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FastAPI Cookbook
FastAPI Cookbook

FastAPI Cookbook: Develop high-performance APIs and web applications with Python

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Profile Icon Giunio De Luca
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Paperback Aug 2024 358 pages 1st Edition
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Paperback Aug 2024 358 pages 1st Edition
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FastAPI Cookbook

Working with Data

Data handling is the backbone of any web application, and this chapter is dedicated to mastering this critical aspect. You will embark on a journey of working with data in FastAPI, where you’ll learn the intricacies of integrating, managing, and optimizing data storage using both Structured Query Language (SQL) and NoSQL databases. We’ll cover how FastAPI, combined with powerful database tools, can create efficient and scalable data management solutions.

Starting with SQL databases, you’ll get hands-on experience in setting up a database, implementing create, read, update and delete (CRUD) operations, and understanding the nuances of working with SQLAlchemy – a popular object-relational mapping (ORM) option for Python. We’ll then shift gears to NoSQL databases, delving into the world of MongoDB. You’ll learn how to integrate it with FastAPI, handle dynamic data structures, and leverage the flexibility and scalability of...

Technical requirements

To effectively run and understand the code in this chapter, ensure you have the following set up. If you’ve followed Chapter 1, First Steps with FastAPI, you should already have some of these installed:

  • Python: Make sure you’ve installed Python version 3.9 or higher on your computer.
  • FastAPI: Install FastAPI along with all its dependencies using the pip install fastapi[all] command. As we saw in Chapter 1, First Steps with FastAPI, this command also installs Uvicorn, an ASGI server that’s necessary to run your FastAPI application.
  • Integrated development environment (IDE): A suitable IDE such as VS Code or PyCharm should be installed. These IDEs offer excellent support for Python and FastAPI development, providing features such as syntax highlighting, code completion, and easy debugging.
  • MongoDB: For the NoSQL database portions of this chapter, MongoDB needs to be installed on your local machine. Download and install the...

Setting up SQL databases

In the world of data handling, the power of Python meets the efficiency of SQL databases. This recipe aims to introduce you to how to integrate SQL databases within your application, a crucial skill for any developer looking to build robust and scalable web applications.

SQL is the standard language for managing and manipulating relational databases. When combined with FastAPI, it unlocks a world of possibilities in data storage and retrieval.

FastAPI’s compatibility with SQL databases is facilitated through ORMs. The most popular one is SQLAlchemy. We will focus on it in this recipe.

Getting ready

To begin, you’ll need to have FastAPI and SQLAlchemy installed in your virtual environment. If you followed the steps in Chapter 1, First Steps with FastAPI, you should have FastAPI already set up. For SQLAlchemy, a simple pip command is all that’s needed:

$ pip install sqlalchemy

Once installed, the next step is to configure...

Understanding CRUD operations with SQLAlchemy

After setting up your SQL database with FastAPI, the next crucial step is creating database models. This process is central to how your application interacts with the database. Database models in SQLAlchemy are essentially Python classes that represent tables in your SQL database. They provide a high-level, object-oriented interface to manipulate database records as if they were regular Python objects.

In this recipe, we will set up the create, read, update and delete (CRUD) endpoints to interact with the database.

Getting ready

With the models set up, you can now implement CRUD operations. These operations form the backbone of most web applications, allowing you to interact with the database.

How to do it…

For each operation, we will create a dedicated endpoint implementing the interacting operation with the database.

Creating a new user

To add a new user, we’ll use a POST request. In the main.py file...

Integrating MongoDB for NoSQL data storage

Transitioning from SQL to NoSQL databases opens up a different paradigm in data storage and management. NoSQL databases, like MongoDB, are known for their flexibility, scalability, and ability to handle large volumes of unstructured data. In this recipe, we’ll explore how to integrate MongoDB, a popular NoSQL database, with FastAPI.

NoSQL databases differ from traditional SQL databases in that they often allow for more dynamic and flexible data models. MongoDB, for example, stores data in binary JSON (BSON) format, which can easily accommodate changes in data structure. This is particularly useful in applications that require rapid development and frequent updates to the database schema.

Getting ready

Make sure you’ve installed MongoDB on your machine. If you haven’t done it yet, you can download the installer from https://www.mongodb.com/try/download/community.

FastAPI doesn’t provide a built-in ORM...

Working with data validation and serialization

Effective data validation stands as a cornerstone of robust web applications, ensuring that incoming data meets predefined criteria and remains safe for processing.

FastAPI harnesses the power of Pydantic, a Python library dedicated to data validation and serialization. By integrating Pydantic models, FastAPI streamlines the process of validating and serializing data, offering an elegant and efficient solution. This recipe shows how to utilize Pydantic models within FastAPI applications, exploring how they enable precise validation and seamless data serialization.

Getting ready

Pydantic models are essentially Python classes that define the structure and validation rules of your data. They use Python’s type annotations to validate that incoming data matches the expected format. When you use a Pydantic model in your FastAPI endpoints, FastAPI automatically validates incoming request data against the model.

In this recipe...

Working with file uploads and downloads

Handling files is a common requirement in web applications, whether it’s uploading user avatars, downloading reports, or processing data files. FastAPI provides efficient and easy-to-implement methods for both uploading and downloading files. This recipe will guide you through how to set up and implement file handling in FastAPI.

