Production Ready Python
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Production Ready Data Science
Production-Ready Data Science is a practical guide to building reliable, maintainable, and scalable data science projects from start to finish. Written for professionals who want to move beyond experiments and deliver real-world solutions, this book covers the essential skills and workflows for taking code from notebook to production. You'll learn how to: Organize messy notebooks into maintainable, modular code. Create reproducible environments and streamline deployments. Apply best practices for variables, functions, and classes. Implement automated testing, configuration management, and logging. Validate and version your datasets for accuracy and traceability. Automate deployment with continuous integration and package distribution. Through step-by-step examples, you'll master Python tools using like Git, uv, Pytest, Hydra, Loguru, Pandera, DVC, GitHub Actions, and marimo to ensure your projects are reproducible, testable, and production-ready. Whether you're a data scientist, machine learning engineer, or software developer, this book equips you with the skills to deliver bulletproof systems that scale.
A Blueprint for Production-Ready Web Applications
Author: Dr. Philip Jones
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-09-23
Go from setting up your production environment, to building an app, to deploying it to the web using industry best practices along the way Key FeaturesFollow a blueprint to build production-ready apps that can be adapted and tailored to your requirementsLearn how to combine a React frontend with a Quart backend, and run them in Docker on AWSAdopt industry best practices that can be used in your personal as well as work projectsBook Description A Blueprint for Production-Ready Web Applications will help you expand upon your coding knowledge and teach you how to create a complete web application. Unlike other guides that focus solely on a singular technology or process, this book shows you how to combine different technologies and processes as needed to meet industry standards. You'll begin by learning how to set up your development environment, and use Quart and React to create the backend and frontend, respectively. This book then helps you get to grips with managing and validating accounts, structuring relational tables, and creating forms to manage data. As you progress through the chapters, you'll gain a comprehensive understanding of web application development by creating a to-do app, which can be used as a base for your future projects. Finally, you'll find out how to deploy and monitor your application, along with discovering advanced concepts such as managing database migrations and adding multifactor authentication. By the end of this web development book, you'll be able to apply the lessons and industry best practices that you've learned to both your personal and work projects, allowing you to further develop your coding portfolio. What you will learnSet up an optimum development environment for building web appsCreate a working backend Quart app that can be tailored to suit your needsBuild a user management system with passwords and authenticationBuild a single-page application with React Router and FormikDeploy your app to AWS and understand the importance of monitoringDiscover advanced concepts such as managing database migrationsWho this book is for This book is for software engineers like recent computer science or bootcamp graduates who already know how to program and want to learn how to build an app by following standard industry processes such as continuous integration and continuous deployment (CI/CD). Working knowledge of TypeScript/JavaScript, Python, HTML, CSS, and SQL is needed. You don't, however, need prior experience with Quart, React, AWS, and all other specific technologies and processes, as they will be introduced in the book.
Production-Ready Python
Author: John C Avila
language: en
Publisher: Independently Published
Release Date: 2025-10-11
Production-Ready Python: Deploy, Scale, and Automate Resilient Applications with Docker, Kubernetes, and Cloud Infrastructure Modern Python systems run in distributed, containerized, and automated environments. This book shows you how to take your Python applications from development to production with the reliability, scalability, and observability demanded by today's engineering standards. You will learn to build and operate production-grade Python services using Docker, Kubernetes, Terraform, and CI/CD pipelines. Through real-world examples, each chapter teaches you how to containerize your code, deploy at scale, automate workflows, and maintain reliability with modern cloud-native practices. What you will learn: Structure Python projects for modularity, scalability, and maintainability Build optimized Docker images and secure containerized workloads Deploy resilient applications on Kubernetes using manifests and Helm Automate build and release pipelines with GitHub Actions and GitLab CI Monitor and trace Python microservices using Prometheus, Grafana, and OpenTelemetry Manage secrets, credentials, and network security in production environments Apply Infrastructure as Code with Terraform for repeatable deployments Implement rollback, blue-green, and canary strategies safely This guide is written for Python developers, DevOps engineers, and cloud practitioners who want to bridge the gap between writing code and running reliable systems in production. Whether you are deploying APIs, background workers, or data pipelines, Production-Ready Python gives you the complete playbook to design, automate, and operate Python systems that perform under real-world workloads.