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Building Python Microservices with FastAPI

Building Python Microservices with FastAPI

By : Sherwin John C. Tragura
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Building Python Microservices with FastAPI

Building Python Microservices with FastAPI

4 (8)
By: Sherwin John C. Tragura

Overview of this book

FastAPI is an Asynchronous Server Gateway Interface (ASGI)-based framework that can help build modern, manageable, and fast microservices. Because of its asynchronous core platform, this ASGI-based framework provides the best option when it comes to performance, reliability, and scalability over the WSGI-based Django and Flask. When working with Python, Flask, and Django microservices, you’ll be able to put your knowledge to work with this practical guide to building seamlessly manageable and fast microservices. You’ll begin by understanding the background of FastAPI and learning how to install, configure, and use FastAPI to decompose business units. You’ll explore a unique and asynchronous REST API framework that can provide a better option when it comes to building microservices. After that, this book will guide you on how to apply and translate microservices design patterns in building various microservices applications and RESTful APIs using the FastAPI framework. By the end of this microservices book, you’ll be able to understand, build, deploy, test, and experiment with microservices and their components using the FastAPI framework.
Table of Contents (17 chapters)
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1
Part 1: Application-Related Architectural Concepts for FastAPI microservice development
6
Part 2: Data-Centric and Communication-Focused Microservices Concerns and Issues
11
Part 3: Infrastructure-Related Issues, Numerical and Symbolic Computations, and Testing Microservices

Setting up the virtual environment

Let us start with the proper way of setting up the development environment of our FastAPI application. In Python development, it is common to manage the libraries and extension modules that are needed using a virtual environment. A virtual environment is a way of creating multiple different and parallel installations of Python interpreters and their dependencies where each has the application(s) to be compiled and run. Each instance has its own set of libraries depending on the requirements of its application(s). But first, we need to install the virtualenv module to pursue the creation of these instances:

pip install virtualenv

The following list describes the benefits of having a virtual environment:

  • To avoid the overlapping of the library version
  • To avoid broken installed module files due to namespace collisions
  • To localize the libraries to avoid conflicts with the globally installed modules on which some applications are...
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