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Author: Eidan James Rosado
Publisher: Viratec Interactive LLC
ISBN:
Category : Computers
Languages : en
Pages : 152
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Book Description
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.
Author: Eidan James Rosado
Publisher: Viratec Interactive LLC
ISBN:
Category : Computers
Languages : en
Pages : 152
Get Book Here
Book Description
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.
Author: Philipp Kats
Publisher: Packt Publishing Ltd
ISBN: 1789533066
Category : Computers
Languages : en
Pages : 464
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Book Description
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.
Author: Francois Voron
Publisher: Packt Publishing Ltd
ISBN: 1837637261
Category : Computers
Languages : en
Pages : 423
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Book Description
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.
Author: Tim Peters
Publisher: GitforGits
ISBN: 8119177614
Category : Computers
Languages : en
Pages : 254
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Book Description
"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
Author: Jalem Raj Rohit
Publisher: Packt Publishing Ltd
ISBN: 1787281132
Category : Computers
Languages : en
Pages : 266
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Book Description
Building efficient Python applications at minimal cost by adopting serverless architectures Key Features Design and set up a data flow between cloud services and custom business logic Make your applications efficient and reliable using serverless architecture Build and deploy scalable serverless Python APIs Book Description Serverless architectures allow you to build and run applications and services without having to manage the infrastructure. Many companies have adopted this architecture to save cost and improve scalability. This book will help you design serverless architectures for your applications with AWS and Python. The book is divided into three modules. The first module explains the fundamentals of serverless architecture and how AWS lambda functions work. In the next module, you will learn to build, release, and deploy your application to production. You will also learn to log and test your application. In the third module, we will take you through advanced topics such as building a serverless API for your application. You will also learn to troubleshoot and monitor your app and master AWS lambda programming concepts with API references. Moving on, you will also learn how to scale up serverless applications and handle distributed serverless systems in production. By the end of the book, you will be equipped with the knowledge required to build scalable and cost-efficient Python applications with a serverless framework. What you will learn Understand how AWS Lambda and Microsoft Azure Functions work and use them to create an application Explore various triggers and how to select them, based on the problem statement Build deployment packages for Lambda functions Master the finer details about building Lambda functions and versioning Log and monitor serverless applications Learn about security in AWS and Lambda functions Scale up serverless applications to handle huge workloads and serverless distributed systems in production Understand SAM model deployment in AWS Lambda Who this book is for This book is for Python developers who would like to learn about serverless architecture. Python programming knowledge is assumed.
Author: Abdulwahid Abdulhaque Barguzar
Publisher: Packt Publishing Ltd
ISBN: 1788837932
Category : Computers
Languages : en
Pages : 313
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Book Description
Master serverless architectures in Python and their implementation, with Zappa on three different frameworks. Key Features Scalable serverless Python web services using Django, Flask, and Pyramid. Learn Asynchronous task execution on AWS Lambda and scheduling using Zappa. Implementing Zappa in a Docker container. Book Description Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application. This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC. By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python. What you will learn Build, test, and deploy a simple web service using AWS CLI Integrate Flask-based Python applications, via AWS CLI configuration Design Rest APIs integrated with Zappa for Flask and Django Create a project in the Pyramid framework and configure it with Zappa Generate SSL Certificates using Amazon Certificate Manager Configure custom domains with AWS Route 53 Create a Docker container similar to AWS Lambda Who this book is for Python Developers who are interested in learning how to develop fast and highly scalable serverless applications in Python, will find this book useful
Author: Serkan Sakinmaz
Publisher: Packt Publishing Ltd
ISBN: 1804618071
Category : Computers
Languages : en
Pages : 224
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Book Description
A comprehensive guide to implementing Python applications in AWS while learning about key AWS services Purchase of the print or Kindle book includes a free PDF eBook Key Features Gain hands-on experience in AWS services to effectively implement Python programming Utilize Python with open source libraries to develop data pipelines, APIs, and database applications Leverage the power of AWS to create a cloud-based server and use monitoring and logging features Book Description AWS provides a vast variety of services for implementing Python applications, which can pose a challenge for those without an AWS background. This book addresses one of the more predominant problems of choosing the right service and stepping into the implementation of exciting Python apps using AWS. The book begins by showing you how to install Python and create an AWS account, before helping you explore AWS Lambda, EC2, Elastic Beanstalk, and S3 for Python programming. You'll then gain hands-on experience in using these services to build the Python application. As you advance, you'll discover how to debug Python apps using PyCharm, and then start deploying the Python applications on Elastic Beanstalk. You'll also learn how to monitor Python applications using the CloudWatch service, along with creating and publishing APIs on AWS to access the Python application. The concluding chapters will help you get to grips with storing unstructured and semi-structured data using NoSQL and DynamoDB, as well as advance your knowledge using the Glue serverless data integration service in AWS. By the end of this Python book, you'll be able to take your application development skills up a notch with AWS services and advance in your career. What you will learn Understand the fundamentals of AWS services for Python programming Find out how to configure AWS services to build Python applications Run and deploy Python applications using Lambda, EC2, and Elastic Beanstalk Provision EC2 servers on AWS and run Python applications Debug and monitor Python applications using PyCharm and CloudWatch Understand database operations on AWS by learning about DynamoDB and RDS Explore the API gateway service on AWS using Python to grasp API programming Who this book is for This book is for cloud developers, software developers, and IT specialists who want to develop Python applications on AWS as well as learn the concepts underlying AWS services for implementing the applications. Experience in Python programming is needed to be able to implement the applications on AWS.
