Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Building Data Science Applications with FastAPI
  • Table Of Contents Toc
Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI - Second Edition

By : Voron
4.2 (9)
close
close
Building Data Science Applications with FastAPI

Building Data Science Applications with FastAPI

4.2 (9)
By: Voron

Overview of this book

Building Data Science Applications with FastAPI is the go-to resource for creating efficient and dependable data science API backends. This second edition incorporates the latest Python and FastAPI advancements, along with two new AI projects – a real-time object detection system and a text-to-image generation platform using Stable Diffusion. The book starts with the basics of FastAPI and modern Python programming. You'll grasp FastAPI's robust dependency injection system, which facilitates seamless database communication, authentication implementation, and ML model integration. As you progress, you'll learn testing and deployment best practices, guaranteeing high-quality, resilient applications. Throughout the book, you'll build data science applications using FastAPI with the help of projects covering common AI use cases, such as object detection and text-to-image generation. These hands-on experiences will deepen your understanding of using FastAPI in real-world scenarios. By the end of this book, you'll be well equipped to maintain, design, and monitor applications to meet the highest programming standards using FastAPI, empowering you to create fast and reliable data science API backends with ease while keeping up with the latest advancements.
Table of Contents (21 chapters)
close
close
1
Part 1: Introduction to Python and FastAPI
7
Part 2: Building and Deploying a Complete Web Backend with FastAPI
13
Part 3: Building Resilient and Distributed Data Science Systems with FastAPI

Installing a Python distribution using pyenv

Python is already bundled with most Unix environments. To ensure this is the case, you can run this command in a command line to show the Python version currently installed:

  $ python3 --version

The output version displayed will vary depending on your system. You may think that this is enough to get started, but it poses an important issue: you can’t choose the Python version for your project. Each Python version introduces new features and breaking changes. Thus, it’s important to be able to switch to a recent version for new projects to take advantage of the new features but still be able to run older projects that may not be compatible. This is why we need pyenv.

The pyenv tool (https://github.com/pyenv/pyenv) helps you manage and switch between multiple Python versions on your system. It allows you to set a default Python version for your whole system but also per project.

Beforehand, you need to install several build dependencies on your system to allow pyenv to compile Python on your system. The official documentation provides clear guidance on this (https://github.com/pyenv/pyenv/wiki#suggested- build-environment), but here are the commands you should run:

  1. Install the build dependencies:
    • For macOS users, use the following:
      $ brew install openssl readline sqlite3 xz zlib tcl-tk
    • For Ubuntu users, use the following:
      $ sudo apt update; sudo apt install make build-essential libssl-dev zlib1g-dev \libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev

Package managers

brew and apt are what are commonly known as package managers. Their role is to automate the installation and management of software on your system. Thus, you don’t have to worry about where to download them from and how to install and uninstall them. Those commands just tell the package manager to update its internal package index and then install the list of required packages.

  1. Install pyenv:
    $ curl https://pyenv.run | bash

Tip for macOS users

If you are a macOS user, you can also install it with Homebrew: brew install pyenv.

  1. This will download and execute an installation script that will handle everything for you. At the end, it’ll prompt you with some instructions to add some lines to your shell scripts so that pyenv is discovered properly by your shell:
    • If your shell is bash (the default for most Linux distributions and older versions of macOS), run the following commands:
      echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrcecho 'command -v pyenv >/dev/null || export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrcecho 'eval "$(pyenv init -)"' >> ~/.bashrc
    • If your shell is zsh (the default in the latest version of macOS), run the following commands:
      echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.zshrcecho 'command -v pyenv >/dev/null || export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.zshrcecho 'eval "$(pyenv init -)"' >> ~/.zshrc

What is a shell and how do I know the one I’m using?

The shell is the underlying program running when you start a command line. It’s responsible for interpreting and running your commands. Several variants of those programs have been developed over time, such as bash and zsh. Even though they have their differences, in particular the names of their configuration files, they are mostly inter-compatible. To find out which shell you’re using, you can run the echo $SHELL command.

  1. Reload your shell configuration to apply those changes:
    $ exec "$SHELL"
  2. If everything went well, you should now be able to invoke the pyenv tool:
    $ pyenv>>> pyenv 2.3.6>>> Usage: pyenv <command> [<args>]
  3. We can now install the Python distribution of our choice. Even though FastAPI is compatible with Python 3.7 and later, we’ll use Python 3.10 throughout this book, which has a more mature handling of the asynchronous paradigm and type hinting. All the examples in the book were tested with this version but should work flawlessly with newer versions. Let’s install Python 3.10:
    $ pyenv install 3.10

This may take a few minutes since your system will have to compile Python from the source.

What about Python 3.11?

You might wonder why we use Python 3.10 here while Python 3.11 is already released and is available. At the time of writing, not every library we’ll use throughout this book officially supports this newest version. That’s why we prefer to stick with a more mature version. Don’t worry, though: what you’ll learn here will still be relevant to future versions of Python.

  1. Finally, you can set the default Python version with the following command:
    $ pyenv global 3.10

This will tell your system to always use Python 3.10 by default unless specified otherwise in a specific project.

  1. To make sure everything is in order, run the following command to check the Python version that is invoked by default:
    $ python --versionPython 3.10.8

Congratulations! You can now handle any version of Python on your system and switch it whenever you like!

Why does it show 3.10.8 instead of just 3.10?

The 3.10 version corresponds to a major version of Python. The Python core team regularly publishes major versions with new features, depreciations, and sometimes breaking changes. However, when a new major version is published, previous versions are not forgotten: they continue to receive bug and security fixes. It’s the purpose of the third part of the version.

It’s very possible by the time you’re reading this book that you’ve installed a more recent version of Python 3.10, such as 3.10.9. It just means that fixes have been published. You can find more information about how the Python life cycle works and how long the Python core team plans to support previous versions in this official document: https://devguide.python.org/versions/.

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Building Data Science Applications with FastAPI
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon