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Building Serverless Python Apps Using Fastapi And Aws

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Building Serverless Python Apps Using Fastapi And Aws

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Author : Eidan James Rosado
language : en
Publisher: Viratec Interactive LLC
Release Date : 2022-06-01

Building Serverless Python Apps Using Fastapi And Aws written by Eidan James Rosado and has been published by Viratec Interactive LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

There are varying ways one can pursue starting a new or converting an existing project to a Serverless architecture. One of the many arguments heard is that developers typically don't know where to begin. This book is intended for those seeking to leverage a Serverless set up with a FastAPI project. This book provides a step-by-step guide for building Python APIs on AWS using FastAPI, AWS CDK, GraphQL, and more! It aims to solve one of the more predominant causes of delaying the transition to Serverless by providing engineers with an outline of where to begin on their Serverless journey. Code samples are provided to demonstrate several avenues that can be taken as well as some housekeeping items like formatting and building the continuous integration and delivery pipeline. Readers also get end-of-chapter quizzes, cheat sheets, and access to the full source code from the examples in this book.

Building Serverless Python Apps Using Fastapi And Aws

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Author : Eidan James Rosado
language : en
Publisher: Viratec Interactive LLC
Release Date : 2022-06-01

Building Data Science Applications With Fastapi

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Author : Francois Voron
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-31

Building Data Science Applications With Fastapi written by Francois Voron and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Computers categories.

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 eBook Key Features Uncover the secrets of FastAPI, including async I/O, type hinting, and dependency injection Learn to add authentication, authorization, and interaction with databases in a FastAPI backend Develop real-world projects using pre-trained AI models Book Description 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. What you will learn Explore the basics of modern Python and async I/O programming Get to grips with basic and advanced concepts of the FastAPI framework Deploy a performant and reliable web backend for a data science application Integrate common Python data science libraries into a web backend Integrate an object detection algorithm into a FastAPI backend Build a distributed text-to-image AI system with Stable Diffusion Add metrics and logging and learn how to monitor them Who this book is for This 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.

Learn Python By Building Data Science Applications

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Author : Philipp Kats
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-08-30

Learn Python By Building Data Science Applications written by Philipp Kats and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-30 with Computers categories.

Understand the constructs of the Python programming language and use them to build data science projects Key FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook Description Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards. What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is for If you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.

Building Python Web Apis With Fastapi

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Author : Abdulazeez Abdulazeez Adeshina
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29

Building Python Web Apis With Fastapi written by Abdulazeez Abdulazeez Adeshina and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-29 with Computers categories.

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.

Practical Python Backend Programming

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Author : Tim Peters
language : en
Publisher: GitforGits
Release Date : 2024-01-31

Practical Python Backend Programming written by Tim Peters and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Computers categories.

"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

Python Building Skills For Software Development

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Author : Dr. Mahendra Singh Bora
language : en
Publisher: Singh Publication
Release Date :

Python Building Skills For Software Development written by Dr. Mahendra Singh Bora and has been published by Singh Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

This book is designed to be a comprehensive resource for both beginners and experienced programmers who want to learn or expand their knowledge of the Python programming language. Python is known for its simplicity and versatility, making it an ideal language for a wide range of applications, from web development to data science.

The Fastapi Handbook

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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-06

The Fastapi Handbook written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Computers categories.

"The FastAPI Handbook: Simplifying Web Development with Python" is a comprehensive and accessible guide tailored for both novice and experienced developers looking to harness the power of FastAPI for building high-performance web applications. With its focus on speed, efficiency, and simplicity, FastAPI offers a modern approach to API development, leveraging Python’s type hints, asynchronous capabilities, and automatic documentation generation through OpenAPI standards. This book meticulously covers foundational to advanced concepts, providing readers with a structured pathway to understanding and utilizing FastAPI's full potential. Each chapter is crafted to build on previous topics, gradually introducing complex ideas such as dependency injection, CRUD operations, authentication, and deployment strategies. Readers will gain practical insights and hands-on experience through detailed examples and clear explanations, enabling them to construct scalable, intuitive APIs. Whether you aim to enhance your existing projects or embark on new ones, this handbook equips you with the essential skills and best practices to navigate the evolving landscape of web development confidently. Embrace the power of FastAPI and elevate your application development to new heights.

Building Generative Ai Services With Fastapi

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Author : Alireza Parandeh
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-04-15

Building Generative Ai Services With Fastapi written by Alireza Parandeh and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.

Ready to build production-grade applications with generative AI? This practical guide takes you through designing and deploying AI services using the FastAPI web framework. Learn how to integrate models that process text, images, audio, and video while seamlessly interacting with databases, filesystems, websites, and APIs. Whether you're a web developer, data scientist, or DevOps engineer, this book equips you with the tools to build scalable, real-time AI applications. Author Alireza Parandeh provides clear explanations and hands-on examples covering authentication, concurrency, caching, and retrieval-augmented generation (RAG) with vector databases. You'll also explore best practices for testing AI outputs, optimizing performance, and securing microservices. With containerized deployment using Docker, you'll be ready to launch AI-powered applications confidently in the cloud. Build generative AI services that interact with databases, filesystems, websites, and APIs Manage concurrency in AI workloads and handle long-running tasks Stream AI-generated outputs in real time via WebSocket and server-sent events Secure services with authentication, content filtering, throttling, and rate limiting Optimize AI performance with caching, batch processing, and fine-tuning techniques Visit the Book's Website.

Practical Mlops

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Author : Noah Gift
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-14

Practical Mlops written by Noah Gift and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-14 with Computers categories.

Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start. You'll discover how to: Apply DevOps best practices to machine learning Build production machine learning systems and maintain them Monitor, instrument, load-test, and operationalize machine learning systems Choose the correct MLOps tools for a given machine learning task Run machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware

Building Serverless Python Apps Using Fastapi And Aws

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