Computers and Programming

Python is entering a new performance era. Explore free-threaded execution, Rust extensions and modern tools for building faster, more scalable Python systems. Learn how CPython is changing, when Rust makes sense and how to turn these ideas into production-ready software.

Explore fundamental concepts in modern robotics, kinematics, and control systems with Robotics and Automation: Notes in Robotics and Automation.

Read OTLP from raw bytes to spans: Protobuf wire format, gRPC frames, HTTP payloads, PCAPs, failure modes, and telemetry cost—explained for engineers who need to debug the protocol, not merely configure it.

Learn Argo Rollouts through hands-on Kubernetes labs. Build canary and blue-green deployments, control traffic with Istio, validate releases with Prometheus, run Experiments, automate promotion and rollback, and manage progressive delivery with Argo CD and GitOps.

Git is much bigger than GitHub. This practical guide explores self-hosted platforms, decentralized approaches, secure operations and CI/CD beyond the usual defaults. Learn how to design, deploy and run independent Git infrastructure for real-world engineering, enterprise and regulated environments.

Learn Python from the ground up with clear explanations, practical examples, and a beginner-friendly approach. Build a strong foundation in programming and gain the confidence to move toward real-world Python projects.

A comprehensive technical guide to Python-driven cloud architecture, infrastructure automation, serverless engineering, security, distributed systems, and large-scale AWS operations.Modern cloud infrastructure is more than a collection of virtual machines and managed services. It is a programmable environment in which networking, identity, compute, storage, databases, messaging, and observability must work together as a coherent system. Building reliable cloud platforms requires software engineering discipline, automation, security controls, and a detailed understanding of how these services interact.Mastering AWS: Advanced Python Engineering is a 100-chapter technical reference for senior software engineers, DevOps specialists, cloud architects, platform engineers, and developers seeking to build sophisticated AWS environments with Python.

Learn Dart the right way — from your very first "Hello, World" to advanced topics like Foreign Function Interface, code generation, and modern Dart 3 pattern matching.This comprehensive, 32-chapter guide is designed for complete beginners as well as developers who want a deep, structured reference to Dart — the language behind Flutter and a growing number of command-line and backend applications.What you'll learn:Dart fundamentals: variables, data types, operators, and control flowFunctions, collections (List, Set, Map), and sound null safetyObject-oriented programming: classes, inheritance, mixins, and interfacesGenerics and robust exception handlingAsynchronous programming with Future, async/await, and StreamsModern Dart 3 features: records, pattern matching, and sealed classesExtension methods and zero-cost extension typesIsolates and concurrency for true parallelismDart FFI for calling native C librariesCreating, testing, and publishing your own Dart packagesCode generation with build_runner and json_serializablePub workspaces for monorepo projectsEffective Dart linter rules and professional best practicesEvery chapter includes clear explanations and runnable code examples you can try immediately in DartPad or your local environment. A complete course index at the start and a quick-reference cheat sheet at the end make this book easy to navigate and revisit.Whether you're a student, a self-taught developer, or preparing to build your first Flutter app, this book gives you a solid, complete foundation in Dart — one chapter at a time.

Good software is not about following rules. It is about knowing when they apply. This book explores the judgment behind building software that lasts, from choosing simplicity over cleverness to balancing today’s needs with tomorrow’s costs. Practical, thoughtful and focused on decisions, not dogma.

A practical implementation framework covering 22 essential data center operational domains. Assess gaps, establish priorities and build a controlled improvement roadmap.

From the Linux basics to advanced development workflows, this practical guide shows you how to turn Linux into a powerful software development environment. Learn the command line, work with popular programming languages, use containers and CI/CD, debug and profile applications and build skills you can use every day.

Build a strong foundation in Gleam and learn how to turn its simplicity into reliable, concurrent systems. From language basics and the BEAM to OTP, web development and deployment, this practical guide uses clear explanations and runnable examples to help you build software that is safe, scalable and ready for production.

Build real machine learning applications with TensorFlow.js, from your first model to production-ready systems. Learn how to train and deploy models in the browser and Node.js, tackle real-world challenges and explore modern techniques with practical JavaScript and TypeScript examples you can run and adapt.

Build real-world systems software with Tcl/Tk, from your first installation to production-ready deployment. Learn to create command-line tools, desktop apps, network services and automation frameworks that run across Windows, macOS and Linux. Practical code and clear explanations take you from foundation to confident deployment.

Java is entering a new era of faster releases, modern JVMs and evolving enterprise demands. This practical guide helps architects, platform engineers and senior developers navigate LTS upgrades, modernization, migration, performance, security and cloud deployment with clear strategies and production-ready guidance.