-throughput data management and ML model-serving pipelines.
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In the following Tracks

Building APIs in Python

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  1. 1

    FastAPI Basics

    Free

    We’ll start by learning FastAPI’s key features and core use cases. Then we will run our first application and test it out! Finally, we will learn the details of supporting GET and POST operations that include request parameters and build and test those endpoints.

    Play Chapter Now
    Why FastAPI?
    50 xp
    First application
    100 xp
    FastAPI vs. Django
    100 xp
    GET operations
    50 xp
    Hello world
    100 xp
    Hello who?
    100 xp
    POST operations
    50 xp
    Pydantic model
    100 xp
    POST operation in action
    100 xp
  2. 2

    FastAPI Advanced topics

    We’ll start by learning how to support PUT and DELETE operations using FastAPI. Then we will learn how to handle different kinds of errors and always return an appropriate status code in the response. Lastly we'll learn how to use async to enable concurrent requests that can handle higher workloads.

    Play Chapter Now
    PUT and DELETE operations
    50 xp
    PUT operation in action
    100 xp
    DELETE operation in action
    100 xp
    Handling errors
    50 xp
    Status code classification
    100 xp
    Handling a client error
    100 xp
    Using async for concurrent work
    50 xp
    When should we use async?
    50 xp
    Asynchronous DELETE operation
    100 xp
  3. 3

    Building and testing a JSON CRUD API

    We'll start by learning how to write system tests to validate individual FastAPI endpoints. Next we'll build a full JSON CRUD API to manage object lifecycles over HTTP. Finally, we'll learn how to test different application endpoints working together with manual functional tests.

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    FastAPI automated testing
    50 xp
    Unit tests vs. system tests
    100 xp
    System test
    100 xp
    Building a JSON CRUD API
    50 xp
    HTTP operations & CRUD steps
    100 xp
    DELETE operation response
    50 xp
    Complete JSON CRUD API
    100 xp
    Writing a manual functional test
    50 xp
    System tests vs. functional tests
    100 xp
    Functional test
    100 xp
    Wrap up
    50 xp
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In the following Tracks

Building APIs in Python

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collaborators

Collaborator's avatar
George Boorman
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Arne Warnke
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Katerina Zahradova

prerequisites

Introduction to APIs in PythonIntroduction to Object-Oriented Programming in Python
Matt Eckerle HeadshotMatt Eckerle

Software and Data Engineering Leader

Matt is an experienced engineer with a talent for simplifying complex projects and finding efficient solutions to challenging system problems. With a background in diverse technologies, he’s worked across all aspects of delivering real-time data insights and enjoys creating sustainable, impactful solutions.
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