Building Python Web Apis With Fastapi

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Building Python Web APIs with FastAPI

Author : Abdulazeez Abdulazeez Adeshina
Publisher : Packt Publishing Ltd
Page : 216 pages
File Size : 53,5 Mb
Release : 2022-07-29
Category : Computers
ISBN : 9781801074513

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Building Python Web APIs with FastAPI by Abdulazeez Abdulazeez Adeshina Pdf

Discover FastAPI features and best practices for building and deploying high-quality web APIs from scratch Key Features • A practical guide to developing production-ready web APIs rapidly in Python • Learn how to put FastAPI into practice by implementing it in real-world scenarios • Explore FastAPI, its syntax, and configurations for deploying applications Book Description RESTful web services are commonly used to create APIs for web-based applications owing to their light weight and high scalability. This book will show you how FastAPI, a high-performance web framework for building RESTful APIs in Python, allows you to build robust web APIs that are simple and intuitive and makes it easy to build quickly with very little boilerplate code. This book will help you set up a FastAPI application in no time and show you how to use FastAPI to build a REST API that receives and responds to user requests. You'll go on to learn how to handle routing and authentication while working with databases in a FastAPI application. The book walks you through the four key areas: building and using routes for create, read, update, and delete (CRUD) operations; connecting the application to SQL and NoSQL databases; securing the application built; and deploying your application locally or to a cloud environment. By the end of this book, you'll have developed a solid understanding of the FastAPI framework and be able to build and deploy robust REST APIs. What you will learn • Set up a FastAPI application that is fully functional and secure • Understand how to handle errors from requests and send proper responses in FastAPI • Integrate and connect your application to a SQL and NoSQL (MongoDB) database • Perform CRUD operations using SQL and FastAPI • Manage concurrency in FastAPI applications • Implement authentication in a FastAPI application • Deploy a FastAPI application to any platform Who this book is for This book is for Python developers who want to learn FastAPI in a pragmatic way to create robust web APIs with ease. If you are a Django or Flask developer looking to try something new that's faster, more efficient, and produces fewer bugs, this FastAPI Python book is for you. The book assumes intermediate-level knowledge of Python programming.

Building Python Microservices with FastAPI

Author : Sherwin John C. Tragura
Publisher : Packt Publishing Ltd
Page : 420 pages
File Size : 42,8 Mb
Release : 2022-08-30
Category : Computers
ISBN : 9781803238791

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Building Python Microservices with FastAPI by Sherwin John C. Tragura Pdf

Discover the secrets of building Python microservices using the FastAPI framework Key Features Provides a reference that contains definitions, illustrations, comparative analysis, and the implementation of real-world apps Covers concepts, core details, and advanced integration and design-related topics Imparts context, app templates, suggestions, and insights that are helpful to actual projects Book Description 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. What you will learn Understand, orient, and implement REST APIs using the basic components of the FastAPI framework Build asynchronous as well as synchronous REST services using the built-in pydantic module and asyncio support Create small-scale and large-scale microservices applications using features supported by FastAPI Build event-driven and message-driven applications using the framework Create an asynchronous and synchronous data layer with both relational and NoSQL databases Perform numerical and symbolic computations with FastAPI Who this book is for This book is for Python web developers, advanced Python developers, and backend developers using Flask or Django who want to learn how to use the FastAPI framework to implement microservices. Readers familiar with the REST API and microservices will also benefit from this book. Some parts of the book contain general concepts, processes, and instructions that intermediate-level developers and Python enthusiasts can relate to as well.

Building Data Science Applications with FastAPI

Author : Francois Voron
Publisher : Packt Publishing Ltd
Page : 426 pages
File Size : 49,8 Mb
Release : 2021-10-08
Category : Computers
ISBN : 9781801074186

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Building Data Science Applications with FastAPI by Francois Voron Pdf

Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications Key FeaturesCover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency injectionDevelop efficient RESTful APIs for data science with modern PythonBuild, test, and deploy high performing data science and machine learning systems with FastAPIBook Description FastAPI is a web framework for building APIs with Python 3.6 and its later versions based on standard Python-type hints. With this book, you'll be able to create fast and reliable data science API backends using practical examples. This book starts with the basics of the FastAPI framework and associated modern Python programming language concepts. You'll be taken through all the aspects of the framework, including its powerful dependency injection system and how you can use it to communicate with databases, implement authentication and integrate machine learning models. Later, you'll cover best practices relating to testing and deployment to run a high-quality and robust application. You'll also be introduced to the extensive ecosystem of Python data science packages. As you progress, you'll learn how to build data science applications in Python using FastAPI. The book also demonstrates how to develop fast and efficient machine learning prediction backends and test them to achieve the best performance. Finally, you'll see how to implement a real-time face detection system using WebSockets and a web browser as a client. By the end of this FastAPI book, you'll have not only learned how to implement Python in data science projects but also how to maintain and design them to meet high programming standards with the help of FastAPI. What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkImplement a FastAPI dependency to efficiently run a machine learning modelIntegrate a simple face detection algorithm in a FastAPI backendIntegrate common Python data science libraries in a web backendDeploy a performant and reliable web backend for a data science applicationWho this book is for This Python data science book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

Microservice APIs

Author : Jose Haro Peralta
Publisher : Simon and Schuster
Page : 438 pages
File Size : 40,9 Mb
Release : 2023-03-07
Category : Computers
ISBN : 9781638350569

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Microservice APIs by Jose Haro Peralta Pdf

Strategies, best practices, and patterns that will help you design resilient microservices architecture and streamline your API integrations. In Microservice APIs, you’ll discover: Service decomposition strategies for microservices Documentation-driven development for APIs Best practices for designing REST and GraphQL APIs Documenting REST APIs with the OpenAPI specification (formerly Swagger) Documenting GraphQL APIs using the Schema Definition Language Building microservices APIs with Flask, FastAPI, Ariadne, and other frameworks Service implementation patterns for loosely coupled services Property-based testing to validate your APIs, and using automated API testing frameworks like schemathesis and Dredd Adding authentication and authorization to your microservice APIs using OAuth and OpenID Connect (OIDC) Deploying and operating microservices in AWS with Docker and Kubernetes Microservice APIs teaches you practical techniques for designing robust microservices with APIs that are easy to understand, consume, and maintain. You’ll benefit from author José Haro Peralta’s years of experience experimenting with microservices architecture, dodging pitfalls and learning from mistakes he’s made. Inside you’ll find strategies for delivering successful API integrations, implementing services with clear boundaries, managing cloud deployments, and handling microservices security. Written in a framework-agnostic manner, its universal principles can easily be applied to your favorite stack and toolset. About the technology Clean, clear APIs are essential to the success of microservice applications. Well-designed APIs enable reliable integrations between services and help simplify maintenance, scaling, and redesigns. Th is book teaches you the patterns, protocols, and strategies you need to design, build, and deploy effective REST and GraphQL microservices APIs. About the book Microservice APIs gathers proven techniques for creating and building easy-to-consume APIs for microservices applications. Rich with proven advice and Python-based examples, this practical book focuses on implementation over philosophy. You’ll learn how to build robust microservice APIs, test and protect them, and deploy them to the cloud following principles and patterns that work in any language. What's inside Service decomposition strategies for microservices Best practices for designing and building REST and GraphQL APIs Service implementation patterns for loosely coupled components API authorization with OAuth and OIDC Deployments with AWS and Kubernetes About the reader For developers familiar with the basics of web development. Examples are in Python. About the author José Haro Peralta is a consultant, author, and instructor. He’s also the founder of microapis.io. Table of Contents PART 1 INTRODUCING MICROSERVICE APIS 1 What are microservice APIs? 2 A basic API implementation 3 Designing microservices PART 2 DESIGNING AND BUILDING REST APIS 4 Principles of REST API design 5 Documenting REST APIs with OpenAPI 6 Building REST APIs with Python 7 Service implementation patterns for microservices PART 3 DESIGNING AND BUILDING GRAPHQL APIS 8 Designing GraphQL APIs 9 Consuming GraphQL APIs 10 Building GraphQL APIs with Python PART 4 SECURING, TESTING, AND DEPLOYING MICROSERVICE APIS 11 API authorization and authentication 12 Testing and validating APIs 13 Dockerizing microservice APIs 14 Deploying microservice APIs with Kubernetes

Getting started with FastApi

Author : Andrés Cruz Yoris
Publisher : Andres Cruz
Page : 168 pages
File Size : 50,8 Mb
Release : 2024-06-29
Category : Computers
ISBN : 8210379456XXX

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Getting started with FastApi by Andrés Cruz Yoris Pdf

