[Reading Challenge Season 2] <From Planning to Launch with FastAPI> with the Author

This challenge is a challenge to complete reading the book "From Planning to Launch, FastAPI Development White Paper".

🔗 View Book Introduction

If AI coding agents can create everything with just a few clicks, is there really a need to learn FastAPI ourselves?

Of course!

When a person is knowledgeable and provides proper guidance, AI can produce implementations effectively, efficiently, and quickly. Python and FastAPI are technology stacks that AI coding agents frequently choose and utilize well. They are also excellent for humans to learn and use. They are great tools for both humans and AI alike.

However, the concerns and insights gained through the process of launching and operating a service are difficult to fill with AI. Fill that gap through my book and challenge!

Learning Topics and Goals

• It covers the process of developing an appointment scheduling service using FastAPI and launching it by deploying it to a production server.

• You will learn about service planning, data design, TDD, Google integration, deployment to AWS Lightsail, and deployment automation.

• It provides topics for considering policy design and other elements necessary for launching and operating a service.

  
  

Challenge Schedule

• Recruitment Schedule: March 2, 2026, to March 15, 2026

• Challenge Schedule: From March 16, 2026, to June 15, 2026

• Daily reading amount: Average 20–30 pages

Precautions

• Unlike the first round, the review lectures for the second round of this challenge will only be available until June 15th.

• For those who wish to learn at their own pace without a time limit after purchase, we recommend the lecture content to be released in the future. (Scheduled for April or May 2026)

  
  

Challenge Benefits

• Beyond just the contents of the book, video lectures are provided to expand and enhance the learning experience.

  
  

• We increase the completion rate by providing a workload designed for learning and practicing on weekdays.

• Upon completion, you will gain the experience of having deployed a project to an actual cloud service!

• This challenge will end with this current cohort and will be expanded and released as a lecture series afterward. This is the final cohort operated for the purpose of introducing the book, and it is the last chance to participate without a price burden.

• For those who complete all missions and finish the course, I will provide a full refund in the form of a coupon that can be used for my next lecture.

  
  

“Challenge Class 1 Reviews

Participants of the 1st Challenge gave it rave reviews, with an average rating of 4.93.

First, how to differentiate your portfolio

Launching and operating a project is a differentiator in itself. Since many toy projects aim solely at creation, they often stop at running on localhost:8000. While the creator may have put in a lot of effort, unfortunately, the toy projects made by many new or junior developers are generally similar. In a way, this is natural because their experiences and what they have learned are similar.

The second reason why launching and operating a project is a differentiator is that there is a lot of room for self-reflection and personal input during the operation phase. In the development stage, there is a specific project goal, and this goal is likely to be similar to other people's toy projects; however, operation is so diverse that it is difficult to specify a single goal. This is because it is hard to know exactly what the users, or customers, want. Therefore, most user feedback is obtained from users during the operation phase. Your own deliberations and judgments regarding user feedback belong entirely to you.

Effective Methods for Learning and Growth

In 2007, I first encountered the web framework called Django. At the time, there were hardly any resources on the internet, let alone books in Korea. A year later, I published the first-ever Django tutorial series in Korean, which helped me build a personal brand around Python and Django. The brand I established back then continues to benefit my professional life to this day.

My proficiency in Django as a developer grew not so much from developing toy projects, but from launching a service and operating it for several months with even just a few hundred users. To be honest, surprisingly, even up until the point I created that small service with Python and Django, I only knew the basic syntax of Python and had never actually built anything with Django. Looking back now, I grew by spending hours struggling to solve problems that were actually very simple and easy.

It is said that you can achieve better growth by setting the goals of your assignments as learning objectives. If you focus your goals on learning throughout the process of creating, launching, and operating a toy project, you will undoubtedly grow much more than if you simply stopped at running it on your localhost.

Why FastAPI is great for project development and learning

One of the many reasons FastAPI is preferred is that the learning curve is not steep. Developers who have previously developed web application servers with Python can move beyond verification and start developing and operating actual APIs within just a few hours. This is because the framework's intervention in the most basic and frequently used functions is minimal, allowing for development that feels like writing pure Python code.

It is not just for learning purposes. FastAPI is widely used in the industry; it is easy to learn and offers great performance, making it especially popular among those in data processing or AI-related roles.