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.

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.

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

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.

Learn all that’s needed to build a fully functional web application from scratch. Key FeaturesDelve deep into the principle behind RESTful APILearn how to build a scalable web application with the RESTful API architecture and Flask frameworkKnow what are the exact tools and methodology to test your applications and how to use themBook Description Python is a flexible language that can be used for much more than just script development. By knowing the Python RESTful APIs work, you can build a powerful backend for web applications and mobile applications using Python. You'll take your first steps by building a simple API and learning how the frontend web interface can communicate with the backend. You'll also learn how to serialize and deserialize objects using the marshmallow library. Then, you'll learn how to authenticate and authorize users using Flask-JWT. You'll also learn how to enhance your APIs by adding useful features, such as email, image upload, searching, and pagination. You'll wrap up the whole book by deploying your APIs to the cloud. By the end of this book, you'll have the confidence and skill to leverage the power of RESTful APIs and Python to build efficient web applications. What you will learnUnderstand the concept of a RESTful APIBuild a RESTful API using Flask and the Flask-Restful extensionManipulate a database using Flask-SQLAlchemy and Flask-MigrateSend out plaintext and HTML format emails using the Mailgun APIImplement a pagination function using Flask-SQLAlchemyUse caching to improve API performance and efficiently obtain the latest informationDeploy an application to Heroku and test it using PostmanWho this book is for This book is ideal for aspiring software developers who have a basic-to-intermediate knowledge of Python programming and who want to develop web applications using Python. Knowledge of how web applications work will be beneficial but is not essential.

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.

This is not a traditional book. The book has a lot of code. If you don't like the code first approach do not buy this book. Making code available on Github is not an option. This book is for people who have some theoretical knowledge of machine learning and deep learning and want to dive into applied machine learning. The book doesn't explain the algorithms but is more oriented towards how and what should you use to solve machine learning and deep learning problems. The book is not for you if you are looking for pure basics. The book is for you if you are looking for guidance on approaching machine learning problems. The book is best enjoyed with a cup of coffee and a laptop/workstation where you can code along. Table of contents: - Setting up your working environment - Supervised vs unsupervised learning - Cross-validation - Evaluation metrics - Arranging machine learning projects - Approaching categorical variables - Feature engineering - Feature selection - Hyperparameter optimization - Approaching image classification & segmentation - Approaching text classification/regression - Approaching ensembling and stacking - Approaching reproducible code & model serving There are no sub-headings. Important terms are written in bold. I will be answering all your queries related to the book and will be making YouTube tutorials to cover what has not been discussed in the book. To ask questions/doubts, visit this link: https://bit.ly/aamlquestions And Subscribe to my youtube channel: https://bit.ly/abhitubesub

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.

Full Stack Python Security teaches you everything you’ll need to build secure Python web applications. Summary In Full Stack Python Security: Cryptography, TLS, and attack resistance, you’ll learn how to: Use algorithms to encrypt, hash, and digitally sign data Create and install TLS certificates Implement authentication, authorization, OAuth 2.0, and form validation in Django Protect a web application with Content Security Policy Implement Cross Origin Resource Sharing Protect against common attacks including clickjacking, denial of service attacks, SQL injection, cross-site scripting, and more Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you’ll need to build secure Python web applications. As you work through the insightful code snippets and engaging examples, you’ll put security standards, best practices, and more into action. Along the way, you’ll get exposure to important libraries and tools in the Python ecosystem. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Security is a full-stack concern, encompassing user interfaces, APIs, web servers, network infrastructure, and everything in between. Master the powerful libraries, frameworks, and tools in the Python ecosystem and you can protect your systems top to bottom. Packed with realistic examples, lucid illustrations, and working code, this book shows you exactly how to secure Python-based web applications. About the book Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you need to secure Python and Django-based web apps. In it, seasoned security pro Dennis Byrne demystifies complex security terms and algorithms. Starting with a clear review of cryptographic foundations, you’ll learn how to implement layers of defense, secure user authentication and third-party access, and protect your applications against common hacks. What's inside Encrypt, hash, and digitally sign data Create and install TLS certificates Implement authentication, authorization, OAuth 2.0, and form validation in Django Protect against attacks such as clickjacking, cross-site scripting, and SQL injection About the reader For intermediate Python programmers. About the author Dennis Byrne is a tech lead for 23andMe, where he protects the genetic data of more than 10 million customers. Table of Contents 1 Defense in depth PART 1 - CRYPTOGRAPHIC FOUNDATIONS 2 Hashing 3 Keyed hashing 4 Symmetric encryption 5 Asymmetric encryption 6 Transport Layer Security PART 2 - AUTHENTICATION AND AUTHORIZATION 7 HTTP session management 8 User authentication 9 User password management 10 Authorization 11 OAuth 2 PART 3 - ATTACK RESISTANCE 12 Working with the operating system 13 Never trust input 14 Cross-site scripting attacks 15 Content Security Policy 16 Cross-site request forgery 17 Cross-Origin Resource Sharing 18 Clickjacking

Explore the best tools and techniques to create lightweight, maintainable, and scalable Python web services Key FeaturesCombine Python with different data sources to build complex RESTful APIs from scratchConfigure and fine-tune your APIs using the best tools and techniques availableUse command-line and GUI tools to test CRUD operations performed by RESTful Web Services or APIsBook Description Python is the language of choice for millions of developers worldwide that builds great web services in RESTful architecture. This second edition of Hands-On RESTful Python Web Services will cover the best tools you can use to build engaging web services. This book shows you how to develop RESTful APIs using the most popular Python frameworks and all the necessary stacks with Python, combined with related libraries and tools. You’ll learn to incorporate all new features of Python 3.7, Flask 1.0.2, Django 2.1, Tornado 5.1, and also a new framework, Pyramid. As you advance through the chapters, you will get to grips with each of these frameworks to build various web services, and be shown use cases and best practices covering when to use a particular framework. You’ll then successfully develop RESTful APIs with all frameworks and understand how each framework processes HTTP requests and routes URLs. You’ll also discover best practices for validation, serialization, and deserialization. In the concluding chapters, you will take advantage of specific features available in certain frameworks such as integrated ORMs, built-in authorization and authentication, and work with asynchronous code. At the end of each framework, you will write tests for RESTful APIs and improve code coverage. By the end of the book, you will have gained a deep understanding of the stacks needed to build RESTful web services. What you will learnSelect the most appropriate framework based on requirementsDevelop complex RESTful APIs from scratch using PythonUse requests handlers, URL patterns, serialization, and validationsAdd authentication, authorization, and interaction with ORMs and databasesDebug, test, and improve RESTful APIs with four frameworksDesign RESTful APIs with frameworks and create automated testsWho this book is for This book is for web developers who have a working knowledge of Python and would like to build amazing web services by taking advantage of the various frameworks of Python. You should have some knowledge of RESTful APIs.