FastAPI is a great web framework for creating web APIs with Python; It offers us multiple features with which it is possible to create modular, well-structured, scalable APIs with many options such as validations, formats, typing, among others. When you install FastAPI, two very important modules are installed: Pydantic that allows the creation of models for data validation. Starlette, which is a lightweight ASGI tooltip, used to create asynchronous (or synchronous) web services in Python. With these packages, we have the basics to create APIs, but we can easily extend a FastAPI project with other modules to provide the application with more features, such as the database, template engines, among others. FastAPI is a high-performance, easy-to-learn, start-up framework; It is ideal for creating all kinds of sites that not only consist of APIs, but we can install a template manager to return complete web pages. This book is mostly practical, we will learn the basics of FastAPI, knowing its main features based on a small application that we will extend chapter after chapter and whose content you can see below: Chapter 1: We present some essential commands to develop in FastApi , we will prepare the environment and we will give an introduction to the framework . Chapter 2: One of the main factors in FastApi is the creation of resources for the API through functions, in this section we will deal with the basics of this, introducing routing between multiple files as well as the different options for the arguments and parameters of these routes. Chapter 3: In this section, learn how to handle HTTP status codes from API methods and also handle errors/exceptions from API methods. Chapter 4: In this section we will see how to create sample data to use from the automatic documentation that FastAPI offers for each of the API methods. Chapter 5: In this chapter we will see how to implement the upload of files, knowing the different existing variants in FastAPI. Chapter 6: In this chapter we will see how to connect a FastAPI application to a relational database such as MySQL. Chapter 7: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 8: In this chapter we will see installing and using a template engine in Python, specifically Jinja, with which we can return responses in HTML format. Chapter 9: In this chapter we will learn how to use dependencies. Chapter 10: In this chapter we will see how to use middleware to intercept requests to API methods and execute some procedure before the request or after generating the response. Chapter 11: In this chapter we will see how to create a user module, to register users, login, generate access tokens and logout. Chapter 12: In this chapter we will learn about some particularities and functionalities of FastAPI such as the use of annotations and the Ellipsis operator. Chapter 13: In this chapter we will see how to implement unit tests. Chapter 14: In this chapter we will know some general aspects applied to FastAPI.

Django for APIs

Author : William S. Vincent
Publisher : WelcomeToCode
Page : 201 pages
File Size : 47,6 Mb
Release : 2022-02-23
Category : Computers
ISBN : 8210379456XXX

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Django for APIs by William S. Vincent Pdf

Completely updated for Django 4.0 & Django REST Framework 3.13! Django for APIs is a project-based guide to building modern web APIs with Django & Django REST Framework. It is suitable for beginners who have never built an API before as well as professional programmers looking for a fast-paced introduction to Django fundamentals and best practices. Over the course of 200+ pages you'll learn how to set up a new project properly, how web APIs work under the hood, and advanced testing and deployment techniques. Three separate projects are built from scratch with progressively more advanced features including a Library API, Todo API, and Blog API. User authentication, permissions, documentation, viewsets, and routers are all covered thoroughly. Django for APIs is a best-practices guide to building powerful Python-based web APIs with a minimal amount of code.

Effective PyCharm

Author : Michael Kennedy,Matt Harrison
Publisher : Independently Published
Page : 221 pages
File Size : 47,9 Mb
Release : 2019-04-19
Category : Electronic
ISBN : 1095212532

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Effective PyCharm by Michael Kennedy,Matt Harrison Pdf