Getting ready

Let’s create a new project directory called uploads_and_downloads that contains a main.py module with a folder called uploads. This will contain the files from the application side. The directory structure will look like this:

uploads_and_downloads/
|─ uploads/
|─ main.py

We can now proceed to create the appropriate endpoints.

How to do it…

To handle file uploads in FastAPI, you must use the File and UploadFile classes from FastAPI. The UploadFile class is particularly useful as it provides an asynchronous interface and spools large files to disk to avoid...

Handling asynchronous data operations

Asynchronous programming is a core feature of FastAPI that allows you to develop highly efficient web applications. It allows your application to handle multiple tasks concurrently, making it particularly well-suited for I/O-bound operations, such as database interactions, file handling, and network communication.

Let’s delve into leveraging asynchronous programming in FastAPI for data operations, enhancing the performance and responsiveness of your applications.

Getting ready

FastAPI is built on Starlette and Pydantic, which provide a robust foundation for writing asynchronous code in Python using the asyncio library with async/await syntax.

The asyncio library allows you to write non-blocking code that can pause its execution while waiting for I/O operations to complete, and then resume where it left off, all without blocking the main execution thread.

This recipe demonstrates the benefits of using asyncio with FastAPI in...

Securing sensitive data and best practices

In the realm of web development, the security of sensitive data is paramount.

This recipe is a checklist of best practices for securing sensitive data in your FastAPI applications.

Getting ready

First and foremost, it’s crucial to understand the types of data that need protection. Sensitive data can include anything from passwords and tokens to personal user details. Handling such data requires careful consideration and adherence to security best practices.

Understanding the types of data that require protection sets the foundation for implementing robust security measures, such as leveraging environment variables for sensitive configurations, a key aspect of data security in app development.

Instead of hardcoding these values in your source code, they should be stored in environment variables, which can be accessed securely within your application. This approach not only enhances security but also makes your application...

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Key benefits

  • Explore FastAPI in depth, from basic setup to advanced features such as custom middleware and WebSockets
  • Discover practical strategies to optimize app performance and handle high traffic
  • Implement SQL and NoSQL integration techniques for versatile data management in FastAPI applications
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

FastAPI is a cutting-edge Python framework that is revolutionizing the way web apps and APIs are built. Known for its speed, simplicity, and scalability, FastAPI empowers developers to create high-performing applications with ease. This book will help you leverage FastAPI’s immense potential to handle high-traffic scenarios and integrate seamlessly with modern Python tools. The book begins by familiarizing you with the basics of setting up and configuring your FastAPI environment before moving to the intricacies of building RESTful APIs, managing data with SQL and NoSQL databases, and handling authentication and authorization. Next, you'll focus on advanced topics such as custom middleware, WebSocket communication, and integration with various Python libraries. Each chapter is meticulously crafted with practical recipes, progressing from foundational concepts to advanced features and best practices. The concluding chapters show you how to optimize performance, implement rate limiting, and execute background tasks, empowering you to become a proficient FastAPI developer. By the end of this book, you'll have gained the skills you need to migrate existing apps to FastAPI, and be equipped to tackle any challenge in the modern web development landscape, ensuring your apps are not only functional, but also efficient, secure, and scalable.

Who is this book for?

This book is for Python developers looking to enhance their skills to build scalable, high-performance web apps using FastAPI. Professionals seeking practical guidance to create APIs and web apps that can handle significant traffic and scale as needed will also find this book helpful by learning from both foundational insights and advanced techniques. The book is also designed for anyone familiar with RESTful APIs, HTTP protocols, and database systems, as well as developers looking to migrate existing applications to FastAPI or explore its advanced features.

What you will learn

  • Explore advanced FastAPI functionalities such as dependency injection, custom middleware, and WebSockets
  • Discover various types of data storage for powerful app functionality with SQL and NoSQL
  • Implement testing and debugging practices for clean, robust code
  • Integrate authentication and authorization mechanisms to secure web apps
  • Acquire skills to seamlessly migrate existing applications to FastAPI
  • Write unit and integration tests, ensuring reliability and security for your apps
  • Deploy your FastAPI apps to production environments for real-world use
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Table of Contents

14 Chapters
Chapter 1: First Steps with FastAPI Chevron down icon Chevron up icon
Chapter 2: Working with Data Chevron down icon Chevron up icon
Chapter 3: Building RESTful APIs with FastAPI Chevron down icon Chevron up icon
Chapter 4: Authentication and Authorization Chevron down icon Chevron up icon
Chapter 5: Testing and Debugging FastAPI Applications Chevron down icon Chevron up icon
Chapter 6: Integrating FastAPI with SQL Databases Chevron down icon Chevron up icon
Chapter 7: Integrating FastAPI with NoSQL Databases Chevron down icon Chevron up icon
Chapter 8: Advanced Features and Best Practices Chevron down icon Chevron up icon
Chapter 9: Working with WebSocket Chevron down icon Chevron up icon
Chapter 10: Integrating FastAPI with other Python Libraries Chevron down icon Chevron up icon
Chapter 11: Middleware and Webhooks Chevron down icon Chevron up icon
Chapter 12: Deploying and Managing FastAPI Applications Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
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