Author: Tanmoy Sakar
Publisher: BPB Publications
ISBN: 9390684781
Category : Computers
Languages : en
Pages : 203
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Book Description
Building and hosting microservices without servers using AWS Lambda KEY FEATURES ● Learn end-to-end development of microservices using .NET Core and AWS Lambda. ● Learn a new way of hosting the .NET Core Web API on the AWS Lambda serverless platform. ● Mastering microservices using .NET Core and AWS Lambda. DESCRIPTION Building Modern Serverless Web APIs introduces you to the serverless paradigm of the Web API application, its advantages, and presents you the modern approach of developing the Web API. The book makes efficient use of AWS Lambda services to develop efficient, scalable, and cost-effective API solutions. The book begins with a quick introduction to microservices, its characteristics, and current challenges faced in developing and implementing them. The book explores core concepts of ASP.NET Core and some important AWS services that are commonly used to build microservices using AWS. It explores and provides real hands-on microservice patterns and some of the best practices used in designing the serverless architecture. Furthermore, the book covers end-to-end demonstration of an application where you will learn to develop, build, deploy, and monitor microservices on AWS Lambda using .NET Core 3.1. By the end of this book, you will be proficient in developing microservices with AWS Lambda and become a self-starter to build your own secure microservices. WHAT YOU WILL LEARN ● Learn about microservices, their characteristics, patterns, and where to use them. ● Understand popular microservice design patterns being used with the serverless architecture. ● Learn about the ASP.NET Core Web API and its hosting strategies for building serverless microservices. ● Learn about Amazon Web Services and the services commonly used to build microservices. ● Discover how to configure authorization and authentication to secure microservices in AWS. ● Learn about AWS services available for Continuous Deployment and Integration to deploy microservices. WHO THIS BOOK IS FOR This book is for a seasoned .NET developer or AWS practitioner who wants to learn about the microservices architecture, patterns, and how to deploy using AWS Lambda. TABLE OF CONTENTS 1. Microservices: Its Characteristics and Challenges 2. Introduction to the ASP.NET Core Web API 3. Introduction to AWS Services 4. Microservices Patterns 5. The Serverless Paradigm 6. Communication Patterns and Service Discovery 7. Collaborating between Microservices 8. Distributed Monitoring 9. Security 10. Continuous Integration and Deployment 11. AWS Best Practices
Author: Peter Sbarski
Publisher: Simon and Schuster
ISBN: 1638351147
Category : Computers
Languages : en
Pages : 549
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Book Description
Summary Serverless Architectures on AWS teaches you how to build, secure and manage serverless architectures that can power the most demanding web and mobile apps. Forewords by Patrick Debois (Founder of devopsdays) and Dr. Donald F. Ferguson (Columbia University). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology There's a shift underway toward serverless cloud architectures. With the release of serverless computer technologies such as AWS Lambda, developers are now building entirely serverless platforms at scale. In these new architectures, traditional back-end servers are replaced with cloud functions acting as discrete single-purpose services. By composing and combining these serverless cloud functions together in a loose orchestration and adopting useful third-party services, developers can create powerful yet easy-to-understand applications. About the Book Serverless Architectures on AWS teaches you how to build, secure, and manage serverless architectures that can power the most demanding web and mobile apps. You'll get going quickly with this book's ready-made real-world examples, code snippets, diagrams, and descriptions of architectures that can be readily applied. By the end, you'll be able to architect and build your own serverless applications on AWS. What's Inside First steps with serverless computing Important patterns and architectures Writing AWS Lambda functions and using the API Gateway Composing serverless applications using key services like Auth0 and Firebase Securing, deploying, and managing serverless architectures About the Reader This book is for software developers interested in back end technologies. Experience with JavaScript (node.js) and AWS is useful but not required. About the Author Dr. Peter Sbarski is a well-known AWS expert, VP of engineering at A Cloud Guru, and head of Serverlessconf. Table of Contents PART 1 - FIRST STEPS Going serverless Architectures and patterns Building a serverless application Setting up your cloud PART 2 - CORE IDEAS Authentication and authorization Lambda the orchestrator API Gateway PART 3 - GROWING YOUR ARCHITECTURE Storage Database Going the last mile APPENDIXES Services for your serverless architecture Installation and setup More about authentication and authorization Lambda insider Models and mapping
Author: Francois Voron
Publisher: Packt Publishing Ltd
ISBN: 1801074186
Category : Computers
Languages : en
Pages : 426
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Book Description
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.