Hello and welcome to Effective PyCharm. In this book, we're going to look at all the different features of one of the very best environments for interacting and creating Python code, PyCharm. PyCharm is an IDE (integrated development environment) and this book will teach you how you can make the most of this super powerful editor.The first thing we are going to talk about is why do we want to use an IDE in the first place? What value does a relatively heavyweight application like PyCharm bring and why would we want to use it? There are many features that make PyCharm valuable. However, let's begin by talking about the various types of editors we can use and what the trade-offs are there.We're going to start by focusing on creating new projects and working with all the files in them. You'll see there's a bunch of configuration switcheswe can set to be more effective. Then we're going to jump right intowhat I would say is the star of the show--the editor.If you're writing code, you need an editor. You will be writing a lot of code. This includes typing new text and manipulating existing text. The editor has to be awesome and aid you in these tasks. We're going to focus on all the cool features that the PyCharm editor offers. We'll see that source control in particular, Git and Subversion are deeply integrated into PyCharm. There are all sorts of powerful things we can do beyond git, including actual GitHub integration. We are going to focus on source control and the features right inside the IDE.PyCharm is great at *refactoring*. Refactoring code is changing our code to restructure it in a different way, to use a slightly different algorithm, while not actually changing the behavior of the code. There are many powerful techniques in PyCharm that you can use to do this. Because it understands all of your files at once, it can safely refactor. It will even refactor doc strings and other items that could be overlooked without a deep understanding of code structures.There is powerful database tooling in PyCharm. You can interact with most databases including SQLite, MySQL, and Postgres. You can edit the data, edit the schemes, run queries and more. Because PyCharm has a deep understanding of your code, there is even integration between your database schema and the Python text editor. Note that PyCharm has a free version and a professional version. The database features are only available in the professional version.PyCharm is excellent at building web applications using libraries like Django, Pyramid, or Flask. It also has a full JavaScript editor and environment so you can use TypeScript or CoffeeScript. We'll look into both server-side and client-side features.PyCharm has a great visual debugger, and we are going to look at all the different features of it. You can use it to debug and understand your application. It has powerful breakpoint operations and data visualization that typically editors don't have.Profiling is a common task if you want to understand how your code is running. If your application is slow and you want it to go faster, you shouldn't guess where it is slow. PyCharm makes it easy to look at the code determine what it fast and slow, rather than relying on our intuition which may be flawed. PyCharm has some tremendous built-in visual types of tools for us to fundamentally understand the performance of our app.PyCharm has built-in test runners for pytest, unittest, and a number of Python testing frameworks. If you are doing any unit testing or integration testing, PyCharm will come to your aid. For example, one feature you can turn on is auto test execution. If you are changing certain parts of your code, PyCharm will automatically re-run the tests. There are a couple of additional tools that don't really land in any of the above categories. There is a chapter with the additional tools at the end.

Django for APIs

Author : William S. Vincent
Publisher : Unknown
Page : 198 pages
File Size : 54,8 Mb
Release : 2018-06-15
Category : Application program interfaces (Computer software)
ISBN : 1093633948

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Django for APIs by William S. Vincent Pdf

Learn how to build web APIs with Python and Django 2.2. Take a modern API-first approach to creating 3 different Django back-ends: a Library API, Todo API, and a Blog API with user authentication, permissions, proper documentation, and more. You'll even learn how to connect them to a React front-end for a truly full-stack web application. TABLE OF CONTENTS Introduction Chapter 1: Web APIs Chapter 2: Library website and API Chapter 3: Todo API Chapter 4: Todo React Frontend Chapter 5: Blog API Chapter 6: Permissions Chapter 7: User Authentication Chapter 8: Viewsets and Routers Chapter 9: Schemas and Documentation Conclusion

Building Data Science Applications with FastAPI - Second Edition

Author : François Voron
Publisher : Unknown
Page : 0 pages
File Size : 53,8 Mb
Release : 2023-07-31
Category : Electronic
ISBN : 183763274X

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Building Data Science Applications with FastAPI - Second Edition by François Voron Pdf

Learn all the features and best practices of FastAPI to build, deploy, and monitor powerful data science and AI apps, like object detection or image generation.Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesUncover the secrets of FastAPI, including async I/O, type hinting, and dependency injectionLearn to add authentication, authorization, and interaction with databases in a FastAPI backendDevelop real-world projects using pre-trained AI modelsBook DescriptionBuilding 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.What you will learnExplore the basics of modern Python and async I/O programmingGet to grips with basic and advanced concepts of the FastAPI frameworkDeploy a performant and reliable web backend for a data science applicationIntegrate common Python data science libraries into a web backendIntegrate an object detection algorithm into a FastAPI backendBuild a distributed text-to-image AI system with Stable DiffusionAdd metrics and logging and learn how to monitor themWho this book is forThis book is for data scientists and software developers interested in gaining knowledge of FastAPI and its ecosystem to build data science applications. Basic knowledge of data science and machine learning concepts and how to apply them in Python is recommended.

