FastAPI tutorial for beginners - a FastApi docs playlist

FastAPI is a powerful and efficient web API framework that is easy to use and quick to learn. With its built-in data validation and support for async and await, it's a great choice for building APIs in Python. Code the FastAPI docs with me!

FastAPI tutorial for beginners - a FastApi docs playlist
FastAPI tutorial series on YouTube

FastAPI is a powerful and efficient web API framework that is easy to use and quick to learn. With its built-in data validation and support for async and await, it's a great choice for building APIs in Python.

About this playlist

In this playlist, we code the FastAPI docs, starting with the home page (see Part 0 Getting Started below), and then moving into the Tutorial.

Part 0: FastAPI getting started ⚡️ FastAPI tutorial for beginners

Part 0: FastAPI getting started ⚡️ FastAPI tutorial for beginners

Video notes ✏️

In this video - Part O: FastAPI getting started, we work through the FastAPI getting started tutorial on the FastAPI documentation home page. Here's a summary of the steps we take in the video.

Getting started with FastAPI is easy. First, make sure you have Python installed on your machine. If you're on a Mac, you can use Homebrew for this.

Next, use pip to install FastAPI and its dependencies. You can also install the Uvicorn server, which FastAPI uses to run your application.

pip install fastapi
pip install uvicorn["standard"]

Once you have FastAPI installed, it's time to start building your API. FastAPI is built on top of the Starlette framework, so it's easy to define your routes and handlers using async and await. FastAPI also provides built-in support for data validation, which makes it easy to ensure that your API is receiving and returning the right data.

Here's an example of how you can define a route in FastAPI:

from fastapi import FastAPI

app = FastAPI()

async def root():
    return {"message": "Hello World"}

This code defines a route for the root URL ("/") that returns a JSON object with a "message" key.

FastAPI also makes it easy to handle different types of HTTP requests. You can use the, @app.put, and @app.delete decorators to define handlers for POST, PUT, and DELETE requests, respectively.

With FastAPI, you can easily build a web API that supports all of the standard HTTP verbs, and you can do it in just a few lines of code. This makes it a great choice for building APIs quickly and efficiently.

In addition to its built-in features, FastAPI also provides integration with popular third-party tools like SQLAlchemy and Pydantic. This makes it easy to build complex APIs that interact with databases and other external services.

FastAPI docs

The FastAPI documentation is a comprehensive resource that provides detailed information and guidance for working with the FastAPI framework. Whether you're a beginner or an experienced developer, the FastAPI docs offer everything you need to get started and make the most out of this powerful framework.

To begin, the documentation walks you through the process of creating a FastAPI application. It provides clear and concise instructions on how to install FastAPI using pip, ensuring that you have the necessary dependencies in place. The step-by-step guide allows you to quickly set up a FastAPI project and start building your API.

The FastAPI documentation serves as a valuable reference for understanding the various features and capabilities of the framework. It covers a wide range of topics, including request handling, routing, input validation, authentication, database integration, and much more. Each topic is explained in detail, with code examples that illustrate the concepts and demonstrate best practices.

One of the standout features of FastAPI is its seamless integration with Python. Leveraging the power of Python's type hints, FastAPI enables automatic data validation, serialization, and documentation generation. This unique combination allows you to write clean and reliable code while reducing the chances of errors and inconsistencies.

Throughout the FastAPI documentation, you'll find numerous examples that showcase different aspects of the framework. These examples serve as practical illustrations of how to use FastAPI in real-world scenarios. By studying these examples and following along, you can gain a deeper understanding of FastAPI's capabilities and learn how to apply them to your own projects.

In addition to the extensive explanations and examples, the FastAPI documentation also includes helpful guides, tips, and tricks to optimize your development workflow. Whether you're looking to deploy your FastAPI application, integrate it with other technologies, or scale it to handle high loads, the documentation offers guidance and solutions to ensure your success.

The FastAPI documentation is a valuable resource for anyone looking to harness the power of the FastAPI framework. Whether you're starting a new project or migrating an existing one, the documentation provides clear and concise instructions, code examples, and in-depth explanations to help you master FastAPI and build robust and efficient APIs.

Part 1: Intro ⚡️ FastAPI tutorial for beginners - FastAPI docs #vscode

Part 1: Intro ⚡️ FastAPI tutorial for beginners - FastAPI docs #vscode

Video notes ✏️

Welcome to the first video in the FastAPI tutorial for beginners playlist! In this playlist, we will be working through the Tutorial section from the FastAPI docs (the FastAPI documentation). You might have heard about FastAPI's excellent documentation.

The documentation is well-organized, concise, and sprinkled with just the right amount of emojis. However, when you open the Tutorial section and see 44 pages filled with pretty advanced API concepts, it can be overwhelming. Don't worry, I’ve got you covered! Just like the FastAPI documentation, this playlist is structured to gradually build on each topic. Each video will align with the corresponding page in the documentation, allowing you to jump directly to specific topics that suit your API needs. We will use the same project in Visual Studio Code (VSCode) throughout the playlist, with each video building on the previous one.

To get started, we set up Visual Studio Code for this FastAPI series. I guide you through the process step by step.  Make sure you have the Pylance and Python extensions from Microsoft installed in VSCode, as they are crucial for coding in Python. How to create a virtual environment in VSCode.

To do this, go to the search bar in VSCode and look for the "Python: Create Environment" command or type a greater-than sign to filter for commands and then start typing Python. Select the option for a Python virtual environment. If you have multiple Python versions installed, choose the version required for FastAPI (3.7 or higher). Make sure you have the environment created and activated.