Building REST APIs with Flask

Author : Kunal Relan
Publisher : Apress
Page : 209 pages
File Size : 49,6 Mb
Release : 2019-09-12
Category : Computers
ISBN : 9781484250228

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Building REST APIs with Flask by Kunal Relan Pdf

Develop RESTful web services using the Flask micro-framework and integrate them using MySQL. Use Flask to develop, deploy, and manage REST APIs with easy-to-read and understand Python code. Solve your problem from a choice of libraries. Learn to use MySQL as the web services database for your Flask API using SQLAlchemy ORM. Building REST APIs with Flask provides a primer on Flask, RESTful services, and working with pip to set up your virtual environment. The key differences between NoSQL and SQL are covered, and you are taught how to connect MySQL and Flask using SQLAlchemy. Author Kunal Relan presents best practices for creating REST APIs and guides you in structuring your app and testing REST endpoints. He teaches you how to set up authentication and render HTML using views. You learn how to write unit tests for your REST APIs, and understand mocks, assertions, and integration testing. You will know how to document your REST APIs, deploy your Flask application on all of the major cloud platforms, and debug and monitor your Flask application. What You'll LearnUse MySQL to create Flask REST APIs Test REST endpoints Create CRUD endpoints with Flask and MySQL Deploy Flask on all of the major cloud platforms Monitor your Flask application Who This Book Is For Python developers interested in REST API development using Flask and web developers with basic programming knowledge who want to learn how Python and REST APIs work together. Readers should be familiar with Python (command line, or at least pip) and MySQL.

Full Stack FastAPI, React, and MongoDB

Author : Marko Aleksendric
Publisher : Packt Publishing Ltd
Page : 336 pages
File Size : 44,9 Mb
Release : 2022-09-23
Category : Computers
ISBN : 9781803249445

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Full Stack FastAPI, React, and MongoDB by Marko Aleksendric Pdf

Wield the power of Python, React, and MongoDB to build web and data applications quickly and broaden your web development horizons Key FeaturesLearn how to build web applications without having to know the intricacies of the componentsBuild full stack projects without compromising on development speed and app performancePrepare yourself for the diverse world of web development, analytics, and data visualizationBook Description If you need to develop web applications quickly, where do you turn? Enter the FARM stack. The FARM stack combines the power of the Python ecosystem with REST and MongoDB and makes building web applications easy and fast. This book is a fast-paced, concise, and hands-on beginner's guide that will equip you with the skills you need to quickly build web applications by diving just deep enough into the intricacies of the stack's components. The book quickly introduces each element of the stack and then helps you merge them to build a medium-sized web application. You'll set up a document store with MongoDB, build a simple API with FastAPI, and create an application with React. Security is crucial on the web, so you'll learn about authentication and authorization with JSON Web Tokens. You'll also understand how to optimize images, cache responses with Redis, and add additional features to your application as well as explore tips, tricks, and best practices to make your development experience a breeze. Before you know it, you'll be deploying the application to different platforms. By the end of this book, you will have built a couple of functional applications efficiently and will have the springboard you need to delve into diverse and more specialized domains. What you will learnDiscover the flexibility of the FARM stackImplement complete JWT authentication with FastAPIExplore the various Python drivers for MongoDBDiscover the problems that React libraries solveBuild simple and medium web applications with the FARM stackDive into server-side rendering with Next.jsDeploy your app with Heroku, Vercel, Ubuntu Server and NetlifyUnderstand how to deploy and cache a FastAPI backendWho this book is for This book is for web developers and analysts who want to include the power of a modern asynchronous Python framework, a flexible data store and a powerful UI library with the combination of two of the most important programming languages today in their web development toolkit. Beginners in the field of information presentation will also find this book helpful. You must have a beginner-level understanding of Python, JavaScript, and HTML and CSS to get the most out of this book.

REST APIs with Django

Author : William S. Vincent
Publisher : Independently Published
Page : 190 pages
File Size : 51,8 Mb
Release : 2018-06-15
Category : Computers
ISBN : 198302998X

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REST APIs with Django by William S. Vincent Pdf

The internet is powered by RESTful APIs. With the combination of the Django web framework and Django REST Framework, software developers can build robust web APIs in the Python programming language with a minimal amount of code. If you already know basic Django you can transform your websites into APIs in a matter of minutes. In this book we'll go well beyond the basics and build three progressively more complex APIs. We will learn how to connect a backend API to any frontend (such as React). And dive into advanced topics like user authentication, permissions, documentation, and more. TABLE OF CONTENTS * Introduction * Chapter 1: Web APIs * Chapter 2: Library website and API * Chapter 3: Todo API * Chapter 4: Todo React Frontend * Chapter 5: Blog API * Chapter 6: Permissions * Chapter 7: User Authentication * Chapter 8: Viewsets and Routers * Chapter 9: Schemas and Documentation * Conclusion

Machine Learning with LightGBM and Python

Author : Andrich van Wyk
Publisher : Packt Publishing Ltd
Page : 252 pages
File Size : 40,5 Mb
Release : 2023-09-29
Category : Computers
ISBN : 9781800563056

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Machine Learning with LightGBM and Python by Andrich van Wyk Pdf

Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.

FastAPI

Author : Bill Lubanovic
Publisher : "O'Reilly Media, Inc."
Page : 244 pages
File Size : 51,6 Mb
Release : 2023-11-06
Category : Computers
ISBN : 9781098135461

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FastAPI by Bill Lubanovic Pdf

FastAPI is a young yet solid framework that takes advantage of newer Python features in a clean design. As its name implies, FastAPI is indeed fast, rivaling similar frameworks in languages such as Golang. With this practical book, developers familiar with Python will learn how FastAPI lets you accomplish more in less time with less code. Author Bill Lubanovic covers the nuts and bolts of FastAPI development with how-to guides on various topics such as forms, database access, graphics, maps, and more that will take you beyond the basics. This book also includes how-to guides that will get you up to speed on RESTful APIs, data validation, authorization, and performance. With its similarities to frameworks like Flask and Django, you'll find it easy to get started with FastAPI. Through the course of this book, you will: Learn how to build web applications with FastAPI Understand the differences between FastAPI, Starlette, and pydantic Learn two features that set FastAPI apart: asynchronous functions and data type checking and validation Examine new features of Python 3.8+, especially type annotations Understand the differences between sync and async Python Learn how to connect with external APIs and services

Practical Python Backend Programming

Author : Tim Peters
Publisher : GitforGits
Page : 254 pages
File Size : 40,9 Mb
Release : 2024-01-31
Category : Computers
ISBN : 9788119177615

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Practical Python Backend Programming by Tim Peters Pdf

"Practical Python Backend Programming" is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. All sorts of developers, from Python programmers to non-Python programmers, full stack developers, and web developers, will find what they need to know to become experts in backend programming in this entire book. The book covers key topics in backend development, including how to set up stable development environments and how to use virtual environments for better dependency management. With this book, readers will have a firm grasp of Python programming with an emphasis on backend tasks by learning the language's syntax, data structures, and functions. The book teaches you to create and launch dynamic web apps by providing an in-depth look at web frameworks such as Flask and FastAPI. It teaches SQLAlchemy for efficient data handling and advanced database integration, and it shows to improve applications with databases like PostgreSQL, MySQL, and MongoDB. Strategies for managing concurrent operations and improving performance are also covered in the book, along with asynchronous programming in Python. This book delves into various authentication methods, secure communication protocols such as HTTPS, and techniques to secure REST APIs. For efficient management of asynchronous tasks and real-time data processing, it also introduces message brokers such as RabbitMQ and Kafka. The book teaches its readers how to containerize apps and manage them on a large scale by integrating technologies like Docker and Kubernetes. It goes on to talk about how to use serverless architectures, how to use modern tools for continuous integration and deployment, and how to deploy apps to cloud platforms like AWS. Key Learnings Build dynamic web apps with strong backend logic using Flask and FastAPI. Write efficient, well-structured backend code by learning Python's syntax, functions, and best practices. Make your apps more efficient and scalable by using asynchronous programming techniques. Investigate Kubernetes and Docker to orchestrate and containerize apps for improved deployment and scalability. Use AWS's cloud services to deploy apps with guaranteed uptime and lightning-fast performance. Improve efficiency and compatibility by setting up and managing Python development environments. Enhance your data handling capabilities by learning to integrate and manipulate databases using SQLAlchemy. Protect online apps with OAuth and JWT's sophisticated authorization and authentication features. Efficiently process data in real-time and broker messages with RabbitMQ and Kafka. Streamline processes, cut down on mistakes, and implement continuous integration and deployment by following best practices. Table of Content Fundamentals of Backend Development Building Your First Web Application with Flask Advanced Flask Development Introduction to FastAPI Working with Databases Asynchronous Programming in Python User Management and Security Deploying Python Backend Applications Microservices and Cloud Integration Message Brokers and Asynchronous Task Processing