How to install FastAPI - pip

Open a terminal window in VSCode by going to the Terminal dropdown in the menu bar and selecting "New Terminal." Check if your virtual environment is activated (you should see `(.venv)` in your command line prompt). If not, try closing and reopening the terminal or the entire folder to activate it. If you're still facing issues, a quick Google search should help you resolve the activation problem.

In the terminal, run the command `pip install "fastapi[all]"` to install FastAPI with all its optional dependencies and features. Alternatively, you can install only FastAPI without the optional dependencies by running `pip install fastapi`. In that case, if you want to use the FastAPI local server (uvicorn), you will need to install it separately.

The FastAPI docs Advanced User Guide

The last section on the page we're currently working on mentions the FastAPI Advanced User Guide. We’re not going there… at least not in this playlist. This playlist follows the Tutorial section of the FastAPI docs, just as the documentation suggests you do before heading to the Advanced User Guide. Stay tuned for the next video, where we will cover the "First Steps" page.

Part 2: First steps ⚡️ FastAPI tutorial for beginners - building the FastAPI docs #vscode

Part 2: First steps ⚡️ FastAPI tutorial for beginners - building the FastAPI docs #vscode

Video notes ✏️

This video is part of the FastAPI tutorial series for beginners. We'll be working through the "First Steps" page in the FastAPI documentation.  In the last video, we set up Visual Studio Code and installed FastAPI. Now, we dive into the detailed "Recap" section of the page.

Step 1 is about importing the FastAPI module, which provides the functionality we need for our API. We create a Python file called `` and import FastAPI using `from fastapi import FastAPI`. This gives us access to the `FastAPI` class for creating our application.

Step 2 involves creating an instance of the FastAPI class. We create a variable called `app` and assign the instance of the FastAPI class to it.

Step 3 introduces the path operation decorator. We associate a function with an HTTP GET request to the root path using `@app.get("/")`. This decorator tells FastAPI to execute the decorated function when a GET request is made to the root path.

Step 4 is all about defining the path operation function. We use the `async` keyword to create an asynchronous function called `root()`. This allows the function to handle multiple tasks simultaneously without waiting for each task to finish. The async keyword in Python is used to define an asynchronous function. It is part of Python's asynchronous programming capabilities introduced in Python 3.5 with the asyncio module.

To learn more about asynchronous programming and the async keyword in Python, you can refer to the official Python documentation on "Coroutines and Tasks" in the asyncio module. Here's the link to the relevant section in the Python docs: Coroutines and Tasks

This section provides detailed explanations and examples of using coroutines and the async keyword in Python's asynchronous programming model. It covers the concepts and syntax related to working with asynchronous functions and managing concurrent tasks.

Step 5 focuses on returning content in response to the GET request. We can return various Python data types, such as dictionaries, lists, strings, etc. FastAPI automatically serializes supported data types to JSON before sending the response. Unlike some other frameworks, FastAPI handles the JSON serialization automatically.

To see the result in the browser, we use the command `uvicorn main:app --reload` to start the server. Clicking the local server URL or copying it into the browser will display our "Hello World" JSON response. If you encounter 404 errors, they are reminding you to create icons for your app and are safe to ignore for now.

That's it for this video. In the next video, we cover the Path Parameters page of the FastAPI docs.

Part 3: Path parameters ⚡️ FastAPI tutorial for beginners - building the FastAPI docs #vscode

Coming soon.

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How does FastAPI compare to other Python web frameworks?

FastAPI is a Python web framework designed for building fast and efficient web applications. It is often compared to other popular Python web frameworks such as Flask and Django. FastAPI is known for its high performance, easy-to-use interface, and built-in features for dependency management and data validation.

Is FastAPI easy to learn for beginners?

FastAPI can be easy to learn for beginners, especially if they already have a basic understanding of Python programming and web development concepts. FastAPI has an intuitive interface and documentation, making it easy to get started with building web applications.

What are the advantages of using FastAPI?

Some of the advantages of using FastAPI include its high performance, built-in features for dependency management and data validation, easy-to-use interface, and compatibility with asynchronous programming.

Can FastAPI be used for production applications?

Yes, FastAPI can be used for production applications. It has been adopted by many companies and organizations for building high-performance web applications.

Watch the #short on YouTube

FastAPI is popularly used for building APIs, microservices, and web applications that require high performance, scalability, and real-time capabilities. It is often used in industries such as finance, healthcare, and gaming.

FastAPI ⚡️Maybe the best Python API web framework

FastAPI project ideas

Want to try FastAPI out but don't know where to start? Here's a list of some project ideas for beginners:

Todo list API

Build a simple API for creating, reading, updating, and deleting tasks from a to-do list.

Weather API

Create an API that returns current weather data for a given location using an external weather API like OpenWeatherMap.

Quote generator API

Build an API that generates random quotes or inspirational messages.

URL shortener API

Create an API that shortens URLs and returns a shortened link that redirects to the original URL.

Image recognition API

Use a pre-trained machine learning model like TensorFlow to create an API that can identify objects in images.

Movie rating API

Build an API that returns ratings and reviews for movies using an external movie database API like IMDB.

Book recommendation API

Create an API that recommends books based on user preferences and reading history.

Stock market API

Build an API that returns real-time stock market data for a given stock symbol using an external financial data API like Yahoo Finance.

These projects are great for beginners as they are relatively simple, but still provide a good opportunity to learn about the core concepts of building APIs with FastAPI.